Authenticate

video create

Video upload

Normal

large_logo_avatar.webp

medium_logo_avatar.webp

small_logo_avatar.webp

thumbnail_logo_avatar.webp

logo_avatar.webp

Erikka Innes

large_api-video-blog-tutorials.png

medium_api-video-blog-tutorials.png

small_api-video-blog-tutorials.png

thumbnail_api-video-blog-tutorials.png

api-video-blog-tutorials.png

Tutorials

Python

You've prepared the perfect ad copy for your business, but now you're trying to figure out how you can personalize the ad for each business. One great way to do that would be to use a voice over tool that allows you to customize the content based on the location of your customers. Fortunately, this is available! By combining api.video with aflorithmic.ai's voice over this problem is easy to solve. 

## Imagine, if you will, that you own a pizza chain

To make this fun, let's imagine you are the owner of a popular pizza chain - Renzo's pizza chain. You have fifty different outlets and you've prepared the perfect ad: 

--Insert video here-- 

This ad is great for one of your locations, but you want people near all of your restaurants to know they can eat the best pizza for the least dough. For each location, you'd like to run this ad, but have it play information that tells the listener the city, address, day of the week and the time of the offer being described. 

No problem! We can do this in the tutorial today. Let's get started. 

## Prerequisites 

For this project, you're going to need: 

* An api.video account - [Sign up here!](https://api.video)
* An aflorithmic.ai account - [Sign up here!](https://console.api.audio/)

## Installation

We will use the [api.video Python client](https://github.com/apivideo/python-api-client) and [Aflorithic.ai's apiaudio library](https://docs.api.audio/recipes).

Installation for api.video: 
```pip install api.video```

Installation for Aflorithmic:
```pip install -U apiaudio```

### ffmpeg installation
If you want to run the project as-is, you'll also need to install ffmpeg. These instructions help you with installation on a mac. What you'll want to do is make sure you have brew installed. Then it's very easy, you just install with:

```brew install ffmpeg``` 

You need to install ffmpeg before you install the next two items.

### pydub and pyaudio installation
pydub and pyaudio can also be difficult to install, depending on your set up and what you've tried to install already. If you made the mistake of trying to install these before installing ffmpeg, then what you would do is first run:

```brew remove portaudio```

Then, reinstall this like so: 

```brew install portaudio``` 

After these steps, you should be able to successfully install the modules you'll need. Here's the commands: 

```brew pyaudio```

and 

```brew pydub```

## Project overview 
Here's what we're going to do with the example script today:

1. Prompt to collect the api.video API key and the Aflorithmic API key. 
2. Select our video from the Videos folder (for your own tweaks later you can drop other videos here to use, or use a different folder system to organize your content). 
3. Select the script we want from the Script folder and offer the user a preview of the script to make sure it's the right one. 
4. Select the localization .csv file we want to use with our script.
5. Create a sample audio file with the voice over, using the first line from the .csv file
6. Give the user the sample file so they can make sure it sounds like what they want.
7. Next we'll combine the first audio file with the video.  
9. We'll display that file for review by the user to make sure it looks right.
10. If the user approves the file, one by one we'll create an audio file, combine it with the video, tag each video with the information from the csv, and upload it for storage and hosting on api.video.
11. We'll return the user a list of video titles and a link to a playable copy of the final file. 

## Code sample 
Here is the code sample. It's a wizard that will walk you through all the steps. The complete project is available on github here: [https://github.com/apivideo/python-api-client/blob/master/examples/video_audio/README.md](https://github.com/apivideo/python-api-client/blob/master/examples/video_audio/README.md)

## Walkthrough the important stuff
A bunch of the demo is set up to walk you through the process of combining information. We don't need to go over each while loop, but let's go over some details regarding API behavior and the tools used to create the demo. 

### The script 
You can place your script into your code directly by using quotes. It could look like this (I'm saying could because there are a few different ways to set up your api.audio script): 

You can see that the script is split into three sections. This demo doesn't really make use of the features available per section so I'm not going to go into detail for this part. Personalization is achieved by using {{ }} around the name of a column from your csv spreadsheet. They can be used in whatever order you like. 

You can also choose to read your script from a .txt file. If you choose to do this, make sure to take the quotes off from the beginning and end or it will screw up the parser. A common error you will get will say there's a problem with creating a final file or working with a URL and it's usually because something broke before that point, so keep that in mind when debugging. 

In your code, when you set up your script, you'll use a command that looks something like this: 

```script = apiaudio.Script().create(scriptText=text, scriptName=script_details[0], moduleName=script_details[1], projectName=script_details[2])
```

In this snippet, you've already authenticated with your api key (```apiaudip.api_key = your_key```) so now you can work with the api's endpoints. 

The only required field is scriptText, which will contain the text of your script. However it's useful to provide the other names for reference. Be aware that you cannot delete projects or modules. After you set up your script this way, you'll be able to reference it in your code easily via scriptId. Like so:

```script.get("scriptId")```

### The audio file
For starters, when you create an audio file with api.audio, it names your file based on your project name and personalization parameters. In this demo, if you named your project "ad" then every audio file would begin with the word "ad." Next, it puts the headers for the csv file in alphabetical order, and adds the appropriate parameter next to each header. For example, our .csv file has the columns (in this order): 

* city
* address
* day_of_week
* offer_time

After each column title, the entry that appears in the audio file will appear. To separate each column, two underscores are used. Here's a sample:

ad__address_1353%20harlem%20street__city_springfield__day_of_week_tuesday__offer_time_6%20to%208%20pm

So something you'll possibly want to do is rename the files when they arrive. An easy way to handle this is with the built-in os module. 

When creating an audio file you'll do two steps, one is text-to-speech and one is mastering the audio. For text-to-speech you can pick a voice, how fast it will speak and then give it a dictionary containing the list of personalization terms you want to insert into your script. 

You can also choose a template, which will play some background music under your spoken audio. You can see in the demo I used "copacabana." To list voices or background music options, go to the [api.audio API reference docs](https://docs.api.audio/reference) and use the endpoint for listing voices or the endpoint for listing music. 
 
### The .csv
This demo reads information from a .csv file. If you want to read from something else, you can as long as your output for your program to work with becomes a list of dictionaries. .csv is pretty simple to use, so I went with that option.

### Playing a track from your application
You can play a track to check out the audio by using a variety of tools. For this one, I used pydub and pyaudio. These are fairly popular modules. In order to use them, however, audio must be converted to .wav. You will see in the code  that two imports are made from pydub: 

```
from pydub import AudioSegment
from pydub.playback import play
```

These allow us to play straight from the terminal or wherever we may be. The code to convert to .wav and play is very straightforward:

```
wav_track = AudioSegment.from_mp3(file)
wav_track.export(audio_title, format="wav")
```

There are other choices available for converting, but api.audio returns .mp3 files, so we use the from_mp3 choice. 

After we have the track, playing it is as simple as this:

```
play(wav_track)
```

### Merging audio and video 
Prior to uploading your video to api.video, you will want to add the sound and video together. This can be accomplished with ffmpeg, which you need to import to use pydub and pyaudio anyway. The code for merging audio and video is:

```
input_video = ffmpeg.input(video)
input_audio = ffmpeg.input(wav_track)
title = title + ".mp4"
ffmpeg.concat(input_video, input_audio, v=1, a=1).output(title).run()
```

This will produce an mp4. You can then upload it to api.video. 

### Upload to api.video
For details about uploading a video with api.video, you can check out the tutorial about it here: [Upload a Video with the api.video Python Client](https://api.video/blog/tutorials/upload-a-video-with-the-api-video-python-client/)

Something to note is to upload a file, it must be in the same folder as your application or it will not upload.

Once it's uploaded, you can retrieve the .mp4 from the response and play it right away in your browser using the built-in webbrowser module. 

To retrieve the mp4 from the response, you do this:

```
link_mp4 = video_response['assets']['player']
```

And then you can open the link like this:

```
 webbrowser.open(link_mp4)
 ```

This will let you make sure everything combined properly so that the audio matches with the video the way you want. 

### Create all the localized videos
After all the steps to make sure you're creating the right type of video, you can use the recipe from api.audio with a couple of tweaks to create all your new videos with personalized ads by location, then upload them for hosting to api.video.

This demo deletes every video you upload right after the upload happens so you don't end up sitting with fifty videos in a folder.

Thanks for reading! Happy coding. :) 

Localize Advertisement Videos with Personalized Voice Overs!

api.video + aflorithmic.ai: Localize Advertisement Videos with Personalized Voice Overs!

If you'd prefer to watch this tutorial, here's a video version (without the Python client): 
                        <iframe src="https://embed.api.video/vod/vi1cigI8kYmZL5vr4cTJGch6" width="100%" height="100%" frameborder="0" scrolling="no" allowfullscreen="true"></iframe>   

api.video issues a refresh token alongside an access token. You may have seen this if you've examined the json that comes back when you authenticate with your api key. It looks like this (I edited the access_token and refresh_token a lot, they're very long strings in an actual response): 

Each access token is good for one hour, then it expires. You have three ways you can deal with this ongoing expiration: 

* Delegated tokens - If you want, you can use delegated tokens for some of your work. Delegated tokens can have any expiration time you want, so you can avoid dealing with the regular expiration. Delegated tokens are only for use with uploads though. 
* Authenticate again - You can use your API key every time your access token expires, and get a new token. Or, you can use it before your access token expires. 
* Use a refresh token - A refresh token lets you get a new access token without exposing your API credentials. 

In many situations, using a refresh token will be the best option. When you authenticate, store the refresh token somewhere secure so you can use it later. Today's code sample shows you how to retrieve the refresh token, then use it to get a new token. 

And that's it! You can continue developing, or continue services in your system that need a new token to complete tasks. 

If your token expires, hit refresh and protect your API key

small_jozsef-hocza-keys-unsplash.jpg

thumbnail_jozsef-hocza-keys-unsplash.jpg

jozsef-hocza-keys-unsplash.jpg

When your token expires, hit refresh and protect your API key

Delegated Upload

If you have a large video you need to upload, sometimes the server you're uploading to will not accept it in one request. Different servers have different limits. For api.video, you can upload a video file up to a size of 199 MiB before your file is considered too big. Once your video crosses this limit, to upload it you'll need to break it into chunks and send it that way. You send each chunk and the server reassembles it for you. 

In this tutorial, we'll walk through a simple example of how to do a large video upload.

<center><iframe src="https://giphy.com/embed/jVeI3SzbxKGKQ" width="480" height="480" frameBorder="0" class="giphy-embed" allowFullScreen></iframe><p><a href="https://giphy.com/gifs/vhs-vcr-jVeI3SzbxKGKQ">This looks like it would turn into a really big video file.</a></p><br></center>

## Prerequisites
* [Account](https://dashboard.api.video) with api.video 
* api.video API key 
* You'll need access to Python and you'll need to install the requests library if you don't already have it added

And if you'd rather watch this tutorial than read it, check out our video tutorial here: 

## What You'll Be Doing 
This is a quick summary of what you're going to do to upload your large video. 

1. You'll authenticate with api.video using your API key and retrieve a token that lasts one hour that you can use to access all of api.video's other endpoints.
2. You'll create a video container for your video and retrieve the videoId. 
3. You'll use the videoId to create the endpoint you'll send your video to.
4. You'll break up your video file into chunks, then upload each chunk of the video file.

## Troubleshooting / What to Watch Out For 
If you decide to build your own uploader, a few things will help you out: 

* Remember that you must open the file as binary and work with it as binary. It's easy to forget and open it without adding 'rb' or depending on what you're doing, 'wb'.
* Headers are very important. The wrong header will prevent you from sending your content. 
* When using the Content-Range header, you must make sure you are listing the correct set of bytes being sent. If you are off by even one byte, it won't work. You will get weird errors like: 
```UnicodeDecodeError: 'utf-8' codec can't decode byte 0xd1 in position 52: invalid continuation byte``` And the solution is often a simple fix - correct how you're listing your bytes in the header.
* When you send bytes in the Content-Range header, it's inclusive. If you want to send the first 100 bytes, you write it as 0-99. This can get confusing when you're breaking your file into chunks because you can say 'grab the first 100 bytes' and the computer knows to grab 0-99. When you say 'grab the next 100 bytes,' the computer would grab 100-199. However, it's easy to write a dynamic header where you make mistakes like listing 0-100 instead of 0-99, or starting over on the same byte, for example 0-100, then 100-200. All these kinds of mistakes will cause a decode or encoding error. If you choose to build your own uploader instead of using this sample, keep this in mind. 
* If you label what type of file you're sending, you may cause unexpected issues. This sample works by opening, reading, and sending your video file as chunks of binary data. When it arrives, it's encoded into HLS for you, no matter what kind of video it started out as. 

## Code Sample 

```
## How to upload a large video that is over 199 MiB to api.video. (Though this script will also work for videos under 200 MiB if you want to test it out.)

import requests
import os 

## Set up variables for endpoints (we will create the third URL programmatically later)
auth_url = "https://ws.api.video/auth/api-key"
create_url = "https://ws.api.video/videos"

## Set up headers and payload for first authentication request
headers = {
    "Accept": "application/json",
    "Content-Type": "application/json"
}

payload = {
    "apiKey": "your API key here"
}

## Send the first authentication request to get a token. The token can be used for one hour with the rest of the API endpoints.
response = requests.request("POST", auth_url, json=payload, headers=headers)
response = response.json()
token = response.get("access_token")

## Set up headers for authentication - the rest of the endpoints use Bearer authentication.

auth_string = "Bearer " + token

headers2 = {
    "Accept": "application/json",
    "Content-Type": "application/json",
    "Authorization": auth_string
}

## Create the video container payload, you can add more parameters if you like, check out the docs at https://docs.api.video
payload2 = {
    "title": "Demo Vid from my Computer",
    "description": "Video upload test."
}

## Send the request to create the container, and retrieve the videoId from the response.
response = requests.request("POST", create_url, json=payload2, headers=headers2)
response = response.json()
videoId = response["videoId"]

## Create endpoint to upload video to - you have to add the videoId into the URL
upload_url = create_url + "/" + videoId + "/source"

## Set up the chunk size. This is how much you want to read from the file every time you grab a new chunk of your file to read.
## If you're doing a big upload, the recommendation is 50 - 80 MB (50000000-80000000 bytes). It's listed at 6MB (6000000 bytes) because 
## then you can try this sample code with a small file just to see how it will work.  The minimum size for a chunk is 5 MB.

CHUNK_SIZE = 6000000

## This is our chunk reader. This is what gets the next chunk of data ready to send.
def read_in_chunks(file_object, CHUNK_SIZE):
    while True:
        data = file_object.read(CHUNK_SIZE)
        if not data:
            break
        yield data

## Upload your file by breaking it into chunks and sending each piece 
def upload(file, url):
    content_name = str(file)
    content_path = os.path.abspath(file)
    content_size = os.stat(content_path).st_size

    print(content_name, content_path, content_size)

    f = open(content_path, "rb")

    index = 0
    offset = 0
    headers = {}

    for chunk in read_in_chunks(f, CHUNK_SIZE):
        offset = index + len(chunk)
        headers['Content-Range'] = 'bytes %s-%s/%s' % (index, offset -1, content_size)
        headers['Authorization'] = auth_string
        index = offset
        try:

            file = {"file": chunk}
            r = requests.post(url, files=file, headers=headers)
            print(r.json())
            print("r: %s, Content-Range: %s" % (r, headers['Content-Range']))
        except Exception as e:
            print(e)

## Add a path to the file you want to upload, and away we go! 
upload('your-giant-file-here.mp4', upload_url)
```

## Code Walkthrough

Wanna know how it works in a little more detail? Great, here we go! The first couple of sections might look like some of the other blog posts, scroll down for a discussion about the new stuff if that's the case. 

You'll start by adding the requests and os libraries, so you can easily make HTTP requests.

```
import requests
import os
```

Next, let's assign a variable to each endpoint we'll use, they'll be a little easier to work with. We're going to assign two of them here, and we'll use the second one later to build the third one: 
* [Authentication](https://docs.api.video/reference/basic-authentication) endpoint - This is where we send our API key to exchange it for a token. It's **auth_url** in the code sample.
* [Videos](https://docs.api.video/reference/api/Videos#create-a-video-object) endpoint - Specifically we'll use the feature on this endpoint that's for creating a video. It's **create_url** in the code sample.
* [Video Upload](https://docs.api.video/reference/api/Videos#upload-a-video) endpoint - It looks a lot like the other endpoint. It's create_url + "/videoId" + "/source". We'll construct this after we get a videoId to work with. 

```
auth_url = "https://ws.api.video/auth/api-key"
create_url = "https://ws.api.video/videos"
```

### Authentication - Get Your Token
We'll prepare our headers and payload for authentication, then send a POST request to api.video. With the api.video API you start authentication by sending a request using your API key to retrieve a token. You can use your sandbox or your production key, the backend will figure out which you are using and handle it accordingly. If you choose to use your sandbox credentials for this walkthrough, your video will be uploaded with the watermark 'FOR DEVELOPMENT PURPOSES ONLY.': 

```
headers = {
    "Accept": "application/json",
    "Content-Type": "application/json"
}

payload = {
    "apiKey": "your API key here"
}
response = requests.request("POST", auth_url, json=payload, headers=headers)
```

Now we need to get the token from our response, so we can authenticate with the rest of api.video's endpoints when we want to do something. To get the token, we'll convert the response to JSON, then retrieve the token out of the JSON dictionary. 

```
response = response.json()
token = response["access_token"]
```

### Set up a Video Container 
Using the token, we'll get the headers and payload ready for our next request, which will be to ask api.video to create a video container for us.

```
## Set up headers for authentication
headers_bearer = {
    "Accept": "application/json",
    "Content-Type": "application/json",
    "Authorization": auth_string
}

## Create a video container
payload2 = {
    "title": "Demo Vid from my Computer",
    "description": "Video upload of Big Buck Bunny to demo how to do an upload from a folder on your computer."
}
```

api.video endpoints use bearer authentication. Add the authorization header for bearer authentication to your list of headers, and then for the payload we keep it simple, just a title and description. But what about the path to your file? Don't worry we're just creating a container right now. When you upload from your computer, you create a container first, and do your upload second. 

### Send Your Request and Grab the VideoId
For the next part of our walkthrough, we'll send our request, convert the response to JSON, and retrieve the videoId. We need the videoId so we can tell api.video what container we want to upload our video to. 

```
response = requests.request("POST", create_url, json=payload2, headers=headers_bearer)
response = response.json()
videoId = response["videoId"]
```

### Create the Endpoint for Uploading Your Video
Set up the endpoint you'll upload your video to, which is composed of `https://ws.api.video/videos` + `/` + `videoId` + `/source`. 

### Build a Data Chunk Reader
To break your data into chunks, you're going to want to decide how big each chunk should be, and then from an open file keep grabbing the next chunk of data to read. We'll set the chunk size at 1000000 bytes. This is fairly small, in case you wanted to try the sample with a smaller video file to see how it works. If you plan to start using this data chunk reader, make the chunk size larger. A good size is about 50-80 MB or about 50000000-80000000 bytes. 

This function assumes you've already opened your file elsewhere, and it's using **yield**. What this does, is return a generator. Every time you use this function as part of a for loop, it will run until it hits yield, then return the value. Yield 'remembers' where you left off, so each time you loop through, it will return a new chunk of data. 

```
CHUNK_SIZE = 1000000

def read_in_chunks(file_object, CHUNK_SIZE):
    while True:
        data = file_object.read(CHUNK_SIZE)
        if not data:
            break
        yield data
```

### Start Your Large Video Upload 
<center><iframe src="https://giphy.com/embed/TI3IErToEDAERYK7LL" width="480" height="480" frameBorder="0" class="giphy-embed" allowFullScreen></iframe><p><a href="https://giphy.com/gifs/TalentSmiths-loading-talentsmiths-janetsmiths-TI3IErToEDAERYK7LL"></a></p><br></center>
Here's our next function. This one is the upload function, and it contains our chunk reader. What we do here, is use the os library to grab some file details, so we know how big the file we're going to send is, the path to get to it, and the name of the file. 

We open our file, and NOTE...we are opening our file in binary. This is important to remember, since opening a video file in other formats will probably not work. 

Next we set up our index, that's going to represent what point we're at in the file. We also set up the offset, which represents how far forward to move the index after we send each chunk. 

Then we start reading chunks of data. For each chunk of data, we prepare the Content-Range header so we are correctly listing what part of the file we are sending in bytes. To send our data chunk, we need to put it into a one item file dictionary. We do that, and then for readability assign it to a variable. Then we send our request! This will loop through until we're out of data chunks (the last chunk will probably be smaller than the others). 

```
def upload(file, url):
    content_name = str(file)
    content_path = os.path.abspath(file)
    content_size = os.stat(content_path).st_size

    print(content_name, content_path, content_size)

    f = open(content_path, "rb")

    index = 0
    offset = 0
    headers = {}

    for chunk in read_in_chunks(f, CHUNK_SIZE):
        offset = index + len(chunk)
        headers['Content-Range'] = 'bytes %s-%s/%s' % (index, offset -1, content_size)
        headers['Authorization'] = auth_string
        index = offset
        try:

            file = {"file": chunk}
            r = requests.post(url, files=file, headers=headers)
            print(r.json())
            print("r: %s, Content-Range: %s" % (r, headers['Content-Range']))
        except Exception as e:
            print(e)
```

You don't need any other headers. 

You will know you are successful after you send the last chunk. It's possible to receive a -200- response for each chunk, then have it not work out at the very end, so make sure to watch your video upload the first time through. Success is denoted by the response to the last chunk, where you will receive something that looks like this: 

```
{
 'videoId': 'viyourvideoIdz', 
 'title': 'Demo Vid from my Computer', 
 'description': 'Video upload test.', 
 'public': True, 
 'panoramic': False, 
 'mp4Support': True, 
 'publishedAt': '2021-02-08T06:14:53+00:00', 
 'createdAt': '2021-02-08T06:14:53+00:00', 
 'updatedAt': '2021-02-08T06:14:53+00:00', 
 'tags': [], 
 'metadata': [], 
 'source': {
	 'type': 'upload', 
	 'uri': '/videos/vviyourvideoIdz/source'
	 }, 
 'assets': {
	 'iframe': '<iframe src="https://embed.api.video/vod/viyourvideoIdz" width="100%" height="100%" frameborder="0" scrolling="no" allowfullscreen="true"></iframe>', 
	 'player': 'https://embed.api.video/vod/viyourvideoIdz', 
	 'hls': 'https://cdn.api.video/vod/viyourvideoIdz/hls/manifest.m3u8',    
	 'thumbnail': 'https://cdn.api.video/vod/viyourvideoIdz/thumbnail.jpg'
	 }
}
r: <Response [201]>, Content-Range: bytes 4000000-4824145/4824146
```

Check your video's status in [your dashboard](https://dashboard.api.video/). If you have a very large video file, wait a few minutes while api.video finishes processing it. When processing is finished, you'll be able to see a thumbnail for your video and play it from the dashboard. 

If your video upload is unsuccessful, you won't receive the detailed message listed above. You might receive an additional 200 response, or a 400 response for each chunk, depending on how much went wrong with your upload. 
In the dashboard, you may see your video uploaded, but it stays stuck on processing. If this happens, review your code, or contact us with your issue in the [community forum](https://community.api.video/). 



Upload a big video file using Python

small_BigFileWithPython.png

thumbnail_BigFileWithPython.png

Big-File-With-Python.png

If you have some videos on your computer that you need to upload to api.video, you're in luck - today's tutorial will show you how to do just that using Python. Your video must be under 200 MiB to use this method. The code sample is available on github in the [api.video python-examples repository](https://github.com/apivideo/python-examples). Let's get started! 

medium_pexels-designecologist-1779487.jpg

small_pexels-designecologist-1779487.jpg

thumbnail_pexels-designecologist-1779487.jpg

pexels-designecologist-1779487.jpg

## Prerequisites
* An [api.video account](https://dashboard.api.video/register) 
* api.video API key 
* You'll need access to Python and you'll need to install the requests library if you don't already have it added

## What You'll Be Doing
This is a quick summary of what you're going to do to upload your video. 

1. You'll authenticate with api.video using your API key and retrieve a token that lasts one hour that you can use to access all of api.video's other endpoints.
2. You'll create a video container for your video and retrieve the videoId. 
3. You'll use the videoId to upload your video from your computer to api.video. You can only upload a video to the videoId once. If you decide you wanted to upload a different video, you'll have to go through the create container and upload video steps again. You don't need to repeat the part where you get a new token unless your token expires (so if you take an hour long break and come back, you'll need to redo that step then). 

## Code Sample 

```
## How to upload a video under 200 MiB using the api.video API

import requests

## Set up variables for endpoints
auth_url = "https://ws.api.video/auth/api-key"
create_url = "https://ws.api.video/videos"

headers = {
    "Accept": "application/json",
    "Content-Type": "application/json"
}

payload = {
    "apiKey": "your API key here"
}

response = requests.request("POST", auth_url, json=payload, headers=headers)
response = response.json()
token = response.get("access_token")

auth_string = "Bearer " + token


## Set up headers for authentication
headers_bearer = {
    "Accept": "application/json",
    "Content-Type": "application/json",
    "Authorization": auth_string
}

## Create a video container
payload2 = {
    "title": "Demo Vid from my Computer",
    "description": "Video upload of Big Buck Bunny to demo how to do an upload from a folder on your computer."
}

response = requests.request("POST", create_url, json=payload2, headers=headers_bearer)
response = response.json()
videoId = response["videoId"]

## Create endpoint to upload video to
upload_url = upload_url + "/" + videoId + "/source"

## Create upload video headers 
headers_upload = {
    "Accept": "application/vnd.api.video+json",
    "Authorization": auth_string
}

file = {"file": open("local/path/to/myvideo.flv", "rb")}
response = requests.request("POST", upload_url, files=file, headers=headers_upload)
json_response = response.json()
print(json_response)
```

## Code Walkthrough

You'll start by adding the requests library, so you can easily make HTTP requests.

<center><iframe src="https://giphy.com/embed/YGlRW1Am9q7e0" width="320" height="480" frameBorder="0" class="giphy-embed" allowFullScreen></iframe><p><a href="https://giphy.com/gifs/books-libraries-shelves-YGlRW1Am9q7e0">How people added libraries before computers did it for you.</a></p><br></center>

```
import requests
```

Next, let's assign a variable to each endpoint we'll use, they'll be a little easier to work with. We're going to assign two of them here, and we'll use the second one later to build the third one: 
* [Authentication](https://docs.api.video/reference/basic-authentication) endpoint - This is where we send our API key to exchange it for a token. It's **auth_url** in the code sample.
* [Videos](https://docs.api.video/reference/api/Videos#create-a-video-object) endpoint - Specifically we'll use the feature on this endpoint that's for creating a video. It's **create_url** in the code sample.
* [Video Upload](https://docs.api.video/reference/api/Videos#upload-a-video) endpoint - It looks a lot like the other endpoint. It's create_url + "/videoId" + "/source". We'll construct this after we get a videoId to work with. 

```
auth_url = "https://ws.api.video/auth/api-key"
create_url = "https://ws.api.video/videos"
```

### Authentication - Get Your Token
We'll prepare our headers and payload for authentication, then send a POST request to api.video. With the api.video API you start authentication by sending a request using your API key to retrieve a token. You can use your sandbox or your production key, the backend will figure out which you are using and handle it accordingly. If you choose to use your sandbox credentials for this walkthrough, your video will be uploaded with the watermark 'FOR DEVELOPMENT PURPOSES ONLY.': 

```
headers = {
    "Accept": "application/json",
    "Content-Type": "application/json"
}

payload = {
    "apiKey": "your API key here"
}
response = requests.request("POST", auth_url, json=payload, headers=headers)
```

Now we need to get the token from our response, so we can authenticate with the rest of api.video's endpoints when we want to do something. To get the token, we'll convert the response to JSON, then retrieve the token out of the JSON dictionary. 

```
response = response.json()
token = response.get("access_token")
```

### Set up a Video Container 
Using the token, we'll get the headers and payload ready for our next request, which will be to ask api.video to create a video container for us.

```
## Set up headers for authentication
headers_bearer = {
    "Accept": "application/json",
    "Content-Type": "application/json",
    "Authorization": auth_string
}

## Create a video container
payload2 = {
    "title": "Demo Vid from my Computer",
    "description": "Video upload of Big Buck Bunny to demo how to do an upload from a folder on your computer."
}
```

api.video endpoints use bearer authentication. Add the authorization header for bearer authentication to your list of headers, and then for the payload we keep it simple, just a title and description. But what about the path to your file? Don't worry we're just creating a container right now. When you upload from your computer, you create a container first, and do your upload second. 

### Send Your Request and Grab the VideoId
For the next part of our walkthrough, we'll send our request, convert the response to JSON, and retrieve the videoId. We need the videoId so we can tell api.video what container we want to upload our video to. 

```
response = requests.request("POST", create_url, json=payload2, headers=headers_bearer)
response = response.json()
videoId = response["videoId"]
```

### Create the Endpoint for Uploading Your Video
Set up the endpoint you'll upload your video to, which is composed of `https://ws.api.video/videos` + `/` + `videoId` + `/source`. You also need to add the headers. For Python, you don't want to use the "Content-Type": `multipart/form-data` header you see listed if you try the API explorer. Because you are doing an upload with only one part, it won't work. Omit this in your headers. Set things up like this: 

```
headers_upload = {
    "Accept": "application/vnd.api.video+json",
    "Authorization": auth_string
}
```

For the payload, you're sending a video file, so you'll have to open the file, attach it to a dictionary, and for readability, we assign the dictionary to a variable. We use "rb" because we want to open the file as read-only binary format. Check it out: 

```
file = {"file": open("sample-flv-file.flv", "rb")}
```

We can assign our variable in our request to upload our video, and then process and print the request response:

```
response = requests.request("POST", upload_url, files=file, headers=headers_upload)
json_response = response.json()
print(json_response)
```

The response provides a lot of detail about your video:

```
{
	'videoId': 'video ID here', 
	'title': 'Demo Vid from my Computer', 
	'description': 'Video Upload From My Computer', 
	'public': True, 
	'panoramic': False, 
	'mp4Support': True, 
	'publishedAt': '2021-02-05T04:25:02+00:00', 
	'createdAt': '2021-02-05T04:25:02+00:00', 
	'updatedAt': '2021-02-05T04:25:02+00:00', 
	'tags': [], 
	'metadata': [], 
	'source': {
		'type': 'upload', 
		'uri': '/videos/video_ID_here/source'
	 }, 
	'assets': {
		'iframe': '<iframe src="https://embed.api.video/vod/video_ID_here" width="100%" height="100%" frameborder="0" scrolling="no" allowfullscreen="true"></iframe>', 
		'player': 'https://embed.api.video/vod/video_ID_here', 
		'hls': 'https://cdn.api.video/vod/video_ID_here/hls/manifest.m3u8',
		'thumbnail': 'https://cdn.api.video/vod/video_ID_here/thumbnail.jpg'
 }
}
```

* **videoId** - the unique identifier for your new video. Before it was just referencing a container, now it's referencing a container that holds your video!
* **title** - the title you provided for your video when you made the container
* **description** - a description of what the video contains
* **public** - by default, your video is public 
* **panoramic** - by default, your video isn't listed as being a 360° (panoramic is the term api.video uses for 360° or immersive video)
* **mp4Support** - whether you have an mp4 version of your video available or not. By default you do. If you turn this off, your video will not be downloadable from a player and there won't be a link to an mp4 version of your file.
* **publishedAt** - the time your video was published, in ISO-8601 format.
* **createdAt** - the time your video was created, in ISO-8601 format.
* **updatedAt** - the time your video was updated in ISO-8601 format.
* **tags** - you can add individual key words to categorize your videos and make them easier to search if you have a lot of them.
* **metadata** - you can add a dictionary of key value pairs that categorize your videos for searches.
* **source** - this lists the video type, which is upload, and the link you add to the api endpoint to get to your video. 
* **assets** - this is a list of links you can use to set up different services with your video. You can embed an iframe using the iframe code, use the player link to add the file to a player, get the manifest file if you need the source for live streaming, and api.video selects a thumbnail for you automatically. 

You can update all of this information should you choose to. That's it for uploading a video from your computer using Python! 

If you have any questions or suggestions, please share them on our [community forum](https://community.api.video/) and if you still haven't created your api.video account, you can do that [here](https://dashboard.api.video/register). Happy building! 

Upload a video with api.video’s API (Python)

Photo by <a href="https://www.pexels.com/photo/silver-imac-displaying-collage-photos-1779487/">Designecologist</a> from Pexels

Upload a video from your computer with the api.video API (Python)

If Python is your programming language of choice, and you want to quickly upload a video to api.video using a public URL, you've come to the right place. The code sample is available on github in the [api.video python-examples repository](https://github.com/apivideo/python-examples). Let's get started! 

<center><iframe src="https://giphy.com/embed/l0IyjiXOXTX6Yemsg" width="480" height="270" frameBorder="0" class="giphy-embed" allowFullScreen></iframe><p><a href="https://giphy.com/gifs/l0IyjiXOXTX6Yemsg"></a></p><br></center>

## Prerequisites

If you would prefer to watch a video that explains the same information as this tutorial, you can watch this:

* [An api.video account](https://dashboard.api.video/register)
* api.video API key 
* URL for a public video you want to try uploading (we'll be using this link here: [https://www.learningcontainer.com/mp4-sample-video-files-download/#Sample_AVI_File](https://www.learningcontainer.com/mp4-sample-video-files-download/#Sample_AVI_File))
* You'll need access to Python and you'll need to install the requests library if you don't already have it added

You can also review the API reference documentation for uploading videos here: [Upload a video](https://docs.api.video/reference/api/Videos#upload-a-video)

## Code Sample

```
import requests

## Set up variables for endpoints
auth_url = "https://ws.api.video/auth/api-key"
create_url = "https://ws.api.video/videos"

## Set up header for first authentication request
headers = {
    "Accept": "application/json",
    "Content-Type": "application/json"
}

payload = {
    "apiKey": "sandbox or production key here"
}

response = requests.request("POST", auth_url, json=payload, headers=headers)
response = response.json()
token = response.get("access_token")

auth_string = "Bearer " + token


## Set up headers for bearer authentication
headers2 = {
    "Accept": "application/json",
    "Content-Type": "application/json",
    "Authorization": auth_string
}

## Upload the video
payload = {
    "title": "My Demo Video",
    "source": "https://www.learningcontainer.com/mp4-sample-video-files-download/#Sample_AVI_File"
}
response = requests.request("POST", create_url, json=payload, headers=headers2)

## Check out the response
print(response.json())

```

## Code Walkthrough
This section walks through the code to give you an idea of what you'll be doing.

### Set up Authentication with Your API Key
You'll start by adding the requests library, so you can easily make HTTP requests.

```
import requests
```

Next, let's assign a variable to each endpoint we'll use, they'll be a little easier to work with. We're going to use two endpoints today: 
* [Authentication](https://docs.api.video/reference/basic-authentication) endpoint - This is where we send our API key to exchange it for a token. It's **auth_url** in the code sample.
* [Videos](https://docs.api.video/reference/api/Videos#create-a-video-object) endpoint - Specifically we'll use the feature on this endpoint that's for creating a video. It's **create_url** in the code sample.

```
auth_url = "https://ws.api.video/auth/api-key"
create_url = "https://ws.api.video/videos"
```

Create the payload for your headers and the payload for your payload. These are for your authentication request. The api.video API requires that you authenticate with your API key to obtain a token. Your token is good for one hour and can be used to authenticate with all other endpoints. 

NOTE: You can use your sandbox or your production key. The backend for api.video will figure out which you selected and route your request appropriately. If you didn't pay for a full account, all of your videos will be watermarked 'FOR DEVELOPMENT PURPOSES ONLY'.

```
headers = {
    "Accept": "application/json",
    "Content-Type": "application/json"
}

payload = {
    "apiKey": "your API key here"
}

```

Send a request with your header and payload information, convert the response to json so you can retrieve information from it, and then grab **access_token**.

```
response = requests.request("POST", auth_url, json=payload, headers=headers)
response = response.json()
token = response.get("access_token")
```

Now you have your token, you need to set new headers that are for Bearer authentication. Create a string with your token for the new Authorization header, and a new header payload. 

```
auth_string = "Bearer " + token

headers2 = {
    "Accept": "application/json",
    "Content-Type": "application/json",
    "Authorization": auth_string
}
```

### Send Your Video Upload Request

And the part you've been waiting for, the code for video upload! By default, your video is public and includes mp4 support, which is a link to a 1080p mp4 of your file. If you want to change these settings so your video is private or mp4 support is turned off (this will make it so no one can download your video from a player) you can [check our docs](https://docs.api.video/reference/api/Videos#create-a-video-object) for details about all the parameters your payload can include. For now, we'll keep the payload simple: 

```
payload = {
    "title": "My Demo Video",
    "source": "https://www.learningcontainer.com/mp4-sample-video-files-download/#Sample_AVI_File"
}
response = requests.request("POST", create_url, json=payload, headers=headers2)
print(response.json())
```

You can use this payload to see the sample run. For your own upload, you may want to use a different title and a different source link.

### Review Video Details in the Response

When you print the response here, you get back a lot of interesting information about your video: 

```
{'videoId': 'vi8PXlHuWN25wPOVtGfBSQkJ', 
'title': 'My Demo Video', 
'description': '', 
'public': True, 
'panoramic': False, 
'mp4Support': True, 
'publishedAt': '2021-02-04T01:50:23+00:00', 
'createdAt': '2021-02-04T01:50:23+00:00', 
'updatedAt': '2021-02-04T01:50:23+00:00', 
'tags': [], 
'metadata': [], 
'source': {
	'type': 'upload', 
	'uri': '/videos/vi8PXlHuWN25wPOVtGfBSQkJ/source'
	}, 
'assets': {
	'iframe': '<iframe src="https://embed.api.video/vod/vi7EVlHuWN05wPOVtGfBSQkJ" width="100%" height="100%" frameborder="0" scrolling="no" allowfullscreen="true"></iframe>', 
	'player': 'https://embed.api.video/vod/vi8PXlHuWN25wPOVtGfBSQkJ', 
	'hls':'https://cdn.api.video/vod/vi8PXlHuWN25wPOVtGfBSQkJ/hls/manifest.m3u8',   'thumbnail': 'https://cdn.api.video/vod/vi8PXlHuWN25wPOVtGfBSQkJ/thumbnail.jpg'
  }
}
```

* **videoId** - a unique ID that identifies your uploaded video
* **title** - the title of your video
* **description** - if you put a description of your video it appears here
* **public** - whether your video is public or not
* **panoramic** - whether your video is 360° or not
* **mp4Support** - whether your video has an mp4 version of it available or not (turn this off if you don't want people to be able to download your video from a player)
* **publishedAt** - when you first published your uploaded video
* **createdAt** - when your uploaded video was created
* **updatedAt** - when you last updated your video
* **tags** - if you added individual tags to categorize your video with, they appear here
* **metadata** - if you added key value pairs to categorize your videos with, they appear here
* **source** - details about your video source 
* **assets** - different ways you can upload or work with your new video, there's a link you can use with a player, the source file for the hls versio of your video, and a thumbnail that's selected for you (you can change it if you like, but that's a different tutorial)

And that's how you do a simple video upload to api.video! Let us know if you have any questions in [our Community](https://community.api.video/)! Happy building!

Upload a video to api.video using a public URL

large_upload-a-video-to-api-video-using-a-public-url.png

medium_upload-a-video-to-api-video-using-a-public-url.png

small_upload-a-video-to-api-video-using-a-public-url.png

thumbnail_upload-a-video-to-api-video-using-a-public-url.png

upload-a-video-to-api-video-using-a-public-url.png

Video delete

doug.jpg

twitter-brands.svg

Doug Twitter

Doug Sillars

We hate to see it happen, but sometimes a video becomes out of date - the information is no longer correct. Even though you can remove the link, sometimes it is just better to pull it off the web entirely. In this tutorial, we'll walk through the steps to delete a video from your api.video account.

## Authentication

To delete a video from your api.video account, you'll need to [authenticate a session](https://api.video/blog/tutorials/authentication-tutorial/) with your apiKey.  
```
curl -X POST \
https://ws.api.video/auth/api-key \
-H 'Content-Type: application/json' \
-d '{"apiKey": "your_api_key"}'

```

This will return your authorization token for future API requests.

## Deleting


All api.video videos are identified by a videoId.  If you know the videoId of the video you are deleting, you can now begin the deletion process.

> Hint:  The videoId is the random string at the end of the link you use for the video on the web.

Now we simply call the [delete video](https://docs.api.video/reference/api/Videos#delete-a-video-object) endpoint with the videoId in the URL, and the authorization token as a header.

```
curl --request DELETE --url https://ws.api.video/videos/vi3bO7H9UAzibjwF5QxwJcw5  --header 'accept: application/vnd.api.video+json'  --header 'authorization: Bearer {api_token}'
```

This request will delete the video vi3bO7H9UAzibjwF5QxwJcw5.  The api will simply return a 204 response on successful deletion.

## Try it out!

We've built a sample Node application at [delete.a.video](https://delete.a.video). This API selects 3 videos from an api.video account.  This is done with the search video attribute, and will returm the 3 oldest videos called "Live Stream". These three videos are displayed on the page, and by clicking the delete button - you can remove them permanently from the account!

The sample code for the app is on [Github](https://github.com/dougsillars/deleteVideoDemo) if you'd like to use the NodeJS SDK to delete videos.

Questions of comments?  Leave a post on the [community forum](https://community.api.video).

Video deletion: how to delete a video from your account

large_1024px-thebigredbutton-3085157011.jpg

medium_1024px-thebigredbutton-3085157011.jpg

small_1024px-thebigredbutton-3085157011.jpg

thumbnail_1024px-thebigredbutton-3085157011.jpg

1024px-thebigredbutton-3085157011.jpg

Video deletion: Learn how to delete a video from your account

At api.video, we offer a number of ways to upload video into your account. When you [create and upload a video](https://api.video/blog/tutorials/video-upload-tutorial/), the first step is to authenticate with your API, and generate an authentication token.

For a static website, it may not be feasible to create a new token on each page load. For instances like these, we offer a delegated upload token. This token works like a public key to your api.video account, allowing secure uploads without exposing your API key.

## Create an [api.video](https://api.video) account

If you already have an account, you can skip this step.

Before you can start uploading your first video, you need to **[create an api.video account](https://dashboard.api.video/register)**.

Once you are logged in to the Dashboard, select the environment of your choice (sandbox or production) and copy your API key.

large_Screenshot 2024-02-21 at 4.55.04 PM.png

medium_Screenshot 2024-02-21 at 4.55.04 PM.png

small_Screenshot 2024-02-21 at 4.55.04 PM.png

thumbnail_Screenshot 2024-02-21 at 4.55.04 PM.png

copy-api-key-through-dashboard.png

You'll be able to find your API key in the dashboard **[dashboard.api.video](https://dashboard.api.video/overview)**.

There are separate API keys for Sandbox and Production **[environment](https://docs.api.video/reference#environments)**.

In production, you can also manage multiple API keys from your dashboard, for different applications.

## Generate the Upload Token

We will use the [delegated upload API](https://docs.api.video/reference/api/Upload-Tokens#generate-an-upload-token) in order to generate our token. In this example, we will use curl to make the requests, however, you will find examples and code snippets with various programming languages using [api.video API client libraries](https://docs.api.video/sdks/api-clients) in our [documentation](https://docs.api.video/vod/delegated-upload-tokens).

This will result in JSON response with the delegated access token:

`{"token":"to1R5LOYV0091XN3GQva27OS"}`

This token can now be used to upload videos into your api.video account. In the example below, I am uploading a video of clouds into my sandbox account.

Go ahead and try this yourself!  Since the delegated upload is into my sandbox account, the video will be watermarked and deleted after 72 hours. Simply point the ```-F file@``` to a video on your local file system, and it will be uploaded into my sandbox.

You'll receive a response similar to this:


my_cool_video.mp4

These urls can be shared for others to watch your video. On opening the player link, you might see a video like this: (Note the video link in the JSON above has expired and will throw a 404 error).

## Expiring Delegated tokens

Delegated tokens act like a public API - anyone with this token and the api.video url could upload videos into your account. For this reason, you can [revoke](https://docs.api.video/reference/api/Upload-Tokens#delete-an-upload-token) delegated tokens so they can no longer be used.

## Delegated Token Time To Live

In addition to expiration, you can also set a 'time to live' (TTL) when creating a token. Once the token expires, itc an no longer accept uploads.  If you generate the token when the uplaod begins - you must ensure that at least one segment of the video is uploaded before the token expires, or the video will be rejected at the server.  You can split the video with the [JavaScript file API](https://api.video/blog/tutorials/uploading-large-files-with-javascript/).  Once the token expires, you'll have 24 hours to complete the rest of the upload (which should be PLENTY of time).

## HTML 
The [API docs](https://docs.api.video/reference/api/Videos#upload-a-video) have a thorough explanation on how to build a form and upload a video.

## Conclusion

Delegated upload offers a user-friendly method for video uploads, allowing the creation of tokens with specified expiration. This method is ideal for one-time video uploader solutions and quick content uploads without immediate metadata concerns.

Let us know how you are using delegated upload in your video service in our [community forum](https://community.api.video/)


Delegated uploads: Make video uploads with a created token

medium_delegatedupload.jpg

small_delegatedupload.jpg

thumbnail_delegatedupload.jpg

delegated-video-upload.jpg

Delegated uploads: Make video uploads with a token you create

live - create

Live streaming your content is a great way to connect with your audience. In this tutorial, we'll walk through the steps you need to follow to set up a video livestream.

Note: we have example code of setting up a live stream in the [browser](https://api.video/blog/tutorials/live-stream-tutorial/), with [Zoom](https://api.video/blog/video-trends/start-remote-work-with-online-video-and-zoom-us/)
and with [OBS](https://api.video/blog/video-trends/video-live-streaming-in-just-5-easy-steps/).

[Here](https://docs.api.video/reference/api/Live-Streams#create-live-stream) is the direct link to the technical docs to create a live stream.

In order to establish a video livestream, you must first create a livestream container at api.video. Then you can begin streaming with the tool of your choice. In this example, the live stream will be created with OBS, free and open source software for video streaming.  

## Creating Live Stream

### Step 1: Authenticate

You need an access_token in order to create and upload a video.

You will need your API key to obtain the access_token. You can find your API key in [your dashoard](https://dashboard.api.video).  

This tutorial uses the sandbox endpoint. To upload your video in production, simply replace all `sandbox.api.video` instances with `ws.api.video`.

First, call the authentication endpoint and get your access token.


#### Example - Curl Request


### Step 2: Create the Live Stream

Now we [create the live stream](https://docs.api.video/reference/api/Live-Streams#create-live-stream). In the JSON parameter, feel free to edit the name of the live stream from "Your Stream Name" to whatever you want to name your stream.

#### Example - Curl Request

Your Stream Name

Now the server is ready to accept our live stream, and once broadcast begins (JSON above shows broadcasting:false), it will be viewable on the urls listed in the JSON response.

### Connecting Live Video

The JSON response above lists your live stream's streamKey, which will be needed in OBS to connect your video to the server.

in the OBS application:

1. Esablish a source.  In the sources section, choose a video feed to share.  You could choose to share your screen, or to share your camera (on a Mac: Video Capture Device, and then in the "Device" dropdown choose the camera).  You should now see the video source in the main OBS window.
2. Connect OBS to api.video. Under Settings, choose Stream.  You'll see a choice for service - choose custom.
3. The server should be `rtmp://broadcast.api.video/s` and the `streamKey` is the value you received in the Json when you created the stream. Click OK to accept the changes.
4. Press Start Streaming.
5. Share the embed, iFrame, so that others can watch your stream!


Extra Step:  The default video poster that your users will see is api.video branded.  You can update the thumbnail with an image of your choice:

## Conclusion

That's all it takes. We've walked through the process of creating a livestream at [api.video](https://api.video), and then how to connect that video's streamKey into OBS. Using OBS, we are then able to broadcast video to all our viewers, who can watch using the player (oriframe) url provided by the api.

[Give it a try](https://dashboard.api.video/register), and let us know how it worked for you in our [community forum](https://community.api.video). We're also there to help out if you run into any difficulties.

Create a Live Stream

large_create-a-live-stream.png

medium_create-a-live-stream.png

small_create-a-live-stream.png

thumbnail_create-a-live-stream.png

create-a-live-stream.png

Every call made to an api.video API requires an access_token. This tutorial will walk you through the authentication steps.

> NOTE: All of the SDKs abstract out the need for authentication.

You will need your API key to obtain the access_token. You can find your API key in [your Dashboard](https://dashboard.api.video/login).

This tutorial uses the sandbox endpoint. To upload your video in production, simply replace all ```sandbox.api.video``` instances with ```ws.api.video```.

First, call the authentication endpoint and get your access token.

**Example - Curl Request**

**Example - Http Request**
```
POST /auth/api-key HTTP/1.1
Host: sandbox.api.video
Content-Type: application/json
{
	"apiKey": "your_api_key"
}
```

**Example Response:**

The response has the access token and a refresh token. The "expires_in" parameter tells you that the token is valid for 3600 seconds = 1 hour.

## Conclusion

That's all there is to it!  Grab your api_key from [your dashboard](https://dashboard.api.video/login) and give it a try. If you run into any issues, feel free to reach out on our [forum](https://community.api.video), and we'll gladly help out!

Authentication steps

curl

api.video can help you simplify your video hosting and [delivery](https://api.video/product/live-stream/). As such, one of the first things you'll want to do is to upload videos and get them loaded into the service. Once you upload the video, we'll take care of transcoding the video into streams for delivery to your users.

The easiest way to upload videos into api.video is using our API, and we'll walk through the steps to use the API and get your video online in this tutorial.

## Using cURL

This tutorial uses curl and HTTP requests to authenticate your session, create a video, and then upload the video. 

This example works for smaller videos, but as your video gets larger, you will want to break the video into smaller bites (bytes?) to facilitate upload.  Here's how do to that using the [command line](https://api.video/blog/tutorials/video-upload-tutorial-large-videos/). 

### Other languages?

We have many tutorials on video upload.  Here are a few links to help you:

* [JavaScript](https://api.video/blog/tutorials/uploading-large-files-with-javascript/).
* [Python](https://api.video/blog/tutorials/upload-a-video-from-your-computer-with-the-api-video-api-python/)
* [PHP](https://api.video/blog/tutorials/helpful-php-scripts-pt-2-upload-videos-from-an-ftp-server/)

We have several [Clients](https://docs.api.video/) for additional platforms that will help you get started uploading videos quickly.

You can also check out the API reference documentation for uploading a video here: 
* [Create a video](https://docs.api.video/reference/api/Videos#create-a-video-object)
* [Upload a video](https://docs.api.video/reference/api/Videos#upload-a-video)

### Step 1
You need an access_token in order to create and upload a video.

You will need your API key to obtain the access_token. You can find your API key on [your dashboard](https://dashboard.api.video/overview).

This tutorial uses the sandbox endpoint. To upload your video in production, simply replace all ```sandbox.api.video``` instances with ```ws.api.video```.

First, call the authentication endpoint and get your access token.

**Example - Curl Request**

### Step 2
We will use the create video API to create and upload the video.

The ```Authorization: Bearer``` header uses the access_token from the first step. Hint: Make sure to not remove the end ' when pasting in your token.
The ```title``` parameter is required, so you must add a name to your video.
If your video is hosted on a server, you can use ```"source":"url"``` in the JSON to add the video.
If your video is on your local machine, we'll need to do one additional step.

This example also includes the video description.
The response contains links to the video location, and generates a unique identifier ```videoId```.

**Curl Request**

This is a title

### Step 3: Upload the video file.

> In this step, we use the upload endpoint of the API.  You can also use [delegated tokens](https://docs.api.video/reference/api/Videos) for the upload. The advantage of delegated tokens is that these are safe to use on a webpage (whereas your authorisation token is not), and the videos are directly uploaded to api.video.  You can learn more about using [delegated tokens](https://api.video/blog/product-updates/video-access-management-how-to-create-deliver-and-manage-private-videos-and-what/) for this same experience.

In Step 2, we saw how to link to a video already hosted. If the video is not hosted, and must be uploaded, we will call the video upload API:

When the upload is complete, a JSON response similar to that of step 2 is returned.

That's it - if you access the assets links in the response JSON - you can begin sharing the video you just created. Note: The mp4 URL is only added to the API response once the mp4 video has been encoded, which may take a few additional seconds.

## Conclusion

In this post, we learned about authentication of our account with our [api.video](https://api.video) token, creating a video container, and uploading a video into that container. Once your video is uploaded, it is ready to be shared with your audience!

If you have any questions or suggestions, please share them on our [commmunity forum](https://community.api.video/). To start building now, singup for an api.video account [here](https://dashboard.api.video/register). Thanks for reading! 

Video upload with cURL

Announcements

small_cedric.webp

thumbnail_cedric.webp

cedric.webp

Cédric Montet

Company News

AI, models, assistants, agents and prompts sound and look magical on social networks. But from the countless conversations we have had with startups and Enterprise customers over the last months, we have realized that the gap between existing video workflow and concrete use cases is real.

&nbsp;

Whether it’s getting transcripts in seconds, changing the language of your video or being able to search for items in your content – the benefits, value or potential savings you see and can get with AI are obvious.

&nbsp;

This is why we are thrilled to unveil how we are bringing AI into video, where we are heading and how you can get more value from it!

## What does the future of video streaming look like?

AI will completely upend video consumption as we know it today. We envision a world where video is not a content piece anymore which you can only start and stop – because AI will make videos discoverable and universally understandable. More than ever it resonates fully with our core mission – connecting people through their cameras.

&nbsp;

Since Day 1, we are building api.video to make your use cases, first, a reality and, then, a success.

&nbsp;

Back in the days, the fragmented video streaming market, the number of services you had to aggregate, the lack of innovation by the incumbents was preventing you from joining our video-first world, while your efforts and budgets were consumed by maintaining mashups instead of focusing on what matters. 

&nbsp;

This is why we have built the video backbone and seeing that, now, you host 2.5 millions videos on api.video and deliver dozens of millions videos every month demonstrate why simplicity, exceptional performances and an E2E approach were key.


&nbsp;

What’s happening today with AI, the efforts it requires to benchmark, setup and customize LLMs, to run and maintain them, the Infrastructure you have to build to execute them before getting any value, remind us of the state of the streaming market when we had launched api.video.

&nbsp;

Helping you to benefit from the AI revolution by abstracting all the underlying complexity became obvious and a natural next step in our evolution.

&nbsp;

To get there and to bring you there, here is what we are building, api.video’s very first – **Video Model Hub**.

&nbsp;

Let’s start with the root principles encompassing our work on this Hub:

&nbsp;

- **Open-source models over private ones.** We are long time believers and contributors of the open source community and we have chosen to run only models that are available publicly.

- **Your data is… your data.** You already trust us to host and deliver sensitive content,and this is exactly why we won’t train our own models or sell the data generated from your videos to anyone.

- **Privacy at the core.** We host and execute the models inside our own infrastructure. Your data remains inside the api.video infrastructure. Your videos or data is not sent to external partner, SaaS providers like OpenAI, or others.

- **We believe that every organization will eventually build their own models to leverage their unique data sets**. Next year, alongside the ability to run public and open source models on api.video, we will offer you the ability to host your own.

- **One API to rule them all.** As we have already replaced a dozen of services and vendors under GET/videos to make your videos available worldwide in seconds, we are abstracting all the complex work of executing LLMs behind clear and straightforward endpoints.

&nbsp;

At a glance, api.video brings to you today the power of AI by:

- Leveraging its years of experience in video management and building infrastructure, with GPUs.
- Combining with the most advanced LLMs available on the market.

so that you get more value from your videos in a few lines of code!

&nbsp;

## Here are the first three new features from the Video Model Hub

### 1. Summarization of long-form videos

Upload a video in English, Spanish, French, Portuguese or Chinese and get a text summary of 120 characters with the 3 key takeaways discussed in the video (within seconds!). Ideal to index or preview long form recorded meetings or courses!

&nbsp;

_The video below gives you a glimpse into AI summarization._


### 2. Transcription of your video in seconds

Get a transcript (in .VTTformat) from your uploaded video with the timecodes and offer the captions to your audiences. The best part? The api.video player supports VTT files so there’s nothing new that you need to build on your side!
This also makes your content more inclusive by making it accessible to people with hearing impairments. 


### 3. Translation of subtitles in 5 different languages (and more to come!)

Is your video in English? You can get Spanish and French subtitles. In Chinese? You will get English subtitles and three more languages. In short, this is the perfect solution to spread your message to your international audience!

&nbsp;

_Check out the video below for a glimpse into AI translation._ 


_Try it for yourself now by uploading a video in your [sandbox account](https://dashboard.api.video/overview)._ 

## What’s next

From video classification, alteration, generation, audio alteration, metadata generation, we have identified and plan to implement more than 200 additional use cases and features within the upcoming months!

&nbsp;

From next year, we will let you bring your own models on the infrastructure to get even better and more personalized outcomes.

&nbsp;

This is a long-journey and we’re only getting started. The whole team is thrilled to be at the forefront of this next chapter!


AI  >< Video: The Video Model Hub unveiled

small_AI thought leadership.png

thumbnail_AI thought leadership.png

AI-thought-leadership.png

Arushi Gupta

Product updates

Our mission at api.video has always been to turn your use cases into successful realities. We built the video backbone with this goal in mind, and today, you host 2.5 million videos and deliver tens of millions more!

&nbsp;

Helping you harness the power of AI, while simplifying the problems that come along with, was the next direction to take. 

&nbsp;

To achieve this and to support your journey, we bring to you –  **AI features for your videos.**



## What are the AI video features?

### 1. AI video transcription & captions

With AI transcription, you can convert spoken words in your videos into written text, providing an accurate, searchable record of your content. This means you can easily create subtitles, enhancing accessibility for the hearing impaired or getting a written record of your meetings or events. 






### 2. AI video translation

With AI translation, you can translate your videos into multiple languages, ensuring that viewers from different linguistic backgrounds can understand and engage with your content. This can be useful if you’re hosting an international virtual event, creating multilingual educational materials, or expanding your marketing reach.

&nbsp;

Translation will be available for 5 languages – French, English, Spanish, Portuguese and Chinese.


### 3. AI video summarization

Using AI summarization, you can distill lengthy content into concise, digestible summaries, allowing viewers to quickly grasp the key points without watching the entire video with AI video summarization. This can prove invaluable for educational lectures, business presentations, and lengthy seminars where time is of the essence.

## Do you really need this?

Well, the potential [uses of our AI features](https://api.video/use-cases/generative-ai/) are limitless! From e-learning and e-commerce to online streaming, these [AI features](https://api.video/product/ai-features/) are going to be the difference between ordinary and excellent. What can you do really?

&nbsp;

- Summarize educational lectures for a quick review
- Translate virtual events into multiple languages for global reach
- Transcribe video interviews for easy reference
- And so much more!

## More than just encoding, hosting, and delivery

We’ve gone beyond the basics of video hosting and delivery to give you features that are a step up from the ordinary. Now, not only can you ensure that your customers get video delivery at minimal cost, but also that they get the flexibility to offer content  in their preferred language and in a crisp manner. 

&nbsp;

Additionally, when the features are in production, you may also get the option of adding them via your API. This means that you get complete power to add the features you like without having to go through the dashboard.

## Your videos stay private to you

Your data is yours, and we respect that. You already trust us to host and deliver your most sensitive content, which is why we will never train our own models or sell data generated from your videos. Privacy is at the core of everything we do, and that’s why we host and execute the models within our own infrastructure. Your data stays entirely within the api.video ecosystem and is never sent to external partners, SaaS providers like OpenAI or others.

&nbsp;

_Our CEO and founder, Cedric Montet, speaks more about privacy being our topmost concern in his latest [blog](https://api.video/blog/company/video-model-hub-ai/)._

## Give it a try!

See a glimpse how these AI features look like with a free sandbox account! [Upload a video now in your dashboard](https://dashboard.api.video/overview) and witness AI make a difference to your videos. As this is a Beta release, any feedback, questions, doubts on the features are welcome and much appreciated.

Create a sandbox account now 

Lights, Camera, AI Action! Discover our AI features

Introducing AI features to compliment your videos

small_Introducing AI features to compliment your videos.png

thumbnail_Introducing AI features to compliment your videos.png

AI-features-to-compliment-your-videos.png

AI >< Video: The Video Model Hub unveiled

How to integrate AI facial expression detection to control your video – Javascript 

5 AI tools that will save you 10+ hours on video production

Lights, Camera, AI Action! 

Video trends

In a world where time is money and creativity reigns supreme, AI tools that convert text to video are game-changers! These AI-powered wonders are designed to save your day—and countless hours. Join us as we unveil the top 5 AI video tools that can dramatically cut down your video creation and editing time. From transforming text into captivating visuals to adding that perfect touch of magic to your edits, these tools are set to become your new best friends in the digital playground!

## **1. CapCut**

At number 1, we have Capcut. 

&nbsp;

[CapCut](https://www.capcut.com/) surged in popularity due to its user-friendly interface and powerful editing features, making it a favorite among video creators. Its integration with TikTok and social media platforms is also reason for its widespread adoption.

&nbsp;

The best part about using CapCut is that most of these important features are available for free, which kicks out budget-constraints out of the window. CapCut uses AI to empower users to create stunning videos without needing any fancy editing experience. With mobile and desktop apps, as well as a web version, CapCut can easily be used on the go. 

&nbsp;

CapCut offers a range of AI-driven features that are very, very impressive. With 'Smart Cuts & Trims', CapCut's AI automatically detects shaky parts, long pauses, or unnecessary bits, suggesting cuts to tighten up your video and eliminate boring footage. 'Effortless Audio Magic' helps isolate voices and enhance audio quality, making your message crystal clear even if there’s noisy background interference. 'Instant Captions' auto-generate captions, making your videos more accessible and saving you time and effort. Moreover, if your filming didn't capture the perfect lighting, 'Light Like a Pro' allows CapCut’s AI to adjust lighting in your videos post-production, creating the ideal mood.

What I most love about CapCut AI video generator is its AI-driven background removal feature which eliminates the need for a green screen, allowing me to replace any background with an image or color of my choice.

&nbsp;

Something to note about Capcut is that the free version includes watermarks on exported videos. which can be removed only with a paid subscription. This may potentially pose a barrier for you if you’re a budget-conscious user.

## **2. Runway**

[Runway](https://runwayml.com/) can be called a virtual sorcerer's wand for video editing! It has the potential to be an entire AI video production studio, so it can basically create an entire movie without filming a single frame — if you have the time, that is. Runway can generate videos and animations from simple text prompts, create animations from still images, generate lip-syncing avatars based on a recording of your voice, and even allow you to train your own AI models. 

&nbsp;

Runway might be a little intimidating in the beginning. That’s because it has an array of features that take time to understand, execute and implement, and that could be slightly time-taking and if I can say, complex.

Another aspect to note is that while Runway offers a range of pricing plans, the advanced features that truly set it apart are locked behind higher-tier subscriptions, making it less accessible for small businesses or individual creators on a tight budget.

## **3. Invideo AI**

[Invideo AI](https://invideo.io/ai/) is an excellent tool for generating a starting point for your videos. It helps you to quickly create a basic structure for your videos, which can then be further customized and polished. The  features allow you to input simple prompts, from which the tool generates an initial draft that includes relevant footage, transitions, and effects. 

&nbsp;

A few standout features of Invideo AI are an extensive stock media library that offers a range of options to choose from, AI-powered script generation which creates a complete script for your videos and, voiceover addition. Their AI voiceover generator is particularly good because it has an option to add your own voice which it then uses to narrate scripts in. The narration is also decent, with multiple accents and focussing well on the feeling, intent, and emotion behind each word.

Overall, the tool is great for YouTubers and people who want to start off their video making journey with minimal effort. 

&nbsp;

One of the shortcomings of Invideo AI is its dependency on a stable internet connection, as the tool is cloud-based. This can be a significant limitation for users in areas with unreliable internet access. I also noticed that rendering videos on Invideo AI can sometimes be slow, especially for longer or high-resolution projects, so keep enough time in hand before you expect a final video. 

## **4. Wondershare Filmora**

[Wondershare Filmora](https://filmora.wondershare.net/de/ad/videobearbeitungsprogramm-brand.html) has been a staple in the video editing world for over 15 years. Despite its long history, it's continuously evolving, with a suite of AI features that enhance video quality without requiring professional training or extensive time investments. 

&nbsp;

Filmora is a popular choice among full-time influencers and video editors for advanced-level video editing. It is also a preference because the tool keeps evolving based on new technological developments, and therefore is easily able to meet the demanding standards of modern digital media.

&nbsp;

Some of Filmora’s features include 'AI smart cutout', which allows you to cut objects out of scenes simply by painting their area on the screen, and 'AI audio denoise', which helps control background noise. 'AI audio stretch' lets you extend music to match scene transitions, while AI motion tracking enables face blurring for privacy or fun effects. They also have AI remove background which allows you to create imaginative scenes without hefty budgets. 

Wondershare also provides detailed explanations of these features on their website, so if you ever face a problem using any of them, be sure to check their dedicated pages. 


&nbsp;

However, do note that Filmora's performance can be sluggish when handling large files or high-resolution videos, leading to slower rendering times and potential crashes at times.

## **5. Canva Magic Studio**

Easy to use. Neat interface. Quick results. 

&nbsp;

Those were the three things I liked best about [Canva Magic Studio](https://www.canva.com/magic/). 

&nbsp;

Canva Magic Studio looks very promising as an AI video tool. Having been a fan of Canva for infographics, presentations and social posts since the past few years, their AI video tool has quite impressed me. What stands out is that their UI is very, very simple to understand. Plus, their features don't seem to be overwhelming when it comes to video editing, which I often feel is the case with other professional editing tools. 

&nbsp;
 
Canva Magic Studio gives you amazing results when it comes to video quality and is also very quick to generate the final video. The good video quality comes from its integration with Runway (our #2 in the list).

&nbsp;

To show you an example, I used the prompt: "A cute rabbit watching a video on a laptop”. And the [result](https://www.canva.com/design/DAGGCqwwf4A/GS7q42J5C9nx26gxJGR9lA/watch) was surprisingly very apt!

Canva Magic Studio is a great option if you want to bulk-create your social media posts – create a chunk of Instagram reels or Facebook ads in a go or create similar kinds of videos using a single template. The template options Canva offers have a wide range and are decent for beginners to start with.

## Sora – Open AI’s video generator

Open AI sparked a wave of excitement around AI with ChatGPT, demonstrating its incredible potential in natural language processing. Now, it's taking things a step further with [Sora, an innovative AI](https://openai.com/index/sora/) video creator.

Open AI recently shared a series of tweets showing the potential of Sora and I must say, I am amazed. Be it [several giant mammoths](https://x.com/OpenAI/status/1758192960116785459) rushing through a snowy meadow or a [fluffy monster](https://x.com/OpenAI/status/1758192964222988506) behind a melted candle, the kind of videos Sora will be able to create is astounding! It looks like it will be able to take detailed prompts into consideration, just like it did with ChatGPT, to create exactly what the user needs.

&nbsp;

As Sora continues to evolve and improve, it will undoubtedly shape the future of video production, showing way to new forms of storytelling and engagement in the years to come.

## AI is great – but it cannot replace you

While these AI video tools can ease the load for you and save some time, they cannot really take the place of your creativity, intuition, and emotional intelligence. In the end, it is your perspective, personal touch, and experiences that shape the videos you create. 

&nbsp;

_If you’re finding a place to store, host and deliver your [AI generated videos](https://api.video/use-cases/generative-ai/), api.video could be just what you’re looking for. With quick video upload options, flexible hosting capabilities, ability to add watermarks and keep videos private, you can choose api.video for all your video needs. If you would like to test out our features, [sign-up](https://dashboard.api.video/register) for a sandbox account now and you wound’t be disappointed._

small_7 AI Tools for Quick Video Creation.jpg

thumbnail_7 AI Tools for Quick Video Creation.jpg

7-AI-Tools-for-Quick-Video-Creation.jpg

5 ways the human eye impacts how we do video compression

7 eye-opening stats that prove the impact of product videos in e-commerce

5 ways to utilize product videos to boost your e-commerce sales

Yohann Martzolff

React

In today's tech-driven world, enhancing user interaction and creating immersive experiences is crucial. One exciting way to achieve this is by integrating AI facial expression detection into your video content.  In this blog, we'll guide you through the steps to <u>integrate AI facial expression detection to control your videos using React</u>. 

&nbsp;

Let's start.

&nbsp;

_*To learn how to do the integration with Javascript, head to this [blog](https://api.video/blog/tutorials/AI-facial-expression-detection-javascript/).*_

## 1. Create a minimal React app

As the first step, we need to create a new React app. Run the following command for the same. 

Now add the MediaPipe and the api.video React player packages

## 2. Add a video player

You’re going to use the official [api.video’s React player](https://github.com/apivideo/api.video-react-player) in this application, but feel free to use your favorite one and adapt the callbacks to it.

&nbsp;

Replace the code inside `App.tsx` with the following.
The `playerRef` allows us to control the [api.video player](https://api.video/product/player/).

Run your application with the npm run start command and go to `http://localhost:3000/`, you should see a video that you can play, pause or mute. 

## 3. Record your facial expressions

To control the player with your facial expressions, you need to stream your face through your webcam and pass this streamed data to the trained machine-learning model.

&nbsp;

Add a `<video />` HTML tag to `App.tsx`. 
Its `webcamRef` allows the video element to be targeted.
Apply a `display: "none"` inline style to hide the element, and an `autoPlay` attribute so the webcam stream time is updated. 

&nbsp;

**Note:** You can remove the `display: "none"` style and customize your CSS, it doesn’t matter.

## 4. Load the machine-learning model

Before we can use the machine-learning model, we must wait for it to finish loading. These models can be large and take a moment to get everything needed to run.

&nbsp;

Put this logic inside a `useEffect` and store the `faceLandmarker` class as a React stateful value.

## 5. Start detecting the webcam stream

Once the machine-learning model has been loaded and the `faceLandmarker` class has been instantiated, you can start detecting the stream.

&nbsp;

Create a new `useEffect`

Run your application with the `npm run start` command, go to `http://localhost:3000/`, and open your console. You should see a lot of console logs appearing each millisecond.

&nbsp;

Each one of them logs an array of objects of type:

## 6. Use the facial expression detection results

You now have access to a list of facial expression detection results. Use them to do whatever you want and in this case, to control your video player.

Let’s assume that you want to play the video when you smile, and pause it when you do a kiss.

Check the facial expression detection results on each frame and play or pause your video depending on the score of the wanted result by replacing your console.log with the following.

Once again, run your application with the `npm run start` command, go to `http://localhost:3000/`, and try to smile at your webcam. It should trigger the player’s `play` callback and play the video. Then, try to do a kiss ( 😗 ) in front of your webcam, and the video should pause.

## 7. Display the results

It can be helpful to have a visual representation of the detection results. Display these results as a list and highlight the detected facial expressions by adding a `<ul />` HTML tag to your JSX and creating a new ref to target it.

Add the code to update the HTML according to the results.

Now, you should see a list of results displayed in your application, with a green highlight on the ones with more than 60% confidence.

## 8. Code samples

Check the full `App.tsx` code below.

We hope this blog helped you understand the coding behind integrating AI facial expression detection to your videos.

 &nbsp;

_For any questions or doubts you may have, chat with us on our [website](https://api.video/contact/). If you would like to try out api.video for your videos, [sign-up](https://dashboard.api.video/register) for a free sandbox account here._

How to build AI facial expression detection into your videos with React

small_AI face recognition (React) - Version 2.png

thumbnail_AI face recognition (React) - Version 2.png

AI face recognition (React) - Version 2.png

Create a Next.js 13 & React 18 video app

How to create a Next.js 13 & React 18 video app

React Native Livestream Module: building the sample app

How to upload a video with React and NodeJS

Featured article

# api.video blog

api.video Blog

Follow the api.video Blog to explore tutorials, video use cases, and learn about on-demand and live-streaming video updates.

Video on demand

Live streaming

Analytics

Video infrastructure

Video player

AI features

See all features

Online learning & Corporate training

Social & Entertainment

Marketplace & E-commerce

Communication & UGC

Generative AI

Quickstart guides

Documentation

Ecosystem catalog

Clients & SDKs

Community

Blog

Demos

Customer success stories

Help center

Authenticate