b7b7f57b35
Added comprehensive migration documentation and configuration files for restructuring the application to split frontend/backend: New Documentation: - MIGRATION_GUIDE.md: Complete step-by-step migration instructions - MIGRATION_SUMMARY.md: Quick reference guide for deployment - MIGRATION_CHECKLIST.md: Printable checklist for migration day - DEPLOYMENT_RESTRUCTURE.md: Architecture overview and benefits New Configuration Files: - run_api_server.py: Production WSGI server wrapper using Waitress - ai_qc.service: Systemd service configuration for backend - apache_config.conf: Apache virtual host configuration template Updated Files: - requirements.txt: Added waitress>=2.1.2 for production WSGI server - README.md: Added deployment documentation section Migration Overview: - Split current monolithic structure into separate frontend/backend - Move backend to /opt/ai_qc/ (following server standards) - Keep frontend in /var/www/html/ai_qc/ (single index.html) - Use Apache reverse proxy to connect frontend to backend API - Implement systemd service for reliable backend process management Benefits: - Improved security (backend code not in web root) - Better separation of concerns - Follows industry best practices - Matches existing server app patterns (/opt/veo3, /opt/voice2text) - Easier independent updates of frontend/backend 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
39 lines
1.1 KiB
Python
Executable file
39 lines
1.1 KiB
Python
Executable file
#!/usr/bin/env python3
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"""
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Production server wrapper for Visual AI QC
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Runs the Flask application using Waitress WSGI server
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"""
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import argparse
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import sys
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import os
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from waitress import serve
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# Add current directory to Python path
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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# Import the Flask app
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from api_server import app
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def main():
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parser = argparse.ArgumentParser(description='Run Visual AI QC API Server')
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parser.add_argument('--host', default='localhost', help='Host to bind to')
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parser.add_argument('--port', type=int, default=7183, help='Port to bind to')
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parser.add_argument('--workers', type=int, default=2, help='Number of worker threads')
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args = parser.parse_args()
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print(f"Starting Visual AI QC server on {args.host}:{args.port}")
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print(f"Worker threads: {args.workers}")
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print(f"Working directory: {os.getcwd()}")
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# Use Waitress WSGI server (production-ready)
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serve(
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app,
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host=args.host,
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port=args.port,
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threads=args.workers,
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url_scheme='http'
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)
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if __name__ == '__main__':
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main()
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