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Code

cookbook/knowledge/vector_db/pgvector/pgvector_hybrid_search.py
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIChat
from agno.vectordb.pgvector import PgVector, SearchType

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

knowledge = Knowledge(
    name="My PG Vector Knowledge Base",
    description="This is a knowledge base that uses a PG Vector DB",
    vector_db=PgVector(
        table_name="vectors", db_url=db_url, search_type=SearchType.hybrid
    ),
)

knowledge.add_content(
    name="Recipes",
    url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
    metadata={"doc_type": "recipe_book"},
)

agent = Agent(
    model=OpenAIChat(id="gpt-5-mini"),
    knowledge=knowledge,
    search_knowledge=True,
    read_chat_history=True,
    markdown=True,
)
agent.print_response(
    "How do I make chicken and galangal in coconut milk soup", stream=True
)
agent.print_response("What was my last question?", stream=True)

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Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Install libraries

pip install -U psycopg2-binary pgvector pypdf openai agno
3

Set environment variables

export OPENAI_API_KEY=xxx
4

Run Agent

python cookbook/knowledge/vector_db/pgvector/pgvector_hybrid_search.py