Upload adapter_layer.py

adapter_layer.py

@@ -1,22 +1,23 @@
 import os
 import sys
 import json
+import nltk
 import torch
 import inspect
 import logging
-import pydantic
-import codecarbon
-import importlib.util
-from typing import Dict, Any, Optional, List
-from service_registry import registry, MODEL, PRETRAINED_MODEL, TOKENIZER
-import nltk
+import pydantic              # required
+import codecarbon    
+import importlib.util        # required
 from model_List import PromptAnalyzer
+from typing import Dict, Any, Optional, List, Tuple
+from service_registry import registry, MODEL, PRETRAINED_MODEL, TOKENIZER
 
-# Directly import the packages that are now installed
-try:
-    print(f"Successfully using installed dependencies - pydantic: {pydantic.__version__}, codecarbon: {codecarbon.__version__}")
-except ImportError as e:
-    print(f"Error importing dependencies: {e}")
+# Log versions and fail fast if missing
+logger = logging.getLogger(__name__)
+logger.info(f"Using pydantic v{pydantic.__version__}")
+logger.info(f"Using codecarbon v{codecarbon.__version__}")
+
+print(f"Successfully using installed dependencies - pydantic: {pydantic.__version__}, codecarbon: {codecarbon.__version__}")
 
 # Import dependency helpers
 def is_module_available(module_name):
@@ -26,8 +27,6 @@ def is_module_available(module_name):
     except ImportError:
         return False
 
-logger = logging.getLogger(__name__)
-
 class WildnerveModelAdapter:
     """Adapter layer that interfaces between HF inference endpoints and the model."""
     RETRY_COUNT = 5
@@ -144,7 +143,7 @@ class WildnerveModelAdapter:
             "tokenizer": self.tokenizer
         }
     
-    def _split_prompt(self, prompt: str) -> (str, str):
+    def _split_prompt(self, prompt: str) -> Tuple[str, str]:
         """Return (technical_sentences, general_sentences)."""
         # download punkt if needed
         try: