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