README.md

metadata

title: Ai Training Simulator
emoji: 🧠
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 6.16.0
python_version: '3.13'
app_file: app.py
pinned: false
license: mit
short_description: Idle/strategy game
hf_oauth: true

AI Training Simulator

Build Small Hackathon 2026 — Chapter Two (Adventure in Thousand Token Wood)

A browser strategy/idle game where you manage a fake AI startup, all in a terminal-like interface.

How it works

• Start with $100
• Buy upgrades (model size, dataset size/quality, architecture, hardware)
• Run Train Model - cost and reward are simulated based on your upgrade combination
• The chat interface uses FlameF0X/Qwen3-4B-Distilled-Claude-4.6 with huggingface inference. It's a CoT model.
  • Low quality → high temperature → incoherent word salad
  • Upgrade your stack → temperature drops → coherent output
• Unlock Cloud Inference for recurring revenue

Badges targeted

• 🎨 Off-Brand — fully custom UI (no default Gradio look)

Files

File	Purpose
app.py	Gradio app + action handler
state.py	Pure Python game logic (train, upgrade, cloud)
game_config.py	All balance numbers — edit this to tune the game
requirements.txt	Only gradio needed (model runs in browser)

Customising / balancing

Everything tunable is in game_config.py:

• STARTING_MONEY — how much the player starts with
• UPGRADES — levels, costs, quality scores per upgrade
• BASE_TRAIN_COST / multiplier tables — training run economics
• BASE_REWARD + QUALITY_EXPONENT — reward curve shape
• REWARD_NOISE_PCT — variance per run
• CLOUD_* constants — cloud inference economics
• CHAT_TEMP_* — how temperature maps to model quality

Author: Martico2432