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Brand-new release of memory system api to power various agent applications

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@wangyu-ustc wangyu-ustc released this 25 Dec 18:44
· 126 commits to main since this release
v0.1.6
0f3fbdb

🚀 MIRIX 0.1.6 — Pure Memory System API for Any Agent

This release marks a major evolution of MIRIX.

Starting from v0.1.6, MIRIX becomes a dedicated, plug-and-play advanced memory system that any agent can integrate with — rather than a bundled desktop personal assistant.

With this release, MIRIX now provides:

  • ⚙️ Unified Memory API
  • 🧠 Meta-agent & multi-memory architecture
  • ☁️ Hosted Cloud Memory Service
  • 📊 Web Dashboard for visualization, debugging & control
  • ⚡ Ultra-fast retrieval with hybrid search
  • 🔍 Optional embedding search for deeper reasoning
  • 🔐 Secure API key–based access

✨ What’s New

✅ MIRIX as a Standalone Memory Platform

MIRIX is now designed to act as the long-term memory layer for:

  • LLM agents
  • desktop assistants
  • chatbots
  • automation systems
  • multi-agent systems

Just install and start using:

pip install mirix==0.1.6

☁️ MIRIX Cloud + Dashboard

We now provide:

  • Hosted Cloud Memory Service (no infrastructure needed)
  • Memory Dashboard
    • inspect stored memories
    • search & debug
    • monitor usage
    • manage API keys

Sign up at:
👉 https://app.mirix.io

🔄 Branches & Migration

  • main (≥ v0.1.6) → Pure Memory System (API + Cloud)
  • desktop-agent branch → Legacy Desktop Personal Assistant
    (deprecated, but still available)

The previous desktop personal assistant (frontend + backend) is no longer shipped on main.

If you still need the old integrated desktop app:
👉 switch to desktop-agent branch

🧨 Breaking Changes

  • Desktop personal assistant removed from main
  • API-first architecture introduced
  • Cloud usage requires API key

🧪 Example Usage

Add Memory

client.add(
    messages=[
        {"role": "user", "content": [{"type": "text", "text": "We discussed MirixDB indexing performance"}]},
        {"role": "assistant", "content": [{"type": "text", "text": "Noted, I will remember that"}]},
    ],
)

Retrieve Conversational Memory

memories = client.retrieve_with_conversation(
    messages=[
        {"role": "user", "content":[{"type":"text","text":"What did we discuss recently?"}]},
    ],
)
print(memories)

Deep Embedding Search

client.search(
    memory_type="episodic",
    search_field="summary",
    search_method="embedding"
)

❤️ Thank You

Thanks to everyone supporting MIRIX — this upgrade enables MIRIX to power agents of all kinds while scaling to real-world workloads. Much more is coming 😊

If you’re building with MIRIX, we’d love to hear what you create!

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