Upload app.py

app.py

@@ -1,48 +1,49 @@
-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 transformers import AutoTokenizer, AutoModelForSequenceClassification
-import json, os
-from log import log
-
-app = FastAPI()
-
-app.include_router(health_controller.router)
-app.include_router(chat_controller.router)
-app.include_router(test_controller.router)
-app.include_router(admin_controller.router)
-
-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()
-        model_instance.setup(service_config, llm_config)
-        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:
-            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)
-
+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
+
+app = FastAPI()
+
+app.include_router(health_controller.router)
+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()
+        model_instance.setup(service_config, llm_config)
+        llm_models[project_name] = model_instance
+        log(f"✅ '{project_name}' için LLM modeli yüklendi.")
+
+        intent_model_path = llm_config.get("intent_model_path")
+        if intent_model_path:
+            load_intent_model_on_startup(project_name, intent_model_path)
+
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=7860)