Support FLUX reference images through real edit workflow

README.md

@@ -230,3 +230,5 @@ Weitere Dienste und nutzt Decks Musikworker statt einer eigenen GPU-Laufzeit.
 Installation, Verbindung und Einschränkungen: [LadyPoly](deploy/ladypoly/README.md).
 
 Sprachmodell-GPUs und Vision-Projektor werden unabhängig zugeordnet. Der Modell-Split verteilt ausschließlich LLM-Gewichte; eine zusätzliche Projektor-GPU wird nur für mmproj sichtbar gemacht, nicht für Modell-Offload. Die Speicherprüfung berücksichtigt beide Geräte einschließlich Projektorbedarf.
+
+Referenzbilder: Alle derzeit ausführbaren Bildrezepte (Qwen Image 2.1 und FLUX.2 Klein 9B) erlauben bis zu vier Bilder pro Bearbeitungsauftrag. FLUX nutzt VAEEncode und verkettete ReferenceLatent-Nodes für beide Conditioning-Zweige nach dem offiziellen ComfyUI-Workflow: https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_flux2_klein_image_edit_9b_distilled.json . Neue Modellfamilien benötigen einen passenden Workflow; hochgeladene Referenzen werden niemals stillschweigend verworfen.

endpoint.py

@@ -348,7 +348,8 @@ class APIHandler(BaseHTTPRequestHandler):
         if data.get('n',1)!=1 or data.get('response_format','b64_json')!='b64_json':raise APIError('Unterstützt werden n=1 und response_format=b64_json.')
         profile=ep.find_profile(data.get('model'),'image');params=profile['parameters']
         from profiles import image_capabilities
-        if len(reference_images or [])>image_capabilities(profile.get('model'))['reference_images']:raise APIError('Das aktive Bildprofil unterstützt diese Anzahl Referenzbilder nicht.')
+        limit=image_capabilities(profile.get('model'))['reference_images']
+        if len(reference_images or [])>limit:raise APIError(f"Bildprofil {profile['name']}: {len(reference_images or [])} Referenzbilder erhalten; die Deck-Laufzeitanbindung erlaubt maximal {limit}.")
         size=data.get('size')
         if size is not None and (not isinstance(size,str) or (size!='auto' and not re.fullmatch(r'[1-9][0-9]{1,4}x[1-9][0-9]{1,4}',size))):raise APIError('size muss auto oder eine Auflösung wie 1024x1024 sein.')
         # The selected profile owns resource limits; client size is only a preference.

image_test.py

@@ -46,9 +46,10 @@ def select_gpus(devices,model_size,encoder_size,vae_size,offload=False):
     return max(images,key=lambda g:g['free_mib']),encoders[0]
 
 def workflow(prompt,params,seed,family='qwen',references=()):
-    if references and family!='qwen':raise ValueError('Dieses Bildprofil unterstützt keine Referenzbilder.')
+    if family not in ('qwen','flux'):raise ValueError('Für diese Modellfamilie fehlt eine Bildlaufzeit-Anbindung.')
+    if len(references)>4:raise ValueError('Maximal vier Referenzbilder pro Auftrag.')
     if family=='flux':
-        return {
+        graph={
           '1':{'class_type':'UNETLoader','inputs':{'unet_name':'model.safetensors','weight_dtype':'default'}},
           '2':{'class_type':'DeckTextEncoderLoader','inputs':{'clip_name':'encoder.safetensors','family':'flux2'}},
           '3':{'class_type':'VAELoader','inputs':{'vae_name':'vae.safetensors'}},
@@ -64,6 +65,20 @@ def workflow(prompt,params,seed,family='qwen',references=()):
           '13':{'class_type':'ConditioningZeroOut','inputs':{'conditioning':['4',0]}}
         }
 
+        # FLUX.2 editing uses reference latents on both conditioning branches,
+        # with fresh output noise; never silently discard uploaded references.
+        positive=['4',0];negative=['13',0]
+        for index,name in enumerate(references):
+            load,scale,encode,pos,neg=map(str,range(20+index*5,25+index*5))
+            graph[load]={'class_type':'LoadImage','inputs':{'image':name}}
+            graph[scale]={'class_type':'ImageScaleToTotalPixels','inputs':{'image':[load,0],'upscale_method':'lanczos','megapixels':1.0,'resolution_steps':1}}
+            graph[encode]={'class_type':'VAEEncode','inputs':{'pixels':[scale,0],'vae':['3',0]}}
+            graph[pos]={'class_type':'ReferenceLatent','inputs':{'conditioning':positive,'latent':[encode,0]}}
+            graph[neg]={'class_type':'ReferenceLatent','inputs':{'conditioning':negative,'latent':[encode,0]}}
+            positive=[pos,0];negative=[neg,0]
+        graph['10']['inputs'].update(positive=positive,negative=negative)
+        return graph
+
     graph={
       '1':{'class_type':'UnetLoaderGGUF','inputs':{'unet_name':'model.gguf'}},
       '2':{'class_type':'DeckTextEncoderLoader','inputs':{'clip_name':'encoder.safetensors'}},

profiles.py

@@ -65,8 +65,8 @@ def image_recipe(model):
  return None
 
 def image_capabilities(model):
- """Only advertise reference editing for the verified Qwen Image 2.1 workflow."""
- return {'reference_images':4 if model and model.get('repo')==QWEN_REPO and model.get('file','').endswith('.gguf') else 0}
+ """All currently supported image recipes have a reference-image workflow."""
+ return {'reference_images':4 if model and image_recipe(model) else 0}
 
 LTX_REPO='Lightricks/LTX-2.5'
 LTX_FILE='diffusion_models/ltx-2.5-22b-distilled-transformer-bf16.safetensors'

test_image_test.py

@@ -23,7 +23,22 @@ class ImageTestTests(unittest.TestCase):
   self.assertEqual(graph['4']['inputs']['image_2'],['22',0])
   self.assertEqual(graph['6']['inputs']['latent_image'],['4',2])
   self.assertEqual(graph['21']['inputs']['image'],'reference-1.png')
-  with self.assertRaises(ValueError):workflow('test',p,1,'flux',['reference-1.png'])
+  with self.assertRaises(ValueError):workflow('test',p,1,'unknown',['reference-1.png'])
+ def test_flux_references_feed_both_conditioning_branches(self):
+  p=dict(width=512,height=512,steps=4,guidance=1)
+  for count in (1,4):
+   graph=workflow('synthetic edit',p,42,'flux',[f'reference-{i}.png' for i in range(count)])
+   self.assertEqual(sum(n['class_type']=='ReferenceLatent' for n in graph.values()),count*2)
+   self.assertEqual(graph['10']['inputs']['positive'],[str(23+(count-1)*5),0])
+   self.assertEqual(graph['10']['inputs']['negative'],[str(24+(count-1)*5),0])
+   self.assertEqual(graph['22']['inputs']['vae'],['3',0])
+   self.assertEqual(graph['6']['inputs']['latent_image'],['5',0])
+  with self.assertRaises(ValueError):workflow('test',p,1,'flux',['r.png']*5)
+ def test_reference_capabilities_follow_supported_recipes(self):
+  from profiles import image_capabilities,FLUX_REPO,QWEN_REPO
+  self.assertEqual(image_capabilities(dict(repo=FLUX_REPO,file='Flux.2 Klein-9B_fp16_nsfw.safetensors'))['reference_images'],4)
+  self.assertEqual(image_capabilities(dict(repo=QWEN_REPO,file='model.gguf'))['reference_images'],4)
+  self.assertEqual(image_capabilities(dict(repo='unknown',file='model.safetensors'))['reference_images'],0)
  def test_reference_validation_enforces_profile_limit_and_signature(self):
   import base64
   png='data:image/png;base64,'+base64.b64encode(b'\x89PNG\r\n\x1a\nsynthetic').decode()