README.md

metadata

title: VEN - AI Restaurant Matchmaker
emoji: 🍔
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 4.19.2
app_file: app.py
pinned: false
license: mit

🍔 VEN: Semantic Restaurant Discovery System

VEN is an AI-powered recommendation engine designed to find the perfect restaurant in Tel Aviv based on user context, vibe, and specific preferences.

Unlike traditional filters (e.g., "Italian", "Thai"), VEN uses Semantic Search and Persona Matching to understand the intent behind the search (e.g., "A romantic quiet place for a date" vs. "Lively place for drinks with friends").

🚀 Key Features

• Semantic Search: Uses Sentence-Transformers (NLP) to convert user preferences into vector embeddings.
• Persona Matching: Instead of simple keyword matching, the system identifies the user's "Persona" (Reviewer Type) based on their inputs and finds restaurants loved by similar people.
• Smart Filtering: Filters by Budget, Diet, Company, Occasion, and Noise Level.
• One-Click Quick Starters: Pre-configured scenarios for instant recommendations.
• Dark Mode UI: A sleek, modern user interface built with Gradio.

🛠️ Tech Stack

• Python
• Gradio: For the web interface.
• Sentence-Transformers (all-mpnet-base-v2): For generating high-quality text embeddings.
• Scikit-Learn: For calculating Cosine Similarity between user input and reviewer profiles.
• Pandas & NumPy: For data manipulation and vector operations.

🧠 How It Works

1. Input: The user selects their preferences (Budget, Diet, Company, Occasion, Atmosphere).
2. Vectorization: The system creates a textual description of the user's desire and converts it into a mathematical vector using the all-mpnet-base-v2 model.
3. Persona Clustering: The system compares the user's vector against pre-calculated "Taste Profiles" (Personas) derived from the dataset.
4. Similarity Search: It calculates the Cosine Similarity to find the closest match.
5. Ranking: The system ranks restaurants within that Persona cluster and returns the highest-rated match with a relevant review.

🖼️ More Screenshots

Recommendation Card	Filter Settings	Search Results

👥 Authors

• Gal - Data Scientist & Developer
• Matan - Data Scientist & Developer