mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
ed58eeb9c5
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
140 lines
4.5 KiB
Python
140 lines
4.5 KiB
Python
"""Test Bedrock chat model."""
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from typing import Any
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import pytest
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from langchain_core.callbacks import CallbackManager
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from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage
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from langchain_core.outputs import ChatGeneration, LLMResult
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from langchain_community.chat_models import BedrockChat
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from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
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@pytest.fixture
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def chat() -> BedrockChat:
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return BedrockChat(model_id="anthropic.claude-v2", model_kwargs={"temperature": 0})
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@pytest.mark.scheduled
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def test_chat_bedrock(chat: BedrockChat) -> None:
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"""Test BedrockChat wrapper."""
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system = SystemMessage(content="You are a helpful assistant.")
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human = HumanMessage(content="Hello")
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response = chat([system, human])
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assert isinstance(response, BaseMessage)
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assert isinstance(response.content, str)
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@pytest.mark.scheduled
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def test_chat_bedrock_generate(chat: BedrockChat) -> None:
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"""Test BedrockChat wrapper with generate."""
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message = HumanMessage(content="Hello")
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response = chat.generate([[message], [message]])
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assert isinstance(response, LLMResult)
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assert len(response.generations) == 2
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for generations in response.generations:
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for generation in generations:
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assert isinstance(generation, ChatGeneration)
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assert isinstance(generation.text, str)
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assert generation.text == generation.message.content
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@pytest.mark.scheduled
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def test_chat_bedrock_streaming() -> None:
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"""Test that streaming correctly invokes on_llm_new_token callback."""
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callback_handler = FakeCallbackHandler()
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callback_manager = CallbackManager([callback_handler])
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chat = BedrockChat(
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model_id="anthropic.claude-v2",
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streaming=True,
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callback_manager=callback_manager,
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verbose=True,
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)
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message = HumanMessage(content="Hello")
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response = chat([message])
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assert callback_handler.llm_streams > 0
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assert isinstance(response, BaseMessage)
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@pytest.mark.scheduled
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def test_chat_bedrock_streaming_generation_info() -> None:
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"""Test that generation info is preserved when streaming."""
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class _FakeCallback(FakeCallbackHandler):
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saved_things: dict = {}
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def on_llm_end(
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self,
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*args: Any,
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**kwargs: Any,
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) -> Any:
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# Save the generation
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self.saved_things["generation"] = args[0]
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callback = _FakeCallback()
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callback_manager = CallbackManager([callback])
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chat = BedrockChat(
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model_id="anthropic.claude-v2",
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callback_manager=callback_manager,
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)
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list(chat.stream("hi"))
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generation = callback.saved_things["generation"]
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# `Hello!` is two tokens, assert that that is what is returned
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assert generation.generations[0][0].text == " Hello!"
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@pytest.mark.scheduled
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def test_bedrock_streaming(chat: BedrockChat) -> None:
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"""Test streaming tokens from OpenAI."""
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for token in chat.stream("I'm Pickle Rick"):
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assert isinstance(token.content, str)
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@pytest.mark.scheduled
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async def test_bedrock_astream(chat: BedrockChat) -> None:
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"""Test streaming tokens from OpenAI."""
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async for token in chat.astream("I'm Pickle Rick"):
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assert isinstance(token.content, str)
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@pytest.mark.scheduled
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async def test_bedrock_abatch(chat: BedrockChat) -> None:
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"""Test streaming tokens from BedrockChat."""
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result = await chat.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"])
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for token in result:
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assert isinstance(token.content, str)
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@pytest.mark.scheduled
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async def test_bedrock_abatch_tags(chat: BedrockChat) -> None:
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"""Test batch tokens from BedrockChat."""
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result = await chat.abatch(
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["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]}
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)
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for token in result:
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assert isinstance(token.content, str)
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@pytest.mark.scheduled
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def test_bedrock_batch(chat: BedrockChat) -> None:
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"""Test batch tokens from BedrockChat."""
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result = chat.batch(["I'm Pickle Rick", "I'm not Pickle Rick"])
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for token in result:
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assert isinstance(token.content, str)
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@pytest.mark.scheduled
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async def test_bedrock_ainvoke(chat: BedrockChat) -> None:
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"""Test invoke tokens from BedrockChat."""
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result = await chat.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]})
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assert isinstance(result.content, str)
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@pytest.mark.scheduled
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def test_bedrock_invoke(chat: BedrockChat) -> None:
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"""Test invoke tokens from BedrockChat."""
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result = chat.invoke("I'm Pickle Rick", config=dict(tags=["foo"]))
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assert isinstance(result.content, str)
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