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langchain/libs/community/tests/integration_tests/chat_models/test_bedrock.py

164 lines
5.4 KiB
Python

"""Test Bedrock chat model."""
from typing import Any, cast
import pytest
from langchain_core.callbacks import CallbackManager
from langchain_core.messages import (
AIMessageChunk,
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.invoke([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_generate_with_token_usage(chat: BedrockChat) -> None:
"""Test BedrockChat wrapper with generate."""
message = HumanMessage(content="Hello")
response = chat.generate([[message], [message]])
assert isinstance(response, LLMResult)
assert isinstance(response.llm_output, dict)
usage = response.llm_output["usage"]
assert usage["prompt_tokens"] == 20
assert usage["completion_tokens"] > 0
assert usage["total_tokens"] > 0
@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.invoke([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."""
full = None
for token in chat.stream("I'm Pickle Rick"):
full = token if full is None else full + token # type: ignore[operator]
assert isinstance(token.content, str)
assert isinstance(cast(AIMessageChunk, full).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)
assert all([k in result.response_metadata for k in ("usage", "model_id")])
assert result.response_metadata["usage"]["prompt_tokens"] == 13