README.md

metadata

title: Echo
emoji: 🤖
colorFrom: indigo
colorTo: purple
sdk: static
pinned: false
license: mit
short_description: A companion robot that remembers you and grows with you
tags:
  - reachy_mini
  - reachy_mini_python_app
  - companion
  - memory
  - ai

Reachy Echo

A companion robot that remembers you and grows with you.

What Makes Echo Different

Most robot apps treat the robot as a voice interface with decorative movement. Echo is different:

Feature	Traditional	Echo
Memory	Forgets everything	Remembers your name, preferences, conversations
Initiative	Waits for commands	Greets you, suggests breaks, celebrates wins
Models	Single provider	18+ models via LiteLLM (swap anytime)
Movement	Decorative	Communicates emotion and state

Quick Start

Install

cd ~/apps/reachy/apps/echo
pip install -e .

Run (Simulation Mode)

python -m reachy_mini_echo --sim

Open http://localhost:7861

Run (Real Robot)

With the Reachy daemon running:

• Echo appears in the Reachy Mini dashboard
• Or access directly at http://localhost:7861

Features

Memory System

Echo remembers across sessions:

• Your name and preferences
• Past conversations and topics
• Work patterns and habits

Try saying:

• "My name is Alex"
• "I'm a software engineer"
• "What do you know about me?"

Proactive Behaviors

Behavior	What it does	When
Morning Greeting	Personalized hello	First appearance, 6-11am
Work Break Reminder	Suggests a stretch	After 2 hours of work
Build Celebration	Excited dance	When your code builds
Build Support	Sympathetic response	When builds fail
Return Greeting	Welcome back	After 30+ min absence

Model Selection

Switch between 18+ models instantly:

Model	Best for
llama-3.3-70b-cerebras	Fast local inference (default)
claude-opus-4.5-openrouter	Most capable
gpt-5.2-openrouter	Latest GPT
gemini-3-pro-openrouter	Multimodal
qwen-3-235b-cerebras	Large context

Configuration

Environment variables (optional):

# LiteLLM server (defaults to DGX)
export LITELLM_URL=http://your-litellm-server:4000
export LITELLM_API_KEY=your-key

# Default model
export LITELLM_MODEL=llama-3.3-70b-cerebras

UI Overview

┌─────────────────────────────────────────────────────┐
│  🤖 Reachy Echo                                     │
│  A companion that remembers you and grows with you  │
├─────────────────────────────┬───────────────────────┤
│                             │ Status: 🟢 Connected  │
│  Conversation               │                       │
│  ─────────────              │ Model: [dropdown]     │
│  User: Hi there!            │                       │
│  Echo: Hello! How are you?  │ Memory:               │
│                             │ Facts: 3 | Sessions: 5│
│                             │                       │
│  [Type a message...]  [Send]│ Proactive Behaviors:  │
│                             │ ☑ Morning Greeting    │
│                             │ ☑ Work Break Reminder │
│                             │ ☑ Build Celebration   │
│                             │                       │
│                             │ [Clear] [Forget Me]   │
└─────────────────────────────┴───────────────────────┘

Architecture

reachy_mini_echo/
├── main.py           # ReachyMiniEcho app class
├── providers/        # LLM backends (LiteLLM)
├── memory/           # SQLite + fact extraction
└── proactive/        # Trigger/behavior engine

Development

See CLAUDE.md for detailed architecture and development guide.

Adding Behaviors

1. Create behavior class in proactive/behaviors.py
2. Implement execute(echo) method
3. Create trigger in proactive/triggers.py
4. Register in proactive/engine.py

Memory Fact Extraction

Echo automatically extracts facts from conversation:

• "My name is X" → stores name
• "I prefer X" → stores preference
• "I work at X" → stores employer

Privacy

• All data stored locally in data/memory.db
• "Forget Me" button clears personal data
• No cloud storage of conversations
• Local models available for full privacy

License

MIT