import gradio as gr
import pandas as pd
import cloudinary
import cloudinary.uploader
from datetime import datetime
import uuid
from io import BytesIO
from PIL import Image

# Load Excel codes
df = pd.read_excel("RMSheet1.xlsx")
CODES = df["Row Labels"].dropna().astype(str).tolist()

# Cloudinary config (change this to your keys)
cloudinary.config(
    cloud_name="diih3ajsp",       # ← Replace
    api_key="174463748698396",             # ← Replace
    api_secret="Py_vc_NwOSmdmMKUL5M2n2h_TNk"        # ← Replace
)

def upload_to_cloudinary(img, code):
    if img is None or code is None:
        return "❗ Upload image and select code"

    # Generate filename
    filename = f"{code}_{datetime.now().strftime('%Y%m%d_%H%M%S')}_{uuid.uuid4().hex[:6]}.jpg"

    # Save image to buffer
    buffer = BytesIO()
    img.save(buffer, format="JPEG")
    buffer.seek(0)

    # Upload to Cloudinary
    result = cloudinary.uploader.upload(buffer, public_id=filename, folder="multiuser_uploads", resource_type="image")
    
    return f"✅ Uploaded: [View Image]({result['secure_url']})"

# Gradio UI
gr.Interface(
    fn=upload_to_cloudinary,
    inputs=[
        gr.Image(type="pil", label="Capture or Upload Image"),
        gr.Dropdown(choices=CODES, label="Select from column: #code")
    ],
    outputs="markdown",
    title="Cloudinary Image Logger"
).launch()

# Gradio UI with searchable dropdown
gr.Interface(
    fn=upload_to_cloudinary,
    inputs=[
        gr.Image(type="pil", label="Capture or Upload Image"),
        gr.Dropdown(choices=CODES, label="Select from column: #code", filterable=True)
    ],
    outputs="markdown",
    title="Cloudinary Image Logger"
).launch()