🎬 Movie Content Safety Classifier

AI-powered system that determines if a movie is appropriate for children aged 5-10

Built with LangChain, FAISS, and Groq — a complete RAG system with an AI Agent for complex queries.

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✨ Features

Feature	Description
RAG Classification	Semantic search to retrieve relevant safety rules
AI Agent	Answers complex questions using 3 tools
Interactive CLI	Chat-style interface for movie safety queries
Batch Processing	Classify multiple movies at once
Movie Database	30+ movies with details
Knowledge Base	80+ safety Q&A pairs

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🏗️ Architecture

Architecture

USER INTERFACE

[ Interactive CLI ] [ Batch Mode ] [ Agent ]

Retriever
(FAISS)

→

Context
(Top-5 Q&A)

→

LLM
(Groq)

Knowledge Base
(80+ Q&A pairs)

Movie Database (CSV)
(30 movies with details)

User → RAG Chain (Retriever → Context → LLM) → Data Layer (KB + Movies)

Flow: Query → Embedding → FAISS Search → Top-5 Q&A → LLM → Classification

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🚀 Quick Start

Prerequisites

• Python 3.10+
• Groq API key (free) — Get it here

Setup

git clone https://github.com/YOUR_USERNAME/movie-content-safety.git
cd movie-content-safety
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Configure

Create a .env file in the project root:

GROQ_API_KEY=your_api_key_here
GROQ_MODEL=openai/gpt-oss-20b

Note: Get your free Groq API key from console.groq.com

🚀 Run

1. Build the Vector Index

python src/vector_store.py

2. Interactive Movie Classifier

python src/main.py

Example Interaction:

🎬 Enter movie title (or command): The Lion King
📖 Found 'The Lion King' in CSV database!
📝 Year: 1994 | Rating: 8.5 | Genres: Animation, Adventure, Drama

📌 Result:
Classification: Safe for children
Explanation: The movie is animated, family-friendly, and contains no adult content.

3. Batch Classification

python src/main.py --batch --limit 5

4. AI Agent for Complex Queries

python src/agent.py

Example Questions:

• "Can you find me a movie like The Lion King that is appropriate for a 5-year-old?"
• "Is Jurassic Park safe for children?"
• "What are the best family movies in the database?"

📊 Sample Outputs

Agent Response

💭 Your question: What movies are safe for children?

📌 Response:
Here are some movies that are safe for children aged 5-10:

| Movie | Rating | Why it's safe |
|-------|--------|---------------|
| Toy Story | G | Animated, no violence, positive messages |
| Finding Nemo | G | Light-hearted adventure, no scary content |
| Frozen | PG | Positive themes of sisterhood and self-acceptance |
| The Lion King | G | Strong moral lessons, no graphic violence |

Movie Classification

🎬 Enter movie title (or command): The Conjuring
📖 Found 'The Conjuring' in CSV database!
📝 Year: 2013 | Rating: 7.5 | Genres: Horror, Mystery, Thriller

📌 Result:
Classification: Not safe for children
Explanation: The Conjuring is a horror film with a rating of 7.5 (R). It contains supernatural terror, frightening imagery, and intense suspense typical of the horror genre, making it unsuitable for children aged 5-10.

📁 Project Structure

movie-content-safety/
├── data/
│   ├── knowledge_base.csv      # 80+ Q&A safety rules
│   ├── imdb_movies.csv         # 30 movies with details
│   └── faiss_index/            # FAISS vector index
│       ├── index.faiss
│       └── index.pkl
├── src/
│   ├── config.py               # Configuration & API keys
│   ├── vector_store.py         # Build FAISS index
│   ├── rag_chain.py            # RAG pipeline with Groq
│   ├── main.py                 # Interactive CLI
│   └── agent.py                # AI Agent for complex queries
├── .env                        # Environment variables
├── requirements.txt            # Python dependencies
└── README.md                   # This file

🛠️ Tech Stack

Technology	Purpose
LangChain	LLM orchestration framework
FAISS	Vector similarity search
Groq	Fast, free LLM inference
HuggingFace	Embedding models (all-MiniLM-L6-v2)
Python	Core programming language
Pandas	CSV data handling

📦 Dependencies

langchain>=0.3.0
langchain-community>=0.3.0
langchain-core>=0.3.0
langchain-groq>=0.1.0
langchain-huggingface
faiss-cpu
sentence-transformers
pandas
python-dotenv

🔮 Next Steps

• Add web interface (Gradio/Streamlit)
• Add evaluation framework (evals)
• Deploy to production
• Expand knowledge base to 500+ movies
• Add user feedback loop

📫 Let's Connect!

If you found this project interesting, feel free to reach out!

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