diff --git a/MyBullet.py b/MyBullet.py
deleted file mode 100644
index bbb7766..0000000
--- a/MyBullet.py
+++ /dev/null
@@ -1,162 +0,0 @@
-import re
-import requests
-from bs4 import BeautifulSoup
-from collections import Counter
-import pandas as pd
-import time
-
-# 定义需要爬取的视频数量和搜索内容
-BV_NUM = 100  # 需要获取的视频数量
-SEARCH_CONTENT = "吉伊卡哇chiikawa"  # 搜索关键词
-
-# 请求头，防止反爬
-HEADERS = {
-    'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36 Edg/126.0.0.0',
-    "Referer": "https://search.bilibili.com/all?"
-}
-
-# 根据搜索关键词，爬取指定数量的视频BVID
-def get_bv(num):
-    """
-    参数： num: 需要获取的BVID数量
-    返回值： bv_list, 一个包含视频BVID的集合
-    """
-    bv_list = set()  # 使用集合存储获取的BVID，以去重
-    page = 1  # 初始化页码
-    
-    while len(bv_list) < num:
-        # 构造搜索页面的URL
-        search_url = f"https://search.bilibili.com/all?keyword={SEARCH_CONTENT}&page={page}"
-        response = requests.get(search_url, headers=HEADERS)
-        
-        # 使用正则表达式提取BVID
-        pattern = re.compile(r'aid:.*?bvid:"(?P<bvs>.*?)",')
-        matches = pattern.finditer(response.text)
-        
-        # 将BVID加入集合
-        for match in matches:
-            bv_list.add(match.group("bvs"))
-            # 如果达到了指定数量，直接返回结果
-            if len(bv_list) >= num:
-                return bv_list
-        
-        # 增加页码，继续爬取下一页
-        page += 1
-    
-    return bv_list
-
-# 通过bv号获取视频cid，进一步获取弹幕内容
-def fetch_bullet_screen(bv_list):
-    """
-    参数 bv_list: 包含BV号的列表
-    返回值: 弹幕内容列表
-    """
-    my_bullet = []  # 存放所有弹幕的列表
-    for bv in bv_list:
-        cid_url = f"https://api.bilibili.com/x/player/pagelist?bvid={bv}&jsonp=jsonp"
-        response_cid = requests.get(cid_url, headers=HEADERS)
-        response_cid_json = response_cid.json()
-        
-        # 获取视频的cid
-        cid = response_cid_json.get("data", [{}])[0].get("cid")
-        if not cid:
-            print(f"无法获取 {bv} 的cid")
-            continue
-        
-        # 获取对应cid的弹幕内容
-        response_bullet = requests.get(f"https://comment.bilibili.com/{cid}.xml", headers=HEADERS)
-        response_bullet.encoding = "utf-8"
-        
-        # 解析XML格式的弹幕数据
-        soup = BeautifulSoup(response_bullet.text, "xml")
-        danmus = soup.find_all("d")
-        
-        # 将弹幕内容添加到列表中
-        my_bullet.extend([danmu.text for danmu in danmus])
-        print(f"已成功爬取 {bv} 的弹幕")
-    
-    return my_bullet
-
-# 分析弹幕内容，提取包含AI相关词语的完整句子
-def analyze_bullet_screen_with_ai_sentences(my_bullet , ai_keywords):
-    """
-    参数1： my_bullet: 弹幕内容列表
-    参数2： ai_keywords:关键词
-    返回值: 包含AI关键词的完整句子列表
-    返回值: 包含AI关键词的列表
-    返回值: 关键词统计
-    """
-    
-    ai_sentences = []  # 包含关键词的完整句子
-    keyword_only_sentences = []  # 只包含关键词的句子
-    keyword_counts = Counter()  # 计数器，用于统计每个关键词的频次
-
-    for bullet in my_bullet:
-        contains_keyword = False
-        for keyword in ai_keywords:
-            if keyword in bullet:
-                contains_keyword = True
-                ai_sentences.append(bullet)
-                keyword_only_sentences.append(keyword)
-                keyword_counts[keyword] += 1  # 更新关键词计数
-            
-        if contains_keyword:
-            # 只保留包含的关键词
-            keywords_in_bullet = [keyword for keyword in ai_keywords if keyword in bullet]
-    
-    return ai_sentences, keyword_only_sentences, keyword_counts
-
-# 将关键词统计信息保存到Excel文件
-def save_keyword_counts_to_excel(keyword_counts, path='./Chiikawa/keyword_counts.xlsx'):
-    """
-    参数1: keyword_counts: Counter对象，包含每个关键词及其出现次数
-    参数2: path: Excel文件名
-    """
-    counts_df = pd.DataFrame(keyword_counts.items(), columns=["关键词", "出现次数"])
-    
-    # 按出现次数排序，从高到低
-    counts_df.sort_values(by='出现次数', ascending=False, inplace=True)
-    
-    counts_df.to_excel(path, index=False)
-    print(f"关键词统计已保存到 {path}")
-
-# 将包含AI关键词的句子保存到Excel文件
-def save_sentences_to_excel(ai_sentences, keyword_only_sentences,path1='./Chiikawa/sentences.xlsx',path2='./Chiikawa/keyword_only_sentences.xlsx',choose1=True ,choose2=True):
-    """
-    参数1: ai_sentences: 包含AI关键词的句子列表
-    参数2: keyword_only_sentences: 只包含AI关键字的列表
-    参数3: path1: Excel文件名,保存AI关键词句子列表
-    参数4: path2: Excel文件名,保存AI关键词
-    参数5: choose1: 是否保存path1
-    参数6: choose2: 是否保存path2
-    """
-    
-    if(choose1):
-        ai_df = pd.DataFrame(ai_sentences, columns=["包含关键词的弹幕"])
-        ai_df.to_excel(path1, index=False)
-    if(choose2):
-        keyword_only_df = pd.DataFrame(keyword_only_sentences, columns=["关键词"])
-        keyword_only_df.to_excel(path2, index=False)
-    
-    print(f"包含关键词的弹幕句子已保存到 {path1}")
-    print(f"只包含关键词的句子已保存到 {path2}")
-
-def main_bullet():
-    bv_list = get_bv(BV_NUM)
-    # print(bv_list)
-    
-    bullet_screens = fetch_bullet_screen(bv_list)
-    print(f"获取了 {len(bullet_screens)} 条弹幕")
-    
-    ai_keywords = [
-        "537", "小八", "乌萨奇", "吉伊",'飞鼠','手工凯','可爱','呀哈'
-    ]
-    
-    ai_sentences, keyword_only_sentences, keyword_counts = analyze_bullet_screen_with_ai_sentences(bullet_screens, ai_keywords)
-    print(f"提取了 {len(ai_sentences)} 条包含相关关键词的弹幕")
-    
-    save_sentences_to_excel(ai_sentences, keyword_only_sentences, choose2 = False)
-    save_keyword_counts_to_excel(keyword_counts)
-
-if __name__ == '__main__':
-    main_bullet()
\ No newline at end of file