Google Gemini

GEMINI_API_KEY=your-api-key-here

import { createGeminiChat } from "@tanstack/ai-gemini";

const adapter = createGeminiChat("gemini-3.8-flash", process.env.GEMINI_API_KEY!);

import {
  chat,
  chatParamsFromRequest,
  toServerSentEventsResponse,
} from "@tanstack/ai";
import { geminiText } from "@tanstack/ai-gemini";

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

  const stream = chat({
    adapter: geminiText("gemini-3.8-flash"),
    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 { geminiImage } from "@tanstack/ai-gemini";

const result = await generateImage({
  adapter: geminiImage("gemini-nano-banana-2.1"),
  prompt: "A futuristic cityscape at sunset",
  threadId: "thread-1",
  numberOfImages: 1,
  size: "16:9_4K",
});

console.log(result.images);

import { chat, toServerSentEventsResponse } from "@tanstack/ai";
import { geminiText, uploadGeminiFile, geminiVideoPart } from "@tanstack/ai-gemini";

export async function POST(request: Request) {
  const file = await uploadGeminiFile("./demo.mp4", { mimeType: "video/mp4" });

  const stream = chat({
    adapter: geminiText("gemini-3.8-flash"),
    messages: [
      {
        role: "user",
        content: [
          { type: "text", content: "Summarize this video and cite timestamps." },
          geminiVideoPart(file),
        ],
      },
    ],
    threadId: "thread-1",
  });

  return toServerSentEventsResponse(stream);
}

import { generateSpeech } from "@tanstack/ai";
import { geminiSpeech } from "@tanstack/ai-gemini";

const result = await generateSpeech({
  adapter: geminiSpeech("gemini-3.1-flash-tts-preview"),
  text: "Hello from Gemini TTS!",
  threadId: "thread-1",
});

console.log(result.audio); // Base64 encoded audio

import { embed } from "@tanstack/ai";
import { geminiEmbedding } from "@tanstack/ai-gemini";

const result = await embed({
  adapter: geminiEmbedding("gemini-embedding-001"),
  input: "a red guitar",
  dimensions: 1536,
  modelOptions: {
    taskType: "RETRIEVAL_DOCUMENT",
  },
});

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

import { summarize } from "@tanstack/ai";
import { geminiSummarize } from "@tanstack/ai-gemini";

const result = await summarize({
  adapter: geminiSummarize("gemini-3.1-pro-preview"),
  text: "Your long text to summarize...",
  threadId: "thread-1",
  maxLength: 100,
  style: "concise", // "concise" | "bullet-points" | "paragraph"
});

console.log(result.summary);

import { chat } from "@tanstack/ai";
import { geminiText } from "@tanstack/ai-gemini";
import { googleSearchTool } from "@tanstack/ai-gemini/tools";

const stream = chat({
  adapter: geminiText("gemini-3.8-flash"),
  messages: [{ role: "user", content: "What's the weather in Tokyo right now?" }],
  threadId: "thread-1",
  tools: [googleSearchTool()],
});

import { chat } from "@tanstack/ai";
import { geminiText } from "@tanstack/ai-gemini";

const stream = chat({
  adapter: geminiText("gemini-3.8-flash"),
  messages: [{ role: "user", content: "Hello!" }],
  threadId: "thread-1",
  modelOptions: {
    maxOutputTokens: 2048,
    temperature: 0.7,
    topP: 0.9,
    topK: 40,
    stopSequences: ["END"],
  },
});

import { chat } from "@tanstack/ai";
import { geminiText } from "@tanstack/ai-gemini";

const stream = chat({
  adapter: geminiText("gemini-3.8-flash"),
  messages: [{ role: "user", content: "Plan a database migration." }],
  threadId: "thread-1",
  reasoning: "high",
});

import { chat } from "@tanstack/ai";
import { geminiText } from "@tanstack/ai-gemini";

const stream = chat({
  adapter: geminiText("gemini-2.5-pro"),
  messages: [{ role: "user", content: "Check this proof." }],
  threadId: "thread-1",
  reasoning: { level: "high", budgetTokens: 8000 },
});