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langbot-dev

Develop and debug LangBot's backend and web frontend. The skill guides environment setup, API additions, authentication, database migrations, and testing, including updates to matching MCP tools so agents can use changed API features.

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Develop, build, and debug the LangBot core backend and web frontend. Use when working inside the LangBot repository — backend (Python/Quart, src/langbot/pkg), the Vite/React web UI, HTTP API controllers/services, Alembic migrations, or the MCP server. Covers the dev environment (uv, pnpm), repo layout, the API auth model (user token / API key / global key), adding API endpoints, and the rule that API changes must update the MCP server and skills. Triggers on "langbot backend", "langbot dev", "langbot api", "add langbot endpoint", "langbot migration".

集成工具PostgreSQL
查看安装方法

适用场景

  • Set up the LangBot backend and frontend for development
  • Add an API endpoint and its matching MCP tool
  • Update the database schema with Alembic
  • Debug core behavior and run unit or API tests

包含的文件(1)

  • SKILL.md5.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

LangBot Core Development

This skill covers developing the LangBot core (the main repo), distinct from plugin development (see langbot-plugin-dev) and deployment (langbot-deploy).

Stack

  • Backend: Python >=3.11,<4.0, deps via uv. Framework: Quart (async Flask). Serves the HTTP API + pre-built web UI on http://127.0.0.1:5300.
  • Frontend (web/): Vite + React Router 7 + shadcn/ui + Tailwind, managed by pnpm. Dev server on :3000. (NOT Next.js — dev script is vite.)

Dev environment

# Backend
pip install uv
uv sync --dev
uv run main.py            # API + UI on http://127.0.0.1:5300

# Frontend (separate terminal)
cd web
cp .env.example .env
pnpm install
pnpm dev                  # http://127.0.0.1:3000 (reads VITE_API_BASE_URL)

# Lint/format hooks (CI runs the same checks)
uv run pre-commit install

First run generates data/config.yaml; DB defaults to SQLite (PostgreSQL supported). Migrations run automatically on startup.

Repo layout (key paths)

src/langbot/
├── __main__.py             # entrypoint, CLI flags (--standalone-runtime/-box/--debug)
├── pkg/
│   ├── api/
│   │   ├── http/           # Quart controllers + services
│   │   │   ├── controller/groups/   # route groups (@group.group_class)
│   │   │   └── service/             # business logic (called by controllers AND MCP)
│   │   └── mcp/            # MCP server (server.py = tools, mount.py = ASGI dispatch)
│   ├── core/               # app bootstrap, stages, task manager
│   ├── platform/ provider/ pipeline/ plugin/ box/ skill/ rag/ vector/
│   ├── command/ persistence/ storage/ config/ entity/ telemetry/
│   └── templates/config.yaml        # config template (top-level: api, system, plugin, box, space...)
├── web/                    # Vite SPA
└── docker/                 # compose deployment

HTTP API auth model

Route auth is declared per-route via AuthType in pkg/api/http/controller/group.py:

  • NONE — public.
  • USER_TOKEN — web UI JWT (Authorization: Bearer <jwt>).
  • API_KEY — X-API-Key or Authorization: Bearer <key>.
  • USER_TOKEN_OR_API_KEY — either.

Authenticated routes receive an immutable RequestContext containing the principal, authorized Workspace membership, fixed-role permissions, instance, request id, and placement generation. A browser's X-Workspace-Id is only a selector and is always checked against the Account membership. Tenant services must accept this context (or an explicit trusted execution context) and fail closed when it is absent.

API-key authentication accepts:

  1. the global key from config.yaml api.global_api_key only for a community instance with exactly one local Workspace, then
  2. web-UI keys whose one-time lbk_ secret is stored only as a hash and is bound to one Workspace, explicit scopes, status, and optional expiry.

An API key derives its Workspace from the key record and ignores a caller's Workspace selector. Public Bot/Webhook routes similarly derive Workspace from the opaque owning resource rather than a header.

Route groups self-register via @group.group_class(name, path) and are discovered by importutil.import_modules_in_pkg.

Adding an API endpoint

  1. Add/extend a controller in pkg/api/http/controller/groups/ and the matching service method in pkg/api/http/service/.
  2. Pick the right AuthType.
  3. If the endpoint should be agent-accessible, add/adjust the matching MCP tool in pkg/api/mcp/server.py and update the langbot-mcp-ops skill. API and MCP surface must stay aligned (see AGENTS.md).
  4. If lbctl uses the route or capability, check the separate langbot-cli client for compatibility.
  5. Update docs/service-api-openapi.json if you maintain the OpenAPI overview.

Database migrations (Alembic)

Single migration set supports SQLite + PostgreSQL. Files in src/langbot/pkg/persistence/alembic/versions/.

# From project root (needs data/config.yaml)
uv run python -m langbot.pkg.persistence.alembic_runner autogenerate "description"

Standards

  • All code comments/docstrings in English; user-facing strings need i18n (en_US + zh_Hans minimum, ja_JP where present).
  • Consider toC and toB compatibility + security.
  • Commit format: <type>(<scope>): <subject> (feat/fix/docs/refactor/...).

Tests

uv run pytest tests/unit_tests -q          # unit tests
uv run pytest tests/unit_tests/api -q      # API service tests
uv run python tests/manual/mcp_smoke.py    # MCP server e2e smoke

See also

  • langbot-plugin-dev — plugin SDK / runtime development.
  • langbot-testing — WebUI/e2e QA harness (bin/lbs).
  • langbot-deploy — Docker/compose deployment + config.
  • langbot-mcp-ops — operating the LangBot MCP server.
  • langbot-cli — lbctl, a standalone Service API client for managing running Workspaces.

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同一仓库的技能

Deploy and configure LangBot with Docker Compose or Kubernetes. Set up application settings, plugin execution, the Box sandbox for isolated commands, and API authentication, with guidance on hosting choices and common deployment problems.

中文简介正在准备中。当前显示英语简介。

  • Deploy LangBot on a self-hosted server
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中文简介正在准备中。当前显示英语简介。

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中文简介正在准备中。当前显示英语简介。

  • Prepare a local Linux or WSL development environment
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中文简介正在准备中。当前显示英语简介。

  • Connect an MCP client to LangBot
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Build and debug LangBot plugins that handle messages, commands, and AI tool calls. The skill covers SDK usage, common errors, test environment setup, WebSocket message testing, and preparation for publishing to LangBot Space.

中文简介正在准备中。当前显示英语简介。

  • Create a plugin that reacts to incoming messages
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中文简介正在准备中。当前显示英语简介。

  • Add a skill without duplicating existing guidance
  • Organize reference guides and test cases
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langbot-app/LangBot1.8万2026年10月18日 更新

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