Getting Started with Dify: No-Code AI Application Development

A Comprehensive Guide to Quick Start and Practical Implementation

Introduction

Dify is an open-source large language model (LLM) application development platform. It combines the concepts of Backend-as-a-Service and LLMOps to enable developers to quickly build production-grade generative AI applications. Even non-technical personnel can participate in the definition and data operations of AI applications.

By integrating the key technology stacks required for building LLM applications, including support for hundreds of models, an intuitive Prompt orchestration interface, high-quality RAG engines, and a flexible Agent framework, while providing a set of easy-to-use interfaces and APIs, Dify saves developers a lot of time reinventing the wheel, allowing them to focus on innovation and business needs.

The name Dify comes from Define + Modify, referring to defining and continuously improving your AI applications.

Why Use Dify?

You can think of libraries like LangChain as toolboxes with hammers, nails, etc. In comparison, Dify provides a more production-ready, complete solution - think of Dify as a scaffolding system with refined engineering design and software testing.

Importantly, Dify is open source, co-created by a professional full-time team and community. You can self-deploy capabilities similar to Assistants API and GPTs based on any model, maintaining full control over your data with flexible security, all on an easy-to-use interface.

What Can Dify Do?

Workflow: Dify offers a visual canvas to build and test robust AI workflows. This feature enables users to leverage the full range of Dify's capabilities, including model integration and prompt crafting.
Comprehensive Model Support: The platform supports seamless integration with hundreds of proprietary and open-source LLMs, including popular options like GPT, Mistral, Llama3, and any OpenAI API-compatible models. This wide range of supported models ensures flexibility and choice for developers.
Prompt IDE: Dify includes an intuitive Prompt IDE, allowing users to craft prompts, compare model performance, and enhance applications with additional features like text-to-speech.
RAG Pipeline: Dify's RAG (Retrieval-Augmented Generation) capabilities cover everything from document ingestion to retrieval. It includes out-of-the-box support for extracting text from various document formats such as PDFs and PPTs.
Agent Capabilities: Users can define agents using LLM Function Calling or ReAct, and integrate pre-built or custom tools. Dify provides over 50 built-in tools for AI agents, including Google Search, DELL·E, Stable Diffusion, and WolframAlpha.
LLMOps: The platform includes observability features for monitoring and analyzing application logs and performance over time. This allows for continuous improvement of prompts, datasets, and models based on real-world data and annotations.
Backend-as-a-Service: Dify offers corresponding APIs for all its features, enabling effortless integration into existing business logic.