LCORE-2311: Fix Skills

src/pydantic_ai_lightspeed/llamastack/_model.py

@@ -26,7 +26,7 @@
 from pydantic_ai import UnexpectedModelBehavior
 from pydantic_ai._run_context import RunContext
 from pydantic_ai._utils import PeekableAsyncStream, Unset, number_to_datetime
-from pydantic_ai.messages import ModelMessage
+from pydantic_ai.messages import ModelMessage, ModelResponse
 from pydantic_ai.models import (
     ModelRequestParameters,
     StreamedResponse,
@@ -181,15 +181,79 @@ class LlamaStackResponsesModel(OpenAIResponsesModel):
     before the corresponding ``McpCall`` or ``ResponseFunctionToolCall`` item.
     """
 
+    async def request(  # pylint: disable=unused-argument
+        self,
+        messages: list[ModelMessage],
+        model_settings: ModelSettings | None,
+        model_request_parameters: ModelRequestParameters,
+        run_context: RunContext[Any] | None = None,
+    ) -> Any:
+        """Non-streaming request with Llama Stack conversation continuation fix.
+
+        Llama Stack rejects requests containing both ``conversation`` and
+        ``previous_response_id``.  On continuation turns (where a prior
+        ``ModelResponse`` exists), we trim messages to only the new input and
+        disable ``previous_response_id`` so that only ``conversation`` is sent.
+        This ensures all responses are persisted to the conversation.
+        """
+        messages, model_settings = self._prepare_conversation_continuation(
+            messages, model_settings
+        )
+        return await super().request(messages, model_settings, model_request_parameters)
+
+    def _prepare_conversation_continuation(
+        self,
+        messages: list[ModelMessage],
+        model_settings: ModelSettings | None,
+    ) -> tuple[list[ModelMessage], ModelSettings | None]:
+        """Trim messages and disable previous_response_id for conversation continuations.
+
+        Llama Stack rejects requests with both ``previous_response_id`` and
+        ``conversation``. When ``conversation`` is in ``extra_body`` and there's
+        already a ModelResponse in the history (a continuation turn), we:
+
+        1. Trim messages to only those AFTER the last ModelResponse (new input only)
+        2. Disable ``openai_previous_response_id`` so pydantic-ai won't resolve one
+
+        This means Llama Stack receives ``conversation`` (for persistence) plus only
+        the new input items. Llama Stack reconstructs prior history from the
+        conversation and appends the new input correctly.
+        """
+        if not model_settings or not isinstance(model_settings, dict):
+            return messages, model_settings
+
+        extra_body = model_settings.get("extra_body")
+        if not isinstance(extra_body, dict) or "conversation" not in extra_body:
+            return messages, model_settings
+
+        last_response_idx = None
+        for i in range(len(messages) - 1, -1, -1):
+            msg = messages[i]
+            if isinstance(msg, ModelResponse) and msg.provider_response_id:
+                last_response_idx = i
+                break
+
+        if last_response_idx is None:
+            return messages, model_settings
+
+        trimmed_messages = messages[last_response_idx + 1 :]
+
+        new_settings = dict(model_settings)
+        new_settings.pop("openai_previous_response_id", None)
+        return trimmed_messages, cast(ModelSettings, new_settings)
+
     @asynccontextmanager
-    async def request_stream(
+    async def request_stream(  # pylint: disable=unused-argument
         self,
         messages: list[ModelMessage],
         model_settings: ModelSettings | None,
         model_request_parameters: ModelRequestParameters,
         run_context: RunContext[Any] | None = None,
     ) -> AsyncIterator[StreamedResponse]:
-        """Request a streaming response, filtering Llama Stack-specific event quirks.
+        """Request a streaming response with Llama Stack compatibility fixes.
+
+        Applies the same conversation continuation handling as :meth:`request`
+        before calling the Responses API, then filters streaming tool-call events.
 
         Args:
             messages: Model messages for the request.
@@ -201,10 +265,10 @@ async def request_stream(
             A StreamedResponse with the filtered event stream.
         """
         check_allow_model_requests()
-        model_settings, model_request_parameters = self.prepare_request(
-            model_settings,
-            model_request_parameters,
+        messages, model_settings = self._prepare_conversation_continuation(
+            messages, model_settings
         )
+
         model_settings_cast = cast(OpenAIResponsesModelSettings, model_settings or {})
         response = await self._responses_create(
             messages, True, model_settings_cast, model_request_parameters

src/utils/agents/streaming.py

@@ -221,12 +221,29 @@ async def generate_agent_response(
         context.query_request.conversation_id is None
         and bool(context.query_request.generate_topic_summary)
     )
-    topic_summary = await maybe_get_topic_summary(
-        generate_topic_summary=should_generate_topic_summary,
-        input_text=context.query_request.query,
-        client=context.client,
-        model_id=responses_params.model,
-    )
+    try:
+        topic_summary = await maybe_get_topic_summary(
+            generate_topic_summary=should_generate_topic_summary,
+            input_text=context.query_request.query,
+            client=context.client,
+            model_id=responses_params.model,
+        )
+    except HTTPException as exc:
+        logger.warning(
+            "Topic summary failed for request %s: %s",
+            context.request_id,
+            exc.detail,
+        )
+        detail: dict[str, str] = exc.detail if isinstance(exc.detail, dict) else {}
+        yield serialize_event(
+            ErrorStreamPayload.create(
+                status_code=exc.status_code,
+                response=detail.get("response", "Internal server error"),
+                cause=detail.get("cause", str(exc.detail)),
+            ),
+            media_type,
+        )
+        return
     logger.info("Consuming tokens")
     consume_query_tokens(
         user_id=context.user_id,

src/utils/pydantic_ai.py

@@ -21,7 +21,6 @@
     {
         "conversation",
         "max_infer_iters",
-        "tools",
         "tool_choice",
         "include",
         "text",
@@ -68,6 +67,8 @@ def _model_settings_from_responses_params(
     if responses_params.extra_headers:
         settings_dict["extra_headers"] = dict(responses_params.extra_headers)
     settings_dict["openai_store"] = responses_params.store
+    if responses_params.tools is not None:
+        settings_dict["openai_native_tools"] = responses_params.tools
     if responses_params.previous_response_id is not None:
         settings_dict["openai_previous_response_id"] = (
             responses_params.previous_response_id

src/utils/query.py

@@ -574,10 +574,9 @@ def handle_known_apistatus_errors(
     Returns:
         AbstractErrorResponse: The error response model.
     """
-    if error.status_code == 400:
-        error_message = getattr(error, "message", str(error))
-        if is_context_length_error(error_message):
-            return PromptTooLongResponse(model=model_id)
-    elif error.status_code == 429:
+    error_message = getattr(error, "message", str(error))
+    if is_context_length_error(error_message):
+        return PromptTooLongResponse(model=model_id)
+    if error.status_code == 429:
         return QuotaExceededResponse.model(model_id)
     return InternalServerErrorResponse.generic()

tests/unit/utils/test_pydantic_ai.py

@@ -82,6 +82,7 @@ def minimal_params_fixture(self, mocker: MockerFixture) -> object:
         params.parallel_tool_calls = None
         params.extra_headers = None
         params.store = False
+        params.tools = None
         params.previous_response_id = None
         return params
 
@@ -138,7 +139,6 @@ def test_extra_body_from_lls_fields(self, mocker: MockerFixture) -> None:
             "model": "test/model",
             "conversation": "conv-123",
             "max_infer_iters": 5,
-            "tools": [{"type": "function"}],
             "tool_choice": "auto",
         }
         params.max_output_tokens = None
@@ -147,14 +147,15 @@ def test_extra_body_from_lls_fields(self, mocker: MockerFixture) -> None:
         params.extra_headers = None
         params.store = False
         params.previous_response_id = None
+        params.tools = [{"type": "function"}]
 
         settings = _model_settings_from_responses_params(params)
 
         assert "extra_body" in settings
         assert settings["extra_body"]["conversation"] == "conv-123"
         assert settings["extra_body"]["max_infer_iters"] == 5
-        assert settings["extra_body"]["tools"] == [{"type": "function"}]
         assert settings["extra_body"]["tool_choice"] == "auto"
+        assert settings["openai_native_tools"] == [{"type": "function"}]
 
     def test_extra_body_only_includes_known_fields(self, mocker: MockerFixture) -> None:
         """Test that extra_body only includes fields in _LLS_RESPONSES_EXTRA_FIELDS."""
@@ -189,7 +190,6 @@ def test_contains_expected_fields(self) -> None:
         expected = {
             "conversation",
             "max_infer_iters",
-            "tools",
             "tool_choice",
             "include",
             "text",