scrapybara-python-template: Cursor rule for Cursor

You are working with Scrapybara, a Python SDK for deploying and managing remote desktop instances for AI agents. Use this guide to properly interact with the SDK.

CORE SDK USAGE:

• Initialize client: from scrapybara import Scrapybara; client = Scrapybara(api_key="KEY")
• Instance lifecycle: instance = client.start_ubuntu(timeout_hours=1) instance.pause() # Pause to save resources instance.resume(timeout_hours=1) # Resume work instance.stop() # Terminate and clean up
• Instance types: ubuntu_instance = client.start_ubuntu(): supports bash, computer, edit, browser browser_instance = client.start_browser(): supports computer, browser windows_instance = client.start_windows(): supports computer

TYPE IMPORTS:

• Core types: from scrapybara import Scrapybara
• Instance types: from scrapybara.client import UbuntuInstance, BrowserInstance, WindowsInstance
• Tool types: from scrapybara.tools import Tool, BashTool, ComputerTool, EditTool
• Model types: from scrapybara.anthropic import Anthropic
• Message types: from pydantic import BaseModel from typing import List, Union, Optional, Any
• Error types: from scrapybara.core.api_error import ApiError

CORE INSTANCE OPERATIONS:

• Screenshots: instance.screenshot().base_64_image
• Bash commands: instance.bash(command="ls -la")
• Mouse control: instance.computer(action="move_mouse", coordinates=[x, y])
• Click actions: instance.computer(action="click_mouse", button="right", coordinates=[x, y])
• Drag actions: instance.computer(action="drag_mouse", path=[[x1, y1], [x2, y2]])
• Scroll actions: instance.computer(action="scroll", coordinates=[x, y], delta_x=0, delta_y=0)
• Key actions: instance.computer(action="press_key", keys=[keys])
• Type actions: instance.computer(action="type_text", text="Hello world")
• Wait actions: instance.computer(action="wait", duration=3)
• Get cursor position: instance.computer(action="get_cursor_position").output
• File operations: instance.file.read(path="/path/file"), instance.file.write(path="/path/file", content="data")

ACT SDK (Primary Focus):

• Purpose: Enables building computer use agents with unified tools and model interfaces
• Core components:

1. Model: Handles LLM integration (currently Anthropic) from scrapybara.anthropic import Anthropic model = Anthropic() # Or model = Anthropic(api_key="KEY") for own key
2. Tools: Interface for computer interactions
   • BashTool: Run shell commands
   • ComputerTool: Mouse/keyboard control
   • EditTool: File operations tools = [ BashTool(instance), ComputerTool(instance), EditTool(instance), ]
3. Prompt:
   • system: system prompt, recommend to use UBUNTU_SYSTEM_PROMPT, BROWSER_SYSTEM_PROMPT, WINDOWS_SYSTEM_PROMPT
   • prompt: simple user prompt
   • messages: list of messages
   • Only include either prompt or messages, not both response = client.act( model=Anthropic(), tools=tools, system=UBUNTU_SYSTEM_PROMPT, prompt="Task", on_step=handle_step ) messages = response.messages steps = response.steps text = response.text output = response.output usage = response.usage

MESSAGE HANDLING:

• Response Structure: Messages are structured with roles (user/assistant/tool) and typed content
• Content Types:
• TextPart: Simple text content TextPart(type="text", text="content")
• ImagePart: Base64 or URL images ImagePart(type="image", image="base64...", mime_type="image/png")
• ReasoningPart: Model reasoning content ReasoningPart( type="reasoning", id="id", reasoning="reasoning", signature="signature", instructions="instructions" )
• ToolCallPart: Tool invocations ToolCallPart( type="tool-call", tool_call_id="id", tool_name="bash", args={"command": "ls"} )
• ToolResultPart: Tool execution results ToolResultPart( type="tool-result", tool_call_id="id", tool_name="bash", result="output", is_error=False )