Database
Architecture
List indexes
This operation returns a list of all indexes in a project.
from pinecone.grpc import PineconeGRPC as Pinecone
pc = Pinecone(api_key="YOUR_API_KEY")
index_list = pc.list_indexes()
print(index_list)
[{
"name": "example-sparse-index",
"metric": "dotproduct",
"host": "example-sparse-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
"spec": {
"serverless": {
"cloud": "aws",
"region": "us-east-1"
}
},
"status": {
"ready": true,
"state": "Ready"
},
"vector_type": "sparse",
"dimension": null,
"deletion_protection": "disabled",
"tags": {
"environment": "development"
}
}, {
"name": "example-dense-index",
"metric": "cosine",
"host": "example-dense-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
"spec": {
"serverless": {
"cloud": "aws",
"region": "us-east-1"
}
},
"status": {
"ready": true,
"state": "Ready"
},
"vector_type": "dense",
"dimension": 1536,
"deletion_protection": "disabled",
"tags": {
"environment": "development"
}
}]
from pinecone.grpc import PineconeGRPC as Pinecone
pc = Pinecone(api_key="YOUR_API_KEY")
index_list = pc.list_indexes()
print(index_list)
[{
"name": "example-sparse-index",
"metric": "dotproduct",
"host": "example-sparse-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
"spec": {
"serverless": {
"cloud": "aws",
"region": "us-east-1"
}
},
"status": {
"ready": true,
"state": "Ready"
},
"vector_type": "sparse",
"dimension": null,
"deletion_protection": "disabled",
"tags": {
"environment": "development"
}
}, {
"name": "example-dense-index",
"metric": "cosine",
"host": "example-dense-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
"spec": {
"serverless": {
"cloud": "aws",
"region": "us-east-1"
}
},
"status": {
"ready": true,
"state": "Ready"
},
"vector_type": "dense",
"dimension": 1536,
"deletion_protection": "disabled",
"tags": {
"environment": "development"
}
}]
Authorizations
Response
The list of indexes that exist in the project.
The IndexModel describes the configuration and status of a Pinecone index.
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 '-'.
1 - 45
"example-index"
The dimensions of the vectors to be inserted in the index.
1 <= x <= 20000
1536
The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'.
cosine
, euclidean
, dotproduct
The URL address where the index is hosted.
"semantic-search-c01b5b5.svc.us-west1-gcp.pinecone.io"
Configuration needed to deploy a pod-based index.
The environment where the index is hosted.
"us-east1-gcp"
The type of pod to use. One of s1
, p1
, or p2
appended with .
and one of x1
, x2
, x4
, or x8
.
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.
x >= 1
The number of shards. Shards split your data across multiple pods so you can fit more data into an index.
x >= 1
The number of pods to be used in the index. This should be equal to shards
x replicas
.'
x >= 1
1
Configuration for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when metadata_config
is present, only specified metadata fields are indexed. These configurations are only valid for use with pod-based indexes.
By default, all metadata is indexed; to change this behavior, use this property to specify an array of metadata fields that should be indexed.
{
"indexed": ["genre", "title", "imdb_rating"]
}
The name of the collection to be used as the source for the index.
"movie-embeddings"
{
"environment": "us-east1-gcp",
"metadata_config": {
"indexed": ["genre", "title", "imdb_rating"]
},
"pod_type": "p1.x1",
"pods": 1,
"replicas": 1,
"shards": 1,
"source_collection": "movie-embeddings"
}
Configuration needed to deploy a serverless index.
{
"pod": {
"environment": "us-east-1-aws",
"metadata_config": {
"indexed": ["genre", "title", "imdb_rating"]
},
"pod_type": "p1.x1",
"pods": 1,
"replicas": 1,
"shards": 1
}
}
Whether deletion protection is enabled/disabled for the index.
disabled
, enabled
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.
{ "tag0": "val0", "tag1": "val1" }
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from pinecone.grpc import PineconeGRPC as Pinecone
pc = Pinecone(api_key="YOUR_API_KEY")
index_list = pc.list_indexes()
print(index_list)
[{
"name": "example-sparse-index",
"metric": "dotproduct",
"host": "example-sparse-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
"spec": {
"serverless": {
"cloud": "aws",
"region": "us-east-1"
}
},
"status": {
"ready": true,
"state": "Ready"
},
"vector_type": "sparse",
"dimension": null,
"deletion_protection": "disabled",
"tags": {
"environment": "development"
}
}, {
"name": "example-dense-index",
"metric": "cosine",
"host": "example-dense-index-govk0nt.svc.aped-4627-b74a.pinecone.io",
"spec": {
"serverless": {
"cloud": "aws",
"region": "us-east-1"
}
},
"status": {
"ready": true,
"state": "Ready"
},
"vector_type": "dense",
"dimension": 1536,
"deletion_protection": "disabled",
"tags": {
"environment": "development"
}
}]