Overview
Permanently delete a namespace and all its contained documents or vectors. This operation is irreversible and will free up storage space in your account.
This action is permanent and cannot be undone. All data in the namespace will be lost forever.
Authentication
Your API key for authentication
Path Parameters
The name of the namespace to delete
curl -X DELETE "https://api.moorcheh.ai/v1/namespaces/my-old-documents" \
-H "x-api-Key: your-api-key-here"
202 - Accepted
401 - Unauthorized
403 - Forbidden
404 - Not Found
429 - Rate Limited
500 - Server Error
{
"status" : "pending" ,
"message" : "Request accepted. Namespace 'my-documents' has been queued for deletion."
}
Response Fields
Status of the deletion request (“success” for accepted deletions)
Human-readable confirmation message
Name of the namespace being deleted
ISO 8601 timestamp when deletion was initiated
Estimated ISO 8601 timestamp when deletion will be complete
Deletion Process
Initiate Deletion
The DELETE request starts the namespace deletion process
Background Processing
The system removes all documents/vectors and associated metadata
Storage Cleanup
Storage space is freed and becomes available for new data
Index Updates
Search indexes and internal references are updated
Important Notes
Deletion is processed asynchronously and may take several minutes for large namespaces
You can continue using other namespaces while deletion is in progress
Storage quota is updated once deletion is complete
Deleted namespace names become available for reuse after completion
Best Practices
Backup Important Data : Export or backup critical data before deletion
Verify Namespace Name : Double-check the namespace name before deletion
Monitor Usage : Use the list namespaces endpoint to confirm deletion completion
Plan Downtime : Consider impact on applications using the namespace
Use Cases
Data Cleanup : Remove old or unused namespaces to free up storage
Project Completion : Delete namespaces for completed projects
Resource Management : Manage namespace limits by removing unused ones
Data Lifecycle : Implement data retention policies