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RAG & Knowledge Systems

Pdf Rag With LLAMA2 And Gradio

Pdf Rag With LLAMA2 And Gradio is a Python chatbot that answers questions about uploaded PDF files through conversational retrieval, keeps chat history, and can display pages associated with answers. It uses Gradio, LangChain, ChromaDB, and configurable Hugging Face model and embedding details, with Llama 2 among its named technologies.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Pdf Rag With LLAMA2 And Gradio — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you want a locally run, PDF-focused question-answering interface and can configure its model and embeddings.

Who it is for

  • Readers who need to ask questions about PDF documents and refer back to relevant pages.
  • Developers seeking a self-hosted Python starting point for a PDF question-answering chatbot.

Documented uses

  • Ask questions about content extracted from uploaded PDFs.
  • Keep a conversation history while researching a document.
  • Locate the PDF pages associated with generated answers.
  • Configure the Hugging Face model and embeddings used by the application.
Before you choose

Requirements & limits

The repository is public and identifies the project as Apache-2.0 licensed; its README documents running the application locally.

  • The application is documented as a local run using python app.py from the src directory.
  • Model and embedding details are specified in config.yaml and may need updating for a different choice.
  • The documented stack includes Gradio, LangChain, ChromaDB, Hugging Face, and Llama 2.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up and open the chatbot locally

Install the project dependencies and start the Gradio PDF chatbot from the repository.

Before you start

  • Python project checkout
  • Dependencies listed in requirements.txt
  • Model and embeddings details configured in config.yaml

Steps

  1. Install dependencies with the command below.

    Documented command
    pip install -r requirements.txt

  2. Set the Hugging Face model and embeddings details in config.yaml as needed.

  3. Change into the src directory.

  4. Run the command below.

    Documented command
    python app.py

Expected outcome

The README's documented local startup path for the chatbot interface.

Guide limitations

  • The README does not specify hardware requirements or guarantee compatibility for particular model and embedding configurations.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
18 October 2026
Original website title
Niez-Gharbi/PDF-RAG-with-Llama2-and-Gradio · Official homepage title · retained in its source language
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