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Dify is an open-source LLM application development platform that enables teams to build and deploy agentic workflows, RAG pipelines, and AI agents effortlessly.
Dify is a comprehensive, open-source LLM application development platform designed to bridge the gap between complex AI models and practical, production-ready applications. It addresses the core challenges developers face when building with Large Language Models (LLMs), such as prompt engineering, context management, and workflow orchestration. By providing a visual interface combined with robust developer tools, Dify allows teams to move from a simple prompt to a sophisticated "agentic workflow" in minutes rather than weeks.
At its heart, Dify functions as a "Backend-as-a-Service" for LLM apps. It simplifies the creation of Retrieval-Augmented Generation (RAG) pipelines, allowing users to ingest their own data—such as PDFs, Notion pages, or structured text—and make it searchable for the AI. This ensures that the generated responses are grounded in specific, private, or up-to-date information. Beyond simple chat, Dify excels at creating autonomous agents that can use tools, execute code, and follow complex multi-step logic to complete tasks.
The platform is built for scale and flexibility. Whether you are a solo developer looking to experiment with the latest models like Claude 3.5 or GPT-4, or an enterprise team needing to deploy secure, self-hosted AI solutions, Dify provides the necessary infrastructure. Its open-source nature fosters a transparent environment where users can contribute to the ecosystem, while its cloud offering provides a zero-setup path to deployment. By automating the "plumbing" of AI development—such as session management, data cleaning, and API orchestration—Dify empowers creators to focus on the unique value of their AI applications.
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A visual canvas to design complex logic, loops, and multi-step tasks for autonomous AI agents.
Comprehensive tools for data ingestion, cleaning, and vector storage to ground LLMs in your own data.
Integrate AI into any application using standardized APIs and Web SDKs, eliminating the need for custom backends.
Connect your agents to external tools, APIs, and code execution environments to perform real-world actions.
Monitor application performance, inspect logs, and refine prompts based on real user interactions.