src/streamlit_app.py

import streamlit as st
from PIL import Image
import io
import uuid
import urllib.parse
from ocr_engine import extract_weight_from_image  # Your OCR logic

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

# Unique key for camera input refresh
if "camera_key" not in st.session_state:
    st.session_state.camera_key = str(uuid.uuid4())

# UI - Input type selector
input_method = st.radio("📸 Choose Input Method", ["Camera", "Upload"], horizontal=True)

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

# Initialize variables
image_bytes = None
image = None

# ----------------- CAMERA -----------------
if input_method == "Camera":
    cam_image = st.camera_input("📷 Capture the weight display", key=st.session_state.camera_key)
    if cam_image is not None:
        image_bytes = cam_image.getvalue()

# ----------------- UPLOAD -----------------
elif input_method == "Upload":
    uploaded_image = st.file_uploader("📁 Upload image (JPG, PNG)", type=["jpg", "jpeg", "png"])
    if uploaded_image is not None:
        image_bytes = uploaded_image.read()

# ----------------- PROCESS IMAGE -----------------
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). Try a smaller file.")
            st.stop()

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

        st.write(f"🛠️ DEBUG: weight = {weight}, confidence = {confidence}")

        if not weight or confidence < 80:
            st.error(f"⚠️ OCR confidence too low ({int(confidence)}%). Please try again.")
        else:
            st.success(f"✅ Detected Weight: {weight} g (Confidence: {int(confidence)}%)")

            # Salesforce link
            device_id = "BAL-001"
            image_url = ""  # Optional if you host it

            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 here to confirm and log in Salesforce]({salesforce_url})", unsafe_allow_html=True)

    except Exception as e:
        st.error("❌ Failed to read/process the image.")
        st.exception(e)