Workflow-Engine / api /core /moderation /input_moderation.py
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import logging
from typing import Optional
from core.app.app_config.entities import AppConfig
from core.moderation.base import ModerationAction, ModerationError
from core.moderation.factory import ModerationFactory
from core.ops.entities.trace_entity import TraceTaskName
from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
from core.ops.utils import measure_time
logger = logging.getLogger(__name__)
class InputModeration:
def check(
self,
app_id: str,
tenant_id: str,
app_config: AppConfig,
inputs: dict,
query: str,
message_id: str,
trace_manager: Optional[TraceQueueManager] = None,
) -> tuple[bool, dict, str]:
"""
Process sensitive_word_avoidance.
:param app_id: app id
:param tenant_id: tenant id
:param app_config: app config
:param inputs: inputs
:param query: query
:param message_id: message id
:param trace_manager: trace manager
:return:
"""
if not app_config.sensitive_word_avoidance:
return False, inputs, query
sensitive_word_avoidance_config = app_config.sensitive_word_avoidance
moderation_type = sensitive_word_avoidance_config.type
moderation_factory = ModerationFactory(
name=moderation_type, app_id=app_id, tenant_id=tenant_id, config=sensitive_word_avoidance_config.config
)
with measure_time() as timer:
moderation_result = moderation_factory.moderation_for_inputs(inputs, query)
if trace_manager:
trace_manager.add_trace_task(
TraceTask(
TraceTaskName.MODERATION_TRACE,
message_id=message_id,
moderation_result=moderation_result,
inputs=inputs,
timer=timer,
)
)
if not moderation_result.flagged:
return False, inputs, query
if moderation_result.action == ModerationAction.DIRECT_OUTPUT:
raise ModerationError(moderation_result.preset_response)
elif moderation_result.action == ModerationAction.OVERRIDDEN:
inputs = moderation_result.inputs
query = moderation_result.query
return True, inputs, query