神译局是36氪旗下编译团队，关注科技、商业、职场、生活等领域，重点介绍国外的新技术、新观点、新风向。 编者按：2025年是智能体之年。本文从理论到实践对AI智能体开发进行了全面介绍，为你从外行变成专家提供了完整指南。文章来自编译。 学习用n8n创建低代码AI智能体，实现工作自动化。 我们再也掌控不了机器了。 是它们在控制我们。 ——京特·安德斯（Günther Anders） 初识通用人工智能的那一夜 2022年12月1日， 我死死盯着屏幕，又瞥了床头柜一眼。 凌晨3:26 死寂卧室里回荡，耳鸣嗡嗡作响。 19岁熬夜本属寻常——学习、打工、派对狂欢。 但我干的不是这些。我浑身冒汗。 眼袋浮肿，但跟压力和咖啡因无关。 是因为别的什么东西... ...某种尚未命名的存在。 感觉有点像机械蝴蝶。 那或许是我第一次触到通用人工智能的火花。 我被迫开灯驱散耳鸣。 看着刚发布的ChatGPT-3.5在屏幕上逐字吐露答案。 多数人对此毫无觉察。 杨立昆（Yann LeCun）视之为随机鹦鹉。 于我而言，这是人类史上最重大的时刻。 顿悟如洪流席卷—— "x他妈的...这玩意是活的？" 一道泪痕划过脸颊。 我凝视着空无一物的镜 ...

Core Insights - The article discusses the competitive landscape of Agent platforms, highlighting the importance of factors such as traffic, data privacy, tool ecosystem, and addressing hallucination issues in vertical domains [1][2]. Group 1: Agent Platforms Overview - Dify has established an early presence in the open-source community, but faces competition from platforms like FastGPT and N8N [3]. - FastGPT, along with Dify and Coze, emphasizes core functionalities such as visual workflow orchestration, a no-code platform, and a toolchain that includes model selection and knowledge bases [4][11]. - FastGPT's tool ecosystem is noted to be weaker compared to Coze and Dify, lacking depth in vertical tools and general life/efficiency tools [7][8]. Group 2: Platform Comparisons - Coze is designed for rapid deployment and ease of use, making it suitable for business departments with tight timelines [26]. - Dify offers a comprehensive LLMOps capability, balancing flexibility and control, ideal for medium to large teams that require private and cloud service options [26]. - N8N is positioned as a workflow automation engine, providing over 500 nodes and script mixing for efficient cross-system integration, catering to development teams [26]. Group 3: User Preferences and Use Cases - Developer preferences for Agent platforms focus on freedom, extensibility, and privatization, while product/operations teams prioritize no-code solutions, visualization, and quick validation [19]. - For quick deployment of a Q&A bot with minimal coding, Coze is the preferred choice, while N8N is favored for complex integrations and custom logic [23][24]. - The article emphasizes that no single platform can meet all needs, suggesting common combinations of platforms for different tasks [28].

Core Viewpoint - The article provides a comprehensive comparison of five mainstream LLM application platforms: Dify, Coze, n8n, FastGPT, and RAGFlow, emphasizing the importance of selecting the right platform based on individual needs and use cases [1][2]. Group 1: Overview of LLM Platforms - LLM application platforms significantly lower the development threshold for AI applications, accelerating the transition from concept to product [2]. - These platforms allow users to focus on business logic and user experience innovation rather than repetitive underlying technology construction [3]. Group 2: Platform Characteristics - **n8n**: Known for its powerful general workflow automation capabilities, it allows users to embed LLM nodes into complex automation processes [4]. - **Coze**: Launched by ByteDance, it emphasizes low-code/no-code AI agent development, enabling rapid construction and deployment of conversational AI applications [5]. - **FastGPT**: An open-source AI agent construction platform focused on knowledge base Q&A systems, offering data processing, model invocation, and visual workflow orchestration capabilities [6]. - **Dify**: An open-source LLM application development platform that integrates BaaS and LLMOps concepts, providing a one-stop solution for rapid AI application development and operation [7]. - **RAGFlow**: An open-source RAG engine focused on deep document understanding, specializing in knowledge extraction and high-quality Q&A from complex formatted documents [8][40]. Group 3: Detailed Platform Analysis - **Dify**: Described as a "Swiss Army Knife" of LLM platforms, it offers a comprehensive set of features including RAG pipelines, AI workflows, monitoring tools, and model management [8][10][12]. - **Coze**: Positioned as the "LEGO" of LLM platforms, it allows users to easily create and publish AI agents with a wide range of built-in tools and plugins [21][25]. - **FastGPT**: Recognized for its ability to quickly build high-quality knowledge bases, it supports various document formats and provides a user-friendly interface for creating AI Q&A assistants [33][35]. - **RAGFlow**: Distinguished by its deep document understanding capabilities, it supports extensive data preprocessing and knowledge graph functionalities [40][42]. - **n8n**: A low-code workflow automation tool that connects various applications and services, enhancing business process automation [46][49]. Group 4: User Suitability and Recommendations - For beginners in AI application development, Coze is recommended as the easiest platform to start with [61]. - For businesses requiring automation across multiple systems, n8n's robust workflow capabilities can save significant time [62]. - For building internal knowledge bases or Q&A systems, FastGPT and RAGFlow are suitable options, with FastGPT being lighter and RAGFlow offering higher performance [63]. - For teams with long-term plans to develop scalable enterprise-level AI applications, Dify's comprehensive ecosystem is advantageous [63]. Group 5: Key Considerations for Platform Selection - Budget considerations include the costs of self-hosting open-source platforms versus subscription fees for cloud services [68]. - Technical capabilities of the team should influence the choice of platform, with no-code options like Coze being suitable for those with limited technical skills [68]. - Deployment preferences, such as the need for local data privacy, should also be evaluated [69]. - Core functionality requirements must be clearly defined to select the platform that best meets specific needs [70]. - The sustainability of the platform, including update frequency and community support, is crucial for long-term viability [71]. - Data security and compliance are particularly important for enterprise users, with self-hosted solutions offering greater control over data [72].