执行推理 API
新版 API 参考
有关最新的 API 详情，请参阅 执行推理 API。
使用推理端点对输入文本执行推理任务。
请求
POST /_inference/<inference_id>
POST /_inference/<task_type>/<inference_id>
前置条件
- 需要
monitor_inference集群权限（内置的inference_admin和inference_user角色授予此权限）。
描述
执行推理 API 使你能够使用机器学习模型对你作为输入提供的数据执行特定任务。API 返回包含任务结果的响应。你使用的推理端点可以执行在通过创建推理 API 创建端点时定义的一种特定任务。
路径参数
<inference_id>（必需，字符串）推理端点的唯一标识符。
<task_type>（可选，字符串）模型执行的推理任务类型。
查询参数
timeout（可选，超时时间）控制等待推理完成的时间。默认为 30 秒。
请求体
input（必需，字符串或字符串数组）你要对其执行推理任务的文本。
input可以是单个字符串或数组。completion任务类型的推理端点目前仅支持单个字符串作为输入。query（必需，字符串）仅用于重排序（rerank）推理端点。搜索查询文本。
task_settings（可选，对象）单个推理请求的任务设置。这些设置特定于你指定的
<task_type>，并覆盖初始化服务时指定的任务设置。
示例
补全示例
以下示例对示例问题执行补全。
POST _inference/completion/openai_chat_completions
{
"input": "What is Elastic?"
}
API 返回以下响应：
{
"completion": [
{
"result": "Elastic is a company that provides a range of software solutions for search, logging, security, and analytics. Their flagship product is Elasticsearch, an open-source, distributed search engine that allows users to search, analyze, and visualize large volumes of data in real-time. Elastic also offers products such as Kibana, a data visualization tool, and Logstash, a log management and pipeline tool, as well as various other tools and solutions for data analysis and management."
}
]
}
重排序示例
以下示例对示例输入执行重排序。
POST _inference/rerank/cohere_rerank
{
"input": ["luke", "like", "leia", "chewy","r2d2", "star", "wars"],
"query": "star wars main character"
}
API 返回以下响应：
{
"rerank": [
{
"index": "2",
"relevance_score": "0.011597361",
"text": "leia"
},
{
"index": "0",
"relevance_score": "0.006338922",
"text": "luke"
},
{
"index": "5",
"relevance_score": "0.0016166499",
"text": "star"
},
{
"index": "4",
"relevance_score": "0.0011695103",
"text": "r2d2"
},
{
"index": "1",
"relevance_score": "5.614787E-4",
"text": "like"
},
{
"index": "6",
"relevance_score": "3.7850367E-4",
"text": "wars"
},
{
"index": "3",
"relevance_score": "1.2508839E-5",
"text": "chewy"
}
]
}
稀疏嵌入示例
以下示例对示例句子执行稀疏嵌入。
POST _inference/sparse_embedding/my-elser-model
{
"input": "The sky above the port was the color of television tuned to a dead channel."
}
API 返回以下响应：
{
"sparse_embedding": [
{
"port": 2.1259406,
"sky": 1.7073475,
"color": 1.6922266,
"dead": 1.6247464,
"television": 1.3525393,
"above": 1.2425821,
"tuned": 1.1440028,
"colors": 1.1218185,
"tv": 1.0111054,
"ports": 1.0067928,
"poem": 1.0042328,
"channel": 0.99471164,
"tune": 0.96235967,
"scene": 0.9020516,
(...)
},
(...)
]
}
文本嵌入示例
以下示例使用 Cohere 集成对示例句子执行文本嵌入。
POST _inference/text_embedding/my-cohere-endpoint
{
"input": "The sky above the port was the color of television tuned to a dead channel.",
"task_settings": {
"input_type": "ingest"
}
}
API 返回以下响应：
{
"text_embedding": [
{
"embedding": [
{
0.018569946,
-0.036895752,
0.01486969,
-0.0045204163,
-0.04385376,
0.0075950623,
0.04260254,
-0.004005432,
0.007865906,
0.030792236,
-0.050476074,
0.011795044,
-0.011642456,
-0.010070801,
(...)
},
(...)
]
}
]
}