Update app.py

app.py

@@ -83,8 +83,12 @@ total_gpu = sample_data['total']['total']
 used_gpu = sample_data['total']['used']
 timestamp_list = []
 
+
 name_list = []
 timestamp_gpu_data = []
+timestamp_inference_data = []
+timestamp_list_date = []
+
 for block in sample_data['chain']:
     timestamp_list.append(block['timestamp'] )
     for t in block['transactions']:
@@ -93,13 +97,20 @@ for block in sample_data['chain']:
                 name_list.append(t['id'])
 
 timestamp_gpu_data = [[0 for _ in range(len(name_list))]]
+timestamp_inference_data = [sample_data['chain'][0]['timestamp']]
 for block in sample_data['chain']:
     temp = timestamp_gpu_data[int(block['index']) - 1]
+    if strftime('%Y-%m-%d', localtime( timestamp_list_date[-1] )) != strftime('%Y-%m-%d', localtime( block['timestamp'] )):
+        timestamp_list_date.append(block['timestamp'])
+        timestamp_inference_data.append(0)
+    
     for t in block['transactions']:
         if t['kind'] == "add":
             temp[name_list.index(t['id'])] += int(t['data'])
         elif t['kind'] == "out":
             temp[name_list.index(t['id'])] = 0
+        elif:
+            timestamp_inference_data[-1] += 1
     timestamp_gpu_data.append(copy.deepcopy(temp))
 timestamp_gpu_data = timestamp_gpu_data[0:-1]
 col1, col2, col3 = st.columns(3)
@@ -113,7 +124,10 @@ last_timestamp = strftime('%Y-%m-%d %I:%M:%S %p', localtime( sample_data['chain'
 st.area_chart(chart_data)
 st.caption(f'last updated in timestamp {last_timestamp}.')
 
-
+for d in timestamp_list_date:
+    d = strftime('%Y-%m-%d', localtime( d ))
+call_data = pd.DataFrame(timestamp_inference_data, columns = ["inference call"], index = timestamp_list_date)
+st.area_chart(call_data)
 
 class BubbleChart:
     def __init__(self, data, bubble_spacing=0, n_bins=5):