diff --git a/README.md b/README.md
index 5817980..deafdfa 100644
--- a/README.md
+++ b/README.md
@@ -1,369 +1,369 @@
-# 🚀 LLM-Powered URL Health Checker Generator
-
-[![Python](https://img.shields.io/badge/Python-3.10%2B-blue.svg)](https://python.org)
-[![LLM APIs](https://img.shields.io/badge/LLM-Multi--Provider-green.svg)](https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator/src/branch/main)
-[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
-[![Jupyter](https://img.shields.io/badge/Jupyter-Notebook-orange.svg)](https://jupyter.org)
-
-🤖 **AI-Powered Code Generation** | 🌐 **URL Health Monitoring** | 📊 **DevOps Tooling** | ⚡ **Automated CLI Tools**
-
-> **Transform ideas into code with ANY LLM API!** This project showcases how to harness various Large Language Model APIs (OpenAI, Anthropic Claude, Google Gemini, Azure, local models, and more) to automatically generate production-ready Python CLI tools. Watch as AI creates a sophisticated URL health monitoring system that rivals hand-coded solutions.
-
-## 🎯 What This Project Does
-
-This project demonstrates cutting-edge AI-assisted development by:
-- 🧠 **Intelligently generating** complete Python applications using any LLM API
-- 🔍 **Creating a professional URL health checker** with advanced monitoring capabilities
-- 📈 **Showcasing practical AI applications** in DevOps and system administration
-- 🛠️ **Providing a universal framework** for AI-powered code generation across multiple providers
-
-## 🌟 Supported LLM Providers
-
-| Provider | Models | Configuration |
-|----------|---------|--------------|
-| **OpenAI** | GPT-4, GPT-3.5-Turbo | Standard OpenAI API |
-| **Anthropic** | Claude 3 Opus, Sonnet, Haiku | Claude API |
-| **Google** | Gemini Pro, Gemini Ultra | Google AI Studio |
-| **Azure OpenAI** | GPT-4, GPT-3.5 | Azure OpenAI Service |
-| **Cohere** | Command, Generate | Cohere API |
-| **Hugging Face** | Various open models | Inference API |
-| **Local Models** | LLaMA, Mistral, etc. | Ollama, LM Studio |
-| **Custom APIs** | Any OpenAI-compatible | Custom endpoints |
-
-## 🚀 Features
-
-### Core Framework
-- **Universal LLM Support**: Works with any OpenAI-compatible API endpoint
-- **Provider Flexibility**: Easy switching between different LLM providers
-- **Smart Configuration Management**: Secure environment variable handling with validation
-- **AI-Powered Code Generation**: Uses your choice of LLM to generate complete, functional Python scripts
-- **Modular Design**: Clean, reusable configuration class for API integration
-- **Error Handling**: Robust validation and error management across providers
-
-### Generated URL Health Checker
-- **Batch URL Testing**: Process multiple URLs from input files
-- **Performance Monitoring**: Measure and report response times
-- **Status Code Tracking**: Monitor HTTP response codes
-- **Configurable Parameters**: Customizable timeouts and retry mechanisms
-- **CSV Export**: Structured data output for analysis
-- **Summary Statistics**: Real-time reporting of test results
-- **CLI Interface**: Professional command-line tool with argument parsing
-
-## ⚡ Quick Start
-
-```bash
-# 1. Clone and setup
-git clone https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator.git
-cd LLM-Powered-URL-Health-Checker-Generator
-
-# 2. Install dependencies
-pip install openai anthropic google-generativeai python-dotenv requests
-
-# 3. Configure environment (see provider examples below)
-cp .env.example .env
-# Edit .env with your preferred provider
-
-# 4. Run the notebook to generate the tool
-jupyter notebook Final.ipynb
-
-# 5. Use the generated URL checker
-echo "https://github.com" > urls.txt
-python url_checker.py --input urls.txt --output results.csv
-```
-
-## 📋 Prerequisites
-
-- Python 3.10+
-- Access to at least one LLM API (see supported providers)
-- Required Python packages (see installation)
-
-## 🔧 Detailed Installation
-
-### 1. **Clone the Repository**
-   ```bash
-   git clone https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator.git
-   cd LLM-Powered-URL-Health-Checker-Generator
-   ```
-
-### 2. **Set Up Python Environment** (Recommended)
-   ```bash
-   # Create virtual environment
-   python -m venv venv
-   
-   # Activate it (Windows)
-   venv\Scripts\activate
-   # Or on Linux/Mac
-   source venv/bin/activate
-   ```
-
-### 3. **Install Dependencies**
-   ```bash
-   # Core dependencies
-   pip install python-dotenv requests jupyter
-   
-   # Install based on your provider:
-   pip install openai           # For OpenAI
-   pip install anthropic        # For Claude
-   pip install google-generativeai  # For Gemini
-   # Or install all:
-   pip install -r requirements.txt
-   ```
-
-### 4. **Configure Environment Variables**
-
-Create a `.env` file based on your chosen provider:
-
-#### OpenAI Configuration
-```env
-LLM_PROVIDER=openai
-OPENAI_API_KEY=sk-your_api_key_here
-BASE_URL=https://api.openai.com/v1
-MODEL_NAME=gpt-4
-```
-
-#### Anthropic Claude Configuration
-```env
-LLM_PROVIDER=anthropic
-ANTHROPIC_API_KEY=sk-ant-your_api_key_here
-BASE_URL=https://api.anthropic.com
-MODEL_NAME=claude-3-opus-20240229
-```
-
-#### Google Gemini Configuration
-```env
-LLM_PROVIDER=google
-GOOGLE_API_KEY=your_api_key_here
-MODEL_NAME=gemini-pro
-```
-
-#### Azure OpenAI Configuration
-```env
-LLM_PROVIDER=azure
-AZURE_API_KEY=your_api_key_here
-BASE_URL=https://your-resource.openai.azure.com
-AZURE_DEPLOYMENT_NAME=your-deployment
-MODEL_NAME=gpt-4
-```
-
-#### Local Models (Ollama) Configuration
-```env
-LLM_PROVIDER=ollama
-BASE_URL=http://localhost:11434/v1
-MODEL_NAME=llama2:13b
-# No API key needed for local models
-```
-
-#### Custom OpenAI-Compatible API
-```env
-LLM_PROVIDER=custom
-API_KEY=your_api_key_here
-BASE_URL=https://your-custom-endpoint.com/v1
-MODEL_NAME=your-model-name
-```
-
-## 🎯 Usage Guide
-
-### Step 1: Generate the URL Checker
-1. **Open the Jupyter Notebook:**
-   ```bash
-   jupyter notebook Final.ipynb
-   ```
-
-2. **Select your LLM provider** in the configuration cell
-
-3. **Execute all cells** to:
-   - Configure your chosen LLM API connection
-   - Generate the URL health checker script
-   - Save it as `url_checker.py`
-
-### Step 2: Prepare Your URL List
-Create a `urls.txt` file with websites to monitor:
-```text
-https://www.google.com
-https://github.com
-https://stackoverflow.com
-https://httpbin.org/status/200
-https://httpbin.org/delay/3
-# Comments are ignored
-https://nonexistent-website-12345.com
-```
-
-### Step 3: Run the Health Checker
-```bash
-# Basic usage
-python url_checker.py
-
-# Custom parameters
-python url_checker.py --input my_sites.txt --output health_report.csv --timeout 10 --retries 5
-```
-
-## 📊 Example Output
-
-### Console Output
-```
-🔍 URL Health Checker Starting...
-✅ https://www.google.com - 200 OK (156ms)
-✅ https://github.com - 200 OK (245ms)
-❌ https://nonexistent-site.com - Connection failed
-📊 Summary: 2/3 successful (66.7%), Average: 200ms
-```
-
-### CSV Report (`results.csv`)
-```csv
-url,status_code,response_time_ms,success
-https://www.google.com,200,156.3,True
-https://github.com,200,245.7,True
-https://nonexistent-site.com,0,0.0,False
-```
-
-## 🛠️ Command Line Options
-
-| Option | Default | Description | Example |
-|--------|---------|-------------|---------|
-| `--input` | `urls.txt` | Input file containing URLs | `--input websites.txt` |
-| `--output` | `results.csv` | Output CSV file for results | `--output report.csv` |
-| `--timeout` | `5` | Request timeout in seconds | `--timeout 10` |
-| `--retries` | `3` | Number of retry attempts | `--retries 5` |
-
-## 🏗️ Project Architecture
-
-```
-LLM-Powered-URL-Health-Checker-Generator/
-├── 📓 Final.ipynb              # Main LLM integration notebook
-├── 📄 README.md               # This documentation
-├── 🐍 url_checker.py          # Generated URL health checker
-├── ⚙️  .env                   # Environment variables (create this)
-├── ⚙️  .env.example           # Example environment configuration
-├── 📝 urls.txt               # Input URLs list
-├── 📊 results.csv            # Output results
-├── 📦 requirements.txt       # Python dependencies
-└── 📜 .gitignore             # Git ignore file
-```
-
-## 🔐 Security & Best Practices
-
-### Environment Security
-- ✅ **Never commit `.env` files** - Add to `.gitignore`
-- ✅ **Use environment variables** for all API keys
-- ✅ **Rotate API keys regularly**
-- ✅ **Monitor API usage** and set billing alerts
-- ✅ **Use provider-specific security features** (API key restrictions, rate limits)
-
-### Code Safety
-- ✅ **Review generated code** before execution
-- ✅ **Test with safe URLs** first
-- ✅ **Use virtual environments** to isolate dependencies
-- ✅ **Validate input files** before processing
-
-
-
-## 🤖 LLM Integration Details
-
-### Model Configuration Examples
-
-#### OpenAI GPT-4
-```python
-model="gpt-4"
-temperature=0.2        # Low for consistent code
-max_tokens=8000        # Balanced for complete scripts
-```
-
-#### Claude 3 Opus
-```python
-model="claude-3-opus-20240229"
-temperature=0.2
-max_tokens=4000
-```
-
-#### Gemini Pro
-```python
-model="gemini-pro"
-temperature=0.2
-max_tokens=8192
-```
-
-#### Local Models (Ollama)
-```python
-model="codellama:13b"
-temperature=0.1        # Very low for code consistency
-max_tokens=4096
-```
-
-### Prompt Engineering
-The project uses carefully crafted prompts optimized for each provider to ensure:
-- 🎯 **Focused output** - Only relevant code generation
-- 🔧 **Practical functionality** - Real-world utility
-- 📚 **Documentation** - Self-explaining code
-- ⚡ **Efficiency** - Optimized performance
-- 🔄 **Provider compatibility** - Works across different LLMs
-
-## 📈 Use Cases
-
-### DevOps & Monitoring
-- **Website uptime monitoring**
-- **API endpoint health checks**
-- **Load balancer status verification**
-- **CDN performance testing**
-- **Multi-region availability checking**
-
-### Development & Testing
-- **Integration test automation**
-- **Environment validation**
-- **Dependency verification**
-- **Service discovery**
-- **CI/CD pipeline validation**
-
-
-## 🤝 Contributing
-
-We welcome contributions! Here's how to get started:
-
-### 1. Fork & Clone
-```bash
-# Fork the repository on GitPasha first, then:
-git clone https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator.git
-```
-
-### 2. Create Feature Branch
-```bash
-git checkout -b feature/amazing-new-feature
-```
-### 3. Make Changes
-- Add support for new LLM providers
-- Improve prompt engineering
-- Add new tool generation capabilities
-- Update documentation
-- Add tests if applicable
-
-### 4. Submit Pull Request
-```bash
-git add .
-git commit -m "✨ Add amazing new feature"
-git push origin feature/amazing-new-feature
-```
-
-
-## 🙏 Acknowledgments
-
-- **LLM Providers** - OpenAI, Anthropic, Google, and the open-source community
-- **Python Community** - For excellent libraries (`requests`, `python-dotenv`)
-- **Jupyter Project** - For the interactive development environment
-- **Open Source Models** - LLaMA, Mistral, and other contributors
-- **Contributors** - Everyone who helps improve this project
-
-## 📞 Support & Community
-
-### Getting Help
-- 🐛 **Bug Reports**: [GitPasha Issues](https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator/issues)
-- 💡 **Feature Requests**: [GitPasha Discussions](https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator/discussions)
-- 📖 **Documentation**: This README and notebook comments
-- 💬 **Community**: Join our discussions for tips and tricks
-
-### Troubleshooting
-| Problem | Solution |
-|---------|----------|
-| `ModuleNotFoundError` | Run `pip install -r requirements.txt` |
-| `API Key Error` | Check your `.env` file and provider configuration |
-| `Timeout Issues` | Increase `--timeout` parameter or switch providers |
-| `Generation Fails` | Verify API credits, permissions, and model availability |
+# 🚀 LLM-Powered URL Health Checker Generator
+
+[![Python](https://img.shields.io/badge/Python-3.10%2B-blue.svg)](https://python.org)
+[![LLM APIs](https://img.shields.io/badge/LLM-Multi--Provider-green.svg)](https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator/src/branch/main)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+[![Jupyter](https://img.shields.io/badge/Jupyter-Notebook-orange.svg)](https://jupyter.org)
+
+🤖 **AI-Powered Code Generation** | 🌐 **URL Health Monitoring** | 📊 **DevOps Tooling** | ⚡ **Automated CLI Tools**
+
+> **Transform ideas into code with ANY LLM API!** This project showcases how to harness various Large Language Model APIs (OpenAI, Anthropic Claude, Google Gemini, Azure, local models, and more) to automatically generate production-ready Python CLI tools. Watch as AI creates a sophisticated URL health monitoring system that rivals hand-coded solutions.
+
+## 🎯 What This Project Does
+
+This project demonstrates cutting-edge AI-assisted development by:
+- 🧠 **Intelligently generating** complete Python applications using any LLM API
+- 🔍 **Creating a professional URL health checker** with advanced monitoring capabilities
+- 📈 **Showcasing practical AI applications** in DevOps and system administration
+- 🛠️ **Providing a universal framework** for AI-powered code generation across multiple providers
+
+## 🌟 Supported LLM Providers
+
+| Provider | Models | Configuration |
+|----------|---------|--------------|
+| **OpenAI** | GPT-4, GPT-3.5-Turbo | Standard OpenAI API |
+| **Anthropic** | Claude 3 Opus, Sonnet, Haiku | Claude API |
+| **Google** | Gemini Pro, Gemini Ultra | Google AI Studio |
+| **Azure OpenAI** | GPT-4, GPT-3.5 | Azure OpenAI Service |
+| **Cohere** | Command, Generate | Cohere API |
+| **Hugging Face** | Various open models | Inference API |
+| **Local Models** | LLaMA, Mistral, etc. | Ollama, LM Studio |
+| **Custom APIs** | Any OpenAI-compatible | Custom endpoints |
+
+## 🚀 Features
+
+### Core Framework
+- **Universal LLM Support**: Works with any OpenAI-compatible API endpoint
+- **Provider Flexibility**: Easy switching between different LLM providers
+- **Smart Configuration Management**: Secure environment variable handling with validation
+- **AI-Powered Code Generation**: Uses your choice of LLM to generate complete, functional Python scripts
+- **Modular Design**: Clean, reusable configuration class for API integration
+- **Error Handling**: Robust validation and error management across providers
+
+### Generated URL Health Checker
+- **Batch URL Testing**: Process multiple URLs from input files
+- **Performance Monitoring**: Measure and report response times
+- **Status Code Tracking**: Monitor HTTP response codes
+- **Configurable Parameters**: Customizable timeouts and retry mechanisms
+- **CSV Export**: Structured data output for analysis
+- **Summary Statistics**: Real-time reporting of test results
+- **CLI Interface**: Professional command-line tool with argument parsing
+
+## ⚡ Quick Start
+
+```bash
+# 1. Clone and setup
+git clone https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator.git
+cd LLM-Powered-URL-Health-Checker-Generator
+
+# 2. Install dependencies
+pip install openai anthropic google-generativeai python-dotenv requests
+
+# 3. Configure environment (see provider examples below)
+cp .env.example .env
+# Edit .env with your preferred provider
+
+# 4. Run the notebook to generate the tool
+jupyter notebook Final.ipynb
+
+# 5. Use the generated URL checker
+echo "https://github.com" > urls.txt
+python url_checker.py --input urls.txt --output results.csv
+```
+
+## 📋 Prerequisites
+
+- Python 3.10+
+- Access to at least one LLM API (see supported providers)
+- Required Python packages (see installation)
+
+## 🔧 Detailed Installation
+
+### 1. **Clone the Repository**
+   ```bash
+   git clone https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator.git
+   cd LLM-Powered-URL-Health-Checker-Generator
+   ```
+
+### 2. **Set Up Python Environment** (Recommended)
+   ```bash
+   # Create virtual environment
+   python -m venv venv
+   
+   # Activate it (Windows)
+   venv\Scripts\activate
+   # Or on Linux/Mac
+   source venv/bin/activate
+   ```
+
+### 3. **Install Dependencies**
+   ```bash
+   # Core dependencies
+   pip install python-dotenv requests jupyter
+   
+   # Install based on your provider:
+   pip install openai           # For OpenAI
+   pip install anthropic        # For Claude
+   pip install google-generativeai  # For Gemini
+   # Or install all:
+   pip install -r requirements.txt
+   ```
+
+### 4. **Configure Environment Variables**
+
+Create a `.env` file based on your chosen provider:
+
+#### OpenAI Configuration
+```env
+LLM_PROVIDER=openai
+OPENAI_API_KEY=sk-your_api_key_here
+BASE_URL=https://api.openai.com/v1
+MODEL_NAME=gpt-4
+```
+
+#### Anthropic Claude Configuration
+```env
+LLM_PROVIDER=anthropic
+ANTHROPIC_API_KEY=sk-ant-your_api_key_here
+BASE_URL=https://api.anthropic.com
+MODEL_NAME=claude-3-opus-20240229
+```
+
+#### Google Gemini Configuration
+```env
+LLM_PROVIDER=google
+GOOGLE_API_KEY=your_api_key_here
+MODEL_NAME=gemini-pro
+```
+
+#### Azure OpenAI Configuration
+```env
+LLM_PROVIDER=azure
+AZURE_API_KEY=your_api_key_here
+BASE_URL=https://your-resource.openai.azure.com
+AZURE_DEPLOYMENT_NAME=your-deployment
+MODEL_NAME=gpt-4
+```
+
+#### Local Models (Ollama) Configuration
+```env
+LLM_PROVIDER=ollama
+BASE_URL=http://localhost:11434/v1
+MODEL_NAME=llama2:13b
+# No API key needed for local models
+```
+
+#### Custom OpenAI-Compatible API
+```env
+LLM_PROVIDER=custom
+API_KEY=your_api_key_here
+BASE_URL=https://your-custom-endpoint.com/v1
+MODEL_NAME=your-model-name
+```
+
+## 🎯 Usage Guide
+
+### Step 1: Generate the URL Checker
+1. **Open the Jupyter Notebook:**
+   ```bash
+   jupyter notebook Final.ipynb
+   ```
+
+2. **Select your LLM provider** in the configuration cell
+
+3. **Execute all cells** to:
+   - Configure your chosen LLM API connection
+   - Generate the URL health checker script
+   - Save it as `url_checker.py`
+
+### Step 2: Prepare Your URL List
+Create a `urls.txt` file with websites to monitor:
+```text
+https://www.google.com
+https://github.com
+https://stackoverflow.com
+https://httpbin.org/status/200
+https://httpbin.org/delay/3
+# Comments are ignored
+https://nonexistent-website-12345.com
+```
+
+### Step 3: Run the Health Checker
+```bash
+# Basic usage
+python url_checker.py
+
+# Custom parameters
+python url_checker.py --input my_sites.txt --output health_report.csv
+```
+
+## 📊 Example Output
+
+### Console Output
+```
+🔍 URL Health Checker Starting...
+✅ https://www.google.com - 200 OK (156ms)
+✅ https://github.com - 200 OK (245ms)
+❌ https://nonexistent-site.com - Connection failed
+📊 Summary: 2/3 successful (66.7%), Average: 200ms
+```
+
+### CSV Report (`results.csv`)
+```csv
+url,status_code,response_time_ms,success
+https://www.google.com,200,156.3,True
+https://github.com,200,245.7,True
+https://nonexistent-site.com,0,0.0,False
+```
+
+## 🛠️ Command Line Options
+
+| Option | Default | Description | Example |
+|--------|---------|-------------|---------|
+| `--input` | `urls.txt` | Input file containing URLs | `--input websites.txt` |
+| `--output` | `results.csv` | Output CSV file for results | `--output report.csv` |
+| `--timeout` | `5` | Request timeout in seconds | `--timeout 10` |
+| `--retries` | `3` | Number of retry attempts | `--retries 5` |
+
+## 🏗️ Project Architecture
+
+```
+LLM-Powered-URL-Health-Checker-Generator/
+├── 📓 Final.ipynb              # Main LLM integration notebook
+├── 📄 README.md               # This documentation
+├── 🐍 url_checker.py          # Generated URL health checker
+├── ⚙️  .env                   # Environment variables (create this)
+├── ⚙️  .env.example           # Example environment configuration
+├── 📝 urls.txt               # Input URLs list
+├── 📊 results.csv            # Output results
+├── 📦 requirements.txt       # Python dependencies
+└── 📜 .gitignore             # Git ignore file
+```
+
+## 🔐 Security & Best Practices
+
+### Environment Security
+- ✅ **Never commit `.env` files** - Add to `.gitignore`
+- ✅ **Use environment variables** for all API keys
+- ✅ **Rotate API keys regularly**
+- ✅ **Monitor API usage** and set billing alerts
+- ✅ **Use provider-specific security features** (API key restrictions, rate limits)
+
+### Code Safety
+- ✅ **Review generated code** before execution
+- ✅ **Test with safe URLs** first
+- ✅ **Use virtual environments** to isolate dependencies
+- ✅ **Validate input files** before processing
+
+
+
+## 🤖 LLM Integration Details
+
+### Model Configuration Examples
+
+#### OpenAI GPT-4
+```python
+model="gpt-4"
+temperature=0.2        # Low for consistent code
+max_tokens=8000        # Balanced for complete scripts
+```
+
+#### Claude 3 Opus
+```python
+model="claude-3-opus-20240229"
+temperature=0.2
+max_tokens=4000
+```
+
+#### Gemini Pro
+```python
+model="gemini-pro"
+temperature=0.2
+max_tokens=8192
+```
+
+#### Local Models (Ollama)
+```python
+model="codellama:13b"
+temperature=0.1        # Very low for code consistency
+max_tokens=4096
+```
+
+### Prompt Engineering
+The project uses carefully crafted prompts optimized for each provider to ensure:
+- 🎯 **Focused output** - Only relevant code generation
+- 🔧 **Practical functionality** - Real-world utility
+- 📚 **Documentation** - Self-explaining code
+- ⚡ **Efficiency** - Optimized performance
+- 🔄 **Provider compatibility** - Works across different LLMs
+
+## 📈 Use Cases
+
+### DevOps & Monitoring
+- **Website uptime monitoring**
+- **API endpoint health checks**
+- **Load balancer status verification**
+- **CDN performance testing**
+- **Multi-region availability checking**
+
+### Development & Testing
+- **Integration test automation**
+- **Environment validation**
+- **Dependency verification**
+- **Service discovery**
+- **CI/CD pipeline validation**
+
+
+## 🤝 Contributing
+
+We welcome contributions! Here's how to get started:
+
+### 1. Fork & Clone
+```bash
+# Fork the repository on GitPasha first, then:
+git clone https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator.git
+```
+
+### 2. Create Feature Branch
+```bash
+git checkout -b feature/amazing-new-feature
+```
+### 3. Make Changes
+- Add support for new LLM providers
+- Improve prompt engineering
+- Add new tool generation capabilities
+- Update documentation
+- Add tests if applicable
+
+### 4. Submit Pull Request
+```bash
+git add .
+git commit -m "✨ Add amazing new feature"
+git push origin feature/amazing-new-feature
+```
+
+
+## 🙏 Acknowledgments
+
+- **LLM Providers** - OpenAI, Anthropic, Google, and the open-source community
+- **Python Community** - For excellent libraries (`requests`, `python-dotenv`)
+- **Jupyter Project** - For the interactive development environment
+- **Open Source Models** - LLaMA, Mistral, and other contributors
+- **Contributors** - Everyone who helps improve this project
+
+## 📞 Support & Community
+
+### Getting Help
+- 🐛 **Bug Reports**: [GitPasha Issues](https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator/issues)
+- 💡 **Feature Requests**: [GitPasha Discussions](https://app.gitpasha.com/MahmoudZaafan/LLM-Powered-URL-Health-Checker-Generator/discussions)
+- 📖 **Documentation**: This README and notebook comments
+- 💬 **Community**: Join our discussions for tips and tricks
+
+### Troubleshooting
+| Problem | Solution |
+|---------|----------|
+| `ModuleNotFoundError` | Run `pip install -r requirements.txt` |
+| `API Key Error` | Check your `.env` file and provider configuration |
+| `Timeout Issues` | Increase `--timeout` parameter or switch providers |
+| `Generation Fails` | Verify API credits, permissions, and model availability |
 | `Provider Not Working` | Check API end
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