Simple Installation Guide¶

Quick Start (5 minutes)¶

# 1. Install
git clone https://github.com/jfraeys/fetch_ml.git
cd fetch_ml
make install

# 2. Setup (auto-configures)
./bin/ml setup

# 3. Run experiments
./bin/ml run my-experiment.py

That's it. Everything else is optional.

What If I Want More Control?¶

Manual Configuration (Optional)¶

# Edit settings if defaults don't work
nano ~/.ml/config.toml

Monitoring Dashboard (Optional)¶

# Real-time monitoring
./bin/tui

Senior Developer Feedback¶

"Keep it simple" - Most data scientists want: 1. One installation command 2. Sensible defaults
3. Works without configuration 4. Advanced features available when needed

Current plan is too complex because it asks users to decide between: - CLI vs TUI vs Both - Zig vs Go build tools - Manual vs auto config - Multiple environment variables

Better approach: Start simple, add complexity gradually.

Recommended Simplified Workflow¶

Single Binary - Combine CLI + basic TUI functionality
Auto-Discovery - Detect common ML environments automatically
Progressive Disclosure - Show advanced options only when needed
Zero Config - Work out-of-the-box with localhost defaults

The goal: "It just works" for 80% of use cases.