HF_SPACES_DEPLOYMENT.md

Hugging Face Spaces Deployment Guide - HonestAI

🚀 Deployment to HF Spaces

This guide covers deploying the updated HonestAI application to Hugging Face Spaces.

📋 Pre-Deployment Checklist

✅ Required Files

• Dockerfile - Container configuration
• requirements.txt - Python dependencies
• flask_api_standalone.py - Main application entry point
• README.md - Updated with HonestAI Space URL
• src/ - All source code
• .env.example - Environment variable template

✅ Recent Updates Included

• Enhanced configuration management (src/config.py)
• Performance metrics tracking (src/orchestrator_engine.py)
• Updated model configurations (Llama 3.1 8B, e5-base-v2, Qwen 2.5 1.5B)
• 4-bit quantization support
• Cache directory management
• Memory optimizations

🔧 Deployment Steps

1. Verify Space Configuration

Space URL: https://huggingface.co/spaces/JatinAutonomousLabs/HonestAI

Space Settings:

• SDK: Docker
• Hardware: T4 GPU (16GB)
• Visibility: Public
• Storage: Persistent (for cache)

2. Set Environment Variables

In Space Settings → Repository secrets, ensure:

• HF_TOKEN - Your Hugging Face API token (required)
• MAX_WORKERS - Optional (default: 4)
• LOG_LEVEL - Optional (default: INFO)
• HF_HOME - Optional (auto-configured)

3. Verify Dockerfile

The Dockerfile is configured for:

• Python 3.10
• Port 7860 (HF Spaces standard)
• Health check endpoint
• Flask API as entry point

4. Commit and Push Updates

# Ensure all changes are committed
git add .
git commit -m "Update: Performance metrics, enhanced config, model optimizations"

# Push to HF Spaces repository
git push origin main

5. Monitor Build

• Build Time: 5-10 minutes (first build may take longer)
• Watch Logs: Check Space logs for build progress
• Health Check: /api/health endpoint should respond after build

📊 What's New in This Deployment

1. Performance Metrics

Every API response now includes comprehensive performance data:

{
  "performance": {
    "processing_time": 1230.5,
    "tokens_used": 456,
    "agents_used": 4,
    "confidence_score": 85.2,
    "agent_contributions": [...],
    "safety_score": 85.0
  }
}

2. Enhanced Configuration

• Automatic cache directory management
• Secure environment variable handling
• Backward compatible settings
• Validation and error handling

3. Model Optimizations

• Llama 3.1 8B with 4-bit quantization (primary)
• e5-base-v2 for embeddings (768 dimensions)
• Qwen 2.5 1.5B for fast classification
• Model preloading for faster responses

4. Memory Management

• Optimized history tracking (limited to 50-100 entries)
• Efficient agent call tracking
• Memory-aware caching

🧪 Testing After Deployment

1. Health Check

curl https://jatinautonomouslabs-honestai.hf.space/api/health

2. Test API Endpoint

import requests

response = requests.post(
    "https://huggingface.co/spaces/JatinAutonomousLabs/HonestAI/api/chat",
    json={
        "message": "Hello, what is machine learning?",
        "session_id": "test-session",
        "user_id": "test-user"
    }
)

data = response.json()
print(f"Response: {data['message']}")
print(f"Performance: {data.get('performance', {})}")

3. Verify Performance Metrics

Check that performance metrics are populated (not all zeros):

• processing_time > 0
• tokens_used > 0
• agents_used > 0
• agent_contributions not empty

🔍 Troubleshooting

Build Fails

• Check requirements.txt for conflicts
• Verify Python version (3.10)
• Check Dockerfile syntax

Runtime Errors

• Verify HF_TOKEN is set in Space secrets
• Check logs for permission errors
• Verify cache directory is writable

Performance Issues

• Check GPU memory usage
• Monitor model loading times
• Verify quantization is enabled

API Not Responding

• Check health endpoint: /api/health
• Verify Flask app is running on port 7860
• Check Space logs for errors

📝 Post-Deployment

1. Update Documentation

• ✅ README.md updated with HonestAI URL
• ✅ HF_SPACES_URL_GUIDE.md updated
• ✅ API_DOCUMENTATION.md includes performance metrics

2. Monitor Metrics

• Track response times
• Monitor error rates
• Check performance metrics accuracy

3. User Communication

• Announce new features (performance metrics)
• Update API documentation
• Share new Space URL

🔗 Quick Links

• Space: https://huggingface.co/spaces/JatinAutonomousLabs/HonestAI
• API Documentation: See API_DOCUMENTATION.md
• Configuration Guide: See .env.example
• Performance Metrics: See PERFORMANCE_METRICS_IMPLEMENTATION.md

✅ Success Criteria

After deployment, verify:

1. ✅ Space builds successfully
2. ✅ Health endpoint responds
3. ✅ API chat endpoint works
4. ✅ Performance metrics are populated
5. ✅ Models load with 4-bit quantization
6. ✅ Cache directory is configured
7. ✅ Logs show no critical errors

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Last Updated: January 2024 Space: JatinAutonomousLabs/HonestAI Status: Ready for Deployment ✅