@shog-lab/pi-memory

Persistent, inspectable memory as a drop-in pi extension.

A pi extension package that turns any repo into the home of a persistent agent. Memory survives across sessions, accumulates over time, and the agent maintains its own knowledge through a periodic memory-audit.

Inspired by Karpathy's LLM Wiki — knowledge as flat markdown the LLM curates itself.

Why

LLM agents that lose everything between sessions can't accumulate. RAG-only setups see history as searchable chunks but don't learn from contradictions, deprecations, or refinements. pi-mind treats memory as a two-layer system (raw event stream + curated knowledge markdown — the SoT for the KG via the frontmatter triples: field) with a derived SQLite index, gives the agent tools to write/read/lint its own knowledge, and gets out of the way otherwise.

Memory model

Memory lives in $PI_MIND_DIR (default ./.pi-mind in the current repo) with three peer directories:

.pi-mind/
├── raw/    — what happened
│   ├── sessions/      conversation transcripts
│   ├── observations/  things the agent noticed during work
│   ├── compaction/    auto-saved conversation summaries
│   └── maintenance-log/  jsonl trail of internal ops
├── knowledge/   — what's true
│   └── *.md           compiled facts, decisions, concepts (frontmatter + body) + `triples` field (KG SoT)

Two layers plus a derived KG index: raw (append-only event stream), knowledge (compiled markdown — also the SoT for the KG via its triples: frontmatter field), and the KG index (SQLite kg_* tables in .pi-mind/.pi-mind-index.db, rebuilt from frontmatter on every sync). There is no graph/ directory — the KG lives in SQLite, not on disk as a separate file layer.

Install

npm i -D @shog-lab/pi-memory

postinstall symlinks extensions/memory/ and skills/*/ into the host repo's .pi/, then creates the raw/ knowledge/ directories. Idempotent — re-running npm install is safe.

pnpm projects

pnpm may skip dependency lifecycle scripts unless the package is approved for builds (for example via pnpm approve-builds / onlyBuiltDependencies). If .pi/ or .pi-mind/ was not created after install, run the init command manually from your repo root:

INIT_CWD="$PWD" pnpm exec pi-mind-init

Fallback if pnpm exec cannot resolve the bin:

INIT_CWD="$PWD" node node_modules/@shog-lab/pi-memory/bin/init.js

If you also installed @shog-lab/pi-bus, run its init too:

INIT_CWD="$PWD" pnpm exec pi-bus-init
# or: INIT_CWD="$PWD" node node_modules/@shog-lab/pi-bus/bin/init.js

pi-mind declares @earendil-works/pi-coding-agent as a peer dependency. Make sure pi is on PATH (typically via npm i -g @earendil-works/pi-coding-agent — the pi coding-agent runtime).

Quickstart

cd ~/my-repo
npm i -D @shog-lab/pi-memory

pi                          # interactive: memory auto-loaded, system prompt injected
# > "记一下 I prefer pm2 over forever for process management"
# (agent calls remember_this tool → .pi-mind/knowledge/*.md, source: explicit)

pi -p "what do you know about my preferences?"
# (agent retrieves and answers via L1/L2 injection)

npx pi-mind-lint                # validate knowledge schema
npx pi-mind-lint --prune        # dry-run: show what forget would delete
npx pi-mind-lint --prune --apply  # really delete stale memories + raw artifacts

The forget mechanism runs automatically every 50 writes (see Memory maintenance); the manual --prune is for emergency cleanup or audit.

Optional cron for memory-audit (no cron is required; the extension is daemon-free):

0 22 * * * cd /path/to/repo && pi -p "use memory-audit skill" >> .pi-mind/cron.log 2>&1

Frontmatter schema

Knowledge entries have a strict frontmatter:

---
date: 2026-05-08T10:00:00.000Z
type: project
tier: L2
tags: [auth, decision]
triples: [["alice", "owns", "auth-service"]]
---

We chose JWT over sessions because of mobile client constraints.

| Field | Required | Values | Purpose | |---|---|---|---| | date | yes | ISO 8601 | sort, recency boost, staleness check | | type | yes | user / project / agent-feedback / reference / compaction | subject axis — who/what is this about | | tier | yes | L1 / L2 | recall axis — L1 always-injected, L2 retrieved by relevance | | tags | no | string[] | free-form topic keywords (no subject/tier encoding) | | triples | no | [[subject, predicate, object], ...] | structured KG relations | | source | no | explicit / compaction / observe (or any string) | informational — which writer produced this entry. Set by saveMemory; not used by retrieval. | | image | no | relative path under $PI_MIND_DIR (e.g. raw/images/abc.png) | link to a stored image; rendered as ![](../<image>) in the body. |

The type × tier orthogonality is deliberate: any subject can be L1 (high-priority) or L2 (default). See lib/schema.ts for the canonical definitions and LEGACY_TYPE_MAP for migration of old enums.

Page interconnection

Use [[page-name]] to link knowledge entries. When pi retrieves the linker, the linked page is loaded too:

This builds on [[agent-memory]] and supersedes [[old-design-2024]].

Knowledge graph triples

When a memory involves people, schedules, or relationships, add triples. The KG module indexes them for queries like "who owns X" or "when does Y happen":

triples: [["alice", "owns", "auth-service"], ["alice", "role", "backend-lead"]]

Naming convention (the KG index is only as good as the predicate vocabulary — fragmented relations never get joined):

• Entity: canonical lowercase for stable identifiers; preserve natural casing for proper nouns (DeepSeek V4, --rebuild-kg). Multi-word entities use hyphens / underscores (auth-service, ml-model).
• Predicate: snake_case verb phrase. addTriple normalizes spaces to _ on ingest, so uses model and uses_model end up the same — write it snake_case anyway. No copula (is, has), no related_to (pick a direction).
• Direction: pick one. Never mix owns / owner_of / owned_by — that's relation fragmentation.

Good: carol uses_model DeepSeek V4 · pi-memory released_version 0.12.0 · pi-mind-lint supports_flag --rebuild-kg. Bad: x is y · a has b · p related_to q.

Audit the current state at any time:

npx pi-mind-lint --kg-health     # read-only: top predicates, suspicious list, orphan check

The memory-audit skill runs this on every audit. See AGENTS.md (KG naming convention) for the full rationale and the audit policy.

Retrieval

Each turn, the memory extension automatically injects relevant memory into the agent's context, before any tool call:

• L1 entries — always injected (token budget capped, default 2000)
• L2 entries — FTS5 + vector search by relevance to the user's prompt, scored with type-weights (configurable in pi-mind-config.json) and recency boost
• Linked pages — [[link]] resolution pulls in connected entries
• Token budget — total injection capped (default 4000) to leave room for actual reasoning

Configure via a pi-mind-config.json in $PI_MIND_DIR/ (auto-loaded). Defaults live in extensions/memory/core.ts.

Vector search requires Ollama

L2 vector search is powered by the nomic-embed-text model served by a local Ollama daemon (default URL http://localhost:11434, configurable via pi-mind-config.json → embedding.ollamaUrl).

• If Ollama is running with nomic-embed-text pulled — vector search works; new memory entries are embedded as they're indexed.
• If Ollama is down / model not pulled / network unreachable — vector search is automatically skipped and retrieval falls back to FTS5 keyword search. A one-line warning is logged to the agent's stderr ([pi-mind] embedding call failed: ...). Retrieval still works; the agent just sees fewer topically-similar matches.
• Embedding requests are timed out at 5s to avoid blocking the turn on a hung daemon. On timeout the warning reads [pi-mind] embedding timed out after 5000ms ... and FTS5 fallback kicks in.

To install Ollama + the model:

# Install Ollama: see https://ollama.com/download
ollama pull nomic-embed-text
ollama serve   # if not already running as a service

Memory maintenance

Three mechanisms keep memory healthy. None require a daemon — pi-mind has no background process; everything piggybacks on the natural rhythm of agent interaction.

• knowledge-lint — validates frontmatter, finds duplicates, flags stale entries. With --fix it auto-migrates legacy fields. With --prune it deletes age-expired memories + raw artifacts (--prune --apply to actually delete; default is dry-run).
• memory-audit — agent-executed skill: scans the maintenance log, samples LLM decisions, surfaces problems. Triggered by an "audit overdue" notice the extension injects into the agent's context at before_agent_start; the agent decides when to honor it.
• Auto-forget — saveMemory increments a persistent counter (raw/maintenance-log/last-forget.json); every 50 writes the extension runs forgetOldMemories() synchronously and resets. No cron needed.

Retention policy (lib/forget.ts):

| Target | Retention | |---|---| | knowledge/ type=user, project | Never auto-deleted (durable preferences / decisions) | | knowledge/ type=agent-feedback | Frontmatter date > 60 days | | knowledge/ type=reference | Frontmatter date > 90 days | | raw/compaction/*.md | mtime > 30 days | | raw/sessions/<cwd>/*.jsonl | mtime > 14 days; empty cwd-dirs pruned | | raw/maintenance-log/*.jsonl | mtime > 30 days (markers preserved) |

Optional cron — only if you want memory-audit to fire even without an interactive session:

0 22 * * * cd /repo && pi -p "use memory-audit skill" >> .pi-mind/cron.log 2>&1

Composing with other pi packages

pi-mind defines the structure of $PI_MIND_DIR/raw/ but does not own it. Other packages can write to their own subdirectories:

.pi-mind/raw/
├── sessions/         pi-mind: pi session archives
├── compaction/       pi-mind: auto summaries
├── observations/     pi-mind: agent's own notes
└── browser/          pi-chrome: browser task outcomes (if installed)

memory-audit scans the entire raw/ tree, so anything any package writes there gets reviewed automatically. Convention: each package writes only to its own subdirectory and uses the same frontmatter schema. See pi-chrome for an example sibling package.

Benchmarks

The LongMemEval harness moved to a top-level private workspace at eval/longmemeval/ on 2026-06-08. It is internal dev tooling; NOT published — the workspace has private: true and is not in any package's files. Build the memory extension first, then run from the monorepo root:

npm run build --workspace=@shog-lab/pi-memory
npm run eval:longmemeval -- --split oracle --limit 5 --out /tmp/eval-run

The harness bypasses any container or daemon — it spawns pi via spawnPi (from @shog-lab/pi-utils) with an explicit -e path to the compiled memory extension. Scoring has two paths: a TS port of LongMemEval's official get_anscheck_prompt (run with --judge), or feed hypothesis.jsonl to LongMemEval's official Python evaluator. See the eval workspace's README for both pipelines.

History: the harness lived at packages/eval/ (workspace) through 2026-05-26, then packages/core/eval/ through 2026-06-08, then eval/longmemeval/ (private top-level workspace) — always intended as internal tooling; now structurally outside published package artifacts. Each move was a git mv that preserves history.

Architecture

pi process (the runtime)
  ↓ extension load
memory extension initializes:
  - reads .pi-mind/ from disk
  - syncs FTS5 + vector + KG index in .pi-mind/.pi-mind-index.db
    (KG index is rebuilt from frontmatter `triples` fields on every sync;
    frontmatter is the source of truth, the SQLite kg_* tables are a
    derived, rebuildable index)
  - registers hooks: before_agent_start / turn_end / session_compact
  - registers tools: remember_this, observe, recall_memory,
                     update_memory, mark_memory_audit_complete
    (no forget_memory tool — old memories drop via retention policy in
    lib/forget.ts, auto-run every 50 writes; for emergency manual prune
    use the CLI: `npx pi-mind-lint --prune --apply`)
  - injects system-prompt.md into agent context (via pi.injectContext)
  ↓
agent runs:
  - before_agent_start: L1 always-inject + L2 query-relevant retrieval; cache userPrompt
  - turn_end: archive sessions (filtered to this host repo only — see lib/session-archive.ts)
  - on saveMemory (from remember_this / observe): bump persistent counter;
    every 50 writes auto-run forgetOldMemories (mechanical retention policy)
  - session_compact: pi-side summary saved to raw/compaction/ + syncIndex
  ↓ pi process exit
SQLite + filesystem persist, in-memory state cleared

No background memory writers in 0.6.0+ — two were removed for violating the "Memory is passive" design principle (see top-level AGENTS.md):

• the agent_end worth-remembering-llm detector (qwen3:4b via Ollama) that auto-captured high-signal turns; and
• the session_compact fire-and-forget classifier sub-agent ("B-spawn") that promoted each compaction summary into a knowledge/ entry.

Both were lifecycle-triggered LLMs writing curated state with no user in the trigger chain. Compaction summaries are still persisted to raw/compaction/ and remain retrievable on their own (syncIndex scans raw/ as well as knowledge/, so a type: compaction entry is searchable at tier L2 — see getScanDirs). They age out via the normal retention policy unless explicitly promoted into durable knowledge/ via the memory-audit skill, in a visible turn. All curated knowledge now requires explicit remember_this / observe calls (or an audit) in a visible turn.

Key implementation notes:

• Concurrency safety: withGroupLock (proper-lockfile) wraps all multi-step writes (syncIndex, saveMemory, KG mutations). Reentrant via reference counting. SQLite gets busy_timeout = 5000 as a second wall.
• Schema convergence (Plan C): type=subject + tier=recall two-axis design, replacing earlier overlapping type field that conflated both. See lib/schema.ts:LEGACY_TYPE_MAP for documented lossy migrations.
• No double-source for schema: lib/schema.ts is the single source; core.ts and scripts/knowledge-lint.ts both import from it.
• Soft-trigger maintenance: cron + skills + audit log, not exception-throwing CI gates. Agent maintains its own house.

Status

Stable core, active development. @shog-lab/[email protected] is published; this repo dogfoods it (run pi here to see the agent work on its own codebase). 296 tests pass across 18 test files (npm test). Memory model, schema, lint, memory-audit, and forget are stable APIs; smaller surfaces (tools, hooks) may evolve.

Note: @shog-lab/[email protected] is the successor to @shog-lab/[email protected]. The package was renamed on 2026-06-09; the on-disk directory moved from packages/core/ to packages/memory/, the npm name flipped, and the version was bumped (a rename is a breaking surface change for users, hence minor-bump from 0.13.1 → 0.14.0). The CLI binaries (pi-mind-init, pi-mind-lint) are intentionally unchanged to avoid a one-shot break for existing users — the rename is about the npm/distribution surface, not the CLI surface.

Roadmap (no fixed dates):

• [ ] Per-pi-process saveMemory call-site validation (currently relies on TS literal types)
• [ ] Migration of long-running pi-mind users from legacy schemas (handled in lint --fix today)
• [ ] Vector embedding cache to skip re-embed on unchanged content
• [ ] Optional encryption-at-rest for sensitive knowledge entries

License

MIT