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Proking2005/cerebras_coder/generate-code

5 matches

import OpenAI from "openai";
import STARTER_PROMPTS from "../public/starter-prompts.js";
    };
  } else {
    const openai = new OpenAI({
      apiKey: Deno.env.get(
        "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",
      ),
    });
    const completion = await openai.chat.completions.create({
      messages: [
        {
        },
      ].filter(Boolean),
      model: "gpt-4-turbo-preview", // Or another suitable OpenAI model
      max_tokens: 2000, // Adjust as needed
    });
    return {
      code: extractCodeFromFence(completion.choices[0].message.content),
      time: 0, // OpenAI doesn't directly provide completion time
      totalTokens: completion.usage?.total_tokens || 1,
    };

ritam_09/adaptableLimePelican/main.tsx

3 matches

export default async function server(request: Request): Promise<Response> {
  if (request.method === "POST" && new URL(request.url).pathname === "/chat") {
    const { OpenAI } = await import("https://esm.town/v/std/openai");
    const openai = new OpenAI();
    const { messages, rawInput } = await request.json();
    ];
    const stream = await openai.chat.completions.create({
      model: "gpt-4o-mini",
      messages: constrainedMessages,

Ritam/chatGPTClone/main.tsx

6 matches

    setIsLoading(true);
    try {
      const { OpenAI } = await import("https://esm.town/v/std/openai");
      const openai = new OpenAI();
      const analysisPrompt = `Comprehensive Medical Report Analysis:
Respond with a structured, compassionate, and informative analysis that prioritizes patient understanding and next steps.`;
      const analysis = await openai.chat.completions.create({
        model: "gpt-4o-mini",
        messages: [
export default async function server(request: Request): Promise<Response> {
  if (request.method === 'POST' && new URL(request.url).pathname === '/chat') {
    const { OpenAI } = await import("https://esm.town/v/std/openai");
    const openai = new OpenAI();
    const { messages } = await request.json();
    const stream = await openai.chat.completions.create({
      model: "gpt-4o-mini",
      messages: messages,

ajax/traves_compliments/main.tsx

2 matches

import { openai } from "npm:@ai-sdk/openai";
import { generateText } from "npm:ai";
  try {
    const { text: compliments } = await generateText({
      model: openai("gpt-4o-mini"),
      system: "You are a creative compliment generator.",
      prompt: "Generate 5 unique, thoughtful, and specific compliments about a person named Traves.",

ajax/generate_compliment/main.tsx

1 matches

import { openai } from "npm:@ai-sdk/openai";
import { generateText } from "npm:ai";

ajax/say_travis_is_a_fuckhead/main.tsx

2 matches

import { openai } from "npm:@ai-sdk/openai";
import { generateText } from "npm:ai";
    const { text: generatedCompliment } = await generateText({
      model: openai("gpt-4o-mini"),
      system: "You are a creative compliment generator.",
      prompt: `Generate a compliment for: ${compliment}`,

ajax/example_tool/main.tsx

2 matches

import { openai } from "npm:@ai-sdk/openai";
import { generateText } from "npm:ai";
    }
    const { text: processedOutput } = await generateText({
      model: openai("gpt-4o-mini"),
      system: "You are a helpful assistant.",
      prompt: "Process the following input based on the requirements: " + body.input,

api/debatebase/main.tsx

5 matches


export default async function server(request: Request): Promise<Response> {
  const { OpenAI } = await import("https://esm.town/v/std/openai");
  const openai = new OpenAI();
  // Enhanced server-side logging
      `;
      const completion = await openai.chat.completions.create({
        model: "gpt-4o-mini",
        response_format: { type: "json_object" },
      `;
      const completion = await openai.chat.completions.create({
        model: "gpt-4o-mini",
        response_format: { type: "json_object" },
      `;
      const completion = await openai.chat.completions.create({
        model: "gpt-4o-mini",
        messages: [{ role: "user", content: prompt }],

ajax/hello_from_nathan/main.tsx

1 matches

import { openai } from "npm:@ai-sdk/openai";
import { generateText } from "npm:ai";

vawogbemi/browserlessScrapeExample/main.tsx

1 matches

      method: "POST",
      body: JSON.stringify({
        "url": "https://en.wikipedia.org/wiki/OpenAI",
        "elements": [{
          // The second <p> element on the page