Choosing Your Path: UFO² or UFO³ Galaxy?

Not sure which UFO framework to use? This guide will help you make the right choice based on your specific needs.

🗺️ Quick Decision Tree

Use this interactive flowchart to find the best solution for your use case:

graph TD Start[What are you trying to automate?] --> Q1{Involves multiple devices/platforms?} Q1 -->|Yes| Q2{Need parallel execution across devices?} Q1 -->|No| Q3{Complex multi-app workflow on Windows?} Q2 -->|Yes| Galaxy[✨ Use UFO³ Galaxy] Q2 -->|No, sequential| Q4{Can tasks run independently?} Q4 -->|Yes, independent| UFO2_Multi[Use UFO² on each device separately] Q4 -->|No, dependencies| Galaxy Q3 -->|Yes| UFO2[🪟 Use UFO²] Q3 -->|No, simple task| UFO2 Q3 -->|Might scale later| Hybrid[Use UFO² now, Galaxy-ready setup] Galaxy --> GalaxyDoc[📖 See Galaxy Quick Start] UFO2 --> UFO2Doc[📖 See UFO² Quick Start] UFO2_Multi --> UFO2Doc Hybrid --> MigrationDoc[📖 See Migration Guide] style Galaxy fill:#fff9c4 style UFO2 fill:#c8e6c9 style UFO2_Multi fill:#c8e6c9 style Hybrid fill:#e1bee7 click GalaxyDoc "./getting_started/quick_start_galaxy.md" click UFO2Doc "./getting_started/quick_start_ufo2.md" click MigrationDoc "./getting_started/migration_ufo2_to_galaxy.md"

📊 Quick Comparison Matrix

Dimension	UFO² Desktop AgentOS	UFO³ Galaxy
Target Scope	Single Windows desktop	Multiple devices (Windows/Linux/macOS)
Best For	Simple local automation	Complex cross-device workflows
Setup Complexity	⭐ Simple	⭐⭐⭐ Moderate (requires device pool)
Learning Curve	⭐⭐ Easy	⭐⭐⭐⭐ Advanced
Execution Model	Sequential multi-app	Parallel DAG orchestration
Network Required	❌ No	✅ Yes (WebSocket between devices)
Parallelism	Within single device	Across multiple devices
Fault Tolerance	Retry on same device	Retry + task migration
Typical Latency	10-30s (local)	20-60s (includes orchestration)
Ideal Task Count	1-5 steps	5-20+ steps with dependencies

Quick Rule of Thumb: - 1 device + simple workflow → UFO² - 2+ devices OR complex dependencies → Galaxy - Not sure? → Start with UFO², migrate later (Migration Guide)

🎯 Scenario-Based Recommendations

Scenario 1: Desktop Productivity Automation

Task: "Create a weekly report: extract data from Excel, generate charts in PowerPoint, send via Outlook"

Recommendation: ✅ UFO²

Why: - All applications on one Windows desktop - Sequential workflow (Excel → PowerPoint → Outlook) - No cross-device dependencies

Learn More: UFO² Overview

Scenario 2: Development Workflow Automation

Task: "Clone repo on my laptop, build Docker image on GPU server, run tests on CI cluster, open results on my desktop"

Recommendation: ✅ UFO³ Galaxy

Why: - Spans 3+ devices (laptop, GPU server, CI cluster, desktop) - Sequential dependencies (clone → build → test → display) - Requires device coordination and data transfer

Learn More: Galaxy Overview

Scenario 3: Batch Data Processing

Task: "Process 100 files: fetch from cloud, clean data, run ML model, save results"

Recommendation: Depends on setup

Setup	Recommendation	Why
Single powerful workstation	✅ UFO²	All processing on one machine, simpler
Distributed cluster	✅ Galaxy	Parallel processing across nodes, faster
Mix (local + cloud GPU)	✅ Galaxy	Heterogeneous resources

Learn More: - UFO² for Single Device - Galaxy for Distributed

Scenario 4: Cross-Platform Testing

Task: "Test web app on Windows Chrome, Linux Firefox, and macOS Safari"

Recommendation: ✅ UFO³ Galaxy

Why: - Requires 3 different OS platforms - Parallel execution saves time - Centralized result aggregation

Learn More: Galaxy Multi-Platform Support

Scenario 5: File Management & Organization

Task: "Organize Downloads folder by file type, compress old files, upload to cloud"

Recommendation: ✅ UFO²

Why: - Single-device local file operations - No network dependencies - Simple sequential workflow

Learn More: UFO² Quick Start

Scenario 6: Multi-Stage Data Pipeline

Task: "Collect logs from 5 Linux servers, aggregate on central server, analyze, generate dashboard on Windows"

Recommendation: ✅ UFO³ Galaxy

Why: - Multiple source devices (5 Linux servers) - Parallel log collection (5x faster than sequential) - Cross-platform (Linux → Windows) - Complex dependency graph

Learn More: Galaxy Task Constellation

Scenario 7: Learning Agent Development

Task: "I'm new to agent development and want to learn by building simple automation"

Recommendation: ✅ UFO²

Why: - Simpler architecture (easier to understand) - Faster feedback loop (local execution) - Comprehensive documentation and examples - Can upgrade to Galaxy later

Learn More: UFO² Quick Start

Scenario 8: Enterprise Workflow Integration

Task: "Integrate with existing CI/CD pipeline across dev laptops, build servers, and test farms"

Recommendation: ✅ UFO³ Galaxy

Why: - Enterprise-scale device coordination - Fault tolerance with automatic recovery - Formal safety guarantees for correctness - Supports heterogeneous infrastructure

Learn More: Galaxy Architecture

🔀 Hybrid Approaches

You don't have to choose just one! Here are common hybrid patterns:

Pattern 1: UFO² as Galaxy Device

Setup: Run UFO² in agent-server mode as a Galaxy device

# On Windows desktop
python -m ufo --mode agent-server --port 5005

Benefits: - Keep UFO² for local Windows expertise - Gain Galaxy's cross-device orchestration - Best of both worlds

Learn More: UFO² as Galaxy Device

Pattern 2: Gradual Migration

Strategy: Start with UFO² for immediate needs, prepare for Galaxy expansion

Phase 1: Use UFO² standalone

python -m ufo --task "Your current task"

Phase 2: Make UFO² Galaxy-compatible

# config/galaxy/devices.yaml (prepare in advance)
devices:
  - device_id: "my_windows"
    server_url: "ws://localhost:5005/ws"
    capabilities: ["office", "web"]

Phase 3: Add Galaxy when needed

# Start using Galaxy for multi-device tasks
python -m galaxy --request "Cross-device workflow"

Learn More: Migration Guide

Pattern 3: Domain-Specific Split

Strategy: Use different frameworks for different workflow types

Workflow Type	Framework	Example
Daily desktop tasks	UFO²	Email processing, document creation
Development workflows	Galaxy	Code build → test → deploy
Data processing	Galaxy (if distributed)	Multi-node ML training
Quick automation	UFO²	One-off tasks

Learn More: When to Use Which

🚫 Common Misconceptions

Misconception 1: "Galaxy is always better because it's newer"

Reality: UFO² is better for simple single-device tasks due to: - Lower latency (no network overhead) - Simpler setup and debugging - Battle-tested stability

Use Galaxy only when you actually need multi-device orchestration.

Misconception 2: "I need to rewrite everything to migrate to Galaxy"

Reality: UFO² can run as a Galaxy device with zero code changes:

# Existing UFO² instance becomes Galaxy device
python -m ufo --mode agent-server --port 5005

Learn More: Migration Guide

Misconception 3: "Galaxy can't run on a single device"

Reality: Galaxy works perfectly on one device if you need: - DAG-based workflow planning - Advanced monitoring and trajectory reports - Preparation for future multi-device expansion

# Single-device Galaxy setup
devices:
  - device_id: "localhost"
    server_url: "ws://localhost:5005/ws"

Misconception 4: "UFO² is deprecated in favor of Galaxy"

Reality: UFO² is actively maintained and recommended for single-device use: - More efficient for local tasks - Simpler for beginners - Core component when used as Galaxy device

Both frameworks are complementary, not competing.

🎓 Learning Paths

For Beginners

Week 1-2: Start with UFO² 1. UFO² Quick Start 2. Build simple automation (file management, email, etc.) 3. Understand HostAgent/AppAgent architecture

Week 3-4: Explore Advanced UFO² 4. Hybrid GUI-API Actions 5. MCP Server Integration 6. Customization & Learning

Week 5+: Graduate to Galaxy (if needed) 7. Migration Guide 8. Galaxy Quick Start 9. Build cross-device workflows

For Experienced Developers

Direct to Galaxy if you already know you need multi-device: 1. Galaxy Quick Start 2. Task Constellation Concepts 3. ConstellationAgent Deep Dive 4. Performance Monitoring

📋 Decision Checklist

Still unsure? Answer these questions:

Q1: Does your workflow involve 2+ physical devices?

✅ Yes → Galaxy
❌ No → Continue to Q2

Q2: Do you need parallel execution across different machines?

✅ Yes → Galaxy
❌ No → Continue to Q3

Q3: Does your workflow have complex dependencies (DAG structure)?

✅ Yes, complex DAG → Galaxy
❌ No, simple sequence → Continue to Q4

Q4: Are you comfortable with distributed systems concepts?

✅ Yes → Galaxy (if any of Q1-Q3 is yes)
❌ No → UFO² (learn basics first)

Q5: Do you need cross-platform support (Windows + Linux)?

✅ Yes → Galaxy
❌ No, Windows only → UFO²

Result:

3+ "Galaxy" answers → Use Galaxy (Quick Start)
Mostly "UFO²" answers → Use UFO² (Quick Start)
Mixed answers → Start with UFO², keep Galaxy option open (Migration Guide)

🔗 Next Steps

If you chose UFO²:

If you chose Galaxy:

If you're still exploring:

💡 Pro Tips

Start Simple

When in doubt, start with UFO². It's easier to scale up to Galaxy later than to debug a complex Galaxy setup when you don't need it.

Hybrid is Valid

Don't feel locked into one choice. You can use UFO² for local tasks and Galaxy for cross-device workflows simultaneously.

Test Before Committing

Try both for a simple workflow to see which feels more natural for your use case:

# UFO² test
python -m ufo --task "Create test report"

# Galaxy test  
python -m galaxy --request "Create test report"

Network Requirements

Galaxy requires stable network connectivity between devices. If your environment has network restrictions, UFO² might be more reliable.

🤝 Getting Help

Documentation: https://microsoft.github.io/UFO/
GitHub Issues: https://github.com/microsoft/UFO/issues
Discussions: https://github.com/microsoft/UFO/discussions

Still have questions? Check the Migration FAQ or open a discussion on GitHub!