mirror of
https://github.com/trycua/computer.git
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147 lines
4.4 KiB
Python
147 lines
4.4 KiB
Python
"""
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Example usage of the agent library with docstring-based tool definitions.
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"""
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import asyncio
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import logging
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from agent import ComputerAgent
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from computer import Computer
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from computer.helpers import sandboxed
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@sandboxed()
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def read_file(location: str) -> str:
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"""Read contents of a file
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Parameters
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----------
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location : str
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Path to the file to read
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Returns
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-------
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str
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Contents of the file or error message
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"""
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try:
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with open(location, 'r') as f:
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return f.read()
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except Exception as e:
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return f"Error reading file: {str(e)}"
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def save_note(content: str, filename: str = "note.txt") -> str:
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"""Save content to a note file
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Parameters
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----------
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content : str
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Content to save to the file
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filename : str, optional
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Name of the file to save to (default is "note.txt")
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Returns
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-------
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str
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Success or error message
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"""
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try:
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with open(filename, 'w') as f:
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f.write(content)
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return f"Saved note to {filename}"
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except Exception as e:
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return f"Error saving note: {str(e)}"
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def calculate(a: int, b: int) -> int:
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"""Calculate the sum of two integers
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Parameters
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----------
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a : int
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First integer
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b : int
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Second integer
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Returns
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-------
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int
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Sum of the two integers
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"""
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return a + b
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async def main():
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"""Example usage of ComputerAgent with different models"""
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# Example 1: Using Claude with computer and custom tools
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print("=== Example 1: Claude with Computer ===")
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import os
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import dotenv
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import json
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dotenv.load_dotenv()
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assert os.getenv("CUA_CONTAINER_NAME") is not None, "CUA_CONTAINER_NAME is not set"
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assert os.getenv("CUA_API_KEY") is not None, "CUA_API_KEY is not set"
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async with Computer(
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os_type="linux",
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provider_type="cloud",
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name=os.getenv("CUA_CONTAINER_NAME") or "",
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api_key=os.getenv("CUA_API_KEY") or ""
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) as computer:
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agent = ComputerAgent(
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# Supported models:
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# == OpenAI CUA (computer-use-preview) ==
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model="openai/computer-use-preview",
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# == Anthropic CUA (Claude > 3.5) ==
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# model="anthropic/claude-opus-4-20250514",
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# model="anthropic/claude-sonnet-4-20250514",
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# model="anthropic/claude-3-7-sonnet-20250219",
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# model="anthropic/claude-3-5-sonnet-20241022",
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# == UI-TARS ==
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# model="huggingface-local/ByteDance-Seed/UI-TARS-1.5-7B",
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# TODO: add local mlx provider
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# model="mlx-community/UI-TARS-1.5-7B-6bit",
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# model="ollama_chat/0000/ui-tars-1.5-7b",
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# == Omniparser + Any LLM ==
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# model="omniparser+..."
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# model="omniparser+anthropic/claude-opus-4-20250514",
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tools=[computer],
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only_n_most_recent_images=3,
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verbosity=logging.INFO,
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trajectory_dir="trajectories",
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use_prompt_caching=True,
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max_trajectory_budget={ "max_budget": 1.0, "raise_error": True, "reset_after_each_run": False },
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)
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history = []
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while True:
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user_input = input("> ")
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history.append({"role": "user", "content": user_input})
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# Non-streaming usage
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async for result in agent.run(history, stream=False):
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history += result["output"]
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# # Print output
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# for item in result["output"]:
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# if item["type"] == "message":
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# print(item["content"][0]["text"])
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# elif item["type"] == "computer_call":
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# action = item["action"]
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# action_type = action["type"]
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# action_args = {k: v for k, v in action.items() if k != "type"}
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# print(f"{action_type}({action_args})")
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# elif item["type"] == "function_call":
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# action = item["name"]
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# action_args = item["arguments"]
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# print(f"{action}({action_args})")
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# elif item["type"] == "function_call_output":
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# print("===>", item["output"])
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if __name__ == "__main__":
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asyncio.run(main()) |