Prerequisites
- Experience with Python
- Experience with Music Blocks
- Experience with LLMs/Chatbots
- Experience with AWS
- Experience with FastAPI
Description
The idea is to enhance Music Blocks with an AI-powered debugger. This feature aims to bridge the gap between users' creative ideas and their ability to troubleshoot or fully utilize the platform's features. This AI-powered debugger will provide real-time assistance by answering questions, explaining features, and offering creative suggestions. It will help users quickly identify and resolve issues in their projects or block connections This enhancement would make the platform more accessible for beginners while streamlining the debugging and experimentation process for advanced users.
Specifically, we aim to achieve the following:
- Train an open-source LLM to understand Music Blocks projects and develop the ability to debug them effectively.
- Implement robust Retrieval-Augmented Generation (RAG) for the LLM model to enhance contextual understanding.
- Integrate the AI chatbot and debugger into the Music Blocks platform.
- Develop FastAPI endpoints to deploy the model efficiently.
- Work on techniques to minimize hallucinations and improve accuracy.
Project Length
350 hours
Difficulty
Hard
Coding Mentors
Walter Bender Sumit Srivastava
Assisting Mentors
Devin Ulibarri