The CSV URL Reader processes CSV files directly from URLs, allowing you to create knowledge bases from remote CSV data sources.

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Code

examples/concepts/knowledge/readers/csv_reader_url_async.py
import asyncio

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.pgvector import PgVector

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

knowledge = Knowledge(
    # Table name: ai.csv_documents
    vector_db=PgVector(
        table_name="csv_documents",
        db_url=db_url,
    ),
)

# Initialize the Agent with the knowledge
agent = Agent(
    knowledge=knowledge,
    search_knowledge=True,
)

if __name__ == "__main__":
    # Comment out after first run
    asyncio.run(
        knowledge.add_content_async(
            url="https://agno-public.s3.amazonaws.com/demo_data/IMDB-Movie-Data.csv"
        )
    )

    # Create and use the agent
    asyncio.run(
        agent.aprint_response("What genre of movies are present here?", markdown=True)
    )

​
Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Install libraries

pip install -U pandas requests sqlalchemy psycopg pgvector agno
3

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 \
  agno/pgvector:16
4

Run Agent

python examples/concepts/knowledge/readers/csv_reader_url_async.py

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Params

ParameterTypeDefaultDescription
urlstrRequiredURL pointing to a CSV file to download and read