CF Workers AI backend: flux direct (backnforth contract) + local border-flood keyer

/api/gen prefers Cloudflare flux-1-schnell (free ~10k neurons/day) over the
farm; /api/rmbg falls back to a Pillow border-flood white-keyer when no
MB_TOKEN (flood from edges through near-white only — traps-ledger rule, white
ON the garment survives). Creds in gitignored .env, lifted from ultra.
Verified end-to-end: brown-corduroy-jacket flux'd, keyed, in the wardrobe.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

.gitignore

@@ -4,3 +4,4 @@ out/
 jobs/
 __pycache__/
 .DS_Store
+.env

server.py

@@ -30,8 +30,18 @@ EXTRA_BODIES = [os.path.expanduser('~/Documents/anatomy'),
 CACHE = os.path.join(ROOT, '.glbcache')
 BLENDER = os.environ.get('WG_BLENDER', '/Applications/Blender.app/Contents/MacOS/Blender')
 OPS = os.path.join(ROOT, 'blender_ops.py')
+# .env beside server.py (gitignored) — CF Workers AI creds live here, lifted from
+# backnforth/.env on ultra (the proven flux.mjs contract). Never printed, never committed.
+_envp = os.path.join(ROOT, '.env')
+if os.path.exists(_envp):
+    for _l in open(_envp):
+        if '=' in _l and not _l.startswith('#'):
+            k, v = _l.split('=', 1)
+            os.environ.setdefault(k.strip(), v.strip())
 MB = os.environ.get('MB_HOST', 'http://100.89.131.57:8777')
 MB_TOKEN = os.environ.get('MB_TOKEN', '')
+CF_ACCT = os.environ.get('CLOUDFLARE_ACCOUNT_ID', '')
+CF_TOKEN = os.environ.get('CLOUDFLARE_API_TOKEN', '')
 PORT = int(os.environ.get('WG_PORT', 8150))
 HOST = os.environ.get('WG_HOST', '127.0.0.1')
 for d in list(DIRS.values()) + [CACHE]:
@@ -182,7 +192,8 @@ class H(BaseHTTPRequestHandler):
         if u.path == '/':
             return self.send(200, open(os.path.join(ROOT, 'web', 'index.html'), 'rb').read(), 'text/html')
         if u.path == '/api/lib':
-            return self.j({'lib': scan(), 'mb': bool(MB_TOKEN), 'blender': os.path.exists(BLENDER)})
+            return self.j({'lib': scan(), 'mb': bool(MB_TOKEN), 'cf': bool(CF_ACCT and CF_TOKEN),
+                           'blender': os.path.exists(BLENDER)})
         if u.path.startswith('/api/job/'):
             jid = u.path.rsplit('/', 1)[1]
             return self.j(JOBS.get(jid) or {'status': 'unknown'})
@@ -256,8 +267,8 @@ class H(BaseHTTPRequestHandler):
             return self.j({'job': jid})
 
         if u.path == '/api/gen':                  # the garment pipeline, step 1: flux image
-            if not MB_TOKEN:
+            if not (CF_ACCT and CF_TOKEN) and not MB_TOKEN:
-                return self.j({'error': 'MB_TOKEN not set on this box — export MB_TOKEN=… and restart'}, 400)
+                return self.j({'error': 'no image backend — need .env CF creds or MB_TOKEN'}, 400)
             prompt = body.get('prompt', '')
             style = ('product photo of a single {} laid flat on a plain white background, '
                      'front view, no mannequin, no person, no text, soft even lighting, '
@@ -265,36 +276,73 @@ class H(BaseHTTPRequestHandler):
             jid = new_job('gen', 'flux: ' + prompt[:40])
 
             def fx(jid):
+                tgt = os.path.join(DIRS['gen'], slug(prompt) + '.png')
+                if CF_ACCT and CF_TOKEN:          # Cloudflare Workers AI direct — the flux.mjs contract
+                    import base64
+                    JOBS[jid]['note'] = 'cloudflare flux-1-schnell'
+                    req = urllib.request.Request(
+                        f'https://api.cloudflare.com/client/v4/accounts/{CF_ACCT}/ai/run/@cf/black-forest-labs/flux-1-schnell',
+                        data=json.dumps({'prompt': style, 'steps': 8, 'width': 768, 'height': 768}).encode(),
+                        headers={'Authorization': 'Bearer ' + CF_TOKEN, 'Content-Type': 'application/json'})
+                    with urllib.request.urlopen(req, timeout=120) as r:
+                        out = json.load(r)
+                    if not out.get('success'):
+                        raise RuntimeError(str(out.get('errors'))[:300])
+                    with open(tgt, 'wb') as f:
+                        f.write(base64.b64decode(out['result']['image']))
+                    return tgt
                 j = mb_req('/api/jobs', {'operator': 'flux_local', 'asset_id': None,
                                          'params': {'prompt': style, 'model': 'flux2-klein-4b',
                                                     'steps': 4, 'width': 768, 'height': 768,
                                                     'seed': int(time.time()) % 99991}})
-                done = mb_wait(j.get('id') or j.get('job_id'), jid)
+                mb_wait(j.get('id') or j.get('job_id'), jid)
                 outs = mb_outputs(j.get('id') or j.get('job_id'))
                 if not outs:
                     raise RuntimeError('no image came back')
-                tgt = os.path.join(DIRS['gen'], slug(prompt) + '.png')
                 return mb_download(outs[0], tgt)
             job_thread(jid, fx)
             return self.j({'job': jid})
 
-        if u.path == '/api/rmbg':                 # step 2: cut it out
+        if u.path == '/api/rmbg':                 # step 2: cut it out (farm RMBG, else local white-keyer)
-            if not MB_TOKEN:
-                return self.j({'error': 'MB_TOKEN not set'}, 400)
             p = body.get('path', '')
             if not allowed(p):
                 return self.j({'error': 'nope'}, 403)
             jid = new_job('rmbg', 'cutout ' + os.path.basename(p))
 
             def fx(jid):
+                tgt = p.rsplit('.', 1)[0] + '-cut.png'
+                if MB_TOKEN:                       # RMBG-2.0 on the farm — best quality
                     aid = mb_upload(p)
                     j = mb_req('/api/jobs', {'operator': 'bg_remove_local', 'asset_id': aid, 'params': {}})
                     mb_wait(j.get('id') or j.get('job_id'), jid)
                     outs = mb_outputs(j.get('id') or j.get('job_id'))
                     if not outs:
                         raise RuntimeError('no cutout came back')
-                tgt = p.rsplit('.', 1)[0] + '-cut.png'
                     return mb_download(outs[0], tgt)
+                # local fallback: border-flood white-keyer (never naive white→alpha — traps ledger).
+                # flood from the edges through near-white pixels only, so white ON the garment survives.
+                JOBS[jid]['note'] = 'local white-keyer'
+                from PIL import Image
+                im = Image.open(p).convert('RGBA')
+                w, h = im.size
+                px = im.load()
+                near = lambda c: c[0] > 232 and c[1] > 232 and c[2] > 232
+                seen = bytearray(w * h)
+                stack = [(x, y) for x in range(w) for y in (0, h - 1)] + \
+                        [(x, y) for y in range(h) for x in (0, w - 1)]
+                while stack:
+                    x, y = stack.pop()
+                    i = y * w + x
+                    if seen[i] or not near(px[x, y]):
+                        continue
+                    seen[i] = 1
+                    px[x, y] = (0, 0, 0, 0)
+                    if x > 0: stack.append((x - 1, y))
+                    if x < w - 1: stack.append((x + 1, y))
+                    if y > 0: stack.append((x, y - 1))
+                    if y < h - 1: stack.append((x, y + 1))
+                im.save(tgt)
+                return tgt
             job_thread(jid, fx)
             return self.j({'job': jid})
 

web/index.html

@@ -228,7 +228,8 @@ $('clearAtBtn').onclick = () => { attached.forEach(a => a.parent && a.parent.rem
 async function refresh() {
   const r = await fetch('/api/lib').then(r => r.json());
   LIB = r.lib;
-  $('farm').textContent = (r.blender ? 'blender ✓' : 'blender ✗') + ' · farm ' + (r.mb ? '✓' : 'token missing');
+  $('farm').textContent = (r.blender ? 'blender ✓' : 'blender ✗') +
+    ' · flux ' + (r.cf ? 'cf ✓' : r.mb ? 'farm ✓' : '✗') + ' · farm3D ' + (r.mb ? '✓' : 'token missing');
   renderLists();
 }
 function rowHtml(it, kind) {