Create a Mistral inference endpoint Generally available; Added in 8.15.0

PUT /_inference/{task_type}/{mistral_inference_id}

Api key auth Basic auth Bearer auth

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

Required authorization

Cluster privileges: manage_inference

Path parameters

task_type string

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

Values are text_embedding, completion, or chat_completion.
mistral_inference_id string Required

The unique identifier of the inference endpoint.

Query parameters

timeout string

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

External documentation

application/json

Body Required

chunking_settings object

The chunking configuration object.

External documentation
Hide chunking_settings attributes Show chunking_settings attributes object
- max_chunk_size number
  
  The maximum size of a chunk in words. This value cannot be higher than 300 or lower than 20 (for sentence strategy) or 10 (for word strategy).
  
  Default value is 250.
- overlap number
  
  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.
  
  Default value is 100.
- sentence_overlap number
  
  The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.
  
  Default value is 1.
- strategy string
  
  The chunking strategy: sentence or word.
  
  Default value is sentence.
service string Required

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

Value is mistral.
service_settings object Required

Settings used to install the inference model. These settings are specific to the mistral service.
Hide service_settings attributes Show service_settings attributes object
- api_key string Required
  
  A valid API key of your Mistral account. You can find your Mistral API keys or you can create a new one on the API Keys page.
  
  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. After creating the inference model, you cannot change the associated API key. If you want to use a different API key, delete the inference model and recreate it with the same name and the updated API key.
  
  External documentation
- max_input_tokens number
  
  The maximum number of tokens per input before chunking occurs.
- model string Required
  
  The name of the model to use for the inference task. Refer to the Mistral models documentation for the list of available models.
  
  External documentation
- rate_limit object
  
  This setting helps to minimize the number of rate limit errors returned from the Mistral API. By default, the mistral service sets the number of requests allowed per minute to 240.
  Hide rate_limit attribute Show rate_limit attribute object
  
  requests_per_minute number
  
  The number of requests allowed per minute.

Responses

200 application/json
Hide response attributes Show response attributes object
- chunking_settings object
  
  Chunking configuration object
  
  Hide chunking_settings attributes Show chunking_settings attributes object
  
  max_chunk_size number
  
  The maximum size of a chunk in words. This value cannot be higher than 300 or lower than 20 (for sentence strategy) or 10 (for word strategy).
  
  Default value is 250.
  
  overlap number
  
  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.
  
  Default value is 100.
  
  sentence_overlap number
  
  The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.
  
  Default value is 1.
  
  strategy string
  
  The chunking strategy: sentence or word.
  
  Default value is sentence.
- 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 string Required
  
  The task type
  
  Value is text_embedding.

PUT /_inference/{task_type}/{mistral_inference_id}

PUT _inference/text_embedding/mistral-embeddings-test
{
  "service": "mistral",
  "service_settings": {
    "api_key": "Mistral-API-Key",
    "model": "mistral-embed" 
  }
}

resp = client.inference.put(
    task_type="text_embedding",
    inference_id="mistral-embeddings-test",
    inference_config={
        "service": "mistral",
        "service_settings": {
            "api_key": "Mistral-API-Key",
            "model": "mistral-embed"
        }
    },
)

const response = await client.inference.put({
  task_type: "text_embedding",
  inference_id: "mistral-embeddings-test",
  inference_config: {
    service: "mistral",
    service_settings: {
      api_key: "Mistral-API-Key",
      model: "mistral-embed",
    },
  },
});

response = client.inference.put(
  task_type: "text_embedding",
  inference_id: "mistral-embeddings-test",
  body: {
    "service": "mistral",
    "service_settings": {
      "api_key": "Mistral-API-Key",
      "model": "mistral-embed"
    }
  }
)

$resp = $client->inference()->put([
    "task_type" => "text_embedding",
    "inference_id" => "mistral-embeddings-test",
    "body" => [
        "service" => "mistral",
        "service_settings" => [
            "api_key" => "Mistral-API-Key",
            "model" => "mistral-embed",
        ],
    ],
]);

curl -X PUT -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"service":"mistral","service_settings":{"api_key":"Mistral-API-Key","model":"mistral-embed"}}' "$ELASTICSEARCH_URL/_inference/text_embedding/mistral-embeddings-test"

client.inference().put(p -> p
    .inferenceId("mistral-embeddings-test")
    .taskType(TaskType.TextEmbedding)
    .inferenceConfig(i -> i
        .service("mistral")
        .serviceSettings(JsonData.fromJson("{\"api_key\":\"Mistral-API-Key\",\"model\":\"mistral-embed\"}"))
    )
);

Request example

Run `PUT _inference/text_embedding/mistral-embeddings-test` to create a Mistral inference endpoint that performs a text embedding task.

{
  "service": "mistral",
  "service_settings": {
    "api_key": "Mistral-API-Key",
    "model": "mistral-embed" 
  }
}