pygents 0.5.1

A lightweight async framework for structuring and running AI agents in Python

pygents

A lightweight async framework for structuring and running AI agents in Python. Define tools, queue turns, stream results.

Install

pip install pygents

Requires Python 3.12+.

Example

import asyncio
from pygents import Agent, Turn, tool

@tool()
async def greet(name: str) -> str:
    return f"Hello, {name}!"

async def main():
    agent = Agent("greeter", "Greets people", [greet])
    # Use kwargs:
    await agent.put(Turn("greet", kwargs={"name": "World"}))
    # Or positional args:
    await agent.put(Turn("greet", args=["World"]))

    async for turn, value in agent.run():
        print(value)  # "Hello, World!"

asyncio.run(main())

Tools are async functions. Turns say which tool to run and with what args. Agents process a queue of turns and stream results. The loop exits when the queue is empty.

Features

• Streaming — agents yield (turn, value) as results are produced
• Inter-agent messaging — agents can send turns to each other
• Dynamic arguments — callable positional args and kwargs evaluated at runtime
• Timeouts — per-turn, default 60s
• Per-tool locking — opt-in serialization for shared state (lock is acquired inside the tool wrapper, so turn-level hooks run outside the tool lock)
• Fixed kwargs — decorator kwargs (e.g. @tool(permission="admin")) are merged into every invocation; call-time kwargs override
• Hooks — @hook(hook_type, lock=..., **fixed_kwargs) decorator; hooks stored as a list and selected by type; turn, agent, tool, and memory hooks; same fixed_kwargs and lock options as tools
• Serialization — to_dict() / from_dict() for turns and agents

Docs

Full documentation: uv run mkdocs serve. MkDocs is an optional dependency—install with pip install -e ".[docs]" (or use uv run as above) so the library itself does not depend on it.