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Maximum size is ${MEDIA_CONSTRAINTS.maxFileSize / (1024 * 1024)}MB` \n }, 400);\n }\n\n // Sanitize filename\n const cleanFileName = sanitizeFileName(fileName);\n \n // Store file in blob storage\n const blobKey = `media_${user.id}_${Date.now()}_${cleanFileName}`;\n await blob.set(blobKey, fileData);\n\n // Analyze based on media type\n let analysisResult: AnalysisResponse;\n \n switch (mediaType) {\n case 'image':\n analysisResult = await analyzeImage(fileData, cleanFileName);\n break;\n case 'audio':\n analysisResult = await analyzeAudio(fileData, cleanFileName);\n break;\n case 'video':\n analysisResult = await analyzeVideo(fileData, cleanFileName);\n break;\n default:\n return c.json({ \n success: false, \n message: 'Unsupported media type' \n }, 400);\n }\n\n if (!analysisResult.success) {\n // Clean up blob if analysis failed\n await blob.delete(blobKey);\n return c.json(analysisResult, 500);\n }\n\n // Save analysis to database\n const mediaAnalysis = await createMediaAnalysis(\n user.id,\n mediaType,\n cleanFileName,\n estimatedSize,\n blobKey,\n analysisResult.analysis!.description,\n analysisResult.analysis!.tags,\n analysisResult.analysis!.confidence\n );\n\n return c.json({\n success: true,\n analysis: analysisResult.analysis,\n mediaId: mediaAnalysis.id,\n message: 'Media analyzed successfully'\n });\n\n } catch (error) {\n console.error('Media analysis error:', error);\n return c.json({ \n success: false, \n message: 'Failed to analyze media' \n }, 500);\n }\n});\n\n// Search media analyses\nmedia.post('/search', requireAuth, async (c) => {\n try {\n const user = getCurrentUser(c);\n const { query, mediaType, limit = 20 }: SearchRequest = await c.req.json();\n\n if (!query || query.trim().length === 0) {\n return c.json({ \n success: false, \n message: 'Search query is required' \n }, 400);\n }\n\n // Perform search\n const results = await searchMediaAnalyses(\n user.id, \n query.trim(), \n mediaType, \n Math.min(limit, 50) // Cap at 50 results\n );\n\n // Save search to history\n await createSearchHistory(user.id, query.trim(), mediaType || null, results.length);\n\n // Generate search suggestions\n const suggestions = await generateSearchSuggestions(query);\n\n return c.json({\n success: true,\n results,\n suggestions,\n message: `Found ${results.length} results`\n });\n\n } catch (error) {\n console.error('Search error:', error);\n return c.json({ \n success: false, \n message: 'Search failed' \n }, 500);\n }\n});\n\n// Get user's media history\nmedia.get('/history', requireAuth, async (c) => {\n try {\n const user = getCurrentUser(c);\n const limit = parseInt(c.req.query('limit') || '50');\n \n const analyses = await getUserMediaAnalyses(user.id, Math.min(limit, 100));\n \n return c.json({\n success: true,\n analyses,\n message: `Retrieved ${analyses.length} analyses`\n });\n\n } catch (error) {\n console.error('History error:', error);\n return c.json({ \n success: false, \n message: 'Failed to retrieve history' \n }, 500);\n }\n});\n\n// Delete media analysis\nmedia.delete('/:id', requireAuth, async (c) => {\n try {\n const user = getCurrentUser(c);\n const id = parseInt(c.req.param('id'));\n\n if (isNaN(id)) {\n return c.json({ \n success: false, \n message: 'Invalid media ID' \n }, 400);\n }\n\n const deleted = await deleteMediaAnalysis(id, user.id);\n \n if (!deleted) {\n return c.json({ \n success: false, \n message: 'Media analysis not found or access denied' \n }, 404);\n }\n\n return c.json({\n success: true,\n message: 'Media analysis deleted successfully'\n });\n\n } catch (error) {\n console.error('Delete error:', error);\n return c.json({ \n success: false, \n message: 'Failed to delete media analysis' \n }, 500);\n }\n});\n\n// Get media file (for viewing)\nmedia.get('/file/:id', requireAuth, async (c) => {\n try {\n const user = getCurrentUser(c);\n const id = parseInt(c.req.param('id'));\n\n if (isNaN(id)) {\n return c.json({ \n success: false, \n message: 'Invalid media ID' \n }, 400);\n }\n\n // Get media analysis to verify ownership and get blob key\n const analysis = await getUserMediaAnalyses(user.id, 1000)\n .then(analyses => analyses.find(a => a.id === id));\n\n if (!analysis) {\n return c.json({ \n success: false, \n message: 'Media not found or access denied' \n }, 404);\n }\n\n // Get file from blob storage\n const fileData = await blob.get(analysis.blob_key);\n \n if (!fileData) {\n return c.json({ \n success: false, \n message: 'Media file not found in storage' \n }, 404);\n }\n\n // Determine content type\n const extension = extractFileExtension(analysis.file_name);\n let contentType = 'application/octet-stream';\n \n if (['jpg', 'jpeg'].includes(extension)) contentType = 'image/jpeg';\n else if (extension === 'png') contentType = 'image/png';\n else if (extension === 'webp') contentType = 'image/webp';\n else if (extension === 'mp4') contentType = 'video/mp4';\n else if (extension === 'webm') contentType = 'video/webm';\n else if (extension === 'mp3') contentType = 'audio/mpeg';\n else if (extension === 'wav') contentType = 'audio/wav';\n\n return new Response(fileData, {\n headers: {\n 'Content-Type': contentType,\n 'Content-Disposition': `inline; filename=\"${analysis.file_name}\"`\n }\n });\n\n } catch (error) {\n console.error('File retrieval error:', error);\n return c.json({ \n success: false, \n message: 'Failed to retrieve media file' \n }, 500);\n }\n});\n\nexport default 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AI/ML Media Recognition Platform\n\nA comprehensive platform for AI-powered media recognition with user authentication, real-time analysis, and intelligent search capabilities.\n\n## Features\n\n- **User Authentication**: Secure login/signup system with session management\n- **Multi-Media Support**: Image, video, and audio recognition\n- **Real-time Capture**: In-browser media capture capabilities\n- **AI Analysis**: Powered by OpenAI's vision and audio models\n- **Intelligent Search**: Find similar content based on descriptions\n- **Secure Storage**: User data and media metadata stored securely\n\n## Architecture\n\n### Backend (`/backend/`)\n- **index.ts**: Main Hono server with API routes\n- **database/**: SQLite database setup and queries\n- **routes/**: Modular route handlers\n- **auth/**: Authentication middleware and utilities\n\n### Frontend (`/frontend/`)\n- **index.html**: Main application shell\n- **components/**: React components for UI\n- **services/**: API communication and media handling\n- **utils/**: Client-side utilities\n\n### Shared (`/shared/`)\n- **types.ts**: TypeScript interfaces and types\n- **utils.ts**: Shared utility functions\n\n## API Endpoints\n\n- `POST /api/auth/login` - User login\n- `POST /api/auth/signup` - User registration\n- `POST /api/auth/logout` - User logout\n- `GET /api/auth/me` - Get current user\n- `POST /api/media/analyze` - Analyze uploaded media\n- `POST /api/media/search` - Search similar content\n- `GET /api/media/history` - Get user's analysis history\n\n## Technology Stack\n\n- **Backend**: Hono, SQLite, OpenAI API\n- **Frontend**: React, TailwindCSS\n- **AI/ML**: OpenAI GPT-4 Vision, Whisper\n- **Storage**: Val Town Blob storage\n- **Authentication**: JWT-based sessions\n\n## Getting Started\n\n1. Set up environment variables:\n - `OPENAI_API_KEY`: Your OpenAI API key\n - `JWT_SECRET`: Secret for JWT token signing\n\n2. The application will automatically create database tables on first run\n\n3. Access the application at the HTTP endpoint URL\n\n## Security Features\n\n- Password hashing with bcrypt\n- JWT-based authentication\n- CORS protection\n- Input validation and sanitization\n- Secure file upload handling",[143],"61d6e258-3cb8-11f0-a555-9e149126039e","04_email.tsx","61d6e2ee-3cb8-11f0-a555-9e149126039e",5,["D",1748542306158],"email","// This code is triggered when an email is sent to its unique address.\n// Click \"Run\", copy and paste the email address and send an email to it.\n// This example will log the email details received.\nexport default async function emailHandler(email: Email){\n console.log(\"Email received!\", email.from, email.subject, email.text);\n for (const file of email.attachments) {\n console.log(`Filename: ${file.name}`);\n console.log(`Content Type: ${file.type}`);\n console.log(`Content: ${await file.text()}`);\n }\n}",[151],"61d4961a-3cb8-11f0-a555-9e149126039e","03_cron.tsx","61d496ba-3cb8-11f0-a555-9e149126039e",4,["D",1748542306141],"interval","// This cron runs on a schedule (e.g. every hour, day).\n// Configure the timer with the 🕒 icon in the top right.\n// This example just logs the current time.\nexport function scheduledHandler() {\n const timestamp = new Date().toISOString();\n console.log(`Cron val executed at: ${timestamp}`);\n return `Executed at ${timestamp}`;\n}",[159],"61d29036-3cb8-11f0-a555-9e149126039e","02_http.tsx",3,["D",1748542306129],"http","// This code responds to HTTP web requests.\n// Access it via its public URL (you can also pick a nicer subdomain).\n// Try adding ?name=YourName to the URL!\nexport default function httpHandler(req: Request): Response {\n const url = new URL(req.url);\n const name = url.searchParams.get(\"name\") || \"Friend\";\n console.log(`Greeted ${name} via HTTP`);\n return new Response(`Hello, ${name}! Welcome to Val Town.`);\n}",[167],"61d0c65c-3cb8-11f0-a555-9e149126039e","01_script.tsx","61d0c706-3cb8-11f0-a555-9e149126039e",2,["D",1748542306117],"// This script returns a random fun fact\n// You can run scripts manually in this view or call it from other vals.\nexport default function getRandomFact() {\n const funFacts = [\n \"Honey never spoils.\",\n \"Bananas are actually berries, but strawberries are not.\",\n \"Val Town has a citizen Juicy Bear. 🐻\",\n ];\n const fact = funFacts[Math.floor(Math.random() * funFacts.length)];\n return fact;\n}\nconsole.log(\"Fun fact:\", getRandomFact());\n",[174],"532f31b8-3cba-11f0-b872-9e149126039e","shared","d1679996-877c-44a1-9d8e-b54e3dba81a5",8,["D",1748543140561],"directory",[181],"630ab242-3cba-11f0-bbbe-9e149126039e","backend","b451bc98-fdf2-4a33-a9e6-5d661aed07bd",10,["D",1748543167164],[188],"pulls","branches","forks","envVars",{"_200":61,"_202":61},"connections",{"_200":61,"_201":61},"count","unfilledCount","emptyCount",{"_42":187,"_31":188,"_29":189,"_136":-5,"_40":41,"_39":190,"_138":57,"_37":326,"_13":61,"_33":185,"_35":-5,"_23":24,"_140":-5,"_224":327,"_26":328},{"_42":322,"_31":321,"_29":315,"_136":189,"_40":41,"_39":316,"_138":57,"_37":323,"_13":61,"_33":185,"_35":-5,"_23":24,"_140":-5,"_224":324,"_26":325},{"_42":313,"_31":243,"_29":314,"_136":315,"_40":41,"_39":316,"_138":57,"_37":317,"_13":61,"_33":34,"_35":318,"_23":24,"_140":-5,"_224":319,"_26":320},{"_42":309,"_31":301,"_29":295,"_136":189,"_40":41,"_39":190,"_138":57,"_37":310,"_13":61,"_33":185,"_35":-5,"_23":24,"_140":-5,"_224":311,"_26":312},{"_42":302,"_31":303,"_29":304,"_136":295,"_40":41,"_39":190,"_138":57,"_37":305,"_13":61,"_33":34,"_35":306,"_23":24,"_140":-5,"_224":307,"_26":308},{"_42":292,"_31":293,"_29":294,"_136":295,"_40":41,"_39":296,"_138":57,"_37":297,"_13":61,"_33":34,"_35":298,"_23":24,"_140":-5,"_224":299,"_26":300},{"_42":288,"_31":279,"_29":275,"_136":189,"_40":41,"_39":283,"_138":57,"_37":289,"_13":61,"_33":185,"_35":-5,"_23":24,"_140":-5,"_224":290,"_26":291},{"_42":280,"_31":281,"_29":282,"_136":275,"_40":41,"_39":283,"_138":57,"_37":284,"_13":61,"_33":34,"_35":285,"_23":24,"_140":-5,"_224":286,"_26":287},{"_42":274,"_31":32,"_29":30,"_136":275,"_40":41,"_39":14,"_138":57,"_37":276,"_13":61,"_33":34,"_35":36,"_23":24,"_140":-5,"_224":277,"_26":278},{"_42":270,"_31":269,"_29":263,"_136":189,"_40":41,"_39":264,"_138":57,"_37":271,"_13":61,"_33":185,"_35":-5,"_23":24,"_140":-5,"_224":272,"_26":273},{"_42":260,"_31":261,"_29":262,"_136":263,"_40":41,"_39":264,"_138":57,"_37":265,"_13":61,"_33":34,"_35":266,"_23":24,"_140":-5,"_224":267,"_26":268},{"_42":180,"_31":181,"_29":182,"_136":-5,"_40":41,"_39":183,"_138":57,"_37":257,"_13":61,"_33":185,"_35":-5,"_23":24,"_140":-5,"_224":258,"_26":259},{"_42":250,"_31":251,"_29":252,"_136":182,"_40":41,"_39":183,"_138":57,"_37":253,"_13":61,"_33":34,"_35":254,"_23":24,"_140":-5,"_224":255,"_26":256},{"_42":242,"_31":243,"_29":244,"_136":182,"_40":41,"_39":245,"_138":57,"_37":246,"_13":61,"_33":34,"_35":247,"_23":24,"_140":-5,"_224":248,"_26":249},{"_42":173,"_31":174,"_29":175,"_136":-5,"_40":41,"_39":176,"_138":57,"_37":239,"_13":61,"_33":34,"_35":178,"_23":24,"_140":-5,"_224":240,"_26":241},{"_42":166,"_31":167,"_29":55,"_136":-5,"_40":41,"_39":168,"_138":57,"_37":236,"_13":61,"_33":170,"_35":171,"_23":24,"_140":-5,"_224":237,"_26":238},{"_42":158,"_31":159,"_29":160,"_136":-5,"_40":41,"_39":161,"_138":57,"_37":233,"_13":61,"_33":163,"_35":164,"_23":24,"_140":-5,"_224":234,"_26":235},{"_42":150,"_31":151,"_29":152,"_136":-5,"_40":41,"_39":153,"_138":57,"_37":230,"_13":61,"_33":155,"_35":156,"_23":24,"_140":-5,"_224":231,"_26":232},{"_42":142,"_31":143,"_29":144,"_136":-5,"_40":41,"_39":145,"_138":57,"_37":227,"_13":147,"_33":20,"_35":148,"_23":24,"_140":-5,"_224":228,"_26":229},{"_42":133,"_31":134,"_29":135,"_136":-5,"_40":41,"_39":137,"_138":57,"_37":223,"_13":61,"_33":34,"_35":104,"_23":24,"_140":-5,"_224":225,"_26":226},["D",1748542449711],"children",[],[134],["D",1748543129866],[],[143],["D",1748542306158],[],[151],["D",1748542306141],[],[159],["D",1748542306129],[],[167],["D",1748542306117],[],[174],"5ac9717c-3cba-11f0-a693-9e149126039e","utils.ts","5ac97244-3cba-11f0-a693-9e149126039e",9,["D",1748543153316],"// Shared utility functions\n\nexport function validateEmail(email: string): boolean {\n const emailRegex = /^[^\\s@]+@[^\\s@]+\\.[^\\s@]+$/;\n return emailRegex.test(email);\n}\n\nexport function validatePassword(password: string): { valid: boolean; message?: string } {\n if (password.length < 8) {\n return { valid: false, message: 'Password must be at least 8 characters long' };\n }\n if (!/(?=.*[a-z])/.test(password)) {\n return { valid: false, message: 'Password must contain at least one lowercase letter' };\n }\n if (!/(?=.*[A-Z])/.test(password)) {\n return { valid: false, message: 'Password must contain at least one uppercase letter' };\n }\n if (!/(?=.*\\d)/.test(password)) {\n return { valid: false, message: 'Password must contain at least one number' };\n }\n return { valid: true };\n}\n\nexport function formatFileSize(bytes: number): string {\n if (bytes === 0) return '0 Bytes';\n const k = 1024;\n const sizes = ['Bytes', 'KB', 'MB', 'GB'];\n const i = Math.floor(Math.log(bytes) / Math.log(k));\n return parseFloat((bytes / Math.pow(k, i)).toFixed(2)) + ' ' + sizes[i];\n}\n\nexport function formatDate(dateString: string): string {\n const date = new Date(dateString);\n return date.toLocaleDateString() + ' ' + date.toLocaleTimeString();\n}\n\nexport function generateId(): string {\n return Math.random().toString(36).substr(2, 9);\n}\n\nexport function sanitizeFileName(fileName: string): string {\n return fileName.replace(/[^a-zA-Z0-9.-]/g, '_');\n}\n\nexport function extractFileExtension(fileName: string): string {\n return fileName.split('.').pop()?.toLowerCase() || '';\n}\n\nexport function isValidMediaType(mimeType: string, allowedTypes: string[]): boolean {\n return allowedTypes.includes(mimeType);\n}\n\nexport function truncateText(text: string, maxLength: number): string {\n if (text.length <= maxLength) return text;\n return text.substr(0, maxLength) + '...';\n}\n\nexport function debounce any>(\n func: T,\n wait: number\n): (...args: Parameters) => void {\n let timeout: number | undefined;\n return (...args: Parameters) => {\n clearTimeout(timeout);\n timeout = setTimeout(() => func(...args), wait);\n };\n}\n\nexport function createFormData(data: Record): FormData {\n const formData = new FormData();\n Object.entries(data).forEach(([key, value]) => {\n if (value instanceof File) {\n formData.append(key, value);\n } else {\n formData.append(key, JSON.stringify(value));\n }\n });\n return formData;\n}",[],[181,243],"532f12f0-3cba-11f0-b872-9e149126039e","types.ts","532f13cc-3cba-11f0-b872-9e149126039e",["D",1748543140561],"// Shared TypeScript types and interfaces\n\nexport interface User {\n id: number;\n email: string;\n username: string;\n created_at: string;\n}\n\nexport interface AuthResponse {\n success: boolean;\n user?: User;\n token?: string;\n message?: string;\n}\n\nexport interface MediaAnalysis {\n id: number;\n user_id: number;\n media_type: 'image' | 'video' | 'audio';\n file_name: string;\n file_size: number;\n analysis_result: string;\n tags: string[];\n confidence_score: number;\n created_at: string;\n}\n\nexport interface AnalysisRequest {\n mediaType: 'image' | 'video' | 'audio';\n fileName: string;\n fileData: string; // base64 encoded\n}\n\nexport interface AnalysisResponse {\n success: boolean;\n analysis?: {\n description: string;\n tags: string[];\n confidence: number;\n objects?: string[];\n emotions?: string[];\n text?: string;\n };\n message?: string;\n}\n\nexport interface SearchRequest {\n query: string;\n mediaType?: 'image' | 'video' | 'audio';\n limit?: number;\n}\n\nexport interface SearchResponse {\n success: boolean;\n results?: MediaAnalysis[];\n message?: string;\n}\n\nexport interface ApiResponse {\n success: boolean;\n data?: T;\n message?: string;\n error?: string;\n}\n\nexport interface CaptureOptions {\n video?: boolean;\n audio?: boolean;\n facingMode?: 'user' | 'environment';\n}\n\nexport interface MediaConstraints {\n maxFileSize: number; // in bytes\n allowedTypes: string[];\n maxDuration?: number; // for video/audio in seconds\n}\n\nexport const MEDIA_CONSTRAINTS: MediaConstraints = {\n maxFileSize: 50 * 1024 * 1024, // 50MB\n allowedTypes: [\n 'image/jpeg',\n 'image/png',\n 'image/webp',\n 'video/mp4',\n 'video/webm',\n 'audio/mp3',\n 'audio/wav',\n 'audio/webm'\n ],\n maxDuration: 300 // 5 minutes\n};",[],[181,251],["D",1748543140561],[215,216],[181],"8b012448-3cba-11f0-8bcc-9e149126039e","ai-analysis.ts","8b012510-3cba-11f0-8bcc-9e149126039e","25c031c1-741e-47c3-9312-45c5ab04aaf1",13,["D",1748543234212],"import { OpenAI } from \"https://esm.town/v/std/openai\";\nimport type { AnalysisResponse } from \"../../shared/types.ts\";\n\nconst openai = new OpenAI();\n\nexport async function analyzeImage(imageData: string, fileName: string): Promise {\n try {\n // Remove data URL prefix if present\n const base64Data = imageData.replace(/^data:image\\/[a-z]+;base64,/, '');\n \n const response = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [\n {\n role: \"user\",\n content: [\n {\n type: \"text\",\n text: `Analyze this image and provide:\n1. A detailed description of what you see\n2. List of objects/subjects in the image\n3. Emotions or mood if people are present\n4. Any text visible in the image\n5. Tags for categorization\n6. Confidence level (0-1)\n\nFormat your response as JSON with the following structure:\n{\n \"description\": \"detailed description\",\n \"objects\": [\"object1\", \"object2\"],\n \"emotions\": [\"emotion1\", \"emotion2\"],\n \"text\": \"any visible text\",\n \"tags\": [\"tag1\", \"tag2\", \"tag3\"],\n \"confidence\": 0.95\n}`\n },\n {\n type: \"image_url\",\n image_url: {\n url: `data:image/jpeg;base64,${base64Data}`\n }\n }\n ]\n }\n ],\n max_tokens: 1000\n });\n\n const content = response.choices[0]?.message?.content;\n if (!content) {\n throw new Error('No response from AI model');\n }\n\n // Parse the JSON response\n const analysis = JSON.parse(content);\n \n return {\n success: true,\n analysis: {\n description: analysis.description,\n tags: analysis.tags || [],\n confidence: analysis.confidence || 0.8,\n objects: analysis.objects || [],\n emotions: analysis.emotions || [],\n text: analysis.text || ''\n }\n };\n } catch (error) {\n console.error('Image analysis error:', error);\n return {\n success: false,\n message: `Failed to analyze image: ${error.message}`\n };\n }\n}\n\nexport async function analyzeAudio(audioData: string, fileName: string): Promise {\n try {\n // For audio analysis, we'll use Whisper for transcription and then analyze the text\n // Note: This is a simplified approach. In production, you might want to use specialized audio analysis APIs\n \n // Convert base64 to blob for Whisper API\n const base64Data = audioData.replace(/^data:audio\\/[^;]+;base64,/, '');\n const audioBuffer = Uint8Array.from(atob(base64Data), c => c.charCodeAt(0));\n const audioBlob = new Blob([audioBuffer], { type: 'audio/wav' });\n \n // Create a File object for the API\n const audioFile = new File([audioBlob], fileName, { type: 'audio/wav' });\n \n const transcription = await openai.audio.transcriptions.create({\n file: audioFile,\n model: \"whisper-1\",\n });\n\n const text = transcription.text;\n \n // Analyze the transcribed text\n const textAnalysis = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [\n {\n role: \"user\",\n content: `Analyze this audio transcription and provide:\n1. A summary of the content\n2. Key topics discussed\n3. Emotional tone\n4. Language detected\n5. Tags for categorization\n6. Confidence level (0-1)\n\nTranscription: \"${text}\"\n\nFormat your response as JSON:\n{\n \"description\": \"summary of audio content\",\n \"topics\": [\"topic1\", \"topic2\"],\n \"emotions\": [\"emotion1\", \"emotion2\"],\n \"language\": \"detected language\",\n \"tags\": [\"tag1\", \"tag2\", \"tag3\"],\n \"confidence\": 0.95\n}`\n }\n ],\n max_tokens: 800\n });\n\n const analysisContent = textAnalysis.choices[0]?.message?.content;\n if (!analysisContent) {\n throw new Error('No response from AI model');\n }\n\n const analysis = JSON.parse(analysisContent);\n \n return {\n success: true,\n analysis: {\n description: analysis.description,\n tags: analysis.tags || [],\n confidence: analysis.confidence || 0.8,\n objects: analysis.topics || [],\n emotions: analysis.emotions || [],\n text: text\n }\n };\n } catch (error) {\n console.error('Audio analysis error:', error);\n return {\n success: false,\n message: `Failed to analyze audio: ${error.message}`\n };\n }\n}\n\nexport async function analyzeVideo(videoData: string, fileName: string): Promise {\n try {\n // For video analysis, we'll extract a frame and analyze it as an image\n // In a production environment, you might want to extract multiple frames or use specialized video analysis\n \n // This is a simplified approach - we'll treat the video thumbnail as an image\n // In practice, you'd need to extract frames from the video\n \n const response = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [\n {\n role: \"user\",\n content: `Analyze this video file and provide:\n1. A description of what the video likely contains based on the filename: \"${fileName}\"\n2. Estimated content type (educational, entertainment, documentary, etc.)\n3. Suggested tags for categorization\n4. Confidence level (0-1)\n\nFormat your response as JSON:\n{\n \"description\": \"estimated video content description\",\n \"contentType\": \"content type\",\n \"tags\": [\"tag1\", \"tag2\", \"tag3\"],\n \"confidence\": 0.7\n}`\n }\n ],\n max_tokens: 500\n });\n\n const content = response.choices[0]?.message?.content;\n if (!content) {\n throw new Error('No response from AI model');\n }\n\n const analysis = JSON.parse(content);\n \n return {\n success: true,\n analysis: {\n description: analysis.description,\n tags: analysis.tags || [],\n confidence: analysis.confidence || 0.6, // Lower confidence for filename-based analysis\n objects: [analysis.contentType] || [],\n emotions: [],\n text: ''\n }\n };\n } catch (error) {\n console.error('Video analysis error:', error);\n return {\n success: false,\n message: `Failed to analyze video: ${error.message}`\n };\n }\n}\n\nexport async function generateSearchSuggestions(query: string): Promise {\n try {\n const response = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [\n {\n role: \"user\",\n content: `Generate 5 related search suggestions for the query: \"${query}\"\n \n Focus on:\n - Similar concepts\n - Related objects or subjects\n - Alternative descriptions\n - Broader or narrower terms\n \n Return as a JSON array of strings:\n [\"suggestion1\", \"suggestion2\", \"suggestion3\", \"suggestion4\", \"suggestion5\"]`\n }\n ],\n max_tokens: 200\n });\n\n const content = response.choices[0]?.message?.content;\n if (!content) {\n return [];\n }\n\n return JSON.parse(content);\n } catch (error) {\n console.error('Search suggestions error:', error);\n return [];\n }\n}",[],[188,269,261],"services","8b014a68-3cba-11f0-8bcc-9e149126039e",["D",1748543234212],[213],[188,269],"ad0f3fc0-3cba-11f0-93f2-9e149126039e","8ff4979e-279f-4940-9f37-2aa3515ba625",["D",1748543291349],[],[188,279,32],"routes","98a5cb58-3cba-11f0-8962-9e149126039e","auth.ts","98a5cbf8-3cba-11f0-8962-9e149126039e",14,["D",1748543257101],"import { Hono } from \"https://esm.sh/hono@3.11.7\";\nimport { \n createUser, \n getUserByEmail, \n getUserByUsername, \n getUserPasswordHash,\n deleteUserSessions \n} from \"../database/queries.ts\";\nimport { \n hashPassword, \n verifyPassword, \n createUserSession, \n invalidateSession,\n requireAuth,\n getCurrentUser,\n getTokenFromRequest\n} from \"../auth/utils.ts\";\nimport { validateEmail, validatePassword } from \"../../shared/utils.ts\";\nimport type { AuthResponse } from \"../../shared/types.ts\";\n\nconst auth = new Hono();\n\n// Register new user\nauth.post('/signup', async (c) => {\n try {\n const { email, username, password } = await c.req.json();\n\n // Validate input\n if (!email || !username || !password) {\n return c.json({ \n success: false, \n message: 'Email, username, and password are required' \n }, 400);\n }\n\n if (!validateEmail(email)) {\n return c.json({ \n success: false, \n message: 'Invalid email format' \n }, 400);\n }\n\n const passwordValidation = validatePassword(password);\n if (!passwordValidation.valid) {\n return c.json({ \n success: false, \n message: passwordValidation.message \n }, 400);\n }\n\n // Check if user already exists\n const existingUserByEmail = await getUserByEmail(email);\n if (existingUserByEmail) {\n return c.json({ \n success: false, \n message: 'User with this email already exists' \n }, 409);\n }\n\n const existingUserByUsername = await getUserByUsername(username);\n if (existingUserByUsername) {\n return c.json({ \n success: false, \n message: 'Username already taken' \n }, 409);\n }\n\n // Create user\n const passwordHash = await hashPassword(password);\n const user = await createUser(email, username, passwordHash);\n const token = await createUserSession(user.id);\n\n const response: AuthResponse = {\n success: true,\n user,\n token,\n message: 'User created successfully'\n };\n\n return c.json(response, 201);\n } catch (error) {\n console.error('Signup error:', error);\n return c.json({ \n success: false, \n message: 'Internal server error' \n }, 500);\n }\n});\n\n// Login user\nauth.post('/login', async (c) => {\n try {\n const { email, password } = await c.req.json();\n\n if (!email || !password) {\n return c.json({ \n success: false, \n message: 'Email and password are required' \n }, 400);\n }\n\n // Get user and password hash\n const user = await getUserByEmail(email);\n if (!user) {\n return c.json({ \n success: false, \n message: 'Invalid email or password' \n }, 401);\n }\n\n const passwordHash = await getUserPasswordHash(email);\n if (!passwordHash) {\n return c.json({ \n success: false, \n message: 'Invalid email or password' \n }, 401);\n }\n\n // Verify password\n const isValidPassword = await verifyPassword(password, passwordHash);\n if (!isValidPassword) {\n return c.json({ \n success: false, \n message: 'Invalid email or password' \n }, 401);\n }\n\n // Create session\n const token = await createUserSession(user.id);\n\n const response: AuthResponse = {\n success: true,\n user,\n token,\n message: 'Login successful'\n };\n\n return c.json(response);\n } catch (error) {\n console.error('Login error:', error);\n return c.json({ \n success: false, \n message: 'Internal server error' \n }, 500);\n }\n});\n\n// Logout user\nauth.post('/logout', requireAuth, async (c) => {\n try {\n const token = getTokenFromRequest(c);\n if (token) {\n await invalidateSession(token);\n }\n\n return c.json({ \n success: true, \n message: 'Logout successful' \n });\n } catch (error) {\n console.error('Logout error:', error);\n return c.json({ \n success: false, \n message: 'Internal server error' \n }, 500);\n }\n});\n\n// Get current user\nauth.get('/me', requireAuth, async (c) => {\n try {\n const user = getCurrentUser(c);\n return c.json({ \n success: true, \n user \n });\n } catch (error) {\n console.error('Get user error:', error);\n return c.json({ \n success: false, \n message: 'Internal server error' \n }, 500);\n }\n});\n\n// Logout from all devices\nauth.post('/logout-all', requireAuth, async (c) => {\n try {\n const user = getCurrentUser(c);\n await deleteUserSessions(user.id);\n\n return c.json({ \n success: true, \n message: 'Logged out from all devices' \n });\n } catch (error) {\n console.error('Logout all error:', error);\n return c.json({ \n success: false, \n message: 'Internal server error' \n }, 500);\n }\n});\n\nexport default auth;",[],[188,279,281],"98a5d85a-3cba-11f0-8962-9e149126039e",["D",1748543257101],[210,211],[188,279],"70861c36-3cba-11f0-8367-9e149126039e","queries.ts","70861cf4-3cba-11f0-8367-9e149126039e","7007d617-c866-4d62-b49d-4382369ad7cd",11,["D",1748543189786],"import { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nimport type { User, MediaAnalysis } from \"../../shared/types.ts\";\n\n// User queries\nexport async function createUser(email: string, username: string, passwordHash: string): Promise {\n const result = await sqlite.execute(\n `INSERT INTO users_v1 (email, username, password_hash) VALUES (?, ?, ?) RETURNING *`,\n [email, username, passwordHash]\n );\n return result[0] as User;\n}\n\nexport async function getUserByEmail(email: string): Promise {\n const result = await sqlite.execute(\n `SELECT id, email, username, created_at FROM users_v1 WHERE email = ?`,\n [email]\n );\n return result[0] as User || null;\n}\n\nexport async function getUserByUsername(username: string): Promise {\n const result = await sqlite.execute(\n `SELECT id, email, username, created_at FROM users_v1 WHERE username = ?`,\n [username]\n );\n return result[0] as User || null;\n}\n\nexport async function getUserById(id: number): Promise {\n const result = await sqlite.execute(\n `SELECT id, email, username, created_at FROM users_v1 WHERE id = ?`,\n [id]\n );\n return result[0] as User || null;\n}\n\nexport async function getUserPasswordHash(email: string): Promise {\n const result = await sqlite.execute(\n `SELECT password_hash FROM users_v1 WHERE email = ?`,\n [email]\n );\n return result[0]?.password_hash || null;\n}\n\n// Session queries\nexport async function createSession(userId: number, tokenHash: string, expiresAt: string): Promise {\n await sqlite.execute(\n `INSERT INTO user_sessions_v1 (user_id, token_hash, expires_at) VALUES (?, ?, ?)`,\n [userId, tokenHash, expiresAt]\n );\n}\n\nexport async function validateSession(tokenHash: string): Promise {\n const result = await sqlite.execute(\n `SELECT user_id FROM user_sessions_v1 WHERE token_hash = ? AND expires_at > datetime('now')`,\n [tokenHash]\n );\n return result[0]?.user_id || null;\n}\n\nexport async function deleteSession(tokenHash: string): Promise {\n await sqlite.execute(\n `DELETE FROM user_sessions_v1 WHERE token_hash = ?`,\n [tokenHash]\n );\n}\n\nexport async function deleteUserSessions(userId: number): Promise {\n await sqlite.execute(\n `DELETE FROM user_sessions_v1 WHERE user_id = ?`,\n [userId]\n );\n}\n\n// Media analysis queries\nexport async function createMediaAnalysis(\n userId: number,\n mediaType: string,\n fileName: string,\n fileSize: number,\n blobKey: string,\n analysisResult: string,\n tags: string[],\n confidenceScore: number\n): Promise {\n const result = await sqlite.execute(\n `INSERT INTO media_analyses_v1 \n (user_id, media_type, file_name, file_size, blob_key, analysis_result, tags, confidence_score) \n VALUES (?, ?, ?, ?, ?, ?, ?, ?) RETURNING *`,\n [userId, mediaType, fileName, fileSize, blobKey, JSON.stringify(tags), analysisResult, confidenceScore]\n );\n \n const analysis = result[0] as any;\n return {\n ...analysis,\n tags: JSON.parse(analysis.tags)\n } as MediaAnalysis;\n}\n\nexport async function getUserMediaAnalyses(userId: number, limit: number = 50): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM media_analyses_v1 WHERE user_id = ? ORDER BY created_at DESC LIMIT ?`,\n [userId, limit]\n );\n \n return result.map((analysis: any) => ({\n ...analysis,\n tags: JSON.parse(analysis.tags)\n })) as MediaAnalysis[];\n}\n\nexport async function getMediaAnalysisById(id: number, userId: number): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM media_analyses_v1 WHERE id = ? AND user_id = ?`,\n [id, userId]\n );\n \n if (!result[0]) return null;\n \n const analysis = result[0] as any;\n return {\n ...analysis,\n tags: JSON.parse(analysis.tags)\n } as MediaAnalysis;\n}\n\nexport async function searchMediaAnalyses(\n userId: number,\n query: string,\n mediaType?: string,\n limit: number = 20\n): Promise {\n let sql = `\n SELECT * FROM media_analyses_v1 \n WHERE user_id = ? AND (\n analysis_result LIKE ? OR \n tags LIKE ? OR \n file_name LIKE ?\n )\n `;\n \n const params: any[] = [userId, `%${query}%`, `%${query}%`, `%${query}%`];\n \n if (mediaType) {\n sql += ` AND media_type = ?`;\n params.push(mediaType);\n }\n \n sql += ` ORDER BY created_at DESC LIMIT ?`;\n params.push(limit);\n \n const result = await sqlite.execute(sql, params);\n \n return result.map((analysis: any) => ({\n ...analysis,\n tags: JSON.parse(analysis.tags)\n })) as MediaAnalysis[];\n}\n\nexport async function deleteMediaAnalysis(id: number, userId: number): Promise {\n const result = await sqlite.execute(\n `DELETE FROM media_analyses_v1 WHERE id = ? AND user_id = ?`,\n [id, userId]\n );\n return result.changes > 0;\n}\n\n// Search history queries\nexport async function createSearchHistory(\n userId: number,\n query: string,\n mediaType: string | null,\n resultsCount: number\n): Promise {\n await sqlite.execute(\n `INSERT INTO search_history_v1 (user_id, query, media_type, results_count) VALUES (?, ?, ?, ?)`,\n [userId, query, mediaType, resultsCount]\n );\n}\n\nexport async function getUserSearchHistory(userId: number, limit: number = 10): Promise {\n const result = await sqlite.execute(\n `SELECT query, media_type, results_count, created_at \n FROM search_history_v1 \n WHERE user_id = ? \n ORDER BY created_at DESC \n LIMIT ?`,\n [userId, limit]\n );\n return result;\n}",[],[188,301,293],"database","630a8f06-3cba-11f0-bbbe-9e149126039e","migrations.ts","630a8fe2-3cba-11f0-bbbe-9e149126039e",["D",1748543167164],"import { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\n\n// Database schema definitions and migrations\n\nexport async function initializeDatabase() {\n // Users table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS users_v1 (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n email TEXT UNIQUE NOT NULL,\n username TEXT UNIQUE NOT NULL,\n password_hash TEXT NOT NULL,\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n updated_at DATETIME DEFAULT CURRENT_TIMESTAMP\n )\n `);\n\n // Media analyses table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS media_analyses_v1 (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n user_id INTEGER NOT NULL,\n media_type TEXT NOT NULL CHECK (media_type IN ('image', 'video', 'audio')),\n file_name TEXT NOT NULL,\n file_size INTEGER NOT NULL,\n blob_key TEXT NOT NULL,\n analysis_result TEXT NOT NULL,\n tags TEXT NOT NULL, -- JSON array of tags\n confidence_score REAL NOT NULL DEFAULT 0.0,\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n FOREIGN KEY (user_id) REFERENCES users_v1 (id) ON DELETE CASCADE\n )\n `);\n\n // User sessions table for JWT token management\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS user_sessions_v1 (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n user_id INTEGER NOT NULL,\n token_hash TEXT NOT NULL,\n expires_at DATETIME NOT NULL,\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n FOREIGN KEY (user_id) REFERENCES users_v1 (id) ON DELETE CASCADE\n )\n `);\n\n // Search history table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS search_history_v1 (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n user_id INTEGER NOT NULL,\n query TEXT NOT NULL,\n media_type TEXT,\n results_count INTEGER NOT NULL DEFAULT 0,\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n FOREIGN KEY (user_id) REFERENCES users_v1 (id) ON DELETE CASCADE\n )\n `);\n\n // Create indexes for better performance\n await sqlite.execute(`\n CREATE INDEX IF NOT EXISTS idx_media_analyses_user_id ON media_analyses_v1(user_id)\n `);\n \n await sqlite.execute(`\n CREATE INDEX IF NOT EXISTS idx_media_analyses_type ON media_analyses_v1(media_type)\n `);\n \n await sqlite.execute(`\n CREATE INDEX IF NOT EXISTS idx_media_analyses_created_at ON media_analyses_v1(created_at)\n `);\n \n await sqlite.execute(`\n CREATE INDEX IF NOT EXISTS idx_user_sessions_user_id ON user_sessions_v1(user_id)\n `);\n \n await sqlite.execute(`\n CREATE INDEX IF NOT EXISTS idx_user_sessions_expires_at ON user_sessions_v1(expires_at)\n `);\n\n console.log('Database initialized successfully');\n}\n\nexport async function cleanupExpiredSessions() {\n await sqlite.execute(`\n DELETE FROM user_sessions_v1 \n WHERE expires_at < datetime('now')\n `);\n}",[],[188,301,303],"630ab3dc-3cba-11f0-bbbe-9e149126039e",["D",1748543167164],[207,208],[188,301],"79666162-3cba-11f0-a622-9e149126039e","79666202-3cba-11f0-a622-9e149126039e","4a597fca-4fe3-4edc-9b5a-2d40ac8f5452",12,["D",1748543204677],"import { Context } from \"https://esm.sh/hono@3.11.7\";\nimport { sign, verify } from \"https://esm.sh/jsonwebtoken@9.0.2\";\nimport { hash, compare } from \"https://esm.sh/bcryptjs@2.4.3\";\nimport { getUserById, validateSession, createSession, deleteSession } from \"../database/queries.ts\";\nimport type { User } from \"../../shared/types.ts\";\n\nconst JWT_SECRET = Deno.env.get('JWT_SECRET') || 'your-secret-key-change-in-production';\nconst TOKEN_EXPIRY = '7d'; // 7 days\n\nexport async function hashPassword(password: string): Promise {\n return await hash(password, 12);\n}\n\nexport async function verifyPassword(password: string, hash: string): Promise {\n return await compare(password, hash);\n}\n\nexport function generateToken(userId: number): string {\n return sign({ userId }, JWT_SECRET, { expiresIn: TOKEN_EXPIRY });\n}\n\nexport async function verifyToken(token: string): Promise {\n try {\n const decoded = verify(token, JWT_SECRET) as { userId: number };\n return decoded.userId;\n } catch {\n return null;\n }\n}\n\nexport async function createUserSession(userId: number): Promise {\n const token = generateToken(userId);\n const tokenHash = await hash(token, 10);\n const expiresAt = new Date(Date.now() + 7 * 24 * 60 * 60 * 1000).toISOString(); // 7 days\n \n await createSession(userId, tokenHash, expiresAt);\n return token;\n}\n\nexport async function validateUserSession(token: string): Promise {\n const userId = await verifyToken(token);\n if (!userId) return null;\n \n const tokenHash = await hash(token, 10);\n const sessionUserId = await validateSession(tokenHash);\n \n if (!sessionUserId || sessionUserId !== userId) return null;\n \n return await getUserById(userId);\n}\n\nexport async function invalidateSession(token: string): Promise {\n const tokenHash = await hash(token, 10);\n await deleteSession(tokenHash);\n}\n\nexport function getTokenFromRequest(c: Context): string | null {\n const authHeader = c.req.header('Authorization');\n if (authHeader && authHeader.startsWith('Bearer ')) {\n return authHeader.substring(7);\n }\n \n // Also check cookies as fallback\n const cookieToken = c.req.header('Cookie')\n ?.split(';')\n .find(cookie => cookie.trim().startsWith('auth_token='))\n ?.split('=')[1];\n \n return cookieToken || null;\n}\n\nexport async function requireAuth(c: Context, next: () => Promise) {\n const token = getTokenFromRequest(c);\n \n if (!token) {\n return c.json({ success: false, message: 'Authentication required' }, 401);\n }\n \n const user = await validateUserSession(token);\n if (!user) {\n return c.json({ success: false, message: 'Invalid or expired token' }, 401);\n }\n \n // Add user to context\n c.set('user', user);\n await next();\n}\n\nexport function getCurrentUser(c: Context): User {\n return c.get('user');\n}",[],[188,321,243],"auth","796685e8-3cba-11f0-a622-9e149126039e",["D",1748543204677],[205],[188,321],["D",1748543167164],[204,206,209,212],[188],["D",1748542306097],{"_95":94,"_102":98},{"_95":94,"_96":-5,"_97":98,"_18":53,"_99":100,"_101":24},{"_13":84,"_31":85,"_42":41,"_86":43,"_87":-5,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":44,"_93":94},"ctx",{"_77":-5,"_122":366,"_367":368,"_369":370,"_371":24,"_372":24,"_373":24,"_374":57,"_375":-5,"_376":-7,"_377":-7,"_378":61,"_379":24,"_380":24,"_381":-5,"_382":24,"_383":24,"_384":24,"_385":-5},"ENV",{"_337":338,"_339":340,"_341":85,"_342":343,"_344":345,"_346":347,"_348":349,"_350":351,"_352":353,"_354":355,"_356":357,"_358":359,"_360":361,"_362":363,"_364":365},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","c73f21da490985bff19c279eb0e09db24d688e4f","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Diff · v15