Update app.py

app.py

@@ -1,92 +1,20 @@
 import gradio as gr
-from PIL import Image
-from datetime import datetime
-import pytz
 from ocr_engine import extract_weight
-from simple_salesforce import Salesforce
-import base64
-import os
-
-# Salesforce credentials
-SF_USERNAME = "[email protected]"
-SF_PASSWORD = "autoweight@32"
-SF_TOKEN = "UgiHKWT0aoZRX9gvTYDjAiRY"
-
-# Connect to Salesforce
-sf = Salesforce(username=SF_USERNAME, password=SF_PASSWORD, security_token=SF_TOKEN)
+from PIL import Image
+import tempfile
 
 def process_image(image):
-    if image is None:
-        return "❌ No image provided", "", None, gr.update(visible=True)
-    try:
-        # Extract weight using OCR (your updated function should handle any clear image)
-        weight = extract_weight(image)
-
-        ist = pytz.timezone('Asia/Kolkata')
-        timestamp = datetime.now(ist).strftime("%Y-%m-%d %H:%M:%S IST")
-
-        if not weight or "No valid" in weight:
-            return "❌ Unable to detect. Try again with a clearer image.", "", image, gr.update(visible=True)
-
-        # Save image temporarily
-        image_path = "snapshot.jpg"
-        image.save(image_path)
-
-        # Create Weight_Log__c record
-        record = sf.Weight_Log__c.create({
-            "Captured_Weight__c": float(weight.replace("kg", "").strip()),
-            "Captured_At__c": datetime.now(ist).isoformat(),
-            "Device_ID__c": "DEVICE-001",
-            "Status__c": "Confirmed"
-        })
-
-        # Upload image as ContentVersion
-        with open(image_path, "rb") as f:
-            encoded_image = base64.b64encode(f.read()).decode("utf-8")
-
-        content = sf.ContentVersion.create({
-            "Title": f"Snapshot_{timestamp}",
-            "PathOnClient": "snapshot.jpg",
-            "VersionData": encoded_image
-        })
-
-        content_id = sf.query(
-            f"SELECT ContentDocumentId FROM ContentVersion WHERE Id = '{content['id']}'"
-        )['records'][0]['ContentDocumentId']
-
-        sf.ContentDocumentLink.create({
-            "ContentDocumentId": content_id,
-            "LinkedEntityId": record['id'],
-            "ShareType": "V",
-            "Visibility": "AllUsers"
-        })
-
-        return weight, timestamp, image, gr.update(visible=False)
-    except Exception as e:
-        return f"Error: {str(e)}", "", None, gr.update(visible=True)
-
-# Updated header: Removed "and logs it into Salesforce"
-with gr.Blocks(css=".gr-button {background-color: #2e7d32 !important; color: white !important;}") as demo:
-    gr.Markdown("""
-    <h1 style='text-align: center; color: #2e7d32;'>📷 Auto Weight Logger</h1>
-    <p style='text-align: center;'>Upload or capture a digital weight image. Detects weight using AI OCR.</p>
-    <hr style='border: 1px solid #ddd;'/>
-    """)
-
-    with gr.Row():
-        image_input = gr.Image(type="pil", label="📁 Upload or Capture Image")
-
-    detect_btn = gr.Button("🚀 Detect Weight")
-
-    with gr.Row():
-        weight_out = gr.Textbox(label="📦 Detected Weight", placeholder="e.g., 97.9 kg", show_copy_button=True)
-        time_out = gr.Textbox(label="🕒 Captured At (IST)", placeholder="e.g., 2025-07-01 12:00:00")
-
-    snapshot = gr.Image(label="📸 Snapshot Preview")
-    retake_btn = gr.Button("🔁 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])
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as f:
+        image.save(f.name)
+        result = extract_weight(f.name)
+    return result
+
+demo = gr.Interface(
+    fn=process_image,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Auto Weight Detector",
+    description="Upload an image of a digital balance showing weight in g or kg (e.g. 52.25 g, 75.8 kg)"
+)
 
 demo.launch()