Almond Industry RAG System
AI-powered question-answering for the almond industry, enabling food professionals to access insights from extensive documentation via natural language.
PythonFastAPIAzure OpenAICognitive SearchReactTypeScriptRAG
Project Overview
Developed a comprehensive AI-powered question-answering system for the almond industry, enabling food professionals and product developers to access insights from extensive industry documentation through natural language queries.
Key Technologies
Backend
- Python / FastAPI (REST API, streaming responses)
- Azure OpenAI and Cognitive Search (semantic retrieval)
- Server-Sent Events for live chat
Frontend
- React / TypeScript
- Real-time chat UI with typing indicators
- CSS Modules
AI/ML
- RAG architecture
- Semantic search with vector embeddings
- Auto-citation system
- AI-generated follow-up questions
DevOps
- Azure cloud hosting
- Vite bundler
- Auth + environment config
Key Features
- Semantic search across 100+ almond industry documents
- Real-time chat with live streaming responses
- Automatic citation generation with superscripts
- Contextual AI follow-up suggestions
- Basic auth-protected access
- Mobile responsive design
Technical Achievements
- Replaced manual document search with real-time AI interface
- Achieved 90%+ reduction in time spent finding information
- Improved answer accuracy with citations
- Built modular and scalable architecture
Business Impact
- Democratized access to industry knowledge
- Accelerated product R&D and decision-making
- Saved time and boosted research efficiency by 90%+