Fixed Size Chunking

Fixed size chunking is a method of splitting documents into smaller chunks of a specified size, with optional overlap between chunks. This is useful when you want to process large documents in smaller, manageable pieces.

Code

import asyncio
from agno.agent import Agent
from agno.knowledge.chunking.fixed import FixedSizeChunking
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.pdf_reader import PDFReader
from agno.vectordb.pgvector import PgVector

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

knowledge = Knowledge(
    vector_db=PgVector(table_name="recipes_fixed_size_chunking", db_url=db_url),
)

asyncio.run(knowledge.add_content_async(
    url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
    reader=PDFReader(
        name="Fixed Size Chunking Reader",
        chunking_strategy=FixedSizeChunking(),
    ),
))
agent = Agent(
    knowledge=knowledge,
    search_knowledge=True,
)

agent.print_response("How to make Thai curry?", 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 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 cookbook/knowledge/chunking/fixed_size_chunking.py
   

Fixed Size Chunking Params

Parameter	Type	Default	Description
chunk_size	int	5000	The maximum size of each chunk.
overlap	int	0	The number of characters to overlap between chunks.