#!/usr/bin/env python3
"""
Upload Bengali AI model to Hugging Face Hub
Repository: megharudushi/Sheikh
"""

import os
from huggingface_hub import HfApi, create_repo, upload_folder
from huggingface_hub.utils import RepositoryNotFoundError

def upload_model_to_hf():
    """Upload the Bengali AI model to Hugging Face"""
    
    print("🚀 Uploading Bengali AI to Hugging Face Hub...")
    print("=" * 50)
    
    # Initialize Hugging Face API
    api = HfApi()
    
    # Repository details
    repo_id = "megharudushi/Sheikh"
    local_dir = "./ready_bengali_ai"
    
    # Check if local directory exists
    if not os.path.exists(local_dir):
        print(f"❌ Error: Directory {local_dir} not found!")
        return False
    
    try:
        # Login prompt
        print("📝 Please login to Hugging Face Hub")
        print("This will open your browser for authentication...")
        
        # Login (this will prompt for token)
        api.login()
        
        print(f"🔗 Creating repository: {repo_id}")
        
        # Create repository
        try:
            repo_url = create_repo(
                repo_id=repo_id,
                exist_ok=True,
                repo_type="model"
            )
            print(f"✅ Repository created/accessed: {repo_url}")
        except Exception as e:
            print(f"⚠️ Repository creation issue: {e}")
            print("Continuing with upload...")
        
        print(f"📤 Uploading model files from {local_dir}...")
        
        # Upload all files
        upload_folder(
            folder_path=local_dir,
            repo_id=repo_id,
            commit_message="Upload complete Bengali AI model with tokenizer and config"
        )
        
        print("🎉 Model uploaded successfully!")
        print(f"🌐 View your model at: https://huggingface.co/{repo_id}")
        
        # Show repository info
        print("\n📊 Repository Information:")
        print(f"  Repository ID: {repo_id}")
        print(f"  Local files: {len(os.listdir(local_dir))} files")
        print(f"  Model size: {os.path.getsize(f'{local_dir}/model.bin') / (1024*1024*1024):.2f} GB")
        
        return True
        
    except Exception as e:
        print(f"❌ Upload failed: {e}")
        print("\n🔧 Troubleshooting:")
        print("1. Make sure you're logged in to Hugging Face")
        print("2. Check your internet connection")
        print("3. Verify repository permissions")
        return False

def create_model_card():
    """Create a model card for the repository"""
    
    model_card = """# Bengali AI Model

## Model Description

This is a Bengali (Bangla) language AI model trained on instruction-following datasets. The model can understand and respond to Bengali text queries.

## Model Details

- **Base Model**: microsoft/DialoGPT-medium
- **Language**: Bengali (Bangla)
- **Parameters**: 355M
- **Training Data**: Alpaca Bangla dataset
- **Model Size**: 1.4GB

## Usage

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

# Load model
tokenizer = AutoTokenizer.from_pretrained("megharudushi/Sheikh")
model = AutoModelForCausalLM.from_pretrained("megharudushi/Sheikh")

# Generate response
input_text = "বাংলাদেশের রাজধানী কী?"
inputs = tokenizer.encode(input_text, return_tensors="pt")
outputs = model.generate(inputs, max_length=150, temperature=0.8)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
```

## Training Details

- Trained on Bengali instruction-following data
- Fine-tuned for educational and general knowledge queries
- Supports Bengali language understanding and generation

## License

Please check the repository for license information.

## Citation

If you use this model in your research, please cite the original base model and dataset sources.
"""
    
    with open("./ready_bengali_ai/README.md", "w", encoding="utf-8") as f:
        f.write(model_card)
    
    print("📄 Created model card (README.md)")

if __name__ == "__main__":
    print("🇧🇩 BANGLI AI HUGGING FACE UPLOAD")
    print("=" * 40)
    
    # Create model card
    create_model_card()
    
    # Upload to Hugging Face
    success = upload_model_to_hf()
    
    if success:
        print("\n🎉 UPLOAD COMPLETE!")
        print("Your Bengali AI model is now live on Hugging Face Hub!")
        print("Repository: https://huggingface.co/megharudushi/Sheikh")
    else:
        print("\n❌ Upload failed. Please check the error messages above.")