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1import { Hono } from "https://esm.sh/hono@3.11.7";
2import { OpenAI } from "https://esm.town/v/std/openai";
3import { getAllTools, getToolsByCategory, getToolById, searchTools } from "../database/queries";
4import { AITool, SearchRequest, ToolCategory } from "../../shared/types";
5
6const api = new Hono();
7const openai = new OpenAI();
8
9// Get all tools
65      const allTools = await getAllTools();
66      
67      // Use OpenAI to analyze the query and recommend tools
68      const aiResponse = await openai.chat.completions.create({
69        model: "gpt-4o-mini",
70        messages: [

46- Frontend: React with Tailwind CSS
47- Backend: Hono API framework
48- AI: OpenAI for query understanding and tool recommendations
49- Database: SQLite for tool information storage

2import React, { useState, useEffect, useCallback } from "https://esm.sh/react@18.2.0";
3import { createRoot } from "https://esm.sh/react-dom@18.2.0/client";
4import { OpenAI } from "https://esm.town/v/std/openai";
5
6// Enhanced subjects with more detailed metadata
394
395export default async function server(request: Request): Promise<Response> {
396  const { OpenAI } = await import("https://esm.town/v/std/openai");
397  const openai = new OpenAI();
398
399  if (request.method === 'POST') {
402    if (request.url.includes('/generate-question')) {
403      try {
404        const completion = await openai.chat.completions.create({
405          messages: [
406            { 

3  const incomingMsg = formData.get("Body")?.toString();
4
5  // Send the SMS text to OpenAI
6  const response = await fetch("https://api.openai.com/v1/chat/completions", {
7    method: "POST",
8    headers: {
9      Authorization: `Bearer ${Deno.env.get("OPENAI_API_KEY")}`,
10      "Content-Type": "application/json",
11    },

88Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.
89
90### OpenAI
91
92```ts
93import { OpenAI } from "https://esm.town/v/std/openai";
94const openai = new OpenAI();
95const completion = await openai.chat.completions.create({
96  messages: [
97    { role: "user", content: "Say hello in a creative way" },

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" },

88Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.
89
90### OpenAI
91
92```ts
93import { OpenAI } from "https://esm.town/v/std/openai";
94const openai = new OpenAI();
95const completion = await openai.chat.completions.create({
96  messages: [
97    { role: "user", content: "Say hello in a creative way" },

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" },

1import { OpenAI } from "https://esm.town/v/std/openai";
2import { Video, ClipSuggestion, KeyframeInfo, TranscriptSegment } from '../../shared/types.ts';
3
4// Initialize OpenAI client
5const openai = new OpenAI();
6
7/**
25    
26    // In a real implementation, we would analyze the actual video content
27    // For this demo, we'll simulate video analysis using OpenAI
28    
29    // First, check if we have transcript data
70async function simulateTranscriptGeneration(video: Video): Promise<TranscriptSegment[]> {
71  // In a real implementation, we would use a speech-to-text service
72  // For this demo, we'll generate a fake transcript using OpenAI
73  
74  const prompt = `Generate a realistic transcript for a ${video.duration || 300} second video titled "${video.title}".
78Format the response as a JSON array of objects with 'start', 'end', and 'text' properties.`;
79
80  const completion = await openai.chat.completions.create({
81    model: "gpt-4o-mini",
82    messages: [{ role: "user", content: prompt }],
114): Promise<KeyframeInfo[]> {
115  // In a real implementation, we would analyze video frames and audio
116  // For this demo, we'll use OpenAI to identify potential key moments from the transcript
117  
118  const transcriptText = transcript.map(segment => segment.text).join(" ");
129Format the response as a JSON array of objects with 'time', 'confidence', and 'description' properties.`;
130
131  const completion = await openai.chat.completions.create({
132    model: "gpt-4o-mini",
133    messages: [{ role: "user", content: prompt }],
254): Promise<string> {
255  // In a real implementation, we would use more sophisticated NLP
256  // For this demo, we'll use OpenAI to generate a title
257  
258  const transcriptText = relevantTranscript.map(segment => segment.text).join(" ");
267The title should be attention-grabbing and optimized for social media engagement.`;
268
269  const completion = await openai.chat.completions.create({
270    model: "gpt-4o-mini",
271    messages: [{ role: "user", content: prompt }],
286): Promise<string> {
287  // In a real implementation, we would use more sophisticated NLP
288  // For this demo, we'll use OpenAI to generate a description
289  
290  const transcriptText = relevantTranscript.map(segment => segment.text).join(" ");
301Include relevant hashtags if appropriate.`;
302
303  const completion = await openai.chat.completions.create({
304    model: "gpt-4o-mini",
305    messages: [{ role: "user", content: prompt }],

36- **Backend**: Hono (API framework)
37- **Database**: SQLite
38- **AI Services**: OpenAI for content analysis, external video processing APIs
39- **Authentication**: JWT-based auth system
40- **Storage**: Val Town blob storage for metadata, external storage for video files