Supermemory SDK

Official Python and JavaScript SDKs for Supermemory

Python SDK

pip install supermemory

JavaScript SDK

npm install supermemory

TypeScript

Installation

npm install supermemory

Quick Start

import Supermemory from 'supermemory';

const client = new Supermemory({
  apiKey: process.env.SUPERMEMORY_API_KEY,  // Default, can be omitted
});

// Add a memory
await client.add({ content: "Meeting notes from Q1 planning", containerTags: ["user_123"] });

// Search memories
const response = await client.search.documents({
  q: "planning notes",
  containerTags: ["user_123"]
});
console.log(response.results);

// Get user profile
const profile = await client.profile({ containerTag: "user_123" });
console.log(profile.profile.static);
console.log(profile.profile.dynamic);

Common Operations

// Add with metadata
await client.add({
  content: "Technical design doc",
  containerTags: ["user_123"],
  metadata: { category: "engineering", priority: "high" }
});

// Search with filters
const results = await client.search.documents({
  q: "design document",
  containerTags: ["user_123"],
  filters: {
    AND: [
      { key: "category", value: "engineering" }
    ]
  }
});

// List documents
const docs = await client.documents.list({ containerTags: ["user_123"], limit: 10 });

// Delete a document
await client.documents.delete({ docId: "doc_123" });

Python

Installation

pip install supermemory

Quick Start

import os
from supermemory import Supermemory

client = Supermemory(
    api_key=os.environ.get("SUPERMEMORY_API_KEY"),  # Default, can be omitted
)

# Add a memory
client.add(content="Meeting notes from Q1 planning", container_tags=["user_123"])

# Search memories
response = client.search.documents(
    q="planning notes",
    container_tags=["user_123"]
)
print(response.results)

# Get user profile
profile = client.profile(container_tag="user_123")
print(profile.profile.static)
print(profile.profile.dynamic)

Common Operations

# Add with metadata
client.add(
    content="Technical design doc",
    container_tags=["user_123"],
    metadata={"category": "engineering", "priority": "high"}
)

# Search with filters
results = client.search.documents(
    q="design document",
    container_tags=["user_123"],
    filters={
        "AND": [
            {"key": "category", "value": "engineering"}
        ]
    }
)

# List documents
docs = client.documents.list(container_tags=["user_123"], limit=10)

# Delete a document
client.documents.delete(doc_id="doc_123")