emdb-namespaces

# Namespaces in EmergentDB Help the user work with namespaces to organize vectors into isolated groups. ## TypeScript SDK ```typescript import { EmergentDB } from "emergentdb"; const db = new EmergentDB("emdb_your_api_key"); // List all namespaces const namespaces = await db.listNamespaces(); // ["default", "production", "staging"] // Insert into a namespace (creates it automatically) await db.insert(1, embedding, { title: "Doc" }, "production"); // Search within a namespace const results = await db.search(queryVec, { k: 10, includeMetadata: true, namespace: "production", }); // Batch insert into a namespace await db.batchInsert(vectors, "staging"); ``` ## Python SDK ```python from emergentdb import EmergentDB db = EmergentDB("emdb_your_api_key") # List all namespaces namespaces = db.list_namespaces() # ["default", "production", "staging"] # Insert into a namespace (creates it automatically) db.insert(1, embedding, metadata={"title": "Doc"}, namespace="production") # Search within a namespace results = db.search(query_vec, k=10, include_metadata=True, namespace="production") # Batch insert into a namespace db.batch_insert(vectors, namespace="staging") ``` ## Key Details - **Auto-created**: Namespaces are created automatically on first insert. No setup required. - **Isolation**: Vectors in one namespace are completely invisible to searches in another. - **Default namespace**: If no namespace is specified, operations use `"default"`. - **Naming**: Namespace names are strings up to 64 characters. - **Listing**: `listNamespaces()` / `list_namespaces()` returns all namespaces for your account. ## Plans & Limits | Plan | Vectors | Price | |------|---------|-------| | Free | 10,000 | $0/mo | | Launch | 500,000 | $29/mo | | Scale | 2,500,000 | $99/mo | Namespaces share your account's total vector quota. Upgrade from the billing page. ## Common Pattern: Multi-Environment Setup ```python from emergentdb import EmergentDB db = EmergentDB("emdb_your_api_key") # Separate environments by namespace for doc in documents: db.insert(doc["id"], doc["embedding"], metadata=doc["meta"], namespace="staging") # Promote to production when ready for doc in documents: db.insert(doc["id"], doc["embedding"], metadata=doc["meta"], namespace="production") ``` When helping the user, suggest namespaces for organizing data by environment, tenant, or data type.