diff --git "a/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/.keep" "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/.keep"
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git "a/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/README.md" "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/README.md"
new file mode 100644
index 0000000000000000000000000000000000000000..da79b6e2da74f59db38e8a05af0f6e5040c8210b
--- /dev/null
+++ "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/README.md"
@@ -0,0 +1,57 @@
+### 项目简介
+
+本项目是一个基于搜索引擎的信息获取系统，通过搜索引擎为模型检索所需的信息。系统利用大语言模型（LLM）将用户问题拆解为子问题，结合搜索引擎并行获取相关内容，最终生成针对用户问题的精准摘要。该项目可补充现有的 RAG（Retrieval-Augmented Generation）和 `chat_to_db` 模块，特别适用于处理涉及最新信息或本地文档库未包含的内容。
+
+### 项目流程图
+
+![项目流程图](./agent.png)
+
+1. **输入问题与子问题拆解**
+
+   - 系统接收用户的问题，使用大语言模型将其拆解为多个子问题，增加搜索的广度和深度。
+
+2. **并行搜索**
+
+   - 系统将主问题和子问题通过搜索引擎并行搜索，获取相关网页的标题和链接，并过滤无效链接。
+
+3. **基于 TF-IDF 筛选最优标题**
+
+   - 使用 TF-IDF 和余弦相似度计算标题与问题的相关性，筛选出最优的链接，并去重，确保搜索结果的质量。
+
+4. **网页爬取与内容过滤**
+
+   - 爬取筛选出的网页内容，过滤乱码、广告页面和无效内容，仅保留有效的文本信息，提升信息的准确性。
+
+5. **生成摘要**
+
+   - 将爬取的内容与原问题和子问题整合，使用大语言模型生成针对问题的精准摘要，并返回给用户。
+
+### 可调节参数
+
+运行程序时，可以通过命令行参数调整程序的行为：
+
+- `--qury`：所提问的问题（默认值："请问NLP是什么？"）。
+- `--model_path`：模型路径（默认值：`"/home/nfs02/model/Qwen1.5-14B-Chat"`）。
+- `--max_new_tokens`：生成文本的最大长度，控制摘要的字数（默认值：`500`）。
+- `--summary`：是否生成总结，布尔值，`True` 或 `False`（默认值：`True`）。
+- `--splitQFlag`：是否将问题拆解为子问题，布尔值，`True` 或 `False`（默认值：`True`）。
+- `--mainTopn`：主问题的 Top N 网页选择，用于控制爬取的网页数量（默认值：`3`）。
+- `--subTopn`：子问题的 Top N 网页选择（默认值：`1`）。
+
+### 安装与运行
+
+1. **克隆项目仓库：**
+
+   ```bash
+   git clone https://gitee.com/hupeng2023/open-source-summer.git
+   cd repo(请修改为对应目录)
+
+2. **安装依赖：**
+
+   ```bash
+   pip install -r requirements.txt
+
+3. **运行程序：**
+
+   ```bash
+   python main.py --qury "请问NLP是什么？"
diff --git "a/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/Searchagent.py" "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/Searchagent.py"
new file mode 100644
index 0000000000000000000000000000000000000000..07577428b32ef3e1aca6c1d67b968bc6d5b5f686
--- /dev/null
+++ "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/Searchagent.py"
@@ -0,0 +1,368 @@
+import requests
+from bs4 import BeautifulSoup
+from promptSet import prompt,user_agent_pool
+import torch
+import re
+import random
+import concurrent.futures
+from urllib.parse import urlparse
+from collections import Counter
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.metrics.pairwise import cosine_similarity
+from typing import List, Optional
+from readability import Document
+import chardet
+import time
+import os
+from modelSet import getModel
+import argparse
+
+TIMEOUT=1.5 # 网页请求超时时间
+MAX_TOKENS=4000 # 网页+问题的输入文本最大长度
+black_list: Optional[List[str]] = [
+    'enoN', 'researchgate.net','zhihu.com' # 知乎爬不下来，知乎好像有api。
+]
+
+video_sites = [
+    "youtube.com", "vimeo.com", "dailymotion.com", "youku.com",
+    "bilibili.com", "v.qq.com", "iqiyi.com", "netflix.com",
+    "hulu.com", "primevideo.com"
+]
+
+all_filtered_sites = list(set(video_sites + black_list))
+
+def is_video_site(url):
+    """判断链接是否属于常见视频网站"""
+    parsed_url = urlparse(url)
+    domain = parsed_url.netloc
+    return any(filtered_site in domain for filtered_site in all_filtered_sites)
+
+def filtByTFIDF(query, results, top_n=1):
+    # 计算TF-IDF特征,去选择最相关的结果
+    titles=[result["title"] for result in results]
+    vectorizer = TfidfVectorizer().fit_transform([query] + titles)
+    vectors = vectorizer.toarray()
+    
+    # 计算相似度
+    cosine_similarities = cosine_similarity(vectors[0:1], vectors[1:]).flatten()
+    
+    # 根据相似度对结果进行排序
+    sorted_indices = cosine_similarities.argsort()[::-1][:top_n]
+    filtered_results = [results[i] for i in sorted_indices]
+    
+    return filtered_results
+
+
+def baidu_search(query, max_results=5, top_n=1,timeout=TIMEOUT):
+    """从百度搜索中获取搜索结果并过滤无关链接"""
+    # 构建百度搜索的URL
+    url = f"https://www.baidu.com/s?wd={query}"
+    
+    # 发送GET请求
+    headers = {
+        "User-Agent": random.choice(user_agent_pool)}
+    try:
+        response = requests.get(url, headers=headers,timeout=timeout)
+    except requests.RequestException as e:
+        print(f"无法访问 {url}: {e}")
+        return []
+
+    # 解析HTML内容
+    soup = BeautifulSoup(response.text, "html.parser")
+    
+    # 提取搜索结果标题和链接
+    results = []
+    for item in soup.find_all('h3', class_='t'):
+        if len(results) >= max_results:
+            break
+        title = item.get_text()
+        link = item.a['href']
+        
+        # 过滤掉常见视频网站的链接
+        if not is_video_site(link):
+            results.append({"title": title, "link": link, "query": query})
+    
+    if len(results) <= top_n:
+        return results
+
+    return filtByTFIDF(query, results, top_n=top_n)
+
+
+
+def decodeQList(output_text):
+    # 使用正则表达式匹配列表中的每个子问题
+    # 假设子问题列表格式为 ["子问题1", "子问题2", ...]
+    pattern = r'"\s*(.*?)\s*"'
+    matches = re.findall(pattern, output_text)
+    
+    # 提取出每个子问题并返回一个列表
+    sub_questions = [match for match in matches]
+    
+    return sub_questions
+
+
+def splitQ(query):
+    # 使用模型生成文本
+    context=prompt['splitQ'].format(question=query)
+    response = getModelResultByLLM(context)
+    # Print the response text
+    query_list = decodeQList(response)
+    query_list = [query] + query_list
+    query_list = list(Counter(query_list).keys())
+    print(query_list)
+    return query_list
+
+
+def fetch_page_content_old(link):
+    headers = {
+        "User-Agent": random.choice(user_agent_pool)
+    }
+    try:
+        response = requests.get(link, headers=headers)
+        response.raise_for_status()  # 检查请求是否成功
+        soup = BeautifulSoup(response.text, "html.parser")
+        
+        # 选取主要内容的可能标签
+        main_content = soup.find('article') or soup.find('div', class_='content') or soup.find('div', class_='main') or soup.find('div', class_='article-body')
+        
+        # 如果找不到指定的内容块，则使用 <p> 标签作为默认内容
+        if main_content:
+            paragraphs = main_content.find_all('p')
+        else:
+            paragraphs = soup.find_all('p')
+
+        # 过滤掉可能的无关内容
+        content = '\n'.join([p.get_text() for p in paragraphs if p.get_text(strip=True)])
+
+        return content.strip() if content else None
+
+    except requests.RequestException as e:
+        print(f"无法访问 {link}: {e}")
+        return None
+
+def is_page_valid(text, threshold=0.8):
+    # 过滤乱码和无效内容的网页
+    # 使用正则表达式匹配中文字符
+    chinese_pattern = re.compile(r'[\u4e00-\u9fff]')
+    # 匹配数字
+    digit_pattern = re.compile(r'\d')
+    # 匹配英语字母
+    english_pattern = re.compile(r'[a-zA-Z]')
+    # 匹配中英文常见标点符号
+    punctuation_pattern = re.compile(r'[，。？！：；、“”‘’《》〈〉【】\[\](),.!?\'":;]')
+
+    # 确保文本不为空
+    if not text or len(text) == 0:
+        return False  # 如果文本为空，认为是乱码
+
+    total_count = len(text)
+
+    # 统计中文、数字、英语字符和标点符号的数量
+    valid_count = (
+        len(chinese_pattern.findall(text)) +
+        len(digit_pattern.findall(text)) +
+        len(english_pattern.findall(text)) +
+        len(punctuation_pattern.findall(text))
+    )
+    
+    # 计算有效字符比例
+    valid_ratio = valid_count / total_count
+
+    # 如果有效字符比例超过阈值，则返回True表示内容有效，否则返回False
+    return valid_ratio >= threshold
+
+
+def clean_html_content(html_content):
+    # 去除 HTML 标签
+    soup = BeautifulSoup(html_content, "html.parser")
+    text = soup.get_text()
+
+    # 移除多余的空行和空格
+    text = re.sub(r'\n+', '\n', text)
+    text = re.sub(r'\s+', ' ', text).strip()
+
+    # 去除常见的符号和无关内容
+    text = re.sub(r'[<>|*{}]', '', text)
+
+    return text
+
+
+def fetch_page_content(url,timeout=TIMEOUT):
+    headers = {
+        "User-Agent": random.choice(user_agent_pool),
+        "Accept-Language": "en-US,en;q=0.9",
+        "Accept-Encoding": "gzip, deflate, br",
+        "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8",
+        "Connection": "keep-alive",
+    }
+    try:
+        with requests.Session() as session:
+            session.headers.update(headers)
+            
+            # 使用Session获取页面内容
+            response = session.get(url, timeout=timeout)
+            response.raise_for_status()  # 检查请求是否成功
+            detected_encoding = chardet.detect(response.content)['encoding']
+            if detected_encoding:
+                response.encoding = detected_encoding  # 设置检测到的编码
+            doc = Document(response.text)
+            content = doc.summary()
+            # 清理内容
+            cleaned_content = clean_html_content(content)
+    except requests.RequestException as e:
+        print(f"Error fetching content from {url}: {e}")
+        return None 
+    return cleaned_content
+
+
+# 检查是否为重定向链接并返回最终的链接（如果有重定向）
+def resolve_redirect(link):
+    try:
+        # 检查是否为重定向链接
+        response = requests.head(link, allow_redirects=False)
+        if 300 <= response.status_code < 400:
+            # 重定向链接，获取重定向目标
+            redirect_url = response.headers.get('Location')
+            if redirect_url:
+                return redirect_url  # 返回重定向后的目标链接
+        return link  # 如果没有重定向，返回原始链接
+    except Exception as e:
+        print(f"Error checking redirection for {link}: {e}")
+        return link  # 出错时返回原始链接
+
+def cleanResults(search_results,redirect=True):
+    # 排除重复的link和None值
+    filtered_results = []
+    if not redirect:
+        for loc,result in enumerate(search_results):
+            if result is None or result["link"] in [res["link"] for res in filtered_results]:
+                continue
+            filtered_results.append(result)
+            # 并行检查重定向并替换链接
+    else:
+        with concurrent.futures.ThreadPoolExecutor() as executor:
+            resolved_links = executor.map(lambda result: resolve_redirect(result["link"]), search_results)
+            # 遍历 search_results，并根据返回的 resolved_links 更新链接
+            for result, final_link in zip(search_results, resolved_links):
+                if any(site in final_link for site in black_list + video_sites):
+                    continue
+
+                # 检查重复的链接
+                if final_link in [res["link"] for res in filtered_results]:
+                    continue
+
+                # 更新结果中的链接为重定向目标（如果有）
+                result["link"] = final_link
+                filtered_results.append(result)
+    return filtered_results
+
+def search(query,mainTopn=3,subTopn=1,summary=True,splitQFlag=True):
+    # 拆分问题为子问题，增加上原问题并去重
+    if splitQFlag:
+        query_list = splitQ(query)
+    else:
+        query_list = [query]
+
+    # 使用并行的方式搜索每个子问题
+    search_results = []
+    top_nSet=[mainTopn] + [subTopn]*(len(query_list)-1)
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        results = executor.map(lambda loc_q: baidu_search(loc_q[1], max_results=5, top_n=top_nSet[loc_q[0]]), enumerate(query_list))
+        for result in results:
+            search_results.extend(result)
+
+    print(search_results)
+    # 过滤掉重复的链接和None值
+    search_results=cleanResults(search_results)
+
+    # 并行爬取每个链接的内容
+    page_contents = []
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        links = [result["link"] for result in search_results]
+        contents = executor.map(fetch_page_content, links)
+        # 将结果按顺序添加回 search_results 中
+        for result, content in zip(search_results, contents):
+            if content and is_page_valid (content):
+                result["content"] = content
+                page_contents.append(result)
+
+
+    if summary:
+        return summaryResultByLLM(page_contents)
+    return page_contents
+
+
+def getModelResultByLLM(text,max_tokens=MAX_TOKENS):
+    # 使用模型生成文本
+    text=text[:min(max_tokens, len(text))]
+    text = tokenizer.apply_chat_template(
+        [{"role": "user", "content": text}],
+        tokenize=False,
+    add_generation_prompt=True
+    )
+    model_inputs = tokenizer([text], return_tensors="pt")['input_ids'].to(device)
+    # input_text= tokenizer.decode(model_inputs[0], skip_special_tokens=True)
+    # print(f"输入文本: {input_text}")
+    # 在不更新梯度的情况下生成结果
+    with torch.no_grad():
+        generated_ids = model.module.generate(
+            input_ids=model_inputs,
+            max_new_tokens=max_new_tokens,
+        )
+
+    # 确保正确计算生成的token，并排除输入部分
+    generated_ids = [
+        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs, generated_ids)
+    ]
+    
+    # 将生成的token ID解码为可读文本
+    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    
+    return response
+
+def summaryResultByLLM(page_contents):
+    # 将搜索结果和子问题拼接成一个文本，并使用模型筛选关键信息
+    link=[content["link"] for content in page_contents]
+    main_query = page_contents[0]['query']
+    mainAnswer = ""
+    subq=""
+    answer=""
+    query =None
+    for loc, content in enumerate(page_contents):
+        if content['query'] == main_query:
+            mainAnswer+=prompt['pageItem'].format(id=loc, content=content['content'])
+        elif content['query'] == query:
+            answer+=prompt['pageItem'].format(id=loc, content=content['content'])
+        else:
+            if query:
+                subq+=prompt['subq'].format(subq=query,answers=answer,subqLast=prompt['subq'])
+            query = content['query']
+            answer=prompt['pageItem'].format(id=loc, content=content['content'])
+    if query:
+        if subq!="":
+            subq=subq.format(subq=query,answers=answer,subqLast="")
+        else:
+            subq=prompt['subq'].format(subq=query,answers=answer,subqLast="")
+    context=prompt['summary'].format(question=main_query,answers=mainAnswer,subq=subq)
+    infrence_time = time.time()
+    response=getModelResultByLLM(context)
+    infrence_time = time.time()-infrence_time
+    print(f"总结推理时间: {infrence_time:.2f}秒")
+    return response, link
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="解析模型相关参数的示例。")
+    parser.add_argument('--qury', type=str, default="请问NLP是什么？", help='所提问的问题')
+    parser.add_argument('--model_path', type=str, default="/home/nfs02/model/Qwen1.5-14B-Chat", help='模型路径')
+    parser.add_argument('--max_new_tokens', type=int, default=500, help='生成文本的最大长度')
+    parser.add_argument('--summary', type=bool, default=True, help='是否生成总结')
+    parser.add_argument('--splitQFlag', type=bool, default=True, help='是否分割子问题')
+    parser.add_argument('--mainTopn', type=int, default=3, help='主任务的 top n 网页选择')
+    parser.add_argument('--subTopn', type=int, default=1, help='子任务的 top n 网页选择')
+    args = parser.parse_args()
+
+    model_path = args.model_path
+    model, tokenizer, device = getModel(model_path)
+
+    max_new_tokens = args.max_new_tokens
+    print(search(args.qury,mainTopn=args.mainTopn,subTopn=args.subTopn,summary=args.summary,splitQFlag=args.splitQFlag))
\ No newline at end of file
diff --git "a/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/agent.png" "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/agent.png"
new file mode 100644
index 0000000000000000000000000000000000000000..2d30b4c70e9fd62ed31ae47d8c7c93742ffc0170
Binary files /dev/null and "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/agent.png" differ
diff --git "a/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/modelSet.py" "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/modelSet.py"
new file mode 100644
index 0000000000000000000000000000000000000000..889b63e27f7ed84f82b0d59e05192f1674137e45
--- /dev/null
+++ "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/modelSet.py"
@@ -0,0 +1,24 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+from transformers import BertTokenizer, BertModel
+# import bitsandbytes as bnb
+# import os
+# os.environ["CUDA_VISIBLE_DEVICES"] = "2,3"
+
+# 加载模型和tokenizer
+def getModel(model_path = "/home/nfs02/model/Qwen1.5-14B-Chat"):
+    tokenizer = AutoTokenizer.from_pretrained(model_path)
+    # 加载模型,8bit
+    model = AutoModelForCausalLM.from_pretrained(model_path, load_in_8bit=True)
+    if torch.cuda.device_count() >= 1:
+        print(f"使用 {torch.cuda.device_count()} 块 GPU!")
+        model = torch.nn.DataParallel(model)
+    # 如果有GPU可用，使用GPU，否则使用CPU cuda
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    model.to(device)
+    return model, tokenizer, device
+
+bertFlag = False
+if bertFlag:
+    bertTokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
+    bertModel = BertModel.from_pretrained('bert-base-uncased')
\ No newline at end of file
diff --git "a/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/promptSet.py" "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/promptSet.py"
new file mode 100644
index 0000000000000000000000000000000000000000..8df7704b81384a5129f056835792b538905c5521
--- /dev/null
+++ "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/promptSet.py"
@@ -0,0 +1,193 @@
+prompt={}
+prompt['splitQ'] = """
+现在是2024年，你是一个拆分问题的智能助手，负责将"需拆分问题"拆分为可通过搜索回答的子问题。
+
+## 任务介绍
+将问题拆分为多个单一、具体的子问题，便于搜索获取答案。每个子问题应涉及一个特定的知识点、时间、地点、人物或事件。请避免复合问题（如多个知识点的问题或者多个事物的比较加筛选）或重复提问（提问已经提问过的问题）。子问题必须完整独立，避免使用模糊表达，如"该组织，以上内容"。
+
+
+## 返回格式
+返回一个列表，每个元素为一个子问题。如果不可拆分，请返回空列表。
+
+## 样例
+样例问题：什么是生成式 AI？
+答案：["生成式模型定义", "生成式模型的运作原理是什么？", "生成式模型的应用有哪些？"]
+样例问题：中国的2023年的GDP是多少？
+答案：[]
+
+需拆分问题：{question}
+"""
+
+prompt['summary'] = """
+根据问题和拆解出的子问题，筛选有助于回答问题的网页内容，并在300字内总结。每个关键点需标明网页ID，格式为`[[int]]`，多个ID用`[[id_1]][[id_2]]`表示。
+
+- 回答需逻辑清晰、结构分明，易于理解。
+- 确保每个关键点引用对应的搜索结果来源，保持专业、严谨的表达。
+- 回答必须完整，避免使用模糊表达，如"基于上述内容"，最终展示的内容不包含网页内容。
+- 统一语法和词汇，保持文档一致性和连贯性。
+- 由于网页过长，网页内容可能被截断，请专注于抽取关键信息。
+
+用户问题：{question} {answers} {subq}
+"""
+
+
+prompt['subq'] = "\n子问题：{subq} {answers} {subqLast}"
+
+prompt['pageItem'] = "\n搜索到的网页ID：{id} 网页内容：{content}"
+
+
+
+user_agent_pool = [  # User-Agent池
+    # Cent Browser 4.3.9.248，Chromium 86.0.4240.198，2021.01
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.198 Safari/537.36',
+
+    # Edge
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.63 Safari/537.36 Edg/93.0.961.38',
+    # 2021.09
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.63 Safari/537.36 Edg/93.0.961.44',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.63 Safari/537.36 Edg/93.0.961.47',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.82 Safari/537.36 Edg/93.0.961.52',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36 Edg/94.0.992.31',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36 Edg/94.0.992.37',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.71 Safari/537.36 Edg/94.0.992.38',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.81 Safari/537.36 Edg/94.0.992.47',
+    # 2021.10
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.81 Safari/537.36 Edg/94.0.992.50',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.54 Safari/537.36 Edg/95.0.1020.30',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.54 Safari/537.36 Edg/95.0.1020.40',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.69 Safari/537.36 Edg/95.0.1020.44',
+    # 2021.11
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.69 Safari/537.36 Edg/95.0.1020.53',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.45 Safari/537.36 Edg/96.0.1054.29',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.55 Safari/537.36 Edg/96.0.1054.34',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.55 Safari/537.36 Edg/96.0.1054.41',
+    # 2021.12
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.55 Safari/537.36 Edg/96.0.1054.43',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.93 Safari/537.36 Edg/96.0.1054.53',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.110 Safari/537.36 Edg/96.0.1054.62',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36 Edg/97.0.1072.55',
+    # 2022.01
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36 Edg/97.0.1072.62',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.99 Safari/537.36 Edg/97.0.1072.69',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.99 Safari/537.36 Edg/97.0.1072.76',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.80 Safari/537.36 Edg/98.0.1108.43',
+    # 2022.02
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.80 Safari/537.36 Edg/98.0.1108.50',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.102 Safari/537.36 Edg/98.0.1108.55',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.102 Safari/537.36 Edg/98.0.1108.56',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.102 Safari/537.36 Edg/98.0.1108.62',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.51 Safari/537.36 Edg/99.0.1150.30',
+    # 2022.03
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.51 Safari/537.36 Edg/99.0.1150.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.51 Safari/537.36 Edg/99.0.1150.39',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.74 Safari/537.36 Edg/99.0.1150.46',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.74 Safari/537.36 Edg/99.0.1150.52',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.74 Safari/537.36 Edg/99.0.1150.55',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.60 Safari/537.36 Edg/100.0.1185.29',
+    # 2022.04
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.75 Safari/537.36 Edg/100.0.1185.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.75 Safari/537.36 Edg/100.0.1185.39',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.127 Safari/537.36 Edg/100.0.1185.44',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.127 Safari/537.36 Edg/100.0.1185.50',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.41 Safari/537.36 Edg/101.0.1210.32',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.54 Safari/537.36 Edg/101.0.1210.39',
+    # 2022.05
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.64 Safari/537.36 Edg/101.0.1210.47',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.64 Safari/537.36 Edg/101.0.1210.53',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.5005.63 Safari/537.36 Edg/102.0.1245.30',
+    # 2022.06
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.5005.63 Safari/537.36 Edg/102.0.1245.33',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.5005.63 Safari/537.36 Edg/102.0.1245.39',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.5005.124 Safari/537.36 Edg/102.0.1245.41',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.5005.124 Safari/537.36 Edg/102.0.1245.44',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.53 Safari/537.36 Edg/103.0.1264.37',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.66 Safari/537.36 Edg/103.0.1264.44',
+    # 2022.07
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.114 Safari/537.36 Edg/103.0.1264.49',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.114 Safari/537.36 Edg/103.0.1264.62',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.134 Safari/537.36 Edg/103.0.1264.71',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.134 Safari/537.36 Edg/103.0.1264.77',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.5112.81 Safari/537.36 Edg/104.0.1293.47',
+    # 2022.08
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.5112.81 Safari/537.36 Edg/104.0.1293.54',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.5112.102 Safari/537.36 Edg/104.0.1293.63',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.5112.102 Safari/537.36 Edg/104.0.1293.70',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36 Edg/105.0.1343.27',
+    # 2022.09
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36 Edg/105.0.1343.33',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36 Edg/105.0.1343.42',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36 Edg/105.0.1343.50',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36 Edg/105.0.1343.53',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/106.0.0.0 Safari/537.36 Edg/106.0.1370.34',
+    # 2022.10
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/106.0.0.0 Safari/537.36 Edg/106.0.1370.37',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/106.0.0.0 Safari/537.36 Edg/106.0.1370.42',
+
+    # Chrome
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.63 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.54 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.71 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.81 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.54 Safari/537.36',
+    # 2021.10
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.69 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.45 Safari/537.36',
+    # 2021.11
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.93 Safari/537.36',
+    # 2021.12
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.110 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36',
+    # 2022.01
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.99 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.81 Safari/537.36',
+    # 2022.02
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.82 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.102 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.51 Safari/537.36',
+    # 2022.03
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.74 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.82 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.60 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.75 Safari/537.36',
+    # 2022.04
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.88 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.127 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.41 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.54 Safari/537.36',
+    # 2022.05
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.64 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.67 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.5005.63 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.5005.115 Safari/537.36',
+    # 2022.06
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.53 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.66 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.114 Safari/537.36',
+    # 2022.07
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.5060.134 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.5112.81 Safari/537.36',
+    # 2022.08
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.5112.102 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.5195.54 Safari/537.36',
+    # 2022.09
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.5195.102 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.5195.127 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/106.0.5249.91 Safari/537.36',
+    # 2022.10
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/106.0.5249.103 Safari/537.36',
+
+    # Chrome Beta
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.41 Safari/537.36',
+    # 2021.09
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.17 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.32 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.40 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.49 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.18 Safari/537.36',
+    # 2021.10
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.27 Safari/537.36',
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.35 Safari/537.36',
+    # 2021.11
+    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.45 Safari/537.36'
+]
\ No newline at end of file
diff --git "a/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/requirements.txt" "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/requirements.txt"
new file mode 100644
index 0000000000000000000000000000000000000000..ccbe4dcafeb09866210d194b890db99626741f70
--- /dev/null
+++ "b/summer2024EulerCopilot\346\231\272\350\203\275\346\220\234\347\264\242Agent\346\217\222\344\273\266\345\274\200\345\217\221/requirements.txt"
@@ -0,0 +1,9 @@
+torch
+transformers==4.41.0
+scikit-learn
+requests
+beautifulsoup4
+lxml
+readability
+chardet
+