Generate a video from a text prompt using Cosmos Predict 2.5 2B (post-trained).
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/cosmos-predict-2.5/text-to-video", {
input: {
prompt: "A static, locked-off camera frames an industrial conveyor belt steadily transporting rough rocks through a dimly lit quarry processing facility. The belt runs horizontally across the center of the frame, its thick black rubber surface textured with dust and fine gravel. Jagged gray and brown stones of varying sizes tumble forward in a slow, continuous motion, their sharp edges catching the light. Subtle vibrations ripple through the belt’s surface as small pebbles bounce and shift. In the background, blurred steel beams, pipes, and muted industrial machinery create depth without distraction. Cool, diffused overhead lighting casts soft shadows and highlights the gritty textures, emphasizing dust particles in the air and the raw, rugged surfaces of the rocks."
},
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/cosmos-predict-2.5/text-to-video", {
input: {
prompt: "A static, locked-off camera frames an industrial conveyor belt steadily transporting rough rocks through a dimly lit quarry processing facility. The belt runs horizontally across the center of the frame, its thick black rubber surface textured with dust and fine gravel. Jagged gray and brown stones of varying sizes tumble forward in a slow, continuous motion, their sharp edges catching the light. Subtle vibrations ripple through the belt’s surface as small pebbles bounce and shift. In the background, blurred steel beams, pipes, and muted industrial machinery create depth without distraction. Cool, diffused overhead lighting casts soft shadows and highlights the gritty textures, emphasizing dust particles in the air and the raw, rugged surfaces of the rocks."
},
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/cosmos-predict-2.5/text-to-video", {
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/cosmos-predict-2.5/text-to-video", {
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.
prompt string* requiredThe text prompt describing the video to generate.
negative_prompt stringA negative prompt to guide generation away from undesired content. Default value: "The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality."
num_frames integerNumber of frames to generate. Must be between 9 and 93. Default value: 93
num_inference_steps integerNumber of denoising steps. More steps yield higher quality but take longer. Default value: 35
guidance_scale floatClassifier-free guidance scale. Higher values increase prompt adherence. Default value: 7
seed integerRandom seed for reproducible generation.
sync_mode booleanIf True, the media will be returned as a data URI and the output data won't be available in the request history.
video_output_type VideoOutputTypeEnumThe format of the output video. Default value: "X264 (.mp4)"
Possible enum values: X264 (.mp4), VP9 (.webm), PRORES4444 (.mov), GIF (.gif)
video_quality VideoQualityEnumThe quality of the output video. Default value: "high"
Possible enum values: low, medium, high, maximum
{
"prompt": "A static, locked-off camera frames an industrial conveyor belt steadily transporting rough rocks through a dimly lit quarry processing facility. The belt runs horizontally across the center of the frame, its thick black rubber surface textured with dust and fine gravel. Jagged gray and brown stones of varying sizes tumble forward in a slow, continuous motion, their sharp edges catching the light. Subtle vibrations ripple through the belt’s surface as small pebbles bounce and shift. In the background, blurred steel beams, pipes, and muted industrial machinery create depth without distraction. Cool, diffused overhead lighting casts soft shadows and highlights the gritty textures, emphasizing dust particles in the air and the raw, rugged surfaces of the rocks.",
"negative_prompt": "The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality.",
"num_frames": 93,
"num_inference_steps": 35,
"guidance_scale": 7,
"video_output_type": "X264 (.mp4)",
"video_quality": "high"
}The generated video file.
seed integer* requiredThe random seed used for generation.
{
"video": {
"content_type": "video/mp4",
"url": "https://v3b.fal.media/files/b/0a8fabc5/qAi19s0dSuQHDZ3O7D_HV_FkSwbls1.mp4"
}
}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.
width integerThe width of the video
height integerThe height of the video
fps floatThe FPS of the video
duration floatThe duration of the video
num_frames integerThe number of frames in the video