PPTX Reader Async

The PPTX Reader with asynchronous processing allows you to read and extract text content from PowerPoint (.pptx) files with better performance for concurrent operations.

Code

pptx_reader_async.py

import asyncio

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.pptx_reader import PPTXReader
from agno.vectordb.pgvector import PgVector

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

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

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

def main():
    # Load the knowledge
    asyncio.run(
        knowledge.add_content_async(
            path="data/pptx_files",
            reader=PPTXReader(),
        )
    )

    # Create and use the agent
    asyncio.run(
        agent.aprint_response(
            "What can you tell me about the content in these PowerPoint presentations?", markdown=True
        )
    )

if __name__ == "__main__":
    main()

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 python-pptx 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 pptx_reader_async.py
   

PPTX Reader Params

Parameter	Type	Default	Description
file	Union[Path, IO[Any]]	Required	Path to PPTX file or file-like object containing a PowerPoint presentation
name	Optional[str]	None	Optional name for the document
chunk	bool	True	Whether to chunk the document
chunk_size	int	5000	Size of chunks when chunking is enabled
chunking_strategy	Optional[ChunkingStrategy]	DocumentChunking()	Strategy for chunking the document
encoding	Optional[str]	None	Text encoding to use for reading