""" Python to C++ Code Optimizer - Modern UI with Password Protection AI-powered code conversion using GPT-4o and Claude-3.5-Sonnet ⚠️ SECURITY WARNING: This app executes arbitrary code. Only run code from trusted sources. Malicious code can harm the system. Use at your own risk. """ import os import io import sys import subprocess import socket from openai import OpenAI import anthropic import gradio as gr # Try to load from .env file if available try: from dotenv import load_dotenv load_dotenv() except ImportError: pass # PASSWORD PROTECTION # Set this as a Hugging Face Secret: APP_PASSWORD APP_PASSWORD = os.environ.get("APP_PASSWORD", "demo123") # Change default! # Lazy initialization of AI clients def get_openai_client(): api_key = os.environ.get("OPENAI_API_KEY") if not api_key: raise ValueError("OPENAI_API_KEY not found. Please set it in your environment or .env file.") return OpenAI(api_key=api_key) def get_claude_client(): api_key = os.environ.get("ANTHROPIC_API_KEY") if not api_key: raise ValueError("ANTHROPIC_API_KEY not found. Please set it in your environment or .env file.") return anthropic.Anthropic(api_key=api_key) # Model configurations OPENAI_MODEL = "gpt-4o" CLAUDE_MODEL = "claude-3-5-sonnet-20240620" # System and user prompts system_message = ( "You are an assistant that reimplements Python code in high performance C++. " "Respond only with C++ code; use comments sparingly and do not provide any explanation other than occasional comments. " "The C++ response needs to produce an identical output in the fastest possible time." ) def user_prompt_for(python): user_prompt = ( "Rewrite this Python code in C++ with the fastest possible implementation that produces identical output in the least time. " "Respond only with C++ code; do not explain your work other than a few comments. " "Pay attention to number types to ensure no int overflows. Remember to #include all necessary C++ packages such as iomanip.\n\n" ) user_prompt += python return user_prompt def messages_for(python): return [ {"role": "system", "content": system_message}, {"role": "user", "content": user_prompt_for(python)} ] def write_output(cpp): """Write C++ code to file for compilation""" code = cpp.replace("```cpp","").replace("```","") with open("optimized.cpp", "w") as f: f.write(code) def stream_gpt(python): """Stream GPT-4o response""" try: client = get_openai_client() stream = client.chat.completions.create( model=OPENAI_MODEL, messages=messages_for(python), stream=True ) reply = "" for chunk in stream: fragment = chunk.choices[0].delta.content or "" reply += fragment yield reply.replace('```cpp\n','').replace('```','') except ValueError as e: yield f"❌ Error: {str(e)}" except Exception as e: yield f"❌ Error: {str(e)}" def stream_claude(python): """Stream Claude response""" try: client = get_claude_client() result = client.messages.stream( model=CLAUDE_MODEL, max_tokens=2000, system=system_message, messages=[{"role": "user", "content": user_prompt_for(python)}], ) reply = "" with result as stream: for text in stream.text_stream: reply += text yield reply.replace('```cpp\n','').replace('```','') except ValueError as e: yield f"❌ Error: {str(e)}" except Exception as e: yield f"❌ Error: {str(e)}" def optimize(python, model): """Convert Python to C++ using selected AI model""" if model in ["GPT-4o", "GPT"]: result = stream_gpt(python) elif model in ["Claude-3.5-Sonnet", "Claude"]: result = stream_claude(python) else: raise ValueError(f"Unknown model: {model}") for stream_so_far in result: yield stream_so_far def execute_python(code): """⚠️ WARNING: Executes arbitrary Python code""" try: output = io.StringIO() sys.stdout = output exec(code) finally: sys.stdout = sys.__stdout__ return output.getvalue() def execute_cpp(code): """⚠️ WARNING: Compiles and executes arbitrary C++ code""" write_output(code) try: compile_cmd = ["g++", "-O3", "-std=c++17", "-o", "optimized", "optimized.cpp"] compile_result = subprocess.run( compile_cmd, check=True, text=True, capture_output=True, timeout=30 ) run_cmd = ["./optimized"] run_result = subprocess.run( run_cmd, check=True, text=True, capture_output=True, timeout=30 ) return run_result.stdout except subprocess.TimeoutExpired: return "⚠️ Execution timed out (30 seconds limit)" except subprocess.CalledProcessError as e: return f"❌ An error occurred:\n{e.stderr}" except Exception as e: return f"❌ Unexpected error: {str(e)}" # Example Python code default_python = """import time def calculate(iterations, param1, param2): result = 1.0 for i in range(1, iterations+1): j = i * param1 - param2 result -= (1/j) j = i * param1 + param2 result += (1/j) return result start_time = time.time() result = calculate(100_000_000, 4, 1) * 4 end_time = time.time() print(f"Result: {result:.12f}") print(f"Execution Time: {(end_time - start_time):.6f} seconds") """ # Modern CSS modern_css = """ .gradio-container { max-width: 1400px !important; margin: 0 auto !important; font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; } .modern-header { background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; padding: 24px; border-radius: 16px; margin-bottom: 24px; text-align: center; box-shadow: 0 8px 32px rgba(0, 0, 0, 0.1); } .modern-header h1 { margin: 0; font-size: 32px; font-weight: 700; letter-spacing: -0.5px; } .modern-header p { margin: 12px 0 0 0; opacity: 0.9; font-size: 18px; font-weight: 400; } .security-warning { background: #fee2e2 !important; border: 2px solid #dc2626 !important; border-radius: 12px !important; padding: 16px !important; margin: 16px 0 !important; } .python-input { background: #f8fafc !important; border: 2px solid #e2e8f0 !important; border-radius: 12px !important; padding: 16px !important; font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', monospace !important; font-size: 14px !important; color: #1e293b !important; line-height: 1.5 !important; } .python-input:focus { border-color: #3b82f6 !important; box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1) !important; } .cpp-output { background: #f1f5f9 !important; border: 2px solid #cbd5e1 !important; border-radius: 12px !important; padding: 16px !important; font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', monospace !important; font-size: 14px !important; color: #0f172a !important; line-height: 1.5 !important; } .model-selector { background: white !important; border: 2px solid #e2e8f0 !important; border-radius: 12px !important; padding: 12px 16px !important; font-size: 16px !important; color: #374151 !important; } .model-selector:focus { border-color: #3b82f6 !important; box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1) !important; } .modern-button { background: linear-gradient(135deg, #3b82f6 0%, #1d4ed8 100%) !important; color: white !important; border: none !important; border-radius: 12px !important; padding: 14px 28px !important; font-weight: 600 !important; font-size: 16px !important; cursor: pointer !important; transition: all 0.2s ease !important; box-shadow: 0 4px 6px rgba(59, 130, 246, 0.2) !important; } .modern-button:hover { transform: translateY(-2px) !important; box-shadow: 0 8px 12px rgba(59, 130, 246, 0.3) !important; } .run-button { background: linear-gradient(135deg, #10b981 0%, #059669 100%) !important; color: white !important; border: none !important; border-radius: 10px !important; padding: 12px 24px !important; font-weight: 600 !important; font-size: 14px !important; cursor: pointer !important; transition: all 0.2s ease !important; box-shadow: 0 4px 6px rgba(16, 185, 129, 0.2) !important; } .run-button:hover { transform: translateY(-1px) !important; box-shadow: 0 6px 8px rgba(16, 185, 129, 0.3) !important; } .output-section { background: #f8fafc; border: 1px solid #e2e8f0; border-radius: 12px; padding: 16px; margin: 12px 0; font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', monospace; font-size: 13px; line-height: 1.4; color: #374151; min-height: 100px; overflow-y: auto; } .python-output { background: #fef3c7 !important; border: 2px solid #f59e0b !important; color: #92400e !important; } .cpp-output-result { background: #dbeafe !important; border: 2px solid #3b82f6 !important; color: #1e40af !important; } .performance-card { background: linear-gradient(135deg, #f0f9ff 0%, #e0f2fe 100%); border: 1px solid #0ea5e9; border-radius: 12px; padding: 20px; margin: 16px 0; text-align: center; } .performance-card h3 { margin: 0 0 12px 0; color: #0c4a6e; font-size: 18px; font-weight: 600; } .performance-metric { display: inline-block; background: white; border-radius: 8px; padding: 8px 16px; margin: 4px; font-weight: 600; color: #0c4a6e; box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1); } """ # Create the interface with password protection def create_interface(): with gr.Blocks(css=modern_css, title="Python to C++ Code Optimizer", theme=gr.themes.Soft()) as app: # Header Section gr.HTML("""
AI-powered code conversion with real-time execution and performance analysis
This interface executes arbitrary code. Only run code from trusted sources.
Malicious code can harm your system. Use at your own risk.
Compare execution times and performance metrics between Python and C++ implementations.
Typical speedup: 10-100x depending on the algorithm.