prevectorchunks-core 0.1.1

A Python module that allows conversion of a document into chunks to be inserted into Pinecone vector database

📚 PreVectorChunks

A lightweight utility for document chunking and vector database upserts — designed for developers building RAG (Retrieval-Augmented Generation) solutions.

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✨ Who Needs This Module?

Any developer working with:

• RAG pipelines
• Vector Databases (like Pinecone, Weaviate, etc.)
• AI applications requiring similar content retrieval

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🎯 What Does This Module Do?

This module helps you:

• Chunk documents into smaller fragments
• Insert (upsert) fragments into a vector database
• Fetch & update existing chunks from a vector database

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📦 Installation

pip install prevectorchunks

How to import in a file:

from PreVectorChunks.services import chunk_documents_crud_vdb

#How to use Pinecone and OpenAI:
#Use a .env file in your project root to configure API keys:

PINECONE_API_KEY=YOUR_API_KEY
OPENAI_API_KEY=YOUR_API_KEY

#how to call relevant functions:
#Four key functions that you can call are below: 
#function that chunks any document 
chunk_documents(instructions,file_path="content_playground/content.json"): 
#function that chunks any document as well as inserts into vdb - you need an index name inside index_n
chunk_and_upsert_to_vdb(index_n,instructions,file_path="content_playground/content.json"): 
#function that loads existing chunks from vdb by document name - you need an index name inside index_n 
fetch_vdb_chunks_grouped_by_document_name(index_n): 
#function that updates existing chunks - you need an index name inside index_n 
update_vdb_chunks_grouped_by_document_name(index_n,dataset):