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Osman Furkan Küçük

Agentic RAG Advisor for Health & Culture Tourism

A RAG assistant that answers questions about health and culture tourism.

  • Python
  • LangGraph
  • vLLM
  • Qdrant
  • Redis
  • RabbitMQ
  • FastAPI
  • Next.js
  • Docker
01

Approach

An agent that classifies intent, retrieves, checks its own evidence and only then answers.

  • Intent classification routes each query before retrieval.
  • Hybrid dense + sparse retrieval with Reciprocal Rank Fusion (RRF).
  • Retrieval grading with re-query.
  • Generation on vLLM, streamed to the client over SSE.
  • Model side: RAG-aware SFT data and QLoRA fine-tuning, evaluated with RAGAS.
02

Architecture

Fig. 1Agentic RAG pipeline, orchestrated with LangGraph. The accent-bordered step is the agent’s decision point.