
When this happens...
Live Stream Started
Live Stream Ended
New Live Stream Created
New Video Created

Automatically do this!
Create an index
Generate vectors
Delete an Index
Fetch Index by Name
When this happensTriggers
A trigger is an event that starts a workflow.
This Trigger will fire when a Live stream has Begun Broadcasting
Triggers whe a Live stream ended
Returns newly created live streams at scheduled time intervals.
Returns newly created videos based on the scheduled time interval.
Action is the task that follows automatically within your api.video integrations.
Create an index for vectors created with an external embedding model.
Generate vector embeddings for input data.
Removes a specified index by its ID or name.
Returns details and structure of a specified index.

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To start, connect both your api.video and Pinecone accounts to viaSocket. Once connected, you can set up a workflow where an event in api.video triggers actions in Pinecone (or vice versa).
Absolutely. You can customize how api.video data is recorded in Pinecone. This includes choosing which data fields go into which fields of Pinecone, setting up custom formats, and filtering out unwanted information.
The data sync between api.video and Pinecone typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between api.video and Pinecone. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
api.video is a video hosting and streaming service that allows users to upload, manage, and deliver videos with ease. It provides APIs to integrate video functionalities into applications.
Learn MorePinecone is a vector database designed to provide fast and scalable similarity search and machine learning applications. It enables developers to build high-performance applications that require real-time vector search and retrieval, making it ideal for AI-driven solutions.
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