Input
GitLab REST API path, e.g. /api/v4/user
Allowed values: GET, POST, PUT, PATCH, DELETE.
URL query parameters as key-value pairs.
Additional request headers.
Request body (POST/PUT/PATCH).
05
Retry count on 5xx/timeout. Range: 0 to 5.
Idle
Example output — click Run to generate your own
Production endpoint
Send your first request
OpenAI-compatible endpoint with unified authentication and usage tracking.
POST
https://api.sandbase.ai/v1/runModel ID
sandbase/gitlab01
Input Schema
6 parameters · 1 required · 5 optional
| Parameter | Type | Required | Description |
|---|---|---|---|
endpoint | string | Required | GitLab REST API path, e.g. /api/v4/user |
body | object | Optional | Request body (POST/PUT/PATCH). |
method | string | Optional | Options: GET, POST, PUT, PATCH, DELETE GETPOSTPUTPATCHDELETE |
params | object | Optional | URL query parameters as key-value pairs. |
headers | object | Optional | Additional request headers. |
retries | integer | Optional | Retry count on 5xx/timeout. · Min: 0 · Max: 5 |
02
Output Schema
| Field | Type | Description |
|---|---|---|
id | string | Unique identifier for the generation task |
status | string | Task status: pending, running, completed, failed, timeout |
model | string | Model used for the generation |
outputs | array | Array of output items |
outputs[].url | string | URL of the generated artifact |
outputs[].content_type | string | MIME type (e.g. image/png, video/mp4) |
error | object | null | Error details if failed, null on success |
error.type | string | Machine-readable error type code |
error.message | string | Human-readable error description |
03
Code Examples
Ready-to-run snippets
curl -X POST https://api.sandbase.ai/v1/run \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "sandbase/gitlab",
"prompt": "a beautiful sunset over mountains"
}'API README
GitLab
Access the GitLab REST API through OAuth.
Capability
Access the GitLab REST API through OAuth. It supports applications, agents, and automated workflows that need structured results.
Common use cases
- Build focused dashboards and discovery experiences.
- Create repeatable integrations for internal tools and automation.
- Support research, monitoring, and downstream data workflows.

