Create app.py

app.py

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+import gradio as gr
+import time
+import random # To simulate variations like seed
+
+# --- Placeholder Function (Will Contain Your AI Logic Later) ---
+def process_prompt_and_generate(user_prompt, image_resolution, guidance_scale, seed, animation_frames, animation_style):
+    """
+    This function simulates the AI pipeline. It accepts more parameters now.
+    It yields updates for the status and logs.
+    """
+    logs = []
+    status = "Starting processing..."
+    yield user_prompt, "", None, None, "", "", "", "", "", "\n".join(logs), status # Initial state
+
+    if not user_prompt:
+        logs.append("Error: No prompt provided.")
+        status = "Error: No prompt provided."
+        yield user_prompt, "", None, None, "", "", "", "", "", "\n".join(logs), status
+        return
+
+    # --- Simulate Prompt Enhancement ---
+    status = "Enhancing prompt..."
+    logs.append(f"User Prompt: '{user_prompt}'")
+    logs.append(f"Parameters: Resolution={image_resolution}, Guidance Scale={guidance_scale}, Seed={seed}, Frames={animation_frames}, Style={animation_style}")
+    yield user_prompt, "", None, None, "", "", "", "", "", "\n".join(logs), status
+    time.sleep(1.5) # Simulate time
+
+    enhanced_prompt = f"Stunning, highly detailed, {animation_style.lower()} animation frame of {user_prompt}, cinematic lighting, high focus, 8k, trending on Artstation. Seed: {seed}" # Dummy enhancement
+    logs.append(f"Enhanced Prompt: '{enhanced_prompt}'")
+    yield user_prompt, enhanced_prompt, None, None, "", "", "", "", "", "\n".join(logs), status
+    time.sleep(1) # Simulate time
+
+    # --- Simulate Image Generation ---
+    status = "Generating image..."
+    logs.append(f"Generating initial image ({image_resolution}px)...")
+    yield user_prompt, enhanced_prompt, None, None, "", "", "", "", "", "\n".join(logs), status
+    time.sleep(3) # Simulate time
+
+    # In a real app, this would call a model and return an image path/object
+    dummy_image_path = "https://gradio-app.github.io/assets/tower.jpg" # Example image
+    logs.append(f"Image generated successfully.")
+    yield user_prompt, enhanced_prompt, dummy_image_path, None, "", "", "", "", "", "\n".join(logs), status
+    time.sleep(1)
+
+    # --- Simulate Animation ---
+    status = "Generating animation..."
+    logs.append(f"Generating animation ({animation_frames} frames, style: {animation_style})...")
+    yield user_prompt, enhanced_prompt, dummy_image_path, None, "", "", "", "", "", "\n".join(logs), status
+    time.sleep(4) # Simulate time
+
+    # In a real app, this would call an animation model and return a video path/object
+    dummy_video_path = "https://gradio-app.github.io/assets/video-demo.mp4" # Example video
+    logs.append(f"Animation generated successfully.")
+    yield user_prompt, enhanced_prompt, dummy_image_path, dummy_video_path, "", "", "", "", "", "\n".join(logs), status
+    time.sleep(1)
+
+    # --- Finalizing Outputs ---
+    status = "Process complete!"
+    logs.append("All steps finished.")
+
+    # Prepare metadata string for display
+    metadata = f"Resolution: {image_resolution}px\nGuidance Scale: {guidance_scale}\nSeed: {seed}\nFrames: {animation_frames}\nStyle: {animation_style}"
+
+
+    # The yield statements above sent partial updates. The final return sends the complete data.
+    # However, with generator functions (`yield`), the final result is implicitly what was yielded last.
+    # To ensure all outputs are correctly populated at the end, it's often better to have
+    # the function return the final state once processing is completely done.
+    # Let's refactor slightly to use a single return at the end for simplicity with Gradio's output mapping.
+    # (Alternative: Use gr.Progress and yield intermediary results explicitly)
+
+    # Reset logs for the final return state (or append "Complete")
+    logs.append("Final output ready.")
+
+    return (user_prompt, enhanced_prompt, dummy_image_path, dummy_video_path,
+            str(image_resolution), str(guidance_scale), str(seed), str(animation_frames), animation_style,
+            "\n".join(logs), status)
+
+
+# --- Gradio UI Definition ---
+
+# Choose a more modern theme
+theme = gr.themes.Monochrome().set(
+    # Customize colors slightly for a softer look
+    # You can inspect theme objects and their attributes
+    # button_primary_background_fill="linear-gradient(to right, #6a11cb 0%, #2575fc 100%)", # Example gradient
+    # button_primary_color="white",
+    # button_secondary_background_fill="gray",
+    # spacing_size_lg="2rem" # Example spacing adjustment
+)
+
+
+with gr.Blocks(theme=theme, title="AI Creative Studio") as demo:
+
+    # --- Header Section ---
+    with gr.Row(variant="panel"): # Use a panel variant for distinct header background
+        with gr.Column(scale=1, min_width=100):
+             # Placeholder for a logo or icon
+            gr.Image(value="https://gradio-app.github.io/assets/logo.svg",
+                     label="Studio Logo",
+                     show_label=False, # Hide the label below the image
+                     height=80,
+                     width=80,
+                     container=False) # Prevent adding extra padding/margin around the image
+
+        with gr.Column(scale=4):
+            gr.Markdown(
+                """
+                # 🎨 Multi-Step AI Creative Pipeline 🚀
+                Unleash your imagination! Input a prompt, and our AI orchestrates a sequence:
+                Prompt Enhancement → Image Generation → Animation.
+                """
+            )
+    gr.Markdown("---") # Separator
+
+    # --- Main Content Area (Input & Output side-by-side initially) ---
+    with gr.Row():
+
+        # --- Input & Controls Column ---
+        with gr.Column(scale=1):
+            gr.Markdown("## ✍️ Your Creative Input")
+            prompt_input = gr.TextArea(
+                label="Enter your prompt here:",
+                placeholder="e.g., A majestic dragon flying over snow-capped mountains at sunset",
+                lines=5,
+                interactive=True
+            )
+            gr.Examples(
+                ["A cyberpunk street scene with neon lights", "A cozy cabin in a snowy forest, digital painting", "An astronaut riding a horse on the moon, surrealism"],
+                inputs=prompt_input
+            )
+
+            # Advanced Options (Collapsed)
+            with gr.Accordion("🛠️ Advanced Settings", open=False):
+                gr.Markdown("Configure specific parameters for generation.")
+
+                with gr.Row():
+                    image_resolution = gr.Slider(label="Image Resolution (px)", minimum=256, maximum=1024, value=512, step=128, interactive=True)
+                    guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=20.0, value=7.0, step=0.1, interactive=True)
+
+                with gr.Row():
+                    seed = gr.Number(label="Seed (-1 for random)", value=-1, precision=0, interactive=True)
+                    animation_frames = gr.Slider(label="Animation Frames", minimum=10, maximum=100, value=40, step=5, interactive=True)
+
+                animation_style = gr.Radio(
+                    label="Animation Style",
+                    choices=["Zoom In", "Pan Left", "Rotate", "Swirl"],
+                    value="Zoom In",
+                    interactive=True
+                )
+                # Add a button to randomize seed easily
+                randomize_seed_button = gr.Button("🎲 Randomize Seed")
+
+            # Action Button
+            generate_button = gr.Button("✨ Generate Pipeline Results ✨", variant="primary")
+
+            # Live Status Indicator
+            status_display = gr.Textbox(label="Status", value="Ready", interactive=False, show_copy_button=False)
+
+
+        # --- Output & Results Column ---
+        with gr.Column(scale=2): # Make output column wider
+            gr.Markdown("## ✅ Generation Results")
+
+            # Row for prompts
+            with gr.Row():
+                original_prompt_output = gr.Textbox(label="Original Prompt Used", interactive=False, lines=3, scale=1, show_copy_button=True)
+                enhanced_prompt_output = gr.Textbox(label="Enhanced Prompt (AI)", interactive=False, lines=3, scale=1, show_copy_button=True)
+
+            # Row for media
+            with gr.Row():
+                generated_image_output = gr.Image(label="Generated Image", interactive=False, height=450, show_share_button=True)
+                generated_animation_output = gr.Video(label="Generated Animation", interactive=False, height=450, show_share_button=True)
+
+
+            # Display Parameters Used (Collapsed or in a smaller section)
+            with gr.Accordion("🔬 Parameters Used", open=False): # Collapsible section for details
+                parameters_used_output = gr.Textbox(
+                    label="Generation Parameters",
+                    interactive=False,
+                    lines=5,
+                    show_copy_button=True
+                )
+                # Dummy output components to catch the individual parameters
+                # We will combine them in the process_prompt_and_generate function for the Textbox above
+                res_out = gr.Textbox(visible=False)
+                gs_out = gr.Textbox(visible=False)
+                seed_out = gr.Textbox(visible=False)
+                frames_out = gr.Textbox(visible=False)
+                style_out = gr.Textbox(visible=False)
+
+
+            # Download Buttons (Placeholder)
+            gr.Markdown("### Download Results")
+            with gr.Row():
+                 # These buttons are just placeholders for now.
+                 # Real download logic needs separate functions.
+                 download_image_button = gr.Button("⬇️ Download Image", interactive=False) # Make interactive=True when download logic is added
+                 download_video_button = gr.Button("⬇️ Download Video", interactive=False) # Make interactive=True when download logic is added
+
+    gr.Markdown("---") # Separator
+
+    # --- Logs and Debug Information ---
+    with gr.Accordion("⚙️ Processing Logs & Debug Info", open=False):
+        logs_output = gr.Textbox(
+            label="Detailed Logs",
+            interactive=False,
+            lines=15, # More lines for detailed logs
+            max_lines=30,
+            show_copy_button=True,
+            # Add some visual cues for logs
+            container=True # Gives it a distinct container style
+        )
+
+    # --- Define Interactions ---
+
+    # Button click triggers the main processing function
+    # The outputs list maps the function's return values to UI components
+    generate_button.click(
+        fn=process_prompt_and_generate,
+        inputs=[
+            prompt_input,
+            image_resolution,
+            guidance_scale,
+            seed,
+            animation_frames,
+            animation_style
+        ],
+        outputs=[
+            original_prompt_output,
+            enhanced_prompt_output,
+            generated_image_output,
+            generated_animation_output,
+            res_out, # Catch individual params to reconstruct metadata
+            gs_out,
+            seed_out,
+            frames_out,
+            style_out,
+            logs_output, # Logs are updated incrementally/finally
+            status_display # Status is updated incrementally/finally
+        ]
+    )
+
+    # Update the combined parameters display after the main function runs
+    # This uses the individual output components as inputs for a new function
+    def update_parameters_display(res, gs, seed, frames, style):
+         if not res: # Check if results exist
+             return ""
+         metadata = f"Resolution: {res}px\nGuidance Scale: {gs}\nSeed: {seed}\nFrames: {frames}\nStyle: {style}"
+         return metadata
+
+    # Add a state component to hold the output parameters temporarily
+    # Or simply chain the update after the main click, using the same outputs
+    # Let's chain it for simplicity here. The order matters.
+    # This click event fires AFTER the main click event completes and updates its outputs.
+    # It takes the updated outputs as its inputs.
+    generate_button.click(
+        fn=update_parameters_display,
+        inputs=[res_out, gs_out, seed_out, frames_out, style_out],
+        outputs=[parameters_used_output]
+    )
+
+    # Randomize Seed Button Interaction
+    def randomize():
+        return random.randint(1, 1000000) # Generate a random seed
+
+    randomize_seed_button.click(
+        fn=randomize,
+        inputs=[],
+        outputs=[seed] # Update the seed number input field
+    )
+
+
+# --- Launch the App ---
+if __name__ == "__main__":
+    print("Gradio AI Creative Studio is starting...")
+    demo.launch()
+    print("App launched!")