2300 lines
72 KiB
JSON
2300 lines
72 KiB
JSON
{
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|
"components": {
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"schemas": {
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"CancelImportResponse": {
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"description": "The response for the `cancel_import` operation.",
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"type": "object"
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},
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"DeleteRequest": {
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"description": "The request for the `delete` operation.",
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"properties": {
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"deleteAll": {
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"default": "false",
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"description": "This indicates that all vectors in the index namespace should be deleted.",
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"example": false,
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"type": "boolean"
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},
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"filter": {
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"description": "If specified, the metadata filter here will be used to select the vectors to delete. This is mutually exclusive with specifying ids to delete in the ids param or using delete_all=True. See [Delete data](https://docs.pinecone.io/guides/manage-data/delete-data#delete-records-by-metadata).",
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"type": "object"
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},
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"ids": {
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"description": "Vectors to delete.",
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"example": [
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"id-0",
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"id-1"
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],
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"items": {
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"type": "string"
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},
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"maxLength": 1000,
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"minLength": 1,
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"type": "array"
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},
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"namespace": {
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"description": "The namespace to delete vectors from, if applicable.",
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"example": "example-namespace",
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"type": "string"
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}
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},
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"type": "object"
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},
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"DeleteResponse": {
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"description": "The response for the `delete` operation.",
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"type": "object"
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},
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"DescribeIndexStatsRequest": {
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"description": "The request for the `describe_index_stats` operation.",
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"properties": {
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"filter": {
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"description": "If this parameter is present, the operation only returns statistics for vectors that satisfy the filter. See [Understanding metadata](https://docs.pinecone.io/guides/index-data/indexing-overview#metadata).\n\nServerless indexes do not support filtering `describe_index_stats` by metadata.",
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"type": "object"
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}
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},
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"type": "object"
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},
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"EmbedInputs": {
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"example": {
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"text": "chunk_text"
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},
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"type": "object"
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},
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"FetchResponse": {
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"description": "The response for the `fetch` operation.",
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"example": {
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"namespace": "example-namespace",
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"usage": {
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"readUnits": 1
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},
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"vectors": {
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"id-1": {
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"id": "id-1",
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"values": [
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1.0,
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1.5
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]
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},
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"id-2": {
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"id": "id-2",
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"values": [
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2.0,
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1.0
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]
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}
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}
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},
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"properties": {
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"namespace": {
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"description": "The namespace of the vectors.",
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"example": "example-namespace",
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"type": "string"
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},
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"usage": {
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"$ref": "#/components/schemas/Usage"
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},
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"vectors": {
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"additionalProperties": {
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"$ref": "#/components/schemas/Vector"
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},
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"title": "The fetched vectors, in the form of a map between the fetched ids and the fetched vectors",
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"type": "object"
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}
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},
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"type": "object"
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},
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"Hit": {
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"description": "A record whose vector values are similar to the provided search query.",
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"example": {
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"_id": "example-record-1",
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"_score": 0.9281134605407715,
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"fields": {
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"data": "your example text",
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"more_data": {
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"text": "your example text"
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}
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}
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},
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"properties": {
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"_id": {
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"description": "The record id of the search hit.",
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"type": "string"
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},
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"_score": {
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"description": "The similarity score of the returned record.",
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"format": "float",
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"type": "number"
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},
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"fields": {
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"description": "The selected record fields associated with the search hit.",
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"type": "object"
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}
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},
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"required": [
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"_id",
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"_score",
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"fields"
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],
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"type": "object"
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},
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"ImportErrorMode": {
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"description": "Indicates how to respond to errors during the import process.",
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"properties": {
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"onError": {
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"description": "Indicates how to respond to errors during the import process.",
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"enum": [
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"abort",
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"continue"
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],
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"type": "string"
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}
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},
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"type": "object"
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},
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"ImportModel": {
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"description": "The model for an import operation.",
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"properties": {
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"createdAt": {
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"description": "The start time of the import operation.",
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"format": "date-time",
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"type": "string"
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},
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"error": {
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"description": "The error message if the import process failed.",
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"type": "string"
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},
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"finishedAt": {
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"description": "The end time of the import operation.",
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"format": "date-time",
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"type": "string"
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},
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"id": {
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"description": "Unique identifier for the import operation.",
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"example": "101",
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"maxLength": 1000,
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"minLength": 1,
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"type": "string"
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},
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"percentComplete": {
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"description": "The progress made by the operation, as a percentage.",
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"example": 42.2,
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"format": "float",
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"maximum": 100.0,
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"minimum": 0.0,
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"type": "number"
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},
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"recordsImported": {
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"description": "The number of records successfully imported.",
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"example": 1000000,
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"format": "int64",
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"type": "integer"
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},
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"status": {
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"description": "The status of the operation.",
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"enum": [
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"Pending",
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"InProgress",
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"Failed",
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"Completed",
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"Cancelled"
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],
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"example": "Pending",
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"type": "string"
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},
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"uri": {
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"description": "The URI from where the data is imported.",
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"type": "string"
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}
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},
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"type": "object"
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},
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"IndexDescription": {
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"description": "The response for the `describe_index_stats` operation.",
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"example": {
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"dimension": 1024,
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"index_fullness": 0.4,
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"namespaces": {
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"": {
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"vectorCount": 50000
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},
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"example-namespace-2": {
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"vectorCount": 30000
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}
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},
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"totalVectorCount": 80000
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},
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"properties": {
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"dimension": {
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"description": "The dimension of the indexed vectors. Not specified if `sparse` index.",
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"example": 1024,
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"format": "int64",
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"type": "integer"
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},
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"indexFullness": {
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"description": "The fullness of the index, regardless of whether a metadata filter expression was passed. The granularity of this metric is 10%.\n\nServerless indexes scale automatically as needed, so index fullness is relevant only for pod-based indexes.\n\nThe index fullness result may be inaccurate during pod resizing; to get the status of a pod resizing process, use [`describe_index`](https://docs.pinecone.io/reference/api/2024-10/control-plane/describe_index).",
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"example": 0.4,
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"format": "float",
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"type": "number"
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},
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"metric": {
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"description": "The metric used to measure similarity.",
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"example": "cosine",
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"type": "string"
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},
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"namespaces": {
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"additionalProperties": {
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"$ref": "#/components/schemas/NamespaceSummary"
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},
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"description": "A mapping for each namespace in the index from the namespace name to a summary of its contents. If a metadata filter expression is present, the summary will reflect only vectors matching that expression.",
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"type": "object"
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},
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"totalVectorCount": {
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"description": "The total number of vectors in the index, regardless of whether a metadata filter expression was passed",
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"example": 80000,
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"format": "int64",
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"type": "integer"
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},
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"vectorType": {
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"description": "The type of vectors stored in the index.",
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"example": "dense",
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"type": "string"
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}
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},
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"type": "object"
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},
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"ListImportsResponse": {
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"description": "The response for the `list_imports` operation.",
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"properties": {
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"data": {
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"items": {
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"$ref": "#/components/schemas/ImportModel"
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},
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"type": "array"
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},
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"pagination": {
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"$ref": "#/components/schemas/Pagination"
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}
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},
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"type": "object"
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},
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"ListItem": {
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"properties": {
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"id": {
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"example": "document1#abb",
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"type": "string"
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}
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},
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"type": "object"
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},
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"ListNamespacesResponse": {
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"properties": {
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"namespaces": {
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"description": "The list of namespaces belonging to this index.",
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"items": {
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"$ref": "#/components/schemas/NamespaceDescription"
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},
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"type": "array"
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},
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"pagination": {
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"$ref": "#/components/schemas/Pagination"
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}
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},
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"type": "object"
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},
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"ListResponse": {
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"description": "The response for the `list` operation.",
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"properties": {
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"namespace": {
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"description": "The namespace of the vectors.",
|
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"example": "example-namespace",
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"type": "string"
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},
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"pagination": {
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"$ref": "#/components/schemas/Pagination"
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},
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"usage": {
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"$ref": "#/components/schemas/Usage"
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},
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"vectors": {
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"example": [
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{
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"id": "document1#abb"
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},
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{
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"id": "document1#abc"
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}
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],
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"items": {
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"$ref": "#/components/schemas/ListItem"
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},
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"title": "A list of ids",
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"type": "array"
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}
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},
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"type": "object"
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},
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"NamespaceDescription": {
|
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"description": "A description of a namespace, including the name and record count.",
|
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"properties": {
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"name": {
|
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"description": "The name of the namespace.",
|
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"example": "example-namespace",
|
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"type": "string"
|
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},
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"record_count": {
|
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"description": "The total amount of records within the namespace.",
|
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"example": 20000,
|
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"format": "int64",
|
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"type": "integer"
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}
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},
|
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"type": "object"
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},
|
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"NamespaceSummary": {
|
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"description": "A summary of the contents of a namespace.",
|
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"properties": {
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|
"vectorCount": {
|
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"description": "The number of vectors stored in this namespace. Note that updates to this field may lag behind updates to the underlying index and corresponding query results, etc.",
|
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"example": 50000,
|
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"format": "int64",
|
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"type": "integer"
|
|
}
|
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},
|
|
"type": "object"
|
|
},
|
|
"Pagination": {
|
|
"properties": {
|
|
"next": {
|
|
"example": "Tm90aGluZyB0byBzZWUgaGVyZQo=",
|
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"type": "string"
|
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}
|
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},
|
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"type": "object"
|
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},
|
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"QueryRequest": {
|
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"description": "The request for the `query` operation.",
|
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"properties": {
|
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"filter": {
|
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"description": "The filter to apply. You can use vector metadata to limit your search. See [Understanding metadata](https://docs.pinecone.io/guides/index-data/indexing-overview#metadata).",
|
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"example": {
|
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"genre": {
|
|
"$in": [
|
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"comedy",
|
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"documentary",
|
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"drama"
|
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]
|
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},
|
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"year": {
|
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"$eq": 2019
|
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}
|
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},
|
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"type": "object"
|
|
},
|
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"id": {
|
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"description": "The unique ID of the vector to be used as a query vector. Each request can contain either the `vector` or `id` parameter.",
|
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"example": "example-vector-1",
|
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"maxLength": 512,
|
|
"type": "string"
|
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},
|
|
"includeMetadata": {
|
|
"default": "false",
|
|
"description": "Indicates whether metadata is included in the response as well as the ids.",
|
|
"example": true,
|
|
"type": "boolean"
|
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},
|
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"includeValues": {
|
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"default": "false",
|
|
"description": "Indicates whether vector values are included in the response. For on-demand indexes, setting this to `true` may increase latency, especially with higher `topK` values, because vector values are retrieved from object storage. Unless you need vector values, set this to `false` for better performance.",
|
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"example": true,
|
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"type": "boolean"
|
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},
|
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"namespace": {
|
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"description": "The namespace to query.",
|
|
"example": "example-namespace",
|
|
"type": "string"
|
|
},
|
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"queries": {
|
|
"deprecated": true,
|
|
"description": "DEPRECATED. Use `vector` or `id` instead.",
|
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"items": {
|
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"$ref": "#/components/schemas/QueryVector"
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},
|
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"maxLength": 10,
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"minLength": 1,
|
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"type": "array"
|
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},
|
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"sparseVector": {
|
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"$ref": "#/components/schemas/SparseValues"
|
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},
|
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"topK": {
|
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"description": "The number of results to return for each query.",
|
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"example": 10,
|
|
"format": "int64",
|
|
"maximum": 10000.0,
|
|
"minimum": 1.0,
|
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"required": [
|
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"top_k"
|
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],
|
|
"type": "integer"
|
|
},
|
|
"vector": {
|
|
"description": "The query vector. This should be the same length as the dimension of the index being queried. Each `query` request can contain only one of the parameters `id` or `vector`.",
|
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"example": [
|
|
0.1,
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|
0.2,
|
|
0.3,
|
|
0.4,
|
|
0.5,
|
|
0.6,
|
|
0.7,
|
|
0.8
|
|
],
|
|
"items": {
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"maxLength": 20000,
|
|
"minLength": 1,
|
|
"type": "array"
|
|
}
|
|
},
|
|
"required": [
|
|
"topK"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"QueryResponse": {
|
|
"description": "The response for the `query` operation. These are the matches found for a particular query vector. The matches are ordered from most similar to least similar.",
|
|
"properties": {
|
|
"matches": {
|
|
"description": "The matches for the vectors.",
|
|
"items": {
|
|
"$ref": "#/components/schemas/ScoredVector"
|
|
},
|
|
"type": "array"
|
|
},
|
|
"namespace": {
|
|
"description": "The namespace for the vectors.",
|
|
"type": "string"
|
|
},
|
|
"results": {
|
|
"deprecated": true,
|
|
"description": "DEPRECATED. The results of each query. The order is the same as `QueryRequest.queries`.",
|
|
"items": {
|
|
"$ref": "#/components/schemas/SingleQueryResults"
|
|
},
|
|
"type": "array"
|
|
},
|
|
"usage": {
|
|
"$ref": "#/components/schemas/Usage"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"QueryVector": {
|
|
"deprecated": true,
|
|
"description": "A single query vector within a `QueryRequest`.",
|
|
"properties": {
|
|
"filter": {
|
|
"description": "An override for the metadata filter to apply. This replaces the request-level filter.",
|
|
"example": {
|
|
"genre": {
|
|
"$in": [
|
|
"comedy",
|
|
"documentary",
|
|
"drama"
|
|
]
|
|
},
|
|
"year": {
|
|
"$eq": 2019
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"namespace": {
|
|
"description": "An override the namespace to search.",
|
|
"example": "example-namespace",
|
|
"type": "string"
|
|
},
|
|
"sparseValues": {
|
|
"$ref": "#/components/schemas/SparseValues"
|
|
},
|
|
"topK": {
|
|
"description": "An override for the number of results to return for this query vector.",
|
|
"example": 10,
|
|
"format": "int64",
|
|
"maximum": 10000,
|
|
"minimum": 1,
|
|
"type": "integer"
|
|
},
|
|
"values": {
|
|
"description": "The query vector values. This should be the same length as the dimension of the index being queried.",
|
|
"example": [
|
|
0.1,
|
|
0.2,
|
|
0.3,
|
|
0.4,
|
|
0.5,
|
|
0.6,
|
|
0.7,
|
|
0.8
|
|
],
|
|
"items": {
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"maxLength": 20000,
|
|
"minLength": 1,
|
|
"required": [
|
|
"values"
|
|
],
|
|
"type": "array"
|
|
}
|
|
},
|
|
"required": [
|
|
"values"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"ScoredVector": {
|
|
"properties": {
|
|
"id": {
|
|
"description": "This is the vector's unique id.",
|
|
"example": "example-vector-1",
|
|
"maxLength": 512,
|
|
"minLength": 1,
|
|
"required": [
|
|
"id"
|
|
],
|
|
"type": "string"
|
|
},
|
|
"metadata": {
|
|
"description": "This is the metadata, if it is requested.",
|
|
"example": {
|
|
"genre": "documentary",
|
|
"year": 2019
|
|
},
|
|
"type": "object"
|
|
},
|
|
"score": {
|
|
"description": "This is a measure of similarity between this vector and the query vector. The higher the score, the more they are similar.",
|
|
"example": 0.08,
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"sparseValues": {
|
|
"$ref": "#/components/schemas/SparseValues"
|
|
},
|
|
"values": {
|
|
"description": "This is the vector data, if it is requested.",
|
|
"example": [
|
|
0.1,
|
|
0.2,
|
|
0.3,
|
|
0.4,
|
|
0.5,
|
|
0.6,
|
|
0.7,
|
|
0.8
|
|
],
|
|
"items": {
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"type": "array"
|
|
}
|
|
},
|
|
"required": [
|
|
"id"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"SearchRecordsRequest": {
|
|
"description": "A search request for records in a specific namespace.",
|
|
"example": {
|
|
"fields": [
|
|
"chunk_text"
|
|
],
|
|
"query": {
|
|
"inputs": {
|
|
"text": "your query text"
|
|
},
|
|
"top_k": 10
|
|
}
|
|
},
|
|
"properties": {
|
|
"fields": {
|
|
"description": "The fields to return in the search results. If not specified, the response will include all fields.",
|
|
"example": [
|
|
"chunk_text"
|
|
],
|
|
"items": {
|
|
"type": "string"
|
|
},
|
|
"maxLength": 100,
|
|
"type": "array"
|
|
},
|
|
"query": {
|
|
"description": ".",
|
|
"properties": {
|
|
"filter": {
|
|
"description": "The filter to apply. You can use vector metadata to limit your search. See [Understanding metadata](https://docs.pinecone.io/guides/index-data/indexing-overview#metadata).",
|
|
"type": "object"
|
|
},
|
|
"id": {
|
|
"description": "The unique ID of the vector to be used as a query vector.",
|
|
"example": "example-vector-1",
|
|
"maxLength": 512,
|
|
"type": "string"
|
|
},
|
|
"inputs": {
|
|
"$ref": "#/components/schemas/EmbedInputs"
|
|
},
|
|
"top_k": {
|
|
"description": "The number of similar records to return.",
|
|
"example": 10,
|
|
"format": "int32",
|
|
"type": "integer"
|
|
},
|
|
"vector": {
|
|
"$ref": "#/components/schemas/SearchRecordsVector"
|
|
}
|
|
},
|
|
"required": [
|
|
"top_k"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"rerank": {
|
|
"description": "Parameters for reranking the initial search results.",
|
|
"properties": {
|
|
"model": {
|
|
"description": "The name of the [reranking model](https://docs.pinecone.io/guides/search/rerank-results#reranking-models) to use.",
|
|
"example": "bge-reranker-v2-m3",
|
|
"type": "string"
|
|
},
|
|
"parameters": {
|
|
"additionalProperties": true,
|
|
"description": "Additional model-specific parameters. Refer to the [model guide](https://docs.pinecone.io/guides/search/rerank-results#reranking-models) for available model parameters.",
|
|
"example": {
|
|
"truncate": "END"
|
|
},
|
|
"type": "object"
|
|
},
|
|
"query": {
|
|
"description": "The query to rerank documents against. If a specific rerank query is specified, it overwrites the query input that was provided at the top level.",
|
|
"example": "What is the capital of France?",
|
|
"type": "string"
|
|
},
|
|
"rank_fields": {
|
|
"description": "The field(s) to consider for reranking. If not provided, the default is `[\"text\"]`.\n\nThe number of fields supported is [model-specific](https://docs.pinecone.io/guides/search/rerank-results#reranking-models).\n",
|
|
"example": [
|
|
"chunk_text",
|
|
"title"
|
|
],
|
|
"items": {
|
|
"type": "string"
|
|
},
|
|
"type": "array"
|
|
},
|
|
"top_n": {
|
|
"description": "The number of top results to return after reranking. Defaults to top_k.",
|
|
"example": 5,
|
|
"format": "int32",
|
|
"type": "integer"
|
|
}
|
|
},
|
|
"required": [
|
|
"model",
|
|
"rank_fields"
|
|
],
|
|
"type": "object"
|
|
}
|
|
},
|
|
"required": [
|
|
"query"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"SearchRecordsResponse": {
|
|
"description": "The records search response.",
|
|
"example": {
|
|
"result": {
|
|
"hits": [
|
|
{
|
|
"_id": "example-record-1",
|
|
"_score": 0.9281134605407715,
|
|
"fields": {
|
|
"data": "your example text"
|
|
}
|
|
}
|
|
]
|
|
},
|
|
"usage": {
|
|
"embed_total_tokens": 10,
|
|
"read_units": 5
|
|
}
|
|
},
|
|
"properties": {
|
|
"result": {
|
|
"properties": {
|
|
"hits": {
|
|
"description": "The hits for the search document request.",
|
|
"items": {
|
|
"$ref": "#/components/schemas/Hit"
|
|
},
|
|
"type": "array"
|
|
}
|
|
},
|
|
"required": [
|
|
"hits"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"usage": {
|
|
"$ref": "#/components/schemas/SearchUsage"
|
|
}
|
|
},
|
|
"required": [
|
|
"usage",
|
|
"result"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"SearchRecordsVector": {
|
|
"properties": {
|
|
"sparse_indices": {
|
|
"description": "The sparse embedding indices.",
|
|
"example": [
|
|
10,
|
|
3,
|
|
156
|
|
],
|
|
"items": {
|
|
"format": "int32",
|
|
"minimum": 0,
|
|
"type": "integer"
|
|
},
|
|
"type": "array"
|
|
},
|
|
"sparse_values": {
|
|
"description": "The sparse embedding values.",
|
|
"example": [
|
|
0.1,
|
|
0.2,
|
|
0.3
|
|
],
|
|
"items": {
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"type": "array"
|
|
},
|
|
"values": {
|
|
"$ref": "#/components/schemas/VectorValues"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"SearchUsage": {
|
|
"properties": {
|
|
"embed_total_tokens": {
|
|
"description": "The number of embedding tokens consumed by this operation.",
|
|
"example": 2,
|
|
"format": "int32",
|
|
"minimum": 0,
|
|
"type": "integer"
|
|
},
|
|
"read_units": {
|
|
"description": "The number of read units consumed by this operation.",
|
|
"example": 5,
|
|
"format": "int32",
|
|
"minimum": 0,
|
|
"type": "integer"
|
|
},
|
|
"rerank_units": {
|
|
"description": "The number of rerank units consumed by this operation.",
|
|
"example": 1,
|
|
"format": "int32",
|
|
"minimum": 0,
|
|
"type": "integer"
|
|
}
|
|
},
|
|
"required": [
|
|
"read_units"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"SearchVector": {
|
|
"properties": {
|
|
"values": {
|
|
"$ref": "#/components/schemas/VectorValues"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"SingleQueryResults": {
|
|
"properties": {
|
|
"matches": {
|
|
"description": "The matches for the vectors.",
|
|
"items": {
|
|
"$ref": "#/components/schemas/ScoredVector"
|
|
},
|
|
"type": "array"
|
|
},
|
|
"namespace": {
|
|
"description": "The namespace for the vectors.",
|
|
"example": "example-namespace",
|
|
"type": "string"
|
|
}
|
|
},
|
|
"title": "The query results for a single `QueryVector`",
|
|
"type": "object"
|
|
},
|
|
"SparseValues": {
|
|
"description": "Vector sparse data. Represented as a list of indices and a list of corresponded values, which must be with the same length.",
|
|
"properties": {
|
|
"indices": {
|
|
"description": "The indices of the sparse data.",
|
|
"example": [
|
|
1,
|
|
312,
|
|
822,
|
|
14,
|
|
980
|
|
],
|
|
"items": {
|
|
"format": "int64",
|
|
"type": "integer"
|
|
},
|
|
"maxLength": 1000,
|
|
"minLength": 1,
|
|
"required": [
|
|
"indices"
|
|
],
|
|
"type": "array"
|
|
},
|
|
"values": {
|
|
"description": "The corresponding values of the sparse data, which must be with the same length as the indices.",
|
|
"example": [
|
|
0.1,
|
|
0.2,
|
|
0.3,
|
|
0.4,
|
|
0.5
|
|
],
|
|
"items": {
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"maxLength": 1000,
|
|
"minLength": 1,
|
|
"required": [
|
|
"values"
|
|
],
|
|
"type": "array"
|
|
}
|
|
},
|
|
"required": [
|
|
"indices",
|
|
"values"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"StartImportRequest": {
|
|
"description": "The request for the `start_import` operation.",
|
|
"properties": {
|
|
"errorMode": {
|
|
"$ref": "#/components/schemas/ImportErrorMode"
|
|
},
|
|
"integrationId": {
|
|
"description": "The id of the [storage integration](https://docs.pinecone.io/guides/operations/integrations/manage-storage-integrations) that should be used to access the data.",
|
|
"maxLength": 1000,
|
|
"type": "string"
|
|
},
|
|
"uri": {
|
|
"description": "The URI of the bucket (or container) and import directory containing the namespaces and Parquet files you want to import. For example, `s3://BUCKET_NAME/IMPORT_DIR` for Amazon S3, `gs://BUCKET_NAME/IMPORT_DIR` for Google Cloud Storage, or `https://STORAGE_ACCOUNT.blob.core.windows.net/CONTAINER_NAME/IMPORT_DIR` for Azure Blob Storage. For more information, see [Import records](https://docs.pinecone.io/guides/index-data/import-data#prepare-your-data).",
|
|
"maxLength": 1500,
|
|
"minLength": 1,
|
|
"type": "string"
|
|
}
|
|
},
|
|
"required": [
|
|
"uri"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"StartImportResponse": {
|
|
"description": "The response for the `start_import` operation.",
|
|
"properties": {
|
|
"id": {
|
|
"description": "Unique identifier for the import operation.",
|
|
"example": "101",
|
|
"maxLength": 1000,
|
|
"minLength": 1,
|
|
"type": "string"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"UpdateRequest": {
|
|
"description": "The request for the `update` operation.",
|
|
"properties": {
|
|
"id": {
|
|
"description": "Vector's unique id.",
|
|
"example": "example-vector-1",
|
|
"maxLength": 512,
|
|
"minLength": 1,
|
|
"required": [
|
|
"id"
|
|
],
|
|
"type": "string"
|
|
},
|
|
"namespace": {
|
|
"description": "The namespace containing the vector to update.",
|
|
"example": "example-namespace",
|
|
"type": "string"
|
|
},
|
|
"setMetadata": {
|
|
"description": "Metadata to set for the vector.",
|
|
"example": {
|
|
"genre": "documentary",
|
|
"year": 2019
|
|
},
|
|
"type": "object"
|
|
},
|
|
"sparseValues": {
|
|
"$ref": "#/components/schemas/SparseValues"
|
|
},
|
|
"values": {
|
|
"description": "Vector data.",
|
|
"example": [
|
|
0.1,
|
|
0.2,
|
|
0.3,
|
|
0.4,
|
|
0.5,
|
|
0.6,
|
|
0.7,
|
|
0.8
|
|
],
|
|
"items": {
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"maxLength": 20000,
|
|
"minLength": 1,
|
|
"type": "array"
|
|
}
|
|
},
|
|
"required": [
|
|
"id"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"UpdateResponse": {
|
|
"description": "The response for the `update` operation.",
|
|
"type": "object"
|
|
},
|
|
"UpsertRecord": {
|
|
"description": "The request for the `upsert` operation.",
|
|
"example": {
|
|
"_id": "example-record-1"
|
|
},
|
|
"properties": {
|
|
"_id": {
|
|
"description": "The unique ID of the record to upsert. Note that `id` can be used as an alias for `_id`.",
|
|
"type": "string"
|
|
}
|
|
},
|
|
"required": [
|
|
"_id"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"UpsertRequest": {
|
|
"description": "The request for the `upsert` operation.",
|
|
"properties": {
|
|
"namespace": {
|
|
"description": "The namespace where you upsert vectors.",
|
|
"example": "example-namespace",
|
|
"type": "string"
|
|
},
|
|
"vectors": {
|
|
"description": "An array containing the vectors to upsert. Recommended batch limit is up to 1000 vectors.",
|
|
"items": {
|
|
"$ref": "#/components/schemas/Vector"
|
|
},
|
|
"maxLength": 1000,
|
|
"minLength": 1,
|
|
"type": "array"
|
|
}
|
|
},
|
|
"required": [
|
|
"vectors"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"UpsertResponse": {
|
|
"description": "The response for the `upsert` operation.",
|
|
"properties": {
|
|
"upsertedCount": {
|
|
"description": "The number of vectors upserted.",
|
|
"example": 2,
|
|
"format": "int64",
|
|
"type": "integer"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"Usage": {
|
|
"properties": {
|
|
"readUnits": {
|
|
"description": "The number of read units consumed by this operation.",
|
|
"example": 5,
|
|
"format": "int64",
|
|
"type": "integer"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"Vector": {
|
|
"properties": {
|
|
"id": {
|
|
"description": "This is the vector's unique id.",
|
|
"example": "example-vector-1",
|
|
"maxLength": 512,
|
|
"minLength": 1,
|
|
"required": [
|
|
"id"
|
|
],
|
|
"type": "string"
|
|
},
|
|
"metadata": {
|
|
"description": "This is the metadata included in the request.",
|
|
"example": {
|
|
"genre": "documentary",
|
|
"year": 2019
|
|
},
|
|
"type": "object"
|
|
},
|
|
"sparseValues": {
|
|
"$ref": "#/components/schemas/SparseValues"
|
|
},
|
|
"values": {
|
|
"description": "This is the vector data included in the request.",
|
|
"example": [
|
|
0.1,
|
|
0.2,
|
|
0.3,
|
|
0.4,
|
|
0.5,
|
|
0.6,
|
|
0.7,
|
|
0.8
|
|
],
|
|
"items": {
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"maxLength": 20000,
|
|
"minLength": 1,
|
|
"required": [
|
|
"values"
|
|
],
|
|
"type": "array"
|
|
}
|
|
},
|
|
"required": [
|
|
"id"
|
|
],
|
|
"type": "object"
|
|
},
|
|
"VectorValues": {
|
|
"description": "This is the vector data included in the request.",
|
|
"items": {
|
|
"format": "float",
|
|
"type": "number"
|
|
},
|
|
"maxLength": 20000,
|
|
"minLength": 1,
|
|
"type": "array"
|
|
},
|
|
"protobufAny": {
|
|
"properties": {
|
|
"typeUrl": {
|
|
"type": "string"
|
|
},
|
|
"value": {
|
|
"format": "byte",
|
|
"type": "string"
|
|
}
|
|
},
|
|
"type": "object"
|
|
},
|
|
"protobufNullValue": {
|
|
"default": "NULL_VALUE",
|
|
"description": "`NullValue` is a singleton enumeration to represent the null value for the `Value` type union.\nThe JSON representation for `NullValue` is JSON `null`.",
|
|
"enum": [
|
|
"NULL_VALUE"
|
|
],
|
|
"type": "string"
|
|
},
|
|
"rpcStatus": {
|
|
"properties": {
|
|
"code": {
|
|
"format": "int32",
|
|
"type": "integer"
|
|
},
|
|
"details": {
|
|
"items": {
|
|
"$ref": "#/components/schemas/protobufAny"
|
|
},
|
|
"type": "array"
|
|
},
|
|
"message": {
|
|
"type": "string"
|
|
}
|
|
},
|
|
"type": "object"
|
|
}
|
|
},
|
|
"securitySchemes": {
|
|
"ApiKeyAuth": {
|
|
"description": "An API Key is required to call Pinecone APIs. Get yours from the [console](https://app.pinecone.io/).",
|
|
"in": "header",
|
|
"name": "Api-Key",
|
|
"type": "apiKey"
|
|
}
|
|
}
|
|
},
|
|
"externalDocs": {
|
|
"description": "More Pinecone.io API docs",
|
|
"url": "https://docs.pinecone.io/introduction"
|
|
},
|
|
"info": {
|
|
"contact": {
|
|
"email": "support@pinecone.io",
|
|
"name": "Pinecone Support",
|
|
"url": "https://support.pinecone.io"
|
|
},
|
|
"description": "Pinecone is a vector database that makes it easy to search and retrieve billions of high-dimensional vectors.",
|
|
"license": {
|
|
"name": "Apache 2.0",
|
|
"url": "https://www.apache.org/licenses/LICENSE-2.0"
|
|
},
|
|
"title": "Pinecone Data Plane API",
|
|
"version": "2025-04"
|
|
},
|
|
"openapi": "3.0.3",
|
|
"paths": {
|
|
"/bulk/imports": {
|
|
"get": {
|
|
"description": "List all recent and ongoing import operations.\n\nBy default, `list_imports` returns up to 100 imports per page. If the `limit` parameter is set, `list` returns up to that number of imports instead. Whenever there are additional IDs to return, the response also includes a `pagination_token` that you can use to get the next batch of imports. When the response does not include a `pagination_token`, there are no more imports to return.\n\nFor guidance and examples, see [Import data](https://docs.pinecone.io/guides/index-data/import-data).",
|
|
"operationId": "listBulkImports",
|
|
"parameters": [
|
|
{
|
|
"description": "Max number of operations to return per page.",
|
|
"example": 10,
|
|
"in": "query",
|
|
"name": "limit",
|
|
"schema": {
|
|
"default": "100",
|
|
"format": "int32",
|
|
"maximum": 100,
|
|
"minimum": 1,
|
|
"type": "integer"
|
|
},
|
|
"style": "form"
|
|
},
|
|
{
|
|
"description": "Pagination token to continue a previous listing operation.",
|
|
"in": "query",
|
|
"name": "paginationToken",
|
|
"schema": {
|
|
"type": "string"
|
|
},
|
|
"style": "form"
|
|
}
|
|
],
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/ListImportsResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "A list of import operations"
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "List imports",
|
|
"tags": [
|
|
"Bulk Operations"
|
|
]
|
|
},
|
|
"post": {
|
|
"description": "Start an asynchronous import of vectors from object storage into an index.\n\nFor guidance and examples, see [Import data](https://docs.pinecone.io/guides/index-data/import-data).",
|
|
"operationId": "startBulkImport",
|
|
"requestBody": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/StartImportRequest"
|
|
}
|
|
}
|
|
},
|
|
"required": true
|
|
},
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/StartImportResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "Successful import operation"
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Start import",
|
|
"tags": [
|
|
"Bulk Operations"
|
|
]
|
|
}
|
|
},
|
|
"/bulk/imports/{id}": {
|
|
"delete": {
|
|
"description": "Cancel an import operation if it is not yet finished. It has no effect if the operation is already finished.\n\nFor guidance and examples, see [Import data](https://docs.pinecone.io/guides/index-data/import-data).",
|
|
"operationId": "cancelBulkImport",
|
|
"parameters": [
|
|
{
|
|
"description": "Unique identifier for the import operation.",
|
|
"example": "101",
|
|
"in": "path",
|
|
"name": "id",
|
|
"required": true,
|
|
"schema": {
|
|
"maxLength": 1000,
|
|
"minLength": 1,
|
|
"type": "string"
|
|
},
|
|
"style": "simple"
|
|
}
|
|
],
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/CancelImportResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "Operation cancelled successfully"
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Cancel an import",
|
|
"tags": [
|
|
"Bulk Operations"
|
|
]
|
|
},
|
|
"get": {
|
|
"description": "Return details of a specific import operation.\n\nFor guidance and examples, see [Import data](https://docs.pinecone.io/guides/index-data/import-data).",
|
|
"operationId": "describeBulkImport",
|
|
"parameters": [
|
|
{
|
|
"description": "Unique identifier for the import operation.",
|
|
"example": "101",
|
|
"in": "path",
|
|
"name": "id",
|
|
"required": true,
|
|
"schema": {
|
|
"maxLength": 1000,
|
|
"minLength": 1,
|
|
"type": "string"
|
|
},
|
|
"style": "simple"
|
|
}
|
|
],
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/ImportModel"
|
|
}
|
|
}
|
|
},
|
|
"description": "Details of the import operation."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Describe an import",
|
|
"tags": [
|
|
"Bulk Operations"
|
|
]
|
|
}
|
|
},
|
|
"/describe_index_stats": {
|
|
"post": {
|
|
"description": "Return statistics about the contents of an index, including the vector count per namespace, the number of dimensions, and the index fullness.\n\nServerless indexes scale automatically as needed, so index fullness is relevant only for pod-based indexes.",
|
|
"operationId": "describeIndexStats",
|
|
"requestBody": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/DescribeIndexStatsRequest"
|
|
}
|
|
}
|
|
},
|
|
"required": true
|
|
},
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/IndexDescription"
|
|
}
|
|
}
|
|
},
|
|
"description": "A successful response."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Get index stats",
|
|
"tags": [
|
|
"Vector Operations"
|
|
]
|
|
}
|
|
},
|
|
"/namespaces": {
|
|
"get": {
|
|
"description": "List all namespaces in a serverless index.\n\nUp to 100 namespaces are returned at a time by default, in sorted order (bitwise \u201cC\u201d collation). If the `limit` parameter is set, up to that number of namespaces are returned instead. Whenever there are additional namespaces to return, the response also includes a `pagination_token` that you can use to get the next batch of namespaces. When the response does not include a `pagination_token`, there are no more namespaces to return.\n\nFor guidance and examples, see [Manage namespaces](https://docs.pinecone.io/guides/manage-data/manage-namespaces).\n\n**Note:** This operation is not supported for pod-based indexes.",
|
|
"operationId": "listNamespacesOperation",
|
|
"parameters": [
|
|
{
|
|
"description": "Max number namespaces to return per page.",
|
|
"example": 10,
|
|
"in": "query",
|
|
"name": "limit",
|
|
"schema": {
|
|
"format": "int32",
|
|
"type": "integer"
|
|
},
|
|
"style": "form"
|
|
},
|
|
{
|
|
"description": "Pagination token to continue a previous listing operation.",
|
|
"in": "query",
|
|
"name": "paginationToken",
|
|
"schema": {
|
|
"type": "string"
|
|
},
|
|
"style": "form"
|
|
}
|
|
],
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/ListNamespacesResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "A successful response"
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "List namespaces",
|
|
"tags": [
|
|
"Namespace Operations"
|
|
]
|
|
}
|
|
},
|
|
"/namespaces/{namespace}": {
|
|
"delete": {
|
|
"description": "Delete a namespace from a serverless index. Deleting a namespace is irreversible; all data in the namespace is permanently deleted.\n\nFor guidance and examples, see [Manage namespaces](https://docs.pinecone.io/guides/manage-data/manage-namespaces).\n\n**Note:** This operation is not supported for pod-based indexes.",
|
|
"operationId": "deleteNamespace",
|
|
"parameters": [
|
|
{
|
|
"description": "The namespace to delete",
|
|
"in": "path",
|
|
"name": "namespace",
|
|
"required": true,
|
|
"schema": {
|
|
"type": "string"
|
|
},
|
|
"style": "simple"
|
|
}
|
|
],
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/DeleteResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "A successful response"
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Delete a namespace",
|
|
"tags": [
|
|
"Namespace Operations"
|
|
]
|
|
},
|
|
"get": {
|
|
"description": "Describe a namespace in a serverless index, including the total number of vectors in the namespace.\n\nFor guidance and examples, see [Manage namespaces](https://docs.pinecone.io/guides/manage-data/manage-namespaces).\n\n**Note:** This operation is not supported for pod-based indexes.",
|
|
"operationId": "describeNamespace",
|
|
"parameters": [
|
|
{
|
|
"description": "The namespace to describe",
|
|
"in": "path",
|
|
"name": "namespace",
|
|
"required": true,
|
|
"schema": {
|
|
"type": "string"
|
|
},
|
|
"style": "simple"
|
|
}
|
|
],
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/NamespaceDescription"
|
|
}
|
|
}
|
|
},
|
|
"description": "A description of a namespace."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Describe a namespace",
|
|
"tags": [
|
|
"Namespace Operations"
|
|
]
|
|
}
|
|
},
|
|
"/query": {
|
|
"post": {
|
|
"description": "Search a namespace using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores.\n\nFor guidance, examples, and limits, see [Search](https://docs.pinecone.io/guides/search/search-overview).",
|
|
"operationId": "queryVectors",
|
|
"requestBody": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/QueryRequest"
|
|
}
|
|
}
|
|
},
|
|
"required": true
|
|
},
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/QueryResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "A successful response."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Search with a vector",
|
|
"tags": [
|
|
"Vector Operations"
|
|
]
|
|
}
|
|
},
|
|
"/records/namespaces/{namespace}/search": {
|
|
"post": {
|
|
"description": "Search a namespace with a query text, query vector, or record ID and return the most similar records, along with their similarity scores. Optionally, rerank the initial results based on their relevance to the query. \n\nSearching with text is supported only for [indexes with integrated embedding](https://docs.pinecone.io/guides/indexes/create-an-index#integrated-embedding). Searching with a query vector or record ID is supported for all indexes. \n\nFor guidance, examples, and limits, see [Search](https://docs.pinecone.io/guides/search/search-overview).",
|
|
"operationId": "searchRecordsNamespace",
|
|
"parameters": [
|
|
{
|
|
"description": "The namespace to search.",
|
|
"in": "path",
|
|
"name": "namespace",
|
|
"required": true,
|
|
"schema": {
|
|
"type": "string"
|
|
},
|
|
"style": "simple"
|
|
}
|
|
],
|
|
"requestBody": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/SearchRecordsRequest"
|
|
}
|
|
}
|
|
},
|
|
"required": true
|
|
},
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/SearchRecordsResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "A successful search namespace response."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Search with text",
|
|
"tags": [
|
|
"Vector Operations"
|
|
]
|
|
}
|
|
},
|
|
"/records/namespaces/{namespace}/upsert": {
|
|
"post": {
|
|
"description": "Upsert text into a namespace. Pinecone converts the text to vectors automatically using the hosted embedding model associated with the index.\n\nUpserting text is supported only for [indexes with integrated embedding](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models).\n\nFor guidance, examples, and limits, see [Upsert data](https://docs.pinecone.io/guides/index-data/upsert-data).",
|
|
"operationId": "upsertRecordsNamespace",
|
|
"parameters": [
|
|
{
|
|
"description": "The namespace to upsert records into.",
|
|
"in": "path",
|
|
"name": "namespace",
|
|
"required": true,
|
|
"schema": {
|
|
"type": "string"
|
|
},
|
|
"style": "simple"
|
|
}
|
|
],
|
|
"requestBody": {
|
|
"content": {
|
|
"application/x-ndjson": {
|
|
"schema": {
|
|
"items": {
|
|
"$ref": "#/components/schemas/UpsertRecord"
|
|
},
|
|
"type": "array"
|
|
}
|
|
}
|
|
},
|
|
"description": "Each record in the request body must include an `_id` field and a field that matches your index's `field_map` configuration (such as `chunk_text` or `data`). All other fields are stored as metadata.\n",
|
|
"required": true
|
|
},
|
|
"responses": {
|
|
"201": {
|
|
"description": "A successful response."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Upsert text",
|
|
"tags": [
|
|
"Vector Operations"
|
|
]
|
|
}
|
|
},
|
|
"/vectors/delete": {
|
|
"post": {
|
|
"description": "Delete vectors by id from a single namespace.\n\nFor guidance and examples, see [Delete data](https://docs.pinecone.io/guides/manage-data/delete-data).",
|
|
"operationId": "deleteVectors",
|
|
"requestBody": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/DeleteRequest"
|
|
}
|
|
}
|
|
},
|
|
"required": true
|
|
},
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/DeleteResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "A successful response."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Delete vectors",
|
|
"tags": [
|
|
"Vector Operations"
|
|
]
|
|
}
|
|
},
|
|
"/vectors/fetch": {
|
|
"get": {
|
|
"description": "Look up and return vectors by ID from a single namespace. The returned vectors include the vector data and/or metadata.\n\nFor on-demand indexes, since vector values are retrieved from object storage, fetch operations may have increased latency. If you only need metadata or IDs, consider using the query operation with `includeValues` set to `false` instead.\n\nFor guidance and examples, see [Fetch data](https://docs.pinecone.io/guides/manage-data/fetch-data).",
|
|
"operationId": "fetchVectors",
|
|
"parameters": [
|
|
{
|
|
"description": "The vector IDs to fetch. Does not accept values containing spaces.",
|
|
"explode": true,
|
|
"in": "query",
|
|
"name": "ids",
|
|
"required": true,
|
|
"schema": {
|
|
"items": {
|
|
"type": "string"
|
|
},
|
|
"type": "array"
|
|
},
|
|
"style": "form"
|
|
},
|
|
{
|
|
"in": "query",
|
|
"name": "namespace",
|
|
"schema": {
|
|
"type": "string"
|
|
},
|
|
"style": "form"
|
|
}
|
|
],
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/FetchResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "A successful response."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Fetch vectors",
|
|
"tags": [
|
|
"Vector Operations"
|
|
]
|
|
}
|
|
},
|
|
"/vectors/list": {
|
|
"get": {
|
|
"description": "List the IDs of vectors in a single namespace of a serverless index. An optional prefix can be passed to limit the results to IDs with a common prefix.\n\nReturns up to 100 IDs at a time by default in sorted order (bitwise \"C\" collation). If the `limit` parameter is set, `list` returns up to that number of IDs instead. Whenever there are additional IDs to return, the response also includes a `pagination_token` that you can use to get the next batch of IDs. When the response does not include a `pagination_token`, there are no more IDs to return.\n\nFor guidance and examples, see [List record IDs](https://docs.pinecone.io/guides/manage-data/list-record-ids).\n\n**Note:** `list` is supported only for serverless indexes.",
|
|
"operationId": "listVectors",
|
|
"parameters": [
|
|
{
|
|
"description": "The vector IDs to fetch. Does not accept values containing spaces.",
|
|
"in": "query",
|
|
"name": "prefix",
|
|
"schema": {
|
|
"type": "string"
|
|
},
|
|
"style": "form"
|
|
},
|
|
{
|
|
"description": "Max number of IDs to return per page.",
|
|
"in": "query",
|
|
"name": "limit",
|
|
"schema": {
|
|
"default": "100",
|
|
"format": "int64",
|
|
"type": "integer"
|
|
},
|
|
"style": "form"
|
|
},
|
|
{
|
|
"description": "Pagination token to continue a previous listing operation.",
|
|
"in": "query",
|
|
"name": "paginationToken",
|
|
"schema": {
|
|
"type": "string"
|
|
},
|
|
"style": "form"
|
|
},
|
|
{
|
|
"in": "query",
|
|
"name": "namespace",
|
|
"schema": {
|
|
"type": "string"
|
|
},
|
|
"style": "form"
|
|
}
|
|
],
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/ListResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "A successful response."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "List vector IDs",
|
|
"tags": [
|
|
"Vector Operations"
|
|
]
|
|
}
|
|
},
|
|
"/vectors/update": {
|
|
"post": {
|
|
"description": "Update a vector in a namespace. If a value is included, it will overwrite the previous value. If a `set_metadata` is included, the values of the fields specified in it will be added or overwrite the previous value.\n\nFor guidance and examples, see [Update data](https://docs.pinecone.io/guides/manage-data/update-data).",
|
|
"operationId": "updateVector",
|
|
"requestBody": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/UpdateRequest"
|
|
}
|
|
}
|
|
},
|
|
"required": true
|
|
},
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/UpdateResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "A successful response."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Update a vector",
|
|
"tags": [
|
|
"Vector Operations"
|
|
]
|
|
}
|
|
},
|
|
"/vectors/upsert": {
|
|
"post": {
|
|
"description": "Upsert vectors into a namespace. If a new value is upserted for an existing vector ID, it will overwrite the previous value.\n\nFor guidance, examples, and limits, see [Upsert data](https://docs.pinecone.io/guides/index-data/upsert-data).",
|
|
"operationId": "upsertVectors",
|
|
"requestBody": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/UpsertRequest"
|
|
}
|
|
}
|
|
},
|
|
"required": true
|
|
},
|
|
"responses": {
|
|
"200": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/UpsertResponse"
|
|
}
|
|
}
|
|
},
|
|
"description": "A successful response."
|
|
},
|
|
"400": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "Bad request. The request body included invalid request parameters."
|
|
},
|
|
"4XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
},
|
|
"5XX": {
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/rpcStatus"
|
|
}
|
|
}
|
|
},
|
|
"description": "An unexpected error response."
|
|
}
|
|
},
|
|
"summary": "Upsert vectors",
|
|
"tags": [
|
|
"Vector Operations"
|
|
]
|
|
}
|
|
}
|
|
},
|
|
"security": [
|
|
{
|
|
"ApiKeyAuth": []
|
|
}
|
|
],
|
|
"servers": [
|
|
{
|
|
"url": "https://{index_host}",
|
|
"variables": {
|
|
"index_host": {
|
|
"default": "unknown",
|
|
"description": "host of the index"
|
|
}
|
|
}
|
|
}
|
|
],
|
|
"tags": [
|
|
{
|
|
"name": "Vector Operations"
|
|
},
|
|
{
|
|
"name": "Bulk Operations"
|
|
},
|
|
{
|
|
"name": "Namespace Operations"
|
|
}
|
|
]
|
|
}
|