Emo: Emotional Emoji AI Buddy 😄

Overview

Emo is an expressive AI chatbot built with Nuxt on the frontend and Lemonade Server on the backend. It transcribes your speech in real time and dynamically changes its facial expression based on the AI's response.

Features:

• Runs entirely on your local machine via Lemonade Server — no data sent to the cloud
• Real-time speech recognition and transcription
• Dynamic emotion display driven by AI responses
• Thanks to Lemonade Server, you can use a GPU (NVIDIA/AMD) or a Ryzen AI NPU (AI 300 series and later) for better performance

Limitations:

Due to the models currently supported by Lemonade Server, the following constraints apply:

• English only — The TTS model (kokoro-v1) is trained on English.
• Speech recognition latency — Whisper currently runs on CPU only, so it can be hard to achieve both low latency and high accuracy at the same time

Quick Start

Install Emo

Install Emo by downloading the latest release from the Releases page.

Windows users:

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SmartScreen on Windows may block the app since it's not signed. If that happens, click "More info" and then "Run anyway". Or it may be better to build the executable yourself by following the instructions in the Development section below 😏

• emo_***_portable.exe is the portable version that doesn't require installation. You can run it directly. But you may need to install the required Visual C++ Redistributable if you don't have it already.
• emo_***_setup.exe is the installer version.

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Linux users:

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• emo_***_amd64.AppImage is the x64 portable version that doesn't require installation.
• emo_***_aarch64.AppImage is the arm64 portable version that doesn't require installation.

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macOS users:

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NOTE: Mac version has not been tested yet. If you have tried it and it works, please let me know 😄

Only Arm (Apple Silicon) Macs are supported.

Like Windows, macOS may block the app since it's not signed. You can bypass this by right-clicking the app, selecting "Open", and then confirming to open it.

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Start Lemonade Server

Launch Lemonade Server and load the following models:

Role	Model
LLM with tool-calling	Qwen3.5-9B-GGUF (or any model suited to your environment)
Speech Recognition	Whisper-Base
TTS	kokoro-v1

NOTE: If you load different models in Lemonade Server, make sure to select them in Emo's Settings.

Uninstall

You can uninstall Emo according to the standard procedure for your OS.

However, Emo's configuration file is stored separately and won't be removed automatically. You can delete it manually if you want to remove all settings:

• Windows: C:\Users\<User>\AppData\Roaming\com.github.ryomo.emo
• Linux: /home/<user>/.config/com.github.ryomo.emo
• macOS: /Users/<user>/Library/Application Support/com.github.ryomo.emo

Troubleshooting

WSL networking issue

If you run Lemonade Server on Windows and Emo inside WSL, Emo may not be able to reach the server. To fix this, open WSL Settings and set Networking Mode to Mirrored.

"Enable Thinking" option doesn't work

If you disable "Enable Thinking" in settings, but the model still seems to be "thinking" and takes a long time to respond, set --chat-template-kwargs '{"enable_thinking": false}' to "LLAMACPP ARGUMENTS" in Lemonade Server's model configuration.

Development

Setup

npm install

# pnpm
pnpm install

Run the App in your Browser

npm run dev

# pnpm
pnpm dev

Open http://localhost:3000/ in your browser.

NOTE: In this mode, app settings do not persist. Settings changes won't be saved to disk.

Build Executable with Tauri

First, make sure you have the Tauri prerequisites installed, then run:

npm run tauri dev

# pnpm
pnpm tauri dev

This will launch the app in development mode with Tauri.

If everything works fine, you can proceed to build the production executable:

npm run tauri build

# pnpm
pnpm tauri build

The built executable will be located in src-tauri/target/release/.

Release Process

Below is the process for releasing a new version of Emo on GitHub.
Just a reminder for myself 😄

1. Go to Actions → release → Run workflow, enter the version number (e.g. 1.2.3), and run it.
   • This automatically updates src-tauri/tauri.conf.json and src-tauri/Cargo.toml, commits the changes, and creates + pushes the v*.*.* tag.
   • Then, the app is built and a draft release is created for each platform.
2. Once the workflow completes, go to the GitHub releases page, find the draft release, review the content, and publish it.
3. Don't forget git pull to update your local repository with the new tag.