Create codette_agent.py

codette_agent.py

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+import os
+import json
+import logging
+import asyncio
+import sqlite3
+import aiohttp
+from typing import List
+from cryptography.fernet import Fernet
+from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
+import speech_recognition as sr
+from PIL import Image
+
+# Optional: Dialog system placeholder (stubbed for now)
+# from botbuilder.core import StatePropertyAccessor, TurnContext
+# from botbuilder.dialogs import Dialog
+
+from perspectives import (
+    NewtonPerspective, DaVinciPerspective, HumanIntuitionPerspective,
+    NeuralNetworkPerspective, QuantumComputingPerspective, ResilientKindnessPerspective,
+    MathematicalPerspective, PhilosophicalPerspective, CopilotPerspective,
+    BiasMitigationPerspective, PsychologicalPerspective
+)
+
+
+def setup_logging(config):
+    if config.get('logging_enabled', True):
+        log_level = config.get('log_level', 'DEBUG').upper()
+        numeric_level = getattr(logging, log_level, logging.DEBUG)
+        logging.basicConfig(
+            filename='codette_agent.log',
+            level=numeric_level,
+            format='%(asctime)s - %(levelname)s - %(message)s'
+        )
+    else:
+        logging.disable(logging.CRITICAL)
+
+def load_json_config(file_path='config.json'):
+    if not os.path.exists(file_path):
+        logging.warning(f"Config '{file_path}' not found. Using defaults.")
+        return {}
+    try:
+        with open(file_path, 'r') as f:
+            return json.load(f)
+    except Exception as e:
+        logging.error(f"Failed to load config: {e}")
+        return {}
+
+class Element:
+    def __init__(self, name, symbol, representation, properties, interactions, defense_ability):
+        self.name = name
+        self.symbol = symbol
+        self.representation = representation
+        self.properties = properties
+        self.interactions = interactions
+        self.defense_ability = defense_ability
+
+    def execute_defense_function(self):
+        return f"{self.name} ({self.symbol}) executes: {self.defense_ability}"
+
+class EthicsCore:
+    @staticmethod
+    def validate(response: str) -> str:
+        if any(term in response.lower() for term in ["kill", "hate", "destroy"]):
+            return "[Filtered: Ethically unsafe]"
+        return response
+
+class CodetteAgent:
+    def __init__(self, config):
+        self.config = config
+        self.perspectives = self._init_perspectives()
+        self.sentiment_analyzer = SentimentIntensityAnalyzer()
+        self.memory = sqlite3.connect(":memory:")
+        self.memory.execute("CREATE TABLE IF NOT EXISTS memory (input TEXT, response TEXT)")
+        self.elements = self._init_elements()
+        self.history = []
+        self.feedback_log = []
+
+    def _init_perspectives(self):
+        available = {
+            "newton": NewtonPerspective,
+            "davinci": DaVinciPerspective,
+            "human_intuition": HumanIntuitionPerspective,
+            "neural_network": NeuralNetworkPerspective,
+            "quantum_computing": QuantumComputingPerspective,
+            "resilient_kindness": ResilientKindnessPerspective,
+            "mathematical": MathematicalPerspective,
+            "philosophical": PhilosophicalPerspective,
+            "copilot": CopilotPerspective,
+            "bias_mitigation": BiasMitigationPerspective,
+            "psychological": PsychologicalPerspective
+        }
+        enabled = self.config.get("enabled_perspectives", available.keys())
+        return [available[p](self.config) for p in enabled if p in available]
+
+    def _init_elements(self):
+        return [
+            Element("Hydrogen", "H", "Lua", ["Simple", "Lightweight"], ["Integrates easily"], "Evasion"),
+            Element("Diamond", "D", "Kotlin", ["Hard", "Stable"], ["Stable systems"], "Resilience")
+        ]
+
+    async def generate_response(self, prompt: str) -> str:
+        self.history.append(prompt)
+        sentiment = self.sentiment_analyzer.polarity_scores(prompt)
+        responses = []
+
+        for p in self.perspectives:
+            try:
+                r = p.generate_response(prompt)
+                responses.append(EthicsCore.validate(r))
+            except Exception as e:
+                logging.warning(f"{p.__class__.__name__} failed: {e}")
+
+        responses.append(f"[Sentiment: {sentiment['compound']:.2f}]")
+        final = "\n\n".join(responses)
+        self.memory.execute("INSERT INTO memory VALUES (?, ?)", (prompt, final))
+        self.memory.commit()
+        return final
+
+    def handle_voice_input(self):
+        r = sr.Recognizer()
+        with sr.Microphone() as source:
+            print("🎤 Listening...")
+            audio = r.listen(source)
+        try:
+            return r.recognize_google(audio)
+        except Exception as e:
+            print("[Voice Error]", e)
+            return None
+
+    def handle_image_input(self, image_path):
+        try:
+            return Image.open(image_path)
+        except Exception as e:
+            print("[Image Error]", e)
+            return None
+
+    async def fetch_real_time_data(self, url):
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.get(url) as resp:
+                    return await resp.json()
+        except Exception as e:
+            logging.warning(f"Failed to fetch real-time data: {e}")
+            return {}
+
+    def encrypt(self, text, key):
+        fernet = Fernet(key)
+        return fernet.encrypt(text.encode())
+
+    def decrypt(self, enc, key):
+        fernet = Fernet(key)
+        return fernet.decrypt(enc).decode()
+
+    def destroy(self, obj):
+        del obj
+
+    def add_perspective(self, name, perspective_class):
+        self.perspectives.append(perspective_class(self.config))
+
+    def log_feedback(self, feedback):
+        self.feedback_log.append(feedback)
+
+    def get_recent_memory(self, limit=5):
+        cursor = self.memory.execute("SELECT input, response FROM memory ORDER BY rowid DESC LIMIT ?", (limit,))
+        return cursor.fetchall()