Provider Configuration

AI Agent Flow supports six LLM providers — cloud and local. Configuration is handled interactively via aiagentflow init, which writes a .aiagentflow/config.json file in your project directory.

aiagentflow init

The wizard walks you through selecting providers, entering API keys, assigning models per agent role, and setting workflow preferences.

Anthropic (Recommended)

Claude Sonnet 4 is the recommended model for architecture and coding tasks due to its strong reasoning and large context window.

Get your API key at console.anthropic.com.

Default model: claude-sonnet-4-20250514

OpenAI

Compatible with GPT-4o, GPT-4o-mini, and o-series models.

Get your API key at platform.openai.com.

Default model: gpt-4o-mini

Google Gemini

Gemini's large context window makes it excellent for analyzing large codebases.

Get your API key at aistudio.google.com.

Default model: gemini-2.0-flash

Groq

Groq provides extremely fast inference on open-source models. The free tier is generous — good for testing and rapid iteration.

Get your API key at console.groq.com.

Default model: llama-3.3-70b-versatile

OpenRouter

OpenRouter proxies 100+ models through a single OpenAI-compatible API. Many models are available for free — no credit card required.

Get your API key at openrouter.ai.

Default model: meta-llama/llama-3.1-8b-instruct:free

Ollama (Local First)

For maximum privacy, run AI Agent Flow entirely offline using local models via Ollama.

1. Install Ollama
2. Pull a model:

   ollama pull llama3.2
   

3. Select Ollama during aiagentflow init — no API key needed.

Default model: llama3.2:latest

Assigning Models Per Agent

During aiagentflow init you can assign different providers and models to each of the six agent roles (Architect, Coder, Reviewer, Tester, Fixer, Judge). This lets you use a powerful model for the Architect while using a faster/cheaper one for repetitive tasks like the Fixer.

The configuration is saved to .aiagentflow/config.json in your project root.