mirror of
https://github.com/langbot-app/LangBot.git
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RockChinQ
2957e3a04f
The English and Japanese guide/features pages led their platform enumerations with China-only platforms (WeChat, WeCom, DingTalk), and the "AI customer service" example named China-only platforms to a global / Japanese audience. Reorder the marketing enumerations and examples so each locale leads with the platforms mainstream in its region: - en: Discord, Telegram, Slack first, then QQ/WeChat/WeCom/Lark/DingTalk - ja: LINE, Slack, Discord, Telegram first, then the China platforms Only the hero/landing prose and the use-case examples are reordered; the functional webhook/adapter reference lists are left as-is. The Chinese docs already lead with China platforms and are unchanged. No platform is added that LangBot does not actually support.
56 lines
2.9 KiB
Plaintext
56 lines
2.9 KiB
Plaintext
---
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title: "Welcome to LangBot Documentation"
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description: "LangBot is an open-source LLM bot platform connecting Discord, Telegram, WeChat, Slack and more to GPT, Claude, Gemini, DeepSeek and Dify. Start here."
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---
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LangBot is an **open-source, production-grade**, LLM-native instant messaging bot platform. It connects large language models — OpenAI, Anthropic, Gemini, DeepSeek and more — and Agent platforms like Dify, Coze and n8n to mainstream messaging platforms including Discord, Telegram, Slack, QQ, WeChat, WeCom, Lark and DingTalk. With built-in Agent, RAG knowledge base, MCP, Skills and a code sandbox, plus an out-of-the-box web management panel, you can get your AI bot online in minutes — no hand-written config files required.
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## What You Can Build
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- **AI customer service / enterprise assistant**: deploy a knowledge-base-backed AI agent to Slack, Discord, Lark, WeCom or DingTalk to answer customer and employee questions automatically.
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- **Community operations**: provide AI-powered Q&A, content moderation and interaction in Discord, Telegram and QQ groups.
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- **Workflow integration**: plug your existing Dify / n8n / Coze workflows straight into chat platforms — no need to rewrite business logic.
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- **Multi-platform reach**: one bot covers every platform, managed centrally from a unified panel.
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## Documentation Structure
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The documentation is divided into the following sections:
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- Deployment and Usage (Must Read): Detailed steps for deploying and using LangBot
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- Plugins: Information related to plugin usage and development
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- Practice: Many excellent use cases for LangBot
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- Development: Information related to participating in LangBot development
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## Quick Start Guide
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<Tip>
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**Don't want to self-host?** Try [LangBot Cloud](https://space.langbot.app/cloud) — get started instantly with zero infrastructure. Just sign up, pay, and go.
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</Tip>
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> Two ways to get started quickly:
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>
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> - Use the simplified tutorial from community resources (see left sidebar)
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> - Read the documentation to deploy it yourself (method described below)
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### 1. Deploy LangBot
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Read the **Deploy LangBot** section on the left and choose a method to deploy LangBot
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After deployment, open `http://127.0.0.1:5300` or `http://your-server-public-ip:5300`
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Complete the initialization by entering an email and password, and make sure to save them
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### 2. Configure Bots
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Check [Configure Bots](/en/usage/platforms/readme) in the left sidebar
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### 3. Configure Models
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Check [Configure Dialogue Models](/en/usage/models/readme) in the left sidebar
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<br />
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After completing the above two steps, you can start using LangBot. If you need to configure more features, you can set them in the [Pipeline](/en/usage/pipelines/readme) section
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