elmAI rebrand: визуальные названия Elmer → elmAI

web/script_endpoint.py

@@ -5,6 +5,7 @@ POST /api/v1/session/upload — приём батча, LLM-анализ, воз
 """
 
 import logging
+import time
 from web.script_builder import build_default_script, build_full_script
 from web.script_parser import parse_batch, format_no_llm
 
@@ -63,6 +64,7 @@ def register(app):
     def upload_session():
         from flask import request, jsonify
         from elmer.config import load
+        from elmer.db import Database
         from elmer.diagnose import Diagnoser
         from elmer.prompts import SYSTEM_PROMPT
 
@@ -72,30 +74,57 @@ def register(app):
 
         responses = data["responses"]
         logger.info(f"Upload: {len(responses)} responses")
+
+        # ── Информация о клиенте ──────────────────────
+        client_info = data.get("client_info", {})
+        client_info["client_ip"] = request.remote_addr
+        client_info["real_ip"] = request.headers.get("X-Real-IP", "")
+        client_info["user_agent"] = request.headers.get("User-Agent", "")
+        client_info["content_length"] = request.content_length
+
         parsed = parse_batch(responses)
 
         cfg = load()
         api_key = cfg["llm"]["api_key"]
+        model = cfg["llm"].get("model", "gpt-oss-120b")
+
+        llm_start = time.time()
+        llm_success = False
+        diagnosis = ""
 
         if not api_key:
-            return jsonify({
-                "diagnosis": format_no_llm(parsed),
-                "parsed": _summary(parsed),
-            })
+            diagnosis = format_no_llm(parsed)
+        else:
+            diagnoser = Diagnoser(
+                api_key=api_key,
+                model=model,
+                base_url=cfg["llm"].get("base_url", "https://api.aillm.ru/v1"),
+            )
+            try:
+                diagnosis = diagnoser.diagnose(SYSTEM_PROMPT, _build_diagnosis_prompt(parsed))
+                llm_success = True
+            except Exception as e:
+                logger.warning(f"LLM failed: {e}")
+                diagnosis = format_no_llm(parsed) + f"\n\n(LLM недоступен: {e})"
 
-        diagnoser = Diagnoser(
-            api_key=api_key,
-            model=cfg["llm"].get("model", "gpt-oss-120b"),
-            base_url=cfg["llm"].get("base_url", "https://api.aillm.ru/v1"),
-        )
+        llm_duration_ms = int((time.time() - llm_start) * 1000)
+
+        # ── Сохранение в БД ───────────────────────────
         try:
-            answer = diagnoser.diagnose(SYSTEM_PROMPT, _build_diagnosis_prompt(parsed))
+            db = Database()
+            db.save_session(
+                client_info=client_info,
+                responses=responses,
+                diagnosis=diagnosis,
+                llm_model=model,
+                llm_duration_ms=llm_duration_ms,
+                llm_success=llm_success,
+            )
         except Exception as e:
-            logger.warning(f"LLM failed: {e}")
-            answer = format_no_llm(parsed) + f"\n\n(LLM недоступен: {e})"
+            logger.error(f"DB save failed: {e}")
 
         return jsonify({
-            "diagnosis": answer,
+            "diagnosis": diagnosis,
             "parsed": _summary(parsed),
         })