Authorizations
Body
The desired configuration for the index and associated embedding model.
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 public cloud where you would like your index hosted.
Possible values: gcp, aws, or azure.
"aws"
The region where you would like your index to be created.
"us-east-1"
Specify the integrated inference embedding configuration for the index.
Once set the model cannot be changed, but you can later update the embedding configuration for an integrated inference index including field map, read parameters, or write parameters.
Refer to the model guide for available models and model details.
{
"field_map": { "text": "your-text-field" },
"metric": "cosine",
"model": "multilingual-e5-large",
"read_parameters": { "input_type": "query", "truncate": "NONE" },
"write_parameters": { "input_type": "passage" }
}Whether deletion protection is enabled/disabled for the index.
Possible values: disabled or 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" }Schema for the behavior of Pinecone's internal metadata index. By default, all metadata is indexed; when schema is present, only fields which are present in the fields object with a filterable: true are indexed. Note that filterable: false is not currently supported.
{
"fields": {
"description": { "filterable": true },
"genre": { "filterable": true },
"year": { "filterable": true }
}
}- Option 1
- Option 2
Response
The index has successfully been created for the embedding model.
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 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.
The URL address where the index is hosted.
"semantic-search-c01b5b5.svc.us-west1-gcp.pinecone.io"
{
"pod": {
"environment": "us-east-1-aws",
"metadata_config": {
"indexed": ["genre", "title", "imdb_rating"]
},
"pod_type": "p1.x1",
"pods": 1,
"replicas": 1,
"shards": 1
}
}{
"ready": true,
"state": "ScalingUpPodSize"
}The index vector type. You can use 'dense' or 'sparse'. If 'dense', the vector dimension must be specified. If 'sparse', the vector dimension should not be specified.
The dimensions of the vectors to be inserted in the index.
1 <= x <= 200001536
The private endpoint URL of an index.
"semantic-search-c01b5b5.svc.private.us-west1-gcp.pinecone.io"
Whether deletion protection is enabled/disabled for the index.
Possible values: disabled or 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" }The embedding model and document fields mapped to embedding inputs.
{
"field_map": { "text": "your-text-field" },
"metric": "cosine",
"model": "multilingual-e5-large",
"read_parameters": { "input_type": "query", "truncate": "NONE" },
"write_parameters": { "input_type": "passage" }
}