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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" },

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" },

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" },

// === Replace these with your real keys/numbers ===
const openai = new OpenAI({ apiKey: "sk-..." });
const clinicianPhone = "+1YOURCELLPHONE";
const twilioNumber = "+1YOURTWILIONUMBER";
    `A dental patient asked: "${question}". Write 3 short, professional draft responses a dentist could choose from. Keep each under 30 words.`;
  const result = await openai.chat.completions.create({
    model: "gpt-4",
    messages: [{ role: "user", content: prompt }],

// === Replace these with your real keys/numbers ===
const openai = new OpenAI({ apiKey: "sk-..." });
const clinicianPhone = "+1YOURCELLPHONE";
const twilioNumber = "+1YOURTWILIONUMBER";
const prompt = `A dental patient asked: "${question}". Write 3 short, professional draft responses a dentist could choose from. Keep each under 30 words.`;
const result = await openai.chat.completions.create({
model: "gpt-4",
messages: [{ role: "user", content: prompt }],

// src/openai_service.ts
import { LogFunction } from "https://esm.town/v/join/crit/types";
import { OpenAI } from "https://esm.town/v/std/openai"; // Val Town specific import
/**
 * Invokes the OpenAI Chat Completion API with specified prompts and parameters.
 * @param systemPrompt The system message to guide the AI's behavior.
 * @param userPrompt The user's message or query.
 * @throws Error if the API call fails critically.
 */
export async function invokeOpenAIChatCompletion(
  systemPrompt: string,
  userPrompt: string,
  logger(
    "AUDIT",
    "OpenAIService",
    `Initiating LLM call for task ${taskId}`,
    { systemPromptLength: systemPrompt.length, userPromptLength: userPrompt.length },
  try {
    const openAIClient = new OpenAI(); // API key should be configured via environment variables
    const completion = await openAIClient.chat.completions.create({
      model: "gpt-4o-mini", // Consider making this configurable
      messages: [
      logger(
        "WARN",
        "OpenAIService",
        `LLM call for task ${taskId} yielded no content.`,
        { usageData, finishReason },
    logger(
      "INFO",
      "OpenAIService",
      `LLM call for task ${taskId} successful.`,
      { responseLength: responseText.length, usageData, finishReason },
    logger(
      "CRITICAL",
      "OpenAIService",
      `LLM call for task ${taskId} failed: ${error.message}`,
      { error: errorDetails },
    );
    throw new Error(
      `OpenAI Service Failure: ${error.message}`
        + (error.code ? ` (Code: ${error.code}, Status: ${error.status})` : ` (Status: ${error.status})`),
    );

// src/ai_agent_runner.ts
import { invokeOpenAIChatCompletion } from "https://esm.town/v/join/crit/openai_service";
import {
  BaseIncidentContext,
    }
    const rawOpenAIResult = await invokeOpenAIChatCompletion(
      systemPrompt,
      userPrompt,
      logger,
    );
    if (!rawOpenAIResult) {
      const msg = `LLM returned no content for task ${taskId}.`;
      logger("WARN", agentName, msg, {}, masterIncidentId, taskId);
    let parsedOutput: T_Output;
    try {
      parsedOutput = outputSchemaParser(rawOpenAIResult);
    } catch (parseError: any) {
      const msg = `Failed to parse LLM output for task ${taskId}. Error: ${parseError.message}`;
        agentName,
        msg,
        { rawResponsePreview: rawOpenAIResult.substring(0, 500) },
        masterIncidentId,
        taskId,