aditya-p17 / ChatWithPDFs

ChatWithPDFs

This project involves the development of a robust RAG (Retrieval-Augmented Generation) application designed to facilitate user interactions with PDF documents. By leveraging the Gemini API for advanced document processing and LangChain for natural language understanding and generation, this application provides an intuitive and efficient interface for users to query, summarize, and interact with PDF content.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

• Python version greater than 3.11 installed
• Gemini API key from AI Studio

Installing

1. Clone the repository

   You can clone the repository by running the following command in your terminal:

   git clone https://github.com/aditya-p17/ChatWithPDFs.git

2. Set up a virtual environment Before any step, install virtualenv

   pip install virtualenv

   It's recommended to set up a virtual environment to isolate the dependencies of this project.

   • On Linux:

     You can do this by running:

     python3 -m virtualenv venv

     source venv/bin/activate

   • On Windows:

     You can do this by running:

     py -m virtualenv venv

     .\venv\Scripts\activate

   This will create a new virtual environment in a folder named venv and activate it. While the virtual environment is activated, any packages you install with pip will be installed in the virtual environment, not globally.

3. Install the dependencies

   After setting up and activating the virtual environment, you can install the required Python packages with pip by running:

   pip install -r requirements.txt

4. Get your Gemini API key from AI Studio.

5. Create a .env file in the project directory and add your Gemini API key:

   GOOGLE_API_KEY=your_gemini_api_key_here

6. Run the Streamlit application:

   streamlit run app.py