# Netlify AI Gateway

> Reference for Netlify AI Gateway — the managed proxy that routes calls to OpenAI, Anthropic, and Google Gemini SDKs without provider API keys. Use this skill any time the user wants to add AI on a Netlify site (chat, completion, reasoning, image generation, image-to-image edit/stylize), choose or change a model, wire up the OpenAI / Anthropic / @google/genai SDK, decide which provider to use for an image-gen feature (it's Gemini-only on the gateway), or debug "model not found" / "API key missing" against the gateway. Required reading before pinning a model — the gateway exposes a curated subset, not every provider model.

- Skill: `om-scogo/netlify-ai-gateway` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds add om-scogo/netlify-ai-gateway`
- Raw SKILL.md: https://api.skillmd.com/api/skills/om-scogo/netlify-ai-gateway/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: om-scogo (https://skillmd.com/u/om-scogo)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/om-scogo/netlify-ai-gateway

---


# Netlify AI 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.

> **Usage is credit-metered:** Gateway calls draw down your Netlify AI credit/inference allowance and start returning errors once it's exhausted — there's no separate provider bill behind it. Budget for this explicitly in any bulk or fan-out design (generating content for hundreds of rows/pages, retry loops), and don't retry unbounded.

Netlify AI Gateway provides access to AI models from multiple providers without managing API keys directly. It is available on all Netlify sites.

## How It Works

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.

Always make the call through the provider's official SDK, constructed bare (`new OpenAI()`, `new Anthropic()`, `new GoogleGenAI()`) — the SDK reads the auto-injected base URL and key from the environment. **Don't hand-roll the gateway call with a raw `fetch()` and a manually-read `process.env.OPENAI_API_KEY`** (or a hardcoded key/URL): the injected key is only a placeholder, and rolling your own request bypasses the supported path the gateway expects.

## Setup

1. Enable AI on your site in the Netlify UI
2. Deploy to production at least once — the gateway does not activate until then
3. Install the provider SDK you want to use

Don't set your own `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, `GEMINI_API_KEY`, or `GOOGLE_API_KEY` (the `@google/genai` SDK reads either `GEMINI_API_KEY` or `GOOGLE_API_KEY`). Doing so disables Netlify's auto-injection and routes calls directly to the provider, bypassing the gateway.

## Using OpenAI SDK

```bash
npm install openai
```

```typescript
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!" }],
});
```

## Using Anthropic SDK

```bash
npm install @anthropic-ai/sdk
```

```typescript
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();
// `ANTHROPIC_API_KEY` and `ANTHROPIC_BASE_URL` are auto-injected; the SDK
// reads both from the environment, so no constructor args are needed.

const message = await client.messages.create({
  model: "claude-sonnet-4-5-20250929",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Hello!" }],
});
```

## Using Google Gemini SDK

Use `@google/genai` (the unified Google GenAI SDK). The older `@google/generative-ai` package does not pick up the gateway env vars.

```bash
npm install @google/genai
```

```typescript
import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});
// `GEMINI_API_KEY` and `GOOGLE_GEMINI_BASE_URL` are auto-injected. The SDK also
// honors `GOOGLE_API_KEY`; leave both Gemini keys unset so the gateway's
// injection isn't shadowed.

const response = await ai.models.generateContent({
  model: "gemini-2.5-flash",
  contents: "Hello!",
});

const text = response.text;
```

## In a Netlify Function

```typescript
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",
};
```

Return the reply as JSON with `Response.json({...})`, even when the request only asks for "the reply text" back — a raw `text/plain` body breaks JSON-consuming clients and diverges from the convention used everywhere else in Netlify Functions.

## Image Generation

Image generation on the gateway is supported through **Gemini image models** (e.g., `gemini-2.5-flash-image`, `gemini-3-pro-image`, `gemini-3.1-flash-image`, `gemini-3.1-flash-lite-image`). 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.

### Text-to-image

```typescript
import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

const response = await ai.models.generateContent({
  model: "gemini-3.1-flash-image",
  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");
```

### Image-to-image (edit / stylize an input image)

Pass the source image as an additional content part with `inlineData`:

```typescript
const sourceBase64 = sourceBuffer.toString("base64");

const response = await ai.models.generateContent({
  model: "gemini-3.1-flash-image",
  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.

## Environment Variables

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. You don't read these yourself — the SDK picks them up.

When your own code needs some *other* environment value (a config flag, a model name you've parameterized), prefer `Netlify.env.get("VAR")` — it works in Netlify Functions and Edge Functions, and Edge Functions expose **only** `Netlify.env.get`. (In a framework's own server routes, use whatever that framework documents for env access — often `process.env`.)

## Local Development

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.

Local injection also requires the working directory to be **linked** to the Netlify site. `netlify dev` pulls the gateway base URL and placeholder key from the linked site's environment, so an unlinked directory has no site context — nothing is injected and gateway calls fail even when the site has already been deployed to production. Run `netlify link` (or `netlify init`) in the project first, then start `netlify dev`. A bare framework dev server started outside `netlify dev` / `@netlify/vite-plugin` also gets no gateway env vars.

## Usage metering and where the gateway runs

**Gateway usage is credit-metered.** Calls draw down your Netlify AI credit/inference allowance; when that limit is reached the gateway **pauses** and returns errors until the allowance resets or is raised. There's no separate provider bill to fall back on — an unbounded loop of gateway calls burns the allowance and then starts failing, so budget for it and don't retry indefinitely.

**Gateway credentials are runtime-only.** Netlify injects the base URL and placeholder key only into runtime compute — deployed functions, edge functions, and server-rendered routes at request time. They are **not** present during the build: AI calls made at build time, in prerender/SSG, or in a build plugin get no gateway credentials and fail. Do AI work at request time (in a function or server route) and cache the result if you need it to look precomputed (e.g. to Netlify Blobs) — don't call the gateway from build scripts or static-generation hooks.

## No browser-callable gateway — proxy through server code

Gateway credentials are injected only into server-side runtime compute (functions, edge functions, server-rendered routes). There is **no browser-callable gateway endpoint**: client-side JavaScript has no gateway credentials, and there is no public URL a browser can hit to reach the gateway directly. Client code (React/Vue/vanilla JS running in the browser) that constructs a provider SDK against the gateway will find no key and fail — and "fixing" it by hardcoding a real provider key in the client leaks that key to every visitor AND bypasses the gateway (a user-set key disables Netlify's auto-injection).

The correct pattern is to proxy: put the gateway call in a **Netlify Function** (or edge function / server route), and have the browser `fetch()` your own endpoint (e.g. `/api/chat`). The function talks to the gateway server-side with the auto-injected credentials and returns the result to the client. Never import a provider SDK into a browser bundle to call the gateway, and never expose a provider API key to the client.

## Long generations and the function timeout

A gateway call runs inside your function, so it is bound by the **60-second synchronous function timeout**. Large completions, reasoning models, and image generations can run longer than that, and a synchronous function that exceeds the ceiling is terminated before it can respond. Two mitigations:

- **Stream the response.** Enable streaming on the SDK call and return a `ReadableStream` (e.g. `Content-Type: text/event-stream`), forwarding the provider's tokens/chunks as they arrive — for example `stream: true` on the OpenAI SDK, `client.messages.stream(...)` on Anthropic, or `generateContentStream(...)` on `@google/genai`. Streaming sends bytes to the client incrementally instead of buffering the whole completion inside the sync window, and is the right default for interactive chat and long text.
- **Use a background function** for long, fire-and-forget jobs (batch generation, large image renders). Background functions run up to 15 minutes, but they return a `202` immediately and their return value is ignored — they cannot hand the result back to the caller. Persist the output (e.g. to Netlify Blobs or a database) and have the client poll or fetch it.

Don't leave a slow synchronous generation unstreamed and assume it will finish — bound the model and `max_tokens`, and choose streaming or a background function based on how long the job runs.

## Errors & Troubleshooting

- **Unsupported model:** the gateway returns an HTTP error. Check the "Available Models" list below — the gateway exposes a curated subset, not every model the provider offers.
- **`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.
- **Calls succeed but skip the gateway / aren't tracked:** check you haven't set your own `*_API_KEY`. Any user-set provider key shadows Netlify's auto-injection and routes directly to the provider.
- **Limits:** 200k-token context window. Batch inference, custom request headers, and OpenAI priority processing are not supported. Anthropic prompt caching is limited to the 5-minute ephemeral cache; Gemini explicit caching is not supported.

## Available Models

_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._

### Anthropic (chat)
- `claude-haiku-4-5`, `claude-haiku-4-5-20251001`
- `claude-sonnet-4-0`, `claude-sonnet-4-20250514`, `claude-sonnet-4-5`, `claude-sonnet-4-5-20250929`, `claude-sonnet-4-6`
- `claude-opus-4-1-20250805`, `claude-opus-4-20250514`, `claude-opus-4-5`, `claude-opus-4-5-20251101`, `claude-opus-4-6`, `claude-opus-4-7`

### OpenAI (chat / reasoning / Codex)
- gpt-4 family: `gpt-4o`, `gpt-4o-mini`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4.1-nano`
- gpt-5: `gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-5-pro`, `gpt-5-codex`; dated: `gpt-5-2025-08-07`, `gpt-5-mini-2025-08-07`
- gpt-5.1: `gpt-5.1`, `gpt-5.1-codex`, `gpt-5.1-codex-max`, `gpt-5.1-codex-mini`; dated: `gpt-5.1-2025-11-13`
- gpt-5.2: `gpt-5.2`, `gpt-5.2-codex`, `gpt-5.2-pro`; dated: `gpt-5.2-2025-12-11`, `gpt-5.2-pro-2025-12-11`
- gpt-5.3: `gpt-5.3-chat-latest`, `gpt-5.3-codex` (no unversioned `gpt-5.3`)
- gpt-5.4: `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-2026-03-05`
- gpt-5.5: `gpt-5.5`, `gpt-5.5-pro`; dated: `gpt-5.5-2026-04-23`, `gpt-5.5-pro-2026-04-23`
- Reasoning (o-series): `o3`, `o3-mini`, `o4-mini`

### Google Gemini (chat + image)
- Chat: `gemini-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`, `gemini-3.1-pro-preview`, `gemini-3.1-pro-preview-customtools`, `gemini-flash-latest`, `gemini-flash-lite-latest`
- Image: `gemini-2.5-flash-image`, `gemini-3-pro-image`, `gemini-3.1-flash-image`, `gemini-3.1-flash-lite-image`