Getting Started

中文

LangChain4j-AIDeepin Langchain4j-aideepin is an open source, offline deployable Retrieval Enhancement Generation (RAG) project based on large language models such as ChatGPT and application frameworks such as Langchain4j.

Website

http://www.aideepin.com

Feature

• Login & Register
• Multiple Conversation | Multiple character
• AI Draw
• Prompt
• Quota
• Knowledge base(RAG)
• AI Search(RAG)
• Multiple models switch at will
• Multiple search engine switch at will

Support Models

• ChatGPT 3.5
• 通义千问
• 文心一言
• ollama
• DALL-E 2

Support Search Engines

Google

Bing (TODO)

百度 (TODO)

Introduction

This repository is a back-end project, front-end project in langchain4j-aideepin-web

Backend：

jdk17

springboot3.0.5

langchain4j(Java version of LangChain)

Postgresql(需要安装pgvector扩展)

Frontend：

vue3+typescript+pnpm

Build and run this project

Init

a. Init database

• Create database schema: aideepin
• Run: docs/create.sql
• Update language model config:

Openai setting

update adi_sys_config set value = '{"secret_key":"my_openai_secret_key","models":["gpt-3.5-turbo"]}' where name = 'openai_setting';

Dashscope setting

update adi_sys_config set value = '{"api_key":"my_dashcope_api_key","models":["my model name,eg:qwen-max"]}' where name = 'dashscope_setting';

Qianfan setting

update adi_sys_config set value = '{"api_key":"my_qianfan_api_key","secret_key":"my_qianfan_secret_key","models":["my model name,eg:ERNIE-Bot"]}' where name = 'qianfan_setting';

Ollama setting

update adi_sys_config set value = '{"base_url":"my_ollama_base_url","models":["my model name,eg:tinydolphin"]}' where name = 'ollama_setting';

• Search engine setting

Google:

update adi_sys_config set value = '{"url":"https://www.googleapis.com/customsearch/v1","key":"my key from cloud.google.com","cx":"my cx from programmablesearchengine.google.com"}' where name = 'google_setting';

b. Init properties

• postgresql: spring.datasource in application-[dev|prod].xml
• redis: spring.data.redis in application-[dev|prod].xml
• mail: spring.mail in application.xml

Compile & Run

• Enter the project root directory:

cd langchain4j-aideepin

• Package：

mvn clean package -Dmaven.test.skip=true

• Run:

a. Run by jar：

cd adi-bootstrap/target
nohup java -jar -Xms768m -Xmx1024m -XX:+HeapDumpOnOutOfMemoryError adi-chat-0.0.1-SNAPSHOT.jar --spring.profiles.active=[dev|prod] dev/null 2>&1 &

b. Run by docker

cd adi-bootstrap
docker build . -t aideepin:0.0.1
docker run -d \
  --name=aideepin \
  -e APP_PROFILE=[dev|prod] \
  -v="/data/aideepin/logs:/data/logs" \
  aideepin:0.0.1

TODO：

Enhance RAG

More search engine（BING、百度）

Screenshot

AI Chat：

AI Draw：

Knowlege base：

Embedding：

Quota：

!