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Code

cookbook/models/groq/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.add_content(
    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)

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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

Set your API key

export GROQ_API_KEY=xxx
3

Install libraries

pip install -U ddgs sqlalchemy pgvector pypdf openai groq agno
4

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
5

Run Agent

python cookbook/models/groq/knowledge.py