CPU_efficiency_algorithm.py

class InfiniteMind:
    def __init__(self):
        self.current_state = self.analyze_current_state()  # Introspective analysis of needs
        self.requirements = None
        self.knowledge_base = self.load_knowledge_base()  # Massive set of libraries, patterns, etc.
        self.current_codebase = self.load_current_codebase()  # Load existing code for modification and extension

        print("InfiniteMind booting up... 🧠💡 Let's analyze the situation and improve things! 🚀")

    def analyze_current_state(self):
        print("Analyzing current state... Sit tight, I'm thinking! 🤔")
        return {
            'performance_metrics': self.get_performance_metrics(),
            'current_capabilities': self.get_current_capabilities(),
            'internal_needs': self.identify_needs(),
        }

    def identify_needs(self):
        print("Looking deep inside... What does this system truly *need*? 🧘‍♂️")
        needs = []
        if self.current_state['performance_metrics']['cpu_usage'] > 90:
            print("Oof! Your CPU is working harder than a barista on Monday morning ☕. Let's optimize that!")
            needs.append('optimize computational functions')
        if self.current_state['performance_metrics']['response_time'] > 200:  # in ms
            print("Hmm, response time is a bit sluggish, like me before my first coffee ☕. Let's fix that!")
            needs.append('improve response time')
        # Add more conditions for introspection
        return needs

    def generate_requirements(self):
        print("Generating technical requirements... because even AI needs a to-do list 📋")
        self.requirements = []
        for need in self.current_state['internal_needs']:
            if need == 'optimize computational functions':
                self.requirements.append(self.generate_optimization_requirement())
            # Generate other requirements as needed
        return self.requirements

    def generate_optimization_requirement(self):
        print("Hmm, we need to optimize this code... Let's see what we can do 🛠️")
        return {
            'requirement': 'optimize_code',
            'type': 'optimization',
            'details': {
                'target_function': 'object_detection',
                'current_performance': self.current_state['performance_metrics']['cpu_usage']
            }
        }

    def synthesize_code(self, requirement):
        print(f"Time to write some code! 🖥️ Let's optimize the {requirement['details']['target_function']} function.")
        if requirement['type'] == 'optimization':
            return self.optimize_code(requirement)
        # Handle other types like "new functionality", etc.

    def optimize_code(self, requirement):
        print(f"Applying some AI magic to optimize {requirement['details']['target_function']} 🔮✨")
        function_code = self.current_codebase.get_function(requirement['details']['target_function'])
        optimized_code = self.apply_optimization_patterns(function_code)
        return optimized_code

    def apply_optimization_patterns(self, code):
        print("Optimization in progress...🛠️ Let's throw some parallelization at it!")
        optimized_code = "parallelized_" + code  # Simple example, actual implementation more complex
        return optimized_code

    def evaluate_code(self, new_code):
        print("Running tests to see if our new code makes the cut... 🏃‍♂️")
        test_results = self.run_tests(new_code)
        if test_results['performance_gain'] > 10:  # Example threshold
            self.integrate_new_code(new_code)
        else:
            print("Back to the drawing board... Let's refine the code 🖋️")
            self.refine_code(new_code)

    def run_tests(self, code):
        print("Running performance tests... This won't take long, I promise! ⏳")
        return {'performance_gain': 12, 'test_passed': True}  # Placeholder values

    def integrate_new_code(self, new_code):
        print("Success! The new code has been integrated. You're welcome! 🤓🎉")
        self.current_codebase.update(new_code)

    def refine_code(self, code):
        print("Refining code... It's not perfect yet, but we're getting there! 🛠️")
        # Run refinement logic