README.md

metadata

title: CreatorStudio AI Backend Develop
emoji: 🚀
colorFrom: blue
colorTo: indigo
sdk: docker
pinned: false

CreatorStudio AI Backend

CreatorStudio AI is a powerful, enterprise-grade AI content generation and study platform. It leverages state-of-the-art Large Language Models (LLMs) and cloud infrastructure to transform documents and media into a wide array of educational and creative content.

🚀 Features

• 🔐 Robust Authentication: Secure JWT-based authentication system with password hashing and user-scoped data access.
• 📂 Source Management: Integrated AWS S3 file management for seamless document uploads, listing, and storage.
• 🧠 Advanced RAG (Retrieval-Augmented Generation): Chat with your uploaded documents using Azure AI Search and OpenAI/Gemini, enabling high-precision context-aware interactions.
• 🎙️ Podcast Generation: Automatically transform text and documents into professional podcast scripts and audio segments.
• 🎬 Video Generation: Create engaging video summaries and slide-based videos from static content using MoviePy and FFmpeg.
• 📝 Interactive Study Tools:
  • Flashcards: AI-generated flashcards tailored to your source material.
  • Quizzes: Customizable quizzes with multiple-choice questions, hints, and detailed explanations.
  • Mind Maps: Visualize complex relationships with auto-generated Mermaid.js mind maps.
• 📊 Smart Reports: Generate structured, professional reports and summaries from various source materials.

🛠️ Tech Stack

• Framework: FastAPI (Python 3.x)
• Database: SQLAlchemy ORM with support for relational databases (e.g., MSSQL/PostgreSQL).
• AI Infrastructure:
  • LLMs: OpenAI GPT-4o, Google Gemini Pro.
  • RAG: Azure AI Search, Azure OpenAI Embeddings.
• Cloud & Processing:
  • Storage: AWS S3, Azure Blob Storage.
  • Media: MoviePy, FFmpeg, Pydub for audio/video processing.
  • Documents: PyPDF2, pdf2image, Pillow for comprehensive document handling.

📁 Project Structure

CreatorStudio AI/
├── api/                # FastAPI routers and endpoint logic
│   ├── auth.py         # Authentication & User management
│   ├── sources.py      # S3 Source file management
│   ├── rag.py          # Azure RAG indexing and querying
│   ├── podcast.py      # Podcast generation endpoints
│   ├── flashcards.py   # Flashcard generation logic
│   └── ...             # Quizzes, Mindmaps, Reports, Video Gen
├── core/               # Core application configuration
│   ├── config.py       # Pydantic settings & Environment management
│   ├── database.py     # DB connection & Session management
│   ├── prompts.py      # Centralized AI prompt templates
│   └── security.py     # JWT & Password hashing utilities
├── models/             # Data models
│   ├── db_models.py    # SQLAlchemy database models (User, Source, RAG, etc.)
│   └── schemas.py      # Pydantic request/response schemas for API
├── services/           # Business logic & 3rd party integrations
│   ├── s3_service.py   # AWS S3 integration
│   ├── rag_service.py  # Azure AI Search & RAG logic
│   ├── podcast_service.py # Podcast creation & script logic
│   ├── video_generator_service.py # Video processing
│   └── ...             # Specialized services for all features
├── main.py             # Application entry point & Router inclusion
└── requirements.txt    # Project dependencies

⚙️ Setup & Installation

1. Clone the repository
2. Create a Virtual Environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install Dependencies:

   pip install -r requirements.txt
   

4. Configure Environment Variables: Create a .env file in the root directory based on the following template:

   # AWS Configuration
   AWS_ACCESS_KEY_ID=your_aws_key
   AWS_SECRET_ACCESS_KEY=your_aws_secret
   AWS_S3_BUCKET=your_bucket_name
   
   # Azure RAG & OpenAI
   AZURE_SEARCH_ENDPOINT=your_endpoint
   AZURE_SEARCH_KEY=your_search_key
   AZURE_OPENAI_API_KEY=your_openai_key
   AZURE_OPENAI_ENDPOINT=your_openai_endpoint
   
   # LLM Keys
   OPENAI_API_KEY=your_openai_key
   GEMINI_API_KEY=your_gemini_key
   
   # Database & Security
   DATABASE_URL=your_db_connection_string
   SECRET_KEY=your_jwt_secret_key
   

5. Run the Server:

   python main.py
   

   The API will be available at http://localhost:8000. Access the interactive documentation at http://localhost:8000/docs.

📖 API Documentation

The backend provides a fully interactive Swagger UI at /docs for testing and exploration.

• Auth: /api/auth/register, /api/auth/login
• Sources: /api/sources/upload, /api/sources/list, /api/sources/{id}
• RAG: /api/rag/index, /api/rag/query
• Content Generation: /api/podcast, /api/flashcards, /api/mindmaps, /api/quizzes, /api/reports, /api/video_generator

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© 2026 CreatorStudio AI Team. All rights reserved.