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Edit a Workflow

Learn how to modify, optimize, and maintain your existing workflows in Vectense Platform.

Accessing Workflow Editor​

  1. Go to Workflows: Click "Workflows" in the main navigation
  2. Find Workflow: Locate the workflow you want to edit
  3. Open Editor: Click on the workflow name or "Edit" button

Editor Interface​

The workflow editor provides:

  • Visual Workflow Builder: Drag-and-drop interface for workflow steps
  • Configuration Panels: Detailed settings for triggers, steps, and actions
  • Testing Tools: Manual execution and debugging capabilities
  • Monitoring Dashboard: Real-time execution status and metrics

Editing Workflow Components​

Basic Information​

Workflow Name and Description

  • Update workflow name for clarity
  • Modify description to reflect current functionality
  • Add documentation for team members

Active Status

  • Toggle workflow active/inactive state
  • Inactive workflows don't respond to triggers
  • Useful for maintenance and testing

Modifying Triggers​

Edit Existing Triggers Click on the trigger to modify its configuration:

Scheduled Triggers

  • Update cron expressions for new timing
  • Change timezone settings
  • Modify output variable names

Webhook Triggers

  • Update shared keys for security
  • Change memory variable assignments
  • Modify authentication requirements

File System Triggers

  • Update monitored directory paths
  • Change file pattern filters
  • Modify trigger conditions

Add New Triggers

  • Click "Add Trigger" to include additional trigger types
  • Configure multiple triggers for the same workflow
  • Set up redundant triggering mechanisms

Remove Triggers

  • Select trigger and click "Remove"
  • Confirm deletion and impact on workflow
  • Update dependent configurations

Modifying Workflow Steps​

Edit Step Configuration Click on any step to modify its settings:

LLM Actions

  • Update persona configuration (role, goals, skills)
  • Modify system instructions and prompts
  • Change AI model selection
  • Update input/output variable mappings

HTTP Actions

  • Change API endpoints and methods
  • Update request headers and authentication
  • Modify request body templates
  • Change response processing logic

File Actions

  • Update file paths and naming patterns
  • Change file format and content templates
  • Modify file access permissions
  • Update error handling for file operations

Add New Steps

  • Click "Add Step" to insert new actions
  • Choose from available integration types
  • Configure step parameters
  • Set up data flow with existing steps

Reorder Steps

  • Drag steps to change execution order
  • Ensure data dependencies are maintained
  • Update memory variable references
  • Test execution flow after reordering

Remove Steps

  • Select step and click "Remove"
  • Verify no other steps depend on removed step's outputs
  • Clean up unused memory variables

Memory Variable Management​

Variable Configuration

  • Input Variables: Data from triggers
  • Processing Variables: Intermediate step outputs
  • Output Variables: Final workflow results

Update Variable Names

  • Rename variables for clarity
  • Update all references throughout workflow
  • Maintain data type consistency

Variable Scope

  • Understand variable lifetime and accessibility
  • Clean up unused variables
  • Optimize memory usage

Data Flow Visualization

  • Use editor tools to trace data flow
  • Identify bottlenecks and dependencies
  • Optimize variable usage patterns

Advanced Editing Features​

Conditional Logic​

Adding Conditions

  • Click "Add Condition" to create branching logic
  • Configure condition expressions
  • Set up alternative execution paths

Condition Types

  • Value Comparisons: Compare variables to specific values
  • Data Presence: Check if variables contain data
  • Pattern Matching: Use regular expressions for text matching
  • Custom Logic: Write JavaScript expressions for complex conditions

Branch Management

  • Configure different steps for each condition branch
  • Handle error conditions and edge cases
  • Merge branches back to common execution paths

Error Handling​

Retry Configuration

  • Set up automatic retry for failed steps
  • Configure retry limits and delays
  • Define retry conditions and exceptions

Error Actions

  • Add specific actions for error scenarios
  • Send notifications on failures
  • Log error details for debugging

Graceful Degradation

  • Configure fallback actions when primary actions fail
  • Maintain workflow execution with reduced functionality
  • Provide meaningful error messages to users

Performance Optimization​

Step Parallelization

  • Identify steps that can run concurrently
  • Configure parallel execution groups
  • Optimize overall workflow execution time

Resource Management

  • Optimize AI model usage for cost efficiency
  • Implement caching for repeated operations
  • Minimize data transfer between steps

Execution Monitoring

  • Add performance measurement steps
  • Track execution metrics
  • Identify optimization opportunities

Persona Management​

Updating AI Personas​

Role Refinement

  • Adjust persona roles based on workflow results
  • Specialize roles for specific tasks
  • Update role descriptions for clarity

Goal Optimization

  • Refine goals based on execution outcomes
  • Add specific success criteria
  • Update goals to match business requirements

Skills Enhancement

  • Add new skills based on workflow needs
  • Remove irrelevant skills
  • Organize skills by priority

Communication Style

  • Adjust tone and style based on audience feedback
  • Optimize for specific output formats
  • Maintain consistency across workflow steps

Guardrails Updates

  • Update safety constraints based on experience
  • Add new restrictions as needed
  • Remove overly restrictive guardrails

Persona Testing​

  • Test persona changes with sample inputs
  • Verify output quality and consistency
  • Gather feedback from workflow users

Testing Modified Workflows​

Manual Testing​

Test Individual Steps

  • Use step-by-step testing mode
  • Verify each modification works correctly
  • Check data flow between modified steps

End-to-End Testing

  • Run complete workflow with test data
  • Verify all modifications work together
  • Check final outputs meet requirements

Edge Case Testing

  • Test with unusual or edge case inputs
  • Verify error handling improvements
  • Ensure robustness of modifications

A/B Testing​

Version Comparison

  • Run both original and modified versions
  • Compare performance and results
  • Make data-driven decisions about changes

Gradual Rollout

  • Deploy modifications to limited triggers first
  • Monitor performance and results
  • Expand deployment after validation

Regression Testing​

  • Ensure modifications don't break existing functionality
  • Test all workflow paths and conditions
  • Verify integration compatibility

Version Control and Backup​

Workflow Versioning​

  • Automatic versioning of workflow changes
  • Ability to revert to previous versions
  • Compare different workflow versions

Change Documentation​

  • Add comments explaining modifications
  • Document the reason for changes
  • Include testing results and validation

Backup Best Practices​

  • Export workflow configurations regularly
  • Maintain documentation of changes
  • Create backup copies before major modifications

Monitoring Modified Workflows​

Performance Tracking​

  • Monitor execution metrics after modifications
  • Compare performance before and after changes
  • Track success rates and error frequencies

Cost Analysis​

  • Monitor AI model usage costs
  • Track resource consumption changes
  • Optimize for cost efficiency

User Feedback​

  • Collect feedback on workflow outputs
  • Monitor user satisfaction with results
  • Make iterative improvements based on feedback

Common Modification Scenarios​

Adding New Integrations​

  1. Identify Integration Point: Determine where to add new integration
  2. Configure Integration: Set up new connection parameters
  3. Update Data Flow: Modify memory variables and data mapping
  4. Test Integration: Verify connectivity and data exchange
  5. Deploy Gradually: Roll out to limited scope first

Improving AI Responses​

  1. Analyze Current Outputs: Review AI response quality
  2. Refine Prompts: Update system instructions and persona
  3. Adjust Context: Modify knowledge base queries
  4. Test Improvements: Compare new vs. old responses
  5. Deploy Updates: Implement improvements in production

Optimizing Performance​

  1. Identify Bottlenecks: Find slow or resource-intensive steps
  2. Implement Caching: Cache frequent operations
  3. Parallelize Steps: Run independent steps concurrently
  4. Optimize AI Usage: Use appropriate models for each task
  5. Monitor Improvements: Track performance gains

Scaling Workflows​

  1. Analyze Capacity: Understand current limits
  2. Optimize Resource Usage: Improve efficiency
  3. Add Parallel Processing: Handle higher volumes
  4. Monitor Performance: Ensure scaling doesn't degrade quality
  5. Plan Further Growth: Prepare for continued scaling

Troubleshooting Edit Issues​

Common Problems​

Changes Not Saving

  • Check user permissions for workflow editing
  • Verify workflow is not currently running
  • Ensure valid configuration before saving

Broken Data Flow

  • Verify memory variable names and types
  • Check step dependencies and ordering
  • Test data flow with sample inputs

Integration Failures

  • Verify external system connectivity
  • Check API keys and authentication
  • Test integration configurations independently

Getting Help​

  • Documentation: Reference specific integration guides
  • Version History: Review previous working configurations
  • Support: Contact technical support for complex issues
  • Community: Share challenges with user community

Best Practices for Workflow Editing​

Change Management​

  • Test Before Deploying: Always test modifications thoroughly
  • Document Changes: Keep detailed records of modifications
  • Gradual Rollout: Deploy changes incrementally
  • Monitor Impact: Track the effects of modifications

Collaboration​

  • Team Coordination: Communicate changes with team members
  • Permission Management: Ensure appropriate edit access
  • Review Process: Implement peer review for critical workflows
  • Knowledge Sharing: Document lessons learned

Maintenance​

  • Regular Reviews: Periodically review workflow performance
  • Continuous Improvement: Make iterative optimizations
  • Technology Updates: Keep up with platform improvements
  • Security Updates: Maintain security best practices

With these editing capabilities, you can continuously improve and optimize your workflows. Next, explore Jobs to understand workflow execution monitoring and management.