Update app.py

app.py

@@ -67,6 +67,50 @@ import pandas as pd
 import os
 
 
+def gauge_chart() -> alt.Chart:
+    # Assuming obtain_source_target_datasets() returns a tuple where the first item is the dataset
+    source_dataset, _ = obtain_source_target_datasets()
+    total_records = int(os.getenv("TARGET_RECORDS"))  # This should be the total number of records you want to annotate.
+    annotated_records = len(source_dataset)  # This is the number of records already annotated.
+    pending_records = total_records - annotated_records  # Calculate the pending records.
+
+    # Prepare data for the gauge chart
+    gauge_data = pd.DataFrame({
+        'category': ['Annotated', 'Remaining'],
+        'value': [annotated_records, pending_records]
+    })
+
+    # The background of the gauge
+    base = alt.Chart(pd.DataFrame({'value': [total_records], 'category': ['Total']})).mark_bar(
+        color='#e0e0e0', size=40
+    ).encode(
+        alt.X('value:Q', scale=alt.Scale(domain=[0, total_records]), title='Record Count'),
+        alt.Y('category:N', axis=alt.Axis(title=''))
+    )
+
+    # The value part of the gauge
+    value_bar = alt.Chart(gauge_data).mark_bar(size=40).encode(
+        alt.X('value:Q'),
+        alt.Y('category:N', axis=alt.Axis(title='')),
+        alt.Color('category:N', scale=alt.Scale(domain=['Annotated', 'Remaining'], range=['#28a745', '#dcdcdc']))
+    )
+
+    # Combine the bars to create a gauge effect
+    chart = alt.layer(base, value_bar).properties(
+        title='Progress Towards Goal',
+        width=700,
+        height=100
+    )
+
+    # Add a text label for the current value
+    text = alt.Chart(pd.DataFrame({'value': [annotated_records + pending_records/2], 'text': [f'{annotated_records} / {total_records}']})).mark_text(
+        align='center', baseline='middle', fontSize=16, fontWeight='bold', dy=-30
+    ).encode(
+        x='value:Q',
+        text='text:N'
+    )
+
+    return (chart + text)
 
 def progress_bar_chart() -> alt.Chart:
     source_dataset, _ = obtain_source_target_datasets()
@@ -77,7 +121,7 @@ def progress_bar_chart() -> alt.Chart:
 
     # Create a DataFrame for the progress bar data.
     progress_data = pd.DataFrame({
-        'status': ['Completed', 'Pending'],
+        'status': ['Pending','Completed'],
         'percentage': [percentage_complete, 100 - percentage_complete],
         'actual': [pending_records, annotated_records]
     })