一、browser-use是什么

Browser Use 是一款開源Python庫，專為大語言模型設計的智能瀏覽器工具，目的是讓 AI 能夠像人類一樣自然地瀏覽和操作網頁。它支持多標簽頁管理、視覺識別、內容提取，并能記錄和重復執行特定動作。Browser Use 還支持開發者自定義動作，如保存數據到數據庫，文件等。支持多種主流的大型語言模型，如 DeepSeek，GPT-4 和 Claude等，并支持同時運行多個任務，具備自我修正功能，從而提高任務執行的準確性和效率。

官網：https://browser-use.com/

項目網址 ：https://github.com/browser-use/browser-use

Browser-use采用的技術棧為：

• 1、Observation：頁面解析層，采用DOM解析+截圖輔助的非視覺+視覺方案。
  • DOM解析（HTML + XPath）：Browser-use通過底層框架（如Playwright）獲取當前頁面的完整HTML結構，并提取文本、元素屬性等關鍵信息。
  • 截圖輔助：在某些情況下（如驗證碼識別、動態圖形驗證），純HTML解析可能無法直接獲取信息，此時系統會自動或按需生成頁面截圖，并將截圖作為輔助輸入傳遞給視覺模型
• 2、Thought：核心決策層，分析Observation提供的頁面信息并生成操作指令。
• 3、Action：指令執行層，微軟開發的Playwright作為瀏覽器控制框架直接與瀏覽器交互完成自動化任務。Playwright作為新一代高性能UI自動化測試框架，提供低延遲、高穩定性的瀏覽器控制能力，支持快速頁面加載和元素操作。

二、browser-use webui 主要功能

提供了全新的網頁界面，簡單好用，方便操作。
支持更多大語言模型，比如 Gemini、OpenAI、Azure 等，哦，還有最近爆火的國產大模型 DeepSeek，未來還會加更多。
支持用自己的瀏覽器，不用再反復登錄，還能錄屏。
定制了更智能的 Agent，通過優化后的提示讓瀏覽器使用更高效。

使用場景

• 自動化任務：適合重復高頻的瀏覽器操作任務，如表單填寫，信息檢索，文件下載
• 數據收集：適合爬取網絡上的數據，如爬蟲自動化測試：適合WEB UI
• 自動化測試，結合pytest輕松實現web自動化

三、使用教程

1.python 安裝

python 官網： https://www.python.org/downloads/版本必須在 3.11 以上。

2、把項目clone下來

git clone https://github.com/browser-use/web-ui.git
cd web-ui

3、安裝依賴

pip install browser-use
playwright install
pip install -r requirements.txt

4、配置環境

基于 .env.example 復制一個 .env 文件，并在 .env 文件中修改以下信息

# 路徑 Chrome 瀏覽器路徑（檢查下自己的路徑），例如
# Mac OS "/Applications/Google Chrome.app/Contents/MacOS/Google Chrome"
# Windows "C:\Program Files\Google\Chrome\Application\chrome.exe"
CHROME_PATH="/Applications/Google Chrome.app/Contents/MacOS/Google Chrome"# 瀏覽器的用戶數據路徑，例如
# Mac OS "/Users/<YourUsername>/Library/Application Support/Google/Chrome"
# Windows "C:\Users\<YourUsername>\AppData\Local\Google\Chrome\User Data"
CHROME_USER_DATA="/Users/<YourUsername>/Library/Application Support/Google/Chrome"# 還有一些大模型的 API Key 也要改
...

5、啟動

執行如下命令啟動

python webui.py --ip 127.0.0.1 --port 7788

啟動成功如下所示：

瀏覽器訪問 http://127.0.0.1:7788/，看到如下界面就成功了

6、配置

1.配置 Agent

注意，這里的 Use Vision，默認是選中狀態，如果使用的 DeepSeek 不能勾選，因為 DeepSeek 不支持視覺輸入，注意這里很多人踩坑，一定要注意。

2.配置要用的大模型

例如，下面我用的是 deepseek。

3.關于瀏覽器的一些設置

四、DeepSeek 的API獲取

DeepSeek ：https://platform.deepseek.com/api_keys

五、界面Demo 演示

輸入要執行的任務就可以點擊 Run Agent 了

以下是運行時的項目日志輸出，記錄了執行步驟

執行的過程中也會打開瀏覽器和跳轉到目標網站，按照區塊一樣對頁面元素做標注。

在 Recodings 下會記錄執行過程和反饋結果，還可以回看的。

六、代碼示例

1.創建Agent

from langchain_openai import ChatOpenAI
from browser_use import Agent
import asyncioasync def main():agent = Agent(task="Go to Reddit, search for 'browser-use' in the search bar, click on the first post and return the first comment.",llm=ChatOpenAI(model="gpt-4o"),)result = await agent.run()print(result)asyncio.run(main())

如果沒有openai-key的可以使用其他模型，下面以DeepSeek為例：

該文件在 browser-use/examples/deepseek.py

import asyncio
import osfrom dotenv import load_dotenv
from langchain_openai import ChatOpenAI
from pydantic import SecretStrfrom browser_use import Agent# dotenv
load_dotenv()api_key = os.getenv('DEEPSEEK_API_KEY', 'sk-xxxxxx')
if not api_key:raise ValueError('DEEPSEEK_API_KEY is not set')async def run_search():agent = Agent(task=("1. 在搜索框中輸入抖音并搜索"'2. 點擊搜索結果中的第一個鏈接''3. 關閉掃碼登錄'	'3. 返回第一個視頻的內容'),llm=ChatOpenAI(base_url='https://api.deepseek.com/v1',model='deepseek-chat',api_key=SecretStr(api_key),),use_vision=False,)await agent.run()if __name__ == '__main__':asyncio.run(run_search())

運行結果如下：

七、實例展示

一、爬取基金數據

llm = ChatOpenAI(model='deepseek-chat',api_key='*************',base_url='https://api.deepseek.com',temperature=0
)asyncdefmain():agent = Agent(task="""1、導航到網址:https://fund.eastmoney.com/2、點擊基金排行3、返回排行前10的基金數據，以json格式返回""",llm=llm,use_vision=False,)result = await agent.run()print(result.final_result())asyncio.run(main())

二、效果展示

1、導航到指定網址

2、點擊基金排行

3、提取top 10的基金數據

DEBUG    [browser_use] --act Execution time: 0.00 seconds
INFO     [controller] 📄  Extracted from page
: ```json
{
"top_10_funds": [{"rank": 1,"fund_code": "018124","fund_name": "永贏先進制造智選混合發起A","date": "03-07","unit_net_value": "2.1654","cumulative_net_value": "2.1654","daily_growth_rate": "2.21%","1_week": "9.15%","1_month": "17.58%","3_months": "64.06%","6_months": "191.13%","1_year": "115.94%","since_inception": "116.54%","handling_fee": "0.15%"},{"rank": 2,"fund_code": "018125","fund_name": "永贏先進制造智選混合發起C","date": "03-07","unit_net_value": "2.1501","cumulative_net_value": "2.1501","daily_growth_rate": "2.21%","1_week": "9.15%","1_month": "17.54%","3_months": "63.89%","6_months": "190.55%","1_year": "115.07%","since_inception": "115.01%","handling_fee": "0.00%"},{"rank": 3,"fund_code": "016530","fund_name": "鵬華碳中和主題混合A","date": "03-07","unit_net_value": "1.7881","cumulative_net_value": "1.7881","daily_growth_rate": "3.00%","1_week": "10.23%","1_month": "22.92%","3_months": "68.07%","6_months": "178.39%","1_year": "104.00%","since_inception": "78.81%","handling_fee": "0.15%"},{"rank": 4,"fund_code": "016531","fund_name": "鵬華碳中和主題混合C","date": "03-07","unit_net_value": "1.7685","cumulative_net_value": "1.7685","daily_growth_rate": "3.00%","1_week": "10.21%","1_month": "22.86%","3_months": "67.81%","6_months": "177.59%","1_year": "102.79%","since_inception": "76.85%","handling_fee": "0.00%"},{"rank": 5,"fund_code": "001970","fund_name": "泰信鑫選靈活配置混合A","date": "03-07","unit_net_value": "1.3310","cumulative_net_value": "1.3310","daily_growth_rate": "-1.04%","1_week": "7.25%","1_month": "4.80%","3_months": "31.00%","6_months": "125.59%","1_year": "95.45%","since_inception": "33.10%","handling_fee": "0.15%"},{"rank": 6,"fund_code": "002580","fund_name": "泰信鑫選靈活配置混合C","date": "03-07","unit_net_value": "1.3220","cumulative_net_value": "1.3220","daily_growth_rate": "-0.97%","1_week": "7.31%","1_month": "4.84%","3_months": "31.15%","6_months": "125.60%","1_year": "95.27%","since_inception": "31.67%","handling_fee": "0.00%"},{"rank": 7,"fund_code": "016295","fund_name": "新華利率債債券E","date": "03-07","unit_net_value": "1.7977","cumulative_net_value": "1.9906","daily_growth_rate": "-0.13%","1_week": "-0.06%","1_month": "-0.66%","3_months": "0.85%","6_months": "94.13%","1_year": "92.89%","since_inception": "99.00%","handling_fee": "0.00%"},{"rank": 8,"fund_code": "019457","fund_name": "平安先進制造主題股票發起A","date": "03-07","unit_net_value": "1.7593","cumulative_net_value": "1.7593","daily_growth_rate": "1.78%","1_week": "10.41%","1_month": "23.92%","3_months": "57.40%","6_months": "134.29%","1_year": "90.71%","since_inception": "75.93%","handling_fee": "0.15%"},{"rank": 9,"fund_code": "019458","fund_name": "平安先進制造主題股票發起C","date": "03-07","unit_net_value": "1.7452","cumulative_net_value": "1.7452","daily_growth_rate": "1.78%","1_week": "10.40%","1_month": "23.87%","3_months": "57.17%","6_months": "133.60%","1_year": "89.59%","since_inception": "74.52%","handling_fee": "0.00%"},{"rank": 10,"fund_code": "007713","fund_name": "華富科技動能混合A","date": "03-07","unit_net_value": "1.4600","cumulative_net_value": "1.5100","daily_growth_rate": "1.47%","1_week": "8.19%","1_month": "18.94%","3_months": "47.07%","6_months": "135.41%","1_year": "89.14%","since_inception": "51.93%","handling_fee": "0.15%"}]
}

二、結合pytest實現頁面自動化測試
異步執行需要安裝插件pytest-asyncio

pip install pytest-asyncio

@pytest.mark.asyncio
@pytest.mark.parametrize("username,password,expected", [("kevin@xxxx.com", "a123456", "kevin"),("kevin@xxxx.com", "123456", "賬號密碼輸入錯誤")])
asyncdeftest_login(username, password, expected):agent = Agent(task=f"""1、導航到網址:https://xxxxxxx.com2、輸入用戶名:{username}, 密碼:{password}3、點擊登錄按鈕4、驗證是否登錄成功,登錄成功返回{expected}""",llm=llm,use_vision=False,)result = await agent.run()assert expected in str(result.final_result())

三、總結

Browser Use 深度集成大語言模型（LLM），通過語義理解與視覺決策鏈實現零硬編碼自動化，徹底顛覆傳統腳本開發模式。AI 自動解析頁面結構、動態生成操作路徑，無需人工編寫 XPath/CSS 定位器，開發效率提升 5 倍以上，尤其擅長處理動態驗證、反爬策略及多步驟交互場景，成為金融數據抓取、跨平臺測試的新一代智能引擎。