migrating to new columns

LLM_openai.py

@@ -12,10 +12,11 @@ def expense_classifier(expense):
             "content": [
         {
           "type": "text",
-          "text": """You are a helpful personal finance assistant. 
-          The user will input some expense concept and you will classify it in a broader category from the following:
-            [alcohol, food, restaurant, clothing, entertainment, transport, sports, wellbeing, personal_development,others] 
-            Provide only the category as an answer
+          "text": """Eres un asistente contable muy eficiente.
+          El usuario ingresará un gasto y tú lo clasificaráas en una categoria general de las siguientes:
+          [insumo, gasto fijo, sueldo].
+          Por favor sólo la categoria como respuesta.
+          
             """
         }
       ]

app.py

@@ -20,6 +20,7 @@ spreadsheet = gc.open("Snackers_spreadsheet").sheet1
 def update_spend_from_image(img):
     ##This processes the image
     extracted_dictionay_from_image=process_image(img)
+
     total_from_receipt=extracted_dictionay_from_image['total']
     concept_from_receipt=extracted_dictionay_from_image['purchase_summary']
     shop_type=extracted_dictionay_from_image['store_type']
@@ -29,18 +30,18 @@ def update_spend_from_image(img):
     concept_and_shop=concept_from_receipt+" from "+shop_type+f" ({shop_name})"
     
     ##The function update_spend in the line below only takes a string and float
-    category, day_month, todays_amount, current_week_amount , fig, fig2, fig3=update_spend(concept_and_shop, total_from_receipt, receipt_items)
+    category, day_month, todays_amount, current_week_amount , fig, fig2, fig3=update_spend(shop_name, total_from_receipt, concept_and_shop,receipt_items)
 
     return category, day_month, todays_amount, current_week_amount , fig, fig2, fig3
 
 
 
-def update_spend(concept, amount, items_from_receipt=None):
+def update_spend(concept, amount, description ,items_from_receipt=None):
     category=expense_classifier(concept)
     today = datetime.date.today()
     
     # Append a new row
-    spreadsheet.append_row([str(today), concept,float(amount),category, items_from_receipt ])
+    spreadsheet.append_row([str(today), concept,float(amount), description,category, items_from_receipt ])
     
     day_month, todays_amount, current_week_amount , fig, fig2, fig3=dataframe_process(spreadsheet)
     return category, day_month, todays_amount, current_week_amount , fig, fig2, fig3
@@ -63,9 +64,11 @@ with gr.Blocks() as demo:
     
     with gr.Tab("Entrada manual"):
         with gr.Row():
-            concept = gr.Textbox(label="Concepto")
+            concept = gr.Textbox(label="Cliente o Proveedor")
         with gr.Row():
             amount= gr.Textbox(label="Monto")
+        with gr.Row():
+            description= gr.Textbox(label="descripcion")
         btn_manual = gr.Button("Ingresar gasto")
 
     with gr.Tab("Cargar recibo"):
@@ -91,10 +94,12 @@ with gr.Blocks() as demo:
         category_plot=gr.Plot()
 
 
-    btn_manual.click(fn=update_spend, inputs=[concept, amount], outputs=[expense_class,ui_date, expenses_today,expenses_this_week,
+    btn_manual.click(fn=update_spend, inputs=[concept, amount, description ,], outputs=[expense_class,ui_date, expenses_today,expenses_this_week,
                                                                   daily_plot,week_plot,category_plot])
+
     btn_image.click(fn=update_spend_from_image, inputs=[input_image], outputs=[expense_class,ui_date, expenses_today,expenses_this_week,
                                                                   daily_plot,week_plot,category_plot])
+
     btn_show.click(fn=show_plots, inputs=[], outputs=[expense_class,ui_date, expenses_today,expenses_this_week,
                                                                   daily_plot,week_plot,category_plot])
 

dataframe_processing.py

@@ -5,26 +5,26 @@ from utils import create_plot, create_barplot
 def dataframe_process(sheet):
     # Create dataframe
     df = pd.DataFrame(sheet.get_all_records())
-    df['date'] = pd.to_datetime(df['date'])
-    df['week'] = df['date'].dt.to_period('W')
+    df['fecha'] = pd.to_datetime(df['fecha'])
+    df['week'] = df['fecha'].dt.to_period('W')
 
     #Per day
-    daily_total=df[['concept','amount','category','date']].groupby('date').sum().reset_index()
-    daily_total['month_day'] = daily_total['date'].dt.strftime('%m-%d')
+    daily_total=df[['cliente_proveedor','amount','category','fecha']].groupby('fecha').sum().reset_index()
+    daily_total['month_day'] = daily_total['fecha'].dt.strftime('%m-%d')
 
     
 
     fig = create_plot(daily_total['month_day'],daily_total['amount'])
 
-    daily_total=daily_total.sort_values(by='date', ascending=False)
-    daily_total=daily_total[['date', 'amount']]
+    daily_total=daily_total.sort_values(by='fecha', ascending=False)
+    daily_total=daily_total[['fecha', 'amount']]
     todays_amount=daily_total.iloc[0]['amount']
-    todays_date=daily_total.iloc[0]['date']
+    todays_date=daily_total.iloc[0]['fecha']
     day_month = todays_date.strftime('%m-%d-%Y')
 
     #Per week
     # Group by 'week' and sum the values
-    weekly_df = df[['concept','amount','category','week']].groupby('week').sum().reset_index()
+    weekly_df = df[['cliente_proveedor','amount','category','week']].groupby('week').sum().reset_index()
     weekly_df=weekly_df.sort_values(by='week', ascending=True)
     # weekly_df.index=weekly_df.index.strftime('%m-%d')
     current_week_amount="{:.2f}".format(weekly_df.iloc[-1]['amount'])
@@ -35,7 +35,7 @@ def dataframe_process(sheet):
 
 
     #Per category
-    expenses_per_category=df[['concept','amount','category']].groupby('category').sum().reset_index()
+    expenses_per_category=df[['cliente_proveedor','amount','category']].groupby('category').sum().reset_index()
     expenses_per_category=expenses_per_category.sort_values(by='amount', ascending=False)
     fig3 = create_barplot(expenses_per_category['category'],expenses_per_category['amount'],"categoria","monto","gasto por categoria")