# Quick Start Tutorial

Get started with Adastrea Director in just a few minutes!

## 🎯 What You'll Learn

In this tutorial, you'll:
- ✅ Run your first query
- ✅ Ingest documentation
- ✅ Create an implementation plan
- ✅ Use the GUI application

**Time Required:** 5-10 minutes

## Prerequisites

✅ You've completed [Installation & Setup](Getting-Started.md)

## Step 1: Your First Query (CLI)

Let's start with a simple query using the command-line interface:

```bash
# Activate your virtual environment (if not already active)
source venv/bin/activate  # Linux/Mac
venv\Scripts\activate     # Windows

# Start the interactive assistant
python main.py
```

You'll see a prompt like this:
```
Adastrea Director - Context-Aware Assistant
Type 'quit' or 'exit' to end the session.

> 
```

Try asking a question:
```
> What is Adastrea Director?
```

**Note:** The first query may be slow as it loads the embeddings model. Subsequent queries will be much faster!

## Step 2: Ingest Documentation

To get meaningful answers about your project, you need to populate the knowledge base:

### Option A: Sample Documentation

Start with the project's own documentation:

```bash
# Ingest the README and core documentation
python ingest.py --docs-dir .
```

This will:
- ✅ Scan for markdown files
- ✅ Process and chunk documents
- ✅ Create vector embeddings
- ✅ Store in the database

### Option B: Your Project Documentation

Ingest your own documentation:

```bash
# Ingest from a specific directory
python ingest.py --docs-dir /path/to/your/docs

# Ingest multiple types of files
python ingest.py --docs-dir /path/to/your/docs --file-types .md .txt .rst
```

### Option C: Adastrea Game Repository (For Team Members)

```bash
# Set your GitHub token
export GITHUB_TOKEN="ghp_your_token_here"

# Populate with game repository
python ingest_game_repo.py
```

See the [Document Ingestion Guide](Document-Ingestion.md) for advanced options.

## Step 3: Use the Planning System (P2)

Now let's create an implementation plan:

```bash
# Start interactive planning mode
python planner.py --interactive
```

Try this example goal:
```
> Add a player inventory system with drag-and-drop UI
```

The planner will:
- 📊 Analyze your goal
- 📋 Break it down into prioritized tasks
- 🔗 Identify dependencies
- 💻 Suggest code implementations
- ⏱️ Estimate effort required

### Export Your Plan

```bash
# Plan a specific goal and export to markdown
python planner.py "Optimize rendering pipeline" --export markdown --output plan.md

# Export to JSON for programmatic use
python planner.py "Add multiplayer support" --export json --output plan.json
```

## Step 4: Use the GUI Application

For a more user-friendly experience:

```bash
python gui_director.py
```

### GUI Quick Tour

**1. Main Interface:**
- **Query Tab:** Ask questions about your project
- **Ingest List Tab:** See what's in your knowledge base
- **Conversation History:** View all Q&A with timestamps

**2. Settings Dialog (Ctrl+,):**
- Configure API keys
- Select LLM provider (Gemini, OpenAI, Ollama)
- Choose embedding provider
- Adjust display options

**3. Useful Shortcuts:**
- `Enter` or `Ctrl+Enter` - Send question
- `Ctrl+K` - Quick API key setup
- `Ctrl+,` - Open settings
- `Ctrl+U` - Update knowledge base
- `Ctrl+L` - Clear conversation
- `Ctrl+E` - Export conversation

### Your First GUI Query

1. Type your question in the input box at the bottom
2. Press Enter or click "Send"
3. Watch as the AI processes your query
4. View the response with source citations

## Step 5: Explore Advanced Features

### Agent Orchestration (P3)

```bash
# Start the agent orchestrator CLI
python agent_orchestrator_cli.py start --all

# Check agent status
python agent_orchestrator_cli.py status

# View the real-time dashboard
python agent_dashboard.py --auto-start
```

### Unreal Engine Plugin

If you're working in Unreal Engine:

1. Copy `Plugins/AdastreaDirector` to your UE project's `Plugins` folder
2. Regenerate project files
3. Build your project
4. Open **Window → Developer Tools → Adastrea Director**

See the [Plugin Guide](Plugin-Setup.md) for detailed instructions.

## Common Workflows

### Workflow 1: Documentation Q&A

```bash
# 1. Ingest your docs
python ingest.py --docs-dir /path/to/docs

# 2. Start asking questions
python main.py
> How do I implement feature X?
> What are the requirements for Y?
> Explain the architecture of Z
```

### Workflow 2: Planning & Implementation

```bash
# 1. Define your goal
python planner.py --interactive
> Add user authentication with OAuth2

# 2. Review the generated plan
# 3. Export for your team
python planner.py "Add authentication" --export markdown --output auth_plan.md

# 4. Follow the implementation steps
```

### Workflow 3: Continuous Development

```bash
# 1. Keep knowledge base updated
python ingest.py --docs-dir . --update

# 2. Use GUI for quick queries during development
python gui_director.py

# 3. Generate plans as needed
python planner.py "Refactor module X"
```

## Tips for Success

### 🎯 Getting Better Answers

1. **Be Specific:** Instead of "How do I code this?", ask "How do I implement a singleton pattern for a game manager in C++?"

2. **Provide Context:** The more documents you ingest, the better the answers

3. **Use Natural Language:** Write questions as you would ask a colleague

### 📚 Maintaining Your Knowledge Base

1. **Regular Updates:** Re-run ingestion when documentation changes
   ```bash
   python ingest.py --docs-dir . --update
   ```

2. **Check What's Ingested:** Use the Ingest List tab in the GUI to see all documents

3. **Organize Documents:** Keep documentation in a structured directory for easier ingestion

### ⚡ Performance Tips

1. **First Query is Slow:** The initial query loads models - this is normal
2. **Use Local Config:** Save API keys to avoid re-entering them
3. **GPU Acceleration:** If you have a GPU, embeddings will be faster

## Troubleshooting Quick Fixes

**No/Poor Responses:**
- ✅ Ensure you've ingested relevant documentation
- ✅ Check your API key is set correctly
- ✅ Verify internet connection (for API-based LLMs)

**Slow Performance:**
- ✅ First query is always slow (loading models)
- ✅ Subsequent queries should be fast
- ✅ Consider using GPU acceleration

**GUI Won't Start:**
- ✅ Ensure tkinter is installed (see [Installation Guide](Getting-Started.md))
- ✅ Try running `python -m tkinter` to test

## Next Steps

Now that you're familiar with the basics:

- **📖 [Context-Aware Assistant Guide](../usage/Context-Aware-Assistant.md)** - Deep dive into P1 features
- **📋 [Planning System Guide](../usage/Planning-System.md)** - Master P2 planning capabilities
- **🤖 [Autonomous Agents Guide](../usage/Autonomous-Agents.md)** - Set up P3 proactive monitoring
- **🎨 [GUI Application Guide](../usage/GUI-Application.md)** - Explore all GUI features

## Example Queries to Try

Here are some example queries to get you started:

```
> What is the main purpose of this project?
> How do I contribute to this project?
> What are the system requirements?
> Explain the RAG architecture
> How do I add a new agent?
> What testing framework is used?
> How do I troubleshoot installation issues?
```

## Getting Help

- **📖 [FAQ](FAQ.md)** - Common questions and answers
- **🔧 [Troubleshooting](Troubleshooting.md)** - Solve common issues
- **🐛 [Report Issues](https://github.com/Mittenzx/Adastrea-Director/issues)** - Found a bug?
- **💬 [Discussions](https://github.com/Mittenzx/Adastrea-Director/discussions)** - Ask questions

---

**Congratulations! You're now ready to use Adastrea Director!** 🎉

[← Back to Getting Started](Getting-Started.md) | [Explore Usage Guides →](../usage/Context-Aware-Assistant.md)