This is the single method to check the execution status of an AI task, and obtain the result of any type of AI task.
Based on the results of processing, the “result” field will contain an answer corresponding to the type of the initially created task:
ASR: Transcribe video
ASR: Translate subtitles
CM: Sports detection
CM: Not Safe For Work (NSFW) content detection
CM: Soft nudity detection
CM: Hard nudity detection
CM: Objects recognition (soon)
etc… (see other methods from /ai/ domain)
A queue is used to process videos. The waiting time depends on the total number of requests in the system, so sometimes you will have to wait.
Statuses:
Each task is processed in sub-stages, for example, original language is first determined in a video, and then transcription is performed. In such cases, the video processing status may change from “STARTED” to “PENDING”, and back. This is due to waiting for resources for a specific processing sub-stage. In this case, the overall percentage “progress” of video processing will reflect the full picture.
The result data is stored for 1 month, after which it is deleted.
For billing conditions see the corresponding methods in /ai/ domain. The task is billed only after successful completion of the task and transition to “SUCCESS” status.
API key for authentication. Make sure to include the word apikey, followed by a single space and then your token.
Example: apikey 1234$abcdef
ID of the task to get status of execution or result. This value is taken from the response of the initial AI task creation method.
Result of AI task execution
ID of the AI task
Status of processing the AI task. See GET /ai/results method for description.
PENDING, STARTED, SUCCESS, FAILURE, REVOKED, RETRY Percentage of task completed. A value greater than 0 means that it has been taken into operation and is being processed.
Type of AI task
content-moderation, transcription The object will correspond to the task type that was specified in the original request. There will be one object for transcription, another for searching for nudity, and so on.
{
"url": "https://demo-files.gvideo.io/apidocs/spritefright-blender-cut30sec.mp4",
"task_name": "transcription",
"audio_language": "ger"
}{
"concatenated_text": "Come on team, we mustn't dilly dally when there's so much nature to see! I was thinking, we should call our class project, Fungi in a Forest!",
"subtitles": [
{
"start_time": "00:00:00.009",
"end_time": "00:00:03.689",
"text": "Come on team, we mustn't dilly dally when there's so much nature to see!"
},
{
"start_time": "00:00:04.129",
"end_time": "00:00:08.169",
"text": "I was thinking, we should call our class project, Fungi in a Forest!"
}
],
"vttContent": "WEBVTT\n\n1\n00:00:00.009 --> 00:00:03.689\nCome on team, we mustn't dilly dally when there's so much nature to see!\n\n2\n00:00:04.129 --> 00:00:08.169\nI was thinking, we should call our class project, Fungi in a Forest!\n\n",
"languages": ["eng"]
}