pi-memory

Persistent memory for pi. Learns corrections, preferences, and project patterns from sessions and injects them into future conversations.

Features

• Automatic learning — Extracts preferences, project patterns, and corrections from conversations at session end via LLM consolidation
• Context injection — Automatically adds relevant memory into every new session's system prompt
• Corrections stick — Mistakes you correct once become permanent lessons (e.g. "use sed for daily notes, not echo >>")
• Complements session-search — session-search finds what you did, pi-memory remembers what you learned

Install

pi install pi-memory

Or add to ~/.pi/agent/settings.json:

{
  "packages": ["npm:pi-memory"]
}

Memory Types

| Type | Key prefix | Example | |------|-----------|---------| | Preferences | pref.* | pref.commit_style → "conventional commits" | | Project patterns | project.* | project.rosie.di → "Dagger dependency injection" | | Tool preferences | tool.* | tool.sed → "use for daily note insertion" | | User identity | user.* | user.timezone → "US/Pacific" | | Lessons | (table) | "DON'T: use echo >> for vault notes, use sed" |

Tools

| Tool | Description | |------|-------------| | memory_search | Search semantic memory by keyword | | memory_remember | Manually store a fact or lesson | | memory_forget | Delete a fact or lesson | | memory_lessons | List learned corrections | | memory_stats | Show memory statistics |

Commands

| Command | Description | |---------|-------------| | /memory-consolidate | Manually trigger memory extraction from current session |

How It Works

1. session_start — Opens the SQLite store, shows memory stats briefly in the status bar
2. before_agent_start — Builds a <memory> context block from stored facts and lessons, appends it to the system prompt
3. agent_end — Collects conversation messages for later consolidation
4. session_shutdown — Runs LLM consolidation (via pi -p --print) to extract structured knowledge, then closes the store

Consolidation

At session end, if there were ≥3 user messages, the extension sends the conversation to an LLM and asks it to extract:

• Preferences — coding style, workflow habits, tool choices
• Project patterns — languages, frameworks, architecture decisions
• Corrections — things you corrected, mistakes to avoid

Only facts with confidence ≥ 0.8 are stored. Lessons are deduplicated using exact match and Jaccard similarity (≥ 0.7 threshold).

Injection

At session start, stored memory is organized into sections (preferences, project context scoped to cwd, tool preferences, lessons, user identity) and injected as a <memory> block in the system prompt. The block is capped at 8KB.

Storage

SQLite database at ~/.pi/memory/memory.db (WAL mode). Three tables:

• semantic — key-value facts with confidence scores
• lessons — learned corrections with dedup
• events — audit log of all memory operations

License

MIT