Update app.py

app.py

@@ -1,5 +1,4 @@
 import gradio as gr
-from IPython.display import IFrame
 from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
 
 model_name = "NimaKL/FireWatch_tiny_75k"
@@ -20,25 +19,21 @@ custom_style = """
     }
 """
 
-# Define the function to display the Google Sheets document
-def show_sheet():
-    return IFrame("https://docs.google.com/spreadsheets/d/1b2aAZ8ue5NI7hZ-MiNc8y4dFthbrRiXlsaEeYSHgNCM/edit?usp=sharing", width=800, height=600)
+# Define a function to generate HTML for embedding the Google Sheets document
+def get_sheet_html():
+    return f'<iframe src="https://docs.google.com/spreadsheets/d/1b2aAZ8ue5NI7hZ-MiNc8y4dFthbrRiXlsaEeYSHgNCM/preview" width="640" height="480"></iframe>'
 
 io = gr.Interface(
     fn=predict,
     inputs="text",
     outputs="text",
     title="FireWatch",
-    description="Predict whether a data row describes a fire hazard or not.",
+    description="Predict whether a data row describes a fire hazard or not. \
+    <br><br>Here is a <a href='https://docs.google.com/spreadsheets/d/1b2aAZ8ue5NI7hZ-MiNc8y4dFthbrRiXlsaEeYSHgNCM/preview'>Google Sheets document</a> containing sample data.",
     output_description="Prediction",
     examples=[['-26.76123, 147.15512, 393.02, 203.63'], ['-26.7598, 147.14514, 361.54, 79.4'], ['-25.70059, 149.48932, 313.9, 5.15'], ['-24.4318, 151.83102, 307.98, 8.79'], ['-23.21878, 148.91298, 314.08, 7.4'], ['7.87518, 19.9241, 316.32, 39.63'], ['-20.10942, 148.14326, 314.39, 8.8'], ['7.87772, 19.9048, 304.14, 13.43'], ['-20.79866, 124.46834, 366.74, 89.06']],
-    output_component_names=["Prediction"],
     theme="Streamlit",
-    css=custom_style,
-    article="<h2>FireWatch App</h2><p>This app predicts whether a data row describes a fire hazard or not. The prediction is based on a machine learning model that has been trained on a dataset of data rows.</p><h2>Data Rows Sheet</h2>"
+    css=custom_style
 )
 
-# Add the IFrame component to the app
-io.add_component("Sample Data Sheet", gr.outputs.HTML, show_sheet)
-
 io.launch()