Check the release in one command (simple/check_release.sh)

README.md

@@ -65,26 +65,22 @@ segment was recomputed bit for bit on a second machine. The other terms are defi
 ollama run ryoari/openverifiablellm "Tell me about the Moon."
 ```
 
-**2. Consistency check, no GPU (10 minutes).** Needs Python 3.12 or newer, `git`, `openssl`,
-`sha256sum` and network access. On macOS, `sha256sum` comes with `brew install coreutils` (as
-`gsha256sum`).
+**2. Consistency check, no GPU (about 2 minutes).** Needs Python 3.12 or newer, `git`, `openssl`
+and network access. One command sets up a CPU-only Python environment, downloads the release without
+its checkpoints, checks the downloaded files against their hash list, and checks the record and the
+weights:
 
 ```bash
-pip install huggingface_hub torch numpy
-hf download AOSSIE/openverifiable-enwiki-20260901-20260918-r1-evidence \
-  --repo-type dataset --include "release/simple-run/*" --exclude "*/ckpt-*" --local-dir ovl
-cd ovl/release/simple-run
-sha256sum -c --ignore-missing release-hashes.txt
-git clone -q --depth 1 --branch v1.1.0 https://github.com/AOSSIE-Org/OpenVerifiableLLM ovl-code
-OVL_DEVICE=cpu python ovl-code/simple/ovl.py verify --run . --weights conversation-model.pt
+git clone -q --depth 1 https://github.com/AOSSIE-Org/OpenVerifiableLLM
+bash OpenVerifiableLLM/simple/check_release.sh
 # anchor anchor.json: chain head MATCH (38 entries)
 # anchor timestamp freetsa: OK (Oct 20 14:38:43 2026 GMT)
 # anchor timestamp digicert: OK (Oct 20 14:38:43 2026 GMT)
 # weights conversation-model.pt: MATCH chain entry 37
+# OVL release check PASS: the released model matches its timestamped training record.
 ```
 
-Use `ovl.py` from the v1.1.0 tag (v1.0.2 or newer works too). The copy in the download's `code/`
-folder is older and does not check the anchor.
+To run each step yourself, pinned to the v1.1.0 code, see [docs/verify.md](docs/verify.md#1-consistency-check-without-a-gpu).
 
 **3. Verification, on an RTX 5090 (about 1 hour, about US$1.50).**
 [Deploy the RunPod template](https://console.runpod.io/deploy?template=mai1ozh35g), wait, and read

docs/verify.md

@@ -17,12 +17,16 @@ folder `release/simple-run/`. The terms (segment, boundary, chain entry, anchor)
 
 ## 1. Consistency check, without a GPU
 
-Needs Python 3.12 or newer, `git`, `openssl`, `sha256sum` and network access. On macOS,
-`sha256sum` comes with `brew install coreutils` (as `gsha256sum`). Download `release/simple-run/`
+`bash simple/check_release.sh`, from a clone of this repository, does all of this in one command (about
+2 minutes). By hand, it needs Python 3.12 or newer, `git`, `openssl`, `sha256sum` and network access. On
+macOS, `sha256sum` comes with `brew install coreutils` (as `gsha256sum`). Download `release/simple-run/`
 without the `ckpt-*.pt` files, then from that folder:
 
 ```bash
-pip install huggingface_hub torch numpy
+# On Linux, add --index-url https://download.pytorch.org/whl/cpu to the torch install: the default
+# download includes CUDA (several GB), and this check needs only the CPU.
+pip install torch
+pip install huggingface_hub numpy
 sha256sum -c --ignore-missing release-hashes.txt   # every downloaded file matches the hash list
 git clone -q --depth 1 --branch v1.1.0 https://github.com/AOSSIE-Org/OpenVerifiableLLM ovl-code
 OVL_DEVICE=cpu python ovl-code/simple/ovl.py verify --run . --weights conversation-model.pt

simple/README.md

@@ -10,6 +10,7 @@ see [verify](../docs/verify.md).
 
 | I want to… | Run | Needs |
 |---|---|---|
+| Check the release in one command (download, hashes, record, weights) | `bash simple/check_release.sh` | any CPU, ~2 minutes |
 | Check the released weights and record | `python simple/ovl.py verify --run RUN --weights RUN/conversation-model.pt` | any CPU |
 | Check one training segment of the release | `bash simple/verify_segment.sh` | RTX 5090 |
 | Do that in one click on a fresh pod | the RunPod template in [`checker_template.md`](checker_template.md), which runs [`checker_pod.sh`](checker_pod.sh) | RTX 5090 pod |
@@ -34,6 +35,7 @@ On a CPU, set `OVL_DEVICE=cpu`.
 | [`ovl.py`](ovl.py) | The loop. Commands: `train`, `verify` (`--weights`, `--segment`, `--random`, `--all`, `--data`; it needs the run's `anchor.json` and its two timestamps, or `--anchor FILE`; `--no-anchor` and `--no-timestamps` are only for a run that hasn't been anchored yet), `fork`, `chat`, `bench` |
 | [`model.py`](model.py), [`data.py`](data.py) | The GPT model, and the token ids, batch layout and seeding shared with the data preparation (copied unchanged from commit `3f882ad`) |
 | [`stamp.py`](stamp.py) | RFC 3161 timestamps (FreeTSA and DigiCert) for each chain entry while training runs; `--check` verifies them. `OVL_TIMESTAMP=0` turns stamping off |
+| [`check_release.sh`](check_release.sh) | The laptop check in one command: a CPU-only Python environment, the release without its checkpoints, the hash list, then `ovl.py verify` |
 | [`verify_segment.sh`](verify_segment.sh) | Downloads the release's data, record and the needed checkpoints, then checks `K` random segments (or `SEGMENTS="7 8"`) |
 | [`checker_pod.sh`](checker_pod.sh) | One-click check for a fresh RTX 5090 pod: fetches the release code at a pinned revision, runs `verify_segment.sh`, prints one result line to share |
 | [`checker_template.md`](checker_template.md) | The description and start command of the public RunPod template |

simple/check_release.sh

@@ -0,0 +1,74 @@
+#!/usr/bin/env bash
+# The consistency check of the released model in one command, on any computer, no GPU.
+#
+#   git clone --depth 1 https://github.com/AOSSIE-Org/OpenVerifiableLLM
+#   bash OpenVerifiableLLM/simple/check_release.sh            # works in ./ovl-check
+#
+# It makes a Python environment (CPU-only PyTorch), downloads the release without its
+# checkpoints (about 330 MB; the Python environment takes about 1 GB), checks every downloaded file against release-hashes.txt, then runs
+# `ovl.py verify`: the record's hash chain, its two timestamps, and the released weights.
+# Takes about 2 minutes. Needs Python 3.12 or newer, git, openssl and network access. Set OVL_PYTHON to use an existing
+# Python that already has torch, numpy and huggingface_hub, and skip the install.
+# It recomputes no training: that needs an RTX 5090 (docs/verify.md).
+set -euo pipefail
+
+WORK=${1:-ovl-check}
+RUN_PATH=${RUN_PATH:-release/simple-run}
+REPO=AOSSIE/openverifiable-enwiki-20260901-20260918-r1-evidence
+CODE=$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)
+mkdir -p "$WORK"; WORK=$(cd "$WORK" && pwd)
+fail() { echo "OVL release check FAIL: $*" >&2; exit 1; }
+
+command -v openssl >/dev/null || fail "openssl not found; it checks the record's timestamps"
+if [ -n "${OVL_PYTHON:-}" ]; then
+  PY=$OVL_PYTHON
+else
+  BASE=$(command -v python3 || command -v python) || fail "Python 3.12 or newer not found"
+  "$BASE" -c 'import sys; sys.exit(sys.version_info < (3, 12))' || fail "needs Python 3.12 or newer, found $("$BASE" -V)"
+  if [ ! -x "$WORK/venv/bin/python" ]; then
+    echo "== Python environment in $WORK/venv"
+    "$BASE" -m venv "$WORK/venv"
+    "$WORK/venv/bin/python" -m pip install -q --upgrade pip
+    # On Linux the default PyTorch download includes CUDA (several GB); this check needs only the CPU.
+    [ "$(uname -s)" = Linux ] && TORCH_INDEX=(--index-url https://download.pytorch.org/whl/cpu) || TORCH_INDEX=()
+    "$WORK/venv/bin/python" -m pip install -q "${TORCH_INDEX[@]}" torch
+    "$WORK/venv/bin/python" -m pip install -q numpy huggingface_hub
+  fi
+  PY=$WORK/venv/bin/python
+fi
+
+echo "== Downloading $RUN_PATH (without checkpoints)"
+"$PY" - "$REPO" "$RUN_PATH" "$WORK" <<'PY'
+import sys
+from huggingface_hub import snapshot_download
+repo, path, out = sys.argv[1:]
+snapshot_download(repo, repo_type="dataset", allow_patterns=[f"{path}/*"], ignore_patterns=[f"{path}/ckpt-*"],
+                  local_dir=out)
+PY
+RUN=$WORK/$RUN_PATH
+
+echo "== Checking downloaded files against release-hashes.txt"
+"$PY" - "$RUN" <<'PY' || fail "a downloaded file differs from release-hashes.txt"
+import hashlib, sys
+from pathlib import Path
+run, bad, n = Path(sys.argv[1]), 0, 0
+for line in (run / "release-hashes.txt").read_text(encoding="utf-8").splitlines():
+    want, name = line.split(maxsplit=1)
+    f = run / name.lstrip("*")
+    if not f.is_file():
+        continue  # not downloaded, like the checkpoints
+    h = hashlib.sha256()
+    with f.open("rb") as fh:
+        for chunk in iter(lambda: fh.read(1 << 20), b""):
+            h.update(chunk)
+    n += 1
+    if h.hexdigest() != want:
+        print(f"{name}: FAILED"); bad += 1
+print(f"{n} files: {'all match' if not bad else f'{bad} differ'}")
+sys.exit(1 if bad or not n else 0)
+PY
+
+echo "== Checking the record and the released weights"
+OVL_DEVICE=cpu "$PY" "$CODE/simple/ovl.py" verify --run "$RUN" --weights "$RUN/conversation-model.pt" \
+  || fail "verify did not pass (see above)"
+echo "OVL release check PASS: the released model matches its timestamped training record."