Festive Flix - RAG Holiday Movie Search

Semantic search for holiday movies using Django, MongoDB Atlas, and Voyage AI embeddings. Uses Retrieval Augmented Generation (RAG) to find movies by meaning rather than keywords.

Quick Setup

Prerequisites: Python 3.8+, MongoDB Atlas account, Voyage AI API key

1. Clone & install:

git clone <repository-url> && cd django-rag
python -m venv venv && source venv/bin/activate
pip install -r requirements.txt && pip install django==5.2.7

2. Configure - Create .env:

VOYAGE_API_KEY=your_api_key
MONGO_URI=your_mongodb_connection_string

3. Load data:

python json_upload.py
python langchain_integration.py

4. Run:

python manage.py runserver
# Visit http://127.0.0.1:8000/search/

How It Works

Converts movie plots to vector embeddings using Voyage AI, stores them in MongoDB with vector index, then searches by semantic similarity. Example queries: "magical Christmas story" or "angel helps someone in need".

Tech Stack

• Django 5.2.7 - Web framework
• MongoDB Atlas - Used as both operation and vector database
• Voyage AI - Embeddings model (voyage-3-lite)
• LangChain - Framework for building AI applications

Key Files

• json_upload.py - Load movies into MongoDB
• langchain_integration.py - Generate embeddings
• festive_flix/views.py - Search logic
• holiday_movies.json - Sample dataset

Troubleshooting

Missing API key: Ensure .env has VOYAGE_API_KEY and MONGO_URI

No results: Run both json_upload.py and langchain_integration.py

Vector index error: Create vector search index in MongoDB Atlas named vector_index

Disclaimer

Use at your own risk; not a supported MongoDB product