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Usage Guide

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Creating a Pipeline​

  1. Right-click in the Explorer or click + in the RocketRide sidebar.
  2. Choose Create Pipeline to create a new .pipe file.
  3. The visual editor opens automatically for .pipe files.
  4. Drag components from the component palette onto the canvas.
  5. Configure each component's properties in the properties panel.
  6. Connect component outputs to inputs by drawing connections between lanes.
  7. Save the file, changes are auto-saved.

Running a Pipeline​

  1. Right-click a .pipe file in the Explorer or sidebar.
  2. Select Run Pipeline, or use Ctrl+Shift+P and search for RocketRide: Run Pipeline.
  3. The Status page opens with real-time execution monitoring.
  4. Watch data flow through components, view completion metrics, and check for errors.

Debugging a Pipeline​

  1. Right-click a .pipe file and select Debug Pipeline.
  2. The debugger opens with breakpoint support.
  3. Set breakpoints on components to pause execution.
  4. Step through the pipeline and inspect variable values at each breakpoint.

Attaching to a Running Pipeline​

If a pipeline is already running on the server:

  1. Right-click a .pipe file and select Attach to Pipeline.
  2. The Status page opens and streams real-time data from the running pipeline.

Deploying to Cloud​

  1. Right-click a .pipe file and select Deploy Pipeline.
  2. The Deploy page opens.
  3. Configure deployment settings.
  4. Click Deploy to push the pipeline to RocketRide.ai cloud.

Pipeline Editor​

The visual editor provides:

  • Component palette: Browse and search available nodes (sources, LLMs, stores, etc.).
  • Canvas: Drag-and-drop workspace for arranging components.
  • Properties panel: Configure selected component settings (API keys, models, connection strings, etc.).
  • Lane connections: Draw lines between component output and input lanes to define data flow.

Monitoring Execution​

The Status page shows:

  • Component status: Pending, running, completed, or failed indicators for each component.
  • Data flow: Visual representation of data moving through the pipeline.
  • Metrics: Completion rates and timing charts.
  • Errors: Detailed error messages and logs for failed components.

AI-Assisted Development​

When enabled, the Copilot and Cursor integrations provide:

  • Pipeline structure suggestions based on your use case.
  • Component configuration recommendations.
  • Error diagnosis and fix suggestions.
  • Pipeline optimization tips.

Enable these in settings under rocketride.integrations.copilot and rocketride.integrations.cursor.