Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/uniai-lab/uniai-maas
An opensource AI & model as a service platform.
https://github.com/uniai-lab/uniai-maas
ai chatglm chatgpt gpt kimichat midjourney moonshot spark stability-ai uniai
Last synced: 4 days ago
JSON representation
An opensource AI & model as a service platform.
- Host: GitHub
- URL: https://github.com/uniai-lab/uniai-maas
- Owner: uniai-lab
- License: mit
- Created: 2023-04-10T14:13:16.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-29T04:41:54.000Z (about 2 months ago)
- Last Synced: 2024-10-29T01:32:36.576Z (16 days ago)
- Topics: ai, chatglm, chatgpt, gpt, kimichat, midjourney, moonshot, spark, stability-ai, uniai
- Language: TypeScript
- Homepage: https://www.uniai.us
- Size: 2.27 MB
- Stars: 27
- Watchers: 4
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
UniAI MaaS
Powered by the eponymous node.js library uniai.
## Overview
[Simplified Chinese (简体中文说明)](./README_CN.md) 🇨🇳
### Model as a Service
**UniAI MaaS** aims to implement a model as a service platform integrated multi AI models, allowing developers to focus on developing Generative AI applications.
### Retrieval Augmented Generation
The platform supports a vector database, and an object storage service which enables users to upload, parse, and manage MS office files.
### Multi-modals & Multi-models
In addition to text generation models, it also offers multi-modal models such as image generation and recognition.
### Application
UniAI MaaS supports custom application development for integration with platforms like WeChat Mini Programs.
### About
UniAI, powered by the node.js library of the same name **uniai**, provides seamless access and management of a diverse range of AI models and utilities. To incorporate UniAI into your own project, you can install it via [npm](https://www.npmjs.com/package/uniai) or [Github](https://github.com/devilyouwei/UniAI).
### Frontend Example
Front end:
## Integrated Models
UniAI integrates multiple AI models, including:
- [IFLYTEK/Spark](https://xinghuo.xfyun.cn)
- [THUDM/ChatGLM-6B](https://github.com/THUDM/ChatGLM3)
- [ZHIPU/GLM](https://github.com/THUDM/ChatGLM3)
- [MoonShot/moonshot](https://www.moonshot.cn/)
- [OpenAI/GPT](https://platform.openai.com)
- [Baidu/WenXin workshop](https://cloud.baidu.com/product/wenxinworkshop)
- [Google/Gemini](https://makersuite.google.com/app/)
- [Stability AI](https://platform.stability.ai/)
- [OpenAI/DALL-E](https://platform.openai.com)
- [Midjourney](https://github.com/novicezk/midjourney-proxy)
## Samples
Discover how UniAI is utilized and experience it firsthand:
### LeChat Mini App
To launch the mini app, use WeChat to scan the following QR code.
### LeChat Pro
👍 We recommend:
- Multi-model Chat
- Office file upload and parse
- Image generation
- Image recognition
## System Requirements
Ensure you have the following `NPM` libs installed:
- Node.js (version >= 18) - [nvm Installation Guide](https://github.com/nvm-sh/nvm)
- Docker & Docker-compose
- LibreOffice for document conversion (libreoffice-convert)
- pdf-to-img (canvas-node) - [Canvas NPM Package](https://www.npmjs.com/package/canvas)
## Getting Started
### Configuration
Create an `.env` file at the project root path:
```bash
touch ./.env
```
Fill the `.env` file with the following environment variables:
```bash
# Platform default admin token
ADMIN_TOKEN=
# OPENAI GPT
OPENAI_API= # openai proxy
OPENAI_KEY= # openai key
# Google AI studio
GOOGLE_AI_API= # google proxy
GOOGLE_AI_KEY= # google key
# ZHIPU AI
# ZHIPU_AI_API= #zhipu proxy
ZHIPU_AI_KEY= # zhipu key
GLM_API= # local deployed glm6b
# SPARK
FLY_APP_ID= # iflytek app id
FLY_API_KEY= # ilfytek api key
FLY_API_SECRET= # iflytek api secret
# baidu wenxin workshop
# BAIDU_API=http://192.168.41.52:5300
BAIDU_API_KEY=
BAIDU_SECRET_KEY=
# Moonshot
# MOONSHOT_API=http://192.168.41.52:5400
MOONSHOT_KEY=
# Stable Diffusion
STABLE_DIFFUSION_API=
# Midjourney
MJ_API= # https://github.com/novicezk/midjourney-proxy
MJ_IMG_PROXY= # proxy to discord cdn images
MJ_TOKEN= # mj token
# stability ai
STABILITY_KEY=
# PostgreSQL database
DB_DIALECT=postgres
POSTGRES_HOST=localhost
POSTGRES_PORT=5432
POSTGRES_USER=postgres
POSTGRES_PASS=postgres
POSTGRES_DB=uniai
# Redis cache
REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_PASS=redis
REDIS_DB=0
# WeChat
WX_APP_ID= # wechat miniapp id
WX_APP_SECRET= # wechat miniapp secret
WX_MCH_ID=
WX_PAY_PRIVATE=
WX_PAY_CERT=
WX_PAY_KEY=
# MINIO storage
MINIO_END_POINT=localhost
MINIO_ACCESS_KEY=
MINIO_SECRET_KEY=
MINIO_PORT=9000
MINIO_BUCKET=uniai
# gee code test
GEE_TEST_ID=
GEE_TEST_KEY=
# aliyun SMS account
ALI_KEY_ID=
ALI_KEY_SECRET=
ALI_SMS_TEMPLATE=
ALI_SMS_SIGN=
# For Docker start pgvector
POSTGRES_DATA_PATH=./data
# For Docker start Minio
MINIO_DATA_PATH=./data
MINIO_ROOT_USER=root
MINIO_ROOT_PASS=12345678
```
### Installation Steps
**Node-gyp Installation**
```bash
npm -g install node-gyp
```
**LibreOffice Installation**
- Ubuntu: `sudo apt install libreoffice`
- Mac: `brew install libreoffice`
**Node-Canvas Support**
- Reference: [Canvas NPM Documentation](https://www.npmjs.com/package/canvas)
- Install dependencies as per your operating system.
**Using Yarn (Recommended over npm)**
```bash
npm -g install yarn
yarn
```
**Sharp Support**
```bash
yarn add sharp --ignore-engines
```
### Starting the Database
For databases like PostgresSQL (pgvector), Docker and Docker-compose can be used for setup:
```bash
sudo apt install docker.io docker-compose
```
**Docker Commands for Database Services**
- Start pgvector: `yarn docker up pgvector`
- Start Redis: `yarn docker up redis`
- Start Minio: `yarn docker up minio`
**Important Notes**
- Ensure proper permissions for Docker volumes.
- Configure Minio after Docker initialization.
- Default Docker settings are available in `.env`.
Minio Access:
- URL: `http://localhost:9000`
- Default Username: `root`
- Default Password: `12345678`
### Running UniAI
**Development Mode**
- Initializes the database.
```bash
yarn dev
```
**Production Mode**
- Compile TypeScript files and start the application.
```bash
yarn tsc
yarn start
```
⚠️ Avoid compiling TypeScript files in development mode. Use `yarn clean` before `yarn dev` if `tsc` was previously run.
### Cleaning Up
```bash
yarn clean
```
## Documentation
Access UniAI's APIs through common Web HTTP methods, including SSE. For detailed documentation, visit [UniAI API Documentation](https://documenter.getpostman.com/view/9347507/2s93Y5Pf2J).
## Available Models
UniAI integrates various AI models, focusing on NLP and CV domains. Specific models need to be deployed independently. Download URLs and guides are provided.
### NLP Models
- OpenAI GPT, GLM/ChatGLM, IFLYTEK/SPARK, Google/Gemini, Moonshot, Baidu
### CV Models
- OpenAI DALL-E, Stable Diffusion, MidJourney
## Future Enhancements
UniAI is planning to expand its capabilities across:
- Prediction APIs
- Training APIs
- Prompting APIs
- Resource Management APIs
## Contributing
Youwei Huang
Institute of Intelligent Computing Technology, Suzhou, CAS
## License
Powered by [Egg.js](https://www.eggjs.org/)
[MIT](./LICENSE)
Copyright (c) 2022-present, Youwei Huang