镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 14:36:48 +00:00
rename folder
这个提交包含在:
@@ -11,7 +11,7 @@ class PaperFileGroup():
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self.sp_file_tag = []
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# count_token
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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self.get_token_num = get_token_num
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@@ -11,7 +11,7 @@ class PaperFileGroup():
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self.sp_file_tag = []
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# count_token
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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self.get_token_num = get_token_num
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@@ -5,7 +5,7 @@ import logging
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def input_clipping(inputs, history, max_token_limit):
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import numpy as np
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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@@ -63,7 +63,7 @@ def request_gpt_model_in_new_thread_with_ui_alive(
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"""
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import time
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from concurrent.futures import ThreadPoolExecutor
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from request_llm.bridge_all import predict_no_ui_long_connection
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from request_llms.bridge_all import predict_no_ui_long_connection
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# 用户反馈
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chatbot.append([inputs_show_user, ""])
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yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
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@@ -177,7 +177,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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"""
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import time, random
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from concurrent.futures import ThreadPoolExecutor
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from request_llm.bridge_all import predict_no_ui_long_connection
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from request_llms.bridge_all 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(sys_prompt_array)
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if max_workers == -1: # 读取配置文件
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@@ -165,7 +165,7 @@ class LatexPaperFileGroup():
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self.sp_file_tag = []
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# count_token
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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self.get_token_num = get_token_num
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@@ -103,7 +103,7 @@ def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_fi
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inputs_show_user_array = []
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# get_token_num
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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enc = model_info[llm_kwargs['llm_model']]['tokenizer']
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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@@ -1,7 +1,7 @@
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from pydantic import BaseModel, Field
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from typing import List
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from toolbox import update_ui_lastest_msg, disable_auto_promotion
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from request_llm.bridge_all import predict_no_ui_long_connection
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from request_llms.bridge_all import predict_no_ui_long_connection
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from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
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import copy, json, pickle, os, sys, time
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@@ -1,7 +1,7 @@
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from pydantic import BaseModel, Field
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from typing import List
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from toolbox import update_ui_lastest_msg, get_conf
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from request_llm.bridge_all import predict_no_ui_long_connection
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from request_llms.bridge_all import predict_no_ui_long_connection
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from crazy_functions.json_fns.pydantic_io import GptJsonIO
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import copy, json, pickle, os, sys
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@@ -5,7 +5,7 @@ import datetime
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def gen_image(llm_kwargs, prompt, resolution="256x256"):
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import requests, json, time, os
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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proxies, = get_conf('proxies')
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# Set up OpenAI API key and model
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@@ -32,7 +32,7 @@ def 解析docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot
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print(file_content)
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# private_upload里面的文件名在解压zip后容易出现乱码(rar和7z格式正常),故可以只分析文章内容,不输入文件名
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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max_token = model_info[llm_kwargs['llm_model']]['max_token']
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TOKEN_LIMIT_PER_FRAGMENT = max_token * 3 // 4
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paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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@@ -41,7 +41,7 @@ def split_audio_file(filename, split_duration=1000):
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def AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history):
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import os, requests
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from moviepy.editor import AudioFileClip
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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# 设置OpenAI密钥和模型
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api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
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@@ -13,7 +13,7 @@ class PaperFileGroup():
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self.sp_file_tag = []
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# count_token
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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self.get_token_num = get_token_num
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@@ -21,7 +21,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
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TOKEN_LIMIT_PER_FRAGMENT = 2500
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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@@ -95,7 +95,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
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# 递归地切割PDF文件
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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@@ -19,7 +19,7 @@ def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
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TOKEN_LIMIT_PER_FRAGMENT = 2500
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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@@ -2,7 +2,7 @@ from toolbox import CatchException, update_ui
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
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import requests
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from bs4 import BeautifulSoup
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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def google(query, proxies):
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query = query # 在此处替换您要搜索的关键词
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@@ -2,7 +2,7 @@ from toolbox import CatchException, update_ui
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
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import requests
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from bs4 import BeautifulSoup
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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def bing_search(query, proxies=None):
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@@ -48,7 +48,7 @@ from pydantic import BaseModel, Field
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from typing import List
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from toolbox import CatchException, update_ui, is_the_upload_folder
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from toolbox import update_ui_lastest_msg, disable_auto_promotion
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from request_llm.bridge_all import predict_no_ui_long_connection
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from request_llms.bridge_all import predict_no_ui_long_connection
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from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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from crazy_functions.crazy_utils import input_clipping
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from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
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@@ -13,7 +13,7 @@ class PaperFileGroup():
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self.sp_file_tag = []
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# count_token
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from request_llm.bridge_all import model_info
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from request_llms.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(
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enc.encode(txt, disallowed_special=()))
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@@ -2,7 +2,7 @@ from toolbox import update_ui
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from toolbox import CatchException, get_conf, markdown_convertion
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from crazy_functions.crazy_utils import input_clipping
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from crazy_functions.agent_fns.watchdog import WatchDog
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from request_llm.bridge_all import predict_no_ui_long_connection
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from request_llms.bridge_all import predict_no_ui_long_connection
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import threading, time
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import numpy as np
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from .live_audio.aliyunASR import AliyunASR
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