AI Restaurant Assistant

A modern, full-stack restaurant discovery assistant powered by AI. Built with React, TypeScript, FastAPI, and OpenAI's GPT-4o, this application helps users find and explore restaurants through an intuitive chat interface.

📸 Images

Main chat interface with Chef Ava

Multiple restaurant recommendations with detailed information

Multi-conversation management

🌟 Key Features

Intelligent Restaurant Discovery

• Personal AI-powered restaurant assistant (Chef Ava) that understands natural language queries
• Detailed restaurant information including photos, ratings, reviews, hours, and pricing
• Integration with Yelp's API for comprehensive and up-to-date restaurant data
• Visual restaurant cards with multiple photos and interactive navigation

Multi-Conversation Management

• Support for creation of different conversations
• Conversation sidebar for easy navigation between chats
• Auto-saving conversations
• Ability to delete or switch between conversations
• Conversation persistence across sessions

User Authentication & Personalization

• Google account integration for secure authentication
• Personal conversation history tied to user accounts
• Separate conversation spaces for different users
• Profile picture and name integration from Google account

Chat Features

• Real-time streaming responses
• Message editing and deletion capabilities
• Fullscreen mode for better visibility
• Minimizable chat widget
• Markdown support in responses

🛠️ Tech Stack

Frontend

• React 18 with TypeScript
• TailwindCSS
• Google OAuth

Backend

• Python 3.11+
• FastAPI
• SQLite
• OpenAI API
• Yelp Fusion API

🚀 Getting Started

Prerequisites

• Node.js 18+
• Python 3.11+
• pip
• OpenAI API key
• Google OAuth credentials
• Yelp API key

Installation

1. Clone the repository:

git clone https://github.com/yourusername/restaurant-assistant.git
cd restaurant-assistant

2. Create and Activate New Virtual Env

python3.12 -m venv venv

source venv/bin/activate  # On Unix/MacOS
# or
.\venv\Scripts\activate  # On Windows

3. Setup Backend:

cd backend
pip install -r requirements.txt

4. Create your .env file in the backend directory:

# backend/.env
touch .env

5. Add API keys inside .env file:

OPENAI_API_KEY=your_openai_key
GOOGLE_CLIENT_ID=your_google_client_id
YELP_API_KEY=your_yelp_api_key

6. Start Backend Server

uvicorn app.main:app --reload

7. In a new termial - Setup Frontend:

source venv/bin/activate  # On Unix/MacOS
# or
.\venv\Scripts\activate  # On Windows

cd frontend
npm install
npm run dev

The application will be available at:

• Frontend: http://localhost:5173
• Backend: http://localhost:8000
• API Docs: http://localhost:8000/docs

🔒 Security Features

• Google OAuth2 authentication
• CORS protection

📚 API Documentation

Key Endpoints

Authentication

• POST /api/auth/google-login: Google OAuth login

Messages

• POST /api/messages/stream: Stream chat messages
• PUT /api/messages/{message_id}: Update message
• DELETE /api/messages/{message_id}: Delete message

Conversations

• GET /api/messages/conversations: Get user conversations
• POST /api/messages/new-conversation: Create new conversation
• DELETE /api/messages/conversations/{conversation_id}: Delete conversation

Restaurant Search

• GET /api/yelp/businesses/search: Search restaurants
• GET /api/yelp/businesses/{business_id}: Get business details

Full API documentation is available at /docs when running the backend server.

👨‍💻 Contributors

• Gabriel Mendonca (gmunhoz0810) -> GitHub | LinkedIn