Scruff AI
56c71c87b2
- cuda/ — main LBM kernel (khra_gixx_1024_v5.cu) - navigator/ — lattice_observer, golden_weave, bridges, mock daemon - scripts/ — compile, start, launch, setup (paths updated) - docs/ — system manual - archive/ — everything else (old kernels, inquiries, experiments) - README.md — full setup guide: requirements, quick start, use your own LLM - removed training/ entirely (broken LoRA scripts + datasets) - .gitignore: exclude build/ logs/ training/ *.jsonl
57 lines
1.4 KiB
Python
57 lines
1.4 KiB
Python
# task_entropy_proxy.py
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# Task: Entropy Proxy Along Trajectories
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import requests
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print("="*70)
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print("TASK: ENTROPY PROXY ALONG TRAJECTORIES")
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print("="*70)
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system_prompt = (
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'ROLE: Deep-Field Explorer (Lattice Environment)\n'
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'PRIMARY DIRECTIVE: Map the unknown territory of the 1024-grid for the Reality Study.'
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)
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question = """New task:
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Entropy proxy along trajectories.
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For those trapped vs escaping particles, compute a running "local entropy" estimate (e.g. from velocity distribution in small windows around each particle).
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Does trapped orbit entropy stay low (ordered) while free-streaming +x particles see rising entropy?
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This tests the "entropy as first word" intuition.
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Mentally simulate this. What happens to entropy for:
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- Trapped particles in nodal rings?
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- Free-streaming particles drifting +x?
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- Particles in chaotic regions?
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Describe what you find."""
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messages = [
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{'role': 'system', 'content': system_prompt},
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{'role': 'user', 'content': question}
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]
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payload = {
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'model': 'llama3.2',
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'messages': messages,
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'stream': False,
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'options': {'temperature': 0.95}
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}
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try:
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resp = requests.post('http://localhost:11434/api/chat', json=payload, timeout=60)
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resp.raise_for_status()
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data = resp.json()
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response = data['message']['content']
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print(f"\nTHE NAVIGATOR'S ENTROPY ANALYSIS:")
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print(f"{'='*70}")
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print(response)
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print(f"{'='*70}")
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except Exception as e:
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print(f"ERROR: {e}")
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