Update src/streamlit_app.py

src/streamlit_app.py

@@ -2,6 +2,7 @@ import streamlit as st
 from PIL import Image
 from ocr_engine import extract_weight_from_image
 import urllib.parse
+from datetime import datetime
 
 st.set_page_config(page_title="⚖️ Auto Weight Logger", layout="centered")
 st.title("⚖️ Auto Weight Logger")
@@ -29,11 +30,24 @@ if img_data:
             st.experimental_rerun()
         st.stop()
 
-    st.success(f"✅ Detected Weight: {weight} g (Confidence: {int(confidence)}%)")
-
+    # ✅ Prepare data for preview and URL
     device_id = "BAL-001"
-    image_url = ""
-
+    image_url = ""  # optional - add later if you host the image
+    captured_at = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    status = "Pending Submission"
+
+    # ✅ Show full preview
+    st.markdown("### 📋 Record Preview (before sending to Salesforce)")
+    st.write({
+        "Auto Number": "Will be generated in Salesforce",
+        "Captured Weight": f"{weight} g",
+        "Captured At": captured_at,
+        "Snapshot Image": "Attached" if image_url else "Not available",
+        "Device ID": device_id,
+        "Status": status
+    })
+
+    # ✅ Encode for Salesforce
     encoded_weight = urllib.parse.quote(str(weight))
     encoded_device = urllib.parse.quote(device_id)
     encoded_image_url = urllib.parse.quote(image_url)
@@ -43,5 +57,6 @@ if img_data:
         f"weight_logger_page?WeightInput={encoded_weight}&DeviceID={encoded_device}&ImageURL={encoded_image_url}"
     )
 
+    # ✅ Show Salesforce link
     st.markdown("### 📤 Send to Salesforce")
     st.markdown(f"[✅ Click here to confirm and log in Salesforce]({salesforce_url})", unsafe_allow_html=True)