From netlify-skills
Routes AI model calls through Netlify's managed proxy for OpenAI, Anthropic, and Gemini. Use when adding AI to a Netlify site, choosing models, or debugging gateway errors.
How this skill is triggered — by the user, by Claude, or both
Slash command
/netlify-skills:netlify-ai-gatewayThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
> **IMPORTANT:** Only use models listed in the "Available Models" section below. AI Gateway does not support every model a provider offers. Using an unsupported model returns an HTTP error from the gateway.
IMPORTANT: Only use models listed in the "Available Models" section below. AI Gateway does not support every model a provider offers. Using an unsupported model returns an HTTP error from the gateway.
First-deploy requirement: The AI Gateway only activates after a site has had at least one production deploy. Local dev (
netlify dev,@netlify/vite-plugin) will NOT have gateway access on a brand-new project until you deploy to production once.
Netlify AI Gateway provides access to AI models from multiple providers without managing API keys directly. It is available on all Netlify sites.
The AI Gateway acts as a proxy — you use standard provider SDKs but point them at Netlify's gateway URL. Netlify auto-injects both the base URL and a placeholder API key for each provider, then authenticates upstream on your behalf.
Don't set your own OPENAI_API_KEY, ANTHROPIC_API_KEY, or GEMINI_API_KEY. Doing so disables Netlify's auto-injection and routes calls directly to the provider, bypassing the gateway.
npm install openai
import OpenAI from "openai";
const openai = new OpenAI();
// `OPENAI_API_KEY` and `OPENAI_BASE_URL` are auto-injected; the SDK
// reads both from the environment, so no constructor args are needed.
const completion = await openai.chat.completions.create({
model: "gpt-4o-mini",
messages: [{ role: "user", content: "Hello!" }],
});
npm install @anthropic-ai/sdk
import Anthropic from "@anthropic-ai/sdk";
const client = new Anthropic({
baseURL: Netlify.env.get("ANTHROPIC_BASE_URL"),
});
// `ANTHROPIC_API_KEY` is auto-injected — no `apiKey` arg needed.
const message = await client.messages.create({
model: "claude-sonnet-4-5-20250929",
max_tokens: 1024,
messages: [{ role: "user", content: "Hello!" }],
});
Use @google/genai (the unified Google GenAI SDK). The older @google/generative-ai package does not pick up the gateway env vars.
npm install @google/genai
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({});
// `GEMINI_API_KEY` and `GOOGLE_GEMINI_BASE_URL` are auto-injected.
const response = await ai.models.generateContent({
model: "gemini-2.5-flash",
contents: "Hello!",
});
const text = response.text;
import type { Config, Context } from "@netlify/functions";
import OpenAI from "openai";
export default async (req: Request, context: Context) => {
const { prompt } = await req.json();
const openai = new OpenAI();
const completion = await openai.chat.completions.create({
model: "gpt-4o-mini",
messages: [{ role: "user", content: prompt }],
});
return Response.json({
response: completion.choices[0].message.content,
});
};
export const config: Config = {
path: "/api/ai",
method: "POST",
};
Image generation on the gateway is supported through Gemini image models (e.g., gemini-2.5-flash-image, gemini-3-pro-image-preview, gemini-3.1-flash-image-preview). OpenAI's image models (gpt-image-1, dall-e-*) are not routed through the gateway.
Both text-to-image and image-to-image use the same generateContent method as chat — only the model and response shape differ. The image is returned as base64 inlineData on a content part, not as a URL.
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({});
const response = await ai.models.generateContent({
model: "gemini-3.1-flash-image-preview",
contents: "A watercolor portrait of a corgi wearing a beret",
});
const imagePart = response.candidates[0].content.parts.find(
(p) => p.inlineData,
);
const base64 = imagePart.inlineData.data;
const mimeType = imagePart.inlineData.mimeType; // e.g. "image/png"
const bytes = Buffer.from(base64, "base64");
Pass the source image as an additional content part with inlineData:
const sourceBase64 = sourceBuffer.toString("base64");
const response = await ai.models.generateContent({
model: "gemini-3.1-flash-image-preview",
contents: [
{ text: "Restyle this photo as a Picasso-era cubist portrait" },
{ inlineData: { mimeType: "image/png", data: sourceBase64 } },
],
});
The response shape is the same — pull base64 and mimeType off the first part with inlineData. Most callers persist the bytes to Netlify Blobs (see netlify-blobs/SKILL.md) and serve a URL back to the client rather than returning multi-MB base64 in the function response.
All of these are injected automatically by Netlify when AI is enabled. Setting your own value for any of the per-provider vars disables gateway routing.
| Variable | Provider | Purpose |
|---|---|---|
OPENAI_BASE_URL | OpenAI | Gateway endpoint |
OPENAI_API_KEY | OpenAI | Placeholder; satisfies the SDK's "key required" check |
ANTHROPIC_BASE_URL | Anthropic | Gateway endpoint |
ANTHROPIC_API_KEY | Anthropic | Placeholder; satisfies the SDK's "key required" check |
GOOGLE_GEMINI_BASE_URL | Google Gemini | Gateway endpoint |
GEMINI_API_KEY | Google Gemini | Placeholder; satisfies the SDK's "key required" check |
NETLIFY_AI_GATEWAY_BASE_URL | (universal) | Provider-agnostic gateway endpoint |
NETLIFY_AI_GATEWAY_KEY | (universal) | Provider-agnostic gateway key |
The real upstream API keys live on Netlify's side. The per-provider *_API_KEY vars are placeholders so the SDKs construct successfully; the gateway authenticates server-side.
With @netlify/vite-plugin or netlify dev, gateway environment variables are injected automatically into the local process — but only after the site has had at least one production deploy. A brand-new local-only project will see "API key missing" or "model not found" errors until you deploy.
OPENAI_API_KEY missing (or equivalent) at runtime: AI Features are disabled on the site, or the project has not had a production deploy yet.*_API_KEY. Any user-set provider key shadows Netlify's auto-injection and routes directly to the provider.Verified 2026-04-30 against the live AI Gateway providers list. The user-facing reference is https://docs.netlify.com/build/ai-gateway/overview/ — re-check before pinning a new model.
claude-haiku-4-5, claude-haiku-4-5-20251001claude-sonnet-4-0, claude-sonnet-4-20250514, claude-sonnet-4-5, claude-sonnet-4-5-20250929, claude-sonnet-4-6claude-opus-4-1-20250805, claude-opus-4-20250514, claude-opus-4-5, claude-opus-4-5-20251101, claude-opus-4-6, claude-opus-4-7gpt-4o, gpt-4o-mini, gpt-4.1, gpt-4.1-mini, gpt-4.1-nanogpt-5, gpt-5-mini, gpt-5-nano, gpt-5-pro, gpt-5-codex; dated: gpt-5-2025-08-07, gpt-5-mini-2025-08-07gpt-5.1, gpt-5.1-codex, gpt-5.1-codex-max, gpt-5.1-codex-mini; dated: gpt-5.1-2025-11-13gpt-5.2, gpt-5.2-codex, gpt-5.2-pro; dated: gpt-5.2-2025-12-11, gpt-5.2-pro-2025-12-11gpt-5.3-chat-latest, gpt-5.3-codex (no unversioned gpt-5.3)gpt-5.4, gpt-5.4-mini, gpt-5.4-nano, gpt-5.4-pro; dated: gpt-5.4-2026-03-05, gpt-5.4-mini-2026-03-17, gpt-5.4-nano-2026-03-17, gpt-5.4-pro-2026-03-05gpt-5.5, gpt-5.5-pro; dated: gpt-5.5-2026-04-23, gpt-5.5-pro-2026-04-23o3, o3-mini, o4-minigemini-2.0-flash, gemini-2.0-flash-lite, gemini-2.5-flash, gemini-2.5-flash-lite, gemini-2.5-pro, gemini-3-flash-preview, gemini-3.1-flash-lite-preview, gemini-3.1-pro-preview, gemini-3.1-pro-preview-customtools, gemini-flash-latest, gemini-flash-lite-latestgemini-2.5-flash-image, gemini-3-pro-image-preview, gemini-3.1-flash-image-previewnpx claudepluginhub netlify/context-and-tools --plugin netlify-skillsProvides expert guidance for Vercel AI Gateway configuration: model routing, provider failover, cost tracking, unified API for multiple AI providers like OpenAI, Anthropic, Gemini.
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