124 lines
3.7 KiB
Python
124 lines
3.7 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from semantic_kernel.connectors.ai.open_ai import (
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OpenAIChatCompletion,
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OpenAIChatPromptExecutionSettings,
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)
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from semantic_kernel.contents import ChatHistory
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"""
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# Reasoning Models Sample
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This sample demonstrates an example of how to use reasoning models such as OpenAI’s o1 and o1-mini for inference.
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Reasoning models currently have certain limitations, which are outlined below.
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1. Requires API version `2024-09-01-preview` or later.
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- `reasoning_effort` and `developer_message` are only supported in API version `2024-12-01-preview` or later.
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- o1-mini is not supported property `developer_message` `reasoning_effort` now.
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2. Developer message must be used instead of system message
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3. Parallel tool invocation is currently not supported
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4. Token limit settings need to consider both reasoning and completion tokens
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# Unsupported Properties ⛔
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The following parameters are currently not supported:
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- temperature
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- top_p
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- presence_penalty
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- frequency_penalty
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- logprobs
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- top_logprobs
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- logit_bias
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- max_tokens
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- stream
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- tool_choice
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# .env examples
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OpenAI: semantic_kernel/connectors/ai/open_ai/settings/open_ai_settings.py
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```.env
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OPENAI_API_KEY=*******************
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OPENAI_CHAT_MODEL_ID=o1-2024-12-17
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```
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Azure OpenAI: semantic_kernel/connectors/ai/open_ai/settings/azure_open_ai_settings.py
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```.env
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AZURE_OPENAI_API_KEY=*******************
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AZURE_OPENAI_ENDPOINT=https://*********.openai.azure.com
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AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=o1-2024-12-17
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AZURE_OPENAI_API_VERSION="2024-12-01-preview"
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```
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Note: Unsupported features may be added in future updates.
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"""
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chat_service = OpenAIChatCompletion(service_id="reasoning", instruction_role="developer")
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# Set the reasoning effort to "medium" and the maximum completion tokens to 5000.
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request_settings = OpenAIChatPromptExecutionSettings(
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service_id="reasoning", max_completion_tokens=2000, reasoning_effort="medium"
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)
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# Create a ChatHistory object
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chat_history = ChatHistory()
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# This is the system message that gives the chatbot its personality.
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developer_message = """
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As an assistant supporting the user,
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you recognize all user input
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as questions or consultations and answer them.
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"""
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# The developer message was newly introduced for reasoning models such as OpenAI’s o1 and o1-mini.
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# `system message` cannot be used with reasoning models.
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chat_history.add_developer_message(developer_message)
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async def chat() -> bool:
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try:
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user_input = input("User:> ")
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except KeyboardInterrupt:
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print("\n\nExiting chat...")
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return False
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except EOFError:
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print("\n\nExiting chat...")
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return False
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if user_input == "exit":
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print("\n\nExiting chat...")
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return False
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chat_history.add_user_message(user_input)
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# Get the chat message content from the chat completion service.
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response = await chat_service.get_chat_message_content(
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chat_history=chat_history,
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settings=request_settings,
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)
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if response:
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print(f"Reasoning model:> {response}")
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# Add the chat message to the chat history to keep track of the conversation.
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chat_history.add_message(response)
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return True
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async def main() -> None:
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# Start the chat loop. The chat loop will continue until the user types "exit".
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chatting = True
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while chatting:
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chatting = await chat()
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# Sample output:
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# User:> Why is the sky blue in one sentence?
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# Mosscap:> The sky appears blue because air molecules in the atmosphere scatter shorter-wavelength (blue)
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# light more efficiently than longer-wavelength (red) light.
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if __name__ == "__main__":
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asyncio.run(main())
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