pip install stagehand-py

from crewai import Agent, Task, Crew
from crewai_tools import StagehandTool
from stagehand.schemas import AvailableModel

# Initialize the tool with your API keys using a context manager
with StagehandTool(
    api_key="your-browserbase-api-key",
    project_id="your-browserbase-project-id",
    model_api_key="your-llm-api-key",  # OpenAI 또는 Anthropic API 키
    model_name=AvailableModel.CLAUDE_3_7_SONNET_LATEST,  # 선택 사항: 사용할 모델 지정
) as stagehand_tool:
    # Create an agent with the tool
    researcher = Agent(
        role="Web Researcher",
        goal="Find and summarize information from websites",
        backstory="I'm an expert at finding information online.",
        verbose=True,
        tools=[stagehand_tool],
    )

    # Create a task that uses the tool
    research_task = Task(
        description="Go to https://www.example.com and tell me what you see on the homepage.",
        agent=researcher,
    )

    # Run the crew
    crew = Crew(
        agents=[researcher],
        tasks=[research_task],
        verbose=True,
    )

    result = crew.kickoff()
    print(result)

from crewai import Agent, Task, Crew
from crewai_tools import StagehandTool
from stagehand.schemas import AvailableModel

# Initialize the tool with your API keys
stagehand_tool = StagehandTool(
    api_key="your-browserbase-api-key",
    project_id="your-browserbase-project-id",
    model_api_key="your-llm-api-key",
    model_name=AvailableModel.CLAUDE_3_7_SONNET_LATEST,
)

try:
    # Create an agent with the tool
    researcher = Agent(
        role="Web Researcher",
        goal="Find and summarize information from websites",
        backstory="I'm an expert at finding information online.",
        verbose=True,
        tools=[stagehand_tool],
    )

    # Create a task that uses the tool
    research_task = Task(
        description="Go to https://www.example.com and tell me what you see on the homepage.",
        agent=researcher,
    )

    # Run the crew
    crew = Crew(
        agents=[researcher],
        tasks=[research_task],
        verbose=True,
    )

    result = crew.kickoff()
    print(result)
finally:
    # Explicitly clean up resources
    stagehand_tool.close()

# Perform an action (default behavior)
result = stagehand_tool.run(
    instruction="Click the login button", 
    url="https://example.com",
    command_type="act"  # Default, so can be omitted
)

# Fill out a form
result = stagehand_tool.run(
    instruction="Fill the contact form with name 'John Doe', email 'john@example.com', and message 'Hello world'", 
    url="https://example.com/contact"
)

# 모든 상품 정보 추출
result = stagehand_tool.run(
    instruction="Extract all product names, prices, and descriptions", 
    url="https://example.com/products",
    command_type="extract"
)

# 선택자를 사용하여 특정 정보 추출
result = stagehand_tool.run(
    instruction="Extract the main article title and content", 
    url="https://example.com/blog/article",
    command_type="extract",
    selector=".article-container"  # 선택적 CSS 선택자
)

# 인터랙티브 요소 찾기
result = stagehand_tool.run(
    instruction="Find all interactive elements in the navigation menu", 
    url="https://example.com",
    command_type="observe"
)

# 폼 필드 식별
result = stagehand_tool.run(
    instruction="Identify all the input fields in the registration form", 
    url="https://example.com/register",
    command_type="observe",
    selector="#registration-form"
)

stagehand_tool = StagehandTool(
    api_key="your-browserbase-api-key",
    project_id="your-browserbase-project-id",
    model_api_key="your-llm-api-key",
    model_name=AvailableModel.CLAUDE_3_7_SONNET_LATEST,
    dom_settle_timeout_ms=5000,  # DOM이 안정될 때까지 더 오래 대기
    headless=True,  # 브라우저를 헤드리스 모드로 실행
    self_heal=True,  # 오류에서 복구를 시도
    wait_for_captcha_solves=True,  # CAPTCHA 해결을 기다림
    verbose=1,  # 로깅 상세 수준 제어 (0-3)
)