Visual Workflow AI
Execution

Execution Basics

Understanding the fundamental execution flow in Visual Workflow AI

When you run a workflow in Visual Workflow AI, the execution engine follows a systematic process to ensure blocks are executed in the correct order with proper data flow.

Execution Flow

The execution engine runs workflows in layers, processing blocks based on their dependencies:

Validation: Ensures the workflow has a starter block with no incoming connections and all blocks are properly connected.

Layer-based Execution: Identifies which blocks can execute next based on completed dependencies and executes them in parallel.

Path Updates: Router and Condition blocks update the active execution path, determining which blocks execute next.

Iteration Processing: Loop and Parallel blocks manage iterations and create virtual instances for concurrent execution.

Result Collection: Outputs from the final blocks are collected and returned as the workflow result.

Block Types and Execution

Different block types have different execution behaviors:

Orchestration blocks control the flow of execution through your workflow.

Starter Block
Router Block
Condition Block
Loop Block
Parallel Block

Processing blocks transform data and generate new outputs.

Agent Block
Function Block
Evaluator Block
Workflow Block

Integration blocks connect with external systems.

API Block
Knowledge Base Block
Response Block
Tool Blocks

Execution Methods

Visual Workflow AI offers multiple ways to trigger workflow execution:

Manual Execution

Run workflows on-demand through the Visual Workflow AI interface by clicking the "Run" button. This is perfect for:

  • Testing during development
  • One-off tasks
  • Workflows that need human supervision

Scheduled Execution

Configure workflows to run automatically on a specified schedule:

  • Set up recurring executions using cron expressions
  • Define start times and frequency
  • Configure timezone settings
  • Set minimum and maximum execution intervals

API Endpoints

Each workflow can be exposed as an API endpoint:

  • Get a unique URL for your workflow
  • Configure authentication requirements
  • Send custom inputs via POST requests
  • Receive execution results as JSON responses

Webhooks

Configure workflows to execute in response to external events:

  • Set up webhook triggers from third-party services
  • Process incoming webhook data as workflow input
  • Configure webhook security settings
  • Support for specialized webhooks (GitHub, Stripe, etc.)

The execution method you choose depends on your workflow's purpose. Manual execution is great for development, while scheduled execution, API endpoints, and webhooks are better for production use cases.

Execution Context

Each workflow execution maintains a context that tracks:

  • Block States: Outputs and execution status of each block
  • Execution Path: Active blocks based on routing decisions
  • Loop/Parallel State: Current iterations and distribution items
  • Environment Variables: Configuration values available during execution
  • Execution Logs: Detailed records of each block's execution

Real-Time Monitoring

Monitor your workflow execution in real-time:

  • Active Block Highlighting: Currently executing blocks pulse with animation
  • Live Logs: Execution logs appear instantly in the logs panel
  • Block States: Visual indicators show success, error, or pending states
  • Performance Metrics: Execution time for each block

These monitoring features help you understand workflow behavior and quickly identify any issues.