Mem0 with Ollama Locally - Memory Layer for Personalized AI

 This video is a step-by-step easy tutorial to install Mem0 locally and integrate it with Ollama local model.

Code:

conda create -n mem python=3.11 -y && conda activate mem

pip install torch

pip install -U transformers sentencepiece accelerate

pip install sentence_transformers

pip install ollama

pip install mem0ai

import os

from mem0 import Memory

os.environ["OPENAI_API_KEY"] = ""

config = {

    "llm": {

        "provider": "ollama",

        "config": {

            "model": "llama3.1:latest",

            "temperature": 0.1,

            "max_tokens": 2000,

        }

    }

}

m = Memory.from_config(config)

m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})

# Get all memories

all_memories = m.get_all()

print(all_memories)

# Get a single memory by ID

specific_memory = m.get("59565340-c742-4e09-8128-702e810cb4fd")

print(specific_memory)

related_memories = m.search(query="alice hobbies?", user_id="alice")

print(related_memories)

result = m.update(memory_id="59565340-c742-4e09-8128-702e810cb4fd", data="Visited Brisbane in Winter")

print(result)

m.delete(memory_id="59565340-c742-4e09-8128-702e810cb4fd") # Delete a memory

m.delete_all(user_id="alice") # Delete all memories

all_memories = m.get_all()

print(all_memories)