epochdb 0.1.0

An agentic memory engine designed for lossless, tiered verbatim storage and multi-hop retrieval.

EpochDB

EpochDB is an agentic memory engine designed for lossless, tiered verbatim storage and multi-hop retrieval.

Why

I had this idea while playing with LMDB. I wanted to create a memory system that could store conversations in a hybrid way, using in-memory for the most recent conversations and on-disk for older conversations. So, in order to have immutable data, I decided to use Parquet files for the on-disk storage.

Overview

Traditional AI memory systems compress conversations through destructive summarization. EpochDB bypasses this constraint by storing "Unified Memory Atoms"—the raw text intrinsically paired with dense embeddings.

EpochDB uses a tiered architecture reminiscent of CPU caching:

1. L1: Working Memory: Sub-millisecond HNSW vector index in RAM.
2. L2: Historical Archive: Cold storage in immutable, time-partitioned .parquet files via PyArrow.

It uniquely handles multi-hop retrieval over time-partitioned data using a Global Entity Index.

How It Works

See how_it_works.md for a detailed technical dive into the architecture.

Benchmarks & Examples

See benchmark.md for traces of EpochDB successfully integrated via LangGraph. Check out example_langgraph.py for the source code.