AI Providers

VMark's AI Genies need an AI provider to generate suggestions. You can use a locally installed CLI tool or connect directly to a REST API.

Quick Setup

The fastest way to get started:

1. Open Settings > Integrations
2. Click Detect to scan for installed CLI tools
3. If a CLI is found (e.g., Claude, Gemini), select it — you're done
4. If no CLI is available, choose a REST provider, enter your API key, and select a model

Only one provider can be active at a time.

CLI Providers

CLI providers use locally installed AI tools. VMark runs them as subprocesses and streams their output back to the editor.

Provider	CLI Command	Install
Claude	claude	Claude Code
Codex	codex	OpenAI Codex CLI
Gemini	gemini	Google Gemini CLI
Ollama	ollama	Ollama

How CLI Detection Works

Click Detect in Settings > Integrations. VMark searches your $PATH for each CLI command and reports availability. If a CLI is found, its radio button becomes selectable.

Advantages

• No API key needed — the CLI handles authentication using your existing login
• Dramatically cheaper — CLI tools use your subscription plan (e.g., Claude Max, ChatGPT Plus/Pro, Google One AI Premium), which costs a fixed monthly fee. REST API providers charge per token and can cost 10–30x more for heavy usage
• Uses your CLI config — model preferences, system prompts, and billing are managed by the CLI itself
• Works offline — Ollama runs entirely on your machine

Subscription vs API for Developers

If you're also using these tools for vibe-coding (Claude Code, Codex CLI, Gemini CLI), the same subscription covers both VMark's AI Genies and your coding sessions — no extra cost.

Setup: Claude CLI

1. Install Claude Code: npm install -g @anthropic-ai/claude-code
2. Run claude once in your terminal to authenticate
3. In VMark, click Detect, then select Claude

Setup: Gemini CLI

1. Install Gemini CLI: npm install -g @anthropic-ai/gemini-cli (or via the official repo)
2. Run gemini once to authenticate with your Google account
3. In VMark, click Detect, then select Gemini

Setup: Ollama (CLI)

1. Install Ollama from ollama.com
2. Pull a model: ollama pull llama3.2
3. In VMark, click Detect, then select Ollama

Ollama runs models locally — no internet needed, no API key, complete privacy.

REST API Providers

REST providers connect directly to cloud APIs. Each requires an endpoint, API key, and model name.

Provider	Default Endpoint	Env Variable
Anthropic	https://api.anthropic.com	ANTHROPIC_API_KEY
OpenAI	https://api.openai.com	OPENAI_API_KEY
Google AI	(built-in)	GOOGLE_API_KEY or GEMINI_API_KEY
Ollama (API)	http://localhost:11434	—

Configuration Fields

When you select a REST provider, three fields appear:

• API Endpoint — The base URL (hidden for Google AI, which uses a fixed endpoint)
• API Key — Your secret key (stored in memory only — never written to disk)
• Model — The model identifier (e.g., claude-sonnet-4-5-20250929, gpt-4o, gemini-2.0-flash)

Environment Variable Auto-Fill

VMark reads standard environment variables on launch. If ANTHROPIC_API_KEY, OPENAI_API_KEY, or GEMINI_API_KEY is set in your shell profile, the API key field auto-populates when you select that provider.

This means you can set your key once in ~/.zshrc or ~/.bashrc:

export ANTHROPIC_API_KEY="sk-ant-..."

Then restart VMark — no manual key entry needed.

Setup: Anthropic (REST)

1. Get an API key from console.anthropic.com
2. In VMark Settings > Integrations, select Anthropic
3. Paste your API key
4. Choose a model (default: claude-sonnet-4-5-20250929)

Setup: OpenAI (REST)

1. Get an API key from platform.openai.com
2. In VMark Settings > Integrations, select OpenAI
3. Paste your API key
4. Choose a model (default: gpt-4o)

Setup: Google AI (REST)

1. Get an API key from aistudio.google.com
2. In VMark Settings > Integrations, select Google AI
3. Paste your API key
4. Choose a model (default: gemini-2.0-flash)

Setup: Ollama API (REST)

Use this when you want REST-style access to a local Ollama instance, or when Ollama is running on another machine on your network.

1. Ensure Ollama is running: ollama serve
2. In VMark Settings > Integrations, select Ollama (API)
3. Set endpoint to http://localhost:11434 (or your Ollama host)
4. Leave API key empty
5. Set model to your pulled model name (e.g., llama3.2)

Choosing a Provider

Situation	Recommendation
Already have Claude Code installed	Claude (CLI) — zero config, uses your subscription
Already have Codex or Gemini installed	Codex / Gemini (CLI) — uses your subscription
Need privacy / offline	Install Ollama → Ollama (CLI)
Custom or self-hosted model	Ollama (API) with your endpoint
Want the cheapest cloud option	Any CLI provider — subscription is dramatically cheaper than API
No subscription, light usage only	Set API key env var → REST provider (pay-per-token)
Need the highest quality output	Claude (CLI) or Anthropic (REST) with claude-sonnet-4-5-20250929

Per-Genie Model Override

Individual genies can override the provider's default model using the model frontmatter field:

---
name: quick-fix
description: Quick grammar fix
scope: selection
model: claude-haiku-4-5-20251001
---

This is useful for routing simple tasks to faster/cheaper models while keeping a powerful default.

Security Notes

• API keys are ephemeral — stored in memory only, never written to disk or localStorage
• Environment variables are read once on launch and cached in memory
• CLI providers use your existing CLI authentication — VMark never sees your credentials
• All requests go directly from your machine to the provider — no VMark servers in between

Troubleshooting

"No AI provider available" — Click Detect to scan for CLIs, or configure a REST provider with an API key.

CLI shows "Not found" — The CLI is not in your $PATH. Install it or check your shell profile. On macOS, GUI apps may not inherit terminal $PATH — try adding the path to /etc/paths.d/.

REST provider returns 401 — Your API key is invalid or expired. Generate a new one from the provider's console.

REST provider returns 429 — You've hit a rate limit. Wait a moment and try again, or switch to a different provider.

Slow responses — CLI providers add subprocess overhead. For faster responses, use REST providers which connect directly. For the fastest local option, use Ollama with a small model.

Model not found error — The model identifier doesn't match what the provider offers. Check the provider's docs for valid model names.

See Also

• AI Genies — How to use AI-powered writing assistance
• MCP Setup — External AI integration via Model Context Protocol