Metadata-Version: 2.4
Name: vish-rag-lib
Version: 0.1.8
Summary: Simple RAG library
Author: Vishakha
Author-email: Vishakha <badgujarvishakha8@gmail.com>
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: faiss-cpu
Requires-Dist: sentence-transformers
Requires-Dist: requests
Requires-Dist: PyPDF2
Dynamic: author
Dynamic: requires-python

# Vishakha Rag lib
A simple RAG (Retrival-Agumented-Generation) Library Using PDFs and LLMs.

## Features ##
-Load Pdf files
-Chuks texts
-generate embeddings
-store in vector database
-search nearast vectors
-Retirive revelant Data
-Connect With any LLM Api

## Usage ##
''' Python
from vish_rag_lib import RAGSystem

rag=RAGSystem()
rag.ingest("Sample.pdf")

def my_llm(prompt):
   return "LLM respones"
answer=rag.ask("What is AI?",my_llm)
print(answer)

# Installation #
pip install vish-rag-lib

# Work-Flow-RAG #
Chunks-Text divided into small Parts
Embedding-Sentence convert into meaining base vectors 
vectors-Loading embeddings search the similar queary answers
Retriever- User queary storted in vectorDB (Most relevan chunks search)
