Connect Tusky and Pinecone to Build Intelligent Automations
Enable Integrations or automations with these events of Tusky and Pinecone
Enable Integrations or automations with these events of Tusky and Pinecone
Actions
Create Vault
Creates a Vault.
Delete Vault
Delete an existing vault.
Create Folder
Creates a Folder.
Update User Account
Update an existing account .
Create an index
Create an index for vectors created with an external embedding model.
Generate vectors
Generate vector embeddings for input data.
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Frequently Asked Questions
To start, connect both your Tusky and Pinecone accounts to viaSocket. Once connected, you can set up a workflow where an event in Tusky triggers actions in Pinecone (or vice versa).
Absolutely. You can customize how Tusky 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 Tusky 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 Tusky 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.
About Tusky
Tusky is a user-friendly and efficient client for Mastodon, a decentralized social network. It allows users to connect, share, and interact with others in a seamless and privacy-focused environment. With its intuitive interface and robust features, Tusky enhances the social media experience by providing tools for managing posts, following users, and engaging with content across the Mastodon network.
Learn MoreAbout Pinecone
Pinecone 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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