Centralize image family runtime and workflow adapters

image_test.py

@@ -13,7 +13,7 @@ import threading
 import time
 import urllib.request
 import uuid
-from profiles import QWEN_REPO, FLUX_REPO, image_recipe, image_capabilities
+from profiles import image_adapter, image_recipe, image_capabilities
 
 PYTHON=Path('/opt/deck-image-python/bin/python')
 COMFY=Path('/opt/deck-comfy')
@@ -160,11 +160,11 @@ class ImageTests:
         encoder=self.profiles._component(model,'text_encoder',profile.get('components',{}).get('text_encoder'))
         vae=self.profiles._component(model,'vae',profile.get('components',{}).get('vae'))
         mem={line.split(':')[0]:int(line.split()[1])*1024 for line in Path('/proc/meminfo').read_text().splitlines() if line.startswith(('MemAvailable:','MemTotal:'))}
-        required_ram=max(20*GIB,encoder['size']*2+4*GIB,model['size']+8*GIB if model['repo']==FLUX_REPO else 0)
+        required_ram=max(20*GIB,encoder['size']*2+4*GIB,model['size']+8*GIB if image_adapter(model)['offload'] else 0)
         headroom=cgroup_headroom()
         if headroom is not None and headroom<required_ram:raise ValueError('Deck-RAM-Limit reicht für Textencoder und Arbeitsdaten nicht aus.')
         if mem.get('MemAvailable',0)<required_ram+4*GIB:raise ValueError('Aktuell zu wenig freier System-RAM; produktive Dienste bleiben unverändert.')
-        gpu,encoder_gpu=select_gpus(probe(),model['size'],encoder['size'],vae['size'],offload=model['repo']==FLUX_REPO);self.root.mkdir(parents=True,exist_ok=True,mode=0o700)
+        gpu,encoder_gpu=select_gpus(probe(),model['size'],encoder['size'],vae['size'],offload=image_adapter(model)['offload']);self.root.mkdir(parents=True,exist_ok=True,mode=0o700)
         if shutil.disk_usage(self.root).free<10*GIB:raise ValueError('Weniger als 10 GiB freier Plattenspeicher.')
         job_id=uuid.uuid4().hex;seed=params['seed'] if params['seed']>=0 else secrets.randbelow(2147483648)
         self.cancel.clear();self.job=dict(id=job_id,state='running',phase='Bildlaufzeit startet',profile_id=profile_id,profile_name=profile['name'],started_at=time.time(),gpu=gpu['name'],encoder_gpu=encoder_gpu['name'],seed=seed,parameters=params,reference_count=len(references))
@@ -181,7 +181,7 @@ class ImageTests:
             if self.cancel.is_set():raise InterruptedError()
             self._phase('Prompt-Aufwerter entladen; Bildlaufzeit startet')
         directory.mkdir(mode=0o700)
-        for role,item,filename in [('unet',model,'model.safetensors' if model['repo']==FLUX_REPO else 'model.gguf'),('clip',encoder,'encoder.safetensors'),('vae',vae,'vae.safetensors')]:
+        for role,item,filename in [('unet',model,image_adapter(model)['model_filename']),('clip',encoder,'encoder.safetensors'),('vae',vae,'vae.safetensors')]:
             dest=directory/'models'/role;dest.mkdir(parents=True);(dest/filename).symlink_to(self.model_path(item))
         for folder in ('output','temp','user','input'):(directory/folder).mkdir()
         names=[]
@@ -218,7 +218,7 @@ class ImageTests:
                 if time.monotonic()>deadline:raise ValueError('Bildlaufzeit wurde nicht rechtzeitig bereit.')
                 time.sleep(1)
         nodes=request('/object_info')
-        graph=workflow(prompt,params,seed,'flux' if model['repo']==FLUX_REPO else 'qwen',names)
+        graph=workflow(prompt,params,seed,image_adapter(model)['workflow'],names)
         required={node['class_type'] for node in graph.values()}
         if not required.issubset(nodes):raise ValueError('Der installierten Bildlaufzeit fehlen erforderliche Nodes für dieses Bildmodell.')
         self._phase('Auftrag wird verarbeitet · Textencoder auf RTX 3060 · Bildberechnung auf RTX 5080')