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//контекст: она работает доулой и переводчиком русско-испаноскго всего пару месяцев и хочеть стать высококвалифицированным медицинским переводчиком;\
const data = {
  "model": "openai/gpt-4o",
  "messages": [
    {

const data = {
  "model": "openai/gpt-4o",
  "messages": [
    {

  if (url.searchParams.has("nextMessage")) {
    const { OpenAI } = await import("https://esm.town/v/std/openai");
    const openai = new OpenAI();
    const { personality1, personality2, topic, conversation, currentSpeaker } = await req.json();
    const currentPersonality = currentSpeaker === 1 ? personality1 : personality2;
    const response = await openai.chat.completions.create({
      messages: [
        {

// Your JSON data
const data = {
  "model": "openai/gpt-4o",
  "messages": [
    {

// Your JSON data
const data = {
  "model": "openai/gpt-4o",
  "messages": [
    {

// @ts-ignore
import { OpenAI } from "https://esm.town/v/std/openai?v=4";
import { blob } from "https://esm.town/v/std/blob?v=11";
import { Hono } from "npm:hono@4.4.12";
  try {
    const openai = new OpenAI();
    const response = await openai.chat.completions.create({
      model: "gpt-4o",
      response_format: { type: "json_object" },

_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-ignore
import { OpenAI } from "https://esm.town/v/std/openai?v=4";
// @ts-ignore
import { Hono } from "npm:hono@4.4.12";
  wizardState.rawRequirements = rawRequirements;
  const openai = new OpenAI();
  const completion = await openai.chat.completions.create({
    model: "gpt-4o",
    messages: [

// @ts-ignore
import { OpenAI } from "https://esm.town/v/std/openai?v=4";
// --- TYPE DEFINITIONS ---
  const action = url.searchParams.get("action");
  const openai = new OpenAI();
  if (req.method === "POST") {
            throw new Error("Invalid 'goal' provided.");
          }
          const completion = await openai.chat.completions.create({
            model: "gpt-4o",
            messages: [
            throw new Error("Invalid 'tasks' array provided.");
          }
          const completion = await openai.chat.completions.create({
            model: "gpt-4o",
            messages: [

```
### OpenAI
Do not use val.town std library, import from https://esm.town/v/cricks_unmixed4u/openai-client/main.tsx
TypeScript interface for interacting with OpenAI's chat models, with optional global rate limiting, and uses Val Town's SQLite for persistent rate limit tracking.
Key Components
Message Type: Defines the structure for chat messages (role and content).
ChatOpenAI(model: string): Factory function returning an object with an invoke(messages) method. This method sends an array of messages to the specified OpenAI chat model and returns the assistant's response.
GlobalRateLimitedChatOpenAI(model: string, requestsPerSecond: number): Decorator for ChatOpenAI that enforces a global rate limit (requests per second) using a persistent SQLite table.
GlobalRateLimiter: Class that implements the rate limiting logic. It checks the number of requests in the current time window and throws an error if the limit is exceeded. It uses a table (global_rate_limit_1) in Val Town's SQLite.
ensureGlobalRateLimitTableExists: Ensures the rate limit tracking table exists in the database at startup.
Usage
Use ChatOpenAI(model) for direct, unlimited access to OpenAI chat completions.
Use GlobalRateLimitedChatOpenAI(model, requestsPerSecond) to enforce a global rate limit on chat completions, suitable for shared or public-facing endpoints.
Val Town/Platform Notes
Uses Val Town’s standard SQLite API for persistent storage.
Designed for server-side use (no browser-specific code).
No secrets are hardcoded; OpenAI API keys are managed by the OpenAI SDK/environment.
### Email