MoodMatcher is a web app that analyzes your mood and recommends a movie based on how you feel. It uses a Node.js/Express backend, a modern HTML/CSS/JS frontend, and integrates with Groq and Firebase for authentication and AI-powered recommendations.

• Maintainer: Sarah Kazi

• AI Mood Analysis: Uses Groq's Llama-3.3 model to interpret your text input and identify key emotions like Happy, Sad, Anxious, and more.
• Personalized Recommendations: Get movie suggestions (Hollywood or Bollywood) tailored to your mood, complete with a description and a reason for the match.
• "Surprise Me" Mode: Feeling adventurous? Get a completely random and unexpected movie recommendation with a single click.
• Voice Input: Speak your mood directly into the app using your browser's built-in speech recognition capabilities.
• User Authentication: Secure sign-up and login with email/password or Google, powered by Firebase.
• Mood History & Trends: Track your past moods and view your emotional trends over time with an interactive doughnut chart.
• Movie Trailers: Instantly watch the official movie trailer directly within the app, fetched from the YouTube API.
• User Profile: View your personal stats, including total movies watched and your most frequent moods.
• Modern UI: A sleek, responsive, and animated user interface with both light and dark themes.

• Frontend: HTML5, CSS3, Vanilla JavaScript
• Backend: Node.js, Express.js
• AI: Groq API (llama-3.3-70b-versatile model)
• Authentication: Firebase Authentication
• APIs: YouTube Data API
• Libraries: Chart.js for data visualization

Follow these instructions to get a copy of the project up and running on your local machine for development and testing purposes.

• Node.js and npm installed on your machine.

1. Clone the repository:

   git clone https://github.com/sarah-kazi/mood_movie.git
   cd mood_movie

2. Install NPM packages:

   npm install

3. Set up environment variables: Create a .env file in the root directory by copying the example file:

   cp .env.example .env

   Now, open the .env file and add your secret keys and configuration values. You will need API keys/credentials for:

   • Groq API
   • Firebase (for authentication)
   • YouTube Data API

   # .env
   GROQ_API_KEY=your-groq-api-key-here
   
   FIREBASE_PROJECT_ID=your_firebase_project_id
   FIREBASE_PRIVATE_KEY_ID=your_firebase_private_key_id
   FIREBASE_PRIVATE_KEY="-----BEGIN PRIVATE KEY-----\nYour private key here\n-----END PRIVATE KEY-----\n"
   FIREBASE_CLIENT_EMAIL=your_firebase_client_email
   FIREBASE_CLIENT_ID=your_firebase_client_id
   # ... other Firebase variables from .env.example
   
   YOUTUBE_API_KEY=your_youtube_api_key_here
   
   PORT=3000

   Create a firebaseconfig.js file in the public directory by copying the below format:

   // Replace with your own Firebase config
    const firebaseConfig = {
      apiKey: "",
      authDomain: "",
      projectId: "",
      storageBucket: "",
      messagingSenderId: "",
      appId: "",
      measurementId: ""
    };
    export default firebaseConfig;

You have a few options to run the server, based on the scripts in package.json:

• Demo Mode (No API Keys Required): This script runs a demo version of the application.

  npm run quick

• Development Mode: This command starts the server using nodemon, which will automatically restart the server whenever you make changes to the code.

  npm run dev

• Production Mode: This command starts the server in a standard way.

  npm start

Once the server is running, open your browser and navigate to http://localhost:3000.

• Check out CONTRIBUTING.md for details regarding how to contribute to each module.

The backend server provides the following RESTful API endpoints, which are protected by Firebase authentication.

This project is licensed under the MIT License.