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Engram

Jarvis's persistent memory system. Obsidian-native, SQLite-indexed, zero heavy dependencies.

Architecture

  • Source of truth: Obsidian vault (markdown files with YAML frontmatter)
  • Query layer: SQLite FTS5 index, rebuilt incrementally on change
  • Live sync: watchdog file watcher (inotify on Linux)
  • Ingest: LLM extraction pipeline writes Entity + Fact notes back to vault
  • Briefing: session start injection with standing rules, open loops, recent context

Install

git clone https://github.com/atomlaunch/engram.git
cd engram
pip install -e .

Setup

# Copy config template
mkdir -p ~/.engram
cp config.example.json ~/.engram/config.json
# Edit vault_path and other settings

# Copy AGENTS.md to vault root
cp templates/AGENTS.md ~/obsidian-vault/AGENTS.md

# Build initial index
engram index

Usage

engram index              # Scan vault and build index
engram index --watch      # Keep running and watch for changes
engram brief              # Print session briefing
engram search "discord"   # Full-text search
engram search "rule" --type fact
engram ingest             # Run LLM extraction pipeline
engram session "Summary of what happened" --threads "item1,item2"
engram version            # Version + index stats

Note Types

  • entity -- people, projects, tools, concepts (Memory/Entities/)
  • fact -- decisions, preferences, rules, lessons (Memory/Facts/)
  • session -- session snapshots (Memory/Sessions/)

Artifact Types (Facts)

Type Description
durable_fact Stable truth, long shelf life
preference How TheDev likes things done
standing_rule Always apply (importance: 1.0)
decision Something decided with context
lesson Learned from failure or success
open_loop Unresolved thread to revisit
constraint Hard limit or boundary

Versioning

Semver. Each release tagged on GitHub. Schema migrations in migrations/.

See CHANGELOG.md for full history.

Requirements

  • Python >= 3.11
  • watchdog >= 4.0
  • python-frontmatter >= 1.1
  • anthropic >= 0.40 (for ingest pipeline)
  • click >= 8.1

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Temporal Knowledge Graph Memory for AI Agents

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