Pinecone · Schema

ModelInfo

Represents the model configuration including model type, supported parameters, and other model details.

Vector DatabaseArtificial IntelligenceEmbeddingsRAGDatabaseA2AVector Search

Properties

Name Type Description
model string The name of the model.
short_description string A summary of the model.
type string The type of model (e.g. 'embed' or 'rerank').
vector_type string Whether the embedding model produces 'dense' or 'sparse' embeddings.
default_dimension integer The default embedding model dimension (applies to dense embedding models only).
modality string The modality of the model (e.g. 'text').
max_sequence_length integer The maximum tokens per sequence supported by the model.
max_batch_size integer The maximum batch size (number of sequences) supported by the model.
provider_name string The name of the provider of the model.
supported_dimensions array The list of supported dimensions for the model (applies to dense embedding models only).
supported_metrics object
supported_parameters array List of parameters supported by the model.
View JSON Schema on GitHub

JSON Schema

pinecone-modelinfo-schema.json Raw ↑
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "#/components/schemas/ModelInfo",
  "title": "ModelInfo",
  "description": "Represents the model configuration including model type, supported parameters, and other model details.",
  "type": "object",
  "properties": {
    "model": {
      "example": "multilingual-e5-large",
      "description": "The name of the model.",
      "type": "string"
    },
    "short_description": {
      "example": "multilingual-e5-large",
      "description": "A summary of the model.",
      "type": "string"
    },
    "type": {
      "example": "embed",
      "description": "The type of model (e.g. 'embed' or 'rerank').",
      "type": "string"
    },
    "vector_type": {
      "description": "Whether the embedding model produces 'dense' or 'sparse' embeddings.",
      "type": "string"
    },
    "default_dimension": {
      "example": 1024,
      "description": "The default embedding model dimension (applies to dense embedding models only).",
      "type": "integer",
      "format": "int32",
      "minimum": 1,
      "maximum": 20000
    },
    "modality": {
      "example": "text",
      "description": "The modality of the model (e.g. 'text').",
      "type": "string"
    },
    "max_sequence_length": {
      "example": 512,
      "description": "The maximum tokens per sequence supported by the model.",
      "type": "integer",
      "format": "int32",
      "minimum": 1
    },
    "max_batch_size": {
      "example": 96,
      "description": "The maximum batch size (number of sequences) supported by the model.",
      "type": "integer",
      "format": "int32",
      "minimum": 1
    },
    "provider_name": {
      "example": "NVIDIA",
      "description": "The name of the provider of the model.",
      "type": "string"
    },
    "supported_dimensions": {
      "description": "The list of supported dimensions for the model (applies to dense embedding models only).",
      "type": "array",
      "items": {
        "example": 1024,
        "type": "integer",
        "format": "int32",
        "minimum": 1,
        "maximum": 20000
      }
    },
    "supported_metrics": {
      "$ref": "#/components/schemas/ModelInfoSupportedMetrics"
    },
    "supported_parameters": {
      "description": "List of parameters supported by the model.",
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/ModelInfoSupportedParameter"
      }
    }
  },
  "required": [
    "model",
    "short_description",
    "type",
    "supported_parameters"
  ]
}

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