test_fake_list_chat_model_batch() — langchain Function Reference

Architecture documentation for the test_fake_list_chat_model_batch() function in test_fake_chat_model.py from the langchain codebase.

Function python LangChainCore LanguageModelBase

Entity Profile

LangChainCore→ LanguageModelBase→ test_fake_list_chat_model_batch() — langchain Function Reference

Dependency Diagram

graph TD
  ff7300ce_486c_b2b6_f816_d387bafd6e51["test_fake_list_chat_model_batch()"]
  06318702_96e4_1032_1475_4dde8fe1f643["test_fake_chat_model.py"]
  ff7300ce_486c_b2b6_f816_d387bafd6e51 -->|defined in| 06318702_96e4_1032_1475_4dde8fe1f643
  style ff7300ce_486c_b2b6_f816_d387bafd6e51 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/tests/unit_tests/fake/test_fake_chat_model.py lines 230–240

def test_fake_list_chat_model_batch() -> None:
    expected = [
        _any_id_ai_message(content="a"),
        _any_id_ai_message(content="b"),
        _any_id_ai_message(content="c"),
    ]
    for _ in range(20):
        # run this 20 times to test race condition in batch
        fake = FakeListChatModel(responses=["a", "b", "c"])
        resp = fake.batch(["1", "2", "3"])
        assert resp == expected