Update app.py

app.py

@@ -6,66 +6,9 @@ import tempfile
 import os
 import uuid
 import gradio as gr
+import Methods
 
 
-# function to plot and save an AgentImage
-def plot_and_save_agent_image(agent_image, save_path=None):
-    # Convert AgentImage to a raw PIL Image
-    pil_image = agent_image.to_raw()
-
-    # Plot the image using PIL's show method
-    pil_image.show()
-
-    # If save_path is provided, save the image
-    if save_path:
-        pil_image.save(save_path)
-        print(f"Image saved to {save_path}")
-    else:
-        print("No save path provided. Image not saved.")
-
-
-def generate_prompts_for_object(object_name):
-    prompts = {
-        "past": f"Show an old version of a {object_name} from its early days.",
-        "present": f"Show a {object_name} with from present with current features/design/technology.",
-        "future": f"Show a futuristic version of a {object_name}, by predicting advanced features and futuristic design."
-    }
-    return prompts
-
-
-# Function to generate the car industry history
-def generate_object_history(object_name):
-    images = []
-    
-    # Get prompts for the object
-    prompts = generate_prompts_for_object(object_name)
-    
-    # Generate sequential images and display them
-    for time_period, frame in prompts.items():
-        print(f"Generating {time_period} frame: {frame}")
-        result = agent.run(frame)  # The tool generates the image
-        
-        # Append the image to the list for GIF creation
-        images.append(result.to_raw())  # Ensure we're using raw image for GIF
-
-        # Save each image with the appropriate name (past, present, future)
-        image_filename = f"{object_name}_{time_period}.png"
-        plot_and_save_agent_image(result, save_path=image_filename)
-        
-        
-    # Create GIF from images
-    gif_path = f"{object_name}_evolution.gif"
-    images[0].save(
-        gif_path, 
-        save_all=True, 
-        append_images=images[1:], 
-        duration=1000,  # Duration in milliseconds for each frame
-        loop=0          # Infinite loop
-    )
-    
-    # Return images and GIF path
-    return images, gif_path
-
 # Import text-to-image tool from Hub 
 # m-ric/text-to-image model generates images based on textual descriptions.
 image_generation_tool = load_tool("m-ric/text-to-image", cache=False) #cache=False ensures it fetches the latest tool updates directly from the Hub.