refactored

app.py

@@ -1,7 +1,10 @@
 import os
 import sys
+import gradio as gr
 from utils import load_embeddings
-from ui import create_demo
+from embeddings import create_product_embeddings
+from similarity import compute_similarities
+from ui import categorize_products_from_text, categorize_products_from_file
 
 # Path to the embeddings file
 EMBEDDINGS_PATH = "ingredient_embeddings_voyageai.pkl"
@@ -12,18 +15,186 @@ if not os.path.exists(EMBEDDINGS_PATH):
     print(f"Please ensure the file exists at {os.path.abspath(EMBEDDINGS_PATH)}")
     sys.exit(1)
 
-# Load embeddings
+# Load embeddings globally
 try:
     embeddings_data = load_embeddings(EMBEDDINGS_PATH)
-    # Update the embeddings in the ui module
+    # Make embeddings available to the UI functions
     import ui
     ui.embeddings = embeddings_data
 except Exception as e:
     print(f"Error loading embeddings: {e}")
     sys.exit(1)
 
-# Create the Gradio interface
-demo = create_demo()
+# Basic CSS theme
+css = """
+.container {
+    max-width: 1200px; 
+    margin: auto; 
+    padding: 0;
+}
+footer {display: none !important;}
+.header {
+    background-color: #0d47a1; 
+    padding: 15px 20px; 
+    border-radius: 10px; 
+    color: white; 
+    margin-bottom: 20px;
+    display: flex;
+    align-items: center;
+}
+.header svg {
+    margin-right: 10px;
+    height: 30px;
+    width: 30px;
+}
+.header h1 {
+    margin: 0;
+    font-size: 24px;
+}
+.description {
+    margin-bottom: 20px; 
+    padding: 15px; 
+    background-color: #f5f5f5; 
+    border-radius: 5px;
+}
+"""
 
-# For Hugging Face Spaces, we need to use the app variable
-app = demo
+# Custom theme
+theme = gr.themes.Soft(
+    primary_hue="blue",
+    secondary_hue="indigo",
+    font=[gr.themes.GoogleFont("Inter"), "ui-sans-serif", "system-ui"]
+).set(
+    button_primary_background_fill="*primary_500",
+    button_primary_background_fill_hover="*primary_600",
+    button_secondary_background_fill="*neutral_200",
+    block_title_text_size="lg",
+    block_label_text_size="md"
+)
+
+# Create the Gradio interface directly in this file for Spaces
+with gr.Blocks(css=css, theme=theme) as app:
+    # Header with icon
+    gr.HTML("""
+    <div class="header">
+        <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="white">
+            <path d="M12 2L2 7l10 5 10-5-10-5zM2 17l10 5 10-5M2 12l10 5 10-5"></path>
+        </svg>
+        <h1>Product Categorization Tool</h1>
+    </div>
+    <div class="description">
+        This tool analyzes products and finds the most similar ingredients using AI embeddings.
+        Just enter product names or upload a file to get started.
+    </div>
+    """)
+    
+    with gr.Tabs():
+        with gr.TabItem("Text Input"):
+            with gr.Row():
+                with gr.Column(scale=2):
+                    example_products = [
+                        "Tomato Sauce\nApple Pie\nGreek Yogurt\nChocolate Chip Cookies",
+                        "Banana Bread\nOrange Juice\nGrilled Chicken\nCaesar Salad",
+                        "Vanilla Ice Cream\nPizza Dough\nStrawberry Jam\nGrilled Salmon"
+                    ]
+                    
+                    text_input = gr.Textbox(
+                        lines=10, 
+                        placeholder="Enter product names, one per line", 
+                        label="Product Names"
+                    )
+                    
+                    gr.Examples(
+                        examples=example_products,
+                        inputs=text_input,
+                        label="Example Product Sets"
+                    )
+                    
+                    with gr.Row():
+                        with gr.Column(scale=1):
+                            top_n = gr.Slider(
+                                minimum=1, 
+                                maximum=10, 
+                                value=5, 
+                                step=1, 
+                                label="Number of Top Categories"
+                            )
+                        with gr.Column(scale=1):
+                            confidence = gr.Slider(
+                                minimum=0.1, 
+                                maximum=0.9, 
+                                value=0.5, 
+                                step=0.05, 
+                                label="Confidence Threshold"
+                            )
+                    
+                    submit_button = gr.Button("Categorize Products", variant="primary")
+                
+                with gr.Column(scale=3):
+                    text_output = gr.HTML(label="Categorization Results", 
+                                         value="<div style='height: 450px; display: flex; justify-content: center; align-items: center; color: #666;'>Results will appear here</div>")
+            
+            submit_button.click(
+                fn=categorize_products_from_text,
+                inputs=[text_input, top_n, confidence],
+                outputs=text_output
+            )
+        
+        with gr.TabItem("File Upload"):
+            with gr.Row():
+                with gr.Column(scale=2):
+                    file_input = gr.File(
+                        label="Upload JSON or text file with products",
+                        file_types=[".json", ".txt"]
+                    )
+                    
+                    with gr.Accordion("Help", open=False):
+                        gr.Markdown("""
+                        - JSON files should contain either:
+                          - A list of objects with a 'name' field for each product
+                          - A simple array of product name strings
+                        - Text files should have one product name per line
+                        """)
+                    
+                    with gr.Row():
+                        with gr.Column(scale=1):
+                            file_top_n = gr.Slider(
+                                minimum=1, 
+                                maximum=10, 
+                                value=5, 
+                                step=1, 
+                                label="Number of Top Categories"
+                            )
+                        with gr.Column(scale=1):
+                            file_confidence = gr.Slider(
+                                minimum=0.1, 
+                                maximum=0.9, 
+                                value=0.5, 
+                                step=0.05, 
+                                label="Confidence Threshold"
+                            )
+                    
+                    file_button = gr.Button("Process File", variant="primary")
+                
+                with gr.Column(scale=3):
+                    file_output = gr.HTML(
+                        label="Categorization Results",
+                        value="<div style='height: 450px; display: flex; justify-content: center; align-items: center; color: #666;'>Upload a file to see results</div>"
+                    )
+            
+            file_button.click(
+                fn=categorize_products_from_file,
+                inputs=[file_input, file_top_n, file_confidence],
+                outputs=file_output
+            )
+    
+    # Footer
+    gr.HTML("""
+    <div style="margin-top: 20px; text-align: center; color: #666;">
+        Powered by Voyage AI embeddings • Built with Gradio
+    </div>
+    """)
+
+# For Hugging Face Spaces compatibility - do not remove
+if __name__ == "__main__":
+    app.launch()