mnemara-core 0.1.0

Local-first, explainable AI memory engine for embedded and service-based systems
Documentation

mnemara-core

mnemara-core provides the product-neutral memory domain model, query types, scoring configuration, evaluation helpers, and async store traits that the rest of the Mnemara workspace builds on.

Install

Add the crate to your Rust project with:

cargo add mnemara-core

What it contains

  • MemoryRecord, MemoryScope, MemoryRecordKind, MemoryQualityState, and MemoryTrustLevel
  • RecallQuery, RecallFilters, RecallResult, and recall explanation types
  • BatchUpsertRequest, UpsertRequest, DeleteRequest, and admin operation request and report types
  • EngineConfig, scoring profiles, embedding-provider configuration, and evaluation helpers
  • MemoryStore, the async trait implemented by the file and sled backends

Minimal example

use mnemara_core::{EngineConfig, RecallQuery, RecallScoringProfile};

let mut config = EngineConfig::default();
config.recall_scoring_profile = RecallScoringProfile::Balanced;

let query = RecallQuery {
    query_text: "reconnect storm mitigation".to_string(),
    ..Default::default()
};

Related crates

  • mnemara for the facade crate
  • mnemara-store-file for the file-backed implementation
  • mnemara-store-sled for the embedded sled-backed implementation
  • mnemara-protocol for protobuf and gRPC surface types
  • mnemara-server for the standalone daemon

Project documentation: https://github.com/deliberium/mnemara