Update streamlit_dashboard.py

streamlit_dashboard.py

@@ -139,57 +139,65 @@ def save_system_health(mongo_status, chroma_status, api_status, llm_status):
 
 def plot_status(df_service, title, container):
     """
-    Plots the health status of a single service over time using a step chart.
+    Plots the health status of a single service over time.
+    Uses a step chart if there are 2+ points, otherwise just a marker for single points.
     """
     if df_service.empty:
         container.info(f"No data available for {title}.")
         return
 
-    # Ensure data is sorted by Time for correct line/step plotting
-    df_service = df_service.sort_values('Time')
+    # Ensure data is sorted by Time for correct line/step plotting and reset index
+    df_service = df_service.sort_values('Time').reset_index(drop=True)
+
+    # Determine line_shape based on number of data points to avoid artifacts with single points
+    # 'linear' for a single point with markers=True results in just the marker being shown.
+    effective_line_shape = 'hv' if len(df_service) >= 2 else 'linear'
 
     fig = px.line(
         df_service,
         x="Time",
         y="StatusNumeric",
-        color="ReadableStatus",
+        color="ReadableStatus",  # Color lines/markers by "LIVE" or "DISCONNECTED"
         title=title,
-        color_discrete_map={
+        color_discrete_map={     # Ensure "LIVE" is green and "DISCONNECTED" is red
             "LIVE": "green",
             "DISCONNECTED": "red"
         },
-        labels={"StatusNumeric": "Status"},
-        line_shape='hv',  # Horizontal-then-Vertical step chart. 'vh' is also an option.
-        markers=True      # Show markers at each data point
+        labels={"StatusNumeric": "Status", "ReadableStatus": "Legend"}, # Adjust legend title if shown
+        line_shape=effective_line_shape,
+        markers=True  # Always show markers at data points
     )
 
-    fig.update_traces(
-        marker=dict(size=8), # Adjust marker size
-        line=dict(width=3)   # Adjust line width
-    )
+    # Adjust marker and line properties based on the number of points
+    if len(df_service) == 1:
+        fig.update_traces(
+            marker_size=12,
+            line_width=0 # Ensure no line is drawn for a single point, only marker
+        )
+    else:  # len(df_service) > 1
+        fig.update_traces(
+            marker_size=8,
+            line_width=3 # Width for the step line
+        )
 
     fig.update_layout(
         yaxis=dict(
             tickmode="array",
             tickvals=[0, 1],
             ticktext=["DISCONNECTED", "LIVE"],
-            range=[-0.1, 1.1], # Keep a little padding
-            zeroline=False, # No need for zeroline with custom ticks and step
+            range=[-0.2, 1.2],  # Add some padding to y-axis
+            zeroline=False,     # Zeroline often not needed with these custom ticks
         ),
         xaxis_title="Time",
-        yaxis_title="Status", # Redundant with labels but good practice
-        # Set x-axis range to ensure all charts show the same window,
-        # even if one service has no recent data.
-        xaxis_range=[
-            datetime.now() - timedelta(hours=3, minutes=5), # Add a little buffer
-            datetime.now() + timedelta(minutes=5)            # Add a little buffer
+        yaxis_title="Status",
+        xaxis_range=[ # Ensure consistent 3-hour window across all charts
+            datetime.now() - timedelta(hours=3, minutes=5), # 5 min buffer past
+            datetime.now() + timedelta(minutes=5)            # 5 min buffer future
         ],
-        showlegend=False, # Keep legend hidden as title is descriptive enough
-        margin=dict(l=20, r=20, t=50, b=20) # Adjust margins
+        showlegend=False,  # Legend is redundant given the chart titles and y-axis
+        margin=dict(l=40, r=20, t=60, b=40) # Adjust margins for titles/labels
     )
 
-    container.plotly_chart(fig, use_container_width=True)
-
 
 def main():
     st_autorefresh(interval=10_000, key="health_watch")