Update app.py

app.py

@@ -1,3 +1,4 @@
+
 import os
 from paddleocr import PaddleOCR
 from PIL import Image
@@ -9,10 +10,12 @@ import pandas as pd
 import matplotlib.pyplot as plt
 from io import BytesIO
 from fuzzywuzzy import process
+import plotly.graph_objects as go
+import kaleido  # Ensure kaleido is imported
 
 #📌 Attribute mappings: readable names to Salesforce API names
 ATTRIBUTE_MAPPING = {
-    "Product name": "Productname__c",
+  "Product name": "Productname__c",
     "Colour": "Colour__c",
     "Motortype": "Motortype__c",
     "Frequency": "Frequency__c",
@@ -71,12 +74,11 @@ ATTRIBUTE_MAPPING = {
     "SRnumber": "SRnumber__c",
     "TypeOfEndUse": "TypeOfEndUse__c",
     "Model Name": "Model_Name_Number__c",
-    "coolingmethod": "coolingmethod__c"
+    "coolingmethod": "coolingmethod__c" 
 }
-
+       
 # List of product names to match
-PRODUCT_NAMES = [
-    "Centrifugal mono block pump", "SINGLE PHASE MOTOR STARTER", "EasyPact EZC 100",
+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 COMMERCIAL MOTORS", "Fusion",
@@ -101,7 +103,7 @@ PRODUCT_NAMES = [
     "Various Repair and Maintenance Parts", "Earthmax Pump",
     "Water Tank, Filters, Water Pump", "Centrifugal Water Pump for Agriculture",
     "mono block pumps"
-]
+                ]
 
 #📌 Salesforce credentials
 SALESFORCE_USERNAME = "venkatramana@sandbox.com"
@@ -219,15 +221,7 @@ def interact_with_salesforce(mode, entry_type, quantity, extracted_text):
     except Exception as e:
         return f"❌ Error interacting with Salesforce: {str(e)}"
 
-import pandas as pd
-import plotly.express as px
-from simple_salesforce import Salesforce
-
-# Salesforce Credentials (Assumed to be defined elsewhere)
-SALESFORCE_USERNAME = "your_username"
-SALESFORCE_PASSWORD = "your_password"
-SALESFORCE_SECURITY_TOKEN = "your_security_token"
-
+# Function to pull data from Salesforce MotorDataAPI
 def pull_data_from_motor_api():
     try:
         sf = Salesforce(
@@ -236,319 +230,113 @@ def pull_data_from_motor_api():
             security_token=SALESFORCE_SECURITY_TOKEN
         )
         motor_data = sf.apexecute("MotorDataAPI/", method="GET")
-        if motor_data and isinstance(motor_data, list) and len(motor_data) > 0:
-            return motor_data  # API returns the list of records
-        else:
-            print("No data received from MotorDataAPI.")
-            return []
-    except Exception as e:
-        print(f"Error pulling data from MotorDataAPI: {str(e)}")
-        return []
-
-def format_salesforce_data():
-    try:
-        data = pull_data_from_motor_api()
-        if isinstance(data, list) and len(data) > 0:
-            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:
-            print("No valid data available for formatting.")
-            return None
+        return motor_data  # API returns the list of records
     except Exception as e:
-        print(f"Error formatting data: {str(e)}")
-        return None
+        return f"Error pulling data from MotorDataAPI: {str(e)}"
 
-def generate_interactive_bar_chart(df):
+# Function to pull structured data from Salesforce and display as a table
+def pull_data_from_salesforce():
     try:
-        if df is None or df.empty:
-            print("No data available for visualization.")
-            return
-        
-        fig = px.bar(
-            df,
-            x="Product Name",
-            y="Current Stocks",
-            hover_data={"Product Name": True, "Current Stocks": True},
-            text="Current Stocks",
-            title="Stock Distribution by Product Name"
+        sf = Salesforce(
+            username=SALESFORCE_USERNAME,
+            password=SALESFORCE_PASSWORD,
+            security_token=SALESFORCE_SECURITY_TOKEN
         )
-        fig.update_traces(textposition='outside')
+       
+        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 bar graph using Plotly with Tooltip, Hover Effect, and Zooming
+        fig = go.Figure()
+        fig.add_trace(go.Bar(
+            x=df['Product Name'],
+            y=df['Current Stocks'],
+            marker=dict(color='blue'),
+            hoverinfo='x+y',
+            hovertemplate='<b>Product Name:</b> %{x}<br><b>Current Stocks:</b> %{y}<extra></extra>',
+            text=df['Current Stocks'],
+            textposition='outside'
+        ))
+       
         fig.update_layout(
-            xaxis_title="Product Name",
-            yaxis_title="Current Stocks",
-            hovermode="x unified"
+            title="Current Stocks of Products",
+            xaxis=dict(title="Product Name", tickangle=-45),
+            yaxis=dict(title="Stock Quantity"),
+            hovermode='x',
+            dragmode='zoom',
+            showlegend=False
         )
-        fig.show()
+       
+        return "Data successfully retrieved.", df, excel_path, fig
     except Exception as e:
-        print(f"Error generating interactive chart: {str(e)}")
+        return f"Error fetching data: {str(e)}", None, None, None
 
-# Fetch and visualize data
-data_df = format_salesforce_data()
-if data_df is not None and not data_df.empty:
-    generate_interactive_bar_chart(data_df)
-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;
-    }
-"""
+# Unified function to handle image processing and Salesforce interaction
+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
 
+    product_name = match_product_name(extracted_text)
+    attributes = extract_attributes(extracted_text)
+    if product_name:
+        attributes["Product name"] = product_name
 
+    # Interact with Salesforce
+    message = interact_with_salesforce(mode, entry_type, quantity, extracted_text)
 
+    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
+
+# Gradio Interface
+def app():
+    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=False),
+            ],
+            outputs=[
+                gr.Text(label="Extracted Text"),
+                gr.Text(label="Result")
+            ],
+            title="Image Text Extraction",
+            description="Upload an image and extract text using OCR."
+        ),
+        gr.Interface(
+            fn=pull_data_from_salesforce,
+            inputs=[],
+            outputs=[
+                gr.Text(label="Status"),
+                gr.Dataframe(label="Salesforce Data Table"),
+                gr.File(label="Download Salesforce Data"),
+                gr.Plot(label="Stock Distribution Bar Graph")
+            ],
+            title="Salesforce Data Export",
+            description="View, visualize (zoom-in/out, hover details), and download Salesforce data (Product Name, Model Name, Current Stocks)."
+        )
+    ], ["OCR Processing", "Salesforce Data Export"])
 
 if __name__ == "__main__":
-    app().launch(share=True) 
+    app().launch(share=True)
+