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73 lines
2.0 KiB
Python
73 lines
2.0 KiB
Python
from crewai_tools import EXASearchTool
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from crewai import LLM, Agent, Crew, Task
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import os
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llm = LLM(
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model="anthropic/claude-3-5-sonnet-20241022",
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api_key=os.getenv("ANTHROPIC_API_KEY"),
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)
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agent = Agent(
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role="researcher",
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backstory="A researcher who can research the web",
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goal="Research the web",
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tools=[EXASearchTool()],
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llm=llm,
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)
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task = Task(
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description="Research the web based on the query: {query}",
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expected_output="A list of 10 bullet points of the most relevant information about the web",
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agent=agent,
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)
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crew = Crew(
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agents=[agent],
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tasks=[task],
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verbose=True,
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tracing=True,
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)
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# result = crew.kickoff(inputs={"query": "What are ai agents?"})
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# print("result", result)
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# print("usage_metrics", result.token_usage)
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def anthropic_tool_use_runner():
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def get_weather(location: str) -> str:
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return f"The weather in {location} is sunny"
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llm = LLM(
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model="anthropic/claude-3-5-sonnet-20241022",
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api_key=os.getenv("ANTHROPIC_API_KEY"),
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)
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result = llm.call(
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messages=[{"role": "user", "content": "What is the weather in San Francisco?"}],
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available_functions={"get_weather": get_weather},
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tools=[
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{
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"type": "function",
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"function": {
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"name": "get_weather",
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"description": "Get the weather in a location",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The location to get the weather for",
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}
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},
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"required": ["location"],
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},
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},
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}
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],
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)
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print("anthropic tool use result", result)
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if __name__ == "__main__":
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anthropic_tool_use_runner()
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