Resolve warnings of logger library (#2681)

Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>

packages/dbgpt-app/src/dbgpt_app/knowledge/_cli/knowledge_client.py

@@ -58,7 +58,7 @@ class KnowledgeApiClient(ApiClient):
             return self._post("/knowledge/space/add", data=request)
         except Exception as e:
             if "have already named" in str(e):
-                logger.warn(f"you have already named {request.name}")
+                logger.warning(f"you have already named {request.name}")
             else:
                 raise e
 
@@ -143,7 +143,7 @@ def knowledge_init(
                 )
             except Exception as ex:
                 if overwrite and "have already named" in str(ex):
-                    logger.warn(
+                    logger.warning(
                         f"Document {filename} already exist in space {space.name}, "
                         "overwrite it"
                     )
@@ -172,7 +172,7 @@ def knowledge_init(
             return doc_id
         except Exception as e:
             if skip_wrong_doc:
-                logger.warn(f"Upload {filename} to {space.name} failed: {str(e)}")
+                logger.warning(f"Upload {filename} to {space.name} failed: {str(e)}")
             else:
                 raise e
 
@@ -195,7 +195,7 @@ def knowledge_init(
         doc_ids = [r.result() for r in as_completed(tasks)]
         doc_ids = list(filter(lambda x: x, doc_ids))
         if not doc_ids:
-            logger.warn("Warning: no document to sync")
+            logger.warning("Warning: no document to sync")
             return
 
 
@@ -374,7 +374,7 @@ def knowledge_delete(
                 .lower()
             )
             if user_input != "yes":
-                logger.warn("Delete operation cancelled.")
+                logger.warning("Delete operation cancelled.")
                 return
         client.space_delete(space)
         logger.info("Delete the whole knowledge space successfully!")
@@ -390,7 +390,7 @@ def knowledge_delete(
                 .lower()
             )
             if user_input != "yes":
-                logger.warn("Delete operation cancelled.")
+                logger.warning("Delete operation cancelled.")
                 return
         client.document_delete(space_name, KnowledgeDocumentRequest(doc_name=doc_name))
         logger.info(

packages/dbgpt-app/src/dbgpt_app/scene/base_chat.py

@@ -610,7 +610,7 @@ class BaseChat(ABC):
         return prompt_define_response
 
     def _blocking_stream_call(self):
-        logger.warn(
+        logger.warning(
             "_blocking_stream_call is only temporarily used in webserver and will be "
             "deleted soon, please use stream_call to replace it for higher performance"
         )

packages/dbgpt-core/src/dbgpt/agent/resource/tool/autogpt/plugins_util.py

@@ -68,7 +68,7 @@ def create_directory_if_not_exists(directory_path: str) -> bool:
             logger.debug(f"Created directory: {directory_path}")
             return True
         except OSError as e:
-            logger.warn(f"Error creating directory {directory_path}: {e}")
+            logger.warning(f"Error creating directory {directory_path}: {e}")
             return False
     else:
         logger.info(f"Directory {directory_path} already exists")

packages/dbgpt-core/src/dbgpt/core/awel/dag/base.py

@@ -1065,7 +1065,7 @@ def _get_graph(dag: DAG):
     try:
         from graphviz import Digraph
     except ImportError:
-        logger.warn("Can't import graphviz, skip visualize DAG")
+        logger.warning("Can't import graphviz, skip visualize DAG")
         return None, None
     dot = Digraph(name=dag.dag_id)
     mermaid_str = "graph TD;\n"  # Initialize Mermaid graph definition

packages/dbgpt-core/src/dbgpt/model/adapter/loader.py

@@ -25,13 +25,13 @@ def _hf_check_quantization(model_params: HFLLMDeployModelParameters):
     has_quantization = model_params.quantization is not None
     if has_quantization:
         if model_params.real_device != "cuda":
-            logger.warn(
+            logger.warning(
                 "8-bit quantization and 4-bit quantization just supported by cuda"
             )
             return False
         elif "chatglm" in model_name:
             if "int4" not in model_name:
-                logger.warn(
+                logger.warning(
                     "chatglm or chatglm2 not support quantization now, see: "
                     "https://github.com/huggingface/transformers/issues/25228"
                 )
@@ -389,7 +389,7 @@ def load_huggingface_quantization_model(
             tokenizer.bos_token_id = 1
             tokenizer.pad_token_id = 0
         except Exception as e:
-            logger.warn(f"{str(e)}")
+            logger.warning(f"{str(e)}")
     else:
         logger.info(
             "Current model type is not LlamaForCausalLM, load tokenizer by "

packages/dbgpt-core/src/dbgpt/model/cluster/worker/manager.py

@@ -80,7 +80,7 @@ async def _async_heartbeat_sender(
         try:
             await send_heartbeat_func(worker_run_data)
         except Exception as e:
-            logger.warn(f"Send heartbeat func error: {str(e)}")
+            logger.warning(f"Send heartbeat func error: {str(e)}")
         finally:
             await asyncio.sleep(heartbeat_interval)
 

packages/dbgpt-core/src/dbgpt/model/proxy/base.py

@@ -145,7 +145,7 @@ class TiktokenProxyTokenizer(ProxyTokenizer):
             )
         except ImportError:
             self._support_encoding = False
-            logger.warn("tiktoken not installed, cannot count tokens")
+            logger.warning("tiktoken not installed, cannot count tokens")
             return None
         try:
             if not model_name:

packages/dbgpt-core/src/dbgpt/model/utils/token_utils.py

@@ -71,7 +71,7 @@ class ProxyTokenizerWrapper:
             )
         except ImportError:
             self._support_encoding = False
-            logger.warn("tiktoken not installed, cannot count tokens, returning -1")
+            logger.warning("tiktoken not installed, cannot count tokens, returning -1")
             return -1
         try:
             if not model_name:

packages/dbgpt-core/src/dbgpt/storage/cache/manager.py

@@ -167,7 +167,7 @@ def initialize_cache(
                 persist_dir, mem_table_buffer_mb=max_memory_mb
             )
         except ImportError as e:
-            logger.warn(
+            logger.warning(
                 f"Can't import DiskCacheStorage, use MemoryCacheStorage, import error "
                 f"message: {str(e)}"
             )

packages/dbgpt-core/src/dbgpt/util/model_utils.py

@@ -12,7 +12,7 @@ def _clear_model_cache(device="cuda"):
 
         _clear_torch_cache(device)
     except ImportError:
-        logger.warn("Torch not installed, skip clear torch cache")
+        logger.warning("Torch not installed, skip clear torch cache")
     # TODO clear other cache
 
 
@@ -30,7 +30,7 @@ def _clear_torch_cache(device="cuda"):
 
                 empty_cache()
             except Exception as e:
-                logger.warn(f"Clear mps torch cache error, {str(e)}")
+                logger.warning(f"Clear mps torch cache error, {str(e)}")
         elif (hasattr(backends, "cuda") and backends.cuda.is_built()) or torch.has_cuda:
             device_count = torch.cuda.device_count()
             for device_id in range(device_count):

packages/dbgpt-core/src/dbgpt/util/speech/eleven_labs.py

@@ -86,6 +86,6 @@ class ElevenLabsSpeech(VoiceBase):
             os.remove("speech.mpeg")
             return True
         else:
-            logger.warn("Request failed with status code:", response.status_code)
+            logger.warning("Request failed with status code:", response.status_code)
             logger.info("Response content:", response.content)
             return False

packages/dbgpt-serve/src/dbgpt_serve/datasource/service/db_summary_client.py

@@ -88,7 +88,7 @@ class DBSummaryClient:
                 self.db_summary_embedding(item["db_name"], item["db_type"])
             except Exception as e:
                 message = traceback.format_exc()
-                logger.warn(
+                logger.warning(
                     f"{item['db_name']}, {item['db_type']} summary error!{str(e)}, "
                     f"detail: {message}"
                 )