github-actions[bot]
commented
3 days ago Hi there! Thanks for opening this issue @Varsha-1605!. We appreciate your contribution to this open-source project. We aim to respond or assign your issue as soon as possible.
Anjaliavv51
Is there an existing issue for this?
Feature Description
Description:
Implement a RAG-based URL Analyzer for Retro to allow users to input article URLs related to vintage topics and receive personalized answers. The system will retrieve article content, generate embeddings, and provide custom responses using Retrieval-Augmented Generation (RAG) for enhanced user engagement.
Key Objectives:
1. URL Content Retrieval:
Implement web scraping to fetch and clean the content of URLs provided by users. Ensure it can handle various article formats and dynamic content using tools like BeautifulSoup, requests, or Selenium.
2. Content Embeddings and Storage:
Process the article content and generate embeddings using a pre-trained model (OpenAI GPT, Hugging Face Transformers). Store content embeddings in a retrieval system (e.g., FAISS) for efficient searching.
3. Personalized Question Answering:
Implement a QA system where the user can ask specific questions related to the article, and the system retrieves the most relevant information. Use the RAG model to combine article retrieval with language generation for highly tailored responses.
4. Recommendations and Connections:
Based on the analyzed article, provide personalized product or collection recommendations that align with the article's themes or the user’s preferences (e.g., vintage clothing, retro tech, etc.).
5. Frontend Integration:
Create a user-friendly interface (using Streamlit or another frontend framework) where users can input URLs, ask questions, and view personalized responses.
Use Case
Use Cases:
1. Vintage Fashion Enthusiasts:
Users input URLs to articles about 60s or 70s fashion, ask questions about key trends, and receive insights into the era’s fashion, along with recommendations for similar items on Retro.
2. Retro Tech Aficionados:
A user interested in old tech submits an article link about 80s computers and asks, "What impact did this have on modern technology?" They receive an insightful answer along with suggestions for related tech products.
3. Cultural History Learners:
A user exploring vintage cultural stories inputs an article link about retro music and asks questions about its historical significance, receiving detailed information and links to Retro’s music-related collections.
4. Vintage Home Decor Shoppers:
After reading an article on retro home decor, a user inputs the URL and asks about the most iconic 60s decor trends, receiving both a personalized summary and product recommendations from Retro’s catalog.
5. Educational Research:
Retro can use the tool to analyze popular articles in the vintage space, understand user queries, and create educational content to meet those interests, improving brand credibility and authority.
Benefits
Benefits:
1. Enhanced User Engagement:
Users can explore and engage with vintage-themed content more deeply by receiving personalized responses and insights from articles.
2. Personalized User Experience:
By tailoring answers and recommendations based on the article content, the platform offers a more individualized experience, aligning with user interests.
3. Improved Content Interaction:
Users can interact with external articles in a meaningful way, allowing them to gain more value from the content they’re already consuming.
4. Increased Product Discoverability:
The system can recommend products or collections based on the themes of the article, increasing the chances of users finding items they like.
5. Educational Value:
Users can ask historical or cultural questions about the vintage topics and get informative answers, enhancing Retro’s educational appeal.
6. SEO and Content Creation:
The insights from analyzing articles can help Retro identify trending topics, create relevant content, and improve SEO, driving more traffic to the platform.
Add ScreenShots
I have already worked on it.
Priority
High
Record