test_search_result_tool_message() — langchain Function Reference

Source Code

libs/partners/anthropic/tests/integration_tests/test_chat_models.py lines 1925–1980

def test_search_result_tool_message() -> None:
    """Test that we can pass a search result tool message to the model."""
    llm = ChatAnthropic(
        model=MODEL_NAME,  # type: ignore[call-arg]
    )

    @tool
    def retrieval_tool(query: str) -> list[dict]:
        """Retrieve information from a knowledge base."""
        return [
            {
                "type": "search_result",
                "title": "Leave policy",
                "source": "HR Leave Policy 2025",
                "citations": {"enabled": True},
                "content": [
                    {
                        "type": "text",
                        "text": (
                            "To request vacation days, submit a leave request form "
                            "through the HR portal. Approval will be sent by email."
                        ),
                    },
                ],
            },
        ]

    tool_call = {
        "type": "tool_call",
        "name": "retrieval_tool",
        "args": {"query": "vacation days request process"},
        "id": "toolu_abc123",
    }

    tool_message = retrieval_tool.invoke(tool_call)
    assert isinstance(tool_message, ToolMessage)
    assert isinstance(tool_message.content, list)

    messages = [
        HumanMessage("How do I request vacation days?"),
        AIMessage(
            [{"type": "text", "text": "Let me look that up for you."}],
            tool_calls=[tool_call],
        ),
        tool_message,
    ]

    result = llm.invoke(messages)
    assert isinstance(result, AIMessage)
    assert isinstance(result.content, list)
    assert any("citations" in block for block in result.content)

    assert (
        _convert_from_v1_to_anthropic(result.content_blocks, [], "anthropic")
        == result.content
    )