Update app.py

app.py

@@ -9,6 +9,7 @@ import pandas as pd
 import matplotlib.pyplot as plt
 from io import BytesIO
 from fuzzywuzzy import process
+import kaleido  # Ensure kaleido is imported
 
 # Attribute mappings: readable names to Salesforce API names
 ATTRIBUTE_MAPPING = {
@@ -79,7 +80,7 @@ PRODUCT_NAMES = [
     "Centrifugal mono block pump", "SINGLE PHASE MOTOR STARTER", "EasyPact EZC 100",
     "Openwell Submersible Pumpset", "Electric Motor", "Self Priming Pump",
     "Control panel for single phase submersible pumps", "MOTOR", "Submersible pump set",
-    "Fusion submersible pump set", "DCT", "Shock proof water proof", "CG COMMERCIALMOTORS", "Fusion",
+    "Fusion submersible pump set", "DCT", "Shock proof water proof", "CG COMMERCIAL MOTORS", "Fusion",
     "control panel for single phase submerisible pumps",
     "single phase digital starter dry run and timer panel", "5HP AV1 XL Kirloskar Pump",
     "Phase stainless steel submersible pump", "Submersible pump", "WB15X",
@@ -161,25 +162,21 @@ def interact_with_salesforce(mode, entry_type, quantity, extracted_text):
         object_name = None
         field_name = None
         product_field_name = "Product_Name__c"  # Correct field for product name in the object
-        model_field_name = "Modal_Name__c"  # Correct field for model name in the object
+        model_field_name = "Model_Name__c"  # Correct field for model name in the object
 
         if mode == "Entry":
             if entry_type == "Sales":
-                object_name = "VENKATA_RAMANA_MOTORS__c"
-                field_name = "Quantity__c"
+                object_name = "Inventory__c"
+                field_name = "Stock_Quantity__c"
             elif entry_type == "Non-Sales":
-                object_name = "UNBILLING_DATA__c"
-                field_name = "TotalQuantity__c"
+                object_name = "Unbilled_Inventory__c"
+                field_name = "Unbilled_Quantity__c"
         elif mode == "Exit":
             if entry_type == "Sales":
-                object_name = "Inventory_Management__c"
-                product_field_name = "Product_Name__c"
-                model_field_name = "Modal_Name__c"
-                field_name = "Quantity_Sold__c"
+                object_name = "Inventory__c"
+                field_name = "Sold_Quantity__c"
             elif entry_type == "Non-Sales":
-                object_name = "Un_Billable__c"
-                product_field_name = "Product_Name__c"
-                model_field_name = "Model_Name__c"
+                object_name = "Unbilled_Inventory__c"
                 field_name = "Sold_Out__c"
 
         if not object_name or not field_name:
@@ -200,60 +197,56 @@ def interact_with_salesforce(mode, entry_type, quantity, extracted_text):
         attributes["Product name"] = product_name
 
         if mode == "Exit":
-            query = f"SELECT Id, {field_name} FROM {object_name} WHERE {product_field_name} = '{product_name}' OR {model_field_name} = '{attributes.get('Model Name', '')}' LIMIT 1"
+            query = f"SELECT Id, {field_name}, Stock_Quantity__c FROM {object_name} WHERE {product_field_name} = '{product_name}' OR {model_field_name} = '{attributes.get('Model Name', '')}' LIMIT 1"
             response = sf.query(query)
 
             if response["records"]:
                 record_id = response["records"][0]["Id"]
-                updated_quantity = quantity  # Overwrite the quantity, don't add
-                sf_object.update(record_id, {field_name: updated_quantity})
-                return f"Updated record for product '{product_name}' in {object_name}. New {field_name}: {updated_quantity}."
+                current_stock = response["records"][0].get("Stock_Quantity__c", 0)
+                updated_quantity = current_stock - quantity  # Deduct sold quantity
+                sf_object.update(record_id, {field_name: quantity, "Stock_Quantity__c": updated_quantity})
+                return f"Updated record for product '{product_name}' in {object_name}. New {field_name}: {quantity}, Updated Stock: {updated_quantity}."
             else:
                 return f"No matching record found for product '{product_name}' in {object_name}."
         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}."
+            return f"✅ Data successfully exported to Salesforce object {object_name}."
 
     except Exception as e:
-        return f"Error interacting with Salesforce: {str(e)}"
+        return f"❌ Error interacting with Salesforce: {str(e)}"
 
-# Function to pull data from Salesforce MotorDataAPI
-def pull_data_from_motor_api():
+# 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
         )
-        motor_data = sf.apexecute("MotorDataAPI/", method="GET")
-        return motor_data  # API returns the list of records
-    except Exception as e:
-        return f"Error pulling data from MotorDataAPI: {str(e)}"
-
-# Function to format Salesforce data into a DataFrame with readable headers
-def format_salesforce_data():
-    try:
-        data = pull_data_from_motor_api()
-        if isinstance(data, list):
-            df = pd.DataFrame(data)
-            df = df.rename(columns={
-                "Product_Name__c": "Product Name",
-                "Modal_Name__c": "Model Name",
-                "Current_Stocks__c": "Current Stocks"
-            })
-            # Remove unnecessary columns
-            df = df[["Product Name", "Model Name", "Current Stocks"]]
-            return df
-        else:
-            return None
-    except Exception as e:
-        return None
-
-# Function to generate a bar graph from Salesforce data
-def generate_bar_graph(df):
-    try:
+        
+        query = "SELECT Product_Name__c, Model_Name__c, Stock_Quantity__c FROM Inventory__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",
+            "Model_Name__c": "Model Name",
+            "Stock_Quantity__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")
@@ -265,9 +258,10 @@ def generate_bar_graph(df):
         plt.savefig(buffer, format="png")
         buffer.seek(0)
         img = Image.open(buffer)
-        return img
+        
+        return "Data successfully retrieved.", df, excel_path, img
     except Exception as e:
-        return None
+        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):
@@ -288,43 +282,35 @@ def process_image(image, mode, entry_type, quantity):
 
 # Gradio Interface
 def app():
-    df = format_salesforce_data()
-    table_component = None
-    bar_graph_component = None
-
-    if df is not None:
-        table_component = df.to_html(index=False)
-        bar_graph_image = generate_bar_graph(df)
-        if bar_graph_image:
-            bar_graph_component = bar_graph_image
-
     return gr.TabbedInterface([
         gr.Interface(
             fn=process_image,
             inputs=[
-                gr.Image(type="numpy", label="Upload Image"),
-                gr.Dropdown(label="Mode", choices=["Entry", "Exit"], value="Entry"),
-                gr.Radio(label="Entry Type", choices=["Sales", "Non-Sales"], value="Sales"),
-                gr.Number(label="Quantity", value=1, interactive=True),
+                gr.Image(type="numpy", label="📄 Upload Image"),
+                gr.Dropdown(label="📌 Mode", choices=["Entry", "Exit"], value="Entry"),
+                gr.Radio(label="📦 Entry Type", choices=["Sales", "Non-Sales"], value="Sales"),
+                gr.Number(label="🔢 Quantity", value=1, interactive=True),
             ],
             outputs=[
-                gr.Text(label="Image Data Viewer"),
-                gr.Text(label="Result")
+                gr.Text(label="📝 Extracted Image Data"),
+                gr.Text(label="🚀 Result")
             ],
-            title="Salesforce Export",
-            description="Upload an image, select Entry/Exit mode and Sales/Non-Sales type, and specify quantity."
+            title="🏢 Inventory Management",
+            description="📦 Inventory Management System"
         ),
         gr.Interface(
-            fn=lambda: (table_component, bar_graph_component),
+            fn=pull_data_from_salesforce,
             inputs=[],
             outputs=[
-                gr.HTML(label="Salesforce Data Table"),
-                gr.Image(type="pil", label="Stock Distribution Bar Graph")
+                gr.Text(label="Status"),
+                gr.Dataframe(label="📦 Salesforce Data Table"),
+                gr.File(label="Download Salesforce Data"),
+                gr.Image(label="📉 Stock Distribution Bar Graph")
             ],
-            title="Salesforce Data",
-            description="View structured Salesforce data as a table and bar graph."
+            title="📊 Salesforce Data Export",
+            description="View, visualize (zoom-in/out), and download Salesforce data (Product Name, Model Name, Current Stocks)."
         )
-    ], ["Processing", "Salesforce Data"])
+    ], ["📥 OCR Processing", "📊 Salesforce Data Export"])
 
 if __name__ == "__main__":
-    app().launch(share=True)
+    app().launch(share=True)