Ollama PDF RAG Streamlit UI

Overview

This Streamlit application leverages Ollama and LangChain to create a PDF-based Retrieval-Augmented Generation (RAG) system. Users can upload PDF documents and ask questions about their content, utilizing language models to generate answers based on the document's text.

Features

• PDF Upload: Users can upload PDF documents to be processed.
• Question Processing: Ask questions about the content of the uploaded PDFs.
• Document Viewing: View uploaded PDFs directly in the application.
• Vector Database Creation: Automatically creates a vector database from the uploaded PDF to facilitate document retrieval and question answering.
• RAG Pipeline implemented in order to comply to everything above

Installation

1. Clone this repository.
2. Ensure you have Python 3.8 or newer installed.
3. Install Ollama locally(https://ollama.com/download/mac)
4. Pull Ollama:

   ollama pull llama3

5. Start/create a python enviorment

   python -m myenv
   source myenv/bin/activate

6. Install required packages:

   pip install streamlit pdfplumber ollama langchain
   

To start the application: streamlit run app.py