1import { anthropic } from "npm:@ai-sdk/anthropic";
2import { openai } from "npm:@ai-sdk/openai";
3import { generateText, streamText } from "npm:ai";
4import { getSystemPrompt } from "./prompt.tsx";
34 const maxSteps = 10;
35
36 const model = Deno.env.get("ANTHROPIC_API_KEY") ? anthropic("claude-3-7-sonnet-latest") : openai("gpt-4.1");
37
38 const options = {
1// Telegram Bot that uses OpenAI's DALL-E to generate images
2import { OpenAI } from "https://esm.town/v/std/openai";
3
4// Initialize OpenAI client
5const openai = new OpenAI();
6
7// Telegram Bot API types
91}
92
93// Function to generate an image using OpenAI's DALL-E
94async function generateImage(prompt: string) {
95 try {
96 const response = await openai.images.generate({
97 model: "dall-e-3",
98 prompt: prompt,
123 chatId,
124 "👋 Welcome to the Image Generation Bot!\n\n" +
125 "I can generate images based on your descriptions using OpenAI's DALL-E model.\n\n" +
126 "Simply send me a description of the image you want to create, and I'll generate it for you.\n\n" +
127 "For example: *A serene lake surrounded by mountains at sunset*"
94Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.
95
96### OpenAI
97
98```ts
99import { OpenAI } from "https://esm.town/v/std/openai";
100const openai = new OpenAI();
101const completion = await openai.chat.completions.create({
102 messages: [
103 { role: "user", content: "Say hello in a creative way" },
1// Val Town Narrative Engine with Integrated Test UI
2// =============================================================================
3import { OpenAI } from "https://esm.town/v/std/openai"; // Val Town's OpenAI integration
4// import { Env } from "https://esm.town/v/std/env"; // Not needed if OpenAI() handles API key
5
6// --- Configuration & Constants ---
7const OPENAI_MODEL = "gpt-4o";
8const MAX_TOKENS_RESPONSE = 700;
9
127}
128
129// --- OpenAI System Prompt (same as before) ---
130const SYSTEM_PROMPT = `
131You are a Rick and Morty-styled transdimensional narrative engine, probably cobbled together by Rick in a drunken stupor. Your primary role is to generate hilariously chaotic, compelling, and atmospherically bizarre narrative turns for an epic journey to save the multiverse (or, you know, whatever Rick feels like doing).
549 } = ensureDefaultsAndInferStates(inputContext);
550
551 const contextForOpenAI = {
552 ...processedContext,
553 _inferred_states_for_your_convenience: {
558 };
559 const userMessage = `Input Context JSON (with inferred states for your reference):\n${
560 JSON.stringify(contextForOpenAI, null, 2)
561 }`;
562
563 try {
564 const openai = new OpenAI();
565 const completion = await openai.chat.completions.create({
566 model: OPENAI_MODEL,
567 response_format: { type: "json_object" },
568 messages: [
576 const rawContent = completion.choices[0]?.message?.content;
577 if (!rawContent) {
578 console.error("OpenAI returned an empty response message.");
579 return new Response(
580 JSON.stringify(
581 getFallbackOutput("OpenAI empty response.", processedContext),
582 ),
583 { status: 500, headers: { "Content-Type": "application/json" } },
595 ) {
596 console.error(
597 "OpenAI response missing critical fields or incorrect structure.",
598 JSON.stringify(generatedJson, null, 2),
599 );
602 JSON.stringify(
603 getFallbackOutput(
604 "OpenAI response schema validation failed after generation.",
605 processedContext,
606 ),
618 });
619 } catch (error) {
620 console.error("Error during OpenAI API call or processing:", error);
621 let errorMessage = "Internal server error";
622 if (error.response && error.response.data && error.response.data.error) { // More specific OpenAI error
623 errorMessage = `OpenAI API Error: ${error.response.data.error.message}`;
624 } else if (error.message) {
625 errorMessage = error.message;
1import { fetch } from "https://esm.town/v/std/fetch";
2import { OpenAI } from "https://esm.town/v/std/openai";
3import { z } from "npm:zod";
4
524}
525
526async function callOpenAI(sysP: string, userP: string, mid: string, tid: string, log: LogFn): Promise<string | null> {
527 log("DB", "OpenAI", `Call tid=${tid}`, { sL: sysP.length, uL: userP.length }, mid, tid);
528 try { // @ts-ignore
529 const oai = new OpenAI();
530 const comp = await oai.chat.completions.create({
531 model: "gpt-4o-mini",
537 const usg = comp.usage;
538 if (!resT) {
539 log("WN", "OpenAI", `No text tid=${tid}.`, { usg, fin: comp.choices[0]?.finish_reason }, mid, tid);
540 return null;
541 }
542 log("IN", "OpenAI", `OK tid=${tid}`, { rL: resT.length, usg, fin: comp.choices[0]?.finish_reason }, mid, tid);
543 return resT.trim();
544 } catch (err: any) {
552 st: err.status,
553 };
554 log("ER", "OpenAI", `Fail tid=${tid}:${err.message}`, { e: eD }, mid, tid);
555 throw new Error(
556 `OpenAI Fail: ${err.message}` + (err.code ? `(C:${err.code},S:${err.status})` : `(S:${err.status})`),
557 );
558 }
785 return { mid, cid: tid, p: {} as TOD, e: `${aC.name} fail:PromptGenErr.` };
786 }
787 const rOR = await callOpenAI(sP, uP, mid, tid, l);
788 if (!rOR) {
789 l("WN", aC.name, `OpenAI no content tid=${tid}.`, 0, mid, tid);
790 return { mid, cid: tid, p: {} as TOD, e: `${aC.name} fail:AI no content.` };
791 }
1import { OpenAI } from "https://esm.town/v/std/openai";
2
3// Interface for formatting rules
123export async function extractFlightInfoWithAI(event: any): Promise<string> {
124 try {
125 const openai = new OpenAI();
126
127 const prompt = `
135 `;
136
137 const completion = await openai.chat.completions.create({
138 messages: [
139 { role: "system", content: "You extract airport codes from flight information." },
1246 <a href="?q=function" className="example-link">function</a>
1247 <a href="?q=discord" className="example-link">discord</a>
1248 <a href="?q=openai" className="example-link">openai</a>
1249 <a href="?q=react" className="example-link">react</a>
1250 </div>
1400 <a href="?q=function" className="example-link">function</a>
1401 <a href="?q=discord" className="example-link">discord</a>
1402 <a href="?q=openai" className="example-link">openai</a>
1403 <a href="?q=react" className="example-link">react</a>
1404 </div>
198 },
199 {
200 "title": "An Introduction to OpenAI fine-tuning",
201 "slug": "an-introduction-to-openai-fine-tuning",
202 "link": "/blog/an-introduction-to-openai-fine-tuning",
203 "description": "How to customize OpenAI to your liking",
204 "pubDate": "Fri, 25 Aug 2023 00:00:00 GMT",
205 "author": "Steve Krouse",
417 "slug": "val-town-newsletter-16",
418 "link": "/blog/val-town-newsletter-16",
419 "description": "Our seed round, growing team, Codeium completions, @std/openai, and more",
420 "pubDate": "Mon, 22 Apr 2024 00:00:00 GMT",
421 "author": "Steve Krouse",
29- Maintains context within conversations
30- Generates images based on text descriptions
31- Analyzes uploaded images using OpenAI's vision capabilities
32- Simple rule-based response system
33
47### Backend
48- Built with Hono for routing
49- OpenAI integration for image analysis
50- Val Town image generation service integration
51- Conversation context tracking with support for different message types
57
58### Image Analysis
59- Uses OpenAI's vision capabilities to analyze uploaded images
60- Supports common image formats (JPEG, PNG, etc.)
61- Provides detailed descriptions of image content
4
5// For image analysis
6import { OpenAI } from "https://esm.town/v/std/openai";
7
8const app = new Hono();
9const openai = new OpenAI();
10
11// Unwrap Hono errors to see original error details
172}
173
174// Image analysis function using OpenAI
175async function analyzeImage(imageData: string) {
176 try {
178 const base64Image = imageData.split(',')[1];
179
180 // Call OpenAI API to analyze the image
181 const response = await openai.chat.completions.create({
182 model: "gpt-4o",
183 messages: [
