docs/structure.md

🏗️ Project Structure

├── app.py                   # Main FastAPI app entrypoint
├── config.py                # Configuration loader (.env, settings)
├── features/
│   ├── text_classifier/     # English (GPT-2) classifier
│   │   ├── controller.py
│   │   ├── inferencer.py
│   │   ├── model_loader.py
│   │   ├── preprocess.py
│   │   └── routes.py
│   └── nepali_text_classifier/ # Nepali (sentencepiece) classifier
│       ├── controller.py
│       ├── inferencer.py
│       ├── model_loader.py
│       ├── preprocess.py
│       └── routes.py
├── np_text_model/           # Nepali model artifacts (auto-downloaded)
│   ├── classifier/
│   │   └── sentencepiece.bpe.model
│   └── model_95_acc.pth
├── models/                  # English GPT-2 model/tokenizer (auto-downloaded)
│   ├── merges.txt
│   ├── tokenizer.json
│   └── model_weights.pth
├── Dockerfile               # Container build config
├── Procfile                 # Deployment entrypoint (for PaaS)
├── requirements.txt         # Python dependencies
├── README.md     
├── Docs                     # documents
└── .env                     # Secret token(s), environment config

🌟 Key Files and Their Roles

• app.py: Entry point initializing FastAPI app and routes.
• Procfile: Tells Railway (or similar platforms) how to run the program.
• requirements.txt: Tracks all Python dependencies for the project.
• __init__.py: Package initializer for the root module and submodules.
• features/text_classifier/
  • controller.py: Handles logic between routes and the model.
  • inferencer.py: Runs inference and returns predictions as well as file system utilities.
• features/NP/
  • controller.py: Handles logic between routes and the model.
  • inferencer.py: Runs inference and returns predictions as well as file system utilities.
  • model_loader.py: Loads the ML model and tokenizer.
  • preprocess.py: Prepares input text for the model.
  • routes.py: Defines API routes for text classification.

-Main