@prisma/studio-core

@prisma/studio-core

@prisma/studio-core is the embeddable Prisma Studio package.

It provides the same core experience as Prisma Studio: a visual way to explore schema, browse table data, edit rows, filter/sort/paginate records, inspect relation data, and run SQL queries with an operation log.

This package is published to npm and consumed by Prisma surfaces such as Console and CLI integrations.

Embedding Studio

Import the UI entrypoint, include the packaged CSS once, and pass a configured adapter into Studio:

import { Studio } from "@prisma/studio-core/ui";
import "@prisma/studio-core/ui/index.css";
import { createStudioBFFClient } from "@prisma/studio-core/data/bff";
import { createPostgresAdapter } from "@prisma/studio-core/data/postgres-core";

const adapter = createPostgresAdapter({
  executor: createStudioBFFClient({
    url: "/api/query",
  }),
});

export function EmbeddedStudio() {
  return (
    <Studio
      adapter={adapter}
      aiFilter={async (request) => {
        const response = await fetch("/api/ai-filter", {
          body: JSON.stringify({ prompt: request }),
          headers: { "content-type": "application/json" },
          method: "POST",
        });

        const payload = (await response.json()) as {
          error?: unknown;
          text?: unknown;
        };

        if (!response.ok) {
          throw new Error(
            typeof payload.error === "string"
              ? payload.error
              : `AI filter request failed (${response.status} ${response.statusText})`,
          );
        }

        if (typeof payload.text !== "string") {
          throw new Error("AI filter response did not include text.");
        }

        return payload.text;
      }}
    />
  );
}

adapter is required. aiFilter is optional and is the new LLM completion hook: it takes the user's natural-language request and returns JSON text describing one or more filters. When aiFilter is omitted, Studio renders only the manual filter controls and hides the inline AI prompt entirely. Studio handles prompt construction, type-aware validation, correction retries, and conversion into the normal URL-backed filter pills. The hook can return regular column filters or a SQL fallback when the request cannot be expressed with the predefined operators.

Telemetry

This package includes anonymized telemetry to help us improve Prisma Studio. Use implies consent. Learn more in our Privacy Policy.

Run Studio Locally

Requirements:

• Node.js ^20.19 || ^22.12 || ^24.0
• pnpm 8
• bun

Install dependencies and start the demo:

pnpm install
pnpm demo:ppg

Then open http://localhost:4310.

To enable the demo's AI filtering flow, copy .env.example to .env and set ANTHROPIC_API_KEY. The demo reads that key server-side and calls Anthropic Haiku 4.5 directly over HTTP for the aiFilter hook. Set STUDIO_DEMO_AI_FILTERING_ENABLED=false to hide the AI filter UI without removing the key. .env and .env.local are gitignored.

The demo:

• starts Prisma Postgres dev (ppg-dev) programmatically via @prisma/dev
• uses direct TCP for query execution
• seeds sample relational data on startup
• auto-rebuilds and reloads the UI when source files change

The demo database is intentionally ephemeral: it is pre-seeded when the demo starts and reset when the demo process stops.

Useful Commands

• pnpm demo:ppg - run local Studio demo with seeded Prisma Postgres dev
• pnpm typecheck - run TypeScript checks
• pnpm lint - run ESLint (--fix)
• pnpm test - run default vitest suite
• pnpm test:checkpoint - run checkpoint tests
• pnpm test:data - run data-layer tests
• pnpm test:demo - run demo/server tests
• pnpm test:ui - run UI tests
• pnpm test:e2e - run e2e tests
• pnpm demo:ppg:build - bundle the demo server with bun build
• pnpm demo:ppg:bundle - build and run the bundled demo server
• pnpm build - build distributable package with tsup
• pnpm check:exports - validate package export map/types

When bundling the demo with bun build, we use --packages external so @prisma/dev can resolve its PGlite runtime assets (WASM/data/extensions) directly from node_modules at runtime.

Development Workflow

For day-to-day development, use an agent with Playwright available and let the agent run the demo itself.

Recommended flow:

• Let the agent run pnpm demo:ppg.
• Let the agent inspect terminal logs and browser behavior together.
• Let the agent verify UI state via Playwright after changes.

Because the demo is pre-seeded and resets between runs, update seed data whenever needed to reproduce richer scenarios.

Seed data lives in /Users/sorenschmidt/code/studio-private/demo/ppg-dev/server.ts (seedDatabase).