Search

    language,
    offset = 0,
    model = "openai/gpt-oss-120b",
    reasoning_effort = "medium",
    tools = [],
  }
  const isGptOss = typeof model === "string" && model.startsWith("openai/gpt-oss");
  const supportsReasoning = isGptOss;
  const supportsTools = isGptOss;
  const baseUrl = (typeof base_url === "string" && base_url.trim()) ? base_url.trim().replace(/\/$/, "") : "";
  let endpoint = "https://api.groq.com/openai/v1/chat/completions";
  if (baseUrl) {
    if (/(\/v\d+)?\/(chat\/)?completions$/i.test(baseUrl)) {

export async function groqChatCompletion(apiKey, payload) {
  console.log('>>> [groqChatCompletion] Payload:', payload);
  const response = await fetch('https://api.groq.com/openai/v1/chat/completions', {
    method: 'POST',
    headers: {
  try {
    const res = await groqChatCompletion(apiKey, {
      model: 'openai/gpt-oss-120b',
      messages: [
        { role: 'system', content: 'Classify the user request as either links or text. Respond with a single token: links or text. Use links if the user appears to want a search results list of sources; use text if the user is asking for an explanation/summary/definition.' },

        language,
        offset = 0,
        model = 'openai/gpt-oss-120b',
        reasoning_effort = 'medium',
        tools = [],
      }
      const isGptOss = typeof model === 'string' && model.startsWith('openai/gpt-oss');
      const supportsReasoning = isGptOss;
      const supportsTools = isGptOss;
      const encoder = new TextEncoder();
      const baseUrl = (typeof base_url === 'string' && base_url.trim()) ? base_url.trim().replace(/\/$/, '') : '';
      let endpoint = 'https://api.groq.com/openai/v1/chat/completions';
      if (baseUrl) {
        if (/(\/v\d+)?\/(chat\/)?completions$/i.test(baseUrl)) {

import { Hono } from "https://esm.sh/hono@3.11.7";
import { OpenAI } from "https://esm.town/v/std/openai";
import { email } from "https://esm.town/v/std/email";
import type { ChatRequest, ChatResponse, InviteRequest, InviteDetails } from "../../shared/types.ts";
const api = new Hono();
const openai = new OpenAI();
// Middleware to ensure user is authenticated
  const messages = await getConversationMessages(currentConversationId);
  
  // Prepare messages for OpenAI (exclude the current user message since we'll add it)
  const chatMessages = messages
    .filter(m => m.id !== userMessage.id) // Exclude the message we just added
  try {
    // Get response from ChatGPT
    const completion = await openai.chat.completions.create({
      messages: chatMessages,
      model: "gpt-4o-mini",

- **Automatic user creation** on first login
- **Conversation history storage** with full message history
- **ChatGPT integration** via OpenAI API
- **Group chat functionality** with role-based permissions
- **Email invitations** with secure tokens

## Tech Stack
- **Backend**: Hono, LastLogin auth, SQLite, OpenAI, Server-Sent Events
- **Frontend**: React, TailwindCSS, Real-time SSE connections
- **Database**: SQLite with participant and invitation tables

              <div class="relative">
                <select x-model="selectedModel" @change="onModelChange()" class="px-2 py-1 pr-8 border border-gray-200 dark:border-gray-600 bg-white dark:bg-gray-700 rounded-md focus:ring-2 focus:ring-blue-500 appearance-none text-xs w-full dark:text-gray-200">
                  <option value="openai/gpt-oss-120b">openai/gpt-oss-120b</option>
                  <option value="openai/gpt-oss-20b">openai/gpt-oss-20b</option>
                  <option value="llama-3.1-8b-instant">llama-3.1-8b-instant</option>
                  <option value="llama-3.3-70b-versatile">llama-3.3-70b-versatile</option>
                <span>JSON mode</span>
              </label>
              <label class="inline-flex items-center gap-2 text-xs text-gray-600 dark:text-gray-300" x-show="selectedModel && selectedModel.startsWith('openai/gpt-oss')">
                <input type="checkbox" x-model="useBrowserSearch" @change="onUseBrowserSearchChange()" class="rounded border-gray-300 dark:border-gray-600">
                <span>browser search</span>
              </label>
              <label class="inline-flex items-center gap-2 text-xs text-gray-600 dark:text-gray-300" x-show="selectedModel && selectedModel.startsWith('openai/gpt-oss')">
                <input type="checkbox" x-model="useCodeInterpreter" @change="onUseCodeInterpreterChange()" class="rounded border-gray-300 dark:border-gray-600">
                <span>code interpreter</span>

- ✅ Chat message display with user/assistant styling
- ✅ Message input with textarea and send button
- ✅ OpenAI API integration (GPT-4o-mini)
- ✅ Real-time message updates
- ✅ Loading states and typing indicators

import { sqlite } from "https://esm.town/v/stevekrouse/sqlite/main.tsx";
import { readFile, serveFile } from "https://esm.town/v/std/utils@85-main/index.ts";
import { OpenAI } from "https://esm.town/v/std/openai";
const app = new Hono();
const openai = new OpenAI();
// Unwrap Hono errors to see original error details
});
// Send a message and get OpenAI response
app.post("/api/threads/:threadId/messages", async (c) => {
  const email = c.req.header('X-LastLogin-Email');
    );
    // Prepare messages for OpenAI (limit to last 20 messages to avoid token limits)
    const messages = messageHistory.slice(-20).map(msg => ({
      role: msg.role as 'user' | 'assistant',
    }));
    // Get OpenAI response
    const completion = await openai.chat.completions.create({
      model: "gpt-4o-mini",
      messages: messages,
    
    if (!assistantResponse) {
      throw new Error("No response from OpenAI");
    }

import { PresidentDocs } from "./nonprofitDocs";
import { OpenAI } from "https://esm.town/v/std/openai";
const openai = new OpenAI();
export default async function (req: Request): Promise<Response> {
  // { role: "user", content: "Say hello in a creative way" },
  const completion = await openai.chat.completions.create({
    messages: [
      { role: "system", content: systemPrompt },