import asyncio from os import getenv from agno.agent import Agent from agno.knowledge.knowledge import Knowledge from agno.knowledge.reader.wikipedia_reader import WikipediaReader from agno.vectordb.lightrag import LightRag vector_db = LightRag( api_key=getenv("LIGHTRAG_API_KEY"), ) knowledge = Knowledge( name="My Pinecone Knowledge Base", description="This is a knowledge base that uses a Pinecone Vector DB", vector_db=vector_db, ) asyncio.run( knowledge.add_content( name="Recipes", path="cookbook/08_knowledge/testing_resources/cv_1.pdf", metadata={"doc_type": "recipe_book"}, ) ) asyncio.run( knowledge.add_content( name="Recipes", topics=["Manchester United"], reader=WikipediaReader(), ) ) asyncio.run( knowledge.add_content( name="Recipes", url="https://en.wikipedia.org/wiki/Manchester_United_F.C.", ) ) agent = Agent( knowledge=knowledge, search_knowledge=True, read_chat_history=False, ) asyncio.run( agent.aprint_response("What skills does Jordan Mitchell have?", markdown=True) ) asyncio.run( agent.aprint_response( "In what year did Manchester United change their name?", markdown=True ) )
Set up your virtual environment
uv venv --python 3.12 source .venv/bin/activate
Install dependencies
uv pip install -U agno lightrag
Export your API keys
export OPENAI_API_KEY=your_openai_api_key_here export LIGHTRAG_API_KEY=your_lightrag_api_key_here
Run Agent
python agentic_rag_with_lightrag.py
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