* fix(cloud): show owner model balance and enforce single owner
* fix(migrations): create owner index idempotently
---------
Co-authored-by: dadachann <185672915+dadachann@users.noreply.github.com>
- Add group-by-type button to extensions category header (mirrors the
agent group-by-kind pattern) — syncs with the extensions page Switch
via shared SidebarDataContext state
- Relocate both group and refresh controls to sit left-aligned
immediately after the title for both Agent and Extensions sections
- Add plugins.groupByTypeShort i18n key to all 8 locales
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Add a toggle (left of the "+" button) that groups the Agent section by
kind, showing "Agent" and "Pipeline" sub-headers. State persists in
localStorage, mirroring the extensions group-by-type pattern.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Drop the text label; keep the icon with a title tooltip so names have
more room in the narrow sidebar.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Add a trailing badge (icon + label) to each entry in the sidebar Agent
section so users can tell Agent orchestration apart from legacy Pipeline.
Thread the agent `kind` field through SidebarEntityItem.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* feat: Implement workflow form handling for paused workflows
- Added module-level storage for pending forms to manage state across sessions.
- Introduced functions to set, get, and clear pending forms with expiration handling.
- Enhanced DifyServiceAPIRunner to support resuming paused workflows via form actions.
- Implemented logic to yield human input requests and display appropriate messages.
- Updated workflow submission methods to handle paused states and resume actions.
- Ensured proper merging of pending form actions with user inputs for seamless interaction.
* feat: Add '_routed_by_rule' variable to form action in Lark and Telegram adapters
* feat: Enhance Lark and Telegram adapters with new form handling for paused workflows
* feat: Enhance TelegramAdapter to handle form action buttons and message threading
* feat: Improve TelegramAdapter message handling with enhanced error management and draft message support
* feat: Add the function for formatting human input text to support adapters without rich UI.
* feat(dingtalk): implement human input card support and card action handling
- Add a new module `card_callback.py` to handle card action button clicks from DingTalk.
- Introduce `DingTalkCardActionHandler` to process card action callbacks and extract parameters.
- Update `DingTalkAdapter` to manage card state and handle form input through a single card template.
- Add configuration for `human_input_card_template_id` in `dingtalk.yaml` to specify the template for human input.
- Create a new card template `dingtalk_human_input_card.json` for rendering human input prompts and buttons.
* feat(dingtalk): enhance human input card functionality with streaming support and active turn management
- Updated the DingTalk card template to enable streaming mode and multi-update configuration.
- Removed the obsolete delete_card method from DingTalkClient to streamline card management.
- Enhanced DingTalkAdapter to manage active turn cards and accumulated streaming text, ensuring a seamless user experience during human input prompts.
- Modified the create_message_card method to utilize existing active cards for resumed workflows, preventing duplication.
- Improved the _paint_form_on_card method to update existing cards with human input prompts and buttons dynamically.
- Updated the dingtalk_human_input_card.json template to reflect the new streaming capabilities and configuration options.
* feat(wecom): implement Dify human input pause handling with button interaction support
* feat(qqofficial): implement Dify human input button interaction handling and markdown keyboard support
* feat(qqofficial): implement one-click QR binding and enhance localization support
* feat(discord): implement Discord form view with button interactions for Dify actions
* fix(telegram): correct group chat type check and handle oversized callback data for Telegram actions
fix(difysvapi): ensure safe access to remove-think configuration in pipeline settings
* feat(dify): add support for chatflow app type and enhance human input handling
* feat(telegram): add action title feedback for user selections in Telegram messages
* feat(lark): enhance LarkAdapter to store form content for resume notices
* feat(dingtalk): update display formatting for card content with HTML line breaks
* feat(dingtalk): add feedback functionality to cards with 👍/👎 buttons
- Implemented feedback state management for cards, allowing users to provide feedback via thumbs up/down buttons.
- Enhanced card rendering to include feedback buttons when appropriate.
- Registered feedback listeners to handle feedback events and update card states accordingly.
- Updated the card template to support dynamic button rendering for feedback actions.
- Improved error handling and logging for feedback actions and card updates.
* fix: add Avatar component to dingtalk_human_input_card.json for enhanced user interaction
* feat(wecom): add optional source block to interactive template cards for enhanced branding
* feat(wecom): add functions for template card action extraction and update, enhance button interaction handling
* feat(qqofficial): synchronize passive-reply counter with inbound message sequence
* feat(qqofficial): add method to identify invisible form placeholder chunks in messages
* feat(dingtalk): add download link for human input card template and enhance dynamic form configuration
* feat(telegram): enhance message handling with group stream deletion and form placeholder detection
* Add unit tests for DingTalk, Lark, WeComBot, and Dify service API runners
- Implement tests for DingTalk adapter helper functions including form content cleaning, input extraction, and completed input lines.
- Create unit tests for Lark adapter helper functions focusing on input extraction and completed input lines.
- Add tests for WeComBot template card functionalities, including event extraction and payload building for human input.
- Enhance Dify service API runner tests to cover human input forms, including input collection, action handling, and form snapshot extraction.
* feat: Enhance Telegram and QQ Official adapters with select field handling and form action processing
- Added support for select fields in Telegram adapter, including option extraction and callback handling.
- Implemented form action processing for Telegram callbacks, improving user interaction feedback.
- Introduced new helper functions for building keyboards and resolving select button actions in QQ Official adapter.
- Enhanced DifyServiceAPIRunner to handle cumulative streaming responses and improve error handling during workflow resumes.
- Added unit tests for new functionalities in Telegram and QQ Official adapters, ensuring robust behavior for select fields and form actions.
* feat(lark): add functions for current input definitions and visible form content handling
feat(qqofficial): update fallback text handling for non-streaming scenarios
feat(difysvapi): enhance form content processing for interactive fields and actions
test: add unit tests for Lark and QQ Official adapter functionalities
* Add tests for DingTalk adapter content processing and markdown formatting
- Updated the assertion in `test_dingtalk_completed_input_lines_include_text_and_select_values` to remove unnecessary markdown formatting.
- Added new tests to verify that `_dingtalk_clean_form_content` maintains the order of prompts and completed values in various scenarios.
- Introduced `test_dingtalk_card_markdown_preserves_internal_line_breaks` to ensure internal line breaks are correctly converted to HTML line breaks.
* feat: Refactor input handling and feedback messages across multiple adapters
* feat: Update the human-computer interaction template cards, and optimize the prompt information and content display.
* feat: Refactor pending form handling to isolate by bot and pipeline
* feat: Enhance error handling and caching for Dify and WeCom interactions
* feat: Enhance select input handling and validation in Dify API runner and Telegram adapter
* feat: Add missing completed input lines handling in DingTalk adapter
* feat: Add pipeline_uuid handling across multiple adapters and update related tests
The in-product plugin/add-extension help links went through
link.langbot.app/{lang}/docs/plugins, which now 404s (it resolved to the
removed /usage/plugin/plugin-intro path). Point them directly at the
current docs page docs.langbot.app/{lang}/plugin/plugin-intro (verified
200 for zh/en/ja).
The previous truncate/shrink-0 pass only touched leaf nodes, but the
min-content floor was set by two ancestors: the flex-1 left group lacked
min-w-0, and CardHeader is a CSS grid whose implicit single column
defaults to min-content. Constrain both (min-w-0 on the header grid +
explicit grid-cols-[minmax(0,1fr)], min-w-0 on the inner flex groups) so
the provider name / base_url+key subtitle actually truncate instead of
forcing the card — and the whole settings modal — wider than the viewport.
- PanelToolbar: allow wrapping and tighten padding on small screens so the
primary action (e.g. "创建 API 密钥") no longer runs off the dialog edge.
- ProviderCard header: let the provider name truncate and pin the model-count
badge and right-side action group with shrink-0 so credits / + controls stay
inside the card on narrow viewports.
- monitoring: stack filters full-width, scrollable tab bar, reduce card/content padding on mobile
- models dialog: provider form modal no longer overflows viewport on small screens; shared panel body padding shrinks on mobile
- plugin logs: reduce horizontal padding on mobile
* feat(api): support global API key from config.yaml (api.global_api_key)
Accept a config-defined global API key anywhere a web-UI key is accepted
(X-API-Key / Bearer), with no login session and no DB record. Useful for
automated deployments and AI agents (HTTP API + MCP). Defaults to empty
(disabled); does not require the lbk_ prefix.
- templates/config.yaml: add api.global_api_key with security notes
- service/apikey.py: verify_api_key checks global key first (constant-time)
- docs/API_KEY_AUTH.md: document the global key + security guidance
- tests: cover global-key match, prefix-free, fallback-to-db, disabled
* feat(mcp): expose LangBot management as an MCP server at /mcp
Add an MCP (Model Context Protocol) server so external AI agents can manage a
LangBot instance. Reuses the same API-key auth as the HTTP API (including the
config.yaml global API key).
- pkg/api/mcp/server.py: FastMCP server wrapping the service layer; 21 curated
tools across system/bots/pipelines/models/knowledge/mcp-servers/skills
- pkg/api/mcp/mount.py: ASGI dispatcher fronting Quart; authenticates /mcp
requests with an API key, runs the streamable-HTTP session manager lifespan
- controller/main.py: serve the wrapped ASGI app via hypercorn (was run_task)
- web: new 'MCP' tab in the API integration dialog showing endpoint, auth, and
client config; i18n for 8 locales
- tests/manual/mcp_smoke.py: e2e check (401 unauth, list tools, call tools)
Tool surface is intentionally curated (not all ~25 route groups) to keep the
agent surface small, safe, and maintainable. Extend deliberately.
* feat(skills): add in-repo skills/ as the single source of truth
Migrate the agent skills + QA/e2e test harness from the (now archived)
langbot-app/langbot-skills repo into LangBot/skills/, and add four new skills.
Migrated:
- langbot-plugin-dev, langbot-testing (e2e), langbot-env-setup,
langbot-skills-maintenance, langbot-eba-adapter-dev
- the bin/lbs CLI (src/, test/, scripts/, schemas/, qa-agent-docs/)
New:
- langbot-dev core backend + web development
- langbot-deploy Docker/K8s deployment + config.yaml + global API key
- langbot-mcp-ops operating the LangBot MCP server (/mcp)
- langbot-space-ops operating the Space marketplace MCP server
- src/cli.ts repoRoot(): recognize the skills assets root (skills.index.json +
bin/lbs) so the CLI works when nested inside the LangBot repo
- README.md: unified skill catalog; skills.index.json regenerated
Parity with source verified: bin/lbs validate + node test suite match the
source repo (only the uncommitted .lbpkg build-artifact fixture differs).
* docs(agents): document agent-facing surfaces + API/MCP/skills sync rule
* docs(readme): add 'Built for AI Agents' section across all locales
Highlight MCP server, in-repo skills (single source of truth), AGENTS.md
sync rule, and llms.txt. Cross-link LangBot Space MCP marketplace.
* style(mcp): fix ruff format + prettier lint in MCP server and API panel
* style(web): prettier format MCP i18n locale entries
* docs(skills): note MCP instance control in dev/testing skills
All development-guidance skills now point to the LangBot instance MCP
server (/mcp) and the Space marketplace MCP server, reusing API keys.
- Add PanelToolbar/PanelBody primitives so all four settings tabs share
the same top-toolbar + scrollable-body rhythm under the unified header.
- API panel: drop the heavy gray shadowed TabsList; move the create
action into the toolbar next to the tabs, lighten per-tab hints.
- Storage panel: reuse PanelToolbar for the generated-at/refresh bar.
- Account panel: wrap content in PanelBody for consistent padding.
- Models panel: keep the pinned LangBot Models (Space) card at the very
top, above the add-custom-provider row (intentional pin), using
PanelBody instead of a top toolbar.
- Add a shared section header (icon + title + description) with right
padding so the dialog close X no longer overlaps panel content, and
every tab now shares the same top layout for a consistent look.
- Shorten inner sidebar nav labels (Models/API/Storage/Account) via new
settingsDialog.nav.* i18n keys across all 8 locales.
- Add common.apiIntegrationDescription and account.settingsDescription
for the new header.
The model-selector in dynamic forms (pipeline / knowledge base settings)
still opened the old standalone ModelsDialog. Point it at the unified
SettingsDialog (section pinned to models) and delete the now-unused
ModelsDialog wrapper so only the new dialog remains.
Pin the dialog to a fixed 80vh (cap 800px) so switching sections no
longer resizes it; panels scroll their own content internally. Override
the SidebarProvider wrapper's default h-svh with h-full so both columns
fill the dialog height. Narrow the inner settings sidebar to w-44.
Merge API integration, model settings, account settings and storage
analysis into one SettingsDialog with a shadcn inner sidebar for
section switching. Preserve existing ?action= query-param deep links
(showModelSettings / showAccountSettings / showApiIntegrationSettings /
showStorageAnalysis) by mapping each to a section. Extract reusable
panels and keep ModelsDialog as a thin wrapper for the dynamic-form
model picker.
* refactor(provider): use LiteLLM as unified LLM requester backend
- Replace 23+ individual requester implementations with unified litellmchat.py
- Add litellm_provider field to 27 YAML manifests for provider routing
- Delete redundant requester subclasses
- Add unit tests for LiteLLMRequester (29 tests)
- Fix num_retries parameter name (was max_retries)
- Fix exception handling order for subclass exceptions
LiteLLM provides unified API for 100+ providers, eliminating need for
provider-specific requesters.
* fix: ruff format provider.py
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* refactor(provider): simplify LiteLLM requester usage handling
- Remove unused Anthropic-specific tool schema generation
- Share completion argument construction between normal and streaming calls
- Use LiteLLM/OpenAI native usage fields for monitoring
- Collect stream token usage from LiteLLM stream_options
- Update LiteLLM requester tests for unified usage fields
* restore: restore deleted provider requester files
Restore individual provider requester implementations that were
removed in de61b5d3. These files coexist with the unified
litellmchat.py backend.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* feat: update requesters and improve provider selection UI
- Added `litellm_provider` field to various requesters' YAML configurations.
- Removed obsolete Python requester files for OpenRouter, PPIO, QHAIGC, ShengSuanYun, SiliconFlow, Space, TokenPony, VolcArk, and Xai.
- Introduced new requesters for Tencent and Together AI with corresponding YAML configurations and SVG icons.
- Enhanced the ProviderForm component to include a searchable dropdown for selecting providers, improving user experience.
- Updated localization files to include search provider text for both English and Chinese.
* fix(provider): align litellm rebase with master
* fix(provider): capture streaming token usage; add token observability
The LiteLLM streaming requester only captured usage when a chunk had an
empty `choices` list. Many OpenAI-compatible gateways (e.g. new-api) and
providers send the final usage payload in a chunk that still carries an
empty-delta choice, so streamed calls always recorded 0 tokens in the
monitoring logs/dashboard (non-streaming worked).
- Capture stream usage whenever a chunk carries it, regardless of choices
- Add robust _normalize_usage (dict/obj shapes, derive missing total_tokens)
- Register litellm in bootutils/deps.py (was in pyproject only)
- Add MonitoringService.get_token_statistics + /monitoring/token-statistics
endpoint: summary, per-model breakdown, token timeseries, and a
zero-token-success data-quality signal
- Add TokenMonitoring dashboard tab (summary tiles, stacked token chart,
per-model table) + i18n (en/zh)
- Regression tests for stream usage capture and usage normalization
Verified end-to-end against a real OpenAI-compatible endpoint with
gpt-5.5 and claude-opus-4-8: tokens now recorded non-zero for both
streaming and non-streaming paths.
* refactor(provider): simplify litellm capabilities
* style: simplify wrapped expressions
* feat(models): persist context metadata
* fix(provider): handle dict embeddings and openai-compatible rerank in LiteLLMRequester
- invoke_embedding: support both object- and dict-shaped response.data
entries (OpenAI-compatible gateways like new-api return dicts)
- invoke_rerank: litellm.arerank rejects the 'openai' provider, so for
openai-compatible (or unspecified) providers call the standard
Jina/Cohere-style POST /v1/rerank endpoint directly over HTTP
- accept both 'relevance_score' and 'score' fields in rerank results
- add unit tests for the openai-compatible HTTP rerank path
* feat(provider): enforce requester support_type when adding models
- frontend: AddModelPopover only shows model-type tabs (llm/embedding/
rerank) that the provider's requester declares in its manifest
support_type; ModelsDialog fetches requester manifests and maps
requester -> support_type, passed down through ProviderCard
- backend: add _validate_provider_supports guard in create_llm_model /
create_embedding_model / create_rerank_model so a model cannot be
attached to a provider whose requester does not support that type,
even if the frontend restriction is bypassed (manifests without
support_type are allowed for backward compatibility)
- manifests: correct support_type for providers that do not offer all
three model types:
- llm only: anthropic, deepseek, groq, moonshot, openrouter, xai
- llm + text-embedding: openai, gemini, mistral
- add rerank to new-api (verified working via /v1/rerank)
- set llm + text-embedding + rerank for aggregator/unknown gateways
* feat(provider): add searchable alias to requester manifests
- add a free-text 'alias' field to every requester manifest spec,
containing the vendor's English/Chinese names, pinyin, common
nicknames and flagship model-series names (e.g. moonshot -> kimi,
月之暗面; zhipu -> glm, 智谱清言)
- frontend: ProviderForm requester search now also matches against
alias (substring/contains), so searching 'kimi' surfaces Moonshot,
'硅基' surfaces SiliconFlow, etc.
- also fix support_type: openrouter (relay) supports embedding+rerank;
LangBot Space gains rerank (coming soon)
* fix(provider): make support_type guard defensive against incomplete model_mgr
- _validate_provider_supports now uses getattr to gracefully skip when
model_mgr / provider_dict / manifest lookup is unavailable, instead of
raising AttributeError (fixes unit tests that mock ap.model_mgr as a
bare SimpleNamespace)
- add TestValidateProviderSupports covering: allow supported type,
reject unsupported type, allow when support_type missing, allow when
provider unknown, degrade safely when model_mgr is incomplete
* fix(persistence): guard 0004 migration against missing llm_models table
The 0004_add_llm_model_context_length migration called
inspector.get_columns('llm_models') unconditionally, raising
NoSuchTableError when the table does not exist (e.g. migrating a
fresh/empty DB, as exercised by the integration tests where
create_all() registers no tables because the ORM models are not
imported). Every other migration guards with a table-existence check
first; add the same guard here for both upgrade and downgrade.
Also restore the test head assertion to 0004 (it had been lowered to
0003 to mask this failure).
* Merge branch 'master' into feat/litellm
Resolve conflicts:
- uv.lock: regenerated via 'uv lock' to reconcile litellm/fastuuid
(ours) with openai bump (master).
- Alembic migrations: master added 0004_add_mcp_readme while this
branch added 0004_add_llm_model_context_length, both as children of
0003 (would create multiple heads). Re-chain the litellm migration as
0005_add_llm_model_context_length with down_revision=0004_add_mcp_readme
for a single linear head. Update test head assertion accordingly.
* fix(persistence): shorten migration revision id to fit varchar(32)
PostgreSQL stores alembic_version.version_num as varchar(32).
'0005_add_llm_model_context_length' (33 chars) overflowed it, raising
StringDataRightTruncationError in the PG migration tests. Rename the
revision (and file) to '0005_add_llm_context_length' (27 chars) and
update the head assertions in both SQLite and PostgreSQL migration
tests.
---------
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: fdc310 <2213070223@qq.com>
Co-authored-by: RockChinQ <rockchinq@gmail.com>
Cloud/NAT deployments couldn't complete WeCom-family / Official Account /
QQ Official setup because the trusted-IP (IP whitelist) value — the
server's egress IPs — was nowhere visible in LangBot.
- config.yaml: new system.outbound_ips list (env: SYSTEM__OUTBOUND_IPS,
comma-separated), exposed via GET /api/v1/system/info
- dynamic form: generic __system.*-named display-only fields resolved
from systemContext (same namespace as show_if), one read-only row per
value with a copy button, excluded from form state and emitted values;
hidden entirely when the deployment provides no IPs
- manifests: trusted-IP display field for wecom, wecomcs, wecombot,
officialaccount, qqofficial
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* 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.
* build(docker): ship a self-contained nsjail sandbox backend in the image
Compile nsjail 3.6 from source in a dedicated multi-stage build and carry
only the binary plus its runtime libs (libprotobuf32, libnl-route-3-200)
into the final image. This lets the Box runtime isolate sandboxed code via
nsjail user/mount/pid/net namespaces without a host Docker socket — the
prerequisite for running Box on LangBot Cloud (k8s), where mounting
docker.sock would grant node root and is not acceptable for multi-tenant.
The build toolchain (build-essential/bison/flex/protobuf-dev/libnl-dev)
stays in the nsjail-build stage and is not present in the shipped image.
Verified: image builds (583MB), nsjail --help exits 0, libraries resolve,
and the real NsjailBackend executes an isolated command end-to-end on a
v6.1/cgroup2 host matching LangBot Cloud prod (rlimit fallback path, since
container /sys/fs/cgroup is read-only; PID-namespace isolation confirmed).
* feat(box): SaaS guard to force a single global sandbox scope
Add system.limitation.force_box_session_id_template: when non-empty it
overrides every pipeline's box-session-id-template at resolve time, pinning
all queries to one shared sandbox (e.g. {global}). This is the authoritative,
unbypassable guard — it runs on every exec call, so editing the pipeline
config via API cannot escape it. The web UI locks the Sandbox Scope selector
via a combined box_scope_editable flag (box available AND not forced).
* build(deps): pin langbot-plugin==0.4.2b1 (nsjail cgroup container-safety beta)
* fix(web): show forced sandbox scope + make disabled tooltip tap-friendly
When a SaaS deployment pins every pipeline to a fixed sandbox scope via
system.limitation.force_box_session_id_template, the Sandbox Scope selector was
correctly locked but still displayed the pipeline's stored value (e.g. the
per-chat default), misrepresenting the scope that the runtime actually enforces
on every exec. Coerce the displayed/saved value to the forced template so the
locked selector truthfully shows the active scope (e.g. Global).
Also fix the disabled_tooltip being invisible on touch devices: hover-only Radix
tooltips never open without a pointer, so the explanation of why the field is
locked could not be read on mobile. Wrap the info icon so a tap toggles the
tooltip while desktop hover still works.
* feat(web): hide sidebar new-version prompt for edition=cloud
Cloud instances are upgraded centrally by the operator, so surfacing a GitHub
'new version available' badge to tenants is misleading and actionable only by
the operator. Skip the release check entirely when edition=cloud.
* style(web): prettier formatting for DisabledTooltipIcon ternary
* chore(deps): bump langbot-plugin to 0.4.2b2
Picks up the SDK fix that creates a read-write host_path before the
nsjail bind-mount, fixing the SaaS MCP shared-workspace sandbox failure
(exec exit 255 with empty output when host_path didn't exist).
* chore(deps): bump langbot-plugin to 0.4.2b3
Picks up the nsjail /dev-node fix so stdio MCP servers (uvx-launched) can
start under force_global_sandbox instead of failing with 'Connection closed
/ please check URL'.
* fix(web): show real MCP runtime status on installed extensions list
The installed-extensions list badge keyed solely off the enable flag, so a
server that was still CONNECTING (or in ERROR) was shown as 'Connected'.
Reflect the actual runtime_info.status (connecting/connected/error/disabled)
with matching colors, and poll quietly every 3s while any MCP server is
connecting so the badge transitions without a manual refresh.
* chore(deps): bump langbot-plugin to 0.4.2b4
Picks up the 30s start_managed_process timeout so cold uvx MCP bootstraps
don't get torn down mid-install.
* style(web): satisfy prettier — parenthesize nullish-coalescing in ternary
* fix(mcp): isolate transient test sessions from the shared Box session
A config-page 'test' (server_name='_', no persisted UUID) ran in the same
shared 'mcp-shared' Box session as live MCP servers. A failing test (e.g.
empty args) churned that shared session and tore down healthy, already-
connected servers — leaving them stuck after exhausting their retries.
Mark UUID-less sessions as transient, give them their own isolated Box
session ('mcp-test-<uuid>'), and fully delete that session on cleanup so
tests can never disturb live servers and don't leak sessions.
* fix(mcp): tear down transient test session after test completes
A successful config-page test left its isolated 'mcp-test-<uuid>' Box
session running (the lifecycle task blocks until shutdown). Wrap the
transient test coroutine so it always shuts the session down afterward,
preventing isolated test sessions from leaking.
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>
Junyan Qin