"""Test Bedrock chat model.""" from typing import Any 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_community.chat_models import BedrockChat from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler @pytest.fixture def chat() -> BedrockChat: return BedrockChat(model_id="anthropic.claude-v2", model_kwargs={"temperature": 0}) @pytest.mark.scheduled def test_chat_bedrock(chat: BedrockChat) -> None: """Test BedrockChat wrapper.""" system = SystemMessage(content="You are a helpful assistant.") human = HumanMessage(content="Hello") response = chat([system, human]) assert isinstance(response, BaseMessage) assert isinstance(response.content, str) @pytest.mark.scheduled def test_chat_bedrock_generate(chat: BedrockChat) -> None: """Test BedrockChat wrapper with generate.""" message = HumanMessage(content="Hello") response = chat.generate([[message], [message]]) assert isinstance(response, LLMResult) assert len(response.generations) == 2 for generations in response.generations: for generation in generations: assert isinstance(generation, ChatGeneration) assert isinstance(generation.text, str) assert generation.text == generation.message.content @pytest.mark.scheduled def test_chat_bedrock_streaming() -> None: """Test that streaming correctly invokes on_llm_new_token callback.""" callback_handler = FakeCallbackHandler() callback_manager = CallbackManager([callback_handler]) chat = BedrockChat( model_id="anthropic.claude-v2", streaming=True, callback_manager=callback_manager, verbose=True, ) message = HumanMessage(content="Hello") response = chat([message]) assert callback_handler.llm_streams > 0 assert isinstance(response, BaseMessage) @pytest.mark.scheduled def test_chat_bedrock_streaming_generation_info() -> None: """Test that generation info is preserved when streaming.""" class _FakeCallback(FakeCallbackHandler): saved_things: dict = {} def on_llm_end( self, *args: Any, **kwargs: Any, ) -> Any: # Save the generation self.saved_things["generation"] = args[0] callback = _FakeCallback() callback_manager = CallbackManager([callback]) chat = BedrockChat( model_id="anthropic.claude-v2", callback_manager=callback_manager, ) list(chat.stream("hi")) generation = callback.saved_things["generation"] # `Hello!` is two tokens, assert that that is what is returned assert generation.generations[0][0].text == " Hello!" @pytest.mark.scheduled def test_bedrock_streaming(chat: BedrockChat) -> None: """Test streaming tokens from OpenAI.""" for token in chat.stream("I'm Pickle Rick"): assert isinstance(token.content, str) @pytest.mark.scheduled async def test_bedrock_astream(chat: BedrockChat) -> None: """Test streaming tokens from OpenAI.""" async for token in chat.astream("I'm Pickle Rick"): assert isinstance(token.content, str) @pytest.mark.scheduled async def test_bedrock_abatch(chat: BedrockChat) -> None: """Test streaming tokens from BedrockChat.""" result = await chat.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"]) for token in result: assert isinstance(token.content, str) @pytest.mark.scheduled async def test_bedrock_abatch_tags(chat: BedrockChat) -> None: """Test batch tokens from BedrockChat.""" result = await chat.abatch( ["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]} ) for token in result: assert isinstance(token.content, str) @pytest.mark.scheduled def test_bedrock_batch(chat: BedrockChat) -> None: """Test batch tokens from BedrockChat.""" result = chat.batch(["I'm Pickle Rick", "I'm not Pickle Rick"]) for token in result: assert isinstance(token.content, str) @pytest.mark.scheduled async def test_bedrock_ainvoke(chat: BedrockChat) -> None: """Test invoke tokens from BedrockChat.""" result = await chat.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]}) assert isinstance(result.content, str) @pytest.mark.scheduled def test_bedrock_invoke(chat: BedrockChat) -> None: """Test invoke tokens from BedrockChat.""" result = chat.invoke("I'm Pickle Rick", config=dict(tags=["foo"])) assert isinstance(result.content, str)