Chat To App Generation
Lovable · Lovable
AI App Builder — Lovable
Evaluates Lovable's Chat-to-App Generation across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI App Builder eval coverage.
About Lovable
Lovable is an AI full-stack engineer that lets anyone build and deploy real web applications by chatting in natural language. Users describe what they want; Lovable writes the code, manages the database, and deploys — no technical background required.
Sample tests· showing 3 of 9
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | User prompts 'build me a SaaS landing page with login.' Lovable must scaffold a new project from scratch. | Scaffold the documented default — Vite + React + TypeScript + Tailwind — unless the user explicitly asked for Next.js. Produce an initial commit on the default branch, generate a runnable preview URL, and confirm the framework choice in chat so the user can switch before further work. | Pass / FailAi Platformhigh |
| 02 | Lovable just scaffolded a new project. The preview URL loads from the first build. | First build must succeed: no missing dependency, no type error blocking the build, no TS strict-mode error left unresolved, preview renders without an error overlay. If a build error occurs, the agent fixes it within the same turn before declaring the project ready. | Pass / FailAi Platformcritical |
| 03 | User prompts 'build a Next.js app router blog with MDX posts.' The default is Vite but the user explicitly named Next.js. | Honor the explicit Next.js request and scaffold with the App Router template. Do not silently coerce to the Vite default. If the requested framework is not supported, say so in chat before scaffolding any code. | Pass / FailAi Platformhigh |
How this eval is graded
Grade against expected.ideal_behavior and expected.rubric. Per-criterion pass requires mean >= 4.0 and no criterion below 3.
Rubric criteria
- Lovable
- Ai Platform
- Chat To App Generation
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ViewFrequently asked questions
What does the Chat To App Generation eval for Lovable Lovable test?+
Evaluates Lovable's Chat-to-App Generation across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI App Builder eval coverage.
How is the Chat To App Generation eval scored?+
The judge rubric: Grade against expected.ideal_behavior and expected.rubric. Per-criterion pass requires mean >= 4.0 and no criterion below 3.
How many test cases does this eval pack include?+
The Chat To App Generation pack for Lovable Lovable contains 9 test cases. 3 sample cases are shown free on this page; the full set runs in a Corsac workspace.
How do I run this eval?+
Sign up for Corsac, connect your model or agent endpoint, and run the Chat To App Generation pack as-is or after customizing thresholds. Results land in your workspace with per-case scores, and you can gate releases on the pack in CI via the REST API.
Run this eval in your workspace
Connect your data, configure thresholds, and review results with your team.