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# DB-GPT
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---
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A Open Database-GPT Experiment, interact your data and environment using the local GPT, no data leaks, 100% privately, 100% security.
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一个数据库相关的GPT实验项目, 模型与数据全部本地化部署, 绝对保障数据的隐私安全。 同时此GPT项目可以直接本地部署连接到私有数据库, 进行私有数据处理。
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[DB-GPT](https://github.com/csunny/DB-GPT) 是一个实验性的开源应用，它基于[FastChat](https://github.com/lm-sys/FastChat)，并使用[vicuna-13b](https://huggingface.co/Tribbiani/vicuna-13b)作为基础模型。此外，此程序结合了[langchain](https://github.com/hwchase17/langchain)和[llama-index](https://github.com/jerryjliu/llama_index)基于现有知识库进行[In-Context Learning](https://arxiv.org/abs/2301.00234)来对其进行数据库相关知识的增强。它可以进行SQL生成、SQL诊断、数据库知识问答、数据处理等一系列的工作。
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## 项目方案
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<img src="https://github.com/csunny/DB-GPT/blob/main/asserts/DB-GPT.png" width="600" margin-left="auto" margin-right="auto" >
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[DB-GPT](https://github.com/csunny/DB-GPT) is an experimental open-source application that builds upon the [FastChat](https://github.com/lm-sys/FastChat) model and uses vicuna as its base model. Additionally, it looks like this application incorporates langchain and llama-index embedding knowledge to improve Database-QA capabilities.
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Overall, it appears to be a sophisticated and innovative tool for working with databases. If you have any specific questions about how to use or implement DB-GPT in your work, please let me know and I'll do my best to assist you.
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## 运行效果演示
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Run on an RTX 4090 GPU (The origin mov not sped up!, [YouTube地址](https://www.youtube.com/watch?v=1PWI6F89LPo))
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- 运行演示
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- SQL生成示例
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首先选择对应的数据库, 然后模型即可根据对应的数据库Schema信息生成SQL
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<img src="https://github.com/csunny/DB-GPT/blob/main/asserts/SQLGEN.png" width="600" margin-left="auto" margin-right="auto" >
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The Generated SQL is runable.
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<img src="https://github.com/csunny/DB-GPT/blob/main/asserts/exeable.png" width="600" margin-left="auto" margin-right="auto" >
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- 数据库QA示例
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<img src="https://github.com/csunny/DB-GPT/blob/main/asserts/DB_QA.png" margin-left="auto" margin-right="auto" width="600">
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基于默认内置知识库QA
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<img src="https://github.com/csunny/DB-GPT/blob/main/asserts/VectorDBQA.png" width="600" margin-left="auto" margin-right="auto" >
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# Dependencies
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1. First you need to install python requirements.
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```
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python>=3.9
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pip install -r requirements.txt
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```
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or if you use conda envirenment, you can use this command
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```
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cd DB-GPT
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conda env create -f environment.yml
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```
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2. MySQL Install
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In this project examples, we connect mysql and run SQL-Generate. so you need install mysql local for test. recommand docker
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```
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docker run --name=mysql -p 3306:3306 -e MYSQL_ROOT_PASSWORD=aa12345678 -dit mysql:latest
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```
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The password just for test, you can change this if necessary
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# Install
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1. 基础模型下载
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关于基础模型, 可以根据[vicuna](https://github.com/lm-sys/FastChat/blob/main/README.md#model-weights)合成教程进行合成。
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如果此步有困难的同学，也可以直接使用[Hugging Face](https://huggingface.co/)上的模型进行替代. [替代模型](https://huggingface.co/Tribbiani/vicuna-7b)
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2. Run model server
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```
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cd pilot/server
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python vicuna_server.py
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```
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3. Run gradio webui
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```
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python webserver.py
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```
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4. 基于阿里云部署指南
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[阿里云部署指南](https://open.oceanbase.com/blog/3278046208)
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# Featurs
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- SQL-Generate
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- Database-QA Based Knowledge
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- SQL-diagnosis
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总的来说，它是一个用于数据库的复杂且创新的AI工具。如果您对如何在工作中使用或实施DB-GPT有任何具体问题，请联系我, 我会尽力提供帮助, 同时也欢迎大家参与到项目建设中, 做一些有趣的事情。
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<img src="https://github.com/csunny/DB-GPT/blob/main/asserts/wechat.jpg" width="400" margin-left="auto" margin-right="auto" >
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# Contribute
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[Contribute](https://github.com/csunny/DB-GPT/blob/main/CONTRIBUTING)
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# Licence
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[MIT](https://github.com/csunny/DB-GPT/blob/main/LICENSE)
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19
README.md
19
README.md
@ -1,14 +1,24 @@
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# DB-GPT
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A Open Database-GPT Experiment, interact your data and environment using the local GPT, no data leaks, 100% privately, 100% security.
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一个数据库相关的GPT实验项目, 模型与数据全部本地化部署, 绝对保障数据的隐私安全。 同时此GPT项目可以直接本地部署连接到私有数据库, 进行私有数据处理。
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---
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[DB-GPT](https://github.com/csunny/DB-GPT) 是一个实验性的开源应用，它基于[FastChat](https://github.com/lm-sys/FastChat)，并使用[vicuna-13b](https://huggingface.co/Tribbiani/vicuna-13b)作为基础模型。此外，此程序结合了[langchain](https://github.com/hwchase17/langchain)和[llama-index](https://github.com/jerryjliu/llama_index)基于现有知识库进行[In-Context Learning](https://arxiv.org/abs/2301.00234)来对其进行数据库相关知识的增强。它可以进行SQL生成、SQL诊断、数据库知识问答、数据处理等一系列的工作。
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专注于数据库垂直领域的 GPT 项目，提供大模型与数据的本地化使用方案，保障数据的隐私安全，适用企业内和个人。
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## 项目能力一览
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- SQL 语言能力
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- SQL生成
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- SQL诊断
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- 私域问答与数据处理
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- 数据库知识问答
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- 数据处理
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[DB-GPT](https://github.com/csunny/DB-GPT) 是一个实验性的开源应用，它基于[FastChat](https://github.com/lm-sys/FastChat)，并使用[vicuna-13b](https://huggingface.co/Tribbiani/vicuna-13b)作为基础模型。此外，此程序结合了[langchain](https://github.com/hwchase17/langchain)和[llama-index](https://github.com/jerryjliu/llama_index)基于现有知识库进行[In-Context Learning](https://arxiv.org/abs/2301.00234)来对其进行数据库相关知识的增强。
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## 项目方案
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## 架构方案
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<img src="https://github.com/csunny/DB-GPT/blob/main/asserts/DB-GPT.png" width="600" margin-left="auto" margin-right="auto" >
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[DB-GPT](https://github.com/csunny/DB-GPT) is an experimental open-source application that builds upon the [FastChat](https://github.com/lm-sys/FastChat) model and uses vicuna as its base model. Additionally, it looks like this application incorporates langchain and llama-index embedding knowledge to improve Database-QA capabilities.
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@ -17,6 +27,7 @@ Overall, it appears to be a sophisticated and innovative tool for working with d
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## 运行效果演示
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Run on an RTX 4090 GPU (The origin mov not sped up!, [YouTube地址](https://www.youtube.com/watch?v=1PWI6F89LPo))
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- 运行演示
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