Intelligent Document-Based Text Summarization and Question Answering System
Ensure you have the following installed on your system:
Python 3.8+
Node.js 16+ npm
Clone the repository (if not already):
git clone https://github.com/CDChaitanya/ReadEasy-AI
cd ReadEasy-AI
Run the project setup script:
source run_project.sh
This will:
Create and activate a Python virtual environment
Install backend dependencies from requirements.txt
Install frontend dependencies via npm install
Start both the Flask server and React frontend
And it opens the http://localhost:3000
Upload your transcript.txt file using the upload button
Click the "Summarize" button
⏳ Wait a few moments while the model processes and summarizes the document
Once the summary appears, you can enter a question related to the uploaded transcript
Click "Ask" --- the system will respond with an answer

This diagram shows the general structure and flow of the ReadEasy system.

Here’s the visual representation of the summarization processing window in the application.

This image shows a sample of the summary generated by the system.

This image demonstrates how the question-answering process works in the project.
Intelligent Document-Based Text Summarization and Question Answering System
Ensure you have the following installed on your system:
Python 3.8+
Node.js 16+ npm
Clone the repository (if not already):
git clone https://github.com/CDChaitanya/ReadEasy-AI
cd ReadEasy-AI
Run the project setup script:
source run_project.sh
This will:
Create and activate a Python virtual environment
Install backend dependencies from requirements.txt
Install frontend dependencies via npm install
Start both the Flask server and React frontend
And it opens the http://localhost:3000
Upload your transcript.txt file using the upload button
Click the "Summarize" button
⏳ Wait a few moments while the model processes and summarizes the document
Once the summary appears, you can enter a question related to the uploaded transcript
Click "Ask" --- the system will respond with an answer

This diagram shows the general structure and flow of the ReadEasy system.

Here’s the visual representation of the summarization processing window in the application.

This image shows a sample of the summary generated by the system.

This image demonstrates how the question-answering process works in the project.