mirror of
https://github.com/hwchase17/langchain
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392f1b3218
* Adds an Anthropic ChatModel * Factors out common code in our LLMModel and ChatModel * Supports streaming llm-tokens to the callbacks on a delta basis (until a future V2 API does that for us) * Some fixes
82 lines
2.7 KiB
Python
82 lines
2.7 KiB
Python
"""Test Anthropic API wrapper."""
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from typing import List
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import pytest
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from langchain.callbacks.base import CallbackManager
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from langchain.chat_models.anthropic import ChatAnthropic
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from langchain.schema import (
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AIMessage,
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BaseMessage,
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ChatGeneration,
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HumanMessage,
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LLMResult,
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)
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from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
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def test_anthropic_call() -> None:
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"""Test valid call to anthropic."""
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chat = ChatAnthropic(model="bare-nano-0")
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message = HumanMessage(content="Hello")
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response = chat([message])
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assert isinstance(response, AIMessage)
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assert isinstance(response.content, str)
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def test_anthropic_streaming() -> None:
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"""Test streaming tokens from anthropic."""
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chat = ChatAnthropic(model="bare-nano-0", streaming=True)
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message = HumanMessage(content="Hello")
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response = chat([message])
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assert isinstance(response, AIMessage)
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assert isinstance(response.content, str)
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def test_anthropic_streaming_callback() -> 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 = ChatAnthropic(
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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="Write me a sentence with 100 words.")
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chat([message])
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assert callback_handler.llm_streams > 1
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@pytest.mark.asyncio
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async def test_anthropic_async_streaming_callback() -> 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 = ChatAnthropic(
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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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chat_messages: List[BaseMessage] = [
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HumanMessage(content="How many toes do dogs have?")
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]
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result: LLMResult = await chat.agenerate([chat_messages])
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assert callback_handler.llm_streams > 1
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assert isinstance(result, LLMResult)
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for response in result.generations[0]:
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assert isinstance(response, ChatGeneration)
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assert isinstance(response.text, str)
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assert response.text == response.message.content
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def test_formatting() -> None:
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chat = ChatAnthropic()
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chat_messages: List[BaseMessage] = [HumanMessage(content="Hello")]
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result = chat._convert_messages_to_prompt(chat_messages)
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assert result == "\n\nHuman: Hello\n\nAssistant:"
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chat_messages = [HumanMessage(content="Hello"), AIMessage(content="Answer:")]
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result = chat._convert_messages_to_prompt(chat_messages)
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assert result == "\n\nHuman: Hello\n\nAssistant: Answer:"
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