Implement logging to db
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@ -391,7 +391,7 @@ const functions = {
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const gptEmbed = new Discord.MessageEmbed()
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.setAuthor({ name: "NodBot powered by GPT-3", iconURL: "https://assets.vfsh.dev/openai-logos/PNGs/openai-logomark.png" })
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.setDescription(`**Prompt**\n${prompt}\n\n**Response**\n${response}`)
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.setFooter({ text: `This prompt used ${usage.tokens} tokens for a cost of ${usage.usd}¢` })
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.setFooter({ text: `This prompt used ${usage.tokens} tokens for a cost of ${usage.usdc}¢` })
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return { embeds: [gptEmbed] };
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}
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},
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@ -488,6 +488,12 @@ const functions = {
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resolve();
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});
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})
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},
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openai(user, prompt, engine, tokens, usdc) {
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const query = `INSERT INTO openai (user, prompt, engine, tokens, usdc) VALUES (${db.escape(user)}, ${db.escape(prompt)}, ${db.escape(engine)}, ${db.escape(tokens)}, ${db.escape(usdc)})`;
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db.query(query, (err) => {
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if (err) throw err;
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});
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}
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},
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download: {
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@ -17,9 +17,10 @@ module.exports = {
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const responseText = response.choices[0].text.slice(2);
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const usage = {
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tokens: response.usage.total_tokens,
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usd: response.usage.total_tokens * ( 0.2 / 1000 ) // 0.2¢ per 1000 tokens or 0.0002¢ per token.
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usdc: response.usage.total_tokens * ( 0.2 / 1000 ) // 0.2¢ per 1000 tokens or 0.0002¢ per token.
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};
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const gptEmbed = fn.embeds.gpt(userPrompt, responseText, usage);
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await interaction.editReply(gptEmbed);
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fn.upload.openai(interaction.user.id, userPrompt, "gpt-3.5-turbo", usage.tokens, usage.usdc);
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},
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};
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@ -1,5 +1,6 @@
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const { SlashCommandBuilder } = require('@discordjs/builders');
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const fn = require('../functions.js');
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const strings = require("../strings.json");
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module.exports = {
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data: new SlashCommandBuilder()
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@ -28,6 +29,7 @@ module.exports = {
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const imageUrl = await fn.openAI.imagePrompt(userPrompt, size);
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const dalleEmbed = fn.embeds.dalle(userPrompt, imageUrl, size);
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await interaction.editReply(dalleEmbed);
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fn.upload.openai(interaction.user.id, userPrompt, "dalle", 0, strings.costs.dalle[size]);
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} catch (err) {
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const errorId = fn.generateErrorId();
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console.error(`${errorId}: ${err}`);
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