This is my first trying the new Vercel's generative UI with AI SDK, I am using Google's Gemini AI with the gemini-1.5-pro-latest model, It worked flawlessly on my local but when deployed it returns this response:
responseBody: '{\n' +
' "error": {\n' +
' "code": 429,\n' +
' "message": "Resource has been exhausted (e.g. check quota).",\n' +
' "status": "RESOURCE_EXHAUSTED"\n' +
' }\n' +
'}\n',
I am using Next 14 with Typescript, so the function is on server side (copied from Vercel's documentation), here is the function to call the SDK:
export async function continueConversation(
input: string
): Promise<ClientMessage> {
"use server";
const history = getMutableAIState();
const result = await streamUI({
model: google("models/gemini-1.5-pro-latest"),
system: `
You are a general purpose assistant, you can help the user with a variety of tasks. You can tell jokes, give place and song recommendations, and much more. You are a professional, don't use emote.
`,
messages: [...history.get(), { role: "user", content: input }],
text: ({ content, done }) => {
if (done) {
history.done((messages: ServerMessage[]) => [
...messages,
{ role: "assistant", content },
]);
}
return (
<article className="markdown-container">
<Markdown remarkPlugins={[remarkGfm]}>{content}</Markdown>
</article>
);
},
tools: {
getJoke: {
description:
"A tool when the user wants a joke. The joke should make the user laugh.",
parameters: z.object({
category: z.string().optional().describe("the category of the joke"),
}),
generate: async function* ({ category }) {
yield <LoaderCircle />;
const joke = await generateObject({
model: google("models/gemini-1.5-pro-latest"),
schema: jokeSchema,
prompt:
"Generate a joke that will make the user laugh. The joke should be in the category of " +
category +
". If no category is provided, ask the user for a category.",
});
return <JokeComponent joke={joke.object} />;
},
},
getPlaces: {
description:
"A tool when the user wants place recommendations based on the location and type.",
parameters: z.object({
location: z.string().describe("the user's location"),
type: z.string().optional().describe("the type of place"),
}),
generate: async function* ({ location, type }) {
yield <LoaderCircle className="loader-circle" />;
const places = await generateObject({
model: google("models/gemini-1.5-pro-latest"),
schema: placeSchema,
prompt:
"Generate an array of places to visit in " +
location +
" with the type of " +
(type || "any type") +
". The array should contain at least 5 places.",
});
if (places && places.object && Array.isArray(places.object)) {
return <PlaceComponent place={places.object} />;
} else {
return <p>Something went wrong, please try again later.</p>;
}
},
},
getSongs: {
description:
"A tool when the user wants song recommendations based on the genre.",
parameters: z.object({
genre: z.string().optional().describe("the genre of the song"),
singer: z.string().optional().describe("the singer of the song"),
}),
generate: async function* ({ genre, singer }) {
yield <LoaderCircle />;
const songs = await generateObject({
model: google("models/gemini-1.5-pro-latest"),
schema: songSchema,
prompt:
"Generate songs recommendation in the genre of " +
(genre || "any genres") +
"or by the singer " +
(singer || "any singer") +
". Return an array of 3 songs.",
});
if (songs && songs.object && Array.isArray(songs.object)) {
return <SongComponent song={songs.object} />;
} else {
return <p>Something went wrong, please try again later.</p>;
}
},
},
},
});
return {
id: nanoid(),
role: "assistant",
display: result.value,
};
}
Here is the full actions.tsx and page.tsx:
I tried to change the API key with new accounts to no avail, the thing is, it still works on my local :< Any suggestions will be very appreciated, thanks!
If you are seeing a 429 quota error, then you have run out of quota.
You can see the default quota here: https://ai.google.dev/pricing (make sure you choose the model you are using).
As you are using gemini-1.5-pro-latest, and I assume you're using the free tier, your quota is 2 requests per minute. If you try a 2-turn request locally, and then deploy the same API key to another environment and run it within a minute, you won't have any remaining quota.
Try waiting a minute and see if the error persists. Otherwise try using a model with more quota, like gemini-1.5-flash-latest.