Run workflows

Executing an AI Workflow in CogniBlocks

Before running a CogniBlocks Workflow, ensure that: ✅ All necessary Cognitive Units (Blocks) are placed in the workspace. ✅ Connections between Blocks are properly established. ✅ Required inputs (if applicable) are provided. ✅ Any modified Blocks are saved and compiled before execution.

Once everything is set, initiate the workflow by clicking the "Execute" button.

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Monitoring Execution Logs

Once the workflow starts running:

• Click the Logs button to view real-time execution details.

• If this is the first time running a workflow, Docker images will be built before execution.

• On subsequent runs (if no changes were made), containers will execute without rebuilding, reducing execution time.

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Workflow Execution History & Data Storage

When a CogniBlocks Workflow is executed, a dedicated directory is created to store execution details.

📂 Workspace Storage Structure:

bashCopyEdit/workspace/.cache/workflow-${workflow_id}/
  ├── {run_uuid}/
  │   ├── outputs/   # Stores generated output files  
  │   ├── logs/      # Execution logs for debugging  
  │   ├── results.json  # Detailed workflow execution report  
  ├── workflow.json  # Workflow structure & Block connections  

• Each workflow run creates a unique subdirectory named after a UUID for version tracking.

• The workflow.json file outlines the structure & links between Blocks.

• If the run is successful, a results.json file is generated, logging:

  • Block Inputs & Outputs

  • Execution timestamps

  • Processing metadata

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🚀 Now you’re ready to execute, monitor, and analyze workflows in CogniBlocks!