test_glm4_stream() — langchain Function Reference

Architecture documentation for the test_glm4_stream() function in test_base.py from the langchain codebase.

Function python LangChainCore LanguageModelBase

Entity Profile

LangChainCore→ LanguageModelBase→ test_glm4_stream() — langchain Function Reference

Dependency Diagram

graph TD
  705f8a06_8729_723d_8671_5fccaa4c59f5["test_glm4_stream()"]
  48232d20_f8c1_b597_14fa_7dc407e9bfe5["test_base.py"]
  705f8a06_8729_723d_8671_5fccaa4c59f5 -->|defined in| 48232d20_f8c1_b597_14fa_7dc407e9bfe5
  style 705f8a06_8729_723d_8671_5fccaa4c59f5 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/openai/tests/unit_tests/chat_models/test_base.py lines 421–443

def test_glm4_stream(mock_glm4_completion: list) -> None:
    llm_name = "glm-4"
    llm = ChatOpenAI(model=llm_name, stream_usage=True)
    mock_client = MagicMock()

    def mock_create(*args: Any, **kwargs: Any) -> MockSyncContextManager:
        return MockSyncContextManager(mock_glm4_completion)

    mock_client.create = mock_create
    usage_chunk = mock_glm4_completion[-1]

    usage_metadata: UsageMetadata | None = None
    with patch.object(llm, "client", mock_client):
        for chunk in llm.stream("你的名字叫什么？只回答名字"):
            assert isinstance(chunk, AIMessageChunk)
            if chunk.usage_metadata is not None:
                usage_metadata = chunk.usage_metadata

    assert usage_metadata is not None

    assert usage_metadata["input_tokens"] == usage_chunk["usage"]["prompt_tokens"]
    assert usage_metadata["output_tokens"] == usage_chunk["usage"]["completion_tokens"]
    assert usage_metadata["total_tokens"] == usage_chunk["usage"]["total_tokens"]