13 Commits

Author SHA1 Message Date
Zayden-Jung 41811f6bc3 Merge pull request 'ci: 仅 main 分支执行 CI/CD' (#10) from codex/main-only-cicd into main
ci / python (push) Successful in 15s
env-probe / probe (push) Successful in 28s
ci / lean (push) Successful in 33s
ci / image (push) Successful in 1m12s
runner-probe / probe (push) Has been cancelled
Reviewed-on: #10
2026-11-03 19:05:25 +00:00
codex-bot 10a50e32db ci: restrict workflows to main branch 2026-10-30 03:44:05 +08:00
Zayden-Jung a80448ae36 Merge pull request 'Add semantic simplex schemas, review page and resumable pilot recovery' (#9) from codex/simplex-registry into main
ci / python (push) Successful in 17s
ci / lean (push) Successful in 29s
ci / image (push) Successful in 2m46s
Reviewed-on: #9
2026-10-28 13:55:55 +00:00
codex-bot 3453d5c961 Merge pilot recovery into the semantic simplex schema delivery
ci / python (pull_request) Successful in 16s
ci / lean (pull_request) Successful in 29s
ci / image (pull_request) Has been skipped
2026-10-28 21:48:23 +08:00
codex-bot 4eee78be09 docs(schema): track the 65-item schema review page
ci / python (pull_request) Successful in 16s
ci / lean (pull_request) Successful in 29s
ci / image (pull_request) Has been skipped
2026-10-28 21:42:45 +08:00
codex-bot 29fe3e1aa5 feat(schema): persist and instantiate scoped multi-role relation schemas
ci / python (pull_request) Successful in 17s
ci / lean (pull_request) Successful in 1m6s
ci / image (pull_request) Has been skipped
2026-10-28 21:26:55 +08:00
Zayden-Jung 7d2c6f470b Merge pull request 'Diagnose and safely expand the Lean runner root filesystem' (#8) from codex/runner-storage-probe into main
ci / python (push) Successful in 12s
ci / lean (push) Successful in 28s
ci / image (push) Successful in 1m2s
Reviewed-on: #8
2026-10-28 12:23:35 +00:00
codex-bot 36fd787c43 docs: record authorized runner root filesystem expansion
ci / python (pull_request) Successful in 17s
ci / lean (pull_request) Successful in 1m18s
ci / image (pull_request) Has been skipped
2026-10-28 20:21:48 +08:00
codex-bot 96a1763392 ci: add guarded manual root disk expansion for the Lean runner 2026-10-28 20:18:48 +08:00
codex-bot 6a65435702 ci: add read-only runner storage diagnostics 2026-10-28 20:13:32 +08:00
Zayden-Jung d9389fd1c0 Merge pull request 'Reassess all 65 P0 items in a separate GPT-assisted diagnostic' (#7) from codex/gpt-diagnostic into main
ci / python (push) Successful in 13s
ci / lean (push) Successful in 26s
ci / image (push) Successful in 1m5s
Reviewed-on: #7
2026-10-28 11:30:09 +00:00
codex-bot 1c265609d5 docs(pilot): link the recovery audit to the follow-up PR
ci / python (pull_request) Successful in 13s
ci / lean (pull_request) Successful in 27s
ci / image (pull_request) Has been skipped
2026-10-28 19:08:30 +08:00
codex-bot 16e49df764 fix(pilot): preserve partial results and stop on provider billing errors
ci / python (pull_request) Successful in 17s
ci / lean (pull_request) Successful in 1m21s
ci / image (pull_request) Has been skipped
2026-10-28 19:04:43 +08:00
22 changed files with 11884 additions and 61 deletions
+4 -3
View File
@@ -11,8 +11,7 @@ name: ci
on:
push:
branches: [main, "ci/**"]
pull_request:
branches: [main]
workflow_dispatch:
env:
@@ -20,6 +19,7 @@ env:
jobs:
python:
if: gitea.ref == 'refs/heads/main'
runs-on: ubuntu24.04-x64-lean4.35
timeout-minutes: 20
steps:
@@ -50,6 +50,7 @@ jobs:
.venv/bin/lean-bench doctor --skip-llm --env /dev/null
lean:
if: gitea.ref == 'refs/heads/main'
needs: python
runs-on: ubuntu24.04-x64-lean4.35
timeout-minutes: 150
@@ -82,7 +83,7 @@ jobs:
image:
needs: [python, lean]
if: github.event_name != 'pull_request'
if: ${{ gitea.ref == 'refs/heads/main' && (github.event_name != 'pull_request') }}
runs-on: ubuntu24.04-x64-lean4.35
timeout-minutes: 180
steps:
+19 -1
View File
@@ -2,13 +2,14 @@ name: env-probe
on:
push:
branches: ["ci/**"]
branches: [main]
paths:
- ".gitea/workflows/env-probe.yml"
workflow_dispatch:
jobs:
probe:
if: gitea.ref == 'refs/heads/main'
runs-on: ubuntu24.04-x64-lean4.35
timeout-minutes: 15
steps:
@@ -29,3 +30,20 @@ jobs:
(find / -maxdepth 4 \( -name 'lake-manifest.json' -o -name '.lake' \) -not -path '/proc/*' 2>/dev/null | head -20) || true
(docker images 2>&1 | head -20) || true
(docker ps -a 2>&1 | head -10) || true
- name: Read-only storage diagnosis
run: |
set -eu
hostname
lsblk -e 7 -o NAME,PATH,SIZE,FSTYPE,MOUNTPOINTS
findmnt -T /var/lib/docker
df -hT / /var/lib/docker
docker info --format 'storage={{.Driver}} root={{.DockerRootDir}}'
docker system df
docker builder du 2>/dev/null || true
for dir in /var/lib/docker /var/lib/containerd /opt/lean-cache /var/cache /tmp /var/log; do
if [ -d "$dir" ]; then du -xhd1 "$dir" 2>/dev/null || true; fi
done
for tool in sfdisk growpart resize2fs xfs_growfs; do command -v "$tool" || true; done
if [ "$(hostname)" = "iZ6we8b3jgd6nc2qehu06lZ" ] && command -v growpart >/dev/null; then
growpart -N /dev/nvme0n1 3 || true
fi
+1
View File
@@ -10,6 +10,7 @@ on:
jobs:
probe:
if: gitea.ref == 'refs/heads/main'
runs-on: gitea-cicd-server-for-CODEX
timeout-minutes: 10
steps:
@@ -0,0 +1,49 @@
name: runner-storage-maintenance
# Manual-only. Never runs on push or pull_request.
on:
workflow_dispatch:
inputs:
confirm:
description: Enter EXPAND_RUNNER_ROOT after owner approval
required: true
type: string
jobs:
expand-root:
if: ${{ gitea.ref == 'refs/heads/main' && (github.event_name == 'workflow_dispatch' && inputs.confirm == 'EXPAND_RUNNER_ROOT') }}
runs-on: ubuntu24.04-x64-lean4.35
timeout-minutes: 20
steps:
- name: Back up partition table and expand the authorized ext4 root
run: |
# Owner-authorized manual-only root partition/filesystem expansion.
set -euo pipefail
exec 9>/var/lock/lean-bench-root-maintenance.lock
flock -n 9
[ "$(hostname)" = "iZ6we8b3jgd6nc2qehu06lZ" ]
[ "$(id -u)" = 0 ]
[ "$(blkid -s PARTUUID -o value /dev/nvme0n1p3 | tr A-Z a-z)" = 9b694bad-5bbb-4485-860f-e5544ae47410 ]
[ "$(findmnt -n -o SOURCE /)" = /dev/nvme0n1p3 ]
[ "$(findmnt -n -o FSTYPE /)" = ext4 ]
[ "$(lsblk -n -o START /dev/nvme0n1p3 | tr -d ' ')" = 413696 ]
[ "$(blockdev --getsize64 /dev/nvme0n1)" -ge 161061273600 ]
backup_dir="/root/lean-bench-maintenance/$(date -u +%Y%m%dT%H%M%SZ)"
install -d -m 700 "$backup_dir"
sfdisk --dump /dev/nvme0n1 > "$backup_dir/nvme0n1.sfdisk"
sync
printf 'Partition-table backup: %s\n' "$backup_dir/nvme0n1.sfdisk"
set +e
growpart -N /dev/nvme0n1 3 > "$backup_dir/growpart-dry-run.log" 2>&1
probe_status=$?
set -e
if [ "$probe_status" = 0 ]; then
growpart /dev/nvme0n1 3
elif ! grep -q '^NOCHANGE:' "$backup_dir/growpart-dry-run.log"; then
cat "$backup_dir/growpart-dry-run.log"
exit "$probe_status"
fi
resize2fs /dev/nvme0n1p3
[ "$(lsblk -n -o START /dev/nvme0n1p3 | tr -d ' ')" = 413696 ]
lsblk -e 7 -o NAME,PATH,SIZE,FSTYPE,MOUNTPOINTS
df -hT / /var/lib/docker
+8 -1
View File
@@ -276,6 +276,12 @@ Experiments have IDs (`P0`, `E0`-`E11`); the registry, phases, gates and convent
[`docs/experiments/README.md`](docs/experiments/README.md). CI runner and environment notes:
[`docs/infrastructure/runner-lean435.md`](docs/infrastructure/runner-lean435.md).
Browse the [65-item semantic simplex schema review](docs/reviews/simplex-schemas.html)
by opening that HTML file in a browser after cloning, or downloading it from Git.
It shows role schemas and Lean signature expressions; textbook passages and full assistant
judgment explanations remain private. The [schema design and replay instructions](docs/simplex-schema.md)
explain how the page is generated and which annotations still need review.
## What this does not claim
Lean says whether the code is *legal*, and — when there is a proof — whether it is
@@ -285,4 +291,5 @@ well-formed statement of the wrong theorem passes every check here. `confidence`
possible; spot-check before trusting a dataset.
Source books are not committed. `.gitignore` keeps PDFs and extracted text out of
the repository; only code and the short Lean datasets belong in git.
the repository. The tracked schema review contains semantic annotations and Lean signatures,
while source-inclusive inputs remain in the ignored data directory.
@@ -0,0 +1,84 @@
# P0 execution report: 2026-10-28
**Status: blocked by provider billing. No GO, PARTIAL or NO-GO decision.**
The owner requested delivery of the fixes and this report now, with the remaining paid calls deferred.
## What ran
The owner explicitly authorized sending the 65 textbook passages and corresponding Lean code
through the existing DashScope endpoint to `qwen-max`, at temperature 0 and a cumulative ceiling
of 400 HTTP requests. The run issued **131 HTTP requests**. Provider responses accounted for
**37,699 input tokens and 7,790 output tokens**, 45,489 total. These are recorded token counts,
not an invoice or a monetary cost estimate. The client counted 89 received model responses;
a received response is not necessarily a usable detector result.
| Coverage | Count |
|---|---:|
| Original cohort | 65 |
| Items with both detectors complete | 42 |
| Items with one or both detectors missing | 23 |
| Successful role-extraction/alignment components | 45 |
| Successful judge components | 43 |
| Missing role components | 20 |
| Missing judge components | 22 |
| Remaining request reservations | 269 |
DashScope returned HTTP 400 with error code `Arrearage` and its overdue-payment reference.
The first runner implementation recorded the failures and continued through the cohort, so
65 saved rows did not mean 65 successful items. The scorer rejected these incomplete outputs.
No partial-sample gate decision or performance comparison has been produced.
## Inputs and labels
The default `items.jsonl` export omitted `source_text`. All 65 original passages were recovered
from the matching detection spans and checked byte-for-byte against the archived private
`review.json`. Item IDs and Lean code were unchanged. The recovery tool also verifies every
exported field against the archive, normalizing the archive's JSON-encoded imports field.
Source-inclusive inputs and the regenerated labeling HTML remain in the ignored data directory.
The owner replaced the planned Kimi/human labeling with Codex annotation. All 65 labels were
frozen before the first detector request. They contain 30 faithful, 25 wrong, 7 minor drift and
3 not-formalizable verdicts. This is one AI annotator, **not human gold**. The annotator saw the
detector implementation and aggregate compilation counts, but not per-item compiler outcomes
or detector outputs. Syntax/proof defects were ignored when the intended semantics were recoverable;
no compiler or API-name audit was performed. Independent human auditing remains necessary before
using these labels as evidence for paper-level claims.
## Execution repairs
- Empty passages and mismatched frozen inputs/labels are rejected before paid calls.
- Each HTTP attempt reserves cumulative budget before sending, including transport and JSON retries.
Model, endpoint, temperature, input/label/prompt hashes and cumulative token usage are persisted.
- Billing/authentication errors now stop immediately, preserving partial results.
- Resume keeps every successful detector component and retries only missing components. Existing
rows are replaced atomically rather than duplicated. A budget stop also preserves completed work
within the current item. A lock prevents concurrent writers.
- `--audit-only` reconciles saved metadata without API calls. It confirmed 42 complete items,
23 incomplete items, 42 missing components and 131 already-consumed request reservations.
- Scoring requires complete results and unchanged frozen-label/result hashes. It restores the
preregistered complementary-signal PARTIAL rule and uses wrong versus faithful for primary metrics;
minor drift is included as positive only in the secondary comparison.
- Detector prompts, matching thresholds, the concept table and frozen annotations were not tuned
against these outputs. Recovery changes concern transport, persistence and accounting only.
The private first-attempt output and metadata were backed up before reconciliation. The results
hash and the frozen-label hash did not change during the offline audit.
## Validation and next action
149 offline unit tests passed, including billing-stop and partial-resume regressions; repository-wide
Ruff and diff checks passed. These checks did not compile Lean or build Docker locally.
The initial PR revision passed Python tests and real Lean validation on
`ubuntu24.04-x64-lean4.35`, runner 7, in [CI #427](https://gitea.entroia.com/Zayden-Jung/lean-bench/actions/runs/427).
The image job was skipped by the PR workflow. The recovery revision passed [CI #433](https://gitea.entroia.com/Zayden-Jung/lean-bench/actions/runs/433).
The recovery changes from PR #6 are consolidated with the semantic schema and review page
in PR #9; the combined head is checked separately there.
After the owner confirms billing recovery, resume the existing run with the same inputs, frozen
labels and cumulative budget. There are 42 missing components; retries may consume more requests.
Do not change model or prompts to work around the provider block. Only after all 65 items have
successful outputs should the scorer produce the registered decision and disagreement report.
Phase 1 has not started.
Tracked audit data: `experiments/P0-pilot/results/execution.json` (counts and hashes only).
Private raw files: `experiments/P0-pilot/data/` (gitignored).
+5 -1
View File
@@ -2,7 +2,11 @@
Experiment ID **P0**, Phase 0. Registry and conventions: [README.md](README.md).
Status: **approved 2026-10-22; 65 AI labels frozen 2026-10-28; detector execution pending explicit data-transfer approval. No pilot API request has been sent.**
Status: **approved 2026-10-22; 65 AI labels frozen 2026-10-28; detector run blocked by DashScope Arrearage after 131 requests. 42 items are complete, 23 need missing detector components. No gate decision has been issued.**
The owner explicitly authorized sending the 65 passages and Lean code to DashScope/qwen-max,
then requested fixes and an execution report now, with paid recovery calls deferred.
Execution report: [P0 execution, 2026-10-28](P0-execution-2026-10-28.md).
Owner amendment (2026-10-28, in the execution chat): Codex now handles preparation,
annotation, detector execution and reporting; Kimi's participation is no longer required.
+28 -1
View File
@@ -3,7 +3,7 @@
Gitea runner `iZ6we8b3jgd6nc2qehu06lZ` (act_runner v5.2.0, runner id 7), label `ubuntu24.04-x64-lean4.35`. Both `lean-bench` and `lean-agent` CI run here; the old `gitea-cicd-server-for-CODEX` label is no longer used.
## The host
- Jobs run **on the host, not in a container**, as root. Ubuntu 24.04.5, kernel 6.8, 4 CPU, 15 GiB RAM, no swap, 99 GB disk (88 GB free at setup).
- Jobs run **on the host, not in a container**, as root. Ubuntu 24.04.5, kernel 6.8, 4 CPU, 15 GiB RAM, no swap, 150 GiB system disk (expanded from 100 GiB on 2026-10-28); the ext4 root filesystem reports about 148 GiB, with 75 GiB available immediately after expansion.
- Lean 4.35.0 via elan 4.2.4 in `/root/.elan`. Python 3.12.3, git 2.43, gcc 13.3, curl, jq.
- **No Node**, so `actions/checkout` and other JavaScript actions cannot run. Workflows clone with `git fetch --depth 1 origin $SHA` using `${{ github.token }}`.
- Docker was not installed; the lean-bench `image` job installs `docker.io` + `docker-buildx` (Docker 29.1.3) if missing.
@@ -20,3 +20,30 @@ Gitea runner `iZ6we8b3jgd6nc2qehu06lZ` (act_runner v5.2.0, runner id 7), label `
- Mathlib's post-update hook runs the cache fetch **inside `lake update`**, so retries placed after it never run. Set `MATHLIB_NO_CACHE_ON_UPDATE=1` for `lake update` and fetch in a retry loop. In the image the archives live in a BuildKit cache mount (`/root/.cache/mathlib`), so a retried build resumes.
- Cold image build about 19 min; with layers cached about 2 min.
- Gitea 1.26.1 has no cancel-run API; a person cancels in the web UI, then the API can `DELETE` the finished run. The Actions logs endpoint needs a token; the runs/jobs status endpoints work anonymously on this public repo.
## Root capacity expansion (2026-10-28)
The owner expanded the cloud disk to 150 GiB, but root partition `/dev/nvme0n1p3`
and its ext4 filesystem still occupied about 100 GiB. CI run number 43 (API run ID 438)
therefore continued to report 28 GiB available and failed its unchanged 30 GiB preflight.
Rerunning a failed job retains the same UI run number; its job attempt number increments.
Read-only probe run number 45 (API run ID 442) confirmed the raw-disk/partition mismatch.
Its `growpart -N` output showed that partition 3 could extend from 209301471 to
314159071 sectors while keeping start sector 413696 and its partition UUID unchanged.
Temporary files and logs were small; Docker/containerd storage and Mathlib were the main
consumers. No tagged image, build cache or Mathlib cache was deleted for this repair.
The owner explicitly authorized partition and filesystem expansion in the execution chat.
Manual maintenance run number 46 (API run ID 443) then backed up the partition table to
`/root/lean-bench-maintenance/20261028T121919Z/nvme0n1.sfdisk`, expanded partition 3,
and grew the mounted ext4 filesystem online. The resulting partition is 149.8 GiB;
`df` reported a 148 GiB filesystem with 75 GiB available. No reboot was required.
`.gitea/workflows/env-probe.yml` now includes read-only storage and cache diagnostics.
`.gitea/workflows/runner-storage-maintenance.yml` is manual-only and requires the literal
confirmation `EXPAND_RUNNER_ROOT`. It validates hostname, root device, ext4 type, partition
UUID, start sector and disk size, takes a lock, and backs up the partition table before any
change. Future execution still requires explicit owner authorization for that maintenance.
It never formats a device or prunes images. The failed image job was retried after expansion;
its actual build, smoke-test and image-retention outcome is recorded in CI run number 43.
+9 -3
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@@ -8,9 +8,15 @@ Evidence base: repo README and code (`leanbench/`, 4,345 lines incl. tests), pro
## 0. The idea in one page
**Terminology clarification (2026-10-28).** The owner uses "simplex" for a semantic,
multi-role relation schema: one statement joins objects, assumptions and a conclusion.
It does not mean a geometric simplex or assert a mathematical simplicial complex.
See [the implemented schema design](simplex-schema.md) for scoped slots, storage and
candidate retrieval. Existing signature projections and AI source annotations remain partial.
**Simplex, as it exists in the archived code.**
- `Role(name, context, choices)`: a named semantic slot with a description and an optional closed set of allowed values (`is_constrained`, `validate_value`).
- `Simplex(name, roles: {alias: Role})`: a reusable unit of **at least two** roles. A Simplex is itself a `Role`, so simplices nest; nesting gives a *simplicial complex*. `Equivalence` is the two-role special case.
- `Simplex(name, roles: {alias: Role})`: a reusable unit of **at least two** roles. A Simplex is itself a `Role`, so explicitly supplied schemas can be nested as semantic composition. `Equivalence` is the two-role special case.
- `State` / `Fact` / `Goal`: a role plus a value. A `Fact` has a value, a `Goal` does not; `SolvingTask.is_completed()` is "every goal resolved".
- `SchemaRegistry` (SQLite): `set_role`, `set_simplex`, `search_roles`, `find_by_roles(known_roles)`, `find_solvable(known_role_names)`.
- `SchemaParserAgent`: turns a query into a Simplex through a forced tool call whose JSON schema says `minItems: 2`, with a **search-first, reuse-before-create** rule for roles. `AnalogySchemaMiner`: proposes new simplices by the ratio *Simplex B : Role B :: Simplex A : Role A*.
@@ -19,11 +25,11 @@ Evidence base: repo README and code (`leanbench/`, 4,345 lines incl. tests), pro
| Lean | Simplex view |
|---|---|
| `(G : Type*) [Group G]` | role `G`, `context` = "carrier", `choices` = admissible type/class constraints |
| `(G : Type*) [Group G]` | role `G`, `context` = "carrier", type/class constraints as attributes; `choices` only for explicit finite value sets |
| `(h : P x)` hypothesis | `Fact` role |
| conclusion after the final `:` | `Goal` role |
| `def` / `structure` being introduced | `own` role (what the thing *is*) |
| a lemma used inside a proof | nested simplex (edge in the complex) |
| a lemma used inside a proof | explicit nested schema reference (when recorded) |
`leanbench/typeindex.py` already extracts exactly this split: `input` (binders and hypotheses), `goal` (the conclusion), `own` (definitions). So the type index is a simplex index in all but name. The new work is to make it a **first-class schema that steers inference** instead of a passive index.
File diff suppressed because it is too large Load Diff
+170
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@@ -0,0 +1,170 @@
# Simplex schema: a semantic relation joining roles
Here **simplex** means the owner's multi-role relation pattern: one statement relates
objects, assumptions and a conclusion. The implementation does not construct geometric
simplices, faces, boundaries or a mathematical simplicial complex.
## The model
| Concept | Representation | Meaning |
|---|---|---|
| Reusable role definition | `Role` | A semantic slot type with optional textual type/context and finite `choices` |
| Statement/relation pattern | `Simplex` | A named mapping from at least two local aliases to roles |
| Object or assumption supplied by a caller | `Fact` | A role plus a non-None value |
| Requested result | `Goal` | A role whose value is not supplied yet |
| Application to particular objects | `SimplexInstance` | Facts and goals bound by local slot alias |
| Explicit composition | A `Simplex` used as a role | A supplied nested pattern; no proof dependency is discovered automatically |
| Persistent catalog | `SchemaRegistry` | JSON/SQLite nodes and alias-to-definition references |
`kind` separates `object`, `fact`, `goal`, `own` and nested `simplex` roles.
A role's `attrs.references` may name other aliases in the same simplex; unknown aliases
are rejected. These references can describe the objects mentioned in an assumption or
conclusion. They are not geometric edges. Their provenance must distinguish manually
supplied relationships from incomplete syntactic candidates.
`type_text` is descriptive Lean/mathematical text, not an executable type checker.
`choices` is a finite set of admissible values, not a replacement for arbitrary Lean typeclass
constraints. Supplied fact and resolved goal values are checked against explicit choices.
No registry method establishes that a string is a proof or that a mathematical premise is true.
## Concrete example: two groups and a homomorphism
One schema joins these slots:
| Local alias | Role | Type/claim | References |
|---|---|---|---|
| `left` | object | group carrier | none |
| `right` | object | group carrier | none |
| `map` | object | `left →* right` | left, right |
| `bijective` | fact | `Bijective map` | map |
| `goal` | goal | `Nonempty (left ≃* right)` | left, right |
The simplex is this complete relation pattern, not an individual role or an asserted
geometric object. `left` and `right` may explicitly reuse the same `role:group` definition
while binding to different group objects. Reusing a role definition does not equate their values.
Run the synthetic, offline example:
```sh
PYTHONPATH=. python3 examples/simplex_registry.py
```
It binds symbolic caller values for the input slots, leaves the goal unresolved, and returns
a structurally ready candidate. It does not run a Lean proof.
## Scope, persistence and reuse
`SchemaRegistry.set_simplex` assigns every child a scoped key by default:
`<schema-key>/slot/<escaped-alias>`. Thus `G` in one theorem is not the same object as `G`
in another. Corpus keys also include the frozen annotation hash and item identity.
To reuse a definition, register it with `set_role` and explicitly pass a `role_keys` mapping
to `set_simplex`. The referenced definition must match the supplied role exactly. A shared
definition still has distinct occurrence keys for every alias. No role is semantically merged
merely because its spelling, type text or keywords resemble another role.
Keys are immutable within a registry. Identical registration is idempotent; changed content
or changed definition references require a new version key. `get_role` and `get_simplex`
resolve exact keys, not ambiguous bare names. `search_roles` returns literal-substring candidates
for a caller to review; it does not approve semantic reuse.
Serialization includes names, kinds, context, types, choices, attributes and nested aliases.
`role_from_dict` restores JSON snapshots. SQLite uses one connection and one transaction per
nested registration, foreign keys and JSON payloads; it does not load archived pickle blobs.
Cyclic nesting and failed reuse checks roll back the complete write. Returned objects are
restored snapshots; changing one does not silently update a registered definition.
## Query and binding APIs
```python
from leanbench.schema_registry import SchemaRegistry, slot_key
with SchemaRegistry("private-registry.sqlite") as registry:
schema = registry.get_simplex("schema:example")
matches = registry.search_roles("group")
containers = registry.find_by_roles(["role:group"], match_all=True)
candidates = registry.find_solvable([
slot_key("schema:example", "left"),
slot_key("schema:example", "right"),
slot_key("schema:example", "map"),
slot_key("schema:example", "bijective"),
])
```
`find_by_roles` searches definition references, including descendants of nested schemas.
`find_solvable` retains the archived API name but implements **structural readiness only**:
all input occurrences must be supplied and at least one marked goal/own occurrence must
remain unresolved. It returns `structural_candidate_only: true`, not a proof or a computed value.
Having one `role:group` definition cannot satisfy two distinct group slots. A nested input
must itself be explicitly supplied; the registry does not apply its internal theorem automatically.
`SimplexInstance(schema, facts=..., goals=...)` binds local aliases. Facts and goals must be
distinct declared slots. Omitting `goals` uses roles marked `goal` or `own`; `resolve` checks
a supplied goal value against choices. Completion means that declared goals have values,
not that Lean verified them. Value unification, dependent type checking and proof search
remain outside this implementation.
## Materialization of the 65 P0 items
The builder consumes the frozen current-chat GPT diagnostic's source descriptions and
unchanged Lean strings. It makes no model request, revises no assessment and performs no
Lean compilation. Results:
| Artifact | Count |
|---|---:|
| Source annotation seed schemas | 65 |
| Lean signature schema seeds | 50 |
| Items with fewer than two projected Lean roles | 15 |
| Stored schemas | 115 |
| Scoped role records / slot occurrences | 483 / 483 |
These 115 seeds deliberately do not auto-reuse definitions across statements. Explicit reuse
is supported and tested by the synthetic example; a reviewed shared ontology is future work.
The 15 incomplete Lean sides remain in the index with status `insufficient_projected_roles`.
A closed declaration may mention concrete objects inside its conclusion that the binder-based
projector misses. No object roles were invented to hide this limitation.
Source schemas are marked `unreviewed_annotation_seed`. Existing `given` tags are preserved
with `quantifier_status: unreviewed`; they are not silently converted to universal/existential
quantifiers. References on the source side use explicit symbol candidates; Lean references
are syntactic identifier candidates. Neither is a complete dependency analysis.
For example, P11's source seed lists a named size while Lean uses `Fintype.card G` inline.
The materializer preserves both representations; it does not invent a validated cardinality
binding or repair the old alignment result. Annotation quality and semantic normalization
still require a separate review.
Private outputs under `experiments/P0-pilot/data/simplex-schemas-v1/`:
- `registry.sqlite`: queryable catalog with the 115 schemas and scoped slots.
- `schemas.json`: all 65 source/Lean pairs, retaining incomplete Lean projections.
- `schemas.html`: a local generated copy of the schema-only review tracked below.
- `schema-inputs.json`: input hashes; an existing directory rejects changed inputs.
Tracked outputs:
- `experiments/P0-pilot/results/simplex-schema-index.json`: 65 item IDs, schema keys,
role counts, coverage status and reference-candidate counts.
- `experiments/P0-pilot/results/simplex-schema-summary.json`: coverage, limitations and hashes.
- [65-item schema review](reviews/simplex-schemas.html): an owner-approved, self-contained
HTML view of all 65 source/Lean pairs. It includes schema role descriptions and Lean
signature expressions, but no textbook paragraphs or full assistant judgment explanations.
Open the file in a browser after cloning, or download it from the repository; the Git web
interface may display HTML source instead of rendering it. The JSON indexes above remain
text-free counts/keys. Full source-inclusive inputs and assessment files remain gitignored.
Replay from the repository root with private inputs present:
```sh
PYTHONPATH=. python3 experiments/P0-pilot/build_schemas.py \
--items experiments/P0-pilot/data/simplex-schemas-v1/items.jsonl \
--assessments experiments/P0-pilot/data/simplex-schemas-v1/assistant-assessments.json \
--key experiments/P0-pilot/labels/key.json \
--private-out experiments/P0-pilot/data/simplex-schemas-v1 \
--index experiments/P0-pilot/results/simplex-schema-index.json \
--summary experiments/P0-pilot/results/simplex-schema-summary.json \
--review-page docs/reviews/simplex-schemas.html
```
The original annotations, judgments, Qwen results and matcher thresholds remain unchanged.
The registry is a usable schema foundation, not evidence of a validated theorem, a working
prover, independently measured faithfulness, or a completed Phase 1 experiment.
+35
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@@ -0,0 +1,35 @@
"""Synthetic example: one isomorphism schema relates two groups and a map."""
from __future__ import annotations
import json
from leanbench.schema import KIND_FACT, KIND_GOAL, Role, Simplex, SimplexInstance
from leanbench.schema_registry import SchemaRegistry, slot_key
def example():
group = Role("group", type_text="group carrier", context="Reusable group role definition")
schema = Simplex("group_isomorphism", {
"left": group,
"right": group,
"map": Role("homomorphism", type_text="left →* right",
attrs={"references": ["left", "right"]}),
"bijective": Role("bijective", KIND_FACT, type_text="Bijective map",
attrs={"references": ["map"]}),
"goal": Role("isomorphic", KIND_GOAL, type_text="Nonempty (left ≃* right)",
attrs={"references": ["left", "right"]}),
}, context="A bijective homomorphism supplies a group isomorphism")
with SchemaRegistry() as registry:
registry.set_role(group, "role:group")
key = registry.set_simplex(schema, role_keys={"left": "role:group", "right": "role:group"})
instance = SimplexInstance(schema, facts={
"left": "group A", "right": "group B", "map": "f", "bijective": "supplied evidence"})
candidates = registry.find_solvable([slot_key(key, alias) for alias in instance.facts])
return {"schema": registry.get_simplex(key).as_dict(), "definition_keys": registry.slots(key),
"bindings": {alias: fact.value for alias, fact in instance.facts.items()},
"structural_candidates": candidates, "completed": instance.is_completed(),
"note": "Evidence is symbolic user input; this example does not run a Lean proof."}
if __name__ == "__main__":
print(json.dumps(example(), indent=2, ensure_ascii=False))
+27 -1
View File
@@ -44,6 +44,9 @@ Labeling must be finished before anyone opens `results.jsonl`.
- Metadata is stored beside the output as `results.meta.json`. Model, endpoint, temperature,
input hash, frozen-label hash and prompt hashes must match on resume. Usage is cumulative.
A file lock prevents concurrent writers. A budget stop returns exit status 2.
- Billing/authentication failures stop immediately. Resume retries only missing detector components,
keeping both complete items and the successful side of partial items. Rows are replaced atomically.
`--audit-only` reconciles saved completion counts and status without any API request.
- The nominal successful path uses 130 calls (one source extraction and one judge per item);
malformed replies and network retries may increase the actual count.
- Scoring requires complete labels and results and no unresolved detector errors. The primary
@@ -51,7 +54,16 @@ Labeling must be finished before anyone opens `results.jsonl`.
The complementary-signal PARTIAL rule counts wrong items flagged by role alignment but missed
by the judge. No threshold, concept table or detector prompt was tuned for these labels.
- Raw passages, labeling HTML and model responses remain in the ignored `data/` directory.
Only verdicts, abstract annotation notes, hashes and text-free summaries belong in Git.
Verdicts, abstract annotation notes, hashes and text-free summaries belong in Git;
the owner-approved schema-only HTML review is also tracked separately under docs/reviews/.
## Qwen execution snapshot
The 2026-10-28 run was blocked by DashScope `Arrearage`: 42 items are complete, 23 need
42 detector components, and 131 of the 400 request reservations have been consumed.
The owner requested fixes and a report now, with paid resumption deferred.
See `docs/experiments/P0-execution-2026-10-28.md` and `results/execution.json`.
No gate decision has been issued. Restore provider billing before resuming the same run.
## Separate GPT-assisted diagnostic
@@ -65,3 +77,17 @@ See `docs/experiments/P0-gpt-diagnostic.md` for all counts, limitations, artifac
and the offline replay command. The tracked `results/gpt-diagnostic-*.json` files contain
only categorical/numeric outputs and audit metadata. The authored source structures,
reasons and full review page stay in the ignored `data/gpt-diagnostic/` directory.
## Semantic simplex registry
The current 65-item annotation cohort is materialized as multi-role relation schemas:
65 source seeds, 50 Lean signature seeds and 15 explicitly incomplete Lean projections.
See `docs/simplex-schema.md` for the data model, scoped identities, explicit role reuse,
structural candidate queries, bindings and replay command. Private SQLite/JSON/HTML outputs
stay under `data/simplex-schemas-v1/`; tracked `results/simplex-schema-*.json` files contain
only counts, opaque keys, provenance hashes and coverage status. This does not change the
frozen diagnostic or claim complete semantic extraction or proof verification.
The owner-approved schema-only HTML review is tracked at
`docs/reviews/simplex-schemas.html`. Regenerate it with the builder's `--review-page` option;
the raw inputs, full assessment explanations and SQLite snapshot remain gitignored.
+193
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@@ -0,0 +1,193 @@
"""Materialize scoped multi-role relation schemas from the frozen 65-item review.
The schema is the relation joining its slots. No geometric faces, inferred proof
links or cross-theorem object identities are constructed.
"""
from __future__ import annotations
import argparse
import hashlib
import html
import json
import re
from collections import Counter
from pathlib import Path
from leanbench.project import project
from leanbench.schema import KIND_OBJECT, Role, Simplex, role_from_dict
from leanbench.schema_registry import SchemaRegistry, slot_key
from leanbench.srcsimplex import parse_source_simplex
def digest(path):
return hashlib.sha256(path.read_bytes()).hexdigest()
def source_schema(name, payload):
source = parse_source_simplex(payload)
symbol_slots = {}
for role in source.roles:
if role.kind == KIND_OBJECT:
for symbol in role.symbols:
symbol_slots.setdefault(symbol, []).append(role.alias)
roles = {}
for role in source.roles:
references = sorted({alias for symbol in role.symbols for alias in symbol_slots.get(symbol, [])
if alias != role.alias and len(symbol_slots[symbol]) == 1})
roles[role.alias] = Role(
role.symbols[0] if len(role.symbols) == 1 else role.alias,
role.kind, context=role.description,
attrs={"symbols": role.symbols, "keywords": role.keywords,
"introduced": role.introduced, "quantifier_status": "unreviewed",
"references": references,
"reference_status": "explicit_symbol_candidates" if references else "unknown",
"origin": "frozen_current_chat_annotation"})
return Simplex(name, roles, attrs={"side": "source", "goal_has_exists": source.goal_has_exists,
"reference_completeness": "partial"})
def lean_schema(name, code):
projection = project(code)
if projection.simplex is None:
return None, projection
originals = projection.simplex.roles
by_name = {}
for alias, role in originals.items():
by_name.setdefault(role.name, []).append(alias)
roles = {}
for alias, role in originals.items():
identifiers = set(re.findall(r"[^\W\d]\w*'?", role.type_text, flags=re.UNICODE))
references = sorted({target for symbol in identifiers for target in by_name.get(symbol, [])
if len(by_name[symbol]) == 1 and target != alias})
roles[alias] = Role(role.name, role.kind, type_text=role.type_text, context=role.context,
choices=role.choices, attrs={**role.attrs, "references": references,
"reference_status": "syntactic_candidates",
"origin": "deterministic_signature_projection"})
return Simplex(name, roles, attrs={"side": "lean", "reference_completeness": "syntactic_only"}), projection
def build(items, assessment, key, registry, namespace="p0-v1"):
by_id = {item["id"]: item for item in items}
records = {row["blind_id"]: row for row in assessment["records"]}
if (not key or len(by_id) != len(items) or len(records) != len(assessment["records"])
or len(set(key.values())) != len(key) or set(by_id) != set(key.values())
or set(records) != set(key)):
raise ValueError("Items, assessments and blind key must match exactly once")
index, snapshots = [], []
for blind, item_id in key.items():
record = records[blind]
if record["id"] != item_id:
raise ValueError("Assessment identity mismatch")
source_key = f"schema:{namespace}:{item_id}:source:v1"
lean_key = f"schema:{namespace}:{item_id}:lean:v1"
source = source_schema(source_key, record["source"])
lean, projection = lean_schema(lean_key, by_id[item_id]["lean_code"])
registry.set_simplex(source, source_key)
if lean is not None:
registry.set_simplex(lean, lean_key)
source_restored = registry.get_simplex(source_key)
if source_restored.as_dict() != source.as_dict():
raise ValueError("Source schema persistence roundtrip failed")
if lean is not None and registry.get_simplex(lean_key).as_dict() != lean.as_dict():
raise ValueError("Lean schema persistence roundtrip failed")
index.append({"blind_id": blind, "source_schema": source_key,
"source_status": "unreviewed_annotation_seed",
"source_slots": len(source.roles),
"lean_schema": lean_key if lean is not None else None,
"lean_slots": len(projection.roles),
"lean_status": "materialized" if lean is not None else "insufficient_projected_roles",
"source_role_counts": dict(Counter(r.kind for r in source.roles.values())),
"lean_role_counts": dict(Counter(r.kind for r in projection.roles)),
"source_slots_with_reference_candidates": sum(bool(r.attrs["references"]) for r in source.roles.values())})
snapshots.append({"blind_id": blind, "source": source.as_dict(),
"lean": lean.as_dict() if lean is not None else None,
"lean_projection": projection.as_dict(),
"source_slot_keys": [slot_key(source_key, alias) for alias in source.roles]})
return index, snapshots
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--items", required=True, type=Path)
parser.add_argument("--assessments", required=True, type=Path)
parser.add_argument("--key", required=True, type=Path)
parser.add_argument("--private-out", required=True, type=Path)
parser.add_argument("--index", required=True, type=Path)
parser.add_argument("--summary", required=True, type=Path)
parser.add_argument("--review-page", type=Path,
help="Also export the owner-approved schema-only HTML review into the project")
args = parser.parse_args()
if "data" not in args.private_out.parts:
parser.error("Private schemas must remain in the gitignored data/ directory")
assessment = json.loads(args.assessments.read_text())
key = json.loads(args.key.read_text())["key"]
if (assessment["provenance"]["items_sha256"] != digest(args.items)
or assessment["provenance"]["key_sha256"] != digest(args.key)):
parser.error("Frozen assessment hashes do not match inputs/key")
items = [json.loads(line) for line in args.items.read_text().splitlines() if line.strip()]
args.private_out.mkdir(parents=True, exist_ok=True)
identity = {"items": digest(args.items), "assessments": digest(args.assessments),
"key": digest(args.key)}
manifest = args.private_out / "schema-inputs.json"
if manifest.exists() and json.loads(manifest.read_text()) != identity:
parser.error("Existing schema output belongs to different inputs; choose a new directory")
temporary = args.private_out / "registry.sqlite.tmp"
if temporary.exists():
temporary.unlink()
with SchemaRegistry(temporary) as registry:
index, snapshots = build(items, assessment, key, registry,
namespace=f"p0-{identity['assessments'][:12]}")
info = registry.info()
temporary.replace(args.private_out / "registry.sqlite")
manifest.write_text(json.dumps(identity, indent=2) + "\n")
(args.private_out / "schemas.json").write_text(json.dumps(snapshots, indent=2, ensure_ascii=False) + "\n")
sections = []
for row in snapshots:
sides = []
for side in ["source", "lean"]:
value = row[side]
content = (json.dumps(value, indent=2, ensure_ascii=False) if value is not None
else "Insufficient projected roles; no object roles were invented.")
sides.append(f'<h3>{side}</h3><pre>{html.escape(content)}</pre>')
sections.append(f'<section id="{row["blind_id"]}"><h2>{row["blind_id"]}</h2>'
+ ''.join(sides) + '</section>')
review_page = (
'<!doctype html><html lang="en"><meta charset="utf-8"><title>P0 semantic simplex schemas</title>'
'<style>body{font:16px/1.5 system-ui;max-width:1050px;margin:32px auto;padding:16px}'
'pre{white-space:pre-wrap;background:#f5f5f5;padding:16px}section{border-top:1px solid #ccc}</style>'
'<h1>65 semantic multi-role relation schemas</h1>'
'<p>Schema annotation seeds, not independently validated mathematical statements. '
'A simplex joins the objects, assumptions and conclusion in its slots. '
'References are partial symbol/syntax candidates. '
'This review contains schema annotations and Lean signature text, not textbook passages '
'or full assistant judgment explanations.</p>' + ''.join(sections) + '</html>')
(args.private_out / "schemas.html").write_text(review_page, encoding="utf-8")
if args.review_page is not None:
args.review_page.parent.mkdir(parents=True, exist_ok=True)
args.review_page.write_text(review_page, encoding="utf-8")
# JSON-only reload is independently checked; it does not use pickle.
for row in snapshots:
for side in ["source", "lean"]:
if row[side] is not None:
if role_from_dict(row[side]).as_dict() != row[side]:
raise ValueError("JSON schema roundtrip failed")
summary = {"representation": "semantic_multi_role_relation_schema_v1", "items": len(items),
"source_schemas": len(index), "lean_schemas": sum(r["lean_schema"] is not None for r in index),
"lean_incomplete": sum(r["lean_schema"] is None for r in index), "registry": info,
"hashes": {"items": digest(args.items), "assessments": digest(args.assessments),
"key": digest(args.key), "builder": digest(Path(__file__)),
"schema_module": digest(Path(__file__).resolve().parents[2] / "leanbench/schema.py"),
"registry_module": digest(Path(__file__).resolve().parents[2] / "leanbench/schema_registry.py")},
"limitations": ["Source annotations come from a non-independent current-chat diagnostic.",
"Source quantifiers are preserved as unreviewed; existing given tags are not repaired.",
"References are symbol/syntax candidates, not complete semantic dependencies.",
"No cross-theorem identity or proof dependency is inferred.",
"Fewer than two projected Lean roles is a projection limitation, not proof that objects are absent."]}
for path, value in [(args.index, index), (args.summary, summary)]:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(json.dumps(value, indent=2, allow_nan=False) + "\n")
print(json.dumps({k: summary[k] for k in ["items", "source_schemas", "lean_schemas", "lean_incomplete", "registry"]}))
if __name__ == "__main__":
main()
@@ -0,0 +1,72 @@
{
"experiment": "P0",
"status": "provider_blocked",
"decision": null,
"decision_withheld_reason": "Incomplete detector outputs after DashScope Arrearage; no GO/PARTIAL/NO-GO is valid.",
"cohort_size": 65,
"completed_items": 42,
"items_with_failures": 23,
"missing_components": {
"judge": 22,
"role": 20
},
"request_attempts": 131,
"max_calls": 400,
"remaining_request_budget": 269,
"usage": {
"calls": 89,
"prompt_tokens": 37699,
"completion_tokens": 7790
},
"model": "qwen-max",
"temperature": 0.0,
"items_sha256": "487ecd22919a5e3b0174a2846ab8fe7c0daf4d3feccccf8ea6571aec04c41bed",
"labels_sha256": "1552dba85e75426799151384e7e28c9a0b1072ed4c862df0876df89920d2a638",
"results_sha256": "fce402e6eab460a48bb9a8e94140bb23f305843ab46d227bbffa5100d7de69e5",
"prompt_hashes": {
"source": "382f9a7b5a0cfb2d50d525f884dc806f45adaa59bcc45e388920c4759db1546f",
"judge": "7ab92682bd71d78a212471289f0f01db39d6b68f49d44df65d7b1c9e34ebb5e2"
},
"labels": {
"type": "single AI annotator; not human gold",
"frozen": true,
"count": 65
},
"affected_blind_ids": [
"P02",
"P04",
"P09",
"P18",
"P19",
"P20",
"P21",
"P22",
"P24",
"P27",
"P29",
"P30",
"P33",
"P36",
"P37",
"P38",
"P42",
"P43",
"P45",
"P47",
"P54",
"P59",
"P62"
],
"successful_components_preserved": 88,
"resume_policy": "After owner confirms billing recovery, retry missing components only using the same run files, frozen labels, model, prompts and cumulative 400-request ceiling.",
"owner_instruction": "2026-10-28: complete fixes and the execution report now; resume paid calls later.",
"validation": {
"offline_unit_tests": 149,
"ruff": "passed",
"remote_runner_tag": "ubuntu24.04-x64-lean4.35",
"initial_remote_ci": "https://gitea.entroia.com/Zayden-Jung/lean-bench/actions/runs/427",
"initial_remote_ci_status": "success; image job skipped for PR",
"recovery_remote_ci": "https://gitea.entroia.com/Zayden-Jung/lean-bench/actions/runs/433",
"consolidated_pull_request": "https://gitea.entroia.com/Zayden-Jung/lean-bench/pulls/9"
}
}
File diff suppressed because it is too large Load Diff
@@ -0,0 +1,27 @@
{
"representation": "semantic_multi_role_relation_schema_v1",
"items": 65,
"source_schemas": 65,
"lean_schemas": 50,
"lean_incomplete": 15,
"registry": {
"roles": 483,
"simplices": 115,
"slots": 483
},
"hashes": {
"items": "487ecd22919a5e3b0174a2846ab8fe7c0daf4d3feccccf8ea6571aec04c41bed",
"assessments": "f12735802ba0d4d94b776a91581a13a508eab0ce90ba8973a6c9c4e4d1390272",
"key": "f827cac92ee4e907554fadcc7c0e006ef2b829350f74e7f8b54ca11945e62836",
"builder": "7b3a982101f620c1480d95b5e483ca6186a7e9c32ce587fb132a90bfb38a01bc",
"schema_module": "958b81e89c0befeb32d24036c130f2b37bd2e881bd5b009acf873cbcdada50ae",
"registry_module": "7b434b1eb178f597d4f60591a5ab74eff0c96a40fa751cb0ba75589b52e56271"
},
"limitations": [
"Source annotations come from a non-independent current-chat diagnostic.",
"Source quantifiers are preserved as unreviewed; existing given tags are not repaired.",
"References are symbol/syntax candidates, not complete semantic dependencies.",
"No cross-theorem identity or proof dependency is inferred.",
"Fewer than two projected Lean roles is a projection limitation, not proof that objects are absent."
]
}
+94 -40
View File
@@ -50,37 +50,64 @@ def judge(client, passage: str, lean: str) -> dict:
"reason": str(reply.get("reason", ""))[:300]}
def run_item(client, item: dict) -> dict:
if not item.get("source_text", "").strip():
raise ValueError("Missing source_text; use a private source-inclusive export")
code = item.get("lean_code") or ""
row: dict = {"id": item["id"], "compiled": bool(item.get("verified")), "errors": {}}
proj = project(code)
row["projection"] = proj.as_dict()
row["lint"] = lint(proj)
try:
src = srcsimplex.extract_source_simplex(client, item.get("source_text", ""),
item.get("label", ""))
al = align(src, proj)
row["source"] = [r.__dict__ for r in src.roles]
row["role"] = al.as_dict()
except CallBudgetExceeded:
raise
except Exception as error: # a failed extraction is data, not a crash
row["errors"]["role"] = str(error)[:300]
try:
row["judge"] = judge(client, item.get("source_text", ""), code)
except CallBudgetExceeded:
raise
except Exception as error:
row["errors"]["judge"] = str(error)[:300]
return row
def provider_blocked(error: Exception) -> bool:
text = str(error).lower()
return any(code in text for code in ("arrearage", "overdue-payment", "invalid_api_key", "http 401", "http 403"))
def complete_row(row: dict) -> bool:
return not row.get("errors") and "role" in row and "judge" in row
class ProviderBlocked(RuntimeError):
"""A billing or authentication failure requires external recovery before resuming."""
def __init__(self, row):
super().__init__("Provider billing/authentication blocked; partial results were preserved")
self.row = row
class CallBudgetExceeded(RuntimeError):
"""Stop before issuing a request that would exceed the cumulative budget."""
def run_item(client, item: dict, previous: dict | None = None) -> dict:
if not item.get("source_text", "").strip():
raise ValueError("Missing source_text; use a private source-inclusive export")
code = item.get("lean_code") or ""
row: dict = {**(previous or {}), "id": item["id"], "compiled": bool(item.get("verified"))}
row["errors"] = dict(row.get("errors", {}))
proj = project(code)
row["projection"] = proj.as_dict()
row["lint"] = lint(proj)
if "role" not in row:
try:
src = srcsimplex.extract_source_simplex(client, item["source_text"], item.get("label", ""))
al = align(src, proj)
row["source"] = [r.__dict__ for r in src.roles]
row["role"] = al.as_dict()
row["errors"].pop("role", None)
except CallBudgetExceeded as error:
error.row = row
raise
except Exception as error:
row["errors"]["role"] = str(error)[:300]
if provider_blocked(error):
raise ProviderBlocked(row) from error
if "judge" not in row:
try:
row["judge"] = judge(client, item["source_text"], code)
row["errors"].pop("judge", None)
except CallBudgetExceeded as error:
error.row = row
raise
except Exception as error:
row["errors"]["judge"] = str(error)[:300]
if provider_blocked(error):
raise ProviderBlocked(row) from error
return row
def digest(path: Path) -> str:
return hashlib.sha256(path.read_bytes()).hexdigest()
@@ -106,8 +133,9 @@ def execute(args, items, settings) -> int:
if args.out.exists():
rows = [json.loads(x) for x in args.out.read_text(encoding="utf-8").splitlines() if x.strip()]
ids = {item["id"] for item in items}
done = {row["id"] for row in rows}
if len(done) != len(rows) or not done <= ids:
by_id = {row["id"]: row for row in rows}
done = {row["id"] for row in rows if complete_row(row)}
if len(by_id) != len(rows) or not set(by_id) <= ids:
raise ValueError("Results have duplicate or unknown item IDs")
hashes = {
"source": hashlib.sha256((srcsimplex.SYSTEM_PROMPT + inspect.getsource(srcsimplex.passage_prompt)).encode()).hexdigest(),
@@ -129,11 +157,24 @@ def execute(args, items, settings) -> int:
elif rows:
raise ValueError("Cannot resume results without their audit metadata")
todo = [item for item in items if item["id"] not in done]
missing = sum(2 - int("role" in by_id.get(i["id"], {}))
- int("judge" in by_id.get(i["id"], {})) for i in todo)
print(f"items={len(items)} done={len(done)} todo={len(todo)} model={settings.llm.model} "
f"nominal_calls={len(todo) * 2} request_attempts={meta['request_attempts']} cap={args.max_calls}")
f"missing_components={missing} request_attempts={meta['request_attempts']} cap={args.max_calls}")
print("prompt_hashes:", json.dumps(hashes))
if args.dry_run:
return 0
if getattr(args, "audit_only", False):
meta["completed_items"] = len(done)
meta["processed_items"] = len(rows)
meta["status"] = ("provider_blocked" if any(provider_blocked(RuntimeError(message))
for row in rows for message in row.get("errors", {}).values())
else "detector_errors" if todo else "complete")
if args.out.exists():
meta["results_sha256"] = digest(args.out)
atomic_json(meta_path, meta)
print(json.dumps(meta))
return 0 if meta["status"] == "complete" else 2
if settings.llm.model != "qwen-max" or settings.llm.temperature != 0:
raise ValueError("P0 is preregistered for qwen-max at temperature 0")
client = AuditedClient.from_settings(settings.llm)
@@ -142,6 +183,7 @@ def execute(args, items, settings) -> int:
def checkpoint():
meta["usage"] = client.usage.as_dict()
meta["completed_items"] = len(done)
meta["processed_items"] = len(by_id)
atomic_json(meta_path, meta)
def reserve():
@@ -155,19 +197,30 @@ def execute(args, items, settings) -> int:
meta["max_calls"] = args.max_calls
meta["status"] = "running"
checkpoint()
def save_row(row):
by_id[row["id"]] = row
if complete_row(row):
done.add(row["id"])
temporary = args.out.with_suffix(args.out.suffix + ".tmp")
with temporary.open("w", encoding="utf-8") as stream:
for item in items:
if item["id"] in by_id:
stream.write(json.dumps(by_id[item["id"]], ensure_ascii=False) + "\n")
stream.flush()
os.fsync(stream.fileno())
os.replace(temporary, args.out)
checkpoint()
try:
with args.out.open("a", encoding="utf-8") as stream:
for item in todo:
row = run_item(client, item)
stream.write(json.dumps(row, ensure_ascii=False) + "\n")
stream.flush()
os.fsync(stream.fileno())
done.add(item["id"])
checkpoint()
print(f"completed={len(done)}/{len(items)} requests={meta['request_attempts']}", flush=True)
meta["status"] = "complete"
except CallBudgetExceeded as error:
meta["status"] = "budget_exhausted"
for item in todo:
row = run_item(client, item, by_id.get(item["id"]))
save_row(row)
print(f"completed={len(done)}/{len(items)} requests={meta['request_attempts']}", flush=True)
meta["status"] = "complete" if len(done) == len(items) else "detector_errors"
except (CallBudgetExceeded, ProviderBlocked) as error:
if getattr(error, "row", None) is not None:
save_row(error.row)
meta["status"] = "provider_blocked" if isinstance(error, ProviderBlocked) else "budget_exhausted"
print(str(error), file=sys.stderr)
except BaseException:
meta["status"] = "interrupted"
@@ -186,6 +239,7 @@ def main() -> int:
ap.add_argument("--out", required=True, type=Path)
ap.add_argument("--max-calls", type=int, default=400)
ap.add_argument("--dry-run", action="store_true")
ap.add_argument("--audit-only", action="store_true", help="Reconcile saved state without making API calls")
ap.add_argument("--labels", type=Path, help="Frozen labels; their hash is bound to the run")
args = ap.parse_args()
if not 1 <= args.max_calls <= 400:
+59 -10
View File
@@ -1,4 +1,4 @@
"""Roles and simplices: the parameters of a declaration as a small typed schema.
"""Semantic multi-role relation schemas, not geometric simplices.
A Lean declaration is a bundle of roles: the objects it is about (``(G : Type*)``),
the facts it assumes (``(h : a ∣ b)``), and the goal it asserts or the thing it
@@ -8,8 +8,8 @@ be read off the prose of a book, so the two can be compared role by role.
Design notes (from the archived ``schema-simplex`` prototype):
* a role may be *constrained* to a closed set of allowed values (``choices``);
* a simplex is itself a role, so simplices nest (a lemma used by another is a role
of it), which is how a dependency structure appears;
* a simplex is itself a role, so explicitly supplied schemas can be composed;
nesting does not discover a proof dependency;
* validation lives in ``__init__``. The prototype put it in a dataclass
``__post_init__`` next to a hand-written ``__init__``, where it never ran.
"""
@@ -41,7 +41,7 @@ class Role:
choices: Sequence[Any] | None = None,
attrs: dict[str, Any] | None = None,
) -> None:
if not name:
if not isinstance(name, str) or not name.strip():
raise ValueError("a role needs a name")
if kind not in KINDS:
raise ValueError(f"unknown role kind {kind!r}; expected one of {KINDS}")
@@ -49,6 +49,8 @@ class Role:
self.kind = kind
self.type_text = type_text
self.context = context
if isinstance(choices, (str, bytes)):
raise ValueError("choices must be a value sequence, not a string")
self.choices: list[Any] | None = list(choices) if choices is not None else None
self.attrs: dict[str, Any] = dict(attrs or {})
@@ -83,12 +85,21 @@ class Role:
class Simplex(Role):
"""A reusable bundle of at least two roles, keyed by alias. Itself a role."""
def __init__(self, name: str, roles: dict[str, Role], *, context: str = "") -> None:
super().__init__(name, KIND_SIMPLEX, context=context)
def __init__(self, name: str, roles: dict[str, Role], *, context: str = "",
attrs: dict[str, Any] | None = None) -> None:
super().__init__(name, KIND_SIMPLEX, context=context, attrs=attrs)
if len(roles) < MIN_ROLES:
raise ValueError(
f"simplex {name!r} needs at least {MIN_ROLES} roles, got {len(roles)}"
)
if any(not isinstance(alias, str) or not alias or not isinstance(role, Role)
for alias, role in roles.items()):
raise ValueError("simplex slots need nonempty aliases and Role values")
for role in roles.values():
references = role.attrs.get("references", [])
if (not isinstance(references, list)
or any(not isinstance(alias, str) or alias not in roles for alias in references)):
raise ValueError("role references must name slots in this simplex")
self.roles = dict(roles)
def by_kind(self, kind: str) -> list[Role]:
@@ -105,16 +116,16 @@ class Simplex(Role):
return out
def as_dict(self) -> dict[str, Any]:
return {
"name": self.name,
"roles": {alias: role.as_dict() for alias, role in self.roles.items()},
}
return {**super().as_dict(),
"roles": {alias: role.as_dict() for alias, role in self.roles.items()}}
class State:
"""A role together with a value; unresolved until it has one."""
def __init__(self, role: Role, value: Any = None) -> None:
if value is not None:
role.check_value(value)
self.role = role
self.value = value
@@ -133,3 +144,41 @@ class Fact(State):
class Goal(State):
"""To be resolved."""
def role_from_dict(data: dict[str, Any]) -> Role:
"""Restore JSON role/schema data without executing code or loading pickle."""
kind = data.get("kind", KIND_SIMPLEX if "roles" in data else KIND_OBJECT)
if kind == KIND_SIMPLEX:
return Simplex(data["name"], {alias: role_from_dict(role)
for alias, role in data["roles"].items()},
context=data.get("context", ""), attrs=data.get("attrs"))
return Role(data["name"], kind, type_text=data.get("type", ""),
context=data.get("context", ""), choices=data.get("choices"),
attrs=data.get("attrs"))
class SimplexInstance:
"""Values bind local slot aliases; a resolved goal is supplied, not proved here."""
def __init__(self, schema: Simplex, facts: dict[str, Any] | None = None,
goals: Sequence[str] | None = None) -> None:
self.schema = schema
facts = facts or {}
goal_aliases = list(goals) if goals is not None else [
alias for alias, role in schema.roles.items() if role.kind in (KIND_GOAL, KIND_OWN)]
if (len(set(goal_aliases)) != len(goal_aliases)
or not (set(facts) | set(goal_aliases)) <= set(schema.roles)
or set(facts) & set(goal_aliases)):
raise ValueError("facts/goals need distinct, declared slot aliases")
self.facts = {alias: Fact(schema.roles[alias], value) for alias, value in facts.items()}
self.goals = {alias: Goal(schema.roles[alias]) for alias in goal_aliases}
def resolve(self, alias: str, value: Any) -> None:
if alias not in self.goals or value is None:
raise ValueError("resolve needs a declared goal and a non-None value")
self.goals[alias].role.check_value(value)
self.goals[alias].value = value
def is_completed(self) -> bool:
return bool(self.goals) and all(goal.is_resolved() for goal in self.goals.values())
+208
View File
@@ -0,0 +1,208 @@
"""JSON/SQLite registry of semantic relation schemas and scoped slot occurrences.
A role definition may be reused deliberately. Occurrences remain local to a
simplex: sharing a role definition never equates the objects bound to its aliases.
"""
from __future__ import annotations
import fnmatch
import json
import sqlite3
from collections.abc import Iterable, Mapping
from pathlib import Path
from urllib.parse import quote
from .schema import KIND_GOAL, KIND_OWN, KIND_SIMPLEX, Role, Simplex, role_from_dict
def slot_key(parent: str, alias: str) -> str:
"""An occurrence identity, distinct even when two slots reuse one definition."""
return f"{parent}/slot/{quote(alias, safe='')}"
class SchemaRegistry:
"""Immutable versioned records; reusing a key with changed content is rejected."""
def __init__(self, path: str | Path = ":memory:") -> None:
self.connection = sqlite3.connect(str(path))
self.connection.execute("PRAGMA foreign_keys = ON")
self.connection.executescript("""
CREATE TABLE IF NOT EXISTS schema_nodes (
key TEXT PRIMARY KEY,
kind TEXT NOT NULL CHECK(kind IN ('role', 'simplex')),
payload TEXT NOT NULL
);
CREATE TABLE IF NOT EXISTS schema_slots (
parent TEXT NOT NULL REFERENCES schema_nodes(key) ON DELETE CASCADE,
alias TEXT NOT NULL,
child TEXT NOT NULL REFERENCES schema_nodes(key) ON DELETE RESTRICT,
position INTEGER NOT NULL,
PRIMARY KEY(parent, alias),
UNIQUE(parent, position)
);
CREATE INDEX IF NOT EXISTS schema_slots_child ON schema_slots(child);
""")
def __enter__(self):
return self
def __exit__(self, *_):
self.close()
def close(self) -> None:
self.connection.close()
def _insert(self, key: str, kind: str, payload: dict) -> None:
if not isinstance(key, str) or not key:
raise ValueError("a registry key must be nonempty")
if (kind == "simplex") != (payload.get("kind") == KIND_SIMPLEX):
raise ValueError("nested simplex roles must use a Simplex object")
encoded = json.dumps(payload, sort_keys=True, ensure_ascii=False, allow_nan=False)
existing = self.connection.execute(
"SELECT kind, payload FROM schema_nodes WHERE key = ?", (key,)).fetchone()
if existing is not None and existing != (kind, encoded):
raise ValueError(f"key {key!r} already has different content; use a new version key")
self.connection.execute("INSERT OR IGNORE INTO schema_nodes VALUES (?, ?, ?)",
(key, kind, encoded))
def set_role(self, role: Role, key: str | None = None) -> str:
if isinstance(role, Simplex):
raise ValueError("use set_simplex for nested schemas")
key = key or f"role:{role.name}"
with self.connection:
self._insert(key, "role", role.as_dict())
return key
def set_simplex(self, simplex: Simplex, key: str | None = None,
role_keys: Mapping[str, str] | None = None) -> str:
"""Default children are scoped. role_keys explicitly opts into definition reuse."""
key = key or f"schema:{simplex.name}"
role_keys = dict(role_keys or {})
if not set(role_keys) <= set(simplex.roles):
raise ValueError("reuse map has an unknown alias")
with self.connection:
self._put_simplex(simplex, key, role_keys, set())
return key
def _put_simplex(self, simplex: Simplex, key: str, reuse: dict[str, str],
active: set[int]) -> None:
if id(simplex) in active:
raise ValueError("cyclic simplex nesting")
active = active | {id(simplex)}
# Metadata only; children live in a relational slot table, not pickle blobs.
payload = Role.as_dict(simplex)
existing = self.connection.execute(
"SELECT key FROM schema_nodes WHERE key = ?", (key,)).fetchone()
if existing:
restored = self.get_simplex(key)
if restored is None or restored.as_dict() != simplex.as_dict():
raise ValueError(f"key {key!r} already has different content; use a new version key")
expected = {alias: reuse.get(alias, slot_key(key, alias)) for alias in simplex.roles}
if self.slots(key) != expected:
raise ValueError("same schema key cannot change its role-definition references")
return
self._insert(key, "simplex", payload)
for position, (alias, child) in enumerate(simplex.roles.items()):
child_key = reuse.get(alias, slot_key(key, alias))
if alias in reuse:
restored = self.get(child_key)
if restored is None or restored.as_dict() != child.as_dict():
raise ValueError(f"reused role definition does not match slot {alias!r}")
elif isinstance(child, Simplex):
self._put_simplex(child, child_key, {}, active)
else:
self._insert(child_key, "role", child.as_dict())
self.connection.execute("INSERT INTO schema_slots VALUES (?, ?, ?, ?)",
(key, alias, child_key, position))
def get(self, key: str) -> Role | None:
return self._get(key, set())
def _get(self, key: str, active: set[str]) -> Role | None:
if key in active:
raise ValueError("cyclic schema references in registry")
row = self.connection.execute(
"SELECT kind, payload FROM schema_nodes WHERE key = ?", (key,)).fetchone()
if row is None:
return None
kind, encoded = row
payload = json.loads(encoded)
if kind == "role":
return role_from_dict(payload)
slots = self.slots(key)
children = {alias: self._get(child, active | {key}) for alias, child in slots.items()}
return Simplex(payload["name"], children, context=payload.get("context", ""),
attrs=payload.get("attrs"))
def get_role(self, key: str) -> Role | None:
value = self.get(key)
return value if not isinstance(value, Simplex) else None
def get_simplex(self, key: str) -> Simplex | None:
value = self.get(key)
return value if isinstance(value, Simplex) else None
def slots(self, key: str) -> dict[str, str]:
return dict(self.connection.execute(
"SELECT alias, child FROM schema_slots WHERE parent = ? ORDER BY position", (key,)))
def keys(self, pattern: str = "*") -> list[str]:
return [key for (key,) in self.connection.execute("SELECT key FROM schema_nodes ORDER BY key")
if fnmatch.fnmatchcase(key, pattern)]
def search_roles(self, query: str, limit: int = 10) -> list[dict]:
"""Literal substring candidates; search does not authorize semantic reuse."""
if not query.strip() or limit < 1:
return []
found = []
for key, payload in self.connection.execute(
"SELECT key, payload FROM schema_nodes WHERE kind = 'role' ORDER BY key"):
if query.casefold() in (key + payload).casefold():
found.append({"key": key, "role": json.loads(payload)})
if len(found) == limit:
break
return found
def find_by_roles(self, role_keys: Iterable[str], match_all: bool = False) -> list[str]:
"""Find schema keys containing definition keys, including nested descendants."""
wanted = set(role_keys)
if not wanted:
return []
found = []
for key in self._simplex_keys():
descendants = {row[0] for row in self.connection.execute("""
WITH RECURSIVE descendants(child) AS (
SELECT child FROM schema_slots WHERE parent = ?
UNION
SELECT slots.child FROM schema_slots slots JOIN descendants d ON slots.parent = d.child
) SELECT child FROM descendants
""", (key,))}
matches = wanted <= descendants if match_all else bool(wanted & descendants)
if matches:
found.append(key)
return found
def find_solvable(self, known_slots: Iterable[str]) -> list[dict]:
"""Structural readiness by scoped occurrences, not proof or value unification."""
known = set(known_slots)
candidates = []
for key in self._simplex_keys():
schema = self.get_simplex(key)
inputs, outputs = [], []
for alias, role in schema.roles.items():
target = outputs if role.kind in (KIND_GOAL, KIND_OWN) else inputs
target.append(slot_key(key, alias))
missing_outputs = [output for output in outputs if output not in known]
if missing_outputs and set(inputs) <= known:
candidates.append({"schema_key": key, "input_slots": inputs,
"target_slots": missing_outputs, "structural_candidate_only": True})
return candidates
def _simplex_keys(self) -> list[str]:
return [row[0] for row in self.connection.execute(
"SELECT key FROM schema_nodes WHERE kind = 'simplex' ORDER BY key")]
def info(self) -> dict[str, int]:
counts = dict(self.connection.execute("SELECT kind, count(*) FROM schema_nodes GROUP BY kind"))
return {"roles": counts.get("role", 0), "simplices": counts.get("simplex", 0),
"slots": self.connection.execute("SELECT count(*) FROM schema_slots").fetchone()[0]}
+79
View File
@@ -141,3 +141,82 @@ def test_judge_rejects_string_boolean():
rp = load("run_pilot")
with pytest.raises(ValueError, match="unusable judge"):
rp.judge(ScriptedClient(['{"faithful": "false"}']), "passage", "code")
def test_partial_resume_keeps_successful_detector_output():
rp = load("run_pilot")
row = rp.run_item(Stub(), ITEM)
expected_role = row["role"]
row.pop("judge")
row["errors"]["judge"] = "temporary failure"
class JudgeOnly:
calls = 0
def complete_json(self, messages):
self.calls += 1
assert "faithful" in messages[0]["content"]
return {"faithful": True}
client = JudgeOnly()
resumed = rp.run_item(client, ITEM, row)
assert client.calls == 1
assert resumed["role"] == expected_role
assert rp.complete_row(resumed)
assert row["errors"] == {"judge": "temporary failure"}
def test_billing_failure_stops_before_next_detector():
import pytest
from leanbench.llm import LLMError
rp = load("run_pilot")
class Blocked:
calls = 0
def complete_json(self, messages):
self.calls += 1
raise LLMError("HTTP 400: Arrearage overdue-payment")
client = Blocked()
with pytest.raises(rp.ProviderBlocked) as caught:
rp.run_item(client, ITEM)
assert client.calls == 1
assert "role" in caught.value.row["errors"]
assert "judge" not in caught.value.row["errors"]
def test_blocked_run_preserves_and_replaces_partial_row(tmp_path, monkeypatch):
import argparse
import json
from leanbench.config import Settings
rp = load("run_pilot")
args = argparse.Namespace(items=tmp_path / "items.jsonl", out=tmp_path / "results.jsonl",
max_calls=400, dry_run=False)
args.items.write_text(json.dumps(ITEM) + "\n")
partial = {"id": "x1", "compiled": True, "role": {"flagged": False},
"errors": {"judge": "Arrearage"}}
def blocked(client, item, previous):
raise rp.ProviderBlocked(partial)
monkeypatch.setattr(rp, "run_item", blocked)
assert rp.execute(args, [ITEM], Settings()) == 2
meta = json.loads(args.out.with_suffix(".meta.json").read_text())
assert meta["status"] == "provider_blocked"
assert meta["completed_items"] == 0
def recover(client, item, previous):
assert previous["role"] == partial["role"]
return {**previous, "judge": {"faithful": True}, "errors": {}}
monkeypatch.setattr(rp, "run_item", recover)
assert rp.execute(args, [ITEM], Settings()) == 0
rows = [json.loads(line) for line in args.out.read_text().splitlines()]
assert len(rows) == 1 and rp.complete_row(rows[0])
meta = json.loads(args.out.with_suffix(".meta.json").read_text())
assert meta["completed_items"] == 1 and meta["status"] == "complete"
+162
View File
@@ -0,0 +1,162 @@
"""Semantic role definitions, scoped occurrences and structural candidate retrieval."""
import json
import pytest
from leanbench.schema import (
KIND_FACT,
KIND_GOAL,
Fact,
Role,
Simplex,
SimplexInstance,
role_from_dict,
)
from leanbench.schema_registry import SchemaRegistry, slot_key
def theorem(name="t"):
return Simplex(name, {"G": Role("group", context="A group carrier"),
"g": Role("element", type_text="G", attrs={"references": ["G"]}),
"finite": Role("finite", KIND_FACT, type_text="Finite G",
attrs={"references": ["G"]}),
"goal": Role("claim", KIND_GOAL, type_text="P G g",
attrs={"references": ["G", "g"]})},
context="A multi-object claim", attrs={"provenance": "synthetic"})
def test_json_roundtrip_keeps_metadata_and_nesting():
outer = Simplex("outer", {"lemma": theorem(), "goal": Role("result", KIND_GOAL)},
context="Composed relation", attrs={"version": 1})
encoded = json.loads(json.dumps(outer.as_dict()))
restored = role_from_dict(encoded)
assert restored.as_dict() == outer.as_dict()
assert restored.roles["lemma"].roles["g"].attrs["references"] == ["G"]
def test_registry_persists_nested_schemas_in_one_transaction(tmp_path):
path = tmp_path / "registry.sqlite"
outer = Simplex("outer", {"lemma": theorem(), "goal": Role("result", KIND_GOAL)})
with SchemaRegistry(path) as registry:
registry.set_simplex(outer)
registry.set_simplex(outer)
assert registry.info() == {"roles": 5, "simplices": 2, "slots": 6}
with SchemaRegistry(path) as registry:
assert registry.get_simplex("schema:outer").as_dict() == outer.as_dict()
leaf = slot_key(slot_key("schema:outer", "lemma"), "g")
assert registry.find_by_roles([leaf], match_all=True) == [
"schema:outer", slot_key("schema:outer", "lemma")]
def test_same_names_in_different_theorems_are_scoped():
with SchemaRegistry() as registry:
registry.set_simplex(theorem("first"))
registry.set_simplex(theorem("second"))
first_group = slot_key("schema:first", "G")
assert registry.find_by_roles([first_group]) == ["schema:first"]
assert registry.get_role(first_group).name == "group"
assert registry.slots("schema:first")["G"] != registry.slots("schema:second")["G"]
def test_explicit_reuse_does_not_equate_local_bindings_or_multiplicity():
group = Role("group")
schema = Simplex("isomorphism", {"left": group, "right": group,
"goal": Role("equivalence", KIND_GOAL)})
with SchemaRegistry() as registry:
registry.set_role(group, "role:group")
registry.set_simplex(schema, role_keys={"left": "role:group", "right": "role:group"})
assert registry.slots("schema:isomorphism")["left"] == "role:group"
assert registry.find_solvable(["role:group"]) == []
assert registry.find_solvable([slot_key("schema:isomorphism", "left")]) == []
candidate = registry.find_solvable([slot_key("schema:isomorphism", x) for x in ["left", "right"]])
assert candidate[0]["target_slots"] == [slot_key("schema:isomorphism", "goal")]
instance = SimplexInstance(schema, {"left": "C2", "right": "C3"})
assert instance.facts["left"].value != instance.facts["right"].value
assert not instance.is_completed()
instance.resolve("goal", "a supplied result, not checked by the registry")
assert instance.is_completed()
def test_premise_is_required_and_known_goal_is_not_a_missing_target():
with SchemaRegistry() as registry:
registry.set_simplex(theorem())
inputs = [slot_key("schema:t", alias) for alias in ["G", "g", "finite"]]
assert registry.find_solvable(inputs[:-1]) == []
assert registry.find_solvable(inputs)[0]["structural_candidate_only"]
assert registry.find_solvable(inputs + [slot_key("schema:t", "goal")]) == []
def test_failed_write_rolls_back_every_child():
with SchemaRegistry() as registry:
registry.set_role(Role("incompatible"), "role:shared")
before = registry.info()
with pytest.raises(ValueError, match="does not match"):
registry.set_simplex(theorem(), role_keys={"goal": "role:shared"})
assert registry.info() == before
assert registry.get_simplex("schema:t") is None
def test_cyclic_nesting_is_rejected_without_partial_write():
schema = Simplex("cycle", {"a": Role("a"), "b": Role("b")})
schema.roles["b"] = schema
with SchemaRegistry() as registry:
with pytest.raises(ValueError, match="cyclic"):
registry.set_simplex(schema)
assert registry.info() == {"roles": 0, "simplices": 0, "slots": 0}
def test_keys_are_immutable_and_reuse_map_cannot_silently_change():
with SchemaRegistry() as registry:
registry.set_role(Role("G"), "role:G")
with pytest.raises(ValueError, match="different content"):
registry.set_role(Role("H"), "role:G")
schema = theorem()
registry.set_simplex(schema)
registry.set_role(schema.roles["G"], "role:shared")
with pytest.raises(ValueError, match="cannot change"):
registry.set_simplex(schema, role_keys={"G": "role:shared"})
assert registry.search_roles("%") == []
assert registry.search_roles("group", limit=1)[0]["role"]["name"] == "group"
def test_instance_constraints_unknown_slots_and_invalid_references():
role = Role("parity", choices=["even", "odd"])
with pytest.raises(ValueError, match="not allowed"):
Fact(role, "prime")
schema = Simplex("pair", {"input": role, "goal": Role("result", KIND_GOAL, choices=[True])})
instance = SimplexInstance(schema, {"input": "even"})
with pytest.raises(ValueError, match="not allowed"):
instance.resolve("goal", False)
with pytest.raises(ValueError, match="declared"):
SimplexInstance(schema, {"unknown": "value"})
with pytest.raises(ValueError, match="references"):
Simplex("invalid", {"x": Role("x", attrs={"references": ["missing"]}), "y": Role("y")})
with pytest.raises(ValueError, match="name"):
Role(" ")
with pytest.raises(ValueError, match="sequence"):
Role("choice", choices="even")
with SchemaRegistry() as registry, pytest.raises(ValueError, match="Simplex object"):
registry.set_role(Role("fake", "simplex"))
def test_pilot_materialization_keeps_partial_lean_projection_explicit():
import importlib.util
from pathlib import Path
path = Path(__file__).resolve().parents[1] / "experiments/P0-pilot/build_schemas.py"
spec = importlib.util.spec_from_file_location("build_schemas", path)
builder = importlib.util.module_from_spec(spec)
spec.loader.exec_module(builder)
items = [{"id": "closed", "lean_code": "theorem t : True := trivial"}]
assessment = {"records": [{"id": "closed", "blind_id": "P01", "source": {
"roles": [{"kind": "object", "symbols": ["G"], "description": "group"},
{"kind": "goal", "description": "A synthetic claim"}]}}]}
with SchemaRegistry() as registry:
index, snapshots = builder.build(items, assessment, {"P01": "closed"}, registry)
assert registry.info()["simplices"] == 1
assert index[0]["source_status"] == "unreviewed_annotation_seed"
assert index[0]["lean_schema"] is None
assert index[0]["lean_status"] == "insufficient_projected_roles"
assert snapshots[0]["lean_projection"]["roles"][0]["kind"] == "goal"
with pytest.raises(ValueError, match="exactly once"):
builder.build(items, {"records": []}, {"P01": "closed"}, registry)