Update app.py

app.py

@@ -1,4 +1,4 @@
-import os
+mport os
 from paddleocr import PaddleOCR
 from PIL import Image
 import gradio as gr
@@ -10,7 +10,7 @@ import matplotlib.pyplot as plt
 from io import BytesIO
 from fuzzywuzzy import process
 
-#📌 Attribute mappings: readable names to Salesforce API names
+# Attribute mappings: readable names to Salesforce API names
 ATTRIBUTE_MAPPING = {
     "Product name": "Productname__c",
     "Colour": "Colour__c",
@@ -103,12 +103,12 @@ PRODUCT_NAMES = [
     "mono block pumps"
 ]
 
-#📌 Salesforce credentials
+# Salesforce credentials
 SALESFORCE_USERNAME = "venkatramana@sandbox.com"
 SALESFORCE_PASSWORD = "Venkat12345@"
 SALESFORCE_SECURITY_TOKEN = "GhcJJmjBEefdnukJoz4CAQlR"
 
-#🧠 Initialize PaddleOCR
+# Initialize PaddleOCR
 ocr = PaddleOCR(use_angle_cls=True, lang='en')
 
 # Function to extract text using PaddleOCR
@@ -148,7 +148,7 @@ def extract_attributes(extracted_text):
 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(
@@ -205,7 +205,8 @@ def interact_with_salesforce(mode, entry_type, quantity, extracted_text):
 
             if response["records"]:
                 record_id = response["records"][0]["Id"]
-                updated_quantity = quantity  # Overwrite the quantity, don't add
+                current_quantity = response["records"][0].get(field_name, 0) or 0
+                updated_quantity = max(0, current_quantity + quantity)
                 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}."
             else:
@@ -214,101 +215,60 @@ def interact_with_salesforce(mode, entry_type, quantity, extracted_text):
             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)}"
-import pandas as pd
-import matplotlib.pyplot as plt
-from io import BytesIO
-from PIL import Image
-from simple_salesforce import Salesforce
-import gradio as gr
+        return f"Error interacting with Salesforce: {str(e)}"
 
-# 📌 Salesforce Credentials
-SALESFORCE_USERNAME = "venkatramana@sandbox.com"
-SALESFORCE_PASSWORD = "Venkat12345@"
-SALESFORCE_SECURITY_TOKEN = "GhcJJmjBEefdnukJoz4CAQlR"
-
-# 📌 Function to Fetch and Display Salesforce Data (Stock Table & Graph)
-def fetch_salesforce_data():
+# Function to pull data from Salesforce MotorDataAPI
+def pull_data_from_motor_api():
     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)}"
 
-        # SOQL Query to fetch stock details
-        query = "SELECT Product_Name__c, Current_Stocks__c FROM Inventory_Management__c LIMIT 100"
-        response = sf.query(query)
-        records = response.get('records', [])
-
-        if not records:
-            return "<p>No Data Found</p>", None  # Return empty result if no records found
-
-        # Convert Salesforce Data into Pandas DataFrame
-        df = pd.DataFrame(records)
-        df.rename(columns={'Product_Name__c': 'Product Name', 'Current_Stocks__c': 'Current Stocks'}, inplace=True)
-        df.drop(columns=['attributes'], inplace=True, errors='ignore')
-
-        # Convert DataFrame to HTML Table
-        table_html = df.to_html(index=False)
-
-        # Generate Inventory Graph
-        graph_image = generate_inventory_graph(df)
-
-        return table_html, graph_image
-
+# 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 f"❌ Error fetching data: {str(e)}", None
+        return None
 
-# 📊 Function to Generate Inventory Stock Graph
-def generate_inventory_graph(df):
+# Function to generate a bar graph from Salesforce data
+def generate_bar_graph(df):
     try:
-        fig, ax = plt.subplots(figsize=(12, 6))
-        df.plot(kind='bar', x="Product Name", y="Current Stocks", ax=ax, legend=False, color="royalblue")
-        ax.set_title("Inventory Stock Distribution", fontsize=14, fontweight="bold")
-        ax.set_xlabel("Product Name", fontsize=12)
-        ax.set_ylabel("Stock Quantity", fontsize=12)
+        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()
-
-        # Save the graph to a buffer
         buffer = BytesIO()
         plt.savefig(buffer, format="png")
         buffer.seek(0)
-
-        return Image.open(buffer)
-
+        img = Image.open(buffer)
+        return img
     except Exception as e:
-        return None  # Return None if graph generation fails
-
-# 📌 Gradio UI for Viewing Salesforce Data (Table & Graph)
-def app():
-    with gr.Blocks() as interface:
-        gr.Markdown("<h1>📊 Salesforce Stock & Inventory Overview</h1>")
-
-        with gr.Row():
-            with gr.Column():
-                gr.Markdown("<h3>📋 Stock Data Table</h3>")
-                salesforce_table = gr.HTML(label="📦 Inventory Table")
-
-            with gr.Column():
-                gr.Markdown("<h3>📈 Inventory Stock Graph</h3>")
-                salesforce_graph = gr.Image(type="pil", label="📉 Stock Graph")
-
-        generate_button = gr.Button("⚡ Fetch Data")
-
-        # Clicking "Fetch Data" will display the table & graph
-        generate_button.click(fn=fetch_salesforce_data, inputs=[], outputs=[salesforce_table, salesforce_graph])
-
-    return interface
-
-# 🚀 Launch the Gradio App
-if __name__ == "__main__":
-    interface = app()
-    interface.launch(share=True)
+        return None
 
 # Unified function to handle image processing and Salesforce interaction
 def process_image(image, mode, entry_type, quantity):
@@ -327,276 +287,45 @@ def process_image(image, mode, entry_type, quantity):
     numbered_output = "\n".join([f"{key}: {value}" for key, value in attributes.items()])
     return f"Extracted Text:\n{extracted_text}\n\nAttributes and Values:\n{numbered_output}", message
 
-
-import gradio as gr
-import numpy as np
-from PIL import Image
-
-# Function to fetch and return Salesforce data
-def generate_salesforce_data():
+# 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)
-        return table_component, bar_graph_image
-    return "<p>No Data Available</p>", None
-
-def app():
-    with gr.Blocks(css="""
-        /* General Styling */
-        .gradio-container { 
-            background: #0b0f29; /* Deep Dark Blue */
-            font-family: 'Poppins', sans-serif;
-            color: white;
-            padding: 10px;
-        }
-
-        h1, h2, h3 {
-            text-align: center;
-            color: white;
-            font-weight: bold;
-            text-shadow: 0px 0px 10px rgba(255,255,255,0.8);
-        }
-
-        /* Cards & Elements */
-        .card {
-            background: rgba(255, 255, 255, 0.1);
-            border-radius: 15px;
-            padding: 20px;
-            width: 100%;
-            max-width: 900px; /* Prevents extra-wide tables */
-            margin: auto; /* Centers the table */
-            box-shadow: 0px 0px 25px rgba(0, 255, 255, 0.6);
-            transition: 0.3s;
-        }
-
-        .card:hover {
-            box-shadow: 0px 0px 30px rgba(0, 255, 255, 0.9);
-        }
-
-        /* Buttons */
-        .gradio-button {
-            background: linear-gradient(to right, #ff416c, #ff4b2b);
-            color: white !important;
-            border-radius: 10px !important;
-            font-weight: bold;
-            padding: 12px;
-            transition: all 0.3s ease-in-out;
-            box-shadow: 0px 0px 20px rgba(255, 0, 255, 0.6);
-        }
-
-        .gradio-button:hover {
-            background: linear-gradient(to right, #ff4b2b, #ff416c);
-            box-shadow: 0px 0px 30px rgba(255, 0, 255, 0.9);
-        }
-
-        /* Tabs */
-        .gradio-tab {
-            font-size: 16px;
-            color: white;
-            font-weight: bold;
-            text-shadow: 0px 0px 10px rgba(255, 255, 255, 0.6);
-        }
-
-        /* Scrollable Table */
-        .table-container {
-            width: 100%;
-            max-width: 900px;
-            max-height: 400px; /* Controls table height */
-            overflow-y: auto; /* Enables vertical scrolling */
-            overflow-x: auto; /* Enables horizontal scrolling if needed */
-            display: flex;
-            justify-content: center;
-            margin: auto;
-        }
-
-        table {
-            width: 100%;
-            border-collapse: collapse;
-            background: rgba(255, 255, 255, 0.1);
-            color: white;
-            min-width: 600px;
-        }
-
-        th, td {
-            padding: 12px;
-            text-align: left;
-            border-bottom: 1px solid rgba(255, 255, 255, 0.2);
-            font-size: 14px;
-        }
-
-        th {
-            background: rgba(0, 255, 255, 0.2);
-        }
-
-        /* Mobile View */
-        @media (max-width: 768px) {
-            .gradio-container {
-                padding: 10px;
-            }
-
-            .card {
-                width: 100%;
-                max-width: 100%;
-                padding: 10px;
-            }
-
-            .table-container {
-                max-height: 350px; /* Adjusts for mobile */
-                overflow-y: scroll; /* Ensures vertical scrolling */
-            }
-
-            table {
-                width: 100%;
-                min-width: 100%;
-            }
-
-            th, td {
-                font-size: 12px;
-                padding: 8px;
-            }
-        }
-
-    """) as interface:
-
-        gr.Markdown("<h1>🏢 VENKATARAMANA MOTORS</h1>")
-
-        with gr.Tab("📥 Stock Entry & Processing"):
-            with gr.Row():
-                with gr.Column():
-                    gr.Markdown("<h3>📌 Upload & Process</h3>")
-                    image_input = gr.Image(type="numpy", label="📄 Upload Image", elem_classes="card")
-                    mode_dropdown = gr.Dropdown(label="📌 Mode", choices=["Entry", "Exit"], value="Entry", elem_classes="card")
-                    entry_type_radio = gr.Radio(label="📦 Entry Type", choices=["Sales", "Non-Sales"], value="Sales", elem_classes="card")
-                    quantity_input = gr.Number(label="🔢 Quantity", value=1, interactive=True, elem_classes="card")
-
-                with gr.Column():
-                    gr.Markdown("<h3>📊 Processed Data</h3>")
-                    image_view = gr.Text(label="📜 Image Data Viewer", interactive=False, elem_classes="card")
-                    result_output = gr.Text(label="📝 Processed Result", interactive=False, elem_classes="card")
-                    submit_button = gr.Button("🔍 Process Image", elem_id="process-btn", elem_classes="gradio-button")
-
-        with gr.Tab("📊 Salesforce Data Overview"):
-            gr.Markdown("<h3>📑 Stock Table</h3>")
-            with gr.Row(elem_classes="table-container"):
-                salesforce_table = gr.HTML(label="📦 Salesforce Data Table", elem_classes="card")
-
-            gr.Markdown("<h3>📈 Inventory Analytics</h3>")
-            with gr.Row():
-                salesforce_graph = gr.Image(type="pil", label="📉 Stock Distribution Bar Graph", elem_classes="card")
-
-            generate_button = gr.Button("⚡ Generate Data", elem_classes="gradio-button")
-
-        # Clicking "Generate Data" fetches table & graph
-        generate_button.click(fn=generate_salesforce_data, inputs=[], outputs=[salesforce_table, salesforce_graph])
-
-        submit_button.click(fn=process_image, inputs=[image_input, mode_dropdown, entry_type_radio, quantity_input], outputs=[image_view, result_output])
-
-        return interface
-
-interface = app()
-interface.launch()
-css = """
-    body {
-        background: linear-gradient(135deg, #282c34, #4b79a1);
-        font-family: 'Poppins', sans-serif;
-    }
-
-    .gradio-container {
-        border-radius: 20px;
-        padding: 30px;
-        background: rgba(255, 255, 255, 0.2);
-        backdrop-filter: blur(10px);
-        box-shadow: 0px 8px 30px rgba(0, 123, 255, 0.4);
-        border: 2px solid rgba(255, 255, 255, 0.4);
-    }
-
-    .gradio-title {
-        font-size: 48px;
-        font-weight: bold;
-        text-align: center;
-        background: linear-gradient(90deg, #ff7eb3, #ff758c);
-        -webkit-background-clip: text;
-        -webkit-text-fill-color: transparent;
-        text-shadow: 5px 5px 20px rgba(255, 105, 180, 0.6);
-        margin-bottom: 20px;
-        animation: glow 2s infinite alternate;
-    }
-
-    @keyframes glow {
-        from {
-            text-shadow: 5px 5px 30px rgba(255, 87, 134, 0.6);
-        }
-        to {
-            text-shadow: 6px 6px 40px rgba(255, 54, 90, 1);
-        }
-    }
-
-    .gradio-box {
-        border-radius: 15px;
-        padding: 25px;
-        background: linear-gradient(135deg, #6a11cb, #2575fc);
-        box-shadow: 0px 6px 25px rgba(30, 144, 255, 0.6);
-        border: 2px solid #6a5acd;
-        color: white;
-        font-size: 18px;
-    }
-
-    .gradio-button {
-        border-radius: 12px;
-        padding: 18px 36px;
-        font-size: 20px;
-        font-weight: bold;
-        color: #fff;
-        background: linear-gradient(135deg, #1e90ff, #00bfff);
-        box-shadow: 0px 6px 25px rgba(0, 191, 255, 0.6);
-        transition: all 0.3s ease-in-out;
-    }
-
-    .gradio-button:hover {
-        background: linear-gradient(135deg, #00bfff, #1e90ff);
-        box-shadow: 0px 10px 35px rgba(0, 191, 255, 0.9);
-        transform: scale(1.1);
-    }
-
-    .gradio-input {
-        border-radius: 10px;
-        padding: 16px;
-        font-size: 18px;
-        background: rgba(255, 255, 255, 0.3);
-        border: 2px solid rgba(0, 123, 255, 0.5);
-        color: #fff;
-        transition: 0.3s;
-    }
-
-    .gradio-input:focus {
-        border: 2px solid #1e90ff;
-        outline: none;
-        box-shadow: 0px 5px 20px rgba(30, 144, 255, 0.6);
-    }
-
-    .gradio-output {
-        background: linear-gradient(135deg, #f39c12, #e74c3c);
-        padding: 22px;
-        border-radius: 15px;
-        color: white;
-        font-size: 20px;
-        text-align: center;
-        border: 2px solid #f39c12;
-    }
-
-    .gradio-file {
-        background: linear-gradient(135deg, #8e44ad, #3498db);
-        color: white;
-        padding: 16px;
-        border-radius: 15px;
-        text-align: center;
-        font-size: 18px;
-    }
-"""
-
-
-
+        if bar_graph_image:
+            bar_graph_component = bar_graph_image
+
+    return gr.TabbedInterface([
+        gr.Interface(
+            fn=process_image,
+            inputs=[
+                gr.Image(type="numpy", label="📄ᴜᴘʟᴏᴀᴅ ɪᴍᴀɢᴇ"),
+                gr.Dropdown(label="📌Mode", choices=["ᴇɴᴛʀʏ", "ᴇxɪᴛ"], value="Entry"),
+                gr.Radio(label="Entry Type", choices=["ꜱᴀʟᴇꜱ", "ɴᴏɴ-ꜱᴀʟᴇꜱ"], value="Sales"),
+                gr.Number(label="🔢Quantity", value=1, interactive=True),
+            ],
+            outputs=[
+                gr.Text(label="ɪᴍᴀɢᴇ ᴅᴀᴛᴀ ᴠɪᴇᴡᴇʀ"),
+                gr.Text(label="📝ＲＥＳＵＬＴ")
+            ],
+            title="🏢𝑽𝑬𝑵𝑲𝑨𝑻𝑨𝑹𝑨𝑴𝑨𝑵𝑨 𝑴𝑶𝑻𝑶𝑹𝑺",
+            description="📦𝐈𝐍𝐕𝐄𝐍𝐓𝐎𝐑𝐘 𝐌𝐀𝐍𝐀𝐆𝐄𝐌𝐄𝐍𝐓"
+        ),
+        gr.Interface(
+            fn=lambda: (table_component, bar_graph_component),
+            inputs=[],
+            outputs=[
+                gr.HTML(label="📈ꜱᴀʟᴇꜱꜰᴏʀᴄᴇ ᴅᴀᴛᴀ ᴇxᴘᴏʀᴛ"),
+                gr.Image(type="pil", label="Stock Distribution Bar Graph")
+            ],
+            title="Salesforce Data",
+            description="View structured Salesforce data as a table and bar graph."
+        )
+    ], ["Processing", "📊Salesforce Data Export"])
 
 if __name__ == "__main__":
-    app().launch(share=True) 
+    app().launch(share=True)