--- title: "CreateVectorStore" method: POST path: "/v1/namespaces/{tenant_meta.namespace}/vector-stores" tags: ["VectorStoreService"] --- # CreateVectorStore `POST /v1/namespaces/{tenant_meta.namespace}/vector-stores` ## Request - Base URL: `https://api.endorlabs.com` - URL: `https://api.endorlabs.com/v1/namespaces/{tenant_meta.namespace}/vector-stores` - Auth: none declared Creates an VectorStore. ## Path parameters - `tenant_meta.namespace` string, required ## Request body - VectorStoreServiceCreateVectorStoreBody: Represents a vector store in the system. The vector store will create all the infrastructure for semantic searches. - `meta` V1Meta, required: Common fields for all Endor Labs resources. - `annotations` object: Annotations can be used to attach metadata to a resource message. Annotation values can be small or large, structured or unstructured, and may include characters not permitted by labels. The keys may contain alphanumerics, underscores (_), dots (.) and dashes (-). The values of an annotation must be 16384 bytes or smaller. - `create_time` string, date-time: Time the resource was created. Format: 2017-01-15T01:30:15.01Z RFC 3339: https://www.ietf.org/rfc/rfc3339.txt. - `created_by` string: Name and authentication source of the user who created the object, for example, ewok@endor.ai@google@api-key. - `description` string: Resource description. Must be less than 1024 bytes. - `index_data` V1IndexData: IndexData is used to index the resource for search. It's an internal object. - `data` string[] - `search_score` number, float: search_score is the score of the resource for search. Internal use only. - `tenant` string - `will_be_deleted_at` string, date-time: Time that the resource will be deleted. - `kind` string: Resource kind, for example, HelloResponse. Auto-generated using the protobuf message proto.MessageName().Name(). - `name` string, required: Resource name. Must be 63 characters or less. - `parent_kind` string: Parent object resource kind, for example, Project. - `parent_uuid` string: Parent object UUID. - `references` object: Map of objects referenced in a query API. - `tags` string[]: List of tags attached to the resource. Tags can be used to select objects and to find collections of objects that satisfy certain conditions. A tag must be 255 characters or less. - `update_time` string, date-time: Time the resource was last updated. Note: Updated on all create/patch/delete operations. Format: 2017-01-15T01:30:15.01Z RFC 3339: https://www.ietf.org/rfc/rfc3339.txt. - `updated_by` string: Name and authentication source of the last user who updated the object, for example, vulnerabilityingestor@endor.ai@x509. - `upsert_time` string, date-time: Time the resource was last upserted. Note: create_time is only set the first time the resource is created. upsert_time is set every time the resource is upseted. Format: 2017-01-15T01:30:15.01Z RFC 3339: https://www.ietf.org/rfc/rfc3339.txt. - `version` string: Message version. - `propagate` boolean: Vector stores can be propagated and accessed in child namespaces. - `spec` V1VectorStoreSpec - `apply_uniqueness_index_changes` boolean: apply_uniqueness_index_changes explicitly authorizes migrating uniqueness indexes when the requested uniqueness_fields differ from the currently provisioned index. This must be true any time changes are made to the uniqueness_fields. - `dimensions` integer: Dimensions is the number of dimensions to be used. - `embedding_model` 'EMBEDDING_MODEL_UNSPECIFIED' | 'EMBEDDING_MODEL_OPENAI_TEXT_EMBEDDING_ADA_002' | 'EMBEDDING_MODEL_OPENAI_TEXT_EMBEDDING_3_SMALL' | 'EMBEDDING_MODEL_GOOGLE_TEXT_EMBEDDING_LARGE' | 'EMBEDDING_MODEL_OPENAI_TEXT_EMBEDDING_3_LARGE', required: EmbeddingModel is the model of the embedding provider. - `embedding_provider` 'EMBEDDING_PROVIDER_UNSPECIFIED' | 'EMBEDDING_PROVIDER_OPENAI' | 'EMBEDDING_PROVIDER_GOOGLE', required: EmbeddingProvider is the provider of the embeddings. - `search_index_fields` string: search_index_fields lists metadata fields that queries filter on beyond the uniqueness fields. A non-unique index is ensured on each field when the store is created or next opened, so equality filters on it can avoid a full scan. The declared set is authoritative: adding a field creates its index and removing a field drops it, both on the next open. - `uniqueness_fields` string: uniqueness_fields specifies which metadata fields are used for document uniqueness. When provided, a unique index is created on these fields at store creation time. All add/update/delete operations must include these fields in document metadata. - `tenant_meta` object: VectorStores are associated with a tenant or are global. - `uuid` string: The UUID of an VectorStore. ## Response `200` A successful response. - V1VectorStore: Represents a vector store in the system. The vector store will create all the infrastructure for semantic searches. - `meta` V1Meta, required: Common fields for all Endor Labs resources. - `annotations` object: Annotations can be used to attach metadata to a resource message. Annotation values can be small or large, structured or unstructured, and may include characters not permitted by labels. The keys may contain alphanumerics, underscores (_), dots (.) and dashes (-). The values of an annotation must be 16384 bytes or smaller. - `create_time` string, date-time: Time the resource was created. Format: 2017-01-15T01:30:15.01Z RFC 3339: https://www.ietf.org/rfc/rfc3339.txt. - `created_by` string: Name and authentication source of the user who created the object, for example, ewok@endor.ai@google@api-key. - `description` string: Resource description. Must be less than 1024 bytes. - `index_data` V1IndexData: IndexData is used to index the resource for search. It's an internal object. - `data` string[] - `search_score` number, float: search_score is the score of the resource for search. Internal use only. - `tenant` string - `will_be_deleted_at` string, date-time: Time that the resource will be deleted. - `kind` string: Resource kind, for example, HelloResponse. Auto-generated using the protobuf message proto.MessageName().Name(). - `name` string, required: Resource name. Must be 63 characters or less. - `parent_kind` string: Parent object resource kind, for example, Project. - `parent_uuid` string: Parent object UUID. - `references` object: Map of objects referenced in a query API. - `tags` string[]: List of tags attached to the resource. Tags can be used to select objects and to find collections of objects that satisfy certain conditions. A tag must be 255 characters or less. - `update_time` string, date-time: Time the resource was last updated. Note: Updated on all create/patch/delete operations. Format: 2017-01-15T01:30:15.01Z RFC 3339: https://www.ietf.org/rfc/rfc3339.txt. - `updated_by` string: Name and authentication source of the last user who updated the object, for example, vulnerabilityingestor@endor.ai@x509. - `upsert_time` string, date-time: Time the resource was last upserted. Note: create_time is only set the first time the resource is created. upsert_time is set every time the resource is upseted. Format: 2017-01-15T01:30:15.01Z RFC 3339: https://www.ietf.org/rfc/rfc3339.txt. - `version` string: Message version. - `propagate` boolean: Vector stores can be propagated and accessed in child namespaces. - `spec` V1VectorStoreSpec - `apply_uniqueness_index_changes` boolean: apply_uniqueness_index_changes explicitly authorizes migrating uniqueness indexes when the requested uniqueness_fields differ from the currently provisioned index. This must be true any time changes are made to the uniqueness_fields. - `dimensions` integer: Dimensions is the number of dimensions to be used. - `embedding_model` 'EMBEDDING_MODEL_UNSPECIFIED' | 'EMBEDDING_MODEL_OPENAI_TEXT_EMBEDDING_ADA_002' | 'EMBEDDING_MODEL_OPENAI_TEXT_EMBEDDING_3_SMALL' | 'EMBEDDING_MODEL_GOOGLE_TEXT_EMBEDDING_LARGE' | 'EMBEDDING_MODEL_OPENAI_TEXT_EMBEDDING_3_LARGE', required: EmbeddingModel is the model of the embedding provider. - `embedding_provider` 'EMBEDDING_PROVIDER_UNSPECIFIED' | 'EMBEDDING_PROVIDER_OPENAI' | 'EMBEDDING_PROVIDER_GOOGLE', required: EmbeddingProvider is the provider of the embeddings. - `search_index_fields` string: search_index_fields lists metadata fields that queries filter on beyond the uniqueness fields. A non-unique index is ensured on each field when the store is created or next opened, so equality filters on it can avoid a full scan. The declared set is authoritative: adding a field creates its index and removing a field drops it, both on the next open. - `uniqueness_fields` string: uniqueness_fields specifies which metadata fields are used for document uniqueness. When provided, a unique index is created on these fields at store creation time. All add/update/delete operations must include these fields in document metadata. - `tenant_meta` V1TenantMeta: Tenant related data for the tenant containing the resource. - `namespace` string, required: Namespaces are a way to organize organizational units into virtual groupings of resources. Namespaces must be a fully qualified name, for example, the child namespace of namespace "endor.prod" called "app" is called "endor.prod.app". - `uuid` string: The UUID of an VectorStore. ## Other responses - `default`: An unexpected error response. ## Changes - **2026-11-03** `4acd9fe15140`: 1 info - endpoint added [Operation history](https://skmtc.dev/endorlabs/apis/endor-labs-rest-api-reference/changes/v1/namespaces/:tenant_meta.namespace/vector-stores/post.md) --- [API](https://skmtc.dev/endorlabs/apis/endor-labs-rest-api-reference.md) - [All operations](https://skmtc.dev/endorlabs/apis/endor-labs-rest-api-reference/llms.txt) - [OpenAPI document](https://skmtc.dev/endorlabs/apis/endor-labs-rest-api-reference/revisions/4acd9fe15140?raw)