Embedding
Embeddings serve as the A.I.-native approach for representing various data types, including text, images, and soon, audio and video, making them the perfect fit for integration with A.I.-powered tools and algorithms.
Within the Index Network, an Item can have many embeddings which serves as multi-dimensional representations for items in specific contexts.
Storing embeddings in a decentralized way efficiently promotes a cohesive and interconnected knowledge network for A.I.-driven applications.
Schema
The Embedding
schema consists of several key properties:
Property | Description | Type |
---|---|---|
modelName | Name of the model used for generating the embedding. | String |
vector | The embedding vector, represented as an array of floats. | Array of Floats |
context | Context information associated with the embedding, detailed in the | EmbeddingContext |
indexId | Identifier of the Index associated with this embedding. | StreamID |
index | The actual Index object associated with this embedding, accessed through | Index |
itemId | Identifier of the item (node) associated with this embedding. | StreamID |
item | The actual Node object associated with this embedding, accessed through | Node |
createdAt | The timestamp when the Embedding was initially created, for historical record-keeping. | DateTime |
updatedAt | The timestamp when the Embedding was last updated, ensuring data accuracy. | DateTime |
deletedAt | The timestamp when the Embedding was deleted (if applicable). | DateTime |
controllerDID | The Decentralized Identifier (DID) of the controller for access control. | DID |
version | The CommitID representing the version or state of the Embedding for version control. | CommitID |
Context Schema
The EmbeddingContext
type in a data model plays a crucial role in enhancing the interoperability of embeddings. It provides a standardized and enriched representation of data, such as a node's content augmented with additional context, ensuring that embeddings are universally applicable across different systems. T
Property | Description |
---|---|
context | The transformed representation of a node before obtaining embeddings. This includes the node's content with added context information for embedding tasks like summaries, etc. Raw document is used if it's null. |
description | A human-readable description of the related context. It helps in understanding the nature and purpose of the context used for embedding. |
category | The category or namespace for the embedding. Example values might include "summaries", "knowledge_graph", "document", etc., indicating the domain or type of embedding being used. |
Endpoints
This section provides details about the available API endpoints.
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