app.py

import gradio as gr
from PIL import Image
import hopsworks


project = hopsworks.login(project="ID2223_L2")
fs = project.get_feature_store()

predictions_fg = fs.get_feature_group(name="weather_predictions", version=1)
query = predictions_fg.select_all()
predictions_df = query.read(read_options={"use_hive": True})

predictions_df = predictions_df.sort_values(by=["timestamp_local"])

print(predictions_df)
print(predictions_df.tail(4))

dataset_api = project.get_dataset_api()

dataset_api.download("Resources/weather/last_prediction.txt")
dataset_api.download("Resources/weather/prediction_graph.png")

def latest_prediction(path):
   f = open(path,"r")
   date = f.readline()
   temp = f.readline()
   f.close()

   return "Prediction at time   : "+date+"\n\nPredicted temperature:"+temp

with gr.Blocks() as demo:
    with gr.Row():
      with gr.Column():
          gr.Label("Latest Predicted Forecast/n/n"+latest_prediction("last_prediction.txt"))
          #gr.Markdown(latest_prediction("last_prediction.txt"))
      with gr.Column():          
          gr.Label("Graph of Recent Predictions")      
          input_img = gr.Image("prediction_graph.png", elem_id="temperature-graph")
    with gr.Row():
      with gr.Column():
          gr.Label("Recent Prediction History")
          gr.DataFrame(predictions_df, interactive=False)    

demo.launch()