> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Create an index with integrated embedding
> Create a serverless index with an integrated embedding model. Pinecone automatically embeds text written to the specified field at write time and embeds queries at read time using the same model.
This is a convenience wrapper around [Create Index](#tag/Manage-Indexes/operation/create_index) that constructs a `semantic_text` schema field from the model parameters you provide. For full control over schema composition (e.g., combining semantic text with metadata fields), use Create Index directly.
For guidance and examples, see [Create an index](https://docs.pinecone.io/guides/index-data/create-an-index#integrated-embedding).
```python Python theme={null}
from pinecone import Pinecone
pc = Pinecone(api_key="YOUR_API_KEY")
index_model = pc.create_index_for_model(
name="docs-example",
cloud="aws",
region="us-east-1",
embed={
"model": "multilingual-e5-large",
"field_map": {"text": "chunk_text"}
}
)
```
```shell curl theme={null}
PINECONE_API_KEY="YOUR_API_KEY"
curl "https://api.pinecone.io/indexes/create-for-model" \
-H "Api-Key: $PINECONE_API_KEY" \
-H "Content-Type: application/json" \
-H "X-Pinecone-Api-Version: 2026-01.alpha" \
-d '{
"name": "docs-example",
"cloud": "aws",
"region": "us-east-1",
"embed": {
"model": "multilingual-e5-large",
"field_map": {"text": "chunk_text"}
}
}'
```
## OpenAPI
````yaml https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-01.alpha/db_control_2026-01.alpha.oas.yaml post /indexes/create-for-model
openapi: 3.0.3
info:
title: Pinecone Control Plane API
description: >-
Pinecone is a vector database that makes it easy to search and retrieve
billions of high-dimensional vectors.
contact:
name: Pinecone Support
url: https://support.pinecone.io
email: support@pinecone.io
license:
name: Apache 2.0
url: https://www.apache.org/licenses/LICENSE-2.0
version: 2026-01.alpha
servers:
- url: https://api.pinecone.io
description: Production API endpoints
security:
- ApiKeyAuth: []
tags:
- name: Manage Indexes
description: Actions that manage indexes
externalDocs:
description: More Pinecone.io API docs
url: https://docs.pinecone.io/introduction
paths:
/indexes/create-for-model:
post:
tags:
- Manage Indexes
summary: Create an index with integrated embedding
description: >-
Create a serverless index with an integrated embedding model. Pinecone
automatically embeds text written to the specified field at write time
and embeds queries at read time using the same model.
This is a convenience wrapper around [Create
Index](#tag/Manage-Indexes/operation/create_index) that constructs a
`semantic_text` schema field from the model parameters you provide. For
full control over schema composition (e.g., combining semantic text with
metadata fields), use Create Index directly.
For guidance and examples, see [Create an
index](https://docs.pinecone.io/guides/index-data/create-an-index#integrated-embedding).
operationId: create_index_for_model
parameters:
- in: header
name: X-Pinecone-Api-Version
description: Required date-based version header
required: true
schema:
default: 2026-01.alpha
type: string
style: simple
requestBody:
description: >-
The desired configuration for the index and associated embedding
model.
content:
application/json:
schema:
$ref: '#/components/schemas/CreateIndexForModelRequest'
examples:
index-for-model:
summary: Creating a serverless index for the specified model
value:
deletion_protection: enabled
deployment:
cloud: aws
deployment_type: managed
region: us-east-1
field: content
model: multilingual-e5-large
name: multilingual-e5-large-index
read_parameters:
input_type: query
truncate: NONE
write_parameters:
input_type: passage
required: true
responses:
'201':
description: The index has been successfully created.
content:
application/json:
schema:
$ref: '#/components/schemas/IndexModel'
examples:
created:
summary: Index created with integrated embedding
value:
deletion_protection: enabled
deployment:
cloud: aws
deployment_type: managed
region: us-east-1
host: >-
multilingual-e5-large-index-c01b5b5.svc.us-east1.pinecone.io
name: multilingual-e5-large-index
read_capacity:
mode: OnDemand
status:
state: Ready
schema:
fields:
content:
metric: cosine
model: multilingual-e5-large
read_parameters:
input_type: query
truncate: NONE
type: semantic_text
write_parameters:
input_type: passage
status:
ready: false
state: Initializing
'400':
description: Bad request. The request body included invalid request parameters.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
examples:
index-metric-validation-error:
summary: Validation error
value:
error:
code: INVALID_ARGUMENT
message: >-
Bad request. The request body included invalid request
parameters.
status: 400
'401':
description: 'Unauthorized. Possible causes: Invalid API key.'
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
examples:
unauthorized:
summary: Unauthorized
value:
error:
code: UNAUTHENTICATED
message: Invalid API key.
status: 401
'402':
description: >-
Payment required. Organization is on a paid plan and is delinquent
on payment.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
examples:
payment-required:
summary: Payment required
value:
error:
code: PAYMENT_REQUIRED
message: >-
Request failed. Pay all past due invoices to lift
restrictions on your account.
status: 402
'404':
description: Unknown cloud or region when creating a serverless index.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
examples:
serverless-spec-cloud-not-found:
summary: Cannot create serverless index with invalid spec.
value:
error:
code: NOT_FOUND
message: 'Resource cloud: aws region: us-west1 not found.'
status: 404
'409':
description: Index of given name already exists.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
examples:
index-name-already-exists:
summary: Index name needs to be unique
value:
error:
code: ALREADY_EXISTS
message: Resource already exists.
status: 409
'422':
description: Unprocessable entity. The request body could not be deserialized.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
examples:
missing-field:
summary: Unprocessable entity
value:
error:
code: UNPROCESSABLE_ENTITY
message: >-
Failed to deserialize the JSON body into the target
type: missing field `metric` at line 1 column 16
status: 422
'500':
description: Internal server error.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
examples:
internal-server-error:
summary: Internal server error
value:
error:
code: UNKNOWN
message: Internal server error
status: 500
components:
schemas:
CreateIndexForModelRequest:
description: >-
Configuration for creating an index with an integrated embedding model.
The server constructs a `semantic_text` schema field named `field` using
the provided model parameters.
type: object
properties:
name:
example: example-index
description: >-
The name of the index. Auto-generated if not provided. Resource name
must be 1-45 characters long, start and end with an alphanumeric
character, and consist only of lower case alphanumeric characters or
'-'. Callers that require retry-safe behavior should provide an
explicit name — a duplicate request with the same name returns 409,
making success detectable on retry.
type: string
minLength: 1
maxLength: 45
deployment:
$ref: '#/components/schemas/ManagedDeployment'
field:
example: content
description: >-
The name of the schema field that will hold the embedded text. This
becomes a `semantic_text` field in the index schema.
type: string
model:
example: multilingual-e5-large
description: >-
The name of the embedding model to use. Refer to the [model
guide](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models)
for available models and details.
type: string
metric:
description: >-
The distance metric to be used for similarity search. You can use
'euclidean', 'cosine', or 'dotproduct'. If the 'vector_type' is
'sparse', the metric must be 'dotproduct'. If the `vector_type` is
`dense`, the metric defaults to 'cosine'.
Possible values: `cosine`, `euclidean`, or `dotproduct`.
x-enum:
- cosine
- euclidean
- dotproduct
type: string
write_parameters:
example:
input_type: passage
description: >-
Model-specific parameters applied when embedding documents at write
time.
type: object
read_parameters:
example:
input_type: query
truncate: NONE
description: >-
Model-specific parameters applied when embedding queries at read
time.
type: object
read_capacity:
$ref: '#/components/schemas/ReadCapacity'
tags:
$ref: '#/components/schemas/IndexTags'
deletion_protection:
$ref: '#/components/schemas/DeletionProtection'
required:
- model
- field
IndexModel:
example:
deletion_protection: disabled
deployment:
cloud: aws
deployment_type: managed
region: us-east-1
host: my-index-abc123.svc.pinecone.io
name: my-index
read_capacity:
mode: OnDemand
status:
state: Ready
schema:
fields:
embedding:
dimension: 1536
metric: cosine
type: dense_vector
title:
full_text_search:
language: en
stemming: false
stop_words: false
type: string
status:
ready: true
state: Ready
description: >-
The IndexModel describes the configuration and status of a Pinecone
index.
type: object
properties:
name:
example: example-index
description: >
The name of the index. Resource name must be 1-45 characters long,
start and end with an alphanumeric character, and consist only of
lower case alphanumeric characters or '-'.
type: string
minLength: 1
maxLength: 45
host:
example: semantic-search-c01b5b5.svc.us-west1-gcp.pinecone.io
description: The URL address where the index is hosted.
type: string
private_host:
example: semantic-search-c01b5b5.svc.private.us-west1-gcp.pinecone.io
description: The private endpoint URL of an index.
type: string
status:
example:
ready: true
state: Ready
description: The current status of the index.
type: object
properties:
ready:
description: Whether the index is ready for use.
type: boolean
state:
description: >-
The current state of the index.
Possible values: `Initializing`, `InitializationFailed`,
`ScalingUp`, `ScalingDown`, `ScalingUpPodSize`,
`ScalingDownPodSize`, `Terminating`, `Ready`, or `Disabled`.
x-enum:
- Initializing
- InitializationFailed
- ScalingUp
- ScalingDown
- ScalingUpPodSize
- ScalingDownPodSize
- Terminating
- Ready
- Disabled
type: string
required:
- ready
- state
deployment:
$ref: '#/components/schemas/IndexDeployment'
read_capacity:
$ref: '#/components/schemas/ReadCapacityResponse'
source_collection:
example: movie-embeddings
description: The name of the collection this index was created from, if any.
type: string
source_backup_id:
example: 670e8400-e29b-41d4-a716-446655440000
description: The ID of the backup this index was restored from, if any.
type: string
cmek_id:
example: arn:aws:kms:us-east-1:123456789012:key/mrk-abc123
description: >-
The ID of the customer-managed encryption key (CMEK) used to encrypt
this index, if any.
type: string
schema:
$ref: '#/components/schemas/IndexSchema'
tags:
$ref: '#/components/schemas/IndexTags'
deletion_protection:
$ref: '#/components/schemas/DeletionProtection'
required:
- name
- host
- status
- deployment
- schema
- deletion_protection
ErrorResponse:
example:
error:
code: QUOTA_EXCEEDED
message: >-
The index exceeds the project quota of 5 pods by 2 pods. Upgrade
your account or change the project settings to increase the quota.
status: 429
description: The response shape used for all error responses.
type: object
properties:
status:
example: 500
description: The HTTP status code of the error.
type: integer
error:
example:
code: INVALID_ARGUMENT
message: >-
Index name must contain only lowercase alphanumeric characters or
hyphens, and must not begin or end with a hyphen.
description: Detailed information about the error that occurred.
type: object
properties:
code:
description: >-
The error code.
Possible values: `OK`, `UNKNOWN`, `INVALID_ARGUMENT`,
`DEADLINE_EXCEEDED`, `QUOTA_EXCEEDED`, `NOT_FOUND`,
`ALREADY_EXISTS`, `PERMISSION_DENIED`, `UNAUTHENTICATED`,
`RESOURCE_EXHAUSTED`, `FAILED_PRECONDITION`, `ABORTED`,
`OUT_OF_RANGE`, `UNIMPLEMENTED`, `INTERNAL`, `UNAVAILABLE`,
`DATA_LOSS`, `FORBIDDEN`, `UNPROCESSABLE_ENTITY`, or
`PAYMENT_REQUIRED`.
x-enum:
- OK
- UNKNOWN
- INVALID_ARGUMENT
- DEADLINE_EXCEEDED
- QUOTA_EXCEEDED
- NOT_FOUND
- ALREADY_EXISTS
- PERMISSION_DENIED
- UNAUTHENTICATED
- RESOURCE_EXHAUSTED
- FAILED_PRECONDITION
- ABORTED
- OUT_OF_RANGE
- UNIMPLEMENTED
- INTERNAL
- UNAVAILABLE
- DATA_LOSS
- FORBIDDEN
- UNPROCESSABLE_ENTITY
- PAYMENT_REQUIRED
type: string
message:
example: >-
Index name must contain only lowercase alphanumeric characters
or hyphens, and must not begin or end with a hyphen.
description: A human-readable description of the error
type: string
details:
description: >-
Additional information about the error. This field is not
guaranteed to be present.
type: object
required:
- code
- message
required:
- status
- error
ManagedDeployment:
example:
cloud: aws
deployment_type: managed
region: us-east-1
title: Serverless
description: >-
Deployment configuration for a serverless (managed) index. Serverless
indexes scale automatically and you are billed only for the resources
you use. This deployment type also covers full-text search indexes,
which are serverless under the hood.
type: object
properties:
deployment_type:
description: >-
Identifies this as a managed (serverless) deployment. Must be
`managed`.
type: string
enum:
- managed
cloud:
example: aws
description: |-
The public cloud where the index is hosted.
Possible values: `gcp`, `aws`, or `azure`.
x-enum:
- gcp
- aws
- azure
type: string
region:
example: us-east-1
description: The region where the index is hosted.
type: string
required:
- deployment_type
- cloud
- region
additionalProperties: false
ReadCapacity:
description: >-
By default the index will be created with read capacity mode
`OnDemand`. If you prefer to allocate dedicated read nodes for your
workload, you must specify mode `Dedicated` and additional
configurations for `node_type` and `scaling`.
discriminator:
propertyName: mode
mapping:
OnDemand:
$ref: '#/components/schemas/ReadCapacityOnDemandSpec'
Dedicated:
$ref: '#/components/schemas/ReadCapacityDedicatedSpec'
oneOf:
- $ref: '#/components/schemas/ReadCapacityOnDemandSpec'
- $ref: '#/components/schemas/ReadCapacityDedicatedSpec'
IndexTags:
example:
tag0: val0
tag1: val1
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.
type: object
additionalProperties:
type: string
DeletionProtection:
description: >-
Whether [deletion
protection](http://docs.pinecone.io/guides/manage-data/manage-indexes#configure-deletion-protection)
is enabled/disabled for the index.
Possible values: `disabled` or `enabled`.
default: disabled
x-enum:
- disabled
- enabled
type: string
IndexDeployment:
description: >-
The deployment configuration of a Pinecone index. The `deployment_type`
field indicates which infrastructure model the index uses.
- `pod`: Dedicated pod-based infrastructure. Suitable for workloads that
require predictable performance.
- `managed`: Serverless infrastructure managed by Pinecone, including
full-text search indexes. Scales automatically; billed per usage.
- `byoc`: Bring-your-own-compute. Runs in customer-managed
infrastructure.
discriminator:
propertyName: deployment_type
mapping:
pod:
$ref: '#/components/schemas/PodDeployment'
managed:
$ref: '#/components/schemas/ManagedDeployment'
byoc:
$ref: '#/components/schemas/ByocDeployment'
oneOf:
- $ref: '#/components/schemas/PodDeployment'
- $ref: '#/components/schemas/ManagedDeployment'
- $ref: '#/components/schemas/ByocDeployment'
ReadCapacityResponse:
description: Response containing read capacity configuration
discriminator:
propertyName: mode
mapping:
OnDemand:
$ref: '#/components/schemas/ReadCapacityOnDemandSpecResponse'
Dedicated:
$ref: '#/components/schemas/ReadCapacityDedicatedSpecResponse'
oneOf:
- $ref: '#/components/schemas/ReadCapacityOnDemandSpecResponse'
- $ref: '#/components/schemas/ReadCapacityDedicatedSpecResponse'
IndexSchema:
example:
fields:
embedding:
dimension: 1536
metric: cosine
type: dense_vector
title:
full_text_search:
language: en
stemming: false
stop_words: false
type: string
description: >-
The schema of a Pinecone index. The schema defines the typed fields that
documents in the index can contain, including vector fields, semantic
text fields, and metadata fields.
type: object
properties:
fields:
description: >-
A map of field names to their configurations. Field names must be
unique, non-empty strings and must not use the reserved names `_id`,
`_values`, or `_sparse_values`.
type: object
additionalProperties:
$ref: '#/components/schemas/IndexSchemaField'
required:
- fields
ReadCapacityOnDemandSpec:
example:
mode: OnDemand
title: On-demand
type: object
properties:
mode:
description: >-
The mode of the index. Possible values: `OnDemand` or `Dedicated`.
Defaults to `OnDemand`. If set to `Dedicated`,
`dedicated.node_type`, and `dedicated.scaling` must be specified.
type: string
required:
- mode
additionalProperties: false
ReadCapacityDedicatedSpec:
example:
dedicated:
manual:
replicas: 1
shards: 1
node_type: t1
scaling: Manual
mode: Dedicated
title: Dedicated
type: object
properties:
mode:
description: >-
The mode of the index. Possible values: `OnDemand` or `Dedicated`.
Defaults to `OnDemand`. If set to `Dedicated`,
`dedicated.node_type`, and `dedicated.scaling` must be specified.
type: string
dedicated:
$ref: '#/components/schemas/ReadCapacityDedicatedConfig'
required:
- mode
- dedicated
additionalProperties: true
PodDeployment:
example:
deployment_type: pod
environment: us-east1-gcp
pod_type: p1.x1
replicas: 1
shards: 1
title: Pod-based
description: Deployment configuration for a pod-based index.
type: object
properties:
deployment_type:
description: Identifies this as a pod-based deployment. Must be `pod`.
type: string
enum:
- pod
environment:
example: us-east1-gcp
description: The environment where the index is hosted.
type: string
replicas:
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.
default: 1
type: integer
format: int32
minimum: 1
shards:
description: >-
The number of shards. Shards split your data across multiple pods so
you can fit more data into an index.
default: 1
type: integer
format: int32
minimum: 1
pod_type:
description: >-
The type of pod to use. One of `s1`, `p1`, or `p2` appended with `.`
and one of `x1`, `x2`, `x4`, or `x8`.
default: p1.x1
type: string
required:
- deployment_type
- environment
- pod_type
additionalProperties: false
ByocDeployment:
example:
deployment_type: byoc
environment: aws-us-east-1-b921
title: BYOC
description: Deployment configuration for a bring-your-own-compute (BYOC) index.
type: object
properties:
deployment_type:
description: Identifies this as a BYOC deployment. Must be `byoc`.
type: string
enum:
- byoc
environment:
example: aws-us-east-1-b921
description: The BYOC environment where the index is hosted.
type: string
required:
- deployment_type
- environment
additionalProperties: false
ReadCapacityOnDemandSpecResponse:
example:
mode: OnDemand
status:
state: Ready
title: On-demand
type: object
properties:
mode:
description: >-
The mode of the index. Possible values: `OnDemand` or `Dedicated`.
Defaults to `OnDemand`. If set to `Dedicated`,
`dedicated.node_type`, and `dedicated.scaling` must be specified.
type: string
status:
$ref: '#/components/schemas/ReadCapacityStatus'
required:
- mode
- status
additionalProperties: false
ReadCapacityDedicatedSpecResponse:
example:
dedicated:
manual:
replicas: 2
shards: 2
node_type: t1
scaling: Manual
mode: Dedicated
status:
current_replicas: 2
current_shards: 2
state: Ready
title: Dedicated
type: object
properties:
mode:
description: >-
The mode of the index. Possible values: `OnDemand` or `Dedicated`.
Defaults to `OnDemand`. If set to `Dedicated`,
`dedicated.node_type`, and `dedicated.scaling` must be specified.
type: string
dedicated:
$ref: '#/components/schemas/ReadCapacityDedicatedConfig'
status:
$ref: '#/components/schemas/ReadCapacityStatus'
required:
- mode
- dedicated
- status
additionalProperties: false
IndexSchemaField:
description: >-
The configuration of a single field in the index schema.
Most fields carry a `type` property that identifies the field type:
- `dense_vector`: Fixed-dimension floating-point vectors for ANN search.
- `sparse_vector`: Sparse vectors for keyword or hybrid search. -
`semantic_text`: Text field backed by an integrated embedding model. -
`string`: String field for full-text search or metadata filtering. -
`string_list`: String array field. - `float`: Numeric field. -
`integer`: Legacy numeric field from older indexes (pre-dating float
normalization). Will not appear in new indexes.
- `boolean`: Boolean field.
Fields in older indexes may omit `type` entirely. These are legacy
metadata fields from before typed schemas were introduced.
anyOf:
- $ref: '#/components/schemas/TypedIndexSchemaField'
- $ref: '#/components/schemas/LegacyMetadataField'
ReadCapacityDedicatedConfig:
description: >-
Configuration for dedicated read capacity. See [this
guide](https://docs.pinecone.io/guides/index-data/dedicated-read-nodes)
for more details on how to configure dedicated read capacity.
type: object
properties:
node_type:
description: >-
The type of machines to use. Available options: `b1` and `t1`. `t1`
includes increased processing power and memory.
type: string
scaling:
description: The type of scaling strategy to use.
type: string
manual:
$ref: '#/components/schemas/ScalingConfigManual'
ReadCapacityStatus:
description: >-
The current status of factors affecting the read capacity of a
serverless index
type: object
properties:
state:
description: >-
The `state` describes the overall status of factors relating to the
read capacity of an index.
Available values:
- `Ready` is the state most of the time
- `Scaling` if the number of replicas or shards has been recently
updated by calling the [configure index
endpoint](https://docs.pinecone.io/reference/api/2026-04/control-plane/configure_index)
- `Migrating` if the index is being migrated to a new `node_type`
- `Error` if there is an error with the read capacity configuration.
In that case, see `error_message` for more details.
type: string
current_replicas:
description: >-
The number of replicas. Each replica has dedicated compute
resources and data storage. Increasing this number will increase
the total throughput of the index.
type: integer
format: int32
current_shards:
description: >-
The number of shards. Each shard has dedicated storage. Increasing
shards alleiviates index fullness.
type: integer
format: int32
error_message:
description: >-
An optional error message indicating any issues with your read
capacity configuration
type: string
required:
- state
TypedIndexSchemaField:
title: Typed field
description: >-
A schema field that carries a `type` discriminator. This covers all
field types in current use. See `IndexSchemaField` for the full union
that also includes legacy untyped fields.
discriminator:
propertyName: type
mapping:
dense_vector:
$ref: '#/components/schemas/DenseVectorField'
sparse_vector:
$ref: '#/components/schemas/SparseVectorField'
semantic_text:
$ref: '#/components/schemas/SemanticTextField'
string:
$ref: '#/components/schemas/ResponseStringField'
string_list:
$ref: '#/components/schemas/StringListField'
float:
$ref: '#/components/schemas/FloatField'
integer:
$ref: '#/components/schemas/IntegerField'
boolean:
$ref: '#/components/schemas/BooleanField'
oneOf:
- $ref: '#/components/schemas/DenseVectorField'
- $ref: '#/components/schemas/SparseVectorField'
- $ref: '#/components/schemas/SemanticTextField'
- $ref: '#/components/schemas/ResponseStringField'
- $ref: '#/components/schemas/StringListField'
- $ref: '#/components/schemas/FloatField'
- $ref: '#/components/schemas/IntegerField'
- $ref: '#/components/schemas/BooleanField'
LegacyMetadataField:
example:
filterable: true
title: Legacy metadata
description: >-
A legacy metadata field from indexes created before typed schema fields
were introduced. The original data type of the field (string, float,
boolean, etc.) was not recorded. Only the `filterable` flag is
available. This field type will not appear in new indexes; it may appear
in responses for older indexes pending schema migration.
type: object
properties:
filterable:
description: Whether this field is indexed for metadata filtering.
type: boolean
required:
- filterable
additionalProperties: false
ScalingConfigManual:
description: The config to use for manual read capacity scaling.
type: object
properties:
replicas:
description: >-
The number of replicas to use. Replicas duplicate the compute
resources and data of an index, allowing higher query throughput and
availability. Setting replicas to 0 disables the index but can be
used to reduce costs while usage is paused.
type: integer
format: int32
minimum: 0
shards:
description: >-
The number of shards to use. Shards determine the storage capacity
of an index, with each shard providing 250 GB of storage.
type: integer
format: int32
minimum: 1
DenseVectorField:
example:
dimension: 1536
metric: cosine
type: dense_vector
title: Dense vector
description: >-
A dense vector field configuration. Stores fixed-dimension
floating-point vectors for approximate nearest-neighbor (ANN) search.
type: object
properties:
type:
description: Identifies this as a dense vector field. Must be `dense_vector`.
type: string
enum:
- dense_vector
dimension:
example: 1536
description: The number of dimensions in the dense vectors stored in this field.
type: integer
metric:
example: cosine
description: |-
The distance metric used for similarity search.
Possible values: `cosine`, `dotproduct`, or `euclidean`.
x-enum:
- cosine
- dotproduct
- euclidean
type: string
required:
- type
- dimension
- metric
SparseVectorField:
example:
type: sparse_vector
title: Sparse vector
description: >-
A sparse vector field configuration. Stores sparse vectors for keyword
or hybrid search.
type: object
properties:
type:
description: Identifies this as a sparse vector field. Must be `sparse_vector`.
type: string
enum:
- sparse_vector
required:
- type
SemanticTextField:
example:
model: multilingual-e5-large
type: semantic_text
title: Semantic text
description: >-
A semantic text field configuration. Backed by an integrated embedding
model that embeds text at write and query time, enabling semantic
similarity search without separate embedding calls.
type: object
properties:
type:
description: Identifies this as a semantic text field. Must be `semantic_text`.
type: string
enum:
- semantic_text
model:
example: multilingual-e5-large
description: The name of the integrated embedding model to use for this field.
type: string
metric:
example: cosine
description: >-
The distance metric used for similarity search. Defaults to the
model's preferred metric if not specified.
Possible values: `cosine`, `dotproduct`, or `euclidean`.
x-enum:
- cosine
- dotproduct
- euclidean
type: string
write_parameters:
example:
input_type: passage
description: >-
Model-specific parameters applied at write time, such as
`input_type`.
type: object
read_parameters:
example:
input_type: query
description: >-
Model-specific parameters applied at query time, such as
`input_type`.
type: object
required:
- type
- model
ResponseStringField:
example:
full_text_search:
language: en
stemming: false
stop_words: false
type: string
title: String
description: >-
A string field as returned in index schema responses. String fields
configured for full-text search include a `full_text_search` object;
string fields used for metadata filtering only include a `filterable`
flag.
type: object
properties:
type:
description: Identifies this as a string field. Must be `string`.
type: string
enum:
- string
description:
description: Optional description for this field.
type: string
full_text_search:
description: >-
Full-text search configuration. Present when the field is indexed
for full-text search.
type: object
properties:
language:
example: en
description: The language used for text analysis. Defaults to `en`.
default: en
type: string
stemming:
description: Whether stemming is applied during text analysis.
type: boolean
stop_words:
description: >-
Whether stop words are filtered during text analysis. Only
`true` if `stemming: true`.
type: boolean
ngram:
description: >-
Character n-gram tokenization configuration. Present only when
the field is configured for n-gram substring matching.
type: object
properties:
min_gram:
example: 2
description: Minimum n-gram length.
type: integer
max_gram:
example: 3
description: Maximum n-gram length.
type: integer
prefix_only:
description: >-
Whether only prefix n-grams anchored at the start of the
token are generated.
type: boolean
required:
- min_gram
- max_gram
- prefix_only
additionalProperties: false
required:
- language
- stemming
- stop_words
additionalProperties: false
filterable:
description: Whether this field is indexed for metadata filtering.
type: boolean
required:
- type
StringListField:
example:
filterable: true
type: string_list
title: String array
description: >-
A string array field configuration. String array values are not declared
in the index schema; include them as document metadata instead — they
are indexed automatically at upsert time.
type: object
properties:
type:
description: Identifies this as a string array field. Must be `string_list`.
type: string
enum:
- string_list
description:
description: Optional description for this field.
type: string
filterable:
description: Whether this field is indexed for metadata filtering.
type: boolean
required:
- type
FloatField:
example:
type: float
title: Float
description: >-
A numeric (floating-point) field configuration. Numeric values are not
declared in the index schema; include them as document metadata instead
— they are indexed automatically at upsert time.
type: object
properties:
type:
description: Identifies this as a float field. Must be `float`.
type: string
enum:
- float
description:
description: Optional description for this field.
type: string
filterable:
description: Whether this field is indexed for metadata filtering.
type: boolean
required:
- type
IntegerField:
example:
filterable: true
type: integer
title: Integer
description: >-
A legacy integer field configuration. Integer fields were used in older
index schemas before numeric values were normalized to `float` at upsert
time. New indexes will not produce this field type; it may appear in
responses for indexes created before that normalization was introduced.
type: object
properties:
type:
description: Identifies this as an integer field. Must be `integer`.
type: string
enum:
- integer
description:
description: Optional description for this field.
type: string
filterable:
description: Whether this field is indexed for metadata filtering.
type: boolean
required:
- type
BooleanField:
example:
type: boolean
title: Boolean
description: >-
A boolean field configuration. Boolean values are not declared in the
index schema; include them as document metadata instead — they are
indexed automatically at upsert time.
type: object
properties:
type:
description: Identifies this as a boolean field. Must be `boolean`.
type: string
enum:
- boolean
description:
description: Optional description for this field.
type: string
filterable:
description: Whether this field is indexed for metadata filtering.
type: boolean
required:
- type
securitySchemes:
ApiKeyAuth:
type: apiKey
in: header
name: Api-Key
description: >-
An API Key is required to call Pinecone APIs. Get yours from the
[console](https://app.pinecone.io/).
````