Create an Nvidia inference endpoint

Auth

Create an inference endpoint to perform an inference task with the nvidia service.

Required authorization

Cluster privileges manage_inference

Path parameters

task_type enum required

The type of the inference task that the model will perform. NOTE: The chat_completion task type only supports streaming and only through the _stream API.

Values: chat_completion completion rerank text_embedding
nvidia_inference_id string required

The unique identifier of the inference endpoint.

Query parameters

timeout string · default: 30s

Specifies the amount of time to wait for the inference endpoint to be created.

Request body

chunking_settings object

The chunking configuration object. Applies only to the text_embedding task type. Not applicable to the rerank, completion, or chat_completion task types.

Reference
max_chunk_size number · default: 250

The maximum size of a chunk in words. This value cannot be lower than 20 (for sentence strategy) or 10 (for word strategy). This value should not exceed the window size for the associated model.

overlap number · default: 100

The number of overlapping words for chunks. It is applicable only to a word chunking strategy. This value cannot be higher than half the max_chunk_size value.

sentence_overlap number · default: 1

The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.

separator_group string

Only applicable to the recursive strategy and required when using it.

Sets a predefined list of separators in the saved chunking settings based on the selected text type. Values can be markdown or plaintext.

Using this parameter is an alternative to manually specifying a custom separators list.

separators string[]

Only applicable to the recursive strategy and required when using it.

A list of strings used as possible split points when chunking text.

Each string can be a plain string or a regular expression (regex) pattern. The system tries each separator in order to split the text, starting from the first item in the list.

After splitting, it attempts to recombine smaller pieces into larger chunks that stay within the max_chunk_size limit, to reduce the total number of chunks generated.

strategy string · default: sentence

The chunking strategy: sentence, word, none or recursive.

  • If strategy is set to recursive, you must also specify:
  • max_chunk_size
  • either separators orseparator_group

Learn more about different chunking strategies in the linked documentation.

Reference
service enum required

The type of service supported for the specified task type. In this case, nvidia.

Values: nvidia
service_settings object required

Settings used to install the inference model. These settings are specific to the nvidia service.

api_key string required

A valid API key for your Nvidia endpoint. Can be found in API Keys section of Nvidia account settings.

url string

The URL of the Nvidia model endpoint. If not provided, the default endpoint URL is used depending on the task type:

  • For text_embedding task - https://integrate.api.nvidia.com/v1/embeddings.
  • For completion and chat_completion tasks - https://integrate.api.nvidia.com/v1/chat/completions.
  • For rerank task - https://ai.api.nvidia.com/v1/retrieval/nvidia/reranking.
model_id string required

The name of the model to use for the inference task. Refer to the model's documentation for the name if needed. Service has been tested and confirmed to be working with the following models:

  • For text_embedding task - nvidia/llama-3.2-nv-embedqa-1b-v2.
  • For completion and chat_completion tasks - microsoft/phi-3-mini-128k-instruct.
  • For rerank task - nv-rerank-qa-mistral-4b:1. Service doesn't support text_embedding task baai/bge-m3 and nvidia/nvclip models due to them not recognizing the input_type parameter.
max_input_tokens number

For a text_embedding task, the maximum number of tokens per input. Inputs exceeding this value are truncated prior to sending to the Nvidia API.

similarity enum

For a text_embedding task, the similarity measure. One of cosine, dot_product, l2_norm.

Values: cosine dot_product l2_norm
rate_limit object

This setting helps to minimize the number of rate limit errors returned from the Nvidia API. By default, the nvidia service sets the number of requests allowed per minute to 3000.

requests_per_minute number

The number of requests allowed per minute. By default, the number of requests allowed per minute is set by each service as follows:

  • alibabacloud-ai-search service: 1000
  • amazonbedrock service: 240
  • anthropic service: 50
  • azureaistudio service: 240
  • azureopenai service and task type text_embedding: 1440
  • azureopenai service and task types completion or chat_completion: 120
  • cohere service: 10000
  • contextualai service: 1000
  • elastic service and task type chat_completion: 240
  • fireworksai service: 6000
  • googleaistudio service: 360
  • googlevertexai service: 30000
  • hugging_face service: 3000
  • jinaai service: 2000
  • llama service: 3000
  • mistral service: 240
  • openai service and task type text_embedding: 3000
  • openai service and task type completion: 500
  • openshift_ai service: 3000
  • voyageai service: 2000
  • watsonxai service: 120
task_settings object

Settings to configure the inference task. Applies only to the text_embedding task type. Not applicable to the rerank, completion, or chat_completion task types. These settings are specific to the task type you specified.

input_type enum

For a text_embedding task, type of input sent to the Nvidia endpoint. Valid values are:

  • ingest: Mapped to Nvidia's passage value in request. Used when generating embeddings during indexing.
  • search: Mapped to Nvidia's query value in request. Used when generating embeddings during querying.
Important

For Nvidia endpoints, if the input_type field is not specified, it defaults to query.

Values: ingest search
truncate enum

For a text_embedding task, the method used by the Nvidia model to handle inputs longer than the maximum token length. Valid values are:

  • END: When the input exceeds the maximum input token length, the end of the input is discarded.
  • NONE: When the input exceeds the maximum input token length, an error is returned.
  • START: When the input exceeds the maximum input token length, the start of the input is discarded.
Values: END NONE START

Response

application/json
chunking_settings object

The chunking configuration object. Applies only to the embedding, sparse_embedding and text_embedding task types. Not applicable to the rerank, completion, or chat_completion task types.

max_chunk_size number · default: 250

The maximum size of a chunk in words. This value cannot be lower than 20 (for sentence strategy) or 10 (for word strategy). This value should not exceed the window size for the associated model.

overlap number · default: 100

The number of overlapping words for chunks. It is applicable only to a word chunking strategy. This value cannot be higher than half the max_chunk_size value.

sentence_overlap number · default: 1

The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.

separator_group string

Only applicable to the recursive strategy and required when using it.

Sets a predefined list of separators in the saved chunking settings based on the selected text type. Values can be markdown or plaintext.

Using this parameter is an alternative to manually specifying a custom separators list.

separators string[]

Only applicable to the recursive strategy and required when using it.

A list of strings used as possible split points when chunking text.

Each string can be a plain string or a regular expression (regex) pattern. The system tries each separator in order to split the text, starting from the first item in the list.

After splitting, it attempts to recombine smaller pieces into larger chunks that stay within the max_chunk_size limit, to reduce the total number of chunks generated.

strategy string · default: sentence

The chunking strategy: sentence, word, none or recursive.

  • If strategy is set to recursive, you must also specify:
  • max_chunk_size
  • either separators orseparator_group

Learn more about different chunking strategies in the linked documentation.

Reference
service string required

The service type

service_settings object required

Settings specific to the service

task_settings object

Task settings specific to the service and task type

inference_id string required

The inference ID

task_type enum required

The task type

Values: chat_completion completion rerank text_embedding