Drop-in SDKs

The gateway speaks the protocols you already use: the OpenAI, Anthropic, and Google AI APIs, with messages, tools, and multi-turn conversation working exactly as they do natively. If you already use one of those SDKs, keep it. Point it at Opper and swap the API key for an Opper one, and every call now flows through the gateway. You get 300+ models, fallback routing, traces, and organization Rules without rewriting anything.

Setup

For all three SDKs the change is the same:

Set the base URL to https://api.opper.ai/v3/compat
Pass your Opper API key as the SDK’s normal api_key

Opper reads the key from Authorization: Bearer, which is what the OpenAI SDK sends. On the routes that serve a vendor’s own protocol it reads that protocol’s header too — x-api-key on the Anthropic Messages endpoints, x-goog-api-key on the Google ones. So all three SDKs authenticate with nothing but their normal api_key.

SDK examples

OpenAI
Anthropic
Google AI

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.opper.ai/v3/compat",
    api_key=os.environ["OPPER_API_KEY"],
)

response = client.chat.completions.create(
    model="openai/gpt-5-mini",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
    baseURL: "https://api.opper.ai/v3/compat",
    apiKey: process.env.OPPER_API_KEY!,
});

const response = await client.chat.completions.create({
    model: "openai/gpt-5-mini",
    messages: [{ role: "user", content: "Hello" }],
});
console.log(response.choices[0].message.content);

Works with chat.completions.create, embeddings.create, and responses.create.

import os
from anthropic import Anthropic

client = Anthropic(
    base_url="https://api.opper.ai/v3/compat",
    api_key=os.environ["OPPER_API_KEY"],
)

message = client.messages.create(
    model="anthropic/claude-sonnet-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}],
)
print(message.content[0].text)

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

const client = new Anthropic({
    baseURL: "https://api.opper.ai/v3/compat",
    apiKey: process.env.OPPER_API_KEY!,
});

const message = await client.messages.create({
    model: "anthropic/claude-sonnet-4-6",
    max_tokens: 1024,
    messages: [{ role: "user", content: "Hello" }],
});
if (message.content[0].type === "text") console.log(message.content[0].text);

client.models.list() also works, but the model list isn’t a Messages route, so it reads only the bearer header. On a client you list models from, pass the key as auth_token (authToken in TypeScript) instead of api_key.

import os
from google import genai

client = genai.Client(
    api_key=os.environ["OPPER_API_KEY"],
    http_options={"base_url": "https://api.opper.ai/v3/compat"},
)

response = client.models.generate_content(
    model="gemini/gemini-2.5-pro",
    contents="Hello",
)
print(response.text)

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

const client = new GoogleGenAI({
    apiKey: process.env.OPPER_API_KEY!,
    httpOptions: { baseUrl: "https://api.opper.ai/v3/compat" },
});

const response = await client.models.generateContent({
    model: "gemini/gemini-2.5-pro",
    contents: "Hello",
});
console.log(response.text);

Cross-vendor models

The model field is provider-prefixed: openai/gpt-5.5, anthropic/claude-sonnet-4-6, gemini/gemini-2.5-pro. You can call any of them from any SDK. Your code calling client.messages.create(...) with the Anthropic SDK can still talk to a Google model.

Browse the full catalog on the Models page.

Opper extras

Each SDK lets you send Opper-specific options through an extras field. Use them to wire in fallback models, attach tags for filtering traces, or skip automatic scoring.

Option	Does this
`fallback_models`	A list of models to try if the first one fails.
`tags`	A key/value object for grouping calls in traces.
`span_uuid`	Attach this call to a parent span you created with the Opper SDK.
`evaluate`	Set to `false` to skip score check scoring.

Python with extras

response = client.chat.completions.create(
    model="openai/gpt-5-mini",
    messages=[{"role": "user", "content": "Hello"}],
    extra_body={
        "fallback_models": ["anthropic/claude-haiku-4-5"],
        "tags": {"user_id": "u_123"},
        "evaluate": False,
    },
)

To attribute usage and cost per customer or team — not just label traces — send tags with the X-Opper-Tags header instead, then group spend by tag in analytics. See Tags & usage attribution.

All the URLs

You usually don’t need this. Your SDK appends the right path. For reference:

URL	What it mimics
`POST /v3/compat/chat/completions`	OpenAI Chat Completions
`POST /v3/compat/responses`	OpenAI Responses API
`POST /v3/compat/embeddings`	OpenAI Embeddings
`POST /v3/compat/v1/messages`	Anthropic Messages
`GET /v3/compat/v1/models`	Anthropic Models list
`POST /v3/compat/v1beta/interactions`	Google AI Interactions
`POST /v3/compat/openresponses`	OpenResponses (vendor-neutral)

Hostnames: global and EU

The same gateway is reachable on three hostnames. All of them take the same auth and serve the same models.

Hostname	What it is
`api.opper.ai/v3/compat`	The canonical URL used above. Served from the EU (Stockholm).
`gw.opper.ai`	Global edge endpoint — TLS terminates at the CDN edge nearest your callers, then rides an accelerated path to the EU backend.
`eu.gw.opper.ai`	EU-resident twin of `gw` — TLS terminates only in Stockholm, for hard EU-residency requirements.

The gw hosts also serve the vendor paths at cleaner base URLs, so SDK config gets shorter:

OpenAI SDK:     base_url = "https://gw.opper.ai/openai/v1"
Anthropic SDK:  base_url = "https://gw.opper.ai/anthropic"
Google AI SDK:  base_url = "https://gw.opper.ai/google"

POST https://gw.opper.ai/chat/completions and POST https://gw.opper.ai/v1/messages also work at the bare root, for tools that take only a hostname and no path.

Frameworks

Vercel AI SDK

Use Opper’s native provider for streamText and generateObject. No compat layer needed.

LangChain / LlamaIndex

Point them at the /v3/compat base URL.

What’s next

Tool calling

Let the model invoke your tools.

Vision & PDFs

Send images and documents in messages.

Streaming

Stream the response token-by-token.

Structured output

Get JSON back, validated against a schema.

Get started

Platform

Build

Observe & Control

Integrations

Tutorials

Tooling

Drop-in SDKs

Setup

SDK examples

Cross-vendor models

Opper extras

All the URLs

Hostnames: global and EU

Frameworks

Vercel AI SDK

LangChain / LlamaIndex

What’s next

Tool calling

Vision & PDFs

Streaming

Structured output

​Setup

​SDK examples

​Cross-vendor models

​Opper extras

​All the URLs

​Hostnames: global and EU

​Frameworks

Vercel AI SDK

LangChain / LlamaIndex

​What’s next

Tool calling

Vision & PDFs

Streaming

Structured output

Setup

SDK examples

Cross-vendor models

Opper extras

All the URLs

Hostnames: global and EU

Frameworks

What’s next