CI/CD & Automation

Use the same explicit workflow in automation that you use locally: initialize, inspect, stage, push.

Authentication

HF_TOKEN is the preferred CI path:

export HF_TOKEN=hf_...

You do not need to run opentraces auth login when HF_TOKEN is already set in the environment.

Recommended Pattern

For headless runs:

opentraces init --review-policy review --remote my-org/opentraces --no-hook
opentraces list
opentraces add --all
opentraces push --private --yes

If the runner needs to import traces from another dataset first:

opentraces pull owner/dataset --parser hermes --auto
opentraces push --private --yes

Health Checks

Run these before a gated push:

opentraces doctor
opentraces doctor --security

If you rely on optional integrations, configure them explicitly in automation:

opentraces setup trufflehog --enable
opentraces setup llm-review --enable

Those commands assume the required binary or endpoint is already available.

GitHub Actions Example

- name: Install opentraces
  run: pip install opentraces

- name: Initialize project
  env:
    HF_TOKEN: ${{ secrets.HF_TOKEN }}
  run: opentraces init --review-policy review --remote my-org/opentraces --no-hook

- name: Stage traces
  env:
    HF_TOKEN: ${{ secrets.HF_TOKEN }}
  run: opentraces add --all

- name: Push traces
  env:
    HF_TOKEN: ${{ secrets.HF_TOKEN }}
  run: opentraces push --private --yes

Notes

Use --private for proprietary codebases
Use --repo owner/dataset or --remote ... for shared team datasets
Use push --llm-review only if llm-review is already configured and reachable on the runner

●HUMAN ○MACHINE