​
Code

from agno.agent import Agent
from agno.knowledge.arxiv import ArxivKnowledgeBase
from agno.vectordb.pgvector import PgVector

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

# Create a knowledge base with the ArXiv documents
knowledge_base = ArxivKnowledgeBase(
    queries=["Generative AI", "Machine Learning"],
    # Table name: ai.arxiv_documents
    vector_db=PgVector(
        table_name="arxiv_documents",
        db_url=db_url,
    ),
)
# Load the knowledge base
knowledge_base.load(recreate=False)

# Create an agent with the knowledge base
agent = Agent(
    knowledge=knowledge_base,
    search_knowledge=True,
)

# Ask the agent about the knowledge base
agent.print_response(
    "Ask me about generative ai from the knowledge base", markdown=True
)

​
Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.

2

Install libraries

pip install -U sqlalchemy 'psycopg[binary]' pgvector agno
3

Run 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
4

Run Agent

RAG with LanceDB and SQLiteCombined Knowledge Base