Commit Graph
4 Commits
Author SHA1 Message Date
aleleba d9629c44ae Phase 6.1: capture verified Penpot API ground truth for the LoRA #2 dataset
The 41 existing Penpot seeds contain hand-fabricated penpot_api_info and
high_level_overview tool results that assert facts the server never said,
which is how the model learned an API that does not exist. This adds four
schema files that make the seed corpus mechanically verifiable against the
real server instead.

- penpot_api_docs.md: 34 verbatim captures of high_level_overview and
  penpot_api_info, each headed by the exact request that produced it. Every
  penpot_api_info tool result in a seed must be a subset of lines of this
  file, in original order. Records three places where the served docs
  contradict the runtime (addFlexLayout/addGridLayout copy-paste in the Grid
  section, flex.appendChild for grid children, withChildren vs
  includeChildren), plus the createText() example that is the direct cause
  of the production failure.
- penpot_system_prompt.md: the server's instructions block verbatim. Goes as
  a system message into ~30% of the new seeds; it is the countermeasure to
  the "don't pick your own colours" rule that produces the grey boxes.
- penpot_errors.md: the real error strings, including a section on silent
  failures that raise nothing at all and are why the read-back invariant
  exists.
- PENPOT_API_VERIFIED.md: the allow-list. No seed may reference a member
  absent from it. Documents the four root causes (findShapeById arity 1,
  no shape.layout, createText() returning null, the #B1B2B5 default fill),
  the twelve anti-grey-box invariants, and the forbidden-pattern list the
  linter checks.

Live re-verification of the error strings is still pending: the Penpot
plugin is not currently connected, so it is deferred to the gate 5 baseline
step, which needs the live connection anyway.
2026-07-30 16:46:33 +00:00
aleleba 73e7f721cd Fase 2: seeds de los 6 buckets (294 ejemplos: penpot 41, otros_mcps 102, skills_adherencia 55, delegacion_subagentes 25, negativos 46, manejo_errores 25) 2026-07-29 00:49:25 +00:00
aleleba b2aa855a70 Fase 1: schemas de los 5 MCPs y script de generacion de replay
data/schemas/*.json: dump fiel de las tool definitions reales de
Penpot (4), Gitea (53), GitHub-personal (43), Docmost (17) y
Atlassian (37), obtenidas directo de las definiciones ya cargadas
en la sesion de Claude Code (no se escribio un cliente MCP nuevo,
para no arriesgar desviarse del esquema real).

PENPOT_DEPLOYMENT_NOTES.md: investigacion del codigo fuente oficial
de @penpot/mcp confirma que import_image y export_shape.filePath
estan ausentes porque este deployment corre en modo remoto/multi-
usuario (isFileSystemAccessEnabled() = !isRemoteMode()) -- documentado
tambien en una subpagina nueva de Docmost.

scripts/03_build_replay.py: genera ~700 ejemplos de replay (anti-
forgetting) contra el vLLM de produccion, 80 prompts semilla
(conversacion general/codigo/razonamiento) x 9 pasadas variando
temperatura. Mapea el campo "reasoning" de la API de vLLM a
"reasoning_content" para la convencion de chat template.
2026-07-28 05:34:55 +00:00
aleleba 572ee0b60e Fase 0: estructura base de carpetas y docker-compose de training
Scaffolding inicial del repo: carpetas scripts/, data/schemas/,
data/raw/, out/, .gitignore para binarios/checkpoints, y el
docker-compose.yml del contenedor de training (imagen NGC pytorch
25.12-py3, GPU reservada, bind mounts a ai-projects vía NFS y a
~/ft-models en disco local rápido de spark) sin tocar jupyter-pyt
ni el vllm de producción.
2026-07-28 03:42:37 +00:00