Update app.py

app.py

@@ -1,13 +1,17 @@
 pip install diffusers transformers accelerate
 pip install gradio
+
 import torch
 from diffusers import StableDiffusionPipeline
-import matplotlib.pyplot as plt
 import gradio as gr
-# List of NSFW prompt keywords
-NSFW_KEYWORDS = ["nude", "naked", "sex", "porn", "erotic", "nsfw", "boobs", "breasts", "genital", "vagina", "penis"]
 
-# Load models dictionary
+# NSFW keywords filter list
+NSFW_KEYWORDS = [
+    "nude", "naked", "sex", "porn", "erotic", "nsfw",
+    "boobs", "breasts", "genital", "vagina", "penis"
+]
+
+# Available models
 MODELS = {
     "Stable Diffusion v1.5": "runwayml/stable-diffusion-v1-5",
     "Dreamlike Diffusion": "dreamlike-art/dreamlike-diffusion-1.0",
@@ -15,6 +19,15 @@ MODELS = {
     "Waifu Diffusion (Anime Style)": "hakurei/waifu-diffusion"
 }
 
+# Example prompts
+example_prompts = [
+    "A futuristic city at sunset in cyberpunk style",
+    "A cute dog astronaut floating in space",
+    "A dreamy landscape with flying islands",
+    "An ancient temple in a deep jungle",
+    
+]
+
 loaded_pipelines = {}
 
 def get_pipeline(model_name):
@@ -32,7 +45,6 @@ def generate_image(prompt, model_name):
     pipe = get_pipeline(model_name)
     result = pipe(prompt)
     
-    # Check output safety
     if result.nsfw_content_detected and any(result.nsfw_content_detected):
         raise gr.Error("❌ Sorry, the generated image was flagged as NSFW. Try a different prompt.")
     
@@ -41,10 +53,12 @@ def generate_image(prompt, model_name):
 def generate_and_return_image(prompt, model_name):
     if any(word in prompt.lower() for word in NSFW_KEYWORDS):
         raise gr.Error("❌ Sorry, I can't generate images with NSFW content.")
-
+    
     image = generate_image(prompt, model_name)
     image.save("generated.png")
     return image
+
+# Gradio Interface
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="sky", secondary_hue="blue")) as demo:
     gr.Markdown("## 🎨 Text-to-Image Generator")
 
@@ -67,4 +81,4 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="sky", secondary_hue="blue")) as
     generate_button.click(fn=generate_and_return_image, inputs=[prompt, model_choice], outputs=image_output)
     download_button.click(fn=lambda: "generated.png", outputs=gr.File())
 
-demo.launch()
+demo.launch()