LangBot
0
LangBot is an open-source LLM-native instant messaging robot platform designed to connect large language models and AI applications to any chat service. It supports major messaging platforms like QQ, WeChat, Discord, Slack, and Feishu, allowing easy integration with OpenAI, DeepSeek, and local models. With a web-based UI and flexible configuration, developers can deploy, manage, and customize bots to handle customer queries, notifications, and automated workflows seamlessly.
AI Memory Systems
AI Platforms & Frameworks
Web Tools
Text Generation
#Chatbot Development
#AI Integration
#multi-channel messaging
#Open-source AI
#customer service automation
#scalable architecture
#conversation workflows
#bot management
#plugin framework
#Large Language Models
#rate limiting strategies
#analytics tools
#enterprise messaging solutions
#rapid deployment
#Community Management Tools
#customizable responses
#role-based access
#local model support
#messaging platform unification
...
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LangBot is an open-source LLM-native instant messaging robot platform designed to connect large language models and AI applications to any chat service. It supports major messaging platforms like QQ, WeChat, Discord, Slack, and Feishu, allowing easy integration with OpenAI, DeepSeek, and local models. With a web-based UI and flexible configuration, developers can deploy, manage, and customize bots to handle customer queries, notifications, and automated workflows seamlessly.
AI Memory Systems
AI Platforms & Frameworks
Web Tools
Text Generation
#Chatbot Development
#AI Integration
#multi-channel messaging
#Open-source AI
#customer service automation
#scalable architecture
#conversation workflows
#bot management
#plugin framework
#Large Language Models
#rate limiting strategies
#analytics tools
#enterprise messaging solutions
#rapid deployment
#Community Management Tools
#customizable responses
#role-based access
#local model support
#messaging platform unification
...
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What is LangBot?
LangBot is a self-hosted, open-source platform that enables seamless integration of large language models into multiple messaging channels. It offers a web-based UI for deploying and managing bots, supports model providers including OpenAI, DeepSeek, and local LLMs, and adapts to platforms such as QQ, WeChat, Discord, Slack, Feishu, and DingTalk. Developers can configure conversation workflows, implement rate limiting strategies, and extend functionality with plugins. Built for scalability, LangBot unifies message handling, model interaction, and analytics into a single framework, accelerating the creation of conversational AI applications for customer service, internal notifications, and community management.
Who will use LangBot?
- Software developers
- Customer support teams
- DevOps engineers
- AI enthusiasts
- SMB and enterprise IT teams
How to use the LangBot?
- Step1: Clone the LangBot repository or download the release package from GitHub.
- Step2: Install dependencies and set up the environment (Node.js, Docker, or Python as required).
- Step3: Configure your preferred LLM providers (OpenAI, DeepSeek, local Ollama) in the settings file.
- Step4: Obtain API tokens or credentials for each messaging platform (Slack, WeChat, QQ, Discord, etc.).
- Step5: Update the platform integration settings with tokens and webhook URLs.
- Step6: Start the LangBot server and access the web UI at http://localhost:port.
- Step7: In the web UI, create and customize bot instances, define conversation workflows, and set rate limits.
- Step8: Deploy bots to production and monitor logs and usage in the dashboard.
Platform
- web
- mac
- windows
- linux
LangBot's Core Features & Benefits
The Core Features
- Multi-platform messaging integration (Slack, WeChat, QQ, Discord, Feishu, DingTalk)
- Support for multiple LLM providers (OpenAI, DeepSeek, Ollama, local models)
- Web-based UI for bot management and configuration
- Customizable conversation workflows and response strategies
- Plugin and extension framework for additional functionality
- Session rate limiting and retry strategies
- Role-based access control and multi-tenant support
The Benefits
- Rapid deployment of AI chatbots across channels
- Open-source flexibility for custom extensions
- Unified interface for managing multiple messaging platforms
- Scalable architecture for enterprise workloads
- Flexible model integration to optimize cost and performance
- Improved customer engagement with automated responses
LangBot's Main Use Cases & Applications
- 24/7 customer service chatbots for e-commerce
- Internal team notifications and alerts in Slack or Teams
- Automated community moderation on Discord
- Sales lead qualification via messaging apps
- IT helpdesk automation for employee support
LangBot's Pros & Cons
The Pros
Supports multiple large language models and platforms
High stability and rich features including access control and filtering
Plugin extensibility with a large active community
Multi-platform support including QQ, WeChat, Discord, Telegram, Slack
Offers various deployment options including Docker and cloud services
Web management panel simplifies configuration and operation
The Cons
No dedicated official mobile app links for iOS or Android found
Some supported platforms are still in development
Installation and maintenance may require technical knowledge
FAQs of LangBot
LangBot Company Information
Analytic of LangBot
Visit Over Time
Monthly Visits
23.2k
Avg Visit Duration
00:07:48
Page Per Visit
6.05
Bounce Rate
37.51%
Nov 2025 - Jan 2026 All Traffic
Geography
Top 5 Regions
China
81.89%
Taiwan
9.73%
United States
3.29%
Hong Kong
2.9%
Japan
1.72%
Nov 2025 - Jan 2026 Worldwide Desktop Only
Traffic Sources
Direct
61.63%
Referrals
19.63%
Search
17.63%
Social
0.67%
Paid Referrals
0.36%
Mail
0.07%
Nov 2025 - Jan 2026 Desktop Only
Top Keywords
| Keyword | Traffic | Cost Per Click |
|---|---|---|
| langbot | 220 | $ 2.00 |
| qq群机器人 | 150 | $ -- |
| 企业微信智能机器人开发和botid | -- | $ -- |
| newapi | 10.3k | $ 3.28 |
| 如何qq加上ai机器人 | 200 | $ -- |
LangBot Reviews
5/5
LangBot's Main Competitors and alternatives?
- Botpress
- Rasa
- Microsoft Bot Framework
- Dialogflow
- OpenDialog
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