Python SDK Quickstart - Mem0

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Get started with Mem0’s Python SDK in under 5 minutes. This guide shows you how to install Mem0 and store your first memory.

Prerequisites

• Python 3.10 or higher
• OpenAI API key ( Get one here)

Set your OpenAI API key:

export OPENAI_API_KEY="your-openai-api-key"

Uses OpenAI by default. Want to use Ollama, Anthropic, or local models? See Configuration.

Installation

1. Install via pip

pip install mem0ai

2. Initialize Memory

from mem0 import Memory

m = Memory()

3. Add a memory

messages = [\
    {"role": "user", "content": "Hi, I'm Alex. I love basketball and gaming."},\
    {"role": "assistant", "content": "Hey Alex! I'll remember your interests."}\
]
m.add(messages, user_id="alex")

4. Search memories

results = m.search("What do you know about me?", filters={"user_id": "alex"})
print(results)

Output:

{
  "results": [\
    {\
      "id": "mem_123abc",\
      "memory": "Name is Alex. Enjoys basketball and gaming.",\
      "user_id": "alex",\
      "categories": ["personal_info"],\
      "created_at": "2025-10-22T04:40:22.864647-07:00",\
      "score": 0.89\
    }\
  ]
}

By default Memory() wires up:

• OpenAI gpt-5-mini for fact extraction and updates
• OpenAI text-embedding-3-small embeddings (1536 dimensions)
• Qdrant vector store with on-disk data at /tmp/qdrant
• SQLite history at ~/.mem0/history.db
• No reranker (add one in the config when you need it)

What’s next?

Memory operations \ \ Search, update, and manage memories with the full CRUD API.

Configure for production \ \ Swap in your own LLM, embedder, and vector store.

Add to your framework \ \ Wire Mem0 into LangChain, CrewAI, LangGraph, and 20+ more.

If you have any questions, please feel free to reach out: