| import gradio as gr | |
| import numpy as np | |
| from PIL import Image | |
| import requests | |
| import hopsworks | |
| import joblib | |
| import os | |
| project = hopsworks.login(api_key_value="B8TDkmcSyPyWFM2o.YuXEbXM7MUFk5gdBXFXsbMz24uZipqY4BttbZ9wIoZ0cn9vQd4bSWgj57vDGXqdh") | |
| mr = project.get_model_registry() | |
| model = mr.get_model("iris_modal2", version=1) | |
| model_dir = model.download() | |
| model = joblib.load(model_dir + "/air_model2.pkl") | |
| def forecast(): | |
| x = [ 0. , 24 , -0.68645433, -0.06804887, -0.31264014, | |
| -0.13749569, -0.32063957, -0.2942814 , -0.18460245, -0.41253886, | |
| 0.06395449, 0.71276574, -0.36466156, -1.03879548, -0.65985627, | |
| 0 , 0 , 0.12254366, 0.39172671, 0.34205118, | |
| 0.21383452, -1.0216134 , 0.40277851, -0.34577169, -0.36832646, | |
| -0.7210296 , 0 ] | |
| res = model.predict(np.asarray(x).reshape(-1, 1)) | |
| return model_dir | |
| demo = gr.Interface( | |
| fn=forecast, | |
| title="Air Quality Prediction", | |
| description="Get aqi value", | |
| allow_flagging="never", | |
| inputs=[], | |
| outputs=gr.Textbox(label="Result: ")) | |
| demo.launch() |