What are the core concepts of Dify's workflow feature? How to design complex workflows?

Dify's Workflow feature allows users to orchestrate complex AI application processes visually, with core concepts including:

1. Node Types

   • Start Node: Defines workflow input parameters
   • LLM Node: Calls large language models for text generation
   • Knowledge Base Retrieval Node: Retrieves relevant information from knowledge base
   • Condition Node: Executes different logic based on conditions
   • Code Node: Executes custom Python/JavaScript code
   • HTTP Request Node: Calls external APIs
   • Template Node: Processes text using Jinja2 templates
   • End Node: Defines workflow output

2. Data Flow

   • Nodes pass data through variables
   • Supports referencing outputs from previous nodes
   • Supports global variables and context variables

3. Orchestration

   • Drag-and-drop visual interface
   • Supports serial and parallel execution
   • Supports loops and conditional branches

Use cases:

• Complex Q&A processes (multi-step retrieval, validation, generation)
• Automated document processing (extraction, analysis, report generation)
• Multi-model collaboration (using different models for different tasks)
• External system integration (calling third-party APIs)

Candidates should understand the basic concepts of workflows and how to design complex workflows to solve real-world problems.