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https://github.com/av/harbor

Effortlessly run LLM backends, APIs, frontends, and services with one command.
https://github.com/av/harbor
ai bash cli container docker docker-compose exl2 gguf llm local npm package pypi safetensors self-hosted tool tools
Last synced: 6 days ago
JSON representation
Effortlessly run LLM backends, APIs, frontends, and services with one command.
Host: GitHub
URL: https://github.com/av/harbor
Owner: av
License: apache-2.0
Created: 2024-07-27T18:46:59.000Z (5 months ago)
Default Branch: main
Last Pushed: 2024-11-24T10:40:31.000Z (19 days ago)
Last Synced: 2024-11-24T11:20:35.849Z (19 days ago)
Topics: ai, bash, cli, container, docker, docker-compose, exl2, gguf, llm, local, npm, package, pypi, safetensors, self-hosted, tool, tools
Language: TypeScript
Homepage: https://github.com/av/harbor
Size: 6.39 MB
Stars: 548
Watchers: 8
Forks: 37
Open Issues: 29
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project

awesome-ai-tools - Harbor - run LLM backends, APIs, frontends, and services with one command (Other / Music)
trackawesomelist - Harbor (⭐458) - run LLM backends, APIs, frontends, and services with one command (Recently Updated / [Oct 28, 2024](/content/2024/10/28/README.md))
README

        ![Harbor project logo](https://github.com/av/harbor/raw/main/docs/harbor-2.png)

[![GitHub Tag](https://img.shields.io/github/v/tag/av/harbor)](https://github.com/av/harbor/releases)

[![NPM Version](https://img.shields.io/npm/v/%40avcodes%2Fharbor?labelColor=red&color=white)](https://www.npmjs.com/package/@avcodes/harbor)

[![PyPI - Version](https://img.shields.io/pypi/v/llm-harbor?labelColor=blue)](https://pypi.org/project/llm-harbor/)

![GitHub repo size](https://img.shields.io/github/repo-size/av/harbor)

![GitHub repo file or directory count](https://img.shields.io/github/directory-file-count/av/harbor?type=file&extension=yml&label=compose%20files&color=orange)

[![Visitors](https://api.visitorbadge.io/api/visitors?path=av%2Fharbor&countColor=%23263759&style=flat)](https://visitorbadge.io/status?path=av%2Fharbor)

![GitHub language count](https://img.shields.io/github/languages/count/av/harbor)

[![Discord](https://img.shields.io/badge/Discord-Harbor-blue?logo=discord&logoColor=white)](https://discord.gg/8nDRphrhSF)

Effortlessly run LLM backends, APIs, frontends, and services with one command.

Harbor is a containerized LLM toolkit that allows you to run LLMs and additional services. It consists of a CLI and a companion App that allows you to manage and run AI services with ease.

![Screenshot of Harbor CLI and App together](https://github.com/av/harbor/wiki/harbor-app-3.png)

## Services

##### UIs

[Open WebUI](https://github.com/av/harbor/wiki/2.1.1-Frontend:-Open-WebUI) ⦁︎

[ComfyUI](https://github.com/av/harbor/wiki/2.1.2-Frontend:-ComfyUI) ⦁︎

[LibreChat](https://github.com/av/harbor/wiki/2.1.3-Frontend:-LibreChat) ⦁︎

[HuggingFace ChatUI](https://github.com/av/harbor/wiki/2.1.4-Frontend:-ChatUI) ⦁︎

[Lobe Chat](https://github.com/av/harbor/wiki/2.1.5-Frontend:-Lobe-Chat) ⦁︎

[Hollama](https://github.com/av/harbor/wiki/2.1.6-Frontend:-hollama) ⦁︎

[parllama](https://github.com/av/harbor/wiki/2.1.7-Frontend:-parllama) ⦁︎

[BionicGPT](https://github.com/av/harbor/wiki/2.1.8-Frontend:-BionicGPT) ⦁︎

[AnythingLLM](https://github.com/av/harbor/wiki/2.1.9-Frontend:-AnythingLLM) ⦁︎

[Chat Nio](https://github.com/av/harbor/wiki/2.1.10-Frontend:-Chat-Nio)

##### Backends

[Ollama](https://github.com/av/harbor/wiki/2.2.1-Backend:-Ollama) ⦁︎

[llama.cpp](https://github.com/av/harbor/wiki/2.2.2-Backend:-llama.cpp) ⦁︎

[vLLM](https://github.com/av/harbor/wiki/2.2.3-Backend:-vLLM) ⦁︎

[TabbyAPI](https://github.com/av/harbor/wiki/2.2.4-Backend:-TabbyAPI) ⦁︎

[Aphrodite Engine](https://github.com/av/harbor/wiki/2.2.5-Backend:-Aphrodite-Engine) ⦁︎

[mistral.rs](https://github.com/av/harbor/wiki/2.2.6-Backend:-mistral.rs) ⦁︎

[openedai-speech](https://github.com/av/harbor/wiki/2.2.7-Backend:-openedai-speech) ⦁︎

[faster-whisper-server](https://github.com/av/harbor/wiki/2.2.14-Backend:-Faster-Whisper) ⦁︎

[Parler](https://github.com/av/harbor/wiki/2.2.8-Backend:-Parler) ⦁︎

[text-generation-inference](https://github.com/av/harbor/wiki/2.2.9-Backend:-text-generation-inference) ⦁︎

[LMDeploy](https://github.com/av/harbor/wiki/2.2.10-Backend:-lmdeploy) ⦁︎

[AirLLM](https://github.com/av/harbor/wiki/2.2.11-Backend:-AirLLM) ⦁︎

[SGLang](https://github.com/av/harbor/wiki/2.2.12-Backend:-SGLang) ⦁︎

[KTransformers](https://github.com/av/harbor/wiki/2.2.13-Backend:-KTransformers) ⦁︎

[Nexa SDK](https://github.com/av/harbor/wiki/2.2.15-Backend:-Nexa-SDK)

##### Satellites

[Harbor Bench](https://github.com/av/harbor/wiki/5.1.-Harbor-Bench) ⦁︎

[Harbor Boost](https://github.com/av/harbor/wiki/5.2.-Harbor-Boost) ⦁︎

[SearXNG](https://github.com/av/harbor/wiki/2.3.1-Satellite:-SearXNG) ⦁︎

[Perplexica](https://github.com/av/harbor/wiki/2.3.2-Satellite:-Perplexica) ⦁︎

[Dify](https://github.com/av/harbor/wiki/2.3.3-Satellite:-Dify) ⦁︎

[Plandex](https://github.com/av/harbor/wiki/2.3.4-Satellite:-Plandex) ⦁︎

[LiteLLM](https://github.com/av/harbor/wiki/2.3.5-Satellite:-LiteLLM) ⦁︎

[LangFuse](https://github.com/av/harbor/wiki/2.3.6-Satellite:-langfuse) ⦁︎

[Open Interpreter](https://github.com/av/harbor/wiki/2.3.7-Satellite:-Open-Interpreter) ⦁

︎[cloudflared](https://github.com/av/harbor/wiki/2.3.8-Satellite:-cloudflared) ⦁︎

[cmdh](https://github.com/av/harbor/wiki/2.3.9-Satellite:-cmdh) ⦁︎

[fabric](https://github.com/av/harbor/wiki/2.3.10-Satellite:-fabric) ⦁︎

[txtai RAG](https://github.com/av/harbor/wiki/2.3.11-Satellite:-txtai-RAG) ⦁︎

[TextGrad](https://github.com/av/harbor/wiki/2.3.12-Satellite:-TextGrad) ⦁︎

[Aider](https://github.com/av/harbor/wiki/2.3.13-Satellite:-aider) ⦁︎

[aichat](https://github.com/av/harbor/wiki/2.3.14-Satellite:-aichat) ⦁︎

[omnichain](https://github.com/av/harbor/wiki/2.3.16-Satellite:-omnichain) ⦁︎

[lm-evaluation-harness](https://github.com/av/harbor/wiki/2.3.17-Satellite:-lm-evaluation-harness) ⦁︎

[JupyterLab](https://github.com/av/harbor/wiki/2.3.18-Satellite:-JupyterLab) ⦁︎

[ol1](https://github.com/av/harbor/wiki/2.3.19-Satellite:-ol1) ⦁︎

[OpenHands](https://github.com/av/harbor/wiki/2.3.20-Satellite:-OpenHands) ⦁︎

[LitLytics](https://github.com/av/harbor/wiki/2.3.21-Satellite:-LitLytics) ⦁︎

[Repopack](https://github.com/av/harbor/wiki/2.3.22-Satellite:-Repopack) ⦁︎

[n8n](https://github.com/av/harbor/wiki/2.3.23-Satellite:-n8n) ⦁︎

[Bolt.new](https://github.com/av/harbor/wiki/2.3.24-Satellite:-Bolt.new) ⦁︎

[Open WebUI Pipelines](https://github.com/av/harbor/wiki/2.3.25-Satellite:-Open-WebUI-Pipelines) ⦁︎

[Qdrant](https://github.com/av/harbor/wiki/2.3.26-Satellite:-Qdrant) ⦁︎

[K6](https://github.com/av/harbor/wiki/2.3.27-Satellite:-K6) ⦁︎

[Promptfoo](https://github.com/av/harbor/wiki/2.3.28-Satellite:-Promptfoo) ⦁︎

[Webtop](https://github.com/av/harbor/wiki/2.3.29-Satellite:-Webtop) ⦁︎

[OmniParser](https://github.com/av/harbor/wiki/2.3.30-Satellite:-OmniParser) ⦁︎

[Flowise](https://github.com/av/harbor/wiki/2.3.31-Satellite:-Flowise)

See [services documentation](https://github.com/av/harbor/wiki/2.-Services) for a brief overview of each.

## Blitz Tour

![Diagram outlining Harbor's service structure](https://raw.githubusercontent.com/wiki/av/harbor/harbor-arch-diag.png)

```bash

# Run Harbor with default services:

# Open WebUI and Ollama

harbor up

# Run Harbor with additional services

# Running SearXNG automatically enables Web RAG in Open WebUI

harbor up searxng

# Run additional/alternative LLM Inference backends

# Open Webui is automatically connected to them.

harbor up llamacpp tgi litellm vllm tabbyapi aphrodite sglang ktransformers

# Run different Frontends

harbor up librechat chatui bionicgpt hollama

# Get a free quality boost with

# built-in optimizing proxy

harbor up boost

# Use FLUX in Open WebUI in one command

harbor up comfyui

# Use custom models for supported backends

harbor llamacpp model https://huggingface.co/user/repo/model.gguf

# Shortcut to HF Hub to find the models

harbor hf find gguf gemma-2

# Use HFDownloader and official HF CLI to download models

harbor hf dl -m google/gemma-2-2b-it -c 10 -s ./hf

harbor hf download google/gemma-2-2b-it

# Where possible, cache is shared between the services

harbor tgi model google/gemma-2-2b-it

harbor vllm model google/gemma-2-2b-it

harbor aphrodite model google/gemma-2-2b-it

harbor tabbyapi model google/gemma-2-2b-it-exl2

harbor mistralrs model google/gemma-2-2b-it

harbor opint model google/gemma-2-2b-it

harbor sglang model google/gemma-2-2b-it

# Convenience tools for docker setup

harbor logs llamacpp

harbor exec llamacpp ./scripts/llama-bench --help

harbor shell vllm

# Tell your shell exactly what you think about it

harbor opint

harbor aider

harbor aichat

harbor cmdh

# Use fabric to LLM-ify your linux pipes

cat ./file.md | harbor fabric --pattern extract_extraordinary_claims | grep "LK99"

# Access service CLIs without installing them

harbor hf scan-cache

harbor ollama list

# Open services from the CLI

harbor open webui

harbor open llamacpp

# Print yourself a QR to quickly open the

# service on your phone

harbor qr

# Feeling adventurous? Expose your harbor

# to the internet

harbor tunnel

# Config management

harbor config list

harbor config set webui.host.port 8080

# Create and manage config profiles

harbor profile save l370b

harbor profile use default

# Lookup recently used harbor commands

harbor history

# Eject from Harbor into a standalone Docker Compose setup

# Will export related services and variables into a standalone file.

harbor eject searxng llamacpp > docker-compose.harbor.yml

# Run a build-in LLM benchmark with

# your own tasks

harbor bench run

# Gimmick/Fun Area

# Argument scrambling, below commands are all the same as above

# Harbor doesn't care if it's "vllm model" or "model vllm", it'll

# figure it out.

harbor model vllm

harbor vllm model

harbor config get webui.name

harbor get config webui_name

harbor tabbyapi shell

harbor shell tabbyapi

# 50% gimmick, 50% useful

# Ask harbor about itself

harbor how to ping ollama container from the webui?

```

## Harbor App Demo

https://github.com/user-attachments/assets/a5cd2ef1-3208-400a-8866-7abd85808503

In the demo, Harbor App is used to launch a default stack with [Ollama](./2.2.1-Backend:-Ollama) and [Open WebUI](./2.1.1-Frontend:-Open-WebUI) services. Later, [SearXNG](./2.3.1-Satellite:-SearXNG) is also started, and WebUI can connect to it for the Web RAG right out of the box. After that, [Harbor Boost](./5.2.-Harbor-Boost) is also started and connected to the WebUI automatically to induce more creative outputs. As a final step, Harbor config is adjusted in the App for the [`klmbr`](./5.2.-Harbor-Boost#klmbr---boost-llm-creativity) module in the [Harbor Boost](./5.2.-Harbor-Boost), which makes the output unparseable for the LLM (yet still undetstandable for humans).

## Documentation

- [Installing Harbor](https://github.com/av/harbor/wiki/1.0.-Installing-Harbor)


  Guides to install Harbor CLI and App

- [Harbor User Guide](https://github.com/av/harbor/wiki/1.-Harbor-User-Guide)


  High-level overview of working with Harbor

- [Harbor App](https://github.com/av/harbor/wiki/1.1-Harbor-App)


  Overview and manual for the Harbor companion application

- [Harbor Services](https://github.com/av/harbor/wiki/2.-Services)


  Catalog of services available in Harbor

- [Harbor CLI Reference](https://github.com/av/harbor/wiki/3.-Harbor-CLI-Reference)


  Read more about Harbor CLI commands and options.

  Read about supported services and the ways to configure them.

- [Compatibility](https://github.com/av/harbor/wiki/4.-Compatibility)


  Known compatibility issues between the services and models as well as possible workarounds.

- [Harbor Bench](https://github.com/av/harbor/wiki/5.1.-Harbor-Bench)


  Documentation for the built-in LLM benchmarking service.

- [Harbor Boost](https://github.com/av/harbor/wiki/5.2.-Harbor-Boost)


  Documentation for the built-in LLM optimiser proxy.

- [Harbor Compose Setup](https://github.com/av/harbor/wiki/6.-Harbor-Compose-Setup)


  Read about the way Harbor uses Docker Compose to manage services.

- [Adding A New Service](https://github.com/av/harbor/wiki/7.-Adding-A-New-Service)


  Documentation on bringing more services into the Harbor toolkit.

## Why?

- Convenience factor

- Workflow/setup centralisation

If you're comfortable with Docker and Linux administration - you likely don't need Harbor per se to manage your local LLM environment. However, you're also likely to eventually arrive to a similar solution. I know this for a fact, since I was rocking pretty much similar setup, just without all the whistles and bells.

Harbor is not designed as a deployment solution, but rather as a helper for the local LLM development environment. It's a good starting point for experimenting with LLMs and related services.

You can later eject from Harbor and use the services in your own setup, or continue using Harbor as a base for your own configuration.

## Overview and Features

This project consists of a fairly large shell CLI, fairly small `.env` file and enourmous (for one repo) amount of `docker-compose` files.

#### Features

- Manage local LLM stack with a concise CLI

- Convenience utilities for common tasks (model management, configuration, service debug, URLs, tunnels, etc.)

- Access service CLIs (`hf`, `ollama`, etc.) via Docker without install

- Services are pre-configured to work together (contributions welcome)

- Host cache is shared and reused - Hugging Face, ollama, etc.

- Co-located service configs

- Built-in LLM benchmarking service

- Manage configuration profiles for different use cases

- Eject to run without harbor with `harbor eject`