app.py

import gradio as gr
from transformers import pipeline

# This is the key line:
# It loads your private model from your *other* repository.
pipe = pipeline(
    "text-classification",
    model="kxshrx/infrnce-bert-classifier"
)

def classify_log(log_text):
    # This function runs the classification.
    results = pipe(log_text, top_k=None)
    # We format the result into a simple dictionary.
    return {item['label']: item['score'] for item in results[0]}

# This creates a simple web UI for testing and, more importantly,
# an API endpoint that we can call.
gr.Interface(
    fn=classify_log,
    inputs=gr.Textbox(lines=5, label="Log Entry"),
    outputs=gr.Label(num_top_classes=6),
    title="Infrnce Private Log Classifier API"
).launch()