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"description": "A sample blah manifest demonstrating various tool types and configurations.", "env": { "OPENAI_API_KEY": "your-openai-api-key-here", }, "tools": [
import { openai } from "npm:@ai-sdk/openai";import { generateText } from "npm:ai"; } const { text: fact } = await generateText({ model: openai("gpt-4o-mini"), system: "You are an expert in world trivia.", prompt: `Provide an interesting and fun fact about the country: ${body.country}.`,
import { openai } from "npm:@ai-sdk/openai";import { generateText } from "npm:ai"; const countriesList = body.countries.join(", "); const { text: recipes } = await generateText({ model: openai("gpt-4o-mini"), system: "You are a culinary expert.", prompt: `Provide a list of popular recipes from the following countries: ${countriesList}.`,
];// Mock fallacy detection for when OpenAI failsfunction mockFallacyDetection(text) { const lowercaseText = text.toLowerCase(); try { // Dynamically import OpenAI with error handling const openAIModule = await import("https://esm.town/v/std/openai").catch(err => { console.error("Failed to import OpenAI module:", err); throw new Error("Could not load AI analysis module"); }); const OpenAI = openAIModule.OpenAI; const openai = new OpenAI(); const response = await openai.chat.completions.create({ model: "gpt-4o-mini", messages: [
export default async function server(request: Request): Promise<Response> { if (request.method === 'POST') { const { OpenAI } = await import("https://esm.town/v/std/openai"); const openai = new OpenAI(); // Parse multipart form data // Transcribe audio const transcriptionResponse = await openai.audio.transcriptions.create({ file: base64Audio, model: "whisper-1", // Generate AI response const chatCompletion = await openai.chat.completions.create({ messages: [ { // Generate audio response const speechResponse = await openai.audio.speech.create({ model: "tts-1", voice: "nova",
export default async function server(request: Request): Promise<Response> { if (request.method === 'POST') { const { OpenAI } = await import("https://esm.town/v/std/openai"); const openai = new OpenAI(); const { theme } = await request.json(); const completion = await openai.chat.completions.create({ messages: [ {
export default async function server(request: Request): Promise<Response> { if (request.method === 'POST') { const { OpenAI } = await import("https://esm.town/v/std/openai"); const openai = new OpenAI(); const { theme } = await request.json(); const completion = await openai.chat.completions.create({ messages: [ {
export default async function server(request: Request): Promise<Response> { if (request.method === 'POST' && new URL(request.url).pathname === '/analyze') { const { OpenAI } = await import("https://esm.town/v/std/openai"); const openai = new OpenAI(); const body = await request.json(); try { const completion = await openai.chat.completions.create({ messages: [ { }); } catch (error) { console.error('OpenAI Analysis Error:', error); return new Response(JSON.stringify({ diagnosis: 'Unable to generate analysis',function parseAnalysis(analysis: string) { // Basic parsing of OpenAI response const sections = analysis.split('\n\n'); return {
} // Dynamically import OpenAI with error handling let OpenAI; try { const module = await import("https://esm.town/v/std/openai"); OpenAI = module.OpenAI; } catch (importError) { console.error("OpenAI Import Error:", importError); return new Response( JSON.stringify({ error: "Failed to import OpenAI module", details: String(importError), }), } // Ensure OpenAI is available if (!OpenAI) { return new Response( JSON.stringify({ error: "OpenAI module not found", }), { } // Create OpenAI instance const openai = new OpenAI(); // Create OpenAI completion with comprehensive error handling let completion; try { completion = await openai.chat.completions.create({ messages: body.messages, model: "gpt-4o-mini", }); } catch (completionError) { console.error("OpenAI Completion Error:", completionError); return new Response( JSON.stringify({
export default async function server(request: Request): Promise<Response> { const { OpenAI } = await import("https://esm.town/v/std/openai"); const { sqlite } = await import("https://esm.town/v/stevekrouse/sqlite"); }; const openai = new OpenAI(); const KEY = extractKey(new URL(import.meta.url)); const SCHEMA_VERSION = 3; // Increment schema version for tool support // Call Maverick to create the tool definition const maverickCompletion = await openai.chat.completions.create({ model: "gpt-4o-mini", response_format: { type: "json_object" }, `; const oracleCompletion = await openai.chat.completions.create({ model: "gpt-4o-mini", response_format: { type: "json_object" }, `; const agentBCompletion = await openai.chat.completions.create({ model: "gpt-4o-mini", response_format: { type: "json_object" }, `; const agentBCompletion = await openai.chat.completions.create({ model: "gpt-4o-mini", response_format: { type: "json_object" }, // Make completion call with the appropriate agent prompt const analysisCompletion = await openai.chat.completions.create({ model: "gpt-4o-mini", response_format: { type: "json_object" }, // Make completion call with the appropriate agent prompt const agentCompletion = await openai.chat.completions.create({ model: "gpt-4o-mini", response_format: { type: "json_object" },
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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