import time
from threading import Thread
class MakeAI:
def create_text_analysis_module(self):
return “Text Analysis Module”
def create_image_recognition_module(self):
return "Image Recognition Module"
def create_data_processing_module(self):
return "Data Processing Module"
def train_new_model(self):
return "New Trained Model"
class VSCode:
def analyze_performance(self, metrics, logs):
return {
“textAnalysis”: “Optimized Text Model”,
“imageRecognition”: “Improved Image Recognition”,
“dataProcessing”: “Faster Data Processing”
}
def analyze_feedback(self, feedback_data):
return {
"uiImprovements": "Better VS Code UI Settings",
"featureRequests": "Suggested VS Code Extensions"
}
class API:
def init(self):
self.modules = {}
def register_module(self, name, module):
self.modules[name] = module
def scale_up(self):
print("Scaling up resources...")
def scale_down(self):
print("Scaling down resources...")
def deploy_model(self, model):
print(f"Deploying model: {model}")
def update_ui(self, improvements):
print(f"Applying UI updates: {improvements}")
def update_features(self, features):
print(f"Adding new features: {features}")
class MonitoringService:
def get_metrics(self):
return {“CPU_Usage”: 75, “Memory_Usage”: 65}
def get_usage_metrics(self):
class UsageMetrics:
def is_high_load(self): return True
def is_low_load(self): return False
return UsageMetrics()
class LoggingService:
def get_logs(self):
return [“Error: Something went wrong”]
class TestingService:
def validate_model(self, model):
return True
class DataManager:
def setup_data_storage(self): pass
def setup_data_versioning(self): pass
def setup_data_processing(self): pass
class SecurityManager:
def setup_roles_and_permissions(self): pass
def setup_endpoint_security(self): pass
class CacheManager:
def setup_caching(self): pass
def setup_async_processing(self): pass
class UserFeedbackService:
def get_feedback_data(self):
return [“Users request VS Code dark mode optimization”]
def collect_feedback(self): pass
def analyze_feedback(self): pass
def integrate_make_ai_with_vscode():
make_ai = MakeAI()
vscode = VSCode()
api = API()
# Register Modules
api.register_module("textAnalysis", make_ai.create_text_analysis_module())
api.register_module("imageRecognition", make_ai.create_image_recognition_module())
api.register_module("dataProcessing", make_ai.create_data_processing_module())
monitoring_service = MonitoringService()
logging_service = LoggingService()
testing_service = TestingService()
def continuous_improvement():
while True:
performance_metrics = monitoring_service.get_metrics()
error_logs = logging_service.get_logs()
analysis_results = vscode.analyze_performance(performance_metrics, error_logs)
print("Optimizing Modules with VS Code:", analysis_results)
time.sleep(10)
def handle_scaling():
while True:
usage_metrics = monitoring_service.get_usage_metrics()
if usage_metrics.is_high_load():
api.scale_up()
elif usage_metrics.is_low_load():
api.scale_down()
time.sleep(5)
def automated_deployment():
while True:
new_model = make_ai.train_new_model()
if testing_service.validate_model(new_model):
api.deploy_model(new_model)
time.sleep(60)
def process_user_feedback():
while True:
feedback_data = UserFeedbackService().get_feedback_data()
feedback_analysis = vscode.analyze_feedback(feedback_data)
api.update_ui(feedback_analysis["uiImprovements"])
api.update_features(feedback_analysis["featureRequests"])
time.sleep(30)
# Start all background tasks
Thread(target=continuous_improvement, daemon=True).start()
Thread(target=handle_scaling, daemon=True).start()
Thread(target=automated_deployment, daemon=True).start()
Thread(target=process_user_feedback, daemon=True).start()
integrate_make_ai_with_vscode()