demo_srm_fdp

Flask: A lightweight WSGI web application framework in Python. It is used to create the web server and handle HTTP requests.
summarize.py: This module contains the summarize_document function, which is responsible for summarizing the uploaded document's content. You can enhance this function with more advanced summarization techniques as needed.

app.py:
- This is the main application file that sets up the Flask server and defines the routes for the application.
- It includes the following routes:
  - /: The home route that renders the main interface for document upload.
  - /upload: Handles file uploads, reads the content of the uploaded document, and generates a summary using the summarize_document function.
  - /ask: Accepts user questions and provides answers based on the summary using the answer_question function.
summarize.py:
- Contains the summarize_document function, which currently provides a placeholder implementation for summarization. You can replace this with a more sophisticated summarization algorithm or library.
templates/index.html:
- The HTML template for the user interface. It includes a form for uploading documents, displays the generated summary, and allows users to ask questions based on the summary.
data.txt:
- A sample text file that can be used as input for the summarization function. It contains information about transformers in natural language processing.

How to Run the Project

Install Flask: Make sure you have Flask installed. You can install it using pip:
```
pip install Flask
```
Run the Application: Execute the following command in your terminal:
```
python app.py
```
Access the Application: Open your web browser and navigate to http://127.0.0.1:5000/ to access the application.
Upload a Document: Use the provided interface to upload a text document (e.g., data.txt) and receive a summary.
Ask Questions: After viewing the summary, you can ask questions related to the content, and the application will provide answers based on the implemented logic.

Improve the summarization logic in summarize.py using advanced NLP techniques or libraries.
Enhance the Q&A functionality to provide more accurate and context-aware answers.
Implement user authentication and session management for a more personalized experience.

This project is open-source and available for modification and distribution. Feel free to contribute or use it as a base for your own projects!