---
title: Node.js Guide
description: 'Get started with Mem0 quickly!'
icon: "node"
iconType: "solid"
---

> Welcome to the Mem0 quickstart guide. This guide will help you get up and running with Mem0 in no time.

## Installation

To install Mem0, you can use npm. Run the following command in your terminal:

```bash
npm install mem0ai
```

## Basic Usage

### Initialize Mem0

<Tabs>
  <Tab title="Basic">
```typescript
import { Memory } from 'mem0ai/oss';

const memory = new Memory();
```
  </Tab>
  <Tab title="Advanced">
If you want to run Mem0 in production, initialize using the following method:

```typescript
import { Memory } from 'mem0ai/oss';

const memory = new Memory({
    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',
      },
    },
    historyDbPath: 'memory.db',
  });
```
  </Tab>
</Tabs>


### Store a Memory

<CodeGroup>
```typescript Code
// For a user
const result = await memory.add('Hi, my name is John and I am a software', 'user123');
console.log(result);

// const messages = [
//    {"role": "user", "content": "Hi, I'm Alex. I like to play cricket on weekends."},
//    {"role": "assistant", "content": "Hello Alex! It's great to know that you enjoy playing cricket on weekends. I'll remember that for future reference."}
// ]
// await memory.add(messages, 'user123');
```

```json Output
{
  "results": [
    {
      "id": "c03c9045-df76-4949-bbc5-d5dc1932aa5c",
      "memory": "Name is John",
      "metadata": [Object]
    },
    {
      "id": "cbb1fe73-0bf1-4067-8c1f-63aa53e7b1a4",
      "memory": "Is a software",
      "metadata": [Object]
    }
  ]
}
```
</CodeGroup>

### Retrieve Memories

<CodeGroup>
```typescript Code
// Get all memories
const allMemories = await memory.getAll('user123');
console.log(allMemories)
```

```json Output
{
  "results": [
    {
      "id": "892db2ae-06d9-49e5-8b3e-585ef9b85b8e",
      "memory": "Name is Alex Jones",
      "hash": "1a271c007316c94377175ee80e746a19",
      "createdAt": "2025-02-27T16:33:20.557Z",
      "updatedAt": "2025-02-27T16:33:27.051Z",
      "metadata": {},
      "userId": "user123"
    },
    {
      "id": "475bde34-21e6-42ab-8bef-0ab84474f156",
      "memory": "Likes to play cricket on weekends",
      "hash": "285d07801ae42054732314853e9eadd7",
      "createdAt": "2025-02-27T16:33:20.560Z",
      "updatedAt": undefined,
      "metadata": {},
      "userId": "user123"
    }
  ]
}
```
</CodeGroup>


<br />

<CodeGroup>
```typescript Code
// Get a single memory by ID
const singleMemory = await memory.get('6c1c11a2-4fbc-4a2b-8e8a-d60e67e57aaa');
console.log(singleMemory);
```

```json Output
{
  "id": "6c1c11a2-4fbc-4a2b-8e8a-d60e67e57aaa",
  "memory": "Name is Alex",
  "hash": "d0fccc8fa47f7a149ee95750c37bb0ca",
  "createdAt": "2025-02-27T16:37:04.378Z",
  "updatedAt": undefined,
  "metadata": {},
  "userId": "user123"
}
```
</CodeGroup>

### Search Memories

<CodeGroup>
```typescript Code
const result = await memory.search('What do you know about me?', 'user123');
console.log(result);
```

```json Output
{
  "results": [
    {
      "id": "28c3eee7-186e-4644-8c5d-13b306233d4e",
      "memory": "Name is Alex",
      "hash": "d0fccc8fa47f7a149ee95750c37bb0ca",
      "createdAt": "2025-02-27T16:43:56.310Z",
      "updatedAt": undefined,
      "score": 0.08920719231944799,
      "metadata": {},
      "userId": "user123"
    },
    {
      "id": "f3433da0-45f4-444f-a4bc-59a170890a1f",
      "memory": "Likes to play cricket on weekends",
      "hash": "285d07801ae42054732314853e9eadd7",
      "createdAt": "2025-02-27T16:43:56.314Z",
      "updatedAt": undefined,
      "score": 0.06869761478135689,
      "metadata": {},
      "userId": "user123"
    }
  ]
}
```
</CodeGroup>

### Update a Memory

<CodeGroup>
```typescript Code
const result = await memory.update(
  '6c1c11a2-4fbc-4a2b-8e8a-d60e67e57aaa',
  'I love India, it is my favorite country.',
  'user123'
);
console.log(result);
```

```json Output
{
  "message": "Memory updated successfully!"
}
```
</CodeGroup>

### Memory History

<CodeGroup>
```typescript Code
const history = await memory.history('d2cc4cef-e0c1-47dd-948a-677030482e9e');
console.log(history);
```

```json Output
[
  {
    "id": 39,
    "memory_id": "d2cc4cef-e0c1-47dd-948a-677030482e9e",
    "previous_value": "Name is Alex",
    "new_value": "Name is Alex Jones",
    "action": "UPDATE",
    "created_at": "2025-02-27T16:46:15.853Z",
    "updated_at": "2025-02-27T16:46:20.909Z",
    "is_deleted": 0
  },
  {
    "id": 37,
    "memory_id": "d2cc4cef-e0c1-47dd-948a-677030482e9e",
    "previous_value": null,
    "new_value": "Name is Alex",
    "action": "ADD",
    "created_at": "2025-02-27T16:46:15.853Z",
    "updated_at": null,
    "is_deleted": 0
  }
]
```
</CodeGroup>

### Delete Memory

```typescript
// Delete a memory by id
await memory.delete('bf4d4092-cf91-4181-bfeb-b6fa2ed3061b');

// Delete all memories for a user
await memory.deleteAll('alice');
```

### Reset Memory

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

## Configuration Parameters

Mem0 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.

<AccordionGroup>
<Accordion title="Vector Store Configuration">
| Parameter    | Description                     | Default     |
|-------------|---------------------------------|-------------|
| `provider`   | Vector store provider (e.g., "memory") | "memory"   |
| `host`       | Host address                    | "localhost" |
| `port`       | Port number                     | undefined       |
</Accordion>

<Accordion title="LLM Configuration">
| Parameter              | Description                                   | Provider          |
|-----------------------|-----------------------------------------------|-------------------|
| `provider`            | LLM provider (e.g., "openai", "anthropic")    | All              |
| `model`               | Model to use                                  | All              |
| `temperature`         | Temperature of the model                      | All              |
| `apiKey`             | API key to use                                | All              |
| `maxTokens`          | Tokens to generate                            | All              |
| `topP`               | Probability threshold for nucleus sampling    | All              |
| `topK`               | Number of highest probability tokens to keep  | All              |
| `openaiBaseUrl`     | Base URL for OpenAI API                      | OpenAI           |
</Accordion>

<Accordion title="Embedder Configuration">
| Parameter    | Description                     | Default                      |
|-------------|---------------------------------|------------------------------|
| `provider`   | Embedding provider              | "openai"                     |
| `model`      | Embedding model to use          | "text-embedding-3-small"     |
| `apiKey`    | API key for embedding service   | None                        |
</Accordion>

<Accordion title="General Configuration">
| Parameter         | Description                          | Default                    |
|------------------|--------------------------------------|----------------------------|
| `historyDbPath` | Path to the history database         | "{mem0_dir}/history.db"    |
| `version`         | API version                          | "v1.0"                     |
| `customPrompt`   | Custom prompt for memory processing  | None                       |
</Accordion>

<Accordion title="Complete Configuration Example">
```typescript
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',
        },
      },
      historyDbPath: 'memory.db',
      customPrompt: "I'm a virtual assistant. I'm here to help you with your queries.",
    }
```
</Accordion>
</AccordionGroup>

If you have any questions, please feel free to reach out to us using one of the following methods:

<Snippet file="get-help.mdx" />