# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.

# %% auto 0
__all__ = ['model', 'tokz', 'trainer', 'intf', 'tok_func', 'classify_message']

# %% app.ipynb 1
import numpy as np
import pandas as pd
import gradio as gr
from datasets import Dataset
from transformers import AutoModelForSequenceClassification, AutoTokenizer, Trainer

# %% app.ipynb 2
import warnings, logging
warnings.simplefilter('ignore')
logging.disable(logging.WARNING)

# %% app.ipynb 3
model = AutoModelForSequenceClassification.from_pretrained("./spam_model/")
tokz = AutoTokenizer.from_pretrained("./spam_model/")
trainer = Trainer(model, tokenizer=tokz)

# %% app.ipynb 5
def tok_func(x):
    return tokz(x["input"])

# %% app.ipynb 7
def classify_message(text):
    input_ds = Dataset.from_pandas(pd.DataFrame([text], columns=['input'])).map(tok_func, batched=True)
    spam_prob = np.clip(trainer.predict(input_ds).predictions.astype(float), 0, 1)[0, 0]
    return f'{100*spam_prob:.1f}% probability being Spam'

# %% app.ipynb 8
intf = gr.Interface(fn=classify_message, inputs='text', outputs='text')
intf.launch(inline=False)