dsh-mnemosyne

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A DeepSeek Harness plugin for Mnemosyne — local-first, SQLite-backed cross-session memory.

Local-first memory for DSH: remember, recall, and consolidate context across sessions.

About Mnemosyne

Mnemosyne is a zero-cloud, SQLite-backed, local-first AI memory system. One pip install, one SQLite file, no external services required. It uses a BEAM (Bilevel Episodic-Associative Memory) architecture:

• Working Memory — Hot context tier, auto-injected before LLM calls, TTL-based eviction
• Episodic Memory — Long-term storage with sqlite-vec + FTS5 hybrid search (50% vector similarity + 30% FTS5 rank + 20% importance)
• TripleStore — Temporal knowledge graph with version chains

Mnemosyne supports MCP, Python SDK, and multiple agent frameworks (Claude Code, Cursor, Codex, OpenWebUI, Pi, etc.). This plugin integrates it into DSH.

About Pi-mnemosyne

This plugin is ported from @mnemosyne-oss/pi-mnemosyne — the official Pi coding agent extension for Mnemosyne. All memory logic lives in the mnemosyne CLI (pip install mnemosyne-memory), and the plugin stays CLI-first: normal shared-memory operations shell out to the CLI. The port to DSH adds a settings panel, automatic CLI installation, config management, turn-end auto-consolidation, and — beyond the original stateless proxy — a few thin bridges that do not reimplement memory logic: a small Python helper run through the CLI's venv interpreter for session-scoped access, direct-SQLite scope migrations, and an env bridge for the write filter (ignore_patterns / write_classifier).

Features

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