diff options
Diffstat (limited to 'autogpts/autogpt/autogpt/models/base_open_ai_plugin.py')
| -rw-r--r-- | autogpts/autogpt/autogpt/models/base_open_ai_plugin.py | 251 |
1 files changed, 251 insertions, 0 deletions
diff --git a/autogpts/autogpt/autogpt/models/base_open_ai_plugin.py b/autogpts/autogpt/autogpt/models/base_open_ai_plugin.py new file mode 100644 index 000000000..a269bb9c4 --- /dev/null +++ b/autogpts/autogpt/autogpt/models/base_open_ai_plugin.py @@ -0,0 +1,251 @@ +"""Handles loading of plugins.""" +from typing import Any, Dict, List, Optional, Tuple, TypedDict, TypeVar + +from auto_gpt_plugin_template import AutoGPTPluginTemplate + +PromptGenerator = TypeVar("PromptGenerator") + + +class Message(TypedDict): + role: str + content: str + + +class BaseOpenAIPlugin(AutoGPTPluginTemplate): + """ + This is a BaseOpenAIPlugin class for generating AutoGPT plugins. + """ + + def __init__(self, manifests_specs_clients: dict): + # super().__init__() + self._name = manifests_specs_clients["manifest"]["name_for_model"] + self._version = manifests_specs_clients["manifest"]["schema_version"] + self._description = manifests_specs_clients["manifest"]["description_for_model"] + self._client = manifests_specs_clients["client"] + self._manifest = manifests_specs_clients["manifest"] + self._openapi_spec = manifests_specs_clients["openapi_spec"] + + def can_handle_on_response(self) -> bool: + """This method is called to check that the plugin can + handle the on_response method. + Returns: + bool: True if the plugin can handle the on_response method.""" + return False + + def on_response(self, response: str, *args, **kwargs) -> str: + """This method is called when a response is received from the model.""" + return response + + def can_handle_post_prompt(self) -> bool: + """This method is called to check that the plugin can + handle the post_prompt method. + Returns: + bool: True if the plugin can handle the post_prompt method.""" + return False + + def post_prompt(self, prompt: PromptGenerator) -> PromptGenerator: + """This method is called just after the generate_prompt is called, + but actually before the prompt is generated. + Args: + prompt (PromptGenerator): The prompt generator. + Returns: + PromptGenerator: The prompt generator. + """ + return prompt + + def can_handle_on_planning(self) -> bool: + """This method is called to check that the plugin can + handle the on_planning method. + Returns: + bool: True if the plugin can handle the on_planning method.""" + return False + + def on_planning( + self, prompt: PromptGenerator, messages: List[Message] + ) -> Optional[str]: + """This method is called before the planning chat completion is done. + Args: + prompt (PromptGenerator): The prompt generator. + messages (List[str]): The list of messages. + """ + + def can_handle_post_planning(self) -> bool: + """This method is called to check that the plugin can + handle the post_planning method. + Returns: + bool: True if the plugin can handle the post_planning method.""" + return False + + def post_planning(self, response: str) -> str: + """This method is called after the planning chat completion is done. + Args: + response (str): The response. + Returns: + str: The resulting response. + """ + return response + + def can_handle_pre_instruction(self) -> bool: + """This method is called to check that the plugin can + handle the pre_instruction method. + Returns: + bool: True if the plugin can handle the pre_instruction method.""" + return False + + def pre_instruction(self, messages: List[Message]) -> List[Message]: + """This method is called before the instruction chat is done. + Args: + messages (List[Message]): The list of context messages. + Returns: + List[Message]: The resulting list of messages. + """ + return messages + + def can_handle_on_instruction(self) -> bool: + """This method is called to check that the plugin can + handle the on_instruction method. + Returns: + bool: True if the plugin can handle the on_instruction method.""" + return False + + def on_instruction(self, messages: List[Message]) -> Optional[str]: + """This method is called when the instruction chat is done. + Args: + messages (List[Message]): The list of context messages. + Returns: + Optional[str]: The resulting message. + """ + + def can_handle_post_instruction(self) -> bool: + """This method is called to check that the plugin can + handle the post_instruction method. + Returns: + bool: True if the plugin can handle the post_instruction method.""" + return False + + def post_instruction(self, response: str) -> str: + """This method is called after the instruction chat is done. + Args: + response (str): The response. + Returns: + str: The resulting response. + """ + return response + + def can_handle_pre_command(self) -> bool: + """This method is called to check that the plugin can + handle the pre_command method. + Returns: + bool: True if the plugin can handle the pre_command method.""" + return False + + def pre_command( + self, command_name: str, arguments: Dict[str, Any] + ) -> Tuple[str, Dict[str, Any]]: + """This method is called before the command is executed. + Args: + command_name (str): The command name. + arguments (Dict[str, Any]): The arguments. + Returns: + Tuple[str, Dict[str, Any]]: The command name and the arguments. + """ + return command_name, arguments + + def can_handle_post_command(self) -> bool: + """This method is called to check that the plugin can + handle the post_command method. + Returns: + bool: True if the plugin can handle the post_command method.""" + return False + + def post_command(self, command_name: str, response: str) -> str: + """This method is called after the command is executed. + Args: + command_name (str): The command name. + response (str): The response. + Returns: + str: The resulting response. + """ + return response + + def can_handle_chat_completion( + self, messages: Dict[Any, Any], model: str, temperature: float, max_tokens: int + ) -> bool: + """This method is called to check that the plugin can + handle the chat_completion method. + Args: + messages (List[Message]): The messages. + model (str): The model name. + temperature (float): The temperature. + max_tokens (int): The max tokens. + Returns: + bool: True if the plugin can handle the chat_completion method.""" + return False + + def handle_chat_completion( + self, messages: List[Message], model: str, temperature: float, max_tokens: int + ) -> str: + """This method is called when the chat completion is done. + Args: + messages (List[Message]): The messages. + model (str): The model name. + temperature (float): The temperature. + max_tokens (int): The max tokens. + Returns: + str: The resulting response. + """ + + def can_handle_text_embedding(self, text: str) -> bool: + """This method is called to check that the plugin can + handle the text_embedding method. + + Args: + text (str): The text to be convert to embedding. + Returns: + bool: True if the plugin can handle the text_embedding method.""" + return False + + def handle_text_embedding(self, text: str) -> list[float]: + """This method is called to create a text embedding. + + Args: + text (str): The text to be convert to embedding. + Returns: + list[float]: The created embedding vector. + """ + + def can_handle_user_input(self, user_input: str) -> bool: + """This method is called to check that the plugin can + handle the user_input method. + + Args: + user_input (str): The user input. + + Returns: + bool: True if the plugin can handle the user_input method.""" + return False + + def user_input(self, user_input: str) -> str: + """This method is called to request user input to the user. + + Args: + user_input (str): The question or prompt to ask the user. + + Returns: + str: The user input. + """ + + def can_handle_report(self) -> bool: + """This method is called to check that the plugin can + handle the report method. + + Returns: + bool: True if the plugin can handle the report method.""" + return False + + def report(self, message: str) -> None: + """This method is called to report a message to the user. + + Args: + message (str): The message to report. + """ |