Val Town Code SearchReturn to Val Town

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" },

11 * and also to upload new resources.
12 * * It utilizes the LLM-Safe Fork of @std/sqlite (adjust import if necessary).
13 * Assumes 'openai' secret is set in Val Town environment variables.
14 * * Last Updated: 2025-05-08 (SQLite refactor, Glassmorphic UI, and Upload Form)
15 */
625export default async function(req: Request) {
626  // --- Dynamic Imports (Inside Handler for Val Town) ---
627  const { OpenAI } = await import("https://esm.town/v/std/openai");
628  const val_fetch = (await import("https://esm.town/v/std/fetch")).fetch;
629  const { PDFExtract } = await import("npm:pdf.js-extract");
653  }
654
655  // --- Helper Function: Call OpenAI API ---
656  async function callOpenAI(
657    openai: OpenAI,
658    systemPrompt: string,
659    userMessage: string,
662  ): Promise<{ role: "assistant" | "system"; content: string | object }> {
663    try {
664      const response = await openai.chat.completions.create({
665        model,
666        messages: [{ role: "system", content: systemPrompt }, { role: "user", content: userMessage }],
680      return { role: "assistant", content };
681    } catch (error) {
682      console.error(`OpenAI call failed (ExpectJSON: ${expectJson}):`, error);
683      let msg = "Error communicating with AI.";
684      if (error.message) msg += ` Details: ${error.message}`;
685      if ((error as any).status === 401) msg = "OpenAI Auth Error. Check your 'openai' secret in Val Town.";
686      if ((error as any).status === 429) msg = "OpenAI Rate Limit Exceeded.";
687      return { role: "system", content: msg };
688    }
694    log: LogEntry[],
695  ): Promise<{ finalLog: LogEntry[]; extractedTagsCount: number; documentIdentifier: string | null }> {
696    const openai = new OpenAI();
697    log.push({ agent: "System", type: "step", message: "Workflow started." });
698
805    log.push({ agent: "System", type: "step", message: "Extracting searchable tags with LLM..." });
806    const tagAgent = "Autism Tag Extraction Agent";
807    const llmResponse = await callOpenAI(openai, autismTagExtractionSystemPrompt, textToAnalyze, "gpt-4o", true);
808
809    let extractedTags: string[] = [];