Quickstart¶
This page walks through a minimal YAML pipeline, running it from Python and the CLI.
1. Create a pipeline file¶
Save as pipeline.yaml:
name: quickstart
settings:
tracing: true
steps:
- id: reply
type: template_response
config:
template: "Answer placeholder for: {query}"
The template_response component fills an output field from the {query} placeholder in your input payload.
2. Run from Python¶
from oris import Pipeline
pipeline = Pipeline.from_yaml("pipeline.yaml")
result = pipeline.run({"query": "What is responsible AI?"})
print(result.output)
You should see a dict that includes your original query and a string output from the template.
3. Run from the CLI¶
oris validate pipeline.yaml
oris run pipeline.yaml --input-json '{"query":"What is responsible AI?"}'
Pretty-printed JSON and debug-style trace lines on stderr:
4. Inspect structured output¶
summary = result.to_run_summary()
print(summary["status"], summary["run_id"])
print(summary["trace"])
See Runs, output & traces for the full summary shape.
Sample files in the repo¶
The repository includes ready-made YAML under examples/ and Jupyter notebooks you can execute locally—see Examples.
Next¶
- Concepts overview — how pieces fit together
- CLI reference — all
orissubcommands - SafeRunner — wrap external LLM code with the same policy checks