Curtain Call Critic
Lovable AI structures theatrical critiques so reviewers write faster; AIsa captures it.
AIsa Chat (LLM Router)· frontier reasoning
Section · AIsa
full primer →The kernel.
Performance review gets a frontier-model brain: a server function calls AIsa's LLM router and directors read a tailored, on-brand answer they can act on.
Why this primitiveCritics can verbally process their immediate post-show reactions and answer guided questions while walking home from the venue.
Kernel
an OpenAI-compatible `POST /v1/chat/completions` against https://api.aisa.one/v1 — pick any frontier model (openai/gpt-4o-mini, anthropic/claude-3-5-sonnet, google/gemini-2.5-flash, qwen/qwen2.5-72b, deepseek/deepseek-chat) through one endpoint, one key
Drives the UI as
a prompt box or chat surface that returns markdown the user can read, copy, or act on
Required key.
AISA_API_KEY
Single key for AIsa chat completions, image generation, video generation and live skills. Free tier covers a hackathon weekend.
open ↗Add this in your Lovable project under Settings → Secrets before pasting the prompt below.
Appendix · Mega-prompt
The build prompt.
budget · 1 message
Paste into a fresh Lovable project. Make sure the key above is set first. read the build strategy →
Build "Curtain Call Critic" as a ONE-SHOT Lovable build. The participant has only
5 credits — this single message must produce a working demo with no follow-ups.
Single-page TanStack Start app. Cut scope ruthlessly.
CONCEPT
Lovable AI structures theatrical critiques so reviewers write faster; AIsa captures it.
Discipline: Theater & Live Performance (performance review).
Recipe: AIsa Chat (LLM Router) (frontier reasoning) as the single creative surface.
Why this kernel: Critics can verbally process their immediate post-show reactions and answer guided questions while walking home from the venue.
LOVABLE BUDGET (HARD CAP: ONE-SHOT, ~5 CREDITS TOTAL):
The participant has FIVE Lovable credits for the whole build. This prompt MUST
ship a working demo on the FIRST message with zero follow-ups. Engineer for that.
- ONE TanStack Start app, ONE route (`src/routes/index.tsx`). No extra pages, no auth, no nav.
- ONE TanStack server function in `src/lib/aisa.functions.ts` that proxies the AIsa call.
- ONE client surface (a textarea + button, or chat box, or prompt-to-canvas) wired to it.
- NO database, NO Lovable Cloud, NO auth, NO file uploads, NO extra integrations.
- NO tests, NO docs pages, NO settings screens, NO theming toggles.
- Libraries: template defaults + `zod`. Nothing else.
- Keep the diff small enough to land in one build pass. If a feature is not on
screen in the user flow below, do not build it. Cut scope before adding scope.
STACK
- TanStack Start app, the index route only.
- AIsa is the only AI dependency. All API calls live inside a `createServerFn`
handler so `AISA_API_KEY` stays on the server.
- Client surface fits the kernel: a prompt box that returns the result.
- Tailwind + shadcn. Editorial look: gold accent on a dark or warm-cream
background, generous type, one strong headline, one primary action.
- Footer renders: "Built during the AIsa Creative Hackathon organised by StreetKode Fam during Indian Krump Festival 14".
SERVER FUNCTION (src/lib/aisa.functions.ts) — AIsa chat completions:
```ts
import { createServerFn } from "@tanstack/react-start";
import { z } from "zod";
/** Built during the AIsa Creative Hackathon organised by StreetKode Fam during Indian Krump Festival 14 */
export const ask = createServerFn({ method: "POST" })
.inputValidator((d) => z.object({ topic: z.string().min(1).max(2000) }).parse(d))
.handler(async ({ data }) => {
const r = await fetch("https://api.aisa.one/v1/chat/completions", {
method: "POST",
headers: {
"Authorization": `Bearer ${process.env.AISA_API_KEY!}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "gpt-4o-mini",
messages: [
{ role: "system", content: `You are an expert helper for performance review. ` +
`Reply in friendly markdown, under 180 words, with concrete next steps.` },
{ role: "user", content: data.topic },
],
temperature: 0.7,
}),
});
if (r.status === 402) throw new Error("AIsa balance exhausted — top up at console.aisa.one.");
if (r.status === 429) throw new Error("AIsa rate limited — try again in a moment.");
if (!r.ok) throw new Error(`AIsa chat failed: ${r.status}`);
const j = await r.json();
return { reply: j.choices[0].message.content as string };
});
```
CLIENT (in `src/routes/index.tsx`):
```tsx
import { useServerFn } from "@tanstack/react-start";
import { useState } from "react";
import ReactMarkdown from "react-markdown";
import { ask } from "@/lib/aisa.functions";
const run = useServerFn(ask);
const [topic, setTopic] = useState("");
const [reply, setReply] = useState<string | null>(null);
const [busy, setBusy] = useState(false);
const onAsk = async () => {
setBusy(true); setReply(null);
try { const { reply } = await run({ data: { topic } }); setReply(reply); }
finally { setBusy(false); }
};
```
Use BARE model ids (e.g. `gpt-4o-mini`, `claude-3-5-sonnet`, `gemini-2.5-flash`,
`qwen2.5-72b`) — NO `openai/`, `anthropic/`, or `google/` prefix. Browse the live
list at https://aisa.one/models.
USER FLOW (the entire app — nothing else exists)
1. Land on the page; the headline previews what the demo does for performance review.
2. The primary action (a prompt box or chat surface that returns markdown the user can read, copy, or act on) is one tap away; the rest of the layout supports it.
3. AIsa runs the kernel server-side, the result lands on screen, the user can retry or copy.
KEY — only ONE secret is required:
1. `AISA_API_KEY`. Sign up at https://console.aisa.one, copy the key into
Project Settings -> Secrets. Read it only on the server via
`process.env.AISA_API_KEY`. Never prefix with `VITE_`, never expose
to the client. A single key unlocks chat, image, video and skills.
CREDIT (must appear in UI footer AND as JSDoc on the server function):
Built during the AIsa Creative Hackathon organised by StreetKode Fam during Indian Krump Festival 14
Market sizing.
TAM
$30B
global live performance market
SAM
$800M
arts journalism and media
SOM
$25M
review dictation software
Indicative figures for hackathon pitches — refine with your own research before raising.
Adjacent entries.
playwright script polishing
Dialogue Rhythm Doctor
Lovable AI rewrites clunky dialogue so the playwright fixes pacing; AIsa reads the new lines aloud to test the written rhythm.
director stage blockingBlocking Whisper Guide
Lovable AI generates stage blocking instructions so the director plans movement; AIsa writes them into an earpiece during tech rehearsals.
actor memorization rehearsalLine Prompt Shadow
Lovable AI creates mnemonic cues so actors remember forgotten lines; AIsa whispers the prompts gently during solo rehearsal runs.
lighting design programmingCue Sequence Narrator
Lovable AI writes poetic lighting state descriptions so designers visualize moods; AIsa narrates the cue sequence aloud to inspire programming.