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@@ -1,5 +1,5 @@
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> [!IMPORTANT]
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> [!IMPORTANT]
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> `master主分支`最新动态(2025.2.4): 增加deepseek-r1支持
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> `master主分支`最新动态(2025.3.2): 修复大量代码typo / 联网组件支持Jina的api / 增加deepseek-r1支持
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> `frontier开发分支`最新动态(2024.12.9): 更新对话时间线功能,优化xelatex论文翻译
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> `frontier开发分支`最新动态(2024.12.9): 更新对话时间线功能,优化xelatex论文翻译
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> `wiki文档`最新动态(2024.12.5): 更新ollama接入指南
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> `wiki文档`最新动态(2024.12.5): 更新ollama接入指南
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>
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>
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@@ -8,7 +8,7 @@
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> 2024.10.10: 突发停电,紧急恢复了提供[whl包](https://drive.google.com/drive/folders/14kR-3V-lIbvGxri4AHc8TpiA1fqsw7SK?usp=sharing)的文件服务器
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> 2024.10.10: 突发停电,紧急恢复了提供[whl包](https://drive.google.com/drive/folders/14kR-3V-lIbvGxri4AHc8TpiA1fqsw7SK?usp=sharing)的文件服务器
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> 2024.5.1: 加入Doc2x翻译PDF论文的功能,[查看详情](https://github.com/binary-husky/gpt_academic/wiki/Doc2x)
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> 2024.5.1: 加入Doc2x翻译PDF论文的功能,[查看详情](https://github.com/binary-husky/gpt_academic/wiki/Doc2x)
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> 2024.3.11: 全力支持Qwen、GLM、DeepseekCoder等中文大语言模型! SoVits语音克隆模块,[查看详情](https://www.bilibili.com/video/BV1Rp421S7tF/)
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> 2024.3.11: 全力支持Qwen、GLM、DeepseekCoder等中文大语言模型! SoVits语音克隆模块,[查看详情](https://www.bilibili.com/video/BV1Rp421S7tF/)
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> 2024.1.17: 安装依赖时,请选择`requirements.txt`中**指定的版本**。 安装命令:`pip install -r requirements.txt`。本项目完全开源免费,您可通过订阅[在线服务](https://github.com/binary-husky/gpt_academic/wiki/online)的方式鼓励本项目的发展。
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> 2024.1.17: 安装依赖时,请选择`requirements.txt`中**指定的版本**。 安装命令:`pip install -r requirements.txt`。
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<br>
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<br>
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@@ -428,7 +428,6 @@ timeline LR
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1. `master` 分支: 主分支,稳定版
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1. `master` 分支: 主分支,稳定版
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2. `frontier` 分支: 开发分支,测试版
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2. `frontier` 分支: 开发分支,测试版
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3. 如何[接入其他大模型](request_llms/README.md)
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3. 如何[接入其他大模型](request_llms/README.md)
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4. 访问GPT-Academic的[在线服务并支持我们](https://github.com/binary-husky/gpt_academic/wiki/online)
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### V:参考与学习
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### V:参考与学习
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@@ -344,6 +344,8 @@ NUM_CUSTOM_BASIC_BTN = 4
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DAAS_SERVER_URLS = [ f"https://niuziniu-biligpt{i}.hf.space/stream" for i in range(1,5) ]
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DAAS_SERVER_URLS = [ f"https://niuziniu-biligpt{i}.hf.space/stream" for i in range(1,5) ]
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# 在互联网搜索组件中,负责将搜索结果整理成干净的Markdown
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JINA_API_KEY = ""
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"""
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"""
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--------------- 配置关联关系说明 ---------------
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--------------- 配置关联关系说明 ---------------
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@@ -113,7 +113,7 @@ def get_crazy_functions():
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"Group": "学术",
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"Group": "学术",
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"Color": "stop",
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"Color": "stop",
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"AsButton": True,
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"AsButton": True,
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"Info": "Arixv论文精细翻译 | 输入参数arxiv论文的ID,比如1812.10695",
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"Info": "ArXiv论文精细翻译 | 输入参数arxiv论文的ID,比如1812.10695",
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"Function": HotReload(Latex翻译中文并重新编译PDF), # 当注册Class后,Function旧接口仅会在“虚空终端”中起作用
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"Function": HotReload(Latex翻译中文并重新编译PDF), # 当注册Class后,Function旧接口仅会在“虚空终端”中起作用
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"Class": Arxiv_Localize, # 新一代插件需要注册Class
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"Class": Arxiv_Localize, # 新一代插件需要注册Class
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},
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},
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@@ -352,7 +352,7 @@ def get_crazy_functions():
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"ArgsReminder": r"如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 "
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"ArgsReminder": r"如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 "
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r"例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: "
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r"例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: "
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r'If the term "agent" is used in this section, it should be translated to "智能体". ',
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r'If the term "agent" is used in this section, it should be translated to "智能体". ',
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"Info": "Arixv论文精细翻译 | 输入参数arxiv论文的ID,比如1812.10695",
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"Info": "ArXiv论文精细翻译 | 输入参数arxiv论文的ID,比如1812.10695",
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"Function": HotReload(Latex翻译中文并重新编译PDF), # 当注册Class后,Function旧接口仅会在“虚空终端”中起作用
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"Function": HotReload(Latex翻译中文并重新编译PDF), # 当注册Class后,Function旧接口仅会在“虚空终端”中起作用
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"Class": Arxiv_Localize, # 新一代插件需要注册Class
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"Class": Arxiv_Localize, # 新一代插件需要注册Class
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},
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},
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@@ -434,36 +434,6 @@ def get_crazy_functions():
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logger.error(trimmed_format_exc())
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logger.error(trimmed_format_exc())
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logger.error("Load function plugin failed")
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logger.error("Load function plugin failed")
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# try:
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# from crazy_functions.联网的ChatGPT import 连接网络回答问题
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# function_plugins.update(
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# {
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# "连接网络回答问题(输入问题后点击该插件,需要访问谷歌)": {
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# "Group": "对话",
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# "Color": "stop",
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# "AsButton": False, # 加入下拉菜单中
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# # "Info": "连接网络回答问题(需要访问谷歌)| 输入参数是一个问题",
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# "Function": HotReload(连接网络回答问题),
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# }
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# }
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# )
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# from crazy_functions.联网的ChatGPT_bing版 import 连接bing搜索回答问题
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# function_plugins.update(
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# {
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# "连接网络回答问题(中文Bing版,输入问题后点击该插件)": {
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# "Group": "对话",
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# "Color": "stop",
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# "AsButton": False, # 加入下拉菜单中
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# "Info": "连接网络回答问题(需要访问中文Bing)| 输入参数是一个问题",
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# "Function": HotReload(连接bing搜索回答问题),
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# }
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# }
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# )
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# except:
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# logger.error(trimmed_format_exc())
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# logger.error("Load function plugin failed")
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try:
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try:
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from crazy_functions.SourceCode_Analyse import 解析任意code项目
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from crazy_functions.SourceCode_Analyse import 解析任意code项目
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@@ -771,6 +741,9 @@ def get_multiplex_button_functions():
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"常规对话":
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"常规对话":
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"",
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"",
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"查互联网后回答":
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"查互联网后回答",
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"多模型对话":
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"多模型对话":
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"询问多个GPT模型", # 映射到上面的 `询问多个GPT模型` 插件
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"询问多个GPT模型", # 映射到上面的 `询问多个GPT模型` 插件
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@@ -7,7 +7,7 @@ from bs4 import BeautifulSoup
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from functools import lru_cache
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from functools import lru_cache
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from itertools import zip_longest
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from itertools import zip_longest
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from check_proxy import check_proxy
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from check_proxy import check_proxy
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from toolbox import CatchException, update_ui, get_conf, update_ui_lastest_msg
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from toolbox import CatchException, update_ui, get_conf, update_ui_latest_msg
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from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
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from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
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from request_llms.bridge_all import model_info
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from request_llms.bridge_all import model_info
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from request_llms.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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@@ -49,7 +49,7 @@ def search_optimizer(
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mutable = ["", time.time(), ""]
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mutable = ["", time.time(), ""]
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llm_kwargs["temperature"] = 0.8
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llm_kwargs["temperature"] = 0.8
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try:
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try:
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querys_json = predict_no_ui_long_connection(
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query_json = predict_no_ui_long_connection(
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inputs=query,
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inputs=query,
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llm_kwargs=llm_kwargs,
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llm_kwargs=llm_kwargs,
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history=[],
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history=[],
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@@ -57,31 +57,31 @@ def search_optimizer(
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observe_window=mutable,
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observe_window=mutable,
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)
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)
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except Exception:
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except Exception:
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querys_json = "1234"
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query_json = "null"
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#* 尝试解码优化后的搜索结果
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#* 尝试解码优化后的搜索结果
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querys_json = re.sub(r"```json|```", "", querys_json)
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query_json = re.sub(r"```json|```", "", query_json)
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try:
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try:
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querys = json.loads(querys_json)
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queries = json.loads(query_json)
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except Exception:
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except Exception:
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#* 如果解码失败,降低温度再试一次
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#* 如果解码失败,降低温度再试一次
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try:
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try:
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llm_kwargs["temperature"] = 0.4
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llm_kwargs["temperature"] = 0.4
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querys_json = predict_no_ui_long_connection(
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query_json = predict_no_ui_long_connection(
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inputs=query,
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inputs=query,
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llm_kwargs=llm_kwargs,
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llm_kwargs=llm_kwargs,
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history=[],
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history=[],
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sys_prompt=sys_prompt,
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sys_prompt=sys_prompt,
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observe_window=mutable,
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observe_window=mutable,
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)
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)
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querys_json = re.sub(r"```json|```", "", querys_json)
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query_json = re.sub(r"```json|```", "", query_json)
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querys = json.loads(querys_json)
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queries = json.loads(query_json)
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except Exception:
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except Exception:
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#* 如果再次失败,直接返回原始问题
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#* 如果再次失败,直接返回原始问题
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querys = [query]
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queries = [query]
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links = []
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links = []
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success = 0
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success = 0
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Exceptions = ""
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Exceptions = ""
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for q in querys:
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for q in queries:
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try:
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try:
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link = searxng_request(q, proxies, categories, searxng_url, engines=engines)
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link = searxng_request(q, proxies, categories, searxng_url, engines=engines)
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if len(link) > 0:
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if len(link) > 0:
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@@ -175,10 +175,17 @@ def scrape_text(url, proxies) -> str:
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Returns:
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Returns:
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str: The scraped text
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str: The scraped text
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"""
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"""
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from loguru import logger
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headers = {
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headers = {
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'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
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'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
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'Content-Type': 'text/plain',
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'Content-Type': 'text/plain',
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}
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}
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# 首先采用Jina进行文本提取
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if get_conf("JINA_API_KEY"):
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try: return jina_scrape_text(url)
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except: logger.debug("Jina API 请求失败,回到旧方法")
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try:
|
try:
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response = requests.get(url, headers=headers, proxies=proxies, timeout=8)
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response = requests.get(url, headers=headers, proxies=proxies, timeout=8)
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if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
|
if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
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@@ -193,21 +200,39 @@ def scrape_text(url, proxies) -> str:
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text = "\n".join(chunk for chunk in chunks if chunk)
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text = "\n".join(chunk for chunk in chunks if chunk)
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return text
|
return text
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|
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|
def jina_scrape_text(url) -> str:
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|
"jina_39727421c8fa4e4fa9bd698e5211feaaDyGeVFESNrRaepWiLT0wmHYJSh-d"
|
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|
headers = {
|
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|
'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
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'Content-Type': 'text/plain',
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"X-Retain-Images": "none",
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"Authorization": f'Bearer {get_conf("JINA_API_KEY")}'
|
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}
|
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response = requests.get("https://r.jina.ai/" + url, headers=headers, proxies=None, timeout=8)
|
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|
if response.status_code != 200:
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|
raise ValueError("Jina API 请求失败,开始尝试旧方法!" + response.text)
|
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|
if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
|
||||||
|
result = response.text
|
||||||
|
result = result.replace("\\[", "[").replace("\\]", "]").replace("\\(", "(").replace("\\)", ")")
|
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return response.text
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|
|
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|
|
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def internet_search_with_analysis_prompt(prompt, analysis_prompt, llm_kwargs, chatbot):
|
def internet_search_with_analysis_prompt(prompt, analysis_prompt, llm_kwargs, chatbot):
|
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from toolbox import get_conf
|
from toolbox import get_conf
|
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proxies = get_conf('proxies')
|
proxies = get_conf('proxies')
|
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categories = 'general'
|
categories = 'general'
|
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searxng_url = None # 使用默认的searxng_url
|
searxng_url = None # 使用默认的searxng_url
|
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engines = None # 使用默认的搜索引擎
|
engines = None # 使用默认的搜索引擎
|
||||||
yield from update_ui_lastest_msg(lastmsg=f"检索中: {prompt} ...", chatbot=chatbot, history=[], delay=1)
|
yield from update_ui_latest_msg(lastmsg=f"检索中: {prompt} ...", chatbot=chatbot, history=[], delay=1)
|
||||||
urls = searxng_request(prompt, proxies, categories, searxng_url, engines=engines)
|
urls = searxng_request(prompt, proxies, categories, searxng_url, engines=engines)
|
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yield from update_ui_lastest_msg(lastmsg=f"依次访问搜索到的网站 ...", chatbot=chatbot, history=[], delay=1)
|
yield from update_ui_latest_msg(lastmsg=f"依次访问搜索到的网站 ...", chatbot=chatbot, history=[], delay=1)
|
||||||
if len(urls) == 0:
|
if len(urls) == 0:
|
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return None
|
return None
|
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max_search_result = 5 # 最多收纳多少个网页的结果
|
max_search_result = 5 # 最多收纳多少个网页的结果
|
||||||
history = []
|
history = []
|
||||||
for index, url in enumerate(urls[:max_search_result]):
|
for index, url in enumerate(urls[:max_search_result]):
|
||||||
yield from update_ui_lastest_msg(lastmsg=f"依次访问搜索到的网站: {url['link']} ...", chatbot=chatbot, history=[], delay=1)
|
yield from update_ui_latest_msg(lastmsg=f"依次访问搜索到的网站: {url['link']} ...", chatbot=chatbot, history=[], delay=1)
|
||||||
res = scrape_text(url['link'], proxies)
|
res = scrape_text(url['link'], proxies)
|
||||||
prefix = f"第{index}份搜索结果 [源自{url['source'][0]}搜索] ({url['title'][:25]}):"
|
prefix = f"第{index}份搜索结果 [源自{url['source'][0]}搜索] ({url['title'][:25]}):"
|
||||||
history.extend([prefix, res])
|
history.extend([prefix, res])
|
||||||
@@ -222,7 +247,7 @@ def internet_search_with_analysis_prompt(prompt, analysis_prompt, llm_kwargs, ch
|
|||||||
llm_kwargs=llm_kwargs,
|
llm_kwargs=llm_kwargs,
|
||||||
history=history,
|
history=history,
|
||||||
sys_prompt="请从搜索结果中抽取信息,对最相关的两个搜索结果进行总结,然后回答问题。",
|
sys_prompt="请从搜索结果中抽取信息,对最相关的两个搜索结果进行总结,然后回答问题。",
|
||||||
console_slience=False,
|
console_silence=False,
|
||||||
)
|
)
|
||||||
return gpt_say
|
return gpt_say
|
||||||
|
|
||||||
@@ -246,23 +271,52 @@ def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
|
|||||||
urls = search_optimizer(txt, proxies, optimizer_history, llm_kwargs, optimizer, categories, searxng_url, engines)
|
urls = search_optimizer(txt, proxies, optimizer_history, llm_kwargs, optimizer, categories, searxng_url, engines)
|
||||||
history = []
|
history = []
|
||||||
if len(urls) == 0:
|
if len(urls) == 0:
|
||||||
chatbot.append((f"结论:{txt}",
|
chatbot.append((f"结论:{txt}", "[Local Message] 受到限制,无法从searxng获取信息!请尝试更换搜索引擎。"))
|
||||||
"[Local Message] 受到限制,无法从searxng获取信息!请尝试更换搜索引擎。"))
|
|
||||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
return
|
return
|
||||||
|
|
||||||
# ------------- < 第2步:依次访问网页 > -------------
|
# ------------- < 第2步:依次访问网页 > -------------
|
||||||
|
from concurrent.futures import ThreadPoolExecutor
|
||||||
|
from textwrap import dedent
|
||||||
max_search_result = 5 # 最多收纳多少个网页的结果
|
max_search_result = 5 # 最多收纳多少个网页的结果
|
||||||
if optimizer == "开启(增强)":
|
if optimizer == "开启(增强)":
|
||||||
max_search_result = 8
|
max_search_result = 8
|
||||||
chatbot.append(["联网检索中 ...", None])
|
template = dedent("""
|
||||||
for index, url in enumerate(urls[:max_search_result]):
|
<details>
|
||||||
res = scrape_text(url['link'], proxies)
|
<summary>{TITLE}</summary>
|
||||||
prefix = f"第{index}份搜索结果 [源自{url['source'][0]}搜索] ({url['title'][:25]}):"
|
<div class="search_result">{URL}</div>
|
||||||
history.extend([prefix, res])
|
<div class="search_result">{CONTENT}</div>
|
||||||
res_squeeze = res.replace('\n', '...')
|
</details>
|
||||||
chatbot[-1] = [prefix + "\n\n" + res_squeeze[:500] + "......", None]
|
""")
|
||||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
|
||||||
|
buffer = ""
|
||||||
|
|
||||||
|
# 创建线程池
|
||||||
|
with ThreadPoolExecutor(max_workers=5) as executor:
|
||||||
|
# 提交任务到线程池
|
||||||
|
futures = []
|
||||||
|
for index, url in enumerate(urls[:max_search_result]):
|
||||||
|
future = executor.submit(scrape_text, url['link'], proxies)
|
||||||
|
futures.append((index, future, url))
|
||||||
|
|
||||||
|
# 处理完成的任务
|
||||||
|
for index, future, url in futures:
|
||||||
|
# 开始
|
||||||
|
prefix = f"正在加载 第{index+1}份搜索结果 [源自{url['source'][0]}搜索] ({url['title'][:25]}):"
|
||||||
|
string_structure = template.format(TITLE=prefix, URL=url['link'], CONTENT="正在加载,请稍后 ......")
|
||||||
|
yield from update_ui_latest_msg(lastmsg=(buffer + string_structure), chatbot=chatbot, history=history, delay=0.1) # 刷新界面
|
||||||
|
|
||||||
|
# 获取结果
|
||||||
|
res = future.result()
|
||||||
|
|
||||||
|
# 显示结果
|
||||||
|
prefix = f"第{index+1}份搜索结果 [源自{url['source'][0]}搜索] ({url['title'][:25]}):"
|
||||||
|
string_structure = template.format(TITLE=prefix, URL=url['link'], CONTENT=res[:1000] + "......")
|
||||||
|
buffer += string_structure
|
||||||
|
|
||||||
|
# 更新历史
|
||||||
|
history.extend([prefix, res])
|
||||||
|
yield from update_ui_latest_msg(lastmsg=buffer, chatbot=chatbot, history=history, delay=0.1) # 刷新界面
|
||||||
|
|
||||||
# ------------- < 第3步:ChatGPT综合 > -------------
|
# ------------- < 第3步:ChatGPT综合 > -------------
|
||||||
if (optimizer != "开启(增强)"):
|
if (optimizer != "开启(增强)"):
|
||||||
|
|||||||
@@ -38,11 +38,12 @@ class NetworkGPT_Wrap(GptAcademicPluginTemplate):
|
|||||||
}
|
}
|
||||||
return gui_definition
|
return gui_definition
|
||||||
|
|
||||||
def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
|
def execute(txt, llm_kwargs, plugin_kwargs:dict, chatbot, history, system_prompt, user_request):
|
||||||
"""
|
"""
|
||||||
执行插件
|
执行插件
|
||||||
"""
|
"""
|
||||||
if plugin_kwargs["categories"] == "网页": plugin_kwargs["categories"] = "general"
|
if plugin_kwargs.get("categories", None) == "网页": plugin_kwargs["categories"] = "general"
|
||||||
if plugin_kwargs["categories"] == "学术论文": plugin_kwargs["categories"] = "science"
|
elif plugin_kwargs.get("categories", None) == "学术论文": plugin_kwargs["categories"] = "science"
|
||||||
|
else: plugin_kwargs["categories"] = "general"
|
||||||
yield from 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
|
yield from 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
|
||||||
|
|
||||||
|
|||||||
@@ -1,5 +1,5 @@
|
|||||||
from toolbox import update_ui, trimmed_format_exc, get_conf, get_log_folder, promote_file_to_downloadzone, check_repeat_upload, map_file_to_sha256
|
from toolbox import update_ui, trimmed_format_exc, get_conf, get_log_folder, promote_file_to_downloadzone, check_repeat_upload, map_file_to_sha256
|
||||||
from toolbox import CatchException, report_exception, update_ui_lastest_msg, zip_result, gen_time_str
|
from toolbox import CatchException, report_exception, update_ui_latest_msg, zip_result, gen_time_str
|
||||||
from functools import partial
|
from functools import partial
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
|
|
||||||
@@ -41,7 +41,7 @@ def switch_prompt(pfg, mode, more_requirement):
|
|||||||
return inputs_array, sys_prompt_array
|
return inputs_array, sys_prompt_array
|
||||||
|
|
||||||
|
|
||||||
def desend_to_extracted_folder_if_exist(project_folder):
|
def descend_to_extracted_folder_if_exist(project_folder):
|
||||||
"""
|
"""
|
||||||
Descend into the extracted folder if it exists, otherwise return the original folder.
|
Descend into the extracted folder if it exists, otherwise return the original folder.
|
||||||
|
|
||||||
@@ -130,7 +130,7 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
|
|||||||
|
|
||||||
if not txt.startswith('https://arxiv.org/abs/'):
|
if not txt.startswith('https://arxiv.org/abs/'):
|
||||||
msg = f"解析arxiv网址失败, 期望格式例如: https://arxiv.org/abs/1707.06690。实际得到格式: {url_}。"
|
msg = f"解析arxiv网址失败, 期望格式例如: https://arxiv.org/abs/1707.06690。实际得到格式: {url_}。"
|
||||||
yield from update_ui_lastest_msg(msg, chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui_latest_msg(msg, chatbot=chatbot, history=history) # 刷新界面
|
||||||
return msg, None
|
return msg, None
|
||||||
# <-------------- set format ------------->
|
# <-------------- set format ------------->
|
||||||
arxiv_id = url_.split('/abs/')[-1]
|
arxiv_id = url_.split('/abs/')[-1]
|
||||||
@@ -156,16 +156,16 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
|
|||||||
return False
|
return False
|
||||||
|
|
||||||
if os.path.exists(dst) and allow_cache:
|
if os.path.exists(dst) and allow_cache:
|
||||||
yield from update_ui_lastest_msg(f"调用缓存 {arxiv_id}", chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui_latest_msg(f"调用缓存 {arxiv_id}", chatbot=chatbot, history=history) # 刷新界面
|
||||||
success = True
|
success = True
|
||||||
else:
|
else:
|
||||||
yield from update_ui_lastest_msg(f"开始下载 {arxiv_id}", chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui_latest_msg(f"开始下载 {arxiv_id}", chatbot=chatbot, history=history) # 刷新界面
|
||||||
success = fix_url_and_download()
|
success = fix_url_and_download()
|
||||||
yield from update_ui_lastest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui_latest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
|
||||||
|
|
||||||
if not success:
|
if not success:
|
||||||
yield from update_ui_lastest_msg(f"下载失败 {arxiv_id}", chatbot=chatbot, history=history)
|
yield from update_ui_latest_msg(f"下载失败 {arxiv_id}", chatbot=chatbot, history=history)
|
||||||
raise tarfile.ReadError(f"论文下载失败 {arxiv_id}")
|
raise tarfile.ReadError(f"论文下载失败 {arxiv_id}")
|
||||||
|
|
||||||
# <-------------- extract file ------------->
|
# <-------------- extract file ------------->
|
||||||
@@ -288,7 +288,7 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo
|
|||||||
return
|
return
|
||||||
|
|
||||||
# <-------------- if is a zip/tar file ------------->
|
# <-------------- if is a zip/tar file ------------->
|
||||||
project_folder = desend_to_extracted_folder_if_exist(project_folder)
|
project_folder = descend_to_extracted_folder_if_exist(project_folder)
|
||||||
|
|
||||||
# <-------------- move latex project away from temp folder ------------->
|
# <-------------- move latex project away from temp folder ------------->
|
||||||
from shared_utils.fastapi_server import validate_path_safety
|
from shared_utils.fastapi_server import validate_path_safety
|
||||||
@@ -365,7 +365,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
|
|||||||
try:
|
try:
|
||||||
txt, arxiv_id = yield from arxiv_download(chatbot, history, txt, allow_cache)
|
txt, arxiv_id = yield from arxiv_download(chatbot, history, txt, allow_cache)
|
||||||
except tarfile.ReadError as e:
|
except tarfile.ReadError as e:
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
"无法自动下载该论文的Latex源码,请前往arxiv打开此论文下载页面,点other Formats,然后download source手动下载latex源码包。接下来调用本地Latex翻译插件即可。",
|
"无法自动下载该论文的Latex源码,请前往arxiv打开此论文下载页面,点other Formats,然后download source手动下载latex源码包。接下来调用本地Latex翻译插件即可。",
|
||||||
chatbot=chatbot, history=history)
|
chatbot=chatbot, history=history)
|
||||||
return
|
return
|
||||||
@@ -404,7 +404,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
|
|||||||
return
|
return
|
||||||
|
|
||||||
# <-------------- if is a zip/tar file ------------->
|
# <-------------- if is a zip/tar file ------------->
|
||||||
project_folder = desend_to_extracted_folder_if_exist(project_folder)
|
project_folder = descend_to_extracted_folder_if_exist(project_folder)
|
||||||
|
|
||||||
# <-------------- move latex project away from temp folder ------------->
|
# <-------------- move latex project away from temp folder ------------->
|
||||||
from shared_utils.fastapi_server import validate_path_safety
|
from shared_utils.fastapi_server import validate_path_safety
|
||||||
@@ -518,7 +518,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
|
|||||||
# repeat, project_folder = check_repeat_upload(file_manifest[0], hash_tag)
|
# repeat, project_folder = check_repeat_upload(file_manifest[0], hash_tag)
|
||||||
|
|
||||||
# if repeat:
|
# if repeat:
|
||||||
# yield from update_ui_lastest_msg(f"发现重复上传,请查收结果(压缩包)...", chatbot=chatbot, history=history)
|
# yield from update_ui_latest_msg(f"发现重复上传,请查收结果(压缩包)...", chatbot=chatbot, history=history)
|
||||||
# try:
|
# try:
|
||||||
# translate_pdf = [f for f in glob.glob(f'{project_folder}/**/merge_translate_zh.pdf', recursive=True)][0]
|
# translate_pdf = [f for f in glob.glob(f'{project_folder}/**/merge_translate_zh.pdf', recursive=True)][0]
|
||||||
# promote_file_to_downloadzone(translate_pdf, rename_file=None, chatbot=chatbot)
|
# promote_file_to_downloadzone(translate_pdf, rename_file=None, chatbot=chatbot)
|
||||||
@@ -531,7 +531,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
|
|||||||
# report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"发现重复上传,但是无法找到相关文件")
|
# report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"发现重复上传,但是无法找到相关文件")
|
||||||
# yield from update_ui(chatbot=chatbot, history=history)
|
# yield from update_ui(chatbot=chatbot, history=history)
|
||||||
# else:
|
# else:
|
||||||
# yield from update_ui_lastest_msg(f"未发现重复上传", chatbot=chatbot, history=history)
|
# yield from update_ui_latest_msg(f"未发现重复上传", chatbot=chatbot, history=history)
|
||||||
|
|
||||||
# <-------------- convert pdf into tex ------------->
|
# <-------------- convert pdf into tex ------------->
|
||||||
chatbot.append([f"解析项目: {txt}", "正在将PDF转换为tex项目,请耐心等待..."])
|
chatbot.append([f"解析项目: {txt}", "正在将PDF转换为tex项目,请耐心等待..."])
|
||||||
@@ -543,7 +543,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
|
|||||||
return False
|
return False
|
||||||
|
|
||||||
# <-------------- translate latex file into Chinese ------------->
|
# <-------------- translate latex file into Chinese ------------->
|
||||||
yield from update_ui_lastest_msg("正在tex项目将翻译为中文...", chatbot=chatbot, history=history)
|
yield from update_ui_latest_msg("正在tex项目将翻译为中文...", chatbot=chatbot, history=history)
|
||||||
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
|
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
|
||||||
if len(file_manifest) == 0:
|
if len(file_manifest) == 0:
|
||||||
report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.tex文件: {txt}")
|
report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.tex文件: {txt}")
|
||||||
@@ -551,7 +551,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
|
|||||||
return
|
return
|
||||||
|
|
||||||
# <-------------- if is a zip/tar file ------------->
|
# <-------------- if is a zip/tar file ------------->
|
||||||
project_folder = desend_to_extracted_folder_if_exist(project_folder)
|
project_folder = descend_to_extracted_folder_if_exist(project_folder)
|
||||||
|
|
||||||
# <-------------- move latex project away from temp folder ------------->
|
# <-------------- move latex project away from temp folder ------------->
|
||||||
from shared_utils.fastapi_server import validate_path_safety
|
from shared_utils.fastapi_server import validate_path_safety
|
||||||
@@ -571,7 +571,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
|
|||||||
switch_prompt=_switch_prompt_)
|
switch_prompt=_switch_prompt_)
|
||||||
|
|
||||||
# <-------------- compile PDF ------------->
|
# <-------------- compile PDF ------------->
|
||||||
yield from update_ui_lastest_msg("正在将翻译好的项目tex项目编译为PDF...", chatbot=chatbot, history=history)
|
yield from update_ui_latest_msg("正在将翻译好的项目tex项目编译为PDF...", chatbot=chatbot, history=history)
|
||||||
success = yield from 编译Latex(chatbot, history, main_file_original='merge',
|
success = yield from 编译Latex(chatbot, history, main_file_original='merge',
|
||||||
main_file_modified='merge_translate_zh', mode='translate_zh',
|
main_file_modified='merge_translate_zh', mode='translate_zh',
|
||||||
work_folder_original=project_folder, work_folder_modified=project_folder,
|
work_folder_original=project_folder, work_folder_modified=project_folder,
|
||||||
|
|||||||
@@ -1,5 +1,5 @@
|
|||||||
from toolbox import CatchException, check_packages, get_conf
|
from toolbox import CatchException, check_packages, get_conf
|
||||||
from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion
|
from toolbox import update_ui, update_ui_latest_msg, disable_auto_promotion
|
||||||
from toolbox import trimmed_format_exc_markdown
|
from toolbox import trimmed_format_exc_markdown
|
||||||
from crazy_functions.crazy_utils import get_files_from_everything
|
from crazy_functions.crazy_utils import get_files_from_everything
|
||||||
from crazy_functions.pdf_fns.parse_pdf import get_avail_grobid_url
|
from crazy_functions.pdf_fns.parse_pdf import get_avail_grobid_url
|
||||||
@@ -57,9 +57,9 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
|||||||
yield from 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url)
|
yield from 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url)
|
||||||
return
|
return
|
||||||
|
|
||||||
if method == "ClASSIC":
|
if method == "Classic":
|
||||||
# ------- 第三种方法,早期代码,效果不理想 -------
|
# ------- 第三种方法,早期代码,效果不理想 -------
|
||||||
yield from update_ui_lastest_msg("GROBID服务不可用,请检查config中的GROBID_URL。作为替代,现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
|
yield from update_ui_latest_msg("GROBID服务不可用,请检查config中的GROBID_URL。作为替代,现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
|
||||||
yield from 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
yield from 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
||||||
return
|
return
|
||||||
|
|
||||||
@@ -77,7 +77,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
|||||||
if grobid_url is not None:
|
if grobid_url is not None:
|
||||||
yield from 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url)
|
yield from 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url)
|
||||||
return
|
return
|
||||||
yield from update_ui_lastest_msg("GROBID服务不可用,请检查config中的GROBID_URL。作为替代,现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
|
yield from update_ui_latest_msg("GROBID服务不可用,请检查config中的GROBID_URL。作为替代,现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
|
||||||
yield from 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
yield from 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
||||||
return
|
return
|
||||||
|
|
||||||
|
|||||||
@@ -19,7 +19,7 @@ class PDF_Tran(GptAcademicPluginTemplate):
|
|||||||
"additional_prompt":
|
"additional_prompt":
|
||||||
ArgProperty(title="额外提示词", description="例如:对专有名词、翻译语气等方面的要求", default_value="", type="string").model_dump_json(), # 高级参数输入区,自动同步
|
ArgProperty(title="额外提示词", description="例如:对专有名词、翻译语气等方面的要求", default_value="", type="string").model_dump_json(), # 高级参数输入区,自动同步
|
||||||
"pdf_parse_method":
|
"pdf_parse_method":
|
||||||
ArgProperty(title="PDF解析方法", options=["DOC2X", "GROBID", "ClASSIC"], description="无", default_value="GROBID", type="dropdown").model_dump_json(),
|
ArgProperty(title="PDF解析方法", options=["DOC2X", "GROBID", "Classic"], description="无", default_value="GROBID", type="dropdown").model_dump_json(),
|
||||||
}
|
}
|
||||||
return gui_definition
|
return gui_definition
|
||||||
|
|
||||||
|
|||||||
@@ -4,7 +4,7 @@ from typing import List
|
|||||||
from shared_utils.fastapi_server import validate_path_safety
|
from shared_utils.fastapi_server import validate_path_safety
|
||||||
|
|
||||||
from toolbox import report_exception
|
from toolbox import report_exception
|
||||||
from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
|
from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_latest_msg
|
||||||
from shared_utils.fastapi_server import validate_path_safety
|
from shared_utils.fastapi_server import validate_path_safety
|
||||||
from crazy_functions.crazy_utils import input_clipping
|
from crazy_functions.crazy_utils import input_clipping
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||||
@@ -92,7 +92,7 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
|
|||||||
chatbot.append([txt, f'正在清空 ({current_context}) ...'])
|
chatbot.append([txt, f'正在清空 ({current_context}) ...'])
|
||||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
rag_worker.purge_vector_store()
|
rag_worker.purge_vector_store()
|
||||||
yield from update_ui_lastest_msg('已清空', chatbot, history, delay=0) # 刷新界面
|
yield from update_ui_latest_msg('已清空', chatbot, history, delay=0) # 刷新界面
|
||||||
return
|
return
|
||||||
|
|
||||||
# 3. Normal Q&A processing
|
# 3. Normal Q&A processing
|
||||||
@@ -109,10 +109,10 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
|
|||||||
|
|
||||||
# 5. If input is clipped, add input to vector store before retrieve
|
# 5. If input is clipped, add input to vector store before retrieve
|
||||||
if input_is_clipped_flag:
|
if input_is_clipped_flag:
|
||||||
yield from update_ui_lastest_msg('检测到长输入, 正在向量化 ...', chatbot, history, delay=0) # 刷新界面
|
yield from update_ui_latest_msg('检测到长输入, 正在向量化 ...', chatbot, history, delay=0) # 刷新界面
|
||||||
# Save input to vector store
|
# Save input to vector store
|
||||||
rag_worker.add_text_to_vector_store(txt_origin)
|
rag_worker.add_text_to_vector_store(txt_origin)
|
||||||
yield from update_ui_lastest_msg('向量化完成 ...', chatbot, history, delay=0) # 刷新界面
|
yield from update_ui_latest_msg('向量化完成 ...', chatbot, history, delay=0) # 刷新界面
|
||||||
|
|
||||||
if len(txt_origin) > REMEMBER_PREVIEW:
|
if len(txt_origin) > REMEMBER_PREVIEW:
|
||||||
HALF = REMEMBER_PREVIEW // 2
|
HALF = REMEMBER_PREVIEW // 2
|
||||||
@@ -142,7 +142,7 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
|
|||||||
)
|
)
|
||||||
|
|
||||||
# 8. Remember Q&A
|
# 8. Remember Q&A
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
model_say + '</br></br>' + f'对话记忆中, 请稍等 ({current_context}) ...',
|
model_say + '</br></br>' + f'对话记忆中, 请稍等 ({current_context}) ...',
|
||||||
chatbot, history, delay=0.5
|
chatbot, history, delay=0.5
|
||||||
)
|
)
|
||||||
@@ -150,4 +150,4 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
|
|||||||
history.extend([i_say, model_say])
|
history.extend([i_say, model_say])
|
||||||
|
|
||||||
# 9. Final UI Update
|
# 9. Final UI Update
|
||||||
yield from update_ui_lastest_msg(model_say, chatbot, history, delay=0, msg=tip)
|
yield from update_ui_latest_msg(model_say, chatbot, history, delay=0, msg=tip)
|
||||||
@@ -1,5 +1,5 @@
|
|||||||
import pickle, os, random
|
import pickle, os, random
|
||||||
from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
|
from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_latest_msg
|
||||||
from crazy_functions.crazy_utils import input_clipping
|
from crazy_functions.crazy_utils import input_clipping
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||||
from request_llms.bridge_all import predict_no_ui_long_connection
|
from request_llms.bridge_all import predict_no_ui_long_connection
|
||||||
@@ -9,7 +9,7 @@ from loguru import logger
|
|||||||
from typing import List
|
from typing import List
|
||||||
|
|
||||||
|
|
||||||
SOCIAL_NETWOK_WORKER_REGISTER = {}
|
SOCIAL_NETWORK_WORKER_REGISTER = {}
|
||||||
|
|
||||||
class SocialNetwork():
|
class SocialNetwork():
|
||||||
def __init__(self):
|
def __init__(self):
|
||||||
@@ -78,7 +78,7 @@ class SocialNetworkWorker(SaveAndLoad):
|
|||||||
for f in friend.friends_list:
|
for f in friend.friends_list:
|
||||||
self.add_friend(f)
|
self.add_friend(f)
|
||||||
msg = f"成功添加{len(friend.friends_list)}个联系人: {str(friend.friends_list)}"
|
msg = f"成功添加{len(friend.friends_list)}个联系人: {str(friend.friends_list)}"
|
||||||
yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=0)
|
||||||
|
|
||||||
|
|
||||||
def run(self, txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
|
def run(self, txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
|
||||||
@@ -104,12 +104,12 @@ class SocialNetworkWorker(SaveAndLoad):
|
|||||||
}
|
}
|
||||||
|
|
||||||
try:
|
try:
|
||||||
Explaination = '\n'.join([f'{k}: {v["explain_to_llm"]}' for k, v in self.tools_to_select.items()])
|
Explanation = '\n'.join([f'{k}: {v["explain_to_llm"]}' for k, v in self.tools_to_select.items()])
|
||||||
class UserSociaIntention(BaseModel):
|
class UserSociaIntention(BaseModel):
|
||||||
intention_type: str = Field(
|
intention_type: str = Field(
|
||||||
description=
|
description=
|
||||||
f"The type of user intention. You must choose from {self.tools_to_select.keys()}.\n\n"
|
f"The type of user intention. You must choose from {self.tools_to_select.keys()}.\n\n"
|
||||||
f"Explaination:\n{Explaination}",
|
f"Explanation:\n{Explanation}",
|
||||||
default="SocialAdvice"
|
default="SocialAdvice"
|
||||||
)
|
)
|
||||||
pydantic_cls_instance, err_msg = select_tool(
|
pydantic_cls_instance, err_msg = select_tool(
|
||||||
@@ -118,7 +118,7 @@ class SocialNetworkWorker(SaveAndLoad):
|
|||||||
pydantic_cls=UserSociaIntention
|
pydantic_cls=UserSociaIntention
|
||||||
)
|
)
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"无法理解用户意图 {err_msg}",
|
lastmsg=f"无法理解用户意图 {err_msg}",
|
||||||
chatbot=chatbot,
|
chatbot=chatbot,
|
||||||
history=history,
|
history=history,
|
||||||
@@ -150,10 +150,10 @@ def I人助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt,
|
|||||||
# 1. we retrieve worker from global context
|
# 1. we retrieve worker from global context
|
||||||
user_name = chatbot.get_user()
|
user_name = chatbot.get_user()
|
||||||
checkpoint_dir=get_log_folder(user_name, plugin_name='experimental_rag')
|
checkpoint_dir=get_log_folder(user_name, plugin_name='experimental_rag')
|
||||||
if user_name in SOCIAL_NETWOK_WORKER_REGISTER:
|
if user_name in SOCIAL_NETWORK_WORKER_REGISTER:
|
||||||
social_network_worker = SOCIAL_NETWOK_WORKER_REGISTER[user_name]
|
social_network_worker = SOCIAL_NETWORK_WORKER_REGISTER[user_name]
|
||||||
else:
|
else:
|
||||||
social_network_worker = SOCIAL_NETWOK_WORKER_REGISTER[user_name] = SocialNetworkWorker(
|
social_network_worker = SOCIAL_NETWORK_WORKER_REGISTER[user_name] = SocialNetworkWorker(
|
||||||
user_name,
|
user_name,
|
||||||
llm_kwargs,
|
llm_kwargs,
|
||||||
checkpoint_dir=checkpoint_dir,
|
checkpoint_dir=checkpoint_dir,
|
||||||
|
|||||||
@@ -1,5 +1,5 @@
|
|||||||
import os, copy, time
|
import os, copy, time
|
||||||
from toolbox import CatchException, report_exception, update_ui, zip_result, promote_file_to_downloadzone, update_ui_lastest_msg, get_conf, generate_file_link
|
from toolbox import CatchException, report_exception, update_ui, zip_result, promote_file_to_downloadzone, update_ui_latest_msg, get_conf, generate_file_link
|
||||||
from shared_utils.fastapi_server import validate_path_safety
|
from shared_utils.fastapi_server import validate_path_safety
|
||||||
from crazy_functions.crazy_utils import input_clipping
|
from crazy_functions.crazy_utils import input_clipping
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
|
from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
|
||||||
@@ -117,7 +117,7 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
|
|||||||
logger.error(f"文件: {fp} 的注释结果未能成功")
|
logger.error(f"文件: {fp} 的注释结果未能成功")
|
||||||
file_links = generate_file_link(preview_html_list)
|
file_links = generate_file_link(preview_html_list)
|
||||||
|
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
f"当前任务: <br/>{'<br/>'.join(tasks)}.<br/>" +
|
f"当前任务: <br/>{'<br/>'.join(tasks)}.<br/>" +
|
||||||
f"剩余源文件数量: {remain}.<br/>" +
|
f"剩余源文件数量: {remain}.<br/>" +
|
||||||
f"已完成的文件: {sum(worker_done)}.<br/>" +
|
f"已完成的文件: {sum(worker_done)}.<br/>" +
|
||||||
|
|||||||
@@ -7,7 +7,7 @@ from bs4 import BeautifulSoup
|
|||||||
from functools import lru_cache
|
from functools import lru_cache
|
||||||
from itertools import zip_longest
|
from itertools import zip_longest
|
||||||
from check_proxy import check_proxy
|
from check_proxy import check_proxy
|
||||||
from toolbox import CatchException, update_ui, get_conf, promote_file_to_downloadzone, update_ui_lastest_msg, generate_file_link
|
from toolbox import CatchException, update_ui, get_conf, promote_file_to_downloadzone, update_ui_latest_msg, generate_file_link
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
|
||||||
from request_llms.bridge_all import model_info
|
from request_llms.bridge_all import model_info
|
||||||
from request_llms.bridge_all import predict_no_ui_long_connection
|
from request_llms.bridge_all import predict_no_ui_long_connection
|
||||||
@@ -46,7 +46,7 @@ def download_video(bvid, user_name, chatbot, history):
|
|||||||
# pause a while
|
# pause a while
|
||||||
tic_time = 8
|
tic_time = 8
|
||||||
for i in range(tic_time):
|
for i in range(tic_time):
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"即将下载音频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。",
|
lastmsg=f"即将下载音频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。",
|
||||||
chatbot=chatbot, history=[], delay=1)
|
chatbot=chatbot, history=[], delay=1)
|
||||||
|
|
||||||
@@ -61,13 +61,13 @@ def download_video(bvid, user_name, chatbot, history):
|
|||||||
# preview
|
# preview
|
||||||
preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files]
|
preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files]
|
||||||
file_links = generate_file_link(preview_list)
|
file_links = generate_file_link(preview_list)
|
||||||
yield from update_ui_lastest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
|
||||||
chatbot.append((None, f"即将下载视频。"))
|
chatbot.append((None, f"即将下载视频。"))
|
||||||
|
|
||||||
# pause a while
|
# pause a while
|
||||||
tic_time = 16
|
tic_time = 16
|
||||||
for i in range(tic_time):
|
for i in range(tic_time):
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"即将下载视频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。",
|
lastmsg=f"即将下载视频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。",
|
||||||
chatbot=chatbot, history=[], delay=1)
|
chatbot=chatbot, history=[], delay=1)
|
||||||
|
|
||||||
@@ -78,7 +78,7 @@ def download_video(bvid, user_name, chatbot, history):
|
|||||||
# preview
|
# preview
|
||||||
preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files_part2]
|
preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files_part2]
|
||||||
file_links = generate_file_link(preview_list)
|
file_links = generate_file_link(preview_list)
|
||||||
yield from update_ui_lastest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
|
||||||
|
|
||||||
# return
|
# return
|
||||||
return downloaded_files + downloaded_files_part2
|
return downloaded_files + downloaded_files_part2
|
||||||
@@ -110,7 +110,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
|
|||||||
# 结构化生成
|
# 结构化生成
|
||||||
internet_search_keyword = user_wish
|
internet_search_keyword = user_wish
|
||||||
|
|
||||||
yield from update_ui_lastest_msg(lastmsg=f"发起互联网检索: {internet_search_keyword} ...", chatbot=chatbot, history=[], delay=1)
|
yield from update_ui_latest_msg(lastmsg=f"发起互联网检索: {internet_search_keyword} ...", chatbot=chatbot, history=[], delay=1)
|
||||||
from crazy_functions.Internet_GPT import internet_search_with_analysis_prompt
|
from crazy_functions.Internet_GPT import internet_search_with_analysis_prompt
|
||||||
result = yield from internet_search_with_analysis_prompt(
|
result = yield from internet_search_with_analysis_prompt(
|
||||||
prompt=internet_search_keyword,
|
prompt=internet_search_keyword,
|
||||||
@@ -119,7 +119,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
|
|||||||
chatbot=chatbot
|
chatbot=chatbot
|
||||||
)
|
)
|
||||||
|
|
||||||
yield from update_ui_lastest_msg(lastmsg=f"互联网检索结论: {result} \n\n 正在生成进一步检索方案 ...", chatbot=chatbot, history=[], delay=1)
|
yield from update_ui_latest_msg(lastmsg=f"互联网检索结论: {result} \n\n 正在生成进一步检索方案 ...", chatbot=chatbot, history=[], delay=1)
|
||||||
rf_req = dedent(f"""
|
rf_req = dedent(f"""
|
||||||
The user wish to get the following resource:
|
The user wish to get the following resource:
|
||||||
{user_wish}
|
{user_wish}
|
||||||
@@ -132,7 +132,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
|
|||||||
rf_req = dedent(f"""
|
rf_req = dedent(f"""
|
||||||
The user wish to get the following resource:
|
The user wish to get the following resource:
|
||||||
{user_wish}
|
{user_wish}
|
||||||
Generate reseach keywords (less than 5 keywords) accordingly.
|
Generate research keywords (less than 5 keywords) accordingly.
|
||||||
""")
|
""")
|
||||||
gpt_json_io = GptJsonIO(Query)
|
gpt_json_io = GptJsonIO(Query)
|
||||||
inputs = rf_req + gpt_json_io.format_instructions
|
inputs = rf_req + gpt_json_io.format_instructions
|
||||||
@@ -146,12 +146,12 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
|
|||||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
|
||||||
# 获取候选资源
|
# 获取候选资源
|
||||||
candadate_dictionary: dict = get_video_resource(video_engine_keywords)
|
candidate_dictionary: dict = get_video_resource(video_engine_keywords)
|
||||||
candadate_dictionary_as_str = json.dumps(candadate_dictionary, ensure_ascii=False, indent=4)
|
candidate_dictionary_as_str = json.dumps(candidate_dictionary, ensure_ascii=False, indent=4)
|
||||||
|
|
||||||
# 展示候选资源
|
# 展示候选资源
|
||||||
candadate_display = "\n".join([f"{i+1}. {it['title']}" for i, it in enumerate(candadate_dictionary)])
|
candidate_display = "\n".join([f"{i+1}. {it['title']}" for i, it in enumerate(candidate_dictionary)])
|
||||||
chatbot.append((None, f"候选:\n\n{candadate_display}"))
|
chatbot.append((None, f"候选:\n\n{candidate_display}"))
|
||||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
|
||||||
# 结构化生成
|
# 结构化生成
|
||||||
@@ -160,7 +160,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
|
|||||||
{user_wish}
|
{user_wish}
|
||||||
|
|
||||||
Select the most relevant and suitable video resource from the following search results:
|
Select the most relevant and suitable video resource from the following search results:
|
||||||
{candadate_dictionary_as_str}
|
{candidate_dictionary_as_str}
|
||||||
|
|
||||||
Note:
|
Note:
|
||||||
1. The first several search video results are more likely to satisfy the user's wish.
|
1. The first several search video results are more likely to satisfy the user's wish.
|
||||||
|
|||||||
@@ -1,5 +1,5 @@
|
|||||||
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
|
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
|
||||||
from toolbox import report_exception, get_log_folder, update_ui_lastest_msg, Singleton
|
from toolbox import report_exception, get_log_folder, update_ui_latest_msg, Singleton
|
||||||
from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom
|
from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom
|
||||||
from crazy_functions.agent_fns.general import AutoGenGeneral
|
from crazy_functions.agent_fns.general import AutoGenGeneral
|
||||||
|
|
||||||
|
|||||||
@@ -8,7 +8,7 @@ class EchoDemo(PluginMultiprocessManager):
|
|||||||
while True:
|
while True:
|
||||||
msg = self.child_conn.recv() # PipeCom
|
msg = self.child_conn.recv() # PipeCom
|
||||||
if msg.cmd == "user_input":
|
if msg.cmd == "user_input":
|
||||||
# wait futher user input
|
# wait father user input
|
||||||
self.child_conn.send(PipeCom("show", msg.content))
|
self.child_conn.send(PipeCom("show", msg.content))
|
||||||
wait_success = self.subprocess_worker_wait_user_feedback(wait_msg="我准备好处理下一个问题了.")
|
wait_success = self.subprocess_worker_wait_user_feedback(wait_msg="我准备好处理下一个问题了.")
|
||||||
if not wait_success:
|
if not wait_success:
|
||||||
|
|||||||
@@ -27,7 +27,7 @@ def gpt_academic_generate_oai_reply(
|
|||||||
llm_kwargs=llm_config,
|
llm_kwargs=llm_config,
|
||||||
history=history,
|
history=history,
|
||||||
sys_prompt=self._oai_system_message[0]['content'],
|
sys_prompt=self._oai_system_message[0]['content'],
|
||||||
console_slience=True
|
console_silence=True
|
||||||
)
|
)
|
||||||
assumed_done = reply.endswith('\nTERMINATE')
|
assumed_done = reply.endswith('\nTERMINATE')
|
||||||
return True, reply
|
return True, reply
|
||||||
|
|||||||
@@ -10,7 +10,7 @@ from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_
|
|||||||
# TODO: 解决缩进问题
|
# TODO: 解决缩进问题
|
||||||
|
|
||||||
find_function_end_prompt = '''
|
find_function_end_prompt = '''
|
||||||
Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to sperate functions, class functions etc.
|
Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to separate functions, class functions etc.
|
||||||
- Provide the line number where the first visible function ends.
|
- Provide the line number where the first visible function ends.
|
||||||
- Provide the line number where the next visible function begins.
|
- Provide the line number where the next visible function begins.
|
||||||
- If there are no other functions in this page, you should simply return the line number of the last line.
|
- If there are no other functions in this page, you should simply return the line number of the last line.
|
||||||
@@ -59,7 +59,7 @@ OUTPUT:
|
|||||||
|
|
||||||
|
|
||||||
|
|
||||||
revise_funtion_prompt = '''
|
revise_function_prompt = '''
|
||||||
You need to read the following code, and revise the source code ({FILE_BASENAME}) according to following instructions:
|
You need to read the following code, and revise the source code ({FILE_BASENAME}) according to following instructions:
|
||||||
1. You should analyze the purpose of the functions (if there are any).
|
1. You should analyze the purpose of the functions (if there are any).
|
||||||
2. You need to add docstring for the provided functions (if there are any).
|
2. You need to add docstring for the provided functions (if there are any).
|
||||||
@@ -117,7 +117,7 @@ def zip_result(folder):
|
|||||||
'''
|
'''
|
||||||
|
|
||||||
|
|
||||||
revise_funtion_prompt_chinese = '''
|
revise_function_prompt_chinese = '''
|
||||||
您需要阅读以下代码,并根据以下说明修订源代码({FILE_BASENAME}):
|
您需要阅读以下代码,并根据以下说明修订源代码({FILE_BASENAME}):
|
||||||
1. 如果源代码中包含函数的话, 你应该分析给定函数实现了什么功能
|
1. 如果源代码中包含函数的话, 你应该分析给定函数实现了什么功能
|
||||||
2. 如果源代码中包含函数的话, 你需要为函数添加docstring, docstring必须使用中文
|
2. 如果源代码中包含函数的话, 你需要为函数添加docstring, docstring必须使用中文
|
||||||
@@ -188,9 +188,9 @@ class PythonCodeComment():
|
|||||||
self.language = language
|
self.language = language
|
||||||
self.observe_window_update = observe_window_update
|
self.observe_window_update = observe_window_update
|
||||||
if self.language == "chinese":
|
if self.language == "chinese":
|
||||||
self.core_prompt = revise_funtion_prompt_chinese
|
self.core_prompt = revise_function_prompt_chinese
|
||||||
else:
|
else:
|
||||||
self.core_prompt = revise_funtion_prompt
|
self.core_prompt = revise_function_prompt
|
||||||
self.path = None
|
self.path = None
|
||||||
self.file_basename = None
|
self.file_basename = None
|
||||||
self.file_brief = ""
|
self.file_brief = ""
|
||||||
@@ -222,7 +222,7 @@ class PythonCodeComment():
|
|||||||
history=[],
|
history=[],
|
||||||
sys_prompt="",
|
sys_prompt="",
|
||||||
observe_window=[],
|
observe_window=[],
|
||||||
console_slience=True
|
console_silence=True
|
||||||
)
|
)
|
||||||
|
|
||||||
def extract_number(text):
|
def extract_number(text):
|
||||||
@@ -316,7 +316,7 @@ class PythonCodeComment():
|
|||||||
def tag_code(self, fn, hint):
|
def tag_code(self, fn, hint):
|
||||||
code = fn
|
code = fn
|
||||||
_, n_indent = self.dedent(code)
|
_, n_indent = self.dedent(code)
|
||||||
indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preseve them in the OUTPUT.)"
|
indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preserve them in the OUTPUT.)"
|
||||||
brief_reminder = "" if self.file_brief == "" else f"({self.file_basename} abstract: {self.file_brief})"
|
brief_reminder = "" if self.file_brief == "" else f"({self.file_basename} abstract: {self.file_brief})"
|
||||||
hint_reminder = "" if hint is None else f"(Reminder: do not ignore or modify code such as `{hint}`, provide complete code in the OUTPUT.)"
|
hint_reminder = "" if hint is None else f"(Reminder: do not ignore or modify code such as `{hint}`, provide complete code in the OUTPUT.)"
|
||||||
self.llm_kwargs['temperature'] = 0
|
self.llm_kwargs['temperature'] = 0
|
||||||
@@ -333,7 +333,7 @@ class PythonCodeComment():
|
|||||||
history=[],
|
history=[],
|
||||||
sys_prompt="",
|
sys_prompt="",
|
||||||
observe_window=[],
|
observe_window=[],
|
||||||
console_slience=True
|
console_silence=True
|
||||||
)
|
)
|
||||||
|
|
||||||
def get_code_block(reply):
|
def get_code_block(reply):
|
||||||
@@ -400,7 +400,7 @@ class PythonCodeComment():
|
|||||||
return revised
|
return revised
|
||||||
|
|
||||||
def begin_comment_source_code(self, chatbot=None, history=None):
|
def begin_comment_source_code(self, chatbot=None, history=None):
|
||||||
# from toolbox import update_ui_lastest_msg
|
# from toolbox import update_ui_latest_msg
|
||||||
assert self.path is not None
|
assert self.path is not None
|
||||||
assert '.py' in self.path # must be python source code
|
assert '.py' in self.path # must be python source code
|
||||||
# write_target = self.path + '.revised.py'
|
# write_target = self.path + '.revised.py'
|
||||||
@@ -409,10 +409,10 @@ class PythonCodeComment():
|
|||||||
# with open(self.path + '.revised.py', 'w+', encoding='utf8') as f:
|
# with open(self.path + '.revised.py', 'w+', encoding='utf8') as f:
|
||||||
while True:
|
while True:
|
||||||
try:
|
try:
|
||||||
# yield from update_ui_lastest_msg(f"({self.file_basename}) 正在读取下一段代码片段:\n", chatbot=chatbot, history=history, delay=0)
|
# yield from update_ui_latest_msg(f"({self.file_basename}) 正在读取下一段代码片段:\n", chatbot=chatbot, history=history, delay=0)
|
||||||
next_batch, line_no_start, line_no_end = self.get_next_batch()
|
next_batch, line_no_start, line_no_end = self.get_next_batch()
|
||||||
self.observe_window_update(f"正在处理{self.file_basename} - {line_no_start}/{len(self.full_context)}\n")
|
self.observe_window_update(f"正在处理{self.file_basename} - {line_no_start}/{len(self.full_context)}\n")
|
||||||
# yield from update_ui_lastest_msg(f"({self.file_basename}) 处理代码片段:\n\n{next_batch}", chatbot=chatbot, history=history, delay=0)
|
# yield from update_ui_latest_msg(f"({self.file_basename}) 处理代码片段:\n\n{next_batch}", chatbot=chatbot, history=history, delay=0)
|
||||||
|
|
||||||
hint = None
|
hint = None
|
||||||
MAX_ATTEMPT = 2
|
MAX_ATTEMPT = 2
|
||||||
|
|||||||
@@ -1,7 +1,7 @@
|
|||||||
import os
|
import os
|
||||||
import threading
|
import threading
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
from shared_utils.char_visual_effect import scolling_visual_effect
|
from shared_utils.char_visual_effect import scrolling_visual_effect
|
||||||
from toolbox import update_ui, get_conf, trimmed_format_exc, get_max_token, Singleton
|
from toolbox import update_ui, get_conf, trimmed_format_exc, get_max_token, Singleton
|
||||||
|
|
||||||
def input_clipping(inputs, history, max_token_limit, return_clip_flags=False):
|
def input_clipping(inputs, history, max_token_limit, return_clip_flags=False):
|
||||||
@@ -256,7 +256,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
|
|||||||
# 【第一种情况】:顺利完成
|
# 【第一种情况】:顺利完成
|
||||||
gpt_say = predict_no_ui_long_connection(
|
gpt_say = predict_no_ui_long_connection(
|
||||||
inputs=inputs, llm_kwargs=llm_kwargs, history=history,
|
inputs=inputs, llm_kwargs=llm_kwargs, history=history,
|
||||||
sys_prompt=sys_prompt, observe_window=mutable[index], console_slience=True
|
sys_prompt=sys_prompt, observe_window=mutable[index], console_silence=True
|
||||||
)
|
)
|
||||||
mutable[index][2] = "已成功"
|
mutable[index][2] = "已成功"
|
||||||
return gpt_say
|
return gpt_say
|
||||||
@@ -326,7 +326,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
|
|||||||
mutable[thread_index][1] = time.time()
|
mutable[thread_index][1] = time.time()
|
||||||
# 在前端打印些好玩的东西
|
# 在前端打印些好玩的东西
|
||||||
for thread_index, _ in enumerate(worker_done):
|
for thread_index, _ in enumerate(worker_done):
|
||||||
print_something_really_funny = f"[ ...`{scolling_visual_effect(mutable[thread_index][0], scroller_max_len)}`... ]"
|
print_something_really_funny = f"[ ...`{scrolling_visual_effect(mutable[thread_index][0], scroller_max_len)}`... ]"
|
||||||
observe_win.append(print_something_really_funny)
|
observe_win.append(print_something_really_funny)
|
||||||
# 在前端打印些好玩的东西
|
# 在前端打印些好玩的东西
|
||||||
stat_str = ''.join([f'`{mutable[thread_index][2]}`: {obs}\n\n'
|
stat_str = ''.join([f'`{mutable[thread_index][2]}`: {obs}\n\n'
|
||||||
@@ -389,11 +389,11 @@ def read_and_clean_pdf_text(fp):
|
|||||||
"""
|
"""
|
||||||
提取文本块主字体
|
提取文本块主字体
|
||||||
"""
|
"""
|
||||||
fsize_statiscs = {}
|
fsize_statistics = {}
|
||||||
for wtf in l['spans']:
|
for wtf in l['spans']:
|
||||||
if wtf['size'] not in fsize_statiscs: fsize_statiscs[wtf['size']] = 0
|
if wtf['size'] not in fsize_statistics: fsize_statistics[wtf['size']] = 0
|
||||||
fsize_statiscs[wtf['size']] += len(wtf['text'])
|
fsize_statistics[wtf['size']] += len(wtf['text'])
|
||||||
return max(fsize_statiscs, key=fsize_statiscs.get)
|
return max(fsize_statistics, key=fsize_statistics.get)
|
||||||
|
|
||||||
def ffsize_same(a,b):
|
def ffsize_same(a,b):
|
||||||
"""
|
"""
|
||||||
@@ -433,11 +433,11 @@ def read_and_clean_pdf_text(fp):
|
|||||||
|
|
||||||
############################## <第 2 步,获取正文主字体> ##################################
|
############################## <第 2 步,获取正文主字体> ##################################
|
||||||
try:
|
try:
|
||||||
fsize_statiscs = {}
|
fsize_statistics = {}
|
||||||
for span in meta_span:
|
for span in meta_span:
|
||||||
if span[1] not in fsize_statiscs: fsize_statiscs[span[1]] = 0
|
if span[1] not in fsize_statistics: fsize_statistics[span[1]] = 0
|
||||||
fsize_statiscs[span[1]] += span[2]
|
fsize_statistics[span[1]] += span[2]
|
||||||
main_fsize = max(fsize_statiscs, key=fsize_statiscs.get)
|
main_fsize = max(fsize_statistics, key=fsize_statistics.get)
|
||||||
if REMOVE_FOOT_NOTE:
|
if REMOVE_FOOT_NOTE:
|
||||||
give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT
|
give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT
|
||||||
except:
|
except:
|
||||||
@@ -610,9 +610,9 @@ class nougat_interface():
|
|||||||
|
|
||||||
|
|
||||||
def NOUGAT_parse_pdf(self, fp, chatbot, history):
|
def NOUGAT_parse_pdf(self, fp, chatbot, history):
|
||||||
from toolbox import update_ui_lastest_msg
|
from toolbox import update_ui_latest_msg
|
||||||
|
|
||||||
yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度:正在排队, 等待线程锁...",
|
yield from update_ui_latest_msg("正在解析论文, 请稍候。进度:正在排队, 等待线程锁...",
|
||||||
chatbot=chatbot, history=history, delay=0)
|
chatbot=chatbot, history=history, delay=0)
|
||||||
self.threadLock.acquire()
|
self.threadLock.acquire()
|
||||||
import glob, threading, os
|
import glob, threading, os
|
||||||
@@ -620,7 +620,7 @@ class nougat_interface():
|
|||||||
dst = os.path.join(get_log_folder(plugin_name='nougat'), gen_time_str())
|
dst = os.path.join(get_log_folder(plugin_name='nougat'), gen_time_str())
|
||||||
os.makedirs(dst)
|
os.makedirs(dst)
|
||||||
|
|
||||||
yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度:正在加载NOUGAT... (提示:首次运行需要花费较长时间下载NOUGAT参数)",
|
yield from update_ui_latest_msg("正在解析论文, 请稍候。进度:正在加载NOUGAT... (提示:首次运行需要花费较长时间下载NOUGAT参数)",
|
||||||
chatbot=chatbot, history=history, delay=0)
|
chatbot=chatbot, history=history, delay=0)
|
||||||
command = ['nougat', '--out', os.path.abspath(dst), os.path.abspath(fp)]
|
command = ['nougat', '--out', os.path.abspath(dst), os.path.abspath(fp)]
|
||||||
self.nougat_with_timeout(command, cwd=os.getcwd(), timeout=3600)
|
self.nougat_with_timeout(command, cwd=os.getcwd(), timeout=3600)
|
||||||
|
|||||||
@@ -1,4 +1,4 @@
|
|||||||
from toolbox import CatchException, update_ui, update_ui_lastest_msg
|
from toolbox import CatchException, update_ui, update_ui_latest_msg
|
||||||
from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
|
from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||||
from request_llms.bridge_all import predict_no_ui_long_connection
|
from request_llms.bridge_all import predict_no_ui_long_connection
|
||||||
@@ -13,7 +13,7 @@ class MiniGame_ASCII_Art(GptAcademicGameBaseState):
|
|||||||
else:
|
else:
|
||||||
if prompt.strip() == 'exit':
|
if prompt.strip() == 'exit':
|
||||||
self.delete_game = True
|
self.delete_game = True
|
||||||
yield from update_ui_lastest_msg(lastmsg=f"谜底是{self.obj},游戏结束。", chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg=f"谜底是{self.obj},游戏结束。", chatbot=chatbot, history=history, delay=0.)
|
||||||
return
|
return
|
||||||
chatbot.append([prompt, ""])
|
chatbot.append([prompt, ""])
|
||||||
yield from update_ui(chatbot=chatbot, history=history)
|
yield from update_ui(chatbot=chatbot, history=history)
|
||||||
@@ -31,12 +31,12 @@ class MiniGame_ASCII_Art(GptAcademicGameBaseState):
|
|||||||
self.cur_task = 'identify user guess'
|
self.cur_task = 'identify user guess'
|
||||||
res = get_code_block(raw_res)
|
res = get_code_block(raw_res)
|
||||||
history += ['', f'the answer is {self.obj}', inputs, res]
|
history += ['', f'the answer is {self.obj}', inputs, res]
|
||||||
yield from update_ui_lastest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)
|
||||||
|
|
||||||
elif self.cur_task == 'identify user guess':
|
elif self.cur_task == 'identify user guess':
|
||||||
if is_same_thing(self.obj, prompt, self.llm_kwargs):
|
if is_same_thing(self.obj, prompt, self.llm_kwargs):
|
||||||
self.delete_game = True
|
self.delete_game = True
|
||||||
yield from update_ui_lastest_msg(lastmsg="你猜对了!", chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg="你猜对了!", chatbot=chatbot, history=history, delay=0.)
|
||||||
else:
|
else:
|
||||||
self.cur_task = 'identify user guess'
|
self.cur_task = 'identify user guess'
|
||||||
yield from update_ui_lastest_msg(lastmsg="猜错了,再试试,输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg="猜错了,再试试,输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)
|
||||||
@@ -63,7 +63,7 @@ prompts_terminate = """小说的前文回顾:
|
|||||||
"""
|
"""
|
||||||
|
|
||||||
|
|
||||||
from toolbox import CatchException, update_ui, update_ui_lastest_msg
|
from toolbox import CatchException, update_ui, update_ui_latest_msg
|
||||||
from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
|
from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||||
from request_llms.bridge_all import predict_no_ui_long_connection
|
from request_llms.bridge_all import predict_no_ui_long_connection
|
||||||
@@ -112,7 +112,7 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
|
|||||||
if prompt.strip() == 'exit' or prompt.strip() == '结束剧情':
|
if prompt.strip() == 'exit' or prompt.strip() == '结束剧情':
|
||||||
# should we terminate game here?
|
# should we terminate game here?
|
||||||
self.delete_game = True
|
self.delete_game = True
|
||||||
yield from update_ui_lastest_msg(lastmsg=f"游戏结束。", chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg=f"游戏结束。", chatbot=chatbot, history=history, delay=0.)
|
||||||
return
|
return
|
||||||
if '剧情收尾' in prompt:
|
if '剧情收尾' in prompt:
|
||||||
self.cur_task = 'story_terminate'
|
self.cur_task = 'story_terminate'
|
||||||
@@ -137,8 +137,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
|
|||||||
)
|
)
|
||||||
self.story.append(story_paragraph)
|
self.story.append(story_paragraph)
|
||||||
# # 配图
|
# # 配图
|
||||||
yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
|
||||||
yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
|
||||||
|
|
||||||
# # 构建后续剧情引导
|
# # 构建后续剧情引导
|
||||||
previously_on_story = ""
|
previously_on_story = ""
|
||||||
@@ -171,8 +171,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
|
|||||||
)
|
)
|
||||||
self.story.append(story_paragraph)
|
self.story.append(story_paragraph)
|
||||||
# # 配图
|
# # 配图
|
||||||
yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
|
||||||
yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
|
||||||
|
|
||||||
# # 构建后续剧情引导
|
# # 构建后续剧情引导
|
||||||
previously_on_story = ""
|
previously_on_story = ""
|
||||||
@@ -204,8 +204,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
|
|||||||
chatbot, history_, self.sys_prompt_
|
chatbot, history_, self.sys_prompt_
|
||||||
)
|
)
|
||||||
# # 配图
|
# # 配图
|
||||||
yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
|
||||||
yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
|
yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
|
||||||
|
|
||||||
# terminate game
|
# terminate game
|
||||||
self.delete_game = True
|
self.delete_game = True
|
||||||
|
|||||||
@@ -2,7 +2,7 @@ import time
|
|||||||
import importlib
|
import importlib
|
||||||
from toolbox import trimmed_format_exc, gen_time_str, get_log_folder
|
from toolbox import trimmed_format_exc, gen_time_str, get_log_folder
|
||||||
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
|
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
|
||||||
from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_lastest_msg
|
from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_latest_msg
|
||||||
import multiprocessing
|
import multiprocessing
|
||||||
|
|
||||||
def get_class_name(class_string):
|
def get_class_name(class_string):
|
||||||
|
|||||||
@@ -102,10 +102,10 @@ class GptJsonIO():
|
|||||||
logging.info(f'Repairing json:{response}')
|
logging.info(f'Repairing json:{response}')
|
||||||
repair_prompt = self.generate_repair_prompt(broken_json = response, error=repr(e))
|
repair_prompt = self.generate_repair_prompt(broken_json = response, error=repr(e))
|
||||||
result = self.generate_output(gpt_gen_fn(repair_prompt, self.format_instructions))
|
result = self.generate_output(gpt_gen_fn(repair_prompt, self.format_instructions))
|
||||||
logging.info('Repaire json success.')
|
logging.info('Repair json success.')
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
# 没辙了,放弃治疗
|
# 没辙了,放弃治疗
|
||||||
logging.info('Repaire json fail.')
|
logging.info('Repair json fail.')
|
||||||
raise JsonStringError('Cannot repair json.', str(e))
|
raise JsonStringError('Cannot repair json.', str(e))
|
||||||
return result
|
return result
|
||||||
|
|
||||||
|
|||||||
@@ -3,7 +3,7 @@ import re
|
|||||||
import shutil
|
import shutil
|
||||||
import numpy as np
|
import numpy as np
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
from toolbox import update_ui, update_ui_lastest_msg, get_log_folder, gen_time_str
|
from toolbox import update_ui, update_ui_latest_msg, get_log_folder, gen_time_str
|
||||||
from toolbox import get_conf, promote_file_to_downloadzone
|
from toolbox import get_conf, promote_file_to_downloadzone
|
||||||
from crazy_functions.latex_fns.latex_toolbox import PRESERVE, TRANSFORM
|
from crazy_functions.latex_fns.latex_toolbox import PRESERVE, TRANSFORM
|
||||||
from crazy_functions.latex_fns.latex_toolbox import set_forbidden_text, set_forbidden_text_begin_end, set_forbidden_text_careful_brace
|
from crazy_functions.latex_fns.latex_toolbox import set_forbidden_text, set_forbidden_text_begin_end, set_forbidden_text_careful_brace
|
||||||
@@ -20,7 +20,7 @@ def split_subprocess(txt, project_folder, return_dict, opts):
|
|||||||
"""
|
"""
|
||||||
break down latex file to a linked list,
|
break down latex file to a linked list,
|
||||||
each node use a preserve flag to indicate whether it should
|
each node use a preserve flag to indicate whether it should
|
||||||
be proccessed by GPT.
|
be processed by GPT.
|
||||||
"""
|
"""
|
||||||
text = txt
|
text = txt
|
||||||
mask = np.zeros(len(txt), dtype=np.uint8) + TRANSFORM
|
mask = np.zeros(len(txt), dtype=np.uint8) + TRANSFORM
|
||||||
@@ -85,14 +85,14 @@ class LatexPaperSplit():
|
|||||||
"""
|
"""
|
||||||
break down latex file to a linked list,
|
break down latex file to a linked list,
|
||||||
each node use a preserve flag to indicate whether it should
|
each node use a preserve flag to indicate whether it should
|
||||||
be proccessed by GPT.
|
be processed by GPT.
|
||||||
"""
|
"""
|
||||||
def __init__(self) -> None:
|
def __init__(self) -> None:
|
||||||
self.nodes = None
|
self.nodes = None
|
||||||
self.msg = "*{\\scriptsize\\textbf{警告:该PDF由GPT-Academic开源项目调用大语言模型+Latex翻译插件一键生成," + \
|
self.msg = "*{\\scriptsize\\textbf{警告:该PDF由GPT-Academic开源项目调用大语言模型+Latex翻译插件一键生成," + \
|
||||||
"版权归原文作者所有。翻译内容可靠性无保障,请仔细鉴别并以原文为准。" + \
|
"版权归原文作者所有。翻译内容可靠性无保障,请仔细鉴别并以原文为准。" + \
|
||||||
"项目Github地址 \\url{https://github.com/binary-husky/gpt_academic/}。"
|
"项目Github地址 \\url{https://github.com/binary-husky/gpt_academic/}。"
|
||||||
# 请您不要删除或修改这行警告,除非您是论文的原作者(如果您是论文原作者,欢迎加REAME中的QQ联系开发者)
|
# 请您不要删除或修改这行警告,除非您是论文的原作者(如果您是论文原作者,欢迎加README中的QQ联系开发者)
|
||||||
self.msg_declare = "为了防止大语言模型的意外谬误产生扩散影响,禁止移除或修改此警告。}}\\\\"
|
self.msg_declare = "为了防止大语言模型的意外谬误产生扩散影响,禁止移除或修改此警告。}}\\\\"
|
||||||
self.title = "unknown"
|
self.title = "unknown"
|
||||||
self.abstract = "unknown"
|
self.abstract = "unknown"
|
||||||
@@ -151,7 +151,7 @@ class LatexPaperSplit():
|
|||||||
"""
|
"""
|
||||||
break down latex file to a linked list,
|
break down latex file to a linked list,
|
||||||
each node use a preserve flag to indicate whether it should
|
each node use a preserve flag to indicate whether it should
|
||||||
be proccessed by GPT.
|
be processed by GPT.
|
||||||
P.S. use multiprocessing to avoid timeout error
|
P.S. use multiprocessing to avoid timeout error
|
||||||
"""
|
"""
|
||||||
import multiprocessing
|
import multiprocessing
|
||||||
@@ -351,7 +351,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
|
|||||||
max_try = 32
|
max_try = 32
|
||||||
chatbot.append([f"正在编译PDF文档", f'编译已经开始。当前工作路径为{work_folder},如果程序停顿5分钟以上,请直接去该路径下取回翻译结果,或者重启之后再度尝试 ...']); yield from update_ui(chatbot=chatbot, history=history)
|
chatbot.append([f"正在编译PDF文档", f'编译已经开始。当前工作路径为{work_folder},如果程序停顿5分钟以上,请直接去该路径下取回翻译结果,或者重启之后再度尝试 ...']); yield from update_ui(chatbot=chatbot, history=history)
|
||||||
chatbot.append([f"正在编译PDF文档", '...']); yield from update_ui(chatbot=chatbot, history=history); time.sleep(1); chatbot[-1] = list(chatbot[-1]) # 刷新界面
|
chatbot.append([f"正在编译PDF文档", '...']); yield from update_ui(chatbot=chatbot, history=history); time.sleep(1); chatbot[-1] = list(chatbot[-1]) # 刷新界面
|
||||||
yield from update_ui_lastest_msg('编译已经开始...', chatbot, history) # 刷新Gradio前端界面
|
yield from update_ui_latest_msg('编译已经开始...', chatbot, history) # 刷新Gradio前端界面
|
||||||
# 检查是否需要使用xelatex
|
# 检查是否需要使用xelatex
|
||||||
def check_if_need_xelatex(tex_path):
|
def check_if_need_xelatex(tex_path):
|
||||||
try:
|
try:
|
||||||
@@ -396,32 +396,32 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
|
|||||||
shutil.copyfile(may_exist_bbl, target_bbl)
|
shutil.copyfile(may_exist_bbl, target_bbl)
|
||||||
|
|
||||||
# https://stackoverflow.com/questions/738755/dont-make-me-manually-abort-a-latex-compile-when-theres-an-error
|
# https://stackoverflow.com/questions/738755/dont-make-me-manually-abort-a-latex-compile-when-theres-an-error
|
||||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history) # 刷新Gradio前端界面
|
yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
|
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
|
||||||
|
|
||||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history) # 刷新Gradio前端界面
|
yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
|
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
|
||||||
|
|
||||||
if ok and os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf')):
|
if ok and os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf')):
|
||||||
# 只有第二步成功,才能继续下面的步骤
|
# 只有第二步成功,才能继续下面的步骤
|
||||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history) # 刷新Gradio前端界面
|
yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
if not os.path.exists(pj(work_folder_original, f'{main_file_original}.bbl')):
|
if not os.path.exists(pj(work_folder_original, f'{main_file_original}.bbl')):
|
||||||
ok = compile_latex_with_timeout(f'bibtex {main_file_original}.aux', work_folder_original)
|
ok = compile_latex_with_timeout(f'bibtex {main_file_original}.aux', work_folder_original)
|
||||||
if not os.path.exists(pj(work_folder_modified, f'{main_file_modified}.bbl')):
|
if not os.path.exists(pj(work_folder_modified, f'{main_file_modified}.bbl')):
|
||||||
ok = compile_latex_with_timeout(f'bibtex {main_file_modified}.aux', work_folder_modified)
|
ok = compile_latex_with_timeout(f'bibtex {main_file_modified}.aux', work_folder_modified)
|
||||||
|
|
||||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history) # 刷新Gradio前端界面
|
yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
|
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
|
||||||
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
|
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
|
||||||
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
|
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
|
||||||
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
|
ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
|
||||||
|
|
||||||
if mode!='translate_zh':
|
if mode!='translate_zh':
|
||||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
|
yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
logger.info( f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
|
logger.info( f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
|
||||||
ok = compile_latex_with_timeout(f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex', os.getcwd())
|
ok = compile_latex_with_timeout(f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex', os.getcwd())
|
||||||
|
|
||||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history) # 刷新Gradio前端界面
|
yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
|
ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
|
||||||
ok = compile_latex_with_timeout(f'bibtex merge_diff.aux', work_folder)
|
ok = compile_latex_with_timeout(f'bibtex merge_diff.aux', work_folder)
|
||||||
ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
|
ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
|
||||||
@@ -435,13 +435,13 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
|
|||||||
results_ += f"原始PDF编译是否成功: {original_pdf_success};"
|
results_ += f"原始PDF编译是否成功: {original_pdf_success};"
|
||||||
results_ += f"转化PDF编译是否成功: {modified_pdf_success};"
|
results_ += f"转化PDF编译是否成功: {modified_pdf_success};"
|
||||||
results_ += f"对比PDF编译是否成功: {diff_pdf_success};"
|
results_ += f"对比PDF编译是否成功: {diff_pdf_success};"
|
||||||
yield from update_ui_lastest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面
|
yield from update_ui_latest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
|
||||||
if diff_pdf_success:
|
if diff_pdf_success:
|
||||||
result_pdf = pj(work_folder_modified, f'merge_diff.pdf') # get pdf path
|
result_pdf = pj(work_folder_modified, f'merge_diff.pdf') # get pdf path
|
||||||
promote_file_to_downloadzone(result_pdf, rename_file=None, chatbot=chatbot) # promote file to web UI
|
promote_file_to_downloadzone(result_pdf, rename_file=None, chatbot=chatbot) # promote file to web UI
|
||||||
if modified_pdf_success:
|
if modified_pdf_success:
|
||||||
yield from update_ui_lastest_msg(f'转化PDF编译已经成功, 正在尝试生成对比PDF, 请稍候 ...', chatbot, history) # 刷新Gradio前端界面
|
yield from update_ui_latest_msg(f'转化PDF编译已经成功, 正在尝试生成对比PDF, 请稍候 ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
result_pdf = pj(work_folder_modified, f'{main_file_modified}.pdf') # get pdf path
|
result_pdf = pj(work_folder_modified, f'{main_file_modified}.pdf') # get pdf path
|
||||||
origin_pdf = pj(work_folder_original, f'{main_file_original}.pdf') # get pdf path
|
origin_pdf = pj(work_folder_original, f'{main_file_original}.pdf') # get pdf path
|
||||||
if os.path.exists(pj(work_folder, '..', 'translation')):
|
if os.path.exists(pj(work_folder, '..', 'translation')):
|
||||||
@@ -472,7 +472,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
|
|||||||
work_folder_modified=work_folder_modified,
|
work_folder_modified=work_folder_modified,
|
||||||
fixed_line=fixed_line
|
fixed_line=fixed_line
|
||||||
)
|
)
|
||||||
yield from update_ui_lastest_msg(f'由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第{buggy_lines}行 ...', chatbot, history) # 刷新Gradio前端界面
|
yield from update_ui_latest_msg(f'由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第{buggy_lines}行 ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
if not can_retry: break
|
if not can_retry: break
|
||||||
|
|
||||||
return False # 失败啦
|
return False # 失败啦
|
||||||
|
|||||||
@@ -168,7 +168,7 @@ def set_forbidden_text(text, mask, pattern, flags=0):
|
|||||||
def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
|
def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
|
||||||
"""
|
"""
|
||||||
Move area out of preserve area (make text editable for GPT)
|
Move area out of preserve area (make text editable for GPT)
|
||||||
count the number of the braces so as to catch compelete text area.
|
count the number of the braces so as to catch complete text area.
|
||||||
e.g.
|
e.g.
|
||||||
\begin{abstract} blablablablablabla. \end{abstract}
|
\begin{abstract} blablablablablabla. \end{abstract}
|
||||||
"""
|
"""
|
||||||
@@ -188,7 +188,7 @@ def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
|
|||||||
def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
|
def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
|
||||||
"""
|
"""
|
||||||
Add a preserve text area in this paper (text become untouchable for GPT).
|
Add a preserve text area in this paper (text become untouchable for GPT).
|
||||||
count the number of the braces so as to catch compelete text area.
|
count the number of the braces so as to catch complete text area.
|
||||||
e.g.
|
e.g.
|
||||||
\caption{blablablablabla\texbf{blablabla}blablabla.}
|
\caption{blablablablabla\texbf{blablabla}blablabla.}
|
||||||
"""
|
"""
|
||||||
@@ -214,7 +214,7 @@ def reverse_forbidden_text_careful_brace(
|
|||||||
):
|
):
|
||||||
"""
|
"""
|
||||||
Move area out of preserve area (make text editable for GPT)
|
Move area out of preserve area (make text editable for GPT)
|
||||||
count the number of the braces so as to catch compelete text area.
|
count the number of the braces so as to catch complete text area.
|
||||||
e.g.
|
e.g.
|
||||||
\caption{blablablablabla\texbf{blablabla}blablabla.}
|
\caption{blablablablabla\texbf{blablabla}blablabla.}
|
||||||
"""
|
"""
|
||||||
@@ -287,23 +287,23 @@ def find_main_tex_file(file_manifest, mode):
|
|||||||
在多Tex文档中,寻找主文件,必须包含documentclass,返回找到的第一个。
|
在多Tex文档中,寻找主文件,必须包含documentclass,返回找到的第一个。
|
||||||
P.S. 但愿没人把latex模板放在里面传进来 (6.25 加入判定latex模板的代码)
|
P.S. 但愿没人把latex模板放在里面传进来 (6.25 加入判定latex模板的代码)
|
||||||
"""
|
"""
|
||||||
canidates = []
|
candidates = []
|
||||||
for texf in file_manifest:
|
for texf in file_manifest:
|
||||||
if os.path.basename(texf).startswith("merge"):
|
if os.path.basename(texf).startswith("merge"):
|
||||||
continue
|
continue
|
||||||
with open(texf, "r", encoding="utf8", errors="ignore") as f:
|
with open(texf, "r", encoding="utf8", errors="ignore") as f:
|
||||||
file_content = f.read()
|
file_content = f.read()
|
||||||
if r"\documentclass" in file_content:
|
if r"\documentclass" in file_content:
|
||||||
canidates.append(texf)
|
candidates.append(texf)
|
||||||
else:
|
else:
|
||||||
continue
|
continue
|
||||||
|
|
||||||
if len(canidates) == 0:
|
if len(candidates) == 0:
|
||||||
raise RuntimeError("无法找到一个主Tex文件(包含documentclass关键字)")
|
raise RuntimeError("无法找到一个主Tex文件(包含documentclass关键字)")
|
||||||
elif len(canidates) == 1:
|
elif len(candidates) == 1:
|
||||||
return canidates[0]
|
return candidates[0]
|
||||||
else: # if len(canidates) >= 2 通过一些Latex模板中常见(但通常不会出现在正文)的单词,对不同latex源文件扣分,取评分最高者返回
|
else: # if len(candidates) >= 2 通过一些Latex模板中常见(但通常不会出现在正文)的单词,对不同latex源文件扣分,取评分最高者返回
|
||||||
canidates_score = []
|
candidates_score = []
|
||||||
# 给出一些判定模板文档的词作为扣分项
|
# 给出一些判定模板文档的词作为扣分项
|
||||||
unexpected_words = [
|
unexpected_words = [
|
||||||
"\\LaTeX",
|
"\\LaTeX",
|
||||||
@@ -316,19 +316,19 @@ def find_main_tex_file(file_manifest, mode):
|
|||||||
"reviewers",
|
"reviewers",
|
||||||
]
|
]
|
||||||
expected_words = ["\\input", "\\ref", "\\cite"]
|
expected_words = ["\\input", "\\ref", "\\cite"]
|
||||||
for texf in canidates:
|
for texf in candidates:
|
||||||
canidates_score.append(0)
|
candidates_score.append(0)
|
||||||
with open(texf, "r", encoding="utf8", errors="ignore") as f:
|
with open(texf, "r", encoding="utf8", errors="ignore") as f:
|
||||||
file_content = f.read()
|
file_content = f.read()
|
||||||
file_content = rm_comments(file_content)
|
file_content = rm_comments(file_content)
|
||||||
for uw in unexpected_words:
|
for uw in unexpected_words:
|
||||||
if uw in file_content:
|
if uw in file_content:
|
||||||
canidates_score[-1] -= 1
|
candidates_score[-1] -= 1
|
||||||
for uw in expected_words:
|
for uw in expected_words:
|
||||||
if uw in file_content:
|
if uw in file_content:
|
||||||
canidates_score[-1] += 1
|
candidates_score[-1] += 1
|
||||||
select = np.argmax(canidates_score) # 取评分最高者返回
|
select = np.argmax(candidates_score) # 取评分最高者返回
|
||||||
return canidates[select]
|
return candidates[select]
|
||||||
|
|
||||||
|
|
||||||
def rm_comments(main_file):
|
def rm_comments(main_file):
|
||||||
@@ -374,7 +374,7 @@ def find_tex_file_ignore_case(fp):
|
|||||||
|
|
||||||
def merge_tex_files_(project_foler, main_file, mode):
|
def merge_tex_files_(project_foler, main_file, mode):
|
||||||
"""
|
"""
|
||||||
Merge Tex project recrusively
|
Merge Tex project recursively
|
||||||
"""
|
"""
|
||||||
main_file = rm_comments(main_file)
|
main_file = rm_comments(main_file)
|
||||||
for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
|
for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
|
||||||
@@ -429,7 +429,7 @@ def find_title_and_abs(main_file):
|
|||||||
|
|
||||||
def merge_tex_files(project_foler, main_file, mode):
|
def merge_tex_files(project_foler, main_file, mode):
|
||||||
"""
|
"""
|
||||||
Merge Tex project recrusively
|
Merge Tex project recursively
|
||||||
P.S. 顺便把CTEX塞进去以支持中文
|
P.S. 顺便把CTEX塞进去以支持中文
|
||||||
P.S. 顺便把Latex的注释去除
|
P.S. 顺便把Latex的注释去除
|
||||||
"""
|
"""
|
||||||
|
|||||||
@@ -1,4 +1,4 @@
|
|||||||
from toolbox import update_ui, get_conf, promote_file_to_downloadzone, update_ui_lastest_msg, generate_file_link
|
from toolbox import update_ui, get_conf, promote_file_to_downloadzone, update_ui_latest_msg, generate_file_link
|
||||||
from shared_utils.docker_as_service_api import stream_daas
|
from shared_utils.docker_as_service_api import stream_daas
|
||||||
from shared_utils.docker_as_service_api import DockerServiceApiComModel
|
from shared_utils.docker_as_service_api import DockerServiceApiComModel
|
||||||
import random
|
import random
|
||||||
@@ -25,7 +25,7 @@ def download_video(video_id, only_audio, user_name, chatbot, history):
|
|||||||
status_buf += "\n\n"
|
status_buf += "\n\n"
|
||||||
status_buf += "DaaS file attach: \n\n"
|
status_buf += "DaaS file attach: \n\n"
|
||||||
status_buf += str(output_manifest['server_file_attach'])
|
status_buf += str(output_manifest['server_file_attach'])
|
||||||
yield from update_ui_lastest_msg(status_buf, chatbot, history)
|
yield from update_ui_latest_msg(status_buf, chatbot, history)
|
||||||
|
|
||||||
return output_manifest['server_file_attach']
|
return output_manifest['server_file_attach']
|
||||||
|
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
from pydantic import BaseModel, Field
|
from pydantic import BaseModel, Field
|
||||||
from typing import List
|
from typing import List
|
||||||
from toolbox import update_ui_lastest_msg, disable_auto_promotion
|
from toolbox import update_ui_latest_msg, disable_auto_promotion
|
||||||
from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder
|
from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder
|
||||||
from request_llms.bridge_all import predict_no_ui_long_connection
|
from request_llms.bridge_all import predict_no_ui_long_connection
|
||||||
from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
|
from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
|
||||||
|
|||||||
@@ -113,7 +113,7 @@ def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_fi
|
|||||||
return [txt]
|
return [txt]
|
||||||
else:
|
else:
|
||||||
# raw_token_num > TOKEN_LIMIT_PER_FRAGMENT
|
# raw_token_num > TOKEN_LIMIT_PER_FRAGMENT
|
||||||
# find a smooth token limit to achieve even seperation
|
# find a smooth token limit to achieve even separation
|
||||||
count = int(math.ceil(raw_token_num / TOKEN_LIMIT_PER_FRAGMENT))
|
count = int(math.ceil(raw_token_num / TOKEN_LIMIT_PER_FRAGMENT))
|
||||||
token_limit_smooth = raw_token_num // count + count
|
token_limit_smooth = raw_token_num // count + count
|
||||||
return breakdown_text_to_satisfy_token_limit(txt, limit=token_limit_smooth, llm_model=llm_kwargs['llm_model'])
|
return breakdown_text_to_satisfy_token_limit(txt, limit=token_limit_smooth, llm_model=llm_kwargs['llm_model'])
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
import os
|
import os
|
||||||
from toolbox import CatchException, report_exception, get_log_folder, gen_time_str, check_packages
|
from toolbox import CatchException, report_exception, get_log_folder, gen_time_str, check_packages
|
||||||
from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
|
from toolbox import update_ui, promote_file_to_downloadzone, update_ui_latest_msg, disable_auto_promotion
|
||||||
from toolbox import write_history_to_file, promote_file_to_downloadzone, get_conf, extract_archive
|
from toolbox import write_history_to_file, promote_file_to_downloadzone, get_conf, extract_archive
|
||||||
from crazy_functions.pdf_fns.parse_pdf import parse_pdf, translate_pdf
|
from crazy_functions.pdf_fns.parse_pdf import parse_pdf, translate_pdf
|
||||||
|
|
||||||
|
|||||||
@@ -14,17 +14,17 @@ def extract_text_from_files(txt, chatbot, history):
|
|||||||
final_result(list):文本内容
|
final_result(list):文本内容
|
||||||
page_one(list):第一页内容/摘要
|
page_one(list):第一页内容/摘要
|
||||||
file_manifest(list):文件路径
|
file_manifest(list):文件路径
|
||||||
excption(string):需要用户手动处理的信息,如没出错则保持为空
|
exception(string):需要用户手动处理的信息,如没出错则保持为空
|
||||||
"""
|
"""
|
||||||
|
|
||||||
final_result = []
|
final_result = []
|
||||||
page_one = []
|
page_one = []
|
||||||
file_manifest = []
|
file_manifest = []
|
||||||
excption = ""
|
exception = ""
|
||||||
|
|
||||||
if txt == "":
|
if txt == "":
|
||||||
final_result.append(txt)
|
final_result.append(txt)
|
||||||
return False, final_result, page_one, file_manifest, excption #如输入区内容不是文件则直接返回输入区内容
|
return False, final_result, page_one, file_manifest, exception #如输入区内容不是文件则直接返回输入区内容
|
||||||
|
|
||||||
#查找输入区内容中的文件
|
#查找输入区内容中的文件
|
||||||
file_pdf,pdf_manifest,folder_pdf = get_files_from_everything(txt, '.pdf')
|
file_pdf,pdf_manifest,folder_pdf = get_files_from_everything(txt, '.pdf')
|
||||||
@@ -33,20 +33,20 @@ def extract_text_from_files(txt, chatbot, history):
|
|||||||
file_doc,doc_manifest,folder_doc = get_files_from_everything(txt, '.doc')
|
file_doc,doc_manifest,folder_doc = get_files_from_everything(txt, '.doc')
|
||||||
|
|
||||||
if file_doc:
|
if file_doc:
|
||||||
excption = "word"
|
exception = "word"
|
||||||
return False, final_result, page_one, file_manifest, excption
|
return False, final_result, page_one, file_manifest, exception
|
||||||
|
|
||||||
file_num = len(pdf_manifest) + len(md_manifest) + len(word_manifest)
|
file_num = len(pdf_manifest) + len(md_manifest) + len(word_manifest)
|
||||||
if file_num == 0:
|
if file_num == 0:
|
||||||
final_result.append(txt)
|
final_result.append(txt)
|
||||||
return False, final_result, page_one, file_manifest, excption #如输入区内容不是文件则直接返回输入区内容
|
return False, final_result, page_one, file_manifest, exception #如输入区内容不是文件则直接返回输入区内容
|
||||||
|
|
||||||
if file_pdf:
|
if file_pdf:
|
||||||
try: # 尝试导入依赖,如果缺少依赖,则给出安装建议
|
try: # 尝试导入依赖,如果缺少依赖,则给出安装建议
|
||||||
import fitz
|
import fitz
|
||||||
except:
|
except:
|
||||||
excption = "pdf"
|
exception = "pdf"
|
||||||
return False, final_result, page_one, file_manifest, excption
|
return False, final_result, page_one, file_manifest, exception
|
||||||
for index, fp in enumerate(pdf_manifest):
|
for index, fp in enumerate(pdf_manifest):
|
||||||
file_content, pdf_one = read_and_clean_pdf_text(fp) # (尝试)按照章节切割PDF
|
file_content, pdf_one = read_and_clean_pdf_text(fp) # (尝试)按照章节切割PDF
|
||||||
file_content = file_content.encode('utf-8', 'ignore').decode() # avoid reading non-utf8 chars
|
file_content = file_content.encode('utf-8', 'ignore').decode() # avoid reading non-utf8 chars
|
||||||
@@ -72,8 +72,8 @@ def extract_text_from_files(txt, chatbot, history):
|
|||||||
try: # 尝试导入依赖,如果缺少依赖,则给出安装建议
|
try: # 尝试导入依赖,如果缺少依赖,则给出安装建议
|
||||||
from docx import Document
|
from docx import Document
|
||||||
except:
|
except:
|
||||||
excption = "word_pip"
|
exception = "word_pip"
|
||||||
return False, final_result, page_one, file_manifest, excption
|
return False, final_result, page_one, file_manifest, exception
|
||||||
for index, fp in enumerate(word_manifest):
|
for index, fp in enumerate(word_manifest):
|
||||||
doc = Document(fp)
|
doc = Document(fp)
|
||||||
file_content = '\n'.join([p.text for p in doc.paragraphs])
|
file_content = '\n'.join([p.text for p in doc.paragraphs])
|
||||||
@@ -82,4 +82,4 @@ def extract_text_from_files(txt, chatbot, history):
|
|||||||
final_result.append(file_content)
|
final_result.append(file_content)
|
||||||
file_manifest.append(os.path.relpath(fp, folder_word))
|
file_manifest.append(os.path.relpath(fp, folder_word))
|
||||||
|
|
||||||
return True, final_result, page_one, file_manifest, excption
|
return True, final_result, page_one, file_manifest, exception
|
||||||
@@ -60,7 +60,7 @@ def similarity_search_with_score_by_vector(
|
|||||||
self, embedding: List[float], k: int = 4
|
self, embedding: List[float], k: int = 4
|
||||||
) -> List[Tuple[Document, float]]:
|
) -> List[Tuple[Document, float]]:
|
||||||
|
|
||||||
def seperate_list(ls: List[int]) -> List[List[int]]:
|
def separate_list(ls: List[int]) -> List[List[int]]:
|
||||||
lists = []
|
lists = []
|
||||||
ls1 = [ls[0]]
|
ls1 = [ls[0]]
|
||||||
for i in range(1, len(ls)):
|
for i in range(1, len(ls)):
|
||||||
@@ -82,7 +82,7 @@ def similarity_search_with_score_by_vector(
|
|||||||
continue
|
continue
|
||||||
_id = self.index_to_docstore_id[i]
|
_id = self.index_to_docstore_id[i]
|
||||||
doc = self.docstore.search(_id)
|
doc = self.docstore.search(_id)
|
||||||
if not self.chunk_conent:
|
if not self.chunk_content:
|
||||||
if not isinstance(doc, Document):
|
if not isinstance(doc, Document):
|
||||||
raise ValueError(f"Could not find document for id {_id}, got {doc}")
|
raise ValueError(f"Could not find document for id {_id}, got {doc}")
|
||||||
doc.metadata["score"] = int(scores[0][j])
|
doc.metadata["score"] = int(scores[0][j])
|
||||||
@@ -104,12 +104,12 @@ def similarity_search_with_score_by_vector(
|
|||||||
id_set.add(l)
|
id_set.add(l)
|
||||||
if break_flag:
|
if break_flag:
|
||||||
break
|
break
|
||||||
if not self.chunk_conent:
|
if not self.chunk_content:
|
||||||
return docs
|
return docs
|
||||||
if len(id_set) == 0 and self.score_threshold > 0:
|
if len(id_set) == 0 and self.score_threshold > 0:
|
||||||
return []
|
return []
|
||||||
id_list = sorted(list(id_set))
|
id_list = sorted(list(id_set))
|
||||||
id_lists = seperate_list(id_list)
|
id_lists = separate_list(id_list)
|
||||||
for id_seq in id_lists:
|
for id_seq in id_lists:
|
||||||
for id in id_seq:
|
for id in id_seq:
|
||||||
if id == id_seq[0]:
|
if id == id_seq[0]:
|
||||||
@@ -132,7 +132,7 @@ class LocalDocQA:
|
|||||||
embeddings: object = None
|
embeddings: object = None
|
||||||
top_k: int = VECTOR_SEARCH_TOP_K
|
top_k: int = VECTOR_SEARCH_TOP_K
|
||||||
chunk_size: int = CHUNK_SIZE
|
chunk_size: int = CHUNK_SIZE
|
||||||
chunk_conent: bool = True
|
chunk_content: bool = True
|
||||||
score_threshold: int = VECTOR_SEARCH_SCORE_THRESHOLD
|
score_threshold: int = VECTOR_SEARCH_SCORE_THRESHOLD
|
||||||
|
|
||||||
def init_cfg(self,
|
def init_cfg(self,
|
||||||
@@ -209,16 +209,16 @@ class LocalDocQA:
|
|||||||
|
|
||||||
# query 查询内容
|
# query 查询内容
|
||||||
# vs_path 知识库路径
|
# vs_path 知识库路径
|
||||||
# chunk_conent 是否启用上下文关联
|
# chunk_content 是否启用上下文关联
|
||||||
# score_threshold 搜索匹配score阈值
|
# score_threshold 搜索匹配score阈值
|
||||||
# vector_search_top_k 搜索知识库内容条数,默认搜索5条结果
|
# vector_search_top_k 搜索知识库内容条数,默认搜索5条结果
|
||||||
# chunk_sizes 匹配单段内容的连接上下文长度
|
# chunk_sizes 匹配单段内容的连接上下文长度
|
||||||
def get_knowledge_based_conent_test(self, query, vs_path, chunk_conent,
|
def get_knowledge_based_content_test(self, query, vs_path, chunk_content,
|
||||||
score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
|
score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
|
||||||
vector_search_top_k=VECTOR_SEARCH_TOP_K, chunk_size=CHUNK_SIZE,
|
vector_search_top_k=VECTOR_SEARCH_TOP_K, chunk_size=CHUNK_SIZE,
|
||||||
text2vec=None):
|
text2vec=None):
|
||||||
self.vector_store = FAISS.load_local(vs_path, text2vec)
|
self.vector_store = FAISS.load_local(vs_path, text2vec)
|
||||||
self.vector_store.chunk_conent = chunk_conent
|
self.vector_store.chunk_content = chunk_content
|
||||||
self.vector_store.score_threshold = score_threshold
|
self.vector_store.score_threshold = score_threshold
|
||||||
self.vector_store.chunk_size = chunk_size
|
self.vector_store.chunk_size = chunk_size
|
||||||
|
|
||||||
@@ -241,7 +241,7 @@ class LocalDocQA:
|
|||||||
|
|
||||||
|
|
||||||
|
|
||||||
def construct_vector_store(vs_id, vs_path, files, sentence_size, history, one_conent, one_content_segmentation, text2vec):
|
def construct_vector_store(vs_id, vs_path, files, sentence_size, history, one_content, one_content_segmentation, text2vec):
|
||||||
for file in files:
|
for file in files:
|
||||||
assert os.path.exists(file), "输入文件不存在:" + file
|
assert os.path.exists(file), "输入文件不存在:" + file
|
||||||
import nltk
|
import nltk
|
||||||
@@ -297,7 +297,7 @@ class knowledge_archive_interface():
|
|||||||
files=file_manifest,
|
files=file_manifest,
|
||||||
sentence_size=100,
|
sentence_size=100,
|
||||||
history=[],
|
history=[],
|
||||||
one_conent="",
|
one_content="",
|
||||||
one_content_segmentation="",
|
one_content_segmentation="",
|
||||||
text2vec = self.get_chinese_text2vec(),
|
text2vec = self.get_chinese_text2vec(),
|
||||||
)
|
)
|
||||||
@@ -319,19 +319,19 @@ class knowledge_archive_interface():
|
|||||||
files=[],
|
files=[],
|
||||||
sentence_size=100,
|
sentence_size=100,
|
||||||
history=[],
|
history=[],
|
||||||
one_conent="",
|
one_content="",
|
||||||
one_content_segmentation="",
|
one_content_segmentation="",
|
||||||
text2vec = self.get_chinese_text2vec(),
|
text2vec = self.get_chinese_text2vec(),
|
||||||
)
|
)
|
||||||
VECTOR_SEARCH_SCORE_THRESHOLD = 0
|
VECTOR_SEARCH_SCORE_THRESHOLD = 0
|
||||||
VECTOR_SEARCH_TOP_K = 4
|
VECTOR_SEARCH_TOP_K = 4
|
||||||
CHUNK_SIZE = 512
|
CHUNK_SIZE = 512
|
||||||
resp, prompt = self.qa_handle.get_knowledge_based_conent_test(
|
resp, prompt = self.qa_handle.get_knowledge_based_content_test(
|
||||||
query = txt,
|
query = txt,
|
||||||
vs_path = self.kai_path,
|
vs_path = self.kai_path,
|
||||||
score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
|
score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
|
||||||
vector_search_top_k=VECTOR_SEARCH_TOP_K,
|
vector_search_top_k=VECTOR_SEARCH_TOP_K,
|
||||||
chunk_conent=True,
|
chunk_content=True,
|
||||||
chunk_size=CHUNK_SIZE,
|
chunk_size=CHUNK_SIZE,
|
||||||
text2vec = self.get_chinese_text2vec(),
|
text2vec = self.get_chinese_text2vec(),
|
||||||
)
|
)
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
from pydantic import BaseModel, Field
|
from pydantic import BaseModel, Field
|
||||||
from typing import List
|
from typing import List
|
||||||
from toolbox import update_ui_lastest_msg, disable_auto_promotion
|
from toolbox import update_ui_latest_msg, disable_auto_promotion
|
||||||
from request_llms.bridge_all import predict_no_ui_long_connection
|
from request_llms.bridge_all import predict_no_ui_long_connection
|
||||||
from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
|
from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
|
||||||
import copy, json, pickle, os, sys, time
|
import copy, json, pickle, os, sys, time
|
||||||
@@ -9,14 +9,14 @@ import copy, json, pickle, os, sys, time
|
|||||||
def read_avail_plugin_enum():
|
def read_avail_plugin_enum():
|
||||||
from crazy_functional import get_crazy_functions
|
from crazy_functional import get_crazy_functions
|
||||||
plugin_arr = get_crazy_functions()
|
plugin_arr = get_crazy_functions()
|
||||||
# remove plugins with out explaination
|
# remove plugins with out explanation
|
||||||
plugin_arr = {k:v for k, v in plugin_arr.items() if ('Info' in v) and ('Function' in v)}
|
plugin_arr = {k:v for k, v in plugin_arr.items() if ('Info' in v) and ('Function' in v)}
|
||||||
plugin_arr_info = {"F_{:04d}".format(i):v["Info"] for i, v in enumerate(plugin_arr.values(), start=1)}
|
plugin_arr_info = {"F_{:04d}".format(i):v["Info"] for i, v in enumerate(plugin_arr.values(), start=1)}
|
||||||
plugin_arr_dict = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
|
plugin_arr_dict = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
|
||||||
plugin_arr_dict_parse = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
|
plugin_arr_dict_parse = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
|
||||||
plugin_arr_dict_parse.update({f"F_{i}":v for i, v in enumerate(plugin_arr.values(), start=1)})
|
plugin_arr_dict_parse.update({f"F_{i}":v for i, v in enumerate(plugin_arr.values(), start=1)})
|
||||||
prompt = json.dumps(plugin_arr_info, ensure_ascii=False, indent=2)
|
prompt = json.dumps(plugin_arr_info, ensure_ascii=False, indent=2)
|
||||||
prompt = "\n\nThe defination of PluginEnum:\nPluginEnum=" + prompt
|
prompt = "\n\nThe definition of PluginEnum:\nPluginEnum=" + prompt
|
||||||
return prompt, plugin_arr_dict, plugin_arr_dict_parse
|
return prompt, plugin_arr_dict, plugin_arr_dict_parse
|
||||||
|
|
||||||
def wrap_code(txt):
|
def wrap_code(txt):
|
||||||
@@ -55,7 +55,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
|
|||||||
plugin_selection: str = Field(description="The most related plugin from one of the PluginEnum.", default="F_0000")
|
plugin_selection: str = Field(description="The most related plugin from one of the PluginEnum.", default="F_0000")
|
||||||
reason_of_selection: str = Field(description="The reason why you should select this plugin.", default="This plugin satisfy user requirement most")
|
reason_of_selection: str = Field(description="The reason why you should select this plugin.", default="This plugin satisfy user requirement most")
|
||||||
# ⭐ ⭐ ⭐ 选择插件
|
# ⭐ ⭐ ⭐ 选择插件
|
||||||
yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n查找可用插件中...", chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n查找可用插件中...", chatbot=chatbot, history=history, delay=0)
|
||||||
gpt_json_io = GptJsonIO(Plugin)
|
gpt_json_io = GptJsonIO(Plugin)
|
||||||
gpt_json_io.format_instructions = "The format of your output should be a json that can be parsed by json.loads.\n"
|
gpt_json_io.format_instructions = "The format of your output should be a json that can be parsed by json.loads.\n"
|
||||||
gpt_json_io.format_instructions += """Output example: {"plugin_selection":"F_1234", "reason_of_selection":"F_1234 plugin satisfy user requirement most"}\n"""
|
gpt_json_io.format_instructions += """Output example: {"plugin_selection":"F_1234", "reason_of_selection":"F_1234 plugin satisfy user requirement most"}\n"""
|
||||||
@@ -74,13 +74,13 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
|
|||||||
msg += "请求的Prompt为:\n" + wrap_code(get_inputs_show_user(inputs, plugin_arr_enum_prompt))
|
msg += "请求的Prompt为:\n" + wrap_code(get_inputs_show_user(inputs, plugin_arr_enum_prompt))
|
||||||
msg += "语言模型回复为:\n" + wrap_code(gpt_reply)
|
msg += "语言模型回复为:\n" + wrap_code(gpt_reply)
|
||||||
msg += "\n但您可以尝试再试一次\n"
|
msg += "\n但您可以尝试再试一次\n"
|
||||||
yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
|
yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
|
||||||
return
|
return
|
||||||
if plugin_sel.plugin_selection not in plugin_arr_dict_parse:
|
if plugin_sel.plugin_selection not in plugin_arr_dict_parse:
|
||||||
msg = f"抱歉, 找不到合适插件执行该任务, 或者{llm_kwargs['llm_model']}无法理解您的需求。"
|
msg = f"抱歉, 找不到合适插件执行该任务, 或者{llm_kwargs['llm_model']}无法理解您的需求。"
|
||||||
msg += f"语言模型{llm_kwargs['llm_model']}选择了不存在的插件:\n" + wrap_code(gpt_reply)
|
msg += f"语言模型{llm_kwargs['llm_model']}选择了不存在的插件:\n" + wrap_code(gpt_reply)
|
||||||
msg += "\n但您可以尝试再试一次\n"
|
msg += "\n但您可以尝试再试一次\n"
|
||||||
yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
|
yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
|
||||||
return
|
return
|
||||||
|
|
||||||
# ⭐ ⭐ ⭐ 确认插件参数
|
# ⭐ ⭐ ⭐ 确认插件参数
|
||||||
@@ -90,7 +90,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
|
|||||||
appendix_info = get_recent_file_prompt_support(chatbot)
|
appendix_info = get_recent_file_prompt_support(chatbot)
|
||||||
|
|
||||||
plugin = plugin_arr_dict_parse[plugin_sel.plugin_selection]
|
plugin = plugin_arr_dict_parse[plugin_sel.plugin_selection]
|
||||||
yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0)
|
||||||
class PluginExplicit(BaseModel):
|
class PluginExplicit(BaseModel):
|
||||||
plugin_selection: str = plugin_sel.plugin_selection
|
plugin_selection: str = plugin_sel.plugin_selection
|
||||||
plugin_arg: str = Field(description="The argument of the plugin.", default="")
|
plugin_arg: str = Field(description="The argument of the plugin.", default="")
|
||||||
@@ -109,6 +109,6 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
|
|||||||
fn = plugin['Function']
|
fn = plugin['Function']
|
||||||
fn_name = fn.__name__
|
fn_name = fn.__name__
|
||||||
msg = f'{llm_kwargs["llm_model"]}为您选择了插件: `{fn_name}`\n\n插件说明:{plugin["Info"]}\n\n插件参数:{plugin_sel.plugin_arg}\n\n假如偏离了您的要求,按停止键终止。'
|
msg = f'{llm_kwargs["llm_model"]}为您选择了插件: `{fn_name}`\n\n插件说明:{plugin["Info"]}\n\n插件参数:{plugin_sel.plugin_arg}\n\n假如偏离了您的要求,按停止键终止。'
|
||||||
yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
|
yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
|
||||||
yield from fn(plugin_sel.plugin_arg, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, -1)
|
yield from fn(plugin_sel.plugin_arg, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, -1)
|
||||||
return
|
return
|
||||||
@@ -1,6 +1,6 @@
|
|||||||
from pydantic import BaseModel, Field
|
from pydantic import BaseModel, Field
|
||||||
from typing import List
|
from typing import List
|
||||||
from toolbox import update_ui_lastest_msg, get_conf
|
from toolbox import update_ui_latest_msg, get_conf
|
||||||
from request_llms.bridge_all import predict_no_ui_long_connection
|
from request_llms.bridge_all import predict_no_ui_long_connection
|
||||||
from crazy_functions.json_fns.pydantic_io import GptJsonIO
|
from crazy_functions.json_fns.pydantic_io import GptJsonIO
|
||||||
import copy, json, pickle, os, sys
|
import copy, json, pickle, os, sys
|
||||||
@@ -9,7 +9,7 @@ import copy, json, pickle, os, sys
|
|||||||
def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
|
def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
|
||||||
ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
|
ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
|
||||||
if not ALLOW_RESET_CONFIG:
|
if not ALLOW_RESET_CONFIG:
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"当前配置不允许被修改!如需激活本功能,请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
|
lastmsg=f"当前配置不允许被修改!如需激活本功能,请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
|
||||||
chatbot=chatbot, history=history, delay=2
|
chatbot=chatbot, history=history, delay=2
|
||||||
)
|
)
|
||||||
@@ -30,7 +30,7 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
|
|||||||
new_option_value: str = Field(description="the new value of the option", default=None)
|
new_option_value: str = Field(description="the new value of the option", default=None)
|
||||||
|
|
||||||
# ⭐ ⭐ ⭐ 分析用户意图
|
# ⭐ ⭐ ⭐ 分析用户意图
|
||||||
yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n读取新配置中", chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n读取新配置中", chatbot=chatbot, history=history, delay=0)
|
||||||
gpt_json_io = GptJsonIO(ModifyConfigurationIntention)
|
gpt_json_io = GptJsonIO(ModifyConfigurationIntention)
|
||||||
inputs = "Analyze how to change configuration according to following user input, answer me with json: \n\n" + \
|
inputs = "Analyze how to change configuration according to following user input, answer me with json: \n\n" + \
|
||||||
">> " + txt.rstrip('\n').replace('\n','\n>> ') + '\n\n' + \
|
">> " + txt.rstrip('\n').replace('\n','\n>> ') + '\n\n' + \
|
||||||
@@ -44,11 +44,11 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
|
|||||||
|
|
||||||
ok = (explicit_conf in txt)
|
ok = (explicit_conf in txt)
|
||||||
if ok:
|
if ok:
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}",
|
lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}",
|
||||||
chatbot=chatbot, history=history, delay=1
|
chatbot=chatbot, history=history, delay=1
|
||||||
)
|
)
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}\n\n正在修改配置中",
|
lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}\n\n正在修改配置中",
|
||||||
chatbot=chatbot, history=history, delay=2
|
chatbot=chatbot, history=history, delay=2
|
||||||
)
|
)
|
||||||
@@ -57,25 +57,25 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
|
|||||||
from toolbox import set_conf
|
from toolbox import set_conf
|
||||||
set_conf(explicit_conf, user_intention.new_option_value)
|
set_conf(explicit_conf, user_intention.new_option_value)
|
||||||
|
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"正在执行任务: {txt}\n\n配置修改完成,重新页面即可生效。", chatbot=chatbot, history=history, delay=1
|
lastmsg=f"正在执行任务: {txt}\n\n配置修改完成,重新页面即可生效。", chatbot=chatbot, history=history, delay=1
|
||||||
)
|
)
|
||||||
else:
|
else:
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"失败,如果需要配置{explicit_conf},您需要明确说明并在指令中提到它。", chatbot=chatbot, history=history, delay=5
|
lastmsg=f"失败,如果需要配置{explicit_conf},您需要明确说明并在指令中提到它。", chatbot=chatbot, history=history, delay=5
|
||||||
)
|
)
|
||||||
|
|
||||||
def modify_configuration_reboot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
|
def modify_configuration_reboot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
|
||||||
ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
|
ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
|
||||||
if not ALLOW_RESET_CONFIG:
|
if not ALLOW_RESET_CONFIG:
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"当前配置不允许被修改!如需激活本功能,请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
|
lastmsg=f"当前配置不允许被修改!如需激活本功能,请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
|
||||||
chatbot=chatbot, history=history, delay=2
|
chatbot=chatbot, history=history, delay=2
|
||||||
)
|
)
|
||||||
return
|
return
|
||||||
|
|
||||||
yield from modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention)
|
yield from modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention)
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"正在执行任务: {txt}\n\n配置修改完成,五秒后即将重启!若出现报错请无视即可。", chatbot=chatbot, history=history, delay=5
|
lastmsg=f"正在执行任务: {txt}\n\n配置修改完成,五秒后即将重启!若出现报错请无视即可。", chatbot=chatbot, history=history, delay=5
|
||||||
)
|
)
|
||||||
os.execl(sys.executable, sys.executable, *sys.argv)
|
os.execl(sys.executable, sys.executable, *sys.argv)
|
||||||
|
|||||||
@@ -5,7 +5,7 @@ class VoidTerminalState():
|
|||||||
self.reset_state()
|
self.reset_state()
|
||||||
|
|
||||||
def reset_state(self):
|
def reset_state(self):
|
||||||
self.has_provided_explaination = False
|
self.has_provided_explanation = False
|
||||||
|
|
||||||
def lock_plugin(self, chatbot):
|
def lock_plugin(self, chatbot):
|
||||||
chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->虚空终端'
|
chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->虚空终端'
|
||||||
|
|||||||
@@ -1,4 +1,4 @@
|
|||||||
from toolbox import CatchException, update_ui, update_ui_lastest_msg
|
from toolbox import CatchException, update_ui, update_ui_latest_msg
|
||||||
from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
|
from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||||
from request_llms.bridge_all import predict_no_ui_long_connection
|
from request_llms.bridge_all import predict_no_ui_long_connection
|
||||||
|
|||||||
@@ -15,7 +15,7 @@ Testing:
|
|||||||
|
|
||||||
|
|
||||||
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
|
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
|
||||||
from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_lastest_msg
|
from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_latest_msg
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
|
||||||
from crazy_functions.crazy_utils import input_clipping, try_install_deps
|
from crazy_functions.crazy_utils import input_clipping, try_install_deps
|
||||||
from crazy_functions.gen_fns.gen_fns_shared import is_function_successfully_generated
|
from crazy_functions.gen_fns.gen_fns_shared import is_function_successfully_generated
|
||||||
@@ -27,7 +27,7 @@ import time
|
|||||||
import glob
|
import glob
|
||||||
import multiprocessing
|
import multiprocessing
|
||||||
|
|
||||||
templete = """
|
template = """
|
||||||
```python
|
```python
|
||||||
import ... # Put dependencies here, e.g. import numpy as np.
|
import ... # Put dependencies here, e.g. import numpy as np.
|
||||||
|
|
||||||
@@ -77,10 +77,10 @@ def gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history):
|
|||||||
|
|
||||||
# 第二步
|
# 第二步
|
||||||
prompt_compose = [
|
prompt_compose = [
|
||||||
"If previous stage is successful, rewrite the function you have just written to satisfy following templete: \n",
|
"If previous stage is successful, rewrite the function you have just written to satisfy following template: \n",
|
||||||
templete
|
template
|
||||||
]
|
]
|
||||||
i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable templete. "
|
i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable template. "
|
||||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||||
inputs=i_say, inputs_show_user=inputs_show_user,
|
inputs=i_say, inputs_show_user=inputs_show_user,
|
||||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
|
llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
|
||||||
@@ -164,18 +164,18 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
|
|||||||
if get_plugin_arg(plugin_kwargs, key="file_path_arg", default=False):
|
if get_plugin_arg(plugin_kwargs, key="file_path_arg", default=False):
|
||||||
file_path = get_plugin_arg(plugin_kwargs, key="file_path_arg", default=None)
|
file_path = get_plugin_arg(plugin_kwargs, key="file_path_arg", default=None)
|
||||||
file_list.append(file_path)
|
file_list.append(file_path)
|
||||||
yield from update_ui_lastest_msg(f"当前文件: {file_path}", chatbot, history, 1)
|
yield from update_ui_latest_msg(f"当前文件: {file_path}", chatbot, history, 1)
|
||||||
elif have_any_recent_upload_files(chatbot):
|
elif have_any_recent_upload_files(chatbot):
|
||||||
file_dir = get_recent_file_prompt_support(chatbot)
|
file_dir = get_recent_file_prompt_support(chatbot)
|
||||||
file_list = glob.glob(os.path.join(file_dir, '**/*'), recursive=True)
|
file_list = glob.glob(os.path.join(file_dir, '**/*'), recursive=True)
|
||||||
yield from update_ui_lastest_msg(f"当前文件处理列表: {file_list}", chatbot, history, 1)
|
yield from update_ui_latest_msg(f"当前文件处理列表: {file_list}", chatbot, history, 1)
|
||||||
else:
|
else:
|
||||||
chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
|
chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
|
||||||
yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
|
yield from update_ui_latest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
|
||||||
return # 2. 如果没有文件
|
return # 2. 如果没有文件
|
||||||
if len(file_list) == 0:
|
if len(file_list) == 0:
|
||||||
chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
|
chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
|
||||||
yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
|
yield from update_ui_latest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
|
||||||
return # 2. 如果没有文件
|
return # 2. 如果没有文件
|
||||||
|
|
||||||
# 读取文件
|
# 读取文件
|
||||||
@@ -183,7 +183,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
|
|||||||
|
|
||||||
# 粗心检查
|
# 粗心检查
|
||||||
if is_the_upload_folder(txt):
|
if is_the_upload_folder(txt):
|
||||||
yield from update_ui_lastest_msg(f"请在输入框内填写需求, 然后再次点击该插件! 至于您的文件,不用担心, 文件路径 {txt} 已经被记忆. ", chatbot, history, 1)
|
yield from update_ui_latest_msg(f"请在输入框内填写需求, 然后再次点击该插件! 至于您的文件,不用担心, 文件路径 {txt} 已经被记忆. ", chatbot, history, 1)
|
||||||
return
|
return
|
||||||
|
|
||||||
# 开始干正事
|
# 开始干正事
|
||||||
@@ -195,7 +195,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
|
|||||||
code, installation_advance, txt, file_type, llm_kwargs, chatbot, history = \
|
code, installation_advance, txt, file_type, llm_kwargs, chatbot, history = \
|
||||||
yield from gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history)
|
yield from gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history)
|
||||||
chatbot.append(["代码生成阶段结束", ""])
|
chatbot.append(["代码生成阶段结束", ""])
|
||||||
yield from update_ui_lastest_msg(f"正在验证上述代码的有效性 ...", chatbot, history, 1)
|
yield from update_ui_latest_msg(f"正在验证上述代码的有效性 ...", chatbot, history, 1)
|
||||||
# ⭐ 分离代码块
|
# ⭐ 分离代码块
|
||||||
code = get_code_block(code)
|
code = get_code_block(code)
|
||||||
# ⭐ 检查模块
|
# ⭐ 检查模块
|
||||||
@@ -206,11 +206,11 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
|
|||||||
if not traceback: traceback = trimmed_format_exc()
|
if not traceback: traceback = trimmed_format_exc()
|
||||||
# 处理异常
|
# 处理异常
|
||||||
if not traceback: traceback = trimmed_format_exc()
|
if not traceback: traceback = trimmed_format_exc()
|
||||||
yield from update_ui_lastest_msg(f"第 {j+1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n", chatbot, history, 5)
|
yield from update_ui_latest_msg(f"第 {j+1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n", chatbot, history, 5)
|
||||||
|
|
||||||
# 代码生成结束, 开始执行
|
# 代码生成结束, 开始执行
|
||||||
TIME_LIMIT = 15
|
TIME_LIMIT = 15
|
||||||
yield from update_ui_lastest_msg(f"开始创建新进程并执行代码! 时间限制 {TIME_LIMIT} 秒. 请等待任务完成... ", chatbot, history, 1)
|
yield from update_ui_latest_msg(f"开始创建新进程并执行代码! 时间限制 {TIME_LIMIT} 秒. 请等待任务完成... ", chatbot, history, 1)
|
||||||
manager = multiprocessing.Manager()
|
manager = multiprocessing.Manager()
|
||||||
return_dict = manager.dict()
|
return_dict = manager.dict()
|
||||||
|
|
||||||
|
|||||||
@@ -8,7 +8,7 @@
|
|||||||
|
|
||||||
import time
|
import time
|
||||||
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
|
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
|
||||||
from toolbox import get_conf, select_api_key, update_ui_lastest_msg, Singleton
|
from toolbox import get_conf, select_api_key, update_ui_latest_msg, Singleton
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
|
||||||
from crazy_functions.crazy_utils import input_clipping, try_install_deps
|
from crazy_functions.crazy_utils import input_clipping, try_install_deps
|
||||||
from crazy_functions.agent_fns.persistent import GradioMultiuserManagerForPersistentClasses
|
from crazy_functions.agent_fns.persistent import GradioMultiuserManagerForPersistentClasses
|
||||||
|
|||||||
@@ -1,5 +1,5 @@
|
|||||||
from toolbox import CatchException, report_exception, get_log_folder, gen_time_str
|
from toolbox import CatchException, report_exception, get_log_folder, gen_time_str
|
||||||
from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
|
from toolbox import update_ui, promote_file_to_downloadzone, update_ui_latest_msg, disable_auto_promotion
|
||||||
from toolbox import write_history_to_file, promote_file_to_downloadzone
|
from toolbox import write_history_to_file, promote_file_to_downloadzone
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
|
from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
|
||||||
|
|||||||
@@ -166,7 +166,7 @@ class PointWithTrace(Scene):
|
|||||||
|
|
||||||
```
|
```
|
||||||
|
|
||||||
# do not use get_graph, this funciton is deprecated
|
# do not use get_graph, this function is deprecated
|
||||||
|
|
||||||
class ExampleFunctionGraph(Scene):
|
class ExampleFunctionGraph(Scene):
|
||||||
def construct(self):
|
def construct(self):
|
||||||
|
|||||||
@@ -324,16 +324,16 @@ def 生成多种Mermaid图表(
|
|||||||
if os.path.exists(txt): # 如输入区无内容则直接解析历史记录
|
if os.path.exists(txt): # 如输入区无内容则直接解析历史记录
|
||||||
from crazy_functions.pdf_fns.parse_word import extract_text_from_files
|
from crazy_functions.pdf_fns.parse_word import extract_text_from_files
|
||||||
|
|
||||||
file_exist, final_result, page_one, file_manifest, excption = (
|
file_exist, final_result, page_one, file_manifest, exception = (
|
||||||
extract_text_from_files(txt, chatbot, history)
|
extract_text_from_files(txt, chatbot, history)
|
||||||
)
|
)
|
||||||
else:
|
else:
|
||||||
file_exist = False
|
file_exist = False
|
||||||
excption = ""
|
exception = ""
|
||||||
file_manifest = []
|
file_manifest = []
|
||||||
|
|
||||||
if excption != "":
|
if exception != "":
|
||||||
if excption == "word":
|
if exception == "word":
|
||||||
report_exception(
|
report_exception(
|
||||||
chatbot,
|
chatbot,
|
||||||
history,
|
history,
|
||||||
@@ -341,7 +341,7 @@ def 生成多种Mermaid图表(
|
|||||||
b=f"找到了.doc文件,但是该文件格式不被支持,请先转化为.docx格式。",
|
b=f"找到了.doc文件,但是该文件格式不被支持,请先转化为.docx格式。",
|
||||||
)
|
)
|
||||||
|
|
||||||
elif excption == "pdf":
|
elif exception == "pdf":
|
||||||
report_exception(
|
report_exception(
|
||||||
chatbot,
|
chatbot,
|
||||||
history,
|
history,
|
||||||
@@ -349,7 +349,7 @@ def 生成多种Mermaid图表(
|
|||||||
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade pymupdf```。",
|
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade pymupdf```。",
|
||||||
)
|
)
|
||||||
|
|
||||||
elif excption == "word_pip":
|
elif exception == "word_pip":
|
||||||
report_exception(
|
report_exception(
|
||||||
chatbot,
|
chatbot,
|
||||||
history,
|
history,
|
||||||
|
|||||||
@@ -1,4 +1,4 @@
|
|||||||
from toolbox import CatchException, update_ui, ProxyNetworkActivate, update_ui_lastest_msg, get_log_folder, get_user
|
from toolbox import CatchException, update_ui, ProxyNetworkActivate, update_ui_latest_msg, get_log_folder, get_user
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_files_from_everything
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_files_from_everything
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
install_msg ="""
|
install_msg ="""
|
||||||
@@ -42,7 +42,7 @@ def 知识库文件注入(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
|||||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
# from crazy_functions.crazy_utils import try_install_deps
|
# from crazy_functions.crazy_utils import try_install_deps
|
||||||
# try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
|
# try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
|
||||||
# yield from update_ui_lastest_msg("安装完成,您可以再次重试。", chatbot, history)
|
# yield from update_ui_latest_msg("安装完成,您可以再次重试。", chatbot, history)
|
||||||
return
|
return
|
||||||
|
|
||||||
# < --------------------读取文件--------------- >
|
# < --------------------读取文件--------------- >
|
||||||
@@ -95,7 +95,7 @@ def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
|||||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
# from crazy_functions.crazy_utils import try_install_deps
|
# from crazy_functions.crazy_utils import try_install_deps
|
||||||
# try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
|
# try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
|
||||||
# yield from update_ui_lastest_msg("安装完成,您可以再次重试。", chatbot, history)
|
# yield from update_ui_latest_msg("安装完成,您可以再次重试。", chatbot, history)
|
||||||
return
|
return
|
||||||
|
|
||||||
# < ------------------- --------------- >
|
# < ------------------- --------------- >
|
||||||
|
|||||||
@@ -47,7 +47,7 @@ explain_msg = """
|
|||||||
from pydantic import BaseModel, Field
|
from pydantic import BaseModel, Field
|
||||||
from typing import List
|
from typing import List
|
||||||
from toolbox import CatchException, update_ui, is_the_upload_folder
|
from toolbox import CatchException, update_ui, is_the_upload_folder
|
||||||
from toolbox import update_ui_lastest_msg, disable_auto_promotion
|
from toolbox import update_ui_latest_msg, disable_auto_promotion
|
||||||
from request_llms.bridge_all import predict_no_ui_long_connection
|
from request_llms.bridge_all import predict_no_ui_long_connection
|
||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||||
from crazy_functions.crazy_utils import input_clipping
|
from crazy_functions.crazy_utils import input_clipping
|
||||||
@@ -113,19 +113,19 @@ def 虚空终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
|
|||||||
# 用简单的关键词检测用户意图
|
# 用简单的关键词检测用户意图
|
||||||
is_certain, _ = analyze_intention_with_simple_rules(txt)
|
is_certain, _ = analyze_intention_with_simple_rules(txt)
|
||||||
if is_the_upload_folder(txt):
|
if is_the_upload_folder(txt):
|
||||||
state.set_state(chatbot=chatbot, key='has_provided_explaination', value=False)
|
state.set_state(chatbot=chatbot, key='has_provided_explanation', value=False)
|
||||||
appendix_msg = "\n\n**很好,您已经上传了文件**,现在请您描述您的需求。"
|
appendix_msg = "\n\n**很好,您已经上传了文件**,现在请您描述您的需求。"
|
||||||
|
|
||||||
if is_certain or (state.has_provided_explaination):
|
if is_certain or (state.has_provided_explanation):
|
||||||
# 如果意图明确,跳过提示环节
|
# 如果意图明确,跳过提示环节
|
||||||
state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
|
state.set_state(chatbot=chatbot, key='has_provided_explanation', value=True)
|
||||||
state.unlock_plugin(chatbot=chatbot)
|
state.unlock_plugin(chatbot=chatbot)
|
||||||
yield from update_ui(chatbot=chatbot, history=history)
|
yield from update_ui(chatbot=chatbot, history=history)
|
||||||
yield from 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
|
yield from 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
|
||||||
return
|
return
|
||||||
else:
|
else:
|
||||||
# 如果意图模糊,提示
|
# 如果意图模糊,提示
|
||||||
state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
|
state.set_state(chatbot=chatbot, key='has_provided_explanation', value=True)
|
||||||
state.lock_plugin(chatbot=chatbot)
|
state.lock_plugin(chatbot=chatbot)
|
||||||
chatbot.append(("虚空终端状态:", explain_msg+appendix_msg))
|
chatbot.append(("虚空终端状态:", explain_msg+appendix_msg))
|
||||||
yield from update_ui(chatbot=chatbot, history=history)
|
yield from update_ui(chatbot=chatbot, history=history)
|
||||||
@@ -141,7 +141,7 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
|||||||
# ⭐ ⭐ ⭐ 分析用户意图
|
# ⭐ ⭐ ⭐ 分析用户意图
|
||||||
is_certain, user_intention = analyze_intention_with_simple_rules(txt)
|
is_certain, user_intention = analyze_intention_with_simple_rules(txt)
|
||||||
if not is_certain:
|
if not is_certain:
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"正在执行任务: {txt}\n\n分析用户意图中", chatbot=chatbot, history=history, delay=0)
|
lastmsg=f"正在执行任务: {txt}\n\n分析用户意图中", chatbot=chatbot, history=history, delay=0)
|
||||||
gpt_json_io = GptJsonIO(UserIntention)
|
gpt_json_io = GptJsonIO(UserIntention)
|
||||||
rf_req = "\nchoose from ['ModifyConfiguration', 'ExecutePlugin', 'Chat']"
|
rf_req = "\nchoose from ['ModifyConfiguration', 'ExecutePlugin', 'Chat']"
|
||||||
@@ -154,13 +154,13 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
|||||||
user_intention = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
|
user_intention = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
|
||||||
lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
|
lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
|
||||||
except JsonStringError as e:
|
except JsonStringError as e:
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 失败 当前语言模型({llm_kwargs['llm_model']})不能理解您的意图", chatbot=chatbot, history=history, delay=0)
|
lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 失败 当前语言模型({llm_kwargs['llm_model']})不能理解您的意图", chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
else:
|
else:
|
||||||
pass
|
pass
|
||||||
|
|
||||||
yield from update_ui_lastest_msg(
|
yield from update_ui_latest_msg(
|
||||||
lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
|
lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
|
||||||
chatbot=chatbot, history=history, delay=0)
|
chatbot=chatbot, history=history, delay=0)
|
||||||
|
|
||||||
|
|||||||
@@ -42,7 +42,7 @@ class AsyncGptTask():
|
|||||||
MAX_TOKEN_ALLO = 2560
|
MAX_TOKEN_ALLO = 2560
|
||||||
i_say, history = input_clipping(i_say, history, max_token_limit=MAX_TOKEN_ALLO)
|
i_say, history = input_clipping(i_say, history, max_token_limit=MAX_TOKEN_ALLO)
|
||||||
gpt_say_partial = predict_no_ui_long_connection(inputs=i_say, llm_kwargs=llm_kwargs, history=history, sys_prompt=sys_prompt,
|
gpt_say_partial = predict_no_ui_long_connection(inputs=i_say, llm_kwargs=llm_kwargs, history=history, sys_prompt=sys_prompt,
|
||||||
observe_window=observe_window[index], console_slience=True)
|
observe_window=observe_window[index], console_silence=True)
|
||||||
except ConnectionAbortedError as token_exceed_err:
|
except ConnectionAbortedError as token_exceed_err:
|
||||||
logger.error('至少一个线程任务Token溢出而失败', e)
|
logger.error('至少一个线程任务Token溢出而失败', e)
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||||
from toolbox import CatchException, report_exception, promote_file_to_downloadzone
|
from toolbox import CatchException, report_exception, promote_file_to_downloadzone
|
||||||
from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion, write_history_to_file
|
from toolbox import update_ui, update_ui_latest_msg, disable_auto_promotion, write_history_to_file
|
||||||
import logging
|
import logging
|
||||||
import requests
|
import requests
|
||||||
import time
|
import time
|
||||||
@@ -156,7 +156,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
|||||||
history = []
|
history = []
|
||||||
meta_paper_info_list = yield from get_meta_information(txt, chatbot, history)
|
meta_paper_info_list = yield from get_meta_information(txt, chatbot, history)
|
||||||
if len(meta_paper_info_list) == 0:
|
if len(meta_paper_info_list) == 0:
|
||||||
yield from update_ui_lastest_msg(lastmsg='获取文献失败,可能触发了google反爬虫机制。',chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(lastmsg='获取文献失败,可能触发了google反爬虫机制。',chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
batchsize = 5
|
batchsize = 5
|
||||||
for batch in range(math.ceil(len(meta_paper_info_list)/batchsize)):
|
for batch in range(math.ceil(len(meta_paper_info_list)/batchsize)):
|
||||||
|
|||||||
@@ -1141,7 +1141,7 @@
|
|||||||
"内容太长了都会触发token数量溢出的错误": "An error of token overflow will be triggered if the content is too long",
|
"内容太长了都会触发token数量溢出的错误": "An error of token overflow will be triggered if the content is too long",
|
||||||
"chatbot 为WebUI中显示的对话列表": "chatbot is the conversation list displayed in WebUI",
|
"chatbot 为WebUI中显示的对话列表": "chatbot is the conversation list displayed in WebUI",
|
||||||
"修改它": "Modify it",
|
"修改它": "Modify it",
|
||||||
"然后yeild出去": "Then yield it out",
|
"然后yield出去": "Then yield it out",
|
||||||
"可以直接修改对话界面内容": "You can directly modify the conversation interface content",
|
"可以直接修改对话界面内容": "You can directly modify the conversation interface content",
|
||||||
"additional_fn代表点击的哪个按钮": "additional_fn represents which button is clicked",
|
"additional_fn代表点击的哪个按钮": "additional_fn represents which button is clicked",
|
||||||
"按钮见functional.py": "See functional.py for buttons",
|
"按钮见functional.py": "See functional.py for buttons",
|
||||||
@@ -1732,7 +1732,7 @@
|
|||||||
"或者重启之后再度尝试": "Or try again after restarting",
|
"或者重启之后再度尝试": "Or try again after restarting",
|
||||||
"免费": "Free",
|
"免费": "Free",
|
||||||
"仅在Windows系统进行了测试": "Tested only on Windows system",
|
"仅在Windows系统进行了测试": "Tested only on Windows system",
|
||||||
"欢迎加REAME中的QQ联系开发者": "Feel free to contact the developer via QQ in REAME",
|
"欢迎加README中的QQ联系开发者": "Feel free to contact the developer via QQ in README",
|
||||||
"当前知识库内的有效文件": "Valid files in the current knowledge base",
|
"当前知识库内的有效文件": "Valid files in the current knowledge base",
|
||||||
"您可以到Github Issue区": "You can go to the Github Issue area",
|
"您可以到Github Issue区": "You can go to the Github Issue area",
|
||||||
"刷新Gradio前端界面": "Refresh the Gradio frontend interface",
|
"刷新Gradio前端界面": "Refresh the Gradio frontend interface",
|
||||||
@@ -1759,7 +1759,7 @@
|
|||||||
"报错信息如下. 如果是与网络相关的问题": "Error message as follows. If it is related to network issues",
|
"报错信息如下. 如果是与网络相关的问题": "Error message as follows. If it is related to network issues",
|
||||||
"功能描述": "Function description",
|
"功能描述": "Function description",
|
||||||
"禁止移除或修改此警告": "Removal or modification of this warning is prohibited",
|
"禁止移除或修改此警告": "Removal or modification of this warning is prohibited",
|
||||||
"Arixv翻译": "Arixv translation",
|
"ArXiv翻译": "ArXiv translation",
|
||||||
"读取优先级": "Read priority",
|
"读取优先级": "Read priority",
|
||||||
"包含documentclass关键字": "Contains the documentclass keyword",
|
"包含documentclass关键字": "Contains the documentclass keyword",
|
||||||
"根据文本使用GPT模型生成相应的图像": "Generate corresponding images using GPT model based on the text",
|
"根据文本使用GPT模型生成相应的图像": "Generate corresponding images using GPT model based on the text",
|
||||||
@@ -1998,7 +1998,7 @@
|
|||||||
"开始最终总结": "Start final summary",
|
"开始最终总结": "Start final summary",
|
||||||
"openai的官方KEY需要伴随组织编码": "Openai's official KEY needs to be accompanied by organizational code",
|
"openai的官方KEY需要伴随组织编码": "Openai's official KEY needs to be accompanied by organizational code",
|
||||||
"将子线程的gpt结果写入chatbot": "Write the GPT result of the sub-thread into the chatbot",
|
"将子线程的gpt结果写入chatbot": "Write the GPT result of the sub-thread into the chatbot",
|
||||||
"Arixv论文精细翻译": "Fine translation of Arixv paper",
|
"ArXiv论文精细翻译": "Fine translation of ArXiv paper",
|
||||||
"开始接收chatglmft的回复": "Start receiving replies from chatglmft",
|
"开始接收chatglmft的回复": "Start receiving replies from chatglmft",
|
||||||
"请先将.doc文档转换为.docx文档": "Please convert .doc documents to .docx documents first",
|
"请先将.doc文档转换为.docx文档": "Please convert .doc documents to .docx documents first",
|
||||||
"避免多用户干扰": "Avoid multiple user interference",
|
"避免多用户干扰": "Avoid multiple user interference",
|
||||||
@@ -2360,7 +2360,7 @@
|
|||||||
"请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件": "Please set ALLOW_RESET_CONFIG=True in config.py and restart the software",
|
"请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件": "Please set ALLOW_RESET_CONFIG=True in config.py and restart the software",
|
||||||
"按照自然语言描述生成一个动画 | 输入参数是一段话": "Generate an animation based on natural language description | Input parameter is a sentence",
|
"按照自然语言描述生成一个动画 | 输入参数是一段话": "Generate an animation based on natural language description | Input parameter is a sentence",
|
||||||
"你的hf用户名如qingxu98": "Your hf username is qingxu98",
|
"你的hf用户名如qingxu98": "Your hf username is qingxu98",
|
||||||
"Arixv论文精细翻译 | 输入参数arxiv论文的ID": "Fine translation of Arixv paper | Input parameter is the ID of arxiv paper",
|
"ArXiv论文精细翻译 | 输入参数arxiv论文的ID": "Fine translation of ArXiv paper | Input parameter is the ID of arxiv paper",
|
||||||
"无法获取 abstract": "Unable to retrieve abstract",
|
"无法获取 abstract": "Unable to retrieve abstract",
|
||||||
"尽可能地仅用一行命令解决我的要求": "Try to solve my request using only one command",
|
"尽可能地仅用一行命令解决我的要求": "Try to solve my request using only one command",
|
||||||
"提取插件参数": "Extract plugin parameters",
|
"提取插件参数": "Extract plugin parameters",
|
||||||
|
|||||||
@@ -753,7 +753,7 @@
|
|||||||
"手动指定和筛选源代码文件类型": "ソースコードファイルタイプを手動で指定およびフィルタリングする",
|
"手动指定和筛选源代码文件类型": "ソースコードファイルタイプを手動で指定およびフィルタリングする",
|
||||||
"更多函数插件": "その他の関数プラグイン",
|
"更多函数插件": "その他の関数プラグイン",
|
||||||
"看门狗的耐心": "監視犬の忍耐力",
|
"看门狗的耐心": "監視犬の忍耐力",
|
||||||
"然后yeild出去": "そして出力する",
|
"然后yield出去": "そして出力する",
|
||||||
"拆分过长的IPynb文件": "長すぎるIPynbファイルを分割する",
|
"拆分过长的IPynb文件": "長すぎるIPynbファイルを分割する",
|
||||||
"1. 把input的余量留出来": "1. 入力の余裕を残す",
|
"1. 把input的余量留出来": "1. 入力の余裕を残す",
|
||||||
"请求超时": "リクエストがタイムアウトしました",
|
"请求超时": "リクエストがタイムアウトしました",
|
||||||
@@ -1803,7 +1803,7 @@
|
|||||||
"默认值为1000": "デフォルト値は1000です",
|
"默认值为1000": "デフォルト値は1000です",
|
||||||
"写出文件": "ファイルに書き出す",
|
"写出文件": "ファイルに書き出す",
|
||||||
"生成的视频文件路径": "生成されたビデオファイルのパス",
|
"生成的视频文件路径": "生成されたビデオファイルのパス",
|
||||||
"Arixv论文精细翻译": "Arixv論文の詳細な翻訳",
|
"ArXiv论文精细翻译": "ArXiv論文の詳細な翻訳",
|
||||||
"用latex编译为PDF对修正处做高亮": "LaTeXでコンパイルしてPDFに修正をハイライトする",
|
"用latex编译为PDF对修正处做高亮": "LaTeXでコンパイルしてPDFに修正をハイライトする",
|
||||||
"点击“停止”键可终止程序": "「停止」ボタンをクリックしてプログラムを終了できます",
|
"点击“停止”键可终止程序": "「停止」ボタンをクリックしてプログラムを終了できます",
|
||||||
"否则将导致每个人的Claude问询历史互相渗透": "さもないと、各人のClaudeの問い合わせ履歴が相互に侵入します",
|
"否则将导致每个人的Claude问询历史互相渗透": "さもないと、各人のClaudeの問い合わせ履歴が相互に侵入します",
|
||||||
@@ -1987,7 +1987,7 @@
|
|||||||
"前面是中文逗号": "前面是中文逗号",
|
"前面是中文逗号": "前面是中文逗号",
|
||||||
"的依赖": "的依赖",
|
"的依赖": "的依赖",
|
||||||
"材料如下": "材料如下",
|
"材料如下": "材料如下",
|
||||||
"欢迎加REAME中的QQ联系开发者": "欢迎加REAME中的QQ联系开发者",
|
"欢迎加README中的QQ联系开发者": "欢迎加README中的QQ联系开发者",
|
||||||
"开始下载": "開始ダウンロード",
|
"开始下载": "開始ダウンロード",
|
||||||
"100字以内": "100文字以内",
|
"100字以内": "100文字以内",
|
||||||
"创建request": "リクエストの作成",
|
"创建request": "リクエストの作成",
|
||||||
|
|||||||
@@ -771,7 +771,7 @@
|
|||||||
"查询代理的地理位置": "查詢代理的地理位置",
|
"查询代理的地理位置": "查詢代理的地理位置",
|
||||||
"是否在输入过长时": "是否在輸入過長時",
|
"是否在输入过长时": "是否在輸入過長時",
|
||||||
"chatGPT分析报告": "chatGPT分析報告",
|
"chatGPT分析报告": "chatGPT分析報告",
|
||||||
"然后yeild出去": "然後yield出去",
|
"然后yield出去": "然後yield出去",
|
||||||
"用户取消了程序": "使用者取消了程式",
|
"用户取消了程序": "使用者取消了程式",
|
||||||
"琥珀色": "琥珀色",
|
"琥珀色": "琥珀色",
|
||||||
"这里是特殊函数插件的高级参数输入区": "這裡是特殊函數插件的高級參數輸入區",
|
"这里是特殊函数插件的高级参数输入区": "這裡是特殊函數插件的高級參數輸入區",
|
||||||
@@ -1587,7 +1587,7 @@
|
|||||||
"否则将导致每个人的Claude问询历史互相渗透": "否則將導致每個人的Claude問詢歷史互相滲透",
|
"否则将导致每个人的Claude问询历史互相渗透": "否則將導致每個人的Claude問詢歷史互相滲透",
|
||||||
"提问吧! 但注意": "提問吧!但注意",
|
"提问吧! 但注意": "提問吧!但注意",
|
||||||
"待处理的word文档路径": "待處理的word文檔路徑",
|
"待处理的word文档路径": "待處理的word文檔路徑",
|
||||||
"欢迎加REAME中的QQ联系开发者": "歡迎加REAME中的QQ聯繫開發者",
|
"欢迎加README中的QQ联系开发者": "歡迎加README中的QQ聯繫開發者",
|
||||||
"建议暂时不要使用": "建議暫時不要使用",
|
"建议暂时不要使用": "建議暫時不要使用",
|
||||||
"Latex没有安装": "Latex沒有安裝",
|
"Latex没有安装": "Latex沒有安裝",
|
||||||
"在这里放一些网上搜集的demo": "在這裡放一些網上搜集的demo",
|
"在这里放一些网上搜集的demo": "在這裡放一些網上搜集的demo",
|
||||||
@@ -1989,7 +1989,7 @@
|
|||||||
"请耐心等待": "請耐心等待",
|
"请耐心等待": "請耐心等待",
|
||||||
"在执行完成之后": "在執行完成之後",
|
"在执行完成之后": "在執行完成之後",
|
||||||
"参数简单": "參數簡單",
|
"参数简单": "參數簡單",
|
||||||
"Arixv论文精细翻译": "Arixv論文精細翻譯",
|
"ArXiv论文精细翻译": "ArXiv論文精細翻譯",
|
||||||
"备份和下载": "備份和下載",
|
"备份和下载": "備份和下載",
|
||||||
"当前报错的latex代码处于第": "當前報錯的latex代碼處於第",
|
"当前报错的latex代码处于第": "當前報錯的latex代碼處於第",
|
||||||
"Markdown翻译": "Markdown翻譯",
|
"Markdown翻译": "Markdown翻譯",
|
||||||
|
|||||||
@@ -1265,9 +1265,9 @@ def LLM_CATCH_EXCEPTION(f):
|
|||||||
"""
|
"""
|
||||||
装饰器函数,将错误显示出来
|
装饰器函数,将错误显示出来
|
||||||
"""
|
"""
|
||||||
def decorated(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list, console_slience:bool):
|
def decorated(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list, console_silence:bool):
|
||||||
try:
|
try:
|
||||||
return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
|
return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence)
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
|
tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
|
||||||
observe_window[0] = tb_str
|
observe_window[0] = tb_str
|
||||||
@@ -1275,7 +1275,7 @@ def LLM_CATCH_EXCEPTION(f):
|
|||||||
return decorated
|
return decorated
|
||||||
|
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list=[], console_slience:bool=False):
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
发送至LLM,等待回复,一次性完成,不显示中间过程。但内部(尽可能地)用stream的方法避免中途网线被掐。
|
发送至LLM,等待回复,一次性完成,不显示中间过程。但内部(尽可能地)用stream的方法避免中途网线被掐。
|
||||||
inputs:
|
inputs:
|
||||||
@@ -1297,7 +1297,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys
|
|||||||
if '&' not in model:
|
if '&' not in model:
|
||||||
# 如果只询问“一个”大语言模型(多数情况):
|
# 如果只询问“一个”大语言模型(多数情况):
|
||||||
method = model_info[model]["fn_without_ui"]
|
method = model_info[model]["fn_without_ui"]
|
||||||
return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
|
return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence)
|
||||||
else:
|
else:
|
||||||
# 如果同时询问“多个”大语言模型,这个稍微啰嗦一点,但思路相同,您不必读这个else分支
|
# 如果同时询问“多个”大语言模型,这个稍微啰嗦一点,但思路相同,您不必读这个else分支
|
||||||
executor = ThreadPoolExecutor(max_workers=4)
|
executor = ThreadPoolExecutor(max_workers=4)
|
||||||
@@ -1314,7 +1314,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys
|
|||||||
method = model_info[model]["fn_without_ui"]
|
method = model_info[model]["fn_without_ui"]
|
||||||
llm_kwargs_feedin = copy.deepcopy(llm_kwargs)
|
llm_kwargs_feedin = copy.deepcopy(llm_kwargs)
|
||||||
llm_kwargs_feedin['llm_model'] = model
|
llm_kwargs_feedin['llm_model'] = model
|
||||||
future = executor.submit(LLM_CATCH_EXCEPTION(method), inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_slience)
|
future = executor.submit(LLM_CATCH_EXCEPTION(method), inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_silence)
|
||||||
futures.append(future)
|
futures.append(future)
|
||||||
|
|
||||||
def mutex_manager(window_mutex, observe_window):
|
def mutex_manager(window_mutex, observe_window):
|
||||||
|
|||||||
@@ -139,7 +139,7 @@ global glmft_handle
|
|||||||
glmft_handle = None
|
glmft_handle = None
|
||||||
#################################################################################
|
#################################################################################
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
多线程方法
|
多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
|
|||||||
@@ -125,7 +125,7 @@ def verify_endpoint(endpoint):
|
|||||||
raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
|
raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
|
||||||
return endpoint
|
return endpoint
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_slience:bool=False):
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
发送至chatGPT,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免中途网线被掐。
|
发送至chatGPT,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免中途网线被掐。
|
||||||
inputs:
|
inputs:
|
||||||
@@ -203,7 +203,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
|
|||||||
if (not has_content) and (not has_role): continue # raise RuntimeError("发现不标准的第三方接口:"+delta)
|
if (not has_content) and (not has_role): continue # raise RuntimeError("发现不标准的第三方接口:"+delta)
|
||||||
if has_content: # has_role = True/False
|
if has_content: # has_role = True/False
|
||||||
result += delta["content"]
|
result += delta["content"]
|
||||||
if not console_slience: print(delta["content"], end='')
|
if not console_silence: print(delta["content"], end='')
|
||||||
if observe_window is not None:
|
if observe_window is not None:
|
||||||
# 观测窗,把已经获取的数据显示出去
|
# 观测窗,把已经获取的数据显示出去
|
||||||
if len(observe_window) >= 1:
|
if len(observe_window) >= 1:
|
||||||
@@ -231,7 +231,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
|
|||||||
inputs 是本次问询的输入
|
inputs 是本次问询的输入
|
||||||
top_p, temperature是chatGPT的内部调优参数
|
top_p, temperature是chatGPT的内部调优参数
|
||||||
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
||||||
chatbot 为WebUI中显示的对话列表,修改它,然后yeild出去,可以直接修改对话界面内容
|
chatbot 为WebUI中显示的对话列表,修改它,然后yield出去,可以直接修改对话界面内容
|
||||||
additional_fn代表点击的哪个按钮,按钮见functional.py
|
additional_fn代表点击的哪个按钮,按钮见functional.py
|
||||||
"""
|
"""
|
||||||
from request_llms.bridge_all import model_info
|
from request_llms.bridge_all import model_info
|
||||||
|
|||||||
@@ -16,7 +16,7 @@ import base64
|
|||||||
import glob
|
import glob
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc, is_the_upload_folder, \
|
from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc, is_the_upload_folder, \
|
||||||
update_ui_lastest_msg, get_max_token, encode_image, have_any_recent_upload_image_files, log_chat
|
update_ui_latest_msg, get_max_token, encode_image, have_any_recent_upload_image_files, log_chat
|
||||||
|
|
||||||
|
|
||||||
proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
|
proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
|
||||||
@@ -67,7 +67,7 @@ def verify_endpoint(endpoint):
|
|||||||
"""
|
"""
|
||||||
return endpoint
|
return endpoint
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
|
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_silence=False):
|
||||||
raise NotImplementedError
|
raise NotImplementedError
|
||||||
|
|
||||||
|
|
||||||
@@ -183,7 +183,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
|||||||
if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
|
if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
|
||||||
# 判定为数据流的结束,gpt_replying_buffer也写完了
|
# 判定为数据流的结束,gpt_replying_buffer也写完了
|
||||||
lastmsg = chatbot[-1][-1] + f"\n\n\n\n「{llm_kwargs['llm_model']}调用结束,该模型不具备上下文对话能力,如需追问,请及时切换模型。」"
|
lastmsg = chatbot[-1][-1] + f"\n\n\n\n「{llm_kwargs['llm_model']}调用结束,该模型不具备上下文对话能力,如需追问,请及时切换模型。」"
|
||||||
yield from update_ui_lastest_msg(lastmsg, chatbot, history, delay=1)
|
yield from update_ui_latest_msg(lastmsg, chatbot, history, delay=1)
|
||||||
log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
|
log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
|
||||||
break
|
break
|
||||||
# 处理数据流的主体
|
# 处理数据流的主体
|
||||||
|
|||||||
@@ -69,7 +69,7 @@ def decode_chunk(chunk):
|
|||||||
return need_to_pass, chunkjson, is_last_chunk
|
return need_to_pass, chunkjson, is_last_chunk
|
||||||
|
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
|
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_silence=False):
|
||||||
"""
|
"""
|
||||||
发送至chatGPT,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免中途网线被掐。
|
发送至chatGPT,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免中途网线被掐。
|
||||||
inputs:
|
inputs:
|
||||||
@@ -151,7 +151,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
|||||||
inputs 是本次问询的输入
|
inputs 是本次问询的输入
|
||||||
top_p, temperature是chatGPT的内部调优参数
|
top_p, temperature是chatGPT的内部调优参数
|
||||||
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
||||||
chatbot 为WebUI中显示的对话列表,修改它,然后yeild出去,可以直接修改对话界面内容
|
chatbot 为WebUI中显示的对话列表,修改它,然后yield出去,可以直接修改对话界面内容
|
||||||
additional_fn代表点击的哪个按钮,按钮见functional.py
|
additional_fn代表点击的哪个按钮,按钮见functional.py
|
||||||
"""
|
"""
|
||||||
if inputs == "": inputs = "空空如也的输入栏"
|
if inputs == "": inputs = "空空如也的输入栏"
|
||||||
|
|||||||
@@ -68,7 +68,7 @@ def verify_endpoint(endpoint):
|
|||||||
raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
|
raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
|
||||||
return endpoint
|
return endpoint
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_slience:bool=False):
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
发送,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免中途网线被掐。
|
发送,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免中途网线被掐。
|
||||||
inputs:
|
inputs:
|
||||||
@@ -111,7 +111,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
|
|||||||
if chunkjson['event_type'] == 'stream-start': continue
|
if chunkjson['event_type'] == 'stream-start': continue
|
||||||
if chunkjson['event_type'] == 'text-generation':
|
if chunkjson['event_type'] == 'text-generation':
|
||||||
result += chunkjson["text"]
|
result += chunkjson["text"]
|
||||||
if not console_slience: print(chunkjson["text"], end='')
|
if not console_silence: print(chunkjson["text"], end='')
|
||||||
if observe_window is not None:
|
if observe_window is not None:
|
||||||
# 观测窗,把已经获取的数据显示出去
|
# 观测窗,把已经获取的数据显示出去
|
||||||
if len(observe_window) >= 1:
|
if len(observe_window) >= 1:
|
||||||
@@ -132,7 +132,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
|
|||||||
inputs 是本次问询的输入
|
inputs 是本次问询的输入
|
||||||
top_p, temperature是chatGPT的内部调优参数
|
top_p, temperature是chatGPT的内部调优参数
|
||||||
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
||||||
chatbot 为WebUI中显示的对话列表,修改它,然后yeild出去,可以直接修改对话界面内容
|
chatbot 为WebUI中显示的对话列表,修改它,然后yield出去,可以直接修改对话界面内容
|
||||||
additional_fn代表点击的哪个按钮,按钮见functional.py
|
additional_fn代表点击的哪个按钮,按钮见functional.py
|
||||||
"""
|
"""
|
||||||
# if is_any_api_key(inputs):
|
# if is_any_api_key(inputs):
|
||||||
|
|||||||
@@ -8,7 +8,7 @@ import os
|
|||||||
import time
|
import time
|
||||||
from request_llms.com_google import GoogleChatInit
|
from request_llms.com_google import GoogleChatInit
|
||||||
from toolbox import ChatBotWithCookies
|
from toolbox import ChatBotWithCookies
|
||||||
from toolbox import get_conf, update_ui, update_ui_lastest_msg, have_any_recent_upload_image_files, trimmed_format_exc, log_chat, encode_image
|
from toolbox import get_conf, update_ui, update_ui_latest_msg, have_any_recent_upload_image_files, trimmed_format_exc, log_chat, encode_image
|
||||||
|
|
||||||
proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY')
|
proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY')
|
||||||
timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
|
timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
|
||||||
@@ -16,7 +16,7 @@ timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check
|
|||||||
|
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=[],
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=[],
|
||||||
console_slience:bool=False):
|
console_silence:bool=False):
|
||||||
# 检查API_KEY
|
# 检查API_KEY
|
||||||
if get_conf("GEMINI_API_KEY") == "":
|
if get_conf("GEMINI_API_KEY") == "":
|
||||||
raise ValueError(f"请配置 GEMINI_API_KEY。")
|
raise ValueError(f"请配置 GEMINI_API_KEY。")
|
||||||
@@ -60,7 +60,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
|
|||||||
|
|
||||||
# 检查API_KEY
|
# 检查API_KEY
|
||||||
if get_conf("GEMINI_API_KEY") == "":
|
if get_conf("GEMINI_API_KEY") == "":
|
||||||
yield from update_ui_lastest_msg(f"请配置 GEMINI_API_KEY。", chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(f"请配置 GEMINI_API_KEY。", chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
|
|
||||||
# 适配润色区域
|
# 适配润色区域
|
||||||
|
|||||||
@@ -55,7 +55,7 @@ class GetGLMHandle(Process):
|
|||||||
if self.jittorllms_model is None:
|
if self.jittorllms_model is None:
|
||||||
device = get_conf('LOCAL_MODEL_DEVICE')
|
device = get_conf('LOCAL_MODEL_DEVICE')
|
||||||
from .jittorllms.models import get_model
|
from .jittorllms.models import get_model
|
||||||
# availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
|
# available_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
|
||||||
args_dict = {'model': 'llama'}
|
args_dict = {'model': 'llama'}
|
||||||
print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
|
print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
|
||||||
self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
|
self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
|
||||||
@@ -107,7 +107,7 @@ global llama_glm_handle
|
|||||||
llama_glm_handle = None
|
llama_glm_handle = None
|
||||||
#################################################################################
|
#################################################################################
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
多线程方法
|
多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
|
|||||||
@@ -55,7 +55,7 @@ class GetGLMHandle(Process):
|
|||||||
if self.jittorllms_model is None:
|
if self.jittorllms_model is None:
|
||||||
device = get_conf('LOCAL_MODEL_DEVICE')
|
device = get_conf('LOCAL_MODEL_DEVICE')
|
||||||
from .jittorllms.models import get_model
|
from .jittorllms.models import get_model
|
||||||
# availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
|
# available_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
|
||||||
args_dict = {'model': 'pangualpha'}
|
args_dict = {'model': 'pangualpha'}
|
||||||
print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
|
print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
|
||||||
self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
|
self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
|
||||||
@@ -107,7 +107,7 @@ global pangu_glm_handle
|
|||||||
pangu_glm_handle = None
|
pangu_glm_handle = None
|
||||||
#################################################################################
|
#################################################################################
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
多线程方法
|
多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
|
|||||||
@@ -55,7 +55,7 @@ class GetGLMHandle(Process):
|
|||||||
if self.jittorllms_model is None:
|
if self.jittorllms_model is None:
|
||||||
device = get_conf('LOCAL_MODEL_DEVICE')
|
device = get_conf('LOCAL_MODEL_DEVICE')
|
||||||
from .jittorllms.models import get_model
|
from .jittorllms.models import get_model
|
||||||
# availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
|
# available_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
|
||||||
args_dict = {'model': 'chatrwkv'}
|
args_dict = {'model': 'chatrwkv'}
|
||||||
print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
|
print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
|
||||||
self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
|
self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
|
||||||
@@ -107,7 +107,7 @@ global rwkv_glm_handle
|
|||||||
rwkv_glm_handle = None
|
rwkv_glm_handle = None
|
||||||
#################################################################################
|
#################################################################################
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
多线程方法
|
多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
|
|||||||
@@ -46,8 +46,8 @@ class GetLlamaHandle(LocalLLMHandle):
|
|||||||
top_p = kwargs['top_p']
|
top_p = kwargs['top_p']
|
||||||
temperature = kwargs['temperature']
|
temperature = kwargs['temperature']
|
||||||
history = kwargs['history']
|
history = kwargs['history']
|
||||||
console_slience = kwargs.get('console_slience', True)
|
console_silence = kwargs.get('console_silence', True)
|
||||||
return query, max_length, top_p, temperature, history, console_slience
|
return query, max_length, top_p, temperature, history, console_silence
|
||||||
|
|
||||||
def convert_messages_to_prompt(query, history):
|
def convert_messages_to_prompt(query, history):
|
||||||
prompt = ""
|
prompt = ""
|
||||||
@@ -57,7 +57,7 @@ class GetLlamaHandle(LocalLLMHandle):
|
|||||||
prompt += f"\n[INST]{query}[/INST]"
|
prompt += f"\n[INST]{query}[/INST]"
|
||||||
return prompt
|
return prompt
|
||||||
|
|
||||||
query, max_length, top_p, temperature, history, console_slience = adaptor(kwargs)
|
query, max_length, top_p, temperature, history, console_silence = adaptor(kwargs)
|
||||||
prompt = convert_messages_to_prompt(query, history)
|
prompt = convert_messages_to_prompt(query, history)
|
||||||
# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-
|
# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-
|
||||||
# code from transformers.llama
|
# code from transformers.llama
|
||||||
@@ -72,9 +72,9 @@ class GetLlamaHandle(LocalLLMHandle):
|
|||||||
generated_text = ""
|
generated_text = ""
|
||||||
for new_text in streamer:
|
for new_text in streamer:
|
||||||
generated_text += new_text
|
generated_text += new_text
|
||||||
if not console_slience: print(new_text, end='')
|
if not console_silence: print(new_text, end='')
|
||||||
yield generated_text.lstrip(prompt_tk_back).rstrip("</s>")
|
yield generated_text.lstrip(prompt_tk_back).rstrip("</s>")
|
||||||
if not console_slience: print()
|
if not console_silence: print()
|
||||||
# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-
|
# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-
|
||||||
|
|
||||||
def try_to_import_special_deps(self, **kwargs):
|
def try_to_import_special_deps(self, **kwargs):
|
||||||
|
|||||||
@@ -169,7 +169,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
|
|||||||
log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_bro_result)
|
log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_bro_result)
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None,
|
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None,
|
||||||
console_slience=False):
|
console_silence=False):
|
||||||
gpt_bro_init = MoonShotInit()
|
gpt_bro_init = MoonShotInit()
|
||||||
watch_dog_patience = 60 # 看门狗的耐心, 设置10秒即可
|
watch_dog_patience = 60 # 看门狗的耐心, 设置10秒即可
|
||||||
stream_response = gpt_bro_init.generate_messages(inputs, llm_kwargs, history, sys_prompt, True)
|
stream_response = gpt_bro_init.generate_messages(inputs, llm_kwargs, history, sys_prompt, True)
|
||||||
|
|||||||
@@ -95,7 +95,7 @@ class GetGLMHandle(Process):
|
|||||||
- Its responses must not be vague, accusatory, rude, controversial, off-topic, or defensive.
|
- Its responses must not be vague, accusatory, rude, controversial, off-topic, or defensive.
|
||||||
- It should avoid giving subjective opinions but rely on objective facts or phrases like \"in this context a human might say...\", \"some people might think...\", etc.
|
- It should avoid giving subjective opinions but rely on objective facts or phrases like \"in this context a human might say...\", \"some people might think...\", etc.
|
||||||
- Its responses must also be positive, polite, interesting, entertaining, and engaging.
|
- Its responses must also be positive, polite, interesting, entertaining, and engaging.
|
||||||
- It can provide additional relevant details to answer in-depth and comprehensively covering mutiple aspects.
|
- It can provide additional relevant details to answer in-depth and comprehensively covering multiple aspects.
|
||||||
- It apologizes and accepts the user's suggestion if the user corrects the incorrect answer generated by MOSS.
|
- It apologizes and accepts the user's suggestion if the user corrects the incorrect answer generated by MOSS.
|
||||||
Capabilities and tools that MOSS can possess.
|
Capabilities and tools that MOSS can possess.
|
||||||
"""
|
"""
|
||||||
@@ -172,7 +172,7 @@ global moss_handle
|
|||||||
moss_handle = None
|
moss_handle = None
|
||||||
#################################################################################
|
#################################################################################
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
多线程方法
|
多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
|
|||||||
@@ -209,7 +209,7 @@ def predict_no_ui_long_connection(
|
|||||||
history=[],
|
history=[],
|
||||||
sys_prompt="",
|
sys_prompt="",
|
||||||
observe_window=[],
|
observe_window=[],
|
||||||
console_slience=False,
|
console_silence=False,
|
||||||
):
|
):
|
||||||
"""
|
"""
|
||||||
多线程方法
|
多线程方法
|
||||||
|
|||||||
@@ -52,7 +52,7 @@ def decode_chunk(chunk):
|
|||||||
pass
|
pass
|
||||||
return chunk_decoded, chunkjson, is_last_chunk
|
return chunk_decoded, chunkjson, is_last_chunk
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
|
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_silence=False):
|
||||||
"""
|
"""
|
||||||
发送至chatGPT,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免中途网线被掐。
|
发送至chatGPT,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免中途网线被掐。
|
||||||
inputs:
|
inputs:
|
||||||
@@ -99,7 +99,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
|
|||||||
logger.info(f'[response] {result}')
|
logger.info(f'[response] {result}')
|
||||||
break
|
break
|
||||||
result += chunkjson['message']["content"]
|
result += chunkjson['message']["content"]
|
||||||
if not console_slience: print(chunkjson['message']["content"], end='')
|
if not console_silence: print(chunkjson['message']["content"], end='')
|
||||||
if observe_window is not None:
|
if observe_window is not None:
|
||||||
# 观测窗,把已经获取的数据显示出去
|
# 观测窗,把已经获取的数据显示出去
|
||||||
if len(observe_window) >= 1:
|
if len(observe_window) >= 1:
|
||||||
@@ -124,7 +124,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
|||||||
inputs 是本次问询的输入
|
inputs 是本次问询的输入
|
||||||
top_p, temperature是chatGPT的内部调优参数
|
top_p, temperature是chatGPT的内部调优参数
|
||||||
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
||||||
chatbot 为WebUI中显示的对话列表,修改它,然后yeild出去,可以直接修改对话界面内容
|
chatbot 为WebUI中显示的对话列表,修改它,然后yield出去,可以直接修改对话界面内容
|
||||||
additional_fn代表点击的哪个按钮,按钮见functional.py
|
additional_fn代表点击的哪个按钮,按钮见functional.py
|
||||||
"""
|
"""
|
||||||
if inputs == "": inputs = "空空如也的输入栏"
|
if inputs == "": inputs = "空空如也的输入栏"
|
||||||
|
|||||||
@@ -119,7 +119,7 @@ def verify_endpoint(endpoint):
|
|||||||
raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
|
raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
|
||||||
return endpoint
|
return endpoint
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_slience:bool=False):
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
发送至chatGPT,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免中途网线被掐。
|
发送至chatGPT,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免中途网线被掐。
|
||||||
inputs:
|
inputs:
|
||||||
@@ -188,7 +188,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
|
|||||||
if (not has_content) and (not has_role): continue # raise RuntimeError("发现不标准的第三方接口:"+delta)
|
if (not has_content) and (not has_role): continue # raise RuntimeError("发现不标准的第三方接口:"+delta)
|
||||||
if has_content: # has_role = True/False
|
if has_content: # has_role = True/False
|
||||||
result += delta["content"]
|
result += delta["content"]
|
||||||
if not console_slience: print(delta["content"], end='')
|
if not console_silence: print(delta["content"], end='')
|
||||||
if observe_window is not None:
|
if observe_window is not None:
|
||||||
# 观测窗,把已经获取的数据显示出去
|
# 观测窗,把已经获取的数据显示出去
|
||||||
if len(observe_window) >= 1:
|
if len(observe_window) >= 1:
|
||||||
@@ -213,7 +213,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
|
|||||||
inputs 是本次问询的输入
|
inputs 是本次问询的输入
|
||||||
top_p, temperature是chatGPT的内部调优参数
|
top_p, temperature是chatGPT的内部调优参数
|
||||||
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
||||||
chatbot 为WebUI中显示的对话列表,修改它,然后yeild出去,可以直接修改对话界面内容
|
chatbot 为WebUI中显示的对话列表,修改它,然后yield出去,可以直接修改对话界面内容
|
||||||
additional_fn代表点击的哪个按钮,按钮见functional.py
|
additional_fn代表点击的哪个按钮,按钮见functional.py
|
||||||
"""
|
"""
|
||||||
from request_llms.bridge_all import model_info
|
from request_llms.bridge_all import model_info
|
||||||
|
|||||||
@@ -121,7 +121,7 @@ def generate_from_baidu_qianfan(inputs, llm_kwargs, history, system_prompt):
|
|||||||
|
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
⭐多线程方法
|
⭐多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
|
|||||||
@@ -1,12 +1,12 @@
|
|||||||
import time
|
import time
|
||||||
import os
|
import os
|
||||||
from toolbox import update_ui, get_conf, update_ui_lastest_msg
|
from toolbox import update_ui, get_conf, update_ui_latest_msg
|
||||||
from toolbox import check_packages, report_exception, log_chat
|
from toolbox import check_packages, report_exception, log_chat
|
||||||
|
|
||||||
model_name = 'Qwen'
|
model_name = 'Qwen'
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
⭐多线程方法
|
⭐多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
@@ -35,13 +35,13 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
|||||||
try:
|
try:
|
||||||
check_packages(["dashscope"])
|
check_packages(["dashscope"])
|
||||||
except:
|
except:
|
||||||
yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖,安装方法```pip install --upgrade dashscope```。",
|
yield from update_ui_latest_msg(f"导入软件依赖失败。使用该模型需要额外依赖,安装方法```pip install --upgrade dashscope```。",
|
||||||
chatbot=chatbot, history=history, delay=0)
|
chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
|
|
||||||
# 检查DASHSCOPE_API_KEY
|
# 检查DASHSCOPE_API_KEY
|
||||||
if get_conf("DASHSCOPE_API_KEY") == "":
|
if get_conf("DASHSCOPE_API_KEY") == "":
|
||||||
yield from update_ui_lastest_msg(f"请配置 DASHSCOPE_API_KEY。",
|
yield from update_ui_latest_msg(f"请配置 DASHSCOPE_API_KEY。",
|
||||||
chatbot=chatbot, history=history, delay=0)
|
chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
|
|
||||||
|
|||||||
@@ -1,5 +1,5 @@
|
|||||||
import time
|
import time
|
||||||
from toolbox import update_ui, get_conf, update_ui_lastest_msg
|
from toolbox import update_ui, get_conf, update_ui_latest_msg
|
||||||
from toolbox import check_packages, report_exception
|
from toolbox import check_packages, report_exception
|
||||||
|
|
||||||
model_name = '云雀大模型'
|
model_name = '云雀大模型'
|
||||||
@@ -10,7 +10,7 @@ def validate_key():
|
|||||||
return True
|
return True
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
⭐ 多线程方法
|
⭐ 多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
@@ -42,12 +42,12 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
|||||||
try:
|
try:
|
||||||
check_packages(["zhipuai"])
|
check_packages(["zhipuai"])
|
||||||
except:
|
except:
|
||||||
yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖,安装方法```pip install --upgrade zhipuai```。",
|
yield from update_ui_latest_msg(f"导入软件依赖失败。使用该模型需要额外依赖,安装方法```pip install --upgrade zhipuai```。",
|
||||||
chatbot=chatbot, history=history, delay=0)
|
chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
|
|
||||||
if validate_key() is False:
|
if validate_key() is False:
|
||||||
yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置HUOSHAN_API_KEY", chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置HUOSHAN_API_KEY", chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
|
|
||||||
if additional_fn is not None:
|
if additional_fn is not None:
|
||||||
|
|||||||
@@ -2,7 +2,7 @@
|
|||||||
import time
|
import time
|
||||||
import threading
|
import threading
|
||||||
import importlib
|
import importlib
|
||||||
from toolbox import update_ui, get_conf, update_ui_lastest_msg
|
from toolbox import update_ui, get_conf, update_ui_latest_msg
|
||||||
from multiprocessing import Process, Pipe
|
from multiprocessing import Process, Pipe
|
||||||
|
|
||||||
model_name = '星火认知大模型'
|
model_name = '星火认知大模型'
|
||||||
@@ -14,7 +14,7 @@ def validate_key():
|
|||||||
return True
|
return True
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
⭐多线程方法
|
⭐多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
@@ -43,7 +43,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
|||||||
yield from update_ui(chatbot=chatbot, history=history)
|
yield from update_ui(chatbot=chatbot, history=history)
|
||||||
|
|
||||||
if validate_key() is False:
|
if validate_key() is False:
|
||||||
yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET", chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET", chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
|
|
||||||
if additional_fn is not None:
|
if additional_fn is not None:
|
||||||
|
|||||||
@@ -225,7 +225,7 @@ def predict_no_ui_long_connection(
|
|||||||
history=[],
|
history=[],
|
||||||
sys_prompt="",
|
sys_prompt="",
|
||||||
observe_window=None,
|
observe_window=None,
|
||||||
console_slience=False,
|
console_silence=False,
|
||||||
):
|
):
|
||||||
"""
|
"""
|
||||||
多线程方法
|
多线程方法
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
import time
|
import time
|
||||||
import os
|
import os
|
||||||
from toolbox import update_ui, get_conf, update_ui_lastest_msg, log_chat
|
from toolbox import update_ui, get_conf, update_ui_latest_msg, log_chat
|
||||||
from toolbox import check_packages, report_exception, have_any_recent_upload_image_files
|
from toolbox import check_packages, report_exception, have_any_recent_upload_image_files
|
||||||
from toolbox import ChatBotWithCookies
|
from toolbox import ChatBotWithCookies
|
||||||
|
|
||||||
@@ -13,7 +13,7 @@ def validate_key():
|
|||||||
return True
|
return True
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
⭐多线程方法
|
⭐多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
@@ -49,7 +49,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
|
|||||||
yield from update_ui(chatbot=chatbot, history=history)
|
yield from update_ui(chatbot=chatbot, history=history)
|
||||||
|
|
||||||
if validate_key() is False:
|
if validate_key() is False:
|
||||||
yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
|
|
||||||
if additional_fn is not None:
|
if additional_fn is not None:
|
||||||
|
|||||||
@@ -91,7 +91,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
|||||||
inputs 是本次问询的输入
|
inputs 是本次问询的输入
|
||||||
top_p, temperature是chatGPT的内部调优参数
|
top_p, temperature是chatGPT的内部调优参数
|
||||||
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
||||||
chatbot 为WebUI中显示的对话列表,修改它,然后yeild出去,可以直接修改对话界面内容
|
chatbot 为WebUI中显示的对话列表,修改它,然后yield出去,可以直接修改对话界面内容
|
||||||
additional_fn代表点击的哪个按钮,按钮见functional.py
|
additional_fn代表点击的哪个按钮,按钮见functional.py
|
||||||
"""
|
"""
|
||||||
if additional_fn is not None:
|
if additional_fn is not None:
|
||||||
@@ -112,7 +112,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
|||||||
|
|
||||||
|
|
||||||
mutable = ["", time.time()]
|
mutable = ["", time.time()]
|
||||||
def run_coorotine(mutable):
|
def run_coroutine(mutable):
|
||||||
async def get_result(mutable):
|
async def get_result(mutable):
|
||||||
# "tgui:galactica-1.3b@localhost:7860"
|
# "tgui:galactica-1.3b@localhost:7860"
|
||||||
|
|
||||||
@@ -126,7 +126,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
|||||||
break
|
break
|
||||||
asyncio.run(get_result(mutable))
|
asyncio.run(get_result(mutable))
|
||||||
|
|
||||||
thread_listen = threading.Thread(target=run_coorotine, args=(mutable,), daemon=True)
|
thread_listen = threading.Thread(target=run_coroutine, args=(mutable,), daemon=True)
|
||||||
thread_listen.start()
|
thread_listen.start()
|
||||||
|
|
||||||
while thread_listen.is_alive():
|
while thread_listen.is_alive():
|
||||||
@@ -142,7 +142,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
|||||||
|
|
||||||
|
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience=False):
|
def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence=False):
|
||||||
raw_input = "What I would like to say is the following: " + inputs
|
raw_input = "What I would like to say is the following: " + inputs
|
||||||
prompt = raw_input
|
prompt = raw_input
|
||||||
tgui_say = ""
|
tgui_say = ""
|
||||||
@@ -151,7 +151,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
|
|||||||
addr, port = addr_port.split(':')
|
addr, port = addr_port.split(':')
|
||||||
|
|
||||||
|
|
||||||
def run_coorotine(observe_window):
|
def run_coroutine(observe_window):
|
||||||
async def get_result(observe_window):
|
async def get_result(observe_window):
|
||||||
async for response in run(context=prompt, max_token=llm_kwargs['max_length'],
|
async for response in run(context=prompt, max_token=llm_kwargs['max_length'],
|
||||||
temperature=llm_kwargs['temperature'],
|
temperature=llm_kwargs['temperature'],
|
||||||
@@ -162,6 +162,6 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
|
|||||||
print('exit when no listener')
|
print('exit when no listener')
|
||||||
break
|
break
|
||||||
asyncio.run(get_result(observe_window))
|
asyncio.run(get_result(observe_window))
|
||||||
thread_listen = threading.Thread(target=run_coorotine, args=(observe_window,))
|
thread_listen = threading.Thread(target=run_coroutine, args=(observe_window,))
|
||||||
thread_listen.start()
|
thread_listen.start()
|
||||||
return observe_window[0]
|
return observe_window[0]
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
import time
|
import time
|
||||||
import os
|
import os
|
||||||
from toolbox import update_ui, get_conf, update_ui_lastest_msg, log_chat
|
from toolbox import update_ui, get_conf, update_ui_latest_msg, log_chat
|
||||||
from toolbox import check_packages, report_exception, have_any_recent_upload_image_files
|
from toolbox import check_packages, report_exception, have_any_recent_upload_image_files
|
||||||
from toolbox import ChatBotWithCookies
|
from toolbox import ChatBotWithCookies
|
||||||
|
|
||||||
@@ -18,7 +18,7 @@ def make_media_input(inputs, image_paths):
|
|||||||
return inputs
|
return inputs
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
|
||||||
observe_window:list=[], console_slience:bool=False):
|
observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
⭐多线程方法
|
⭐多线程方法
|
||||||
函数的说明请见 request_llms/bridge_all.py
|
函数的说明请见 request_llms/bridge_all.py
|
||||||
@@ -57,12 +57,12 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
|
|||||||
try:
|
try:
|
||||||
check_packages(["zhipuai"])
|
check_packages(["zhipuai"])
|
||||||
except:
|
except:
|
||||||
yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖,安装方法```pip install --upgrade zhipuai```。",
|
yield from update_ui_latest_msg(f"导入软件依赖失败。使用该模型需要额外依赖,安装方法```pip install --upgrade zhipuai```。",
|
||||||
chatbot=chatbot, history=history, delay=0)
|
chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
|
|
||||||
if validate_key() is False:
|
if validate_key() is False:
|
||||||
yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
|
yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
|
||||||
return
|
return
|
||||||
|
|
||||||
if additional_fn is not None:
|
if additional_fn is not None:
|
||||||
|
|||||||
@@ -216,7 +216,7 @@ class LocalLLMHandle(Process):
|
|||||||
def get_local_llm_predict_fns(LLMSingletonClass, model_name, history_format='classic'):
|
def get_local_llm_predict_fns(LLMSingletonClass, model_name, history_format='classic'):
|
||||||
load_message = f"{model_name}尚未加载,加载需要一段时间。注意,取决于`config.py`的配置,{model_name}消耗大量的内存(CPU)或显存(GPU),也许会导致低配计算机卡死 ……"
|
load_message = f"{model_name}尚未加载,加载需要一段时间。注意,取决于`config.py`的配置,{model_name}消耗大量的内存(CPU)或显存(GPU),也许会导致低配计算机卡死 ……"
|
||||||
|
|
||||||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=[], console_slience:bool=False):
|
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=[], console_silence:bool=False):
|
||||||
"""
|
"""
|
||||||
refer to request_llms/bridge_all.py
|
refer to request_llms/bridge_all.py
|
||||||
"""
|
"""
|
||||||
|
|||||||
@@ -4,7 +4,7 @@ import traceback
|
|||||||
import requests
|
import requests
|
||||||
|
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
from toolbox import get_conf, is_the_upload_folder, update_ui, update_ui_lastest_msg
|
from toolbox import get_conf, is_the_upload_folder, update_ui, update_ui_latest_msg
|
||||||
|
|
||||||
proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf(
|
proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf(
|
||||||
"proxies", "TIMEOUT_SECONDS", "MAX_RETRY"
|
"proxies", "TIMEOUT_SECONDS", "MAX_RETRY"
|
||||||
@@ -350,14 +350,14 @@ def get_predict_function(
|
|||||||
chunk = next(stream_response)
|
chunk = next(stream_response)
|
||||||
except StopIteration:
|
except StopIteration:
|
||||||
if wait_counter != 0 and gpt_replying_buffer == "":
|
if wait_counter != 0 and gpt_replying_buffer == "":
|
||||||
yield from update_ui_lastest_msg(lastmsg="模型调用失败 ...", chatbot=chatbot, history=history, msg="failed")
|
yield from update_ui_latest_msg(lastmsg="模型调用失败 ...", chatbot=chatbot, history=history, msg="failed")
|
||||||
break
|
break
|
||||||
except requests.exceptions.ConnectionError:
|
except requests.exceptions.ConnectionError:
|
||||||
chunk = next(stream_response) # 失败了,重试一次?再失败就没办法了。
|
chunk = next(stream_response) # 失败了,重试一次?再失败就没办法了。
|
||||||
response_text, reasoning_content, finish_reason, decoded_chunk = decode_chunk(chunk)
|
response_text, reasoning_content, finish_reason, decoded_chunk = decode_chunk(chunk)
|
||||||
if decoded_chunk == ': keep-alive':
|
if decoded_chunk == ': keep-alive':
|
||||||
wait_counter += 1
|
wait_counter += 1
|
||||||
yield from update_ui_lastest_msg(lastmsg="等待中 " + "".join(["."] * (wait_counter%10)), chatbot=chatbot, history=history, msg="waiting ...")
|
yield from update_ui_latest_msg(lastmsg="等待中 " + "".join(["."] * (wait_counter%10)), chatbot=chatbot, history=history, msg="waiting ...")
|
||||||
continue
|
continue
|
||||||
# 返回的数据流第一次为空,继续等待
|
# 返回的数据流第一次为空,继续等待
|
||||||
if response_text == "" and (reasoning == False or reasoning_content == "") and finish_reason != "False":
|
if response_text == "" and (reasoning == False or reasoning_content == "") and finish_reason != "False":
|
||||||
|
|||||||
@@ -8,7 +8,7 @@ def is_full_width_char(ch):
|
|||||||
return True # CJK标点符号
|
return True # CJK标点符号
|
||||||
return False
|
return False
|
||||||
|
|
||||||
def scolling_visual_effect(text, scroller_max_len):
|
def scrolling_visual_effect(text, scroller_max_len):
|
||||||
text = text.\
|
text = text.\
|
||||||
replace('\n', '').replace('`', '.').replace(' ', '.').replace('<br/>', '.....').replace('$', '.')
|
replace('\n', '').replace('`', '.').replace(' ', '.').replace('<br/>', '.....').replace('$', '.')
|
||||||
place_take_cnt = 0
|
place_take_cnt = 0
|
||||||
|
|||||||
@@ -85,7 +85,7 @@ def get_chat_default_kwargs():
|
|||||||
"history": [],
|
"history": [],
|
||||||
"sys_prompt": "You are AI assistant",
|
"sys_prompt": "You are AI assistant",
|
||||||
"observe_window": None,
|
"observe_window": None,
|
||||||
"console_slience": False,
|
"console_silence": False,
|
||||||
}
|
}
|
||||||
|
|
||||||
return default_chat_kwargs
|
return default_chat_kwargs
|
||||||
|
|||||||
@@ -88,6 +88,32 @@ def zip_extract_member_new(self, member, targetpath, pwd):
|
|||||||
return targetpath
|
return targetpath
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
def safe_extract_rar(file_path, dest_dir):
|
||||||
|
import rarfile
|
||||||
|
import posixpath
|
||||||
|
with rarfile.RarFile(file_path) as rf:
|
||||||
|
os.makedirs(dest_dir, exist_ok=True)
|
||||||
|
base_path = os.path.abspath(dest_dir)
|
||||||
|
for file_info in rf.infolist():
|
||||||
|
orig_filename = file_info.filename
|
||||||
|
filename = posixpath.normpath(orig_filename).lstrip('/')
|
||||||
|
# 路径遍历防护
|
||||||
|
if '..' in filename or filename.startswith('../'):
|
||||||
|
raise Exception(f"Attempted Path Traversal in {orig_filename}")
|
||||||
|
# 符号链接防护
|
||||||
|
if hasattr(file_info, 'is_symlink') and file_info.is_symlink():
|
||||||
|
raise Exception(f"Attempted Symlink in {orig_filename}")
|
||||||
|
# 构造完整目标路径
|
||||||
|
target_path = os.path.join(base_path, filename)
|
||||||
|
final_path = os.path.normpath(target_path)
|
||||||
|
# 最终路径校验
|
||||||
|
if not final_path.startswith(base_path):
|
||||||
|
raise Exception(f"Attempted Path Traversal in {orig_filename}")
|
||||||
|
rf.extractall(dest_dir)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
def extract_archive(file_path, dest_dir):
|
def extract_archive(file_path, dest_dir):
|
||||||
import zipfile
|
import zipfile
|
||||||
import tarfile
|
import tarfile
|
||||||
@@ -132,14 +158,11 @@ def extract_archive(file_path, dest_dir):
|
|||||||
# 此外,Windows上还需要安装winrar软件,配置其Path环境变量,如"C:\Program Files\WinRAR"才可以
|
# 此外,Windows上还需要安装winrar软件,配置其Path环境变量,如"C:\Program Files\WinRAR"才可以
|
||||||
elif file_extension == ".rar":
|
elif file_extension == ".rar":
|
||||||
try:
|
try:
|
||||||
import rarfile
|
import rarfile # 用来检查rarfile是否安装,不要删除
|
||||||
|
safe_extract_rar(file_path, dest_dir)
|
||||||
with rarfile.RarFile(file_path) as rf:
|
|
||||||
rf.extractall(path=dest_dir)
|
|
||||||
logger.info("Successfully extracted rar archive to {}".format(dest_dir))
|
|
||||||
except:
|
except:
|
||||||
logger.info("Rar format requires additional dependencies to install")
|
logger.info("Rar format requires additional dependencies to install")
|
||||||
return "\n\n解压失败! 需要安装pip install rarfile来解压rar文件。建议:使用zip压缩格式。"
|
return "<br/><br/>解压失败! 需要安装pip install rarfile来解压rar文件。建议:使用zip压缩格式。"
|
||||||
|
|
||||||
# 第三方库,需要预先pip install py7zr
|
# 第三方库,需要预先pip install py7zr
|
||||||
elif file_extension == ".7z":
|
elif file_extension == ".7z":
|
||||||
@@ -151,7 +174,7 @@ def extract_archive(file_path, dest_dir):
|
|||||||
logger.info("Successfully extracted 7z archive to {}".format(dest_dir))
|
logger.info("Successfully extracted 7z archive to {}".format(dest_dir))
|
||||||
except:
|
except:
|
||||||
logger.info("7z format requires additional dependencies to install")
|
logger.info("7z format requires additional dependencies to install")
|
||||||
return "\n\n解压失败! 需要安装pip install py7zr来解压7z文件"
|
return "<br/><br/>解压失败! 需要安装pip install py7zr来解压7z文件"
|
||||||
else:
|
else:
|
||||||
return ""
|
return ""
|
||||||
return ""
|
return ""
|
||||||
|
|||||||
@@ -45,28 +45,161 @@ Any folded content here. It requires an empty line just above it.
|
|||||||
|
|
||||||
md ="""
|
md ="""
|
||||||
|
|
||||||
在这种场景中,您希望机器 B 能够通过轮询机制来间接地“请求”机器 A,而实际上机器 A 只能主动向机器 B 发出请求。这是一种典型的客户端-服务器轮询模式。下面是如何实现这种机制的详细步骤:
|
<details>
|
||||||
|
<summary>第0份搜索结果 [源自google搜索] (汤姆·赫兰德):</summary>
|
||||||
|
<div class="search_result">https://baike.baidu.com/item/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7/3687216</div>
|
||||||
|
<div class="search_result">Title: 汤姆·赫兰德
|
||||||
|
|
||||||
### 机器 B 的实现
|
URL Source: https://baike.baidu.com/item/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7/3687216
|
||||||
|
|
||||||
1. **安装 FastAPI 和必要的依赖库**:
|
Markdown Content:
|
||||||
```bash
|
网页新闻贴吧知道网盘图片视频地图文库资讯采购百科
|
||||||
pip install fastapi uvicorn
|
百度首页
|
||||||
```
|
登录
|
||||||
|
注册
|
||||||
|
进入词条
|
||||||
|
全站搜索
|
||||||
|
帮助
|
||||||
|
首页
|
||||||
|
秒懂百科
|
||||||
|
特色百科
|
||||||
|
知识专题
|
||||||
|
加入百科
|
||||||
|
百科团队
|
||||||
|
权威合作
|
||||||
|
个人中心
|
||||||
|
汤姆·赫兰德
|
||||||
|
播报
|
||||||
|
讨论
|
||||||
|
上传视频
|
||||||
|
英国男演员
|
||||||
|
汤姆·赫兰德(Tom Holland),1996年6月1日出生于英国英格兰泰晤士河畔金斯顿,英国男演员。2008年,出演音乐剧《跳出我天地》而崭露头角。2010年,作为主演参加音乐剧《跳出我天地》的五周年特别演出。2012年10月11日,主演的个人首部电影《海啸奇迹》上映,并凭该电影获得第84届美国国家评论协会奖最具突破男演员奖。2016年10月15日,与查理·汉纳姆、西耶娜·米勒合作出演的电影《 ... >>>
|
||||||
|
|
||||||
2. **创建 FastAPI 服务**:
|
目录
|
||||||
```python
|
1早年经历
|
||||||
from fastapi import FastAPI
|
2演艺经历
|
||||||
from fastapi.responses import JSONResponse
|
▪影坛新星
|
||||||
from uuid import uuid4
|
▪角色多变
|
||||||
from threading import Lock
|
▪跨界翘楚
|
||||||
import time
|
3个人生活
|
||||||
|
▪家庭
|
||||||
|
▪恋情
|
||||||
|
▪社交
|
||||||
|
4主要作品
|
||||||
|
▪参演电影
|
||||||
|
▪参演电视剧
|
||||||
|
▪配音作品
|
||||||
|
▪导演作品
|
||||||
|
▪杂志写真
|
||||||
|
5社会活动
|
||||||
|
6获奖记录
|
||||||
|
7人物评价
|
||||||
|
基本信息
|
||||||
|
汤姆·赫兰德(Tom Holland),1996年6月1日出生于英国英格兰泰晤士河畔金斯顿,英国男演员。 [67]
|
||||||
|
2008年,出演音乐剧《跳出我天地》而崭露头角 [1]。2010年,作为主演参加音乐剧《跳出我天地》的五周年特别演出 [2]。2012年10月11日,主演的个人首部电影《海啸奇迹》上映,并凭该电影获得第84届美国国家评论协会奖最具突破男演员奖 [3]。2016年10月15日,与查理·汉纳姆、西耶娜·米勒合作出演的电影《迷失Z城》在纽约电影节首映 [17];2017年,主演的《蜘蛛侠:英雄归来》上映,他凭该电影获得第19届青少年选择奖最佳暑期电影男演员奖,以及第70届英国电影和电视艺术学院奖最佳新星奖。 [72]2019年,主演的电影《蜘蛛侠:英雄远征》上映 [5];同年,凭借该电影获得第21届青少年选择奖最佳夏日电影男演员奖 [6]。2024年4月,汤姆·霍兰德主演的伦敦西区新版舞台剧《罗密欧与朱丽叶》公布演员名单。 [66]
|
||||||
|
2024年,......</div>
|
||||||
|
</details>
|
||||||
|
|
||||||
app = FastAPI()
|
<details>
|
||||||
|
<summary>第1份搜索结果 [源自google搜索] (汤姆·霍兰德):</summary>
|
||||||
|
<div class="search_result">https://zh.wikipedia.org/zh-hans/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7</div>
|
||||||
|
<div class="search_result">Title: 汤姆·赫兰德
|
||||||
|
|
||||||
# 字典用于存储请求和状态
|
URL Source: https://zh.wikipedia.org/zh-hans/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7
|
||||||
requests = {}
|
|
||||||
process_lock = Lock()
|
Published Time: 2015-06-24T01:08:01Z
|
||||||
|
|
||||||
|
Markdown Content:
|
||||||
|
| 汤姆·霍兰德
|
||||||
|
Tom Holland |
|
||||||
|
| --- |
|
||||||
|
| [](https://zh.wikipedia.org/wiki/File:Tom_Holland_by_Gage_Skidmore.jpg)
|
||||||
|
|
||||||
|
2016年在[圣地牙哥国际漫画展](https://zh.wikipedia.org/wiki/%E8%81%96%E5%9C%B0%E7%89%99%E5%93%A5%E5%9C%8B%E9%9A%9B%E6%BC%AB%E7%95%AB%E5%B1%95 "圣地牙哥国际漫画展")的霍兰德
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
|
||||||
|
| 男演员 |
|
||||||
|
| 昵称 | 荷兰弟[\[1\]](https://zh.wikipedia.org/zh-hans/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7#cite_note-1) |
|
||||||
|
| 出生 | 汤玛斯·史丹利·霍兰德
|
||||||
|
(Thomas Stanley Holland)[\[2\]](https://zh.wikipedia.org/zh-hans/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7#cite_note-2)
|
||||||
|
|
||||||
|
|
||||||
|
1996年6月1日(28岁)
|
||||||
|
|
||||||
|
英国[英格兰](https://zh.wikipedia.org/wiki/%E8%8B%B1%E6%A0%BC%E8%98%AD "英格兰")[泰晤士河畔金斯顿](https://zh.wikipedia.org/wiki/%E6%B3%B0%E6%99%A4......</div>
|
||||||
|
</details>
|
||||||
|
|
||||||
|
<details>
|
||||||
|
<summary>第2份搜索结果 [源自google搜索] (为什么汤姆赫兰德被称为荷兰弟?):</summary>
|
||||||
|
<div class="search_result">https://www.zhihu.com/question/363988307</div>
|
||||||
|
<div class="search_result">Title: 为什么汤姆赫兰德被称为荷兰弟? - 知乎
|
||||||
|
|
||||||
|
URL Source: https://www.zhihu.com/question/363988307
|
||||||
|
|
||||||
|
Markdown Content:
|
||||||
|
要说漫威演员里面,谁是最牛的存在,不好说,各有各的看法,但要说谁是最能剧透的,毫无疑问,是我们的汤姆赫兰德荷兰弟,可以说,他算得上是把剧透给玩明白了,先后剧透了不少的电影桥段,以至于漫威后面像防贼一样防着人家荷兰弟,可大家知道吗?你永远想象不到荷兰弟的嘴巴到底有多能漏风?
|
||||||
|
|
||||||
|

|
||||||
|
|
||||||
|
故事要回到《侏罗纪世界2》的筹备期间,当时,荷兰弟也参与了面试,计划在剧中饰演一个角色,原本,这也没啥,这都是好莱坞的传统了,可是,当时的导演胡安根本不知道荷兰弟的“风光伟绩”,于是乎,人家便屁颠屁颠把侏罗纪世界2的资料拿过来给荷兰弟,虽然,后面没有让荷兰弟出演这部电影,但导演似乎忘了他的嘴巴是开过光的。
|
||||||
|
|
||||||
|

|
||||||
|
|
||||||
|
荷兰弟把剧情刻在了脑子
|
||||||
|
......</div>
|
||||||
|
</details>
|
||||||
|
|
||||||
|
<details>
|
||||||
|
<summary>第3份搜索结果 [源自google搜索] (爱戴名表被喷配不上赞达亚,荷兰弟曝近照气质大变,2):</summary>
|
||||||
|
<div class="search_result">https://www.sohu.com/a/580380519_120702487</div>
|
||||||
|
<div class="search_result">Title: 爱戴名表被喷配不上赞达亚,荷兰弟曝近照气质大变,26岁资产惊人_蜘蛛侠_手表_罗伯特·唐尼
|
||||||
|
|
||||||
|
URL Source: https://www.sohu.com/a/580380519_120702487
|
||||||
|
|
||||||
|
Markdown Content:
|
||||||
|
2022-08-27 19:00 来源: [BEGEEL宾爵表](https://www.sohu.com/a/580380519_120702487?spm=smpc.content-abroad.content.1.1739375950559fBhgNpP)
|
||||||
|
|
||||||
|
发布于:广东省
|
||||||
|
|
||||||
|
近日,大家熟悉的荷兰弟,也就演漫威超级英雄“蜘蛛侠”而走红的英国男星汤姆·赫兰德(Tom Holland),最近在没有任何预警的情况下宣布自己暂停使用社交媒体,原因网络暴力已经严重影响到他的心理健康了。虽然自出演蜘蛛侠以来,对荷兰弟的骂声就没停过,但不可否认他确实是一位才貌双全的好演员,同时也是一位拥有高雅品味的地道英伦绅士,从他近年名表收藏的趋势也能略知一二。
|
||||||
|
|
||||||
|

|
||||||
|
|
||||||
|
2016年,《美国队长3:内战》上映,汤姆·赫兰德扮演的“史上最嫩”蜘蛛侠也正式登场。这个美国普通学生,由于意外被一只受过放射性感染的蜘蛛咬到,并因此获得超能力,化身邻居英雄蜘蛛侠警恶惩奸。和蜘蛛侠彼得·帕克一样,当时年仅20岁的荷兰弟无论戏里戏外的穿搭都是少年感十足,走的阳光邻家大男孩路线,手上戴的最多的就是来自卡西欧的电子表,还有来自Nixon sentry的手表,千元级别甚至是百元级。
|
||||||
|
|
||||||
|
20岁的荷兰弟走的是邻家大男孩路线
|
||||||
|
|
||||||
|

|
||||||
|
|
||||||
|
随着荷兰弟主演的《蜘蛛侠:英雄归来》上演,第三代蜘蛛侠的话痨性格和年轻活力的形象瞬间圈粉无数。荷兰弟的知名度和演艺收入都大幅度增长,他的穿衣品味也渐渐从稚嫩少年风转变成轻熟绅士风。从简单的T恤短袖搭配牛仔裤,开始向更加丰富的造型发展,其中变化最明显的就是他手腕上的表。
|
||||||
|
|
||||||
|
荷兰弟的衣品日......</div>
|
||||||
|
</details>
|
||||||
|
|
||||||
|
<details>
|
||||||
|
<summary>第4份搜索结果 [源自google搜索] (荷兰弟居然要休息一年,因演戏演到精神分裂…):</summary>
|
||||||
|
<div class="search_result">https://www.sohu.com/a/683718058_544020</div>
|
||||||
|
<div class="search_result">Title: 荷兰弟居然要休息一年,因演戏演到精神分裂…_Holland_Tom_工作
|
||||||
|
|
||||||
|
URL Source: https://www.sohu.com/a/683718058_544020
|
||||||
|
|
||||||
|
Markdown Content:
|
||||||
|
荷兰弟居然要休息一年,因演戏演到精神分裂…\_Holland\_Tom\_工作
|
||||||
|
===============
|
||||||
|
|
||||||
|
* [](http://www.sohu.com/?spm=smpc.content-abroad.nav.1.1739375954055TcEvWsY)
|
||||||
|
* [新闻](http://news.sohu.com/?spm=smpc.content-abroad.nav.2.1739375954055TcEvWsY)
|
||||||
|
* [体育](http://sports.sohu.com/?spm=smpc.content-abroad.nav.3.1739375954055TcEvWsY)
|
||||||
|
* [汽车](http://auto.sohu.com/?spm=smpc.content-abroad.nav.4.1739375954055TcEvWsY)
|
||||||
|
* [房产](http://www.focus.cn/?spm=smpc.content-abroad.nav.5.1739375954055TcEvWsY)
|
||||||
|
* [旅游](http://travel.sohu.com/?spm=smpc.content-abroad.nav.6.1739375954055TcEvWsY)
|
||||||
|
* [教育](http://learning.sohu.com/?spm=smpc.content-abroad.nav.7.1739375954055TcEvWsY)
|
||||||
|
* [时尚](http://fashion.sohu.com/?spm=smpc.content-abroad.nav.8.1739375954055TcEvWsY)
|
||||||
|
* [科技](http://it.sohu.com/?spm=smpc.content-abroad.nav.9.1739375954055TcEvWsY)
|
||||||
|
* [财经](http://business.sohu.com/?spm=smpc.content-abroad.nav.10.17393759......</div>
|
||||||
|
</details>
|
||||||
|
|
||||||
"""
|
"""
|
||||||
def validate_path():
|
def validate_path():
|
||||||
|
|||||||
@@ -48,8 +48,6 @@ if __name__ == "__main__":
|
|||||||
|
|
||||||
# plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695")
|
# plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695")
|
||||||
|
|
||||||
# plugin_test(plugin='crazy_functions.联网的ChatGPT->连接网络回答问题', main_input="谁是应急食品?")
|
|
||||||
|
|
||||||
# plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples")
|
# plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples")
|
||||||
|
|
||||||
# plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.")
|
# plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.")
|
||||||
|
|||||||
@@ -48,8 +48,6 @@ if __name__ == "__main__":
|
|||||||
|
|
||||||
# plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695")
|
# plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695")
|
||||||
|
|
||||||
# plugin_test(plugin='crazy_functions.联网的ChatGPT->连接网络回答问题', main_input="谁是应急食品?")
|
|
||||||
|
|
||||||
# plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples")
|
# plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples")
|
||||||
|
|
||||||
# plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.")
|
# plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.")
|
||||||
|
|||||||
@@ -9,7 +9,7 @@ from textwrap import dedent
|
|||||||
# TODO: 解决缩进问题
|
# TODO: 解决缩进问题
|
||||||
|
|
||||||
find_function_end_prompt = '''
|
find_function_end_prompt = '''
|
||||||
Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to sperate functions, class functions etc.
|
Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to separate functions, class functions etc.
|
||||||
- Provide the line number where the first visible function ends.
|
- Provide the line number where the first visible function ends.
|
||||||
- Provide the line number where the next visible function begins.
|
- Provide the line number where the next visible function begins.
|
||||||
- If there are no other functions in this page, you should simply return the line number of the last line.
|
- If there are no other functions in this page, you should simply return the line number of the last line.
|
||||||
@@ -58,7 +58,7 @@ OUTPUT:
|
|||||||
|
|
||||||
|
|
||||||
|
|
||||||
revise_funtion_prompt = '''
|
revise_function_prompt = '''
|
||||||
You need to read the following code, and revise the code according to following instructions:
|
You need to read the following code, and revise the code according to following instructions:
|
||||||
1. You should analyze the purpose of the functions (if there are any).
|
1. You should analyze the purpose of the functions (if there are any).
|
||||||
2. You need to add docstring for the provided functions (if there are any).
|
2. You need to add docstring for the provided functions (if there are any).
|
||||||
@@ -147,7 +147,7 @@ class ContextWindowManager():
|
|||||||
history=[],
|
history=[],
|
||||||
sys_prompt="",
|
sys_prompt="",
|
||||||
observe_window=[],
|
observe_window=[],
|
||||||
console_slience=True
|
console_silence=True
|
||||||
)
|
)
|
||||||
|
|
||||||
def extract_number(text):
|
def extract_number(text):
|
||||||
@@ -240,15 +240,15 @@ class ContextWindowManager():
|
|||||||
def tag_code(self, fn):
|
def tag_code(self, fn):
|
||||||
code = ''.join(fn)
|
code = ''.join(fn)
|
||||||
_, n_indent = self.dedent(code)
|
_, n_indent = self.dedent(code)
|
||||||
indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preseve them in the OUTPUT.)"
|
indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preserve them in the OUTPUT.)"
|
||||||
self.llm_kwargs['temperature'] = 0
|
self.llm_kwargs['temperature'] = 0
|
||||||
result = predict_no_ui_long_connection(
|
result = predict_no_ui_long_connection(
|
||||||
inputs=revise_funtion_prompt.format(THE_CODE=code, INDENT_REMINDER=indent_reminder),
|
inputs=revise_function_prompt.format(THE_CODE=code, INDENT_REMINDER=indent_reminder),
|
||||||
llm_kwargs=self.llm_kwargs,
|
llm_kwargs=self.llm_kwargs,
|
||||||
history=[],
|
history=[],
|
||||||
sys_prompt="",
|
sys_prompt="",
|
||||||
observe_window=[],
|
observe_window=[],
|
||||||
console_slience=True
|
console_silence=True
|
||||||
)
|
)
|
||||||
|
|
||||||
def get_code_block(reply):
|
def get_code_block(reply):
|
||||||
|
|||||||
@@ -323,3 +323,12 @@
|
|||||||
opacity: 0.8;
|
opacity: 0.8;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
.search_result {
|
||||||
|
font-size: smaller;
|
||||||
|
font-style: italic;
|
||||||
|
margin: 0px;
|
||||||
|
padding: 1em;
|
||||||
|
line-height: 1.5;
|
||||||
|
text-wrap: wrap;
|
||||||
|
opacity: 0.8;
|
||||||
|
}
|
||||||
|
|||||||
@@ -598,7 +598,7 @@ function(t) {
|
|||||||
default.VIEW_LOGICAL_MAX_BOTTOM, w.
|
default.VIEW_LOGICAL_MAX_BOTTOM, w.
|
||||||
default.VIEW_LOGICAL_MAX_TOP), B.setMaxScale(w.
|
default.VIEW_LOGICAL_MAX_TOP), B.setMaxScale(w.
|
||||||
default.VIEW_MAX_SCALE), B.setMinScale(w.
|
default.VIEW_MAX_SCALE), B.setMinScale(w.
|
||||||
default.VIEW_MIN_SCALE), U = new M.L2DMatrix44, U.multScale(1, i / e), G = new M.L2DMatrix44, G.multTranslate(-i / 2, -e / 2), G.multScale(2 / i, -2 / i), F = v(), (0, D.setContext)(F), !F) return console.error("Failed to create WebGL context."), void(window.WebGLRenderingContext && console.error("Your browser don't support WebGL, check https://get.webgl.org/ for futher information."));
|
default.VIEW_MIN_SCALE), U = new M.L2DMatrix44, U.multScale(1, i / e), G = new M.L2DMatrix44, G.multTranslate(-i / 2, -e / 2), G.multScale(2 / i, -2 / i), F = v(), (0, D.setContext)(F), !F) return console.error("Failed to create WebGL context."), void(window.WebGLRenderingContext && console.error("Your browser don't support WebGL, check https://get.webgl.org/ for further information."));
|
||||||
window.Live2D.setGL(F), F.clearColor(0, 0, 0, 0), a(t), s()
|
window.Live2D.setGL(F), F.clearColor(0, 0, 0, 0), a(t), s()
|
||||||
}
|
}
|
||||||
function s() {
|
function s() {
|
||||||
|
|||||||
@@ -183,7 +183,7 @@ def update_ui(chatbot:ChatBotWithCookies, history:list, msg:str="正常", **kwar
|
|||||||
yield cookies, chatbot_gr, json_history, msg
|
yield cookies, chatbot_gr, json_history, msg
|
||||||
|
|
||||||
|
|
||||||
def update_ui_lastest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list, delay:float=1, msg:str="正常"): # 刷新界面
|
def update_ui_latest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list, delay:float=1, msg:str="正常"): # 刷新界面
|
||||||
"""
|
"""
|
||||||
刷新用户界面
|
刷新用户界面
|
||||||
"""
|
"""
|
||||||
@@ -679,7 +679,7 @@ def run_gradio_in_subpath(demo, auth, port, custom_path):
|
|||||||
return True
|
return True
|
||||||
if len(path) == 0:
|
if len(path) == 0:
|
||||||
logger.info(
|
logger.info(
|
||||||
"ilegal custom path: {}\npath must not be empty\ndeploy on root url".format(
|
"illegal custom path: {}\npath must not be empty\ndeploy on root url".format(
|
||||||
path
|
path
|
||||||
)
|
)
|
||||||
)
|
)
|
||||||
@@ -690,14 +690,14 @@ def run_gradio_in_subpath(demo, auth, port, custom_path):
|
|||||||
return True
|
return True
|
||||||
return False
|
return False
|
||||||
logger.info(
|
logger.info(
|
||||||
"ilegal custom path: {}\npath should begin with '/'\ndeploy on root url".format(
|
"illegal custom path: {}\npath should begin with '/'\ndeploy on root url".format(
|
||||||
path
|
path
|
||||||
)
|
)
|
||||||
)
|
)
|
||||||
return False
|
return False
|
||||||
|
|
||||||
if not is_path_legal(custom_path):
|
if not is_path_legal(custom_path):
|
||||||
raise RuntimeError("Ilegal custom path")
|
raise RuntimeError("Illegal custom path")
|
||||||
import uvicorn
|
import uvicorn
|
||||||
import gradio as gr
|
import gradio as gr
|
||||||
from fastapi import FastAPI
|
from fastapi import FastAPI
|
||||||
|
|||||||
Reference in New Issue
Block a user