# SOME DESCRIPTIVE TITLE.
# Copyright (C) 2023, csunny
# This file is distributed under the same license as the DB-GPT package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2023.
#
#, fuzzy
msgid ""
msgstr ""
"Project-Id-Version: DB-GPT 👏👏 0.3.5\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2023-08-16 18:31+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
"Language-Team: zh_CN <LL@li.org>\n"
"Plural-Forms: nplurals=1; plural=0;\n"
"MIME-Version: 1.0\n"
"Content-Type: text/plain; charset=utf-8\n"
"Content-Transfer-Encoding: 8bit\n"
"Generated-By: Babel 2.12.1\n"

#: ../../getting_started/application/kbqa/kbqa.md:1
#: a06d9329c98f44ffaaf6fc09ba53d97e
msgid "KBQA"
msgstr ""

#: ../../getting_started/application/kbqa/kbqa.md:3
#: bb6943c115754b1fafb7467313100753
msgid ""
"DB-GPT supports a knowledge question-answering module, which aims to "
"create an intelligent expert in the field of databases and provide "
"professional knowledge-based answers to database practitioners."
msgstr " DB-GPT支持知识问答模块，知识问答的初衷是打造DB领域的智能专家，为数据库从业人员解决专业的知识问题回答"

#: ../../getting_started/application/kbqa/kbqa.md:5
#: a13ac963479e4d4fbcbcc4fec7863274
msgid "![chat_knowledge](../../../../assets/chat_knowledge.png)"
msgstr "![chat_knowledge](../../../../assets/chat_knowledge.png)"

#: ../../getting_started/application/kbqa/kbqa.md:5
#: f4db3a8d04634059a74be1b2b3c948ef
msgid "chat_knowledge"
msgstr "chat_knowledge"

#: ../../getting_started/application/kbqa/kbqa.md:7
#: ../../getting_started/application/kbqa/kbqa.md:10
#: 86856cce95c845eb83ed44d8713b0ef6 f787e9ad9f7444a5923fe3476ab4d287
msgid "KBQA abilities"
msgstr "KBQA现有能力"

#: ../../getting_started/application/kbqa/kbqa.md:11
#: df1c88b28a2d46b2b3f5fae1caec000e
msgid "Knowledge Space."
msgstr "知识空间"

#: ../../getting_started/application/kbqa/kbqa.md:12
#: 7f6c99d0c1394f08b246daa1343c24b2
msgid "Multi Source Knowledge Source Embedding."
msgstr "多数据源Embedding"

#: ../../getting_started/application/kbqa/kbqa.md:13
#: 3c1274c3e65f426bbee219227f681e27
msgid "Embedding Argument Adjust"
msgstr "Embedding参数自定义"

#: ../../getting_started/application/kbqa/kbqa.md:14
#: 52fb29f7ee8745e6b78145f5be23b8ce
msgid "Chat Knowledge"
msgstr "知识问答"

#: ../../getting_started/application/kbqa/kbqa.md:15
#: 83e427c46d844c6a9bb5954342ae7c42
msgid "Multi Vector DB"
msgstr "多向量数据库管理"

#: ../../getting_started/application/kbqa/kbqa.md:19
#: 07c1e189d0f84db69b6a51cf23ede7dc
msgid "Steps to KBQA In DB-GPT"
msgstr "怎样一步一步使用KBQA"

#: ../../getting_started/application/kbqa/kbqa.md:21
#: 36e4195e5c3a4bedb7d11243e5705f0a
msgid "1.Create Knowledge Space"
msgstr "1.首先创建知识空间"

#: ../../getting_started/application/kbqa/kbqa.md:22
#: 5c92d41df2b04374a6c7ce40308f738b
msgid ""
"If you are using Knowledge Space for the first time, you need to create a"
" Knowledge Space and set your name, owner, description. "
"![create_space](../../../../assets/kbqa/create_space.png)"
msgstr "如果你是第一次使用，先创建知识空间，指定名字,拥有者和描述信息"

#: ../../getting_started/application/kbqa/kbqa.md:22
#: c5f6e842be384977be1bd667b1e0ab5d
msgid "create_space"
msgstr "create_space"

#: ../../getting_started/application/kbqa/kbqa.md:27
#: c98434920955416ca5273892f9086bc5
msgid "2.Create Knowledge Document"
msgstr "2.上传知识"

#: ../../getting_started/application/kbqa/kbqa.md:28
#: d63f798e8270455587d1afd98c72e995
msgid ""
"DB-GPT now support Multi Knowledge Source, including Text, WebUrl, and "
"Document(PDF, Markdown, Word, PPT, HTML and CSV). After successfully "
"uploading a document for translation, the backend system will "
"automatically read and split and chunk the document, and then import it "
"into the vector database. Alternatively, you can manually synchronize the"
" document. You can also click on details to view the specific document "
"slicing content."
msgstr "DB-GPT支持多数据源，包括Text纯文本, WebUrl和Document(PDF, Markdown, Word, PPT, HTML and CSV)。上传文档成功后后台会自动将文档内容进行读取，切片，然后导入到向量数据库中，当然你也可以手动进行同步，你也可以点击详情查看具体的文档切片内容"

#: ../../getting_started/application/kbqa/kbqa.md:30
#: 18becde7bdc34e9cb7017ff7711d1634
msgid "2.1 Choose Knowledge Type:"
msgstr "2.1 选择知识类型"

#: ../../getting_started/application/kbqa/kbqa.md:31
#: 755dfd18812249e591647d233ec9253b
msgid "![document](../../../../assets/kbqa/document.jpg)"
msgstr "![document](../../../../assets/kbqa/document.jpg)"

#: ../../getting_started/application/kbqa/kbqa.md:31
#: 10faa2236fa84dc284f7ce6d68acc43c
msgid "document"
msgstr "document"

#: ../../getting_started/application/kbqa/kbqa.md:33
#: 04449bfa78b14d1cb42c1259f67531d1
msgid "2.2 Upload Document:"
msgstr "2.2上传文档"

#: ../../getting_started/application/kbqa/kbqa.md:34
#: de14e2d7a6c54623bfc8af2fc6e20c62
msgid "![upload](../../../../assets/kbqa/upload.jpg)"
msgstr "![upload](../../../../assets/kbqa/upload.jpg)"

#: ../../getting_started/application/kbqa/kbqa.md:34
#: ../../getting_started/application/kbqa/kbqa.md:38
#: ../../getting_started/application/kbqa/kbqa.md:43
#: ../../getting_started/application/kbqa/kbqa.md:56
#: 0e3ab13b9d064b238fba283d6f466051 65ea0b9b43ef4c64897a6e65781129c7
#: cb65cb968a91492d9526f47e74b179e1 f0ff29911159497fb542942b6deb6972
msgid "upload"
msgstr "upload"

#: ../../getting_started/application/kbqa/kbqa.md:37
#: 77d936d2502f41feb2721da86cc1ebb1
msgid "3.Chat With Knowledge"
msgstr "3.知识问答"

#: ../../getting_started/application/kbqa/kbqa.md:38
#: ae72c3236e564949b142a945f3474425
msgid "![upload](../../../../assets/kbqa/begin_chat.jpg)"
msgstr "![upload](../../../../assets/kbqa/begin_chat.jpg)"

#: ../../getting_started/application/kbqa/kbqa.md:40
#: b9d701985d404a9196bb896718f41e36
msgid "4.Adjust Space arguments"
msgstr "4.调整知识参数"

#: ../../getting_started/application/kbqa/kbqa.md:41
#: 6155bbf401ef44ea8d761c83ae5ceb9a
msgid ""
"Each knowledge space supports argument customization, including the "
"relevant arguments for vector retrieval and the arguments for knowledge "
"question-answering prompts."
msgstr "每一个知识空间都支持参数自定义, 包括向量召回的相关参数以及知识问答Promp参数"

#: ../../getting_started/application/kbqa/kbqa.md:42
#: b9ac70b5ee99435a962dcb040b5ba4fc
msgid "4.1 Embedding"
msgstr "4.1 Embedding"

#: ../../getting_started/application/kbqa/kbqa.md:43
#: 0ca2398756924828a904921456b863b5
msgid "Embedding Argument ![upload](../../../../assets/kbqa/embedding.png)"
msgstr "Embedding Argument ![upload](../../../../assets/kbqa/embedding.png)"

#: ../../getting_started/application/kbqa/kbqa.md:47
#: e8b3e973e3b940e4bbf3180b7d6057ec
msgid "Embedding arguments"
msgstr "Embedding arguments"

#: ../../getting_started/application/kbqa/kbqa.md:48
#: 1cff4790d546455abeca725ae8b53c0d
msgid "topk:the top k vectors based on similarity score."
msgstr "topk:相似性检索出tok条文档"

#: ../../getting_started/application/kbqa/kbqa.md:49
#: 525aaa02028b4900919526290b6da9ef
msgid "recall_score:set a threshold score for the retrieval of similar vectors."
msgstr "recall_score:向量检索相关度衡量指标分数"

#: ../../getting_started/application/kbqa/kbqa.md:50
#: dead3b559b134e52a3cf38e29b1982e1
msgid "recall_type:recall type."
msgstr "recall_type:召回类型"

#: ../../getting_started/application/kbqa/kbqa.md:51
#: 7c48de3186a14fcf96ee2bc6d715bd4c
msgid "model:A model used to create vector representations of text or other data."
msgstr "model:embdding模型"

#: ../../getting_started/application/kbqa/kbqa.md:52
#: 875ba3d051b847a5b3357a4eef583c0a
msgid "chunk_size:The size of the data chunks used in processing."
msgstr "chunk_size:文档切片阈值大小"

#: ../../getting_started/application/kbqa/kbqa.md:53
#: e43f2bb091594532ba69ed3e3a385cdd
msgid "chunk_overlap:The amount of overlap between adjacent data chunks."
msgstr "chunk_overlap:文本块之间的最大重叠量。保留一些重叠可以保持文本块之间的连续性（例如使用滑动窗口）"

#: ../../getting_started/application/kbqa/kbqa.md:55
#: e21e19688fa042a4b60860ffa6bcf119
msgid "4.2 Prompt"
msgstr "4.2 Prompt"

#: ../../getting_started/application/kbqa/kbqa.md:56
#: 00f0bddcd9174b7a84a25b7fe6d286e9
msgid "Prompt Argument ![upload](../../../../assets/kbqa/prompt.png)"
msgstr "Prompt Argument ![upload](../../../../assets/kbqa/prompt.png)"

#: ../../getting_started/application/kbqa/kbqa.md:60
#: d5ff2b76a04949708b3c9050db647927
msgid "Prompt arguments"
msgstr "Prompt arguments"

#: ../../getting_started/application/kbqa/kbqa.md:61
#: 817a8744378546a2b049f44793b4554b
msgid ""
"scene:A contextual parameter used to define the setting or environment in"
" which the prompt is being used."
msgstr "scene:上下文环境的场景定义"

#: ../../getting_started/application/kbqa/kbqa.md:62
#: 5330c26a4fc34ff6ba5fea1910cfbdc0
msgid ""
"template:A pre-defined structure or format for the prompt, which can help"
" ensure that the AI system generates responses that are consistent with "
"the desired style or tone."
msgstr ""
"template:预定义的提示结构或格式，可以帮助确保AI系统生成与所期望的风格或语气一致的回复。"

#: ../../getting_started/application/kbqa/kbqa.md:63
#: a34cd8248e6b44228868c2a02e12466f
msgid "max_token:The maximum number of tokens or words allowed in a prompt."
msgstr "max_token: prompt token最大值"

#: ../../getting_started/application/kbqa/kbqa.md:65
#: 7da49aac293f462b9e3968fa1493dba1
msgid "5.Change Vector Database"
msgstr "5.Change Vector Database"

#: ../../getting_started/application/kbqa/kbqa.md:67
#: 680bfb451eb040e0aa55f8faa12bb75a
msgid "Vector Store SETTINGS"
msgstr "Vector Store SETTINGS"

#: ../../getting_started/application/kbqa/kbqa.md:68
#: 32820ae6807840119a786e92124ad209
msgid "Chroma"
msgstr "Chroma"

#: ../../getting_started/application/kbqa/kbqa.md:69
#: 7573aa05bc914fc2993b2531475b3b99
msgid "VECTOR_STORE_TYPE=Chroma"
msgstr "VECTOR_STORE_TYPE=Chroma"

#: ../../getting_started/application/kbqa/kbqa.md:70
#: cc2c5521ba6e417eb5b3cf96375c2a08
msgid "MILVUS"
msgstr "MILVUS"

#: ../../getting_started/application/kbqa/kbqa.md:71
#: fc5dfa54c8a24b069e2709c309e43faa
msgid "VECTOR_STORE_TYPE=Milvus"
msgstr "VECTOR_STORE_TYPE=Milvus"

#: ../../getting_started/application/kbqa/kbqa.md:72
#: 8661384f0c4a40a0b79fad94bbee1792
msgid "MILVUS_URL=127.0.0.1"
msgstr "MILVUS_URL=127.0.0.1"

#: ../../getting_started/application/kbqa/kbqa.md:73
#: 2035d343d34f47fa9fa84eb841afa2f8
msgid "MILVUS_PORT=19530"
msgstr "MILVUS_PORT=19530"

#: ../../getting_started/application/kbqa/kbqa.md:74
#: e0d8bd8d1dfb425bb50d5c8bf4a134ab
msgid "MILVUS_USERNAME"
msgstr "MILVUS_USERNAME"

#: ../../getting_started/application/kbqa/kbqa.md:75
#: dec547e6b4354c71857fa7c92c08bfa6
msgid "MILVUS_PASSWORD"
msgstr "MILVUS_PASSWORD"

#: ../../getting_started/application/kbqa/kbqa.md:76
#: 9ad3f325f79e49309bd3419f48015e90
msgid "MILVUS_SECURE="
msgstr "MILVUS_SECURE="

#: ../../getting_started/application/kbqa/kbqa.md:78
#: f6e15bf479da496fbcdf7621bad4dda8
msgid "WEAVIATE"
msgstr "WEAVIATE"

#: ../../getting_started/application/kbqa/kbqa.md:79
#: f7838d5de0a9452486adceb3a26369ee
msgid "WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network"
msgstr "WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.networkc"

