Create services/model_service.py

services/model_service.py

@@ -0,0 +1,41 @@
+# services/model_service.py
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from sentence_transformers import SentenceTransformer
+import torch
+from functools import lru_cache
+from config.config import settings
+import logging
+
+logger = logging.getLogger(__name__)
+
+class ModelService:
+    _instance = None
+
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+
+    def __init__(self):
+        if not self._initialized:
+            self._initialized = True
+            self._load_models()
+
+    @lru_cache(maxsize=1)
+    def _load_models(self):
+        try:
+            self.tokenizer = AutoTokenizer.from_pretrained(settings.MODEL_NAME)
+            self.model = AutoModelForCausalLM.from_pretrained(
+                settings.MODEL_NAME,
+                torch_dtype=torch.float16 if settings.DEVICE == "cuda" else torch.float32,
+                device_map="auto" if settings.DEVICE == "cuda" else None
+            )
+            self.embedder = SentenceTransformer(settings.EMBEDDER_MODEL)
+        except Exception as e:
+            logger.error(f"Error loading models: {e}")
+            raise
+
+    def get_models(self):
+        return self.tokenizer, self.model, self.embedder
+