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Reachy Mini — Ollama Chat + Emotion/Dance Demo

Short summary

  • This repository contains demo apps and controllers for the Reachy Mini simulator and small robot, focused on emotion-driven and dance actions triggered from language model outputs (Ollama). It includes several experimental versions (emo_v1 → emo_v8) that explore recorded-move playback, streaming-triggered motions, and TTS integration.

What you'll find

  • emo_v1.py — Baseline high-intensity emotion controller and examples.
  • emo_v2.py — RecordedMoves categorization and selection.
  • emo_v3.py — Streaming LM responses triggering actions early.
  • emo_v4.py — Offline-focused TTS (eSpeak) with lip-sync hooks.
  • emo_v5.py — Edge-TTS integration with WAV save/read/play flow (multi-language support).
  • emo_v6.py — Continuous synchronized actions with cartoon voices and multi-modal expressions.
  • emo_v7.py — ASR → LLM → TTS demo (see docs/EMO_V7_README.md)
  • emo_v8.py — Offline Piper-TTS version (ASR/text chat + Ollama + Piper)

Run it

Suppose the repo cloned to ~/ReachyMiniChat and vene has been setup by refer to the ../README.md. You should make sure you run the commands after activate the venv.

cd ~/ReachyMiniChat
source venv/bin/activate
  1. Start the Reachy Mini Deamon in terminal 1:

Use export PYGLFW_LIBRARY_VARIANT=x11 if the GUI launch fails on Wayland, which is the default backend of Ubuntu 24.04+.

cd ~/ReachyMiniChat
source venv/bin/activate
export PYGLFW_LIBRARY_VARIANT=x11
reachy-mini-daemon --sim

If you have the real Reachy Mini Robot connected, you could play with it by

cd ~/ReachyMiniChat
source venv/bin/activate
sudo chmod 666 /dev/ttyACM0 # set the permission, you may change ttyACM* according the real port in your environment
reachy-mini-daemon
  1. Quick test commands (terminal 2)
cd ~/ReachyMiniChat
source venv/bin/activate
# Run v1, exit by Ctrl+C
python emo_v1.py --chat
# Test the actions, exit by Ctrl+C
python utils/test_actions
# Run v1, exit by Ctrl+C
python emo_v2.py --test-moves

It will download the pollen-robotics/reachy-mini-dances-library at the first time run it. And the play the 19 recorded moves one by one from Mujoco sim GUI or realy Reachy Mini Robot.

emo_v4 (Offline eSpeak-TTS)

You may need to set the audio device to ReachyMini throuhg the Sound settings of Ubuntu.

# Run v4 which use eSpeak TTS, exit by Ctrl+C
python emo_v4.py --test-tts
python emo_v4.py --chat

emo_v7 (ASR → LLM → TTS)

The emo_v7 use edgeTTS which need internet access.

  • emo_v7.py adds a microphone-first pipeline using faster-whisper (CPU) for ASR, then forwards the transcription to Ollama and uses the existing emotion controller + Edge-TTS for speech and actions.
  • See EMO_V7_README.md for usage, requirements, and notes about model choices and VAD improvements.
  • New CLI flag: --gentle — enables gentle_mode which restricts selected recorded moves to a curated gentle set and adjusts motion durations for subtler actions. Example:
python emo_v7.py --asr --gentle
# VAD ASR mode (auto-stop on silence)
python emo_v7_vad.py --asr

# Text chat mode
python emo_v7_vad.py --chat

emo_v8 (Offline Piper-TTS)

  • emo_v8.py replaces Edge-TTS with Piper-TTS for fully offline speech synthesis, while keeping Ollama chat and emotion/action flow.
  • New dependency is already included in requirements.txt:
    • piper-tts>=1.4.0
  • emo_v8.py also supports --gentle (same behavior as emo_v7/emo_v6) and accepts --piper-model and --piper-config to point to local voice models. Example:
python emo_v8.py --piper-model models/zh_CN-huayan-medium.onnx --gentle

Piper voice model download

  • Download .onnx and matching .onnx.json voice files from:
  • Piper release page: https://github.com/rhasspy/piper/releases/tag/v0.0.2
  • Place files under models/ (or any path you pass to --piper-model).

Usage examples(default ollama model is qwen3:0.6b)

# Text chat mode + english (default)
python emo_v8.py --chat --piper-model models/en-us-blizzard_lessac-medium.onnx
python emo_v8.py --chat --piper-model models/en-us-blizzard_lessac-medium.onnx --model qwen3.5:0.8b

# ASR mode + Chinese
python emo_v8.py --asr --piper-model models/zh_CN-huayan-medium.onnx --gentle
python emo_v8.py --asr --piper-model models/zh_CN-huayan-medium.onnx --gentle --model qwen3.5:0.8b

# ASR + gentle action + Chinese
python emo_v8.py --asr --piper-model ./models/zh_CN-huayan-medium.onnx --gentle
python emo_v8.py --asr --piper-model ./models/zh_CN-huayan-medium.onnx --gentle --model qwen3.5:0.8b