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feat: Command-line tool with knowledge repository initialization
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@@ -8,7 +8,7 @@ msgid ""
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msgstr ""
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"Project-Id-Version: DB-GPT 0.3.0\n"
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"Report-Msgid-Bugs-To: \n"
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"POT-Creation-Date: 2023-07-31 17:04+0800\n"
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"POT-Creation-Date: 2023-09-01 18:16+0800\n"
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"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
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"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
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"Language: zh_CN\n"
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@@ -19,11 +19,11 @@ msgstr ""
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"Content-Transfer-Encoding: 8bit\n"
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"Generated-By: Babel 2.12.1\n"
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#: ../../modules/knownledge.md:1 b18cf12f806941f3b9d1c13b52d0dfe5
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#: ../../modules/knownledge.md:1 ba585bf3ba464c32a156d308f39e65dc
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msgid "Knownledge"
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msgstr "知识"
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#: ../../modules/knownledge.md:3 3fe78b30d3994e4484df41a677614eb2
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#: ../../modules/knownledge.md:3 bc5d67c51b004ff8b2d1bbca17fd4aa7
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msgid ""
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"As the knowledge base is currently the most significant user demand "
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"scenario, we natively support the construction and processing of "
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@@ -31,15 +31,15 @@ msgid ""
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"base management strategies in this project, such as:"
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msgstr "由于知识库是当前用户需求最显著的场景,我们原生支持知识库的构建和处理。同时,我们还在本项目中提供了多种知识库管理策略,如:"
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#: ../../modules/knownledge.md:4 17b2485a12744b5587655201be50e023
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#: ../../modules/knownledge.md:4 519f2686500340d191ad5a91eabc7676
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msgid "Default built-in knowledge base"
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msgstr "默认内置知识库"
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#: ../../modules/knownledge.md:5 e137d9916a0a4a0681dbfed5d5a5065f
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#: ../../modules/knownledge.md:5 93a25018fc144dfe98fcea0755f2ea94
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msgid "Custom addition of knowledge bases"
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msgstr "自定义新增知识库"
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#: ../../modules/knownledge.md:6 0bca133996d4435b84245f2b53f43d72
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#: ../../modules/knownledge.md:6 37359e14b2464b2c9fc4e5621755bb0d
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msgid ""
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"Various usage scenarios such as constructing knowledge bases through "
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"plugin capabilities and web crawling. Users only need to organize the "
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@@ -47,51 +47,52 @@ msgid ""
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"the knowledge base required for the large model."
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msgstr "各种使用场景,例如通过插件功能和爬虫构建知识库。用户只需要组织知识文档,并且他们可以使用我们现有的功能来构建大型模型所需的知识库。"
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#: ../../modules/knownledge.md:9 7355eed198514efc8e3bc178039b0251
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#: ../../modules/knownledge.md:9 656fcb11886546df9e058227d94481b3
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msgid "Create your own knowledge repository"
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msgstr "创建你自己的知识库"
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#: ../../modules/knownledge.md:11 96e0276a5d3047fea5410e9b33c33308
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#: ../../modules/knownledge.md:11 37fc3ae2cfe044f8ac61de484bf0653d
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msgid ""
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"1.Place personal knowledge files or folders in the pilot/datasets "
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"directory."
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msgstr "1.将个人知识文件或文件夹放在pilot/datasets目录中。"
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#: ../../modules/knownledge.md:13 8762c0a463094c19924cdd4b7b1b1ede
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#: ../../modules/knownledge.md:13 a675d90485834690bfca68b41a10c085
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msgid ""
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"We currently support many document formats: txt, pdf, md, html, doc, ppt,"
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" and url."
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msgstr "当前支持txt, pdf, md, doc, ppt, html文档格式"
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#: ../../modules/knownledge.md:15 752a5e7c623a49439ecf1ce8e6ccca7d
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#: ../../modules/knownledge.md:15 f2c25b0536ff4b3191e13f3020e883a6
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msgid "before execution:"
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msgstr "在执行之前"
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#: ../../modules/knownledge.md:22 fbef967557a94b938f8e47497bb43c20
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#: ../../modules/knownledge.md:22 65427906c8b54cd699a07ed482251c83
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msgid ""
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"2.Update your .env, set your vector store type, VECTOR_STORE_TYPE=Chroma "
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"(now only support Chroma and Milvus, if you set Milvus, please set "
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"MILVUS_URL and MILVUS_PORT)"
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msgstr "2.更新你的.env,设置你的向量存储类型,VECTOR_STORE_TYPE=Chroma(现在只支持Chroma和Milvus,如果你设置了Milvus,请设置MILVUS_URL和MILVUS_PORT)"
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#: ../../modules/knownledge.md:25 f1745e2f17864711a636ecbdd6cb9833
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msgid "2.Run the knowledge repository script in the tools directory."
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msgstr "2.在tools目录执行知识入库脚本"
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#: ../../modules/knownledge.md:25 287ae6ee51cc4b668d99e48b81147d3f
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#, fuzzy
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msgid "2.Run the knowledge repository initialization command"
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msgstr "2.执行知识入库命令"
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#: ../../modules/knownledge.md:34 5ae832d038b245a29a9e089f9e169cb0
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#: ../../modules/knownledge.md:31 1fe0ac58d8354c7fba782901cb0673d8
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msgid ""
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"Optionally, you can run `python tools/knowledge_init.py -h` command to "
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"see more usage."
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msgstr ""
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"Optionally, you can run `dbgpt knowledge load --help` command to see more"
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" usage."
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msgstr "另外,你可以运行 `dbgpt knowledge load --help` 命令来查看更多的用法"
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#: ../../modules/knownledge.md:36 4aab02276dfd41819dbd218ecc608326
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#: ../../modules/knownledge.md:33 e1607e330195470f9087bd4ffbc6d45d
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msgid ""
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"3.Add the knowledge repository in the interface by entering the name of "
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"your knowledge repository (if not specified, enter \"default\") so you "
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"can use it for Q&A based on your knowledge base."
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msgstr "如果选择新增知识库,在界面上新增知识库输入你的知识库名"
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#: ../../modules/knownledge.md:38 f990c8495c994aa1beb040ede6b2329a
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#: ../../modules/knownledge.md:35 0614e35ccfba42ea9e63881cb481815e
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msgid ""
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"Note that the default vector model used is text2vec-large-chinese (which "
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"is a large model, so if your personal computer configuration is not "
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@@ -101,3 +102,9 @@ msgstr ""
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"注意,这里默认向量模型是text2vec-large-chinese(模型比较大,如果个人电脑配置不够建议采用text2vec-base-"
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"chinese),因此确保需要将模型download下来放到models目录中。"
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#~ msgid ""
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#~ "Optionally, you can run `python "
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#~ "tools/knowledge_init.py -h` command to see "
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#~ "more usage."
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#~ msgstr ""
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@@ -22,16 +22,13 @@ python -m spacy download zh_core_web_sm
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2.Update your .env, set your vector store type, VECTOR_STORE_TYPE=Chroma
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(now only support Chroma and Milvus, if you set Milvus, please set MILVUS_URL and MILVUS_PORT)
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2.Run the knowledge repository script in the tools directory.
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```
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python tools/knowledge_init.py
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--vector_name : your vector store name default_value:default
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2.Run the knowledge repository initialization command
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```bash
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dbgpt knowledge load
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```
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Optionally, you can run `python tools/knowledge_init.py -h` command to see more usage.
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Optionally, you can run `dbgpt knowledge load --help` command to see more usage.
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3.Add the knowledge repository in the interface by entering the name of your knowledge repository (if not specified, enter "default") so you can use it for Q&A based on your knowledge base.
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