revert test and demo_agent loggers

core/tests/utils.py

@@ -4,13 +4,10 @@
 import pytest
 
 
-logger = logging.getLogger(__name__)
-
-
 # setup code, executed ahead of first test
 @pytest.fixture(scope="session", autouse=True)
 def setup_playwright(playwright: playwright.sync_api.Playwright):
     # bugfix: re-use pytest-playwright's playwright instance in browsergym
     # https://github.com/microsoft/playwright-python/issues/2053
     browsergym.core._set_global_playwright(playwright)
-    logger.info("Browsergym is using the playwright instance provided by pytest-playwright.")
+    logging.info("Browsergym is using the playwright instance provided by pytest-playwright.")

demo_agent/agents/legacy/dynamic_prompting.py

@@ -25,9 +25,6 @@
 )
 
 
-logger = logging.getLogger(__name__)
-
-
 @dataclass
 class Flags:
     use_html: bool = True
@@ -216,7 +213,7 @@ def fit_tokens(
             return prompt
         shrinkable.shrink()
 
-    logger.info(
+    logging.info(
         dedent(
             f"""\
             After {max_iterations} shrink iterations, the prompt is still
@@ -377,7 +374,7 @@ def __init__(
             self.instructions = ChatInstructions(obs_history[-1]["chat_messages"])
         else:
             if sum([msg["role"] == "user" for msg in obs_history[-1]["chat_messages"]]) > 1:
-                logger.warning(
+                logging.warning(
                     "Agent is in goal mode, but multiple user messages are present in the chat. Consider switching to `enable_chat=True`."
                 )
             self.instructions = GoalInstructions(obs_history[-1]["goal"])

demo_agent/agents/legacy/utils/chat_api.py

@@ -22,9 +22,6 @@
 from transformers import GPT2TokenizerFast
 
 
-logger = logging.getLogger(__name__)
-
-
 @dataclass
 class ChatModelArgs:
     """Serializable object for instantiating a generic chat model.
@@ -166,21 +163,21 @@ def __init__(
 
         if max_new_tokens is None:
             max_new_tokens = max_total_tokens - max_input_tokens
-            logger.warning(
+            logging.warning(
                 f"max_new_tokens is not specified. Setting it to {max_new_tokens} (max_total_tokens - max_input_tokens)."
             )
 
         self.tokenizer = AutoTokenizer.from_pretrained(model_name)
         if isinstance(self.tokenizer, GPT2TokenizerFast):
             # TODO: make this less hacky once tokenizer.apply_chat_template is more mature
-            logger.warning(
+            logging.warning(
                 f"No chat template is defined for {model_name}. Resolving to the hard-coded templates."
             )
             self.tokenizer = None
             self.prompt_template = get_prompt_template(model_name)
 
         if temperature < 1e-3:
-            logger.warning(
+            logging.warning(
                 "some weird things might happen when temperature is too low for some models."
             )
 
@@ -189,17 +186,17 @@ def __init__(
         }
 
         if model_url is not None:
-            logger.info("Loading the LLM from a URL")
+            logging.info("Loading the LLM from a URL")
             client = InferenceClient(model=model_url, token=eai_token)
             self.llm = partial(
                 client.text_generation, temperature=temperature, max_new_tokens=max_new_tokens
             )
         elif hf_hosted:
-            logger.info("Serving the LLM on HuggingFace Hub")
+            logging.info("Serving the LLM on HuggingFace Hub")
             model_kwargs["max_length"] = max_new_tokens
             self.llm = HuggingFaceHub(repo_id=model_name, model_kwargs=model_kwargs)
         else:
-            logger.info("Loading the LLM locally")
+            logging.info("Loading the LLM locally")
             pipe = pipeline(
                 task="text-generation",
                 model=model_name,
@@ -217,7 +214,7 @@ def _call(
         **kwargs: Any,
     ) -> str:
         if stop is not None or run_manager is not None or kwargs:
-            logger.warning(
+            logging.warning(
                 "The `stop`, `run_manager`, and `kwargs` arguments are ignored in this implementation."
             )
 
@@ -236,7 +233,7 @@ def _call(
             except Exception as e:
                 if itr == self.n_retry_server - 1:
                     raise e
-                logger.warning(
+                logging.warning(
                     f"Failed to get a response from the server: \n{e}\n"
                     f"Retrying... ({itr+1}/{self.n_retry_server})"
                 )