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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
User Profile-Based Long-Term Memory for AI Chatbot Applications.
| Date | Stars |
|---|---|
| 2026-07-24 | 2789 |
| 2026-07-25 | 2791 |
| 2026-07-28 | 2791 |
| 2026-07-30 | 2791 |
| 2026-08-06 | 2791 |
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<div align="center">
<a href="https://memobase.io">
<picture>
<img alt="Memobase logo" src="./assets/images/logo.png" width="80%">
</picture>
</a>
<h1>Memobase</h1>
<p>
<a href="https://pypi.org/project/memobase/">
<img src="https://img.shields.io/pypi/v/memobase.svg">
</a>
<a href="https://www.npmjs.com/package/@memobase/memobase">
<img src="https://img.shields.io/npm/v/@memobase/memobase.svg?logo=npm&logoColor=fff&style=flat&labelColor=2C2C2C&color=28CF8D">
</a>
<a href="https://jsr.io/@memobase/memobase">
<img src="https://img.shields.io/jsr/v/@memobase/memobase.svg?logo=jsr&logoColor=fff&style=flat&labelColor=2C2C2C&color=28CF8D" />
</a>
<a href="https://pkg.go.dev/github.com/memodb-io/memobase/src/client/memobase-go">
<img src="https://img.shields.io/badge/go-reference-blue?logo=go&logoColor=fff&style=flat&labelColor=2C2C2C&color=28CF8D" />
</a>
<a href="./src/mcp">
<img src="https://img.shields.io/badge/MCP-Memobase-green">
</a>
</p>
<p>
<a href="https://github.com/memodb-io/memobase/actions/workflows/publish.yaml">
<img src="https://github.com/memodb-io/memobase/actions/workflows/publish.yaml/badge.svg">
</a>
<a href="https://github.com/orgs/memodb-io/packages?repo_name=memobase">
<img src="https://img.shields.io/github/v/tag/memodb-io/memobase">
</a>
</p>
<p>
<a href="https://app.memobase.io/playground">
<img src="https://img.shields.io/badge/Memobase-Playground-blue">
</a>
<a href="https://discord.gg/YdgwU4d9NB">
<img src="https://dcbadge.limes.pink/api/server/YdgwU4d9NB?style=flat">
</a>
</p>
</div>
## News
- 🚀 Meet [Acontext](https://github.com/memodb-io/Acontext), Context Data Platform that Improves your Agent with Experiences.
Memobase is a **user profile-based memory system** designed to bring long-term user memory to your LLM applications. Whether you're building virtual companions, educational tools, or personalized assistants, Memobase empowers your AI to **remember**, **understand**, and **evolve** with your users.
Memobase offers the perfect balance for your product among various memory solutions. At Memobase, we focus on three key metrics simultaneously:
- **Performance**: Although Memobase is not specifically designed for RAG/search tasks, it still achieves top-tier search performance in the LOCOMO benchmark.
- **LLM Cost**: Memobase includes a built-in buffer for each user to batch-process their chats, allowing the overhead to be distributed efficiently. Additionally, we carefully design our prompts and workflows, ensuring there are no "agents" in the system that could lead to excessive costs.
- **Latency**: Memobase works similarly to the memory system behind ChatGPT: for each user, there is always a user profile and event timeline available. This allows you to access the most important memories of a user without any pre-processing, but only few SQL operations, keeping online latency under 100ms.
Check out the profile [result](./docs/experiments/900-chats/readme.md) (compared with [mem0](https://github.com/mem0ai/mem0)) from a 900-turns real-world chatting:
<details>
<summary>Partial Profile Output</summary>
```python
{
"basic_info": {
"language_spoken": ["English", "Korean"],
"name": "오*영"
},
"demographics": {
"marital_status": "married"
},
"education": {
"notes": "Had an English teacher who emphasized capitalization rules during school days",
"major": "국어국문학과 (Korean Language and Literature)"
},
"interest": {
"games": "User is interested in Cyberpunk 2077 and wants to create a game better than it",
"youtube_channels": "Kurzgesagt",
...
},
"psychological": {...},
"work": {"working_industry": ..., "title": ..., },
...
}
```
</details>
## 🎉 Recent Updates
- `0.0.40`: we updated the internal workflows in Memobase, reducing the number of LLM calls in a single run from apExcerpt of 14,560 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:30c7a0870641ab63, topic:rag, topic:memory, desc:long-term memory
matched fp:30c7a0870641ab63, topic:chatgpt, desc:chatbot, readme:playground
