src/streamlit_app.py

import streamlit as st
from PIL import Image, UnidentifiedImageError
import io
import uuid
import urllib.parse
import pytz
from datetime import datetime
from ocr_engine import extract_weight_from_image  # your OCR function

# Setup
st.set_page_config(page_title="⚖️ Auto Weight Logger", layout="centered")
st.title("⚖️ Auto Weight Logger")

# IST timezone
ist = pytz.timezone('Asia/Kolkata')

# Session state
if "camera_key" not in st.session_state:
    st.session_state.camera_key = str(uuid.uuid4())

# Input method
input_mode = st.radio("📸 Select Input Method", ["Camera", "Upload"], horizontal=True)

# Reset
if st.button("🔁 Clear / Retake"):
    st.session_state.camera_key = str(uuid.uuid4())
    st.experimental_rerun()

image_bytes = None
image = None

# Camera input
if input_mode == "Camera":
    cam_photo = st.camera_input("📷 Take a photo of the weight display", key=st.session_state.camera_key)
    if cam_photo is not None:
        image_bytes = cam_photo.getvalue()

# Upload input
elif input_mode == "Upload":
    uploaded_file = st.file_uploader("📁 Upload a JPG/PNG image", type=["jpg", "jpeg", "png"])
    if uploaded_file is not None:
        try:
            image_bytes = uploaded_file.read()
        except Exception as e:
            st.error("❌ Failed to read uploaded file.")
            st.exception(e)

# Image display and OCR
if image_bytes:
    try:
        image = Image.open(io.BytesIO(image_bytes))
        st.image(image, caption="📸 Snapshot", use_column_width=True)

        if len(image_bytes) > 5 * 1024 * 1024:
            st.error("❌ Image too large (>5MB).")
            st.stop()

        with st.spinner("🔍 Extracting weight using OCR..."):
            weight, confidence = extract_weight_from_image(image)

        if not weight or confidence < 80:
            st.error(f"⚠️ OCR Confidence too low ({int(confidence)}%). Try again.")
        else:
            # IST time
            captured_time = datetime.now(ist).strftime("%Y-%m-%d %I:%M:%S %p")

            st.success("✅ OCR Success")
            st.markdown(f"### 📦 Captured Weight: `{weight} g`")
            st.markdown(f"### 🕒 Captured At (IST): `{captured_time}`")

            # Salesforce link
            device_id = "BAL-001"
            image_url = ""  # optional if stored externally

            salesforce_url = (
                "https://autoweightlogger-dev-ed.my.salesforce-sites.com/"
                f"weight_logger_page?WeightInput={urllib.parse.quote(str(weight))}"
                f"&DeviceID={urllib.parse.quote(device_id)}&ImageURL={urllib.parse.quote(image_url)}"
            )

            st.markdown("### 📤 Send to Salesforce")
            st.markdown(f"[✅ Click to Log in Salesforce]({salesforce_url})", unsafe_allow_html=True)

    except UnidentifiedImageError:
        st.error("❌ Unsupported or invalid image format.")
    except Exception as e:
        st.error("❌ Unexpected error processing image.")
        st.exception(e)