Quick Change Caller

Required key.

Add this in your Lovable project under Settings → Secrets before pasting the prompt below.

Paste into a fresh Lovable project. Make sure the key above is set first. read the build strategy →

Build "Quick Change Caller" 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 plans backstage quick-change choreography so dressers avoid delays; Fish Audio reads step-by-step garment swaps during chaotic dress rehearsals.
Discipline: Theater & Live Performance (costume design backstage).
Recipe: Lovable AI brain + Fish Audio Text-to-Speech (streaming voice) as the voice surface.
Why this voice surface: Clear spoken instructions keep wardrobe crews synchronized when their hands are full of costumes.

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.
- TWO TanStack server functions max: one for the Lovable AI call (the brain),
  one for the Fish Audio call (the voice). Fold them into one if the voice
  primitive does not need server-side text generation.
- ONE client surface (a button, a mic, or a prompt box) wired to those server fns.
- 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 + `ai` + `@ai-sdk/openai-compatible` + `zod`.
  Fish Audio is plain `fetch` — do NOT install an audio SDK.
- 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.
- Lovable AI Gateway (the brain) + Fish Audio (the voice). All calls live
  inside `createServerFn` handlers so both keys stay on the server.
- Client surface fits the kernel: a prompt box for narration and voice design,
  a mic button for the voice loop, a live caption strip for transcription.
  Render markdown from the brain with `react-markdown` if you show the text.
- 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 Creative AI & Quantum Hackathon organised by StreetKode Fam during Indian Krump Festival 14".

BRAIN — Lovable AI Gateway (free for participants, no key prompt needed):
```ts
// src/lib/ai-gateway.server.ts
import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
export function gateway() {
  return createOpenAICompatible({
    name: "lovable",
    baseURL: "https://ai.gateway.lovable.dev/v1",
    headers: {
      "Lovable-API-Key": process.env.LOVABLE_API_KEY!,
      "X-Lovable-AIG-SDK": "vercel-ai-sdk",
    },
  });
}
```
Default model: `google/gemini-3-flash-preview`. Use `generateText` (or
`streamText` for long output) from `ai`. Keep prompts and model calls inside
the server function — never call the gateway from client code.

FISH AUDIO NOTES (read before writing the fetch call):
- Base URL `https://api.fish.audio`. Auth is `Authorization: Bearer <key>`.
- The TTS backend is chosen with a REQUEST HEADER, not a body field:
  `model: s2.1-pro`. (`s2.1-pro-free` is the same model at $0 for prototyping; `s1` is legacy.)
- `POST /v1/tts` takes JSON and returns RAW AUDIO BYTES, not JSON. Read it with
  `await res.arrayBuffer()` and base64 it with `Buffer.from(buf).toString("base64")`.
- Body fields: `text` (required), `format` ("mp3" | "wav" | "pcm" | "opus"),
  `mp3_bitrate` (64 | 128 | 192), `sample_rate`, `prosody: { speed, volume }`,
  and `reference_id` to speak in a specific voice model. Omit `reference_id`
  to use the default voice — that is the right call for a one-shot demo.
- `POST /v1/asr` takes `multipart/form-data` (`audio` file, optional `language`,
  `ignore_timestamps=false` for segment times) and returns JSON
  `{ text, duration, segments: [{ text, start, end }] }`.
- Errors come back as `{ "message": "...", "status": 401 }`. Always check
  `res.ok` and surface `res.status` plus a short slice of the body.

SERVER FUNCTION (src/lib/coach.functions.ts) — brain + voice in one call:
```ts
import { createServerFn } from "@tanstack/react-start";
import { generateText } from "ai";
import { z } from "zod";
import { gateway } from "./ai-gateway.server";

/** Built during the Creative AI & Quantum Hackathon organised by StreetKode Fam during Indian Krump Festival 14 */
export const speakAdvice = createServerFn({ method: "POST" })
  .inputValidator((d) => z.object({
    topic: z.string().min(1).max(500),
    language: z.string().default("English"),
  }).parse(d))
  .handler(async ({ data }) => {
    // 1. BRAIN — Lovable AI writes the answer for the costume design backstage use case.
    const { text } = await generateText({
      model: gateway()("google/gemini-3-flash-preview"),
      system: `You are an expert helper for costume design backstage. Answer in ${data.language}. ` +
              `Keep it warm, specific, under 120 words. Markdown is fine but no headings.`,
      prompt: data.topic,
    });

    // 2. VOICE — Fish Audio reads it back. Raw audio bytes come back, not JSON.
    const r = await fetch("https://api.fish.audio/v1/tts", {
      method: "POST",
      headers: {
        Authorization: `Bearer ${process.env.FISH_AUDIO_API_KEY!}`,
        "Content-Type": "application/json",
        model: "s2.1-pro",
      },
      body: JSON.stringify({ text, format: "mp3", mp3_bitrate: 128 }),
    });
    if (!r.ok) throw new Error(`TTS failed: ${r.status} ${(await r.text()).slice(0, 120)}`);
    const buf = await r.arrayBuffer();
    return { text, audio: Buffer.from(buf).toString("base64") };
  });
```

CLIENT (in the page component):
```tsx
import { useServerFn } from "@tanstack/react-start";
import { speakAdvice } from "@/lib/coach.functions";

const ask = useServerFn(speakAdvice);
const onSubmit = async (topic: string, language: string) => {
  const { text, audio } = await ask({ data: { topic, language } });
  // render `text` on screen with react-markdown, then:
  await new Audio(`data:audio/mpeg;base64,${audio}`).play();
};
```

Voice: Fish Audio's default. To use a specific one, pass `reference_id` from
https://fish.audio/discovery — but do not spend build budget on a voice picker.

TRANSLATION — included by default:
Add a language `<Select>` to the UI (English, Español, Français, Deutsch,
Português, हिंदी, 日本語). Before sending the AI output to Fish Audio, ask the
gateway to translate it into the chosen language in the same server function,
then pass the translated text to `/v1/tts`. Fish Audio's S2 models are
multilingual and detect the language from the text itself, so no extra
parameter is needed. Default the select to English so the demo works without a
click.

USER FLOW (the entire app — nothing else exists)
1. Land on the page; the headline previews what the demo does for costume design backstage.
2. The primary action (a 'play' button (or auto-play) that streams lifelike narration of any text the app generates) is one tap away; the rest of the layout supports it.
3. Lovable AI does the thinking, Fish Audio handles the voice surface, and the
   result (audio + any text) stays on screen so the user can retry or share.

KEYS — both already provided to participants for free:
1. `LOVABLE_API_KEY` (the AI brain). Auto-injected in every Lovable project.
   Read it only on the server via `process.env.LOVABLE_API_KEY`. Never prefix
   with `VITE_` and never expose to the client.
2. `FISH_AUDIO_API_KEY` (the voice). Ask Lovable to store it as a project
   secret (Project Settings -> Secrets); grab the key from
   https://fish.audio/go-api. Read it only on the server and send it as
   `Authorization: Bearer ${process.env.FISH_AUDIO_API_KEY}`. Never prefix with
   `VITE_`, never call api.fish.audio from the browser.

CREDIT (must appear in UI footer AND as JSDoc on the server function):
Built during the Creative AI & Quantum Hackathon organised by StreetKode Fam during Indian Krump Festival 14

Market sizing.

Indicative figures for hackathon pitches — refine with your own research before raising.