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

Recommended: Install pi-total-recall to get the complete context stack — persistent memory, session history search, and local knowledge search in one package:

pi install pi-total-recall

Or install pi-memory standalone:

pi install pi-memory

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

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

Memory Types

Tools

Commands

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.

Selective lesson injection — By default, all lessons are injected into every session. When you have many lessons across different domains, this can waste context. Enable selective mode to filter lessons by relevance:

{
  "memory": {
    "lessonInjection": "selective"
  }
}

Add this to ~/.pi/agent/settings.json. In selective mode, lessons are filtered by:

1. Prompt relevance — FTS search against the user's first message
2. Project context — lessons matching the current working directory's project
3. Category inference — keywords in the prompt trigger relevant categories (e.g. "pentest" pulls in bug-bounty lessons, "blog post" pulls in writing lessons)
4. General lessons — always included regardless of prompt

The result is capped at 15 most relevant lessons instead of all of them.

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