---
title: MiniMax
description: "Configure MiniMax as an LLM provider in Mem0 with API key setup and optional custom endpoint configuration."
---

To use MiniMax LLM models, you have to set the `MINIMAX_API_KEY` environment variable. You can also optionally set `MINIMAX_API_BASE` if you need to use a different API endpoint (defaults to "https://api.minimax.io/v1").

## Usage

```python
import os
from mem0 import Memory

os.environ["MINIMAX_API_KEY"] = "your-api-key"
os.environ["OPENAI_API_KEY"] = "your-api-key" # for embedder model

config = {
    "llm": {
        "provider": "minimax",
        "config": {
            "model": "MiniMax-M2.7",  # default model
            "temperature": 0.2,
            "max_tokens": 2000,
            "top_p": 1.0
        }
    }
}

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"})
```

You can also configure the API base URL in the config:

```python
config = {
    "llm": {
        "provider": "minimax",
        "config": {
            "model": "MiniMax-M2.7",
            "minimax_base_url": "https://your-custom-endpoint.com",
            "api_key": "your-api-key"  # alternatively to using environment variable
        }
    }
}
```

## Config

All available parameters for the `minimax` config are present in [Master List of All Params in Config](../config).
