From 4e34ae05879ce288eeb5649bca62be27992ab348 Mon Sep 17 00:00:00 2001
From: oobabooga <112222186+oobabooga@users.noreply.github.com>
Date: Tue, 6 Feb 2024 08:22:08 -0800
Subject: [PATCH] Minor logging improvements

---
 modules/models.py | 10 +++++-----
 server.py         |  2 +-
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/modules/models.py b/modules/models.py
index 5929e868..038669f3 100644
--- a/modules/models.py
+++ b/modules/models.py
@@ -54,7 +54,7 @@ sampler_hijack.hijack_samplers()
 
 
 def load_model(model_name, loader=None):
-    logger.info(f"Loading {model_name}")
+    logger.info(f"Loading \"{model_name}\"")
     t0 = time.time()
 
     shared.is_seq2seq = False
@@ -246,7 +246,7 @@ def llamacpp_loader(model_name):
     else:
         model_file = list(Path(f'{shared.args.model_dir}/{model_name}').glob('*.gguf'))[0]
 
-    logger.info(f"llama.cpp weights detected: {model_file}")
+    logger.info(f"llama.cpp weights detected: \"{model_file}\"")
     model, tokenizer = LlamaCppModel.from_pretrained(model_file)
     return model, tokenizer
 
@@ -257,7 +257,7 @@ def llamacpp_HF_loader(model_name):
     for fname in [model_name, "oobabooga_llama-tokenizer", "llama-tokenizer"]:
         path = Path(f'{shared.args.model_dir}/{fname}')
         if all((path / file).exists() for file in ['tokenizer_config.json', 'special_tokens_map.json', 'tokenizer.model']):
-            logger.info(f'Using tokenizer from: {path}')
+            logger.info(f'Using tokenizer from: \"{path}\"')
             break
     else:
         logger.error("Could not load the model because a tokenizer in transformers format was not found. Please download oobabooga/llama-tokenizer.")
@@ -298,7 +298,7 @@ def ctransformers_loader(model_name):
                 logger.error("Could not find a model for ctransformers.")
                 return None, None
 
-    logger.info(f'ctransformers weights detected: {model_file}')
+    logger.info(f'ctransformers weights detected: \"{model_file}\"')
     model, tokenizer = ctrans.from_pretrained(model_file)
     return model, tokenizer
 
@@ -393,7 +393,7 @@ def HQQ_loader(model_name):
     from hqq.core.quantize import HQQBackend, HQQLinear
     from hqq.engine.hf import HQQModelForCausalLM
 
-    logger.info(f"Loading HQQ model with backend: {shared.args.hqq_backend}")
+    logger.info(f"Loading HQQ model with backend: \"{shared.args.hqq_backend}\"")
 
     model_dir = Path(f'{shared.args.model_dir}/{model_name}')
     model = HQQModelForCausalLM.from_quantized(str(model_dir))
diff --git a/server.py b/server.py
index 6ef9005d..681fe4e7 100644
--- a/server.py
+++ b/server.py
@@ -187,7 +187,7 @@ if __name__ == "__main__":
         settings_file = Path('settings.json')
 
     if settings_file is not None:
-        logger.info(f"Loading settings from {settings_file}")
+        logger.info(f"Loading settings from \"{settings_file}\"")
         file_contents = open(settings_file, 'r', encoding='utf-8').read()
         new_settings = json.loads(file_contents) if settings_file.suffix == "json" else yaml.safe_load(file_contents)
         shared.settings.update(new_settings)