new files

app.py

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+from gradio_client import Client
+import gradio as gr
+
+# Define paths to reference images for shapes
+shape_images = {
+    "Circle": "circle.png",
+    "Square": "square.png"
+    # "Triangle": "triangle.png"
+}
+
+# Define color palette as hex codes or color names
+color_palette = {
+    "Red": "#FF0000",
+    "Blue": "#0000FF",
+    "Green": "#008000",
+    "Yellow": "#FFFF00",
+    "Purple": "#800080",
+    "Orange": "#FFA500"
+}
+default_color = "Red"
+default_color_hex = color_palette[default_color]
+
+def generate_icon(shape, color, description):
+    client = Client("multimodalart/stable-cascade")
+    color_hex = color_palette.get(color, color_palette[default_color])
+    print(color_hex)
+    print(shape)
+    print(description)
+    # Construct prompt based on user description and selected characteristics
+    prompt = (f"Create a {description} icon in the shape of a {shape} with {color} color..")
+    
+    # Call the API with the constructed prompt
+    result = client.predict(
+        prompt=prompt,
+        negative_prompt="",
+        seed=0,
+        width=1024,
+        height=1024,
+        prior_num_inference_steps=20,
+        prior_guidance_scale=4,
+        decoder_num_inference_steps=10,
+        decoder_guidance_scale=0,
+        num_images_per_prompt=1,
+        api_name="/run"
+    )
+    
+    # Return the result image
+    return result
+
+def gradio_interface():
+    with gr.Blocks() as demo:
+        gr.Markdown("### AI Icon Generator")
+        custom_css = """
+        <style>
+        .custom-button {
+            width: 150px; /* Set the width of the button */
+            height: 40px; /* Set the height of the button */
+            font-size: 16px; /* Set the font size */
+            text-align: center; /* Center text */
+        }
+        .output-image {
+            width: 200px; /* Set the width of the output image */
+            height: 200px; /* Set the height of the output image */
+            object-fit: contain; /* Ensure the image scales proportionally */
+        }
+        </style>
+        """
+        gr.HTML(custom_css)
+        # Display reference images for shapes as selectable options
+        shape_options = gr.Radio(
+            choices=list(shape_images.keys()), 
+            label="Select Shape"
+        )
+
+        # Display shape images with fixed sizes using a layout
+        with gr.Row():
+            for shape, path in shape_images.items():
+                with gr.Column():
+                    gr.Image(
+                        value=path, 
+                        label=shape,
+                        type="pil",
+                        elem_classes="shape-image",
+                        height=100,
+                        width=100
+                    )  # Remove this line
+
+        # Dropdown for color palette
+        color_options = gr.Dropdown(
+            choices=list(color_palette.keys()), 
+            label="Select Color",
+            value=default_color
+        )
+        # color_hex = gr.Textbox(
+        #     label="Color Hex Code", 
+        #     value=color_palette[default_color],
+        #     visible=False
+        # )
+
+        # # Update color hex code when a color is selected
+        # def update_color_hex(color):
+        #     return color_palette[color]
+
+        # color_options.change(fn=update_color_hex, inputs=[color_options], outputs=[color_hex])
+
+        # Textbox for additional description
+        description_text = gr.Textbox(
+            label="Describe the Icon", 
+            placeholder="e.g., textile, steel, modern, futuristic"
+        )
+
+        with gr.Row():
+            submit_btn = gr.Button("Generate Icon", elem_classes="custom-button")
+            output_image = gr.Image(type="pil", elem_classes="output-image")
+
+        # Connect the function to the button
+        submit_btn.click(
+            generate_icon,
+            inputs=[shape_options, color_options, description_text],
+            outputs=[output_image]
+        )
+
+    demo.launch(share=True)
+
+# Run the Gradio interface
+if __name__ == "__main__":
+    gradio_interface()

requirements.txt

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+aiofiles==23.2.1
+annotated-types==0.7.0
+anyio==4.4.0
+certifi==2024.8.30
+charset-normalizer==3.3.2
+click==8.1.7
+contourpy==1.3.0
+cycler==0.12.1
+fastapi==0.112.4
+ffmpy==0.4.0
+filelock==3.15.4
+fonttools==4.53.1
+fsspec==2024.9.0
+gradio==4.43.0
+gradio_client==1.3.0
+h11==0.14.0
+httpcore==1.0.5
+httpx==0.27.2
+huggingface-hub==0.24.6
+idna==3.8
+importlib_resources==6.4.4
+Jinja2==3.1.4
+kiwisolver==1.4.7
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+matplotlib==3.9.2
+mdurl==0.1.2
+numpy==2.1.1
+orjson==3.10.7
+packaging==24.1
+pandas==2.2.2
+pillow==10.4.0
+pydantic==2.9.0
+pydantic_core==2.23.2
+pydub==0.25.1
+Pygments==2.18.0
+pyparsing==3.1.4
+python-dateutil==2.9.0.post0
+python-multipart==0.0.9
+pytz==2024.1
+PyYAML==6.0.2
+requests==2.32.3
+rich==13.8.0
+ruff==0.6.4
+semantic-version==2.10.0
+shellingham==1.5.4
+six==1.16.0
+sniffio==1.3.1
+starlette==0.38.4
+tomlkit==0.12.0
+tqdm==4.66.5
+typer==0.12.5
+typing_extensions==4.12.2
+tzdata==2024.1
+urllib3==2.2.2
+uvicorn==0.30.6
+websockets==12.0