Create a Fireworks AI inference endpoint

Auth

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

Required authorization

Cluster privileges manage_inference

Path parameters

task_type enum required

The type of the inference task that the model will perform.

Values: chat_completion completion text_embedding
fireworksai_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 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, fireworksai.

Values: fireworksai
service_settings object required

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

api_key string required

A valid API key for your Fireworks AI account. You can find or create your API keys in the Fireworks AI dashboard.

Important

You need to provide the API key only once, during the inference model creation. The get inference endpoint API does not retrieve your API key.

External docs
model_id string required

The name of the model to use for the inference task. Refer to the Fireworks AI documentation for the list of available models for chat completion, completion, and text embedding. For text embedding, supported models include the Qwen3 embedding family (e.g. fireworks/qwen3-embedding-8b) and other models in the Fireworks model library.

External docs
url string

The URL endpoint to use for the requests. If not provided, the default Fireworks AI API endpoint is used.

dimensions number

For a text_embedding task, the number of dimensions the resulting output embeddings should have. Variable-length embeddings are supported via this parameter.

similarity enum · default: cosine

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

Values: cosine dot_product l2_norm
External docs
rate_limit object

This setting helps to minimize the number of rate limit errors returned from the Fireworks AI API. Rate limit grouping is per API key only. By default, the fireworksai service sets the number of requests allowed per minute to 6000.

External docs
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 completion or chat_completion task types. Not applicable to the text_embedding task type. These settings are specific to the task type you specified.

user string

For a completion orchat_completion task, specify the user issuing the request. This information can be used for abuse detection.

headers map string to string

For a completion orchat_completion task. Specifies custom HTTP header parameters. For example:

"headers": {
  "Custom-Header": "Some-Value",
  "Another-Custom-Header": "Another-Value"
}

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 text_embedding