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Process 3D Model Mv
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/hunyuan3d/v2/multi-view", {
input: {
front_image_url: "https://storage.googleapis.com/falserverless/model_tests/video_models/front.png",
back_image_url: "https://storage.googleapis.com/falserverless/model_tests/video_models/back.png",
left_image_url: "https://storage.googleapis.com/falserverless/model_tests/video_models/left.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"
});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/hunyuan3d/v2/multi-view", {
input: {
front_image_url: "https://storage.googleapis.com/falserverless/model_tests/video_models/front.png",
back_image_url: "https://storage.googleapis.com/falserverless/model_tests/video_models/back.png",
left_image_url: "https://storage.googleapis.com/falserverless/model_tests/video_models/left.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("fal-ai/hunyuan3d/v2/multi-view", {
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/hunyuan3d/v2/multi-view", {
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.
front_image_url string* requiredURL of image to use while generating the 3D model.
back_image_url string* requiredURL of image to use while generating the 3D model.
left_image_url string* requiredURL of image to use while generating the 3D model.
seed integerThe same seed and the same prompt given to the same version of the model will output the same image every time.
num_inference_steps integerNumber of inference steps to perform. Default value: 50
guidance_scale floatGuidance scale for the model. Default value: 7.5
octree_resolution integerOctree resolution for the model. Default value: 256
textured_mesh booleanIf set true, textured mesh will be generated and the price charged would be 3 times that of white mesh.
{
"front_image_url": "https://storage.googleapis.com/falserverless/model_tests/video_models/front.png",
"back_image_url": "https://storage.googleapis.com/falserverless/model_tests/video_models/back.png",
"left_image_url": "https://storage.googleapis.com/falserverless/model_tests/video_models/left.png",
"num_inference_steps": 50,
"guidance_scale": 7.5,
"octree_resolution": 256
}Generated 3D object file.
seed integer* requiredSeed value used for generation.
{
"model_mesh": {
"url": "https://storage.googleapis.com/falserverless/model_tests/video_models/mesh.glb",
"file_name": "white_mesh.glb",
"file_size": 720696,
"content_type": "model/gltf-binary"
}
}url string* requiredThe URL where the file can be downloaded from.
content_type stringThe mime type of the file.
file_name stringThe name of the file. It will be auto-generated if not provided.
file_size integerThe size of the file in bytes.