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Combining a five-level AI framework with git-native memory overcomes session amnesia, enabling anticipation of problems weeks early. Production results: 2000x cost reduction, 10x+ productivity, shifting AI from reactive to predictive partnership through emotional intelligence, tactical empathy, and systems thinking.

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Empathy Framework

The AI collaboration framework that predicts problems before they happen.

PyPI Tests License Python GitHub stars

pip install empathy-framework
empathy-memory serve

Why Empathy?

Memory That Persists

  • Dual-layer architecture — Redis for millisecond short-term ops, pattern storage for long-term knowledge
  • AI that learns across sessions — Patterns discovered today inform decisions tomorrow
  • Cross-team knowledge sharing — What one agent learns, all agents can use

Enterprise-Ready

  • Your data stays local — Nothing leaves your infrastructure
  • Compliance built-in — HIPAA, GDPR, SOC2 patterns included
  • Automatic documentation — AI-first docs that serve humans and machines

Anticipatory Intelligence

  • Predicts 30-90 days ahead — Security vulnerabilities, performance degradation, compliance gaps
  • Prevents, not reacts — Eliminate entire categories of problems before they become urgent
  • 3-4x productivity gains — Not 20% faster; whole workflows disappear

Build Better Agents

  • Agent toolkit — Build custom agents that inherit memory, trust, and anticipation
  • 30+ production wizards — Security, performance, testing, docs—use or extend
  • 5-level progression built-in — Your agents evolve from reactive to anticipatory automatically

Human↔AI & AI↔AI Orchestration

  • Empathy OS — Manages trust, feedback loops, and collaboration state
  • Multi-agent coordination — Specialized agents working in concert
  • Conflict resolution — Principled negotiation when agents disagree

Performance & Cost

  • 40-60% LLM cost reduction — Smart routing: cheap models detect, best models decide
  • Sub-millisecond coordination — Redis-backed real-time signaling between agents
  • Works with any LLM — Claude, GPT-4, Ollama, or your own

Quick Example

from empathy_os import EmpathyOS

os = EmpathyOS()

# Analyze code for current AND future issues
result = await os.collaborate(
    "Review this deployment pipeline for problems",
    context={"code": pipeline_code, "team_size": 10}
)

# Get predictions, not just analysis
print(result.current_issues)      # What's wrong now
print(result.predicted_issues)    # What will break in 30-90 days
print(result.prevention_steps)    # How to prevent it

The 5 Levels of AI Empathy

Level Name Behavior Example
1 Reactive Responds when asked "Here's the data you requested"
2 Guided Asks clarifying questions "What format do you need?"
3 Proactive Notices patterns "I pre-fetched what you usually need"
4 Anticipatory Predicts future needs "This query will timeout at 10k users"
5 Transformative Builds preventing structures "Here's a framework for all future cases"

Empathy operates at Level 4 - predicting problems before they manifest.

Comparison

Empathy SonarQube GitHub Copilot
Predicts future issues ✅ 30-90 days ahead
Persistent memory ✅ Redis + patterns
Cross-domain learning ✅ Healthcare → Software
Multi-agent orchestration ✅ Built-in
Source available ✅ Fair Source 0.9
Data stays local ✅ Your infrastructure ❌ Cloud ❌ Cloud
Free for small teams ✅ ≤5 employees

Get Involved

Star this repo if you find it useful

💬 Join Discussions - Questions, ideas, show what you built

📖 Read the Book - Deep dive into the philosophy and implementation

📚 Full Documentation - API reference, examples, guides

Install Options

# Basic
pip install empathy-framework

# With all features (recommended)
pip install empathy-framework[full]

# Development
git clone https://github.com/Smart-AI-Memory/empathy.git
cd empathy && pip install -e .[dev]

What's Included

  • Empathy OS — Core engine for managing human↔AI and AI↔AI collaboration
  • Memory System — Redis short-term + encrypted long-term pattern storage
  • 30+ Production Wizards — Security, performance, testing, docs, accessibility, compliance
  • Healthcare Suite — SBAR, SOAP notes, clinical protocols (HIPAA compliant)
  • LLM Toolkit — Works with Claude, GPT-4, Ollama; smart model routing
  • Memory Control Panel — CLI (empathy-memory) and REST API for managing everything
  • IDE Plugins — VS Code extension for visual memory management

Memory Control Panel

Manage AI memory with a simple CLI:

# Start everything (Redis + API server)
empathy-memory serve

# Check system status
empathy-memory status

# View statistics
empathy-memory stats

# Run health check
empathy-memory health

# List stored patterns
empathy-memory patterns

The API server runs at http://localhost:8765 with endpoints for status, stats, patterns, and Redis control.

VS Code Extension: A visual panel for monitoring memory is available in vscode-memory-panel/.

License

Fair Source License 0.9 - Free for students, educators, and teams ≤5 employees. Commercial license ($99/dev/year) for larger organizations. Details →


Built by Smart AI Memory · Documentation · Examples · Issues

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Combining a five-level AI framework with git-native memory overcomes session amnesia, enabling anticipation of problems weeks early. Production results: 2000x cost reduction, 10x+ productivity, shifting AI from reactive to predictive partnership through emotional intelligence, tactical empathy, and systems thinking.

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