FastEmbed - Mem0 — ContextQMD

You can use FastEmbed to run embedding models locally in Mem0. FastEmbed is an ONNX-based embedding library that runs efficiently on CPU without requiring a GPU or an external API key.

Installation

bash

pip install fastembed

Usage

<CodeGroup> ```python Python import os from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your_api_key" # For LLM

config = { "embedder": { "provider": "fastembed", "config": { "model": "thenlper/gte-large" } } }

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="john")

</CodeGroup>

### Config

Here are the parameters available for configuring FastEmbed embedder:

| Parameter | Description | Default Value |
| --- | --- | --- |
| `model` | The name of the FastEmbed model to use | `thenlper/gte-large` |
| `embedding_dims` | Dimensions of the embedding model (auto-derived from the model if not set) | `None` |