Search

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" },

function widgetMeta(invoking?: string, invoked?: string) {
  return {
    "openai/outputTemplate": WIDGET_URI,
    "openai/toolInvocation/invoking": invoking,
    "openai/toolInvocation/invoked": invoked,
    "openai/widgetAccessible": true,
    "openai/resultCanProduceWidget": true,
  } as const;
}
          _meta: {
            ...widgetMeta(),
            "openai/widgetCSP": {
              connect_domains: [baseUrl, "https://esm.sh", "https://cdn.jsdelivr.net"],
              resource_domains: [baseUrl, "https://esm.sh", "https://cdn.jsdelivr.net"],
  _meta: widgetMeta("Loading messages...", "Messages loaded"),
  handler: async (args, ctx) => {
    const subject = ctx.request.params._meta?.["openai/subject"];
    if (!subject) {
      throw new Error("Missing openai/subject in request metadata");
    }
  _meta: widgetMeta("Loading message...", "Message loaded"),
  handler: async ({ id }, ctx) => {
    const subject = ctx.request.params._meta?.["openai/subject"];
    if (!subject) {
      throw new Error("Missing openai/subject in request metadata");
    }
    }
    const subject = ctx.request.params._meta?.["openai/subject"];
    if (!subject) {
      throw new Error("Missing openai/subject in request metadata");
    }

type UnknownObject = Record<string, unknown>;
export interface OpenAiGlobals<
  ToolInput extends UnknownObject = UnknownObject,
  ToolOutput extends UnknownObject = UnknownObject,
}
export interface OpenAIWidgetAPI<
  ToolInput extends UnknownObject = UnknownObject,
  ToolOutput extends UnknownObject = UnknownObject,
  ToolResponseMetadata extends UnknownObject = UnknownObject,
  WidgetState extends UnknownObject = UnknownObject,
> extends OpenAiGlobals<
    ToolInput,
    ToolOutput,
}
export const SET_GLOBALS_EVENT_TYPE = "openai:set_globals";
export interface SetGlobalsEvent
  extends CustomEvent<{ globals: Partial<OpenAiGlobals> }> {
  type: typeof SET_GLOBALS_EVENT_TYPE;
}
declare global {
  interface Window {
    openai: OpenAIWidgetAPI;
  }
}
export function getOpenAI(): OpenAIWidgetAPI | undefined {
  return window.openai;
}

import type { MessageListOutput } from "../../../shared/types.ts";
import { useTheme, useToolOutput } from "../hooks.ts";
import { getOpenAI } from "../openai-types.ts";
export function MessageListWidget() {
  async function handleAddMessage() {
    await getOpenAI()?.sendFollowUpMessage({
      prompt: "Add a new message",
    });

import type { MessageDetailOutput } from "../../../shared/types.ts";
import { useTheme, useToolOutput } from "../hooks.ts";
import { getOpenAI } from "../openai-types.ts";
export function MessageDetailWidget() {
  async function handleBackToList() {
    await getOpenAI()?.sendFollowUpMessage({
      prompt: "Show me all messages",
    });

/** @jsxImportSource https://esm.sh/react@19 */
import { useCallback, useEffect, useState, useSyncExternalStore } from "https://esm.sh/react@19";
import type { OpenAiGlobals, SetGlobalsEvent } from "./openai-types.ts";
import { getOpenAI, SET_GLOBALS_EVENT_TYPE } from "./openai-types.ts";
type UnknownObject = Record<string, unknown>;
export function useOpenAiGlobal<K extends keyof OpenAiGlobals>(
  key: K,
): OpenAiGlobals[K] {
  return useSyncExternalStore(
    (onChange) => {
      };
    },
    () => window.openai[key],
  );
}
export function useToolOutput<T = UnknownObject>(): T | null {
  return useOpenAiGlobal("toolOutput") as T | null;
}
export function useTheme(): "light" | "dark" {
  return useOpenAiGlobal("theme");
}
  defaultState: T | (() => T),
): readonly [T, (state: React.SetStateAction<T>) => void] {
  const widgetStateFromWindow = useOpenAiGlobal("widgetState") as T | null;
  const [widgetState, _setWidgetState] = useState<T>(() => {
            : stateOrUpdater;
        getOpenAI()?.setWidgetState(newState);
        return newState;
      });

// BACKEND API VAL
import { Hono } from "npm:hono@4.4.12";
import { OpenAI } from "https://esm.town/v/std/openai";
import type { Context } from "npm:hono@4.4.12";
import { streamText } from "npm:hono@4.4.12/streaming";
// --- BACKEND SERVICES ---
const services = {
  async callOpenAI(
    systemPrompt: string,
    userContent: string | object,
      c = null,
    } = options;
    const openai = new OpenAI();
    const messages: any[] = [{ role: "system", content: systemPrompt }, {
      role: "user",
    if (isJson) requestPayload.response_format = { type: "json_object" };
    try {
      const completion = await openai.chat.completions.create(requestPayload);
      if (stream && c) {
        return streamText(c, async (s) => {
      return completion;
    } catch (e) {
      console.error(`Error calling OpenAI: ${e.message}`);
      throw new Error("AI service failed.");
    }
  }
  const userContent = `Company Context: ${JSON.stringify(company_context)}`;
  return services.callOpenAI(config.prompts.INDUSTRY_GENERATOR, userContent, {
    c,
    isJson: true,
    },
  };
  return services.callOpenAI(config.prompts.DYNAMIC_LIST_GENERATOR, payload, {
    c,
    isJson: true,
  };
  // We call OpenAI, expecting JSON
  return services.callOpenAI(config.prompts.TASK_DEFINER, userContent, {
    c,
    isJson: true,
  // in case the userPrompt logic diverges more significantly later.
  if (category === "prompt_building") {
    return services.callOpenAI(systemPrompt, userPrompt, { c, stream: true });
  } else {
    return services.callOpenAI(systemPrompt, userPrompt, { c, stream: true });
  }
});
      briefing,
    );
    const criteriaCompletion = await services.callOpenAI(
      "You are a helpful assistant following strict output rules.",
      criteriaPrompt,
      raw_output: first_draft,
    };
    return services.callOpenAI(config.prompts.EVALUATOR_AGENT, userContent, {
      c,
      isJson: true,
## QA Critique
${critique}`;
  return services.callOpenAI(config.prompts.REFINER_AGENT, userContent, {
    c,
    stream: true,

_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" },

// OpenAI + Orama Strategy: Semantic search using OpenAI embeddings and Orama
// Faster than JigsawStack (~100-200ms vs ~550ms for query embeddings)
import { create, insertMultiple, search } from "npm:@orama/orama@latest";
// OpenAI embeddings function
export const generateEmbeddings = async (content: string): Promise<number[] | null> => {
  const OPENAI_API_KEY = Deno.env.get("OPENAI_API_KEY");
  const OPENAI_API_URL = "https://api.openai.com/v1/embeddings";
  
  if (!OPENAI_API_KEY) {
    console.warn("OPENAI_API_KEY not found - embeddings disabled");
    return null;
  }
  
  try {
    const response = await fetch(OPENAI_API_URL, {
      method: "POST",
      headers: {
        "Authorization": `Bearer ${OPENAI_API_KEY}`,
        "Content-Type": "application/json",
      },
    if (!response.ok) {
      const errorText = await response.text().catch(() => response.statusText);
      throw new Error(`OpenAI API error: ${response.status} ${response.statusText} - ${errorText.substring(0, 200)}`);
    }
    
  } catch (error) {
    const errorMessage = error instanceof Error ? error.message : String(error);
    console.error("OpenAI embeddings failed:", errorMessage);
    return null;
  }
export const searchStrategy: SearchStrategy = {
  name: "openai-orama",
  description: "Semantic search using OpenAI embeddings with Orama vector search (faster than JigsawStack)",
  search: async (query: string, pages: Page[], options: SearchOptions = {}): Promise<SearchResult[]> => {
    const limit = options.limit || 10;
        snippet: page ? generateSnippet(page.content, queryWords, query.toLowerCase()) : hit.document.content.substring(0, 200) + '...',
        metadata: {
          strategy: "openai-orama",
          similarity: hit.score,
          ...(enableTiming && { timings }),

// OpenAI + Cosine Similarity Strategy: Direct cosine similarity calculation
// Fastest for small datasets (<100 pages) - no DB overhead
import { generateSnippet, cosineSimilarity } from "./utils.ts";
// OpenAI embeddings function
export const generateEmbeddings = async (content: string): Promise<number[] | null> => {
  const OPENAI_API_KEY = Deno.env.get("OPENAI_API_KEY");
  const OPENAI_API_URL = "https://api.openai.com/v1/embeddings";
  
  if (!OPENAI_API_KEY) {
    console.warn("OPENAI_API_KEY not found - embeddings disabled");
    return null;
  }
  
  try {
    const response = await fetch(OPENAI_API_URL, {
      method: "POST",
      headers: {
        "Authorization": `Bearer ${OPENAI_API_KEY}`,
        "Content-Type": "application/json",
      },
    if (!response.ok) {
      const errorText = await response.text().catch(() => response.statusText);
      throw new Error(`OpenAI API error: ${response.status} ${response.statusText} - ${errorText.substring(0, 200)}`);
    }
    
  } catch (error) {
    const errorMessage = error instanceof Error ? error.message : String(error);
    console.error("OpenAI embeddings failed:", errorMessage);
    return null;
  }
export const searchStrategy: SearchStrategy = {
  name: "openai-cosine",
  description: "Semantic search using OpenAI embeddings with direct cosine similarity (fastest for small datasets)",
  search: async (query: string, pages: Page[], options: SearchOptions = {}): Promise<SearchResult[]> => {
    const limit = options.limit || 10;
      snippet: generateSnippet(page.content, queryWords, query.toLowerCase()),
      metadata: {
        strategy: "openai-cosine",
        similarity,
        ...(enableTiming && { timings }),