Week 1 Contribution: Code Explainer by r00trose

- Interactive code explainer using Llama 3.2 via Ollama
- Notebook and Terminal modes
- Local LLM integration (no API costs)
- Multiple examples included

week1/community-contributions/r00trose/README.md

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+# Code Explainer - LLM Engineering Week 1
+
+An AI-powered code explanation tool using Llama 3.2 via Ollama.
+
+## 🎯 Project Overview
+
+This project demonstrates prompt engineering and local LLM integration by building a code explanation assistant. The tool analyzes code snippets and provides beginner-friendly, line-by-line explanations.
+
+## ✨ Features
+
+- **Local LLM Integration**: Uses Ollama with Llama 3.2 (no API costs!)
+- **Two Modes of Operation**:
+  - 📓 **Notebook Mode**: Interactive Jupyter notebook with rich Markdown display
+  - 💻 **Terminal Mode**: Interactive CLI for continuous code explanation
+- **Smart Explanations**: 
+  - Summarizes overall purpose
+  - Line-by-line breakdown
+  - Highlights key programming concepts
+  - Beginner-friendly language
+- **Multiple Examples**: Loops, list comprehensions, OOP, recursion, decorators
+- **Streaming Responses**: Real-time output as the model generates
+
+## 🛠️ Technologies Used
+
+- **Ollama**: Local LLM runtime
+- **Llama 3.2**: Meta's language model
+- **OpenAI Python SDK**: API-compatible interface
+- **IPython**: Rich markdown display
+- **python-dotenv**: Environment management
+
+## 📋 Prerequisites
+
+1. **Ollama installed** - Download from [ollama.com](https://ollama.com)
+2. **Python 3.8+**
+3. **Llama 3.2 model pulled**:
+   ```bash
+   ollama pull llama3.2
+   ```
+
+## 🚀 Setup
+
+### 1. Clone the repository
+```bash
+git clone <your-repo-url>
+cd llm-engineering/week1/my-solutions
+```
+
+### 2. Install dependencies
+```bash
+pip install -r requirements.txt
+```
+
+### 3. (Optional) Configure environment
+```bash
+cp .env.example .env
+# Edit .env if needed
+```
+
+## 💡 Usage
+
+### Notebook Mode
+
+1. Open `day1-solution.ipynb` in Jupyter or VS Code
+2. Run cells sequentially
+3. Use `explain_code_interactive()` function with your own code
+
+```python
+explain_code_interactive("""
+def fibonacci(n):
+    if n <= 1:
+        return n
+    return fibonacci(n-1) + fibonacci(n-2)
+""")
+```
+
+### Terminal Mode
+
+```bash
+python code_explainer.py
+```
+
+Then:
+- Paste your code
+- Press Enter twice (empty line)
+- Get explanation!
+
+**Commands:**
+- `quit` / `exit` / `q` - Exit
+- `clear` - Start fresh
+- `examples` - See sample code snippets
+
+## 🎓 Why Ollama?
+
+I chose Ollama over OpenAI API for this project because:
+
+✅ **No API Costs**: Completely free to use  
+✅ **Privacy**: All data stays local  
+✅ **Offline**: Works without internet  
+✅ **Learning**: Hands-on experience with local LLM deployment  
+✅ **Speed**: Fast responses on local hardware  
+
+## 📝 Examples Included
+
+1. **Recursion** - Fibonacci sequence
+2. **Loops** - Simple iteration
+3. **List Comprehensions** - Filtering and mapping
+4. **Object-Oriented Programming** - Classes and methods
+5. **Decorators** - Advanced Python concepts
+
+## 🔧 Customization
+
+### Change the model
+Edit `code_explainer.py`:
+```python
+explainer = CodeExplainer(model="llama3.2:3b")  # Use smaller model
+```
+
+### Adjust temperature
+Lower temperature = more consistent, Higher = more creative:
+```python
+temperature=0.3  # Current setting for code explanations
+```
+
+### Modify system prompt
+Customize how the model explains code in the `system_prompt` variable.
+
+## 🤝 Contributing
+
+This is a course assignment, but feel free to fork and improve!
+
+## 📄 License
+
+MIT License - feel free to use for learning purposes.
+
+## 👤 Author
+
+İrem İrem  
+LLM Engineering Course - Week 1 Assignment
+
+## 🙏 Acknowledgments
+
+- **Ed Donner** - Course instructor for the excellent LLM Engineering course
+- **Anthropic** - For Ollama framework
+- **Meta** - For Llama 3.2 model