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// @ts-ignore
import { OpenAI } from "https://esm.town/v/std/openai?v=4";
import { Hono } from "npm:hono@4.4.12";
const app = new Hono();
// Endpoint to generate a new world using OpenAI
app.post("/build-world", async (c) => {
  try {
    }
    const openai = new OpenAI();
    const completion = await openai.chat.completions.create({
      model: "gpt-4o",
      messages: [

Configure the following variables in your environment: 
- `AGENT_API_KEY` (This is a secure token that you choose to secure the agent.tsx POST endpoint)
- `OPENAI_API_KEY` (An OpenAI API Key)
- `EXA_API_KEY` (Optional, though needed if you use the web search tool)

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import { z } from "npm:zod@4.0.5";
import { generateText, stepCountIs, tool } from "npm:ai@5.0.15";
import { openai } from "npm:@ai-sdk/openai@2.0.15";
import { Sandbox } from "npm:@e2b/code-interpreter";
const result = await generateText({
  model: openai("gpt-4o"),
  stopWhen: stepCountIs(5),
  tools: {

// @ts-ignore
import { OpenAI } from "https://esm.town/v/std/openai?v=4";
// --- AI BEHAVIORAL GUIDELINES ---
  if (req.method === "POST") {
    try {
      const openai = new OpenAI();
      const body = await req.json();
      ];
      const completion = await openai.chat.completions.create({
        model: "gpt-4o",
        messages: 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
```ts
import { 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
```ts
import { 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-nocheck
import { OpenAI } from "https://esm.town/v/std/openai?v=4";
// --- AI BEHAVIORAL GUIDELINES ---
  if (url.pathname === "/generatePrompts" && req.method === "POST") {
    try {
      const openai = new OpenAI();
      const { subject } = await req.json();
      }
      const completion = await openai.chat.completions.create({
        model: "gpt-4o",
        messages: [

import { streamText } from "npm:hono@4.4.12/streaming";
// @ts-ignore
import { OpenAI } from "https://esm.town/v/std/openai?v=4";
// --- TYPE DEFINITIONS ---
// --- API HELPER ---
async function callOpenAI(
  systemPrompt: string,
  userContent: string | object,
  isJson = true,
) {
  const openai = new OpenAI();
  const content = typeof userContent === "string"
    ? userContent
    : JSON.stringify(userContent);
  const completion = await openai.chat.completions.create({
    model: "gpt-4o",
    messages: [
  }
  const { context } = await c.req.json();
  const result = await callOpenAI(LIST_GENERATOR_PROMPT(type, context), "");
  return c.json(result);
});
app.post("/api/prompt/dynamic", async (c) => {
  const body = await c.req.json();
  const result = await callOpenAI(PROMPT_REFINER_PROMPT, body);
  return c.json(result);
});
app.post("/api/inputs", async (c) => {
  const { refined_prompt } = await c.req.json();
  const result = await callOpenAI(FORM_GENERATOR_PROMPT, { refined_prompt });
  return c.json(result);
});
app.post("/api/clarify", async (c) => {
  const { refined_prompt } = await c.req.json();
  const result = await callOpenAI(CLARIFICATION_PROMPT, { refined_prompt });
  return c.json(result);
});
    inputs: { ...user_inputs, ...clarifications },
  };
  const raw_output_v1 = await callOpenAI(
    "Execute the provided prompt template using the given inputs. Produce only the raw output.",
    v1UserContent,
    output: raw_output_v1,
  };
  const { criteria } = await callOpenAI(
    CRITERIA_GENERATOR_PROMPT,
    criteriaContext,
    criteria: criteria,
  };
  const evaluation_v1: Evaluation = await callOpenAI(
    EVALUATOR_PROMPT,
    v1EvalContext,
    evaluation: evaluation_v1,
  };
  const raw_output_v2 = await callOpenAI(
    REFINER_PROMPT,
    v2RefineContext,
    criteria: criteria,
  };
  const evaluation_v2: Evaluation = await callOpenAI(
    EVALUATOR_PROMPT,
    v2EvalContext,

import { Hono } from "npm:hono@4.4.12";
// @ts-ignore
import { OpenAI } from "https://esm.town/v/std/openai";
import type { Context } from "npm:hono@4.4.12";
import { streamText } from "npm:hono/streaming";
const services = {
  /**
   * A centralized function for making calls to the OpenAI API.
   * @param systemPrompt - The system prompt to guide the AI.
   * @param userContent - The user's input.
   * @param options - Additional options like model, streaming, and response format.
   * @returns A promise that resolves to the parsed JSON response or an OpenAI stream.
   */
  async callOpenAI(
    systemPrompt: string,
    userContent: string | object,
    } = options;
    const openai = new OpenAI();
    const messages: any[] = [
      { role: "system", content: systemPrompt },
    try {
      const completion = await openai.chat.completions.create(requestPayload);
      if (stream && c) {
      return completion;
    } catch (e) {
      console.error(`Error calling OpenAI: ${e.message}`);
      throw new Error("AI service failed.");
    }
    ...body,
  };
  return services.callOpenAI(
    config.prompts.DYNAMIC_LIST_GENERATOR,
    userContent,
    JSON.stringify(company_context)
  }\n\nOccupation: ${occupation_title}\n\nTask: ${task}`;
  return services.callOpenAI(config.prompts.PROMPT_REFINER, userContent, {
    c,
    isJson: true,
app.post("/api/inputs", async (c: Context) => {
  const { refined_prompt } = await c.req.json<InputsBody>();
  return services.callOpenAI(config.prompts.INPUT_EXTRACTOR, refined_prompt, {
    c,
    isJson: true,
app.post("/api/clarify", async (c: Context) => {
  const { refined_prompt } = await c.req.json<ClarifyBody>();
  return services.callOpenAI(
    config.prompts.CLARIFICATION_AGENT,
    refined_prompt,
  return streamText(c, async (stream) => {
    try {
      const openai = new OpenAI();
      // 2. First call to the AI to see if it wants to use a tool
      const initialResponse = await openai.chat.completions.create({
        model: config.models.major,
        messages,
        // 5. Make the final call with tool results included, and stream the response
        const finalStream = await openai.chat.completions.create({
          model: config.models.major,
          messages,
    JSON.stringify(company_context)
  }\n\nTask Briefing:\n${refined_prompt}`;
  return services.callOpenAI(
    config.prompts.EVALUATION_CRITERIA_GENERATOR,
    userContent,
  const systemPrompt =
    `${config.prompts.EVALUATOR_AGENT}\n\nOutput Language: ${language}`;
  return services.callOpenAI(systemPrompt, userContent, { c, stream: true });
});
  const systemPrompt =
    `${config.prompts.EVALUATOR_AGENT}\n\nOutput Language: ${language}`;
  return services.callOpenAI(systemPrompt, userContent, { c, stream: true });
});
  const systemPrompt =
    `${config.prompts.REFINER_AGENT}\n\nOutput Language: ${language}`;
  return services.callOpenAI(systemPrompt, userContent, { c, stream: true });
});