- 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>
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>
- Move conditions toggle between event select and arrow; drop "IF" label
- Remove "all events" (*) option from event select
- Add i18n labels for concrete event names (zh/en/ja) via bots.eventNames
- Narrow fallback event set to message.received for adapters without
declared supported_events (legacy adapters only emit message.received)
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
Two unrelated frontend fixes:
- LanguageSelector mounts each time the sidebar account dropdown opens and
unconditionally called i18n.changeLanguage() on mount, emitting a
languageChanged event even when the language was unchanged. That handed
every useTranslation() consumer a fresh `t` reference, re-running effects
keyed on `t` (e.g. the plugins page system-status fetch) and surfacing as
a page "refresh". Guard the call so it only fires on an actual change.
- Plugin logs auto-refresh control changed from a toggle Button to a
Switch + Label; the on/off button i18n keys are replaced by a single
static logsAutoRefresh label across all 8 locales.
Port the Space marketplace recommendation carousel UX into the in-app
add-extension page: a 10s auto-advance driven by a smooth countdown ring
that doubles as a pause/resume toggle, and manual prev/next now reset the
countdown. Adds market.recommendation.{pause,resume} across 8 locales.
Replace the three-way transport choice (stdio / sse / httpstream) for
connecting LangBot to external MCP servers with two modes: local (stdio)
and remote. Remote servers only require a URL; the runtime auto-detects
the transport (tries Streamable HTTP, falls back to SSE).
- provider/tools/loaders/mcp.py: add _init_remote_server() with
Streamable-HTTP-then-SSE probing; dispatch 'remote' lifecycle, keep
legacy sse/http branches for back-compat
- plugin/connector.py: normalize legacy http/sse marketplace modes to
'remote' on Space install, preserving connection params
- entity/persistence/mcp.py: document mode as stdio, remote (legacy: sse, http)
- alembic 0006: idempotent data migration mapping existing sse/http rows
to remote (downgrade maps back to http)
- api/http/service/mcp.py: stash runtime_info (status + tool list) into
test task metadata before tearing down the temp session
- web: collapse mode dropdown to local/remote, remote renders URL+timeout
only, edit auto-maps legacy sse/http to remote; show tools after test in
create mode from task metadata; remove dead plugins/mcp-server/ tree
- i18n: local/remote labels + mode/url hints across 8 locales
* 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 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.
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.
Add a Logs tab beside Documentation on the plugin detail page, showing
the output a plugin prints through the standard Python logger (per the
wiki style guide). Logs are captured from the plugin's stderr by the
plugin runtime and fetched on demand.
- Bump langbot-plugin pin to 0.4.4 (adds GET_PLUGIN_LOGS action)
- plugin_connector/handler: get_plugin_logs RPC client
- HTTP route GET /api/v1/plugins/<author>/<name>/logs (limit + level)
- Frontend: wrap detail right panel in Docs/Logs Tabs; PluginLogs
component with level filter, manual + 3s auto refresh, bottom-follow
- i18n: 7 new keys across all 8 locales
- i18n: add models.searchProviders, monitoring.tabs.tokens and the
monitoring.tokens.* block (incl. bucket.hour/day) to es-ES, ja-JP,
ru-RU, th-TH, vi-VN and zh-Hant, which were missing them and failed
the Check i18n Keys CI.
- api: generate_jwt_token built 'exp' from a naive datetime.now(), which
PyJWT validates against UTC — in any timezone ahead of UTC the token
was already expired at issue time. Use datetime.now(timezone.utc).
* 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>
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.
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.
Junyan Qin