Update app.py

app.py

@@ -52,14 +52,11 @@ class S3ModelLoader:
     
     def download_model_from_s3(self, model_name):
         try:
-            logging.info(f"Trying to load {model_name} from S3...")
             config = AutoConfig.from_pretrained(f"s3://{self.bucket_name}/{model_name}")
             model = AutoModelForCausalLM.from_pretrained(f"s3://{self.bucket_name}/{model_name}", config=config)
             tokenizer = AutoTokenizer.from_pretrained(f"s3://{self.bucket_name}/{model_name}")
-            logging.info(f"Loaded {model_name} from S3 successfully.")
             return model, tokenizer
-        except Exception as e:
-            logging.error(f"Error loading {model_name} from S3: {e}")
+        except Exception:
             return None, None
 
     async def load_model_and_tokenizer(self, model_name):
@@ -73,15 +70,12 @@ class S3ModelLoader:
 
     async def download_and_save_model_from_huggingface(self, model_name):
         try:
-            logging.info(f"Downloading {model_name} from Hugging Face...")
             with tqdm(unit="B", unit_scale=True, desc=f"Downloading {model_name}") as t:
                 model = AutoModelForCausalLM.from_pretrained(model_name, token=HUGGINGFACE_HUB_TOKEN, _tqdm=t)
                 tokenizer = AutoTokenizer.from_pretrained(model_name, token=HUGGINGFACE_HUB_TOKEN)
-            logging.info(f"Downloaded {model_name} successfully.")
             self.upload_model_to_s3(model_name, model, tokenizer)
             return model, tokenizer
         except Exception as e:
-            logging.error(f"Error downloading model from Hugging Face: {e}")
             raise HTTPException(status_code=500, detail=f"Error downloading model from Hugging Face: {e}")
 
     def upload_model_to_s3(self, model_name, model, tokenizer):
@@ -89,9 +83,7 @@ class S3ModelLoader:
             s3_uri = self._get_s3_uri(model_name)
             model.save_pretrained(s3_uri)
             tokenizer.save_pretrained(s3_uri)
-            logging.info(f"Saved {model_name} to S3 successfully.")
         except Exception as e:
-            logging.error(f"Error saving {model_name} to S3: {e}")
             raise HTTPException(status_code=500, detail=f"Error saving model to S3: {e}")
 
 app = FastAPI()
@@ -182,7 +174,6 @@ def download_all_models_in_background():
     try:
         response = requests.get(models_url)
         if response.status_code != 200:
-            logging.error("Error al obtener la lista de modelos de Hugging Face.")
             raise HTTPException(status_code=500, detail="Error al obtener la lista de modelos.")
         
         models = response.json()
@@ -190,7 +181,6 @@ def download_all_models_in_background():
             model_name = model["id"]
             model_loader.download_and_save_model_from_huggingface(model_name)
     except Exception as e:
-        logging.error(f"Error al descargar modelos en segundo plano: {e}")
         raise HTTPException(status_code=500, detail="Error al descargar modelos en segundo plano.")
 
 def run_in_background():