trial

app.py

@@ -5,8 +5,8 @@ from pycaret.classification import *
 
 os.environ['MLFLOW_TRACKING_USERNAME'] = 'fandanabil1379'
 os.environ['MLFLOW_TRACKING_PASSWORD'] = 'dadc32f6246f307c2fe4928f3074068f628b79ba'
-os.environ["HF_HOME"] = '~/.cache/huggingface'
 
+@st.cache_data
 def convert_df(df):
    return df.to_csv(index=False).encode('utf-8')
 
@@ -23,18 +23,22 @@ def load_model():
    loaded_model = mlflow.sklearn.load_model(f"models:/{model_name}/{stage}")
    return loaded_model
 
-# load data
-uploaded_file = st.file_uploader("Choose a file", type={"csv"})
-if uploaded_file is not None:
-   # do prediction
-   df = pd.read_csv(uploaded_file)
-   model = load_model()
-   prediction = predict_model(model, df).drop(columns='Unnamed: 0')
-
-   # show the result
-   st.write(prediction)
-
-   # download the result
-   csv = convert_df(prediction)
-   if st.download_button('Download Prediction', csv, 'prediction.csv'):
-      st.write('Thanks for downloading!')
+@st.cache_data(experimental_allow_widgets=True)
+def prediction():
+   # load data
+   uploaded_file = st.file_uploader("Choose a file", type={"csv"})
+   if uploaded_file is not None:
+      # do prediction
+      df = pd.read_csv(uploaded_file)
+      model = load_model()
+      prediction = predict_model(model, df).drop(columns='Unnamed: 0')
+
+      # show the result
+      st.write(prediction)
+
+      # download the result
+      csv = convert_df(prediction)
+      if st.download_button('Download Prediction', csv, 'prediction.csv'):
+         st.write('Thanks for downloading!')
+
+prediction()

logs.log

@@ -157,3 +157,57 @@ Feature names unseen at fit time:
 2023-08-03 10:59:29,379:INFO:Preloading libraries
 2023-08-03 10:59:29,379:INFO:Set up data.
 2023-08-03 10:59:29,386:INFO:Set up index.
+2023-08-04 07:20:45,982:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2023-08-04 07:20:45,982:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2023-08-04 07:20:45,982:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2023-08-04 07:20:45,982:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2023-08-04 07:20:53,862:INFO:Initializing predict_model()
+2023-08-04 07:20:53,862:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x28219fd00>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib),
+         steps=[('combine',
+                 TransformerWrapper(transformer=TransformerWrapper(include=['ed'],
+                                                                   transformer=Combine()))),
+                ('remove outlier',
+                 TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))),
+                ('normalize',
+                 TransformerWrapper(transformer=TransformerWrapper(exclude=['ed',
+                                                                            'age'],
+                                                                   transformer=RobustScaler()))),
+                ('actual_estimator',
+                 LogisticRegression(C=8.956999999999999,
+                                    class_weight='balanced', max_iter=1000,
+                                    random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x282183310>)
+2023-08-04 07:20:53,862:INFO:Checking exceptions
+2023-08-04 07:20:53,862:INFO:Preloading libraries
+2023-08-04 07:20:53,864:INFO:Set up data.
+2023-08-04 07:20:53,873:INFO:Set up index.
+2023-08-04 07:22:16,503:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2023-08-04 07:22:16,503:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2023-08-04 07:22:16,503:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2023-08-04 07:22:16,503:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2023-08-04 07:23:22,156:INFO:Initializing predict_model()
+2023-08-04 07:23:22,157:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x1715802e0>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib),
+         steps=[('combine',
+                 TransformerWrapper(transformer=TransformerWrapper(include=['ed'],
+                                                                   transformer=Combine()))),
+                ('remove outlier',
+                 TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))),
+                ('normalize',
+                 TransformerWrapper(transformer=TransformerWrapper(exclude=['ed',
+                                                                            'age'],
+                                                                   transformer=RobustScaler()))),
+                ('actual_estimator',
+                 LogisticRegression(C=8.956999999999999,
+                                    class_weight='balanced', max_iter=1000,
+                                    random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x171536dc0>)
+2023-08-04 07:23:22,157:INFO:Checking exceptions
+2023-08-04 07:23:22,157:INFO:Preloading libraries
+2023-08-04 07:23:22,159:INFO:Set up data.
+2023-08-04 07:23:22,167:INFO:Set up index.