dataelement/bisheng

★ 11,986⑂ 0

BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation

About dataelement/bisheng

dataelement/bisheng is an open-source project on GitHub, mainly written in Python. BISHENG is an open LLM devops platform for next generation Enterprise AI applications. It currently holds 11,986 stars and 0 forks with 0 open issues, and was last pushed on an unknown date (repository created unknown).

Project Overview

AI Homed tracks it on the AI Models & LLM Tools board.

GitHub Repository Details

Repository dataelement/bisheng · default branch - · size 0 KB · watchers 0 · source: GitHub REST API and repository README

README

Proudly made by Chinese,May we, like the creators of Deepseek and Black Myth: Wukong, bring more wonder and greatness to the world.

源自中国匠心,希望我们能像 [Deepseek]、[黑神话:悟空] 团队一样,给世界带来更多美好。
https://github.com/dataelement/bisheng/blob/HEAD/Bisheng banner

https://github.com/dataelement/bisheng/blob/HEAD/license

简体中文 | English | 日本語

https://github.com/dataelement/bisheng/blob/HEAD/dataelement%2Fbisheng | Trendshift

BISHENG is an open LLM application devops platform, focusing on enterprise scenarios. It has been used by a large number of industry leading organizations and Fortune 500 companies.

"Bi Sheng" was the inventor of movable type printing, which played a vital role in promoting the transmission of human knowledge. We hope that BISHENG can also provide strong support for the widespread implementation of intelligent applications. Everyone is welcome to participate.

Features

1. Lingsight, a general-purpose agent with expert-level taste: Through the AGL(Agent Guidance Language) framework, we embed domain experts’ preferences, experience, and business logic into the AI, enabling the agent to exhibit “expert-level understanding” when handling tasks.

https://github.com/dataelement/bisheng/blob/HEAD/sence1

2. Unique BISHENG Workflow

https://github.com/dataelement/bisheng/blob/HEAD/sence0

3. Designed for Enterprise Applications: Document review, fixed-layout report generation, multi-agent collaboration, policy update comparison, support ticket assistance, customer service assistance, meeting minutes generation, resume screening, call record analysis, unstructured data governance, knowledge mining, data analysis, and more. The platform supports the construction of highly complex enterprise application scenarios and offers deep optimization with hundreds of components and thousands of parameters.

https://github.com/dataelement/bisheng/blob/HEAD/sence1

4. Enterprise-grade features are the fundamental guarantee for application implementation: security review, RBAC, user group management, traffic control by group, SSO/LDAP, vulnerability scanning and patching, high availability deployment solutions, monitoring, statistics, and more.

https://github.com/dataelement/bisheng/blob/HEAD/sence2

5. High-Precision Document Parsing: Our high-precision document parsing model is trained on a vast amount of high-quality data accumulated over past 5 years. It includes high-precision printed text, handwritten text, and rare character recognition models, table recognition models, layout analysis models, and seal models., table recognition models, layout analysis models, and seal models. You can deploy it privately for free.

https://github.com/dataelement/bisheng/blob/HEAD/sence3

6. A community for sharing best practices across various enterprise scenarios: An open repository of application cases and best practices.

Quick start

Please ensure the following conditions are met before installing BISHENG:

> Recommended hardware condition: 18 virtual cores, 48G. In addition to installing BISHENG, we will also install the following third-party components by default: ES, Milvus, and Onlyoffice.

Download BISHENG

git clone https://github.com/dataelement/bisheng.git

Enter the installation directory

cd bisheng/docker

If the system does not have the git command, you can download the BISHENG code as a zip file.

wget https://github.com/dataelement/bisheng/archive/refs/heads/main.zip

Unzip and enter the installation directory

unzip main.zip && cd bisheng-main/docker
Start BISHENG
docker compose -f docker-compose.yml -p bisheng up -d
After the startup is complete, access http://IP:3001 in the browser. The login page will appear, proceed with user registration.

By default, the first registered user will become the system admin.

For more installation and deployment issues, refer to::Self-hosting

Acknowledgement

This repo benefits from langchain langflow unstructured and LLaMA-Factory . Thanks for their wonderful works.

Thank you to our contributors:

Community & contact

Welcome to join our discussion group https://github.com/dataelement/bisheng/blob/HEAD/Wechat QR Code

GitHub Stars & Activity

11,986Stars
0Forks
0Open issues
PythonLanguage

GitHub Popularity

GitHub stars11,986
Forks0
Open issues0
Primary languagePython
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Stars gained today0
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Last pushed-

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Trending statusnot on today's boards

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