liman-core 0.1.0

Liman AgentOps Core Library

Liman Core

Core library for Liman - a declarative YAML-based agent framework with custom DSL for building AI workflows.

What is it?

Liman Core provides low-level building blocks for creating AI agents through YAML manifests.
This repo introduces a Node and NodeActor architecture for defining and executing agent workflows.
Nodes are stateless specifications that store configuration, while NodeActors are stateful instances that execute specific nodes. Use these components to build your own orchestration system or use the built-in one in liman.

Key Features

• YAML-First: Define entire agent workflows in declarative YAML
• Node Architecture: LLM, Tool, Function, and custom nodes with automatic composition
• Edge DSL: Smart conditional routing between nodes with custom expressions
• Multi-Language: Built-in localization for prompts and descriptions
• Plugin System: Extensible architecture with authentication, telemetry, and custom plugins
• NodeActor: Async execution engine with state management and error handling

Installation

pip install liman_core

Requires Python 3.10+

Quick Example

from liman_core import LLMNode, ToolNode, NodeActor, Registry

# Initialize registry
registry = Registry()

# Create tool
tool_spec = {
    "kind": "ToolNode",
    "name": "calculator",
    "func": "math.sqrt",
    "description": {"en": "Calculate square root"}
}
tool = ToolNode.from_dict(tool_spec, registry)

# Create LLM node with tool
llm_spec = {
    "kind": "LLMNode",
    "name": "assistant",
    "tools": ["calculator"],
    "prompts": {"system": {"en": "You are a math assistant"}}
}
llm_node = LLMNode.from_dict(llm_spec, registry)

# Execute with NodeActor
actor = NodeActor.create(llm_node, llm=your_llm_instance)
result = await actor.execute("What's the square root of 16?", execution_id)

Core Components

Nodes (Stateless Specifications)

• LLMNode: LLM requests with system prompts and tool integration
• ToolNode: Function definitions for LLM tool calling
• FunctionNode: Custom Python functions

Nodes are building blocks that store configuration and behavior but contain no execution state.

NodeActor (Stateful Execution)

Stateful execution engine that wraps a specific node, handles state management, and executes async operations with error handling and recovery.

Edge DSL

nodes:
  - target: success_handler
    when: "status == 'complete' and retry_count < 3"
  - target: error_handler
    when: "failed and critical == true"

Registry & Plugins

Central component registry with extensible plugin system for auth, telemetry, and custom functionality.

Architecture

Registry → Node (stateless) → NodeActor (stateful) → Execution
    ↓           ↓                    ↓
 Plugins    Spec Config        State Management

Use .print_spec() on any node to inspect its YAML specification.

Development

# Activate virtual environment
source .venv/bin/activate

# Run tests
poe test

# Type checking
poe mypy

# Linting
poe lint

# Formatting
poe format