One library. Your workflow.
Use cases
Bring structure to the scripts that build, train, generate, and move your data. Tubeless connects typed steps so you can preview the work and see what happened at each stage.
01 / CI/CD
Make every release step explicit.
Turn build, validation, and publication scripts into one pipeline. Pass artifacts between typed steps and make successful checks a prerequisite for publishing.
Check the plan before a release
Preview a target and its prerequisites without executing steps. Mark publication steps to skip during dry runs.
Find the failed step
Record step results, timings, and logs. Export an NDJSON trace as a CI artifact to inspect after the job ends.
02 / ML flows
Connect the work around your model.
Keep the path from a dataset to a model artifact in one typed workflow. Use your own functions for preparation and evaluation, and call a training service when the heavy compute belongs elsewhere.
Reuse an evaluation workflow
Compose evaluation as a child pipeline, then fan out across datasets or model candidates with bounded concurrency and per-item progress.
Check results at the boundary
Validate remote outputs with a schema and make model registration depend on an evaluation step that rejects unacceptable results.
03 / LLM workflows
Give each model call a place in the flow.
Build a document enrichment job, a retrieval-augmented answer flow, or a batch evaluation. Keep prompts and provider calls in your own code while Tubeless tracks the steps around them.
Control API traffic
Use retry and rate-limit helpers around provider calls. Fan out over documents with bounded concurrency and forward cancellation to requests.
Validate before saving
Check structured model output with a schema before downstream steps consume it. Use a custom dry-run handler for a preview that avoids a paid model call.
04 / Data pipelines
Follow your data from source to destination.
Read from your source, normalize records, enrich them through an API, and write the result. Each step declares the data it needs, with TypeScript checking the values passed between steps.
See progress through a batch
Report completed items and inspect keyed failures in child pipelines. Use checkpointed batch helpers when your application needs to track completed work for a later run.
Preview writes deliberately
Mark database and filesystem writes to skip during dry runs, or supply a side-effect-free preview handler. Inspect recorded logs and timings in the local Studio.
05 / Operational workflows
Turn repeat tasks into inspectable runbooks.
Wrap a tenant setup task, a migration, or a maintenance script in a named command. Declare its inputs and prerequisites so teammates can preview the work and follow its progress.
Offer one command catalog
Register commands explicitly in a project manifest. Use the same definitions from the terminal or launch them through the local Studio.
Make side effects visible
Provide dry-run previews for mutations and record real runs for troubleshooting. Pass cancellation into long-running work and inspect the steps that completed.
Start with a script you already run.
Choose its inputs, give each stage a name, and connect the outputs. Keep the domain logic in your own functions.