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Getting Started with Scout-AI

This guide helps you install Scout-AI, configure your first inference endpoint, and run your first conversation. It is intended for anyone new to the framework — both human developers and coding agents.

You should read this if: you have never used Scout-AI before.

What is Scout-AI?

Scout-AI is a framework for building AI applications on top of LLMs. It gives you:

  • Chats: plain-text conversation files you can inspect, edit, and version.
  • Agents: reusable, stateful assistants with tools and personas.
  • Tools: let the model call functions, query databases, or run code.
  • Multi-agent workflows: orchestrate specialists to solve complex tasks.

Scout-AI is written in Ruby and uses the Scout Workflow engine for reproducibility and provenance.

Installation

Prerequisites

  • Ruby 3.0+
  • An LLM provider account (OpenAI, Anthropic, etc.) or a local model (Ollama, vLLM)

Install Scout-AI

gem install scout-ai

Or, if you're working from the source repository:

git clone https://github.com/mvazque2/scout-ai.git
cd scout-ai
bundle install

Set your API key

export ANTHROPIC_KEY="sk-ant-..."   # or OPENAI_KEY, GLM_KEY, ...

(Or put key: in the endpoint YAML below.)

Configure your first endpoint

An endpoint is a named configuration for a provider + model. There is no CLI command for this: endpoints are YAML files under ~/.scout/etc/AI/, one per endpoint, that you write by hand.

# ~/.scout/etc/AI/anthropic.yaml
backend: anthropic
model: claude-sonnet-4-20250514
key: sk-ant-...   # optional; ANTHROPIC_KEY is read when absent

RunningInference.md is the canonical endpoint reference: full key set (backend, url, key, model), the -ck option, and the provider table.

Your first conversation

From the command line

scout-ai llm ask "Hello! What can you do?"

You should see a response from the model.

Using a specific endpoint

scout-ai llm ask -e anthropic "Hello!"

Your first chat file

Create a file hello.chat:

system:

You are a friendly assistant. Keep your answers short.

user:

What is 2 + 2?

Run it:

scout-ai llm ask -c hello.chat

Your first agent

Agents are named directories. Create one under ~/.scout/chats/Agent/ (the location LLM.load_agent and scout-ai agent look up regardless of your current directory):

mkdir -p ~/.scout/chats/Agent/Greeter

Create ~/.scout/chats/Agent/Greeter/start_chat:

system:

You are a friendly greeter. Always greet by name.

Use it from the CLI:

scout-ai agent ask Greeter "Hi, I'm Alice!"

Or from Ruby:

require 'scout-ai'

agent = LLM.load_agent('Greeter')
agent.start
agent.user "Hi, I'm Alice!"
puts agent.chat

Where to go next

If you want to understand how Scout-AI is implemented internally, see the ../developer/ documentation.