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- [ ] Get OpenTownie or Gemini or Claude or OpenAI to synthesize the core of these patterns into a prompt we can use to make more ReactRouter apps, such as...- [ ] Convert this or into the basic react router guest book (and preserve this forum app in another project?)- [ ] To what extent can these patterns be packaged up into a Val Town Router project? Would be neat to get the version pinning thing all centralized, can this as-a-library be that centralized place?Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.### OpenAI```tsimport { 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" }, } const apiKey = __secrets['openai_api_key']; if (!apiKey) { return Response.json({ error: "OpenAI API key not configured" }, { status: 500 }); } // Call OpenAI Vision API with manufacturing-focused prompt const openaiResponse = await fetch("https://api.openai.com/v1/chat/completions", { method: "POST", headers: { }); if (!openaiResponse.ok) { const errorText = await openaiResponse.text(); console.error("OpenAI API error:", errorText); return Response.json({ error: "Failed to generate production specifications", } const data = await openaiResponse.json(); const instructions = data.choices[0].message.content; } const apiKey = __secrets['openai_api_key']; if (!apiKey) { return Response.json({ error: "OpenAI API key not configured" }, { status: 500 }); } console.log(`Generating image ${nextImageNumber} for prompt ${promptId}`); // Prepare OpenAI request let enhancedPrompt = promptData.prompt_text; } const openaiRequestBody: any = { model: "dall-e-3", prompt: enhancedPrompt, console.log(`Using enhanced prompt with style guidance`); // Call OpenAI API const openaiResponse = await fetch("https://api.openai.com/v1/images/generations", { method: "POST", headers: { "Authorization": `Bearer ${apiKey}` }, body: JSON.stringify(openaiRequestBody) }); if (!openaiResponse.ok) { const error = await openaiResponse.text(); console.error("OpenAI API error:", error); return Response.json({ success: false, error: "OpenAI API error", details: error }, { status: 500 }); } const data = await openaiResponse.json(); const imageUrl = data.data[0]?.url; return Response.json({ success: false, error: "No image URL in OpenAI response" }, { status: 500 }); } } const apiKey = __secrets['openai_api_key']; if (!apiKey) { return Response.json({ error: "OpenAI API key not configured" }, { status: 500 }); } const imageContent = await platform.getContentFile(referenceImagePath); // Convert to base64 for OpenAI Vision API const base64Image = btoa(String.fromCharCode(...new Uint8Array(imageContent))); const dataUrl = `data:image/png;base64,${base64Image}`; console.log(`Analyzing reference image: ${referenceImagePath}`); // Use OpenAI Vision API to analyze the image const visionResponse = await fetch("https://api.openai.com/v1/chat/completions", { method: "POST", headers: { if (!visionResponse.ok) { const error = await visionResponse.text(); console.error("OpenAI Vision API error:", error); return Response.json({ success: false, } const apiKey = __secrets['openai_api_key']; if (!apiKey) { return Response.json({ error: "OpenAI API key not configured" }, { status: 500 }); } console.log(`Generating image ${i + 1}/${promptData.image_count} for prompt ${promptId}`); // Call OpenAI API const openaiResponse = await fetch("https://api.openai.com/v1/images/generations", { method: "POST", headers: { }); if (!openaiResponse.ok) { const error = await openaiResponse.text(); console.error("OpenAI API error:", error); continue; } const data = await openaiResponse.json(); const imageUrl = data.data[0]?.url; ) { try { const { OpenAI } = await import("https://esm.town/v/std/openai"); const openai = new OpenAI(); const body = await request.json(); const imageBase64 = body.image.split(",")[1]; } else prompt = "Describe this media content."; const response = await openai.chat.completions.create({ model: "gpt-4o", messages: [Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.### OpenAI```tsimport { 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 create a fresh table.### OpenAI```tsimport { 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" },// @ts-ignoreimport { OpenAI } from "https://esm.town/v/std/openai?v=4";// @ts-ignoreimport { blob } from "https://esm.town/v/std/blob?v=11";const MAX_DEPTH = 4;const CROSS_EXAMINE_DEPTH_INTERVAL = 2;const openai = new OpenAI();const INDEX_KEY = "totem_index"; } const completion = await openai.chat.completions.create({ model: "gpt-4o", messages: [reconsumeralization
import { OpenAI } from "https://esm.town/v/std/openai";
import { sqlite } from "https://esm.town/v/stevekrouse/sqlite";
/**
* Practical Implementation of Collective Content Intelligence
* Bridging advanced AI with collaborative content creation
*/
exp
kwhinnery_openai
lost1991
import { OpenAI } from "https://esm.town/v/std/openai";
export default async function(req: Request): Promise<Response> {
if (req.method === "OPTIONS") {
return new Response(null, {
headers: {
"Access-Control-Allow-Origin": "*",
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