src/streamlit_app.py

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

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

# ------------------------------
# ✅ Session state management
# ------------------------------
if "show_camera" not in st.session_state:
    st.session_state.show_camera = True

# 🔘 Clear or Retake Button pressed
if st.button("🔁 Clear / Retake Photo"):
    st.session_state.show_camera = False  # hide camera temporarily
    st.rerun()

# 🔄 Reset camera on next run
if not st.session_state.show_camera:
    st.session_state.show_camera = True
    st.rerun()

# ------------------------------
# 📷 Show camera input
# ------------------------------
img_data = None
if st.session_state.show_camera:
    img_data = st.camera_input("📷 Capture the weight display")

# ------------------------------
# ✅ Process if image is captured
# ------------------------------
if img_data:
    st.success("✅ Image captured successfully!")

    if len(img_data.getvalue()) > 5 * 1024 * 1024:
        st.error("❌ Image too large (>5MB). Please try again.")
        st.stop()

    image = Image.open(img_data)
    st.image(image, caption="📸 Snapshot", use_column_width=True)

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

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

    # ❌ Handle low confidence
    if not weight or confidence < 80:
        st.error(f"⚠️ OCR confidence too low ({int(confidence)}%). Please retake the photo.")
        if st.button("🔁 Retake Photo"):
            st.session_state.show_camera = False
            st.rerun()
        st.stop()

    # ✅ Success
    st.success(f"✅ Detected Weight: {weight} g (Confidence: {int(confidence)}%)")

    # Salesforce URL setup
    device_id = "BAL-001"
    image_url = ""  # Optional: add image hosting logic later

    encoded_weight = urllib.parse.quote(str(weight))
    encoded_device = urllib.parse.quote(device_id)
    encoded_image_url = urllib.parse.quote(image_url)

    salesforce_url = (
        "https://autoweightlogger-dev-ed.my.salesforce-sites.com/"
        f"weight_logger_page?WeightInput={encoded_weight}&DeviceID={encoded_device}&ImageURL={encoded_image_url}"
    )

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