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Question Answering From PDF File

This Project only for Exploration about Simple RAG (Retrieval Augmented Generation) Implementation with PDF File.

Project Structure

The directory structure of new project looks like this:


│
├── src                    <- Source code
│   ├── models             <- Model scripts
│   ├── utils              <- Utility scripts
│
├── app.py                 <- Main Application
│
├── .env.example           <- Example of file for storing private environment variables
├── .gitignore             <- List of files ignored by git
├── requirements.txt       <- File for installing python dependencies
└── README.md

How to run

1. Clone this repository

To get started, clone this repository onto your local machine. Follow the instructions below:

  1. Open a terminal or Command Prompt.
  2. Change to the directory where you want to clone the repository.
  3. Enter the following command to clone the repository: 
    git clone https://github.com/MuhFaridanSutariya/pdf.ai.git
  4. Once the cloning process is complete, navigate into the cloned directory using the cd command: 
    cd pdf.ai

2. System Requirements

Make sure your system meets the following requirements before proceeding:

  • Python 3.10+ is installed on your computer.
  • Pip (Python package installer) is installed.

3. Create a Virtual Environment

A virtual environment will allow you to separate this project from the global Python installation. Follow these steps to create a virtual environment:

On Windows: Open Command Prompt and enter the following command:

python -m venv virtualenv_name

Replace virtualenv_name with the desired name for your virtual environment.

On macOS and Linux: Open the terminal and enter the following command:

python3 -m venv virtualenv_name

Replace virtualenv_name with the desired name for your virtual environment.

4. Activate the Virtual Environment

After creating the virtual environment, you need to activate it before installing the requirements. Use the following steps:

On Windows: In Command Prompt, enter the following command:

virtualenv_name\Scripts\activate

Replace virtualenv_name with the name you provided in the previous step.

On macOS and Linux: In the terminal, enter the following command:

source virtualenv_name/bin/activate.bat

Replace virtualenv_name with the name you provided in the previous step.

5. Install Requirements

Once the virtual environment is activated, you can install the project requirements from the requirements.txt file. Follow these steps:

On Windows, macOS, and Linux: In the activated virtual environment, navigate to the directory where the requirements.txt file is located. Then, enter the following command:

pip install -r requirements.txt

This command will install all the required packages specified in the requirements.txt file

6. Run Chainlit

How to run Web App:

chainlit run app.py

References

Built using inspiration from LinkedIn Learning course 'Hands-On AI: Building LLM-Powered Apps' by Han-chung Lee