Dify is an open-source LLM app development platform designed to bridge the gap between prototype and production for AI applications. Written primarily in TypeScript, it provides a comprehensive suite of tools for building, deploying, and managing agentic workflows and AI-powered applications. The platform is classified across multiple AI and development domains including dialogue systems, conversational AI, language modeling, code generation, and machine learning, reflecting its broad applicability across different AI use cases.
The core functionality centers on a visual workflow builder that allows developers to construct and test AI workflows on a canvas interface. The platform integrates with hundreds of language models from dozens of inference providers, including proprietary models like GPT-4 and Gemini as well as open-source options such as Llama3 and Mistral. This model agnostic approach extends to OpenAI API-compatible models, giving users flexibility in their LLM selection. The comprehensive model support is complemented by a Prompt IDE that enables intuitive prompt crafting, model performance comparison, and integration of additional features like text-to-speech for chat applications.
Dify incorporates extensive RAG (Retrieval-Augmented Generation) pipeline capabilities that handle the complete document processing workflow, from ingestion through retrieval. The platform provides out-of-the-box support for extracting text from PDFs, PowerPoint presentations, and other common document formats. For agentic capabilities, users can define agents based on either LLM Function Calling or ReAct patterns and equip them with pre-built or custom tools. The platform includes over 50 built-in tools for AI agents, such as Google Search, DALL-E, Stable Diffusion, and WolframAlpha.
The platform emphasizes production readiness through its LLMOps features, which enable monitoring and analysis of application logs and performance metrics over time. This observability is enhanced through integrations with tools like Opik, Langfuse, and Arize Phoenix, allowing teams to continuously improve prompts, datasets, and models based on production data and annotations. All of Dify's capabilities are exposed through APIs, functioning as a Backend-as-a-Service offering that enables seamless integration into existing business logic.
Dify maintains active community engagement with a star count of 147,683 as of July 2026, showing consistent growth. The project demonstrates strong maintenance patterns with a median issue and PR response latency of 0.1 hours, though mean latency is 390.3 hours, indicating some variation in response times. The most active issue categories tracked are bugs with 4,889 items, enhancements with 1,842 items, and cant-reproduce issues with 675 items. Primary contributors include crazywoola with 19,472 tracked events, laipz8200 with 1,969 events, and fatelei with 1,257 events. The project shares contributors with major repositories including Microsoft's VSCode and TypeScript, as well as the Rust language project.
The platform is available through multiple deployment options: Dify Cloud for zero-setup access with free GPT-4 calls included in the sandbox plan, self-hosted Community Edition for organizations wanting full control, and enterprise editions with additional features for larger organizations. Docker Compose deployment is supported for quick local setup, requiring minimum system specifications of 2 CPU cores and 4 GB RAM.
