You can use embedding models from Ollama to run Mem0 locally.
import os
from mem0 import Memory
os.environ["OPENAI_API_KEY"] = "your_api_key" # For LLM
config = {
"embedder": {
"provider": "ollama",
"config": {
"model": "mxbai-embed-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 a thriller movies? They can be quite engaging."},
{"role": "user", "content": "Iām 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")
Here are the parameters available for configuring Ollama embedder:
Parameter | Description | Default Value |
---|
model | The name of the OpenAI model to use | nomic-embed-text |
embedding_dims | Dimensions of the embedding model | 512 |
ollama_base_url | Base URL for ollama connection | None |