AsyncBaseTracer Class — langchain Architecture

Source Code

libs/core/langchain_core/tracers/base.py lines 531–918

class AsyncBaseTracer(_TracerCore, AsyncCallbackHandler, ABC):
    """Async base interface for tracers."""

    @abstractmethod
    @override
    async def _persist_run(self, run: Run) -> None:
        """Persist a run."""

    @override
    async def _start_trace(self, run: Run) -> None:
        """Start a trace for a run.

        Starting a trace will run concurrently with each `_on_[run_type]_start` method.
        No `_on_[run_type]_start` callback should depend on operations in
        `_start_trace`.
        """
        super()._start_trace(run)
        await self._on_run_create(run)

    @override
    async def _end_trace(self, run: Run) -> None:
        """End a trace for a run.

        Ending a trace will run concurrently with each `_on_[run_type]_end` method.
        No `_on_[run_type]_end` callback should depend on operations in `_end_trace`.
        """
        if not run.parent_run_id:
            await self._persist_run(run)
        self.run_map.pop(str(run.id))
        await self._on_run_update(run)

    @override
    async def on_chat_model_start(
        self,
        serialized: dict[str, Any],
        messages: list[list[BaseMessage]],
        *,
        run_id: UUID,
        parent_run_id: UUID | None = None,
        tags: list[str] | None = None,
        metadata: dict[str, Any] | None = None,
        name: str | None = None,
        **kwargs: Any,
    ) -> Any:
        chat_model_run = self._create_chat_model_run(
            serialized=serialized,
            messages=messages,
            run_id=run_id,
            parent_run_id=parent_run_id,
            tags=tags,
            metadata=metadata,
            name=name,
            **kwargs,
        )
        tasks = [
            self._start_trace(chat_model_run),
            self._on_chat_model_start(chat_model_run),
        ]
        await asyncio.gather(*tasks)
        return chat_model_run

    @override
    async def on_llm_start(
        self,
        serialized: dict[str, Any],
        prompts: list[str],
        *,
        run_id: UUID,
        parent_run_id: UUID | None = None,
        tags: list[str] | None = None,
        metadata: dict[str, Any] | None = None,
        **kwargs: Any,
    ) -> None:
        llm_run = self._create_llm_run(
            serialized=serialized,
            prompts=prompts,
            run_id=run_id,
            parent_run_id=parent_run_id,
            tags=tags,
            metadata=metadata,
            **kwargs,