empathy-framework 5.0.1

AI collaboration framework with real LLM agent execution, AskUserQuestion tool integration, Socratic agent generation, progressive tier escalation (70-85% cost savings), meta-orchestration, dynamic agent composition (6 patterns), intelligent caching (85% hit rate), semantic workflow discovery, visual workflow editor, MCP integration for Claude Code, and multi-agent orchestration.

Empathy Framework

AI-powered developer workflows with cost optimization and pattern learning.

Run code review, debugging, testing, and release workflows from your terminal or Claude Code. Smart tier routing saves 34-86% on LLM costs.

pip install empathy-framework[developer]

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🎯 Transitioning to Claude-Native Architecture

Empathy Framework is evolving to focus exclusively on Anthropic/Claude to unlock features impossible with multi-provider abstraction:

• 📦 Prompt Caching: 90% cost reduction on repeated prompts
• 📖 200K Context: Largest context window available (vs 128K for competitors)
• 🧠 Extended Thinking: See Claude's internal reasoning process
• 🔧 Advanced Tool Use: Optimized for agentic workflows

Timeline:

• ✅ v4.8.0 (Jan 2026): Deprecation warnings for OpenAI/Google/Ollama providers
• ✅ v5.0.0 (Jan 26, 2026): Non-Anthropic providers removed (BREAKING - COMPLETE)
• 🎯 v5.1.0 (Feb 2026): Prompt caching enabled by default

Migration Guide: docs/CLAUDE_NATIVE.md

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What's New in v4.9.0

⚡ 18x Faster Performance - Massive performance gains through Phase 2 optimizations:

• Redis Two-Tier Caching: 2x faster memory operations (37,000x for cached keys)
• Generator Expressions: 99.9% memory reduction across 27 optimizations
• Parallel Scanning: Multi-core processing enabled by default (2-4x faster)
• Incremental Scanning: Git diff-based updates (10x faster)

🧭 Natural Language Workflows - Use plain English instead of workflow names:

/workflows "find security vulnerabilities"  # → security-audit
/workflows "check code performance"         # → perf-audit
/workflows "predict bugs"                   # → bug-predict
/plan "review my code"                      # → code-review

📊 Real-World Performance:

• Combined workflow: 3.59s → 0.2s (18x faster)
• Full scan: 3,472 files in 0.98s (was 3.59s)
• Redis cached operations: 37ms → 0.001ms

🎯 Improved Navigation:

• Split /workflow into /workflows (automated analysis) and /plan (planning/review)
• Clearer hub organization with better categorization
• Natural language routing matches intent to workflow

See CHANGELOG.md | Performance Docs

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What's New in v4.7.0

$0 Workflows via Skills - Multi-agent workflows run through Claude Code's Task tool instead of API calls. No additional cost with your Claude subscription.

Socratic Workflows - Interactive discovery through guided questions. Workflows ask what you need rather than requiring upfront configuration.

Security Hardened - Fixed critical vulnerabilities (path traversal, JWT, SSRF).

Hub-Based Commands - Organized workflows into intuitive command hubs.

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Quick Start

1. Install

pip install empathy-framework[developer]

2. Configure

# Auto-detect API keys
python -m empathy_os.models.cli provider

# Or set explicitly
python -m empathy_os.models.cli provider --set anthropic

3. Use

In Claude Code:

/dev           # Developer tools (debug, commit, PR, review)
/testing       # Run tests, coverage, benchmarks
/workflows     # Automated analysis (security, bugs, perf)
/plan          # Planning, TDD, code review
/docs          # Documentation generation
/release       # Release preparation

# Natural language support:
/workflows "find security issues"
/plan "review my code"

CLI:

empathy workflow run security-audit --path ./src
empathy workflow run test-coverage --target 90
empathy telemetry show  # View cost savings

Python:

from empathy_os import EmpathyOS

async with EmpathyOS() as empathy:
    result = await empathy.level_2_guided(
        "Review this code for security issues"
    )
    print(result["response"])

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Command Hubs

Workflows are organized into hubs for easy discovery:

Hub	Command	Description
Developer	/dev	Debug, commit, PR, code review, quality
Testing	/testing	Run tests, coverage analysis, benchmarks
Documentation	/docs	Generate and manage documentation
Release	/release	Release prep, security scan, publishing
Workflows	/workflows	Automated analysis (security, bugs, perf)
Plan	/plan	Planning, TDD, code review, refactoring
Utilities	/utilities	Project init, dependencies, profiling
Learning	/learning	Pattern learning and session evaluation
Context	/context	State management and memory
Agent	/agent	Create and manage custom agents

Natural Language Support:

# Use plain English - intelligent routing matches your intent
/workflows "find security vulnerabilities"  # → security-audit
/workflows "check code performance"         # → perf-audit
/workflows "predict bugs"                   # → bug-predict
/plan "review my code"                      # → code-review
/plan "help me plan this feature"           # → planning

# Or use traditional workflow names
/workflows security-audit
/plan code-review

Interactive menus:

/dev                    # Show interactive menu
/dev "debug auth error" # Jump directly to debugging
/testing "run coverage" # Run coverage analysis
/release                # Start release preparation

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Socratic Method

Workflows guide you through discovery instead of requiring upfront configuration:

You: /dev

Claude: What development task do you need?
  1. Debug issue
  2. Create commit
  3. PR workflow
  4. Quality check

You: 1

Claude: What error or unexpected behavior are you seeing?

How it works:

1. Discovery - Workflow asks targeted questions to understand your needs
2. Context gathering - Collects relevant code, errors, and constraints
3. Dynamic agent creation - Assembles the right team based on your answers
4. Execution - Runs with appropriate tier selection

Create custom agents with Socratic guidance:

/agent create    # Guided agent creation
/agent team      # Build multi-agent teams interactively

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Cost Optimization

Skills = $0 (Claude Code)

When using Claude Code, workflows run as skills through the Task tool - no API costs:

/dev           # $0 - uses your Claude subscription
/testing       # $0
/release       # $0
/agent create  # $0

API Mode (CI/CD, Automation)

For programmatic use, smart tier routing saves 34-86%:

Tier	Model	Use Case	Cost
CHEAP	Haiku / GPT-4o-mini	Formatting, simple tasks	~$0.005
CAPABLE	Sonnet / GPT-4o	Bug fixes, code review	~$0.08
PREMIUM	Opus / o1	Architecture, complex design	~$0.45

# Track API usage and savings
empathy telemetry savings --days 30

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Key Features

Multi-Agent Workflows

# 4 parallel agents check release readiness
empathy orchestrate release-prep

# Sequential coverage improvement
empathy orchestrate test-coverage --target 90

Response Caching

Up to 57% cache hit rate on similar prompts. Zero config needed.

from empathy_os.workflows import SecurityAuditWorkflow

workflow = SecurityAuditWorkflow(enable_cache=True)
result = await workflow.execute(target_path="./src")
print(f"Cache hit rate: {result.cost_report.cache_hit_rate:.1f}%")

Pattern Learning

Workflows learn from outcomes and improve over time:

from empathy_os.orchestration.config_store import ConfigurationStore

store = ConfigurationStore()
best = store.get_best_for_task("release_prep")
print(f"Success rate: {best.success_rate:.1%}")

Multi-Provider Support

from empathy_llm_toolkit.providers import (
    AnthropicProvider,  # Claude
    OpenAIProvider,     # GPT-4
    GeminiProvider,     # Gemini
    LocalProvider,      # Ollama, LM Studio
)

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CLI Reference

# Provider configuration
python -m empathy_os.models.cli provider
python -m empathy_os.models.cli provider --set hybrid

# Workflows
empathy workflow list
empathy workflow run <workflow-name>

# Cost tracking
empathy telemetry show
empathy telemetry savings --days 30
empathy telemetry export --format csv

# Orchestration
empathy orchestrate release-prep
empathy orchestrate test-coverage --target 90

# Meta-workflows
empathy meta-workflow list
empathy meta-workflow run release-prep --real

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Install Options

# Individual developers (recommended)
pip install empathy-framework[developer]

# All LLM providers
pip install empathy-framework[llm]

# With caching (semantic similarity)
pip install empathy-framework[cache]

# Enterprise (auth, rate limiting)
pip install empathy-framework[enterprise]

# Healthcare (HIPAA compliance)
pip install empathy-framework[healthcare]

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

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Environment Setup

# At least one provider required
export ANTHROPIC_API_KEY="sk-ant-..."
export OPENAI_API_KEY="sk-..."
export GOOGLE_API_KEY="..."

# Optional: Redis for memory
export REDIS_URL="redis://localhost:6379"

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VSCode Extension

Install the Empathy VSCode extension for:

• Dashboard - Health score, costs, patterns
• One-Click Workflows - Run from command palette
• Memory Panel - Manage Redis and patterns
• Cost Tracking - Real-time savings display

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Documentation

• Quick Start Guide
• CLI Reference
• Testing Guide
• Keyboard Shortcuts
• Full Documentation

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Security

• Path traversal protection on all file operations
• JWT authentication with rate limiting
• PII scrubbing in telemetry
• HIPAA/GDPR compliance options
• Automated security scanning with 82% accuracy (Phase 3 AST-based detection)

See SECURITY.md for vulnerability reporting.

Security Scanning

Automated security scanning in CI/CD - 82% accuracy, blocks critical issues:

# Run security audit locally
empathy workflow run security-audit

# Scan specific directory
empathy workflow run security-audit --input '{"path":"./src"}'

Documentation:

• Developer Workflow Guide - Quick reference for handling security findings (all developers)
• CI/CD Integration Guide - Complete setup and troubleshooting (DevOps, developers)
• Scanner Architecture - Technical implementation details (engineers, architects)
• Remediation Process - 3-phase methodology for improving scanners (security teams, leadership)
• API Reference - Complete API documentation (developers extending scanner)

Key achievements:

• 82.3% reduction in false positives (350 → 62 findings)
• 16x improvement in scanner accuracy
• <15 minute average fix time for critical issues
• Zero critical vulnerabilities in production code

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Contributing

See CONTRIBUTING.md for guidelines.

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License

Fair Source License 0.9 - Free for students, educators, and teams ≤5 employees. Commercial license for larger organizations. Details →

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