Update app.py

app.py

@@ -42,7 +42,9 @@ def generate_summary(df):
     yesterday = now - timedelta(days=1)
     last_14 = now - timedelta(days=14)
 
-    df["timestamp"] = pd.to_datetime(df["timestamp"])
+    # Konvertera timestamp till datetime
+    df["timestamp"] = pd.to_datetime(df["timestamp"], errors="coerce")
+    # Filtrera loggar för senaste 24h och 14 dagar
     df_day = df[df["timestamp"] >= yesterday.replace(hour=0, minute=0, second=0)]
     df_14 = df[df["timestamp"] >= last_14]
 
@@ -50,9 +52,55 @@ def generate_summary(df):
     summary.append(f"📅 Datum: {now.strftime('%Y-%m-%d')}")
     summary.append(f"🗨️ Antal meddelanden senaste 24h: {len(df_day)}")
     summary.append(f"👥 Unika sessioner senaste 24h: {df_day['session_id'].nunique()}")
-    summary.append(f"🕒 Snittsvarstid senaste 24h: {round(df_day['response_time'].mean(), 2)} sekunder")
+
+    # Beräkna snitt antal meddelanden per session (om minst en session finns)
+    unique_sessions = df_day['session_id'].nunique()
+    avg_messages_per_session = round(len(df_day) / unique_sessions, 2) if unique_sessions > 0 else 0
+    summary.append(f"📊 Meddelanden per session (snitt): {avg_messages_per_session}")
+
+    # Snittsvarstid (om kolumnen finns och har giltiga värden)
+    if "response_time" in df_day.columns and not df_day["response_time"].empty:
+        avg_response_time = round(df_day["response_time"].mean(), 2)
+        summary.append(f"🕒 Snittsvarstid senaste 24h: {avg_response_time} sekunder")
+    else:
+        summary.append("🕒 Snittsvarstid senaste 24h: N/A")
+
     summary.append(f"📊 Antal meddelanden (14 dagar): {len(df_14)}")
     summary.append(f"📈 Unika användare (14 dagar): {df_14['user_id'].nunique()}")
+
+    # Likes och dislikes under senaste 24h
+    if "feedback" in df_day.columns:
+        df_day_feedback = df_day.dropna(subset=["feedback"])
+        likes = df_day_feedback[df_day_feedback["feedback"] == "up"].shape[0]
+        dislikes = df_day_feedback[df_day_feedback["feedback"] == "down"].shape[0]
+    else:
+        likes, dislikes = 0, 0
+    summary.append(f"👍 Likes senaste 24h: {likes}")
+    summary.append(f"👎 Dislikes senaste 24h: {dislikes}")
+
+    # Nyckeltal kring webbläsare: visa de tre mest använda
+    if "browser" in df_day.columns:
+        browser_counts = df_day["browser"].value_counts()
+        top_browsers = browser_counts.head(3)
+        browser_summary = "🌐 Browser-fördelning senaste 24h: " + ", ".join([f"{browser}: {count}" for browser, count in top_browsers.items()])
+    else:
+        browser_summary = "🌐 Browser-fördelning senaste 24h: Ingen data"
+    summary.append(browser_summary)
+
+    # Tre exempel på frågor och svar med tumme ner
+    if "feedback" in df_day.columns:
+        df_down = df_day[df_day["feedback"] == "down"].dropna(subset=["user_message", "bot_reply"])
+    else:
+        df_down = pd.DataFrame()
+    if not df_down.empty:
+        examples = df_down.head(3)
+        examples_text = "❌ Exempel på frågor och svar med tumme ner:\n"
+        for idx, row in examples.iterrows():
+            examples_text += f"• Fråga: {row['user_message']}\n  Svar: {row['bot_reply']}\n"
+    else:
+        examples_text = "❌ Inga exempel med tumme ner hittades senaste 24h."
+    summary.append(examples_text)
+
     return "\n".join(summary)
 
 # --- Huvudfunktion ---