Create an AlibabaCloud AI Search inference endpoint | Elasticsearch API documentation (v9)

Path parameters

task_typestring Required
The type of the inference task that the model will perform.
Values are completion, rerank, space_embedding, or text_embedding.
alibabacloud_inference_idstring Required
The unique identifier of the inference endpoint.

application/json

Body

chunking_settingsobject
Hide chunking_settings attributes Show chunking_settings attributes object
- max_chunk_sizenumber
  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).
- overlapnumber
  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_overlapnumber
  The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.
- strategystring
  The chunking strategy: sentence or word.
servicestring Required
Value is alibabacloud-ai-search.
service_settingsobject Required
Hide service_settings attributes Show service_settings attributes object
- api_keystring Required
  A valid API key for the AlibabaCloud AI Search API.
- hoststring Required
  The name of the host address used for the inference task. You can find the host address in the API keys section of the documentation.
  External documentation
- rate_limitobject
  Hide rate_limit attribute Show rate_limit attribute object
  requests_per_minutenumber
  The number of requests allowed per minute.
- service_idstring Required
  The name of the model service to use for the inference task. The following service IDs are available for the completion task:
  ops-qwen-turbo
  qwen-turbo
  qwen-plus
  qwen-max ÷ qwen-max-longcontext
  The following service ID is available for the rerank task:
  ops-bge-reranker-larger
  The following service ID is available for the sparse_embedding task:
  ops-text-sparse-embedding-001
  The following service IDs are available for the text_embedding task:
  ops-text-embedding-001 ops-text-embedding-zh-001 ops-text-embedding-en-001 ops-text-embedding-002
- workspacestring Required
  The name of the workspace used for the inference task.
task_settingsobject
Hide task_settings attributes Show task_settings attributes object
- input_typestring
  For a sparse_embedding or text_embedding task, specify the type of input passed to the model. Valid values are:
  ingest for storing document embeddings in a vector database.
  search for storing embeddings of search queries run against a vector database to find relevant documents.
- return_tokenboolean
  For a sparse_embedding task, it affects whether the token name will be returned in the response. It defaults to false, which means only the token ID will be returned in the response.

Responses

200 application/json
Hide response attributes Show response attributes object
- chunking_settingsobject
  Hide chunking_settings attributes Show chunking_settings attributes object
  max_chunk_sizenumber
  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).
  overlapnumber
  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_overlapnumber
  The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.
  strategystring
  The chunking strategy: sentence or word.
- servicestring Required
  The service type
- service_settingsobject Required
- task_settingsobject
- inference_idstring Required
  The inference Id
- task_typestring Required
  Values are text_embedding, rerank, completion, or sparse_embedding.

PUT /_inference/{task_type}/{alibabacloud_inference_id}

PUT _inference/completion/alibabacloud_ai_search_completion
{
    "service": "alibabacloud-ai-search",
    "service_settings": {
        "host" : "default-j01.platform-cn-shanghai.opensearch.aliyuncs.com",
        "api_key": "AlibabaCloud-API-Key",
        "service_id": "ops-qwen-turbo",
        "workspace" : "default"
    }
}

curl \
 --request PUT 'http://api.example.com/_inference/{task_type}/{alibabacloud_inference_id}' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n    \"service\": \"alibabacloud-ai-search\",\n    \"service_settings\": {\n        \"host\" : \"default-j01.platform-cn-shanghai.opensearch.aliyuncs.com\",\n        \"api_key\": \"AlibabaCloud-API-Key\",\n        \"service_id\": \"ops-qwen-turbo\",\n        \"workspace\" : \"default\"\n    }\n}"'

Request examples

Run `PUT _inference/completion/alibabacloud_ai_search_completion` to create an inference endpoint that performs a completion task.

{
    "service": "alibabacloud-ai-search",
    "service_settings": {
        "host" : "default-j01.platform-cn-shanghai.opensearch.aliyuncs.com",
        "api_key": "AlibabaCloud-API-Key",
        "service_id": "ops-qwen-turbo",
        "workspace" : "default"
    }
}

Run `PUT _inference/rerank/alibabacloud_ai_search_rerank` to create an inference endpoint that performs a rerank task.

{
    "service": "alibabacloud-ai-search",
    "service_settings": {
        "api_key": "AlibabaCloud-API-Key",
        "service_id": "ops-bge-reranker-larger",
        "host": "default-j01.platform-cn-shanghai.opensearch.aliyuncs.com",
        "workspace": "default"
    }
}

Run `PUT _inference/sparse_embedding/alibabacloud_ai_search_sparse` to create an inference endpoint that performs perform a sparse embedding task.

{
    "service": "alibabacloud-ai-search",
    "service_settings": {
        "api_key": "AlibabaCloud-API-Key",
        "service_id": "ops-text-sparse-embedding-001",
        "host": "default-j01.platform-cn-shanghai.opensearch.aliyuncs.com",
        "workspace": "default"
    }
}

Run `PUT _inference/text_embedding/alibabacloud_ai_search_embeddings` to create an inference endpoint that performs a text embedding task.

{
    "service": "alibabacloud-ai-search",
    "service_settings": {
        "api_key": "AlibabaCloud-API-Key",
        "service_id": "ops-text-embedding-001",
        "host": "default-j01.platform-cn-shanghai.opensearch.aliyuncs.com",
        "workspace": "default"
    }
}