Create core/dashboard.py

core/dashboard.py

@@ -1,40 +1,24 @@
-import time
 import pandas as pd
-import gradio as gr
 from datetime import datetime
 
 class ErohaDashboard:
     def __init__(self):
         self.logs = []
-        self.start_time = time.time()
 
     def log_request(self, model_name, query_type, response_time):
-        self.logs.append({
+        entry = {
             "time": datetime.now().strftime("%H:%M:%S"),
             "model": model_name,
             "type": query_type,
-            "response_time": response_time
-        })
-        # храним только последние 20 записей
-        if len(self.logs) > 20:
-            self.logs = self.logs[-20:]
+            "response_time": response_time,
+        }
+        self.logs.append(entry)
 
-    def get_metrics(self):
+    def dashboard_ui(self):
         if not self.logs:
-            return "—", "—", "—"
-        avg_time = round(sum(l["response_time"] for l in self.logs) / len(self.logs), 2)
-        last_model = self.logs[-1]["model"]
-        total_requests = len(self.logs)
-        return last_model, total_requests, avg_time
+            return "📭 Пока нет данных", pd.DataFrame(columns=["time", "model", "type", "response_time"])
 
-    def dashboard_ui(self):
-        df = pd.DataFrame(self.logs) if self.logs else pd.DataFrame([{
-            "time": "—", "model": "—", "type": "—", "response_time": "—"
-        }])
-        last_model, total_requests, avg_time = self.get_metrics()
-        return (
-            f"🧠 **Активная модель:** {last_model}\n"
-            f"📊 **Запросов обработано:** {total_requests}\n"
-            f"⚡ **Среднее время ответа:** {avg_time} сек.",
-            df
-        )
+        df = pd.DataFrame(self.logs)
+        avg_time = round(df["response_time"].mean(), 2)
+        text = f"📊 **Запросов:** {len(df)} | ⚡ **Среднее время ответа:** {avg_time} сек"
+        return text, df