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t6_mem0/docs/components/llms/models/gemini.mdx
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---
title: Gemini
---
<Snippet file="paper-release.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": "Im 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).