🎥 Movie Recommendation Chatbot

This is a chatbot that provides movie recommendations based on user input, such as a genre (e.g., Action, Comedy) or an actor's name (e.g., Leonardo DiCaprio). The chatbot leverages the OMDb API, NLP techniques, and FastAPI to deliver personalized movie suggestions.
We are also working on integrating Wikipedia to enhance the information provided about movies, genres, and actors.

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🚀 Features

• Accepts queries like:
  • "Recommend some action movies."
  • "Show me movies starring Leonardo DiCaprio."
• Fetches movie data (title, plot, genre, rating, etc.) from the OMDb API.
• Uses NLP to extract entities (genre, actor) from user input.
• Provides up to 5 or 10 movie recommendations per query.
• Built with FastAPI for fast, asynchronous performance.
• Upcoming Feature: Wikipedia integration for detailed information about movies, genres, and actors.

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🛠️ Tech Stack

• Python: Core programming language.
• FastAPI: Framework for building the chatbot backend.
• spaCy: For natural language processing (NLP).
• FuzzyWuzzy: For fuzzy matching of actor names.
• OMDb API: For fetching movie data.
• Uvicorn: ASGI server to run the FastAPI application.
• Wikipedia API (In Progress): To fetch additional details about movies and related topics.

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📂 Project Structure

movie-recommendation-chatbot/
├── app.py               # Main application file
├── static/              # Static assets for UI (e.g., index.html)
│   └── index.html
├── movie_utils.py       # Movie recommendation logic
├── nlp_utils.py         # NLP-related logic for user queries
├── requirements.txt     # Dependencies
├── README.md            # Project overview
└── config.py            # (Excluded in GitHub) Contains API keys

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⚙️ Prerequisites

1. Python 3.9 or higher: Ensure Python is installed.
2. OMDb API Key: Get an API key from OMDb API. - Get Your Key With In Hour !!!!!

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🔧 Setup Instructions

1. Clone the Repository:

   git clone https://github.com/R-Mahesh45/movie-recommendation-chatbot.git
   cd movie-recommendation-chatbot

2. Install Dependencies: Use the requirements.txt file to install dependencies.

   pip install -r requirements.txt

3. Set Up API Keys: Create a config.py file in the project root and add:

   OMDB_API_KEY = "your_api_key_here" - i have removed mine 
   OMDB_API_URL = "http://www.omdbapi.com/"

4. Run the Application: Start the FastAPI application using Uvicorn.

   uvicorn app:app --reload

   The app will run at: http://127.0.0.1:8000

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🖥️ How to Use

1. Open your browser and navigate to http://127.0.0.1:8000/static/index.html.
2. Enter your query, such as:
   • "Show me some action movies."
   • "What are the top 5 Leonardo DiCaprio movies?"
3. The chatbot will respond with movie recommendations.

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✨ Example Output

User Input: "Recommend some action movies."
Bot Output:

Here are the top action movies:
1. The Dark Knight (2008)
   - Genre: Action, Crime, Drama
   - IMDb Rating: 9.0
   - Plot: When the menace known as The Joker wreaks havoc...
   - Starring: Christian Bale, Heath Ledger

2. Inception (2010)
   - Genre: Action, Adventure, Sci-Fi
   - IMDb Rating: 8.8
   - Plot: A thief who steals corporate secrets...
   - Starring: Leonardo DiCaprio, Joseph Gordon-Levitt

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🛠️ Key Functions

1. Movie Recommendation (movie_utils.py)

Fetches movies from the OMDb API and provides detailed information, including:

• Title, genre, plot, actors, rating, and poster.

2. Natural Language Processing (nlp_utils.py)

• Extracts genres and actors using spaCy.
• Fuzzy matches actor names using FuzzyWuzzy.

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🚀 Future Enhancements

• Add support for director-based queries.
• Improve recommendations using collaborative filtering or content-based algorithms.
• Deploy the chatbot to a live server (e.g., AWS, Heroku).
• Enhance the UI for better user experience.
• Wikipedia Integration: Fetch in-depth information about movies, genres, and actors directly from Wikipedia.

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🖋️ License

This project is licensed under the MIT License. Feel free to use and modify it!

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💬 Feedback

If you have suggestions or feedback, feel free to open an issue or contribute to the project. Your input is appreciated!