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Run Query
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientThe @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.
Set FAL_KEY as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.
import { fal } from "@fal-ai/client";
const result = await fal.subscribe("fal-ai/moondream3-preview/query", {
input: {
image_url: "https://storage.googleapis.com/falserverless/example_inputs/moondream-3-preview/query_in.jpg",
prompt: "List the safety measures taken by this worker in a JSON array under `safety_measures` key"
},
logs: true,
onQueueUpdate: (update) => {
if (update.status === "IN_PROGRESS") {
update.logs.map((log) => log.message).forEach(console.log);
}
},
});
console.log(result.data);
console.log(result.requestId);The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_KEY"
});When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY. Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide.
The client API provides a convenient way to submit requests to the model.
import { fal } from "@fal-ai/client";
const { request_id } = await fal.queue.submit("fal-ai/moondream3-preview/query", {
input: {
image_url: "https://storage.googleapis.com/falserverless/example_inputs/moondream-3-preview/query_in.jpg",
prompt: "List the safety measures taken by this worker in a JSON array under `safety_measures` key"
},
webhookUrl: "https://optional.webhook.url/for/results",
});You can fetch the status of a request to check if it is completed or still in progress.
import { fal } from "@fal-ai/client";
const status = await fal.queue.status("fal-ai/moondream3-preview/query", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
logs: true,
});Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.
import { fal } from "@fal-ai/client";
const result = await fal.queue.result("fal-ai/moondream3-preview/query", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.
You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.
You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.
We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.
import { fal } from "@fal-ai/client";
const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).
Read more about file handling in our file upload guide.
image_url string* requiredURL of the image to be processed
prompt string* requiredQuery to be asked in the image
reasoning booleanWhether to include detailed reasoning behind the answer Default value: true
temperature floatSampling temperature to use, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If not set, defaults to 0.
top_p floatNucleus sampling probability mass to use, between 0 and 1.
{
"image_url": "https://storage.googleapis.com/falserverless/example_inputs/moondream-3-preview/query_in.jpg",
"prompt": "List the safety measures taken by this worker in a JSON array under `safety_measures` key",
"reasoning": true
}finish_reason string* requiredReason for finishing the output generation
Usage information for the request
output string* requiredAnswer to the query about the image
reasoning stringDetailed reasoning behind the answer, if enabled
{
"finish_reason": "stop",
"usage_info": {
"prefill_time_ms": 54.45315001998097,
"ttft_ms": 91.87838807702065,
"decode_time_ms": 811.5944429300725,
"input_tokens": 737,
"output_tokens": 23
},
"output": "{\n \"safety_measures\": [\n \"Red hard hat\",\n \"Safety glasses\"\n ]\n}",
"reasoning": "The worker is wearing a red hard hat for head protection and safety glasses for eye protection."
}input_tokens integer* requiredNumber of input tokens processed
output_tokens integer* requiredNumber of output tokens generated
prefill_time_ms float* requiredTime taken for prefill in milliseconds
decode_time_ms float* requiredTime taken for decoding in milliseconds
ttft_ms float* requiredTime to first token in milliseconds