[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-alfredfrancis--ai-chatbot-framework":3,"tool-alfredfrancis--ai-chatbot-framework":64},[4,17,27,35,43,56],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":16},3808,"stable-diffusion-webui","AUTOMATIC1111\u002Fstable-diffusion-webui","stable-diffusion-webui 是一个基于 Gradio 构建的网页版操作界面，旨在让用户能够轻松地在本地运行和使用强大的 Stable Diffusion 图像生成模型。它解决了原始模型依赖命令行、操作门槛高且功能分散的痛点，将复杂的 AI 绘图流程整合进一个直观易用的图形化平台。\n\n无论是希望快速上手的普通创作者、需要精细控制画面细节的设计师，还是想要深入探索模型潜力的开发者与研究人员，都能从中获益。其核心亮点在于极高的功能丰富度：不仅支持文生图、图生图、局部重绘（Inpainting）和外绘（Outpainting）等基础模式，还独创了注意力机制调整、提示词矩阵、负向提示词以及“高清修复”等高级功能。此外，它内置了 GFPGAN 和 CodeFormer 等人脸修复工具，支持多种神经网络放大算法，并允许用户通过插件系统无限扩展能力。即使是显存有限的设备，stable-diffusion-webui 也提供了相应的优化选项，让高质量的 AI 艺术创作变得触手可及。",162132,3,"2026-04-05T11:01:52",[13,14,15],"开发框架","图像","Agent","ready",{"id":18,"name":19,"github_repo":20,"description_zh":21,"stars":22,"difficulty_score":23,"last_commit_at":24,"category_tags":25,"status":16},1381,"everything-claude-code","affaan-m\u002Feverything-claude-code","everything-claude-code 是一套专为 AI 编程助手（如 Claude Code、Codex、Cursor 等）打造的高性能优化系统。它不仅仅是一组配置文件，而是一个经过长期实战打磨的完整框架，旨在解决 AI 代理在实际开发中面临的效率低下、记忆丢失、安全隐患及缺乏持续学习能力等核心痛点。\n\n通过引入技能模块化、直觉增强、记忆持久化机制以及内置的安全扫描功能，everything-claude-code 能显著提升 AI 在复杂任务中的表现，帮助开发者构建更稳定、更智能的生产级 AI 代理。其独特的“研究优先”开发理念和针对 Token 消耗的优化策略，使得模型响应更快、成本更低，同时有效防御潜在的攻击向量。\n\n这套工具特别适合软件开发者、AI 研究人员以及希望深度定制 AI 工作流的技术团队使用。无论您是在构建大型代码库，还是需要 AI 协助进行安全审计与自动化测试，everything-claude-code 都能提供强大的底层支持。作为一个曾荣获 Anthropic 黑客大奖的开源项目，它融合了多语言支持与丰富的实战钩子（hooks），让 AI 真正成长为懂上",138956,2,"2026-04-05T11:33:21",[13,15,26],"语言模型",{"id":28,"name":29,"github_repo":30,"description_zh":31,"stars":32,"difficulty_score":23,"last_commit_at":33,"category_tags":34,"status":16},2271,"ComfyUI","Comfy-Org\u002FComfyUI","ComfyUI 是一款功能强大且高度模块化的视觉 AI 引擎，专为设计和执行复杂的 Stable Diffusion 图像生成流程而打造。它摒弃了传统的代码编写模式，采用直观的节点式流程图界面，让用户通过连接不同的功能模块即可构建个性化的生成管线。\n\n这一设计巧妙解决了高级 AI 绘图工作流配置复杂、灵活性不足的痛点。用户无需具备编程背景，也能自由组合模型、调整参数并实时预览效果，轻松实现从基础文生图到多步骤高清修复等各类复杂任务。ComfyUI 拥有极佳的兼容性，不仅支持 Windows、macOS 和 Linux 全平台，还广泛适配 NVIDIA、AMD、Intel 及苹果 Silicon 等多种硬件架构，并率先支持 SDXL、Flux、SD3 等前沿模型。\n\n无论是希望深入探索算法潜力的研究人员和开发者，还是追求极致创作自由度的设计师与资深 AI 绘画爱好者，ComfyUI 都能提供强大的支持。其独特的模块化架构允许社区不断扩展新功能，使其成为当前最灵活、生态最丰富的开源扩散模型工具之一，帮助用户将创意高效转化为现实。",107662,"2026-04-03T11:11:01",[13,14,15],{"id":36,"name":37,"github_repo":38,"description_zh":39,"stars":40,"difficulty_score":23,"last_commit_at":41,"category_tags":42,"status":16},3704,"NextChat","ChatGPTNextWeb\u002FNextChat","NextChat 是一款轻量且极速的 AI 助手，旨在为用户提供流畅、跨平台的大模型交互体验。它完美解决了用户在多设备间切换时难以保持对话连续性，以及面对众多 AI 模型不知如何统一管理的痛点。无论是日常办公、学习辅助还是创意激发，NextChat 都能让用户随时随地通过网页、iOS、Android、Windows、MacOS 或 Linux 端无缝接入智能服务。\n\n这款工具非常适合普通用户、学生、职场人士以及需要私有化部署的企业团队使用。对于开发者而言，它也提供了便捷的自托管方案，支持一键部署到 Vercel 或 Zeabur 等平台。\n\nNextChat 的核心亮点在于其广泛的模型兼容性，原生支持 Claude、DeepSeek、GPT-4 及 Gemini Pro 等主流大模型，让用户在一个界面即可自由切换不同 AI 能力。此外，它还率先支持 MCP（Model Context Protocol）协议，增强了上下文处理能力。针对企业用户，NextChat 提供专业版解决方案，具备品牌定制、细粒度权限控制、内部知识库整合及安全审计等功能，满足公司对数据隐私和个性化管理的高标准要求。",87618,"2026-04-05T07:20:52",[13,26],{"id":44,"name":45,"github_repo":46,"description_zh":47,"stars":48,"difficulty_score":23,"last_commit_at":49,"category_tags":50,"status":16},2268,"ML-For-Beginners","microsoft\u002FML-For-Beginners","ML-For-Beginners 是由微软推出的一套系统化机器学习入门课程，旨在帮助零基础用户轻松掌握经典机器学习知识。这套课程将学习路径规划为 12 周，包含 26 节精炼课程和 52 道配套测验，内容涵盖从基础概念到实际应用的完整流程，有效解决了初学者面对庞大知识体系时无从下手、缺乏结构化指导的痛点。\n\n无论是希望转型的开发者、需要补充算法背景的研究人员，还是对人工智能充满好奇的普通爱好者，都能从中受益。课程不仅提供了清晰的理论讲解，还强调动手实践，让用户在循序渐进中建立扎实的技能基础。其独特的亮点在于强大的多语言支持，通过自动化机制提供了包括简体中文在内的 50 多种语言版本，极大地降低了全球不同背景用户的学习门槛。此外，项目采用开源协作模式，社区活跃且内容持续更新，确保学习者能获取前沿且准确的技术资讯。如果你正寻找一条清晰、友好且专业的机器学习入门之路，ML-For-Beginners 将是理想的起点。",84991,"2026-04-05T10:45:23",[14,51,52,53,15,54,26,13,55],"数据工具","视频","插件","其他","音频",{"id":57,"name":58,"github_repo":59,"description_zh":60,"stars":61,"difficulty_score":10,"last_commit_at":62,"category_tags":63,"status":16},3128,"ragflow","infiniflow\u002Fragflow","RAGFlow 是一款领先的开源检索增强生成（RAG）引擎，旨在为大语言模型构建更精准、可靠的上下文层。它巧妙地将前沿的 RAG 技术与智能体（Agent）能力相结合，不仅支持从各类文档中高效提取知识，还能让模型基于这些知识进行逻辑推理和任务执行。\n\n在大模型应用中，幻觉问题和知识滞后是常见痛点。RAGFlow 通过深度解析复杂文档结构（如表格、图表及混合排版），显著提升了信息检索的准确度，从而有效减少模型“胡编乱造”的现象，确保回答既有据可依又具备时效性。其内置的智能体机制更进一步，使系统不仅能回答问题，还能自主规划步骤解决复杂问题。\n\n这款工具特别适合开发者、企业技术团队以及 AI 研究人员使用。无论是希望快速搭建私有知识库问答系统，还是致力于探索大模型在垂直领域落地的创新者，都能从中受益。RAGFlow 提供了可视化的工作流编排界面和灵活的 API 接口，既降低了非算法背景用户的上手门槛，也满足了专业开发者对系统深度定制的需求。作为基于 Apache 2.0 协议开源的项目，它正成为连接通用大模型与行业专有知识之间的重要桥梁。",77062,"2026-04-04T04:44:48",[15,14,13,26,54],{"id":65,"github_repo":66,"name":67,"description_en":68,"description_zh":69,"ai_summary_zh":69,"readme_en":70,"readme_zh":71,"quickstart_zh":72,"use_case_zh":73,"hero_image_url":74,"owner_login":75,"owner_name":76,"owner_avatar_url":77,"owner_bio":78,"owner_company":79,"owner_location":80,"owner_email":78,"owner_twitter":81,"owner_website":82,"owner_url":83,"languages":84,"stars":113,"forks":114,"last_commit_at":115,"license":116,"difficulty_score":117,"env_os":118,"env_gpu":118,"env_ram":118,"env_deps":119,"category_tags":132,"github_topics":133,"view_count":23,"oss_zip_url":78,"oss_zip_packed_at":78,"status":16,"created_at":146,"updated_at":147,"faqs":148,"releases":182},2125,"alfredfrancis\u002Fai-chatbot-framework","ai-chatbot-framework","A python chatbot framework with Natural Language Understanding and Artificial Intelligence.","ai-chatbot-framework 是一个基于 Python 构建的开源聊天机器人开发平台，旨在让用户无需深厚的编程背景也能轻松打造具备自然语言理解（NLU）和人工智能能力的智能对话助手。它主要解决了传统机器人开发门槛高、配置复杂的问题，通过提供可视化的低代码管理后台，让用户能直观地设计多轮对话场景、训练意图识别与实体提取模型，并轻松部署到网站、Facebook Messenger 等渠道。\n\n这款工具特别适合希望自主掌控数据的企业开发者、AI 爱好者以及需要快速验证对话逻辑的产品团队。其独特亮点在于强大的技术兼容性：既支持传统的 Spacy 词嵌入和机器学习算法，也集成了基于大语言模型（LLM）的零样本 NLU 能力，甚至具备工具调用（API 请求）和持久化上下文记忆功能。此外，项目采用完全自托管架构，结合 Docker 与 Kubernetes 支持，确保了数据隐私与部署灵活性。无论是想从零构建客服机器人，还是探索 RAG 知识库问答，ai-chatbot-framework 都提供了一套完整且现代化的技术栈，帮助使用者高效实现创意。","\u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Falfredfrancis_ai-chatbot-framework_readme_6b4d9a579fe4.png\" width=\"280\"\u002F>\n\n[![Join the chat at https:\u002F\u002Fgitter.im\u002Fai-chatbot-framework\u002FLobby](https:\u002F\u002Fbadges.gitter.im\u002Fai-chatbot-framework\u002FLobby.svg)](https:\u002F\u002Fgitter.im\u002Fai-chatbot-framework\u002FLobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [![Build Status](https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Factions\u002Fworkflows\u002Fevaluate-backend.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Factions\u002Fworkflows\u002Fevaluate-backend.yml) [![Build Status](https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Factions\u002Fworkflows\u002Fevaluate-frontend.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Factions\u002Fworkflows\u002Fevaluate-frontend.yml)\n\n\nAI Chatbot Framework is an open-source, self-hosted, DIY Chatbot building platform built in Python. With this tool, it’s easy to create Natural Language conversational scenarios with no coding efforts whatsoever. \nThe smooth UI makes it effortless to create and train conversations to the bot. AI Chatbot Framework can live on any channel of your choice (such as Messenger, Slack etc.).\n\nYou don’t need to be an expert at artificial intelligence to create an awesome chatbot that has AI capabilities. With this project you can create an AI powered chatbot in no time.  Read the [documentation](docs\u002FREADME.md) to get started.\n\n![](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Falfredfrancis_ai-chatbot-framework_readme_7c9853d2497d.png)\n\n## Features\n- Fully Self-Hosted\n- Low-Code, DIY Admin Dashboard for Bot Development\n- Multi-turn Conversations\n- API request fulfilment (Tool Calling)\n- Persistent Memory & Context Management\n- Advanced Natural Language Understanding (NLU)\n  - Spacy Word Embeddings\n  - Intent Recognition (ML)\n  - Entity Extraction (ML)\n  - Zero shot NLU using Large Language Models (LLMs)\n- Knowledge Base & FAQ answering using RAG (in development)\n- Conversation Logs\n- Channel Integrations\n  - Web via REST API\u002FChat Snippet\n  - Facebook Messenger\n  - Slack (coming soon)\n  - WhatsApp via Twilio (coming soon)\n\n### Documentation\n\nCheck out our [documentation](docs\u002FREADME.md) to get started.\n\n### Tech Stack\n\n - Python \u002F FastAPI \u002F Pydantic\n - MongoDB \u002F Motor\n - React \u002F NextJS\n - scikit-learn \u002F Tensorflow \u002F Keras\n - Spacy \u002F python-crfsuite\n - Docker \u002F docker-compose \u002F Kubernetes \u002F Helm\n\n### Contributing\n\nWant to contribute? Check out our [contribution guidelines](CONTRIBUTING.md).\n\n\u003Chr>\u003C\u002Fhr>\n","\u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Falfredfrancis_ai-chatbot-framework_readme_6b4d9a579fe4.png\" width=\"280\"\u002F>\n\n[![加入聊天室 https:\u002F\u002Fgitter.im\u002Fai-chatbot-framework\u002FLobby](https:\u002F\u002Fbadges.gitter.im\u002Fai-chatbot-framework\u002FLobby.svg)](https:\u002F\u002Fgitter.im\u002Fai-chatbot-framework\u002FLobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [![构建状态](https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Factions\u002Fworkflows\u002Fevaluate-backend.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Factions\u002Fworkflows\u002Fevaluate-backend.yml) [![构建状态](https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Factions\u002Fworkflows\u002Fevaluate-frontend.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Factions\u002Fworkflows\u002Fevaluate-frontend.yml)\n\n\nAI聊天机器人框架是一个开源、可自托管的DIY聊天机器人搭建平台，基于Python开发。借助该工具，无需任何编码即可轻松创建自然语言对话场景。\n其流畅的用户界面使为机器人创建和训练对话变得轻而易举。AI聊天机器人框架可以部署在您选择的任何渠道上（如Messenger、Slack等）。\n\n您无需成为人工智能专家，也能创建具备AI能力的优秀聊天机器人。通过本项目，您可以快速搭建一个由AI驱动的聊天机器人。请阅读[文档](docs\u002FREADME.md)以开始使用。\n\n![](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Falfredfrancis_ai-chatbot-framework_readme_7c9853d2497d.png)\n\n## 功能特性\n- 完全自托管\n- 低代码、DIY管理后台，用于机器人开发\n- 多轮对话\n- API请求执行（工具调用）\n- 持久化记忆与上下文管理\n- 高级自然语言理解（NLU）\n  - SpaCy词嵌入\n  - 意图识别（机器学习）\n  - 实体抽取（机器学习）\n  - 使用大型语言模型（LLMs）实现零样本NLU\n- 基于RAG的知识库与FAQ问答功能（开发中）\n- 对话日志\n- 渠道集成\n  - Web端：通过REST API\u002F聊天小部件\n  - Facebook Messenger\n  - Slack（即将支持）\n  - WhatsApp：通过Twilio接入（即将支持）\n\n### 文档\n请查看我们的[文档](docs\u002FREADME.md)，开始使用。\n\n### 技术栈\n- Python \u002F FastAPI \u002F Pydantic\n- MongoDB \u002F Motor\n- React \u002F Next.js\n- scikit-learn \u002F TensorFlow \u002F Keras\n- SpaCy \u002F python-crfsuite\n- Docker \u002F docker-compose \u002F Kubernetes \u002F Helm\n\n### 贡献\n想参与贡献吗？请查看我们的[贡献指南](CONTRIBUTING.md)。\n\n\u003Chr>\u003C\u002Fhr>","# AI Chatbot Framework 快速上手指南\n\nAI Chatbot Framework 是一个基于 Python 的开源、自托管对话机器人构建平台。它提供低代码管理面板，支持多轮对话、工具调用（API）、持久化记忆以及基于 LLM 的零样本自然语言理解（NLU），无需深厚的 AI 背景即可快速搭建智能客服或助手。\n\n## 环境准备\n\n在开始之前，请确保您的开发环境满足以下要求：\n\n*   **操作系统**：Linux (推荐 Ubuntu\u002FCentOS), macOS 或 Windows (需安装 WSL2)\n*   **核心依赖**：\n    *   [Docker](https:\u002F\u002Fdocs.docker.com\u002Fget-docker\u002F) (版本 20.10+)\n    *   [Docker Compose](https:\u002F\u002Fdocs.docker.com\u002Fcompose\u002Finstall\u002F) (版本 2.0+)\n    *   Git\n*   **硬件建议**：至少 4GB 可用内存（若启用大型语言模型功能，建议 8GB+）\n\n> **国内加速提示**：\n> 若拉取 Docker 镜像速度较慢，建议配置国内镜像加速器（如阿里云、腾讯云、网易云等）。\n> 编辑 `\u002Fetc\u002Fdocker\u002Fdaemon.json` (Linux) 或 Docker Desktop 设置，添加如下配置示例：\n> ```json\n> {\n>   \"registry-mirrors\": [\"https:\u002F\u002F\u003Cyour-id>.mirror.aliyuncs.com\"]\n> }\n> ```\n> 配置后重启 Docker 服务：`sudo systemctl restart docker`\n\n## 安装步骤\n\n本项目推荐使用 Docker Compose 进行一键部署，包含后端 (FastAPI)、前端 (NextJS) 及数据库 (MongoDB)。\n\n1.  **克隆项目仓库**\n    ```bash\n    git clone https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework.git\n    cd ai-chatbot-framework\n    ```\n\n2.  **配置环境变量（可选）**\n    复制示例配置文件并根据需要修改（例如设置 MongoDB 密码或 LLM API Key）：\n    ```bash\n    cp .env.example .env\n    # 使用编辑器修改 .env 文件\n    ```\n\n3.  **启动服务**\n    在项目根目录下运行以下命令构建并启动所有容器：\n    ```bash\n    docker-compose up -d --build\n    ```\n\n4.  **验证安装**\n    等待约 1-2 分钟让服务初始化完成后，访问以下地址：\n    *   **管理后台**：`http:\u002F\u002Flocalhost:3000`\n    *   **API 文档**：`http:\u002F\u002Flocalhost:8000\u002Fdocs`\n\n## 基本使用\n\n安装完成后，您可以通过可视化的管理后台轻松创建第一个机器人。\n\n### 1. 创建新机器人\n1.  登录管理后台 (`http:\u002F\u002Flocalhost:3000`)。\n2.  点击 **\"Create New Bot\"**，输入机器人名称和描述。\n3.  进入机器人配置页面。\n\n### 2. 训练对话场景 (No-Code)\n在 **Training** 选项卡中，您可以定义意图（Intents）和实体（Entities）：\n*   **添加用户语句**：输入用户可能说的话（例如：\"我想查询天气\"、\"今天气温多少\"）。\n*   **标记实体**：选中句子中的关键信息（如地点、时间），将其标记为 Entity。\n*   **设置回复**：配置机器人的回应文本或触发 API 调用。\n*   点击 **\"Train\"** 按钮，系统将自动利用 Spacy 或配置的 LLM 进行模型训练。\n\n### 3. 测试与集成\n*   **在线测试**：切换到 **Chat** 选项卡，直接在浏览器中与刚训练好的机器人对话，验证多轮上下文和意图识别效果。\n*   **渠道集成**：\n    *   **Web 嵌入**：在 **Settings** 中获取 Chat Snippet 代码，将其粘贴到您的网站 HTML 中即可悬浮显示。\n    *   **API 调用**：通过 `http:\u002F\u002Flocalhost:8000\u002Fapi\u002Fchat` 发送 POST 请求集成到其他应用。\n    ```bash\n    curl -X POST http:\u002F\u002Flocalhost:8000\u002Fapi\u002Fchat \\\n      -H \"Content-Type: application\u002Fjson\" \\\n      -d '{\"bot_id\": \"your-bot-id\", \"message\": \"你好\"}'\n    ```\n\n现在，您已经成功部署并运行了一个具备自然语言理解能力的 AI 聊天机器人。更多高级功能（如 RAG 知识库、复杂工具调用）请参考项目官方文档。","某中型电商公司的客服团队希望为官网构建一个能理解用户自然语言、自动处理退换货查询的智能助手，以减轻人工压力。\n\n### 没有 ai-chatbot-framework 时\n- **开发门槛高**：团队需从零搭建 NLP 模型，非 AI 专家的后端开发人员难以独立完成意图识别和实体提取算法。\n- **上下文丢失严重**：传统规则机器人无法记忆多轮对话，用户需重复陈述订单号或问题细节，体验极差。\n- **集成与维护复杂**：缺乏统一的管理后台，每次更新问答逻辑都需修改代码并重新部署，且难以同时对接网页和 Facebook Messenger 等多渠道。\n- **数据隐私担忧**：使用第三方 SaaS 聊天机器人服务导致客户敏感数据存储在外部服务器，不符合公司数据安全合规要求。\n\n### 使用 ai-chatbot-framework 后\n- **低代码快速构建**：利用其可视化 Admin Dashboard，客服人员无需编写代码即可通过界面训练“退货”、“查单”等意图，Spacy 和 LLM 技术自动处理复杂的自然语言理解。\n- **智能记忆多轮交互**：内置的持久化内存机制让机器人能记住用户上一句提供的订单号，在后续追问中自动关联上下文，实现流畅的多轮对话。\n- **全渠道一键分发**：通过配置即可将同一套对话逻辑同时发布到官网 REST API 和 Facebook Messenger，并在统一后台查看日志和管理回复策略。\n- **完全自主可控**：基于 Docker 实现完全自托管，所有对话数据和用户信息均存储在公司内部的 MongoDB 中，彻底消除数据外泄风险。\n\nai-chatbot-framework 让非 AI 专家也能在保障数据隐私的前提下，低成本构建出具备深度理解能力的企业级智能客服系统。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Falfredfrancis_ai-chatbot-framework_7c9853d2.png","alfredfrancis","Alfred Francis","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002Falfredfrancis_aa63c887.jpg",null,"DeliveryHero","Berlin, Germany","alfredpfrancis","https:\u002F\u002Falfredfrancis.in\u002F","https:\u002F\u002Fgithub.com\u002Falfredfrancis",[85,89,93,97,101,105,109],{"name":86,"color":87,"percentage":88},"TypeScript","#3178c6",48.6,{"name":90,"color":91,"percentage":92},"Python","#3572A5",43.7,{"name":94,"color":95,"percentage":96},"JavaScript","#f1e05a",4.4,{"name":98,"color":99,"percentage":100},"CSS","#663399",1.4,{"name":102,"color":103,"percentage":104},"Dockerfile","#384d54",1,{"name":106,"color":107,"percentage":108},"Smarty","#f0c040",0.8,{"name":110,"color":111,"percentage":112},"Shell","#89e051",0.1,2152,746,"2026-04-01T06:12:00","MIT",4,"未说明",{"notes":120,"python":118,"dependencies":121},"该项目支持完全自托管，提供 Docker、docker-compose、Kubernetes 和 Helm 部署方案。后端基于 Python (FastAPI)，前端基于 React (NextJS)。功能涵盖多轮对话、工具调用、持久化记忆及基于 Spacy 和大语言模型（LLM）的自然语言理解（NLU）。目前知识库与 RAG 功能尚在开发中。",[122,123,124,125,126,127,128,129,130,131],"FastAPI","Pydantic","MongoDB","Motor","React","NextJS","scikit-learn","Tensorflow","Keras","Spacy",[13,26],[134,67,135,136,137,138,139,140,141,142,143,144,145],"chatbot","ai-chatbot","conversational-ai","hacktoberfest","help-wanted","llm","tool-calling","deepseek","langchain","nextjs","openai","python","2026-03-27T02:49:30.150509","2026-04-06T07:05:51.220422",[149,154,158,163,168,173,178],{"id":150,"question_zh":151,"answer_zh":152,"source_url":153},9773,"如何在 Windows 系统上运行该项目？","在 Windows 上直接运行可能会遇到 'make' 命令无法识别的问题。推荐的解决方案是使用 Docker Compose 进行部署，这在 Ubuntu 和 Windows（通过 Docker Desktop）上都能正常工作。请按照项目文档中的 Docker Compose 设置指南进行操作，以避免环境配置困难。","https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fissues\u002F89",{"id":155,"question_zh":156,"answer_zh":157,"source_url":153},9774,"运行时出现 'RuntimeError: module compiled against API version...' (numpy 版本不匹配) 错误怎么办？","该错误通常是由于 numpy、pandas 或 tensorflow 的版本不兼容导致的。虽然尝试单独更改这些库的版本可能无效，但最稳定的解决方法是使用官方推荐的 Docker Compose 设置，它能确保所有依赖项的版本正确匹配。如果必须在本地运行，请检查并重新安装与当前 TensorFlow 版本兼容的 numpy 版本。",{"id":159,"question_zh":160,"answer_zh":161,"source_url":162},9775,"与机器人聊天时遇到 '500 Internal Server Error' 错误如何解决？","此错误通常与 Flask 版本有关（特别是 Flask 0.12.3 存在已知问题）。解决方案是将 Flask 降级到 0.12.2 或升级到 0.12.4 及以上版本。如果您使用的是 Docker，可以通过查看日志确认错误：`docker-compose exec iky_backend cat logs\u002Fgunicorn-error.log`，然后调整依赖版本重新构建。","https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fissues\u002F80",{"id":164,"question_zh":165,"answer_zh":166,"source_url":167},9776,"添加意图（Intent）时出现 '502 Bad Gateway' 或 'Host is unreachable' 错误怎么办？","这通常是由于后端服务未正确启动或容器间网络通信失败导致的。请确保您使用的是最新的 master 分支代码，该问题已在最新版本中修复。务必使用 `docker-compose` 进行设置，如果问题依旧，请运行 `docker-compose logs` 命令查看详细输出以便进一步排查。","https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fissues\u002F152",{"id":169,"question_zh":170,"answer_zh":171,"source_url":172},9777,"运行 'make setup' 时提示 'Failed to load nlu model' 或路径不存在错误怎么办？","此问题通常是由 spacy 和 flask 之间的版本不匹配引起的。维护者已确认该问题并在后续版本中修复。请确保拉取最新的代码库，或者手动检查并调整 spacy 和 flask 的版本以确保兼容性。建议使用 Docker 环境以避免此类本地依赖冲突。","https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fissues\u002F116",{"id":174,"question_zh":175,"answer_zh":176,"source_url":177},9778,"框架是否支持西班牙语或其他非英语语言？","是的，框架支持多语言。您可以创建特定语言（如西班牙语）的故事（stories）并使用相应的意图（intents）进行训练。系统的响应可以通过 API 调用获取，根据您的参数配置，可以返回多种语言的回复。","https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fissues\u002F27",{"id":179,"question_zh":180,"answer_zh":181,"source_url":172},9779,"在非 Docker 环境下（如 Mac）安装时遇到依赖或模型加载问题怎么办？","非 Docker 安装容易受到操作系统和本地 Python 环境差异的影响，导致模型加载失败或命令执行错误。如果遇到此类问题，强烈建议切换到 Docker Compose 安装方式，这是官方推荐的方法，能够屏蔽底层环境差异，确保 'make setup' 和模型训练等步骤顺利执行。",[183,188,193,198,203,208,213,218,223,228,233],{"id":184,"version":185,"summary_zh":186,"released_at":187},107070,"v1.0.0-alpha.10","## What's Changed\r\n* refactor: Intent & Entity UI improvements by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F194\r\n* chore: more documentation by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F192\r\n* chore: update llm integration docs by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F193\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcompare\u002Fv1.0.0-alpha.9...v1.0.0-alpha.10","2025-02-03T12:35:04",{"id":189,"version":190,"summary_zh":191,"released_at":192},107071,"v1.0.0-alpha.9","## What's Changed\r\n* fix: fix context propagation by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F190\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcompare\u002Fv1.0.0-alpha.8...v1.0.0-alpha.9","2025-02-02T10:33:20",{"id":194,"version":195,"summary_zh":196,"released_at":197},107072,"v1.0.0-alpha.8","## What's Changed\r\n* feat: Zero-shot NLU by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F189\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcompare\u002Fv1.0.0-alpha.7...v1.0.0-alpha.8","2025-02-02T00:19:42",{"id":199,"version":200,"summary_zh":201,"released_at":202},107073,"v1.0.0-alpha.7","## What's Changed\r\n* feat: add chat logs by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F186\r\n* chore: Refactor base url by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F184\r\n* chore: refactor configuration by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F185\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcompare\u002Fv1.0.0-alpha.6...v1.0.0-alpha.7","2025-01-28T21:37:46",{"id":204,"version":205,"summary_zh":206,"released_at":207},107074,"v1.0.0-alpha.6","## What's Changed\r\n* fix: only store config once by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F182\r\n* feat: Facebook channel by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F183\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcompare\u002Fv1.0.0-alpha.5...v1.0.0-alpha.6","2025-01-25T10:40:19",{"id":209,"version":210,"summary_zh":211,"released_at":212},107075,"v1.0.0-alpha.5","## What's Changed\r\n* feat: Persistent chat state by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F181\r\n* chore: Add test coverage for dialogue manager by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F179\r\n* chore: add contribution guidelines by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F180\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcompare\u002Fv1.0.0-alpha.4...v1.0.0-alpha.5","2025-01-21T14:46:05",{"id":214,"version":215,"summary_zh":216,"released_at":217},107076,"v1.0.0-alpha.4","## What's Changed\r\n* refactor: update NLU components follow pipeline interface by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F171\r\n* chore: separate test and release CI pipelines by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F172\r\n* chore: ruff linter and formatter by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F173\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcompare\u002Fv1.0.0-alpha.3...v1.0.0-alpha.4","2025-01-19T21:07:09",{"id":219,"version":220,"summary_zh":221,"released_at":222},107077,"v1.0.0-alpha.3","## What's Changed\r\n* improved configurations with env override support  @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcommit\u002F4f1b045fcf5e7cf599a665581e0cddfb6146abc3\r\n* refactor dialogue manager initialisation & usage  @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcommit\u002Fa2534b69f1fc8f819892c68e8973424d9ce9ddfa\r\n* async http client for api fulfilment  @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcommit\u002F469b740d11fe0e377d53af6ac40540849008ce8b\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcompare\u002Fv1.0.0-alpha.2...v1.0.0-alpha.3","2025-01-12T11:34:09",{"id":224,"version":225,"summary_zh":226,"released_at":227},107078,"v1.0.0-alpha.2","## What's Changed\r\n* update entity extractor to train single model for all entities @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcommit\u002F1f297940cd3047fd3f799aeef2593a73c13f15c7\r\n* fix missing default parameter type value during intent creation  @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcommit\u002F6dfdb39dfec95e7357d3122bb5d1e4807f824ee2\r\n* move model training to fastapi background_tasks @alfredfrancis  in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcommit\u002Fdfa98a1525bca8555181fd4363d93f42b1ab9ddd\r\n\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcompare\u002Fv1.0.0-alpha.1...v1.0.0-alpha.2","2025-01-10T20:28:50",{"id":229,"version":230,"summary_zh":231,"released_at":232},107079,"v1.0.0-alpha.1","## What's Changed\r\n* upgrade dependencies by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F164\r\n* advanced slot filling by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F167\r\n* refactor dialogue management by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F165\r\n* refactor: refactor NLU by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F169\r\n* migrate Angular to Nextjs for admin UI by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F166\r\n* migrate to FastAPI by @alfredfrancis in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F170\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcompare\u002F0.0.1...v1.0.0-alpha.1","2025-01-10T15:40:10",{"id":234,"version":235,"summary_zh":236,"released_at":237},107080,"0.0.1","## What's Changed\r\n* includes legacy code base\r\n\r\n## New Contributors\r\n* @michaelluk made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F1\r\n* @khaledMohammed000 made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F2\r\n* @robmeadows made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F11\r\n* @lesyk made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F30\r\n* @gitter-badger made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F41\r\n* @albertpaulp made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F46\r\n* @Contextualist made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F38\r\n* @jondekerh made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F53\r\n* @brianray made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F58\r\n* @georgepadayatti made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F74\r\n* @hadifar made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F87\r\n* @marcoswca made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F92\r\n* @wp07e made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F97\r\n* @AdnanMuhib made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F109\r\n* @tnodine made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F122\r\n* @dependabot made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F127\r\n* @varatharaj-digiledge made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F131\r\n* @abugra made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F139\r\n* @timgates42 made their first contribution in https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fpull\u002F146\r\n\r\n**Full Changelog**: https:\u002F\u002Fgithub.com\u002Falfredfrancis\u002Fai-chatbot-framework\u002Fcommits\u002F0.0.1","2025-01-08T12:05:10"]