_create_llm_run() — langchain Function Reference

Architecture documentation for the _create_llm_run() function in core.py from the langchain codebase.

Function python Observability Tracers

Entity Profile

Observability→ Tracers→ _create_llm_run() — langchain Function Reference

Dependency Diagram

graph TD
  c8ce297d_cd94_91e0_ec5e_a8c75391127b["_create_llm_run()"]
  70348e44_de0f_ccb4_c06a_8453289ed93e["_TracerCore"]
  c8ce297d_cd94_91e0_ec5e_a8c75391127b -->|defined in| 70348e44_de0f_ccb4_c06a_8453289ed93e
  style c8ce297d_cd94_91e0_ec5e_a8c75391127b fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/langchain_core/tracers/core.py lines 195–222

    def _create_llm_run(
        self,
        serialized: dict[str, Any],
        prompts: list[str],
        run_id: UUID,
        tags: list[str] | None = None,
        parent_run_id: UUID | None = None,
        metadata: dict[str, Any] | None = None,
        name: str | None = None,
        **kwargs: Any,
    ) -> Run:
        """Create a llm run."""
        start_time = datetime.now(timezone.utc)
        if metadata:
            kwargs.update({"metadata": metadata})
        return Run(
            id=run_id,
            parent_run_id=parent_run_id,
            serialized=serialized,
            # TODO: Figure out how to expose kwargs here
            inputs={"prompts": prompts},
            extra=kwargs,
            events=[{"name": "start", "time": start_time}],
            start_time=start_time,
            run_type="llm",
            tags=tags or [],
            name=name,
        )