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29 Commits

Author SHA1 Message Date
Your Name
e7b73f3041 update readme 2023-04-24 00:43:57 +08:00
Your Name
ed8db8c8ae README 2023-04-23 23:49:55 +08:00
Your Name
df97213d3b version 3.3 2023-04-23 23:43:07 +08:00
Your Name
97443d1f83 移除依赖 2023-04-23 23:40:18 +08:00
Your Name
59bed52faf 修改依赖的引用方式 2023-04-23 23:39:54 +08:00
Your Name
3814c3a915 修改依赖 2023-04-23 23:36:55 +08:00
Your Name
d98d0a291e 移动函数位置 2023-04-23 23:34:13 +08:00
Your Name
ee94fa6dc4 拆分成两个文件 2023-04-23 23:32:35 +08:00
Your Name
d2e46f6684 更新提示 2023-04-23 23:26:23 +08:00
Your Name
5948dcacd5 加线程锁 2023-04-23 23:25:49 +08:00
Your Name
3041858e7f 优化提示 2023-04-23 23:16:25 +08:00
Your Name
9c2a6bc413 优化错误提示 2023-04-23 23:13:00 +08:00
Your Name
1cf8b6c6c8 修复细节 2023-04-23 22:47:45 +08:00
Your Name
781ef4487c 修复一些细节 2023-04-23 22:44:18 +08:00
Your Name
4a494354b1 显示newbing回复的网址 2023-04-23 22:34:24 +08:00
Your Name
385c775aa5 支持3.10以下的python版本使用newbing 2023-04-23 20:54:57 +08:00
binary-husky
518385dea2 add newbing, testing 2023-04-23 19:17:09 +08:00
binary-husky
4d1eea7bd5 更新说明 2023-04-23 18:40:58 +08:00
binary-husky
9cb51ccc70 restore default model 2023-04-23 18:38:05 +08:00
binary-husky
94dc398163 restore default model 2023-04-23 18:37:15 +08:00
binary-husky
65317e33af Merge branch 'newbing' into v3.3 2023-04-23 18:35:21 +08:00
binary-husky
06fbdf43af 更正部分注释 2023-04-23 18:34:16 +08:00
binary-husky
ab61418410 better traceback 2023-04-23 18:13:30 +08:00
binary-husky
0785ff2aed 微调对话裁剪 2023-04-23 17:45:56 +08:00
binary-husky
676fe40d39 优化chatgpt对话的截断策略 2023-04-23 17:32:44 +08:00
binary-husky
0b89673ee9 Merge pull request #571 from codycjy/notebook_args
feat(jupyter): use args to disable Markdown parse
2023-04-23 11:24:41 +08:00
binary-husky
2f4e050612 Update README.md 2023-04-23 11:22:35 +08:00
binary-husky
2b96217f2b 实现Newbing聊天功能 2023-04-22 21:18:35 +08:00
saltfish
13342c2988 feat(jupter): use args to disable Markdown parse 2023-04-22 21:11:24 +08:00
13 changed files with 827 additions and 41 deletions

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@@ -20,24 +20,25 @@ If you like this project, please give it a Star. If you've come up with more use
--- | ---
一键润色 | 支持一键润色、一键查找论文语法错误
一键中英互译 | 一键中英互译
一键代码解释 | 可以正确显示代码、解释代码
一键代码解释 | 显示代码、解释代码、生成代码、给代码加注释
[自定义快捷键](https://www.bilibili.com/video/BV14s4y1E7jN) | 支持自定义快捷键
[配置代理服务器](https://www.bilibili.com/video/BV1rc411W7Dr) | 支持配置代理服务器
模块化设计 | 支持自定义高阶的函数插件与[函数插件],插件支持[热更新](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
[自我程序剖析](https://www.bilibili.com/video/BV1cj411A7VW) | [函数插件] [一键读懂](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A)本项目的源代码
[程序剖析](https://www.bilibili.com/video/BV1cj411A7VW) | [函数插件] 一键可以剖析其他Python/C/C++/Java/Lua/...项目树
读论文 | [函数插件] 一键解读latex论文全文并生成摘要
读论文、翻译论文 | [函数插件] 一键解读latex/pdf论文全文并生成摘要
Latex全文翻译、润色 | [函数插件] 一键翻译或润色latex论文
批量注释生成 | [函数插件] 一键批量生成函数注释
chat分析报告生成 | [函数插件] 运行后自动生成总结汇报
生成GPT分析报告 | [函数插件] 运行后自动生成总结汇报支持一键导出html格式对话记录
Markdown中英互译 | [函数插件] 看到上面5种语言的[README](https://github.com/binary-husky/chatgpt_academic/blob/master/docs/README_EN.md)了吗?
[arxiv小助手](https://www.bilibili.com/video/BV1LM4y1279X) | [函数插件] 输入arxiv文章url即可一键翻译摘要+下载PDF
[PDF论文全文翻译功能](https://www.bilibili.com/video/BV1KT411x7Wn) | [函数插件] PDF论文提取题目&摘要+翻译全文(多线程)
[谷歌学术统合小助手](https://www.bilibili.com/video/BV19L411U7ia) | [函数插件] 给定任意谷歌学术搜索页面URLgpt帮你选择有趣的文章
[谷歌学术统合小助手](https://www.bilibili.com/video/BV19L411U7ia) | [函数插件] 给定任意谷歌学术搜索页面URLGPT帮你写Related Works
互联网信息聚合+GPT | [函数插件] 一键让ChatGPT先Google搜索再回答问题信息流永不过时
公式/图片/表格显示 | 可以同时显示公式的tex形式和渲染形式支持公式、代码高亮
多线程函数插件支持 | 支持多线调用chatgpt一键处理海量文本或程序
启动暗色gradio[主题](https://github.com/binary-husky/chatgpt_academic/issues/173) | 在浏览器url后面添加```/?__dark-theme=true```可以切换dark主题
[多LLM模型](https://www.bilibili.com/video/BV1wT411p7yf)支持,[API2D](https://api2d.com/)接口支持 | 同时被GPT3.5、GPT4和[清华ChatGLM](https://github.com/THUDM/ChatGLM-6B)伺候的感觉一定会很不错吧?
更多LLM模型接入 | 新加入Newbing测试接口(新必应AI)
huggingface免科学上网[在线体验](https://huggingface.co/spaces/qingxu98/gpt-academic) | 登陆huggingface后复制[此空间](https://huggingface.co/spaces/qingxu98/gpt-academic)
…… | ……
@@ -277,7 +278,8 @@ docker run --rm -it --net=host --gpus=all gpt-academic bash
## Todo 与 版本规划:
- version 3.2+ (todo): 函数插件支持更多参数接口
- version 3.3+ (todo): NewBing支持
- version 3.2: 函数插件支持更多参数接口 (保存对话功能, 解读任意语言代码+同时询问任意的LLM组合)
- version 3.1: 支持同时问询多个gpt模型支持api2d支持多个apikey负载均衡
- version 3.0: 对chatglm和其他小型llm的支持
- version 2.6: 重构了插件结构,提高了交互性,加入更多插件

View File

@@ -45,7 +45,7 @@ MAX_RETRY = 2
# OpenAI模型选择是gpt4现在只对申请成功的人开放体验gpt-4可以试试api2d
LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm"]
AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "newbing"]
# 本地LLM模型如ChatGLM的执行方式 CPU/GPU
LOCAL_MODEL_DEVICE = "cpu" # 可选 "cuda"
@@ -58,8 +58,14 @@ CONCURRENT_COUNT = 100
AUTHENTICATION = []
# 重新URL重新定向实现更换API_URL的作用常规情况下不要修改!!
# 格式 {"https://api.openai.com/v1/chat/completions": "重定向的URL"}
# 格式 {"https://api.openai.com/v1/chat/completions": "在这里填写重定向的api.openai.com的URL"}
API_URL_REDIRECT = {}
# 如果需要在二级路径下运行(常规情况下,不要修改!!需要配合修改main.py才能生效!
CUSTOM_PATH = "/"
# 如果需要使用newbing把newbing的长长的cookie放到这里
NEWBING_STYLE = "creative" # ["creative", "balanced", "precise"]
NEWBING_COOKIES = """
your bing cookies here
"""

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@@ -35,6 +35,8 @@ def get_crazy_functions():
"Color": "stop",
"AsButton":False,
"Function": HotReload(解析ipynb文件),
"AdvancedArgs": True, # 调用时唤起高级参数输入区默认False
"ArgsReminder": "若输入0则不解析notebook中的Markdown块", # 高级参数输入区的显示提示
},
"批量总结Word文档": {
"Color": "stop",

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@@ -1,5 +1,4 @@
import traceback
from toolbox import update_ui, get_conf
from toolbox import update_ui, get_conf, trimmed_format_exc
def input_clipping(inputs, history, max_token_limit):
import numpy as np
@@ -94,12 +93,12 @@ def request_gpt_model_in_new_thread_with_ui_alive(
continue # 返回重试
else:
# 【选择放弃】
tb_str = '```\n' + traceback.format_exc() + '```'
tb_str = '```\n' + trimmed_format_exc() + '```'
mutable[0] += f"[Local Message] 警告,在执行过程中遭遇问题, Traceback\n\n{tb_str}\n\n"
return mutable[0] # 放弃
except:
# 【第三种情况】:其他错误:重试几次
tb_str = '```\n' + traceback.format_exc() + '```'
tb_str = '```\n' + trimmed_format_exc() + '```'
print(tb_str)
mutable[0] += f"[Local Message] 警告,在执行过程中遭遇问题, Traceback\n\n{tb_str}\n\n"
if retry_op > 0:
@@ -220,14 +219,14 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
continue # 返回重试
else:
# 【选择放弃】
tb_str = '```\n' + traceback.format_exc() + '```'
tb_str = '```\n' + trimmed_format_exc() + '```'
gpt_say += f"[Local Message] 警告,线程{index}在执行过程中遭遇问题, Traceback\n\n{tb_str}\n\n"
if len(mutable[index][0]) > 0: gpt_say += "此线程失败前收到的回答:\n\n" + mutable[index][0]
mutable[index][2] = "输入过长已放弃"
return gpt_say # 放弃
except:
# 【第三种情况】:其他错误
tb_str = '```\n' + traceback.format_exc() + '```'
tb_str = '```\n' + trimmed_format_exc() + '```'
print(tb_str)
gpt_say += f"[Local Message] 警告,线程{index}在执行过程中遭遇问题, Traceback\n\n{tb_str}\n\n"
if len(mutable[index][0]) > 0: gpt_say += "此线程失败前收到的回答:\n\n" + mutable[index][0]

View File

@@ -67,11 +67,16 @@ def parseNotebook(filename, enable_markdown=1):
def ipynb解释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
enable_markdown = plugin_kwargs.get("advanced_arg", "1")
try:
enable_markdown = int(enable_markdown)
except ValueError:
enable_markdown = 1
pfg = PaperFileGroup()
print(file_manifest)
for fp in file_manifest:
file_content = parseNotebook(fp, enable_markdown=1)
file_content = parseNotebook(fp, enable_markdown=enable_markdown)
pfg.file_paths.append(fp)
pfg.file_contents.append(file_content)

View File

@@ -98,7 +98,8 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
history.extend([ "第一批", gpt_say ])
meta_paper_info_list = meta_paper_info_list[10:]
chatbot.append(["状态?", "已经全部完成"])
chatbot.append(["状态?",
"已经全部完成您可以试试让AI写一个Related Works例如您可以继续输入Write a \"Related Works\" section about \"你搜索的研究领域\" for me."])
msg = '正常'
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
res = write_results_to_file(history)

View File

@@ -11,7 +11,7 @@
import tiktoken
from functools import lru_cache
from concurrent.futures import ThreadPoolExecutor
from toolbox import get_conf
from toolbox import get_conf, trimmed_format_exc
from .bridge_chatgpt import predict_no_ui_long_connection as chatgpt_noui
from .bridge_chatgpt import predict as chatgpt_ui
@@ -19,6 +19,9 @@ from .bridge_chatgpt import predict as chatgpt_ui
from .bridge_chatglm import predict_no_ui_long_connection as chatglm_noui
from .bridge_chatglm import predict as chatglm_ui
from .bridge_newbing import predict_no_ui_long_connection as newbing_noui
from .bridge_newbing import predict as newbing_ui
# from .bridge_tgui import predict_no_ui_long_connection as tgui_noui
# from .bridge_tgui import predict as tgui_ui
@@ -48,6 +51,7 @@ class LazyloadTiktoken(object):
API_URL_REDIRECT, = get_conf("API_URL_REDIRECT")
openai_endpoint = "https://api.openai.com/v1/chat/completions"
api2d_endpoint = "https://openai.api2d.net/v1/chat/completions"
newbing_endpoint = "wss://sydney.bing.com/sydney/ChatHub"
# 兼容旧版的配置
try:
API_URL, = get_conf("API_URL")
@@ -59,6 +63,7 @@ except:
# 新版配置
if openai_endpoint in API_URL_REDIRECT: openai_endpoint = API_URL_REDIRECT[openai_endpoint]
if api2d_endpoint in API_URL_REDIRECT: api2d_endpoint = API_URL_REDIRECT[api2d_endpoint]
if newbing_endpoint in API_URL_REDIRECT: newbing_endpoint = API_URL_REDIRECT[newbing_endpoint]
# 获取tokenizer
@@ -116,7 +121,15 @@ model_info = {
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
# newbing
"newbing": {
"fn_with_ui": newbing_ui,
"fn_without_ui": newbing_noui,
"endpoint": newbing_endpoint,
"max_token": 4096,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
}
@@ -128,10 +141,7 @@ def LLM_CATCH_EXCEPTION(f):
try:
return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
except Exception as e:
from toolbox import get_conf
import traceback
proxies, = get_conf('proxies')
tb_str = '\n```\n' + traceback.format_exc() + '\n```\n'
tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
observe_window[0] = tb_str
return tb_str
return decorated
@@ -182,7 +192,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
def mutex_manager(window_mutex, observe_window):
while True:
time.sleep(0.5)
time.sleep(0.25)
if not window_mutex[-1]: break
# 看门狗watchdog
for i in range(n_model):

View File

@@ -21,7 +21,7 @@ import importlib
# config_private.py放自己的秘密如API和代理网址
# 读取时首先看是否存在私密的config_private配置文件不受git管控如果有则覆盖原config文件
from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys
from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc
proxies, API_KEY, TIMEOUT_SECONDS, MAX_RETRY = \
get_conf('proxies', 'API_KEY', 'TIMEOUT_SECONDS', 'MAX_RETRY')
@@ -145,7 +145,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
yield from update_ui(chatbot=chatbot, history=history, msg="api-key不满足要求") # 刷新界面
return
history.append(inputs); history.append(" ")
history.append(inputs); history.append("")
retry = 0
while True:
@@ -198,21 +198,24 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
chunk_decoded = chunk.decode()
error_msg = chunk_decoded
if "reduce the length" in error_msg:
chatbot[-1] = (chatbot[-1][0], "[Local Message] Reduce the length. 本次输入过长,或历史数据过长. 历史缓存数据现已释放,您可以请再次尝试.")
history = [] # 清除历史
if len(history) >= 2: history[-1] = ""; history[-2] = "" # 清除当前溢出的输入history[-2] 是本次输入, history[-1] 是本次输出
history = clip_history(inputs=inputs, history=history, tokenizer=model_info[llm_kwargs['llm_model']]['tokenizer'],
max_token_limit=(model_info[llm_kwargs['llm_model']]['max_token'])) # history至少释放二分之一
chatbot[-1] = (chatbot[-1][0], "[Local Message] Reduce the length. 本次输入过长, 或历史数据过长. 历史缓存数据已部分释放, 您可以请再次尝试. (若再次失败则更可能是因为输入过长.)")
# history = [] # 清除历史
elif "does not exist" in error_msg:
chatbot[-1] = (chatbot[-1][0], f"[Local Message] Model {llm_kwargs['llm_model']} does not exist. 模型不存在或者您没有获得体验资格.")
chatbot[-1] = (chatbot[-1][0], f"[Local Message] Model {llm_kwargs['llm_model']} does not exist. 模型不存在, 或者您没有获得体验资格.")
elif "Incorrect API key" in error_msg:
chatbot[-1] = (chatbot[-1][0], "[Local Message] Incorrect API key. OpenAI以提供了不正确的API_KEY为由拒绝服务.")
chatbot[-1] = (chatbot[-1][0], "[Local Message] Incorrect API key. OpenAI以提供了不正确的API_KEY为由, 拒绝服务.")
elif "exceeded your current quota" in error_msg:
chatbot[-1] = (chatbot[-1][0], "[Local Message] You exceeded your current quota. OpenAI以账户额度不足为由拒绝服务.")
chatbot[-1] = (chatbot[-1][0], "[Local Message] You exceeded your current quota. OpenAI以账户额度不足为由, 拒绝服务.")
elif "bad forward key" in error_msg:
chatbot[-1] = (chatbot[-1][0], "[Local Message] Bad forward key. API2D账户额度不足.")
elif "Not enough point" in error_msg:
chatbot[-1] = (chatbot[-1][0], "[Local Message] Not enough point. API2D账户点数不足.")
else:
from toolbox import regular_txt_to_markdown
tb_str = '```\n' + traceback.format_exc() + '```'
tb_str = '```\n' + trimmed_format_exc() + '```'
chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk_decoded[4:])}")
yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面
return

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@@ -0,0 +1,249 @@
"""
========================================================================
第一部分来自EdgeGPT.py
https://github.com/acheong08/EdgeGPT
========================================================================
"""
from .edge_gpt import NewbingChatbot
load_message = "等待NewBing响应。"
"""
========================================================================
第二部分子进程Worker调用主体
========================================================================
"""
import time
import json
import re
import asyncio
import importlib
import threading
from toolbox import update_ui, get_conf, trimmed_format_exc
from multiprocessing import Process, Pipe
def preprocess_newbing_out(s):
pattern = r'\^(\d+)\^' # 匹配^数字^
sub = lambda m: '\['+m.group(1)+'\]' # 将匹配到的数字作为替换值
result = re.sub(pattern, sub, s) # 替换操作
if '[1]' in result:
result += '\n\n```\n' + "\n".join([r for r in result.split('\n') if r.startswith('[')]) + '\n```\n'
return result
def preprocess_newbing_out_simple(result):
if '[1]' in result:
result += '\n\n```\n' + "\n".join([r for r in result.split('\n') if r.startswith('[')]) + '\n```\n'
return result
class NewBingHandle(Process):
def __init__(self):
super().__init__(daemon=True)
self.parent, self.child = Pipe()
self.newbing_model = None
self.info = ""
self.success = True
self.local_history = []
self.check_dependency()
self.start()
self.threadLock = threading.Lock()
def check_dependency(self):
try:
self.success = False
import certifi, httpx, rich
self.info = "依赖检测通过等待NewBing响应。注意目前不能多人同时调用NewBing接口有线程锁否则将导致每个人的NewBing问询历史互相渗透。调用NewBing时会自动使用已配置的代理。"
self.success = True
except:
self.info = "缺少的依赖如果要使用Newbing除了基础的pip依赖以外您还需要运行`pip install -r request_llm/requirements_newbing.txt`安装Newbing的依赖。"
self.success = False
def ready(self):
return self.newbing_model is not None
async def async_run(self):
# 读取配置
NEWBING_STYLE, = get_conf('NEWBING_STYLE')
from request_llm.bridge_all import model_info
endpoint = model_info['newbing']['endpoint']
while True:
# 等待
kwargs = self.child.recv()
question=kwargs['query']
history=kwargs['history']
system_prompt=kwargs['system_prompt']
# 是否重置
if len(self.local_history) > 0 and len(history)==0:
await self.newbing_model.reset()
self.local_history = []
# 开始问问题
prompt = ""
if system_prompt not in self.local_history:
self.local_history.append(system_prompt)
prompt += system_prompt + '\n'
# 追加历史
for ab in history:
a, b = ab
if a not in self.local_history:
self.local_history.append(a)
prompt += a + '\n'
if b not in self.local_history:
self.local_history.append(b)
prompt += b + '\n'
# 问题
prompt += question
self.local_history.append(question)
# 提交
async for final, response in self.newbing_model.ask_stream(
prompt=question,
conversation_style=NEWBING_STYLE, # ["creative", "balanced", "precise"]
wss_link=endpoint, # "wss://sydney.bing.com/sydney/ChatHub"
):
if not final:
print(response)
self.child.send(str(response))
else:
print('-------- receive final ---------')
self.child.send('[Finish]')
def run(self):
"""
这个函数运行在子进程
"""
# 第一次运行,加载参数
self.success = False
self.local_history = []
if (self.newbing_model is None) or (not self.success):
# 代理设置
proxies, = get_conf('proxies')
if proxies is None:
self.proxies_https = None
else:
self.proxies_https = proxies['https']
# cookie
NEWBING_COOKIES, = get_conf('NEWBING_COOKIES')
try:
cookies = json.loads(NEWBING_COOKIES)
except:
self.success = False
tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
self.child.send(f'[Local Message] 不能加载Newbing组件。NEWBING_COOKIES未填写或有格式错误。')
self.child.send('[Fail]')
self.child.send('[Finish]')
raise RuntimeError(f"不能加载Newbing组件。NEWBING_COOKIES未填写或有格式错误。")
try:
self.newbing_model = NewbingChatbot(proxy=self.proxies_https, cookies=cookies)
except:
self.success = False
tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
self.child.send(f'[Local Message] 不能加载Newbing组件。{tb_str}')
self.child.send('[Fail]')
self.child.send('[Finish]')
raise RuntimeError(f"不能加载Newbing组件。")
self.success = True
try:
# 进入任务等待状态
asyncio.run(self.async_run())
except Exception:
tb_str = '```\n' + trimmed_format_exc() + '```'
self.child.send(f'[Local Message] Newbing失败 {tb_str}.')
self.child.send('[Fail]')
self.child.send('[Finish]')
def stream_chat(self, **kwargs):
"""
这个函数运行在主进程
"""
self.threadLock.acquire()
self.parent.send(kwargs) # 发送请求到子进程
while True:
res = self.parent.recv() # 等待newbing回复的片段
if res == '[Finish]':
break # 结束
elif res == '[Fail]':
self.success = False
break
else:
yield res # newbing回复的片段
self.threadLock.release()
"""
========================================================================
第三部分:主进程统一调用函数接口
========================================================================
"""
global newbing_handle
newbing_handle = None
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
"""
多线程方法
函数的说明请见 request_llm/bridge_all.py
"""
global newbing_handle
if (newbing_handle is None) or (not newbing_handle.success):
newbing_handle = NewBingHandle()
observe_window[0] = load_message + "\n\n" + newbing_handle.info
if not newbing_handle.success:
error = newbing_handle.info
newbing_handle = None
raise RuntimeError(error)
# 没有 sys_prompt 接口因此把prompt加入 history
history_feedin = []
for i in range(len(history)//2):
history_feedin.append([history[2*i], history[2*i+1]] )
watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
response = ""
observe_window[0] = "[Local Message]: 等待NewBing响应中 ..."
for response in newbing_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=sys_prompt, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
observe_window[0] = preprocess_newbing_out_simple(response)
if len(observe_window) >= 2:
if (time.time()-observe_window[1]) > watch_dog_patience:
raise RuntimeError("程序终止。")
return preprocess_newbing_out_simple(response)
def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
"""
单线程方法
函数的说明请见 request_llm/bridge_all.py
"""
chatbot.append((inputs, "[Local Message]: 等待NewBing响应中 ..."))
global newbing_handle
if (newbing_handle is None) or (not newbing_handle.success):
newbing_handle = NewBingHandle()
chatbot[-1] = (inputs, load_message + "\n\n" + newbing_handle.info)
yield from update_ui(chatbot=chatbot, history=[])
if not newbing_handle.success:
newbing_handle = None
return
if additional_fn is not None:
import core_functional
importlib.reload(core_functional) # 热更新prompt
core_functional = core_functional.get_core_functions()
if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs) # 获取预处理函数(如果有的话)
inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
history_feedin = []
for i in range(len(history)//2):
history_feedin.append([history[2*i], history[2*i+1]] )
chatbot[-1] = (inputs, "[Local Message]: 等待NewBing响应中 ...")
yield from update_ui(chatbot=chatbot, history=history, msg="NewBing响应缓慢尚未完成全部响应请耐心完成后再提交新问题。")
for response in newbing_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=system_prompt, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
chatbot[-1] = (inputs, preprocess_newbing_out(response))
yield from update_ui(chatbot=chatbot, history=history, msg="NewBing响应缓慢尚未完成全部响应请耐心完成后再提交新问题。")
history.extend([inputs, preprocess_newbing_out(response)])
yield from update_ui(chatbot=chatbot, history=history, msg="完成全部响应,请提交新问题。")

409
request_llm/edge_gpt.py Normal file
View File

@@ -0,0 +1,409 @@
"""
========================================================================
第一部分来自EdgeGPT.py
https://github.com/acheong08/EdgeGPT
========================================================================
"""
import argparse
import asyncio
import json
import os
import random
import re
import ssl
import sys
import uuid
from enum import Enum
from typing import Generator
from typing import Literal
from typing import Optional
from typing import Union
import websockets.client as websockets
DELIMITER = "\x1e"
# Generate random IP between range 13.104.0.0/14
FORWARDED_IP = (
f"13.{random.randint(104, 107)}.{random.randint(0, 255)}.{random.randint(0, 255)}"
)
HEADERS = {
"accept": "application/json",
"accept-language": "en-US,en;q=0.9",
"content-type": "application/json",
"sec-ch-ua": '"Not_A Brand";v="99", "Microsoft Edge";v="110", "Chromium";v="110"',
"sec-ch-ua-arch": '"x86"',
"sec-ch-ua-bitness": '"64"',
"sec-ch-ua-full-version": '"109.0.1518.78"',
"sec-ch-ua-full-version-list": '"Chromium";v="110.0.5481.192", "Not A(Brand";v="24.0.0.0", "Microsoft Edge";v="110.0.1587.69"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-model": "",
"sec-ch-ua-platform": '"Windows"',
"sec-ch-ua-platform-version": '"15.0.0"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-origin",
"x-ms-client-request-id": str(uuid.uuid4()),
"x-ms-useragent": "azsdk-js-api-client-factory/1.0.0-beta.1 core-rest-pipeline/1.10.0 OS/Win32",
"Referer": "https://www.bing.com/search?q=Bing+AI&showconv=1&FORM=hpcodx",
"Referrer-Policy": "origin-when-cross-origin",
"x-forwarded-for": FORWARDED_IP,
}
HEADERS_INIT_CONVER = {
"authority": "edgeservices.bing.com",
"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
"accept-language": "en-US,en;q=0.9",
"cache-control": "max-age=0",
"sec-ch-ua": '"Chromium";v="110", "Not A(Brand";v="24", "Microsoft Edge";v="110"',
"sec-ch-ua-arch": '"x86"',
"sec-ch-ua-bitness": '"64"',
"sec-ch-ua-full-version": '"110.0.1587.69"',
"sec-ch-ua-full-version-list": '"Chromium";v="110.0.5481.192", "Not A(Brand";v="24.0.0.0", "Microsoft Edge";v="110.0.1587.69"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-model": '""',
"sec-ch-ua-platform": '"Windows"',
"sec-ch-ua-platform-version": '"15.0.0"',
"sec-fetch-dest": "document",
"sec-fetch-mode": "navigate",
"sec-fetch-site": "none",
"sec-fetch-user": "?1",
"upgrade-insecure-requests": "1",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36 Edg/110.0.1587.69",
"x-edge-shopping-flag": "1",
"x-forwarded-for": FORWARDED_IP,
}
def get_ssl_context():
import certifi
ssl_context = ssl.create_default_context()
ssl_context.load_verify_locations(certifi.where())
return ssl_context
class NotAllowedToAccess(Exception):
pass
class ConversationStyle(Enum):
creative = "h3imaginative,clgalileo,gencontentv3"
balanced = "galileo"
precise = "h3precise,clgalileo"
CONVERSATION_STYLE_TYPE = Optional[
Union[ConversationStyle, Literal["creative", "balanced", "precise"]]
]
def _append_identifier(msg: dict) -> str:
"""
Appends special character to end of message to identify end of message
"""
# Convert dict to json string
return json.dumps(msg) + DELIMITER
def _get_ran_hex(length: int = 32) -> str:
"""
Returns random hex string
"""
return "".join(random.choice("0123456789abcdef") for _ in range(length))
class _ChatHubRequest:
"""
Request object for ChatHub
"""
def __init__(
self,
conversation_signature: str,
client_id: str,
conversation_id: str,
invocation_id: int = 0,
) -> None:
self.struct: dict = {}
self.client_id: str = client_id
self.conversation_id: str = conversation_id
self.conversation_signature: str = conversation_signature
self.invocation_id: int = invocation_id
def update(
self,
prompt,
conversation_style,
options,
) -> None:
"""
Updates request object
"""
if options is None:
options = [
"deepleo",
"enable_debug_commands",
"disable_emoji_spoken_text",
"enablemm",
]
if conversation_style:
if not isinstance(conversation_style, ConversationStyle):
conversation_style = getattr(ConversationStyle, conversation_style)
options = [
"nlu_direct_response_filter",
"deepleo",
"disable_emoji_spoken_text",
"responsible_ai_policy_235",
"enablemm",
conversation_style.value,
"dtappid",
"cricinfo",
"cricinfov2",
"dv3sugg",
]
self.struct = {
"arguments": [
{
"source": "cib",
"optionsSets": options,
"sliceIds": [
"222dtappid",
"225cricinfo",
"224locals0",
],
"traceId": _get_ran_hex(32),
"isStartOfSession": self.invocation_id == 0,
"message": {
"author": "user",
"inputMethod": "Keyboard",
"text": prompt,
"messageType": "Chat",
},
"conversationSignature": self.conversation_signature,
"participant": {
"id": self.client_id,
},
"conversationId": self.conversation_id,
},
],
"invocationId": str(self.invocation_id),
"target": "chat",
"type": 4,
}
self.invocation_id += 1
class _Conversation:
"""
Conversation API
"""
def __init__(
self,
cookies,
proxy,
) -> None:
self.struct: dict = {
"conversationId": None,
"clientId": None,
"conversationSignature": None,
"result": {"value": "Success", "message": None},
}
import httpx
self.proxy = proxy
proxy = (
proxy
or os.environ.get("all_proxy")
or os.environ.get("ALL_PROXY")
or os.environ.get("https_proxy")
or os.environ.get("HTTPS_PROXY")
or None
)
if proxy is not None and proxy.startswith("socks5h://"):
proxy = "socks5://" + proxy[len("socks5h://") :]
self.session = httpx.Client(
proxies=proxy,
timeout=30,
headers=HEADERS_INIT_CONVER,
)
for cookie in cookies:
self.session.cookies.set(cookie["name"], cookie["value"])
# Send GET request
response = self.session.get(
url=os.environ.get("BING_PROXY_URL")
or "https://edgeservices.bing.com/edgesvc/turing/conversation/create",
)
if response.status_code != 200:
response = self.session.get(
"https://edge.churchless.tech/edgesvc/turing/conversation/create",
)
if response.status_code != 200:
print(f"Status code: {response.status_code}")
print(response.text)
print(response.url)
raise Exception("Authentication failed")
try:
self.struct = response.json()
except (json.decoder.JSONDecodeError, NotAllowedToAccess) as exc:
raise Exception(
"Authentication failed. You have not been accepted into the beta.",
) from exc
if self.struct["result"]["value"] == "UnauthorizedRequest":
raise NotAllowedToAccess(self.struct["result"]["message"])
class _ChatHub:
"""
Chat API
"""
def __init__(self, conversation) -> None:
self.wss = None
self.request: _ChatHubRequest
self.loop: bool
self.task: asyncio.Task
print(conversation.struct)
self.request = _ChatHubRequest(
conversation_signature=conversation.struct["conversationSignature"],
client_id=conversation.struct["clientId"],
conversation_id=conversation.struct["conversationId"],
)
async def ask_stream(
self,
prompt: str,
wss_link: str,
conversation_style: CONVERSATION_STYLE_TYPE = None,
raw: bool = False,
options: dict = None,
) -> Generator[str, None, None]:
"""
Ask a question to the bot
"""
if self.wss and not self.wss.closed:
await self.wss.close()
# Check if websocket is closed
self.wss = await websockets.connect(
wss_link,
extra_headers=HEADERS,
max_size=None,
ssl=get_ssl_context()
)
await self._initial_handshake()
# Construct a ChatHub request
self.request.update(
prompt=prompt,
conversation_style=conversation_style,
options=options,
)
# Send request
await self.wss.send(_append_identifier(self.request.struct))
final = False
while not final:
objects = str(await self.wss.recv()).split(DELIMITER)
for obj in objects:
if obj is None or not obj:
continue
response = json.loads(obj)
if response.get("type") != 2 and raw:
yield False, response
elif response.get("type") == 1 and response["arguments"][0].get(
"messages",
):
resp_txt = response["arguments"][0]["messages"][0]["adaptiveCards"][
0
]["body"][0].get("text")
yield False, resp_txt
elif response.get("type") == 2:
final = True
yield True, response
async def _initial_handshake(self) -> None:
await self.wss.send(_append_identifier({"protocol": "json", "version": 1}))
await self.wss.recv()
async def close(self) -> None:
"""
Close the connection
"""
if self.wss and not self.wss.closed:
await self.wss.close()
class NewbingChatbot:
"""
Combines everything to make it seamless
"""
def __init__(
self,
cookies,
proxy
) -> None:
if cookies is None:
cookies = {}
self.cookies = cookies
self.proxy = proxy
self.chat_hub: _ChatHub = _ChatHub(
_Conversation(self.cookies, self.proxy),
)
async def ask(
self,
prompt: str,
wss_link: str,
conversation_style: CONVERSATION_STYLE_TYPE = None,
options: dict = None,
) -> dict:
"""
Ask a question to the bot
"""
async for final, response in self.chat_hub.ask_stream(
prompt=prompt,
conversation_style=conversation_style,
wss_link=wss_link,
options=options,
):
if final:
return response
await self.chat_hub.wss.close()
return None
async def ask_stream(
self,
prompt: str,
wss_link: str,
conversation_style: CONVERSATION_STYLE_TYPE = None,
raw: bool = False,
options: dict = None,
) -> Generator[str, None, None]:
"""
Ask a question to the bot
"""
async for response in self.chat_hub.ask_stream(
prompt=prompt,
conversation_style=conversation_style,
wss_link=wss_link,
raw=raw,
options=options,
):
yield response
async def close(self) -> None:
"""
Close the connection
"""
await self.chat_hub.close()
async def reset(self) -> None:
"""
Reset the conversation
"""
await self.close()
self.chat_hub = _ChatHub(_Conversation(self.cookies, self.proxy))

View File

@@ -0,0 +1,8 @@
BingImageCreator
certifi
httpx
prompt_toolkit
requests
rich
websockets
httpx[socks]

View File

@@ -5,7 +5,20 @@ import inspect
import re
from latex2mathml.converter import convert as tex2mathml
from functools import wraps, lru_cache
############################### 插件输入输出接驳区 #######################################
"""
========================================================================
第一部分
函数插件输入输出接驳区
- ChatBotWithCookies: 带Cookies的Chatbot类为实现更多强大的功能做基础
- ArgsGeneralWrapper: 装饰器函数,用于重组输入参数,改变输入参数的顺序与结构
- update_ui: 刷新界面用 yield from update_ui(chatbot, history)
- CatchException: 将插件中出的所有问题显示在界面上
- HotReload: 实现插件的热更新
- trimmed_format_exc: 打印traceback为了安全而隐藏绝对地址
========================================================================
"""
class ChatBotWithCookies(list):
def __init__(self, cookie):
self._cookies = cookie
@@ -20,6 +33,7 @@ class ChatBotWithCookies(list):
def get_cookies(self):
return self._cookies
def ArgsGeneralWrapper(f):
"""
装饰器函数,用于重组输入参数,改变输入参数的顺序与结构。
@@ -47,6 +61,7 @@ def ArgsGeneralWrapper(f):
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
return decorated
def update_ui(chatbot, history, msg='正常', **kwargs): # 刷新界面
"""
刷新用户界面
@@ -54,10 +69,18 @@ def update_ui(chatbot, history, msg='正常', **kwargs): # 刷新界面
assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时可用clear将其清空然后用for+append循环重新赋值。"
yield chatbot.get_cookies(), chatbot, history, msg
def trimmed_format_exc():
import os, traceback
str = traceback.format_exc()
current_path = os.getcwd()
replace_path = "."
return str.replace(current_path, replace_path)
def CatchException(f):
"""
装饰器函数捕捉函数f中的异常并封装到一个生成器中返回并显示到聊天当中。
"""
@wraps(f)
def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
try:
@@ -66,7 +89,7 @@ def CatchException(f):
from check_proxy import check_proxy
from toolbox import get_conf
proxies, = get_conf('proxies')
tb_str = '```\n' + traceback.format_exc() + '```'
tb_str = '```\n' + trimmed_format_exc() + '```'
if chatbot is None or len(chatbot) == 0:
chatbot = [["插件调度异常", "异常原因"]]
chatbot[-1] = (chatbot[-1][0],
@@ -93,7 +116,23 @@ def HotReload(f):
return decorated
####################################### 其他小工具 #####################################
"""
========================================================================
第二部分
其他小工具:
- write_results_to_file: 将结果写入markdown文件中
- regular_txt_to_markdown: 将普通文本转换为Markdown格式的文本。
- report_execption: 向chatbot中添加简单的意外错误信息
- text_divide_paragraph: 将文本按照段落分隔符分割开生成带有段落标签的HTML代码。
- markdown_convertion: 用多种方式组合将markdown转化为好看的html
- format_io: 接管gradio默认的markdown处理方式
- on_file_uploaded: 处理文件的上传(自动解压)
- on_report_generated: 将生成的报告自动投射到文件上传区
- clip_history: 当历史上下文过长时,自动截断
- get_conf: 获取设置
- select_api_key: 根据当前的模型类别抽取可用的api-key
========================================================================
"""
def get_reduce_token_percent(text):
"""
@@ -113,7 +152,6 @@ def get_reduce_token_percent(text):
return 0.5, '不详'
def write_results_to_file(history, file_name=None):
"""
将对话记录history以Markdown格式写入文件中。如果没有指定文件名则使用当前时间生成文件名。
@@ -369,6 +407,9 @@ def find_recent_files(directory):
def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
"""
当文件被上传时的回调函数
"""
if len(files) == 0:
return chatbot, txt
import shutil
@@ -388,8 +429,7 @@ def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
shutil.copy(file.name, f'private_upload/{time_tag}/{file_origin_name}')
err_msg += extract_archive(f'private_upload/{time_tag}/{file_origin_name}',
dest_dir=f'private_upload/{time_tag}/{file_origin_name}.extract')
moved_files = [fp for fp in glob.glob(
'private_upload/**/*', recursive=True)]
moved_files = [fp for fp in glob.glob('private_upload/**/*', recursive=True)]
if "底部输入区" in checkboxes:
txt = ""
txt2 = f'private_upload/{time_tag}'
@@ -508,7 +548,7 @@ def clear_line_break(txt):
class DummyWith():
"""
这段代码定义了一个名为DummyWith的空上下文管理器
它的作用是……额……用,即在代码结构不变得情况下取代其他的上下文管理器。
它的作用是……额……就是不起作用,即在代码结构不变得情况下取代其他的上下文管理器。
上下文管理器是一种Python对象用于与with语句一起使用
以确保一些资源在代码块执行期间得到正确的初始化和清理。
上下文管理器必须实现两个方法,分别为 __enter__()和 __exit__()。
@@ -522,6 +562,9 @@ class DummyWith():
return
def run_gradio_in_subpath(demo, auth, port, custom_path):
"""
把gradio的运行地址更改到指定的二次路径上
"""
def is_path_legal(path: str)->bool:
'''
check path for sub url
@@ -551,3 +594,52 @@ def run_gradio_in_subpath(demo, auth, port, custom_path):
return {"message": f"Gradio is running at: {custom_path}"}
app = gr.mount_gradio_app(app, demo, path=custom_path)
uvicorn.run(app, host="0.0.0.0", port=port) # , auth=auth
def clip_history(inputs, history, tokenizer, max_token_limit):
"""
reduce the length of history by clipping.
this function search for the longest entries to clip, little by little,
until the number of token of history is reduced under threshold.
通过裁剪来缩短历史记录的长度。
此函数逐渐地搜索最长的条目进行剪辑,
直到历史记录的标记数量降低到阈值以下。
"""
import numpy as np
from request_llm.bridge_all import model_info
def get_token_num(txt):
return len(tokenizer.encode(txt, disallowed_special=()))
input_token_num = get_token_num(inputs)
if input_token_num < max_token_limit * 3 / 4:
# 当输入部分的token占比小于限制的3/4时裁剪时
# 1. 把input的余量留出来
max_token_limit = max_token_limit - input_token_num
# 2. 把输出用的余量留出来
max_token_limit = max_token_limit - 128
# 3. 如果余量太小了,直接清除历史
if max_token_limit < 128:
history = []
return history
else:
# 当输入部分的token占比 > 限制的3/4时直接清除历史
history = []
return history
everything = ['']
everything.extend(history)
n_token = get_token_num('\n'.join(everything))
everything_token = [get_token_num(e) for e in everything]
# 截断时的颗粒度
delta = max(everything_token) // 16
while n_token > max_token_limit:
where = np.argmax(everything_token)
encoded = tokenizer.encode(everything[where], disallowed_special=())
clipped_encoded = encoded[:len(encoded)-delta]
everything[where] = tokenizer.decode(clipped_encoded)[:-1] # -1 to remove the may-be illegal char
everything_token[where] = get_token_num(everything[where])
n_token = get_token_num('\n'.join(everything))
history = everything[1:]
return history

View File

@@ -1,5 +1,5 @@
{
"version": 3.2,
"version": 3.3,
"show_feature": true,
"new_feature": "保存对话功能 <-> 解读任意语言代码+同时询问任意的LLM组合 <-> 添加联网Google回答问题插件 <-> 修复ChatGLM上下文BUG <-> 添加支持清华ChatGLM和GPT-4 <-> 改进架构支持与多个LLM模型同时对话 <-> 添加支持API2D国内可支持gpt4"
"new_feature": "支持NewBing !! <-> 保存对话功能 <-> 解读任意语言代码+同时询问任意的LLM组合 <-> 添加联网Google回答问题插件 <-> 修复ChatGLM上下文BUG <-> 添加支持清华ChatGLM和GPT-4 <-> 改进架构支持与多个LLM模型同时对话 <-> 添加支持API2D国内可支持gpt4"
}