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import { openai } from "npm:@ai-sdk/openai";
import ValTown from "npm:@valtown/sdk";
import { generateObject, generateText } from "npm:ai";
    const generateImplStart = Date.now();
    const { text: implementation } = await generateText({
      model: openai("gpt-4o"),
      system: `
# VALTOWN HTTP Cloud Function Generator Prompt
5. **AI API Integration (if applicable)**:  
   - If the toolDescription indicates that creative enrichment or additional processing via AI is needed, integrate an AI API call into the function.  
   - Import { openai } from "npm:@ai-sdk/openai" and { generateText } from "npm:ai".  
   - Use the model "gpt-4o-mini".  
   - Construct a detailed, context-appropriate prompt for the AI call and integrate its response into the function’s output.
---typescript
import { openai } from "npm:@ai-sdk/openai";
import { generateText } from "npm:ai";
    }
    const { text: analysis } = await generateText({
      model: openai("gpt-4o-mini"),
      system: "You are a creative code analyst.",
      prompt: "Analyze the following recent changes in the code: " + body.recent_changes,
    const { object: manifestoConfig } = await generateObject({
      model: openai("gpt-4o"),
      schema: z.object({
        manifestoConfigPureJson: z.string(),
    const { object: updatedManifestoConfigTypescript } = await generateObject({
      model: openai("gpt-4o"),
      system: promptForUpdatedManifest,
      schema: z.object({

import { openai } from "npm:@ai-sdk/openai";
import ValTown from "npm:@valtown/sdk";
import { generateObject, generateText } from "npm:ai";
    const generateImplStart = Date.now();
    const { text: implementation } = await generateText({
      model: openai("gpt-4o"),
      system: `
# VALTOWN HTTP Cloud Function Generator Prompt
5. **AI API Integration (if applicable)**:  
   - If the toolDescription indicates that creative enrichment or additional processing via AI is needed, integrate an AI API call into the function.  
   - Import { openai } from "npm:@ai-sdk/openai" and { generateText } from "npm:ai".  
   - Use the model "gpt-4o-mini".  
   - Construct a detailed, context-appropriate prompt for the AI call and integrate its response into the function’s output.
---typescript
import { openai } from "npm:@ai-sdk/openai";
import { generateText } from "npm:ai";
    }
    const { text: analysis } = await generateText({
      model: openai("gpt-4o-mini"),
      system: "You are a creative code analyst.",
      prompt: "Analyze the following recent changes in the code: " + body.recent_changes,
    const { object: manifestoConfig } = await generateObject({
      model: openai("gpt-4o"),
      schema: z.object({
        manifestoConfigPureJson: z.string(),
    const { object: updatedManifestoConfigTypescript } = await generateObject({
      model: openai("gpt-4o"),
      system: promptForUpdatedManifest,
      schema: z.object({

    "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 fails
function 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 {