Dify is an open-source LLM application development platform that consolidates five things that typically require separate tools: dataset/RAG management, workflow orchestration, agent building, model provider management, and API generation. It's designed to replace the custom glue code most teams write to stitch these together.
The architecture is opinionated and production-oriented. Where Flowise prioritizes simplicity, Dify prioritizes completeness.
Self-Hosting
git clone https://github.com/langgenius/dify
cd dify/docker
cp .env.example .env
# Edit .env with your API keys
docker compose up -d
Dify runs as a set of Docker services (API, web, worker, db, redis, vector store). The web UI is available at http://localhost.
Team workspace
Ship faster with chat, meetings, and projects in one place — Zlyqor.
Each node type (LLM, Code, HTTP Request, Knowledge Retrieval, If-Else, Loop) is configured in a side panel.
Model Provider Hub
Dify connects to 30+ model providers through a unified interface: OpenAI, Anthropic, Google Gemini, Mistral, Bedrock, Azure OpenAI, Ollama (local), and hosted open-source models. You configure provider credentials once in Settings and reference models by name in any workflow.
Prompt Management with A/B Testing
Dify stores prompts as versioned assets. You can run A/B tests by routing a percentage of traffic to a new prompt version and comparing response quality metrics side-by-side before promoting.
API and Webhook Integration
Every Dify application exposes an API endpoint. The response format is consistent regardless of whether the app is a chatbot, workflow, or agent:
Flowise is simpler and maps more directly to LangChain concepts - good for developers who think in chains. Dify has better built-in RAG management, more robust dataset tooling, and prompt A/B testing - better for teams building production customer-facing applications where content management matters.
Practical deep-dives on LLMs, developer tools, and AI engineering. No filler. Unsubscribe any time.
// written byFIG. AUTH-01
530
Mahmudul Haque Qudrati
CEO & ML Engineer
CEO and ML Engineer at Pristren. Builds AI-powered software for teams and writes about machine learning, LLMs, developer tools, and practical AI applications.
Open Code Review – An AI-powered code review CLI tool: A Practical Overview
Open Code Review is an open-source CLI tool from Alibaba that uses AI to review code changes. It runs locally, supports multiple LLMs, and costs about $0.01 per review. Here's a practical breakdown.
