import binascii import tempfile from dify_plugin.core.runtime.entities.plugin.request import ( ModelInvokeLLMRequest, ModelInvokeModerationRequest, ModelInvokeRerankRequest, ModelInvokeSpeech2TextRequest, ModelInvokeTTSRequest, ModelInvokeTextEmbeddingRequest, ModelValidateModelCredentialsRequest, ModelValidateProviderCredentialsRequest, ToolInvokeRequest, ToolValidateCredentialsRequest, ) from dify_plugin.core.runtime.session import Session from dify_plugin.model.large_language_model import LargeLanguageModel from dify_plugin.model.moderation_model import ModerationModel from dify_plugin.model.rerank_model import RerankModel from dify_plugin.model.speech2text_model import Speech2TextModel from dify_plugin.model.text_embedding_model import TextEmbeddingModel from dify_plugin.model.tts_model import TTSModel from dify_plugin.plugin_registration import PluginRegistration from dify_plugin.tool.entities import ToolRuntime class PluginExecutor: def __init__(self, registration: PluginRegistration) -> None: self.registration = registration def validate_tool_provider_credentials( self, session: Session, data: ToolValidateCredentialsRequest ): provider_instance = self.registration.get_tool_provider_cls(data.provider) if provider_instance is None: raise ValueError(f"Provider `{data.provider}` not found") provider_instance = provider_instance() try: provider_instance.validate_credentials(data.credentials) except Exception as e: raise ValueError( f"Failed to validate provider credentials: {type(e).__name__}: {str(e)}" ) return { "result": True } def invoke_tool(self, session: Session, request: ToolInvokeRequest): provider_cls = self.registration.get_tool_provider_cls(request.provider) if provider_cls is None: raise ValueError(f"Provider `{request.provider}` not found") tool_cls = self.registration.get_tool_cls(request.provider, request.tool) if tool_cls is None: raise ValueError( f"Tool `{request.tool}` not found for provider `{request.provider}`" ) # instantiate provider and tool provider = provider_cls() tool = tool_cls( runtime=ToolRuntime( credentials=request.credentials, user_id=request.user_id, session_id=session.session_id, ) ) # invoke tool try: return session.run_tool( action=request.action, provider=provider, tool=tool, parameters=request.tool_parameters, ) except Exception as e: raise ValueError(f"Failed to invoke tool: {type(e).__name__}: {str(e)}") def validate_model_provider_credentials( self, session: Session, data: ModelValidateProviderCredentialsRequest ): provider_instance = self.registration.get_model_provider_instance(data.provider) if provider_instance is None: raise ValueError(f"Provider `{data.provider}` not found") try: provider_instance.validate_provider_credentials(data.credentials) except Exception as e: raise ValueError( f"Failed to validate provider credentials: {type(e).__name__}: {str(e)}" ) return { "result": True } def validate_model_credentials( self, session: Session, data: ModelValidateModelCredentialsRequest ): provider_instance = self.registration.get_model_provider_instance(data.provider) if provider_instance is None: raise ValueError(f"Provider `{data.provider}` not found") model_instance = self.registration.get_model_instance( data.provider, data.model_type ) if model_instance is None: raise ValueError( f"Model `{data.model_type}` not found for provider `{data.provider}`" ) try: model_instance.validate_credentials(data.model, data.credentials) except Exception as e: raise ValueError( f"Failed to validate model credentials: {type(e).__name__}: {str(e)}" ) return { "result": True } def invoke_llm(self, session: Session, data: ModelInvokeLLMRequest): model_instance = self.registration.get_model_instance( data.provider, data.model_type ) if isinstance(model_instance, LargeLanguageModel): return model_instance.invoke( data.model, data.credentials, data.prompt_messages, data.model_parameters, data.tools, data.stop, data.stream, data.user_id, ) def invoke_text_embedding( self, session: Session, data: ModelInvokeTextEmbeddingRequest ): model_instance = self.registration.get_model_instance( data.provider, data.model_type ) if isinstance(model_instance, TextEmbeddingModel): return model_instance.invoke( data.model, data.credentials, data.texts, data.user_id, ) def invoke_rerank(self, session: Session, data: ModelInvokeRerankRequest): model_instance = self.registration.get_model_instance( data.provider, data.model_type ) if isinstance(model_instance, RerankModel): return model_instance.invoke( data.model, data.credentials, data.query, data.docs, data.score_threshold, data.top_n, data.user_id, ) def invoke_tts(self, session: Session, data: ModelInvokeTTSRequest): model_instance = self.registration.get_model_instance( data.provider, data.model_type ) if isinstance(model_instance, TTSModel): b = model_instance.invoke( data.model, data.credentials, data.content_text, data.voice, data.user_id, ) if isinstance(b, bytes): return {"result": binascii.hexlify(b).decode()} for chunk in b: yield {"result": binascii.hexlify(bytes(chunk)).decode()} def invoke_speech_to_text( self, session: Session, data: ModelInvokeSpeech2TextRequest ): model_instance = self.registration.get_model_instance( data.provider, data.model_type ) with tempfile.NamedTemporaryFile(suffix=".mp3", mode="wb", delete=True) as temp: temp.write(binascii.unhexlify(data.file)) temp.flush() with open(temp.name, "rb") as f: if isinstance(model_instance, Speech2TextModel): return { "result": model_instance.invoke( data.model, data.credentials, f, data.user_id, ) } def invoke_moderation(self, session: Session, data: ModelInvokeModerationRequest): model_instance = self.registration.get_model_instance( data.provider, data.model_type ) if isinstance(model_instance, ModerationModel): return { "result": model_instance.invoke( data.model, data.credentials, data.text, data.user_id, ) }