Platform
The platform at platform.schemalabs.ai, page by page, how each maps to the API, and Chat.
The platform is a client of the same API: every button is a REST call, an endpoint created over the API appears in the list immediately, and both surfaces draw one usage meter.
Pages
Nav: Dashboard · Data · Quick run · Workspace · Endpoints · Reports · Chat · API, with account settings behind your name.
| Page | What it does | REST |
|---|---|---|
| Dashboard | Getting started, the base catalog, org state (endpoints live, held-out at a glance, usage brief) | GET /v2/models, /v2/endpoints, /v2/usage |
| Data | Connections and datasets: names, types, rows, sizes, sync state, pin state, synthetic generator. A catalog view; analytical outputs come from runs and appear on Reports | /v2/data |
| Quick run | The same POST /v2/run as the API: one action, full bundle rendered, nothing saved. Continue in Workspace carries the configuration over | POST /v2/run |
| Workspace | Compose an endpoint configuration (data, target, task, base), preview the bundle, publish with Create endpoint | POST /v2/endpoints on publish |
| Endpoints | The stateful objects: serve URL and curl example, pinned data, System Instructions, Chat tab, history, logs, Refresh / Upgrade / Delete | /v2/endpoints, /v2/serve/:id |
| Reports | Every report, newest first, pinned first. Star to pin; Compare any two side by side (where the upgrade delta is read) | /v2/reports |
| Chat | Ask an endpoint’s pinned data questions in plain language | platform only |
| API | Keys with scopes, endpoint URLs with curl examples, jobs with status and exact cell count, notifications | /v2/keys, /v2/jobs |
Both run surfaces render the bundle exactly as the API returns it, prediction labeled in-context; the held-out badge appears on endpoint results. The cell count is shown before you confirm any job.
The endpoint page
- Serve URL with curl example. Serving is REST-only with a
serve-scoped key. - Pinned data:
ds @ dsvper dataset, with Refresh on current data. - System Instructions: the endpoint’s system-prompt library, edited here. See System prompts.
- History: the report trail. Logs: the operation trail, never row data.
Chat
Chat connects an endpoint to an LLM of your choice and answers questions over the pinned dataset. Chat narrates the bundle already computed on the endpoint with your LLM; it runs no inference of its own. You see only the answer, rendered as best fits the question: a sentence, a table, a chart.
- Bring your own LLM key. Narration runs on your provider account; Schema meters no tokens and no cells for Chat. Sessions are rate-limited.
- Consent is recorded when you connect a provider, and again before the first send when the endpoint’s column profile flags PII.
- Compare: off, two endpoints, or two LLMs. The same prompt fans out and the answers render side by side.
- System Instructions are toggleable per conversation; toggling changes nothing on the endpoint. Adding, editing, or deleting a fragment writes the endpoint library and is a config revision.
- Chat answers are narration: the graded number lives on the endpoint’s held-out report.
- Requires an endpoint whose dataset is pinned; nothing else.
Over REST, call POST /v2/serve/:id and narrate the bundle with your own LLM, applying the endpoint’s exposed system_prompts for parity. See Agents and LLM frameworks.
What lives where
- Chat is platform-only; serving is REST-only (humans preview with Quick run or a Workspace preview).
- Account and org administration are platform-only.
- Notifications (job completion, usage alerts) arrive in the platform and by email; programmatic consumers poll
GET /v2/jobs/:idandGET /v2/usage. - Plan availability per surface: see Plans.