test_automatic_metadata.py — langchain Source File

Source Code

"""Test automatic tool call count storage in tracers."""

from __future__ import annotations

from unittest.mock import MagicMock

from langchain_core.messages import AIMessage
from langchain_core.messages.tool import ToolCall
from langchain_core.outputs import ChatGeneration, LLMResult
from langchain_core.tracers.core import _TracerCore
from langchain_core.tracers.schemas import Run


class MockTracerCore(_TracerCore):
    """Mock tracer core for testing LLM run completion."""

    def __init__(self) -> None:
        super().__init__()

    def _persist_run(self, run: Run) -> None:
        """Mock implementation of _persist_run."""


def test_complete_llm_run_automatically_stores_tool_call_count() -> None:
    """Test that `_complete_llm_run` automatically stores tool call count."""
    tracer = MockTracerCore()

    run = MagicMock(spec=Run)
    run.id = "test-llm-run-id"
    run.run_type = "llm"
    run.extra = {}
    run.outputs = {}
    run.events = []
    run.end_time = None
    run.inputs = {}

    tracer.run_map[str(run.id)] = run

    tool_calls = [
        ToolCall(name="search", args={"query": "test"}, id="call_1"),
        ToolCall(name="calculator", args={"expression": "2+2"}, id="call_2"),
    ]
    message = AIMessage(content="Test", tool_calls=tool_calls)
    generation = ChatGeneration(message=message)
    response = LLMResult(generations=[[generation]])

    # Complete the LLM run (this should trigger automatic metadata storage)
    completed_run = tracer._complete_llm_run(response=response, run_id=run.id)

    assert "tool_call_count" in completed_run.extra
    assert completed_run.extra["tool_call_count"] == 2


def test_complete_llm_run_handles_no_tool_calls() -> None:
    """Test that `_complete_llm_run` handles runs with no tool calls gracefully."""
    tracer = MockTracerCore()

    run = MagicMock(spec=Run)
    run.id = "test-llm-run-id-no-tools"
    run.run_type = "llm"
// ... (96 more lines)