Create app.py

app.py

@@ -0,0 +1,45 @@
+# App v3.0
+import pandas as pd
+import pickle
+import gradio as gr
+
+with open(r'database\vect_index.pickle', 'rb') as file:
+    vect_index = pickle.load(file)
+with open(r'database\vect_values.pickle', 'rb') as file:
+    vect_values = pickle.load(file)
+    
+df = pd.read_excel('database\perfume_database_cleaned.xlsx')
+brand_options = list(df['brand'].unique())
+perfume_options = list(df['perfume'].unique())
+
+def perfume_change(brand):
+    names = list(df.query(f"brand=='{brand}'")['perfume'])
+    return gr.update(choices=names, value=None)
+
+def filter_by_perfume(selected_brand, selected_perfume):
+    perfume_index = df.query(f"brand=='{selected_brand}' & perfume=='{selected_perfume}'").index[0]
+    df_filter = df.iloc[vect_index[perfume_index], :].reset_index(drop=True)
+    df_filter['similarity'] = vect_values[perfume_index]
+    df_filter['similarity'] = df_filter['similarity'].map("{:.2%}".format)
+    df_filter['notes'] = df_filter['notes'].str.split(',').apply(sorted, 1).str.join(',').str.strip(',')
+    df_filter = df_filter[['brand', 'perfume', 'similarity', 'notes']]
+    return df_filter
+
+with gr.Blocks(theme='freddyaboulton/dracula_revamped') as demo:
+    gr.Markdown(
+    """
+    # Perfume Recommendation
+    Select brand and perfume below to find top 5 most similar perfumes based on notes
+    """)
+    
+    with gr.Row():
+        brand_dropdown = gr.Dropdown(choices=brand_options, value='Hugo Boss', label="Brand")
+        perfume_dropdown = gr.Dropdown(choices=perfume_options, value='Boss Soul', label="Perfume Name")
+        brand_dropdown.change(fn=perfume_change, inputs=[brand_dropdown], outputs=[perfume_dropdown])
+        btn = gr.Button(value="Search", scale=.1)
+        
+    with gr.Row():
+        output_df = gr.outputs.Dataframe(type='pandas')
+        btn.click(filter_by_perfume, inputs=[brand_dropdown, perfume_dropdown], outputs=[output_df])
+        
+demo.launch()