forked from kaixindelele/ChatPaper
-
Notifications
You must be signed in to change notification settings - Fork 0
/
app.py
155 lines (128 loc) · 6.13 KB
/
app.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
import argparse
import logging
from contextlib import redirect_stdout
from io import StringIO
from pprint import pformat
from flask import Flask, Response, jsonify, request, url_for
from flask_cors import CORS
from chat_arxiv import ArxivParams, chat_arxiv_main
from chat_paper import PaperParams, chat_paper_main
from chat_response import ResponseParams, chat_response_main
from chat_reviewer import ReviewerParams, chat_reviewer_main
app = Flask(__name__)
CORS(app)
@app.route("/", methods=["GET"])
@app.route("/index", methods=["GET"])
def home():
arxiv_url = url_for("arxiv", _external=True, query="GPT-4", key_word="GPT robot", page_num=1, max_results=1, days=1,
sort="web", save_image=False, file_format="md", language="zh")
paper_url = url_for("paper", _external=True, pdf_path="", query="all: ChatGPT robot",
key_word="reinforcement learning", filter_keys="ChatGPT robot", max_results=1, sort="Relevance",
save_image=False, file_format="md", language="zh")
response_url = url_for("response", _external=True, comment_path="review_comments.txt", file_format="txt",
language="en")
reviewer_url = url_for("reviewer", _external=True, paper_path="", file_format="txt",
research_fields="computer science, artificial intelligence and reinforcement learning",
language="en")
return f'''
<h1>ChatPaper,Flask版本的优势</h1>
<p>GitHub 项目地址:<a href="https://github.com/kaixindelele/ChatPaper" target="_blank">https://github.com/kaixindelele/ChatPaper</a></p>
<p>将原始的 Python 脚本改为使用 Flask 构建的 Web 服务具有以下优点:</p>
<ul>
<li><strong>易用性</strong>:通过简单的 HTTP 请求,用户可以轻松访问和使用各个功能,无需在本地安装 Python 或其他依赖。</li>
<li><strong>跨平台兼容性</strong>:作为 Web 服务,Flask 应用程序可以在任何支持 HTTP 请求的设备和平台上运行,从而提高了应用程序的可访问性。</li>
<li><strong>可扩展性</strong>:使用 Flask 可以更轻松地扩展应用程序,以包含其他功能、中间件和 API 端点。</li>
<li><strong>易于集成</strong>:Flask 应用程序可以与其他 Web 服务和前端框架(如 React、Vue.js 等)轻松集成,从而提供更丰富的用户体验。</li>
</ul>
<h1>功能描述和调用方法</h1>
<h2>arxiv</h2>
<p>搜索 Arxiv 上的论文。参数:query, key_word, page_num, max_results, days, sort, save_image, file_format, language</p>
<p>示例:<a href="{arxiv_url}" target="_blank">{arxiv_url}</a></p>
<h2>paper</h2>
<p>搜索并分析论文。参数:pdf_path, query, key_word, filter_keys, max_results, sort, save_image, file_format, language</p>
<p>示例:<a href="{paper_url}" target="_blank">{paper_url}</a></p>
<h2>response</h2>
<p>处理论文审稿评论。参数:comment_path, file_format, language</p>
<p>示例:<a href="{response_url}" target="_blank">{response_url}</a></p>
<h2>reviewer</h2>
<p>查找论文审稿人。参数:paper_path, file_format, research_fields, language</p>
<p>示例:<a href="{reviewer_url}" target="_blank">{reviewer_url}</a></p>
'''
def process_request(main_function, params_class, default_values):
args = request.args.to_dict()
for key, value in args.items():
if key in default_values:
args[key] = type(default_values[key])(value)
params = params_class(**{**default_values, **args})
output = StringIO()
with redirect_stdout(output):
main_function(args=params)
output_str = output.getvalue()
output_lines = [line.strip() for line in output_str.split("\n") if line.strip()]
formatted_output_str = "\n".join(output_lines)
return pformat(formatted_output_str)
@app.route("/arxiv", methods=["GET"])
def arxiv():
default_values = {
"query": "GPT-4",
"key_word": "GPT robot",
"page_num": 1,
"max_results": 1,
"days": 1,
"sort": "web",
"save_image": False,
"file_format": "md",
"language": "zh"
}
return process_request(chat_arxiv_main, ArxivParams, default_values)
@app.route("/paper", methods=["GET"])
def paper():
default_values = {
"pdf_path": "",
"query": "all: ChatGPT robot",
"key_word": "reinforcement learning",
"filter_keys": "ChatGPT robot",
"max_results": 1,
"sort": "Relevance",
"save_image": False,
"file_format": "md",
"language": "zh"
}
return process_request(chat_paper_main, PaperParams, default_values)
@app.route("/response", methods=["GET"])
def response():
default_values = {
"comment_path": "review_comments.txt",
"file_format": "txt",
"language": "en"
}
return process_request(chat_response_main, ResponseParams, default_values)
@app.route("/reviewer", methods=["GET"])
def reviewer():
default_values = {
"paper_path": "",
"file_format": "txt",
"research_fields": "computer science, artificial intelligence and reinforcement learning",
"language": "en"
}
return process_request(chat_reviewer_main, ReviewerParams, default_values)
def get_log_level(args):
if args.verbose == 2:
return logging.INFO
elif args.verbose > 2:
return logging.DEBUG
else:
return logging.WARN
if __name__ == "__main__":
# Initialize the main argument parser
parser = argparse.ArgumentParser(description='Description of main script')
parser.add_argument("--debug", "-d", help="deploy debug mode",
action="store_true", default=False)
parser.add_argument("--verbose", "-v", action="count", default=1)
args = parser.parse_args()
logging.basicConfig(level=get_log_level(
args), format="%(asctime)s %(message)s", datefmt="%m/%d/%Y %I:%M:%S %p")
if args.debug:
app.run(debug=True, threaded=True, host='0.0.0.0', port=5000)
else:
app.run(debug=False, threaded=True, host='0.0.0.0', port=5000)