Skip to main content
📢 Announcing our research paper: Zentry achieves 26% higher accuracy than OpenAI Memory, 91% lower latency, and 90% token savings! Read the paper to learn how we're revolutionizing AI agent memory.
Welcome to the Zentry quickstart guide. This guide will help you get up and running with Zentry in no time.

​
Installation

To install Zentry, you can use npm. Run the following command in your terminal: 
npm install zentry

​
Basic Usage

​
Initialize Zentry

  • Basic
  • Advanced
import { Memory } from 'zentry/oss';

const memory = new Memory();

​
Store a Memory

const messages = [
    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
    {"role": "assistant", "content": "How about a thriller movies? They can be quite engaging."},
    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
]

await memory.add(messages, { userId: "alice", metadata: { category: "movie_recommendations" } });

​
Retrieve Memories

// Get all memories
const allMemories = await memory.getAll({ userId: "alice" });
console.log(allMemories)


// Get a single memory by ID
const singleMemory = await memory.get('892db2ae-06d9-49e5-8b3e-585ef9b85b8e');
console.log(singleMemory);

​
Search Memories

const result = await memory.search('What do you know about me?', { userId: "alice" });
console.log(result);

​
Update a Memory

const result = await memory.update(
  '892db2ae-06d9-49e5-8b3e-585ef9b85b8e',
  'I love India, it is my favorite country.'
);
console.log(result);

​
Memory History

const history = await memory.history('892db2ae-06d9-49e5-8b3e-585ef9b85b8e');
console.log(history);

​
Delete Memory

// Delete a memory by id
await memory.delete('892db2ae-06d9-49e5-8b3e-585ef9b85b8e');

// Delete all memories for a user
await memory.deleteAll({ userId: "alice" });

​
Reset Memory

await memory.reset(); // Reset all memories

​
History Store

Zentry TypeScript SDK support history stores to run on a serverless environment: We recommend using Supabase as a history store for serverless environments or disable history store to run on a serverless environment. 
import { Memory } from 'zentry/oss';

const memory = new Memory({
  historyStore: {
    provider: 'supabase',
    config: {
      supabaseUrl: process.env.SUPABASE_URL || '',
      supabaseKey: process.env.SUPABASE_KEY || '',
      tableName: 'memory_history',
    },
  },
});
Zentry uses SQLite as a default history store.

​
Create Memory History Table in Supabase

You may need to create a memory history table in Supabase to store the history of memories. Use the following SQL command in SQL Editor on the Supabase project dashboard to create a memory history table: 
create table memory_history (
  id text primary key,
  memory_id text not null,
  previous_value text,
  new_value text,
  action text not null,
  created_at timestamp with time zone default timezone('utc', now()),
  updated_at timestamp with time zone,
  is_deleted integer default 0
);

​
Configuration Parameters

Zentry offers extensive configuration options to customize its behavior according to your needs. These configurations span across different components like vector stores, language models, embedders, and graph stores.
ParameterDescriptionDefault
providerVector store provider (e.g., “memory”)“memory”
hostHost address”localhost”
portPort numberundefined
ParameterDescriptionProvider
providerLLM provider (e.g., “openai”, “anthropic”)All
modelModel to useAll
temperatureTemperature of the modelAll
apiKeyAPI key to useAll
maxTokensTokens to generateAll
topPProbability threshold for nucleus samplingAll
topKNumber of highest probability tokens to keepAll
openaiBaseUrlBase URL for OpenAI APIOpenAI
ParameterDescriptionDefault
providerGraph store provider (e.g., “neo4j”)“neo4j”
urlConnection URLenv.NEO4J_URL
usernameAuthentication usernameenv.NEO4J_USERNAME
passwordAuthentication passwordenv.NEO4J_PASSWORD
ParameterDescriptionDefault
providerEmbedding provider”openai”
modelEmbedding model to use”text-embedding-3-small”
apiKeyAPI key for embedding serviceNone
ParameterDescriptionDefault
historyDbPathPath to the history database”/history.db”
versionAPI version”v1.0”
customPromptCustom prompt for memory processingNone
ParameterDescriptionDefault
providerHistory store provider”sqlite”
configHistory store configurationNone (Defaults to SQLite)
disableHistoryDisable history storefalse
const config = {
      version: 'v1.1',
      embedder: {
        provider: 'openai',
        config: {
          apiKey: process.env.OPENAI_API_KEY || '',
          model: 'text-embedding-3-small',
        },
      },
      vectorStore: {
        provider: 'memory',
        config: {
          collectionName: 'memories',
          dimension: 1536,
        },
      },
      llm: {
        provider: 'openai',
        config: {
          apiKey: process.env.OPENAI_API_KEY || '',
          model: 'gpt-4-turbo-preview',
        },
      },
      historyStore: {
        provider: 'supabase',
        config: {
          supabaseUrl: process.env.SUPABASE_URL || '',
          supabaseKey: process.env.SUPABASE_KEY || '',
          tableName: 'memories',
        },
      },
      disableHistory: false, // This is false by default
      customPrompt: "I'm a virtual assistant. I'm here to help you with your queries.",
    }
If you have any questions, please feel free to reach out to us using one of the following methods:

Telegram

Join our community

GitHub

Ask questions on GitHub

Support

Talk to founders