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
if "image_data" not in st.session_state:
    st.session_state.image_data = None
if "input_mode" not in st.session_state:
    st.session_state.input_mode = "Camera"
if "camera_key" not in st.session_state:
    st.session_state.camera_key = str(uuid.uuid4())

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

# Clear/reset image
if st.button("🔁 Clear / Retake Photo"):
    st.session_state.image_data = None
    st.session_state.camera_key = str(uuid.uuid4())

# Get image input
uploaded_image = None

if st.session_state.image_data is None:
    if st.session_state.input_mode == "Camera":
        uploaded_image = st.camera_input("📷 Capture the weight display", key=st.session_state.camera_key)
    else:
        uploaded_image = st.file_uploader("📁 Upload an image of the weight display", type=["jpg", "jpeg", "png"])

    if uploaded_image:
        st.session_state.image_data = uploaded_image

# Process image
if st.session_state.image_data:
    st.success("✅ Image received successfully!")

    # Convert to PIL image
    try:
        image_bytes = st.session_state.image_data.read() if hasattr(st.session_state.image_data, 'read') else st.session_state.image_data.getvalue()
        image = Image.open(io.BytesIO(image_bytes))
    except Exception as e:
        st.error("❌ Failed to load image.")
        st.stop()

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

    # Size check
    if len(image_bytes) > 5 * 1024 * 1024:
        st.error("❌ Image too large (>5MB). Please upload a smaller image.")
        st.stop()

    # OCR Extraction
    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)}%)")

        # Generate Salesforce URL
        device_id = "BAL-001"
        image_url = ""  # You can upload to S3 or Salesforce Files if needed

        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)

    # Retake or upload another
    if st.button("🔁 Retake / Upload Another"):
        st.session_state.image_data = None
        st.session_state.camera_key = str(uuid.uuid4())