Cohere Embed API
The Cohere Embed API generates vector embeddings from text and images, enabling semantic search, clustering, and classification use cases. It supports multilingual content and can process both text and image inputs using the Embed v3 model family. Developers can use these embeddings to build retrieval systems, recommendation engines, and other applications that require understanding semantic similarity between content.
Cohere Embed API is one of 9 APIs that cohere publishes on the APIs.io network, described by a machine-readable OpenAPI specification.
Tagged areas include Artificial Intelligence, Embeddings, Natural Language Processing, Semantic Search, and Vector Search. The published artifact set on APIs.io includes API documentation and an OpenAPI specification.
This API exposes 1 operation across 1 path, and defines 3 schemas. It is described by OpenAPI 3.1.0, at version 2.0.
Requests are made against a single base URL, https://api.cohere.com.
Metadata
The identity and technical contract details declared by the specification.
Authentication & Security 1
Cohere Embed API declares
1 security scheme
for authenticating requests.
It accepts HTTP bearer tokens (bearerAuth).
By default, every request must be authenticated.
bearerAuth— Bearer authentication using a Cohere API key. Pass the API key in the Authorization header as Bearer .
Paths & Operations 1
Across 1 path, the API surfaces 1 operation — 1 POST. Each is listed below with its method, path, parameters, and response codes.
Endpoints for generating vector embeddings from text and image inputs using Cohere embedding models.
Schemas 3
The contract defines 3 schemas that model the data the API accepts and returns. The most detailed are EmbedRequest (6 properties), EmbedResponse (4 properties), Error (1 property). Each schema is shown below with its type and property counts.
Specification
The full machine-readable OpenAPI contract behind this narrative.
Source
More from cohere 8
Other APIs cohere publishes across the network.