> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# CSV Row Chunking

> Split CSV files into one chunk per row with RowChunking.

`CSVReader` parses the records, then `RowChunking` creates one chunk for each non-empty normalized row and records its logical row number in metadata.

<Steps>
  <Step title="Create a Python file">
    ```python csv_row_chunking.py theme={null}
    from agno.agent import Agent
    from agno.knowledge.chunking.row import RowChunking
    from agno.knowledge.knowledge import Knowledge
    from agno.knowledge.reader.csv_reader import CSVReader
    from agno.vectordb.pgvector import PgVector

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

    knowledge_base = Knowledge(
        vector_db=PgVector(table_name="imdb_movies_row_chunking", db_url=db_url),
    )

    knowledge_base.insert(
        url="https://agno-public.s3.amazonaws.com/demo_data/IMDB-Movie-Data.csv",
        reader=CSVReader(
            chunking_strategy=RowChunking(),
        ),
    )

    agent = Agent(
        knowledge=knowledge_base,
        search_knowledge=True,
    )

    agent.print_response("Tell me about the movie Guardians of the Galaxy", markdown=True)
    ```
  </Step>

  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno sqlalchemy psycopg pgvector aiofiles openai
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <Snippet file="set-openai-key.mdx" />
  </Step>

  <Snippet file="run-pgvector-step.mdx" />

  <Step title="Run the script">
    ```bash theme={null}
    python csv_row_chunking.py
    ```
  </Step>
</Steps>

## CSV Row Chunking Params

<Snippet file="chunking-csv-row.mdx" />

## Developer Resources

* [Chunking overview](/knowledge/concepts/chunking/overview)
* [Chunking strategies examples](/examples/knowledge/building-blocks/chunking-strategies)
* [CSV reader](/knowledge/concepts/readers/csv-reader)