hyperspace-memory (Python) 🚀

Drop-in replacement for Mem0, Zep, and MemGPT powered by the HyperspaceDB native memory engine with 1-bit ADC quantization, MRL in-RAM cascades, and Lorentz hyperbolic spaces.

⚡ Key Advantages over Mem0 & Zep

• 100x Lower Search Latency: Sub-millisecond (< 0.5 ms) retrieval via MRL in-RAM cascade indexing.
• 98% RAM & Storage Reduction: Native extreme 1-bit ADC and turbo 4-bit Lloyd-Max quantization (compressed down to ~100B per vector).
• Zero Extra LLM Calls: Direct vector and graph traversal memory operations without forcing expensive LLM parsing for every insert.
• 100% Mem0 API Compatibility: Replace from mem0 import Memory with from hyperspace_memory import Memory without altering your application code.

📦 Installation

pip install hyperspace-memory

🛠 Quick Start (Mem0 Drop-In Migration)

from hyperspace_memory import Memory

# 1. Initialize Memory (connects to HyperspaceDB)
memory = Memory(config={
    "host": "the.yar.ink",
    "api_key": "YOUR_YARINK_API_KEY",
    "quantization": "medium_plus"  # "none" | "medium_plus" | "turbo" | "extreme"
})

# 2. Add Memory
res = memory.add(
    "User prefers Rust and dark mode UI over Python and light mode.",
    user_id="user_123",
    metadata={"category": "preferences"}
)
print("Added Memory:", res)

# 3. Search Memory
results = memory.search("What programming language does the user prefer?", user_id="user_123", limit=3)
for item in results:
    print(f"Memory: {item['memory']} (Score: {item['score']})")

# 4. Get All Memories for User
all_memories = memory.get_all(user_id="user_123")

# 5. Delete & Reset
memory.delete(results[0]["id"])

📄 License

MIT © YARlabs.