doc(ChatKnowledge): Add documents for knowledge command line

This commit is contained in:
FangYin Cheng
2023-09-28 12:50:37 +08:00
parent 5dfe611478
commit 5b9a0fa7c0
3 changed files with 361 additions and 65 deletions

View File

@@ -91,4 +91,207 @@ Prompt Argument
#### WEAVIATE
* WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network
```
## KBQA command line
### Load your local documents to DB-GPT
```bash
dbgpt knowledge load --space_name my_kbqa_space --local_doc_path ./pilot/datasets --vector_store_type Chroma
```
- `--space_name`: Your knowledge space name, default: `default`
- `--local_doc_path`: Your document directory or document file path, default: `./pilot/datasets`
- `--vector_store_type`: Vector store type, default: `Chroma`
**View the `dbgpt knowledge load --help`help**
```
dbgpt knowledge load --help
```
Here you can see the parameters:
```
Usage: dbgpt knowledge load [OPTIONS]
Load your local knowledge to DB-GPT
Options:
--space_name TEXT Your knowledge space name [default: default]
--vector_store_type TEXT Vector store type. [default: Chroma]
--local_doc_path TEXT Your document directory or document file path.
[default: ./pilot/datasets]
--skip_wrong_doc Skip wrong document.
--overwrite Overwrite existing document(they has same name).
--max_workers INTEGER The maximum number of threads that can be used to
upload document.
--pre_separator TEXT Preseparator, this separator is used for pre-
splitting before the document is actually split by
the text splitter. Preseparator are not included
in the vectorized text.
--separator TEXT This is the document separator. Currently, only
one separator is supported.
--chunk_size INTEGER Maximum size of chunks to split.
--chunk_overlap INTEGER Overlap in characters between chunks.
--help Show this message and exit.
```
### List knowledge space
#### List knowledge space
```
dbgpt knowledge list
```
Output should look something like the following:
```
+------------------------------------------------------------------+
| All knowledge spaces |
+----------+-------------+-------------+-------------+-------------+
| Space ID | Space Name | Vector Type | Owner | Description |
+----------+-------------+-------------+-------------+-------------+
| 6 | n1 | Chroma | DB-GPT | DB-GPT cli |
| 5 | default_2 | Chroma | DB-GPT | DB-GPT cli |
| 4 | default_1 | Chroma | DB-GPT | DB-GPT cli |
| 3 | default | Chroma | DB-GPT | DB-GPT cli |
+----------+-------------+-------------+-------------+-------------+
```
#### List documents in knowledge space
```
dbgpt knowledge list --space_name default
```
Output should look something like the following:
```
+------------------------------------------------------------------------+
| Space default description |
+------------+-----------------+--------------+--------------+-----------+
| Space Name | Total Documents | Current Page | Current Size | Page Size |
+------------+-----------------+--------------+--------------+-----------+
| default | 1 | 1 | 1 | 20 |
+------------+-----------------+--------------+--------------+-----------+
+-----------------------------------------------------------------------------------------------------------------------------------+
| Documents of space default |
+------------+-------------+---------------+----------+--------+----------------------------+----------+----------------------------+
| Space Name | Document ID | Document Name | Type | Chunks | Last Sync | Status | Result |
+------------+-------------+---------------+----------+--------+----------------------------+----------+----------------------------+
| default | 61 | Knowledge.pdf | DOCUMENT | 745 | 2023-09-28T03:25:39.065762 | FINISHED | document embedding success |
+------------+-------------+---------------+----------+--------+----------------------------+----------+----------------------------+
```
#### List chunks of document in space `default`
```
dbgpt knowledge list --space_name default --doc_id 61 --page_size 5
```
```
+-----------------------------------------------------------------------------------+
| Document 61 in default description |
+------------+-------------+--------------+--------------+--------------+-----------+
| Space Name | Document ID | Total Chunks | Current Page | Current Size | Page Size |
+------------+-------------+--------------+--------------+--------------+-----------+
| default | 61 | 745 | 1 | 5 | 5 |
+------------+-------------+--------------+--------------+--------------+-----------+
+-----------------------------------------------------------------------------------------------------------------------+
| chunks of document id 61 in space default |
+------------+-------------+---------------+----------+-----------------------------------------------------------------+
| Space Name | Document ID | Document Name | Content | Meta Data |
+------------+-------------+---------------+----------+-----------------------------------------------------------------+
| default | 61 | Knowledge.pdf | [Hidden] | {'source': '/app/pilot/data/default/Knowledge.pdf', 'page': 10} |
| default | 61 | Knowledge.pdf | [Hidden] | {'source': '/app/pilot/data/default/Knowledge.pdf', 'page': 9} |
| default | 61 | Knowledge.pdf | [Hidden] | {'source': '/app/pilot/data/default/Knowledge.pdf', 'page': 9} |
| default | 61 | Knowledge.pdf | [Hidden] | {'source': '/app/pilot/data/default/Knowledge.pdf', 'page': 8} |
| default | 61 | Knowledge.pdf | [Hidden] | {'source': '/app/pilot/data/default/Knowledge.pdf', 'page': 8} |
+------------+-------------+---------------+----------+-----------------------------------------------------------------+
```
#### More list usage
```
dbgpt knowledge list --help
```
```
Usage: dbgpt knowledge list [OPTIONS]
List knowledge space
Options:
--space_name TEXT Your knowledge space name. If None, list all
spaces
--doc_id INTEGER Your document id in knowledge space. If Not
None, list all chunks in current document
--page INTEGER The page for every query [default: 1]
--page_size INTEGER The page size for every query [default: 20]
--show_content Query the document content of chunks
--output [text|html|csv|latex|json]
The output format
--help Show this message and exit.
```
### Delete your knowledge space or document in space
#### Delete your knowledge space
```
dbgpt knowledge delete --space_name default
```
#### Delete your document in space
```
dbgpt knowledge delete --space_name default --doc_name Knowledge.pdf
```
#### More delete usage
```
dbgpt knowledge delete --help
```
```
Usage: dbgpt knowledge delete [OPTIONS]
Delete your knowledge space or document in space
Options:
--space_name TEXT Your knowledge space name [default: default]
--doc_name TEXT The document name you want to delete. If doc_name is
None, this command will delete the whole space.
-y Confirm your choice
--help Show this message and exit.
```
#### More knowledge usage
```
dbgpt knowledge --help
```
```
Usage: dbgpt knowledge [OPTIONS] COMMAND [ARGS]...
Knowledge command line tool
Options:
--address TEXT Address of the Api server(If not set, try to read from
environment variable: API_ADDRESS). [default:
http://127.0.0.1:5000]
--help Show this message and exit.
Commands:
delete Delete your knowledge space or document in space
list List knowledge space
load Load your local documents to DB-GPT
```

View File

@@ -8,7 +8,7 @@ msgid ""
msgstr ""
"Project-Id-Version: DB-GPT 👏👏 0.3.5\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2023-08-29 21:14+0800\n"
"POT-Creation-Date: 2023-09-28 12:43+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
@@ -20,12 +20,12 @@ msgstr ""
"Generated-By: Babel 2.12.1\n"
#: ../../getting_started/application/kbqa/kbqa.md:1
#: 4b44ec7d6b3b492489b84bab4471fe46
#: 2f77b0e5795f4d3593b5f04c54c2c6c2
msgid "KBQA"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:3
#: c4217f8786e24f5190354d129b21dff5
#: 1e4f61ecf9084777ae451d2259bf804d
msgid ""
"![chat_knowledge](https://github.com/eosphoros-ai/DB-"
"GPT/assets/13723926/bc343c94-df3e-41e5-90d5-23b68c768c59)"
@@ -33,12 +33,12 @@ msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:3
#: ../../getting_started/application/kbqa/kbqa.md:7
#: 2f02ab2494b54fff87e7d1e310f38119 dc0349e48d5e4d89b1f9f353813c9f06
#: 7144258d06f3459d9404ef583b4f3696 e0aec0e78a9a40a2a6c6d496a5966fe8
msgid "chat_knowledge"
msgstr "chat_knowledge"
#: ../../getting_started/application/kbqa/kbqa.md:5
#: 149c4c9e15004aaf992c5896deb9e541
#: 4eeebe69ee5b4055bb2ac48444b5f3cc
msgid ""
"DB-GPT supports a knowledge question-answering module, which aims to "
"create an intelligent expert in the field of databases and provide "
@@ -46,7 +46,7 @@ msgid ""
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:7
#: c7e103a20a2e4989aab8a750cdc4dbf4
#: 99ec2e6a023744878a8e970de7588dfe
msgid ""
"![chat_knowledge](https://github.com/eosphoros-ai/DB-"
"GPT/assets/13723926/6e55f2e5-94f7-4906-aed6-097db5c6c721)"
@@ -54,83 +54,83 @@ msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:9
#: ../../getting_started/application/kbqa/kbqa.md:12
#: 3ddf012fb6d74eb1be1a0fd0ada9ddf6 e29bffef26fb44ac978d6cbe6584f48f
#: 77f6d58b0c714a0cbb2510aa2a036560 f3837660bb674945904a2acb34fd816a
msgid "KBQA abilities"
msgstr "KBQA现有能力"
#: ../../getting_started/application/kbqa/kbqa.md:13
#: 87cf02966b574d6db8baf0839b13e1e7
#: 96d691596d1f4309bd29e4d8b3a3bc61
msgid "Knowledge Space."
msgstr "知识空间"
#: ../../getting_started/application/kbqa/kbqa.md:14
#: 2777488125234408aa7156a69fcfacef
#: 36fe78a666a0410380e338674bb76e96
msgid "Multi Source Knowledge Source Embedding."
msgstr "多数据源Embedding"
#: ../../getting_started/application/kbqa/kbqa.md:15
#: c50f2de4ea6f4aedb7d4fd674ee3f6f7
#: 14659bb6964b402ba2aa912feffe0a28
msgid "Embedding Argument Adjust"
msgstr "Embedding参数自定义"
#: ../../getting_started/application/kbqa/kbqa.md:16
#: f8a7af83e94e45239bd0efdb06eb320b
#: c72212e1a0e54aa9b0b5adee687fed65
msgid "Chat Knowledge"
msgstr "知识问答"
#: ../../getting_started/application/kbqa/kbqa.md:17
#: e6025e23178f4f58a6d4c75a6bc1d036
#: d5fea791138240e8b26b4da0a7d3a4bf
msgid "Multi Vector DB"
msgstr "多向量数据库管理"
#: ../../getting_started/application/kbqa/kbqa.md:21
#: 0780e1d27af244429186caa866772c06
#: d2460e9418c44064be16f8b8bd76bf7a
msgid ""
"If your DB type is Sqlite, there is nothing to do to build KBQA service "
"database schema."
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:23
#: 38584aba054f4520a0b1d9b00d6abf06
#: b0ebff37da05465fb5c91abb496647ee
msgid ""
"If your DB type is Mysql or other DBTYPE, you will build kbqa service "
"database schema."
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:25
#: 9ef800860afe4728b2103286864ed3fb
#: ac0e3e657e9c4dfaafdb8884bf0d915a
msgid "Mysql"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:26
#: 3b30239fd457457eb707821794e786db
#: 4b899ec4f62c47a79e9cff79524ed069
msgid ""
"$ mysql -h127.0.0.1 -uroot -paa12345678 < "
"./assets/schema/knowledge_management.sql"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:28
#: 1cd533c2f0254f8d8d10bafe5811a279
#: a74b6c512b4d4ed399d5ee25e4a4f44a
msgid "or"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:30
#: 2b57e7d9a70f427e81122fe8d7d3c50b
#: 87216b282f664c6abfe736db5e3badd5
msgid "execute DBGPT/assets/schema/knowledge_management.sql"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:33
#: 45a0c8c8ff0a4b48ac2d66b4713c4108
#: 67aaa574f941485c8ba55a9058750175
msgid "Steps to KBQA In DB-GPT"
msgstr "怎样一步一步使用KBQA"
#: ../../getting_started/application/kbqa/kbqa.md:35
#: 2ff844b9a29f4717909d091a57d58fe8
#: 202ed073da4948a49d32b1beca69292d
msgid "1.Create Knowledge Space"
msgstr "1.首先创建知识空间"
#: ../../getting_started/application/kbqa/kbqa.md:36
#: 081e1d1ef5bb42ddbd7330dd3ac1d38e
#: f1defb29643f4664a125cf127e63ef71
#, fuzzy
msgid ""
"If you are using Knowledge Space for the first time, you need to create a"
@@ -140,17 +140,17 @@ msgid ""
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:36
#: 4a393bf0f50647d4b0cfc64db80847eb
#: 378e6091c3eb4f0d8ca4d4144303dde1
msgid "create_space"
msgstr "create_space"
#: ../../getting_started/application/kbqa/kbqa.md:41
#: 96303597bc364952b7249e805486e73f
#: 669504b548ce4b7b9ea4c463b446cf39
msgid "2.Create Knowledge Document"
msgstr "2.上传知识"
#: ../../getting_started/application/kbqa/kbqa.md:42
#: 765f93f2b668491cb6824ea4706cb449
#: 731b15e4396b450589d619fccd78d542
msgid ""
"DB-GPT now support Multi Knowledge Source, including Text, WebUrl, and "
"Document(PDF, Markdown, Word, PPT, HTML and CSV). After successfully "
@@ -165,29 +165,29 @@ msgstr ""
"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:44
#: a0eddeecc620479483bf50857da39ffd
#: 7c020f677a364693800952d558ba357e
msgid "2.1 Choose Knowledge Type:"
msgstr "2.1 选择知识类型"
#: ../../getting_started/application/kbqa/kbqa.md:45
#: 44de66f399324454b389d5c348af94e9
#: c88460c498ff4fbca22f35e181c66723
msgid ""
"![document](https://github.com/eosphoros-ai/DB-"
"GPT/assets/13723926/5b8173da-f444-4607-9d12-14bcab8179d0)"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:45
#: 1ae65290b99d490bb72b060084ecc726
#: 60fcd6db28c546728bf9c015b63e9434
msgid "document"
msgstr "document"
#: ../../getting_started/application/kbqa/kbqa.md:47
#: d8720434626444b593bb3b06b50dc70f
#: ffb8436b6e97468296e5852530e3d9c8
msgid "2.2 Upload Document:"
msgstr "2.2上传文档"
#: ../../getting_started/application/kbqa/kbqa.md:48
#: 2d4bcbeb391a47b89454b06cb041dff2
#: a652b17e64b040938cf4e09ef7ed470a
msgid ""
"![upload](https://github.com/eosphoros-ai/DB-GPT/assets/13723926"
"/91b338fc-d3b2-476e-9396-3f6b4f16a890)"
@@ -197,30 +197,30 @@ msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:52
#: ../../getting_started/application/kbqa/kbqa.md:57
#: ../../getting_started/application/kbqa/kbqa.md:70
#: 58b32cb59a6242679f4a1e5fc7ca819f 81041a1f25b64b19a7f662ed55029224
#: 8891e61f67014355b74c17d013c09cca f0e9c548494f4045a3dc92e993f4cfe7
#: 3f1c6873d54c47fea96d91188f728af9 434f854aa1af4f4bbf9ec4060388c643
#: c1404f398cc3480d9c59b4ce326501e7 f18624fc081d4276859d4a4c99e998ee
msgid "upload"
msgstr "upload"
#: ../../getting_started/application/kbqa/kbqa.md:51
#: 645bf91a4f6a428a9e99ca29599c0722
#: 6695dbe6d16e43d7b88dbad61039ff7e
msgid "3.Chat With Knowledge"
msgstr "3.知识问答"
#: ../../getting_started/application/kbqa/kbqa.md:52
#: 85077af67bd740c1b3b02996dc287a80
#: 30b3afb9cb4d4705833ba15580425b05
msgid ""
"![upload](https://github.com/eosphoros-ai/DB-"
"GPT/assets/13723926/a8281be7-1454-467d-81c9-15ef108aac10)"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:54
#: 42d5776030ad4109810a0cb18e19de37
#: 05cc4bf0473f4f88aef63342b714d472
msgid "4.Adjust Space arguments"
msgstr "4.调整知识参数"
#: ../../getting_started/application/kbqa/kbqa.md:55
#: a8ea23895a4b4312b1c1e072865f8b90
#: 9ec125362dbb4aec864777313b1a8327
msgid ""
"Each knowledge space supports argument customization, including the "
"relevant arguments for vector retrieval and the arguments for knowledge "
@@ -228,78 +228,78 @@ msgid ""
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:56
#: 2f5c087e4f7a49828aa797fafff237f0
#: 54fd9461ced1436aa6c51984024caa74
msgid "4.1 Embedding"
msgstr "4.1 Embedding"
#: ../../getting_started/application/kbqa/kbqa.md:57
#: 47087bf391b642f3ba73e461d2d132a0
#: 4b17fde7063e40e88dd121024f3e1c42
msgid ""
"Embedding Argument ![upload](https://github.com/eosphoros-ai/DB-"
"GPT/assets/13723926/f1221bd5-d049-4ceb-96e6-8709e76e502e)"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:61
#: 1ed384ba0501423184a4c977d86b8b3a
#: 6715234540d74eb79da60cf5ec29e236
msgid "Embedding arguments"
msgstr "Embedding arguments"
#: ../../getting_started/application/kbqa/kbqa.md:62
#: 848962be69a348ffab3dd48839fb100a
#: af7ed9e32c6846b6a75893a55e0d78a4
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:63
#: 0880963aeb9c426187809a7086c224a8
#: 05290f955cd142a2857d20786edf0952
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:64
#: a6ead8ae58164749b83e5c972537fe8b
#: b6e088dda8f142438bc0baebd357fa0e
msgid "recall_type:recall type."
msgstr "recall_type:召回类型"
#: ../../getting_started/application/kbqa/kbqa.md:65
#: 70d900b0948849d080effcdfc79bb685
#: 509bb3adefb74b65baea79bcbe94a240
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:66
#: 489a58835a5d4c98ad5f6f904f7af370
#: 43ef5b6a16c0435b9b7416d3600556e5
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:67
#: b42781f2340c478f86137147fd4a6c91
#: 800fb14f22304155bedc5dc666f56a25
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:69
#: 5f027d4a10394e7da3d4b50fc2663f82
#: 5497d17bcf014ad5b61d5febd7a9fda5
msgid "4.2 Prompt"
msgstr "4.2 Prompt"
#: ../../getting_started/application/kbqa/kbqa.md:70
#: 9ad62d8626584e80a82fcef239c0f546
#: dd9cdfac5aae44c8998b36ae0ed286b8
msgid ""
"Prompt Argument ![upload](https://github.com/eosphoros-ai/DB-"
"GPT/assets/13723926/9918c9c3-ed64-4804-9e05-fa7d7d177bec)"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:74
#: ec0717b8d210410f9894d2a4f51642e1
#: fbede51cc73444aab74fa646834ea1c2
msgid "Prompt arguments"
msgstr "Prompt arguments"
#: ../../getting_started/application/kbqa/kbqa.md:75
#: 7cf68eacd5ae4151abdefe44feb239e1
#: a85ab9b05ec04cd59d3f4539599a8e35
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:76
#: 2d9293acfb1a495c9b08261e957b2395
#: 48258fcdbb134a0e820347185ea45ca0
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 "
@@ -307,75 +307,168 @@ msgid ""
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:77
#: 307dd62261214e4e84beb7f19b3e2f26
#: 2dab662fc6a945b3b2691831f16b52e7
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:79
#: 07b797731fa74738acb3e1fb4c03deac
#: a7c5a81457334f39a8956146fe4aa951
msgid "5.Change Vector Database"
msgstr "5.Change Vector Database"
#: ../../getting_started/application/kbqa/kbqa.md:81
#: 43fa40ced23842b48007b4264c1423c0
#: dccbc6e611e64f79aadb849ae1cdf0d2
msgid "Vector Store SETTINGS"
msgstr "Vector Store SETTINGS"
#: ../../getting_started/application/kbqa/kbqa.md:82
#: 0ed4e0c6a81e4265b443a2c6d05d440b
#: a3af9f960c3144b2884a5ff3dc4f8cfa
msgid "Chroma"
msgstr "Chroma"
#: ../../getting_started/application/kbqa/kbqa.md:83
#: 8ef2d15ffd0c4919bdbfdb52443021eb
#: f195989635ec403d9f7ece263c451fa2
msgid "VECTOR_STORE_TYPE=Chroma"
msgstr "VECTOR_STORE_TYPE=Chroma"
#: ../../getting_started/application/kbqa/kbqa.md:84
#: 08504aaae0014bd9992345f036989198
#: 9821aa494e514654bf33335c2db7700f
msgid "MILVUS"
msgstr "MILVUS"
#: ../../getting_started/application/kbqa/kbqa.md:85
#: aa30fe77dc3f46bfb153b81e0cbdfb97
#: 1d7ef3150b6549fc834567f2647c32db
msgid "VECTOR_STORE_TYPE=Milvus"
msgstr "VECTOR_STORE_TYPE=Milvus"
#: ../../getting_started/application/kbqa/kbqa.md:86
#: e14c1646e5ca4677a471645c13dca835
#: 702e9fc52c1d45cc9136ffd0a1bbcbc8
msgid "MILVUS_URL=127.0.0.1"
msgstr "MILVUS_URL=127.0.0.1"
#: ../../getting_started/application/kbqa/kbqa.md:87
#: 0f0614f951934fd6abfb0fd45e0b79e7
#: 44ed55973e50490db566f5d65fa87207
msgid "MILVUS_PORT=19530"
msgstr "MILVUS_PORT=19530"
#: ../../getting_started/application/kbqa/kbqa.md:88
#: 4dafbbd894e4469e80414b54bde69193
#: e1e13a389f404a3384e96b178b7887d0
msgid "MILVUS_USERNAME"
msgstr "MILVUS_USERNAME"
#: ../../getting_started/application/kbqa/kbqa.md:89
#: 1759ec4d744e42a5a928c6abcc2dd2ac
#: 5755432971214b6dbe016a1556be759c
msgid "MILVUS_PASSWORD"
msgstr "MILVUS_PASSWORD"
#: ../../getting_started/application/kbqa/kbqa.md:90
#: d44bcea1db4f4388bc2ae7968e541761
#: f92e8123fadc4f67a3a81ce76f642d67
msgid "MILVUS_SECURE="
msgstr "MILVUS_SECURE="
#: ../../getting_started/application/kbqa/kbqa.md:92
#: f33218e0880f4d888438d3333f4a0895
#: 5ad47c8768484e67a0b919d290b0fcde
msgid "WEAVIATE"
msgstr "WEAVIATE"
#: ../../getting_started/application/kbqa/kbqa.md:93
#: 42a2102b236447ff83820d3a1602c3f2
#: 139b2fab9a294215ba152710e464d425
msgid "WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network"
msgstr "WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.networkc"
#: ../../getting_started/application/kbqa/kbqa.md:96
#: bd9c81cd547142fab5857dbf0df441d0
msgid "KBQA command line"
msgstr "KBQA 命令行工具"
#: ../../getting_started/application/kbqa/kbqa.md:98
#: fba52bfa428549e683c9cfb8e9684636
msgid "Load your local documents to DB-GPT"
msgstr "将你的本地文档导入到 DB-GPT"
#: ../../getting_started/application/kbqa/kbqa.md:104
#: 5c3e7fa9b2b04e6097781d3f406c2bae
msgid "`--space_name`: Your knowledge space name, default: `default`"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:105
#: 083bb6913da64f8a880b20e31d138d7b
msgid ""
"`--local_doc_path`: Your document directory or document file path, "
"default: `./pilot/datasets`"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:106
#: 7b17564ffc7a43ab8e5beb023f18a59a
msgid "`--vector_store_type`: Vector store type, default: `Chroma`"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:108
#: 814bdf5ecddd4490af57dcab73ae8c85
msgid "**View the `dbgpt knowledge load --help`help**"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:114
#: f1aaa308ef4b46f1adbb8ec64738f361
msgid "Here you can see the parameters:"
msgstr ""
#: ../../getting_started/application/kbqa/kbqa.md:141
#: ../../getting_started/application/kbqa/kbqa.md:143
#: 163ff96e128641509933c1871b6bde64 fca3ea3c13bc4fa3bfa33845f4d88b52
#, fuzzy
msgid "List knowledge space"
msgstr "查看知识空间"
#: ../../getting_started/application/kbqa/kbqa.md:149
#: ../../getting_started/application/kbqa/kbqa.md:169
#: 57b89ee3fde745ff8502ede525fc4a8c d9852d13a9b444618a598ba4abe47493
msgid "Output should look something like the following:"
msgstr "输出如下:"
#: ../../getting_started/application/kbqa/kbqa.md:163
#: 14300078a0a74aee9cf6e54c470e3862
#, fuzzy
msgid "List documents in knowledge space"
msgstr "查看某个知识空间中的文档"
#: ../../getting_started/application/kbqa/kbqa.md:188
#: b9afd5b23fb947c691d66f82f86c36f2
msgid "List chunks of document in space `default`"
msgstr "查看某个知识空间文档中的块"
#: ../../getting_started/application/kbqa/kbqa.md:217
#: 294d9d963299400db39c5c51ab5d2e23
msgid "More list usage"
msgstr "更多 list 命令用户"
#: ../../getting_started/application/kbqa/kbqa.md:242
#: 5d962a6b5b2d4fb6809bc84cb7711120
msgid "Delete your knowledge space or document in space"
msgstr "删除你的知识空间或者知识空间中的文档"
#: ../../getting_started/application/kbqa/kbqa.md:244
#: f1deee3aaf8e41308f2f81974032e4d4
#, fuzzy
msgid "Delete your knowledge space"
msgstr "删除知识空间"
#: ../../getting_started/application/kbqa/kbqa.md:250
#: ba2314a2d20944f7b64a60e67a5b8d94
msgid "Delete your document in space"
msgstr "删除知识空间中的文档"
#: ../../getting_started/application/kbqa/kbqa.md:257
#: 2400777f270d40e2adcdc38a2d3cb73a
msgid "More delete usage"
msgstr "更多删除用法"
#: ../../getting_started/application/kbqa/kbqa.md:276
#: 4e79bbda201347f2822b1742805923a6
#, fuzzy
msgid "More knowledge usage"
msgstr "更知识库命令用法"
#~ msgid "![chat_knowledge](../../../../assets/chat_knowledge.png)"
#~ msgstr "![chat_knowledge](../../../../assets/chat_knowledge.png)"

View File

@@ -18,7 +18,7 @@ logger = logging.getLogger("dbgpt_cli")
default=API_ADDRESS,
required=False,
show_default=True,
help=("Address of the Api server."),
help=("Address of the Api server(If not set, try to read from environment variable: API_ADDRESS)."),
)
def knowledge_cli_group(address: str):
"""Knowledge command line tool"""
@@ -126,7 +126,7 @@ def load(
chunk_size: int,
chunk_overlap: int,
):
"""Load your local knowledge to DB-GPT"""
"""Load your local documents to DB-GPT"""
from pilot.server.knowledge._cli.knowledge_client import knowledge_init
knowledge_init(