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PDF_Insight_App

A full-stack application that allows users to upload PDF documents and ask questions regarding the content of these documents. The backend processes these documents and utilizes natural language processing to provide answers to the questions posed by the users.

Tools and Technologies:

Backend: FastAPI

NLP Processing: LLamaIndex

Frontend: React.js

Database: SQLite

File Storage: Local filesystem for storing uploaded PDFs

First Setup your React.js App

Step 1: Open git bash and Clone the repository and open the directory

git clone https://github.com/Maanit491/PDF_Insight_App.git

cd PDF_Insight_App

Step2: Open your terminal in the project directory and do

cd frontend

Step 3: Install npm

npm install

Step 4: Start your application

npm start

(Runs the app in the development mode.
Open http://localhost:3000 to view it in your browser.)

for more information about react setup, you can refer to the "README.md" File present in the "frontend" folder of this repository.

FastAPI Application Setup Guide for backend

This guide will help you set up a virtual environment and run a FastAPI application. Follow these steps to get your application up and running.

Prerequisites

Make sure you have the following installed on your system:

  • Python 3.7+
  • pip (Python package installer)
  • virtualenv (optional but recommended for creating isolated environments)

Steps

1. Open Another Terminal for running Backend

Open another terminal(not the one where your react is running) and run:

cd PDF_Insight_App

cd backend

2. Create a Virtual Environment

Creating a virtual environment ensures that dependencies are managed separately from other projects. You can create a virtual environment using the venv module (included with Python) or virtualenv.

Using venv

python -m venv env

Using virtualenv

virtualenv env

3. Activate the Virtual Environment

Activate the virtual environment you created.

On macOS and Linux

source env/bin/activate

On Windows

.\env\Scripts\Activate.ps1

Now you are in your environment.

4. Install Dependencies

Install the required dependencies using pip. Make sure you are in the project directory where the requirements.txt file is located.

pip install -r requirements.txt

5.Go to the .env file in the "app" folder and add your OPENAI_API_KEY.

OPENAI_API_KEY="enter_your_openai_key_here"

6. Run the Application

Run the FastAPI application using uvicorn, which is an ASGI server for Python.

uvicorn app.main:app --reload
  • main is the name of your Python file (without the .py extension) containing the FastAPI app.
  • app is the name of the FastAPI instance in your main file.
  • The --reload flag is useful for development, as it reloads the server when you make changes to your code.

Your application should now be running at http://127.0.0.1:8000.

7. Access the Application

Open your web browser and go to:

http://127.0.0.1:8000

You can also access the automatic interactive API documentation provided by FastAPI:

  • Swagger UI: http://127.0.0.1:8000/docs
  • ReDoc: http://127.0.0.1:8000/redoc

8. Deactivate the Virtual Environment

Once you are done working on your application, you can deactivate the virtual environment by running:

deactivate

Additional Tips

  • To add new dependencies, install them using pip and update requirements.txt:

    pip install <package_name>
pip freeze > requirements.txt

API Documentation

Endpoints

POST /uploadfile

This endpoint is for uploading PDF documents.

POST /api/query

This endpoint processes a user's query and returns a response from the NLP model.

Demo Video

https://drive.google.com/file/d/1Ts409ftscYUnY0dk5I9hJ-Eah13POg7b/view?usp=sharing