# # Copyright 2024 The InfiniFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from abc import ABC from agent.component.base import ComponentBase, ComponentParamBase import deepl class DeepLParam(ComponentParamBase): """ Define the DeepL component parameters. """ def __init__(self): super().__init__() self.auth_key = "xxx" self.parameters = [] self.source_lang = "ZH" self.target_lang = "EN-GB" def check(self): self.check_valid_value( self.source_lang, "Source language", ["AR", "BG", "CS", "DA", "DE", "EL", "EN", "ES", "ET", "FI", "FR", "HU", "ID", "IT", "JA", "KO", "LT", "LV", "NB", "NL", "PL", "PT", "RO", "RU", "SK", "SL", "SV", "TR", "UK", "ZH"], ) self.check_valid_value( self.target_lang, "Target language", [ "AR", "BG", "CS", "DA", "DE", "EL", "EN-GB", "EN-US", "ES", "ET", "FI", "FR", "HU", "ID", "IT", "JA", "KO", "LT", "LV", "NB", "NL", "PL", "PT-BR", "PT-PT", "RO", "RU", "SK", "SL", "SV", "TR", "UK", "ZH", ], ) class DeepL(ComponentBase, ABC): component_name = "DeepL" def _run(self, history, **kwargs): if self.check_if_canceled("DeepL processing"): return ans = self.get_input() ans = " - ".join(ans["content"]) if "content" in ans else "" if not ans: return DeepL.be_output("") if self.check_if_canceled("DeepL processing"): return try: translator = deepl.Translator(self._param.auth_key) result = translator.translate_text(ans, source_lang=self._param.source_lang, target_lang=self._param.target_lang) return DeepL.be_output(result.text) except Exception as e: if self.check_if_canceled("DeepL processing"): return return DeepL.be_output("**Error**:" + str(e))