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180 lines
6.6 KiB
Python
180 lines
6.6 KiB
Python
# ========= Copyright 2023-2026 @ CAMEL-AI.org. All Rights Reserved. =========
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ========= Copyright 2023-2026 @ CAMEL-AI.org. All Rights Reserved. =========
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from typing import List, Literal, Optional, Union
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from camel.interpreters import (
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DockerInterpreter,
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E2BInterpreter,
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InternalPythonInterpreter,
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JupyterKernelInterpreter,
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MicrosandboxInterpreter,
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SubprocessInterpreter,
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)
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from camel.logger import get_logger
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from camel.toolkits import FunctionTool
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from camel.toolkits.base import BaseToolkit
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from camel.utils import MCPServer
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logger = get_logger(__name__)
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@MCPServer()
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class CodeExecutionToolkit(BaseToolkit):
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r"""A toolkit for code execution.
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Args:
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sandbox (str): The environment type used to execute code.
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(default: `subprocess`)
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verbose (bool): Whether to print the output of the code execution.
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(default: :obj:`False`)
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unsafe_mode (bool): If `True`, the interpreter runs the code
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by `eval()` without any security check. (default: :obj:`False`)
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import_white_list (Optional[List[str]]): A list of allowed imports.
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(default: :obj:`None`)
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require_confirm (bool): Whether to require confirmation before
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executing code. (default: :obj:`False`)
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timeout (Optional[float]): General timeout for toolkit operations.
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(default: :obj:`None`)
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microsandbox_config (Optional[dict]): Configuration for microsandbox
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interpreter. Available keys: 'server_url', 'api_key',
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'namespace', 'sandbox_name', 'timeout'.
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If None, uses default configuration. (default: :obj:`None`)
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"""
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def __init__(
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self,
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sandbox: Literal[
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"internal_python",
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"jupyter",
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"docker",
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"subprocess",
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"e2b",
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"microsandbox",
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] = "subprocess",
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verbose: bool = False,
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unsafe_mode: bool = False,
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import_white_list: Optional[List[str]] = None,
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require_confirm: bool = False,
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timeout: Optional[float] = None,
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# Microsandbox configuration dictionary
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microsandbox_config: Optional[dict] = None,
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) -> None:
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super().__init__(timeout=timeout)
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self.verbose = verbose
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self.unsafe_mode = unsafe_mode
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self.import_white_list = import_white_list or list()
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# Type annotation for interpreter to allow all possible types
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self.interpreter: Union[
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InternalPythonInterpreter,
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JupyterKernelInterpreter,
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DockerInterpreter,
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SubprocessInterpreter,
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E2BInterpreter,
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MicrosandboxInterpreter,
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]
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if sandbox == "internal_python":
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self.interpreter = InternalPythonInterpreter(
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unsafe_mode=self.unsafe_mode,
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import_white_list=self.import_white_list,
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)
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elif sandbox == "jupyter":
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self.interpreter = JupyterKernelInterpreter(
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require_confirm=require_confirm,
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print_stdout=self.verbose,
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print_stderr=self.verbose,
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)
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elif sandbox == "docker":
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self.interpreter = DockerInterpreter(
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require_confirm=require_confirm,
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print_stdout=self.verbose,
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print_stderr=self.verbose,
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)
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elif sandbox == "subprocess":
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self.interpreter = SubprocessInterpreter(
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require_confirm=require_confirm,
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print_stdout=self.verbose,
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print_stderr=self.verbose,
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)
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elif sandbox == "e2b":
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self.interpreter = E2BInterpreter(require_confirm=require_confirm)
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elif sandbox == "microsandbox":
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# Extract parameters with proper types for microsandbox
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config = microsandbox_config or {}
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self.interpreter = MicrosandboxInterpreter(
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require_confirm=require_confirm,
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server_url=config.get("server_url"),
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api_key=config.get("api_key"),
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namespace=config.get("namespace", "default"),
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sandbox_name=config.get("sandbox_name"),
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timeout=config.get("timeout", 30),
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)
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else:
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raise RuntimeError(
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f"The sandbox type `{sandbox}` is not supported."
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)
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def execute_code(self, code: str, code_type: str = "python") -> str:
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r"""Execute a given code snippet.
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Args:
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code (str): The input code to the Code Interpreter tool call.
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code_type (str): The type of the code to be executed
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(e.g. node.js, python, etc). (default: obj:`python`)
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Returns:
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str: The text output from the Code Interpreter tool call.
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"""
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output = self.interpreter.run(code, code_type)
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content = (
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f"Executed the code below:\n```{code_type}\n{code}\n```\n"
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f"> Executed Results:\n{output}"
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)
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if self.verbose:
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print(content)
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return content
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def execute_command(self, command: str) -> Union[str, tuple[str, str]]:
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r"""Execute a command can be used to resolve the dependency of the
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code. Useful if there's dependency issues when you try to execute code.
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Args:
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command (str): The command to execute.
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Returns:
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Union[str, tuple[str, str]]: The output of the command.
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"""
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output = self.interpreter.execute_command(command)
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content = (
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f"Executed the command below:\n```sh\n{command}\n```\n"
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f"> Executed Results:\n{output}"
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)
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if self.verbose:
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print(content)
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return content
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def get_tools(self) -> List[FunctionTool]:
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r"""Returns a list of FunctionTool objects representing the
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functions in the toolkit.
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Returns:
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List[FunctionTool]: A list of FunctionTool objects
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representing the functions in the toolkit.
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"""
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return [
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FunctionTool(self.execute_code),
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FunctionTool(self.execute_command),
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]
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