22 Commits
Author SHA1 Message Date
chunzhi b20f43b2a8 Update main.py 2023-04-05 12:26:03 +08:00
Your Name ee7494c0b7 处理没有文件返回的问题 2023-04-05 02:15:47 +08:00
qingxu fu dcdc8351e7 BUG FIX 2023-04-05 01:58:34 +08:00
binary-husky a239abac50 Update version 2023-04-04 22:34:28 +08:00
binary-husky 1042d28e1f Update version 2023-04-04 22:20:39 +08:00
binary-husky 7b75422c26 Update version 2023-04-04 22:20:21 +08:00
binary-husky 99817e9040 Update version 2023-04-04 22:17:47 +08:00
qingxu fu c9fa26405d 规划版本号 2023-04-04 21:38:20 +08:00
binary-husky 005232afa6 Update issue templates 2023-04-04 17:13:40 +08:00
binary-husky 5b8cc5a899 Update README.md 2023-04-04 15:33:53 +08:00
qingxu fu a4137e7170 修复代码英文重构Bug 2023-04-04 15:23:42 +08:00
qingxu fu aaf44750d9 默认暗色护眼主题 2023-04-03 20:56:00 +08:00
binary-husky bd6eb90449 Merge pull request #290 from LiZheGuang/master
fix: 🐛 修复react解析项目不显示在下拉列表的问题
2023-04-03 17:58:28 +08:00
LiZheGuang b5a48369a4 fix: 🐛 修复react解析项目不显示在下拉列表的问题 2023-04-03 17:44:09 +08:00
binary-husky 6b5bdbe98a Update issue templates 2023-04-03 17:00:51 +08:00
qingxu fu 69624c66d7 update README 2023-04-03 09:32:01 +08:00
binary-husky 69be335d22 Update README.md 2023-04-03 01:49:40 +08:00
binary-husky bb1e410cb4 Update README.md 2023-04-03 01:47:49 +08:00
binary-husky 9ccc53fa96 Update README.md 2023-04-03 01:39:17 +08:00
binary-husky 4b83486b3d Update README.md 2023-04-03 01:38:44 +08:00
binary-husky 417c8325de Update README.md 2023-04-03 01:03:00 +08:00
binary-husky d51ae6abb2 Update README.md 2023-04-03 01:01:57 +08:00
27 changed files with 272 additions and 278 deletions
+19
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@@ -0,0 +1,19 @@
---
name: Bug report
about: Create a report to help us improve
title: ''
labels: ''
assignees: ''
---
**Describe the bug 简述**
**Screen Shot 截图**
**Terminal Traceback 终端traceback(如果有)**
Before submitting an issue 提交issue之前:
- Please try to upgrade your code. 如果您的代码不是最新的,建议您先尝试更新代码
- Please check project wiki for common problem solutions.项目[wiki](https://github.com/binary-husky/chatgpt_academic/wiki)有一些常见问题的解决方法
+10
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@@ -0,0 +1,10 @@
---
name: Feature request
about: Suggest an idea for this project
title: ''
labels: ''
assignees: ''
---
+2 -1
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@@ -139,4 +139,5 @@ config_private.py
gpt_log
private.md
private_upload
other_llms
other_llms
cradle.py
+21 -4
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@@ -46,6 +46,8 @@ arxiv小助手 | [函数插件] 输入arxiv文章url即可一键翻译摘要+下
图片显示 | 可以在markdown中显示图片
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
支持GPT输出的markdown表格 | 可以输出支持GPT的markdown表格
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
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)
…… | ……
</div>
@@ -113,7 +115,7 @@ python -m pip install -r requirements.txt
# (选择二.2conda activate gptac_venv
# (选择二.3python -m pip install -r requirements.txt
# 备注:使用官方pip源或者阿里pip源,其他pip源(如清华pip)有可能出问题,临时换源方法:
# 备注:使用官方pip源或者阿里pip源,其他pip源(如一些大学的pip)有可能出问题,临时换源方法:
# python -m pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
```
@@ -255,9 +257,24 @@ python check_proxy.py
<img src="https://user-images.githubusercontent.com/96192199/227504931-19955f78-45cd-4d1c-adac-e71e50957915.png" height="400" >
</div>
## Todo:
- (Top Priority) 调用另一个开源项目text-generation-webui的web接口,使用其他llm模型
- 总结大工程源代码时,文本过长、token溢出的问题(目前的方法是直接二分丢弃处理溢出,过于粗暴,有效信息大量丢失)
### 源代码转译英文
<div align="center">
<img src="https://user-images.githubusercontent.com/96192199/229720562-fe6c3508-6142-4635-a83d-21eb3669baee.png" height="400" >
</div>
## Todo 与 版本规划:
- version 3 (Todo):
- - 支持gpt4和其他更多llm
- version 2.3+ (Todo):
- - 总结大工程源代码时文本过长、token溢出的问题
- - 实现项目打包部署
- - 函数插件参数接口优化
- - 自更新
- version 2.3: 增强多线程交互性
- version 2.2: 函数插件支持热重载
- version 2.1: 可折叠式布局
- version 2.0: 引入模块化函数插件
- version 1.0: 基础功能
-150
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@@ -1,150 +0,0 @@
import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
import gradio as gr
from predict import predict
from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf
# 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT = \
get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT')
# 如果WEB_PORT是-1, 则随机选取WEB端口
PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
if not AUTHENTICATION: AUTHENTICATION = None
initial_prompt = "Serve me as a writing and programming assistant."
title_html = "<h1 align=\"center\">ChatGPT 学术优化</h1>"
description = """代码开源和更新[地址🚀](https://github.com/binary-husky/chatgpt_academic),感谢热情的[开发者们❤️](https://github.com/binary-husky/chatgpt_academic/graphs/contributors)"""
# 问询记录, python 版本建议3.9+(越新越好)
import logging
os.makedirs("gpt_log", exist_ok=True)
try:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO, encoding="utf-8")
except:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO)
print("所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log, 请注意自我隐私保护哦!")
# 一些普通功能模块
from functional import get_functionals
functional = get_functionals()
# 高级函数插件
from functional_crazy import get_crazy_functionals
crazy_fns = get_crazy_functionals()
# 处理markdown文本格式的转变
gr.Chatbot.postprocess = format_io
# 做一些外观色彩上的调整
from theme import adjust_theme, advanced_css
set_theme = adjust_theme()
cancel_handles = []
with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
gr.HTML(title_html)
# To add a Duplicate Space badge
gr.HTML('''<center><a href="https://huggingface.co/spaces/qingxu98/gpt-academic?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>请您打开此页面后务必点击上方的“复制空间”(Duplicate Space)按钮!<br/>切忌在“复制空间”(Duplicate Space)之前填入API_KEY或进行提问,否则您的API_KEY将极可能被空间所有者攫取!</center>''')
with gr.Row().style(equal_height=True):
with gr.Column(scale=2):
chatbot = gr.Chatbot()
chatbot.style(height=CHATBOT_HEIGHT)
history = gr.State([])
with gr.Column(scale=1):
with gr.Row():
api_key = gr.Textbox(show_label=False, placeholder="输入API_KEY,输入后自动生效.").style(container=False)
with gr.Row():
txt = gr.Textbox(show_label=False, placeholder="输入问题.").style(container=False)
with gr.Row():
submitBtn = gr.Button("提交", variant="primary")
with gr.Row():
resetBtn = gr.Button("重置", variant="secondary"); resetBtn.style(size="sm")
stopBtn = gr.Button("停止", variant="secondary"); stopBtn.style(size="sm")
with gr.Row():
from check_proxy import check_proxy
status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {check_proxy(proxies)}")
with gr.Accordion("基础功能区", open=True) as area_basic_fn:
with gr.Row():
for k in functional:
variant = functional[k]["Color"] if "Color" in functional[k] else "secondary"
functional[k]["Button"] = gr.Button(k, variant=variant)
with gr.Accordion("函数插件区", open=True) as area_crazy_fn:
with gr.Row():
gr.Markdown("注意:以下“红颜色”标识的函数插件需从input区读取路径作为参数.")
with gr.Row():
for k in crazy_fns:
if not crazy_fns[k].get("AsButton", True): continue
variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
crazy_fns[k]["Button"] = gr.Button(k, variant=variant)
with gr.Row():
with gr.Accordion("更多函数插件", open=True):
dropdown_fn_list = [k for k in crazy_fns.keys() if not crazy_fns[k].get("AsButton", True)]
with gr.Column(scale=1):
dropdown = gr.Dropdown(dropdown_fn_list, value=r"打开插件列表", label="").style(container=False)
with gr.Column(scale=1):
switchy_bt = gr.Button(r"请先从插件列表中选择", variant="secondary")
with gr.Row():
with gr.Accordion("点击展开“文件上传区”。上传本地文件可供红色函数插件调用。", open=False) as area_file_up:
file_upload = gr.Files(label="任何文件, 但推荐上传压缩文件(zip, tar)", file_count="multiple")
with gr.Accordion("展开SysPrompt & 交互界面布局 & Github地址", open=False):
system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",)
temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",)
checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
gr.Markdown(description)
# 功能区显示开关与功能区的互动
def fn_area_visibility(a):
ret = {}
ret.update({area_basic_fn: gr.update(visible=("基础功能区" in a))})
ret.update({area_crazy_fn: gr.update(visible=("函数插件区" in a))})
return ret
checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn] )
# 整理反复出现的控件句柄组合
input_combo = [txt, top_p, api_key, temperature, chatbot, history, system_prompt]
output_combo = [chatbot, history, status]
predict_args = dict(fn=predict, inputs=input_combo, outputs=output_combo)
empty_txt_args = dict(fn=lambda: "", inputs=[], outputs=[txt]) # 用于在提交后清空输入栏
# 提交按钮、重置按钮
cancel_handles.append(txt.submit(**predict_args)) #; txt.submit(**empty_txt_args) 在提交后清空输入栏
cancel_handles.append(submitBtn.click(**predict_args)) #; submitBtn.click(**empty_txt_args) 在提交后清空输入栏
resetBtn.click(lambda: ([], [], "已重置"), None, output_combo)
# 基础功能区的回调函数注册
for k in functional:
click_handle = functional[k]["Button"].click(predict, [*input_combo, gr.State(True), gr.State(k)], output_combo)
cancel_handles.append(click_handle)
# 文件上传区,接收文件后与chatbot的互动
file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt], [chatbot, txt])
# 函数插件-固定按钮区
for k in crazy_fns:
if not crazy_fns[k].get("AsButton", True): continue
click_handle = crazy_fns[k]["Button"].click(crazy_fns[k]["Function"], [*input_combo, gr.State(PORT)], output_combo)
click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
cancel_handles.append(click_handle)
# 函数插件-下拉菜单与随变按钮的互动
def on_dropdown_changed(k):
variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
return {switchy_bt: gr.update(value=k, variant=variant)}
dropdown.select(on_dropdown_changed, [dropdown], [switchy_bt] )
# 随变按钮的回调函数注册
def route(k, *args, **kwargs):
if k in [r"打开插件列表", r"请先从插件列表中选择"]: return
yield from crazy_fns[k]["Function"](*args, **kwargs)
click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
# def expand_file_area(file_upload, area_file_up):
# if len(file_upload)>0: return {area_file_up: gr.update(open=True)}
# click_handle.then(expand_file_area, [file_upload, area_file_up], [area_file_up])
cancel_handles.append(click_handle)
# 终止按钮的回调函数注册
stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
# gradio的inbrowser触发不太稳定,回滚代码到原始的浏览器打开函数
def auto_opentab_delay():
import threading, webbrowser, time
print(f"如果浏览器没有自动打开,请复制并转到以下URL: http://localhost:{PORT}")
def open():
time.sleep(2)
webbrowser.open_new_tab(f"http://localhost:{PORT}")
threading.Thread(target=open, name="open-browser", daemon=True).start()
auto_opentab_delay()
demo.title = "ChatGPT 学术优化"
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=False)
+1 -1
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@@ -28,7 +28,7 @@ CHATBOT_HEIGHT = 1115
TIMEOUT_SECONDS = 25
# 网页的端口, -1代表随机端口
WEB_PORT = 7860
WEB_PORT = -1
# 如果OpenAI不响应(网络卡顿、代理失败、KEY失效),重试的次数限制
MAX_RETRY = 2
@@ -132,7 +132,7 @@ def get_name(_url_):
@CatchException
def 下载arxiv论文并翻译摘要(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 下载arxiv论文并翻译摘要(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
CRAZY_FUNCTION_INFO = "下载arxiv论文并翻译摘要,函数插件作者[binary-husky]。正在提取摘要并下载PDF文档……"
import glob
@@ -172,7 +172,7 @@ def 下载arxiv论文并翻译摘要(txt, top_p, api_key, temperature, chatbot,
yield chatbot, history, '正常'
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
chatbot[-1] = (i_say_show_user, gpt_say)
history.append(i_say_show_user); history.append(gpt_say)
yield chatbot, history, msg
@@ -1,41 +1,126 @@
import threading
from predict import predict_no_ui_long_connection
from toolbox import CatchException, write_results_to_file
from toolbox import CatchException, write_results_to_file, report_execption
def extract_code_block_carefully(txt):
splitted = txt.split('```')
n_code_block_seg = len(splitted) - 1
if n_code_block_seg <= 1: return txt
# 剩下的情况都开头除去 ``` 结尾除去一次 ```
txt_out = '```'.join(splitted[1:-1])
return txt_out
def breakdown_txt_to_satisfy_token_limit(txt, limit, must_break_at_empty_line=True):
from transformers import GPT2TokenizerFast
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2")
get_token_cnt = lambda txt: len(tokenizer(txt)["input_ids"])
def cut(txt_tocut, must_break_at_empty_line): # 递归
if get_token_cnt(txt_tocut) <= limit:
return [txt_tocut]
else:
lines = txt_tocut.split('\n')
estimated_line_cut = limit / get_token_cnt(txt_tocut) * len(lines)
estimated_line_cut = int(estimated_line_cut)
for cnt in reversed(range(estimated_line_cut)):
if must_break_at_empty_line:
if lines[cnt] != "": continue
print(cnt)
prev = "\n".join(lines[:cnt])
post = "\n".join(lines[cnt:])
if get_token_cnt(prev) < limit: break
if cnt == 0:
print('what the f?')
raise RuntimeError("存在一行极长的文本!")
print(len(post))
# 列表递归接龙
result = [prev]
result.extend(cut(post, must_break_at_empty_line))
return result
try:
return cut(txt, must_break_at_empty_line=True)
except RuntimeError:
return cut(txt, must_break_at_empty_line=False)
def break_txt_into_half_at_some_linebreak(txt):
lines = txt.split('\n')
n_lines = len(lines)
pre = lines[:(n_lines//2)]
post = lines[(n_lines//2):]
return "\n".join(pre), "\n".join(post)
@CatchException
def 全项目切换英文(txt, top_p, api_key, temperature, chatbot, history, sys_prompt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
# 集合文件
import time, glob, os
def 全项目切换英文(txt, top_p, temperature, chatbot, history, sys_prompt, WEB_PORT):
# 第1步:清空历史,以免输入溢出
history = []
# 第2步:尝试导入依赖,如果缺少依赖,则给出安装建议
try:
import openai, transformers
except:
report_execption(chatbot, history,
a = f"解析项目: {txt}",
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 openai transformers```。")
yield chatbot, history, '正常'
return
# 第3步:集合文件
import time, glob, os, shutil, re, openai
os.makedirs('gpt_log/generated_english_version', exist_ok=True)
os.makedirs('gpt_log/generated_english_version/crazy_functions', exist_ok=True)
file_manifest = [f for f in glob.glob('./*.py') if ('test_project' not in f) and ('gpt_log' not in f)] + \
[f for f in glob.glob('./crazy_functions/*.py') if ('test_project' not in f) and ('gpt_log' not in f)]
# file_manifest = ['./toolbox.py']
i_say_show_user_buffer = []
# 随便显示点什么防止卡顿的感觉
# 第4步:随便显示点什么防止卡顿的感觉
for index, fp in enumerate(file_manifest):
# if 'test_project' in fp: continue
with open(fp, 'r', encoding='utf-8') as f:
file_content = f.read()
i_say_show_user =f'[{index}/{len(file_manifest)}] 接下来请将以下代码中包含的所有中文转化为英文,只输出代码: {os.path.abspath(fp)}'
i_say_show_user =f'[{index}/{len(file_manifest)}] 接下来请将以下代码中包含的所有中文转化为英文,只输出转化后的英文代码,请用代码块输出代码: {os.path.abspath(fp)}'
i_say_show_user_buffer.append(i_say_show_user)
chatbot.append((i_say_show_user, "[Local Message] 等待多线程操作,中间过程不予显示."))
yield chatbot, history, '正常'
# 任务函数
# 第5步:Token限制下的截断与处理
MAX_TOKEN = 2500
# from transformers import GPT2TokenizerFast
# print('加载tokenizer中')
# tokenizer = GPT2TokenizerFast.from_pretrained("gpt2")
# get_token_cnt = lambda txt: len(tokenizer(txt)["input_ids"])
# print('加载tokenizer结束')
# 第6步:任务函数
mutable_return = [None for _ in file_manifest]
observe_window = [[""] for _ in file_manifest]
def thread_worker(fp,index):
if index > 10:
time.sleep(60)
print('Openai 限制免费用户每分钟20次请求,降低请求频率中。')
with open(fp, 'r', encoding='utf-8') as f:
file_content = f.read()
i_say = f'接下来请将以下代码中包含的所有中文转化为英文,只输出代码,文件名是{fp},文件代码是 ```{file_content}```'
# ** gpt request **
gpt_say = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
mutable_return[index] = gpt_say
i_say_template = lambda fp, file_content: f'接下来请将以下代码中包含的所有中文转化为英文,只输出代码,文件名是{fp},文件代码是 ```{file_content}```'
try:
gpt_say = ""
# 分解代码文件
file_content_breakdown = breakdown_txt_to_satisfy_token_limit(file_content, MAX_TOKEN)
for file_content_partial in file_content_breakdown:
i_say = i_say_template(fp, file_content_partial)
# # ** gpt request **
gpt_say_partial = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, temperature=temperature, history=[], sys_prompt=sys_prompt, observe_window=observe_window[index])
gpt_say_partial = extract_code_block_carefully(gpt_say_partial)
gpt_say += gpt_say_partial
mutable_return[index] = gpt_say
except ConnectionAbortedError as token_exceed_err:
print('至少一个线程任务Token溢出而失败', e)
except Exception as e:
print('至少一个线程任务意外失败', e)
# 所有线程同时开始执行任务函数
# 第7步:所有线程同时开始执行任务函数
handles = [threading.Thread(target=thread_worker, args=(fp,index)) for index, fp in enumerate(file_manifest)]
for h in handles:
h.daemon = True
@@ -43,19 +128,23 @@ def 全项目切换英文(txt, top_p, api_key, temperature, chatbot, history, sy
chatbot.append(('开始了吗?', f'多线程操作已经开始'))
yield chatbot, history, '正常'
# 循环轮询各个线程是否执行完毕
# 第8步:循环轮询各个线程是否执行完毕
cnt = 0
while True:
time.sleep(1)
cnt += 1
time.sleep(0.2)
th_alive = [h.is_alive() for h in handles]
if not any(th_alive): break
stat = ['执行中' if alive else '已完成' for alive in th_alive]
stat_str = '|'.join(stat)
cnt += 1
chatbot[-1] = (chatbot[-1][0], f'多线程操作已经开始,完成情况: {stat_str}' + ''.join(['.']*(cnt%4)))
# 更好的UI视觉效果
observe_win = []
for thread_index, alive in enumerate(th_alive):
observe_win.append("[ ..."+observe_window[thread_index][0][-60:].replace('\n','').replace('```','...').replace(' ','.').replace('<br/>','.....').replace('$','.')+"... ]")
stat = [f'执行中: {obs}\n\n' if alive else '已完成\n\n' for alive, obs in zip(th_alive, observe_win)]
stat_str = ''.join(stat)
chatbot[-1] = (chatbot[-1][0], f'多线程操作已经开始,完成情况: \n\n{stat_str}' + ''.join(['.']*(cnt%10+1)))
yield chatbot, history, '正常'
# 把结果写入文件
# 第9步:把结果写入文件
for index, h in enumerate(handles):
h.join() # 这里其实不需要join了,肯定已经都结束了
fp = file_manifest[index]
@@ -63,13 +152,17 @@ def 全项目切换英文(txt, top_p, api_key, temperature, chatbot, history, sy
i_say_show_user = i_say_show_user_buffer[index]
where_to_relocate = f'gpt_log/generated_english_version/{fp}'
with open(where_to_relocate, 'w+', encoding='utf-8') as f: f.write(gpt_say.lstrip('```').rstrip('```'))
if gpt_say is not None:
with open(where_to_relocate, 'w+', encoding='utf-8') as f:
f.write(gpt_say)
else: # 失败
shutil.copyfile(file_manifest[index], where_to_relocate)
chatbot.append((i_say_show_user, f'[Local Message] 已完成{os.path.abspath(fp)}的转化,\n\n存入{os.path.abspath(where_to_relocate)}'))
history.append(i_say_show_user); history.append(gpt_say)
yield chatbot, history, '正常'
time.sleep(1)
# 备份一个文件
# 第10步:备份一个文件
res = write_results_to_file(history)
chatbot.append(("生成一份任务执行报告", res))
yield chatbot, history, '正常'
+5 -5
View File
@@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file, pre
fast_debug = False
def 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
def 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
import time, os
# pip install python-docx 用于docx格式,跨平台
# pip install pywin32 用于doc格式,仅支持Win平台
@@ -40,7 +40,7 @@ def 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatb
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature,
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature,
history=[]) # 带超时倒计时
chatbot[-1] = (i_say_show_user, gpt_say)
history.append(i_say_show_user);
@@ -66,7 +66,7 @@ def 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatb
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature,
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature,
history=history) # 带超时倒计时
chatbot[-1] = (i_say, gpt_say)
@@ -79,7 +79,7 @@ def 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatb
@CatchException
def 总结word文档(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 总结word文档(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
import glob, os
# 基本信息:功能、贡献者
@@ -124,4 +124,4 @@ def 总结word文档(txt, top_p, api_key, temperature, chatbot, history, systemP
return
# 开始正式执行任务
yield from 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
+5 -5
View File
@@ -57,7 +57,7 @@ def clean_text(raw_text):
return final_text.strip()
def 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
def 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
import time, glob, os, fitz
print('begin analysis on:', file_manifest)
for index, fp in enumerate(file_manifest):
@@ -78,7 +78,7 @@ def 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbo
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
print('[2] end gpt req')
chatbot[-1] = (i_say_show_user, gpt_say)
@@ -96,7 +96,7 @@ def 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbo
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
chatbot[-1] = (i_say, gpt_say)
history.append(i_say); history.append(gpt_say)
@@ -107,7 +107,7 @@ def 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbo
@CatchException
def 批量总结PDF文档(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 批量总结PDF文档(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
import glob, os
# 基本信息:功能、贡献者
@@ -151,4 +151,4 @@ def 批量总结PDF文档(txt, top_p, api_key, temperature, chatbot, history, sy
return
# 开始正式执行任务
yield from 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
@@ -61,7 +61,7 @@ def readPdf(pdfPath):
return outTextList
def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
import time, glob, os
from bs4 import BeautifulSoup
print('begin analysis on:', file_manifest)
@@ -83,7 +83,7 @@ def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chat
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
print('[2] end gpt req')
chatbot[-1] = (i_say_show_user, gpt_say)
@@ -101,7 +101,7 @@ def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chat
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
chatbot[-1] = (i_say, gpt_say)
history.append(i_say); history.append(gpt_say)
@@ -113,7 +113,7 @@ def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chat
@CatchException
def 批量总结PDF文档pdfminer(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 批量总结PDF文档pdfminer(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
import glob, os
@@ -147,5 +147,5 @@ def 批量总结PDF文档pdfminer(txt, top_p, api_key, temperature, chatbot, his
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或pdf文件: {txt}")
yield chatbot, history, '正常'
return
yield from 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
+4 -4
View File
@@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file, pre
fast_debug = False
def 生成函数注释(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
def 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
import time, glob, os
print('begin analysis on:', file_manifest)
for index, fp in enumerate(file_manifest):
@@ -19,7 +19,7 @@ def 生成函数注释(file_manifest, project_folder, top_p, api_key, temperatur
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
print('[2] end gpt req')
chatbot[-1] = (i_say_show_user, gpt_say)
@@ -37,7 +37,7 @@ def 生成函数注释(file_manifest, project_folder, top_p, api_key, temperatur
@CatchException
def 批量生成函数注释(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 批量生成函数注释(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
import glob, os
if os.path.exists(txt):
@@ -54,4 +54,4 @@ def 批量生成函数注释(txt, top_p, api_key, temperature, chatbot, history,
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
yield chatbot, history, '正常'
return
yield from 生成函数注释(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
+23 -22
View File
@@ -2,7 +2,7 @@ from predict import predict_no_ui
from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down
fast_debug = False
def 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
import time, glob, os
print('begin analysis on:', file_manifest)
for index, fp in enumerate(file_manifest):
@@ -19,7 +19,7 @@ def 解析源代码(file_manifest, project_folder, top_p, api_key, temperature,
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
chatbot[-1] = (i_say_show_user, gpt_say)
history.append(i_say_show_user); history.append(gpt_say)
@@ -34,7 +34,7 @@ def 解析源代码(file_manifest, project_folder, top_p, api_key, temperature,
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
chatbot[-1] = (i_say, gpt_say)
history.append(i_say); history.append(gpt_say)
@@ -47,7 +47,7 @@ def 解析源代码(file_manifest, project_folder, top_p, api_key, temperature,
@CatchException
def 解析项目本身(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
import time, glob, os
file_manifest = [f for f in glob.glob('./*.py') if ('test_project' not in f) and ('gpt_log' not in f)] + \
@@ -65,8 +65,8 @@ def 解析项目本身(txt, top_p, api_key, temperature, chatbot, history, syste
if not fast_debug:
# ** gpt request **
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature)
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[], long_connection=True) # 带超时倒计时
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature)
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[], long_connection=True) # 带超时倒计时
chatbot[-1] = (i_say_show_user, gpt_say)
history.append(i_say_show_user); history.append(gpt_say)
@@ -79,8 +79,8 @@ def 解析项目本身(txt, top_p, api_key, temperature, chatbot, history, syste
if not fast_debug:
# ** gpt request **
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history)
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history, long_connection=True) # 带超时倒计时
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature, history=history)
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history, long_connection=True) # 带超时倒计时
chatbot[-1] = (i_say, gpt_say)
history.append(i_say); history.append(gpt_say)
@@ -90,7 +90,7 @@ def 解析项目本身(txt, top_p, api_key, temperature, chatbot, history, syste
yield chatbot, history, '正常'
@CatchException
def 解析一个Python项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 解析一个Python项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
import glob, os
if os.path.exists(txt):
@@ -105,11 +105,11 @@ def 解析一个Python项目(txt, top_p, api_key, temperature, chatbot, history,
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何python文件: {txt}")
yield chatbot, history, '正常'
return
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
@CatchException
def 解析一个C项目的头文件(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 解析一个C项目的头文件(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
import glob, os
if os.path.exists(txt):
@@ -119,17 +119,17 @@ def 解析一个C项目的头文件(txt, top_p, api_key, temperature, chatbot, h
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield chatbot, history, '正常'
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.h', recursive=True)] # + \
# [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] + \
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.h', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.hpp', recursive=True)] #+ \
# [f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
if len(file_manifest) == 0:
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.h头文件: {txt}")
yield chatbot, history, '正常'
return
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
@CatchException
def 解析一个C项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 解析一个C项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
import glob, os
if os.path.exists(txt):
@@ -141,16 +141,17 @@ def 解析一个C项目(txt, top_p, api_key, temperature, chatbot, history, syst
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.h', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.hpp', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
if len(file_manifest) == 0:
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.h头文件: {txt}")
yield chatbot, history, '正常'
return
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
@CatchException
def 解析一个Java项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 解析一个Java项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
import glob, os
if os.path.exists(txt):
@@ -168,11 +169,11 @@ def 解析一个Java项目(txt, top_p, api_key, temperature, chatbot, history, s
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何java文件: {txt}")
yield chatbot, history, '正常'
return
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
@CatchException
def 解析一个Rect项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 解析一个Rect项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
import glob, os
if os.path.exists(txt):
@@ -191,11 +192,11 @@ def 解析一个Rect项目(txt, top_p, api_key, temperature, chatbot, history, s
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何Rect文件: {txt}")
yield chatbot, history, '正常'
return
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
@CatchException
def 解析一个Golang项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 解析一个Golang项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
import glob, os
if os.path.exists(txt):
@@ -210,4 +211,4 @@ def 解析一个Golang项目(txt, top_p, api_key, temperature, chatbot, history,
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何golang文件: {txt}")
yield chatbot, history, '正常'
return
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
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@@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file, pre
fast_debug = False
def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
import time, glob, os
print('begin analysis on:', file_manifest)
for index, fp in enumerate(file_manifest):
@@ -20,7 +20,7 @@ def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chat
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
print('[2] end gpt req')
chatbot[-1] = (i_say_show_user, gpt_say)
@@ -38,7 +38,7 @@ def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chat
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
chatbot[-1] = (i_say, gpt_say)
history.append(i_say); history.append(gpt_say)
@@ -50,7 +50,7 @@ def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chat
@CatchException
def 读文章写摘要(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 读文章写摘要(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
import glob, os
if os.path.exists(txt):
@@ -67,4 +67,4 @@ def 读文章写摘要(txt, top_p, api_key, temperature, chatbot, history, syste
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
yield chatbot, history, '正常'
return
yield from 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
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@@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file
import datetime
@CatchException
def 高阶功能模板函数(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def 高阶功能模板函数(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
history = [] # 清空历史,以免输入溢出
chatbot.append(("这是什么功能?", "[Local Message] 请注意,您正在调用一个[函数插件]的模板,该函数面向希望实现更多有趣功能的开发者,它可以作为创建新功能函数的模板。为了做到简单易读,该函数只有25行代码,所以不会实时反馈文字流或心跳,请耐心等待程序输出完成。此外我们也提供可同步处理大量文件的多线程Demo供您参考。您若希望分享新的功能模组,请不吝PR!"))
yield chatbot, history, '正常' # 由于请求gpt需要一段时间,我们先及时地做一次状态显示
@@ -17,7 +17,7 @@ def 高阶功能模板函数(txt, top_p, api_key, temperature, chatbot, history,
# history = [] 每次询问不携带之前的询问历史
gpt_say = predict_no_ui_long_connection(
inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=[],
inputs=i_say, top_p=top_p, temperature=temperature, history=[],
sys_prompt="当你想发送一张照片时,请使用Markdown, 并且不要有反斜线, 不要用代码块。使用 Unsplash API (https://source.unsplash.com/1280x720/? < PUT_YOUR_QUERY_HERE >)。") # 请求gpt,需要一段时间
chatbot[-1] = (i_say, gpt_say)
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@@ -43,7 +43,7 @@ def get_crazy_functionals():
"AsButton": False, # 加入下拉菜单中
"Function": 解析一个Java项目
},
"解析整个Java项目": {
"解析整个React项目": {
"Color": "stop", # 按钮颜色
"AsButton": False, # 加入下拉菜单中
"Function": 解析一个Rect项目
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@@ -1,4 +1,3 @@
assert False, "Huggingface版请运行app.py"
import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
import gradio as gr
from predict import predict
@@ -41,9 +40,6 @@ set_theme = adjust_theme()
cancel_handles = []
with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
gr.HTML(title_html)
# To add a Duplicate Space badge
gr.HTML('''<center><a href="https://huggingface.co/spaces/qingxu98/gpt-academic?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>请您打开此页面后务必点击上方的“复制空间”(Duplicate Space)按钮!<br/>切忌在“复制空间”(Duplicate Space)之前填入API_KEY或进行提问,否则您的API_KEY将极可能被空间所有者攫取!</center>''')
with gr.Row().style(equal_height=True):
with gr.Column(scale=2):
chatbot = gr.Chatbot()
@@ -51,9 +47,7 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
history = gr.State([])
with gr.Column(scale=1):
with gr.Row():
api_key = gr.Textbox(show_label=False, placeholder="输入API_KEY,输入后自动生效.").style(container=False)
with gr.Row():
txt = gr.Textbox(show_label=False, placeholder="输入问题.").style(container=False)
txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False)
with gr.Row():
submitBtn = gr.Button("提交", variant="primary")
with gr.Row():
@@ -99,7 +93,7 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
return ret
checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn] )
# 整理反复出现的控件句柄组合
input_combo = [txt, top_p, api_key, temperature, chatbot, history, system_prompt]
input_combo = [txt, top_p, temperature, chatbot, history, system_prompt]
output_combo = [chatbot, history, status]
predict_args = dict(fn=predict, inputs=input_combo, outputs=output_combo)
empty_txt_args = dict(fn=lambda: "", inputs=[], outputs=[txt]) # 用于在提交后清空输入栏
@@ -140,12 +134,14 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
# gradio的inbrowser触发不太稳定,回滚代码到原始的浏览器打开函数
def auto_opentab_delay():
import threading, webbrowser, time
print(f"如果浏览器没有自动打开,请复制并转到以下URL: http://localhost:{PORT}")
print(f"如果浏览器没有自动打开,请复制并转到以下URL")
print(f"\t(亮色主体): http://localhost:{PORT}")
print(f"\t(暗色主体): http://localhost:{PORT}/?__dark-theme=true")
def open():
time.sleep(2)
webbrowser.open_new_tab(f"http://localhost:{PORT}")
webbrowser.open_new_tab(f"http://localhost:{PORT}/?__dark-theme=true")
threading.Thread(target=open, name="open-browser", daemon=True).start()
auto_opentab_delay()
demo.title = "ChatGPT 学术优化"
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=False)
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=Flase, server_port=8080, auth=chunzhi233233)
+15 -11
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@@ -38,18 +38,18 @@ def get_full_error(chunk, stream_response):
break
return chunk
def predict_no_ui(inputs, top_p, api_key, temperature, history=[], sys_prompt=""):
def predict_no_ui(inputs, top_p, temperature, history=[], sys_prompt=""):
"""
发送至chatGPT等待回复一次性完成不显示中间过程
predict函数的简化版
用于payload比较大的情况或者用于实现多线带嵌套的复杂功能
inputs 是本次问询的输入
top_p, api_key, 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数量溢出的错误然后raise ConnectionAbortedError
"""
headers, payload = generate_payload(inputs, top_p, api_key, temperature, history, system_prompt=sys_prompt, stream=False)
headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt=sys_prompt, stream=False)
retry = 0
while True:
@@ -71,11 +71,12 @@ def predict_no_ui(inputs, top_p, api_key, temperature, history=[], sys_prompt=""
raise ConnectionAbortedError("Json解析不合常规,可能是文本过长" + response.text)
def predict_no_ui_long_connection(inputs, top_p, api_key, temperature, history=[], sys_prompt=""):
def predict_no_ui_long_connection(inputs, top_p, temperature, history=[], sys_prompt="", observe_window=None):
"""
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的方法避免有人中途掐网线
observe_window用于负责跨越线程传递已经输出的部分大部分时候仅仅为了fancy的视觉效果留空即可
"""
headers, payload = generate_payload(inputs, top_p, api_key, temperature, history, system_prompt=sys_prompt, stream=True)
headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt=sys_prompt, stream=True)
retry = 0
while True:
@@ -105,20 +106,23 @@ def predict_no_ui_long_connection(inputs, top_p, api_key, temperature, history=[
delta = json_data["delta"]
if len(delta) == 0: break
if "role" in delta: continue
if "content" in delta: result += delta["content"]; print(delta["content"], end='')
if "content" in delta:
result += delta["content"]
print(delta["content"], end='')
if observe_window is not None: observe_window[0] += delta["content"]
else: raise RuntimeError("意外Json结构:"+delta)
if json_data['finish_reason'] == 'length':
raise ConnectionAbortedError("正常结束,但显示Token不足。")
return result
def predict(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_prompt='',
def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='',
stream = True, additional_fn=None):
"""
发送至chatGPT流式获取输出
用于基础的对话功能
inputs 是本次问询的输入
top_p, api_key, 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
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
additional_fn代表点击的哪个按钮按钮见functional.py
@@ -136,7 +140,7 @@ def predict(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_
chatbot.append((inputs, ""))
yield chatbot, history, "等待响应"
headers, payload = generate_payload(inputs, top_p, api_key, temperature, history, system_prompt, stream)
headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt, stream)
history.append(inputs); history.append(" ")
retry = 0
@@ -198,13 +202,13 @@ def predict(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_
yield chatbot, history, "Json异常" + error_msg
return
def generate_payload(inputs, top_p, api_key, temperature, history, system_prompt, stream):
def generate_payload(inputs, top_p, temperature, history, system_prompt, stream):
"""
整合所有信息选择LLM模型生成http请求为发送请求做准备
"""
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {api_key}"
"Authorization": f"Bearer {API_KEY}"
}
conversation_cnt = len(history) // 2
+3 -3
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@@ -90,12 +90,12 @@ async def run(context, max_token=512):
def predict_tgui(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_prompt='', stream = True, additional_fn=None):
def predict_tgui(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', stream = True, additional_fn=None):
"""
发送至chatGPT流式获取输出
用于基础的对话功能
inputs 是本次问询的输入
top_p, api_key, 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
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
additional_fn代表点击的哪个按钮按钮见functional.py
@@ -144,7 +144,7 @@ def predict_tgui(inputs, top_p, api_key, temperature, chatbot=[], history=[], sy
def predict_tgui_no_ui(inputs, top_p, api_key, temperature, history=[], sys_prompt=""):
def predict_tgui_no_ui(inputs, top_p, temperature, history=[], sys_prompt=""):
raw_input = "What I would like to say is the following: " + inputs
prompt = inputs
tgui_say = ""
+2 -4
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@@ -3,7 +3,5 @@ requests[socks]
mdtex2html
Markdown
latex2mathml
pdfminer
beautifulsoup4
rarfile
py7zr
openai
transformers
+5 -5
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@@ -131,11 +131,11 @@
这个程序文件中包含了几个函数,分别是:
1. `解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)`:通过输入文件路径列表对程序文件进行逐文件分析,根据分析结果做出整体功能和构架的概括,并生成包括每个文件功能的markdown表格。
2. `解析项目本身(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对当前文件夹下的所有Python文件及其子文件夹进行逐文件分析,并生成markdown表格。
3. `解析一个Python项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有Python文件及其子文件夹进行逐文件分析,并生成markdown表格。
4. `解析一个C项目的头文件(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有头文件进行逐文件分析,并生成markdown表格。
5. `解析一个C项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有.h、.cpp、.c文件及其子文件夹进行逐文件分析,并生成markdown表格。
1. `解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)`:通过输入文件路径列表对程序文件进行逐文件分析,根据分析结果做出整体功能和构架的概括,并生成包括每个文件功能的markdown表格。
2. `解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对当前文件夹下的所有Python文件及其子文件夹进行逐文件分析,并生成markdown表格。
3. `解析一个Python项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有Python文件及其子文件夹进行逐文件分析,并生成markdown表格。
4. `解析一个C项目的头文件(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有头文件进行逐文件分析,并生成markdown表格。
5. `解析一个C项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有.h、.cpp、.c文件及其子文件夹进行逐文件分析,并生成markdown表格。
程序中还包含了一些辅助函数和变量,如CatchException装饰器函数,report_execption函数、write_results_to_file函数等。在执行过程中还会调用其他模块中的函数,如toolbox模块的函数和predict模块的函数。
+15 -15
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@@ -16,13 +16,13 @@ def get_reduce_token_percent(text):
except:
return 0.5, '不详'
def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[], sys_prompt='', long_connection=True):
def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[], sys_prompt='', long_connection=True):
"""
调用简单的predict_no_ui接口但是依然保留了些许界面心跳功能当对话太长时会自动采用二分法截断
i_say: 当前输入
i_say_show_user: 显示到对话界面上的当前输入例如输入整个文件时你绝对不想把文件的内容都糊到对话界面上
chatbot: 对话界面句柄
top_p, api_key, temperature: gpt参数
top_p, temperature: gpt参数
history: gpt参数 对话历史
sys_prompt: gpt参数 sys_prompt
long_connection: 是否采用更稳定的连接方式推荐
@@ -39,9 +39,9 @@ def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_
while True:
try:
if long_connection:
mutable[0] = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
mutable[0] = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
else:
mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
break
except ConnectionAbortedError as token_exceeded_error:
# 尝试计算比例,尽可能多地保留文本
@@ -108,9 +108,9 @@ 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, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
try:
yield from f(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
except Exception as e:
from check_proxy import check_proxy
from toolbox import get_conf
@@ -303,7 +303,7 @@ def on_file_uploaded(files, chatbot, txt):
def on_report_generated(files, chatbot):
from toolbox import find_recent_files
report_files = find_recent_files('gpt_log')
if len(report_files) == 0: return files, chatbot
if len(report_files) == 0: return None, chatbot
# files.extend(report_files)
chatbot.append(['汇总报告如何远程获取?', '汇总报告已经添加到右侧“文件上传区”(可能处于折叠状态),请查收。'])
return report_files, chatbot
@@ -313,14 +313,14 @@ def read_single_conf_with_lru_cache(arg):
try: r = getattr(importlib.import_module('config_private'), arg)
except: r = getattr(importlib.import_module('config'), arg)
# 在读取API_KEY时,检查一下是不是忘了改config
# if arg=='API_KEY':
# # 正确的 API_KEY 是 "sk-" + 48 位大小写字母数字的组合
# API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", r)
# if API_MATCH:
# print(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
# else:
# assert False, "正确的 API_KEY 是 'sk-' + '48 位大小写字母数字' 的组合,请在config文件中修改API密钥, 添加海外代理之后再运行。" + \
# "(如果您刚更新过代码,请确保旧版config_private文件中没有遗留任何新增键值)"
if arg=='API_KEY':
# 正确的 API_KEY 是 "sk-" + 48 位大小写字母数字的组合
API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", r)
if API_MATCH:
print(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
else:
assert False, "正确的 API_KEY 是 'sk-' + '48 位大小写字母数字' 的组合,请在config文件中修改API密钥, 添加海外代理之后再运行。" + \
"(如果您刚更新过代码,请确保旧版config_private文件中没有遗留任何新增键值)"
if arg=='proxies':
if r is None:
print('[PROXY] 网络代理状态:未配置。无代理状态下很可能无法访问。建议:检查USE_PROXY选项是否修改。')
+5
View File
@@ -0,0 +1,5 @@
{
"version": 2.3,
"show_feature": true,
"new_feature": "修复多线程插件Bug;加入版本检查功能。"
}