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License Texts 31 EN
At least one license candidate text was verified for every one of the 2,400 frozen evaluation snapshots. This establishes acquisition, not complete legal review, model quality, or blanket training/redistribution permission.
Follow the precommitted plan, recompute experiment 29 membership and retain all 2,400 tasks. Only the 170 snapshots without root candidates receive bounded nested lookup: immediate files in Matplotlib's LICENSE directory, or license-name files in Axum's axum and axum-* packages. Do not recursively scan arbitrary code or vendor paths.
| Item | Result |
|---|---|
| Selected snapshots / snapshots with verified text | 2,400 / 2,400 |
| Snapshots requiring nested lookup | 170 |
| No candidates / tree failures / blob failures / symlinks | 0 each |
| Per-snapshot text references | 4,941 |
| Unique repository/path/object tuples | 169 |
| Distinct text objects / total text bytes | 159 / 820,911 |
Publish repository aggregates; keep individual tasks, commits, text digests and original bodies local. The 169 tuples are not license types. Finding at least one text does not establish coverage of every file in a snapshot.
Match subtree IDs to parent entries. Verify blob response ID, declared size and base64, then recompute Git blob SHA-1 from content and record a separate SHA-256. Bound text to 256KiB, valid UTF-8 without NUL, and reverify cached bodies. Do not follow symlinks arbitrarily.
Use one request at a time, minimum 250ms start spacing, 30-second timeout and 2MiB API response limit. Persist only verified bodies through a temporary file and atomic rename. Require a new output directory.
go run ./cmd/riido-licensetext --out .cache/license-texts-new
go run ./cmd/riido-licensetext --offline --out .cache/license-texts-offline-newPinned source projections and previous root caches are prerequisites. Offline mode never fills missing entries over the network. Both aggregate and private inventory match the original collection byte for byte, including an actual 2,400-snapshot replay under the race detector. Run full Go race/vet, formatting and redacted secret checks.
One M4 Pro CPU cache replay took 0.63s wall, 0.39s user, 0.13s sys and 29,130,752 bytes maximum RSS (about 27.8MiB). This excludes initial network collection, model/GPU execution and full source storage.
The acquired Matplotlib text permits analysis/testing with notice preservation and a change summary for distributed derivatives. Separate font/image terms are also present, so a single repository-wide assumption is insufficient. Axum package text includes MIT; the selected historical Terraform text is Business Source License 1.1. MPL 2.0 is named as the Change License, not evidence that the current conditions are MPL. The text permits non-production use and separately defines an Additional Use Grant and version-specific change timing. Do not substitute a current repository license for historical conditions. These are representative text checks, not completed legal review of all 159 bodies.
- MIT requires preservation of copyright and permission notices in copies or substantial portions. Official text
- Apache 2.0 redistribution includes license-copy, modification-notice, attribution and applicable NOTICE requirements. Official section 4
- Mozilla distinguishes internal use from external distribution; distribution obligations include source availability for covered files. Official MPL FAQ
Prepare subsequent evaluation with sources kept local and only aggregate findings published. Repository code licensing does not automatically resolve issue-author text or every third-party file. Raw corpus/source bundles and trained-model publication each require applicable-condition review. This experiment performs neither training nor model publication.
53 of the 2,400 requests exceed the existing 8,192-byte input bound. Keep these tasks and precommit input-window and cost accounting before constructing pre-fix file catalogs and evaluating helpful/harmful hints. Source preparation must not substitute for quality evaluation. Production readiness remains false; existing final reserves remain unused.
Follow-up: experiment 32 executes all 2,400 complete requests, including 53 long ones. This uses synthetic candidates; real file retrieval quality remains separate.
riidolaya is experimental. No demonstrated Codex cost savings; repository selection is preview-only.
riidolaya는 실험 단계입니다. Codex 절감은 미입증이며 저장소 선택은 preview입니다.
English README · 한국어 README · Versioned Wiki sources / Wiki 원본
이전 연구 안내 펼치기 / Earlier research
- 실제 이어 학습 V3 · 한국어 · Actual V3 training · English
- 진행·완료 보고·질문100건 결과 KO · 100-case results EN
- 라벨·이모지·상태 힌트 KO · Content/state hints EN
- 개발 진행·완료 보고·질문 pilot KO · Development pilot EN
- 작은 검증 기록 KO · Compact evidence EN
- 현재 개발 자료 35개·다음 학습 조건 · 35-row data and next training gates
- 개발용 학습 자료 2개 · Two qualified training requests
- 첫 두 과제 실제 관측 · First two actual observations
- 전체 사용법 KO · Full usage EN
- 작은 동작 힌트 KO · Small hints EN
- 설명 보강 비교76 · Caption diagnostic76
- Go 압축 가중치78 · Packed Go weights78
- 공개 함수 동작 검증 · Public function verification
- 다음 학습 자료 준비 · Training data preparation
- 동작에서 학습 정답·실제 학습79 · Grounded labels and actual fit79
- 소스 동작 관찰 · Source observations
- 저장 크기와 RAM · Storage and RAM
- 라이선스 · Licensing
- 시점별 기록 원문 / Chronological history
- 전체 연구 링크 / Full research index
- 문서 목록 / Documentation