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import gradio as gr | |
import os | |
import pandas as pd | |
import mindsdb_sdk | |
# Connect to cloud server | |
email = os.environ.get('email') | |
passw = os.environ.get('passw') | |
# Connect to MindsDB Pro | |
server = mindsdb_sdk.connect('https://cloud.mindsdb.com', login=email, password=passw, is_managed=True) | |
project = server.get_project("mindsdb") | |
model = project.list_models()[0] | |
def classify_text(text): | |
# Classify text using the loaded model | |
var = {"Text": text} | |
data = pd.DataFrame(var, index=[0]) | |
result = model.predict(data) | |
label = result['topic'] | |
#score = result['score'] | |
return f"Label: {label}" | |
# Create Gradio interface | |
iface = gr.Interface( | |
fn=classify_text, | |
inputs=gr.inputs.Textbox(label="Enter text to classify"), | |
outputs="text", | |
title="Identify spoiler comments with zero-shot text classification", | |
description="Input a comment here" | |
) | |
# Launch the interface | |
iface.launch() |