Create lab-01-installation-and-basics.md

Fixes #385

Author: santosomar

ai_research/ollama-labs/lab-01-installation-and-basics.md

@@ -0,0 +1,226 @@
+# Lab 1: Getting Started with Ollama - Installation and Basic Usage
+
+## Objective
+In this lab, you will learn how to install Ollama, download your first model, and interact with it using the command-line interface. By the end of this lab, you'll understand the basics of running and chatting with local large language models.
+
+## Prerequisites
+- A computer running macOS, Windows, or Linux
+- At least 8GB of RAM (16GB recommended)
+- At least 10GB of free disk space
+- Basic familiarity with the command line/terminal
+
+## Estimated Time
+30-45 minutes
+
+## Part 1: Installing Ollama
+
+### Step 1: Download and Install Ollama
+
+1. Visit [https://ollama.com/download](https://ollama.com/download)
+2. Download the installer for your operating system:
+   - **macOS**: Download the `.dmg` file
+   - **Windows**: Download the `.exe` installer
+   - **Linux**: Use the installation script (see below)
+
+#### For Linux users:
+```bash
+curl -fsSL https://ollama.com/install.sh | sh
+```
+
+### Step 2: Verify Installation
+
+After installation, open a terminal/command prompt and verify Ollama is installed:
+
+```bash
+ollama --version
+```
+
+You should see the version number displayed.
+
+### Step 3: Check if Ollama is Running
+
+Ollama typically starts automatically. To verify:
+
+```bash
+ollama ps
+```
+
+If Ollama isn't running, start it with:
+
+```bash
+ollama serve
+```
+
+## Part 2: Running Your First Model
+
+### Step 1: Download a Model
+
+Let's start with a smaller model that's great for learning. Download the `gemma3` model:
+
+```bash
+ollama pull gemma3
+```
+
+**Note**: This will download several gigabytes of data. The download time depends on your internet connection.
+
+### Step 2: List Available Models
+
+After the download completes, verify the model is available:
+
+```bash
+ollama ls
+```
+
+You should see `gemma3` in the list of available models.
+
+## Part 3: Interacting with the Model
+
+### Step 1: Start a Chat Session
+
+Run the model in interactive mode:
+
+```bash
+ollama run gemma3
+```
+
+### Step 2: Have a Conversation
+
+Try these prompts:
+
+1. **Basic greeting**:
+   ```
+   Hello! Can you introduce yourself?
+   ```
+
+2. **Ask a question**:
+   ```
+   What is the capital of France?
+   ```
+
+3. **Request an explanation**:
+   ```
+   Explain how photosynthesis works in simple terms.
+   ```
+
+4. **Creative task**:
+   ```
+   Write a haiku about artificial intelligence.
+   ```
+
+### Step 3: Exit the Chat
+
+To exit the interactive session, type:
+```
+/bye
+```
+
+Or press `Ctrl+D` (macOS/Linux) or `Ctrl+C` (Windows).
+
+## Part 4: Multiline Input
+
+### Step 1: Using Multiline Mode
+
+Start another chat session:
+```bash
+ollama run gemma3
+```
+
+Try a multiline input using triple quotes:
+```
+"""Write a short story about a robot
+learning to paint. Make it 
+heartwarming and inspirational."""
+```
+
+## Part 5: Managing Models
+
+### Step 1: View Model Information
+
+Get detailed information about your model:
+
+```bash
+ollama show gemma3
+```
+
+### Step 2: Check Running Models
+
+See which models are currently loaded in memory:
+
+```bash
+ollama ps
+```
+
+### Step 3: Stop a Model
+
+To unload a model from memory:
+
+```bash
+ollama stop gemma3
+```
+
+### Step 4: Remove a Model (Optional)
+
+If you want to free up disk space, you can remove a model:
+
+```bash
+ollama rm gemma3
+```
+
+**Note**: Don't do this if you want to continue with the remaining labs!
+
+## Exercises
+
+### Exercise 1: Model Comparison
+1. Pull another small model: `ollama pull llama3.2`
+2. Ask both models the same question and compare their responses
+3. Document the differences in style, accuracy, and response time
+
+### Exercise 2: Use Cases
+For each of the following tasks, interact with the model and evaluate its performance:
+1. Code explanation (paste a simple Python function and ask it to explain)
+2. Language translation (translate a sentence to another language)
+3. Math problem solving (give it a word problem)
+4. Creative writing (ask for a poem or story)
+
+### Exercise 3: Model Management
+1. Check how much disk space your models are using (hint: check `ollama ls`)
+2. Experiment with the `ollama ps` command while a model is running
+3. Stop and restart a model, observing the load time
+
+## Lab Questions
+
+Answer these questions based on your experience:
+
+1. What is the size of the `gemma3` model you downloaded?
+2. How long did it take for the model to load the first time you ran it?
+3. What happens when you ask the model a question about current events?
+4. What are the advantages of running models locally versus using cloud-based APIs?
+5. What limitations did you notice when interacting with the model?
+
+## Troubleshooting
+
+### Issue: "ollama: command not found"
+- **Solution**: Restart your terminal or add Ollama to your PATH manually
+
+### Issue: Model download is very slow
+- **Solution**: Check your internet connection; large models can take time to download
+
+### Issue: "Out of memory" errors
+- **Solution**: Try a smaller model or close other applications to free up RAM
+
+### Issue: Model responses are very slow
+- **Solution**: This is normal for larger models on systems without GPUs. Consider using a smaller model.
+
+## Summary
+
+In this lab, you learned how to:
+- Install Ollama on your system
+- Download and manage language models
+- Interact with models using the command-line interface
+- Use multiline input for complex prompts
+- Manage model resources (loading, stopping, removing)
+
+## Next Steps
+
+Continue to **Lab 2: Working with the CLI** to learn advanced command-line features and model management techniques.
+