mirror of
https://github.com/langgenius/dify-plugin-sdks.git
synced 2026-07-22 02:15:22 -04:00
immortal-wm
2fc9753673
* fix latency calc * feat: add timing context management to AIModel for latency tracking - Introduced a new TimingContextRaceConditionError to handle race conditions in multi-threaded environments. - Implemented a timing_context method in AIModel to track request timing and prevent concurrent usage. - Updated various model classes (LargeLanguageModel, ModerationModel, RerankModel, Speech2TextModel, TextEmbeddingModel, TTSModel) to utilize the new timing context for latency calculations. - Added tests to validate timing context behavior under concurrent and sequential usage scenarios. * feat: implement ModelFactory for dynamic model instance creation - Added ModelFactory class to generate stateless model instances based on provider configurations and model classes. - Updated PluginRegistration to utilize ModelFactory for managing model instances, enhancing code organization and maintainability. * feat: add unit tests for model registry and mock model provider - Introduced a new test file for validating model registry functionality. - Implemented mock classes for model provider and LLM to facilitate testing. - Added tests to ensure correct model instance retrieval from the registry. * apply ruff --------- Co-authored-by: Yeuoly <admin@srmxy.cn>
55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
from abc import abstractmethod
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from pydantic import ConfigDict
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from dify_plugin.entities.model import ModelType
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from dify_plugin.interfaces.model.ai_model import AIModel
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class ModerationModel(AIModel):
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"""
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Model class for moderation model.
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"""
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model_type: ModelType = ModelType.MODERATION
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# pydantic configs
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model_config = ConfigDict(protected_namespaces=())
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############################################################
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# Methods that can be implemented by plugin #
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############################################################
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@abstractmethod
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def _invoke(self, model: str, credentials: dict, text: str, user: str | None = None) -> bool:
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"""
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Invoke large language model
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:param model: model name
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:param credentials: model credentials
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:param text: text to moderate
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:param user: unique user id
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:return: false if text is safe, true otherwise
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"""
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raise NotImplementedError
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############################################################
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# For executor use only #
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############################################################
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def invoke(self, model: str, credentials: dict, text: str, user: str | None = None) -> bool:
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"""
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Invoke moderation model
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:param model: model name
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:param credentials: model credentials
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:param text: text to moderate
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:param user: unique user id
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:return: false if text is safe, true otherwise
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"""
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with self.timing_context():
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try:
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return self._invoke(model, credentials, text, user)
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except Exception as e:
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raise self._transform_invoke_error(e) from e
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