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fal-ai/ffmpeg-api/metadata
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fal-ai/ffmpeg-api/metadata
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LLMs
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Table of contents

Get encoding metadata from video and audio files using FFmpeg API.
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fal-ai/ffmpeg-api/metadata

Get encoding metadata from video and audio files using FFmpeg API.
Inference
Commercial use
Schema
LLMs
PlaygroundAPI
Loading API documentation

Table of contents

Table of contents

1. Calling the API

  • Install the client
  • Setup your API Key
  • Submit a request

2. Authentication

  • API Key

3. Queue

  • Submit a request
  • Fetch request status
  • Get the result

4. Files

  • Data URI (base64)
  • Hosted files (URL)
  • Uploading files

5. Schema

  • Input
  • Output
  • Other

About

Metadata

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client
Migrate to @fal-ai/client

The @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.

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/ffmpeg-api/metadata", {
  input: {
    media_url: ""
  },
  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#

In an environment where you cannot set environment variables, you can configure the API key manually on the client.
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#

Long-running requests

For long-running requests, such as training jobs or models with slower inference times, it is recommended to check the Queue status and rely on Webhooks instead of blocking while waiting for the result.

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/ffmpeg-api/metadata", {
  input: {
    media_url: ""
  },
  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/ffmpeg-api/metadata", {
  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/ffmpeg-api/metadata", {
  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#

media_url string* required

URL of the media file (video or audio) to analyze

extract_frames boolean

Whether to extract the start and end frames for videos. Note that when true the request will be slower.

{
  "media_url": ""
}

Output#

media Video | Audio* required

Metadata for the analyzed media file (either Video or Audio)

{
  "media": {
    "media_type": "video",
    "url": "",
    "content_type": "",
    "file_name": "",
    "codec": "",
    "container": "",
    "timebase": "",
    "resolution": {
      "aspect_ratio": ""
    },
    "format": {
      "container": "",
      "video_codec": "",
      "profile": "",
      "pixel_format": ""
    }
  }
}

Other types#

Video#

media_type string

Type of media (always 'video') Default value: "video"

url string* required

URL where the media file can be accessed

content_type string* required

MIME type of the media file

file_name string* required

Original filename of the media

file_size integer* required

Size of the file in bytes

duration float* required

Duration of the media in seconds

bitrate integer* required

Overall bitrate of the media in bits per second

codec string* required

Codec used to encode the media

container string* required

Container format of the media file (e.g., 'mp4', 'mov')

fps integer* required

Frames per second

frame_count integer* required

Total number of frames in the video

timebase string* required

Time base used for frame timestamps

resolution Resolution* required

Video resolution information

format VideoFormat* required

Detailed video format information

audio AudioTrack

Audio track information if video has audio

start_frame_url string

URL of the extracted first frame

end_frame_url string

URL of the extracted last frame

Audio#

media_type string

Type of media (always 'audio') Default value: "audio"

url string* required

URL where the media file can be accessed

content_type string* required

MIME type of the media file

file_name string* required

Original filename of the media

file_size integer* required

Size of the file in bytes

duration float* required

Duration of the media in seconds

bitrate integer* required

Overall bitrate of the media in bits per second

codec string* required

Codec used to encode the media

container string* required

Container format of the media file (e.g., 'mp4', 'mov')

channels integer* required

Number of audio channels

sample_rate integer* required

Audio sample rate in Hz

Resolution#

aspect_ratio string* required

Display aspect ratio (e.g., '16:9')

width integer* required

Width of the video in pixels

height integer* required

Height of the video in pixels

VideoFormat#

container string* required

Container format of the video

video_codec string* required

Video codec used (e.g., 'h264')

profile string* required

Codec profile (e.g., 'main', 'high')

level float* required

Codec level (e.g., 4.1)

pixel_format string* required

Pixel format used (e.g., 'yuv420p')

bitrate integer* required

Video bitrate in bits per second

AudioTrack#

codec string* required

Audio codec used (e.g., 'aac', 'mp3')

channels integer* required

Number of audio channels

sample_rate integer* required

Audio sample rate in Hz

bitrate integer* required

Audio bitrate in bits per second