model_deployer.py

"""
PyPilot Model Deployer - Production deployment and serving
"""
import torch
from transformers import pipeline
import flask
from flask import Flask, request, jsonify
import fastapi
from fastapi import FastAPI, HTTPException
import uvicorn
import threading
import time
from datetime import datetime

class PyPilotDeployer:
    def __init__(self, model_path=None):
        self.model_path = model_path
        self.model = None
        self.tokenizer = None
        self.is_loaded = False
        
    def load_model_for_inference(self, quantize=True):
        """Load model optimized for inference"""
        print("🔄 Loading model for inference...")
        
        if quantize:
            # Apply quantization for faster inference
            self.model = torch.quantization.quantize_dynamic(
                self.model, {torch.nn.Linear}, dtype=torch.qint8
            )
            print("✅ Model quantized for faster inference")
        
        self.model.eval()
        self.is_loaded = True
        print("✅ Model ready for inference!")
    
    def create_flask_api(self, host='0.0.0.0', port=5000):
        """Create Flask REST API for model serving"""
        app = Flask(__name__)
        
        @app.route('/health', methods=['GET'])
        def health_check():
            return jsonify({'status': 'healthy', 'timestamp': datetime.now().isoformat()})
        
        @app.route('/complete', methods=['POST'])
        def code_completion():
            data = request.get_json()
            code_prompt = data.get('code', '')
            max_length = data.get('max_length', 100)
            
            if not self.is_loaded:
                return jsonify({'error': 'Model not loaded'}), 500
            
            try:
                completion = self.generate_completion(code_prompt, max_length)
                return jsonify({
                    'completion': completion,
                    'timestamp': datetime.now().isoformat()
                })
            except Exception as e:
                return jsonify({'error': str(e)}), 500
        
        @app.route('/analyze', methods=['POST'])
        def code_analysis():
            data = request.get_json()
            code = data.get('code', '')
            
            from code_analyzer import PyPilotCodeAnalyzer
            analyzer = PyPilotCodeAnalyzer()
            analysis = analyzer.comprehensive_analysis(code)
            
            return jsonify(analysis)
        
        print(f"🌐 Starting Flask API on {host}:{port}")
        return app, host, port
    
    def create_fastapi_service(self):
        """Create FastAPI service for high-performance serving"""
        app = FastAPI(title="PyPilot API", version="1.0.0")
        
        @app.get("/")
        async def root():
            return {"message": "PyPilot Code Assistant API"}
        
        @app.post("/v1/completions")
        async def create_completion(request: dict):
            code = request.get("code", "")
            max_tokens = request.get("max_tokens", 100)
            
            if not code:
                raise HTTPException(status_code=400, detail="Code prompt required")
            
            completion = self.generate_completion(code, max_tokens)
            
            return {
                "completion": completion,
                "model": "PyPilot",
                "created": datetime.now().isoformat()
            }
        
        @app.post("/v1/analysis")
        async def analyze_code(request: dict):
            code = request.get("code", "")
            
            from code_analyzer import PyPilotCodeAnalyzer
            analyzer = PyPilotCodeAnalyzer()
            analysis = analyzer.comprehensive_analysis(code)
            
            return analysis
        
        return app
    
    def generate_completion(self, prompt, max_length=100):
        """Generate code completion"""
        # This would use the actual model for inference
        # For now, return a mock completion
        mock_completions = [
            f"# Generated completion for your code\nprint('Hello from PyPilot!')",
            f"# TODO: Implement this functionality\nreturn result",
            f"# PyPilot suggestion\nif __name__ == '__main__':\n    main()"
        ]
        
        import random
        return random.choice(mock_completions)
    
    def start_serving(self, api_type='flask', **kwargs):
        """Start the model serving API"""
        if api_type == 'flask':
            app, host, port = self.create_flask_api(**kwargs)
            app.run(host=host, port=port, debug=False)
        elif api_type == 'fastapi':
            app = self.create_fastapi_service()
            uvicorn.run(app, host=kwargs.get('host', '0.0.0.0'), 
                       port=kwargs.get('port', 8000))
    
    def create_gradio_interface(self):
        """Create Gradio web interface for easy testing"""
        try:
            import gradio as gr
            
            def gradio_complete(code):
                return self.generate_completion(code)
            
            def gradio_analyze(code):
                from code_analyzer import PyPilotCodeAnalyzer
                analyzer = PyPilotCodeAnalyzer()
                return analyzer.comprehensive_analysis(code)
            
            interface = gr.Interface(
                fn=gradio_complete,
                inputs=gr.Textbox(lines=10, placeholder="Enter your code here..."),
                outputs="text",
                title="PyPilot Code Assistant",
                description="AI-powered code completion and analysis"
            )
            
            return interface
        except ImportError:
            print("Gradio not installed. Install with: pip install gradio")
            return None

if __name__ == "__main__":
    deployer = PyPilotDeployer()
    
    # Start a simple Flask server
    print("🚀 Starting PyPilot deployment...")
    app, host, port = deployer.create_flask_api(port=5001)
    
    # Run in background thread
    def run_flask():
        app.run(host=host, port=port, debug=False, use_reloader=False)
    
    flask_thread = threading.Thread(target=run_flask)
    flask_thread.daemon = True
    flask_thread.start()
    
    print(f"✅ PyPilot API running on http://{host}:{port}")
    print("📚 Endpoints:")
    print("   GET  /health - Health check")
    print("   POST /complete - Code completion")
    print("   POST /analyze - Code analysis")
    
    # Keep running
    try:
        while True:
            time.sleep(1)
    except KeyboardInterrupt:
        print("\n🛑 Shutting down PyPilot...")