feat: Add id and finish_reason to ModelResponse

Author: fatelei

pydantic_ai_slim/pydantic_ai/messages.py

@@ -792,6 +792,13 @@ class ModelResponse:
     vendor_id: str | None = None
     """Vendor ID as specified by the model provider. This can be used to track the specific request to the model."""
 
+    id: str | None = None
+    """Unique identifier for the model response, e.g. as returned by the model provider (OpenAI, etc)."""
+
+    finish_reason: str | None = None
+    """The reason the model finished generating this response, e.g. 'stop', 'length', etc."""
+
+
     def otel_events(self, settings: InstrumentationSettings) -> list[Event]:
         """Return OpenTelemetry events for the response."""
         result: list[Event] = []

pydantic_ai_slim/pydantic_ai/models/function.py

@@ -137,6 +137,8 @@ async def request(
         if not response.usage.has_values():  # pragma: no branch
             response.usage = _estimate_usage(chain(messages, [response]))
             response.usage.requests = 1
+        response.id = getattr(response, 'id', None)
+        response.finish_reason = getattr(response, 'finish_reason', None)
         return response
 
     @asynccontextmanager

pydantic_ai_slim/pydantic_ai/models/openai.py

@@ -420,6 +420,8 @@ def _process_response(self, response: chat.ChatCompletion | str) -> ModelRespons
             timestamp=timestamp,
             vendor_details=vendor_details,
             vendor_id=response.id,
+            id=response.id,
+            finish_reason=choice.finish_reason,
         )
 
     async def _process_streamed_response(self, response: AsyncStream[ChatCompletionChunk]) -> OpenAIStreamedResponse:

pydantic_ai_slim/pydantic_ai/models/test.py

@@ -227,23 +227,41 @@ def _request(
                                 output[part.tool_name] = part.content
                 if output:
                     return ModelResponse(
-                        parts=[TextPart(pydantic_core.to_json(output).decode())], model_name=self._model_name
+                        parts=[TextPart(pydantic_core.to_json(output).decode())],
+                        model_name=self._model_name,
+                        id=None,
+                        finish_reason=None,
                     )
                 else:
-                    return ModelResponse(parts=[TextPart('success (no tool calls)')], model_name=self._model_name)
+                    return ModelResponse(
+                        parts=[TextPart('success (no tool calls)')], model_name=self._model_name, id=None, finish_reason=None
+                    )
             else:
-                return ModelResponse(parts=[TextPart(response_text)], model_name=self._model_name)
+                return ModelResponse(
+                    parts=[TextPart(response_text)],
+                    model_name=self._model_name,
+                    id=None,
+                    finish_reason=None,
+                )
         else:
             assert output_tools, 'No output tools provided'
             custom_output_args = output_wrapper.value
             output_tool = output_tools[self.seed % len(output_tools)]
             if custom_output_args is not None:
                 return ModelResponse(
-                    parts=[ToolCallPart(output_tool.name, custom_output_args)], model_name=self._model_name
+                    parts=[ToolCallPart(output_tool.name, custom_output_args)],
+                    model_name=self._model_name,
+                    id=None,
+                    finish_reason=None,
                 )
             else:
                 response_args = self.gen_tool_args(output_tool)
-                return ModelResponse(parts=[ToolCallPart(output_tool.name, response_args)], model_name=self._model_name)
+                return ModelResponse(
+                    parts=[ToolCallPart(output_tool.name, response_args)],
+                    model_name=self._model_name,
+                    id=None,
+                    finish_reason=None,
+                )
 
 
 @dataclass