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// MEES Assistant API Endpoint with v2 API
// Remember to add your environment variables in Val settings:
// - OPENAI_API_KEY
// - PINECONE_API_KEY
// - ASSISTANT_ID
// - PARSER_ASSISTANT_ID (optional)
import { OpenAI } from "https://deno.land/x/openai@v4.20.1/mod.ts";
import { Pinecone } from "https://esm.sh/@pinecone-database/pinecone@2.0.0";
// Use OpenAI client only for embeddings
const openai = new OpenAI({
  apiKey: Deno.env.get("OPENAI_API_KEY"),
});
async function parseQueryIntent(query: string) {
  try {
    const OPENAI_API_KEY = Deno.env.get("OPENAI_API_KEY");
    // Create a quick thread for parsing
    const threadResponse = await fetch("https://api.openai.com/v1/threads", {
      method: "POST",
      headers: {
        "Authorization": `Bearer ${OPENAI_API_KEY}`,
        "Content-Type": "application/json",
        "OpenAI-Beta": "assistants=v2",
      },
      body: JSON.stringify({}),
    // Add the query
    await fetch(`https://api.openai.com/v1/threads/${thread.id}/messages`, {
      method: "POST",
      headers: {
        "Authorization": `Bearer ${OPENAI_API_KEY}`,
        "Content-Type": "application/json",
        "OpenAI-Beta": "assistants=v2",
      },
      body: JSON.stringify({
    // Run the parser assistant
    const runResponse = await fetch(`https://api.openai.com/v1/threads/${thread.id}/runs`, {
      method: "POST",
      headers: {
        "Authorization": `Bearer ${OPENAI_API_KEY}`,
        "Content-Type": "application/json",
        "OpenAI-Beta": "assistants=v2",
      },
      body: JSON.stringify({
      const statusResponse = await fetch(
        `https://api.openai.com/v1/threads/${thread.id}/runs/${run.id}`,
        {
          headers: {
            "Authorization": `Bearer ${OPENAI_API_KEY}`,
            "OpenAI-Beta": "assistants=v2",
          },
        },
    // Get the response
    const messagesResponse = await fetch(
      `https://api.openai.com/v1/threads/${thread.id}/messages?order=desc&limit=1`,
      {
        headers: {
          "Authorization": `Bearer ${OPENAI_API_KEY}`,
          "OpenAI-Beta": "assistants=v2",
        },
      },
  // Get embedding for query
  const embeddingResponse = await openai.embeddings.create({
    model: "text-embedding-3-small",
    input: query,
        });
        // Step 4: Format data for OpenAI
        debugInfo += `\n\n📦 STEP 4: DATA FORMATTING FOR OPENAI\n${"-".repeat(40)}\n`;
        const formattedResults = searchResults.slice(0, 10).map((match) => {
          const mediaInText = extractMediaFromText(meta.text || "");
          // Truncate text for OpenAI
          let textContent = meta.text || "";
          const maxTextLength = 500;
        });
        debugInfo += `✅ Formatted ${formattedResults.length} results for OpenAI\n`;
        debugInfo += `📄 Sample formatted result:\n${
          JSON.stringify(formattedResults[0], null, 2).substring(0, 800)
    }
    const OPENAI_API_KEY = Deno.env.get("OPENAI_API_KEY");
    if (!OPENAI_API_KEY) {
      throw new Error("OPENAI_API_KEY not found in environment variables");
    }
    }
    // IMPORTANT: All OpenAI API calls use these headers with assistants=v2
    const baseHeaders = {
      "Authorization": `Bearer ${OPENAI_API_KEY}`,
      "Content-Type": "application/json",
      "OpenAI-Beta": "assistants=v2",
    };
    console.log("Assistant ID:", ASSISTANT_ID);
    console.log("Using OpenAI-Beta: assistants=v2");
    // Parse the query first (if parser assistant is configured)
    let thread;
    if (threadId) {
      const threadResponse = await fetch(`https://api.openai.com/v1/threads/${threadId}`, {
        headers: baseHeaders,
      });
      thread = await threadResponse.json();
    } else {
      const threadResponse = await fetch("https://api.openai.com/v1/threads", {
        method: "POST",
        headers: baseHeaders,
    // Add message to thread with v2 headers
    const messageResponse = await fetch(`https://api.openai.com/v1/threads/${thread.id}/messages`, {
      method: "POST",
      headers: baseHeaders,
    // Run the assistant with v2 headers
    const runResponse = await fetch(`https://api.openai.com/v1/threads/${thread.id}/runs`, {
      method: "POST",
      headers: baseHeaders,
              const mediaInText = extractMediaFromText(meta.text || "");
              // OPTIMIZATION: Only send text excerpts to OpenAI
              let textContent = meta.text || "";
              const maxTextLength = 500;
      const statusResponse = await fetch(
        `https://api.openai.com/v1/threads/${thread.id}/runs/${run.id}`,
        { headers: baseHeaders },
      );
          // Submit tool outputs with v2 headers
          const toolOutputResponse = await fetch(
            `https://api.openai.com/v1/threads/${thread.id}/runs/${run.id}/submit_tool_outputs`,
            {
              method: "POST",
    // Get the assistant's response with v2 headers
    const messagesResponse = await fetch(
      `https://api.openai.com/v1/threads/${thread.id}/messages?order=desc&limit=20`,
      { headers: baseHeaders },
    );

import { OpenAI } from "https://esm.town/v/std/openai";
import React, { useEffect, useState } from "npm:react";
const openai = new OpenAI();
interface Todo {
`;
      const response = await openai.chat.completions.create({
        model: "gpt-4",
        messages: [{ role: "user", content: prompt }],

import type { MCPTool, ThoughtFork, ThoughtExploration } from "../../../shared/types.ts";
import type { AuthContext } from "../auth.ts";
import { OpenAI } from "https://esm.town/v/std/openai";
import {
  createThoughtFork,
} from "../../database/queries.ts";
const openai = new OpenAI();
export const forkThoughtTools: MCPTool[] = [
    
    try {
      const completion = await openai.chat.completions.create({
        messages: [
          {
  try {
    const completion = await openai.chat.completions.create({
      messages: [
        {
async function extractInsights(content: string): Promise<string[]> {
  try {
    const completion = await openai.chat.completions.create({
      messages: [
        {
  try {
    const completion = await openai.chat.completions.create({
      messages: [
        {

      <footer className="mt-12 text-center text-gray-500 text-sm">
        <p>Built with ❤️ on Val Town • Powered by OpenAI</p>
      </footer>
    </div>

- ✅ Create, read, update, and delete TODO items
- 🤖 AI-powered task prioritization using OpenAI
- 📱 Responsive web interface
- 💾 SQLite database storage

  if (request.method === 'POST' && new URL(request.url).pathname === '/ai-analysis') {
    try {
      const { OpenAI } = await import("https://esm.town/v/std/openai");
      
      const body: AIAnalysisRequest = await request.json();
      }
      const openai = new OpenAI();
      const prompt = `Tu ek expert crypto trader aur market analyst hai. 
      Creative aur informative hinglish mein jawab do. Agar user ne koi specific coin mention kiya hai to uske baare mein detailed analysis do.`;
      const completion = await openai.chat.completions.create({
        messages: [{ role: "user", content: prompt }],
        model: "gpt-4o-mini",

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" },

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