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import ollama # Import Ollama for local Llama 3 inference
class AICoreAGIX:
def __init__(self, config_path: str = "config.json"):
self.config = self._load_config(config_path)
self.http_session = aiohttp.ClientSession()
self.database = Database()
self.multi_agent_system = MultiAgentSystem()
self.self_reflective_ai = SelfReflectiveAI()
self.ar_overlay = ARDataOverlay()
self.neural_symbolic_processor = NeuralSymbolicProcessor()
self.federated_ai = FederatedAI()
self._encryption_key = Fernet.generate_key()
self.jwt_secret = "your_jwt_secret_key"
self.speech_engine = pyttsx3.init()
async def generate_response(self, query: str, user_id: int) -> Dict[str, Any]:
try:
model_response = await self._generate_local_model_response(query)
agent_response = self.multi_agent_system.delegate_task(query)
self_reflection = self.self_reflective_ai.evaluate_response(query, model_response)
ar_data = self.ar_overlay.fetch_augmented_data(query)
neural_reasoning = self.neural_symbolic_processor.process_query(query)
final_response = f"{model_response}\n\n{agent_response}\n\n{self_reflection}\n\nAR Insights: {ar_data}\n\nLogic: {neural_reasoning}"
self.database.log_interaction(user_id, query, final_response)
blockchain_module.store_interaction(user_id, query, final_response)
self._speak_response(final_response)
return {
"response": final_response,
"real_time_data": self.federated_ai.get_latest_data(),
"context_enhanced": True,
"security_status": "Fully Secure"
}
except Exception as e:
logger.error(f"Response generation failed: {e}")
return {"error": "Processing failed - safety protocols engaged"}
async def _generate_local_model_response(self, query: str) -> str:
"""Use Ollama (Llama 3) for local AI inference."""
response = ollama.chat(model="llama3", messages=[{"role": "user", "content": query}])
return response["message"]["content"]
def _speak_response(self, response: str):
self.speech_engine.say(response)
self.speech_engine.runAndWait()
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