532b8ce204 feat(agent): add cross-platform interactive cards for QQ, WeCom, Feishu and DingTalk (#2787)
* feat(agent): add cross-platform interactive card tool

* fix(agent): create pipelines with selected runner defaults

* fix(agent): enable reliable cross-platform card interactions

* feat(dingtalk): deliver A2UI cards and restore agent replies

* Fix DingTalk A2UI form submissions and agent replies

* Restore LangBot branding on DingTalk A2UI cards

* Use compatible Markdown link in DingTalk A2UI branding

* Place LangBot branding above DingTalk card content

* Stream DingTalk replies without a source message

* Move DingTalk branding into compact card footer

* fix(wecombot): handle native select card callbacks

* fix(wecombot): stream replies after HITL cards

* fix(dingtalk): show submitted HITL choices in cards

* fix(lark): stream replies after HITL submissions

* fix(plugins): refresh LocalAgent source hashes

* fix(dify): merge HITL resume streaming into in-tree plugin

* feat(interactions): resume runner in place after card submission

* fix(interactions): respect live adapter APIs and preserve deadlines

* fix(ci): lock blocking interaction SDK for dependent checks

* test(runner): keep legacy SDK probe importable

* fix(interactions): align adapter manifests and close timed-out streams

* fix(agent): avoid duplicate replies and enable LocalAgent cards

* chore(plugins): sync LocalAgent catalog version

* refactor(agent): unify blocking interaction callbacks and adapters

* chore(deps): pin blocking interaction SDK revision

* test(agent): remove obsolete async fixture mark

* test(interaction): update legacy admission assertions

* fix(qqofficial): keep card callbacks responsive

* fix(runner): keep blocking card interactions alive

* ci(plugins): expect SDK 0.7.20 in Runner workflows

Co-Authored-By: Claude Opus 5.5 <[email protected]>
Co-authored-by: multica-agent <[email protected]>

* ci(plugins): test coding Runners against SDK 0.7.20

Claude Code and Codex now call ctx.request_interaction, first released in 0.7.20.

Co-Authored-By: Claude Opus 5.5 <[email protected]>
Co-authored-by: multica-agent <[email protected]>

* fix(discord): deliver guild interaction cards to the originating channel

Pipeline group conversations are keyed by guild id, so send_interaction
targeted the guild and Discord returned Unknown Channel. Resolve the channel
from the message being answered, edit cards in that channel, and report the
card's conversation on callbacks so the Host scope check matches.

Co-Authored-By: Claude Opus 5.5 <[email protected]>
Co-authored-by: multica-agent <[email protected]>

---------

Co-authored-by: RockChinQ <[email protected]>
Co-authored-by: Claude Opus 5.5 <[email protected]>
Co-authored-by: multica-agent <[email protected]>
2026-11-03 21:45:49 +08:00
2025-11-06 21:34:02 +08:00
2025-10-07 00:15:56 +08:00
2025-09-13 09:44:18 +08:00

LangBot

LangBot - Easy-to-use global IM bot platform designed for the LLM era | Product Hunt

Production-grade platform for building agentic IM bots.

Quickly build, debug, and ship AI bots to Slack, Discord, Telegram, WeChat, and more.

English / 简体中文 / 繁體中文 / 日本語 / Español / Français / 한국어 / Русский / Tiếng Việt

Discord Ask DeepWiki GitHub release (latest by date) python GitHub stars

Website | Features | Docs | API | Cloud | Plugin Market | Roadmap


What is LangBot?

LangBot is an open-source, production-grade platform for building AI-powered instant messaging bots. It connects Large Language Models (LLMs) to any chat platform, enabling you to create intelligent agents that can converse, execute tasks, and integrate with your existing workflows.

LangBot web management dashboard — real-time monitoring of message volume, model calls, success rate and active sessions

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, Coze, n8n, Langflow, Deerflow, Weknora.
  • 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 support.
  • Web Management Panel — Configure, manage, and monitor your bots through an intuitive browser interface. No YAML editing required.
  • Multi-Pipeline Architecture — Different bots for different scenarios, with comprehensive monitoring and exception handling.

→ Learn more about all features

📍 Practical guides: deploy a multi-platform AI bot in 5 minutes, connect DeepSeek to WeChat, Discord, and Telegram, run a Dify Agent in Discord, Telegram, and Slack, and build an n8n-powered chatbot.


😎 Stay Updated

Click the Star and Watch buttons in the top-right corner of the repository to get the latest updates.

star gif

Quick Start

Official plugin source index: plugins/README.md · machine-readable catalog · independent plugin releases. Plugins are installed separately and are not bundled in Core releases.

Deploy on LangBot Cloud

space.langbot.app/cloud

Zero deployment, ready to use.

One-Line Launch

uvx langbot

Requires uv. Visit http://localhost:5300 — done.

Docker Compose

git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
docker compose --profile all up -d

One-Click Cloud Deploy

Deploy on Zeabur Deploy on Railway

More options: Docker · Manual · BTPanel · Kubernetes


Supported Platforms

Platform Status Notes
Discord ✅ Official
Telegram ✅ Official
Slack ✅ Official
LINE ✅ Official
QQ ✅ Personal & Official API (Channel, DM, Group)
WeCom ✅ Enterprise WeChat, External CS, AI Bot
WeChat ✅ Personal & Official Account
Lark ✅ Official
DingTalk ✅ Official
KOOK ✅ Official
Satori ✅
Email ✅ Matrix, Satori
Matrix ✅ Supports multiple bridged platforms such as Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip, and more

Supported LLMs & Integrations

Provider Type Status
OpenAI LLM ✅
Anthropic LLM ✅
DeepSeek LLM ✅
Google Gemini LLM ✅
xAI LLM ✅
Moonshot LLM ✅
Zhipu AI LLM ✅
Ollama Local LLM ✅
LM Studio Local LLM ✅
Dify LLMOps ✅
MCP Protocol ✅
SiliconFlow Gateway ✅
Aliyun Bailian Gateway ✅
Volc Engine Ark Gateway ✅
ModelScope Gateway ✅
GiteeAI Gateway ✅
CompShare GPU Platform ✅
PPIO GPU Platform ✅
ShengSuanYun GPU Platform ✅
接口 AI Gateway ✅
302.AI Gateway ✅
Qiniu Gateway ✅

→ View all integrations


Why LangBot?

Use Case How LangBot Helps
Customer Support Deploy AI agents to Slack/Discord/Telegram that answer questions using your knowledge base
Internal Tools Connect n8n/Dify workflows to WeCom/DingTalk for automated business processes
Community Management Moderate QQ/Discord groups with AI-powered content filtering and interaction
Multi-Platform Presence One bot, all platforms. Manage from a single dashboard

Built for AI Agents 🤖

LangBot is agent-friendly by design — your coding agents (Claude Code, Codex, Copilot, Cursor, …) can operate, extend, and deploy LangBot with first-class support:

  • MCP Server — LangBot exposes a built-in Model Context Protocol endpoint at /mcp, mirroring the HTTP API so an agent can manage bots, pipelines, plugins, and models programmatically. Authenticate with the same API key (set a global key in config.yaml or use a per-user key) — no login flow required. Configure it in the Web panel's API & MCP tab.
  • CLI (lbctl) — The standalone LangBot CLI lets agents manage a running LangBot Workspace from a terminal through the Service API. It uses an API key and supports bots, pipelines, knowledge bases, models, plugins, skills, and MCP servers. See the CLI repository for installation and commands.
  • In-repo Skills — The skills/ directory is the single source of truth for working with LangBot: plugin development, core development, end-to-end testing, deployment, and operating the LangBot / LangBot Space MCP servers. Point your agent at this directory and it knows how to build.
  • AGENTS.md — Every repo ships an AGENTS.md (symlinked to CLAUDE.md) describing architecture, conventions, and the rule that API changes must keep the MCP server and skills in sync.
  • llms.txt — Machine-readable project context for LLMs is published on the website.

Cloud / Marketplace: LangBot Space also exposes an MCP server so agents can search and inspect the plugin / MCP / skill marketplace, authenticated with a Personal Access Token.


Community

Discord


Contributors

Thanks to all contributors who have helped make LangBot better:

Documentation source · langbot-docs archive

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