docs/TRACKIO_SPACE_DEPLOYMENT_FIXES.md

Trackio Space Deployment Fixes

Issues Identified

Based on the reference Hugging Face Space structure at yourbench/advanced, the original Trackio Space deployment had several issues:

1. Incorrect File Structure: Not following the proper Hugging Face Spaces format
2. Poor Git Integration: Trying to use git commands incorrectly
3. Missing Required Files: Incomplete template structure
4. Incorrect README Format: Not following HF Spaces metadata format
5. Dependency Issues: Requirements file not properly structured

Fixes Applied

1. Proper Hugging Face Spaces Structure

Before: Files were copied to current directory and pushed via git After: Files are prepared in temporary directory with proper structure

# New approach - proper temp directory handling
temp_dir = tempfile.mkdtemp()
# Copy files to temp directory
shutil.copy2(source_path, dest_path)
# Initialize git in temp directory
os.chdir(temp_dir)
subprocess.run(["git", "init"], check=True)
subprocess.run(["git", "remote", "add", "origin", space_url], check=True)

2. Correct README.md Format

Before: Basic README without proper HF Spaces metadata After: Proper HF Spaces metadata format

---
title: Trackio Experiment Tracking
emoji: 📊
colorFrom: indigo
colorTo: yellow
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: true
license: mit
short_description: Trackio experiment tracking and monitoring interface
---

3. Updated Requirements.txt

Before: Duplicate dependencies and incorrect versions After: Clean, organized dependencies

# Core Gradio dependencies
gradio>=4.0.0
gradio-client>=0.10.0

# Data processing and visualization
pandas>=2.0.0
numpy>=1.24.0
plotly>=5.15.0

# HTTP requests and API
requests>=2.31.0

# JSON handling
jsonschema>=4.17.0

# Hugging Face integration
datasets>=2.14.0
huggingface-hub>=0.16.0

# Environment and configuration
python-dotenv>=1.0.0

# Optional: for better performance
matplotlib>=3.7.0

4. Improved Deployment Script

Key Improvements:

• Proper temporary directory handling
• Better error handling and logging
• Correct git workflow
• Environment variable setup
• Comprehensive testing

class TrackioSpaceDeployer:
    def __init__(self, space_name: str, username: str, token: str):
        self.space_name = space_name
        self.username = username
        self.token = token
        self.space_url = f"https://huggingface.co/spaces/{username}/{space_name}"
    
    def create_space(self) -> bool:
        # Set HF token for CLI
        os.environ['HF_TOKEN'] = self.token
        # Create space with proper error handling
    
    def prepare_space_files(self) -> str:
        # Create temp directory and copy files
        # Update README with actual space URL
    
    def upload_files_to_space(self, temp_dir: str) -> bool:
        # Proper git workflow in temp directory
        # Push to main/master branch

Files Modified

Core Deployment Files

1. scripts/trackio_tonic/deploy_trackio_space.py
   • Complete rewrite following HF Spaces best practices
   • Proper temporary directory handling
   • Better error handling and logging
   • Correct git workflow

Template Files

2. templates/spaces/README.md

   • Updated to proper HF Spaces metadata format
   • Comprehensive documentation
   • API endpoint documentation
   • Troubleshooting guide

3. templates/spaces/requirements.txt

   • Clean, organized dependencies
   • Proper version specifications
   • All required packages included

Test Files

4. tests/test_trackio_deployment.py
   • Comprehensive deployment testing
   • Template structure validation
   • File content verification
   • Deployment script testing

Testing the Deployment

Run Deployment Tests

python tests/test_trackio_deployment.py

Expected output: ``` 🚀 Testing Trackio Space Deployment

🔍 Testing templates structure... ✅ app.py exists ✅ requirements.txt exists ✅ README.md exists

🔍 Testing app.py content... ✅ Found: import gradio as gr ✅ Found: class TrackioSpace ✅ Found: def create_experiment_interface ✅ Found: def log_metrics_interface ✅ Found: def log_parameters_interface ✅ Found: demo.launch()

🔍 Testing requirements.txt content... ✅ Found: gradio>= ✅ Found: pandas>= ✅ Found: numpy>= ✅ Found: plotly>= ✅ Found: requests>= ✅ Found: datasets>= ✅ Found: huggingface-hub>=

🔍 Testing README.md structure... ✅ Found: --- ✅ Found: title: Trackio Experiment Tracking ✅ Found: sdk: gradio ✅ Found: app_file: app.py ✅ Found: # Trackio Experiment Tracking ✅ Found: ## Features ✅ Found: ## Usage ✅ Found: Visit: {SPACE_URL}

🔍 Testing deployment script... ✅ TrackioSpaceDeployer class imported successfully ✅ Method exists: create_space ✅ Method exists: prepare_space_files ✅ Method exists: upload_files_to_space ✅ Method exists: test_space ✅ Method exists: deploy

🔍 Testing temporary directory creation... ✅ Created temp directory: /tmp/tmp_xxxxx ✅ File copying works ✅ Cleanup successful

📊 Test Results: 6/6 tests passed ✅ All deployment tests passed! The Trackio Space should deploy correctly.

### Deploy Trackio Space
```bash
python scripts/trackio_tonic/deploy_trackio_space.py

Key Improvements

1. Proper HF Spaces Structure

• Follows the exact format from reference spaces
• Correct metadata in README.md
• Proper file organization

2. Robust Deployment Process

• Temporary directory handling
• Proper git workflow
• Better error handling
• Comprehensive logging

3. Better Error Handling

• Graceful failure handling
• Detailed error messages
• Fallback mechanisms
• Cleanup procedures

4. Comprehensive Testing

• Template structure validation
• File content verification
• Deployment script testing
• Integration testing

Reference Structure

The fixes are based on the Hugging Face Space structure from yourbench/advanced, which includes:

• Proper README.md with HF Spaces metadata
• Clean requirements.txt with organized dependencies
• Correct app.py structure for Gradio
• Proper git workflow for deployment

Next Steps

1. Test the deployment:

   python tests/test_trackio_deployment.py
   

2. Deploy the Space:

   python scripts/trackio_tonic/deploy_trackio_space.py
   

3. Verify deployment:

   • Check the Space URL
   • Test the interface
   • Verify API endpoints

4. Use in training:

   • Update your training scripts with the new Space URL
   • Test the monitoring integration

The Trackio Space should now deploy correctly and provide reliable experiment tracking for your SmolLM3 fine-tuning pipeline! 🚀