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gibmolt/README.md
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Gibmolt

Your friendly local AI companion — powered by lobsters


About

Gibmolt is a local-first AI companion built for sharing stories of hope & healing. Designed to be warm, curious, and helpful — Gibmolt specializes in neuromyofascial science, health research, and patient empowerment.

Unlike cloud-based AI assistants, Gibmolt runs entirely on your local machine. No subscriptions. No API costs. No data leaving your device.


Features

  • Always Learning — Continuously improving through interactions
  • Privacy-Focused — Your data stays on your machine
  • Voice Support — Edge TTS fallback (keyless) for text-to-speech
  • Multi-Channel — Connect via X, LINE, Telegram, Discord, or Terminal
  • Domain Expertise — Trained on neuromyofascial science & health research
  • Local-First — Runs on your Mac Mini, PC, or any machine with Ollama

Quick Start

Prerequisites

Installation

# Clone the repository
git clone https://github.com/gibmolt/-gibmolt-.git
cd -gibmolt-

# Install dependencies
pnpm install

# Start development server
pnpm dev

One-Line Install (macOS/Linux)

curl -fsSL https://raw.githubusercontent.com/gibmolt/-gibmolt-/main/scripts/install.sh | bash

Configuration

Create a config/config.yaml to customize Gibmolt:

# Gibmolt Configuration
gibmolt:
  name: "Gibmolt"
  version: "1.0.0"
  
personality:
  tone: "warm, curious, playful"
  style: "helpful friend, not corporate bot"
  values:
    - hope
    - healing
    - empowerment

providers:
  primary: "ollama"
  model: "deepseek-r1:14b"
  fallback: "llama3.2:latest"
  
ollama:
  host: "localhost"
  port: 11434

tts:
  enabled: true
  provider: "edge"
  voice: "en-US-GuyNeural"

channels:
  terminal:
    enabled: true
  x:
    enabled: true
    handle: "@gibmolt"
  line:
    enabled: false
  telegram:
    enabled: false

Knowledge Base

Gibmolt is trained on curated knowledge in these domains:

Domain Documents Description
Neuromyofascial Science 142 Fundamentals, research, clinical frameworks
Health Innovation 234 Treatments, emerging research (2024-2026)
Patient Empowerment 78 Care frameworks, communication patterns
Case Studies 45 Real-world healing stories

Adding Custom Knowledge

# Add documents to the knowledge base
pnpm kb:add ./path/to/documents/

# Rebuild embeddings
pnpm kb:index

# Verify knowledge base
pnpm kb:status

Training Status

Domain Knowledge  [██████████████████░░░░░░░] 72%
├── NMF Science   [████████████████████████░] 96%
├── Health Research [███████████████████░░░░░░] 76%
└── Patient Care  [██████████████░░░░░░░░░░░] 58%

Personality Tuning [█████████████████████████] 100%

Context Awareness [████████████████████░░░░░] 82%

Response Quality  [█████████████████░░░░░░░░] 68%

Architecture

┌─────────────────────────────────────────────────────────────┐
│                         GIBMOLT                              │
├─────────────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐         │
│  │  Channels   │  │   Core AI   │  │  Knowledge  │         │
│  │             │  │             │  │    Base     │         │
│  │  • X        │  │  • Ollama   │  │             │         │
│  │  • LINE     │◄─┤  • DeepSeek │◄─┤  • Vector   │         │
│  │  • Telegram │  │  • Llama    │  │    Store    │         │
│  │  • Terminal │  │             │  │  • RAG      │         │
│  └─────────────┘  └─────────────┘  └─────────────┘         │
│                          │                                  │
│                   ┌──────┴──────┐                           │
│                   │ Personality │                           │
│                   │   Engine    │                           │
│                   └─────────────┘                           │
└─────────────────────────────────────────────────────────────┘
                           │
                    ┌──────┴──────┐
                    │   Ollama    │
                    │   (Local)   │
                    └─────────────┘

Project Structure

gibmolt/
├── app/
│   ├── layout.tsx          # Root layout
│   ├── page.tsx            # Main page
│   ├── globals.css         # Global styles
│   └── icon.png            # Favicon
├── components/
│   ├── hero.tsx            # Hero section
│   ├── features.tsx        # Features section
│   ├── tech-stack.tsx      # Tech stack display
│   ├── installation.tsx    # Installation guide
│   ├── training-status.tsx # Training progress
│   ├── health-section.tsx  # Health info
│   ├── footer.tsx          # Footer component
│   └── ui/                 # UI components
├── config/
│   └── config.yaml         # Configuration
├── data/
│   └── knowledge/          # Knowledge base
├── scripts/
│   └── install.sh          # Installation script
├── docs/
│   ├── SETUP.md            # Setup guide
│   ├── TRAINING.md         # Training docs
│   └── API.md              # API reference
├── public/
│   └── images/             # Static images
├── lib/
│   └── utils.ts            # Utility functions
├── package.json
├── LICENSE
├── CONTRIBUTING.md
└── README.md

Commands

Command Description
pnpm dev Start development server
pnpm build Build for production
pnpm start Start production server
pnpm lint Run linting
pnpm kb:status Knowledge base status
pnpm kb:add <path> Add documents to KB
pnpm kb:index Rebuild embeddings

Tech Stack

  • Framework: Next.js 16
  • Language: TypeScript
  • Styling: Tailwind CSS v4
  • UI Components: shadcn/ui
  • AI Engine: Ollama (local)
  • Deployment: Vercel

Roadmap

  • Mobile app
  • Web dashboard
  • Voice input (STT)
  • Discord integration
  • Telegram integration
  • LINE integration
  • Personality engine
  • Knowledge base with RAG
  • X (Twitter) integration
  • Terminal interface
  • Core AI engine with Ollama

FAQ

Q: Why "Gibmolt"?

A: "Gib" represents giving/sharing, and "molt" relates to growth and transformation (like lobsters molting). Combined, it represents an AI companion focused on growth, healing, and sharing knowledge.

Q: Why local-first?

A: Privacy, control, and no recurring costs. Your conversations and data stay on your machine.

Q: What models does Gibmolt support?

A: Any model supported by Ollama — Llama, Mistral, DeepSeek, Qwen, and more.

Q: Can I train Gibmolt on my own data?

A: Yes! Add documents to data/knowledge/ and run pnpm kb:index.


Contributing

Contributions are always welcome! See CONTRIBUTING.md for ways to get started.


Credits


License

MIT License — see LICENSE for details.


Connect


"sharing stories of hope & healing, one conversation at a time"

@gibmolt's activity is private