app.py

import os
from paddleocr import PaddleOCR
from PIL import Image
import gradio as gr
import requests
import re
from simple_salesforce import Salesforce
import pandas as pd
import matplotlib.pyplot as plt
from io import BytesIO
from fuzzywuzzy import process

# Salesforce credentials
SALESFORCE_USERNAME = "venkatramana@sandbox.com"
SALESFORCE_PASSWORD = "Venkat12345@"
SALESFORCE_SECURITY_TOKEN = "GhcJJmjBEefdnukJoz4CAQlR"

# Initialize PaddleOCR
ocr = PaddleOCR(use_angle_cls=True, lang='en')

# Function to extract text using PaddleOCR
def extract_text(image):
    result = ocr.ocr(image)
    extracted_text = []
    for line in result[0]:
        extracted_text.append(line[1][0])
    return "\n".join(extracted_text)

# Function to fetch data from Salesforce and format it into a DataFrame
def fetch_salesforce_data():
    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 MotorDataAPI__c"
        response = sf.query_all(query)
        records = response["records"]
        df = pd.DataFrame(records)
        df = df.rename(columns={
            "Product_Name__c": "Product Name",
            "Modal_Name__c": "Model Name",
            "Current_Stocks__c": "Current Stocks"
        })
        return df[["Product Name", "Model Name", "Current Stocks"]]
    except Exception as e:
        return None

# Function to generate a bar graph from Salesforce data
def generate_salesforce_bar_chart(df):
    try:
        plt.figure(figsize=(12, 6))
        df.plot(kind='bar', x="Product Name", y="Current Stocks", legend=False)
        plt.title("Stock Distribution by Product Name")
        plt.xlabel("Product Name")
        plt.ylabel("Current Stocks")
        plt.xticks(rotation=45, ha="right")
        plt.tight_layout()
        buffer = BytesIO()
        plt.savefig(buffer, format="png")
        buffer.seek(0)
        return Image.open(buffer)
    except Exception as e:
        return None

# 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
    
    return f"Extracted Text:\n{extracted_text}\n\nProcessing Completed.", None

# Function to fetch and return Salesforce data
def get_salesforce_visualization():
    df = fetch_salesforce_data()
    if df is not None:
        table_component = df.to_html(index=False)
        bar_chart_image = generate_salesforce_bar_chart(df)
        return table_component, bar_chart_image
    return "<p>No Data Available</p>", None

def app():
    with gr.Blocks() 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")
                    mode_dropdown = gr.Dropdown(label="📌 Mode", choices=["Entry", "Exit"], value="Entry")
                    entry_type_radio = gr.Radio(label="📦 Entry Type", choices=["Sales", "Non-Sales"], value="Sales")
                    quantity_input = gr.Number(label="🔢 Quantity", value=1, interactive=True)
                
                with gr.Column():
                    gr.Markdown("<h3>📊 Processed Data</h3>")
                    image_view = gr.Text(label="📜 Image Data Viewer", interactive=False)
                    result_output = gr.Text(label="📝 Processed Result", interactive=False)
                    submit_button = gr.Button("🔍 Process Image")

        with gr.Tab("📊 Salesforce Data Overview"):
            gr.Markdown("<h3>📑 Stock Table</h3>")
            with gr.Row():
                salesforce_table = gr.HTML(label="📦 Salesforce Data Table")

            gr.Markdown("<h3>📈 Inventory Analytics</h3>")
            with gr.Row():
                salesforce_graph = gr.Image(type="pil", label="📉 Stock Distribution Bar Graph")
            
            generate_button = gr.Button("⚡ Generate Data")

        generate_button.click(fn=get_salesforce_visualization, 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

if __name__ == "__main__":
    app().launch(share=True)