nonoka 1.1.0

A production-grade, type-safe Python Agent framework

Nonoka

A production-grade, type-safe Python agent framework with deterministic orchestration, conversational execution, and first-class MCP integration.

Features

• Type-safe core — Pydantic-validated schemas throughout; agents, tools, and plans are all strongly typed
• Deterministic orchestration — Plan + Step + ref() for explicit control flow, not just prompt-and-pray
• Conversational execution — ReActAgent, ReflectiveAgent, and PlanExecutor paradigms out of the box
• First-class tools — @tool decorator with automatic Pydantic schema generation
• Prompt engineering — @prompt decorator and PromptTemplate for composable, type-safe prompt construction
• MCP ready — built-in MCP (Model Context Protocol) support via mcp
• Resilient execution — structured error taxonomy (TransientError, LogicError, SafetyError, etc.) with configurable RetryPolicy
• Observable hooks — Hooks system for tracing, logging, and custom middleware
• Multi-backend LLM — powered by litellm, supporting OpenAI, Anthropic, DeepSeek, and 100+ providers

Installation

pip install nonoka

Or with uv:

uv add nonoka

Quick Start

import asyncio
import nonoka

@nonoka.tool
def get_weather(city: str) -> str:
    """Get the weather for a city."""
    return f"Sunny in {city}!"

async def main():
    agent = nonoka.Agent(
        name="weather-bot",
        tools=[get_weather],
    )
    result = await agent.run("What's the weather in Tokyo?")
    print(result.output)

asyncio.run(main())

Plans & Orchestration

Explicit multi-step workflows with type-safe references:

from nonoka import PlanBuilder, ref

plan = (
    PlanBuilder()
    .add_step("research", "Search for information")
    .add_step("summarize", "Summarize findings", depends_on=[ref("research")])
    .build()
)

executor = nonoka.PlanExecutor(plan=plan)
result = await executor.run("Latest AI breakthroughs")

Prompt Templates

Composable, type-safe prompts:

from nonoka import prompt, PromptTemplate

@prompt
def translate(text: str, target: str = "Chinese") -> str:
    """Translate the following text to {target}:

    {text}
    """

# Or programmatically
tpl = PromptTemplate("Summarize this in {style}:\n{content}")
output = tpl.render(style="bullet points", content=long_text)

ReAct Agent

agent = nonoka.ReActAgent(tools=[search, calculator])
result = await agent.run("What is 42 * the current temperature in Paris?")

Configuration

Nonoka integrates with pydantic-settings for environment-driven config:

from pydantic_settings import BaseSettings

class Settings(BaseSettings):
    openai_api_key: str
    default_model: str = "gpt-4o"

    class Config:
        env_prefix = "NONOKA_"

Requirements

• Python >= 3.10

License

MIT