Pinecone · Schema

IndexModel

The IndexModel describes the configuration and status of a Pinecone index.

Vector DatabasesAIEmbeddingsRAG

Properties

Name	Type	Description
name	string	The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or '-'.
dimension	integer	The dimensions of the vectors to be inserted in the index.
metric	string	The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If the 'vector_type' is 'sparse', the metric must be 'dotproduct'. If the `vector_type` is `de
host	string	The URL address where the index is hosted.
private_host	string	The private endpoint URL of an index.
deletion_protection	object
tags	object
embed	object
spec	object	The spec object defines how the index should be deployed.
status	object	The current status of the index
vector_type	string	The index vector type. You can use 'dense' or 'sparse'. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension should not be specified.

View JSON Schema on GitHub

JSON Schema

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "#/components/schemas/IndexModel",
  "title": "IndexModel",
  "description": "The IndexModel describes the configuration and status of a Pinecone index.",
  "type": "object",
  "properties": {
    "name": {
      "example": "example-index",
      "description": "The name of the index. Resource name must be 1-45 characters long, start and end with an alphanumeric character, and consist only of lower case alphanumeric characters or '-'.\n",
      "type": "string",
      "minLength": 1,
      "maxLength": 45
    },
    "dimension": {
      "example": 1536,
      "description": "The dimensions of the vectors to be inserted in the index.",
      "type": "integer",
      "format": "int32",
      "minimum": 1,
      "maximum": 20000
    },
    "metric": {
      "description": "The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If the 'vector_type' is 'sparse', the metric must be 'dotproduct'. If the `vector_type` is `dense`, the metric defaults to 'cosine'.\nPossible values: `cosine`, `euclidean`, or `dotproduct`.",
      "x-enum": [
        "cosine",
        "euclidean",
        "dotproduct"
      ],
      "type": "string"
    },
    "host": {
      "example": "semantic-search-c01b5b5.svc.us-west1-gcp.pinecone.io",
      "description": "The URL address where the index is hosted.",
      "type": "string"
    },
    "private_host": {
      "example": "semantic-search-c01b5b5.svc.private.us-west1-gcp.pinecone.io",
      "description": "The private endpoint URL of an index.",
      "type": "string"
    },
    "deletion_protection": {
      "$ref": "#/components/schemas/DeletionProtection"
    },
    "tags": {
      "$ref": "#/components/schemas/IndexTags"
    },
    "embed": {
      "$ref": "#/components/schemas/ModelIndexEmbed"
    },
    "spec": {
      "example": {
        "pod": {
          "environment": "us-east-1-aws",
          "metadata_config": {
            "indexed": [
              "genre",
              "title",
              "imdb_rating"
            ]
          },
          "pod_type": "p1.x1",
          "pods": 1,
          "replicas": 1,
          "shards": 1
        }
      },
      "description": "The spec object defines how the index should be deployed.",
      "type": "object",
      "oneOf": [
        {
          "title": "Serverless",
          "type": "object",
          "properties": {
            "serverless": {
              "$ref": "#/components/schemas/ServerlessSpecResponse"
            }
          },
          "required": [
            "serverless"
          ],
          "additionalProperties": false
        },
        {
          "title": "Pod-based",
          "type": "object",
          "properties": {
            "pod": {
              "$ref": "#/components/schemas/PodSpec"
            }
          },
          "required": [
            "pod"
          ],
          "additionalProperties": false
        },
        {
          "title": "BYOC",
          "type": "object",
          "properties": {
            "byoc": {
              "$ref": "#/components/schemas/ByocSpecResponse"
            }
          },
          "required": [
            "byoc"
          ],
          "additionalProperties": false
        }
      ]
    },
    "status": {
      "example": {
        "ready": true,
        "state": "ScalingUpPodSize"
      },
      "description": "The current status of the index",
      "type": "object",
      "properties": {
        "ready": {
          "description": "Whether the index is ready for use",
          "type": "boolean"
        },
        "state": {
          "description": "The state of the index.\nPossible values: `Initializing`, `InitializationFailed`, `ScalingUp`, `ScalingDown`, `ScalingUpPodSize`, `ScalingDownPodSize`, `Terminating`, `Ready`, or `Disabled`.",
          "x-enum": [
            "Initializing",
            "InitializationFailed",
            "ScalingUp",
            "ScalingDown",
            "ScalingUpPodSize",
            "ScalingDownPodSize",
            "Terminating",
            "Ready",
            "Disabled"
          ],
          "type": "string"
        }
      },
      "required": [
        "ready",
        "state"
      ]
    },
    "vector_type": {
      "description": "The index vector type. You can use 'dense' or 'sparse'. If 'dense', the vector dimension must be specified.  If 'sparse', the vector dimension should not be specified.",
      "default": "dense",
      "type": "string"
    }
  },
  "required": [
    "name",
    "metric",
    "status",
    "spec",
    "host",
    "vector_type"
  ]
}