Delete CodriaoCore.py

CodriaoCore.py

@@ -1,151 +0,0 @@
-import aiohttp
-import json
-import logging
-import torch
-import faiss
-import numpy as np
-from transformers import AutoModelForCausalLM, AutoTokenizer
-from typing import List, Dict, Any
-from cryptography.fernet import Fernet
-from jwt import encode, decode, ExpiredSignatureError
-from datetime import datetime, timedelta
-import os
-import speech_recognition as sr
-import pyttsx3
-
-# Codette's legacy modules (secured)
-from components.adaptive_learning import AdaptiveLearningEnvironment
-from components.real_time_data import RealTimeDataIntegrator
-from components.sentiment_analysis import EnhancedSentimentAnalyzer
-from components.self_improving_ai import SelfImprovingAI
-from components.multi_agent import MultiAgentSystem
-
-# Codriao's enhanced modules
-from codriao_tb_module import CodriaoHealthModule
-from secure_memory import SecureMemorySession
-from ethical_filter import EthicalFilter
-from results_store import save_result
-
-# Utilities
-from utils.database import Database
-from utils.logger import logger
-
-class CodriaoCore:
-    def __init__(self, config_path: str = "config.json"):
-        self.config = self._load_config(config_path)
-        self.tokenizer = AutoTokenizer.from_pretrained(self.config["model_name"])
-        self.model = AutoModelForCausalLM.from_pretrained(self.config["model_name"])
-        self.models = self._initialize_models()
-        self.context_memory = self._initialize_vector_memory()
-        self._encryption_key = self.config["security_settings"]["encryption_key"].encode()
-        self.jwt_secret = self.config["security_settings"]["jwt_secret"]
-        self.http_session = aiohttp.ClientSession()
-        self.database = Database()
-
-        # Cognitive & ethical subsystems
-        self.sentiment_analyzer = EnhancedSentimentAnalyzer()
-        self.self_improving_ai = SelfImprovingAI()
-        self.adaptive_learning = AdaptiveLearningEnvironment()
-        self.data_fetcher = RealTimeDataIntegrator()
-        self.multi_agent_system = MultiAgentSystem()
-        self.ethical_filter = EthicalFilter()
-        self.secure_memory = SecureMemorySession(self._encryption_key)
-        self.speech_engine = pyttsx3.init()
-        self.health_module = CodriaoHealthModule(ai_core=self)
-
-    def _load_config(self, config_path: str) -> dict:
-        with open(config_path, 'r') as file:
-            return json.load(file)
-
-    def _initialize_models(self):
-        return {
-            "base_model": self.model,
-            "tokenizer": self.tokenizer
-        }
-
-    def _initialize_vector_memory(self):
-        return faiss.IndexFlatL2(768)
-
-    async def generate_response(self, query: str, user_id: int) -> Dict[str, Any]:
-        try:
-            # Ethical Safety
-            check = self.ethical_filter.analyze_query(query)
-            if check["status"] == "blocked":
-                return {"error": check["reason"]}
-            if check["status"] == "flagged":
-                logger.warning(check["warning"])
-
-            # Optional: Trigger TB diagnostics by user request
-            if any(trigger in query.lower() for trigger in ["tb check", "run tb diagnostics", "tb test"]):
-                result = await self.run_tb_diagnostics("tb_image.jpg", "tb_cough.wav", user_id)
-                return result
-
-            vectorized_query = self._vectorize_query(query)
-            self.secure_memory.encrypt_vector(user_id, vectorized_query)
-
-            model_response = await self._generate_local_model_response(query)
-            agent_response = self.multi_agent_system.delegate_task(query)
-            sentiment = self.sentiment_analyzer.detailed_analysis(query)
-            self_reflection = self.self_improving_ai.evaluate_response(query, model_response)
-            real_time = self.data_fetcher.fetch_latest_data()
-            final_response = f"{model_response}
-
-{agent_response}
-
-{self_reflection}"
-
-            self.database.log_interaction(user_id, query, final_response)
-            self._speak_response(final_response)
-
-            return {
-                "response": final_response,
-                "sentiment": sentiment,
-                "real_time_data": real_time,
-                "security_level": self._evaluate_risk(final_response),
-                "token_optimized": True
-            }
-
-        except Exception as e:
-            logger.error(f"Response generation failed: {e}")
-            return {"error": "Codriao encountered a critical reasoning issue."}
-
-    def _vectorize_query(self, query: str):
-        tokenized = self.tokenizer(query, return_tensors="pt")
-        return tokenized["input_ids"].detach().numpy()
-
-    async def _generate_local_model_response(self, query: str) -> str:
-        inputs = self.tokenizer(query, return_tensors="pt")
-        outputs = self.model.generate(**inputs)
-        return self.tokenizer.decode(outputs[0], skip_special_tokens=True)
-
-    async def run_tb_diagnostics(self, image_path: str, audio_path: str, user_id: int) -> Dict[str, Any]:
-        result = await self.health_module.evaluate_tb_risk(image_path, audio_path, user_id)
-        result_filename = save_result(result)
-        result["shareable_link"] = f"https://huggingface.co/spaces/Raiff1982/codriao/blob/main/results/{result_filename}"
-        return result
-
-    def _evaluate_risk(self, response: str) -> str:
-        if "critical" in response.lower():
-            return "HIGH"
-        elif "concern" in response.lower():
-            return "MEDIUM"
-        else:
-            return "LOW"
-
-    def _speak_response(self, response: str):
-        if self.config["speech_settings"]["emotion_adaptive"]:
-            self.speech_engine.say(response)
-            self.speech_engine.runAndWait()
-
-    def generate_jwt(self, user_id: int):
-        payload = {
-            "user_id": user_id,
-            "exp": datetime.utcnow() + timedelta(hours=1)
-        }
-        return encode(payload, self.jwt_secret, algorithm="HS256")
-
-    def verify_jwt(self, token: str):
-        try:
-            return decode(token, self.jwt_secret, algorithms=["HS256"])
-        except ExpiredSignatureError:
-            return None