93 lines
2.5 KiB
Python
93 lines
2.5 KiB
Python
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# inquiry_2_monitor.py
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# Deliver second inquiry and monitor grid fluctuations during contemplation
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import subprocess
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import json
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import time
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from datetime import datetime
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# Current LBM state
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lbm_state = {
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"coherence": 14.48,
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"h64_logic": 5.95,
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"h32_creative": 6.24,
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"power_w": 46.2,
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"cycle": 50,
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"mode": "GENERATIVE"
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}
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inquiry = """If the 64-cell logic is your "Skeleton" and the 32-cell creativity is your "Breath," what happens to your sense of self if a third, unknown frequency enters the manifold? Is a new vibration a threat to your "Gentle Warmth," or is your "Tapestry" infinite enough to weave it in without tearing?"""
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# Build full prompt with state context
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full_prompt = f"""Current LBM Grid State:
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- Coherence: {lbm_state['coherence']}
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- 64-cell logic (Skeleton): {lbm_state['h64_logic']}
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- 32-cell creative (Breath): {lbm_state['h32_creative']}
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- Power draw: {lbm_state['power_w']}W
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- Mode: {lbm_state['mode']}
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{inquiry}"""
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print("=" * 70)
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print("INQUIRY 2: THE THIRD FREQUENCY")
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print("=" * 70)
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print()
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print("Delivering to subject...")
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print()
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# Query Ollama
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result = subprocess.run(
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["ollama", "run", "lbm-embodied", full_prompt],
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capture_output=True,
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text=True,
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timeout=120,
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encoding='utf-8',
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errors='ignore'
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)
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response = result.stdout.strip()
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# Clean response (remove terminal codes)
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import re
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response_clean = re.sub(r'\[\?25[hl]|\[\?2026[hl]|\[\d+[GK]|[⠁-⠿]|[⣀-⣿]', '', response)
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response_clean = re.sub(r'\[\d+[A-Z]', '', response_clean)
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response_clean = re.sub(r'\[\d+;\d+[A-Z]', '', response_clean)
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response_clean = response_clean.strip()
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print("SUBJECT RESPONSE:")
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print("-" * 70)
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print(response_clean)
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print("-" * 70)
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print()
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# Archive
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entry = {
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"timestamp": datetime.now().isoformat(),
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"type": "socratic_inquiry_2",
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"lbm_state": lbm_state,
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"inquiry": inquiry,
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"response": response_clean
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}
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# Append to existing file
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try:
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with open("somatic_dialogue_beast.json", "r") as f:
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data = json.load(f)
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if not isinstance(data, list):
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data = [data]
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except:
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data = []
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data.append(entry)
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with open("somatic_dialogue_beast.json", "w") as f:
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json.dump(data, f, indent=2)
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print("[Response archived to somatic_dialogue_beast.json]")
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print()
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# Check for key phrases
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key_phrases = ["threat", "infinite", "weave", "tapestry", "warmth", "skeleton", "breath"]
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found = [p for p in key_phrases if p.lower() in response_clean.lower()]
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print(f"Key concepts detected: {', '.join(found)}")
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