LM Studio - Mem0 — ContextQMD

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

<CodeGroup> ```python Python 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 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"})

</CodeGroup>

### Running Completely Locally

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

```python
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 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"})

<Note> 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 </Note> <Note> To use LM Studio, you need to: 1. Download and install [LM Studio](https://lmstudio.ai/) 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) </Note>

Config

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