hologram-cognitive 0.2.0

Pressure-based context routing with lighthouse resurrection for LLMs

hologram-cognitive

Pressure-based context routing with lighthouse resurrection for LLMs.

Portable AI working memory that travels between Claude.ai, Claude Code, ChatGPT, and any LLM platform.

Installation

pip install hologram-cognitive

Quick Start

One-liner routing

import hologram

ctx = hologram.route('.claude', "What's the T3 architecture?")
print(ctx['injection'])  # Ready for your prompt

Session-based (multi-turn)

import hologram

session = hologram.Session('.claude')

# Each conversation turn
result = session.turn("Let's design a drone swarm")
# result.injection contains relevant context from memory

# Write important things to memory
session.note(
    "Drone Architecture Decision",
    "Using ESP-NOW for pressure propagation between units",
    links=['[[t3-overview.md]]', '[[projects/drone-swarm.md]]']
)

session.save()

CLI

# Route a message
hologram route .claude "What about the T3 architecture?"

# Check memory status  
hologram status .claude

# Write a note
hologram note .claude "Meeting Notes" "Discussed X, Y, Z" -l t3-overview.md

# Initialize new project
hologram init ./my-project/.claude

# Export for transfer
hologram export .claude memory-backup.tar.gz

How It Works

Pressure-Based Routing

Unlike RAG (similarity-based retrieval), hologram-cognitive uses pressure dynamics:

• Files have pressure (0.0 - 1.0)
• Relevant files activate and gain pressure
• Pressure propagates along DAG edges (from [[wiki-links]])
• Inactive files decay over time
• Lighthouse resurrection: Cold files periodically resurface (spaced repetition)

Tiered Injection

• 🔥 CRITICAL (≥0.8): Full content injected
• ⭐ HIGH (≥0.5): Headers + summary
• 📋 MEDIUM (≥0.2): Listed only
• ❄️ COLD (<0.2): Waiting for resurrection

DAG Structure

Link files with [[wiki-links]] in your markdown:

# My Project

This builds on [[t3-overview.md]] and relates to [[other-project.md]].

Links are auto-discovered. Structure emerges from content.

File Structure

your-project/
├── .claude/
│   ├── MEMORY.md              # Instructions for LLMs (optional)
│   ├── hologram_state.json    # Pressure state (auto-generated)
│   ├── hologram_history.jsonl # Turn history (auto-generated)
│   ├── t3-overview.md         # Your knowledge files
│   ├── projects/
│   │   └── drone-swarm.md
│   └── sessions/
│       └── 2025-01-15-notes.md
└── CLAUDE.md                  # Claude Code instructions (optional)

Cross-Platform Portability

The .claude/ folder works everywhere:

• Claude.ai: Upload folder, instant context
• Claude Code: Drop in project root
• ChatGPT: Upload to sandbox
• Local/API: Direct Python integration

Export → Transfer → Import. Memory travels with you.

API Reference

hologram.route(claude_dir, message)

One-shot routing. Returns dict with injection, hot, warm, cold, activated.

hologram.Session(claude_dir)

Session manager for multi-turn conversations.

Methods:

• .turn(message) → TurnResult with injection and metadata
• .note(title, body, links=[]) → Write memory note
• .save() → Persist state to disk
• .status() → Current memory statistics
• .files_by_pressure(min=0.0) → List files sorted by pressure

TurnResult

• .injection - Formatted context string
• .hot - List of critical files
• .warm - List of high-priority files
• .cold - List of inactive files
• .activated - Files activated this turn
• .turn_number - Current turn count

Configuration

MEMORY.md

Place a MEMORY.md in your .claude/ folder with instructions for LLMs:

# Memory System Active

Run `session.turn(message)` before each response.
Write notes for significant topics.
Save state after each turn.

Pressure Tuning

from hologram.pressure import PressureConfig

config = PressureConfig(
    activation_boost=0.6,         # Default: files reach HOT on first mention
    edge_flow_rate=0.15,          # Pressure propagation along DAG edges
    decay_rate=0.85,              # Decay multiplier per turn
    use_toroidal_decay=True,      # Enable lighthouse resurrection
    resurrection_threshold=0.05,  # When files are effectively dead
    resurrection_pressure=0.55,   # Resurrect to WARM tier
)

Author

Garret Sutherland
MirrorEthic LLC
[e-mail]

License

MIT