test_anthropic_proxy_support() — langchain Function Reference

Architecture documentation for the test_anthropic_proxy_support() function in test_chat_models.py from the langchain codebase.

Function python LangChainCore LanguageModelBase

Entity Profile

LangChainCore→ LanguageModelBase→ test_anthropic_proxy_support() — langchain Function Reference

Dependency Diagram

graph TD
  e6757ba3_5d26_98cf_2601_ca45a473ca1d["test_anthropic_proxy_support()"]
  18428dc5_a41b_90c6_88ad_615296ee3311["test_chat_models.py"]
  e6757ba3_5d26_98cf_2601_ca45a473ca1d -->|defined in| 18428dc5_a41b_90c6_88ad_615296ee3311
  style e6757ba3_5d26_98cf_2601_ca45a473ca1d fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/anthropic/tests/unit_tests/test_chat_models.py lines 77–95

def test_anthropic_proxy_support() -> None:
    """Test that both sync and async clients support proxy configuration."""
    proxy_url = "http://proxy.example.com:8080"

    # Test sync client with proxy
    llm_sync = ChatAnthropic(model=MODEL_NAME, anthropic_proxy=proxy_url)
    sync_client = llm_sync._client
    assert sync_client is not None

    # Test async client with proxy - this should not raise TypeError
    async_client = llm_sync._async_client
    assert async_client is not None

    # Test that clients with different proxy settings are not cached together
    llm_no_proxy = ChatAnthropic(model=MODEL_NAME)
    llm_with_proxy = ChatAnthropic(model=MODEL_NAME, anthropic_proxy=proxy_url)

    # Different proxy settings should result in different cached clients
    assert llm_no_proxy._client._client is not llm_with_proxy._client._client