docs: bootstrap 1b project — epic, issues, open-1b init audit report (#1)

.gitignore

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+# derived / bulky workdirs
+audit/
+inference/
+gitea/
+.venv/
+.venv-*/
+# python / wheels / models
+*.whl
+*.gguf
+__pycache__/

README.md

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+# 1b — Gensyn open-1b
+
+Независимая верификация *auditable training* Gensyn **open-1b** и локальный запуск модели.
+
+- **Epic:** vado/1b#1
+- **Отчёты:** [`reports/`](reports/)
+- **Тела issue:** [`docs/issues/`](docs/issues/)
+
+## Итоги (кратко)
+
+| Задача | Статус |
+|--------|--------|
+| Аудит init-unit open-1b (CPU) | ✅ **MATCH** — `state_hash 16554a11…`; см. [`reports/audit-open1b-init.md`](reports/audit-open1b-init.md) |
+| Аудит тренировочного интервала | ⛔ заблокирован (нет опубликованного interval-unit + RAM/диск) |
+| Локальный inference на Arc B580 | 🔄 в работе |
+
+## Ссылки
+
+- Анонс: https://www.gensyn.ai/news/introducing-open-1b-auditable-training
+- Harness: https://github.com/gensyn-ai/open-transformers
+- Audit app: https://open1b.gensyn.ai/
+
+## Ограничения (по состоянию на 2026-09)
+
+- `repop` (воспроизводимые ядра) — **не open source**, только wheel под «Gensyn Reproducibility License v1.0».
+- v3-хэш **не покрывает** RNG, курсор data-stream, spike state и ключи `meta.json`.
+- В self-serve audit-ките опубликованы **только init-units**; interval-units — «added per run once … published».

docs/issues/01-epic.md

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+# Epic: Gensyn open-1b — верификация auditable training и локальный inference
+
+**Цель.** Независимо проверить заявление Gensyn о *bitwise auditable training* (open-1b) на нашем железе и запустить модель локально; зафиксировать факты, ограничения и решения.
+
+## Контекст
+
+- Анонс 2026-09-15: https://www.gensyn.ai/news/introducing-open-1b-auditable-training (+ PRNewswire 302878850)
+- Harness: https://github.com/gensyn-ai/open-transformers (Apache-2.0)
+- Audit CLI: https://github.com/gensyn-ai/gensyn-audit
+- Audit app: https://open1b.gensyn.ai/ (manifest: https://open1b.gensyn.ai/manifest.json)
+- Модель: HF `Gensyn/open-1b-base`, `-midtrained-93B`, `-sft`
+- Модель: 1.61B total / 1.08B non-emb, 24 слоя, 400B токенов, 80 957 шагов, 48×H100
+- 2dph info-leaf (PO, 2026-09-28): `6703767319c6e2f9fa6d63465934d72e`
+
+## Дети эпика
+
+- `#AUDIT-INIT` — Аудит init-unit open-1b (CPU, Linux x86-64)
+- `#AUDIT-INTERVAL` — Аудит тренировочного интервала open-1b (заблокировано)
+- `#INFERENCE` — Локальный запуск open-1b на Arc B580 (llama.cpp Vulkan)
+- `#REPORT` — Сводный отчёт и запись фактов в 2dph
+
+## Критерий закрытия эпика
+
+Все дочерние issues закрыты с доказательствами (тест/лог/хэш). Заблокированный
+интервальный аудит может остаться открытым, если блокер явно задокументирован
+(нет опубликованного interval-unit + ресурсы хоста).

docs/issues/02-audit-init.md

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+Epic: #EPIC
+
+## Цель
+
+Независимо воспроизвести опубликованный **init-хэш** open-1b официальным harness'ом
+на CPU (Linux x86-64, без NVIDIA).
+
+## Критерии приёмки
+
+- [x] kit `pt-f91110a0d0c8_rp-c9ca6e71e673` скачан; sha256 **всех** файлов сверены с `kit.json`
+- [x] `repop.build_info().commit == kit.json.repop_commit` (`c9ca6e71e673`)
+- [x] `pretrain-audit-replay --from-init --until-step 0 --config-name 1b_repop_v2 --device cpu` → `match=true`
+- [x] отчёт с raw-выводом и таблицей sha256
+
+## Результат (2026-09-28)
+
+✅ **MATCH**. `state_hash = 16554a1119745f1b9bf4ac60b03226e5e9ca1247a2bd56169cd4c822fd457aed`,
+wall 58.3 s, peak RSS 16.8 GB, exit 0.
+
+Отчёт: `audit/REPORT.md`.
+
+## Ограничение
+
+Init-unit по README **не** проверяет тренировочный интервал — это отдельная задача
+`#AUDIT-INTERVAL`.

docs/issues/03-audit-interval.md

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+Epic: #EPIC
+
+## Цель
+
+Воспроизвести **тренировочный интервал** (replay шага против опубликованного hash) —
+именно это доказывает заявление «bitwise auditable training», в отличие от init-unit.
+
+## Критерии приёмки
+
+- [ ] получен interval-unit с canonical target hash (published commitment на шаг)
+- [ ] скачан чекпоинт + шарды, потреблённые интервалом
+- [ ] `pretrain-audit-replay --checkpoint … --until-step N --gcs-root … --expect-hash …` → `MATCH`
+- [ ] отчёт с raw-выводом
+
+## Блокер (2026-09-28)
+
+- ⛔ В kit `pt-f91110a0d0c8_rp-c9ca6e71e673` `trajectory.json` содержит **только init-units**
+  (`100m_smoke_repop`, `1b_repop_run3`, `1b_repop_v2`). Interval-units «added per run once its
+  checkpoints and state_hash files are published» — **не опубликованы**. Self-serve кит
+  не определяет commit на шаг.
+- ⛔ Ресурсы хоста: нужно ~24 ГБ RAM (есть ~11 ГБ) и ≥60 ГБ диска (есть 39 ГБ);
+  один чекпоинт `ckpt/step_000000100/` = 19.31 ГБ.
+- Решение по разблокировке (владелец — PO/пользователь): запросить у audit-app interval-unit,
+  либо выполнять на хосте с ≥32 ГБ RAM / ≥60 ГБ диска (предпочтительно NVIDIA `--device cuda`).
+
+## Примечание
+
+Per-step log доступен на `gs://gensyn-open-1b/logs/state_hashes.jsonl`; harness не умеет
+автоподстановку, а audit-app гейтит сабмиты — это тоже часть блокера.

docs/issues/04-inference.md

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+Epic: #EPIC
+
+## Цель
+
+Поднять open-1b локально и доказать работоспособность на нашем железе
+(Intel Arc B580, Vulkan; без NVIDIA/CUDA).
+
+## Критерии приёмки
+
+- [ ] llama.cpp собран с Vulkan; бэкенд активен на Arc B580
+- [ ] веса HF (`Gensyn/open-1b-sft`, fallback `-base`) скачаны, provenance = точная ревизия
+- [ ] конвертация в GGUF; собран/выбран квант
+- [ ] `llama-cli`/`llama-server` даёт связный ответ; замер tok/s и VRAM
+- [ ] отчёт с точными командами и caveat'ами
+
+## Прочее
+
+- Сервисы — только docker compose (не systemd).
+- Обвязка — Go; Python только через `uv` (канонический `convert_hf_to_gguf.py`).
+
+## Статус
+
+🔄 выполняется фоновым SE-субагентом (2026-09-28).

docs/issues/05-report.md

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+Epic: #EPIC
+
+## Цель
+
+Свести результаты в отчёт и записать проверенные факты в 2dph (brain), пометив
+что подтверждено, а что остаётся ограничением.
+
+## Критерии приёмки
+
+- [ ] сводный отчёт (что доказано / что нет) в репо
+- [ ] info-leaf в 2dph с итогом (source: `po/gensyn`)
+- [ ] явно зафиксированы ограничения: `repop` closed-source, v3-hash не покрывает RNG/cursor/spike/meta, interval-unit не опубликован
+
+## Статус
+
+info-leaf записан: `6703767319c6e2f9fa6d63465934d72e`. Отчёт — по завершении #INFERENCE и #AUDIT-INTERVAL.

reports/audit-open1b-init.md

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+# Gensyn OPEN-1B audit — independent replay (CPU, Linux x86-64)
+
+- **Date:** 2026-09-28
+- **Host:** `brainstation`, Linux x86-64, kernel `7.3.0-070300rc1-generic` (Ubuntu), **no NVIDIA GPU**
+- **Auditor:** SE sub-agent (independent)
+- **Workdir:** `/root/projects/gensyn/audit`
+- **Harness:** `gensyn-ai/open-transformers` @ `d7b7b674cd851f7a16815229f060658180cb772b`
+  ("Initial commit: the OPEN-1B pretraining and audit-replay harness", 2026-09-15), cloned via git.
+- **Verdict:** ✅ **MATCH** on the `1b_repop_v2` init unit. ❌ No training-interval
+  replay run (not defined by this kit and not feasible on this host — see §7).
+
+---
+
+## 1. Kit selection
+
+Four kits were listed. All four `trajectory.json` files declare the **same**
+`1b_repop_v2` init commitment
+`16554a1119745f1b9bf4ac60b03226e5e9ca1247a2bd56169cd4c822fd457aed`, so the choice
+of kit does not change the init hash under test. The authoritative mapping is
+published by the audit app itself at `https://open1b.gensyn.ai/manifest.json`:
+
+```json
+"run":   { "id": "20260722-213626-ad3276b", "model": "1b_repop_v2",
+           "initStateHash": "16554a1119745f1b9bf4ac60b03226e5e9ca1247a2bd56169cd4c822fd457aed" },
+"audit": { "kit": { "id": "pt-f91110a0d0c8_rp-c9ca6e71e673",
+                    "urlBase": "https://storage.googleapis.com/gensyn-audit-public/audit-kit/pt-f91110a0d0c8_rp-c9ca6e71e673" } }
+```
+
+**Kit under test: `pt-f91110a0d0c8_rp-c9ca6e71e673`.**
+
+- `pretrain_commit`: `f91110a0d0c84fa3bad808f365567d9c655d10b2`
+- `repop_commit`:    `c9ca6e71e673660afc6c87de2592fa6f62c87b15`
+- `torch_requirement`: `torch==2.10.0`
+
+(The other three kits — `pt-cb4ac29438bc_rp-…`, `pt-f6bc086dfebd_rp-…`,
+`pt-f5eece09abe6_rp-…` — carry the same init commitment but are older
+pretrain/repop pins. Two share the `c9ca6e71e673` repop but a different pretrain
+commit; the app manifest picks `f91110a0d0c8`.)
+
+## 2. Toolchain
+
+| Component | Version / identity |
+|---|---|
+| Python | 3.11.16 (managed by `uv`; system Python 3.14 untouched) |
+| `uv` | 0.12.17 |
+| PyTorch | `2.10.0+cpu` (`torch.version.cuda == None`) |
+| `repop` | 0.1.5, `build_info().commit == c9ca6e71e673660afc6c87de2592fa6f62c87b15` ✅ (== kit.json `repop_commit`); backends `["cpu","cuda"]` |
+| `pretrain` | 0.1.0 (kit wheel) |
+| Go (glue tools) | go1.27.0 (fabric rule: all glue/parsing in Go) |
+
+**Deviation, stated plainly:** the RUNBOOK targets Linux hosts with an NVIDIA GPU
+and points them at the CUDA 12.9 PyTorch index. This host has no GPU, and the
+README names CPU as the *reference* device, so the exact pin `torch==2.10.0` was
+installed from PyTorch's official **CPU** index (`.../whl/cpu`, wheel
+`2.10.0+cpu`). The pinned version is unchanged; only the CPU build variant was
+chosen deliberately, not by an accidental PyPI fallback. Init is device-independent
+by construction (see §6), so this does not weaken the init result.
+
+Python (`uv`-managed) is used **only** because the vendor harness is Python and
+ships as wheels; all download/verification/listing glue is Go under `tools/`
+(`kitinspect`, `trajinspect`, `kitfetch`, `gslist`).
+
+## 3. Commands run
+
+```bash
+# workdir + docs
+mkdir -p /root/projects/gensyn/audit && cd /root/projects/gensyn/audit
+git clone --depth 1 https://github.com/gensyn-ai/open-transformers
+
+# kit manifests + trajectories (Go inspector)
+go run ./tools/kitinspect kits/*/
+go run ./tools/trajinspect kits/*/trajectory.json
+
+# download + per-file sha256 verification against kit.json (Go tool,
+# downloads to .part, verifies, removes on mismatch)
+go run ./tools/kitfetch kits/pt-f91110a0d0c8_rp-c9ca6e71e673 \
+                        kit-pt-f91110a0d0c8_rp-c9ca6e71e673
+
+# Python 3.11 env
+uv venv --python 3.11 .venv
+uv pip install --python .venv --index-url https://download.pytorch.org/whl/cpu "torch==2.10.0"
+uv pip install --python .venv \
+    ./kit-.../repop-0.1.5-cp311-cp311-linux_x86_64.whl \
+    ./kit-.../pretrain-0.1.0-cp311-cp311-linux_x86_64.whl
+
+# provenance assertions
+.venv/bin/python -c "import repop,json; print(repop.build_info())"
+
+# THE AUDIT (init unit)
+PRETRAIN_AUDIT_MEMLOG=1 /usr/bin/time -v .venv/bin/pretrain-audit-replay \
+    --from-init --until-step 0 \
+    --config-name 1b_repop_v2 \
+    --device cpu \
+    --expect-hash 16554a1119745f1b9bf4ac60b03226e5e9ca1247a2bd56169cd4c822fd457aed
+```
+
+## 4. SHA-256 verification table (all 5 kit files)
+
+Every file was hashed **before** install; the Go fetcher adopts a file only on a
+full 64-hex match and deletes rejected bytes. Expected values are read from the
+kit's own `kit.json`.
+
+| File | expected (`kit.json`) | computed | result |
+|---|---|---|---|
+| `pretrain-0.1.0-cp311-cp311-linux_x86_64.whl` | `ecc49d1c05c0e2876a59d98d877795769d6e9620eb66e4b4c866b16f695fb174` | same | ✅ OK |
+| `pretrain-0.1.0-cp311-cp311-macosx_14_0_arm64.whl` | `fbd23a54aa0bf87775e86493d67f759d1c1f4cc1dcd63ad991fba59dcb92491c` | same | ✅ OK |
+| `repop-0.1.5-cp311-cp311-linux_x86_64.whl` | `15f171643871211b2a772ee83c94833c0be2eef0495790cedc33813c95147ff0` | same | ✅ OK |
+| `repop-0.1.5-cp311-cp311-macosx_14_0_arm64.whl` | `d8658e0327c7278812ecb6dd455cd4cf8723a974a78788adba41d5f747289c69` | same | ✅ OK |
+| `trajectory.json` | `9435515c37d8956d0c81d5bc78c0a383bb6bf27c57b5dbaf1f8be564df0b324a` | same | ✅ OK |
+
+Byte sizes also matched `kit.json`. Only the two **linux_x86_64** wheels were
+installed; the macOS arm64 wheels were downloaded and verified but not installed.
+
+## 5. Init-unit result — MATCH
+
+Raw result object printed by the harness (stdout, exit status 0):
+
+```json
+{
+  "step": 0,
+  "consumed_tokens": 0,
+  "state_hash": "16554a1119745f1b9bf4ac60b03226e5e9ca1247a2bd56169cd4c822fd457aed",
+  "mode": "init",
+  "repop": { "commit": "c9ca6e71e673660afc6c87de2592fa6f62c87b15",
+             "backends": ["cpu", "cuda"], "cuda_arch_list": "7.5 8.0 9.0" },
+  "device": "cpu",
+  "expected":  "16554a1119745f1b9bf4ac60b03226e5e9ca1247a2bd56169cd4c822fd457aed",
+  "match": true,
+  "cpu_threads": { "requested": "auto", "source": "runtime-default",
+                   "torch_num_threads": 8, "omp_num_threads": null, "mkl_num_threads": null }
+}
+```
+
+Log line: `from-init: regenerated init state_hash=16554a1119745f1b expected=16554a1119745f1b MATCH=True`.
+Config `1b_repop_v2`, seed `42`, loss path `fused CE+z-loss`. The only warning is
+the expected `not distributed + no CUDA — parallelize applies AC only (FSDP
+skipped; dev mode)`, i.e. the documented CPU reference path.
+
+**Resource notes:** wall **58.3 s**, user 78.5 s / sys 61.1 s, **peak RSS
+16.80 GB** (16,804,956 KB), **0 swaps**, exit 0. (README/RUNBOOK size this unit at
+~21.9 GB peak on CPU; we measured 16.8 GB. Free RAM was ~11 GB and the unit still
+completed without swapping, so the doc figure is conservative.)
+
+## 6. What this proves — and what it does not
+
+**Proves.** The bytes installed are the bytes `kit.json` published (all five
+SHA-256s match). The `repop` kernel build is the one the kit claims
+(`build_info().commit == repop_commit`). Running the vendor harness on this
+CPU, from seed, the `1b_repop_v2` **initial state** — seeded device-independent
+trunc-normal init plus zeroed optimizer moments — reproduces the published
+canonical hash `16554a11…` **bit-for-bit**. Independent third-party
+reproduction of the run's init commitment: ✅.
+
+**Does not prove.**
+
+1. **No training interval.** Per the README: "An initialization-only unit does
+   not verify a training interval." A match here says nothing about any forward,
+   backward, AdamW or data-stream step. The claimed bitwise reproducibility of
+   *optimizer steps* is **not** tested by this run.
+2. **`repop` is closed source.** Only compiled wheels are shipped; the kernel
+   arithmetic that makes training bitwise reproducible cannot be read or
+   independently re-derived from this kit. The init unit does not even exercise
+   the kernels that the recent `c9ca6e71e673` repin changed (the trajectory notes
+   say exactly this), so a match is *not* evidence for the kernel-level BFR
+   contract at that commit.
+3. **v3-hash coverage.** The README states the v3 hash covers weights, optimizer
+   state, gradients and the batch digest, but **not** RNG, the data-stream
+   cursor, spike state, or the `meta.json` descriptor keys. Even a matching
+   interval hash would leave those unverified.
+4. **Init is the easy case by design.** `init.py` samples Philox on CPU and
+   byte-copies, so it is device-independent; it is expected to match across
+   devices. The hard cross-device claim lives in the training kernels, which
+   this unit does not touch.
+5. Provenance of the *published run* is not established; only that the pinned
+   artifacts reproduce the published commitment on this machine.
+
+## 7. Step-interval replay — deliberately not attempted
+
+Stopping after the init unit is a considered decision, not a stall:
+
+- **Not defined by the kit.** This kit's `trajectory.json` (`init-units-v1`)
+  contains **only 3 init units** — `100m_smoke_repop`, `1b_repop_run3`,
+  `1b_repop_v2`. Its own note says: "Step-interval units are added per run once
+  its checkpoints and state_hash files are published." **No interval unit with a
+  canonical target hash is published here**, so the kit defines no
+  step-interval commitment to check. (The run's per-step log exists at
+  `gs://gensyn-open-1b/logs/state_hashes.jsonl`, but the harness has no automatic
+  lookup and the audit app gates submissions.)
+- **Memory.** A step-interval replay needs ~24 GB (README), and the audit's
+  auto-offload only reaches "every published unit" at that figure. This host had
+  ~11 GB RAM available (29 GB total, 18 GB in use); an init unit already peaked at
+  16.8 GB. The heavy replay would swap-thrash and would not fit honestly.
+- **Disk/size.** One checkpoint `ckpt/step_000000100/` is **19.31 GB**
+  (150 objects); the full `ckpt/` prefix is **15.64 TB** (810 checkpoint dirs).
+  With 39 GB free, a single checkpoint is tight against free space and the
+  documented `--from-init + --gcs-root` combination is broken (wrong shard
+  anchor), so a from-init interval would first require staging shards via
+  `--data-root`.
+
+Re-attempting an interval audit should be done on a host with ≥32 GB free RAM
+(NVIDIA GPU preferred: `--device cuda`) and ≥60 GB free disk.
+
+## 8. Files produced
+
+- `open-transformers/` — harness clone (docs read: `README.md`,
+  `docs/audit-replay-usage.md`, `scripts/audit_volunteer/RUNBOOK.md`)
+- `kits/<kit>/kit.json`, `kits/<kit>/trajectory.json` — manifests
+- `kit-pt-f91110a0d0c8_rp-c9ca6e71e673/` — verified wheels + trajectory
+- `.venv/` — Python 3.11 audit env
+- `init-replay.log` — full captured replay output + `/usr/bin/time -v`
+- `tools/{kitinspect,trajinspect,kitfetch,gslist}` — Go glue
+- `REPORT.md` — this file
+
+No secrets were written. Nothing outside the workdir was modified or deleted.