diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 124420ea8f..63943a1b49 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -52,12 +52,14 @@ repos: - { id: uv-lock, name: "uv-lock-rag", args: [--project, packages/nvidia_nat_rag], files: "packages/nvidia_nat_rag/pyproject.toml" } - { id: uv-lock, name: "uv-lock-ragaai", args: [--project, packages/nvidia_nat_ragaai], files: "packages/nvidia_nat_ragaai/pyproject.toml" } - { id: uv-lock, name: "uv-lock-redis", args: [--project, packages/nvidia_nat_redis], files: "packages/nvidia_nat_redis/pyproject.toml" } + - { id: uv-lock, name: "uv-lock-runtime", args: [--project, packages/nvidia_nat_runtime], files: "packages/nvidia_nat_runtime/pyproject.toml" } - { id: uv-lock, name: "uv-lock-s3", args: [--project, packages/nvidia_nat_s3], files: "packages/nvidia_nat_s3/pyproject.toml" } - { id: uv-lock, name: "uv-lock-semantic_kernel", args: [--project, packages/nvidia_nat_semantic_kernel], files: "packages/nvidia_nat_semantic_kernel/pyproject.toml" } - { id: uv-lock, name: "uv-lock-strands", args: [--project, packages/nvidia_nat_strands], files: "packages/nvidia_nat_strands/pyproject.toml" } - { id: uv-lock, name: "uv-lock-test", args: [--project, packages/nvidia_nat_test], files: "packages/nvidia_nat_test/pyproject.toml" } - { id: uv-lock, name: "uv-lock-vanna", args: [--project, packages/nvidia_nat_vanna], files: "packages/nvidia_nat_vanna/pyproject.toml" } - { id: uv-lock, name: "uv-lock-weave", args: [--project, packages/nvidia_nat_weave], files: "packages/nvidia_nat_weave/pyproject.toml" } + - { id: uv-lock, name: "uv-lock-workspace", args: [--project, packages/nvidia_nat_workspace], files: "packages/nvidia_nat_workspace/pyproject.toml" } - { id: uv-lock, name: "uv-lock-zep_cloud", args: [--project, packages/nvidia_nat_zep_cloud], files: "packages/nvidia_nat_zep_cloud/pyproject.toml" } - repo: local hooks: diff --git a/packages/nvidia_nat_core/src/nat/builder/builder.py b/packages/nvidia_nat_core/src/nat/builder/builder.py index 9b940278c1..853fc0c00c 100644 --- a/packages/nvidia_nat_core/src/nat/builder/builder.py +++ b/packages/nvidia_nat_core/src/nat/builder/builder.py @@ -54,16 +54,19 @@ from nat.data_models.object_store import ObjectStoreBaseConfig from nat.data_models.retriever import RetrieverBaseConfig from nat.data_models.ttc_strategy import TTCStrategyBaseConfig +from nat.data_models.workspace import WorkspaceBaseConfig from nat.experimental.decorators.experimental_warning_decorator import experimental from nat.experimental.test_time_compute.models.stage_enums import PipelineTypeEnum from nat.experimental.test_time_compute.models.stage_enums import StageTypeEnum from nat.finetuning.interfaces.finetuning_runner import Trainer from nat.finetuning.interfaces.trainer_adapter import TrainerAdapter from nat.finetuning.interfaces.trajectory_builder import TrajectoryBuilder +from nat.guardrails.workspace import WorkspaceGuardrail from nat.memory.interfaces import MemoryEditor from nat.middleware.middleware import Middleware from nat.object_store.interfaces import ObjectStore from nat.retriever.interface import Retriever +from nat.workspace.types import WorkspaceManagerBase if typing.TYPE_CHECKING: from nat.builder.sync_builder import SyncBuilder @@ -236,6 +239,37 @@ def get_workflow_config(self) -> FunctionBaseConfig: """ pass + @abstractmethod + def get_workspace_config(self) -> WorkspaceBaseConfig | None: + """Get the workspace configuration. + + Returns: + The workspace configuration if configured, otherwise None + """ + pass + + @abstractmethod + async def get_workspace_manager(self) -> WorkspaceManagerBase | None: + """Get the workspace manager. + + Returns: + The workspace manager if configured, otherwise None + """ + pass + + @abstractmethod + async def get_workspace_guardrails(self) -> list[WorkspaceGuardrail]: + """Get instantiated workspace guardrail instances from the workspace config. + + Implementations should resolve ``WorkspaceBaseConfig.workspace_guardrails`` + refs to live :class:`~nat.guardrails.workspace.WorkspaceGuardrail` instances. + + Returns: + List of workspace guardrail instances configured for the active workspace. + Returns an empty list if no workspace or no guardrails are configured. + """ + pass + @abstractmethod async def get_tools(self, tool_names: Sequence[str | FunctionRef | FunctionGroupRef], diff --git a/packages/nvidia_nat_core/src/nat/builder/child_builder.py b/packages/nvidia_nat_core/src/nat/builder/child_builder.py index 289b74285e..f95d54f2ec 100644 --- a/packages/nvidia_nat_core/src/nat/builder/child_builder.py +++ b/packages/nvidia_nat_core/src/nat/builder/child_builder.py @@ -48,6 +48,7 @@ from nat.data_models.object_store import ObjectStoreBaseConfig from nat.data_models.retriever import RetrieverBaseConfig from nat.data_models.ttc_strategy import TTCStrategyBaseConfig +from nat.data_models.workspace import WorkspaceBaseConfig from nat.experimental.decorators.experimental_warning_decorator import experimental from nat.experimental.test_time_compute.models.stage_enums import PipelineTypeEnum from nat.experimental.test_time_compute.models.stage_enums import StageTypeEnum @@ -60,6 +61,7 @@ from nat.object_store.interfaces import ObjectStore from nat.retriever.interface import Retriever from nat.utils.type_utils import override +from nat.workspace.types import WorkspaceManagerBase class ChildBuilder(Builder): @@ -70,8 +72,8 @@ def __init__(self, workflow_builder: Builder) -> None: self._dependencies = FunctionDependencies() - @override @property + @override def sync_builder(self) -> SyncBuilder: return SyncBuilder(self) @@ -125,6 +127,14 @@ def get_workflow(self) -> Function: def get_workflow_config(self) -> FunctionBaseConfig: return self._workflow_builder.get_workflow_config() + @override + def get_workspace_config(self) -> WorkspaceBaseConfig | None: + return self._workflow_builder.get_workspace_config() + + @override + async def get_workspace_manager(self) -> WorkspaceManagerBase | None: + return await self._workflow_builder.get_workspace_manager() + @override async def get_tools(self, tool_names: Sequence[str | FunctionRef | FunctionGroupRef], diff --git a/packages/nvidia_nat_core/src/nat/builder/component_utils.py b/packages/nvidia_nat_core/src/nat/builder/component_utils.py index 8aa712383e..d2c0f5ebea 100644 --- a/packages/nvidia_nat_core/src/nat/builder/component_utils.py +++ b/packages/nvidia_nat_core/src/nat/builder/component_utils.py @@ -40,6 +40,7 @@ from nat.data_models.object_store import ObjectStoreBaseConfig from nat.data_models.retriever import RetrieverBaseConfig from nat.data_models.ttc_strategy import TTCStrategyBaseConfig +from nat.data_models.workspace_guardrail import WorkspaceGuardrailBaseConfig from nat.utils.type_utils import DecomposedType WORKFLOW_COMPONENT_NAME = "" @@ -57,6 +58,7 @@ ComponentGroup.RETRIEVERS, ComponentGroup.TTC_STRATEGIES, ComponentGroup.MIDDLEWARE, + ComponentGroup.WORKSPACE_GUARDRAILS, ComponentGroup.FUNCTION_GROUPS, ComponentGroup.FUNCTIONS, ComponentGroup.TRAINER_ADAPTERS, @@ -130,6 +132,8 @@ def group_from_component(component: TypedBaseModel) -> ComponentGroup | None: return ComponentGroup.FUNCTION_GROUPS if (isinstance(component, MiddlewareBaseConfig)): return ComponentGroup.MIDDLEWARE + if (isinstance(component, WorkspaceGuardrailBaseConfig)): + return ComponentGroup.WORKSPACE_GUARDRAILS if (isinstance(component, LLMBaseConfig)): return ComponentGroup.LLMS if (isinstance(component, MemoryBaseConfig)): @@ -289,8 +293,8 @@ def build_dependency_sequence(config: "Config") -> list[ComponentInstanceData]: total_node_count = (len(config.embedders) + len(config.functions) + len(config.function_groups) + len(config.llms) + len(config.memory) + len(config.object_stores) + len(config.retrievers) + len(config.ttc_strategies) + len(config.authentication) + len(config.middleware) + - len(config.trainers) + len(config.trajectory_builders) + len(config.trainer_adapters) + 1 - ) # +1 for the workflow + len(config.workspace_guardrails) + len(config.trainers) + len(config.trajectory_builders) + + len(config.trainer_adapters) + 1) # +1 for the workflow dependency_map: dict dependency_graph: nx.DiGraph diff --git a/packages/nvidia_nat_core/src/nat/builder/framework_enum.py b/packages/nvidia_nat_core/src/nat/builder/framework_enum.py index c3ca7c33f0..6596002806 100644 --- a/packages/nvidia_nat_core/src/nat/builder/framework_enum.py +++ b/packages/nvidia_nat_core/src/nat/builder/framework_enum.py @@ -25,3 +25,4 @@ class LLMFrameworkEnum(StrEnum): ADK = "adk" STRANDS = "strands" AUTOGEN = "autogen" + RUNTIME = "runtime" diff --git a/packages/nvidia_nat_core/src/nat/builder/per_user_workflow_builder.py b/packages/nvidia_nat_core/src/nat/builder/per_user_workflow_builder.py index 287ad38a59..aae02715a3 100644 --- a/packages/nvidia_nat_core/src/nat/builder/per_user_workflow_builder.py +++ b/packages/nvidia_nat_core/src/nat/builder/per_user_workflow_builder.py @@ -65,6 +65,7 @@ from nat.data_models.object_store import ObjectStoreBaseConfig from nat.data_models.retriever import RetrieverBaseConfig from nat.data_models.ttc_strategy import TTCStrategyBaseConfig +from nat.data_models.workspace import WorkspaceBaseConfig from nat.experimental.decorators.experimental_warning_decorator import experimental from nat.experimental.test_time_compute.models.stage_enums import PipelineTypeEnum from nat.experimental.test_time_compute.models.stage_enums import StageTypeEnum @@ -78,6 +79,7 @@ from nat.object_store.interfaces import ObjectStore from nat.retriever.interface import Retriever from nat.utils.type_utils import override +from nat.workspace.types import WorkspaceManagerBase logger = logging.getLogger(__name__) @@ -134,8 +136,8 @@ def _get_exit_stack(self) -> AsyncExitStack: "Exit stack not initialized. Did you forget to call `async with PerUserWorkflowBuilder() as builder`?") return self._exit_stack - @override @property + @override def sync_builder(self) -> SyncBuilder: return SyncBuilder(self) @@ -354,6 +356,14 @@ def get_workflow_config(self) -> FunctionBaseConfig: # Otherwise, delegate to shared builder return self._shared_builder.get_workflow_config() + @override + def get_workspace_config(self) -> WorkspaceBaseConfig | None: + return self._shared_builder.get_workspace_config() + + @override + async def get_workspace_manager(self) -> WorkspaceManagerBase | None: + return await self._shared_builder.get_workspace_manager() + @override def get_function_dependencies(self, fn_name: str | FunctionRef) -> FunctionDependencies: if isinstance(fn_name, FunctionRef): diff --git a/packages/nvidia_nat_core/src/nat/builder/sync_builder.py b/packages/nvidia_nat_core/src/nat/builder/sync_builder.py index eecaba0ddf..5ba19ff213 100644 --- a/packages/nvidia_nat_core/src/nat/builder/sync_builder.py +++ b/packages/nvidia_nat_core/src/nat/builder/sync_builder.py @@ -50,6 +50,7 @@ from nat.data_models.object_store import ObjectStoreBaseConfig from nat.data_models.retriever import RetrieverBaseConfig from nat.data_models.ttc_strategy import TTCStrategyBaseConfig +from nat.data_models.workspace import WorkspaceBaseConfig from nat.experimental.test_time_compute.models.stage_enums import PipelineTypeEnum from nat.experimental.test_time_compute.models.stage_enums import StageTypeEnum from nat.finetuning.interfaces.finetuning_runner import Trainer @@ -59,6 +60,7 @@ from nat.middleware.middleware import Middleware from nat.object_store.interfaces import ObjectStore from nat.retriever.interface import Retriever +from nat.workspace.types import WorkspaceManagerBase if typing.TYPE_CHECKING: from nat.experimental.test_time_compute.models.strategy_base import StrategyBase @@ -180,6 +182,22 @@ def get_workflow_config(self) -> FunctionBaseConfig: """ return self._builder.get_workflow_config() + def get_workspace_config(self) -> WorkspaceBaseConfig | None: + """Get the workspace configuration. + + Returns: + The workspace configuration if configured, otherwise None + """ + return self._builder.get_workspace_config() + + def get_workspace_manager(self) -> WorkspaceManagerBase | None: + """Get the workspace manager. + + Returns: + The workspace manager if configured, otherwise None + """ + return self._loop.run_until_complete(self._builder.get_workspace_manager()) + def get_tools(self, tool_names: Sequence[str | FunctionRef | FunctionGroupRef], wrapper_type: LLMFrameworkEnum | str) -> list[typing.Any]: diff --git a/packages/nvidia_nat_core/src/nat/builder/workflow_builder.py b/packages/nvidia_nat_core/src/nat/builder/workflow_builder.py index 0c20935ce6..cd20e85e1f 100644 --- a/packages/nvidia_nat_core/src/nat/builder/workflow_builder.py +++ b/packages/nvidia_nat_core/src/nat/builder/workflow_builder.py @@ -78,6 +78,7 @@ from nat.data_models.retriever import RetrieverBaseConfig from nat.data_models.telemetry_exporter import TelemetryExporterBaseConfig from nat.data_models.ttc_strategy import TTCStrategyBaseConfig +from nat.data_models.workspace import WorkspaceBaseConfig from nat.experimental.decorators.experimental_warning_decorator import experimental from nat.experimental.test_time_compute.models.stage_enums import PipelineTypeEnum from nat.experimental.test_time_compute.models.stage_enums import StageTypeEnum @@ -91,6 +92,7 @@ from nat.object_store.interfaces import ObjectStore from nat.observability.exporter.base_exporter import BaseExporter from nat.utils.type_utils import override +from nat.workspace.types import WorkspaceManagerBase try: from nat.plugins.eval.profiler.decorators.framework_wrapper import chain_wrapped_build_fn @@ -351,6 +353,8 @@ def __init__(self, *, general_config: GeneralConfig | None = None, registry: Typ self._trainers: dict[str, ConfiguredTrainer] = {} self._trainer_adapters: dict[str, ConfiguredTrainerAdapter] = {} self._trajectory_builders: dict[str, ConfiguredTrajectoryBuilder] = {} + self._workspace_config: WorkspaceBaseConfig | None = None + self._workspace_manager: WorkspaceManagerBase | None = None self._context_state = ContextState.get() @@ -444,8 +448,8 @@ async def __aexit__(self, *exc_details): await self._exit_stack.__aexit__(*exc_details) - @override @property + @override def sync_builder(self) -> SyncBuilder: return SyncBuilder(self) @@ -782,6 +786,22 @@ def get_workflow_config(self) -> FunctionBaseConfig: return self._workflow.config + @override + def get_workspace_config(self) -> WorkspaceBaseConfig | None: + return self._workspace_config + + @override + async def get_workspace_manager(self) -> WorkspaceManagerBase | None: + if self._workspace_config is None: + return None + + if self._workspace_manager is None: + workspace_info = self._registry.get_workspace(type(self._workspace_config)) + self._workspace_manager = await self._get_exit_stack().enter_async_context( + workspace_info.build_fn(self._workspace_config)) + + return self._workspace_manager + @override def get_function_dependencies(self, fn_name: str | FunctionRef) -> FunctionDependencies: if isinstance(fn_name, FunctionRef): @@ -1418,6 +1438,9 @@ async def populate_builder(self, config: Config, skip_workflow: bool = False): skip_workflow (bool): If True, skips the workflow instantiation step. Defaults to False. """ + self._workspace_config = config.workspace + self._workspace_manager = None + # Generate the build sequence build_sequence = build_dependency_sequence(config) diff --git a/packages/nvidia_nat_core/src/nat/cli/register_workflow.py b/packages/nvidia_nat_core/src/nat/cli/register_workflow.py index fe268214b6..71afb29770 100644 --- a/packages/nvidia_nat_core/src/nat/cli/register_workflow.py +++ b/packages/nvidia_nat_core/src/nat/cli/register_workflow.py @@ -13,8 +13,10 @@ # See the License for the specific language governing permissions and # limitations under the License. +import inspect from collections.abc import Callable from contextlib import asynccontextmanager +from typing import TYPE_CHECKING from typing import Any from pydantic import BaseModel @@ -51,6 +53,7 @@ from nat.cli.type_registry import RegisteredLoggingMethod from nat.cli.type_registry import RegisteredTelemetryExporter from nat.cli.type_registry import RegisteredToolWrapper +from nat.cli.type_registry import RegisteredWorkspaceGuardrailInfo from nat.cli.type_registry import RegistryHandlerBuildCallableT from nat.cli.type_registry import RegistryHandlerRegisteredCallableT from nat.cli.type_registry import RetrieverClientBuildCallableT @@ -69,6 +72,10 @@ from nat.cli.type_registry import TrajectoryBuilderRegisteredCallableT from nat.cli.type_registry import TTCStrategyBuildCallableT from nat.cli.type_registry import TTCStrategyRegisteredCallableT +from nat.cli.type_registry import WorkspaceBuildCallableT +from nat.cli.type_registry import WorkspaceGuardrailBuildCallableT +from nat.cli.type_registry import WorkspaceGuardrailRegisteredCallableT +from nat.cli.type_registry import WorkspaceRegisteredCallableT from nat.data_models.authentication import AuthProviderBaseConfigT from nat.data_models.component import ComponentEnum from nat.data_models.dataset_handler import EvalDatasetBaseConfigT @@ -88,8 +95,13 @@ from nat.data_models.registry_handler import RegistryHandlerBaseConfigT from nat.data_models.retriever import RetrieverBaseConfigT from nat.data_models.ttc_strategy import TTCStrategyBaseConfigT +from nat.data_models.workspace import WorkspaceBaseConfigT +from nat.data_models.workspace_guardrail import WorkspaceGuardrailBaseConfigT from nat.utils.type_utils import DecomposedType +if TYPE_CHECKING: + from nat.workspace.types import WorkspaceAction + def register_telemetry_exporter(config_type: type[TelemetryExporterConfigT]): """ @@ -166,6 +178,86 @@ def register_front_end_inner( return register_front_end_inner +def add_registered_workspace(config_type: type[WorkspaceBaseConfigT]): + """ + Register a workspace configuration. + """ + + def register_workspace_inner( + fn: WorkspaceBuildCallableT[WorkspaceBaseConfigT]) -> WorkspaceRegisteredCallableT[WorkspaceBaseConfigT]: + from .type_registry import GlobalTypeRegistry + from .type_registry import RegisteredWorkspaceInfo + + context_manager_fn = asynccontextmanager(fn) + + discovery_metadata = DiscoveryMetadata.from_config_type(config_type=config_type, + component_type=ComponentEnum.WORKSPACE) + + GlobalTypeRegistry.get().register_workspace( + RegisteredWorkspaceInfo(full_type=config_type.full_type, + config_type=config_type, + build_fn=context_manager_fn, + discovery_metadata=discovery_metadata)) + + return context_manager_fn + + return register_workspace_inner + + +def register_workspace_guardrail(config_type: type[WorkspaceGuardrailBaseConfigT]): + """Register a workspace guardrail component.""" + + def register_guardrail_inner( + fn: WorkspaceGuardrailBuildCallableT[WorkspaceGuardrailBaseConfigT] + ) -> WorkspaceGuardrailRegisteredCallableT[WorkspaceGuardrailBaseConfigT]: + from .type_registry import GlobalTypeRegistry + + context_manager_fn = asynccontextmanager(fn) + + discovery_metadata = DiscoveryMetadata.from_config_type(config_type=config_type, + component_type=ComponentEnum.WORKSPACE_GUARDRAIL) + + GlobalTypeRegistry.get().register_workspace_guardrail( + RegisteredWorkspaceGuardrailInfo(full_type=config_type.full_type, + config_type=config_type, + build_fn=context_manager_fn, + discovery_metadata=discovery_metadata)) + + return context_manager_fn + + return register_guardrail_inner + + +def register_workspace_action(action_cls: type["WorkspaceAction"]) -> type["WorkspaceAction"]: + """Register a workspace action for discovery. + + Args: + action_cls: Workspace action class to register. + + Returns: + type[WorkspaceAction]: The registered action class. + + Raises: + TypeError: If the action class is abstract or does not inherit from `WorkspaceAction`. + """ + from nat.cli.type_registry import GlobalTypeRegistry + from nat.cli.type_registry import RegisteredWorkspaceActionInfo + from nat.workspace.types import WorkspaceAction + + if not issubclass(action_cls, WorkspaceAction): + raise TypeError("Action class must inherit from WorkspaceAction.") + if inspect.isabstract(action_cls): + raise TypeError("Cannot register an abstract WorkspaceAction.") + + registration = RegisteredWorkspaceActionInfo( + name=action_cls.name, + action_cls=action_cls, + action_schema=action_cls.schema_for_registry(), + ) + GlobalTypeRegistry.get().register_workspace_action(registration) + return action_cls + + def register_function(config_type: type[FunctionConfigT], framework_wrappers: list[LLMFrameworkEnum | str] | None = None): """ diff --git a/packages/nvidia_nat_core/src/nat/cli/type_registry.py b/packages/nvidia_nat_core/src/nat/cli/type_registry.py index a626d26228..00c3121f45 100644 --- a/packages/nvidia_nat_core/src/nat/cli/type_registry.py +++ b/packages/nvidia_nat_core/src/nat/cli/type_registry.py @@ -87,15 +87,21 @@ from nat.data_models.telemetry_exporter import TelemetryExporterConfigT from nat.data_models.ttc_strategy import TTCStrategyBaseConfig from nat.data_models.ttc_strategy import TTCStrategyBaseConfigT +from nat.data_models.workspace import WorkspaceBaseConfig +from nat.data_models.workspace import WorkspaceBaseConfigT +from nat.data_models.workspace_guardrail import WorkspaceGuardrailBaseConfig +from nat.data_models.workspace_guardrail import WorkspaceGuardrailBaseConfigT from nat.experimental.test_time_compute.models.strategy_base import StrategyBase from nat.finetuning.interfaces.finetuning_runner import Trainer from nat.finetuning.interfaces.trainer_adapter import TrainerAdapter from nat.finetuning.interfaces.trajectory_builder import TrajectoryBuilder +from nat.guardrails.workspace import WorkspaceGuardrail from nat.memory.interfaces import MemoryEditor from nat.middleware.middleware import Middleware from nat.object_store.interfaces import ObjectStore from nat.observability.exporter.base_exporter import BaseExporter from nat.registry_handlers.registry_handler_base import AbstractRegistryHandler +from nat.workspace.types import WorkspaceActionSchema logger = logging.getLogger(__name__) @@ -122,6 +128,8 @@ RetrieverProviderBuildCallableT = Callable[[RetrieverBaseConfigT, Builder], AsyncIterator[RetrieverProviderInfo]] TelemetryExporterBuildCallableT = Callable[[TelemetryExporterConfigT, Builder], AsyncIterator[BaseExporter]] ToolWrapperBuildCallableT = Callable[[str, Function, Builder], typing.Any] +WorkspaceBuildCallableT = Callable[[WorkspaceBaseConfigT], AsyncIterator[typing.Any]] +WorkspaceGuardrailBuildCallableT = Callable[[WorkspaceGuardrailBaseConfigT, Builder], AsyncIterator[WorkspaceGuardrail]] AuthProviderRegisteredCallableT = Callable[[AuthProviderBaseConfigT, Builder], AbstractAsyncContextManager[AuthProviderBase]] @@ -153,6 +161,9 @@ RetrieverProviderRegisteredCallableT = Callable[[RetrieverBaseConfigT, Builder], AbstractAsyncContextManager[RetrieverProviderInfo]] TeleExporterRegisteredCallableT = Callable[[TelemetryExporterConfigT, Builder], AbstractAsyncContextManager[typing.Any]] +WorkspaceRegisteredCallableT = Callable[[WorkspaceBaseConfigT], AbstractAsyncContextManager[typing.Any]] +WorkspaceGuardrailRegisteredCallableT = Callable[[WorkspaceGuardrailBaseConfigT, Builder], + AbstractAsyncContextManager[WorkspaceGuardrail]] class RegisteredInfo(BaseModel, typing.Generic[TypedBaseModelT]): @@ -251,6 +262,14 @@ class RegisteredFrontEndInfo(RegisteredInfo[FrontEndBaseConfig]): build_fn: FrontEndRegisteredCallableT = Field(repr=False) +class RegisteredWorkspaceInfo(RegisteredInfo[WorkspaceBaseConfig]): + """ + Represents a registered workspace configuration. + """ + + build_fn: WorkspaceRegisteredCallableT = Field(repr=False) + + class RegisteredFunctionInfo(RegisteredInfo[FunctionBaseConfig]): """ Represents a registered function. Functions are the building blocks of the workflow with predefined inputs, outputs, @@ -314,6 +333,23 @@ class RegisteredMiddlewareInfo(RegisteredInfo[MiddlewareBaseConfig]): build_fn: MiddlewareRegisteredCallableT = Field(repr=False) +class RegisteredWorkspaceGuardrailInfo(RegisteredInfo[WorkspaceGuardrailBaseConfig]): + """Represents registered workspace guardrails.""" + + build_fn: WorkspaceGuardrailRegisteredCallableT = Field(repr=False) + + +class RegisteredWorkspaceActionInfo(BaseModel): + """Represents a registered workspace action.""" + + model_config = ConfigDict(frozen=True, arbitrary_types_allowed=True) + + name: str + action_cls: type[typing.Any] = Field(repr=False) + action_schema: WorkspaceActionSchema + discovery_metadata: DiscoveryMetadata = DiscoveryMetadata() + + class RegisteredLLMProviderInfo(RegisteredInfo[LLMBaseConfig]): """ Represents a registered LLM provider. LLM Providers are the operators of the LLMs. i.e. NIMs, OpenAI, Anthropic, @@ -452,6 +488,9 @@ def __init__(self) -> None: # Front Ends self._registered_front_end_infos: dict[type[FrontEndBaseConfig], RegisteredFrontEndInfo] = {} + # Workspaces + self._registered_workspace_infos: dict[type[WorkspaceBaseConfig], RegisteredWorkspaceInfo] = {} + # Functions self._registered_functions: dict[type[FunctionBaseConfig], RegisteredFunctionInfo] = {} @@ -461,6 +500,13 @@ def __init__(self) -> None: # Middleware self._registered_middleware: dict[type[MiddlewareBaseConfig], RegisteredMiddlewareInfo] = {} + # Workspace guardrails + self._registered_workspace_guardrails: dict[type[WorkspaceGuardrailBaseConfig], + RegisteredWorkspaceGuardrailInfo] = {} + + # Workspace actions + self._registered_workspace_actions: dict[str, RegisteredWorkspaceActionInfo] = {} + # LLMs self._registered_llm_provider_infos: dict[type[LLMBaseConfig], RegisteredLLMProviderInfo] = {} self._llm_client_provider_to_framework: dict[type[LLMBaseConfig], dict[str, RegisteredLLMClientInfo]] = {} @@ -709,6 +755,28 @@ def get_registered_front_ends(self) -> list[RegisteredInfo[FrontEndBaseConfig]]: return list(self._registered_front_end_infos.values()) + def register_workspace(self, registration: RegisteredWorkspaceInfo): + + if (registration.config_type in self._registered_workspace_infos): + raise ValueError(f"A workspace with the same config type `{registration.config_type}` has already been " + "registered.") + + self._registered_workspace_infos[registration.config_type] = registration + + self._registration_changed() + + def get_workspace(self, config_type: type[WorkspaceBaseConfig]) -> RegisteredWorkspaceInfo: + + try: + return self._registered_workspace_infos[config_type] + except KeyError as err: + raise KeyError(f"Could not find a registered workspace for config `{config_type}`. " + f"Registered configs: {set(self._registered_workspace_infos.keys())}") from err + + def get_registered_workspaces(self) -> list[RegisteredInfo[WorkspaceBaseConfig]]: + + return list(self._registered_workspace_infos.values()) + def register_function(self, registration: RegisteredFunctionInfo): if (registration.config_type in self._registered_functions): @@ -818,6 +886,82 @@ def get_registered_middleware(self) -> list[RegisteredInfo[MiddlewareBaseConfig] """ return list(self._registered_middleware.values()) + def register_workspace_guardrail(self, registration: RegisteredWorkspaceGuardrailInfo): + """Register workspace guardrails with the type registry. + + Args: + registration: The workspace guardrail registration information + + Raises: + ValueError: If a workspace guardrail with the same config type is already registered + """ + if registration.config_type in self._registered_workspace_guardrails: + raise ValueError( + f"Workspace guardrail with the same config type `{registration.config_type}` has already been " + "registered.") + + self._registered_workspace_guardrails[registration.config_type] = registration + self._registration_changed() + + def get_workspace_guardrail( + self, + config_type: type[WorkspaceGuardrailBaseConfig], + ) -> RegisteredWorkspaceGuardrailInfo: + """Get registered workspace guardrail by its config type.""" + try: + return self._registered_workspace_guardrails[config_type] + except KeyError as err: + raise KeyError(f"Could not find registered workspace guardrail for config `{config_type}`. " + f"Registered configs: {set(self._registered_workspace_guardrails.keys())}") from err + + def get_registered_workspace_guardrails(self) -> list[RegisteredInfo[WorkspaceGuardrailBaseConfig]]: + """Get all registered workspace guardrails.""" + return list(self._registered_workspace_guardrails.values()) + + def register_workspace_action(self, registration: RegisteredWorkspaceActionInfo) -> None: + """Register a workspace action. + + Args: + registration: The workspace action registration information. + + Raises: + ValueError: If an action with the same name is already registered or the schema name mismatches. + """ + if registration.name in self._registered_workspace_actions: + raise ValueError(f"A workspace action with the same name `{registration.name}` has already been " + "registered.") + if registration.action_schema.name != registration.name: + raise ValueError("Workspace action schema name does not match the registered action name.") + + self._registered_workspace_actions[registration.name] = registration + self._registration_changed() + + def get_workspace_action(self, action_name: str) -> RegisteredWorkspaceActionInfo: + """Get a registered workspace action by name. + + Args: + action_name: The name of the registered workspace action. + + Returns: + RegisteredWorkspaceActionInfo: The registered action information. + + Raises: + KeyError: If the action is not registered. + """ + try: + return self._registered_workspace_actions[action_name] + except KeyError as err: + raise KeyError(f"Could not find a registered workspace action `{action_name}`. " + f"Registered actions: {set(self._registered_workspace_actions.keys())}") from err + + def get_registered_workspace_actions(self) -> list[RegisteredWorkspaceActionInfo]: + """Get all registered workspace actions. + + Returns: + list[RegisteredWorkspaceActionInfo]: List of all registered workspace actions. + """ + return list(self._registered_workspace_actions.values()) + def register_llm_provider(self, info: RegisteredLLMProviderInfo): if (info.config_type in self._registered_llm_provider_infos): @@ -1146,6 +1290,9 @@ def get_infos_by_type(self, component_type: ComponentEnum) -> dict: if component_type == ComponentEnum.FRONT_END: return self._registered_front_end_infos + if component_type == ComponentEnum.WORKSPACE: + return self._registered_workspace_infos + if component_type == ComponentEnum.AUTHENTICATION_PROVIDER: return self._registered_auth_provider_infos @@ -1218,6 +1365,9 @@ def get_infos_by_type(self, component_type: ComponentEnum) -> dict: if component_type == ComponentEnum.MIDDLEWARE: return self._registered_middleware + if component_type == ComponentEnum.WORKSPACE_GUARDRAIL: + return self._registered_workspace_guardrails + if component_type == ComponentEnum.TRAINER: return self._registered_trainer_infos @@ -1237,6 +1387,12 @@ def get_registered_types_by_component_type(self, component_type: ComponentEnum) if component_type == ComponentEnum.FUNCTION_GROUP: return [i.static_type() for i in self._registered_function_groups] + if component_type == ComponentEnum.WORKSPACE: + return [i.static_type() for i in self._registered_workspace_infos] + + if component_type == ComponentEnum.WORKSPACE_GUARDRAIL: + return [i.static_type() for i in self._registered_workspace_guardrails] + if component_type == ComponentEnum.TOOL_WRAPPER: return list(self._registered_tool_wrappers) @@ -1329,6 +1485,12 @@ def compute_annotation(self, cls: type[TypedBaseModelT]): if issubclass(cls, FrontEndBaseConfig): return self._do_compute_annotation(cls, self.get_registered_front_ends()) + if issubclass(cls, WorkspaceBaseConfig): + return self._do_compute_annotation(cls, self.get_registered_workspaces()) + + if issubclass(cls, WorkspaceGuardrailBaseConfig): + return self._do_compute_annotation(cls, self.get_registered_workspace_guardrails()) + if issubclass(cls, FunctionBaseConfig): return self._do_compute_annotation(cls, self.get_registered_functions()) diff --git a/packages/nvidia_nat_core/src/nat/data_models/component.py b/packages/nvidia_nat_core/src/nat/data_models/component.py index e6e054d160..9a4d114952 100644 --- a/packages/nvidia_nat_core/src/nat/data_models/component.py +++ b/packages/nvidia_nat_core/src/nat/data_models/component.py @@ -45,6 +45,8 @@ class ComponentEnum(StrEnum): TRAINER = "trainer" TRAJECTORY_BUILDER = "trajectory_builder" TRAINER_ADAPTER = "trainer_adapter" + WORKSPACE_GUARDRAIL = "workspace_guardrail" + WORKSPACE = "workspace" UNDEFINED = "undefined" @@ -63,3 +65,4 @@ class ComponentGroup(StrEnum): TRAINERS = "trainers" TRAINER_ADAPTERS = "trainer_adapters" TRAJECTORY_BUILDERS = "trajectory_builders" + WORKSPACE_GUARDRAILS = "workspace_guardrails" diff --git a/packages/nvidia_nat_core/src/nat/data_models/component_ref.py b/packages/nvidia_nat_core/src/nat/data_models/component_ref.py index 4b8b80d90f..149ca1de00 100644 --- a/packages/nvidia_nat_core/src/nat/data_models/component_ref.py +++ b/packages/nvidia_nat_core/src/nat/data_models/component_ref.py @@ -190,6 +190,17 @@ def component_group(self): return ComponentGroup.MIDDLEWARE +class WorkspaceGuardrailRef(ComponentRef): + """ + A reference to a workspace guardrail in a NAT configuration object. + """ + + @property + @override + def component_group(self): + return ComponentGroup.WORKSPACE_GUARDRAILS + + class TrainerRef(ComponentRef): """ A reference to a trainer in a NAT configuration object. diff --git a/packages/nvidia_nat_core/src/nat/data_models/config.py b/packages/nvidia_nat_core/src/nat/data_models/config.py index 0229416a99..1f7038607f 100644 --- a/packages/nvidia_nat_core/src/nat/data_models/config.py +++ b/packages/nvidia_nat_core/src/nat/data_models/config.py @@ -51,6 +51,8 @@ from .middleware import FunctionMiddlewareBaseConfig from .object_store import ObjectStoreBaseConfig from .retriever import RetrieverBaseConfig +from .workspace import WorkspaceBaseConfig +from .workspace_guardrail import WorkspaceGuardrailBaseConfig logger = logging.getLogger(__name__) @@ -100,6 +102,10 @@ def _process_validation_error(err: ValidationError, handler: ValidatorFunctionWr registered_keys = GlobalTypeRegistry.get().get_registered_trainer_adapters() elif (info.field_name == "trajectory_builders"): registered_keys = GlobalTypeRegistry.get().get_registered_trajectory_builders() + elif (info.field_name == "workspace"): + registered_keys = GlobalTypeRegistry.get().get_registered_workspaces() + elif (info.field_name == "workspace_guardrails"): + registered_keys = GlobalTypeRegistry.get().get_registered_workspace_guardrails() else: assert False, f"Unknown field name {info.field_name} in validator" @@ -274,6 +280,12 @@ class Config(HashableBaseModel): # Global Options general: GeneralConfig = GeneralConfig() + # Workspace Configuration + workspace: WorkspaceBaseConfig | None = None + + # Workspace Guardrails + workspace_guardrails: dict[str, WorkspaceGuardrailBaseConfig] = Field(default_factory=dict) + # Functions Configuration functions: dict[str, FunctionBaseConfig] = Field(default_factory=dict) @@ -326,6 +338,8 @@ def print_summary(self, stream: typing.TextIO = sys.stdout): stream.write("-" * 20 + "\n") if self.workflow: stream.write(f"Workflow Type: {self.workflow.type}\n") + if self.workspace: + stream.write(f"Workspace Type: {self.workspace.type}\n") stream.write(f"Number of Functions: {len(self.functions)}\n") stream.write(f"Number of Function Groups: {len(self.function_groups)}\n") @@ -336,10 +350,12 @@ def print_summary(self, stream: typing.TextIO = sys.stdout): stream.write(f"Number of Retrievers: {len(self.retrievers)}\n") stream.write(f"Number of TTC Strategies: {len(self.ttc_strategies)}\n") stream.write(f"Number of Authentication Providers: {len(self.authentication)}\n") + stream.write(f"Number of Workspace Guardrails: {len(self.workspace_guardrails)}\n") @field_validator("functions", "function_groups", "middleware", + "workspace_guardrails", "llms", "embedders", "memory", @@ -350,6 +366,7 @@ def print_summary(self, stream: typing.TextIO = sys.stdout): "trainers", "trainer_adapters", "trajectory_builders", + "workspace", mode="wrap") @classmethod def validate_components(cls, value: typing.Any, handler: ValidatorFunctionWrapHandler, info: ValidationInfo): @@ -392,6 +409,12 @@ def rebuild_annotations(cls): typing.Annotated[type_registry.compute_annotation(FunctionMiddlewareBaseConfig), Discriminator(TypedBaseModel.discriminator)]] + WorkspaceGuardrailsAnnotation = dict[ + str, + typing.Annotated[type_registry.compute_annotation(WorkspaceGuardrailBaseConfig), + Discriminator(TypedBaseModel.discriminator)], + ] + MemoryAnnotation = dict[str, typing.Annotated[type_registry.compute_annotation(MemoryBaseConfig), Discriminator(TypedBaseModel.discriminator)]] @@ -422,6 +445,10 @@ def rebuild_annotations(cls): typing.Annotated[type_registry.compute_annotation(TrajectoryBuilderConfig), Discriminator(TypedBaseModel.discriminator)]] + WorkspaceAnnotation = typing.Annotated[type_registry.compute_annotation(WorkspaceBaseConfig), + Discriminator(TypedBaseModel.discriminator)] + OptionalWorkspaceAnnotation = WorkspaceAnnotation | None + should_rebuild = False auth_providers_field = cls.model_fields.get("authentication") @@ -454,6 +481,12 @@ def rebuild_annotations(cls): middleware_field.annotation = MiddlewareAnnotation should_rebuild = True + workspace_guardrails_field = cls.model_fields.get("workspace_guardrails") + if (workspace_guardrails_field is not None + and workspace_guardrails_field.annotation != WorkspaceGuardrailsAnnotation): + workspace_guardrails_field.annotation = WorkspaceGuardrailsAnnotation + should_rebuild = True + memory_field = cls.model_fields.get("memory") if memory_field is not None and memory_field.annotation != MemoryAnnotation: memory_field.annotation = MemoryAnnotation @@ -479,6 +512,11 @@ def rebuild_annotations(cls): workflow_field.annotation = WorkflowAnnotation should_rebuild = True + workspace_field = cls.model_fields.get("workspace") + if workspace_field is not None and workspace_field.annotation != OptionalWorkspaceAnnotation: + workspace_field.annotation = OptionalWorkspaceAnnotation + should_rebuild = True + trainers_field = cls.model_fields.get("trainers") if trainers_field is not None and trainers_field.annotation != TrainersAnnotation: trainers_field.annotation = TrainersAnnotation diff --git a/packages/nvidia_nat_core/src/nat/data_models/skill.py b/packages/nvidia_nat_core/src/nat/data_models/skill.py new file mode 100644 index 0000000000..712314ea7a --- /dev/null +++ b/packages/nvidia_nat_core/src/nat/data_models/skill.py @@ -0,0 +1,347 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Skill definition conforming to the Agent Skills specification (https://agentskills.io).""" + +import base64 +import re +from pathlib import Path +from typing import Any + +import yaml +from pydantic import BaseModel +from pydantic import ConfigDict +from pydantic import Field +from pydantic import field_validator +from pydantic import model_validator + +# --------------------------------------------------------------------------- +# Name validation regex (spec: 1-64 chars, lowercase a-z, digits, hyphens, +# no leading/trailing/consecutive hyphens) +# --------------------------------------------------------------------------- +_NAME_RE = re.compile(r"^[a-z0-9]([a-z0-9-]{0,62}[a-z0-9])?$") +_CONSECUTIVE_HYPHENS_RE = re.compile(r"--") + + +class Skill(BaseModel): + """An Agent Skill per the `agentskills.io `_ spec. + + Required frontmatter + -------------------- + name : str + 1-64 chars, lowercase alphanumeric + hyphens. No leading/trailing/ + consecutive hyphens. Must match the parent directory name when loaded. + description : str + 1-1024 chars. Describes what the skill does and when to use it. + + Optional frontmatter + -------------------- + license, compatibility, allowed_tools, metadata + + Body content + ------------ + content : str + Markdown body with skill instructions (loaded on activation). + """ + + model_config = ConfigDict(frozen=True) + + # Required frontmatter + name: str + description: str = Field(min_length=1, max_length=1024) + + # Optional frontmatter + license: str | None = None + compatibility: str | None = Field(default=None, max_length=500) + allowed_tools: list[str] = Field(default_factory=list) + metadata: dict[str, str] = Field(default_factory=dict) + + # Body content + content: str = "" + + # In-memory resource storage (keys = relative paths, values = raw bytes) + resources: dict[str, bytes] = Field(default_factory=dict, repr=False, exclude=True) + + # Runtime context (not serialised to SKILL.md) + source_dir: Path | None = Field(default=None, repr=False, exclude=True) + + @field_validator("name") + @classmethod + def _validate_name(cls, v: str) -> str: + if not v: + raise ValueError("name is required") + if len(v) > 64: + raise ValueError(f"name must be <= 64 chars, got {len(v)}") + if not _NAME_RE.match(v): + raise ValueError(f"name {v!r} must be lowercase alphanumeric + hyphens, " + "no leading/trailing hyphens") + if _CONSECUTIVE_HYPHENS_RE.search(v): + raise ValueError(f"name {v!r} must not contain consecutive hyphens") + return v + + @model_validator(mode="after") + def _validate_source_dir_match(self) -> "Skill": + if self.source_dir and self.source_dir.name != self.name: + raise ValueError(f"name {self.name!r} must match parent directory {self.source_dir.name!r}") + return self + + # ------------------------------------------------------------------ + # Factory + # ------------------------------------------------------------------ + + @classmethod + def load(cls, skill_dir: str | Path) -> "Skill": + """Load a skill from a directory containing ``SKILL.md``. + + Parses YAML frontmatter (delimited by ``---``) and the remaining + markdown body. Also reads files from ``scripts/``, ``references/``, + and ``assets/`` subdirectories into ``resources``. + """ + skill_dir = Path(skill_dir) + skill_md = skill_dir / "SKILL.md" + if not skill_md.is_file(): + raise FileNotFoundError(f"No SKILL.md found in {skill_dir}") + + raw = skill_md.read_text(encoding="utf-8") + frontmatter, body = _parse_frontmatter(raw) + + # allowed-tools comes as a space-delimited string in the spec + allowed_tools_raw = frontmatter.get("allowed-tools", "") + allowed_tools = allowed_tools_raw.split() if isinstance(allowed_tools_raw, str) and allowed_tools_raw else [] + + # Capture resource files + resources: dict[str, bytes] = {} + for subdir in ("scripts", "references", "assets"): + sub_path = skill_dir / subdir + if sub_path.is_dir(): + for file_path in sorted(sub_path.rglob("*")): + if file_path.is_file(): + rel = str(file_path.relative_to(skill_dir)) + resources[rel] = file_path.read_bytes() + + return cls( + name=frontmatter.get("name", skill_dir.name), + description=frontmatter.get("description", ""), + license=frontmatter.get("license"), + compatibility=frontmatter.get("compatibility"), + allowed_tools=allowed_tools, + metadata=frontmatter.get("metadata") or {}, + content=body, + resources=resources, + source_dir=skill_dir.resolve(), + ) + + # ------------------------------------------------------------------ + # Progressive disclosure helpers + # ------------------------------------------------------------------ + + def to_metadata_prompt(self) -> str: + """Compact metadata for system prompt injection (~50-100 tokens).""" + return f"{self.name}: {self.description}" + + def to_full_prompt(self) -> str: + """Full SKILL.md content for activation.""" + return self.content + + def to_prompt_xml(self, *, include_content: bool = False, location: str | None = None) -> str: + """Generate a ```` XML block per the spec recommendation. + + Parameters + ---------- + include_content + If True, include the full body content (for activated skills). + location + Optional absolute path to SKILL.md for filesystem-based agents. + """ + parts = [ + " ", + f" {_xml_escape(self.name)}", + f" {_xml_escape(self.description)}", + ] + if location: + parts.append(f" {_xml_escape(location)}") + elif self.source_dir: + parts.append(f" {_xml_escape(str(self.source_dir / 'SKILL.md'))}") + if include_content and self.content: + parts.append(f" {_xml_escape(self.content)}") + parts.append(" ") + return "\n".join(parts) + + # ------------------------------------------------------------------ + # Resource access + # ------------------------------------------------------------------ + + def get_resource_path(self, relative_path: str) -> Path | None: + """Resolve a relative path from the skill root directory. + + Returns ``None`` if the skill has no ``source_dir`` or if the + resolved path does not exist. + """ + if self.source_dir is None: + return None + full = (self.source_dir / relative_path).resolve() + # Guard against path traversal + if not str(full).startswith(str(self.source_dir)): + return None + return full if full.exists() else None + + def get_resource(self, relative_path: str) -> bytes | None: + """Get resource bytes by relative path. + + Checks ``self.resources`` first, then falls back to filesystem + read via ``source_dir``. + """ + if relative_path in self.resources: + return self.resources[relative_path] + if self.source_dir is not None: + full = (self.source_dir / relative_path).resolve() + if not str(full).startswith(str(self.source_dir)): + return None + if full.is_file(): + return full.read_bytes() + return None + + def list_resources(self, subdir: str | None = None) -> list[Path]: + """List files in the skill directory. + + Parameters + ---------- + subdir + Optional subdirectory name (e.g. ``"scripts"``, ``"references"``, + ``"assets"``). If ``None``, lists all files recursively. + + When ``source_dir`` is available, reads from the filesystem. + Otherwise, filters keys from the in-memory ``resources`` dict. + """ + if self.source_dir is not None: + root = self.source_dir / subdir if subdir else self.source_dir + if not root.is_dir(): + return [] + return sorted(p for p in root.rglob("*") if p.is_file()) + + # In-memory mode: filter resource keys + if not self.resources: + return [] + prefix = f"{subdir}/" if subdir else "" + return sorted(Path(k) for k in self.resources if k.startswith(prefix)) + + # ------------------------------------------------------------------ + # Serialization + # ------------------------------------------------------------------ + + def to_portable_dict(self) -> dict[str, Any]: + """Serialize to a JSON-compatible dict with base64-encoded resources. + + Excludes ``source_dir`` (runtime-only). + + Resource files are base64-encoded for safe JSON transport. + """ + d = self.model_dump(exclude={"source_dir", "resources"}) + d["resources"] = {k: base64.b64encode(v).decode("ascii") for k, v in self.resources.items()} + return d + + @classmethod + def from_portable_dict(cls, data: dict[str, Any]) -> "Skill": + """Reconstruct a Skill from a ``to_portable_dict()`` output. + + Decodes base64-encoded resources back to bytes. + """ + data = dict(data) # shallow copy to avoid mutating input + raw_resources = data.pop("resources", {}) + resources = {k: base64.b64decode(v) for k, v in raw_resources.items()} + return cls(resources=resources, **data) + + def save(self, directory: str | Path) -> Path: + """Write SKILL.md and resource files to disk. + + Parameters + ---------- + directory + Parent directory in which to create the skill folder (named + after ``self.name``). + + Returns + ------- + Path + The skill directory path. + """ + directory = Path(directory) + skill_dir = directory / self.name + skill_dir.mkdir(parents=True, exist_ok=True) + + # Build SKILL.md with YAML frontmatter + lines = ["---"] + lines.append(f"name: {self.name}") + lines.append(f"description: {self.description}") + if self.license: + lines.append(f"license: {self.license}") + if self.compatibility: + lines.append(f"compatibility: {self.compatibility}") + if self.allowed_tools: + lines.append(f"allowed-tools: {' '.join(self.allowed_tools)}") + if self.metadata: + lines.append("metadata:") + for k, v in self.metadata.items(): + lines.append(f" {k}: \"{v}\"") + lines.append("---") + if self.content: + lines.append(self.content) + + (skill_dir / "SKILL.md").write_text("\n".join(lines), encoding="utf-8") + + # Write resource files + for rel_path, data in self.resources.items(): + file_path = skill_dir / rel_path + file_path.parent.mkdir(parents=True, exist_ok=True) + file_path.write_bytes(data) + + return skill_dir + + +# --------------------------------------------------------------------------- +# Internal helpers +# --------------------------------------------------------------------------- + + +def _xml_escape(text: str) -> str: + """Minimal XML escaping.""" + return text.replace("&", "&").replace("<", "<").replace(">", ">") + + +def _parse_frontmatter(text: str) -> tuple[dict[str, Any], str]: + """Parse YAML frontmatter delimited by ``---`` lines. + + Returns ``(frontmatter_dict, body_string)``. + """ + lines = text.split("\n") + + # The file must start with --- + if not lines or lines[0].strip() != "---": + return {}, text + + end_idx = None + for i in range(1, len(lines)): + if lines[i].strip() == "---": + end_idx = i + break + + if end_idx is None: + return {}, text + + yaml_block = "\n".join(lines[1:end_idx]) + body = "\n".join(lines[end_idx + 1:]).strip() + + frontmatter = yaml.safe_load(yaml_block) or {} + + return frontmatter, body diff --git a/packages/nvidia_nat_core/src/nat/data_models/workspace.py b/packages/nvidia_nat_core/src/nat/data_models/workspace.py new file mode 100644 index 0000000000..7ab45ba1aa --- /dev/null +++ b/packages/nvidia_nat_core/src/nat/data_models/workspace.py @@ -0,0 +1,127 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import datetime +import typing +import uuid +from abc import ABC +from dataclasses import dataclass +from enum import StrEnum +from pathlib import Path + +from pydantic import BaseModel +from pydantic import ConfigDict +from pydantic import Field +from pydantic import model_validator + +from nat.data_models.common import BaseModelRegistryTag +from nat.data_models.common import TypedBaseModel +from nat.data_models.component_ref import WorkspaceGuardrailRef + + +@dataclass(frozen=True) +class ActionContext: + """Context provided to workspace actions.""" + + session_id: str + root_path: Path + + +class WorkspaceBaseConfig(TypedBaseModel, BaseModelRegistryTag, ABC): + """Base configuration for workspaces.""" + working_directory: Path = Field(description="The working directory for the workspace.") + initial_commands: list[str] | Path | str = Field( + description="The initial commands to run in the workspace. Assumes the existence of a shell workspace tool") + workspace_guardrails: list[WorkspaceGuardrailRef] = Field( + default_factory=list, + description="Workspace guardrails to apply to workspace actions.", + ) + endpoint: str | None = Field( + default=None, + description= + "endpoint override to use. Should likely not be used in end-user configurations " + \ + "due to this only being needed for workspace propagation across agents." + ) + session_id: str | None = Field( + default=None, + description="Session identifier to reuse an existing workspace session.", + ) + + @property + def skills_directory(self) -> Path: + return self.working_directory / "skills" + + +WorkspaceBaseConfigT = typing.TypeVar("WorkspaceBaseConfigT", bound=WorkspaceBaseConfig) + + +class ActionStatus(StrEnum): + """Status values for workspace action execution.""" + + SUCCESS = "SUCCESS" + FAILURE = "FAILURE" + BLOCKED_BY_GUARDRAIL = "BLOCKED_BY_GUARDRAIL" + + +class ActionRequest(BaseModel): + """Structured request for a workspace action. + + Args: + action_id: Unique identifier for this action instance. + action_name: Name of the action to execute. + arguments: Key-value arguments for the action. + timestamp: Time the action request was generated. + model_metadata: Optional metadata provided by the model layer. + """ + + model_config = ConfigDict(extra="forbid") + + action_id: uuid.UUID = Field(description="Unique identifier for this action instance.") + action_name: str = Field(description="Name of the action to execute.") + arguments: dict[str, typing.Any] = Field(default_factory=dict, description="Key-value action arguments.") + timestamp: datetime.datetime = Field(description="Time the action request was generated.") + model_metadata: dict[str, typing.Any] | None = Field( + default=None, + description="Optional metadata provided by the model layer.", + ) + + +class ActionResult(BaseModel): + """Structured result for a workspace action. + + Args: + action_id: Identifier of the corresponding action. + status: Execution status for the action. + output: Execution output or returned data. + error_message: Error details for failed or blocked actions. + execution_time: Time taken for action execution in seconds. + """ + + model_config = ConfigDict(extra="forbid") + + action_id: uuid.UUID = Field(default_factory=uuid.uuid4, description="Identifier of the corresponding action.") + status: ActionStatus = Field(description="Execution status for the action.") + output: typing.Any | None = Field(default=None, description="Execution output or returned data.") + error_message: str | None = Field( + default=None, + description="Error details for failed or blocked actions.", + ) + execution_time: float | None = Field(default=None, description="Time taken for action execution in seconds.") + + @model_validator(mode="after") + def _validate_error_message(self) -> "ActionResult": + if self.status in {ActionStatus.FAILURE, ActionStatus.BLOCKED_BY_GUARDRAIL} and not self.error_message: + raise ValueError("error_message must be set for failed or blocked actions.") + return self diff --git a/packages/nvidia_nat_core/src/nat/data_models/workspace_guardrail.py b/packages/nvidia_nat_core/src/nat/data_models/workspace_guardrail.py new file mode 100644 index 0000000000..fe4c09d98c --- /dev/null +++ b/packages/nvidia_nat_core/src/nat/data_models/workspace_guardrail.py @@ -0,0 +1,29 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Base configuration for workspace guardrails.""" + +from __future__ import annotations + +import typing + +from nat.data_models.common import BaseModelRegistryTag +from nat.data_models.common import TypedBaseModel + + +class WorkspaceGuardrailBaseConfig(TypedBaseModel, BaseModelRegistryTag): + """Base configuration for workspace guardrails.""" + + +WorkspaceGuardrailBaseConfigT = typing.TypeVar("WorkspaceGuardrailBaseConfigT", bound=WorkspaceGuardrailBaseConfig) diff --git a/packages/nvidia_nat_core/src/nat/guardrails/__init__.py b/packages/nvidia_nat_core/src/nat/guardrails/__init__.py new file mode 100644 index 0000000000..d1d9d1e7ea --- /dev/null +++ b/packages/nvidia_nat_core/src/nat/guardrails/__init__.py @@ -0,0 +1,14 @@ +# SPDX-FileCopyrightText: Copyright (c) 2024-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/packages/nvidia_nat_core/src/nat/guardrails/workspace.py b/packages/nvidia_nat_core/src/nat/guardrails/workspace.py new file mode 100644 index 0000000000..16201da20e --- /dev/null +++ b/packages/nvidia_nat_core/src/nat/guardrails/workspace.py @@ -0,0 +1,63 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Workspace guardrail base types.""" + +from abc import ABC +from dataclasses import dataclass + +from nat.data_models.workspace import ActionRequest +from nat.data_models.workspace import ActionResult + + +@dataclass(frozen=True) +class WorkspaceGuardrailViolation: + """Guardrail failure details. + + Args: + guardrail_name: Name of the guardrail that blocked the action. + message: Description of the violation. + """ + + guardrail_name: str + message: str + + +class WorkspaceGuardrail(ABC): + """Base class for workspace guardrails.""" + + name: str + + async def validate_action(self, action: ActionRequest) -> WorkspaceGuardrailViolation | None: + """Validate an action before execution. + + Args: + action: Structured action request. + + Returns: + GuardrailViolation if blocked, otherwise None. + """ + return None + + async def sanitize_result(self, action: ActionRequest, result: ActionResult) -> ActionResult: + """Sanitize the action result before returning it to the model layer. + + Args: + action: Structured action request. + result: Action result to sanitize. + + Returns: + ActionResult after any redaction or modification. + """ + return result diff --git a/packages/nvidia_nat_core/src/nat/runtime/loader.py b/packages/nvidia_nat_core/src/nat/runtime/loader.py index a14bd3ab83..628e999277 100644 --- a/packages/nvidia_nat_core/src/nat/runtime/loader.py +++ b/packages/nvidia_nat_core/src/nat/runtime/loader.py @@ -54,13 +54,17 @@ class PluginTypes(IntFlag): A plugin that is an API authentication provider for the workflow. This includes Oauth2, API Key, etc. """ REGISTRY_HANDLER = auto() + """ + A plugin that is a registry handler for the workflow. This includes registry handlers like NAT, etc. + """ + WORKSPACE_ACTION = auto() # Convenience flag for groups of plugin types CONFIG_OBJECT = COMPONENT | FRONT_END | EVALUATOR | AUTHENTICATION """ Any plugin that can be specified in the NAT configuration file. """ - ALL = COMPONENT | FRONT_END | EVALUATOR | REGISTRY_HANDLER | AUTHENTICATION + ALL = COMPONENT | FRONT_END | EVALUATOR | AUTHENTICATION | REGISTRY_HANDLER | WORKSPACE_ACTION """ All plugin types """ @@ -146,6 +150,8 @@ def discover_entrypoints(plugin_type: PluginTypes): plugin_groups.extend(["nat.evaluators"]) if (plugin_type & PluginTypes.AUTHENTICATION): plugin_groups.extend(["nat.authentication_providers"]) + if (plugin_type & PluginTypes.WORKSPACE_ACTION): + plugin_groups.extend(["nat.workspace_actions"]) # Get the entry points for the specified groups nat_plugins = reduce(lambda x, y: list(x) + list(y), [entry_points.select(group=y) for y in plugin_groups]) diff --git a/packages/nvidia_nat_core/src/nat/workspace/__init__.py b/packages/nvidia_nat_core/src/nat/workspace/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/packages/nvidia_nat_core/src/nat/workspace/types.py b/packages/nvidia_nat_core/src/nat/workspace/types.py new file mode 100644 index 0000000000..d485e89d65 --- /dev/null +++ b/packages/nvidia_nat_core/src/nat/workspace/types.py @@ -0,0 +1,156 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import typing +from abc import ABC +from abc import abstractmethod +from dataclasses import dataclass +from pathlib import Path + +from nat.data_models.skill import Skill +from nat.data_models.workspace import ActionContext +from nat.data_models.workspace import ActionResult +from nat.data_models.workspace import WorkspaceBaseConfig + + +@dataclass +class TypeSchema: + type: str + description: str + + +@dataclass +class WorkspaceActionSchema: + name: str + description: str + parameters: list[TypeSchema] + result: TypeSchema + + +@dataclass +class SkillSummary: + name: str + description: str + + +class WorkspaceBase(ABC): + + @abstractmethod + async def get_actions(self) -> list[WorkspaceActionSchema]: + pass + + @abstractmethod + async def get_skills(self) -> list[SkillSummary]: + pass + + @abstractmethod + async def create_skill(self, skill: Skill) -> ActionResult: + pass + + @abstractmethod + async def read_skill(self, skill_name: str) -> Skill | None: + pass + + @abstractmethod + async def execute_action( + self, + action_name: str, + args: dict[str, typing.Any], + model_metadata: dict[str, typing.Any] | None = None, + ) -> ActionResult: + pass + + @abstractmethod + async def upload_file(self, file_path: Path, destination_path: Path) -> ActionResult: + pass + + @abstractmethod + async def delete_file(self, file_path: Path) -> ActionResult: + pass + + @abstractmethod + async def download_file(self, file_path: Path) -> ActionResult: + pass + + @abstractmethod + async def upload_directory(self, directory_path: Path, destination_path: Path) -> ActionResult: + pass + + @abstractmethod + async def download_directory(self, directory_path: Path, destination_path: Path) -> ActionResult: + pass + + @abstractmethod + async def delete_directory(self, directory_path: Path) -> ActionResult: + pass + + +ConfigT = typing.TypeVar("ConfigT", bound=WorkspaceBaseConfig) +InstanceT = typing.TypeVar("InstanceT", bound=WorkspaceBase) + + +class WorkspaceManagerBase(ABC, typing.Generic[ConfigT, InstanceT]): + + def __init__(self, config: ConfigT): + self.config = config + + @abstractmethod + async def __aenter__(self) -> InstanceT: + pass + + @abstractmethod + async def __aexit__(self, exc_type, exc_value, traceback) -> None: + pass + + +class WorkspaceAction(ABC): + """Base interface for workspace actions.""" + + name: str + description: str + parameters: list[TypeSchema] + result: TypeSchema + + _context: ActionContext | None = None + + def set_context(self, context: ActionContext) -> None: + """Bind the action to a session context.""" + self._context = context + + @classmethod + def schema_for_registry(cls) -> WorkspaceActionSchema: + """Return the schema using class attributes.""" + return WorkspaceActionSchema( + name=cls.name, + description=cls.description, + parameters=cls.parameters, + result=cls.result, + ) + + async def __aenter__(self) -> "WorkspaceAction": + return self + + async def __aexit__(self, exc_type, exc_value, traceback) -> None: + return None + + @property + def schema(self) -> WorkspaceActionSchema: + """Return the action schema for API responses.""" + return type(self).schema_for_registry() + + @abstractmethod + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> typing.Any: + """Execute the action with the provided args.""" + raise NotImplementedError diff --git a/packages/nvidia_nat_core/tests/nat/cli/test_type_registry.py b/packages/nvidia_nat_core/tests/nat/cli/test_type_registry.py index 32af580b3c..ab257d0ed3 100644 --- a/packages/nvidia_nat_core/tests/nat/cli/test_type_registry.py +++ b/packages/nvidia_nat_core/tests/nat/cli/test_type_registry.py @@ -18,7 +18,11 @@ from _utils.configs import FunctionTestConfig from nat.builder.builder import Builder from nat.cli.type_registry import RegisteredFunctionInfo +from nat.cli.type_registry import RegisteredWorkspaceActionInfo from nat.cli.type_registry import TypeRegistry +from nat.data_models.discovery_metadata import DiscoveryStatusEnum +from nat.workspace.types import TypeSchema +from nat.workspace.types import WorkspaceActionSchema def test_register_function(registry: TypeRegistry): @@ -37,3 +41,26 @@ def tool_fn(builder: Builder): assert workflow_info.local_name == "function" assert workflow_info.config_type is FunctionTestConfig assert workflow_info.build_fn is tool_fn + + +def test_register_workspace_action(registry: TypeRegistry): + schema = WorkspaceActionSchema( + name="example", + description="Example workspace action.", + parameters=[TypeSchema(type="string", description="Example input.")], + result=TypeSchema(type="object", description="Example output."), + ) + action_cls = type("ExampleAction", (), {}) + + registry.register_workspace_action( + RegisteredWorkspaceActionInfo(name="example", action_cls=action_cls, action_schema=schema)) + + action_info = registry.get_workspace_action("example") + assert action_info.action_cls is action_cls + assert action_info.action_schema == schema + assert action_info.discovery_metadata.package == "test" + assert action_info.discovery_metadata.version == "0.1.0" + assert action_info.discovery_metadata.component_name == "example" + assert action_info.discovery_metadata.description == "Example workspace action." + assert action_info.discovery_metadata.developer_notes == "" + assert action_info.discovery_metadata.status == DiscoveryStatusEnum.SUCCESS diff --git a/packages/nvidia_nat_core/tests/nat/data_models/test_skill.py b/packages/nvidia_nat_core/tests/nat/data_models/test_skill.py new file mode 100644 index 0000000000..e0ce2e6ef3 --- /dev/null +++ b/packages/nvidia_nat_core/tests/nat/data_models/test_skill.py @@ -0,0 +1,598 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for nat.data_models.skill — Skill (Agent Skills spec compliance).""" + +from pathlib import Path + +import pytest +from pydantic import ValidationError + +from nat.data_models.skill import Skill + +# --------------------------------------------------------------------------- +# Construction & defaults +# --------------------------------------------------------------------------- + + +class TestSkillConstruction: + + def test_minimal(self) -> None: + s = Skill(name="my-skill", description="Does things") + assert s.name == "my-skill" + assert s.description == "Does things" + assert s.license is None + assert s.compatibility is None + assert s.allowed_tools == [] + assert s.metadata == {} + assert s.content == "" + assert s.source_dir is None + assert s.resources == {} + + def test_full(self) -> None: + s = Skill( + name="pdf-processing", + description="Extract text from PDFs", + license="Apache-2.0", + compatibility="Requires poppler", + allowed_tools=["Bash(pdftotext:*)", "Read"], + metadata={ + "author": "nvidia", "version": "1.0" + }, + content="# Instructions\nDo the thing.", + source_dir=Path("/tmp/pdf-processing"), + ) + assert s.license == "Apache-2.0" + assert s.compatibility == "Requires poppler" + assert len(s.allowed_tools) == 2 + assert s.metadata["author"] == "nvidia" + assert "Instructions" in s.content + + def test_frozen(self) -> None: + s = Skill(name="test", description="test") + with pytest.raises(ValidationError): + s.name = "other" # type: ignore[misc] + + +# --------------------------------------------------------------------------- +# Name validation (per Agent Skills spec) +# --------------------------------------------------------------------------- + + +class TestSkillNameValidation: + + def test_valid_names(self) -> None: + for name in ["a", "my-skill", "data-analysis", "a1b2c3", "x" * 64]: + Skill(name=name, description="ok") # should not raise + + def test_empty_name(self) -> None: + with pytest.raises(ValidationError, match="name"): + Skill(name="", description="ok") + + def test_too_long(self) -> None: + with pytest.raises(ValidationError, match="64"): + Skill(name="a" * 65, description="ok") + + def test_uppercase(self) -> None: + with pytest.raises(ValidationError, match="lowercase"): + Skill(name="PDF-Processing", description="ok") + + def test_leading_hyphen(self) -> None: + with pytest.raises(ValidationError): + Skill(name="-pdf", description="ok") + + def test_trailing_hyphen(self) -> None: + with pytest.raises(ValidationError): + Skill(name="pdf-", description="ok") + + def test_consecutive_hyphens(self) -> None: + with pytest.raises(ValidationError, match="consecutive"): + Skill(name="pdf--tool", description="ok") + + def test_special_characters(self) -> None: + with pytest.raises(ValidationError): + Skill(name="my_skill", description="ok") # underscores not allowed + + +# --------------------------------------------------------------------------- +# Description validation +# --------------------------------------------------------------------------- + + +class TestSkillDescriptionValidation: + + def test_empty_description(self) -> None: + with pytest.raises(ValidationError, match="description"): + Skill(name="test", description="") + + def test_too_long_description(self) -> None: + with pytest.raises(ValidationError, match="1024"): + Skill(name="test", description="x" * 1025) + + +# --------------------------------------------------------------------------- +# Compatibility validation +# --------------------------------------------------------------------------- + + +class TestSkillCompatibilityValidation: + + def test_too_long_compatibility(self) -> None: + with pytest.raises(ValidationError, match="500"): + Skill(name="test", description="ok", compatibility="x" * 501) + + def test_valid_compatibility(self) -> None: + Skill(name="test", description="ok", compatibility="Requires docker") # should not raise + + +# --------------------------------------------------------------------------- +# Directory name match validation +# --------------------------------------------------------------------------- + + +class TestSkillDirectoryNameValidation: + + def test_name_matches_dir(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + skill_dir.mkdir() + Skill(name="my-skill", description="ok", source_dir=skill_dir.resolve()) # should not raise + + def test_name_mismatch(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "other-name" + skill_dir.mkdir() + with pytest.raises(ValidationError, match="match"): + Skill(name="my-skill", description="ok", source_dir=skill_dir.resolve()) + + +# --------------------------------------------------------------------------- +# Load from SKILL.md +# --------------------------------------------------------------------------- + + +class TestSkillLoad: + + def test_load_minimal(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + skill_dir.mkdir() + (skill_dir / + "SKILL.md").write_text("---\nname: my-skill\ndescription: A test skill.\n---\n\n# Instructions\nDo stuff.\n") + s = Skill.load(skill_dir) + assert s.name == "my-skill" + assert s.description == "A test skill." + assert "Instructions" in s.content + assert s.source_dir == skill_dir.resolve() + + def test_load_with_optional_fields(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "pdf-tool" + skill_dir.mkdir() + (skill_dir / "SKILL.md").write_text("---\n" + "name: pdf-tool\n" + "description: Process PDFs.\n" + "license: MIT\n" + "compatibility: Needs poppler\n" + "allowed-tools: Bash(pdf:*) Read\n" + "metadata:\n" + " author: test\n" + " version: \"2.0\"\n" + "---\n\n" + "Body content here.\n") + s = Skill.load(skill_dir) + assert s.name == "pdf-tool" + assert s.license == "MIT" + assert s.compatibility == "Needs poppler" + assert s.allowed_tools == ["Bash(pdf:*)", "Read"] + assert s.metadata["author"] == "test" + assert s.metadata["version"] == "2.0" + + def test_load_missing_skill_md(self, tmp_path: Path) -> None: + with pytest.raises(FileNotFoundError): + Skill.load(tmp_path) + + def test_load_no_frontmatter(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "bare" + skill_dir.mkdir() + (skill_dir / "SKILL.md").write_text("Just some content.\n") + with pytest.raises(ValidationError, match="description"): + Skill.load(skill_dir) + + def test_load_uses_dir_name_as_default(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "fallback" + skill_dir.mkdir() + (skill_dir / "SKILL.md").write_text("---\ndescription: ok\n---\nBody\n") + s = Skill.load(skill_dir) + assert s.name == "fallback" + + def test_load_captures_resources(self, tmp_path: Path) -> None: + """load() should read scripts/, references/, assets/ into resources.""" + skill_dir = tmp_path / "my-skill" + skill_dir.mkdir() + (skill_dir / "SKILL.md").write_text("---\nname: my-skill\ndescription: ok\n---\nBody\n") + + scripts = skill_dir / "scripts" + scripts.mkdir() + (scripts / "run.py").write_bytes(b"print('hello')") + + refs = skill_dir / "references" + refs.mkdir() + (refs / "REFERENCE.md").write_bytes(b"# Reference") + + assets = skill_dir / "assets" + assets.mkdir() + (assets / "logo.png").write_bytes(b"\x89PNG") + + s = Skill.load(skill_dir) + assert "scripts/run.py" in s.resources + assert s.resources["scripts/run.py"] == b"print('hello')" + assert "references/REFERENCE.md" in s.resources + assert s.resources["references/REFERENCE.md"] == b"# Reference" + assert "assets/logo.png" in s.resources + assert s.resources["assets/logo.png"] == b"\x89PNG" + + def test_load_no_resource_dirs(self, tmp_path: Path) -> None: + """load() with no scripts/references/assets should yield empty resources.""" + skill_dir = tmp_path / "my-skill" + skill_dir.mkdir() + (skill_dir / "SKILL.md").write_text("---\nname: my-skill\ndescription: ok\n---\nBody\n") + s = Skill.load(skill_dir) + assert s.resources == {} + + +# --------------------------------------------------------------------------- +# Progressive disclosure helpers +# --------------------------------------------------------------------------- + + +class TestSkillPrompts: + + def test_to_metadata_prompt(self) -> None: + s = Skill(name="search", description="Search the web") + assert s.to_metadata_prompt() == "search: Search the web" + + def test_to_full_prompt(self) -> None: + s = Skill(name="test", description="d", content="Full body here") + assert s.to_full_prompt() == "Full body here" + + def test_to_prompt_xml_minimal(self) -> None: + s = Skill(name="test", description="A test") + xml = s.to_prompt_xml() + assert "test" in xml + assert "A test" in xml + assert "" not in xml + + def test_to_prompt_xml_with_content(self) -> None: + s = Skill(name="test", description="d", content="Body") + xml = s.to_prompt_xml(include_content=True) + assert "Body" in xml + + def test_to_prompt_xml_with_location(self) -> None: + s = Skill(name="test", description="d") + xml = s.to_prompt_xml(location="/path/to/SKILL.md") + assert "/path/to/SKILL.md" in xml + + def test_to_prompt_xml_with_source_dir(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "test" + skill_dir.mkdir() + s = Skill(name="test", description="d", source_dir=skill_dir) + xml = s.to_prompt_xml() + assert f"{skill_dir}/SKILL.md" in xml + + def test_xml_escaping(self) -> None: + s = Skill(name="test", description="Use bold & stuff") + xml = s.to_prompt_xml() + assert "<b>bold</b>" in xml + assert "&" in xml + + +# --------------------------------------------------------------------------- +# Resource access +# --------------------------------------------------------------------------- + + +class TestSkillResources: + + def test_get_resource_no_source_dir(self) -> None: + s = Skill(name="test", description="d") + assert s.get_resource_path("scripts/run.py") is None + + def test_get_resource_exists(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + scripts = skill_dir / "scripts" + scripts.mkdir(parents=True) + script = scripts / "run.py" + script.write_text("print('hi')") + + s = Skill(name="my-skill", description="d", source_dir=skill_dir) + result = s.get_resource_path("scripts/run.py") + assert result is not None + assert result.name == "run.py" + + def test_get_resource_not_found(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + skill_dir.mkdir() + s = Skill(name="my-skill", description="d", source_dir=skill_dir) + assert s.get_resource_path("nonexistent.py") is None + + def test_get_resource_path_traversal_blocked(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + skill_dir.mkdir() + s = Skill(name="my-skill", description="d", source_dir=skill_dir) + assert s.get_resource_path("../../etc/passwd") is None + + def test_list_resources_no_source_dir(self) -> None: + s = Skill(name="test", description="d") + assert s.list_resources() == [] + + def test_list_resources_all(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + skill_dir.mkdir() + (skill_dir / "SKILL.md").write_text("test") + scripts = skill_dir / "scripts" + scripts.mkdir() + (scripts / "run.py").write_text("code") + + s = Skill(name="my-skill", description="d", source_dir=skill_dir) + files = s.list_resources() + names = [f.name for f in files] + assert "SKILL.md" in names + assert "run.py" in names + + def test_list_resources_subdir(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + scripts = skill_dir / "scripts" + scripts.mkdir(parents=True) + (scripts / "a.py").write_text("a") + (scripts / "b.sh").write_text("b") + (skill_dir / "SKILL.md").write_text("top") + + s = Skill(name="my-skill", description="d", source_dir=skill_dir) + files = s.list_resources(subdir="scripts") + names = [f.name for f in files] + assert "a.py" in names + assert "b.sh" in names + assert "SKILL.md" not in names + + def test_list_resources_missing_subdir(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + skill_dir.mkdir() + s = Skill(name="my-skill", description="d", source_dir=skill_dir) + assert s.list_resources(subdir="nonexistent") == [] + + +# --------------------------------------------------------------------------- +# get_resource (in-memory) +# --------------------------------------------------------------------------- + + +class TestGetResource: + + def test_get_resource_from_memory(self) -> None: + s = Skill( + name="test", + description="d", + resources={"scripts/run.py": b"print('hi')"}, + ) + assert s.get_resource("scripts/run.py") == b"print('hi')" + + def test_get_resource_from_filesystem(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + scripts = skill_dir / "scripts" + scripts.mkdir(parents=True) + (scripts / "run.py").write_bytes(b"code here") + + s = Skill(name="my-skill", description="d", source_dir=skill_dir) + assert s.get_resource("scripts/run.py") == b"code here" + + def test_get_resource_memory_takes_priority(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + scripts = skill_dir / "scripts" + scripts.mkdir(parents=True) + (scripts / "run.py").write_bytes(b"filesystem version") + + s = Skill( + name="my-skill", + description="d", + source_dir=skill_dir, + resources={"scripts/run.py": b"memory version"}, + ) + assert s.get_resource("scripts/run.py") == b"memory version" + + def test_get_resource_not_found(self) -> None: + s = Skill(name="test", description="d") + assert s.get_resource("nonexistent") is None + + def test_get_resource_traversal_blocked(self, tmp_path: Path) -> None: + skill_dir = tmp_path / "my-skill" + skill_dir.mkdir() + s = Skill(name="my-skill", description="d", source_dir=skill_dir) + assert s.get_resource("../../etc/passwd") is None + + +# --------------------------------------------------------------------------- +# list_resources (in-memory, no source_dir) +# --------------------------------------------------------------------------- + + +class TestListResourcesInMemory: + + def test_list_all(self) -> None: + s = Skill( + name="test", + description="d", + resources={ + "scripts/a.py": b"a", + "references/REF.md": b"ref", + "assets/img.png": b"img", + }, + ) + paths = s.list_resources() + names = [str(p) for p in paths] + assert "scripts/a.py" in names + assert "references/REF.md" in names + assert "assets/img.png" in names + + def test_list_subdir(self) -> None: + s = Skill( + name="test", + description="d", + resources={ + "scripts/a.py": b"a", + "scripts/b.sh": b"b", + "references/REF.md": b"ref", + }, + ) + paths = s.list_resources(subdir="scripts") + names = [str(p) for p in paths] + assert "scripts/a.py" in names + assert "scripts/b.sh" in names + assert "references/REF.md" not in names + + def test_list_empty(self) -> None: + s = Skill(name="test", description="d") + assert s.list_resources() == [] + assert s.list_resources(subdir="scripts") == [] + + +# --------------------------------------------------------------------------- +# Portable dict round-trip +# --------------------------------------------------------------------------- + + +class TestPortableDict: + + def test_round_trip(self) -> None: + original = Skill( + name="my-skill", + description="A test skill", + license="MIT", + compatibility="python>=3.11", + allowed_tools=["Bash", "Read"], + metadata={"author": "test"}, + content="# Instructions", + resources={ + "scripts/run.py": b"print('hi')", + "assets/logo.png": b"\x89PNG\r\n", + }, + ) + d = original.to_portable_dict() + + # Resources should be base64-encoded strings + assert isinstance(d["resources"]["scripts/run.py"], str) + + # source_dir should not be in the dict + assert "source_dir" not in d + + # Round-trip + restored = Skill.from_portable_dict(d) + assert restored.name == original.name + assert restored.description == original.description + assert restored.license == original.license + assert restored.compatibility == original.compatibility + assert restored.allowed_tools == original.allowed_tools + assert restored.metadata == original.metadata + assert restored.content == original.content + assert restored.resources == original.resources + assert restored.source_dir is None + + def test_round_trip_no_resources(self) -> None: + original = Skill(name="simple", description="ok") + d = original.to_portable_dict() + restored = Skill.from_portable_dict(d) + assert restored.name == "simple" + assert restored.resources == {} + + +# --------------------------------------------------------------------------- +# save() to disk +# --------------------------------------------------------------------------- + + +class TestSkillSave: + + def test_save_creates_skill_dir(self, tmp_path: Path) -> None: + s = Skill(name="my-skill", description="A test", content="# Body") + result = s.save(tmp_path) + assert result == tmp_path / "my-skill" + assert (result / "SKILL.md").is_file() + + def test_save_writes_frontmatter(self, tmp_path: Path) -> None: + s = Skill( + name="my-skill", + description="A test", + license="MIT", + compatibility="python>=3.11", + allowed_tools=["Bash", "Read"], + metadata={"author": "test"}, + content="# Body", + ) + s.save(tmp_path) + text = (tmp_path / "my-skill" / "SKILL.md").read_text() + assert "name: my-skill" in text + assert "description: A test" in text + assert "license: MIT" in text + assert "compatibility: python>=3.11" in text + assert "allowed-tools: Bash Read" in text + assert "author:" in text + assert "# Body" in text + + def test_save_writes_resources(self, tmp_path: Path) -> None: + s = Skill( + name="my-skill", + description="ok", + resources={ + "scripts/run.py": b"print('hello')", + "assets/data.json": b'{"key": "value"}', + }, + ) + s.save(tmp_path) + assert (tmp_path / "my-skill" / "scripts" / "run.py").read_bytes() == b"print('hello')" + assert (tmp_path / "my-skill" / "assets" / "data.json").read_bytes() == b'{"key": "value"}' + + def test_save_then_load_round_trip(self, tmp_path: Path) -> None: + original = Skill( + name="my-skill", + description="A test skill", + content="# Instructions\nDo stuff.", + resources={"scripts/run.py": b"print('hi')"}, + ) + skill_dir = original.save(tmp_path) + loaded = Skill.load(skill_dir) + assert loaded.name == original.name + assert loaded.description == original.description + assert loaded.content == original.content + assert loaded.resources == original.resources + + +# --------------------------------------------------------------------------- +# Pydantic model_dump / model_validate +# --------------------------------------------------------------------------- + + +class TestPydanticIntegration: + + def test_model_dump_excludes_resources_and_source_dir(self) -> None: + s = Skill( + name="test", + description="ok", + resources={"scripts/a.py": b"code"}, + source_dir=Path("/tmp/test"), + ) + d = s.model_dump() + assert "resources" not in d + assert "source_dir" not in d + assert d["name"] == "test" + + def test_model_validate(self) -> None: + s = Skill.model_validate({"name": "test", "description": "ok"}) + assert s.name == "test" + assert s.resources == {} diff --git a/packages/nvidia_nat_runtime/pyproject.toml b/packages/nvidia_nat_runtime/pyproject.toml new file mode 100644 index 0000000000..81813d713d --- /dev/null +++ b/packages/nvidia_nat_runtime/pyproject.toml @@ -0,0 +1,74 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. +# All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +[build-system] +build-backend = "setuptools.build_meta" +requires = ["setuptools>=64", "setuptools-scm>=8", "setuptools_dynamic_dependencies>=1.0.0"] + + +[tool.setuptools.packages.find] +where = ["src"] +include = ["nat.*"] + + +[tool.setuptools_scm] +git_describe_command = "git describe --long --first-parent" +root = "../.." + + +[project] +name = "nvidia-nat-runtime" +dynamic = ["version", "dependencies", "optional-dependencies"] +requires-python = ">=3.11,<3.14" +description = "Subpackage for runtime components in NVIDIA NeMo Agent Toolkit" +readme = "src/nat/meta/pypi.md" +keywords = ["ai", "agents", "runtime"] +license = { text = "Apache-2.0" } +authors = [{ name = "NVIDIA Corporation" }] +maintainers = [{ name = "NVIDIA Corporation" }] +classifiers = [ + "Programming Language :: Python", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", +] + +[project.urls] +documentation = "https://docs.nvidia.com/nemo/agent-toolkit/latest/" +source = "https://github.com/NVIDIA/NeMo-Agent-Toolkit" + +[tool.setuptools_dynamic_dependencies] +dependencies = [ + # Keep package version constraints as open as possible to avoid conflicts with other packages. Always define a minimum + # version when adding a new package. If unsure, default to using `~=` instead of `==`. Does not apply to nvidia-nat packages. + # Keep sorted!!! + "nvidia-nat-core == {version}", + "openai~=1.106", +] + +[tool.setuptools_dynamic_dependencies.optional-dependencies] +test = [ + "nvidia-nat-test == {version}", +] + +[tool.uv] +build-constraint-dependencies = ["setuptools>=64", "setuptools-scm>=8", "setuptools_dynamic_dependencies>=1.0.0"] +managed = true +config-settings = { editable_mode = "compat" } + +[tool.uv.sources] +nvidia-nat-core = { path = "../nvidia_nat_core", editable = true } +nvidia-nat-test = { path = "../nvidia_nat_test", editable = true } diff --git a/packages/nvidia_nat_runtime/src/nat/meta/pypi.md b/packages/nvidia_nat_runtime/src/nat/meta/pypi.md new file mode 100644 index 0000000000..8d19be71a7 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/meta/pypi.md @@ -0,0 +1,23 @@ + + +![NVIDIA NeMo Agent Toolkit](https://media.githubusercontent.com/media/NVIDIA/NeMo-Agent-Toolkit/refs/heads/main/docs/source/_static/banner.png "NeMo Agent Toolkit banner image") + +# NVIDIA NeMo Agent Toolkit Subpackage +This is a subpackage for runtime components in NVIDIA NeMo Agent Toolkit. + +For more information about NVIDIA NeMo Agent Toolkit, please visit the [NeMo Agent Toolkit package](https://pypi.org/project/nvidia-nat/). diff --git a/packages/nvidia_nat_runtime/src/nat/plugins/runtime/llm.py b/packages/nvidia_nat_runtime/src/nat/plugins/runtime/llm.py new file mode 100644 index 0000000000..2c484538d6 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/plugins/runtime/llm.py @@ -0,0 +1,511 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Runtime LLM clients for raw OpenAI SDK usage. + +This module wires the OpenAI SDK into the NVIDIA NeMo Agent Toolkit runtime +so workflows can call models directly while still emitting intermediate step +events and honoring toolkit configuration defaults. +""" + +from __future__ import annotations + +import logging +import os +from collections.abc import AsyncGenerator +from collections.abc import Mapping +from pathlib import Path +from typing import TYPE_CHECKING +from typing import Any +from typing import TypeAlias +from typing import TypeVar +from typing import cast +from uuid import uuid4 + +from openai import AsyncOpenAI +from openai import AsyncStream +from openai.types.chat import ChatCompletion +from openai.types.chat import ChatCompletionChunk +from openai.types.chat import ChatCompletionMessageParam +from openai.types.chat import CompletionCreateParams +from openai.types.responses import Response +from openai.types.responses import ResponseCreateParams +from openai.types.responses import ResponseInputParam +from openai.types.responses import ResponseStreamEvent +from pydantic import BaseModel + +from nat.builder.builder import Builder +from nat.builder.context import Context +from nat.builder.framework_enum import LLMFrameworkEnum +from nat.cli.register_workflow import register_llm_client +from nat.data_models.common import get_secret_value +from nat.data_models.intermediate_step import IntermediateStepPayload +from nat.data_models.intermediate_step import IntermediateStepType +from nat.data_models.intermediate_step import StreamEventData +from nat.data_models.retry_mixin import RetryMixin +from nat.llm.dynamo_llm import DynamoModelConfig +from nat.llm.dynamo_llm import create_httpx_client_with_dynamo_hooks +from nat.llm.litellm_llm import LiteLlmModelConfig +from nat.llm.nim_llm import NIMModelConfig +from nat.llm.openai_llm import OpenAIModelConfig +from nat.llm.utils.hooks import create_metadata_injection_client +from nat.profiler.prediction_trie import load_prediction_trie +from nat.profiler.prediction_trie.trie_lookup import PredictionTrieLookup +from nat.utils.exception_handlers.automatic_retries import patch_with_retry + +if TYPE_CHECKING: + import httpx + +logger = logging.getLogger(__name__) + +ClientT = TypeVar("ClientT") +ChatMessages: TypeAlias = list[ChatCompletionMessageParam] +LLMInput: TypeAlias = ChatMessages | ResponseInputParam +StreamedChunk: TypeAlias = ChatCompletionChunk | ResponseStreamEvent +StreamPayload: TypeAlias = StreamedChunk | str +ChatCompletionStream: TypeAlias = AsyncGenerator[ChatCompletionChunk, None] +ResponseStream: TypeAlias = AsyncGenerator[ResponseStreamEvent, None] +ChatCompletionOutput: TypeAlias = ChatCompletion | ChatCompletionStream +ResponseOutput: TypeAlias = Response | ResponseStream +LLMOutputPayload: TypeAlias = ChatCompletion | Response | str | list[ChatCompletionChunk] | list[ResponseStreamEvent] + + +def _apply_retry(client: ClientT, llm_config: BaseModel) -> ClientT: + """Wrap a runtime client with retry handling when configured. + + Args: + client: Runtime client instance to wrap. + llm_config: Configuration object that may include retry settings. + + Returns: + The original client when retries are disabled, otherwise a retry-enabled + wrapper. + """ + if isinstance(llm_config, RetryMixin): + return patch_with_retry( + client, + retries=llm_config.num_retries, + retry_codes=llm_config.retry_on_status_codes, + retry_on_messages=llm_config.retry_on_errors, + ) + return client + + +def _build_default_params(llm_config: BaseModel, extra_exclude: set[str] | None = None) -> dict[str, object]: + """Build OpenAI SDK parameters from a model config. + + Args: + llm_config: Configuration object for the model. + extra_exclude: Optional set of config field names to omit. + + Returns: + Dictionary of parameters ready for OpenAI SDK calls, filtered to exclude + non-API fields and unset values. + """ + exclude = {"type", "api_type", "thinking", "api_key", "base_url", "model_name", "max_retries"} + if extra_exclude: + exclude |= extra_exclude + params = llm_config.model_dump( + exclude=exclude, + by_alias=True, + exclude_none=True, + exclude_unset=True, + ) + params.pop("stream_usage", None) + return params + + +def _ensure_stream_usage(params: dict[str, object], stream: bool) -> None: + """Ensure usage metadata is requested for streaming responses. + + Args: + params: Parameter dictionary that will be sent to the OpenAI SDK. + stream: Whether streaming is enabled for the call. + """ + if not stream: + return + stream_options_value = params.get("stream_options") + stream_options = dict(stream_options_value) if isinstance(stream_options_value, Mapping) else {} + stream_options["include_usage"] = True + params["stream_options"] = stream_options + + +def _extract_text_from_chunk(chunk: StreamedChunk | dict[str, object]) -> str | None: + """Extract text content from an OpenAI SDK streaming chunk. + + Args: + chunk: Streaming chunk object or dictionary from the OpenAI SDK. + + Returns: + The extracted text when available, otherwise ``None``. + """ + if isinstance(chunk, dict): + choices = chunk.get("choices") + if isinstance(choices, list) and choices: + choice = choices[0] + delta = choice.get("delta") if isinstance(choice, dict) else None + content = delta.get("content") if isinstance(delta, dict) else None + if isinstance(content, str): + return content + output_text = chunk.get("output_text") + if isinstance(output_text, str): + return output_text + return None + + choices = getattr(chunk, "choices", None) + if choices: + delta = getattr(choices[0], "delta", None) + content = getattr(delta, "content", None) if delta is not None else None + if isinstance(content, str): + return content + + output_text = getattr(chunk, "output_text", None) + if isinstance(output_text, str): + return output_text + + return None + + +class RuntimeOpenAIClient: + """Wrapper around the OpenAI SDK client with toolkit defaults applied. + + The wrapper applies model defaults, emits intermediate step events, and + normalizes streaming usage metadata for NVIDIA NeMo Agent Toolkit workflows. + """ + + def __init__(self, client: AsyncOpenAI, *, model_name: str, default_params: dict[str, object]) -> None: + """Initialize the runtime client wrapper. + + Args: + client: Underlying OpenAI SDK client. + model_name: Default model identifier to use when unspecified. + default_params: Default request parameters applied to calls. + """ + self._client = client + self._model_name = model_name + self._default_params = dict(default_params) + + @property + def client(self) -> AsyncOpenAI: + """Return the underlying OpenAI SDK client.""" + return self._client + + def _build_chat_params(self, **kwargs: object) -> CompletionCreateParams: + """Merge default parameters with chat completion overrides.""" + params = {**self._default_params, **kwargs} + params.setdefault("model", self._model_name) + stream = bool(params.get("stream")) + _ensure_stream_usage(params, stream) + return cast(CompletionCreateParams, params) + + def _build_response_params(self, **kwargs: object) -> ResponseCreateParams: + """Merge default parameters with response overrides.""" + params = {**self._default_params, **kwargs} + params.setdefault("model", self._model_name) + stream = bool(params.get("stream")) + _ensure_stream_usage(params, stream) + return cast(ResponseCreateParams, params) + + def _emit_llm_step(self, + *, + event_type: IntermediateStepType, + step_id: str, + input_data: LLMInput, + output_data: LLMOutputPayload | None) -> None: + """Emit an LLM lifecycle step to the intermediate step manager. + + Args: + event_type: Step event type to emit. + step_id: Unique identifier for this LLM invocation. + input_data: Input data sent to the LLM call. + output_data: Optional response payload. + """ + payload = IntermediateStepPayload( + event_type=event_type, + framework=LLMFrameworkEnum.RUNTIME, + name=self._model_name, + UUID=step_id, + data=StreamEventData(input=input_data, output=output_data), + ) + Context.get().intermediate_step_manager.push_intermediate_step(payload) + + def _emit_llm_chunk(self, *, step_id: str, input_data: LLMInput, chunk: StreamPayload) -> None: + """Emit a streaming token/chunk step. + + Args: + step_id: Unique identifier for this LLM invocation. + input_data: Input data sent to the LLM call. + chunk: Streaming chunk payload. + """ + payload = IntermediateStepPayload( + event_type=IntermediateStepType.LLM_NEW_TOKEN, + framework=LLMFrameworkEnum.RUNTIME, + name=self._model_name, + UUID=step_id, + data=StreamEventData(input=input_data, chunk=chunk), + ) + Context.get().intermediate_step_manager.push_intermediate_step(payload) + + async def chat_completions(self, messages: ChatMessages, **kwargs: object) -> ChatCompletionOutput: + """Create a chat completion using the OpenAI SDK. + + This method emits start/end intermediate steps and, when streaming, + emits token events for each chunk. + + Args: + messages: Chat messages in OpenAI SDK format. + kwargs: Additional OpenAI SDK parameters. + + Returns: + OpenAI SDK response object, or an async generator when streaming. + """ + params = self._build_chat_params(**kwargs) + step_id = str(uuid4()) + self._emit_llm_step(event_type=IntermediateStepType.LLM_START, + step_id=step_id, + input_data=messages, + output_data=None) + if params.get("stream"): + stream = cast(AsyncStream[ChatCompletionChunk], + await self._client.chat.completions.create(messages=messages, **cast(dict[str, Any], params))) + + async def _stream() -> ChatCompletionStream: + chunks: list[ChatCompletionChunk] = [] + text_parts: list[str] = [] + try: + async for chunk in stream: + chunks.append(chunk) + text = _extract_text_from_chunk(chunk) + if text: + text_parts.append(text) + chunk_payload = text if text is not None else chunk + self._emit_llm_chunk(step_id=step_id, input_data=messages, chunk=chunk_payload) + yield chunk + finally: + output_data: LLMOutputPayload = "".join(text_parts) if text_parts else chunks + self._emit_llm_step(event_type=IntermediateStepType.LLM_END, + step_id=step_id, + input_data=messages, + output_data=output_data) + + return _stream() + + response = cast(ChatCompletion, + await self._client.chat.completions.create(messages=messages, **cast(dict[str, Any], params))) + self._emit_llm_step(event_type=IntermediateStepType.LLM_END, + step_id=step_id, + input_data=messages, + output_data=response) + return response + + async def responses(self, input_data: ResponseInputParam, **kwargs: object) -> ResponseOutput: + """Create a response using the OpenAI SDK. + + This method emits start/end intermediate steps and, when streaming, + emits token events for each chunk. + + Args: + input_data: Input payload for the Responses API. + **kwargs: Additional OpenAI SDK parameters. + + Returns: + OpenAI SDK response object, or an async generator when streaming. + """ + params = self._build_response_params(**kwargs) + step_id = str(uuid4()) + self._emit_llm_step(event_type=IntermediateStepType.LLM_START, + step_id=step_id, + input_data=input_data, + output_data=None) + if params.get("stream"): + stream = cast(AsyncStream[ResponseStreamEvent], + await self._client.responses.create(input=input_data, **cast(dict[str, Any], params))) + + async def _stream() -> ResponseStream: + chunks: list[ResponseStreamEvent] = [] + text_parts: list[str] = [] + try: + async for chunk in stream: + chunks.append(chunk) + text = _extract_text_from_chunk(chunk) + if text: + text_parts.append(text) + chunk_payload = text if text is not None else chunk + self._emit_llm_chunk(step_id=step_id, input_data=input_data, chunk=chunk_payload) + yield chunk + finally: + output_data: LLMOutputPayload = "".join(text_parts) if text_parts else chunks + self._emit_llm_step(event_type=IntermediateStepType.LLM_END, + step_id=step_id, + input_data=input_data, + output_data=output_data) + + return _stream() + + response = cast(Response, await self._client.responses.create(input=input_data, **cast(dict[str, Any], params))) + self._emit_llm_step(event_type=IntermediateStepType.LLM_END, + step_id=step_id, + input_data=input_data, + output_data=response) + return response + + +def _build_openai_client(*, api_key: str | None, base_url: str | None, + http_async_client: httpx.AsyncClient) -> AsyncOpenAI: + """Construct an OpenAI SDK client with the provided HTTP transport. + + Args: + api_key: API key for the target endpoint. + base_url: Optional base URL override for OpenAI-compatible endpoints. + http_async_client: Async HTTP client used by the SDK. + + Returns: + Configured `AsyncOpenAI` client instance. + """ + return AsyncOpenAI( + api_key=api_key, + base_url=base_url, + http_client=http_async_client, + ) + + +@register_llm_client(config_type=OpenAIModelConfig, wrapper_type=LLMFrameworkEnum.RUNTIME) +async def openai_runtime(llm_config: OpenAIModelConfig, _builder: Builder) -> AsyncGenerator[RuntimeOpenAIClient, None]: + """Build a runtime OpenAI SDK client for OpenAI-hosted models. + + Args: + llm_config: OpenAI model configuration. + _builder: Builder instance (unused). + + Yields: + Configured runtime client for OpenAI-hosted models. + """ + api_key = get_secret_value(llm_config.api_key) or os.getenv("OPENAI_API_KEY") + async with create_metadata_injection_client() as http_async_client: + oai_client = _build_openai_client( + api_key=api_key, + base_url=llm_config.base_url, + http_async_client=http_async_client, + ) + runtime_client = RuntimeOpenAIClient( + oai_client, + model_name=llm_config.model_name, + default_params=_build_default_params(llm_config), + ) + yield _apply_retry(runtime_client, llm_config) + + +@register_llm_client(config_type=NIMModelConfig, wrapper_type=LLMFrameworkEnum.RUNTIME) +async def nim_runtime(llm_config: NIMModelConfig, _builder: Builder) -> AsyncGenerator[RuntimeOpenAIClient, None]: + """Build a runtime OpenAI SDK client for NVIDIA NIM endpoints. + + Args: + llm_config: NIM model configuration. + _builder: Builder instance (unused). + + Yields: + Configured runtime client for NVIDIA NIM endpoints. + """ + base_url = llm_config.base_url or "https://integrate.api.nvidia.com/v1" + api_key = get_secret_value(llm_config.api_key) or os.getenv("NVIDIA_API_KEY") + if llm_config.base_url and llm_config.base_url.strip() and api_key is None: + api_key = "dummy-api-key" + + async with create_metadata_injection_client() as http_async_client: + oai_client = _build_openai_client( + api_key=api_key, + base_url=base_url, + http_async_client=http_async_client, + ) + runtime_client = RuntimeOpenAIClient( + oai_client, + model_name=llm_config.model_name, + default_params=_build_default_params(llm_config), + ) + yield _apply_retry(runtime_client, llm_config) + + +@register_llm_client(config_type=DynamoModelConfig, wrapper_type=LLMFrameworkEnum.RUNTIME) +async def dynamo_runtime(llm_config: DynamoModelConfig, _builder: Builder) -> AsyncGenerator[RuntimeOpenAIClient, None]: + """Build a runtime OpenAI SDK client for Dynamo endpoints. + + Args: + llm_config: Dynamo model configuration. + _builder: Builder instance (unused). + + Yields: + Configured runtime client for Dynamo endpoints. + """ + api_key = get_secret_value(llm_config.api_key) or os.getenv("OPENAI_API_KEY") + prediction_lookup: PredictionTrieLookup | None = None + if llm_config.prediction_trie_path: + try: + trie_path = Path(llm_config.prediction_trie_path) + trie = load_prediction_trie(trie_path) + prediction_lookup = PredictionTrieLookup(trie) + except FileNotFoundError: + logger.warning("Prediction trie file not found: %s", llm_config.prediction_trie_path) + except Exception as exc: + logger.warning("Failed to load prediction trie: %s", exc) + + http_async_client = create_httpx_client_with_dynamo_hooks( + prefix_template=llm_config.prefix_template, + total_requests=llm_config.prefix_total_requests, + osl=llm_config.prefix_osl, + iat=llm_config.prefix_iat, + timeout=llm_config.request_timeout, + prediction_lookup=prediction_lookup, + ) + async with http_async_client: + oai_client = _build_openai_client( + api_key=api_key, + base_url=llm_config.base_url, + http_async_client=http_async_client, + ) + runtime_client = RuntimeOpenAIClient( + oai_client, + model_name=llm_config.model_name, + default_params=_build_default_params( + llm_config, + extra_exclude=set(DynamoModelConfig.get_dynamo_field_names()), + ), + ) + yield _apply_retry(runtime_client, llm_config) + + +@register_llm_client(config_type=LiteLlmModelConfig, wrapper_type=LLMFrameworkEnum.RUNTIME) +async def litellm_runtime(llm_config: LiteLlmModelConfig, + _builder: Builder) -> AsyncGenerator[RuntimeOpenAIClient, None]: + """Build a runtime OpenAI SDK client for LiteLLM endpoints. + + Args: + llm_config: LiteLLM model configuration. + _builder: Builder instance (unused). + + Yields: + Configured runtime client for LiteLLM endpoints. + """ + api_key = get_secret_value(llm_config.api_key) or os.getenv("OPENAI_API_KEY") + async with create_metadata_injection_client() as http_async_client: + oai_client = _build_openai_client( + api_key=api_key, + base_url=llm_config.base_url, + http_async_client=http_async_client, + ) + runtime_client = RuntimeOpenAIClient( + oai_client, + model_name=llm_config.model_name, + default_params=_build_default_params(llm_config), + ) + yield _apply_retry(runtime_client, llm_config) diff --git a/packages/nvidia_nat_runtime/src/nat/plugins/runtime/register.py b/packages/nvidia_nat_runtime/src/nat/plugins/runtime/register.py new file mode 100644 index 0000000000..867552edbc --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/plugins/runtime/register.py @@ -0,0 +1,18 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from . import llm # noqa: F401 +from . import tool_calling_agent # noqa: F401 +from . import tool_wrapper # noqa: F401 diff --git a/packages/nvidia_nat_runtime/src/nat/plugins/runtime/tool_calling_agent.py b/packages/nvidia_nat_runtime/src/nat/plugins/runtime/tool_calling_agent.py new file mode 100644 index 0000000000..75bb984b2f --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/plugins/runtime/tool_calling_agent.py @@ -0,0 +1,186 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Runtime tool-calling agent implementation.""" + +import json +import logging + +from pydantic import Field + +from nat.builder.builder import Builder +from nat.builder.framework_enum import LLMFrameworkEnum +from nat.builder.function_info import FunctionInfo +from nat.cli.register_workflow import register_function +from nat.data_models.agent import AgentBaseConfig +from nat.data_models.api_server import ChatRequest +from nat.data_models.api_server import ChatRequestOrMessage +from nat.data_models.component_ref import FunctionGroupRef +from nat.data_models.component_ref import FunctionRef +from nat.sdk.agent.agent import Agent +from nat.sdk.agent.state import AgentStatus +from nat.sdk.conversation.runner import ConversationRunner +from nat.sdk.conversation.state import ConversationState +from nat.sdk.event.event import MessageEvent +from nat.sdk.event.event import ObservationEvent +from nat.sdk.llm.builder_client import BuilderLLMClient +from nat.sdk.llm.message import Message +from nat.sdk.llm.message import ToolCall +from nat.sdk.tool.tool import Tool +from nat.utils.type_converter import GlobalTypeConverter + +logger = logging.getLogger(__name__) + + +class RuntimeToolCallingAgentConfig(AgentBaseConfig, name="runtime_tool_calling_agent"): + """Configuration for the runtime tool-calling agent.""" + + description: str = Field(default="Runtime Tool Calling Agent Workflow", + description="Description of this functions use.") + tool_names: list[FunctionRef | FunctionGroupRef] = Field( + default_factory=list, + description="The list of tools to provide to the tool calling agent.", + ) + handle_tool_errors: bool = Field( + default=True, + description="Specify ability to handle tool calling errors.", + ) + max_iterations: int = Field( + default=15, + description="Number of tool calls before stopping the tool calling agent.", + ) + max_history: int = Field( + default=15, + description="Maximum number of messages to keep in the conversation history.", + ) + system_prompt: str = Field( + default="You are a helpful assistant that can use tools to help the user. " + \ + "You will be given a task and you will need to use the tools to " + \ + "complete the task. Only attempt to use the tools. Do not make up " + \ + "information. Only use the tools to answer the user's question.", + description="Provides the system prompt to use with the agent.", + ) + additional_instructions: str | None = Field( + default=None, + description="Additional instructions appended to the system prompt.", + ) + return_direct: list[FunctionRef] | None = Field( + default=None, + description="List of tool names that should return responses directly without LLM processing.", + ) + + +def _build_system_prompt(config: RuntimeToolCallingAgentConfig) -> str | None: + """Create a tool-calling agent system prompt from config.""" + prompt_parts = [] + for prompt in (config.system_prompt, config.additional_instructions): + if prompt: + prompt_parts.append(prompt) + if prompt_parts: + return " ".join(prompt_parts) + return None + + +def _serialize_output(output: object) -> str: + """Serialize tool output to a string for the LLM.""" + if output is None: + return "" + if isinstance(output, str): + return output + try: + return json.dumps(output, default=str) + except TypeError: + return str(output) + + +def _convert_chat_request(chat_request: ChatRequest, system_prompt: str | None) -> list[Message]: + """Convert a ChatRequest into SDK Message objects.""" + messages: list[Message] = [] + if system_prompt: + messages.append(Message(role="system", content=system_prompt)) + for msg in chat_request.messages: + d = msg.model_dump(exclude_none=True) + tool_calls = [] + for tc in d.get("tool_calls", []): + arguments = tc["function"]["arguments"] + if isinstance(arguments, str): + arguments = json.loads(arguments) + tool_calls.append(ToolCall( + id=tc["id"], + name=tc["function"]["name"], + arguments=arguments, + )) + messages.append( + Message( + role=d["role"], + content=d.get("content", ""), + tool_calls=tool_calls if tool_calls else [], + tool_call_id=d.get("tool_call_id"), + )) + return messages + + +@register_function(config_type=RuntimeToolCallingAgentConfig, framework_wrappers=[LLMFrameworkEnum.RUNTIME]) +async def runtime_tool_calling_agent_workflow(config: RuntimeToolCallingAgentConfig, builder: Builder): + """Build a runtime tool-calling agent workflow.""" + + from nat.plugins.runtime.llm import RuntimeOpenAIClient + + runtime_llm = await builder.get_llm(config.llm_name, wrapper_type=LLMFrameworkEnum.RUNTIME) + if not isinstance(runtime_llm, RuntimeOpenAIClient): + raise TypeError("Runtime tool-calling agent requires a RuntimeOpenAIClient LLM wrapper.") + + client = BuilderLLMClient(runtime_llm) + + tools = await builder.get_tools(tool_names=config.tool_names, wrapper_type=LLMFrameworkEnum.RUNTIME) + if not tools: + raise ValueError(f"No tools specified for runtime tool-calling agent '{config.llm_name}'") + tools_by_name: dict[str, Tool] = {tool.name: tool for tool in tools} + + return_direct_names: set[str] = set() + if config.return_direct: + rd_tools = await builder.get_tools(tool_names=config.return_direct, wrapper_type=LLMFrameworkEnum.RUNTIME) + return_direct_names = {t.name for t in rd_tools} if rd_tools else set() + + system_prompt = _build_system_prompt(config) + + async def _response_fn(chat_request_or_message: ChatRequestOrMessage) -> str: + """Execute the runtime tool-calling agent and return its response.""" + chat_request = GlobalTypeConverter.get().convert(chat_request_or_message, to_type=ChatRequest) + initial_messages = _convert_chat_request(chat_request, system_prompt) + + agent = Agent(tools=list(tools_by_name.values()), max_iterations=config.max_iterations) + state = ConversationState() + state.agent_state.status = AgentStatus.RUNNING + + runner = ConversationRunner( + agent=agent, + client=client, + state=state, + tools=tools_by_name, + return_direct_tools=return_direct_names, + handle_tool_errors=config.handle_tool_errors, + max_history=config.max_history, + initial_messages=initial_messages, + ) + + last_event = await runner.run_until_done() + + if isinstance(last_event, ObservationEvent): + return _serialize_output(last_event.output) + if isinstance(last_event, MessageEvent): + return last_event.content + return "" + + yield FunctionInfo.from_fn(_response_fn, description=config.description) diff --git a/packages/nvidia_nat_runtime/src/nat/plugins/runtime/tool_wrapper.py b/packages/nvidia_nat_runtime/src/nat/plugins/runtime/tool_wrapper.py new file mode 100644 index 0000000000..3fd77a6ed1 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/plugins/runtime/tool_wrapper.py @@ -0,0 +1,39 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Runtime tool wrapper — produces SDK Tool instances for the Builder framework.""" + +from nat.builder.builder import Builder +from nat.builder.framework_enum import LLMFrameworkEnum +from nat.builder.function import Function +from nat.cli.register_workflow import register_tool_wrapper +from nat.sdk.tool.tool import Tool + +# Backward-compatible alias so existing imports continue to work. +RuntimeToolWrapper = Tool + + +@register_tool_wrapper(wrapper_type=LLMFrameworkEnum.RUNTIME) +def runtime_tool_wrapper(name: str, fn: Function, _builder: Builder) -> Tool: + """Create a runtime tool wrapper for a toolkit function. + + Args: + name: Tool name exposed to the OpenAI-compatible interface. + fn: Toolkit `Function` to wrap. + _builder: Builder instance (unused). + + Returns: + Configured `Tool` instance. + """ + return Tool.from_function(fn) diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/__init__.py b/packages/nvidia_nat_runtime/src/nat/sdk/__init__.py new file mode 100644 index 0000000000..059f70935c --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/__init__.py @@ -0,0 +1,115 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""NAT SDK — a self-contained toolkit for building agents. + +Usage:: + + from nat.sdk import Agent, Conversation, Tool, tool + + @tool(description="Add two numbers") + def add(a: int, b: int) -> int: + return a + b + + agent = Agent(tools=[add], system_prompt="You are a helpful assistant.") + conv = Conversation(agent=agent, client=my_llm_client) + response = await conv.send_message("What is 2 + 3?") +""" + +# Agent +# Skills +from nat.data_models.skill import Skill + +# Workspace +from nat.data_models.workspace import ActionRequest +from nat.data_models.workspace import ActionResult +from nat.data_models.workspace import ActionStatus +from nat.sdk.agent.agent import Agent +from nat.sdk.agent.state import AgentState +from nat.sdk.agent.state import AgentStatus + +# Conversation +from nat.sdk.conversation.conversation import Conversation +from nat.sdk.conversation.state import ConversationState +from nat.sdk.conversation.state import ConversationStatus +from nat.sdk.conversation.state import UsageStats + +# Events +from nat.sdk.event.event import ActionEvent +from nat.sdk.event.event import ErrorEvent +from nat.sdk.event.event import Event +from nat.sdk.event.event import EventSource +from nat.sdk.event.event import MessageEvent +from nat.sdk.event.event import ObservationEvent +from nat.sdk.event.event import SystemPromptEvent +from nat.sdk.event.log import EventLog + +# LLM +from nat.sdk.llm.client import LLMClient +from nat.sdk.llm.message import LLMResponse +from nat.sdk.llm.message import Message +from nat.sdk.llm.message import TokenUsage +from nat.sdk.llm.message import ToolCall + +# Tools +from nat.sdk.tool.result import ToolResult +from nat.sdk.tool.tool import Tool +from nat.sdk.tool.tool import tool +from nat.workspace.types import WorkspaceBase + +__all__ = [ + # Agent + "Agent", + "AgentState", + "AgentStatus", # Conversation + "Conversation", + "ConversationState", + "ConversationStatus", + "UsageStats", # Events + "ActionEvent", + "ErrorEvent", + "Event", + "EventLog", + "EventSource", + "MessageEvent", + "ObservationEvent", + "SystemPromptEvent", # LLM + "BuilderLLMClient", + "LLMClient", + "LLMResponse", + "Message", + "TokenUsage", + "ToolCall", + "create_llm_client", # Skills + "Skill", # Tools + "Tool", + "ToolResult", + "tool", # Workspace + "ActionRequest", + "ActionResult", + "ActionStatus", + "WorkspaceBase", +] + + +def __getattr__(name: str): # noqa: ANN001 + if name == "BuilderLLMClient": + from nat.sdk.llm.builder_client import BuilderLLMClient + + return BuilderLLMClient + if name == "create_llm_client": + from nat.sdk.llm.builder_client import create_llm_client + + return create_llm_client + raise AttributeError(f"module {__name__!r} has no attribute {name!r}") diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/agent/__init__.py b/packages/nvidia_nat_runtime/src/nat/sdk/agent/__init__.py new file mode 100644 index 0000000000..eee3efe946 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/agent/__init__.py @@ -0,0 +1,24 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from nat.sdk.agent.agent import Agent +from nat.sdk.agent.state import AgentState +from nat.sdk.agent.state import AgentStatus + +__all__ = [ + "Agent", + "AgentState", + "AgentStatus", +] diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/agent/agent.py b/packages/nvidia_nat_runtime/src/nat/sdk/agent/agent.py new file mode 100644 index 0000000000..83b569ad83 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/agent/agent.py @@ -0,0 +1,65 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from pathlib import Path +from typing import Any + +from pydantic import BaseModel +from pydantic import ConfigDict +from pydantic import Field + +from nat.data_models.skill import Skill +from nat.sdk.tool.tool import Tool +from nat.workspace.types import WorkspaceBase + + +class Agent(BaseModel): + """Immutable agent configuration. + + An agent defines *what* an AI assistant is (tools, skills, + system prompt, workspace) but carries no runtime state. Pair with a + :class:`~nat.sdk.conversation.conversation.Conversation` to execute. + """ + + model_config = ConfigDict(frozen=True, extra="forbid", arbitrary_types_allowed=True) + + # Capabilities + tools: list[Tool] = Field(default_factory=list) + skills: list[Skill] = Field(default_factory=list) + skill_discovery_dirs: tuple[str | Path, ...] = Field(default=()) + workspace: WorkspaceBase | None = Field(default=None) + + # System prompt + system_prompt: str = "" + system_prompt_kwargs: dict[str, Any] = Field(default_factory=dict) + + # Execution limits + max_iterations: int = 50 + + def render_system_prompt(self, **extra_kwargs: Any) -> str: + """Render the system prompt template with kwargs. + + Merges ``system_prompt_kwargs`` with any additional keyword + arguments provided at call time. + """ + if not self.system_prompt: + return "" + kwargs = {**self.system_prompt_kwargs, **extra_kwargs} + if kwargs: + try: + return self.system_prompt.format(**kwargs) + except KeyError: + return self.system_prompt + return self.system_prompt diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/agent/state.py b/packages/nvidia_nat_runtime/src/nat/sdk/agent/state.py new file mode 100644 index 0000000000..361619fe5b --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/agent/state.py @@ -0,0 +1,52 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from enum import StrEnum +from typing import Any + +from pydantic import BaseModel +from pydantic import ConfigDict +from pydantic import Field + + +class AgentStatus(StrEnum): + """Runtime status of an agent within a conversation.""" + + IDLE = "idle" + RUNNING = "running" + FINISHED = "finished" + ERROR = "error" + MAX_ITERATIONS = "max_iterations" + + +class AgentState(BaseModel): + """Mutable runtime state for a single agent invocation. + + This is intentionally separated from :class:`~nat.sdk.agent.agent.Agent` + (which is frozen/immutable configuration) so that the same agent + definition can be reused across multiple conversations. + """ + + model_config = ConfigDict(extra="allow") + + iteration: int = Field(default=0) + status: AgentStatus = Field(default=AgentStatus.IDLE) + metadata: dict[str, Any] = Field(default_factory=dict) + + def reset(self) -> None: + """Reset state for a new run.""" + self.iteration = 0 + self.status = AgentStatus.IDLE + self.metadata.clear() diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/conversation/__init__.py b/packages/nvidia_nat_runtime/src/nat/sdk/conversation/__init__.py new file mode 100644 index 0000000000..431ffce9f0 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/conversation/__init__.py @@ -0,0 +1,28 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from nat.sdk.conversation.conversation import Conversation +from nat.sdk.conversation.runner import EventCallback +from nat.sdk.conversation.state import ConversationState +from nat.sdk.conversation.state import ConversationStatus +from nat.sdk.conversation.state import UsageStats + +__all__ = [ + "Conversation", + "ConversationState", + "ConversationStatus", + "EventCallback", + "UsageStats", +] diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/conversation/conversation.py b/packages/nvidia_nat_runtime/src/nat/sdk/conversation/conversation.py new file mode 100644 index 0000000000..0577b3325d --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/conversation/conversation.py @@ -0,0 +1,360 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +import logging +from typing import Any + +from nat.data_models.skill import Skill +from nat.sdk.agent.agent import Agent +from nat.sdk.agent.state import AgentStatus +from nat.sdk.conversation.runner import ConversationRunner +from nat.sdk.conversation.runner import EventCallback +from nat.sdk.conversation.state import ConversationState +from nat.sdk.conversation.state import ConversationStatus +from nat.sdk.event.event import Event +from nat.sdk.event.event import EventSource +from nat.sdk.event.event import MessageEvent +from nat.sdk.event.event import SystemPromptEvent +from nat.sdk.llm.client import LLMClient +from nat.sdk.llm.message import Message +from nat.sdk.skill.tool import build_read_skill_tool +from nat.sdk.tool.tool import Tool +from nat.workspace.types import WorkspaceBase + +logger = logging.getLogger(__name__) + + +class Conversation: + """Main user-facing orchestrator that ties an Agent to runtime state. + + Usage:: + + agent = Agent(tools=[...], system_prompt="You are...") + conv = Conversation(agent=agent, client=my_client) + response = await conv.send_message("Hello!") + + Workspace actions should be added as tools via + ``Tool.from_function_group_config(WorkspaceActionsConfig())`` rather + than passing a workspace directly. + """ + + def __init__( + self, + agent: Agent, + *, + client: LLMClient, + workspace: WorkspaceBase | None = None, + state: ConversationState | None = None, + on_event: EventCallback | None = None, + ) -> None: + self._agent = agent + self._client = client + # Explicit workspace overrides agent.workspace + self._workspace = workspace if workspace is not None else agent.workspace + self._state = state or ConversationState() + self._on_event = on_event + self._initialized = False + + # Index tools by name + self._tools: dict[str, Tool] = {t.name: t for t in agent.tools} + + # Index skills by name + self._skills: dict[str, Skill] = {s.name: s for s in agent.skills} + + # -- Properties -- + + @property + def agent(self) -> Agent: + return self._agent + + @property + def state(self) -> ConversationState: + return self._state + + @property + def tools(self) -> dict[str, Tool]: + return self._tools + + @property + def skills(self) -> dict[str, Skill]: + return self._skills + + # -- Lifecycle -- + + async def initialize(self) -> None: + """Initialize the conversation: discover skills, emit system prompt.""" + if self._initialized: + return + + # Discover skills from configured directories and workspace + await self._discover_skills() + + # Wire skill-activation tool when skills are available + if self._skills: + self._tools["read_skill"] = build_read_skill_tool( + skills=self._skills, + state=self._state, + emit_fn=self._emit_event, + build_skills_context=self._build_skills_section, + ) + + # Emit system prompt event + system_prompt = self._build_system_prompt() + if system_prompt: + self._emit_event(SystemPromptEvent(content=system_prompt)) + + self._initialized = True + + async def close(self) -> None: + """Mark conversation as completed.""" + self._state.status = ConversationStatus.COMPLETED + + async def __aenter__(self) -> Conversation: + await self.initialize() + return self + + async def __aexit__(self, *exc: Any) -> None: + await self.close() + + # -- Core API -- + + async def send_message(self, content: str) -> Message: + """Send a user message and run the agent until it responds. + + Returns the final assistant message. + """ + await self.initialize() + + # Append user message + user_event = MessageEvent(source=EventSource.USER, content=content, role="user") + self._state.events.append(user_event) + if self._on_event: + self._on_event(user_event) + + # Run agent loop + self._state.agent_state.status = AgentStatus.RUNNING + runner = self._create_runner() + last_event = await runner.run_until_done() + + # Extract final message + if isinstance(last_event, MessageEvent): + return Message(role="assistant", content=last_event.content) + + return Message(role="assistant", content=str(last_event)) + + async def step(self) -> Event: + """Execute a single agent step (one LLM call + possible tool execution). + + Returns the last event emitted during this step. + """ + await self.initialize() + runner = self._create_runner() + return await runner.step() + + # -- Skill mutation API -- + + def add_skill(self, skill: Skill) -> None: + """Add or replace a skill and refresh the conversation context. + + If the conversation has already been initialized, a new + :class:`~nat.sdk.event.event.SystemPromptEvent` is emitted with the + updated ```` section so the LLM sees the new skill + immediately. Before initialization the skill is simply registered and + will appear in the initial system prompt. + + Args: + skill: The skill to add. Replaces any existing skill with the + same name. + """ + self._skills[skill.name] = skill + if not self._initialized: + return + # Ensure read_skill tool is present (the closure already holds a + # reference to self._skills, so no rebuild is needed when skills are + # merely added; but we do need to insert the tool if this is the first + # skill being added after initialization). + if "read_skill" not in self._tools: + self._tools["read_skill"] = build_read_skill_tool( + skills=self._skills, + state=self._state, + emit_fn=self._emit_event, + build_skills_context=self._build_skills_section, + ) + self._emit_skills_update() + + def remove_skill(self, skill_name: str) -> None: + """Remove a skill and refresh the conversation context. + + If the conversation has already been initialized, a new + :class:`~nat.sdk.event.event.SystemPromptEvent` is emitted reflecting + the reduced skill list. If no skills remain, the ``read_skill`` tool + is removed from the active tool set. + + Args: + skill_name: Name of the skill to remove. No-op if not found. + """ + self._skills.pop(skill_name, None) + if not self._initialized: + return + self._emit_skills_update() + if not self._skills: + self._tools.pop("read_skill", None) + + def update_skill(self, skill: Skill) -> None: + """Replace an existing skill's definition and refresh the conversation context. + + Functionally equivalent to :meth:`add_skill` but signals intent that + the skill already exists. If the skill is currently activated its new + body will appear in the emitted ```` section + immediately. + + Args: + skill: Updated skill. Must have the same ``name`` as the skill + being replaced. + """ + self._skills[skill.name] = skill + if not self._initialized: + return + self._emit_skills_update() + + # -- Internal -- + + def _emit_event(self, event: Event) -> None: + """Append an event to the state log and notify the callback.""" + self._state.events.append(event) + if self._on_event: + self._on_event(event) + + def _emit_skills_update(self) -> None: + """Emit a SystemPromptEvent containing the current skills section. + + Called after any skill mutation (add/remove/update/activate) so the + LLM's context always reflects the live state of ``self._skills``. + Does nothing when there are no skills to describe. + """ + section = self._build_skills_section() + if section: + self._emit_event(SystemPromptEvent(content=section)) + + def _create_runner(self) -> ConversationRunner: + return ConversationRunner( + agent=self._agent, + client=self._client, + state=self._state, + tools=self._effective_tools(), + workspace=self._workspace, + on_event=self._on_event, + ) + + def _effective_tools(self) -> dict[str, Tool]: + """Return the tool set, filtered by active skills' allowed_tools. + + If no skills are activated, or no activated skill carries an + ``allowed_tools`` restriction, the full tool dict is returned. + Otherwise only tools listed by at least one active skill are kept, + plus ``"read_skill"`` which is always available when skills are present. + """ + if not self._skills: + return self._tools + activated = set(self._state.activated_skills) + if not activated: + return self._tools + # Union of all active skills' allowed_tools; empty list means no restriction + restricted: set[str] = set() + has_restriction = False + for name in activated: + skill = self._skills.get(name) + if skill and skill.allowed_tools: + restricted.update(skill.allowed_tools) + has_restriction = True + if not has_restriction: + return self._tools + # Always keep read_skill available so the LLM can activate more skills + restricted.add("read_skill") + return {k: v for k, v in self._tools.items() if k in restricted} + + async def _discover_skills(self) -> None: + """Discover skills from configured directories and the workspace. + + Filesystem discovery runs first so local skills take precedence over + workspace-provided stubs. + """ + for skill_dir in self._agent.skill_discovery_dirs: + self._scan_skill_directory(skill_dir) + + if self._workspace is not None: + try: + summaries = await self._workspace.get_skills() + for summary in summaries: + if summary.name not in self._skills: + self._skills[summary.name] = Skill(name=summary.name, description=summary.description) + except Exception: + logger.warning("Failed to retrieve skills from workspace", exc_info=True) + + def _scan_skill_directory(self, directory: str | Any) -> None: + """Scan a directory for valid skill folders and register them.""" + from pathlib import Path + + directory = Path(directory) + if not directory.is_dir(): + return + + for child in sorted(directory.iterdir()): + if not child.is_dir(): + continue + skill_md = child / "SKILL.md" + if not skill_md.is_file(): + continue + try: + skill = Skill.load(child) + self._skills[skill.name] = skill + except Exception: + logger.warning("Failed to load skill from %s", child, exc_info=True) + + def _build_skills_section(self) -> str: + """Build the ```` XML section for the current skill state. + + Includes full body content (```` tag) for every skill that + appears in ``state.activated_skills``. + + Returns: + The ```` XML string, or ``""`` if no skills exist. + """ + if not self._skills: + return "" + activated = set(self._state.activated_skills) + parts = [""] + for skill in self._skills.values(): + parts.append(skill.to_prompt_xml(include_content=skill.name in activated)) + parts.append("") + return "\n".join(parts) + + def _build_system_prompt(self) -> str: + """Build the full system prompt including skills metadata.""" + parts: list[str] = [] + + # Agent system prompt + rendered = self._agent.render_system_prompt() + if rendered: + parts.append(rendered) + + # Skills metadata + skills_section = self._build_skills_section() + if skills_section: + parts.append(skills_section) + + return "\n\n".join(parts) diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/conversation/runner.py b/packages/nvidia_nat_runtime/src/nat/sdk/conversation/runner.py new file mode 100644 index 0000000000..c119f8f51a --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/conversation/runner.py @@ -0,0 +1,220 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""ConversationRunner — the agent loop that drives a conversation forward.""" + +import asyncio +import logging +import uuid +from collections.abc import Callable +from typing import Any + +from nat.sdk.agent.agent import Agent +from nat.sdk.agent.state import AgentStatus +from nat.sdk.conversation.state import ConversationState +from nat.sdk.event.event import ActionEvent +from nat.sdk.event.event import ErrorEvent +from nat.sdk.event.event import Event +from nat.sdk.event.event import EventSource +from nat.sdk.event.event import MessageEvent +from nat.sdk.event.event import ObservationEvent +from nat.sdk.llm.client import LLMClient +from nat.sdk.llm.message import LLMResponse +from nat.sdk.llm.message import Message +from nat.sdk.tool.result import ToolResult +from nat.sdk.tool.tool import Tool +from nat.workspace.types import WorkspaceBase + +logger = logging.getLogger(__name__) + +EventCallback = Callable[["Event"], None] + + +class ConversationRunner: + """Drives the agent loop: LLM call -> tool execution -> repeat. + + This class encapsulates the core agentic loop and is used internally + by :class:`~nat.sdk.conversation.conversation.Conversation`. + """ + + def __init__( + self, + agent: Agent, + client: LLMClient, + state: ConversationState, + tools: dict[str, Tool], + *, + workspace: WorkspaceBase | None = None, + on_event: EventCallback | None = None, + return_direct_tools: set[str] | None = None, + handle_tool_errors: bool = True, + max_history: int = 0, + initial_messages: list[Message] | None = None, + ) -> None: + self._agent = agent + self._client = client + self._state = state + self._tools = tools + self._workspace = workspace + self._on_event = on_event + self._return_direct_tools = return_direct_tools or set() + self._handle_tool_errors = handle_tool_errors + self._max_history = max_history + self._initial_messages = initial_messages or [] + + # ------------------------------------------------------------------ + # Public + # ------------------------------------------------------------------ + + async def step(self) -> Event: + """Execute a single agent step (one LLM call + tool execution). + + Returns the last event emitted during this step. + """ + self._state.agent_state.status = AgentStatus.RUNNING + + # Build messages from initial messages + event log + messages = self._initial_messages + self._state.events.to_messages() + + # Apply max_history trimming + if self._max_history > 0 and len(messages) > self._max_history: + messages = messages[-self._max_history:] + + # Call LLM + tools_list = list(self._tools.values()) + response = await self._client.complete(messages, tools_list) + self._state.stats.record(response.usage) + + # Process response + if response.message.tool_calls: + return await self._handle_tool_calls(response) + else: + return self._handle_message(response) + + async def run_until_done(self) -> Event: + """Run the agent loop until it produces a final message or hits a limit. + + Returns the final event. + """ + last_event: Event = ErrorEvent(error="No steps executed") + + while self._state.agent_state.status == AgentStatus.RUNNING: + if self._state.agent_state.iteration >= self._agent.max_iterations: + self._state.agent_state.status = AgentStatus.MAX_ITERATIONS + last_event = self._emit(ErrorEvent(error=f"Max iterations ({self._agent.max_iterations}) reached")) + break + + self._state.agent_state.iteration += 1 + last_event = await self.step() + + # return_direct: check if any recent observation is from a return_direct tool + if self._return_direct_tools: + for event in reversed(self._state.events.events): + if not isinstance(event, ObservationEvent): + break + if event.tool_name in self._return_direct_tools: + self._state.agent_state.status = AgentStatus.FINISHED + return event + + # If the last event is a message from the agent, we're done + if isinstance(last_event, MessageEvent) and last_event.source == EventSource.AGENT: + self._state.agent_state.status = AgentStatus.FINISHED + break + + return last_event + + # ------------------------------------------------------------------ + # Internal + # ------------------------------------------------------------------ + + async def _handle_tool_calls(self, response: LLMResponse) -> Event: + """Process tool calls from an LLM response, executing them concurrently.""" + llm_response_id = str(uuid.uuid4()) + + # 1. Emit all ActionEvents sequentially (preserves event log order) + for tc in response.message.tool_calls: + action_event = ActionEvent( + tool_name=tc.name, + tool_call_id=tc.id, + arguments=tc.arguments, + thought=response.message.content or None, + llm_response_id=llm_response_id, + ) + self._emit(action_event) + + # 2. Execute all tools concurrently + tasks = [self._execute_tool(tc.name, tc.id, tc.arguments) for tc in response.message.tool_calls] + results = await asyncio.gather(*tasks, return_exceptions=True) + + # 3. Handle any exceptions from gather (shouldn't happen since + # _execute_tool already catches exceptions, but be defensive) + last_event: Event = ErrorEvent(error="No tool calls processed") + for result in results: + if isinstance(result, BaseException): + if not self._handle_tool_errors: + raise result + last_event = self._emit(ErrorEvent(error=str(result))) + else: + last_event = result + + return last_event + + async def _execute_tool(self, tool_name: str, tool_call_id: str, arguments: dict[str, Any]) -> ObservationEvent: + """Execute a single tool and emit the observation.""" + tool = self._tools.get(tool_name) + if tool is None: + obs = ObservationEvent( + tool_call_id=tool_call_id, + tool_name=tool_name, + error=f"Unknown tool: {tool_name!r}", + is_error=True, + ) + return self._emit(obs) + + try: + result: ToolResult = await tool.invoke(**arguments) + obs = ObservationEvent( + tool_call_id=tool_call_id, + tool_name=tool_name, + output=result.output, + error=result.error, + is_error=result.is_error, + ) + except Exception as exc: + if not self._handle_tool_errors: + raise + obs = ObservationEvent( + tool_call_id=tool_call_id, + tool_name=tool_name, + error=str(exc), + is_error=True, + ) + + return self._emit(obs) + + def _handle_message(self, response: LLMResponse) -> MessageEvent: + """Handle a text-only LLM response.""" + event = MessageEvent( + source=EventSource.AGENT, + content=response.message.content, + role="assistant", + ) + return self._emit(event) + + def _emit(self, event: Event) -> Event: + """Append an event to the log and notify the callback.""" + self._state.events.append(event) + if self._on_event: + self._on_event(event) + return event diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/conversation/state.py b/packages/nvidia_nat_runtime/src/nat/sdk/conversation/state.py new file mode 100644 index 0000000000..41d8dec86f --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/conversation/state.py @@ -0,0 +1,67 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import uuid +from dataclasses import dataclass +from dataclasses import field +from enum import StrEnum + +from nat.sdk.agent.state import AgentState +from nat.sdk.event.log import EventLog +from nat.sdk.llm.message import TokenUsage + + +class ConversationStatus(StrEnum): + """Lifecycle status of a conversation.""" + + ACTIVE = "active" + PAUSED = "paused" + COMPLETED = "completed" + ERROR = "error" + + +@dataclass +class UsageStats: + """Aggregate usage statistics for a conversation.""" + + total_tokens: int = 0 + prompt_tokens: int = 0 + completion_tokens: int = 0 + llm_calls: int = 0 + + def record(self, usage: TokenUsage | None) -> None: + """Record usage from a single LLM call.""" + self.llm_calls += 1 + if usage: + self.total_tokens += usage.total_tokens + self.prompt_tokens += usage.prompt_tokens + self.completion_tokens += usage.completion_tokens + + +@dataclass +class ConversationState: + """Mutable runtime state for a conversation. + + Owns the event log, agent state, and usage statistics. Intentionally + separated from :class:`~nat.sdk.conversation.conversation.Conversation` + so that state can be inspected, serialised, or transferred independently. + """ + + id: str = field(default_factory=lambda: str(uuid.uuid4())) + events: EventLog = field(default_factory=EventLog) + agent_state: AgentState = field(default_factory=AgentState) + status: ConversationStatus = ConversationStatus.ACTIVE + stats: UsageStats = field(default_factory=UsageStats) + activated_skills: list[str] = field(default_factory=list) diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/event/__init__.py b/packages/nvidia_nat_runtime/src/nat/sdk/event/__init__.py new file mode 100644 index 0000000000..2ea4de41e8 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/event/__init__.py @@ -0,0 +1,34 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from nat.sdk.event.event import ActionEvent +from nat.sdk.event.event import ErrorEvent +from nat.sdk.event.event import Event +from nat.sdk.event.event import EventSource +from nat.sdk.event.event import MessageEvent +from nat.sdk.event.event import ObservationEvent +from nat.sdk.event.event import SystemPromptEvent +from nat.sdk.event.log import EventLog + +__all__ = [ + "ActionEvent", + "ErrorEvent", + "Event", + "EventLog", + "EventSource", + "MessageEvent", + "ObservationEvent", + "SystemPromptEvent", +] diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/event/event.py b/packages/nvidia_nat_runtime/src/nat/sdk/event/event.py new file mode 100644 index 0000000000..cab2329c59 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/event/event.py @@ -0,0 +1,99 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import uuid +from dataclasses import dataclass +from dataclasses import field +from datetime import UTC +from datetime import datetime +from enum import StrEnum +from typing import Any + + +class EventSource(StrEnum): + """Origin of an event in the conversation.""" + + USER = "user" + AGENT = "agent" + SYSTEM = "system" + + +def _make_id() -> str: + return str(uuid.uuid4()) + + +def _now() -> datetime: + return datetime.now(UTC) + + +@dataclass(frozen=True) +class Event: + """Base event in a conversation timeline. + + All events are immutable and carry a unique id plus a UTC timestamp. + """ + + id: str = field(default_factory=_make_id) + timestamp: datetime = field(default_factory=_now) + source: EventSource = EventSource.SYSTEM + + +@dataclass(frozen=True) +class SystemPromptEvent(Event): + """The system prompt injected at the start of a conversation.""" + + source: EventSource = field(default=EventSource.SYSTEM, init=False) + content: str = "" + + +@dataclass(frozen=True) +class MessageEvent(Event): + """A text message from the user or the agent.""" + + content: str = "" + role: str = "user" # "user" or "assistant" + + +@dataclass(frozen=True) +class ActionEvent(Event): + """An agent's request to invoke a tool.""" + + source: EventSource = field(default=EventSource.AGENT, init=False) + tool_name: str = "" + tool_call_id: str = field(default_factory=_make_id) + arguments: dict[str, Any] = field(default_factory=dict) + thought: str | None = None + llm_response_id: str | None = None # groups parallel tool calls from a single LLM response + + +@dataclass(frozen=True) +class ObservationEvent(Event): + """The result of executing a tool call.""" + + source: EventSource = field(default=EventSource.SYSTEM, init=False) + tool_call_id: str = "" + tool_name: str = "" + output: Any = None + error: str | None = None + is_error: bool = False + + +@dataclass(frozen=True) +class ErrorEvent(Event): + """An error that occurred during conversation execution.""" + + source: EventSource = field(default=EventSource.SYSTEM, init=False) + error: str = "" + recoverable: bool = True diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/event/log.py b/packages/nvidia_nat_runtime/src/nat/sdk/event/log.py new file mode 100644 index 0000000000..b4169e8baa --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/event/log.py @@ -0,0 +1,129 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from collections.abc import Iterator + +from nat.sdk.event.event import ActionEvent +from nat.sdk.event.event import Event +from nat.sdk.event.event import MessageEvent +from nat.sdk.event.event import ObservationEvent +from nat.sdk.event.event import SystemPromptEvent +from nat.sdk.llm.message import Message +from nat.sdk.llm.message import ToolCall + + +class EventLog: + """Ordered, append-only event store for a conversation. + + Provides conversion of the event timeline into LLM message format + and detection of pending (unmatched) tool calls. + """ + + def __init__(self) -> None: + self._events: list[Event] = [] + + # -- Mutation -- + + def append(self, event: Event) -> None: + """Append an event to the log.""" + self._events.append(event) + + def extend(self, events: list[Event]) -> None: + """Append multiple events to the log.""" + self._events.extend(events) + + # -- Query -- + + def __len__(self) -> int: + return len(self._events) + + def __iter__(self) -> Iterator[Event]: + return iter(self._events) + + def __getitem__(self, index: int) -> Event: + return self._events[index] + + @property + def events(self) -> list[Event]: + """Return a shallow copy of all events.""" + return list(self._events) + + def get_unmatched_actions(self) -> list[ActionEvent]: + """Return ActionEvents that have no corresponding ObservationEvent.""" + matched_ids: set[str] = set() + for event in self._events: + if isinstance(event, ObservationEvent): + matched_ids.add(event.tool_call_id) + + return [ + event for event in self._events if isinstance(event, ActionEvent) and event.tool_call_id not in matched_ids + ] + + def to_messages(self) -> list[Message]: + """Convert the event log into a list of LLM-compatible messages. + + Groups parallel tool calls (same llm_response_id) into a single + assistant message with multiple tool_calls. + """ + + messages: list[Message] = [] + + # Buffer for grouping parallel ActionEvents by llm_response_id + pending_actions: list[ActionEvent] = [] + + def _flush_actions() -> None: + """Convert buffered ActionEvents into an assistant message + tool results.""" + if not pending_actions: + return + + tool_calls = [ + ToolCall( + id=action.tool_call_id, + name=action.tool_name, + arguments=action.arguments, + ) for action in pending_actions + ] + + # The thought from the first action serves as the assistant text + thought = pending_actions[0].thought or "" + messages.append(Message(role="assistant", content=thought, tool_calls=tool_calls)) + pending_actions.clear() + + for event in self._events: + if isinstance(event, SystemPromptEvent): + messages.append(Message(role="system", content=event.content)) + + elif isinstance(event, MessageEvent): + _flush_actions() + messages.append(Message(role=event.role, content=event.content)) + + elif isinstance(event, ActionEvent): + # Buffer actions; flush when the group changes + if pending_actions and (event.llm_response_id is None + or event.llm_response_id != pending_actions[0].llm_response_id): + _flush_actions() + pending_actions.append(event) + + elif isinstance(event, ObservationEvent): + _flush_actions() + content = event.error if event.is_error else str(event.output) + messages.append(Message( + role="tool", + content=content or "", + tool_call_id=event.tool_call_id, + )) + + _flush_actions() + return messages diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/llm/__init__.py b/packages/nvidia_nat_runtime/src/nat/sdk/llm/__init__.py new file mode 100644 index 0000000000..41c5006c3e --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/llm/__init__.py @@ -0,0 +1,32 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from nat.sdk.llm.builder_client import BuilderLLMClient +from nat.sdk.llm.builder_client import create_llm_client +from nat.sdk.llm.client import LLMClient +from nat.sdk.llm.message import LLMResponse +from nat.sdk.llm.message import Message +from nat.sdk.llm.message import TokenUsage +from nat.sdk.llm.message import ToolCall + +__all__ = [ + "BuilderLLMClient", + "LLMClient", + "LLMResponse", + "Message", + "TokenUsage", + "ToolCall", + "create_llm_client", +] diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/llm/builder_client.py b/packages/nvidia_nat_runtime/src/nat/sdk/llm/builder_client.py new file mode 100644 index 0000000000..222e78aff5 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/llm/builder_client.py @@ -0,0 +1,143 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""LLM client adapter backed by a core RuntimeOpenAIClient from the Builder.""" + +from __future__ import annotations + +import json +import logging +from typing import Any + +from nat.sdk.llm.client import LLMClient +from nat.sdk.llm.message import LLMResponse +from nat.sdk.llm.message import Message +from nat.sdk.llm.message import TokenUsage +from nat.sdk.llm.message import ToolCall +from nat.sdk.tool.tool import Tool + +logger = logging.getLogger(__name__) + + +class BuilderLLMClient(LLMClient): + """LLM client backed by a core :class:`RuntimeOpenAIClient` from the Builder. + + This adapter wraps a ``RuntimeOpenAIClient`` (obtained via the core Builder + system) and inherits from :class:`LLMClient`, bridging the core runtime + infrastructure with the lightweight SDK agent loop. + """ + + def __init__(self, runtime_client: Any) -> None: + """Initialize the adapter. + + Parameters + ---------- + runtime_client + A ``RuntimeOpenAIClient`` instance obtained from the Builder. + """ + self._client = runtime_client + + async def complete( + self, + messages: list[Message], + tools: list[Tool] | None = None, + **kwargs: Any, + ) -> LLMResponse: + """Call the chat completions endpoint via the wrapped runtime client. + + Converts SDK :class:`Message` objects to OpenAI dicts, delegates to + ``RuntimeOpenAIClient.chat_completions``, and parses the response back + into an SDK :class:`LLMResponse`. + """ + openai_messages = [m.to_openai_dict() for m in messages] + + extra_kwargs: dict[str, Any] = dict(kwargs) + if tools is not None and tools: + extra_kwargs["tools"] = [t.to_openai_schema() for t in tools] + + response = await self._client.chat_completions(openai_messages, **extra_kwargs) + + choice = response.choices[0] + + # Parse tool calls + tool_calls: list[ToolCall] = [] + if choice.message.tool_calls: + for tc in choice.message.tool_calls: + try: + arguments = json.loads(tc.function.arguments) + except (json.JSONDecodeError, TypeError): + arguments = {"_raw": tc.function.arguments} + tool_calls.append(ToolCall( + id=tc.id, + name=tc.function.name, + arguments=arguments, + )) + + message = Message( + role="assistant", + content=choice.message.content or "", + tool_calls=tool_calls, + ) + + usage = None + if response.usage: + usage = TokenUsage( + prompt_tokens=response.usage.prompt_tokens or 0, + completion_tokens=response.usage.completion_tokens or 0, + total_tokens=response.usage.total_tokens or 0, + ) + + return LLMResponse( + message=message, + usage=usage, + model=response.model, + finish_reason=choice.finish_reason, + raw=response, + ) + + +async def create_llm_client( + config: Any, + *, + llm_name: str = "default", +) -> BuilderLLMClient: + """Create an :class:`LLMClient` from any core ``LLMBaseConfig``. + + This factory registers the config with the Builder, retrieves the + ``RUNTIME`` wrapper (a ``RuntimeOpenAIClient``), and returns a + :class:`BuilderLLMClient` adapter. + + Parameters + ---------- + config + A core ``LLMBaseConfig`` subclass instance (e.g. ``OpenAIModelConfig``, + ``NIMModelConfig``). + llm_name + Name to register the LLM under in the builder. Defaults to + ``"default"``. + + Returns + ------- + BuilderLLMClient + An SDK-compatible LLM client backed by the core runtime. + """ + from nat.builder.builder import Builder + + builder = Builder.current() + + from nat.builder.framework_enum import LLMFrameworkEnum + + await builder.add_llm(llm_name, config) + runtime_client = await builder.get_llm(llm_name, LLMFrameworkEnum.RUNTIME) + return BuilderLLMClient(runtime_client) diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/llm/client.py b/packages/nvidia_nat_runtime/src/nat/sdk/llm/client.py new file mode 100644 index 0000000000..2d8fddf3cb --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/llm/client.py @@ -0,0 +1,38 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from abc import ABC +from abc import abstractmethod +from typing import Any + +from nat.sdk.llm.message import LLMResponse +from nat.sdk.llm.message import Message +from nat.sdk.tool.tool import Tool + + +class LLMClient(ABC): + """Base class for language-model backends. + + Subclass this to plug in a custom LLM provider. + """ + + @abstractmethod + async def complete( + self, + messages: list[Message], + tools: list[Tool] | None = None, + **kwargs: Any, + ) -> LLMResponse: + ... diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/llm/message.py b/packages/nvidia_nat_runtime/src/nat/sdk/llm/message.py new file mode 100644 index 0000000000..01f987c90f --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/llm/message.py @@ -0,0 +1,93 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import Any + +from pydantic import BaseModel +from pydantic import ConfigDict +from pydantic import Field + + +class ToolCall(BaseModel): + """A tool invocation requested by an LLM.""" + + model_config = ConfigDict(frozen=True) + + id: str + name: str + arguments: dict[str, Any] = Field(default_factory=dict) + + def to_openai_dict(self) -> dict[str, Any]: + """Serialize to the OpenAI chat completion tool_call format.""" + import json + + return { + "id": self.id, + "type": "function", + "function": { + "name": self.name, + "arguments": json.dumps(self.arguments), + }, + } + + +class Message(BaseModel): + """A transport-agnostic message in a conversation. + + Represents system, user, assistant, and tool messages. Assistant messages + may optionally carry ``tool_calls``. Tool result messages carry a + ``tool_call_id`` linking them back to the originating call. + """ + + model_config = ConfigDict(frozen=True) + + role: str # "system" | "user" | "assistant" | "tool" + content: str = "" + tool_calls: list[ToolCall] = Field(default_factory=list) + tool_call_id: str | None = None # set for role="tool" messages + + def to_openai_dict(self) -> dict[str, Any]: + """Serialize to the OpenAI chat completion message format.""" + msg: dict[str, Any] = {"role": self.role, "content": self.content} + + if self.tool_calls: + msg["tool_calls"] = [tc.to_openai_dict() for tc in self.tool_calls] + + if self.tool_call_id is not None: + msg["tool_call_id"] = self.tool_call_id + + return msg + + +class TokenUsage(BaseModel): + """Token counts for a single LLM call.""" + + prompt_tokens: int = 0 + completion_tokens: int = 0 + total_tokens: int = 0 + cached_tokens: int = 0 + reasoning_tokens: int = 0 + + +class LLMResponse(BaseModel): + """The result of an LLM completion call.""" + + model_config = ConfigDict(arbitrary_types_allowed=True) + + message: Message + usage: TokenUsage | None = None + model: str | None = None + finish_reason: str | None = None + raw: Any = Field(default=None, exclude=True) diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/skill/__init__.py b/packages/nvidia_nat_runtime/src/nat/sdk/skill/__init__.py new file mode 100644 index 0000000000..6617ef0d33 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/skill/__init__.py @@ -0,0 +1,19 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Skill activation utilities for the NAT SDK.""" + +from nat.sdk.skill.tool import build_read_skill_tool + +__all__ = ["build_read_skill_tool"] diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/skill/tool.py b/packages/nvidia_nat_runtime/src/nat/sdk/skill/tool.py new file mode 100644 index 0000000000..38eac0063a --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/skill/tool.py @@ -0,0 +1,102 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Skill activation tool for the NAT SDK conversation runtime.""" + +from __future__ import annotations + +from collections.abc import Callable +from typing import TYPE_CHECKING + +from nat.sdk.event.event import SystemPromptEvent +from nat.sdk.tool.tool import Tool + +if TYPE_CHECKING: + from nat.data_models.skill import Skill + from nat.sdk.conversation.state import ConversationState + from nat.sdk.event.event import Event + + +def build_read_skill_tool( + skills: dict[str, Skill], + state: ConversationState, + emit_fn: Callable[[Event], None], + build_skills_context: Callable[[], str], +) -> Tool: + """Build a tool that activates a named skill for the current conversation. + + When invoked by the LLM, this tool: + + 1. Looks up the skill by name. + 2. Marks it as activated in ``state.activated_skills`` (deduplicating). + 3. Calls ``build_skills_context()`` to get the current ```` + section — which now includes the activated skill's full body — and emits + it as a new :class:`~nat.sdk.event.event.SystemPromptEvent` so the LLM + sees the updated context in its message history. + 4. Returns a short confirmation string. + + Using ``build_skills_context`` rather than ``skill.to_full_prompt()`` ensures + that the emitted event always reflects the *complete, current* skills state + (all skills, with content for every activated one) rather than a bare body + snippet. + + Args: + skills: Mapping of skill name → Skill, populated during conversation + initialisation (filesystem + workspace discovery). Mutations to + this dict (add/remove/update) are visible to the tool immediately. + state: Mutable conversation state. ``activated_skills`` is updated + in-place. + emit_fn: Callable that appends an event to the state log and fires the + on_event callback (mirrors ``Conversation._emit_event``). + build_skills_context: Zero-argument callable that returns the current + ```` XML section as a string, incorporating all + currently activated skills. Supplied by + ``Conversation._build_skills_section``. + + Returns: + A :class:`~nat.sdk.tool.tool.Tool` named ``"read_skill"``. + """ + + async def _execute(skill_name: str) -> str: + skill = skills.get(skill_name) + if skill is None: + available = ", ".join(sorted(skills.keys())) + return (f"Error: skill {skill_name!r} not found. " + f"Available skills: {available or 'none'}.") + + if skill.name not in state.activated_skills: + state.activated_skills.append(skill.name) + + context = build_skills_context() + if context: + emit_fn(SystemPromptEvent(content=context)) + + return f"Skill {skill.name!r} activated." + + return Tool( + name="read_skill", + description=("Activate a skill by name to load its full instructions into the " + "conversation. Use this when you need detailed guidance from a skill."), + parameters={ + "type": "object", + "properties": { + "skill_name": { + "type": "string", + "description": "Name of the skill to activate.", + }, + }, + "required": ["skill_name"], + }, + execute=_execute, + ) diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/tool/__init__.py b/packages/nvidia_nat_runtime/src/nat/sdk/tool/__init__.py new file mode 100644 index 0000000000..098597da1d --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/tool/__init__.py @@ -0,0 +1,24 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from nat.sdk.tool.result import ToolResult +from nat.sdk.tool.tool import Tool +from nat.sdk.tool.tool import tool + +__all__ = [ + "Tool", + "ToolResult", + "tool", +] diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/tool/result.py b/packages/nvidia_nat_runtime/src/nat/sdk/tool/result.py new file mode 100644 index 0000000000..5a054a901f --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/tool/result.py @@ -0,0 +1,51 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +from dataclasses import dataclass +from dataclasses import field +from typing import TYPE_CHECKING +from typing import Any + +if TYPE_CHECKING: + from nat.data_models.workspace import ActionResult + + +@dataclass +class ToolResult: + """The outcome of a tool execution.""" + + output: Any = None + error: str | None = None + metadata: dict[str, Any] = field(default_factory=dict) + + @staticmethod + def from_action_result(result: ActionResult) -> ToolResult: + """Convert a core :class:`~nat.data_models.workspace.ActionResult` to a :class:`ToolResult`.""" + from nat.data_models.workspace import ActionStatus + + if result.status != ActionStatus.SUCCESS: + return ToolResult(error=result.error_message or f"Action failed with status {result.status}") + return ToolResult(output=result.output) + + @property + def is_error(self) -> bool: + return self.error is not None + + def __str__(self) -> str: + if self.is_error: + return f"Error: {self.error}" + return str(self.output) if self.output is not None else "" diff --git a/packages/nvidia_nat_runtime/src/nat/sdk/tool/tool.py b/packages/nvidia_nat_runtime/src/nat/sdk/tool/tool.py new file mode 100644 index 0000000000..304fc4b7b2 --- /dev/null +++ b/packages/nvidia_nat_runtime/src/nat/sdk/tool/tool.py @@ -0,0 +1,312 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import inspect +import itertools +import re +from collections.abc import AsyncGenerator +from collections.abc import Awaitable +from collections.abc import Callable +from dataclasses import dataclass +from dataclasses import field +from typing import TYPE_CHECKING +from typing import Any +from typing import get_type_hints +from uuid import uuid4 + +from nat.sdk.tool.result import ToolResult + +if TYPE_CHECKING: + from nat.builder.function import Function + from nat.builder.function import FunctionGroup + from nat.data_models.function import FunctionBaseConfig + from nat.data_models.function import FunctionGroupBaseConfig + +_tool_id_counter = itertools.count() + +ExecuteFn = Callable[..., ToolResult | Awaitable[ToolResult] | Any | Awaitable[Any]] + + +@dataclass(frozen=True) +class Tool: + """An immutable, schema-bearing tool definition. + + ``parameters`` is a JSON Schema dict describing the tool's input. + ``execute`` is a callable that performs the tool's action. + """ + + name: str + description: str + parameters: dict[str, Any] = field(default_factory=lambda: {"type": "object", "properties": {}}) + execute: ExecuteFn = field(default=lambda **_kw: ToolResult(), repr=False) + _fn: Any = field(default=None, repr=False, compare=False, hash=False) + + @staticmethod + def from_function(fn: "Function") -> "Tool": + """Wrap a core Function as an SDK Tool.""" + schema = fn.input_schema.model_json_schema() + + async def _execute(**kwargs: Any) -> ToolResult: + result = await fn.acall_invoke(**kwargs) + return ToolResult(output=result) + + return Tool( + name=fn.display_name, + description=fn.description or "", + parameters=schema, + execute=_execute, + _fn=fn, + ) + + @staticmethod + async def from_function_config(config: "FunctionBaseConfig") -> "Tool": + """Build a Function from config via the type registry and Builder, then wrap as Tool.""" + from nat.builder.builder import Builder + + builder = Builder.current() + name = config.name or f"sdk_fn_{next(_tool_id_counter)}" + fn = await builder.add_function(name, config) + return Tool.from_function(fn) + + @staticmethod + async def from_function_group(group: "FunctionGroup") -> list["Tool"]: + """Wrap each accessible function in a pre-built FunctionGroup as an SDK Tool.""" + functions = await group.get_accessible_functions() + return [Tool.from_function(fn) for fn in functions.values()] + + @staticmethod + async def from_function_group_config(config: "FunctionGroupBaseConfig") -> list["Tool"]: + """Build a FunctionGroup from config via the type registry, then wrap each function as a Tool.""" + from nat.builder.builder import Builder + + builder = Builder.current() + name = f"sdk_fg_{next(_tool_id_counter)}" + group = await builder.add_function_group(name, config) + functions = await group.get_accessible_functions() + return [Tool.from_function(fn) for fn in functions.values()] + + def to_openai_schema(self) -> dict[str, Any]: + """Serialize to the OpenAI function-calling tool format.""" + return { + "type": "function", + "function": { + "name": self.name, + "description": self.description, + "parameters": self.parameters, + }, + } + + @property + def tool_schema(self) -> dict[str, Any]: + """Return the OpenAI tool schema (alias for to_openai_schema).""" + return self.to_openai_schema() + + async def invoke(self, **kwargs: Any) -> ToolResult: + """Execute the tool with tracing, normalising sync/async and wrapping raw returns.""" + from nat.builder.context import Context + from nat.builder.framework_enum import LLMFrameworkEnum + from nat.data_models.intermediate_step import IntermediateStepPayload + from nat.data_models.intermediate_step import IntermediateStepType + from nat.data_models.intermediate_step import StreamEventData + + step_id = str(uuid4()) + step_manager = Context.get().intermediate_step_manager + step_manager.push_intermediate_step( + IntermediateStepPayload( + event_type=IntermediateStepType.TOOL_START, + framework=LLMFrameworkEnum.RUNTIME, + name=self.name, + UUID=step_id, + data=StreamEventData(input=kwargs), + )) + + output = None + result: ToolResult + try: + if self._fn is not None and self._fn.has_streaming_output and not self._fn.has_single_output: + chunks: list[Any] = [] + text_parts: list[str] = [] + async for chunk in self._fn.acall_stream(**kwargs): + if isinstance(chunk, str): + text_parts.append(chunk) + else: + chunks.append(chunk) + output = "".join(text_parts) if text_parts else (chunks if chunks else None) + result = ToolResult(output=output) + else: + raw = self.execute(**kwargs) + if inspect.isawaitable(raw): + raw = await raw + if not isinstance(raw, ToolResult): + raw = ToolResult(output=raw) + result = raw + output = result.output + return result + finally: + step_manager.push_intermediate_step( + IntermediateStepPayload( + event_type=IntermediateStepType.TOOL_END, + framework=LLMFrameworkEnum.RUNTIME, + name=self.name, + UUID=step_id, + data=StreamEventData(input=kwargs, output=output), + )) + + async def stream(self, **kwargs: Any) -> AsyncGenerator[Any, None]: + """Stream results from the tool with tracing. Falls back to invoke for non-streaming tools.""" + from nat.builder.context import Context + from nat.builder.framework_enum import LLMFrameworkEnum + from nat.data_models.intermediate_step import IntermediateStepPayload + from nat.data_models.intermediate_step import IntermediateStepType + from nat.data_models.intermediate_step import StreamEventData + + step_id = str(uuid4()) + step_manager = Context.get().intermediate_step_manager + step_manager.push_intermediate_step( + IntermediateStepPayload( + event_type=IntermediateStepType.TOOL_START, + framework=LLMFrameworkEnum.RUNTIME, + name=self.name, + UUID=step_id, + data=StreamEventData(input=kwargs), + )) + + output = None + try: + if self._fn is not None and self._fn.has_streaming_output and not self._fn.has_single_output: + chunks: list[Any] = [] + text_parts: list[str] = [] + async for chunk in self._fn.acall_stream(**kwargs): + if isinstance(chunk, str): + text_parts.append(chunk) + else: + chunks.append(chunk) + yield chunk + output = "".join(text_parts) if text_parts else (chunks if chunks else None) + else: + result = await self(**kwargs) + output = result.output + yield result.output + finally: + step_manager.push_intermediate_step( + IntermediateStepPayload( + event_type=IntermediateStepType.TOOL_END, + framework=LLMFrameworkEnum.RUNTIME, + name=self.name, + UUID=step_id, + data=StreamEventData(input=kwargs, output=output), + )) + + async def __call__(self, **kwargs: Any) -> ToolResult: + """Execute the tool, normalising sync/async callables and wrapping raw returns.""" + try: + result = self.execute(**kwargs) + if inspect.isawaitable(result): + result = await result + if not isinstance(result, ToolResult): + result = ToolResult(output=result) + return result + except Exception as exc: + return ToolResult(error=str(exc)) + + +# --------------------------------------------------------------------------- +# Convenience decorator +# --------------------------------------------------------------------------- + +_PYTHON_TYPE_TO_JSON: dict[type, str] = { + str: "string", + int: "integer", + float: "number", + bool: "boolean", + list: "array", + dict: "object", +} + + +def _camel_to_snake(name: str) -> str: + s1 = re.sub(r"(.)([A-Z][a-z]+)", r"\1_\2", name) + return re.sub(r"([a-z0-9])([A-Z])", r"\1_\2", s1).lower() + + +def _build_schema_from_function(fn: Callable[..., Any]) -> dict[str, Any]: + """Derive a JSON Schema ``parameters`` object from a function's type hints.""" + hints = get_type_hints(fn) + sig = inspect.signature(fn) + + properties: dict[str, Any] = {} + required: list[str] = [] + + for param_name, param in sig.parameters.items(): + if param_name in ("self", "cls"): + continue + if param_name == "return": + continue + + prop: dict[str, Any] = {} + hint = hints.get(param_name) + if hint is not None: + json_type = _PYTHON_TYPE_TO_JSON.get(hint) + if json_type: + prop["type"] = json_type + + properties[param_name] = prop + + if param.default is inspect.Parameter.empty: + required.append(param_name) + + schema: dict[str, Any] = { + "type": "object", + "properties": properties, + } + if required: + schema["required"] = required + return schema + + +def tool( + description: str, + *, + name: str | None = None, +) -> Callable[[Callable[..., Any]], Tool]: + """Decorator that turns a function into a :class:`Tool`. + + Usage:: + + @tool(description="Search the web") + async def web_search(query: str) -> str: + ... + """ + + def decorator(fn: Callable[..., Any]) -> Tool: + tool_name = name or _camel_to_snake(fn.__name__) + parameters = _build_schema_from_function(fn) + + async def _execute(**kwargs: Any) -> ToolResult: + result = fn(**kwargs) + if inspect.isawaitable(result): + result = await result + if isinstance(result, ToolResult): + return result + return ToolResult(output=result) + + return Tool( + name=tool_name, + description=description, + parameters=parameters, + execute=_execute, + ) + + return decorator diff --git a/packages/nvidia_nat_runtime/tests/conftest.py b/packages/nvidia_nat_runtime/tests/conftest.py new file mode 100644 index 0000000000..a4f1cb6809 --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/conftest.py @@ -0,0 +1,35 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from collections.abc import Iterator + +import pytest + +from nat.builder.context import Context +from nat.builder.context import ContextState +from nat.data_models.intermediate_step import IntermediateStepPayload + + +@pytest.fixture(name="step_payloads") +def fixture_step_payloads(monkeypatch: pytest.MonkeyPatch) -> Iterator[list[IntermediateStepPayload]]: + """Collect intermediate step payloads emitted during a test.""" + payloads: list[IntermediateStepPayload] = [] + context = Context(ContextState.get()) + monkeypatch.setattr(Context, "get", staticmethod(lambda: context)) + manager = context.intermediate_step_manager + subscription = manager.subscribe(lambda step: payloads.append(step.payload)) + try: + yield payloads + finally: + subscription.unsubscribe() diff --git a/packages/nvidia_nat_runtime/tests/sdk/__init__.py b/packages/nvidia_nat_runtime/tests/sdk/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/packages/nvidia_nat_runtime/tests/sdk/conftest.py b/packages/nvidia_nat_runtime/tests/sdk/conftest.py new file mode 100644 index 0000000000..ad992de0c6 --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/conftest.py @@ -0,0 +1,60 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import pytest + +from nat.sdk import Agent +from nat.sdk import Event +from nat.sdk import Tool +from nat.sdk import ToolResult + + +@pytest.fixture +def simple_tool() -> Tool: + + async def _add(a: int, b: int) -> ToolResult: + return ToolResult(output=a + b) + + return Tool( + name="add", + description="Add two numbers", + parameters={ + "type": "object", + "properties": { + "a": { + "type": "integer" + }, + "b": { + "type": "integer" + }, + }, + "required": ["a", "b"], + }, + execute=_add, + ) + + +@pytest.fixture +def simple_agent(simple_tool: Tool) -> Agent: + return Agent( + tools=[simple_tool], + system_prompt="You are a test assistant.", + ) + + +@pytest.fixture +def event_collector() -> list[Event]: + """Collects events emitted during a conversation.""" + return [] diff --git a/packages/nvidia_nat_runtime/tests/sdk/test_agent.py b/packages/nvidia_nat_runtime/tests/sdk/test_agent.py new file mode 100644 index 0000000000..a2d5f5ad2c --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/test_agent.py @@ -0,0 +1,137 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for nat.sdk.agent — Agent and AgentState.""" + +import pytest +from pydantic import ValidationError + +from nat.data_models.skill import Skill +from nat.sdk.agent.agent import Agent +from nat.sdk.agent.state import AgentState +from nat.sdk.agent.state import AgentStatus +from nat.sdk.tool.tool import Tool + +# --------------------------------------------------------------------------- +# AgentStatus +# --------------------------------------------------------------------------- + + +class TestAgentStatus: + + def test_values(self) -> None: + assert AgentStatus.IDLE == "idle" + assert AgentStatus.RUNNING == "running" + assert AgentStatus.FINISHED == "finished" + assert AgentStatus.ERROR == "error" + assert AgentStatus.MAX_ITERATIONS == "max_iterations" + + +# --------------------------------------------------------------------------- +# AgentState +# --------------------------------------------------------------------------- + + +class TestAgentState: + + def test_defaults(self) -> None: + state = AgentState() + assert state.iteration == 0 + assert state.status == AgentStatus.IDLE + assert state.metadata == {} + + def test_mutable(self) -> None: + state = AgentState() + state.iteration = 5 + state.status = AgentStatus.RUNNING + state.metadata["key"] = "value" + assert state.iteration == 5 + assert state.status == AgentStatus.RUNNING + assert state.metadata["key"] == "value" + + def test_reset(self) -> None: + state = AgentState( + iteration=10, + status=AgentStatus.FINISHED, + metadata={"x": 1}, + ) + state.reset() + assert state.iteration == 0 + assert state.status == AgentStatus.IDLE + assert state.metadata == {} + + +# --------------------------------------------------------------------------- +# Agent +# --------------------------------------------------------------------------- + + +class TestAgent: + + def test_minimal(self) -> None: + agent = Agent() + assert agent.tools == [] + assert agent.skills == [] + assert agent.system_prompt == "" + assert agent.system_prompt_kwargs == {} + assert agent.max_iterations == 50 + + def test_with_tools(self) -> None: + t = Tool(name="search", description="Search") + agent = Agent(tools=[t]) + assert len(agent.tools) == 1 + assert agent.tools[0].name == "search" + + def test_with_skills(self) -> None: + s = Skill(name="code-review", description="Review code") + agent = Agent(skills=[s]) + assert len(agent.skills) == 1 + assert agent.skills[0].name == "code-review" + + def test_frozen(self) -> None: + agent = Agent() + with pytest.raises(ValidationError): + agent.max_iterations = 100 # type: ignore[misc] + + def test_render_system_prompt_plain(self) -> None: + agent = Agent(system_prompt="You are a helpful assistant.", ) + assert agent.render_system_prompt() == "You are a helpful assistant." + + def test_render_system_prompt_with_kwargs(self) -> None: + agent = Agent( + system_prompt="Hello {name}, you are a {role}.", + system_prompt_kwargs={ + "name": "Agent", "role": "helper" + }, + ) + result = agent.render_system_prompt() + assert result == "Hello Agent, you are a helper." + + def test_render_system_prompt_with_extra_kwargs(self) -> None: + agent = Agent( + system_prompt="Hi {name}!", + system_prompt_kwargs={"name": "Default"}, + ) + result = agent.render_system_prompt(name="Override") + assert result == "Hi Override!" + + def test_render_system_prompt_empty(self) -> None: + agent = Agent() + assert agent.render_system_prompt() == "" + + def test_render_system_prompt_missing_key_returns_raw(self) -> None: + """If a template key is missing, return the raw template.""" + agent = Agent(system_prompt="Hello {unknown_key}!", ) + result = agent.render_system_prompt() + assert result == "Hello {unknown_key}!" diff --git a/packages/nvidia_nat_runtime/tests/sdk/test_builder_llm_client.py b/packages/nvidia_nat_runtime/tests/sdk/test_builder_llm_client.py new file mode 100644 index 0000000000..3fd47f1d49 --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/test_builder_llm_client.py @@ -0,0 +1,232 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for nat.sdk.llm.builder_client — BuilderLLMClient and create_llm_client.""" + +from unittest.mock import AsyncMock +from unittest.mock import MagicMock +from unittest.mock import patch + +from nat.sdk.llm.builder_client import BuilderLLMClient +from nat.sdk.llm.builder_client import create_llm_client +from nat.sdk.llm.client import LLMClient +from nat.sdk.llm.message import Message +from nat.sdk.tool.tool import Tool + +# --------------------------------------------------------------------------- +# Helpers — fake OpenAI response objects +# --------------------------------------------------------------------------- + + +def _make_fake_response( + content: str = "Hello!", + tool_calls: list | None = None, + model: str = "test-model", + finish_reason: str = "stop", + prompt_tokens: int = 10, + completion_tokens: int = 5, + total_tokens: int = 15, +) -> MagicMock: + """Build a mock ChatCompletion response matching the OpenAI SDK shape.""" + message = MagicMock() + message.content = content + message.tool_calls = tool_calls + + choice = MagicMock() + choice.message = message + choice.finish_reason = finish_reason + + usage = MagicMock() + usage.prompt_tokens = prompt_tokens + usage.completion_tokens = completion_tokens + usage.total_tokens = total_tokens + + response = MagicMock() + response.choices = [choice] + response.model = model + response.usage = usage + return response + + +def _make_tool_call(tc_id: str, name: str, arguments: str) -> MagicMock: + """Build a mock tool call matching the OpenAI SDK shape.""" + fn = MagicMock() + fn.name = name + fn.arguments = arguments + + tc = MagicMock() + tc.id = tc_id + tc.function = fn + return tc + + +# --------------------------------------------------------------------------- +# BuilderLLMClient +# --------------------------------------------------------------------------- + + +class TestBuilderLLMClient: + + async def test_simple_completion(self) -> None: + runtime_client = AsyncMock() + runtime_client.chat_completions.return_value = _make_fake_response(content="Hi there") + + client = BuilderLLMClient(runtime_client) + messages = [Message(role="user", content="Hello")] + response = await client.complete(messages, []) + + assert response.message.role == "assistant" + assert response.message.content == "Hi there" + assert response.model == "test-model" + assert response.usage is not None + assert response.usage.total_tokens == 15 + + async def test_with_tool_calls(self) -> None: + tc = _make_tool_call("tc-1", "add", '{"a": 1, "b": 2}') + runtime_client = AsyncMock() + runtime_client.chat_completions.return_value = _make_fake_response(content="", tool_calls=[tc]) + + client = BuilderLLMClient(runtime_client) + messages = [Message(role="user", content="Add 1+2")] + response = await client.complete(messages, []) + + assert len(response.message.tool_calls) == 1 + assert response.message.tool_calls[0].name == "add" + assert response.message.tool_calls[0].arguments == {"a": 1, "b": 2} + assert response.message.tool_calls[0].id == "tc-1" + + async def test_malformed_tool_call_arguments(self) -> None: + tc = _make_tool_call("tc-2", "broken", "not-valid-json") + runtime_client = AsyncMock() + runtime_client.chat_completions.return_value = _make_fake_response(content="", tool_calls=[tc]) + + client = BuilderLLMClient(runtime_client) + messages = [Message(role="user", content="test")] + response = await client.complete(messages, []) + + assert len(response.message.tool_calls) == 1 + assert response.message.tool_calls[0].arguments == {"_raw": "not-valid-json"} + + async def test_tools_passed_to_runtime(self) -> None: + runtime_client = AsyncMock() + runtime_client.chat_completions.return_value = _make_fake_response() + + tool = Tool( + name="search", + description="Search for things", + parameters={ + "type": "object", "properties": { + "q": { + "type": "string" + } + } + }, + ) + + client = BuilderLLMClient(runtime_client) + messages = [Message(role="user", content="test")] + await client.complete(messages, [tool]) + + # Verify tools were passed as OpenAI schema + call_kwargs = runtime_client.chat_completions.call_args + assert "tools" in call_kwargs.kwargs + + async def test_no_usage(self) -> None: + response = _make_fake_response() + response.usage = None + + runtime_client = AsyncMock() + runtime_client.chat_completions.return_value = response + + client = BuilderLLMClient(runtime_client) + messages = [Message(role="user", content="test")] + result = await client.complete(messages, []) + + assert result.usage is None + + async def test_implements_base_class(self) -> None: + runtime_client = AsyncMock() + client = BuilderLLMClient(runtime_client) + assert isinstance(client, LLMClient) + + async def test_messages_converted_to_openai_format(self) -> None: + runtime_client = AsyncMock() + runtime_client.chat_completions.return_value = _make_fake_response() + + client = BuilderLLMClient(runtime_client) + messages = [ + Message(role="system", content="You are helpful"), + Message(role="user", content="Hi"), + ] + await client.complete(messages, []) + + call_args = runtime_client.chat_completions.call_args + openai_messages = call_args.args[0] + assert openai_messages[0]["role"] == "system" + assert openai_messages[0]["content"] == "You are helpful" + assert openai_messages[1]["role"] == "user" + + +# --------------------------------------------------------------------------- +# create_llm_client factory +# --------------------------------------------------------------------------- + + +class TestCreateLLMClient: + + async def test_factory_with_mock_builder(self) -> None: + mock_runtime_client = AsyncMock() + mock_runtime_client.chat_completions.return_value = _make_fake_response() + + mock_builder = AsyncMock() + mock_builder.get_llm.return_value = mock_runtime_client + + mock_config = MagicMock() + + with patch("nat.builder.builder.Builder.current", return_value=mock_builder): + client = await create_llm_client( + mock_config, + llm_name="test-llm", + ) + + assert isinstance(client, BuilderLLMClient) + mock_builder.add_llm.assert_called_once_with("test-llm", mock_config) + mock_builder.get_llm.assert_called_once() + + async def test_factory_default_name(self) -> None: + mock_builder = AsyncMock() + mock_builder.get_llm.return_value = AsyncMock() + + mock_config = MagicMock() + + with patch("nat.builder.builder.Builder.current", return_value=mock_builder): + await create_llm_client(mock_config) + + mock_builder.add_llm.assert_called_once_with("default", mock_config) + + async def test_factory_returns_working_client(self) -> None: + mock_runtime_client = AsyncMock() + mock_runtime_client.chat_completions.return_value = _make_fake_response(content="Built!") + + mock_builder = AsyncMock() + mock_builder.get_llm.return_value = mock_runtime_client + + mock_config = MagicMock() + + with patch("nat.builder.builder.Builder.current", return_value=mock_builder): + client = await create_llm_client(mock_config) + messages = [Message(role="user", content="test")] + response = await client.complete(messages, []) + + assert response.message.content == "Built!" diff --git a/packages/nvidia_nat_runtime/tests/sdk/test_conversation.py b/packages/nvidia_nat_runtime/tests/sdk/test_conversation.py new file mode 100644 index 0000000000..b31086a3e0 --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/test_conversation.py @@ -0,0 +1,1212 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for nat.sdk.conversation — Conversation, ConversationState, ConversationRunner.""" + +from pathlib import Path +from typing import Any + +import pytest + +from nat.data_models.skill import Skill +from nat.data_models.workspace import ActionResult +from nat.data_models.workspace import ActionStatus +from nat.sdk.agent.agent import Agent +from nat.sdk.agent.state import AgentStatus +from nat.sdk.conversation.conversation import Conversation +from nat.sdk.conversation.state import ConversationState +from nat.sdk.conversation.state import ConversationStatus +from nat.sdk.conversation.state import UsageStats +from nat.sdk.event.event import ActionEvent +from nat.sdk.event.event import Event +from nat.sdk.event.event import MessageEvent +from nat.sdk.event.event import ObservationEvent +from nat.sdk.event.event import SystemPromptEvent +from nat.sdk.llm.client import LLMClient +from nat.sdk.llm.message import LLMResponse +from nat.sdk.llm.message import Message +from nat.sdk.llm.message import TokenUsage +from nat.sdk.llm.message import ToolCall +from nat.sdk.tool.result import ToolResult +from nat.sdk.tool.tool import Tool +from nat.workspace.types import SkillSummary +from nat.workspace.types import TypeSchema +from nat.workspace.types import WorkspaceActionSchema +from nat.workspace.types import WorkspaceBase + +# --------------------------------------------------------------------------- +# UsageStats +# --------------------------------------------------------------------------- + + +class TestUsageStats: + + def test_defaults(self) -> None: + s = UsageStats() + assert s.total_tokens == 0 + assert s.prompt_tokens == 0 + assert s.completion_tokens == 0 + assert s.llm_calls == 0 + + def test_record_with_usage(self) -> None: + s = UsageStats() + s.record(TokenUsage(prompt_tokens=10, completion_tokens=5, total_tokens=15)) + assert s.llm_calls == 1 + assert s.total_tokens == 15 + assert s.prompt_tokens == 10 + + def test_record_none(self) -> None: + s = UsageStats() + s.record(None) + assert s.llm_calls == 1 + assert s.total_tokens == 0 + + def test_accumulate(self) -> None: + s = UsageStats() + s.record(TokenUsage(prompt_tokens=10, completion_tokens=5, total_tokens=15)) + s.record(TokenUsage(prompt_tokens=20, completion_tokens=10, total_tokens=30)) + assert s.llm_calls == 2 + assert s.total_tokens == 45 + assert s.prompt_tokens == 30 + + +# --------------------------------------------------------------------------- +# ConversationState +# --------------------------------------------------------------------------- + + +class TestConversationState: + + def test_defaults(self) -> None: + state = ConversationState() + assert len(state.id) == 36 # UUID + assert len(state.events) == 0 + assert state.agent_state.status == AgentStatus.IDLE + assert state.status == ConversationStatus.ACTIVE + assert state.stats.llm_calls == 0 + assert state.activated_skills == [] + + def test_unique_ids(self) -> None: + s1 = ConversationState() + s2 = ConversationState() + assert s1.id != s2.id + + +# --------------------------------------------------------------------------- +# Fake LLM client for conversation tests +# --------------------------------------------------------------------------- + + +class FakeLLMClient(LLMClient): + """LLM client that returns preconfigured responses in order.""" + + def __init__(self, responses: list[LLMResponse]) -> None: + self._responses = list(responses) + self._call_count = 0 + self.call_log: list[dict[str, Any]] = [] + + async def complete( + self, + messages: list[Message], + tools: list[Tool] = (), + **kwargs: Any, + ) -> LLMResponse: + self.call_log.append({ + "messages": list(messages), + "tools": list(tools), + }) + idx = min(self._call_count, len(self._responses) - 1) + self._call_count += 1 + return self._responses[idx] + + +def _text_response(content: str) -> LLMResponse: + return LLMResponse( + message=Message(role="assistant", content=content), + usage=TokenUsage(prompt_tokens=10, completion_tokens=5, total_tokens=15), + ) + + +def _tool_call_response( + tool_name: str, + arguments: dict[str, Any], + tool_call_id: str = "tc-1", +) -> LLMResponse: + return LLMResponse( + message=Message( + role="assistant", + content="", + tool_calls=[ToolCall(id=tool_call_id, name=tool_name, arguments=arguments)], + ), + usage=TokenUsage(prompt_tokens=10, completion_tokens=5, total_tokens=15), + ) + + +# --------------------------------------------------------------------------- +# Mock Workspace implementing WorkspaceBase +# --------------------------------------------------------------------------- + + +class MockWorkspace(WorkspaceBase): + """A mock workspace for testing that exposes read_file and write_file actions.""" + + def __init__(self, files: dict[str, str] | None = None) -> None: + self._files = dict(files or {}) + + async def get_actions(self) -> list[WorkspaceActionSchema]: + return [ + WorkspaceActionSchema( + name="read_file", + description="Read a file", + parameters=[TypeSchema(type="path", description="File path")], + result=TypeSchema(type="string", description="File content"), + ), + WorkspaceActionSchema( + name="write_file", + description="Write a file", + parameters=[ + TypeSchema(type="path", description="File path"), + TypeSchema(type="content", description="Content to write"), + ], + result=TypeSchema(type="string", description="Confirmation"), + ), + ] + + async def get_skills(self) -> list[SkillSummary]: + return [] + + async def read_skill(self, skill_name: str) -> Skill | None: + return None + + async def create_skill(self, skill: Skill) -> ActionResult: + return ActionResult(status=ActionStatus.SUCCESS, output="created") + + async def execute_action( + self, + action_name: str, + args: dict[str, Any], + model_metadata: dict[str, Any] | None = None, + ) -> ActionResult: + if action_name == "read_file": + path = args.get("path", "") + content = self._files.get(path) + if content is not None: + return ActionResult(status=ActionStatus.SUCCESS, output=content) + return ActionResult(status=ActionStatus.FAILURE, error_message=f"File not found: {path}") + if action_name == "write_file": + path = args.get("path", "") + content = args.get("content", "") + self._files[path] = content + return ActionResult(status=ActionStatus.SUCCESS, output=f"Wrote {len(content)} bytes") + return ActionResult(status=ActionStatus.FAILURE, error_message=f"Unknown action: {action_name}") + + async def upload_file(self, file_path: Path, destination_path: Path) -> ActionResult: + return ActionResult(status=ActionStatus.SUCCESS) + + async def delete_file(self, file_path: Path) -> ActionResult: + return ActionResult(status=ActionStatus.SUCCESS) + + async def download_file(self, file_path: Path) -> ActionResult: + return ActionResult(status=ActionStatus.SUCCESS) + + async def upload_directory(self, directory_path: Path, destination_path: Path) -> ActionResult: + return ActionResult(status=ActionStatus.SUCCESS) + + async def download_directory(self, directory_path: Path, destination_path: Path) -> ActionResult: + return ActionResult(status=ActionStatus.SUCCESS) + + async def delete_directory(self, directory_path: Path) -> ActionResult: + return ActionResult(status=ActionStatus.SUCCESS) + + +# --------------------------------------------------------------------------- +# Conversation — basic send_message +# --------------------------------------------------------------------------- + + +class TestConversationSendMessage: + + async def test_simple_text_response(self) -> None: + client = FakeLLMClient([_text_response("Hello!")]) + agent = Agent(system_prompt="You are helpful.", ) + conv = Conversation(agent=agent, client=client) + response = await conv.send_message("Hi") + + assert response.role == "assistant" + assert response.content == "Hello!" + assert conv.state.stats.llm_calls == 1 + + async def test_events_recorded(self) -> None: + client = FakeLLMClient([_text_response("Reply")]) + agent = Agent(system_prompt="Sys") + conv = Conversation(agent=agent, client=client) + await conv.send_message("User input") + + events = conv.state.events.events + types = [type(e).__name__ for e in events] + assert "SystemPromptEvent" in types + assert "MessageEvent" in types # user + agent messages + + async def test_system_prompt_in_events(self) -> None: + client = FakeLLMClient([_text_response("ok")]) + agent = Agent(system_prompt="Be nice", ) + conv = Conversation(agent=agent, client=client) + await conv.send_message("test") + + sys_events = [e for e in conv.state.events if isinstance(e, SystemPromptEvent)] + assert len(sys_events) == 1 + assert "Be nice" in sys_events[0].content + + async def test_event_callback(self) -> None: + collected: list[Event] = [] + client = FakeLLMClient([_text_response("Hi")]) + agent = Agent() + conv = Conversation(agent=agent, client=client, on_event=collected.append) + await conv.send_message("test") + + assert len(collected) > 0 + # Should include at least user message and agent message + msg_events = [e for e in collected if isinstance(e, MessageEvent)] + assert len(msg_events) >= 2 + + async def test_no_system_prompt_when_empty(self) -> None: + client = FakeLLMClient([_text_response("ok")]) + agent = Agent() # no system_prompt + conv = Conversation(agent=agent, client=client) + await conv.send_message("test") + + sys_events = [e for e in conv.state.events if isinstance(e, SystemPromptEvent)] + assert len(sys_events) == 0 + + +# --------------------------------------------------------------------------- +# Conversation — tool calling +# --------------------------------------------------------------------------- + + +class TestConversationToolCalling: + + async def test_single_tool_call(self) -> None: + + async def _add(a: int, b: int) -> ToolResult: + return ToolResult(output=a + b) + + add_tool = Tool( + name="add", + description="Add numbers", + parameters={ + "type": "object", + "properties": { + "a": { + "type": "integer" + }, + "b": { + "type": "integer" + }, + }, + }, + execute=_add, + ) + + client = FakeLLMClient([ + _tool_call_response("add", { + "a": 2, "b": 3 + }), + _text_response("The answer is 5"), + ]) + agent = Agent(tools=[add_tool]) + conv = Conversation(agent=agent, client=client) + response = await conv.send_message("What is 2+3?") + + assert response.content == "The answer is 5" + assert conv.state.stats.llm_calls == 2 + + # Verify events include action and observation + action_events = [e for e in conv.state.events if isinstance(e, ActionEvent)] + obs_events = [e for e in conv.state.events if isinstance(e, ObservationEvent)] + assert len(action_events) == 1 + assert action_events[0].tool_name == "add" + assert len(obs_events) == 1 + assert obs_events[0].output == 5 + + async def test_tool_error(self) -> None: + + async def _fail() -> ToolResult: + return ToolResult(error="tool broke") + + fail_tool = Tool(name="fail", description="Fails", execute=_fail) + + client = FakeLLMClient([ + _tool_call_response("fail", {}), + _text_response("Sorry, the tool failed."), + ]) + agent = Agent(tools=[fail_tool]) + conv = Conversation(agent=agent, client=client) + await conv.send_message("Do it") + + obs_events = [e for e in conv.state.events if isinstance(e, ObservationEvent)] + assert len(obs_events) == 1 + assert obs_events[0].is_error + assert "tool broke" in obs_events[0].error + + async def test_unknown_tool(self) -> None: + client = FakeLLMClient([ + _tool_call_response("nonexistent", {}), + _text_response("I don't have that tool."), + ]) + agent = Agent() + conv = Conversation(agent=agent, client=client) + await conv.send_message("test") + + obs_events = [e for e in conv.state.events if isinstance(e, ObservationEvent)] + assert len(obs_events) == 1 + assert obs_events[0].is_error + assert "Unknown tool" in obs_events[0].error + + async def test_tool_exception(self) -> None: + + async def _explode() -> ToolResult: + raise RuntimeError("kaboom") + + explode_tool = Tool(name="explode", description="Explodes", execute=_explode) + + client = FakeLLMClient([ + _tool_call_response("explode", {}), + _text_response("Something went wrong."), + ]) + agent = Agent(tools=[explode_tool]) + conv = Conversation(agent=agent, client=client) + await conv.send_message("boom") + + obs_events = [e for e in conv.state.events if isinstance(e, ObservationEvent)] + assert len(obs_events) == 1 + assert obs_events[0].is_error + assert "kaboom" in obs_events[0].error + + async def test_multiple_tool_calls_in_sequence(self) -> None: + + async def _mul(x: int, y: int) -> ToolResult: + return ToolResult(output=x * y) + + mul_tool = Tool( + name="multiply", + description="Multiply", + parameters={ + "type": "object", + "properties": { + "x": { + "type": "integer" + }, + "y": { + "type": "integer" + }, + }, + }, + execute=_mul, + ) + + client = FakeLLMClient([ + _tool_call_response("multiply", { + "x": 2, "y": 3 + }, "tc-1"), + _tool_call_response("multiply", { + "x": 6, "y": 7 + }, "tc-2"), + _text_response("2*3=6, then 6*7=42"), + ]) + agent = Agent(tools=[mul_tool]) + conv = Conversation(agent=agent, client=client) + await conv.send_message("Chain multiply") + + assert conv.state.stats.llm_calls == 3 + action_events = [e for e in conv.state.events if isinstance(e, ActionEvent)] + assert len(action_events) == 2 + + +# --------------------------------------------------------------------------- +# Conversation — max iterations +# --------------------------------------------------------------------------- + + +class TestConversationMaxIterations: + + async def test_max_iterations_stop(self) -> None: + """Agent should stop after max_iterations even if still calling tools.""" + + async def _noop() -> ToolResult: + return ToolResult(output="ok") + + noop = Tool(name="noop", description="Noop", execute=_noop) + + # Return infinite tool calls + client = FakeLLMClient([_tool_call_response("noop", {})] * 10 + [_text_response("done")]) + agent = Agent(tools=[noop], max_iterations=3) + conv = Conversation(agent=agent, client=client) + await conv.send_message("loop forever") + + assert conv.state.agent_state.status == AgentStatus.MAX_ITERATIONS + assert conv.state.stats.llm_calls <= 3 + + +# --------------------------------------------------------------------------- +# Conversation — workspace integration +# --------------------------------------------------------------------------- + + +class TestConversationWithWorkspace: + """Workspace tools are now pre-built and passed via agent.tools. + + The Conversation no longer auto-discovers workspace actions; instead, + users should use ``Tool.from_function_group_config(WorkspaceActionsConfig())`` + or build tools manually and pass them as ``agent.tools``. + """ + + @staticmethod + def _make_workspace_tools(ws: MockWorkspace) -> list[Tool]: + """Build SDK Tools wrapping a MockWorkspace's actions.""" + + async def _read_file(path: str = "") -> ToolResult: + result = await ws.execute_action("read_file", {"path": path}) + return ToolResult.from_action_result(result) + + async def _write_file(path: str = "", content: str = "") -> ToolResult: + result = await ws.execute_action("write_file", {"path": path, "content": content}) + return ToolResult.from_action_result(result) + + return [ + Tool(name="read_file", description="Read a file", execute=_read_file), + Tool(name="write_file", description="Write a file", execute=_write_file), + ] + + async def test_workspace_tools_available(self) -> None: + client = FakeLLMClient([_text_response("ok")]) + ws = MockWorkspace() + tools = self._make_workspace_tools(ws) + agent = Agent(tools=tools) + conv = Conversation(agent=agent, client=client, workspace=ws) + await conv.initialize() + + # Workspace tools should be in the registry + assert "read_file" in conv.tools + assert "write_file" in conv.tools + + async def test_workspace_tool_execution(self) -> None: + ws = MockWorkspace(files={"test.txt": "file content"}) + tools = self._make_workspace_tools(ws) + + client = FakeLLMClient([ + _tool_call_response("read_file", {"path": "test.txt"}), + _text_response("File contains: file content"), + ]) + agent = Agent(tools=tools) + conv = Conversation(agent=agent, client=client, workspace=ws) + await conv.send_message("Read test.txt") + + obs_events = [e for e in conv.state.events if isinstance(e, ObservationEvent)] + assert len(obs_events) == 1 + assert obs_events[0].output == "file content" + + +# --------------------------------------------------------------------------- +# Conversation — skills +# --------------------------------------------------------------------------- + + +class TestConversationWithSkills: + + async def test_skills_in_system_prompt(self) -> None: + client = FakeLLMClient([_text_response("ok")]) + skill = Skill(name="code-review", description="Review code changes") + agent = Agent( + system_prompt="You are helpful.", + skills=[skill], + ) + conv = Conversation(agent=agent, client=client) + await conv.send_message("test") + + sys_events = [e for e in conv.state.events if isinstance(e, SystemPromptEvent)] + assert len(sys_events) == 1 + assert "" in sys_events[0].content + assert "code-review" in sys_events[0].content + + +# --------------------------------------------------------------------------- +# Conversation — context manager +# --------------------------------------------------------------------------- + + +class TestConversationContextManager: + + async def test_async_context_manager(self) -> None: + client = FakeLLMClient([_text_response("hi")]) + agent = Agent() + async with Conversation(agent=agent, client=client) as conv: + response = await conv.send_message("test") + assert response.content == "hi" + + async def test_initialize_idempotent(self) -> None: + client = FakeLLMClient([_text_response("ok")]) + agent = Agent(system_prompt="Sys") + conv = Conversation(agent=agent, client=client) + await conv.initialize() + await conv.initialize() # second call should be no-op + + sys_events = [e for e in conv.state.events if isinstance(e, SystemPromptEvent)] + assert len(sys_events) == 1 # only one system prompt + + +# --------------------------------------------------------------------------- +# Conversation — LLM client receives correct messages +# --------------------------------------------------------------------------- + + +class TestConversationMessagePassing: + + async def test_messages_passed_to_llm(self) -> None: + client = FakeLLMClient([_text_response("reply")]) + agent = Agent(system_prompt="System prompt here") + conv = Conversation(agent=agent, client=client) + await conv.send_message("User says hello") + + assert len(client.call_log) == 1 + messages = client.call_log[0]["messages"] + roles = [m.role for m in messages] + assert "system" in roles + assert "user" in roles + + async def test_tools_passed_to_llm(self) -> None: + t = Tool(name="search", description="Search") + client = FakeLLMClient([_text_response("ok")]) + agent = Agent(tools=[t]) + conv = Conversation(agent=agent, client=client) + await conv.send_message("test") + + tools = client.call_log[0]["tools"] + assert len(tools) == 1 + assert tools[0].name == "search" + + async def test_usage_stats_accumulated(self) -> None: + client = FakeLLMClient([ + _tool_call_response("noop", {}), + _text_response("done"), + ]) + + async def _noop() -> ToolResult: + return ToolResult(output="ok") + + noop = Tool(name="noop", description="Noop", execute=_noop) + agent = Agent(tools=[noop]) + conv = Conversation(agent=agent, client=client) + await conv.send_message("test") + + assert conv.state.stats.llm_calls == 2 + assert conv.state.stats.total_tokens == 30 # 15 * 2 + + +# --------------------------------------------------------------------------- +# ConversationRunner — new parameters (return_direct, handle_tool_errors, +# max_history, initial_messages) +# --------------------------------------------------------------------------- + + +class TestConversationRunnerExtensions: + """Tests for the extended ConversationRunner parameters.""" + + async def test_return_direct_stops_on_matching_tool(self) -> None: + """Runner stops and returns ObservationEvent when a return_direct tool completes.""" + from nat.sdk.conversation.runner import ConversationRunner + + async def _greet(name: str = "world") -> ToolResult: + return ToolResult(output=f"Hello, {name}!") + + greet = Tool( + name="greet", + description="Greet someone", + parameters={ + "type": "object", "properties": { + "name": { + "type": "string" + } + } + }, + execute=_greet, + ) + + client = FakeLLMClient([ + _tool_call_response("greet", {"name": "Alice"}), + ]) + agent = Agent(tools=[greet], max_iterations=5) + state = ConversationState() + state.agent_state.status = AgentStatus.RUNNING + + runner = ConversationRunner( + agent=agent, + client=client, + state=state, + tools={"greet": greet}, + return_direct_tools={"greet"}, + ) + event = await runner.run_until_done() + + assert isinstance(event, ObservationEvent) + assert event.output == "Hello, Alice!" + assert state.agent_state.status == AgentStatus.FINISHED + + async def test_return_direct_does_not_trigger_for_other_tools(self) -> None: + """Non-return_direct tools proceed normally through the loop.""" + from nat.sdk.conversation.runner import ConversationRunner + + async def _noop() -> ToolResult: + return ToolResult(output="ok") + + noop = Tool(name="noop", description="Noop", execute=_noop) + + client = FakeLLMClient([ + _tool_call_response("noop", {}), + _text_response("All done"), + ]) + agent = Agent(tools=[noop], max_iterations=5) + state = ConversationState() + state.agent_state.status = AgentStatus.RUNNING + + runner = ConversationRunner( + agent=agent, + client=client, + state=state, + tools={"noop": noop}, + return_direct_tools={"some_other_tool"}, + ) + event = await runner.run_until_done() + + assert isinstance(event, MessageEvent) + assert event.content == "All done" + + async def test_handle_tool_errors_false_raises(self) -> None: + """When handle_tool_errors=False, tool exceptions propagate.""" + from nat.sdk.conversation.runner import ConversationRunner + + async def _explode() -> ToolResult: + raise ValueError("kaboom") + + explode = Tool(name="explode", description="Explodes", execute=_explode) + + client = FakeLLMClient([_tool_call_response("explode", {})]) + agent = Agent(tools=[explode], max_iterations=5) + state = ConversationState() + state.agent_state.status = AgentStatus.RUNNING + + runner = ConversationRunner( + agent=agent, + client=client, + state=state, + tools={"explode": explode}, + handle_tool_errors=False, + ) + with pytest.raises(ValueError, match="kaboom"): + await runner.run_until_done() + + async def test_handle_tool_errors_true_continues(self) -> None: + """When handle_tool_errors=True, tool exceptions become error observations.""" + from nat.sdk.conversation.runner import ConversationRunner + + async def _explode() -> ToolResult: + raise ValueError("kaboom") + + explode = Tool(name="explode", description="Explodes", execute=_explode) + + client = FakeLLMClient([ + _tool_call_response("explode", {}), + _text_response("I see the error"), + ]) + agent = Agent(tools=[explode], max_iterations=5) + state = ConversationState() + state.agent_state.status = AgentStatus.RUNNING + + runner = ConversationRunner( + agent=agent, + client=client, + state=state, + tools={"explode": explode}, + handle_tool_errors=True, + ) + event = await runner.run_until_done() + + assert isinstance(event, MessageEvent) + assert event.content == "I see the error" + + obs_events = [e for e in state.events if isinstance(e, ObservationEvent)] + assert len(obs_events) == 1 + assert obs_events[0].is_error + assert "kaboom" in obs_events[0].error + + async def test_max_history_trims_messages(self) -> None: + """max_history limits the number of messages sent to the LLM.""" + from nat.sdk.conversation.runner import ConversationRunner + + client = FakeLLMClient([_text_response("ok")]) + agent = Agent(max_iterations=5) + state = ConversationState() + state.agent_state.status = AgentStatus.RUNNING + + # Pre-populate with initial messages to exceed the limit + initial_messages = [ + Message(role="system", content="sys"), + Message(role="user", content="msg1"), + Message(role="assistant", content="resp1"), + Message(role="user", content="msg2"), + Message(role="assistant", content="resp2"), + Message(role="user", content="msg3"), + ] + + runner = ConversationRunner( + agent=agent, + client=client, + state=state, + tools={}, + max_history=3, + initial_messages=initial_messages, + ) + await runner.step() + + # LLM should receive only the last 3 messages + assert len(client.call_log) == 1 + messages = client.call_log[0]["messages"] + assert len(messages) == 3 + # last 3 of [sys, msg1, resp1, msg2, resp2, msg3] = [msg2, resp2, msg3] + assert messages[0].content == "msg2" + assert messages[1].content == "resp2" + assert messages[2].content == "msg3" + + async def test_initial_messages_prepended(self) -> None: + """initial_messages are prepended before event-derived messages.""" + from nat.sdk.conversation.runner import ConversationRunner + + client = FakeLLMClient([_text_response("reply")]) + agent = Agent(max_iterations=5) + state = ConversationState() + state.agent_state.status = AgentStatus.RUNNING + + initial = [ + Message(role="system", content="Be helpful"), + Message(role="user", content="Hello"), + ] + + runner = ConversationRunner( + agent=agent, + client=client, + state=state, + tools={}, + initial_messages=initial, + ) + await runner.step() + + messages = client.call_log[0]["messages"] + assert len(messages) == 2 + assert messages[0].role == "system" + assert messages[0].content == "Be helpful" + assert messages[1].role == "user" + assert messages[1].content == "Hello" + + +# --------------------------------------------------------------------------- +# Conversation — skill activation (read_skill tool) +# --------------------------------------------------------------------------- + + +class TestConversationSkillActivation: + """Tests for the read_skill tool and skill lifecycle.""" + + async def test_read_skill_tool_injected_when_skills_present(self) -> None: + """read_skill is auto-injected when the agent has skills.""" + client = FakeLLMClient([_text_response("ok")]) + skill = Skill(name="code-review", description="Review code changes") + agent = Agent(skills=[skill]) + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + assert "read_skill" in conv.tools + + async def test_read_skill_tool_absent_when_no_skills(self) -> None: + """read_skill is NOT injected when the agent has no skills.""" + client = FakeLLMClient([_text_response("ok")]) + agent = Agent() + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + assert "read_skill" not in conv.tools + + async def test_read_skill_unknown_name_returns_error(self) -> None: + """Calling read_skill with an unknown name returns an error string.""" + client = FakeLLMClient([_text_response("ok")]) + skill = Skill(name="code-review", description="Review code changes") + agent = Agent(skills=[skill]) + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + tool = conv.tools["read_skill"] + result = await tool(skill_name="nonexistent") + assert result.error is None # no exception, just a string output + assert "not found" in result.output + + async def test_read_skill_activates_skill(self) -> None: + """Calling read_skill on a valid skill marks it as activated.""" + client = FakeLLMClient([_text_response("ok")]) + skill = Skill(name="code-review", description="Review code changes", content="Do X then Y.") + agent = Agent(skills=[skill]) + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + tool = conv.tools["read_skill"] + result = await tool(skill_name="code-review") + + assert "code-review" in conv.state.activated_skills + assert "activated" in result.output + + async def test_read_skill_emits_system_prompt_event(self) -> None: + """Calling read_skill emits a SystemPromptEvent containing the full skills section.""" + collected: list[Event] = [] + client = FakeLLMClient([_text_response("ok")]) + skill = Skill(name="code-review", description="Review code", content="My instructions.") + agent = Agent(skills=[skill]) + conv = Conversation(agent=agent, client=client, on_event=collected.append) + await conv.initialize() + + tool = conv.tools["read_skill"] + await tool(skill_name="code-review") + + # The emitted event carries the full section, which + # includes for the now-activated skill. + skill_events = [e for e in collected if isinstance(e, SystemPromptEvent) and "My instructions" in e.content] + assert len(skill_events) == 1 + assert "" in skill_events[0].content + assert "My instructions" in skill_events[0].content + + async def test_read_skill_no_duplicate_activation(self) -> None: + """Calling read_skill twice for the same skill does not duplicate activated_skills.""" + client = FakeLLMClient([_text_response("ok")]) + skill = Skill(name="code-review", description="Review code") + agent = Agent(skills=[skill]) + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + tool = conv.tools["read_skill"] + await tool(skill_name="code-review") + await tool(skill_name="code-review") + + assert conv.state.activated_skills.count("code-review") == 1 + + async def test_allowed_tools_filtering(self) -> None: + """After activating a skill with allowed_tools, runner receives filtered tools.""" + + async def _search(q: str = "") -> ToolResult: + return ToolResult(output="results") + + async def _write(content: str = "") -> ToolResult: + return ToolResult(output="written") + + search_tool = Tool(name="search", description="Search", execute=_search) + write_tool = Tool(name="write_file", description="Write", execute=_write) + + # Skill restricts to only 'search' + skill = Skill(name="research", description="Research skill", allowed_tools=["search"]) + + client = FakeLLMClient([_text_response("done")]) + agent = Agent(tools=[search_tool, write_tool], skills=[skill]) + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + # Activate the skill + tool = conv.tools["read_skill"] + await tool(skill_name="research") + + # _effective_tools should filter to only search + read_skill + effective = conv._effective_tools() + assert "search" in effective + assert "read_skill" in effective + assert "write_file" not in effective + + async def test_no_allowed_tools_restriction_returns_all(self) -> None: + """Skill with no allowed_tools restriction keeps all tools available.""" + + async def _search(q: str = "") -> ToolResult: + return ToolResult(output="results") + + search_tool = Tool(name="search", description="Search", execute=_search) + # Skill with no allowed_tools restriction + skill = Skill(name="general", description="General skill") + + client = FakeLLMClient([_text_response("done")]) + agent = Agent(tools=[search_tool], skills=[skill]) + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + await conv.tools["read_skill"](skill_name="general") + + effective = conv._effective_tools() + assert "search" in effective + assert "read_skill" in effective + + +# --------------------------------------------------------------------------- +# Conversation — workspace skill sync +# --------------------------------------------------------------------------- + + +class MockWorkspaceWithSkills(MockWorkspace): + """MockWorkspace that returns skills from get_skills().""" + + def __init__(self, skill_names: list[str], **kwargs: Any) -> None: + super().__init__(**kwargs) + self._skill_names = skill_names + + async def get_skills(self) -> list[SkillSummary]: + return [SkillSummary(name=n, description=f"Skill {n}") for n in self._skill_names] + + async def read_skill(self, skill_name: str) -> Skill | None: + return None + + +class TestConversationWorkspaceSkillSync: + + async def test_workspace_skills_appear_in_skills(self) -> None: + """Skills returned by workspace.get_skills() are added to _skills.""" + client = FakeLLMClient([_text_response("ok")]) + ws = MockWorkspaceWithSkills(skill_names=["ws-skill"]) + agent = Agent() + conv = Conversation(agent=agent, client=client, workspace=ws) + await conv.initialize() + + assert "ws-skill" in conv.skills + + async def test_local_skills_take_precedence_over_workspace(self) -> None: + """Local skills (agent.skills) are not overwritten by workspace stubs.""" + client = FakeLLMClient([_text_response("ok")]) + ws = MockWorkspaceWithSkills(skill_names=["code-review"]) + local_skill = Skill(name="code-review", description="Local version", content="Local content.") + agent = Agent(skills=[local_skill]) + conv = Conversation(agent=agent, client=client, workspace=ws) + await conv.initialize() + + # Local skill should remain, content unchanged + assert conv.skills["code-review"].content == "Local content." + + async def test_workspace_skills_trigger_read_skill_tool(self) -> None: + """read_skill is injected when workspace skills are discovered.""" + client = FakeLLMClient([_text_response("ok")]) + ws = MockWorkspaceWithSkills(skill_names=["ws-skill"]) + agent = Agent() + conv = Conversation(agent=agent, client=client, workspace=ws) + await conv.initialize() + + assert "read_skill" in conv.tools + + +# --------------------------------------------------------------------------- +# Conversation — close() +# --------------------------------------------------------------------------- + + +class TestConversationClose: + + async def test_close_sets_completed_status(self) -> None: + """close() marks the conversation as COMPLETED.""" + client = FakeLLMClient([_text_response("ok")]) + agent = Agent() + conv = Conversation(agent=agent, client=client) + await conv.close() + + assert conv.state.status == ConversationStatus.COMPLETED + + async def test_context_manager_calls_close(self) -> None: + """Exiting the async context manager sets status to COMPLETED.""" + client = FakeLLMClient([_text_response("ok")]) + agent = Agent() + async with Conversation(agent=agent, client=client) as conv: + pass + + assert conv.state.status == ConversationStatus.COMPLETED + + +# --------------------------------------------------------------------------- +# Conversation — runtime skill mutations (add / remove / update) +# --------------------------------------------------------------------------- + + +class TestConversationSkillMutations: + """Tests that add_skill / remove_skill / update_skill keep the LLM context fresh.""" + + # -- add_skill -- + async def test_add_skill_appears_in_skills(self) -> None: + client = FakeLLMClient([_text_response("ok")]) + agent = Agent() + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + new_skill = Skill(name="new-skill", description="Newly added") + conv.add_skill(new_skill) + + assert "new-skill" in conv.skills + + async def test_add_skill_emits_system_prompt_update(self) -> None: + collected: list[Event] = [] + client = FakeLLMClient([_text_response("ok")]) + agent = Agent() + conv = Conversation(agent=agent, client=client, on_event=collected.append) + await conv.initialize() + + new_skill = Skill(name="new-skill", description="Newly added") + conv.add_skill(new_skill) + + update_events = [e for e in collected if isinstance(e, SystemPromptEvent) and "new-skill" in e.content] + assert len(update_events) == 1 + assert "" in update_events[0].content + + async def test_add_skill_after_init_injects_read_skill_tool(self) -> None: + """read_skill is added to tools when the first skill is added post-init.""" + client = FakeLLMClient([_text_response("ok")]) + agent = Agent() # no skills initially + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + assert "read_skill" not in conv.tools + + conv.add_skill(Skill(name="late-skill", description="Added late")) + + assert "read_skill" in conv.tools + + async def test_add_skill_before_init_no_event(self) -> None: + """add_skill before initialize() registers the skill but emits no event yet.""" + collected: list[Event] = [] + client = FakeLLMClient([_text_response("ok")]) + agent = Agent() + conv = Conversation(agent=agent, client=client, on_event=collected.append) + + conv.add_skill(Skill(name="early-skill", description="Added early")) + + assert "early-skill" in conv.skills + assert not any(isinstance(e, SystemPromptEvent) for e in collected) + + async def test_add_skill_before_init_appears_in_initial_prompt(self) -> None: + """A skill added before initialize() shows up in the initial system prompt.""" + collected: list[Event] = [] + client = FakeLLMClient([_text_response("ok")]) + agent = Agent() + conv = Conversation(agent=agent, client=client, on_event=collected.append) + + conv.add_skill(Skill(name="pre-skill", description="Added before init")) + await conv.initialize() + + init_events = [e for e in collected if isinstance(e, SystemPromptEvent)] + assert len(init_events) == 1 + assert "pre-skill" in init_events[0].content + + # -- remove_skill -- + + async def test_remove_skill_not_in_skills(self) -> None: + client = FakeLLMClient([_text_response("ok")]) + skill = Skill(name="old-skill", description="Will be removed") + agent = Agent(skills=[skill]) + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + conv.remove_skill("old-skill") + + assert "old-skill" not in conv.skills + + async def test_remove_skill_emits_system_prompt_update(self) -> None: + collected: list[Event] = [] + client = FakeLLMClient([_text_response("ok")]) + skill_a = Skill(name="skill-a", description="Keep this") + skill_b = Skill(name="skill-b", description="Remove this") + agent = Agent(skills=[skill_a, skill_b]) + conv = Conversation(agent=agent, client=client, on_event=collected.append) + await conv.initialize() + + conv.remove_skill("skill-b") + + # The update event should list only the remaining skill + update_events = [ + e for e in collected + if isinstance(e, SystemPromptEvent) and "skill-a" in e.content and "skill-b" not in e.content + ] + assert len(update_events) == 1 + + async def test_remove_last_skill_drops_read_skill_tool(self) -> None: + client = FakeLLMClient([_text_response("ok")]) + skill = Skill(name="solo-skill", description="Only skill") + agent = Agent(skills=[skill]) + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + assert "read_skill" in conv.tools + conv.remove_skill("solo-skill") + assert "read_skill" not in conv.tools + + async def test_remove_nonexistent_skill_is_noop(self) -> None: + """Removing a skill that doesn't exist does not raise.""" + client = FakeLLMClient([_text_response("ok")]) + agent = Agent() + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + conv.remove_skill("phantom-skill") # should not raise + + # -- update_skill -- + + async def test_update_skill_replaces_definition(self) -> None: + client = FakeLLMClient([_text_response("ok")]) + original = Skill(name="my-skill", description="Original", content="Old body.") + agent = Agent(skills=[original]) + conv = Conversation(agent=agent, client=client) + await conv.initialize() + + updated = Skill(name="my-skill", description="Updated", content="New body.") + conv.update_skill(updated) + + assert conv.skills["my-skill"].description == "Updated" + assert conv.skills["my-skill"].content == "New body." + + async def test_update_skill_emits_system_prompt_update(self) -> None: + collected: list[Event] = [] + client = FakeLLMClient([_text_response("ok")]) + original = Skill(name="my-skill", description="Original") + agent = Agent(skills=[original]) + conv = Conversation(agent=agent, client=client, on_event=collected.append) + await conv.initialize() + + conv.update_skill(Skill(name="my-skill", description="Updated description")) + + update_events = [ + e for e in collected if isinstance(e, SystemPromptEvent) and "Updated description" in e.content + ] + assert len(update_events) == 1 + + async def test_update_activated_skill_emits_new_body(self) -> None: + """Updating an already-activated skill emits a SystemPromptEvent with new body.""" + collected: list[Event] = [] + client = FakeLLMClient([_text_response("ok")]) + original = Skill(name="my-skill", description="Skill", content="Old body.") + agent = Agent(skills=[original]) + conv = Conversation(agent=agent, client=client, on_event=collected.append) + await conv.initialize() + + # Activate the skill + await conv.tools["read_skill"](skill_name="my-skill") + + # Now update with new content + updated = Skill(name="my-skill", description="Skill", content="New body.") + conv.update_skill(updated) + + update_events = [e for e in collected if isinstance(e, SystemPromptEvent) and "New body." in e.content] + assert len(update_events) >= 1 diff --git a/packages/nvidia_nat_runtime/tests/sdk/test_event.py b/packages/nvidia_nat_runtime/tests/sdk/test_event.py new file mode 100644 index 0000000000..ec5155383b --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/test_event.py @@ -0,0 +1,224 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for nat.sdk.event.event — Event base and concrete types.""" + +from datetime import UTC + +from nat.sdk.event.event import ActionEvent +from nat.sdk.event.event import ErrorEvent +from nat.sdk.event.event import Event +from nat.sdk.event.event import EventSource +from nat.sdk.event.event import MessageEvent +from nat.sdk.event.event import ObservationEvent +from nat.sdk.event.event import SystemPromptEvent + +# --------------------------------------------------------------------------- +# EventSource enum +# --------------------------------------------------------------------------- + + +class TestEventSource: + + def test_values(self) -> None: + assert EventSource.USER == "user" + assert EventSource.AGENT == "agent" + assert EventSource.SYSTEM == "system" + + def test_membership(self) -> None: + assert "user" in EventSource.__members__.values() + + +# --------------------------------------------------------------------------- +# Event base +# --------------------------------------------------------------------------- + + +class TestEvent: + + def test_default_id_is_uuid(self) -> None: + e = Event() + assert len(e.id) == 36 # UUID format + assert "-" in e.id + + def test_unique_ids(self) -> None: + e1 = Event() + e2 = Event() + assert e1.id != e2.id + + def test_default_timestamp_is_utc(self) -> None: + e = Event() + assert e.timestamp.tzinfo == UTC + + def test_default_source_is_system(self) -> None: + e = Event() + assert e.source == EventSource.SYSTEM + + def test_custom_source(self) -> None: + e = Event(source=EventSource.USER) + assert e.source == EventSource.USER + + def test_frozen(self) -> None: + e = Event() + try: + e.id = "new-id" # type: ignore[misc] + assert False, "Should have raised" + except AttributeError: + pass + + +# --------------------------------------------------------------------------- +# SystemPromptEvent +# --------------------------------------------------------------------------- + + +class TestSystemPromptEvent: + + def test_defaults(self) -> None: + e = SystemPromptEvent() + assert e.source == EventSource.SYSTEM + assert e.content == "" + + def test_with_content(self) -> None: + e = SystemPromptEvent(content="You are a helpful assistant.") + assert e.content == "You are a helpful assistant." + + def test_source_always_system(self) -> None: + e = SystemPromptEvent() + assert e.source == EventSource.SYSTEM + + +# --------------------------------------------------------------------------- +# MessageEvent +# --------------------------------------------------------------------------- + + +class TestMessageEvent: + + def test_user_message(self) -> None: + e = MessageEvent(source=EventSource.USER, content="Hello", role="user") + assert e.source == EventSource.USER + assert e.content == "Hello" + assert e.role == "user" + + def test_assistant_message(self) -> None: + e = MessageEvent( + source=EventSource.AGENT, + content="Hi there!", + role="assistant", + ) + assert e.source == EventSource.AGENT + assert e.role == "assistant" + + def test_default_role(self) -> None: + e = MessageEvent() + assert e.role == "user" + + def test_empty_content(self) -> None: + e = MessageEvent() + assert e.content == "" + + +# --------------------------------------------------------------------------- +# ActionEvent +# --------------------------------------------------------------------------- + + +class TestActionEvent: + + def test_defaults(self) -> None: + e = ActionEvent() + assert e.source == EventSource.AGENT + assert e.tool_name == "" + assert e.arguments == {} + assert e.thought is None + assert e.llm_response_id is None + + def test_with_fields(self) -> None: + e = ActionEvent( + tool_name="search", + tool_call_id="tc-1", + arguments={"query": "test"}, + thought="I should search", + llm_response_id="resp-1", + ) + assert e.tool_name == "search" + assert e.tool_call_id == "tc-1" + assert e.arguments == {"query": "test"} + assert e.thought == "I should search" + assert e.llm_response_id == "resp-1" + + def test_source_always_agent(self) -> None: + e = ActionEvent() + assert e.source == EventSource.AGENT + + def test_tool_call_id_auto_generated(self) -> None: + e1 = ActionEvent() + e2 = ActionEvent() + assert e1.tool_call_id != e2.tool_call_id + + +# --------------------------------------------------------------------------- +# ObservationEvent +# --------------------------------------------------------------------------- + + +class TestObservationEvent: + + def test_defaults(self) -> None: + e = ObservationEvent() + assert e.source == EventSource.SYSTEM + assert e.tool_call_id == "" + assert e.tool_name == "" + assert e.output is None + assert e.error is None + assert e.is_error is False + + def test_success(self) -> None: + e = ObservationEvent( + tool_call_id="tc-1", + tool_name="search", + output="found it", + ) + assert e.output == "found it" + assert e.is_error is False + + def test_error(self) -> None: + e = ObservationEvent( + tool_call_id="tc-1", + tool_name="search", + error="not found", + is_error=True, + ) + assert e.error == "not found" + assert e.is_error is True + + +# --------------------------------------------------------------------------- +# ErrorEvent +# --------------------------------------------------------------------------- + + +class TestErrorEvent: + + def test_defaults(self) -> None: + e = ErrorEvent() + assert e.source == EventSource.SYSTEM + assert e.error == "" + assert e.recoverable is True + + def test_non_recoverable(self) -> None: + e = ErrorEvent(error="fatal", recoverable=False) + assert e.error == "fatal" + assert e.recoverable is False diff --git a/packages/nvidia_nat_runtime/tests/sdk/test_event_log.py b/packages/nvidia_nat_runtime/tests/sdk/test_event_log.py new file mode 100644 index 0000000000..8b0e82472c --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/test_event_log.py @@ -0,0 +1,220 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for nat.sdk.event.log — EventLog.""" + +from nat.sdk.event.event import ActionEvent +from nat.sdk.event.event import EventSource +from nat.sdk.event.event import MessageEvent +from nat.sdk.event.event import ObservationEvent +from nat.sdk.event.event import SystemPromptEvent +from nat.sdk.event.log import EventLog + + +class TestEventLogBasics: + + def test_empty(self) -> None: + log = EventLog() + assert len(log) == 0 + assert list(log) == [] + + def test_append_and_len(self) -> None: + log = EventLog() + log.append(MessageEvent(content="hi")) + assert len(log) == 1 + + def test_extend(self) -> None: + log = EventLog() + log.extend([MessageEvent(content="a"), MessageEvent(content="b")]) + assert len(log) == 2 + + def test_iteration(self) -> None: + log = EventLog() + e1 = MessageEvent(content="first") + e2 = MessageEvent(content="second") + log.append(e1) + log.append(e2) + assert list(log) == [e1, e2] + + def test_getitem(self) -> None: + log = EventLog() + e = MessageEvent(content="test") + log.append(e) + assert log[0] is e + + def test_events_returns_copy(self) -> None: + log = EventLog() + log.append(MessageEvent(content="test")) + events = log.events + events.clear() + assert len(log) == 1 + + +class TestEventLogUnmatchedActions: + + def test_no_actions(self) -> None: + log = EventLog() + log.append(MessageEvent(content="hi")) + assert log.get_unmatched_actions() == [] + + def test_unmatched_action(self) -> None: + log = EventLog() + action = ActionEvent(tool_name="search", tool_call_id="tc-1") + log.append(action) + unmatched = log.get_unmatched_actions() + assert len(unmatched) == 1 + assert unmatched[0].tool_call_id == "tc-1" + + def test_matched_action(self) -> None: + log = EventLog() + log.append(ActionEvent(tool_name="search", tool_call_id="tc-1")) + log.append(ObservationEvent(tool_call_id="tc-1", tool_name="search", output="ok")) + assert log.get_unmatched_actions() == [] + + def test_partial_match(self) -> None: + log = EventLog() + log.append(ActionEvent(tool_name="a", tool_call_id="tc-1")) + log.append(ActionEvent(tool_name="b", tool_call_id="tc-2")) + log.append(ObservationEvent(tool_call_id="tc-1", tool_name="a", output="ok")) + unmatched = log.get_unmatched_actions() + assert len(unmatched) == 1 + assert unmatched[0].tool_call_id == "tc-2" + + +class TestEventLogToMessages: + + def test_system_prompt(self) -> None: + log = EventLog() + log.append(SystemPromptEvent(content="Be helpful")) + messages = log.to_messages() + assert len(messages) == 1 + assert messages[0].role == "system" + assert messages[0].content == "Be helpful" + + def test_user_message(self) -> None: + log = EventLog() + log.append(MessageEvent(source=EventSource.USER, content="Hi", role="user")) + messages = log.to_messages() + assert len(messages) == 1 + assert messages[0].role == "user" + assert messages[0].content == "Hi" + + def test_assistant_message(self) -> None: + log = EventLog() + log.append(MessageEvent( + source=EventSource.AGENT, + content="Hello!", + role="assistant", + )) + messages = log.to_messages() + assert len(messages) == 1 + assert messages[0].role == "assistant" + + def test_action_and_observation(self) -> None: + log = EventLog() + log.append( + ActionEvent( + tool_name="add", + tool_call_id="tc-1", + arguments={ + "a": 1, "b": 2 + }, + thought="Let me add", + llm_response_id="resp-1", + )) + log.append(ObservationEvent(tool_call_id="tc-1", tool_name="add", output="3")) + messages = log.to_messages() + + # Should produce: assistant message with tool_calls, then tool result + assert len(messages) == 2 + assert messages[0].role == "assistant" + assert len(messages[0].tool_calls) == 1 + assert messages[0].tool_calls[0].name == "add" + assert messages[0].content == "Let me add" + + assert messages[1].role == "tool" + assert messages[1].tool_call_id == "tc-1" + assert messages[1].content == "3" + + def test_parallel_tool_calls_grouped(self) -> None: + """Multiple ActionEvents with the same llm_response_id become one assistant message.""" + log = EventLog() + log.append( + ActionEvent( + tool_name="a", + tool_call_id="tc-1", + arguments={}, + thought="Doing both", + llm_response_id="resp-1", + )) + log.append(ActionEvent( + tool_name="b", + tool_call_id="tc-2", + arguments={}, + llm_response_id="resp-1", + )) + log.append(ObservationEvent(tool_call_id="tc-1", tool_name="a", output="r1")) + log.append(ObservationEvent(tool_call_id="tc-2", tool_name="b", output="r2")) + + messages = log.to_messages() + # 1 assistant message with 2 tool_calls + 2 tool results + assert len(messages) == 3 + assert messages[0].role == "assistant" + assert len(messages[0].tool_calls) == 2 + assert messages[1].role == "tool" + assert messages[2].role == "tool" + + def test_error_observation(self) -> None: + log = EventLog() + log.append(ActionEvent( + tool_name="fail", + tool_call_id="tc-1", + arguments={}, + llm_response_id="resp-1", + )) + log.append(ObservationEvent( + tool_call_id="tc-1", + tool_name="fail", + error="boom", + is_error=True, + )) + messages = log.to_messages() + assert messages[1].role == "tool" + assert messages[1].content == "boom" + + def test_full_conversation_flow(self) -> None: + """System prompt -> user message -> tool call -> observation -> assistant response.""" + log = EventLog() + log.append(SystemPromptEvent(content="You are helpful")) + log.append(MessageEvent(source=EventSource.USER, content="Add 1+2", role="user")) + log.append( + ActionEvent( + tool_name="add", + tool_call_id="tc-1", + arguments={ + "a": 1, "b": 2 + }, + thought="", + llm_response_id="resp-1", + )) + log.append(ObservationEvent(tool_call_id="tc-1", tool_name="add", output="3")) + log.append(MessageEvent( + source=EventSource.AGENT, + content="The answer is 3", + role="assistant", + )) + + messages = log.to_messages() + assert len(messages) == 5 + assert [m.role for m in messages] == ["system", "user", "assistant", "tool", "assistant"] diff --git a/packages/nvidia_nat_runtime/tests/sdk/test_message.py b/packages/nvidia_nat_runtime/tests/sdk/test_message.py new file mode 100644 index 0000000000..a7eafe0ec1 --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/test_message.py @@ -0,0 +1,159 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for nat.sdk.llm.message — Message, ToolCall, TokenUsage, LLMResponse.""" + +from pydantic import ValidationError + +from nat.sdk.llm.message import LLMResponse +from nat.sdk.llm.message import Message +from nat.sdk.llm.message import TokenUsage +from nat.sdk.llm.message import ToolCall + +# --------------------------------------------------------------------------- +# ToolCall +# --------------------------------------------------------------------------- + + +class TestToolCall: + + def test_creation(self) -> None: + tc = ToolCall(id="tc-1", name="search", arguments={"query": "test"}) + assert tc.id == "tc-1" + assert tc.name == "search" + assert tc.arguments == {"query": "test"} + + def test_default_arguments(self) -> None: + tc = ToolCall(id="tc-1", name="noop") + assert tc.arguments == {} + + def test_to_openai_dict(self) -> None: + tc = ToolCall(id="tc-1", name="search", arguments={"query": "hello"}) + d = tc.to_openai_dict() + assert d["id"] == "tc-1" + assert d["type"] == "function" + assert d["function"]["name"] == "search" + assert '"query"' in d["function"]["arguments"] + assert '"hello"' in d["function"]["arguments"] + + def test_frozen(self) -> None: + tc = ToolCall(id="tc-1", name="test") + try: + tc.id = "new" # type: ignore[misc] + assert False, "Should have raised" + except ValidationError: + pass + + +# --------------------------------------------------------------------------- +# Message +# --------------------------------------------------------------------------- + + +class TestMessage: + + def test_user_message(self) -> None: + m = Message(role="user", content="Hello") + assert m.role == "user" + assert m.content == "Hello" + assert m.tool_calls == [] + assert m.tool_call_id is None + + def test_assistant_message_with_tool_calls(self) -> None: + tc = ToolCall(id="tc-1", name="search", arguments={"q": "x"}) + m = Message(role="assistant", content="Searching...", tool_calls=[tc]) + assert len(m.tool_calls) == 1 + assert m.tool_calls[0].name == "search" + + def test_tool_result_message(self) -> None: + m = Message(role="tool", content="result data", tool_call_id="tc-1") + assert m.role == "tool" + assert m.tool_call_id == "tc-1" + + def test_to_openai_dict_simple(self) -> None: + m = Message(role="user", content="Hi") + d = m.to_openai_dict() + assert d == {"role": "user", "content": "Hi"} + + def test_to_openai_dict_with_tool_calls(self) -> None: + tc = ToolCall(id="tc-1", name="add", arguments={"a": 1}) + m = Message(role="assistant", content="", tool_calls=[tc]) + d = m.to_openai_dict() + assert "tool_calls" in d + assert len(d["tool_calls"]) == 1 + assert d["tool_calls"][0]["function"]["name"] == "add" + + def test_to_openai_dict_tool_result(self) -> None: + m = Message(role="tool", content="42", tool_call_id="tc-1") + d = m.to_openai_dict() + assert d["role"] == "tool" + assert d["tool_call_id"] == "tc-1" + assert d["content"] == "42" + + def test_to_openai_dict_no_extra_keys(self) -> None: + m = Message(role="system", content="Be nice") + d = m.to_openai_dict() + assert set(d.keys()) == {"role", "content"} + + +# --------------------------------------------------------------------------- +# TokenUsage +# --------------------------------------------------------------------------- + + +class TestTokenUsage: + + def test_defaults(self) -> None: + u = TokenUsage() + assert u.prompt_tokens == 0 + assert u.completion_tokens == 0 + assert u.total_tokens == 0 + assert u.cached_tokens == 0 + assert u.reasoning_tokens == 0 + + def test_custom_values(self) -> None: + u = TokenUsage( + prompt_tokens=100, + completion_tokens=50, + total_tokens=150, + cached_tokens=20, + reasoning_tokens=10, + ) + assert u.prompt_tokens == 100 + assert u.total_tokens == 150 + + +# --------------------------------------------------------------------------- +# LLMResponse +# --------------------------------------------------------------------------- + + +class TestLLMResponse: + + def test_creation(self) -> None: + msg = Message(role="assistant", content="Hi") + resp = LLMResponse(message=msg) + assert resp.message.content == "Hi" + assert resp.usage is None + assert resp.model is None + assert resp.finish_reason is None + assert resp.raw is None + + def test_with_usage(self) -> None: + msg = Message(role="assistant", content="") + usage = TokenUsage(prompt_tokens=10, completion_tokens=5, total_tokens=15) + resp = LLMResponse(message=msg, usage=usage, model="gpt-4", finish_reason="stop") + assert resp.usage.total_tokens == 15 + assert resp.model == "gpt-4" + assert resp.finish_reason == "stop" diff --git a/packages/nvidia_nat_runtime/tests/sdk/test_skill_tool.py b/packages/nvidia_nat_runtime/tests/sdk/test_skill_tool.py new file mode 100644 index 0000000000..058f053377 --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/test_skill_tool.py @@ -0,0 +1,200 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Unit tests for nat.sdk.skill.tool.build_read_skill_tool.""" + +from nat.data_models.skill import Skill +from nat.sdk.conversation.state import ConversationState +from nat.sdk.event.event import Event +from nat.sdk.event.event import SystemPromptEvent +from nat.sdk.skill.tool import build_read_skill_tool +from nat.sdk.tool.tool import Tool + +# --------------------------------------------------------------------------- +# Test helper +# --------------------------------------------------------------------------- + + +def _build_skills_section(skills: dict[str, Skill], state: ConversationState) -> str: + """Inline replica of Conversation._build_skills_section for isolated tests.""" + if not skills: + return "" + activated = set(state.activated_skills) + parts = [""] + for skill in skills.values(): + parts.append(skill.to_prompt_xml(include_content=skill.name in activated)) + parts.append("") + return "\n".join(parts) + + +def _make_tool( + skills: dict[str, Skill], + state: ConversationState | None = None, +) -> tuple[Tool, ConversationState, list[Event]]: + """Wire up a read_skill tool with event capture and an inline skills-context builder.""" + state = state or ConversationState() + emitted: list[Event] = [] + + tool = build_read_skill_tool( + skills=skills, + state=state, + emit_fn=emitted.append, + build_skills_context=lambda: _build_skills_section(skills, state), + ) + return tool, state, emitted + + +# --------------------------------------------------------------------------- +# Tests +# --------------------------------------------------------------------------- + + +class TestBuildReadSkillTool: + + def test_tool_name(self) -> None: + tool, _, _ = _make_tool({}) + assert tool.name == "read_skill" + + def test_tool_has_description(self) -> None: + tool, _, _ = _make_tool({}) + assert tool.description + + def test_tool_has_skill_name_parameter(self) -> None: + tool, _, _ = _make_tool({}) + props = tool.parameters.get("properties", {}) + assert "skill_name" in props + assert tool.parameters.get("required") == ["skill_name"] + + async def test_unknown_skill_returns_error_string(self) -> None: + tool, state, emitted = _make_tool({}) + result = await tool(skill_name="no-such-skill") + + assert result.error is None # tool itself didn't raise + assert "not found" in result.output + assert state.activated_skills == [] + assert emitted == [] + + async def test_known_skill_appends_to_activated_skills(self) -> None: + skill = Skill(name="my-skill", description="Does stuff") + tool, state, _ = _make_tool({"my-skill": skill}) + + await tool(skill_name="my-skill") + + assert "my-skill" in state.activated_skills + + async def test_known_skill_emits_system_prompt_event(self) -> None: + skill = Skill(name="my-skill", description="Does stuff", content="# My Skill\nDo X.") + tool, _, emitted = _make_tool({"my-skill": skill}) + + await tool(skill_name="my-skill") + + assert len(emitted) == 1 + assert isinstance(emitted[0], SystemPromptEvent) + + async def test_emitted_content_is_available_skills_section(self) -> None: + """The emitted SystemPromptEvent contains the full section.""" + skill = Skill(name="my-skill", description="Does stuff", content="Full body here.") + tool, _, emitted = _make_tool({"my-skill": skill}) + + await tool(skill_name="my-skill") + + content = emitted[0].content + assert "" in content + assert "my-skill" in content + # Body appears inside tag because the skill is now activated + assert "Full body here." in content + + async def test_emitted_content_includes_all_skills(self) -> None: + """The updated section lists every skill, not just the activated one.""" + skill_a = Skill(name="alpha", description="Alpha skill") + skill_b = Skill(name="beta", description="Beta skill", content="Beta body.") + skills = {"alpha": skill_a, "beta": skill_b} + tool, _, emitted = _make_tool(skills) + + await tool(skill_name="beta") + + content = emitted[0].content + assert "alpha" in content + assert "beta" in content + # Only the activated skill has body content + assert "Beta body." in content + + async def test_activation_is_idempotent(self) -> None: + """Calling the tool twice for the same skill does not duplicate activated_skills.""" + skill = Skill(name="my-skill", description="Does stuff") + tool, state, emitted = _make_tool({"my-skill": skill}) + + await tool(skill_name="my-skill") + await tool(skill_name="my-skill") + + assert state.activated_skills.count("my-skill") == 1 + # A fresh SystemPromptEvent is still emitted on each call + assert len(emitted) == 2 + + async def test_returns_confirmation_string(self) -> None: + skill = Skill(name="my-skill", description="Does stuff") + tool, _, _ = _make_tool({"my-skill": skill}) + + result = await tool(skill_name="my-skill") + + assert result.error is None + assert "my-skill" in result.output + assert "activated" in result.output + + async def test_error_string_lists_available_skills(self) -> None: + skill_a = Skill(name="skill-a", description="Skill A") + skill_b = Skill(name="skill-b", description="Skill B") + tool, _, _ = _make_tool({"skill-a": skill_a, "skill-b": skill_b}) + + result = await tool(skill_name="missing") + + assert "skill-a" in result.output + assert "skill-b" in result.output + + async def test_multiple_skills_each_activatable(self) -> None: + skills = { + "alpha": Skill(name="alpha", description="Alpha skill", content="Alpha body."), + "beta": Skill(name="beta", description="Beta skill", content="Beta body."), + } + tool, state, emitted = _make_tool(skills) + + await tool(skill_name="alpha") + await tool(skill_name="beta") + + assert "alpha" in state.activated_skills + assert "beta" in state.activated_skills + assert len(emitted) == 2 + # Second emission should have both skills' bodies + second_content = emitted[1].content + assert "Alpha body." in second_content + assert "Beta body." in second_content + + async def test_no_event_emitted_when_skills_section_is_empty(self) -> None: + """When build_skills_context returns '', no event is emitted.""" + skill = Skill(name="my-skill", description="Does stuff") + state = ConversationState() + emitted: list[Event] = [] + + # Provide a context builder that always returns empty + tool = build_read_skill_tool( + skills={"my-skill": skill}, + state=state, + emit_fn=emitted.append, + build_skills_context=lambda: "", + ) + + await tool(skill_name="my-skill") + + assert emitted == [] + assert "my-skill" in state.activated_skills diff --git a/packages/nvidia_nat_runtime/tests/sdk/test_tool.py b/packages/nvidia_nat_runtime/tests/sdk/test_tool.py new file mode 100644 index 0000000000..142a1f7fc2 --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/test_tool.py @@ -0,0 +1,202 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for nat.sdk.tool.tool — Tool and @tool decorator.""" + +import pytest + +from nat.sdk.tool.result import ToolResult +from nat.sdk.tool.tool import Tool +from nat.sdk.tool.tool import tool + +# --------------------------------------------------------------------------- +# Tool +# --------------------------------------------------------------------------- + + +class TestTool: + + def test_creation(self) -> None: + t = Tool(name="test", description="A test tool") + assert t.name == "test" + assert t.description == "A test tool" + assert t.parameters == {"type": "object", "properties": {}} + + def test_frozen(self) -> None: + t = Tool(name="test", description="test") + with pytest.raises(AttributeError): + t.name = "other" # type: ignore[misc] + + def test_to_openai_schema(self) -> None: + t = Tool( + name="search", + description="Search the web", + parameters={ + "type": "object", + "properties": { + "query": { + "type": "string" + } + }, + "required": ["query"], + }, + ) + schema = t.to_openai_schema() + assert schema["type"] == "function" + assert schema["function"]["name"] == "search" + assert schema["function"]["description"] == "Search the web" + assert "query" in schema["function"]["parameters"]["properties"] + + async def test_call_sync_returning_tool_result(self) -> None: + + def _fn(x: int) -> ToolResult: + return ToolResult(output=x * 2) + + t = Tool(name="double", description="Double", execute=_fn) + result = await t(x=5) + assert result.output == 10 + assert not result.is_error + + async def test_call_async_returning_tool_result(self) -> None: + + async def _fn(x: int) -> ToolResult: + return ToolResult(output=x * 2) + + t = Tool(name="double", description="Double", execute=_fn) + result = await t(x=5) + assert result.output == 10 + + async def test_call_sync_returning_raw_value(self) -> None: + + def _fn(x: int) -> int: + return x * 3 + + t = Tool(name="triple", description="Triple", execute=_fn) + result = await t(x=4) + assert result.output == 12 + + async def test_call_async_returning_raw_value(self) -> None: + + async def _fn(x: int) -> str: + return f"result={x}" + + t = Tool(name="format", description="Format", execute=_fn) + result = await t(x=7) + assert result.output == "result=7" + + async def test_call_exception_becomes_error(self) -> None: + + def _fn() -> None: + raise ValueError("boom") + + t = Tool(name="fail", description="Fail", execute=_fn) + result = await t() + assert result.is_error + assert "boom" in result.error + + +# --------------------------------------------------------------------------- +# @tool decorator +# --------------------------------------------------------------------------- + + +class TestToolDecorator: + + def test_basic_decorator(self) -> None: + + @tool(description="Add two numbers") + def add(a: int, b: int) -> int: + return a + b + + assert isinstance(add, Tool) + assert add.name == "add" + assert add.description == "Add two numbers" + assert "a" in add.parameters["properties"] + assert "b" in add.parameters["properties"] + assert "a" in add.parameters["required"] + assert "b" in add.parameters["required"] + + def test_custom_name(self) -> None: + + @tool(description="Search", name="web_search") + def search(query: str) -> str: + return query + + assert search.name == "web_search" + + def test_schema_from_type_hints(self) -> None: + + @tool(description="Test types") + def typed_fn( + name: str, + count: int, + rate: float, + flag: bool, + items: list, + data: dict, + ) -> str: + return "" + + props = typed_fn.parameters["properties"] + assert props["name"]["type"] == "string" + assert props["count"]["type"] == "integer" + assert props["rate"]["type"] == "number" + assert props["flag"]["type"] == "boolean" + assert props["items"]["type"] == "array" + assert props["data"]["type"] == "object" + + def test_optional_params_not_required(self) -> None: + + @tool(description="Test") + def fn(required_arg: str, optional_arg: str = "default") -> str: + return "" + + assert "required_arg" in fn.parameters["required"] + assert "optional_arg" not in fn.parameters.get("required", []) + + async def test_execute_sync_function(self) -> None: + + @tool(description="Add") + def add(a: int, b: int) -> int: + return a + b + + result = await add(a=3, b=4) + assert result.output == 7 + + async def test_execute_async_function(self) -> None: + + @tool(description="Greet") + async def greet(name: str) -> str: + return f"Hello {name}" + + result = await greet(name="World") + assert result.output == "Hello World" + + def test_camel_to_snake_conversion(self) -> None: + + @tool(description="Test") + def MyToolName() -> str: + return "" + + assert MyToolName.name == "my_tool_name" + + async def test_exception_captured(self) -> None: + + @tool(description="Fail") + def bad() -> None: + raise RuntimeError("oops") + + result = await bad() + assert result.is_error + assert "oops" in result.error diff --git a/packages/nvidia_nat_runtime/tests/sdk/test_tool_bridge.py b/packages/nvidia_nat_runtime/tests/sdk/test_tool_bridge.py new file mode 100644 index 0000000000..ee0a19d36a --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/test_tool_bridge.py @@ -0,0 +1,204 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for Tool bridge methods: from_function, from_function_config, from_function_group_config.""" + +from __future__ import annotations + +from unittest.mock import AsyncMock +from unittest.mock import MagicMock +from unittest.mock import patch + +from pydantic import BaseModel + +from nat.sdk.tool.tool import Tool + +# --------------------------------------------------------------------------- +# Helpers +# --------------------------------------------------------------------------- + + +class _DummyInput(BaseModel): + query: str + + +def _make_mock_function(*, display_name: str = "my_func", description: str = "A mock function") -> MagicMock: + """Create a mock core Function with the expected interface.""" + fn = MagicMock() + fn.display_name = display_name + fn.description = description + fn.input_schema = _DummyInput + fn.acall_invoke = AsyncMock(return_value="mock_result") + return fn + + +# --------------------------------------------------------------------------- +# Tool.from_function +# --------------------------------------------------------------------------- + + +class TestToolFromFunction: + + def test_wraps_name_and_description(self) -> None: + fn = _make_mock_function(display_name="search", description="Search the web") + tool = Tool.from_function(fn) + assert tool.name == "search" + assert tool.description == "Search the web" + + def test_schema_from_input_schema(self) -> None: + fn = _make_mock_function() + tool = Tool.from_function(fn) + assert "properties" in tool.parameters + assert "query" in tool.parameters["properties"] + + async def test_execute_calls_acall_invoke(self) -> None: + fn = _make_mock_function() + tool = Tool.from_function(fn) + result = await tool(query="hello") + fn.acall_invoke.assert_called_once_with(query="hello") + assert result.output == "mock_result" + + def test_none_description_becomes_empty_string(self) -> None: + fn = _make_mock_function(description=None) + fn.description = None + tool = Tool.from_function(fn) + assert tool.description == "" + + +# --------------------------------------------------------------------------- +# Tool.from_function_config +# --------------------------------------------------------------------------- + + +class TestToolFromFunctionConfig: + + async def test_uses_builder(self) -> None: + """from_function_config should get Builder.current() and use it to build.""" + mock_fn = _make_mock_function(display_name="built_func") + + mock_builder = MagicMock() + mock_builder.add_function = AsyncMock(return_value=mock_fn) + + mock_config = MagicMock() + mock_config.name = "custom_name" + + with patch("nat.builder.builder.Builder.current", return_value=mock_builder): + tool = await Tool.from_function_config(mock_config) + + assert tool.name == "built_func" + mock_builder.add_function.assert_awaited_once() + + async def test_auto_generates_name_when_config_name_is_none(self) -> None: + mock_fn = _make_mock_function() + mock_builder = MagicMock() + mock_builder.add_function = AsyncMock(return_value=mock_fn) + + mock_config = MagicMock() + mock_config.name = None + + with patch("nat.builder.builder.Builder.current", return_value=mock_builder): + await Tool.from_function_config(mock_config) + + # Verify the name passed to add_function starts with sdk_fn_ + mock_builder.add_function.assert_awaited_once() + name_arg = mock_builder.add_function.call_args[0][0] + assert name_arg.startswith("sdk_fn_") + + +# --------------------------------------------------------------------------- +# Tool.from_function_group +# --------------------------------------------------------------------------- + + +class TestToolFromFunctionGroup: + + async def test_wraps_accessible_functions(self) -> None: + fn1 = _make_mock_function(display_name="func_x", description="X") + fn2 = _make_mock_function(display_name="func_y", description="Y") + mock_functions = {"grp__func_x": fn1, "grp__func_y": fn2} + + mock_group = MagicMock() + mock_group.get_accessible_functions = AsyncMock(return_value=mock_functions) + + tools = await Tool.from_function_group(mock_group) + + assert len(tools) == 2 + names = {t.name for t in tools} + assert names == {"func_x", "func_y"} + mock_group.get_accessible_functions.assert_awaited_once() + + async def test_empty_group_returns_empty_list(self) -> None: + mock_group = MagicMock() + mock_group.get_accessible_functions = AsyncMock(return_value={}) + + tools = await Tool.from_function_group(mock_group) + + assert tools == [] + + +# --------------------------------------------------------------------------- +# Tool.from_function_group_config +# --------------------------------------------------------------------------- + + +class TestToolFromFunctionGroupConfig: + + async def test_returns_list_of_tools(self) -> None: + fn1 = _make_mock_function(display_name="func_a", description="A") + fn2 = _make_mock_function(display_name="func_b", description="B") + + mock_group = MagicMock() + mock_group.get_accessible_functions = AsyncMock(return_value={"group__func_a": fn1, "group__func_b": fn2}) + + mock_builder = MagicMock() + mock_builder.add_function_group = AsyncMock(return_value=mock_group) + + mock_config = MagicMock() + + with patch("nat.builder.builder.Builder.current", return_value=mock_builder): + tools = await Tool.from_function_group_config(mock_config) + + assert len(tools) == 2 + names = {t.name for t in tools} + assert names == {"func_a", "func_b"} + + async def test_empty_group_returns_empty_list(self) -> None: + mock_group = MagicMock() + mock_group.get_accessible_functions = AsyncMock(return_value={}) + + mock_builder = MagicMock() + mock_builder.add_function_group = AsyncMock(return_value=mock_group) + + mock_config = MagicMock() + + with patch("nat.builder.builder.Builder.current", return_value=mock_builder): + tools = await Tool.from_function_group_config(mock_config) + + assert tools == [] + + +# --------------------------------------------------------------------------- +# Auto-incrementing counter +# --------------------------------------------------------------------------- + + +class TestToolIdCounter: + + def test_counter_produces_unique_values(self) -> None: + """The module-level counter should produce strictly increasing values.""" + from nat.sdk.tool.tool import _tool_id_counter + + val1 = next(_tool_id_counter) + val2 = next(_tool_id_counter) + assert val2 > val1 diff --git a/packages/nvidia_nat_runtime/tests/sdk/test_tool_result.py b/packages/nvidia_nat_runtime/tests/sdk/test_tool_result.py new file mode 100644 index 0000000000..f8a8dee95e --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/sdk/test_tool_result.py @@ -0,0 +1,85 @@ +# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for nat.sdk.tool.result — ToolResult.""" + +from nat.data_models.workspace import ActionResult +from nat.data_models.workspace import ActionStatus +from nat.sdk.tool.result import ToolResult + + +class TestToolResult: + + def test_success(self) -> None: + r = ToolResult(output="hello") + assert r.output == "hello" + assert r.error is None + assert not r.is_error + assert r.metadata == {} + + def test_error(self) -> None: + r = ToolResult(error="something broke") + assert r.is_error + assert r.output is None + + def test_with_metadata(self) -> None: + r = ToolResult(output="ok", metadata={"duration": 1.5}) + assert r.metadata["duration"] == 1.5 + + def test_str_success(self) -> None: + r = ToolResult(output=42) + assert str(r) == "42" + + def test_str_error(self) -> None: + r = ToolResult(error="fail") + assert str(r) == "Error: fail" + + def test_str_none_output(self) -> None: + r = ToolResult() + assert str(r) == "" + + def test_is_error_false_when_no_error(self) -> None: + r = ToolResult(output="data") + assert r.is_error is False + + def test_is_error_true_when_error_set(self) -> None: + r = ToolResult(error="e") + assert r.is_error is True + + def test_both_output_and_error(self) -> None: + """Edge case: if both are set, is_error is True.""" + r = ToolResult(output="partial", error="warning") + assert r.is_error + assert r.output == "partial" + + +class TestFromActionResult: + + def test_success(self) -> None: + r = ActionResult(status=ActionStatus.SUCCESS, output="hello") + tr = ToolResult.from_action_result(r) + assert tr.output == "hello" + assert not tr.is_error + + def test_failure(self) -> None: + r = ActionResult(status=ActionStatus.FAILURE, error_message="fail") + tr = ToolResult.from_action_result(r) + assert tr.is_error + assert "fail" in tr.error + + def test_blocked(self) -> None: + r = ActionResult(status=ActionStatus.BLOCKED_BY_GUARDRAIL, error_message="blocked") + tr = ToolResult.from_action_result(r) + assert tr.is_error + assert "blocked" in tr.error diff --git a/packages/nvidia_nat_runtime/tests/test_llm.py b/packages/nvidia_nat_runtime/tests/test_llm.py new file mode 100644 index 0000000000..81a7bd7b70 --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/test_llm.py @@ -0,0 +1,273 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from collections.abc import AsyncGenerator +from types import SimpleNamespace +from typing import Any +from typing import cast + +import pytest +from openai import AsyncOpenAI +from openai.types.chat import ChatCompletion +from openai.types.chat import ChatCompletionMessage +from openai.types.chat import ChatCompletionMessageParam +from openai.types.chat.chat_completion import Choice as ChatCompletionChoice +from openai.types.chat.chat_completion_chunk import ChatCompletionChunk +from openai.types.chat.chat_completion_chunk import Choice as ChatCompletionChunkChoice +from openai.types.chat.chat_completion_chunk import ChoiceDelta +from openai.types.responses.response_text_delta_event import ResponseTextDeltaEvent +from pydantic import SecretStr + +from nat.data_models.common import OptionalSecretStr +from nat.data_models.intermediate_step import IntermediateStepPayload +from nat.data_models.intermediate_step import IntermediateStepType +from nat.data_models.retry_mixin import RetryMixin +from nat.llm.openai_llm import OpenAIModelConfig +from nat.plugins.runtime import llm as runtime_llm + + +class FakeRetryConfig(RetryMixin): + """Retry config for `_apply_retry` verification.""" + + +class FakeChatCompletions: + """Mock for OpenAI chat completion endpoint.""" + + def __init__(self, response: object) -> None: + self.response = response + self.calls: list[dict[str, Any]] = [] + + async def create(self, **kwargs: Any) -> object: + self.calls.append(kwargs) + return self.response + + +class FakeResponses: + """Mock for OpenAI responses endpoint.""" + + def __init__(self, response: object) -> None: + self.response = response + self.calls: list[dict[str, Any]] = [] + + async def create(self, **kwargs: Any) -> object: + self.calls.append(kwargs) + return self.response + + +class FakeAsyncOpenAI: + """Fake OpenAI client with chat/responses routes.""" + + def __init__(self, *, chat_response: object, response_response: object) -> None: + self.chat = SimpleNamespace(completions=FakeChatCompletions(chat_response)) + self.responses = FakeResponses(response_response) + + +def _chat_completion(content: str | None) -> ChatCompletion: + message = ChatCompletionMessage.model_construct(role="assistant", content=content) + choice = ChatCompletionChoice.model_construct(index=0, message=message, finish_reason="stop", logprobs=None) + return ChatCompletion.model_construct( + id="completion-id", + choices=[choice], + created=0, + model="model", + object="chat.completion", + service_tier=None, + system_fingerprint=None, + usage=None, + ) + + +def _chat_chunk(content: str | None) -> ChatCompletionChunk: + delta = ChoiceDelta.model_construct(content=content) + choice = ChatCompletionChunkChoice.model_construct(index=0, delta=delta, finish_reason=None, logprobs=None) + return ChatCompletionChunk.model_construct( + id="chunk-id", + choices=[choice], + created=0, + model="model", + object="chat.completion.chunk", + service_tier=None, + system_fingerprint=None, + usage=None, + ) + + +def _response_text_event(text: str) -> ResponseTextDeltaEvent: + return ResponseTextDeltaEvent.model_construct( + content_index=0, + delta=text, + item_id="item-id", + logprobs=[], + output_index=0, + sequence_number=0, + type="response.output_text.delta", + output_text=text, + ) + + +def _collect_event_types(payloads: list[IntermediateStepPayload]) -> list[IntermediateStepType]: + return [payload.event_type for payload in payloads] + + +def test_build_default_params_excludes_internal_fields() -> None: + """Ensure default params strip non-API fields.""" + api_key: OptionalSecretStr = SecretStr("secret") + params = runtime_llm._build_default_params( + OpenAIModelConfig(model_name="model-name", api_key=api_key, base_url="https://example.com", temperature=0.7)) + assert "model" not in params + assert "type" not in params + assert "api_key" not in params + assert "base_url" not in params + assert "stream_usage" not in params + assert params["temperature"] == 0.7 + + +def test_build_default_params_extra_exclude_removes_fields() -> None: + """Verify extra exclude values are honored.""" + api_key: OptionalSecretStr = SecretStr("secret") + params = runtime_llm._build_default_params( + OpenAIModelConfig(model_name="model-name", api_key=api_key, base_url="https://example.com", temperature=0.7), + extra_exclude={"temperature"}, + ) + assert "temperature" not in params + + +def test_ensure_stream_usage_injects_usage() -> None: + """Stream params should always include usage metadata.""" + params: dict[str, object] = {"stream_options": {"foo": "bar"}} + runtime_llm._ensure_stream_usage(params, stream=True) + stream_options = cast(dict[str, object], params["stream_options"]) + assert stream_options["include_usage"] is True + assert stream_options["foo"] == "bar" + + +def test_ensure_stream_usage_noop_when_not_streaming() -> None: + """Non-streaming calls should not be modified.""" + params: dict[str, object] = {} + runtime_llm._ensure_stream_usage(params, stream=False) + assert params == {} + + +def test_extract_text_from_chunk_dict() -> None: + """Dictionary chunks should extract content or output_text.""" + assert runtime_llm._extract_text_from_chunk({"choices": [{"delta": {"content": "hi"}}]}) == "hi" + assert runtime_llm._extract_text_from_chunk({"output_text": "yo"}) == "yo" + + +def test_extract_text_from_chunk_object() -> None: + """Object chunks should extract delta content.""" + chunk = _chat_chunk("hello") + assert runtime_llm._extract_text_from_chunk(chunk) == "hello" + + +def test_apply_retry_wraps_retry_mixin(monkeypatch: pytest.MonkeyPatch) -> None: + """Retry mixin should route to retry patch helper.""" + sentinel = object() + + def _fake_patch(client: object, **_kwargs: object) -> object: + return sentinel + + monkeypatch.setattr(runtime_llm, "patch_with_retry", _fake_patch) + result = runtime_llm._apply_retry(client=object(), llm_config=FakeRetryConfig()) + assert result is sentinel + + +async def test_runtime_openai_chat_completions_non_stream(step_payloads) -> None: + """Non-streaming chat calls emit start/end events.""" + response = _chat_completion("done") + client = FakeAsyncOpenAI(chat_response=response, response_response=object()) + runtime_client = runtime_llm.RuntimeOpenAIClient(cast(AsyncOpenAI, client), + model_name="demo", + default_params={"temperature": 0.1}) + messages = cast(list[ChatCompletionMessageParam], [{"role": "user", "content": "hi"}]) + + result = await runtime_client.chat_completions(messages) + + assert result is response + event_types = _collect_event_types(step_payloads) + assert event_types == [IntermediateStepType.LLM_START, IntermediateStepType.LLM_END] + chat_calls = client.chat.completions.calls + assert chat_calls[0]["model"] == "demo" + assert chat_calls[0]["temperature"] == 0.1 + + +async def test_runtime_openai_chat_completions_streaming(step_payloads) -> None: + """Streaming chat calls emit token events and final output.""" + chunks = [_chat_chunk("hello"), _chat_chunk(" world")] + + async def _stream() -> AsyncGenerator[ChatCompletionChunk, None]: + for chunk in chunks: + yield chunk + + client = FakeAsyncOpenAI(chat_response=_stream(), response_response=object()) + runtime_client = runtime_llm.RuntimeOpenAIClient(cast(AsyncOpenAI, client), model_name="demo", default_params={}) + messages = cast(list[ChatCompletionMessageParam], [{"role": "user", "content": "hi"}]) + + stream = cast(AsyncGenerator[ChatCompletionChunk, None], + await runtime_client.chat_completions(messages, stream=True)) + results = [chunk async for chunk in stream] + + assert results == chunks + event_types = _collect_event_types(step_payloads) + assert event_types == [ + IntermediateStepType.LLM_START, + IntermediateStepType.LLM_NEW_TOKEN, + IntermediateStepType.LLM_NEW_TOKEN, + IntermediateStepType.LLM_END, + ] + assert step_payloads[-1].data.output == "hello world" + + +async def test_runtime_openai_responses_streaming(step_payloads) -> None: + """Streaming responses emit token events and final output.""" + chunks = [ + _response_text_event("first"), + _response_text_event(" second"), + ] + + async def _stream() -> AsyncGenerator[object, None]: + for chunk in chunks: + yield chunk + + client = FakeAsyncOpenAI(chat_response=object(), response_response=_stream()) + runtime_client = runtime_llm.RuntimeOpenAIClient(cast(AsyncOpenAI, client), model_name="demo", default_params={}) + + stream = cast(AsyncGenerator[ResponseTextDeltaEvent, None], + await runtime_client.responses([{ + "role": "user", "content": "hi" + }], stream=True)) + results = [chunk async for chunk in stream] + + assert results == chunks + event_types = _collect_event_types(step_payloads) + assert event_types == [ + IntermediateStepType.LLM_START, + IntermediateStepType.LLM_NEW_TOKEN, + IntermediateStepType.LLM_NEW_TOKEN, + IntermediateStepType.LLM_END, + ] + assert step_payloads[-1].data.output == "first second" + + +async def test_runtime_openai_responses_non_stream(step_payloads) -> None: + """Non-streaming responses emit start/end events.""" + response = object() + client = FakeAsyncOpenAI(chat_response=object(), response_response=response) + runtime_client = runtime_llm.RuntimeOpenAIClient(cast(AsyncOpenAI, client), model_name="demo", default_params={}) + + result = await runtime_client.responses([{"role": "user", "content": "hi"}]) + + assert result is response + event_types = _collect_event_types(step_payloads) + assert event_types == [IntermediateStepType.LLM_START, IntermediateStepType.LLM_END] diff --git a/packages/nvidia_nat_runtime/tests/test_tool_calling_agent.py b/packages/nvidia_nat_runtime/tests/test_tool_calling_agent.py new file mode 100644 index 0000000000..2c4654e85e --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/test_tool_calling_agent.py @@ -0,0 +1,252 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +from collections.abc import AsyncGenerator +from collections.abc import Callable +from dataclasses import dataclass +from typing import TYPE_CHECKING +from typing import Any +from typing import cast + +import pytest +from openai import AsyncOpenAI +from openai.types.chat import ChatCompletion +from openai.types.chat import ChatCompletionMessage +from openai.types.chat.chat_completion import Choice as ChatCompletionChoice +from openai.types.chat.chat_completion_message_function_tool_call import ChatCompletionMessageFunctionToolCall +from openai.types.chat.chat_completion_message_function_tool_call import Function as ToolFunction +from pydantic import BaseModel + +from nat.builder.builder import Builder +from nat.builder.framework_enum import LLMFrameworkEnum +from nat.builder.function import Function +from nat.builder.function_info import FunctionInfo +from nat.data_models.api_server import ChatRequest +from nat.data_models.component_ref import FunctionRef +from nat.data_models.component_ref import LLMRef +from nat.data_models.function import EmptyFunctionConfig +from nat.plugins.runtime import tool_calling_agent as runtime_agent +from nat.sdk.tool.tool import Tool + +if TYPE_CHECKING: + from nat.plugins.runtime.llm import RuntimeOpenAIClient + + +def _make_llm(responses: list[ChatCompletion]) -> RuntimeOpenAIClient: + """Create a RuntimeOpenAIClient backed by fake responses (lazy import).""" + from nat.plugins.runtime.llm import RuntimeOpenAIClient as _Cls + return _Cls(cast(AsyncOpenAI, FakeAsyncOpenAI(responses)), model_name="demo", default_params={}) + + +class InputSchema(BaseModel): + """Input schema for runtime tool-calling agent tests.""" + + q: str + + +class RuntimeTestFunction(Function[InputSchema, object, object]): + """Concrete function implementation for agent tests.""" + + def __init__(self, + *, + name: str = "tool", + description: str, + output: object | None = None, + error: Exception | None = None) -> None: + super().__init__(config=EmptyFunctionConfig(name=name), description=description, input_schema=InputSchema) + self._output = output + self._error = error + self.calls: list[dict[str, Any]] = [] + + async def _ainvoke(self, value: InputSchema) -> object | None: + self.calls.append(value.model_dump()) + if self._error: + raise self._error + return self._output + + async def _astream(self, value: InputSchema) -> AsyncGenerator[object, None]: + yield self._output + + @property + def has_streaming_output(self) -> bool: + return False + + @property + def has_single_output(self) -> bool: + return True + + +class FakeChatCompletions: + """Mock for OpenAI chat completion endpoint.""" + + def __init__(self, responses: list[ChatCompletion]) -> None: + self._responses = list(responses) + + async def create(self, **_kwargs: Any) -> ChatCompletion: + return self._responses.pop(0) + + +class FakeAsyncOpenAI: + """Fake OpenAI client with chat completions route.""" + + def __init__(self, responses: list[ChatCompletion]) -> None: + self.chat = type("Chat", (), {"completions": FakeChatCompletions(responses)})() + self.responses = type("Responses", (), {"create": lambda **_kwargs: None})() + + +@dataclass +class FakeBuilder: + """Minimal builder to supply LLMs and tools.""" + + llm: RuntimeOpenAIClient + tools: dict[str, Tool] + + async def get_llm(self, _name: str, wrapper_type: LLMFrameworkEnum) -> RuntimeOpenAIClient: + return self.llm + + async def get_tools(self, tool_names: list[FunctionRef], wrapper_type: LLMFrameworkEnum) -> list[Tool]: + return [self.tools[str(name)] for name in tool_names] + + +def _tool_call(tool_id: str, name: str, arguments: str) -> ChatCompletionMessageFunctionToolCall: + function = ToolFunction.model_construct(name=name, arguments=arguments) + return ChatCompletionMessageFunctionToolCall.model_construct(id=tool_id, function=function, type="function") + + +def _chat_completion(content: str | None, + tool_calls: list[ChatCompletionMessageFunctionToolCall] | None) -> ChatCompletion: + message = ChatCompletionMessage.model_construct(role="assistant", content=content, tool_calls=tool_calls) + choice = ChatCompletionChoice.model_construct(index=0, message=message, finish_reason="stop", logprobs=None) + return ChatCompletion.model_construct( + id="completion-id", + choices=[choice], + created=0, + model="model", + object="chat.completion", + service_tier=None, + system_fingerprint=None, + usage=None, + ) + + +async def _build_agent(config: runtime_agent.RuntimeToolCallingAgentConfig, + llm: RuntimeOpenAIClient, + tools: dict[str, Tool]) -> FunctionInfo: + builder = cast(Builder, FakeBuilder(llm=llm, tools=tools)) + async with runtime_agent.runtime_tool_calling_agent_workflow(config, builder) as function_info: + return cast(FunctionInfo, function_info) + + +async def _call_agent(function_info: FunctionInfo, request: ChatRequest) -> str: + response_fn = cast(Callable[[ChatRequest], Any], function_info.single_fn) + return await response_fn(request) + + +async def test_tool_calling_agent_returns_final_response() -> None: + """Agent returns the final model response after tool use.""" + tool_call = _tool_call("call-1", "tool", '{"q": "x"}') + responses = [ + _chat_completion(None, [tool_call]), + _chat_completion("done", None), + ] + llm = _make_llm(responses) + function = RuntimeTestFunction(description="desc", output={"ok": True}) + tool = Tool.from_function(function) + config = runtime_agent.RuntimeToolCallingAgentConfig(llm_name=LLMRef("demo"), + tool_names=[FunctionRef("tool")], + max_iterations=2, + max_history=5) + function_info = await _build_agent(config, llm, {"tool": tool}) + + result = await _call_agent(function_info, ChatRequest.from_string("hi")) + + assert result == "done" + assert function.calls == [{"q": "x"}] + + +async def test_tool_calling_agent_return_direct() -> None: + """Return-direct tools short-circuit to tool output.""" + tool_call = _tool_call("call-1", "tool", '{"q": "x"}') + responses = [_chat_completion(None, [tool_call])] + llm = _make_llm(responses) + function = RuntimeTestFunction(description="desc", output={"ok": True}) + tool = Tool.from_function(function) + config = runtime_agent.RuntimeToolCallingAgentConfig(llm_name=LLMRef("demo"), + tool_names=[FunctionRef("tool")], + return_direct=[FunctionRef("tool")], + max_iterations=1) + function_info = await _build_agent(config, llm, {"tool": tool}) + + result = await _call_agent(function_info, ChatRequest.from_string("hi")) + + assert result == '{"ok": true}' + + +async def test_tool_calling_agent_handles_tool_error_when_enabled() -> None: + """Tool errors are surfaced to the LLM when enabled.""" + tool_call = _tool_call("call-1", "tool", '{"q": "x"}') + responses = [ + _chat_completion(None, [tool_call]), + _chat_completion("done", None), + ] + llm = _make_llm(responses) + function = RuntimeTestFunction(description="desc", error=RuntimeError("boom")) + tool = Tool.from_function(function) + config = runtime_agent.RuntimeToolCallingAgentConfig(llm_name=LLMRef("demo"), + tool_names=[FunctionRef("tool")], + handle_tool_errors=True, + max_iterations=2) + function_info = await _build_agent(config, llm, {"tool": tool}) + + result = await _call_agent(function_info, ChatRequest.from_string("hi")) + + assert result == "done" + + +async def test_tool_calling_agent_raises_tool_error_when_disabled() -> None: + """Tool errors raise when error handling is disabled.""" + tool_call = _tool_call("call-1", "tool", '{"q": "x"}') + responses = [_chat_completion(None, [tool_call])] + llm = _make_llm(responses) + function = RuntimeTestFunction(description="desc", error=RuntimeError("boom")) + tool = Tool.from_function(function) + config = runtime_agent.RuntimeToolCallingAgentConfig(llm_name=LLMRef("demo"), + tool_names=[FunctionRef("tool")], + handle_tool_errors=False, + max_iterations=1) + function_info = await _build_agent(config, llm, {"tool": tool}) + + with pytest.raises(RuntimeError, match="boom"): + await _call_agent(function_info, ChatRequest.from_string("hi")) + + +async def test_tool_calling_agent_max_iterations() -> None: + """Agent stops and returns empty when exceeding max iterations.""" + tool_call = _tool_call("call-1", "tool", '{"q": "x"}') + responses = [_chat_completion(None, [tool_call])] + llm = _make_llm(responses) + function = RuntimeTestFunction(description="desc", output={"ok": True}) + tool = Tool.from_function(function) + config = runtime_agent.RuntimeToolCallingAgentConfig(llm_name=LLMRef("demo"), + tool_names=[FunctionRef("tool")], + max_iterations=0) + function_info = await _build_agent(config, llm, {"tool": tool}) + + result = await _call_agent(function_info, ChatRequest.from_string("hi")) + + # With max_iterations=0, the runner hits the limit before any step and returns an ErrorEvent. + # The response_fn returns "" for non-message/non-observation events. + assert result == "" diff --git a/packages/nvidia_nat_runtime/tests/test_tool_wrapper.py b/packages/nvidia_nat_runtime/tests/test_tool_wrapper.py new file mode 100644 index 0000000000..ac44f63823 --- /dev/null +++ b/packages/nvidia_nat_runtime/tests/test_tool_wrapper.py @@ -0,0 +1,188 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from collections.abc import AsyncGenerator +from typing import cast + +import pytest +from pydantic import BaseModel + +from nat.builder.function import Function +from nat.data_models.function import EmptyFunctionConfig +from nat.data_models.intermediate_step import IntermediateStepPayload +from nat.data_models.intermediate_step import IntermediateStepType +from nat.plugins.runtime.tool_wrapper import RuntimeToolWrapper +from nat.sdk.tool.tool import Tool + + +class InputSchema(BaseModel): + """Input schema for the fake function.""" + + name: str + + +class RuntimeTestFunction(Function[InputSchema, object, object]): + """Concrete function implementation for tool wrapper tests.""" + + def __init__(self, + *, + description: str, + has_streaming_output: bool, + has_single_output: bool, + stream_chunks: list[object] | None = None, + invoke_result: object | None = None, + invoke_error: Exception | None = None) -> None: + super().__init__(config=EmptyFunctionConfig(), description=description, input_schema=InputSchema) + self._has_streaming_output = has_streaming_output + self._has_single_output = has_single_output + self._stream_chunks = stream_chunks or [] + self._invoke_result = invoke_result + self._invoke_error = invoke_error + + @property + def has_streaming_output(self) -> bool: + return self._has_streaming_output + + @property + def has_single_output(self) -> bool: + return self._has_single_output + + async def _ainvoke(self, value: InputSchema) -> object: + if self._invoke_error: + raise self._invoke_error + return self._invoke_result + + async def _astream(self, value: InputSchema) -> AsyncGenerator[object, None]: + for chunk in self._stream_chunks: + yield chunk + + +def _event_types(payloads: list[IntermediateStepPayload]) -> list[IntermediateStepType]: + return [payload.event_type for payload in payloads] + + +def _make_tool(fn: Function, name: str = "tool") -> Tool: + """Create a Tool from a Function, mirroring the runtime_tool_wrapper factory.""" + return Tool.from_function(fn) + + +def test_backward_compat_alias() -> None: + """RuntimeToolWrapper should be an alias for Tool.""" + assert RuntimeToolWrapper is Tool + + +def test_tool_schema() -> None: + """Tool schema should include name, description, and parameters.""" + fn = RuntimeTestFunction(description="desc", has_streaming_output=False, has_single_output=True, invoke_result="ok") + tool = _make_tool(fn) + schema = tool.tool_schema + function_schema = cast(dict[str, object], schema["function"]) + assert function_schema["description"] == "desc" + assert "parameters" in function_schema + + +async def test_tool_invoke_streaming(step_payloads) -> None: + """Streaming invoke aggregates text outputs.""" + fn = RuntimeTestFunction(description="desc", + has_streaming_output=True, + has_single_output=False, + stream_chunks=["hi", " there"]) + tool = _make_tool(fn) + result = await tool.invoke(name="alice") + + assert result.output == "hi there" + assert _event_types(step_payloads) == [ + IntermediateStepType.TOOL_START, + IntermediateStepType.FUNCTION_START, + IntermediateStepType.FUNCTION_END, + IntermediateStepType.TOOL_END, + ] + assert step_payloads[-1].data.output == "hi there" + + +async def test_tool_invoke_non_streaming(step_payloads) -> None: + """Non-streaming invoke forwards to acall_invoke.""" + fn = RuntimeTestFunction(description="desc", + has_streaming_output=False, + has_single_output=True, + invoke_result={"ok": True}) + tool = _make_tool(fn) + + result = await tool.invoke(name="bob") + + assert result.output == {"ok": True} + assert _event_types(step_payloads) == [ + IntermediateStepType.TOOL_START, + IntermediateStepType.FUNCTION_START, + IntermediateStepType.FUNCTION_END, + IntermediateStepType.TOOL_END, + ] + assert step_payloads[-1].data.output == {"ok": True} + + +async def test_tool_invoke_error_emits_end(step_payloads) -> None: + """Errors should still emit TOOL_END with a None output.""" + fn = RuntimeTestFunction(description="desc", + has_streaming_output=False, + has_single_output=True, + invoke_error=RuntimeError("boom")) + tool = _make_tool(fn) + + with pytest.raises(RuntimeError, match="boom"): + await tool.invoke(name="bob") + + assert _event_types(step_payloads) == [ + IntermediateStepType.TOOL_START, + IntermediateStepType.FUNCTION_START, + IntermediateStepType.FUNCTION_END, + IntermediateStepType.TOOL_END, + ] + assert step_payloads[-1].data.output is None + + +async def test_tool_stream_streaming(step_payloads) -> None: + """Streaming API yields chunks and aggregates output.""" + fn = RuntimeTestFunction(description="desc", + has_streaming_output=True, + has_single_output=False, + stream_chunks=["a", "b"]) + tool = _make_tool(fn) + + results = [chunk async for chunk in tool.stream(name="cara")] + + assert results == ["a", "b"] + assert _event_types(step_payloads) == [ + IntermediateStepType.TOOL_START, + IntermediateStepType.FUNCTION_START, + IntermediateStepType.FUNCTION_END, + IntermediateStepType.TOOL_END, + ] + assert step_payloads[-1].data.output == "ab" + + +async def test_tool_stream_non_streaming(step_payloads) -> None: + """Stream API should yield a single result for non-streaming tools.""" + fn = RuntimeTestFunction(description="desc", has_streaming_output=False, has_single_output=True, invoke_result="ok") + tool = _make_tool(fn) + + results = [chunk async for chunk in tool.stream(name="dana")] + + assert results == ["ok"] + assert _event_types(step_payloads) == [ + IntermediateStepType.TOOL_START, + IntermediateStepType.FUNCTION_START, + IntermediateStepType.FUNCTION_END, + IntermediateStepType.TOOL_END, + ] + assert step_payloads[-1].data.output == "ok" diff --git a/packages/nvidia_nat_runtime/uv.lock b/packages/nvidia_nat_runtime/uv.lock new file mode 100644 index 0000000000..b70f507469 --- /dev/null +++ b/packages/nvidia_nat_runtime/uv.lock @@ -0,0 +1,2822 @@ +version = 1 +revision = 3 +requires-python = ">=3.11, <3.14" +resolution-markers = [ + "python_full_version >= '3.13'", + "python_full_version == '3.12.*'", + "python_full_version < '3.12'", +] + +[manifest] +build-constraints = [ + { name = "setuptools", specifier = ">=64" }, + { name = "setuptools-dynamic-dependencies", specifier = ">=1.0.0" }, + { name = "setuptools-scm", specifier = ">=8" }, +] + +[[package]] +name = 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under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +[build-system] +build-backend = "setuptools.build_meta" +requires = ["setuptools>=64", "setuptools-scm>=8", "setuptools_dynamic_dependencies>=1.0.0"] + + +[tool.setuptools.packages.find] +where = ["src"] +include = ["nat.*"] + + +[tool.setuptools_scm] +git_describe_command = "git describe --long --first-parent" +root = "../.." + + +[project] +name = "nvidia-nat-workspace" +dynamic = ["version", "dependencies", "optional-dependencies"] +requires-python = ">=3.11,<3.14" +description = "Subpackage for workspace utilities in NVIDIA NeMo Agent Toolkit" +readme = "src/nat/meta/pypi.md" +keywords = ["ai", "agents", "workspace"] +license = { text = "Apache-2.0" } +authors = [{ name = "NVIDIA Corporation" }] +maintainers = [{ name = "NVIDIA Corporation" }] +classifiers = [ + "Programming Language :: Python", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", +] + +[project.urls] +documentation = "https://docs.nvidia.com/nemo/agent-toolkit/latest/" +source = "https://github.com/NVIDIA/NeMo-Agent-Toolkit" + +[tool.setuptools_dynamic_dependencies] +dependencies = [ + # Keep package version constraints as open as possible to avoid conflicts with other packages. Always define a minimum + # version when adding a new package. If unsure, default to using `~=` instead of `==`. Does not apply to nvidia-nat packages. + # Keep sorted!!! + "nvidia-nat-core == {version}", +] + +[tool.setuptools_dynamic_dependencies.optional-dependencies] +all = [ + "cloudmesh-apptainer~=5.0", + "docker~=7.1", +] +docker = [ + "docker~=7.1" +] +apptainer = [ + "cloudmesh-apptainer~=5.0" +] +test = [ + "nvidia-nat-test == {version}", +] + +[tool.uv] +build-constraint-dependencies = ["setuptools>=64", "setuptools-scm>=8", "setuptools_dynamic_dependencies>=1.0.0"] +managed = true +config-settings = { editable_mode = "compat" } + +[tool.uv.sources] +nvidia-nat-core = { path = "../nvidia_nat_core", editable = true } +nvidia-nat-test = { path = "../nvidia_nat_test", editable = true } + +[project.entry-points.'nat.components'] +nat_workspace = "nat.plugins.workspace.register" + +[project.entry-points.'nat.workspace_actions'] +nat_workspace_actions = "nat.workspace_actions.workspace.register" diff --git a/packages/nvidia_nat_workspace/src/nat/meta/pypi.md b/packages/nvidia_nat_workspace/src/nat/meta/pypi.md new file mode 100644 index 0000000000..d2f3546c94 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/meta/pypi.md @@ -0,0 +1,23 @@ + + +![NVIDIA NeMo Agent Toolkit](https://media.githubusercontent.com/media/NVIDIA/NeMo-Agent-Toolkit/refs/heads/main/docs/source/_static/banner.png "NeMo Agent Toolkit banner image") + +# NVIDIA NeMo Agent Toolkit Subpackage +This is a subpackage for workspace utilities in NVIDIA NeMo Agent Toolkit. + +For more information about NVIDIA NeMo Agent Toolkit, please visit the [NeMo Agent Toolkit package](https://pypi.org/project/nvidia-nat/). diff --git a/packages/nvidia_nat_workspace/src/nat/plugins/workspace/__init__.py b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/packages/nvidia_nat_workspace/src/nat/plugins/workspace/apptainer.py b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/apptainer.py new file mode 100644 index 0000000000..4da03c0414 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/apptainer.py @@ -0,0 +1,203 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Apptainer-backed workspace implementation.""" + +import asyncio +import hashlib +import os +import socket +import subprocess +import threading +import typing +import uuid +from collections.abc import AsyncIterator +from dataclasses import dataclass +from pathlib import Path + +from pydantic import Field + +from nat.cli.register_workflow import add_registered_workspace +from nat.data_models.workspace import WorkspaceBaseConfig +from nat.plugins.workspace.client import ApiWorkspace +from nat.plugins.workspace.client import ApiWorkspaceManagerBase +from nat.plugins.workspace.client import ApiWorkspaceSessionEntry +from nat.plugins.workspace.client import WorkspaceApiClient +from nat.plugins.workspace.server import _wait_for_server +from nat.plugins.workspace.types import ImagePullPolicy +from nat.plugins.workspace.types import Mount + +if typing.TYPE_CHECKING: + from cloudmesh.apptainer.apptainer import Apptainer + + +class ApptainerWorkspaceConfig(WorkspaceBaseConfig, name="apptainer"): + """Configuration for Apptainer workspaces.""" + + mounts: list[Mount] = Field( + default_factory=list, + description="List of (host_path, container_path, access_mode) tuples.", + ) + image: str = Field(description="Apptainer image to use for the workspace.") + image_pull_policy: ImagePullPolicy = Field(description="Policy for pulling the Apptainer image.") + http_timeout_seconds: float = Field(default=30.0, description="HTTP timeout for workspace API requests.") + apptainer_options: list[str] = Field( + default_factory=list, + description="Extra Apptainer options for instance startup.", + ) + + +class ApptainerWorkspace(ApiWorkspace): + """Apptainer workspace.""" + + def __init__(self, + config: ApptainerWorkspaceConfig, + api_client: WorkspaceApiClient, + instance_name: str | None = None, + session_id: str | None = None): + super().__init__(config=config, api_client=api_client, session_id=session_id) + self.config = config + self.instance_name = instance_name + + +@dataclass +class _ApptainerBackend: + instance_name: str | None + server_process: subprocess.Popen[str] | None + + +class ApptainerWorkspaceManager(ApiWorkspaceManagerBase[ApptainerWorkspaceConfig, ApptainerWorkspace, + _ApptainerBackend]): + _sessions: typing.ClassVar[dict[str, ApiWorkspaceSessionEntry[_ApptainerBackend]]] = {} + _session_lock: typing.ClassVar[threading.Lock] = threading.Lock() + + def __init__(self, config: ApptainerWorkspaceConfig): + super().__init__(config=config) + self._apptainer: Apptainer | None = None + + def _build_workspace(self, entry: ApiWorkspaceSessionEntry[_ApptainerBackend]) -> ApptainerWorkspace: + instance_name = entry.backend.instance_name if entry.backend else None + return ApptainerWorkspace( + config=self.config, + api_client=entry.api_client, + instance_name=instance_name, + session_id=entry.session_id, + ) + + async def _start_backend(self, session_id: str) -> tuple[str, _ApptainerBackend]: + instance_name, base_url, server_process = await asyncio.to_thread(self._start_instance, session_id) + return base_url, _ApptainerBackend(instance_name=instance_name, server_process=server_process) + + async def _shutdown_backend(self, backend: _ApptainerBackend | None) -> None: + if backend is None or backend.instance_name is None: + return + await asyncio.to_thread(self._stop_instance, backend.instance_name, backend.server_process) + + def _import_apptainer(self) -> "Apptainer": + try: + from cloudmesh.apptainer.apptainer import Apptainer + except ImportError as exc: + raise ImportError("cloudmesh-apptainer is required for Apptainer workspaces. " + "Install with `uv pip install 'nvidia-nat-workspace[apptainer]'`.") from exc + return Apptainer() + + def _build_bind_options(self) -> list[str]: + options: list[str] = [] + for mount in self.config.mounts: + mode = "ro" if mount.access_mode == "r" else mount.access_mode + options.append(f"--bind {mount.host_path}:{mount.container_path}:{mode}") + options.extend(self.config.apptainer_options) + return options + + def _resolve_image_name(self) -> str: + assert self._apptainer is not None + image_ref = self.config.image + image_path = Path(image_ref) + if image_path.exists(): + self._apptainer.add_location(str(image_path)) + return image_path.name + + if "://" in image_ref: + if self.config.image_pull_policy == "Never": + raise RuntimeError(f"Apptainer image {image_ref} is not available locally.") + images_dir = self.config.working_directory / ".apptainer" + images_dir.mkdir(parents=True, exist_ok=True) + digest = hashlib.sha1(image_ref.encode("utf-8")).hexdigest()[:10] + target_path = images_dir / f"{digest}.sif" + if self.config.image_pull_policy == "Always" or not target_path.exists(): + self._apptainer.download(name=str(target_path), url=image_ref) + self._apptainer.add_location(str(target_path)) + return target_path.name + + try: + self._apptainer.find_image(image_ref) + return image_ref + except Exception as exc: + raise RuntimeError(f"Apptainer image {image_ref} not found.") from exc + + def _allocate_port(self) -> int: + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock: + sock.bind(("127.0.0.1", 0)) + return sock.getsockname()[1] + + def _start_instance(self, session_id: str) -> tuple[str, str, subprocess.Popen[str]]: + self._apptainer = self._import_apptainer() + instance_name = f"nat-workspace-{uuid.uuid4().hex[:10]}" + image_name = self._resolve_image_name() + self._apptainer.start( + name=instance_name, + image=image_name, + options=self._build_bind_options(), + clean=False, + ) + + host_port = self._allocate_port() + env = os.environ.copy() + env["APPTAINERENV_NAT_WORKSPACE_ROOT"] = str(self.config.working_directory) + command = [ + "apptainer", + "exec", + f"instance://{instance_name}", + "python", + "-m", + "nat.plugins.workspace.server", + "--host", + "0.0.0.0", + "--port", + str(host_port), + ] + server_process = subprocess.Popen(command, + env=env, + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + text=True) + _wait_for_server("127.0.0.1", host_port, 10.0) + base_url = f"http://127.0.0.1:{host_port}" + return instance_name, base_url, server_process + + def _stop_instance(self, instance_name: str, server_process: subprocess.Popen[str] | None) -> None: + if server_process is not None and server_process.poll() is None: + server_process.terminate() + try: + server_process.wait(timeout=5) + except subprocess.TimeoutExpired: + server_process.kill() + + apptainer = self._import_apptainer() + apptainer.stop(name=instance_name) + + +@add_registered_workspace(ApptainerWorkspaceConfig) +async def apptainer_workspace(config: ApptainerWorkspaceConfig) -> AsyncIterator[ApptainerWorkspaceManager]: + yield ApptainerWorkspaceManager(config) diff --git a/packages/nvidia_nat_workspace/src/nat/plugins/workspace/client.py b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/client.py new file mode 100644 index 0000000000..77e1eea237 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/client.py @@ -0,0 +1,911 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""HTTP utilities for workspace API integrations.""" + +import io +import shutil +import sys +import tarfile +import threading +import typing +import uuid +from abc import abstractmethod +from dataclasses import dataclass +from datetime import UTC +from datetime import datetime +from pathlib import Path + +import httpx +from pydantic import ValidationError + +from nat.data_models.skill import Skill +from nat.data_models.workspace import ActionRequest +from nat.data_models.workspace import ActionResult +from nat.data_models.workspace import ActionStatus +from nat.data_models.workspace import WorkspaceBaseConfig +from nat.guardrails.workspace import WorkspaceGuardrail +from nat.guardrails.workspace import WorkspaceGuardrailViolation +from nat.workspace.types import SkillSummary +from nat.workspace.types import TypeSchema +from nat.workspace.types import WorkspaceActionSchema +from nat.workspace.types import WorkspaceBase +from nat.workspace.types import WorkspaceManagerBase + + +def normalize_base_url(url: str) -> str: + """Normalize a base URL string for HTTP clients.""" + trimmed = url.rstrip("/") + if "://" not in trimmed: + return f"http://{trimmed}" + return trimmed + + +def _safe_extract(archive: tarfile.TarFile, destination: Path) -> None: + """Safely extract a tar archive to the destination directory.""" + root = destination.resolve() + + if sys.version_info >= (3, 12): + archive.extractall(path=destination, filter="data") + else: + for member in archive.getmembers(): + member_path = (root / member.name).resolve() + if root != member_path and root not in member_path.parents: + raise ValueError(f"Archive member path escapes destination: {member.name}") + archive.extractall(path=destination) + + +def _guardrail_name(guardrail: WorkspaceGuardrail) -> str: + return getattr(guardrail, "name", guardrail.__class__.__name__) + + +def _format_guardrail_message(violation: WorkspaceGuardrailViolation) -> str: + if violation.message: + return f"{violation.guardrail_name}: {violation.message}" + return violation.guardrail_name + + +def _new_action_result( + *, + action_id: uuid.UUID | None = None, + status: ActionStatus, + output: typing.Any | None, + error_message: str | None, + execution_time: float | None = None, +) -> ActionResult: + return ActionResult( + action_id=action_id or uuid.uuid4(), + status=status, + output=output, + error_message=error_message, + execution_time=execution_time, + ) + + +async def _run_workspace_guardrails( + action: ActionRequest, + workspace_guardrails: list[WorkspaceGuardrail], +) -> WorkspaceGuardrailViolation | None: + for workspace_guardrail in workspace_guardrails: + guardrail_name = _guardrail_name(workspace_guardrail) + try: + violation = await workspace_guardrail.validate_action(action) + except Exception as exc: # noqa: BLE001 + return WorkspaceGuardrailViolation(guardrail_name=guardrail_name, message=f"Guardrail error: {exc}") + if violation is not None: + return violation + return None + + +async def _apply_workspace_guardrails( + action: ActionRequest, + result: ActionResult, + workspace_guardrails: list[WorkspaceGuardrail], +) -> ActionResult: + updated = result + for workspace_guardrail in workspace_guardrails: + guardrail_name = _guardrail_name(workspace_guardrail) + try: + updated = await workspace_guardrail.sanitize_result(action, updated) + except Exception as exc: # noqa: BLE001 + return ActionResult( + action_id=action.action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Guardrail {guardrail_name} failed: {exc}", + execution_time=updated.execution_time, + ) + return updated + + +class WorkspaceApiClient: + """HTTP client for workspace API endpoints.""" + + def __init__(self, http_client: httpx.AsyncClient): + self._http_client = http_client + + @staticmethod + def _url(path: str) -> str: + return f"/api/{path.lstrip('/')}" + + @staticmethod + def _extract_list(payload: typing.Any, key: str) -> list[typing.Any]: + if isinstance(payload, dict): + items = payload.get(key) + else: + items = payload + if not isinstance(items, list): + raise ValueError(f"Expected list payload for '{key}'") + return items + + @staticmethod + def _parse_type_schema(raw: dict[str, typing.Any]) -> TypeSchema: + return TypeSchema(type=str(raw.get("type", "")), description=str(raw.get("description", ""))) + + def _parse_action_schema(self, raw: dict[str, typing.Any]) -> WorkspaceActionSchema: + parameters = [self._parse_type_schema(param) for param in raw.get("parameters", [])] + result = self._parse_type_schema(raw.get("result", {})) + return WorkspaceActionSchema( + name=str(raw.get("name", "")), + description=str(raw.get("description", "")), + parameters=parameters, + result=result, + ) + + @staticmethod + def _parse_skill_summary(raw: dict[str, typing.Any]) -> SkillSummary: + return SkillSummary(name=str(raw.get("name", "")), description=str(raw.get("description", ""))) + + async def get_actions(self) -> list[WorkspaceActionSchema]: + """Return action schemas from the workspace API.""" + try: + response = await self._http_client.get(self._url("actions")) + response.raise_for_status() + payload = response.json() + items = self._extract_list(payload, "actions") + return [self._parse_action_schema(item) for item in items] + except httpx.RequestError as exc: + raise RuntimeError("Workspace action discovery request failed.") from exc + except (httpx.HTTPStatusError, ValueError) as exc: + raise RuntimeError("Workspace action discovery returned invalid data.") from exc + + async def get_skills(self) -> list[SkillSummary]: + """Return skill summaries from the workspace API.""" + try: + response = await self._http_client.get(self._url("skills")) + response.raise_for_status() + payload = response.json() + items = self._extract_list(payload, "skills") + return [self._parse_skill_summary(item) for item in items] + except httpx.RequestError as exc: + raise RuntimeError("Workspace skill discovery request failed.") from exc + except (httpx.HTTPStatusError, ValueError) as exc: + raise RuntimeError("Workspace skill discovery returned invalid data.") from exc + + async def read_skill(self, skill_name: str) -> Skill | None: + """Return a single skill by name from the workspace API.""" + try: + response = await self._http_client.get(self._url(f"skills/{skill_name}")) + except httpx.RequestError as exc: + raise RuntimeError(f"Workspace read_skill request failed for {skill_name!r}.") from exc + if response.status_code == 404: + return None + try: + response.raise_for_status() + return Skill.from_portable_dict(response.json()) + except (httpx.HTTPStatusError, ValueError) as exc: + raise RuntimeError(f"Workspace read_skill returned invalid data for {skill_name!r}.") from exc + + async def create_skill(self, skill: Skill) -> ActionResult: + """Create a skill via the workspace API.""" + action_id = uuid.uuid4() + payload = skill.to_portable_dict() + try: + response = await self._http_client.post(self._url("skills/new"), json=payload) + except httpx.RequestError as exc: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to create skill {skill.name}: {exc}", + ) + + if response.status_code in {200, 201}: + return _new_action_result( + action_id=action_id, + status=ActionStatus.SUCCESS, + output={ + "status": "created", "name": skill.name + }, + error_message=None, + ) + if response.status_code == 409: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Skill {skill.name} already exists", + ) + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to create skill {skill.name}: {response.status_code} {response.text}", + ) + + async def execute_action(self, action_request: ActionRequest) -> ActionResult: + """Execute an action request via the workspace API.""" + payload = action_request.model_dump(mode="json", exclude_none=True) + try: + response = await self._http_client.post( + self._url(f"actions/{action_request.action_name}/execute"), + json=payload, + ) + except httpx.RequestError as exc: + return _new_action_result( + action_id=action_request.action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Action {action_request.action_name} failed to execute: {exc}", + ) + + if response.status_code == 404: + return _new_action_result( + action_id=action_request.action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Action {action_request.action_name} not found", + ) + if not response.is_success: + return _new_action_result( + action_id=action_request.action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=(f"Action {action_request.action_name} failed to execute: " + f"{response.status_code} {response.text}"), + ) + try: + payload = response.json() + except ValueError: + payload = response.text + + if isinstance(payload, dict): + try: + return ActionResult.model_validate(payload) + except ValidationError: + output = payload.get("result", payload) + else: + output = payload + + return _new_action_result( + action_id=action_request.action_id, + status=ActionStatus.SUCCESS, + output=output, + error_message=None, + ) + + async def execute_action_from_args( + self, + action_name: str, + args: dict[str, typing.Any], + model_metadata: dict[str, typing.Any] | None = None, + ) -> ActionResult: + """Execute an action via the workspace API.""" + if args is None: + args = {} + try: + action_request = ActionRequest( + action_id=uuid.uuid4(), + action_name=action_name, + arguments=args, + timestamp=datetime.now(tz=UTC), + model_metadata=model_metadata, + ) + except ValidationError as exc: + return _new_action_result( + action_id=uuid.uuid4(), + status=ActionStatus.FAILURE, + output=None, + error_message=f"Action {action_name} failed to serialize request: {exc}", + ) + return await self.execute_action(action_request) + + async def upload_file(self, file_path: Path, destination_path: Path) -> ActionResult: + """Upload a file to the workspace API.""" + action_id = uuid.uuid4() + try: + content = file_path.read_bytes() + except FileNotFoundError: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Local file {file_path} not found", + ) + except Exception as exc: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to read local file {file_path}: {exc}", + ) + + try: + response = await self._http_client.post( + self._url("file/upload"), + params={ + "type": "file", "destination": str(destination_path) + }, + content=content, + ) + except httpx.RequestError as exc: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to upload file {file_path}: {exc}", + ) + + if response.status_code in {200, 201}: + return _new_action_result( + action_id=action_id, + status=ActionStatus.SUCCESS, + output={ + "status": "uploaded", "path": str(destination_path) + }, + error_message=None, + ) + if response.status_code == 409: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Workspace file {destination_path} already exists", + ) + if response.status_code == 404: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Workspace path {destination_path} not found", + ) + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=(f"Failed to upload file {file_path} to {destination_path}: " + f"{response.status_code} {response.text}"), + ) + + async def delete_file(self, file_path: Path) -> ActionResult: + """Delete a file via the workspace API.""" + action_id = uuid.uuid4() + try: + response = await self._http_client.post( + self._url("file/delete"), + params={ + "type": "file", "path": str(file_path) + }, + ) + except httpx.RequestError as exc: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to delete file {file_path}: {exc}", + ) + + if response.status_code in {200, 204}: + return _new_action_result( + action_id=action_id, + status=ActionStatus.SUCCESS, + output={ + "status": "deleted", "path": str(file_path) + }, + error_message=None, + ) + if response.status_code == 404: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Workspace file {file_path} not found", + ) + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to delete file {file_path}: {response.status_code} {response.text}", + ) + + async def download_file(self, file_path: Path) -> ActionResult: + """Download a file from the workspace API.""" + action_id = uuid.uuid4() + try: + response = await self._http_client.get( + self._url("file/download"), + params={ + "type": "file", "path": str(file_path) + }, + ) + except httpx.RequestError as exc: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to download file {file_path}: {exc}", + ) + + if response.status_code == 404: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Workspace file {file_path} not found", + ) + if not response.is_success: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to download file {file_path}: {response.status_code} {response.text}", + ) + + destination_path = Path(".") / file_path.name + try: + destination_path.write_bytes(response.content) + except Exception as exc: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to write file {destination_path}: {exc}", + ) + return _new_action_result( + action_id=action_id, + status=ActionStatus.SUCCESS, + output={ + "status": "downloaded", "path": str(destination_path) + }, + error_message=None, + ) + + async def upload_directory(self, directory_path: Path, destination_path: Path) -> ActionResult: + """Upload a directory to the workspace API.""" + action_id = uuid.uuid4() + if not directory_path.exists(): + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Local directory {directory_path} not found", + ) + if not directory_path.is_dir(): + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Local path {directory_path} is not a directory", + ) + + try: + archive = io.BytesIO() + with tarfile.open(fileobj=archive, mode="w:gz") as tar: + tar.add(directory_path, arcname=".") + archive.seek(0) + except Exception as exc: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to archive directory {directory_path}: {exc}", + ) + + try: + response = await self._http_client.post( + self._url("file/upload"), + params={ + "type": "folder", "destination": str(destination_path) + }, + content=archive.getvalue(), + headers={"Content-Type": "application/gzip"}, + ) + except httpx.RequestError as exc: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to upload directory {directory_path}: {exc}", + ) + + if response.status_code in {200, 201}: + return _new_action_result( + action_id=action_id, + status=ActionStatus.SUCCESS, + output={ + "status": "uploaded", "path": str(destination_path) + }, + error_message=None, + ) + if response.status_code == 409: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Workspace directory {destination_path} already exists", + ) + if response.status_code == 404: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Workspace path {destination_path} not found", + ) + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=(f"Failed to upload directory {directory_path} to {destination_path}: " + f"{response.status_code} {response.text}"), + ) + + async def download_directory(self, directory_path: Path, destination_path: Path) -> ActionResult: + """Download a directory from the workspace API.""" + action_id = uuid.uuid4() + if destination_path.exists(): + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Local directory {destination_path} already exists", + ) + + try: + response = await self._http_client.get( + self._url("file/download"), + params={ + "type": "folder", "path": str(directory_path) + }, + ) + except httpx.RequestError as exc: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to download directory {directory_path}: {exc}", + ) + + if response.status_code == 404: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Workspace directory {directory_path} not found", + ) + if not response.is_success: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=(f"Failed to download directory {directory_path}: " + f"{response.status_code} {response.text}"), + ) + + try: + destination_path.mkdir(parents=True, exist_ok=False) + with tarfile.open(fileobj=io.BytesIO(response.content), mode="r:gz") as tar: + _safe_extract(tar, destination_path) + except Exception as exc: + shutil.rmtree(destination_path, ignore_errors=True) + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to extract directory {directory_path}: {exc}", + ) + + return _new_action_result( + action_id=action_id, + status=ActionStatus.SUCCESS, + output={ + "status": "downloaded", "path": str(destination_path) + }, + error_message=None, + ) + + async def delete_directory(self, directory_path: Path) -> ActionResult: + """Delete a directory via the workspace API.""" + action_id = uuid.uuid4() + try: + response = await self._http_client.post( + self._url("file/delete"), + params={ + "type": "folder", "path": str(directory_path) + }, + ) + except httpx.RequestError as exc: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Failed to delete directory {directory_path}: {exc}", + ) + + if response.status_code in {200, 204}: + return _new_action_result( + action_id=action_id, + status=ActionStatus.SUCCESS, + output={ + "status": "deleted", "path": str(directory_path) + }, + error_message=None, + ) + if response.status_code == 404: + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=f"Workspace directory {directory_path} not found", + ) + return _new_action_result( + action_id=action_id, + status=ActionStatus.FAILURE, + output=None, + error_message=(f"Failed to delete directory {directory_path}: " + f"{response.status_code} {response.text}"), + ) + + +class ApiWorkspace(WorkspaceBase): + """Workspace implementation backed by a workspace API client.""" + + def __init__(self, config: WorkspaceBaseConfig, api_client: WorkspaceApiClient, session_id: str | None = None): + self.config = config + self._api_client = api_client + self.session_id = session_id + self._workspace_guardrails: list[WorkspaceGuardrail] = [] + + def add_workspace_guardrail(self, workspace_guardrail: WorkspaceGuardrail) -> None: + """Add a workspace guardrail that runs before action execution.""" + guardrail_name = _guardrail_name(workspace_guardrail) + if any(_guardrail_name(existing) == guardrail_name for existing in self._workspace_guardrails): + raise ValueError(f"Workspace guardrail '{guardrail_name}' already exists.") + self._workspace_guardrails.append(workspace_guardrail) + + def remove_workspace_guardrail(self, guardrail_name: str) -> bool: + """Remove a workspace guardrail by name.""" + for index, workspace_guardrail in enumerate(self._workspace_guardrails): + if _guardrail_name(workspace_guardrail) == guardrail_name: + del self._workspace_guardrails[index] + return True + return False + + def clear_workspace_guardrails(self) -> None: + """Remove all workspace guardrails from the workspace.""" + self._workspace_guardrails.clear() + + def list_workspace_guardrails(self) -> tuple[WorkspaceGuardrail, ...]: + """Return the workspace guardrails currently configured on this workspace.""" + return tuple(self._workspace_guardrails) + + async def get_actions(self) -> list[WorkspaceActionSchema]: + """Return action schemas from the workspace API.""" + return await self._api_client.get_actions() + + async def get_skills(self) -> list[SkillSummary]: + """Return skill summaries from the workspace API.""" + return await self._api_client.get_skills() + + async def read_skill(self, skill_name: str) -> Skill | None: + """Return a single skill by name from the workspace API.""" + return await self._api_client.read_skill(skill_name) + + async def create_skill(self, skill: Skill) -> ActionResult: + """Create a skill using the workspace API.""" + return await self._api_client.create_skill(skill=skill) + + async def upload_file(self, file_path: Path, destination_path: Path) -> ActionResult: + """Upload a file using the workspace API.""" + return await self._api_client.upload_file(file_path=file_path, destination_path=destination_path) + + async def delete_file(self, file_path: Path) -> ActionResult: + """Delete a file using the workspace API.""" + return await self._api_client.delete_file(file_path=file_path) + + async def download_file(self, file_path: Path) -> ActionResult: + """Download a file using the workspace API.""" + return await self._api_client.download_file(file_path=file_path) + + async def upload_directory(self, directory_path: Path, destination_path: Path) -> ActionResult: + """Upload a directory using the workspace API.""" + return await self._api_client.upload_directory(directory_path=directory_path, destination_path=destination_path) + + async def download_directory(self, directory_path: Path, destination_path: Path) -> ActionResult: + """Download a directory using the workspace API.""" + return await self._api_client.download_directory(directory_path=directory_path, + destination_path=destination_path) + + async def delete_directory(self, directory_path: Path) -> ActionResult: + """Delete a directory using the workspace API.""" + return await self._api_client.delete_directory(directory_path=directory_path) + + async def execute_action( + self, + action_name: str, + args: dict[str, typing.Any], + model_metadata: dict[str, typing.Any] | None = None, + ) -> ActionResult: + """Execute an action using the workspace API.""" + if args is None: + args = {} + try: + action_request = ActionRequest( + action_id=uuid.uuid4(), + action_name=action_name, + arguments=args, + timestamp=datetime.now(tz=UTC), + model_metadata=model_metadata, + ) + except ValidationError as exc: + return _new_action_result( + action_id=uuid.uuid4(), + status=ActionStatus.FAILURE, + output=None, + error_message=f"Action {action_name} failed to serialize request: {exc}", + ) + + violation = await _run_workspace_guardrails(action_request, self._workspace_guardrails) + if violation is not None: + return ActionResult( + action_id=action_request.action_id, + status=ActionStatus.BLOCKED_BY_GUARDRAIL, + output=None, + error_message=_format_guardrail_message(violation), + execution_time=None, + ) + + result = await self._api_client.execute_action(action_request) + if isinstance(result, ActionResult): + return await _apply_workspace_guardrails(action_request, result, self._workspace_guardrails) + return result + + +ApiConfigT = typing.TypeVar("ApiConfigT", bound=WorkspaceBaseConfig) +ApiWorkspaceT = typing.TypeVar("ApiWorkspaceT", bound=ApiWorkspace) +BackendT = typing.TypeVar("BackendT") + + +@dataclass +class ApiWorkspaceSessionEntry(typing.Generic[BackendT]): + """Session entry for API-backed workspace managers. + + Attributes: + session_id: Unique identifier for the workspace session. + base_url: Base URL used for the workspace API. + http_client: HTTP client bound to the workspace API. + api_client: Workspace API client wrapper. + ref_count: Reference count for the shared session. + backend: Backend-specific metadata for cleanup and workspace construction. + """ + + session_id: str + base_url: str + http_client: httpx.AsyncClient + api_client: WorkspaceApiClient + ref_count: int + backend: BackendT | None + + +class ApiWorkspaceManagerBase( + WorkspaceManagerBase[ApiConfigT, ApiWorkspaceT], + typing.Generic[ApiConfigT, ApiWorkspaceT, BackendT], +): + """Base manager for API-backed workspace sessions.""" + + _sessions: typing.ClassVar[dict[str, ApiWorkspaceSessionEntry[typing.Any]]] + _session_lock: typing.ClassVar[threading.Lock] + + def __init__(self, config: ApiConfigT): + super().__init__(config=config) + self._session_id: str | None = None + + async def __aenter__(self) -> ApiWorkspaceT: + """Open or reuse a workspace session.""" + self._session_id = self.config.session_id or uuid.uuid4().hex + entry = await self._get_or_create_session(self._session_id) + return self._build_workspace(entry) + + async def __aexit__(self, exc_type, exc_value, traceback) -> None: + """Release a workspace session.""" + if self._session_id is None: + return + await self._release_session(self._session_id) + self._session_id = None + + @abstractmethod + def _build_workspace(self, entry: ApiWorkspaceSessionEntry[BackendT]) -> ApiWorkspaceT: + """Construct a workspace instance from a session entry.""" + raise NotImplementedError + + def _endpoint_override(self) -> str | None: + return self.config.endpoint + + def _session_headers(self, session_id: str) -> dict[str, str]: + return {"X-Workspace-Session": session_id} + + def _http_timeout_seconds(self) -> float: + return typing.cast(float, getattr(self.config, "http_timeout_seconds", 30.0)) + + @abstractmethod + async def _start_backend(self, session_id: str) -> tuple[str, BackendT | None]: + """Start the workspace backend and return its base URL and metadata.""" + raise NotImplementedError + + async def _shutdown_backend(self, backend: BackendT | None) -> None: + """Stop any backend resources associated with a session.""" + return + + async def _resolve_base_url(self, session_id: str) -> tuple[str, BackendT | None]: + endpoint = self._endpoint_override() + if endpoint: + return normalize_base_url(endpoint), None + return await self._start_backend(session_id) + + async def _get_or_create_session(self, session_id: str) -> ApiWorkspaceSessionEntry[BackendT]: + with self._session_lock: + entry = self._sessions.get(session_id) + if entry is not None: + entry.ref_count += 1 + return entry + + base_url, backend = await self._resolve_base_url(session_id) + headers = self._session_headers(session_id) + http_client = httpx.AsyncClient( + base_url=base_url, + headers=headers or None, + timeout=httpx.Timeout(self._http_timeout_seconds()), + ) + api_client = WorkspaceApiClient(http_client) + entry = ApiWorkspaceSessionEntry( + session_id=session_id, + base_url=base_url, + http_client=http_client, + api_client=api_client, + ref_count=1, + backend=backend, + ) + + with self._session_lock: + self._sessions[session_id] = entry + return entry + + async def _release_session(self, session_id: str) -> None: + entry: ApiWorkspaceSessionEntry[BackendT] | None = None + with self._session_lock: + current = self._sessions.get(session_id) + if current is None: + return + current.ref_count -= 1 + if current.ref_count <= 0: + entry = self._sessions.pop(session_id) + + if entry is None: + return + + try: + await entry.http_client.post("/api/session/close") + except httpx.RequestError: + pass + await entry.http_client.aclose() + await self._shutdown_backend(entry.backend) diff --git a/packages/nvidia_nat_workspace/src/nat/plugins/workspace/docker.py b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/docker.py new file mode 100644 index 0000000000..3e815640fb --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/docker.py @@ -0,0 +1,192 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Docker-backed workspace implementation.""" + +import asyncio +import socket +import threading +import typing +from collections.abc import AsyncIterator +from dataclasses import dataclass + +from pydantic import Field + +from nat.cli.register_workflow import add_registered_workspace +from nat.data_models.workspace import WorkspaceBaseConfig +from nat.plugins.workspace.client import ApiWorkspace +from nat.plugins.workspace.client import ApiWorkspaceManagerBase +from nat.plugins.workspace.client import ApiWorkspaceSessionEntry +from nat.plugins.workspace.client import WorkspaceApiClient +from nat.plugins.workspace.server import _wait_for_server +from nat.plugins.workspace.types import ImagePullPolicy +from nat.plugins.workspace.types import Mount + +if typing.TYPE_CHECKING: + from docker.client import DockerClient + + +class DockerWorkspaceConfig(WorkspaceBaseConfig, name="docker"): + """Configuration for Docker workspaces.""" + + mounts: list[Mount] = Field( + default_factory=list, + description="List of (host_path, container_path, access_mode) tuples.", + ) + image: str = Field(description="Docker image to use for the workspace.") + image_pull_policy: ImagePullPolicy = Field(description="Policy for pulling the Docker image.") + container_port: int = Field(default=8000, description="Container port for the workspace API endpoint.") + http_timeout_seconds: float = Field(default=30.0, description="HTTP timeout for workspace API requests.") + environment: dict[str, str] = Field(default_factory=dict, description="Environment variables for the container.") + command: str | list[str] | None = Field( + default=None, + description="Command to start the workspace API server inside the container.", + ) + + +class DockerWorkspace(ApiWorkspace): + """Docker workspace.""" + + def __init__(self, + config: DockerWorkspaceConfig, + api_client: WorkspaceApiClient, + container_id: str | None = None, + session_id: str | None = None): + super().__init__(config=config, api_client=api_client, session_id=session_id) + self.config = config + self.container_id = container_id + + +@dataclass +class _DockerBackend: + container_id: str | None + + +class DockerWorkspaceManager(ApiWorkspaceManagerBase[DockerWorkspaceConfig, DockerWorkspace, _DockerBackend]): + _sessions: typing.ClassVar[dict[str, ApiWorkspaceSessionEntry[_DockerBackend]]] = {} + _session_lock: typing.ClassVar[threading.Lock] = threading.Lock() + + def _build_workspace(self, entry: ApiWorkspaceSessionEntry[_DockerBackend]) -> DockerWorkspace: + container_id = entry.backend.container_id if entry.backend else None + return DockerWorkspace( + config=self.config, + api_client=entry.api_client, + container_id=container_id, + session_id=entry.session_id, + ) + + async def _start_backend(self, session_id: str) -> tuple[str, _DockerBackend]: + container_id, base_url = await asyncio.to_thread(self._start_container, session_id) + await asyncio.to_thread(_wait_for_server, "127.0.0.1", int(base_url.rsplit(":", 1)[1]), 10.0) + return base_url, _DockerBackend(container_id=container_id) + + async def _shutdown_backend(self, backend: _DockerBackend | None) -> None: + if backend is None or backend.container_id is None: + return + await asyncio.to_thread(self._stop_container, backend.container_id) + + @staticmethod + def _import_docker() -> typing.Any: + try: + import docker + except ImportError as exc: + raise ImportError( + "docker is required for Docker workspaces. Install with " + \ + "`uv pip install 'nvidia-nat-workspace[docker]'`." + ) from exc + return docker + + def _volume_bindings(self) -> dict[str, dict[str, str]]: + volumes: dict[str, dict[str, str]] = {} + for mount in self.config.mounts: + mode = "ro" if mount.access_mode == "r" else mount.access_mode + volumes[str(mount.host_path)] = {"bind": str(mount.container_path), "mode": mode} + return volumes + + def _ensure_image(self, docker_module, docker_client: "DockerClient") -> None: + + policy = self.config.image_pull_policy + image = self.config.image + + if policy == "Always": + docker_client.images.pull(image) + return + + try: + docker_client.images.get(image) + except docker_module.errors.ImageNotFound as exc: + if policy == "Never": + raise RuntimeError(f"Docker image {image} not found.") from exc + docker_client.images.pull(image) + + def _allocate_port(self) -> int: + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock: + sock.bind(("127.0.0.1", 0)) + return sock.getsockname()[1] + + def _start_container(self, session_id: str) -> tuple[str, str]: + docker_module: typing.Any = self._import_docker() + docker_client = docker_module.from_env() + self._ensure_image(docker_module, docker_client) + + host_port = self._allocate_port() + environment = dict(self.config.environment) + environment.setdefault("NAT_WORKSPACE_ROOT", str(self.config.working_directory)) + command = self.config.command + if command is None: + command = [ + "python", + "-m", + "nat.plugins.workspace.server", + "--host", + "0.0.0.0", + "--port", + str(self.config.container_port), + ] + + container = docker_client.containers.run( + self.config.image, + detach=True, + ports={f"{self.config.container_port}/tcp": host_port}, + volumes=self._volume_bindings(), + environment=environment or None, + command=command, + labels={"nat_session_id": session_id}, + ) + docker_client.close() + base_url = f"http://127.0.0.1:{host_port}" + return container.id, base_url + + def _stop_container(self, container_id: str) -> None: + docker_module: typing.Any = self._import_docker() + docker_client = docker_module.from_env() + try: + container = docker_client.containers.get(container_id) + except docker_module.errors.NotFound: + docker_client.close() + return + + try: + container.stop() + finally: + try: + container.remove(force=True) + except Exception: + pass + docker_client.close() + + +@add_registered_workspace(DockerWorkspaceConfig) +async def docker_workspace(config: DockerWorkspaceConfig) -> AsyncIterator[DockerWorkspaceManager]: + yield DockerWorkspaceManager(config) diff --git a/packages/nvidia_nat_workspace/src/nat/plugins/workspace/local.py b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/local.py new file mode 100644 index 0000000000..af312cdc28 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/local.py @@ -0,0 +1,82 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Local workspace implementation backed by a workspace API.""" + +from __future__ import annotations + +import threading +import typing +from collections.abc import AsyncIterator +from dataclasses import dataclass +from pathlib import Path + +from pydantic import Field + +from nat.cli.register_workflow import add_registered_workspace +from nat.data_models.workspace import WorkspaceBaseConfig +from nat.plugins.workspace.client import ApiWorkspace +from nat.plugins.workspace.client import ApiWorkspaceManagerBase +from nat.plugins.workspace.client import ApiWorkspaceSessionEntry +from nat.plugins.workspace.client import WorkspaceApiClient +from nat.plugins.workspace.server import WorkspaceApiServerHandle +from nat.plugins.workspace.server import start_workspace_api_server +from nat.plugins.workspace.server import stop_workspace_api_server + + +class LocalWorkspaceConfig(WorkspaceBaseConfig, name="local"): + """Configuration for local workspaces.""" + http_timeout_seconds: float = Field(default=30.0, description="HTTP timeout for workspace API requests.") + + +class LocalWorkspace(ApiWorkspace): + """Local workspace.""" + + def __init__(self, config: LocalWorkspaceConfig, api_client: WorkspaceApiClient, session_id: str | None = None): + super().__init__(config=config, api_client=api_client, session_id=session_id) + self.config = config + + +@dataclass +class _LocalBackend: + server: WorkspaceApiServerHandle | None + + +class LocalWorkspaceManager(ApiWorkspaceManagerBase[LocalWorkspaceConfig, LocalWorkspace, _LocalBackend]): + _sessions: typing.ClassVar[dict[str, ApiWorkspaceSessionEntry[_LocalBackend]]] = {} + _session_lock: typing.ClassVar[threading.Lock] = threading.Lock() + + def _build_workspace(self, entry: ApiWorkspaceSessionEntry[_LocalBackend]) -> LocalWorkspace: + session_root = self._session_working_directory(entry.session_id) + session_config = self.config.model_copy(update={"working_directory": session_root}) + return LocalWorkspace(config=session_config, api_client=entry.api_client, session_id=entry.session_id) + + def _session_working_directory(self, session_id: str) -> Path: + session_root = self.config.working_directory.resolve() / session_id + session_root.mkdir(parents=True, exist_ok=True) + return session_root + + async def _start_backend(self, session_id: str) -> tuple[str, _LocalBackend]: + server = start_workspace_api_server(self.config.working_directory) + return server.base_url, _LocalBackend(server=server) + + async def _shutdown_backend(self, backend: _LocalBackend | None) -> None: + if backend is None or backend.server is None: + return + stop_workspace_api_server(backend.server) + + +@add_registered_workspace(LocalWorkspaceConfig) +async def local_workspace(config: LocalWorkspaceConfig) -> AsyncIterator[LocalWorkspaceManager]: + yield LocalWorkspaceManager(config) diff --git a/packages/nvidia_nat_workspace/src/nat/plugins/workspace/register.py b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/register.py new file mode 100644 index 0000000000..d3f5adb37b --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/register.py @@ -0,0 +1,20 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from . import apptainer # noqa: F401 +from . import docker # noqa: F401 +from . import local # noqa: F401 +from . import remote # noqa: F401 +from . import workspace_actions # noqa: F401 diff --git a/packages/nvidia_nat_workspace/src/nat/plugins/workspace/remote.py b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/remote.py new file mode 100644 index 0000000000..d2a18c47d3 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/remote.py @@ -0,0 +1,72 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Remote workspace implementation backed by a runtime API.""" + +import threading +import typing +from collections.abc import AsyncIterator + +from pydantic import Field + +from nat.cli.register_workflow import add_registered_workspace +from nat.data_models.workspace import WorkspaceBaseConfig +from nat.plugins.workspace.client import ApiWorkspace +from nat.plugins.workspace.client import ApiWorkspaceManagerBase +from nat.plugins.workspace.client import ApiWorkspaceSessionEntry +from nat.plugins.workspace.client import WorkspaceApiClient +from nat.plugins.workspace.types import ImagePullPolicy + + +class RemoteWorkspaceConfig(WorkspaceBaseConfig, name="remote"): + """Configuration for remote workspaces.""" + + runtime_api_url: str = Field(description="Runtime API endpoint for workspace execution.") + runtime_api_key: str = Field(description="Runtime API key for workspace execution.") + image: str = Field(description="Runtime image to use for the workspace.") + image_pull_policy: ImagePullPolicy = Field(description="Policy for pulling the runtime image.", ) + http_timeout_seconds: float = Field(default=30.0, description="HTTP timeout for workspace API requests.") + + +class RemoteWorkspace(ApiWorkspace): + """Remote workspace.""" + + def __init__(self, config: RemoteWorkspaceConfig, api_client: WorkspaceApiClient, session_id: str | None = None): + super().__init__(config=config, api_client=api_client, session_id=session_id) + self.config = config + + +class RemoteWorkspaceManager(ApiWorkspaceManagerBase[RemoteWorkspaceConfig, RemoteWorkspace, None]): + _sessions: typing.ClassVar[dict[str, ApiWorkspaceSessionEntry[None]]] = {} + _session_lock: typing.ClassVar[threading.Lock] = threading.Lock() + + def _build_workspace(self, entry: ApiWorkspaceSessionEntry[None]) -> RemoteWorkspace: + return RemoteWorkspace(config=self.config, api_client=entry.api_client, session_id=entry.session_id) + + def _endpoint_override(self) -> str | None: + return self.config.endpoint or self.config.runtime_api_url + + def _session_headers(self, session_id: str) -> dict[str, str]: + headers = super()._session_headers(session_id) + if self.config.runtime_api_key: + headers["Authorization"] = f"Bearer {self.config.runtime_api_key}" + return headers + + async def _start_backend(self, session_id: str) -> tuple[str, None]: + raise RuntimeError("Remote workspaces do not start a local backend.") + + +@add_registered_workspace(RemoteWorkspaceConfig) +async def remote_workspace(config: RemoteWorkspaceConfig) -> AsyncIterator["RemoteWorkspaceManager"]: + yield RemoteWorkspaceManager(config) diff --git a/packages/nvidia_nat_workspace/src/nat/plugins/workspace/server.py b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/server.py new file mode 100644 index 0000000000..ee4c5ac003 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/server.py @@ -0,0 +1,468 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Workspace API server for session-scoped operations.""" + +import argparse +import asyncio +import inspect +import io +import multiprocessing +import multiprocessing.process +import os +import socket +import tarfile +import threading +import time +import typing +import uuid +from dataclasses import dataclass +from dataclasses import field +from datetime import UTC +from datetime import datetime +from pathlib import Path + +import httpx +from fastapi import FastAPI +from fastapi import HTTPException +from fastapi import Request +from fastapi import Response +from fastapi.responses import FileResponse +from fastapi.responses import JSONResponse +from fastapi.responses import StreamingResponse +from pydantic import BaseModel +from pydantic import Field +from pydantic import ValidationError + +from nat.cli.type_registry import GlobalTypeRegistry +from nat.data_models.skill import Skill +from nat.data_models.workspace import ActionRequest +from nat.data_models.workspace import ActionResult +from nat.data_models.workspace import ActionStatus +from nat.workspace.types import ActionContext +from nat.workspace.types import WorkspaceAction +from nat.workspace.types import WorkspaceActionSchema + +SESSION_HEADER = "X-Workspace-Session" + + +@dataclass +class WorkspaceApiServerHandle: + """Handle for a running workspace API server process.""" + + process: multiprocessing.process.BaseProcess + host: str + port: int + root_path: Path + + @property + def base_url(self) -> str: + return f"http://{self.host}:{self.port}" + + +class SkillCreateRequest(BaseModel): + """Request payload for creating a skill (portable dict format).""" + + name: str = Field(description="Skill name.") + description: str = Field(description="Skill description.") + license: str | None = Field(default=None, description="License identifier.") + compatibility: str | None = Field(default=None, description="Compatibility info.") + allowed_tools: list[str] = Field(default_factory=list, description="Allowed tools.") + metadata: dict[str, str] = Field(default_factory=dict, description="Metadata key-value pairs.") + content: str = Field(default="", description="Skill body / instructions.") + resources: dict[str, str] = Field(default_factory=dict, description="Base64-encoded resource files.") + + +@dataclass +class SessionState: + """In-memory state for a workspace session.""" + + root: Path + skills: dict[str, Skill] = field(default_factory=dict) + + +class SessionStore: + """Thread-safe store of session state and filesystem roots.""" + + def __init__(self, base_root: Path): + self._base_root = base_root + self._lock = threading.Lock() + self._sessions: dict[str, SessionState] = {} + + def get_session(self, session_id: str) -> SessionState: + with self._lock: + session = self._sessions.get(session_id) + if session is None: + session_root = (self._base_root / session_id).resolve() + session_root.mkdir(parents=True, exist_ok=True) + session = SessionState(root=session_root) + self._sessions[session_id] = session + return session + + +class ActionInstanceStore: + """Manages per-session action instances.""" + + def __init__(self) -> None: + self._lock = asyncio.Lock() + self._instances: dict[str, dict[str, WorkspaceAction]] = {} + + async def get_action(self, session_id: str, action_cls: type[WorkspaceAction], + context: ActionContext) -> WorkspaceAction: + async with self._lock: + session_actions = self._instances.setdefault(session_id, {}) + action = session_actions.get(action_cls.name) + if action is None: + action = action_cls() + action.set_context(context) + session_actions[action_cls.name] = action + created = True + else: + action.set_context(context) + created = False + + if created: + await action.__aenter__() + return action + + async def close_session(self, session_id: str) -> None: + async with self._lock: + actions = self._instances.pop(session_id, {}) + for action in actions.values(): + await action.__aexit__(None, None, None) + + +def _require_session_id(request: Request) -> str: + session_id = request.headers.get(SESSION_HEADER) + if not session_id: + raise HTTPException(status_code=400, detail=f"Missing {SESSION_HEADER} header.") + return session_id + + +def _resolve_path(root: Path, relative_path: str | None) -> Path: + rel = Path(relative_path or ".") + if rel.is_absolute(): + rel = Path(str(rel).lstrip("/")) + resolved = (root / rel).resolve() + if root != resolved and root not in resolved.parents: + raise HTTPException(status_code=400, detail="Invalid path outside workspace root.") + return resolved + + +def _safe_extract(archive: tarfile.TarFile, destination: Path) -> None: + root = destination.resolve() + for member in archive.getmembers(): + member_path = (root / member.name).resolve() + if root != member_path and root not in member_path.parents: + raise HTTPException(status_code=400, detail=f"Archive member escapes destination: {member.name}") + archive.extractall(path=destination) + + +def _action_schema_payload(schema: WorkspaceActionSchema) -> dict[str, object]: + return { + "name": schema.name, + "description": schema.description, + "parameters": [{ + "type": param.type, "description": param.description + } for param in schema.parameters], + "result": { + "type": schema.result.type, + "description": schema.result.description, + }, + } + + +def _action_request_from_payload(action_name: str, payload: object) -> ActionRequest: + if payload is None: + payload = {} + if not isinstance(payload, dict): + raise HTTPException(status_code=400, detail="Action payload must be a JSON object.") + payload = typing.cast(dict[str, typing.Any], payload) + + payload_keys = {"action_name", "action_id", "arguments", "timestamp", "model_metadata"} + if payload_keys.intersection(payload.keys()): + try: + action_request = ActionRequest.model_validate(payload) + except ValidationError as exc: + raise HTTPException(status_code=400, detail="Invalid action request payload.") from exc + if action_request.action_name != action_name: + raise HTTPException(status_code=400, detail="Action name does not match the route.") + return action_request + + args = payload.get("args", {}) + if args is None: + args = {} + if not isinstance(args, dict): + raise HTTPException(status_code=400, detail="Action args must be an object.") + + return ActionRequest( + action_id=uuid.uuid4(), + action_name=action_name, + arguments=args, + timestamp=datetime.now(tz=UTC), + ) + + +def create_workspace_app(root_path: Path) -> FastAPI: + """Create the workspace API app rooted at the provided path.""" + from nat.runtime.loader import PluginTypes + from nat.runtime.loader import discover_and_register_plugins + + discover_and_register_plugins(PluginTypes.WORKSPACE_ACTION) + + app = FastAPI() + root_path = root_path.resolve() + root_path.mkdir(parents=True, exist_ok=True) + store = SessionStore(root_path) + action_store = ActionInstanceStore() + + @app.get("/api/health") + async def health_check() -> dict[str, str]: + return {"status": "ok"} + + @app.get("/api/actions") + async def list_actions(request: Request) -> JSONResponse: + payload = [ + _action_schema_payload(action.action_schema) + for action in GlobalTypeRegistry.get().get_registered_workspace_actions() + ] + return JSONResponse({"actions": payload}) + + @app.get("/api/skills") + async def list_skills(request: Request) -> JSONResponse: + session = store.get_session(_require_session_id(request)) + payload = [{"name": s.name, "description": s.description} for s in session.skills.values()] + return JSONResponse({"skills": payload}) + + @app.get("/api/skills/{skill_name}") + async def get_skill(skill_name: str, request: Request) -> JSONResponse: + session = store.get_session(_require_session_id(request)) + skill = session.skills.get(skill_name) + if skill is None: + raise HTTPException(status_code=404, detail="Skill not found.") + return JSONResponse(skill.to_portable_dict()) + + @app.post("/api/skills/new") + async def create_skill(request: Request, payload: SkillCreateRequest) -> JSONResponse: + session = store.get_session(_require_session_id(request)) + if payload.name in session.skills: + raise HTTPException(status_code=409, detail="Skill already exists.") + try: + skill = Skill.from_portable_dict(payload.model_dump()) + except Exception as exc: + raise HTTPException(status_code=422, detail=f"Invalid skill data: {exc}") from exc + session.skills[skill.name] = skill + return JSONResponse({"status": "created", "name": skill.name}) + + @app.post("/api/actions/{action_name}/execute") + async def execute_action(action_name: str, request: Request) -> JSONResponse: + session_id = _require_session_id(request) + session = store.get_session(session_id) + payload = await request.json() + action_request = _action_request_from_payload(action_name, payload) + + try: + action_info = GlobalTypeRegistry.get().get_workspace_action(action_request.action_name) + except KeyError as exc: + raise HTTPException(status_code=404, detail="Action not found.") from exc + action_cls = typing.cast(type[WorkspaceAction], action_info.action_cls) + + context = ActionContext(session_id=session_id, root_path=session.root) + action = await action_store.get_action(session_id, action_cls, context) + start_time = time.monotonic() + try: + output = action.execute(context=context, args=action_request.arguments) + if inspect.isawaitable(output): + output = await output + status = ActionStatus.SUCCESS + error_message = None + except Exception as exc: # noqa: BLE001 + status = ActionStatus.FAILURE + error_message = f"{type(exc).__name__}: {exc}" + output = None + + result = ActionResult( + action_id=action_request.action_id, + status=status, + output=output, + error_message=error_message, + execution_time=time.monotonic() - start_time, + ) + return JSONResponse(result.model_dump(mode="json", exclude_none=True)) + + @app.post("/api/session/close") + async def close_session(request: Request) -> JSONResponse: + session_id = _require_session_id(request) + await action_store.close_session(session_id) + return JSONResponse({"status": "closed"}) + + @app.post("/api/file/upload") + async def upload_file( + request: Request, + type: str, # noqa: A002 + destination: str | None = None) -> JSONResponse: + session = store.get_session(_require_session_id(request)) + session_root = session.root + if destination is None or destination == "": + if type == "folder": + destination = "." + else: + destination = f"upload-{uuid.uuid4().hex}" + dest = _resolve_path(session_root, destination) + content = await request.body() + + if type == "file": + dest.parent.mkdir(parents=True, exist_ok=True) + dest.write_bytes(content) + return JSONResponse({"status": "uploaded", "path": str(dest.relative_to(session_root))}) + if type == "folder": + dest.mkdir(parents=True, exist_ok=True) + with tarfile.open(fileobj=io.BytesIO(content), mode="r:gz") as archive: + _safe_extract(archive, dest) + return JSONResponse({"status": "uploaded", "path": str(dest.relative_to(session_root))}) + + raise HTTPException(status_code=400, detail="Invalid upload type.") + + @app.get("/api/file/download", response_model=None) + async def download_file(request: Request, type: str, path: str) -> Response: # noqa: A002 + session = store.get_session(_require_session_id(request)) + session_root = session.root + target = _resolve_path(session_root, path) + if not target.exists(): + raise HTTPException(status_code=404, detail="Path not found.") + + if type == "file": + return FileResponse(target) + if type == "folder": + archive_buffer = io.BytesIO() + with tarfile.open(fileobj=archive_buffer, mode="w:gz") as archive: + archive.add(target, arcname=".") + archive_buffer.seek(0) + return StreamingResponse(archive_buffer, media_type="application/gzip") + + raise HTTPException(status_code=400, detail="Invalid download type.") + + @app.get("/api/file/list") + async def list_file(request: Request, type: str, path: str | None = None) -> JSONResponse: # noqa: A002 + session = store.get_session(_require_session_id(request)) + session_root = session.root + target = _resolve_path(session_root, path) + if not target.exists(): + raise HTTPException(status_code=404, detail="Path not found.") + + if type == "file": + content = target.read_text(encoding="utf-8", errors="replace") + return JSONResponse({"type": "file", "content": content}) + if type == "folder": + entries = [{ + "name": entry.name, "type": "folder" if entry.is_dir() else "file" + } for entry in sorted(target.iterdir(), key=lambda item: item.name)] + return JSONResponse({"type": "folder", "entries": entries}) + + raise HTTPException(status_code=400, detail="Invalid list type.") + + @app.post("/api/file/delete") + async def delete_file(request: Request, type: str, path: str) -> JSONResponse: # noqa: A002 + session = store.get_session(_require_session_id(request)) + session_root = session.root + target = _resolve_path(session_root, path) + if not target.exists(): + raise HTTPException(status_code=404, detail="Path not found.") + + if type == "file": + target.unlink() + return JSONResponse({"status": "deleted"}) + if type == "folder": + for child in sorted(target.rglob("*"), reverse=True): + if child.is_file() or child.is_symlink(): + child.unlink() + elif child.is_dir(): + child.rmdir() + target.rmdir() + return JSONResponse({"status": "deleted"}) + + raise HTTPException(status_code=400, detail="Invalid delete type.") + + return app + + +def _resolve_root_path(root_path: str | None) -> Path: + if root_path: + return Path(root_path) + env_root = os.environ.get("NAT_WORKSPACE_ROOT") + if env_root: + return Path(env_root) + return Path.cwd() + + +def run_workspace_api_server(root_path: str | None, host: str, port: int) -> None: + """Run the workspace API server with the given root.""" + import uvicorn + + app = create_workspace_app(_resolve_root_path(root_path)) + uvicorn.run(app, host=host, port=port, log_level="warning") + + +def _wait_for_server(host: str, port: int, timeout_seconds: float) -> None: + url = f"http://{host}:{port}/api/health" + deadline = time.time() + timeout_seconds + while time.time() < deadline: + try: + response = httpx.get(url, timeout=1.0) + if response.status_code == 200: + return + except httpx.RequestError: + time.sleep(0.1) + raise RuntimeError("Workspace API server failed to start.") + + +def _allocate_port() -> int: + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock: + sock.bind(("127.0.0.1", 0)) + return sock.getsockname()[1] + + +def start_workspace_api_server(root_path: Path, + host: str = "127.0.0.1", + timeout_seconds: float = 10.0) -> WorkspaceApiServerHandle: + """Start the workspace API server in a background process.""" + port = _allocate_port() + ctx = multiprocessing.get_context("spawn") + process = ctx.Process(target=run_workspace_api_server, args=(str(root_path), host, port), daemon=True) + process.start() + _wait_for_server(host=host, port=port, timeout_seconds=timeout_seconds) + return WorkspaceApiServerHandle(process=process, host=host, port=port, root_path=root_path) + + +def stop_workspace_api_server(handle: WorkspaceApiServerHandle, timeout_seconds: float = 5.0) -> None: + """Stop a running workspace API server process.""" + if handle.process.is_alive(): + handle.process.terminate() + handle.process.join(timeout=timeout_seconds) + if handle.process.is_alive(): + handle.process.kill() + + +def main() -> None: + """Run the workspace API server from the command line.""" + parser = argparse.ArgumentParser(description="Workspace API server") + parser.add_argument("--host", default="0.0.0.0", help="Host interface to bind.") + parser.add_argument("--port", type=int, default=8000, help="Port to bind.") + parser.add_argument("--root", default=None, help="Workspace root path.") + args = parser.parse_args() + run_workspace_api_server(root_path=args.root, host=args.host, port=args.port) + + +if __name__ == "__main__": + main() diff --git a/packages/nvidia_nat_workspace/src/nat/plugins/workspace/types.py b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/types.py new file mode 100644 index 0000000000..296b746424 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/types.py @@ -0,0 +1,30 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from pathlib import Path +from typing import Literal +from typing import TypeAlias + +from pydantic import BaseModel + +MountMode: TypeAlias = Literal["r", "rw"] + +ImagePullPolicy: TypeAlias = Literal["Always", "IfNotPresent", "Never"] + + +class Mount(BaseModel): + host_path: Path + container_path: Path + access_mode: MountMode diff --git a/packages/nvidia_nat_workspace/src/nat/plugins/workspace/workspace_actions.py b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/workspace_actions.py new file mode 100644 index 0000000000..caa5d4cbbf --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/plugins/workspace/workspace_actions.py @@ -0,0 +1,137 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Function group that exposes workspace actions as callable functions.""" + +from __future__ import annotations + +import logging +import typing + +from pydantic import BaseModel +from pydantic import Field +from pydantic import create_model + +from nat.builder.function import FunctionGroup +from nat.cli.register_workflow import register_function_group +from nat.data_models.function import FunctionGroupBaseConfig +from nat.workspace.types import TypeSchema +from nat.workspace.types import WorkspaceActionSchema + +if typing.TYPE_CHECKING: + from nat.builder.builder import Builder + +logger = logging.getLogger(__name__) + +# Mapping from TypeSchema type strings to Python types. +_TYPE_MAP: dict[str, type] = { + "string": str, + "number": float, + "integer": int, + "boolean": bool, + "object": dict, + "array": list, + "path": str, + "content": str, +} + + +def _parse_param_name(ts: TypeSchema) -> tuple[str, str]: + """Extract (param_name, description) from a TypeSchema. + + The convention is ``"param_name: Description text."``; if no colon is + present the whole description is used as both name and description. + """ + desc = ts.description + if ":" in desc: + name, _, remainder = desc.partition(":") + return name.strip(), remainder.strip() + return desc.strip(), desc.strip() + + +def _build_input_model(schema: WorkspaceActionSchema) -> type[BaseModel] | None: + """Dynamically create a Pydantic model from a WorkspaceActionSchema's parameters.""" + if not schema.parameters: + return None + + field_definitions: dict[str, typing.Any] = {} + for ts in schema.parameters: + param_name, description = _parse_param_name(ts) + python_type = _TYPE_MAP.get(ts.type, typing.Any) + field_definitions[param_name] = ( + python_type, + Field(description=description), + ) + + model_name = f"{schema.name}_input" + return create_model(model_name, **field_definitions) + + +class WorkspaceActionsConfig(FunctionGroupBaseConfig, name="workspace_actions"): + """Configuration for exposing workspace actions as a function group. + + When used with the Builder system, workspace actions are automatically + discovered from the configured workspace and registered as functions. + """ + + +@register_function_group(config_type=WorkspaceActionsConfig) +async def build_workspace_actions(config: WorkspaceActionsConfig, builder: Builder): + """Build a function group from workspace actions. + + Discovers available actions from the configured workspace and exposes + each as a callable function within the group. + """ + from nat.data_models.workspace import ActionResult + from nat.data_models.workspace import ActionStatus + + workspace_manager = await builder.get_workspace_manager() + if workspace_manager is None: + raise RuntimeError("No workspace configured. WorkspaceActionsConfig requires a workspace " + "to be configured in the workflow.") + + async with workspace_manager as workspace: + # Wire guardrails from config → live instances + guardrails = await builder.get_workspace_guardrails() + for guardrail in guardrails: + workspace.add_workspace_guardrail(guardrail) + + action_schemas = await workspace.get_actions() + + group = FunctionGroup(config=config) + + for schema in action_schemas: + ws = workspace + input_model = _build_input_model(schema) + + # Capture loop variables in a factory to avoid late-binding issues. + def _make_execute(action_name: str = schema.name, bound_ws=ws): + + async def _execute(**kwargs: typing.Any, ) -> str: + result: ActionResult = await bound_ws.execute_action(action_name, kwargs) + if result.status != ActionStatus.SUCCESS: + raise RuntimeError(result.error_message or f"Action failed with status {result.status}") + return str(result.output) if result.output is not None else "" + + return _execute + + group.add_function( + name=schema.name, + fn=_make_execute(), + description=schema.description, + input_schema=input_model, + ) + + logger.info("Registered %d workspace actions as functions", len(action_schemas)) + yield group diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/__init__.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/__init__.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/__init__.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/__init__.py new file mode 100644 index 0000000000..bcd923c929 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/__init__.py @@ -0,0 +1,14 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/edit_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/edit_action.py new file mode 100644 index 0000000000..c36e28dd4d --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/edit_action.py @@ -0,0 +1,343 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Edit action implementation using advanced replacement strategies with fuzzy matching fallbacks.""" + +from __future__ import annotations + +import errno +import typing +from pathlib import Path + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction +from nat.workspace_actions.workspace.utils.file_state import ( + clear_file_read_state, + get_file_read_state, + register_file_read, +) +from nat.workspace_actions.workspace.utils.levenshtein import find_similar_file +from nat.workspace_actions.workspace.utils.path_utils import resolve_workspace_path +from nat.workspace_actions.workspace.utils.replacers import ( + has_multiple_matches, + perform_advanced_replacement, +) + + +SMART_QUOTE_REPLACEMENTS: dict[str, str] = { + "\u2019": "'", + "\u2018": "'", + "\u201C": '"', + "\u201D": '"', + "\u2013": "-", + "\u2014": "-", + "\u2026": "...", +} + +_REPLACER_STRATEGIES = [ + "SimpleReplacer", + "LineTrimmedReplacer", + "BlockAnchorReplacer", + "WhitespaceNormalizedReplacer", + "IndentationFlexibleReplacer", + "EscapeNormalizedReplacer", + "TrimmedBoundaryReplacer", + "ContextAwareReplacer", + "MultiOccurrenceReplacer", +] + + +def _normalize_line_endings(text: str) -> str: + """Normalize CRLF line endings to LF.""" + return text.replace("\r\n", "\n") + + +def _normalize_smart_quotes(text: str) -> str: + """Replace smart/curly quotes and dashes with ASCII equivalents.""" + normalized = text + for source, target in SMART_QUOTE_REPLACEMENTS.items(): + normalized = normalized.replace(source, target) + return normalized + + +def _generate_edit_snippet(old_content: str, new_content: str) -> str | None: + """Generate a context diff snippet highlighting changed lines.""" + old_lines = old_content.split("\n") + new_lines = new_content.split("\n") + max_length = max(len(old_lines), len(new_lines)) + + first_changed = -1 + last_changed = -1 + for index in range(max_length): + old_line = old_lines[index] if index < len(old_lines) else None + new_line = new_lines[index] if index < len(new_lines) else None + if old_line != new_line: + if first_changed == -1: + first_changed = index + last_changed = index + + if first_changed == -1: + return None + + context = 3 + start = max(0, first_changed - context) + end = min(max(len(new_lines) - 1, 0), last_changed + context) + + snippet_lines: list[str] = [] + for index in range(start, end + 1): + line_number = index + 1 + line_text = new_lines[index] if index < len(new_lines) else "" + marker = "\u2192" if first_changed <= index <= last_changed else " " + snippet_lines.append(f"{line_number:>4}{marker} {line_text}") + return "\n".join(snippet_lines) + + +def _get_file_mtime(file_path: Path) -> float | None: + """Get file modification time, or None on error.""" + try: + return file_path.stat().st_mtime + except OSError: + return None + + +def _format_not_found(path: Path) -> str: + """Format a file-not-found message with optional similar-file suggestion.""" + suggestion = find_similar_file(str(path)) + if suggestion: + return f"File not found: {path}. Did you mean: {suggestion}?" + return f"File not found: {path}." + + +def perform_edit( + file_path: str, + old_string: str, + new_string: str, + replace_all: bool, + root_path: Path, + session_id: str, +) -> dict[str, typing.Any]: + """Perform a single edit operation on a file. + + This is the core edit logic, extracted so it can be reused by multi_edit_action. + + Returns a dict with keys: path, replacements, modified, snippet, replacer_used. + Raises ValueError or FileNotFoundError on failure. + """ + path = resolve_workspace_path(file_path, root_path) + + if old_string != "" and old_string == new_string: + raise ValueError("old_string and new_string are identical") + + # --- create mode --- + if old_string == "": + if path.exists(): + try: + existing_content = path.read_text(encoding="utf-8") + if existing_content.strip(): + raise ValueError( + "Cannot create - file already exists and is not empty." + ) + except OSError: + # If file is unreadable we still attempt to overwrite in create mode. + pass + + path.parent.mkdir(parents=True, exist_ok=True) + path.write_text(new_string, encoding="utf-8") + clear_file_read_state(session_id, str(path)) + return { + "path": str(path), + "replacements": 1, + "modified": True, + "snippet": _generate_edit_snippet("", new_string), + "replacer_used": None, + } + + # --- file must exist for replacement --- + if not path.exists(): + raise FileNotFoundError(_format_not_found(path)) + + # --- read-before-edit validation --- + read_state = get_file_read_state(session_id, str(path)) + if read_state is None: + content_for_state = _normalize_line_endings(path.read_text(encoding="utf-8")) + register_file_read(session_id, str(path), content_for_state) + read_state = get_file_read_state(session_id, str(path)) + + current_mtime = _get_file_mtime(path) + if read_state is not None and current_mtime is not None: + if current_mtime > read_state.timestamp: + current_content = _normalize_line_endings(path.read_text(encoding="utf-8")) + if current_content != read_state.content: + raise ValueError("File has been modified since you last read it.") + + content = _normalize_line_endings(path.read_text(encoding="utf-8")) + original_content = content + + normalized_old = _normalize_smart_quotes(old_string) + normalized_new = _normalize_smart_quotes(new_string) + + # --- try advanced replacement --- + replacement = perform_advanced_replacement( + content, + old_string, + new_string, + replace_all, + ) + if replacement is None and normalized_old != old_string: + replacement = perform_advanced_replacement( + content, + normalized_old, + normalized_new, + replace_all, + ) + + if replacement is None: + multiple_matches = has_multiple_matches(content, old_string) or ( + normalized_old != old_string + and has_multiple_matches(content, normalized_old) + ) + if multiple_matches and not replace_all: + raise ValueError( + "String matches multiple locations. Add more context or use " + "replace_all=True." + ) + strategies = ", ".join(_REPLACER_STRATEGIES) + raise ValueError( + "String not found in file. Matching strategies attempted: " + f"{strategies}." + ) + + path.write_text(replacement.new_content, encoding="utf-8") + clear_file_read_state(session_id, str(path)) + snippet = _generate_edit_snippet(original_content, replacement.new_content) + + replacer_used: str | None = None + if replacement.replacer_used != "SimpleReplacer": + replacer_used = replacement.replacer_used + + return { + "path": str(path), + "replacements": replacement.replaced_count, + "modified": True, + "snippet": snippet, + "replacer_used": replacer_used, + } + + +@register_workspace_action +class EditAction(WorkspaceAction): + """Edit file content via string replacement with fuzzy matching fallbacks.""" + + name = "edit" + description = ( + "Edit file content via string replacement with context snippets showing changes.\n" + "\n" + "Uses 9 advanced matching strategies for robust replacements:\n" + "1. Exact match\n" + "2. Line-trimmed (ignores leading/trailing whitespace per line)\n" + "3. Block anchor (first/last lines as anchors)\n" + "4. Whitespace normalized\n" + "5. Indentation flexible\n" + "6. Escape normalized\n" + "7. Trimmed boundary\n" + "8. Context aware\n" + "9. Multi-occurrence (handles replace_all mode)\n" + "\n" + "Guidelines:\n" + "- The old_string should match the file content (tries multiple strategies if exact match fails)\n" + "- Include enough context (3-5 lines before/after) to ensure uniqueness\n" + "- If old_string appears multiple times, add more context or use replace_all=true\n" + "\n" + "File creation mode (old_string=''):\n" + "- Creates a new file if it doesn't exist\n" + "- Fails if file exists and is not empty (prevents accidental overwrites)\n" + "- Creates parent directories automatically\n" + "\n" + "The tool will:\n" + "- Show a context snippet with changed lines marked\n" + "- Detect if the file was modified since you last read it\n" + "- Suggest similar filenames if the file is not found\n" + "- Normalize smart quotes and Windows line endings automatically" + ) + parameters = [ + TypeSchema(type="string", description="file_path: Absolute or workspace-relative path to modify."), + TypeSchema(type="string", description="old_string: Text to replace. Empty string enables create mode."), + TypeSchema(type="string", description="new_string: Replacement text."), + TypeSchema(type="boolean", description="replace_all: Replace all matches instead of requiring uniqueness. Default false."), + ] + result = TypeSchema( + type="object", + description="Result payload with path, replacements, modified, snippet, and replacer_used.", + ) + + def __init__(self) -> None: + pass + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + file_path_str = args.get("file_path") + if not isinstance(file_path_str, str) or not file_path_str.strip(): + return {"is_error": True, "error": "Action requires a non-empty 'file_path' string."} + + old_string = args.get("old_string", "") + if not isinstance(old_string, str): + return {"is_error": True, "error": "'old_string' must be a string."} + + new_string = args.get("new_string", "") + if not isinstance(new_string, str): + return {"is_error": True, "error": "'new_string' must be a string."} + + replace_all = bool(args.get("replace_all", False)) + + try: + result = perform_edit( + file_path=file_path_str, + old_string=old_string, + new_string=new_string, + replace_all=replace_all, + root_path=context.root_path, + session_id=context.session_id, + ) + return result + except FileNotFoundError as exc: + path = resolve_workspace_path(file_path_str, context.root_path) + return { + "is_error": True, + "error": str(exc), + "path": str(path), + "replacements": 0, + "modified": False, + } + except OSError as exc: + path = resolve_workspace_path(file_path_str, context.root_path) + if exc.errno == errno.EACCES: + message = f"Permission denied: {file_path_str}" + else: + message = str(exc) + return { + "is_error": True, + "error": message, + "path": str(path), + "replacements": 0, + "modified": False, + } + except Exception as exc: + path = resolve_workspace_path(file_path_str, context.root_path) + return { + "is_error": True, + "error": str(exc), + "path": str(path), + "replacements": 0, + "modified": False, + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/multi_edit_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/multi_edit_action.py new file mode 100644 index 0000000000..357b2d3e0e --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/multi_edit_action.py @@ -0,0 +1,162 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Multi-edit action implementation for applying sequential edits to a single file.""" + +from __future__ import annotations + +import typing + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction +from nat.workspace_actions.workspace.file.edit_action import perform_edit +from nat.workspace_actions.workspace.utils.path_utils import resolve_workspace_path + + +@register_workspace_action +class MultiEditAction(WorkspaceAction): + """Apply multiple sequential edit operations to a single file.""" + + name = "multi_edit" + description = ( + "Apply multiple sequential edit operations to a single file.\n" + "\n" + "When to use:\n" + "- When you need to make several related changes to one file\n" + "- When changes should be applied together atomically\n" + "- More efficient than multiple separate edit calls\n" + "\n" + "How it works:\n" + "- Edits are applied sequentially in order\n" + "- If any edit fails, remaining edits are skipped\n" + "- Each edit uses the same validation as the edit action\n" + "\n" + "Important:\n" + "- Order matters: edits are applied sequentially\n" + "- Each old_string must be unique in the file (unless using replace_all)" + ) + parameters = [ + TypeSchema(type="string", description="file_path: Absolute or workspace-relative path to modify."), + TypeSchema( + type="array", + description=( + "edits: Ordered list of edit operations. " + "Each element is an object with old_string (string), new_string (string), " + "and optional replace_all (boolean, default false)." + ), + ), + ] + result = TypeSchema( + type="object", + description=( + "Result payload with path, total_edits, successful_edits, failed_edits, " + "total_replacements, modified, and results." + ), + ) + + def __init__(self) -> None: + pass + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + file_path_str = args.get("file_path") + if not isinstance(file_path_str, str) or not file_path_str.strip(): + return {"is_error": True, "error": "Action requires a non-empty 'file_path' string."} + + edits = args.get("edits") + if not isinstance(edits, list) or not edits: + return {"is_error": True, "error": "Action requires a non-empty 'edits' array."} + + path = resolve_workspace_path(file_path_str, context.root_path) + + if not path.exists(): + return { + "is_error": True, + "error": f"File does not exist: {path}", + "path": str(path), + "total_edits": len(edits), + "successful_edits": 0, + "failed_edits": len(edits), + "total_replacements": 0, + "modified": False, + "results": [], + } + + results: list[dict[str, typing.Any]] = [] + total_replacements = 0 + modified = False + + for index, edit in enumerate(edits): + if not isinstance(edit, dict): + results.append({ + "index": index, + "success": False, + "replacements": 0, + "error": "Each edit must be an object with old_string and new_string.", + }) + break + + old_string = edit.get("old_string", "") + new_string = edit.get("new_string", "") + replace_all = bool(edit.get("replace_all", False)) + + if not isinstance(old_string, str) or not isinstance(new_string, str): + results.append({ + "index": index, + "success": False, + "replacements": 0, + "error": "old_string and new_string must be strings.", + }) + break + + try: + result = perform_edit( + file_path=str(path), + old_string=old_string, + new_string=new_string, + replace_all=replace_all, + root_path=context.root_path, + session_id=context.session_id, + ) + replacements = int(result["replacements"]) + results.append({ + "index": index, + "success": True, + "replacements": replacements, + "error": None, + }) + total_replacements += replacements + modified = modified or bool(result["modified"]) + except Exception as exc: + results.append({ + "index": index, + "success": False, + "replacements": 0, + "error": str(exc), + }) + break + + successful_edits = sum(1 for item in results if item["success"]) + failed_edits = len(edits) - successful_edits + + return { + "path": str(path), + "total_edits": len(edits), + "successful_edits": successful_edits, + "failed_edits": failed_edits, + "total_replacements": total_replacements, + "modified": modified, + "results": results, + **({"is_error": True} if failed_edits > 0 else {}), + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/read_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/read_action.py new file mode 100644 index 0000000000..5e3d75577f --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/read_action.py @@ -0,0 +1,420 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Read action implementation for workspace files.""" + +from __future__ import annotations + +import errno +import json +import typing + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction +from nat.workspace_actions.workspace.utils.file_state import register_file_read +from nat.workspace_actions.workspace.utils.levenshtein import find_similar_file +from nat.workspace_actions.workspace.utils.path_utils import resolve_workspace_path + +try: + import nbformat +except Exception: # pragma: no cover - optional fallback when dependency missing + nbformat = None + + +MAX_TEXT_FILE_SIZE = 10 * 1024 * 1024 +MAX_LINE_LENGTH = 2000 +DEFAULT_MAX_LINES = 2000 +MAX_CONTENT_CHARS = 100000 + +IMAGE_EXTENSIONS = {".png", ".jpg", ".jpeg", ".gif", ".webp"} +_BINARY_SUFFIXES = ( + ".exe", + ".dll", + ".so", + ".dylib", + ".bin", + ".dat", + ".zip", + ".tar", + ".tar.gz", + ".tgz", + ".rar", + ".7z", + ".png", + ".jpg", + ".jpeg", + ".gif", + ".webp", + ".pdf", + ".pyc", + ".pyo", + ".class", + ".o", + ".obj", + ".a", + ".lib", + ".mp3", + ".mp4", + ".mov", + ".avi", + ".wav", + ".ttf", + ".otf", + ".woff", + ".woff2", +) + + +def _is_image_file(file_path: typing.Any) -> bool: + from pathlib import Path + + return Path(file_path).suffix.lower() in IMAGE_EXTENSIONS + + +def _is_binary_file(file_path: typing.Any) -> bool: + from pathlib import Path + + lowered = Path(file_path).name.lower() + return lowered.endswith(_BINARY_SUFFIXES) + + +def _format_file_size(size: int) -> str: + if size < 1024: + return f"{size}B" + if size < 1024 * 1024: + return f"{size / 1024:.1f}KB" + return f"{size / (1024 * 1024):.1f}MB" + + +def _parse_notebook(raw_content: str) -> dict[str, typing.Any]: + """Parse a notebook from raw JSON, trying nbformat first.""" + if nbformat is not None: + try: + notebook = nbformat.reads(raw_content, as_version=4) + if hasattr(notebook, "dict"): + return notebook.dict() + if isinstance(notebook, dict): + return notebook + except Exception: + # Fall back to plain JSON parsing for loosely-structured notebooks. + pass + parsed = json.loads(raw_content) + if not isinstance(parsed, dict): + raise ValueError("Notebook root must be an object") + return parsed + + +@register_workspace_action +class ReadAction(WorkspaceAction): + """Read a file from the workspace with numbered lines and pagination.""" + + name = "read" + description = ( + "Read a file from the workspace. Returns file contents with line numbers.\n" + "Lines are numbered starting at 1, using format: LINE_NUMBER|LINE_CONTENT\n" + "\n" + "Supports multiple file types:\n" + "- Text files: Returns content with line numbers\n" + "- Jupyter Notebooks (.ipynb): Returns formatted cells with outputs\n" + "- Images (PNG, JPEG, GIF, WebP): Returns image file metadata\n" + "\n" + "Features:\n" + "- Tracks file reads for edit validation\n" + "- Enforces 10MB size limit for text files\n" + "- Truncates long lines (>2000 chars)\n" + "- Suggests similar filenames if file not found\n" + "- Use offset/limit for pagination on large files" + ) + parameters = [ + TypeSchema(type="string", description="file_path: Absolute or workspace-relative path to read."), + TypeSchema(type="number", description="offset: Line number to start from (1-indexed). Defaults to 1."), + TypeSchema(type="number", description="limit: Maximum lines to return. Defaults to 2000."), + ] + result = TypeSchema( + type="object", + description="Result payload with content, total_lines, lines_returned, start_line, and end_line.", + ) + + def __init__(self) -> None: + pass + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + file_path_str = args.get("file_path") + if not isinstance(file_path_str, str) or not file_path_str.strip(): + return {"is_error": True, "error": "Action requires a non-empty 'file_path' string."} + + offset = args.get("offset") + limit = args.get("limit") + + file_path = resolve_workspace_path(file_path_str, context.root_path) + + # --- stat the file --- + try: + stats = file_path.stat() + except OSError as exc: + return self._file_stat_error(file_path, exc) + + if not file_path.is_file(): + return { + "is_error": True, + "error": f"Path is not a file: {file_path}", + "content": "", + "total_lines": 0, + "lines_returned": 0, + "start_line": 0, + "end_line": 0, + } + + # --- image detection --- + if _is_image_file(file_path): + content = f"[Image file: {_format_file_size(stats.st_size)}]" + register_file_read(context.session_id, str(file_path), content) + return { + "content": content, + "total_lines": 1, + "lines_returned": 1, + "start_line": 1, + "end_line": 1, + } + + # --- notebook reading --- + if file_path.suffix.lower() == ".ipynb": + return self._read_notebook(file_path, context.session_id) + + # --- binary detection --- + if _is_binary_file(file_path): + return { + "is_error": True, + "error": "This tool cannot read binary files.", + "content": "", + "total_lines": 0, + "lines_returned": 0, + "start_line": 0, + "end_line": 0, + } + + # --- file size check --- + if stats.st_size > MAX_TEXT_FILE_SIZE: + return { + "is_error": True, + "error": ( + f"File size ({_format_file_size(stats.st_size)}) exceeds the " + f"maximum allowed size ({_format_file_size(MAX_TEXT_FILE_SIZE)}). " + "Use offset/limit to read portions of the file." + ), + "content": "", + "total_lines": 0, + "lines_returned": 0, + "start_line": 0, + "end_line": 0, + } + + # --- read text content --- + try: + raw_content = file_path.read_text(encoding="utf-8") + except UnicodeDecodeError: + return { + "is_error": True, + "error": "This tool cannot read binary files.", + "content": "", + "total_lines": 0, + "lines_returned": 0, + "start_line": 0, + "end_line": 0, + } + except OSError as exc: + return { + "is_error": True, + "error": str(exc), + "content": "", + "total_lines": 0, + "lines_returned": 0, + "start_line": 0, + "end_line": 0, + } + + normalized = raw_content.replace("\r\n", "\n") + register_file_read(context.session_id, str(file_path), normalized) + + if normalized == "": + return { + "content": "File is empty.", + "total_lines": 0, + "lines_returned": 0, + "start_line": 0, + "end_line": 0, + } + + lines = normalized.split("\n") + total_lines = len(lines) + start_line = int(offset) if offset is not None else 1 + line_limit = int(limit) if limit is not None else DEFAULT_MAX_LINES + + if start_line > total_lines: + return { + "is_error": True, + "error": f"Start line {start_line} exceeds total lines {total_lines}.", + "content": "", + "total_lines": total_lines, + "lines_returned": 0, + "start_line": start_line, + "end_line": start_line, + } + + end_line = min(total_lines, start_line + line_limit - 1) + selected_lines = lines[start_line - 1 : end_line] + + formatted_lines: list[str] = [] + total_chars = 0 + actual_end_line = start_line + + for index, line in enumerate(selected_lines): + line_number = start_line + index + truncated_line = ( + f"{line[:MAX_LINE_LENGTH]}... [truncated]" + if len(line) > MAX_LINE_LENGTH + else line + ) + formatted = f"{line_number:>6}|{truncated_line}" + projected_size = total_chars + len(formatted) + 1 + if projected_size > MAX_CONTENT_CHARS and formatted_lines: + break + formatted_lines.append(formatted) + total_chars = projected_size + actual_end_line = line_number + + content = "\n".join(formatted_lines) + has_more = actual_end_line < total_lines + was_truncated = actual_end_line < end_line + if has_more or was_truncated: + remaining = total_lines - actual_end_line + content += ( + f"\n\n... [{remaining} more lines. " + f"Use offset={actual_end_line + 1} to continue.] ..." + ) + + return { + "content": content, + "total_lines": total_lines, + "lines_returned": len(formatted_lines), + "start_line": start_line, + "end_line": actual_end_line, + } + + def _read_notebook( + self, file_path: typing.Any, session_id: str + ) -> dict[str, typing.Any]: + """Read and format a Jupyter notebook.""" + try: + raw_content = file_path.read_text(encoding="utf-8") + except OSError as exc: + return { + "is_error": True, + "error": f"Failed to read notebook: {exc}", + "content": "", + "total_lines": 0, + "lines_returned": 0, + "start_line": 0, + "end_line": 0, + } + + try: + notebook = _parse_notebook(raw_content) + cells: list[dict[str, typing.Any]] = notebook.get("cells", []) + formatted_cells: list[str] = [] + for idx, cell in enumerate(cells, start=1): + cell_type = str(cell.get("cell_type", "unknown")) + source = cell.get("source", "") + if isinstance(source, list): + source_text = "".join(str(item) for item in source) + else: + source_text = str(source) + + output_block = "" + if cell_type == "code": + outputs = cell.get("outputs", []) + output_texts: list[str] = [] + for output in outputs if isinstance(outputs, list) else []: + text_value = output.get("text") + if text_value: + if isinstance(text_value, list): + output_texts.append("".join(str(v) for v in text_value)) + else: + output_texts.append(str(text_value)) + data = output.get("data") + if isinstance(data, dict) and "text/plain" in data: + plain = data["text/plain"] + if isinstance(plain, list): + output_texts.append("".join(str(v) for v in plain)) + else: + output_texts.append(str(plain)) + if output_texts: + joined_output = "\n".join(output_texts) + output_block = f"\n\n[Output]\n{joined_output}" + + formatted_cells.append( + ( + f"--- Cell {idx} ({cell_type}) ---\n" + f"{source_text}{output_block}" + ).rstrip() + ) + + content = ( + "\n\n".join(formatted_cells) + if formatted_cells + else "Notebook has no cells." + ) + register_file_read(session_id, str(file_path), raw_content.replace("\r\n", "\n")) + total_cells = len(formatted_cells) + return { + "content": content, + "total_lines": total_cells, + "lines_returned": total_cells, + "start_line": 1 if total_cells else 0, + "end_line": total_cells, + } + except Exception as exc: + return { + "is_error": True, + "error": f"Failed to parse notebook: {exc}", + "content": "", + "total_lines": 0, + "lines_returned": 0, + "start_line": 0, + "end_line": 0, + } + + def _file_stat_error( + self, file_path: typing.Any, exc: OSError + ) -> dict[str, typing.Any]: + """Build an error result for file stat failures.""" + if exc.errno == errno.ENOENT: + suggestion = find_similar_file(str(file_path)) + message = f"File not found: {file_path}." + if suggestion: + message = f"{message} Did you mean: {suggestion}?" + elif exc.errno == errno.EACCES: + message = f"Permission denied: {file_path}" + else: + message = str(exc) + return { + "is_error": True, + "error": message, + "content": "", + "total_lines": 0, + "lines_returned": 0, + "start_line": 0, + "end_line": 0, + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/write_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/write_action.py new file mode 100644 index 0000000000..1aff65c7a4 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/file/write_action.py @@ -0,0 +1,92 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Write action implementation for creating or overwriting workspace files.""" + +from __future__ import annotations + +import errno +import typing + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction +from nat.workspace_actions.workspace.utils.file_state import clear_file_read_state +from nat.workspace_actions.workspace.utils.path_utils import resolve_workspace_path + + +@register_workspace_action +class WriteAction(WorkspaceAction): + """Create or overwrite a file in the workspace.""" + + name = "write" + description = ( + "Create or overwrite a file in the workspace.\n" + "Creates the file and any necessary parent directories if they do not exist.\n" + "Overwrites the file if it already exists.\n" + "\n" + "Usage:\n" + "- Provide file_path (absolute or workspace-relative) and content string.\n" + "- For new files in nested directories, parent directories are created automatically.\n" + "- Prefer the edit action for modifying existing files (not write)." + ) + parameters = [ + TypeSchema(type="string", description="file_path: Absolute or workspace-relative file path to write."), + TypeSchema(type="string", description="content: File contents to write."), + ] + result = TypeSchema( + type="object", + description="Result payload with path, bytes_written, and created flags.", + ) + + def __init__(self) -> None: + pass + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + file_path_str = args.get("file_path") + if not isinstance(file_path_str, str) or not file_path_str.strip(): + return {"is_error": True, "error": "Action requires a non-empty 'file_path' string."} + + content = args.get("content") + if not isinstance(content, str): + return {"is_error": True, "error": "Action requires a 'content' string."} + + file_path = resolve_workspace_path(file_path_str, context.root_path) + parent = file_path.parent + created = not file_path.exists() + + try: + parent.mkdir(parents=True, exist_ok=True) + file_path.write_text(content, encoding="utf-8") + bytes_written = len(content.encode("utf-8")) + clear_file_read_state(context.session_id, str(file_path)) + return { + "path": str(file_path), + "bytes_written": bytes_written, + "created": created, + } + except OSError as exc: + if exc.errno == errno.EACCES: + message = f"Permission denied: {file_path}" + elif exc.errno == errno.EISDIR: + message = f"Is a directory: {file_path}" + else: + message = f"Write failed: {exc}" + return { + "is_error": True, + "error": message, + "path": str(file_path), + "bytes_written": 0, + "created": created, + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/register.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/register.py new file mode 100644 index 0000000000..e230268d86 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/register.py @@ -0,0 +1,27 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .terminal import bash_action # noqa: F401 +from .file import edit_action # noqa: F401 +from .file import multi_edit_action # noqa: F401 +from .file import read_action # noqa: F401 +from .file import write_action # noqa: F401 +from .search import glob_action # noqa: F401 +from .search import grep_action # noqa: F401 +from .search import list_action # noqa: F401 +from .todo import todo_read_action # noqa: F401 +from .todo import todo_write_action # noqa: F401 +from .web import web_search_action # noqa: F401 +from .web import web_fetch_action # noqa: F401 \ No newline at end of file diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/__init__.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/__init__.py new file mode 100644 index 0000000000..bcd923c929 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/__init__.py @@ -0,0 +1,14 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/glob_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/glob_action.py new file mode 100644 index 0000000000..be2318ffe2 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/glob_action.py @@ -0,0 +1,239 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Glob action implementation for file pattern matching.""" + +from __future__ import annotations + +import asyncio +import glob as glob_module +import os +import typing +from pathlib import Path, PurePosixPath + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction +from nat.workspace_actions.workspace.utils.path_utils import resolve_workspace_path +from nat.workspace_actions.workspace.utils.ripgrep_utils import get_ripgrep_path + +MAX_RESULTS = 1000 +_FALLBACK_EXCLUDED_DIRS: set[str] = {".git", "node_modules", "dist"} + + +def _normalize_pattern(pattern: str) -> str: + """Prepend ``**/`` when the pattern does not already start with it.""" + if not pattern.startswith("**/") and not pattern.startswith("/"): + return f"**/{pattern}" + return pattern + + +def _extract_search_path_from_pattern(pattern: str) -> tuple[Path | None, str]: + """Split an absolute glob pattern into a concrete directory and a relative glob.""" + expanded = os.path.expanduser(pattern) + if not os.path.isabs(expanded): + return None, expanded + + path_obj = Path(expanded) + parts = path_obj.parts + + search_parts: list[str] = [] + for part in parts: + if glob_module.has_magic(part): + break + search_parts.append(part) + + if not search_parts: + search_path = Path("/") + adjusted_pattern = expanded.lstrip("/") + else: + search_path = Path(*search_parts) + remaining_parts = parts[len(search_parts):] + adjusted_pattern = str(Path(*remaining_parts)) if remaining_parts else "**/*" + + return search_path.resolve(), adjusted_pattern + + +def _resolve_search_target( + glob_pattern: str, + target_directory: str | None, + root_path: Path, +) -> tuple[Path, str]: + """Resolve the search directory and normalise the glob pattern.""" + pattern = glob_pattern + + if target_directory: + search_directory = resolve_workspace_path(target_directory, root_path) + if os.path.isabs(pattern): + extracted_dir, extracted_pattern = _extract_search_path_from_pattern(pattern) + if extracted_dir is not None: + search_directory = extracted_dir + pattern = extracted_pattern + else: + extracted_dir, extracted_pattern = _extract_search_path_from_pattern(pattern) + search_directory = extracted_dir if extracted_dir is not None else root_path.resolve() + pattern = extracted_pattern + + return search_directory, _normalize_pattern(pattern) + + +async def _glob_with_ripgrep(search_directory: Path, pattern: str) -> list[str]: + """Run ripgrep in ``--files`` mode with a glob filter (async).""" + rg_path = get_ripgrep_path() + if rg_path is None: + raise RuntimeError("ripgrep is not available") + + process = await asyncio.create_subprocess_exec( + rg_path, + "--files", + "--glob", + pattern, + "--max-count", + str(MAX_RESULTS), + "--sort", + "modified", + str(search_directory), + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + + stdout_bytes, stderr_bytes = await asyncio.wait_for(process.communicate(), timeout=30) + stdout = stdout_bytes.decode("utf-8", errors="replace") if stdout_bytes else "" + stderr = stderr_bytes.decode("utf-8", errors="replace") if stderr_bytes else "" + + if process.returncode not in (0, 1): + raise RuntimeError(stderr.strip() or "ripgrep glob search failed") + if process.returncode == 1: + return [] + + files: list[str] = [] + for line in stdout.splitlines(): + candidate = line.strip() + if not candidate: + continue + candidate_path = Path(candidate) + if not candidate_path.is_absolute(): + candidate_path = (search_directory / candidate_path).resolve() + if candidate_path.is_file(): + files.append(str(candidate_path)) + + return files[:MAX_RESULTS] + + +def _glob_with_python(search_directory: Path, pattern: str) -> list[str]: + """Fallback glob using ``os.walk`` and ``PurePosixPath.match``.""" + normalized_pattern = pattern.replace("\\", "/") + candidate_patterns = [normalized_pattern] + if normalized_pattern.startswith("**/"): + candidate_patterns.append(normalized_pattern[3:]) + + matches: list[Path] = [] + for root, dirs, files in os.walk(search_directory): + dirs[:] = [d for d in dirs if d not in _FALLBACK_EXCLUDED_DIRS] + for file_name in files: + candidate = Path(root) / file_name + relative = candidate.relative_to(search_directory).as_posix() + if any( + PurePosixPath(relative).match(pattern_candidate) + for pattern_candidate in candidate_patterns + ): + matches.append(candidate) + + matches.sort(key=lambda path: path.stat().st_mtime, reverse=True) + return [str(path.resolve()) for path in matches[:MAX_RESULTS]] + + +@register_workspace_action +class GlobAction(WorkspaceAction): + """Find files matching a glob pattern in the workspace.""" + + name = "glob" + description = ( + "Find files matching a glob pattern in the workspace.\n" + "Returns matching file paths sorted by modification time (most recent first).\n" + "\n" + "Features:\n" + "- High-performance matching using ripgrep with automatic fallback\n" + "- Sorts results by modification time (most recent first)\n" + "- Supports standard glob patterns (*, **, ?, etc.)\n" + "- Automatically skips .git, node_modules, dist directories\n" + "- Patterns not starting with '**/' are automatically prepended with '**/' for recursive matching\n" + "\n" + "Use this tool when you need to find files by name patterns." + ) + parameters = [ + TypeSchema(type="string", description="glob_pattern: Glob pattern to match files."), + TypeSchema(type="string", description="target_directory: Optional absolute directory path to search in."), + ] + result = TypeSchema( + type="object", + description="Result with files, count, pattern, and search_directory.", + ) + + def __init__(self) -> None: + pass + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + glob_pattern = args.get("glob_pattern") + if not isinstance(glob_pattern, str) or not glob_pattern.strip(): + return { + "is_error": True, + "error": "A non-empty 'glob_pattern' string is required.", + "files": [], + "count": 0, + "pattern": str(glob_pattern), + "search_directory": str(context.root_path), + } + + target_directory = args.get("target_directory") + + try: + search_directory, pattern = _resolve_search_target( + glob_pattern, target_directory, context.root_path, + ) + + if not search_directory.is_dir(): + return { + "is_error": True, + "error": f"Path is not a directory: {search_directory}", + "files": [], + "count": 0, + "pattern": pattern, + "search_directory": str(search_directory), + } + + files: list[str] + if get_ripgrep_path() is not None: + try: + files = await _glob_with_ripgrep(search_directory, pattern) + except Exception: + files = _glob_with_python(search_directory, pattern) + else: + files = _glob_with_python(search_directory, pattern) + + return { + "files": files, + "count": len(files), + "pattern": pattern, + "search_directory": str(search_directory), + } + except Exception as exc: + return { + "is_error": True, + "error": str(exc), + "files": [], + "count": 0, + "pattern": glob_pattern, + "search_directory": str(context.root_path), + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/grep_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/grep_action.py new file mode 100644 index 0000000000..871bb18b65 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/grep_action.py @@ -0,0 +1,330 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Grep action implementation using ripgrep.""" + +from __future__ import annotations + +import asyncio +import re +import typing +from pathlib import Path + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction +from nat.workspace_actions.workspace.utils.ripgrep_utils import get_ripgrep_path + + +def _get_ripgrep_timeout() -> int: + """Use a longer timeout under WSL due to slower filesystem behaviour.""" + try: + release = Path("/proc/version").read_text(encoding="utf-8").lower() + if "microsoft" in release or "wsl" in release: + return 60 + except OSError: + pass + return 10 + + +def _is_eagain_error(stderr: str) -> bool: + lowered = stderr.lower() + return ( + "os error 11" in lowered + or "resource temporarily unavailable" in lowered + or "eagain" in lowered + ) + + +def _resolve_search_path(path_value: str | None, root_path: Path) -> Path: + """Resolve a search path relative to the workspace root.""" + if path_value is None: + return root_path + path = Path(path_value).expanduser() + if not path.is_absolute(): + path = root_path / path + return path.resolve() + + +def _build_args(args: dict[str, typing.Any], search_path: Path) -> list[str]: + """Build the ripgrep argument list from action parameters.""" + rg_args: list[str] = [] + + output_mode = args.get("output_mode", "content") + + if output_mode == "files_with_matches": + rg_args.append("-l") + elif output_mode == "count": + rg_args.append("-c") + else: + rg_args.append("-n") + + if args.get("case_insensitive"): + rg_args.append("-i") + + if output_mode == "content": + context_after = args.get("context_after") + if context_after is not None: + rg_args.extend(["-A", str(int(context_after))]) + context_before = args.get("context_before") + if context_before is not None: + rg_args.extend(["-B", str(int(context_before))]) + context = args.get("context") + if context is not None: + rg_args.extend(["-C", str(int(context))]) + + if args.get("multiline"): + rg_args.extend(["-U", "--multiline-dotall"]) + + rg_type = args.get("type") + if rg_type: + rg_args.extend(["--type", str(rg_type)]) + + glob = args.get("glob") + if glob: + rg_args.extend(["--glob", str(glob)]) + + rg_args.extend(["--max-columns", "500"]) + rg_args.extend(["--", str(args["pattern"]), str(search_path)]) + return rg_args + + +async def _run_ripgrep( + args: list[str], + cwd: str, + timeout_seconds: int, + *, + is_retry: bool = False, + use_single_threaded: bool = False, +) -> tuple[str, str, int, bool]: + """Execute ripgrep asynchronously. Returns (stdout, stderr, exit_code, use_single_threaded).""" + rg_path = get_ripgrep_path() + if rg_path is None: + return "", "ripgrep not found.", -1, use_single_threaded + + final_args = args + if use_single_threaded and not is_retry: + final_args = ["-j", "1", *args] + + process = await asyncio.create_subprocess_exec( + rg_path, + *final_args, + cwd=cwd, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + + try: + stdout_bytes, stderr_bytes = await asyncio.wait_for( + process.communicate(), timeout=timeout_seconds, + ) + stdout = stdout_bytes.decode("utf-8", errors="replace") if stdout_bytes else "" + stderr = stderr_bytes.decode("utf-8", errors="replace") if stderr_bytes else "" + exit_code = process.returncode if process.returncode is not None else -1 + except asyncio.TimeoutError: + process.kill() + stdout_bytes, stderr_bytes = await process.communicate() + stdout = stdout_bytes.decode("utf-8", errors="replace") if stdout_bytes else "" + stderr = stderr_bytes.decode("utf-8", errors="replace") if stderr_bytes else "" + timeout_message = "Timeout: ripgrep exceeded time limit" + stderr = (stderr + "\n" if stderr else "") + timeout_message + return stdout, stderr, -1, use_single_threaded + + if not is_retry and exit_code not in (0, 1) and _is_eagain_error(stderr): + return await _run_ripgrep( + ["-j", "1", *args], + cwd=cwd, + timeout_seconds=timeout_seconds, + is_retry=True, + use_single_threaded=True, + ) + + return stdout, stderr, exit_code, use_single_threaded + + +def _apply_pagination( + stdout: str, + offset: int, + head_limit: int | None, +) -> tuple[str, bool, int]: + """Slice output lines by offset and head_limit.""" + lines = stdout.splitlines() + total_lines = len(lines) + truncated = False + + processed = lines + if offset > 0: + processed = processed[offset:] + + if head_limit is not None and head_limit >= 0 and len(processed) > head_limit: + processed = processed[:head_limit] + truncated = True + + return "\n".join(processed), truncated, total_lines + + +def _count_results( + output: str, + output_mode: str, +) -> tuple[int, int]: + """Parse ripgrep output to count matches and files.""" + lines = [line for line in output.splitlines() if line.strip()] + + if output_mode == "files_with_matches": + count = len(lines) + return count, count + + if output_mode == "count": + match_count = 0 + files_matched = 0 + for line in lines: + match = re.search(r":(\d+)$", line) + if match: + match_count += int(match.group(1)) + files_matched += 1 + return match_count, files_matched + + # content mode + file_set: set[str] = set() + match_count = 0 + for line in lines: + match = re.match(r"^([^:]+):(\d+):", line) + if match: + file_set.add(match.group(1)) + match_count += 1 + return match_count, len(file_set) + + +@register_workspace_action +class GrepAction(WorkspaceAction): + """Search file contents using ripgrep.""" + + name = "grep" + description = ( + "Search file contents using ripgrep.\n" + "\n" + "Usage:\n" + "- ALWAYS use this grep action for search tasks. NEVER invoke grep or rg via bash.\n" + "- Supports full regex syntax (e.g., 'log.*Error', 'function\\\\s+\\\\w+', 'import.*from')\n" + "- Filter files with glob parameter (e.g., '*.js', '**/*.tsx') or type parameter (e.g., 'py', 'js', 'rust')\n" + "- Output modes: 'content' (default), 'files_with_matches', 'count'\n" + "\n" + "Pattern syntax (ripgrep, not grep):\n" + "- Literal braces need escaping: use 'interface\\\\{\\\\}' to find 'interface{}' in Go\n" + "- Word boundaries: use '\\\\bword\\\\b' to match whole words only\n" + "\n" + "Multiline matching:\n" + "- By default patterns match within single lines only\n" + "- For cross-line patterns, set multiline=true\n" + "\n" + "Best practices:\n" + "- Call multiple grep actions in parallel when searching for different patterns\n" + "- Use type parameter for efficiency when searching specific file types\n" + "- Use head_limit to cap results when you only need a few matches\n" + "- Use context/context_before/context_after to see surrounding code" + ) + parameters = [ + TypeSchema(type="string", description="pattern: Regex pattern to search for."), + TypeSchema(type="string", description="path: File or directory to search in. Defaults to workspace root."), + TypeSchema(type="string", description="glob: Glob file filter, e.g. '*.py'."), + TypeSchema(type="string", description="type: Ripgrep file type, e.g. py, js, rust."), + TypeSchema(type="boolean", description="case_insensitive: Case-insensitive search. Default false."), + TypeSchema(type="number", description="context_after: Lines to show after each match."), + TypeSchema(type="number", description="context_before: Lines to show before each match."), + TypeSchema(type="number", description="context: Lines to show before and after each match."), + TypeSchema(type="boolean", description="multiline: Enable multiline matching. Default false."), + TypeSchema(type="string", description="output_mode: content, files_with_matches, or count. Default content."), + TypeSchema(type="number", description="head_limit: Limit output entries after applying offset."), + TypeSchema(type="number", description="offset: Skip first N output entries. Default 0."), + ] + result = TypeSchema( + type="object", + description="Result with output, match_count, files_matched, truncated, total_lines, offset.", + ) + + def __init__(self) -> None: + self._use_single_threaded_mode = False + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + pattern = args.get("pattern") + if not isinstance(pattern, str) or not pattern.strip(): + return { + "is_error": True, + "error": "A non-empty 'pattern' string is required.", + "output": "", + "match_count": 0, + "files_matched": 0, + "truncated": False, + "total_lines": None, + "offset": None, + } + + if get_ripgrep_path() is None: + return { + "is_error": True, + "error": "ripgrep (rg) is not available in PATH.", + "output": "", + "match_count": 0, + "files_matched": 0, + "truncated": False, + "total_lines": None, + "offset": None, + } + + search_path = _resolve_search_path(args.get("path"), context.root_path) + rg_args = _build_args(args, search_path) + timeout_seconds = _get_ripgrep_timeout() + + stdout, stderr, exit_code, self._use_single_threaded_mode = await _run_ripgrep( + rg_args, + cwd=str(context.root_path), + timeout_seconds=timeout_seconds, + use_single_threaded=self._use_single_threaded_mode, + ) + + if exit_code not in (0, 1): + return { + "is_error": True, + "error": stderr.strip() or f"ripgrep exited with code {exit_code}", + "output": stdout, + "match_count": 0, + "files_matched": 0, + "truncated": False, + "total_lines": None, + "offset": None, + } + + offset = int(args.get("offset", 0)) + head_limit_raw = args.get("head_limit") + head_limit = int(head_limit_raw) if head_limit_raw is not None else None + + output, truncated, total_lines = _apply_pagination( + stdout=stdout, + offset=offset, + head_limit=head_limit, + ) + + output_mode = args.get("output_mode", "content") + match_count, files_matched = _count_results(output, output_mode) + displayed_output = output if output else "No matches found." + include_pagination = offset > 0 or head_limit is not None + + return { + "output": displayed_output, + "match_count": match_count, + "files_matched": files_matched, + "truncated": truncated, + "total_lines": total_lines if include_pagination else None, + "offset": offset if include_pagination else None, + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/list_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/list_action.py new file mode 100644 index 0000000000..fc03bc73a5 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/search/list_action.py @@ -0,0 +1,367 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""List action implementation for directory tree views.""" + +from __future__ import annotations + +import asyncio +import os +import typing +from pathlib import Path, PurePosixPath + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction +from nat.workspace_actions.workspace.utils.ripgrep_utils import get_ripgrep_path + +MAX_FILES = 200 + +DEFAULT_IGNORE_PATTERNS = [ + "node_modules/", + "__pycache__/", + ".git/", + "dist/", + "build/", + "target/", + "vendor/", + "bin/", + "obj/", + ".idea/", + ".vscode/", + ".zig-cache/", + "zig-out/", + ".coverage/", + "coverage/", + "tmp/", + "temp/", + ".cache/", + "cache/", + "logs/", + ".venv/", + "venv/", + "env/", + ".next/", + ".nuxt/", + ".output/", + ".turbo/", + ".parcel-cache/", + ".pytest_cache/", + ".mypy_cache/", + ".ruff_cache/", + ".tox/", + ".eggs/", + "*.egg-info/", + ".sass-cache/", + ".gradle/", + ".mvn/", + ".cargo/", + "Pods/", + ".dart_tool/", + ".pub-cache/", +] + + +def _resolve_root(path_value: str | None, root_path: Path) -> Path: + """Resolve the listing root directory.""" + if path_value is None: + return root_path.resolve() + root = Path(path_value).expanduser() + if not root.is_absolute(): + root = root_path / root + return root.resolve() + + +async def _get_files_with_ripgrep( + root: Path, + ignore_patterns: list[str], + show_hidden: bool, + max_depth: int | None, +) -> tuple[list[str], bool]: + """List files using ripgrep (async).""" + rg_path = get_ripgrep_path() + if rg_path is None: + raise RuntimeError("ripgrep is not available") + + cmd = [rg_path, "--files", "--sort", "path"] + for pattern in ignore_patterns: + cmd.extend(["--glob", f"!{pattern}"]) + if show_hidden: + cmd.append("--hidden") + if max_depth is not None: + cmd.extend(["--max-depth", str(max_depth)]) + cmd.append(str(root)) + + process = await asyncio.create_subprocess_exec( + *cmd, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + + stdout_bytes, stderr_bytes = await asyncio.wait_for(process.communicate(), timeout=30) + stdout = stdout_bytes.decode("utf-8", errors="replace") if stdout_bytes else "" + stderr = stderr_bytes.decode("utf-8", errors="replace") if stderr_bytes else "" + + if process.returncode not in (0, 1): + raise RuntimeError(stderr.strip() or "ripgrep list search failed") + + files: list[str] = [] + for line in stdout.splitlines(): + candidate = line.strip() + if not candidate: + continue + candidate_path = Path(candidate) + if not candidate_path.is_absolute(): + candidate_path = (root / candidate_path).resolve() + if candidate_path.is_file(): + files.append(str(candidate_path)) + + truncated = len(files) > MAX_FILES + return files[:MAX_FILES], truncated + + +def _is_ignored(path_value: str, ignore_patterns: list[str], *, is_dir: bool) -> bool: + """Check whether a relative path matches any ignore pattern.""" + for pattern in ignore_patterns: + if pattern.endswith("/"): + prefix = pattern[:-1] + if path_value == prefix or path_value.startswith(f"{prefix}/"): + return True + continue + + if PurePosixPath(path_value).match(pattern): + return True + + if is_dir and PurePosixPath(f"{path_value}/").match(pattern): + return True + + return False + + +def _get_files_with_walk( + root: Path, + ignore_patterns: list[str], + show_hidden: bool, + max_depth: int | None, +) -> tuple[list[str], bool]: + """Fallback file listing using ``os.walk``.""" + matches: list[str] = [] + truncated = False + + for current_root, dirs, files in os.walk(root, topdown=True): + current_root_path = Path(current_root) + relative_root = current_root_path.relative_to(root) + depth = 0 if str(relative_root) == "." else len(relative_root.parts) + + if max_depth is not None and depth >= max_depth: + dirs[:] = [] + + filtered_dirs: list[str] = [] + for dir_name in dirs: + if not show_hidden and dir_name.startswith("."): + continue + rel_dir = (current_root_path / dir_name).relative_to(root).as_posix() + if _is_ignored(rel_dir, ignore_patterns, is_dir=True): + continue + filtered_dirs.append(dir_name) + dirs[:] = filtered_dirs + + for file_name in files: + if not show_hidden and file_name.startswith("."): + continue + full_path = current_root_path / file_name + rel_path = full_path.relative_to(root).as_posix() + if _is_ignored(rel_path, ignore_patterns, is_dir=False): + continue + + matches.append(str(full_path.resolve())) + if len(matches) >= MAX_FILES: + truncated = True + return matches, truncated + + return matches, truncated + + +async def _get_files( + root: Path, + ignore_patterns: list[str], + show_hidden: bool, + max_depth: int | None, +) -> tuple[list[str], bool]: + """Retrieve file list, preferring ripgrep with os.walk fallback.""" + if get_ripgrep_path() is not None: + try: + return await _get_files_with_ripgrep( + root=root, + ignore_patterns=ignore_patterns, + show_hidden=show_hidden, + max_depth=max_depth, + ) + except Exception: + pass + + return _get_files_with_walk( + root=root, + ignore_patterns=ignore_patterns, + show_hidden=show_hidden, + max_depth=max_depth, + ) + + +def _build_tree(files: list[str], root: Path) -> tuple[str, int]: + """Construct a tree string and return the directory count.""" + tree: dict[str, typing.Any] = {"dirs": {}, "files": []} + directories: set[str] = set() + + for file_path in files: + relative = Path(file_path).resolve().relative_to(root).parts + node = tree + path_accumulator: list[str] = [] + + for part in relative[:-1]: + path_accumulator.append(part) + directories.add("/".join(path_accumulator)) + node = node["dirs"].setdefault(part, {"dirs": {}, "files": []}) + + node["files"].append(relative[-1]) + + lines = [f"{root.name or str(root)}/"] + lines.extend(_render_node(tree, prefix="")) + return "\n".join(lines), len(directories) + + +def _render_node(node: dict[str, typing.Any], prefix: str) -> list[str]: + """Render a tree node with box-drawing connectors.""" + lines: list[str] = [] + + dir_entries = sorted(node["dirs"].items(), key=lambda item: item[0]) + file_entries = sorted(node["files"]) + children: list[tuple[str, str, typing.Any]] = [ + *(("dir", name, child) for name, child in dir_entries), + *(("file", name, None) for name in file_entries), + ] + + for index, (entry_type, name, child) in enumerate(children): + is_last = index == len(children) - 1 + connector = "\u2514\u2500\u2500 " if is_last else "\u251c\u2500\u2500 " + next_prefix = f"{prefix}{' ' if is_last else '\u2502 '}" + + if entry_type == "dir": + lines.append(f"{prefix}{connector}{name}/") + lines.extend(_render_node(child, next_prefix)) + else: + lines.append(f"{prefix}{connector}{name}") + + return lines + + +@register_workspace_action +class ListAction(WorkspaceAction): + """List directory contents as a tree view.""" + + name = "list" + description = ( + "List directory contents as a tree view.\n" + "\n" + "Features:\n" + "- Tree-style output showing directory hierarchy\n" + "- Smart ignore patterns for common build artifacts\n" + "- Supports hidden files and depth limiting\n" + "\n" + "Default ignored patterns include:\n" + "- node_modules/, dist/, build/, target/\n" + "- .git/, .vscode/, .idea/\n" + "- __pycache__/, .venv/, venv/\n" + "- coverage/, .cache/, logs/\n" + "- And many more common artifacts\n" + "\n" + "Use the ignore parameter to add custom patterns.\n" + "Use max_depth to limit traversal depth (1-10)." + ) + parameters = [ + TypeSchema(type="string", description="path: Directory to list. Defaults to workspace root."), + TypeSchema(type="array", description="ignore: Additional ignore glob patterns."), + TypeSchema(type="boolean", description="show_hidden: Include hidden files/directories. Default false."), + TypeSchema(type="number", description="max_depth: Maximum directory depth to traverse (1-10)."), + ] + result = TypeSchema( + type="object", + description="Result with root, tree, file_count, dir_count, and truncated.", + ) + + def __init__(self) -> None: + pass + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + try: + root = _resolve_root(args.get("path"), context.root_path) + + if not root.is_dir(): + return { + "is_error": True, + "error": f"Path is not a directory: {root}", + "root": str(root), + "tree": "", + "file_count": 0, + "dir_count": 0, + "truncated": False, + } + + ignore_patterns = [*DEFAULT_IGNORE_PATTERNS, *(args.get("ignore") or [])] + + show_hidden = bool(args.get("show_hidden", False)) + + max_depth_raw = args.get("max_depth") + max_depth: int | None = None + if max_depth_raw is not None: + max_depth = max(1, min(10, int(max_depth_raw))) + + files, truncated = await _get_files( + root=root, + ignore_patterns=ignore_patterns, + show_hidden=show_hidden, + max_depth=max_depth, + ) + + if not files: + tree = f"{root.name or str(root)}/\n (empty or all files ignored)" + return { + "root": str(root), + "tree": tree, + "file_count": 0, + "dir_count": 0, + "truncated": False, + } + + tree, dir_count = _build_tree(files=files, root=root) + if truncated: + tree = f"{tree}\n... (truncated, showing first {MAX_FILES} files)" + + return { + "root": str(root), + "tree": tree, + "file_count": len(files), + "dir_count": dir_count, + "truncated": truncated, + } + except Exception as exc: + return { + "is_error": True, + "error": str(exc), + "root": str(context.root_path), + "tree": "", + "file_count": 0, + "dir_count": 0, + "truncated": False, + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/terminal/__init__.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/terminal/__init__.py new file mode 100644 index 0000000000..bcd923c929 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/terminal/__init__.py @@ -0,0 +1,14 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/terminal/bash_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/terminal/bash_action.py new file mode 100644 index 0000000000..9a9151bbbe --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/terminal/bash_action.py @@ -0,0 +1,243 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Bash action implementation with separate streams, truncation, and diagnostics.""" + +from __future__ import annotations + +import asyncio +import os +import signal +import time +import typing +from pathlib import Path + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction +from nat.workspace_actions.workspace.utils.bash_commands import ( + interpret_exit_code, + is_image_output, + is_long_running_command, +) + +DEFAULT_TIMEOUT_SECONDS = 120 +MAX_TIMEOUT_SECONDS = 600 +MAX_OUTPUT_BYTES = 100 * 1024 # 100 KB + + +@register_workspace_action +class BashAction(WorkspaceAction): + """Execute shell commands within the workspace session root.""" + + name = "bash" + description = ( + "Execute a shell command in the terminal.\n" + "\n" + "Commands run synchronously with a configurable timeout (default 120s, max 600s).\n" + "Output (stdout/stderr) is captured separately and returned.\n" + "\n" + "When NOT to use Bash:\n" + "- For file reading: use the read action (not cat/head/tail)\n" + "- For file editing: use the edit action (not sed/awk)\n" + "- For file writing: use the write action (not echo/cat with heredoc)\n" + "- For searching files: use the grep action (not grep/rg)\n" + "- For finding files: use the glob action (not find/ls)\n" + "\n" + "Guidelines:\n" + "- Always provide a description parameter explaining what the command does.\n" + "- For commands that may take longer than 120s, set timeout_seconds appropriately.\n" + "- Use absolute paths when possible to avoid working directory issues.\n" + "- Chain related commands with && to ensure proper sequencing.\n" + "\n" + "Exit code interpretation:\n" + "- 127: Command not found\n" + "- 126: Command not executable\n" + "- 137: Process killed (SIGKILL, possibly OOM)\n" + "- 130: Process interrupted (Ctrl+C)\n" + "- 143: Process terminated (SIGTERM)" + ) + parameters = [ + TypeSchema(type="string", description="command: Shell command to execute."), + TypeSchema(type="number", description="timeout_seconds: Optional timeout in seconds (default 120, max 600)."), + TypeSchema(type="string", description="working_directory: Optional working directory relative to workspace root."), + TypeSchema(type="object", description="env: Optional environment variable overrides."), + TypeSchema(type="string", description="description: Optional short description of what the command does."), + ] + result = TypeSchema( + type="object", + description="Result with stdout, stderr, exit_code, timed_out, duration_ms, signal, and exit_code_interpretation.", + ) + + def __init__(self) -> None: + pass + + async def __aenter__(self) -> BashAction: + return self + + async def __aexit__(self, exc_type, exc_value, traceback) -> None: + return None + + # ------------------------------------------------------------------ + # Helpers + # ------------------------------------------------------------------ + + @staticmethod + def _resolve_env(env_overrides: object | None) -> dict[str, str]: + env = os.environ.copy() + if env_overrides is None: + return env + if not isinstance(env_overrides, dict): + raise ValueError("'env' must be a dictionary of string keys to string values.") + for key, value in env_overrides.items(): + if not isinstance(key, str) or not isinstance(value, str): + raise ValueError("'env' must be a dictionary of string keys to string values.") + env[key] = value + return env + + @staticmethod + def _truncate_output(output: str) -> str: + """Keep the last *MAX_OUTPUT_BYTES* of output, prefixing with a truncation notice.""" + if is_image_output(output): + return output + encoded = output.encode("utf-8", errors="replace") + if len(encoded) <= MAX_OUTPUT_BYTES: + return output + tail = encoded[-MAX_OUTPUT_BYTES:] + tail_text = tail.decode("utf-8", errors="replace") + removed_text = output[: max(len(output) - len(tail_text), 0)] + removed_lines = max(removed_text.count("\n"), 1) + return f"[...{removed_lines} lines truncated...]\n{tail_text}" + + def _resolve_cwd(self, context: ActionContext, working_directory: str | None) -> Path: + root = context.root_path.resolve() + if working_directory is None: + return root + path = Path(working_directory) + if not path.is_absolute(): + path = root / path + resolved = path.resolve() + # Ensure the resolved path is within the workspace root. + try: + resolved.relative_to(root) + except ValueError as exc: + raise ValueError( + f"working_directory must be within the workspace root ({root})." + ) from exc + return resolved + + # ------------------------------------------------------------------ + # Execute + # ------------------------------------------------------------------ + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + command = args.get("command") + if not isinstance(command, str) or not command.strip(): + raise ValueError("Action requires a non-empty 'command' string.") + + # Timeout + timeout_seconds = args.get("timeout_seconds", DEFAULT_TIMEOUT_SECONDS) + try: + timeout_seconds = float(timeout_seconds) + except (TypeError, ValueError) as exc: + raise ValueError("'timeout_seconds' must be a number.") from exc + timeout_seconds = min(timeout_seconds, MAX_TIMEOUT_SECONDS) + + # Working directory + cwd = self._resolve_cwd(context, args.get("working_directory")) + + # Environment + env = self._resolve_env(args.get("env")) + + # Long-running warning + long_running_warning = "" + if is_long_running_command(command): + long_running_warning = ( + "Warning: command appears long-running. " + "Consider running it with a larger timeout or in the background.\n" + ) + + start = time.perf_counter() + signal_name: str | None = None + + process = await asyncio.create_subprocess_exec( + "bash", + "--noprofile", + "--norc", + "-c", + command, + cwd=str(cwd), + env=env, + stdin=asyncio.subprocess.PIPE, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + + timed_out = False + try: + stdout_bytes, stderr_bytes = await asyncio.wait_for( + process.communicate(), + timeout=timeout_seconds, + ) + except TimeoutError: + timed_out = True + # Graceful shutdown: SIGTERM → wait 2s → SIGKILL + process.terminate() + try: + stdout_bytes, stderr_bytes = await asyncio.wait_for( + process.communicate(), + timeout=2, + ) + except TimeoutError: + process.kill() + stdout_bytes, stderr_bytes = await process.communicate() + signal_name = "SIGTERM" + + stdout = stdout_bytes.decode("utf-8", errors="replace") if stdout_bytes else "" + stderr = stderr_bytes.decode("utf-8", errors="replace") if stderr_bytes else "" + + exit_code: int | None = None if timed_out else process.returncode + + # Detect signal from negative return code + if exit_code is not None and exit_code < 0 and signal_name is None: + try: + signal_name = signal.Signals(-exit_code).name + except (ValueError, KeyError): + signal_name = None + + # Truncate large outputs + stdout = self._truncate_output(stdout) + stderr = self._truncate_output(stderr) + + # Prepend long-running warning + if long_running_warning: + stderr = f"{long_running_warning}{stderr}" + + # Timeout annotation + if timed_out: + timeout_msg = f"Command timed out after {timeout_seconds}s." + stderr = f"{stderr}\n{timeout_msg}" if stderr else timeout_msg + + interpretation = interpret_exit_code(exit_code, signal_name) + duration_ms = int((time.perf_counter() - start) * 1000) + + return { + "stdout": stdout, + "stderr": stderr, + "exit_code": exit_code, + "timed_out": timed_out, + "duration_ms": duration_ms, + "signal": signal_name, + "exit_code_interpretation": interpretation, + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/todo/__init__.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/todo/__init__.py new file mode 100644 index 0000000000..bcd923c929 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/todo/__init__.py @@ -0,0 +1,14 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/todo/todo_read_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/todo/todo_read_action.py new file mode 100644 index 0000000000..1a75b80f6a --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/todo/todo_read_action.py @@ -0,0 +1,107 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""TodoRead workspace action for inspecting the session todo store.""" + +from __future__ import annotations + +import typing + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction +from nat.workspace_actions.workspace.utils.todo_store import ( + calculate_summary, + get_todo_by_id, + get_todos, + is_task_blocked, +) + + +@register_workspace_action +class TodoReadAction(WorkspaceAction): + """Read todo items from the session task store.""" + + name = "todo_read" + description = ( + "Read the current todo list from the session task store.\n" + "\n" + "Basic usage: call with no parameters to get all todos.\n" + "\n" + "Filtering:\n" + "- By ID: provide id to get a specific todo\n" + "- By status: provide status to filter (pending/in_progress/completed/cancelled/error/skipped/paused)\n" + "\n" + "Output includes: todos, count, summary, available (unblocked pending), and blocked lists." + ) + parameters = [ + TypeSchema(type="string", description="id: Optional specific task id to read."), + TypeSchema(type="string", description="status: Optional status filter (pending/in_progress/completed/cancelled/error/skipped/paused)."), + TypeSchema(type="boolean", description="include_blocked: Include blocked and available pending task views. Default true."), + ] + result = TypeSchema( + type="object", + description="Result payload with todos, count, summary, available, and blocked lists.", + ) + + def __init__(self) -> None: + pass + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + task_id = args.get("id") + status = args.get("status") + include_blocked = args.get("include_blocked", True) + + all_todos = get_todos(context.session_id) + + if task_id: + found = get_todo_by_id(context.session_id, task_id) + if found is None: + summary = calculate_summary(all_todos) + return { + "is_error": True, + "error": f"Todo with ID '{task_id}' not found", + "todos": [], + "count": 0, + "summary": summary, + "available": [], + "blocked": [], + } + todos = [found] + else: + todos = list(all_todos) + + if status is not None: + todos = [todo for todo in todos if todo.status == status] + + store = {todo.id: todo for todo in all_todos} + pending = [todo for todo in all_todos if todo.status == "pending"] + + if include_blocked: + available = [todo for todo in pending if not is_task_blocked(todo.id, store)] + blocked = [todo for todo in pending if is_task_blocked(todo.id, store)] + else: + available = [] + blocked = [] + + summary = calculate_summary(all_todos) + + return { + "todos": [item.model_dump() for item in todos], + "count": len(todos), + "summary": summary, + "available": [item.model_dump() for item in available], + "blocked": [item.model_dump() for item in blocked], + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/todo/todo_write_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/todo/todo_write_action.py new file mode 100644 index 0000000000..3971631353 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/todo/todo_write_action.py @@ -0,0 +1,192 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""TodoWrite workspace action for creating and updating session todos.""" + +from __future__ import annotations + +import typing + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction +from nat.workspace_actions.workspace.utils.todo_store import ( + TodoItem, + calculate_summary, + get_todos, + set_todos, + validate_dependencies, + validate_todo_graph, +) + + +@register_workspace_action +class TodoWriteAction(WorkspaceAction): + """Create or update todo items in the session task store.""" + + name = "todo_write" + description = ( + "Create or update todo items in the session task store.\n" + "Helps track progress, organize complex tasks, and demonstrate thoroughness.\n" + "\n" + "Use proactively for:\n" + "1. Complex multi-step tasks (3+ distinct steps)\n" + "2. Non-trivial tasks requiring careful planning\n" + "3. After receiving new instructions: capture requirements as todos (merge=false)\n" + "4. After completing tasks: mark complete with merge=true and add follow-ups\n" + "\n" + "Task states: pending, in_progress, completed, cancelled, error, skipped, paused\n" + "\n" + "Task management:\n" + "- Update status in real-time\n" + "- Mark complete IMMEDIATELY after finishing\n" + "- Only ONE task in_progress at a time\n" + "\n" + "Task dependencies:\n" + "- Use blocks/blocked_by to create task dependency chains\n" + "- Automatic circular dependency detection\n" + "- Validation ensures all referenced tasks exist" + ) + parameters = [ + TypeSchema( + type="array", + description=( + "todos: List of todo item objects. Each item requires: " + "id (string), content (string), status (string). " + "Optional fields: active_form (string), metadata (object), " + "emoji (string), blocks (array of ids), blocked_by (array of ids)." + ), + ), + TypeSchema( + type="boolean", + description="merge: If true, merge into existing todos; if false, replace entire list.", + ), + ] + result = TypeSchema( + type="object", + description="Result payload with created, updated, removed counts, todos list, and summary.", + ) + + def __init__(self) -> None: + pass + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + raw_todos = args.get("todos") + if not raw_todos or not isinstance(raw_todos, list): + return self._error(context.session_id, "Action requires a non-empty 'todos' array.") + + merge = args.get("merge", False) + + # Parse and validate each incoming todo item. + incoming: list[TodoItem] = [] + for raw in raw_todos: + if not isinstance(raw, dict): + return self._error(context.session_id, "Each todo must be a dictionary.") + for required_field in ("id", "content", "status"): + if required_field not in raw: + return self._error( + context.session_id, + f"Todo item missing required field '{required_field}'.", + ) + try: + item = TodoItem( + id=raw["id"], + content=raw["content"], + status=raw["status"], + active_form=raw.get("active_form"), + metadata=raw.get("metadata"), + emoji=raw.get("emoji"), + blocks=raw.get("blocks"), + blocked_by=raw.get("blocked_by"), + ) + except Exception as exc: + return self._error(context.session_id, f"Invalid todo item: {exc}") + incoming.append(item) + + current_store = {todo.id: todo for todo in get_todos(context.session_id)} + + # Build candidate store. + if merge: + candidate = dict(current_store) + for item in incoming: + candidate[item.id] = item + else: + candidate = {item.id: item for item in incoming} + + # Validate per-item dependencies with batch cross-reference support. + pending_ids = {item.id for item in incoming} + for item in incoming: + dependency_error = validate_dependencies( + session_id=context.session_id, + task_id=item.id, + blocked_by=item.blocked_by, + pending_task_ids=pending_ids, + store=candidate, + ) + if dependency_error: + return self._error( + context.session_id, + f"Dependency validation failed for task {item.id}: {dependency_error}", + ) + + # Validate full graph for cycles. + graph_error = validate_todo_graph(candidate) + if graph_error: + return self._error(context.session_id, f"Dependency validation failed: {graph_error}") + + # Count changes and persist. + if merge: + created = 0 + updated = 0 + removed = 0 + for item in incoming: + if item.id in current_store: + updated += 1 + else: + created += 1 + current_store[item.id] = item + set_todos(context.session_id, current_store.values()) + else: + previous_ids = set(current_store.keys()) + new_ids = {item.id for item in incoming} + created = len(new_ids - previous_ids) + updated = len(new_ids & previous_ids) + removed = len(previous_ids - new_ids) + set_todos(context.session_id, incoming) + + todos = get_todos(context.session_id) + summary = calculate_summary(todos) + + return { + "created": created, + "updated": updated, + "removed": removed, + "todos": [item.model_dump() for item in todos], + "summary": summary, + } + + @staticmethod + def _error(session_id: str, message: str) -> dict[str, typing.Any]: + current_todos = get_todos(session_id) + summary = calculate_summary(current_todos) + return { + "is_error": True, + "error": message, + "created": 0, + "updated": 0, + "removed": 0, + "todos": [item.model_dump() for item in current_todos], + "summary": summary, + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/__init__.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/__init__.py new file mode 100644 index 0000000000..b989b354c6 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/__init__.py @@ -0,0 +1,30 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# re-export utilities +from nat.workspace_actions.workspace.utils.file_state import ( + clear_file_read_state, + get_file_read_state, + register_file_read, +) +from nat.workspace_actions.workspace.utils.levenshtein import find_similar_file, levenshtein_distance +from nat.workspace_actions.workspace.utils.path_utils import resolve_workspace_path, validate_within_root +from nat.workspace_actions.workspace.utils.replacers import has_multiple_matches, perform_advanced_replacement +from nat.workspace_actions.workspace.utils.bash_commands import ( + interpret_exit_code, + is_long_running_command, + is_read_only_command, +) +from nat.workspace_actions.workspace.utils.ripgrep_utils import get_ripgrep_path diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/bash_commands.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/bash_commands.py new file mode 100644 index 0000000000..dd4052a050 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/bash_commands.py @@ -0,0 +1,239 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Bash command classification and exit-code interpretation utilities.""" + +from __future__ import annotations + +import re + + +READ_ONLY_COMMANDS: set[str] = { + # File inspection + "ls", + "cat", + "head", + "tail", + "less", + "more", + "grep", + "awk", + "sed", + "find", + "which", + "whereis", + "type", + "file", + "stat", + "wc", + "diff", + "cmp", + # System info + "pwd", + "echo", + "printf", + "date", + "cal", + "uptime", + "whoami", + "id", + "groups", + "env", + "printenv", + "set", + "export", + "hostname", + "uname", + "df", + "du", + "free", + "ps", + "top", + "htop", + "pgrep", + "lsof", + "netstat", + "ss", + "ip", + "ifconfig", + # VCS operations (read-only) + "git status", + "git log", + "git diff", + "git show", + "git branch", + "git remote", + "git tag", + "git describe", + "git rev-parse", + "git ls-files", + "git blame", + # Package managers (query only) + "npm list", + "npm ls", + "npm view", + "npm info", + "npm outdated", + "npm audit", + "yarn list", + "yarn info", + "yarn why", + "pnpm list", + "pnpm why", + "pip list", + "pip show", + "pip freeze", + "pip check", + "cargo tree", + "cargo metadata", + "cargo check", + "go list", + "go mod graph", + "go version", + # Container/orchestration + "docker ps", + "docker images", + "docker logs", + "docker inspect", + "kubectl get", + "kubectl describe", + "kubectl logs", + # Modern tools + "tree", + "exa", + "bat", + "rg", + "fd", + "ag", + "ack", + "jq", + "yq", + "curl --head", + "curl -I", + "wget --spider", + "test", + "[", + "[[", +} + + +LONG_RUNNING_COMMANDS: list[str] = [ + "npm run dev", + "npm run start", + "npm run serve", + "npm run watch", + "yarn dev", + "yarn start", + "yarn serve", + "yarn watch", + "pnpm dev", + "pnpm start", + "pnpm serve", + "pnpm watch", + "python -m http.server", + "python3 -m http.server", + "node server", + "nodemon", + "ts-node-dev", + "cargo run", + "cargo watch", + "go run", + "docker-compose up", + "docker compose up", + "kubectl port-forward", + "kubectl proxy", + "tail -f", + "watch", + "webpack --watch", + "vite", + "next dev", + "nuxt dev", +] + + +_IMAGE_DATA_URI_RE = re.compile(r"^data:image/[a-z0-9.+_-]+;base64,", re.IGNORECASE) + + +def is_read_only_command(command: str) -> bool: + """Return whether a command is considered read-only.""" + trimmed = command.strip().lower() + if not trimmed: + return False + + first_word = trimmed.split()[0] + + # Check single-word commands first. + if first_word in READ_ONLY_COMMANDS: + return True + + # Then check multi-word prefixes (e.g., "git status", "npm list"). + for read_only in READ_ONLY_COMMANDS: + if " " in read_only and trimmed.startswith(read_only): + return True + + # For piped commands, all parts must be read-only. + if "|" in command: + parts = [part.strip() for part in command.split("|")] + return all(is_read_only_command(part) for part in parts) + + return False + + +def is_long_running_command(command: str) -> bool: + """Return whether a command is likely long-running.""" + trimmed = command.strip().lower() + return any(trimmed.startswith(cmd) for cmd in LONG_RUNNING_COMMANDS) + + +def interpret_exit_code(code: int | None, sig: str | None) -> str | None: + """Map exit codes/signals to human-readable explanations.""" + if sig: + signal_map = { + "SIGTERM": "Process was terminated", + "SIGKILL": "Process was forcefully killed", + "SIGINT": "Process was interrupted (Ctrl+C)", + "SIGSEGV": "Process crashed (segmentation fault)", + "SIGPIPE": "Broken pipe (output destination closed)", + } + return signal_map.get(sig, f"Process received signal: {sig}") + + if code is None: + return None + + match code: + case 0 | 1 | 2: + return None + case 126: + return "Command found but not executable" + case 127: + return "Command not found" + case 128: + return "Invalid exit argument" + case 130: + return "Process terminated by Ctrl+C (SIGINT)" + case 137: + return "Process killed (SIGKILL, possibly OOM)" + case 139: + return "Segmentation fault (SIGSEGV)" + case 143: + return "Process terminated (SIGTERM)" + case _: + if 128 < code < 192: + return f"Process terminated by signal {code - 128}" + return None + + +def is_image_output(output: str) -> bool: + """Return whether output starts with a base64 image data URI.""" + return bool(_IMAGE_DATA_URI_RE.match(output.strip())) diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/file_state.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/file_state.py new file mode 100644 index 0000000000..f0c0541cac --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/file_state.py @@ -0,0 +1,64 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Session-scoped file read-state tracking for read-before-edit validation.""" + +from __future__ import annotations + +import time +from dataclasses import dataclass +from pathlib import Path + + +@dataclass(frozen=True) +class FileReadState: + """State recorded when a file is read.""" + + content: str + timestamp: float + + +_session_states: dict[str, dict[str, FileReadState]] = {} + + +def _to_abs_path(file_path: str) -> str: + return str(Path(file_path).resolve()) + + +def register_file_read(session_id: str, file_path: str, content: str) -> None: + """Record that a file was read, including its content and timestamp.""" + states = _session_states.setdefault(session_id, {}) + states[_to_abs_path(file_path)] = FileReadState( + content=content, + timestamp=time.time(), + ) + + +def get_file_read_state(session_id: str, file_path: str) -> FileReadState | None: + """Get previously recorded read state for a file path.""" + states = _session_states.get(session_id, {}) + return states.get(_to_abs_path(file_path)) + + +def clear_file_read_state(session_id: str, file_path: str) -> None: + """Clear any read state associated with a file path.""" + states = _session_states.get(session_id) + if states is not None: + states.pop(_to_abs_path(file_path), None) + + +def clear_session_state(session_id: str) -> None: + """Clear all file read state for a session.""" + _session_states.pop(session_id, None) diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/levenshtein.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/levenshtein.py new file mode 100644 index 0000000000..c182ff64ac --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/levenshtein.py @@ -0,0 +1,108 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Levenshtein distance utilities for fuzzy file-name matching.""" + +from __future__ import annotations + +import os +from pathlib import Path + + +def levenshtein_distance(a: str, b: str) -> int: + """Return the Levenshtein edit distance between two strings.""" + if a == b: + return 0 + if not a: + return len(b) + if not b: + return len(a) + + matrix = [[0] * (len(a) + 1) for _ in range(len(b) + 1)] + + for i in range(len(b) + 1): + matrix[i][0] = i + for j in range(len(a) + 1): + matrix[0][j] = j + + for i in range(1, len(b) + 1): + for j in range(1, len(a) + 1): + if b[i - 1] == a[j - 1]: + matrix[i][j] = matrix[i - 1][j - 1] + else: + matrix[i][j] = min( + matrix[i - 1][j - 1] + 1, # substitution + matrix[i][j - 1] + 1, # insertion + matrix[i - 1][j] + 1, # deletion + ) + + return matrix[len(b)][len(a)] + + +def find_similar_file(file_path: str) -> str | None: + """Find the best similar file in the same directory. + + Strategy: + 1) Case-insensitive exact basename match. + 2) Fuzzy stem match with Levenshtein distance < 3. + """ + path = Path(file_path) + directory = path.parent + basename = path.name.lower() + + try: + files = os.listdir(directory) + except OSError: + return None + + for file_name in files: + if file_name.lower() == basename and file_name != path.name: + return str(directory / file_name) + + target_stem = path.stem.lower() + best_match: str | None = None + best_distance = float("inf") + + for file_name in files: + distance = levenshtein_distance(target_stem, Path(file_name).stem.lower()) + if distance < 3 and distance < best_distance: + best_distance = distance + best_match = str(directory / file_name) + + return best_match + + +def find_similar_files(file_path: str, max_suggestions: int = 3) -> list[str]: + """Find multiple similar file candidates sorted by distance.""" + if max_suggestions <= 0: + return [] + + path = Path(file_path) + directory = path.parent + target_stem = path.stem.lower() + + try: + files = os.listdir(directory) + except OSError: + return [] + + distances: list[tuple[int, str]] = [] + for file_name in files: + distance = levenshtein_distance(target_stem, Path(file_name).stem.lower()) + if distance < 3: + distances.append((distance, str(directory / file_name))) + + distances.sort(key=lambda item: item[0]) + return [path for _, path in distances[:max_suggestions]] diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/path_utils.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/path_utils.py new file mode 100644 index 0000000000..db4355355d --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/path_utils.py @@ -0,0 +1,35 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Shared path resolution for workspace actions.""" + +from __future__ import annotations + +from pathlib import Path + + +def resolve_workspace_path(file_path: str, root_path: Path) -> Path: + """Resolve a file path relative to the workspace root.""" + path = Path(file_path) + if not path.is_absolute(): + path = root_path / path + return path.resolve() + + +def validate_within_root(resolved: Path, root_path: Path) -> None: + """Raise ValueError if resolved path escapes the workspace root.""" + resolved_root = root_path.resolve() + if resolved_root != resolved and resolved_root not in resolved.parents: + raise ValueError(f"Path escapes workspace root: {resolved}") diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/replacers.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/replacers.py new file mode 100644 index 0000000000..6e909870b6 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/replacers.py @@ -0,0 +1,455 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Advanced replacement strategies used by file-edit tooling.""" + +from __future__ import annotations + +import re +from collections.abc import Callable, Generator +from dataclasses import dataclass + +from nat.workspace_actions.workspace.utils.levenshtein import levenshtein_distance + + +Replacer = Callable[[str, str], Generator[str, None, None]] + + +SINGLE_CANDIDATE_SIMILARITY_THRESHOLD = 0.0 +MULTIPLE_CANDIDATES_SIMILARITY_THRESHOLD = 0.3 + + +def _substring_from_line_range( + content: str, + lines: list[str], + start_line: int, + end_line: int, +) -> str: + start_index = 0 + for idx in range(start_line): + start_index += len(lines[idx]) + 1 + + end_index = start_index + for idx in range(start_line, end_line + 1): + end_index += len(lines[idx]) + if idx < end_line: + end_index += 1 + + return content[start_index:end_index] + + +def simple_replacer(_content: str, find: str) -> Generator[str, None, None]: + """Yield the search string as-is.""" + yield find + + +def line_trimmed_replacer(content: str, find: str) -> Generator[str, None, None]: + """Match a block by comparing line content after trimming whitespace.""" + original_lines = content.split("\n") + search_lines = find.split("\n") + + if search_lines and search_lines[-1] == "": + search_lines.pop() + + if not search_lines: + return + + for i in range(0, len(original_lines) - len(search_lines) + 1): + matches = True + for j in range(len(search_lines)): + if original_lines[i + j].strip() != search_lines[j].strip(): + matches = False + break + + if matches: + end_line = i + len(search_lines) - 1 + yield _substring_from_line_range(content, original_lines, i, end_line) + + +def block_anchor_replacer(content: str, find: str) -> Generator[str, None, None]: + """Use first/last lines as anchors, fuzzy-matching middle lines.""" + original_lines = content.split("\n") + search_lines = find.split("\n") + + if len(search_lines) < 3: + return + + if search_lines and search_lines[-1] == "": + search_lines.pop() + + if len(search_lines) < 3: + return + + first_line_search = search_lines[0].strip() + last_line_search = search_lines[-1].strip() + search_block_size = len(search_lines) + + candidates: list[tuple[int, int]] = [] + for i, line in enumerate(original_lines): + if line.strip() != first_line_search: + continue + for j in range(i + 2, len(original_lines)): + if original_lines[j].strip() == last_line_search: + candidates.append((i, j)) + break + + if not candidates: + return + + if len(candidates) == 1: + start_line, end_line = candidates[0] + actual_block_size = end_line - start_line + 1 + + similarity = 0.0 + lines_to_check = min(search_block_size - 2, actual_block_size - 2) + + if lines_to_check > 0: + upper = min(search_block_size - 1, actual_block_size - 1) + for j in range(1, upper): + original_line = original_lines[start_line + j].strip() + search_line = search_lines[j].strip() + max_len = max(len(original_line), len(search_line)) + if max_len == 0: + continue + distance = levenshtein_distance(original_line, search_line) + similarity += (1 - distance / max_len) / lines_to_check + if similarity >= SINGLE_CANDIDATE_SIMILARITY_THRESHOLD: + break + else: + similarity = 1.0 + + if similarity >= SINGLE_CANDIDATE_SIMILARITY_THRESHOLD: + yield _substring_from_line_range( + content, + original_lines, + start_line, + end_line, + ) + return + + best_match: tuple[int, int] | None = None + max_similarity = -1.0 + + for start_line, end_line in candidates: + actual_block_size = end_line - start_line + 1 + similarity = 0.0 + lines_to_check = min(search_block_size - 2, actual_block_size - 2) + + if lines_to_check > 0: + upper = min(search_block_size - 1, actual_block_size - 1) + for j in range(1, upper): + original_line = original_lines[start_line + j].strip() + search_line = search_lines[j].strip() + max_len = max(len(original_line), len(search_line)) + if max_len == 0: + continue + distance = levenshtein_distance(original_line, search_line) + similarity += 1 - distance / max_len + similarity /= lines_to_check + else: + similarity = 1.0 + + if similarity > max_similarity: + max_similarity = similarity + best_match = (start_line, end_line) + + if max_similarity >= MULTIPLE_CANDIDATES_SIMILARITY_THRESHOLD and best_match: + start_line, end_line = best_match + yield _substring_from_line_range(content, original_lines, start_line, end_line) + + +def whitespace_normalized_replacer( + content: str, + find: str, +) -> Generator[str, None, None]: + """Match with normalized whitespace.""" + + def normalize_whitespace(text: str) -> str: + return re.sub(r"\s+", " ", text).strip() + + normalized_find = normalize_whitespace(find) + lines = content.split("\n") + + for line in lines: + if normalize_whitespace(line) == normalized_find: + yield line + else: + normalized_line = normalize_whitespace(line) + if normalized_find in normalized_line: + words = re.split(r"\s+", find.strip()) + if words and words[0]: + pattern = r"\s+".join(re.escape(word) for word in words) + try: + regex = re.compile(pattern) + except re.error: + regex = None + if regex: + match = regex.search(line) + if match: + yield match.group(0) + + find_lines = find.split("\n") + if len(find_lines) > 1: + for i in range(0, len(lines) - len(find_lines) + 1): + block = "\n".join(lines[i : i + len(find_lines)]) + if normalize_whitespace(block) == normalized_find: + yield block + + +def indentation_flexible_replacer( + content: str, + find: str, +) -> Generator[str, None, None]: + """Match a block by removing shared indentation.""" + + def remove_indentation(text: str) -> str: + lines = text.split("\n") + non_empty_lines = [line for line in lines if line.strip()] + if not non_empty_lines: + return text + + min_indent = min( + len(re.match(r"^(\s*)", line).group(1)) for line in non_empty_lines + ) + return "\n".join( + line if not line.strip() else line[min_indent:] for line in lines + ) + + normalized_find = remove_indentation(find) + content_lines = content.split("\n") + find_lines = find.split("\n") + + if not find_lines: + return + + for i in range(0, len(content_lines) - len(find_lines) + 1): + block = "\n".join(content_lines[i : i + len(find_lines)]) + if remove_indentation(block) == normalized_find: + yield block + + +def escape_normalized_replacer(content: str, find: str) -> Generator[str, None, None]: + """Unescape common escape sequences in search text, then match.""" + + def unescape_string(value: str) -> str: + def replace_match(match: re.Match[str]) -> str: + captured = match.group(1) + mapping = { + "n": "\n", + "t": "\t", + "r": "\r", + "'": "'", + '"': '"', + "`": "`", + "\\": "\\", + "\n": "\n", + "$": "$", + } + return mapping.get(captured, match.group(0)) + + return re.sub(r"\\(n|t|r|'|\"|`|\\|\n|\$)", replace_match, value) + + unescaped_find = unescape_string(find) + + if unescaped_find in content: + yield unescaped_find + + lines = content.split("\n") + find_lines = unescaped_find.split("\n") + if not find_lines: + return + + for i in range(0, len(lines) - len(find_lines) + 1): + block = "\n".join(lines[i : i + len(find_lines)]) + unescaped_block = unescape_string(block) + if unescaped_block == unescaped_find: + yield block + + +def trimmed_boundary_replacer(content: str, find: str) -> Generator[str, None, None]: + """Trim search boundaries and try matching.""" + trimmed_find = find.strip() + if trimmed_find == find: + return + + if trimmed_find in content: + yield trimmed_find + + lines = content.split("\n") + find_lines = find.split("\n") + if not find_lines: + return + + for i in range(0, len(lines) - len(find_lines) + 1): + block = "\n".join(lines[i : i + len(find_lines)]) + if block.strip() == trimmed_find: + yield block + + +def context_aware_replacer(content: str, find: str) -> Generator[str, None, None]: + """Context-line matching heuristic using first/last lines as anchors.""" + find_lines = find.split("\n") + if len(find_lines) < 3: + return + + if find_lines and find_lines[-1] == "": + find_lines.pop() + + if len(find_lines) < 3: + return + + content_lines = content.split("\n") + first_line = find_lines[0].strip() + last_line = find_lines[-1].strip() + + for i, line in enumerate(content_lines): + if line.strip() != first_line: + continue + + for j in range(i + 2, len(content_lines)): + if content_lines[j].strip() == last_line: + block_lines = content_lines[i : j + 1] + block = "\n".join(block_lines) + + if len(block_lines) == len(find_lines): + matching_lines = 0 + total_non_empty_lines = 0 + + for k in range(1, len(block_lines) - 1): + block_line = block_lines[k].strip() + find_line = find_lines[k].strip() + if block_line or find_line: + total_non_empty_lines += 1 + if block_line == find_line: + matching_lines += 1 + + if ( + total_non_empty_lines == 0 + or matching_lines / total_non_empty_lines >= 0.5 + ): + yield block + break + break + + +def multi_occurrence_replacer(content: str, find: str) -> Generator[str, None, None]: + """Yield a candidate for each non-overlapping exact occurrence.""" + if not find: + return + + start_index = 0 + while True: + index = content.find(find, start_index) + if index == -1: + break + yield find + start_index = index + len(find) + + +ALL_REPLACERS: list[Replacer] = [ + simple_replacer, + line_trimmed_replacer, + block_anchor_replacer, + whitespace_normalized_replacer, + indentation_flexible_replacer, + escape_normalized_replacer, + trimmed_boundary_replacer, + context_aware_replacer, + multi_occurrence_replacer, +] + + +@dataclass(frozen=True) +class ReplacementResult: + """Result payload for an advanced replacement attempt.""" + + new_content: str + replaced_count: int + replacer_used: str + matched_string: str + + +def perform_advanced_replacement( + content: str, + old_string: str, + new_string: str, + replace_all: bool, +) -> ReplacementResult | None: + """Try replacement with cascading fallback strategies.""" + if old_string == new_string: + return None + + replacer_names = [ + "SimpleReplacer", + "LineTrimmedReplacer", + "BlockAnchorReplacer", + "WhitespaceNormalizedReplacer", + "IndentationFlexibleReplacer", + "EscapeNormalizedReplacer", + "TrimmedBoundaryReplacer", + "ContextAwareReplacer", + "MultiOccurrenceReplacer", + ] + + for replacer, replacer_name in zip(ALL_REPLACERS, replacer_names, strict=True): + for search in replacer(content, old_string): + index = content.find(search) + if index == -1: + continue + + if replace_all: + if not search: + continue + return ReplacementResult( + new_content=content.replace(search, new_string), + replaced_count=content.count(search), + replacer_used=replacer_name, + matched_string=search, + ) + + last_index = content.rfind(search) + if index != last_index: + continue + + return ReplacementResult( + new_content=( + content[:index] + new_string + content[index + len(search) :] + ), + replaced_count=1, + replacer_used=replacer_name, + matched_string=search, + ) + + return None + + +def has_multiple_matches(content: str, old_string: str) -> bool: + """Return whether search appears multiple times via any replacer.""" + for replacer in ALL_REPLACERS: + match_count = 0 + for search in replacer(content, old_string): + first_index = content.find(search) + if first_index == -1: + continue + + last_index = content.rfind(search) + if first_index != last_index: + return True + + match_count += 1 + if match_count > 1: + return True + + return False diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/ripgrep_utils.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/ripgrep_utils.py new file mode 100644 index 0000000000..853308da0d --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/ripgrep_utils.py @@ -0,0 +1,27 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Ripgrep binary detection utility.""" + +from __future__ import annotations + +import functools +import shutil + + +@functools.lru_cache(maxsize=1) +def get_ripgrep_path() -> str | None: + """Return the path to the ripgrep binary, or None if unavailable.""" + return shutil.which("rg") diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/todo_store.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/todo_store.py new file mode 100644 index 0000000000..5e4af3c963 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/utils/todo_store.py @@ -0,0 +1,204 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Session-scoped in-memory todo store for TodoWrite and TodoRead tools.""" + +from __future__ import annotations + +from collections.abc import Iterable +from typing import Any, Literal + +from pydantic import BaseModel, ConfigDict, Field + + +TodoStatus = Literal[ + "pending", + "in_progress", + "completed", + "cancelled", + "error", + "skipped", + "paused", +] + + +class TodoItem(BaseModel): + """Canonical todo item representation in store.""" + + model_config = ConfigDict(extra="forbid") + + id: str + content: str + status: TodoStatus + active_form: str | None = None + metadata: dict[str, Any] | None = None + emoji: str | None = None + blocks: list[str] | None = None + blocked_by: list[str] | None = None + + +_session_stores: dict[str, dict[str, TodoItem]] = {} + + +def clear_todos(session_id: str) -> None: + """Clear all todos from the session's in-memory store.""" + store = _session_stores.get(session_id) + if store is not None: + store.clear() + + +def set_todos(session_id: str, todos: Iterable[TodoItem]) -> None: + """Replace session's todo store with provided items.""" + store = _session_stores.setdefault(session_id, {}) + store.clear() + for todo in todos: + store[todo.id] = todo + + +def get_todos(session_id: str) -> list[TodoItem]: + """Return all todos in insertion order.""" + store = _session_stores.get(session_id, {}) + return list(store.values()) + + +def get_todo_by_id(session_id: str, task_id: str) -> TodoItem | None: + """Return one todo by id.""" + store = _session_stores.get(session_id, {}) + return store.get(task_id) + + +def is_task_blocked(task_id: str, store: dict[str, TodoItem] | None = None) -> bool: + """Return whether a task is blocked by unfinished dependencies.""" + active_store = store or {} + task = active_store.get(task_id) + if task is None or not task.blocked_by: + return False + for blocker_id in task.blocked_by: + blocker = active_store.get(blocker_id) + if blocker is not None and blocker.status != "completed": + return True + return False + + +def get_blocked_tasks(task_id: str, store: dict[str, TodoItem] | None = None) -> list[TodoItem]: + """Return tasks that are blocked by the provided task.""" + active_store = store or {} + task = active_store.get(task_id) + if task is None or not task.blocks: + return [] + return [active_store[item_id] for item_id in task.blocks if item_id in active_store] + + +def get_blocking_tasks(task_id: str, store: dict[str, TodoItem] | None = None) -> list[TodoItem]: + """Return tasks currently blocking the provided task.""" + active_store = store or {} + task = active_store.get(task_id) + if task is None or not task.blocked_by: + return [] + return [active_store[item_id] for item_id in task.blocked_by if item_id in active_store] + + +def get_available_tasks(store: dict[str, TodoItem] | None = None) -> list[TodoItem]: + """Return pending tasks that are not blocked.""" + active_store = store or {} + return [ + task + for task in active_store.values() + if task.status == "pending" and not is_task_blocked(task.id, active_store) + ] + + +def calculate_summary(todos: list[TodoItem]) -> dict[str, int]: + """Build per-status counts and total.""" + summary = { + "pending": 0, + "in_progress": 0, + "completed": 0, + "cancelled": 0, + "error": 0, + "skipped": 0, + "paused": 0, + "total": len(todos), + } + for todo in todos: + summary[todo.status] += 1 + return summary + + +def validate_dependencies( + session_id: str, + task_id: str, + blocked_by: list[str] | None, + pending_task_ids: set[str] | None = None, + store: dict[str, TodoItem] | None = None, +) -> str | None: + """Validate one task dependency list against an existing todo store.""" + active_store = dict(store or _session_stores.get(session_id, {})) + dependencies = blocked_by or [] + if not dependencies: + return None + + for dependency_id in dependencies: + exists_in_store = dependency_id in active_store + exists_in_batch = dependency_id in (pending_task_ids or set()) + if not exists_in_store and not exists_in_batch: + return f"Task {dependency_id} does not exist" + if dependency_id == task_id: + return "Task cannot be blocked by itself" + + original = active_store.get(task_id) + if original is not None: + active_store[task_id] = original.model_copy(update={"blocked_by": dependencies}) + + if _has_cycle(active_store): + return "Circular dependency detected" + return None + + +def validate_todo_graph(store: dict[str, TodoItem]) -> str | None: + """Validate all dependency links and detect cycles for a todo graph.""" + for task in store.values(): + dependencies = task.blocked_by or [] + for dependency_id in dependencies: + if dependency_id == task.id: + return "Task cannot be blocked by itself" + if dependency_id not in store: + return f"Task {dependency_id} does not exist" + if _has_cycle(store): + return "Circular dependency detected" + return None + + +def _has_cycle(store: dict[str, TodoItem]) -> bool: + visited: dict[str, int] = {} + + def dfs(task_id: str) -> bool: + state = visited.get(task_id, 0) + if state == 1: + return True + if state == 2: + return False + visited[task_id] = 1 + task = store.get(task_id) + for dependency_id in (task.blocked_by or []) if task else []: + if dependency_id in store and dfs(dependency_id): + return True + visited[task_id] = 2 + return False + + for task_id in store: + if visited.get(task_id, 0) == 0 and dfs(task_id): + return True + return False diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/web/__init__.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/web/__init__.py new file mode 100644 index 0000000000..bcd923c929 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/web/__init__.py @@ -0,0 +1,14 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/web/web_fetch_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/web/web_fetch_action.py new file mode 100644 index 0000000000..a4bc86ced5 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/web/web_fetch_action.py @@ -0,0 +1,292 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Web fetch action implementation for retrieving and converting web content.""" + +from __future__ import annotations + +import logging +import re +import typing +from urllib.parse import urlparse + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction + +logger = logging.getLogger(__name__) + +DEFAULT_TIMEOUT_MS = 30_000 +MAX_TIMEOUT_MS = 120_000 +DEFAULT_MAX_LENGTH = 100_000 +MAX_MAX_LENGTH = 500_000 + +_BLOCKED_HOSTNAMES = frozenset({"localhost", "127.0.0.1"}) +_BLOCKED_PREFIXES = ("192.168.", "10.", "172.16.", "172.17.", "172.18.", "172.19.", + "172.20.", "172.21.", "172.22.", "172.23.", "172.24.", + "172.25.", "172.26.", "172.27.", "172.28.", "172.29.", + "172.30.", "172.31.") + + +def _is_private_host(hostname: str) -> bool: + """Return True if the hostname resolves to a private/local address.""" + lowered = hostname.lower() + if lowered in _BLOCKED_HOSTNAMES: + return True + return any(lowered.startswith(prefix) for prefix in _BLOCKED_PREFIXES) + + +def _extract_title(html_content: str) -> str | None: + """Extract the tag content from HTML.""" + match = re.search(r"<title[^>]*>([\s\S]*?)", html_content, re.IGNORECASE) + if match: + import html + + return html.unescape(match.group(1)).strip() or None + return None + + +def _extract_description(html_content: str) -> str | None: + """Extract the meta description from HTML.""" + match = re.search( + r']*name=["\']description["\'][^>]*content=["\']([^"\']*)["\']', + html_content, + re.IGNORECASE, + ) + if not match: + match = re.search( + r']*content=["\']([^"\']*)["\'][^>]*name=["\']description["\']', + html_content, + re.IGNORECASE, + ) + if match: + import html + + return html.unescape(match.group(1)).strip() or None + return None + + +def _html_to_markdown(html_content: str, *, max_length: int) -> str: + """Convert HTML to readable markdown-like text. + + This is a lightweight conversion that strips tags and preserves structure. + For full-fidelity conversion, consider using a library like markdownify. + """ + text = html_content + + # Remove script and style blocks + text = re.sub(r"", "", text, flags=re.IGNORECASE) + text = re.sub(r"", "", text, flags=re.IGNORECASE) + text = re.sub(r"", "", text, flags=re.IGNORECASE) + text = re.sub(r"", "", text) + + # Convert headings + for level in range(1, 7): + prefix = "#" * level + text = re.sub( + rf"]*>([\s\S]*?)", + rf"\n\n{prefix} \1\n\n", + text, + flags=re.IGNORECASE, + ) + + # Convert links + text = re.sub( + r']*href=["\']([^"\']*)["\'][^>]*>([\s\S]*?)', + r"[\2](\1)", + text, + flags=re.IGNORECASE, + ) + + # Convert paragraphs and line breaks + text = re.sub(r"]*>", "\n\n", text, flags=re.IGNORECASE) + text = re.sub(r"

", "", text, flags=re.IGNORECASE) + text = re.sub(r"", "\n", text, flags=re.IGNORECASE) + text = re.sub(r"", "\n---\n", text, flags=re.IGNORECASE) + + # Convert lists + text = re.sub(r"]*>", "\n- ", text, flags=re.IGNORECASE) + text = re.sub(r"", "", text, flags=re.IGNORECASE) + + # Convert code blocks + text = re.sub(r"]*>([\s\S]*?)", r"\n```\n\1\n```\n", text, flags=re.IGNORECASE) + text = re.sub(r"]*>([\s\S]*?)", r"`\1`", text, flags=re.IGNORECASE) + + # Convert bold and italic + text = re.sub(r"<(?:b|strong)[^>]*>([\s\S]*?)", r"**\1**", text, flags=re.IGNORECASE) + text = re.sub(r"<(?:i|em)[^>]*>([\s\S]*?)", r"*\1*", text, flags=re.IGNORECASE) + + # Strip remaining HTML tags + text = re.sub(r"<[^>]*>", "", text) + + # Decode entities + import html + + text = html.unescape(text) + + # Collapse excessive whitespace + text = re.sub(r"\n{3,}", "\n\n", text) + text = re.sub(r"[ \t]+", " ", text) + text = "\n".join(line.strip() for line in text.splitlines()) + text = text.strip() + + if len(text) > max_length: + text = text[:max_length] + "\n\n[Content truncated]" + + return text + + +@register_workspace_action +class WebFetchAction(WorkspaceAction): + """Fetch content from a URL and return it as readable text.""" + + name = "web_fetch" + description = ( + "Fetch content from a URL and return it as readable markdown (text only).\n" + "\n" + "Use this tool to:\n" + "- Read documentation pages (e.g., API docs, library guides)\n" + "- Get content from articles or blog posts\n" + "- Fetch static web page content\n" + "\n" + "Features:\n" + "- Converts HTML to readable markdown automatically\n" + "- Extracts page title and meta description (include_metadata: true)\n" + "- Supports custom timeout (default: 30s, max: 120s)\n" + "- Truncates long content (max_length, default: 100k chars)\n" + "\n" + "Limitations:\n" + "- Cannot render JavaScript or interact with dynamic content\n" + "- Cannot fetch from localhost or private IP addresses (security)\n" + "- Only http/https protocols supported\n" + "\n" + "For searching the web, use web_search first." + ) + parameters = [ + TypeSchema(type="string", description="url: URL to fetch (required). Must be http or https."), + TypeSchema(type="boolean", description="raw: Return raw HTML instead of markdown. Default false."), + TypeSchema(type="number", description="max_length: Maximum content length in characters (100-500000, default 100000)."), + TypeSchema(type="number", description="timeout_ms: Request timeout in milliseconds (1000-120000, default 30000)."), + TypeSchema(type="boolean", description="include_metadata: Extract page title and description. Default true."), + ] + result = TypeSchema( + type="object", + description="Result with content, title, description, url, content_type, and length.", + ) + + def __init__(self) -> None: + pass + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + url_str = args.get("url") + if not isinstance(url_str, str) or not url_str.strip(): + return {"is_error": True, "error": "A non-empty 'url' string is required."} + + # Validate URL + try: + parsed = urlparse(url_str) + except Exception: + return {"is_error": True, "error": f"Invalid URL: {url_str}"} + + if parsed.scheme not in ("http", "https"): + return { + "is_error": True, + "error": f"Unsupported protocol: {parsed.scheme}. Only http and https are supported.", + } + + hostname = (parsed.hostname or "").lower() + if _is_private_host(hostname): + return { + "is_error": True, + "error": "Cannot fetch from localhost or private IP addresses.", + } + + raw = bool(args.get("raw", False)) + max_length = int(args.get("max_length", DEFAULT_MAX_LENGTH)) + max_length = max(100, min(max_length, MAX_MAX_LENGTH)) + timeout_ms = int(args.get("timeout_ms", DEFAULT_TIMEOUT_MS)) + timeout_ms = max(1000, min(timeout_ms, MAX_TIMEOUT_MS)) + include_metadata = bool(args.get("include_metadata", True)) + + try: + import httpx + except ImportError: + return { + "is_error": True, + "error": "httpx is required for web_fetch. Install with: pip install httpx", + } + + try: + async with httpx.AsyncClient( + timeout=timeout_ms / 1000.0, + follow_redirects=True, + headers={"User-Agent": "Mozilla/5.0 (compatible; NATBot/1.0)"}, + ) as client: + response = await client.get(url_str) + response.raise_for_status() + + content_type = response.headers.get("content-type", "") + final_url = str(response.url) + raw_content = response.text + + # Extract metadata + title: str | None = None + description: str | None = None + if include_metadata and "text/html" in content_type: + title = _extract_title(raw_content) + description = _extract_description(raw_content) + + # Convert HTML to markdown or keep raw + if raw or "text/html" not in content_type: + content = raw_content + else: + content = _html_to_markdown(raw_content, max_length=max_length) + + # Truncate if needed + if len(content) > max_length: + content = content[:max_length] + "\n\n[Content truncated]" + + return { + "content": content, + "title": title, + "description": description, + "url": final_url, + "content_type": content_type, + "length": len(content), + } + + except Exception as exc: + error_message = str(exc) + + # Provide helpful error messages + if "ENOTFOUND" in error_message or "getaddrinfo" in error_message or "Name or service not known" in error_message: + return { + "is_error": True, + "error": f"DNS lookup failed for {hostname}. The domain may not exist.", + } + if "ECONNREFUSED" in error_message or "Connection refused" in error_message: + return { + "is_error": True, + "error": f"Connection refused by {hostname}. The server may be down.", + } + if "timeout" in error_message.lower() or "timed out" in error_message.lower(): + return { + "is_error": True, + "error": f"Request timed out after {timeout_ms}ms.", + } + + return { + "is_error": True, + "error": f"Failed to fetch URL: {error_message}", + } diff --git a/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/web/web_search_action.py b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/web/web_search_action.py new file mode 100644 index 0000000000..ab1951ba88 --- /dev/null +++ b/packages/nvidia_nat_workspace/src/nat/workspace_actions/workspace/web/web_search_action.py @@ -0,0 +1,298 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Web search action implementation using SearXNG with DuckDuckGo fallback.""" + +from __future__ import annotations + +import html +import json +import logging +import os +import re +import typing +from urllib.parse import urlencode + +from nat.cli.register_workflow import register_workspace_action +from nat.data_models.workspace import ActionContext +from nat.workspace.types import TypeSchema, WorkspaceAction + +logger = logging.getLogger(__name__) + +DEFAULT_MAX_RESULTS = 10 +MAX_RESULTS = 20 +DEFAULT_SEARXNG_URL = "https://searx.be" +SEARCH_TIMEOUT_SECONDS = 15 + +_VALID_TIME_RANGES = {"day", "week", "month", "year", "all"} +_VALID_ENGINES = {"searxng", "duckduckgo", "auto"} + + +def _get_http_client() -> typing.Any: + """Lazily import and return an httpx.AsyncClient.""" + import httpx # noqa: F811 + + return httpx.AsyncClient( + timeout=SEARCH_TIMEOUT_SECONDS, + follow_redirects=True, + headers={"User-Agent": "Mozilla/5.0 (compatible; NATBot/1.0)"}, + ) + + +def _strip_html_tags(text: str) -> str: + """Remove HTML tags and decode entities.""" + stripped = re.sub(r"<[^>]*>", "", text) + return html.unescape(stripped).strip() + + +async def _search_searxng( + query: str, + *, + max_results: int, + searxng_url: str, + time_range: str, + safe_search: bool, +) -> list[dict[str, str]]: + """Search via a SearXNG instance (JSON API).""" + params: dict[str, str] = { + "q": query, + "format": "json", + "pageno": "1", + } + if time_range != "all": + params["time_range"] = time_range + if safe_search: + params["safesearch"] = "1" + + search_url = f"{searxng_url}/search?{urlencode(params)}" + client = _get_http_client() + try: + async with client: + response = await client.get(search_url) + response.raise_for_status() + if "application/json" not in response.headers.get("content-type", ""): + logger.warning("SearXNG returned non-JSON response for %s", search_url) + return [] + data = response.json() + except Exception as exc: + logger.warning("SearXNG search failed: %s", exc) + return [] + + raw_results = data.get("results", []) + if not isinstance(raw_results, list): + return [] + + results: list[dict[str, str]] = [] + for item in raw_results[:max_results]: + url = item.get("url", "") + if not url: + continue + results.append({ + "title": item.get("title", "Untitled"), + "url": url, + "snippet": item.get("content", ""), + "source": "searxng", + }) + return results + + +async def _search_duckduckgo( + query: str, + *, + max_results: int, + safe_search: bool, +) -> list[dict[str, str]]: + """Search via DuckDuckGo Lite (HTML scraping fallback).""" + params: dict[str, str] = {"q": query, "kl": "us-en"} + if safe_search: + params["kp"] = "1" + + client = _get_http_client() + try: + async with client: + response = await client.get( + f"https://lite.duckduckgo.com/lite/?{urlencode(params)}" + ) + response.raise_for_status() + page_html = response.text + except Exception as exc: + logger.warning("DuckDuckGo search failed: %s", exc) + return [] + + # Extract result links with rel="nofollow" + link_pattern = re.compile( + r']*rel=["\']?nofollow["\']?[^>]*href=["\']([^"\']+)["\'][^>]*>' + r"([\s\S]*?)", + re.IGNORECASE, + ) + snippet_pattern = re.compile( + r']*class=["\'][^"\']*result-snippet[^"\']*["\'][^>]*>' + r"([\s\S]*?)", + re.IGNORECASE, + ) + + urls: list[str] = [] + titles: list[str] = [] + for match in link_pattern.finditer(page_html): + raw_url = match.group(1) + title_html = match.group(2) + if not raw_url or "duckduckgo.com" in raw_url or raw_url.startswith(("/", "#")): + continue + # Decode DDG redirect URLs + uddg_match = re.search(r"uddg=([^&]+)", raw_url) + if uddg_match: + from urllib.parse import unquote + + raw_url = unquote(uddg_match.group(1)) + urls.append(raw_url) + titles.append(_strip_html_tags(title_html) or "Untitled") + + snippets: list[str] = [] + for match in snippet_pattern.finditer(page_html): + snippets.append(_strip_html_tags(match.group(1))) + + results: list[dict[str, str]] = [] + for i in range(min(len(urls), max_results)): + results.append({ + "title": titles[i] if i < len(titles) else "Untitled", + "url": urls[i], + "snippet": snippets[i] if i < len(snippets) else "", + "source": "duckduckgo", + }) + return results + + +@register_workspace_action +class WebSearchAction(WorkspaceAction): + """Search the web and return results with titles, URLs, and snippets.""" + + name = "web_search" + description = ( + "Search the web and return a list of results with titles, URLs, and snippets.\n" + "\n" + "Use this tool to:\n" + "- Find current information not in your training data\n" + "- Research documentation, tutorials, or guides\n" + "- Look up error messages or technical problems\n" + "- Find recent news or updates about topics\n" + "\n" + "Options:\n" + "- max_results: Number of results (1-20, default: 10)\n" + "- time_range: Filter by recency - 'day', 'week', 'month', 'year', or 'all' (default)\n" + "- safe_search: Enable safe search (default: true)\n" + "- engine: 'searxng', 'duckduckgo', or 'auto' (default, tries SearXNG first)\n" + "\n" + "Tips for effective searches:\n" + "- Be specific: 'TypeScript generics tutorial' vs just 'TypeScript'\n" + "- Include version/year for tech topics: 'Node.js 20 features'\n" + "- Use quotes for exact phrases: '\"cannot read property\" undefined'\n" + "\n" + "After searching, use web_fetch to read the full content of promising results." + ) + parameters = [ + TypeSchema(type="string", description="query: Search query string (required)."), + TypeSchema(type="number", description="max_results: Number of results to return (1-20, default 10)."), + TypeSchema(type="string", description="engine: Search engine - 'searxng', 'duckduckgo', or 'auto' (default)."), + TypeSchema(type="string", description="searxng_url: Custom SearXNG instance URL."), + TypeSchema(type="string", description="time_range: Filter results by recency - 'day', 'week', 'month', 'year', or 'all' (default)."), + TypeSchema(type="boolean", description="safe_search: Enable safe search filtering. Default true."), + ] + result = TypeSchema( + type="object", + description="Result with results (list), total_results, query, engine, and summary.", + ) + + def __init__(self) -> None: + pass + + async def execute(self, context: ActionContext, args: dict[str, typing.Any]) -> dict[str, typing.Any]: + query = args.get("query") + if not isinstance(query, str) or not query.strip(): + return { + "is_error": True, + "error": "A non-empty 'query' string is required.", + "results": [], + "total_results": 0, + "query": str(query) if query else "", + "engine": "none", + "summary": "", + } + + max_results = min(int(args.get("max_results", DEFAULT_MAX_RESULTS)), MAX_RESULTS) + engine = str(args.get("engine", "auto")).lower() + if engine not in _VALID_ENGINES: + engine = "auto" + + time_range = str(args.get("time_range", "all")).lower() + if time_range not in _VALID_TIME_RANGES: + time_range = "all" + + safe_search = bool(args.get("safe_search", True)) + searxng_url = str(args.get("searxng_url", "")).strip() or os.environ.get( + "SEARXNG_URL", DEFAULT_SEARXNG_URL + ) + + results: list[dict[str, str]] = [] + used_engine = "none" + + try: + # Try SearXNG first + if engine in ("searxng", "auto"): + results = await _search_searxng( + query, + max_results=max_results, + searxng_url=searxng_url, + time_range=time_range, + safe_search=safe_search, + ) + if results: + used_engine = "searxng" + + # Fallback to DuckDuckGo + if not results and engine in ("duckduckgo", "auto"): + results = await _search_duckduckgo( + query, + max_results=max_results, + safe_search=safe_search, + ) + if results: + used_engine = "duckduckgo" + + # Build summary + if not results: + summary = ( + f'No search results for "{query}" - all search engines failed or ' + "returned no results. Check network connectivity or try again later." + ) + else: + plural = "s" if len(results) > 1 else "" + summary = f'Found {len(results)} result{plural} for "{query}" using {used_engine}' + + return { + "results": results, + "total_results": len(results), + "query": query, + "engine": used_engine, + "summary": summary, + } + except Exception as exc: + return { + "is_error": True, + "error": str(exc), + "results": [], + "total_results": 0, + "query": query, + "engine": used_engine, + "summary": "", + } diff --git a/packages/nvidia_nat_workspace/tests/test_api_workspace_manager.py b/packages/nvidia_nat_workspace/tests/test_api_workspace_manager.py new file mode 100644 index 0000000000..7b95b155b9 --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_api_workspace_manager.py @@ -0,0 +1,447 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +import threading +from dataclasses import dataclass +from pathlib import Path +from typing import Any + +import httpx +import pytest +from pydantic import Field + +import nat.plugins.workspace.client as api_client_module +from nat.data_models.skill import Skill +from nat.data_models.workspace import ActionRequest +from nat.data_models.workspace import ActionResult +from nat.data_models.workspace import ActionStatus +from nat.data_models.workspace import WorkspaceBaseConfig +from nat.guardrails.workspace import WorkspaceGuardrail +from nat.guardrails.workspace import WorkspaceGuardrailViolation +from nat.plugins.workspace.client import ApiWorkspace +from nat.plugins.workspace.client import ApiWorkspaceManagerBase +from nat.plugins.workspace.client import ApiWorkspaceSessionEntry +from nat.plugins.workspace.client import WorkspaceApiClient +from nat.plugins.workspace.server import WorkspaceApiServerHandle +from nat.plugins.workspace.server import start_workspace_api_server +from nat.plugins.workspace.server import stop_workspace_api_server +from nat.workspace.types import SkillSummary + + +class TestWorkspaceConfig(WorkspaceBaseConfig, name="test"): + """Configuration for API workspace manager tests.""" + + __test__ = False + http_timeout_seconds: float = Field(default=12.0, description="HTTP timeout for workspace API requests.") + + +@dataclass +class TestBackend: + """Backend metadata for API workspace manager tests.""" + + __test__ = False + session_id: str + + +class TestWorkspace(ApiWorkspace): + """Workspace implementation for API workspace manager tests.""" + + __test__ = False + + def __init__(self, + config: TestWorkspaceConfig, + api_client: WorkspaceApiClient, + session_id: str | None = None, + backend: object | None = None): + super().__init__(config=config, api_client=api_client, session_id=session_id) + self.backend = backend + self.config = config + + +class TestWorkspaceManager(ApiWorkspaceManagerBase[TestWorkspaceConfig, TestWorkspace, TestBackend]): + """Concrete API workspace manager implementation for tests.""" + + __test__ = False + _sessions: dict[str, + ApiWorkspaceSessionEntry[TestBackend]] = {} # pyright: ignore[reportIncompatibleVariableOverride] + _session_lock: threading.Lock = threading.Lock() # pyright: ignore[reportIncompatibleVariableOverride] + + def __init__(self, + config: TestWorkspaceConfig, + *, + base_url: str = "http://backend", + extra_header: str | None = None): + super().__init__(config=config) + self.base_url = base_url + self.extra_header = extra_header + self.start_calls: list[str] = [] + self.shutdown_calls: list[TestBackend | None] = [] + + def _build_workspace(self, entry: ApiWorkspaceSessionEntry[TestBackend]) -> TestWorkspace: + return TestWorkspace( + config=self.config, + api_client=entry.api_client, + session_id=entry.session_id, + backend=entry.backend, + ) + + def _session_headers(self, session_id: str) -> dict[str, str]: + headers = super()._session_headers(session_id) + if self.extra_header is not None: + headers["X-Test-Header"] = self.extra_header + return headers + + async def _start_backend(self, session_id: str) -> tuple[str, TestBackend]: + self.start_calls.append(session_id) + return self.base_url, TestBackend(session_id=session_id) + + async def _shutdown_backend(self, backend: TestBackend | None) -> None: + self.shutdown_calls.append(backend) + + +@dataclass +class E2EBackend: + """Backend metadata for end-to-end API workspace tests.""" + + handle: WorkspaceApiServerHandle + + +class E2EWorkspaceManager(ApiWorkspaceManagerBase[TestWorkspaceConfig, TestWorkspace, E2EBackend]): + """API workspace manager that starts a real workspace server.""" + + _sessions: dict[str, + ApiWorkspaceSessionEntry[E2EBackend]] = {} # pyright: ignore[reportIncompatibleVariableOverride] + _session_lock: threading.Lock = threading.Lock() # pyright: ignore[reportIncompatibleVariableOverride] + + def __init__(self, config: TestWorkspaceConfig, *, base_root: Path | None = None): + super().__init__(config=config) + self.base_root = base_root or config.working_directory + + def _build_workspace(self, entry: ApiWorkspaceSessionEntry[E2EBackend]) -> TestWorkspace: + return TestWorkspace( + config=self.config, + api_client=entry.api_client, + session_id=entry.session_id, + backend=entry.backend, + ) + + async def _start_backend(self, session_id: str) -> tuple[str, E2EBackend]: + handle = start_workspace_api_server(self.base_root) + return handle.base_url, E2EBackend(handle=handle) + + async def _shutdown_backend(self, backend: E2EBackend | None) -> None: + if backend is None: + return + stop_workspace_api_server(backend.handle) + + +@pytest.fixture(name="fixture_httpx_clients") +def fixture_httpx_clients(monkeypatch: pytest.MonkeyPatch) -> list[Any]: + """Patch httpx.AsyncClient to capture construction parameters.""" + clients: list[Any] = [] + + class FakeAsyncClient: + + def __init__(self, base_url: str, headers: dict[str, str] | None, timeout: httpx.Timeout): + self.base_url = base_url + self.headers = headers + self.timeout = timeout + self.post_calls: list[str] = [] + self.closed = False + self.raise_on_post: Exception | None = None + clients.append(self) + + async def post(self, path: str) -> None: + if self.raise_on_post is not None: + raise self.raise_on_post + self.post_calls.append(path) + + async def aclose(self) -> None: + self.closed = True + + monkeypatch.setattr(api_client_module.httpx, "AsyncClient", FakeAsyncClient) + return clients + + +@pytest.fixture(name="fixture_reset_manager_sessions") +def fixture_reset_manager_sessions() -> None: + """Reset session cache for manager tests.""" + TestWorkspaceManager._sessions = {} + + +@pytest.fixture(name="fixture_reset_e2e_sessions") +def fixture_reset_e2e_sessions() -> None: + """Reset session cache for end-to-end manager tests.""" + E2EWorkspaceManager._sessions = {} + + +@pytest.fixture(name="fixture_test_config") +def fixture_test_config(tmp_path: Path) -> TestWorkspaceConfig: + """Provide a base workspace config for manager tests.""" + return TestWorkspaceConfig( + working_directory=tmp_path / "workspace-root", + initial_commands=[], + session_id="session-123", + ) + + +async def test_manager_reuses_session_and_cleans_up( + fixture_test_config: TestWorkspaceConfig, + fixture_httpx_clients: list[Any], + fixture_reset_manager_sessions: None, +) -> None: + manager_one = TestWorkspaceManager(fixture_test_config) + manager_two = TestWorkspaceManager(fixture_test_config) + + workspace_one = await manager_one.__aenter__() + workspace_two = await manager_two.__aenter__() + + assert manager_one.start_calls == ["session-123"] + assert manager_two.start_calls == [] + assert workspace_one.backend is workspace_two.backend + assert workspace_one.session_id == "session-123" + assert workspace_one.backend is not None + + assert len(fixture_httpx_clients) == 1 + client = fixture_httpx_clients[0] + assert client.base_url == "http://backend" + assert client.headers == {"X-Workspace-Session": "session-123"} + assert isinstance(client.timeout, httpx.Timeout) + assert client.timeout.connect == pytest.approx(12.0) + assert client.timeout.read == pytest.approx(12.0) + assert client.timeout.write == pytest.approx(12.0) + assert client.timeout.pool == pytest.approx(12.0) + + await manager_one.__aexit__(None, None, None) + assert client.post_calls == [] + assert manager_one.shutdown_calls == [] + assert manager_two.shutdown_calls == [] + + await manager_two.__aexit__(None, None, None) + assert client.post_calls == ["/api/session/close"] + assert client.closed is True + assert manager_two.shutdown_calls == [workspace_one.backend] + + +async def test_manager_uses_endpoint_override_and_custom_headers( + fixture_test_config: TestWorkspaceConfig, + fixture_httpx_clients: list[Any], + fixture_reset_manager_sessions: None, +) -> None: + config = fixture_test_config.model_copy(update={"endpoint": "localhost:4321"}) + manager = TestWorkspaceManager(config, extra_header="value") + + workspace = await manager.__aenter__() + + assert manager.start_calls == [] + assert workspace.backend is None + assert len(fixture_httpx_clients) == 1 + client = fixture_httpx_clients[0] + assert client.base_url == "http://localhost:4321" + assert client.headers == {"X-Workspace-Session": "session-123", "X-Test-Header": "value"} + + await manager.__aexit__(None, None, None) + assert manager.shutdown_calls == [None] + + +async def test_manager_ignores_close_errors( + fixture_test_config: TestWorkspaceConfig, + fixture_httpx_clients: list[Any], + fixture_reset_manager_sessions: None, +) -> None: + manager = TestWorkspaceManager(fixture_test_config) + await manager.__aenter__() + + client = fixture_httpx_clients[0] + client.raise_on_post = httpx.RequestError("boom", request=None) + + await manager.__aexit__(None, None, None) + assert client.closed is True + assert manager.shutdown_calls == [TestBackend(session_id="session-123")] + + +async def test_api_workspace_manager_e2e_single_session( + tmp_path: Path, + fixture_reset_e2e_sessions: None, +) -> None: + base_root = tmp_path / "workspace-root" + config = TestWorkspaceConfig( + working_directory=base_root, + initial_commands=[], + session_id="e2e-single", + ) + manager = E2EWorkspaceManager(config) + + workspace = await manager.__aenter__() + backend = workspace.backend + assert isinstance(backend, E2EBackend) + assert backend.handle.process.is_alive() + + actions = await workspace.get_actions() + assert any(action.name == "bash" for action in actions) + + action_result = await workspace.execute_action("bash", {"command": "echo hello"}) + assert isinstance(action_result, ActionResult) + assert action_result.status is ActionStatus.SUCCESS + assert action_result.error_message is None + assert action_result.execution_time is not None + assert isinstance(action_result.output, dict) + assert action_result.output["stdout"].strip() == "hello" + + create_result = await workspace.create_skill(Skill(name="alpha", description="Skill for API workspace tests.")) + assert isinstance(create_result, ActionResult) + assert create_result.status is ActionStatus.SUCCESS + skills = await workspace.get_skills() + assert all(isinstance(s, SkillSummary) for s in skills) + assert any(skill.name == "alpha" for skill in skills) + full_skill = await workspace.read_skill("alpha") + assert full_skill is not None + assert full_skill.description == "Skill for API workspace tests." + + upload_dir = tmp_path / "upload" + upload_dir.mkdir() + (upload_dir / "note.txt").write_text("hello", encoding="utf-8") + upload_result = await workspace.upload_directory(upload_dir, Path("project")) + assert isinstance(upload_result, ActionResult) + assert upload_result.status is ActionStatus.SUCCESS + + download_dir = tmp_path / "downloaded" + download_result = await workspace.download_directory(Path("project"), download_dir) + assert isinstance(download_result, ActionResult) + assert download_result.status is ActionStatus.SUCCESS + assert (download_dir / "note.txt").read_text(encoding="utf-8") == "hello" + + local_file = tmp_path / "local.txt" + local_file.write_text("payload", encoding="utf-8") + upload_file_result = await workspace.upload_file(local_file, Path("file.txt")) + assert isinstance(upload_file_result, ActionResult) + assert upload_file_result.status is ActionStatus.SUCCESS + + list_response = await workspace._api_client._http_client.get( + "/api/file/list", + params={ + "type": "folder", "path": "." + }, + ) + list_response.raise_for_status() + list_payload = list_response.json() + entries = {entry["name"]: entry["type"] for entry in list_payload["entries"]} + assert entries["project"] == "folder" + assert entries["file.txt"] == "file" + + delete_dir_result = await workspace.delete_directory(Path("project")) + assert isinstance(delete_dir_result, ActionResult) + assert delete_dir_result.status is ActionStatus.SUCCESS + delete_file_result = await workspace.delete_file(Path("file.txt")) + assert isinstance(delete_file_result, ActionResult) + assert delete_file_result.status is ActionStatus.SUCCESS + + await manager.__aexit__(None, None, None) + assert backend.handle.process.is_alive() is False + + +async def test_api_workspace_manager_e2e_multiple_sessions( + tmp_path: Path, + fixture_reset_e2e_sessions: None, +) -> None: + base_root = tmp_path / "workspace-root" + server_handle = start_workspace_api_server(base_root) + try: + config_one = TestWorkspaceConfig( + working_directory=base_root, + initial_commands=[], + session_id="session-a", + endpoint=server_handle.base_url, + ) + config_two = TestWorkspaceConfig( + working_directory=base_root, + initial_commands=[], + session_id="session-b", + endpoint=server_handle.base_url, + ) + manager_one = E2EWorkspaceManager(config_one) + manager_two = E2EWorkspaceManager(config_two) + + workspace_one = await manager_one.__aenter__() + workspace_two = await manager_two.__aenter__() + + local_a = tmp_path / "a.txt" + local_a.write_text("alpha", encoding="utf-8") + upload_a = await workspace_one.upload_file(local_a, Path("shared.txt")) + assert isinstance(upload_a, ActionResult) + assert upload_a.status is ActionStatus.SUCCESS + + not_found = await workspace_two.delete_file(Path("shared.txt")) + assert isinstance(not_found, ActionResult) + assert not_found.status is ActionStatus.FAILURE + assert not_found.error_message is not None + + local_b = tmp_path / "b.txt" + local_b.write_text("beta", encoding="utf-8") + upload_b = await workspace_two.upload_file(local_b, Path("shared.txt")) + assert isinstance(upload_b, ActionResult) + assert upload_b.status is ActionStatus.SUCCESS + + delete_a = await workspace_one.delete_file(Path("shared.txt")) + assert isinstance(delete_a, ActionResult) + assert delete_a.status is ActionStatus.SUCCESS + delete_b = await workspace_two.delete_file(Path("shared.txt")) + assert isinstance(delete_b, ActionResult) + assert delete_b.status is ActionStatus.SUCCESS + + await manager_one.__aexit__(None, None, None) + await manager_two.__aexit__(None, None, None) + finally: + stop_workspace_api_server(server_handle) + assert server_handle.process.is_alive() is False + + +class _BlockActionGuardrail(WorkspaceGuardrail): + name = "block-test" + + async def validate_action(self, action: ActionRequest) -> WorkspaceGuardrailViolation | None: + return WorkspaceGuardrailViolation(guardrail_name=self.name, message=f"Blocked {action.action_name}") + + +async def test_api_workspace_guardrails_block_and_remove( + tmp_path: Path, + fixture_reset_e2e_sessions: None, +) -> None: + base_root = tmp_path / "workspace-root" + config = TestWorkspaceConfig( + working_directory=base_root, + initial_commands=[], + session_id="guardrail-session", + ) + manager = E2EWorkspaceManager(config) + + workspace = await manager.__aenter__() + workspace.add_workspace_guardrail(_BlockActionGuardrail()) + + blocked = await workspace.execute_action("bash", {"command": "echo hello"}) + assert isinstance(blocked, ActionResult) + assert blocked.status is ActionStatus.BLOCKED_BY_GUARDRAIL + assert blocked.error_message is not None + + removed = workspace.remove_workspace_guardrail("block-test") + assert removed is True + allowed = await workspace.execute_action("bash", {"command": "echo hello"}) + assert isinstance(allowed, ActionResult) + assert allowed.status is ActionStatus.SUCCESS + assert isinstance(allowed.output, dict) + assert allowed.output["stdout"].strip() == "hello" + + await manager.__aexit__(None, None, None) diff --git a/packages/nvidia_nat_workspace/tests/test_bash_action.py b/packages/nvidia_nat_workspace/tests/test_bash_action.py new file mode 100644 index 0000000000..af7122c09b --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_bash_action.py @@ -0,0 +1,202 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +import asyncio +import time +from pathlib import Path + +import pytest + +from nat.data_models.workspace import ActionContext +from nat.workspace_actions.workspace.terminal.bash_action import BashAction + + +@pytest.fixture(name="fixture_action_context") +def fixture_action_context(tmp_path: Path) -> ActionContext: + return ActionContext(session_id="test-session", root_path=tmp_path.resolve()) + + +@pytest.fixture(name="fixture_bash_action") +def fixture_bash_action() -> BashAction: + return BashAction() + + +async def _wait_for_marker(marker_path: Path, timeout_seconds: float = 1.0) -> None: + deadline = time.monotonic() + timeout_seconds + while time.monotonic() < deadline: + if marker_path.exists(): + return + await asyncio.sleep(0.01) + raise AssertionError("Marker file was not created in time.") + + +async def test_bash_action_executes_command( + fixture_action_context: ActionContext, + fixture_bash_action: BashAction, +) -> None: + fixture_bash_action.set_context(fixture_action_context) + async with fixture_bash_action as action: + result = await action.execute( + fixture_action_context, + {"command": "pwd"}, + ) + + assert result["timed_out"] is False + assert result["exit_code"] == 0 + assert result["stderr"] == "" + assert result["stdout"].strip() == str(fixture_action_context.root_path) + assert isinstance(result["duration_ms"], int) + assert result["duration_ms"] >= 0 + assert result["signal"] is None + assert result["exit_code_interpretation"] is None + + +async def test_bash_action_timeout( + fixture_action_context: ActionContext, + fixture_bash_action: BashAction, +) -> None: + fixture_bash_action.set_context(fixture_action_context) + async with fixture_bash_action as action: + result = await action.execute( + fixture_action_context, + { + "command": "sleep 1", "timeout_seconds": 0.01 + }, + ) + + assert result["timed_out"] is True + assert result["exit_code"] is None + assert result["signal"] == "SIGTERM" + assert "timed out" in result["stderr"] + + +async def test_bash_action_parallel_commands( + fixture_action_context: ActionContext, + fixture_bash_action: BashAction, +) -> None: + fixture_bash_action.set_context(fixture_action_context) + marker_path = fixture_action_context.root_path / "marker.txt" + if marker_path.exists(): + marker_path.unlink() + + async with fixture_bash_action as action: + long_command = "echo started > marker.txt; sleep 0.4; rm -f marker.txt" + long_task = asyncio.create_task(action.execute(fixture_action_context, {"command": long_command})) + + await _wait_for_marker(marker_path) + + short_command = "if [ -f marker.txt ]; then echo busy; else echo idle; fi" + short_result = await action.execute(fixture_action_context, {"command": short_command}) + long_result = await long_task + + assert short_result["timed_out"] is False + assert short_result["exit_code"] == 0 + assert short_result["stdout"].strip() == "busy" + assert long_result["timed_out"] is False + assert long_result["exit_code"] == 0 + + +async def test_bash_separate_stderr( + fixture_action_context: ActionContext, + fixture_bash_action: BashAction, +) -> None: + """Verify stdout and stderr are captured independently.""" + fixture_bash_action.set_context(fixture_action_context) + async with fixture_bash_action as action: + result = await action.execute( + fixture_action_context, + {"command": "echo out_msg; echo err_msg >&2"}, + ) + + assert result["exit_code"] == 0 + assert "out_msg" in result["stdout"] + assert "err_msg" in result["stderr"] + # stderr should NOT leak into stdout + assert "err_msg" not in result["stdout"] + + +async def test_bash_exit_code_interpretation( + fixture_action_context: ActionContext, + fixture_bash_action: BashAction, +) -> None: + """Non-zero well-known exit codes get a human-readable interpretation.""" + fixture_bash_action.set_context(fixture_action_context) + async with fixture_bash_action as action: + result = await action.execute( + fixture_action_context, + {"command": "exit 127"}, + ) + + assert result["exit_code"] == 127 + assert result["exit_code_interpretation"] == "Command not found" + + +async def test_bash_output_truncation( + fixture_action_context: ActionContext, + fixture_bash_action: BashAction, +) -> None: + """Output exceeding 100 KB is truncated with a notice.""" + fixture_bash_action.set_context(fixture_action_context) + # Generate ~150 KB of output (each line ~101 bytes with padding) + async with fixture_bash_action as action: + result = await action.execute( + fixture_action_context, + {"command": "python3 -c \"print('A' * 100 + '\\n') * 1500\""}, + ) + + # Fallback: generate via seq + printf for reliability + async with fixture_bash_action as action: + result = await action.execute( + fixture_action_context, + {"command": "for i in $(seq 1 1500); do printf '%0100d\\n' $i; done"}, + ) + + assert result["exit_code"] == 0 + assert "[..." in result["stdout"] + assert "truncated...]" in result["stdout"] + + +async def test_bash_working_directory( + fixture_action_context: ActionContext, + fixture_bash_action: BashAction, +) -> None: + """Custom working_directory resolves relative to workspace root.""" + fixture_bash_action.set_context(fixture_action_context) + subdir = fixture_action_context.root_path / "subdir" + subdir.mkdir() + + async with fixture_bash_action as action: + result = await action.execute( + fixture_action_context, + {"command": "pwd", "working_directory": "subdir"}, + ) + + assert result["exit_code"] == 0 + assert result["stdout"].strip() == str(subdir) + + +async def test_bash_working_directory_escape_rejected( + fixture_action_context: ActionContext, + fixture_bash_action: BashAction, +) -> None: + """working_directory outside the workspace root is rejected.""" + fixture_bash_action.set_context(fixture_action_context) + async with fixture_bash_action as action: + with pytest.raises(ValueError, match="within the workspace root"): + await action.execute( + fixture_action_context, + {"command": "pwd", "working_directory": "/tmp"}, + ) diff --git a/packages/nvidia_nat_workspace/tests/test_edit_action.py b/packages/nvidia_nat_workspace/tests/test_edit_action.py new file mode 100644 index 0000000000..1a32654c26 --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_edit_action.py @@ -0,0 +1,191 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +from pathlib import Path + +import pytest + +from nat.data_models.workspace import ActionContext +from nat.workspace_actions.workspace.file.edit_action import EditAction +from nat.workspace_actions.workspace.file.read_action import ReadAction + + +@pytest.fixture(name="fixture_action_context") +def fixture_action_context(tmp_path: Path) -> ActionContext: + return ActionContext(session_id="test-session-edit", root_path=tmp_path.resolve()) + + +@pytest.fixture(name="fixture_edit_action") +def fixture_edit_action() -> EditAction: + return EditAction() + + +@pytest.fixture(name="fixture_read_action") +def fixture_read_action() -> ReadAction: + return ReadAction() + + +async def test_edit_exact_replace( + fixture_action_context: ActionContext, + fixture_edit_action: EditAction, + fixture_read_action: ReadAction, +) -> None: + """Replace a string in a file and verify replacements=1.""" + file_path = fixture_action_context.root_path / "edit_me.txt" + file_path.write_text("Hello World\nGoodbye World\n", encoding="utf-8") + + # Read the file first (required for edit validation) + await fixture_read_action.execute( + fixture_action_context, + {"file_path": str(file_path)}, + ) + + result = await fixture_edit_action.execute( + fixture_action_context, + { + "file_path": str(file_path), + "old_string": "Hello World", + "new_string": "Hi World", + }, + ) + + assert "is_error" not in result + assert result["replacements"] == 1 + assert result["modified"] is True + assert file_path.read_text(encoding="utf-8") == "Hi World\nGoodbye World\n" + + +async def test_edit_create_mode( + fixture_action_context: ActionContext, + fixture_edit_action: EditAction, +) -> None: + """Use old_string='' (create mode) to create a new file.""" + file_path = fixture_action_context.root_path / "created_by_edit.txt" + + result = await fixture_edit_action.execute( + fixture_action_context, + { + "file_path": str(file_path), + "old_string": "", + "new_string": "brand new content", + }, + ) + + assert "is_error" not in result + assert result["replacements"] == 1 + assert result["modified"] is True + assert file_path.read_text(encoding="utf-8") == "brand new content" + + +async def test_edit_file_not_found( + fixture_action_context: ActionContext, + fixture_edit_action: EditAction, +) -> None: + """Attempt to edit a nonexistent file and verify is_error.""" + result = await fixture_edit_action.execute( + fixture_action_context, + { + "file_path": str(fixture_action_context.root_path / "nope.txt"), + "old_string": "foo", + "new_string": "bar", + }, + ) + + assert result["is_error"] is True + assert result["replacements"] == 0 + assert result["modified"] is False + + +async def test_edit_identical_strings( + fixture_action_context: ActionContext, + fixture_edit_action: EditAction, +) -> None: + """Passing identical old_string and new_string should produce an error.""" + file_path = fixture_action_context.root_path / "same.txt" + file_path.write_text("same content", encoding="utf-8") + + result = await fixture_edit_action.execute( + fixture_action_context, + { + "file_path": str(file_path), + "old_string": "same content", + "new_string": "same content", + }, + ) + + assert result["is_error"] is True + assert "identical" in result["error"].lower() + + +async def test_edit_replace_all( + fixture_action_context: ActionContext, + fixture_edit_action: EditAction, + fixture_read_action: ReadAction, +) -> None: + """Use replace_all=True to replace multiple occurrences of a string.""" + file_path = fixture_action_context.root_path / "multi.txt" + file_path.write_text("foo bar foo baz foo\n", encoding="utf-8") + + # Read the file first + await fixture_read_action.execute( + fixture_action_context, + {"file_path": str(file_path)}, + ) + + result = await fixture_edit_action.execute( + fixture_action_context, + { + "file_path": str(file_path), + "old_string": "foo", + "new_string": "qux", + "replace_all": True, + }, + ) + + assert "is_error" not in result + assert result["replacements"] == 3 + assert result["modified"] is True + assert file_path.read_text(encoding="utf-8") == "qux bar qux baz qux\n" + + +async def test_edit_string_not_found( + fixture_action_context: ActionContext, + fixture_edit_action: EditAction, + fixture_read_action: ReadAction, +) -> None: + """Try to replace text that does not exist in the file and verify is_error.""" + file_path = fixture_action_context.root_path / "no_match.txt" + file_path.write_text("alpha beta gamma\n", encoding="utf-8") + + # Read the file first + await fixture_read_action.execute( + fixture_action_context, + {"file_path": str(file_path)}, + ) + + result = await fixture_edit_action.execute( + fixture_action_context, + { + "file_path": str(file_path), + "old_string": "delta", + "new_string": "epsilon", + }, + ) + + assert result["is_error"] is True + assert "not found" in result["error"].lower() or "string" in result["error"].lower() + assert result["replacements"] == 0 + assert result["modified"] is False diff --git a/packages/nvidia_nat_workspace/tests/test_glob_action.py b/packages/nvidia_nat_workspace/tests/test_glob_action.py new file mode 100644 index 0000000000..eaa0596a3b --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_glob_action.py @@ -0,0 +1,91 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +from pathlib import Path + +import pytest + +from nat.data_models.workspace import ActionContext +from nat.workspace_actions.workspace.search.glob_action import GlobAction + + +@pytest.fixture(name="fixture_action_context") +def fixture_action_context(tmp_path: Path) -> ActionContext: + return ActionContext(session_id="test-session-glob", root_path=tmp_path.resolve()) + + +@pytest.fixture(name="fixture_glob_action") +def fixture_glob_action() -> GlobAction: + return GlobAction() + + +async def test_glob_matches_pattern( + fixture_action_context: ActionContext, + fixture_glob_action: GlobAction, +) -> None: + """Create .py and .txt files, glob for *.py, verify only .py files found.""" + root = fixture_action_context.root_path + (root / "script.py").write_text("print('hello')", encoding="utf-8") + (root / "notes.txt").write_text("some notes", encoding="utf-8") + (root / "lib.py").write_text("import os", encoding="utf-8") + + result = await fixture_glob_action.execute( + fixture_action_context, + {"glob_pattern": "*.py"}, + ) + + assert "is_error" not in result + assert result["count"] == 2 + file_names = [Path(f).name for f in result["files"]] + assert "script.py" in file_names + assert "lib.py" in file_names + assert "notes.txt" not in file_names + + +async def test_glob_no_matches( + fixture_action_context: ActionContext, + fixture_glob_action: GlobAction, +) -> None: + """Glob for *.rs in a directory containing only .py files.""" + root = fixture_action_context.root_path + (root / "main.py").write_text("pass", encoding="utf-8") + + result = await fixture_glob_action.execute( + fixture_action_context, + {"glob_pattern": "*.rs"}, + ) + + assert "is_error" not in result + assert result["count"] == 0 + assert result["files"] == [] + + +async def test_glob_not_a_directory( + fixture_action_context: ActionContext, + fixture_glob_action: GlobAction, +) -> None: + """Provide a file path as target_directory and verify error.""" + root = fixture_action_context.root_path + file_path = root / "afile.txt" + file_path.write_text("content", encoding="utf-8") + + result = await fixture_glob_action.execute( + fixture_action_context, + {"glob_pattern": "*.py", "target_directory": str(file_path)}, + ) + + assert result["is_error"] is True + assert "not a directory" in result["error"].lower() diff --git a/packages/nvidia_nat_workspace/tests/test_list_action.py b/packages/nvidia_nat_workspace/tests/test_list_action.py new file mode 100644 index 0000000000..72ae14bd63 --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_list_action.py @@ -0,0 +1,105 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +from pathlib import Path + +import pytest + +from nat.data_models.workspace import ActionContext +from nat.workspace_actions.workspace.search.list_action import ListAction + + +@pytest.fixture(name="fixture_action_context") +def fixture_action_context(tmp_path: Path) -> ActionContext: + return ActionContext(session_id="test-session-list", root_path=tmp_path.resolve()) + + +@pytest.fixture(name="fixture_list_action") +def fixture_list_action() -> ListAction: + return ListAction() + + +async def test_list_directory( + fixture_action_context: ActionContext, + fixture_list_action: ListAction, +) -> None: + """Create several files, list the directory, and verify the tree output has correct file_count.""" + root = fixture_action_context.root_path + (root / "a.txt").write_text("a", encoding="utf-8") + (root / "b.txt").write_text("b", encoding="utf-8") + sub = root / "sub" + sub.mkdir() + (sub / "c.txt").write_text("c", encoding="utf-8") + + result = await fixture_list_action.execute( + fixture_action_context, + {"path": str(root)}, + ) + + assert "is_error" not in result + assert result["file_count"] == 3 + # The tree output should mention the file names + tree = result["tree"] + assert "a.txt" in tree + assert "b.txt" in tree + assert "c.txt" in tree + assert "sub" in tree + + +async def test_list_empty_directory( + fixture_action_context: ActionContext, + fixture_list_action: ListAction, +) -> None: + """List an empty directory and verify file_count=0.""" + empty_dir = fixture_action_context.root_path / "empty" + empty_dir.mkdir() + + result = await fixture_list_action.execute( + fixture_action_context, + {"path": str(empty_dir)}, + ) + + assert "is_error" not in result + assert result["file_count"] == 0 + + +async def test_list_with_max_depth( + fixture_action_context: ActionContext, + fixture_list_action: ListAction, +) -> None: + """Create nested directories and verify depth limiting works with max_depth=1.""" + root = fixture_action_context.root_path + (root / "top.txt").write_text("top", encoding="utf-8") + level1 = root / "level1" + level1.mkdir() + (level1 / "mid.txt").write_text("mid", encoding="utf-8") + level2 = level1 / "level2" + level2.mkdir() + (level2 / "deep.txt").write_text("deep", encoding="utf-8") + + result = await fixture_list_action.execute( + fixture_action_context, + {"path": str(root), "max_depth": 1}, + ) + + assert "is_error" not in result + tree = result["tree"] + # top.txt should be listed (depth 0) + assert "top.txt" in tree + # mid.txt is at depth 1, should be included + assert "mid.txt" in tree + # deep.txt is at depth 2, should NOT be included with max_depth=1 + assert "deep.txt" not in tree diff --git a/packages/nvidia_nat_workspace/tests/test_local_workspace.py b/packages/nvidia_nat_workspace/tests/test_local_workspace.py new file mode 100644 index 0000000000..9a6a17ed51 --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_local_workspace.py @@ -0,0 +1,178 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +import typing +from multiprocessing.process import BaseProcess +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +import httpx +import pytest + +import nat.plugins.workspace.client as api_client_module +from nat.plugins.workspace import local as local_module +from nat.plugins.workspace.local import LocalWorkspaceConfig +from nat.plugins.workspace.local import LocalWorkspaceManager +from nat.plugins.workspace.server import WorkspaceApiServerHandle + + +@pytest.fixture(name="fixture_httpx_clients") +def fixture_httpx_clients(monkeypatch: pytest.MonkeyPatch) -> list[Any]: + """Patch httpx.AsyncClient to capture construction parameters.""" + clients: list[Any] = [] + + class FakeAsyncClient: + + def __init__(self, base_url: str, headers: dict[str, str] | None, timeout: httpx.Timeout): + self.base_url = base_url + self.headers = headers + self.timeout = timeout + self.post_calls: list[str] = [] + self.closed = False + clients.append(self) + + async def post(self, path: str) -> None: + self.post_calls.append(path) + + async def aclose(self) -> None: + self.closed = True + + monkeypatch.setattr(api_client_module.httpx, "AsyncClient", FakeAsyncClient) + return clients + + +@pytest.fixture(name="fixture_reset_local_sessions") +def fixture_reset_local_sessions() -> None: + """Reset session cache for local workspace tests.""" + LocalWorkspaceManager._sessions = {} + + +@pytest.fixture(name="fixture_server_handle") +def fixture_server_handle(tmp_path: Path) -> WorkspaceApiServerHandle: + """Return a fake workspace server handle.""" + return WorkspaceApiServerHandle( + process=typing.cast(BaseProcess, SimpleNamespace()), + host="127.0.0.1", + port=8123, + root_path=tmp_path / "workspace-root", + ) + + +@pytest.fixture(name="fixture_server_controls") +def fixture_server_controls( + monkeypatch: pytest.MonkeyPatch, + fixture_server_handle: WorkspaceApiServerHandle, +) -> dict[str, Any]: + """Patch workspace server start/stop helpers.""" + calls: dict[str, Any] = {"start": [], "stop": []} + + def fake_start(root_path: Path, host: str = "127.0.0.1", timeout_seconds: float = 10.0) -> WorkspaceApiServerHandle: + calls["start"].append((root_path, host, timeout_seconds)) + return fixture_server_handle + + def fake_stop(handle: WorkspaceApiServerHandle, timeout_seconds: float = 5.0) -> None: + calls["stop"].append((handle, timeout_seconds)) + + monkeypatch.setattr(local_module, "start_workspace_api_server", fake_start) + monkeypatch.setattr(local_module, "stop_workspace_api_server", fake_stop) + return calls + + +async def test_local_workspace_uses_session_directory( + tmp_path: Path, + fixture_httpx_clients: list[Any], + fixture_server_controls: dict[str, Any], + fixture_server_handle: WorkspaceApiServerHandle, + fixture_reset_local_sessions: None, +) -> None: + base_dir = tmp_path / "workspace-root" + config = LocalWorkspaceConfig( + working_directory=base_dir, + initial_commands=[], + session_id="local-session", + ) + manager = LocalWorkspaceManager(config) + + workspace = await manager.__aenter__() + + assert fixture_server_controls["start"] == [(base_dir, "127.0.0.1", 10.0)] + assert workspace.config.working_directory == base_dir / "local-session" + assert workspace.config.working_directory.exists() + assert config.working_directory == base_dir + + client = fixture_httpx_clients[0] + assert client.base_url == "http://127.0.0.1:8123" + + await manager.__aexit__(None, None, None) + assert fixture_server_controls["stop"] == [(fixture_server_handle, 5.0)] + + +async def test_local_workspace_endpoint_override_skips_server( + tmp_path: Path, + fixture_httpx_clients: list[Any], + fixture_server_controls: dict[str, Any], + fixture_reset_local_sessions: None, +) -> None: + base_dir = tmp_path / "workspace-root" + config = LocalWorkspaceConfig( + working_directory=base_dir, + initial_commands=[], + session_id="override-session", + endpoint="localhost:9000", + ) + manager = LocalWorkspaceManager(config) + + workspace = await manager.__aenter__() + + assert fixture_server_controls["start"] == [] + assert workspace.config.working_directory == base_dir / "override-session" + assert workspace.config.working_directory.exists() + + client = fixture_httpx_clients[0] + assert client.base_url == "http://localhost:9000" + + await manager.__aexit__(None, None, None) + assert fixture_server_controls["stop"] == [] + + +async def test_local_workspace_reuses_session_and_cleans_up( + tmp_path: Path, + fixture_httpx_clients: list[Any], + fixture_server_controls: dict[str, Any], + fixture_reset_local_sessions: None, +) -> None: + base_dir = tmp_path / "workspace-root" + config = LocalWorkspaceConfig( + working_directory=base_dir, + initial_commands=[], + session_id="shared-session", + ) + manager_one = LocalWorkspaceManager(config) + manager_two = LocalWorkspaceManager(config) + + await manager_one.__aenter__() + await manager_two.__aenter__() + + assert len(fixture_server_controls["start"]) == 1 + + await manager_one.__aexit__(None, None, None) + assert fixture_server_controls["stop"] == [] + + await manager_two.__aexit__(None, None, None) + assert fixture_server_controls["stop"] != [] + assert fixture_httpx_clients[0].post_calls == ["/api/session/close"] + assert fixture_httpx_clients[0].closed is True diff --git a/packages/nvidia_nat_workspace/tests/test_multi_edit_action.py b/packages/nvidia_nat_workspace/tests/test_multi_edit_action.py new file mode 100644 index 0000000000..740843f148 --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_multi_edit_action.py @@ -0,0 +1,111 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +from pathlib import Path + +import pytest + +from nat.data_models.workspace import ActionContext +from nat.workspace_actions.workspace.file.multi_edit_action import MultiEditAction +from nat.workspace_actions.workspace.file.read_action import ReadAction + + +@pytest.fixture(name="fixture_action_context") +def fixture_action_context(tmp_path: Path) -> ActionContext: + return ActionContext(session_id="test-session-multi-edit", root_path=tmp_path.resolve()) + + +@pytest.fixture(name="fixture_multi_edit_action") +def fixture_multi_edit_action() -> MultiEditAction: + return MultiEditAction() + + +@pytest.fixture(name="fixture_read_action") +def fixture_read_action() -> ReadAction: + return ReadAction() + + +async def test_multi_edit_sequential( + fixture_action_context: ActionContext, + fixture_multi_edit_action: MultiEditAction, + fixture_read_action: ReadAction, +) -> None: + """Apply 2 sequential edits and verify both succeed.""" + file_path = fixture_action_context.root_path / "multi_edit.txt" + file_path.write_text("aaa bbb ccc\n", encoding="utf-8") + + # Read the file first (required for edit validation) + await fixture_read_action.execute( + fixture_action_context, + {"file_path": str(file_path)}, + ) + + result = await fixture_multi_edit_action.execute( + fixture_action_context, + { + "file_path": str(file_path), + "edits": [ + {"old_string": "aaa", "new_string": "AAA"}, + {"old_string": "bbb", "new_string": "BBB"}, + ], + }, + ) + + assert result["total_edits"] == 2 + assert result["successful_edits"] == 2 + assert result["failed_edits"] == 0 + assert result["total_replacements"] == 2 + assert result["modified"] is True + assert "is_error" not in result + assert file_path.read_text(encoding="utf-8") == "AAA BBB ccc\n" + + +async def test_multi_edit_stops_on_failure( + fixture_action_context: ActionContext, + fixture_multi_edit_action: MultiEditAction, + fixture_read_action: ReadAction, +) -> None: + """First edit succeeds, second edit fails (string not found), verify counts.""" + file_path = fixture_action_context.root_path / "partial_edit.txt" + file_path.write_text("apple banana\n", encoding="utf-8") + + # Read the file first + await fixture_read_action.execute( + fixture_action_context, + {"file_path": str(file_path)}, + ) + + result = await fixture_multi_edit_action.execute( + fixture_action_context, + { + "file_path": str(file_path), + "edits": [ + {"old_string": "apple", "new_string": "APPLE"}, + {"old_string": "cherry", "new_string": "CHERRY"}, # does not exist + ], + }, + ) + + assert result["total_edits"] == 2 + assert result["successful_edits"] == 1 + assert result["failed_edits"] == 1 + assert result["is_error"] is True + # The first edit should have been applied + assert file_path.read_text(encoding="utf-8") == "APPLE banana\n" + # Check that results list reflects success then failure + assert len(result["results"]) == 2 + assert result["results"][0]["success"] is True + assert result["results"][1]["success"] is False diff --git a/packages/nvidia_nat_workspace/tests/test_read_action.py b/packages/nvidia_nat_workspace/tests/test_read_action.py new file mode 100644 index 0000000000..63bd0280c4 --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_read_action.py @@ -0,0 +1,129 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +from pathlib import Path + +import pytest + +from nat.data_models.workspace import ActionContext +from nat.workspace_actions.workspace.file.read_action import ReadAction + + +@pytest.fixture(name="fixture_action_context") +def fixture_action_context(tmp_path: Path) -> ActionContext: + return ActionContext(session_id="test-session-read", root_path=tmp_path.resolve()) + + +@pytest.fixture(name="fixture_read_action") +def fixture_read_action() -> ReadAction: + return ReadAction() + + +async def test_read_normal_file( + fixture_action_context: ActionContext, + fixture_read_action: ReadAction, +) -> None: + """Write a file and read it back, verifying that content includes line numbers.""" + file_path = fixture_action_context.root_path / "hello.txt" + file_path.write_text("line one\nline two\nline three\n", encoding="utf-8") + + result = await fixture_read_action.execute( + fixture_action_context, + {"file_path": str(file_path)}, + ) + + assert "is_error" not in result + assert result["total_lines"] == 4 # trailing newline produces an empty 4th line + assert result["lines_returned"] > 0 + # Content should contain numbered lines (e.g. " 1|line one") + content = result["content"] + assert "1|" in content + assert "line one" in content + assert "line two" in content + + +async def test_read_with_offset_and_limit( + fixture_action_context: ActionContext, + fixture_read_action: ReadAction, +) -> None: + """Read lines 2-3 from a 5-line file using offset and limit.""" + file_path = fixture_action_context.root_path / "five_lines.txt" + file_path.write_text("aaa\nbbb\nccc\nddd\neee", encoding="utf-8") + + result = await fixture_read_action.execute( + fixture_action_context, + {"file_path": str(file_path), "offset": 2, "limit": 2}, + ) + + assert "is_error" not in result + assert result["start_line"] == 2 + assert result["end_line"] == 3 + assert result["lines_returned"] == 2 + content = result["content"] + assert "bbb" in content + assert "ccc" in content + # Line 1 (aaa) should not be present in the output + assert "aaa" not in content + + +async def test_read_file_not_found( + fixture_action_context: ActionContext, + fixture_read_action: ReadAction, +) -> None: + """Attempt to read a nonexistent file and verify is_error is True.""" + result = await fixture_read_action.execute( + fixture_action_context, + {"file_path": str(fixture_action_context.root_path / "does_not_exist.txt")}, + ) + + assert result["is_error"] is True + assert "not found" in result["error"].lower() or "no such file" in result["error"].lower() + + +async def test_read_binary_file( + fixture_action_context: ActionContext, + fixture_read_action: ReadAction, +) -> None: + """Attempt to read a binary file (.exe) and verify an error about binary content.""" + file_path = fixture_action_context.root_path / "program.exe" + file_path.write_bytes(b"\x00\x01\x02\x03") + + result = await fixture_read_action.execute( + fixture_action_context, + {"file_path": str(file_path)}, + ) + + assert result["is_error"] is True + assert "binary" in result["error"].lower() + + +async def test_read_empty_file( + fixture_action_context: ActionContext, + fixture_read_action: ReadAction, +) -> None: + """Read an empty file and verify the content says 'File is empty.'.""" + file_path = fixture_action_context.root_path / "empty.txt" + file_path.write_text("", encoding="utf-8") + + result = await fixture_read_action.execute( + fixture_action_context, + {"file_path": str(file_path)}, + ) + + assert "is_error" not in result + assert result["content"] == "File is empty." + assert result["total_lines"] == 0 + assert result["lines_returned"] == 0 diff --git a/packages/nvidia_nat_workspace/tests/test_todo_actions.py b/packages/nvidia_nat_workspace/tests/test_todo_actions.py new file mode 100644 index 0000000000..ba09c6d43c --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_todo_actions.py @@ -0,0 +1,277 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +import uuid +from pathlib import Path + +import pytest + +from nat.data_models.workspace import ActionContext +from nat.workspace_actions.workspace.todo.todo_read_action import TodoReadAction +from nat.workspace_actions.workspace.todo.todo_write_action import TodoWriteAction +from nat.workspace_actions.workspace.utils.todo_store import clear_todos + + +@pytest.fixture(name="fixture_action_context") +def fixture_action_context(tmp_path: Path) -> ActionContext: + # Use a unique session id per test to avoid cross-test state pollution. + session_id = f"test-session-todo-{uuid.uuid4().hex[:8]}" + return ActionContext(session_id=session_id, root_path=tmp_path.resolve()) + + +@pytest.fixture(name="fixture_todo_write") +def fixture_todo_write() -> TodoWriteAction: + return TodoWriteAction() + + +@pytest.fixture(name="fixture_todo_read") +def fixture_todo_read() -> TodoReadAction: + return TodoReadAction() + + +@pytest.fixture(autouse=True) +def _cleanup_todos(fixture_action_context: ActionContext): + """Ensure todo store is clean before and after each test.""" + clear_todos(fixture_action_context.session_id) + yield + clear_todos(fixture_action_context.session_id) + + +async def test_todo_create_and_read( + fixture_action_context: ActionContext, + fixture_todo_write: TodoWriteAction, + fixture_todo_read: TodoReadAction, +) -> None: + """Write todos, then read them back and verify.""" + write_result = await fixture_todo_write.execute( + fixture_action_context, + { + "todos": [ + {"id": "task-1", "content": "First task", "status": "pending"}, + {"id": "task-2", "content": "Second task", "status": "in_progress"}, + ], + }, + ) + + assert "is_error" not in write_result + assert write_result["created"] == 2 + assert write_result["updated"] == 0 + + read_result = await fixture_todo_read.execute( + fixture_action_context, + {}, + ) + + assert "is_error" not in read_result + assert read_result["count"] == 2 + ids = {item["id"] for item in read_result["todos"]} + assert ids == {"task-1", "task-2"} + + +async def test_todo_merge_mode( + fixture_action_context: ActionContext, + fixture_todo_write: TodoWriteAction, + fixture_todo_read: TodoReadAction, +) -> None: + """Write an initial set, then merge new items preserving existing ones.""" + # Initial write + await fixture_todo_write.execute( + fixture_action_context, + { + "todos": [ + {"id": "t1", "content": "Original", "status": "pending"}, + ], + }, + ) + + # Merge a new item + merge_result = await fixture_todo_write.execute( + fixture_action_context, + { + "todos": [ + {"id": "t2", "content": "Merged", "status": "pending"}, + ], + "merge": True, + }, + ) + + assert "is_error" not in merge_result + assert merge_result["created"] == 1 + assert merge_result["updated"] == 0 + + read_result = await fixture_todo_read.execute(fixture_action_context, {}) + assert read_result["count"] == 2 + ids = {item["id"] for item in read_result["todos"]} + assert ids == {"t1", "t2"} + + +async def test_todo_replace_mode( + fixture_action_context: ActionContext, + fixture_todo_write: TodoWriteAction, + fixture_todo_read: TodoReadAction, +) -> None: + """Write an initial set, then replace entirely with a new set.""" + # Initial write + await fixture_todo_write.execute( + fixture_action_context, + { + "todos": [ + {"id": "old-1", "content": "Old task", "status": "pending"}, + {"id": "old-2", "content": "Another old", "status": "completed"}, + ], + }, + ) + + # Replace (merge=False is default) + replace_result = await fixture_todo_write.execute( + fixture_action_context, + { + "todos": [ + {"id": "new-1", "content": "New task", "status": "pending"}, + ], + "merge": False, + }, + ) + + assert "is_error" not in replace_result + assert replace_result["created"] == 1 + assert replace_result["removed"] == 2 + + read_result = await fixture_todo_read.execute(fixture_action_context, {}) + assert read_result["count"] == 1 + assert read_result["todos"][0]["id"] == "new-1" + + +async def test_todo_filter_by_status( + fixture_action_context: ActionContext, + fixture_todo_write: TodoWriteAction, + fixture_todo_read: TodoReadAction, +) -> None: + """Write todos with mixed statuses and filter by pending.""" + await fixture_todo_write.execute( + fixture_action_context, + { + "todos": [ + {"id": "a", "content": "Pending task", "status": "pending"}, + {"id": "b", "content": "Done task", "status": "completed"}, + {"id": "c", "content": "Another pending", "status": "pending"}, + ], + }, + ) + + read_result = await fixture_todo_read.execute( + fixture_action_context, + {"status": "pending"}, + ) + + assert "is_error" not in read_result + assert read_result["count"] == 2 + statuses = {item["status"] for item in read_result["todos"]} + assert statuses == {"pending"} + + +async def test_todo_read_by_id( + fixture_action_context: ActionContext, + fixture_todo_write: TodoWriteAction, + fixture_todo_read: TodoReadAction, +) -> None: + """Read a specific todo by id.""" + await fixture_todo_write.execute( + fixture_action_context, + { + "todos": [ + {"id": "target", "content": "Target task", "status": "pending"}, + {"id": "other", "content": "Other task", "status": "completed"}, + ], + }, + ) + + read_result = await fixture_todo_read.execute( + fixture_action_context, + {"id": "target"}, + ) + + assert "is_error" not in read_result + assert read_result["count"] == 1 + assert read_result["todos"][0]["id"] == "target" + assert read_result["todos"][0]["content"] == "Target task" + + +async def test_todo_read_not_found( + fixture_action_context: ActionContext, + fixture_todo_read: TodoReadAction, +) -> None: + """Read a nonexistent todo id and verify is_error.""" + read_result = await fixture_todo_read.execute( + fixture_action_context, + {"id": "nonexistent"}, + ) + + assert read_result["is_error"] is True + assert "not found" in read_result["error"].lower() + assert read_result["count"] == 0 + + +async def test_todo_dependency_validation( + fixture_action_context: ActionContext, + fixture_todo_write: TodoWriteAction, +) -> None: + """A blocked_by reference to a nonexistent task should produce is_error.""" + write_result = await fixture_todo_write.execute( + fixture_action_context, + { + "todos": [ + { + "id": "depends", + "content": "Depends on ghost", + "status": "pending", + "blocked_by": ["ghost-task"], + }, + ], + }, + ) + + assert write_result["is_error"] is True + assert "does not exist" in write_result["error"].lower() or "dependency" in write_result["error"].lower() + + +async def test_todo_cycle_detection( + fixture_action_context: ActionContext, + fixture_todo_write: TodoWriteAction, +) -> None: + """Create a circular dependency (A blocked by B, B blocked by A) and verify is_error.""" + write_result = await fixture_todo_write.execute( + fixture_action_context, + { + "todos": [ + { + "id": "cycle-a", + "content": "Task A", + "status": "pending", + "blocked_by": ["cycle-b"], + }, + { + "id": "cycle-b", + "content": "Task B", + "status": "pending", + "blocked_by": ["cycle-a"], + }, + ], + }, + ) + + assert write_result["is_error"] is True + assert "circular" in write_result["error"].lower() or "cycle" in write_result["error"].lower() diff --git a/packages/nvidia_nat_workspace/tests/test_web_actions.py b/packages/nvidia_nat_workspace/tests/test_web_actions.py new file mode 100644 index 0000000000..9b0d449bbd --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_web_actions.py @@ -0,0 +1,398 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +import json +from pathlib import Path +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest + +from nat.data_models.workspace import ActionContext +from nat.workspace_actions.workspace.web.web_search_action import WebSearchAction +from nat.workspace_actions.workspace.web.web_fetch_action import WebFetchAction + + +@pytest.fixture(name="fixture_action_context") +def fixture_action_context(tmp_path: Path) -> ActionContext: + return ActionContext(session_id="test-session-web", root_path=tmp_path.resolve()) + + +# --------------------------------------------------------------------------- +# WebSearchAction tests +# --------------------------------------------------------------------------- + + +@pytest.fixture(name="fixture_search_action") +def fixture_search_action() -> WebSearchAction: + return WebSearchAction() + + +async def test_web_search_requires_query( + fixture_action_context: ActionContext, + fixture_search_action: WebSearchAction, +) -> None: + """Empty or missing query returns an error.""" + result = await fixture_search_action.execute(fixture_action_context, {}) + assert result["is_error"] is True + assert "query" in result["error"].lower() + + result2 = await fixture_search_action.execute(fixture_action_context, {"query": ""}) + assert result2["is_error"] is True + + +async def test_web_search_searxng_success( + fixture_action_context: ActionContext, + fixture_search_action: WebSearchAction, +) -> None: + """SearXNG returning valid JSON results produces a successful response.""" + fake_response = MagicMock() + fake_response.status_code = 200 + fake_response.headers = {"content-type": "application/json"} + fake_response.raise_for_status = MagicMock() + fake_response.json.return_value = { + "results": [ + {"title": "Result 1", "url": "https://example.com/1", "content": "Snippet 1"}, + {"title": "Result 2", "url": "https://example.com/2", "content": "Snippet 2"}, + ], + } + + mock_client = AsyncMock() + mock_client.get = AsyncMock(return_value=fake_response) + mock_client.__aenter__ = AsyncMock(return_value=mock_client) + mock_client.__aexit__ = AsyncMock(return_value=False) + + with patch( + "nat.workspace_actions.workspace.web.web_search_action._get_http_client", + return_value=mock_client, + ): + result = await fixture_search_action.execute( + fixture_action_context, + {"query": "test query", "engine": "searxng"}, + ) + + assert "is_error" not in result + assert result["total_results"] == 2 + assert result["engine"] == "searxng" + assert result["query"] == "test query" + assert len(result["results"]) == 2 + assert result["results"][0]["title"] == "Result 1" + assert result["results"][0]["url"] == "https://example.com/1" + + +async def test_web_search_fallback_to_duckduckgo( + fixture_action_context: ActionContext, + fixture_search_action: WebSearchAction, +) -> None: + """When SearXNG returns empty results, DuckDuckGo fallback is attempted.""" + # SearXNG returns empty + searxng_response = MagicMock() + searxng_response.status_code = 200 + searxng_response.headers = {"content-type": "application/json"} + searxng_response.raise_for_status = MagicMock() + searxng_response.json.return_value = {"results": []} + + # DDG returns HTML with results + ddg_html = ( + '' + 'DDG Result' + '' + '
DDG snippet
' + ) + ddg_response = MagicMock() + ddg_response.status_code = 200 + ddg_response.headers = {"content-type": "text/html"} + ddg_response.raise_for_status = MagicMock() + ddg_response.text = ddg_html + + call_count = 0 + + async def fake_get(url, **kwargs): + nonlocal call_count + call_count += 1 + if "searx" in url.lower() or "searxng" in url.lower(): + return searxng_response + return ddg_response + + mock_client = AsyncMock() + mock_client.get = AsyncMock(side_effect=fake_get) + mock_client.__aenter__ = AsyncMock(return_value=mock_client) + mock_client.__aexit__ = AsyncMock(return_value=False) + + with patch( + "nat.workspace_actions.workspace.web.web_search_action._get_http_client", + return_value=mock_client, + ): + result = await fixture_search_action.execute( + fixture_action_context, + {"query": "test fallback", "engine": "auto"}, + ) + + assert "is_error" not in result + assert result["engine"] == "duckduckgo" + assert result["total_results"] >= 1 + assert result["results"][0]["url"] == "https://example.com/ddg" + + +async def test_web_search_no_results( + fixture_action_context: ActionContext, + fixture_search_action: WebSearchAction, +) -> None: + """When all engines return empty, summary reflects it.""" + empty_response = MagicMock() + empty_response.status_code = 200 + empty_response.headers = {"content-type": "application/json"} + empty_response.raise_for_status = MagicMock() + empty_response.json.return_value = {"results": []} + + ddg_response = MagicMock() + ddg_response.status_code = 200 + ddg_response.headers = {"content-type": "text/html"} + ddg_response.raise_for_status = MagicMock() + ddg_response.text = "" + + async def fake_get(url, **kwargs): + if "duckduckgo" in url: + return ddg_response + return empty_response + + mock_client = AsyncMock() + mock_client.get = AsyncMock(side_effect=fake_get) + mock_client.__aenter__ = AsyncMock(return_value=mock_client) + mock_client.__aexit__ = AsyncMock(return_value=False) + + with patch( + "nat.workspace_actions.workspace.web.web_search_action._get_http_client", + return_value=mock_client, + ): + result = await fixture_search_action.execute( + fixture_action_context, + {"query": "obscure nonexistent query xyz"}, + ) + + assert result["total_results"] == 0 + assert "no search results" in result["summary"].lower() + + +async def test_web_search_max_results_capped( + fixture_action_context: ActionContext, + fixture_search_action: WebSearchAction, +) -> None: + """max_results is capped at 20.""" + fake_response = MagicMock() + fake_response.status_code = 200 + fake_response.headers = {"content-type": "application/json"} + fake_response.raise_for_status = MagicMock() + fake_response.json.return_value = { + "results": [ + {"title": f"R{i}", "url": f"https://example.com/{i}", "content": f"S{i}"} + for i in range(30) + ], + } + + mock_client = AsyncMock() + mock_client.get = AsyncMock(return_value=fake_response) + mock_client.__aenter__ = AsyncMock(return_value=mock_client) + mock_client.__aexit__ = AsyncMock(return_value=False) + + with patch( + "nat.workspace_actions.workspace.web.web_search_action._get_http_client", + return_value=mock_client, + ): + result = await fixture_search_action.execute( + fixture_action_context, + {"query": "many results", "max_results": 50, "engine": "searxng"}, + ) + + assert "is_error" not in result + assert result["total_results"] <= 20 + + +# --------------------------------------------------------------------------- +# WebFetchAction tests +# --------------------------------------------------------------------------- + + +@pytest.fixture(name="fixture_fetch_action") +def fixture_fetch_action() -> WebFetchAction: + return WebFetchAction() + + +async def test_web_fetch_requires_url( + fixture_action_context: ActionContext, + fixture_fetch_action: WebFetchAction, +) -> None: + """Empty or missing url returns an error.""" + result = await fixture_fetch_action.execute(fixture_action_context, {}) + assert result["is_error"] is True + assert "url" in result["error"].lower() + + +async def test_web_fetch_rejects_private_hosts( + fixture_action_context: ActionContext, + fixture_fetch_action: WebFetchAction, +) -> None: + """Localhost and private IPs are blocked.""" + for blocked_url in [ + "http://localhost/path", + "http://127.0.0.1/path", + "http://192.168.1.1/path", + "http://10.0.0.1/path", + ]: + result = await fixture_fetch_action.execute( + fixture_action_context, {"url": blocked_url} + ) + assert result["is_error"] is True + assert "private" in result["error"].lower() or "localhost" in result["error"].lower() + + +async def test_web_fetch_rejects_unsupported_protocol( + fixture_action_context: ActionContext, + fixture_fetch_action: WebFetchAction, +) -> None: + """Non-http(s) protocols are rejected.""" + result = await fixture_fetch_action.execute( + fixture_action_context, {"url": "ftp://example.com/file"} + ) + assert result["is_error"] is True + assert "unsupported protocol" in result["error"].lower() + + +async def test_web_fetch_html_conversion( + fixture_action_context: ActionContext, + fixture_fetch_action: WebFetchAction, +) -> None: + """HTML content is converted to markdown-like text.""" + html_content = ( + "Test Page" + '' + "" + "

Hello World

" + "

This is a test paragraph.

" + 'Link' + "" + ) + + fake_response = MagicMock() + fake_response.status_code = 200 + fake_response.headers = {"content-type": "text/html; charset=utf-8"} + fake_response.url = "https://example.com/page" + fake_response.text = html_content + fake_response.raise_for_status = MagicMock() + + mock_client = AsyncMock() + mock_client.get = AsyncMock(return_value=fake_response) + mock_client.__aenter__ = AsyncMock(return_value=mock_client) + mock_client.__aexit__ = AsyncMock(return_value=False) + + with patch("nat.workspace_actions.workspace.web.web_fetch_action.httpx", create=True) as mock_httpx: + mock_httpx.AsyncClient = MagicMock(return_value=mock_client) + + # Patch at module level since httpx is imported inside execute + with patch( + "nat.workspace_actions.workspace.web.web_fetch_action.WebFetchAction.execute", + wraps=fixture_fetch_action.execute, + ): + # We need to mock httpx import inside execute + pass + + # Use a direct approach - mock the httpx module + import types + mock_httpx_module = types.ModuleType("httpx") + mock_httpx_module.AsyncClient = MagicMock(return_value=mock_client) + + with patch.dict("sys.modules", {"httpx": mock_httpx_module}): + result = await fixture_fetch_action.execute( + fixture_action_context, + {"url": "https://example.com/page"}, + ) + + assert "is_error" not in result + assert result["title"] == "Test Page" + assert result["description"] == "A test page" + assert "Hello World" in result["content"] + # The lightweight HTML→markdown converter wraps content in ** + assert "test**" in result["content"] + assert "[Link](https://example.com)" in result["content"] + assert result["content_type"] == "text/html; charset=utf-8" + assert isinstance(result["length"], int) + + +async def test_web_fetch_raw_mode( + fixture_action_context: ActionContext, + fixture_fetch_action: WebFetchAction, +) -> None: + """Raw mode returns unprocessed content.""" + raw_html = "

raw

" + + fake_response = MagicMock() + fake_response.status_code = 200 + fake_response.headers = {"content-type": "text/html"} + fake_response.url = "https://example.com/raw" + fake_response.text = raw_html + fake_response.raise_for_status = MagicMock() + + mock_client = AsyncMock() + mock_client.get = AsyncMock(return_value=fake_response) + mock_client.__aenter__ = AsyncMock(return_value=mock_client) + mock_client.__aexit__ = AsyncMock(return_value=False) + + import types + mock_httpx_module = types.ModuleType("httpx") + mock_httpx_module.AsyncClient = MagicMock(return_value=mock_client) + + with patch.dict("sys.modules", {"httpx": mock_httpx_module}): + result = await fixture_fetch_action.execute( + fixture_action_context, + {"url": "https://example.com/raw", "raw": True}, + ) + + assert "is_error" not in result + # Raw mode should preserve HTML tags + assert "

raw

" in result["content"] + + +async def test_web_fetch_truncation( + fixture_action_context: ActionContext, + fixture_fetch_action: WebFetchAction, +) -> None: + """Content exceeding max_length is truncated.""" + long_content = "A" * 1000 + + fake_response = MagicMock() + fake_response.status_code = 200 + fake_response.headers = {"content-type": "text/plain"} + fake_response.url = "https://example.com/long" + fake_response.text = long_content + fake_response.raise_for_status = MagicMock() + + mock_client = AsyncMock() + mock_client.get = AsyncMock(return_value=fake_response) + mock_client.__aenter__ = AsyncMock(return_value=mock_client) + mock_client.__aexit__ = AsyncMock(return_value=False) + + import types + mock_httpx_module = types.ModuleType("httpx") + mock_httpx_module.AsyncClient = MagicMock(return_value=mock_client) + + with patch.dict("sys.modules", {"httpx": mock_httpx_module}): + result = await fixture_fetch_action.execute( + fixture_action_context, + {"url": "https://example.com/long", "max_length": 200}, + ) + + assert "is_error" not in result + assert "[Content truncated]" in result["content"] + assert result["length"] <= 200 + len("\n\n[Content truncated]") diff --git a/packages/nvidia_nat_workspace/tests/test_workspace_actions.py b/packages/nvidia_nat_workspace/tests/test_workspace_actions.py new file mode 100644 index 0000000000..720b2e8d6e --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_workspace_actions.py @@ -0,0 +1,149 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tests for build_workspace_actions guardrail wiring.""" + +from __future__ import annotations + +from typing import Any +from unittest.mock import AsyncMock +from unittest.mock import MagicMock + +import pytest + +from nat.guardrails.workspace import WorkspaceGuardrail +from nat.guardrails.workspace import WorkspaceGuardrailViolation +from nat.plugins.workspace.workspace_actions import WorkspaceActionsConfig +from nat.plugins.workspace.workspace_actions import build_workspace_actions +from nat.workspace.types import TypeSchema +from nat.workspace.types import WorkspaceActionSchema + +# --------------------------------------------------------------------------- +# Helpers +# --------------------------------------------------------------------------- + + +class _BlockingGuardrail(WorkspaceGuardrail): + """Guardrail that blocks every action.""" + + name = "always-block" + + async def validate_action(self, action: Any) -> WorkspaceGuardrailViolation: + return WorkspaceGuardrailViolation( + guardrail_name=self.name, + message="Blocked by test guardrail.", + ) + + +def _make_mock_workspace(actions: list[WorkspaceActionSchema] | None = None, ) -> MagicMock: + """Return a MagicMock workspace with get_actions and guardrail tracking.""" + workspace = MagicMock() + workspace.get_actions = AsyncMock(return_value=actions or []) + workspace.add_workspace_guardrail = MagicMock() + return workspace + + +def _make_mock_builder( + workspace: MagicMock, + guardrails: list[WorkspaceGuardrail] | None = None, +) -> MagicMock: + """Return a MagicMock builder that yields the given workspace.""" + manager = MagicMock() + manager.__aenter__ = AsyncMock(return_value=workspace) + manager.__aexit__ = AsyncMock(return_value=None) + + builder = MagicMock() + builder.get_workspace_manager = AsyncMock(return_value=manager) + builder.get_workspace_guardrails = AsyncMock(return_value=guardrails or []) + return builder + + +# --------------------------------------------------------------------------- +# Tests +# --------------------------------------------------------------------------- + + +async def test_guardrails_added_to_workspace() -> None: + """build_workspace_actions calls add_workspace_guardrail for each guardrail.""" + guardrail = _BlockingGuardrail() + workspace = _make_mock_workspace() + builder = _make_mock_builder(workspace=workspace, guardrails=[guardrail]) + + async with build_workspace_actions(WorkspaceActionsConfig(), builder): + pass + + workspace.add_workspace_guardrail.assert_called_once_with(guardrail) + + +async def test_no_guardrails_skips_add() -> None: + """build_workspace_actions with empty guardrails list never calls add_workspace_guardrail.""" + workspace = _make_mock_workspace() + builder = _make_mock_builder(workspace=workspace, guardrails=[]) + + async with build_workspace_actions(WorkspaceActionsConfig(), builder): + pass + + workspace.add_workspace_guardrail.assert_not_called() + + +async def test_multiple_guardrails_all_added() -> None: + """All guardrails returned by get_workspace_guardrails are added.""" + + class _GuardrailA(WorkspaceGuardrail): + name = "guardrail-a" + + class _GuardrailB(WorkspaceGuardrail): + name = "guardrail-b" + + g_a, g_b = _GuardrailA(), _GuardrailB() + workspace = _make_mock_workspace() + builder = _make_mock_builder(workspace=workspace, guardrails=[g_a, g_b]) + + async with build_workspace_actions(WorkspaceActionsConfig(), builder): + pass + + assert workspace.add_workspace_guardrail.call_count == 2 + calls = {c.args[0] for c in workspace.add_workspace_guardrail.call_args_list} + assert g_a in calls + assert g_b in calls + + +async def test_no_workspace_raises() -> None: + """build_workspace_actions raises RuntimeError when no workspace is configured.""" + builder = MagicMock() + builder.get_workspace_manager = AsyncMock(return_value=None) + + with pytest.raises(RuntimeError, match="No workspace configured"): + async with build_workspace_actions(WorkspaceActionsConfig(), builder): + pass + + +async def test_actions_exposed_as_functions() -> None: + """Functions in the yielded group correspond to workspace actions.""" + actions = [ + WorkspaceActionSchema( + name="ping", + description="Ping the workspace", + parameters=[], + result=TypeSchema(type="string", description="Response"), + ), + ] + workspace = _make_mock_workspace(actions=actions) + builder = _make_mock_builder(workspace=workspace) + + async with build_workspace_actions(WorkspaceActionsConfig(), builder) as group: + functions = await group.get_accessible_functions() + + # Functions are namespaced by the group config name, e.g. "workspace_actions__ping" + assert any("ping" in key for key in functions) diff --git a/packages/nvidia_nat_workspace/tests/test_write_action.py b/packages/nvidia_nat_workspace/tests/test_write_action.py new file mode 100644 index 0000000000..d3bba0f3af --- /dev/null +++ b/packages/nvidia_nat_workspace/tests/test_write_action.py @@ -0,0 +1,109 @@ +# SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# SPDX-License-Identifier: Apache-2.0 +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from __future__ import annotations + +from pathlib import Path + +import pytest + +from nat.data_models.workspace import ActionContext +from nat.workspace_actions.workspace.file.write_action import WriteAction + + +@pytest.fixture(name="fixture_action_context") +def fixture_action_context(tmp_path: Path) -> ActionContext: + return ActionContext(session_id="test-session-write", root_path=tmp_path.resolve()) + + +@pytest.fixture(name="fixture_write_action") +def fixture_write_action() -> WriteAction: + return WriteAction() + + +async def test_write_creates_new_file( + fixture_action_context: ActionContext, + fixture_write_action: WriteAction, +) -> None: + """Write a new file and verify created=True.""" + file_path = fixture_action_context.root_path / "new_file.txt" + + result = await fixture_write_action.execute( + fixture_action_context, + {"file_path": str(file_path), "content": "hello world"}, + ) + + assert "is_error" not in result + assert result["created"] is True + assert result["bytes_written"] == len("hello world".encode("utf-8")) + assert file_path.read_text(encoding="utf-8") == "hello world" + + +async def test_write_overwrites_existing( + fixture_action_context: ActionContext, + fixture_write_action: WriteAction, +) -> None: + """Write a file twice; the second write should report created=False.""" + file_path = fixture_action_context.root_path / "overwrite.txt" + + result1 = await fixture_write_action.execute( + fixture_action_context, + {"file_path": str(file_path), "content": "first"}, + ) + assert result1["created"] is True + + result2 = await fixture_write_action.execute( + fixture_action_context, + {"file_path": str(file_path), "content": "second"}, + ) + assert result2["created"] is False + assert "is_error" not in result2 + assert file_path.read_text(encoding="utf-8") == "second" + + +async def test_write_auto_creates_dirs( + fixture_action_context: ActionContext, + fixture_write_action: WriteAction, +) -> None: + """Write to a nested path and verify parent directories are created.""" + file_path = fixture_action_context.root_path / "nested" / "path" / "file.txt" + + result = await fixture_write_action.execute( + fixture_action_context, + {"file_path": str(file_path), "content": "deep content"}, + ) + + assert "is_error" not in result + assert result["created"] is True + assert file_path.exists() + assert file_path.read_text(encoding="utf-8") == "deep content" + + +async def test_write_bytes_written( + fixture_action_context: ActionContext, + fixture_write_action: WriteAction, +) -> None: + """Verify bytes_written matches the UTF-8 encoded length of the content.""" + # Use a string with multi-byte characters to ensure UTF-8 encoding is used. + content = "hello \u00e9\u00e8\u00ea \u2603" # accented chars + snowman + file_path = fixture_action_context.root_path / "utf8_test.txt" + + result = await fixture_write_action.execute( + fixture_action_context, + {"file_path": str(file_path), "content": content}, + ) + + assert "is_error" not in result + expected_bytes = len(content.encode("utf-8")) + assert result["bytes_written"] == expected_bytes diff --git a/packages/nvidia_nat_workspace/uv.lock b/packages/nvidia_nat_workspace/uv.lock new file mode 100644 index 0000000000..c6f8874d29 --- /dev/null +++ b/packages/nvidia_nat_workspace/uv.lock @@ -0,0 +1,3027 @@ +version = 1 +revision = 3 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