finished app no frills

app.py

@@ -23,31 +23,31 @@ Original file is located at
 """
 
 def train_and_inference(api_key, ontology_id, model_run_id):
-    st.write('thisisstarting')
+    # st.write('thisisstarting')
     api_key = api_key # insert Labelbox API key
     ontology_id = ontology_id # get the ontology ID from the Settings tab at the top left of your model run
     model_run_id = model_run_id #get the model run ID from the settings gear icon on the right side of your Model Run
-    st.write('1')
+    # st.write('1')
     import pydantic
     st.write(pydantic.__version__)
 
     import numpy as np
-    st.write('2')
+    # st.write('2')
     import tensorflow as tf
-    st.write('3')
+    # st.write('3')
     from tensorflow.keras import layers
-    st.write('4')
+    # st.write('4')
     from tensorflow.keras.models import Sequential
-    st.write('5')
+    # st.write('5')
     from tensorflow.keras.preprocessing.image import ImageDataGenerator
-    st.write('6')
+    # st.write('6')
     import os
-    st.write('7')
+    # st.write('7')
     import labelbox
-    st.write('zat')
+    # st.write('zat')
     from labelbox import Client
-    st.write('8')
-    st.write('9')
+    # st.write('8')
+    # st.write('9')
     import numpy as np
     import tensorflow as tf
     from tensorflow.keras import layers
@@ -80,7 +80,7 @@ def train_and_inference(api_key, ontology_id, model_run_id):
     import uuid
     import time
     import requests
-    st.write('madeithrhougtheimports')
+    # st.write('imports')
 
     """Connect to labelbox client
     Define Model Variables
@@ -192,14 +192,15 @@ def train_and_inference(api_key, ontology_id, model_run_id):
                 loss='categorical_crossentropy',
                 metrics=['accuracy'])
 
-
+    st.write("training")
     history = model.fit(
         train_ds,
         validation_data=validation_ds,
         epochs=EPOCHS
     )
 
-    """#Run Inference on Model run Datarows"""
+    """Run Inference on Model run Datarows"""
+    st.write('running Inference')
 
     import numpy as np
     import requests
@@ -266,15 +267,15 @@ def train_and_inference(api_key, ontology_id, model_run_id):
 
     st.write(prediction_import.errors == [])
     if prediction_import.errors == []:
-        return "you're a wizard harry"
+        return "Model Trained and inference ran successfully"
 
-st.title("Key Input and Button Example")
+st.title("Enter Applicable IDs and keys below")
 api_key = st.text_input("Enter your api key:", type="password")
 model_run_id = st.text_input("Enter your model run ID:")
 ontology_id = st.text_input("Enter your ontology ID:")
 
 if st.button("Train and run inference"):
-    st.write('letsgo')
+    st.write('Starting Up...')
         # Check if the key is not empty
     if api_key + model_run_id + ontology_id:
         result = train_and_inference(api_key, ontology_id, model_run_id)