CogVideoX-5B Video to Video
About
Video to video generation using CogVideoX-5B.
1. Calling the API#
Install the client#
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientMigrate to @fal-ai/client
The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Please check the migration guide for more information.
Setup your API Key#
Set FAL_KEY as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"Submit a request#
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/cogvideox-5b/video-to-video", {
  input: {
    prompt: "An astronaut stands triumphantly at the peak of a towering mountain. Panorama of rugged peaks and valleys. Very futuristic vibe and animated aesthetic. Highlights of purple and golden colors in the scene. The sky is looks like an animated/cartoonish dream of galaxies, nebulae, stars, planets, moons, but the remainder of the scene is mostly realistic. ",
    video_url: "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/hiker.mp4"
  },
  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);2. Authentication#
The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.
API Key#
import { fal } from "@fal-ai/client";
fal.config({
  credentials: "YOUR_FAL_KEY"
});Protect your API 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.
3. Queue#
Submit a request#
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/cogvideox-5b/video-to-video", {
  input: {
    prompt: "An astronaut stands triumphantly at the peak of a towering mountain. Panorama of rugged peaks and valleys. Very futuristic vibe and animated aesthetic. Highlights of purple and golden colors in the scene. The sky is looks like an animated/cartoonish dream of galaxies, nebulae, stars, planets, moons, but the remainder of the scene is mostly realistic. ",
    video_url: "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/hiker.mp4"
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});Fetch request status#
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/cogvideox-5b/video-to-video", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});Get the result#
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/cogvideox-5b/video-to-video", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);4. Files#
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.
Data URI (base64)#
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.
Hosted files (URL)#
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.
Uploading files#
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);Auto uploads
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.
5. Schema#
Input#
prompt string* requiredThe prompt to generate the video from.
The size of the generated video.
Possible enum values: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9
Note: For custom image sizes, you can pass the width and height as an object:
"image_size": {
  "width": 1280,
  "height": 720
}negative_prompt stringThe negative prompt to generate video from Default value: ""
The LoRAs to use for the image generation. We currently support one lora.
num_inference_steps integerThe number of inference steps to perform. Default value: 50
seed integerThe same seed and the same prompt given to the same version of the model will output the same video every time.
guidance_scale floatThe CFG (Classifier Free Guidance) scale is a measure of how close you want
the model to stick to your prompt when looking for a related video to show you. Default value: 7
use_rife booleanUse RIFE for video interpolation Default value: true
export_fps integerThe target FPS of the video Default value: 16
video_url string* requiredThe video to generate the video from.
strength floatThe strength to use for Video to Video.  1.0 completely remakes the video while 0.0 preserves the original. Default value: 0.8
{
  "prompt": "An astronaut stands triumphantly at the peak of a towering mountain. Panorama of rugged peaks and valleys. Very futuristic vibe and animated aesthetic. Highlights of purple and golden colors in the scene. The sky is looks like an animated/cartoonish dream of galaxies, nebulae, stars, planets, moons, but the remainder of the scene is mostly realistic. ",
  "video_size": {
    "height": 480,
    "width": 720
  },
  "negative_prompt": "Distorted, discontinuous, Ugly, blurry, low resolution, motionless, static, disfigured, disconnected limbs, Ugly faces, incomplete arms",
  "num_inference_steps": 50,
  "guidance_scale": 7,
  "use_rife": true,
  "export_fps": 16,
  "video_url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/hiker.mp4",
  "strength": 0.8
}Output#
The URL to the generated video
seed integer* requiredSeed of the generated video. It will be the same value of the one passed in the input or the randomly generated that was used in case none was passed.
prompt string* requiredThe prompt used for generating the video.
{
  "video": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  },
  "prompt": ""
}Other types#
ImageSize#
width integerThe width of the generated image. Default value: 512
height integerThe height of the generated image. Default value: 512
LoraWeight#
path string* requiredURL or the path to the LoRA weights.
scale floatThe scale of the LoRA weight. This is used to scale the LoRA weight
before merging it with the base model. Default value: 1
File#
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.
file_data stringFile data