design

Local_Pdf_Chat_RAG: Smarter QA

Name: Local_Pdf_Chat_RAG: Smarter QA
Author: weiwill88

Get retrieval-augmented generation with Local_Pdf_Chat_RAG, ideal for founders new to NLP and QA tools

931 stars177 forksPythonQuality 8/10Updated 7/4/2026100% free · open source

What it does

Local_Pdf_Chat_RAG generates human-like text based on the content of local PDF files using retrieval-augmented generation, ideal for founders new to NLP and QA tools

Install / run

git clone https://github.com/weiwill88/Local_Pdf_Chat_RAG.git

When to use it

•You need to generate text based on a large corpus of local PDF files
•You want to build a QA system that can retrieve information from local PDF files
•You are looking for a simple, pure Python implementation of a RAG framework

Quick start

1Run `python setup.py install` to install the required dependencies
2Create a new directory for your PDF files and add them to the `pdfs` folder
3Modify the `config.json` file to specify the path to your PDF files and other settings
4Run `python app.py` to start the Local_Pdf_Chat_RAG server
5Use a tool like `curl` or a web browser to interact with the Local_Pdf_Chat_RAG API

Ready-to-paste prompt

Run `python app.py -p 'What is the main topic of the PDF file called example.pdf?'` to generate a response based on the content of the `example.pdf` file

Heads up: Make sure you have the required dependencies, including FAISS and BM25, installed and configured correctly, as specified in the README

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