mirror of
https://github.com/microsoft/semantic-kernel.git
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Eduard van Valkenburg
b8835d2ccd
### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? 2. What problem does it solve? 3. What scenario does it contribute to? 4. If it fixes an open issue, please link to the issue here. --> Small update to the reasoning samples, that leverages the latest updates to those api's. Fixed typing issue in filters. ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [x] The code builds clean without any errors or warnings - [x] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [x] All unit tests pass, and I have added new tests where possible - [x] I didn't break anyone 😄
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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