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from transformers import pipeline
import gradio as gr
# Initialize the pipeline with TensorFlow
pipe = pipeline("text-classification", model="ZachBeesley/Spam-Detector", framework="tf")
# Function to process the input text and return the predicted label
def predict(text):
try:
# Use the pipeline to classify the text
result = pipe(text)
# Extract the predicted label and confidence score
label = result[0]["label"]
confidence = result[0]["score"]
# Return the result
return f"Predicted label: {label}\nConfidence: {confidence:.2f}"
except Exception as e:
# Handle errors
return f"Error: {str(e)}"
# Create the Gradio interface
iface = gr.Interface(
fn=predict,
inputs=gr.Textbox(label="Email Text", placeholder="Paste your email text here..."),
outputs="text",
title="Spam Email Detector",
description="Enter an email and find out if it's spam or not."
)
# Launch the interface
iface.launch()
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