from fastai.vision.all import *
import gradio as gr

# 1. Load the model
learn = load_learner('hydration_model.pkl')

# 2. Get the labels from the model automatically
categories = learn.dls.vocab

# 3. Define the function
def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))

# 4. Build the interface
image = gr.Image(type="pil") # Allow uploading or taking a photo
label = gr.Label()
examples = [] # You can add example filenames here later if you upload images

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label)
intf.launch(inline=False)