test_browser_use.py

import pdb

from dotenv import load_dotenv

load_dotenv()
import sys

sys.path.append(".")
import asyncio
import os
import sys
from pprint import pprint

from browser_use import Agent
from browser_use.agent.views import AgentHistoryList

from src.utils import utils


async def test_browser_use_org():
    from browser_use.browser.browser import Browser, BrowserConfig
    from browser_use.browser.context import (
        BrowserContextConfig,
        BrowserContextWindowSize,
    )

    # llm = utils.get_llm_model(
    #     provider="azure_openai",
    #     model_name="gpt-4o",
    #     temperature=0.8,
    #     base_url=os.getenv("AZURE_OPENAI_ENDPOINT", ""),
    #     api_key=os.getenv("AZURE_OPENAI_API_KEY", ""),
    # )

    # llm = utils.get_llm_model(
    #     provider="deepseek",
    #     model_name="deepseek-chat",
    #     temperature=0.8
    # )
    
    llm = utils.get_llm_model(
        provider="ollama", model_name="deepseek-r1:14b", temperature=0.5
    )

    window_w, window_h = 1920, 1080
    use_vision = False
    use_own_browser = False
    if use_own_browser:
        chrome_path = os.getenv("CHROME_PATH", None)
        if chrome_path == "":
            chrome_path = None
    else:
        chrome_path = None
        
    tool_calling_method = "json_schema"  # setting to json_schema when using ollma

    browser = Browser(
        config=BrowserConfig(
            headless=False,
            disable_security=True,
            chrome_instance_path=chrome_path,
            extra_chromium_args=[f"--window-size={window_w},{window_h}"],
        )
    )
    async with await browser.new_context(
        config=BrowserContextConfig(
            trace_path="./tmp/traces",
            save_recording_path="./tmp/record_videos",
            no_viewport=False,
            browser_window_size=BrowserContextWindowSize(
                width=window_w, height=window_h
            ),
        )
    ) as browser_context:
        agent = Agent(
            task="go to google.com and type 'OpenAI' click search and give me the first url",
            llm=llm,
            browser_context=browser_context,
            use_vision=use_vision,
            tool_calling_method=tool_calling_method
        )
        history: AgentHistoryList = await agent.run(max_steps=10)

        print("Final Result:")
        pprint(history.final_result(), indent=4)

        print("\nErrors:")
        pprint(history.errors(), indent=4)

        # e.g. xPaths the model clicked on
        print("\nModel Outputs:")
        pprint(history.model_actions(), indent=4)

        print("\nThoughts:")
        pprint(history.model_thoughts(), indent=4)
    # close browser
    await browser.close()


async def test_browser_use_custom():
    from browser_use.browser.context import BrowserContextWindowSize
    from browser_use.browser.browser import BrowserConfig
    from playwright.async_api import async_playwright

    from src.agent.custom_agent import CustomAgent
    from src.agent.custom_prompts import CustomSystemPrompt, CustomAgentMessagePrompt
    from src.browser.custom_browser import CustomBrowser
    from src.browser.custom_context import BrowserContextConfig
    from src.controller.custom_controller import CustomController

    window_w, window_h = 1920, 1080
    
    # llm = utils.get_llm_model(
    #     provider="openai",
    #     model_name="gpt-4o",
    #     temperature=0.8,
    #     base_url=os.getenv("OPENAI_ENDPOINT", ""),
    #     api_key=os.getenv("OPENAI_API_KEY", ""),
    # )

    llm = utils.get_llm_model(
        provider="azure_openai",
        model_name="gpt-4o",
        temperature=0.8,
        base_url=os.getenv("AZURE_OPENAI_ENDPOINT", ""),
        api_key=os.getenv("AZURE_OPENAI_API_KEY", ""),
    )

    # llm = utils.get_llm_model(
    #     provider="gemini",
    #     model_name="gemini-2.0-flash-exp",
    #     temperature=1.0,
    #     api_key=os.getenv("GOOGLE_API_KEY", "")
    # )

    # llm = utils.get_llm_model(
    #     provider="deepseek",
    #     model_name="deepseek-reasoner",
    #     temperature=0.8
    # )
    
    # llm = utils.get_llm_model(
    #     provider="deepseek",
    #     model_name="deepseek-chat",
    #     temperature=0.8
    # )

    # llm = utils.get_llm_model(
    #     provider="ollama", model_name="qwen2.5:7b", temperature=0.5
    # )
    
    # llm = utils.get_llm_model(
    #     provider="ollama", model_name="deepseek-r1:14b", temperature=0.5
    # )

    controller = CustomController()
    use_own_browser = True
    disable_security = True
    use_vision = False  # Set to False when using DeepSeek
    
    max_actions_per_step = 1
    playwright = None
    browser = None
    browser_context = None

    try:
        extra_chromium_args = [f"--window-size={window_w},{window_h}"]
        if use_own_browser:
            chrome_path = os.getenv("CHROME_PATH", None)
            if chrome_path == "":
                chrome_path = None
            chrome_user_data = os.getenv("CHROME_USER_DATA", None)
            if chrome_user_data:
                extra_chromium_args += [f"--user-data-dir={chrome_user_data}"]
        else:
            chrome_path = None
        browser = CustomBrowser(
            config=BrowserConfig(
                headless=False,
                disable_security=disable_security,
                chrome_instance_path=chrome_path,
                extra_chromium_args=extra_chromium_args,
            )
        )
        browser_context = await browser.new_context(
            config=BrowserContextConfig(
                trace_path="./tmp/traces",
                save_recording_path="./tmp/record_videos",
                no_viewport=False,
                browser_window_size=BrowserContextWindowSize(
                    width=window_w, height=window_h
                ),
            )
        )
        agent = CustomAgent(
            task="Search 'Nvidia' and give me the first url",
            add_infos="",  # some hints for llm to complete the task
            llm=llm,
            browser=browser,
            browser_context=browser_context,
            controller=controller,
            system_prompt_class=CustomSystemPrompt,
            agent_prompt_class=CustomAgentMessagePrompt,
            use_vision=use_vision,
            max_actions_per_step=max_actions_per_step
        )
        history: AgentHistoryList = await agent.run(max_steps=100)

        print("Final Result:")
        pprint(history.final_result(), indent=4)

        print("\nErrors:")
        pprint(history.errors(), indent=4)

        # e.g. xPaths the model clicked on
        print("\nModel Outputs:")
        pprint(history.model_actions(), indent=4)

        print("\nThoughts:")
        pprint(history.model_thoughts(), indent=4)
        # close browser
    except Exception:
        import traceback

        traceback.print_exc()
    finally:
        # 显式关闭持久化上下文
        if browser_context:
            await browser_context.close()

        # 关闭 Playwright 对象
        if playwright:
            await playwright.stop()
        if browser:
            await browser.close()

if __name__ == "__main__":
    # asyncio.run(test_browser_use_org())
    asyncio.run(test_browser_use_custom())