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https://github.com/OpenHands/OpenHands.git
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2de75d4782
* minimal docker sandbox * make container_image as an argument (fall back to ubuntu); increase timeout to avoid return too early for long running commands; * add a minimal working (imperfect) example * fix typo * change default container name * attempt to fix "Bad file descriptor" error * handle ctrl+D * add Python gitignore * push sandbox to shared dockerhub for ease of use * move codeact example into research folder * add README for opendevin * change container image name to opendevin dockerhub * move folder; change example to a more general agent * update Message and Role * update docker sandbox to support mounting folder and switch to user with correct permission * make network as host * handle erorrs when attrs are not set yet * convert codeact agent into a compatible agent * add workspace to gitignore * make sure the agent interface adjustment works for langchain_agent
125 lines
4.5 KiB
Python
125 lines
4.5 KiB
Python
import os
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import re
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import argparse
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from litellm import completion
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from termcolor import colored
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from typing import List, Dict
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from opendevin.agent import Agent, Message, Role
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from opendevin.sandbox.docker import DockerInteractive
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assert (
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"OPENAI_API_KEY" in os.environ
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), "Please set the OPENAI_API_KEY environment variable."
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SYSTEM_MESSAGE = """You are a helpful assistant. You will be provided access (as root) to a bash shell to complete user-provided tasks.
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You will be able to execute commands in the bash shell, interact with the file system, install packages, and receive the output of your commands.
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DO NOT provide code in ```triple backticks```. Instead, you should execute bash command on behalf of the user by wrapping them with <execute> and </execute>.
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For example:
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You can list the files in the current directory by executing the following command:
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<execute>ls</execute>
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You can also install packages using pip:
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<execute> pip install numpy </execute>
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You can also write a block of code to a file:
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<execute>
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echo "import math
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print(math.pi)" > math.py
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</execute>
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When you are done, execute "exit" to close the shell and end the conversation.
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"""
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INVALID_INPUT_MESSAGE = (
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"I don't understand your input. \n"
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"If you want to execute command, please use <execute> YOUR_COMMAND_HERE </execute>.\n"
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"If you already completed the task, please exit the shell by generating: <execute> exit </execute>."
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)
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def parse_response(response) -> str:
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action = response.choices[0].message.content
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if "<execute>" in action and "</execute>" not in action:
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action += "</execute>"
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return action
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class CodeActAgent(Agent):
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def __init__(
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self,
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instruction: str,
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workspace_dir: str,
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model_name: str,
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max_steps: int = 100
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) -> None:
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"""
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Initializes a new instance of the CodeActAgent class.
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Parameters:
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- instruction (str): The instruction for the agent to execute.
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- max_steps (int): The maximum number of steps to run the agent.
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"""
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super().__init__(instruction, workspace_dir, model_name, max_steps)
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self._history = [Message(Role.SYSTEM, SYSTEM_MESSAGE)]
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self._history.append(Message(Role.USER, instruction))
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self.env = DockerInteractive(workspace_dir=workspace_dir)
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print(colored("===USER:===\n" + instruction, "green"))
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def _history_to_messages(self) -> List[Dict]:
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return [message.to_dict() for message in self._history]
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def run(self) -> None:
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"""
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Starts the execution of the assigned instruction. This method should
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be implemented by subclasses to define the specific execution logic.
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"""
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for _ in range(self.max_steps):
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response = completion(
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messages=self._history_to_messages(),
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model=self.model_name,
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stop=["</execute>"],
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temperature=0.0,
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seed=42,
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)
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action = parse_response(response)
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self._history.append(Message(Role.ASSISTANT, action))
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print(colored("===ASSISTANT:===\n" + action, "yellow"))
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command = re.search(r"<execute>(.*)</execute>", action, re.DOTALL)
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if command is not None:
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# a command was found
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command = command.group(1)
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if command.strip() == "exit":
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print(colored("Exit received. Exiting...", "red"))
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break
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# execute the code
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observation = self.env.execute(command)
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self._history.append(Message(Role.ASSISTANT, observation))
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print(colored("===ENV OBSERVATION:===\n" + observation, "blue"))
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else:
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# we could provide a error message for the model to continue similar to
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# https://github.com/xingyaoww/mint-bench/blob/main/mint/envs/general_env.py#L18-L23
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observation = INVALID_INPUT_MESSAGE
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self._history.append(Message(Role.ASSISTANT, observation))
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print(colored("===ENV OBSERVATION:===\n" + observation, "blue"))
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self.env.close()
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def chat(self, message: str) -> None:
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"""
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Optional method for interactive communication with the agent during its execution. Implementations
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can use this method to modify the agent's behavior or state based on chat inputs.
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Parameters:
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- message (str): The chat message or command.
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"""
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raise NotImplementedError
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Agent.register("CodeActAgent", CodeActAgent)
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