Dára Home is a multilingual, voice-first smart home assistant built for Nigeria. It uses N-ATLaS for Reasoning and intent understanding in English, Yoruba, Hausa, and Igbo, Whisper for speech-to-text, a Flutter app for interaction, and custom ESP32 firmware (C++) for real-world device control
# Dára Home (Dara-awarri) 🇳🇬
**Dára Home** is a multilingual, voice-first smart home assistant designed specifically for the Nigerian context. It bridges the gap between modern smart home technology and local linguistic reality by supporting **English, Yoruba, Hausa, and Igbo**.
## 🏗️ Architecture Overview
The system operates on a **Controller-Facilitator** model where the Mobile App acts as the central brain for orchestration, while the Backend handles intelligence and the ESP32 handles physical execution.
### 🔄 How It Works
1. **Voice Command**: The user speaks into the **Mobile App** (e.g., *"Tan ina yara mi"* - Turn on my room light).
2. **Processing**: The app sends the audio to the **Backend**.
3. **Intelligence**:
* **STT**: Audio is transcribed to text (e.g., "Tan ina yara mi").
* **Reasoning**: The N-ATLaS model (finetuned LLM) analyzes the text, detects the language (`yo`), intent (`INSTRUCTION`), action (`TURN_ON`), and device (`LIGHT`).
* **Response**: The system generates a natural text response in the same language and converts it to audio.
4. **Action**: The Backend returns the *Intent* and *Audio* to the App.
5. **Execution**:
* The **App** plays the audio response to the user.
* If an action is required, the **App** directly calls the **ESP32** over the local network (e.g., `POST http:// /light/turn/on`).
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## 📂 Repository Structure
This monorepo contains three distinct components:
### 1. `dara-mobile-app/` (Flutter)
The user interface and central controller.
* **Features/Roles**: Voice recording, audio playback, state management (`AppState`), and direct HTTP control of local ESP32 devices.
* **Key Tech**: Flutter, Provider, HTTP, Audio Players.
### 2. `dara-backend/` (FastAPI / Python)
The intelligence layer hosted in the cloud/locally.
* **Features/Roles**: Speech-to-Text (Deepgram/Whisper), Intent Classification (N-ATLaS on Modal), Text-to-Speech (Spitch).
* **Key Tech**: Python, FastAPI, Modal, Spitch.
### 3. ` …