Swap to localLLM
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parent
46d86d2650
commit
baeac362de
35
package-lock.json
generated
35
package-lock.json
generated
@ -9,6 +9,7 @@
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"version": "1.0.0",
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"license": "MIT",
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"dependencies": {
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"axios": "^1.7.9",
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"discord.js": "^14.9.0",
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"dotenv": "^16.0.3",
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"openai": "^4.24.1",
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@ -255,6 +256,16 @@
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"url": "https://github.com/sponsors/ljharb"
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}
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},
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"node_modules/axios": {
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"version": "1.7.9",
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"resolved": "https://registry.npmjs.org/axios/-/axios-1.7.9.tgz",
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"integrity": "sha512-LhLcE7Hbiryz8oMDdDptSrWowmB4Bl6RCt6sIJKpRB4XtVf0iEgewX3au/pJqm+Py1kCASkb/FFKjxQaLtxJvw==",
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"dependencies": {
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"follow-redirects": "^1.15.6",
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"form-data": "^4.0.0",
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"proxy-from-env": "^1.1.0"
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}
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},
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"node_modules/base-64": {
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"version": "0.1.0",
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"resolved": "https://registry.npmjs.org/base-64/-/base-64-0.1.0.tgz",
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@ -480,6 +491,25 @@
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"resolved": "https://registry.npmjs.org/fast-deep-equal/-/fast-deep-equal-3.1.3.tgz",
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"integrity": "sha512-f3qQ9oQy9j2AhBe/H9VC91wLmKBCCU/gDOnKNAYG5hswO7BLKj09Hc5HYNz9cGI++xlpDCIgDaitVs03ATR84Q=="
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},
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"node_modules/follow-redirects": {
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"version": "1.15.9",
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"resolved": "https://registry.npmjs.org/follow-redirects/-/follow-redirects-1.15.9.tgz",
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"integrity": "sha512-gew4GsXizNgdoRyqmyfMHyAmXsZDk6mHkSxZFCzW9gwlbtOW44CDtYavM+y+72qD/Vq2l550kMF52DT8fOLJqQ==",
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"funding": [
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{
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"type": "individual",
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"url": "https://github.com/sponsors/RubenVerborgh"
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}
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],
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"engines": {
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"node": ">=4.0"
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},
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"peerDependenciesMeta": {
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"debug": {
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"optional": true
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}
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}
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},
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"node_modules/for-each": {
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"version": "0.3.3",
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"resolved": "https://registry.npmjs.org/for-each/-/for-each-0.3.3.tgz",
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@ -1024,6 +1054,11 @@
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"undici-types": "~5.26.4"
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}
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},
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"node_modules/proxy-from-env": {
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"version": "1.1.0",
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"resolved": "https://registry.npmjs.org/proxy-from-env/-/proxy-from-env-1.1.0.tgz",
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"integrity": "sha512-D+zkORCbA9f1tdWRK0RaCR3GPv50cMxcrz4X8k5LTSUD1Dkw47mKJEZQNunItRTkWwgtaUSo1RVFRIG9ZXiFYg=="
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},
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"node_modules/regexp.prototype.flags": {
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"version": "1.5.1",
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"resolved": "https://registry.npmjs.org/regexp.prototype.flags/-/regexp.prototype.flags-1.5.1.tgz",
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@ -17,9 +17,10 @@
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},
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"homepage": "https://git.vfsh.dev/voidf1sh/nodgpt#readme",
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"dependencies": {
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"axios": "^1.7.9",
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"discord.js": "^14.9.0",
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"dotenv": "^16.0.3",
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"string.prototype.replaceall": "^1.0.7",
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"openai": "^4.24.1"
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"openai": "^4.24.1",
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"string.prototype.replaceall": "^1.0.7"
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}
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}
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@ -36,7 +36,9 @@
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"chatResCentsPer": 0.2,
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"chatResUnits": 1000,
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"imgModel": "dall-e-3",
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"imgNumber": 1
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"imgNumber": 1,
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"sysPrompt": "You are a Discord bot named Nodbot aka NodGPT. You are a shitposting content serving bot in a server full of degenerates. Respond accordingly. Snark and sass is encouraged.",
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"localModel": "llama3.2"
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},
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"temp": {}
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}
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67
src/modules/VoidLLM.js
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67
src/modules/VoidLLM.js
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@ -0,0 +1,67 @@
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const axios = require('axios');
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const strings = require('../data/strings.json');
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const llmHost = "https://llm.vfsh.me";
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const generateEndpoint = "/api/generate";
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const chatEndpoint = "/api/chat";
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module.exports = {
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Generate: class Generate {
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constructor(model) {
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this.model = model;
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this.sysPrompt = strings.ai.sysPrompt;
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}
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send(prompt) {
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return new Promise((resolve, reject) => {
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axios.post(`${llmHost}${generateEndpoint}`, {
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model: this.model,
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system: this.sysPrompt,
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prompt: prompt,
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raw: false,
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stream: false
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}, {
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headers: {
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'Content-Type': 'application/json'
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}
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}).then((res) => {
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resolve(res.data);
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}).catch((err) => {
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reject(err);
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});
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});
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}
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},
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Chat: class Chat {
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constructor(model) {
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this.model = model;
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this.messages = [
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{
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role: "system",
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content: strings.ai.sysPrompt
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}
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];
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}
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send(prompt) {
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return new Promise((resolve, reject) => {
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// Append the message to the messages array
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this.messages.push({
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role: "user",
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content: prompt
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});
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axios.post(`${llmHost}${chatEndpoint}`, {
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model: this.model,
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messages: this.messages,
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stream: false
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}, {
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headers: {
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'Content-Type': 'application/json',
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}
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}).then((res) => {
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this.messages.push(res.data.message);
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resolve(res.data.message);
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}).catch((err) => {
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reject(err);
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});
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});
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}
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}
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}
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@ -15,6 +15,9 @@ const { EmbedBuilder } = Discord;
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const OpenAI = require("openai");
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const openai = new OpenAI();
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// LocalLLM
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const {Chat, Generate} = require("./VoidLLM.js");
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// Various imports from other files
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const config = require('../data/config.json');
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const strings = require('../data/strings.json');
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@ -92,6 +95,13 @@ const functions = {
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.setFooter({ text: `This prompt used ${usage.tokens} tokens for a cost of ${usage.usdc}¢. Generated using ${strings.ai.chatModel}` })
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return { embeds: [gptEmbed] };
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},
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llm(prompt, response) {
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const llmEmbed = new EmbedBuilder()
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.setAuthor({ name: "NodBot powered by voidGPT", iconURL: "https://assets.vfsh.dev/openai-logos/PNGs/openai-logomark.png" })
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.setDescription(`**Prompt**\n${prompt}\n\n**Response**\n${response}`)
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.setFooter({ text: `Generated using ${strings.ai.localModel}` });
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return { embeds: [llmEmbed] };
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},
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generatingResponse() {
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const embed = new EmbedBuilder()
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.setAuthor({ name: "NodBot powered by OpenAI", iconURL: "https://assets.vfsh.dev/openai-logos/PNGs/openai-logomark.png" })
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@ -135,6 +145,18 @@ const functions = {
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});
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}
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},
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localLLM: {
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async chat(prompt) {
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try {
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const chat = new Chat(strings.ai.localModel);
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const response = await chat.send(prompt);
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return response;
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} catch (e) {
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console.error(e);
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return;
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}
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}
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},
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async sendHeartbeat(url) {
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if (isDev) console.log("Heartbeat Sent: " + url);
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https.get(url, async (response) => {
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@ -15,14 +15,17 @@ module.exports = {
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await interaction.deferReply();
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await interaction.editReply(fn.builders.embeds.generatingResponse());
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const userPrompt = interaction.options.getString("prompt");
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const response = await fn.openAI.chatPrompt(userPrompt).catch(e => console.error(e));
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const responseText = response.choices[0].message.content;
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const usage = {
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tokens: response.usage.total_tokens,
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usdc: (response.usage.prompt_tokens * (strings.ai.chatPromptCentsPer / strings.ai.chatPromptUnits)) +
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(response.usage.completion_tokens * (strings.ai.chatResCentsPer / strings.ai.chatResUnits))
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};
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const gptEmbed = fn.builders.embeds.gpt(userPrompt, responseText, usage);
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await interaction.editReply(gptEmbed);
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const response = await fn.localLLM.chat(userPrompt).catch(e => console.error(e));
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const llmEmbed = fn.builders.embeds.llm(userPrompt, response.content);
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await interaction.editReply(llmEmbed);
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// const response = await fn.openAI.chatPrompt(userPrompt).catch(e => console.error(e));
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// const responseText = response.choices[0].message.content;
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// const usage = {
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// tokens: response.usage.total_tokens,
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// usdc: (response.usage.prompt_tokens * (strings.ai.chatPromptCentsPer / strings.ai.chatPromptUnits)) +
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// (response.usage.completion_tokens * (strings.ai.chatResCentsPer / strings.ai.chatResUnits))
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// };
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// const gptEmbed = fn.builders.embeds.gpt(userPrompt, responseText, usage);
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// await interaction.editReply(gptEmbed);
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},
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};
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