pgvector_real_wow.py

"""PGVector Vector Store - Agent-First Example

Docker: docker run -d --name pgvector -e POSTGRES_PASSWORD=postgres -p 5433:5432 pgvector/pgvector:pg16
"""
import os
from praisonaiagents import Agent

url = os.getenv("PGVECTOR_URL", "postgresql://postgres:postgres@localhost:5433/postgres")

# Agent-first approach: use knowledge parameter with PGVector
agent = Agent(
    name="Assistant",
    instructions="You are a helpful assistant with access to documents.",
    knowledge={"sources": ["./docs/guide.pdf"], "vector_store": {"provider": "pgvector", "url": url}}
)

# Chat - agent uses knowledge for RAG
response = agent.chat("What information do you have?")
print(f"Response: {response}")

print("PASSED: PGVector with Agent")

# --- Advanced: Direct PGVector Usage ---
# import psycopg2
# conn = psycopg2.connect(url)
# cur = conn.cursor()
# cur.execute("CREATE EXTENSION IF NOT EXISTS vector")