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Google Gemini Embeddings API

Generate text embedding vectors for semantic search, classification, clustering, and retrieval tasks using Gemini embedding models.

Google Gemini Embeddings API is one of 15 APIs that Google Gemini publishes on the APIs.io network, described by a machine-readable OpenAPI specification and an AsyncAPI event-driven specification.

This API exposes 1 JSON Schema definition.

Tagged areas include Embeddings. The published artifact set on APIs.io includes an OpenAPI specification, API documentation, an AsyncAPI specification, a getting-started guide, pricing, rate-limit docs, and 1 JSON Schema.

This API exposes 1 operation across 1 path, and defines 10 schemas. It is described by OpenAPI 3.1.0, at version v1beta.

Requests are made against a single base URL, https://generativelanguage.googleapis.com/v1beta.

1 operations 1 paths 10 schemas 1 POST

Metadata

The identity and technical contract details declared by the specification.

Specification
OpenAPI 3.1.0
API Version
v1beta
Base URL
https://generativelanguage.googleapis.com
Authentication
API Key
License
Terms of Service
Resource Areas
1

Authentication & Security 1

Google Gemini Embeddings API declares 1 security scheme for authenticating requests. An API key is passed in the query as key (ApiKeyAuth). By default, every request must be authenticated.

  • ApiKeyAuth — API key for authenticating requests. Obtain from Google AI Studio at https://aistudio.google.com/app/apikey.

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.

Embeddings 1

Generate text embedding vectors for semantic search, classification, clustering, and retrieval tasks using Gemini embedding models.

POST
/models/{model}:embedContent
Google Gemini Generates a text embedding vector from the input Content using the specified Gemini Embedding model.
embedContent 2 params body → 200400401404429

Schemas 10

The contract defines 10 schemas that model the data the API accepts and returns. The most detailed are Part (5 properties), EmbedContentRequest (4 properties), Blob (2 properties), FunctionCall (2 properties). Each schema is shown below with its type and property counts.

EmbedContentRequest
object
Request containing the Content for the model to embed.
4 properties 1 required
FunctionCall
object
A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name with the arguments and their values.
2 properties
Blob
object
Raw media bytes with MIME type information.
2 properties
FunctionResponse
object
The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from…
2 properties
EmbedContentResponse
object
The response to an EmbedContentRequest.
1 property
ContentEmbedding
object
A list of floats representing an embedding.
1 property
FileData
object
URI based data for media uploaded via the Files API.
2 properties
Content
object
The base structured datatype containing multi-part content of a message. A Content includes a role field designating the producer of the Content and a parts fi…
2 properties
Part
object
A datatype containing media that is part of a multi-part Content message. A Part consists of data which has an associated datatype. A Part can only contain one…
5 properties
ErrorResponse
object
Error response from the API.
1 property

Specification

The full machine-readable OpenAPI contract behind this narrative.

Source

google-gemini-embeddings-api-openapi.yml Raw ↑

Other APIs Google Gemini publishes across the network.

Gemini Pro API
Gemini Pro Vision API
Gemini Ultra API
Gemini Embedding API
Gemini Live API
Gemini Context Caching API
Gemini Fine-Tuning API
Gemini Interactions API
Vertex AI Gemini API
Vertex AI Imagen API
Vertex AI Gemini Live API
Vertex AI Text Embeddings API
Where this information came from

This is an independent, third-party profile of Google Gemini Embeddings API, published by API Evangelist. We do not operate, host, resell, or support these APIs, and we are not affiliated with or endorsed by the company unless stated above. Everything here is built from publicly available information — the company's own site, developer portal, documentation, public repositories, and the specifications it publishes for public use. Nothing is obtained by breaching a system, defeating an access control, or using credentials.

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