Agent with Knowledge

Code

knowledge.py

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.models.groq import Groq
from agno.vectordb.pgvector import PgVector

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

knowledge = Knowledge(
    vector_db=PgVector(table_name="recipes", db_url=db_url),
)
# Add content to the knowledge
knowledge.insert(url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf")

agent = Agent(
    model=Groq(id="llama-3.3-70b-versatile"),
    knowledge=knowledge,
)
agent.print_response("How to make Thai curry?", markdown=True)

Usage

Set up your virtual environment

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

uv venv --python 3.12
.venv\Scripts\activate

Set your API key

export GROQ_API_KEY=xxx
export OPENAI_API_KEY=xxx

Install dependencies

uv pip install -U sqlalchemy psycopg pgvector pypdf openai groq agno

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

Run Agent

Save the code above as knowledge.py, then run:

python knowledge.py

Get Started

Basics

Advanced

Production

Providers

Other

Additional Resources

Agent with Knowledge

Code

Usage

Developer Resources

​Code

​Usage

​Developer Resources

Code

Usage

Developer Resources