|
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) |
|
|