src/streamlit_app.py

import streamlit as st
from PIL import Image
from ocr_engine import extract_weight_from_image
import urllib.parse
import uuid
import io

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

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

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

# Clear button
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_method == "Camera":
    camera_image = st.camera_input("📷 Capture the weight display", key=st.session_state.camera_key)
    if camera_image is not None:
        image_bytes = camera_image.getvalue()

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

# ----- IMAGE PROCESSING -----
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). Please use a smaller one.")
            st.stop()

        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 redirect link
            device_id = "BAL-001"
            image_url = ""  # Optional

            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 load or process the image.")
        st.exception(e)