Skillget

local-ai-toolkit

agent
Security Audit
Pass
Health Pass
  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Community trust — 16 GitHub stars
Code Pass
  • Code scan — Scanned 3 files during light audit, no dangerous patterns found
Permissions Pass
  • Permissions — No dangerous permissions requested
Purpose
This project provides a self-hosted AI toolkit that bundles an LLM gateway, workflow automation, and a chat interface, all running locally via Docker Compose and backed by a shared PostgreSQL database.

Security Assessment
The automated code scan found no dangerous patterns, hardcoded secrets, or excessive permissions in the tracked scripts. However, running this toolkit involves significant operational considerations. Because it orchestrates Docker containers, it inherently executes shell commands and manages local infrastructure. Network requests are made to external services, specifically requiring an API key to connect to Ollama cloud models. The project explicitly warns that it is for local experimentation only; it lacks TLS, authentication proxies, and ships with default database credentials in the `.env` template. Users must generate and manage their own secure passwords and API keys. Overall risk is rated as Medium—safe for local development, but risky if exposed to a public network.

Quality Assessment
The project is highly active, with its most recent push occurring today. It utilizes the permissive and standard MIT license. While the repository is relatively new and has a modest community trust indicator with 16 GitHub stars, the project structure is clean, well-documented, and straightforward to audit.

Verdict
Safe to use locally, but use with caution if you plan to expose the services beyond your local machine.
SUMMARY

A self-hosted AI toolkit running locally via Docker Compose, bundling an LLM gateway, workflow automation, and a chat UI — all backed by a shared PostgreSQL database.

README.md

AI Local Toolkit

A self-hosted AI toolkit running locally via Docker Compose, bundling an LLM gateway, workflow automation, and a chat UI — all backed by a shared PostgreSQL database.

All free Ollama Cloud models are pre-configured out of the box. Just create an Ollama account, generate an API key, and you're ready to go. Additional models and providers can be added later through LiteLLM.

⚠️ Warning: This project is intended for local development and experimentation only. It does not implement any security hardening (no TLS, no authentication proxy, default credentials, etc.). If you choose to deploy it in a production environment, you do so entirely at your own risk.

Services

Service Description URL
LiteLLM LLM proxy / API gateway http://localhost:4000
n8n Workflow automation http://localhost:5678
Open WebUI Chat interface for LLMs http://localhost:3000
PostgreSQL Shared database (LiteLLM + n8n) localhost:5432

Prerequisites

  • Docker & Docker Compose
  • A Docker network named ai-toolkit — used so all containers can communicate with each other simply by container name (e.g. http://litellm:4000):
    docker network create ai-toolkit

Quick Start

  1. Clone the repository

  2. Create your .env file

    cp .env.dist .env

    Edit .env and fill in the required values:

    # Postgres
POSTGRES_DB=postgres
POSTGRES_USER=postgres
POSTGRES_PASSWORD=<your_secure_password>

# LiteLLM
LITELLM_MASTER_KEY=sk-<generate_a_key>
LITELLM_SALT_KEY=sk-<generate_a_key>
OLLAMA_API_KEY=<your_ollama_api_key>

# General
TZ=<YOUR_TIMEZONE>

  3. Configure LiteLLM models

    Edit config/litellm_config.yaml to add or modify the models available through the proxy.

  4. Start the stack

    docker compose up -d

  5. Verify

    docker compose ps

Project Structure

.
├── .env                          # Environment variables (git-ignored)
├── .env.dist                     # Environment variables template
├── docker-compose.yml            # Service definitions
├── config/
│   ├── init_db.sh                # Creates n8n & litellm databases on first run
│   └── litellm_config.yaml       # LiteLLM model configuration
└── README.md

Configuration

LiteLLM

LiteLLM acts as a unified API gateway to multiple LLM providers. Models are configured in config/litellm_config.yaml. The admin UI is available at http://localhost:4000/ui.

Authentication uses the LITELLM_MASTER_KEY defined in your .env file.

n8n

n8n provides workflow automation with a visual editor at http://localhost:5678. It uses PostgreSQL for persistent storage.

Open WebUI

Open WebUI provides a ChatGPT-like interface at http://localhost:3000. Connect it to LiteLLM by configuring http://litellm:4000 as the OpenAI-compatible API endpoint (with your LITELLM_MASTER_KEY as the API key).

PostgreSQL

A single PostgreSQL 16 instance is shared by LiteLLM and n8n. The config/init_db.sh script automatically creates the n8n and litellm databases on first initialization.

Note: The init script only runs when the postgres-data volume is created for the first time. To re-run it, remove the volume:

docker compose down
docker volume rm toolkit_postgres-data
docker compose up -d

Useful Commands

# Start all services
docker compose up -d

# Stop all services
docker compose down

# View logs
docker compose logs -f

# View logs for a specific service
docker compose logs -f litellm

# Restart a single service
docker compose restart n8n

# Reset everything (removes all data)
docker compose down -v
docker compose up -d

Networking

All services communicate over a shared Docker network named ai-toolkit. Internal service hostnames:

Hostname Port
postgres 5432
litellm 4000
n8n 5678
openwebui 8080

Reviews (0)

No results found