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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.

Parâmetros para "Run an embedding request attributed to an organization"

Cabeçalhos
Nome, Tipo, Descrição
accept string

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

Parâmetros de caminho
Nome, Tipo, Descrição
org string Obrigatório

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

Parâmetros de consulta
Nome, Tipo, Descrição
api-version string

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

Parâmetros do corpo
Nome, Tipo, Descrição
model string Obrigatório

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 Obrigatório

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.

Padrão: float

Pode ser um dos: 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.

Códigos de status de resposta HTTP para "Run an embedding request attributed to an organization"

Código de statusDescrição
200

OK

Exemplos de código para "Run an embedding request attributed to an organization"

Exemplo de solicitação

post/orgs/{org}/inference/embeddings
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."]}'

Resposta

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.

Parâmetros para "Run an embedding request"

Cabeçalhos
Nome, Tipo, Descrição
accept string

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

Parâmetros de consulta
Nome, Tipo, Descrição
api-version string

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

Parâmetros do corpo
Nome, Tipo, Descrição
model string Obrigatório

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 Obrigatório

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.

Padrão: float

Pode ser um dos: 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.

Códigos de status de resposta HTTP para "Run an embedding request"

Código de statusDescrição
200

OK

Exemplos de código para "Run an embedding request"

Exemplo de solicitação

post/inference/embeddings
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."]}'

Resposta

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 } }