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Add a simple gpt-oss example #1440
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import asyncio | ||
import logging | ||
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from openai import AsyncOpenAI | ||
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from agents import Agent, OpenAIChatCompletionsModel, Runner, set_tracing_disabled | ||
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set_tracing_disabled(True) | ||
logging.basicConfig(level=logging.DEBUG) | ||
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# This is an example of how to use gpt-oss with Ollama. | ||
# Refer to https://cookbook.openai.com/articles/gpt-oss/run-locally-ollama for more details. | ||
# If you prefer using LM Studio, refer to https://cookbook.openai.com/articles/gpt-oss/run-locally-lmstudio | ||
gpt_oss_model = OpenAIChatCompletionsModel( | ||
model="gpt-oss:20b", | ||
openai_client=AsyncOpenAI( | ||
base_url="http://localhost:11434/v1", | ||
api_key="ollama", | ||
), | ||
) | ||
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async def main(): | ||
# Note that using a custom outputType for an agent may not work well with gpt-oss models. | ||
# Consider going with the default "text" outputType. | ||
# See also: https://github.com/openai/openai-agents-python/issues/1414 | ||
agent = Agent( | ||
name="Assistant", | ||
instructions="You're a helpful assistant. You provide a concise answer to the user's question.", | ||
model=gpt_oss_model, | ||
) | ||
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result = await Runner.run(agent, "Tell me about recursion in programming.") | ||
print(result.final_output) | ||
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if __name__ == "__main__": | ||
asyncio.run(main()) | ||
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might be nice to automatically start ollama here as well, but not required
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yeah, but perhaps we can do something in the future 😸