Mem0

个性化人工智能的内存层。『The memory layer for Personalized AI』

Github星跟踪图

Mem0: The Memory Layer for Personalized AI

Mem0 provides a smart, self-improving memory layer for Large Language Models, enabling personalized AI experiences across applications.

Note: The Mem0 repository now also includes the Embedchain project. We continue to maintain and support Embedchain ❤️. You can find the Embedchain codebase in the embedchain directory.

🚀 Quick Start

Installation

pip install mem0ai

Basic Usage

import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "xxx"

# Initialize Mem0
m = Memory()

# Store a memory from any unstructured text
result = m.add("I am working on improving my tennis skills. Suggest some online courses.", user_id="alice", metadata={"category": "hobbies"})
print(result)
# Created memory: Improving her tennis skills. Looking for online suggestions.

# Retrieve memories
all_memories = m.get_all()
print(all_memories)

# Search memories
related_memories = m.search(query="What are Alice's hobbies?", user_id="alice")
print(related_memories)

# Update a memory
result = m.update(memory_id="m1", data="Likes to play tennis on weekends")
print(result)

# Get memory history
history = m.history(memory_id="m1")
print(history)

🔑 Core Features

  • Multi-Level Memory: User, Session, and AI Agent memory retention
  • Adaptive Personalization: Continuous improvement based on interactions
  • Developer-Friendly API: Simple integration into various applications
  • Cross-Platform Consistency: Uniform behavior across devices
  • Managed Service: Hassle-free hosted solution

📖 Documentation

For detailed usage instructions and API reference, visit our documentation at docs.mem0.ai.

🔧 Advanced Usage

For production environments, you can use Qdrant as a vector store:

from mem0 import Memory

config = {
    "vector_store": {
        "provider": "qdrant",
        "config": {
            "host": "localhost",
            "port": 6333,
        }
    },
}

m = Memory.from_config(config)

🗺️ Roadmap

  • Integration with various LLM providers
  • Support for LLM frameworks
  • Integration with AI Agents frameworks
  • Customizable memory creation/update rules
  • Hosted platform support

🙋‍♂️ Support

Join our Slack or Discord community for support and discussions.
If you have any questions, feel free to reach out to us using one of the following methods:

主要指标

概览
名称与所有者mem0ai/mem0
主编程语言Python
编程语言 (语言数: 9)
平台
许可证Apache License 2.0
所有者活动
创建于2023-06-20 08:58:36
推送于2025-04-23 17:27:50
最后一次提交
发布数242
最新版本名称v0.1.93 (发布于 )
第一版名称release (发布于 )
用户参与
星数27.9k
关注者数147
派生数2.7k
提交数1.5k
已启用问题?
问题数807
打开的问题数246
拉请求数1440
打开的拉请求数62
关闭的拉请求数216
项目设置
已启用Wiki?
已存档?
是复刻?
已锁定?
是镜像?
是私有?