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You're viewing version 2.13 of the OpenSearch documentation. This version is no longer maintained. For the latest version, see the current documentation. For information about OpenSearch version maintenance, see Release Schedule and Maintenance Policy.

Get an agent

Introduced 2.13

You can retrieve agent information using the agent_id.

Path and HTTP methods

GET /_plugins/_ml/agents/<agent_id>

Path parameters

The following table lists the available path parameters.

Parameter Data type Description
agent_id String The agent ID of the agent to retrieve.

Example request

GET /_plugins/_ml/agents/N8AE1osB0jLkkocYjz7D

Example response

{
  "name": "Test_Agent_For_RAG",
  "type": "flow",
  "description": "this is a test agent",
  "tools": [
    {
      "type": "VectorDBTool",
      "parameters": {
        "input": "${parameters.question}",
        "source_field": """["text"]""",
        "embedding_field": "embedding",
        "index": "my_test_data",
        "model_id": "zBRyYIsBls05QaITo5ex"
      },
      "include_output_in_agent_response": false
    },
    {
      "type": "MLModelTool",
      "description": "A general tool to answer any question",
      "parameters": {
        "model_id": "ygAzT40Bdo8gePIqxk0H",
        "prompt": """

Human:You are a professional data analyst. You will always answer question based on the given context first. If the answer is not directly shown in the context, you will analyze the data and find the answer. If you don't know the answer, just say don't know. 

 Context:
${parameters.VectorDBTool.output}

Human:${parameters.question}

Assistant:"""
      },
      "include_output_in_agent_response": false
    }
  ],
  "created_time": 1706821658743,
  "last_updated_time": 1706821658743
}

Response fields

For response field descriptions, see Register Agent API request fields.

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