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481d3855dc
- `llm(prompt)` -> `llm.invoke(prompt)`
- `llm(prompt=prompt` -> `llm.invoke(prompt)` (same with `messages=`)
- `llm(prompt, callbacks=callbacks)` -> `llm.invoke(prompt,
config={"callbacks": callbacks})`
- `llm(prompt, **kwargs)` -> `llm.invoke(prompt, **kwargs)`
63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
"""Test Anthropic API wrapper."""
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from typing import List
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from langchain_core.callbacks import (
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CallbackManager,
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)
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from langchain_core.messages import AIMessage, BaseMessage, HumanMessage
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from langchain_core.outputs import ChatGeneration, LLMResult
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from langchain_community.chat_models.litellm import ChatLiteLLM
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from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
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def test_litellm_call() -> None:
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"""Test valid call to litellm."""
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chat = ChatLiteLLM(
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model="test",
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)
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message = HumanMessage(content="Hello")
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response = chat.invoke([message])
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assert isinstance(response, AIMessage)
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assert isinstance(response.content, str)
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def test_litellm_generate() -> None:
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"""Test generate method of anthropic."""
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chat = ChatLiteLLM(model="test")
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chat_messages: List[List[BaseMessage]] = [
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[HumanMessage(content="How many toes do dogs have?")]
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]
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messages_copy = [messages.copy() for messages in chat_messages]
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result: LLMResult = chat.generate(chat_messages)
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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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assert chat_messages == messages_copy
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def test_litellm_streaming() -> None:
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"""Test streaming tokens from anthropic."""
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chat = ChatLiteLLM(model="test", streaming=True)
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message = HumanMessage(content="Hello")
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response = chat.invoke([message])
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assert isinstance(response, AIMessage)
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assert isinstance(response.content, str)
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def test_litellm_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 = ChatLiteLLM(
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model="test",
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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 10 words.")
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chat.invoke([message])
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assert callback_handler.llm_streams > 1
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