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Documentation Index

Fetch the complete documentation index at: https://docs.mem0.ai/llms.txt

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

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”).

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Usage

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: 
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
        }
    }
}

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Config

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