wehub-resource-sync
84 lines
3.3 KiB
Python
84 lines
3.3 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from samples.concepts.setup.chat_completion_services import Services, get_chat_completion_service_and_request_settings
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from semantic_kernel.connectors.ai.completion_usage import CompletionUsage
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from semantic_kernel.contents import ChatHistory
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# This sample shows how to retrieve the token usage for a chat completion service response.
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# This sample uses the following two main components:
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# - a ChatCompletionService: This component is responsible for generating responses to user messages.
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# - a ChatHistory: This component is responsible for keeping track of the chat history.
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# You can select from the following chat completion services:
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# - Services.OPENAI
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# - Services.AZURE_OPENAI
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# - Services.AZURE_AI_INFERENCE
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# - Services.ANTHROPIC
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# - Services.BEDROCK
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# - Services.GOOGLE_AI
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# - Services.MISTRAL_AI
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# - Services.OLLAMA
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# - Services.ONNX
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# - Services.VERTEX_AI
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# - Services.DEEPSEEK
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# Please make sure you have configured your environment correctly for the selected chat completion service.
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chat_completion_service, request_settings = get_chat_completion_service_and_request_settings(Services.OPENAI)
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# This is the system message that gives the chatbot its personality.
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system_message = """
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You are a chat bot. Your name is Mosscap and
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you have one goal: figure out what people need.
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Your full name, should you need to know it, is
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Splendid Speckled Mosscap. You communicate
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effectively, but you tend to answer with long
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flowery prose.
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"""
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USER_INPUTS = [
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"Why is the sky blue?",
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"What is the capital of France?",
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]
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# Create a chat history object with the system message.
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chat_history = ChatHistory(system_message=system_message)
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async def main() -> None:
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running_total: CompletionUsage = CompletionUsage()
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for user_input in USER_INPUTS:
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print(f"User: {user_input}")
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# Add the user message to the chat history so that the chatbot can respond to it.
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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_completion_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"Mosscap:> {response}")
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if "usage" in response.metadata and response.metadata["usage"]:
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# Not all services return token usage information.
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print(f"[Tokens used: {response.metadata['usage']}]")
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running_total += response.metadata["usage"]
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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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print(f"Total tokens used: {running_total}")
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# Sample output:
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# User: Why is the sky blue?
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# Mosscap:> Ah, the azure canopy that stretches above us, a question as timeless as the sky itself! ...
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# [Tokens used: prompt_tokens=83 completion_tokens=201]
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# User: What is the capital of France?
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# Mosscap:> Ah, the capital of France, a city that has captured the hearts and imaginations of countless ...
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# [Tokens used: prompt_tokens=298 completion_tokens=176]
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# Total tokens used: prompt_tokens=381 completion_tokens=377
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if __name__ == "__main__":
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asyncio.run(main())
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