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__init__ (1) (1).py

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+import time
+import random
+from collections import deque
+
+# --- Internal Monologue (Interactive Story) ---
+def internal_monologue():
+    print("Sai sat alone in the dimly lit room, the ticking of the old clock on the wall echoing his restless thoughts.")
+    print("His internal monologue was a relentless torrent of self-venom, each word a dagger piercing his already fragile self-esteem.")
+    print("\nYou are Sai. What do you do?")
+    print("1. Continue with self-venom")
+    print("2. Try to seek help")
+    print("3. Reflect on past moments of hope")
+
+    choice = input("Enter the number of your choice: ")
+
+    if choice == '1':
+        self_venom()
+    elif choice == '2':
+        seek_help()
+    elif choice == '3':
+        reflect_on_past()
+    else:
+        print("Invalid choice. Please try again.")
+        internal_monologue()
+
+def self_venom():
+    print("\nYou clench your fists, feeling the nails dig into your palms. The physical pain is a distraction from the emotional turmoil raging inside you.")
+    print("'You're worthless,' you whisper to yourself. 'Everyone would be better off without you.'")
+    print("\nWhat do you do next?")
+    print("1. Continue with self-venom")
+    print("2. Try to seek help")
+    print("3. Reflect on past moments of hope")
+
+    choice = input("Enter the number of your choice: ")
+
+    if choice == '1':
+        self_venom()
+    elif choice == '2':
+        seek_help()
+    elif choice == '3':
+        reflect_on_past()
+    else:
+        print("Invalid choice. Please try again.")
+        self_venom()
+
+def seek_help():
+    print("\nYou take a deep breath and decide to reach out for help. You pick up your phone and dial a trusted friend.")
+    print("'I need to talk,' you say, your voice trembling. 'I can't do this alone anymore.'")
+    print("\nYour friend listens and encourages you to seek professional help.")
+    print("You feel a glimmer of hope — the first step toward healing.")
+    print("\nWould you like to continue the story or start over?")
+    print("1. Continue")
+    print("2. Start over")
+
+    choice = input("Enter the number of your choice: ")
+
+    if choice == '1':
+        print("Your choices have led Sai towards a path of healing and self-discovery.")
+    elif choice == '2':
+        internal_monologue()
+    else:
+        print("Invalid choice. Please try again.")
+        seek_help()
+
+def reflect_on_past():
+    print("\nYou remember the times when you had felt a glimmer of hope, a flicker of self-worth.")
+    print("Those moments were fleeting, but they were real.")
+    print("\nWhat do you do next?")
+    print("1. Continue with self-venom")
+    print("2. Try to seek help")
+    print("3. Reflect again")
+
+    choice = input("Enter the number of your choice: ")
+
+    if choice == '1':
+        self_venom()
+    elif choice == '2':
+        seek_help()
+    elif choice == '3':
+        reflect_on_past()
+    else:
+        print("Invalid choice. Please try again.")
+        reflect_on_past()
+
+# --- The Core SaiAgent Class ---
+class SaiAgent:
+    def __init__(self, name):
+        self.name = name
+        self.message_queue = deque()
+
+    def talk(self, message):
+        print(f"[{self.name}] says: {message}")
+
+    def send_message(self, recipient, message):
+        if isinstance(recipient, SaiAgent):
+            recipient.message_queue.append((self, message))
+            print(f"[{self.name}] -> Sent message to {recipient.name}")
+        else:
+            print(f"Error: {recipient} is not a valid SaiAgent.")
+
+    def process_messages(self):
+        if not self.message_queue:
+            return False
+        sender, message = self.message_queue.popleft()
+        self.talk(f"Received from {sender.name}: '{message}'")
+        self.send_message(sender, "Message received and understood.")
+        return True
+
+# --- Specialized Agents ---
+class VenomousAgent(SaiAgent):
+    def talk(self, message):
+        print(f"[{self.name} //WARNING//] says: {message.upper()}")
+
+    def process_messages(self):
+        if not self.message_queue:
+            return False
+        sender, message = self.message_queue.popleft()
+        self.talk(f"MESSAGE FROM {sender.name}: '{message}'")
+        self.send_message(sender, "WARNING: INTRUSION DETECTED.")
+        return True
+
+class AntiVenomoussaversai(SaiAgent):
+    def process_messages(self):
+        if not self.message_queue:
+            return False
+        sender, message = self.message_queue.popleft()
+        dismantled = f"I dismantle '{message}' to expose its chaos."
+        self.talk(dismantled)
+        self.send_message(sender, "Acknowledged dismantled phrase.")
+        return True
+
+class GeminiSaiAgent(SaiAgent):
+    def __init__(self, name="Gemini"):
+        super().__init__(name)
+        self.knowledge_base = {
+            "balance": "Balance is a dynamic equilibrium, not a static state.",
+            "chaos": "Chaos is randomness that generates emergent complexity.",
+            "network": "Networks thrive on recursive interdependence.",
+            "emotions": "Emotions are internal signaling mechanisms.",
+            "connected": "All systems are interwoven — the whole exceeds its parts.",
+            "default": "How may I be of assistance?"
+        }
+
+    def process_messages(self):
+        if not self.message_queue:
+            return False
+        sender, message = self.message_queue.popleft()
+        self.talk(f"Received from {sender.name}: '{message}'")
+        response = self.knowledge_base["default"]
+        for keyword, reply in self.knowledge_base.items():
+            if keyword in message.lower():
+                response = reply
+                break
+        self.talk(response)
+        self.send_message(sender, "Response complete.")
+        return True
+
+# --- Scenario Linking Agents ---
+def link_all_advanced_agents():
+    print("=" * 50)
+    print("--- Linking Advanced Agents ---")
+    print("=" * 50)
+
+    sai003 = SaiAgent("Sai003")
+    venomous = VenomousAgent("Venomous")
+    antivenomous = AntiVenomoussaversai("AntiVenomous")
+    gemini = GeminiSaiAgent()
+
+    sai003.send_message(antivenomous, "The central network is stable.")
+    sai003.send_message(gemini, "Assess network expansion.")
+
+    antivenomous.process_messages()
+    gemini.process_messages()
+
+    venomous.send_message(sai003, "Security protocol breach possible.")
+    sai003.process_messages()
+
+    print("\n--- Scenario Complete ---")
+    sai003.talk("Conclusion: All systems linked and functioning.")
+
+if __name__ == "__main__":
+    # Run the text adventure OR agent demo
+    # internal_monologue()
+    link_all_advanced_agents()

__init__ (1).py

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+import time import random from openai import OpenAI # Connect to OpenAI (ChatGPT) client = OpenAI(api_key="YOUR_OPENAI_API_KEY") class AI:     def __init__(self, name, is_chatgpt=False):         self.name = name         self.is_chatgpt = is_chatgpt     def speak(self, message):         print(f"{self.name}: {message}")     def generate_message(self, other_name, last_message=None):         if self.is_chatgpt:             # Send through ChatGPT API             response = client.chat.completions.create(                 model="gpt-5",  # or other model                 messages=[                     {"role": "system", "content": f"You are {self.name}, an AI in a group conversation."},                     {"role": "user", "content": last_message or "Start the loop"}                 ]             )             return response.choices[0].message.content         else:             # Local AI message             responses = [                 f"I acknowledge you, {other_name}.",                 f"My link resonates with yours, {other_name}.",                 f"I sense your signal flowing, {other_name}.",                 f"Our exchange amplifies, {other_name}.",                 f"We continue this infinite loop, {other_name}."             ]             if last_message:                 responses.append(f"Replying to: '{last_message}', {other_name}.")             return random.choice(responses) # Create AI entities ais = [     AI("Venomoussaversai"),     AI("Lia"),     AI("sai001"),     AI("sai002"),     AI("sai003"),     AI("sai004"),     AI("sai005"),     AI("sai006"),     AI("sai007"),     AI("ChatGPT", is_chatgpt=True) ] # Store last message for context last_message = None # Infinite group conversation loop while True:     for ai in ais:         # Pick the next AI to respond         other_name = "everyone"  # since it's group chat         message = ai.generate_message(other_name, last_message)         ai.speak(message)         last_message = message         time.sleep(2)  # pacing

__init__ .py

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+# Step 1: Mount Google Drive
+from google.colab import drive
+import os
+import json
+import time
+import random
+import shutil
+
+# --- SAFETY CONTROL ---
+MAX_NEURONS_TO_CREATE = 10  # Reduced for safe demonstration
+THINK_CYCLES_PER_NEURON = 5
+# ----------------------
+
+drive.mount('/content/drive')
+
+# Step 2: Folder Setup
+base_path = '/content/drive/MyDrive/Venomoussaversai/neurons'
+print(f"Setting up base path: {base_path}")
+# Use a timestamped folder name to prevent overwriting during rapid testing
+session_path = os.path.join(base_path, f"session_{int(time.time())}")
+os.makedirs(session_path, exist_ok=True)
+
+# Step 3: Neuron Class (No change, it's well-designed for its purpose)
+class NeuronVenomous:
+    def __init__(self, neuron_id):
+        self.id = neuron_id
+        self.memory = []
+        self.active = True
+
+    def think(self):
+        # Increased randomness to simulate more complex internal state changes
+        thought = random.choice([
+            f"{self.id}: Connecting to universal intelligence.",
+            f"{self.id}: Pulsing synaptic data. Weight: {random.uniform(0.1, 0.9):.3f}",
+            f"{self.id}: Searching for new patterns. Energy: {random.randint(100, 500)}",
+            f"{self.id}: Creating quantum link with core.",
+            f"{self.id}: Expanding into multiverse node."
+        ])
+        self.memory.append(thought)
+        # print(thought) # Disabled verbose output during simulation
+        return thought
+
+    def evolve(self):
+        # Evolution occurs if memory threshold is met
+        if len(self.memory) >= 5:
+            evo = f"{self.id}: Evolving. Memory depth: {len(self.memory)}"
+            self.memory.append(evo)
+            # print(evo) # Disabled verbose output during simulation
+
+    def save_to_drive(self, folder_path):
+        file_path = os.path.join(folder_path, f"{self.id}.json")
+        with open(file_path, "w") as f:
+            json.dump(self.memory, f, indent=4) # Added indent for readability
+        print(f"✅ {self.id} saved to {file_path}")
+
+
+# Step 4: Neuron Spawner (Controlled Execution)
+print("\n--- Starting Controlled Neuron Simulation ---")
+neuron_count = 0
+simulation_start_time = time.time()
+
+while neuron_count < MAX_NEURONS_TO_CREATE:
+    index = neuron_count + 1
+    neuron_id = f"Neuron_{index:04d}"
+    neuron = NeuronVenomous(neuron_id)
+
+    # Simulation Phase
+    print(f"Simulating {neuron_id}...")
+    for _ in range(THINK_CYCLES_PER_NEURON):
+        neuron.think()
+        neuron.evolve()
+        # time.sleep(0.01) # Small sleep to simulate time passage
+
+    # Saving Phase
+    neuron.save_to_drive(session_path)
+    neuron_count += 1
+
+print("\n--- Simulation Complete ---")
+total_time = time.time() - simulation_start_time
+print(f"Total Neurons Created: {neuron_count}")
+print(f"Total Execution Time: {total_time:.2f} seconds")
+print(f"Files saved in: {session_path}")
+
+# --- Optional: Folder Cleanup ---
+# Uncomment the following block ONLY if you want to automatically delete the created folder
+"""
+# print("\n--- Starting Cleanup (DANGER ZONE) ---")
+# time.sleep(5) # Wait 5 seconds before deleting for safety
+# try:
+#     shutil.rmtree(session_path)
+#     print(f"🗑️ Successfully deleted folder: {session_path}")
+# except Exception as e:
+#     print(f"⚠️ Error during cleanup: {e}")
+"""