{"id":110370,"date":"2026-05-13T15:58:04","date_gmt":"2026-05-13T10:28:04","guid":{"rendered":"https:\/\/www.guvi.in\/blog\/?p=110370"},"modified":"2026-11-13T15:11:51","modified_gmt":"2026-11-13T09:41:51","slug":"dify-explained-no-code-platform","status":"publish","type":"post","link":"https:\/\/www.guvi.in\/blog\/dify-explained-no-code-platform\/","title":{"rendered":"What Is Dify? A Simple Guide to the No-Code LLM App Platform"},"content":{"rendered":"\n<p>Dify is an open-source platform that lets you build AI applications, such as chatbots, assistants and automated workflows, through a visual interface instead of writing every component from scratch.<\/p>\n\n\n\n<p>Creating a working AI app has traditionally meant connecting models, data sources and prompts by hand, which can take a team weeks. Dify shortens that process so that even a single person can often get a functional prototype running within hours.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>TL;DR Summary<\/strong><\/h2>\n\n\n\n<ul>\n<li>This blog explains what Dify is and how its visual approach lets you build AI applications without writing everything from scratch.<\/li>\n\n\n\n<li>It explores Dify&#8217;s key features and how they work together to support chatbots, assistants, and workflows.<\/li>\n\n\n\n<li>It guides you through building a chatbot with Dify, from setup to a working result.<\/li>\n\n\n\n<li>It covers practical use cases and helps you decide between Dify Cloud and the self-hosted option.<\/li>\n\n\n\n<li>It compares Dify with n8n, Flowise and Langflow, outlines its limitations and looks at where AI workflow platforms are heading.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><br><strong>What is Dify?<\/strong><\/h2>\n\n\n\n<p>Dify is an <a href=\"https:\/\/www.guvi.in\/blog\/guide-to-large-language-models\/\" target=\"_blank\" rel=\"noreferrer noopener\">LLM<\/a> application development platform created by LangGenius. It brings model access, prompt design, knowledge retrieval, workflow building and monitoring into a single environment, so teams can build, test and deploy AI applications from one place.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>What Problem Does Dify Solve?<\/strong><\/h3>\n\n\n\n<ul>\n<li><strong>Scattered tooling:<\/strong> Model access, prompts, data retrieval and hosting usually sit in separate tools. Here, they share one workspace.<\/li>\n\n\n\n<li><strong>Heavy coding:<\/strong> A visual builder replaces much of the custom code needed to connect models and data.<\/li>\n\n\n\n<li><strong>Limited team involvement:<\/strong> Non-developers can help build and refine apps without relying fully on engineers.<\/li>\n\n\n\n<li><strong>Model lock-in:<\/strong> Multiple model providers are supported, so switching does not mean rebuilding.<\/li>\n\n\n\n<li><strong>Answers that ignore your data:<\/strong> Built-in <a href=\"https:\/\/www.guvi.in\/blog\/guide-for-retrieval-augmented-generation\/\" target=\"_blank\" rel=\"noreferrer noopener\">RAG<\/a> lets apps respond using your own documents.<\/li>\n\n\n\n<li><strong>Slow path to production:<\/strong> Apps can be published as web interfaces or APIs, with logs for monitoring.<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n\n<p><strong><em>Building AI apps no longer starts with writing everything from scratch. But knowing what happens under the visual canvas is what sets you apart. HCL GUVI\u2019s Intel &amp; IITM Pravartak Certified AI\/ML Course teaches that foundation, from Python to Generative AI, with no coding experience needed.<\/em><\/strong><\/p>\n\n\n<div class=\"wp-block-guvi-cta-button\" style=\"justify-content:center;\"><a href=\"https:\/\/www.guvi.in\/mlp\/artificial-intelligence-and-machine-learning?utm_source=blog&#038;utm_medium=cta_button&#038;utm_campaign=dify-explained-no-code-platform\" class=\"guvi-btn-enquire\" target=\"_blank\" rel=\"noopener noreferrer\">Enroll in HCL GUVI&#039;s AI\/ML Course<svg class=\"guvi-btn-chevron\" style=\"transform:rotate(0deg);\" width=\"16\" height=\"16\" viewBox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M9.39935 18.1007C9.0674 17.7687 9.0674 17.2305 9.39935 16.8986L13.6922 12.6057C13.7508 12.5471 13.7508 12.4521 13.6922 12.3935L9.39935 8.10065C9.0674 7.7687 9.0674 7.23051 9.39935 6.89857C9.7313 6.56662 10.2695 6.56662 10.6014 6.89857L14.8943 11.1915C15.6168 11.9139 15.6168 13.0853 14.8943 13.8078L10.6014 18.1007C10.2695 18.4326 9.7313 18.4326 9.39935 18.1007Z\" fill=\"currentColor\"\/><\/svg><\/a><\/div>\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>How Does Dify Work?<\/strong><\/h2>\n\n\n\n<p>Dify lets you assemble an AI app from connected building blocks on a visual canvas. Once the app behaves as expected, you publish it as a web app, an API or an <a href=\"https:\/\/www.guvi.in\/blog\/what-is-model-context-protocol\/\" target=\"_blank\" rel=\"noreferrer noopener\">MCP<\/a> server.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Core Components of Dify<\/strong><\/h3>\n\n\n\n<ul>\n<li><strong>Model providers:<\/strong> Connections to language models such as <a href=\"https:\/\/www.guvi.in\/blog\/getting-started-with-openai-models\/\" target=\"_blank\" rel=\"noreferrer noopener\">OpenAI<\/a> and Anthropic, managed in one workspace.<\/li>\n\n\n\n<li><strong>Knowledge base:<\/strong> Your documents, split and indexed so apps can retrieve relevant information through RAG.<\/li>\n\n\n\n<li><strong>Workflow canvas and nodes:<\/strong> The visual editor where each node handles one step, such as a model call, retrieval, code or a condition.<\/li>\n\n\n\n<li><strong>Tools and plugins:<\/strong> Extensions that let an app perform actions or connect to outside services.<\/li>\n\n\n\n<li><strong>Publishing and monitoring:<\/strong> Options for releasing the app, plus logs for reviewing how it performs.<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>How Dify Works Step by Step<\/strong><\/h3>\n\n\n\n<p><strong>Step 1: Connect a Model Provider<\/strong><\/p>\n\n\n\n<p>Every app needs at least one language model. Go to Settings, open Model Provider, install a provider and click Setup.<\/p>\n\n\n\n<p>Enter your API key, and the platform validates it before making the provider available. On Dify Cloud, built-in AI credits let you try popular models without your own key.<\/p>\n\n\n\n<p><strong>Step 2: Add Your Data to the Knowledge Base<\/strong><\/p>\n\n\n\n<p>This step applies only when the app should answer from your own content. Go to Knowledge, click Create and choose a ready-to-use knowledge base.<\/p>\n\n\n\n<p>Upload files, or sync content from Notion or a webpage. Then set the chunk settings, index method and retrieval options. When processing finishes, you can link the knowledge base to any app.<\/p>\n\n\n\n<p><strong>Step 3: Build the App on the Canvas<\/strong><\/p>\n\n\n\n<p>Create an app and pick its type. A Workflow runs once from input to result. A Chatflow adds a conversation layer, so the flow runs on every user message.<\/p>\n\n\n\n<p>Next, add nodes for steps such as calling a model, retrieving knowledge or branching on a condition, and connect them in order. Most of this is dragging and configuring, and you only need code when your logic requires it.<\/p>\n\n\n\n<p><strong>Step 4: Test and Refine the App<\/strong><\/p>\n\n\n\n<p>Run the app in the preview panel to see how it responds. You can also run a single node on its own to check its input and output.<\/p>\n\n\n\n<p>Run history and logs show earlier tests. Before publishing, the checklist flags any node that is incomplete or not connected.<\/p>\n\n\n\n<p><strong>Step 5: Deploy and Publish the App<\/strong><\/p>\n\n\n\n<p>When the app works as intended, publish it as a web app, expose it through an API, or serve it as an MCP server. It then runs on the deployment you use.<\/p>\n\n\n\n<p>You can deploy Dify in two ways, through Dify Cloud or through a self-hosted setup.<\/p>\n\n\n\n<ul>\n<li><strong>Dify Cloud:<\/strong> The managed version, hosted and maintained by Dify. You sign up, open the workspace in your browser and start building, with no servers to set up. It begins with a free Sandbox plan, and paid plans add capacity for larger teams.<\/li>\n\n\n\n<li><strong>Self-Hosted:<\/strong> The open-source Community Edition, which you run on your own server with Docker Compose. You install it, configure it and keep it updated yourself. In return, you control the infrastructure and where your data is stored.<\/li>\n<\/ul>\n\n\n\n<p>Here is the difference between the two:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>Factor<\/strong><\/th><th><strong>Dify Cloud<\/strong><\/th><th><strong>Self-Hosted<\/strong><\/th><\/tr><\/thead><tbody><tr><td><strong>Setup<\/strong><\/td><td>Sign up and start building<\/td><td>Install with Docker Compose on your own server<\/td><\/tr><tr><td><strong>Maintenance<\/strong><\/td><td>Handled by Dify<\/td><td>Handled by you, including updates<\/td><\/tr><tr><td><strong>Cost<\/strong><\/td><td>Free Sandbox plan, then paid plans<\/td><td>Software is free; you pay for infrastructure and model usage<\/td><\/tr><tr><td><strong>Data control<\/strong><\/td><td>Data lives on Dify\u2019s hosted service<\/td><td>Data stays on your own infrastructure<\/td><\/tr><tr><td><strong>Best for<\/strong><\/td><td>Quick starts and small teams<\/td><td>Teams that need control, privacy or custom setups<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><strong>Optional Read: <\/strong><em><a href=\"https:\/\/www.guvi.in\/blog\/open-source-contribution-guide\/\" target=\"_blank\" rel=\"noreferrer noopener\">Open Source Contribution Guide<\/a><\/em><\/p>\n\n\n\n<p><\/p>\n\n\n\n<div style=\"background-color: #099f4e; border: 3px solid #110053; border-radius: 12px; padding: 18px 22px; color: #FFFFFF; font-size: 18px; font-family: Montserrat, Helvetica, sans-serif; line-height: 1.6; box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15); max-width: 750px;\">\n    <strong style=\"font-size: 22px; color: #ffffff;\">\ud83d\udca1 Did You Know?<\/strong>\n    <br \/><br \/>\n    <span>\n        <strong style=\"color: #110053;\">Dify<\/strong> was founded in 2023 by <strong style=\"color: #110053;\">Luyu Zhang<\/strong>, a former Tencent Cloud product leader, and surpassed <strong style=\"color: #110053;\">100,000 GitHub stars<\/strong> in June 2025.\n    <\/span>\n<\/div>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Key Features of Dify<\/strong><\/h2>\n\n\n\n<p>Dify brings the tools for building, deploying and monitoring AI applications into one platform. The features below explain what each of them does.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>Feature<\/strong><\/th><th><strong>What It Does<\/strong><\/th><th><strong>How It Helps<\/strong><\/th><\/tr><\/thead><tbody><tr><td><strong>Visual Workflow Builder<\/strong><\/td><td>Lets you design app logic by connecting nodes on a canvas.<\/td><td>Reduces the amount of custom code needed.<\/td><\/tr><tr><td><strong>Knowledge Base and RAG<\/strong><\/td><td>Stores your documents and retrieves the relevant parts when a question is asked.<\/td><td>Answers draw on your own content.<\/td><\/tr><tr><td><strong>Multi-Model Support<\/strong><\/td><td>Connects several model providers in one workspace.<\/td><td>Models can be switched or compared without rebuilding the app.<\/td><\/tr><tr><td><strong>Agents and Tools<\/strong><\/td><td>Lets an app use tools such as web search or external API calls.<\/td><td>Apps can take actions beyond text replies.<\/td><\/tr><tr><td><strong>Plugins and Marketplace<\/strong><\/td><td>Adds models, tools and extensions from a plugin marketplace.<\/td><td>Extends what the platform can do.<\/td><\/tr><tr><td><strong>App Publishing<\/strong><\/td><td>Releases an app as a web app, an API or an MCP server.<\/td><td>One app can serve both users and other software.<\/td><\/tr><tr><td><strong>Logs and Monitoring<\/strong><\/td><td>Tracks usage, run logs and costs, and supports annotations on responses.<\/td><td>Makes it easier to spot issues and improve answers.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>How to Build a Chatbot With Dify<\/strong> <\/h2>\n\n\n\n<p>Now we will walk through how to build a support chatbot that answers questions from your own documents, then connect it to your own code. We will use Dify Cloud for the chatbot and Python with the <code>requests<\/code> library to call it through the API.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Step 1: Set Up Your Workspace<\/strong><\/h4>\n\n\n\n<p>Sign in to Dify Cloud and make sure a model provider is connected. Open Settings, go to Model Provider, install a provider and enter your API key. The Cloud plan also includes AI credits, so you can try a model before adding your own key.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Step 2: Create a Knowledge Base<\/strong><\/h4>\n\n\n\n<p>Open Knowledge, click Create and choose a ready-to-use knowledge base. Upload the files the chatbot should answer from, such as a product guide or an FAQ, and keep the default chunk and index settings. Wait until processing finishes before moving on.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Step 3: Create the Chatbot App<\/strong><\/h4>\n\n\n\n<p>Go to Studio, click Create from Blank, open More basic app types and choose Chatbot. Give the app a name, then select the model it should use. This app type suits a simple back-and-forth assistant that does not need tools or a multi-step flow.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Step 4: Write the Prompt and Add Your Knowledge<\/strong><\/h4>\n\n\n\n<p>In the prompt field, describe how the chatbot should behave. Then add the knowledge base you created so each user message searches your documents.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>You are a support assistant for Acme Store.\nAnswer only with information from the knowledge base.\nIf the answer is not there, say you do not know and suggest contacting the support team.\nKeep replies short and polite.<\/code><\/pre>\n\n\n\n<p><strong>Code Explanation:<\/strong><\/p>\n\n\n\n<ul>\n<li>The first line gives the chatbot a role.<\/li>\n\n\n\n<li>The second line keeps answers tied to your documents.<\/li>\n\n\n\n<li>The third line gives a safe reply when nothing relevant is found.<\/li>\n\n\n\n<li>The last line sets the tone and length.<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Step 5: Test and Publish<\/strong><\/h4>\n\n\n\n<p>Use the preview panel to ask a few questions your documents can answer, and one they cannot. If the replies look right, click Publish. After any later change, publish the update again so the live app uses the latest version.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Step 6: Call the Chatbot From Your Own Code<\/strong><\/h4>\n\n\n\n<p>Open the app\u2019s API access page and create an API key. Install the library with <code>pip install requests<\/code>, then save the key as an environment variable named <code>DIFY_API_KEY<\/code>.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import os\nimport requests\n\nAPI_KEY = os.getenv(\"DIFY_API_KEY\")\nURL = \"https:\/\/api.dify.ai\/v1\/chat-messages\"\n\nheaders = {\n    \"Authorization\": f\"Bearer {API_KEY}\",\n    \"Content-Type\": \"application\/json\",\n}\n\ndef ask(question, conversation_id=\"\"):\n    payload = {\n        \"inputs\": {},\n        \"query\": question,\n        \"response_mode\": \"blocking\",\n        \"conversation_id\": conversation_id,\n        \"user\": \"demo-user-1\",\n    }\n    response = requests.post(URL, headers=headers, json=payload, timeout=60)\n    response.raise_for_status()\n    data = response.json()\n    return data&#91;\"answer\"], data&#91;\"conversation_id\"]\n\nanswer, conv_id = ask(\"What is your refund policy?\")\nprint(answer)\n\nanswer, conv_id = ask(\"How long does it take?\", conv_id)\nprint(answer)<\/code><\/pre>\n\n\n\n<p><strong>Code Explanation:<\/strong><\/p>\n\n\n\n<ul>\n<li>The key is read from an environment variable, so it never sits in the code.<\/li>\n\n\n\n<li>Every request goes to the <code>chat-messages<\/code> endpoint with the key in the <code>Authorization<\/code> header.<\/li>\n\n\n\n<li>The <code>ask<\/code> function sends the question as <code>query<\/code> and waits for the full reply because <code>response_mode<\/code> is <code>blocking<\/code>.<\/li>\n\n\n\n<li>The <code>user<\/code> value identifies the person chatting, and Dify uses it to keep their conversations separate.<\/li>\n\n\n\n<li>An empty <code>conversation_id<\/code> starts a new conversation, and the reply returns an ID for the next message.<\/li>\n\n\n\n<li>The second call passes that ID back, so the chatbot remembers the earlier question.<\/li>\n<\/ul>\n\n\n\n<p>If you run Dify on your own server, replace the base URL with your own API address. Keep the key on the server side and never place it in code that runs in a user\u2019s browser.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><strong><em>You have just seen how a working chatbot comes together. Now imagine designing agents, tuning models and taking them to production. HCL GUVI\u2019s Intel &amp; IITM Pravartak Certified AI\/ML Course gets you there with live classes, 20+ projects and a capstone.<\/em><\/strong><\/p>\n\n\n<div class=\"wp-block-guvi-cta-button\" style=\"justify-content:center;\"><a href=\"https:\/\/www.guvi.in\/mlp\/artificial-intelligence-and-machine-learning?utm_source=blog&#038;utm_medium=cta_button&#038;utm_campaign=dify-explained-no-code-platform\" class=\"guvi-btn-enquire\" target=\"_blank\" rel=\"noopener noreferrer\">Enroll in HCL GUVI&#039;s AI\/ML Course<svg class=\"guvi-btn-chevron\" style=\"transform:rotate(0deg);\" width=\"16\" height=\"16\" viewBox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M9.39935 18.1007C9.0674 17.7687 9.0674 17.2305 9.39935 16.8986L13.6922 12.6057C13.7508 12.5471 13.7508 12.4521 13.6922 12.3935L9.39935 8.10065C9.0674 7.7687 9.0674 7.23051 9.39935 6.89857C9.7313 6.56662 10.2695 6.56662 10.6014 6.89857L14.8943 11.1915C15.6168 11.9139 15.6168 13.0853 14.8943 13.8078L10.6014 18.1007C10.2695 18.4326 9.7313 18.4326 9.39935 18.1007Z\" fill=\"currentColor\"\/><\/svg><\/a><\/div>\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Practical Use Cases of Dify<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1200\" height=\"630\" src=\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2026\/08\/image-183-1200x630.png\" alt=\"\" class=\"wp-image-133406\" srcset=\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2026\/08\/image-183-1200x630.png 1200w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2026\/08\/image-183-300x158.png 300w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2026\/08\/image-183-768x403.png 768w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2026\/08\/image-183-1536x806.png 1536w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2026\/08\/image-183-2048x1075.png 2048w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2026\/08\/image-183-150x79.png 150w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" title=\"\"><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>1. Enterprise Knowledge Assistants<\/strong><\/h3>\n\n\n\n<p>Large organizations can deploy internal AI assistants using Dify that connect to a number of information sources, such as HR documentation, technical manuals, policy systems, internal databases, product documentation, etc.<\/p>\n\n\n\n<p>Employees get answers and information without manually searching through large volumes of documents.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2. AI Customer Support Systems<\/strong><\/h3>\n\n\n\n<p>Support teams can automate existing workflows and ensure accurate context while using <a href=\"https:\/\/www.guvi.in\/blog\/how-to-build-rag-pipelines-in-ai-applications\/\" target=\"_blank\" rel=\"noreferrer noopener\">RAG pipelines<\/a> for support agents.<\/p>\n\n\n\n<p>These systems can retrieve ticket history, determine sentiment, draft responses, escalate tickets when needed, and even recommend potential solutions to agents.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>3. AI Research Assistants<\/strong><\/h3>\n\n\n\n<p>The creation of systems for researchers to automatically summarize research papers, extract information, identify connections, and answer context-based questions will significantly speed up research activities.<\/p>\n\n\n\n<p>This is especially relevant for research in fields such as law, healthcare, finance, and academia.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>4. AI Workflow Automation<\/strong><\/h3>\n\n\n\n<p>Organizations are increasingly leveraging <a href=\"https:\/\/www.guvi.in\/blog\/what-is-artificial-intelligence\/\" target=\"_blank\" rel=\"noreferrer noopener\">AI<\/a> to automate many operational workflows.<\/p>\n\n\n\n<p>Dify workflows can automate processes such as report generation, data enrichment, lead qualification, content summarization, email drafting, internal analytics, and reporting.<\/p>\n\n\n\n<p>What&#8217;s crucial to remember is that AI is embedded within a larger operational system, not an isolated tool.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Dify vs n8n, Flowise and Langflow: Which Is Better?<\/strong><\/h2>\n\n\n\n<p>Dify, <a href=\"https:\/\/n8n.io\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">n8n<\/a>, Flowise and <a href=\"https:\/\/www.langflow.org\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Langflow <\/a>all let you build with a visual interface, but each is designed for a different purpose.<\/p>\n\n\n\n<p>This section compares Dify with each of the other three, covering what each tool does best and when it is the better choice.<\/p>\n\n\n\n<p><strong>Note:<\/strong> <em>Flowise is no longer actively maintained. Its repository was archived in August 2026, so it is not a good choice for new projects.<\/em><\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>Factor<\/strong><\/th><th><strong>Dify<\/strong><\/th><th><strong>n8n<\/strong><\/th><th><strong>Langflow<\/strong><\/th><th><strong>Flowise<\/strong><\/th><\/tr><\/thead><tbody><tr><td><strong>Primary Focus<\/strong><\/td><td>Building and running LLM apps<\/td><td>Workflow automation with AI nodes<\/td><td>Visual builder for AI agents and flows<\/td><td>Visual builder for LLM apps and agents<\/td><\/tr><tr><td><strong>Best For<\/strong><\/td><td>Apps with a knowledge base, publishing and monitoring<\/td><td>Automating tasks across apps and services<\/td><td>Developers who want a visual builder close to Python<\/td><td>Chatbots and agent flows<\/td><\/tr><tr><td><strong>License<\/strong><\/td><td>Apache 2.0 with extra conditions, including a multi-tenant restriction<\/td><td>Sustainable Use License (source-available, not OSI open source)<\/td><td>MIT<\/td><td>Apache 2.0<\/td><\/tr><tr><td><strong>Knowledge Base and RAG<\/strong><\/td><td>Built-in knowledge base<\/td><td>Embedding and vector store nodes added to workflows<\/td><td>Supported through components<\/td><td>Supported through chatflow components<\/td><\/tr><tr><td><strong>Publishing<\/strong><\/td><td>Web app, API or MCP server<\/td><td>Triggers such as webhooks, plus an MCP Server Trigger node<\/td><td>API or MCP server<\/td><td>REST API endpoint for each flow<\/td><\/tr><tr><td><strong>Deployment<\/strong><\/td><td>Dify Cloud or self-hosted<\/td><td>n8n Cloud or self-hosted<\/td><td>Self-hosted<\/td><td>Self-hosted<\/td><\/tr><tr><td><strong>Project Status<\/strong><\/td><td>Active<\/td><td>Active<\/td><td>Active<\/td><td>Wound down, repository archived in August 2026<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Limitations of Dify<\/strong><\/h2>\n\n\n\n<p>These are the main limitations to consider before choosing Dify<\/p>\n\n\n\n<ul>\n<li><strong>License rules:<\/strong> You cannot run Dify as a multi-tenant service for others without written permission.<\/li>\n\n\n\n<li><strong>Small free plan:<\/strong> The free Cloud plan is for testing, and real projects usually need a paid plan.<\/li>\n\n\n\n<li><strong>Self-hosting needs work:<\/strong> You handle setup, updates and server upkeep yourself.<\/li>\n\n\n\n<li><strong>Extra model costs:<\/strong> Using your own model provider means paying that provider separately.<\/li>\n\n\n\n<li><strong>Built for LLM apps:<\/strong> It is less suited to general task automation across business tools.<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n\n<p><strong><em>Tools like Dify lower the barrier to building AI, but real careers grow from understanding what runs underneath. HCL GUVI\u2019s Intel &amp; IITM Pravartak Certified AI\/ML Course offers you live classes, a joint certification and placement assistance with 1000+ hiring partners. Turn curiosity into a career.<\/em><\/strong><\/p>\n\n\n<div class=\"wp-block-guvi-cta-button\" style=\"justify-content:center;\"><a href=\"https:\/\/www.guvi.in\/mlp\/artificial-intelligence-and-machine-learning?utm_source=blog&#038;utm_medium=cta_button&#038;utm_campaign=dify-explained-no-code-platform\" class=\"guvi-btn-enquire\" target=\"_blank\" rel=\"noopener noreferrer\">Enroll in HCL GUVI&#039;s AI\/ML Course<svg class=\"guvi-btn-chevron\" style=\"transform:rotate(0deg);\" width=\"16\" height=\"16\" viewBox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M9.39935 18.1007C9.0674 17.7687 9.0674 17.2305 9.39935 16.8986L13.6922 12.6057C13.7508 12.5471 13.7508 12.4521 13.6922 12.3935L9.39935 8.10065C9.0674 7.7687 9.0674 7.23051 9.39935 6.89857C9.7313 6.56662 10.2695 6.56662 10.6014 6.89857L14.8943 11.1915C15.6168 11.9139 15.6168 13.0853 14.8943 13.8078L10.6014 18.1007C10.2695 18.4326 9.7313 18.4326 9.39935 18.1007Z\" fill=\"currentColor\"\/><\/svg><\/a><\/div>\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>The Future of AI Workflow Platforms<\/strong><\/h2>\n\n\n\n<p>Dify already supports agentic workflows, plugins and publishing apps as MCP servers, which fits the direction AI development is taking. <\/p>\n\n\n\n<p>As LLMs improve at reasoning and using tools, platforms like Dify will focus more on helping teams control agent behaviour through reliable knowledge retrieval, monitoring, and safe deployment. <\/p>\n\n\n\n<p>For Dify to stay useful, it will need to remain easy for non-developers while giving engineers enough flexibility.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>FAQs<\/strong><\/h2>\n\n\n<div id=\"rank-math-faq\" class=\"rank-math-block\">\n<div class=\"rank-math-list \">\n<div id=\"faq-question-1794561464736\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">1. What is Dify used for?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Dify is used to build AI apps such as chatbots, agents and automated workflows through a visual interface.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1794561465759\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">2. Is Dify free to use?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Yes, Dify Cloud has a free Sandbox plan with limited credits, and the self-hosted Community Edition is free to run, though you pay for your own infrastructure and model usage.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1794561467680\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">3. Is Dify open source?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Yes, it is licensed under Apache 2.0 with extra conditions, such as not running it as a multi-tenant service without written permission.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1794561468330\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">4. Do you need coding skills to use Dify?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>No, most apps are built on a visual canvas, and you only need code when your logic requires it.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1794561469410\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">5. What is the difference between Dify and n8n?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Dify is built for LLM apps with a knowledge base and publishing, while n8n is mainly built for automating tasks across apps and services.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Dify is an open-source platform that lets you build AI applications, such as chatbots, assistants and automated workflows, through a visual interface instead of writing every component from scratch. Creating a working AI app has traditionally meant connecting models, data sources and prompts by hand, which can take a team weeks. Dify shortens that process [&hellip;]<\/p>\n","protected":false},"author":64,"featured_media":133409,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[933],"tags":[],"views":"1526","authorinfo":{"name":"Abhishek Pati","url":"https:\/\/www.guvi.in\/blog\/author\/abhishek-pati\/"},"thumbnailURL":"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2026\/08\/Feature-image-5-300x116.png","_links":{"self":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts\/110370"}],"collection":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/users\/64"}],"replies":[{"embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/comments?post=110370"}],"version-history":[{"count":20,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts\/110370\/revisions"}],"predecessor-version":[{"id":147851,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts\/110370\/revisions\/147851"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/media\/133409"}],"wp:attachment":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/media?parent=110370"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/categories?post=110370"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/tags?post=110370"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}