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Yeonsoo101/README.md

Yeonsoo Jang

Building practical LLM applications — RAG, agentic systems, and the production engineering around them.

What I'm building

  • pension-rag — Q&A chatbot over Aviva and UK gov pension documents. Hybrid BM25 + vector retrieval with Cohere reranking, ChromaDB, served via FastAPI with a Next.js frontend.
  • GDG_AI_DEV_CAMP_2026 — Multi-agent systems coursework; capstone is a culture concierge full-stack agent app.
  • ai_driving_route_planner — Streamlit app that finds round-trip driving routes with parking-friendly stops, using Google Places, OpenRouteService, and GPT review classification.

Focus areas

RAG · agent patterns · prompt engineering · LLM evaluation · production concerns (latency, cost, safety, observability)

Contact

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  1. ai-driving-route-planner ai-driving-route-planner Public

    Streamlit app that finds round-trip driving routes with parking-friendly stops, using Google Places, OpenRouteService, and GPT review classification.

    Python

  2. GDG_AI_DEV_CAMP_2026 GDG_AI_DEV_CAMP_2026 Public

    AI DevCamp 2026_materials and assignments

    HTML

  3. pension-rag pension-rag Public

    Aviva pension Q&A RAG chatbot — FastAPI + Next.js + ChromaDB + OpenAI/Cohere

    Python