Update app.py

app.py

@@ -1,5 +1,7 @@
 import os
 import time
+import json
+
 import base64
 from collections import defaultdict
 from typing import List, Dict
@@ -999,7 +1001,8 @@ with gr.Blocks(
         segs["rag_retrieve_done"] = (time.perf_counter() - t_r0) * 1000.0
 
         # LLM (chat_with_clare must return 3 values)
-        t_llm0 = time.perf_counter()
+        start_ts = time.time()
+
         answer, new_history, llm_stats = chat_with_clare(
             message=message,
             history=chat_history,
@@ -1012,8 +1015,15 @@ with gr.Blocks(
             cognitive_state=cognitive_state,
             rag_context=rag_context_text,
         )
-        mark("llm_done")
-        segs["llm_done"] = (time.perf_counter() - t_llm0) * 1000.0
+        
+        end_ts = time.time()
+        latency_ms = (end_ts - start_ts) * 1000.0
+        
+        # === optional: print profiled metrics locally ===
+        try:
+            print("[LLM_PROFILE] " + json.dumps(llm_stats, ensure_ascii=False))
+        except Exception:
+            pass
 
         # merge llm_stats into perf
         perf = {
@@ -1239,17 +1249,18 @@ with gr.Blocks(
                 {
                     "experiment_id": experiment_id,
                     "student_id": student_id,
-                    "event_type": "micro_quiz_start",
-                    "timestamp": time.time(),
-                    "latency_ms": perf["total_ms"],
-                    "question": quiz_instruction,
+                    "event_type": "chat_turn",
+                    "timestamp": end_ts,
+                    "latency_ms": latency_ms,
+                    "question": message,
                     "answer": answer,
                     "model_name": model_name_val,
                     "language": resolved_lang,
                     "learning_mode": mode_val,
-                    "ttft_ms": perf.get("segments_ms", {}).get("llm_ttft_ms"),
+                    "llm_stats": llm_stats,
                 }
             )
+
         except Exception as e:
             print("log_event error:", e)