Stirrup Integration

AVELIN API is compatible with Stirrup — Lightweight framework for building agents using ChatCompletionsClient and your own API key.

Stirrup is a minimal agent framework built around the ChatCompletionsClient interface — the same interface every OpenAI-compatible API exposes. Its killer feature is radical simplicity: instead of pulling in a heavy framework with dozens of dependencies, Stirrup lets you build custom agents in minutes using just the standard chat completions API you already know. No abstraction layers, no vendor-specific SDKs.

Built for developers who want full control and zero bloat, Stirrup is the right choice when LangChain or CrewAI feel like overkill. Pair it with AVELIN's OpenAI-compatible endpoint and you have a production agent stack with minimal surface area for bugs.

Why AVELIN + Stirrup? Leverage AVELIN's frontier models with 1M-token context windows, automatic failover, and competitive pricing for automation workflows.

Quick Setup

Step 1: Get your AVELIN API key

Sign up at avelin.ai and generate an API key. It will look like sk-ave...xxxx.

Step 2: Configure AVELIN

Most automation tools support OpenAI-compatible endpoints via environment variables:

export OPENAI_API_BASE=https://api.avelin.ai/v1
export OPENAI_API_KEY=sk-avelin-YOUR_KEY

API Reference

EndpointURL
OpenAI-compatiblehttps://api.avelin.ai/v1
Anthropic-compatiblehttps://api.avelin.ai
Use caseModelWhy
Complex automationavelin-agentic-ultraTop-tier reasoning for multi-step workflows
Standard tasksavelin-agentic-proBalanced performance and cost
High-volume simple tasksavelin-agentic-fastLowest cost, fastest response
Code-heavy automationavelin-coding-pro1M context, code understanding
Research workflowsavelin-ultraFlagship reasoning capabilities

Why AVELIN for Stirrup?

  • Agentic models: Purpose-built for tool-calling and multi-step planning
  • Automatic failover: Automation keeps running if a provider is down
  • 1M context: Track complex workflows without losing context
  • Cost optimization: Prompt caching reduces costs by ~80% on repeated prompts

Troubleshooting

IssueSolution
API key errorVerify OPENAI_API_BASE includes /v1
Agent loopsLower temperature to 0.0-0.1, use avelin-agentic-ultra
Token limitBreak workflow into smaller steps
Tool failuresUse avelin-agentic-ultra for best tool-calling reliability