--- type: api title: Create a Fireworks AI inference endpoint description: Create an inference endpoint to perform an inference task with the `fireworksai` service. url: https://www.elastic.co/elastic/docs-builder/docs/4371/api/doc/elasticsearch/v9/operation/operation-inference-put-fireworksai resource: https://www.elastic.co/elastic/docs-builder/docs/4371/api/doc/elasticsearch/v9/operation/operation-inference-put-fireworksai products: - Elasticsearch --- # Create a Fireworks AI inference endpoint Availability: 9.4+ ## Paths - `PUT` `/_inference/{task_type}/{fireworksai_inference_id}` - [Api key auth](/elastic/docs-builder/docs/4371/api/doc/elasticsearch/v9/authentication#apikeyauth) - [Basic auth](/elastic/docs-builder/docs/4371/api/doc/elasticsearch/v9/authentication#basicauth) - [Bearer auth](/elastic/docs-builder/docs/4371/api/doc/elasticsearch/v9/authentication#bearerauth) #### Path Parameters - `task_type` (enum FireworksAITaskType) The type of the inference task that the model will perform. Values: `chat_completion`, `completion`, `text_embedding` - `fireworksai_inference_id` (string Id) The unique identifier of the inference endpoint. ## Description Create an inference endpoint to perform an inference task with the `fireworksai` service. ## Required authorization * Cluster privileges: `manage_inference` ## Query String Parameters - `timeout` (string Duration · default: 30s) Specifies the amount of time to wait for the inference endpoint to be created. ## Request Body `application/json` - `chunking_settings` ({} InferenceChunkingSettings) — optional The chunking configuration object. Applies only to the `text_embedding` task type. Not applicable to the `completion` or `chat_completion` task types. - `max_chunk_size` (number · default: 250) — optional 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) — optional 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) — optional 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) — optional 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) — optional 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) — optional The chunking strategy: `sentence`, `word`, `none` or `recursive`. * If `strategy` is set to `recursive`, you must also specify: - `max_chunk_size` - either `separators` or`separator_group` Learn more about different chunking strategies in the linked documentation. - `service` (enum FireworksAIServiceType) — required The type of service supported for the specified task type. In this case, `fireworksai`. Values: `fireworksai` - `service_settings` ({} FireworksAIServiceSettings) — 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. - `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. - `url` (string) — optional The URL endpoint to use for the requests. If not provided, the default Fireworks AI API endpoint is used. - `dimensions` (number) — optional 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 FireworksAISimilarityType · default: cosine) — optional For a `text_embedding` task, the similarity measure. One of cosine, dot_product, l2_norm. Values: `cosine`, `dot_product`, `l2_norm` - `rate_limit` ({} RateLimitSetting) — optional 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. - `requests_per_minute` (number) — optional 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` ({} FireworksAITaskSettings) — optional 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) — optional For a `completion` or`chat_completion` task, specify the user issuing the request. This information can be used for abuse detection. - `headers` (map string to string) — optional For a `completion` or`chat_completion` task. Specifies custom HTTP header parameters. For example: ``` "headers": { "Custom-Header": "Some-Value", "Another-Custom-Header": "Another-Value" } ``` ## Response `application/json` - `chunking_settings` ({} InferenceChunkingSettings) 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` or`separator_group` Learn more about different chunking strategies in the linked documentation. - `service` (string) The service type - `service_settings` (ServiceSettings) Settings specific to the service - `task_settings` (TaskSettings) Task settings specific to the service and task type - `inference_id` (string) The inference Id - `task_type` (enum TaskTypeFireworksAI) The task type Values: `chat_completion`, `completion`, `text_embedding` ## Code Examples #### Console ```console PUT _inference/text_embedding/my-fireworks-embeddings { "service": "fireworksai", "service_settings": { "api_key": "your-api-key", "model_id": "fireworks/qwen3-embedding-8b" } } ``` #### JavaScript ```javascript const response = await client.inference.put({ task_type: "text_embedding", inference_id: "my-fireworks-embeddings", inference_config: { service: "fireworksai", service_settings: { api_key: "your-api-key", model_id: "fireworks/qwen3-embedding-8b", }, }, }); ``` #### Python ```python resp = client.inference.put( task_type="text_embedding", inference_id="my-fireworks-embeddings", inference_config={ "service": "fireworksai", "service_settings": { "api_key": "your-api-key", "model_id": "fireworks/qwen3-embedding-8b" } }, ) ``` #### curl ```curl curl -X PUT "$ELASTICSEARCH_URL/_inference/text_embedding/my-fireworks-embeddings" \ -H "Authorization: ApiKey $ELASTIC_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "service": "fireworksai", "service_settings": { "api_key": "your-api-key", "model_id": "fireworks/qwen3-embedding-8b" } }' ``` #### Java ```java client.inference().put(p -> p .inferenceId("my-fireworks-embeddings") .taskType(TaskType.TextEmbedding) .inferenceConfig(i -> i .service("fireworksai") .serviceSettings(JsonData.fromJson(""" {"api_key":"your-api-key","model_id":"fireworks/qwen3-embedding-8b"} """)) ) ); ``` #### C# ```c# var response = await client.Inference .PutAsync(new PutInferenceRequest() { InferenceId = "my-fireworks-embeddings", TaskType = TaskType.TextEmbedding, InferenceConfig = new() { Service = "fireworksai", ServiceSettings = JsonSerializer.Deserialize(""" { "api_key": "your-api-key", "model_id": "fireworks/qwen3-embedding-8b" } """) } }); ``` #### PHP ```php $resp = $client->inference()->put([ "task_type" => "text_embedding", "inference_id" => "my-fireworks-embeddings", "body" => [ "service" => "fireworksai", "service_settings" => [ "api_key" => "your-api-key", "model_id" => "fireworks/qwen3-embedding-8b", ], ], ]); ``` #### Ruby ```ruby response = client.inference.put( task_type: "text_embedding", inference_id: "my-fireworks-embeddings", body: { "service": "fireworksai", "service_settings": { "api_key": "your-api-key", "model_id": "fireworks/qwen3-embedding-8b" } } ) ``` ## Response Examples #### Response for created text embedding endpoint A successful response when creating a Fireworks AI `text_embedding` inference endpoint. ```json { "inference_id": "my-fireworks-embeddings", "task_type": "text_embedding", "service": "fireworksai", "service_settings": { "model_id": "fireworks/qwen3-embedding-8b", "url": "https://api.fireworks.ai/inference/v1/embeddings", "similarity": "cosine", "dimensions": 4096, "rate_limit": { "requests_per_minute": 6000 } }, "chunking_settings": { "strategy": "sentence", "max_chunk_size": 250, "sentence_overlap": 1 } } ``` #### Response for created completion endpoint A successful response when creating a Fireworks AI `chat_completion` inference endpoint. ```json { "inference_id": "my-fireworks-chat", "task_type": "chat_completion", "service": "fireworksai", "service_settings": { "model_id": "accounts/fireworks/models/deepseek-v3p1", "rate_limit": { "requests_per_minute": 6000 } } } ```