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zhnt/loushang

★ 15PythonAudience · developerComplexity · 4/5Setup · hard

TLDR

Loushang is a layered AI-era operating system framework built in Python, providing a kernel, protocol layer, adapters, and extension points for building agent-driven workflows in a monorepo.

Mindmap

mindmap
  root((loushang))
    What it does
      AI agent runtime
      Layered OS framework
      Terminal UI
    Architecture
      Kernel layer
      Protocol layer
      Adapters
      Extension points
    Packages
      loushang-ai
      loushang-agent
      loushang-channel
      loushang-coding
    Use cases
      Build AI workflows
      Manage complexity
      Custom extensions
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Things people build with this

USE CASE 1

Build a custom AI agent runtime that routes tasks through different LLMs using the adapter layer.

USE CASE 2

Create a terminal-based interface for monitoring and managing AI workflows with loushang-tui.

USE CASE 3

Extend the framework with a coding assistant component via loushang-coding without breaking the core architecture.

Tech stack

Python

Getting it running

Difficulty · hard Time to first run · 1day+

Documentation is in Chinese and internal architecture docs are not included in the README, making onboarding without Chinese language knowledge difficult.

In plain English

Loushang is described as an operating system for the AI era, aimed at helping individuals, teams, and organizations find opportunities, manage complexity, and move quickly. The README is written in Chinese. Beyond that framing, the description is brief. The project follows a layered architecture with four parts: a kernel that defines how the system runs, a protocol layer that defines how it communicates with the outside world, adapters that connect it to different environments and interfaces, and extension points that allow customization without breaking consistency. The code is organized as a monorepo containing several packages: loushang-ai, loushang-agent, loushang-channel, loushang-tui, loushang-methods, and loushang-coding. The package names suggest coverage of AI integration, agent runtime, a terminal UI, and a coding-focused component. The README links to internal architecture documents covering topics like AI streaming, agent types, and a channel boundary protocol, but those documents are not reproduced in the README itself.

Copy-paste prompts

Prompt 1
I have the loushang framework cloned. Walk me through creating a new adapter that connects to an external LLM API following the protocol layer conventions.
Prompt 2
Using loushang-agent, help me define an agent that takes a task description and breaks it into subtasks, then delegates each to a different AI model.
Prompt 3
Show me how to add a custom extension point to loushang that adds a new command to the loushang-tui terminal interface.
Prompt 4
Explain the channel boundary protocol used in loushang and write a minimal example of two components communicating through it.
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