Code
cookbook/90_models/meta/llama/knowledge.py
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.models.meta import Llama
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=Llama(id="Llama-4-Maverick-17B-128E-Instruct-FP8"), knowledge=knowledge
)
agent.print_response("How to make Thai curry?", markdown=True)
Usage
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Set your API keys
export LLAMA_API_KEY=YOUR_API_KEY
export OPENAI_API_KEY=YOUR_API_KEY
3
Install dependencies
uv pip install llama-api-client sqlalchemy psycopg pgvector pypdf openai agno
4
Run Agent
python cookbook/90_models/meta/llama/knowledge.py