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AgenticLoopEngine base and ReAct implementation for OVOS, with SKILL.md and AGENTS.md runtime consumption

Project description

ovos-agentic-loop

PyPI License Python

Agent-loop ChatEngine plugins for OVOS. Implements seven agentic reasoning patterns (ReAct, Plan-and-Execute, Reflexion, Self-Ask, Chain-of-Thought, CRITIC, Tree-of-Thoughts), five built-in toolboxes, SKILL.md integration, and AGENTS.md context management — all as standard OPM plugins.


Features

  • 7 loop architectures — from simple Chain-of-Thought to full Reflexion and Tree-of-Thoughts beam search
  • 5 built-in toolboxes — filesystem, shell, web search, clock, math (calculator + unit conversion + statistics)
  • SKILL.md toolbox — turns any installed SKILL.md file into an agent tool
  • AGENTS.md context manager — loads structured system prompts from AGENTS.md files at runtime
  • No LLM bundled — wire any OPM ChatEngine as the inner brain
  • No persona bundled — compose your own persona using the provided primitives

Installation

pip install ovos-agentic-loop

# Optional: web search support
pip install 'ovos-agentic-loop[web]'

Quick Start

Minimal ReAct agent with a calculator

from ovos_agentic_loop.react import ReActLoopEngine
from ovos_agentic_loop.tools.math import MathToolBox
from ovos_plugin_manager.templates.agents import AgentMessage, MessageRole

# Wire a local LLM as the brain (any OPM ChatEngine works)
engine = ReActLoopEngine({
    "brain": "ovos-chat-openai-plugin",
    "ovos-chat-openai-plugin": {
        "api_url": "http://localhost:11434/v1/chat/completions",
    },
    "max_iterations": 8,
})
engine.load_toolboxes([MathToolBox()])

response = engine.continue_chat([
    AgentMessage(role=MessageRole.USER, content="What is 17 * 23 + sqrt(144)?")
])
print(response.content)

Persona JSON (all-in-one config)

{
  "name": "MyAgent",
  "solvers": ["ovos-react-loop"],
  "ovos-react-loop": {
    "brain": "ovos-chat-openai-plugin",
    "ovos-chat-openai-plugin": {
      "api_url": "http://localhost:11434/v1/chat/completions"
    },
    "toolboxes": ["ovos-math-tools", "ovos-web-search-tools", "ovos-clock-tools"],
    "max_iterations": 10
  }
}

Loop Architectures

Entry point Class Best for
ovos-react-loop ReActLoopEngine General tool-using Q&A
ovos-plan-execute-loop PlanAndExecuteEngine Multi-step tasks requiring a plan
ovos-reflexion-loop ReflexionEngine Tasks requiring self-critique and retry
ovos-self-ask-loop SelfAskEngine Compositional questions needing sub-questions
ovos-chain-of-thought-loop ChainOfThoughtEngine Reasoning without tools (math, logic)
ovos-critic-loop CRITICEngine Factual tasks requiring claim verification
ovos-tree-of-thoughts-loop TreeOfThoughtsEngine Exploration-heavy problems (beam search)

Built-in Toolboxes

Entry point Class Tools
ovos-math-tools MathToolBox evaluate_expression, unit_convert, statistics_summary, solve_equation
ovos-filesystem-tools FileSystemToolBox read_file, write_file, list_directory, search_in_files, find_files
ovos-shell-tools ShellToolBox run_command (disabled by default; set allow_shell: true to enable)
ovos-web-search-tools WebSearchToolBox web_search (requires ovos-agentic-loop[web])
ovos-clock-tools ClockToolBox get_current_datetime
ovos-skill-md-toolbox SkillMDToolBox One tool per installed SKILL.md

SKILL.md Integration

Any package that ships a SKILL.md file is automatically discovered and exposed as an agent tool:

---
name: my-skill
description: Does something useful.
---
You are a helpful assistant specialised in...

The tool name is the slugified name field; the SKILL.md body becomes the system prompt for a sub-LLM call.


AGENTS.md Context Management

AgentsMDContextManager assembles system prompts from AGENTS.md files at runtime — the same files Claude Code reads at dev-time:

from ovos_agentic_loop.context.agents_md import AgentsMDContextManager

ctx = AgentsMDContextManager({
    "agents_md_sources": ["auto"],          # auto-discover from installed packages
    "include_sections": ["Rules", "Style"], # filter to specific headings
})
messages = ctx.build_conversation_context(utterance, session_id="s1")

Security Notes

  • ShellToolBoxallow_shell defaults to False. Only enable with fully-trusted LLMs; the command string is passed directly to /bin/sh.
  • FileSystemToolBox — set root_path to restrict file access to a subtree. Without it, the agent can read any world-readable file.
  • MathToolBox — uses ast.parse with an allowlist; eval() is never called.

Documentation


License

Apache 2.0 — see LICENSE.

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