https://github.com/xenoswarlocks/metriforge
Generate intelligent, realistic test emails containing system performance metrics, trend analysis, and actionable insights using AI
https://github.com/xenoswarlocks/metriforge
Last synced: 2 months ago
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Generate intelligent, realistic test emails containing system performance metrics, trend analysis, and actionable insights using AI
- Host: GitHub
- URL: https://github.com/xenoswarlocks/metriforge
- Owner: XenosWarlocks
- License: mit
- Created: 2025-01-08T11:49:56.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-01-08T11:58:54.000Z (4 months ago)
- Last Synced: 2025-01-18T10:32:41.799Z (4 months ago)
- Language: Python
- Size: 12.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🎯 MetriForge: Smart Test Email Generator for System Metrics
[](https://opensource.org/licenses/MIT)
[](https://www.python.org/downloads/)
[](https://github.com/psf/black)
> Generate intelligent, realistic test emails containing system performance metrics, trend analysis, and actionable insights using AI.
## 🚀 Features
- **Smart Metric Generation**: Creates realistic system performance, reliability, and resource utilization metrics
- **Trend Analysis**: Generates meaningful time-series data with configurable trends and volatility
- **AI-Powered Content**: Uses Google's Gemini AI to create contextually relevant email content
- **Customizable Focus Areas**: Target specific metric categories (performance, reliability, resource usage)
- **Professional Formatting**: ASCII tables, trend visualizations, and clear sectioning
- **Batch Processing**: Generate multiple unique test emails with consistent metrics
- **Detailed Reporting**: Comprehensive generation reports with metric summaries and trends
## 📋 Prerequisites
- Python 3.8 or higher
- Google Cloud API key with Gemini AI access
- Required Python packages (see `requirements.txt`)
## 🛠️ Installation
1. Clone the repository:
```bash
git clone https://github.com/XenosWarlocks/metriforge.git
cd metriforge
```
2. Create and activate a virtual environment:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. Install required packages:
```bash
pip install -r requirements.txt
```
## 💫 Usage
Basic usage with default settings:
```bash
python metriforge.py --api-key YOUR_API_KEY --num-emails 5
```
Advanced usage with customization:
```bash
python metriforge.py \
--api-key YOUR_API_KEY \
--num-emails 10 \
--word-count 500 \
--metrics-focus performance \
--urgency-level high \
--min-trend-days 60 \
--include-recommendations \
--verbose
```
## 🎨 Configuration Options
| Option | Description | Default |
|--------|-------------|---------|
| `--api-key` | Google Gemini AI API key | Required |
| `--num-emails` | Number of emails to generate | Required |
| `--word-count` | Words per email | 300 |
| `--output-dir` | Output directory | "metric_reports" |
| `--metrics-focus` | Focus area (performance/reliability/resource/all) | "all" |
| `--urgency-level` | Anomaly frequency (low/medium/high) | "medium" |
| `--min-trend-days` | Days of trend data | 30 |
| `--include-recommendations` | Add AI recommendations | False |
| `--verbose` | Detailed logging | False |
## 📊 Output Format
The generator creates three types of files for each run:
1. **Test Emails** (`test_email_*.txt`):
- Professional format with headers
- Executive summary
- Metric tables and trends
- Analysis and recommendations
2. **Metric Data** (`metrics_*.json`):
- Raw metric values
- Trend data
- Targets and thresholds
- Performance indicators
3. **Batch Report** (`generation_report_*.json`):
- Generation statistics
- Average metrics
- Trend analysis
- Success/failure rates
## 🌟 Example Output
```
+==================================================+
| AUTOMATED METRICS REPORT |
| THIS IS A TEST EMAIL |
+==================================================+
Executive Summary:
Critical performance metrics show a 15% improvement in response time...
Current Metrics Performance:
+-----------------+----------+---------+----------+-----------+
| Metric | Current | Target | Unit | Status |
+-----------------+----------+---------+----------+-----------+
| response_time | 85.20 | 100.0 | ms | NORMAL |
| throughput | 1025.50 | 1000.0 | req/s | HIGH |
+-----------------+----------+---------+----------+-----------+
```
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
## 📝 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## ✨ Acknowledgments
- Google Gemini AI for natural language generation
- The Python community for excellent libraries
- Contributors and testers
## 🔮 Future Plans
- [ ] Add support for custom metric templates
- [ ] Implement more sophisticated trend algorithms
- [ ] Add export to various formats (PDF, HTML)
- [ ] Create a web interface
- [ ] Add support for more AI models
- [ ] Implement real-time metric simulation
## 📧 Contact
For questions and support, please open an issue or contact the maintainers.
---
Made with ❤️ by [Xenos Warlocks]