OpenAI - Mem0

Documentation Index

Fetch the complete documentation index at: /llms.txt

Use this file to discover all available pages before exploring further.

To use OpenAI embedding models, set the OPENAI_API_KEY environment variable. You can obtain the OpenAI API key from the OpenAI Platform.

Usage

Python

import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your_api_key"

config = {
    "embedder": {
        "provider": "openai",
        "config": {
            "model": "text-embedding-3-large"
        }
    }
}

m = Memory.from_config(config)
messages = [
    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
    {"role": "assistant", "content": "How about 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."
    }
]
m.add(messages, user_id="john")

TypeScript

import { Memory } from 'mem0ai/oss';

const config = {
  embedder: {
    provider: 'openai',
    config: {
      apiKey: 'your-openai-api-key',
      model: 'text-embedding-3-large',
    },
  },
};

const memory = new Memory(config);
await memory.add("I'm visiting Paris", { userId: "john" });

Config

Here are the parameters available for configuring OpenAI embedder:

• Python

• TypeScript