# LangBot

Production-grade platform for building agentic IM bots across Discord, Slack, Telegram, LINE, WeChat, Feishu, DingTalk, and more.

## Agent Decision Summary
- Risk level: elevated
- Source confidence: medium
- Recommended workflows: Local or private AI stack
- Permission surface: messages
- Agent JSON: https://www.openagent.bot/bots/langbot.agent.json

## Summary
LangBot is an open-source AI bot project focused on production-grade platform for building agentic im bots across discord, slack, telegram, line, wechat, feishu, dingtalk, and more.


## Guide
### What it is
LangBot is an open-source AI bot project tracked by OpenAgent.bot. LangBot is an open-source AI bot project focused on production-grade platform for building agentic im bots across discord, slack, telegram, line, wechat, feishu, dingtalk, and more.

### Why it matters
LangBot matters because many useful agents will not live only inside an IDE or web app. They need to work inside the communication channels people already use, with source code that can be inspected, self-hosted, and adapted around privacy, permissions, memory, and operational controls.

### How it works
Open the official repository first, review setup instructions, verify the license, then test the project with non-sensitive data before connecting real accounts or production workflows.


### FAQ
- Is LangBot open source?
  - Yes. The linked GitHub repository lists Apache-2.0 licensing information; verify the current license before production use.
- Who should evaluate LangBot?
  - Builders evaluating self-hosted AI bots for real messaging channels
## What It Does
LangBot is an open-source AI bot project tracked by OpenAgent.bot. LangBot is an open-source AI bot project focused on production-grade platform for building agentic im bots across discord, slack, telegram, line, wechat, feishu, dingtalk, and more.

## How To Evaluate
Open the official repository first, review setup instructions, verify the license, then test the project with non-sensitive data before connecting real accounts or production workflows.

## Why It Matters
LangBot matters because many useful agents will not live only inside an IDE or web app. They need to work inside the communication channels people already use, with source code that can be inspected, self-hosted, and adapted around privacy, permissions, memory, and operational controls.


## Best For
- Builders evaluating self-hosted AI bots for real messaging channels
- Teams comparing Discord, Telegram, Slack, WhatsApp, Matrix, or WeChat AI assistant options
- Developers who want open-source bot infrastructure instead of closed chatbot SaaS

## Not For
- Teams unwilling to review bot permissions, channel credentials, and data retention policies
- Users who only need a hosted consumer chatbot with no deployment work

## What It Actually Does
- Lives in existing communication channels: LangBot brings AI assistance into messaging surfaces rather than forcing users into a separate app.
  - Why it matters: Bots become useful when they meet users where coordination already happens.
- Self-hostable source path: The public repository lets teams inspect runtime behavior, credentials handling, and integration choices before deployment.
  - Why it matters: AI bots can see sensitive conversations, so source review and controlled hosting matter.
- Good comparison target for agent gateways: The project shows how open bots connect LLMs, permissions, plugins, memory, or channel adapters.
  - Why it matters: These patterns are likely to become a core part of practical open-agent infrastructure.

## Typical Use Cases
- Team chat AI assistant: Deploy or study LangBot as a starting point for AI help inside messaging channels.
- Personal always-on bot: Evaluate whether its channel support, model support, and hosting model fit a private personal assistant workflow.
- Agent gateway prototype: Use the project to compare how bots handle message routing, model calls, plugins, and long-running tasks.

## How It Compares
- When to choose LangBot: Choose it when its official repository shows the workflow, license, and integration model you need more directly than a broad framework.

## Fit Matrix
- Local or private AI stack: strong. LangBot has multiple signals for local or private ai stack, including matching tags, capabilities, category, or positioning. Required check: Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
- Browser automation: partial. LangBot has at least one signal for browser automation, but should be checked against a real task before adoption. Required check: Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs.
- Coding agent workflow: partial. LangBot has at least one signal for coding agent workflow, but should be checked against a real task before adoption. Required check: Run a small repository change and inspect the diff, tests, and rollback path.
- Evaluation and observability: partial. LangBot has at least one signal for evaluation and observability, but should be checked against a real task before adoption. Required check: Add one repeatable test case and confirm results can run again in review or CI.
- Memory or RAG workflow: partial. LangBot has at least one signal for memory or rag workflow, but should be checked against a real task before adoption. Required check: Create, update, retrieve, correct, and delete memory or retrieval objects with real data.
- Reusable skill workflow: partial. LangBot has at least one signal for reusable skill workflow, but should be checked against a real task before adoption. Required check: Run one skill end to end and check whether it produces evidence or structured output.

## Evidence
- verified: LangBot is listed as open source. Source: License metadata: Apache-2.0
- verified: LangBot has a recorded GitHub repository: langbot-app/LangBot. Source: Resource facts and GitHub source link.
- inferred: LangBot supports these recorded deployment modes: self hosted, cloud. Source: OpenAgent decision signal metadata.
- inferred: LangBot is tagged with messaging, workflow orchestration capabilities. Source: OpenAgent capability taxonomy.

## Missing Checks
- Dedicated docs link is missing.
- Repository freshness has not been recorded.

## Next Actions
- Inspect repository: https://github.com/langbot-app/LangBot

## Facts
- Category: bots
- Resource type: bot
- Open source: yes
- License: Apache-2.0
- Last verified: 2026-06-05
- GitHub repo: langbot-app/LangBot
- GitHub stars: 16210

## Capabilities
- messaging
- workflow-orchestration

## Structured Use Case Tags
- self-hosted-ai
- chatbot

## Getting Started
- Review the repository: https://github.com/langbot-app/LangBot

## Links
- GitHub: https://github.com/langbot-app/LangBot

## Structured Outputs
- JSON: https://www.openagent.bot/bots/langbot.json
- Markdown: https://www.openagent.bot/bots/langbot.md
- Agent JSON: https://www.openagent.bot/bots/langbot.agent.json
- Canonical: https://www.openagent.bot/bots/langbot