"""Test JinaChat wrapper.""" from typing import cast import pytest from langchain_core.callbacks import CallbackManager from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage from langchain_core.outputs import ChatGeneration, LLMResult from langchain_core.pydantic_v1 import SecretStr from pytest import CaptureFixture, MonkeyPatch from langchain_community.chat_models.jinachat import JinaChat from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler def test_jinachat_api_key_is_secret_string() -> None: llm = JinaChat(jinachat_api_key="secret-api-key") # type: ignore[arg-type, call-arg] assert isinstance(llm.jinachat_api_key, SecretStr) def test_jinachat_api_key_masked_when_passed_from_env( monkeypatch: MonkeyPatch, capsys: CaptureFixture ) -> None: """Test initialization with an API key provided via an env variable""" monkeypatch.setenv("JINACHAT_API_KEY", "secret-api-key") llm = JinaChat() # type: ignore[call-arg] print(llm.jinachat_api_key, end="") # noqa: T201 captured = capsys.readouterr() assert captured.out == "**********" def test_jinachat_api_key_masked_when_passed_via_constructor( capsys: CaptureFixture, ) -> None: """Test initialization with an API key provided via the initializer""" llm = JinaChat(jinachat_api_key="secret-api-key") # type: ignore[arg-type, call-arg] print(llm.jinachat_api_key, end="") # noqa: T201 captured = capsys.readouterr() assert captured.out == "**********" def test_uses_actual_secret_value_from_secretstr() -> None: """Test that actual secret is retrieved using `.get_secret_value()`.""" llm = JinaChat(jinachat_api_key="secret-api-key") # type: ignore[arg-type, call-arg] assert cast(SecretStr, llm.jinachat_api_key).get_secret_value() == "secret-api-key" def test_jinachat() -> None: """Test JinaChat wrapper.""" chat = JinaChat(max_tokens=10) # type: ignore[call-arg] message = HumanMessage(content="Hello") response = chat.invoke([message]) assert isinstance(response, BaseMessage) assert isinstance(response.content, str) def test_jinachat_system_message() -> None: """Test JinaChat wrapper with system message.""" chat = JinaChat(max_tokens=10) # type: ignore[call-arg] system_message = SystemMessage(content="You are to chat with the user.") human_message = HumanMessage(content="Hello") response = chat.invoke([system_message, human_message]) assert isinstance(response, BaseMessage) assert isinstance(response.content, str) def test_jinachat_generate() -> None: """Test JinaChat wrapper with generate.""" chat = JinaChat(max_tokens=10) # type: ignore[call-arg] message = HumanMessage(content="Hello") response = chat.generate([[message], [message]]) assert isinstance(response, LLMResult) assert len(response.generations) == 2 for generations in response.generations: assert len(generations) == 1 for generation in generations: assert isinstance(generation, ChatGeneration) assert isinstance(generation.text, str) assert generation.text == generation.message.content def test_jinachat_streaming() -> None: """Test that streaming correctly invokes on_llm_new_token callback.""" callback_handler = FakeCallbackHandler() callback_manager = CallbackManager([callback_handler]) chat = JinaChat( # type: ignore[call-arg] max_tokens=10, streaming=True, temperature=0, callback_manager=callback_manager, verbose=True, ) message = HumanMessage(content="Hello") response = chat.invoke([message]) assert callback_handler.llm_streams > 0 assert isinstance(response, BaseMessage) async def test_async_jinachat() -> None: """Test async generation.""" chat = JinaChat(max_tokens=102) # type: ignore[call-arg] message = HumanMessage(content="Hello") response = await chat.agenerate([[message], [message]]) assert isinstance(response, LLMResult) assert len(response.generations) == 2 for generations in response.generations: assert len(generations) == 1 for generation in generations: assert isinstance(generation, ChatGeneration) assert isinstance(generation.text, str) assert generation.text == generation.message.content async def test_async_jinachat_streaming() -> None: """Test that streaming correctly invokes on_llm_new_token callback.""" callback_handler = FakeCallbackHandler() callback_manager = CallbackManager([callback_handler]) chat = JinaChat( # type: ignore[call-arg] max_tokens=10, streaming=True, temperature=0, callback_manager=callback_manager, verbose=True, ) message = HumanMessage(content="Hello") response = await chat.agenerate([[message], [message]]) assert callback_handler.llm_streams > 0 assert isinstance(response, LLMResult) assert len(response.generations) == 2 for generations in response.generations: assert len(generations) == 1 for generation in generations: assert isinstance(generation, ChatGeneration) assert isinstance(generation.text, str) assert generation.text == generation.message.content def test_jinachat_extra_kwargs() -> None: """Test extra kwargs to chat openai.""" # Check that foo is saved in extra_kwargs. llm = JinaChat(foo=3, max_tokens=10) # type: ignore[call-arg] assert llm.max_tokens == 10 assert llm.model_kwargs == {"foo": 3} # Test that if extra_kwargs are provided, they are added to it. llm = JinaChat(foo=3, model_kwargs={"bar": 2}) # type: ignore[call-arg] assert llm.model_kwargs == {"foo": 3, "bar": 2} # Test that if provided twice it errors with pytest.raises(ValueError): JinaChat(foo=3, model_kwargs={"foo": 2}) # type: ignore[call-arg] # Test that if explicit param is specified in kwargs it errors with pytest.raises(ValueError): JinaChat(model_kwargs={"temperature": 0.2}) # type: ignore[call-arg]