Integrate RAG planning flow

.env.example

@@ -1,14 +1,42 @@
-AZURE_API_VERSION=xxxx
-AZURE_API_BASE=xxxx
-AZURE_API_KEY=xxx
-# LITELLM_PROXY_API_BASE=xxx
-# LITELLM_PROXY_API_KEY=xxxx
-# DEEPSEEK_API_KEY=xxxx
+# Azure
+AZURE_API_VERSION=2024-12-01-preview
+AZURE_API_BASE=https://your-azure-endpoint.openai.azure.com/
+AZURE_API_KEY=your-azure-api-key
 
+# Optional model provider keys
+DEEPSEEK_API_KEY=
+LITELLM_PROXY_API_BASE=http://litellm.example.com:4000
+LITELLM_PROXY_API_KEY=your-litellm-proxy-key
+GPT_KEY=your-gpt-key
+OPENAI_API_KEY=your-openai-api-key
+
+# Bohrium / Materials
+BOHRIUM_USER_ID=your-bohrium-user-id
+BOHRIUM_BASE_URL=https://openapi.test.dp.tech
+BOHRIUM_ACCESS_KEY=your-bohrium-access-key
+BOHRIUM_PROJECT_ID=your-bohrium-project-id
+MATERIALS_ACCESS_KEY=your-materials-access-key
+MATERIALS_PROJECT_ID=your-materials-project-id
+MATERIALS_SKU_ID=your-materials-sku-id
+
+# OPIK
+OPIK_URL_OVERRIDE=https://your-opik-url/api
+OPIK_WORKSPACE=default
 OPIK_PROJECT_NAME=test
-MATERIALS_ACCESS_KEY=xxxx
-MATERIALS_PROJECT_ID=xxxx
 
-OPENAI_API_KEY=sk-XX
-GPT_CHAT_MODEL=gpt-5-chat
-GPT_BASE_URL=xxx
+# Default model
+DEFAULT_MODEL=azure/gpt-5-chat
+# DEFAULT_MODEL=deepseek/deepseek-chat
+BOHRIUM_USE_SANDBOX=1
+
+# RAG plan-make (used by rag/settings.yaml and rag/plan_llm.py)
+PLAN_MAKE_MODEL=qwen3-vl-plus
+PLAN_MAKE_API_KEY=your-plan-make-api-key
+PLAN_MAKE_API_BASE=https://dashscope.aliyuncs.com/compatible-mode/v1
+
+# OSS
+OSS_ENABLED=true
+OSS_BUCKET_NAME=your-oss-bucket
+OSS_ACCESS_KEY_ID=your-oss-access-key-id
+OSS_ACCESS_KEY_SECRET=your-oss-access-key-secret
+OSS_ENDPOINT=https://oss-cn-zhangjiakou.aliyuncs.com

agents/matmaster_agent/core_agents/comp_agents/recommend_summary_agent/agent.py

@@ -54,6 +54,9 @@
     ToolConnectAgent,
 )
 from agents.matmaster_agent.flow_agents.model import PlanStepStatusEnum
+from agents.matmaster_agent.flow_agents.tool_name_utils import (
+    normalize_tool_name_to_canonical,
+)
 from agents.matmaster_agent.llm_config import MatMasterLlmConfig
 from agents.matmaster_agent.locales import i18n
 from agents.matmaster_agent.logger import PrefixFilter
@@ -209,7 +212,11 @@ async def _run_events(self, ctx: InvocationContext) -> AsyncGenerator[Event, Non
         if isinstance(tool_schema, str):
             tool_schema = tool_schema.replace('{', '[').replace('}', ']')
 
-        tool_args_recommend_prompt = ALL_TOOLS[current_step_tool_name].get(
+        canonical_tool = (
+            normalize_tool_name_to_canonical(current_step_tool_name)
+            or current_step_tool_name
+        )
+        tool_args_recommend_prompt = ALL_TOOLS.get(canonical_tool, {}).get(
             'args_setting', ''
         )
 
@@ -338,8 +345,12 @@ async def _run_events(self, ctx: InvocationContext) -> AsyncGenerator[Event, Non
         yield update_state_event(ctx, state_delta={'matmaster_flow_active': None})
 
         # TODO: needs a better way to handle customized summary prompt
-        if ALL_TOOLS[current_step_tool_name].get('summary_prompt') is not None:
-            custom_prompt = ALL_TOOLS[current_step_tool_name].get('summary_prompt')
+        canonical_tool = (
+            normalize_tool_name_to_canonical(current_step_tool_name)
+            or current_step_tool_name
+        )
+        if ALL_TOOLS.get(canonical_tool, {}).get('summary_prompt') is not None:
+            custom_prompt = ALL_TOOLS[canonical_tool].get('summary_prompt')
             self.summary_agent.instruction = (
                 f"{custom_prompt}\n\n{get_vocabulary_enforce_prompt()}"
             )