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数据与研究 · SKILL.md

open-assistant

open-assistant

【数据与研究】Use Open-Assistant repository guidance for backend task APIs, OA JSONL data utilities, Next.js contribution/chat UI, and local inference services.

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技能说明

GitHub

name: open-assistant description: "Use Open-Assistant repository guidance for backend task APIs, OA JSONL data utilities, Next.js contribution/chat UI, and local inference services." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Open-Assistant repo skill

Use this repo skill when a task involves the LAION Open-Assistant repository: data-collection backend APIs, shared protocol schemas, OA JSONL exports, the Next.js website/task UI, or the local inference server/worker/chat stack. The upstream project is completed, so prefer targeted maintenance, debugging, local development, and data/inference workflow support over broad product-roadmap changes.

First decisions

  1. Check staleness: read references/repo-provenance.md before assuming this skill matches a checkout. If the commit, package versions, service layout, or major evidence paths changed, run refresh-repo-skill.

  2. Orient in the repo: read references/setup-and-architecture.md for the selected source scope, Docker profiles, service boundaries, and excluded heavy areas.

  3. Review managed routing: inspect references/repo-routing-metadata.json when you need the structured scenario metadata that keeps repo-skills-router placement aligned with this skill.

  4. Diagnose shared failures: read references/troubleshooting.md for cross-cutting Docker, Python, Node, secrets, and boundary-handoff issues.

  5. Run a safe layout check when a checkout is available:

    python scripts/check_open_assistant_stack.py --repo-root <repo-root>
    

Setup at a glance

Use the smallest stack that matches the task:

  • Backend and OA data utilities: python -m pip install -r backend/requirements.txt followed by python -m pip install -e 'oasst-shared[dev]' -e 'oasst-data[dev]'.
  • Website work: from website/, run npm ci before npm run lint, npm run typecheck, or Jest/Cypress checks.
  • Inference server/worker inspection: python -m pip install -r inference/server/requirements.txt for server imports and lightweight route checks. Keep _lorem for CPU-only plumbing checks before any real model config.
  • Full local stack debugging: use the Docker compose profile that matches the layer you are touching rather than starting every service.

Minimal verification once a checkout is available:

python scripts/check_open_assistant_stack.py --repo-root <repo-root>

Route by task

User intentGo toWhy
FastAPI backend, task lifecycle, /api/v1/tasks, messages/users/stats/text labels, backend settings, DB export/import, shared Python API client, or backend errorssub-skills/backend/SKILL.mdOwns backend API semantics, oasst_shared protocol models, oasst_data, and safe OA JSONL tooling.
OA JSONL files, message trees, flatten/filter/split operations, backend exports, data schema validationsub-skills/backend/SKILL.mdOwns bundled oasst_jsonl_tool.py and data-format reference.
Next.js website, contribution task pages, label/rank/reply UI, frontend API client, chat UI, Prisma, NextAuth, Jest, Cypress, Storybook, feature flags, or localizationsub-skills/website/SKILL.mdOwns browser/Next layer, website package scripts, UI route maps, tests, and locale helpers.
Inference FastAPI server, websocket workers, text client, _lorem/distilgpt2 smoke paths, model config names, SSE chat events, plugins, safety server, GPU sizing/OOMsub-skills/inference/SKILL.mdOwns inference services, model registry, worker protocol, and generation troubleshooting.
Docker profile confusion, local stack selection, service boundaries, or whether a task crosses backend/website/inferencereferences/setup-and-architecture.mdSummarizes profiles, service ownership, and handoff boundaries.

Safe bundled scripts

Scripts that accept --repo-root are intended for a user's current checkout, not for this skill's original construction checkout.

Scope boundaries

Included in this generated skill:

  • Backend REST API, settings, task lifecycle, DB export/import semantics, shared Python schemas/API client, and oasst_data JSONL utilities.
  • Website local dev, task UI, chat UI integration, frontend API client behavior, tests, Prisma, feature flags, and localization.
  • Inference server/worker/text-client/safety stack, model config registry, worker websocket protocol, SSE events, plugin parsing, and GPU sizing guidance.

Excluded from this generated skill run:

  • model/ training, reward modeling, RLHF, evaluation, pretokenization, and large-model export tools. These require a separate model-training extension because they involve heavy torch/DeepSpeed/FlashAttention/model/dataset/GPU dependencies.
  • Production deployment, Ansible, infrastructure operations, and credentials-bound systems.
  • Exploratory notebooks and historical analysis artifacts.
  • Docusaurus docs-site maintenance except where it informs setup boundaries.

Operating cautions

  • Do not start Docker services, download model weights, run GPU workers, call Hugging Face APIs, mutate databases, or run production/infrastructure scripts unless the user explicitly asks and accepts resource, credential, and rollback requirements.
  • Keep backend, website, and inference symptoms separate. Report the exact failing layer, command/route, status/body, and environment signals when routing to another sub-skill.
  • Use _lorem for no-download inference plumbing checks before attempting real model configurations.
  • Use safe JSONL file helpers before any DB import/export workflow. Real DB import is mutating unless a dry-run rollback is explicitly selected.
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