- 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
Apache-2.0 ยท Bots
LangBot
Production-grade platform for building agentic IM bots across Discord, Slack, Telegram, LINE, WeChat, Feishu, DingTalk, and more.
16K stars 1.4K forks Apache-2.0 license 2026-06-05 verified
$
# LangBot$
pip install langbot$
npx langbot --help Open sourceSelf-hosted
Overview
What is LangBot?
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.
Lives in existing communication channels
LangBot brings AI assistance into messaging surfaces rather than forcing users into a separate app.
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.
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.
These patterns are likely to become a core part of practical open-agent infrastructure. Use cases
What teams use it for
Ecosystem
Tags & capabilities
Integrations
Comparison
How it stacks up
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.
FAQ
Questions
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
Decision brief
JSON
Should you use LangBot?
- Teams unwilling to review bot permissions, channel credentials, and data retention policies
- Users who only need a hosted consumer chatbot with no deployment work
- Verified 2026-06-05
- License: Apache-2.0
- Repo: langbot-app/LangBot
- Open-source signal
Deployment
self hosted, cloud
Permission surface
messages
Decision signals
Self-hostable
Agent packet
Structured decision data for LangBot
This packet is the compact machine-readable view agents should use before following source links or taking action.
Capabilities
messaging, workflow orchestration
Constraints
open source, self hosted
Deployment
self hosted, cloud
Permission surface
messages
Recommended workflows
Local or private AI stack
Overview
What LangBot does
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 to evaluate it
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.
Facts
Known metadata and operating surface
These fields are separated from editorial interpretation so agents can reason over facts and missing checks.
Resource type bot
Category Bots
Maturity active
Difficulty Unknown
License Apache-2.0
Pricing open source
Verified 2026-06-05
Source confidence medium
Risk level elevated
Fit matrix
Where LangBot fits in an agent stack
strong
Local or private AI stack
LangBot has multiple signals for local or private ai stack, including matching tags, capabilities, category, or positioning.
- Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Browser automation
LangBot has at least one signal for browser automation, but should be checked against a real task before adoption.
- Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Coding agent workflow
LangBot has at least one signal for coding agent workflow, but should be checked against a real task before adoption.
- Run a small repository change and inspect the diff, tests, and rollback path.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Evaluation and observability
LangBot has at least one signal for evaluation and observability, but should be checked against a real task before adoption.
- Add one repeatable test case and confirm results can run again in review or CI.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Memory or RAG workflow
LangBot has at least one signal for memory or rag workflow, but should be checked against a real task before adoption.
- Create, update, retrieve, correct, and delete memory or retrieval objects with real data.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Reusable skill workflow
LangBot has at least one signal for reusable skill workflow, but should be checked against a real task before adoption.
- Run one skill end to end and check whether it produces evidence or structured output.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
Inputs and outputs
What an agent should inspect
Likely inputs
- Repositories, files, issues, terminal output, and test results
- Official setup instructions and a small real workflow
Likely outputs
- Diffs, commits, explanations, test results, or review notes
- Scores, traces, regression results, dashboards, or failure cases
- A decision on whether this resource fits the target workflow
Evidence
Sources, claims, and missing checks
Claims are marked separately from source links so future crawlers and reviewers can update them without rewriting the page.
LangBot is listed as open source.
License metadata: Apache-2.0LangBot has a recorded GitHub repository: langbot-app/LangBot.
Resource facts and GitHub source link.LangBot supports these recorded deployment modes: self hosted, cloud.
OpenAgent decision signal metadata.LangBot is tagged with messaging, workflow orchestration capabilities.
OpenAgent capability taxonomy.- Dedicated docs link is missing.
- Repository freshness has not been recorded.
Next action
How to start evaluating LangBot
Inspect repository
Check license, recent activity, issues, examples, and security-sensitive code paths.
Open source Compare
Alternatives and nearby resources
Use related resources to compare category fit, license, deployment model, and first-workflow behavior.
FAQ
Common questions about LangBot
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