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Run Vision
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientSet 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("nvidia/nemotron-3-5-super/vision", {
input: {
prompt: "Summarize the key ideas of hybrid Mamba-Transformer models.",
image_url: "https://storage.googleapis.com/falserverless/example_inputs/dog.png"
},
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"
});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("nvidia/nemotron-3-5-super/vision", {
input: {
prompt: "Summarize the key ideas of hybrid Mamba-Transformer models.",
image_url: "https://storage.googleapis.com/falserverless/example_inputs/dog.png"
},
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("nvidia/nemotron-3-5-super/vision", {
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("nvidia/nemotron-3-5-super/vision", {
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);Read more about file handling in our file upload guide.
prompt string* requiredText prompt to send to the model.
system_prompt stringOptional system prompt to steer the model.
reasoning_mode ReasoningModeEnumthink emits an explicit reasoning trace before the final answer; no_think returns a direct answer. Default value: "no_think"
Possible enum values: think, no_think
max_tokens integerMaximum number of tokens to generate. Default value: 1024
temperature floatSampling temperature. NVIDIA recommends 1.0 for all tasks. Default value: 1
top_p floatNucleus sampling probability mass. Default value: 0.95
enable_safety_checker booleanWhether to enable the safety checker. Default value: true
image_url string* requiredURL of the image to reason about. RGB JPEG or PNG.
{
"prompt": "Summarize the key ideas of hybrid Mamba-Transformer models.",
"system_prompt": "You are a concise assistant.",
"reasoning_mode": "no_think",
"max_tokens": 1024,
"temperature": 1,
"top_p": 0.95,
"enable_safety_checker": true,
"image_url": "https://storage.googleapis.com/falserverless/example_inputs/dog.png"
}output string* requiredGenerated text response.
reasoning stringReasoning trace, returned only in think mode.
finish_reason stringReason generation stopped. Default value: "stop"
Token usage for the request.
{
"output": "Hello! How can I help?",
"finish_reason": "stop",
"usage": {
"output_tokens": 87,
"input_tokens": 24
}
}input_tokens integer* requiredNumber of input tokens processed.
output_tokens integer* requiredNumber of output tokens generated.