genegulanesjr-lapis

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原始内容

LaPis

Persistent memory for the Pi coding agent. LaPis gives Pi a local memory layer for decisions, bugfixes, patterns, indexed code, indexed docs, and session context.

It runs as one Pi extension plus one local Node.js backend. Storage is SQLite by default at ~/.pi/memory/memory.db; there are no cloud dependencies and no API keys.

LaPis banner — persistent memory for the Pi coding agent

Walkthrough

A 30-second tour of the LaPis lifecycle. The GIF below autoplays inline (silent); click it to watch on YouTube with the voiceover.

LaPis 30s walkthrough — gem, memory types, lifecycle, dream, shipping

Source composition lives at repo-media/html-video/lapis-slideshow/index.html — edit the prompts and re-render with npx hyperframes render.

Architecture

LaPis is a modular monolith: one installable Pi extension with clear internal ownership between Pi adapters, CLI routing, feature services, and shared platform/storage code. The same backend also serves an MCP stdio server (lapis mcp) and a Claude Code hooks bridge (lapis claude-code install). The Pi extension calls the backend through in-process dispatch() when possible, with child-process fallback for streaming operations such as indexing.

All three architecture views are interactive HTML — clickable nodes, themeable (light/dark), and animated request paths with marching dashes on highlighted edges.

Architecture overview

The full stack from Pi prompt to SQLite row. Chips animate 3 representative request lifecycles.

👉 Open the architecture overview — Save memory · Recall at start · Index code/docs

Module boundaries

The dependency view. Highlights the layered architecture, peer relationships between feature services, and the trust-sync bridge (the only explicit memory↔code link).

👉 Open the module boundaries diagram — Request flow · Feature peers · Trust bridge

Memory lifecycle

How data moves through the four primary operations into one local SQLite store. The trust path is highlighted in violet to mark it as the only memory↔code bridge.

👉 Open the memory lifecycle diagram — Write · Read · Index · Trust

For dependency rules and module ownership details, see docs/ARCHITECTURE.md and docs/MODULE_MAP.md.

Install

pi install git:github.com/GeneGulanesJr/LaPis

Restart Pi and memory auto-wires on session start. Use pi update --extensions to keep it up to date.

LaPis does not install npm dependencies at runtime. If you are running from a local clone or developing the extension, install dependencies explicitly:

npm install

Use with Claude Code

LaPis also integrates with the Claude Code CLI — same persistent memory, code guardrails, and session lifecycle as the Pi extension, wired through Claude Code's MCP + hooks config.

npx -y @genegulanesjr/lapis claude-code install
npx -y @genegulanesjr/lapis claude-code doctor   # verify install

This writes .mcp.json (MCP tools) and .claude/settings.json (lifecycle hooks). On first use, approve the LaPis MCP server via /mcp in an interactive claude session.

Full setup, hook mapping, troubleshooting, and install flags: docs/CLAUDE_CODE.md.

MCP server (tools only)

For MCP hosts that need LaPis tools without hooks:

npx -y @genegulanesjr/lapis mcp

See docs/MCP.md.

What It Does

  • Remembers across sessions - decisions, bugfixes, patterns, discoveries, and constraints persist.

  • Auto-injects context - new sessions start with relevant memories loaded.

  • Indexes code - web-tree-sitter parses JS/TS/TSX/Go/Python/Rust/SQL for semantic code lookup and analysis.

    LaPis memory-code module

  • Indexes docs - Markdown sections, links, glossary terms, and code examples become searchable.

  • Tracks trust - memories linked to changed code lose confidence; stable linked code recovers trust.

  • Deduplicates memory - similar saves are merged or flagged before they clutter recall.

  • Manages workspaces - project isolation is explicit through create/list/archive workflows.

  • Cleans stale memory - the Dream Cycle removes superseded, never-useful, and replaced memories based on quality signals.

    LaPis dream-cycle module

  • Exposes an HTTP API - optional REST server for programmatic access to missions, milestones, working units, todo/ledger domain, and code analysis.

    LaPis dispatch-flow module — in-process dispatch with child-process fallback

  • Pre-coding intelligence - preflight checks combine memory, code, and docs into before-coding context.

  • Compresses CLI output - token-saving output compression reduces context window usage automatically.

  • Memory dashboard - observability command for memory health, statistics, and index quality.

Benchmarks

Token Efficiency

The wire format (wire-format.js) uses compact encoding to reduce the token footprint of analysis responses inside Pi's context window. The benchmark runs real CLI commands against indexed repos, passes output through compactResponse(), and compares byte sizes.

Run it with:

node bench/bench-tokens.js

Latest local run: May 24, 2026, with fresh reindexes for both repos. call-hierarchy and blast-radius were skipped because the benchmark could not select a representative symbol with callers.

Percentage Saved per Tool

Tool LaPis / PiMemoryExtension PCBuilder
importance 21% 24%
hotspots 0% 0%
dead-code 44% 50%
coupling 37% 40%
extraction 23% 22%
import-graph 18% 20%
cycles 0% 0%
overall 40% 49%

Total Savings

LaPis / PiMemoryExtension PCBuilder
Repo size 292 files / 6,913 symbols 171 files / 207,599 symbols
Raw JSON 692.6 KB 36.7 MB
Compact format 417.5 KB 18.5 MB
Bytes saved 275.1 KB 18.1 MB
Tokens saved ~80,500 tokens ~5,436,007 tokens

See bench/README.md for benchmark usage and interpretation notes.

Paired Memory

The paired benchmark measures whether memory helps by running the same task twice: once with LaPis disabled and once with LaPis active. It is an internal regression and directional benchmark, not a comprehensive external evaluation. It is designed to catch regressions in LaPis behavior; it should not be read as a claim about typical real-world usage, where prompts, repositories, model behavior, provider cache state, and tool choices vary.

Run it with:

npm run bench:pi-paired

Latest run: bench/results/pi-paired-2026-05-24T14-47-20-651Z/report.json

Metric Memory On Without Memory Savings
Facts correct 18/18 18/18 no loss
Active tokens 3,192 42,954 -92.6%
Wall time ~86s ~233s -63.1%
Tool calls 6 49 -87.8%
Failed tools 0 4 -100%

Per-category Breakdown

Category Facts (on) Tokens (on) Savings
prior-decision 3/3 128 99.0%
bug-history 3/3 603 94.2%
staleness 3/3 426 94.2%
navigation 3/3 72 99.0%
negative-control 6/6 1,963 65.7%

What Each Category Tests

Category What it tests
prior-decision Recalls an architectural decision and its rationale, then names the current module involved.
bug-history Recalls why a fix exists, including the historical failure mode that is not obvious from the final code alone.
staleness Checks whether LaPis warns that an indexed code view may be stale and should be verified or reindexed before trust.
navigation Uses memory to jump to the likely hook/module and confirm where extension wiring lives.
negative-control Asks current-source questions that should not need memory facts; memory-on should route cheaply to code lookup instead of adding overhead.

Memory-on achieved perfect accuracy with 92.6% fewer active tokens overall. Memory-dependent tasks saved 94.2-99.0% active tokens in this run.

The paired benchmark also reports behavior counters. In the latest run, memory-on used 6 total tools, 4 code-oriented tools, 4 memory tools, 12 assistant turns, and 0 failed tools. These counters help distinguish real memory regressions from normal provider cache and latency variance. The negative-control tasks are current-source questions; they should avoid memory facts and route quickly through memory-code search plus targeted reads when code verification is needed.

Requirements

  • Node.js
  • better-sqlite3 for local SQLite access
  • No Python dependency
  • No API keys or cloud services

Documentation

License

ISC