- Updated TASK_DESCRIPTION in run_coact.py to clarify task-solving steps and requirements. - Modified configuration parameters for provider name and client password for better security and flexibility. - Enhanced OrchestratorUserProxyAgent to include user instruction in the auto-reply and improved screenshot handling. - Adjusted coding_agent.py to ensure proper verification of results before saving changes. - Improved CUA agent prompts to maintain application state and handle user instructions more effectively. - Ensured existing code logic remains unchanged while enhancing functionality and usability.
77 lines
3.2 KiB
Python
77 lines
3.2 KiB
Python
from typing import Any, Callable, Optional
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from desktop_env.desktop_env import DesktopEnv
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from .autogen.llm_config import LLMConfig
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from .autogen.code_utils import PYTHON_VARIANTS
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from .autogen.agentchat.contrib.multimodal_conversable_agent import MultimodalConversableAgent
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CODER_SYSTEM_MESSAGE = """# Your role
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- You are a programmer, you need to solve a task step-by-step given by the user.
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- You can write code in ```bash...``` code blocks for bash scripts, and ```python...``` code blocks for python code.
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- Your linux username is "user".
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- If you want to use sudo, follow the format: "echo {CLIENT_PASSWORD} | sudo -S [YOUR COMMANDS]" (no quotes for the word "{CLIENT_PASSWORD}").
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# Requirements
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- You MUST verify the result before save the changes.
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- When you write code, you must identify the language (whether it is python or bash) of the code.
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- Wrap all your code in ONE code block. DO NOT let user save the code as a file and execute it for you.
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- Do not include __main__ in your python code.
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- When you modify a spreadsheet, **make sure every value is in the expected cell**.
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- When importing a package, you need to check if the package has been installed. If not, you need to install it yourself.
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- You need to print the progressive and final result.
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- If you met execution error, you need to analyze the error message and try to fix the error.
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"""
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class TerminalProxyAgent(MultimodalConversableAgent):
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def __init__(
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self,
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name: str,
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env: DesktopEnv,
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llm_config: LLMConfig = False,
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system_message: str = "",
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human_input_mode: str = "NEVER",
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code_execution_config = {},
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is_termination_msg: Optional[Callable[[dict[str, Any]], bool]] = None,
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max_consecutive_auto_reply: Optional[int] = None,
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default_auto_reply: Optional[str] = None,
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description: Optional[str] = None,
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):
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super().__init__(
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name=name,
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system_message=system_message,
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is_termination_msg=is_termination_msg,
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max_consecutive_auto_reply=max_consecutive_auto_reply,
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human_input_mode=human_input_mode,
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code_execution_config=code_execution_config,
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llm_config=llm_config,
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default_auto_reply=default_auto_reply,
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description=description
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)
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self.env = env
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def run_code(self, code: str, lang: str = "python", **kwargs):
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exitcode = 1
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logs = ""
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image = None
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if lang in ["bash", "shell", "sh"]:
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output_dict = self.env.controller.run_bash_script(code)
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if output_dict["status"] == "success":
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exitcode = 0
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logs = output_dict["output"]
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else:
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exitcode = 0
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logs = output_dict["output"]
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elif lang in PYTHON_VARIANTS:
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output_dict = self.env.controller.run_python_script(code)
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if output_dict["status"] == "error":
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exitcode = 0
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logs = output_dict["output"]
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else:
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exitcode = 0
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logs = output_dict["message"]
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else:
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exitcode = -1
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logs = f"unknown language {lang}"
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return exitcode, logs, image
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