Update app.py

app.py

@@ -2,6 +2,9 @@ import gradio as gr
 import random
 import os
 
+# model = gr.load("models/prithivMLmods/SD3.5-Turbo-Realism-2.0-LoRA") # <-- This model is also working
+model = gr.load("models/Purz/face-projection")
+
 
 default_negative_prompt = (
     "Extra limbs, Extra fingers or toes, Disfigured face, Distorted hands, Mutated body parts, "
@@ -15,18 +18,17 @@ default_negative_prompt = (
     "Unrealistic anatomy, Bad proportions, Unrealistic colors, Artificial look, Background noise, Unwanted objects, Repetitive patterns, Artifacting, Abstract shapes, Out of focus"
 )
 
-model = gr.load("models/Purz/face-projection")
-
-def generate_image(text, seed, width, height, guidance_scale, num_inference_steps, negative_prompt):
+def generate_image(text, seed, width, height, guidance_scale, num_inference_steps, negative_prompt=default_negative_prompt):
     if seed is not None:
         random.seed(seed)
 
     if text in [example[0] for example in examples]:
         print(f"Using example: {text}")
 
+
     result_image = model(text, negative_prompt=negative_prompt)
     
-    print(f"Width: {width}, Height: {height}, Guidance Scale: {guidance_scale}, Inference Steps: {num_inference_steps}, Negative Prompt: {negative_prompt}")
+    print(f"Width: {width}, Height: {height}, Guidance Scale: {guidance_scale}, Inference Steps: {num_inference_steps}")
     
     return result_image
 
@@ -55,15 +57,6 @@ interface = gr.Interface(
         gr.Slider(label="Height", minimum=512, maximum=2048, step=64, value=1024),
         gr.Slider(label="Guidance Scale", minimum=0.1, maximum=20.0, step=0.1, value=3.0),
         gr.Slider(label="Number of inference steps", minimum=1, maximum=40, step=1, value=28),
-        gr.Dropdown(
-            label="Negative Prompt",
-            choices=[
-                "Default Negative Prompt",
-                "None",
-            ],
-            value="Default Negative Prompt",
-            description="Choose a negative prompt to apply to the image generation."
-        ),
     ],
     outputs=gr.Image(label="Generated Image"),
     examples=examples,
@@ -71,17 +64,4 @@ interface = gr.Interface(
     description="Sorry for the inconvenience. The model is currently running on the CPU, which might affect performance. We appreciate your understanding.",
 )
 
-def get_negative_prompt(negative_prompt_choice):
-    if negative_prompt_choice == "Default Negative Prompt":
-        return default_negative_prompt
-    else:
-        return ""
-
-
-def generate_image_with_negative_prompt(text, seed, width, height, guidance_scale, num_inference_steps, negative_prompt_choice):
-    negative_prompt = get_negative_prompt(negative_prompt_choice)
-    return generate_image(text, seed, width, height, guidance_scale, num_inference_steps, negative_prompt)
-
-interface.fn = generate_image_with_negative_prompt
-
-interface.launch()
+interface.launch()