anvyonagentic 3.0.1

Open-source multi-agent framework for task decomposition, delegation, and execution

Anvyon Agentic

Open-source multi-agent framework for task decomposition, delegation, and execution.

Anvyon Agentic is a Python library for building multi-agent systems that decompose, delegate, and execute complex tasks. It provides a simple yet powerful foundation for agentic workflows with pluggable LLM providers.

Features

• Zero required dependencies — core library uses only Python stdlib
• Task decomposition — break complex tasks into manageable subtasks via LLM
• Agent registry — register, list, and find agents by skill
• Basic delegation — create and manage delegation contracts
• Executor routing — route tasks to the right execution path (LLM or tool)
• Built-in tools — calculate, datetime, text_transform, json_parse, web_search
• Pluggable LLM providers — bring your own LLM or use the built-in Anthropic provider

Looking for advanced features? PERT analysis, Monte Carlo simulation, RL optimization, trust calibration, oversight/governance, delegation memory, and human-in-the-loop are available in the anvyonenterprise package.

Installation

pip install anvyonagentic

With Anthropic (Claude) support:

pip install anvyonagentic[anthropic]

For development:

pip install anvyonagentic[dev]

Quick Start

from anvyonagentic import Task, AgentRegistry, BasicOrchestrator, ToolRegistry

tasks = [
    Task(id="T1", description="Parse user input",
         optimistic=0.5, most_likely=1.0, pessimistic=2.0),
    Task(id="T2", description="Process data",
         optimistic=1.0, most_likely=2.0, pessimistic=3.0,
         depends_on=["T1"]),
]

registry = AgentRegistry()
agents = registry.find_by_skill("reasoning")
print(f"Found agent: {agents[0].name}")

orchestrator = BasicOrchestrator()
results = orchestrator.run(tasks)
print(results)

tools = ToolRegistry()
result = tools.execute("calculate", {"expression": "2 + 2 * 3"})
print(result)

Architecture

Modules

Module	Description
anvyonagentic.core	Task, AgentRegistry, BasicOrchestrator
anvyonagentic.router	ExecutorRouter, DelegationManager
anvyonagentic.tools	ToolRegistry with built-in tools

Default Agents

Agent	Type	Skills
llm_reasoner	llm	reasoning, analysis, text generation, planning
tool_executor	tool	calculation, data processing, JSON parsing
code_agent	llm	coding, debugging, testing, code review
research_agent	hybrid	search, research, fact-checking

Advanced Usage

Custom Agents

from anvyonagentic import AgentRegistry, WorkerAgent

registry = AgentRegistry()

registry.register(WorkerAgent(
    name="sql_expert",
    skills=["sql", "database", "query_optimization"],
    agent_type="tool",
    description="Specialized SQL and database agent"
))

agents = registry.find_by_skill("database")
print(f"Found agent: {agents[0].name}")

Built-in Tools

from anvyonagentic import ToolRegistry

tools = ToolRegistry()

result = tools.execute("calculate", {"expression": "2 + 2 * 3"})
print(result)  # {"success": True, "data": {"result": 8}}

result = tools.execute("datetime", {"format": "iso"})
result = tools.execute("text_transform", {"text": "hello", "operation": "upper"})

Enterprise Features

For advanced capabilities including PERT analysis, Monte Carlo simulation, RL optimization, trust calibration, oversight/governance, delegation memory, and human-in-the-loop approval, see the anvyonenterprise package.

pip install anvyonenterprise

Contributing

Contributions are welcome. Please open an issue first to discuss what you would like to change.

git clone https://github.com/anvyon/anvyonagentic.git
cd anvyonagentic
pip install -e ".[dev]"
pytest

License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). See LICENSE for the full text.