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Devansh959/Zomato-AI-Recommender

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App README

Zomato AI Recommender

Zomato UI Showcase Python FastAPI Streamlit

An AI-powered restaurant recommendation engine featuring a premium, futuristic dark-mode UI inspired by Zomato. This full-stack application utilizes a FastAPI backend to handle complex filtering logic and integrates an LLM (Groq) for intelligent, context-aware personalized dining suggestions.

✨ Features

  • —Intelligent Recommendations: Uses Large Language Models (LLM) to analyze your specific preferences (e.g., "Must have a great view, family-friendly") and provides personalized reasoning for each suggestion.
  • —Advanced Filtering: Filter by Location, Cuisine, Max Budget, and Minimum Rating.
  • —Premium UI/UX: A carefully crafted dark-theme frontend with deep blacks, Zomato's signature red and gold accents, micro-animations, and tactile depth.
  • —High-Performance Backend: Built with FastAPI for rapid, asynchronous API endpoints.
  • —Automated Setup: Easily spin up both frontend and backend services concurrently with a single script.

🛠️ Tech Stack

  • —Frontend: Streamlit, Custom HTML/CSS/JS (Vanilla CSS without Tailwind), Base64 Image Processing
  • —Backend: FastAPI, Python
  • —AI / LLM: Groq API Integration
  • —Database: SQLite (local dataset ingestion)
  • —Typography: DM Sans, Playfair Display, Metropolis

🚀 Getting Started

Prerequisites

  • —Python 3.8 or higher
  • —Git (optional, for cloning)
  • —An active Groq API Key

Installation

  1. 1.Clone the repository:
bash
   git clone https://github.com/Devansh959/Zomato_AI_Recommend.git
   cd Zomato_AI_Recommend
  1. 1.Set up a Virtual Environment:
bash
   python -m venv venv
   # On Windows
   venv\Scripts\activate
   # On macOS/Linux
   source venv/bin/activate
  1. 1.Install Dependencies:
bash
   pip install -r requirements.txt
  1. 1.Environment Variables: Ensure you have a .env file in the root directory containing your API keys and configuration:
env
   GROQ_API_KEY=your_groq_api_key_here

Running the Application

The project includes a convenient batch script to launch both the FastAPI backend and the Streamlit frontend simultaneously.

Simply run:

bash
.\run_all.bat

(Alternatively, you can run the services manually in separate terminal windows.)

  • —The FastAPI Backend will run on: http://localhost:8000
  • —The Streamlit Frontend will run on: http://localhost:8501

To stop the servers, you can run .\stop_servers.bat if available, or manually terminate the processes in your terminal (Ctrl+C).

🎨 Design Philosophy

The frontend was designed with a "Premium Zomato Dark Theme" aesthetic. It explicitly avoids flat SaaS styling in favor of:

  • —Layered Surfaces: Subtle background gradients and glassmorphism.
  • —Tactile Depth: Glow effects (--shadow-neon) on active inputs and hover states.
  • —Typography: Serif headings (Playfair Display) paired with clean sans-serif body text (DM Sans / Metropolis).
  • —Custom Branding: Pure CSS Zomato logo injection for high-fidelity rendering.

📝 License

This project is open-source and available under the MIT License.