feat: preserve logprobs from chat completions API in ModelResponse

src/agents/models/chatcmpl_helpers.py

@@ -3,6 +3,12 @@
 from contextvars import ContextVar
 
 from openai import AsyncOpenAI
+from openai.types.chat.chat_completion_token_logprob import ChatCompletionTokenLogprob
+from openai.types.responses.response_output_text import Logprob, LogprobTopLogprob
+from openai.types.responses.response_text_delta_event import (
+    Logprob as DeltaLogprob,
+    LogprobTopLogprob as DeltaTopLogprob,
+)
 
 from ..model_settings import ModelSettings
 from ..version import __version__
@@ -41,3 +47,54 @@ def get_stream_options_param(
         )
         stream_options = {"include_usage": include_usage} if include_usage is not None else None
         return stream_options
+
+    @classmethod
+    def convert_logprobs_for_output_text(
+        cls, logprobs: list[ChatCompletionTokenLogprob] | None
+    ) -> list[Logprob] | None:
+        if not logprobs:
+            return None
+
+        converted: list[Logprob] = []
+        for token_logprob in logprobs:
+            converted.append(
+                Logprob(
+                    token=token_logprob.token,
+                    logprob=token_logprob.logprob,
+                    bytes=token_logprob.bytes or [],
+                    top_logprobs=[
+                        LogprobTopLogprob(
+                            token=top_logprob.token,
+                            logprob=top_logprob.logprob,
+                            bytes=top_logprob.bytes or [],
+                        )
+                        for top_logprob in token_logprob.top_logprobs
+                    ],
+                )
+            )
+        return converted
+
+    @classmethod
+    def convert_logprobs_for_text_delta(
+        cls, logprobs: list[ChatCompletionTokenLogprob] | None
+    ) -> list[DeltaLogprob] | None:
+        if not logprobs:
+            return None
+
+        converted: list[DeltaLogprob] = []
+        for token_logprob in logprobs:
+            converted.append(
+                DeltaLogprob(
+                    token=token_logprob.token,
+                    logprob=token_logprob.logprob,
+                    top_logprobs=[
+                        DeltaTopLogprob(
+                            token=top_logprob.token,
+                            logprob=top_logprob.logprob,
+                        )
+                        for top_logprob in token_logprob.top_logprobs
+                    ]
+                    or None,
+                )
+            )
+        return converted

src/agents/models/chatcmpl_stream_handler.py

@@ -42,6 +42,7 @@
 from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
 
 from ..items import TResponseStreamEvent
+from .chatcmpl_helpers import ChatCmplHelpers
 from .fake_id import FAKE_RESPONSES_ID
 
 
@@ -105,6 +106,7 @@ async def handle_stream(
                 continue
 
             delta = chunk.choices[0].delta
+            choice_logprobs = chunk.choices[0].logprobs
 
             # Handle thinking blocks from Anthropic (for preserving signatures)
             if hasattr(delta, "thinking_blocks") and delta.thinking_blocks:
@@ -266,6 +268,15 @@ async def handle_stream(
                         type="response.content_part.added",
                         sequence_number=sequence_number.get_and_increment(),
                     )
+                delta_logprobs = (
+                    ChatCmplHelpers.convert_logprobs_for_text_delta(
+                        choice_logprobs.content if choice_logprobs else None
+                    )
+                    or []
+                )
+                output_logprobs = ChatCmplHelpers.convert_logprobs_for_output_text(
+                    choice_logprobs.content if choice_logprobs else None
+                )
                 # Emit the delta for this segment of content
                 yield ResponseTextDeltaEvent(
                     content_index=state.text_content_index_and_output[0],
@@ -275,10 +286,15 @@ async def handle_stream(
                     is not None,  # fixed 0 -> 0 or 1
                     type="response.output_text.delta",
                     sequence_number=sequence_number.get_and_increment(),
-                    logprobs=[],
+                    logprobs=delta_logprobs,
                 )
                 # Accumulate the text into the response part
                 state.text_content_index_and_output[1].text += delta.content
+                if output_logprobs:
+                    existing_logprobs = state.text_content_index_and_output[1].logprobs or []
+                    state.text_content_index_and_output[1].logprobs = (
+                        existing_logprobs + output_logprobs
+                    )
 
             # Handle refusals (model declines to answer)
             # This is always set by the OpenAI API, but not by others e.g. LiteLLM

src/agents/models/openai_chatcompletions.py

@@ -9,7 +9,13 @@
 from openai.types import ChatModel
 from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessage
 from openai.types.chat.chat_completion import Choice
-from openai.types.responses import Response
+from openai.types.responses import (
+    Response,
+    ResponseOutputItem,
+    ResponseOutputMessage,
+    ResponseOutputText,
+)
+from openai.types.responses.response_output_text import Logprob
 from openai.types.responses.response_prompt_param import ResponsePromptParam
 
 from .. import _debug
@@ -119,12 +125,33 @@ async def get_response(
 
             items = Converter.message_to_output_items(message) if message is not None else []
 
+            logprob_models = None
+            if first_choice and first_choice.logprobs and first_choice.logprobs.content:
+                logprob_models = ChatCmplHelpers.convert_logprobs_for_output_text(
+                    first_choice.logprobs.content
+                )
+
+            if logprob_models:
+                self._attach_logprobs_to_output(items, logprob_models)
+
             return ModelResponse(
                 output=items,
                 usage=usage,
                 response_id=None,
             )
 
+    def _attach_logprobs_to_output(
+        self, output_items: list[ResponseOutputItem], logprobs: list[Logprob]
+    ) -> None:
+        for output_item in output_items:
+            if not isinstance(output_item, ResponseOutputMessage):
+                continue
+
+            for content in output_item.content:
+                if isinstance(content, ResponseOutputText):
+                    content.logprobs = logprobs
+                    return
+
     async def stream_response(
         self,
         system_instructions: str | None,

tests/test_openai_chatcompletions.py

@@ -6,13 +6,17 @@
 import httpx
 import pytest
 from openai import AsyncOpenAI, omit
-from openai.types.chat.chat_completion import ChatCompletion, Choice
+from openai.types.chat.chat_completion import ChatCompletion, Choice, ChoiceLogprobs
 from openai.types.chat.chat_completion_chunk import ChatCompletionChunk
 from openai.types.chat.chat_completion_message import ChatCompletionMessage
 from openai.types.chat.chat_completion_message_tool_call import (  # type: ignore[attr-defined]
     ChatCompletionMessageFunctionToolCall,
     Function,
 )
+from openai.types.chat.chat_completion_token_logprob import (
+    ChatCompletionTokenLogprob,
+    TopLogprob,
+)
 from openai.types.completion_usage import (
     CompletionUsage,
     PromptTokensDetails,
@@ -98,6 +102,65 @@ async def patched_fetch_response(self, *args, **kwargs):
     assert resp.response_id is None
 
 
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_get_response_attaches_logprobs(monkeypatch) -> None:
+    msg = ChatCompletionMessage(role="assistant", content="Hi!")
+    choice = Choice(
+        index=0,
+        finish_reason="stop",
+        message=msg,
+        logprobs=ChoiceLogprobs(
+            content=[
+                ChatCompletionTokenLogprob(
+                    token="Hi",
+                    logprob=-0.5,
+                    bytes=[1],
+                    top_logprobs=[TopLogprob(token="Hi", logprob=-0.5, bytes=[1])],
+                ),
+                ChatCompletionTokenLogprob(
+                    token="!",
+                    logprob=-0.1,
+                    bytes=[2],
+                    top_logprobs=[TopLogprob(token="!", logprob=-0.1, bytes=[2])],
+                ),
+            ]
+        ),
+    )
+    chat = ChatCompletion(
+        id="resp-id",
+        created=0,
+        model="fake",
+        object="chat.completion",
+        choices=[choice],
+        usage=None,
+    )
+
+    async def patched_fetch_response(self, *args, **kwargs):
+        return chat
+
+    monkeypatch.setattr(OpenAIChatCompletionsModel, "_fetch_response", patched_fetch_response)
+    model = OpenAIProvider(use_responses=False).get_model("gpt-4")
+    resp: ModelResponse = await model.get_response(
+        system_instructions=None,
+        input="",
+        model_settings=ModelSettings(),
+        tools=[],
+        output_schema=None,
+        handoffs=[],
+        tracing=ModelTracing.DISABLED,
+        previous_response_id=None,
+        conversation_id=None,
+        prompt=None,
+    )
+    assert len(resp.output) == 1
+    assert isinstance(resp.output[0], ResponseOutputMessage)
+    text_part = resp.output[0].content[0]
+    assert isinstance(text_part, ResponseOutputText)
+    assert text_part.logprobs is not None
+    assert [lp.token for lp in text_part.logprobs] == ["Hi", "!"]
+
+
 @pytest.mark.allow_call_model_methods
 @pytest.mark.asyncio
 async def test_get_response_with_refusal(monkeypatch) -> None:

tests/test_openai_chatcompletions_stream.py

@@ -7,6 +7,11 @@
     ChoiceDelta,
     ChoiceDeltaToolCall,
     ChoiceDeltaToolCallFunction,
+    ChoiceLogprobs,
+)
+from openai.types.chat.chat_completion_token_logprob import (
+    ChatCompletionTokenLogprob,
+    TopLogprob,
 )
 from openai.types.completion_usage import (
     CompletionTokensDetails,
@@ -15,6 +20,7 @@
 )
 from openai.types.responses import (
     Response,
+    ResponseCompletedEvent,
     ResponseFunctionToolCall,
     ResponseOutputMessage,
     ResponseOutputRefusal,
@@ -128,6 +134,113 @@ async def patched_fetch_response(self, *args, **kwargs):
     assert completed_resp.usage.output_tokens_details.reasoning_tokens == 3
 
 
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_stream_response_includes_logprobs(monkeypatch) -> None:
+    chunk1 = ChatCompletionChunk(
+        id="chunk-id",
+        created=1,
+        model="fake",
+        object="chat.completion.chunk",
+        choices=[
+            Choice(
+                index=0,
+                delta=ChoiceDelta(content="Hi"),
+                logprobs=ChoiceLogprobs(
+                    content=[
+                        ChatCompletionTokenLogprob(
+                            token="Hi",
+                            logprob=-0.5,
+                            bytes=[1],
+                            top_logprobs=[TopLogprob(token="Hi", logprob=-0.5, bytes=[1])],
+                        )
+                    ]
+                ),
+            )
+        ],
+    )
+    chunk2 = ChatCompletionChunk(
+        id="chunk-id",
+        created=1,
+        model="fake",
+        object="chat.completion.chunk",
+        choices=[
+            Choice(
+                index=0,
+                delta=ChoiceDelta(content=" there"),
+                logprobs=ChoiceLogprobs(
+                    content=[
+                        ChatCompletionTokenLogprob(
+                            token=" there",
+                            logprob=-0.25,
+                            bytes=[2],
+                            top_logprobs=[TopLogprob(token=" there", logprob=-0.25, bytes=[2])],
+                        )
+                    ]
+                ),
+            )
+        ],
+        usage=CompletionUsage(
+            completion_tokens=5,
+            prompt_tokens=7,
+            total_tokens=12,
+            prompt_tokens_details=PromptTokensDetails(cached_tokens=2),
+            completion_tokens_details=CompletionTokensDetails(reasoning_tokens=3),
+        ),
+    )
+
+    async def fake_stream() -> AsyncIterator[ChatCompletionChunk]:
+        for c in (chunk1, chunk2):
+            yield c
+
+    async def patched_fetch_response(self, *args, **kwargs):
+        resp = Response(
+            id="resp-id",
+            created_at=0,
+            model="fake-model",
+            object="response",
+            output=[],
+            tool_choice="none",
+            tools=[],
+            parallel_tool_calls=False,
+        )
+        return resp, fake_stream()
+
+    monkeypatch.setattr(OpenAIChatCompletionsModel, "_fetch_response", patched_fetch_response)
+    model = OpenAIProvider(use_responses=False).get_model("gpt-4")
+    output_events = []
+    async for event in model.stream_response(
+        system_instructions=None,
+        input="",
+        model_settings=ModelSettings(),
+        tools=[],
+        output_schema=None,
+        handoffs=[],
+        tracing=ModelTracing.DISABLED,
+        previous_response_id=None,
+        conversation_id=None,
+        prompt=None,
+    ):
+        output_events.append(event)
+
+    text_delta_events = [
+        event for event in output_events if event.type == "response.output_text.delta"
+    ]
+    assert len(text_delta_events) == 2
+    assert [lp.token for lp in text_delta_events[0].logprobs] == ["Hi"]
+    assert [lp.token for lp in text_delta_events[1].logprobs] == [" there"]
+
+    completed_event = next(event for event in output_events if event.type == "response.completed")
+    assert isinstance(completed_event, ResponseCompletedEvent)
+    completed_resp = completed_event.response
+    assert isinstance(completed_resp.output[0], ResponseOutputMessage)
+    text_part = completed_resp.output[0].content[0]
+    assert isinstance(text_part, ResponseOutputText)
+    assert text_part.text == "Hi there"
+    assert text_part.logprobs is not None
+    assert [lp.token for lp in text_part.logprobs] == ["Hi", " there"]
+
+
 @pytest.mark.allow_call_model_methods
 @pytest.mark.asyncio
 async def test_stream_response_yields_events_for_refusal_content(monkeypatch) -> None: