Vessel

A modern, feature-rich web interface for Ollama

Features • Screenshots • Quick Start • Installation • Configuration • Development

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Features

Core Chat Experience

• Real-time streaming — Watch responses appear token by token
• Conversation history — All chats stored locally in IndexedDB
• Message editing — Edit any message and regenerate responses with branching
• Branch navigation — Explore different response paths from edited messages
• Markdown rendering — Full GFM support with tables, lists, and formatting
• Syntax highlighting — Beautiful code blocks powered by Shiki with 100+ languages
• Dark/Light mode — Seamless theme switching with system preference detection

Built-in Tools (Function Calling)

Vessel includes five powerful tools that models can invoke automatically:

Tool	Description
Web Search	Search the internet for current information, news, weather, prices
Fetch URL	Read and extract content from any webpage
Calculator	Safe math expression parser with functions (sqrt, sin, cos, log, etc.)
Get Location	Detect user location via GPS or IP for local queries
Get Time	Current date/time with timezone support

Model Management

• Model browser — Browse, search, and pull models from Ollama registry
• Live status — See which models are currently loaded in memory
• Quick switch — Change models mid-conversation
• Model metadata — View parameters, quantization, and capabilities

Developer Experience

• Beautiful code generation — Syntax-highlighted output for any language
• Copy code blocks — One-click copy with visual feedback
• Scroll to bottom — Smart auto-scroll with manual override
• Keyboard shortcuts — Navigate efficiently with hotkeys

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Screenshots

Clean, modern chat interface	Syntax-highlighted code output
Integrated web search with styled results	Light theme for daytime use
Browse and manage Ollama models

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Quick Start

Prerequisites

• Docker and Docker Compose
• Ollama installed and running locally

One-Line Install

curl -fsSL https://somegit.dev/vikingowl/vessel/raw/main/install.sh | bash

Or Clone and Run

git clone https://somegit.dev/vikingowl/vessel.git
cd vessel
./install.sh

The installer will:

• Check for Docker, Docker Compose, and Ollama
• Start the frontend and backend services
• Optionally pull a starter model (llama3.2)

Once running, open http://localhost:7842 in your browser.

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Installation

Option 1: Install Script (Recommended)

The install script handles everything automatically:

./install.sh              # Install and start
./install.sh --update     # Update to latest version
./install.sh --uninstall  # Remove installation

Requirements:

• Ollama must be installed and running locally
• Docker and Docker Compose
• Linux or macOS

Option 2: Docker Compose (Manual)

# Make sure Ollama is running first
ollama serve

# Start Vessel
docker compose up -d

Option 3: Manual Setup (Development)

Prerequisites

• Node.js 20+
• Go 1.24+
• Ollama running locally

Frontend

cd frontend
npm install
npm run dev

Frontend runs on http://localhost:5173

Backend

cd backend
go mod tidy
go run cmd/server/main.go -port 9090

Backend API runs on http://localhost:9090

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Configuration

Environment Variables

Frontend

Variable	Default	Description
OLLAMA_API_URL	http://localhost:11434	Ollama API endpoint
BACKEND_URL	http://localhost:9090	Vessel backend API

Backend

Variable	Default	Description
OLLAMA_URL	http://localhost:11434	Ollama API endpoint
PORT	8080	Backend server port
GIN_MODE	debug	Gin mode (debug, release)

Docker Compose Override

Create docker-compose.override.yml for local customizations:

services:
  frontend:
    environment:
      - CUSTOM_VAR=value
    ports:
      - "3000:3000"  # Different port

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Architecture

vessel/
├── frontend/               # SvelteKit 5 application
│   ├── src/
│   │   ├── lib/
│   │   │   ├── components/ # UI components
│   │   │   ├── stores/     # Svelte 5 runes state
│   │   │   ├── tools/      # Built-in tool definitions
│   │   │   ├── storage/    # IndexedDB (Dexie)
│   │   │   └── api/        # API clients
│   │   └── routes/         # SvelteKit routes
│   └── Dockerfile
│
├── backend/                # Go API server
│   ├── cmd/server/         # Entry point
│   └── internal/
│       ├── api/            # HTTP handlers
│       │   ├── fetcher.go  # URL fetching with wget/curl/chromedp
│       │   ├── search.go   # Web search via DuckDuckGo
│       │   └── routes.go   # Route definitions
│       ├── database/       # SQLite storage
│       └── models/         # Data models
│
├── docker-compose.yml      # Production setup
└── docker-compose.dev.yml  # Development with hot reload

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Tech Stack

Frontend

• SvelteKit 5 — Full-stack framework
• Svelte 5 — Runes-based reactivity
• TypeScript — Type safety
• Tailwind CSS — Utility-first styling
• Skeleton UI — Component library
• Shiki — Syntax highlighting
• Dexie — IndexedDB wrapper
• Marked — Markdown parser
• DOMPurify — XSS sanitization

Backend

• Go 1.24 — Fast, compiled backend
• Gin — HTTP framework
• SQLite — Embedded database
• chromedp — Headless browser

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Development

Running Tests

# Frontend unit tests
cd frontend
npm run test

# With coverage
npm run test:coverage

# Watch mode
npm run test:watch

Type Checking

cd frontend
npm run check

Development Mode

Use the dev compose file for hot reloading:

docker compose -f docker-compose.dev.yml up

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API Reference

Backend Endpoints

Method	Endpoint	Description
POST	/api/v1/proxy/search	Web search via DuckDuckGo
POST	/api/v1/proxy/fetch	Fetch URL content
GET	/api/v1/location	Get user location from IP
GET	/api/v1/models/registry	Browse Ollama model registry
GET	/api/v1/models/search	Search models
POST	/api/v1/chats/sync	Sync conversations

Ollama Proxy

All requests to /ollama/* are proxied to the Ollama API, enabling CORS.

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Roadmap

• Docker Ollama support (for systems without local Ollama)
• Image generation (Stable Diffusion, Hugging Face models)
• Hugging Face integration
• Voice input/output
• Multi-user support
• Plugin system

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Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

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License

Copyright (C) 2026 VikingOwl

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.

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Made with Ollama and Svelte