AI in Test Automation - Browser Use - Web UI - Part 3 - Write Tasks in Code

from langchain_openai import ChatOpenAI
from browser_use import Agent
import asyncio
from dotenv import load_dotenv
load_dotenv()

async def main():
    agent = Agent(
        task="Compare the price of gpt-4o and DeepSeek-V3",
        llm=ChatOpenAI(model="gpt-4o"),
    )
    await agent.run()

asyncio.run(main())

OPENAI_API_KEY=

ANTHROPIC_API_KEY=

AZURE_OPENAI_ENDPOINT=
AZURE_OPENAI_KEY=

GEMINI_API_KEY=

DEEPSEEK_API_KEY=

import asyncio

from langchain_google_genai import ChatGoogleGenerativeAI
from browser_use import Agent
from pydantic import SecretStr
import os
from dotenv import load_dotenv

# Load the environment variables
load_dotenv()

# Get the API key from the environment
api_key = os.getenv("GEMINI_API_KEY")

# Initialize the model
llm = ChatGoogleGenerativeAI(model='gemini-2.0-flash-exp', api_key=SecretStr(os.getenv('GEMINI_API_KEY')))

# Create agent with the model
agent = Agent(
    task="Vào trang web https://www.google.com tìm từ khóa 'anhtester' và click vào link đầu tiên lấy cái câu giới thiệu ra cho tôi.",
    llm=llm
)


async def main():
    await agent.run()


asyncio.run(main())

pip install -U langchain-google-genai

{
  "introduction": "Anh Tester chia sẻ kiến thức Tester, khóa học Testing miễn phí về Automation Testing, Playwright, Selenium C#, Selenium Java, Appium, WinAppDriver, Jenkins, Katalon Studio, akaAT Studio và kiến thức tài liệu về Manual Testing"
}

import asyncio

from langchain_google_genai import ChatGoogleGenerativeAI
from browser_use import Agent
from pydantic import SecretStr
import os
from dotenv import load_dotenv

# Load the environment variables
load_dotenv()

# Get the API key from the environment
api_key = os.getenv("GEMINI_API_KEY")

# Initialize the model
llm = ChatGoogleGenerativeAI(model='gemini-2.0-flash-exp', api_key=SecretStr(os.getenv('GEMINI_API_KEY')))

# Create agent with the model
agent = Agent(
    task='''
        Vào trang web https://www.google.com
        Tìm từ khóa 'anhtester' và click vào link đầu tiên lấy cái câu giới thiệu ra cho tôi
        Tiếp tục click vào menu Blog
        Tìm bài viết có tiêu đề 'API Testing Interview Questions and Answers 2024' và click vào bài viết đó
        Lấy câu trả lời từ câu hỏi 'What is API Testing?' bên trong bài viết đó ra giúp tôi
        ''',
    llm=llm
)


async def main():
    await agent.run()


asyncio.run(main())

import asyncio

from langchain_google_genai import ChatGoogleGenerativeAI
from browser_use import Agent
from pydantic import SecretStr
import os
from dotenv import load_dotenv

# Load the environment variables
load_dotenv()

# Get the API key from the environment
api_key = os.getenv("GEMINI_API_KEY")

# Initialize the model
llm = ChatGoogleGenerativeAI(model='gemini-2.0-flash-exp', api_key=SecretStr(os.getenv('GEMINI_API_KEY')))


async def main():
    # Create agent1 with the model
    agent1 = Agent(
        task='''
            Vào trang web https://anhtester.com
            Tìm khoá học có tên 'Khoá học Python dành cho Tester'
            Lấy thông tin học phí ra giúp tôi
            ''',
        llm=llm
    )
    await agent1.run()

    # Create agent2 with the model
    agent2 = Agent(
        task='''
            Go to 'https://crm.anhtester.com/admin/authentication'
            Login with email and password: 'admin@example.com' and '123456'
            Click menu Customers to open the Customer page
            Search the customer 'Anh Tester' on search field in customer page
            Get the Company column of the table
            Verify the Company column results contains 'Anh Tester' value on table
            ''',
        llm=llm
    )
    await agent2.run()


asyncio.run(main())

import asyncio

from browser_use.controller.service import Controller
from langchain_google_genai import ChatGoogleGenerativeAI
from browser_use import Agent
from pydantic import SecretStr, BaseModel
import os
from dotenv import load_dotenv
import json

# Load the environment variables
load_dotenv()

# Get the API key from the environment
api_key = os.getenv("GEMINI_API_KEY")

# Initialize the model
llm = ChatGoogleGenerativeAI(model='gemini-2.0-flash-exp', api_key=SecretStr(os.getenv('GEMINI_API_KEY')))


class ExtractResults(BaseModel):
    anhtester_page_introduction: str
    api_answer: str


controller = Controller(output_model=ExtractResults)

# Create agent with the model
agent = Agent(
    task='''
        Vào trang web https://www.google.com
        Tìm từ khóa 'anhtester' và click vào link đầu tiên lấy cái câu giới thiệu ra cho tôi
        Tiếp tục click vào menu Blog
        Tìm bài viết có tiêu đề 'API Testing Interview Questions and Answers 2024' và click vào bài viết đó
        Lấy câu trả lời từ câu hỏi 'What is API Testing?' bên trong bài viết đó ra giúp tôi
        ''',
    llm=llm,
    controller=controller
)


async def main():
    history = await agent.run()

    result = history.final_result()  # Lấy kết quả cuối cùng

    result_dict = json.loads(result)  # Chuyển đổi chuỗi JSON thành dictionary

    # Truy xuất dữ liệu
    print(f"\nKết quả Introduction: {result_dict["anhtester_page_introduction"]}")  # Xem kết quả
    print(f"\nKết quả API Answer: {result_dict["api_answer"]}")

    # Kiểm tra kết quả với các giá trị mong muốn (so sánh chứa chuỗi)
    assert "Anh Tester chia sẻ kiến thức Tester" in result_dict["anhtester_page_introduction"]
    assert "API Testing is a type of software testing" in result_dict["api_answer"]


asyncio.run(main())

class ExtractResults(BaseModel):
    anhtester_page_introduction: str
    api_answer: str​

controller = Controller(output_model=ExtractResults)

agent = Agent(
    task=task,
    llm=llm,
    controller=controller
)

history = await agent.run()

result = history.final_result() # Lấy kết quả cuối cùng

result_dict = json.loads(result)  # Chuyển đổi chuỗi JSON thành dictionary

import asyncio

from browser_use.browser.browser import Browser, BrowserConfig
from browser_use.browser.context import BrowserContext, BrowserContextConfig
from langchain_google_genai import ChatGoogleGenerativeAI
from browser_use import Agent
from pydantic import SecretStr
import os
from dotenv import load_dotenv

# Load the environment variables
load_dotenv()

# Get the API key from the environment
api_key = os.getenv("GEMINI_API_KEY")

# Initialize the model
llm = ChatGoogleGenerativeAI(model='gemini-2.0-flash-exp', api_key=SecretStr(os.getenv('GEMINI_API_KEY')))

# Create BrowserConfig of Browser Use provided
browser_config = BrowserConfig(
    headless=False,
    disable_security=True
)

# Create browser instance with the BrowserConfig
browser = Browser(config=browser_config)

# Ensure project_root is a string
project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '.'))
recording_path = os.path.join(project_root, 'exports', 'recordings')
trace_path = os.path.join(project_root, 'exports', 'traces')

# Create the directory if it does not exist
if not os.path.exists(recording_path):
    os.makedirs(recording_path)
if not os.path.exists(trace_path):
    os.makedirs(trace_path)

# Create BrowserContextConfig of Browser Use provided
browser_context_config = BrowserContextConfig(
    wait_for_network_idle_page_load_time=3.0,
    browser_window_size={'width': 1600, 'height': 900},
    locale='vi-VN',
    highlight_elements=True,
    viewport_expansion=-1,
    save_recording_path=os.path.join(project_root, 'exports', 'recordings'),
    trace_path=os.path.join(project_root, 'exports', 'traces')
)

# Create browser context with the BrowserContextConfig
browser_context = BrowserContext(
    browser=browser,
    config=browser_context_config
)

# Create agent with the model and browser context
agent = Agent(
    task="Vào trang web https://www.google.com tìm từ khóa 'anhtester' và click vào link đầu tiên lấy cái câu giới thiệu ra cho tôi.",
    llm=llm,
    browser_context=browser_context
)


async def main():
    await agent.run()

    # Close the browser context and browser
    await browser_context.close()
    await browser.close()


asyncio.run(main())

"""
	Configuration for the Browser.

	Default values:
		headless: True
			Whether to run browser in headless mode

		disable_security: True
			Disable browser security features

		extra_chromium_args: []
			Extra arguments to pass to the browser

		wss_url: None
			Connect to a browser instance via WebSocket

		cdp_url: None
			Connect to a browser instance via CDP

		chrome_instance_path: None
			Path to a Chrome instance to use to connect to your normal browser
			e.g. '/Applications/Google\ Chrome.app/Contents/MacOS/Google\ Chrome'
"""

"""
	Configuration for the BrowserContext.

	Default values:
	    cookies_file: None
	        Path to cookies file for persistence

	        disable_security: True
	                Disable browser security features

	    minimum_wait_page_load_time: 0.5
	        Minimum time to wait before getting page state for LLM input

	        wait_for_network_idle_page_load_time: 1.0
	                Time to wait for network requests to finish before getting page state.
	                Lower values may result in incomplete page loads.

	    maximum_wait_page_load_time: 5.0
	        Maximum time to wait for page load before proceeding anyway

	    wait_between_actions: 1.0
	        Time to wait between multiple per step actions

	    browser_window_size: {
	            'width': 1280,
	            'height': 1100,
	        }
	        Default browser window size

	    no_viewport: False
	        Disable viewport

	    save_recording_path: None
	        Path to save video recordings

	    save_downloads_path: None
	        Path to save downloads to

	    trace_path: None
	        Path to save trace files. It will auto name the file with the TRACE_PATH/{context_id}.zip

	    locale: None
	        Specify user locale, for example en-GB, de-DE, etc. Locale will affect navigator.language value, Accept-Language request header value as well as number and date formatting rules. If not provided, defaults to the system default locale.

	    user_agent: 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/85.0.4183.102 Safari/537.36'
	        custom user agent to use.

	    highlight_elements: True
	        Highlight elements in the DOM on the screen

	    viewport_expansion: 500
	        Viewport expansion in pixels. This amount will increase the number of elements which are included in the state what the LLM will see. If set to -1, all elements will be included (this leads to high token usage). If set to 0, only the elements which are visible in the viewport will be included.

	    allowed_domains: None
	        List of allowed domains that can be accessed. If None, all domains are allowed.
	        Example: ['example.com', 'api.example.com']

	    include_dynamic_attributes: bool = True
	        Include dynamic attributes in the CSS selector. If you want to reuse the css_selectors, it might be better to set this to False.
"""