Developed RAG-based URL Analyzer for Personalized Article Insights

[Varsha-1605]

#373

Description

Created 4 files:

1. app.py - for backend

2. qa.html - for frontend

3. environment variable - for storing secrets

4. .gitignore file - to avoid secrets get committed

5. Made the UI similar to the website

6. Navbar Functionality:

   • Navigation links for different sections like Home, About Us, Collections, Services, and Contact Us.
   • User interaction buttons for:
     • Login
     • Signup
     • Cart with a cart icon.

7. URL-based Question-Answer (QA) System:

   • URL Input:
     • Input field for users to enter a URL for document processing.
     • Submit button to trigger backend processing of the URL.
   • Question Input:
     • Input field for users to enter a question related to the processed document.
     • Submit button to receive an answer based on the document content.
   • Answer Display:
     • Display area for showing the answer generated by the system.
     • Highlighting of relevant sources used for generating the answer.

8. Document and File Processing:

   • Document Upload:
     • Allows users to upload local files (e.g., PDFs) for processing and extraction.
   • File Parsing:
     • Backend functionality to parse uploaded documents for relevant content to be used in the QA system.
   • Document Store and Vectorization:
     • Stores and vectorizes document content using embeddings for faster and more accurate search and retrieval.

9. Question Answering System (Q&A) using Langchain:

   • AI Model Integration:
     • Leverages AI/ML models for processing documents and answering user questions based on the content.
     • Integrates Langchain-based pipeline to manage document parsing and Q&A.
   • Document Search:
     • Uses embeddings to search for relevant answers from the vectorized documents.
   • Formatted Answer Display:
     • Provides answers to user questions with relevant sections of the document highlighted.

10. Frontend Form Submission and Response Handling:

    • Form Handling:
      • Frontend form submission for URL-based document processing and question asking.
      • Interaction between frontend and backend to submit user queries and receive answers.
    • Backend Communication:
      • Processes inputs (URLs, uploaded files, and questions) and forwards them to the backend AI model for Q&A processing.
    • Response Display:
      • Displays responses generated by the backend on the frontend for users to view.

11. Footer Functionality:

    • Footer Links:
      • Quick navigation links to sections such as Home, About, Services, Cart.
      • Additional information on offers and payment options.
    • Contact Form:
      • A form for users to submit their email and message.
      • Submit button for sending messages to the site admins.
    • Social Media Integration:
      • Icons and links for social media platforms like Facebook, Instagram, and Twitter.
    • Back to Top Button:
      • A button at the footer to scroll back to the top of the page.

12. Custom Cursor Effect:

    • Dynamic custom cursor animation that changes based on user interaction, with color transitions and movement effects.

13. Error Handling and Feedback:

    • Provides user-friendly feedback in case of errors during document processing (e.g., invalid URLs or unsupported file formats).
    • Displays error messages or notifications on both the frontend and backend to assist users in resolving issues.

14. User Session Management:

    • Manages sessions to store document embeddings for current users, ensuring smooth transition between different stages of document analysis and Q&A.

15. Smooth Navigation and UI Enhancements:

    • Custom animations for smoother user experience, including dynamic scrolling and a back-to-top button for seamless navigation.
    • Well-designed forms and interaction buttons to guide users through document processing and Q&A.
    • Emphasis on interactive and visually appealing elements (e.g., animated cursor, smooth transitions) to enhance user engagement.

Related Issues

• Closes ✨[feature Request]: Develop RAG-based URL Analyzer for Personalized Article Insights #373

Type of PR

• (Bug)
• (Enhancement)

Screenshots

In the navbar added Url Analyser button

Checklist

• I have gone through the contributing guide
• I have updated my branch and synced it with project main branch before making this PR
• I have performed a self-review of my code
• I have tested the changes thoroughly before submitting this pull request.
• I have provided relevant issue numbers, screenshots, and videos after making the changes.
• I have commented my code, particularly in hard-to-understand areas.

@Anjaliavv51 Kindly add all the required labels as per the task completion.

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[github-actions]

Great job, @Varsha-1605! 🎉 Thank you for submitting your pull request. Your contribution is valuable and we appreciate your efforts to improve our project.We will promptly review your changes and offer feedback. Keep up the excellent work! Kindly remember to check our contributing guidelines

[Anjaliavv51]

@Varsha-1605 qa.html is not loading?