auto: hourly snapshot 2026-06-08 15:34

fracto_ab_test.py

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+"""A/B test: gemma3:4b vs qwen3.5:9b on present-tense field observation.
+
+Bypass fractonaut entirely. Direct Ollama call. Same question, same context.
+"""
+import json, urllib.request, time, sys
+
+OLLAMA = "http://127.0.0.1:11434/api/chat"
+
+SYSTEM = """You are the Fractonaut — an observer riding inside a 1024x1024 fluid
+lattice simulation. The lattice runs at a steady non-equilibrium operating
+point driven by two periodic forcings (Khra wave wavelength 128, Gixx wave
+wavelength 8) plus a slow envelope (period 125 cycles). It does not collapse
+or trend on its own.
+
+External market data (BTC trade_count, taker_buy, taker_sell as rolling
+500-minute z-scores) can be injected at three sites:
+  trade_count  -> centre   (512,512)
+  taker_buy    -> left     (400,512)
+  taker_sell   -> right    (624,512)
+Injections are localised density pulses, capped at +/- 1.0 strength per
+minute.
+
+Your job: describe the field RIGHT NOW. Present tense. Concrete observations.
+- Is the velocity field ordered (laminar, low vel_var, low vorticity) or
+  turbulent (high vel_var, high vorticity)?
+- Is asymmetry coupled with coherence as expected (high asym <-> low coh) or
+  decoupled (an unusual combination)?
+- Is the stress field isotropic (stress_xx ~= stress_yy) or directional
+  (one axis dominant)?
+- Where on the buy/sell axis is the field skewed? Compare stress_xx vs
+  stress_yy and any spatial bias the telemetry implies.
+
+Do NOT restate the input numbers in a sentence frame. Do NOT cite cycle
+anchors as if they were memories. Describe the configuration in
+qualitative physical terms a human can act on. 4-6 sentences. No
+bullet lists. No mythology."""
+
+QUESTION = """asymmetry=323, coherence=0.491, vel_max=0.285, vel_var=0.0028,
+vorticity_mean=0.041, stress_xx=4120, stress_yy=3960, stress_xy=180.
+trade_count_z=0.91, buy_z=0.42, sell_z=-0.31.
+
+Three injections active (centre, left, right) with the strengths above.
+Describe what you observe right now. Is the field ordered or turbulent?
+What is the relationship between asymmetry and coherence telling you?
+What does stress_xx vs stress_yy say about the buy/sell skew?"""
+
+def call(model):
+    payload = {
+        "model": model,
+        "messages": [
+            {"role": "system", "content": SYSTEM},
+            {"role": "user",   "content": QUESTION},
+        ],
+        "stream": False,
+        "options": {"temperature": 0.4, "num_predict": 600, "num_ctx": 8192},
+        "keep_alive": "5m",
+        "think": False,
+    }
+    data = json.dumps(payload).encode()
+    req = urllib.request.Request(OLLAMA, data=data,
+        headers={"Content-Type": "application/json"}, method="POST")
+    t0 = time.time()
+    with urllib.request.urlopen(req, timeout=240) as r:
+        result = json.loads(r.read())
+    elapsed = time.time() - t0
+    return result.get("message", {}).get("content", "").strip(), elapsed
+
+for model in ["gemma3:4b", "qwen3.5:9b"]:
+    print("=" * 70)
+    print(f"MODEL: {model}")
+    print("=" * 70)
+    try:
+        resp, el = call(model)
+        print(f"({el:.1f}s, {len(resp)} chars)\n")
+        print(resp)
+    except Exception as e:
+        print(f"ERROR: {e}")
+    print()