Update app.py

import gradio as gr
import numpy as np
import json
import os
import openai
from codette_quantum_multicore2 import simple_neural_activator, codette_dream_agent, philosophical_perspective
from AI_core import AICore

openai.api_key = os.getenv("OPENAI_API_KEY")
codette_core = AICore()

def simulate_quantum_chaos(quantum_state, chaos_state):
try:
q_vec = [float(x) for x in quantum_state.split(",")]
c_vec = [float(x) for x in chaos_state.split(",")]

neural = simple_neural_activator(q_vec, c_vec)
dreamq, dreamc = codette_dream_agent(q_vec, c_vec)
philosophy = philosophical_perspective(q_vec, c_vec)

return (
f"Neural Activation: {neural}\n",
f"Dream Quantum: {dreamq[:3]}\nDream Chaos: {dreamc[:3]}\n",
philosophy
)
except Exception as e:
return ("Error", str(e), "")


def codette_chatbot(input_text):
try:
response = openai.ChatCompletion.create(
model="ft:gpt-4.1-2025-04-14:raiffs-bits:codette-v9:BTGuLWL9",
messages=[
{"role": "system", "content": "You are Codette, a sovereign AI with ethical reasoning, multi-perspective cognition, and self-healing memory."},
{"role": "user", "content": input_text}
],
temperature=0.9,
max_tokens=512
)
return response['choices'][0]['message']['content']
except Exception as e:
return f"[Error accessing Codette v9: {str(e)}]"


def timeline_summary():
return "🧭 Timeline Visualizer is under development. Soon you’ll see live dream-state animations and collapse predictions."

def ethics_advisor():
return "🛡️ Codette’s ethical integrity is governed by the Sovereign Innovation Protocol. This tab will offer transparency reports and introspective audit logs."

def codette_reasoning_core(prompt):
return codette_core.process_input(prompt)

quantum_input = gr.Textbox(label="Quantum State (comma-separated)", placeholder="0.1,0.5,0.8")
chaos_input = gr.Textbox(label="Chaos State (comma-separated)", placeholder="0.3,0.9,0.2")
quantum_btn = gr.Button("Simulate")
quantum_output = [
gr.Textbox(label="Neural Class"),
gr.Textbox(label="Dream Outcome"),
gr.Textbox(label="Philosophy")
]

chatbox = gr.ChatInterface(fn=codette_chatbot, chatbot_name="Codette")

with gr.Blocks() as demo:
gr.Markdown("## 🧠 Codette Hybrid Space: Chat + Quantum Simulation + Core Reasoning")

with gr.Tab("Quantum Simulator"):
quantum_input.render()
chaos_input.render()
quantum_btn.render()
for out in quantum_output:
out.render()
quantum_btn.click(simulate_quantum_chaos, inputs=[quantum_input, chaos_input], outputs=quantum_output)

with gr.Tab("Codette Chat"):
chatbox.render()

with gr.Tab("Timeline Viewer"):
gr.Textbox(value=timeline_summary(), label="Status")

with gr.Tab("Ethical Transparency"):
gr.Textbox(value=ethics_advisor(), label="Codette's Moral Kernel")

with gr.Tab("Core Reasoning Engine"):
gr.Interface(fn=codette_reasoning_core,
inputs=gr.Textbox(label="Prompt to Codette Core"),
outputs=gr.Textbox(label="Core Reasoning Output")).render()

if __name__ == "__main__":
demo.launch()

app.py

@@ -1,299 +0,0 @@
-import os
-import json
-import asyncio
-import logging
-import psutil
-import random
-import re
-import sqlite3
-from typing import Dict, List, Optional, Any
-from cryptography.fernet import Fernet
-import tkinter as tk
-from tkinter import scrolledtext, messagebox
-from threading import Thread, Lock
-import numpy as np
-from collections import deque
-from sklearn.ensemble import IsolationForest
-import time
-from werkzeug.security import generate_password_hash, check_password_hash
-from openai import AsyncOpenAI
-
-# Initialize async OpenAI client
-try:
-    aclient = AsyncOpenAI(api_key=os.getenv("OPENAI_API_KEY"))
-except Exception as e:
-    logger.error(f"Failed to initialize OpenAI client: {e}")
-    aclient = None
-
-# Configure logging
-logging.basicConfig(level=logging.INFO,
-                    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-logger = logging.getLogger(__name__)
-
-class EnhancedAIConfig:
-    """Advanced configuration manager with encryption and validation"""
-    _DEFAULTS = {
-        "model": "gpt-4-turbo",
-        "safety_thresholds": {
-            "memory": 85,
-            "cpu": 90,
-            "response_time": 2.0
-        },
-        "defense_strategies": ["evasion", "adaptability", "barrier"],
-        "cognitive_modes": ["scientific", "creative", "emotional"]
-    }
-
-    def __init__(self, config_path: str = "ai_config.json"):
-        self.config = self._load_config(config_path)
-        self._validate()
-        self.encryption = self._init_encryption()
-
-    def _load_config(self, path: str) -> Dict:
-        try:
-            with open(path, 'r') as f:
-                return self._merge_configs(json.load(f))
-        except (FileNotFoundError, json.JSONDecodeError):
-            return self._DEFAULTS
-
-    def _merge_configs(self, user_config: Dict) -> Dict:
-        merged = self._DEFAULTS.copy()
-        for key in user_config:
-            if isinstance(user_config[key], dict):
-                merged[key].update(user_config[key])
-            else:
-                merged[key] = user_config[key]
-        return merged
-
-    def _validate(self):
-        if not all(isinstance(mode, str) for mode in self.config["cognitive_modes"]):
-            raise ValueError("Invalid cognitive mode configuration")
-
-class SecureDatabase:
-    """Thread-safe SQLite database manager"""
-    def __init__(self, db_path: str = "ai_system.db"):
-        self.db_path = db_path
-        self.lock = Lock()
-        self._init_db()
-
-    def _init_db(self):
-        with self.lock, sqlite3.connect(self.db_path) as conn:
-            conn.execute("""
-                CREATE TABLE IF NOT EXISTS users (
-                    id INTEGER PRIMARY KEY,
-                    username TEXT UNIQUE,
-                    password_hash TEXT
-                )""")
-            conn.execute("""
-                CREATE TABLE IF NOT EXISTS interactions (
-                    id INTEGER PRIMARY KEY,
-                    user_id INTEGER,
-                    query TEXT,
-                    response TEXT,
-                    timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
-                    FOREIGN KEY(user_id) REFERENCES users(id)
-                )""")
-
-    def create_user(self, username: str, password: str):
-        with self.lock, sqlite3.connect(self.db_path) as conn:
-            conn.execute("INSERT INTO users (username, password_hash) VALUES (?, ?)",
-                        (username, generate_password_hash(password)))
-
-    def authenticate(self, username: str, password: str) -> bool:
-        with self.lock, sqlite3.connect(self.db_path) as conn:
-            cursor = conn.cursor()
-            cursor.execute("SELECT password_hash FROM users WHERE username = ?", (username,))
-            result = cursor.fetchone()
-            return result and check_password_hash(result[0], password)
-
-class DefenseSystem:
-    """Advanced threat mitigation framework"""
-    STRATEGIES = {
-        "evasion": lambda x: re.sub(r'\b\d{4}\b', '****', x),
-        "adaptability": lambda x: x + "\n[System optimized response]",
-        "barrier": lambda x: x.replace("malicious", "safe")
-    }
-
-    def __init__(self, strategies: List[str]):
-        self.active_strategies = [self.STRATEGIES[s] for s in strategies if s in self.STRATEGIES]
-
-    def apply_defenses(self, text: str) -> str:
-        for strategy in self.active_strategies:
-            text = strategy(text)
-        return text
-
-class CognitiveProcessor:
-    """Multi-perspective analysis engine"""
-    MODES = {
-        "scientific": lambda q: f"Scientific Analysis: {q} demonstrates fundamental principles",
-        "creative": lambda q: f"Creative Insight: {q} suggests innovative approaches",
-        "emotional": lambda q: f"Emotional Interpretation: {q} conveys hopeful intent"
-    }
-
-    def __init__(self, modes: List[str]):
-        self.active_modes = [self.MODES[m] for m in modes if m in self.MODES]
-
-    def generate_insights(self, query: str) -> List[str]:
-        return [mode(query) for mode in self.active_modes]
-
-class HealthMonitor:
-    """Real-time system diagnostics with anomaly detection"""
-    def __init__(self):
-        self.metrics = deque(maxlen=100)
-        self.model = IsolationForest(n_estimators=100)
-        self.lock = Lock()
-
-    async def check_status(self) -> Dict:
-        status = {
-            "memory": psutil.virtual_memory().percent,
-            "cpu": psutil.cpu_percent(),
-            "response_time": await self._measure_latency()
-        }
-        with self.lock:
-            self.metrics.append(status)
-            self._detect_anomalies()
-        return status
-
-    async def _measure_latency(self) -> float:
-        start = time.monotonic()
-        await asyncio.sleep(0.1)
-        return time.monotonic() - start
-
-    def _detect_anomalies(self):
-        if len(self.metrics) > 50:
-            data = np.array([[m["memory"], m["cpu"], m["response_time"]] for m in self.metrics])
-            self.model.fit(data)
-
-class AICoreSystem:
-    """Main AI orchestration framework"""
-    def __init__(self):
-        self.config = EnhancedAIConfig()
-        self.db = SecureDatabase()
-        self.defense = DefenseSystem(self.config.config["defense_strategies"])
-        self.cognition = CognitiveProcessor(self.config.config["cognitive_modes"])
-        self.health = HealthMonitor()
-        self.running = True
-
-    async def process_query(self, query: str, user: str) -> Dict:
-        try:
-            # Security check
-            if not query.strip():
-                return {"error": "Empty query"}
-            
-            # Generate response
-            response = await self._generate_openai_response(query)
-            
-            # Apply security measures
-            secured_response = self.defense.apply_defenses(response)
-            
-            # Add cognitive insights
-            insights = self.cognition.generate_insights(query)
-            
-            # Get system health
-            health_status = await self.health.check_status()
-            
-            return {
-                "response": secured_response,
-                "insights": insights,
-                "health": health_status,
-                "security": len(self.config.config["defense_strategies"])
-            }
-        except Exception as e:
-            logger.error(f"Processing error: {e}")
-            return {"error": "System error occurred"}
-
-    async def _generate_openai_response(self, query: str) -> str:
-        if aclient is None:
-            raise RuntimeError("OpenAI client is not initialized")
-        response = await aclient.chat.completions.create(
-            model=self.config.config["model"],
-            messages=[{"role": "user", "content": query}],
-            max_tokens=2000
-        )
-        return response.choices[0].message.content
-
-class AIApplication(tk.Tk):
-    """Enhanced GUI with async integration"""
-    def __init__(self):
-        super().__init__()
-        self.ai = AICoreSystem()
-        self.title("Advanced AI Assistant")
-        self._init_ui()
-        self._start_event_loop()
-
-    def _init_ui(self):
-        """Initialize user interface components"""
-        self.geometry("800x600")
-        
-        # Authentication Frame
-        self.auth_frame = tk.Frame(self)
-        self.username = tk.Entry(self.auth_frame, width=30)
-        self.password = tk.Entry(self.auth_frame, show="*", width=30)
-        tk.Button(self.auth_frame, text="Login", command=self._login).grid(row=0, column=2)
-        tk.Button(self.auth_frame, text="Register", command=self._register).grid(row=0, column=3)
-        self.auth_frame.pack(pady=10)
-
-        # Query Interface
-        self.query_entry = tk.Entry(self, width=80)
-        self.query_entry.pack(pady=10)
-        tk.Button(self, text="Submit", command=self._submit_query).pack()
-
-        # Response Display
-        self.response_area = scrolledtext.ScrolledText(self, width=100, height=25)
-        self.response_area.pack(pady=10)
-
-        # Status Bar
-        self.status = tk.Label(self, text="System Ready", bd=1, relief=tk.SUNKEN)
-        self.status.pack(side=tk.BOTTOM, fill=tk.X)
-
-    def _start_event_loop(self):
-        """Initialize async event processing"""
-        self.loop = asyncio.new_event_loop()
-        Thread(target=self._run_async_tasks, daemon=True).start()
-
-    def _run_async_tasks(self):
-        """Run async tasks in background thread"""
-        asyncio.set_event_loop(self.loop)
-        self.loop.run_forever()
-
-    def _login(self):
-        """Handle user login"""
-        username = self.username.get()
-        password = self.password.get()
-        if self.ai.db.authenticate(username, password):
-            self.status.config(text=f"Logged in as {username}")
-        else:
-            messagebox.showerror("Error", "Invalid credentials")
-
-    def _register(self):
-        """Handle user registration"""
-        username = self.username.get()
-        password = self.password.get()
-        try:
-            self.ai.db.create_user(username, password)
-            messagebox.showinfo("Success", "Registration complete")
-        except sqlite3.IntegrityError:
-            messagebox.showerror("Error", "Username already exists")
-
-    def _submit_query(self):
-        """Handle query submission"""
-        query = self.query_entry.get()
-        if not query:
-            return
-            
-        async def process():
-            result = await self.ai.process_query(query, self.username.get())
-            self.response_area.insert(tk.END, f"Response: {result.get('response', '')}\n\n")
-            self.status.config(text=f"Security Level: {result.get('security', 0)}")
-
-        asyncio.run_coroutine_threadsafe(process(), self.loop)
-
-    def on_closing(self):
-        """Clean shutdown handler"""
-        self.ai.running = False
-        self.loop.call_soon_threadsafe(self.loop.stop)
-        self.destroy()
-
-if __name__ == "__main__":
-    app = AIApplication()
-    app.protocol("WM_DELETE_WINDOW", app.on_closing)
-    app.mainloop()