d79b3744cb
This change remove `BaseComponent`'s: - run_raw - run_batch_raw - run_document - run_batch_document - is_document - is_batch Each component is expected to support multiple types of inputs and a single type of output. Since we want the component to work out-of-the-box with both standardized and customized use cases, supporting multiple types of inputs are expected. At the same time, to reduce the complexity of understanding how to use a component, we restrict a component to only have a single output type. To accommodate these changes, we also refactor some components to remove their run_raw, run_batch_raw... methods, and to decide the common output interface for those components. Tests are updated accordingly. Commit changes: * Add kwargs to vector store's query * Simplify the BaseComponent * Update tests * Remove support for Python 3.8 and 3.9 * Bump version 0.3.0 * Fix github PR caching still use old environment after bumping version --------- Co-authored-by: ian <ian@cinnamon.is>
70 lines
2.2 KiB
Python
70 lines
2.2 KiB
Python
from unittest.mock import patch
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from langchain.chat_models import AzureChatOpenAI as AzureChatOpenAILC
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from langchain.schema.messages import AIMessage, HumanMessage, SystemMessage
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from openai.types.chat.chat_completion import ChatCompletion
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from kotaemon.llms.base import LLMInterface
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from kotaemon.llms.chats.openai import AzureChatOpenAI
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_openai_chat_completion_response = ChatCompletion.parse_obj(
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{
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"id": "chatcmpl-7qyuw6Q1CFCpcKsMdFkmUPUa7JP2x",
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"object": "chat.completion",
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"created": 1692338378,
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"model": "gpt-35-turbo",
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"system_fingerprint": None,
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"choices": [
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{
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"index": 0,
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"finish_reason": "stop",
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"message": {
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"role": "assistant",
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"content": "Hello! How can I assist you today?",
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"function_call": None,
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"tool_calls": None,
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},
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}
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],
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"usage": {"completion_tokens": 9, "prompt_tokens": 10, "total_tokens": 19},
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}
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)
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@patch(
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"openai.resources.chat.completions.Completions.create",
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side_effect=lambda *args, **kwargs: _openai_chat_completion_response,
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)
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def test_azureopenai_model(openai_completion):
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model = AzureChatOpenAI(
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openai_api_base="https://test.openai.azure.com/",
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openai_api_key="some-key",
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openai_api_version="2023-03-15-preview",
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deployment_name="gpt35turbo",
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temperature=0,
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)
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assert isinstance(
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model.agent, AzureChatOpenAILC
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), "Agent not wrapped in Langchain's AzureChatOpenAI"
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# test for str input - stream mode
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output = model("hello world")
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assert isinstance(
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output, LLMInterface
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), "Output for single text is not LLMInterface"
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openai_completion.assert_called()
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# test for list[message] input - stream mode
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messages = [
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SystemMessage(content="You are a philosohper"),
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HumanMessage(content="What is the meaning of life"),
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AIMessage(content="42"),
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HumanMessage(content="What is the meaning of 42"),
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]
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output = model(messages)
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assert isinstance(
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output, LLMInterface
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), "Output for single text is not LLMInterface"
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openai_completion.assert_called()
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