from agno.agent import Agent from agno.knowledge.pdf_url import PDFUrlKnowledgeBase from agno.vectordb.pgvector import PgVector db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai" vector_db = PgVector(table_name="recipes", db_url=db_url) knowledge_base = PDFUrlKnowledgeBase( urls=["https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"], vector_db=vector_db, ) knowledge_base.load(recreate=False) # Comment out after first run agent = Agent(knowledge=knowledge_base, show_tool_calls=True) agent.print_response("How to make Thai curry?", markdown=True)
Create a virtual environment
Open the Terminal and create a python virtual environment.
Terminal
python3 -m venv .venv source .venv/bin/activate
Start PgVector
docker run -d \ -e POSTGRES_DB=ai \ -e POSTGRES_USER=ai \ -e POSTGRES_PASSWORD=ai \ -e PGDATA=/var/lib/postgresql/data/pgdata \ -v pgvolume:/var/lib/postgresql/data \ -p 5532:5432 \ --name pgvector \ agnohq/pgvector:16
Install libraries
pip install -U sqlalchemy pgvector psycopg pypdf openai agno
Run Agent
python cookbook/agent_concepts/vector_dbs/pg_vector.py
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