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4import { AgentContext, AgentInput, AgentOutput } from "https://esm.town/v/salon/mandate/interfaces.ts";
5import { fetch } from "https://esm.town/v/std/fetch";
6import { OpenAI } from "https://esm.town/v/std/openai";
7// If Deno.env is used, ensure it's for Val Town secrets if possible or clearly noted.
8// For direct Deno.env.get('OPENAI_API_KEY'), it relies on the Val Town environment variable being set.
9// The std/openai library usually handles API key abstraction using user's Val Town secrets.
10
11// Your provided summarizerAgent
27    }
28
29    const openai = new OpenAI(); // Using OpenAI client as per your example
30
31    log("INFO", "SummarizerAgent", "Generating summary with OpenAI...");
32    const completion = await openai.chat.completions.create({
33      model: "gpt-4o-mini", // Explicitly setting a model
34      messages: [
45
46    if (summary === "Could not generate summary.") {
47      log("WARN", "SummarizerAgent", "OpenAI did not return a valid summary content.");
48    }
49
200// Your provided combinerAgent (not directly used in the 12-step orchestrator, but kept for reference)
201export async function combinerAgent(
202  // ... (combinerAgent code as you provided, also updating its OpenAI call) ...
203  input: AgentInput<{
204    summary?: string;
254    }
255
256    const openai = new OpenAI(); // Using OpenAI client as per your example
257    log("INFO", "CombinerAgent", "Combining text with OpenAI...");
258    const completion = await openai.chat.completions.create({
259      model: "gpt-4o-mini", // Explicitly setting a model
260      messages: [
274    const combined = completion.choices[0]?.message?.content?.trim() ?? "Could not combine information.";
275    if (combined === "Could not combine information.")
276      log("WARN", "CombinerAgent", "OpenAI did not return valid combined content.");
277    log("SUCCESS", "CombinerAgent", "Combined successfully");
278    return { mandateId, correlationId: taskId, payload: { combined } };
336  const { userQuery } = input.payload;
337  log("INFO", "ConfigurationAgent", `Processing query: ${userQuery}`);
338  const openai = new OpenAI();
339
340  const systemPrompt =
347
348  try {
349    const completion = await openai.chat.completions.create({
350      model: "gpt-4o-mini",
351      messages: [{ role: "system", content: systemPrompt }, { role: "user", content: userQuery }],
483  const { log } = context;
484  const { articles, topic, keywords } = input.payload;
485  const openai = new OpenAI();
486  let relevantArticles: FetchedArticle[] = [];
487  log("INFO", "RelevanceAssessmentAgent", `Assessing relevance for ${articles.length} articles on topic: ${topic}`);
496    let assessment = { isRelevant: false, rationale: "LLM assessment failed or unclear." };
497    try {
498      const completion = await openai.chat.completions.create({
499        model: "gpt-4o-mini",
500        messages: [{ role: "system", content: "You are a relevance assessor. Output JSON." }, {
559): Promise<AgentOutput<{ articlesWithSentiment: FetchedArticle[] }>> {
560  const { log } = context;
561  const openai = new OpenAI();
562  let articlesWithSentiment: FetchedArticle[] = [];
563  if (!input.payload.articles)
572    let sentimentScore: FetchedArticle["sentimentScore"] = 0.0;
573    try {
574      const completion = await openai.chat.completions.create({
575        model: "gpt-4o-mini",
576        messages: [{ role: "system", content: "You are a sentiment analysis expert. Output JSON." }, {
607): Promise<AgentOutput<{ articlesWithThemes: FetchedArticle[] }>> {
608  const { log } = context;
609  const openai = new OpenAI();
610  let articlesWithThemes: FetchedArticle[] = [];
611  log(
621    let themeResult: { themes: string[]; entities: FetchedArticle["entities"] } = { themes: [], entities: [] };
622    try {
623      const completion = await openai.chat.completions.create({
624        model: "gpt-4o-mini",
625        messages: [{ role: "system", content: "You are a thematic/NER expert. Output JSON." }, {
653  const { log } = context;
654  const { articlesWithThemes, topic, historicalContextSummary } = input.payload;
655  const openai = new OpenAI();
656  log(
657    "INFO",
676  let trendReport: any = { dominantSentiment: "N/A", keyThemes: [], emergingPatterns: "Not analyzed." };
677  try {
678    const completion = await openai.chat.completions.create({
679      model: "gpt-4o-mini",
680      messages: [{ role: "system", content: "Trend analysis expert. Output JSON." }, {
697  let anomalyReport: any = { anomaliesFound: false, anomalyDetails: [] };
698  try {
699    const completion = await openai.chat.completions.create({
700      model: "gpt-4o-mini",
701      messages: [{ role: "system", content: "Anomaly detection expert. Output JSON." }, {
724  const { log } = context;
725  const { trendReport, anomalyReport, config, articlesCount } = input.payload;
726  const openai = new OpenAI();
727  log("INFO", "InsightGenerationAgent", `Generating insights for topic: ${config.topic}`);
728  const contextSummary =
737  let insights: string[] = ["No specific insights generated."];
738  try {
739    const completion = await openai.chat.completions.create({
740      model: "gpt-4o-mini",
741      messages: [{ role: "system", content: "Strategic analyst providing concise insights." }, {
852
853  log("INFO", "ReportCompilationAgent", `Compiling report for topic: ${config.topic}`); // Directly use 'config'
854  const openai = new OpenAI(); // Ensure API key is configured via environment variables or client options
855
856  // The agent code used 'relevantArticles'. If 'articlesWithThemes' is the correct data source
882  let finalReport = "Report generation failed.";
883  try {
884    const completion = await openai.chat.completions.create({
885      model: "gpt-4o-mini",
886      messages: [
912  const { log } = context;
913  const { anomalyReport, insights, config } = input.payload;
914  const openai = new OpenAI();
915  let criticalInfo = "";
916  if (anomalyReport?.anomaliesFound && anomalyReport.anomalyDetails.length > 0) {
932  let alertMessage: string | undefined = undefined;
933  try {
934    const completion = await openai.chat.completions.create({
935      model: "gpt-4o-mini",
936      messages: [{ role: "system", content: "Alert generation specialist." }, { role: "user", content: prompt }],

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" },

3import { validator } from "https://esm.sh/hono@4.3.7/validator";
4// Using @valtown/sqlite
5import { OpenAI } from "https://esm.town/v/std/openai?v=1";
6import { Batch, sqlite, Statement } from "https://esm.town/v/std/sqlite?v=4";
7
190
191async function draftColdEmail(
192  openai: OpenAI,
193  businessName: string | undefined,
194  websiteUrl: string,
241
242  try {
243    const chatCompletion = await openai.chat.completions.create({
244      model: "gpt-3.5-turbo",
245      messages: [{ role: "user", content: prompt }],
250    const responseText = chatCompletion.choices[0]?.message?.content?.trim();
251    if (!responseText) {
252      await updateLeadStatus(leadId, "error_drafting_empty_response", {}, "OpenAI returned empty response");
253      return null;
254    }
279  } catch (error) {
280    console.error(`Error drafting email for ${emailAddress} (lead ${leadId}):`, error);
281    await updateLeadStatus(leadId, "error_drafting", {}, `OpenAI API error: ${error.message}`);
282    return null;
283  }
286async function processJob(jobId: string, searchQuery: string) {
287  await updateJobStatus(jobId, "processing_search");
288  const openaiApiKey = Deno.env.get("openai");
289  if (!openaiApiKey) {
290    console.error("OpenAI API key secret 'openai' is not set.");
291    await updateJobStatus(jobId, "failed_config", "OpenAI API key not configured.");
292    return;
293  }
294  const openai = new OpenAI({ apiKey: openaiApiKey });
295
296  const websites = await searchWebsites(searchQuery, jobId);
327    const emailAddress = await extractEmailsFromWebsite(site.url, leadId);
328    if (emailAddress) {
329      await draftColdEmail(openai, truncatedBusinessName, site.url, emailAddress, searchQuery, leadId);
330    }
331  }

94Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.
95
96### OpenAI
97
98```ts
99import { OpenAI } from "https://esm.town/v/std/openai";
100const openai = new OpenAI();
101const completion = await openai.chat.completions.create({
102  messages: [
103    { role: "user", content: "Say hello in a creative way" },

198  },
199  {
200    "title": "An Introduction to OpenAI fine-tuning",
201    "slug": "an-introduction-to-openai-fine-tuning",
202    "link": "/blog/an-introduction-to-openai-fine-tuning",
203    "description": "How to customize OpenAI to your liking",
204    "pubDate": "Fri, 25 Aug 2023 00:00:00 GMT",
205    "author": "Steve Krouse",
417    "slug": "val-town-newsletter-16",
418    "link": "/blog/val-town-newsletter-16",
419    "description": "Our seed round, growing team, Codeium completions, @std/openai, and more",
420    "pubDate": "Mon, 22 Apr 2024 00:00:00 GMT",
421    "author": "Steve Krouse",

198  },
199  {
200    "title": "An Introduction to OpenAI fine-tuning",
201    "slug": "an-introduction-to-openai-fine-tuning",
202    "link": "/blog/an-introduction-to-openai-fine-tuning",
203    "description": "How to customize OpenAI to your liking",
204    "pubDate": "Fri, 25 Aug 2023 00:00:00 GMT",
205    "author": "Steve Krouse",
417    "slug": "val-town-newsletter-16",
418    "link": "/blog/val-town-newsletter-16",
419    "description": "Our seed round, growing team, Codeium completions, @std/openai, and more",
420    "pubDate": "Mon, 22 Apr 2024 00:00:00 GMT",
421    "author": "Steve Krouse",

1import { OpenAI } from "https://esm.town/v/std/openai";
2import { telegramSendMessage } from "https://esm.town/v/vtdocs/telegramSendMessage?v=5";
3import {
15  console.log(`received: ${text}`)
16  if (text) {
17    const response = await translateWithOpenAI(text);
18    console.log(`translated to: ${response}`);
19    ctx.reply(response);
33
34
35async function translateWithOpenAI(text: string) {
36   const openai = new OpenAI();
37  const completion = await openai.chat.completions.create({
38    messages: [
39      {

1import { OpenAI } from "https://esm.town/v/std/openai";
2import { telegramSendMessage } from "https://esm.town/v/vtdocs/telegramSendMessage?v=5";
3import {
15  console.log(`received: ${text}`)
16  if (text) {
17    const response = await translateWithOpenAI(text);
18    console.log(`translated to: ${response}`);
19    ctx.reply(response);
33
34
35async function translateWithOpenAI(text: string) {
36   const openai = new OpenAI();
37  const completion = await openai.chat.completions.create({
38    messages: [
39      {

4// SERVER-SIDE LOGIC (TypeScript)
5// =============================================================================
6import { OpenAI } from "https://esm.town/v/std/openai";
7
8// --- Configuration ---
23  maskSrc?: string;
24}
25interface OpenAIResponse {
26  races: RaceInfo[];
27}
105];
106
107// --- OpenAI Generation Function ---
108async function generateRaceDataWithOpenAI(): Promise<RaceInfo[]> {
109  const openai = new OpenAI();
110  const numToRequest = Math.max(1, NUM_CARDS_TO_GENERATE);
111  const prompt =
126Return STRICTLY as a single JSON object: { "races": [ { race1 }, { race2 }, ... ] }. No introductory text or explanations outside the JSON structure.`;
127  try {
128    console.info(`Requesting ${numToRequest} race data generation from OpenAI...`);
129    const completion = await openai.chat.completions.create({
130      model: "gpt-4o",
131      messages: [{ role: "user", content: prompt }],
134    });
135    const rawContent = completion.choices[0]?.message?.content;
136    if (!rawContent) throw new Error("OpenAI returned an empty response message.");
137
138    let parsedJson;
140      parsedJson = JSON.parse(rawContent);
141    } catch (parseError) {
142      console.error("Failed to parse OpenAI JSON response:", parseError);
143      console.error("Raw OpenAI response:", rawContent);
144      throw new Error(`JSON Parsing Error: ${parseError.message}`);
145    }
160    ) {
161      console.warn(
162        `OpenAI response JSON failed validation for ${numToRequest} races:`,
163        JSON.stringify(parsedJson, null, 2),
164      );
165      throw new Error(
166        "OpenAI response JSON structure, count, data types, color format, hint value, or mask URL invalid.",
167      );
168    }
169
170    const generatedData = (parsedJson as OpenAIResponse).races.map(race => ({
171      ...race,
172      borderAnimationHint: race.borderAnimationHint || "none",
173    }));
174    console.info(`Successfully generated and validated ${generatedData.length} races from OpenAI.`);
175    return generatedData;
176  } catch (error) {
177    console.error("Error fetching or processing data from OpenAI:", error);
178    console.warn("Using fallback race data due to the error.");
179    return fallbackRaceData.slice(0, numToRequest).map(race => ({
186// --- Main HTTP Handler (Val Town Entry Point) ---
187export default async function server(request: Request): Promise<Response> {
188  const activeRaceData = await generateRaceDataWithOpenAI();
189
190  const css = `

1import { OpenAI } from "https://esm.town/v/std/openai";
2import { telegramSendMessage } from "https://esm.town/v/vtdocs/telegramSendMessage?v=5";
3import {
15  console.log(`received: ${text}`)
16  if (text) {
17    const response = await translateWithOpenAI(text);
18    console.log(`translated to: ${response}`);
19    ctx.reply(response);
33
34
35async function translateWithOpenAI(text: string) {
36   const openai = new OpenAI();
37  const completion = await openai.chat.completions.create({
38    messages: [
39      {