{
"name": "pinecone",
"displayName": "Pinecone",
"version": "2.0.2",
"description": "A Pulumi package for creating and managing Pinecone resources.",
"keywords": [
"pulumi",
"pinecone",
"category/utility",
"kind/native"
],
"homepage": "https://www.pinecone.io",
"license": "Apache-2.0",
"attribution": "This Pulumi package is based on the [`pinecone` Terraform Provider](https://github.com/pinecone-io/terraform-provider-pinecone).",
"repository": "https://github.com/pinecone-io/pulumi-pinecone",
"pluginDownloadURL": "github://api.github.com/pinecone-io/pulumi-pinecone",
"publisher": "pinecone-io",
"meta": {
"moduleFormat": "(.*)(?:/[^/]*)"
},
"language": {
"csharp": {
"packageReferences": {
"Pulumi": "3.*"
},
"compatibility": "tfbridge20",
"rootNamespace": "PineconeDatabase"
},
"go": {
"importBasePath": "github.com/pinecone-io/pulumi-pinecone/sdk/v2/go/pinecone",
"generateResourceContainerTypes": true,
"generateExtraInputTypes": true
},
"nodejs": {
"packageName": "@pinecone-database/pulumi",
"packageDescription": "A Pulumi package for creating and managing Pinecone resources.",
"readme": "> This provider is a derived work of the [Terraform Provider](https://github.com/pinecone-io/terraform-provider-pinecone)\n> distributed under [MPL 2.0](https://www.mozilla.org/en-US/MPL/2.0/). If you encounter a bug or missing feature,\n> first check the [`pulumi-pinecone` repo](https://github.com/pinecone-io/pulumi-pinecone/issues); however, if that doesn't turn up anything,\n> please consult the source [`terraform-provider-pinecone` repo](https://github.com/pinecone-io/terraform-provider-pinecone/issues).",
"dependencies": {
"@pulumi/pulumi": "^3.0.0"
},
"devDependencies": {
"@types/mime": "^2.0.0",
"@types/node": "^10.0.0"
},
"compatibility": "tfbridge20",
"disableUnionOutputTypes": true
},
"python": {
"packageName": "pinecone_pulumi",
"requires": {
"pulumi": ">=3.0.0,<4.0.0"
},
"readme": "> This provider is a derived work of the [Terraform Provider](https://github.com/pinecone-io/terraform-provider-pinecone)\n> distributed under [MPL 2.0](https://www.mozilla.org/en-US/MPL/2.0/). If you encounter a bug or missing feature,\n> first check the [`pulumi-pinecone` repo](https://github.com/pinecone-io/pulumi-pinecone/issues); however, if that doesn't turn up anything,\n> please consult the source [`terraform-provider-pinecone` repo](https://github.com/pinecone-io/terraform-provider-pinecone/issues).",
"compatibility": "tfbridge20",
"pyproject": {}
}
},
"config": {
"variables": {
"apiKey": {
"type": "string",
"description": "Pinecone API Key. Can be configured by setting PINECONE_API_KEY environment variable.",
"defaultInfo": {
"environment": [
"PINECONE_API_KEY"
]
},
"secret": true
},
"clientId": {
"type": "string",
"description": "Pinecone Client ID for admin operations. Can be configured by setting PINECONE_CLIENT_ID environment variable.",
"defaultInfo": {
"environment": [
"PINECONE_CLIENT_ID"
]
},
"secret": true
},
"clientSecret": {
"type": "string",
"description": "Pinecone Client Secret for admin operations. Can be configured by setting PINECONE_CLIENT_SECRET environment variable.",
"defaultInfo": {
"environment": [
"PINECONE_CLIENT_SECRET"
]
},
"secret": true
}
}
},
"types": {
"pinecone:index/CollectionTimeouts:CollectionTimeouts": {
"properties": {
"create": {
"type": "string",
"description": "Timeout defaults to 5 mins. Accepts a string that can be [parsed as a duration](https://pkg.go.dev/time#ParseDuration) consisting of numbers and unit suffixes, such as \"30s\" or \"2h45m\". Valid time units are \"s\" (seconds), \"m\" (minutes), \"h\" (hours).\n"
},
"delete": {
"type": "string",
"description": "Timeout defaults to 5 mins. Accepts a string that can be [parsed as a duration](https://pkg.go.dev/time#ParseDuration) consisting of numbers and unit suffixes, such as \"30s\" or \"2h45m\". Valid time units are \"s\" (seconds), \"m\" (minutes), \"h\" (hours).\n"
}
},
"type": "object"
},
"pinecone:index/IndexEmbed:IndexEmbed": {
"properties": {
"dimension": {
"type": "integer",
"description": "The dimension of the embedding model, specifying the size of the output vector.\n"
},
"fieldMap": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "Identifies the name of the text field from your document model that will be embedded.\n"
},
"metric": {
"type": "string",
"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'.\n"
},
"model": {
"type": "string",
"description": "the name of the embedding model to use for the index.\n"
},
"readParameters": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "The read parameters for the embedding model.\n"
},
"vectorType": {
"type": "string",
"description": "The index vector type associated with the model. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension will be nil.\n"
},
"writeParameters": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "The write parameters for the embedding model.\n"
}
},
"type": "object",
"language": {
"nodejs": {
"requiredOutputs": [
"dimension",
"fieldMap",
"metric",
"model",
"readParameters",
"vectorType",
"writeParameters"
]
}
}
},
"pinecone:index/IndexSpec:IndexSpec": {
"properties": {
"pod": {
"$ref": "#/types/pinecone:index%2FIndexSpecPod:IndexSpecPod",
"description": "Configuration needed to deploy a pod-based index.\n"
},
"serverless": {
"$ref": "#/types/pinecone:index%2FIndexSpecServerless:IndexSpecServerless",
"description": "Configuration needed to deploy a serverless index.\n"
}
},
"type": "object"
},
"pinecone:index/IndexSpecPod:IndexSpecPod": {
"properties": {
"environment": {
"type": "string",
"description": "The environment where the index is hosted.\n"
},
"metadataConfig": {
"$ref": "#/types/pinecone:index%2FIndexSpecPodMetadataConfig:IndexSpecPodMetadataConfig",
"description": "Configuration for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when metadata*config is present, only specified metadata fields are indexed. These configurations are only valid for use with pod-based indexes.\n"
},
"podType": {
"type": "string",
"description": "The type of pod to use. One of s1, p1, or p2 appended with . and one of x1, x2, x4, or x8.\n"
},
"pods": {
"type": "integer",
"description": "The number of pods to be used in the index. This should be equal to shards x replicas.'\n"
},
"replicas": {
"type": "integer",
"description": "The number of replicas. Replicas duplicate your index. They provide higher availability and throughput. Replicas can be scaled up or down as your needs change.\n"
},
"shards": {
"type": "integer",
"description": "The number of shards. Shards split your data across multiple pods so you can fit more data into an index.\n"
},
"sourceCollection": {
"type": "string",
"description": "The name of the collection to create an index from.\n"
}
},
"type": "object",
"required": [
"environment",
"podType"
],
"language": {
"nodejs": {
"requiredOutputs": [
"environment",
"metadataConfig",
"podType",
"pods",
"replicas",
"shards"
]
}
}
},
"pinecone:index/IndexSpecPodMetadataConfig:IndexSpecPodMetadataConfig": {
"properties": {
"indexeds": {
"type": "array",
"items": {
"type": "string"
},
"description": "The indexed fields.\n"
}
},
"type": "object",
"required": [
"indexeds"
]
},
"pinecone:index/IndexSpecServerless:IndexSpecServerless": {
"properties": {
"cloud": {
"type": "string",
"description": "The public cloud where you would like your index hosted. [gcp|aws|azure]\n"
},
"region": {
"type": "string",
"description": "The region where you would like your index to be created.\n"
}
},
"type": "object",
"required": [
"cloud",
"region"
]
},
"pinecone:index/IndexStatus:IndexStatus": {
"properties": {
"ready": {
"type": "boolean",
"description": "Ready.\n"
},
"state": {
"type": "string",
"description": "Initializing InitializationFailed ScalingUp ScalingDown ScalingUpPodSize ScalingDownPodSize Upgrading Terminating Ready\n"
}
},
"type": "object",
"language": {
"nodejs": {
"requiredOutputs": [
"ready",
"state"
]
}
}
},
"pinecone:index/IndexTimeouts:IndexTimeouts": {
"properties": {
"create": {
"type": "string",
"description": "Timeout defaults to 5 mins. Accepts a string that can be [parsed as a duration](https://pkg.go.dev/time#ParseDuration) consisting of numbers and unit suffixes, such as \"30s\" or \"2h45m\". Valid time units are \"s\" (seconds), \"m\" (minutes), \"h\" (hours).\n"
},
"delete": {
"type": "string",
"description": "Timeout defaults to 5 mins. Accepts a string that can be [parsed as a duration](https://pkg.go.dev/time#ParseDuration) consisting of numbers and unit suffixes, such as \"30s\" or \"2h45m\". Valid time units are \"s\" (seconds), \"m\" (minutes), \"h\" (hours).\n"
}
},
"type": "object"
},
"pinecone:index/getCollectionsCollection:getCollectionsCollection": {
"properties": {
"dimension": {
"type": "integer",
"description": "The dimension of the vectors stored in each record held in the collection.\n"
},
"environment": {
"type": "string",
"description": "The environment where the collection is hosted.\n"
},
"name": {
"type": "string",
"description": "The name of the collection.\n"
},
"size": {
"type": "integer",
"description": "The size of the collection in bytes.\n"
},
"status": {
"type": "string",
"description": "The status of the collection.\n"
},
"vectorCount": {
"type": "integer",
"description": "The number of records stored in the collection.\n"
}
},
"type": "object",
"required": [
"dimension",
"environment",
"name",
"size",
"status",
"vectorCount"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getEmbed:getEmbed": {
"properties": {
"dimension": {
"type": "integer",
"description": "The dimension of the embedding model, specifying the size of the output vector.\n"
},
"fieldMap": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "Identifies the name of the text field from your document model that will be embedded.\n"
},
"metric": {
"type": "string",
"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'.\n"
},
"model": {
"type": "string",
"description": "the name of the embedding model to use for the index.\n"
},
"readParameters": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "The read parameters for the embedding model.\n"
},
"vectorType": {
"type": "string",
"description": "The index vector type associated with the model. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension will be nil.\n"
},
"writeParameters": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "The write parameters for the embedding model.\n"
}
},
"type": "object",
"required": [
"dimension",
"fieldMap",
"metric",
"model",
"readParameters",
"vectorType",
"writeParameters"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getEsIndex:getEsIndex": {
"properties": {
"deletionProtection": {
"type": "string",
"description": "Index deletion protection configuration\n"
},
"dimension": {
"type": "integer",
"description": "Index dimension\n"
},
"embed": {
"$ref": "#/types/pinecone:index%2FgetEsIndexEmbed:getEsIndexEmbed",
"description": "Specify the integrated inference embedding configuration for the index. Once set, the model cannot be changed. However, you can later update the embedding configuration—including field map, read parameters, and write parameters.\n"
},
"host": {
"type": "string",
"description": "The URL address where the index is hosted.\n"
},
"metric": {
"type": "string",
"description": "Index metric\n"
},
"name": {
"type": "string",
"description": "Index name\n"
},
"spec": {
"$ref": "#/types/pinecone:index%2FgetEsIndexSpec:getEsIndexSpec",
"description": "Spec\n"
},
"status": {
"$ref": "#/types/pinecone:index%2FgetEsIndexStatus:getEsIndexStatus",
"description": "Configuration for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when metadata_config is present, only specified metadata fields are indexed. To specify metadata fields to index, provide an array of the following form: [example_metadata_field]\n"
},
"tags": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '', or '-'. Values must be alphanumeric, ';', '@', '', '-', '.', '+', or ' '. To unset a key, set the value to be an empty string.\n"
},
"vectorType": {
"type": "string",
"description": "Index vector type\n"
}
},
"type": "object",
"required": [
"deletionProtection",
"dimension",
"embed",
"host",
"metric",
"name",
"spec",
"status",
"tags",
"vectorType"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getEsIndexEmbed:getEsIndexEmbed": {
"properties": {
"dimension": {
"type": "integer",
"description": "The dimension of the embedding model, specifying the size of the output vector.\n"
},
"fieldMap": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "Identifies the name of the text field from your document model that will be embedded.\n"
},
"metric": {
"type": "string",
"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'.\n"
},
"model": {
"type": "string",
"description": "the name of the embedding model to use for the index.\n"
},
"readParameters": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "The read parameters for the embedding model.\n"
},
"vectorType": {
"type": "string",
"description": "The index vector type associated with the model. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension will be nil.\n"
},
"writeParameters": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "The write parameters for the embedding model.\n"
}
},
"type": "object",
"required": [
"dimension",
"fieldMap",
"metric",
"model",
"readParameters",
"vectorType",
"writeParameters"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getEsIndexSpec:getEsIndexSpec": {
"properties": {
"pod": {
"$ref": "#/types/pinecone:index%2FgetEsIndexSpecPod:getEsIndexSpecPod",
"description": "Configuration needed to deploy a pod-based index.\n"
},
"serverless": {
"$ref": "#/types/pinecone:index%2FgetEsIndexSpecServerless:getEsIndexSpecServerless",
"description": "Configuration needed to deploy a serverless index.\n"
}
},
"type": "object",
"required": [
"pod",
"serverless"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getEsIndexSpecPod:getEsIndexSpecPod": {
"properties": {
"environment": {
"type": "string",
"description": "The environment where the index is hosted.\n"
},
"metadataConfig": {
"$ref": "#/types/pinecone:index%2FgetEsIndexSpecPodMetadataConfig:getEsIndexSpecPodMetadataConfig",
"description": "Configuration for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when metadata*config is present, only specified metadata fields are indexed. These configurations are only valid for use with pod-based indexes.\n"
},
"podType": {
"type": "string",
"description": "The type of pod to use. One of s1, p1, or p2 appended with . and one of x1, x2, x4, or x8.\n"
},
"pods": {
"type": "integer",
"description": "The number of pods to be used in the index. This should be equal to shards x replicas.'\n"
},
"replicas": {
"type": "integer",
"description": "The number of replicas. Replicas duplicate your index. They provide higher availability and throughput. Replicas can be scaled up or down as your needs change.\n"
},
"shards": {
"type": "integer",
"description": "The number of shards. Shards split your data across multiple pods so you can fit more data into an index.\n"
},
"sourceCollection": {
"type": "string",
"description": "The name of the collection to create an index from.\n"
}
},
"type": "object",
"required": [
"environment",
"metadataConfig",
"podType",
"pods",
"replicas",
"shards",
"sourceCollection"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getEsIndexSpecPodMetadataConfig:getEsIndexSpecPodMetadataConfig": {
"properties": {
"indexeds": {
"type": "array",
"items": {
"type": "string"
},
"description": "The indexed fields.\n"
}
},
"type": "object",
"required": [
"indexeds"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getEsIndexSpecServerless:getEsIndexSpecServerless": {
"properties": {
"cloud": {
"type": "string",
"description": "Ready.\n"
},
"region": {
"type": "string",
"description": "Initializing InitializationFailed ScalingUp ScalingDown ScalingUpPodSize ScalingDownPodSize Upgrading Terminating Ready\n"
}
},
"type": "object",
"required": [
"cloud",
"region"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getEsIndexStatus:getEsIndexStatus": {
"properties": {
"ready": {
"type": "boolean",
"description": "Ready.\n"
},
"state": {
"type": "string",
"description": "Initializing InitializationFailed ScalingUp ScalingDown ScalingUpPodSize ScalingDownPodSize Upgrading Terminating Ready\n"
}
},
"type": "object",
"required": [
"ready",
"state"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getSpec:getSpec": {
"properties": {
"pod": {
"$ref": "#/types/pinecone:index%2FgetSpecPod:getSpecPod",
"description": "Configuration needed to deploy a pod-based index.\n"
},
"serverless": {
"$ref": "#/types/pinecone:index%2FgetSpecServerless:getSpecServerless",
"description": "Configuration needed to deploy a serverless index.\n"
}
},
"type": "object",
"required": [
"pod",
"serverless"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getSpecPod:getSpecPod": {
"properties": {
"environment": {
"type": "string",
"description": "The environment where the index is hosted.\n"
},
"metadataConfig": {
"$ref": "#/types/pinecone:index%2FgetSpecPodMetadataConfig:getSpecPodMetadataConfig",
"description": "Configuration for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when metadata*config is present, only specified metadata fields are indexed. These configurations are only valid for use with pod-based indexes.\n"
},
"podType": {
"type": "string",
"description": "The type of pod to use. One of s1, p1, or p2 appended with . and one of x1, x2, x4, or x8.\n"
},
"pods": {
"type": "integer",
"description": "The number of pods to be used in the index. This should be equal to shards x replicas.'\n"
},
"replicas": {
"type": "integer",
"description": "The number of replicas. Replicas duplicate your index. They provide higher availability and throughput. Replicas can be scaled up or down as your needs change.\n"
},
"shards": {
"type": "integer",
"description": "The number of shards. Shards split your data across multiple pods so you can fit more data into an index.\n"
},
"sourceCollection": {
"type": "string",
"description": "The name of the collection to create an index from.\n"
}
},
"type": "object",
"required": [
"environment",
"metadataConfig",
"podType",
"pods",
"replicas",
"shards",
"sourceCollection"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getSpecPodMetadataConfig:getSpecPodMetadataConfig": {
"properties": {
"indexeds": {
"type": "array",
"items": {
"type": "string"
},
"description": "The indexed fields.\n"
}
},
"type": "object",
"required": [
"indexeds"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getSpecServerless:getSpecServerless": {
"properties": {
"cloud": {
"type": "string",
"description": "Ready.\n"
},
"region": {
"type": "string",
"description": "Initializing InitializationFailed ScalingUp ScalingDown ScalingUpPodSize ScalingDownPodSize Upgrading Terminating Ready\n"
}
},
"type": "object",
"required": [
"cloud",
"region"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
},
"pinecone:index/getStatus:getStatus": {
"properties": {
"ready": {
"type": "boolean",
"description": "Ready.\n"
},
"state": {
"type": "string",
"description": "Initializing InitializationFailed ScalingUp ScalingDown ScalingUpPodSize ScalingDownPodSize Upgrading Terminating Ready\n"
}
},
"type": "object",
"required": [
"ready",
"state"
],
"language": {
"nodejs": {
"requiredInputs": []
}
}
}
},
"provider": {
"description": "The provider type for the pinecone package. By default, resources use package-wide configuration\nsettings, however an explicit `Provider` instance may be created and passed during resource\nconstruction to achieve fine-grained programmatic control over provider settings. See the\n[documentation](https://www.pulumi.com/docs/reference/programming-model/#providers) for more information.\n",
"properties": {
"apiKey": {
"type": "string",
"description": "Pinecone API Key. Can be configured by setting PINECONE_API_KEY environment variable.",
"secret": true
},
"clientId": {
"type": "string",
"description": "Pinecone Client ID for admin operations. Can be configured by setting PINECONE_CLIENT_ID environment variable.",
"secret": true
},
"clientSecret": {
"type": "string",
"description": "Pinecone Client Secret for admin operations. Can be configured by setting PINECONE_CLIENT_SECRET environment variable.",
"secret": true
}
},
"type": "object",
"inputProperties": {
"apiKey": {
"type": "string",
"description": "Pinecone API Key. Can be configured by setting PINECONE_API_KEY environment variable.",
"defaultInfo": {
"environment": [
"PINECONE_API_KEY"
]
},
"secret": true
},
"clientId": {
"type": "string",
"description": "Pinecone Client ID for admin operations. Can be configured by setting PINECONE_CLIENT_ID environment variable.",
"defaultInfo": {
"environment": [
"PINECONE_CLIENT_ID"
]
},
"secret": true
},
"clientSecret": {
"type": "string",
"description": "Pinecone Client Secret for admin operations. Can be configured by setting PINECONE_CLIENT_SECRET environment variable.",
"defaultInfo": {
"environment": [
"PINECONE_CLIENT_SECRET"
]
},
"secret": true
}
},
"methods": {
"terraformConfig": "pulumi:providers:pinecone/terraformConfig"
}
},
"resources": {
"pinecone:index/apiKey:ApiKey": {
"description": "The `pinecone.ApiKey` resource lets you create and manage API keys in Pinecone. Learn more about API keys in the [docs](https://docs.pinecone.io/guides/authentication/api-keys).\n\n## Example Usage\n\n\n```typescript\nimport * as pulumi from \"@pulumi/pulumi\";\nimport * as pinecone from \"@pulumi/pinecone\";\n\n// Create API key with default roles (ProjectEditor)\nconst example = new pinecone.ApiKey(\"example\", {\n name: \"example-api-key\",\n projectId: \"your-project-id\",\n});\n// Create API key with custom roles\nconst customRoles = new pinecone.ApiKey(\"custom_roles\", {\n name: \"custom-roles-api-key\",\n projectId: \"your-project-id\",\n roles: [\n \"ProjectViewer\",\n \"DataPlaneViewer\",\n ],\n});\n// Create an API key that can be updated later\nconst updatable = new pinecone.ApiKey(\"updatable\", {\n name: \"example-updatable-key\",\n projectId: \"your-project-id\",\n roles: [\"ProjectEditor\"],\n});\nexport const apiKeyRoles = example.roles;\n```\n```python\nimport pulumi\nimport pulumi_pinecone as pinecone\n\n# Create API key with default roles (ProjectEditor)\nexample = pinecone.ApiKey(\"example\",\n name=\"example-api-key\",\n project_id=\"your-project-id\")\n# Create API key with custom roles\ncustom_roles = pinecone.ApiKey(\"custom_roles\",\n name=\"custom-roles-api-key\",\n project_id=\"your-project-id\",\n roles=[\n \"ProjectViewer\",\n \"DataPlaneViewer\",\n ])\n# Create an API key that can be updated later\nupdatable = pinecone.ApiKey(\"updatable\",\n name=\"example-updatable-key\",\n project_id=\"your-project-id\",\n roles=[\"ProjectEditor\"])\npulumi.export(\"apiKeyRoles\", example.roles)\n```\n```csharp\nusing System.Collections.Generic;\nusing System.Linq;\nusing Pulumi;\nusing Pinecone = Pulumi.Pinecone;\n\nreturn await Deployment.RunAsync(() => \n{\n // Create API key with default roles (ProjectEditor)\n var example = new Pinecone.ApiKey(\"example\", new()\n {\n Name = \"example-api-key\",\n ProjectId = \"your-project-id\",\n });\n\n // Create API key with custom roles\n var customRoles = new Pinecone.ApiKey(\"custom_roles\", new()\n {\n Name = \"custom-roles-api-key\",\n ProjectId = \"your-project-id\",\n Roles = new[]\n {\n \"ProjectViewer\",\n \"DataPlaneViewer\",\n },\n });\n\n // Create an API key that can be updated later\n var updatable = new Pinecone.ApiKey(\"updatable\", new()\n {\n Name = \"example-updatable-key\",\n ProjectId = \"your-project-id\",\n Roles = new[]\n {\n \"ProjectEditor\",\n },\n });\n\n return new Dictionary\n {\n [\"apiKeyRoles\"] = example.Roles,\n };\n});\n```\n```go\npackage main\n\nimport (\n\t\"github.com/pulumi/pulumi-terraform-provider/sdks/go/pinecone/v2/pinecone\"\n\t\"github.com/pulumi/pulumi/sdk/v3/go/pulumi\"\n)\n\nfunc main() {\n\tpulumi.Run(func(ctx *pulumi.Context) error {\n\t\t// Create API key with default roles (ProjectEditor)\n\t\texample, err := pinecone.NewApiKey(ctx, \"example\", &pinecone.ApiKeyArgs{\n\t\t\tName: pulumi.String(\"example-api-key\"),\n\t\t\tProjectId: pulumi.String(\"your-project-id\"),\n\t\t})\n\t\tif err != nil {\n\t\t\treturn err\n\t\t}\n\t\t// Create API key with custom roles\n\t\t_, err = pinecone.NewApiKey(ctx, \"custom_roles\", &pinecone.ApiKeyArgs{\n\t\t\tName: pulumi.String(\"custom-roles-api-key\"),\n\t\t\tProjectId: pulumi.String(\"your-project-id\"),\n\t\t\tRoles: pulumi.StringArray{\n\t\t\t\tpulumi.String(\"ProjectViewer\"),\n\t\t\t\tpulumi.String(\"DataPlaneViewer\"),\n\t\t\t},\n\t\t})\n\t\tif err != nil {\n\t\t\treturn err\n\t\t}\n\t\t// Create an API key that can be updated later\n\t\t_, err = pinecone.NewApiKey(ctx, \"updatable\", &pinecone.ApiKeyArgs{\n\t\t\tName: pulumi.String(\"example-updatable-key\"),\n\t\t\tProjectId: pulumi.String(\"your-project-id\"),\n\t\t\tRoles: pulumi.StringArray{\n\t\t\t\tpulumi.String(\"ProjectEditor\"),\n\t\t\t},\n\t\t})\n\t\tif err != nil {\n\t\t\treturn err\n\t\t}\n\t\tctx.Export(\"apiKeyRoles\", example.Roles)\n\t\treturn nil\n\t})\n}\n```\n```java\npackage generated_program;\n\nimport com.pulumi.Context;\nimport com.pulumi.Pulumi;\nimport com.pulumi.core.Output;\nimport com.pulumi.pinecone.ApiKey;\nimport com.pulumi.pinecone.ApiKeyArgs;\nimport java.util.List;\nimport java.util.ArrayList;\nimport java.util.Map;\nimport java.io.File;\nimport java.nio.file.Files;\nimport java.nio.file.Paths;\n\npublic class App {\n public static void main(String[] args) {\n Pulumi.run(App::stack);\n }\n\n public static void stack(Context ctx) {\n // Create API key with default roles (ProjectEditor)\n var example = new ApiKey(\"example\", ApiKeyArgs.builder()\n .name(\"example-api-key\")\n .projectId(\"your-project-id\")\n .build());\n\n // Create API key with custom roles\n var customRoles = new ApiKey(\"customRoles\", ApiKeyArgs.builder()\n .name(\"custom-roles-api-key\")\n .projectId(\"your-project-id\")\n .roles( \n \"ProjectViewer\",\n \"DataPlaneViewer\")\n .build());\n\n // Create an API key that can be updated later\n var updatable = new ApiKey(\"updatable\", ApiKeyArgs.builder()\n .name(\"example-updatable-key\")\n .projectId(\"your-project-id\")\n .roles(\"ProjectEditor\")\n .build());\n\n ctx.export(\"apiKeyRoles\", example.roles());\n }\n}\n```\n```yaml\nresources:\n # Create API key with default roles (ProjectEditor)\n example:\n type: pinecone:ApiKey\n properties:\n name: example-api-key\n projectId: your-project-id\n # Create API key with custom roles\n customRoles:\n type: pinecone:ApiKey\n name: custom_roles\n properties:\n name: custom-roles-api-key\n projectId: your-project-id\n roles:\n - ProjectViewer\n - DataPlaneViewer\n # Create an API key that can be updated later\n updatable:\n type: pinecone:ApiKey\n properties:\n name: example-updatable-key\n projectId: your-project-id\n roles:\n - ProjectEditor\noutputs:\n # Example of how to update the API key\n # resource \"pinecone_api_key\" \"updatable\" {\n # name = \"updated-name\"\n # roles = [\"ProjectViewer\", \"DataPlaneViewer\"]\n # }\n apiKeyRoles: ${example.roles}\n```\n\n",
"properties": {
"key": {
"type": "string",
"description": "The generated API key value.\n",
"secret": true
},
"name": {
"type": "string",
"description": "The name of the API key to be created. Must be 1-80 characters long.\n"
},
"projectId": {
"type": "string",
"description": "The project ID where the API key will be created. Required for creation, optional for updates.\n"
},
"roles": {
"type": "array",
"items": {
"type": "string"
},
"description": "The roles assigned to the API key. Valid values are: ProjectEditor, ProjectViewer, ControlPlaneEditor, ControlPlaneViewer, DataPlaneEditor, DataPlaneViewer. Defaults to [\"ProjectEditor\"].\n"
}
},
"type": "object",
"required": [
"key",
"name",
"roles"
],
"inputProperties": {
"name": {
"type": "string",
"description": "The name of the API key to be created. Must be 1-80 characters long.\n"
},
"projectId": {
"type": "string",
"description": "The project ID where the API key will be created. Required for creation, optional for updates.\n"
},
"roles": {
"type": "array",
"items": {
"type": "string"
},
"description": "The roles assigned to the API key. Valid values are: ProjectEditor, ProjectViewer, ControlPlaneEditor, ControlPlaneViewer, DataPlaneEditor, DataPlaneViewer. Defaults to [\"ProjectEditor\"].\n"
}
},
"stateInputs": {
"description": "Input properties used for looking up and filtering ApiKey resources.\n",
"properties": {
"key": {
"type": "string",
"description": "The generated API key value.\n",
"secret": true
},
"name": {
"type": "string",
"description": "The name of the API key to be created. Must be 1-80 characters long.\n"
},
"projectId": {
"type": "string",
"description": "The project ID where the API key will be created. Required for creation, optional for updates.\n"
},
"roles": {
"type": "array",
"items": {
"type": "string"
},
"description": "The roles assigned to the API key. Valid values are: ProjectEditor, ProjectViewer, ControlPlaneEditor, ControlPlaneViewer, DataPlaneEditor, DataPlaneViewer. Defaults to [\"ProjectEditor\"].\n"
}
},
"type": "object"
}
},
"pinecone:index/collection:Collection": {
"description": "The `pinecone.Collection` resource lets you create and manage collections in Pinecone. Learn more about collections in the docs.\n\n## Example Usage\n\n\n```typescript\nimport * as pulumi from \"@pulumi/pulumi\";\nimport * as pinecone from \"@pulumi/pinecone\";\n\nconst test = new pinecone.Index(\"test\", {\n name: \"tftestindex\",\n dimension: 10,\n spec: {\n pod: {\n environment: \"us-west4-gcp\",\n podType: \"s1.x1\",\n },\n },\n});\nconst testCollection = new pinecone.Collection(\"test\", {\n name: \"tftestcollection\",\n source: test.name,\n});\n```\n```python\nimport pulumi\nimport pulumi_pinecone as pinecone\n\ntest = pinecone.Index(\"test\",\n name=\"tftestindex\",\n dimension=10,\n spec={\n \"pod\": {\n \"environment\": \"us-west4-gcp\",\n \"pod_type\": \"s1.x1\",\n },\n })\ntest_collection = pinecone.Collection(\"test\",\n name=\"tftestcollection\",\n source=test.name)\n```\n```csharp\nusing System.Collections.Generic;\nusing System.Linq;\nusing Pulumi;\nusing Pinecone = Pulumi.Pinecone;\n\nreturn await Deployment.RunAsync(() => \n{\n var test = new Pinecone.Index(\"test\", new()\n {\n Name = \"tftestindex\",\n Dimension = 10,\n Spec = new Pinecone.Inputs.IndexSpecArgs\n {\n Pod = new Pinecone.Inputs.IndexSpecPodArgs\n {\n Environment = \"us-west4-gcp\",\n PodType = \"s1.x1\",\n },\n },\n });\n\n var testCollection = new Pinecone.Collection(\"test\", new()\n {\n Name = \"tftestcollection\",\n Source = test.Name,\n });\n\n});\n```\n```go\npackage main\n\nimport (\n\t\"github.com/pulumi/pulumi-terraform-provider/sdks/go/pinecone/v2/pinecone\"\n\t\"github.com/pulumi/pulumi/sdk/v3/go/pulumi\"\n)\n\nfunc main() {\n\tpulumi.Run(func(ctx *pulumi.Context) error {\n\t\ttest, err := pinecone.NewIndex(ctx, \"test\", &pinecone.IndexArgs{\n\t\t\tName: pulumi.String(\"tftestindex\"),\n\t\t\tDimension: pulumi.Float64(10),\n\t\t\tSpec: &pinecone.IndexSpecArgs{\n\t\t\t\tPod: &pinecone.IndexSpecPodArgs{\n\t\t\t\t\tEnvironment: pulumi.String(\"us-west4-gcp\"),\n\t\t\t\t\tPodType: pulumi.String(\"s1.x1\"),\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t\tif err != nil {\n\t\t\treturn err\n\t\t}\n\t\t_, err = pinecone.NewCollection(ctx, \"test\", &pinecone.CollectionArgs{\n\t\t\tName: pulumi.String(\"tftestcollection\"),\n\t\t\tSource: test.Name,\n\t\t})\n\t\tif err != nil {\n\t\t\treturn err\n\t\t}\n\t\treturn nil\n\t})\n}\n```\n```java\npackage generated_program;\n\nimport com.pulumi.Context;\nimport com.pulumi.Pulumi;\nimport com.pulumi.core.Output;\nimport com.pulumi.pinecone.Index;\nimport com.pulumi.pinecone.IndexArgs;\nimport com.pulumi.pinecone.inputs.IndexSpecArgs;\nimport com.pulumi.pinecone.inputs.IndexSpecPodArgs;\nimport com.pulumi.pinecone.Collection;\nimport com.pulumi.pinecone.CollectionArgs;\nimport java.util.List;\nimport java.util.ArrayList;\nimport java.util.Map;\nimport java.io.File;\nimport java.nio.file.Files;\nimport java.nio.file.Paths;\n\npublic class App {\n public static void main(String[] args) {\n Pulumi.run(App::stack);\n }\n\n public static void stack(Context ctx) {\n var test = new Index(\"test\", IndexArgs.builder()\n .name(\"tftestindex\")\n .dimension(10.0)\n .spec(IndexSpecArgs.builder()\n .pod(IndexSpecPodArgs.builder()\n .environment(\"us-west4-gcp\")\n .podType(\"s1.x1\")\n .build())\n .build())\n .build());\n\n var testCollection = new Collection(\"testCollection\", CollectionArgs.builder()\n .name(\"tftestcollection\")\n .source(test.name())\n .build());\n\n }\n}\n```\n```yaml\nresources:\n test:\n type: pinecone:Index\n properties:\n name: tftestindex\n dimension: 10\n spec:\n pod:\n environment: us-west4-gcp\n podType: s1.x1\n testCollection:\n type: pinecone:Collection\n name: test\n properties:\n name: tftestcollection\n source: ${test.name}\n```\n\n",
"properties": {
"dimension": {
"type": "integer",
"description": "The dimension of the vectors stored in each record held in the collection.\n"
},
"environment": {
"type": "string",
"description": "The environment where the collection is hosted.\n"
},
"name": {
"type": "string",
"description": "The name of the collection.\n"
},
"size": {
"type": "integer",
"description": "The size of the collection in bytes.\n"
},
"source": {
"type": "string",
"description": "The name of the source index to be used as the source for the collection.\n"
},
"status": {
"type": "string",
"description": "The status of the collection.\n"
},
"timeouts": {
"$ref": "#/types/pinecone:index%2FCollectionTimeouts:CollectionTimeouts"
},
"vectorCount": {
"type": "integer",
"description": "The number of records stored in the collection.\n"
}
},
"type": "object",
"required": [
"dimension",
"environment",
"name",
"size",
"source",
"status",
"vectorCount"
],
"inputProperties": {
"dimension": {
"type": "integer",
"description": "The dimension of the vectors stored in each record held in the collection.\n"
},
"name": {
"type": "string",
"description": "The name of the collection.\n"
},
"size": {
"type": "integer",
"description": "The size of the collection in bytes.\n"
},
"source": {
"type": "string",
"description": "The name of the source index to be used as the source for the collection.\n"
},
"timeouts": {
"$ref": "#/types/pinecone:index%2FCollectionTimeouts:CollectionTimeouts"
},
"vectorCount": {
"type": "integer",
"description": "The number of records stored in the collection.\n"
}
},
"requiredInputs": [
"source"
],
"stateInputs": {
"description": "Input properties used for looking up and filtering Collection resources.\n",
"properties": {
"dimension": {
"type": "integer",
"description": "The dimension of the vectors stored in each record held in the collection.\n"
},
"environment": {
"type": "string",
"description": "The environment where the collection is hosted.\n"
},
"name": {
"type": "string",
"description": "The name of the collection.\n"
},
"size": {
"type": "integer",
"description": "The size of the collection in bytes.\n"
},
"source": {
"type": "string",
"description": "The name of the source index to be used as the source for the collection.\n"
},
"status": {
"type": "string",
"description": "The status of the collection.\n"
},
"timeouts": {
"$ref": "#/types/pinecone:index%2FCollectionTimeouts:CollectionTimeouts"
},
"vectorCount": {
"type": "integer",
"description": "The number of records stored in the collection.\n"
}
},
"type": "object"
}
},
"pinecone:index/index:Index": {
"description": "The `pinecone.Index` resource lets you create and manage indexes in Pinecone. Learn more about indexes in the [docs](https://docs.pinecone.io/guides/indexes/understanding-indexes).\n\n## Example Usage\n\n\n```typescript\nimport * as pulumi from \"@pulumi/pulumi\";\nimport * as pinecone from \"@pulumi/pinecone\";\n\nconst test = new pinecone.Index(\"test\", {\n name: \"tftestindex\",\n dimension: 10,\n spec: {\n serverless: {\n cloud: \"aws\",\n region: \"us-west-2\",\n },\n },\n});\n```\n```python\nimport pulumi\nimport pulumi_pinecone as pinecone\n\ntest = pinecone.Index(\"test\",\n name=\"tftestindex\",\n dimension=10,\n spec={\n \"serverless\": {\n \"cloud\": \"aws\",\n \"region\": \"us-west-2\",\n },\n })\n```\n```csharp\nusing System.Collections.Generic;\nusing System.Linq;\nusing Pulumi;\nusing Pinecone = Pulumi.Pinecone;\n\nreturn await Deployment.RunAsync(() => \n{\n var test = new Pinecone.Index(\"test\", new()\n {\n Name = \"tftestindex\",\n Dimension = 10,\n Spec = new Pinecone.Inputs.IndexSpecArgs\n {\n Serverless = new Pinecone.Inputs.IndexSpecServerlessArgs\n {\n Cloud = \"aws\",\n Region = \"us-west-2\",\n },\n },\n });\n\n});\n```\n```go\npackage main\n\nimport (\n\t\"github.com/pulumi/pulumi-terraform-provider/sdks/go/pinecone/v2/pinecone\"\n\t\"github.com/pulumi/pulumi/sdk/v3/go/pulumi\"\n)\n\nfunc main() {\n\tpulumi.Run(func(ctx *pulumi.Context) error {\n\t\t_, err := pinecone.NewIndex(ctx, \"test\", &pinecone.IndexArgs{\n\t\t\tName: pulumi.String(\"tftestindex\"),\n\t\t\tDimension: pulumi.Float64(10),\n\t\t\tSpec: &pinecone.IndexSpecArgs{\n\t\t\t\tServerless: &pinecone.IndexSpecServerlessArgs{\n\t\t\t\t\tCloud: pulumi.String(\"aws\"),\n\t\t\t\t\tRegion: pulumi.String(\"us-west-2\"),\n\t\t\t\t},\n\t\t\t},\n\t\t})\n\t\tif err != nil {\n\t\t\treturn err\n\t\t}\n\t\treturn nil\n\t})\n}\n```\n```java\npackage generated_program;\n\nimport com.pulumi.Context;\nimport com.pulumi.Pulumi;\nimport com.pulumi.core.Output;\nimport com.pulumi.pinecone.Index;\nimport com.pulumi.pinecone.IndexArgs;\nimport com.pulumi.pinecone.inputs.IndexSpecArgs;\nimport com.pulumi.pinecone.inputs.IndexSpecServerlessArgs;\nimport java.util.List;\nimport java.util.ArrayList;\nimport java.util.Map;\nimport java.io.File;\nimport java.nio.file.Files;\nimport java.nio.file.Paths;\n\npublic class App {\n public static void main(String[] args) {\n Pulumi.run(App::stack);\n }\n\n public static void stack(Context ctx) {\n var test = new Index(\"test\", IndexArgs.builder()\n .name(\"tftestindex\")\n .dimension(10.0)\n .spec(IndexSpecArgs.builder()\n .serverless(IndexSpecServerlessArgs.builder()\n .cloud(\"aws\")\n .region(\"us-west-2\")\n .build())\n .build())\n .build());\n\n }\n}\n```\n```yaml\nresources:\n test:\n type: pinecone:Index\n properties:\n name: tftestindex\n dimension: 10\n spec:\n serverless:\n cloud: aws\n region: us-west-2\n```\n\n",
"properties": {
"deletionProtection": {
"type": "string",
"description": "Whether deletion protection for the index is enabled. You can use 'enabled', or 'disabled'.\n"
},
"dimension": {
"type": "integer",
"description": "The dimensions of the vectors to be inserted in the index\n"
},
"embed": {
"$ref": "#/types/pinecone:index%2FIndexEmbed:IndexEmbed",
"description": "Specify the integrated inference embedding configuration for the index. Once set, the model cannot be changed. However, you can later update the embedding configuration—including field map, read parameters, and write parameters.\n"
},
"host": {
"type": "string",
"description": "The URL address where the index is hosted."
},
"metric": {
"type": "string",
"description": "The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If the 'vector_type' is 'sparse', the metric must be 'dotproduct'. If the vector_type is dense, the metric defaults to 'cosine'."
},
"name": {
"type": "string",
"description": "The name of the index to be created. The maximum length is 45 characters.\n"
},
"spec": {
"$ref": "#/types/pinecone:index%2FIndexSpec:IndexSpec",
"description": "Spec"
},
"status": {
"$ref": "#/types/pinecone:index%2FIndexStatus:IndexStatus",
"description": "Status"
},
"tags": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '', or '-'. Values must be alphanumeric, ';', '@', '', '-', '.', '+', or ' '. To unset a key, set the value to be an empty string."
},
"timeouts": {
"$ref": "#/types/pinecone:index%2FIndexTimeouts:IndexTimeouts"
},
"vectorType": {
"type": "string",
"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."
}
},
"type": "object",
"required": [
"deletionProtection",
"dimension",
"embed",
"host",
"metric",
"name",
"status",
"tags",
"vectorType"
],
"inputProperties": {
"deletionProtection": {
"type": "string",
"description": "Whether deletion protection for the index is enabled. You can use 'enabled', or 'disabled'.\n"
},
"dimension": {
"type": "integer",
"description": "The dimensions of the vectors to be inserted in the index\n"
},
"embed": {
"$ref": "#/types/pinecone:index%2FIndexEmbed:IndexEmbed",
"description": "Specify the integrated inference embedding configuration for the index. Once set, the model cannot be changed. However, you can later update the embedding configuration—including field map, read parameters, and write parameters.\n"
},
"metric": {
"type": "string",
"description": "The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If the 'vector_type' is 'sparse', the metric must be 'dotproduct'. If the vector_type is dense, the metric defaults to 'cosine'."
},
"name": {
"type": "string",
"description": "The name of the index to be created. The maximum length is 45 characters.\n"
},
"spec": {
"$ref": "#/types/pinecone:index%2FIndexSpec:IndexSpec",
"description": "Spec"
},
"tags": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '', or '-'. Values must be alphanumeric, ';', '@', '', '-', '.', '+', or ' '. To unset a key, set the value to be an empty string."
},
"timeouts": {
"$ref": "#/types/pinecone:index%2FIndexTimeouts:IndexTimeouts"
},
"vectorType": {
"type": "string",
"description": "The index vector type. You can use 'dense' or 'sparse'. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension should not be specified."
}
},
"stateInputs": {
"description": "Input properties used for looking up and filtering Index resources.\n",
"properties": {
"deletionProtection": {
"type": "string",
"description": "Whether deletion protection for the index is enabled. You can use 'enabled', or 'disabled'.\n"
},
"dimension": {
"type": "integer",
"description": "The dimensions of the vectors to be inserted in the index\n"
},
"embed": {
"$ref": "#/types/pinecone:index%2FIndexEmbed:IndexEmbed",
"description": "Specify the integrated inference embedding configuration for the index. Once set, the model cannot be changed. However, you can later update the embedding configuration—including field map, read parameters, and write parameters.\n"
},
"host": {
"type": "string",
"description": "The URL address where the index is hosted."
},
"metric": {
"type": "string",
"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'."
},
"name": {
"type": "string",
"description": "The name of the index to be created. The maximum length is 45 characters.\n"
},
"spec": {
"$ref": "#/types/pinecone:index%2FIndexSpec:IndexSpec",
"description": "Spec"
},
"status": {
"$ref": "#/types/pinecone:index%2FIndexStatus:IndexStatus",
"description": "Status"
},
"tags": {
"type": "object",
"additionalProperties": {
"type": "string"
},
"description": "Custom user tags added to an index. Keys must be 80 characters or less. Values must be 120 characters or less. Keys must be alphanumeric, '', or '-'. Values must be alphanumeric, ';', '@', '', '-', '.', '+', or ' '. To unset a key, set the value to be an empty string."
},
"timeouts": {
"$ref": "#/types/pinecone:index%2FIndexTimeouts:IndexTimeouts"
},
"vectorType": {
"type": "string",
"description": "The index vector type. You can use 'dense' or 'sparse'. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension should not be specified."
}
},
"type": "object"
}
}
},
"functions": {
"pinecone:index/get:get": {
"description": "Index data source\n\n",
"inputs": {
"description": "A collection of arguments for invoking get.\n",
"properties": {
"embed": {
"$ref": "#/types/pinecone:index%2FgetEmbed:getEmbed",
"description": "Specify the integrated inference embedding configuration for the index. Once set, the model cannot be changed. However, you can later update the embedding configuration—including field map, read parameters, and write parameters.\n"
},
"name": {
"type": "string",
"description": "Index name\n"
},
"spec": {
"$ref": "#/types/pinecone:index%2FgetSpec:getSpec"
},
"status": {
"$ref": "#/types/pinecone:index%2FgetStatus:getStatus"
}
},
"type": "object",
"required": [
"name"
]
},
"outputs": {
"description": "A collection of values returned by get.\n",
"properties": {
"deletionProtection": {
"type": "string"
},
"dimension": {
"type": "integer"
},
"embed": {
"$ref": "#/types/pinecone:index%2FgetEmbed:getEmbed",
"description": "Specify the integrated inference embedding configuration for the index. Once set, the model cannot be changed. However, you can later update the embedding configuration—including field map, read parameters, and write parameters.\n"
},
"host": {
"type": "string"
},
"id": {
"type": "string"
},
"metric": {
"type": "string"
},
"name": {
"description": "Index name\n",
"type": "string"
},
"spec": {
"$ref": "#/types/pinecone:index%2FgetSpec:getSpec"
},
"status": {
"$ref": "#/types/pinecone:index%2FgetStatus:getStatus"
},
"tags": {
"additionalProperties": {
"type": "string"
},
"type": "object"
},
"vectorType": {
"type": "string"
}
},
"required": [
"deletionProtection",
"dimension",
"embed",
"host",
"id",
"metric",
"name",
"spec",
"status",
"tags",
"vectorType"
],
"type": "object"
}
},
"pinecone:index/getCollection:getCollection": {
"description": "Collection data source\n\n",
"inputs": {
"description": "A collection of arguments for invoking getCollection.\n",
"properties": {
"name": {
"type": "string",
"description": "The name of the collection.\n"
}
},
"type": "object",
"required": [
"name"
]
},
"outputs": {
"description": "A collection of values returned by getCollection.\n",
"properties": {
"dimension": {
"description": "The dimension of the vectors stored in each record held in the collection.\n",
"type": "integer"
},
"environment": {
"description": "The environment where the collection is hosted.\n",
"type": "string"
},
"id": {
"description": "Collection identifier\n",
"type": "string"
},
"name": {
"description": "The name of the collection.\n",
"type": "string"
},
"size": {
"description": "The size of the collection in bytes.\n",
"type": "integer"
},
"status": {
"description": "The status of the collection.\n",
"type": "string"
},
"vectorCount": {
"description": "The number of records stored in the collection.\n",
"type": "integer"
}
},
"required": [
"dimension",
"environment",
"id",
"name",
"size",
"status",
"vectorCount"
],
"type": "object"
}
},
"pinecone:index/getCollections:getCollections": {
"description": "Collections data source\n\n",
"outputs": {
"description": "A collection of values returned by getCollections.\n",
"properties": {
"collections": {
"description": "List of the collections in your project\n",
"items": {
"$ref": "#/types/pinecone:index%2FgetCollectionsCollection:getCollectionsCollection"
},
"type": "array"
},
"id": {
"description": "Collections identifier\n",
"type": "string"
}
},
"required": [
"collections",
"id"
],
"type": "object"
}
},
"pinecone:index/getEs:getEs": {
"description": "Indexes data source\n\n",
"outputs": {
"description": "A collection of values returned by getEs.\n",
"properties": {
"id": {
"description": "Indexes identifier\n",
"type": "string"
},
"indexes": {
"description": "List of the indexes in your project\n",
"items": {
"$ref": "#/types/pinecone:index%2FgetEsIndex:getEsIndex"
},
"type": "array"
}
},
"required": [
"id",
"indexes"
],
"type": "object"
}
},
"pulumi:providers:pinecone/terraformConfig": {
"description": "This function returns a Terraform config object with terraform-namecased keys,to be used with the Terraform Module Provider.",
"inputs": {
"properties": {
"__self__": {
"$ref": "#/resources/pulumi:providers:pinecone"
}
},
"type": "object",
"required": [
"__self__"
]
},
"outputs": {
"properties": {
"result": {
"additionalProperties": {
"$ref": "pulumi.json#/Any"
},
"type": "object"
}
},
"required": [
"result"
],
"type": "object"
}
}
}
}