把函数插件并行数量限制放到config中
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@ -33,6 +33,9 @@ LAYOUT = "LEFT-RIGHT" # "LEFT-RIGHT"(左右布局) # "TOP-DOWN"(上下布
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# 发送请求到OpenAI后,等待多久判定为超时
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# 发送请求到OpenAI后,等待多久判定为超时
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TIMEOUT_SECONDS = 30
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TIMEOUT_SECONDS = 30
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# 多线程函数插件中,默认允许多少路线程同时访问OpenAI。OpenAI的限制是不能超过20
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DEFAULT_WORKER_NUM = 8
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# 网页的端口, -1代表随机端口
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# 网页的端口, -1代表随机端口
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WEB_PORT = -1
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WEB_PORT = -1
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@ -92,7 +92,7 @@ def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
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chatbot=chatbot,
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chatbot=chatbot,
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history_array=[[""] for _ in range(n_split)],
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history_array=[[""] for _ in range(n_split)],
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sys_prompt_array=sys_prompt_array,
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sys_prompt_array=sys_prompt_array,
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max_workers=5, # 并行任务数量限制,最多同时执行5个,其他的排队等待
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# max_workers=5, # 并行任务数量限制,最多同时执行5个,其他的排队等待
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scroller_max_len = 80
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scroller_max_len = 80
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)
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)
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@ -90,7 +90,7 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
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chatbot=chatbot,
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chatbot=chatbot,
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history_array=[[""] for _ in range(n_split)],
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history_array=[[""] for _ in range(n_split)],
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sys_prompt_array=sys_prompt_array,
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sys_prompt_array=sys_prompt_array,
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max_workers=5, # OpenAI所允许的最大并行过载
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# max_workers=5, # OpenAI所允许的最大并行过载
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scroller_max_len = 80
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scroller_max_len = 80
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)
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)
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@ -1,10 +1,9 @@
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import traceback
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import traceback
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from toolbox import update_ui
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from toolbox import update_ui, get_conf
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def input_clipping(inputs, history, max_token_limit):
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def input_clipping(inputs, history, max_token_limit):
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import tiktoken
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import tiktoken
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import numpy as np
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import numpy as np
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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@ -132,7 +131,7 @@ def request_gpt_model_in_new_thread_with_ui_alive(
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def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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inputs_array, inputs_show_user_array, llm_kwargs,
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inputs_array, inputs_show_user_array, llm_kwargs,
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chatbot, history_array, sys_prompt_array,
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chatbot, history_array, sys_prompt_array,
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refresh_interval=0.2, max_workers=5, scroller_max_len=30,
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refresh_interval=0.2, max_workers=-1, scroller_max_len=30,
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handle_token_exceed=True, show_user_at_complete=False,
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handle_token_exceed=True, show_user_at_complete=False,
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retry_times_at_unknown_error=2,
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retry_times_at_unknown_error=2,
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):
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):
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@ -153,7 +152,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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history_array (list): List of chat history (历史对话输入,双层列表,第一层列表是子任务分解,第二层列表是对话历史)
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history_array (list): List of chat history (历史对话输入,双层列表,第一层列表是子任务分解,第二层列表是对话历史)
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sys_prompt_array (list): List of system prompts (系统输入,列表,用于输入给GPT的前提提示,比如你是翻译官怎样怎样)
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sys_prompt_array (list): List of system prompts (系统输入,列表,用于输入给GPT的前提提示,比如你是翻译官怎样怎样)
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refresh_interval (float, optional): Refresh interval for UI (default: 0.2) (刷新时间间隔频率,建议低于1,不可高于3,仅仅服务于视觉效果)
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refresh_interval (float, optional): Refresh interval for UI (default: 0.2) (刷新时间间隔频率,建议低于1,不可高于3,仅仅服务于视觉效果)
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max_workers (int, optional): Maximum number of threads (default: 10) (最大线程数,如果子任务非常多,需要用此选项防止高频地请求openai导致错误)
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max_workers (int, optional): Maximum number of threads (default: see config.py) (最大线程数,如果子任务非常多,需要用此选项防止高频地请求openai导致错误)
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scroller_max_len (int, optional): Maximum length for scroller (default: 30)(数据流的显示最后收到的多少个字符,仅仅服务于视觉效果)
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scroller_max_len (int, optional): Maximum length for scroller (default: 30)(数据流的显示最后收到的多少个字符,仅仅服务于视觉效果)
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handle_token_exceed (bool, optional): (是否在输入过长时,自动缩减文本)
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handle_token_exceed (bool, optional): (是否在输入过长时,自动缩减文本)
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handle_token_exceed:是否自动处理token溢出的情况,如果选择自动处理,则会在溢出时暴力截断,默认开启
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handle_token_exceed:是否自动处理token溢出的情况,如果选择自动处理,则会在溢出时暴力截断,默认开启
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@ -168,6 +167,10 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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from request_llm.bridge_chatgpt import predict_no_ui_long_connection
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from request_llm.bridge_chatgpt import predict_no_ui_long_connection
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assert len(inputs_array) == len(history_array)
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assert len(inputs_array) == len(history_array)
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assert len(inputs_array) == len(sys_prompt_array)
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assert len(inputs_array) == len(sys_prompt_array)
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if max_workers == -1: # 读取配置文件
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try: max_workers, = get_conf('DEFAULT_WORKER_NUM')
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except: max_workers = 8
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if max_workers <= 0 or max_workers >= 20: max_workers = 8
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executor = ThreadPoolExecutor(max_workers=max_workers)
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executor = ThreadPoolExecutor(max_workers=max_workers)
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n_frag = len(inputs_array)
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n_frag = len(inputs_array)
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# 用户反馈
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# 用户反馈
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@ -176,7 +179,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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# 跨线程传递
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# 跨线程传递
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mutable = [["", time.time(), "等待中"] for _ in range(n_frag)]
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mutable = [["", time.time(), "等待中"] for _ in range(n_frag)]
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#
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# 子线程任务
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def _req_gpt(index, inputs, history, sys_prompt):
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def _req_gpt(index, inputs, history, sys_prompt):
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gpt_say = ""
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gpt_say = ""
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retry_op = retry_times_at_unknown_error
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retry_op = retry_times_at_unknown_error
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@ -73,7 +73,7 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
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chatbot=chatbot,
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chatbot=chatbot,
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history_array=[[""] for _ in range(n_split)],
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history_array=[[""] for _ in range(n_split)],
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sys_prompt_array=sys_prompt_array,
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sys_prompt_array=sys_prompt_array,
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max_workers=5, # OpenAI所允许的最大并行过载
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# max_workers=5, # OpenAI所允许的最大并行过载
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scroller_max_len = 80
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scroller_max_len = 80
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)
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)
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@ -98,7 +98,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
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history_array=[[paper_meta] for _ in paper_fragments],
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history_array=[[paper_meta] for _ in paper_fragments],
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sys_prompt_array=[
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sys_prompt_array=[
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"请你作为一个学术翻译,负责把学术论文的片段准确翻译成中文。" for _ in paper_fragments],
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"请你作为一个学术翻译,负责把学术论文的片段准确翻译成中文。" for _ in paper_fragments],
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max_workers=5 # OpenAI所允许的最大并行过载
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# max_workers=5 # OpenAI所允许的最大并行过载
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)
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)
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# 整理报告的格式
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# 整理报告的格式
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