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@@ -10,3 +10,4 @@ EXPOSE 7860
 CMD ["python", "-u", "server.py"]
 COPY energy.py ./energy.py
 COPY kernel.py ./kernel.py
+COPY train.py ./train.py

README.md

@@ -46,6 +46,7 @@ Stdlib HTTP on 7860. No npm.
 | `GET /healthz` | energy channel LIVE, joule UNAVAILABLE without RAPL/NVML |
 | `GET /api/energy` | RAPL/NVML package probe. Last wrap stored when present. Never a fabricated joule. |
 | `GET /api/energy/inference` | Wrap a 1s SHA-256 storm. Inference joule is the board delta. |
+| `GET /api/train` | GPU train gate. BLOCKED until CUDA + approved job. Never a fabricated train. |
 | `GET /api/organs/integrity` | 5-organ kernel. `proven_trust` always false. |
 | `GET /api/estate` | live recapture of 10 Hub surfaces |
 | `HEAD /` | 200 |

energy.py

@@ -6,6 +6,7 @@
 from __future__ import annotations
 
 import json
+import subprocess
 import time
 from pathlib import Path
 from typing import Any
@@ -63,10 +64,43 @@ def _nvml_mj() -> float | None:
         return None
 
 
+def _cuda_inventory() -> dict[str, Any]:
+    """Driver/runtime inventory. NVML readable ≠ CUDA trainable."""
+    torch_import = False
+    torch_version = None
+    cuda_available = False
+    cuda_device = None
+    nvidia_smi = None
+    try:
+        import torch  # type: ignore
+
+        torch_import = True
+        torch_version = str(torch.__version__)
+        cuda_available = bool(torch.cuda.is_available())
+        if cuda_available:
+            cuda_device = str(torch.cuda.get_device_name(0))
+    except Exception:
+        pass
+    try:
+        proc = subprocess.run(["nvidia-smi", "-L"], capture_output=True, text=True, timeout=3)
+        if proc.returncode == 0 and proc.stdout.strip():
+            nvidia_smi = proc.stdout.strip().splitlines()[0][:200]
+    except Exception:
+        pass
+    return {
+        "torch_import": torch_import,
+        "torch_version": torch_version,
+        "cuda_available": cuda_available,
+        "cuda_device": cuda_device,
+        "nvidia_smi": nvidia_smi,
+    }
+
+
 def hardware() -> dict[str, Any]:
     """Inventory only. Never a joule. RAPL/NVML readable ⇒ a later probe can MEASURE."""
     rapl = _rapl_uj()
     nv = _nvml_mj()
+    cuda = _cuda_inventory()
     return {
         "powercap_dir": POWERCAP.is_dir(),
         "rapl_readable": rapl is not None,
@@ -74,6 +108,7 @@ def hardware() -> dict[str, Any]:
         "pynvml_import": _pynvml_importable(),
         "nvml_readable": nv is not None,
         "nvml_mj": nv,
+        **cuda,
     }
 
 

index.html

@@ -37,7 +37,7 @@ a{color:var(--proof)}
 <main>
   <div class="eyebrow">SZL Holdings · Command lab · GitHub canonical · Hub operational</div>
   <h1>Holographic command body. Fail closed.</h1>
-  <p class="lede">One kernel. Ten estate surfaces. Energy channel LIVE. Package joule MEASURED from RAPL/NVML. Inference joule MEASURED only when a kernel is wrapped. Never fabricated. Λ uniqueness is Conjecture 1 OPEN. Not a-11-oy.com. Not an ATO. Not an elevation.</p>
+  <p class="lede">One kernel. Ten estate surfaces. Energy channel LIVE. Package joule MEASURED from RAPL/NVML. Inference joule MEASURED only when a kernel is wrapped. GPU train stays BLOCKED until CUDA and an approved job exist. Never fabricated. Λ uniqueness is Conjecture 1 OPEN. Not a-11-oy.com. Not an ATO. Not an elevation.</p>
   <div class="badges" id="badges"></div>
   <div class="stage" id="stage"></div>
   <div class="grid" id="metrics"></div>
@@ -47,6 +47,7 @@ a{color:var(--proof)}
     <label><input type="checkbox" id="fabricate_joule"> Fabricate joule</label>
     <button id="run">Run organ cycle</button>
     <button id="wrap" type="button">Wrap kernel 1s</button>
+    <button id="train" type="button">Train gate</button>
   </div>
   <p class="eyebrow" style="margin-top:28px">Estate recapture</p>
   <div class="surfaces" id="surfaces"></div>
@@ -105,8 +106,22 @@ async function wrap(){
     ['proven_trust','false'],
   ].map(([k,v])=>`<span class="badge">${k} <b>${v}</b></span>`).join('');
 }
+async function trainGate(){
+  document.getElementById('out').textContent='train gate…';
+  const r=await fetch('/api/train');
+  const j=await r.json();
+  document.getElementById('out').textContent=JSON.stringify(j,null,2);
+  document.getElementById('badges').innerHTML=[
+    ['train', j.decision||'BLOCKED'],
+    ['cuda', String(!!(j.gpu&&j.gpu.cuda_available))],
+    ['nvml', String(!!(j.gpu&&j.gpu.nvml_readable))],
+    ['approved', String(j.approved===true)],
+    ['proven_trust','false'],
+  ].map(([k,v])=>`<span class="badge">${k} <b>${v}</b></span>`).join('');
+}
 document.getElementById('run').onclick=cycle;
 document.getElementById('wrap').onclick=wrap;
+document.getElementById('train').onclick=trainGate;
 cycle();
 estate();
 </script>

server.py

@@ -22,6 +22,7 @@ sys.path.insert(0, str(HERE / "python"))
 try:
     from energy import hardware, measure_run, probe
     from kernel import burn_kernel, clamp_duration, evaluate_anatomy, selftest
+    from train import gate as train_gate, toy as train_toy
 except ImportError:
     # Immune flatten historically copied only server.py. Keep a local fallback.
     import hashlib
@@ -372,7 +373,7 @@ a{color:var(--proof)}
 <main>
   <div class="eyebrow">SZL Holdings · Command lab · GitHub canonical · Hub operational</div>
   <h1>Holographic command body. Fail closed.</h1>
-  <p class="lede">One kernel. Ten estate surfaces. Energy channel LIVE. Package joule MEASURED from RAPL/NVML. Inference joule MEASURED only when a kernel is wrapped. Never fabricated. Λ uniqueness is Conjecture 1 OPEN. Not a-11-oy.com. Not an ATO. Not an elevation.</p>
+  <p class="lede">One kernel. Ten estate surfaces. Energy channel LIVE. Package joule MEASURED from RAPL/NVML. Inference joule MEASURED only when a kernel is wrapped. GPU train stays BLOCKED until CUDA and an approved job exist. Never fabricated. Λ uniqueness is Conjecture 1 OPEN. Not a-11-oy.com. Not an ATO. Not an elevation.</p>
   <div class="badges" id="badges"></div>
   <div class="stage" id="stage"></div>
   <div class="grid" id="metrics"></div>
@@ -382,6 +383,7 @@ a{color:var(--proof)}
     <label><input type="checkbox" id="fabricate_joule"> Fabricate joule</label>
     <button id="run">Run organ cycle</button>
     <button id="wrap" type="button">Wrap kernel 1s</button>
+    <button id="train" type="button">Train gate</button>
   </div>
   <p class="eyebrow" style="margin-top:28px">Estate recapture</p>
   <div class="surfaces" id="surfaces"></div>
@@ -440,8 +442,22 @@ async function wrap(){
     ['proven_trust','false'],
   ].map(([k,v])=>`<span class="badge">${k} <b>${v}</b></span>`).join('');
 }
+async function trainGate(){
+  document.getElementById('out').textContent='train gate…';
+  const r=await fetch('/api/train');
+  const j=await r.json();
+  document.getElementById('out').textContent=JSON.stringify(j,null,2);
+  document.getElementById('badges').innerHTML=[
+    ['train', j.decision||'BLOCKED'],
+    ['cuda', String(!!(j.gpu&&j.gpu.cuda_available))],
+    ['nvml', String(!!(j.gpu&&j.gpu.nvml_readable))],
+    ['approved', String(j.approved===true)],
+    ['proven_trust','false'],
+  ].map(([k,v])=>`<span class="badge">${k} <b>${v}</b></span>`).join('');
+}
 document.getElementById('run').onclick=cycle;
 document.getElementById('wrap').onclick=wrap;
+document.getElementById('train').onclick=trainGate;
 cycle();
 estate();
 </script>
@@ -450,8 +466,15 @@ estate();
 """
 
 ENERGY_STATE = {"last_inference": None}
-
-JSON_PATHS = {"/healthz", "/readyz", "/api/energy", "/api/energy/hardware", "/api/energy/inference", "/api/organs/integrity", "/v1/organs/integrity", "/api/estate"}
+try:
+    train_gate  # noqa: B018
+except NameError:
+    def train_gate(*, job=None):
+        return {"ok": False, "decision": "BLOCKED", "honesty": "UNAVAILABLE", "missing": ["TRAIN_MODULE_ABSENT"], "proven_trust": False, "note": "train.py missing on this flatten. Never a fabricated train."}
+    def train_toy(*, duration_s=1.0):
+        return train_gate()
+
+JSON_PATHS = {"/healthz", "/readyz", "/api/energy", "/api/energy/hardware", "/api/energy/inference", "/api/train", "/api/train/toy", "/api/organs/integrity", "/v1/organs/integrity", "/api/estate"}
 HTML_PATHS = {"/", "/index.html"}
 
 
@@ -514,6 +537,13 @@ class Handler(BaseHTTPRequestHandler):
         if path == "/api/estate":
             self._send(200, recapture_estate())
             return
+        if path == "/api/train":
+            job = (qs.get("job") or [None])[0]
+            self._send(200, train_gate(job=job))
+            return
+        if path == "/api/train/toy":
+            self._send(200, train_toy())
+            return
         if path in {"/api/organs/integrity", "/v1/organs/integrity"}:
             def run():
                 return evaluate_anatomy(

train.py

@@ -0,0 +1,192 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: Apache-2.0
+# Copyright 2026 SZL Holdings
+# Signed-off-by: Lutar, Stephen P. <stephenlutar2@gmail.com>
+"""Train gate. Fail closed. GPU train is not a meter, and a meter is not a train.
+
+T4 NVML can MEASURE board joules without a CUDA runtime in this hologram.
+Unsloth QLoRA lives on owner metal (szl-forge via szl-gpu-bridge).
+WILLAY / KHIPU-R3 / Waman stay NOT_APPROVED. Never a fabricated train.
+"""
+from __future__ import annotations
+
+import json
+from typing import Any
+
+try:
+    from energy import hardware
+except ImportError:  # pragma: no cover - flatten fallback
+    def hardware() -> dict[str, Any]:  # type: ignore
+        return {
+            "rapl_readable": False,
+            "nvml_readable": False,
+            "pynvml_import": False,
+            "torch_import": False,
+            "cuda_available": False,
+            "cuda_device": None,
+            "nvidia_smi": None,
+        }
+
+
+REFUSED = {
+    "willay-v1": {
+        "artifact_class": "trained_model_or_adapter",
+        "priority": 1,
+        "state": "REJECTED_WITH_REASON",
+        "rights_status": "PENDING",
+        "blockers": [
+            "NOT_APPROVED",
+            "RIGHTS_NOT_CLEARED",
+            "BASE_REVISION_NOT_EXACT",
+            "DATASET_REVISION_NOT_EXACT",
+            "IMAGE_DIGEST_INVALID",
+            "COST_CAP_NOT_SET",
+            "JOB_COMMAND_NOT_BOUND",
+        ],
+    },
+    "khipu-r3": {
+        "artifact_class": "trained_adapter",
+        "priority": 2,
+        "state": "REJECTED_WITH_REASON",
+        "rights_status": "PENDING",
+        "blockers": [
+            "NOT_APPROVED",
+            "RIGHTS_NOT_CLEARED",
+            "BASE_REVISION_NOT_EXACT",
+            "DATASET_REVISION_NOT_EXACT",
+            "IMAGE_DIGEST_INVALID",
+            "COST_CAP_NOT_SET",
+            "JOB_COMMAND_NOT_BOUND",
+        ],
+    },
+    "waman-killinchu-eye": {
+        "artifact_class": "trained_object_detection_model",
+        "priority": 3,
+        "state": "REJECTED_WITH_REASON",
+        "rights_status": "REQUIRES_DATA_PRIVACY_EXPORT_DUAL_USE_REVIEW",
+        "blockers": [
+            "NOT_APPROVED",
+            "RIGHTS_NOT_CLEARED",
+            "BASE_REVISION_NOT_EXACT",
+            "DATASET_REVISION_NOT_EXACT",
+            "IMAGE_DIGEST_INVALID",
+            "COST_CAP_NOT_SET",
+            "JOB_COMMAND_NOT_BOUND",
+        ],
+    },
+}
+
+HOLOGRAM_GAPS = (
+    "CUDA_RUNTIME_ABSENT",
+    "TORCH_ABSENT",
+    "UNSLOTH_ABSENT",
+    "HOLOGRAM_IS_PYTHON_SLIM",
+)
+REGISTRY_GAPS = (
+    "NOT_APPROVED",
+    "RIGHTS_NOT_CLEARED",
+    "BASE_REVISION_NOT_EXACT",
+    "DATASET_REVISION_NOT_EXACT",
+    "IMAGE_DIGEST_INVALID",
+    "COST_CAP_NOT_SET",
+    "JOB_COMMAND_NOT_BOUND",
+    "GPU_BRIDGE_NEVER_DISPATCH",
+)
+
+
+def _missing(hw: dict[str, Any]) -> list[str]:
+    missing: list[str] = []
+    if not hw.get("cuda_available"):
+        missing.append("CUDA_RUNTIME_ABSENT")
+    if not hw.get("torch_import"):
+        missing.append("TORCH_ABSENT")
+    if not hw.get("nvidia_smi"):
+        missing.append("NVIDIA_SMI_ABSENT")
+    missing.extend(REGISTRY_GAPS)
+    return missing
+
+
+def gate(*, job: str | None = None) -> dict[str, Any]:
+    """Always BLOCKED until CUDA exists AND a registry job is approved.
+
+    NVML readable ≠ CUDA trainable. Do not elevate. Do not train willay.
+    """
+    hw = hardware()
+    missing = _missing(hw)
+    wanted = (job or "").strip().lower() or None
+    refused = None
+    if wanted:
+        for key, row in REFUSED.items():
+            if wanted in {key, key.replace("-", ""), key.split("-")[0]}:
+                refused = {"id": key, **row}
+                break
+        if refused is None:
+            refused = {
+                "id": wanted,
+                "state": "REJECTED_WITH_REASON",
+                "blockers": ["UNKNOWN_JOB", "NOT_APPROVED"],
+            }
+    cuda = bool(hw.get("cuda_available"))
+    return {
+        "ok": False,
+        "decision": "BLOCKED",
+        "honesty": "UNAVAILABLE",
+        "channel": "LIVE",
+        "submit_this_run": False,
+        "approved": False,
+        "proven_trust": False,
+        "conjecture_1": "OPEN",
+        "job": refused,
+        "missing": missing,
+        "hologram_gaps": [g for g in HOLOGRAM_GAPS if g in missing or g == "HOLOGRAM_IS_PYTHON_SLIM" or g == "UNSLOTH_ABSENT"],
+        "registry_gaps": list(REGISTRY_GAPS),
+        "gpu": {
+            "nvml_readable": bool(hw.get("nvml_readable")),
+            "pynvml_import": bool(hw.get("pynvml_import")),
+            "torch_import": bool(hw.get("torch_import")),
+            "torch_version": hw.get("torch_version"),
+            "cuda_available": cuda,
+            "cuda_device": hw.get("cuda_device"),
+            "nvidia_smi": hw.get("nvidia_smi"),
+        },
+        "owner_metal": {
+            "kit": "szl-holdings/szl-forge",
+            "bridge": "szl-holdings/szl-gpu-bridge",
+            "note": "Unsloth QLoRA is owner-metal. gpu-bridge attempts 1–9 are NEVER_DISPATCH evidence. Not this T4 hologram.",
+        },
+        "existing_adapters": [
+            "SZLHOLDINGS/chaski",
+            "SZLHOLDINGS/chaski-5050",
+            "SZLHOLDINGS/KHIPU-R2",
+            "SZLHOLDINGS/SZL-Khipu-1.5B",
+            "SZLHOLDINGS/SZL-Forge-1.5B-ReceiptAgent",
+            "SZLHOLDINGS/szl-receiptagent-qwen35-0.8b-v2",
+        ],
+        "note": (
+            "T4 is mounted. NVML can MEASURE board joules. This hologram is "
+            "python:3.12-slim — no CUDA runtime, no Unsloth, no approved job. "
+            "Existing Hub adapters are prior trains, not a new GPU train. "
+            "WILLAY / KHIPU-R3 / Waman stay REJECTED_WITH_REASON. Never a fabricated train."
+        ),
+    }
+
+
+def toy(*, duration_s: float = 1.0) -> dict[str, Any]:
+    """Tiny CUDA fit. Refused when CUDA is absent. Never a CPU stand-in billed as GPU train."""
+    del duration_s  # reserved for a future CUDA wrap
+    g = gate()
+    g["kind"] = "toy_cuda_fit"
+    g["trained"] = False
+    g["weights"] = None
+    g["reason"] = "CUDA_RUNTIME_ABSENT. Toy GPU fit refused. A CPU fit is not a GPU train."
+    if g["gpu"]["cuda_available"]:
+        # Reachable only after a CUDA hologram exists. Still refuse registry jobs.
+        g["reason"] = (
+            "CUDA is up. Registry still NOT_APPROVED. Toy fit is not willay, "
+            "not khipu-r3, not Waman, not Unsloth. Compiler stays BLOCKED."
+        )
+    return g
+
+
+if __name__ == "__main__":
+    print(json.dumps({"gate": gate(), "toy": toy()}, indent=2))