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CodeInterp
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personal_a
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| 5813d65e52 |
@ -93,7 +93,7 @@ Latex论文一键校对 | [函数插件] 仿Grammarly对Latex文章进行语法
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1. 下载项目
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```sh
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git clone https://github.com/binary-husky/gpt_academic.git
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git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
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cd gpt_academic
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```
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@ -126,7 +126,7 @@ python -m pip install -r request_llm/requirements_chatglm.txt
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# 【可选步骤II】支持复旦MOSS
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python -m pip install -r request_llm/requirements_moss.txt
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git clone https://github.com/OpenLMLab/MOSS.git request_llm/moss # 注意执行此行代码时,必须处于项目根路径
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git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llm/moss # 注意执行此行代码时,必须处于项目根路径
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# 【可选步骤III】确保config.py配置文件的AVAIL_LLM_MODELS包含了期望的模型,目前支持的全部模型如下(jittorllms系列目前仅支持docker方案):
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AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "newbing", "moss"] # + ["jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
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@ -149,7 +149,7 @@ python main.py
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[](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml)
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``` sh
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git clone https://github.com/binary-husky/gpt_academic.git # 下载项目
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git clone --depth=1 https://github.com/binary-husky/gpt_academic.git # 下载项目
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cd gpt_academic # 进入路径
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nano config.py # 用任意文本编辑器编辑config.py, 配置 “Proxy”, “API_KEY” 以及 “WEB_PORT” (例如50923) 等
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docker build -t gpt-academic . # 安装
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@ -80,6 +80,7 @@ ChatGLM_PTUNING_CHECKPOINT = "" # 例如"/home/hmp/ChatGLM2-6B/ptuning/output/6b
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# 本地LLM模型如ChatGLM的执行方式 CPU/GPU
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LOCAL_MODEL_DEVICE = "cpu" # 可选 "cuda"
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LOCAL_MODEL_QUANT = "FP16" # 默认 "FP16" "INT4" 启用量化INT4版本 "INT8" 启用量化INT8版本
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# 设置gradio的并行线程数(不需要修改)
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@ -22,7 +22,8 @@ def split_subprocess(txt, project_folder, return_dict, opts):
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mask = np.zeros(len(txt), dtype=np.uint8) + TRANSFORM
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# 吸收title与作者以上的部分
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text, mask = set_forbidden_text(text, mask, r"(.*?)\\maketitle", re.DOTALL)
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text, mask = set_forbidden_text(text, mask, r"^(.*?)\\maketitle", re.DOTALL)
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text, mask = set_forbidden_text(text, mask, r"^(.*?)\\begin{document}", re.DOTALL)
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# 吸收iffalse注释
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text, mask = set_forbidden_text(text, mask, r"\\iffalse(.*?)\\fi", re.DOTALL)
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# 吸收在42行以内的begin-end组合
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@ -19,7 +19,7 @@ class AliyunASR():
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pass
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def test_on_error(self, message, *args):
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# print("on_error args=>{}".format(args))
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print("on_error args=>{}".format(args))
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pass
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def test_on_close(self, *args):
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@ -50,6 +50,8 @@ class AliyunASR():
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rad.clean_up()
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temp_folder = tempfile.gettempdir()
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TOKEN, APPKEY = get_conf('ALIYUN_TOKEN', 'ALIYUN_APPKEY')
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if len(TOKEN) == 0:
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TOKEN = self.get_token()
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self.aliyun_service_ok = True
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URL="wss://nls-gateway.aliyuncs.com/ws/v1"
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sr = nls.NlsSpeechTranscriber(
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@ -91,3 +93,38 @@ class AliyunASR():
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self.stop = True
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self.stop_msg = 'Aliyun音频服务异常,请检查ALIYUN_TOKEN和ALIYUN_APPKEY是否过期。'
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r = sr.stop()
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def get_token(self):
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from toolbox import get_conf
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import json
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from aliyunsdkcore.request import CommonRequest
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from aliyunsdkcore.client import AcsClient
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AccessKey_ID, AccessKey_secret = get_conf('ALIYUN_ACCESSKEY', 'ALIYUN_SECRET')
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# 创建AcsClient实例
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client = AcsClient(
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AccessKey_ID,
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AccessKey_secret,
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"cn-shanghai"
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)
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# 创建request,并设置参数。
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request = CommonRequest()
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request.set_method('POST')
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request.set_domain('nls-meta.cn-shanghai.aliyuncs.com')
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request.set_version('2019-02-28')
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request.set_action_name('CreateToken')
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try:
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response = client.do_action_with_exception(request)
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print(response)
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jss = json.loads(response)
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if 'Token' in jss and 'Id' in jss['Token']:
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token = jss['Token']['Id']
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expireTime = jss['Token']['ExpireTime']
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print("token = " + token)
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print("expireTime = " + str(expireTime))
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except Exception as e:
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print(e)
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return token
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@ -179,12 +179,12 @@ def 语音助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
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import nls
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from scipy import io
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except:
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chatbot.append(["导入依赖失败", "使用该模块需要额外依赖, 安装方法:```pip install --upgrade pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git```"])
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chatbot.append(["导入依赖失败", "使用该模块需要额外依赖, 安装方法:```pip install --upgrade aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git```"])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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TOKEN, APPKEY = get_conf('ALIYUN_TOKEN', 'ALIYUN_APPKEY')
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if TOKEN == "" or APPKEY == "":
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APPKEY = get_conf('ALIYUN_APPKEY')
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if APPKEY == "":
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chatbot.append(["导入依赖失败", "没有阿里云语音识别APPKEY和TOKEN, 详情见https://help.aliyun.com/document_detail/450255.html"])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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@ -37,15 +37,23 @@ class GetGLMHandle(Process):
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# 子进程执行
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# 第一次运行,加载参数
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retry = 0
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LOCAL_MODEL_QUANT, device = get_conf('LOCAL_MODEL_QUANT', 'LOCAL_MODEL_DEVICE')
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if LOCAL_MODEL_QUANT == "INT4": # INT4
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_model_name_ = "THUDM/chatglm2-6b-int4"
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elif LOCAL_MODEL_QUANT == "INT8": # INT8
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_model_name_ = "THUDM/chatglm2-6b-int8"
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else:
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_model_name_ = "THUDM/chatglm2-6b" # FP16
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while True:
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try:
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if self.chatglm_model is None:
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self.chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True)
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device, = get_conf('LOCAL_MODEL_DEVICE')
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self.chatglm_tokenizer = AutoTokenizer.from_pretrained(_model_name_, trust_remote_code=True)
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if device=='cpu':
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self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).float()
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self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).float()
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else:
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self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).half().cuda()
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self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).half().cuda()
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self.chatglm_model = self.chatglm_model.eval()
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break
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else:
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@ -681,6 +681,7 @@ def read_single_conf_with_lru_cache(arg):
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else:
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print亮红( "[API_KEY] 您的 API_KEY 不满足任何一种已知的密钥格式,请在config文件中修改API密钥之后再运行。")
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if arg == 'proxies':
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if not read_single_conf_with_lru_cache('USE_PROXY'): r = None # 检查USE_PROXY,防止proxies单独起作用
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if r is None:
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print亮红('[PROXY] 网络代理状态:未配置。无代理状态下很可能无法访问OpenAI家族的模型。建议:检查USE_PROXY选项是否修改。')
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else:
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6
version
6
version
@ -1,5 +1,5 @@
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{
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"version": 3.46,
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"version": 3.47,
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"show_feature": true,
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"new_feature": "临时修复theme的文件丢失问题 <-> 新增实时语音对话插件(自动断句,脱手对话) <-> 支持加载自定义的ChatGLM2微调模型 <-> 动态ChatBot窗口高度 <-> 修复Azure接口的BUG <-> 完善多语言模块 <-> 完善本地Latex矫错和翻译功能 <-> 增加gpt-3.5-16k的支持 <-> 新增最强Arxiv论文翻译插件 <-> 修复gradio复制按钮BUG <-> 修复PDF翻译的BUG, 新增HTML中英双栏对照 <-> 添加了OpenAI图片生成插件"
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}
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"new_feature": "优化一键升级 <-> 提高arxiv翻译速度和成功率 <-> 支持自定义APIKEY格式 <-> 临时修复theme的文件丢失问题 <-> 新增实时语音对话插件(自动断句,脱手对话) <-> 支持加载自定义的ChatGLM2微调模型 <-> 动态ChatBot窗口高度 <-> 修复Azure接口的BUG <-> 完善多语言模块 <-> 完善本地Latex矫错和翻译功能 <-> 增加gpt-3.5-16k的支持"
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}
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