Update app.py

app.py

@@ -2,10 +2,9 @@ from fastapi import FastAPI
 from controllers import chat_controller, test_controller, admin_controller, health_controller
 from core import service_config, session_store, llm_models, INTENT_MODELS
 from llm_model import LLMModel
-from log import log
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
-import json
-import os
+import json, os
+from log import log
 
 app = FastAPI()
 
@@ -14,26 +13,10 @@ app.include_router(chat_controller.router)
 app.include_router(test_controller.router)
 app.include_router(admin_controller.router)
 
-def load_intent_model_on_startup(project_name, model_path):
-    log(f"🔧 Intent modeli yükleniyor: {project_name} → {model_path}")
-    try:
-        tokenizer = AutoTokenizer.from_pretrained(model_path)
-        model = AutoModelForSequenceClassification.from_pretrained(model_path)
-        with open(os.path.join(model_path, "label2id.json")) as f:
-            label2id = json.load(f)
-
-        INTENT_MODELS[project_name] = {
-            "model": model,
-            "tokenizer": tokenizer,
-            "label2id": label2id
-        }
-        log(f"✅ Intent modeli yüklendi: {project_name}")
-    except Exception as e:
-        log(f"❌ Intent modeli yüklenemedi: {project_name}, Hata: {e}")
-
 if __name__ == "__main__":
     log("🌐 Servis başlatılıyor...")
     service_config.load(is_reload=False)
+
     for project_name in service_config.projects:
         llm_config = service_config.get_project_llm_config(project_name)
         model_instance = LLMModel()
@@ -41,9 +24,25 @@ if __name__ == "__main__":
         llm_models[project_name] = model_instance
         log(f"✅ '{project_name}' için LLM modeli yüklendi.")
 
+        # ✅ Intent modeli yükleme eklendi
         intent_model_path = llm_config.get("intent_model_path")
         if intent_model_path:
-            load_intent_model_on_startup(project_name, intent_model_path)
+            try:
+                log(f"🔧 Intent modeli yükleniyor: {project_name} → {intent_model_path}")
+                tokenizer = AutoTokenizer.from_pretrained(intent_model_path)
+                model = AutoModelForSequenceClassification.from_pretrained(intent_model_path)
+                with open(os.path.join(intent_model_path, "label2id.json")) as f:
+                    label2id = json.load(f)
+
+                INTENT_MODELS[project_name] = {
+                    "model": model,
+                    "tokenizer": tokenizer,
+                    "label2id": label2id
+                }
+                log(f"✅ Intent modeli yüklendi: {project_name}")
+            except Exception as e:
+                log(f"❌ Intent modeli yüklenemedi: {project_name}, Hata: {e}")
 
     import uvicorn
     uvicorn.run(app, host="0.0.0.0", port=7860)
+