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45} & Partial<Record<Month, Day>>;
46
47export let openAiUsageTypes;

1import { fetch } from "https://esm.town/v/std/fetch?v=4";
2
3const fetchOpenAiUsageData = async (today: string) => {
4  const response = await fetch(
5    `https://api.openai.com/v1/usage?date=${today}`,
6    {
7      method: "GET",
8      headers: {
9        Authorization: `Bearer ${Deno.env.get("OPENAI_API_KEY")}`,
10      },
11    },
13
14  if (!response.ok) {
15    throw new Error("Failed to fetch openAI usage data.");
16  }
17
19};
20
21export { fetchOpenAiUsageData };

2import { getImageTotals } from "./getImageTotals";
3import { getTextTotals } from "./getTextTotals";
4import { DayTotal, UsageDB } from "./openAiUsageTypes";
5
6const createDayTotal = async (data, whisper_api_data, dalle_api_data) => {

10});
11
12interface OpenAiPricing {
13  textPricing: {
14    [key: string]: {
29}
30
31export const openAiPricing: OpenAiPricing = {
32  textPricing: {
33    "gpt-3.5-turbo-16k-0613": createPricing(3000, 4000),

1import { createDayTotal } from "./createDayTotal";
2import { cronEvalLogger as logger } from "https://esm.town/v/nbbaier/cronLogger";
3import { fetchOpenAiUsageData } from "./fetchOpenAiUsageData";
4import { updateBlobUsageDB } from "./updateBlobUsageDB";
5import { blob } from "https://esm.town/v/std/blob?v=11";
7import { DateTime } from "npm:luxon";
8
9const fetchAndStoreOpenAiUsage = async (interval: Interval) => {
10  const timeZone = "America/Chicago";
11  const date = DateTime.now();
15
16  try {
17    const { data, whisper_api_data, dalle_api_data } = await fetchOpenAiUsageData(today);
18
19    const day_total = await createDayTotal(data, whisper_api_data, dalle_api_data);
27};
28
29export default logger(fetchAndStoreOpenAiUsage);

IcarusBot.cursorrules4 matches

@wittiest•Updated 2 weeks ago

100Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.
101
102### OpenAI
103```ts
104import { OpenAI } from "https://esm.town/v/std/openai";
105const openai = new OpenAI();
106const completion = await openai.chat.completions.create({
107  messages: [
108    { role: "user", content: "Say hello in a creative way" },

1import { OpenAI } from "https://esm.town/v/std/openai";
2
3export default async function anthropicCompletion(
4  prompt: string,
5) {
6  const openai = new OpenAI();
7
8  try {
9    const completion = await openai.chat.completions.create({
10      messages: [
11        { role: "user", content: prompt },

3
4import { email } from "https://esm.town/v/std/email";
5import { OpenAI } from "https://esm.town/v/std/OpenAI";
6
7// ------------------------------ Email Address ------------------------------
19  console.log(e);
20
21  // Use OpenAI provided by Val Town to reply to the email
22  const openai = new OpenAI();
23  let chatCompletion = await openai.chat.completions.create({
24    messages: [{
25      role: "user",

5// ---------------- Val Town Standard Library ----------------
6// Val Town provides limited free hosted services, including
7// functions for sending emails and using OpenAI
8import { email } from "https://esm.town/v/std/email";
9import { OpenAI } from "https://esm.town/v/std/OpenAI";
10
11// --------------------- Get weather data --------------------
22
23export default async function() {
24  // Use OpenAI provided by Val Town to get weather reccomendation
25  // Experiment with changing the prompt
26  const openai = new OpenAI();
27  let chatCompletion = await openai.chat.completions.create({
28    messages: [{
29      role: "user",

5 * Allows users to specify hat sequence (e.g., "W,R,B,Y,G,B") or use default.
6 * Simulates workflow visualization via structured text logs.
7 * Uses OpenAI via @std/openai for agent responses.
8 * Based on previous multi-agent simulation structures.
9 *
334// --- Main Request Handler (Server Code for ThinkingFlow MVP) ---
335export default async function(req: Request) {
336  // Dynamic Import of OpenAI Library
337  const { OpenAI } = await import("https://esm.town/v/std/openai");
338
339  // --- OpenAI API Call Helper (Reused) ---
340  async function callOpenAI(
341    systemPrompt: string,
342    userMessage: string, // Can be query or intermediate context
344  ): Promise<{ role: "assistant" | "system"; content: string }> {
345    try {
346      const openai = new OpenAI();
347
348      const response = await openai.chat.completions.create({
349        model: model,
350        messages: [
356
357      if (!response.choices?.[0]?.message?.content) {
358        console.error("OpenAI API returned unexpected structure:", JSON.stringify(response));
359        throw new Error("Received invalid or empty response from AI model.");
360      }
361      return { role: "assistant", content: response.choices[0].message.content };
362    } catch (error) {
363      console.error(`OpenAI API call failed for model ${model}. Error:`, error.message, error.response?.data);
364      let errorMessage = `Error with AI model (${model}).`;
365      let statusCode = error.status || error.response?.status;
366      if (statusCode === 401) errorMessage = "OpenAI Auth Error (401). Check Val Town 'openai' secret.";
367      else if (statusCode === 429) errorMessage = "OpenAI Rate Limit/Quota Error (429). Check OpenAI plan.";
368      else if (statusCode === 400) errorMessage = `OpenAI Bad Request (400). Details: ${error.message}`;
369      else if (statusCode >= 500) errorMessage = `OpenAI Server Error (${statusCode}). Try again later.`;
370      else if (error.code === "ENOTFOUND" || error.code === "ECONNREFUSED")
371        errorMessage = `Network Error (${error.code}). Cannot connect to OpenAI.`;
372      else if (error.message.includes("secret")) errorMessage = error.message;
373      else errorMessage += ` Details: ${error.message}`;
464      currentPrompt = currentPrompt.replace("{{CONTEXT}}", ""); // No inter-hat context for MVP
465
466      const hatResponse = await callOpenAI(currentPrompt, trimmedQuery); // Pass original query as user message
467
468      // Log response or error
495        .replace("{{COLLECTED_OUTPUTS}}", outputsText);
496
497      const summaryResponse = await callOpenAI(finalPrompt, "Synthesize the collected outputs.");
498
499      conversationLog.push({ agent: "Blue Hat", message: summaryResponse.content }); // Log summary or error