Namespaces

What are Namespaces?

Namespaces are isolated containers for storing and organizing your data in Moorcheh. They provide separate environments for your documents or vectors, ensuring data separation and enabling organized data management.

Each namespace can store either text documents or vector embeddings, but not both. Choose the type based on your use case.

Namespace Types

Text Namespaces
Vector Namespaces

Text Namespaces

Text namespaces automatically handle embedding generation. Simply upload your text, and Moorcheh takes care of the vectorization.Best for:

Document search
Knowledge bases
Content management
File uploads (PDF, DOCX, etc.)

Example:

# Create text namespace
client.create_namespace(
    namespace_name="my-documents",
    type="text"
)

Vector Namespaces

Vector namespaces store pre-computed embeddings, giving you full control over the embedding model and process.Best for:

Custom embedding models
Pre-existing embeddings
Advanced use cases

Example:

# Create vector namespace
client.create_namespace(
    namespace_name="my-vectors",
    type="vector",
    vector_dimension=1536  # Must match your embeddings
)

Creating a Namespace

from moorcheh_sdk import MoorchehClient

client = MoorchehClient(api_key="your-api-key")

# Text namespace
namespace = client.create_namespace(
    namespace_name="my-documents",
    type="text"
)

# Vector namespace with specific dimension
namespace = client.create_namespace(
    namespace_name="my-vectors",
    type="vector",
    vector_dimension=1536
)

# Text namespace
curl -X POST "https://api.moorcheh.ai/v1/namespaces" \
  -H "Content-Type: application/json" \
  -H "x-api-key: your-api-key" \
  -d '{
    "namespace_name": "my-documents",
    "type": "text"
  }'

# Vector namespace
curl -X POST "https://api.moorcheh.ai/v1/namespaces" \
  -H "Content-Type: application/json" \
  -H "x-api-key: your-api-key" \
  -d '{
    "namespace_name": "my-vectors",
    "type": "vector",
    "vector_dimension": 1536
  }'

Listing Namespaces

# Get all namespaces
namespaces = client.list_namespaces()

for ns in namespaces:
    print(f"Name: {ns['namespace_name']}")
    print(f"Type: {ns['type']}")
    print(f"Items: {ns['item_count']}")

curl -X GET "https://api.moorcheh.ai/v1/namespaces" \
  -H "Content-Type: application/json" \
  -H "x-api-key: your-api-key"

Deleting a Namespace

Deleting a namespace is permanent and cannot be undone. All data in the namespace will be lost.

# Delete namespace
client.delete_namespace(namespace_name="my-documents")

curl -X DELETE "https://api.moorcheh.ai/v1/namespaces/my-documents" \
  -H "Content-Type: application/json" \
  -H "x-api-key: your-api-key"

Naming Guidelines

Good namespace names:

product-docs
customer_support_v2
legal-contracts-2024
blog_embeddings

Avoid:

Special characters (except - and _)
Spaces
Very long names (> 64 characters)

Next Steps

Upload Text

Learn how to upload text documents

Upload Vectors

Work with custom vector embeddings

Search

Perform semantic search

API Reference

Complete namespace API documentation

Getting Started

Core Concepts

Advanced

Legal

What are Namespaces?

Namespace Types

Text Namespaces

Vector Namespaces

Creating a Namespace

Listing Namespaces

Deleting a Namespace

Naming Guidelines

Next Steps

Upload Text

Upload Vectors

Search

API Reference

​What are Namespaces?

​Namespace Types

​Text Namespaces

​Vector Namespaces

​Creating a Namespace

​Listing Namespaces

​Deleting a Namespace

​Naming Guidelines

​Next Steps

Upload Text

Upload Vectors

Search

API Reference

What are Namespaces?

Namespace Types

Text Namespaces

Vector Namespaces

Creating a Namespace

Listing Namespaces

Deleting a Namespace

Naming Guidelines

Next Steps