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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.

Pipeline Execution Defaults​

Trace verbosity, the idle timeout (TTL), task arguments, and debug output for pipeline runs are configured once in Settings → Pipeline — they are workspace settings, not per-pipeline options:

  • Pipeline Trace Level (rocketride.pipelineTraceLevel, default summary): how much execution-trace data the engine emits — full, summary, metadata, or none. Higher levels populate the Flow and Trace tabs, but full inlines entire payloads (including images), which can noticeably slow runs that process large images.
  • Pipeline TTL (rocketride.pipelineTTL, default 900 = 15 minutes): how long the engine keeps a pipeline alive without activity before stopping it. Fixed choices from 15 minutes to 8 hours, plus "Run forever or until you stop it" (0 = no timeout).
  • Task Arguments (rocketride.taskArguments, default empty): additional command-line arguments passed to each pipeline task process. The engine splits the string using shell parsing rules, so quoted paths are preserved.
  • Pipeline Debug Output (rocketride.pipelineDebugOutput, default false): appends --trace=debugOut to the task arguments (unless they already contain a --trace= flag) for detailed task trace logging.

The extension host reads these from the workspace settings and passes them to the engine on each run/restart (the status:pipelineAction message carries only the action and source). The engine process itself starts with no extra flags — these settings apply per task, not to the server.

.env Auto-Sync​

After a successful engine connection, the extension syncs the workspace .env only for the development connection group using a self-hosted mode (local, Docker, service, or direct/on-prem connection). It writes the resolved ROCKETRIDE_URI (including a dynamic local port when applicable) and ROCKETRIDE_APIKEY, preserves existing comments and variables, and does not rewrite the file when its contents are already current. The RocketRide Python SDK reads the workspace .env automatically from its process working directory; the TypeScript SDK and CLIs read only process environment variables, so export the values first (for example, set -a; source .env).

Cloud connections are not synced because their OAuth token is not an SDK API key. Deployment connections, workspaces with no folder open, and unreadable .env files are also skipped; a sync failure never affects the connection itself. Keep .env gitignored.

The extension never automatically removes these keys: disconnecting, engine exit, or switching to cloud leaves the last-synced values in place. Remove them by hand if you no longer want them. Each development-group self-hosted connection syncs again, so a hand-edited ROCKETRIDE_APIKEY is overwritten on the next successful connection.

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.

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