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191    && new URL(request.url).pathname === "/generate-blog"
192  ) {
193    const { OpenAI } = await import("https://esm.town/v/std/openai");
194    const openai = new OpenAI();
195
196    try {
199
200      if (topic === "RANDOM") {
201        const randomTopicCompletion = await openai.chat.completions.create({
202          messages: [
203            {
220      }
221
222      const completion = await openai.chat.completions.create({
223        messages: [
224          {

1import { email } from "https://esm.town/v/std/email?v=11";
2import { OpenAI } from "npm:openai";
3
4let location = "Asia, Taipei";
8).then(r => r.json());
9
10const openai = new OpenAI();
11let chatCompletion = await openai.chat.completions.create({
12  messages: [{
13    role: "user",

5export async function getModelBuilder(spec: {
6  type?: "llm" | "chat" | "embedding";
7  provider?: "openai" | "huggingface";
8} = { type: "llm", provider: "openai" }, options?: any) {
9  // 3. 從 lodash-es 中導入函數
10  const { extend, cond, matches, invoke } = await import("npm:lodash-es");
22  // 5. 為每個提供者設置 API 密鑰
23  const args = extend({ callbacks }, options);
24  if (spec?.provider === "openai")
25    args.openAIApiKey = process.env.OPENAI;
26  else if (spec?.provider === "huggingface")
27    args.apiKey = process.env.HUGGINGFACE;
30  const setup = cond([
31    [
32      matches({ type: "llm", provider: "openai" }),
33      async () => {
34        const { OpenAI } = await import("npm:langchain/llms/openai");
35        return new OpenAI(args);
36      },
37    ],
38    [
39      matches({ type: "chat", provider: "openai" }),
40      async () => {
41        const { ChatOpenAI } = await import("npm:langchain/chat_models/openai");
42        return new ChatOpenAI(args);
43      },
44    ],
45    [
46      matches({ type: "embedding", provider: "openai" }),
47      async () => {
48        const { OpenAIEmbeddings } = await import(
49          "npm:langchain/embeddings/openai"
50        );
51        return new OpenAIEmbeddings(args);
52      },
53    ],

287export default async function server(request) {
288  if (request.method === "POST" && new URL(request.url).pathname === "/chat") {
289    const { OpenAI } = await import("https://esm.town/v/std/openai");
290    const openai = new OpenAI();
291
292    try {
339      }
340
341      const completion = await openai.chat.completions.create({
342        messages: messages,
343        model: imageFiles.length > 0 ? "chatgpt-4o-latest" : "gpt-4o",
350      );
351    } catch (error) {
352      console.error("OpenAI API error:", error);
353      return new Response(
354        JSON.stringify({ error: "Failed to get AI response" }),

526 * Server-side logic for generating prompts.
527 * The server expects a POST request to "/generate-prompts" with either text or image form data.
528 * It uses OpenAI API to generate detailed and concise prompts.
529 */
530export default async function server(request: Request): Promise<Response> {
531  if (request.method === "POST" && new URL(request.url).pathname === "/generate-prompts") {
532    try {
533      const { OpenAI } = await import("https://esm.town/v/std/openai");
534      const openai = new OpenAI();
535      const formData = await request.formData();
536      const inputType = formData.get("inputType") as string;
627      }
628
629      console.log("Sending request to OpenAI:", JSON.stringify(analysisMessages, null, 2));
630
631      const completion = await openai.chat.completions.create({
632        model: "chatgpt-4o-latest",
633        messages: analysisMessages,
635      });
636
637      console.log("Received response from OpenAI:", JSON.stringify(completion, null, 2));
638
639      const content = completion.choices[0].message.content || "";
695  if (request.method === "POST" && new URL(request.url).pathname === "/clarify-prompts") {
696    try {
697      const { OpenAI } = await import("https://esm.town/v/std/openai");
698      const openai = new OpenAI();
699      const { inputType, originalInput, clarificationAnswer } = await request.json();
700
749      const analysisMessages = [systemMessage, userMessage];
750
751      console.log("Sending clarification request to OpenAI:", JSON.stringify(analysisMessages, null, 2));
752
753      const completion = await openai.chat.completions.create({
754        model: "chatgpt-4o-latest",
755        messages: analysisMessages,
757      });
758
759      console.log("Received clarification response from OpenAI:", JSON.stringify(completion, null, 2));
760
761      const content = completion.choices[0].message.content || "";

307    const url = new URL(request.url);
308    if (url.pathname === "/generate-prompts") {
309      const { OpenAI } = await import("https://esm.sh/openai@4.11.1");
310      const openai = new OpenAI({
311        apiKey: Deno.env.get("OPENAI_API_KEY"),
312      });
313
316
317      try {
318        const completion = await openai.chat.completions.create({
319          model: "chatgpt-4o-latest", // Changed from "gpt-4o-latest" to "chatgpt-4o-latest"
320          messages: [
364
365        if (!response) {
366          throw new Error("No response from OpenAI");
367        }
368

5  options = {},
6) => {
7  // Initialize OpenAI API stub
8  const { Configuration, OpenAIApi } = await import(
9    "https://esm.sh/openai@3.3.0"
10  );
11  const configuration = new Configuration({
12    apiKey: process.env.OPENAI,
13  });
14  const openai = new OpenAIApi(configuration);
15  // Request chat completion
16  const messages = typeof prompt === "string"
17    ? [{ role: "user", content: prompt }]
18    : prompt;
19  const { data } = await openai.createChatCompletion({
20    model: "gpt-3.5-turbo-0613",
21    messages,

11
12### Toolings
13* Llms can uses [tools](https://platform.openai.com/docs/guides/function-calling), meaning you can make this an agent and a whole lot more useful.
14  
15

1import { zodResponseFormat } from "https://esm.sh/openai/helpers/zod";
2import { z } from "https://esm.sh/zod";
3import { email } from "https://esm.town/v/std/email";
4import { OpenAI } from "https://esm.town/v/std/openai";
5
6export default async function(e: Email) {
7  const client = new OpenAI();
8
9  const Messages = z.object({

1import { OpenAI } from "https://esm.town/v/std/openai?v=5"
2import { sqlite } from "https://esm.town/v/std/sqlite?v=6"
3import { Chess } from "npm:chess.js"
131  return c.html(`<body>
132  <div class='p-4'>
133  <h2 class='font-bold'>OpenAI Chess</h2>
134  <p class='pb-4'>Play chess against ChatGPT-4</p>
135    <div id="myBoard" style="width: 400px"></div>
171    chess.move(san)
172
173    const openai = new OpenAI()
174
175    let messages = []
182        args: [c.req.param().id, `Requesting response to ${san}`],
183      })
184      const completion = await openai.chat.completions.create({
185        messages: [
186          {