Dify AI: Create LLM Applications for Free Without Any Code!

baoshi.rao

Dify is an easy-to-use LLMOps platform designed to empower more people to create sustainable AI-native applications. By providing visual orchestration for various application types, Dify offers out-of-the-box applications and can also serve as a backend service API. It unifies the development process, using a single API for plugin and dataset integration, and provides a single interface for prompt engineering, visual analysis, and continuous improvement.

Project address: https://github.com/langgenius/dify

Applications created with Dify include:

Out-of-the-box websites supporting both form mode and chat conversation mode
A single API that includes plugin functionality, context enhancement, and more, saving you backend coding work
Visual data analysis, log review, and annotation for applications

Key features:

LLM Support: When building Dify AI applications, you can choose functionalities based on different models. Dify is compatible with Langchain, which means it supports various LLMs. Currently supported models include:

OpenAI: GPT4, GPT3.5-turbo, GPT3.5-turbo-16k, text-davinci-003
Azure OpenAI Service
Anthropic: Claude2, Claude-instant
Replicate
Hugging Face Hub
ChatGLM
Llama2
MiniMax
Spark
Wenxin

Dify AI provides the following free resources for registered Dify cloud users (register at dify.ai

200 free OpenAI queries for building OpenAI-based applications
Visual orchestration: Build AI applications in minutes by visually composing and debugging prompts
Text embedding: Fully automated text preprocessing embeds your data in context without complex concepts. Supports PDF, TXT, and data synced from Notion, web pages, and APIs
API-based: Backend as a service. Directly access web applications or integrate via API without complex backend setup
Plugins: Dify's "Smart Chat" now supports first-party plugins like web browsing, Google Search, Wikipedia, etc., enabling online lookup, web content analysis, and conversational explanations of AI reasoning
Team workspace: Team members can join workspaces to collaboratively edit, manage, and use team AI applications
Data annotation and improvement: Visually inspect AI application logs and improve data through annotation. Observe AI's reasoning process to continuously enhance performance (coming soon)