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import gradio as gr | |
from transformers import pipeline | |
# Load your model from Hugging Face Hub | |
pipe = pipeline("text-classification", model="rbarac/open-rotor-copilot") # Or your exact model/task | |
def analyze_text_input(input_str): | |
# Input_str could be: "gyro_std=123.4, vbat_drop=0.91, ..." etc. | |
result = pipe(input_str) | |
return result[0]["label"] | |
iface = gr.Interface( | |
fn=analyze_text_input, | |
inputs=gr.Textbox(label="Feature string", placeholder="gyro_std=123.4, vbat_drop=0.91, ..."), | |
outputs=gr.Textbox(label="Detected Issue / Reason"), | |
title="Open Rotor Copilot (Single Example)", | |
description="Paste a windowed feature string and get detected issue & explanation." | |
) | |
if __name__ == "__main__": | |
iface.launch() |