From 48a821ffb86d503f6190c5822ed82b1ad60f9c38 Mon Sep 17 00:00:00 2001 From: hxsz1997 <45651968+hxsz1997@users.noreply.github.com> Date: Wed, 3 Apr 2024 17:02:56 +0800 Subject: [PATCH] Modify ZH log to EN in Startup (#19) * modify zh log to en in startup * modify a typo of Start switching LLM --- startup.py | 40 ++++++++++++++++++++-------------------- 1 file changed, 20 insertions(+), 20 deletions(-) diff --git a/startup.py b/startup.py index f0bb1839bb..d1c9d94d38 100644 --- a/startup.py +++ b/startup.py @@ -44,7 +44,7 @@ @deprecated( since="0.3.0", - message="模型启动功能将于 Langchain-Chatchat 0.3.x重写,支持更多模式和加速启动，0.2.x中相关功能将废弃", + message="The model startup functionality will be rewritten in Langchain-Chatchat 0.3.x to support more modes and accelerate startup. The related functionality in 0.2.x will be deprecated.", removal="0.3.0") def create_controller_app( dispatch_method: str, @@ -339,9 +339,9 @@ def release_worker( return {"code": 500, "msg": msg[language]} if new_model_name: - logger.info(f"开始切换LLM模型：从 {model_name} 到 {new_model_name}") + logger.info(f"Start switching LLM: From {model_name} to {new_model_name}") else: - logger.info(f"即将停止LLM模型： {model_name}") + logger.info(f"About to stop LLM: {model_name}") if model_name not in available_models: msg = { @@ -615,26 +615,26 @@ def dump_server_info(after_start=False, args=None): print("\n") print("=" * 30 + "Langchain-Chatchat Configuration" + "=" * 30) - print(f"操作系统：{platform.platform()}.") - print(f"python版本：{sys.version}") - print(f"项目版本：{VERSION}") - print(f"langchain版本：{langchain.__version__}. fastchat版本：{fastchat.__version__}") + print(f"Operating system: {platform.platform()}.") + print(f"Python version: {sys.version}") + print(f"Project version: {VERSION}") + print(f"langchain version: {langchain.__version__}. fastchat version: {fastchat.__version__}") print("\n") models = LLM_MODELS if args and args.model_name: models = args.model_name - print(f"当前使用的分词器：{TEXT_SPLITTER_NAME}") - print(f"当前启动的LLM模型：{models} @ {llm_device()}") + print(f"Current tokenizer: {TEXT_SPLITTER_NAME}") + print(f"Current running LLM: {models} @ {llm_device()}") for model in models: pprint(get_model_worker_config(model)) - print(f"当前Embbedings模型： {EMBEDDING_MODEL} @ {embedding_device()}") + print(f"Current embbeding model: {EMBEDDING_MODEL} @ {embedding_device()}") if after_start: print("\n") - print(f"服务端运行信息：") + print(f"Server runtime information: ") if args.openai_api: print(f" OpenAI API Server: {fschat_openai_api_address()}") if args.api: @@ -699,8 +699,8 @@ def f(signal_received, frame): dump_server_info(args=args) if len(sys.argv) > 1: - logger.info(f"正在启动服务：") - logger.info(f"如需查看 llm_api 日志，请前往 {LOG_PATH}") + logger.info(f"Starting the service: ") + logger.info(f"To view the llm_api logs, please go to {LOG_PATH}") processes = {"online_api": {}, "model_worker": {}} @@ -831,7 +831,7 @@ def process_count(): if isinstance(cmd, list): model_name, cmd, new_model_name = cmd if cmd == "start": # 运行新模型 - logger.info(f"准备启动新模型进程：{new_model_name}") + logger.info(f"Preparing to launch the new model process: {new_model_name}") process = Process( target=run_model_worker, name=f"model_worker - {new_model_name}", @@ -846,18 +846,18 @@ def process_count(): process.name = f"{process.name} ({process.pid})" processes["model_worker"][new_model_name] = process e.wait() - logger.info(f"成功启动新模型进程：{new_model_name}") + logger.info(f"Successfully launched the new model process: {new_model_name}") elif cmd == "stop": if process := processes["model_worker"].get(model_name): time.sleep(1) process.terminate() process.join() - logger.info(f"停止模型进程：{model_name}") + logger.info(f"Stop the model process: {model_name}") else: - logger.error(f"未找到模型进程：{model_name}") + logger.error(f"Model process not found: {model_name}") elif cmd == "replace": if process := processes["model_worker"].pop(model_name, None): - logger.info(f"停止模型进程：{model_name}") + logger.info(f"Stop the model process: {model_name}") start_time = datetime.now() time.sleep(1) process.terminate() @@ -877,9 +877,9 @@ def process_count(): processes["model_worker"][new_model_name] = process e.wait() timing = datetime.now() - start_time - logger.info(f"成功启动新模型进程：{new_model_name}。用时：{timing}。") + logger.info(f"Successfully launched the new model process: {new_model_name}. Time taken: {timing}.") else: - logger.error(f"未找到模型进程：{model_name}") + logger.error(f"Model process not found: {model_name}") # for process in processes.get("model_worker", {}).values(): # process.join()