ActuatorAI

A powerful framework for building natural language interfaces to actions

Overview

ActuatorAI makes it easy to create AI-powered interfaces that can understand natural language requests and execute corresponding actions. It provides a clean, declarative API for defining actions and their natural language triggers.

Features

• ✨ Simple Declarative API - Define actions with intuitive decorators
• 🧠 Built-in LLM Integration - Leverages state-of-the-art language models
• 🔌 Extensible Architecture - Create custom actions, formatters, and adapters
• 🌐 API Server - Ready-to-use FastAPI server for web integration
• 🛠️ Customizable - Configure to use different LLM providers

Installation

pip install actuator-ai

Quick Start

Basic Usage

from actuator_ai.core import action, ActuatorAI

# Define an action with a natural language pattern
@action("Get the weather for {location}")
def get_weather(location: str):
    # Your implementation here
    return {"temperature": 72, "condition": "sunny"}

# Create an ActuatorAI instance
ai = ActuatorAI()

# Process a natural language request
result = ai.process("What's the weather in San Francisco?")
print(result)

Multiple Actions

@action("Find restaurants in {city}")
def find_restaurants(city: str):
    return {"restaurants": ["Restaurant A", "Restaurant B"]}

@action("Book a flight from {origin} to {destination}")
def book_flight(origin: str, destination: str):
    return {"flight": "AB123", "departure": "9:00 AM"}

# ActuatorAI will automatically determine which action to use
result = ai.process("Find me some restaurants in New York")

API Server

ActuatorAI includes a ready-to-use FastAPI server:

from actuator_ai.api import create_app

app = create_app()

# Run with: uvicorn my_module:app --reload

Documentation

For full documentation, examples, and advanced usage, visit our GitHub repository.

License

MIT