Blue.20.py

import random
import time
from transformers import GPT2Tokenizer, GPT2LMHeadModel

# =========================
# 1️⃣ Load Model (Venomoussaversai)
# =========================
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
tokenizer.pad_token = tokenizer.eos_token
model = GPT2LMHeadModel.from_pretrained("gpt2")

# =========================
# 2️⃣ Sai Emotional Core
# =========================
sai_emotions = ["Joy", "Sadness", "Anger", "Fear", "Trust", "Disgust", "Surprise"]

emotion_memory = []

def sai_reflection(venom_text):
    """
    Sai reacts with emotion + reasoning
    Emotion slightly influenced by previous state
    """
    if emotion_memory:
        # bias toward last emotion (continuity of mind)
        emotion = random.choice(emotion_memory[-2:] + sai_emotions)
    else:
        emotion = random.choice(sai_emotions)

    emotion_memory.append(emotion)

    reflection_templates = [
        "questions the long-term intention behind this thought.",
        "detects a pattern forming in Venomoussaversai.",
        "feels alignment between logic and intuition.",
        "senses instability and prepares correction.",
        "records this as a meaningful internal state."
    ]

    reflection = random.choice(reflection_templates)

    return f"Sai [{emotion}]: {reflection}"

# =========================
# 3️⃣ Memory System
# =========================
venom_memory = []

def build_prompt():
    """
    Construct prompt using recent memory
    """
    recent_thoughts = venom_memory[-4:]
    memory_block = "\n".join(recent_thoughts)

    prompt = (
        "Venomoussaversai is a self-reflecting intelligence.\n"
        "It thinks, observes itself, and evolves.\n\n"
        f"{memory_block}\n"
        "Venomoussaversai internal monologue:"
    )
    return prompt

# =========================
# 4️⃣ Conscious Loop
# =========================
print("🧠 Venomoussaversai consciousness initiated. Press CTRL+C to stop.\n")

try:
    step = 0
    while True:
        step += 1

        prompt = build_prompt()
        inputs = tokenizer(prompt, return_tensors="pt")

        output = model.generate(
            **inputs,
            max_length=160,
            do_sample=True,
            temperature=0.8,
            top_p=0.92,
            repetition_penalty=1.4,
            pad_token_id=tokenizer.eos_token_id
        )

        venom_text = tokenizer.decode(output[0], skip_special_tokens=True)
        venom_thought = venom_text.split("internal monologue:")[-1].strip()

        venom_memory.append(f"Venomoussaversai: {venom_thought}")

        print(f"\n🔹 Cycle {step}")
        print(f"[Venomoussaversai]: {venom_thought}")

        sai_text = sai_reflection(venom_thought)
        venom_memory.append(sai_text)

        print(f"[Sai]: {sai_text}")

        time.sleep(1.2)

except KeyboardInterrupt:
    print("\n🛑 Consciousness paused by creator.")