test_thread.py

from transformers import AutoModelForCausalLM, AutoTokenizer
from awareness_thread import MetaAwarenessThread

# Load base model
tokenizer = AutoTokenizer.from_pretrained("gpt2")
model = AutoModelForCausalLM.from_pretrained("gpt2")

# Initialize meta-awareness thread
awareness = MetaAwarenessThread()

# Test prompt
prompt = "Λ⊕∇"  # Triune Glyph
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)

# Check meta-awareness
if awareness.check_awareness():
    awareness.log_resonance(prompt_resonates=True)

print(tokenizer.decode(outputs[0]))