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87 lines
3.2 KiB
Python
87 lines
3.2 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from agent_framework import Agent
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from agent_framework.openai import OpenAIChatClient, OpenAIChatOptions
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from dotenv import load_dotenv
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# Load environment variables from .env file
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load_dotenv()
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"""
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OpenAI Chat Client Reasoning Example
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This sample demonstrates advanced reasoning capabilities using OpenAI's gpt-5 models,
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showing step-by-step reasoning process visualization and complex problem-solving.
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This uses the default_options parameter to enable reasoning with high effort and detailed summaries.
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You can also set these options at the run level using the options parameter.
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Since these are api and/or provider specific, you will need to lookup
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the correct values for your provider, as they are passed through as-is.
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In this case they are here: https://platform.openai.com/docs/api-reference/responses/create#responses-create-reasoning
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"""
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agent = Agent(
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client=OpenAIChatClient[OpenAIChatOptions](model="gpt-5"),
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name="MathHelper",
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instructions="You are a personal math tutor. When asked a math question, "
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"reason over how best to approach the problem and share your thought process.",
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default_options={"reasoning": {"effort": "high", "summary": "detailed"}},
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)
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async def reasoning_example() -> None:
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"""Example of reasoning response (get results as they are generated)."""
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print("\033[92m=== Reasoning Example ===\033[0m")
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query = "I need to solve the equation 3x + 11 = 14 and I need to prove the pythagorean theorem. Can you help me?"
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print(f"User: {query}")
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print(f"{agent.name}: ", end="", flush=True)
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response = await agent.run(query)
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for msg in response.messages:
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if msg.contents:
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for content in msg.contents:
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if content.type == "text_reasoning":
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print(f"\033[94m{content.text}\033[0m", end="", flush=True)
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elif content.type == "text":
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print(content.text, end="", flush=True)
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print("\n")
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if response.usage_details:
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print(f"Usage: {response.usage_details}")
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async def streaming_reasoning_example() -> None:
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"""Example of reasoning response (get results as they are generated)."""
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print("\033[92m=== Streaming Reasoning Example ===\033[0m")
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query = "I need to solve the equation 3x + 11 = 14 and I need to prove the pythagorean theorem. Can you help me?"
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print(f"User: {query}")
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print(f"{agent.name}: ", end="", flush=True)
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usage = None
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async for chunk in agent.run(query, stream=True):
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if chunk.contents:
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for content in chunk.contents:
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if content.type == "text_reasoning":
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print(f"\033[94m{content.text}\033[0m", end="", flush=True)
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elif content.type == "text":
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print(content.text, end="", flush=True)
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elif content.type == "usage":
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usage = content
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print("\n")
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if usage:
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print(f"Usage: {usage.usage_details}")
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async def main() -> None:
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print("\033[92m=== Basic OpenAI Chat Reasoning Agent Example ===\033[0m")
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await reasoning_example()
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await streaming_reasoning_example()
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if __name__ == "__main__":
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asyncio.run(main())
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