OpenAI

OPENAI_API_KEY=sk-...

import { createOpenaiChat } from "@tanstack/ai-openai";

const adapter = createOpenaiChat("gpt-6.1-sol", process.env.OPENAI_API_KEY!);

import {
  chat,
  chatParamsFromRequest,
  toServerSentEventsResponse,
} from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";

export async function POST(request: Request) {
  const { messages, threadId, runId } = await chatParamsFromRequest(request);

  const stream = chat({
    adapter: openaiText("gpt-6.1-sol"),
    messages,
    threadId,
    runId,
  });

  return toServerSentEventsResponse(stream);
}

import { useState } from "react";
import { useChat, fetchServerSentEvents } from "@tanstack/ai-react";

export function Chat() {
  const [input, setInput] = useState("");
  const { messages, sendMessage } = useChat({
    connection: fetchServerSentEvents("/api/chat"),
    threadId: "support-chat",
  });

  return (
    <form
      onSubmit={(event) => {
        event.preventDefault();
        sendMessage(input);
        setInput("");
      }}
    >
      {messages.map((message) => (
        <p key={message.id}>
          {message.parts
            .map((part) => (part.type === "text" ? part.content : ""))
            .join("")}
        </p>
      ))}
      <input value={input} onChange={(event) => setInput(event.target.value)} />
    </form>
  );
}

import { generateImage } from "@tanstack/ai";
import { openaiImage } from "@tanstack/ai-openai";

const result = await generateImage({
  adapter: openaiImage("gpt-image-2.5-flare"),
  prompt: "A futuristic cityscape at sunset",
  threadId: "thread-1",
  numberOfImages: 1,
  size: "1024x1024",
  modelOptions: {
    quality: "high",
  },
});

console.log(result.images);

import { generateSpeech } from "@tanstack/ai";
import { openaiSpeech } from "@tanstack/ai-openai";

const result = await generateSpeech({
  adapter: openaiSpeech("tts-1"),
  text: "Hello, welcome to TanStack AI!",
  threadId: "thread-1",
  voice: "alloy",
  format: "mp3",
});

// result.audio holds base64-encoded audio
console.log(result.format); // "mp3"

import { generateTranscription } from "@tanstack/ai";
import { openaiTranscription } from "@tanstack/ai-openai";
import { audioFile } from "./audio";

const result = await generateTranscription({
  adapter: openaiTranscription("whisper-1"),
  audio: audioFile, // File object or base64 string
  language: "en",
  threadId: "thread-1",
});

console.log(result.text);

import { embed } from "@tanstack/ai";
import { openaiEmbedding } from "@tanstack/ai-openai";

const result = await embed({
  adapter: openaiEmbedding("text-embedding-3-small"),
  input: ["a red guitar", "a blue drum kit"],
});

console.log(result.embeddings[0]?.vector);
console.log(result.usage?.promptTokens);

import { embed } from "@tanstack/ai";
import { openaiEmbedding } from "@tanstack/ai-openai";

const result = await embed({
  adapter: openaiEmbedding("text-embedding-3-large"),
  input: "a red guitar",
  dimensions: 1024,
});

import { summarize } from "@tanstack/ai";
import { openaiSummarize } from "@tanstack/ai-openai";

const result = await summarize({
  adapter: openaiSummarize("gpt-5-mini"),
  text: "Your long text to summarize...",
  threadId: "thread-1",
  maxLength: 100,
  style: "concise", // "concise" | "bullet-points" | "paragraph"
});

console.log(result.summary);

import { decide, choice, score, boolean } from "@tanstack/ai";
import { openaiDecider } from "@tanstack/ai-openai";

const ticket = {
  subject: "Charged twice for the same invoice",
  body: "Please refund the extra payment.",
};

const result = await decide({
  adapter: openaiDecider("gpt-6-luna"),
  state: ticket,
  questions: {
    queue: choice({
      instructions: "Which team should handle this ticket?",
      options: {
        billing: "Payments, invoices, refunds",
        tech: "Bugs, outages, integrations",
        sales: "Pricing, upgrades, new accounts",
      },
    }),
    urgency: score({
      instructions: "How urgent is this ticket?",
      levels: ["low", "medium", "high"],
    }),
    refund: boolean({
      instructions: "Is the customer asking for a refund?",
    }),
  },
});

console.log(result.queue.value); // "billing"
console.log(result.urgency.value); // "medium"
console.log(result.refund.value); // true
console.log(result.meta.usage);

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { webSearchTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-6.1-sol"),
  messages: [{ role: "user", content: "What's new in AI this week?" }],
  threadId: "thread-1",
  tools: [webSearchTool({ type: "web_search" })],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";

const stream = chat({
  adapter: openaiText("gpt-4.1"),
  messages: [{ role: "user", content: "Hello!" }],
  threadId: "thread-1",
  modelOptions: {
    temperature: 0.7,
    max_output_tokens: 1000,
    top_p: 0.9,
  },
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";

const stream = chat({
  adapter: openaiText("gpt-6.1-sol"),
  messages: [{ role: "user", content: "Plan a database migration." }],
  threadId: "thread-1",
  reasoning: "xhigh",
});