Skip to content

Introduction to AI-VERDE API

AI-VERDE exposes an OpenAI-compatible API, so any tool or library that supports OpenAI can connect to it using your AI-VERDE API key. AI-VERDE also accepts Anthropic-style requests (used by Claude Code and the Anthropic SDK) and, for Claude Code only, AWS Bedrock-style requests for Claude models hosted on AWS Bedrock. This section explains how to get your key and use it across a range of environments.

Getting Started

Before using the API you will need to:

  1. Obtain your API key — Sign in at chat.cyverse.ai, open your course or team details, and copy the key from the API Key tab. See Obtaining your AI-VERDE API Key for step-by-step instructions.
  2. Know which models are available — Your available models are listed on the same API Key page. You can also retrieve them programmatically; see Getting a List of Models.

What's in This Section

Section What it covers
Using Your API Key for AWS Bedrock Models Claude models on AWS Bedrock with Claude Code and the Claude Code for VS Code extension
Using Your API Key in Code Python integration with LangChain, LlamaIndex, and the Anthropic Python SDK
Using CLI Coding Assistants Terminal-based AI coding tools: Claude Code Router, Aider, Claude Code, Codex, and OpenCode
Using IDEs VS Code integration: Claude Code for VS Code and Codex for VS Code
Using Desktop Clients GUI chat clients such as Chatbox AI

Base URL and Authentication

When configuring a client, you need your API key (copied from the AI-VERDE dashboard) and a base URL. The base URL depends on which style of API the client speaks:

API style Base URL Used by
OpenAI-compatible https://llm-api.cyverse.ai/v1 Aider, Codex, OpenCode, Claude Code Router, Chatbox AI, Codex for VS Code, and most OpenAI clients
Anthropic-style https://llm-api.cyverse.ai Claude Code (Anthropic models), Claude Code (non-Anthropic models), Claude Code for VS Code, Anthropic Python SDK
AWS Bedrock https://llm-api.cyverse.ai/bedrock Claude Code on Bedrock, Claude Code for VS Code on Bedrock

If your course details show a different base URL ending in /v1, use it for OpenAI-compatible clients, remove /v1 for Anthropic-style clients, and replace /v1 with /bedrock for AWS Bedrock.

Note

The LangChain and LlamaIndex examples use LiteLLM's litellm_proxy provider, which takes the base URL without /v1 (https://llm-api.cyverse.ai).

OpenAI-compatible clients send the API key as a bearer token (Authorization: Bearer <your-api-key>), and Anthropic-style clients may send it in an x-api-key header instead; AI-VERDE accepts either. Each guide shows which setting or environment variable holds the key for that tool.