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AI-powered movie and series search engine with plot summaries, cast info, spoiler-safe explanations, and real-time “where to watch” links. Built using Groq-Ms, TMDB, and a modern web stack.

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MovieMonk 🎬

MovieMonk is an AI-powered movie and TV show discovery platform that provides accurate summaries, real-time data, and comprehensive details about your favorite titles. By combining the power of TMDB, IMDB, and advanced AI models (Groq, Mistral, OpenRouter), MovieMonk delivers a rich, spoiler-free, and interactive experience.

Live Demo License: MIT


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Features

MovieMonk stands out by integrating verified database information with generative AI context:

  • Verified Data Sources: Pulls cast, crew, ratings, and release info directly from TMDB and OMDB.
  • AI-Generated Summaries: Utilizes cutting-edge LLMs (via Groq & Mistral) to generate custom plot summaries, trivia, and analysis.
  • Streaming Availability: Instantly find where to watch movies/shows on platforms like Netflix, Prime Video, and others.
  • Search-First Architecture: Features a robust search system powered by Google Search (SerpApi) to handle complex queries, regional titles (Malayalam, Tamil, Telugu, etc.), and disambiguation.
  • Cinematic UI: A modern, responsive "Cyberpunk/Dark" aesthetic with glassmorphism effects and smooth animations.
  • Smart Disambiguation: Handles ambiguous queries (e.g., "RRR") by presenting a Google-like result list before processing with AI.

Architecture

The application is built on a modern stack focusing on performance and type safety:

  • Frontend: React (Vite) + TypeScript
  • Styling: Custom CSS variables with a semantic design system (no heavy frameworks)
  • Data Layer:
    • TMDB API: Primary source for structured movie metadata.
    • SerpApi (Google Search): Fallback/Enrichment layer for finding obscure or regional titles.
    • Perplexity AI: Tertiary fallback for deep web context.
  • AI Layer:
    • Groq: High-speed inference for movie summaries (Llama 3).
    • Mistral: Specialized model for person/biography data.
    • OpenRouter: Fallback for complex reasoning tasks.
  • Infrastructure: Vercel Serverless Functions

Setup & Installation

Follow these steps to run MovieMonk locally:

1. Clone the Repository

git clone https://github.com/mfscpayload-690/moviemonk-ai.git
cd moviemonk-ai

2. Install Dependencies

npm install

3. Configure Environment Variables

Create a .env.local file in the root directory. You will need API keys for the services used.

# Core Data APIs
TMDB_API_KEY=your_tmdb_key
OMDB_API_KEY=your_omdb_key
SERPAPI_KEY=your_serpapi_key

# AI Providers
GROQ_API_KEY=your_groq_key
MISTRAL_API_KEY=your_mistral_key
OPENROUTER_API_KEY=your_openrouter_key
PERPLEXITY_API_KEY=your_perplexity_key

4. Run Development Server

npm run dev

The application will be available at http://localhost:3000.

5. Production Build

To build the application for production:

npm run build

Contributing

We welcome contributions to MovieMonk!

  1. Fork the repository.
  2. Create a feature branch: git checkout -b feature/new-feature
  3. Commit your changes: git commit -m 'Add new feature'
  4. Push to the branch: git push origin feature/new-feature
  5. Submit a Pull Request.

License

This project is licensed under the MIT License.

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AI-powered movie and series search engine with plot summaries, cast info, spoiler-safe explanations, and real-time “where to watch” links. Built using Groq-Ms, TMDB, and a modern web stack.

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