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Author SHA1 Message Date
84bd8d5a9f MVP 2024-01-01 14:27:10 -05:00
8 changed files with 376 additions and 12 deletions

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@ -4,3 +4,4 @@ STATUS_CHANNEL_ID=
DEBUG= DEBUG=
HEARTBEAT_URL= HEARTBEAT_URL=
BOT_ID= BOT_ID=
OPENAI_API_KEY=

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@ -11,6 +11,7 @@
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@ -19,6 +19,7 @@
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},
"ai": {
"chatModel": "gpt-3.5-turbo",
"chatPromptCentsPer": 0.15,
"chatPromptUnits": 1000,
"chatResCentsPer": 0.2,
"chatResUnits": 1000,
"imgModel": "dall-e-3",
"imgNumber": 1
},
"temp": {}
} }

View File

@ -9,7 +9,7 @@ const token = process.env.TOKEN;
const fs = require('fs'); const fs = require('fs');
const commands = []; const commands = [];
const commandFiles = fs.readdirSync('./slash-commands').filter(file => file.endsWith('.js')); const commandFiles = fs.readdirSync('./src/slash-commands').filter(file => file.endsWith('.js'));
for (const file of commandFiles) { for (const file of commandFiles) {
const command = require(`../slash-commands/${file}`); const command = require(`../slash-commands/${file}`);

View File

@ -9,7 +9,11 @@ const https = require('https');
// Discord.js // Discord.js
const Discord = require('discord.js'); const Discord = require('discord.js');
const { EmbedBuilder, ActionRowBuilder, ButtonBuilder, ButtonStyle } = Discord; const { EmbedBuilder } = Discord;
// OpenAI
const OpenAI = require("openai");
const openai = new OpenAI();
// Various imports from other files // Various imports from other files
const config = require('../data/config.json'); const config = require('../data/config.json');
@ -70,9 +74,67 @@ const functions = {
.setDescription(strings.embeds.rules) .setDescription(strings.embeds.rules)
.setFooter({ text: strings.embeds.rulesFooter }); .setFooter({ text: strings.embeds.rulesFooter });
return { embeds: [embed], components: [actionRow] }; return { embeds: [embed], components: [actionRow] };
},
dalle(prompt, imageData) {
const dalleEmbed = new EmbedBuilder()
.setAuthor({ name: "NodBot powered by DALL-E", iconURL: "https://assets.vfsh.dev/openai-logos/PNGs/openai-logomark.png" })
.addFields(
{ name: "Prompt", value: prompt }
)
.setImage(imageData.url)
.setFooter({ text: `Revised Prompt: ${imageData.revPrompt}` })
return { embeds: [dalleEmbed] };
},
gpt(prompt, response, usage) {
const gptEmbed = new EmbedBuilder()
.setAuthor({ name: "NodBot powered by GPT-3.5", iconURL: "https://assets.vfsh.dev/openai-logos/PNGs/openai-logomark.png" })
.setDescription(`**Prompt**\n${prompt}\n\n**Response**\n${response}`)
.setFooter({ text: `This prompt used ${usage.tokens} tokens for a cost of ${usage.usdc}¢. Generated using ${strings.ai.chatModel}` })
return { embeds: [gptEmbed] };
},
generatingResponse() {
const embed = new EmbedBuilder()
.setAuthor({ name: "NodBot powered by OpenAI", iconURL: "https://assets.vfsh.dev/openai-logos/PNGs/openai-logomark.png" })
.setImage("https://media.tenor.com/aHMHzNGCb4kAAAAC/sucks.gif")
.setDescription("Generating a response, please stand by.")
.setFooter({ text: "Ligma balls" });
return { embeds: [embed] };
} }
} }
}, },
openAI: {
chatPrompt(userPrompt) {
return new Promise(async (resolve, reject) => {
const response = await openai.chat.completions.create({
messages: [{
role: 'user',
content: userPrompt
}],
model: strings.ai.chatModel
}).catch(e => {
reject(e);
return null;
});
resolve(response);
});
},
imagePrompt(userPrompt, size, userId) {
return new Promise(async (resolve, reject) => {
try {
const response = await openai.images.generate({
model: strings.ai.imgModel,
prompt: userPrompt,
n: strings.ai.imgNumber,
size: "1024x1024"
});
resolve({url: response.data[0].url, revPrompt: response.data[0].revised_prompt});
} catch (e) {
reject(e);
return;
}
});
}
},
async sendHeartbeat(url) { async sendHeartbeat(url) {
if (isDev) console.log("Heartbeat Sent: " + url); if (isDev) console.log("Heartbeat Sent: " + url);
https.get(url, async (response) => { https.get(url, async (response) => {
@ -85,6 +147,18 @@ const functions = {
if ( !(parsedData.ok) ) console.error("Heartbeat failed"); if ( !(parsedData.ok) ) console.error("Heartbeat failed");
}); });
}).on("error", (error) => console.error(error)); }).on("error", (error) => console.error(error));
},
generateErrorId() {
const digitCount = 10;
const digits = [];
for (let i = 0; i < digitCount; i++) {
const randBase = Math.random();
const randNumRaw = randBase * 10;
const randNumRound = Math.floor(randNumRaw);
digits.push(randNumRound);
}
const errorId = digits.join("");
return errorId;
} }
}; };

View File

@ -13,7 +13,7 @@ module.exports = {
), ),
async execute(interaction) { async execute(interaction) {
await interaction.deferReply(); await interaction.deferReply();
await interaction.editReply(fn.embeds.generatingResponse()); await interaction.editReply(fn.builders.embeds.generatingResponse());
const userPrompt = interaction.options.getString("prompt"); const userPrompt = interaction.options.getString("prompt");
const response = await fn.openAI.chatPrompt(userPrompt).catch(e => console.error(e)); const response = await fn.openAI.chatPrompt(userPrompt).catch(e => console.error(e));
const responseText = response.choices[0].message.content; const responseText = response.choices[0].message.content;
@ -22,8 +22,7 @@ module.exports = {
usdc: (response.usage.prompt_tokens * (strings.ai.chatPromptCentsPer / strings.ai.chatPromptUnits)) + usdc: (response.usage.prompt_tokens * (strings.ai.chatPromptCentsPer / strings.ai.chatPromptUnits)) +
(response.usage.completion_tokens * (strings.ai.chatResCentsPer / strings.ai.chatResUnits)) (response.usage.completion_tokens * (strings.ai.chatResCentsPer / strings.ai.chatResUnits))
}; };
const gptEmbed = fn.embeds.gpt(userPrompt, responseText, usage); const gptEmbed = fn.builders.embeds.gpt(userPrompt, responseText, usage);
await interaction.editReply(gptEmbed); await interaction.editReply(gptEmbed);
fn.upload.openai(interaction.user.id, userPrompt, strings.ai.chatModel, usage.tokens, usage.usdc);
}, },
}; };

View File

@ -23,14 +23,13 @@ module.exports = {
async execute(interaction) { async execute(interaction) {
try { try {
await interaction.deferReply(); await interaction.deferReply();
await interaction.editReply(fn.embeds.generatingResponse()); await interaction.editReply(fn.builders.embeds.generatingResponse());
const userPrompt = interaction.options.getString("prompt"); const userPrompt = interaction.options.getString("prompt");
const size = interaction.options.getString("size") ? interaction.options.getString("size") : "512x512"; const size = interaction.options.getString("size") ? interaction.options.getString("size") : "512x512";
const imageUrl = await fn.openAI.imagePrompt(userPrompt, size); const imageData = await fn.openAI.imagePrompt(userPrompt, size);
const dalleEmbed = fn.embeds.dalle(userPrompt, imageUrl, size); const dalleEmbed = fn.builders.embeds.dalle(userPrompt, imageData);
await interaction.editReply(dalleEmbed); await interaction.editReply(dalleEmbed);
fn.upload.openai(interaction.user.id, userPrompt, "dalle", 0, strings.costs.dalle[size]);
} catch (err) { } catch (err) {
const errorId = fn.generateErrorId(); const errorId = fn.generateErrorId();
console.error(`${errorId}: ${err}`); console.error(`${errorId}: ${err}`);