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39 lines
805 B
Python
39 lines
805 B
Python
from praisonaiagents import Agent, Task, Agents
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# Define the configuration for the Knowledge instance
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config = {
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"vector_store": {
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"provider": "chroma",
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"config": {
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"collection_name": "praison",
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"path": ".praison"
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}
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}
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}
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# Create an agent
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rag_agent = Agent(
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name="RAG Agent",
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role="Information Specialist",
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goal="Retrieve knowledge efficiently",
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llm="gpt-4o-mini"
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)
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# Define a task for the agent
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rag_task = Task(
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name="RAG Task",
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description="What is KAG?",
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expected_output="Answer to the question",
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agent=rag_agent,
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context=[config] # Vector Database provided as context
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)
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# Build Agents
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agents = AgentManager(
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agents=[rag_agent],
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tasks=[rag_task],
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user_id="user1"
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)
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# Start Agents
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agents.start() |