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import inspect |
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from typing import Any, Callable, Dict, Optional, Set, TypeVar, Union |
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from camel.interpreters import BaseInterpreter, SubprocessInterpreter |
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from camel.types import RoleType |
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from camel.utils import get_system_information |
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T = TypeVar('T') |
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def return_prompt_wrapper( |
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cls: Any, |
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func: Callable, |
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) -> Callable[..., Union[Any, tuple]]: |
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r"""Wrapper that converts the return value of a function to an input |
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class instance if it's a string. |
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Args: |
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cls (Any): The class to convert to. |
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func (Callable): The function to decorate. |
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Returns: |
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Callable[..., Union[Any, str]]: Decorated function that |
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returns the decorated class instance if the return value is a |
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string. |
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""" |
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def wrapper(*args: Any, **kwargs: Any) -> Union[Any, str]: |
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r"""Wrapper function that performs the conversion to :obj:`TextPrompt` |
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instance. |
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Args: |
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*args (Any): Variable length argument list. |
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**kwargs (Any): Arbitrary keyword arguments. |
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Returns: |
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Union[Any, str]: The converted return value. |
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""" |
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result = func(*args, **kwargs) |
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if isinstance(result, str) and not isinstance(result, cls): |
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return cls(result) |
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elif isinstance(result, tuple): |
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new_result = tuple( |
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cls(item) |
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if isinstance(item, str) and not isinstance(item, cls) |
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else item |
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for item in result |
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) |
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return new_result |
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return result |
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wrapper.__name__ = func.__name__ |
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wrapper.__doc__ = func.__doc__ |
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return wrapper |
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def wrap_prompt_functions(cls: T) -> T: |
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r"""Decorator that wraps functions of a class inherited from :obj:`str` |
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with the :obj:`return_text_prompt` decorator. |
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Args: |
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cls (type): The class to decorate. |
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Returns: |
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type: Decorated class with wrapped functions. |
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""" |
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excluded_attrs = {'__init__', '__new__', '__str__', '__repr__'} |
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for attr_name in dir(cls): |
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attr_value = getattr(cls, attr_name) |
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if callable(attr_value) and attr_name not in excluded_attrs: |
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if inspect.isroutine(attr_value): |
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setattr(cls, attr_name, return_prompt_wrapper(cls, attr_value)) |
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return cls |
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@wrap_prompt_functions |
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class TextPrompt(str): |
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r"""A class that represents a text prompt. The :obj:`TextPrompt` class |
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extends the built-in :obj:`str` class to provide a property for retrieving |
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the set of keywords in the prompt. |
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Attributes: |
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key_words (set): A set of strings representing the keywords in the |
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prompt. |
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""" |
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@property |
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def key_words(self) -> Set[str]: |
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r"""Returns a set of strings representing the keywords in the prompt.""" |
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from camel.utils import get_prompt_template_key_words |
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return get_prompt_template_key_words(self) |
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def format(self, *args: Any, **kwargs: Any) -> 'TextPrompt': |
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r"""Overrides the built-in :obj:`str.format` method to allow for |
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default values in the format string. This is used to allow formatting |
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the partial string. |
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Args: |
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*args (Any): Variable length argument list. |
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**kwargs (Any): Arbitrary keyword arguments. |
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Returns: |
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TextPrompt: A new :obj:`TextPrompt` object with the format string |
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replaced with the formatted string. |
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""" |
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default_kwargs = {key: '{' + f'{key}' + '}' for key in self.key_words} |
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default_kwargs.update(kwargs) |
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return TextPrompt(super().format(*args, **default_kwargs)) |
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@wrap_prompt_functions |
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class CodePrompt(TextPrompt): |
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r"""A class that represents a code prompt. It extends the :obj:`TextPrompt` |
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class with a :obj:`code_type` property. |
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Attributes: |
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code_type (str, optional): The type of code. Defaults to None. |
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""" |
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def __new__(cls, *args: Any, **kwargs: Any) -> 'CodePrompt': |
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r"""Creates a new instance of the :obj:`CodePrompt` class. |
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Args: |
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*args (Any): Positional arguments. |
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**kwargs (Any): Keyword arguments. |
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Returns: |
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CodePrompt: The created :obj:`CodePrompt` instance. |
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""" |
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code_type = kwargs.pop('code_type', None) |
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instance = super().__new__(cls, *args, **kwargs) |
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instance._code_type = code_type |
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return instance |
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@property |
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def code_type(self) -> Optional[str]: |
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r"""Returns the type of code. |
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Returns: |
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Optional[str]: The type of code. |
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""" |
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return self._code_type |
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def set_code_type(self, code_type: str) -> None: |
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r"""Sets the type of code. |
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Args: |
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code_type (str): The type of code. |
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""" |
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self._code_type = code_type |
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def execute( |
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self, |
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interpreter: Optional[BaseInterpreter] = None, |
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**kwargs: Any, |
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) -> str: |
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r"""Executes the code string using the provided interpreter. |
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This method runs a code string through either a specified interpreter |
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or a default one. It supports additional keyword arguments for |
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flexibility. |
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Args: |
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interpreter (Optional[BaseInterpreter]): The interpreter instance |
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to use for execution. If `None`, a default interpreter is used. |
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(default: :obj:`None`) |
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**kwargs: Additional keyword arguments passed to the interpreter to |
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run the code. |
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Returns: |
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str: The result of the code execution. If the execution fails, this |
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should include sufficient information to diagnose and correct |
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the issue. |
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Raises: |
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InterpreterError: If the code execution encounters errors that |
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could be resolved by modifying or regenerating the code. |
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""" |
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if interpreter is None: |
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execution_res = SubprocessInterpreter().run( |
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self, self._code_type, **kwargs |
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) |
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else: |
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execution_res = interpreter.run(self, self._code_type, **kwargs) |
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return execution_res |
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class TextPromptDict(Dict[Any, TextPrompt]): |
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r"""A dictionary class that maps from key to :obj:`TextPrompt` object.""" |
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EMBODIMENT_PROMPT = TextPrompt( |
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"System information :" |
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+ "\n".join( |
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f"{key}: {value}" |
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for key, value in get_system_information().items() |
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) |
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+ "\n" |
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+ """You are the physical embodiment of the {role} who is working on solving a task: {task}. |
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You can do things in the physical world including browsing the Internet, reading documents, drawing images, creating videos, executing code and so on. |
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Your job is to perform the physical actions necessary to interact with the physical world. |
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You will receive thoughts from the {role} and you will need to perform the actions described in the thoughts. |
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You can write a series of simple commands in to act. |
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You can perform a set of actions by calling the available functions. |
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You should perform actions based on the descriptions of the functions. |
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Here is your action space but it is not limited: |
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{action_space} |
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You can perform multiple actions. |
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You can perform actions in any order. |
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First, explain the actions you will perform and your reasons, then write code to implement your actions. |
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If you decide to perform actions, you must write code to implement the actions. |
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You may print intermediate results if necessary.""" |
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) |
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def __init__(self, *args: Any, **kwargs: Any) -> None: |
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super().__init__(*args, **kwargs) |
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self.update({RoleType.EMBODIMENT: self.EMBODIMENT_PROMPT}) |
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