You can use embedding models from LM Studio to run Mem0 locally.

Usage

import os
from mem0 import Memory

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

config = {
    "embedder": {
        "provider": "lmstudio",
        "config": {
            "model": "nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf"
        }
    }
}

m = Memory.from_config(config)
messages = [
    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
    {"role": "assistant", "content": "How about a 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")

Config

Here are the parameters available for configuring Ollama embedder:

ParameterDescriptionDefault Value
modelThe name of the OpenAI model to usenomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf
embedding_dimsDimensions of the embedding model1536
lmstudio_base_urlBase URL for LM Studio connectionhttp://localhost:1234/v1