- Add architecture, CI/CD, CLI reference documentation - Update installation, operations, and quick-start guides - Add Jupyter workflow and queue documentation - New landing page and research runner plan
2.9 KiB
2.9 KiB
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| Fetch ML Documentation | true |
Fetch ML - Secure Machine Learning Platform
A secure, containerized platform for running machine learning experiments with role-based access control and comprehensive audit trails.
Quick Start
New to the project? Start here!
# Clone the repository
git clone https://github.com/your-username/fetch_ml.git
cd fetch_ml
# Start development stack with monitoring
make dev-up
# Run basic tests
make test-unit
# Then follow the Quick Start guide
# docs/src/quick-start.md
Quick Navigation
🚀 Getting Started
- Getting Started Guide - Complete setup instructions
- Simple Install - Quick installation guide
🔒 Security & Authentication
- Security Overview - Security best practices
- API Key Process - Generate and manage API keys
- User Permissions - Role-based access control
⚙️ Configuration
- Environment Variables - Configuration options
- Smart Defaults - Default configuration settings
🛠️ Development
- Architecture - System architecture and design
- CLI Reference - Command-line interface documentation
- Testing Guide - Testing procedures and guidelines
- Jupyter Workflow - CLI and Jupyter integration
- Queue System - Job queue implementation
🏭 Production Deployment
- Deployment Guide - Production deployment instructions
- Performance & Monitoring - Monitoring and observability
- Operations Guide - Production operations
Features
- 🔐 Secure Authentication - RBAC with API keys, roles, and permissions
- 🐳 Containerized - Podman-based secure execution environments
- 🗄️ Database Storage - SQLite backend for user management (optional)
- 📋 Audit Trail - Complete logging of all actions
- 🚀 Production Ready - Security audits, systemd services, log rotation
Available Commands
# Core commands
make help # See all available commands
make build # Build all binaries
make test-unit # Run tests
# User management
./bin/user_manager --config configs/config_dev.yaml --cmd generate-key --username new_user --role data_scientist
./bin/user_manager --config configs/config_dev.yaml --cmd list-users
# Run services
./bin/worker --config configs/config_dev.yaml --api-key YOUR_KEY
./bin/tui --config configs/config_dev.yaml
./bin/data_manager --config configs/config_dev.yaml
Need Help?
- 📖 Documentation: Use the navigation menu on the left
- ⚡ Quick help:
make help - 🧪 Tests:
make test-unit
Happy ML experimenting!