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")

# ✅ Flag to reset camera input
if "retake_photo" not in st.session_state:
    st.session_state.retake_photo = False

# 🔘 Retake Photo or Clear button logic
def clear_photo():
    st.session_state.retake_photo = True

st.button("🔁 Clear / Retake Photo", on_click=clear_photo)

# ✅ Skip camera this run, and reset for next
if st.session_state.retake_photo:
    st.session_state.retake_photo = False  # reset the flag
    st.stop()  # stop here → camera will appear on next run

# 📷 Show camera input
img_data = st.camera_input("📷 Capture the weight display")

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}")

    # ❌ Low confidence — offer retake
    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.retake_photo = True
            st.stop()
        st.stop()

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

    device_id = "BAL-001"
    image_url = ""  # Optional hosted image URL

    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)