Update app.py

app.py

@@ -18,13 +18,7 @@ def read_content(file_path: str) -> str:
 
 def predict(prompt, negative_prompt, guidance_scale, num_inference_steps, scheduler, lora, lora_weight):
     pipeline.safety_checker = lambda images, **kwargs: (images, [False] * len(images))
-    if lora == "add_detail":
-        lora = "profaker/add_detail_lora"
-    if lora == "nursing_job":
-        lora = "profaker/Nursing_job_lora"
-    if lora == "nsfw_POV":
-        lora = "profaker/NSFW_POV_lora"
-    pipeline.load_lora_weights(lora)
+    
 
     scheduler_class_name = scheduler.split("-")[0]
     add_kwargs = {}
@@ -34,7 +28,27 @@ def predict(prompt, negative_prompt, guidance_scale, num_inference_steps, schedu
         add_kwargs["algorithm_type"] = "sde-dpmsolver++"
     scheduler = getattr(diffusers, scheduler_class_name)
     pipeline.scheduler = scheduler.from_pretrained("emilianJR/epiCRealism", subfolder="scheduler", **add_kwargs)
-
+    if lora == "add_detail":
+        lora = "profaker/add_detail_lora"
+    if lora == "nursing_job":
+        lora = "profaker/Nursing_job_lora"
+    if lora == "nsfw_POV":
+        lora = "profaker/NSFW_POV_lora"
+    if lora == "None":
+        images = pipeline(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        num_inference_steps=int(num_inference_steps),
+        guidance_scale=guidance_scale
+        ).images[0]
+        print("Prompt", prompt)
+        print("Negative", negative_prompt)
+        print("Steps", num_inference_steps)
+        print("Scale", guidance_scale)
+        print("Scheduler", scheduler)
+        return images
+        
+    pipeline.load_lora_weights(lora)
     images = pipeline(
         prompt=prompt,
         negative_prompt=negative_prompt,
@@ -100,8 +114,8 @@ with image_blocks as demo:
                     scheduler = gr.Dropdown(label="Schedulers", choices=schedulers,
                                             value="DPMSolverMultistepScheduler-Karras")
                 with gr.Row(equal_height=True):
-                    lora = ['add_detail', 'nursing_job', 'nsfw_POV']
-                    lora = gr.Dropdown(label='Lora', choices=lora, value="add-detail")
+                    lora = ['None','add_detail', 'nursing_job', 'nsfw_POV']
+                    lora = gr.Dropdown(label='Lora', choices=lora, value="None")
                     lora_weight = [-1, -0.5, 0, 0.5, 1]
                     lora_weight = gr.Dropdown(label="Lora Weights", choices=lora_weight, value=0.5)
             with gr.Row(equal_height=True):