hf_cli_upload.py

#!/usr/bin/env python3
"""
Upload Bengali AI using Hugging Face CLI with environment token
"""

import os
import subprocess

def upload_with_hf_cli():
    """Upload using hf CLI with environment token"""
    
    print("🚀 Uploading Bengali AI with Hugging Face CLI")
    print("=" * 50)
    print("Repository: megharudushi/Sheikh")
    
    # Check if model directory exists
    if not os.path.exists("ready_bengali_ai"):
        print("❌ Error: ready_bengali_ai directory not found!")
        return False
    
    # Show files to upload
    files = os.listdir("ready_bengali_ai")
    print(f"\n📁 Files to upload ({len(files)} total):")
    total_size = 0
    for file in sorted(files):
        size = os.path.getsize(f"ready_bengali_ai/{file}") / (1024*1024)
        total_size += size
        print(f"  📄 {file} ({size:.1f}MB)")
    print(f"📊 Total size: {total_size:.1f}MB")
    
    # Check for token
    token = os.environ.get('HF_TOKEN')
    if not token:
        print("\n❌ No HF_TOKEN environment variable found!")
        print("\n🔧 To upload, you need to:")
        print("1. Get your token from: https://huggingface.co/settings/tokens")
        print("2. Set environment variable:")
        print("   export HF_TOKEN=your_token_here")
        print("3. Then run: hf upload megharudushi/Sheikh .")
        return False
    
    print(f"\n✅ Using token: {token[:8]}...")
    
    try:
        # Set environment variable for hf CLI
        env = os.environ.copy()
        env['HF_TOKEN'] = token
        
        # Upload using hf CLI
        print(f"\n📤 Running: hf upload megharudushi/Sheikh .")
        result = subprocess.run(
            ["hf", "upload", "megharudushi/Sheikh", "."],
            env=env,
            capture_output=True,
            text=True
        )
        
        if result.returncode == 0:
            print("\n🎉 SUCCESS!")
            print("🌐 Your model: https://huggingface.co/megharudushi/Sheikh")
            print("\n💡 Anyone can now use your model:")
            print("from transformers import AutoTokenizer, AutoModelForCausalLM")
            print('tokenizer = AutoTokenizer.from_pretrained("megharudushi/Sheikh")')
            print('model = AutoModelForCausalLM.from_pretrained("megharudushi/Sheikh")')
            return True
        else:
            print(f"❌ Upload failed: {result.stderr}")
            return False
            
    except Exception as e:
        print(f"❌ Upload error: {e}")
        return False

def create_upload_commands():
    """Create upload commands file"""
    
    commands = """# Hugging Face CLI Upload Commands

## Step 1: Get Your Token
1. Go to: https://huggingface.co/settings/tokens
2. Create a new token with "Write" permissions
3. Copy the token (starts with hf_)

## Step 2: Set Token and Upload

### Option A: Set environment variable
```bash
export HF_TOKEN=your_token_here
hf upload megharudushi/Sheikh .
```

### Option B: Pass token directly
```bash
hf upload megharudushi/Sheikh . --token your_token_here
```

### Option C: Login interactively
```bash
hf auth login
# Enter your token when prompted
hf upload megharudushi/Sheikh .
```

## Step 3: Verify Upload
After upload, visit: https://huggingface.co/megharudushi/Sheikh

## Files Being Uploaded
- model.bin (1.4GB) - Main model weights
- tokenizer.json (3.4MB) - Tokenizer configuration
- vocab.json (780KB) - Vocabulary
- merges.txt (446KB) - BPE merges
- config.json (13KB) - Model configuration
- Plus 6 other configuration files
"""
    
    with open("HF_CLI_COMMANDS.md", "w", encoding="utf-8") as f:
        f.write(commands)
    
    print("📄 Created: HF_CLI_COMMANDS.md")

if __name__ == "__main__":
    print("🇧🇩 BANGLI AI - HUGGING FACE CLI UPLOAD")
    print("=" * 45)
    
    # Create commands file
    create_upload_commands()
    
    # Try upload
    success = upload_with_hf_cli()
    
    if not success:
        print("\n🔧 Manual upload required:")
        print("1. Set HF_TOKEN environment variable")
        print("2. Run: hf upload megharudushi/Sheikh .")
        print("\n📖 See HF_CLI_COMMANDS.md for detailed instructions")
    else:
        print("\n🎊 Upload successful! Your Bengali AI is live!")