Agent Skills › overmind-core/overmind › backend-architecture

backend-architecture

GitHub

提供overbae后端架构全景图,涵盖模块布局、核心设计模式及Celery/Modal等关键组件参考。用于快速导航不熟悉的后端子系统,或跨模块集成业务逻辑与数据流。

.agents/skills/backend-architecture/SKILL.md overmind-core/overmind

触发场景

需要了解后端整体模块结构 在陌生子系统中进行代码导航 需要跨子系统协调行为或集成

安装

npx skills add overmind-core/overmind --skill backend-architecture -g -y
更多选项

非标准路径

npx skills add https://github.com/overmind-core/overmind/tree/main/.agents/skills/backend-architecture -g -y

不安装直接使用

npx skills use overmind-core/overmind@backend-architecture

指定 Agent (Claude Code)

npx skills add overmind-core/overmind --skill backend-architecture -a claude-code -g -y

安装 repo 全部 skill

npx skills add overmind-core/overmind --all -g -y

预览 repo 内 skill

npx skills add overmind-core/overmind --list

SKILL.md

Frontmatter
{
    "name": "backend-architecture",
    "description": "Map of the overbae backend — module layout, the patterns every subsystem shares, and reference files for Celery topology, tracing and scoring, evaluation, capabilities and sync, auth and billing, training, serving and data-first workflows. Use when navigating an unfamiliar backend subsystem or wiring behavior across subsystems."
}

overbae backend map

Single Django app overbae, project-scoped tenancy.

Layout

  • api/ — DRF views and serializers, one module per surface (eval_views.py, datasets.py, optimizer.py, otlp.py, billing.py, mcp.py, …). views.py and serializers.py are legacy monoliths; a new surface gets its own module. The global exception handler (api/exception_handler.py) flattens list errors to {detail}, adds code, maps IntegrityError to 409 conflict, and returns {detail, code: internal_error, error_id} for unhandled errors.
  • models/ — split by domain (iam.py, capabilities.py, traces.py, innermind.py, finetuning.py, datasets.py, dataset_pipeline.py, operations.py, billing.py, …).
  • innermind/ — the eval matrix evaluators, live span and trajectory scoring, deterministic checks, evaluation runs, the Default eval set, health and signals.
  • services/ — business logic. Largest subtrees: datasets/ (Data Workshop; data-workshop skill), mcp/ (mcp skill), connectors/, sft_assets/ (training code baked into the Modal image), codebase/.
  • tasks/ — Celery tasks, roughly one module per feature; utils/task_lock.py for locking.
  • modal/ — Modal app entrypoints (vLLM serving, SFT, native decision evaluation and serving) and models.json. Code shared by those workers and the API lives in the root modal_shared/ package.
  • management/commands/ — seed_demo (seed-demo-data skill), grant_credits, check_workshop_transition, sync_baseten_finetuning_costs.

Patterns every subsystem follows

  • One domain service, three surfaces. REST, MCP and the Console call the same service. Never copy business logic into a view or an MCP adapter.
  • Request keys. An operation that starts work takes a project-scoped request_key. An identical retry returns the original record; a changed payload under the same key conflicts.
  • Durable admission. Waiting work lives in PostgreSQL rows, and a locked dispatcher admits it with per-project fairness. Do not park waiting work in the broker.
  • Unknown provider outcomes are reconciled, never resubmitted. Intent is journaled before a provider call; a lost acknowledgement becomes submission_unknown and is resolved from the saved call ID.
  • Measured, not invented. Missing usage, progress, scores or telemetry stay unknown or null. Never fill a percentage, a zero score, an ETA or a cost from elapsed time or a guess.
  • Status writes use .filter().update(). No Django signals fire; reload the row and wire side effects at the call site.
  • Model IDs: platform models (judges, generation, Jev) live in core/model_registry.py; the training and serving catalog lives in modal/models.json, read through modal/model_registry.py. Jev decisions go through core/decisions.py.
  • Modal code ships separately. Changes under overbae/modal/, modal_shared/ or services/sft_assets/ reach running jobs only after modal deploy; training and serving pin immutable releases.

Reference files

Read the one that matches the task:

File Covers
references/celery.md Workers, queues, routing, admission, deployment order
references/tracing-and-scoring.md Span model, OTLP ingest, span cost, live scoring, signals, Jev
references/evaluation.md Evaluation runs, comparison, judges, context estimates, benchmark selection
references/capabilities.md The agent graph, scans, toml sync, Default eval set, provenance
references/auth-and-billing.md Clerk and local auth, guests, API keys, billing, Overwatch internal endpoints
references/training.md Preparation, launch, monitoring, transfer, native decision training
references/serving.md Deployments, shared-base LoRA, activation, inference requests, operational receipts
references/data-first.md Training plans, partitions, native evaluation, experiments, performance runs

版本历史

  • fe6ddf7 当前 2026-11-02 09:22

    精简了目录路径前缀,更新了services和innermind模块的具体功能描述,新增了关于请求键、持久化准入及状态写入的详细架构规范。

  • e146ecd 2026-10-18 15:41

同 Skill 集合

.agents/skills/api-endpoints/SKILL.md
.agents/skills/code-comments/SKILL.md
.agents/skills/data-workshop/SKILL.md
.agents/skills/engineering-taste/SKILL.md
.agents/skills/frontend-design/SKILL.md
.agents/skills/mcp/SKILL.md
.agents/skills/pr-etiquette/SKILL.md
.agents/skills/run-tests/SKILL.md
.agents/skills/seed-demo-data/SKILL.md
overmind/skills/model-training-engineering/SKILL.md
overmind/skills/overmind-agent/SKILL.md
overmind/skills/overmind-datasets/SKILL.md
overmind/skills/overmind-evaluations/SKILL.md
overmind/skills/overmind-inference/SKILL.md
overmind/skills/overmind-integrations/SKILL.md
overmind/skills/overmind-observability/SKILL.md
overmind/skills/overmind-optimiser/SKILL.md
overmind/skills/overmind-training/SKILL.md
overmind/skills/overmind/SKILL.md
.agents/skills/finetuning-model-onboarding/SKILL.md

元信息

文件数
0
版本
fe6ddf7
Hash
a68f0fd9
收录时间
2026-10-18 15:41

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