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Showing content from https://docs.github.com/en/rest/models/embeddings below:

REST API endpoints for model embeddings

Use the REST API to work with embedding requests for models.

Run an embedding request attributed to an organization

This endpoint allows you to run an embedding request attributed to a specific organization. You must be a member of the organization and have enabled models to use this endpoint. The token used to authenticate must have the models: read permission if using a fine-grained PAT or GitHub App minted token. The request body should contain the model ID and the input text(s) for the embedding request. The response will include the generated embeddings.

Parameters for "Run an embedding request attributed to an organization" Headers Name, Type, Description

accept string

Setting to application/vnd.github+json is recommended.

Path parameters Name, Type, Description

org string Required

The organization login associated with the organization to which the request is to be attributed.

Query parameters Name, Type, Description

api-version string

The API version to use. Optional, but required for some features.

Body parameters Name, Type, Description

model string Required

ID of the specific model to use for the request. The model ID should be in the format of {publisher}/{model_name} where "openai/text-embedding-3-small" is an example of a model ID. You can find supported models in the catalog/models endpoint.

input string or array Required

Input text to embed, encoded as a string or array of strings. To embed multiple inputs in a single request, pass an array of strings. Each input must not exceed the max input tokens for the model, cannot be an empty string, and any array must be 2048 dimensions or less.

encoding_format string

The format to return the embeddings in. Can be either float or base64.

Default: float

Can be one of: float, base64

dimensions integer

The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models.

user string

A unique identifier representing your end-user, which can help us to monitor and detect abuse.

HTTP response status codes for "Run an embedding request attributed to an organization" Status code Description 200

OK

Code samples for "Run an embedding request attributed to an organization" Request example

post/orgs/{org}/inference/embeddings

Copy to clipboard curl request example

curl -L \ -X POST \ -H "Accept: application/vnd.github+json" \ -H "Authorization: Bearer <YOUR-TOKEN>" \ -H "X-GitHub-Api-Version: 2022-11-28" \ https://models.github.ai/orgs/ORG/inference/embeddings \ -d '{"model":"openai/text-embedding-3-small","input":["The food was delicious and the waiter was very friendly.","I had a great time at the restaurant."]}'

Response

Status: 200

{ "object": "list", "data": [ { "object": "embedding", "index": 0, "embedding": [ 0.0023064255, -0.009327292, -0.0028842222 ] } ], "model": "openai/text-embedding-3-small", "usage": { "prompt_tokens": 8, "total_tokens": 8 } }

Run an embedding request

This endpoint allows you to run an embedding request. The token used to authenticate must have the models: read permission if using a fine-grained PAT or GitHub App minted token. The request body should contain the model ID and the input text(s) for the embedding request. The response will include the generated embeddings.

Parameters for "Run an embedding request" Headers Name, Type, Description

accept string

Setting to application/vnd.github+json is recommended.

Query parameters Name, Type, Description

api-version string

The API version to use. Optional, but required for some features.

Body parameters Name, Type, Description

model string Required

ID of the specific model to use for the request. The model ID should be in the format of {publisher}/{model_name} where "openai/text-embedding-3-small" is an example of a model ID. You can find supported models in the catalog/models endpoint.

input string or array Required

Input text to embed, encoded as a string or array of strings. To embed multiple inputs in a single request, pass an array of strings. Each input must not exceed the max input tokens for the model, cannot be an empty string, and any array must be 2048 dimensions or less.

encoding_format string

The format to return the embeddings in. Can be either float or base64.

Default: float

Can be one of: float, base64

dimensions integer

The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models.

user string

A unique identifier representing your end-user, which can help us to monitor and detect abuse.

HTTP response status codes for "Run an embedding request" Status code Description 200

OK

Code samples for "Run an embedding request" Request example

post/inference/embeddings

Copy to clipboard curl request example

curl -L \ -X POST \ -H "Accept: application/vnd.github+json" \ -H "Authorization: Bearer <YOUR-TOKEN>" \ -H "X-GitHub-Api-Version: 2022-11-28" \ https://models.github.ai/inference/embeddings \ -d '{"model":"openai/text-embedding-3-small","input":["The food was delicious and the waiter was very friendly.","I had a great time at the restaurant."]}'

Response

Status: 200

{ "object": "list", "data": [ { "object": "embedding", "index": 0, "embedding": [ 0.0023064255, -0.009327292, -0.0028842222 ] } ], "model": "openai/text-embedding-3-small", "usage": { "prompt_tokens": 8, "total_tokens": 8 } }


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