Upload app.py

app.py

@@ -1,64 +1,16 @@
 import pandas as pd
 from sklearn.metrics.pairwise import cosine_similarity
 import gradio as gr
-
 def find_similar_items(stock_code):
-    try:
-        # Read data source Excel file.
-        df1 = pd.read_excel('IBCF_Online_Retail.xlsx')
-    except FileNotFoundError:
-        return "Error: Excel file not found."
-
-    # Check dataframe information.
-    df1a = df1.dropna(subset=['CustomerID'])
-
-    # Create CustomerID vs Item (Purchased Items, by StockCode) matrix by pivot table function.
-    CustomerID_Item_matrix = df1a.pivot_table(
-        index='CustomerID', 
-        columns='StockCode', 
-        values='Quantity',
-        aggfunc='sum'
-    )
-
-    # Update illustration of the matrix, 1 to represent customer have purchased item, 0 to represent customer haven't purchased.
-    CustomerID_Item_matrix = CustomerID_Item_matrix.applymap(lambda x: 1 if x > 0 else 0)
-
-    # Create Item to Item similarity matrix.
-    item_item_similarity_matrix = pd.DataFrame(
-        cosine_similarity(CustomerID_Item_matrix.T)
-    )
-
-    # Update index to corresponding Item Code (StockCode).
-    item_item_similarity_matrix.columns = CustomerID_Item_matrix.T.index
-    item_item_similarity_matrix['StockCode'] = CustomerID_Item_matrix.T.index
-    item_item_similarity_matrix = item_item_similarity_matrix.set_index('StockCode')
-
-    try:
-        # Convert stock_code to integer
-        stock_code = int(stock_code)
-    except ValueError:
-        return "Error: Invalid stock code."
-
-    try:
-        # Find the top 5 most similar items
-        top_5_similar_items = list(
-            item_item_similarity_matrix\
-                .loc[stock_code]\
-                .sort_values(ascending=False)\
-                .iloc[:5]\
-            .index
-        )
-    except KeyError:
-        return "Stock code not found.Please enter a valid stock code"
-
-    # Return the list of similar items of the given StockCode with item Description.
-    results_df = df1a.loc[df1a['StockCode'].isin(top_5_similar_items), 'Description'].drop_duplicates().to_frame().reset_index(drop=True)
-    results_list = results_df.to_string(header=False, index=False).split('\n')
-    results_list.insert(1, '-'*50)  # Insert dotted line after the first item
-    return "\n".join(results_list)
-
-# Set up the interface
-stock_code_input = gr.inputs.Textbox(label="Enter Stock Code:")
-output_table = gr.outputs.Textbox(label="Recommended Items")
-
-gr.Interface(fn=find_similar_items, inputs=stock_code_input, outputs=output_table,theme=gr.themes.Default(primary_hue="slate")).launch()
+        H='CustomerID';F=False;D=stock_code;C='StockCode'
+        try:I=pd.read_excel('IBCF_Online_Retail.xlsx')
+        except FileNotFoundError:return'Error: Excel file not found.'
+        E=I.dropna(subset=[H]);A=E.pivot_table(index=H,columns=C,values='Quantity',aggfunc='sum');A=A.applymap(lambda x:1 if x>0 else 0);B=pd.DataFrame(cosine_similarity(A.T));B.columns=A.T.index;B[C]=A.T.index;B=B.set_index(C)
+        try:D=int(D)
+        except ValueError:return'Error: Invalid stock code.'
+        try:J=list(B.loc[D].sort_values(ascending=F).iloc[:5].index)
+        except KeyError:return'Stock code not found.Please enter a valid stock code'
+        K=E.loc[E[C].isin(J),'Description'].drop_duplicates().to_frame().reset_index(drop=True);G=K.to_string(header=F,index=F).split('\n');G.insert(1,'-'*50);return '\n'.join(G)
+stock_code_input=gr.inputs.Textbox(label='Enter Stock Code:')
+output_table=gr.outputs.Textbox(label='Recommended Items')
+gr.Interface(fn=find_similar_items,inputs=stock_code_input,outputs=output_table,theme=gr.themes.Default(primary_hue='slate')).launch()