SDK Integration

Endpoints and parameter mappings for the OpenAI and Anthropic SDKs.

This is the reference for integrating the OpenAI and Anthropic SDKs with SERV. For a five-minute setup, start with the Quickstart.

SERV exposes three HTTP endpoints under one base URL: https://inference-api.openserv.ai

Endpoint	Shape	Use it for
POST /v1/chat/completions	OpenAI	Universal. Works with every model in the catalog.
POST /v1/responses	OpenAI	OpenAI models, with streamed reasoning summaries.
POST /v1/messages	Anthropic	Claude and most other providers. See endpoint compatibility.

OpenAI SDK

Chat completions

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://inference-api.openserv.ai/v1",
  apiKey: process.env.SERV_API_KEY,
});

const completion = await client.chat.completions.create({
  model: "gpt-5.4-mini",
  messages: [
    { role: "system", content: "You are a concise assistant." },
    { role: "user", content: "What is a CPU register?" },
  ],
});

console.log(completion.choices[0].message.content);

Responses

Use the Responses API to receive the reasoning trace alongside the answer. OpenAI models only.

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://inference-api.openserv.ai/v1",
  apiKey: process.env.SERV_API_KEY,
});

const response = await client.responses.create({
  model: "gpt-5.4",
  instructions: "You are a careful reasoner.",
  input: "What is the integral of x^2 from 0 to 3?",
});

console.log(response.output_text);

Anthropic SDK

Messages

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

const client = new Anthropic({
  baseURL: "https://inference-api.openserv.ai",
  authToken: process.env.SERV_API_KEY,
});

const message = await client.messages.create({
  model: "claude-haiku-4.5",
  max_tokens: 1024,
  system: "You answer in one sentence.",
  messages: [{ role: "user", content: "What is a CPU register?" }],
});

console.log(message.content.find(b => b.type === "text").text);

Important details

Base URL differs by SDK

SDK	Base URL	Why
OpenAI SDK	https://inference-api.openserv.ai/v1	The OpenAI SDK expects /v1 in the base URL.
Anthropic SDK	https://inference-api.openserv.ai	The Anthropic SDK appends /v1/messages itself. Including /v1 yourself would call /v1/v1/messages, which fails.

Auth field differs by SDK

SDK	Field	Notes
OpenAI SDK	apiKey	Standard.
Anthropic SDK	authToken	apiKey also works, but authToken keeps ANTHROPIC_API_KEY free if you ever fall back to direct Anthropic.

A system prompt is required

Every request needs a system, developer, or instructions message. Requests without one are rejected:

A system prompt is required. Please include a system or developer message in your request.

Where the system prompt goes depends on the endpoint:

Endpoint	Where the system prompt goes
/v1/chat/completions	a { role: "system", content: "..." } message
/v1/responses	top-level instructions
/v1/messages	top-level system

Parameter map

Moving an integration across SDKs comes down to this mapping.

Concept	OpenAI Chat	OpenAI Responses	Anthropic Messages
HTTP path	/v1/chat/completions	/v1/responses	/v1/messages
Auth field (SDK constructor)	apiKey	apiKey	authToken
baseURL suffix to use with SERV	/v1	/v1	(none)
Token cap field	max_completion_tokens	max_output_tokens	max_tokens (required)
System prompt	message with role:"system"	top-level instructions	top-level system
User message shape	{role, content} in messages[]	top-level input (string or array)	{role, content} in messages[]
Reasoning-effort control	reasoning_effort	reasoning: { effort, summary }	thinking: { type:"enabled", budget_tokens }
Streaming	stream: true	stream: true	stream: true
Stop sequences	stop	n/a	stop_sequences
Tool schema	tools: [{type:"function", function:{name, parameters}}]	tools: [{type:"function", ...}]	tools: [{name, input_schema}] (no nested function:)
Tool choice	tool_choice: "auto" | {type:"function", function:{name}}	tool_choice: ...	tool_choice: "auto" | "any" | {type:"tool", name}
Response text	choices[0].message.content	output_text or output[] blocks	content[] array, find the type === "text" block
Token usage	usage.prompt_tokens / completion_tokens / total_tokens	usage.input_tokens / output_tokens / total_tokens	usage.input_tokens / output_tokens
Cache metrics	usage.prompt_tokens_details.cached_tokens	usage.input_tokens_details.cached_tokens	usage.cache_read_input_tokens, usage.cache_creation_input_tokens

See also

• SERV Tools — enable the prompt-injection guard and shadow agents via tool definitions.
• Endpoint compatibility — which models work on which endpoint.
• Quickstart — the five-minute setup.
• SDK Migration — Python, Vercel AI SDK, LangChain, and raw fetch.
• Models — pricing and context windows.