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AI Cafe Recommender — Portfolio Project

A full-stack portfolio project: an AI-driven, vibe-aware café recommender with map UI, busy-hour detection, and optional auto-order agent.
It uses local embeddings for retrieval and Groq (LLaMA-3) for natural language ranking/explanations — a completely free stack for prototyping.


Features

  • Vibe-based recommendations (top 3) using semantic retrieval + LLM re-ranking
  • Interactive map with Google Maps integration (markers, distances, directions)
  • Busy-hour detection (heuristic + optional external popular-times integration)
  • Auto-order agent (simulated by default; can be wired to real ordering APIs)
  • Local, free embeddings (sentence-transformers) + Groq LLaMA-3 for reasoning

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