Update visuals.py

visuals.py

@@ -22,6 +22,7 @@ def create_progress_chart(log_data):
         scores = attempt.get("scores", {})
         values = [scores.get(cat, 0) for cat in categories]
         
+        # Close the loop for radar chart
         values += [values[0]]
         radar_categories = categories + [categories[0]]
         
@@ -67,6 +68,7 @@ def create_calibration_table(log_data):
         
         score = 0
         if isinstance(score_data, dict):
+             # Extract the specific metric score relevant to that Role
              if role == "Plant": 
                  score = score_data.get("Novelty", {}).get("score", 0)
              elif role == "Implementer": 
@@ -87,24 +89,28 @@ def create_cost_summary(log_data):
     Creates a Markdown summary of costs based on usage data found in the log.
     """
     if not log_data or "financial_report" not in log_data:
-        return "**No Financial Data Available**"
+        return "### ⚠️ Financial Data Unavailable\n*Could not retrieve usage statistics.*"
     
     fin = log_data["financial_report"]
-    total = fin.get("total_cost", 0)
-    calib = fin.get("calibration_cost", 0)
-    gen = fin.get("generation_cost", 0)
+    total = fin.get("total_cost", 0.0)
+    calib = fin.get("calibration_cost", 0.0)
+    gen = fin.get("generation_cost", 0.0)
     
     # Calculate Total Tokens
-    total_input = sum(u.get("input", 0) for u in fin.get("usage_breakdown", []))
-    total_output = sum(u.get("output", 0) for u in fin.get("usage_breakdown", []))
+    breakdown = fin.get("usage_breakdown", [])
+    total_input = sum(u.get("input", 0) for u in breakdown)
+    total_output = sum(u.get("output", 0) for u in breakdown)
     
     # Model Usage Breakdown
     models_used = {}
-    for u in fin.get("usage_breakdown", []):
+    for u in breakdown:
         m = u.get("model", "Unknown")
         models_used[m] = models_used.get(m, 0) + 1
     
-    model_str = ", ".join([f"{k} ({v} calls)" for k,v in models_used.items()])
+    if not models_used:
+        model_str = "None recorded"
+    else:
+        model_str = ", ".join([f"{k} ({v} calls)" for k,v in models_used.items()])
 
     md = f"""
     ### 💰 Financial Intelligence Report