Update app.py

app.py

@@ -1,10 +1,8 @@
 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 core import service_config, session_store, llm_models
 from llm_model import LLMModel
 from log import log
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-import json
 import os
 import warnings
 
@@ -20,22 +18,16 @@ app.include_router(admin_controller.router)
 
 BASE_PROJECTS_DIR = "/data/projects"
 
-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}")
+def load_project(project_name, config, project_path):
+    llm_config = config.get_project_llm_config(project_name)
+    model_instance = LLMModel()
+    model_instance.setup(config, llm_config, project_path)
+
+    intent_model_path = os.path.join(project_path, "intent", "trained_model")
+    if os.path.exists(intent_model_path):
+        model_instance.load_intent_model(intent_model_path)
+
+    return model_instance
 
 log("🌐 Servis başlatılıyor...")
 service_config.load(is_reload=False)
@@ -47,16 +39,10 @@ for project_name in service_config.projects:
     os.makedirs(os.path.join(project_path, "llm", "fine_tune"), exist_ok=True)
     os.makedirs(os.path.join(project_path, "intent", "trained_model"), exist_ok=True)
 
-    llm_config = service_config.get_project_llm_config(project_name)
-    model_instance = LLMModel()
-    model_instance.setup(service_config, llm_config, project_path)
+    model_instance = load_project(project_name, service_config, project_path)
     llm_models[project_name] = model_instance
-    log(f"✅ '{project_name}' için LLM modeli yüklendi.")
-
-    intent_model_path = os.path.join(project_path, "intent", "trained_model")
-    if os.path.exists(intent_model_path):
-        load_intent_model_on_startup(project_name, intent_model_path)
+    log(f"✅ '{project_name}' için tüm modeller yüklenip belleğe alındı.")
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+    uvicorn.run(app, host="0.0.0.0", port=7860)