AI & LLM
FeaturedEducational Chatbot using RAG
An innovative educational tool leveraging Small Language Models and RAG architecture to provide accessible learning support for underserved communities, with offline capability.
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Key Features
- Lightweight SLM architecture for device-efficient operation
- Web-based interface for easy accessibility
- 75% accuracy on 4,000-question dataset validated with RAGChecker
- Offline capability for areas with limited internet connectivity
- Supports underserved communities in learning
- Retrieval-Augmented Generation for accurate responses
Challenges Faced
- Running a capable chatbot on limited/offline hardware for underserved communities
- Keeping answers grounded and accurate despite using a small language model
- Validating answer quality without a large evaluation team
Solutions Implemented
- Chose a lightweight SLM architecture optimized for on-device, offline operation
- Used Retrieval-Augmented Generation to ground responses in a curated physics knowledge base
- Validated accuracy (75% on a 4,000-question set) using the RAGChecker framework
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Curious how it was built?
I'd be glad to walk through the architecture and decisions behind Educational Chatbot using RAG.