Metadata-Version: 2.4
Name: macroroni
Version: 0.1.2
Summary: A speech-to-intent controller for a variety of VUI fields.
Author-email: NLP Bros <brainsparkteam@gmail.com>
Project-URL: Homepage, https://github.com/Brainspark1/macroroni
Description-Content-Type: text/markdown

# macroroni

`macroroni` is an open-source, highly adaptable speech-to-intent framework designed for Voice User Interface (VUI) development. It enables developers to seamlessly map spoken commands into actionable programmatic outputs or real-time game inputs (such as controls for classic emulation environments like OpenAI Gym/Gymnasium).

By combining local, cutting-edge Automatic Speech Recognition (ASR) engines with automated Machine Learning intent classification, `macroroni` bridges the gap between raw voice audio and immediate application state updates.

---

## Features

* **Multi-Backend Speech Recognition:** Native support for high-performance localized transcription:
  * **Apple Silicon (MPS):** Optimized hardware acceleration using `mlx-whisper`.
  * **NVIDIA GPU (CUDA):** Fast, quantized execution using `faster-whisper`.
* **Embedded Intent Classifier:** Built-in NLP pipeline featuring a specialized TF-IDF Vectorizer coupled with an optimized, auto-calibrating Logistic Regression model.
* **Low-Latency Architecture:** Employs non-blocking, background thread audio listening combined with ambient noise microphone calibration to minimize latency.
* **Extensible Architecture:** Out-of-the-box support for modular customization (`SingleVoiceController`), including pre-built integrations for gaming wrappers like `gym-super-mario-bros`.

---

## Requirements & System Support

`macroroni` is compatible with Python 3.8+ across major operating systems. Depending on your machine's hardware, ensure you install your preferred localized inference engine:

* For **Apple Silicon Macs (M1/M2/M3/M4):** `pip install mlx-whisper`
* For **NVIDIA GPU Systems:** `pip install faster-whisper`
