Update app.py

app.py

@@ -145,11 +145,13 @@ def extract_attributes(extracted_text):
 
     return attributes
 
-# Function to filter attributes for valid Salesforce fields
+# Function to filter attributes for valid Salesforce fields📊
 def filter_valid_attributes(attributes, valid_fields):
     return {ATTRIBUTE_MAPPING[key]: value for key, value in attributes.items() if ATTRIBUTE_MAPPING[key] in valid_fields}
 
-#📊  Function to interact with Salesforce based on mode and type
+
+#📊 Function to interact with Salesforce based on mode and type
+
 def interact_with_salesforce(mode, entry_type, quantity, extracted_text):
     try:
         sf = Salesforce(
@@ -162,7 +164,6 @@ def interact_with_salesforce(mode, entry_type, quantity, extracted_text):
         object_name = None
         field_name = None
         product_field_name = "Product_Name__c"
-        model_field_name = "Modal_Name__c"  # Correct field for model name
 
         if mode == "Entry":
             if entry_type == "Sales":
@@ -182,97 +183,85 @@ def interact_with_salesforce(mode, entry_type, quantity, extracted_text):
         if not object_name or not field_name:
             return "Invalid mode or entry type."
 
-        # Get valid fields for the specified Salesforce object
-        sf_object = sf.__getattr__(object_name)
-        schema = sf_object.describe()
-        valid_fields = {field["name"] for field in schema["fields"]}
-
-        # Extract product name and attributes
+        # Extract product name
         product_name = match_product_name(extracted_text)
-        attributes = extract_attributes(extracted_text)
-        model_name = attributes.get("Model Name", "").strip()
-
         if not product_name:
             return "Product name could not be matched from the extracted text."
 
-        attributes["Product name"] = product_name
-
         # Handling "Exit" Mode (Updating Records)
-         Extract product name from the OCR text
-        product_name = match_product_name(extracted_text)
-        if not product_name:
-            return "❌ Product name could not be matched from the extracted text."
-
-        # Query Salesforce for the product record
-        query = f"SELECT Id, {field_name} FROM {object_name} WHERE Product_Name__c = '{product_name}' LIMIT 1"
-        response = sf.query(query)
+        if mode == "Exit":
+            query = f"SELECT Id, {field_name} FROM {object_name} WHERE {product_field_name} = '{product_name}' LIMIT 1"
+            response = sf.query(query)
+
+            if response["records"]:
+                record_id = response["records"][0]["Id"]
+                updated_quantity = quantity
+                sf.__getattr__(object_name).update(record_id, {field_name: updated_quantity})
+                return f"✅ Updated record for product '{product_name}' in {object_name}. New {field_name}: {updated_quantity}."
+            else:
+                return f"❌ No matching record found for product '{product_name}' in {object_name}."
 
-        if response["records"]:
-            record_id = response["records"][0]["Id"]
-
-            # Update the quantity sold
-            sf.__getattr__(object_name).update(record_id, {field_name: quantity})
-            return f"✅ Updated {field_name} for '{product_name}' in {object_name}. New Quantity: {quantity}."
-        else:
-            return f"❌ No record found for product '{product_name}' in {object_name}."
+        # Handling "Entry" Mode (Creating Records)
+        try:
+            attributes = {
+                "Productname__c": product_name,  # Mapping product name
+                field_name: quantity  # Mapping quantity based on entry type
+            }
+            # Export data to Salesforce
+            sf.__getattr__(object_name).create(attributes)
+            return f"✅ Data successfully exported to Salesforce object {object_name}."
+        
+        except Exception as e:
+            return f"❌ Error interacting with Salesforce: {str(e)}"
 
     except Exception as e:
-        return f"❌ Salesforce Error: {str(e)}"
+        return f"❌ Error setting up Salesforce connection: {str(e)}"
 
- 
-        # Handling "Entry" Mode (Creating Records)
-    else:
-        filtered_attributes = filter_valid_attributes(attributes, valid_fields)
-        filtered_attributes[field_name] = quantity
-        sf_object.create(filtered_attributes)
-        return f"✅ Data successfully exported to Salesforce object {object_name}."
-    except Exception as e:
-    return f"❌ Error interacting with Salesforce: {str(e)}"
-# Function to pull structured data from Salesforce and display as a table
-def pull_data_from_salesforce():
-    try:
-        sf = Salesforce(
+     # Function to pull structured data from Salesforce and display as a table
+    def pull_data_from_salesforce():
+        try:
+            sf = Salesforce(
             username=SALESFORCE_USERNAME,
             password=SALESFORCE_PASSWORD,
             security_token=SALESFORCE_SECURITY_TOKEN
         )
-       
-        query = "SELECT Product_Name__c, Modal_Name__c, Current_Stocks__c FROM Inventory_Management__c LIMIT 100"
-        response = sf.query_all(query)
-       
-        records = response.get("records", [])
-        if not records:
-            return "No data found in Salesforce.", None, None, None
-       
-        df = pd.DataFrame(records)
-        df = df.drop(columns=['attributes'], errors='ignore')
+            
+            query = "SELECT Product_Name__c, Modal_Name__c, Current_Stocks__c FROM Inventory_Management__c LIMIT 100"
+            response = sf.query_all(query)
+            
+            records = response.get("records", [])
+            if not records:
+                return "No data found in Salesforce.", None, None, None
+                
+                df = pd.DataFrame(records)
+                df = df.drop(columns=['attributes'], errors='ignore')
        
         # Rename columns for better readability
-        df.rename(columns={
-            "Product_Name__c": "Product Name",
-            "Modal_Name__c": "Model Name",
-            "Current_Stocks__c": "Current Stocks"
-        }, inplace=True)
-       
-        excel_path = "salesforce_data.xlsx"
-        df.to_excel(excel_path, index=False)
-       
-        # Generate interactive 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 "Data successfully retrieved.", df, excel_path, img
-    except Exception as e:
-        return f"Error fetching data: {str(e)}", None, None, None
+            df.rename(columns={
+                "Product_Name__c": "Product Name",
+                "Modal_Name__c": "Model Name",
+                "Current_Stocks__c": "Current Stocks"
+            }, inplace=True)
+            
+            excel_path = "salesforce_data.xlsx"
+            df.to_excel(excel_path, index=False)
+            
+            # Generate interactive 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 "Data successfully retrieved.", df, excel_path, img
+        except Exception as e:
+            return f"Error fetching data: {str(e)}", None, None, None
 
 # Unified function to handle image processing and Salesforce interaction
 def process_image(image, mode, entry_type, quantity):
@@ -324,4 +313,5 @@ def app():
     ], ["📥 OCR Processing", "📊 Salesforce Data Export"])
 
 if __name__ == "__main__":
-    app().launch(share=True)
+    app().launch(share=True)
+