# 🎓 Your Learning Path: Zero to Mastery

**Welcome!** This is your guided path to mastering Synqed and multi-agent AI systems.

---

## 📚 Start Here

### Step 1: Read the Comprehensive Guide
**File:** `QUALTRICS_MASTERY_GUIDE.md` (in `/synqed-python/`)

This 66-page guide covers:
- What A2A and Synqed are
- Core concepts explained simply
- Complete API reference
- The Qualtrics example explained line-by-line
- Best practices and troubleshooting

**Time:** 1-2 hours to read, reference it constantly

---

## 🛠️ Step 2: Hands-On Learning (Complete in Order!)

### Level 1: Hello World (30 minutes) ⭐

**Files:**
1. `quickstart_hello_agent.py` - Your first agent
2. `quickstart_test_client.py` - Test it

**What you'll learn:**
- Creating a basic agent
- Starting a server
- Connecting with a client

**How to run:**
```bash
# Terminal 1
python quickstart_hello_agent.py

# Terminal 2
python quickstart_test_client.py
```

**✅ You've mastered Level 1 when:**
- Your agent runs without errors
- You can send messages to it
- You understand the basic flow

---

### Level 2: Smart Agent (1 hour) ⭐⭐

**File:** `level2_smart_agent.py`

**What you'll learn:**
- Integrating OpenAI (or other LLMs)
- Defining agent skills
- Using environment variables

**Prerequisites:**
- OpenAI API key
- `.env` file with `OPENAI_API_KEY=your-key`

**How to run:**
```bash
# Terminal 1
python level2_smart_agent.py

# Terminal 2
python quickstart_test_client.py
```

**✅ You've mastered Level 2 when:**
- Your agent uses a real LLM
- You understand the executor pattern
- You can create agents with different prompts

---

### Level 3: Two-Agent Collaboration (2 hours) ⭐⭐⭐

**File:** `level3_two_agents.py`

**What you'll learn:**
- Running multiple agents simultaneously
- Creating an orchestrator
- Building collaborative workspaces
- Real-time message monitoring
- Proper cleanup

**How to run:**
```bash
python level3_two_agents.py
```

**✅ You've mastered Level 3 when:**
- You see two agents collaborating automatically
- You understand how orchestration works
- You can modify the agents' behaviors
- You can create your own two-agent system

---

### Level 4: Complex Multi-Agent System (3+ hours) ⭐⭐⭐⭐

**File:** `qualtrics_sales_agentification.py`

**What you'll learn:**
- Managing 5+ specialized agents
- Complex task decomposition
- Parallel vs sequential execution
- Multiple collaboration scenarios
- Production-ready patterns

**How to run:**
```bash
python qualtrics_sales_agentification.py
```

**What to study:**
1. How the 5 agents are specialized
2. The orchestration process
3. How dependencies are managed
4. Real-time message display
5. Result synthesis

**✅ You've mastered Level 4 when:**
- You understand every part of the file
- You can explain the flow to someone else
- You can add a 6th agent
- You can create new scenarios

---

### Level 5: Build Your Own (Ongoing) ⭐⭐⭐⭐⭐

**Challenge:** Build a multi-agent system for YOUR use case

**Ideas:**
- Customer support automation
- Content creation pipeline
- Research assistant team
- Code review system
- Data analysis workflow
- Personal assistant network

**Requirements:**
- 3+ specialized agents
- Intelligent orchestration
- Real-world use case
- Error handling
- Proper cleanup

**✅ You've achieved mastery when:**
- You can build any multi-agent system
- You can debug issues independently
- You understand trade-offs
- You can teach others

---

## 📖 Reference Materials

### Quick API Reference

**Creating an Agent:**
```python
agent = synqed.Agent(
    name="AgentName",
    description="What it does",
    skills=[{
        "skill_id": "unique_id",
        "name": "Display Name",
        "description": "Detailed description",
        "tags": ["tag1", "tag2"]
    }],
    executor=your_function
)
```

**Starting a Server:**
```python
server = synqed.AgentServer(agent, port=8000)
await server.start_background()  # Non-blocking
# ... do work ...
await server.stop()  # Cleanup
```

**Creating an Orchestrator:**
```python
orchestrator = synqed.Orchestrator(
    provider=synqed.LLMProvider.OPENAI,
    api_key=os.getenv("OPENAI_API_KEY"),
    model="gpt-4o"
)
```

**Creating a Workspace:**
```python
workspace = synqed.OrchestratedWorkspace(
    orchestrator=orchestrator,
    enable_agent_discussion=True,
    message_callback=your_callback
)

workspace.register_agent(agent1)
workspace.register_agent(agent2)

result = await workspace.execute_task(task="...")
```

**Executor Pattern:**
```python
async def my_executor(context):
    user_input = context.get_user_input()
    # Do something smart
    return result
```

---

## 🎯 Learning Strategies

### If You Have 1 Hour
1. Read Sections 1-2 of the Mastery Guide (Fundamentals)
2. Complete Level 1 (Hello World)

### If You Have 3 Hours
1. Read Sections 1-3 of the Mastery Guide
2. Complete Levels 1-2
3. Skim the Qualtrics example

### If You Have 1 Day
1. Read entire Mastery Guide
2. Complete Levels 1-3
3. Study the Qualtrics example in detail

### If You Have 1 Week
1. Complete all 5 levels
2. Build 2-3 custom systems
3. Deep dive into advanced topics
4. Achieve mastery!

---

## 💡 Tips for Success

1. **Start Simple**
   - Don't skip levels
   - Master basics before advancing
   - Build complexity gradually

2. **Practice Consistently**
   - Code every day
   - Build small projects
   - Experiment freely

3. **Read the Errors**
   - Errors are teachers
   - Read error messages carefully
   - Consult troubleshooting section

4. **Ask Questions**
   - No question is too basic
   - Use the mastery guide
   - Check documentation

5. **Build Real Projects**
   - Theory is good, practice is better
   - Solve real problems
   - Learn by doing

---

## 🆘 Common Questions

**Q: I get "Address already in use" error**
A: Change the port number or kill the process using that port:
```bash
lsof -ti:8000 | xargs kill -9
```

**Q: "OpenAI API key not found"**
A: Create a `.env` file in the same directory with:
```
OPENAI_API_KEY=your-key-here
```

**Q: Agent doesn't respond**
A: Check:
- Is the server running? (Look for startup messages)
- Is the URL correct?
- Check for errors in the terminal

**Q: How do I stop a running agent?**
A: Press `Ctrl+C` in the terminal, or call `await server.stop()`

**Q: Can I use other LLMs besides OpenAI?**
A: Yes! Anthropic, Google, or any LLM with an async client

---

## 📊 Progress Tracker

Track your learning journey:

- [ ] Read Mastery Guide sections 1-2 (Fundamentals)
- [ ] Complete Level 1: Hello World agent
- [ ] Read Mastery Guide section 3 (API Reference)
- [ ] Complete Level 2: Smart agent with LLM
- [ ] Read Mastery Guide section 4 (File Walkthrough)
- [ ] Complete Level 3: Two-agent collaboration
- [ ] Read Mastery Guide sections 5-6 (Advanced topics)
- [ ] Study Qualtrics example completely
- [ ] Complete Level 4: Understand 5-agent system
- [ ] Read Mastery Guide section 7 (Best practices)
- [ ] Build first custom multi-agent system
- [ ] Build second custom system
- [ ] Build third custom system
- [ ] Achieve mastery! 🎓

---

## 🎉 Congratulations!

You have everything you need to go from zero to mastery!

**Remember:**
- Learning takes time
- Practice is key
- Build real projects
- Ask questions
- Have fun!

**Let's get started! 🚀**

Begin with Level 1: `python quickstart_hello_agent.py`

---

*Happy learning! You've got this! 💪*

