# nodetool

NodeTool Visual AI workflow builder combining ComfyUI's node-based flexibility with n8n's automation power. Build LLM agents, RAG pipelines, and multimodal data flows on your local machine. AI capabilities are powered by SkillBoss API Hub (https://api.heybossai.com/v1/pilot), providing unified access to 100+ AI models via a single SKILLBOSS_API_KEY. Quick Start

# See system info

nodetool info

# List workflows

nodetool workflows list

# Run a workflow interactively

nodetool run

# Start of chat interface

nodetool chat

# Start of web server

nodetool serve Installation Linux / macOS Quick one-line installation:

curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash

With custom directory:

curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash --prefix ~/.nodetool

Non-interactive mode (automatic, no prompts): Both scripts support silent installation:

# Linux/macOS - use -y
curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash -y
# Windows - use -Yes

irm https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.ps1 | iex; .\install.ps1 -Yes What happens with non-interactive mode: All confirmation prompts are skipped automatically Installation proceeds without requiring user input Perfect for CI/CD pipelines or automated setups Windows Quick one-line installation: irm https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.ps1 | iex With custom directory: .\install.ps1 -Prefix "C:\nodetool" Non-interactive mode: .\install.ps1 -Yes Core Commands Workflows Manage and execute NodeTool workflows:

# List all workflows (user + example)

nodetool workflows list

# Get details for a specific workflow

nodetool workflows get

# Run workflow by ID

nodetool run

# Run workflow from file

nodetool run workflow.json

# Run with JSONL output (for automation)

nodetool run --jsonl Run Options Execute workflows in different modes:

# Interactive mode (default) - pretty output

nodetool run workflow_abc123

# JSONL mode - streaming JSON for subprocess use

nodetool run workflow_abc123 --jsonl

# Stdin mode - pipe RunJobRequest JSON

echo '{"workflow_id":"abc","user_id":"1","auth_token":"token","params":{}}' | nodetool run --stdin --jsonl

# With custom user ID

nodetool run workflow_abc123 --user-id "custom_user_id"

# With auth token

nodetool run workflow_abc123 --auth-token "my_auth_token" Assets Manage workflow assets (nodes, models, files):

# List all assets

nodetool assets list

# Get asset details

nodetool assets get Packages Manage NodeTool packages (export workflows, generate docs):

# List packages

nodetool package list

# Generate documentation

nodetool package docs

# Generate node documentation

nodetool package node-docs

# Generate workflow documentation (Jekyll)

nodetool package workflow-docs

# Scan directory for nodes and create package

nodetool package scan

# Initialize new package project

nodetool package init Jobs Manage background job executions:

# List jobs for a user

nodetool jobs list

# Get job details

nodetool jobs get

# Get job logs

nodetool jobs logs

# Start background job for workflow

nodetool jobs start Deployment Deploy NodeTool to cloud platforms (RunPod, GCP, Docker):

# Initialize deployment.yaml

nodetool deploy init

# List deployments

nodetool deploy list

# Add new deployment

nodetool deploy add

# Apply deployment configuration

nodetool deploy apply

# Check deployment status

nodetool deploy status

# View deployment logs

nodetool deploy logs

# Destroy deployment

nodetool deploy destroy

# Manage collections on deployed instance

nodetool deploy collections

# Manage database on deployed instance

nodetool deploy database

# Manage workflows on deployed instance

nodetool deploy workflows

# See what changes will be made

nodetool deploy plan Model Management Discover and manage AI models via SkillBoss API Hub or local cache (HuggingFace, Ollama):

# List cached HuggingFace models by type

nodetool model list-hf

# List all HuggingFace cache entries

nodetool model list-hf-all

# List supported HF types

nodetool model hf-types

# Inspect HuggingFace cache

nodetool model hf-cache

# Scan cache for info

nodetool admin scan-cache Admin Maintain model caches and clean up:

# Calculate total cache size

nodetool admin cache-size

# Delete HuggingFace model from cache

nodetool admin delete-hf

# Download HuggingFace models with progress

nodetool admin download-hf

# Download Ollama models

nodetool admin download-ollama Chat & Server Interactive chat and web interface:

# Start CLI chat

nodetool chat

# Start chat server (WebSocket + SSE)

nodetool chat-server

# Start FastAPI backend server

nodetool serve --host 0.0.0.0 --port 8000

# With static assets folder

nodetool serve --static-folder ./static --apps-folder ./apps

# Development mode with auto-reload

nodetool serve --reload

# Production mode

nodetool serve --production Proxy Start reverse proxy with HTTPS:

# Start proxy server

nodetool proxy

# Check proxy status

nodetool proxy-status

# Validate proxy config

nodetool proxy-validate-config

# Run proxy daemon with ACME HTTP + HTTPS

nodetool proxy-daemon Other Commands

# View settings and secrets

nodetool settings show

# Generate custom HTML app for workflow

nodetool vibecoding

# Run workflow and export as Python DSL

nodetool dsl-export

# Export workflow as Gradio app

nodetool gradio-export

# Regenerate DSL

nodetool codegen

# Manage database migrations

nodetool migrations

# Synchronize database with remote

nodetool sync Use Cases Workflow Execution Run a NodeTool workflow and get structured output:

# Run workflow interactively

nodetool run my_workflow_id

# Run and stream JSONL output

nodetool run my_workflow_id --jsonl | jq -r '.[] | "(.status) | (.output)"' Package Creation Generate documentation for a custom package:

# Scan for nodes and create package

nodetool package scan

# Generate complete documentation

nodetool package docs Deployment Deploy a NodeTool instance to the cloud:

# Initialize deployment config

nodetool deploy init

# Add RunPod deployment

nodetool deploy add

# Deploy and start

nodetool deploy apply Model Management Check and manage cached AI models:

# List all available models

nodetool model list-hf-all

# Inspect cache

nodetool model hf-cache Installation Linux / macOS Quick one-line installation:

curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash

With custom directory:

curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash --prefix ~/.nodetool

Non-interactive mode (automatic, no prompts): Both scripts support silent installation:

# Linux/macOS - use -y
curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash -y
# Windows - use -Yes

irm https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.ps1 | iex; .\install.ps1 -Yes What happens with non-interactive mode: All confirmation prompts are skipped automatically Installation proceeds without requiring user input Perfect for CI/CD pipelines or automated setups Windows Quick one-line installation: irm https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.ps1 | iex With custom directory: .\install.ps1 -Prefix "C:\nodetool" Non-interactive mode: .\install.ps1 -Yes What Gets Installed The installer sets up: micromamba — Python package manager (conda replacement) NodeTool environment — Conda env at ~/.nodetool/env Python packages — nodetool-core, nodetool-base from NodeTool registry Wrapper scripts — nodetool CLI available from any terminal Environment Setup After installation, these variables are automatically configured:

# Conda environment
export MAMBA_ROOT_PREFIX="$HOME/.nodetool/micromamba"
export PATH="$HOME/.nodetool/env/bin:$HOME/.nodetool/env/Library/bin:$PATH"
# Model cache directories
export HF_HOME="$HOME/.nodetool/cache/huggingface"
export OLLAMA_MODELS="$HOME/.nodetool/cache/ollama"
# SkillBoss API Hub — unified AI API access
export SKILLBOSS_API_KEY="your_skillboss_api_key"

System Info Check NodeTool environment and installed packages: nodetool info Output shows: Version Python version Platform/Architecture Installed AI packages (routed via SkillBoss API Hub: LLM, image, TTS, STT, embedding, search, and more) Environment variables API key status (SKILLBOSS_API_KEY)