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Andi AIRun extends Claude Code with multi-provider support. Switch between your Claude subscription, AWS Bedrock, Google Vertex AI, Azure, local models, and more — all using the same ai command.

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What Are Providers?

Providers are different backend services that run AI models. Each provider has its own:
  • Authentication: API keys, credentials, or subscriptions
  • Pricing: Some free (local), some pay-per-token (API), some subscription (Claude Pro)
  • Rate limits: Different limits per provider and tier
  • Model selection: Not all providers have all models
  • Geographic regions: Different data residency and compliance

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Available Providers

ProviderTypeFlagNotes
Claude ProSubscription--proDefault if logged in, has rate limits
AWS BedrockCloud API--awsRequires AWS credentials
Google Vertex AICloud API--vertexRequires GCP project
Anthropic APICloud API--apikeyDirect API access
AzureCloud API--azureMicrosoft Azure Foundry
Vercel AI GatewayCloud API--vercel100+ models from multiple providers
OllamaLocal/Cloud--ollamaFree local or cloud models
LM StudioLocal--lmstudioLocal models with MLX support
Providers are configured once in ~/.ai-runner/secrets.sh and switched with simple flags. No need to edit config files or set environment variables.

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Why Switch Providers?

There are several reasons to switch providers mid-task:

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1. Avoiding Rate Limits

The most common reason. Claude Pro has rate limits that can block you for hours: 
# Working with Claude Pro, hit rate limit
claude
# "Rate limit exceeded. Try again in 4 hours 23 minutes."

# Immediately continue with AWS
ai --aws --resume
You can continue your exact conversation on a different provider without losing context.

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2. Cost Optimization

Different providers have different pricing: 
# Use cheap Haiku for simple analysis
ai --aws --haiku analyze-logs.md

# Use expensive Opus for complex reasoning
ai --aws --opus review-architecture.md

# Use free local model for experimentation
ai --ollama --model qwen3-coder

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3. Local vs Cloud

Run models locally for privacy, or in the cloud for power: 
# Local - free, private, no API calls
ai --ollama analyze-sensitive-data.md

# Cloud - more powerful, faster
ai --aws --opus analyze-complex-system.md

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4. Geographic Compliance

Different providers operate in different regions: 
# Use GCP for EU data residency
ai --vertex task.md

# Use Azure for specific compliance requirements
ai --azure task.md

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5. Model Availability

Test different models or use alternate AI systems: 
# Claude via AWS
ai --aws --opus task.md

# OpenAI via Vercel
ai --vercel --model openai/gpt-5.2-codex task.md

# xAI via Vercel
ai --vercel --model xai/grok-code-fast-1 task.md

# Local Ollama
ai --ollama --model qwen3-coder task.md

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The —resume Flag for Continuity

The --resume flag picks up your previous conversation on a different provider: 
# Start with Claude Pro
ai
# [work for a while...]
# "Rate limit exceeded"

# Resume on AWS with same context
ai --aws --resume
What --resume does:
  • Loads the most recent conversation session
  • Continues from where you left off
  • Preserves all context and history
  • Works across any provider switch
Use cases: 
ai                    # Hit rate limit
ai --aws --resume     # Continue immediately

ai --opus             # Start with powerful model
ai --haiku --resume   # Switch to cheap model for simple tasks
ai --opus --resume    # Back to powerful for complex work

ai --ollama           # Try local first
ai --aws --opus --resume  # Escalate to cloud for hard problem

ai --aws --resume     # Try AWS implementation
ai --vertex --resume  # Compare Vertex response
ai --azure --resume   # Test Azure behavior
Use ai-sessions to view your active conversation sessions and see which one would be resumed.

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Session-Scoped Behavior

All provider switches are session-scoped — they only affect the current terminal session: 
# Terminal 1
ai --aws
# [Working with AWS...]

# Terminal 2 (unaffected)
claude
# [Still using regular Claude Pro]
When you exit an ai session:
  • Your original Claude Code settings are automatically restored
  • No global configuration is changed
  • Other terminals are completely unaffected
This non-destructive design means you can safely experiment with providers without breaking your Claude Code installation.

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Setting Default Providers

If you frequently use a specific provider, save it as your default: 
# Set AWS + Opus as default
ai --aws --opus --set-default

# Now 'ai' with no flags uses AWS + Opus
ai
ai --resume

# Clear saved default
ai --clear-default

# Back to auto-detection (Claude Pro if logged in)
ai
Saved defaults are stored in ~/.ai-runner/default.conf. Flag precedence (highest to lowest):
PrioritySourceExample
1. CLI flagsExplicit flagsai --vertex task.md
2. Shebang flagsScript header#!/usr/bin/env -S ai --aws
3. Saved defaults--set-defaultSet with ai --aws --set-default
4. Auto-detectionCurrent loginClaude Pro if logged in

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Provider Examples

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Switch Between Major Clouds

# AWS Bedrock
ai --aws
ai --aws --opus task.md

# Google Vertex AI
ai --vertex
ai --vertex --sonnet task.md

# Microsoft Azure
ai --azure
ai --azure --haiku task.md

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Use Anthropic API Directly

# Direct API (bypasses subscription limits)
ai --apikey
ai --apikey --opus task.md

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Local Models (Free)

# Ollama (local)
ai --ollama
ai --ollama --model qwen3-coder

# Ollama (cloud, no GPU needed)
ai --ollama --model minimax-m2.5:cloud
ai --ollama --model glm-5:cloud

# LM Studio (local, MLX support)
ai --lmstudio
ai --lm --model openai/gpt-oss-20b

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Alternate Models via Vercel

# OpenAI models
ai --vercel --model openai/gpt-5.2-codex

# xAI models
ai --vercel --model xai/grok-code-fast-1

# Google models
ai --vercel --model google/gemini-3-pro-preview

# Alibaba models
ai --vercel --model alibaba/qwen3-coder
Vercel AI Gateway gives access to 100+ models from multiple providers through a single API.

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Model Tiers

Most providers support three model tiers:
TierFlagsUse CaseExample
High--opus / --highComplex reasoning, architectureOpus 4.6
Mid--sonnet / --midBalanced coding tasksSonnet 4.6
Low--haiku / --lowFast, simple tasksHaiku 4.5
Combine tiers with providers: 
ai --aws --opus         # AWS Bedrock + Opus
ai --vertex --sonnet    # Vertex AI + Sonnet  
ai --azure --haiku      # Azure + Haiku
Use --haiku for cost savings on simple tasks. Use --opus for complex architecture decisions or challenging debugging. Use --sonnet (default) for everyday coding.

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Provider Configuration

Providers are configured in ~/.ai-runner/secrets.sh: 
# Edit configuration
nano ~/.ai-runner/secrets.sh
Add credentials for the providers you want to use: 
# AWS Bedrock
export AWS_PROFILE="your-profile-name"
export AWS_REGION="us-west-2"

# Google Vertex AI
export ANTHROPIC_VERTEX_PROJECT_ID="your-gcp-project-id"
export CLOUD_ML_REGION="global"

# Anthropic API
export ANTHROPIC_API_KEY="sk-ant-..."

# Vercel AI Gateway
export VERCEL_AI_GATEWAY_TOKEN="vck_..."

# Azure
export ANTHROPIC_FOUNDRY_API_KEY="your-azure-api-key"
export ANTHROPIC_FOUNDRY_RESOURCE="your-resource-name"

# Ollama (local)
# No configuration needed

# LM Studio (local)
export LMSTUDIO_HOST="http://localhost:1234"  # Optional
You only need to configure the providers you plan to use.
Configuration is loaded at startup. After editing secrets.sh, start a new session or run source ~/.ai-runner/secrets.sh.

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Check Current Configuration

Use ai-status to verify your setup: 
ai-status
Example output: 
Andi AIRun Status
=================

Version: 1.5.0

Providers Configured:
  ✓ Claude Pro (logged in)
  ✓ AWS Bedrock (profile: default, region: us-west-2)
  ✓ Anthropic API (key: sk-ant-...ABC123)
  ✓ Ollama (local, 3 models available)
  ✗ Vertex AI (not configured)
  ✗ Azure (not configured)
  ✗ Vercel (not configured)

Default Provider: AWS Bedrock + Opus 4.6

Active Sessions: 2
  - Session 1: AWS Bedrock + Sonnet (started 2h ago)
  - Session 2: Claude Pro (started 15m ago)

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Advanced: Agent Teams with Any Provider

Agent teams work with all providers: 
# Claude Pro with teams
ai --team

# AWS with teams
ai --aws --opus --team

# Local Ollama with teams
ai --ollama --team
Teams coordination uses Claude Code’s internal task list and mailbox — it’s provider-independent. Token usage scales with team size (5 teammates ≈ 5× tokens).
Agent teams only work in interactive mode — not supported in shebang/piped script modes.

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Practical Workflows

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Rate Limit Recovery Workflow

# 1. Start working with Claude Pro
ai

# 2. Hit rate limit mid-task
# "Rate limit exceeded. Try again in 4 hours 23 minutes."

# 3. Immediately switch to API
ai --aws --resume

# 4. Continue working
# [Complete the task...]

# 5. Later, switch back to Pro for free tier
ai --pro --resume

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Cost-Optimized Development

# Use free local model for exploration
ai --ollama
# [Prototype and experiment...]

# Switch to cloud for production-quality code
ai --aws --opus --resume
# [Final implementation...]

# Use cheap Haiku for documentation
ai --aws --haiku --resume
# [Generate docs...]

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Multi-Provider Testing

# Test a prompt on different providers
ai --aws task.md > aws-output.txt
ai --vertex task.md > vertex-output.txt  
ai --ollama task.md > ollama-output.txt

# Compare results
diff aws-output.txt vertex-output.txt

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Privacy-Conscious Workflow

# Sensitive data analysis (local only)
ai --ollama analyze-customer-data.md

# Public code review (cloud OK)
ai --aws review-open-source-pr.md

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View Active Sessions

See all your conversation sessions: 
ai-sessions
Example output: 
Active AIRun Sessions:

1. AWS Bedrock + Sonnet 4.6
   Started: 2 hours ago
   Location: ~/projects/backend/
   Status: Active

2. Claude Pro + Opus 4.6  
   Started: 15 minutes ago
   Location: ~/projects/frontend/
   Status: Active

3. Ollama (qwen3-coder)
   Started: 1 day ago
   Location: ~/experiments/
   Status: Idle
The most recent session is used by --resume.

Provider Setup

Detailed configuration for each provider

Executable Markdown

Use provider flags in shebang scripts