Update app.py

app.py

@@ -196,11 +196,28 @@ def interact_with_salesforce(mode, entry_type, quantity, attributes):
     except Exception as e:
         return f"❌ Error interacting with Salesforce: {str(e)}"
 
+
+
+# Function to handle edited attributes and export to Salesforce
+def export_to_salesforce(mode, entry_type, quantity, edited_df):
+    try:
+        # Convert edited DataFrame back to dictionary
+        edited_attributes = dict(zip(edited_df["Attribute"], edited_df["Value"]))
+        
+        # Export to Salesforce
+        message = interact_with_salesforce(mode, entry_type, quantity, edited_attributes)
+        return message
+    except Exception as e:
+        return f"❌ Error exporting to Salesforce: {str(e)}"
+
+# ... [unchanged imports and setup code above]
+
 # Function to process image, extract attributes, and allow editing
 def process_image(image, mode, entry_type, quantity):
     extracted_text = extract_text(image)
     if not extracted_text:
-        return "No text detected in the image.", None, None
+        # Return defaults matching: Text, Dataframe, Text
+        return "No text detected in the image.", pd.DataFrame(columns=["Attribute", "Value"]), ""
 
     product_name = match_product_name(extracted_text)
     attributes = extract_attributes(extracted_text)
@@ -214,19 +231,7 @@ def process_image(image, mode, entry_type, quantity):
 
     # Convert attributes to DataFrame for editing
     df = pd.DataFrame(list(attributes.items()), columns=["Attribute", "Value"])
-    return f"Extracted Text:\n{extracted_text}", df, None
-
-# Function to handle edited attributes and export to Salesforce
-def export_to_salesforce(mode, entry_type, quantity, edited_df):
-    try:
-        # Convert edited DataFrame back to dictionary
-        edited_attributes = dict(zip(edited_df["Attribute"], edited_df["Value"]))
-        
-        # Export to Salesforce
-        message = interact_with_salesforce(mode, entry_type, quantity, edited_attributes)
-        return message
-    except Exception as e:
-        return f"❌ Error exporting to Salesforce: {str(e)}"
+    return f"Extracted Text:\n{extracted_text}", df, ""
 
 # Function to pull structured data from Salesforce and display as a table
 def pull_data_from_salesforce(data_type):
@@ -236,21 +241,23 @@ def pull_data_from_salesforce(data_type):
             password=SALESFORCE_PASSWORD,
             security_token=SALESFORCE_SECURITY_TOKEN
         )
-        
+
         if data_type == "Inventory":
             query = "SELECT Productname__c,Model__c, H_p__c, Stage__c, Current_Stocks__c, soldstock__c FROM Inventory_Management__c LIMIT 100"
         else:
             query = "SELECT Productname__c, Model__c, H_p__c, Stage__c, Current_Stock__c, soldstock__c FROM Un_Billable__c LIMIT 100"
-        
+
         response = sf.query_all(query)
         records = response.get("records", [])
-        
+
         if not records:
-            return "No data found in Salesforce.", None, None, None
-        
+            # Return defaults: Dataframe, FilePath, Image
+            empty_df = pd.DataFrame(columns=["Product Name", "Model", "H.P", "Stage", "Current Stocks", "Sold Stock"])
+            return empty_df, "", None
+
         df = pd.DataFrame(records)
         df = df.drop(columns=['attributes'], errors='ignore')
-        
+
         # Rename columns for better readability
         df.rename(columns={
             "Productname__c": "Product Name",
@@ -261,9 +268,33 @@ def pull_data_from_salesforce(data_type):
             "Current_Stock__c": "Current Stocks",
             "soldstock__c": "Sold Stock"
         }, inplace=True)
-        
+
         excel_path = "salesforce_data.xlsx"
         df.to_excel(excel_path, index=False)
+
+        # Generate vertical bar graph using Matplotlib
+        fig, ax = plt.subplots(figsize=(12, 8))
+        df.plot(kind='bar', x="Product Name", y="Current Stocks", ax=ax, legend=False)
+        ax.set_title("Stock Distribution by Product Name")
+        ax.set_xlabel("Product Name")
+        ax.set_ylabel("Current Stocks")
+        plt.xticks(rotation=45, ha="right", fontsize=10)
+        plt.tight_layout()
+        buffer = BytesIO()
+        plt.savefig(buffer, format="png")
+        buffer.seek(0)
+        img = Image.open(buffer)
+
+        return df, excel_path, img
+
+    except Exception as e:
+        # Return safe defaults if something breaks
+        empty_df = pd.DataFrame(columns=["Product Name", "Model", "H.P", "Stage", "Current Stocks", "Sold Stock"])
+        return empty_df, "", None
+
+# Rest of your code remains unchanged below
+# (export_to_salesforce, app(), __main__)
+
         
         # Generate interactive vertical bar graph using Matplotlib
         fig, ax = plt.subplots(figsize=(12, 8))