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import { OpenAI } from "https://esm.town/v/std/openai";
function extractCode(str: string): string {
}
const openai = new OpenAI();
const prompt =
`Generate a TypeScript function named "${functionName}" with the following parameters: ${par
const completion = await openai.chat.completions.create({
messages: [
{
},
{
"title": "An Introduction to OpenAI fine-tuning",
"slug": "an-introduction-to-openai-fine-tuning",
"link": "/blog/an-introduction-to-openai-fine-tuning",
"description": "How to customize OpenAI to your liking",
"pubDate": "Fri, 25 Aug 2023 00:00:00 GMT",
"author": "Steve Krouse",
"link": "/blog/val-town-newsletter-16",
"description":
"Our seed round, growing team, Codeium completions, @std/openai, and more",
"pubDate": "Mon, 22 Apr 2024 00:00:00 GMT",
"author": "Steve Krouse",
Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to cre
### OpenAI
```ts
import { OpenAI } from "https://esm.town/v/std/openai";
const openai = new OpenAI();
const completion = await openai.chat.completions.create({
messages: [
{ role: "user", content: "Say hello in a creative way" },
Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to cre
### OpenAI
```ts
import { OpenAI } from "https://esm.town/v/std/openai";
const openai = new OpenAI();
const completion = await openai.chat.completions.create({
messages: [
{ role: "user", content: "Say hello in a creative way" },
Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to cre
### OpenAI
```ts
import { OpenAI } from "https://esm.town/v/std/openai";
const openai = new OpenAI();
const completion = await openai.chat.completions.create({
messages: [
{ role: "user", content: "Say hello in a creative way" },
import { email } from "https://esm.town/v/std/email";
import { OpenAI } from "https://esm.town/v/std/openai";
import { JSDOM } from "npm:jsdom";
import { NodeHtmlMarkdown, NodeHtmlMarkdownOptions } from "npm:node-html-markdown";
);
const openai = new OpenAI();
console.log(trendingMarkdown);
const completion = await openai.chat.completions.create({
messages: [
{
if (request.method === "POST") {
try {
const { OpenAI } = await import("https://esm.town/v/std/openai");
const openai = new OpenAI();
const formData = await request.formData();
const cvText = new TextDecoder().decode(cvBuffer);
const completion = await openai.chat.completions.create({
messages: [
{
import express from 'express';
import { getMessages, getLinks, getCategories, updateLinkCategory } from './database.js';
import { Configuration, OpenAIApi } from 'openai';
import 'dotenv/config';
app.use(express.json());
// Initialize OpenAI for AI-powered queries
const configuration = new Configuration({
apiKey: process.env.OPENAI_API_KEY,
});
const openai = new OpenAIApi(configuration);
/**
* Function to analyze messages with OpenAI
* @param {Array} messages - Array of message objects
* @param {string} query - User query to analyze messages with
* @returns {Object} - OpenAI response
*/
async function analyzeMessagesWithAI(messages, query) {
try {
// Format messages for OpenAI
const formattedConversation = messages.map(msg => {
const author = msg.author_id === process.env.DISCORD_USER_ID ? 'You' : 'Partner';
`;
// Call OpenAI API
const response = await openai.createCompletion({
model: "gpt-3.5-turbo-instruct",
prompt: prompt,
const links = getLinks(linkFilters);
// If no specific categories, use OpenAI to help filter relevant links
if ((!categories || categories.length === 0) && links.length > 0) {
const relevantLinks = await filterRelevantLinks(links, query);
SPOUSE_USER_ID=spouse_user_id_here
# OpenAI API key (for AI-powered querying)
OPENAI_API_KEY=your_openai_api_key_here
# Val.town settings