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evermind-ai-everos

stakeswky/EverMemOS-LocalFirst

Otheropenclawby stakeswky

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Summary

OpenClaw plugin exposing 0 skills.

Install to Claude Code

openclaw plugin add stakeswky/EverMemOS-LocalFirst

Run in Claude Code. Add the marketplace first with /plugin marketplace add stakeswky/EverMemOS-LocalFirst if you haven't already.

README.md

![banner-gif][banner-gif]

[![][arxiv-badge]][arxiv-link] [![Python][python-badge]][python] [![Docker][docker-badge]][docker] [![FastAPI][fastapi-badge]][fastapi] [![MongoDB][mongodb-badge]][mongodb] [![Elasticsearch][elasticsearch-badge]][elasticsearch] [![Milvus][milvus-badge]][milvus] [![Ask DeepWiki][deepwiki-badge]][deepwiki] [![License][license-badge]][license]

<p><strong>Share EverMemOS Repository</strong></p>

[![][share-x-shield]][share-x-link] [![][share-linkedin-shield]][share-linkedin-link] [![][share-reddit-shield]][share-reddit-link] [![][share-telegram-shield]][share-telegram-link]

[Documentation][documentation] • [API Reference][api-docs] • [Demo][demo-section]

[![English][lang-en-badge]][lang-en-readme] [![简体中文][lang-zh-badge]][lang-zh-readme]

</div>

<br>

[![Memory Genesis Competition 2026][competition-image]][competition-link]

> [!IMPORTANT] > > ### Memory Genesis Competition 2026 > > Join our AI [Memory Competition][competition-link]! Build innovative applications, plugins, or infrastructure improvements powered by EverMemOS. > > Tracks: > - Agent + Memory - Build intelligent agents with long-term, evolving memories > - Platform Plugins - Integrate EverMemOS with VSCode, Chrome, Slack, Notion, LangChain, and more > - OS Infrastructure - Optimize core functionality and performance > > [Get Started with the Competition Starter Kit][starter-kit] > > Join our [Discord][discord] to ask anything you want. AMA session is open to everyone and occurs biweekly.

<br>

<!-- <details> <summary><kbd>Table of Contents</kbd></summary>

<br>

[Welcome to EverMemOS][welcome]
[Introduction][introduction]
[Star and stay tuned with us][star-us]
[Why EverMemOS][why-evermemos]
[Quick Start][quick-start]
[Prerequisites][prerequisites]
[Installation][installation]
[API Usage][api-usage]
[Demo][demo-section]
[Run the Demo][run-demo]
[Full Demo Experience][full-demo-experience]
[Evaluation][evaluation-section]
[Documentation][docs-section]
[GitHub Codespaces][codespaces]
[Questions][questions-section]
[Contributing][contributing]

<br>

</details> -->

Welcome to EverMemOS

Welcome to EverMemOS! Join our community to help improve the project and collaborate with talented developers worldwide.

<br>

Use Cases

[![EverMind + OpenClaw Agent Memory and Plugin][usecase-openclaw-image]][usecase-openclaw-link]

EverMind + OpenClaw Agent Memory and Plugin

Claw is putting the pieces of his memory together. Imagine a 24/7 agent with continuous learning memory that you can carry with you wherever you go next. Check out the [agent_memory][usecase-openclaw-link] branch and the [plugin][usecase-openclaw-plugin-link] for more details.

![divider][divider-light] ![divider][divider-dark]

<br>

[![Live2D Character with Memory][usecase-live2d-image]][usecase-live2d-link]

Live2D Character with Memory

Add long-term memory to your anime character that can talk to you in real-time powered by [TEN Framework][ten-framework-link]. See the [Live2D Character with Memory Example][usecase-live2d-link] for more details.

![divider][divider-light] ![divider][divider-dark]

<br>

[![Computer-Use with Memory][usecase-computer-image]][usecase-computer-link]

Computer-Use with Memory

Use computer-use to launch screenshot to do analysis all in your memory. See the [live demo][usecase-computer-link] for more details.

![divider][divider-light] ![divider][divider-dark]

<br>

[![Game of Thrones Memories][usecase-got-image]][usecase-got-link]

Game of Thrones Memories

A demonstration of AI memory infrastructure through an interactive Q&A experience with "A Game of Thrones". See the [code][usecase-got-link] for more details.

![divider][divider-light] ![divider][divider-dark]

<br>

[![EverMemOS Claude Code Plugin][usecase-claude-image]][usecase-claude-link]

EverMemOS Claude Code Plugin

Persistent memory for Claude Code. Automatically saves and recalls context from past coding sessions. See the [code][usecase-claude-link] for more details.

![divider][divider-light] ![divider][divider-dark]

<br>

[![Visualize Memories with Graphs][usecase-graph-image]][usecase-graph-link]

Visualize Memories with Graphs

Memory Graph view that visualizes your stored entities and how they relate. This is a pure frontend demo which has not been plugged into the backend yet, and we are working on it. See the [live demo][usecase-graph-link].

<!-- ## Introduction

> 💬 More than memory — it's foresight.

EverMemOS enables AI to not only remember what happened, but understand the meaning behind memories and use them to guide decisions. Achieving 93% reasoning accuracy on the LoCoMo benchmark, EverMemOS provides long-term memory capabilities for conversational AI agents through structured extraction, intelligent retrieval, and progressive profile building.

![EverMemOS Architecture Overview][overview-image]

How it works: EverMemOS extracts structured memories from conversations (Encoding), organizes them into episodes and profiles (Consolidation), and intelligently retrieves relevant context when needed (Retrieval).

📄 [Paper][paper-link] • 📚 [Vision & Overview][overview-doc] • 🏗️ [Architecture][architecture-doc] • 📖 [Full Documentation][full-docs]

Latest: v1.2.0 with API enhancements + DB efficiency improvements ([Changelog][changelog-doc])

<br>

Why EverMemOS?

🎯 93% Accuracy - Best-in-class performance on LoCoMo benchmark
🚀 Production Ready - Enterprise-grade with Milvus vector DB, Elasticsearch, MongoDB, and Redis
🔧 Easy Integration - Simple REST API, works with any LLM
📊 Multi-Modal Memory - Episodes, facts, preferences, relations
🔍 Smart Retrieval - BM25, embeddings, or agentic search

![EverMemOS Overall Benchmark Results][benchmark-summary-image]

EverMemOS outperforms existing memory systems across all major benchmarks -->

[![][back-to-top]][readme-top]

</div>

Quick Start

Prerequisites

Python 3.10+ • Docker 20.10+ • uv package manager • 4GB RAM

Verify Prerequisites:

# Verify you have the required versions
python --version  # Should be 3.10+
docker --version  # Should be 20.10+

Installation

# 1. Clone and navigate
git clone https://github.com/EverMind-AI/EverMemOS.git
cd EverMemOS

# 2. Start Docker services
docker compose up -d

# 3. Install uv and dependencies
curl -LsSf https://astral.sh/uv/install.sh | sh
uv sync

# 4. Configure API keys
cp env.template .env
# Edit .env and set:
#   - LLM_API_KEY (for memory extraction)
#   - VECTORIZE_API_KEY (for embedding/rerank)

# 5. Start server
uv run python src/run.py

# 6. Verify installation
curl http://localhost:1995/health
# Expected response: {"status": "healthy", ...}

✅ Server running at http://localhost:1995 • [Full Setup Guide][setup-guide]

[![][back-to-top]][readme-top]

</div>

Basic Usage

Store and retrieve memories with simple Python code:

import requests

API_BASE = "http://localhost:1995/api/v1"

# 1. Store a conversation memory
requests.post(f"{API_BASE}/memories", json={
    "message_id": "msg_001",
    "create_time": "2025-02-01T10:00:00+00:00",
    "sender": "user_001",
    "content": "I love playing soccer on weekends"
})

# 2. Search for relevant memories
response = requests.get(f"{API_BASE}/memories/search", json={
    "query": "What sports does the user like?",
    "user_id": "user_001",
    "memory_types": ["episodic_memory"],
    "retrieve_method": "hybrid"
})

result = response.json().get("result", {})
for memory_group in result.get("memories", []):
    print(f"Memory: {memory_group}")

📖 [More Examples][usage-examples] • 📚 [API Reference][api-docs] • 🎯 [Interactive Demos][interactive-demos]

[![][back-to-top]][readme-top]

</div>

Demo

Run the Demo

# Terminal 1: Start the API server
uv run python src/run.py

# Terminal 2: Run the simple demo
uv run python src/bootstrap.py demo/simple_demo.py

Try it now: Follow the [Demo Guide][interactive-demos] for step-by-step instructions.

Full Demo Experience

# Extract memories from sample data
uv run python src/bootstrap.py demo/extract_memory.py

# Start interactive chat with memory
uv run python src/bootstrap.py demo/chat_with_memory.py

See the [Demo Guide][interactive-demos] for details.

[![][back-to-top]][readme-top]

</div>

Advanced Techniques

[Group Chat Conversations][group-chat-guide] - Combine messages from multiple speakers
[Conversation Metadata Control][metadata-control-guide] - Fine-grained control over conversation context
[Memory Retrieval Strategies][retrieval-strategies-guide] - Lightweight vs Agentic retrieval modes
[Batch Operations][batch-operations-guide] - Process multiple messages efficiently

[![][back-to-top]][readme-top]

</div>

Documentation

| Guide | Description | | ----- | ----------- | | [Quick Start][getting-started] | Installation and configuration | | [Configuration Guide][config-guide] | Environment variables and services | | [API Usage Guide][api-usage-guide] | Endpoints and data formats | | [Development Guide][dev-guide] | Architecture and best practices | | [Memory API][memory-api-doc] | Complete API reference | | [Demo Guide][demo-guide] | Interactive examples | | [Evaluation Guide][evaluation-guide] | Benchmark testing |

[![][back-to-top]][readme-top]

</div>

Evaluation & Benchmarking

EverMemOS achieves 93% overall accuracy on the LoCoMo benchmark, outperforming comparable memory systems.

Benchmark Results

![EverMemOS Benchmark Results][benchmark-image]

Supported Benchmarks

[LoCoMo][locomo-link] - Long-context memory benchmark with single/multi-hop reasoning
[LongMemEval][longmemeval-link] - Multi-session conversation evaluation
[PersonaMem][personamem-link] - Persona-based memory evaluation

Quick Start

# Install evaluation dependencies
uv sync --group evaluation

# Run smoke test (quick verification)
uv run python -m evaluation.cli --dataset locomo --system evermemos --smoke

# Run full evaluation
uv run python -m evaluation.cli --dataset locomo --system evermemos

# View results
cat evaluation/results/locomo-evermemos/report.txt

📊 [Full Evaluation Guide][evaluation-guide] • 📈 [Complete Results][evaluation-results-link]

[![][back-to-top]][readme-top]

</div>

GitHub Codespaces

EverMemOS supports [GitHub Codespaces][codespaces-link] for cloud-based development. This eliminates the need to set up Docker, manage local network configurations, or worry about environment compatibility issues.

[![Open in GitHub Codespaces][codespaces-badge]][codespaces-project-link]

![divider][divider-light] ![divider][divider-dark]

Requirements

| Machine Type | Status | Notes | | ------------ | ------ | ----- | | 2-core (Free tier) | ❌ Not supported | Insufficient resources for infrastructure services | | 4-core | ✅ Minimum | Works but may be slow under load | | 8-core | ✅ Recommended | Good performance with all services | | 16-core+ | ✅ Optimal | Best for heavy development workloads |

> Note: If your company provides GitHub Codespaces, hardware limitations typically will not be an issue since enterprise plans often include access to larger machine types.

Getting Started with Codespaces

1. Click the "Open in GitHub Codespaces" button above 2. Select a 4-core or larger machine when prompted 3. Wait for the container to build and services to start 4. Update API keys in .env (LLM_API_KEY, VECTORIZE_API_KEY, etc.) 5. Run make run to start the server

All infrastructure services (MongoDB, Elasticsearch, Milvus, Redis) start automatically and are pre-configured to work together.

[![][back-to-top]][readme-top]

</div>

Questions

EverMemOS is available on these AI-powered Q&A platforms. They can help you find answers quickly and accurately in multiple languages, covering everything from basic setup to advanced implementation details.

| Service | Link | | ------- | ---- | | DeepWiki | [![Ask DeepWiki][deepwiki-badge]][deepwiki] |

[![][back-to-top]][readme-top]

</div>

<br>

🌟 Star and stay tuned with us

![star us gif][star-gif]

[![][back-to-top]][readme-top]

</div>

Contributing

We love open-source energy! Whether you are squashing bugs, shipping features, sharpening docs, or just tossing in wild ideas, every PR moves EverMemOS forward. Browse [Issues][issues-link] to find your perfect entry point, then show us what you have got. Let us build the future of memory together.

<br>

> [!TIP] > > Welcome all kinds of contributions 🎉 > > Join us in building EverMemOS better! Every contribution makes a difference, from code to documentation. Share your projects on social media to inspire others! > > Connect with one of the EverMemOS maintainers [@elliotchen200][elliot-x-link] on 𝕏 or [@cyfyifanchen][cyfyifanchen-link] on GitHub for project updates, discussions, and collaboration opportunities.

![divider][divider-light] ![divider][divider-dark]

Code Contributors

[![EverMemOS Contributors][contributors-image]][contributors]

![divider][divider-light] ![divider][divider-dark]

Contribution Guidelines

Read our [Contribution Guidelines][contributing-doc] for code standards and Git workflow.

![divider][divider-light] ![divider][divider-dark]

License & Citation & Acknowledgments

[Apache 2.0][license] • [Citation][citation-doc] • [Acknowledgments][acknowledgments-doc]

<br>

[![][back-to-top]][readme-top]

</div>

[readme-top]: #readme-top [welcome]: #welcome-to-evermemos [introduction]: #introduction [why-evermemos]: #why-evermemos [quick-start]: #quick-start [prerequisites]: #prerequisites [installation]: #installation [codespaces]: #github-codespaces [run-demo]: #run-the-demo [full-demo-experience]: #full-demo-experience [api-usage]: #api-usage [evaluation-section]: #evaluation--benchmarking [docs-section]: #documentation [questions-section]: #questions [contributing]: #contributing [demo-section]: #demo

[divider-light]: https://github.com/user-attachments/assets/2e2bbcc6-e6d8-4227-83c6-0620fc96f761#gh-light-mode-only [divider-dark]: https://github.com/user-attachments/assets/d57fad08-4f49-4a1c-bdfc-f659a5d86150#gh-dark-mode-only

[banner-gif]: https://github.com/user-attachments/assets/f661bf5b-9942-4142-8310-9d4c5cc57924 [competition-image]: https://github.com/user-attachments/assets/739a0939-ab1d-4659-81c4-0842466afde9 [usecase-openclaw-image]: https://github.com/user-attachments/assets/0e06da2b-0236-430f-89b4-980b8b6a855f [usecase-live2d-image]: https://github.com/user-attachments/assets/a80bdab3-e5d0-43b9-9e8d-0a9605012a26 [usecase-computer-image]: https://github.com/user-attachments/assets/0d306b4c-bcd7-4e9e-a244-22fa3cb7b727 [usecase-got-image]: https://github.com/user-attachments/assets/d1efe507-4eb7-4867-8996-457497333449 [usecase-claude-image]: https://github.com/user-attachments/assets/b40b2241-b0e6-4fc9-9a35-92139f3a2d81 [usecase-graph-image]: https://github.com/user-attachments/assets/6586e647-dd5f-4f9f-9b26-66f930e8241c [overview-image]: figs/overview.png [benchmark-image]: figs/benchmark_2.png [benchmark-summary-image]: https://github.com/user-attachments/assets/a6ff7523-db24-40f5-96ab-aa94f41b2392 [star-gif]: https://github.com/user-attachments/assets/0c512570-945a-483a-9f47-8e067bd34484

[arxiv-badge]: https://img.shields.io/badge/arXiv-EverMemOS_Paper-F5C842?labelColor=gray&style=flat-square&logo=arxiv&logoColor=white [license-badge]: https://img.shields.io/badge/License-Apache%202.0-blue?labelColor=gray&labelColor=F5C842&style=flat-square

[python-badge]: https://img.shields.io/badge/Python-3.10+-blue?labelColor=gray&style=flat-square&logo=python&logoColor=white&labelColor=F5C842 [docker-badge]: https://img.shields.io/badge/Docker-Supported-4A90E2?labelColor=gray&style=flat-square&logo=docker&logoColor=white&labelColor=F5C842 [fastapi-badge]: https://img.shields.io/badge/FastAPI-Latest-26A69A?labelColor=gray&style=flat-square&logo=fastapi&logoColor=white&labelColor=F5C842 [mongodb-badge]: https://img.shields.io/badge/MongoDB-7.0+-00C853?labelColor=gray&style=flat-square&logo=mongodb&logoColor=white&labelColor=F5C842 [elasticsearch-badge]: https://img.shields.io/badge/Elasticsearch-8.x-0084FF?labelColor=gray&style=flat-square&logo=elasticsearch&logoColor=white&labelColor=F5C842 [milvus-badge]: https://img.shields.io/badge/Milvus-2.4+-00A3E0?labelColor=gray&style=flat-square&labelColor=F5C842

[lang-en-badge]: https://img.shields.io/badge/English-lightgrey?style=flat-square [lang-zh-badge]: https://img.shields.io/badge/简体中文-lightgrey?style=flat-square

[discord-members-badge]: https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Fv10%2Finvites%2FgYep5nQRZJ%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&suffix=%20members&label=Discord&color=404EED&style=for-the-badge&logo=discord&logoColor=white [hugging-face-badge]: https://img.shields.io/badge/Hugging_Face-EverMind-F5C842?style=flat&logo=huggingface&logoColor=white [x-badge]: https://img.shields.io/badge/X/Twitter-EverMind-000000?style=flat&logo=x&logoColor=white [linkedin-badge]: https://img.shields.io/badge/LinkedIn-EverMind-0A66C2?style=flat&logo=linkedin&logoColor=white [reddit-badge]: https://img.shields.io/badge/Reddit-EverMind-FF4500?style=flat&logo=reddit&logoColor=white [wechat-badge]: https://img.shields.io/badge/WeChat-EverMind%20社区-07C160?style=for-the-badge&logo=wechat&logoColor=white

[deepwiki-badge]: https://deepwiki.com/badge.svg

[back-to-top]: https://img.shields.io/badge/-Back_to_top-gray?style=flat-square [codespaces-badge]: https://github.com/codespaces/badge.svg

[arxiv-link]: https://arxiv.org/abs/2601.02163 [python]: https://www.python.org/ [docker]: https://www.docker.com/ [fastapi]: https://fastapi.tiangolo.com/ [mongodb]: https://www.mongodb.com/ [elasticsearch]: https://www.elastic.co/elasticsearch/ [milvus]: https://milvus.io/ [license]: https://github.com/EverMind-AI/EverMemOS/blob/main/LICENSE [documentation]: docs/ [api-docs]: docs/api_docs/memory_api.md [lang-en-readme]: README.md [lang-zh-readme]: README.zh.md [competition-link]: https://luma.com/n88icl03 [starter-kit]: docs/STARTER_KIT.md [discord]: https://discord.gg/gYep5nQRZJ [wechat]: https://github.com/EverMind-AI/EverMemOS/discussions/67 [deepwiki]: https://deepwiki.com/EverMind-AI/EverMemOS [usecase-openclaw-link]: https://github.com/EverMind-AI/EverMemOS/tree/agent_memory [usecase-openclaw-plugin-link]: https://github.com/EverMind-AI/EverMemOS/tree/agent_memory/evermemos-openclaw-plugin [ten-framework-link]: https://github.com/TEN-framework/ten-framework [usecase-live2d-link]: https://github.com/TEN-framework/ten-framework/tree/main/ai_agents/agents/examples/voice-assistant-with-EverMemOS [usecase-computer-link]: https://screenshot-analysis-vercel.vercel.app/ [usecase-got-link]: https://github.com/EverMind-AI/evermem_got_demo [usecase-claude-link]: https://github.com/EverMind-AI/evermem-claude-code [usecase-graph-link]: https://main.d2j21qxnymu6wl.amplifyapp.com/graph.html [paper-link]: https://arxiv.org/abs/2601.02163 [overview-doc]: docs/OVERVIEW.md [architecture-doc]: docs/ARCHITECTURE.md [full-docs]: docs/ [changelog-doc]: docs/CHANGELOG.md [setup-guide]: docs/installation/SETUP.md [usage-examples]: docs/usage/USAGE_EXAMPLES.md [interactive-demos]: docs/usage/DEMOS.md [group-chat-guide]: docs/advanced/GROUP_CHAT_GUIDE.md [metadata-control-guide]: docs/advanced/METADATA_CONTROL.md [retrieval-strategies-guide]: docs/advanced/RETRIEVAL_STRATEGIES.md [batch-operations-guide]: docs/usage/BATCH_OPERATIONS.md [getting-started]: docs/dev_docs/getting_started.md [config-guide]: docs/usage/CONFIGURATION_GUIDE.md [api-usage-guide]: docs/dev_docs/api_usage_guide.md [dev-guide]: docs/dev_docs/development_guide.md [memory-api-doc]: docs/api_docs/memory_api.md [demo-guide]: demo/README.md [evaluation-guide]: evaluation/README.md [locomo-link]: https://github.com/snap-research/locomo [longmemeval-link]: https://huggingface.co/datasets/xiaowu0162/longmemeval-cleaned [personamem-link]: https://huggingface.co/datasets/bowen-upenn/PersonaMem [evaluation-results-link]: https://huggingface.co/datasets/EverMind-AI/EverMemOS_Eval_Results [codespaces-link]: https://github.com/features/codespaces [codespaces-project-link]: https://codespaces.new/EverMind-AI/EverMemOS [issues-link]: https://github.com/EverMind-AI/EverMemOS/issues [elliot-x-link]: https://x.com/elliotchen200 [cyfyifanchen-link]: https://github.com/cyfyifanchen [contributors-image]: https://contrib.rocks/image?repo=EverMind-AI/EverMemOS [contributors]: https://github.com/EverMind-AI/EverMemOS/graphs/contributors [contributing-doc]: CONTRIBUTING.md [citation-doc]: docs/CITATION.md [acknowledgments-doc]: docs/ACKNOWLEDGMENTS.md [hugging-face]: https://huggingface.co/EverMind-AI [x]: https://x.com/EverMindAI [linkedin]: https://www.linkedin.com/company/ai-evermind [reddit]: https://www.reddit.com/r/EverMindAI/

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