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import gradio as gr
import os
import openai
from auto_backgrounds import generate_backgrounds, fake_generator, generate_draft
from utils.file_operations import hash_name
# todo:
# 2. update QQ group and Organization cards
# 4. add auto_polishing function
# 5. Use some simple method for simple tasks (including: writing abstract, conclusion, generate keywords, generate figures...)
# 5.1 Use GPT 3.5 for abstract, conclusion, ... (or may not)
# 5.2 Use local LLM to generate keywords, figures, ...
# 5.3 Use embedding to find most related papers (find a paper dataset)
# 5.4 Use Semantic Scholar API instead of Arxiv API.
# 6. get logs when the procedure is not completed.
openai_key = os.getenv("OPENAI_API_KEY")
access_key_id = os.getenv('AWS_ACCESS_KEY_ID')
secret_access_key = os.getenv('AWS_SECRET_ACCESS_KEY')
if access_key_id is None or secret_access_key is None:
print("Access keys are not provided. Outputs cannot be saved to AWS Cloud Storage.\n")
IS_CACHE_AVAILABLE = False
else:
IS_CACHE_AVAILABLE = True
if openai_key is None:
print("OPENAI_API_KEY is not found in environment variables. The output may not be generated.\n")
IS_OPENAI_API_KEY_AVAILABLE = False
else:
openai.api_key = openai_key
try:
openai.Model.list()
IS_OPENAI_API_KEY_AVAILABLE = True
except Exception as e:
IS_OPENAI_API_KEY_AVAILABLE = False
def clear_inputs(text1, text2):
return "", ""
def wrapped_generator(title, description, openai_key = None,
template = "ICLR2022",
cache_mode = IS_CACHE_AVAILABLE, generator=None):
# if `cache_mode` is True, then follow the following steps:
# check if "title"+"description" have been generated before
# if so, download from the cloud storage, return it
# if not, generate the result.
if generator is None:
# todo: add a Dropdown to select which generator to use.
# generator = generate_backgrounds
generator = generate_draft
# generator = fake_generator
if openai_key is not None:
openai.api_key = openai_key
openai.Model.list()
if cache_mode:
from utils.storage import list_all_files, download_file, upload_file
# check if "title"+"description" have been generated before
input_dict = {"title": title, "description": description, "generator": "generate_draft"} #todo: modify here also
file_name = hash_name(input_dict) + ".zip"
file_list = list_all_files()
# print(f"{file_name} will be generated. Check the file list {file_list}")
if file_name in file_list:
# download from the cloud storage, return it
download_file(file_name)
return file_name
else:
# generate the result.
# output = fake_generate_backgrounds(title, description, openai_key) # todo: use `generator` to control which function to use.
output = generator(title, description, template, "gpt-4")
upload_file(output)
return output
else:
# output = fake_generate_backgrounds(title, description, openai_key)
output = generator(title, description, template, "gpt-4")
return output
theme = gr.themes.Monochrome(font=gr.themes.GoogleFont("Questrial")).set(
background_fill_primary='#E5E4E2',
background_fill_secondary = '#F6F6F6',
button_primary_background_fill="#281A39"
)
with gr.Blocks(theme=theme) as demo:
gr.Markdown('''
# Auto-Draft: 文献整理辅助工具
本Demo提供对[Auto-Draft](https://github.com/CCCBora/auto-draft)的auto_draft功能的测试。通过输入想要生成的论文名称(比如Playing atari with deep reinforcement learning),即可由AI辅助生成论文模板.
***2023-05-03 Update***: 在公开版本中为大家提供了输入OpenAI API Key的地址, 如果有GPT-4的API KEY的话可以在这里体验!
在这个Huggingface Organization里也提供一定额度的免费体验: [AUTO-ACADEMIC](https://huggingface.co/organizations/auto-academic/share/HPjgazDSlkwLNCWKiAiZoYtXaJIatkWDYM).
如果有更多想法和建议欢迎加入QQ群里交流, 如果我在Space里更新了Key我会第一时间通知大家. 群号: ***249738228***.
## 用法
输入想要生成的论文名称(比如Playing Atari with Deep Reinforcement Learning), 点击Submit, 等待大概十分钟, 下载.zip格式的输出,在Overleaf上编译浏览.
''')
with gr.Row():
with gr.Column(scale=2):
key = gr.Textbox(value=openai_key, lines=1, max_lines=1, label="OpenAI Key", visible=not IS_OPENAI_API_KEY_AVAILABLE)
# generator = gr.Dropdown(choices=["学术论文", "文献总结"], value="文献总结", label="Selection", info="目前支持生成'学术论文'和'文献总结'.", interactive=True)
title = gr.Textbox(value="Playing Atari with Deep Reinforcement Learning", lines=1, max_lines=1, label="Title", info="论文标题")
description = gr.Textbox(lines=5, label="Description (Optional)", visible=False)
with gr.Row():
clear_button = gr.Button("Clear")
submit_button = gr.Button("Submit")
with gr.Column(scale=1):
style_mapping = {True: "color:white;background-color:green", False: "color:white;background-color:red"} #todo: to match website's style
availability_mapping = {True: "AVAILABLE", False: "NOT AVAILABLE"}
gr.Markdown(f'''## Huggingface Space Status
当`OpenAI API`显示AVAILABLE的时候这个Space可以直接使用.
当`OpenAI API`显示NOT AVAILABLE的时候这个Space可以通过在左侧输入OPENAI KEY来使用. 需要有GPT-4的API权限.
当`Cache`显示AVAILABLE的时候, 所有的输入和输出会被备份到我的云储存中. 显示NOT AVAILABLE的时候不影响实际使用.
`OpenAI API`: <span style="{style_mapping[IS_OPENAI_API_KEY_AVAILABLE]}">{availability_mapping[IS_OPENAI_API_KEY_AVAILABLE]}</span>. `Cache`: <span style="{style_mapping[IS_CACHE_AVAILABLE]}">{availability_mapping[IS_CACHE_AVAILABLE]}</span>.''')
file_output = gr.File(label="Output")
clear_button.click(fn=clear_inputs, inputs=[title, description], outputs=[title, description])
submit_button.click(fn=wrapped_generator, inputs=[title, description, key], outputs=file_output)
demo.queue(concurrency_count=1, max_size=5, api_open=False)
demo.launch()
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