mirror of
https://github.com/langbot-app/LangBot.git
synced 2026-06-20 20:44:21 +00:00
Junyan Chin
e9dd584792
* feat(api): support global API key from config.yaml (api.global_api_key) Accept a config-defined global API key anywhere a web-UI key is accepted (X-API-Key / Bearer), with no login session and no DB record. Useful for automated deployments and AI agents (HTTP API + MCP). Defaults to empty (disabled); does not require the lbk_ prefix. - templates/config.yaml: add api.global_api_key with security notes - service/apikey.py: verify_api_key checks global key first (constant-time) - docs/API_KEY_AUTH.md: document the global key + security guidance - tests: cover global-key match, prefix-free, fallback-to-db, disabled * feat(mcp): expose LangBot management as an MCP server at /mcp Add an MCP (Model Context Protocol) server so external AI agents can manage a LangBot instance. Reuses the same API-key auth as the HTTP API (including the config.yaml global API key). - pkg/api/mcp/server.py: FastMCP server wrapping the service layer; 21 curated tools across system/bots/pipelines/models/knowledge/mcp-servers/skills - pkg/api/mcp/mount.py: ASGI dispatcher fronting Quart; authenticates /mcp requests with an API key, runs the streamable-HTTP session manager lifespan - controller/main.py: serve the wrapped ASGI app via hypercorn (was run_task) - web: new 'MCP' tab in the API integration dialog showing endpoint, auth, and client config; i18n for 8 locales - tests/manual/mcp_smoke.py: e2e check (401 unauth, list tools, call tools) Tool surface is intentionally curated (not all ~25 route groups) to keep the agent surface small, safe, and maintainable. Extend deliberately. * feat(skills): add in-repo skills/ as the single source of truth Migrate the agent skills + QA/e2e test harness from the (now archived) langbot-app/langbot-skills repo into LangBot/skills/, and add four new skills. Migrated: - langbot-plugin-dev, langbot-testing (e2e), langbot-env-setup, langbot-skills-maintenance, langbot-eba-adapter-dev - the bin/lbs CLI (src/, test/, scripts/, schemas/, qa-agent-docs/) New: - langbot-dev core backend + web development - langbot-deploy Docker/K8s deployment + config.yaml + global API key - langbot-mcp-ops operating the LangBot MCP server (/mcp) - langbot-space-ops operating the Space marketplace MCP server - src/cli.ts repoRoot(): recognize the skills assets root (skills.index.json + bin/lbs) so the CLI works when nested inside the LangBot repo - README.md: unified skill catalog; skills.index.json regenerated Parity with source verified: bin/lbs validate + node test suite match the source repo (only the uncommitted .lbpkg build-artifact fixture differs). * docs(agents): document agent-facing surfaces + API/MCP/skills sync rule * docs(readme): add 'Built for AI Agents' section across all locales Highlight MCP server, in-repo skills (single source of truth), AGENTS.md sync rule, and llms.txt. Cross-link LangBot Space MCP marketplace. * style(mcp): fix ruff format + prettier lint in MCP server and API panel * style(web): prettier format MCP i18n locale entries * docs(skills): note MCP instance control in dev/testing skills All development-guidance skills now point to the LangBot instance MCP server (/mcp) and the Space marketplace MCP server, reusing API keys.
60 lines
2.9 KiB
Markdown
60 lines
2.9 KiB
Markdown
# Schemas
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这个目录存放 LangBot skills 结构化资产的 JSON Schema。
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它们不是测试脚本，也不会执行浏览器动作。它们的作用是定义 agent 和维护者后续新增资产时应该遵守的文件结构。
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## 文件说明
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- `skills/<skill>/fixtures/fixtures.json`
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不是 JSON Schema，但由 `bin/lbs validate` 校验。
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它登记 deterministic fixture 文件、类型和关联 case，供 `bin/lbs fixture check` 做 readiness 检查。
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- `case.schema.json`
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约束 `skills/<skill>/cases/*.yaml` 的格式。
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Case 描述 agent-browser 或 probe QA 路径，包括前置条件、步骤、检查点、诊断手段和关联故障。
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- `suite.schema.json`
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约束 `skills/<skill>/suites/*.yaml` 的格式。
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Suite 只组织 case 集合，用于 smoke、regression 或 release gate 等测试入口。
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- `troubleshooting.schema.json`
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约束 `skills/<skill>/troubleshooting/*.yaml` 的格式。
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Troubleshooting 条目描述症状、日志/错误模式、可能原因、修复步骤和验证信号。
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- `skill-index.schema.json`
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约束生成文件 `skills.index.json` 的格式。
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这个索引用于让 agent 快速发现已有 skills、references、cases、suites 和 troubleshooting。
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- `reports/evidence/<run-id>/result.json`
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不是 catalog schema，而是执行期最终裁定产物，由 `bin/lbs test result` 写入。
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`suite report` 读取其中的 `status`、`reason`、起止时间和 `evidence_collected`，
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并用 `evidence_missing` 防止缺证据的 `pass` 被当作完整通过。
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- `reports/evidence/<run-id>/automation-result.json`
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不是 catalog schema，而是浏览器自动化脚本的原始运行结论，供 `bin/lbs test report`
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展示和推断日志扫描窗口。
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## 为什么需要 schemas
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Schemas 是基础设施护栏：
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- 防止 case、suite 和 troubleshooting 随着增长变得格式混乱
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- 让 `bin/lbs validate` 能发现缺字段和错误结构
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- 为未来编辑器提示和 CI 校验留接口
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- 帮助 agent 新增资产时知道应该写哪些字段
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## 当前校验方式
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`bin/lbs validate` 做轻量、schema 对齐的校验，不引入额外依赖。它会检查必填字段、
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枚举值、boolean 字段、重复列表项、automation 脚本存在性，以及 case、suite、skill、
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troubleshooting 之间的交叉引用。这里的 schema 仍是格式契约；如果未来引入正式 JSON
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Schema validator，应继续保持这些本地交叉引用检查。
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Case 里的 `env` / `automation_env` 表示所有列出的变量都需要配置。遇到二选一输入时，
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使用 `env_any` / `automation_env_any`，每一项写成 `LANGBOT_PIPELINE_URL|LANGBOT_PIPELINE_NAME`
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这类 one-of 组合，避免 agent 因为只配置了 URL 或 name 其中之一而误判未就绪。
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`setup` 和 `preconditions` 是人工确认项，会让 readiness 进入 `manual_check`；
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`setup_automation` 是 `test run` 可以自动执行的准备步骤，配合 `setup_provides_env`
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声明它会生成的机器变量。
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