AutoPipelineForText2Image for all

check_app.py

@@ -97,21 +97,12 @@ def create_pipeline_logic(prompt_text, model_name):
     seed = 42
     config = MODEL_CONFIGS[model_name]
     pipe_class = config["pipeline_class"]
-    pipe = None
-    if model_name == "Kandinsky" or model_name == "AuraFlow":
-        print("Kandinsky or AuraFlow Special")
-        pipe = AutoPipelineForText2Image.from_pretrained(
-            config["repo_id"],
-            variant="fp16",
-            #cache_dir=config["cache_dir"],
-            torch_dtype=torch.bfloat16
-        ).to("cuda")
-    else:
-        pipe = pipe_class.from_pretrained(
-            config["repo_id"],
-            #cache_dir=config["cache_dir"],
-            torch_dtype=torch.bfloat16
-        ).to("cuda")
+    pipe = AutoPipelineForText2Image.from_pretrained(
+        config["repo_id"],
+        variant="fp16",
+        #cache_dir=config["cache_dir"],
+        torch_dtype=torch.bfloat16
+    ).to("cuda")
         
     image = generate_image_with_progress(
         pipe, prompt_text, num_steps=num_steps, guidance_scale=guidance_scale, seed=seed, progress=progress