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12
README.md
12
README.md
@ -1,3 +1,15 @@
|
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---
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title: ChatImprovement
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emoji: 😻
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colorFrom: blue
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colorTo: blue
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sdk: gradio
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sdk_version: 3.32.0
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app_file: app.py
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pinned: false
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---
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# ChatGPT 学术优化
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> **Note**
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>
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> 2023.5.27 对Gradio依赖进行了调整,Fork并解决了官方Gradio的若干Bugs。请及时**更新代码**并重新更新pip依赖。安装依赖时,请严格选择`requirements.txt`中**指定的版本**:
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@ -1,8 +1,10 @@
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import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
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def main():
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import subprocess, sys
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subprocess.check_call([sys.executable, '-m', 'pip', 'install', 'gradio-stable-fork'])
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import gradio as gr
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if gr.__version__ not in ['3.28.3','3.32.2']: assert False, "需要特殊依赖,请务必用 pip install -r requirements.txt 指令安装依赖,详情信息见requirements.txt"
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if gr.__version__ not in ['3.28.3','3.32.3']: assert False, "请用 pip install -r requirements.txt 安装依赖"
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from request_llm.bridge_all import predict
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from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith
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# 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
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@ -54,6 +56,7 @@ def main():
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cancel_handles = []
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with gr.Blocks(title="ChatGPT 学术优化", theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
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gr.HTML(title_html)
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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!<font color="#FF00FF">使用时,先在输入框填入API-KEY然后回车。</font><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!<br/>支持任意数量的OpenAI的密钥和API2D的密钥共存,例如输入"OpenAI密钥1,API2D密钥2",然后提交,即可同时使用两种模型接口。</center>''')
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cookies = gr.State({'api_key': API_KEY, 'llm_model': LLM_MODEL})
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with gr_L1():
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with gr_L2(scale=2):
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@ -63,7 +66,7 @@ def main():
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with gr_L2(scale=1):
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with gr.Accordion("输入区", open=True) as area_input_primary:
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with gr.Row():
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txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False)
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txt = gr.Textbox(show_label=False, lines=2, placeholder="输入问题或API密钥,输入多个密钥时,用英文逗号间隔。支持OpenAI密钥和API2D密钥共存。").style(container=False)
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with gr.Row():
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submitBtn = gr.Button("提交", variant="primary")
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with gr.Row():
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@ -197,10 +200,7 @@ def main():
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threading.Thread(target=warm_up_modules, name="warm-up", daemon=True).start()
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auto_opentab_delay()
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demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
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server_name="0.0.0.0", server_port=PORT,
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favicon_path="docs/logo.png", auth=AUTHENTICATION,
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blocked_paths=["config.py","config_private.py","docker-compose.yml","Dockerfile"])
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demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=False, favicon_path="docs/logo.png", blocked_paths=["config.py","config_private.py","docker-compose.yml","Dockerfile"])
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# 如果需要在二级路径下运行
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# CUSTOM_PATH, = get_conf('CUSTOM_PATH')
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@ -45,10 +45,9 @@ WEB_PORT = -1
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# 如果OpenAI不响应(网络卡顿、代理失败、KEY失效),重试的次数限制
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MAX_RETRY = 2
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# 模型选择是 (注意: LLM_MODEL是默认选中的模型, 同时它必须被包含在AVAIL_LLM_MODELS切换列表中 )
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LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
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AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt35", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "newbing-free", "stack-claude"]
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# P.S. 其他可用的模型还包括 ["gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", "newbing-free", "jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
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# OpenAI模型选择是(gpt4现在只对申请成功的人开放)
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LLM_MODEL = "gpt-3.5-turbo" # 可选 "chatglm"
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AVAIL_LLM_MODELS = ["newbing-free", "gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "api2d-gpt-3.5-turbo"]
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# 本地LLM模型如ChatGLM的执行方式 CPU/GPU
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LOCAL_MODEL_DEVICE = "cpu" # 可选 "cuda"
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@ -226,12 +226,20 @@ def get_crazy_functions():
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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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"连接网络回答问题(先输入问题,再点击按钮,需要访问谷歌)": {
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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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"Color": "stop",
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"AsButton": False, # 加入下拉菜单中
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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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||||
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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"连接网络回答问题(中文Bing版,输入问题后点击该插件)": {
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(连接bing搜索回答问题)
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||||
}
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||||
})
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||||
except:
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||||
print('Load function plugin failed')
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||||
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||||
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@ -27,6 +27,24 @@ def set_forbidden_text(text, mask, pattern, flags=0):
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mask[res.span()[0]:res.span()[1]] = PRESERVE
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||||
return text, mask
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||||
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||||
def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
|
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"""
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Move area out of preserve area (make text editable for GPT)
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count the number of the braces so as to catch compelete text area.
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e.g.
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\begin{abstract} blablablablablabla. \end{abstract}
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"""
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if isinstance(pattern, list): pattern = '|'.join(pattern)
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pattern_compile = re.compile(pattern, flags)
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for res in pattern_compile.finditer(text):
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if not forbid_wrapper:
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mask[res.span()[0]:res.span()[1]] = TRANSFORM
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else:
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mask[res.regs[0][0]: res.regs[1][0]] = PRESERVE # '\\begin{abstract}'
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mask[res.regs[1][0]: res.regs[1][1]] = TRANSFORM # abstract
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||||
mask[res.regs[1][1]: res.regs[0][1]] = PRESERVE # abstract
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return text, mask
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||||
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||||
def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
|
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"""
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Add a preserve text area in this paper (text become untouchable for GPT).
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@ -326,6 +344,7 @@ def split_subprocess(txt, project_folder, return_dict, opts):
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# reverse 操作必须放在最后
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text, mask = reverse_forbidden_text_careful_brace(text, mask, r"\\caption\{(.*?)\}", re.DOTALL, forbid_wrapper=True)
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text, mask = reverse_forbidden_text_careful_brace(text, mask, r"\\abstract\{(.*?)\}", re.DOTALL, forbid_wrapper=True)
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text, mask = reverse_forbidden_text(text, mask, r"\\begin\{abstract\}(.*?)\\end\{abstract\}", re.DOTALL, forbid_wrapper=True)
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root = convert_to_linklist(text, mask)
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||||
# 修复括号
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@ -672,10 +691,9 @@ def remove_buggy_lines(file_path, log_path, tex_name, tex_name_pure, n_fix, work
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print("Fatal error occurred, but we cannot identify error, please download zip, read latex log, and compile manually.")
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||||
return False, -1, [-1]
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||||
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||||
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||||
def compile_latex_with_timeout(command, timeout=60):
|
||||
def compile_latex_with_timeout(command, cwd, timeout=60):
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||||
import subprocess
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||||
process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
|
||||
process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=cwd)
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||||
try:
|
||||
stdout, stderr = process.communicate(timeout=timeout)
|
||||
except subprocess.TimeoutExpired:
|
||||
@ -699,24 +717,24 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
|
||||
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||||
# 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
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||||
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
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ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', 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
|
||||
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex'); os.chdir(current_dir)
|
||||
ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
|
||||
|
||||
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
|
||||
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
|
||||
if not os.path.exists(pj(work_folder_original, f'{main_file_original}.bbl')):
|
||||
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'bibtex {main_file_original}.aux'); os.chdir(current_dir)
|
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ok = compile_latex_with_timeout(f'bibtex {main_file_original}.aux', work_folder_original)
|
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if not os.path.exists(pj(work_folder_modified, f'{main_file_modified}.bbl')):
|
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os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'bibtex {main_file_modified}.aux'); os.chdir(current_dir)
|
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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
|
||||
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
|
||||
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex'); os.chdir(current_dir)
|
||||
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
|
||||
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex'); os.chdir(current_dir)
|
||||
ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
|
||||
ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
|
||||
ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
|
||||
ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
|
||||
|
||||
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
|
||||
@ -724,13 +742,11 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
|
||||
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')
|
||||
|
||||
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
|
||||
os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
|
||||
os.chdir(work_folder); ok = compile_latex_with_timeout(f'bibtex merge_diff.aux'); os.chdir(current_dir)
|
||||
os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
|
||||
os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
|
||||
ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
|
||||
ok = compile_latex_with_timeout(f'bibtex merge_diff.aux', work_folder)
|
||||
ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
|
||||
ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
|
||||
|
||||
# <--------------------->
|
||||
os.chdir(current_dir)
|
||||
|
||||
# <---------- 检查结果 ----------->
|
||||
results_ = ""
|
||||
@ -766,7 +782,6 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
|
||||
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
|
||||
if not can_retry: break
|
||||
|
||||
os.chdir(current_dir)
|
||||
return False # 失败啦
|
||||
|
||||
|
||||
|
||||
102
crazy_functions/联网的ChatGPT_bing版.py
Normal file
102
crazy_functions/联网的ChatGPT_bing版.py
Normal file
@ -0,0 +1,102 @@
|
||||
from toolbox import CatchException, update_ui
|
||||
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
|
||||
import requests
|
||||
from bs4 import BeautifulSoup
|
||||
from request_llm.bridge_all import model_info
|
||||
|
||||
|
||||
def bing_search(query, proxies=None):
|
||||
query = query
|
||||
url = f"https://cn.bing.com/search?q={query}"
|
||||
headers = {'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'}
|
||||
response = requests.get(url, headers=headers, proxies=proxies)
|
||||
soup = BeautifulSoup(response.content, 'html.parser')
|
||||
results = []
|
||||
for g in soup.find_all('li', class_='b_algo'):
|
||||
anchors = g.find_all('a')
|
||||
if anchors:
|
||||
link = anchors[0]['href']
|
||||
if not link.startswith('http'):
|
||||
continue
|
||||
title = g.find('h2').text
|
||||
item = {'title': title, 'link': link}
|
||||
results.append(item)
|
||||
|
||||
for r in results:
|
||||
print(r['link'])
|
||||
return results
|
||||
|
||||
|
||||
def scrape_text(url, proxies) -> str:
|
||||
"""Scrape text from a webpage
|
||||
|
||||
Args:
|
||||
url (str): The URL to scrape text from
|
||||
|
||||
Returns:
|
||||
str: The scraped text
|
||||
"""
|
||||
headers = {
|
||||
'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',
|
||||
'Content-Type': 'text/plain',
|
||||
}
|
||||
try:
|
||||
response = requests.get(url, headers=headers, proxies=proxies, timeout=8)
|
||||
if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
|
||||
except:
|
||||
return "无法连接到该网页"
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
for script in soup(["script", "style"]):
|
||||
script.extract()
|
||||
text = soup.get_text()
|
||||
lines = (line.strip() for line in text.splitlines())
|
||||
chunks = (phrase.strip() for line in lines for phrase in line.split(" "))
|
||||
text = "\n".join(chunk for chunk in chunks if chunk)
|
||||
return text
|
||||
|
||||
@CatchException
|
||||
def 连接bing搜索回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
"""
|
||||
txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
|
||||
llm_kwargs gpt模型参数,如温度和top_p等,一般原样传递下去就行
|
||||
plugin_kwargs 插件模型的参数,暂时没有用武之地
|
||||
chatbot 聊天显示框的句柄,用于显示给用户
|
||||
history 聊天历史,前情提要
|
||||
system_prompt 给gpt的静默提醒
|
||||
web_port 当前软件运行的端口号
|
||||
"""
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
chatbot.append((f"请结合互联网信息回答以下问题:{txt}",
|
||||
"[Local Message] 请注意,您正在调用一个[函数插件]的模板,该模板可以实现ChatGPT联网信息综合。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。您若希望分享新的功能模组,请不吝PR!"))
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间,我们先及时地做一次界面更新
|
||||
|
||||
# ------------- < 第1步:爬取搜索引擎的结果 > -------------
|
||||
from toolbox import get_conf
|
||||
proxies, = get_conf('proxies')
|
||||
urls = bing_search(txt, proxies)
|
||||
history = []
|
||||
|
||||
# ------------- < 第2步:依次访问网页 > -------------
|
||||
max_search_result = 8 # 最多收纳多少个网页的结果
|
||||
for index, url in enumerate(urls[:max_search_result]):
|
||||
res = scrape_text(url['link'], proxies)
|
||||
history.extend([f"第{index}份搜索结果:", res])
|
||||
chatbot.append([f"第{index}份搜索结果:", res[:500]+"......"])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间,我们先及时地做一次界面更新
|
||||
|
||||
# ------------- < 第3步:ChatGPT综合 > -------------
|
||||
i_say = f"从以上搜索结果中抽取信息,然后回答问题:{txt}"
|
||||
i_say, history = input_clipping( # 裁剪输入,从最长的条目开始裁剪,防止爆token
|
||||
inputs=i_say,
|
||||
history=history,
|
||||
max_token_limit=model_info[llm_kwargs['llm_model']]['max_token']*3//4
|
||||
)
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say, inputs_show_user=i_say,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
|
||||
sys_prompt="请从给定的若干条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。"
|
||||
)
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say);history.append(gpt_say)
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
|
||||
|
||||
@ -13,11 +13,11 @@ def 同时问询(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
|
||||
web_port 当前软件运行的端口号
|
||||
"""
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
chatbot.append((txt, "正在同时咨询ChatGPT和ChatGLM……"))
|
||||
chatbot.append((txt, "正在同时咨询gpt-3.5和gpt-4……"))
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间,我们先及时地做一次界面更新
|
||||
|
||||
# llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo&api2d-gpt-3.5-turbo' # 支持任意数量的llm接口,用&符号分隔
|
||||
llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo' # 支持任意数量的llm接口,用&符号分隔
|
||||
llm_kwargs['llm_model'] = 'gpt-3.5-turbo&gpt-4' # 支持任意数量的llm接口,用&符号分隔
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=txt, inputs_show_user=txt,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
|
||||
|
||||
@ -104,7 +104,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
||||
meta_paper_info_list = meta_paper_info_list[batchsize:]
|
||||
|
||||
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."])
|
||||
"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 an academic \"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)
|
||||
|
||||
@ -1,6 +1,7 @@
|
||||
from toolbox import CatchException, update_ui
|
||||
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||
import datetime
|
||||
import datetime, re
|
||||
|
||||
@CatchException
|
||||
def 高阶功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
"""
|
||||
@ -18,12 +19,34 @@ def 高阶功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
|
||||
for i in range(5):
|
||||
currentMonth = (datetime.date.today() + datetime.timedelta(days=i)).month
|
||||
currentDay = (datetime.date.today() + datetime.timedelta(days=i)).day
|
||||
i_say = f'历史中哪些事件发生在{currentMonth}月{currentDay}日?列举两条并发送相关图片。发送图片时,请使用Markdown,将Unsplash API中的PUT_YOUR_QUERY_HERE替换成描述该事件的一个最重要的单词。'
|
||||
i_say = f'历史中哪些事件发生在{currentMonth}月{currentDay}日?用中文列举两条,然后分别给出描述事件的两个英文单词。' + '当你给出关键词时,使用以下json格式:{"KeyWords":[EnglishKeyWord1,EnglishKeyWord2]}。'
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say, inputs_show_user=i_say,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, 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 >)。"
|
||||
sys_prompt='输出格式示例:1908年,美国消防救援事业发展的“美国消防协会”成立。关键词:{"KeyWords":["Fire","American"]}。'
|
||||
)
|
||||
gpt_say = get_images(gpt_say)
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say);history.append(gpt_say)
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
|
||||
|
||||
|
||||
def get_images(gpt_say):
|
||||
def get_image_by_keyword(keyword):
|
||||
import requests
|
||||
from bs4 import BeautifulSoup
|
||||
response = requests.get(f'https://wallhaven.cc/search?q={keyword}', timeout=2)
|
||||
for image_element in BeautifulSoup(response.content, 'html.parser').findAll("img"):
|
||||
if "data-src" in image_element: break
|
||||
return image_element["data-src"]
|
||||
|
||||
for keywords in re.findall('{"KeyWords":\[(.*?)\]}', gpt_say):
|
||||
keywords = [n.strip('"') for n in keywords.split(',')]
|
||||
try:
|
||||
description = keywords[0]
|
||||
url = get_image_by_keyword(keywords[0])
|
||||
img_tag = f"\n\n"
|
||||
gpt_say += img_tag
|
||||
except:
|
||||
continue
|
||||
return gpt_say
|
||||
Binary file not shown.
@ -152,7 +152,7 @@ model_info = {
|
||||
"token_cnt": get_token_num_gpt4,
|
||||
},
|
||||
|
||||
# chatglm
|
||||
# 将 chatglm 直接对齐到 chatglm2
|
||||
"chatglm": {
|
||||
"fn_with_ui": chatglm_ui,
|
||||
"fn_without_ui": chatglm_noui,
|
||||
@ -161,6 +161,15 @@ model_info = {
|
||||
"tokenizer": tokenizer_gpt35,
|
||||
"token_cnt": get_token_num_gpt35,
|
||||
},
|
||||
"chatglm2": {
|
||||
"fn_with_ui": chatglm_ui,
|
||||
"fn_without_ui": chatglm_noui,
|
||||
"endpoint": None,
|
||||
"max_token": 1024,
|
||||
"tokenizer": tokenizer_gpt35,
|
||||
"token_cnt": get_token_num_gpt35,
|
||||
},
|
||||
|
||||
# newbing
|
||||
"newbing": {
|
||||
"fn_with_ui": newbing_ui,
|
||||
|
||||
@ -40,12 +40,12 @@ class GetGLMHandle(Process):
|
||||
while True:
|
||||
try:
|
||||
if self.chatglm_model is None:
|
||||
self.chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
|
||||
self.chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True)
|
||||
device, = get_conf('LOCAL_MODEL_DEVICE')
|
||||
if device=='cpu':
|
||||
self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).float()
|
||||
self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).float()
|
||||
else:
|
||||
self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
|
||||
self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).half().cuda()
|
||||
self.chatglm_model = self.chatglm_model.eval()
|
||||
break
|
||||
else:
|
||||
|
||||
@ -1,4 +1,3 @@
|
||||
./docs/gradio-3.32.2-py3-none-any.whl
|
||||
tiktoken>=0.3.3
|
||||
requests[socks]
|
||||
transformers
|
||||
@ -15,4 +14,4 @@ pymupdf
|
||||
openai
|
||||
numpy
|
||||
arxiv
|
||||
rich
|
||||
rich
|
||||
|
||||
@ -498,7 +498,7 @@ def on_report_generated(cookies, files, chatbot):
|
||||
else:
|
||||
report_files = find_recent_files('gpt_log')
|
||||
if len(report_files) == 0:
|
||||
return None, chatbot
|
||||
return cookies, None, chatbot
|
||||
# files.extend(report_files)
|
||||
file_links = ''
|
||||
for f in report_files: file_links += f'<br/><a href="file={os.path.abspath(f)}" target="_blank">{f}</a>'
|
||||
@ -842,4 +842,4 @@ def objload(file='objdump.tmp'):
|
||||
return
|
||||
with open(file, 'rb') as f:
|
||||
return pickle.load(f)
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user