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34 Commits

Author SHA1 Message Date
RockChinQ
882c9ae8f5 fix(box): trust Box-reported skill paths when filesystem is not shared
In separated deployments (Docker Compose, k8s sidecar, --standalone-box,
remote runtime.endpoint) the Box runtime owns its own filesystem, so the
skill package_root it reports via list_skills is not resolvable on the
LangBot side. LangBot's reload_skills and build_skill_extra_mounts
validated those paths with os.path.isdir() against its own filesystem,
which silently dropped every skill in such deployments — breaking the
sandbox skill feature for the nsjail/SaaS backend.

Add BoxService.shares_filesystem_with_box, derived from the connector
transport (stdio = shared, WebSocket = separated), with an explicit
override seam for tests/embedders. Gate both isdir() guards on it: keep
local validation in shared-fs stdio mode, trust Box-reported paths
otherwise. The Box runtime only reports skills found on its own
filesystem, so those paths are valid there by construction.

Adds topology-derivation tests (real connector, no mocks) and
skill-retention tests for both shared and separated filesystems.
2026-06-07 12:46:52 -04:00
RockChinQ
47fe9bde03 docs(docker): move k8s deployment docs to wiki, drop README_K8S.md
The Kubernetes deployment guide now lives only in the wiki
(docs.langbot.app -> Installation -> Kubernetes). Remove the in-repo
docker/README_K8S.md, repoint the README language variants and the
docker-compose / kubernetes.yaml header comments to the wiki, and keep
kubernetes.yaml self-describing via inline comments.
2026-06-07 11:36:39 -04:00
RockChinQ
5c3a619e2d docs(docker): add Box sandbox runtime to k8s manifest and deploy guide
The k8s manifest was missing the Box runtime that backs the sandbox
tools, the activate skill tool, skill add/edit and stdio MCP. Add a
langbot-box Deployment/Service (port 5410), wire langbot to it via
BOX__RUNTIME__ENDPOINT (explicit Service name since the in-container
default langbot_box uses an underscore, invalid for k8s DNS), and share
the Box workspace root as a node hostPath pinned via podAffinity so the
node Docker daemon resolves bind-mount paths consistently. Document the
component, the shared-FS constraint, security implications and readiness
checks in README_K8S.md (zh + en).
2026-06-07 11:18:27 -04:00
RockChinQ
e223edeb45 docs(agents): add --standalone-box flag and box config keys 2026-06-07 08:57:43 -04:00
RockChinQ
d2c3146334 docs(agents): refresh AGENTS.md for current architecture and runtime/box debugging 2026-06-07 08:43:30 -04:00
Haoxuan Xing
7d9c8e3065 Merge pull request #2231 from langbot-app/TyperBody-patch-1
Update key capabilities in README.md
2026-06-07 13:08:19 +08:00
Haoxuan Xing
f12ed81e1e Update key capabilities in README.md
Added links to Deerflow and Weknora in the capabilities section.
2026-06-07 13:05:46 +08:00
Haoxuan Xing
6d4d19b6d7 Merge pull request #2230 from langbot-app/feat/addweknoradeerflow
Add DeerFlow LangGraph API as a Provider Runner
2026-06-07 12:22:55 +08:00
Typer_Body
07b90f12a2 ruff3 2026-06-07 02:38:05 +08:00
Typer_Body
fd896c6974 ruff2 2026-06-07 02:35:10 +08:00
Typer_Body
1fbfa868fb ruff 2026-06-07 02:31:42 +08:00
Typer_Body
ad05819c2e readme 2026-06-07 02:26:25 +08:00
Typer_Body
0c6f71738c deerflow 2026-06-07 02:17:40 +08:00
Typer_Body
af451e7006 weknora2 2026-06-07 01:14:02 +08:00
Typer_Body
59f20bcc73 weknora 2026-06-07 01:08:39 +08:00
RockChinQ
7eca3cdfca feat(web): show sub-entity name in document title on detail pages
Detail pages (plugin / MCP / pipeline / knowledge base / skill) only showed
the type in the tab title. Drive the /home document title from HomeLayout,
which has the selected entity name via context: '<entity> · <type> · LangBot'
when a sub-entity is open, '<type> · LangBot' otherwise. The top-level hook
now skips /home and only handles login/register/reset-password/wizard.
Type label falls back to a route-derived i18n key on direct page loads.
2026-06-06 12:12:08 -04:00
RockChinQ
c40354f838 feat(web): dynamic document title per route
The browser tab title was hard-coded to 'LangBot' in index.html and never
changed. Add a useDocumentTitle hook that maps the active route to an
existing i18n key and sets document.title to '<page> · LangBot', driven by
a new top-level RootLayout route element. Re-runs on navigation and on
language change so the title stays localized. Falls back to the bare app
name for unmapped routes.
2026-06-06 12:07:41 -04:00
RockChinQ
21a5b4658a fix(plugin-market): keep fixed card width regardless of result count
The result grid used auto-fit tracks, so a single search result stretched
to fill the whole row. Switch to fixed responsive column counts (1/2/3/4
across breakpoints), matching langbot-space, so cards keep a consistent
max width no matter how many results are shown.
2026-06-06 11:40:02 -04:00
RockChinQ
073acaa053 feat(plugin-market): move extension count into search box placeholder
Mirror the langbot-space marketplace change: drop the '共 xxx 个扩展'
stats line below the tag filter, surface the count in the search
placeholder ('搜索 xxx 个扩展、能力或场景...') when no query is active,
and show the total at the bottom via allLoadedCount when searching.
Adds searchPlaceholderCount + allLoadedCount to all 8 locales.
2026-06-06 11:33:46 -04:00
RockChinQ
38759b229d feat(plugin-market): show per-format extension counts in type filter
Mirror the LangBot Space marketplace: the advanced-filter type options
(plugin / MCP / skill) now display their live extension count, e.g.
"插件 (74)". Counts are fetched on mount via three lightweight
searchMarketplaceExtensions calls (page_size=1) reading total per type.
The all-formats option intentionally shows no count.
2026-06-06 08:11:59 -04:00
RockChinQ
efe32e34ae fix(deps): patch Dependabot vulnerability alerts (Python + web)
Python (pyproject.toml + uv.lock):
- aiohttp 3.13.5->3.14.0, langchain-core 1.3.2->1.4.1, langsmith 0.7.36->0.8.9,
  lxml 6.0.2->6.1.1, Mako 1.3.11->1.3.12, PyJWT 2.11.0->2.13.0,
  python-multipart 0.0.26->0.0.32, urllib3 2.6.3->2.7.0, Pygments 2.19.2->2.20.0,
  idna 3.11->3.18, pip 26.0->26.1.2, python-dotenv 1.2.1->1.2.2,
  requests 2.32.5->2.34.2, starlette 0.52.1->1.2.1, uv 0.11.7->0.11.19

web (package.json + both lockfiles):
- axios ->1.17.0, postcss ->8.5.15, react-router(-dom) ->7.17.0 (direct)
- overrides for transitive: flatted >=3.4.2, follow-redirects >=1.16.0,
  minimatch (3.1.3 / 9.0.7), picomatch (2.3.2 / 4.0.4)
- regenerated both package-lock.json and pnpm-lock.yaml in sync

Verified: uv sync + core imports OK; pnpm --frozen-lockfile + tsc + vite build pass.

Not fixable (no upstream patch yet, tracked separately):
- chromadb (critical, <=1.5.9 is latest) — awaiting upstream release
- PyPDF2 (medium, deprecated; needs migration to pypdf, code change)
2026-06-06 06:06:59 -04:00
Junyan Chin
46db4de11a Update QQ Group link in README_CN.md 2026-06-06 17:20:19 +08:00
RockChinQ
170a6756f4 fix(add-extension): load real icon in install confirm dialog from URL params
When the install confirm dialog is opened via URL query params (e.g. from a
marketplace deep link), installInfo carried no icon, so the icon fell back to
the /resources/icon endpoint which 404s for extensions whose icon is an
external URL (simpleicons / iconify), showing a Package placeholder.

Fetch the icon from the marketplace detail API (mcp/skill/plugin) after opening
the dialog and inject it into installInfo, and reset the icon-failed state when
the resolved URL changes so the <img> retries instead of sticking on the
placeholder.
2026-06-06 04:45:46 -04:00
RockChinQ
7330732f62 fix(ci): bump migration head assertion to 0004, apply prettier
- Update test_migrations / test_migrations_postgres head assertion from
  0003 to 0004 after adding the mcp readme migration.
- Reformat MCPForm.tsx / MCPReadme.tsx to satisfy prettier/prettier.
2026-06-06 03:56:14 -04:00
RockChinQ
b08e5ca09a feat(mcp): add Docs/Tools tablist on detail page, tidy sidebar label
Wrap the MCP detail right panel in a compact left-aligned Docs/Tools
tablist (Docs first). Move the tool count into the Tools tab label and
drop the redundant panel title/subtitle; connecting/failed states still
render the status component. Shorten the sidebar 'Installed Extensions'
entry to 'Installed' across all 8 locales, and add tabTools/tabDocs/
noReadme strings.
2026-06-06 03:52:17 -04:00
RockChinQ
dff80a0c0a fix(marketplace): use external icon URL when icon field is absolute
Many MCP / skill records store their icon as an absolute external URL
(simpleicons.org / iconify.design) rather than an uploaded file, so the
/resources/icon endpoint 404s and the card icon breaks. Add
resolveMarketplaceIconURL() which prefers an absolute http(s) icon field
and otherwise falls back to the resources endpoint.
2026-06-06 03:52:09 -04:00
RockChinQ
f54ae4b91c feat(mcp): persist and display marketplace README
Capture the README markdown from LangBot Space when installing an MCP
server and store it on the mcp_servers record (new readme column +
alembic migration 0004). The detail page can then render docs offline,
independent of the server's runtime/connection state.
2026-06-06 03:52:00 -04:00
RockChinQ
e5b3cced1f feat(market): show 24 plugins per page 2026-06-05 11:33:02 -04:00
Junyan Qin
101e04db6d feat(web): add Discord link to sidebar account menu
Add a "Join our Discord" entry to the account dropdown's external-links
group, opening https://discord.gg/wdNEHETs87 in a new tab. lucide-react
has no Discord brand glyph, so include a small inline Discord SVG icon
(brand color). Add the joinDiscord label to all 8 locales.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-04 22:26:55 +08:00
Junyan Qin
b79edda3a7 style(web): give extension cards a subtle border
The softened shadow alone left cards with no visible edge against the
page background. Add `border border-border` so each card has a clear,
restrained boundary while keeping the gentle shadow.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-04 21:49:55 +08:00
Junyan Qin
a20d3d11e5 style(web): soften extension card shadow and hover effect
Reduce the marketplace card box-shadow (4px/0.2 -> 2px/0.06) and the
hover shadow (8px/0.15 -> 5px/0.08, dark proportional) for a more
restrained, understated look.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-04 21:45:35 +08:00
Junyan Qin
3b4c455813 fix(web): distinct extension-format icons (plugin/mcp/skill)
The format filter used Wrench/AudioWaveform/Book for plugin/mcp/skill,
which collided with the plugin-component icons (Tool/EventListener/
KnowledgeEngine) shown right below. Switch formats to Puzzle/Server/
Sparkles — matching the canonical getTypeIcon used by the detail badges
— across the market filter, installed filter, install-queue map and
install-progress dialog.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-04 21:34:23 +08:00
Junyan Qin
c967a2aa82 i18n(market): say "extensions" not "plugins" in the marketplace count
The marketplace now lists plugins, MCPs and skills, so the item count
("Total N plugins") read wrong. Update market.totalPlugins and
market.searchResults to "extensions" across all 8 locales.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-04 21:24:10 +08:00
Junyan Qin
79cc6da96f fix(mcp): surface real cause from TaskGroup ExceptionGroups
MCP connection failures were reported as "unhandled errors in a
TaskGroup (1 sub-exception)" because anyio/the MCP client wrap the real
error in an ExceptionGroup and we interpolated its str() directly. Add
_describe_exception() to recurse into ExceptionGroups and surface the
leaf cause (e.g. "httpx.HTTPStatusError: Client error '410 Gone'") in
both the retry warning and the final error_message.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-04 21:19:18 +08:00
65 changed files with 5290 additions and 1308 deletions

145
AGENTS.md
View File

@@ -1,81 +1,134 @@
# AGENTS.md
This file is for guiding code agents (like Claude Code, GitHub Copilot, OpenAI Codex, etc.) to work in LangBot project.
This file guides code agents (Claude Code, GitHub Copilot, OpenAI Codex, etc.) working in the LangBot project. `CLAUDE.md` is a symlink to this file.
## Project Overview
LangBot is a open-source LLM native instant messaging bot development platform, aiming to provide an out-of-the-box IM robot development experience, with Agent, RAG, MCP and other LLM application functions, supporting global instant messaging platforms, and providing rich API interfaces, supporting custom development.
LangBot is an open-source, LLM-native instant-messaging bot development platform. It aims to provide an out-of-the-box IM bot development experience with Agent, RAG, MCP and other LLM application capabilities, supporting mainstream global IM platforms and exposing rich APIs for custom development.
LangBot has a comprehensive frontend, all operations can be performed through the frontend. The project splited into these major parts:
LangBot has a comprehensive web frontend almost every operation can be performed through it.
- `./src/langbot`: The main python package of the project, below are the main modules in this package:
- `./pkg`: The core python package of the project backend.
- `./pkg/platform`: The platform module of the project, containing the logic of message platform adapters, bot managers, message session managers, etc.
- `./pkg/provider`: The provider module of the project, containing the logic of LLM providers, tool providers, etc.
- `./pkg/pipeline`: The pipeline module of the project, containing the logic of pipelines, stages, query pool, etc.
- `./pkg/api`: The api module of the project, containing the http api controllers and services.
- `./pkg/plugin`: LangBot bridge for connecting with plugin system.
- `./libs`: Some SDKs we previously developed for the project, such as `qq_official_api`, `wecom_api`, etc.
- `./templates`: Templates of config files, components, etc.
- `./web`: Frontend codebase, built with Next.js + **shadcn** + **Tailwind CSS**.
- `./docker`: docker-compose deployment files.
- **Python**: `>=3.11,<4.0`, dependencies managed by `uv`. Package version is in `pyproject.toml`.
- **Frontend**: `web/` is a **Vite + React Router 7 + shadcn/ui + Tailwind CSS** SPA, managed by `pnpm`. (Note: this is NOT Next.js — the `dev` script is `vite`.)
- **Backend framework**: Quart (the async flavour of Flask). The HTTP API and the pre-built web UI are both served by the backend on `http://127.0.0.1:5300`.
## Backend Development
## Repository Layout
We use `uv` to manage dependencies.
```
LangBot/
├── main.py # Entrypoint shim -> langbot.__main__.main()
├── pyproject.toml # Python project + deps (uv), pins langbot-plugin==<x.y.z>
├── src/langbot/
│ ├── __main__.py # Real entrypoint, CLI args (--standalone-runtime, --standalone-box, --debug)
│ ├── pkg/ # Core backend package
│ │ ├── api/ # HTTP API controllers + services (Quart)
│ │ ├── core/ # App bootstrap, stages, task manager
│ │ ├── platform/ # IM platform adapters, bot managers, session managers
│ │ ├── provider/ # LLM providers, requesters, tool providers
│ │ ├── pipeline/ # Pipelines, stages, query pool
│ │ ├── plugin/ # Bridge connecting LangBot to the plugin runtime (see below)
│ │ ├── box/ # Code-sandbox subsystem (Docker / nsjail / E2B backends)
│ │ ├── skill/ # Skill subsystem
│ │ ├── rag/ , vector/ # RAG + vector store
│ │ ├── command/ # Built-in commands
│ │ ├── persistence/ # ORM models + Alembic migrations (SQLite & PostgreSQL)
│ │ ├── storage/ # Object/file storage abstractions
│ │ ├── config/, entity/, discover/, utils/, telemetry/, survey/
│ ├── libs/ # Vendored SDKs (qq_official_api, wecom_api, etc.)
│ └── templates/ # Config/component templates (e.g. templates/config.yaml)
├── web/ # Frontend SPA (Vite + React Router 7 + shadcn + Tailwind)
└── docker/ # docker-compose deployment files
```
## Development Environment Setup
Full guide lives in the wiki: **["开发配置" / Dev Config](https://docs.langbot.app/zh/develop/dev-config)**. Summary:
### Backend
```bash
pip install uv
uv sync --dev
uv sync --dev # uv creates a .venv/ for you; point your editor's interpreter at it
uv run main.py # serves API + web UI on http://127.0.0.1:5300
```
Start the backend and run the project in development mode.
On first run the config file is generated at `data/config.yaml`. DB is SQLite by default (zero setup); PostgreSQL is supported. Migrations run automatically on startup.
```bash
uv run main.py
```
### Frontend
Then you can access the project at `http://127.0.0.1:5300`.
## Frontend Development
We use `pnpm` to manage dependencies.
Requires Node.js + [pnpm](https://pnpm.io/installation).
```bash
cd web
cp .env.example .env
cp .env.example .env # Windows: copy .env.example .env
pnpm install
pnpm dev
pnpm dev # http://127.0.0.1:3000 (npm install / npm run dev also work)
```
Then you can access the project at `http://127.0.0.1:3000`.
`pnpm dev` reads `VITE_API_BASE_URL` from `web/.env` so the dev frontend can reach the backend on port `5300`. In production the frontend is pre-built into static files served by the backend on the same origin.
## Plugin System Architecture
### Code formatting
LangBot is composed of various internal components such as Large Language Model tools, commands, messaging platform adapters, LLM requesters, and more. To meet extensibility and flexibility requirements, we have implemented a production-grade plugin system.
The repo runs lint + format checks in CI. Install the pre-commit hooks so the same checks run locally before each commit:
Each plugin runs in an independent process, managed uniformly by the Plugin Runtime. It has two operating modes: `stdio` and `websocket`. When LangBot is started directly by users (not running in a container), it uses `stdio` mode, which is common for personal users or lightweight environments. When LangBot runs in a container, it uses `websocket` mode, designed specifically for production environments.
```bash
uv run pre-commit install
```
Plugin Runtime automatically starts each installed plugin and interacts through stdio. In plugin development scenarios, developers can use the lbp command-line tool to start plugins and connect to the running Runtime via WebSocket for debugging.
## Plugin System
> Plugin SDK, CLI, Runtime, and entities definitions shared between LangBot and plugins are contained in the [`langbot-plugin-sdk`](https://github.com/langbot-app/langbot-plugin-sdk) repository.
LangBot's plugin system (Plugin SDK, CLI `lbp`, Plugin Runtime, and the shared entity/API definitions) lives in a **separate repository**: [`langbot-plugin-sdk`](https://github.com/langbot-app/langbot-plugin-sdk). LangBot depends on it via the pinned `langbot-plugin` package in `pyproject.toml`.
## Some Development Tips and Standards
### Architecture (what to know inside this repo)
- LangBot is a global project, any comments in code should be in English, and user experience should be considered in all aspects.
- Thus you should consider the i18n support in all aspects.
- LangBot is widely adopted in both toC and toB scenarios, so you should consider the compatibility and security in all aspects.
- If you were asked to make a commit, please follow the commit message format:
- format: <type>(<scope>): <subject>
- type: must be a specific type, such as feat (new feature), fix (bug fix), docs (documentation), style (code style), refactor (refactoring), perf (performance optimization), etc.
- scope: the scope of the commit, such as the package name, the file name, the function name, the class name, the module name, etc.
- subject: the subject of the commit, such as the description of the commit, the reason for the commit, the impact of the commit, etc.
- LangBot uses [Alembic](https://alembic.sqlalchemy.org/) to manage database migrations, supporting both SQLite and PostgreSQL. Migration files are located in `src/langbot/pkg/persistence/alembic/versions/`. If you changed the definition of database entities (ORM models), generate a new migration script by running `uv run python -m langbot.pkg.persistence.alembic_runner autogenerate "description of your change"` in the project root (requires `data/config.yaml` to exist). Review and edit the generated script before committing. Migrations are executed automatically on LangBot startup. For data migrations (e.g. modifying JSON field content), you need to manually add the migration code in the generated script.
- Plugins run as independent processes managed by the **Plugin Runtime**. The Runtime supports two control transports: `stdio` and `websocket`.
- When LangBot is started directly by a user (not in a container), it spawns and connects to the Runtime over **stdio** (lightweight/personal use).
- When LangBot runs in a container, it connects to a standalone Runtime over **WebSocket** (production).
- The bridge code lives in `src/langbot/pkg/plugin/` (`connector.py`, `handler.py`).
- Relevant config (`data/config.yaml`): `plugin.runtime_ws_url` (e.g. `ws://langbot_plugin_runtime:5400/control/ws`). Start LangBot with `--standalone-runtime` to make it connect to an externally-launched Runtime over WebSocket instead of spawning one over stdio.
### Debugging the Plugin Runtime / CLI / SDK
This is documented in detail in the **SDK repo's `AGENTS.md`** and in the wiki page **["调试插件运行时、CLI、SDK" / Plugin Runtime](https://docs.langbot.app/zh/develop/plugin-runtime)**. The short version:
- Clone `LangBot` and `langbot-plugin-sdk` as siblings under one parent dir so the editor resolves shared entities.
- Start a standalone Runtime from the SDK repo: `uv run --no-sync lbp rt` (control port `5400`, debug port `5401`).
- To make LangBot use a locally-modified SDK: from the SDK dir, with LangBot's `.venv` active, run `uv pip install .`, then launch LangBot with `uv run --no-sync main.py --standalone-runtime` (keep `--no-sync` so your local SDK isn't overwritten).
### Debugging the Box (sandbox) runtime
The Box subsystem (`src/langbot/pkg/box/`) is the code sandbox. It picks the first available backend among **Docker / nsjail / E2B**. The standalone Box runtime is launched via the SDK CLI: `lbp box`. Backend selection details, the `lbp box` flags, and the SDK-side architecture are documented in the SDK repo's `AGENTS.md`.
Relevant config (`data/config.yaml`, `box:` section): `box.enabled` (master switch — disabling it also disables the native sandbox tools, skill add/edit, and stdio-mode MCP servers), `box.backend` (`'local'` = Docker/nsjail auto-pick, or `'docker'` / `'nsjail'` / `'e2b'`; also settable via `BOX__BACKEND`), and `box.runtime.endpoint` (external Box runtime base URL, e.g. `ws://127.0.0.1:5410`; empty = local auto-managed runtime). Like the plugin runtime, LangBot can connect to an externally-launched Box runtime by setting that endpoint and starting with `--standalone-box`.
> A common false "No supported sandbox backend (Docker / nsjail / E2B) is available" comes from Docker being installed and running but the current user not being in the `docker` group → `docker info` gets `permission denied` on the socket. Fix: `sudo usermod -aG docker <user>` and restart the backend in a shell that has the new group.
## Development Standards
- LangBot is a global project: **all code comments and docstrings must be in English**, and every user-facing string must support **i18n** (`en_US` + `zh_Hans` at minimum, plus `ja_JP` where the repo already has it).
- LangBot is adopted in both toC and toB scenarios — always consider compatibility and security.
- **Commit message format**: `<type>(<scope>): <subject>`
- `type`: one of `feat`, `fix`, `docs`, `style`, `refactor`, `perf`, `test`, `chore`, etc.
- `scope`: the affected package/module/file/class.
- `subject`: concise description of the change.
### Database migrations (Alembic)
LangBot uses [Alembic](https://alembic.sqlalchemy.org/) for migrations, supporting both SQLite and PostgreSQL from a single set of scripts. Migration files live in `src/langbot/pkg/persistence/alembic/versions/`.
If you change ORM model definitions, generate a migration:
```bash
# Run from the project root (requires data/config.yaml to exist)
uv run python -m langbot.pkg.persistence.alembic_runner autogenerate "description of your change"
```
Review and edit the generated script before committing. Migrations execute automatically on startup. `autogenerate` detects schema changes (add/drop columns, tables, type changes) but **data migrations** (e.g. mutating JSON field contents) must be hand-written into the generated script. `env.py` sets `render_as_batch=True`, so SQLite's ALTER TABLE limits are handled automatically — no need to branch per database. More in the wiki ["开发配置"](https://docs.langbot.app/zh/develop/dev-config#数据库迁移).
## Some Principles
- Keep it simple, stupid.
- Entities should not be multiplied unnecessarily
- Entities should not be multiplied unnecessarily.
- 八荣八耻
以瞎猜接口为耻,以认真查询为荣。
@@ -85,4 +138,4 @@ Plugin Runtime automatically starts each installed plugin and interacts through
以跳过验证为耻,以主动测试为荣。
以破坏架构为耻,以遵循规范为荣。
以假装理解为耻,以诚实无知为荣。
以盲目修改为耻,以谨慎重构为荣。
以盲目修改为耻,以谨慎重构为荣。

View File

@@ -38,7 +38,7 @@ LangBot is an **open-source, production-grade platform** for building AI-powered
### Key Capabilities
- **AI Conversations & Agents** — Multi-turn dialogues, tool calling, multi-modal support, streaming output. Built-in RAG (knowledge base) with deep integration to [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
- **AI Conversations & Agents** — Multi-turn dialogues, tool calling, multi-modal support, streaming output. Built-in RAG (knowledge base) with deep integration to [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org), [Deerflow](https://deerflow.tech), [Weknora](https://weknora.weixin.qq.com).
- **Universal IM Platform Support** — One codebase for Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
- **Production-Ready** — Access control, rate limiting, sensitive word filtering, comprehensive monitoring, and exception handling. Trusted by enterprises.
- **Plugin Ecosystem** — Hundreds of plugins, event-driven architecture, component extensions, and [MCP protocol](https://modelcontextprotocol.io/) support.
@@ -78,7 +78,7 @@ docker compose up -d
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**More options:** [Docker](https://link.langbot.app/en/docs/docker) · [Manual](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
**More options:** [Docker](https://link.langbot.app/en/docs/docker) · [Manual](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](https://docs.langbot.app/en/deploy/langbot/kubernetes)
---

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@@ -13,7 +13,7 @@
[English](README.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-1030838208-blue)](https://qm.qq.com/q/DxZZcNxM1W)
[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-1030838208-blue)](https://qm.qq.com/q/IrlV8QFacU)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
@@ -38,7 +38,7 @@ LangBot 是一个**开源的生产级平台**,用于构建 AI 驱动的即时
### 核心能力
- **AI 对话与 Agent** — 多轮对话、工具调用、多模态、流式输出。自带 RAG知识库深度集成 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
- **AI 对话与 Agent** — 多轮对话、工具调用、多模态、流式输出。自带 RAG知识库深度集成 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)、[Deerflow](https://deerflow.tech)、[Weknora](https://weknora.weixin.qq.com)等 LLMOps 平台。
- **全平台支持** — 一套代码,覆盖 QQ、微信、企业微信、飞书、钉钉、Discord、Telegram、Slack、LINE、KOOK 等平台。
- **生产就绪** — 访问控制、限速、敏感词过滤、全面监控与异常处理,已被多家企业采用。
- **插件生态** — 数百个插件,跨进程的事件驱动架构,组件扩展,适配 [MCP 协议](https://modelcontextprotocol.io/)。
@@ -78,7 +78,7 @@ docker compose up -d
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**更多方式:** [Docker](https://link.langbot.app/zh/docs/docker) · [手动部署](https://link.langbot.app/zh/docs/manual-deploy) · [宝塔面板](https://link.langbot.app/zh/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
**更多方式:** [Docker](https://link.langbot.app/zh/docs/docker) · [手动部署](https://link.langbot.app/zh/docs/manual-deploy) · [宝塔面板](https://link.langbot.app/zh/docs/bt-panel) · [Kubernetes](https://docs.langbot.app/zh/deploy/langbot/kubernetes)
---

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@@ -37,7 +37,7 @@ LangBot es una **plataforma de código abierto y grado de producción** para con
### Capacidades Clave
- **Conversaciones e Agentes IA** — Diálogos de múltiples turnos, llamadas a herramientas, soporte multimodal, salida en streaming. RAG (base de conocimientos) incorporado con integración profunda con [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
- **Conversaciones e Agentes IA** — Diálogos de múltiples turnos, llamadas a herramientas, soporte multimodal, salida en streaming. RAG (base de conocimientos) incorporado con integración profunda con [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org), [Deerflow](https://deerflow.tech)、[Weknora](https://weknora.weixin.qq.com).
- **Soporte Universal de Plataformas de MI** — Un solo código base para Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
- **Listo para Producción** — Control de acceso, limitación de velocidad, filtrado de palabras sensibles, monitoreo completo y manejo de excepciones. De confianza para empresas.
- **Ecosistema de Plugins** — Cientos de plugins, arquitectura basada en eventos, extensiones de componentes y soporte del [protocolo MCP](https://modelcontextprotocol.io/).
@@ -77,7 +77,7 @@ docker compose up -d
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**Más opciones:** [Docker](https://link.langbot.app/en/docs/docker) · [Manual](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
**Más opciones:** [Docker](https://link.langbot.app/en/docs/docker) · [Manual](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](https://docs.langbot.app/en/deploy/langbot/kubernetes)
---

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@@ -37,7 +37,7 @@ LangBot est une **plateforme open-source de niveau production** pour créer des
### Capacités Clés
- **Conversations IA & Agents** — Dialogues multi-tours, appels d'outils, support multimodal, sortie en streaming. RAG (base de connaissances) intégré avec intégration profonde de [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
- **Conversations IA & Agents** — Dialogues multi-tours, appels d'outils, support multimodal, sortie en streaming. RAG (base de connaissances) intégré avec intégration profonde de [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org), [Deerflow](https://deerflow.tech), [Weknora](https://weknora.weixin.qq.com).
- **Support Universel des Plateformes de MI** — Un seul code pour Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
- **Prêt pour la Production** — Contrôle d'accès, limitation de débit, filtrage de mots sensibles, surveillance complète et gestion des exceptions. Approuvé par les entreprises.
- **Écosystème de Plugins** — Des centaines de plugins, architecture événementielle, extensions de composants, et support du [protocole MCP](https://modelcontextprotocol.io/).
@@ -77,7 +77,7 @@ docker compose up -d
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**Plus d'options :** [Docker](https://link.langbot.app/en/docs/docker) · [Manuel](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
**Plus d'options :** [Docker](https://link.langbot.app/en/docs/docker) · [Manuel](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](https://docs.langbot.app/en/deploy/langbot/kubernetes)
---

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@@ -37,7 +37,7 @@ LangBot は、AI搭載のインスタントメッセージングボットを構
### 主な機能
- **AI対話とエージェント** — マルチターン対話、ツール呼び出し、マルチモーダル対応、ストリーミング出力。RAGナレッジベースを内蔵し、[Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) と深く統合。
- **AI対話とエージェント** — マルチターン対話、ツール呼び出し、マルチモーダル対応、ストリーミング出力。RAGナレッジベースを内蔵し、[Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)、[Deerflow](https://deerflow.tech)、[Weknora](https://weknora.weixin.qq.com) と深く統合。
- **ユニバーサルIMプラットフォーム対応** — 単一のコードベースで Discord、Telegram、Slack、LINE、QQ、WeChat、WeCom、Lark、DingTalk、KOOK に対応。
- **本番環境対応** — アクセス制御、レート制限、センシティブワードフィルタリング、包括的な監視、例外処理を搭載。エンタープライズの信頼に応える品質。
- **プラグインエコシステム** — 数百のプラグイン、イベント駆動アーキテクチャ、コンポーネント拡張、[MCPプロトコル](https://modelcontextprotocol.io/)対応。
@@ -77,7 +77,7 @@ docker compose up -d
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**その他:** [Docker](https://link.langbot.app/en/docs/docker) · [手動デプロイ](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
**その他:** [Docker](https://link.langbot.app/en/docs/docker) · [手動デプロイ](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](https://docs.langbot.app/en/deploy/langbot/kubernetes)
---

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@@ -37,7 +37,7 @@ LangBot은 AI 기반 인스턴트 메시징 봇을 구축하기 위한 **오픈
### 핵심 기능
- **AI 대화 및 에이전트** — 멀티턴 대화, 도구 호출, 멀티모달 지원, 스트리밍 출력. 내장 RAG(지식 베이스)와 [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) 심층 통합.
- **AI 대화 및 에이전트** — 멀티턴 대화, 도구 호출, 멀티모달 지원, 스트리밍 출력. 내장 RAG(지식 베이스)와 [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org), [Deerflow](https://deerflow.tech), [Weknora](https://weknora.weixin.qq.com) 심층 통합.
- **유니버설 IM 플랫폼 지원** — 단일 코드베이스로 Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK 지원.
- **프로덕션 레디** — 접근 제어, 속도 제한, 민감어 필터링, 종합 모니터링 및 예외 처리. 기업 환경에서 검증됨.
- **플러그인 생태계** — 수백 개의 플러그인, 이벤트 기반 아키텍처, 컴포넌트 확장, [MCP 프로토콜](https://modelcontextprotocol.io/) 지원.
@@ -77,7 +77,7 @@ docker compose up -d
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**더 많은 옵션:** [Docker](https://link.langbot.app/en/docs/docker) · [수동 배포](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
**더 많은 옵션:** [Docker](https://link.langbot.app/en/docs/docker) · [수동 배포](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](https://docs.langbot.app/en/deploy/langbot/kubernetes)
---

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@@ -37,7 +37,7 @@ LangBot — это **платформа с открытым исходным к
### Ключевые возможности
- **ИИ-диалоги и агенты** — Многораундовые диалоги, вызов инструментов, мультимодальная поддержка, потоковый вывод. Встроенная реализация RAG (база знаний) с глубокой интеграцией в [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
- **ИИ-диалоги и агенты** — Многораундовые диалоги, вызов инструментов, мультимодальная поддержка, потоковый вывод. Встроенная реализация RAG (база знаний) с глубокой интеграцией в [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org), [Deerflow](https://deerflow.tech), [Weknora](https://weknora.weixin.qq.com).
- **Универсальная поддержка IM-платформ** — Единая кодовая база для Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
- **Готовность к продакшену** — Контроль доступа, ограничение скорости, фильтрация чувствительных слов, комплексный мониторинг и обработка исключений. Проверено в корпоративной среде.
- **Экосистема плагинов** — Сотни плагинов, событийно-ориентированная архитектура, расширения компонентов и поддержка [протокола MCP](https://modelcontextprotocol.io/).
@@ -77,7 +77,7 @@ docker compose up -d
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**Другие варианты:** [Docker](https://link.langbot.app/en/docs/docker) · [Ручная установка](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
**Другие варианты:** [Docker](https://link.langbot.app/en/docs/docker) · [Ручная установка](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](https://docs.langbot.app/en/deploy/langbot/kubernetes)
---

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@@ -39,7 +39,7 @@ LangBot 是一個**開源的生產級平台**,用於建構 AI 驅動的即時
### 核心能力
- **AI 對話與 Agent** — 多輪對話、工具調用、多模態、流式輸出。自帶 RAG知識庫深度整合 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
- **AI 對話與 Agent** — 多輪對話、工具調用、多模態、流式輸出。自帶 RAG知識庫深度整合 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)、 [Deerflow](https://deerflow.tech)、[Weknora](https://weknora.weixin.qq.com)等 LLMOps 平台。
- **全平台支援** — 一套程式碼,覆蓋 QQ、微信、企業微信、飛書、釘釘、Discord、Telegram、Slack、LINE、KOOK 等平台。
- **生產就緒** — 存取控制、限速、敏感詞過濾、全面監控與異常處理,已被多家企業採用。
- **外掛生態** — 數百個外掛,事件驅動架構,組件擴展,適配 [MCP 協議](https://modelcontextprotocol.io/)。
@@ -79,7 +79,7 @@ docker compose up -d
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**更多方式:** [Docker](https://link.langbot.app/zh/docs/docker) · [手動部署](https://link.langbot.app/zh/docs/manual-deploy) · [寶塔面板](https://link.langbot.app/zh/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
**更多方式:** [Docker](https://link.langbot.app/zh/docs/docker) · [手動部署](https://link.langbot.app/zh/docs/manual-deploy) · [寶塔面板](https://link.langbot.app/zh/docs/bt-panel) · [Kubernetes](https://docs.langbot.app/zh/deploy/langbot/kubernetes)
---

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@@ -37,7 +37,7 @@ LangBot là một **nền tảng mã nguồn mở, cấp sản xuất** để x
### Khả năng chính
- **Hội thoại AI & Agent** — Đối thoại nhiều lượt, gọi công cụ, hỗ trợ đa phương thức, đầu ra streaming. RAG (cơ sở kiến thức) tích hợp sẵn với tích hợp sâu vào [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
- **Hội thoại AI & Agent** — Đối thoại nhiều lượt, gọi công cụ, hỗ trợ đa phương thức, đầu ra streaming. RAG (cơ sở kiến thức) tích hợp sẵn với tích hợp sâu vào [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org), [Deerflow](https://deerflow.tech), [Weknora](https://weknora.weixin.qq.com).
- **Hỗ trợ đa nền tảng IM** — Một mã nguồn cho Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
- **Sẵn sàng cho sản xuất** — Kiểm soát truy cập, giới hạn tốc độ, lọc từ nhạy cảm, giám sát toàn diện và xử lý ngoại lệ. Được doanh nghiệp tin dùng.
- **Hệ sinh thái Plugin** — Hàng trăm plugin, kiến trúc hướng sự kiện, mở rộng thành phần, và hỗ trợ [giao thức MCP](https://modelcontextprotocol.io/).
@@ -77,7 +77,7 @@ docker compose up -d
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**Thêm tùy chọn:** [Docker](https://link.langbot.app/en/docs/docker) · [Thủ công](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
**Thêm tùy chọn:** [Docker](https://link.langbot.app/en/docs/docker) · [Thủ công](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](https://docs.langbot.app/en/deploy/langbot/kubernetes)
---

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@@ -1,629 +0,0 @@
# LangBot Kubernetes 部署指南 / Kubernetes Deployment Guide
[简体中文](#简体中文) | [English](#english)
---
## 简体中文
### 概述
本指南提供了在 Kubernetes 集群中部署 LangBot 的完整步骤。Kubernetes 部署配置基于 `docker-compose.yaml`,适用于生产环境的容器化部署。
### 前置要求
- Kubernetes 集群(版本 1.19+
- `kubectl` 命令行工具已配置并可访问集群
- 集群中有可用的存储类StorageClass用于持久化存储可选但推荐
- 至少 2 vCPU 和 4GB RAM 的可用资源
### 架构说明
Kubernetes 部署包含以下组件:
1. **langbot**: 主应用服务
- 提供 Web UI端口 5300
- 处理平台 webhook端口 2280-2290
- 数据持久化卷
2. **langbot-plugin-runtime**: 插件运行时服务
- WebSocket 通信(端口 5400
- 插件数据持久化卷
3. **持久化存储**:
- `langbot-data`: LangBot 主数据
- `langbot-plugins`: 插件文件
- `langbot-plugin-runtime-data`: 插件运行时数据
### 快速开始
#### 1. 下载部署文件
```bash
# 克隆仓库
git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
# 或直接下载 kubernetes.yaml
wget https://raw.githubusercontent.com/langbot-app/LangBot/main/docker/kubernetes.yaml
```
#### 2. 部署到 Kubernetes
```bash
# 应用所有配置
kubectl apply -f kubernetes.yaml
# 检查部署状态
kubectl get all -n langbot
# 查看 Pod 日志
kubectl logs -n langbot -l app=langbot -f
```
#### 3. 访问 LangBot
默认情况下LangBot 服务使用 ClusterIP 类型,只能在集群内部访问。您可以选择以下方式之一来访问:
**选项 A: 端口转发(推荐用于测试)**
```bash
kubectl port-forward -n langbot svc/langbot 5300:5300
```
然后访问 http://localhost:5300
**选项 B: NodePort适用于开发环境**
编辑 `kubernetes.yaml`,取消注释 NodePort Service 部分,然后:
```bash
kubectl apply -f kubernetes.yaml
# 获取节点 IP
kubectl get nodes -o wide
# 访问 http://<NODE_IP>:30300
```
**选项 C: LoadBalancer适用于云环境**
编辑 `kubernetes.yaml`,取消注释 LoadBalancer Service 部分,然后:
```bash
kubectl apply -f kubernetes.yaml
# 获取外部 IP
kubectl get svc -n langbot langbot-loadbalancer
# 访问 http://<EXTERNAL_IP>
```
**选项 D: Ingress推荐用于生产环境**
确保集群中已安装 Ingress Controller如 nginx-ingress然后
1. 编辑 `kubernetes.yaml` 中的 Ingress 配置
2. 修改域名为您的实际域名
3. 应用配置:
```bash
kubectl apply -f kubernetes.yaml
# 访问 http://langbot.yourdomain.com
```
### 配置说明
#### 环境变量
`ConfigMap` 中配置环境变量:
```yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: langbot-config
namespace: langbot
data:
TZ: "Asia/Shanghai" # 修改为您的时区
```
#### 存储配置
默认使用动态存储分配。如果您有特定的 StorageClass请在 PVC 中指定:
```yaml
spec:
storageClassName: your-storage-class-name
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 10Gi
```
#### 资源限制
根据您的需求调整资源限制:
```yaml
resources:
requests:
memory: "1Gi"
cpu: "500m"
limits:
memory: "4Gi"
cpu: "2000m"
```
### 常用操作
#### 查看日志
```bash
# 查看 LangBot 主服务日志
kubectl logs -n langbot -l app=langbot -f
# 查看插件运行时日志
kubectl logs -n langbot -l app=langbot-plugin-runtime -f
```
#### 重启服务
```bash
# 重启 LangBot
kubectl rollout restart deployment/langbot -n langbot
# 重启插件运行时
kubectl rollout restart deployment/langbot-plugin-runtime -n langbot
```
#### 更新镜像
```bash
# 更新到最新版本
kubectl set image deployment/langbot -n langbot langbot=rockchin/langbot:latest
kubectl set image deployment/langbot-plugin-runtime -n langbot langbot-plugin-runtime=rockchin/langbot:latest
# 检查更新状态
kubectl rollout status deployment/langbot -n langbot
```
#### 扩容(不推荐)
注意:由于 LangBot 使用 ReadWriteOnce 的持久化存储,不支持多副本扩容。如需高可用,请考虑使用 ReadWriteMany 存储或其他架构方案。
#### 备份数据
```bash
# 备份 PVC 数据
kubectl exec -n langbot -it <langbot-pod-name> -- tar czf /tmp/backup.tar.gz /app/data
kubectl cp langbot/<langbot-pod-name>:/tmp/backup.tar.gz ./backup.tar.gz
```
### 卸载
```bash
# 删除所有资源(保留 PVC
kubectl delete deployment,service,configmap -n langbot --all
# 删除 PVC会删除数据
kubectl delete pvc -n langbot --all
# 删除命名空间
kubectl delete namespace langbot
```
### 故障排查
#### Pod 无法启动
```bash
# 查看 Pod 状态
kubectl get pods -n langbot
# 查看详细信息
kubectl describe pod -n langbot <pod-name>
# 查看事件
kubectl get events -n langbot --sort-by='.lastTimestamp'
```
#### 存储问题
```bash
# 检查 PVC 状态
kubectl get pvc -n langbot
# 检查 PV
kubectl get pv
```
#### 网络访问问题
```bash
# 检查 Service
kubectl get svc -n langbot
# 检查端口转发
kubectl port-forward -n langbot svc/langbot 5300:5300
```
### 生产环境建议
1. **使用特定版本标签**:避免使用 `latest` 标签,使用具体版本号如 `rockchin/langbot:v1.0.0`
2. **配置资源限制**:根据实际负载调整 CPU 和内存限制
3. **使用 Ingress + TLS**:配置 HTTPS 访问和证书管理
4. **配置监控和告警**:集成 Prometheus、Grafana 等监控工具
5. **定期备份**:配置自动备份策略保护数据
6. **使用专用 StorageClass**:为生产环境配置高性能存储
7. **配置亲和性规则**:确保 Pod 调度到合适的节点
### 高级配置
#### 使用 Secrets 管理敏感信息
如果需要配置 API 密钥等敏感信息:
```yaml
apiVersion: v1
kind: Secret
metadata:
name: langbot-secrets
namespace: langbot
type: Opaque
data:
api_key: <base64-encoded-value>
```
然后在 Deployment 中引用:
```yaml
env:
- name: API_KEY
valueFrom:
secretKeyRef:
name: langbot-secrets
key: api_key
```
#### 配置水平自动扩缩容HPA
注意:需要确保使用 ReadWriteMany 存储类型
```yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: langbot-hpa
namespace: langbot
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: langbot
minReplicas: 1
maxReplicas: 3
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
```
### 参考资源
- [LangBot 官方文档](https://docs.langbot.app)
- [Docker 部署文档](https://link.langbot.app/zh/docs/docker)
- [Kubernetes 官方文档](https://kubernetes.io/docs/)
---
## English
### Overview
This guide provides complete steps for deploying LangBot in a Kubernetes cluster. The Kubernetes deployment configuration is based on `docker-compose.yaml` and is suitable for production containerized deployments.
### Prerequisites
- Kubernetes cluster (version 1.19+)
- `kubectl` command-line tool configured with cluster access
- Available StorageClass in the cluster for persistent storage (optional but recommended)
- At least 2 vCPU and 4GB RAM of available resources
### Architecture
The Kubernetes deployment includes the following components:
1. **langbot**: Main application service
- Provides Web UI (port 5300)
- Handles platform webhooks (ports 2280-2290)
- Data persistence volume
2. **langbot-plugin-runtime**: Plugin runtime service
- WebSocket communication (port 5400)
- Plugin data persistence volume
3. **Persistent Storage**:
- `langbot-data`: LangBot main data
- `langbot-plugins`: Plugin files
- `langbot-plugin-runtime-data`: Plugin runtime data
### Quick Start
#### 1. Download Deployment Files
```bash
# Clone repository
git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
# Or download kubernetes.yaml directly
wget https://raw.githubusercontent.com/langbot-app/LangBot/main/docker/kubernetes.yaml
```
#### 2. Deploy to Kubernetes
```bash
# Apply all configurations
kubectl apply -f kubernetes.yaml
# Check deployment status
kubectl get all -n langbot
# View Pod logs
kubectl logs -n langbot -l app=langbot -f
```
#### 3. Access LangBot
By default, LangBot service uses ClusterIP type, accessible only within the cluster. Choose one of the following methods to access:
**Option A: Port Forwarding (Recommended for testing)**
```bash
kubectl port-forward -n langbot svc/langbot 5300:5300
```
Then visit http://localhost:5300
**Option B: NodePort (Suitable for development)**
Edit `kubernetes.yaml`, uncomment the NodePort Service section, then:
```bash
kubectl apply -f kubernetes.yaml
# Get node IP
kubectl get nodes -o wide
# Visit http://<NODE_IP>:30300
```
**Option C: LoadBalancer (Suitable for cloud environments)**
Edit `kubernetes.yaml`, uncomment the LoadBalancer Service section, then:
```bash
kubectl apply -f kubernetes.yaml
# Get external IP
kubectl get svc -n langbot langbot-loadbalancer
# Visit http://<EXTERNAL_IP>
```
**Option D: Ingress (Recommended for production)**
Ensure an Ingress Controller (e.g., nginx-ingress) is installed in the cluster, then:
1. Edit the Ingress configuration in `kubernetes.yaml`
2. Change the domain to your actual domain
3. Apply configuration:
```bash
kubectl apply -f kubernetes.yaml
# Visit http://langbot.yourdomain.com
```
### Configuration
#### Environment Variables
Configure environment variables in ConfigMap:
```yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: langbot-config
namespace: langbot
data:
TZ: "Asia/Shanghai" # Change to your timezone
```
#### Storage Configuration
Uses dynamic storage provisioning by default. If you have a specific StorageClass, specify it in PVC:
```yaml
spec:
storageClassName: your-storage-class-name
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 10Gi
```
#### Resource Limits
Adjust resource limits based on your needs:
```yaml
resources:
requests:
memory: "1Gi"
cpu: "500m"
limits:
memory: "4Gi"
cpu: "2000m"
```
### Common Operations
#### View Logs
```bash
# View LangBot main service logs
kubectl logs -n langbot -l app=langbot -f
# View plugin runtime logs
kubectl logs -n langbot -l app=langbot-plugin-runtime -f
```
#### Restart Services
```bash
# Restart LangBot
kubectl rollout restart deployment/langbot -n langbot
# Restart plugin runtime
kubectl rollout restart deployment/langbot-plugin-runtime -n langbot
```
#### Update Images
```bash
# Update to latest version
kubectl set image deployment/langbot -n langbot langbot=rockchin/langbot:latest
kubectl set image deployment/langbot-plugin-runtime -n langbot langbot-plugin-runtime=rockchin/langbot:latest
# Check update status
kubectl rollout status deployment/langbot -n langbot
```
#### Scaling (Not Recommended)
Note: Due to LangBot using ReadWriteOnce persistent storage, multi-replica scaling is not supported. For high availability, consider using ReadWriteMany storage or alternative architectures.
#### Backup Data
```bash
# Backup PVC data
kubectl exec -n langbot -it <langbot-pod-name> -- tar czf /tmp/backup.tar.gz /app/data
kubectl cp langbot/<langbot-pod-name>:/tmp/backup.tar.gz ./backup.tar.gz
```
### Uninstall
```bash
# Delete all resources (keep PVCs)
kubectl delete deployment,service,configmap -n langbot --all
# Delete PVCs (will delete data)
kubectl delete pvc -n langbot --all
# Delete namespace
kubectl delete namespace langbot
```
### Troubleshooting
#### Pods Not Starting
```bash
# Check Pod status
kubectl get pods -n langbot
# View detailed information
kubectl describe pod -n langbot <pod-name>
# View events
kubectl get events -n langbot --sort-by='.lastTimestamp'
```
#### Storage Issues
```bash
# Check PVC status
kubectl get pvc -n langbot
# Check PV
kubectl get pv
```
#### Network Access Issues
```bash
# Check Service
kubectl get svc -n langbot
# Test port forwarding
kubectl port-forward -n langbot svc/langbot 5300:5300
```
### Production Recommendations
1. **Use specific version tags**: Avoid using `latest` tag, use specific version like `rockchin/langbot:v1.0.0`
2. **Configure resource limits**: Adjust CPU and memory limits based on actual load
3. **Use Ingress + TLS**: Configure HTTPS access and certificate management
4. **Configure monitoring and alerts**: Integrate monitoring tools like Prometheus, Grafana
5. **Regular backups**: Configure automated backup strategy to protect data
6. **Use dedicated StorageClass**: Configure high-performance storage for production
7. **Configure affinity rules**: Ensure Pods are scheduled to appropriate nodes
### Advanced Configuration
#### Using Secrets for Sensitive Information
If you need to configure sensitive information like API keys:
```yaml
apiVersion: v1
kind: Secret
metadata:
name: langbot-secrets
namespace: langbot
type: Opaque
data:
api_key: <base64-encoded-value>
```
Then reference in Deployment:
```yaml
env:
- name: API_KEY
valueFrom:
secretKeyRef:
name: langbot-secrets
key: api_key
```
#### Configure Horizontal Pod Autoscaling (HPA)
Note: Requires ReadWriteMany storage type
```yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: langbot-hpa
namespace: langbot
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: langbot
minReplicas: 1
maxReplicas: 3
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
```
### References
- [LangBot Official Documentation](https://docs.langbot.app)
- [Docker Deployment Guide](https://link.langbot.app/zh/docs/docker)
- [Kubernetes Official Documentation](https://kubernetes.io/docs/)

View File

@@ -1,5 +1,5 @@
# Docker Compose configuration for LangBot
# For Kubernetes deployment, see kubernetes.yaml and README_K8S.md
# For Kubernetes deployment, see kubernetes.yaml and the deployment guide at https://docs.langbot.app
version: "3"
services:

View File

@@ -1,6 +1,8 @@
# Kubernetes Deployment for LangBot
# This file provides Kubernetes deployment manifests for LangBot based on docker-compose.yaml
#
#
# Full deployment guide (zh/en/ja): https://docs.langbot.app -> Installation -> Kubernetes
#
# Usage:
# kubectl apply -f kubernetes.yaml
#
@@ -8,13 +10,15 @@
# - A Kubernetes cluster (1.19+)
# - kubectl configured to communicate with your cluster
# - (Optional) A StorageClass for dynamic volume provisioning
# - For the Box sandbox runtime: a node with a reachable Docker daemon
# (the box mounts the node's /var/run/docker.sock). See the deployment guide.
#
# Components:
# - Namespace: langbot
# - PersistentVolumeClaims for data persistence
# - Deployments for langbot and langbot_plugin_runtime
# - Deployments for langbot, langbot-plugin-runtime, and langbot-box (sandbox)
# - Services for network access
# - ConfigMap for timezone configuration
# - ConfigMap for timezone + runtime endpoints
---
# Namespace
@@ -83,6 +87,11 @@ metadata:
data:
TZ: "Asia/Shanghai"
PLUGIN__RUNTIME_WS_URL: "ws://langbot-plugin-runtime:5400/control/ws"
# Box sandbox runtime endpoint. LangBot connects to the Box runtime over
# WebSocket. The hostname MUST match the langbot-box Service name. Note the
# in-container default ("langbot_box") uses an underscore, which is an
# invalid Kubernetes DNS name — so the endpoint is always set explicitly here.
BOX__RUNTIME__ENDPOINT: "ws://langbot-box:5410"
---
# Deployment for LangBot Plugin Runtime
@@ -169,6 +178,136 @@ spec:
protocol: TCP
name: runtime
---
# Deployment for LangBot Box (sandbox) runtime
#
# The Box runtime backs LangBot's sandbox tools (exec / read / write / edit /
# glob / grep), the `activate` skill tool, skill add/edit, and stdio-mode MCP
# servers. It is OPTIONAL: if you do not deploy it, set `BOX__ENABLED=false` on
# the langbot Deployment (or `box.enabled: false` in config.yaml) so the
# dashboard renders cleanly with sandbox features disabled.
#
# IMPORTANT — how the sandbox actually runs:
# The bundled image ships only the Docker CLI (no dockerd, no nsjail). The Box
# runtime therefore creates sandbox containers by talking to a Docker daemon
# over the mounted socket (`/var/run/docker.sock`). Because that daemon
# resolves bind-mount paths on the NODE filesystem, the Box workspace root
# must be the SAME absolute path inside the box container, inside every
# sandbox container it spawns, AND on the node. That is why this manifest uses
# a hostPath at a fixed absolute path (/app/data/box) and pins langbot + box
# to the same node via podAffinity. A normal PVC will NOT work for the box
# workspace, because the node's dockerd cannot see paths that exist only
# inside the pod's mount namespace.
#
# Security note: mounting the host Docker socket grants the Box runtime (and any
# code executed in the sandbox) effective root on the node. Only deploy Box on
# nodes you trust for this workload, ideally a dedicated node pool. For a
# stronger isolation boundary, switch box.backend to 'e2b' (set E2B_API_KEY) and
# drop the docker.sock mount + hostPath entirely.
apiVersion: apps/v1
kind: Deployment
metadata:
name: langbot-box
namespace: langbot
labels:
app: langbot-box
spec:
replicas: 1
selector:
matchLabels:
app: langbot-box
template:
metadata:
labels:
app: langbot-box
spec:
# Pin to the same node as langbot so they share the hostPath box root.
affinity:
podAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
- labelSelector:
matchLabels:
app: langbot
topologyKey: kubernetes.io/hostname
containers:
- name: langbot-box
image: rockchin/langbot:latest
imagePullPolicy: Always
# Launched through the same CLI entry point as the plugin runtime.
# No flag => WebSocket control transport (default), listening on 5410.
command: ["uv", "run", "--no-sync", "-m", "langbot_plugin.cli.__init__", "box"]
ports:
- containerPort: 5410
name: box-rpc
protocol: TCP
env:
- name: TZ
valueFrom:
configMapKeyRef:
name: langbot-config
key: TZ
# The Box runtime does NOT read box.local.* / BOX__* from its own env;
# it receives its configuration from LangBot via the INIT RPC action.
# Do not add BOX__* here — they would be silently ignored.
volumeMounts:
# Box workspace root — identical path on node, box, and sandbox
# containers (see the IMPORTANT note above).
- name: box-root
mountPath: /app/data/box
# Host Docker socket — the sandbox backend uses it to create containers.
- name: docker-sock
mountPath: /var/run/docker.sock
resources:
requests:
memory: "256Mi"
cpu: "100m"
limits:
memory: "1Gi"
cpu: "1000m"
livenessProbe:
tcpSocket:
port: 5410
initialDelaySeconds: 20
periodSeconds: 10
timeoutSeconds: 5
failureThreshold: 3
readinessProbe:
tcpSocket:
port: 5410
initialDelaySeconds: 10
periodSeconds: 5
timeoutSeconds: 3
failureThreshold: 3
volumes:
- name: box-root
hostPath:
path: /app/data/box
type: DirectoryOrCreate
- name: docker-sock
hostPath:
path: /var/run/docker.sock
type: Socket
restartPolicy: Always
---
# Service for LangBot Box runtime
apiVersion: v1
kind: Service
metadata:
name: langbot-box
namespace: langbot
labels:
app: langbot-box
spec:
type: ClusterIP
selector:
app: langbot-box
ports:
- port: 5410
targetPort: 5410
protocol: TCP
name: box-rpc
---
# Deployment for LangBot
apiVersion: apps/v1
@@ -213,11 +352,36 @@ spec:
configMapKeyRef:
name: langbot-config
key: PLUGIN__RUNTIME_WS_URL
# Box (sandbox) runtime endpoint. Connects LangBot to the langbot-box
# Service over WebSocket. Remove this (and the langbot-box Deployment)
# and set BOX__ENABLED=false if you do not want the sandbox.
- name: BOX__RUNTIME__ENDPOINT
valueFrom:
configMapKeyRef:
name: langbot-config
key: BOX__RUNTIME__ENDPOINT
# box.local.* config — forwarded to the Box runtime via INIT RPC. The
# host_root MUST match the box-root hostPath mountPath below AND the box
# Deployment's box-root mountPath, so that skill package paths resolve
# identically on both sides and on the node's Docker daemon.
- name: BOX__LOCAL__HOST_ROOT
value: "/app/data/box"
- name: BOX__LOCAL__DEFAULT_WORKSPACE
value: "default"
- name: BOX__LOCAL__SKILLS_ROOT
value: "skills"
- name: BOX__LOCAL__ALLOWED_MOUNT_ROOTS
value: "/app/data/box"
volumeMounts:
- name: data
mountPath: /app/data
- name: plugins
mountPath: /app/plugins
# Same node-level box root as the langbot-box Deployment. Mounted over
# the data PVC's /app/data/box subpath so both LangBot and the Box
# runtime (and the node's dockerd) agree on one absolute path.
- name: box-root
mountPath: /app/data/box
resources:
requests:
memory: "1Gi"
@@ -250,6 +414,13 @@ spec:
- name: plugins
persistentVolumeClaim:
claimName: langbot-plugins
# Node-level box workspace root, shared with the langbot-box Deployment.
# hostPath (not PVC) because the node's Docker daemon must see the same
# absolute path when bind-mounting workspaces into sandbox containers.
- name: box-root
hostPath:
path: /app/data/box
type: DirectoryOrCreate
restartPolicy: Always
---

View File

@@ -8,7 +8,7 @@ requires-python = ">=3.11,<4.0"
dependencies = [
"aiocqhttp>=1.4.4",
"aiofiles>=24.1.0",
"aiohttp>=3.13.4",
"aiohttp>=3.14.0",
"aioshutil>=1.5",
"aiosqlite>=0.21.0",
"anthropic>=0.51.0",
@@ -31,27 +31,27 @@ dependencies = [
"psutil>=7.0.0",
"pycryptodome>=3.22.0",
"pydantic>2.0",
"pyjwt>=2.10.1",
"pyjwt>=2.12.0",
"python-telegram-bot>=22.0",
"pyyaml>=6.0.2",
"qq-botpy-rc>=1.2.1.6",
"qrcode>=7.4",
"quart>=0.20.0",
"quart-cors>=0.8.0",
"requests>=2.32.3",
"requests>=2.33.0",
"slack-sdk>=3.35.0",
"alembic>=1.15.0",
"sqlalchemy[asyncio]>=2.0.40",
"sqlmodel>=0.0.24",
"telegramify-markdown>=0.5.1",
"tiktoken>=0.9.0",
"urllib3>=2.4.0",
"urllib3>=2.7.0",
"websockets>=15.0.1",
"python-socks>=2.7.1", # dingtalk missing dependency
"pip>=25.1.1",
"pip>=26.1",
"ruff>=0.11.9",
"pre-commit>=4.2.0",
"uv>=0.11.6",
"uv>=0.11.15",
"mypy>=1.16.0",
"PyPDF2>=3.0.1",
"python-docx>=1.1.0",
@@ -62,10 +62,10 @@ dependencies = [
"ebooklib>=0.18",
"html2text>=2024.2.26",
"langchain>=0.2.0",
"langchain-core>=1.2.28",
"langsmith>=0.7.31",
"python-multipart>=0.0.26",
"Mako>=1.3.11",
"langchain-core>=1.3.3",
"langsmith>=0.8.0",
"python-multipart>=0.0.27",
"Mako>=1.3.12",
"langchain-text-splitters>=1.1.2",
"chromadb>=1.0.0,<2.0.0",
"qdrant-client (>=1.15.1,<2.0.0)",

View File

@@ -0,0 +1,5 @@
from .client import AsyncDeerFlowClient
from .errors import DeerFlowAPIError
from . import stream_utils
__all__ = ['AsyncDeerFlowClient', 'DeerFlowAPIError', 'stream_utils']

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@@ -0,0 +1,204 @@
"""DeerFlow LangGraph HTTP API 客户端
参考 astrbot 的 deerflow_api_client 实现,使用 httpx 适配 LangBot 风格。
"""
from __future__ import annotations
import codecs
import json
import typing
from collections.abc import AsyncGenerator
import httpx
from .errors import DeerFlowAPIError
SSE_MAX_BUFFER_CHARS = 1_048_576
def _normalize_sse_newlines(text: str) -> str:
"""规范化 CRLF/CR 为 LF确保 SSE 块分割稳定"""
return text.replace('\r\n', '\n').replace('\r', '\n')
def _parse_sse_data_lines(data_lines: list[str]) -> typing.Any:
raw_data = '\n'.join(data_lines)
try:
return json.loads(raw_data)
except json.JSONDecodeError:
# 某些 LangGraph 兼容服务端会在单个 SSE 事件中用多个 data 行
# 发送多段 JSON 片段(例如 tuple payload
parsed_lines: list[typing.Any] = []
can_parse_all = True
for line in data_lines:
line = line.strip()
if not line:
continue
try:
parsed_lines.append(json.loads(line))
except json.JSONDecodeError:
can_parse_all = False
break
if can_parse_all and parsed_lines:
return parsed_lines[0] if len(parsed_lines) == 1 else parsed_lines
return raw_data
def _parse_sse_block(block: str) -> dict[str, typing.Any] | None:
if not block.strip():
return None
event_name = 'message'
data_lines: list[str] = []
for line in block.splitlines():
if line.startswith('event:'):
event_name = line[6:].strip()
elif line.startswith('data:'):
data_lines.append(line[5:].lstrip())
if not data_lines:
return None
return {'event': event_name, 'data': _parse_sse_data_lines(data_lines)}
class AsyncDeerFlowClient:
"""DeerFlow LangGraph HTTP API 客户端"""
api_base: str
headers: dict[str, str]
def __init__(
self,
api_base: str = 'http://127.0.0.1:2026',
api_key: str = '',
auth_header: str = '',
) -> None:
self.api_base = api_base.rstrip('/')
self.headers: dict[str, str] = {}
if auth_header:
self.headers['Authorization'] = auth_header
elif api_key:
self.headers['Authorization'] = f'Bearer {api_key}'
async def create_thread(self, timeout: float = 20) -> dict[str, typing.Any]:
"""创建一个新的 LangGraph thread
Returns:
包含 thread_id 等信息的字典
"""
url = f'{self.api_base}/api/langgraph/threads'
payload = {'metadata': {}}
async with httpx.AsyncClient(
trust_env=True,
timeout=timeout,
) as client:
response = await client.post(
url,
headers=self.headers,
json=payload,
)
if response.status_code not in (200, 201):
raise DeerFlowAPIError(
operation='create thread',
status=response.status_code,
body=response.text,
url=url,
)
return response.json()
async def delete_thread(self, thread_id: str, timeout: float = 20) -> None:
"""删除指定 thread"""
url = f'{self.api_base}/api/threads/{thread_id}'
async with httpx.AsyncClient(
trust_env=True,
timeout=timeout,
) as client:
response = await client.delete(url, headers=self.headers)
if response.status_code not in (200, 202, 204, 404):
raise DeerFlowAPIError(
operation='delete thread',
status=response.status_code,
body=response.text,
url=url,
thread_id=thread_id,
)
async def stream_run(
self,
thread_id: str,
payload: dict[str, typing.Any],
timeout: float = 120,
) -> AsyncGenerator[dict[str, typing.Any], None]:
"""运行一次 LangGraph stream 请求,逐事件 yield
Yields:
事件字典 {'event': event_name, 'data': parsed_data}
"""
url = f'{self.api_base}/api/langgraph/threads/{thread_id}/runs/stream'
# 流式请求使用单独的 read timeout 控制
stream_timeout = httpx.Timeout(
connect=min(timeout, 30),
read=timeout,
write=timeout,
pool=timeout,
)
async with httpx.AsyncClient(
trust_env=True,
timeout=stream_timeout,
) as client:
async with client.stream(
'POST',
url,
headers={
**self.headers,
'Accept': 'text/event-stream',
'Content-Type': 'application/json',
},
json=payload,
) as resp:
if resp.status_code != 200:
body = await resp.aread()
raise DeerFlowAPIError(
operation='runs/stream request',
status=resp.status_code,
body=body.decode('utf-8', errors='replace'),
url=url,
thread_id=thread_id,
)
decoder = codecs.getincrementaldecoder('utf-8')('replace')
buffer = ''
async for chunk in resp.aiter_bytes(8192):
buffer += _normalize_sse_newlines(decoder.decode(chunk))
while '\n\n' in buffer:
block, buffer = buffer.split('\n\n', 1)
parsed = _parse_sse_block(block)
if parsed is not None:
yield parsed
if len(buffer) > SSE_MAX_BUFFER_CHARS:
# 缓冲区过大,强制 flush
parsed = _parse_sse_block(buffer)
if parsed is not None:
yield parsed
buffer = ''
# flush 剩余内容
buffer += _normalize_sse_newlines(decoder.decode(b'', final=True))
while '\n\n' in buffer:
block, buffer = buffer.split('\n\n', 1)
parsed = _parse_sse_block(block)
if parsed is not None:
yield parsed
if buffer.strip():
parsed = _parse_sse_block(buffer)
if parsed is not None:
yield parsed

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@@ -0,0 +1,30 @@
from __future__ import annotations
class DeerFlowAPIError(Exception):
"""DeerFlow API 请求失败"""
def __init__(
self,
*,
operation: str = '',
status: int = 0,
body: str = '',
url: str = '',
thread_id: str | None = None,
message: str = '',
) -> None:
self.operation = operation
self.status = status
self.body = body
self.url = url
self.thread_id = thread_id
if message:
super().__init__(message)
return
msg = f'DeerFlow {operation} failed: status={status}, url={url}, body={body}'
if thread_id is not None:
msg = f'DeerFlow {operation} failed: thread_id={thread_id}, status={status}, url={url}, body={body}'
super().__init__(msg)

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@@ -0,0 +1,212 @@
"""DeerFlow LangGraph 流式响应解析工具
参考 astrbot 实现的 deerflow_stream_utils。
"""
from __future__ import annotations
import typing
from collections.abc import Iterable
def extract_text(content: typing.Any) -> str:
"""从消息 content 中提取纯文本"""
if isinstance(content, str):
return content
if isinstance(content, dict):
if isinstance(content.get('text'), str):
return content['text']
if 'content' in content:
return extract_text(content.get('content'))
if 'kwargs' in content and isinstance(content['kwargs'], dict):
return extract_text(content['kwargs'].get('content'))
if isinstance(content, list):
parts: list[str] = []
for item in content:
if isinstance(item, str):
parts.append(item)
elif isinstance(item, dict):
item_type = item.get('type')
if item_type == 'text' and isinstance(item.get('text'), str):
parts.append(item['text'])
elif 'content' in item:
parts.append(extract_text(item['content']))
return '\n'.join([p for p in parts if p]).strip()
return str(content) if content is not None else ''
def extract_messages_from_values_data(data: typing.Any) -> list[typing.Any]:
"""从 values 事件中提取 messages 列表"""
candidates: list[typing.Any] = []
if isinstance(data, dict):
candidates.append(data)
if isinstance(data.get('values'), dict):
candidates.append(data['values'])
elif isinstance(data, list):
candidates.extend([x for x in data if isinstance(x, dict)])
for item in candidates:
messages = item.get('messages')
if isinstance(messages, list):
return messages
return []
def is_ai_message(message: dict[str, typing.Any]) -> bool:
"""判断是否为 AI/assistant 消息"""
role = str(message.get('role', '')).lower()
if role in {'assistant', 'ai'}:
return True
msg_type = str(message.get('type', '')).lower()
if msg_type in {'ai', 'assistant', 'aimessage', 'aimessagechunk'}:
return True
if 'ai' in msg_type and all(token not in msg_type for token in ('human', 'tool', 'system')):
return True
return False
def extract_latest_ai_text(messages: Iterable[typing.Any]) -> str:
"""获取最近一条 AI 消息的文本内容"""
if isinstance(messages, (list, tuple)):
iterable = reversed(messages)
else:
iterable = reversed(list(messages))
for msg in iterable:
if not isinstance(msg, dict):
continue
if is_ai_message(msg):
text = extract_text(msg.get('content'))
if text:
return text
return ''
def extract_latest_ai_message(messages: Iterable[typing.Any]) -> dict[str, typing.Any] | None:
"""获取最近一条 AI 消息对象"""
if isinstance(messages, (list, tuple)):
iterable = reversed(messages)
else:
iterable = reversed(list(messages))
for msg in iterable:
if not isinstance(msg, dict):
continue
if is_ai_message(msg):
return msg
return None
def is_clarification_tool_message(message: dict[str, typing.Any]) -> bool:
"""判断是否为澄清问题工具消息"""
msg_type = str(message.get('type', '')).lower()
tool_name = str(message.get('name', '')).lower()
return msg_type == 'tool' and tool_name == 'ask_clarification'
def extract_latest_clarification_text(messages: Iterable[typing.Any]) -> str:
"""提取最近的澄清问题文本"""
if isinstance(messages, (list, tuple)):
iterable = reversed(messages)
else:
iterable = reversed(list(messages))
for msg in iterable:
if not isinstance(msg, dict):
continue
if is_clarification_tool_message(msg):
text = extract_text(msg.get('content'))
if text:
return text
return ''
def get_message_id(message: typing.Any) -> str:
"""提取消息 ID"""
if not isinstance(message, dict):
return ''
msg_id = message.get('id')
return msg_id if isinstance(msg_id, str) else ''
def extract_event_message_obj(data: typing.Any) -> dict[str, typing.Any] | None:
"""从事件 data 中提取消息对象"""
msg_obj = data
if isinstance(data, (list, tuple)) and data:
msg_obj = data[0]
if isinstance(msg_obj, dict) and isinstance(msg_obj.get('data'), dict):
msg_obj = msg_obj['data']
return msg_obj if isinstance(msg_obj, dict) else None
def extract_ai_delta_from_event_data(data: typing.Any) -> str:
"""从 messages-tuple 事件中提取 AI delta 文本"""
msg_obj = extract_event_message_obj(data)
if not msg_obj:
return ''
if is_ai_message(msg_obj):
return extract_text(msg_obj.get('content'))
return ''
def extract_clarification_from_event_data(data: typing.Any) -> str:
"""从事件中提取澄清问题"""
msg_obj = extract_event_message_obj(data)
if not msg_obj:
return ''
if is_clarification_tool_message(msg_obj):
return extract_text(msg_obj.get('content'))
return ''
def _iter_custom_event_items(data: typing.Any) -> list[dict[str, typing.Any]]:
items: list[dict[str, typing.Any]] = []
if isinstance(data, dict):
return [data]
if isinstance(data, list):
for item in data:
if isinstance(item, dict):
items.append(item)
elif isinstance(item, (list, tuple)):
for nested in item:
if isinstance(nested, dict):
items.append(nested)
return items
def extract_task_failures_from_custom_event(data: typing.Any) -> list[str]:
"""从 custom 事件中提取子任务失败信息"""
failures: list[str] = []
for item in _iter_custom_event_items(data):
event_type = str(item.get('type', '')).lower()
if event_type not in {'task_failed', 'task_timed_out'}:
continue
task_id = str(item.get('task_id', '')).strip()
error_text = extract_text(item.get('error')).strip()
if task_id and error_text:
failures.append(f'{task_id}: {error_text}')
elif error_text:
failures.append(error_text)
elif task_id:
failures.append(f'{task_id}: unknown error')
else:
failures.append('unknown task failure')
return failures
def build_task_failure_summary(failures: list[str]) -> str:
"""构建任务失败摘要"""
if not failures:
return ''
deduped: list[str] = []
seen: set[str] = set()
for failure in failures:
if failure not in seen:
seen.add(failure)
deduped.append(failure)
if len(deduped) == 1:
return f'DeerFlow subtask failed: {deduped[0]}'
joined = '\n'.join([f'- {item}' for item in deduped[:5]])
return f'DeerFlow subtasks failed:\n{joined}'

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@@ -0,0 +1,4 @@
from .client import AsyncWeKnoraClient
from .errors import WeKnoraAPIError
__all__ = ['AsyncWeKnoraClient', 'WeKnoraAPIError']

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@@ -0,0 +1,180 @@
from __future__ import annotations
import httpx
import typing
import json
from .errors import WeKnoraAPIError
class AsyncWeKnoraClient:
"""WeKnora API 客户端"""
api_key: str
base_url: str
def __init__(
self,
api_key: str,
base_url: str = 'http://localhost:80/api/v1',
) -> None:
self.api_key = api_key
self.base_url = base_url
async def create_session(
self,
title: str = '',
description: str = '',
timeout: float = 30.0,
) -> str:
"""创建会话,返回 session_id"""
async with httpx.AsyncClient(
base_url=self.base_url,
trust_env=True,
timeout=timeout,
) as client:
payload: dict[str, typing.Any] = {}
if title:
payload['title'] = title
if description:
payload['description'] = description
response = await client.post(
'/sessions',
headers={
'X-API-Key': self.api_key,
'Content-Type': 'application/json',
},
json=payload,
)
if response.status_code not in (200, 201):
raise WeKnoraAPIError(f'{response.status_code} {response.text}')
data = response.json()
return data['data']['id']
async def agent_chat(
self,
session_id: str,
query: str,
user: str,
agent_id: str = '',
knowledge_base_ids: list[str] | None = None,
web_search_enabled: bool = False,
timeout: float = 120.0,
) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
"""
Agent 智能对话SSE 流式)
响应事件类型:
- agent_query: Agent 开始处理
- thinking: 思考过程
- tool_call: 工具调用
- tool_result: 工具结果
- references: 知识库引用
- answer: 回答内容
- reflection: 反思
- session_title: 会话标题
- error: 错误
"""
if knowledge_base_ids is None:
knowledge_base_ids = []
async with httpx.AsyncClient(
base_url=self.base_url,
trust_env=True,
timeout=timeout,
) as client:
payload: dict[str, typing.Any] = {
'query': query,
'agent_enabled': True,
'channel': 'im',
}
if agent_id:
payload['agent_id'] = agent_id
if knowledge_base_ids:
payload['knowledge_base_ids'] = knowledge_base_ids
if web_search_enabled:
payload['web_search_enabled'] = True
async with client.stream(
'POST',
f'/agent-chat/{session_id}',
headers={
'X-API-Key': self.api_key,
'Content-Type': 'application/json',
},
json=payload,
) as r:
async for chunk in r.aiter_lines():
if r.status_code != 200:
raise WeKnoraAPIError(f'{r.status_code} {chunk}')
if chunk.strip() == '':
continue
if chunk.startswith('data:'):
try:
data = json.loads(chunk[5:].strip())
except json.JSONDecodeError:
continue
yield data
# 收到 error 事件后主动结束流,避免上层未 raise 时持续等待
if data.get('response_type') == 'error':
return
async def knowledge_chat(
self,
session_id: str,
query: str,
user: str,
agent_id: str = 'builtin-quick-answer',
knowledge_base_ids: list[str] | None = None,
timeout: float = 120.0,
) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
"""
知识库 RAG 问答SSE 流式)
响应事件类型:
- references: 知识库引用
- answer: 回答内容
"""
if knowledge_base_ids is None:
knowledge_base_ids = []
async with httpx.AsyncClient(
base_url=self.base_url,
trust_env=True,
timeout=timeout,
) as client:
payload: dict[str, typing.Any] = {
'query': query,
'channel': 'im',
}
if agent_id:
payload['agent_id'] = agent_id
if knowledge_base_ids:
payload['knowledge_base_ids'] = knowledge_base_ids
async with client.stream(
'POST',
f'/knowledge-chat/{session_id}',
headers={
'X-API-Key': self.api_key,
'Content-Type': 'application/json',
},
json=payload,
) as r:
async for chunk in r.aiter_lines():
if r.status_code != 200:
raise WeKnoraAPIError(f'{r.status_code} {chunk}')
if chunk.strip() == '':
continue
if chunk.startswith('data:'):
try:
data = json.loads(chunk[5:].strip())
except json.JSONDecodeError:
continue
yield data
# 收到 error 事件后主动结束流,避免上层未 raise 时持续等待
if data.get('response_type') == 'error':
return

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@@ -0,0 +1,6 @@
class WeKnoraAPIError(Exception):
"""WeKnora API 请求失败"""
def __init__(self, message: str = ''):
self.message = message
super().__init__(self.message)

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@@ -120,13 +120,19 @@ class BoxRuntimeConnector(ManagedRuntimeConnector):
self._relay_port = parsed.port or _DEFAULT_PORT
self._filtered_box_config = _filter_config_for_runtime(_get_box_config(ap))
def _uses_websocket(self) -> bool:
def uses_websocket(self) -> bool:
"""Whether the connector should use WebSocket to reach the Box runtime.
True when:
- Running inside Docker (Box runtime is a separate container)
- The ``--standalone-box`` CLI flag was passed
- An explicit ``runtime.endpoint`` was configured
When this is True the Box runtime lives in a separate process with its
own filesystem view (container, pod sidecar, or remote host), so paths
it reports (e.g. skill ``package_root``) are NOT resolvable on the
LangBot side. When False, Box runs as a stdio child process that shares
LangBot's filesystem.
"""
return bool(
self.configured_runtime_endpoint
@@ -134,6 +140,10 @@ class BoxRuntimeConnector(ManagedRuntimeConnector):
or platform.use_websocket_to_connect_box_runtime()
)
# Backwards-compatible private alias.
def _uses_websocket(self) -> bool:
return self.uses_websocket()
async def initialize(self) -> None:
if self._uses_websocket():
if platform.get_platform() == 'win32' and not self.configured_runtime_endpoint:

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@@ -67,6 +67,10 @@ class BoxService:
self._available = False
self._connector_error: str = ''
self._reconnecting = False
# Optional explicit override for shares_filesystem_with_box. None means
# "derive from the connector transport". Set by tests / embedders that
# know the real LangBot<->Box filesystem topology.
self._shares_filesystem_with_box_override: bool | None = None
@property
def enabled(self) -> bool:
@@ -148,6 +152,32 @@ class BoxService:
def available(self) -> bool:
return self._available
@property
def shares_filesystem_with_box(self) -> bool:
"""Whether LangBot and the Box runtime share a filesystem view.
This is True only when Box runs as a local stdio child process of
LangBot (same container/host). In that case paths the Box runtime
reports — notably skill ``package_root`` — resolve identically on the
LangBot side, so LangBot may validate them against its own filesystem.
It is False for every separated deployment (Docker Compose, k8s
sidecar, ``--standalone-box``, or an explicit ``runtime.endpoint``),
where the Box runtime owns its own filesystem and LangBot must trust
the paths it reports rather than checking them locally.
When Box is wired up with an injected client (tests, custom embeds)
there is no connector to introspect; we conservatively report False so
LangBot never wrongly drops Box-reported skills. An explicit override
can be set via ``_shares_filesystem_with_box`` (used by tests and any
embedder that knows the real topology).
"""
if self._shares_filesystem_with_box_override is not None:
return self._shares_filesystem_with_box_override
if self._runtime_connector is None:
return False
return not self._runtime_connector.uses_websocket()
async def execute_spec_payload(
self,
spec_payload: dict,
@@ -220,14 +250,24 @@ class BoxService:
all skill packages mounted, regardless of which skill is currently
activated.
Skills whose ``package_root`` is missing or no longer a directory on
the LangBot-visible filesystem are skipped with a warning instead of
being passed through to the backend. Without this guard the three
backends behave inconsistently on a stale mount: nsjail refuses to
start the sandbox (failing every exec in the session), Docker
silently auto-creates a root-owned empty directory on the host, and
E2B silently skips the upload — none of which surfaces an
actionable error to the agent or operator.
Path validation is filesystem-topology dependent. When LangBot and the
Box runtime share a filesystem (local stdio mode), a skill whose
``package_root`` is missing or no longer a directory is skipped with a
warning instead of being passed through to the backend. Without that
guard the three backends behave inconsistently on a stale mount: nsjail
refuses to start the sandbox (failing every exec in the session),
Docker silently auto-creates a root-owned empty directory on the host,
and E2B silently skips the upload — none of which surfaces an
actionable error.
When Box runs as a separate process (Docker Compose, k8s sidecar,
``--standalone-box``, or a remote ``runtime.endpoint``), the
``package_root`` reported by ``list_skills`` is the Box runtime's own
filesystem path and is NOT resolvable on the LangBot side. Validating
it locally would wrongly drop every skill, so LangBot trusts the path
and lets the Box runtime resolve it. The Box runtime only ever reports
skills it discovered on its own filesystem, so the path is valid there
by construction.
"""
skill_mgr = getattr(self.ap, 'skill_mgr', None)
if skill_mgr is None:
@@ -235,13 +275,15 @@ class BoxService:
from ..provider.tools.loaders import skill as skill_loader
validate_locally = self.shares_filesystem_with_box
visible_skills = skill_loader.get_visible_skills(self.ap, query)
mounts: list[dict] = []
for skill_name, skill_data in visible_skills.items():
package_root = str(skill_data.get('package_root', '') or '').strip()
if not package_root:
continue
if not os.path.isdir(package_root):
if validate_locally and not os.path.isdir(package_root):
self.ap.logger.warning(
f'Skill "{skill_name}" package_root missing on filesystem '
f'({package_root}); skipping mount to prevent sandbox failures. '

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@@ -0,0 +1,27 @@
from __future__ import annotations
from .. import migration
@migration.migration_class('weknora-api-config', 42)
class WeKnoraAPICfgMigration(migration.Migration):
"""WeKnora API 配置迁移"""
async def need_migrate(self) -> bool:
"""判断当前环境是否需要运行此迁移"""
return 'weknora-api' not in self.ap.provider_cfg.data
async def run(self):
"""执行迁移"""
self.ap.provider_cfg.data['weknora-api'] = {
'base-url': 'http://localhost:8080/api/v1',
'app-type': 'agent',
'api-key': '',
'agent-id': 'builtin-smart-reasoning',
'knowledge-base-ids': [],
'web-search-enabled': False,
'timeout': 120,
'base-prompt': '请回答用户的问题。',
}
await self.ap.provider_cfg.dump_config()

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@@ -0,0 +1,30 @@
from __future__ import annotations
from .. import migration
@migration.migration_class('deerflow-api-config', 43)
class DeerFlowAPICfgMigration(migration.Migration):
"""DeerFlow API 配置迁移"""
async def need_migrate(self) -> bool:
"""判断当前环境是否需要运行此迁移"""
return 'deerflow-api' not in self.ap.provider_cfg.data
async def run(self):
"""执行迁移"""
self.ap.provider_cfg.data['deerflow-api'] = {
'api-base': 'http://127.0.0.1:2026',
'api-key': '',
'auth-header': '',
'assistant-id': 'lead_agent',
'model-name': '',
'thinking-enabled': False,
'plan-mode': False,
'subagent-enabled': False,
'max-concurrent-subagents': 3,
'timeout': 300,
'recursion-limit': 1000,
}
await self.ap.provider_cfg.dump_config()

View File

@@ -11,6 +11,10 @@ class MCPServer(Base):
enable = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=False)
mode = sqlalchemy.Column(sqlalchemy.String(255), nullable=False) # stdio, sse, http
extra_args = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
# Markdown documentation captured from LangBot Space at install time so the
# detail page can show docs even when the server is offline / has no tools.
# Empty string for manually-created servers that have no marketplace README.
readme = sqlalchemy.Column(sqlalchemy.Text, nullable=False, server_default='', default='')
created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
updated_at = sqlalchemy.Column(
sqlalchemy.DateTime,

View File

@@ -0,0 +1,34 @@
"""add readme column to mcp_servers
Revision ID: 0004_add_mcp_readme
Revises: 0003_add_rerank_models
Create Date: 2026-06-06
"""
import sqlalchemy as sa
from alembic import op
revision = '0004_add_mcp_readme'
down_revision = '0003_add_rerank_models'
branch_labels = None
depends_on = None
def upgrade() -> None:
# Add ``readme`` to mcp_servers if the table exists and the column is missing
# (the table may have been created by create_all() with the column already
# present on fresh installs, so guard against duplicate-add).
conn = op.get_bind()
inspector = sa.inspect(conn)
if 'mcp_servers' not in inspector.get_table_names():
return
columns = {col['name'] for col in inspector.get_columns('mcp_servers')}
if 'readme' not in columns:
op.add_column(
'mcp_servers',
sa.Column('readme', sa.Text(), nullable=False, server_default=''),
)
def downgrade() -> None:
op.drop_column('mcp_servers', 'readme')

View File

@@ -248,6 +248,9 @@ class PluginRuntimeConnector(ManagedRuntimeConnector):
mode = mcp_data.get('mode') or 'stdio'
extra_args = mcp_data.get('extra_args') or {}
# Marketplace records carry the rendered README markdown; persist it so
# the detail page Docs tab works offline and without a marketplace round-trip.
readme = mcp_data.get('readme') or ''
# Use __ instead of / to avoid URL routing issues with slashes
name = f'{mcp_data.get("author", "")}__{mcp_data.get("name", "")}'
@@ -267,6 +270,7 @@ class PluginRuntimeConnector(ManagedRuntimeConnector):
'enable': True,
'mode': mode,
'extra_args': extra_args,
'readme': readme,
}
await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_mcp.MCPServer).values(server_data))

View File

@@ -0,0 +1,511 @@
"""DeerFlow LangGraph API Runner
参考 astrbot 的 deerflow_agent_runner 实现,适配 LangBot 的 Runner 接口。
特点:
- 使用 LangGraph HTTP API 接入 deer-flow 后端
- 自动管理 thread_id按 session 隔离)
- 支持 SSE 流式响应解析
- 支持 streaming/非流式两种输出
- 处理 values / messages-tuple / custom 三种事件
"""
from __future__ import annotations
import asyncio
import hashlib
import json
import typing
from collections import deque
from dataclasses import dataclass, field
from langbot.pkg.provider import runner
from langbot.pkg.core import app
import langbot_plugin.api.entities.builtin.provider.message as provider_message
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
from langbot.libs.deerflow_api import client, errors, stream_utils
_MAX_VALUES_HISTORY = 200
@dataclass
class _StreamState:
"""流式状态跟踪"""
latest_text: str = ''
prev_text_for_streaming: str = ''
clarification_text: str = ''
task_failures: list[str] = field(default_factory=list)
seen_message_ids: set[str] = field(default_factory=set)
seen_message_order: deque[str] = field(default_factory=deque)
no_id_message_fingerprints: dict[int, str] = field(default_factory=dict)
baseline_initialized: bool = False
has_values_text: bool = False
run_values_messages: list[dict[str, typing.Any]] = field(default_factory=list)
timed_out: bool = False
@runner.runner_class('deerflow-api')
class DeerFlowAPIRunner(runner.RequestRunner):
"""DeerFlow LangGraph API 对话请求器"""
deerflow_client: client.AsyncDeerFlowClient
def __init__(self, ap: app.Application, pipeline_config: dict):
super().__init__(ap, pipeline_config)
cfg = self.pipeline_config['ai']['deerflow-api']
api_base = cfg.get('api-base', '').strip()
if not api_base or not api_base.startswith(('http://', 'https://')):
raise errors.DeerFlowAPIError(
message='DeerFlow API Base URL 格式错误,必须以 http:// 或 https:// 开头',
)
self.api_base = api_base
self.api_key = cfg.get('api-key', '')
self.auth_header = cfg.get('auth-header', '')
self.assistant_id = cfg.get('assistant-id', 'lead_agent')
self.model_name = cfg.get('model-name', '')
self.thinking_enabled = bool(cfg.get('thinking-enabled', False))
self.plan_mode = bool(cfg.get('plan-mode', False))
self.subagent_enabled = bool(cfg.get('subagent-enabled', False))
self.max_concurrent_subagents = int(cfg.get('max-concurrent-subagents', 3))
self.timeout = int(cfg.get('timeout', 300))
self.recursion_limit = int(cfg.get('recursion-limit', 1000))
self.deerflow_client = client.AsyncDeerFlowClient(
api_base=self.api_base,
api_key=self.api_key,
auth_header=self.auth_header,
)
# ------------------------------------------------------------------
# 辅助方法
# ------------------------------------------------------------------
def _fingerprint_message(self, message: dict[str, typing.Any]) -> str:
try:
raw = json.dumps(message, sort_keys=True, ensure_ascii=False, default=str)
except (TypeError, ValueError):
raw = repr(message)
return hashlib.sha1(raw.encode('utf-8', errors='ignore')).hexdigest()
def _remember_seen_message_id(self, state: _StreamState, msg_id: str) -> None:
if not msg_id or msg_id in state.seen_message_ids:
return
state.seen_message_ids.add(msg_id)
state.seen_message_order.append(msg_id)
while len(state.seen_message_order) > _MAX_VALUES_HISTORY:
dropped = state.seen_message_order.popleft()
state.seen_message_ids.discard(dropped)
def _extract_new_messages_from_values(
self,
values_messages: list[typing.Any],
state: _StreamState,
) -> list[dict[str, typing.Any]]:
new_messages: list[dict[str, typing.Any]] = []
no_id_indexes_seen: set[int] = set()
for idx, msg in enumerate(values_messages):
if not isinstance(msg, dict):
continue
msg_id = stream_utils.get_message_id(msg)
if msg_id:
if msg_id in state.seen_message_ids:
continue
self._remember_seen_message_id(state, msg_id)
new_messages.append(msg)
continue
no_id_indexes_seen.add(idx)
fp = self._fingerprint_message(msg)
if state.no_id_message_fingerprints.get(idx) == fp:
continue
state.no_id_message_fingerprints[idx] = fp
new_messages.append(msg)
for idx in list(state.no_id_message_fingerprints.keys()):
if idx not in no_id_indexes_seen:
state.no_id_message_fingerprints.pop(idx, None)
return new_messages
# ------------------------------------------------------------------
# 用户输入处理
# ------------------------------------------------------------------
def _build_user_content(
self,
prompt: str,
image_urls: list[str],
) -> typing.Any:
"""构建 LangGraph 兼容的 user content支持多模态"""
if not image_urls:
return prompt
content: list[dict[str, typing.Any]] = []
if prompt:
content.append({'type': 'text', 'text': prompt})
for url in image_urls:
if not isinstance(url, str):
continue
url = url.strip()
if not url:
continue
if url.startswith(('http://', 'https://', 'data:')):
content.append({'type': 'image_url', 'image_url': {'url': url}})
return content if content else prompt
def _preprocess_user_message(
self,
query: pipeline_query.Query,
) -> tuple[str, list[str]]:
"""提取用户消息的纯文本与图片 URL 列表"""
plain_text = ''
image_urls: list[str] = []
if isinstance(query.user_message.content, str):
plain_text = query.user_message.content
elif isinstance(query.user_message.content, list):
for ce in query.user_message.content:
if ce.type == 'text':
plain_text += ce.text
elif ce.type == 'image_base64':
# 转换为 data URI 形式
b64 = getattr(ce, 'image_base64', '')
if b64:
if not b64.startswith('data:'):
b64 = f'data:image/png;base64,{b64}'
image_urls.append(b64)
elif ce.type == 'image_url':
url = getattr(ce, 'image_url', '')
if url:
image_urls.append(url)
return plain_text, image_urls
# ------------------------------------------------------------------
# 请求构造
# ------------------------------------------------------------------
def _build_messages(
self,
prompt: str,
image_urls: list[str],
system_prompt: str = '',
) -> list[dict[str, typing.Any]]:
messages: list[dict[str, typing.Any]] = []
if system_prompt:
messages.append({'role': 'system', 'content': system_prompt})
messages.append(
{
'role': 'user',
'content': self._build_user_content(prompt, image_urls),
}
)
return messages
def _build_runtime_configurable(self, thread_id: str) -> dict[str, typing.Any]:
cfg: dict[str, typing.Any] = {
'thread_id': thread_id,
'thinking_enabled': self.thinking_enabled,
'is_plan_mode': self.plan_mode,
'subagent_enabled': self.subagent_enabled,
}
if self.subagent_enabled:
cfg['max_concurrent_subagents'] = self.max_concurrent_subagents
if self.model_name:
cfg['model_name'] = self.model_name
return cfg
def _build_payload(
self,
thread_id: str,
prompt: str,
image_urls: list[str],
system_prompt: str = '',
) -> dict[str, typing.Any]:
runtime_configurable = self._build_runtime_configurable(thread_id)
return {
'assistant_id': self.assistant_id,
'input': {
'messages': self._build_messages(prompt, image_urls, system_prompt),
},
'stream_mode': ['values', 'messages-tuple', 'custom'],
# DeerFlow 2.0 从 config.configurable 读取运行时覆盖
# 同时保留 context 字段做向后兼容
'context': dict(runtime_configurable),
'config': {
'recursion_limit': self.recursion_limit,
'configurable': runtime_configurable,
},
}
# ------------------------------------------------------------------
# Session/Thread 管理
# ------------------------------------------------------------------
async def _ensure_thread_id(self, query: pipeline_query.Query) -> str:
"""从 query.session 取/创建 deerflow thread_id
LangBot 使用 `query.session.using_conversation.uuid` 持久化 conversation id
我们复用这个字段存储 deerflow thread_id与 Dify Runner 同样做法)。
"""
thread_id = query.session.using_conversation.uuid or ''
if thread_id:
return thread_id
thread = await self.deerflow_client.create_thread(timeout=min(30, self.timeout))
thread_id = thread.get('thread_id', '')
if not thread_id:
raise errors.DeerFlowAPIError(message=f'DeerFlow create thread 返回数据缺少 thread_id: {thread}')
query.session.using_conversation.uuid = thread_id
return thread_id
# ------------------------------------------------------------------
# 流式事件处理
# ------------------------------------------------------------------
def _handle_values_event(
self,
data: typing.Any,
state: _StreamState,
) -> str | None:
"""处理 values 事件,返回新的完整文本(增量基础上的全量)"""
values_messages = stream_utils.extract_messages_from_values_data(data)
if not values_messages:
return None
new_messages: list[dict[str, typing.Any]] = []
if not state.baseline_initialized:
state.baseline_initialized = True
for idx, msg in enumerate(values_messages):
if not isinstance(msg, dict):
continue
new_messages.append(msg)
msg_id = stream_utils.get_message_id(msg)
if msg_id:
self._remember_seen_message_id(state, msg_id)
continue
state.no_id_message_fingerprints[idx] = self._fingerprint_message(msg)
else:
new_messages = self._extract_new_messages_from_values(values_messages, state)
latest_text = ''
if new_messages:
state.run_values_messages.extend(new_messages)
if len(state.run_values_messages) > _MAX_VALUES_HISTORY:
state.run_values_messages = state.run_values_messages[-_MAX_VALUES_HISTORY:]
latest_text = stream_utils.extract_latest_ai_text(state.run_values_messages)
if latest_text:
state.has_values_text = True
latest_clarification = stream_utils.extract_latest_clarification_text(
state.run_values_messages,
)
if latest_clarification:
state.clarification_text = latest_clarification
return latest_text or None
def _handle_message_event(
self,
data: typing.Any,
state: _StreamState,
) -> str | None:
"""处理 messages-tuple 事件,返回增量文本
当 values 事件已经提供完整文本时,跳过 messages-tuple 的增量
"""
delta = stream_utils.extract_ai_delta_from_event_data(data)
if delta and not state.has_values_text:
state.latest_text += delta
return delta
maybe_clar = stream_utils.extract_clarification_from_event_data(data)
if maybe_clar:
state.clarification_text = maybe_clar
return None
def _build_final_text(self, state: _StreamState) -> str:
"""构建最终输出文本"""
if state.clarification_text:
return state.clarification_text
# 优先使用最后一条 AI message 的文本
latest_ai = stream_utils.extract_latest_ai_message(state.run_values_messages)
if latest_ai:
text = stream_utils.extract_text(latest_ai.get('content'))
if text:
if state.timed_out:
text += f'\n\nDeerFlow stream 在 {self.timeout}s 后超时,返回部分结果。'
return text
if state.latest_text:
text = state.latest_text
if state.timed_out:
text += f'\n\nDeerFlow stream 在 {self.timeout}s 后超时,返回部分结果。'
return text
# 提取任务失败信息作兜底
failure_text = stream_utils.build_task_failure_summary(state.task_failures)
if failure_text:
return failure_text
return 'DeerFlow 返回空响应'
# ------------------------------------------------------------------
# 主流程
# ------------------------------------------------------------------
async def _stream_messages_chunk(
self,
query: pipeline_query.Query,
) -> typing.AsyncGenerator[provider_message.MessageChunk, None]:
"""流式输出生成器"""
plain_text, image_urls = self._preprocess_user_message(query)
system_prompt = ''
# LangBot 的 pipeline 通常通过 prompt-preprocess 已注入 system prompt
# 这里保持空,让 prompt-preprocess 的内容作为 user message 一并送给 deerflow
thread_id = await self._ensure_thread_id(query)
payload = self._build_payload(
thread_id=thread_id,
prompt=plain_text or 'continue',
image_urls=image_urls,
system_prompt=system_prompt,
)
state = _StreamState()
prev_text = ''
message_idx = 0
try:
async for event in self.deerflow_client.stream_run(
thread_id=thread_id,
payload=payload,
timeout=self.timeout,
):
event_type = event.get('event')
data = event.get('data')
if event_type == 'values':
new_full = self._handle_values_event(data, state)
if new_full and new_full != prev_text:
delta = new_full[len(prev_text) :] if new_full.startswith(prev_text) else new_full
prev_text = new_full
if delta:
message_idx += 1
yield provider_message.MessageChunk(
role='assistant',
content=new_full,
is_final=False,
)
continue
if event_type in {'messages-tuple', 'messages', 'message'}:
delta = self._handle_message_event(data, state)
if delta:
prev_text = state.latest_text
message_idx += 1
yield provider_message.MessageChunk(
role='assistant',
content=prev_text,
is_final=False,
)
continue
if event_type == 'custom':
state.task_failures.extend(
stream_utils.extract_task_failures_from_custom_event(data),
)
continue
if event_type == 'error':
raise errors.DeerFlowAPIError(message=f'DeerFlow stream error event: {data}')
if event_type == 'end':
break
except (asyncio.TimeoutError, TimeoutError):
self.ap.logger.warning(f'DeerFlow stream timed out after {self.timeout}s for thread_id={thread_id}')
state.timed_out = True
# 最终消息
final_text = self._build_final_text(state)
yield provider_message.MessageChunk(
role='assistant',
content=final_text,
is_final=True,
)
async def _messages(
self,
query: pipeline_query.Query,
) -> typing.AsyncGenerator[provider_message.Message, None]:
"""非流式聚合输出"""
plain_text, image_urls = self._preprocess_user_message(query)
thread_id = await self._ensure_thread_id(query)
payload = self._build_payload(
thread_id=thread_id,
prompt=plain_text or 'continue',
image_urls=image_urls,
)
state = _StreamState()
try:
async for event in self.deerflow_client.stream_run(
thread_id=thread_id,
payload=payload,
timeout=self.timeout,
):
event_type = event.get('event')
data = event.get('data')
if event_type == 'values':
self._handle_values_event(data, state)
continue
if event_type in {'messages-tuple', 'messages', 'message'}:
self._handle_message_event(data, state)
continue
if event_type == 'custom':
state.task_failures.extend(
stream_utils.extract_task_failures_from_custom_event(data),
)
continue
if event_type == 'error':
raise errors.DeerFlowAPIError(message=f'DeerFlow stream error event: {data}')
if event_type == 'end':
break
except (asyncio.TimeoutError, TimeoutError):
self.ap.logger.warning(f'DeerFlow stream timed out after {self.timeout}s for thread_id={thread_id}')
state.timed_out = True
final_text = self._build_final_text(state)
yield provider_message.Message(
role='assistant',
content=final_text,
)
async def run(
self,
query: pipeline_query.Query,
) -> typing.AsyncGenerator[provider_message.Message, None]:
"""主入口:根据 adapter 是否支持流式输出,选择流式或非流式"""
if await query.adapter.is_stream_output_supported():
msg_idx = 0
async for msg in self._stream_messages_chunk(query):
msg_idx += 1
msg.msg_sequence = msg_idx
yield msg
else:
async for msg in self._messages(query):
yield msg

View File

@@ -0,0 +1,351 @@
from __future__ import annotations
import typing
import json
from langbot.pkg.provider import runner
from langbot.pkg.core import app
import langbot_plugin.api.entities.builtin.provider.message as provider_message
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
from langbot.libs.weknora_api import client, errors
@runner.runner_class('weknora-api')
class WeKnoraAPIRunner(runner.RequestRunner):
"""WeKnora API 对话请求器"""
weknora_client: client.AsyncWeKnoraClient
def __init__(self, ap: app.Application, pipeline_config: dict):
super().__init__(ap, pipeline_config)
valid_app_types = ['chat', 'agent']
if self.pipeline_config['ai']['weknora-api']['app-type'] not in valid_app_types:
raise errors.WeKnoraAPIError(
f'不支持的 WeKnora 应用类型: {self.pipeline_config["ai"]["weknora-api"]["app-type"]}'
)
api_key = self.pipeline_config['ai']['weknora-api'].get('api-key', '').strip()
if not api_key:
raise errors.WeKnoraAPIError(
'WeKnora API Key 未配置,请在流水线的 WeKnora API 配置中填入 API Key '
'(从 WeKnora 前端 设置 → API Keys 生成)'
)
base_url = self.pipeline_config['ai']['weknora-api'].get('base-url', '').strip()
if not base_url:
raise errors.WeKnoraAPIError('WeKnora Base URL 未配置,请填入服务器地址,例如 http://localhost:8080/api/v1')
self.weknora_client = client.AsyncWeKnoraClient(
api_key=api_key,
base_url=base_url,
)
async def _extract_plain_text(self, query: pipeline_query.Query) -> str:
"""从用户消息中提取纯文本内容"""
plain_text = ''
if isinstance(query.user_message.content, str):
plain_text = query.user_message.content
elif isinstance(query.user_message.content, list):
for ce in query.user_message.content:
if ce.type == 'text':
plain_text += ce.text
if not plain_text:
plain_text = self.pipeline_config['ai']['weknora-api'].get('base-prompt', '')
return plain_text
async def _ensure_session(self, query: pipeline_query.Query) -> str:
"""确保会话存在,如果不存在则创建"""
session_id = query.session.using_conversation.uuid or ''
if not session_id:
user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
session_id = await self.weknora_client.create_session(title=f'IM Chat - {user_tag}')
query.session.using_conversation.uuid = session_id
return session_id
async def _agent_chat_messages(
self, query: pipeline_query.Query
) -> typing.AsyncGenerator[provider_message.Message, None]:
"""调用 Agent 智能对话(非流式聚合输出)"""
session_id = await self._ensure_session(query)
plain_text = await self._extract_plain_text(query)
user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
config = self.pipeline_config['ai']['weknora-api']
agent_id = config.get('agent-id', 'builtin-smart-reasoning')
knowledge_base_ids = config.get('knowledge-base-ids', [])
web_search_enabled = config.get('web-search-enabled', False)
timeout = config.get('timeout', 120)
full_answer = ''
chunk = None
async for chunk in self.weknora_client.agent_chat(
session_id=session_id,
query=plain_text,
user=user_tag,
agent_id=agent_id,
knowledge_base_ids=knowledge_base_ids,
web_search_enabled=web_search_enabled,
timeout=timeout,
):
self.ap.logger.debug('weknora-agent-chunk: ' + str(chunk))
response_type = chunk.get('response_type', '')
content = chunk.get('content', '')
if response_type == 'tool_call':
# 工具调用
tool_data = chunk.get('data', {})
tool_name = tool_data.get('tool_name', '')
if tool_name:
yield provider_message.Message(
role='assistant',
tool_calls=[
provider_message.ToolCall(
id=chunk.get('id', ''),
type='function',
function=provider_message.FunctionCall(
name=tool_name,
arguments=json.dumps(tool_data.get('arguments', {})),
),
)
],
)
elif response_type == 'answer':
if content:
full_answer += content
elif response_type == 'error':
raise errors.WeKnoraAPIError(f'WeKnora 服务错误: {content}')
if chunk is None:
raise errors.WeKnoraAPIError('WeKnora API 没有返回任何响应请检查网络连接和API配置')
if full_answer:
yield provider_message.Message(
role='assistant',
content=full_answer,
)
async def _chat_messages(
self, query: pipeline_query.Query
) -> typing.AsyncGenerator[provider_message.Message, None]:
"""调用知识库 RAG 问答(非流式聚合输出)"""
session_id = await self._ensure_session(query)
plain_text = await self._extract_plain_text(query)
user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
config = self.pipeline_config['ai']['weknora-api']
agent_id = config.get('agent-id', 'builtin-quick-answer')
knowledge_base_ids = config.get('knowledge-base-ids', [])
timeout = config.get('timeout', 120)
full_answer = ''
chunk = None
async for chunk in self.weknora_client.knowledge_chat(
session_id=session_id,
query=plain_text,
user=user_tag,
agent_id=agent_id,
knowledge_base_ids=knowledge_base_ids,
timeout=timeout,
):
self.ap.logger.debug('weknora-chat-chunk: ' + str(chunk))
response_type = chunk.get('response_type', '')
content = chunk.get('content', '')
if response_type == 'answer':
if content:
full_answer += content
elif response_type == 'error':
raise errors.WeKnoraAPIError(f'WeKnora 服务错误: {content}')
if chunk is None:
raise errors.WeKnoraAPIError('WeKnora API 没有返回任何响应请检查网络连接和API配置')
if full_answer:
yield provider_message.Message(
role='assistant',
content=full_answer,
)
async def _agent_chat_messages_chunk(
self, query: pipeline_query.Query
) -> typing.AsyncGenerator[provider_message.MessageChunk, None]:
"""调用 Agent 智能对话(流式输出)"""
session_id = await self._ensure_session(query)
plain_text = await self._extract_plain_text(query)
user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
config = self.pipeline_config['ai']['weknora-api']
agent_id = config.get('agent-id', 'builtin-smart-reasoning')
knowledge_base_ids = config.get('knowledge-base-ids', [])
web_search_enabled = config.get('web-search-enabled', False)
timeout = config.get('timeout', 120)
pending_answer = ''
message_idx = 0
is_final = False
chunk = None
async for chunk in self.weknora_client.agent_chat(
session_id=session_id,
query=plain_text,
user=user_tag,
agent_id=agent_id,
knowledge_base_ids=knowledge_base_ids,
web_search_enabled=web_search_enabled,
timeout=timeout,
):
self.ap.logger.debug('weknora-agent-chunk: ' + str(chunk))
response_type = chunk.get('response_type', '')
content = chunk.get('content', '')
done = chunk.get('done', False)
if response_type == 'tool_call':
tool_data = chunk.get('data', {})
tool_name = tool_data.get('tool_name', '')
if tool_name:
message_idx += 1
yield provider_message.MessageChunk(
role='assistant',
tool_calls=[
provider_message.ToolCall(
id=chunk.get('id', ''),
type='function',
function=provider_message.FunctionCall(
name=tool_name,
arguments=json.dumps(tool_data.get('arguments', {})),
),
)
],
)
elif response_type == 'answer':
message_idx += 1
if content:
pending_answer += content
if done:
is_final = True
# 每 8 个 chunk 输出一次,或最终输出
if message_idx % 8 == 0 or is_final:
yield provider_message.MessageChunk(
role='assistant',
content=pending_answer,
is_final=is_final,
)
elif response_type == 'error':
raise errors.WeKnoraAPIError(f'WeKnora 服务错误: {content}')
if chunk is None:
raise errors.WeKnoraAPIError('WeKnora API 没有返回任何响应请检查网络连接和API配置')
# 确保最终消息已发出
if not is_final and pending_answer:
yield provider_message.MessageChunk(
role='assistant',
content=pending_answer,
is_final=True,
)
async def _chat_messages_chunk(
self, query: pipeline_query.Query
) -> typing.AsyncGenerator[provider_message.MessageChunk, None]:
"""调用知识库 RAG 问答(流式输出)"""
session_id = await self._ensure_session(query)
plain_text = await self._extract_plain_text(query)
user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
config = self.pipeline_config['ai']['weknora-api']
agent_id = config.get('agent-id', 'builtin-quick-answer')
knowledge_base_ids = config.get('knowledge-base-ids', [])
timeout = config.get('timeout', 120)
pending_answer = ''
message_idx = 0
is_final = False
chunk = None
async for chunk in self.weknora_client.knowledge_chat(
session_id=session_id,
query=plain_text,
user=user_tag,
agent_id=agent_id,
knowledge_base_ids=knowledge_base_ids,
timeout=timeout,
):
self.ap.logger.debug('weknora-chat-chunk: ' + str(chunk))
response_type = chunk.get('response_type', '')
content = chunk.get('content', '')
done = chunk.get('done', False)
if response_type == 'answer':
message_idx += 1
if content:
pending_answer += content
if done:
is_final = True
if message_idx % 8 == 0 or is_final:
yield provider_message.MessageChunk(
role='assistant',
content=pending_answer,
is_final=is_final,
)
elif response_type == 'error':
raise errors.WeKnoraAPIError(f'WeKnora 服务错误: {content}')
if chunk is None:
raise errors.WeKnoraAPIError('WeKnora API 没有返回任何响应请检查网络连接和API配置')
if not is_final and pending_answer:
yield provider_message.MessageChunk(
role='assistant',
content=pending_answer,
is_final=True,
)
async def run(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
"""运行请求"""
app_type = self.pipeline_config['ai']['weknora-api']['app-type']
if await query.adapter.is_stream_output_supported():
msg_idx = 0
if app_type == 'agent':
async for msg in self._agent_chat_messages_chunk(query):
msg_idx += 1
msg.msg_sequence = msg_idx
yield msg
elif app_type == 'chat':
async for msg in self._chat_messages_chunk(query):
msg_idx += 1
msg.msg_sequence = msg_idx
yield msg
else:
raise errors.WeKnoraAPIError(f'不支持的 WeKnora 应用类型: {app_type}')
else:
if app_type == 'agent':
async for msg in self._agent_chat_messages(query):
yield msg
elif app_type == 'chat':
async for msg in self._chat_messages(query):
yield msg
else:
raise errors.WeKnoraAPIError(f'不支持的 WeKnora 应用类型: {app_type}')

View File

@@ -240,12 +240,13 @@ class RuntimeMCPSession:
return
if attempt >= self._MAX_RETRIES:
self.status = MCPSessionStatus.ERROR
self.error_message = f'Failed after {self._MAX_RETRIES + 1} attempts: {e}'
self.error_message = f'Failed after {self._MAX_RETRIES + 1} attempts: {self._describe_exception(e)}'
self._ready_event.set()
return
delay = self._RETRY_DELAYS[attempt]
self.ap.logger.warning(
f'MCP session {self.server_name} failed (attempt {attempt + 1}), retrying in {delay}s: {e}'
f'MCP session {self.server_name} failed (attempt {attempt + 1}), '
f'retrying in {delay}s: {self._describe_exception(e)}'
)
await self._cleanup_box_stdio_session()
# Reset status for retry
@@ -254,6 +255,30 @@ class RuntimeMCPSession:
self.error_phase = None
await asyncio.sleep(delay)
@staticmethod
def _describe_exception(exc: BaseException) -> str:
"""Flatten an exception into its underlying leaf messages.
anyio / the MCP client wrap real failures in a TaskGroup, whose own
message is the unhelpful "unhandled errors in a TaskGroup (N
sub-exception)". Recurse into ExceptionGroups so the actual cause
(e.g. ``httpx.HTTPStatusError: Client error '410 Gone'``) is surfaced.
"""
leaves: list[str] = []
def visit(e: BaseException) -> None:
sub = getattr(e, 'exceptions', None)
if sub: # ExceptionGroup / BaseExceptionGroup
for child in sub:
visit(child)
else:
leaves.append(f'{type(e).__name__}: {e}')
visit(exc)
seen: set[str] = set()
unique = [m for m in leaves if not (m in seen or seen.add(m))]
return '; '.join(unique) if unique else f'{type(exc).__name__}: {exc}'
_MONITOR_POLL_INTERVAL = 5
_MONITOR_MAX_CONSECUTIVE_ERRORS = 3

View File

@@ -46,6 +46,13 @@ class SkillManager:
self.ap.logger.info('Box runtime unavailable; skill cache is empty.')
return
# LangBot may only validate Box-reported paths against its own
# filesystem when the two share one (local stdio mode). In separated
# deployments (Docker Compose, k8s sidecar, --standalone-box, remote
# endpoint) the package_root lives on the Box runtime's filesystem and
# is not resolvable here, so we trust what Box reports.
validate_locally = bool(getattr(box_service, 'shares_filesystem_with_box', False))
try:
dropped = 0
for skill_data in await box_service.list_skills():
@@ -53,7 +60,7 @@ class SkillManager:
if not skill_name:
continue
package_root = str(skill_data.get('package_root', '') or '').strip()
if package_root and not os.path.isdir(package_root):
if validate_locally and package_root and not os.path.isdir(package_root):
self.ap.logger.warning(
f'Skill "{skill_name}" reported by Box runtime but '
f'package_root missing on LangBot filesystem '

View File

@@ -47,6 +47,14 @@ stages:
label:
en_US: Langflow API
zh_Hans: Langflow API
- name: weknora-api
label:
en_US: WeKnora API
zh_Hans: WeKnora API
- name: deerflow-api
label:
en_US: DeerFlow API
zh_Hans: DeerFlow API
- name: expire-time
label:
en_US: Conversation expire time (seconds)
@@ -653,3 +661,215 @@ stages:
type: json
required: false
default: '{}'
- name: weknora-api
label:
en_US: WeKnora API
zh_Hans: WeKnora API
description:
en_US: Configure the WeKnora API of the pipeline
zh_Hans: 配置 WeKnora API
config:
- name: base-url
label:
en_US: Base URL
zh_Hans: 基础 URL
description:
en_US: The base URL of the WeKnora server (with /api/v1)
zh_Hans: WeKnora 服务器的基础 URL包含 /api/v1
type: string
required: true
default: 'http://localhost:8080/api/v1'
- name: api-key
label:
en_US: API Key
zh_Hans: API 密钥
description:
en_US: The API key for WeKnora, generated from WeKnora frontend Settings → API Keys
zh_Hans: WeKnora 的 API 密钥,从 WeKnora 前端 设置 → API Keys 生成
type: string
required: true
default: ''
- name: app-type
label:
en_US: App Type
zh_Hans: 应用类型
type: select
required: true
default: agent
options:
- name: agent
label:
en_US: Agent (Smart Reasoning)
zh_Hans: Agent智能推理
- name: chat
label:
en_US: Chat (Knowledge Base RAG)
zh_Hans: 聊天(知识库 RAG
- name: agent-id
label:
en_US: Agent ID
zh_Hans: 智能体 ID
description:
en_US: The Agent ID to use. Built-in agents include builtin-quick-answer, builtin-smart-reasoning, builtin-data-analyst
zh_Hans: 要使用的智能体 ID。内置智能体builtin-quick-answer、builtin-smart-reasoning、builtin-data-analyst
type: string
required: true
default: 'builtin-smart-reasoning'
- name: knowledge-base-ids
label:
en_US: Knowledge Base IDs
zh_Hans: 知识库 ID 列表
description:
en_US: List of WeKnora knowledge base IDs to use (one per line)
zh_Hans: 要使用的 WeKnora 知识库 ID 列表(每行一个)
type: array
required: false
default: []
- name: web-search-enabled
label:
en_US: Enable Web Search
zh_Hans: 启用网络搜索
description:
en_US: Whether to enable web search in agent mode
zh_Hans: 在 Agent 模式下是否启用网络搜索
type: boolean
required: false
default: false
- name: timeout
label:
en_US: Timeout
zh_Hans: 超时时间
description:
en_US: Request timeout in seconds
zh_Hans: 请求超时时间(秒)
type: integer
required: false
default: 120
- name: base-prompt
label:
en_US: Base Prompt
zh_Hans: 基础提示词
description:
en_US: Default prompt when user message is empty (e.g. only images)
zh_Hans: 当用户消息为空(例如仅图片)时使用的默认提示词
type: string
required: false
default: '请回答用户的问题。'
- name: deerflow-api
label:
en_US: DeerFlow API
zh_Hans: DeerFlow API
description:
en_US: Configure the DeerFlow LangGraph API of the pipeline
zh_Hans: 配置 DeerFlow LangGraph API
config:
- name: api-base
label:
en_US: API Base URL
zh_Hans: API 基础 URL
description:
en_US: The base URL of the DeerFlow server (e.g. http://127.0.0.1:2026)
zh_Hans: DeerFlow 服务器的基础 URL例如 http://127.0.0.1:2026
type: string
required: true
default: 'http://127.0.0.1:2026'
- name: api-key
label:
en_US: API Key
zh_Hans: API 密钥
description:
en_US: Optional API key for DeerFlow (leave empty if not required)
zh_Hans: DeerFlow 的 API 密钥(如果不需要可留空)
type: string
required: false
default: ''
- name: auth-header
label:
en_US: Auth Header Name
zh_Hans: 鉴权请求头名称
description:
en_US: Custom auth header name. Leave empty to use "x-api-key"
zh_Hans: 自定义鉴权请求头名称,留空则使用 "x-api-key"
type: string
required: false
default: ''
- name: assistant-id
label:
en_US: Assistant ID
zh_Hans: 助手 ID
description:
en_US: The DeerFlow assistant/graph id (default lead_agent)
zh_Hans: DeerFlow 助手/图 ID默认 lead_agent
type: string
required: true
default: 'lead_agent'
- name: model-name
label:
en_US: Model Name
zh_Hans: 模型名称
description:
en_US: Optional model override forwarded to DeerFlow configurable
zh_Hans: 可选的模型名称覆盖,会作为 configurable 转发给 DeerFlow
type: string
required: false
default: ''
- name: thinking-enabled
label:
en_US: Enable Thinking
zh_Hans: 启用思考
description:
en_US: Whether to enable DeerFlow thinking mode
zh_Hans: 是否启用 DeerFlow 思考模式
type: boolean
required: false
default: false
- name: plan-mode
label:
en_US: Plan Mode
zh_Hans: 规划模式
description:
en_US: Whether to enable DeerFlow plan mode
zh_Hans: 是否启用 DeerFlow 规划模式
type: boolean
required: false
default: false
- name: subagent-enabled
label:
en_US: Enable Subagents
zh_Hans: 启用子代理
description:
en_US: Whether to enable parallel subagent execution
zh_Hans: 是否启用并行子代理执行
type: boolean
required: false
default: false
- name: max-concurrent-subagents
label:
en_US: Max Concurrent Subagents
zh_Hans: 最大并发子代理数
description:
en_US: Maximum number of concurrent subagents (only effective when subagents are enabled)
zh_Hans: 最大并发子代理数(仅在启用子代理时生效)
type: integer
required: false
default: 3
- name: timeout
label:
en_US: Timeout
zh_Hans: 超时时间
description:
en_US: Request timeout in seconds (DeerFlow runs may take a long time)
zh_Hans: 请求超时时间DeerFlow 运行可能耗时较长
type: integer
required: false
default: 300
- name: recursion-limit
label:
en_US: Recursion Limit
zh_Hans: 递归上限
description:
en_US: LangGraph recursion limit for a single run
zh_Hans: 单次运行的 LangGraph 递归上限
type: integer
required: false
default: 1000

View File

@@ -104,7 +104,7 @@ class TestSQLiteMigrationUpgrade:
rev = await get_alembic_current(sqlite_engine)
assert rev is not None, "Expected a revision after upgrade"
# Head should be the latest migration
assert rev.startswith('0003'), f"Expected head to be 0003_*, got {rev}"
assert rev.startswith('0004'), f"Expected head to be 0004_*, got {rev}"
@pytest.mark.asyncio
async def test_upgrade_idempotent(self, sqlite_engine):

View File

@@ -150,8 +150,8 @@ class TestPostgreSQLMigrationUpgrade:
# Verify revision
rev = await get_alembic_current(postgres_engine)
assert rev is not None, "Expected a revision after upgrade"
# Head should be the latest migration (0003 for current state)
assert rev.startswith('0003'), f"Expected head to be 0003_*, got {rev}"
# Head should be the latest migration (0004 for current state)
assert rev.startswith('0004'), f"Expected head to be 0004_*, got {rev}"
@pytest.mark.asyncio
async def test_postgres_upgrade_idempotent(

View File

@@ -190,6 +190,66 @@ async def test_box_service_without_explicit_client_initializes_internal_connecto
connector.initialize.assert_awaited_once()
class TestSharesFilesystemWithBox:
"""``shares_filesystem_with_box`` must reflect the real LangBot<->Box
filesystem topology, which is derived from the connector transport:
- stdio (local child process) → shared filesystem → True
- WebSocket (Docker / sidecar / --standalone-box / remote) → separated → False
This drives whether LangBot validates Box-reported skill paths locally.
Getting it wrong silently drops every skill in separated deployments.
"""
def test_true_for_stdio_connector(self, monkeypatch: pytest.MonkeyPatch):
# Non-Docker Unix, no endpoint, not standalone → stdio transport.
monkeypatch.setattr('langbot.pkg.utils.platform.get_platform', lambda: 'linux')
monkeypatch.setattr('langbot.pkg.utils.platform.standalone_box', False)
service = BoxService(make_app(Mock()))
assert service._runtime_connector is not None
assert service._runtime_connector.uses_websocket() is False
assert service.shares_filesystem_with_box is True
def test_false_for_websocket_connector_via_endpoint(self, monkeypatch: pytest.MonkeyPatch):
monkeypatch.setattr('langbot.pkg.utils.platform.get_platform', lambda: 'linux')
monkeypatch.setattr('langbot.pkg.utils.platform.standalone_box', False)
app = make_app(Mock())
app.instance_config.data['box']['runtime']['endpoint'] = 'ws://pod-x-box:5410'
service = BoxService(app)
assert service._runtime_connector is not None
assert service._runtime_connector.uses_websocket() is True
assert service.shares_filesystem_with_box is False
def test_false_for_websocket_connector_in_docker(self, monkeypatch: pytest.MonkeyPatch):
monkeypatch.setattr('langbot.pkg.utils.platform.get_platform', lambda: 'docker')
monkeypatch.setattr('langbot.pkg.utils.platform.standalone_box', False)
service = BoxService(make_app(Mock()))
assert service.shares_filesystem_with_box is False
def test_false_when_client_injected_without_connector(self):
# Injected client (no connector) → unknown topology → conservative False
# so LangBot never wrongly drops Box-reported skills.
service = BoxService(make_app(Mock()), client=Mock(spec=BoxRuntimeClient))
assert service._runtime_connector is None
assert service.shares_filesystem_with_box is False
def test_explicit_override_wins(self):
service = BoxService(make_app(Mock()), client=Mock(spec=BoxRuntimeClient))
service._shares_filesystem_with_box_override = True
assert service.shares_filesystem_with_box is True
service._shares_filesystem_with_box_override = False
assert service.shares_filesystem_with_box is False
@pytest.mark.asyncio
async def test_box_service_get_sessions_delegates_to_client():
client = Mock()
@@ -1342,11 +1402,16 @@ class TestBuildSkillExtraMounts:
the backend never sees a bad mount.
"""
def _make_service(self, logger, skills):
def _make_service(self, logger, skills, *, shares_filesystem=True):
app = make_app(logger)
app.skill_mgr = SimpleNamespace(skills=skills)
client = Mock(spec=BoxRuntimeClient)
return BoxService(app, client=client)
service = BoxService(app, client=client)
# Tests construct BoxService with an injected client (no connector), so
# set the topology explicitly. Most cases exercise the shared-fs (local
# stdio) path where local package_root validation applies.
service._shares_filesystem_with_box_override = shares_filesystem
return service
def test_skips_skill_with_missing_package_root(self):
logger = Mock()
@@ -1373,6 +1438,30 @@ class TestBuildSkillExtraMounts:
for call in logger.warning.call_args_list
)
def test_trusts_box_paths_when_filesystem_not_shared(self):
"""In separated deployments (Docker Compose, k8s sidecar,
--standalone-box, remote endpoint) the Box runtime owns its own
filesystem. package_root values it reports are NOT resolvable on the
LangBot side, so LangBot must trust them rather than dropping every
skill via a local isdir() check."""
logger = Mock()
skills = {
'a': {'name': 'a', 'package_root': '/box/skills/a'},
'b': {'name': 'b', 'package_root': '/box/skills/b'},
}
service = self._make_service(logger, skills, shares_filesystem=False)
mounts = service.build_skill_extra_mounts(make_query())
assert mounts == [
{'host_path': '/box/skills/a', 'mount_path': '/workspace/.skills/a', 'mode': 'rw'},
{'host_path': '/box/skills/b', 'mount_path': '/workspace/.skills/b', 'mode': 'rw'},
]
# No skill is dropped, so no "missing" warning should be logged.
assert not any(
'package_root missing' in str(call.args[0]) for call in logger.warning.call_args_list
)
def test_skips_skill_with_empty_package_root(self):
logger = Mock()
skills = {
@@ -1383,6 +1472,14 @@ class TestBuildSkillExtraMounts:
assert service.build_skill_extra_mounts(make_query()) == []
def test_empty_package_root_skipped_even_when_not_shared(self):
"""An empty package_root is always invalid regardless of topology."""
logger = Mock()
skills = {'no_root': {'name': 'no_root', 'package_root': ''}}
service = self._make_service(logger, skills, shares_filesystem=False)
assert service.build_skill_extra_mounts(make_query()) == []
def test_returns_empty_when_no_skill_manager(self):
logger = Mock()
app = make_app(logger)

View File

@@ -62,15 +62,17 @@ class TestSkillManagerCache:
@pytest.mark.asyncio
async def test_reload_skills_drops_box_skills_with_missing_package_root(self):
"""When Box reports a skill whose package_root is gone from the
LangBot-visible filesystem, the cache must drop it instead of
keeping a stale entry that would later produce a bad mount."""
"""When LangBot shares a filesystem with Box (local stdio mode) and Box
reports a skill whose package_root is gone from that shared filesystem,
the cache must drop it instead of keeping a stale entry that would later
produce a bad mount."""
from langbot.pkg.skill.manager import SkillManager
with tempfile.TemporaryDirectory() as live_dir:
ghost_dir = os.path.join(live_dir, '_does_not_exist')
box_service = SimpleNamespace(
available=True,
shares_filesystem_with_box=True,
list_skills=AsyncMock(
return_value=[
_make_skill_data(name='alive', package_root=live_dir),
@@ -90,6 +92,37 @@ class TestSkillManagerCache:
warning_messages = [str(call.args[0]) for call in ap.logger.warning.call_args_list]
assert any('ghost' in msg and 'package_root missing' in msg for msg in warning_messages)
@pytest.mark.asyncio
async def test_reload_skills_trusts_box_paths_when_filesystem_not_shared(self):
"""In separated deployments (Docker Compose, k8s sidecar,
--standalone-box, remote endpoint) the package_root reported by Box
lives on the Box runtime's filesystem and is not resolvable on the
LangBot side. The cache must keep every Box-reported skill rather than
dropping them all via a local isdir() check."""
from langbot.pkg.skill.manager import SkillManager
box_service = SimpleNamespace(
available=True,
shares_filesystem_with_box=False,
list_skills=AsyncMock(
return_value=[
_make_skill_data(name='alpha', package_root='/box/skills/alpha'),
_make_skill_data(name='beta', package_root='/box/skills/beta'),
]
),
)
ap = _make_ap()
ap.box_service = box_service
mgr = SkillManager(ap)
await mgr.reload_skills()
assert sorted(mgr.skills) == ['alpha', 'beta']
# No skill dropped → no "package_root missing" warning.
warning_messages = [str(call.args[0]) for call in ap.logger.warning.call_args_list]
assert not any('package_root missing' in msg for msg in warning_messages)
class TestSkillActivationHelper:
"""Skill activation is now Tool-Call based.

521
uv.lock generated
View File

@@ -55,7 +55,7 @@ wheels = [
[[package]]
name = "aiohttp"
version = "3.13.5"
version = "3.14.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aiohappyeyeballs" },
@@ -64,95 +64,111 @@ dependencies = [
{ name = "frozenlist" },
{ name = "multidict" },
{ name = "propcache" },
{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
{ name = "yarl" },
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2225
web/package-lock.json generated

File diff suppressed because it is too large Load Diff

View File

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118
web/pnpm-lock.yaml generated
View File

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resolution: {integrity: sha512-2G3ajSVSZMEtmTjIklRWlNvo8wICEpLihfD/0YMDxbWK2UyP5EGfnoIn9AIQGnF3G/FX0MRbHXdFcD+rL1ZreQ==}
/react-router-dom@7.17.0(react-dom@19.2.1)(react@19.2.1):
resolution: {integrity: sha512-fyU2yjGups/hE6Xz0I5ZYbVL8Gx29eCjgpHaRaTaVU+OOAdfRX05KsvyRm0GO8YQwOkhpU3MurW1jyMUJn+zSw==}
engines: {node: '>=20.0.0'}
peerDependencies:
react: '>=18'
@@ -5103,11 +5139,11 @@ packages:
dependencies:
react: 19.2.1
react-dom: 19.2.1(react@19.2.1)
react-router: 7.14.0(react-dom@19.2.1)(react@19.2.1)
react-router: 7.17.0(react-dom@19.2.1)(react@19.2.1)
dev: false
/react-router@7.14.0(react-dom@19.2.1)(react@19.2.1):
resolution: {integrity: sha512-m/xR9N4LQLmAS0ZhkY2nkPA1N7gQ5TUVa5n8TgANuDTARbn1gt+zLPXEm7W0XDTbrQ2AJSJKhoa6yx1D8BcpxQ==}
/react-router@7.17.0(react-dom@19.2.1)(react@19.2.1):
resolution: {integrity: sha512-FDELK7rTMlCHO5+reyXsPlmfr7N1F91lPHsWYfMEGQm/KQ+F4JFM8jGoeQDmDvdTs93Fw9aSilH+uKRb4/jXvQ==}
engines: {node: '>=20.0.0'}
peerDependencies:
react: '>=18'
@@ -6053,7 +6089,7 @@ packages:
'@types/node': 20.19.30
lightningcss: 1.32.0
picomatch: 4.0.4
postcss: 8.5.8
postcss: 8.5.15
rolldown: 1.0.0-rc.15
tinyglobby: 0.2.15
optionalDependencies:

View File

@@ -0,0 +1,9 @@
import { Outlet } from 'react-router-dom';
import { useDocumentTitle } from '@/hooks/useDocumentTitle';
// Top-level route layout: drives the dynamic document title from the active
// route and renders the matched child route via <Outlet />.
export default function RootLayout() {
useDocumentTitle();
return <Outlet />;
}

View File

@@ -184,13 +184,21 @@ function AddExtensionContent() {
const cloud = getCloudServiceClientSync();
const a = installInfo.plugin_author || '';
const n = installInfo.plugin_name || '';
if (installExtensionType === 'mcp')
return cloud.getMCPMarketplaceIconURL(a, n);
if (installExtensionType === 'skill')
return cloud.getSkillMarketplaceIconURL(a, n);
return cloud.getPluginIconURL(a, n);
return cloud.resolveMarketplaceIconURL(
installExtensionType,
a,
n,
installInfo.plugin_icon,
);
})();
// When the resolved icon URL changes (e.g. the real external icon arrives
// after an async fetch), clear any prior load failure so the <img> retries
// instead of staying on the placeholder.
useEffect(() => {
setInstallIconFailed(false);
}, [installIconURL]);
const [popoverOpen, setPopoverOpen] = useState(false);
const [popoverView, setPopoverView] = useState<PopoverView>('menu');
const [isDragOver, setIsDragOver] = useState(false);
@@ -278,6 +286,23 @@ function AddExtensionContent() {
setInstallIconFailed(false);
setModalOpen(true);
// The icon is not carried in the URL params, so fetch it from the
// marketplace record. Without this the confirm dialog falls back to the
// /resources/icon endpoint, which 404s for extensions whose icon is an
// external URL (simpleicons / iconify), showing a placeholder.
const cloud = getCloudServiceClientSync();
cloud
.fetchMarketplaceIcon(extType, author, name)
.then((icon) => {
if (!icon) return;
setInstallInfo((prev) =>
prev.plugin_author === author && prev.plugin_name === name
? { ...prev, plugin_icon: icon }
: prev,
);
})
.catch(() => {});
setSearchParams(
(current) => {
const next = new URLSearchParams(current);
@@ -326,6 +351,7 @@ function AddExtensionContent() {
plugin_version: plugin.latest_version,
plugin_label: extractI18nObject(plugin.label) || plugin.name,
plugin_description: extractI18nObject(plugin.description) || '',
plugin_icon: plugin.icon || '',
});
setInstallExtensionType(plugin.type || 'plugin');
setPluginInstallStatus(PluginInstallStatus.ASK_CONFIRM);

View File

@@ -119,6 +119,22 @@ function compareVersions(v1: string, v2: string): boolean {
return false;
}
// Discord brand glyph (lucide-react has no Discord icon).
function DiscordIcon({ className }: { className?: string }) {
return (
<svg
role="img"
viewBox="0 0 24 24"
fill="currentColor"
xmlns="http://www.w3.org/2000/svg"
className={className}
aria-hidden="true"
>
<path d="M20.317 4.3698a19.7913 19.7913 0 00-4.8851-1.5152.0741.0741 0 00-.0785.0371c-.211.3753-.4447.8648-.6083 1.2495-1.8447-.2762-3.68-.2762-5.4868 0-.1636-.3933-.4058-.8742-.6177-1.2495a.077.077 0 00-.0785-.037 19.7363 19.7363 0 00-4.8852 1.515.0699.0699 0 00-.0321.0277C.5334 9.0458-.319 13.5799.0992 18.0578a.0824.0824 0 00.0312.0561c2.0528 1.5076 4.0413 2.4228 5.9929 3.0294a.0777.0777 0 00.0842-.0276c.4616-.6304.8731-1.2952 1.226-1.9942a.076.076 0 00-.0416-.1057c-.6528-.2476-1.2743-.5495-1.8722-.8923a.077.077 0 01-.0076-.1277c.1258-.0943.2517-.1923.3718-.2914a.0743.0743 0 01.0776-.0105c3.9278 1.7933 8.18 1.7933 12.0614 0a.0739.0739 0 01.0785.0095c.1202.099.246.1981.3728.2924a.077.077 0 01-.0066.1276 12.2986 12.2986 0 01-1.873.8914.0766.0766 0 00-.0407.1067c.3604.698.7719 1.3628 1.225 1.9932a.076.076 0 00.0842.0286c1.961-.6067 3.9495-1.5219 6.0023-3.0294a.077.077 0 00.0313-.0552c.5004-5.177-.8382-9.6739-3.5485-13.6604a.061.061 0 00-.0312-.0286zM8.02 15.3312c-1.1825 0-2.1569-1.0857-2.1569-2.419 0-1.3332.9555-2.4189 2.157-2.4189 1.2108 0 2.1757 1.0952 2.1568 2.419 0 1.3332-.9555 2.4189-2.1569 2.4189zm7.9748 0c-1.1825 0-2.1569-1.0857-2.1569-2.419 0-1.3332.9554-2.4189 2.1569-2.4189 1.2108 0 2.1757 1.0952 2.1568 2.419 0 1.3332-.946 2.4189-2.1568 2.4189Z" />
</svg>
);
}
// IDs of sidebar entries that have collapsible entity sub-items
const ENTITY_CATEGORY_IDS = [
'bots',
@@ -2077,6 +2093,14 @@ export default function HomeSidebar({
</Badge>
)}
</DropdownMenuItem>
<DropdownMenuItem
onClick={() => {
window.open('https://discord.gg/wdNEHETs87', '_blank');
}}
>
<DiscordIcon className="text-[#5865F2]" />
{t('common.joinDiscord')}
</DropdownMenuItem>
</DropdownMenuGroup>
<DropdownMenuSeparator />

View File

@@ -42,6 +42,7 @@ import {
PluginInstallTaskProvider,
PluginInstallProgressDialog,
} from '@/app/home/plugins/components/plugin-install-task';
import { setDocumentTitle } from '@/hooks/useDocumentTitle';
// Routes that belong to the "Extensions" section
const EXTENSIONS_ROUTES = [
@@ -52,6 +53,28 @@ const EXTENSIONS_ROUTES = [
'/home/plugin-pages',
];
// Map a /home route to the i18n key for its type-level title. Used as a robust
// fallback for the document title on direct page loads, before the sidebar's
// onSelectedChange has populated the local `title` state. Detail routes reuse
// the section key (prefix match), e.g. /home/mcp?id=... -> mcp.title.
const HOME_TITLE_KEYS: { match: (path: string) => boolean; key: string }[] = [
{ match: (p) => p.startsWith('/home/monitoring'), key: 'monitoring.title' },
{ match: (p) => p.startsWith('/home/bots'), key: 'bots.title' },
{ match: (p) => p.startsWith('/home/pipelines'), key: 'pipelines.title' },
{
match: (p) => p.startsWith('/home/add-extension'),
key: 'sidebar.addExtension',
},
{ match: (p) => p.startsWith('/home/extensions'), key: 'plugins.title' },
{ match: (p) => p.startsWith('/home/mcp'), key: 'mcp.title' },
{ match: (p) => p.startsWith('/home/knowledge'), key: 'knowledge.title' },
{ match: (p) => p.startsWith('/home/skills'), key: 'skills.title' },
{
match: (p) => p.startsWith('/home/plugin-pages'),
key: 'sidebar.pluginPages',
},
];
function isExtensionsRoute(pathname: string): boolean {
return EXTENSIONS_ROUTES.some(
(route) => pathname === route || pathname.startsWith(route + '/'),
@@ -147,6 +170,20 @@ function HomeLayoutInner({ children }: { children: React.ReactNode }) {
: t('sidebar.home');
const sectionLink = isExtensions ? '/home/extensions' : '/home/monitoring';
// Drive the browser tab title for the /home section. The type-level label
// prefers the sidebar-provided `title`, falling back to a route-derived key on
// direct page loads. When a sub-entity (plugin / MCP / pipeline / KB / skill)
// is open, its name is prepended: "<entity> · <type> · LangBot".
useEffect(() => {
const routeEntry = HOME_TITLE_KEYS.find((e) => e.match(pathname));
const fallbackType =
routeEntry && t(routeEntry.key) !== routeEntry.key
? t(routeEntry.key)
: null;
const typeLabel = title || fallbackType;
setDocumentTitle(detailEntityName, typeLabel);
}, [pathname, title, detailEntityName, t]);
return (
<SidebarProvider>
<Suspense fallback={<div />}>

View File

@@ -40,6 +40,8 @@ import {
CardTitle,
} from '@/components/ui/card';
import { httpClient } from '@/app/infra/http/HttpClient';
import { Tabs, TabsContent, TabsList, TabsTrigger } from '@/components/ui/tabs';
import MCPReadme from '@/app/home/mcp/components/mcp-form/MCPReadme';
import {
MCPServerRuntimeInfo,
MCPTool,
@@ -264,35 +266,10 @@ function RuntimePanel({
const isConnected =
!mcpTesting && runtimeInfo.status === MCPSessionStatus.CONNECTED;
// Only treat an explicit error (or box-unavailable) as failed; while testing,
// connecting, or in an initial/unresolved state, show "connecting" so we
// don't flash "connection failed" during a normal connection attempt.
const isFailed =
!mcpTesting &&
(runtimeInfo.status === MCPSessionStatus.ERROR ||
runtimeInfo.error_phase === 'box_unavailable');
const tools = runtimeInfo.tools || [];
return (
<section className="space-y-4">
<div className="flex flex-wrap items-start justify-between gap-2">
<div className="space-y-1">
<h3 className="text-sm font-medium">{t('mcp.title')}</h3>
<p className="text-sm text-muted-foreground">
{isConnected
? t('mcp.toolCount', { count: tools.length })
: isFailed
? t('mcp.connectionFailedStatus')
: t('mcp.connecting')}
</p>
</div>
{isConnected && (
<Badge variant="outline">
{t('mcp.toolCount', { count: tools.length })}
</Badge>
)}
</div>
{!isConnected && (
<div className="rounded-md bg-muted/40 p-3">
<StatusDisplay testing={mcpTesting} runtimeInfo={runtimeInfo} t={t} />
@@ -434,6 +411,9 @@ const MCPForm = forwardRef<MCPFormHandle, MCPFormProps>(function MCPForm(
const [runtimeInfo, setRuntimeInfo] = useState<MCPServerRuntimeInfo | null>(
null,
);
// README markdown captured from LangBot Space at install time, surfaced in
// the Docs tab of the detail panel. Empty for manually-created servers.
const [readme, setReadme] = useState<string>('');
const pollingIntervalRef = useRef<NodeJS.Timeout | null>(null);
const watchMode = form.watch('mode');
const {
@@ -611,6 +591,7 @@ const MCPForm = forwardRef<MCPFormHandle, MCPFormProps>(function MCPForm(
setStdioArgs(newStdioArgs);
form.reset(formValues);
setRuntimeInfo(server.runtime_info ?? null);
setReadme(server.readme ?? '');
} catch (error) {
console.error('Failed to load server:', error);
toast.error(t('mcp.loadFailed'));
@@ -1063,6 +1044,42 @@ const MCPForm = forwardRef<MCPFormHandle, MCPFormProps>(function MCPForm(
/>
);
// In edit mode the right side shows a tablist switching between the live
// Tools list and the Docs (README captured from LangBot Space at install).
// Create mode has neither, so it falls back to the bare runtime placeholder.
// The tool count lives in the tab label (only when connected); the panel
// body itself no longer repeats a title/subtitle.
const toolsConnected =
!mcpTesting && runtimeInfo?.status === MCPSessionStatus.CONNECTED;
const toolsCount = runtimeInfo?.tools?.length ?? 0;
const toolsTabLabel = toolsConnected
? `${t('mcp.tabTools')} ${toolsCount}`
: t('mcp.tabTools');
const detailPanel = isEditMode ? (
<Tabs defaultValue="tools" className="flex h-full min-h-0 flex-col">
<TabsList>
<TabsTrigger value="docs" className="flex-none px-4">
{t('mcp.tabDocs')}
</TabsTrigger>
<TabsTrigger value="tools" className="flex-none px-4">
{toolsTabLabel}
</TabsTrigger>
</TabsList>
<TabsContent value="docs" className="mt-4 min-h-0 flex-1 overflow-y-auto">
<MCPReadme readme={readme} />
</TabsContent>
<TabsContent
value="tools"
className="mt-4 min-h-0 flex-1 overflow-y-auto"
>
{runtimePanel}
</TabsContent>
</Tabs>
) : (
runtimePanel
);
if (layout === 'split') {
return (
<Form {...form}>
@@ -1078,7 +1095,7 @@ const MCPForm = forwardRef<MCPFormHandle, MCPFormProps>(function MCPForm(
</div>
<div className="hidden w-px shrink-0 bg-border lg:block" />
<div className="min-w-0 flex-1 pb-6 lg:min-h-0 lg:overflow-y-auto lg:overflow-x-hidden">
{runtimePanel}
{detailPanel}
</div>
</form>
</Form>
@@ -1093,7 +1110,7 @@ const MCPForm = forwardRef<MCPFormHandle, MCPFormProps>(function MCPForm(
className="space-y-5"
>
{sideHeader}
{runtimePanel}
{detailPanel}
{configSection}
{sideFooter}
</form>

View File

@@ -0,0 +1,79 @@
import ReactMarkdown from 'react-markdown';
import remarkGfm from 'remark-gfm';
import rehypeRaw from 'rehype-raw';
import rehypeSanitize from 'rehype-sanitize';
import rehypeHighlight from 'rehype-highlight';
import rehypeSlug from 'rehype-slug';
import rehypeAutolinkHeadings from 'rehype-autolink-headings';
import { useTranslation } from 'react-i18next';
import '@/styles/github-markdown.css';
/**
* Renders the README markdown captured from LangBot Space at install time.
* The README is stored on the MCP server record (``server.readme``) so this
* works offline and regardless of the server's runtime/connection state.
*
* MCP marketplace READMEs reference images by absolute URL (the upstream repo),
* so — unlike plugin READMEs — no asset-path rewriting is needed here.
*/
export default function MCPReadme({ readme }: { readme?: string }) {
const { t } = useTranslation();
if (!readme || !readme.trim()) {
return (
<div className="flex min-h-[220px] items-center justify-center rounded-lg border border-dashed text-sm text-muted-foreground">
{t('mcp.noReadme')}
</div>
);
}
return (
<div className="w-full overflow-auto">
<div className="markdown-body max-w-none p-1 pt-0">
<ReactMarkdown
remarkPlugins={[remarkGfm]}
rehypePlugins={[
rehypeRaw,
rehypeSanitize,
rehypeHighlight,
rehypeSlug,
[
rehypeAutolinkHeadings,
{
behavior: 'wrap',
properties: {
className: ['anchor'],
},
},
],
]}
components={{
ul: ({ children }) => <ul className="list-disc">{children}</ul>,
ol: ({ children }) => <ol className="list-decimal">{children}</ol>,
li: ({ children }) => <li className="ml-4">{children}</li>,
a: ({ children, href, ...props }) => (
<a
href={href}
target="_blank"
rel="noopener noreferrer"
{...props}
>
{children}
</a>
),
img: ({ src, alt, ...props }) => (
<img
src={src}
alt={alt || ''}
className="my-4 h-auto max-w-full rounded-lg"
{...props}
/>
),
}}
>
{readme}
</ReactMarkdown>
</div>
</div>
);
}

View File

@@ -11,7 +11,7 @@ import {
Download,
Package,
Server,
BookOpen,
Sparkles,
CheckCircle2,
XCircle,
Loader2,
@@ -176,7 +176,7 @@ function TaskProgressContent({ task }: { task: PluginInstallTask }) {
// MCP / Skill don't have the plugin's download + dependency-install stages;
// show a single "installing → done/failed" row instead of plugin steps.
const isPlugin = task.extensionType === 'plugin';
const simpleIcon = task.extensionType === 'mcp' ? Server : BookOpen;
const simpleIcon = task.extensionType === 'mcp' ? Server : Sparkles;
const simpleInstallingLabel =
task.extensionType === 'mcp'
? t('addExtension.installStage.mcpInstalling')

View File

@@ -9,9 +9,9 @@ import {
Loader2,
X,
ListTodo,
Wrench,
AudioWaveform,
Book,
Puzzle,
Server,
Sparkles,
} from 'lucide-react';
import { Button } from '@/components/ui/button';
import {
@@ -35,9 +35,9 @@ const STAGE_ICONS: Record<string, React.ElementType> = {
};
const EXTENSION_TYPE_ICONS: Record<string, React.ElementType> = {
plugin: Wrench,
mcp: AudioWaveform,
skill: Book,
plugin: Puzzle,
mcp: Server,
skill: Sparkles,
};
function TaskQueueItem({
@@ -54,7 +54,7 @@ function TaskQueueItem({
const isError = task.stage === InstallStage.ERROR;
const isRunning = !isDone && !isError;
const StageIcon = STAGE_ICONS[task.stage] || Download;
const TypeIcon = EXTENSION_TYPE_ICONS[task.extensionType] || Wrench;
const TypeIcon = EXTENSION_TYPE_ICONS[task.extensionType] || Puzzle;
const getTypeBadgeClass = () => {
switch (task.extensionType) {

View File

@@ -21,8 +21,7 @@ import { extractI18nObject } from '@/i18n/I18nProvider';
import { toast } from 'sonner';
import { useAsyncTask, AsyncTaskStatus } from '@/hooks/useAsyncTask';
import { useSidebarData } from '@/app/home/components/home-sidebar/SidebarDataContext';
import { Loader2, Puzzle } from 'lucide-react';
import { Wrench, AudioWaveform, Book } from 'lucide-react';
import { Loader2, Puzzle, Server, Sparkles } from 'lucide-react';
export interface PluginInstalledComponentRef {
refreshPluginList: () => void;
@@ -44,14 +43,18 @@ export const FilterOptions = [
{
value: 'plugin' as FilterType,
labelKey: 'market.typePlugin',
icon: Wrench,
icon: Puzzle,
},
{
value: 'mcp' as FilterType,
labelKey: 'market.typeMCP',
icon: AudioWaveform,
icon: Server,
},
{
value: 'skill' as FilterType,
labelKey: 'market.typeSkill',
icon: Sparkles,
},
{ value: 'skill' as FilterType, labelKey: 'market.typeSkill', icon: Book },
];
interface PluginInstalledComponentProps {

View File

@@ -17,6 +17,9 @@ import { Separator } from '@/components/ui/separator';
import { ToggleGroup, ToggleGroupItem } from '@/components/ui/toggle-group';
import {
Search,
Puzzle,
Server,
Sparkles,
Wrench,
AudioWaveform,
Hash,
@@ -88,9 +91,9 @@ function MarketPageContent({
const extensionTypeOptions = [
{ value: 'all', label: t('market.filters.allFormats'), icon: null },
{ value: 'plugin', label: t('market.typePlugin'), icon: Wrench },
{ value: 'mcp', label: t('market.typeMCP'), icon: AudioWaveform },
{ value: 'skill', label: t('market.typeSkill'), icon: Book },
{ value: 'plugin', label: t('market.typePlugin'), icon: Puzzle },
{ value: 'mcp', label: t('market.typeMCP'), icon: Server },
{ value: 'skill', label: t('market.typeSkill'), icon: Sparkles },
];
const [searchQuery, setSearchQuery] = useState('');
@@ -121,6 +124,8 @@ function MarketPageContent({
const [hasMore, setHasMore] = useState(true);
const [currentPage, setCurrentPage] = useState(1);
const [total, setTotal] = useState(0);
// Per-format extension counts shown next to the type filter options.
const [typeCounts, setTypeCounts] = useState<Record<string, number>>({});
const [sortOption, setSortOption] = useState<string>(
() => loadMarketFilters().sortOption ?? 'install_count_desc',
);
@@ -142,7 +147,7 @@ function MarketPageContent({
}
}, [typeFilter, componentFilter, selectedTags, sortOption]);
const pageSize = 12; // 每页12个
const pageSize = 24; // 每页24
const searchTimeoutRef = useRef<NodeJS.Timeout | null>(null);
const scrollContainerRef = useRef<HTMLDivElement | null>(null);
const isComposingRef = useRef(false);
@@ -213,12 +218,12 @@ function MarketPageContent({
const transformToVO = useCallback(
(plugin: PluginV4): PluginMarketCardVO => {
const cloudClient = getCloudServiceClientSync();
const iconURL =
plugin.type === 'mcp'
? cloudClient.getMCPMarketplaceIconURL(plugin.author, plugin.name)
: plugin.type === 'skill'
? cloudClient.getSkillMarketplaceIconURL(plugin.author, plugin.name)
: cloudClient.getPluginIconURL(plugin.author, plugin.name);
const iconURL = cloudClient.resolveMarketplaceIconURL(
plugin.type,
plugin.author,
plugin.name,
plugin.icon,
);
return new PluginMarketCardVO({
pluginId: plugin.author + ' / ' + plugin.name,
@@ -317,6 +322,7 @@ function MarketPageContent({
fetchPlugins(1, false, true);
fetchAvailableTags();
fetchRecommendationLists();
fetchTypeCounts();
})();
// eslint-disable-next-line react-hooks/exhaustive-deps
}, []);
@@ -356,6 +362,32 @@ function MarketPageContent({
}
};
// 获取各扩展格式的数量(用于筛选器标签上的计数)
const fetchTypeCounts = async () => {
const types = ['plugin', 'mcp', 'skill'];
try {
const results = await Promise.all(
types.map((type) =>
getCloudServiceClientSync()
.searchMarketplaceExtensions({
page: 1,
page_size: 1,
type_filter: type,
})
.then((res) => res.total)
.catch(() => 0),
),
);
const counts: Record<string, number> = {};
types.forEach((type, i) => {
counts[type] = results[i];
});
setTypeCounts(counts);
} catch (error) {
console.error('Failed to fetch extension type counts:', error);
}
};
// 搜索功能
const handleSearch = useCallback(
(query: string) => {
@@ -600,7 +632,11 @@ function MarketPageContent({
<div className="relative min-w-0 flex-1 lg:max-w-xl">
<Search className="absolute left-3 top-1/2 transform -translate-y-1/2 text-muted-foreground h-4 w-4" />
<Input
placeholder={t('market.searchPlaceholder')}
placeholder={
total > 0
? t('market.searchPlaceholderCount', { count: total })
: t('market.searchPlaceholder')
}
value={searchQuery}
onChange={(e) => handleSearchInputChange(e.target.value)}
onCompositionStart={() => {
@@ -679,6 +715,7 @@ function MarketPageContent({
>
{extensionTypeOptions.map((option) => {
const Icon = option.icon;
const count = typeCounts[option.value];
return (
<ToggleGroupItem
key={option.value}
@@ -688,6 +725,11 @@ function MarketPageContent({
>
{Icon && <Icon className="mr-1 h-3.5 w-3.5" />}
{option.label}
{typeof count === 'number' && (
<span className="ml-1 text-muted-foreground">
({count})
</span>
)}
</ToggleGroupItem>
);
})}
@@ -778,15 +820,6 @@ function MarketPageContent({
);
})}
</div>
{/* 搜索结果统计 */}
{total > 0 && (
<div className="text-center text-muted-foreground text-sm">
{searchQuery
? t('market.searchResults', { count: total })
: t('market.totalPlugins', { count: total })}
</div>
)}
</div>
{/* Scrollable extension list section */}
@@ -825,7 +858,7 @@ function MarketPageContent({
</div>
) : (
<>
<div className="grid grid-cols-[repeat(auto-fit,minmax(min(100%,22rem),1fr))] gap-6 mt-6">
<div className="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 2xl:grid-cols-4 gap-6 mt-6">
{visiblePlugins.map((plugin) => (
<PluginMarketCardComponent
key={plugin.pluginId}
@@ -846,7 +879,9 @@ function MarketPageContent({
{/* No more data hint */}
{!hasMore && plugins.length > 0 && (
<div className="text-center text-muted-foreground py-6">
{t('market.allLoaded')}
{searchQuery
? t('market.allLoadedCount', { count: total })
: t('market.allLoaded')}
{' · '}
<a
href="https://github.com/langbot-app/langbot-plugin-demo/issues/new?template=plugin-request.yml"

View File

@@ -23,13 +23,14 @@ function pluginToVO(
t: (key: string) => string,
): PluginMarketCardVO {
const cloudClient = getCloudServiceClientSync();
// Recommendation lists are mixed-type; resolve the icon per extension type.
const iconURL =
plugin.type === 'mcp'
? cloudClient.getMCPMarketplaceIconURL(plugin.author, plugin.name)
: plugin.type === 'skill'
? cloudClient.getSkillMarketplaceIconURL(plugin.author, plugin.name)
: cloudClient.getPluginIconURL(plugin.author, plugin.name);
// Recommendation lists are mixed-type; resolve the icon per extension type,
// preferring an absolute external icon URL when the record carries one.
const iconURL = cloudClient.resolveMarketplaceIconURL(
plugin.type,
plugin.author,
plugin.name,
plugin.icon,
);
return new PluginMarketCardVO({
pluginId: plugin.author + ' / ' + plugin.name,

View File

@@ -94,7 +94,7 @@ export default function PluginMarketCardComponent({
role="button"
tabIndex={0}
aria-label={t('market.installCard', { name: cardVO.label })}
className="w-[100%] h-[10rem] cursor-pointer bg-white rounded-[10px] shadow-[0px_0px_4px_0_rgba(0,0,0,0.2)] p-3 sm:p-[1rem] hover:shadow-[0px_2px_8px_0_rgba(0,0,0,0.15)] transition-shadow duration-200 outline-none focus-visible:ring-[3px] focus-visible:ring-ring/50 dark:bg-[#1f1f22] dark:shadow-[0px_0px_4px_0_rgba(255,255,255,0.1)] dark:hover:shadow-[0px_2px_8px_0_rgba(255,255,255,0.15)] relative"
className="w-[100%] h-[10rem] cursor-pointer bg-white rounded-[10px] border border-border shadow-[0px_1px_2px_0_rgba(0,0,0,0.06)] p-3 sm:p-[1rem] hover:shadow-[0px_2px_5px_0_rgba(0,0,0,0.08)] transition-shadow duration-200 outline-none focus-visible:ring-[3px] focus-visible:ring-ring/50 dark:bg-[#1f1f22] dark:shadow-[0px_1px_2px_0_rgba(255,255,255,0.04)] dark:hover:shadow-[0px_2px_5px_0_rgba(255,255,255,0.07)] relative"
onClick={handleInstallClick}
onKeyDown={(event) => {
if (event.key === 'Enter' || event.key === ' ') {

View File

@@ -551,6 +551,7 @@ export type MCPServer =
enable: boolean;
extra_args: MCPServerExtraArgsSSE;
runtime_info?: MCPServerRuntimeInfo;
readme?: string;
created_at?: string;
updated_at?: string;
}
@@ -561,6 +562,7 @@ export type MCPServer =
enable: boolean;
extra_args: MCPServerExtraArgsHttp;
runtime_info?: MCPServerRuntimeInfo;
readme?: string;
created_at?: string;
updated_at?: string;
}
@@ -571,6 +573,7 @@ export type MCPServer =
enable: boolean;
extra_args: MCPServerExtraArgsStdio;
runtime_info?: MCPServerRuntimeInfo;
readme?: string;
created_at?: string;
updated_at?: string;
};

View File

@@ -207,6 +207,52 @@ export class CloudServiceClient extends BaseHttpClient {
);
}
public getMCPDetail(
author: string,
name: string,
): Promise<{ mcp: PluginV4 }> {
return this.get<{ mcp: PluginV4 }>(
`/api/v1/marketplace/mcps/${author}/${name}`,
);
}
public getSkillDetail(
author: string,
name: string,
): Promise<{ skill: PluginV4 }> {
return this.get<{ skill: PluginV4 }>(
`/api/v1/marketplace/skills/${author}/${name}`,
);
}
/**
* Resolve the marketplace ``icon`` field for an extension by author/name/type.
* Used when the icon is not already known locally (e.g. an install confirm
* dialog opened from a URL query param carries no icon). Returns the raw
* ``icon`` value from the marketplace record (often an absolute external URL),
* or an empty string if it cannot be fetched.
*/
public async fetchMarketplaceIcon(
type: 'plugin' | 'mcp' | 'skill' | undefined,
author: string,
name: string,
): Promise<string> {
try {
if (type === 'mcp') {
const resp = await this.getMCPDetail(author, name);
return resp?.mcp?.icon || '';
}
if (type === 'skill') {
const resp = await this.getSkillDetail(author, name);
return resp?.skill?.icon || '';
}
const resp = await this.getPluginDetail(author, name);
return resp?.plugin?.icon || '';
} catch {
return '';
}
}
public getPluginREADME(
author: string,
pluginName: string,
@@ -230,6 +276,29 @@ export class CloudServiceClient extends BaseHttpClient {
return `${this.baseURL}/api/v1/marketplace/skills/${author}/${name}/resources/icon`;
}
/**
* Resolve the best icon URL for a marketplace extension.
*
* Many MCP / skill records store their ``icon`` as an absolute external URL
* (e.g. simpleicons.org / iconify.design logos) rather than a file uploaded
* to Space storage. For those, the ``/resources/icon`` endpoint 404s, so we
* must use the external URL directly. Records whose ``icon`` is empty or a
* relative path fall back to the ``/resources/icon`` endpoint (real uploads).
*/
public resolveMarketplaceIconURL(
type: 'plugin' | 'mcp' | 'skill' | undefined,
author: string,
name: string,
icon?: string,
): string {
if (icon && /^https?:\/\//i.test(icon)) {
return icon;
}
if (type === 'mcp') return this.getMCPMarketplaceIconURL(author, name);
if (type === 'skill') return this.getSkillMarketplaceIconURL(author, name);
return this.getPluginIconURL(author, name);
}
public getPluginAssetURL(
author: string,
pluginName: string,

View File

@@ -0,0 +1,65 @@
import { useEffect } from 'react';
import { useLocation } from 'react-router-dom';
import { useTranslation } from 'react-i18next';
const APP_NAME = 'LangBot';
// Map a route path to the i18n key used for its (type-level) document title.
// Reuses existing translation keys so titles stay in sync with the sidebar and
// page headers across all locales. The /home/* section is intentionally NOT
// listed here: those titles are driven from inside HomeLayout, which has access
// to the currently-selected sub-entity name (detailEntityName) via context and
// renders "<entity> · <type> · LangBot".
const ROUTE_TITLE_KEYS: { match: (path: string) => boolean; key: string }[] = [
{ match: (p) => p === '/login', key: 'common.login' },
{ match: (p) => p === '/register', key: 'register.title' },
{ match: (p) => p === '/reset-password', key: 'resetPassword.title' },
{ match: (p) => p === '/wizard', key: 'sidebar.quickStart' },
];
/**
* Builds a "<...parts> · LangBot" document title from the given page-name parts,
* dropping empties. Falls back to the bare app name when no parts resolve.
*/
export function buildDocumentTitle(
...parts: (string | null | undefined)[]
): string {
const clean = parts.filter((p): p is string => !!p && p.trim().length > 0);
return clean.length > 0 ? `${clean.join(' · ')} · ${APP_NAME}` : APP_NAME;
}
/**
* Imperatively set the document title. Centralized so the format stays
* consistent across the top-level layout and the home layout.
*/
export function setDocumentTitle(
...parts: (string | null | undefined)[]
): void {
document.title = buildDocumentTitle(...parts);
}
/**
* Top-level document-title driver for routes OUTSIDE the /home section
* (login, register, reset-password, wizard, and any unmapped route). The /home
* section manages its own title from HomeLayout so it can include the selected
* sub-entity name. Re-runs on navigation and language change so the title stays
* localized.
*/
export function useDocumentTitle() {
const { pathname } = useLocation();
const { t, i18n } = useTranslation();
useEffect(() => {
// Home routes are handled by HomeLayout (it has the entity name in context).
if (pathname.startsWith('/home')) return;
const entry = ROUTE_TITLE_KEYS.find((e) => e.match(pathname));
if (!entry) {
document.title = APP_NAME;
return;
}
const pageName = t(entry.key);
// Guard against an unresolved key (t returns the key itself).
setDocumentTitle(pageName !== entry.key ? pageName : null);
}, [pathname, t, i18n.language]);
}

View File

@@ -2,7 +2,7 @@ const enUS = {
sidebar: {
home: 'Home',
extensions: 'Extensions',
installedPlugins: 'Installed Extensions',
installedPlugins: 'Installed',
pluginMarket: 'Extension Market',
mcpServers: 'MCP Servers',
addExtension: 'Add Extension',
@@ -37,6 +37,7 @@ const enUS = {
helpDocs: 'Get Help',
featureRequest: 'Feature Request',
starOnGitHub: 'Star on GitHub',
joinDiscord: 'Join our Discord',
create: 'Create',
edit: 'Edit',
delete: 'Delete',
@@ -631,13 +632,16 @@ const enUS = {
},
market: {
searchPlaceholder: 'Search plugins...',
searchResults: 'Found {{count}} plugins',
totalPlugins: 'Total {{count}} plugins',
searchPlaceholderCount:
'Search {{count}} extensions, capabilities, or use cases...',
searchResults: 'Found {{count}} extensions',
totalPlugins: 'Total {{count}} extensions',
noPlugins: 'No plugins available',
noResults: 'No relevant plugins found',
loadingMore: 'Loading more...',
loading: 'Loading...',
allLoaded: 'All plugins displayed',
allLoadedCount: 'All {{count}} extensions displayed',
install: 'Install',
installCard: 'Install {{name}}',
installConfirm:
@@ -764,6 +768,9 @@ const enUS = {
toolsFound: 'tools',
unknownError: 'Unknown error',
noToolsFound: 'No tools found',
tabTools: 'Tools',
tabDocs: 'Docs',
noReadme: 'No documentation available',
parseResultFailed: 'Failed to parse test result',
noResultReturned: 'Test returned no result',
getTaskFailed: 'Failed to get task status',

View File

@@ -2,7 +2,7 @@ const esES = {
sidebar: {
home: 'Inicio',
extensions: 'Extensiones',
installedPlugins: 'Plugins instalados',
installedPlugins: 'Instalados',
pluginMarket: 'Tienda',
mcpServers: 'Servidores MCP',
addExtension: 'Añadir extensión',
@@ -40,6 +40,7 @@ const esES = {
helpDocs: 'Obtener ayuda',
featureRequest: 'Solicitar función',
starOnGitHub: 'Dar estrella en GitHub',
joinDiscord: 'Únete a Discord',
create: 'Crear',
edit: 'Editar',
delete: 'Eliminar',
@@ -644,13 +645,16 @@ const esES = {
},
market: {
searchPlaceholder: 'Buscar plugins...',
searchResults: 'Se encontraron {{count}} plugins',
totalPlugins: 'Total {{count}} plugins',
searchPlaceholderCount:
'Buscar {{count}} extensiones, capacidades o casos de uso...',
searchResults: 'Se encontraron {{count}} extensiones',
totalPlugins: 'Total {{count}} extensiones',
noPlugins: 'No hay plugins disponibles',
noResults: 'No se encontraron plugins relevantes',
loadingMore: 'Cargando más...',
loading: 'Cargando...',
allLoaded: 'Todos los plugins mostrados',
allLoadedCount: 'Se muestran las {{count}} extensiones',
install: 'Instalar',
installConfirm:
'¿Estás seguro de que deseas instalar el plugin "{{name}}" ({{version}})?',
@@ -778,6 +782,9 @@ const esES = {
toolsFound: 'herramientas',
unknownError: 'Error desconocido',
noToolsFound: 'No se encontraron herramientas',
tabTools: 'Herramientas',
tabDocs: 'Documentación',
noReadme: 'No hay documentación disponible',
parseResultFailed: 'Error al analizar el resultado de la prueba',
noResultReturned: 'La prueba no devolvió resultados',
getTaskFailed: 'Error al obtener el estado de la tarea',

View File

@@ -2,7 +2,7 @@ const jaJP = {
sidebar: {
home: 'ホーム',
extensions: '拡張機能',
installedPlugins: 'インストール済みプラグイン',
installedPlugins: 'インストール済み',
pluginMarket: 'プラグインマーケット',
mcpServers: 'MCPサーバー',
addExtension: '拡張機能を追加',
@@ -38,6 +38,7 @@ const jaJP = {
helpDocs: 'ヘルプドキュメント',
featureRequest: '機能リクエスト',
starOnGitHub: 'GitHubでStarする',
joinDiscord: 'Discord に参加',
create: '作成',
edit: '編集',
delete: '削除',
@@ -636,13 +637,16 @@ const jaJP = {
},
market: {
searchPlaceholder: 'プラグインを検索...',
searchResults: '{{count}} 個のプラグインが見つかりました',
totalPlugins: '合計 {{count}} 個のプラグイン',
searchPlaceholderCount:
'{{count}} 個の拡張機能・機能・ユースケースを検索...',
searchResults: '{{count}} 個の拡張機能が見つかりました',
totalPlugins: '合計 {{count}} 個の拡張機能',
noPlugins: '利用可能なプラグインがありません',
noResults: '関連するプラグインが見つかりません',
loadingMore: 'さらに読み込み中...',
loading: '読み込み中...',
allLoaded: 'すべてのプラグインが表示されました',
allLoadedCount: '{{count}} 個の拡張機能をすべて表示しました',
install: 'インストール',
installConfirm:
'プラグイン "{{name}}" ({{version}}) をインストールしますか?',
@@ -769,6 +773,9 @@ const jaJP = {
toolsFound: '個のツール',
unknownError: '不明なエラー',
noToolsFound: 'ツールが見つかりません',
tabTools: 'ツール',
tabDocs: 'ドキュメント',
noReadme: 'ドキュメントがありません',
parseResultFailed: 'テスト結果の解析に失敗しました',
noResultReturned: 'テスト結果が返されませんでした',
getTaskFailed: 'タスクステータスの取得に失敗しました',

View File

@@ -2,7 +2,7 @@ const ruRU = {
sidebar: {
home: 'Главная',
extensions: 'Расширения',
installedPlugins: 'Установленные плагины',
installedPlugins: 'Установленные',
pluginMarket: 'Маркетплейс',
mcpServers: 'MCP-серверы',
addExtension: 'Добавить расширение',
@@ -38,6 +38,7 @@ const ruRU = {
helpDocs: 'Помощь',
featureRequest: 'Запрос функции',
starOnGitHub: 'Поставить звезду на GitHub',
joinDiscord: 'Присоединиться к Discord',
create: 'Создать',
edit: 'Редактировать',
delete: 'Удалить',
@@ -642,13 +643,16 @@ const ruRU = {
},
market: {
searchPlaceholder: 'Поиск плагинов...',
searchResults: 'Найдено {{count}} плагинов',
totalPlugins: 'Всего {{count}} плагинов',
searchPlaceholderCount:
'Поиск среди {{count}} расширений, возможностей или сценариев...',
searchResults: 'Найдено {{count}} расширений',
totalPlugins: 'Всего {{count}} расширений',
noPlugins: 'Нет доступных плагинов',
noResults: 'Подходящие плагины не найдены',
loadingMore: 'Загрузка ещё...',
loading: 'Загрузка...',
allLoaded: 'Все плагины отображены',
allLoadedCount: 'Показаны все {{count}} расширений',
install: 'Установить',
installConfirm:
'Вы уверены, что хотите установить плагин "{{name}}" ({{version}})?',
@@ -774,6 +778,9 @@ const ruRU = {
toolsFound: 'инструментов',
unknownError: 'Неизвестная ошибка',
noToolsFound: 'Инструменты не найдены',
tabTools: 'Инструменты',
tabDocs: 'Документация',
noReadme: 'Документация отсутствует',
parseResultFailed: 'Не удалось разобрать результат теста',
noResultReturned: 'Тест не вернул результат',
getTaskFailed: 'Не удалось получить статус задачи',

View File

@@ -2,7 +2,7 @@ const thTH = {
sidebar: {
home: 'หน้าแรก',
extensions: 'ส่วนขยาย',
installedPlugins: 'ปลั๊กอินที่ติดตั้ง',
installedPlugins: 'ที่ติดตั้งแล้ว',
pluginMarket: 'ตลาดปลั๊กอิน',
mcpServers: 'เซิร์ฟเวอร์ MCP',
addExtension: 'เพิ่มส่วนขยาย',
@@ -37,6 +37,7 @@ const thTH = {
helpDocs: 'ขอความช่วยเหลือ',
featureRequest: 'ขอฟีเจอร์ใหม่',
starOnGitHub: 'ให้ดาวบน GitHub',
joinDiscord: 'เข้าร่วม Discord',
create: 'สร้าง',
edit: 'แก้ไข',
delete: 'ลบ',
@@ -623,13 +624,16 @@ const thTH = {
},
market: {
searchPlaceholder: 'ค้นหาปลั๊กอิน...',
searchResults: 'พบ {{count}} ปลั๊กอิน',
totalPlugins: 'ทั้งหมด {{count}} ปลั๊กอิน',
searchPlaceholderCount:
'ค้นหา {{count}} ส่วนขยาย ความสามารถ หรือกรณีใช้งาน...',
searchResults: 'พบ {{count}} ส่วนขยาย',
totalPlugins: 'ทั้งหมด {{count}} ส่วนขยาย',
noPlugins: 'ไม่มีปลั๊กอินที่พร้อมใช้งาน',
noResults: 'ไม่พบปลั๊กอินที่เกี่ยวข้อง',
loadingMore: 'กำลังโหลดเพิ่มเติม...',
loading: 'กำลังโหลด...',
allLoaded: 'แสดงปลั๊กอินทั้งหมดแล้ว',
allLoadedCount: 'แสดงส่วนขยายทั้งหมด {{count}} รายการแล้ว',
install: 'ติดตั้ง',
installConfirm:
'คุณแน่ใจหรือไม่ว่าต้องการติดตั้งปลั๊กอิน "{{name}}" ({{version}})?',
@@ -754,6 +758,9 @@ const thTH = {
toolsFound: 'เครื่องมือ',
unknownError: 'ข้อผิดพลาดที่ไม่ทราบสาเหตุ',
noToolsFound: 'ไม่พบเครื่องมือ',
tabTools: 'เครื่องมือ',
tabDocs: 'เอกสาร',
noReadme: 'ไม่มีเอกสาร',
parseResultFailed: 'ไม่สามารถแยกวิเคราะห์ผลการทดสอบได้',
noResultReturned: 'การทดสอบไม่ส่งผลลัพธ์กลับมา',
getTaskFailed: 'ไม่สามารถดึงสถานะงานได้',

View File

@@ -2,7 +2,7 @@ const viVN = {
sidebar: {
home: 'Trang chủ',
extensions: 'Tiện ích mở rộng',
installedPlugins: 'Plugin đã cài đặt',
installedPlugins: 'Đã cài đặt',
pluginMarket: 'Chợ ứng dụng',
mcpServers: 'Máy chủ MCP',
addExtension: 'Thêm tiện ích mở rộng',
@@ -38,6 +38,7 @@ const viVN = {
helpDocs: 'Trợ giúp',
featureRequest: 'Yêu cầu tính năng',
starOnGitHub: 'Star trên GitHub',
joinDiscord: 'Tham gia Discord',
create: 'Tạo',
edit: 'Chỉnh sửa',
delete: 'Xóa',
@@ -637,13 +638,16 @@ const viVN = {
},
market: {
searchPlaceholder: 'Tìm kiếm plugin...',
searchResults: 'Tìm thấy {{count}} plugin',
totalPlugins: 'Tổng cộng {{count}} plugin',
searchPlaceholderCount:
'Tìm kiếm {{count}} tiện ích mở rộng, khả năng hoặc tình huống...',
searchResults: 'Tìm thấy {{count}} tiện ích mở rộng',
totalPlugins: 'Tổng cộng {{count}} tiện ích mở rộng',
noPlugins: 'Không có plugin nào',
noResults: 'Không tìm thấy plugin liên quan',
loadingMore: 'Đang tải thêm...',
loading: 'Đang tải...',
allLoaded: 'Đã hiển thị tất cả plugin',
allLoadedCount: 'Đã hiển thị tất cả {{count}} tiện ích mở rộng',
install: 'Cài đặt',
installConfirm:
'Bạn có chắc chắn muốn cài đặt plugin "{{name}}" ({{version}}) không?',
@@ -768,6 +772,9 @@ const viVN = {
toolsFound: 'công cụ',
unknownError: 'Lỗi không xác định',
noToolsFound: 'Không tìm thấy công cụ nào',
tabTools: 'Công cụ',
tabDocs: 'Tài liệu',
noReadme: 'Không có tài liệu',
parseResultFailed: 'Phân tích kết quả kiểm tra thất bại',
noResultReturned: 'Kiểm tra không trả về kết quả',
getTaskFailed: 'Lấy trạng thái tác vụ thất bại',

View File

@@ -2,7 +2,7 @@ const zhHans = {
sidebar: {
home: '首页',
extensions: '扩展',
installedPlugins: '已安装扩展',
installedPlugins: '已安装',
pluginMarket: '扩展市场',
mcpServers: 'MCP 服务器',
addExtension: '添加扩展',
@@ -36,6 +36,7 @@ const zhHans = {
helpDocs: '帮助文档',
featureRequest: '需求建议',
starOnGitHub: '在 GitHub 上 Star',
joinDiscord: '加入 Discord 社区',
create: '创建',
edit: '编辑',
delete: '删除',
@@ -605,13 +606,15 @@ const zhHans = {
},
market: {
searchPlaceholder: '搜索插件...',
searchResults: '搜索 {{count}} 个插件',
totalPlugins: ' {{count}} 个插件',
searchPlaceholderCount: '搜索 {{count}} 个扩展、能力或场景...',
searchResults: '搜索到 {{count}} 个扩展',
totalPlugins: '共 {{count}} 个扩展',
noPlugins: '暂无插件',
noResults: '未找到相关插件',
loadingMore: '加载更多...',
loading: '加载中...',
allLoaded: '已显示全部插件',
allLoadedCount: '已显示全部 {{count}} 个扩展',
install: '安装',
installCard: '安装 {{name}}',
installConfirm: '确定要安装插件 "{{name}}" ({{version}}) 吗?',
@@ -736,6 +739,9 @@ const zhHans = {
toolsFound: '个工具',
unknownError: '未知错误',
noToolsFound: '未找到任何工具',
tabTools: '工具',
tabDocs: '文档',
noReadme: '暂无文档',
parseResultFailed: '解析测试结果失败',
noResultReturned: '测试未返回结果',
getTaskFailed: '获取任务状态失败',

View File

@@ -2,7 +2,7 @@ const zhHant = {
sidebar: {
home: '首頁',
extensions: '擴展',
installedPlugins: '已安裝外掛',
installedPlugins: '已安裝',
pluginMarket: '外掛市場',
mcpServers: 'MCP 伺服器',
addExtension: '添加擴展',
@@ -36,6 +36,7 @@ const zhHant = {
helpDocs: '輔助說明',
featureRequest: '需求建議',
starOnGitHub: '在 GitHub 上 Star',
joinDiscord: '加入 Discord 社群',
create: '建立',
edit: '編輯',
delete: '刪除',
@@ -605,13 +606,15 @@ const zhHant = {
},
market: {
searchPlaceholder: '搜尋插件...',
searchResults: '搜尋 {{count}} 個插件',
totalPlugins: ' {{count}} 個插件',
searchPlaceholderCount: '搜尋 {{count}} 個擴展、能力或場景...',
searchResults: '搜尋到 {{count}} 個擴展',
totalPlugins: '共 {{count}} 個擴展',
noPlugins: '暫無插件',
noResults: '未找到相關插件',
loadingMore: '載入更多...',
loading: '載入中...',
allLoaded: '已顯示全部插件',
allLoadedCount: '已顯示全部 {{count}} 個擴展',
install: '安裝',
installCard: '安裝 {{name}}',
installConfirm: '確定要安裝插件 "{{name}}" ({{version}}) 嗎?',
@@ -735,6 +738,9 @@ const zhHant = {
toolsFound: '個工具',
unknownError: '未知錯誤',
noToolsFound: '未找到任何工具',
tabTools: '工具',
tabDocs: '文件',
noReadme: '暫無文件',
parseResultFailed: '解析測試結果失敗',
noResultReturned: '測試未返回結果',
getTaskFailed: '獲取任務狀態失敗',

View File

@@ -25,11 +25,13 @@ import SkillsPage from '@/app/home/skills/page';
import ErrorPage from '@/components/ErrorPage';
import BackendUnavailablePage from '@/components/BackendUnavailablePage';
import PluginPagesPage from '@/app/home/plugin-pages/page';
import RootLayout from '@/app/RootLayout';
const Loading = () => <div>Loading...</div>;
export const router = createBrowserRouter([
{
element: <RootLayout />,
errorElement: <ErrorPage />,
children: [
{