Connect your self-hosted Gitea repositories to Label Studio to streamline annotation workflows and dataset versioning.
Store and track Label Studio exports directly in Gitea for full dataset version history.
Trigger annotation tasks in Label Studio automatically when new data lands in Gitea.
Keep sensitive training data and annotations entirely within your own infrastructure.
Push completed Label Studio annotation exports to Gitea repositories for versioned dataset management.
Automatically create Label Studio tasks when new raw data files are committed to a Gitea repository.
Coordinate annotation completion in Label Studio with Gitea CI pipelines to trigger model retraining.
Open Gitea pull requests for annotation batch reviews before merging labeled datasets into main branches.
Track annotation assignments across Label Studio projects using Gitea issues as coordination layer.
Maintain a full audit trail of who annotated what data by linking Label Studio tasks to Gitea commits.
Link your Gitea instance and Label Studio project to Neotask using your API credentials.
Tell the agent which repositories to watch and how to map data files to annotation tasks.
The agent monitors commits, creates tasks, tracks annotation progress, and pushes exports back to Gitea.
| Gitea Action | Label Studio Action | Use Case |
|---|---|---|
| New file committed | Create annotation task | Trigger labeling for new data |
| Branch merged | Export labeled dataset | Finalize annotation batch |
| Issue created | Create Label Studio project | Organize annotation work |
| CI pipeline triggered | Check annotation completion | Gate training on label status |
| Pull request opened | Request annotation review | QA labeled datasets before merge |
| Tag created | Archive annotation snapshot | Version-pin training datasets |
| Repository webhook fired | Sync task metadata | Keep systems consistent |
Gitea provides self-hosted git infrastructure for teams who need full control over their code and data. Label Studio handles the human-in-the-loop annotation work that machine learning pipelines depend on. Connecting them closes a critical gap in ML data workflows.
ML teams often manage raw data, annotation tasks, and labeled datasets across disconnected systems. Files get copied manually, annotation exports live outside version control, and CI pipelines have no visibility into labeling status.
With Neotask, an AI agent can watch Gitea repositories for new data commits, create corresponding Label Studio annotation tasks, track completion, export labeled datasets, and commit them back to Gitea.
Every annotation export committed to Gitea is tied to a specific commit hash, making it possible to reproduce any training run exactly. This is essential for regulated industries and research environments.
Use consistent file naming in Gitea commits so the agent can map them to Label Studio tasks reliably.
Set up Gitea webhooks pointing to Neotask for the fastest response to new data commits.
Tag annotation export commits in Gitea so you can reproduce any model training run exactly.
Yes. Neotask connects to self-hosted Gitea and Label Studio instances using your API tokens and instance URLs. No data needs to leave your infrastructure.
Yes. You can instruct the agent to watch specific repositories or branches and create corresponding annotation tasks whenever new data files are committed.
By committing Label Studio exports back to Gitea, every labeled dataset is tied to a specific git commit. This gives you a full history of which annotations were used to train each model version.
Yes. You can configure the agent to check Label Studio task status before allowing a Gitea CI pipeline to proceed.
Neotask connects Gitea and Label Studio so your annotation workflow runs itself.
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