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 LLM models, you have to set the OPENAI_API_KEY environment variable. You can obtain the OpenAI API key from the OpenAI Platform.

Note: The following are currently unsupported with reasoning models Parallel tool calling,temperature, top_p, presence_penalty, frequency_penalty, logprobs, top_logprobs, logit_bias, max_tokens

Usage

Python

import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your-api-key"

config = {
    "llm": {
        "provider": "openai",
        "config": {
            "model": "gpt-5-mini",
            "temperature": 0.2,
            "max_tokens": 2000,
        }
    }
}

# Use Openrouter by passing its api key
# os.environ["OPENROUTER_API_KEY"] = "your-api-key"
# config = {
#    "llm": {
#        "provider": "openai",
#        "config": {
#            "model": "meta-llama/llama-3.1-70b-instruct",
#        }
#    }
# }

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="alice", metadata={"category": "movies"})

TypeScript

import { Memory } from 'mem0ai/oss';

const config = {
  llm: {
    provider: 'openai',
    config: {
      apiKey: process.env.OPENAI_API_KEY || '',
      model: 'gpt-4-turbo-preview',
      temperature: 0.2,
      maxTokens: 1500,
    },
  },
};

const memory = new Memory(config);
const 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."}\
]
await memory.add(messages, { userId: "alice", metadata: { category: "movies" } });

We also support the new OpenAI structured-outputs model.

import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your-api-key"

config = {
    "llm": {
        "provider": "openai_structured",
        "config": {
            "model": "gpt-5-mini",
            "temperature": 0.0,
        }
    }
}

m = Memory.from_config(config)

Config

All available parameters for the openai config are present in Master List of All Params in Config.