A streamlined offering generation system for the SEDIMARK infrastructure. This toolbox runs on QWEN-7B model and utilizes PEFT fine-tuning to produce SEDIMARK-compliant JSON-LD offerings. The weights for the models are here and are expected to be in the models/ directory.

# Clone the repository git clone https://github.com/sedimark/offering-generator.git # Clone or copy this directory cd offering-generator # Install dependencies pip install -r requirements.txt

Place your PEFT checkpoint in the models/ directory. The expected structure would look something like this:

offering-generator/ └── models/ └── checkpoint-40/ ├── adapter_config.json ├── adapter_model.safetensors └── tokenizer.json 

Update config.py if your checkpoint path differs.

python run_api.py

The API will be available at http://localhost:8082

python run_gradio.py

The interface will be available at http://localhost:7860

sedimark-clean/ ├── api.py # FastAPI server ├── gradio_app.py # Gradio interface ├── model_loader.py # Model loading utilities ├── offering_generator.py # Core offering generation logic ├── config.py # Configuration ├── run_api.py # API runner script ├── run_gradio.py # Gradio runner script ├── requirements.txt # Dependencies ├── README.md # This file ├── models/ # Model checkpoints (create this) └── outputs/ # Generated offerings (auto-created) 

Edit config.py to customize:

• Model paths and checkpoint locations
• Generation parameters (temperature, top_p, etc.)
• Server ports and settings
• Output directories

• GET / - Service information
• POST /generate - Generate offering with detailed control
• GET /api/offerings/generate - Simple generation endpoint
• GET /health - Health check
• GET /api/offerings/list - List generated offerings

# Simple generation curl "http://localhost:8082/api/offerings/generate?prompt=Generate%20IoT%20sensor%20offering" # Advanced generation curl -X POST "http://localhost:8082/generate" \ -H "Content-Type: application/json" \ -d '{  "prompt": "Generate a SEDIMARK offering for smart city sensors",  "temperature": 0.1,  "max_new_tokens": 4096,  "use_schema": false  }'

from offering_generator import SEDIMARKOfferingGenerator from model_loader import ModelLoader # Initialize loader = ModelLoader() loader.load_model() generator = SEDIMARKOfferingGenerator(loader) # Generate offering = generator.generate_offering( prompt="Generate offering for temperature sensors in Tokyo", use_context=False, temperature=0.1 ) print(json.dumps(offering, indent=2))

# Generate multiple offerings curl "http://localhost:8082/api/offerings/generate?count=3&prompt=Smart%20city%20data"

This clean implementation provides the same powerful SEDIMARK generation capabilities with dramatically reduced complexity, making it ideal for production deployment.