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Create, configure, and manage vector indexes with customizable dimensions, metrics, and cloud deployment options for optimal performance.

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Create Your First Index

  • CLI
  • Python SDK
  • JavaScript SDK
gravixlayer vectors index create --name "my-embeddings" --dimension 1024 --metric cosine --cloud-provider AWS --region us-east-1 --index-type serverless
Example Output:
Creating vector index: my-embeddings
Index created successfully!
   Index ID: aab489e9-98e2-4c63-a264-5010c297ba39
   Name: my-embeddings
   Dimension: 1024
   Metric: cosine
   Cloud Provider: AWS
   Region: us-east-1
   Index Type: serverless
   Vector Type: dense

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List Indexes

  • CLI
  • Python SDK
  • JavaScript SDK
gravixlayer vectors index list
Example Output:
Listing vector indexes...
   Found 2 index(es):

Index ID: 2e1b4b71-745b-4510-b7ab-045ffe390517
Name: protected-embeddings
Dimension: 768
Metric: euclidean
Cloud Provider: AWS
Region: east-us-1
Index Type: serverless
Vector Type: dense
Delete Protection: True
Created: 2025-09-24T17:25:47.194281Z

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Get Index Details

  • CLI
  • Python SDK
  • JavaScript SDK
gravixlayer vectors index get <index-id>

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Update Index

  • CLI
  • Python SDK
  • JavaScript SDK
# Update metadata
gravixlayer vectors index update <index-id> --metadata '{"description":"Updated_embeddings","version":"2.0"}'

# Enable delete protection
gravixlayer vectors index update <index-id> --delete-protection true

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Delete Index

  • CLI
  • Python SDK
  • JavaScript SDK
# Delete index
gravixlayer vectors index delete <index-id>

# Force delete (removes protection first)
gravixlayer vectors index delete <index-id> --force
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