Update app.py

app.py

@@ -3,7 +3,7 @@ from paddleocr import PaddleOCR
 from PIL import Image
 import gradio as gr
 import re
-from simple_salesforce import Salesforce
+# from simple_salesforce import Salesforce  # Commented out to disable Salesforce integration
 import pandas as pd
 
 # Attribute mappings: readable names to Salesforce API names, in desired order
@@ -24,10 +24,10 @@ GENDER_MAPPING = {
     "Other": "Others"  # Map 'Other' to 'Others' to match picklist
 }
 
-# Salesforce credentials
-SALESFORCE_USERNAME = "sathkruthatech@hms.com"
-SALESFORCE_PASSWORD = "Hms@2025"
-SALESFORCE_SECURITY_TOKEN = "5W0grf0aX0M9cD3yDZ2C5F"
+# Salesforce credentials (commented out since Salesforce integration is disabled)
+# SALESFORCE_USERNAME = "sathkruthatech@hms.com"
+# SALESFORCE_PASSWORD = "Hms@2025"
+# SALESFORCE_SECURITY_TOKEN = "5W0grf0aX0M9cD3yDZ2C5F"
 
 # Initialize PaddleOCR
 ocr = PaddleOCR(use_angle_cls=True, lang='en')
@@ -49,7 +49,7 @@ def extract_attributes(extracted_text):
         "Name": r"Name[:\-]?\s*([A-Za-z]+)",  # Allow no space after Name:
         "Age": r"Age[:\-]?\s*(\d{1,3})",
         "Gender": r"Gender[:\-]?\s*(Male|Female|Other)",
-        "Phone Number": r"(?:(?:Phone Number)|Phone|Mobile|Phonenumber)[:\-]?\s*(?:\+91)?([6-9]\d{9})" # Indian number: starts with 6-9, exactly 10 digits
+        "Phone Number": r"(?:(?:Phone Number)|Phone|Mobile|Phonenumber)[:\-]?\s*(?:\+91)?([6-9]\d{9})"
     }
 
     for readable_attr, pattern in patterns.items():
@@ -63,42 +63,39 @@ def extract_attributes(extracted_text):
 
     return attributes
 
-# Function to filter attributes for valid Salesforce fields
-def filter_valid_attributes(attributes, valid_fields):
+# Function to filter attributes for valid Salesforce fields (mocked for now)
+def filter_valid_attributes(attributes, valid_fields=None):
+    # Mock valid fields since Salesforce is disabled
+    if valid_fields is None:
+        valid_fields = {"Name", "Name__c", "Age__c", "Gender__c", "Phone_Number__c"}
+    
     filtered = {ATTRIBUTE_MAPPING[key]: value for key, value in attributes.items() if ATTRIBUTE_MAPPING[key] in valid_fields}
+    
+    # Add the standard 'Name' field using the extracted Name value
+    if "Name" in attributes and "Name" in valid_fields:
+        filtered["Name"] = attributes["Name"]
+    
     return filtered
 
-# Function to interact with Salesforce
+# Function to interact with Salesforce (mocked for now)
 def interact_with_salesforce(attributes):
     try:
-        # Initialize Salesforce connection
-        sf = Salesforce(
-            SALESFORCE_USERNAME = "sathkruthatech@hms.com",
-            SALESFORCE_PASSWORD = "Hms@2025",
-            SALESFORCE_SECURITY_TOKEN = "5W0grf0aX0M9cD3yDZ2C5F",
-            domain="test"  # Set for sandbox instance
-        )
-
-        object_name = "Patient_Registration__c"
-        sf_object = sf.__getattr__(object_name)
-        schema = sf_object.describe()
-        valid_fields = {field["name"] for field in schema["fields"]}
-
+        # Mock Salesforce interaction since we cannot initialize Salesforce
+        valid_fields = {"Name", "Name__c", "Age__c", "Gender__c", "Phone_Number__c"}  # Mocked schema
         filtered_attributes = filter_valid_attributes(attributes, valid_fields)
 
-        # Log the attributes being sent to Salesforce for debugging
-        print(f"Attributes being sent to Salesforce: {filtered_attributes}")
+        # Log the attributes that would be sent to Salesforce
+        print(f"Attributes that would be sent to Salesforce: {filtered_attributes}")
 
-        # Ensure Age__c is a number
+        # Ensure Age__c is a number (for compatibility with Salesforce)
         if "Age__c" in filtered_attributes:
             filtered_attributes["Age__c"] = int(filtered_attributes["Age__c"])
 
-        # Create a new record in Salesforce
-        result = sf_object.create(filtered_attributes)
-        return f"✅ Successfully created Patient Registration record with ID: {result['id']}."
+        # Mock a successful Salesforce response
+        return f"✅ Mock Success: Attributes processed (Salesforce integration disabled). Data: {filtered_attributes}"
 
     except Exception as e:
-        return f"❌ Error interacting with Salesforce: {str(e)}"
+        return f"❌ Error processing attributes: {str(e)}"
 
 # Function to process image and extract attributes
 def process_image(image):
@@ -115,18 +112,18 @@ def process_image(image):
     df = pd.DataFrame(list(ordered_attributes.items()), columns=["Attribute", "Value"])
     return f"Extracted Text:\n{extracted_text}", df, None
 
-# Function to handle edited attributes and export to Salesforce
+# Function to handle edited attributes and export to Salesforce (mocked)
 def export_to_salesforce(edited_df):
     try:
         # Convert edited DataFrame back to dictionary
         edited_attributes = dict(zip(edited_df["Attribute"], edited_df["Value"]))
 
-        # Export to Salesforce
+        # Export to Salesforce (mocked)
         message = interact_with_salesforce(edited_attributes)
         return message
 
     except Exception as e:
-        return f"❌ Error exporting to Salesforce: {str(e)}"
+        return f"❌ Error exporting attributes: {str(e)}"
 
 # Gradio Interface
 def app():