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my-neuro

calendar_todayAdded Jan 28, 2026
categoryAgent & Tooling
codeOpen Source
PythonTypeScriptElectron桌面应用PyTorch大语言模型LangChainFastAPIMultimodalTransformersRAGAI AgentsChromaDBNatural Language ProcessingAgent & ToolingKnowledge Management, Retrieval & RAGModel Training & InferenceComputer Vision & Multimodal

A customizable AI desktop companion project with character settings, voice conversations, long-term memory capabilities, and sub-1-second response times. Integrates with Live2D models for visual presentation.

One-Minute Overview#

My-Neuro is an open-source project that lets you create your own AI desktop companion with customizable characters and voice conversations featuring sub-1-second response times. The project includes long-term memory, visual recognition, voice cloning, and LLM training capabilities, with integration for various Live2D customizations.

Core Value: Create personalized AI companions with human-like interactive experiences

Quick Start#

Installation Difficulty: Medium - Requires AI/LLM knowledge and Python experience, with multiple components to configure

# Clone the project from GitHub
git clone https://github.com/morettt/my-neuro.git

Is this suitable for me?

  • ✅ Need personalized AI assistant: Supports custom character appearance, personality, and voice
  • ✅ Gaming interaction: Supports various gaming companion features like "You Draw I Guess", Monopoly, etc.
  • ✅ Local deployment: Supports fully local inference without third-party API dependencies
  • ❌ Quick deployment: Requires a complex configuration process
  • ❌ Low-technical users: Requires AI model knowledge and programming basics

Core Capabilities#

1. Ultra-Low Latency Response - Realistic Conversation Experience#

  • Fully local inference with conversation delays under 1 second, approaching real human conversation Actual Value: Smooth and natural conversation experience without common AI delays

2. Long-Term Memory System - Building Deep Relationships#

  • Remembers user's key information, personality traits, and preferences Actual Value: AI gets to know the user over time, providing increasingly personalized interactions

3. Multimodal Interaction - Rich Communication Methods#

  • Supports voice, text, visual recognition, and various interaction methods Actual Value: Users can choose their most comfortable communication method, and AI can select the best interaction mode based on context

4. Emotional Simulation System - Human-Like Emotional Expression#

  • Simulates real human emotional changes with independent emotional states Actual Value: AI responses are no longer cold but carry emotion and personality

5. Gaming Companion Features - Immersive Entertainment Experience#

  • Supports multiple gaming companions including "You Draw I Guess", Monopoly, Galgame, Minecraft, etc. Actual Value: AI can serve as a gaming partner, providing new gaming experiences and interactions

Tech Stack & Integration#

Development Language: Python Key Dependencies: GPT-SoVITS (TTS), mindcraft (Minecraft AI), playwright-mcp (web operations), MemOS (memory system) Integration Method: Library/SDK

Maintenance Status#

  • Development Activity: Actively developed with a clear feature roadmap from the author
  • Recent Updates: Recent new releases planned with more features to be implemented in coming months
  • Community Response: Has gained some community support and financial sponsorship

Documentation & Learning Resources#

  • Documentation Quality: Basic, with official website guidance
  • Official Documentation: 点我进官网 (Official Website)
  • Example Code: None, but includes LLM-studio folder with local model inference and fine-tuning guidance

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