Points de terminaison d’API REST pour l'intégration des modèles

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.

Paramètres pour « Run an embedding request attributed to an organization »

En-têtes
Nom, Type, Description
`accept` string Setting to `application/vnd.github+json` is recommended.

Paramètres de chemin d’accès
Nom, Type, Description
`org` string Obligatoire The organization login associated with the organization to which the request is to be attributed.

Paramètres de requête
Nom, Type, Description
`api-version` string The API version to use. Optional, but required for some features.

Paramètres du corps
Nom, Type, Description
`model` string Obligatoire 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 Obligatoire 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` Peut être: `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.

Codes d’état de la réponse HTTP pour « Run an embedding request attributed to an organization »

Code d’état	Description
`200`	OK

Exemples de code pour « Run an embedding request attributed to an organization »

Exemple de requête

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."]}'

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.

Paramètres pour « Run an embedding request »

En-têtes
Nom, Type, Description
`accept` string Setting to `application/vnd.github+json` is recommended.

Paramètres de requête
Nom, Type, Description
`api-version` string The API version to use. Optional, but required for some features.

Paramètres du corps
Nom, Type, Description
`model` string Obligatoire 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 Obligatoire 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` Peut être: `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.

Codes d’état de la réponse HTTP pour « Run an embedding request »

Code d’état	Description
`200`	OK

Exemples de code pour « Run an embedding request »

Exemple de requête

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."]}'

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
  }
}