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Code

cookbook/11_models/cerebras/basic_knowledge.py
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.models.cerebras import Cerebras
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=Cerebras(id="llama-4-scout-17b-16e-instruct"), knowledge=knowledge)
agent.print_response("How to make Thai curry?", markdown=True)

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Usage

1

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate
2

Set your API key

export CEREBRAS_API_KEY=xxx
3

Install dependencies

uv pip install -U agno sqlalchemy pgvector pypdf cerebras_cloud_sdk
4

Start your Postgres server

Ensure your Postgres server is running and accessible at the connection string used in db_url.
5

Run Agent (first time)

The first run will load and index the PDF. This may take a while.
python cookbook/11_models/cerebras/basic_knowledge.py
6

Subsequent Runs

After the first run, comment out or remove knowledge_base.load(recreate=True) to avoid reloading the PDF each time.