slowave 0.4.8

Brain-inspired long-term memory for AI agents — zero LLM during ingest or retrieval

Slowave

A second brain for your AI, shared across every tool.

Slowave gives your AI tools a central, private, local second-brain that:

• persists across sessions
• persists across tools
• reduce your token usage (~86%)
• evolves over time
• costs 0$ (no LLM in the loop)
• runs on your CPU

┌────────────┐   work with   ┌─────────────┐
│            │ ────────────▶ │ Claude Code │ ◀───┐
│            │               └─────────────┘     │    (mcp)
│    You     │               ┌─────────────┐     │    context         ┌────────────┐
│  (local)   │ ────────────▶ │    Cline    │ ◀───┼──▶ remember  ◀───▶ │  Slowave   │◀──────┐
│            │               └─────────────┘     │    recall          │  (local)   │       │
│            │               ┌─────────────┐     │    procedure       └─────┬──────┘       │
│            │ ────────────▶ │   Cursor    │ ◀───┘    feedback              │ evolves      │
└────────────┘               └─────────────┘                                │ decays       │
                                                                            │ reinforces   │
                                                                            │ consolidates │
                                                                            │ learns       │
                                                                            │ workflows    │
                                                                            └──────────────┘                 

Why Slowave?

👊 One memory, every AI tool.
Claude Code, Cline, Claude Desktop, Cursor, Windsurf, and any MCP-compatible client share the same local memory store. Fix a bug in Claude Code tonight — Cline knows the lesson tomorrow. Decide on an architecture in Claude Desktop — it surfaces in your next coding session. Context follows you across tools instead of dying when you close a chat.

🧠 Adaptive memory, not static notes.
Most AI memory is a pile of Markdown. Slowave behaves more like a brain: frequently recalled memories strengthen, stale ones fade, contradicted facts get superseded automatically. You never manually clean up a MEMORY.md file again.

⚙️ Procedural memory: workflows that stick.
Slowave stores reusable procedures — "how we do deploys in this repo", "steps to implement a new feature across projects" or simply "how this spaghetti recipe should be cooked". Recall them by goal and situation, not by keyword search. Your agents learn habits, not just facts.

🔒 Fully local, zero LLM calls.
Ingestion, consolidation, and recall run on your machine using embeddings, FAISS, and SQLite — no LLM in the memory loop, no API key, no data sent to a cloud memory backend. Memory operations cost $0 per query and work offline.

💰 86% fewer tokens than replaying history.
Slowave injects a compact working-memory brief instead of accumulating the full conversation. Over 20 sessions, raw history grew from 96 → 1,875 tokens while Slowave stayed flat at ~136 tokens — with 95% recall quality (the right memory surfaced in 19/20 sessions). Crossover happens at session 2. Measured with the real semantic encoder, not claimed. See the test →

Install

pipx install slowave
slowave setup           # automated configuration

slowave setup detects your platform, wires every client it finds, injects lifecycle hooks, and starts the background worker. Idempotent and safe to re-run. See what gets modified →

[!IMPORTANT] Claude Desktop: after setup, paste the lifecycle block into Settings → General → Instructions for Claude. Cursor: after setup, paste the lifecycle block into Settings → Rules for AI. slowave setup prints the exact text and location for both. All other clients (Cline, Claude Code, Windsurf) are fully automated.

slowave doctor   # verify installation
slowave stats    # memory snapshot

Memory is stored at ~/.slowave/slowave.db. No Ollama, no vector database, no cloud service required.

Full install guide →

What Slowave remembers

Anything that should survive across sessions: preferences, decisions, constraints, lessons learned, open questions, and reusable workflows — for work, research, or personal use. Each memory carries a timestamp, decays if never recalled, and strengthens when it proves useful. Contradictions are detected geometrically and old facts are superseded automatically — no LLM required.

Memory is scoped flexibly: project:my-app, domain:cooking, relationship:alex — or unscoped for universal context.

Benchmarks

Alpha-stage numbers. Internal runs, not independently verified. See docs/benchmarks.md for per-category results, ablation details, and known gaps.

Numbers from the clean ablation sweep (17 variants, strict sample-size validation, zero LLM calls throughout). Full system = salience reranking + episodic consolidation enabled.

Benchmark	n	Cosine baseline	Full system	Δ	LLM calls
LongMemEval	500	87.6%	87.8%	+0.2 pp (saturation)	0
LoCoMo	1986	72.1%	83.5%	+11.4 pp	0
DMR (MSC Self-Instruct)	500	93.6%	88.0%	−5.6 pp ⚠	0
StaleMemory (concrete attrs)	900	—	86–89% detection	—	0

⚠ DMR note: The full system's −5.6 pp on DMR is a protocol artefact — DMR uses keyword-overlap scoring, which penalises salience reranking and schema consolidation (abstractions that improve recall on conversational queries but reduce raw keyword matches). The cosine-only baseline (93.6%) is the fair DMR headline.

Documentation

docs/design	the brain-inspired rationale behind Slowave
docs/architecture.md	How memory consolidation works
docs/install.md	Install, setup, per-client wiring, troubleshooting
docs/slowave_setup.md	slowave setup command help
docs/manual_setup.md	Step-by-step manual configuration guide
docs/benchmarks.md	Per-category results, known gaps, reproducibility
docs/token_efficiency.md	Token efficiency vs. history replay and static knowledge files
docs/limitations.md	Honest limits: scale, language, unsolved categories
docs/cli.md	CLI reference
docs/dashboard.md	Local web UI (slowave dashboard)

Dashboard

Keep Slowave always under control through the local dahsboard.

You use it, Slowave will start connecting the dots

Contributing

Slowave is open source under AGPL-3.0-or-later. Bug reports, install feedback, and focused improvements are welcome — read CONTRIBUTING.md before opening a PR. Commercial licensing terms may be offered in the future.