Skip to main content

A professional Git-based Skill management library for LLM agents.

Project description

LLMRix Skill Plugin Library

llmrix-skill is a professional Git-based Skill and plugin management framework designed for LLM Agents. It encapsulates the complex logic of publishing, versioning, and syncing code, prompts, and tools into an out-of-the-box plugin library, allowing developers to focus on building core Agent logic.

Core Features

As the foundational plugin library for an Agent framework, it provides the following capabilities:

  • Git-Driven Plugin Market: Uses Git repositories as the Single Source of Truth (SSOT) to achieve skill persistence, version tracing, and change tracking.
  • Out-of-the-box Dual Mode Architecture:
    • Worker Mode (Execution): Pure lightweight synchronization, responsible for pulling skills from remote repositories to local storage for high-speed loading by Agent instances.
    • Management Mode (Admin): Integrates with databases to support multi-tenant authentication, skill publishing, metadata parsing, and version rollbacks.
  • Dynamic Metadata Parsing: Automatically parses and validates SKILL.md (YAML Frontmatter) in the skill package to extract the plugin name, description, and category.
  • Concurrency & Safety: Built-in distributed file lock mechanism to prevent file state race conditions during high-concurrency publishing and pulling.

Quick Usage Guide

Installation

You can integrate this plugin library into your Agent project via pip:

pip install llmrix-skill

Scene 1: Syncing Plugins on Agent Execution Node (Worker Mode)

In your Agent execution environment (such as background task nodes, or upon container startup), configure a specific branch to pull the latest skills for model invocation.

from llmrix.skill import GitSkillManager

def sync_skills_for_agent():
    # Initialize the Manager, configuring the remote repository and target branch
    manager = GitSkillManager(
        repo_url="https://github.com/your-org/skill-repo.git",
        branch="develop",                # Highly recommended: specify the branch to pull (e.g., main/develop/v1)
        workspace="/path/to/local/cache" # Local cache path
    )

    # Execute sync, returning the absolute filesystem path where the skills are located
    skills_path = manager.sync()
    print(f"✅ Skill plugins synced to: {skills_path}")
    
    # You can now dynamically load modules under skills_path in your Agent framework

Scene 2: Web Server Management & Publishing (Management Mode)

In your Web API service (such as FastAPI/Django plugin market backend), use GitSkillManager to handle user uploads, publishing, and version rollbacks. It encapsulates database persistence and concurrent file locking.

from llmrix.skill import GitSkillManager
from llmrix.skill import MySQLStorage

# 1. Configure the database adapter
def get_db_connection():
    # Return a pymysql/MySQLdb connection object
    pass

storage = MySQLStorage(connection_factory=get_db_connection)

# 2. Initialize the Manager, dedicated for the management end
manager = GitSkillManager(
    repo_url="git@github.com:your-org/skill-repo.git",
    storage=storage
)

# 3. Publish user-uploaded skills
def publish_user_skill(user_id, uploaded_dir):
    skill = manager.publish(
        code="python_interpreter",      # Unique skill code
        source_dir=uploaded_dir,        # Unzipped directory uploaded by the user
        user_id=user_id,                # Current operating user ID (for auth)
        message="Initial release"       
    )
    print(f"🚀 Publish successful: {skill.name} v{skill.version}")

# 4. Version Rollback
def rollback_skill(user_id):
    skill = manager.rollback(
        code="python_interpreter",
        target_version=1,
        user_id=user_id,
        message="Revert due to bugs"
    )

Skill Package Specification

A standard skill plugin package is a directory containing the following files:

my_awesome_skill/
├── SKILL.md      # Skill description and metadata (Required)
├── main.py       # Core logic (Recommended)
└── requirements.txt # Dependencies (Optional)

SKILL.md must contain a valid YAML Frontmatter header:

---
name: Web Scraper Pro
description: Powerful web scraping tool, supports dynamic rendering.
category: Web & Search
---

Detailed Markdown documentation about this skill goes here...

Module Architecture

You can directly import the required submodules for lower-level extensions:

  • llmrix.skill.services: Contains GitSkillManager, SkillPublisher, and SkillSyncer.
  • llmrix.skill.storage: Contains BaseStorage and MySQLStorage. Inherit BaseStorage to implement your own MongoDB or PostgreSQL adapters.
  • llmrix.skill.git: Low-level Git driver library GitRepository.
  • llmrix.skill.models: Data models Skill and SkillVersion.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llmrix_skill-0.2.10.tar.gz (19.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

llmrix_skill-0.2.10-py3-none-any.whl (24.1 kB view details)

Uploaded Python 3

File details

Details for the file llmrix_skill-0.2.10.tar.gz.

File metadata

  • Download URL: llmrix_skill-0.2.10.tar.gz
  • Upload date:
  • Size: 19.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.18

File hashes

Hashes for llmrix_skill-0.2.10.tar.gz
Algorithm Hash digest
SHA256 751c374c78d876518b8d93a58728668df08f4ce17c90f23baac558a12c67067b
MD5 8593c003d2b26b8d81a011fbc18d2039
BLAKE2b-256 c89ee3fa011557cce84837e6b0c432eb62b3059742f7c83fdcc0e5796cb65321

See more details on using hashes here.

File details

Details for the file llmrix_skill-0.2.10-py3-none-any.whl.

File metadata

  • Download URL: llmrix_skill-0.2.10-py3-none-any.whl
  • Upload date:
  • Size: 24.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.18

File hashes

Hashes for llmrix_skill-0.2.10-py3-none-any.whl
Algorithm Hash digest
SHA256 841e73349f6b971dcd0afcaa71e7e3101babd084984c6f5bf7d16cb78d56af24
MD5 e5e520290a05c9a17fdd95bbe6a42a58
BLAKE2b-256 1795f90901739a172a9683eaba203bf6963b8010b5b1cf0214f5f48e3a381ba6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page