@@ -28,7 +28,7 @@ async def example_usage():
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as well as the ability to fetch URLs. Your job is to identify
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the closest match to a user's request, make the appropriate tool calls,
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and return the URI and CONTENTS of the closest match.""" ,
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- server_names = ["curl " , "filesystem" ],
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+ server_names = ["fetch " , "filesystem" ],
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)
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async with finder_agent :
@@ -44,19 +44,17 @@ async def example_usage():
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# Let's switch the same agent to a different LLM
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llm = await finder_agent .attach_llm (AnthropicAugmentedLLM )
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- # Let's switch the same agent to a different LLM
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- # llm = await finder_agent.attach_llm(AnthropicAugmentedLLM)
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-
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- # result = await llm.generate_str(
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- # message="Print the first 2 paragraphs of https://www.anthropic.com/research/building-effective-agents",
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- # )
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- # logger.info(f"Result: {result}")
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-
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- # Multi-turn conversations
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- # result = await llm.generate_str(
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- # message="Summarize those paragraphs in a 128 character tweet",
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- # )
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- # logger.info(f"Result: {result}")
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+
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+ result = await llm .generate_str (
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+ message = "Print the first 2 paragraphs of https://www.anthropic.com/research/building-effective-agents" ,
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+ )
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+ logger .info (f"Result: { result } " )
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+
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+ # Multi-turn conversations
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+ result = await llm .generate_str (
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+ message = "Summarize those paragraphs in a 128 character tweet" ,
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+ )
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+ logger .info (f"Result: { result } " )
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# Make sure to shut down logging cleanly
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await LoggingConfig .shutdown ()
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