Provider Overview

Understanding AI providers in Andi AIRun

Andi AIRun supports multiple AI providers, allowing you to choose between local models (free, private) and cloud APIs (powerful, scalable).

Quick Reference

Flag	Provider	Type	Notes
--ollama / --ol	Ollama	Local	Free, no API costs, cloud option
--lmstudio / --lm	LM Studio	Local	MLX models (fast on Apple Silicon)
--aws	AWS Bedrock	Cloud	Requires AWS credentials
--vertex	Google Vertex AI	Cloud	Requires GCP project
--apikey	Anthropic API	Cloud	Direct API access
--azure	Microsoft Azure	Cloud	Azure Foundry
--vercel	Vercel AI Gateway	Cloud	Any model: Anthropic, OpenAI, xAI, Google, Meta, more
--pro	Claude Pro	Subscription	Default if logged in

How Configuration Works

All provider credentials are stored in one file: ~/.ai-runner/secrets.sh

Initial Setup

This file is created automatically by ./setup.sh from the secrets.example.sh template:

nano ~/.ai-runner/secrets.sh

Andi AIRun loads this file at startup. You don’t need to set environment variables in your shell profile or .bashrc — just add them to secrets.sh, and then switch providers freely with ai --aws, ai --vertex, etc.

You only need to configure the providers you want to use. Configure multiple providers to switch between them when you hit rate limits or want to use different models.

Session-Scoped Behavior

All provider configurations are session-scoped:

• Changes only affect the active terminal session
• On exit, original settings automatically restore
• Plain claude always runs in native state
• Running claude in another terminal is unaffected

This means you can safely run ai --lmstudio in one terminal while using claude normally in another.

Provider Detection and Defaults

Automatic Provider Selection

If you don’t specify a provider flag, Andi AIRun automatically detects and uses:

1. Claude Pro (if logged in with claude login)
2. First configured provider in secrets.sh

Setting a Default Provider

You can set a default provider to avoid typing the flag every time:

ai --vercel --model xai/grok-code-fast-1 --set-default

Clear the default:

ai --clear-default

Model Tier System

Andi AIRun uses a three-tier model system to balance performance and cost:

Tier Levels

Tier	Aliases	Use Case	Claude Models
High	--opus, --high	Complex reasoning, large refactors	Claude Opus 4.6
Mid	--sonnet, --mid	General coding tasks (default)	Claude Sonnet 4.6
Low	--haiku, --low	Fast operations, small edits	Claude Haiku 4.5

Usage Examples

# Use high tier for complex reasoning
ai --aws --opus task.md

# Use mid tier (default)
ai --aws task.md

# Use low tier for speed and cost savings
ai --vertex --haiku simple-fix.md

Background Model

Andi AIRun uses a “small/fast” model for background operations (like file searches, quick checks). By default, this is set to the Low tier model (Haiku).

For local providers (Ollama, LM Studio), the background model defaults to the same model as the main tier to avoid costly model swapping.

Configuring Model Tiers

You can customize model tiers per provider in secrets.sh:

Cloud Providers

# AWS Bedrock
export CLAUDE_MODEL_OPUS_AWS="global.anthropic.claude-opus-4-6-v1"
export CLAUDE_MODEL_SONNET_AWS="global.anthropic.claude-sonnet-4-6"
export CLAUDE_MODEL_HAIKU_AWS="us.anthropic.claude-haiku-4-5-20251001-v1:0"

# Google Vertex AI
export CLAUDE_MODEL_OPUS_VERTEX="claude-opus-4-6"
export CLAUDE_MODEL_SONNET_VERTEX="claude-sonnet-4-6"
export CLAUDE_MODEL_HAIKU_VERTEX="claude-haiku-4-5@20251001"

# Anthropic API
export CLAUDE_MODEL_OPUS_ANTHROPIC="claude-opus-4-6"
export CLAUDE_MODEL_SONNET_ANTHROPIC="claude-sonnet-4-6"
export CLAUDE_MODEL_HAIKU_ANTHROPIC="claude-haiku-4-5"

# Vercel AI Gateway
export CLAUDE_MODEL_SONNET_VERCEL="xai/grok-code-fast-1"
export CLAUDE_SMALL_FAST_MODEL_VERCEL="xai/grok-code-fast-1"

Local Providers

# Ollama
export OLLAMA_MODEL_HIGH="qwen3-coder"
export OLLAMA_MODEL_MID="qwen3-coder"
export OLLAMA_MODEL_LOW="qwen2.5-coder:7b"
export OLLAMA_SMALL_FAST_MODEL="qwen3-coder"  # Same model to avoid swapping

# LM Studio
export LMSTUDIO_MODEL_HIGH="openai/gpt-oss-20b"
export LMSTUDIO_MODEL_MID="openai/gpt-oss-20b"
export LMSTUDIO_MODEL_LOW="ibm/granite-4-micro"
export LMSTUDIO_SMALL_FAST_MODEL="openai/gpt-oss-20b"  # Same model

Custom Models

Override the tier system with a specific model:

# Use a specific model
ai --vercel --model xai/grok-code-fast-1

# Use a specific Ollama model
ai --ollama --model glm-5:cloud

# Use a specific AWS model
ai --aws --model global.anthropic.claude-opus-4-6-v1

Agent Teams

All providers support agent teams (ai --team). Coordination uses Claude Code’s internal task list and mailbox, not provider-specific features.

Learn More

Read the Claude Code Agent Teams documentation

Next Steps

Local Providers

Set up Ollama or LM Studio for free, private AI

Cloud Providers

Configure AWS, Google, Anthropic, Azure, or Vercel

Switching Providers

Learn to switch providers to avoid rate limits