mirror of
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Merge branch 'main' into Agent_Hub_Dev
# Conflicts: # README.zh.md
This commit is contained in:
yhjun1026
commit
afb5fd1445
132
README.md
132
README.md
@ -62,24 +62,12 @@ Run on an RTX 4090 GPU.
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##### LLM Management
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##### FastChat && vLLM
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##### Trace
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##### Chat Knowledge
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#### Chat with data, and figure charts.
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<p align="left">
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<img src="./assets/chat_excel/chat_excel_6.png" width="800px" />
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</p>
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<p align="left">
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<img src="./assets/chat_dashboard/chat_dashboard_2.png" width="800px" />
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</p>
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## Install
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@ -109,66 +97,61 @@ Run on an RTX 4090 GPU.
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## Features
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Currently, we have released multiple key features, which are listed below to demonstrate our current capabilities:
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- SQL language capabilities
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- SQL generation
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- SQL diagnosis
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- Private domain Q&A and data processing
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- Knowledge Management(We currently support many document formats: txt, pdf, md, html, doc, ppt, and url.)
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- ChatDB
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- ChatExcel
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- ChatDashboard
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- Multi-Agents&Plugins
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- Unified vector storage/indexing of knowledge base
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- Support for unstructured data
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- PDF
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- TXT
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- Markdown
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- CSV
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- DOC
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- PPT
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- WebURL
|
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- Multi LLMs Support, Supports multiple large language models, currently supporting
|
||||
- [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)
|
||||
- [baichuan2-7b/baichuan2-13b](https://huggingface.co/baichuan-inc)
|
||||
- [internlm/internlm-chat-7b](https://huggingface.co/internlm/internlm-chat-7b)
|
||||
- [Qwen/Qwen-7B-Chat/Qwen-14B-Chat](https://huggingface.co/Qwen/)
|
||||
- [Vicuna](https://huggingface.co/Tribbiani/vicuna-13b)
|
||||
- [BlinkDL/RWKV-4-Raven](https://huggingface.co/BlinkDL/rwkv-4-raven)
|
||||
- [camel-ai/CAMEL-13B-Combined-Data](https://huggingface.co/camel-ai/CAMEL-13B-Combined-Data)
|
||||
- [databricks/dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b)
|
||||
- [FreedomIntelligence/phoenix-inst-chat-7b](https://huggingface.co/FreedomIntelligence/phoenix-inst-chat-7b)
|
||||
- [h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b](https://huggingface.co/h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b)
|
||||
- [lcw99/polyglot-ko-12.8b-chang-instruct-chat](https://huggingface.co/lcw99/polyglot-ko-12.8b-chang-instruct-chat)
|
||||
- [lmsys/fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5)
|
||||
- [mosaicml/mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat)
|
||||
- [Neutralzz/BiLLa-7B-SFT](https://huggingface.co/Neutralzz/BiLLa-7B-SFT)
|
||||
- [nomic-ai/gpt4all-13b-snoozy](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy)
|
||||
- [NousResearch/Nous-Hermes-13b](https://huggingface.co/NousResearch/Nous-Hermes-13b)
|
||||
- [openaccess-ai-collective/manticore-13b-chat-pyg](https://huggingface.co/openaccess-ai-collective/manticore-13b-chat-pyg)
|
||||
- [OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5](https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5)
|
||||
- [project-baize/baize-v2-7b](https://huggingface.co/project-baize/baize-v2-7b)
|
||||
- [Salesforce/codet5p-6b](https://huggingface.co/Salesforce/codet5p-6b)
|
||||
- [StabilityAI/stablelm-tuned-alpha-7b](https://huggingface.co/stabilityai/stablelm-tuned-alpha-7b)
|
||||
- [THUDM/chatglm-6b](https://huggingface.co/THUDM/chatglm-6b)
|
||||
- [THUDM/chatglm2-6b](https://huggingface.co/THUDM/chatglm2-6b)
|
||||
- [tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b)
|
||||
- [timdettmers/guanaco-33b-merged](https://huggingface.co/timdettmers/guanaco-33b-merged)
|
||||
- [togethercomputer/RedPajama-INCITE-7B-Chat](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Chat)
|
||||
- [WizardLM/WizardLM-13B-V1.0](https://huggingface.co/WizardLM/WizardLM-13B-V1.0)
|
||||
- [WizardLM/WizardCoder-15B-V1.0](https://huggingface.co/WizardLM/WizardCoder-15B-V1.0)
|
||||
- [baichuan-inc/baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B)
|
||||
- [HuggingFaceH4/starchat-beta](https://huggingface.co/HuggingFaceH4/starchat-beta)
|
||||
- [FlagAlpha/Llama2-Chinese-13b-Chat](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat)
|
||||
- [BAAI/AquilaChat-7B](https://huggingface.co/BAAI/AquilaChat-7B)
|
||||
- [all models of OpenOrca](https://huggingface.co/Open-Orca)
|
||||
- [Spicyboros](https://huggingface.co/jondurbin/spicyboros-7b-2.2?not-for-all-audiences=true) + [airoboros 2.2](https://huggingface.co/jondurbin/airoboros-l2-13b-2.2)
|
||||
- [VMware's OpenLLaMa OpenInstruct](https://huggingface.co/VMware/open-llama-7b-open-instruct)
|
||||
- Private KBQA & data processing
|
||||
|
||||
- Support API Proxy LLMs
|
||||
- [x] [ChatGPT](https://api.openai.com/)
|
||||
- [x] [Tongyi](https://www.aliyun.com/product/dashscope)
|
||||
- [x] [Wenxin](https://cloud.baidu.com/product/wenxinworkshop?track=dingbutonglan)
|
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- [x] [ChatGLM](http://open.bigmodel.cn/)
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The DB-GPT project offers a range of features to enhance knowledge base construction and enable efficient storage and retrieval of both structured and unstructured data. These include built-in support for uploading multiple file formats, the ability to integrate plug-ins for custom data extraction, and unified vector storage and retrieval capabilities for managing large volumes of information.
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- Multiple data sources & visualization
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The DB-GPT project enables seamless natural language interaction with various data sources, including Excel, databases, and data warehouses. It facilitates effortless querying and retrieval of information from these sources, allowing users to engage in intuitive conversations and obtain insights. Additionally, DB-GPT supports the generation of analysis reports, providing users with valuable summaries and interpretations of the data.
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- Multi-Agents&Plugins
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Supports custom plug-ins to perform tasks, natively supports the Auto-GPT plug-in model, and the Agents protocol adopts the Agent Protocol standard
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- Fine-tuning text2SQL
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An automated fine-tuning lightweight framework built around large language models, Text2SQL data sets, LoRA/QLoRA/Pturning and other fine-tuning methods, making TextSQL fine-tuning as convenient as an assembly line. [DB-GPT-Hub](https://github.com/eosphoros-ai/DB-GPT-Hub)
|
||||
|
||||
- Multi LLMs Support, Supports multiple large language models, currently supporting
|
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|
||||
Massive model support, including dozens of large language models such as open source and API agents. Such as LLaMA/LLaMA2, Baichuan, ChatGLM, Wenxin, Tongyi, Zhipu, etc.
|
||||
- [Vicuna](https://huggingface.co/Tribbiani/vicuna-13b)
|
||||
- [vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5)
|
||||
- [LLama2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)
|
||||
- [baichuan2-13b](https://huggingface.co/baichuan-inc)
|
||||
- [baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B)
|
||||
- [chatglm-6b](https://huggingface.co/THUDM/chatglm-6b)
|
||||
- [chatglm2-6b](https://huggingface.co/THUDM/chatglm2-6b)
|
||||
- [falcon-40b](https://huggingface.co/tiiuae/falcon-40b)
|
||||
- [internlm-chat-7b](https://huggingface.co/internlm/internlm-chat-7b)
|
||||
- [Qwen-7B-Chat/Qwen-14B-Chat](https://huggingface.co/Qwen/)
|
||||
- [RWKV-4-Raven](https://huggingface.co/BlinkDL/rwkv-4-raven)
|
||||
- [CAMEL-13B-Combined-Data](https://huggingface.co/camel-ai/CAMEL-13B-Combined-Data)
|
||||
- [dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b)
|
||||
- [h2ogpt-gm-oasst1-en-2048-open-llama-7b](https://huggingface.co/h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b)
|
||||
- [fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5)
|
||||
- [mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat)
|
||||
- [gpt4all-13b-snoozy](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy)
|
||||
- [Nous-Hermes-13b](https://huggingface.co/NousResearch/Nous-Hermes-13b)
|
||||
- [codet5p-6b](https://huggingface.co/Salesforce/codet5p-6b)
|
||||
- [guanaco-33b-merged](https://huggingface.co/timdettmers/guanaco-33b-merged)
|
||||
- [WizardLM-13B-V1.0](https://huggingface.co/WizardLM/WizardLM-13B-V1.0)
|
||||
- [WizardLM/WizardCoder-15B-V1.0](https://huggingface.co/WizardLM/WizardCoder-15B-V1.0)
|
||||
- [Llama2-Chinese-13b-Chat](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat)
|
||||
- [OpenLLaMa OpenInstruct](https://huggingface.co/VMware/open-llama-7b-open-instruct)
|
||||
|
||||
etc.
|
||||
|
||||
- Support API Proxy LLMs
|
||||
- [x] [ChatGPT](https://api.openai.com/)
|
||||
- [x] [Tongyi](https://www.aliyun.com/product/dashscope)
|
||||
- [x] [Wenxin](https://cloud.baidu.com/product/wenxinworkshop?track=dingbutonglan)
|
||||
- [x] [ChatGLM](http://open.bigmodel.cn/)
|
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|
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- Privacy and security
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The privacy and security of data are ensured through various technologies such as privatized large models and proxy desensitization.
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- Support Datasources
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@ -209,6 +192,11 @@ The core capabilities mainly consist of the following parts:
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6. Privacy & Secure: You can be assured that there is no risk of data leakage, and your data is 100% private and secure.
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7. Text2SQL: We enhance the Text-to-SQL performance by applying Supervised Fine-Tuning (SFT) on large language models
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### RAG-IN-Action
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<p align="center">
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<img src="./assets/RAG-IN-ACTION.jpg" width="800px" />
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</p>
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### SubModule
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- [DB-GPT-Hub](https://github.com/eosphoros-ai/DB-GPT-Hub) Text-to-SQL performance by applying Supervised Fine-Tuning (SFT) on large language models.
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- [DB-GPT-Plugins](https://github.com/eosphoros-ai/DB-GPT-Plugins) DB-GPT Plugins, Can run autogpt plugin directly
|
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|
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153
README.zh.md
153
README.zh.md
@ -59,21 +59,19 @@ DB-GPT 是一个开源的以数据库为基础的GPT实验项目，使用本地
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||||
|
||||
##### Chat Excel
|
||||
|
||||
##### Chat Plugin
|
||||
#### Chat Plugin
|
||||
|
||||
##### LLM Management
|
||||
#### LLM Management
|
||||
|
||||
##### FastChat && vLLM
|
||||
|
||||
##### Trace
|
||||
#### FastChat && vLLM
|
||||
|
||||
#### Trace
|
||||
|
||||
##### Chat Knowledge
|
||||
#### Chat Knowledge
|
||||
|
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|
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#### 根据自然语言对话生成分析图表
|
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|
||||
|
||||
|
||||
<p align="left">
|
||||
<img src="./assets/chat_excel/chat_excel_6.png" width="800px" />
|
||||
</p>
|
||||
@ -86,32 +84,6 @@ DB-GPT 是一个开源的以数据库为基础的GPT实验项目，使用本地
|
||||
<img src="./assets/chat_dashboard/chat_dashboard_2.png" width="800px" />
|
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</p>
|
||||
|
||||
#### 根据自然语言对话生成SQL
|
||||
<p align="left">
|
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<img src="./assets/chatSQL.png" width="800px" />
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</p>
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|
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#### 与数据库元数据信息进行对话, 生成准确SQL语句
|
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<p align="left">
|
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<img src="./assets/chatdb.png" width="800px" />
|
||||
</p>
|
||||
|
||||
|
||||
#### 与数据对话, 直接查看执行结果
|
||||
<p align="left">
|
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<img src="./assets/chatdata.png" width="800px" />
|
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</p>
|
||||
|
||||
#### 知识库管理
|
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<p align="left">
|
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<img src="./assets/ks.png" width="800px" />
|
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</p>
|
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|
||||
#### 根据知识库对话, 比如pdf、csv、txt、words等等.
|
||||
<p align="left">
|
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<img src="./assets/chat_knowledge_zh.png" width="800px" />
|
||||
</p>
|
||||
|
||||
## 安装
|
||||
|
||||
|
||||
@ -142,61 +114,59 @@ DB-GPT 是一个开源的以数据库为基础的GPT实验项目，使用本地
|
||||
|
||||
目前我们已经发布了多种关键的特性，这里一一列举展示一下当前发布的能力。
|
||||
|
||||
- SQL 语言能力
|
||||
- SQL生成
|
||||
- SQL诊断
|
||||
- 私域问答与数据处理
|
||||
- 知识库管理(目前支持 txt, pdf, md, html, doc, ppt, and url)
|
||||
- 数据库知识问答
|
||||
- 数据处理
|
||||
- 数据库对话
|
||||
- Chat2Dashboard
|
||||
- 插件模型
|
||||
- 知识库统一向量存储/索引
|
||||
- 非结构化数据支持包括PDF、MarkDown、CSV、WebURL
|
||||
- 多模型支持与管理
|
||||
- 支持多种大语言模型, 当前已支持如下模型:
|
||||
- [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)
|
||||
- [baichuan2-7b/baichuan2-13b](https://huggingface.co/baichuan-inc)
|
||||
- [internlm/internlm-chat-7b](https://huggingface.co/internlm/internlm-chat-7b)
|
||||
- [Qwen/Qwen-7B-Chat/Qwen-14B-Chat](https://huggingface.co/Qwen/)
|
||||
- [Vicuna](https://huggingface.co/Tribbiani/vicuna-13b)
|
||||
- [BlinkDL/RWKV-4-Raven](https://huggingface.co/BlinkDL/rwkv-4-raven)
|
||||
- [camel-ai/CAMEL-13B-Combined-Data](https://huggingface.co/camel-ai/CAMEL-13B-Combined-Data)
|
||||
- [databricks/dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b)
|
||||
- [FreedomIntelligence/phoenix-inst-chat-7b](https://huggingface.co/FreedomIntelligence/phoenix-inst-chat-7b)
|
||||
- [h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b](https://huggingface.co/h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b)
|
||||
- [lcw99/polyglot-ko-12.8b-chang-instruct-chat](https://huggingface.co/lcw99/polyglot-ko-12.8b-chang-instruct-chat)
|
||||
- [lmsys/fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5)
|
||||
- [mosaicml/mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat)
|
||||
- [Neutralzz/BiLLa-7B-SFT](https://huggingface.co/Neutralzz/BiLLa-7B-SFT)
|
||||
- [nomic-ai/gpt4all-13b-snoozy](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy)
|
||||
- [NousResearch/Nous-Hermes-13b](https://huggingface.co/NousResearch/Nous-Hermes-13b)
|
||||
- [openaccess-ai-collective/manticore-13b-chat-pyg](https://huggingface.co/openaccess-ai-collective/manticore-13b-chat-pyg)
|
||||
- [OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5](https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5)
|
||||
- [project-baize/baize-v2-7b](https://huggingface.co/project-baize/baize-v2-7b)
|
||||
- [Salesforce/codet5p-6b](https://huggingface.co/Salesforce/codet5p-6b)
|
||||
- [StabilityAI/stablelm-tuned-alpha-7b](https://huggingface.co/stabilityai/stablelm-tuned-alpha-7b)
|
||||
- [THUDM/chatglm-6b](https://huggingface.co/THUDM/chatglm-6b)
|
||||
- [THUDM/chatglm2-6b](https://huggingface.co/THUDM/chatglm2-6b)
|
||||
- [tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b)
|
||||
- [timdettmers/guanaco-33b-merged](https://huggingface.co/timdettmers/guanaco-33b-merged)
|
||||
- [togethercomputer/RedPajama-INCITE-7B-Chat](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Chat)
|
||||
- [WizardLM/WizardLM-13B-V1.0](https://huggingface.co/WizardLM/WizardLM-13B-V1.0)
|
||||
- [WizardLM/WizardCoder-15B-V1.0](https://huggingface.co/WizardLM/WizardCoder-15B-V1.0)
|
||||
- [baichuan-inc/baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B)
|
||||
- [HuggingFaceH4/starchat-beta](https://huggingface.co/HuggingFaceH4/starchat-beta)
|
||||
- [FlagAlpha/Llama2-Chinese-13b-Chat](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat)
|
||||
- [BAAI/AquilaChat-7B](https://huggingface.co/BAAI/AquilaChat-7B)
|
||||
- [all models of OpenOrca](https://huggingface.co/Open-Orca)
|
||||
- [Spicyboros](https://huggingface.co/jondurbin/spicyboros-7b-2.2?not-for-all-audiences=true) + [airoboros 2.2](https://huggingface.co/jondurbin/airoboros-l2-13b-2.2)
|
||||
- [VMware's OpenLLaMa OpenInstruct](https://huggingface.co/VMware/open-llama-7b-open-instruct)
|
||||
- 私域问答&数据处理
|
||||
|
||||
- 支持在线代理模型
|
||||
- [x] [ChatGPT](https://api.openai.com/)
|
||||
- [x] [Tongyi](https://www.aliyun.com/product/dashscope)
|
||||
- [x] [Wenxin](https://cloud.baidu.com/product/wenxinworkshop?track=dingbutonglan)
|
||||
- [x] [ChatGLM](http://open.bigmodel.cn/)
|
||||
支持内置、多文件格式上传、插件自抓取等方式自定义构建知识库，对海量结构化，非结构化数据做统一向量存储与检索
|
||||
|
||||
- 多数据源&可视化
|
||||
|
||||
支持自然语言与Excel、数据库、数仓等多种数据源交互，并支持分析报告。
|
||||
|
||||
- 自动化微调
|
||||
|
||||
围绕大语言模型、Text2SQL数据集、LoRA/QLoRA/Pturning等微调方法构建的自动化微调轻量框架, 让TextSQL微调像流水线一样方便。详见: [DB-GPT-Hub](https://github.com/eosphoros-ai/DB-GPT-Hub)
|
||||
|
||||
- Multi-Agents&Plugins
|
||||
|
||||
支持自定义插件执行任务，原生支持Auto-GPT插件模型，Agents协议采用Agent Protocol标准
|
||||
|
||||
- 多模型支持与管理
|
||||
|
||||
海量模型支持，包括开源、API代理等几十种大语言模型。如LLaMA/LLaMA2、Baichuan、ChatGLM、文心、通义、智谱等。
|
||||
- 支持多种大语言模型, 当前已支持如下模型:
|
||||
- [Vicuna](https://huggingface.co/Tribbiani/vicuna-13b)
|
||||
- [vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5)
|
||||
- [LLama2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)
|
||||
- [baichuan2-13b](https://huggingface.co/baichuan-inc)
|
||||
- [baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B)
|
||||
- [chatglm-6b](https://huggingface.co/THUDM/chatglm-6b)
|
||||
- [chatglm2-6b](https://huggingface.co/THUDM/chatglm2-6b)
|
||||
- [falcon-40b](https://huggingface.co/tiiuae/falcon-40b)
|
||||
- [internlm-chat-7b](https://huggingface.co/internlm/internlm-chat-7b)
|
||||
- [Qwen-7B-Chat/Qwen-14B-Chat](https://huggingface.co/Qwen/)
|
||||
- [RWKV-4-Raven](https://huggingface.co/BlinkDL/rwkv-4-raven)
|
||||
- [CAMEL-13B-Combined-Data](https://huggingface.co/camel-ai/CAMEL-13B-Combined-Data)
|
||||
- [dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b)
|
||||
- [h2ogpt-gm-oasst1-en-2048-open-llama-7b](https://huggingface.co/h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b)
|
||||
- [fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5)
|
||||
- [mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat)
|
||||
- [gpt4all-13b-snoozy](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy)
|
||||
- [Nous-Hermes-13b](https://huggingface.co/NousResearch/Nous-Hermes-13b)
|
||||
- [codet5p-6b](https://huggingface.co/Salesforce/codet5p-6b)
|
||||
- [guanaco-33b-merged](https://huggingface.co/timdettmers/guanaco-33b-merged)
|
||||
- [WizardLM-13B-V1.0](https://huggingface.co/WizardLM/WizardLM-13B-V1.0)
|
||||
- [WizardLM/WizardCoder-15B-V1.0](https://huggingface.co/WizardLM/WizardCoder-15B-V1.0)
|
||||
- [Llama2-Chinese-13b-Chat](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat)
|
||||
- [OpenLLaMa OpenInstruct](https://huggingface.co/VMware/open-llama-7b-open-instruct)
|
||||
- 支持在线代理模型
|
||||
- [x] [ChatGPT](https://api.openai.com/)
|
||||
- [x] [Tongyi](https://www.aliyun.com/product/dashscope)
|
||||
- [x] [Wenxin](https://cloud.baidu.com/product/wenxinworkshop?track=dingbutonglan)
|
||||
- [x] [ChatGLM](http://open.bigmodel.cn/)
|
||||
|
||||
- 隐私安全
|
||||
|
||||
通过私有化大模型、代理脱敏等多种技术保障数据的隐私安全。
|
||||
|
||||
- 支持数据源
|
||||
|
||||
@ -227,7 +197,7 @@ DB-GPT基于 [FastChat](https://github.com/lm-sys/FastChat) 构建大模型运
|
||||
整个DB-GPT的架构，如下图所示
|
||||
|
||||
<p align="center">
|
||||
<img src="./assets/DB-GPT.png" width="800px" />
|
||||
<img src="./assets/DB-GPT_zh.png" width="800px" />
|
||||
</p>
|
||||
|
||||
核心能力主要有以下几个部分。
|
||||
@ -239,6 +209,11 @@ DB-GPT基于 [FastChat](https://github.com/lm-sys/FastChat) 构建大模型运
|
||||
6. 隐私和安全: 您可以放心，没有数据泄露的风险，您的数据100%私密和安全。
|
||||
7. Text2SQL: 我们通过在大型语言模型监督微调（SFT）来增强文本到SQL的性能
|
||||
|
||||
### RAG生产落地实践架构
|
||||
<p align="center">
|
||||
<img src="./assets/RAG-IN-ACTION.jpg" width="800px" />
|
||||
</p>
|
||||
|
||||
### 子模块
|
||||
- [DB-GPT-Hub](https://github.com/csunny/DB-GPT-Hub) 通过微调来持续提升Text2SQL效果
|
||||
- [DB-GPT-Plugins](https://github.com/csunny/DB-GPT-Plugins) DB-GPT 插件仓库, 兼容Auto-GPT
|
||||
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 232 KiB After Width: | Height: | Size: 686 KiB |
BIN
assets/DB-GPT_zh.png
Normal file
BIN
assets/DB-GPT_zh.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 684 KiB |
BIN
assets/RAG-IN-ACTION.jpg
Normal file
BIN
assets/RAG-IN-ACTION.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 1.1 MiB |
@ -1,7 +1,7 @@
|
||||
LLM USE FAQ
|
||||
==================================
|
||||
##### Q1:how to use openai chatgpt service
|
||||
change your LLM_MODEL
|
||||
change your LLM_MODEL in `.env`
|
||||
````shell
|
||||
LLM_MODEL=proxyllm
|
||||
````
|
||||
@ -16,7 +16,6 @@ PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions
|
||||
make sure your openapi API_KEY is available
|
||||
|
||||
##### Q2 What difference between `python dbgpt_server --light` and `python dbgpt_server`
|
||||
|
||||
```{note}
|
||||
* `python dbgpt_server --light` dbgpt_server does not start the llm service. Users can deploy the llm service separately by using `python llmserver`, and dbgpt_server accesses the llm service through set the LLM_SERVER environment variable in .env. The purpose is to allow for the separate deployment of dbgpt's backend service and llm service.
|
||||
|
||||
@ -24,7 +23,19 @@ make sure your openapi API_KEY is available
|
||||
|
||||
```
|
||||
|
||||
##### Q3 how to use MultiGPUs
|
||||
```{tip}
|
||||
If you want to access an external LLM service(deployed by DB-GPT), you need to
|
||||
|
||||
1.set the variables LLM_MODEL=YOUR_MODEL_NAME, MODEL_SERVER=YOUR_MODEL_SERVER（eg:http://localhost:5000） in the .env file.
|
||||
|
||||
2.execute dbgpt_server.py in light mode
|
||||
|
||||
python pilot/server/dbgpt_server.py --light
|
||||
|
||||
```
|
||||
|
||||
|
||||
##### Q3 How to use MultiGPUs
|
||||
|
||||
DB-GPT will use all available gpu by default. And you can modify the setting `CUDA_VISIBLE_DEVICES=0,1` in `.env` file
|
||||
to use the specific gpu IDs.
|
||||
|
||||
@ -60,12 +60,8 @@ For the entire installation process of DB-GPT, we use the miniconda3 virtual env
|
||||
python>=3.10
|
||||
conda create -n dbgpt_env python=3.10
|
||||
conda activate dbgpt_env
|
||||
# it will take some minutes
|
||||
pip install -e ".[default]"
|
||||
```
|
||||
Before use DB-GPT Knowledge
|
||||
```bash
|
||||
python -m spacy download zh_core_web_sm
|
||||
|
||||
```
|
||||
|
||||
Once the environment is installed, we have to create a new folder "models" in the DB-GPT project, and then we can put all the models downloaded from huggingface in this directory
|
||||
@ -78,26 +74,34 @@ centos:yum install git-lfs
|
||||
ubuntu:apt-get install git-lfs
|
||||
|
||||
macos:brew install git-lfs
|
||||
```
|
||||
##### Download LLM Model and Embedding Model
|
||||
|
||||
If you use OpenAI llm service, see [LLM Use FAQ](https://db-gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)
|
||||
|
||||
```{tip}
|
||||
If you use openai or Axzure or tongyi llm api service, you don't need to download llm model.
|
||||
|
||||
```
|
||||
|
||||
```bash
|
||||
cd DB-GPT
|
||||
mkdir models and cd models
|
||||
#### llm model
|
||||
git clone https://huggingface.co/lmsys/vicuna-13b-v1.5
|
||||
or
|
||||
git clone https://huggingface.co/THUDM/chatglm2-6b
|
||||
|
||||
#### embedding model
|
||||
git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
|
||||
or
|
||||
git clone https://huggingface.co/moka-ai/m3e-large
|
||||
|
||||
#### llm model, if you use openai or Azure or tongyi llm api service, you don't need to download llm model
|
||||
git clone https://huggingface.co/lmsys/vicuna-13b-v1.5
|
||||
or
|
||||
git clone https://huggingface.co/THUDM/chatglm2-6b
|
||||
|
||||
```
|
||||
|
||||
The model files are large and will take a long time to download. During the download, let's configure the .env file, which needs to be copied and created from the .env.template
|
||||
|
||||
if you want to use openai llm service, see [LLM Use FAQ](https://db-gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)
|
||||
|
||||
```{tip}
|
||||
cp .env.template .env
|
||||
```
|
||||
@ -108,7 +112,7 @@ You can configure basic parameters in the .env file, for example setting LLM_MOD
|
||||
|
||||
### 3. Run
|
||||
|
||||
**(Optional) load examples into SQLlite**
|
||||
**(Optional) load examples into SQLite**
|
||||
```bash
|
||||
bash ./scripts/examples/load_examples.sh
|
||||
```
|
||||
@ -118,7 +122,7 @@ On windows platform:
|
||||
.\scripts\examples\load_examples.bat
|
||||
```
|
||||
|
||||
1.Run db-gpt server
|
||||
Run db-gpt server
|
||||
|
||||
```bash
|
||||
python pilot/server/dbgpt_server.py
|
||||
@ -126,19 +130,6 @@ python pilot/server/dbgpt_server.py
|
||||
|
||||
Open http://localhost:5000 with your browser to see the product.
|
||||
|
||||
```{tip}
|
||||
If you want to access an external LLM service, you need to
|
||||
|
||||
1.set the variables LLM_MODEL=YOUR_MODEL_NAME, MODEL_SERVER=YOUR_MODEL_SERVER（eg:http://localhost:5000） in the .env file.
|
||||
|
||||
2.execute dbgpt_server.py in light mode
|
||||
```
|
||||
|
||||
If you want to learn about dbgpt-webui, read https://github./csunny/DB-GPT/tree/new-page-framework/datacenter
|
||||
|
||||
```bash
|
||||
python pilot/server/dbgpt_server.py --light
|
||||
```
|
||||
|
||||
### Multiple GPUs
|
||||
|
||||
|
||||
@ -8,7 +8,7 @@ msgid ""
|
||||
msgstr ""
|
||||
"Project-Id-Version: DB-GPT 👏👏 0.3.5\n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2023-09-25 20:58+0800\n"
|
||||
"POT-Creation-Date: 2023-10-20 22:29+0800\n"
|
||||
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
|
||||
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
|
||||
"Language: zh_CN\n"
|
||||
@ -19,33 +19,34 @@ msgstr ""
|
||||
"Content-Transfer-Encoding: 8bit\n"
|
||||
"Generated-By: Babel 2.12.1\n"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:1 0d4fc79dbfce4f968ab310de12d69f3b
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:1 54763acec7da4deb90669195c54ec3a1
|
||||
msgid "LLM USE FAQ"
|
||||
msgstr "LLM模型使用FAQ"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:3 08873df3ef2741dca8916c4c0d503b4f
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:3 66f73fd2ee7b462e92d3f263792a5e33
|
||||
msgid "Q1:how to use openai chatgpt service"
|
||||
msgstr "我怎么使用OPENAI服务"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:4 7741b098acd347659ccf663b5323666c
|
||||
msgid "change your LLM_MODEL"
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:4 9d178d8462b74cb188bbacf2ac2ac12b
|
||||
#, fuzzy
|
||||
msgid "change your LLM_MODEL in `.env`"
|
||||
msgstr "通过在.env文件设置LLM_MODEL"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:9 018115ec074c48739b730310a8bafa44
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:9 f7ca82f257be4ac09639a7f8af5e83eb
|
||||
msgid "set your OPENAPI KEY"
|
||||
msgstr "set your OPENAPI KEY"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:16 42408d9c11994a848da41c3ab87d7a78
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:16 d6255b20dce34a2690df7e2af3505d97
|
||||
msgid "make sure your openapi API_KEY is available"
|
||||
msgstr "确认openapi API_KEY是否可用"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:18 d9aedc07578d4562bad0ba1f130651de
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:18 6f1c6dbdb31f4210a6d21f0f3a6ae589
|
||||
msgid ""
|
||||
"Q2 What difference between `python dbgpt_server --light` and `python "
|
||||
"dbgpt_server`"
|
||||
msgstr "Q2 `python dbgpt_server --light` 和 `python dbgpt_server`的区别是什么?"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:21 03c03fedaa2f4bfdaefb42fd4164c902
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:20 b839771ae9e34e998b0edf8d69deabdd
|
||||
msgid ""
|
||||
"`python dbgpt_server --light` dbgpt_server does not start the llm "
|
||||
"service. Users can deploy the llm service separately by using `python "
|
||||
@ -57,54 +58,75 @@ msgstr ""
|
||||
"用户可以通过`python "
|
||||
"llmserver`单独部署模型服务，dbgpt_server通过LLM_SERVER环境变量来访问模型服务。目的是为了可以将dbgpt后台服务和大模型服务分离部署。"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:23 61354a0859284346adc3e07c820aa61a
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:22 aba39cef6fe84799bcd03e8f36c41296
|
||||
msgid ""
|
||||
"`python dbgpt_server` dbgpt_server service and the llm service are "
|
||||
"deployed on the same instance. when dbgpt_server starts the service, it "
|
||||
"also starts the llm service at the same time."
|
||||
msgstr "`python dbgpt_server` 是将后台服务和模型服务部署在同一台实例上.dbgpt_server在启动服务的时候同时开启模型服务."
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:27 41ee95bf0b224be995f7530d0b67f712
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:27 c65270d479af49e28e99b35a7932adbd
|
||||
msgid ""
|
||||
"If you want to access an external LLM service(deployed by DB-GPT), you "
|
||||
"need to"
|
||||
msgstr "如果模型服务部署(通过DB-GPT部署)在别的机器，想通过dbgpt服务访问模型服务"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:29 da153e6d18c543f28e0c4e85618e3d3d
|
||||
msgid ""
|
||||
"1.set the variables LLM_MODEL=YOUR_MODEL_NAME, "
|
||||
"MODEL_SERVER=YOUR_MODEL_SERVER（eg:http://localhost:5000） in the .env "
|
||||
"file."
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:31 cd89b8a2075f4407b8036a74151a6377
|
||||
msgid "2.execute dbgpt_server.py in light mode"
|
||||
msgstr "2.execute dbgpt_server.py light 模式"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:33 8f4b9401ac4f4a25a7479bee9ef5e8c1
|
||||
msgid "python pilot/server/dbgpt_server.py --light"
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:38 69e1064cd7554ce6b49da732f800eacc
|
||||
#, fuzzy
|
||||
msgid "Q3 how to use MultiGPUs"
|
||||
msgid "Q3 How to use MultiGPUs"
|
||||
msgstr "Q2 怎么使用 MultiGPUs"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:29 7fce22f0327646399b98b0e20574a2fd
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:40 6de3f105ce96430db5756f38bbd9ca12
|
||||
msgid ""
|
||||
"DB-GPT will use all available gpu by default. And you can modify the "
|
||||
"setting `CUDA_VISIBLE_DEVICES=0,1` in `.env` file to use the specific gpu"
|
||||
" IDs."
|
||||
msgstr "DB-GPT默认加载可利用的gpu，你也可以通过修改 在`.env`文件 `CUDA_VISIBLE_DEVICES=0,1`来指定gpu IDs"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:32 3f4eb824dc924d7ca309dc5057f8360a
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:43 87cb9bfb20af4b259d719df797c42a7d
|
||||
msgid ""
|
||||
"Optionally, you can also specify the gpu ID to use before the starting "
|
||||
"command, as shown below:"
|
||||
msgstr "你也可以指定gpu ID启动"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:42 a77d72f91b864d0aac344b317c100950
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:53 bcfa35cda6304ee5ab9a775a2d4eda63
|
||||
msgid ""
|
||||
"You can modify the setting `MAX_GPU_MEMORY=xxGib` in `.env` file to "
|
||||
"configure the maximum memory used by each GPU."
|
||||
msgstr "同时你可以通过在.env文件设置`MAX_GPU_MEMORY=xxGib`修改每个GPU的最大使用内存"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:44 b3bb92777a1244d5967a4308d14722fc
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:55 a05c5484927844c8bb4791f0a9ccc82e
|
||||
#, fuzzy
|
||||
msgid "Q4 Not Enough Memory"
|
||||
msgstr "Q3 机器显存不够 "
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:46 c3976d81aafa4c6081e37c0d0a115d96
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:57 fe17a023b6eb4a92b1b927e1b94e3784
|
||||
msgid "DB-GPT supported 8-bit quantization and 4-bit quantization."
|
||||
msgstr "DB-GPT 支持 8-bit quantization 和 4-bit quantization."
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:48 93ade142f949449d8f54c0b6d8c8d261
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:59 76c3684c10864b8e87e5c2255b6c0b7f
|
||||
msgid ""
|
||||
"You can modify the setting `QUANTIZE_8bit=True` or `QUANTIZE_4bit=True` "
|
||||
"in `.env` file to use quantization(8-bit quantization is enabled by "
|
||||
"default)."
|
||||
msgstr "你可以通过在.env文件设置`QUANTIZE_8bit=True` or `QUANTIZE_4bit=True`"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:50 be2573907d624ebf8c901301f938577b
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:61 c5d849a38f1a4f0687bbcffb6699dc39
|
||||
msgid ""
|
||||
"Llama-2-70b with 8-bit quantization can run with 80 GB of VRAM, and 4-bit"
|
||||
" quantization can run with 48 GB of VRAM."
|
||||
@ -112,45 +134,45 @@ msgstr ""
|
||||
"Llama-2-70b with 8-bit quantization 可以运行在 80 GB VRAM机器， 4-bit "
|
||||
"quantization可以运行在 48 GB VRAM"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:52 c084d4624e794f7e8ceebadb6f260b49
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:63 867329a5e3b0403083e96f72b8747fb2
|
||||
msgid ""
|
||||
"Note: you need to install the latest dependencies according to "
|
||||
"[requirements.txt](https://github.com/eosphoros-ai/DB-"
|
||||
"GPT/blob/main/requirements.txt)."
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:54 559bcd62af7340f79f5eca817187e13e
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:65 60ceee25e9fb4ddba40c5306bfb0a82f
|
||||
#, fuzzy
|
||||
msgid "Q5 How to Add LLM Service dynamic local mode"
|
||||
msgstr "Q5 怎样动态新增模型服务"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:56 e47101d7d47e486e8572f6acd609fa92
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:67 c99eb7f7ae844884a8f0da94238ea7e0
|
||||
msgid ""
|
||||
"Now DB-GPT through multi-llm service switch, so how to add llm service "
|
||||
"dynamic,"
|
||||
msgstr "DB-GPT支持多个模型服务切换, 怎样添加一个模型服务呢"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:67 5710dd9bf8f54bd388354079b29acdd2
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:78 cd89b8a2075f4407b8036a74151a6377
|
||||
#, fuzzy
|
||||
msgid "Q6 How to Add LLM Service dynamic in remote mode"
|
||||
msgstr "Q5 怎样动态新增模型服务"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:68 9c9311d6daad402a8e0748f00e69e8cf
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:79 8833ce89465848259b08ef0a4fa68d96
|
||||
msgid ""
|
||||
"If you deploy llm service in remote machine instance, and you want to "
|
||||
"add model service to dbgpt server to manage"
|
||||
msgstr "如果你想在远程机器实例部署大模型服务并添加到本地dbgpt_server进行管理"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:70 3ec1565e74384beab23df9d8d4a19a39
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:81 992eb37e3cca48829636c15ba3ec2ee8
|
||||
msgid "use dbgpt start worker and set --controller_addr."
|
||||
msgstr "使用1`dbgpt start worker`命令并设置注册地址--controller_addr"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:80 e2b8a9119f7843beb787d021c973eea4
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:91 0d06d7d6dd3d4780894ecd914c89b5a2
|
||||
#, fuzzy
|
||||
msgid "Q7 dbgpt command not found"
|
||||
msgstr "Q6 dbgpt command not found"
|
||||
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:86 257ae9c462cd4a9abe7d2ff00f6bc891
|
||||
#: ../../getting_started/faq/llm/llm_faq.md:97 5d9beed0d95a4503a43d0e025664273b
|
||||
msgid ""
|
||||
"Q8 When starting the worker_manager on a cloud server and registering it "
|
||||
"with the controller, it is noticed that the worker's exposed IP is a "
|
||||
|
||||
@ -8,7 +8,7 @@ msgid ""
|
||||
msgstr ""
|
||||
"Project-Id-Version: DB-GPT 👏👏 0.3.5\n"
|
||||
"Report-Msgid-Bugs-To: \n"
|
||||
"POT-Creation-Date: 2023-10-17 14:35+0800\n"
|
||||
"POT-Creation-Date: 2023-10-20 22:29+0800\n"
|
||||
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
|
||||
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
|
||||
"Language: zh_CN\n"
|
||||
@ -20,47 +20,47 @@ msgstr ""
|
||||
"Generated-By: Babel 2.12.1\n"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:1
|
||||
#: 73f932b662564edba45fbd711fd19005
|
||||
#: 7bcf028ff0884ea88f25b7e2c9608153
|
||||
msgid "Installation From Source"
|
||||
msgstr "源码安装"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:3
|
||||
#: 70b623827a26447cb9382f1cb568b93c
|
||||
#: 61f0b1135c84423bbaeb5f9f0942ad7d
|
||||
msgid ""
|
||||
"This tutorial gives you a quick walkthrough about use DB-GPT with you "
|
||||
"environment and data."
|
||||
msgstr "本教程为您提供了关于如何使用DB-GPT的使用指南。"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:5
|
||||
#: 6102ada4b19a4062947ad0ee5305dad5
|
||||
#: d7622cd5f69f4a32b3c8e979c6b9f601
|
||||
msgid "Installation"
|
||||
msgstr "安装"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:7
|
||||
#: 7c006c0c72944049bba43fd95daf1bd1
|
||||
#: 4368072b6384496ebeaff3c09ca2f888
|
||||
msgid "To get started, install DB-GPT with the following steps."
|
||||
msgstr "请按照以下步骤安装DB-GPT"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:9
|
||||
#: eac8c7f921a042b79b4d0032c01b095a
|
||||
#: 0dfdf8ac6e314fe7b624a685d9beebd5
|
||||
msgid "1. Hardware Requirements"
|
||||
msgstr "1. 硬件要求"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:10
|
||||
#: 8c430e2db5ce41e8b9d22e6e13c62cb3
|
||||
#: cff920f8732f4f1da3063ec2bc099271
|
||||
msgid ""
|
||||
"DB-GPT can be deployed on servers with low hardware requirements or on "
|
||||
"servers with high hardware requirements."
|
||||
msgstr "DB-GPT可以部署在对硬件要求不高的服务器，也可以部署在对硬件要求高的服务器"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:12
|
||||
#: a6b042509e1149fa8213a014e42eaaae
|
||||
#: 8e3818824d6146c6b265731c277fbd0b
|
||||
#, fuzzy
|
||||
msgid "Low hardware requirements"
|
||||
msgstr "1. 硬件要求"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:13
|
||||
#: 577c8c4edc2e4f45963b2a668385852f
|
||||
#: ca95d66526994173ac1fea20bdea5d67
|
||||
msgid ""
|
||||
"The low hardware requirements mode is suitable for integrating with "
|
||||
"third-party LLM services' APIs, such as OpenAI, Tongyi, Wenxin, or "
|
||||
@ -68,23 +68,23 @@ msgid ""
|
||||
msgstr "Low hardware requirements模式适用于对接第三方模型服务的api,比如OpenAI, 通义千问, 文心.cpp。"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:15
|
||||
#: 384475d3a87043eb9eebc384052ac9cc
|
||||
#: 83fc53cc1b4248139f69f490b859ad8d
|
||||
msgid "DB-GPT provides set proxy api to support LLM api."
|
||||
msgstr "DB-GPT可以通过设置proxy api来支持第三方大模型服务"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:17
|
||||
#: e5bd8a999adb4e07b8b5221f1893251d
|
||||
#: 418a9f24eafc4571b74d86c3f1e57a2d
|
||||
msgid "As our project has the ability to achieve ChatGPT performance of over 85%,"
|
||||
msgstr "由于我们的项目有能力达到85%以上的ChatGPT性能"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:19
|
||||
#: 6a97ed5893414e17bb9c1f8bb21bc965
|
||||
#: 6f85149ab0024cc99e43804206a595ed
|
||||
#, fuzzy
|
||||
msgid "High hardware requirements"
|
||||
msgstr "1. 硬件要求"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:20
|
||||
#: d0c248939b4143a2b01afd051b02ec12
|
||||
#: 31635ffff5084814a14deb3220dd2c17
|
||||
#, fuzzy
|
||||
msgid ""
|
||||
"The high hardware requirements mode is suitable for independently "
|
||||
@ -93,70 +93,72 @@ msgid ""
|
||||
"requirements. However, overall, the project can be deployed and used on "
|
||||
"consumer-grade graphics cards. The specific hardware requirements for "
|
||||
"deployment are as follows:"
|
||||
msgstr "High hardware requirements模式适用于需要独立部署私有大模型服务，比如Llama系列模型，Baichuan, chatglm，vicuna等私有大模型所以对硬件有一定的要求。但总体来说，我们在消费级的显卡上即可完成项目的部署使用，具体部署的硬件说明如下:"
|
||||
msgstr ""
|
||||
"High hardware requirements模式适用于需要独立部署私有大模型服务，比如Llama系列模型，Baichuan, "
|
||||
"chatglm，vicuna等私有大模型所以对硬件有一定的要求。但总体来说，我们在消费级的显卡上即可完成项目的部署使用，具体部署的硬件说明如下:"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 2ee432394f6b4d9cb0a424f4b99bf3be
|
||||
#: d806b90be1614ad3b2e06c92f4b17e5c
|
||||
msgid "GPU"
|
||||
msgstr "GPU"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 4cd716486f994080880f84853b047a5d
|
||||
#: 4b02f41145484389ace0b547384ac269 bbba2ff3fab94482a1761264264deef9
|
||||
msgid "VRAM Size"
|
||||
msgstr "显存"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: d1b33d0348894bfc8a843a3d38c6daaa
|
||||
#: 0ea63c2dcc0e43858a61e01d59ad09f9
|
||||
msgid "Performance"
|
||||
msgstr "Performance"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: d5850bbe7d0a430d993b7e6bd1f24bff
|
||||
#: 6521683eb91e450c928a72688550a63d
|
||||
msgid "RTX 4090"
|
||||
msgstr "RTX 4090"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: c7d15be08ac74624bbfb5eb4554fc7ff
|
||||
#: bb6340c9cdc048fbb0ed55defc1aaeb6 d991b39845ee404198e1a1e35cc416f3
|
||||
msgid "24 GB"
|
||||
msgstr "24 GB"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 219dff2fee83460da55d9d628569365e
|
||||
#: 4134d3a89d364e33b2bdf1c7667e4755
|
||||
msgid "Smooth conversation inference"
|
||||
msgstr "丝滑的对话体验"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 56025c5f37984963943de7accea85850
|
||||
#: 096ff425ac7646a990a7133961c6e6af
|
||||
msgid "RTX 3090"
|
||||
msgstr "RTX 3090"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 8a0b8a0afa0c4cc39eb7c2271775cf60
|
||||
#: ecf670cdbec3493f804e6a785a83c608
|
||||
msgid "Smooth conversation inference, better than V100"
|
||||
msgstr "丝滑的对话体验，性能好于V100"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 2fc5e6ac8a6b4c508944c659adffa0c1
|
||||
#: 837b14e0a3d243bda0df7ab35b70b7e7
|
||||
msgid "V100"
|
||||
msgstr "V100"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: f92a1393539a49db983b06f7276f446b
|
||||
#: 3b20a087c8e342c89ccb807ffc3817c2 b8b6b45253084436a5893896b35a2bd5
|
||||
msgid "16 GB"
|
||||
msgstr "16 GB"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 4e7de52a58d24a0bb10e45e1435128a6
|
||||
#: 772e18bb0ace4f7ea68b51bfc05816ce 9351389a1fac479cbe67b1f8c2c37de5
|
||||
msgid "Conversation inference possible, noticeable stutter"
|
||||
msgstr "Conversation inference possible, noticeable stutter"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 217fe55f590a497ba6622698945e7be8
|
||||
#: aadb62bf48bb49d99a714bcdf3092260
|
||||
msgid "T4"
|
||||
msgstr "T4"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:30
|
||||
#: 30ca67fe27f64df093a2d281e1288c5c
|
||||
#: 4de80d9fcf34470bae806d829836b7d7
|
||||
#, fuzzy
|
||||
msgid ""
|
||||
"If your VRAM Size is not enough, DB-GPT supported 8-bit quantization and "
|
||||
@ -164,105 +166,109 @@ msgid ""
|
||||
msgstr "如果你的显存不够，DB-GPT支持8-bit和4-bit量化版本"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:32
|
||||
#: fc0c3a0730d64e9e98d1b25f4dd5db34
|
||||
#: 00d81cbf48b549f3b9128d3840d01b2e
|
||||
msgid ""
|
||||
"Here are some of the VRAM size usage of the models we tested in some "
|
||||
"common scenarios."
|
||||
msgstr "这里是量化版本的相关说明"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 1f1f6c10209b446f99d520fdb68e0f5d
|
||||
#: dc346f2bca794bb7ae34b330e82ccbcf
|
||||
msgid "Model"
|
||||
msgstr "Model"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 18e3240d407e41f88028b24aeced1bf4
|
||||
#: 8de6cd40de78460ba774650466f8df26
|
||||
msgid "Quantize"
|
||||
msgstr "Quantize"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 03aa79d3c3f54e3c834180b0d1ed9a5c
|
||||
#: 3e412b8f4852482ab07a0f546e37ae7f f30054e0558b41a192cc9a2462b299ec
|
||||
msgid "vicuna-7b-v1.5"
|
||||
msgstr "vicuna-7b-v1.5"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 09419ad0a88c4179979505ef71204fd6 1b4ab0186184493d895eeec12d078c52
|
||||
#: 6acec7b76e604343885aa71d92b04d1e 9b73ca1c18d14972b894db69438e3fb2
|
||||
#: b869995505ae4895b9f13e271470e5cb c9eaf983eeb2486da08e628728ae301f
|
||||
#: ff0a86dc63ce4cd580f354d15d333501
|
||||
#: 14358fa40cf94614acf39a803987631f 2a3f52b26b444783be04ffa795246a03
|
||||
#: 3956734b19aa44c3be08d56348b47a38 751034ca7d00447895fda1d9b8a7364f
|
||||
#: a66d16e5424a42a3a1309dfb8ffc33f9 b8ebce0a9e7e481da5f16214f955665d
|
||||
#: f533b3f37e6f4594aec5e0f59f241683
|
||||
msgid "4-bit"
|
||||
msgstr "4-bit"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: d0d959f022f44bbeb34d67ccf49ba3bd
|
||||
#: 9eac7e866ebe45169c64a952c363ce43 aa56722db3014abd9022067ed5fc4f98
|
||||
#: af4df898fb47471fbb487fcf6e2d40d6
|
||||
msgid "8 GB"
|
||||
msgstr "8 GB"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 01cb7be0064940e8a637df7ed8e15310 13568d8a793b4c2db655f89dc690929a
|
||||
#: 28ce31711f91455b9b910276fa059c65 2dddf2e87a70452fb27a627d62464346
|
||||
#: 3f3f4dc00acb43258dce311f144e0fd7 5aa76fd2fb35474e8d06795e7369ceb4
|
||||
#: d660be499efc4b6ca61da0d5af758620
|
||||
#: 211aaf2e234d46108b5eee5006d5f4bb 40214b2f71ce452db3501ea9d81a0c8a
|
||||
#: 72fcd5e0634e48d79813f1037e6acb45 7756b67568cc40c4b73079b26e79c85d
|
||||
#: 8c21f8e90154407682c093a46b93939d ad937c14bbcd41ac92a3dbbdb8339eed
|
||||
#: d1e7ee217dd64b15b934456c3a72c450
|
||||
msgid "8-bit"
|
||||
msgstr "8-bit"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 3b963a1ce6934229ba7658cb407b6a52
|
||||
#: 4812504dfb9a4b25a5db773d9a08f34f 76ae2407ba4e4013953b9f243d9a5d92
|
||||
#: 927054919de047fd8a83df67e1400622 9773e73eb89847f8a85a2dc55b562916
|
||||
#: ce33d0c3792f43398fc7e2694653d8fc d3dc0d4cceb24d2b9dc5c7120fbed94e
|
||||
msgid "12 GB"
|
||||
msgstr "12 GB"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 30d28dcaa64545198aaa20fe4562bb6d
|
||||
#: 83e6d6ba1aa74946858f0162424752ab b6b99caeaeff44c488e3e819ed337074
|
||||
msgid "vicuna-13b-v1.5"
|
||||
msgstr "vicuna-13b-v1.5"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 28de25a1952049d2b7aff41020e428ff
|
||||
#: 492c5f0d560946fe879f6c339975ba37 970063dda21e4dd8be6f89a3c87832a5
|
||||
#: a66bad6054b24dd99b370312bc8b6fa6
|
||||
msgid "20 GB"
|
||||
msgstr "20 GB"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 535974c886b14c618ca84de1fe63d5e4
|
||||
#: a75f3405085441d8920db49f159588d2 cf635931c55846aea4cbccd92e4f0377
|
||||
msgid "llama-2-7b"
|
||||
msgstr "llama-2-7b"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: cc04760a8b9e4a79a7dada9a11abda2c
|
||||
#: 61d632df8c5149b393d03ac802141125 bc98c895d457495ea26e3537de83b432
|
||||
msgid "llama-2-13b"
|
||||
msgstr "llama-2-13b"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 9e83d8d5ae44411dba4cc6c2d796b20f
|
||||
#: 3ccb1f6d8a924aeeacb5373edc168103 9ecce68e159a4649a8d5e69157af17a1
|
||||
msgid "llama-2-70b"
|
||||
msgstr "llama-2-70b"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: cb6ce389adfc463a9c851eb1e4abfcff
|
||||
#: ca1da6ce08674b3daa0ab9ee0330203f
|
||||
msgid "48 GB"
|
||||
msgstr "48 GB"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 906d664156084223a4efa0ae9804bd33
|
||||
#: 34d4d20e57c1410fbdcabd09a5968cdd
|
||||
msgid "80 GB"
|
||||
msgstr "80 GB"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 957fb0c6f3114a63ba33a1cfb31060e3
|
||||
#: 4ec2213171054c96ac9cd46e259ce7bf 68a1752f76a54287a73e82724723ea75
|
||||
msgid "baichuan-7b"
|
||||
msgstr "baichuan-7b"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md
|
||||
#: 5f3bc4cf57d946cfb38a941250685151
|
||||
#: 103b020a575744ad964c60a367aa1651 c659a720a1024869b09d7cc161bcd8a2
|
||||
msgid "baichuan-13b"
|
||||
msgstr "baichuan-13b"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:51
|
||||
#: 87ae8c58df314b69ae119aa831cb7dd5
|
||||
#: 2259a008d0e14f9e8d1e1d9234b97298
|
||||
msgid "2. Install"
|
||||
msgstr "2. Install"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:56
|
||||
#: 79cdebf089614761bf4299a9ce601b81
|
||||
#: 875c7d8e32574552a48199577c78ccdd
|
||||
msgid ""
|
||||
"We use Sqlite as default database, so there is no need for database "
|
||||
"installation. If you choose to connect to other databases, you can "
|
||||
@ -276,70 +282,78 @@ msgstr ""
|
||||
"GPT快速部署不需要部署相关数据库服务。如果你想使用其他数据库，需要先部署相关数据库服务。我们目前使用Miniconda进行python环境和包依赖管理[安装"
|
||||
" Miniconda](https://docs.conda.io/en/latest/miniconda.html)"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:65
|
||||
#: 03ff2f444721454588095bb348220276
|
||||
msgid "Before use DB-GPT Knowledge"
|
||||
msgstr "在使用知识库之前"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:71
|
||||
#: b6faa4d078a046d6a7c0313e8deef0f3
|
||||
#: ../../getting_started/install/deploy/deploy.md:67
|
||||
#: c03e3290e1144320a138d015171ac596
|
||||
msgid ""
|
||||
"Once the environment is installed, we have to create a new folder "
|
||||
"\"models\" in the DB-GPT project, and then we can put all the models "
|
||||
"downloaded from huggingface in this directory"
|
||||
msgstr "如果你已经安装好了环境需要创建models, 然后到huggingface官网下载模型"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:74
|
||||
#: f43fd2b74d994bf6bb4016e88c43d51a
|
||||
#: ../../getting_started/install/deploy/deploy.md:70
|
||||
#: 933401ac909741ada4acf6bcd4142ed6
|
||||
msgid "Notice make sure you have install git-lfs"
|
||||
msgstr ""
|
||||
msgstr "注意确认你已经安装了git-lfs"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:76
|
||||
#: f558a7ee728a4344af576aa375b43092
|
||||
#: ../../getting_started/install/deploy/deploy.md:72
|
||||
#: e8e4886a83dd402c85fe3fa989322991
|
||||
msgid "centos:yum install git-lfs"
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:78
|
||||
#: bab08604a3ba45b9b827ff5a4b931601
|
||||
#: ../../getting_started/install/deploy/deploy.md:74
|
||||
#: 5ead7e98bddf4fa4845c3d3955f18054
|
||||
msgid "ubuntu:apt-get install git-lfs"
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:80
|
||||
#: b4a107e5f8524acc9aed74318880f9f3
|
||||
#: ../../getting_started/install/deploy/deploy.md:76
|
||||
#: 08acfaaaa2544182a59df54cdf61cd84
|
||||
msgid "macos:brew install git-lfs"
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:97
|
||||
#: ecb5fa1f18154685bb4336d04ac3a386
|
||||
#: ../../getting_started/install/deploy/deploy.md:78
|
||||
#: 312ad44170c34531865576067c58701a
|
||||
msgid "Download LLM Model and Embedding Model"
|
||||
msgstr "下载LLM模型和Embedding模型"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:80
|
||||
#: de54793643434528a417011d2919b2c4
|
||||
#, fuzzy
|
||||
msgid ""
|
||||
"If you use OpenAI llm service, see [LLM Use FAQ](https://db-"
|
||||
"gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)"
|
||||
msgstr ""
|
||||
"如果想使用openai大模型服务, 可以参考[LLM Use FAQ](https://db-"
|
||||
"gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:83
|
||||
#: 50ec1eb7c56a46ac8fbf911c7adc9b0e
|
||||
msgid ""
|
||||
"If you use openai or Azure or tongyi llm api service, you don't need to "
|
||||
"download llm model."
|
||||
msgstr "如果你想通过openai or Azure or tongyi第三方api访问模型服务，你可以不用下载llm模型"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:103
|
||||
#: 03950b2a480149388fb7b88f7d251ef5
|
||||
msgid ""
|
||||
"The model files are large and will take a long time to download. During "
|
||||
"the download, let's configure the .env file, which needs to be copied and"
|
||||
" created from the .env.template"
|
||||
msgstr "模型文件很大，需要很长时间才能下载。在下载过程中，让我们配置.env文件，它需要从。env.template中复制和创建。"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:99
|
||||
#: 0f08b0ecbea14cbdba29ea8d87cf24b4
|
||||
msgid ""
|
||||
"if you want to use openai llm service, see [LLM Use FAQ](https://db-"
|
||||
"gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)"
|
||||
msgstr ""
|
||||
"如果想使用openai大模型服务, 可以参考[LLM Use FAQ](https://db-"
|
||||
"gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:102
|
||||
#: 6efb9a45ab2c45c7b4770f987b639c52
|
||||
#: ../../getting_started/install/deploy/deploy.md:106
|
||||
#: 441c4333216a402a84fd52f8e56fc81b
|
||||
msgid "cp .env.template .env"
|
||||
msgstr "cp .env.template .env"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:105
|
||||
#: b9d2b81a2cf440c3b49a5c06759eb2ba
|
||||
#: ../../getting_started/install/deploy/deploy.md:109
|
||||
#: 4eac3d98df6a4e788234ff0ec1ffd03e
|
||||
msgid ""
|
||||
"You can configure basic parameters in the .env file, for example setting "
|
||||
"LLM_MODEL to the model to be used"
|
||||
msgstr "您可以在.env文件中配置基本参数，例如将LLM_MODEL设置为要使用的模型。"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:107
|
||||
#: 2f6afa40ca994115b16ba28baaf65bde
|
||||
#: ../../getting_started/install/deploy/deploy.md:111
|
||||
#: a36bd6d6236b4c74b161a935ae792b91
|
||||
msgid ""
|
||||
"([Vicuna-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5) based on "
|
||||
"llama-2 has been released, we recommend you set `LLM_MODEL=vicuna-"
|
||||
@ -349,107 +363,81 @@ msgstr ""
|
||||
"/vicuna-13b-v1.5)， "
|
||||
"目前Vicuna-v1.5模型(基于llama2)已经开源了，我们推荐你使用这个模型通过设置LLM_MODEL=vicuna-13b-v1.5"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:109
|
||||
#: 7c5883f9594646198f464e6dafb2f0ff
|
||||
#: ../../getting_started/install/deploy/deploy.md:113
|
||||
#: 78334cbf0c364eb3bc41a2a6c55ebb0d
|
||||
msgid "3. Run"
|
||||
msgstr "3. Run"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:111
|
||||
#: 0e3719a238eb4332b7c15efa3f16e3e2
|
||||
msgid "**(Optional) load examples into SQLlite**"
|
||||
#: ../../getting_started/install/deploy/deploy.md:115
|
||||
#: 6d5ad6eb067d4e9fa1c574b7b706233f
|
||||
msgid "**(Optional) load examples into SQLite**"
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:116
|
||||
#: c901055131ce4688b1c602393913b675
|
||||
#: ../../getting_started/install/deploy/deploy.md:120
|
||||
#: 07219a4ed3c44e349314ae04ebdf58e1
|
||||
msgid "On windows platform:"
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:121
|
||||
#: 777a50f9167c4b8f9c2a96682ccc4c4a
|
||||
msgid "1.Run db-gpt server"
|
||||
#: ../../getting_started/install/deploy/deploy.md:125
|
||||
#: 819be2bb22044440ae00c2e7687ea249
|
||||
#, fuzzy
|
||||
msgid "Run db-gpt server"
|
||||
msgstr "1.Run db-gpt server"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:127
|
||||
#: 62aafb652df8478281ab633d8d082e7f
|
||||
#: ../../getting_started/install/deploy/deploy.md:131
|
||||
#: 5ba6d7c9bf9146c797036ab4b9b4f59e
|
||||
msgid "Open http://localhost:5000 with your browser to see the product."
|
||||
msgstr "打开浏览器访问http://localhost:5000"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:130
|
||||
#: cff18fc20ffd4716bc7cf377730dd5ec
|
||||
msgid "If you want to access an external LLM service, you need to"
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:132
|
||||
#: f27c3aa9e627480a96cd04fcd4bfdaec
|
||||
msgid ""
|
||||
"1.set the variables LLM_MODEL=YOUR_MODEL_NAME, "
|
||||
"MODEL_SERVER=YOUR_MODEL_SERVER（eg:http://localhost:5000） in the .env "
|
||||
"file."
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:134
|
||||
#: e05a395f67924514929cd025fab67e44
|
||||
msgid "2.execute dbgpt_server.py in light mode"
|
||||
msgstr ""
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:137
|
||||
#: a5d7fcb46ba446bf9913646b28b036ed
|
||||
msgid ""
|
||||
"If you want to learn about dbgpt-webui, read https://github./csunny/DB-"
|
||||
"GPT/tree/new-page-framework/datacenter"
|
||||
msgstr ""
|
||||
"如果你想了解web-ui, 请访问https://github./csunny/DB-GPT/tree/new-page-"
|
||||
"framework/datacenter"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:143
|
||||
#: 90c614e7744c4a7f843adb8968b58c78
|
||||
#: be3a2729ef3b4742a403017b31bda7e3
|
||||
#, fuzzy
|
||||
msgid "Multiple GPUs"
|
||||
msgstr "4. Multiple GPUs"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:145
|
||||
#: 7b72e7cbd9d246299de5986772df4825
|
||||
#: ../../getting_started/install/deploy/deploy.md:136
|
||||
#: 00ffa1cc145e4afa830c592a629246f9
|
||||
msgid ""
|
||||
"DB-GPT will use all available gpu by default. And you can modify the "
|
||||
"setting `CUDA_VISIBLE_DEVICES=0,1` in `.env` file to use the specific gpu"
|
||||
" IDs."
|
||||
msgstr "DB-GPT默认加载可利用的gpu，你也可以通过修改 在`.env`文件 `CUDA_VISIBLE_DEVICES=0,1`来指定gpu IDs"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:147
|
||||
#: b7e2f7bbf625464489b3fd9aedb0ed59
|
||||
#: ../../getting_started/install/deploy/deploy.md:138
|
||||
#: bde32a5a8fea4350868be579e9ee6baa
|
||||
msgid ""
|
||||
"Optionally, you can also specify the gpu ID to use before the starting "
|
||||
"command, as shown below:"
|
||||
msgstr "你也可以指定gpu ID启动"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:157
|
||||
#: 69fd2183a143428fb77949f58381d455
|
||||
#: ../../getting_started/install/deploy/deploy.md:148
|
||||
#: 791ed2db2cff44c48342a7828cbd4c45
|
||||
msgid ""
|
||||
"You can modify the setting `MAX_GPU_MEMORY=xxGib` in `.env` file to "
|
||||
"configure the maximum memory used by each GPU."
|
||||
msgstr "同时你可以通过在.env文件设置`MAX_GPU_MEMORY=xxGib`修改每个GPU的最大使用内存"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:159
|
||||
#: 6cd03b9728f943a4a632aa9b061931f0
|
||||
#: ../../getting_started/install/deploy/deploy.md:150
|
||||
#: f86b37c8943e4f5595610706e75b4add
|
||||
#, fuzzy
|
||||
msgid "Not Enough Memory"
|
||||
msgstr "5. Not Enough Memory"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:161
|
||||
#: 4837aba4c80b42819c1a6345de0aa820
|
||||
#: ../../getting_started/install/deploy/deploy.md:152
|
||||
#: 8a7bd02cbeca497aa8eecaaf1910a6ad
|
||||
msgid "DB-GPT supported 8-bit quantization and 4-bit quantization."
|
||||
msgstr "DB-GPT 支持 8-bit quantization 和 4-bit quantization."
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:163
|
||||
#: c1a701e9bc4c4439adfb930d0e953cec
|
||||
#: ../../getting_started/install/deploy/deploy.md:154
|
||||
#: 5ad49b99fe774ba79c50de0cd694807c
|
||||
msgid ""
|
||||
"You can modify the setting `QUANTIZE_8bit=True` or `QUANTIZE_4bit=True` "
|
||||
"in `.env` file to use quantization(8-bit quantization is enabled by "
|
||||
"default)."
|
||||
msgstr "你可以通过在.env文件设置`QUANTIZE_8bit=True` or `QUANTIZE_4bit=True`"
|
||||
|
||||
#: ../../getting_started/install/deploy/deploy.md:165
|
||||
#: 205c101f1f774130a5853dd9b7373d36
|
||||
#: ../../getting_started/install/deploy/deploy.md:156
|
||||
#: b9c80e92137447da91eb944443144c69
|
||||
msgid ""
|
||||
"Llama-2-70b with 8-bit quantization can run with 80 GB of VRAM, and 4-bit"
|
||||
" quantization can run with 48 GB of VRAM."
|
||||
@ -508,3 +496,29 @@ msgstr ""
|
||||
#~ msgid "ubuntu:app-get install git-lfs"
|
||||
#~ msgstr ""
|
||||
|
||||
#~ msgid "Before use DB-GPT Knowledge"
|
||||
#~ msgstr "在使用知识库之前"
|
||||
|
||||
#~ msgid "**(Optional) load examples into SQLlite**"
|
||||
#~ msgstr ""
|
||||
|
||||
#~ msgid "If you want to access an external LLM service, you need to"
|
||||
#~ msgstr ""
|
||||
|
||||
#~ msgid ""
|
||||
#~ "1.set the variables LLM_MODEL=YOUR_MODEL_NAME, "
|
||||
#~ "MODEL_SERVER=YOUR_MODEL_SERVER（eg:http://localhost:5000） in "
|
||||
#~ "the .env file."
|
||||
#~ msgstr ""
|
||||
|
||||
#~ msgid "2.execute dbgpt_server.py in light mode"
|
||||
#~ msgstr ""
|
||||
|
||||
#~ msgid ""
|
||||
#~ "If you want to learn about "
|
||||
#~ "dbgpt-webui, read https://github./csunny/DB-"
|
||||
#~ "GPT/tree/new-page-framework/datacenter"
|
||||
#~ msgstr ""
|
||||
#~ "如果你想了解web-ui, 请访问https://github./csunny/DB-GPT/tree"
|
||||
#~ "/new-page-framework/datacenter"
|
||||
|
||||
|
||||
@ -28,7 +28,11 @@ class WorkerRunData:
|
||||
|
||||
def _to_print_key(self):
|
||||
model_name = self.model_params.model_name
|
||||
model_type = self.model_params.model_type
|
||||
model_type = (
|
||||
self.model_params.model_type
|
||||
if hasattr(self.model_params, "model_type")
|
||||
else "text2vec"
|
||||
)
|
||||
host = self.host
|
||||
port = self.port
|
||||
return f"model {model_name}@{model_type}({host}:{port})"
|
||||
|
||||
2
setup.py
2
setup.py
@ -316,6 +316,7 @@ def core_requires():
|
||||
"jsonschema",
|
||||
# TODO move transformers to default
|
||||
"transformers>=4.31.0",
|
||||
"alembic==1.12.0",
|
||||
]
|
||||
|
||||
|
||||
@ -424,7 +425,6 @@ def default_requires():
|
||||
"dashscope",
|
||||
"chardet",
|
||||
"GitPython",
|
||||
"alembic==1.12.0",
|
||||
]
|
||||
setup_spec.extras["default"] += setup_spec.extras["framework"]
|
||||
setup_spec.extras["default"] += setup_spec.extras["knowledge"]
|
||||
|
||||
Loading…
Reference in New Issue
Block a user