CSV Reader Async

The CSV Reader with asynchronous processing allows you to handle CSV files and integrate them with knowledge bases efficiently.

Code

examples/concepts/knowledge/readers/csv_reader_async.py

import asyncio
from pathlib import Path

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(
    vector_db=PgVector(
        table_name="csv_documents",
        db_url=db_url,
    ),
    max_results=5,  # Number of results to return on search
)

# 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(path=Path("data/csv")))

    # Create and use the agent
    asyncio.run(agent.aprint_response("What is the csv file about", markdown=True))

Usage

1. Create a virtual environment

   Open the Terminal and create a python virtual environment.

   Mac

   python3 -m venv .venv
   source .venv/bin/activate
   
2. Install libraries

   pip install -U pandas 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

   Mac

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

Params

Parameter	Type	Default	Description
file	Union[Path, IO[Any]]	Required	Path to CSV file or file-like object
delimiter	str	","	Character used to separate fields in the CSV
quotechar	str	'"'	Character used to quote fields in the CSV