logger2 / app.py
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import gradio as gr
from PIL import Image
from datetime import datetime
import pytz
import os
from simple_salesforce import Salesforce
from ocr_engine import extract_weight
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
# Salesforce connection
sf = Salesforce(
username=os.getenv("SF_USERNAME"),
password=os.getenv("SF_PASSWORD"),
security_token=os.getenv("SF_TOKEN")
)
def process_image(image):
if image is None:
return "❌ No image provided", "", None, gr.update(visible=True)
try:
weight = extract_weight(image)
ist = pytz.timezone('Asia/Kolkata')
now = datetime.now(ist)
timestamp_display = now.strftime("%Y-%m-%d %H:%M:%S IST")
timestamp_iso = now.isoformat()
if not weight or "No valid" in weight:
return "❌ Unable to detect. Try again with a clearer image.", "", image, gr.update(visible=True)
# Create Salesforce record
sf.Weight_Log__c.create({
'Captured_Weight__c': float(weight.replace("kg", "").strip()),
'Captured_At__c': timestamp_iso,
'Device_ID__c': 'Device-01', # Static or dynamic device ID
'Snapshot_Image__c': 'Manual Entry',
'Status__c': 'Captured'
})
return weight, timestamp_display, image, gr.update(visible=False)
except Exception as e:
return f"Error: {str(e)}", "", None, gr.update(visible=True)
# Gradio UI
with gr.Blocks(css=".gr-button {background-color: #2e7d32 !important; color: white !important;}") as demo:
gr.Markdown("""
<h1 style='text-align: center; color: #2e7d32;'>πŸ“· Auto Weight Logger</h1>
<p style='text-align: center;'>Upload or capture a digital weight image. Detects weight using AI OCR and stores the result in Salesforce.</p>
<hr style='border: 1px solid #ddd;'/>
""")
with gr.Row():
image_input = gr.Image(type="pil", label="πŸ“ Upload or Capture Image")
detect_btn = gr.Button("πŸš€ Detect Weight")
with gr.Row():
weight_out = gr.Textbox(label="πŸ“¦ Detected Weight", placeholder="e.g., 97.9 kg", show_copy_button=True)
time_out = gr.Textbox(label="πŸ•’ Captured At (IST)", placeholder="e.g., 2025-07-01 12:00:00")
snapshot = gr.Image(label="πŸ“Έ Snapshot Preview")
retake_btn = gr.Button("πŸ” Retake / Try Again", visible=False)
detect_btn.click(fn=process_image, inputs=image_input, outputs=[weight_out, time_out, snapshot, retake_btn])
retake_btn.click(fn=lambda: ("", "", None, gr.update(visible=False)),
inputs=[], outputs=[weight_out, time_out, snapshot, retake_btn])
demo.launch()