test_openai_invoke() — langchain Function Reference

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

Function python LangChainCore LanguageModelBase

Entity Profile

LangChainCore→ LanguageModelBase→ test_openai_invoke() — langchain Function Reference

Dependency Diagram

graph TD
  cc72042c_65fd_5078_8d1f_33b07260a3e9["test_openai_invoke()"]
  bd382a4e_442c_13ae_530c_6e34bc43623d["test_base.py"]
  cc72042c_65fd_5078_8d1f_33b07260a3e9 -->|defined in| bd382a4e_442c_13ae_530c_6e34bc43623d
  style cc72042c_65fd_5078_8d1f_33b07260a3e9 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/openai/tests/integration_tests/chat_models/test_base.py lines 234–263

def test_openai_invoke() -> None:
    """Test invoke tokens from ChatOpenAI."""
    llm = ChatOpenAI(
        model="gpt-5-nano",
        service_tier="flex",  # Also test service_tier
        max_retries=3,  # Add retries for 503 capacity errors
    )

    result = llm.invoke("Hello", config={"tags": ["foo"]})
    assert isinstance(result.content, str)

    usage_metadata = result.usage_metadata  # type: ignore[attr-defined]

    # assert no response headers if include_response_headers is not set
    assert "headers" not in result.response_metadata
    assert usage_metadata is not None
    flex_input = usage_metadata.get("input_token_details", {}).get("flex")
    assert isinstance(flex_input, int)
    assert flex_input > 0
    assert flex_input == usage_metadata.get("input_tokens")
    flex_output = usage_metadata.get("output_token_details", {}).get("flex")
    assert isinstance(flex_output, int)
    assert flex_output > 0
    # GPT-5-nano/reasoning model specific. Remove if model used in test changes.
    flex_reasoning = usage_metadata.get("output_token_details", {}).get(
        "flex_reasoning"
    )
    assert isinstance(flex_reasoning, int)
    assert flex_reasoning > 0
    assert flex_reasoning + flex_output == usage_metadata.get("output_tokens")