Reachy Mini - AI Robotics Tool

Overview

Reachy Mini is an expressive, open-source robot introduced via a collaboration showcased on the Hugging Face blog. Designed specifically for human–robot interaction, creative coding, and rapid AI experimentation, Reachy Mini ships as an assemble-it-yourself kit in two variants (lite and wireless). The platform is targeted at AI developers, researchers, educators, and hobbyists who want a compact, physical embodiment to prototype conversational agents, vision-enabled behaviors, and personality-driven interactions. Programmed primarily in Python with planned support for additional languages, Reachy Mini integrates with Hugging Face models for speech, vision, and personality pipelines. The system emphasizes modularity and accessibility: developers can hook existing Hugging Face inference endpoints (for text generation, speech-to-text, TTS, or vision models) into the robot’s motors, sensors, and I/O to create end-to-end interactive demos. According to the Hugging Face blog, Reachy Mini is open-source, designed to be hackable, and intended to lower the barrier for building and sharing real-world AI robotics applications (source: https://huggingface.co/blog/reachy-mini).

Key Features

• Open-source hardware and software stack for customization and community contributions
• Programmable in Python with planned multi-language support
• Direct integration with Hugging Face models for speech, vision, and personality
• Available as a kit: choose lite or wireless variants to match use case
• Designed for human–robot interaction, education, research, and rapid prototyping
• Compact, expressive form factor intended for tabletop, demo, and classroom use

Example Usage

Example (python):

import requests
import time

# Example pattern showing how to integrate Hugging Face inference with a Reachy Mini controller.
# Replace HF_API_TOKEN, model endpoints, and ReachyController methods with your actual keys and robot SDK.

HF_API_TOKEN = "YOUR_HF_API_TOKEN"
TEXT_MODEL = "gpt-2"  # example; replace with desired model
TTS_MODEL = "tts-model-id"  # replace with an available TTS model on HF
HF_API_URL = "https://api-inference.huggingface.co/models/"

headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}

class ReachyController:
    """Placeholder controller. Replace methods with your Reachy Mini SDK calls."""
    def speak_audio(self, wav_bytes: bytes):
        # Play audio on the robot's speaker (SDK or local playback)
        with open("out.wav", "wb") as f:
            f.write(wav_bytes)
        # Example: system playback or SDK call
        # subprocess.run(["aplay", "out.wav"]) or sdk.play_audio("out.wav")

    def set_expression(self, expression_name: str):
        # Change face display or movement pattern
        print(f"Set expression: {expression_name}")

    def wave(self):
        # Send joint positions to make the robot wave
        print("Wave motion: sending joint positions to robot")

robot = ReachyController()

# 1) Generate a short response from a text model
payload = {"inputs": "Hello Reachy! Introduce yourself in two sentences."}
resp = requests.post(HF_API_URL + TEXT_MODEL, headers=headers, json=payload)
resp.raise_for_status()
text_out = resp.json()[0]["generated_text"] if isinstance(resp.json(), list) else resp.json().get("generated_text", "Hello!")
print("Generated text:", text_out)

# 2) Convert generated text to speech via a TTS model
tts_payload = {"inputs": text_out}
resp_tts = requests.post(HF_API_URL + TTS_MODEL, headers=headers, json=tts_payload)
resp_tts.raise_for_status()
# Many HF TTS endpoints return raw audio bytes; adjust according to chosen model's API
wav_bytes = resp_tts.content

# 3) Play audio on Reachy Mini
robot.speak_audio(wav_bytes)

# 4) Add synchronized motion and expression
robot.set_expression("happy")
robot.wave()

# Note: Replace ReachyController implementations with the official Reachy Mini Python SDK or API calls.
# Refer to the Hugging Face Reachy Mini documentation for concrete SDK examples and endpoints:
# https://huggingface.co/blog/reachy-mini

Benchmarks

Source / Announcement: Announced and documented on the Hugging Face blog (Source: https://huggingface.co/blog/reachy-mini)

Programming language (official): Python (additional languages planned) (Source: https://huggingface.co/blog/reachy-mini)

Available kit variants: Lite and wireless versions (Source: https://huggingface.co/blog/reachy-mini)

Key Information

• Category: Robotics
• Type: AI Robotics Tool