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Overview

A pipeline run tracks:
  • Timeline - Chronological sequence of node executions with timestamps
  • State snapshots - Variable values before and after each node execution
  • Run status - Current execution state (In Progress, Completed, Error, Stopped, Interrupt)
  • Node progression - Which nodes have executed and which is currently active
  • Error information - Detailed error messages and stack traces when failures occur
Pipelines can be executed from two locations:
  • Pipeline Editor (Run tab) - Direct execution environment
  • Chat → Canvas - Conversational execution interface
Both methods provide identical run tracking and state management capabilities.

Run States and Status Tracking

Pipeline Run States Each pipeline run progresses through distinct execution states. The current state is displayed in the Run Chipset within the Flow View (Configuration tab).
StateVisual IndicatorDescriptionAvailable Actions
In ProgressIn progressPipeline is actively executing nodesStop execution
CompletedIn progressAll nodes executed successfullyView details, Delete run
ErrorIn progressExecution failed with an exceptionView error details, Delete run
StoppedIn progressManually stopped by userView partial results, Delete run
Run states are visible in the Flow View (Configuration tab), where the Run Chipset displays current and recent runs with their status indicators.

Accessing Run Information

The Run Chipset appears in the Configuration tab (Flow View) and provides access to detailed run information.

From Flow View (Pipeline Editor)

Run Chipset Display:
  • Single Run: Shows one run chipset with status icon and run name
  • Multiple Runs: Shows current run + history icon (🕐 clock icon) to access previous runs
    • Click the history icon to view a dropdown of all previous runs
    • Current/most recent run is always displayed separately
    • Each run in the dropdown can be opened (click run name) or deleted (click delete icon)
    History

From Chat Interface

Access run information from chat executions through Canvas mode:
  1. Navigate to Chat and add/select a pipeline
  2. Execute pipeline with input or conversation starters
  3. Click Settings(gear) button → Canvas view opens
  4. Click Flow Editor tab
  5. View Run Chipset and click run name for details Chat Run
The Chat → Canvas → Flow Editor path provides the same run tracking capabilities as direct pipeline execution.

Run Details Dialog

Click on any run name in the chipset to open the Run Details Dialog, which provides comprehensive information about the execution. Dialog Sections:
  1. Header
    • Run name/label
    • Current status badge
    • Action buttons (Stop/Delete)
    • Close button
  2. Timeline Section
    • Timeline Step: Shows current node being executed (or last completed node)
    • Status Indicator: Real-time status of the current node
    StatusDescriptionVisual Indicator
    In ProgressNode is actively executingIn progress
    CompletedNode finished successfullyIn progress
    ErrorNode failed with an errorIn progress
    StoppedManually stopped by userIn progress
    • Visual Timeline: Stepper component showing all executed nodes
      • Each step shows timestamp (HH:mm:ss format)
      • Click any step to view its state details
      • Green connector line indicates successful progression
      • Red connector line indicates error occurred
  3. States Section
    • Expandable accordion for each state variable
    • Before and After values for each node execution
    • Full-screen view button for detailed inspection
    Run Details

Monitoring Execution

Real-Time Monitoring

During Active Execution:
  • Run Chipset: Shows blue circular progress indicator in Flow View
  • Timeline Tracking: Run Details Dialog displays current node and timestamp
  • Node Highlighting: Active node highlighted in Configuration tab
  • Chat Progress: Results stream progressively in Run or Chat interface
Monitoring Current State:
  1. Click run name in Run Chipset
  2. Run Details Dialog opens
  3. Timeline shows current node execution
  4. States section displays real-time variable values

Active Execution Indicators

Flow View (Configuration Tab):
  • Run chipset displays with blue progress spinner
  • Current node highlighted on canvas
  • Timeline step shows “Performing” status

Output Viewing

State Inspection:
  • Open Run Details Dialog
  • Expand state variable accordions
  • View before/after values for each node

Debugging and Error Handling

Error State Details

When a run enters Error state, the Run Details Dialog provides:
  • Error message: Exception details displayed in red
  • Failed node: Timeline highlights node where error occurred
  • State snapshot: Variable values at time of failure
  • Stack trace: Technical error information in chat interface
Error Hnadling

Best Practices

Initialize with defaults:
state:
  search_query:
    type: str
    value: ""
  max_results:
    type: int
    value: 10
Always map node outputs:
- id: "Fetch Data"
  type: "function"
  function: "jira_toolkit||search"
  output: ["search_results", "messages"]  # Required!
Use interrupts for:
  • Validating data transformations
  • Manual approval gates
  • Debugging complex workflows
  • Human-in-the-loop processes
Configuration:
interrupt_before:
  - "Critical Processing Node"

interrupt_after:
  - "Data Validation"
During Development:
  • Use interrupt points to inspect state
  • Add descriptive node names for clarity
  • Test with edge cases and invalid inputs
In Production:
  • Monitor run history for patterns
  • Track error rates in Monitoring tab
  • Set appropriate step limits
  • Configure conversation starters for guidance

Troubleshooting

Common Execution Errors and Solutions

Purpose: Temporarily override state variable values to test specific scenarios or isolate issues.Method: Set fixed values directly in the state section:
state:
  issue_key:
    type: str
    value: "PROJ-123"  # Hardcoded for testing
  
  user_input:
    type: str
    value: "test query"  # Override user input
  
  max_results:
    type: int
    value: 5  # Fixed value for debugging
Use Cases:
  • Skip user input: Test pipeline logic without manual entry
  • Reproduce errors: Lock specific values that caused failures
  • Isolate node behavior: Test individual nodes with known inputs
  • Validate transformations: Use predictable data to verify outputs
Best Practices:
  • Document hardcoded values with comments
  • Remove or revert before production deployment
  • Use interrupt points to verify hardcoded values are applied
  • Test with multiple hardcoded scenarios (edge cases, invalid data)
Set hardcoded values + interrupt points to step through execution with controlled data:
state:
  debug_data:
    type: str
    value: "test"  # Hardcoded

interrupt_before:
  - "Processing Node"  # Pause to inspect
Error Message:
Entry point is not defined in the schema. 
Please define 'entry_point' in the schema.
Cause: Pipeline has no starting node configured.Solution:
  1. Open pipeline in Configuration tab
  2. Click three dots (⋮) on the node that should start execution
  3. Select “Entry Point” from the menu
  4. Save the pipeline
Entry Point Configuration
Error Message:
Missing required parameter: issue_key
During task with name 'Fetch Jira Ticket'
Cause: Node’s input_mapping references undefined or empty state variable.Solution:
  1. Check if variable is defined in state section
  2. Verify previous nodes populate the variable
  3. Add default value if appropriate:
state:
  issue_key:
    type: str
    value: ""  # Add default
Error Message:
Transition target 'Next Step' not found
Cause: Node’s transition points to non-existent node.Solution:
  1. Open Flow Designer
  2. Check connection from failing node
  3. Ensure target node exists and is properly named
  4. Update transition to correct node ID or END
Error Message:
Expected type 'int' but got 'str' for variable 'count'
Cause: Variable assigned value of wrong type.Solution:
  • Ensure type conversion in Code nodes:
- id: "Convert Types"
  type: "code"
  code:
    type: "fixed"
    value: |
      count_str = alita_state.get('count', '0')
      {"count": int(count_str)}  # Convert to int
  output: ["count"]
  structured_output: true

Understanding Error Structure:
Error during task with name 'Node Name':
[Exception Type]: Error details here

Stack trace:
  File "...", line X, in function
    code line causing error

Current state:
  variable1: value1
  variable2: value2
Key Components:
  1. Node Name: Where the error occurred
  2. Exception Type: Type of Python error (KeyError, ValueError, etc.)
  3. Error Details: Specific message about what went wrong
  4. Stack Trace: Technical execution path (focus on end)
  5. Current State: State variables at time of error
Reading Tips:
  • Focus on the last exception in the stack trace
  • Check Current State section for variable values
  • Node Name tells you exactly where to look in your pipeline
  • Exception Type hints at the category of problem