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Tplus/src/main/java/net/nuggetmc/ai/command/commands/AICommand.java

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package net.nuggetmc.ai.command.commands;
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import com.jonahseguin.drink.annotation.Autofill;
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import com.jonahseguin.drink.annotation.Command;
import com.jonahseguin.drink.annotation.OptArg;
import com.jonahseguin.drink.annotation.Sender;
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import com.jonahseguin.drink.utils.ChatUtils;
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import net.nuggetmc.ai.TerminatorPlus;
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import net.nuggetmc.ai.bot.Bot;
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import net.nuggetmc.ai.bot.BotManager;
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import net.nuggetmc.ai.bot.agent.legacyagent.ai.IntelligenceAgent;
import net.nuggetmc.ai.bot.agent.legacyagent.ai.NeuralNetwork;
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import net.nuggetmc.ai.command.CommandHandler;
import net.nuggetmc.ai.command.CommandInstance;
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import net.nuggetmc.ai.utils.MathUtils;
import org.bukkit.Bukkit;
import org.bukkit.ChatColor;
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import org.bukkit.command.CommandSender;
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import org.bukkit.entity.Player;
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import org.bukkit.scheduler.BukkitScheduler;
import java.util.ArrayList;
import java.util.List;
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public class AICommand extends CommandInstance {
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/*
* ideas
* ability to export neural network data to a text file, and also load from them
* maybe also have a custom extension like .tplus and encrypt it in base64
*/
private final TerminatorPlus plugin;
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private final BotManager manager;
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private final BukkitScheduler scheduler;
private IntelligenceAgent agent;
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public AICommand(CommandHandler commandHandler) {
super(commandHandler);
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this.plugin = TerminatorPlus.getInstance();
this.manager = plugin.getManager();
this.scheduler = Bukkit.getScheduler();
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}
@Command(
desc = "The root command for bot AI training."
)
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public void root(@Sender CommandSender sender) {
commandHandler.sendRootInfo(this, sender);
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}
@Command(
name = "random",
desc = "Create bots with random neural networks, collecting feed data.",
usage = "<amount> <name> [skin]"
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)
public void random(@Sender Player sender, int n, String name, @OptArg String skin) {
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manager.createBots(sender, name, skin, n, NeuralNetwork.RANDOM);
}
@Command(
name = "reinforcement",
desc = "Begin an AI training session.",
usage = "<population-size> <name> [skin]"
)
public void reinforcement(@Sender Player sender, int populationSize, String name, @OptArg String skin) {
// automatically do the -% thing, store values in map
// for now only 1 session at a time, have a set of commandsenders to see output, including console
// automatically reset all existing bots at the start, set targets towards each other
// also in the future make this a subcommand, with /ai reinforcement defaults, /ai reinforcement begin/start
// or just make /ai defaults with reinforcement options
if (agent != null) {
sender.sendMessage("A session is already active.");
return;
}
sender.sendMessage("Starting a new session...");
agent = new IntelligenceAgent(this, populationSize, name, skin);
agent.addUser(sender);
}
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public IntelligenceAgent getSession() {
return agent;
}
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@Command(
name = "stop",
desc = "End a currently running AI training session."
)
public void stop(@Sender CommandSender sender) {
if (agent == null) {
sender.sendMessage("No session is currently active.");
return;
}
sender.sendMessage("Stopping the current session...");
String name = agent.getName();
clearSession();
scheduler.runTaskLater(plugin, () -> sender.sendMessage("The session " + ChatColor.YELLOW + name + ChatColor.RESET + " has been closed."), 10);
}
public void clearSession() {
if (agent != null) {
agent.stop();
agent = null;
}
}
public boolean hasActiveSession() {
return agent != null;
}
@Command(
name = "info",
desc = "Display neural network information about a bot.",
usage = "<name>",
autofill = "infoAutofill"
)
public void info(@Sender CommandSender sender, String name) {
sender.sendMessage("Processing request...");
scheduler.runTaskAsynchronously(plugin, () -> {
try {
Bot bot = manager.getFirst(name);
if (bot == null) {
sender.sendMessage("Could not find bot " + ChatColor.GREEN + name + ChatColor.RESET + "!");
return;
}
if (!bot.hasNeuralNetwork()) {
sender.sendMessage("The bot " + ChatColor.GREEN + name + ChatColor.RESET + " does not have a neural network!");
return;
}
NeuralNetwork network = bot.getNeuralNetwork();
List<String> strings = new ArrayList<>();
network.nodes().forEach((nodeType, node) -> {
strings.add("");
strings.add(ChatColor.YELLOW + "\"" + nodeType.name().toLowerCase() + "\"" + ChatColor.RESET + ":");
List<String> values = new ArrayList<>();
node.getValues().forEach((dataType, value) -> values.add(ChatUtils.BULLET_FORMATTED + "node"
+ dataType.getShorthand().toUpperCase() + ": " + ChatColor.RED + MathUtils.round2Dec(value)));
strings.addAll(values);
});
sender.sendMessage(ChatUtils.LINE);
sender.sendMessage(ChatColor.DARK_GREEN + "NeuralNetwork" + ChatUtils.BULLET_FORMATTED + ChatColor.GRAY + "[" + ChatColor.GREEN + name + ChatColor.GRAY + "]");
strings.forEach(sender::sendMessage);
sender.sendMessage(ChatUtils.LINE);
}
catch (Exception e) {
sender.sendMessage(ChatUtils.EXCEPTION_MESSAGE);
}
});
}
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@Autofill
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public List<String> infoAutofill(CommandSender sender, String[] args) {
if (args.length == 2) {
return manager.fetchNames();
} else {
return null;
}
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}
}