
chatwiki
开箱即用的基于企业私有知识库的LLM大语言模型的智能客服机器人问答系统,支持私有化部署,代码免费开源且可商用,由芝麻小客服官方推出。
Stars: 415

ChatWiki is an open-source knowledge base AI question-answering system. It is built on large language models (LLM) and retrieval-augmented generation (RAG) technologies, providing out-of-the-box data processing, model invocation capabilities, and helping enterprises quickly build their own knowledge base AI question-answering systems. It offers exclusive AI question-answering system, easy integration of models, data preprocessing, simple user interface design, and adaptability to different business scenarios.
README:
ChatWiki是一款开源的知识库 AI 问答系统。系统基于大语言模型(LLM )和检索增强生成(RAG)技术构建,提供开箱即用的数据处理、模型调用等能力,可以帮助企业快速搭建自己的知识库AI 问答系统。
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🚀推荐先使用chatwiki云版本,快速构建验证思路与模式,之后再考虑独立部署,减少试错成本。👉️👉️chatwiki.com
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🚀也可以通过官方demo体验对话效果👉️👉️体验ChatWiki WebApp👉️👉️体验ChatWiki 客户端
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🚀点击下方图片,查看chatwiki演示视频
简单易用的企业专属AI问答智能体
通过导入企业已有知识构建知识库,让 AI 机器人使用关联的知识库回答问题,快速构建企业专属 AI 问答系统。支持DeepSeek R1、doubao pro、qwen max、Openai、Claude 等全球20多种主流模型。
灵活的工作流配置
提供灵活的工作流配置功能,支持多步骤任务编排与自动化处理。用户可根据业务需求自定义问答流程、数据流转,实现复杂场景下的智能化协作与管理。通过工作流,可以实现聊天机器人与业务系统的互通。
提供了多样化的调用渠道
支持 嵌入网站、桌面客户端、WebApp、微信小程序、微信公众号、微信客服、抖音企业号、快手号、视频号 及API调用等,全面覆盖企业多终端业务场景需求。
1、文档图片智能提取与回复
支持从上传的PDF、Word等知识库文档中自动提取内嵌图片,问答过程中当关联到含图片的文档内容时,机器人将同步返回文本与图片信息,实现精准的图文关联回复。
2、对外知识库门户一键生成
内置企业级帮助中心构建能力,支持将知识库内容快速发布为可公开访问的文档站点,提供SEO优化、多访问统计等功能,轻松打造品牌化客户支持门户。
3、智能上下文问题优化
ChatWiki可实时分析用户提问上下文,自动补全模糊或不完整的用户问题。通过意图识别与语义联想,将原始问题转化为精准检索指令,显著提升知识库检索命中率与回答相关性。
4、智能问题引导与常见问题
基于语义分析自动生成**「猜你想问」**推荐列表,也支持手动维护高频常见问题,结合用户历史交互动态优化推荐逻辑,有效提升问题命中率与用户体验。
5、精细化权限管理体系
提供企业级多级权限控制,支持角色分配(管理员/编辑员/只读成员),满足敏感数据管控与团队协作需求。
6、支持几乎所有主流模型
ChatWiki已支持全球20多种主流模型,只需要简单配置模型API key等信息即可成功接入模型。
7、数据自动预处理
提供自动分段、QA分段、手动输入和 CSV 等多种方式导入数据,ChatWiki自动对导入的文本数据进行预处理、向量化或 QA 分割。
8、简单易用的使用方式
ChatWiki采用直观的可视化界面设计,通过简洁易懂的操作步骤,可以轻松完成 AI 问答机器人和知识库的创建。
9、本地化数据存储与安全保障
ChatWiki支持企业使用本地数据库进行数据存储,确保数据完全自主掌控。通过多层安全防护机制(包括数据加密传输、访问权限控制、审计日志等),保障企业敏感信息的安全性,严格遵循数据隐私保护法规,为企业提供安全可靠的知识管理环境。
准备工作
在安装ChatWiki之前,您需要准备一台具有联网功能的linux服务器,并确保服务器满足最低系统要求
- Cpu:最低需要4 Core
- RAM:最低需要16 GB
开始安装
ChatWiki社区版基于Docker部署,请先确保服务器已经安装好Docker。如果没有安装,可以通过以下命令安装:
sudo curl -sSL https://get.docker.com/ | CHANNEL=stable sh
安装好Docker后,逐步执行一下步骤安装ChatWiki社区版
(1).克隆或下载chatwiki项目代码
//从github 克隆代码
git clone https://github.com/zhimaAi/chatwiki.git
//从gitee克隆代码
git clone [email protected]:zhimaAi/chatwiki.git
(2).使用Docker Compose构建并启动项目
cd chatwiki/docker
docker compose up -d
部署手册
在安装和部署中有任何问题或者建议,可以联系我们获取帮助,也可以参考下面的文档。
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前端:vue.js
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后端:golang +python
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数据库:PostgreSQL16+pgvector+zhparser
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缓存:redis5.0
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web服务:nginx
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异步队列:nsq
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进程管理:supervisor
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模型:支持OpenAI、Google Gemini、Claude3、通义千文、文心一言、讯飞星火、百川、腾讯混元等模型。
欢迎联系我们获取帮助,或者提供建议帮助我们改善ChatWiki。您可以通过以下方式联系我们:
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微信: 使用微信扫码加入ChatWiki技术交流群
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邮箱: 您可以发送邮件到[email protected]联系我们。
本仓库遵循ChatWiki Open Source License 开源协议。ChatWiki Open Source License基于Apache License 2.0协议,但是有一些额外的限制,包括:
1、允许作为后台服务商用,但是不可用于多租户SAAS模式。
2、除非您获取特定的商业许可,否则任何形式的商用服务均不可移除ChatWiki页面上的版权信息和ChatWiki logo。
完整协议请查看ChatWiki Open Source License ,需要获取额外的商业许可请联系我们
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