🔐 Mem0 is now SOC 2 and HIPAA compliant! We're committed to the highest standards of data security and privacy, enabling secure memory for enterprises, healthcare, and beyond. Learn more
To use LM Studio with Mem0, you’ll need to have LM Studio running locally with its server enabled. LM Studio provides a way to run local LLMs with an OpenAI-compatible API.

​
Usage

import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your-api-key" # used for embedding model

config = {
    "llm": {
        "provider": "lmstudio",
        "config": {
            "model": "lmstudio-community/Meta-Llama-3.1-70B-Instruct-GGUF/Meta-Llama-3.1-70B-Instruct-IQ2_M.gguf",
            "temperature": 0.2,
            "max_tokens": 2000,
            "lmstudio_base_url": "http://localhost:1234/v1", # default LM Studio API URL
            "lmstudio_response_format": {"type": "json_schema", "json_schema": {"type": "object", "schema": {}}},
        }
    }
}

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="alice", metadata={"category": "movies"})

​
Running Completely Locally

You can also use LM Studio for both LLM and embedding to run Mem0 entirely locally: 
from mem0 import Memory

# No external API keys needed!
config = {
    "llm": {
        "provider": "lmstudio"
    },
    "embedder": {
        "provider": "lmstudio"
    }
}

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="alice123", metadata={"category": "movies"})
When using LM Studio for both LLM and embedding, make sure you have:
  1. An LLM model loaded for generating responses
  2. An embedding model loaded for vector embeddings
  3. The server enabled with the correct endpoints accessible
To use LM Studio, you need to:
  1. Download and install LM Studio
  2. Start a local server from the “Server” tab
  3. Set the appropriate lmstudio_base_url in your configuration (default is usually http://localhost:1234/v1)

​
Config

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