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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 the Gemini model, set the GOOGLE_API_KEY environment variable. You can obtain the Google/Gemini API key from Google AI Studio.
Note: As of the latest release, Mem0 uses the new google.genai SDK instead of the deprecated google.generativeai. All message formatting and model interaction now use the updated types module from google.genai.
Note: Some Gemini models are being deprecated and will retire soon. It is recommended to migrate to the latest stable models like "gemini-2.0-flash-001" or "gemini-2.0-flash-lite-001" to ensure ongoing support and improvements.

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Usage

import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your-openai-api-key"  # Used for embedding model
os.environ["GOOGLE_API_KEY"] = "your-gemini-api-key"

config = {
    "llm": {
        "provider": "gemini",
        "config": {
            "model": "gemini-2.0-flash-001",
            "api_key": "your-gemini-api-key",
            "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 thrillers, but I love sci-fi movies."},
    {"role": "assistant", "content": "Got it! I'll avoid thrillers and suggest sci-fi movies instead."}
]

m.add(messages, user_id="alice", metadata={"category": "movies"})

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Config

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