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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
Terminal and create a python virtual environment.python3 -m venv .venv
source .venv/bin/activate
python3 -m venv .venv
.venv/scripts/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
python cookbook/agent_concepts/vector_dbs/pg_vector.py
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