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220168c4bf
maxkb/apps/locales/zh_Hant/LC_MESSAGES/django.po
CaptainB 220168c4bf chore: add some i18n code
2025-04-21 13:23:22 +08:00

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# SOME DESCRIPTIVE TITLE.
# Copyright (C) YEAR THE PACKAGE'S COPYRIGHT HOLDER
# This file is distributed under the same license as the PACKAGE package.
# FIRST AUTHOR <EMAIL@ADDRESS>, YEAR.
#
#, fuzzy
msgid ""
msgstr ""
"Project-Id-Version: PACKAGE VERSION\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2025-04-21 12:58+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language-Team: LANGUAGE <LL@li.org>\n"
"Language: \n"
"MIME-Version: 1.0\n"
"Content-Type: text/plain; charset=UTF-8\n"
"Content-Transfer-Encoding: 8bit\n"
#: apps/common/auth/authenticate.py:80
msgid "Not logged in, please log in first"
msgstr "未登錄，請先登錄"
#: apps/common/auth/authenticate.py:82 apps/common/auth/authenticate.py:89
#: apps/common/auth/authenticate.py:95
msgid "Authentication information is incorrect! illegal user"
msgstr "身份驗證信息不正確！非法用戶"
#: apps/common/auth/authentication.py:96
msgid "No permission to access"
msgstr "無權限訪問"
#: apps/common/auth/handle/impl/user_token.py:157
msgid "Login expired"
msgstr "登錄已過期"
#: apps/common/exception/handle_exception.py:32
msgid "Unknown exception"
msgstr "未知錯誤"
#: apps/common/forms/base_field.py:64
#, python-brace-format
msgid "The field {field_label} is required"
msgstr "{field_label} 欄位是必填項"
#: apps/common/forms/slider_field.py:56
#, python-brace-format
msgid "The {field_label} cannot be less than {min}"
msgstr "{field_label} 不能小於{min}"
#: apps/common/forms/slider_field.py:62
#, python-brace-format
msgid "The {field_label} cannot be greater than {max}"
msgstr "{field_label} 不能大於{max}"
#: apps/common/result/api.py:17 apps/common/result/api.py:27
msgid "response code"
msgstr "響應碼"
#: apps/common/result/api.py:18 apps/common/result/api.py:19
#: apps/common/result/api.py:28 apps/common/result/api.py:29
msgid "error prompt"
msgstr "錯誤提示"
#: apps/common/result/api.py:43
msgid "total number of data"
msgstr "總數據"
#: apps/common/result/api.py:44
msgid "current page"
msgstr "當前頁"
#: apps/common/result/api.py:45
msgid "page size"
msgstr "每頁大小"
#: apps/common/result/result.py:31
msgid "Success"
msgstr "成功"
#: apps/common/utils/common.py:83
msgid "Text-to-speech node, the text content must be of string type"
msgstr "文本轉語音節點，文本內容必須是字符串類型"
#: apps/common/utils/common.py:85
msgid "Text-to-speech node, the text content cannot be empty"
msgstr "文本轉語音節點，文本內容不能為空"
#: apps/maxkb/settings/base.py:83
msgid "Intelligent customer service platform"
msgstr "智能客服平臺"
#: apps/models_provider/api/model.py:36 apps/models_provider/api/model.py:49
#: apps/models_provider/serializers/model_serializer.py:262
#: apps/models_provider/serializers/model_serializer.py:326
#: apps/modules/serializers/module.py:31 apps/modules/serializers/module.py:63
#: apps/modules/serializers/module.py:95 apps/tools/serializers/tool.py:66
#: apps/tools/serializers/tool.py:87 apps/tools/serializers/tool.py:116
msgid "workspace id"
msgstr "工作空間ID"
#: apps/models_provider/api/model.py:55
#: apps/models_provider/serializers/model_serializer.py:107
#: apps/models_provider/serializers/model_serializer.py:367
msgid "model id"
msgstr "模型ID"
#: apps/models_provider/api/provide.py:17
#: apps/models_provider/api/provide.py:23
#: apps/models_provider/api/provide.py:28
#: apps/models_provider/api/provide.py:30
#: apps/models_provider/api/provide.py:67
#: apps/models_provider/serializers/model_serializer.py:40
#: apps/models_provider/serializers/model_serializer.py:218
#: apps/models_provider/serializers/model_serializer.py:256
#: apps/models_provider/serializers/model_serializer.py:321
msgid "model name"
msgstr "模型名稱"
#: apps/models_provider/api/provide.py:18
#: apps/models_provider/api/provide.py:38
#: apps/models_provider/api/provide.py:61
#: apps/models_provider/api/provide.py:89
#: apps/models_provider/api/provide.py:111
#: apps/models_provider/serializers/model_serializer.py:41
#: apps/models_provider/serializers/model_serializer.py:257
#: apps/models_provider/serializers/model_serializer.py:324
msgid "provider"
msgstr "供應商"
#: apps/models_provider/api/provide.py:19
msgid "icon"
msgstr ""
#: apps/models_provider/api/provide.py:24
msgid "value"
msgstr "值"
#: apps/models_provider/api/provide.py:29
#: apps/models_provider/api/provide.py:55
#: apps/models_provider/api/provide.py:83
#: apps/models_provider/serializers/model_serializer.py:42
#: apps/models_provider/serializers/model_serializer.py:220
#: apps/models_provider/serializers/model_serializer.py:258
#: apps/models_provider/serializers/model_serializer.py:322
msgid "model type"
msgstr "模型類型"
#: apps/models_provider/api/provide.py:34 apps/tools/serializers/tool.py:38
msgid "input type"
msgstr "輸入類型"
#: apps/models_provider/api/provide.py:35
msgid "label"
msgstr "標籤"
#: apps/models_provider/api/provide.py:36
msgid "text field"
msgstr "文本欄位"
#: apps/models_provider/api/provide.py:37
msgid "value field"
msgstr "值"
#: apps/models_provider/api/provide.py:39
msgid "method"
msgstr "方法"
#: apps/models_provider/api/provide.py:40 apps/tools/serializers/tool.py:23
#: apps/tools/serializers/tool.py:37
msgid "required"
msgstr "必填"
#: apps/models_provider/api/provide.py:41
msgid "default value"
msgstr "默認值"
#: apps/models_provider/api/provide.py:42
msgid "relation show field dict"
msgstr "關係顯示欄位"
#: apps/models_provider/api/provide.py:43
msgid "relation trigger field dict"
msgstr "關係觸發欄位"
#: apps/models_provider/api/provide.py:44
msgid "trigger type"
msgstr "觸發類型"
#: apps/models_provider/api/provide.py:45
msgid "attrs"
msgstr "屬性"
#: apps/models_provider/api/provide.py:46
msgid "props info"
msgstr "props 信息"
#: apps/models_provider/base_model_provider.py:60
msgid "Model type cannot be empty"
msgstr "模型類型不能為空"
#: apps/models_provider/base_model_provider.py:85
msgid "The current platform does not support downloading models"
msgstr "當前平臺不支持下載模型"
#: apps/models_provider/base_model_provider.py:140
msgid "LLM"
msgstr "大語言模型"
#: apps/models_provider/base_model_provider.py:141
msgid "Embedding Model"
msgstr "向量模型"
#: apps/models_provider/base_model_provider.py:142
msgid "Speech2Text"
msgstr "語音識別"
#: apps/models_provider/base_model_provider.py:143
msgid "TTS"
msgstr "語音合成"
#: apps/models_provider/base_model_provider.py:144
msgid "Vision Model"
msgstr "視覺模型"
#: apps/models_provider/base_model_provider.py:145
msgid "Image Generation"
msgstr "圖片生成"
#: apps/models_provider/base_model_provider.py:146
msgid "Rerank"
msgstr "重排模型"
#: apps/models_provider/base_model_provider.py:220
msgid "The model does not support"
msgstr "模型不支持"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/aliyun_bai_lian_model_provider.py:42
msgid ""
"With the GTE-Rerank text sorting series model developed by Alibaba Tongyi "
"Lab, developers can integrate high-quality text retrieval and sorting "
"through the LlamaIndex framework."
msgstr ""
"阿里巴巴通義實驗室開發的GTE-Rerank文本排序系列模型，開發者可以通過LlamaIndex"
"框架進行集成高質量文本檢索、排序。"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/aliyun_bai_lian_model_provider.py:45
msgid ""
"Chinese (including various dialects such as Cantonese), English, Japanese, "
"and Korean support free switching between multiple languages."
msgstr "中文（含粵語等各種方言）、英文、日語、韓語支持多個語種自由切換"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/aliyun_bai_lian_model_provider.py:48
msgid ""
"CosyVoice is based on a new generation of large generative speech models, "
"which can predict emotions, intonation, rhythm, etc. based on context, and "
"has better anthropomorphic effects."
msgstr ""
"CosyVoice基於新一代生成式語音大模型，能根據上下文預測情緒、語調、韻律等，具有"
"更好的擬人效果"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/aliyun_bai_lian_model_provider.py:51
msgid ""
"Universal text vector is Tongyi Lab's multi-language text unified vector "
"model based on the LLM base. It provides high-level vector services for "
"multiple mainstream languages around the world and helps developers quickly "
"convert text data into high-quality vector data."
msgstr ""
"通用文本向量，是通義實驗室基於LLM底座的多語言文本統一向量模型，面向全球多個主"
"流語種，提供高水準的向量服務，幫助開發者將文本數據快速轉換為高質量的向量數"
"據。"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/aliyun_bai_lian_model_provider.py:69
#: apps/models_provider/impl/qwen_model_provider/qwen_model_provider.py:40
msgid ""
"Tongyi Wanxiang - a large image model for text generation, supports "
"bilingual input in Chinese and English, and supports the input of reference "
"pictures for reference content or reference style migration. Key styles "
"include but are not limited to watercolor, oil painting, Chinese painting, "
"sketch, flat illustration, two-dimensional, and 3D. Cartoon."
msgstr ""
"通義萬相-文本生成圖像大模型，支持中英文雙語輸入，支持輸入參考圖片進行參考內容"
"或者參考風格遷移，重點風格包括但不限於水彩、油畫、中國畫、素描、扁平插畫、二"
"次元、3D卡通。"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/aliyun_bai_lian_model_provider.py:95
msgid "Alibaba Cloud Bailian"
msgstr "阿里雲百鍊"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/embedding.py:53
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/image.py:50
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py:74
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/reranker.py:61
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/model/tti.py:43
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/model/tts.py:37
#: apps/models_provider/impl/anthropic_model_provider/credential/image.py:33
#: apps/models_provider/impl/anthropic_model_provider/credential/llm.py:57
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/embedding.py:34
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/llm.py:53
#: apps/models_provider/impl/azure_model_provider/credential/embedding.py:37
#: apps/models_provider/impl/azure_model_provider/credential/image.py:55
#: apps/models_provider/impl/azure_model_provider/credential/llm.py:69
#: apps/models_provider/impl/deepseek_model_provider/credential/llm.py:57
#: apps/models_provider/impl/gemini_model_provider/credential/embedding.py:36
#: apps/models_provider/impl/gemini_model_provider/credential/image.py:51
#: apps/models_provider/impl/gemini_model_provider/credential/llm.py:57
#: apps/models_provider/impl/gemini_model_provider/model/stt.py:43
#: apps/models_provider/impl/kimi_model_provider/credential/llm.py:57
#: apps/models_provider/impl/local_model_provider/credential/embedding.py:36
#: apps/models_provider/impl/local_model_provider/credential/reranker.py:37
#: apps/models_provider/impl/ollama_model_provider/credential/embedding.py:37
#: apps/models_provider/impl/ollama_model_provider/credential/reranker.py:44
#: apps/models_provider/impl/openai_model_provider/credential/embedding.py:36
#: apps/models_provider/impl/openai_model_provider/credential/image.py:54
#: apps/models_provider/impl/openai_model_provider/credential/llm.py:59
#: apps/models_provider/impl/qwen_model_provider/credential/image.py:56
#: apps/models_provider/impl/qwen_model_provider/credential/llm.py:56
#: apps/models_provider/impl/qwen_model_provider/model/tti.py:43
#: apps/models_provider/impl/siliconCloud_model_provider/credential/embedding.py:36
#: apps/models_provider/impl/siliconCloud_model_provider/credential/image.py:54
#: apps/models_provider/impl/siliconCloud_model_provider/credential/llm.py:58
#: apps/models_provider/impl/siliconCloud_model_provider/credential/reranker.py:37
#: apps/models_provider/impl/tencent_cloud_model_provider/credential/llm.py:58
#: apps/models_provider/impl/tencent_model_provider/credential/embedding.py:23
#: apps/models_provider/impl/tencent_model_provider/credential/image.py:56
#: apps/models_provider/impl/tencent_model_provider/credential/llm.py:51
#: apps/models_provider/impl/tencent_model_provider/model/tti.py:54
#: apps/models_provider/impl/vllm_model_provider/credential/embedding.py:36
#: apps/models_provider/impl/vllm_model_provider/credential/llm.py:50
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/embedding.py:36
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/image.py:52
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/llm.py:57
#: apps/models_provider/impl/volcanic_engine_model_provider/model/tts.py:77
#: apps/models_provider/impl/wenxin_model_provider/credential/embedding.py:31
#: apps/models_provider/impl/wenxin_model_provider/credential/llm.py:60
#: apps/models_provider/impl/xf_model_provider/credential/embedding.py:31
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:76
#: apps/models_provider/impl/xf_model_provider/model/tts.py:101
#: apps/models_provider/impl/xinference_model_provider/credential/embedding.py:31
#: apps/models_provider/impl/xinference_model_provider/credential/image.py:51
#: apps/models_provider/impl/xinference_model_provider/credential/llm.py:50
#: apps/models_provider/impl/xinference_model_provider/credential/reranker.py:34
#: apps/models_provider/impl/xinference_model_provider/model/tts.py:44
#: apps/models_provider/impl/zhipu_model_provider/credential/image.py:51
#: apps/models_provider/impl/zhipu_model_provider/credential/llm.py:56
#: apps/models_provider/impl/zhipu_model_provider/model/tti.py:49
msgid "Hello"
msgstr "你好"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/image.py:36
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py:60
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/reranker.py:46
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/stt.py:44
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:96
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:89
#: apps/models_provider/impl/anthropic_model_provider/credential/image.py:23
#: apps/models_provider/impl/anthropic_model_provider/credential/llm.py:47
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/embedding.py:21
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/llm.py:40
#: apps/models_provider/impl/azure_model_provider/credential/embedding.py:27
#: apps/models_provider/impl/azure_model_provider/credential/image.py:45
#: apps/models_provider/impl/azure_model_provider/credential/llm.py:59
#: apps/models_provider/impl/azure_model_provider/credential/stt.py:23
#: apps/models_provider/impl/azure_model_provider/credential/tti.py:58
#: apps/models_provider/impl/azure_model_provider/credential/tts.py:41
#: apps/models_provider/impl/deepseek_model_provider/credential/llm.py:47
#: apps/models_provider/impl/gemini_model_provider/credential/embedding.py:26
#: apps/models_provider/impl/gemini_model_provider/credential/image.py:41
#: apps/models_provider/impl/gemini_model_provider/credential/llm.py:47
#: apps/models_provider/impl/gemini_model_provider/credential/stt.py:21
#: apps/models_provider/impl/kimi_model_provider/credential/llm.py:47
#: apps/models_provider/impl/local_model_provider/credential/embedding.py:27
#: apps/models_provider/impl/local_model_provider/credential/reranker.py:28
#: apps/models_provider/impl/ollama_model_provider/credential/embedding.py:26
#: apps/models_provider/impl/ollama_model_provider/credential/image.py:39
#: apps/models_provider/impl/ollama_model_provider/credential/llm.py:44
#: apps/models_provider/impl/ollama_model_provider/credential/reranker.py:27
#: apps/models_provider/impl/ollama_model_provider/credential/reranker.py:31
#: apps/models_provider/impl/openai_model_provider/credential/embedding.py:26
#: apps/models_provider/impl/openai_model_provider/credential/image.py:44
#: apps/models_provider/impl/openai_model_provider/credential/llm.py:48
#: apps/models_provider/impl/openai_model_provider/credential/stt.py:22
#: apps/models_provider/impl/openai_model_provider/credential/tti.py:61
#: apps/models_provider/impl/openai_model_provider/credential/tts.py:40
#: apps/models_provider/impl/qwen_model_provider/credential/image.py:47
#: apps/models_provider/impl/qwen_model_provider/credential/llm.py:47
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:68
#: apps/models_provider/impl/siliconCloud_model_provider/credential/embedding.py:26
#: apps/models_provider/impl/siliconCloud_model_provider/credential/image.py:44
#: apps/models_provider/impl/siliconCloud_model_provider/credential/llm.py:47
#: apps/models_provider/impl/siliconCloud_model_provider/credential/reranker.py:28
#: apps/models_provider/impl/siliconCloud_model_provider/credential/stt.py:22
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tti.py:61
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tts.py:22
#: apps/models_provider/impl/tencent_cloud_model_provider/credential/llm.py:47
#: apps/models_provider/impl/tencent_model_provider/credential/embedding.py:19
#: apps/models_provider/impl/tencent_model_provider/credential/image.py:47
#: apps/models_provider/impl/tencent_model_provider/credential/llm.py:31
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:78
#: apps/models_provider/impl/vllm_model_provider/credential/embedding.py:26
#: apps/models_provider/impl/vllm_model_provider/credential/image.py:42
#: apps/models_provider/impl/vllm_model_provider/credential/llm.py:39
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/embedding.py:26
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/image.py:42
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/llm.py:47
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/stt.py:25
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tti.py:41
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tts.py:51
#: apps/models_provider/impl/wenxin_model_provider/credential/embedding.py:27
#: apps/models_provider/impl/wenxin_model_provider/credential/llm.py:46
#: apps/models_provider/impl/xf_model_provider/credential/embedding.py:27
#: apps/models_provider/impl/xf_model_provider/credential/image.py:29
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:66
#: apps/models_provider/impl/xf_model_provider/credential/stt.py:24
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:47
#: apps/models_provider/impl/xinference_model_provider/credential/embedding.py:19
#: apps/models_provider/impl/xinference_model_provider/credential/image.py:41
#: apps/models_provider/impl/xinference_model_provider/credential/llm.py:39
#: apps/models_provider/impl/xinference_model_provider/credential/reranker.py:25
#: apps/models_provider/impl/xinference_model_provider/credential/stt.py:21
#: apps/models_provider/impl/xinference_model_provider/credential/tti.py:59
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:39
#: apps/models_provider/impl/zhipu_model_provider/credential/image.py:41
#: apps/models_provider/impl/zhipu_model_provider/credential/llm.py:47
#: apps/models_provider/impl/zhipu_model_provider/credential/tti.py:40
#, python-brace-format
msgid "{model_type} Model type is not supported"
msgstr "{model_type} 模型類型不支持"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/image.py:44
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py:68
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/reranker.py:55
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/stt.py:53
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:105
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:98
#, python-brace-format
msgid "{key} is required"
msgstr "{key} 是必填項"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/image.py:60
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py:82
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/reranker.py:69
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/stt.py:67
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:121
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:113
#: apps/models_provider/impl/anthropic_model_provider/credential/image.py:43
#: apps/models_provider/impl/anthropic_model_provider/credential/llm.py:65
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/embedding.py:42
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/llm.py:61
#: apps/models_provider/impl/azure_model_provider/credential/image.py:65
#: apps/models_provider/impl/azure_model_provider/credential/stt.py:40
#: apps/models_provider/impl/azure_model_provider/credential/tti.py:77
#: apps/models_provider/impl/azure_model_provider/credential/tts.py:58
#: apps/models_provider/impl/deepseek_model_provider/credential/llm.py:65
#: apps/models_provider/impl/gemini_model_provider/credential/embedding.py:43
#: apps/models_provider/impl/gemini_model_provider/credential/image.py:61
#: apps/models_provider/impl/gemini_model_provider/credential/llm.py:66
#: apps/models_provider/impl/gemini_model_provider/credential/stt.py:38
#: apps/models_provider/impl/kimi_model_provider/credential/llm.py:64
#: apps/models_provider/impl/local_model_provider/credential/embedding.py:44
#: apps/models_provider/impl/local_model_provider/credential/reranker.py:45
#: apps/models_provider/impl/ollama_model_provider/credential/reranker.py:51
#: apps/models_provider/impl/openai_model_provider/credential/embedding.py:43
#: apps/models_provider/impl/openai_model_provider/credential/image.py:64
#: apps/models_provider/impl/openai_model_provider/credential/llm.py:67
#: apps/models_provider/impl/openai_model_provider/credential/stt.py:39
#: apps/models_provider/impl/openai_model_provider/credential/tti.py:80
#: apps/models_provider/impl/openai_model_provider/credential/tts.py:58
#: apps/models_provider/impl/qwen_model_provider/credential/image.py:66
#: apps/models_provider/impl/qwen_model_provider/credential/llm.py:64
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:86
#: apps/models_provider/impl/siliconCloud_model_provider/credential/embedding.py:43
#: apps/models_provider/impl/siliconCloud_model_provider/credential/image.py:64
#: apps/models_provider/impl/siliconCloud_model_provider/credential/llm.py:66
#: apps/models_provider/impl/siliconCloud_model_provider/credential/reranker.py:44
#: apps/models_provider/impl/siliconCloud_model_provider/credential/stt.py:39
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tti.py:80
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tts.py:40
#: apps/models_provider/impl/tencent_cloud_model_provider/credential/llm.py:66
#: apps/models_provider/impl/tencent_model_provider/credential/embedding.py:30
#: apps/models_provider/impl/tencent_model_provider/credential/image.py:66
#: apps/models_provider/impl/tencent_model_provider/credential/llm.py:57
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:104
#: apps/models_provider/impl/vllm_model_provider/credential/embedding.py:43
#: apps/models_provider/impl/vllm_model_provider/credential/image.py:62
#: apps/models_provider/impl/vllm_model_provider/credential/llm.py:55
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/embedding.py:43
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/image.py:62
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/llm.py:66
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/stt.py:42
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tti.py:58
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tts.py:68
#: apps/models_provider/impl/wenxin_model_provider/credential/embedding.py:38
#: apps/models_provider/impl/xf_model_provider/credential/embedding.py:38
#: apps/models_provider/impl/xf_model_provider/credential/image.py:50
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:84
#: apps/models_provider/impl/xf_model_provider/credential/stt.py:41
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:65
#: apps/models_provider/impl/xinference_model_provider/credential/image.py:60
#: apps/models_provider/impl/xinference_model_provider/credential/reranker.py:40
#: apps/models_provider/impl/xinference_model_provider/credential/stt.py:37
#: apps/models_provider/impl/xinference_model_provider/credential/tti.py:77
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:56
#: apps/models_provider/impl/zhipu_model_provider/credential/image.py:61
#: apps/models_provider/impl/zhipu_model_provider/credential/llm.py:64
#: apps/models_provider/impl/zhipu_model_provider/credential/tti.py:59
#, python-brace-format
msgid ""
"Verification failed, please check whether the parameters are correct: {error}"
msgstr "認證失敗，請檢查參數是否正確：{error}"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py:17
#: apps/models_provider/impl/anthropic_model_provider/credential/llm.py:22
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/llm.py:14
#: apps/models_provider/impl/azure_model_provider/credential/image.py:17
#: apps/models_provider/impl/azure_model_provider/credential/llm.py:23
#: apps/models_provider/impl/deepseek_model_provider/credential/llm.py:22
#: apps/models_provider/impl/gemini_model_provider/credential/image.py:15
#: apps/models_provider/impl/gemini_model_provider/credential/llm.py:22
#: apps/models_provider/impl/kimi_model_provider/credential/llm.py:22
#: apps/models_provider/impl/ollama_model_provider/credential/image.py:12
#: apps/models_provider/impl/ollama_model_provider/credential/llm.py:20
#: apps/models_provider/impl/openai_model_provider/credential/image.py:17
#: apps/models_provider/impl/openai_model_provider/credential/llm.py:23
#: apps/models_provider/impl/qwen_model_provider/credential/image.py:22
#: apps/models_provider/impl/qwen_model_provider/credential/llm.py:22
#: apps/models_provider/impl/siliconCloud_model_provider/credential/image.py:17
#: apps/models_provider/impl/siliconCloud_model_provider/credential/llm.py:22
#: apps/models_provider/impl/tencent_cloud_model_provider/credential/llm.py:22
#: apps/models_provider/impl/tencent_model_provider/credential/image.py:22
#: apps/models_provider/impl/tencent_model_provider/credential/llm.py:14
#: apps/models_provider/impl/vllm_model_provider/credential/image.py:15
#: apps/models_provider/impl/vllm_model_provider/credential/llm.py:15
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/image.py:15
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/llm.py:22
#: apps/models_provider/impl/wenxin_model_provider/credential/llm.py:22
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:22
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:41
#: apps/models_provider/impl/xinference_model_provider/credential/image.py:14
#: apps/models_provider/impl/xinference_model_provider/credential/llm.py:15
#: apps/models_provider/impl/zhipu_model_provider/credential/image.py:15
#: apps/models_provider/impl/zhipu_model_provider/credential/llm.py:22
msgid "Temperature"
msgstr "溫度"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py:18
#: apps/models_provider/impl/anthropic_model_provider/credential/llm.py:23
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/llm.py:15
#: apps/models_provider/impl/azure_model_provider/credential/image.py:18
#: apps/models_provider/impl/azure_model_provider/credential/llm.py:24
#: apps/models_provider/impl/deepseek_model_provider/credential/llm.py:23
#: apps/models_provider/impl/gemini_model_provider/credential/image.py:16
#: apps/models_provider/impl/gemini_model_provider/credential/llm.py:23
#: apps/models_provider/impl/kimi_model_provider/credential/llm.py:23
#: apps/models_provider/impl/ollama_model_provider/credential/image.py:13
#: apps/models_provider/impl/ollama_model_provider/credential/llm.py:21
#: apps/models_provider/impl/openai_model_provider/credential/image.py:18
#: apps/models_provider/impl/openai_model_provider/credential/llm.py:24
#: apps/models_provider/impl/qwen_model_provider/credential/image.py:23
#: apps/models_provider/impl/qwen_model_provider/credential/llm.py:23
#: apps/models_provider/impl/siliconCloud_model_provider/credential/image.py:18
#: apps/models_provider/impl/siliconCloud_model_provider/credential/llm.py:23
#: apps/models_provider/impl/tencent_cloud_model_provider/credential/llm.py:23
#: apps/models_provider/impl/tencent_model_provider/credential/image.py:23
#: apps/models_provider/impl/tencent_model_provider/credential/llm.py:15
#: apps/models_provider/impl/vllm_model_provider/credential/image.py:16
#: apps/models_provider/impl/vllm_model_provider/credential/llm.py:16
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/image.py:16
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/llm.py:23
#: apps/models_provider/impl/wenxin_model_provider/credential/llm.py:23
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:23
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:42
#: apps/models_provider/impl/xinference_model_provider/credential/image.py:15
#: apps/models_provider/impl/xinference_model_provider/credential/llm.py:16
#: apps/models_provider/impl/zhipu_model_provider/credential/image.py:16
#: apps/models_provider/impl/zhipu_model_provider/credential/llm.py:23
msgid ""
"Higher values make the output more random, while lower values make it more "
"focused and deterministic"
msgstr "較高的數值會使輸出更加隨機，而較低的數值會使其更加集中和確定"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py:30
#: apps/models_provider/impl/anthropic_model_provider/credential/llm.py:31
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/llm.py:23
#: apps/models_provider/impl/azure_model_provider/credential/image.py:26
#: apps/models_provider/impl/azure_model_provider/credential/llm.py:32
#: apps/models_provider/impl/azure_model_provider/credential/llm.py:43
#: apps/models_provider/impl/deepseek_model_provider/credential/llm.py:31
#: apps/models_provider/impl/gemini_model_provider/credential/image.py:24
#: apps/models_provider/impl/gemini_model_provider/credential/llm.py:31
#: apps/models_provider/impl/kimi_model_provider/credential/llm.py:31
#: apps/models_provider/impl/ollama_model_provider/credential/image.py:21
#: apps/models_provider/impl/ollama_model_provider/credential/llm.py:29
#: apps/models_provider/impl/openai_model_provider/credential/image.py:26
#: apps/models_provider/impl/openai_model_provider/credential/llm.py:32
#: apps/models_provider/impl/qwen_model_provider/credential/image.py:31
#: apps/models_provider/impl/qwen_model_provider/credential/llm.py:31
#: apps/models_provider/impl/siliconCloud_model_provider/credential/image.py:26
#: apps/models_provider/impl/siliconCloud_model_provider/credential/llm.py:31
#: apps/models_provider/impl/tencent_cloud_model_provider/credential/llm.py:31
#: apps/models_provider/impl/tencent_model_provider/credential/image.py:31
#: apps/models_provider/impl/vllm_model_provider/credential/image.py:24
#: apps/models_provider/impl/vllm_model_provider/credential/llm.py:24
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/image.py:24
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/llm.py:31
#: apps/models_provider/impl/wenxin_model_provider/credential/llm.py:31
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:31
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:50
#: apps/models_provider/impl/xinference_model_provider/credential/image.py:23
#: apps/models_provider/impl/xinference_model_provider/credential/llm.py:24
#: apps/models_provider/impl/zhipu_model_provider/credential/image.py:24
#: apps/models_provider/impl/zhipu_model_provider/credential/llm.py:31
msgid "Output the maximum Tokens"
msgstr "輸出最大Token數"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py:31
msgid "Specify the maximum number of tokens that the model can generate."
msgstr "指定模型可以生成的最大 tokens 數"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py:44
#: apps/models_provider/impl/anthropic_model_provider/credential/image.py:15
#: apps/models_provider/impl/anthropic_model_provider/credential/llm.py:74
msgid "API URL"
msgstr ""
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py:45
#: apps/models_provider/impl/anthropic_model_provider/credential/image.py:16
#: apps/models_provider/impl/anthropic_model_provider/credential/llm.py:75
msgid "API Key"
msgstr ""
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:20
#: apps/models_provider/impl/azure_model_provider/credential/tti.py:15
#: apps/models_provider/impl/openai_model_provider/credential/tti.py:15
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:22
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tti.py:15
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tti.py:15
#: apps/models_provider/impl/xinference_model_provider/credential/tti.py:14
#: apps/models_provider/impl/zhipu_model_provider/credential/tti.py:15
#, fuzzy
#| msgid "page size"
msgid "Image size"
msgstr "每頁大小"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:20
#: apps/models_provider/impl/azure_model_provider/credential/tti.py:15
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:22
msgid "Specify the size of the generated image, such as: 1024x1024"
msgstr "指定生成圖片的尺寸, 如: 1024x1024"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:34
#: apps/models_provider/impl/azure_model_provider/credential/tti.py:40
#: apps/models_provider/impl/openai_model_provider/credential/tti.py:43
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:34
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tti.py:43
#: apps/models_provider/impl/xinference_model_provider/credential/tti.py:41
msgid "Number of pictures"
msgstr "圖片數量"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:34
#: apps/models_provider/impl/azure_model_provider/credential/tti.py:40
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:34
msgid "Specify the number of generated images"
msgstr "指定生成圖片的數量"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:44
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:41
msgid "Style"
msgstr "風格"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:44
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:41
msgid "Specify the style of generated images"
msgstr "指定生成圖片的風格"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:48
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:45
msgid "Default value, the image style is randomly output by the model"
msgstr "默認值，圖片風格由模型隨機輸出"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:49
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:46
msgid "photography"
msgstr "攝影"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:50
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:47
msgid "Portraits"
msgstr "人像寫真"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:51
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:48
msgid "3D cartoon"
msgstr "3D卡通"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:52
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:49
msgid "animation"
msgstr "動畫"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:53
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:50
msgid "painting"
msgstr "油畫"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:54
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:51
msgid "watercolor"
msgstr "水彩"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:55
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:52
msgid "sketch"
msgstr "素描"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:56
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:53
msgid "Chinese painting"
msgstr "中國畫"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tti.py:57
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:54
msgid "flat illustration"
msgstr "扁平插畫"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:20
#, fuzzy
#| msgid "timbre"
msgid "Timbre"
msgstr "音色"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:20
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tts.py:15
msgid "Chinese sounds can support mixed scenes of Chinese and English"
msgstr "中文音色支持中英文混合場景"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:26
msgid "Long Xiaochun"
msgstr "龍小淳"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:27
msgid "Long Xiaoxia"
msgstr "龍小夏"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:28
msgid "Long Xiaochen"
msgstr "龍小誠"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:29
msgid "Long Xiaobai"
msgstr "龍小白"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:30
#, fuzzy
#| msgid "Long laotie"
msgid "Long Laotie"
msgstr "龍老鐵"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:31
msgid "Long Shu"
msgstr "龍書"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:32
msgid "Long Shuo"
msgstr "龍碩"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:33
msgid "Long Jing"
msgstr "龍婧"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:34
msgid "Long Miao"
msgstr "龍妙"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:35
msgid "Long Yue"
msgstr "龍悅"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:36
msgid "Long Yuan"
msgstr "龍媛"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:37
msgid "Long Fei"
msgstr "龍飛"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:38
msgid "Long Jielidou"
msgstr "龍傑力豆"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:39
msgid "Long Tong"
msgstr "龍彤"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:40
msgid "Long Xiang"
msgstr "龍祥"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:47
msgid "Speaking speed"
msgstr "語速"
#: apps/models_provider/impl/aliyun_bai_lian_model_provider/credential/tts.py:47
msgid "[0.5, 2], the default is 1, usually one decimal place is enough"
msgstr "[0.5,2]，默認為1，通常一位小數就足夠了"
#: apps/models_provider/impl/anthropic_model_provider/credential/image.py:28
#: apps/models_provider/impl/anthropic_model_provider/credential/llm.py:52
#: apps/models_provider/impl/azure_model_provider/credential/embedding.py:32
#: apps/models_provider/impl/azure_model_provider/credential/image.py:50
#: apps/models_provider/impl/azure_model_provider/credential/llm.py:64
#: apps/models_provider/impl/azure_model_provider/credential/stt.py:28
#: apps/models_provider/impl/azure_model_provider/credential/tti.py:63
#: apps/models_provider/impl/azure_model_provider/credential/tts.py:46
#: apps/models_provider/impl/deepseek_model_provider/credential/llm.py:52
#: apps/models_provider/impl/gemini_model_provider/credential/embedding.py:31
#: apps/models_provider/impl/gemini_model_provider/credential/image.py:46
#: apps/models_provider/impl/gemini_model_provider/credential/llm.py:52
#: apps/models_provider/impl/gemini_model_provider/credential/stt.py:26
#: apps/models_provider/impl/kimi_model_provider/credential/llm.py:52
#: apps/models_provider/impl/local_model_provider/credential/embedding.py:31
#: apps/models_provider/impl/local_model_provider/credential/reranker.py:32
#: apps/models_provider/impl/ollama_model_provider/credential/embedding.py:46
#: apps/models_provider/impl/ollama_model_provider/credential/llm.py:62
#: apps/models_provider/impl/ollama_model_provider/credential/reranker.py:63
#: apps/models_provider/impl/openai_model_provider/credential/embedding.py:31
#: apps/models_provider/impl/openai_model_provider/credential/image.py:49
#: apps/models_provider/impl/openai_model_provider/credential/llm.py:53
#: apps/models_provider/impl/openai_model_provider/credential/stt.py:27
#: apps/models_provider/impl/openai_model_provider/credential/tti.py:66
#: apps/models_provider/impl/openai_model_provider/credential/tts.py:45
#: apps/models_provider/impl/qwen_model_provider/credential/image.py:51
#: apps/models_provider/impl/qwen_model_provider/credential/llm.py:51
#: apps/models_provider/impl/qwen_model_provider/credential/tti.py:72
#: apps/models_provider/impl/siliconCloud_model_provider/credential/embedding.py:31
#: apps/models_provider/impl/siliconCloud_model_provider/credential/image.py:49
#: apps/models_provider/impl/siliconCloud_model_provider/credential/llm.py:52
#: apps/models_provider/impl/siliconCloud_model_provider/credential/reranker.py:32
#: apps/models_provider/impl/siliconCloud_model_provider/credential/stt.py:27
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tti.py:66
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tts.py:27
#: apps/models_provider/impl/tencent_cloud_model_provider/credential/llm.py:52
#: apps/models_provider/impl/tencent_model_provider/credential/image.py:51
#: apps/models_provider/impl/vllm_model_provider/credential/embedding.py:31
#: apps/models_provider/impl/vllm_model_provider/credential/image.py:47
#: apps/models_provider/impl/vllm_model_provider/credential/llm.py:65
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/embedding.py:31
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/image.py:47
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/llm.py:52
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/stt.py:30
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tti.py:46
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tts.py:56
#: apps/models_provider/impl/wenxin_model_provider/credential/llm.py:55
#: apps/models_provider/impl/wenxin_model_provider/credential/llm.py:72
#: apps/models_provider/impl/xf_model_provider/credential/image.py:34
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:71
#: apps/models_provider/impl/xf_model_provider/credential/stt.py:29
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:52
#: apps/models_provider/impl/xinference_model_provider/credential/embedding.py:40
#: apps/models_provider/impl/xinference_model_provider/credential/image.py:46
#: apps/models_provider/impl/xinference_model_provider/credential/llm.py:59
#: apps/models_provider/impl/xinference_model_provider/credential/reranker.py:29
#: apps/models_provider/impl/xinference_model_provider/credential/stt.py:26
#: apps/models_provider/impl/xinference_model_provider/credential/tti.py:64
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:44
#: apps/models_provider/impl/zhipu_model_provider/credential/image.py:46
#: apps/models_provider/impl/zhipu_model_provider/credential/llm.py:51
#: apps/models_provider/impl/zhipu_model_provider/credential/tti.py:45
#, python-brace-format
msgid "{key} is required"
msgstr "{key} 是必填項"
#: apps/models_provider/impl/anthropic_model_provider/credential/llm.py:32
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/llm.py:24
#: apps/models_provider/impl/azure_model_provider/credential/image.py:27
#: apps/models_provider/impl/azure_model_provider/credential/llm.py:33
#: apps/models_provider/impl/azure_model_provider/credential/llm.py:44
#: apps/models_provider/impl/deepseek_model_provider/credential/llm.py:32
#: apps/models_provider/impl/gemini_model_provider/credential/image.py:25
#: apps/models_provider/impl/gemini_model_provider/credential/llm.py:32
#: apps/models_provider/impl/kimi_model_provider/credential/llm.py:32
#: apps/models_provider/impl/ollama_model_provider/credential/image.py:22
#: apps/models_provider/impl/ollama_model_provider/credential/llm.py:30
#: apps/models_provider/impl/openai_model_provider/credential/image.py:27
#: apps/models_provider/impl/openai_model_provider/credential/llm.py:33
#: apps/models_provider/impl/qwen_model_provider/credential/image.py:32
#: apps/models_provider/impl/qwen_model_provider/credential/llm.py:32
#: apps/models_provider/impl/siliconCloud_model_provider/credential/image.py:27
#: apps/models_provider/impl/siliconCloud_model_provider/credential/llm.py:32
#: apps/models_provider/impl/tencent_cloud_model_provider/credential/llm.py:32
#: apps/models_provider/impl/tencent_model_provider/credential/image.py:32
#: apps/models_provider/impl/vllm_model_provider/credential/image.py:25
#: apps/models_provider/impl/vllm_model_provider/credential/llm.py:25
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/image.py:25
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/llm.py:32
#: apps/models_provider/impl/wenxin_model_provider/credential/llm.py:32
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:32
#: apps/models_provider/impl/xf_model_provider/credential/llm.py:51
#: apps/models_provider/impl/xinference_model_provider/credential/image.py:24
#: apps/models_provider/impl/xinference_model_provider/credential/llm.py:25
#: apps/models_provider/impl/zhipu_model_provider/credential/image.py:25
#: apps/models_provider/impl/zhipu_model_provider/credential/llm.py:32
msgid "Specify the maximum number of tokens that the model can generate"
msgstr "指定模型可以生成的最大 tokens 數"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:36
msgid ""
"An update to Claude 2 that doubles the context window and improves "
"reliability, hallucination rates, and evidence-based accuracy in long "
"documents and RAG contexts."
msgstr ""
"Claude 2 的更新，採用雙倍的上下文窗口，並在長文檔和 RAG 上下文中提高可靠性、"
"幻覺率和循證準確性。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:43
msgid ""
"Anthropic is a powerful model that can handle a variety of tasks, from "
"complex dialogue and creative content generation to detailed command "
"obedience."
msgstr ""
"Anthropic 功能強大的模型，可處理各種任務，從複雜的對話和創意內容生成到詳細的"
"指令服從。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:50
msgid ""
"The Claude 3 Haiku is Anthropic's fastest and most compact model, with near-"
"instant responsiveness. The model can answer simple queries and requests "
"quickly. Customers will be able to build seamless AI experiences that mimic "
"human interactions. Claude 3 Haiku can process images and return text "
"output, and provides 200K context windows."
msgstr ""
"Claude 3 Haiku 是 Anthropic 最快速、最緊湊的模型，具有近乎即時的響應能力。該"
"模型可以快速回答簡單的查詢和請求。客戶將能夠構建模仿人類交互的無縫人工智慧體"
"驗。 Claude 3 Haiku 可以處理圖像和返回文本輸出，並且提供 200K 上下文窗口。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:57
msgid ""
"The Claude 3 Sonnet model from Anthropic strikes the ideal balance between "
"intelligence and speed, especially when it comes to handling enterprise "
"workloads. This model offers maximum utility while being priced lower than "
"competing products, and it's been engineered to be a solid choice for "
"deploying AI at scale."
msgstr ""
"Anthropic 推出的 Claude 3 Sonnet 模型在智能和速度之間取得理想的平衡，尤其是在"
"處理企業工作負載方面。該模型提供最大的效用，同時價格低於競爭產品，並且其經過"
"精心設計，是大規模部署人工智慧的可靠選擇。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:64
msgid ""
"The Claude 3.5 Sonnet raises the industry standard for intelligence, "
"outperforming competing models and the Claude 3 Opus in extensive "
"evaluations, with the speed and cost-effectiveness of our mid-range models."
msgstr ""
"Claude 3.5 Sonnet提高了智能的行業標準，在廣泛的評估中超越了競爭對手的型號和"
"Claude 3 Opus，具有我們中端型號的速度和成本效益。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:71
msgid ""
"A faster, more affordable but still very powerful model that can handle a "
"range of tasks including casual conversation, text analysis, summarization "
"and document question answering."
msgstr ""
"一種更快速、更實惠但仍然非常強大的模型，它可以處理一系列任務，包括隨意對話、"
"文本分析、摘要和文檔問題回答。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:78
msgid ""
"Titan Text Premier is the most powerful and advanced model in the Titan Text "
"series, designed to deliver exceptional performance for a variety of "
"enterprise applications. With its cutting-edge features, it delivers greater "
"accuracy and outstanding results, making it an excellent choice for "
"organizations looking for a top-notch text processing solution."
msgstr ""
"Titan Text Premier 是 Titan Text 系列中功能強大且先進的型號，旨在為各種企業應"
"用程序提供卓越的性能。憑藉其尖端功能，它提供了更高的準確性和出色的結果，使其"
"成為尋求一流文本處理解決方案的組織的絕佳選擇。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:85
msgid ""
"Amazon Titan Text Lite is a lightweight, efficient model ideal for fine-"
"tuning English-language tasks, including summarization and copywriting, "
"where customers require smaller, more cost-effective, and highly "
"customizable models."
msgstr ""
"Amazon Titan Text Lite 是一種輕量級的高效模型，非常適合英語任務的微調，包括摘"
"要和文案寫作等，在這種場景下，客戶需要更小、更經濟高效且高度可定製的模型"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:91
msgid ""
"Amazon Titan Text Express has context lengths of up to 8,000 tokens, making "
"it ideal for a variety of high-level general language tasks, such as open-"
"ended text generation and conversational chat, as well as support in "
"retrieval-augmented generation (RAG). At launch, the model is optimized for "
"English, but other languages are supported."
msgstr ""
"Amazon Titan Text Express 的上下文長度長達 8000 個 tokens，因而非常適合各種高"
"級常規語言任務，例如開放式文本生成和對話式聊天，以及檢索增強生成（RAG）中的支"
"持。在發布時，該模型針對英語進行了優化，但也支持其他語言。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:97
msgid ""
"7B dense converter for rapid deployment and easy customization. Small in "
"size yet powerful in a variety of use cases. Supports English and code, as "
"well as 32k context windows."
msgstr ""
"7B 密集型轉換器，可快速部署，易於定製。體積雖小，但功能強大，適用於各種用例。"
"支持英語和代碼，以及 32k 的上下文窗口。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:103
msgid ""
"Advanced Mistral AI large-scale language model capable of handling any "
"language task, including complex multilingual reasoning, text understanding, "
"transformation, and code generation."
msgstr ""
"先進的 Mistral AI 大型語言模型，能夠處理任何語言任務，包括複雜的多語言推理、"
"文本理解、轉換和代碼生成。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:109
msgid ""
"Ideal for content creation, conversational AI, language understanding, R&D, "
"and enterprise applications"
msgstr "非常適合內容創作、會話式人工智慧、語言理解、研發和企業應用"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:115
msgid ""
"Ideal for limited computing power and resources, edge devices, and faster "
"training times."
msgstr "非常適合有限的計算能力和資源、邊緣設備和更快的訓練時間。"
#: apps/models_provider/impl/aws_bedrock_model_provider/aws_bedrock_model_provider.py:123
msgid ""
"Titan Embed Text is the largest embedding model in the Amazon Titan Embed "
"series and can handle various text embedding tasks, such as text "
"classification, text similarity calculation, etc."
msgstr ""
"Titan Embed Text 是 Amazon Titan Embed 系列中最大的嵌入模型，可以處理各種文本"
"嵌入任務，如文本分類、文本相似度計算等。"
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/embedding.py:28
#: apps/models_provider/impl/aws_bedrock_model_provider/credential/llm.py:47
#, python-brace-format
msgid "The following fields are required: {keys}"
msgstr "以下欄位是必填項: {keys}"
#: apps/models_provider/impl/azure_model_provider/credential/embedding.py:44
#: apps/models_provider/impl/azure_model_provider/credential/llm.py:76
msgid "Verification failed, please check whether the parameters are correct"
msgstr "認證失敗，請檢查參數是否正確"
#: apps/models_provider/impl/azure_model_provider/credential/tti.py:28
#: apps/models_provider/impl/openai_model_provider/credential/tti.py:29
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tti.py:29
#: apps/models_provider/impl/xinference_model_provider/credential/tti.py:28
msgid "Picture quality"
msgstr "圖片質量"
#: apps/models_provider/impl/azure_model_provider/credential/tts.py:17
#: apps/models_provider/impl/openai_model_provider/credential/tts.py:17
msgid ""
"Try out the different sounds (Alloy, Echo, Fable, Onyx, Nova, and Sparkle) "
"to find one that suits your desired tone and audience. The current voiceover "
"is optimized for English."
msgstr ""
"嘗試不同的聲音（合金、回聲、寓言、縞瑪瑙、新星和閃光），找到一種適合您所需的"
"音調和聽眾的聲音。當前的語音針對英語進行了優化。"
#: apps/models_provider/impl/deepseek_model_provider/deepseek_model_provider.py:24
msgid "Good at common conversational tasks, supports 32K contexts"
msgstr "擅長通用對話任務，支持 32K 上下文"
#: apps/models_provider/impl/deepseek_model_provider/deepseek_model_provider.py:29
msgid "Good at handling programming tasks, supports 16K contexts"
msgstr "擅長處理編程任務，支持 16K 上下文"
#: apps/models_provider/impl/gemini_model_provider/gemini_model_provider.py:32
msgid "Latest Gemini 1.0 Pro model, updated with Google update"
msgstr "最新的 Gemini 1.0 Pro 模型，更新了 Google 更新"
#: apps/models_provider/impl/gemini_model_provider/gemini_model_provider.py:36
msgid "Latest Gemini 1.0 Pro Vision model, updated with Google update"
msgstr "最新的Gemini 1.0 Pro Vision模型，隨Google更新而更新"
#: apps/models_provider/impl/gemini_model_provider/gemini_model_provider.py:43
#: apps/models_provider/impl/gemini_model_provider/gemini_model_provider.py:47
#: apps/models_provider/impl/gemini_model_provider/gemini_model_provider.py:54
#: apps/models_provider/impl/gemini_model_provider/gemini_model_provider.py:58
msgid "Latest Gemini 1.5 Flash model, updated with Google updates"
msgstr "最新的Gemini 1.5 Flash模型，隨Google更新而更新"
#: apps/models_provider/impl/gemini_model_provider/model/stt.py:53
msgid "convert audio to text"
msgstr "將音頻轉換為文本"
#: apps/models_provider/impl/local_model_provider/credential/embedding.py:53
#: apps/models_provider/impl/local_model_provider/credential/reranker.py:54
msgid "Model catalog"
msgstr "模型目錄"
#: apps/models_provider/impl/local_model_provider/local_model_provider.py:39
msgid "local model"
msgstr "本地模型"
#: apps/models_provider/impl/ollama_model_provider/credential/embedding.py:30
#: apps/models_provider/impl/ollama_model_provider/credential/image.py:43
#: apps/models_provider/impl/ollama_model_provider/credential/llm.py:48
#: apps/models_provider/impl/ollama_model_provider/credential/reranker.py:35
#: apps/models_provider/impl/vllm_model_provider/credential/llm.py:43
#: apps/models_provider/impl/xinference_model_provider/credential/embedding.py:24
#: apps/models_provider/impl/xinference_model_provider/credential/llm.py:44
msgid "API domain name is invalid"
msgstr "API 域名無效"
#: apps/models_provider/impl/ollama_model_provider/credential/embedding.py:35
#: apps/models_provider/impl/ollama_model_provider/credential/image.py:48
#: apps/models_provider/impl/ollama_model_provider/credential/llm.py:53
#: apps/models_provider/impl/ollama_model_provider/credential/reranker.py:40
#: apps/models_provider/impl/vllm_model_provider/credential/llm.py:47
#: apps/models_provider/impl/xinference_model_provider/credential/embedding.py:30
#: apps/models_provider/impl/xinference_model_provider/credential/llm.py:48
msgid "The model does not exist, please download the model first"
msgstr "模型不存在，請先下載模型"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:56
msgid ""
"Llama 2 is a set of pretrained and fine-tuned generative text models ranging "
"in size from 7 billion to 70 billion. This is a repository of 7B pretrained "
"models. Links to other models can be found in the index at the bottom."
msgstr ""
"Llama 2 是一組經過預訓練和微調的生成文本模型，其規模從 70 億到 700 億個不等。"
"這是 7B 預訓練模型的存儲庫。其他模型的連結可以在底部的索引中找到。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:60
msgid ""
"Llama 2 is a set of pretrained and fine-tuned generative text models ranging "
"in size from 7 billion to 70 billion. This is a repository of 13B pretrained "
"models. Links to other models can be found in the index at the bottom."
msgstr ""
"Llama 2 是一組經過預訓練和微調的生成文本模型，其規模從 70 億到 700 億個不等。"
"這是 13B 預訓練模型的存儲庫。其他模型的連結可以在底部的索引中找到。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:64
msgid ""
"Llama 2 is a set of pretrained and fine-tuned generative text models ranging "
"in size from 7 billion to 70 billion. This is a repository of 70B pretrained "
"models. Links to other models can be found in the index at the bottom."
msgstr ""
"Llama 2 是一組經過預訓練和微調的生成文本模型，其規模從 70 億到 700 億個不等。"
"這是 70B 預訓練模型的存儲庫。其他模型的連結可以在底部的索引中找到。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:68
msgid ""
"Since the Chinese alignment of Llama2 itself is weak, we use the Chinese "
"instruction set to fine-tune meta-llama/Llama-2-13b-chat-hf with LoRA so "
"that it has strong Chinese conversation capabilities."
msgstr ""
"由於Llama2本身的中文對齊較弱，我們採用中文指令集，對meta-llama/Llama-2-13b-"
"chat-hf進行LoRA微調，使其具備較強的中文對話能力。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:72
msgid ""
"Meta Llama 3: The most capable public product LLM to date. 8 billion "
"parameters."
msgstr "Meta Llama 3：迄今為止最有能力的公開產品LLM。80億參數。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:76
msgid ""
"Meta Llama 3: The most capable public product LLM to date. 70 billion "
"parameters."
msgstr "Meta Llama 3：迄今為止最有能力的公開產品LLM。700億參數。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:80
msgid ""
"Compared with previous versions, qwen 1.5 0.5b has significantly enhanced "
"the model's alignment with human preferences and its multi-language "
"processing capabilities. Models of all sizes support a context length of "
"32768 tokens. 500 million parameters."
msgstr ""
"qwen 1.5 0.5b 相較於以往版本，模型與人類偏好的對齊程度以及多語言處理能力上有"
"顯著增強。所有規模的模型都支持32768個tokens的上下文長度。5億參數。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:84
msgid ""
"Compared with previous versions, qwen 1.5 1.8b has significantly enhanced "
"the model's alignment with human preferences and its multi-language "
"processing capabilities. Models of all sizes support a context length of "
"32768 tokens. 1.8 billion parameters."
msgstr ""
"qwen 1.5 1.8b 相較於以往版本，模型與人類偏好的對齊程度以及多語言處理能力上有"
"顯著增強。所有規模的模型都支持32768個tokens的上下文長度。18億參數。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:88
msgid ""
"Compared with previous versions, qwen 1.5 4b has significantly enhanced the "
"model's alignment with human preferences and its multi-language processing "
"capabilities. Models of all sizes support a context length of 32768 tokens. "
"4 billion parameters."
msgstr ""
"qwen 1.5 4b 相較於以往版本，模型與人類偏好的對齊程度以及多語言處理能力上有顯"
"著增強。所有規模的模型都支持32768個tokens的上下文長度。40億參數。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:93
msgid ""
"Compared with previous versions, qwen 1.5 7b has significantly enhanced the "
"model's alignment with human preferences and its multi-language processing "
"capabilities. Models of all sizes support a context length of 32768 tokens. "
"7 billion parameters."
msgstr ""
"qwen 1.5 7b 相較於以往版本，模型與人類偏好的對齊程度以及多語言處理能力上有顯"
"著增強。所有規模的模型都支持32768個tokens的上下文長度。70億參數。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:97
msgid ""
"Compared with previous versions, qwen 1.5 14b has significantly enhanced the "
"model's alignment with human preferences and its multi-language processing "
"capabilities. Models of all sizes support a context length of 32768 tokens. "
"14 billion parameters."
msgstr ""
"qwen 1.5 14b 相較於以往版本，模型與人類偏好的對齊程度以及多語言處理能力上有顯"
"著增強。所有規模的模型都支持32768個tokens的上下文長度。140億參數。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:101
msgid ""
"Compared with previous versions, qwen 1.5 32b has significantly enhanced the "
"model's alignment with human preferences and its multi-language processing "
"capabilities. Models of all sizes support a context length of 32768 tokens. "
"32 billion parameters."
msgstr ""
"qwen 1.5 32b 相較於以往版本，模型與人類偏好的對齊程度以及多語言處理能力上有顯"
"著增強。所有規模的模型都支持32768個tokens的上下文長度。320億參數。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:105
msgid ""
"Compared with previous versions, qwen 1.5 72b has significantly enhanced the "
"model's alignment with human preferences and its multi-language processing "
"capabilities. Models of all sizes support a context length of 32768 tokens. "
"72 billion parameters."
msgstr ""
"qwen 1.5 72b 相較於以往版本，模型與人類偏好的對齊程度以及多語言處理能力上有顯"
"著增強。所有規模的模型都支持32768個tokens的上下文長度。720億參數。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:109
msgid ""
"Compared with previous versions, qwen 1.5 110b has significantly enhanced "
"the model's alignment with human preferences and its multi-language "
"processing capabilities. Models of all sizes support a context length of "
"32768 tokens. 110 billion parameters."
msgstr ""
"qwen 1.5 110b 相較於以往版本，模型與人類偏好的對齊程度以及多語言處理能力上有"
"顯著增強。所有規模的模型都支持32768個tokens的上下文長度。1100億參數。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:153
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:193
msgid ""
"Phi-3 Mini is Microsoft's 3.8B parameter, lightweight, state-of-the-art open "
"model."
msgstr "Phi-3 Mini是Microsoft的3.8B參數，輕量級，最先進的開放模型。"
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:162
#: apps/models_provider/impl/ollama_model_provider/ollama_model_provider.py:197
msgid ""
"A high-performance open embedding model with a large token context window."
msgstr "一個具有大 tokens上下文窗口的高性能開放嵌入模型。"
#: apps/models_provider/impl/openai_model_provider/credential/tti.py:16
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tti.py:16
msgid ""
"The image generation endpoint allows you to create raw images based on text "
"prompts. When using the DALL·E 3, the image size can be 1024x1024, 1024x1792 "
"or 1792x1024 pixels."
msgstr ""
"圖像生成端點允許您根據文本提示創建原始圖像。使用 DALL·E 3 時，圖像的尺寸可以"
"為 1024x1024、1024x1792 或 1792x1024 像素。"
#: apps/models_provider/impl/openai_model_provider/credential/tti.py:29
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tti.py:29
msgid ""
" \n"
"By default, images are produced in standard quality, but with DALL·E 3 you "
"can set quality: \"hd\" to enhance detail. Square, standard quality images "
"are generated fastest.\n"
" "
msgstr ""
"默認情況下，圖像以標準質量生成，但使用 DALL·E 3 時，您可以設置質量：「hd」以"
"增強細節。方形、標準質量的圖像生成速度最快。"
#: apps/models_provider/impl/openai_model_provider/credential/tti.py:44
#: apps/models_provider/impl/siliconCloud_model_provider/credential/tti.py:44
msgid ""
"You can use DALL·E 3 to request 1 image at a time (requesting more images by "
"issuing parallel requests), or use DALL·E 2 with the n parameter to request "
"up to 10 images at a time."
msgstr ""
"您可以使用 DALL·E 3 一次請求 1 個圖像（通過發出並行請求來請求更多圖像），或者"
"使用帶有 n 參數的 DALL·E 2 一次最多請求 10 個圖像。"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:35
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:119
#: apps/models_provider/impl/siliconCloud_model_provider/siliconCloud_model_provider.py:118
msgid "The latest gpt-3.5-turbo, updated with OpenAI adjustments"
msgstr "最新的gpt-3.5-turbo，隨OpenAI調整而更新"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:38
msgid "Latest gpt-4, updated with OpenAI adjustments"
msgstr "最新的gpt-4，隨OpenAI調整而更新"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:40
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:99
msgid ""
"The latest GPT-4o, cheaper and faster than gpt-4-turbo, updated with OpenAI "
"adjustments"
msgstr "最新的GPT-4o，比gpt-4-turbo更便宜、更快，隨OpenAI調整而更新"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:43
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:102
msgid ""
"The latest gpt-4o-mini, cheaper and faster than gpt-4o, updated with OpenAI "
"adjustments"
msgstr "最新的gpt-4o-mini，比gpt-4o更便宜、更快，隨OpenAI調整而更新"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:46
msgid "The latest gpt-4-turbo, updated with OpenAI adjustments"
msgstr "最新的gpt-4-turbo，隨OpenAI調整而更新"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:49
msgid "The latest gpt-4-turbo-preview, updated with OpenAI adjustments"
msgstr "最新的gpt-4-turbo-preview，隨OpenAI調整而更新"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:53
msgid ""
"gpt-3.5-turbo snapshot on January 25, 2024, supporting context length 16,385 "
"tokens"
msgstr "2024年1月25日的gpt-3.5-turbo快照，支持上下文長度16,385 tokens"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:57
msgid ""
"gpt-3.5-turbo snapshot on November 6, 2023, supporting context length 16,385 "
"tokens"
msgstr "2023年11月6日的gpt-3.5-turbo快照，支持上下文長度16,385 tokens"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:61
msgid ""
"[Legacy] gpt-3.5-turbo snapshot on June 13, 2023, will be deprecated on June "
"13, 2024"
msgstr "[Legacy] 2023年6月13日的gpt-3.5-turbo快照，將於2024年6月13日棄用"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:65
msgid ""
"gpt-4o snapshot on May 13, 2024, supporting context length 128,000 tokens"
msgstr "2024年5月13日的gpt-4o快照，支持上下文長度128,000 tokens"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:69
msgid ""
"gpt-4-turbo snapshot on April 9, 2024, supporting context length 128,000 "
"tokens"
msgstr "2024年4月9日的gpt-4-turbo快照，支持上下文長度128,000 tokens"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:72
msgid ""
"gpt-4-turbo snapshot on January 25, 2024, supporting context length 128,000 "
"tokens"
msgstr "2024年1月25日的gpt-4-turbo快照，支持上下文長度128,000 tokens"
#: apps/models_provider/impl/openai_model_provider/openai_model_provider.py:75
msgid ""
"gpt-4-turbo snapshot on November 6, 2023, supporting context length 128,000 "
"tokens"
msgstr "2023年11月6日的gpt-4-turbo快照，支持上下文長度128,000 tokens"
#: apps/models_provider/impl/qwen_model_provider/qwen_model_provider.py:63
msgid "Tongyi Qianwen"
msgstr "通義千問"
#: apps/models_provider/impl/tencent_cloud_model_provider/tencent_cloud_model_provider.py:58
msgid "Tencent Cloud"
msgstr "騰訊雲"
#: apps/models_provider/impl/tencent_model_provider/credential/llm.py:41
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:88
#, python-brace-format
msgid "{keys} is required"
msgstr "{keys} 是必填項"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:14
msgid "painting style"
msgstr "繪畫風格"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:14
msgid "If not passed, the default value is 201 (Japanese anime style)"
msgstr "如果未傳遞，則默認值為201（日本動漫風格）"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:18
msgid "Not limited to style"
msgstr "不限於風格"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:19
msgid "ink painting"
msgstr "水墨畫"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:20
msgid "concept art"
msgstr "概念藝術"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:21
msgid "Oil painting 1"
msgstr "油畫1"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:22
msgid "Oil Painting 2 (Van Gogh)"
msgstr "油畫2（梵谷）"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:23
msgid "watercolor painting"
msgstr "水彩畫"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:24
msgid "pixel art"
msgstr "像素畫"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:25
msgid "impasto style"
msgstr "厚塗風格"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:26
msgid "illustration"
msgstr "插圖"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:27
msgid "paper cut style"
msgstr "剪紙風格"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:28
msgid "Impressionism 1 (Monet)"
msgstr "印象派1（莫奈）"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:29
msgid "Impressionism 2"
msgstr "印象派2"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:31
msgid "classical portraiture"
msgstr "古典肖像畫"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:32
msgid "black and white sketch"
msgstr "黑白素描畫"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:33
msgid "cyberpunk"
msgstr "賽博朋克"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:34
msgid "science fiction style"
msgstr "科幻風格"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:35
msgid "dark style"
msgstr "暗黑風格"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:37
msgid "vaporwave"
msgstr "蒸汽波"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:38
msgid "Japanese animation"
msgstr "日系動漫"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:39
msgid "monster style"
msgstr "怪獸風格"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:40
msgid "Beautiful ancient style"
msgstr "唯美古風"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:41
msgid "retro anime"
msgstr "復古動漫"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:42
msgid "Game cartoon hand drawing"
msgstr "遊戲卡通手繪"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:43
msgid "Universal realistic style"
msgstr "通用寫實風格"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:50
msgid "Generate image resolution"
msgstr "生成圖像解析度"
#: apps/models_provider/impl/tencent_model_provider/credential/tti.py:50
msgid "If not transmitted, the default value is 768:768."
msgstr "不傳默認使用768:768。"
#: apps/models_provider/impl/tencent_model_provider/tencent_model_provider.py:38
msgid ""
"The most effective version of the current hybrid model, the trillion-level "
"parameter scale MOE-32K long article model. Reaching the absolute leading "
"level on various benchmarks, with complex instructions and reasoning, "
"complex mathematical capabilities, support for function call, and "
"application focus optimization in fields such as multi-language translation, "
"finance, law, and medical care"
msgstr ""
"當前混元模型中效果最優版本，萬億級參數規模 MOE-32K 長文模型。在各種 "
"benchmark 上達到絕對領先的水平，複雜指令和推理，具備複雜數學能力，支持 "
"functioncall，在多語言翻譯、金融法律醫療等領域應用重點優化"
#: apps/models_provider/impl/tencent_model_provider/tencent_model_provider.py:45
msgid ""
"A better routing strategy is adopted to simultaneously alleviate the "
"problems of load balancing and expert convergence. For long articles, the "
"needle-in-a-haystack index reaches 99.9%"
msgstr ""
"採用更優的路由策略，同時緩解了負載均衡和專家趨同的問題。長文方面，大海撈針指"
"標達到99.9%"
#: apps/models_provider/impl/tencent_model_provider/tencent_model_provider.py:51
msgid ""
"Upgraded to MOE structure, the context window is 256k, leading many open "
"source models in multiple evaluation sets such as NLP, code, mathematics, "
"industry, etc."
msgstr ""
"升級為 MOE 結構，上下文窗口為 256k ，在 NLP，代碼，數學，行業等多項評測集上領"
"先眾多開源模型"
#: apps/models_provider/impl/tencent_model_provider/tencent_model_provider.py:57
msgid ""
"Hunyuan's latest version of the role-playing model, a role-playing model "
"launched by Hunyuan's official fine-tuning training, is based on the Hunyuan "
"model combined with the role-playing scene data set for additional training, "
"and has better basic effects in role-playing scenes."
msgstr ""
"混元最新版角色扮演模型，混元官方精調訓練推出的角色扮演模型，基於混元模型結合"
"角色扮演場景數據集進行增訓，在角色扮演場景具有更好的基礎效果"
#: apps/models_provider/impl/tencent_model_provider/tencent_model_provider.py:63
msgid ""
"Hunyuan's latest MOE architecture FunctionCall model has been trained with "
"high-quality FunctionCall data and has a context window of 32K, leading in "
"multiple dimensions of evaluation indicators."
msgstr ""
"混元最新 MOE 架構 FunctionCall 模型，經過高質量的 FunctionCall 數據訓練，上下"
"文窗口達 32K，在多個維度的評測指標上處於領先。"
#: apps/models_provider/impl/tencent_model_provider/tencent_model_provider.py:69
msgid ""
"Hunyuan's latest code generation model, after training the base model with "
"200B high-quality code data, and iterating on high-quality SFT data for half "
"a year, the context long window length has been increased to 8K, and it "
"ranks among the top in the automatic evaluation indicators of code "
"generation in the five major languages; the five major languages In the "
"manual high-quality evaluation of 10 comprehensive code tasks that consider "
"all aspects, the performance is in the first echelon."
msgstr ""
"混元最新代碼生成模型，經過 200B 高質量代碼數據增訓基座模型，迭代半年高質量 "
"SFT 數據訓練，上下文長窗口長度增大到 8K，五大語言代碼生成自動評測指標上位居前"
"列；五大語言10項考量各方面綜合代碼任務人工高質量評測上，性能處於第一梯隊"
#: apps/models_provider/impl/tencent_model_provider/tencent_model_provider.py:77
msgid ""
"Tencent's Hunyuan Embedding interface can convert text into high-quality "
"vector data. The vector dimension is 1024 dimensions."
msgstr ""
"騰訊混元 Embedding 接口，可以將文本轉化為高質量的向量數據。向量維度為1024維。"
#: apps/models_provider/impl/tencent_model_provider/tencent_model_provider.py:87
msgid "Mixed element visual model"
msgstr "混元視覺模型"
#: apps/models_provider/impl/tencent_model_provider/tencent_model_provider.py:94
msgid "Hunyuan graph model"
msgstr "混元生圖模型"
#: apps/models_provider/impl/tencent_model_provider/tencent_model_provider.py:125
msgid "Tencent Hunyuan"
msgstr "騰訊混元"
#: apps/models_provider/impl/vllm_model_provider/vllm_model_provider.py:24
#: apps/models_provider/impl/vllm_model_provider/vllm_model_provider.py:42
msgid "Facebook’s 125M parameter model"
msgstr "Facebook的125M參數模型"
#: apps/models_provider/impl/vllm_model_provider/vllm_model_provider.py:25
msgid "BAAI’s 7B parameter model"
msgstr "BAAI的7B參數模型"
#: apps/models_provider/impl/vllm_model_provider/vllm_model_provider.py:26
msgid "BAAI’s 13B parameter mode"
msgstr "BAAI的13B參數模型"
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tti.py:16
msgid ""
"If the gap between width, height and 512 is too large, the picture rendering "
"effect will be poor and the probability of excessive delay will increase "
"significantly. Recommended ratio and corresponding width and height before "
"super score: width*height"
msgstr ""
"寬、高與512差距過大，則出圖效果不佳、延遲過長概率顯著增加。超分前建議比例及對"
"應寬高：width*height"
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tts.py:15
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:15
msgid "timbre"
msgstr "音色"
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tts.py:31
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:28
#, fuzzy
#| msgid "Speaking speed"
msgid "speaking speed"
msgstr "語速"
#: apps/models_provider/impl/volcanic_engine_model_provider/credential/tts.py:31
msgid "[0.2,3], the default is 1, usually one decimal place is enough"
msgstr "[0.2,3]，默認為1，通常保留一位小數即可"
#: apps/models_provider/impl/volcanic_engine_model_provider/volcanic_engine_model_provider.py:39
#: apps/models_provider/impl/volcanic_engine_model_provider/volcanic_engine_model_provider.py:44
#: apps/models_provider/impl/volcanic_engine_model_provider/volcanic_engine_model_provider.py:88
msgid ""
"The user goes to the model inference page of Volcano Ark to create an "
"inference access point. Here, you need to enter ep-xxxxxxxxxx-yyyy to call "
"it."
msgstr ""
"用戶前往火山方舟的模型推理頁面創建推理接入點，這裡需要輸入ep-xxxxxxxxxx-yyyy"
"進行調用"
#: apps/models_provider/impl/volcanic_engine_model_provider/volcanic_engine_model_provider.py:59
msgid "Universal 2.0-Vincent Diagram"
msgstr "通用2.0-文生圖"
#: apps/models_provider/impl/volcanic_engine_model_provider/volcanic_engine_model_provider.py:64
msgid "Universal 2.0Pro-Vincent Chart"
msgstr "通用2.0Pro-文生圖"
#: apps/models_provider/impl/volcanic_engine_model_provider/volcanic_engine_model_provider.py:69
msgid "Universal 1.4-Vincent Chart"
msgstr "通用1.4-文生圖"
#: apps/models_provider/impl/volcanic_engine_model_provider/volcanic_engine_model_provider.py:74
msgid "Animation 1.3.0-Vincent Picture"
msgstr "動漫1.3.0-文生圖"
#: apps/models_provider/impl/volcanic_engine_model_provider/volcanic_engine_model_provider.py:79
msgid "Animation 1.3.1-Vincent Picture"
msgstr "動漫1.3.1-文生圖"
#: apps/models_provider/impl/volcanic_engine_model_provider/volcanic_engine_model_provider.py:113
msgid "volcano engine"
msgstr "火山引擎"
#: apps/models_provider/impl/wenxin_model_provider/credential/llm.py:51
#, python-brace-format
msgid "{model_name} The model does not support"
msgstr "{model_name} 模型不支持"
#: apps/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py:24
#: apps/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py:53
msgid ""
"ERNIE-Bot-4 is a large language model independently developed by Baidu. It "
"covers massive Chinese data and has stronger capabilities in dialogue Q&A, "
"content creation and generation."
msgstr ""
"ERNIE-Bot-4是百度自行研發的大語言模型，覆蓋海量中文數據，具有更強的對話問答、"
"內容創作生成等能力。"
#: apps/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py:27
msgid ""
"ERNIE-Bot is a large language model independently developed by Baidu. It "
"covers massive Chinese data and has stronger capabilities in dialogue Q&A, "
"content creation and generation."
msgstr ""
"ERNIE-Bot是百度自行研發的大語言模型，覆蓋海量中文數據，具有更強的對話問答、內"
"容創作生成等能力。"
#: apps/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py:30
msgid ""
"ERNIE-Bot-turbo is a large language model independently developed by Baidu. "
"It covers massive Chinese data, has stronger capabilities in dialogue Q&A, "
"content creation and generation, and has a faster response speed."
msgstr ""
"ERNIE-Bot-turbo是百度自行研發的大語言模型，覆蓋海量中文數據，具有更強的對話問"
"答、內容創作生成等能力，響應速度更快。"
#: apps/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py:33
msgid ""
"BLOOMZ-7B is a well-known large language model in the industry. It was "
"developed and open sourced by BigScience and can output text in 46 languages "
"and 13 programming languages."
msgstr ""
"BLOOMZ-7B是業內知名的大語言模型，由BigScience研發並開源，能夠以46種語言和13種"
"程式語言輸出文本。"
#: apps/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py:39
msgid ""
"Llama-2-13b-chat was developed by Meta AI and is open source. It performs "
"well in scenarios such as coding, reasoning and knowledge application. "
"Llama-2-13b-chat is a native open source version with balanced performance "
"and effect, suitable for conversation scenarios."
msgstr ""
"Llama-2-13b-chat由Meta AI研發並開源，在編碼、推理及知識應用等場景表現優秀，"
"Llama-2-13b-chat是性能與效果均衡的原生開源版本，適用於對話場景。"
#: apps/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py:42
msgid ""
"Llama-2-70b-chat was developed by Meta AI and is open source. It performs "
"well in scenarios such as coding, reasoning, and knowledge application. "
"Llama-2-70b-chat is a native open source version with high-precision effects."
msgstr ""
"Llama-2-70b-chat由Meta AI研發並開源，在編碼、推理及知識應用等場景表現優秀，"
"Llama-2-70b-chat是高精度效果的原生開源版本。"
#: apps/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py:45
msgid ""
"The Chinese enhanced version developed by the Qianfan team based on "
"Llama-2-7b has performed well on Chinese knowledge bases such as CMMLU and C-"
"EVAL."
msgstr ""
"千帆團隊在Llama-2-7b基礎上的中文增強版本，在CMMLU、C-EVAL等中文知識庫上表現優"
"異。"
#: apps/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py:49
msgid ""
"Embedding-V1 is a text representation model based on Baidu Wenxin large "
"model technology. It can convert text into a vector form represented by "
"numerical values and can be used in text retrieval, information "
"recommendation, knowledge mining and other scenarios. Embedding-V1 provides "
"the Embeddings interface, which can generate corresponding vector "
"representations based on input content. You can call this interface to input "
"text into the model and obtain the corresponding vector representation for "
"subsequent text processing and analysis."
msgstr ""
"Embedding-V1是一個基於百度文心大模型技術的文本表示模型，可以將文本轉化為用數"
"值表示的向量形式，用於文本檢索、信息推薦、知識挖掘等場景。 Embedding-V1提供了"
"Embeddings接口，可以根據輸入內容生成對應的向量表示。您可以通過調用該接口，將"
"文本輸入到模型中，獲取到對應的向量表示，從而進行後續的文本處理和分析。"
#: apps/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py:66
msgid "Thousand sails large model"
msgstr "千帆大模型"
#: apps/models_provider/impl/xf_model_provider/credential/image.py:42
msgid "Please outline this picture"
msgstr "請描述這張圖片"
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:15
msgid "Speaker"
msgstr "發音人"
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:16
msgid ""
"Speaker, optional value: Please go to the console to add a trial or purchase "
"speaker. After adding, the speaker parameter value will be displayed."
msgstr ""
"發音人，可選值：請到控制臺添加試用或購買發音人，添加後即顯示發音人參數值"
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:21
msgid "iFlytek Xiaoyan"
msgstr "訊飛小燕"
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:22
msgid "iFlytek Xujiu"
msgstr "訊飛許久"
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:23
msgid "iFlytek Xiaoping"
msgstr "訊飛小萍"
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:24
msgid "iFlytek Xiaojing"
msgstr "訊飛小婧"
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:25
msgid "iFlytek Xuxiaobao"
msgstr "訊飛許小寶"
#: apps/models_provider/impl/xf_model_provider/credential/tts.py:28
msgid "Speech speed, optional value: [0-100], default is 50"
msgstr "語速，可選值：[0-100]，默認為50"
#: apps/models_provider/impl/xf_model_provider/xf_model_provider.py:39
#: apps/models_provider/impl/xf_model_provider/xf_model_provider.py:50
msgid "Chinese and English recognition"
msgstr "中英文識別"
#: apps/models_provider/impl/xf_model_provider/xf_model_provider.py:66
msgid "iFlytek Spark"
msgstr "訊飛星火"
#: apps/models_provider/impl/xinference_model_provider/credential/tti.py:15
msgid ""
"The image generation endpoint allows you to create raw images based on text "
"prompts. The dimensions of the image can be 1024x1024, 1024x1792, or "
"1792x1024 pixels."
msgstr ""
"圖像生成端點允許您根據文本提示創建原始圖像。圖像的尺寸可以為 1024x1024、"
"1024x1792 或 1792x1024 像素。"
#: apps/models_provider/impl/xinference_model_provider/credential/tti.py:29
msgid ""
"By default, images are generated in standard quality, you can set quality: "
"\"hd\" to enhance detail. Square, standard quality images are generated "
"fastest."
msgstr ""
"默認情況下，圖像以標準質量生成，您可以設置質量：「hd」以增強細節。方形、標準"
"質量的圖像生成速度最快。"
#: apps/models_provider/impl/xinference_model_provider/credential/tti.py:42
msgid ""
"You can request 1 image at a time (requesting more images by making parallel "
"requests), or up to 10 images at a time using the n parameter."
msgstr ""
"您可以一次請求 1 個圖像（通過發出並行請求來請求更多圖像），或者使用 n 參數一"
"次最多請求 10 個圖像。"
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:20
msgid "Chinese female"
msgstr "中文女"
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:21
msgid "Chinese male"
msgstr "中文男"
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:22
msgid "Japanese male"
msgstr "日語男"
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:23
msgid "Cantonese female"
msgstr "粵語女"
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:24
msgid "English female"
msgstr "英文女"
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:25
msgid "English male"
msgstr "英文男"
#: apps/models_provider/impl/xinference_model_provider/credential/tts.py:26
msgid "Korean female"
msgstr "韓語女"
#: apps/models_provider/impl/xinference_model_provider/xinference_model_provider.py:37
msgid ""
"Code Llama is a language model specifically designed for code generation."
msgstr "Code Llama 是一個專門用於代碼生成的語言模型。"
#: apps/models_provider/impl/xinference_model_provider/xinference_model_provider.py:44
msgid ""
" \n"
"Code Llama Instruct is a fine-tuned version of Code Llama's instructions, "
"designed to perform specific tasks.\n"
" "
msgstr ""
"Code Llama Instruct 是 Code Llama 的指令微調版本，專為執行特定任務而設計。"
#: apps/models_provider/impl/xinference_model_provider/xinference_model_provider.py:53
msgid ""
"Code Llama Python is a language model specifically designed for Python code "
"generation."
msgstr "Code Llama Python 是一個專門用於 Python 代碼生成的語言模型。"
#: apps/models_provider/impl/xinference_model_provider/xinference_model_provider.py:60
msgid ""
"CodeQwen 1.5 is a language model for code generation with high performance."
msgstr "CodeQwen 1.5 是一個用於代碼生成的語言模型，具有較高的性能。"
#: apps/models_provider/impl/xinference_model_provider/xinference_model_provider.py:67
msgid "CodeQwen 1.5 Chat is a chat model version of CodeQwen 1.5."
msgstr "CodeQwen 1.5 Chat 是一個聊天模型版本的 CodeQwen 1.5。"
#: apps/models_provider/impl/xinference_model_provider/xinference_model_provider.py:74
msgid "Deepseek is a large-scale language model with 13 billion parameters."
msgstr "Deepseek Chat 是一個聊天模型版本的 Deepseek。"
#: apps/models_provider/impl/zhipu_model_provider/credential/tti.py:16
msgid ""
"Image size, only cogview-3-plus supports this parameter. Optional range: "
"[1024x1024,768x1344,864x1152,1344x768,1152x864,1440x720,720x1440], the "
"default is 1024x1024."
msgstr ""
"圖片尺寸，僅 cogview-3-plus 支持該參數。可選範圍："
"[1024x1024,768x1344,864x1152,1344x768,1152x864,1440x720,720x1440]，默認是"
"1024x1024。"
#: apps/models_provider/impl/zhipu_model_provider/zhipu_model_provider.py:34
msgid ""
"Have strong multi-modal understanding capabilities. Able to understand up to "
"five images simultaneously and supports video content understanding"
msgstr "具有強大的多模態理解能力。能夠同時理解多達五張圖像，並支持視頻內容理解"
#: apps/models_provider/impl/zhipu_model_provider/zhipu_model_provider.py:37
msgid ""
"Focus on single picture understanding. Suitable for scenarios requiring "
"efficient image analysis"
msgstr "專注於單圖理解。適用於需要高效圖像解析的場景"
#: apps/models_provider/impl/zhipu_model_provider/zhipu_model_provider.py:40
msgid ""
"Focus on single picture understanding. Suitable for scenarios requiring "
"efficient image analysis (free)"
msgstr "專注於單圖理解。適用於需要高效圖像解析的場景(免費)"
#: apps/models_provider/impl/zhipu_model_provider/zhipu_model_provider.py:46
msgid ""
"Quickly and accurately generate images based on user text descriptions. "
"Resolution supports 1024x1024"
msgstr "根據用戶文字描述快速、精準生成圖像。解析度支持1024x1024"
#: apps/models_provider/impl/zhipu_model_provider/zhipu_model_provider.py:49
msgid ""
"Generate high-quality images based on user text descriptions, supporting "
"multiple image sizes"
msgstr "根據用戶文字描述生成高質量圖像，支持多圖片尺寸"
#: apps/models_provider/impl/zhipu_model_provider/zhipu_model_provider.py:52
msgid ""
"Generate high-quality images based on user text descriptions, supporting "
"multiple image sizes (free)"
msgstr "根據用戶文字描述生成高質量圖像，支持多圖片尺寸(免費)"
#: apps/models_provider/impl/zhipu_model_provider/zhipu_model_provider.py:75
msgid "zhipu AI"
msgstr "智譜 AI"
#: apps/models_provider/serializers/model_serializer.py:43
#: apps/models_provider/serializers/model_serializer.py:222
#: apps/models_provider/serializers/model_serializer.py:259
#: apps/models_provider/serializers/model_serializer.py:323
msgid "base model"
msgstr "基礎模型"
#: apps/models_provider/serializers/model_serializer.py:44
#: apps/models_provider/serializers/model_serializer.py:260
msgid "parameter configuration"
msgstr "參數配置"
#: apps/models_provider/serializers/model_serializer.py:45
#: apps/models_provider/serializers/model_serializer.py:225
#: apps/models_provider/serializers/model_serializer.py:261
#, fuzzy
#| msgid "Get current user information"
msgid "certification information"
msgstr "獲取當前用戶信息"
#: apps/models_provider/serializers/model_serializer.py:108
#: apps/models_provider/serializers/model_serializer.py:215
#: apps/models_provider/serializers/model_serializer.py:255
#: apps/modules/serializers/module.py:35 apps/tools/serializers/tool.py:65
msgid "user id"
msgstr "用戶ID"
#: apps/models_provider/serializers/model_serializer.py:116
#: apps/models_provider/serializers/model_serializer.py:132
#: apps/models_provider/serializers/model_serializer.py:151
#: apps/models_provider/serializers/model_serializer.py:178
#: apps/models_provider/serializers/model_serializer.py:373
#: apps/models_provider/tools.py:111
msgid "Model does not exist"
msgstr "模型不存在"
#: apps/models_provider/serializers/model_serializer.py:233
#: apps/models_provider/serializers/model_serializer.py:272
#, python-brace-format
msgid "base model【{model_name}】already exists"
msgstr "模型【{model_name}】已存在"
#: apps/models_provider/serializers/model_serializer.py:312
msgid "Model saving failed"
msgstr "模型保存失敗"
#: apps/models_provider/serializers/model_serializer.py:325
msgid "create user"
msgstr "創建者"
#: apps/models_provider/views/model.py:28
#: apps/models_provider/views/model.py:29
msgid "Create model"
msgstr "創建模型"
#: apps/models_provider/views/model.py:30
#: apps/models_provider/views/model.py:57
#: apps/models_provider/views/model.py:74
#: apps/models_provider/views/model.py:86
#: apps/models_provider/views/model.py:97
#: apps/models_provider/views/model.py:111
#: apps/models_provider/views/model.py:122
#: apps/models_provider/views/model.py:138
#: apps/models_provider/views/model.py:152
#: apps/models_provider/views/provide.py:24
#: apps/models_provider/views/provide.py:47
#: apps/models_provider/views/provide.py:61
#: apps/models_provider/views/provide.py:79
#: apps/models_provider/views/provide.py:96
msgid "Model"
msgstr "模型"
#: apps/models_provider/views/model.py:53
#: apps/models_provider/views/model.py:54
msgid "Query model list"
msgstr "查詢模型列表"
#: apps/models_provider/views/model.py:69
#: apps/models_provider/views/model.py:70
msgid "Update model"
msgstr "更新模型"
#: apps/models_provider/views/model.py:82
#: apps/models_provider/views/model.py:83
msgid "Delete model"
msgstr "刪除模型"
#: apps/models_provider/views/model.py:93
#: apps/models_provider/views/model.py:94
msgid "Query model details"
msgstr "查詢模型詳情"
#: apps/models_provider/views/model.py:107
#: apps/models_provider/views/model.py:108
msgid "Get model parameter form"
msgstr "獲取模型參數表單"
#: apps/models_provider/views/model.py:118
#: apps/models_provider/views/model.py:119
msgid "Save model parameter form"
msgstr "保存模型參數表單"
#: apps/models_provider/views/model.py:133
#: apps/models_provider/views/model.py:135
msgid ""
"Query model meta information, this interface does not carry authentication "
"information"
msgstr "查詢模型元信息，該接口不攜帶認證信息"
#: apps/models_provider/views/model.py:148
#: apps/models_provider/views/model.py:149
msgid "Pause model download"
msgstr "下載模型暫停"
#: apps/models_provider/views/provide.py:21
#: apps/models_provider/views/provide.py:22
msgid "Get a list of model suppliers"
msgstr "獲取模型供應商列表"
#: apps/models_provider/views/provide.py:43
#: apps/models_provider/views/provide.py:44
msgid "Get a list of model types"
msgstr "獲取模型類型列表"
#: apps/models_provider/views/provide.py:57
#: apps/models_provider/views/provide.py:58
msgid "Example of obtaining model list"
msgstr "獲取模型列表示例"
#: apps/models_provider/views/provide.py:75
msgid "Get model default parameters"
msgstr "獲取模型默認參數"
#: apps/models_provider/views/provide.py:76
#: apps/models_provider/views/provide.py:92
#: apps/models_provider/views/provide.py:93
msgid "Get the model creation form"
msgstr "獲取模型創建表單"
#: apps/modules/models/module.py:6 apps/modules/models/module.py:13
#: apps/modules/serializers/module.py:29
msgid "module name"
msgstr "模塊名稱"
#: apps/modules/models/module.py:9 apps/modules/serializers/module.py:32
msgid "parent id"
msgstr "父級 ID"
#: apps/modules/serializers/module.py:28 apps/modules/serializers/module.py:62
msgid "module id"
msgstr "模塊 ID"
#: apps/modules/serializers/module.py:30
msgid "module user id"
msgstr "模塊用戶 ID"
#: apps/modules/serializers/module.py:36 apps/modules/serializers/module.py:64
#: apps/modules/serializers/module.py:96 apps/tools/serializers/tool.py:28
msgid "source"
msgstr "來源"
#: apps/modules/serializers/module.py:49
msgid "Module name already exists"
msgstr "模塊名稱已存在"
#: apps/modules/serializers/module.py:70
msgid "Module does not exist"
msgstr "模塊不存在"
#: apps/modules/serializers/module.py:89
msgid "Cannot delete root module"
msgstr "無法刪除根模塊"
#: apps/modules/views/module.py:18 apps/modules/views/module.py:19
msgid "Create module"
msgstr "創建模塊"
#: apps/modules/views/module.py:23 apps/modules/views/module.py:38
#: apps/modules/views/module.py:55 apps/modules/views/module.py:68
#: apps/modules/views/module.py:81
msgid "Module"
msgstr "模塊"
#: apps/modules/views/module.py:34 apps/modules/views/module.py:35
msgid "Get module tree"
msgstr "獲取模塊樹"
#: apps/modules/views/module.py:50 apps/modules/views/module.py:51
msgid "Update module"
msgstr "更新模塊"
#: apps/modules/views/module.py:64 apps/modules/views/module.py:65
msgid "Get module"
msgstr "獲取模塊"
#: apps/modules/views/module.py:77 apps/modules/views/module.py:78
msgid "Delete module"
msgstr "刪除模塊"
#: apps/tools/serializers/tool.py:22
msgid "variable name"
msgstr "變量名稱"
#: apps/tools/serializers/tool.py:24
msgid "type"
msgstr "類型"
#: apps/tools/serializers/tool.py:26
msgid "fields only support string|int|dict|array|float"
msgstr "欄位僅支持字符串|整數|字典|數組|浮點數"
#: apps/tools/serializers/tool.py:30
msgid "The field only supports custom|reference"
msgstr "欄位僅支持自定義|引用"
#: apps/tools/serializers/tool.py:35
#, fuzzy
#| msgid "model name"
msgid "field name"
msgstr "模型名稱"
#: apps/tools/serializers/tool.py:36
#, fuzzy
#| msgid "label"
msgid "field label"
msgstr "標籤"
#: apps/tools/serializers/tool.py:46
msgid "tool name"
msgstr "工具名稱"
#: apps/tools/serializers/tool.py:49
msgid "tool description"
msgstr "工具描述"
#: apps/tools/serializers/tool.py:51
msgid "tool content"
msgstr "工具內容"
#: apps/tools/serializers/tool.py:54
msgid "input field list"
msgstr "輸入欄位列表"
#: apps/tools/serializers/tool.py:56
msgid "init field list"
msgstr "內置欄位列表"
#: apps/tools/serializers/tool.py:58
msgid "Is active"
msgstr "是否啟用"
#: apps/tools/serializers/tool.py:86
#, fuzzy
#| msgid "model id"
msgid "tool id"
msgstr "模型ID"
#: apps/tools/serializers/tool.py:94
msgid "Tool not found"
msgstr "工具未找到"
#: apps/tools/serializers/tool.py:124
msgid "Module not found"
msgstr "模塊未找到"
#: apps/tools/views/tool.py:18 apps/tools/views/tool.py:19
msgid "Create tool"
msgstr "創建工具"
#: apps/tools/views/tool.py:23 apps/tools/views/tool.py:35
#: apps/tools/views/tool.py:51 apps/tools/views/tool.py:63
#: apps/tools/views/tool.py:75
msgid "Tool"
msgstr "工具"
#: apps/tools/views/tool.py:31 apps/tools/views/tool.py:32
#, fuzzy
#| msgid "Get module"
msgid "Get tool by module"
msgstr "獲取模塊"
#: apps/tools/views/tool.py:46 apps/tools/views/tool.py:47
#, fuzzy
#| msgid "Update model"
msgid "Update tool"
msgstr "更新模型"
#: apps/tools/views/tool.py:59 apps/tools/views/tool.py:60
#, fuzzy
#| msgid "Create tool"
msgid "Get tool"
msgstr "創建工具"
#: apps/tools/views/tool.py:71 apps/tools/views/tool.py:72
#, fuzzy
#| msgid "Delete model"
msgid "Delete tool"
msgstr "刪除模型"
#: apps/users/serializers/login.py:27
msgid "Username"
msgstr "用戶名"
#: apps/users/serializers/login.py:28
msgid "Password"
msgstr "密碼"
#: apps/users/serializers/login.py:29 apps/users/serializers/login.py:69
msgid "captcha"
msgstr "驗證碼"
#: apps/users/serializers/login.py:36
msgid "token"
msgstr "令牌"
#: apps/users/serializers/login.py:50
msgid "Captcha code error or expiration"
msgstr "驗證碼錯誤或過期"
#: apps/users/serializers/login.py:53
msgid "The username or password is incorrect"
msgstr "用戶名或密碼不正確"
#: apps/users/serializers/login.py:55
msgid "The user has been disabled, please contact the administrator!"
msgstr "用戶已被禁用，請聯繫管理員！"
#: apps/users/views/login.py:21 apps/users/views/login.py:22
msgid "Log in"
msgstr "登錄"
#: apps/users/views/login.py:23 apps/users/views/login.py:34
#: apps/users/views/user.py:28 apps/users/views/user.py:40
#: apps/users/views/user.py:53
msgid "User management"
msgstr "用戶管理"
#: apps/users/views/login.py:32 apps/users/views/login.py:33
msgid "Get captcha"
msgstr "獲取驗證碼"
#: apps/users/views/user.py:26 apps/users/views/user.py:27
#: apps/users/views/user.py:38
msgid "Get current user information"
msgstr "獲取當前用戶信息"
#~ msgid "Universal female voice"
#~ msgstr "通用女聲"
#~ msgid "Supernatural timbre-ZiZi 2.0"
#~ msgstr "超自然音色-梓梓2.0"
#~ msgid "Supernatural timbre-ZiZi"
#~ msgstr "超自然音色-梓梓"
#~ msgid "Supernatural sound-Ranran 2.0"
#~ msgstr "超自然音色-燃燃2.0"
#~ msgid "Supernatural sound-Ranran"
#~ msgstr "超自然音色-燃燃"
#~ msgid "Universal male voice"
#~ msgstr "通用男聲"
#~ msgid "ADMIN"
#~ msgstr "管理員"
#~ msgid "Super administrator"
#~ msgstr "超級管理員"
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