PgVector Async

Code

async_pg_vector.py

import asyncio

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
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 = Knowledge(
    vector_db=vector_db,
)

agent = Agent(knowledge=knowledge_base)

if __name__ == "__main__":

    asyncio.run(
        knowledge_base.ainsert(url="https://docs.agno.com/agents/overview.md")
    )

    asyncio.run(
        agent.aprint_response("What is the purpose of an Agno Agent?", markdown=True)
    )

Usage

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Install dependencies

   uv pip install -U sqlalchemy psycopg pgvector pypdf openai agno
   
3. Run PgVector

   docker run -d \
     -e POSTGRES_DB=ai \
     -e POSTGRES_USER=ai \
     -e POSTGRES_PASSWORD=ai \
     -e PGDATA=/var/lib/postgresql \
     -v pgvolume:/var/lib/postgresql \
     -p 5532:5432 \
     --name pgvector \
     agnohq/pgvector:18
   
4. Set environment variables

   export OPENAI_API_KEY=xxx
   
5. Run Agent

   python async_pg_vector.py