Delete chat_reviewer.py

chat_reviewer.py

@@ -1,183 +0,0 @@
-import numpy as np
-import os
-import re
-import datetime
-import time
-import openai, tenacity
-import argparse
-import configparser
-import json
-import tiktoken
-from get_paper_from_pdf import Paper
-
-# 定义Reviewer类
-class Reviewer:
-    # 初始化方法，设置属性
-    def __init__(self, args=None):
-        if args.language == 'en':
-            self.language = 'English'
-        elif args.language == 'zh':
-            self.language = 'Chinese'
-        else:
-            self.language = 'Chinese'        
-        # 创建一个ConfigParser对象
-        self.config = configparser.ConfigParser()
-        # 读取配置文件
-        self.config.read('apikey.ini')
-        # 获取某个键对应的值        
-        self.chat_api_list = self.config.get('OpenAI', 'OPENAI_API_KEYS')[1:-1].replace('\'', '').split(',')
-        self.chat_api_list = [api.strip() for api in self.chat_api_list if len(api) > 5]
-        self.cur_api = 0
-        self.file_format = args.file_format        
-        self.max_token_num = 4096
-        self.encoding = tiktoken.get_encoding("gpt2")
-    
-    def validateTitle(self, title):
-        # 修正论文的路径格式
-        rstr = r"[\/\\\:\*\?\"\<\>\|]" # '/ \ : * ? " < > |'
-        new_title = re.sub(rstr, "_", title) # 替换为下划线
-        return new_title
-
-
-    def review_by_chatgpt(self, paper_list):
-        htmls = []
-        for paper_index, paper in enumerate(paper_list):
-            sections_of_interest = self.stage_1(paper)
-            # extract the essential parts of the paper
-            text = ''
-            text += 'Title:' + paper.title + '. '
-            text += 'Abstract: ' + paper.section_texts['Abstract']
-            intro_title = next((item for item in paper.section_names if 'ntroduction' in item), None)
-            if intro_title is not None:
-                text += 'Introduction: ' + paper.section_texts[intro_title]
-            # Similar for conclusion section
-            conclusion_title = next((item for item in paper.section_names if 'onclusion' in item), None)
-            if conclusion_title is not None:
-                text += 'Conclusion: ' + paper.section_texts[conclusion_title]
-            for heading in sections_of_interest:
-                if heading in paper.section_names:
-                    text += heading + ': ' + paper.section_texts[heading]
-            chat_review_text = self.chat_review(text=text)            
-            htmls.append('## Paper:' + str(paper_index+1))
-            htmls.append('\n\n\n')            
-            htmls.append(chat_review_text)
-            
-            # 将审稿意见保存起来
-            date_str = str(datetime.datetime.now())[:13].replace(' ', '-')
-            try:
-                export_path = os.path.join('./', 'output_file')
-                os.makedirs(export_path)
-            except:
-                pass                             
-            mode = 'w' if paper_index == 0 else 'a'
-            file_name = os.path.join(export_path, date_str+'-'+self.validateTitle(paper.title)+"."+self.file_format)
-            self.export_to_markdown("\n".join(htmls), file_name=file_name, mode=mode)
-            htmls = []
-
-
-    def stage_1(self, paper):
-        htmls = []
-        text = ''
-        text += 'Title: ' + paper.title + '. '
-        text += 'Abstract: ' + paper.section_texts['Abstract']
-        openai.api_key = self.chat_api_list[self.cur_api]
-        self.cur_api += 1
-        self.cur_api = 0 if self.cur_api >= len(self.chat_api_list)-1 else self.cur_api
-        messages = [
-            {"role": "system",
-             "content": f"You are a professional reviewer in the field of {args.research_fields}. "
-                        f"I will give you a paper. You need to review this paper and discuss the novelty and originality of ideas, correctness, clarity, the significance of results, potential impact and quality of the presentation. "
-                        f"Due to the length limitations, I am only allowed to provide you the abstract, introduction, conclusion and at most two sections of this paper."
-                        f"Now I will give you the title and abstract and the headings of potential sections. "
-                        f"You need to reply at most two headings. Then I will further provide you the full information, includes aforementioned sections and at most two sections you called for.\n\n"
-                        f"Title: {paper.title}\n\n"
-                        f"Abstract: {paper.section_texts['Abstract']}\n\n"
-                        f"Potential Sections: {paper.section_names[2:-1]}\n\n"
-                        f"Follow the following format to output your choice of sections:"
-                        f"{{chosen section 1}}, {{chosen section 2}}\n\n"},
-            {"role": "user", "content": text},
-        ]
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=messages,
-        )
-        result = ''
-        for choice in response.choices:
-            result += choice.message.content
-        print(result)
-        return result.split(',')
-
-    @tenacity.retry(wait=tenacity.wait_exponential(multiplier=1, min=4, max=10),
-                    stop=tenacity.stop_after_attempt(5),
-                    reraise=True)
-    def chat_review(self, text):
-        openai.api_key = self.chat_api_list[self.cur_api]
-        self.cur_api += 1
-        self.cur_api = 0 if self.cur_api >= len(self.chat_api_list)-1 else self.cur_api
-        review_prompt_token = 1000        
-        text_token = len(self.encoding.encode(text))
-        input_text_index = int(len(text)*(self.max_token_num-review_prompt_token)/text_token)
-        input_text = "This is the paper for your review:" + text[:input_text_index]
-        with open('ReviewFormat.txt', 'r') as file:   # 读取特定的审稿格式
-            review_format = file.read()
-        messages=[
-                {"role": "system", "content": "You are a professional reviewer in the field of "+args.research_fields+". Now I will give you a paper. You need to give a complete review opinion according to the following requirements and format:"+ review_format +" Please answer in {}.".format(self.language)},
-                {"role": "user", "content": input_text},
-            ]
-                
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=messages,
-        )
-        result = ''
-        for choice in response.choices:
-            result += choice.message.content
-        print("********"*10)
-        print(result)
-        print("********"*10)
-        print("prompt_token_used:", response.usage.prompt_tokens)
-        print("completion_token_used:", response.usage.completion_tokens)
-        print("total_token_used:", response.usage.total_tokens)
-        print("response_time:", response.response_ms/1000.0, 's')                    
-        return result        
-                        
-    def export_to_markdown(self, text, file_name, mode='w'):
-        # 使用markdown模块的convert方法，将文本转换为html格式
-        # html = markdown.markdown(text)
-        # 打开一个文件，以写入模式
-        with open(file_name, mode, encoding="utf-8") as f:
-            # 将html格式的内容写入文件
-            f.write(text)                    
-
-def main(args):            
-
-    reviewer1 = Reviewer(args=args)
-    # 开始判断是路径还是文件：   
-    paper_list = []     
-    if args.paper_path.endswith(".pdf"):
-        paper_list.append(Paper(path=args.paper_path))            
-    else:
-        for root, dirs, files in os.walk(args.paper_path):
-            print("root:", root, "dirs:", dirs, 'files:', files) #当前目录路径
-            for filename in files:
-                # 如果找到PDF文件，则将其复制到目标文件夹中
-                if filename.endswith(".pdf"):
-                    paper_list.append(Paper(path=os.path.join(root, filename)))        
-    print("------------------paper_num: {}------------------".format(len(paper_list)))        
-    [print(paper_index, paper_name.path.split('\\')[-1]) for paper_index, paper_name in enumerate(paper_list)]
-    reviewer1.review_by_chatgpt(paper_list=paper_list)
-
-    
-    
-if __name__ == '__main__':    
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--paper_path", type=str, default='', help="path of papers")
-    parser.add_argument("--file_format", type=str, default='txt', help="output file format")
-    parser.add_argument("--research_fields", type=str, default='computer science, artificial intelligence and reinforcement learning', help="the research fields of paper")
-    parser.add_argument("--language", type=str, default='en', help="output lauguage, en or zh")
-    
-    args = parser.parse_args()
-    start_time = time.time()
-    main(args=args)    
-    print("review time:", time.time() - start_time)
-