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import gradio as gr
import hopsworks
import joblib
import pandas as pd
import numpy as np
import folium
import json
import time
from datetime import timedelta, datetime
from branca.element import Figure
from functions import decode_features
#import functions
def greet(total_pred_days):
print("hi")
project = hopsworks.login()
print("connected")
#api = project.get_dataset_api()
# The latest available data timestamp
start_time = 1649196000000
# end_time = 1670972400000
#start_date = datetime.now() - timedelta(days=1)
#start_time = int(start_date.timestamp()) * 1000
print("Time Stamp Set. ")
print("latest_date")
mr=project.get_model_registry()
model = mr.get_model("temp_model", version=2)
model_dir=model.download()
model1 = mr.get_model("tempmax_model", version=2)
model_dir1=model1.download()
model2 = mr.get_model("tempmin_model", version=2)
model_dir2=model2.download()
model = joblib.load(model_dir + "/model_temp.pkl")
model1 = joblib.load(model_dir1 + "/model_tempmax.pkl")
model2 = joblib.load(model_dir2+ "/model_tempmin.pkl")
print("temp_model is now right")
fs = project.get_feature_store()
print("get the store")
feature_view = fs.get_feature_view(
name = 'weather_fv',
version = 1
)
print("get the fv")
X = feature_view.get_batch_data(start_time=start_time)
print("Data batched")
latest_date_unix = str(X.datetime.values[0])[:10]
latest_date = time.ctime(int(latest_date_unix))
X = X.drop(columns=["datetime"]).fillna(0)
preds = model.predict(X)
preds1= model1.predict(X)
preds2= model2.predict(X)
# cities = [city_tuple[0] for city_tuple in cities_coords.keys()]
next_day_date = datetime.today() + timedelta(days=1)
next_day = next_day_date.strftime ('%d/%m/%Y')
str1 = ""
if(total_pred_days == ""):
return "Empty input"
count = int(total_pred_days)
if count > 20:
str1 += "Warning: 20 days at most. " + '\n'
count = 20
if count <0:
str1 = "Invalid input."
return str1
for x in range(count):
if (x != 0):
str1 += (datetime.now() + timedelta(days=x)).strftime('%Y-%m-%d') + " predicted temperature: " +str(int(preds[len(preds) - count + x]))+ " predicted max temperature: " +str(int(preds1[len(preds1) - count + x]))+ " predicted min temperature: " +str(int(preds2[len(preds2) - count + x]))+"\n"
#print(str1)
return str1
demo = gr.Interface(fn=greet, inputs = "text", outputs="text")
if __name__ == "__main__":
demo.launch()
'''
def greet(total_pred_days):
project = hopsworks.login()
#api = project.get_dataset_api()
fs = project.get_feature_store()
feature_view = fs.get_feature_view(
name = 'weather_fv',
version = 1
)
# The latest available data timestamp
start_time = 1635112800000
#start_date = datetime.now() - timedelta(days=1)
#start_time = int(start_date.timestamp()) * 1000
X = feature_view.get_batch_data(start_time=start_time)
latest_date_unix = str(X.datetime.values[0])[:10]
latest_date = time.ctime(int(latest_date_unix))
model = get_model(project=project,
model_name="temp_model",
evaluation_metric="f1_score",
sort_metrics_by="max")
model1 = get_model1(project=project,
model_name="tempmax_model",
evaluation_metric="f1_score",
sort_metrics_by="max")
model2 = get_model2(project=project,
model_name="tempmin_model",
evaluation_metric="f1_score",
sort_metrics_by="max")
X = X.drop(columns=["datetime"]).fillna(0)
preds = model.predict(X)
preds1= model1.predict(X)
preds2= model2.predict(X)
# cities = [city_tuple[0] for city_tuple in cities_coords.keys()]
next_day_date = datetime.today() + timedelta(days=1)
next_day = next_day_date.strftime ('%d/%m/%Y')
str1 = ""
if(total_pred_days == ""):
return "Empty input"
count = int(total_pred_days)
if count > 20:
str1 += "Warning: 20 days at most. " + '\n'
count = 20
if count <0:
str1 = "Invalid input."
return str1
for x in range(count):
if (x != 0):
str1 += (datetime.now() + timedelta(days=x)).strftime('%Y-%m-%d') + " predicted temperature: " +str(int(preds[len(preds) - count + x]))+ " predicted max temperature: " +str(int(preds1[len(preds1) - count + x]))+ " predicted min temperature: " +str(int(preds2[len(preds2) - count + x]))+"\n"
#print(str1)
return str1
demo = gr.Interface(
fn=greet,
inputs=gr.Slider(label="Days of prediction (start from tomorrow)", value=1, minimum=1, maximum=20, step=1),
outputs=gr.outputs.Textbox(label="Prediction results"),
)
if __name__ == "__main__":
demo.launch()
''' |