Primary Reference: The project draws inspiration from the Quivr app, which boasts a robust Supabase backend and logging functionality. Our aim is to integrate similar features while simplifying the approach for our MVP.
Technical Foundation: We are considering the Perplexity project (found at https://github.com/developersdigest/Perplexity-Next-JS-Supabase/tree/main) as a starting point. Modifications needed include adding a user authentication system and file upload capabilities, alongside leveraging OpenAI for chat functionalities.
LMS Integration: We plan to integrate an LMS layer akin to the system showcased in Antonio Erdeljac’s next13-lms-platform (GitHub: https://github.com/AntonioErdeljac/next13-lms-platform, Video: https://www.codewithantonio.com/projects/lms-platform). This will be wrapped around the foundational Quivr application to provide a structured learning environment.

User Flow:

1. Log into the LMS system.
2. Select and view a course, including watching any associated video content.
3. Initiate an interactive session that not only guides users through the course content with questions but also allows for clicking and interacting with content directly within the chat window, mimicking the functionality found in the Perplexity project. This feature enhances the interactive learning experience by providing a dynamic way to engage with the material.
4. All interaction data, including chat history, is stored in Supabase for analysis and feedback.

The developer would need to build a new authentication system on top of the app here – https://github.com/developersdigest/Perplexity-Next-JS-Supabase/tree/main ; and ensure that all chats are logged to supabase; in addition add the ability to upload files to be part of the RAG – this is similar to what Quivr app is doing

Hourly Range: $45.00-$90.00

Posted On: February 14, 2024 12:19 UTC
Category: Full Stack Development
Skills:Next.js, OpenAI API, API, Supabase

Country: United States

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