d849890fac
- Interactive code explainer using Llama 3.2 via Ollama - Notebook and Terminal modes - Local LLM integration (no API costs) - Multiple examples included
145 lines
3.5 KiB
Markdown
145 lines
3.5 KiB
Markdown
# Code Explainer - LLM Engineering Week 1
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An AI-powered code explanation tool using Llama 3.2 via Ollama.
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## 🎯 Project Overview
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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.
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## ✨ Features
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- **Local LLM Integration**: Uses Ollama with Llama 3.2 (no API costs!)
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- **Two Modes of Operation**:
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- 📓 **Notebook Mode**: Interactive Jupyter notebook with rich Markdown display
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- 💻 **Terminal Mode**: Interactive CLI for continuous code explanation
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- **Smart Explanations**:
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- Summarizes overall purpose
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- Line-by-line breakdown
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- Highlights key programming concepts
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- Beginner-friendly language
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- **Multiple Examples**: Loops, list comprehensions, OOP, recursion, decorators
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- **Streaming Responses**: Real-time output as the model generates
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## 🛠️ Technologies Used
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- **Ollama**: Local LLM runtime
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- **Llama 3.2**: Meta's language model
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- **OpenAI Python SDK**: API-compatible interface
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- **IPython**: Rich markdown display
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- **python-dotenv**: Environment management
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## 📋 Prerequisites
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1. **Ollama installed** - Download from [ollama.com](https://ollama.com)
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2. **Python 3.8+**
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3. **Llama 3.2 model pulled**:
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```bash
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ollama pull llama3.2
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```
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## 🚀 Setup
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### 1. Clone the repository
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```bash
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git clone <your-repo-url>
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cd llm-engineering/week1/my-solutions
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```
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### 2. Install dependencies
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```bash
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pip install -r requirements.txt
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```
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### 3. (Optional) Configure environment
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```bash
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cp .env.example .env
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# Edit .env if needed
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```
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## 💡 Usage
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### Notebook Mode
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1. Open `day1-solution.ipynb` in Jupyter or VS Code
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2. Run cells sequentially
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3. Use `explain_code_interactive()` function with your own code
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```python
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explain_code_interactive("""
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def fibonacci(n):
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if n <= 1:
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return n
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return fibonacci(n-1) + fibonacci(n-2)
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""")
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```
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### Terminal Mode
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```bash
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python code_explainer.py
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```
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Then:
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- Paste your code
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- Press Enter twice (empty line)
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- Get explanation!
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**Commands:**
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- `quit` / `exit` / `q` - Exit
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- `clear` - Start fresh
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- `examples` - See sample code snippets
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## 🎓 Why Ollama?
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I chose Ollama over OpenAI API for this project because:
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✅ **No API Costs**: Completely free to use
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✅ **Privacy**: All data stays local
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✅ **Offline**: Works without internet
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✅ **Learning**: Hands-on experience with local LLM deployment
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✅ **Speed**: Fast responses on local hardware
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## 📝 Examples Included
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1. **Recursion** - Fibonacci sequence
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2. **Loops** - Simple iteration
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3. **List Comprehensions** - Filtering and mapping
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4. **Object-Oriented Programming** - Classes and methods
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5. **Decorators** - Advanced Python concepts
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## 🔧 Customization
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### Change the model
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Edit `code_explainer.py`:
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```python
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explainer = CodeExplainer(model="llama3.2:3b") # Use smaller model
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```
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### Adjust temperature
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Lower temperature = more consistent, Higher = more creative:
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```python
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temperature=0.3 # Current setting for code explanations
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```
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### Modify system prompt
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Customize how the model explains code in the `system_prompt` variable.
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## 🤝 Contributing
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This is a course assignment, but feel free to fork and improve!
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## 📄 License
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MIT License - feel free to use for learning purposes.
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## 👤 Author
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İrem İrem
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LLM Engineering Course - Week 1 Assignment
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## 🙏 Acknowledgments
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- **Ed Donner** - Course instructor for the excellent LLM Engineering course
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- **Anthropic** - For Ollama framework
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- **Meta** - For Llama 3.2 model
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