AgenticLoopEngine base and ReAct implementation for OVOS, with SKILL.md and AGENTS.md runtime consumption
Project description
ovos-agentic-loop
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
ChatEngineas 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
ShellToolBox—allow_shelldefaults toFalse. Only enable with fully-trusted LLMs; the command string is passed directly to/bin/sh.FileSystemToolBox— setroot_pathto restrict file access to a subtree. Without it, the agent can read any world-readable file.MathToolBox— usesast.parsewith an allowlist;eval()is never called.
Documentation
- docs/loop-architectures.md — all 7 loop engines with algorithm details
- docs/react-loop.md — ReAct prompt format and parsing
- docs/toolboxes.md — all toolbox schemas and config keys
- docs/skill-md.md — SKILL.md authoring and packaging guide
- docs/agents-md.md — AGENTS.md context manager reference
- docs/opm-integration.md — OPM entry points and persona wiring
License
Apache 2.0 — see LICENSE.
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