Files
infiplot-web/README.md
T
Zonghao Yuan e261f4a346 feat: Runware FLUX.2 image + lazy per-beat TTS (#5)
Reduce median scene-load latency from ~30-80s to ~17-25s by switching image generation to Runware FLUX.2 [klein] 9B KV and moving per-beat TTS synthesis off the scene response into a new lazy /api/beat-audio endpoint with hard timeout + abort support.

- feat(image): migrate to Runware FLUX.2 [klein] 9B KV — task-array API, $0.001/image, sub-second inference.
- feat(tts): split /api/scene into directScene + image + voicedesign-provisioning; lazily synth per beat via /api/beat-audio with 15s hard timeout + AbortSignal threaded to MiMo so timed-out calls don't keep burning sockets/quota; client fans out per-beat fetches on scene-id change with abort + identity-check finally to prevent cross-scene beat-id collisions.
- refactor(tts): slim BeatAudioRequest to { beat, voice } — ~800KB per-beat upload dropped to ~160KB by sending only the speaker's voice instead of the full session.

🤖 Generated with [Claude Code](https://claude.com/claude-code)
2026-05-28 23:43:51 +08:00

92 lines
4.5 KiB
Markdown
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
# 云梦
> An AI-driven visual novel painted by an AI, one scene at a time. You talk and explore within a scene; when the story turns a corner, it paints the next. You click. It paints. The story unfolds.
---
## How it works
The story unfolds as a sequence of **scenes**. Each scene is one AI-painted background plus a short tree of **beats** — moments of narration, dialogue, and the occasional choice. You tap through a scene's beats and the image stays put; only when a choice leads somewhere genuinely new — another place, a new point of view, a jump in time — does the AI paint the next scene.
```
entering a scene
1. Text LLM directs the whole scene at once — a background prompt
plus a tree of beats (narration / dialogue / choices)
2. Image model paints the background once, 16:9, no UI baked in
[ tap through beats — no model calls, instant ]
├─ in-scene choice ──────▶ jump to another beat (instant)
└─ scene-change choice ──▶ the next scene
(usually pre-generated — see below)
```
While you're reading one scene, the engine **speculatively generates the scenes your choices could lead to** — and, for unavoidable next steps, the scene after that. By the time you pick a direction, its image is usually already painted, so the cut feels instant.
Clicking the background itself (not a button) routes through a **vision** model: it reads where you tapped and decides whether you're exploring the current scene (it inserts a beat — no new image) or moving on (a new scene).
There is no traditional game UI baked into the art. The AI paints the world in whatever style you pick — "stick figure on grid paper" or "cyberpunk noir" — and the dialogue panel and choice buttons are a light HTML layer drawn on top, tuned to sit over the scene.
---
## One-click deploy
[![Deploy with Vercel](https://vercel.com/button)](https://vercel.com/new/clone?repository-url=https://github.com/YOUR_USERNAME/yume&env=TEXT_BASE_URL,TEXT_API_KEY,TEXT_MODEL,IMAGE_BASE_URL,IMAGE_API_KEY,IMAGE_MODEL,VISION_BASE_URL,VISION_API_KEY,VISION_MODEL&envDescription=Three%20independently%20configurable%20providers.%20Any%20OpenAI-compatible%20endpoint%20works.&envLink=https://github.com/YOUR_USERNAME/yume%23environment-variables)
After deploy, set the nine environment variables (see below) in your Vercel project. That's it.
---
## Environment variables
Three providers, all independently configurable. Text and Vision accept any OpenAI-compatible endpoint (OpenAI, Anthropic via OpenAI-compat proxy, Gemini, OpenRouter, DeepSeek, local Ollama, …). Image goes to **Runware** (its own task-array protocol, not OpenAI-compatible).
| Provider | Variables | Recommended |
|---|---|---|
| Text · story director | `TEXT_BASE_URL` `TEXT_API_KEY` `TEXT_MODEL` | `claude-opus-4-7` via Anthropic |
| Image · UI renderer | `IMAGE_BASE_URL` `IMAGE_API_KEY` `IMAGE_MODEL` | `runware:400@6` (FLUX.2 [klein] 9B KV) via [Runware](https://runware.ai) |
| Vision · click reader | `VISION_BASE_URL` `VISION_API_KEY` `VISION_MODEL` | `gemini-3-flash` via Google |
See `apps/web/.env.example` for the exact shape.
---
## Local development
Requires Node 20+ and pnpm 9+.
```bash
pnpm install
cp apps/web/.env.example apps/web/.env.local
# fill in the nine env vars
pnpm dev
# open http://localhost:3000
```
---
## Project layout
```
yume/
├── apps/web/ Next.js 16 app — pages + API routes
└── packages/
├── types/ shared TypeScript types
├── ai-client/ unified OpenAI-compatible clients
└── engine/ three-stage AI orchestration (open core)
```
`packages/engine` is the open core — pure TS, no Next.js or browser dependency. Import it directly to build your own visual-novel front-end (Tauri, Electron, CLI, anywhere).
---
## Cost & limits
With the recommended trio, each **scene** is dominated by the text-LLM call. The FLUX.2 [klein] 9B KV image is roughly **\$0.001** per scene (1792×1024, 4 steps, sub-second); the text call is the rest. Tapping through a scene's beats is free. To keep transitions instant, the engine also **pre-generates scenes you might pick but don't** — so real spend runs somewhat higher than the scenes you actually see. There is no rate limiting or auth out of the box — if you make your deployment public, your bill will reflect that. Add limits (and consider lowering the prefetch depth) before sharing widely.