Update app.py

app.py

@@ -1,13 +1,7 @@
 import gradio as gr
 import torch
-from diffusers import StableDiffusionPipeline
 from groq import Groq
 
-# Initialize the Stable Diffusion model
-model_id = "stabilityai/stable-diffusion-2"  # Example model
-sd_pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
-sd_pipe.to("cuda")
-
 # Initialize the Groq client with your API key
 client = Groq(api_key="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")
 
@@ -46,15 +40,11 @@ def generate_movie_content(theme):
     ])
     script = script_response["choices"][0]["message"]["content"]
 
-    # Generate image
-    image_prompt = f"A cinematic illustration of the theme: {theme}"
-    image = sd_pipe(image_prompt).images[0]
-
-    return characters, storyline, script, image
+    return characters, storyline, script
 
 def main_interface(theme):
-    characters, storyline, script, image = generate_movie_content(theme)
-    return f"Main Characters: {characters}\n\nStoryline: {storyline}\n\nScript: {script}", image
+    characters, storyline, script = generate_movie_content(theme)
+    return f"Main Characters: {characters}\n\nStoryline: {storyline}\n\nScript: {script}"
 
 # Gradio Interface
 title = "Movie Generator"
@@ -66,12 +56,11 @@ demo = gr.Interface(
         gr.Textbox(label="Theme", placeholder="Enter the movie theme"),
     ],
     outputs=[
-        gr.Textbox(label="Generated Content"),
-        gr.Image(label="Generated Image"),
+        gr.Textbox(label="Generated Content")
     ],
     title=title,
     description=description,
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()