Kann ich Wireflow vibecoden?

Build me a local visual pipeline runner for AI media generation. Requirements:

- One Vite + React app and one Express server in the same repo, SQLite via
  better-sqlite3, no auth, no accounts, runs on localhost.
- Canvas on React Flow: drag nodes from a palette, wire outputs to inputs,
  pan and zoom, autosave the graph to SQLite on every change.
- Six node types only: Text input, Image import (upload to ./storage), Prompt
  template (interpolates {{upstream}} values), Image generate, Video generate,
  Preview. Generate nodes call fal.ai through @fal-ai/client, FAL_KEY in .env.
- Model config lives in models.json: per model, its fal path and which fields
  are wired ports versus typed-in settings. Ship exactly two entries,
  fal-ai/flux/dev and fal-ai/kling-video/v1/standard/text-to-video.
- Run = topological sort, execute layer by layer, store each node's output in
  SQLite keyed by node id plus a hash of its resolved inputs. Re-running only
  re-executes nodes whose input hash changed.
- Generate nodes NEVER run on edit. Only the Run button or a per-node run
  button submits a job. This rule is the whole point, do not add reactive
  auto-execution anywhere.
- Submit through fal's queue API and poll by request id, persisting the request
  id BEFORE the first poll, so a finished job survives a server restart.
- README covers where FAL_KEY goes, that every run spends real money at
  fal.ai, and how to add a third model to models.json.

Excluded on purpose: multiplayer, credits and billing, iterators or fan-out
over arrays, video assembly, hosted deploys, and any provider besides fal.ai.

Antworte mir auf Deutsch. Oberfläche, Kommentare und README auf Deutsch, alle Bezeichner wie Tabellen, Spalten, Variablen, Routen und Dateinamen bleiben Englisch.