Kinyoo
4ad975e1a5
The State spec landed yesterday as prose; this is the component, plus the revision the designer asked for on review: drop the two typography sets. Scenario decides what you write and which artwork you pick, but never how it is typeset — so there is one layout (16 / 4 / 16), and whether 主提示 renders as a title or as description depends on a single question: does a 辅助说明 follow it. A lone line is not a heading; 16/24 bold makes "还没有知识库" shout louder than the page around it. StateView therefore has one axis, `size` (page / panel / inline) — the container's size, per §3. The inline tier types `image`/`action` as `never`: the spec says they're ignored there, and a compile error says it better than a dev warning this package has no channel for. Exported as StateView, not State, so it never reads as a React state variable. First four consumers migrate off their hand-rolled shells: PermissionEmptyState (which feeds five call sites), ChatEmptyState, KnowledgeListPanel and SkillSelector. Docs site: the demo page, and a preview-card exemption in the doc CSS — the prose rules were flattening every <p> a live component renders to 14/22/400, so the State page's title tier looked identical to its compact one. That page is exactly where a designer comes to eyeball the hierarchy. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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。
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
- 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.
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Unique BISHENG Workflow
- 🧩 Independent and comprehensive application orchestration framework: Enables the execution of various tasks within a single framework (while similar products rely on bot invocation or separate chatflow and workflow modules for different tasks).
- 🔄 Human in the loop: Allows users to intervene and provide feedback during the execution of workflows (including multi-turn conversations), whereas similar products can only execute workflows from start to finish without intervention.
- 💥 Powerful: Supports loops, parallelism, batch processing, conditional logic, and free combination of all logic components. It also handles complex scenarios such as multi-type input/output, report generation, content review, and more.
- 🖐️ User-friendly and intuitive: Operations like loops, parallelism, and batch processing, which require specialized components in similar products, can be easily visualized in BISHENG as a "flowchart" (drawing a loop forms a loop, aligning elements creates parallelism, and selecting multiple items enables batch processing).
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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.
- 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.
- 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.
- 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:
- CPU >= 4 Virtual Cores
- RAM >= 16 GB
- Docker 19.03.9+
- Docker Compose 1.25.1+
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
