---
title: Gemini
---

<Snippet file="security-compliance.mdx" />

To use the Gemini model, set the `GEMINI_API_KEY` environment variable. You can obtain the Gemini API key from [Google AI Studio](https://aistudio.google.com/app/apikey).

> **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.

## Usage

```python
import os
from mem0 import Memory

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

config = {
    "llm": {
        "provider": "gemini",
        "config": {
            "model": "gemini-2.0-flash-001",
            "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"})

```

## Config

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