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import gradio as gr |
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import numpy as np |
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from PIL import Image |
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import requests |
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import hopsworks |
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import joblib |
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project = hopsworks.login(api_key_value="0rdWXlLgEd3mkGOg.iRZ7TtAkWGPlJHNQcAEph6Qbokoaq7QTBRI9ckwWUki8tIYGyBvrKhJvtLoUOGQ4") |
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fs = project.get_feature_store() |
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mr = project.get_model_registry() |
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model = mr.get_model("xgboost_model", version=1) |
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model_dir = model.download() |
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model = joblib.load(model_dir + "/model.pkl") |
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def forecast(): |
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x = 0 |
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return 10 |
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demo = gr.Interface( |
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fn=titanic, |
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title="Air Quality Prediction", |
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description="Get aqi value", |
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allow_flagging="never", |
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outputs=gr.Textbox(label="Result: ")) |
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demo.launch() |
