| from core.extension.extensible import ExtensionModule |
| from core.moderation.base import Moderation, ModerationInputsResult, ModerationOutputsResult |
| from extensions.ext_code_based_extension import code_based_extension |
|
|
|
|
| class ModerationFactory: |
| __extension_instance: Moderation |
|
|
| def __init__(self, name: str, app_id: str, tenant_id: str, config: dict) -> None: |
| extension_class = code_based_extension.extension_class(ExtensionModule.MODERATION, name) |
| self.__extension_instance = extension_class(app_id, tenant_id, config) |
|
|
| @classmethod |
| def validate_config(cls, name: str, tenant_id: str, config: dict) -> None: |
| """ |
| Validate the incoming form config data. |
| |
| :param name: the name of extension |
| :param tenant_id: the id of workspace |
| :param config: the form config data |
| :return: |
| """ |
| code_based_extension.validate_form_schema(ExtensionModule.MODERATION, name, config) |
| extension_class = code_based_extension.extension_class(ExtensionModule.MODERATION, name) |
| extension_class.validate_config(tenant_id, config) |
|
|
| def moderation_for_inputs(self, inputs: dict, query: str = "") -> ModerationInputsResult: |
| """ |
| Moderation for inputs. |
| After the user inputs, this method will be called to perform sensitive content review |
| on the user inputs and return the processed results. |
| |
| :param inputs: user inputs |
| :param query: query string (required in chat app) |
| :return: |
| """ |
| return self.__extension_instance.moderation_for_inputs(inputs, query) |
|
|
| def moderation_for_outputs(self, text: str) -> ModerationOutputsResult: |
| """ |
| Moderation for outputs. |
| When LLM outputs content, the front end will pass the output content (may be segmented) |
| to this method for sensitive content review, and the output content will be shielded if the review fails. |
| |
| :param text: LLM output content |
| :return: |
| """ |
| return self.__extension_instance.moderation_for_outputs(text) |
|
|