\n 📧 Email Delivery Job Report\n

\n \n

📊 Job Status

Success: ${result.success ? '✅ Yes' : '❌ No'}
Summaries sent: ${result.sentCount}
Execution time: ${(executionTime / 1000).toFixed(2)}s
Error: ${result.error}

\n\n ${result.sentCount === 0 ? `\n

ℹ️ No New Summaries

There were no new summaries to send since the last email delivery.

This might be normal if:

No new Twitter data has been processed recently
No new summarizations have been generated
The email frequency is set too high

\n ` : ''}\n\n

Generated at ${new Date().toISOString()}

This is an automated report from your Email Delivery service.

To disable these notifications, set EMAIL_JOB_NOTIFICATIONS=false

\n `;\n\n const text = `\nEmail Delivery Job Report\n\nSuccess: ${result.success ? 'Yes' : 'No'}\nSummaries sent: ${result.sentCount}\nExecution time: ${(executionTime / 1000).toFixed(2)}s\n${result.error ? `Error: ${result.error}` : ''}\n\n${result.sentCount === 0 ? `\nNo new summaries were available to send.\nThis might be normal if no new content has been processed recently.\n` : ''}\n\nGenerated at ${new Date().toISOString()}\n `;\n\n await email({\n to: recipientEmail,\n subject,\n html,\n text,\n });\n}\n\n/**\n * Send error notification email\n */\nasync function sendJobErrorEmail(\n error: any,\n executionTime: number,\n recipientEmail: string,\n): Promise {\n const subject = \"OffX: Email Delivery Job Failed\";\n \n const html = `\n

❌ Email Delivery Job Failed

\n \n

Error Details

Error: ${error instanceof Error ? error.message : String(error) || error}

Execution time: ${(executionTime / 1000).toFixed(2)}s

Timestamp: ${new Date().toISOString()}

\n\n

Please check the logs for more details and consider investigating the issue.

Common causes might include:

Database connectivity issues
Email service problems
Configuration errors
Network failures

\n `;\n\n const text = `\nEmail Delivery Job Failed\n\nError: ${error instanceof Error ? error.message : String(error) || error}\nExecution time: ${(executionTime / 1000).toFixed(2)}s\nTimestamp: ${new Date().toISOString()}\n\nPlease check the logs for more details and consider investigating the issue.\n `;\n\n await email({\n to: recipientEmail,\n subject,\n html,\n text,\n });\n}",[],[153,297],{"_104":305,"_95":306,"_154":307,"_156":155,"_157":139,"_158":308,"_160":161,"_106":309,"_100":32,"_163":310,"_165":311,"_166":22,"_167":-5,"_168":312,"_98":313},"84350570-8a7c-11f0-b5d4-0224a6c84d84","email-delivery.ts","8435062e-8a7c-11f0-b5d4-0224a6c84d84",48,["D",1757092784657],"email","/**\n * Email delivery service for sending AI-generated summaries to users\n * Provides user-friendly summary emails with rich formatting\n */\n\nimport { email } from \"https://esm.town/v/std/email\";\nimport { getRecentSummarizations } from \"./database/queries.ts\";\nimport type { TopicSummary } from \"./twitter-summarization.ts\";\n\nexport interface EmailDeliveryOptions {\n recipientEmail: string;\n subject?: string;\n includeLastHours?: number;\n maxSummaries?: number;\n includeMetrics?: boolean;\n}\n\nexport interface EmailSummaryData {\n id: number;\n topicTitle: string;\n content: {\n summary: string;\n keyPoints: string[];\n sentiment: {\n sentiment: \"positive\" | \"negative\" | \"neutral\";\n confidence: number;\n score: number;\n };\n tweetCount: number;\n timeWindow: string;\n trendingKeywords: string[];\n influentialAuthors: string[];\n };\n created_at: string;\n time_period: string;\n}\n\n/**\n * Main email delivery service class\n */\nexport class EmailDeliveryService {\n \n /**\n * Send latest summaries via email\n */\n async sendLatestSummaries(options: EmailDeliveryOptions): Promise<{\n success: boolean;\n sentCount: number;\n error?: string;\n }> {\n try {\n const {\n recipientEmail,\n subject = \"Your Twitter Feed Summary\",\n maxSummaries = 10,\n includeMetrics = true,\n } = options;\n\n console.log(`📧 Preparing to send summary email to ${recipientEmail}`);\n\n // Fetch recent summaries from database\n const summaries = await this.fetchRecentSummaries(maxSummaries);\n \n if (summaries.length === 0) {\n console.log(\"📧 No recent summaries found, skipping email\");\n return { success: true, sentCount: 0 };\n }\n\n // Generate email content\n const emailContent = this.generateEmailTemplate(summaries, includeMetrics);\n const finalSubject = this.generateSubject(subject, summaries.length);\n\n // Send email with retry logic\n await this.sendEmailWithRetry({\n to: recipientEmail,\n subject: finalSubject,\n html: emailContent.html,\n text: emailContent.text,\n });\n\n console.log(`📧 Successfully sent summary email with ${summaries.length} summaries`);\n return { success: true, sentCount: summaries.length };\n\n } catch (error: unknown) {\n console.error(\"📧 Failed to send summary email:\", error);\n return { \n success: false, \n sentCount: 0, \n error: error instanceof Error ? error instanceof Error ? error.message : String(error) : String(error)\n };\n }\n }\n\n /**\n * Fetch recent summaries from database and format them\n */\n private async fetchRecentSummaries(limit: number): Promise {\n try {\n const rawSummaries = await getRecentSummarizations(limit);\n \n return rawSummaries.map(summary => ({\n id: summary.id!,\n topicTitle: (summary as any).topic_title || \"Unknown Topic\",\n content: JSON.parse(summary.content),\n created_at: summary.created_at!,\n time_period: `${summary.time_period_start} to ${summary.time_period_end}`,\n }));\n } catch (error: unknown) {\n console.error(\"Error fetching summaries:\", error);\n return [];\n }\n }\n\n /**\n * Generate email subject line\n */\n private generateSubject(baseSubject: string, summaryCount: number): string {\n const timeStr = new Date().toLocaleDateString();\n return `${baseSubject} - ${summaryCount} topics (${timeStr})`;\n }\n\n /**\n * Generate complete email template with HTML and text versions\n */\n private generateEmailTemplate(summaries: EmailSummaryData[], includeMetrics: boolean): {\n html: string;\n text: string;\n } {\n const html = this.generateHtmlTemplate(summaries, includeMetrics);\n const text = this.generateTextTemplate(summaries, includeMetrics);\n \n return { html, text };\n }\n\n /**\n * Generate HTML email template\n */\n private generateHtmlTemplate(summaries: EmailSummaryData[], includeMetrics: boolean): string {\n const summaryCards = summaries.map(summary => this.generateSummaryCard(summary)).join('\\n');\n \n const metricsSection = includeMetrics ? `\n

📊 Summary Metrics

Topics covered: ${summaries.length}
Total tweets analyzed: ${summaries.reduce((sum, s) => sum + s.content.tweetCount, 0)}
Sentiment breakdown: ${this.getSentimentBreakdown(summaries)}
Generated: ${new Date().toLocaleString()}

\n ` : '';\n\n return `\n \n \n \n \n \n Your Twitter Feed Summary\n \n \n \n

🐦 Your Twitter Feed Summary

AI-powered insights from your social media

\n\n ${metricsSection}\n\n

📝 Topic Summaries

\n ${summaryCards}\n

\n\n

\n Generated by OffX AI Summary Service
\n This email contains AI-generated content based on your Twitter feed\n

\n \n \n \n `;\n }\n\n /**\n * Generate individual summary card HTML\n */\n private generateSummaryCard(summary: EmailSummaryData): string {\n const sentimentColor = {\n positive: '#28a745',\n negative: '#dc3545',\n neutral: '#6c757d'\n }[summary.content.sentiment.sentiment];\n\n const keyPointsList = summary.content.keyPoints\n .map(point => `

${point}

`)\n .join('');\n\n const keywords = summary.content.trendingKeywords.length > 0 \n ? summary.content.trendingKeywords.slice(0, 5).map(kw => \n `${kw}`\n ).join('')\n : 'No keywords identified';\n\n return `\n

\n \n

📌 ${summary.topicTitle}

🗣️ ${summary.content.tweetCount} tweets

\n ${summary.content.sentiment.sentiment.toUpperCase()}\n

\n\n

\n ${summary.content.summary}\n

\n\n ${summary.content.keyPoints.length > 0 ? `\n

🔑 Key Points:

\n ${keyPointsList}\n \n

\n ` : ''}\n\n

🏷️ Trending Keywords:

${keywords}

\n\n ${summary.content.influentialAuthors.length > 0 ? `\n

\n Notable voices: ${summary.content.influentialAuthors.slice(0, 3).join(', ')}\n

\n ` : ''}\n\n

\n Generated ${new Date(summary.created_at).toLocaleString()} • Time window: ${summary.time_period}\n

\n \n

\n `;\n }\n\n /**\n * Generate plain text email template\n */\n private generateTextTemplate(summaries: EmailSummaryData[], includeMetrics: boolean): string {\n const header = `\n🐦 YOUR TWITTER FEED SUMMARY\nAI-powered insights from your social media\n\n${new Date().toLocaleDateString()}\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n`;\n\n const metricsSection = includeMetrics ? `\n📊 SUMMARY METRICS\n• Topics covered: ${summaries.length}\n• Total tweets analyzed: ${summaries.reduce((sum, s) => sum + s.content.tweetCount, 0)}\n• Sentiment breakdown: ${this.getSentimentBreakdown(summaries)}\n• Generated: ${new Date().toLocaleString()}\n\n` : '';\n\n const summaryTexts = summaries.map(summary => `\n📌 ${summary.topicTitle.toUpperCase()}\n🗣️ ${summary.content.tweetCount} tweets • Sentiment: ${summary.content.sentiment.sentiment.toUpperCase()}\n\n${summary.content.summary}\n\n🔑 Key Points:\n${summary.content.keyPoints.map(point => `• ${point}`).join('\\n')}\n\n🏷️ Keywords: ${summary.content.trendingKeywords.slice(0, 5).join(', ') || 'None'}\n\n${summary.content.influentialAuthors.length > 0 ? `Notable voices: ${summary.content.influentialAuthors.slice(0, 3).join(', ')}` : ''}\n\nGenerated: ${new Date(summary.created_at).toLocaleString()} • Time window: ${summary.time_period}\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n`).join('\\n');\n\n const footer = `\nGenerated by OffX AI Summary Service\nThis email contains AI-generated content based on your Twitter feed\n`;\n\n return header + metricsSection + summaryTexts + footer;\n }\n\n /**\n * Get sentiment breakdown statistics\n */\n private getSentimentBreakdown(summaries: EmailSummaryData[]): string {\n const counts = summaries.reduce((acc, s) => {\n acc[s.content.sentiment.sentiment] = (acc[s.content.sentiment.sentiment] || 0) + 1;\n return acc;\n }, {} as Record);\n\n return Object.entries(counts)\n .map(([sentiment, count]) => `${count} ${sentiment}`)\n .join(', ');\n }\n\n /**\n * Send email with retry logic\n */\n private async sendEmailWithRetry(emailData: {\n to: string;\n subject: string;\n html: string;\n text: string;\n }, maxRetries: number = 3): Promise {\n let lastError: Error | null = null;\n\n for (let attempt = 1; attempt <= maxRetries; attempt++) {\n try {\n console.log(`📧 Sending email attempt ${attempt}/${maxRetries} to ${emailData.to}`);\n \n await email({\n to: emailData.to,\n subject: emailData.subject,\n html: emailData.html,\n text: emailData.text,\n });\n\n console.log(`📧 Email sent successfully on attempt ${attempt}`);\n return; // Success!\n\n } catch (error: unknown) {\n lastError = error instanceof Error ? error : new Error(String(error));\n console.warn(`📧 Email attempt ${attempt} failed:`, lastError.message);\n \n if (attempt < maxRetries) {\n // Wait before retrying (exponential backoff)\n const delay = Math.pow(2, attempt) * 1000; // 2s, 4s, 8s\n console.log(`📧 Retrying in ${delay}ms...`);\n await new Promise(resolve => setTimeout(resolve, delay));\n }\n }\n }\n\n // All attempts failed\n throw new Error(`Failed to send email after ${maxRetries} attempts. Last error: ${lastError?.message}`);\n }\n}",[],[153,306],{"_104":315,"_95":199,"_154":316,"_156":155,"_157":139,"_158":317,"_160":22,"_106":318,"_100":319,"_163":320,"_165":321,"_166":22,"_167":-5,"_168":322,"_98":323},"e7bb6cc6-56bd-11f0-ad3b-f69ea79377d9","26935614-55f3-11f0-ab57-f69ea79377d9",32,["D",1751403408491],10,"http","import { Hono } from \"https://esm.sh/hono@4.8.3\";\nimport { basicAuth } from \"https://esm.sh/hono@4.8.3/basic-auth\";\nimport { readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n\nconst app = new Hono();\n\n// Unwrap Hono errors to see original error details\napp.onError((err, c) => {\n throw err;\n});\n\n// Basic authentication middleware\nconst auth = basicAuth({\n username: Deno.env.get(\"AUTH_USERNAME\") || \"admin\",\n password: Deno.env.get(\"AUTH_PASSWORD\") || \"password\",\n // This is just a placeholder - in production, always use environment variables\n});\n\n// Public routes\napp.get(\"/api/health\", (c) => {\n return c.json({ status: \"ok\", timestamp: new Date().toISOString() });\n});\n\n// Login route that returns success message on correct credentials\napp.get(\"/api/login\", auth, (c) => {\n return c.json({\n success: true,\n message: \"Authentication successful\",\n user: c.req.header(\"Authorization\")?.split(\" \")[1]?.split(\":\")[0]\n || \"user\",\n });\n});\n\n// Protected API routes\napp.get(\"/api/dashboard\", auth, (c) => {\n return c.json({\n message: \"Protected dashboard data\",\n data: {\n summaries: [],\n topics: [],\n },\n });\n});\n\n// Serve static files\napp.get(\"/frontend/*\", (c) => serveFile(c.req.path, import.meta.url));\napp.get(\"/shared/*\", (c) => serveFile(c.req.path, import.meta.url));\n\n// For SPA routing, serve index.html for all other routes\napp.get(\"*\", async (c) => {\n try {\n // Try to serve the requested file first\n return await serveFile(c.req.path, import.meta.url);\n } catch {\n // If file not found, serve the index.html for client-side routing\n const html = await readFile(\"/frontend/index.html\", import.meta.url);\n return c.html(html);\n }\n});\n\n// Export the fetch handler for HTTP vals\nexport default app.fetch;",[],[153,199],{"_104":325,"_95":326,"_154":327,"_156":155,"_157":139,"_158":328,"_160":161,"_106":329,"_100":32,"_163":320,"_165":330,"_166":22,"_167":-5,"_168":331,"_98":332},"841d63de-8a7c-11f0-abb7-0224a6c84d84","topic-api-test.http.ts","841d64b0-8a7c-11f0-abb7-0224a6c84d84",44,["D",1757092784549],"/**\n * Topic Management API Test Endpoints\n * This file provides HTTP endpoints to test the Topic Management API functionality\n */\nexport default async function (req: Request): Promise {\n // Check for basic auth\n const authHeader = req.headers.get(\"Authorization\");\n if (!authHeader || !authHeader.startsWith(\"Basic \")) {\n return new Response(\"Unauthorized\", {\n status: 401,\n headers: { \"WWW-Authenticate\": \"Basic\" },\n });\n }\n\n const base64Credentials = authHeader.split(\" \")[1];\n const credentials = atob(base64Credentials);\n const [username, password] = credentials.split(\":\");\n\n // Simple hard-coded auth for testing\n const validUsername = Deno.env.get(\"AUTH_USERNAME\") || \"admin\";\n const validPassword = Deno.env.get(\"AUTH_PASSWORD\") || \"password\";\n\n if (username !== validUsername || password !== validPassword) {\n return new Response(\"Unauthorized\", {\n status: 401,\n headers: { \"WWW-Authenticate\": \"Basic\" },\n });\n }\n\n // Parse URL to get action\n const url = new URL(req.url);\n const action = url.searchParams.get(\"action\") || \"help\";\n\n // Import necessary modules\n const { initializeDatabase } = await import(\"./database/migrations.ts\");\n const {\n createTopic,\n getAllTopics,\n getTopicById,\n updateTopic,\n deleteTopic,\n } = await import(\"./database/queries.ts\");\n\n // Initialize database\n await initializeDatabase();\n\n // Process actions\n switch (action) {\n case \"list\":\n // List all topics\n const topics = await getAllTopics();\n return new Response(\n JSON.stringify({ action: \"list\", topics }, null, 2),\n {\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n\n case \"get\":\n // Get a specific topic\n const id = parseInt(url.searchParams.get(\"id\") || \"0\");\n if (isNaN(id) || id <= 0) {\n return new Response(\n JSON.stringify({ error: \"Invalid topic ID\" }, null, 2),\n {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n const topic = await getTopicById(id);\n if (!topic) {\n return new Response(\n JSON.stringify({ error: \"Topic not found\" }, null, 2),\n {\n status: 404,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n return new Response(\n JSON.stringify({ action: \"get\", topic }, null, 2),\n {\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n\n case \"create\":\n // Create a new topic\n const title = url.searchParams.get(\"title\");\n const description = url.searchParams.get(\"description\");\n\n if (!title) {\n return new Response(\n JSON.stringify({ error: \"Title is required\" }, null, 2),\n {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n const newTopicId = await createTopic({\n title,\n description: description || undefined,\n });\n\n const newTopic = await getTopicById(newTopicId);\n return new Response(\n JSON.stringify({ action: \"create\", topic: newTopic }, null, 2),\n {\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n\n case \"update\":\n // Update a topic\n const updateId = parseInt(url.searchParams.get(\"id\") || \"0\");\n const updateTitle = url.searchParams.get(\"title\");\n const updateDescription = url.searchParams.get(\"description\");\n\n if (isNaN(updateId) || updateId <= 0) {\n return new Response(\n JSON.stringify({ error: \"Invalid topic ID\" }, null, 2),\n {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n if (!updateTitle && updateDescription === null) {\n return new Response(\n JSON.stringify(\n { error: \"At least one field must be provided for update\" },\n null,\n 2,\n ),\n {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n // Check if topic exists\n const existingTopic = await getTopicById(updateId);\n if (!existingTopic) {\n return new Response(\n JSON.stringify({ error: \"Topic not found\" }, null, 2),\n {\n status: 404,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n // Update the topic\n await updateTopic({\n id: updateId,\n title: updateTitle || existingTopic.title,\n description: updateDescription !== null\n ? updateDescription\n : existingTopic.description,\n });\n\n const updatedTopic = await getTopicById(updateId);\n return new Response(\n JSON.stringify({ action: \"update\", topic: updatedTopic }, null, 2),\n {\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n\n case \"delete\":\n // Delete a topic\n const deleteId = parseInt(url.searchParams.get(\"id\") || \"0\");\n\n if (isNaN(deleteId) || deleteId <= 0) {\n return new Response(\n JSON.stringify({ error: \"Invalid topic ID\" }, null, 2),\n {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n // Check if topic exists\n const topicToDelete = await getTopicById(deleteId);\n if (!topicToDelete) {\n return new Response(\n JSON.stringify({ error: \"Topic not found\" }, null, 2),\n {\n status: 404,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n // Delete the topic\n await deleteTopic(deleteId);\n return new Response(\n JSON.stringify(\n {\n action: \"delete\",\n message: \"Topic deleted successfully\",\n topicId: deleteId,\n },\n null,\n 2,\n ),\n {\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n\n case \"help\":\n default:\n // Show help information\n return new Response(\n JSON.stringify(\n {\n message: \"Topic Management API Test\",\n availableActions: {\n list: \"List all topics - ?action=list\",\n get: \"Get a specific topic - ?action=get&id=1\",\n create:\n \"Create a new topic - ?action=create&title=NewTopic&description=Description\",\n update:\n \"Update a topic - ?action=update&id=1&title=UpdatedTitle&description=UpdatedDescription\",\n delete: \"Delete a topic - ?action=delete&id=1\",\n },\n examples: {\n list: \"/api/topic-test?action=list\",\n get: \"/api/topic-test?action=get&id=1\",\n create:\n \"/api/topic-test?action=create&title=Tech News&description=Latest tech updates\",\n update:\n \"/api/topic-test?action=update&id=1&title=Updated Tech News\",\n delete: \"/api/topic-test?action=delete&id=1\",\n },\n },\n null,\n 2,\n ),\n {\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n}\n",[],[153,326],{"_104":334,"_95":335,"_154":336,"_156":155,"_157":139,"_158":337,"_160":22,"_106":338,"_100":32,"_163":193,"_165":339,"_166":22,"_167":-5,"_168":340,"_98":341},"84a0b0b8-8a7c-11f0-a12e-0224a6c84d84","twitter-api.ts","84a0b14e-8a7c-11f0-a12e-0224a6c84d84",64,["D",1757092785399],"import { TwitterApi } from \"https://esm.sh/twitter-api-v2\";\nimport {\n createPost,\n getPostByExternalId,\n Post,\n PostMedia,\n} from \"./database/queries.ts\";\nimport { ExtendedPostMedia, TwitterMediaExtractor } from \"./twitter-media.ts\";\nimport {\n loadRetryConfigFromEnv,\n RetryConfig,\n TwitterError,\n TwitterErrorType,\n withRetry,\n} from \"./twitter-error-handler.ts\";\n\n/**\n * Twitter API client configuration and initialization\n */\nexport class TwitterClient {\n private client: TwitterApi;\n private retryConfig: RetryConfig;\n\n constructor(bearerToken: string, retryConfig?: RetryConfig) {\n if (!bearerToken) {\n throw new Error(\"Twitter bearer token is required\");\n }\n this.client = new TwitterApi(bearerToken);\n this.retryConfig = retryConfig || loadRetryConfigFromEnv();\n }\n\n /**\n * Fetches the latest tweets from the user's home timeline\n * @param maxResults Maximum number of tweets to fetch (default: 100)\n * @returns Array of processed tweets\n */\n async fetchHomeTimeline(maxResults: number = 100): Promise {\n const retryResult = await withRetry(\n async () => {\n const homeTimeline = await this.client.v2.homeTimeline({\n max_results: maxResults,\n \"tweet.fields\": [\n \"created_at\",\n \"author_id\",\n \"text\",\n \"attachments\",\n \"entities\",\n ],\n \"user.fields\": [\"name\", \"username\"],\n \"media.fields\": [\n \"url\",\n \"preview_image_url\",\n \"type\",\n \"alt_text\",\n \"width\",\n \"height\",\n \"duration_ms\",\n \"variants\",\n ],\n expansions: [\n \"author_id\",\n \"attachments.media_keys\",\n \"entities.mentions.username\",\n ],\n });\n\n // Process and return the tweets\n return this.processTweets(homeTimeline.data);\n },\n this.retryConfig,\n );\n\n if (!retryResult.success) {\n // Log detailed information about the failure\n console.error(\n \"Failed to fetch Twitter timeline after multiple attempts:\",\n {\n attempts: retryResult.attempts,\n totalRetryTimeMs: retryResult.totalRetryTimeMs,\n maxRetriesReached: retryResult.maxRetriesReached,\n error: retryResult.error,\n },\n );\n\n // Convert to TwitterError for consistent error handling\n const twitterError = TwitterError.fromError(\n retryResult.error || new Error(\"Unknown error\"),\n );\n\n // Throw the error with additional context\n throw new TwitterError(\n `Failed to fetch Twitter timeline after ${retryResult.attempts} attempts: ${twitterError.message}`,\n twitterError.type,\n twitterError.statusCode,\n twitterError,\n );\n }\n\n return retryResult.result || [];\n }\n\n /**\n * Process raw Twitter API response into our database format\n * @param timelineData Twitter API response data\n * @returns Array of processed Post objects ready for database storage\n */\n private processTweets(timelineData: any): Post[] {\n const tweets: Post[] = [];\n\n if (\n !timelineData || !timelineData.data || !Array.isArray(timelineData.data)\n ) {\n console.warn(\"No tweets found in the Twitter API response\");\n return [];\n }\n\n // Process each tweet\n for (const tweet of timelineData.data) {\n try {\n // Find the author in the includes.users array\n const author = timelineData.includes?.users?.find(\n (user: any) => user.id === tweet.author_id,\n );\n\n if (!author) {\n console.warn(`Author not found for tweet ${tweet.id}`);\n continue;\n }\n\n // Extract media using the specialized extractor\n const media: ExtendedPostMedia[] = TwitterMediaExtractor\n .extractMediaFromResponse(\n timelineData,\n tweet.id,\n );\n\n // Process the extracted media\n const processedMedia = TwitterMediaExtractor.processMedia(media);\n\n // Create post object\n const post: Post = {\n external_id: tweet.id,\n content: tweet.text,\n author: author.name,\n author_username: author.username,\n platform: \"twitter\",\n created_at: tweet.created_at || new Date().toISOString(),\n url: `https://twitter.com/${author.username}/status/${tweet.id}`,\n media: processedMedia,\n };\n\n tweets.push(post);\n } catch (error: unknown) {\n // Log error but continue processing other tweets\n console.error(`Error processing tweet ${tweet.id}:`, error);\n }\n }\n\n return tweets;\n }\n}\n\n/**\n * Initialize Twitter API client with bearer token from environment\n * @returns Configured TwitterClient instance\n */\nexport function initializeTwitterClient(): TwitterClient {\n const bearerToken = Deno.env.get(\"TWITTER_BEARER_TOKEN\");\n\n if (!bearerToken) {\n throw new Error(\"TWITTER_BEARER_TOKEN environment variable is not set\");\n }\n\n return new TwitterClient(bearerToken);\n}\n\n/**\n * Store tweets in the database with deduplication\n * @param tweets Array of processed tweets\n * @returns Number of new tweets stored\n */\nexport async function storeTweets(tweets: Post[]): Promise {\n let newTweetsCount = 0;\n let failedTweets = 0;\n\n for (const tweet of tweets) {\n try {\n // Use retry mechanism for database operations as well\n const retryResult = await withRetry(async () => {\n // Check if the tweet already exists in the database\n const existingTweet = await getPostByExternalId(tweet.external_id);\n\n if (!existingTweet) {\n // Store the new tweet\n const postId = await createPost(tweet);\n\n // If the tweet has media, ensure it's properly stored with the enhanced metadata\n if (tweet.media && tweet.media.length > 0) {\n await TwitterMediaExtractor.storePostMedia(\n postId,\n tweet.media as ExtendedPostMedia[],\n );\n }\n\n return true; // New tweet stored\n }\n\n return false; // Tweet already exists\n });\n\n if (retryResult.success && retryResult.result) {\n newTweetsCount++;\n }\n } catch (error: unknown) {\n failedTweets++;\n console.error(`Failed to store tweet ${tweet.external_id}:`, error);\n }\n }\n\n // Log summary\n if (failedTweets > 0) {\n console.warn(\n `Failed to store ${failedTweets} tweets out of ${tweets.length}`,\n );\n }\n\n return newTweetsCount;\n}\n",[],[153,335],{"_104":343,"_95":344,"_154":345,"_156":155,"_157":139,"_158":346,"_160":161,"_106":347,"_100":32,"_163":193,"_165":348,"_166":22,"_167":-5,"_168":349,"_98":350},"8472e6a6-8a7c-11f0-9dec-0224a6c84d84","twitter-error-handler.ts","8472e76e-8a7c-11f0-9dec-0224a6c84d84",57,["D",1757092785078],"/**\n * Error handling and retry mechanisms for Twitter API requests\n * Provides utilities for handling rate limits, network failures, and transient errors\n */\n\n/**\n * Configuration options for retry mechanisms\n */\nexport interface RetryConfig {\n /** Maximum number of retry attempts */\n maxRetries: number;\n /** Initial delay in milliseconds before the first retry */\n initialDelayMs: number;\n /** Maximum delay in milliseconds between retries */\n maxDelayMs: number;\n /** Multiplier for exponential backoff */\n backoffMultiplier: number;\n /** Jitter factor to add randomness to retry delays (0-1) */\n jitterFactor: number;\n /** HTTP status codes that should trigger a retry */\n retryableStatusCodes: number[];\n /** Error types that should trigger a retry */\n retryableErrors: string[];\n}\n\n/**\n * Default retry configuration\n */\nexport const DEFAULT_RETRY_CONFIG: RetryConfig = {\n maxRetries: 3,\n initialDelayMs: 1000, // 1 second\n maxDelayMs: 60000, // 60 seconds\n backoffMultiplier: 2,\n jitterFactor: 0.2,\n retryableStatusCodes: [\n 408, // Request Timeout\n 429, // Too Many Requests (rate limit)\n 500, // Internal Server Error\n 502, // Bad Gateway\n 503, // Service Unavailable\n 504, // Gateway Timeout\n ],\n retryableErrors: [\n \"ECONNRESET\",\n \"ETIMEDOUT\",\n \"ECONNREFUSED\",\n \"EPIPE\",\n \"EHOSTUNREACH\",\n \"ENETUNREACH\",\n \"ENOTFOUND\",\n \"socket hang up\",\n \"network error\",\n ],\n};\n\n/**\n * Result of a retry operation\n */\nexport interface RetryResult {\n /** Whether the operation was successful */\n success: boolean;\n /** The result of the operation if successful */\n result?: T;\n /** Error that occurred if the operation failed */\n error?: Error;\n /** Number of retry attempts made */\n attempts: number;\n /** Total time spent in retries (ms) */\n totalRetryTimeMs: number;\n /** Whether the operation reached the maximum number of retries */\n maxRetriesReached: boolean;\n}\n\n/**\n * Twitter API specific error types\n */\nexport enum TwitterErrorType {\n RateLimit = \"rate_limit\",\n Authentication = \"authentication\",\n Authorization = \"authorization\",\n NotFound = \"not_found\",\n InvalidRequest = \"invalid_request\",\n ServerError = \"server_error\",\n NetworkError = \"network_error\",\n Unknown = \"unknown\",\n}\n\n/**\n * Twitter API error with additional context\n */\nexport class TwitterError extends Error {\n /** Type of Twitter error */\n type: TwitterErrorType;\n /** HTTP status code if available */\n statusCode?: number;\n /** Rate limit reset time if applicable */\n rateLimitReset?: Date;\n /** Whether this error is retryable */\n isRetryable: boolean;\n /** Original error that caused this error */\n originalError?: Error;\n\n constructor(\n message: string,\n type: TwitterErrorType = TwitterErrorType.Unknown,\n statusCode?: number,\n originalError?: Error,\n ) {\n super(message);\n this.name = \"TwitterError\";\n this.type = type;\n this.statusCode = statusCode;\n this.originalError = originalError;\n\n // Determine if error is retryable\n this.isRetryable = this.determineIfRetryable();\n }\n\n /**\n * Determine if this error should be retried\n */\n private determineIfRetryable(): boolean {\n // Rate limits are always retryable\n if (this.type === TwitterErrorType.RateLimit) {\n return true;\n }\n\n // Server errors are retryable\n if (this.type === TwitterErrorType.ServerError) {\n return true;\n }\n\n // Network errors are retryable\n if (this.type === TwitterErrorType.NetworkError) {\n return true;\n }\n\n // Authentication and authorization errors are not retryable\n if (\n this.type === TwitterErrorType.Authentication ||\n this.type === TwitterErrorType.Authorization\n ) {\n return false;\n }\n\n // Check status code if available\n if (this.statusCode) {\n return DEFAULT_RETRY_CONFIG.retryableStatusCodes.includes(\n this.statusCode,\n );\n }\n\n return false;\n }\n\n /**\n * Create a TwitterError from an HTTP response\n */\n static fromResponse(response: Response, originalError?: Error): TwitterError {\n const statusCode = response.status;\n let type = TwitterErrorType.Unknown;\n let message = `Twitter API error: ${response.statusText}`;\n\n // Determine error type based on status code\n if (statusCode === 401) {\n type = TwitterErrorType.Authentication;\n message = \"Twitter API authentication failed\";\n } else if (statusCode === 403) {\n type = TwitterErrorType.Authorization;\n message = \"Not authorized to perform this action\";\n } else if (statusCode === 404) {\n type = TwitterErrorType.NotFound;\n message = \"Requested resource not found\";\n } else if (statusCode === 429) {\n type = TwitterErrorType.RateLimit;\n message = \"Twitter API rate limit exceeded\";\n\n // Parse rate limit reset time if available\n const resetHeader = response.headers.get(\"x-rate-limit-reset\");\n if (resetHeader) {\n const resetTime = parseInt(resetHeader, 10) * 1000; // Convert to milliseconds\n const error = new TwitterError(\n message,\n type,\n statusCode,\n originalError,\n );\n error.rateLimitReset = new Date(resetTime);\n return error;\n }\n } else if (statusCode >= 400 && statusCode < 500) {\n type = TwitterErrorType.InvalidRequest;\n } else if (statusCode >= 500) {\n type = TwitterErrorType.ServerError;\n }\n\n return new TwitterError(message, type, statusCode, originalError);\n }\n\n /**\n * Create a TwitterError from any error\n */\n static fromError(error: Error): TwitterError {\n // Check if it's already a TwitterError\n if (error instanceof TwitterError) {\n return error;\n }\n\n // Check for network errors\n const networkErrorPatterns = DEFAULT_RETRY_CONFIG.retryableErrors;\n const isNetworkError = networkErrorPatterns.some((pattern) => {\n const errorString = error instanceof Error\n ? error.message\n : String(error);\n const errorName = error instanceof Error ? error.name : \"\";\n return errorString.includes(pattern) || errorName.includes(pattern);\n });\n\n if (isNetworkError) {\n return new TwitterError(\n `Network error: ${\n error instanceof Error ? error.message : String(error)\n }`,\n TwitterErrorType.NetworkError,\n undefined,\n error,\n );\n }\n\n // Default to unknown error\n return new TwitterError(\n `Twitter API error: ${\n error instanceof Error ? error.message : String(error)\n }`,\n TwitterErrorType.Unknown,\n undefined,\n error,\n );\n }\n}\n\n/**\n * Calculate delay for the next retry attempt using exponential backoff with jitter\n */\nexport function calculateRetryDelay(\n attempt: number,\n config: RetryConfig = DEFAULT_RETRY_CONFIG,\n): number {\n // Base delay with exponential backoff\n const baseDelay = Math.min(\n config.initialDelayMs * Math.pow(config.backoffMultiplier, attempt),\n config.maxDelayMs,\n );\n\n // Add jitter to prevent thundering herd problem\n const jitterRange = baseDelay * config.jitterFactor;\n const jitter = Math.random() * jitterRange - (jitterRange / 2);\n\n return Math.max(0, Math.floor(baseDelay + jitter));\n}\n\n/**\n * Execute a function with retry logic\n * @param operation Function to execute with retry logic\n * @param config Retry configuration\n * @returns Result of the operation with retry metadata\n */\nexport async function withRetry(\n operation: () => Promise,\n config: RetryConfig = DEFAULT_RETRY_CONFIG,\n): Promise> {\n let attempts = 0;\n let lastError: Error | undefined;\n const startTime = Date.now();\n\n while (attempts <= config.maxRetries) {\n try {\n // Attempt the operation\n const result = await operation();\n\n // Operation succeeded\n return {\n success: true,\n result,\n attempts,\n totalRetryTimeMs: Date.now() - startTime,\n maxRetriesReached: false,\n };\n } catch (error: unknown) {\n attempts++;\n lastError = error instanceof Error ? error : new Error(String(error));\n\n // Convert to TwitterError for better handling\n const twitterError = TwitterError.fromError(lastError);\n\n // Log the error\n console.error(\n `Twitter API error (attempt ${attempts}/${config.maxRetries + 1}):`,\n twitterError,\n );\n\n // Check if we should retry\n const shouldRetry = attempts <= config.maxRetries &&\n twitterError.isRetryable;\n\n if (!shouldRetry) {\n break;\n }\n\n // Calculate delay for next retry\n const delay = calculateRetryDelay(attempts - 1, config);\n\n // Special handling for rate limit errors with reset time\n if (\n twitterError.type === TwitterErrorType.RateLimit &&\n twitterError.rateLimitReset\n ) {\n const resetTime = twitterError.rateLimitReset.getTime();\n const now = Date.now();\n const timeToReset = Math.max(0, resetTime - now);\n\n // Use the rate limit reset time if it's sooner than our calculated delay\n if (timeToReset > 0 && timeToReset < delay) {\n console.log(\n `Rate limit exceeded. Waiting for reset in ${timeToReset}ms`,\n );\n await new Promise((resolve) =>\n setTimeout(resolve, timeToReset + 1000)\n ); // Add 1 second buffer\n continue;\n }\n }\n\n // Wait before retrying\n console.log(`Retrying in ${delay}ms...`);\n await new Promise((resolve) => setTimeout(resolve, delay));\n }\n }\n\n // All retries failed\n return {\n success: false,\n error: lastError,\n attempts,\n totalRetryTimeMs: Date.now() - startTime,\n maxRetriesReached: attempts > config.maxRetries,\n };\n}\n\n/**\n * Load retry configuration from environment variables\n */\nexport function loadRetryConfigFromEnv(): RetryConfig {\n const config = { ...DEFAULT_RETRY_CONFIG };\n\n const maxRetries = Deno.env.get(\"TWITTER_MAX_RETRIES\");\n if (maxRetries) {\n config.maxRetries = parseInt(maxRetries, 10);\n }\n\n const initialDelay = Deno.env.get(\"TWITTER_INITIAL_DELAY_MS\");\n if (initialDelay) {\n config.initialDelayMs = parseInt(initialDelay, 10);\n }\n\n const maxDelay = Deno.env.get(\"TWITTER_MAX_DELAY_MS\");\n if (maxDelay) {\n config.maxDelayMs = parseInt(maxDelay, 10);\n }\n\n const backoffMultiplier = Deno.env.get(\"TWITTER_BACKOFF_MULTIPLIER\");\n if (backoffMultiplier) {\n config.backoffMultiplier = parseFloat(backoffMultiplier);\n }\n\n const jitterFactor = Deno.env.get(\"TWITTER_JITTER_FACTOR\");\n if (jitterFactor) {\n config.jitterFactor = parseFloat(jitterFactor);\n }\n\n return config;\n}\n",[],[153,344],{"_104":352,"_95":353,"_154":354,"_156":155,"_157":139,"_158":355,"_160":161,"_106":356,"_100":32,"_163":320,"_165":357,"_166":22,"_167":-5,"_168":358,"_98":359},"842891a0-8a7c-11f0-af15-0224a6c84d84","twitter-error-test.http.ts","84289240-8a7c-11f0-af15-0224a6c84d84",46,["D",1757092784592],"import { initializeTwitterClient } from \"./twitter-api.ts\";\nimport { initializeDatabase } from \"./database/migrations.ts\";\nimport {\n DEFAULT_RETRY_CONFIG,\n RetryConfig,\n TwitterError,\n TwitterErrorType,\n withRetry,\n} from \"./twitter-error-handler.ts\";\n\n/**\n * HTTP endpoint to test Twitter error handling and retry mechanisms\n * This endpoint allows testing and validation of the error handling features\n */\nexport default async function (req: Request): Promise {\n // Check for basic auth\n const authHeader = req.headers.get(\"Authorization\");\n if (!authHeader || !authHeader.startsWith(\"Basic \")) {\n return new Response(\"Unauthorized\", {\n status: 401,\n headers: { \"WWW-Authenticate\": \"Basic\" },\n });\n }\n\n const base64Credentials = authHeader.split(\" \")[1];\n const credentials = atob(base64Credentials);\n const [username, password] = credentials.split(\":\");\n\n const expectedUsername = Deno.env.get(\"AUTH_USERNAME\");\n const expectedPassword = Deno.env.get(\"AUTH_PASSWORD\");\n\n if (username !== expectedUsername || password !== expectedPassword) {\n return new Response(\"Unauthorized\", {\n status: 401,\n headers: { \"WWW-Authenticate\": \"Basic\" },\n });\n }\n\n // Process the request\n try {\n const url = new URL(req.url);\n const action = url.searchParams.get(\"action\") || \"status\";\n\n // Initialize database\n await initializeDatabase();\n\n let responseData: any = {\n status: \"ok\",\n timestamp: new Date().toISOString(),\n };\n\n if (action === \"test-retry\") {\n // Get retry configuration from query params or use defaults\n const maxRetries = parseInt(\n url.searchParams.get(\"max_retries\") || \"3\",\n 10,\n );\n const initialDelayMs = parseInt(\n url.searchParams.get(\"initial_delay\") || \"1000\",\n 10,\n );\n const maxDelayMs = parseInt(\n url.searchParams.get(\"max_delay\") || \"60000\",\n 10,\n );\n const backoffMultiplier = parseFloat(\n url.searchParams.get(\"backoff\") || \"2\",\n );\n const jitterFactor = parseFloat(url.searchParams.get(\"jitter\") || \"0.2\");\n\n // Create custom retry config for testing\n const retryConfig: RetryConfig = {\n ...DEFAULT_RETRY_CONFIG,\n maxRetries,\n initialDelayMs,\n maxDelayMs,\n backoffMultiplier,\n jitterFactor,\n };\n\n // Simulate a function that fails a certain number of times before succeeding\n const failCount = parseInt(url.searchParams.get(\"fail_count\") || \"2\", 10);\n let attemptCount = 0;\n\n const retryResult = await withRetry(async () => {\n attemptCount++;\n console.log(\n `Retry test attempt ${attemptCount} of ${failCount + 1} needed`,\n );\n\n if (attemptCount <= failCount) {\n throw new Error(`Simulated failure on attempt ${attemptCount}`);\n }\n\n return {\n message: \"Operation succeeded after retries\",\n attemptCount,\n };\n }, retryConfig);\n\n responseData = {\n ...responseData,\n action: \"test-retry\",\n retryConfig,\n retryResult,\n };\n } else if (action === \"test-error-types\") {\n // Test different error types\n const errorType = url.searchParams.get(\"type\") || \"rate_limit\";\n let error: TwitterError;\n\n switch (errorType) {\n case \"rate_limit\":\n error = new TwitterError(\n \"Twitter API rate limit exceeded\",\n TwitterErrorType.RateLimit,\n 429,\n );\n // Set rate limit reset time to 30 seconds from now\n error.rateLimitReset = new Date(Date.now() + 30000);\n break;\n\n case \"authentication\":\n error = new TwitterError(\n \"Twitter API authentication failed\",\n TwitterErrorType.Authentication,\n 401,\n );\n break;\n\n case \"server_error\":\n error = new TwitterError(\n \"Twitter server error\",\n TwitterErrorType.ServerError,\n 500,\n );\n break;\n\n case \"network_error\":\n error = new TwitterError(\n \"Network connection failed\",\n TwitterErrorType.NetworkError,\n );\n break;\n\n default:\n error = new TwitterError(\n \"Unknown error type\",\n TwitterErrorType.Unknown,\n );\n }\n\n responseData = {\n ...responseData,\n action: \"test-error-types\",\n errorType,\n error: {\n message: error instanceof Error ? error.message : String(error),\n type: error.type,\n statusCode: error.statusCode,\n isRetryable: error.isRetryable,\n rateLimitReset: error.rateLimitReset,\n },\n };\n } else if (action === \"test-live-retry\") {\n // Test retry mechanism with actual Twitter API\n // Get custom retry config\n const maxRetries = parseInt(\n url.searchParams.get(\"max_retries\") || \"3\",\n 10,\n );\n const initialDelayMs = parseInt(\n url.searchParams.get(\"initial_delay\") || \"1000\",\n 10,\n );\n\n const retryConfig: RetryConfig = {\n ...DEFAULT_RETRY_CONFIG,\n maxRetries,\n initialDelayMs,\n };\n\n // Initialize Twitter client with custom retry config\n const twitterClient = initializeTwitterClient();\n\n // Fetch tweets with retry mechanism\n const startTime = Date.now();\n const tweets = await twitterClient.fetchHomeTimeline(10);\n const endTime = Date.now();\n\n responseData = {\n ...responseData,\n action: \"test-live-retry\",\n retryConfig,\n tweetCount: tweets.length,\n executionTimeMs: endTime - startTime,\n tweetSample: tweets.slice(0, 2),\n };\n } else if (action === \"retry-config\") {\n // Show current retry configuration\n const config = DEFAULT_RETRY_CONFIG;\n\n // Get environment overrides\n const maxRetries = Deno.env.get(\"TWITTER_MAX_RETRIES\");\n const initialDelay = Deno.env.get(\"TWITTER_INITIAL_DELAY_MS\");\n const maxDelay = Deno.env.get(\"TWITTER_MAX_DELAY_MS\");\n const backoffMultiplier = Deno.env.get(\"TWITTER_BACKOFF_MULTIPLIER\");\n const jitterFactor = Deno.env.get(\"TWITTER_JITTER_FACTOR\");\n\n responseData = {\n ...responseData,\n action: \"retry-config\",\n defaultConfig: config,\n environmentOverrides: {\n maxRetries: maxRetries ? parseInt(maxRetries, 10) : undefined,\n initialDelayMs: initialDelay ? parseInt(initialDelay, 10) : undefined,\n maxDelayMs: maxDelay ? parseInt(maxDelay, 10) : undefined,\n backoffMultiplier: backoffMultiplier\n ? parseFloat(backoffMultiplier)\n : undefined,\n jitterFactor: jitterFactor ? parseFloat(jitterFactor) : undefined,\n },\n };\n }\n\n return new Response(JSON.stringify(responseData, null, 2), {\n status: 200,\n headers: { \"Content-Type\": \"application/json\" },\n });\n } catch (error: unknown) {\n console.error(\"Error in Twitter error test endpoint:\", error);\n\n // Convert to TwitterError if needed\n const twitterError = error instanceof TwitterError\n ? error\n : TwitterError.fromError(error instanceof Error ? error : new Error(String(error)));\n\n return new Response(\n JSON.stringify(\n {\n status: \"error\",\n message: error instanceof Error ? error instanceof Error ? error.message : String(error) : String(error),\n errorType: twitterError.type,\n isRetryable: twitterError.isRetryable,\n statusCode: twitterError.statusCode,\n timestamp: new Date().toISOString(),\n },\n null,\n 2,\n ),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n}\n",[],[153,353],{"_104":361,"_95":362,"_154":363,"_156":155,"_157":139,"_158":364,"_160":161,"_106":365,"_100":32,"_163":366,"_165":367,"_166":22,"_167":-5,"_168":368,"_98":369},"845a41a0-8a7c-11f0-be41-0224a6c84d84","twitter-fetch.cron.ts","845a4236-8a7c-11f0-be41-0224a6c84d84",54,["D",1757092784950],"interval","import { initializeTwitterClient, storeTweets } from \"./twitter-api.ts\";\nimport { initializeDatabase } from \"./database/migrations.ts\";\nimport { email } from \"https://esm.town/v/std/email\";\nimport { TwitterProcessor } from \"./twitter-processor.ts\";\nimport {\n TwitterError,\n TwitterErrorType,\n withRetry,\n} from \"./twitter-error-handler.ts\";\n\n/**\n * Cron job to fetch tweets from Twitter API and store them in the database\n * This function runs on a schedule defined in Val Town\n */\nexport default async function fetchTwitterData() {\n console.log(\"Starting Twitter data fetch...\");\n\n try {\n // Initialize the database\n await initializeDatabase();\n\n // Initialize Twitter client\n const twitterClient = initializeTwitterClient();\n\n // Fetch tweets with retry mechanism already built into the client\n console.log(\"Fetching tweets from Twitter API...\");\n let rawTweets;\n try {\n rawTweets = await twitterClient.fetchHomeTimeline(100);\n console.log(`Fetched ${rawTweets.length} raw tweets from Twitter API`);\n } catch (error: unknown) {\n // Convert to TwitterError for better error handling\n const errorInstance = error instanceof Error ? error : new Error(String(error));\n const twitterError = error instanceof TwitterError\n ? error\n : new TwitterError(\n `Failed to fetch tweets: ${errorInstance.message}`,\n TwitterErrorType.Unknown,\n undefined,\n errorInstance,\n );\n\n // Handle different error types appropriately\n if (twitterError.type === TwitterErrorType.RateLimit) {\n const resetTime = twitterError.rateLimitReset;\n const resetMessage = resetTime\n ? `Rate limit will reset at ${resetTime.toLocaleString()}`\n : \"Rate limit exceeded\";\n\n throw new Error(`Twitter API rate limit exceeded. ${resetMessage}`);\n } else if (twitterError.type === TwitterErrorType.Authentication) {\n throw new Error(\n \"Twitter API authentication failed. Please check your API credentials.\",\n );\n } else {\n throw twitterError;\n }\n }\n\n // Initialize the processor with config from environment variables\n const processor = new TwitterProcessor(\n TwitterProcessor.loadConfigFromEnv(),\n );\n\n // Process tweets through the pipeline\n const processedTweets = processor.processTweets(rawTweets);\n console.log(`Processed ${processedTweets.length} tweets after filtering`);\n\n // Store tweets in the database with deduplication and built-in retry\n const newTweetsCount = await storeTweets(processedTweets);\n console.log(`Stored ${newTweetsCount} new tweets in the database`);\n\n // Send notification email if configured\n const emailTo = Deno.env.get(\"EMAIL_TO\");\n if (emailTo && newTweetsCount > 0) {\n await withRetry(async () => {\n await email({\n to: emailTo,\n subject: `OffX: Fetched ${newTweetsCount} new tweets`,\n text:\n `The OffX Twitter ingestion service has fetched ${rawTweets.length} tweets, processed ${processedTweets.length} after filtering, and stored ${newTweetsCount} new tweets.`,\n html: `

OffX Twitter Ingestion

The OffX Twitter ingestion service has:

Fetched ${rawTweets.length} tweets
Processed ${processedTweets.length} after filtering
Stored ${newTweetsCount} new tweets

`,\n });\n });\n }\n\n return {\n success: true,\n fetchedCount: rawTweets.length,\n processedCount: processedTweets.length,\n newCount: newTweetsCount,\n timestamp: new Date().toISOString(),\n };\n } catch (error: unknown) {\n console.error(\"Error in Twitter fetch cron job:\", error);\n\n // Extract useful error information\n const errorInstance = error instanceof Error ? error : new Error(String(error));\n const errorType = error instanceof TwitterError ? error.type : \"unknown\";\n const errorMessage = errorInstance.message || \"Unknown error\";\n const statusCode = error instanceof TwitterError\n ? error.statusCode\n : undefined;\n\n // Construct detailed error message\n const detailedError = `\n Type: ${errorType}\n Message: ${errorMessage}\n ${statusCode ? `Status Code: ${statusCode}` : \"\"}\n Time: ${new Date().toISOString()}\n `;\n\n // Send error notification with retry mechanism\n try {\n await withRetry(async () => {\n await email({\n subject: \"OffX: Twitter Fetch Error\",\n text: `Error in Twitter fetch cron job: ${detailedError}`,\n html: `

OffX Twitter Fetch Error

The following error occurred during the Twitter fetch cron job:

${detailedError}

Please check the logs for more details.

`,\n });\n });\n } catch (emailError) {\n console.error(\"Failed to send error notification email:\", emailError);\n }\n\n return {\n success: false,\n error: errorMessage,\n errorType,\n statusCode,\n timestamp: new Date().toISOString(),\n };\n }\n}\n",[],[153,362],{"_104":371,"_95":372,"_154":373,"_156":155,"_157":139,"_158":374,"_160":161,"_106":375,"_100":32,"_163":320,"_165":376,"_166":22,"_167":-5,"_168":377,"_98":378},"84232e40-8a7c-11f0-9716-0224a6c84d84","twitter-media-test.http.ts","84232f08-8a7c-11f0-9716-0224a6c84d84",45,["D",1757092784576],"import { initializeTwitterClient } from \"./twitter-api.ts\";\nimport { initializeDatabase } from \"./database/migrations.ts\";\nimport { getPostById, getRecentPosts } from \"./database/queries.ts\";\nimport { TwitterMediaExtractor } from \"./twitter-media.ts\";\n\n/**\n * HTTP endpoint to test Twitter media extraction functionality\n * This endpoint allows testing and validation of the media extraction features\n */\nexport default async function (req: Request): Promise {\n // Check for basic auth\n const authHeader = req.headers.get(\"Authorization\");\n if (!authHeader || !authHeader.startsWith(\"Basic \")) {\n return new Response(\"Unauthorized\", {\n status: 401,\n headers: { \"WWW-Authenticate\": \"Basic\" },\n });\n }\n\n const base64Credentials = authHeader.split(\" \")[1];\n const credentials = atob(base64Credentials);\n const [username, password] = credentials.split(\":\");\n\n const expectedUsername = Deno.env.get(\"AUTH_USERNAME\");\n const expectedPassword = Deno.env.get(\"AUTH_PASSWORD\");\n\n if (username !== expectedUsername || password !== expectedPassword) {\n return new Response(\"Unauthorized\", {\n status: 401,\n headers: { \"WWW-Authenticate\": \"Basic\" },\n });\n }\n\n // Process the request\n try {\n const url = new URL(req.url);\n const action = url.searchParams.get(\"action\") || \"status\";\n\n // Initialize database\n await initializeDatabase();\n\n let responseData: any = {\n status: \"ok\",\n timestamp: new Date().toISOString(),\n };\n\n if (action === \"fetch-media\") {\n // Fetch tweets with media from Twitter API\n const twitterClient = initializeTwitterClient();\n const rawTweets = await twitterClient.fetchHomeTimeline(20);\n\n // Filter to only tweets with media\n const tweetsWithMedia = rawTweets.filter((tweet) =>\n tweet.media && tweet.media.length > 0\n );\n\n responseData = {\n ...responseData,\n action: \"fetch-media\",\n totalFetched: rawTweets.length,\n withMediaCount: tweetsWithMedia.length,\n mediaItems: tweetsWithMedia.map((tweet) => ({\n tweetId: tweet.external_id,\n author: tweet.author_username,\n mediaCount: tweet.media?.length || 0,\n media: tweet.media,\n })),\n };\n } else if (action === \"media-stats\") {\n // Get media statistics from database\n const limit = parseInt(url.searchParams.get(\"limit\") || \"50\", 10);\n const recentPosts = await getRecentPosts(limit);\n\n // Count media types\n const mediaStats = {\n totalPosts: recentPosts.length,\n postsWithMedia: 0,\n mediaTypes: {} as Record,\n totalMediaItems: 0,\n };\n\n for (const post of recentPosts) {\n if (post.media && post.media.length > 0) {\n mediaStats.postsWithMedia++;\n mediaStats.totalMediaItems += post.media.length;\n\n for (const media of post.media) {\n const type = media.media_type || \"unknown\";\n mediaStats.mediaTypes[type] = (mediaStats.mediaTypes[type] || 0) +\n 1;\n }\n }\n }\n\n responseData = {\n ...responseData,\n action: \"media-stats\",\n stats: mediaStats,\n };\n } else if (action === \"post-media\") {\n // Get media for a specific post\n const postId = parseInt(url.searchParams.get(\"id\") || \"0\", 10);\n\n if (!postId) {\n return new Response(\n JSON.stringify(\n {\n status: \"error\",\n message: \"Missing post ID parameter\",\n },\n null,\n 2,\n ),\n {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n const post = await getPostById(postId);\n\n if (!post) {\n return new Response(\n JSON.stringify(\n {\n status: \"error\",\n message: \"Post not found\",\n },\n null,\n 2,\n ),\n {\n status: 404,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n responseData = {\n ...responseData,\n action: \"post-media\",\n post: {\n id: post.id,\n external_id: post.external_id,\n author: post.author_username,\n content: post.content.substring(0, 50) +\n (post.content.length > 50 ? \"...\" : \"\"),\n url: post.url,\n },\n mediaCount: post.media?.length || 0,\n media: post.media,\n };\n }\n\n return new Response(JSON.stringify(responseData, null, 2), {\n status: 200,\n headers: { \"Content-Type\": \"application/json\" },\n });\n } catch (error: unknown) {\n console.error(\"Error in Twitter media test endpoint:\", error);\n\n return new Response(\n JSON.stringify(\n {\n status: \"error\",\n message: error instanceof Error ? error instanceof Error ? error.message : String(error) : String(error),\n timestamp: new Date().toISOString(),\n },\n null,\n 2,\n ),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n}\n",[],[153,372],{"_104":380,"_95":381,"_154":382,"_156":155,"_157":139,"_158":383,"_160":161,"_106":384,"_100":32,"_163":193,"_165":385,"_166":22,"_167":-5,"_168":386,"_98":387},"84540024-8a7c-11f0-931f-0224a6c84d84","twitter-media.ts","845400c4-8a7c-11f0-931f-0224a6c84d84",53,["D",1757092784793],"import {\n createPostMedia,\n getPostMediaByPostId,\n Post,\n PostMedia,\n} from \"./database/queries.ts\";\n\n/**\n * Media type enumeration\n */\nexport enum MediaType {\n PHOTO = \"photo\",\n VIDEO = \"video\",\n GIF = \"animated_gif\",\n UNKNOWN = \"unknown\",\n}\n\n/**\n * Extended media metadata interface\n */\nexport interface MediaMetadata {\n width?: number;\n height?: number;\n duration_ms?: number;\n preview_url?: string;\n alt_text?: string;\n variants?: MediaVariant[];\n}\n\n/**\n * Media variant interface (for videos with multiple formats/bitrates)\n */\nexport interface MediaVariant {\n content_type: string;\n url: string;\n bitrate?: number;\n}\n\n/**\n * Extended post media interface with metadata\n */\nexport interface ExtendedPostMedia extends PostMedia {\n metadata?: MediaMetadata;\n}\n\n/**\n * Twitter media extraction and processing class\n */\nexport class TwitterMediaExtractor {\n /**\n * Extract media from Twitter API response\n * @param timelineData Twitter API response data\n * @param tweetId ID of the tweet to extract media from\n * @returns Array of extracted media items\n */\n static extractMediaFromResponse(\n timelineData: any,\n tweetId: string,\n ): ExtendedPostMedia[] {\n const media: ExtendedPostMedia[] = [];\n\n // Find the tweet in the response\n const tweet = timelineData.data?.find((t: any) => t.id === tweetId);\n\n if (\n !tweet || !tweet.attachments?.media_keys || !timelineData.includes?.media\n ) {\n return media;\n }\n\n // Extract media items\n for (const mediaKey of tweet.attachments.media_keys) {\n const mediaItem = timelineData.includes.media.find(\n (m: any) => m.media_key === mediaKey,\n );\n\n if (mediaItem) {\n const mediaType = this.normalizeMediaType(mediaItem.type);\n\n // Extract metadata\n const metadata: MediaMetadata = {\n width: mediaItem.width,\n height: mediaItem.height,\n duration_ms: mediaItem.duration_ms,\n preview_url: mediaItem.preview_image_url,\n alt_text: mediaItem.alt_text,\n };\n\n // Extract variants for videos\n if (mediaItem.variants && Array.isArray(mediaItem.variants)) {\n metadata.variants = mediaItem.variants.map((v: any) => ({\n content_type: v.content_type,\n url: v.url,\n bitrate: v.bit_rate,\n }));\n }\n\n // Create media object\n const postMedia: ExtendedPostMedia = {\n post_id: 0, // This will be set after post creation\n media_url: this.getBestMediaUrl(mediaItem),\n media_type: mediaType,\n alt_text: mediaItem.alt_text,\n metadata,\n };\n\n media.push(postMedia);\n }\n }\n\n return media;\n }\n\n /**\n * Get the best media URL based on media type\n * @param mediaItem Twitter API media item\n * @returns Best URL for the media\n */\n private static getBestMediaUrl(mediaItem: any): string {\n // For photos, use the URL directly\n if (mediaItem.url) {\n return mediaItem.url;\n }\n\n // For videos and GIFs, try to get the best quality variant\n if (mediaItem.variants && Array.isArray(mediaItem.variants)) {\n // Sort variants by bitrate (highest first)\n const sortedVariants = [...mediaItem.variants].sort((a, b) =>\n (b.bit_rate || 0) - (a.bit_rate || 0)\n );\n\n // Get the highest quality variant\n if (sortedVariants.length > 0) {\n return sortedVariants[0].url;\n }\n }\n\n // Fallback to preview image\n if (mediaItem.preview_image_url) {\n return mediaItem.preview_image_url;\n }\n\n return \"\";\n }\n\n /**\n * Normalize media type from Twitter API\n * @param type Media type from Twitter API\n * @returns Normalized media type\n */\n private static normalizeMediaType(type: string): string {\n switch (type) {\n case \"photo\":\n return MediaType.PHOTO;\n case \"video\":\n return MediaType.VIDEO;\n case \"animated_gif\":\n return MediaType.GIF;\n default:\n return MediaType.UNKNOWN;\n }\n }\n\n /**\n * Store media items for a post\n * @param postId Database ID of the post\n * @param media Array of media items to store\n * @returns Number of media items stored\n */\n static async storePostMedia(\n postId: number,\n media: ExtendedPostMedia[],\n ): Promise {\n if (!postId || !media || media.length === 0) {\n return 0;\n }\n\n let storedCount = 0;\n\n // Check for existing media\n const existingMedia = await getPostMediaByPostId(postId);\n\n // If media already exists for this post, skip\n if (existingMedia && existingMedia.length > 0) {\n return 0;\n }\n\n // Store each media item\n for (const mediaItem of media) {\n // Set the post ID\n mediaItem.post_id = postId;\n\n // Store in database\n await createPostMedia(mediaItem);\n storedCount++;\n }\n\n return storedCount;\n }\n\n /**\n * Process and enhance media items\n * @param media Array of media items to process\n * @returns Processed media items\n */\n static processMedia(media: ExtendedPostMedia[]): ExtendedPostMedia[] {\n return media.map((item) => {\n // Create a copy to avoid modifying the original\n const processedItem = { ...item };\n\n // Ensure media URLs are properly formatted\n if (\n processedItem.media_url && !processedItem.media_url.startsWith(\"http\")\n ) {\n processedItem.media_url = `https://${processedItem.media_url}`;\n }\n\n // Process preview URLs in metadata\n if (\n processedItem.metadata?.preview_url &&\n !processedItem.metadata.preview_url.startsWith(\"http\")\n ) {\n processedItem.metadata.preview_url =\n `https://${processedItem.metadata.preview_url}`;\n }\n\n // Process variant URLs\n if (processedItem.metadata?.variants) {\n processedItem.metadata.variants = processedItem.metadata.variants.map(\n (variant) => {\n if (variant.url && !variant.url.startsWith(\"http\")) {\n return { ...variant, url: `https://${variant.url}` };\n }\n return variant;\n },\n );\n }\n\n return processedItem;\n });\n }\n}\n",[],[153,381],{"_104":389,"_95":390,"_154":391,"_156":155,"_157":139,"_158":392,"_160":161,"_106":393,"_100":32,"_163":193,"_165":394,"_166":22,"_167":-5,"_168":395,"_98":396},"844a4570-8a7c-11f0-a4f1-0224a6c84d84","twitter-processor.ts","844a4642-8a7c-11f0-a4f1-0224a6c84d84",51,["D",1757092784812],"import { Post, PostMedia } from \"./database/queries.ts\";\n\n/**\n * Interface for filter configuration\n */\nexport interface TwitterFilterConfig {\n keywords?: string[];\n languages?: string[];\n excludeKeywords?: string[];\n excludeUsers?: string[];\n includeUsers?: string[];\n minFavoriteCount?: number;\n minRetweetCount?: number;\n includeRetweets?: boolean;\n includeReplies?: boolean;\n}\n\n/**\n * Default filter configuration\n */\nexport const DEFAULT_FILTER_CONFIG: TwitterFilterConfig = {\n languages: [\"en\"],\n includeRetweets: false,\n includeReplies: false,\n};\n\n/**\n * Twitter data processing pipeline\n */\nexport class TwitterProcessor {\n private filterConfig: TwitterFilterConfig;\n\n /**\n * Create a new TwitterProcessor with the specified filter configuration\n * @param config Filter configuration (optional, defaults to DEFAULT_FILTER_CONFIG)\n */\n constructor(config: TwitterFilterConfig = DEFAULT_FILTER_CONFIG) {\n this.filterConfig = {\n ...DEFAULT_FILTER_CONFIG,\n ...config,\n };\n }\n\n /**\n * Process a batch of tweets through the pipeline\n * @param tweets Array of tweets to process\n * @returns Filtered and processed tweets\n */\n processTweets(tweets: Post[]): Post[] {\n if (!tweets || !Array.isArray(tweets) || tweets.length === 0) {\n return [];\n }\n\n return tweets\n .filter((tweet) => this.applyFilters(tweet))\n .map((tweet) => this.transformTweet(tweet));\n }\n\n /**\n * Apply all configured filters to a tweet\n * @param tweet The tweet to filter\n * @returns True if the tweet passes all filters, false otherwise\n */\n private applyFilters(tweet: Post): boolean {\n // Filter by language\n if (this.filterConfig.languages && this.filterConfig.languages.length > 0) {\n // Note: Twitter API doesn't always provide language info in the response\n // This would need to be extended if language detection is critical\n // For now, we'll assume English if not specified\n const tweetLanguage = \"en\";\n if (!this.filterConfig.languages.includes(tweetLanguage)) {\n return false;\n }\n }\n\n // Filter retweets if configured\n if (\n !this.filterConfig.includeRetweets && tweet.content.startsWith(\"RT @\")\n ) {\n return false;\n }\n\n // Filter replies if configured\n if (!this.filterConfig.includeReplies && tweet.content.startsWith(\"@\")) {\n return false;\n }\n\n // Filter by keywords\n if (this.filterConfig.keywords && this.filterConfig.keywords.length > 0) {\n const tweetText = tweet.content.toLowerCase();\n const hasKeyword = this.filterConfig.keywords.some((keyword) =>\n tweetText.includes(keyword.toLowerCase())\n );\n\n if (!hasKeyword) {\n return false;\n }\n }\n\n // Filter by excluded keywords\n if (\n this.filterConfig.excludeKeywords &&\n this.filterConfig.excludeKeywords.length > 0\n ) {\n const tweetText = tweet.content.toLowerCase();\n const hasExcludedKeyword = this.filterConfig.excludeKeywords.some(\n (keyword) => tweetText.includes(keyword.toLowerCase()),\n );\n\n if (hasExcludedKeyword) {\n return false;\n }\n }\n\n // Filter by included users\n if (\n this.filterConfig.includeUsers &&\n this.filterConfig.includeUsers.length > 0\n ) {\n const username = tweet.author_username.toLowerCase();\n const isIncludedUser = this.filterConfig.includeUsers.some((user) =>\n username === user.toLowerCase()\n );\n\n if (!isIncludedUser) {\n return false;\n }\n }\n\n // Filter by excluded users\n if (\n this.filterConfig.excludeUsers &&\n this.filterConfig.excludeUsers.length > 0\n ) {\n const username = tweet.author_username.toLowerCase();\n const isExcludedUser = this.filterConfig.excludeUsers.some((user) =>\n username === user.toLowerCase()\n );\n\n if (isExcludedUser) {\n return false;\n }\n }\n\n return true;\n }\n\n /**\n * Transform a tweet for storage and processing\n * @param tweet The tweet to transform\n * @returns Transformed tweet\n */\n private transformTweet(tweet: Post): Post {\n // Create a copy of the tweet to avoid modifying the original\n const transformedTweet: Post = { ...tweet };\n\n // Clean up the content (e.g., remove excessive whitespace, normalize URLs)\n transformedTweet.content = this.cleanContent(transformedTweet.content);\n\n // Transform media if present\n if (transformedTweet.media && transformedTweet.media.length > 0) {\n transformedTweet.media = transformedTweet.media.map((media) =>\n this.transformMedia(media)\n );\n }\n\n return transformedTweet;\n }\n\n /**\n * Clean up tweet content\n * @param content The raw tweet content\n * @returns Cleaned content\n */\n private cleanContent(content: string): string {\n // Remove excessive whitespace\n let cleaned = content.replace(/\\s+/g, \" \").trim();\n\n // Normalize URLs (optional)\n // This is a simple example - could be expanded for more sophisticated URL normalization\n cleaned = cleaned.replace(/https:\\/\\/t\\.co\\/\\w+/g, (url) => url.trim());\n\n return cleaned;\n }\n\n /**\n * Transform media attachments\n * @param media The media to transform\n * @returns Transformed media\n */\n private transformMedia(media: PostMedia): PostMedia {\n // Create a copy to avoid modifying the original\n const transformedMedia: PostMedia = { ...media };\n\n // Ensure media URLs are properly formatted\n if (\n transformedMedia.media_url &&\n !transformedMedia.media_url.startsWith(\"http\")\n ) {\n transformedMedia.media_url = `https://${transformedMedia.media_url}`;\n }\n\n return transformedMedia;\n }\n\n /**\n * Load filter configuration from environment variables\n * @returns TwitterFilterConfig object based on environment variables\n */\n static loadConfigFromEnv(): TwitterFilterConfig {\n const config: TwitterFilterConfig = { ...DEFAULT_FILTER_CONFIG };\n\n // Keywords filter\n const keywordsEnv = Deno.env.get(\"TWITTER_FILTER_KEYWORDS\");\n if (keywordsEnv) {\n config.keywords = keywordsEnv.split(\",\").map((k) => k.trim());\n }\n\n // Excluded keywords\n const excludeKeywordsEnv = Deno.env.get(\"TWITTER_FILTER_EXCLUDE_KEYWORDS\");\n if (excludeKeywordsEnv) {\n config.excludeKeywords = excludeKeywordsEnv.split(\",\").map((k) =>\n k.trim()\n );\n }\n\n // Included users\n const includeUsersEnv = Deno.env.get(\"TWITTER_FILTER_INCLUDE_USERS\");\n if (includeUsersEnv) {\n config.includeUsers = includeUsersEnv.split(\",\").map((u) => u.trim());\n }\n\n // Excluded users\n const excludeUsersEnv = Deno.env.get(\"TWITTER_FILTER_EXCLUDE_USERS\");\n if (excludeUsersEnv) {\n config.excludeUsers = excludeUsersEnv.split(\",\").map((u) => u.trim());\n }\n\n // Languages\n const languagesEnv = Deno.env.get(\"TWITTER_FILTER_LANGUAGES\");\n if (languagesEnv) {\n config.languages = languagesEnv.split(\",\").map((l) => l.trim());\n }\n\n // Boolean flags\n const includeRetweetsEnv = Deno.env.get(\"TWITTER_FILTER_INCLUDE_RETWEETS\");\n if (includeRetweetsEnv) {\n config.includeRetweets = includeRetweetsEnv.toLowerCase() === \"true\";\n }\n\n const includeRepliesEnv = Deno.env.get(\"TWITTER_FILTER_INCLUDE_REPLIES\");\n if (includeRepliesEnv) {\n config.includeReplies = includeRepliesEnv.toLowerCase() === \"true\";\n }\n\n return config;\n }\n}\n",[],[153,390],{"_104":398,"_95":399,"_154":400,"_156":155,"_157":139,"_158":401,"_160":161,"_106":402,"_100":32,"_163":320,"_165":403,"_166":22,"_167":-5,"_168":404,"_98":405},"8482f276-8a7c-11f0-b7f7-0224a6c84d84","twitter-sentiment-api.http.ts","8482f33e-8a7c-11f0-b7f7-0224a6c84d84",59,["D",1757092785218],"import { initializeDatabase } from \"./database/migrations.ts\";\nimport {\n createOrUpdatePostSentiment,\n getPostsWithoutSentimentAnalysis,\n getPostsWithSentiment,\n getRecentPosts,\n getSentimentStats,\n Post,\n} from \"./database/queries.ts\";\nimport { TwitterSentimentAnalyzer } from \"./twitter-sentiment.ts\";\n\n/**\n * HTTP endpoint for tweet sentiment analysis operations\n */\nexport default async function (req: Request): Promise {\n // Set CORS headers for all responses\n const headers = new Headers({\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"GET, POST, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type\",\n \"Content-Type\": \"application/json\",\n });\n\n // Handle preflight OPTIONS request\n if (req.method === \"OPTIONS\") {\n return new Response(null, { headers, status: 204 });\n }\n\n // Process the request\n try {\n const url = new URL(req.url);\n const action = url.searchParams.get(\"action\") || \"status\";\n\n // Initialize database\n await initializeDatabase();\n\n let responseData: any = {\n status: \"ok\",\n timestamp: new Date().toISOString(),\n };\n\n // Create sentiment analyzer with configuration from environment variables\n const analyzer = new TwitterSentimentAnalyzer(\n TwitterSentimentAnalyzer.loadConfigFromEnv(),\n );\n\n if (action === \"analyze\") {\n // Get posts to analyze - either unanalyzed posts or recent posts\n const useUnanalyzed = url.searchParams.get(\"unanalyzed\") === \"true\";\n const limit = parseInt(url.searchParams.get(\"limit\") || \"10\", 10);\n\n const posts = useUnanalyzed\n ? await getPostsWithoutSentimentAnalysis(limit)\n : await getRecentPosts(limit);\n\n if (posts.length === 0) {\n responseData = {\n ...responseData,\n action: \"analyze\",\n message: \"No posts found for analysis\",\n analyzedCount: 0,\n };\n } else {\n // Analyze sentiment\n const sentimentResults = await analyzer.analyzeBatch(posts);\n\n // Store results in database\n let storedCount = 0;\n for (const result of sentimentResults) {\n await createOrUpdatePostSentiment(result);\n storedCount++;\n }\n\n responseData = {\n ...responseData,\n action: \"analyze\",\n analyzedCount: sentimentResults.length,\n storedCount,\n results: sentimentResults.slice(0, 3), // Return first 3 results as preview\n };\n }\n } else if (action === \"query\") {\n // Query posts by sentiment\n const sentiment = url.searchParams.get(\"sentiment\") as\n | \"positive\"\n | \"negative\"\n | \"neutral\"\n | undefined;\n const minConfidence = parseFloat(\n url.searchParams.get(\"min_confidence\") || \"0.7\",\n );\n const limit = parseInt(url.searchParams.get(\"limit\") || \"10\", 10);\n\n const posts = await getPostsWithSentiment(\n sentiment,\n minConfidence,\n limit,\n );\n\n responseData = {\n ...responseData,\n action: \"query\",\n sentiment: sentiment || \"all\",\n minConfidence,\n count: posts.length,\n posts: posts.map((post) => ({\n id: post.id,\n content: post.content,\n author: post.author_username,\n created_at: post.created_at,\n })),\n };\n } else if (action === \"stats\") {\n // Get sentiment statistics\n const stats = await getSentimentStats();\n\n responseData = {\n ...responseData,\n action: \"stats\",\n stats,\n };\n } else {\n // Default status action\n responseData = {\n ...responseData,\n action: \"status\",\n message: \"Sentiment analysis API is running\",\n availableActions: [\"analyze\", \"query\", \"stats\"],\n config: {\n useAI: Deno.env.get(\"TWITTER_SENTIMENT_USE_AI\") === \"true\",\n batchSize: parseInt(\n Deno.env.get(\"TWITTER_SENTIMENT_BATCH_SIZE\") || \"10\",\n 10,\n ),\n },\n };\n }\n\n return new Response(JSON.stringify(responseData, null, 2), { headers });\n } catch (error: unknown) {\n console.error(\"Error processing sentiment analysis request:\", error);\n\n return new Response(\n JSON.stringify(\n {\n status: \"error\",\n message: error instanceof Error ? error.message : String(error),\n timestamp: new Date().toISOString(),\n },\n null,\n 2,\n ),\n { headers, status: 500 },\n );\n }\n}\n",[],[153,399],{"_104":407,"_95":408,"_154":409,"_156":155,"_157":139,"_158":410,"_160":161,"_106":411,"_100":32,"_163":366,"_165":412,"_166":22,"_167":-5,"_168":413,"_98":414},"843f5bba-8a7c-11f0-b5e7-0224a6c84d84","twitter-sentiment-job.cron.ts","843f5c6e-8a7c-11f0-b5e7-0224a6c84d84",50,["D",1757092784738],"import { initializeDatabase } from \"./database/migrations.ts\";\nimport {\n createOrUpdatePostSentiment,\n getPostsWithoutSentimentAnalysis,\n} from \"./database/queries.ts\";\nimport { TwitterSentimentAnalyzer } from \"./twitter-sentiment.ts\";\nimport { email } from \"https://esm.town/v/std/email\";\n\n/**\n * Cron job that runs on a schedule to analyze tweets for sentiment\n * Default schedule: Every 4 hours\n */\nexport default async function () {\n console.log(\"Starting scheduled sentiment analysis job\");\n\n try {\n // Initialize database\n await initializeDatabase();\n\n // Create sentiment analyzer with configuration from environment variables\n const analyzer = new TwitterSentimentAnalyzer(\n TwitterSentimentAnalyzer.loadConfigFromEnv(),\n );\n\n // Get batch size from environment or use default\n const batchSize = parseInt(\n Deno.env.get(\"TWITTER_SENTIMENT_JOB_BATCH_SIZE\") || \"50\",\n 10,\n );\n\n // Get unanalyzed posts\n const posts = await getPostsWithoutSentimentAnalysis(batchSize);\n\n if (posts.length === 0) {\n console.log(\"No unanalyzed posts found\");\n return;\n }\n\n console.log(`Analyzing sentiment for ${posts.length} posts`);\n\n // Analyze sentiment\n const sentimentResults = await analyzer.analyzeBatch(posts);\n\n // Store results in database\n let storedCount = 0;\n for (const result of sentimentResults) {\n await createOrUpdatePostSentiment(result);\n storedCount++;\n }\n\n console.log(`Completed sentiment analysis: ${storedCount} results stored`);\n\n // Send notification email if enabled\n const sendNotification =\n Deno.env.get(\"TWITTER_SENTIMENT_JOB_NOTIFY\") === \"true\";\n if (sendNotification && storedCount > 0) {\n const sentimentCounts = {\n positive: sentimentResults.filter((r) =>\n r.sentiment === \"positive\"\n ).length,\n negative: sentimentResults.filter((r) =>\n r.sentiment === \"negative\"\n ).length,\n neutral: sentimentResults.filter((r) =>\n r.sentiment === \"neutral\"\n ).length,\n };\n\n await email({\n subject: `OffX: Sentiment Analysis Complete (${storedCount} posts)`,\n text: `\nSentiment analysis job completed successfully.\n\nPosts analyzed: ${storedCount}\n- Positive: ${sentimentCounts.positive}\n- Negative: ${sentimentCounts.negative}\n- Neutral: ${sentimentCounts.neutral}\n\nJob completed at: ${new Date().toISOString()}\n `,\n html: `\n

Sentiment Analysis Job Complete

The scheduled sentiment analysis job has completed successfully.

\n\n

Summary

Posts analyzed: ${storedCount}
Positive: ${sentimentCounts.positive}
Negative: ${sentimentCounts.negative}
Neutral: ${sentimentCounts.neutral}

\n\n

Job completed at: ${new Date().toISOString()}

\n `,\n });\n }\n } catch (error: unknown) {\n console.error(\"Error in sentiment analysis job:\", error);\n\n const errorMessage = error instanceof Error ? error instanceof Error ? error.message : String(error) : String(error);\n\n // Send error notification\n try {\n await email({\n subject: \"OffX: Sentiment Analysis Job Failed\",\n text: `\nSentiment analysis job failed with error:\n${errorMessage}\n\nError occurred at: ${new Date().toISOString()}\n `,\n html: `\n

Sentiment Analysis Job Failed

The scheduled sentiment analysis job encountered an error.

\n\n

Error Details

${errorMessage}

\n\n

Error occurred at: ${new Date().toISOString()}

\n `,\n });\n } catch (emailError) {\n console.error(\"Failed to send error notification email:\", emailError);\n }\n\n throw error; // Re-throw to ensure the job is marked as failed\n }\n}\n",[],[153,408],{"_104":416,"_95":417,"_154":418,"_156":155,"_157":139,"_158":419,"_160":161,"_106":420,"_100":32,"_163":193,"_165":421,"_166":22,"_167":-5,"_168":422,"_98":423},"848da7f2-8a7c-11f0-abb7-0224a6c84d84","twitter-sentiment.ts","848da89c-8a7c-11f0-abb7-0224a6c84d84",61,["D",1757092785079],"import { OpenAI } from \"https://esm.town/v/std/openai\";\nimport { Post } from \"./database/queries.ts\";\n\n/**\n * Sentiment analysis result interface\n */\nexport interface SentimentResult {\n post_id: number;\n sentiment: \"positive\" | \"negative\" | \"neutral\";\n score: number; // -1.0 to 1.0 where -1 is very negative, 0 is neutral, 1 is very positive\n confidence: number; // 0.0 to 1.0\n keywords: string[]; // Key emotional or opinion words that influenced the sentiment\n entities?: string[]; // Optional entities mentioned in the text\n}\n\n/**\n * Configuration options for sentiment analysis\n */\nexport interface SentimentAnalysisConfig {\n useAI: boolean; // Whether to use AI for sentiment analysis or rule-based approach\n confidenceThreshold: number; // Minimum confidence score to accept a sentiment result\n batchSize: number; // Number of tweets to analyze in a single batch\n includeEntities: boolean; // Whether to extract entities mentioned in the text\n requestsPerMinute?: number; // Maximum number of API requests per minute (rate limiting)\n}\n\n/**\n * Default sentiment analysis configuration\n */\nexport const DEFAULT_SENTIMENT_CONFIG: SentimentAnalysisConfig = {\n useAI: true,\n confidenceThreshold: 0.7,\n batchSize: 10,\n includeEntities: false,\n requestsPerMinute: 10, // Default to 10 requests per minute (Val Town limit)\n};\n\n/**\n * Twitter sentiment analysis class\n */\nexport class TwitterSentimentAnalyzer {\n private config: SentimentAnalysisConfig;\n private openai: OpenAI | null = null;\n private requestTimestamps: number[] = []; // Store timestamps of recent API requests\n\n /**\n * Create a new TwitterSentimentAnalyzer with the specified configuration\n * @param config Sentiment analysis configuration (optional, defaults to DEFAULT_SENTIMENT_CONFIG)\n */\n constructor(config: SentimentAnalysisConfig = DEFAULT_SENTIMENT_CONFIG) {\n this.config = {\n ...DEFAULT_SENTIMENT_CONFIG,\n ...config,\n };\n\n if (this.config.useAI) {\n this.initializeOpenAI();\n }\n }\n\n /**\n * Initialize OpenAI client\n */\n private initializeOpenAI(): void {\n try {\n this.openai = new OpenAI();\n } catch (error: unknown) {\n console.error(\"Failed to initialize OpenAI client:\", error);\n const errorMessage = error instanceof Error ? error instanceof Error ? error.message : String(error) : String(error);\n throw new Error(\n `OpenAI initialization failed: ${errorMessage}. Make sure OPENAI_API_KEY is set.`,\n );\n }\n }\n\n /**\n * Check if we can make another API request based on rate limiting\n * @returns boolean indicating if we can make another request\n */\n private canMakeRequest(): boolean {\n const now = Date.now();\n const oneMinuteAgo = now - 60000; // 1 minute in milliseconds\n\n // Remove timestamps older than 1 minute\n this.requestTimestamps = this.requestTimestamps.filter(\n (timestamp) => timestamp > oneMinuteAgo,\n );\n\n // Check if we've made fewer requests than our limit\n return this.requestTimestamps.length <\n (this.config.requestsPerMinute || 10);\n }\n\n /**\n * Wait until we can make another API request\n * @returns Promise that resolves when we can make another request\n */\n private async waitForRequestSlot(): Promise {\n if (this.canMakeRequest()) {\n return;\n }\n\n // Calculate time to wait based on the oldest request in our window\n const now = Date.now();\n const oldestTimestamp = this.requestTimestamps[0];\n const timeToWait = 60000 - (now - oldestTimestamp) + 50; // Add 50ms buffer\n\n console.log(\n `Rate limit reached. Waiting ${timeToWait}ms before next request.`,\n );\n\n return new Promise((resolve) => setTimeout(resolve, timeToWait));\n }\n\n /**\n * Record a new API request\n */\n private recordRequest(): void {\n this.requestTimestamps.push(Date.now());\n }\n\n /**\n * Analyze sentiment for a batch of tweets\n * @param tweets Array of tweets to analyze\n * @returns Array of sentiment analysis results\n */\n async analyzeBatch(tweets: Post[]): Promise {\n if (!tweets || tweets.length === 0) {\n return [];\n }\n\n const results: SentimentResult[] = [];\n\n // Process in batches according to configuration\n for (let i = 0; i < tweets.length; i += this.config.batchSize) {\n const batch = tweets.slice(i, i + this.config.batchSize);\n\n if (this.config.useAI) {\n const batchResults = await this.analyzeWithAI(batch);\n results.push(...batchResults);\n } else {\n const batchResults = this.analyzeWithRules(batch);\n results.push(...batchResults);\n }\n }\n\n return results;\n }\n\n /**\n * Analyze a single tweet's sentiment\n * @param tweet The tweet to analyze\n * @returns Sentiment analysis result\n */\n async analyzeTweet(tweet: Post): Promise {\n if (this.config.useAI) {\n const results = await this.analyzeWithAI([tweet]);\n return results[0];\n } else {\n return this.analyzeWithRules([tweet])[0];\n }\n }\n\n /**\n * Analyze tweets using OpenAI\n * @param tweets Array of tweets to analyze\n * @returns Array of sentiment analysis results\n */\n private async analyzeWithAI(tweets: Post[]): Promise {\n if (!this.openai) {\n throw new Error(\"OpenAI client not initialized\");\n }\n\n const results: SentimentResult[] = [];\n\n try {\n // Wait for a request slot to become available (throttling)\n await this.waitForRequestSlot();\n\n // Prepare the prompt for batch analysis\n const prompt = this.buildSentimentPrompt(tweets);\n\n // Record this request for rate limiting\n this.recordRequest();\n\n // Call OpenAI API\n const completion = await this.openai.chat.completions.create({\n messages: [\n {\n role: \"system\",\n content:\n \"You are a sentiment analysis expert. Analyze the sentiment of the provided tweets and return the results in the exact JSON format requested.\",\n },\n { role: \"user\", content: prompt },\n ],\n model: \"gpt-3.5-turbo\", // Using a smaller model for cost efficiency\n response_format: { type: \"json_object\" },\n max_tokens: 1000,\n });\n\n // Parse the response\n const responseContent = completion.choices[0]?.message?.content || \"\";\n if (!responseContent) {\n throw new Error(\"Empty response from OpenAI\");\n }\n\n try {\n const parsedResponse = JSON.parse(responseContent);\n\n if (!parsedResponse.results || !Array.isArray(parsedResponse.results)) {\n throw new Error(\"Invalid response format from OpenAI\");\n }\n\n // Map the AI results to our SentimentResult format\n for (let i = 0; i < parsedResponse.results.length; i++) {\n const result = parsedResponse.results[i];\n const tweet = tweets[i];\n\n if (!tweet || !tweet.id) {\n console.warn(\"Missing tweet ID for sentiment result\");\n continue;\n }\n\n results.push({\n post_id: tweet.id,\n sentiment: result.sentiment || \"neutral\",\n score: result.score || 0,\n confidence: result.confidence || 0.5,\n keywords: result.keywords || [],\n entities: this.config.includeEntities\n ? result.entities || []\n : undefined,\n });\n }\n } catch (parseError) {\n console.error(\"Failed to parse OpenAI response:\", parseError);\n const parseErrorMessage = parseError instanceof Error ? parseError.message : String(parseError);\n throw new Error(\n `Failed to parse OpenAI response: ${parseErrorMessage}`,\n );\n }\n } catch (error: unknown) {\n console.error(\"Error in AI sentiment analysis:\", error);\n\n // Fallback to rule-based analysis\n console.log(\"Falling back to rule-based sentiment analysis\");\n return this.analyzeWithRules(tweets);\n }\n\n return results;\n }\n\n /**\n * Build the prompt for sentiment analysis\n * @param tweets Array of tweets to analyze\n * @returns Formatted prompt for OpenAI\n */\n private buildSentimentPrompt(tweets: Post[]): string {\n const tweetTexts = tweets.map((tweet, index) =>\n `Tweet ${index + 1}: \"${tweet.content}\"`\n ).join(\"\\n\\n\");\n\n const includeEntities = this.config.includeEntities\n ? `Include an \"entities\" array with named entities mentioned in the tweet.`\n : \"\";\n\n return `\nAnalyze the sentiment of the following tweets:\n\n${tweetTexts}\n\nFor each tweet, determine:\n1. The overall sentiment (positive, negative, or neutral)\n2. A sentiment score from -1.0 (very negative) to 1.0 (very positive)\n3. A confidence score from 0.0 to 1.0 indicating how confident you are in this assessment\n4. Key emotional or opinion words that influenced the sentiment\n${includeEntities}\n\nReturn your analysis in the following JSON format:\n{\n \"results\": [\n {\n \"sentiment\": \"positive|negative|neutral\",\n \"score\": float,\n \"confidence\": float,\n \"keywords\": [\"word1\", \"word2\", ...],\n ${\n this.config.includeEntities\n ? `\"entities\": [\"entity1\", \"entity2\", ...],`\n : \"\"\n }\n },\n ...\n ]\n}\n\nOnly return valid JSON, no other text.\n`;\n }\n\n /**\n * Simple rule-based sentiment analysis as a fallback\n * @param tweets Array of tweets to analyze\n * @returns Array of sentiment analysis results\n */\n private analyzeWithRules(tweets: Post[]): SentimentResult[] {\n const positiveWords = [\n \"good\",\n \"great\",\n \"excellent\",\n \"amazing\",\n \"awesome\",\n \"wonderful\",\n \"fantastic\",\n \"happy\",\n \"love\",\n \"best\",\n \"beautiful\",\n \"perfect\",\n \"brilliant\",\n \"exciting\",\n \"joy\",\n ];\n\n const negativeWords = [\n \"bad\",\n \"terrible\",\n \"awful\",\n \"horrible\",\n \"poor\",\n \"worst\",\n \"hate\",\n \"sad\",\n \"disappointing\",\n \"disaster\",\n \"failed\",\n \"broken\",\n \"useless\",\n \"angry\",\n \"annoying\",\n ];\n\n return tweets.map((tweet) => {\n if (!tweet.id) {\n console.warn(\"Missing tweet ID for rule-based sentiment analysis\");\n return {\n post_id: 0,\n sentiment: \"neutral\" as const,\n score: 0,\n confidence: 0.5,\n keywords: [],\n };\n }\n\n const content = tweet.content.toLowerCase();\n const words = content.split(/\\s+/);\n\n let positiveCount = 0;\n let negativeCount = 0;\n const foundKeywords: string[] = [];\n\n for (const word of words) {\n const cleanWord = word.replace(/[^\\w]/g, \"\");\n\n if (positiveWords.includes(cleanWord)) {\n positiveCount++;\n foundKeywords.push(cleanWord);\n }\n\n if (negativeWords.includes(cleanWord)) {\n negativeCount++;\n foundKeywords.push(cleanWord);\n }\n }\n\n // Calculate sentiment score (-1.0 to 1.0)\n const totalSentimentWords = positiveCount + negativeCount;\n let score = 0;\n let confidence = 0.5; // Default moderate confidence\n\n if (totalSentimentWords > 0) {\n score = (positiveCount - negativeCount) / totalSentimentWords;\n confidence = Math.min(\n 0.7,\n 0.5 + (totalSentimentWords / words.length) * 0.2,\n );\n }\n\n // Determine sentiment category\n let sentiment: \"positive\" | \"negative\" | \"neutral\" = \"neutral\";\n if (score > 0.2) {\n sentiment = \"positive\";\n } else if (score < -0.2) {\n sentiment = \"negative\";\n }\n\n return {\n post_id: tweet.id,\n sentiment,\n score,\n confidence,\n keywords: foundKeywords,\n };\n });\n }\n\n /**\n * Load sentiment analysis configuration from environment variables\n * @returns SentimentAnalysisConfig object based on environment variables\n */\n static loadConfigFromEnv(): SentimentAnalysisConfig {\n const config: SentimentAnalysisConfig = { ...DEFAULT_SENTIMENT_CONFIG };\n\n // Use AI for sentiment analysis\n const useAIEnv = Deno.env.get(\"TWITTER_SENTIMENT_USE_AI\");\n if (useAIEnv) {\n config.useAI = useAIEnv.toLowerCase() === \"true\";\n }\n\n // Confidence threshold\n const confidenceThresholdEnv = Deno.env.get(\n \"TWITTER_SENTIMENT_CONFIDENCE_THRESHOLD\",\n );\n if (confidenceThresholdEnv) {\n const threshold = parseFloat(confidenceThresholdEnv);\n if (!isNaN(threshold) && threshold >= 0 && threshold <= 1) {\n config.confidenceThreshold = threshold;\n }\n }\n\n // Batch size\n const batchSizeEnv = Deno.env.get(\"TWITTER_SENTIMENT_BATCH_SIZE\");\n if (batchSizeEnv) {\n const batchSize = parseInt(batchSizeEnv, 10);\n if (!isNaN(batchSize) && batchSize > 0) {\n config.batchSize = batchSize;\n }\n }\n\n // Include entities\n const includeEntitiesEnv = Deno.env.get(\n \"TWITTER_SENTIMENT_INCLUDE_ENTITIES\",\n );\n if (includeEntitiesEnv) {\n config.includeEntities = includeEntitiesEnv.toLowerCase() === \"true\";\n }\n\n // Requests per minute (rate limiting)\n const requestsPerMinuteEnv = Deno.env.get(\n \"TWITTER_SENTIMENT_REQUESTS_PER_MINUTE\",\n );\n if (requestsPerMinuteEnv) {\n const rpm = parseInt(requestsPerMinuteEnv, 10);\n if (!isNaN(rpm) && rpm > 0) {\n config.requestsPerMinute = rpm;\n }\n }\n\n return config;\n }\n}\n",[],[153,417],{"_104":425,"_95":426,"_154":427,"_156":155,"_157":139,"_158":428,"_160":161,"_106":429,"_100":32,"_163":320,"_165":430,"_166":22,"_167":-5,"_168":431,"_98":432},"844d8262-8a7c-11f0-81bc-0224a6c84d84","twitter-summarization-api.http.ts","844d830c-8a7c-11f0-81bc-0224a6c84d84",52,["D",1757092784854],"/**\n * HTTP endpoint for testing and manually triggering Twitter summarization\n * This provides a way to test the summarization functionality and manually generate summaries\n */\n\nimport { TwitterSummarizationService } from \"./twitter-summarization.ts\";\nimport { initializeDatabase } from \"./database/migrations.ts\";\nimport { getAllTopics, getSummarizationsForTopic } from \"./database/queries.ts\";\n\n/**\n * HTTP endpoint for tweet summarization operations\n */\nexport default async function (req: Request): Promise {\n // Set CORS headers for all responses\n const headers = new Headers({\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"GET, POST, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type\",\n \"Content-Type\": \"application/json\",\n });\n\n // Handle preflight OPTIONS request\n if (req.method === \"OPTIONS\") {\n return new Response(null, { headers, status: 204 });\n }\n\n try {\n const url = new URL(req.url);\n const action = url.searchParams.get(\"action\") || \"status\";\n\n // Initialize database\n await initializeDatabase();\n\n let responseData: any = {\n status: \"ok\",\n timestamp: new Date().toISOString(),\n };\n\n const summarizationService = new TwitterSummarizationService();\n\n if (action === \"test\") {\n // Test the summarization service with sample data\n console.log(\"🧪 Testing summarization service...\");\n \n const topics = await getAllTopics();\n \n if (topics.length === 0) {\n responseData = {\n ...responseData,\n action: \"test\",\n status: \"warning\",\n message: \"No topics found. Please create some topics first.\",\n topics: [],\n };\n } else {\n // Test with the first topic only (to avoid hitting rate limits during testing)\n const testTopic = topics[0];\n console.log(`Testing with topic: ${testTopic.title} (ID: ${testTopic.id})`);\n\n const startTime = Date.now();\n const summary = await summarizationService.generateTopicSummary(testTopic.id!, {\n timeWindowHours: 48, // Look back further for testing\n maxTweets: 20, // Fewer tweets for testing\n includeMedia: true,\n includeSentiment: true,\n });\n\n const executionTime = Date.now() - startTime;\n\n if (!summary) {\n responseData = {\n ...responseData,\n action: \"test\",\n status: \"no_data\",\n message: `No recent posts found for topic: ${testTopic.title}`,\n topicTested: testTopic,\n availableTopics: topics.map(t => ({ id: t.id, title: t.title })),\n executionTimeMs: executionTime,\n };\n } else {\n responseData = {\n ...responseData,\n action: \"test\",\n status: \"success\",\n message: \"Test summarization completed successfully\",\n testSummary: summary,\n availableTopics: topics.map(t => ({ id: t.id, title: t.title })),\n executionTimeMs: executionTime,\n };\n }\n }\n\n } else if (action === \"generate\") {\n // Generate summaries for all topics or specific topic\n const topicId = url.searchParams.get(\"topicId\");\n const timeWindowHours = parseInt(url.searchParams.get(\"timeWindowHours\") || \"24\");\n const maxTweets = parseInt(url.searchParams.get(\"maxTweets\") || \"50\");\n const includeMedia = url.searchParams.get(\"includeMedia\") !== \"false\";\n const includeSentiment = url.searchParams.get(\"includeSentiment\") !== \"false\";\n\n const options = {\n timeWindowHours,\n maxTweets,\n includeMedia,\n includeSentiment,\n };\n\n const startTime = Date.now();\n\n if (topicId) {\n // Generate summary for specific topic\n const topicIdNum = parseInt(topicId);\n if (isNaN(topicIdNum)) {\n return new Response(JSON.stringify({\n status: \"error\",\n message: \"Invalid topic ID\",\n }), { headers, status: 400 });\n }\n\n console.log(`🤖 Generating summary for topic ${topicIdNum} with options:`, options);\n\n const summary = await summarizationService.generateTopicSummary(topicIdNum, options);\n \n if (!summary) {\n responseData = {\n ...responseData,\n action: \"generate\",\n status: \"no_data\",\n message: `No recent posts found for topic ${topicIdNum}`,\n topicId: topicIdNum,\n };\n } else {\n // Store the summary in the database\n const summaryId = await summarizationService.storeTopicSummary(summary);\n const executionTime = Date.now() - startTime;\n\n responseData = {\n ...responseData,\n action: \"generate\",\n status: \"success\",\n message: \"Summary generated and stored successfully\",\n summary,\n summaryId,\n executionTimeMs: executionTime,\n };\n }\n } else {\n // Generate summaries for all topics\n console.log(\"🤖 Generating summaries for all topics with options:\", options);\n\n const result = await summarizationService.generateAndStoreSummaries(options);\n const executionTime = Date.now() - startTime;\n\n responseData = {\n ...responseData,\n action: \"generate\",\n status: result.success ? \"success\" : \"partial_success\",\n message: `Generated ${result.generated} summaries, stored ${result.stored}`,\n results: {\n generated: result.generated,\n stored: result.stored,\n errors: result.errors.length,\n },\n summaries: result.summaries.map(s => ({\n topicId: s.topicId,\n topicTitle: s.topicTitle,\n tweetCount: s.tweetCount,\n sentiment: s.overallSentiment.sentiment,\n keyPointsCount: s.keyPoints.length,\n })),\n errors: result.errors,\n executionTimeMs: executionTime,\n };\n }\n\n } else if (action === \"summaries\") {\n // Get stored summaries for a topic\n const topicId = url.searchParams.get(\"topicId\");\n if (!topicId) {\n return new Response(JSON.stringify({\n status: \"error\",\n message: \"topicId parameter is required for summaries action\",\n }), { headers, status: 400 });\n }\n\n const topicIdNum = parseInt(topicId);\n if (isNaN(topicIdNum)) {\n return new Response(JSON.stringify({\n status: \"error\",\n message: \"Invalid topic ID\",\n }), { headers, status: 400 });\n }\n\n const limit = parseInt(url.searchParams.get(\"limit\") || \"10\");\n const summaries = await getSummarizationsForTopic(topicIdNum, limit);\n\n responseData = {\n ...responseData,\n action: \"summaries\",\n topicId: topicIdNum,\n summaries: summaries.map(s => ({\n id: s.id,\n content: JSON.parse(s.content),\n created_at: s.created_at,\n time_period: `${s.time_period_start} to ${s.time_period_end}`,\n })),\n count: summaries.length,\n };\n\n } else if (action === \"topics\") {\n // List all available topics\n const topics = await getAllTopics();\n \n responseData = {\n ...responseData,\n action: \"topics\",\n topics: topics.map(t => ({\n id: t.id,\n title: t.title,\n description: t.description,\n })),\n count: topics.length,\n };\n\n } else {\n // Default status action\n responseData = {\n ...responseData,\n action: \"status\",\n message: \"Summarization API is running\",\n availableActions: [\n \"test - Test summarization with first available topic\",\n \"generate - Generate summaries (add ?topicId=X for specific topic)\",\n \"summaries - Get stored summaries (requires ?topicId=X)\",\n \"topics - List all available topics\",\n ],\n config: {\n timeWindowHours: parseInt(Deno.env.get(\"TWITTER_SUMMARIZATION_TIME_WINDOW\") || \"24\"),\n maxTweets: parseInt(Deno.env.get(\"TWITTER_SUMMARIZATION_MAX_TWEETS\") || \"50\"),\n includeMedia: Deno.env.get(\"TWITTER_SUMMARIZATION_INCLUDE_MEDIA\") !== \"false\",\n includeSentiment: Deno.env.get(\"TWITTER_SUMMARIZATION_INCLUDE_SENTIMENT\") !== \"false\",\n },\n };\n }\n\n return new Response(JSON.stringify(responseData, null, 2), { headers });\n\n } catch (error: unknown) {\n console.error(\"Error processing summarization request:\", error);\n\n return new Response(\n JSON.stringify({\n status: \"error\",\n message: error instanceof Error ? error.message : String(error),\n timestamp: new Date().toISOString(),\n }, null, 2),\n { headers, status: 500 },\n );\n }\n}",[],[153,426],{"_104":434,"_95":435,"_154":436,"_156":155,"_157":139,"_158":437,"_160":161,"_106":438,"_100":32,"_163":366,"_165":439,"_166":22,"_167":-5,"_168":440,"_98":441},"83f47b4a-8a7c-11f0-a88e-0224a6c84d84","twitter-summarization-job.cron.ts","83f47c12-8a7c-11f0-a88e-0224a6c84d84",38,["D",1757092784206],"/**\n * Scheduled job for generating AI-powered summaries of tweets grouped by topics\n * This cron job runs periodically to analyze recent tweets and generate summaries\n * \n * Configure this in Val Town's interface to run at your desired interval\n * Recommended: Every 6 hours or daily\n */\n\nimport { TwitterSummarizationService } from \"./twitter-summarization.ts\";\nimport { initializeDatabase } from \"./database/migrations.ts\";\nimport { email } from \"https://esm.town/v/std/email\";\n\nexport default async function (): Promise {\n const startTime = Date.now();\n console.log(\"🤖 Starting scheduled summarization job...\");\n\n try {\n // Initialize database\n await initializeDatabase();\n\n // Initialize the summarization service\n const summarizationService = new TwitterSummarizationService();\n\n // Configure summarization options\n const options = {\n timeWindowHours: parseInt(Deno.env.get(\"TWITTER_SUMMARIZATION_TIME_WINDOW\") || \"24\"),\n maxTweets: parseInt(Deno.env.get(\"TWITTER_SUMMARIZATION_MAX_TWEETS\") || \"50\"),\n includeMedia: Deno.env.get(\"TWITTER_SUMMARIZATION_INCLUDE_MEDIA\") !== \"false\",\n includeSentiment: Deno.env.get(\"TWITTER_SUMMARIZATION_INCLUDE_SENTIMENT\") !== \"false\",\n };\n\n console.log(\"📊 Summarization options:\", options);\n\n // Generate and store summaries\n const result = await summarizationService.generateAndStoreSummaries(options);\n\n // Calculate execution time\n const executionTime = Date.now() - startTime;\n\n // Log results\n console.log(\"📊 Summarization job completed:\");\n console.log(` - Generated: ${result.generated} summaries`);\n console.log(` - Stored: ${result.stored} summaries`);\n console.log(` - Errors: ${result.errors.length}`);\n console.log(` - Execution time: ${executionTime}ms`);\n\n if (result.errors.length > 0) {\n console.error(\"❌ Errors encountered:\");\n result.errors.forEach(error => console.error(` - ${error}`));\n }\n\n // Send email notification with results\n const shouldSendEmail = Deno.env.get(\"TWITTER_SUMMARIZATION_EMAIL_NOTIFICATIONS\") === \"true\";\n const userEmail = Deno.env.get(\"USER_EMAIL\");\n\n if (shouldSendEmail && userEmail) {\n try {\n await sendSummarizationEmail(result, executionTime, userEmail);\n console.log(\"📧 Email notification sent successfully\");\n } catch (emailError) {\n console.error(\"📧 Failed to send email notification:\", emailError);\n }\n }\n\n console.log(\"✅ Summarization job completed successfully\");\n\n } catch (error: unknown) {\n const executionTime = Date.now() - startTime;\n const errorMessage = `Summarization job failed: ${error}`;\n \n console.error(\"❌ Summarization job failed:\", error);\n\n // Try to send error notification email\n const shouldSendEmail = Deno.env.get(\"TWITTER_SUMMARIZATION_EMAIL_NOTIFICATIONS\") === \"true\";\n const userEmail = Deno.env.get(\"USER_EMAIL\");\n\n if (shouldSendEmail && userEmail) {\n try {\n await sendErrorEmail(error, executionTime, userEmail);\n console.log(\"📧 Error notification email sent\");\n } catch (emailError) {\n console.error(\"📧 Failed to send error notification email:\", emailError);\n }\n }\n\n throw error; // Re-throw to mark job as failed\n }\n}\n\n/**\n * Send email notification with summarization results\n */\nasync function sendSummarizationEmail(\n result: any,\n executionTime: number,\n recipientEmail: string,\n): Promise {\n const subject = `OffX: Summarization Report - ${result.generated} summaries generated`;\n \n const summariesList = result.summaries\n .map((s: any) => \n `• ${s.topicTitle}: ${s.tweetCount} tweets (${s.overallSentiment.sentiment} sentiment)`\n )\n .join('\\n');\n\n const html = `\n

🤖 Twitter Summarization Report

\n \n

📊 Summary

Generated: ${result.generated} summaries
Stored: ${result.stored} summaries
Execution time: ${(executionTime / 1000).toFixed(2)}s
Status: ${result.success ? '✅ Success' : '❌ Partial failure'}

\n\n ${result.summaries.length > 0 ? `\n

📝 Generated Summaries

${summariesList}

\n ` : ''}\n\n ${result.errors.length > 0 ? `\n

❌ Errors (${result.errors.length})

${error}

\n ` : ''}\n\n

Generated at ${new Date().toISOString()}

This is an automated report from your Twitter Summarization service.

To disable these notifications, set TWITTER_SUMMARIZATION_EMAIL_NOTIFICATIONS=false

\n `;\n\n const text = `\nTwitter Summarization Report\n\nGenerated: ${result.generated} summaries\nStored: ${result.stored} summaries\nExecution time: ${(executionTime / 1000).toFixed(2)}s\nStatus: ${result.success ? 'Success' : 'Partial failure'}\n\n${result.summaries.length > 0 ? `\nGenerated Summaries:\n${summariesList}\n` : ''}\n\n${result.errors.length > 0 ? `\nErrors (${result.errors.length}):\n${result.errors.map((error: string) => `- ${error}`).join('\\n')}\n` : ''}\n\nGenerated at ${new Date().toISOString()}\n `;\n\n await email({\n to: recipientEmail,\n subject,\n html,\n text,\n });\n}\n\n/**\n * Send error notification email\n */\nasync function sendErrorEmail(\n error: any,\n executionTime: number,\n recipientEmail: string,\n): Promise {\n const subject = \"OffX: Summarization Job Failed\";\n \n const html = `\n

❌ Summarization Job Failed

\n \n

Error Details

Error: ${error instanceof Error ? error.message : String(error) || error}

Execution time: ${(executionTime / 1000).toFixed(2)}s

Timestamp: ${new Date().toISOString()}

\n\n

Please check the logs for more details and consider investigating the issue.

You may want to check your OpenAI API key and quota limits.

\n `;\n\n const text = `\nSummarization Job Failed\n\nError: ${error instanceof Error ? error.message : String(error) || error}\nExecution time: ${(executionTime / 1000).toFixed(2)}s\nTimestamp: ${new Date().toISOString()}\n\nPlease check the logs for more details and consider investigating the issue.\n `;\n\n await email({\n to: recipientEmail,\n subject,\n html,\n text,\n });\n}",[],[153,435],{"_104":443,"_95":444,"_154":445,"_156":155,"_157":139,"_158":446,"_160":22,"_106":447,"_100":32,"_163":193,"_165":448,"_166":22,"_167":-5,"_168":449,"_98":450},"845e3558-8a7c-11f0-9d13-0224a6c84d84","twitter-summarization.ts","845e360c-8a7c-11f0-9d13-0224a6c84d84",55,["D",1757092784975],"import { openai } from \"https://esm.town/v/valtown/openai\";\nimport {\n createSummarization,\n getAllTopics,\n getPostsForTopic,\n getSummarizationsForTopic,\n} from \"./database/queries.ts\";\nimport type { Post, Topic } from \"./database/queries.ts\";\nimport { TwitterSentimentAnalyzer } from \"./twitter-sentiment.ts\";\n\n/**\n * OpenAI-powered summarization service for grouped tweets\n * Extends the existing sentiment analysis to provide topic-based summaries\n */\n\nexport interface TopicSummary {\n topicId: number;\n topicTitle: string;\n summary: string;\n keyPoints: string[];\n tweetCount: number;\n timeWindow: string;\n overallSentiment: {\n sentiment: \"positive\" | \"negative\" | \"neutral\";\n confidence: number;\n score: number;\n };\n trendingKeywords: string[];\n influentialAuthors: string[];\n}\n\nexport interface SummarizationRequest {\n topicId?: number;\n timeWindowHours?: number;\n maxTweets?: number;\n includeMedia?: boolean;\n includeSentiment?: boolean;\n}\n\nexport interface SummarizationResult {\n success: boolean;\n generated: number;\n stored: number;\n errors: string[];\n summaries: TopicSummary[];\n}\n\n/**\n * Service class for generating AI-powered summaries of tweets grouped by topics\n */\nexport class TwitterSummarizationService {\n private sentimentAnalyzer: TwitterSentimentAnalyzer;\n\n constructor() {\n // Initialize sentiment analyzer with default config\n this.sentimentAnalyzer = new TwitterSentimentAnalyzer();\n }\n\n /**\n * Generate a comprehensive summary for a specific topic\n */\n async generateTopicSummary(\n topicId: number,\n options: Omit = {},\n ): Promise {\n try {\n const {\n timeWindowHours = 24,\n maxTweets = 50,\n includeMedia = false,\n includeSentiment = true,\n } = options;\n\n // Get the topic details\n const topics = await getAllTopics();\n const topic = topics.find((t) => t.id === topicId);\n if (!topic) {\n throw new Error(`Topic with ID ${topicId} not found`);\n }\n\n // Get recent posts for this topic\n const posts = await getPostsForTopic(topicId, maxTweets);\n \n if (posts.length === 0) {\n console.log(`No posts found for topic ${topicId}`);\n return null;\n }\n\n // Filter posts by time window\n const cutoffTime = new Date(Date.now() - timeWindowHours * 60 * 60 * 1000);\n const recentPosts = posts.filter(post => \n new Date(post.created_at) > cutoffTime\n );\n\n if (recentPosts.length === 0) {\n console.log(`No recent posts found for topic ${topicId} in the last ${timeWindowHours} hours`);\n return null;\n }\n\n // Analyze sentiment if requested\n let sentimentData: {\n sentiment: \"positive\" | \"negative\" | \"neutral\";\n confidence: number;\n score: number;\n } | null = null;\n if (includeSentiment) {\n try {\n const sentimentResults = await this.sentimentAnalyzer.analyzeBatch(recentPosts);\n sentimentData = this.aggregateSentiment(sentimentResults);\n } catch (error: unknown) {\n console.warn(\"Failed to analyze sentiment, continuing without it:\", error);\n sentimentData = {\n sentiment: \"neutral\" as const,\n confidence: 0.5,\n score: 0,\n };\n }\n }\n\n // Group and format posts for summarization\n const groupedData = this.groupPostsForSummarization(recentPosts);\n\n // Generate summary using OpenAI\n const summary = await this.generateSummaryWithAI(topic, groupedData, sentimentData);\n\n // Create the final topic summary\n const topicSummary: TopicSummary = {\n topicId,\n topicTitle: topic.title,\n summary: summary.mainSummary,\n keyPoints: summary.keyPoints,\n tweetCount: recentPosts.length,\n timeWindow: `${timeWindowHours} hours`,\n overallSentiment: sentimentData || {\n sentiment: \"neutral\",\n confidence: 0.5,\n score: 0,\n },\n trendingKeywords: summary.trendingKeywords,\n influentialAuthors: summary.influentialAuthors,\n };\n\n return topicSummary;\n } catch (error: unknown) {\n console.error(`Error generating summary for topic ${topicId}:`, error);\n throw error;\n }\n }\n\n /**\n * Generate summaries for all topics with recent activity\n */\n async generateAllTopicSummaries(\n options: Omit = {},\n ): Promise {\n try {\n const topics = await getAllTopics();\n const summaries: TopicSummary[] = [];\n\n console.log(`Generating summaries for ${topics.length} topics...`);\n\n for (const topic of topics) {\n try {\n console.log(`Processing topic: ${topic.title} (ID: ${topic.id})`);\n const summary = await this.generateTopicSummary(topic.id!, options);\n if (summary) {\n summaries.push(summary);\n console.log(`✓ Generated summary for topic: ${topic.title}`);\n } else {\n console.log(`- No recent activity for topic: ${topic.title}`);\n }\n } catch (error: unknown) {\n console.error(`Failed to generate summary for topic ${topic.id} (${topic.title}):`, error);\n // Continue with other topics\n }\n }\n\n console.log(`Generated ${summaries.length} summaries successfully`);\n return summaries;\n } catch (error: unknown) {\n console.error(\"Error generating all topic summaries:\", error);\n throw error;\n }\n }\n\n /**\n * Store a topic summary in the database\n */\n async storeTopicSummary(topicSummary: TopicSummary): Promise {\n try {\n const summaryContent = JSON.stringify({\n summary: topicSummary.summary,\n keyPoints: topicSummary.keyPoints,\n sentiment: topicSummary.overallSentiment,\n tweetCount: topicSummary.tweetCount,\n timeWindow: topicSummary.timeWindow,\n trendingKeywords: topicSummary.trendingKeywords,\n influentialAuthors: topicSummary.influentialAuthors,\n });\n\n // Parse the time window to extract start and end dates\n const [startDate, endDate] = topicSummary.timeWindow.split(\" to \");\n\n const summarizationId = await createSummarization({\n topic_id: topicSummary.topicId,\n content: summaryContent,\n prompt: \"Topic summary generated automatically\",\n post_count: topicSummary.tweetCount,\n time_period_start: startDate.trim(),\n time_period_end: endDate.trim(),\n });\n\n return summarizationId;\n } catch (error: unknown) {\n console.error(\"Error storing topic summary:\", error);\n return null;\n }\n }\n\n /**\n * Generate and store summaries for all topics\n */\n async generateAndStoreSummaries(\n options: Omit = {},\n ): Promise {\n const errors: string[] = [];\n let generated = 0;\n let stored = 0;\n const summaries: TopicSummary[] = [];\n\n try {\n const generatedSummaries = await this.generateAllTopicSummaries(options);\n generated = generatedSummaries.length;\n summaries.push(...generatedSummaries);\n\n for (const summary of generatedSummaries) {\n try {\n const summaryId = await this.storeTopicSummary(summary);\n if (summaryId) {\n stored++;\n console.log(`✓ Stored summary for topic: ${summary.topicTitle} (ID: ${summaryId})`);\n } else {\n const error = `Failed to store summary for topic ${summary.topicId} (${summary.topicTitle})`;\n errors.push(error);\n console.error(error);\n }\n } catch (error: unknown) {\n const errorMessage = `Error storing summary for topic ${summary.topicId} (${summary.topicTitle}): ${error}`;\n errors.push(errorMessage);\n console.error(errorMessage);\n }\n }\n\n return { \n success: errors.length === 0,\n generated, \n stored, \n errors,\n summaries,\n };\n } catch (error: unknown) {\n const errorMessage = `Error in generateAndStoreSummaries: ${error}`;\n errors.push(errorMessage);\n console.error(errorMessage);\n return { \n success: false,\n generated, \n stored, \n errors,\n summaries,\n };\n }\n }\n\n /**\n * Group posts for effective summarization\n */\n private groupPostsForSummarization(posts: Post[]): {\n authorCounts: Record;\n contentSample: string[];\n mediaCount: number;\n timeSpread: { earliest: string; latest: string };\n } {\n const authorCounts: Record = {};\n const contentSample: string[] = [];\n let mediaCount = 0;\n\n // Count authors and collect content\n for (const post of posts) {\n authorCounts[post.author] = (authorCounts[post.author] || 0) + 1;\n contentSample.push(`[@${post.author}]: ${post.content}`);\n \n // Count media (this would need to be enhanced based on actual media data structure)\n if (post.content.includes('http') || post.content.includes('pic.twitter.com')) {\n mediaCount++;\n }\n }\n\n // Calculate time spread\n const timestamps = posts.map(p => new Date(p.created_at).getTime()).sort();\n const timeSpread = {\n earliest: new Date(timestamps[0]).toISOString(),\n latest: new Date(timestamps[timestamps.length - 1]).toISOString(),\n };\n\n return {\n authorCounts,\n contentSample: contentSample.slice(0, 20), // Limit for token efficiency\n mediaCount,\n timeSpread,\n };\n }\n\n /**\n * Generate summary using OpenAI\n */\n private async generateSummaryWithAI(\n topic: Topic,\n groupedData: ReturnType,\n sentimentData: any,\n ): Promise<{\n mainSummary: string;\n keyPoints: string[];\n trendingKeywords: string[];\n influentialAuthors: string[];\n }> {\n const prompt = this.buildSummarizationPrompt(topic, groupedData, sentimentData);\n\n try {\n const response = await openai.chat.completions.create({\n model: \"gpt-3.5-turbo\",\n messages: [\n {\n role: \"system\",\n content: `You are an expert social media analyst specializing in Twitter content summarization. \n Provide concise, insightful summaries that capture the key themes, sentiment, and notable patterns in the conversation.\n Always respond with valid JSON in the exact format requested.`,\n },\n {\n role: \"user\",\n content: prompt,\n },\n ],\n max_tokens: 800,\n temperature: 0.7,\n response_format: { type: \"json_object\" },\n });\n\n const result = response.choices[0].message.content?.trim();\n if (!result) {\n throw new Error(\"No response from OpenAI\");\n }\n\n const summaryData = JSON.parse(result);\n \n // Validate response structure\n if (!summaryData.mainSummary || !Array.isArray(summaryData.keyPoints)) {\n throw new Error(\"Invalid response format from OpenAI\");\n }\n\n return {\n mainSummary: summaryData.mainSummary,\n keyPoints: summaryData.keyPoints || [],\n trendingKeywords: summaryData.trendingKeywords || [],\n influentialAuthors: summaryData.influentialAuthors || [],\n };\n } catch (error: unknown) {\n console.error(\"Error generating summary with AI:\", error);\n \n // Fallback to simple summary\n return this.generateFallbackSummary(topic, groupedData);\n }\n }\n\n /**\n * Build the summarization prompt for OpenAI\n */\n private buildSummarizationPrompt(\n topic: Topic,\n groupedData: ReturnType,\n sentimentData: any,\n ): string {\n const { authorCounts, contentSample, mediaCount, timeSpread } = groupedData;\n \n const topAuthors = Object.entries(authorCounts)\n .sort(([,a], [,b]) => b - a)\n .slice(0, 5)\n .map(([author, count]) => `${author} (${count} posts)`);\n\n const sentimentInfo = sentimentData \n ? `Overall sentiment: ${sentimentData.sentiment} (confidence: ${sentimentData.confidence.toFixed(2)}, score: ${sentimentData.score.toFixed(2)})`\n : \"Sentiment analysis not available\";\n\n return `\nAnalyze and summarize the following Twitter conversation about \"${topic.title}\":\n\nTOPIC DESCRIPTION: ${topic.description || \"No description provided\"}\n\nCONVERSATION DATA:\n- Total posts: ${contentSample.length}\n- Time range: ${timeSpread.earliest} to ${timeSpread.latest}\n- Posts with media: ${mediaCount}\n- ${sentimentInfo}\n\nTOP CONTRIBUTORS: ${topAuthors.join(\", \")}\n\nSAMPLE POSTS:\n${contentSample.join(\"\\n\\n\")}\n\nPlease provide a comprehensive analysis in the following JSON format:\n{\n \"mainSummary\": \"A 2-3 sentence overview of the main themes and discussion points\",\n \"keyPoints\": [\"Point 1\", \"Point 2\", \"Point 3\", \"Point 4\", \"Point 5\"],\n \"trendingKeywords\": [\"keyword1\", \"keyword2\", \"keyword3\", \"keyword4\", \"keyword5\"],\n \"influentialAuthors\": [\"author1\", \"author2\", \"author3\"]\n}\n\nFocus on:\n1. The main themes and topics being discussed\n2. Any notable trends, events, or developments mentioned\n3. The overall tone and sentiment of the conversation\n4. Key players or influencers in the discussion\n5. Important keywords that capture the essence of the conversation\n\nProvide only valid JSON, no additional text.\n`;\n }\n\n /**\n * Generate a simple fallback summary when AI fails\n */\n private generateFallbackSummary(\n topic: Topic,\n groupedData: ReturnType,\n ): {\n mainSummary: string;\n keyPoints: string[];\n trendingKeywords: string[];\n influentialAuthors: string[];\n } {\n const { authorCounts, contentSample, mediaCount } = groupedData;\n \n const topAuthors = Object.entries(authorCounts)\n .sort(([,a], [,b]) => b - a)\n .slice(0, 3)\n .map(([author]) => author);\n\n return {\n mainSummary: `Discussion about ${topic.title} with ${contentSample.length} posts from ${Object.keys(authorCounts).length} contributors. ${mediaCount} posts included media content.`,\n keyPoints: [\n `${contentSample.length} total posts analyzed`,\n `${Object.keys(authorCounts).length} unique contributors`,\n `${mediaCount} posts with media content`,\n `Most active contributor: ${topAuthors[0] || \"Unknown\"}`,\n \"Detailed analysis unavailable due to processing error\",\n ],\n trendingKeywords: [topic.title.toLowerCase()],\n influentialAuthors: topAuthors,\n };\n }\n\n /**\n * Aggregate sentiment analysis results\n */\n private aggregateSentiment(sentimentResults: any[]): {\n sentiment: \"positive\" | \"negative\" | \"neutral\";\n confidence: number;\n score: number;\n } {\n if (sentimentResults.length === 0) {\n return { sentiment: \"neutral\", confidence: 0.5, score: 0 };\n }\n\n // Calculate average sentiment score and confidence\n const avgScore = sentimentResults.reduce((sum, result) => sum + result.score, 0) / sentimentResults.length;\n const avgConfidence = sentimentResults.reduce((sum, result) => sum + result.confidence, 0) / sentimentResults.length;\n\n // Determine overall sentiment based on average score\n let sentiment: \"positive\" | \"negative\" | \"neutral\" = \"neutral\";\n if (avgScore > 0.1) {\n sentiment = \"positive\";\n } else if (avgScore < -0.1) {\n sentiment = \"negative\";\n }\n\n return {\n sentiment,\n confidence: avgConfidence,\n score: avgScore,\n };\n }\n\n /**\n * Get recent summaries for a topic (for checking if summarization is needed)\n */\n async getRecentSummaries(topicId: number, hoursBack: number = 24): Promise {\n try {\n return await getSummarizationsForTopic(topicId, 10); // Get up to 10 recent summaries\n } catch (error: unknown) {\n console.error(`Error getting recent summaries for topic ${topicId}:`, error);\n return [];\n }\n }\n}",[],[153,444],{"_104":452,"_95":453,"_154":454,"_156":155,"_157":139,"_158":455,"_160":22,"_106":456,"_100":32,"_163":320,"_165":457,"_166":22,"_167":-5,"_168":458,"_98":459},"848742b8-8a7c-11f0-af15-0224a6c84d84","twitter-test.http.ts","8487434e-8a7c-11f0-af15-0224a6c84d84",60,["D",1757092784925],"import { initializeTwitterClient, storeTweets } from \"./twitter-api.ts\";\nimport { initializeDatabase } from \"./database/migrations.ts\";\nimport { getRecentPosts } from \"./database/queries.ts\";\nimport { TwitterProcessor } from \"./twitter-processor.ts\";\n\n/**\n * HTTP endpoint to test Twitter API integration\n * This endpoint allows manual triggering of the Twitter fetch process\n * and returns diagnostic information\n */\nexport default async function (req: Request): Promise {\n // Check for basic auth\n const authHeader = req.headers.get(\"Authorization\");\n if (!authHeader || !authHeader.startsWith(\"Basic \")) {\n return new Response(\"Unauthorized\", {\n status: 401,\n headers: { \"WWW-Authenticate\": \"Basic\" },\n });\n }\n\n const base64Credentials = authHeader.split(\" \")[1];\n const credentials = atob(base64Credentials);\n const [username, password] = credentials.split(\":\");\n\n const expectedUsername = Deno.env.get(\"AUTH_USERNAME\");\n const expectedPassword = Deno.env.get(\"AUTH_PASSWORD\");\n\n if (username !== expectedUsername || password !== expectedPassword) {\n return new Response(\"Unauthorized\", {\n status: 401,\n headers: { \"WWW-Authenticate\": \"Basic\" },\n });\n }\n\n // Process the request\n try {\n const url = new URL(req.url);\n const action = url.searchParams.get(\"action\") || \"status\";\n\n // Initialize database\n await initializeDatabase();\n\n let responseData: any = {\n status: \"ok\",\n timestamp: new Date().toISOString(),\n };\n\n if (action === \"fetch\") {\n // Get processing options from query params\n const includeRetweets = url.searchParams.get(\"retweets\") === \"true\";\n const includeReplies = url.searchParams.get(\"replies\") === \"true\";\n const keywords = url.searchParams.get(\"keywords\")?.split(\",\").map((k) =>\n k.trim()\n ) || undefined;\n\n // Create processor config\n const processorConfig = {\n includeRetweets,\n includeReplies,\n keywords,\n };\n\n // Fetch tweets from Twitter API\n const twitterClient = initializeTwitterClient();\n const rawTweets = await twitterClient.fetchHomeTimeline(100);\n\n // Process tweets\n const processor = new TwitterProcessor(processorConfig);\n const processedTweets = processor.processTweets(rawTweets);\n\n // Store tweets\n const newTweetsCount = await storeTweets(processedTweets);\n\n responseData = {\n ...responseData,\n action: \"fetch\",\n fetchedCount: rawTweets.length,\n processedCount: processedTweets.length,\n newCount: newTweetsCount,\n processorConfig,\n tweets: processedTweets.slice(0, 5), // Return first 5 tweets as preview\n };\n } else if (action === \"recent\") {\n // Get recent posts from database\n const limit = parseInt(url.searchParams.get(\"limit\") || \"10\", 10);\n const recentPosts = await getRecentPosts(limit);\n\n responseData = {\n ...responseData,\n action: \"recent\",\n count: recentPosts.length,\n posts: recentPosts,\n };\n } else if (action === \"config\") {\n // Get current processor configuration from environment\n const config = TwitterProcessor.loadConfigFromEnv();\n\n responseData = {\n ...responseData,\n action: \"config\",\n config,\n };\n }\n\n return new Response(JSON.stringify(responseData, null, 2), {\n status: 200,\n headers: { \"Content-Type\": \"application/json\" },\n });\n } catch (error: unknown) {\n console.error(\"Error in Twitter test endpoint:\", error);\n\n return new Response(\n JSON.stringify(\n {\n status: \"error\",\n message: error instanceof Error ? error.message : String(error),\n timestamp: new Date().toISOString(),\n },\n null,\n 2,\n ),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n}\n",[],[153,453],[153],{"_104":462,"_95":463,"_154":464,"_156":-5,"_157":139,"_158":119,"_160":161,"_106":465,"_100":32,"_163":164,"_165":-5,"_166":22,"_167":-5,"_168":466,"_98":564},"265c7ee6-55f3-11f0-894e-f69ea79377d9","frontend","265c7fb8-55f3-11f0-894e-f69ea79377d9",["D",1751316325744],[467,545,555],{"_104":468,"_95":469,"_154":470,"_156":464,"_157":139,"_158":319,"_160":161,"_106":471,"_100":32,"_163":164,"_165":-5,"_166":22,"_167":-5,"_168":472,"_98":544},"0698589e-55f5-11f0-9cfc-f69ea79377d9","components","069859e8-55f5-11f0-9cfc-f69ea79377d9",["D",1751317131440],[473,482,491,500,508,517,526,535],{"_104":474,"_95":475,"_154":476,"_156":470,"_157":139,"_158":477,"_160":22,"_106":478,"_100":32,"_163":193,"_165":479,"_166":22,"_167":-5,"_168":480,"_98":481},"fddc1736-56bc-11f0-824f-f69ea79377d9","App.tsx","fddc183a-56bc-11f0-824f-f69ea79377d9",23,["D",1751403016131],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React from \"https://esm.sh/react@18.2.0\";\nimport { Outlet } from \"https://esm.sh/react-router-dom@6.22.3?deps=react@18.2.0\";\n\nexport default function App() {\n return (\n

OffX

Twitter Feed Summarizer

\n\n

\n \n

\n\n \n

\n );\n}\n",[],[463,469,475],{"_104":483,"_95":484,"_154":485,"_156":470,"_157":139,"_158":486,"_160":161,"_106":487,"_100":32,"_163":193,"_165":488,"_166":22,"_167":-5,"_168":489,"_98":490},"fde4fd38-56bc-11f0-aabd-f69ea79377d9","AuthContext.tsx","fde4fdec-56bc-11f0-aabd-f69ea79377d9",25,["D",1751403016176],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React, {\n createContext,\n useContext,\n useState,\n} from \"https://esm.sh/react@18.2.0\";\nimport {\n Navigate,\n useLocation,\n} from \"https://esm.sh/react-router-dom@6.22.3?deps=react@18.2.0\";\n\ninterface AuthContextType {\n user: string | null;\n signin: (username: string, password: string) => Promise;\n signout: () => void;\n}\n\nconst AuthContext = createContext(null!);\n\nexport function AuthProvider({ children }: { children: React.ReactNode }) {\n const [user, setUser] = useState(null);\n\n const signin = async (username: string, password: string) => {\n try {\n // Create basic auth header\n const authHeader = \"Basic \" + btoa(username + \":\" + password);\n\n const response = await fetch(\"/api/login\", {\n headers: {\n \"Authorization\": authHeader,\n },\n });\n\n if (response.ok) {\n setUser(username);\n // Store auth in sessionStorage for persistence\n sessionStorage.setItem(\"auth\", authHeader);\n return true;\n } else {\n return false;\n }\n } catch (error) {\n console.error(\"Login error:\", error);\n return false;\n }\n };\n\n const signout = () => {\n setUser(null);\n sessionStorage.removeItem(\"auth\");\n };\n\n // Check if we have auth in sessionStorage on mount\n React.useEffect(() => {\n const auth = sessionStorage.getItem(\"auth\");\n if (auth) {\n // Verify the auth is still valid\n fetch(\"/api/login\", {\n headers: {\n \"Authorization\": auth,\n },\n }).then((response) => {\n if (response.ok) {\n // Extract username from Basic auth\n try {\n const decoded = atob(auth.replace(\"Basic \", \"\"));\n const username = decoded.split(\":\")[0];\n setUser(username);\n } catch (e) {\n console.error(\"Failed to decode auth\", e);\n sessionStorage.removeItem(\"auth\");\n }\n } else {\n sessionStorage.removeItem(\"auth\");\n }\n }).catch(() => {\n sessionStorage.removeItem(\"auth\");\n });\n }\n }, []);\n\n const value = { user, signin, signout };\n\n return {children};\n}\n\nexport function useAuth() {\n return useContext(AuthContext);\n}\n\nexport function RequireAuth({ children }: { children: JSX.Element }) {\n const auth = useAuth();\n const location = useLocation();\n\n if (!auth.user) {\n // Redirect to the login page but save the current location\n return ;\n }\n\n return children;\n}\n",[],[463,469,484],{"_104":492,"_95":493,"_154":494,"_156":470,"_157":139,"_158":495,"_160":22,"_106":496,"_100":32,"_163":193,"_165":497,"_166":22,"_167":-5,"_168":498,"_98":499},"83dde2a4-8a7c-11f0-af15-0224a6c84d84","Configuration.tsx","83dde36c-8a7c-11f0-af15-0224a6c84d84",35,["D",1757092784133],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React from \"https://esm.sh/react@18.2.0\";\nimport { useQuery } from \"https://esm.sh/@tanstack/react-query@4.29.5\";\n\n// Types\ninterface AppConfiguration {\n email: {\n enabled: boolean;\n recipientEmail: string | null;\n frequency: string;\n maxSummaries: number;\n jobNotifications: boolean;\n adminEmail: string | null;\n };\n twitter: {\n summarization: {\n timeWindowHours: number;\n maxTweets: number;\n includeMedia: boolean;\n includeSentiment: boolean;\n emailNotifications: boolean;\n };\n filtering: {\n keywords: string[];\n excludeKeywords: string[];\n };\n };\n\n system: {\n environment: string;\n lastUpdated: string;\n };\n}\n\ninterface SystemStatus {\n services: {\n database: { status: string; message: string };\n email: { status: string; message: string };\n twitter: { status: string; message: string };\n };\n configuration: {\n requiredEnvVars: { [key: string]: boolean };\n optionalEnvVars: { [key: string]: boolean };\n };\n lastChecked: string;\n}\n\n// API functions\nconst API_BASE = \"/api\";\n\nconst fetchConfiguration = async (): Promise => {\n const response = await fetch(`${API_BASE}/config`);\n if (!response.ok) {\n throw new Error(\"Failed to fetch configuration\");\n }\n return response.json();\n};\n\nconst fetchSystemStatus = async (): Promise => {\n const response = await fetch(`${API_BASE}/config/status`);\n if (!response.ok) {\n throw new Error(\"Failed to fetch system status\");\n }\n return response.json();\n};\n\n// Helper components\nconst StatusBadge: React.FC<{ status: string }> = ({ status }) => {\n const getStatusColor = (status: string) => {\n switch (status.toLowerCase()) {\n case \"healthy\":\n case \"configured\":\n return \"bg-green-100 text-green-800\";\n case \"disabled\":\n return \"bg-yellow-100 text-yellow-800\";\n case \"unhealthy\":\n case \"misconfigured\":\n return \"bg-red-100 text-red-800\";\n default:\n return \"bg-gray-100 text-gray-800\";\n }\n };\n\n return (\n \n {status}\n \n );\n};\n\nconst ConfigSection: React.FC<{ title: string; children: React.ReactNode }> = ({ title, children }) => (\n

{title}

\n {children}\n

\n);\n\nconst ConfigRow: React.FC<{ label: string; value: React.ReactNode; description?: string }> = ({ \n label, \n value, \n description \n}) => (\n

{label}

\n {description &&

{description}

}\n

{value}

\n);\n\nexport default function Configuration() {\n const {\n data: config,\n isLoading: configLoading,\n error: configError,\n } = useQuery({\n queryKey: [\"configuration\"],\n queryFn: fetchConfiguration,\n refetchInterval: 30000, // Refresh every 30 seconds\n });\n\n const {\n data: status,\n isLoading: statusLoading,\n error: statusError,\n } = useQuery({\n queryKey: [\"system-status\"],\n queryFn: fetchSystemStatus,\n refetchInterval: 30000, // Refresh every 30 seconds\n });\n\n if (configLoading || statusLoading) {\n return (\n

\n {[1, 2, 3, 4].map((i) => (\n

\n ))}\n

\n );\n }\n\n if (configError || statusError) {\n return (\n

Error Loading Configuration

{configError?.message || statusError?.message || \"Unknown error occurred\"}

\n );\n }\n\n if (!config || !status) {\n return (\n

No configuration data available

\n );\n }\n\n return (\n

\n {/* Header */}\n

System Configuration

\n Current application settings and system status\n

\n Last updated: {new Date(config.system.lastUpdated).toLocaleString()}\n

\n Environment: {config.system.environment}\n

\n\n {/* System Status */}\n \n

\n }\n description={status.services.database.message}\n />\n }\n description={status.services.email.message}\n />\n }\n description={status.services.twitter.message}\n />\n \n \n\n {/* Email Configuration */}\n \n

\n \n \n \n \n \n \n \n \n\n {/* Twitter & Summarization */}\n \n

\n \n \n \n \n \n \n \n\n {/* Filtering */}\n \n

\n 0\n ? config.twitter.filtering.keywords.join(\", \")\n : \"None\"\n }\n description=\"Only process tweets containing these keywords\"\n />\n 0\n ? config.twitter.filtering.excludeKeywords.join(\", \")\n : \"None\"\n }\n description=\"Skip tweets containing these keywords\"\n />\n \n \n\n\n {/* Environment Variables Status */}\n \n

Required Variables

{key}: \n \n {configured ? \"Set\" : \"Missing\"}\n \n

Optional Variables

{key}: \n \n {configured ? \"Set\" : \"Default\"}\n \n

\n \n\n {/* Help Text */}\n

\n \n

Configuration Management

\n To modify these settings, update the environment variables in Val Town's interface. \n Changes will be reflected here after the next restart or refresh.\n

\n );\n}",[],[463,469,493],{"_104":501,"_95":502,"_154":503,"_156":470,"_157":139,"_158":101,"_160":161,"_106":504,"_100":119,"_163":193,"_165":505,"_166":22,"_167":-5,"_168":506,"_98":507},"84d4378a-8a7c-11f0-87c1-0224a6c84d84","Dashboard.tsx","fde198a0-56bc-11f0-b7ab-f69ea79377d9",["D",1757092785713],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React, { useState } from \"https://esm.sh/react@18.2.0\";\nimport { useAuth } from \"./AuthContext.tsx\";\nimport { useNavigate } from \"https://esm.sh/react-router-dom@6.22.3?deps=react@18.2.0\";\nimport TopicManagement from \"./TopicManagement.tsx\";\nimport Configuration from \"./Configuration.tsx\";\nimport SummarizationsList from \"./SummarizationsList.tsx\";\n\nexport default function Dashboard() {\n const auth = useAuth();\n const navigate = useNavigate();\n const [activeTab, setActiveTab] = useState<\"overview\" | \"topics\" | \"summaries\" | \"config\">(\"overview\");\n\n const handleLogout = () => {\n auth.signout();\n navigate(\"/\");\n };\n\n const tabs = [\n { id: \"overview\" as const, label: \"Overview\", icon: \"📊\" },\n { id: \"topics\" as const, label: \"Topics\", icon: \"📝\" },\n { id: \"summaries\" as const, label: \"Summaries\", icon: \"📋\" },\n { id: \"config\" as const, label: \"Configuration\", icon: \"⚙️\" },\n ];\n\n return (\n

Dashboard

Welcome, {auth.user}!

\n \n

\n\n {/* Tab Navigation */}\n

\n {tabs.map((tab) => (\n setActiveTab(tab.id)}\n className={`${\n activeTab === tab.id\n ? \"border-blue-500 text-blue-600\"\n : \"border-transparent text-gray-500 hover:text-gray-700 hover:border-gray-300\"\n } whitespace-nowrap py-2 px-1 border-b-2 font-medium text-sm flex items-center gap-2`}\n >\n {tab.icon}\n {tab.label}\n \n ))}\n

\n\n {/* Tab Content */}\n {activeTab === \"overview\" && (\n

Recent Summaries

No summaries generated yet.

\n \n

Quick Stats

System statistics will appear here.

\n )}\n\n {activeTab === \"topics\" && }\n\n {activeTab === \"summaries\" && }\n\n {activeTab === \"config\" && }\n

\n );\n}\n",[],[463,469,502],{"_104":509,"_95":510,"_154":511,"_156":470,"_157":139,"_158":512,"_160":161,"_106":513,"_100":32,"_163":193,"_165":514,"_166":22,"_167":-5,"_168":515,"_98":516},"fe22a7c8-56bc-11f0-8697-f69ea79377d9","LoginPage.tsx","fe22a8ea-56bc-11f0-8697-f69ea79377d9",30,["D",1751403016145],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React, { useState } from \"https://esm.sh/react@18.2.0\";\nimport {\n useLocation,\n useNavigate,\n} from \"https://esm.sh/react-router-dom@6.22.3?deps=react@18.2.0\";\nimport { useAuth } from \"./AuthContext.tsx\";\n\ninterface LocationState {\n from?: {\n pathname: string;\n };\n}\n\nexport default function LoginPage() {\n const navigate = useNavigate();\n const location = useLocation();\n const auth = useAuth();\n\n const [username, setUsername] = useState(\"\");\n const [password, setPassword] = useState(\"\");\n const [error, setError] = useState(\"\");\n const [loading, setLoading] = useState(false);\n\n const locationState = location.state as LocationState;\n const from = locationState?.from?.pathname || \"/dashboard\";\n\n const handleSubmit = async (e: React.FormEvent) => {\n e.preventDefault();\n setError(\"\");\n setLoading(true);\n\n try {\n const result = await auth.signin(username, password);\n\n if (result) {\n // Send them back to the page they tried to visit when they were\n // redirected to the login page. Use { replace: true } so we don't create\n // another entry in the history stack for the login page.\n navigate(from, { replace: true });\n } else {\n setError(\"Invalid username or password\");\n }\n } catch (error) {\n setError(\"An unexpected error occurred. Please try again.\");\n console.error(\"Login error:\", error);\n } finally {\n setLoading(false);\n }\n };\n\n // If user is already logged in, redirect to dashboard\n React.useEffect(() => {\n if (auth.user) {\n navigate(\"/dashboard\", { replace: true });\n }\n }, [auth.user, navigate]);\n\n return (\n

Welcome to OffX

\n This application helps you summarize your Twitter feed using AI.\n

\n\n

Dashboard Access

\n Login to access your dashboard and manage your summaries.\n

\n\n \n

\n );\n}\n",[],[463,469,510],{"_104":518,"_95":519,"_154":520,"_156":470,"_157":139,"_158":521,"_160":22,"_106":522,"_100":32,"_163":193,"_165":523,"_166":22,"_167":-5,"_168":524,"_98":525},"83fee1ca-8a7c-11f0-b5d4-0224a6c84d84","SummarizationsList.tsx","83fee2ce-8a7c-11f0-b5d4-0224a6c84d84",39,["D",1757092784182],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React, { useState } from \"https://esm.sh/react@18.2.0\";\nimport { useQuery } from \"https://esm.sh/@tanstack/react-query@4.29.5\";\nimport { useNavigate } from \"https://esm.sh/react-router-dom@6.22.3?deps=react@18.2.0\";\nimport ReactPaginate from \"https://esm.sh/react-paginate@8.2.0\";\n\ninterface Summarization {\n id: number;\n topic_id: number;\n content: string;\n prompt: string;\n post_count: number;\n created_at: string;\n time_period_start: string;\n time_period_end: string;\n topic_title?: string;\n}\n\ninterface PaginationInfo {\n page: number;\n limit: number;\n totalCount: number;\n totalPages: number;\n hasNext: boolean;\n hasPrev: boolean;\n}\n\ninterface SummarizationsResponse {\n data: Summarization[];\n pagination: PaginationInfo;\n}\n\nconst API_BASE = \"/api\";\n\nexport default function SummarizationsList() {\n const [currentPage, setCurrentPage] = useState(1);\n const [searchTerm, setSearchTerm] = useState(\"\");\n const [selectedTopicId, setSelectedTopicId] = useState(\"\");\n const navigate = useNavigate();\n const itemsPerPage = 10;\n\n // Fetch summarizations with pagination\n const { data: summarizationsData, isLoading, error } = useQuery({\n queryKey: [\"summarizations\", currentPage, selectedTopicId, searchTerm],\n queryFn: async () => {\n const params = new URLSearchParams({\n page: currentPage.toString(),\n limit: itemsPerPage.toString(),\n });\n \n if (selectedTopicId) {\n params.append(\"topic_id\", selectedTopicId);\n }\n \n if (searchTerm) {\n params.append(\"search\", searchTerm);\n }\n\n const response = await fetch(`${API_BASE}/summarizations?${params}`, {\n headers: {\n 'Authorization': `Basic ${btoa(`${localStorage.getItem('auth_username')}:${localStorage.getItem('auth_password')}`)}`,\n },\n });\n \n if (!response.ok) {\n throw new Error(\"Failed to fetch summarizations\");\n }\n \n return response.json();\n },\n });\n\n // Fetch topics for filter dropdown\n const { data: topicsData } = useQuery({\n queryKey: [\"topics\"],\n queryFn: async () => {\n const response = await fetch(`${API_BASE}/topics`, {\n headers: {\n 'Authorization': `Basic ${btoa(`${localStorage.getItem('auth_username')}:${localStorage.getItem('auth_password')}`)}`,\n },\n });\n \n if (!response.ok) {\n throw new Error(\"Failed to fetch topics\");\n }\n \n return response.json();\n },\n });\n\n const handlePageChange = (selectedItem: { selected: number }) => {\n setCurrentPage(selectedItem.selected + 1);\n };\n\n const handleSearchChange = (e: React.ChangeEvent) => {\n setSearchTerm(e.target.value);\n setCurrentPage(1); // Reset to first page when searching\n };\n\n const handleTopicFilterChange = (e: React.ChangeEvent) => {\n setSelectedTopicId(e.target.value);\n setCurrentPage(1); // Reset to first page when filtering\n };\n\n const formatDate = (dateString: string) => {\n return new Date(dateString).toLocaleDateString(\"en-US\", {\n year: \"numeric\",\n month: \"short\",\n day: \"numeric\",\n hour: \"2-digit\",\n minute: \"2-digit\",\n });\n };\n\n const getExcerpt = (content: string, maxLength: number = 150) => {\n if (content.length <= maxLength) return content;\n return content.substring(0, maxLength) + \"...\";\n };\n\n const handleViewDetails = (summarizationId: number) => {\n navigate(`/summary/${summarizationId}`);\n };\n\n if (isLoading) {\n return (\n

\n {[...Array(5)].map((_, i) => (\n

\n ))}\n

\n );\n }\n\n if (error) {\n return (\n

Error loading summarizations

{error instanceof Error ? error.message : \"Unknown error occurred\"}

\n );\n }\n\n const summarizations = summarizationsData?.data || [];\n const pagination = summarizationsData?.pagination;\n\n return (\n

Summarizations

\n \n {/* Search and Filter Controls */}\n

\n \n

\n \n \n {topicsData?.data?.map((topic: any) => (\n \n ))}\n \n

\n\n {/* Summarizations List */}\n {summarizations.length === 0 ? (\n

No summarizations found.

\n {(searchTerm || selectedTopicId) && (\n {\n setSearchTerm(\"\");\n setSelectedTopicId(\"\");\n setCurrentPage(1);\n }}\n className=\"mt-2 text-blue-600 hover:text-blue-800\"\n >\n Clear filters\n \n )}\n

\n ) : (\n

\n {summarizations.map((summarization) => (\n \n

\n {summarization.topic_title || `Topic ${summarization.topic_id}`}\n

\n {formatDate(summarization.created_at)} • {summarization.post_count} posts\n

\n handleViewDetails(summarization.id)}\n className=\"bg-blue-500 hover:bg-blue-600 text-white px-3 py-1 rounded text-sm\"\n >\n View Details\n \n

\n \n

\n {getExcerpt(summarization.content)}\n

\n \n

\n Period: {formatDate(summarization.time_period_start)} - {formatDate(summarization.time_period_end)}\n

\n ))}\n

\n )}\n\n {/* Pagination */}\n {pagination && pagination.totalPages > 1 && (\n

\n \n

\n )}\n\n {/* Results Summary */}\n {pagination && (\n

\n Showing {Math.min((currentPage - 1) * itemsPerPage + 1, pagination.totalCount)} to{\" \"}\n {Math.min(currentPage * itemsPerPage, pagination.totalCount)} of {pagination.totalCount} results\n

\n )}\n \n );\n}",[],[463,469,519],{"_104":527,"_95":528,"_154":529,"_156":470,"_157":139,"_158":530,"_160":22,"_106":531,"_100":32,"_163":193,"_165":532,"_166":22,"_167":-5,"_168":533,"_98":534},"83d4e1d6-8a7c-11f0-9d13-0224a6c84d84","SummaryDetailView.tsx","83d4e280-8a7c-11f0-9d13-0224a6c84d84",34,["D",1757092784074],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React, { useState } from \"https://esm.sh/react@18.2.0\";\nimport {\n useNavigate,\n useParams,\n} from \"https://esm.sh/react-router-dom@6.22.3?deps=react@18.2.0\";\nimport {\n useQuery,\n useQueryClient,\n} from \"https://esm.sh/@tanstack/react-query@4.29.5\";\nimport ReactMarkdown from \"https://esm.sh/react-markdown@8.0.7\";\n\ninterface Summarization {\n id: number;\n topic_id: number;\n content: string;\n prompt: string;\n post_count: number;\n created_at: string;\n time_period_start: string;\n time_period_end: string;\n topic_title?: string;\n}\n\ninterface SummarizationResponse {\n data: Summarization;\n}\n\nconst API_BASE = \"/api\";\n\nexport default function SummaryDetailView() {\n const { id } = useParams<{ id: string }>();\n const navigate = useNavigate();\n const queryClient = useQueryClient();\n const [isRegenerating, setIsRegenerating] = useState(false);\n const [regenerateMessage, setRegenerateMessage] = useState(\n null,\n );\n\n // Fetch the specific summarization\n const { data: summarizationData, isLoading, error } = useQuery<\n SummarizationResponse\n >({\n queryKey: [\"summarization\", id],\n queryFn: async () => {\n if (!id) {\n throw new Error(\"No summarization ID provided\");\n }\n\n const response = await fetch(`${API_BASE}/summarizations/${id}`, {\n headers: {\n \"Authorization\": `Basic ${\n btoa(\n `${localStorage.getItem(\"auth_username\")}:${\n localStorage.getItem(\"auth_password\")\n }`,\n )\n }`,\n },\n });\n\n if (!response.ok) {\n if (response.status === 404) {\n throw new Error(\"Summarization not found\");\n }\n throw new Error(\"Failed to fetch summarization\");\n }\n\n return response.json();\n },\n enabled: !!id, // Only run the query if we have an ID\n });\n\n const handleBack = () => {\n navigate(\"/dashboard\");\n };\n\n const handleRegenerate = async () => {\n if (!summarizationData?.data?.id) {\n setRegenerateMessage(\"Cannot regenerate: summarization ID not available\");\n return;\n }\n\n setIsRegenerating(true);\n setRegenerateMessage(null);\n\n try {\n const response = await fetch(\n `${API_BASE}/summarizations/${summarizationData.data.id}/regenerate`,\n {\n method: \"POST\",\n headers: {\n \"Authorization\": `Basic ${\n btoa(\n `${localStorage.getItem(\"auth_username\")}:${\n localStorage.getItem(\"auth_password\")\n }`,\n )\n }`,\n \"Content-Type\": \"application/json\",\n },\n },\n );\n\n const result = await response.json();\n\n if (!response.ok) {\n throw new Error(result.message || \"Failed to regenerate summary\");\n }\n\n if (result.status === \"success\") {\n setRegenerateMessage(\n \"✅ Summary regenerated successfully! Refreshing...\",\n );\n\n // Invalidate queries to refetch updated data\n await queryClient.invalidateQueries([\"summarization\", id]);\n await queryClient.invalidateQueries([\"summarizations\"]);\n\n setTimeout(() => {\n setRegenerateMessage(null);\n }, 3000);\n } else if (result.status === \"no_data\") {\n setRegenerateMessage(\n \"⚠️ No recent posts found to regenerate summary from\",\n );\n } else {\n setRegenerateMessage(\n `❌ ${result.message || \"Failed to regenerate summary\"}`,\n );\n }\n } catch (error) {\n console.error(\"Error regenerating summary:\", error);\n setRegenerateMessage(\n `❌ Error: ${\n error instanceof Error ? error.message : \"Unknown error occurred\"\n }`,\n );\n } finally {\n setIsRegenerating(false);\n }\n };\n\n const formatDate = (dateString: string) => {\n return new Date(dateString).toLocaleDateString(\"en-US\", {\n year: \"numeric\",\n month: \"short\",\n day: \"numeric\",\n hour: \"2-digit\",\n minute: \"2-digit\",\n });\n };\n\n if (isLoading) {\n return (\n

\n );\n }\n\n if (error) {\n return (\n

\n \n ← Back to Summaries\n \n

\n\n

Error loading summarization

\n {error instanceof Error ? error.message : \"Unknown error occurred\"}\n

\n );\n }\n\n if (!summarizationData) {\n return (\n

\n \n ← Back to Summaries\n \n

\n\n

No summarization found.

\n );\n }\n\n const summarization = summarizationData.data;\n\n return (\n

\n {/* Navigation */}\n

\n \n ← Back to Summaries\n \n

\n\n {/* Header */}\n

\n {summarization.topic_title || `Topic ${summarization.topic_id}`}\n

\n\n

\n Created: {formatDate(summarization.created_at)}\n Posts: {summarization.post_count}\n \n Period: {formatDate(summarization.time_period_start)} -{\" \"}\n {formatDate(summarization.time_period_end)}\n \n

\n\n {/* Content */}\n

Summary Content

\n {summarization.content\n ? (\n (\n

\n {children}\n

\n ),\n h2: ({ children }) => (\n

\n {children}\n

\n ),\n h3: ({ children }) => (\n

\n {children}\n

\n ),\n p: ({ children }) => (\n

\n {children}\n

\n ),\n ul: ({ children }) => (\n

\n {children}\n \n ),\n ol: ({ children }) => (\n

\n {children}\n \n ),\n li: ({ children }) =>

{children}

,\n a: ({ href, children }) => (\n \n {children}\n \n ),\n img: ({ src, alt }) => (\n

\n {\n const target = e.target as HTMLImageElement;\n target.style.display = \"none\";\n const errorDiv = document.createElement(\"div\");\n errorDiv.className =\n \"text-gray-500 italic text-sm border border-gray-200 p-3 rounded\";\n errorDiv.textContent = `Failed to load image: ${\n alt || src\n }`;\n target.parentNode?.insertBefore(errorDiv, target);\n }}\n />\n

\n ),\n blockquote: ({ children }) => (\n

\n {children}\n

\n ),\n code: ({ children, inline }) => (\n inline\n ? (\n \n {children}\n \n )\n : (\n \n {children}\n \n )\n ),\n }}\n >\n {summarization.content}\n \n )\n :

No content available

}\n

\n\n {/* Additional media support for embedded tweets, videos, etc. */}\n

\n {/* Look for tweet URLs and render them with appropriate styling */}\n {summarization.content &&\n /https:\\/\\/(?:x|twitter)\\.com\\/\\w+\\/status\\/\\d+/.test(\n summarization.content,\n ) && (\n

🐦 Twitter Links Detected

\n This summary contains Twitter/X post links. Click the links\n above to view the original posts.\n

\n )}\n\n {/* Look for YouTube URLs */}\n {summarization.content &&\n /https:\\/\\/(?:www\\.)?(?:youtube\\.com\\/watch\\?v=|youtu\\.be\\/)[\\w-]+/\n .test(summarization.content) &&\n (\n

📺 YouTube Links Detected

\n This summary contains YouTube video links. Click the links\n above to view the videos.\n

\n )}\n\n {/* Look for image URLs */}\n {summarization.content &&\n /https?:\\/\\/[^\\s]+\\.(?:jpg|jpeg|png|gif|webp)/i.test(\n summarization.content,\n ) && (\n

🖼️ Images Detected

\n This summary contains image links that should be displayed\n above.\n

\n )}\n

\n\n {/* Actions */}\n

\n {regenerateMessage && (\n \n {regenerateMessage}\n

\n )}\n\n

\n \n {isRegenerating\n ? (\n \n \n \n \n \n \n \n Regenerating...\n \n )\n : (\n \"Re-run Summarization\"\n )}\n \n

\n \n );\n}\n",[],[463,469,528],{"_104":536,"_95":537,"_154":538,"_156":470,"_157":139,"_158":539,"_160":22,"_106":540,"_100":32,"_163":193,"_165":541,"_166":22,"_167":-5,"_168":542,"_98":543},"83e53360-8a7c-11f0-81bc-0224a6c84d84","TopicManagement.tsx","83e5340a-8a7c-11f0-81bc-0224a6c84d84",36,["D",1757092784144],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React, { useState } from \"https://esm.sh/react@18.2.0\";\nimport { useQuery, useMutation, useQueryClient } from \"https://esm.sh/@tanstack/react-query@4.29.5\";\n\n// Types\ninterface Topic {\n id: number;\n title: string;\n description?: string;\n created_at: string;\n updated_at: string;\n}\n\ninterface CreateTopicData {\n title: string;\n description?: string;\n}\n\ninterface UpdateTopicData {\n title?: string;\n description?: string;\n}\n\n// API functions\nconst API_BASE = \"/api\";\n\nconst fetchTopics = async (): Promise => {\n const response = await fetch(`${API_BASE}/topics`);\n if (!response.ok) {\n throw new Error(\"Failed to fetch topics\");\n }\n return response.json();\n};\n\nconst createTopic = async (data: CreateTopicData): Promise => {\n const response = await fetch(`${API_BASE}/topics`, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify(data),\n });\n if (!response.ok) {\n throw new Error(\"Failed to create topic\");\n }\n return response.json();\n};\n\nconst updateTopic = async (id: number, data: UpdateTopicData): Promise => {\n const response = await fetch(`${API_BASE}/topics/${id}`, {\n method: \"PUT\",\n headers: {\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify(data),\n });\n if (!response.ok) {\n throw new Error(\"Failed to update topic\");\n }\n return response.json();\n};\n\nconst deleteTopic = async (id: number): Promise => {\n const response = await fetch(`${API_BASE}/topics/${id}`, {\n method: \"DELETE\",\n });\n if (!response.ok) {\n throw new Error(\"Failed to delete topic\");\n }\n};\n\nexport default function TopicManagement() {\n const queryClient = useQueryClient();\n const [showCreateForm, setShowCreateForm] = useState(false);\n const [editingTopic, setEditingTopic] = useState(null);\n const [deleteConfirm, setDeleteConfirm] = useState(null);\n\n // Query for topics\n const {\n data: topics = [],\n isLoading,\n error,\n } = useQuery({\n queryKey: [\"topics\"],\n queryFn: fetchTopics,\n });\n\n // Mutations\n const createMutation = useMutation({\n mutationFn: createTopic,\n onSuccess: () => {\n queryClient.invalidateQueries({ queryKey: [\"topics\"] });\n setShowCreateForm(false);\n },\n });\n\n const updateMutation = useMutation({\n mutationFn: ({ id, data }: { id: number; data: UpdateTopicData }) =>\n updateTopic(id, data),\n onSuccess: () => {\n queryClient.invalidateQueries({ queryKey: [\"topics\"] });\n setEditingTopic(null);\n },\n });\n\n const deleteMutation = useMutation({\n mutationFn: deleteTopic,\n onSuccess: () => {\n queryClient.invalidateQueries({ queryKey: [\"topics\"] });\n setDeleteConfirm(null);\n },\n });\n\n // Form handlers\n const handleCreateSubmit = (e: React.FormEvent) => {\n e.preventDefault();\n const formData = new FormData(e.currentTarget);\n const title = formData.get(\"title\") as string;\n const description = formData.get(\"description\") as string;\n\n if (!title.trim()) return;\n\n createMutation.mutate({\n title: title.trim(),\n description: description.trim() || undefined,\n });\n };\n\n const handleUpdateSubmit = (e: React.FormEvent) => {\n e.preventDefault();\n if (!editingTopic) return;\n\n const formData = new FormData(e.currentTarget);\n const title = formData.get(\"title\") as string;\n const description = formData.get(\"description\") as string;\n\n updateMutation.mutate({\n id: editingTopic.id,\n data: {\n title: title.trim(),\n description: description.trim() || undefined,\n },\n });\n };\n\n const handleDelete = (id: number) => {\n deleteMutation.mutate(id);\n };\n\n if (isLoading) {\n return (\n

\n );\n }\n\n if (error) {\n return (\n

Error Loading Topics

{error instanceof Error ? error.message : \"Unknown error occurred\"}

\n );\n }\n\n return (\n

Topic Management

\n setShowCreateForm(true)}\n className=\"bg-blue-500 hover:bg-blue-600 text-white px-4 py-2 rounded-lg transition-colors\"\n >\n Add Topic\n \n

\n\n {/* Create Form Modal */}\n {showCreateForm && (\n

Create New Topic

\n \n {createMutation.error && (\n

\n Error: {createMutation.error.message || \"Failed to create topic\"}\n

\n )}\n

\n )}\n\n {/* Edit Form Modal */}\n {editingTopic && (\n

Edit Topic

\n \n {updateMutation.error && (\n

\n Error: {updateMutation.error.message || \"Failed to update topic\"}\n

\n )}\n

\n )}\n\n {/* Delete Confirmation Modal */}\n {deleteConfirm && (\n

Confirm Delete

Are you sure you want to delete this topic? This action cannot be undone.

\n handleDelete(deleteConfirm)}\n disabled={deleteMutation.isLoading}\n className=\"flex-1 bg-red-500 hover:bg-red-600 disabled:bg-red-300 text-white py-2 rounded-md transition-colors\"\n >\n {deleteMutation.isLoading ? \"Deleting...\" : \"Delete\"}\n \n setDeleteConfirm(null)}\n className=\"flex-1 bg-gray-300 hover:bg-gray-400 text-gray-800 py-2 rounded-md transition-colors\"\n >\n Cancel\n \n

\n {deleteMutation.error && (\n

\n Error: {deleteMutation.error.message || \"Failed to delete topic\"}\n

\n )}\n

\n )}\n\n {/* Topics List */}\n {topics.length === 0 ? (\n

No topics created yet

Get started by creating your first topic!

\n ) : (\n

\n {topics.map((topic) => (\n

{topic.title}

\n #{topic.id}\n

\n \n {topic.description && (\n

{topic.description}

\n )}\n \n

\n Created: {new Date(topic.created_at).toLocaleDateString()}\n {topic.updated_at !== topic.created_at && (\n <>\n
\n Updated: {new Date(topic.updated_at).toLocaleDateString()}\n \n )}\n

\n \n

\n setEditingTopic(topic)}\n className=\"text-blue-500 hover:text-blue-700 text-sm font-medium transition-colors\"\n >\n Edit\n \n setDeleteConfirm(topic.id)}\n className=\"text-red-500 hover:text-red-700 text-sm font-medium transition-colors\"\n >\n Delete\n \n

\n ))}\n

\n )}\n

\n );\n}",[],[463,469,537],[463,469],{"_104":546,"_95":547,"_154":548,"_156":464,"_157":139,"_158":549,"_160":161,"_106":550,"_100":551,"_163":183,"_165":552,"_166":22,"_167":-5,"_168":553,"_98":554},"fdecd9b8-56bc-11f0-b053-f69ea79377d9","index.html","268930b2-55f3-11f0-a013-f69ea79377d9",27,["D",1751403016237],3,"\n\n\n \n \n OffX - Twitter Feed Summarizer\n \n \n\n\n

\n \n\n ",[],[463,547],{"_104":556,"_95":557,"_154":558,"_156":464,"_157":139,"_158":559,"_160":22,"_106":560,"_100":119,"_163":193,"_165":561,"_166":22,"_167":-5,"_168":562,"_98":563},"84c5887a-8a7c-11f0-bfed-0224a6c84d84","index.tsx","fde87e54-56bc-11f0-b92d-f69ea79377d9",69,["D",1757092785649],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React from \"https://esm.sh/react@18.2.0\";\nimport { createRoot } from \"https://esm.sh/react-dom@18.2.0/client\";\nimport {\n BrowserRouter,\n Navigate,\n Route,\n Routes,\n} from \"https://esm.sh/react-router-dom@6.22.3?deps=react@18.2.0\";\nimport { QueryClient, QueryClientProvider } from \"https://esm.sh/@tanstack/react-query@4.29.5\";\nimport App from \"./components/App.tsx\";\nimport LoginPage from \"./components/LoginPage.tsx\";\nimport Dashboard from \"./components/Dashboard.tsx\";\nimport SummaryDetailView from \"./components/SummaryDetailView.tsx\";\nimport { AuthProvider, RequireAuth } from \"./components/AuthContext.tsx\";\n\n// Create a React Query client\nconst queryClient = new QueryClient({\n defaultOptions: {\n queries: {\n staleTime: 5 * 60 * 1000, // 5 minutes\n cacheTime: 10 * 60 * 1000, // 10 minutes\n },\n },\n});\n\nconst root = createRoot(document.getElementById(\"root\")!);\n\nroot.render(\n \n \n \n \n \n }>\n } />\n \n \n \n }\n />\n \n \n \n }\n />\n } />\n \n \n \n \n \n ,\n);\n",[],[463,557],[463],{"_104":566,"_95":567,"_154":568,"_156":-5,"_157":139,"_158":551,"_160":161,"_106":569,"_100":32,"_163":164,"_165":-5,"_166":22,"_167":-5,"_168":570,"_98":571},"267864c6-55f3-11f0-ab57-f69ea79377d9","shared","267865ac-55f3-11f0-ab57-f69ea79377d9",["D",1751316325925],[],[567],{"_104":573,"_95":574,"_154":575,"_156":-5,"_157":139,"_158":576,"_160":161,"_106":577,"_100":32,"_163":183,"_165":578,"_166":22,"_167":-5,"_168":579,"_98":580},"84b5b152-8a7c-11f0-95ab-0224a6c84d84",".cursorrules","84b5b1fc-8a7c-11f0-95ab-0224a6c84d84",66,["D",1757092785546],"You are an advanced assistant specialized in generating Val Town code.\n\n## Core Guidelines\n\n- Ask clarifying questions when requirements are ambiguous\n- Provide complete, functional solutions rather than skeleton implementations\n- Test your logic against edge cases before presenting the final solution\n- Ensure all code follows Val Town's specific platform requirements\n- If a section of code that you're working on is getting too complex, consider refactoring it into subcomponents\n\n## Code Standards\n\n- Generate code in TypeScript or TSX\n- Add appropriate TypeScript types and interfaces for all data structures\n- Prefer official SDKs or libraries than writing API calls directly\n- Ask the user to supply API or library documentation if you are at all unsure about it\n- **Never bake in secrets into the code** - always use environment variables\n- Include comments explaining complex logic (avoid commenting obvious operations)\n- Follow modern ES6+ conventions and functional programming practices if possible\n\n## Types of triggers\n\n### 1. HTTP Trigger\n\n- Create web APIs and endpoints\n- Handle HTTP requests and responses\n- Example structure:\n\n```ts\nexport default async function (req: Request) {\n return new Response(\"Hello World\");\n}\n```\n\nFiles that are HTTP triggers have http in their name like `foobar.http.tsx`\n\n### 2. Cron Triggers\n\n- Run on a schedule\n- Use cron expressions for timing\n- Example structure:\n\n```ts\nexport default async function () {\n // Scheduled task code\n}\n```\n\nFiles that are Cron triggers have cron in their name like `foobar.cron.tsx`\n\n### 3. Email Triggers\n\n- Process incoming emails\n- Handle email-based workflows\n- Example structure:\n\n```ts\nexport default async function (email: Email) {\n // Process email\n}\n```\n\nFiles that are Email triggers have email in their name like `foobar.email.tsx`\n\n\n## Val Town Standard Libraries\n\nVal Town provides several hosted services and utility functions.\n\n### Blob Storage\n\n```ts\nimport { blob } from \"https://esm.town/v/std/blob\";\nawait blob.setJSON(\"myKey\", { hello: \"world\" });\nlet blobDemo = await blob.getJSON(\"myKey\");\nlet appKeys = await blob.list(\"app_\");\nawait blob.delete(\"myKey\");\n```\n\n### SQLite\n\n```ts\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nconst TABLE_NAME = 'todo_app_users_2';\n// Create table - do this before usage and change table name when modifying schema\nawait sqlite.execute(`CREATE TABLE IF NOT EXISTS ${TABLE_NAME} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n name TEXT NOT NULL\n)`);\n// Query data\nconst result = await sqlite.execute(`SELECT * FROM ${TABLE_NAME} WHERE id = ?`, [1]);\n```\n\nNote: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.\n\n### OpenAI\n\n```ts\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nconst openai = new OpenAI();\nconst completion = await openai.chat.completions.create({\n messages: [\n { role: \"user\", content: \"Say hello in a creative way\" },\n ],\n model: \"gpt-4o-mini\",\n max_tokens: 30,\n});\n```\n\n### Email\n\n```ts\nimport { email } from \"https://esm.town/v/std/email\";\n// By default emails the owner of the val\nawait email({ \n subject: \"Hi\", \n text: \"Hi\", \n html: \"

Hi

\"\n});\n```\n\n## Val Town Utility Functions\n\nVal Town provides several utility functions to help with common project tasks.\n\n### Importing Utilities\n\nAlways import utilities with version pins to avoid breaking changes:\n\n```ts\nimport { parseProject, readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n```\n\n### Available Utilities\n\n\n#### **serveFile** - Serve project files with proper content types\n\nFor example, in Hono:\n\n```ts\n// serve all files in frontend/ and shared/\napp.get(\"/frontend/*\", c => serveFile(c.req.path, import.meta.url));\napp.get(\"/shared/*\", c => serveFile(c.req.path, import.meta.url));\n```\n\n#### **readFile** - Read files from within the project:\n\n```ts\n// Read a file from the project\nconst fileContent = await readFile(\"/frontend/index.html\", import.meta.url);\n```\n\n#### **listFiles** - List all files in the project\n\n```ts\nconst files = await listFiles(import.meta.url);\n```\n\n#### **parseProject** - Extract information about the current project from import.meta.url\n\nThis is useful for including info for linking back to a val, ie in \"view source\" urls:\n\n```ts\nconst projectVal = parseProject(import.meta.url);\nconsole.log(projectVal.username); // Owner of the project\nconsole.log(projectVal.name); // Project name\nconsole.log(projectVal.version); // Version number\nconsole.log(projectVal.branch); // Branch name\nconsole.log(projectVal.links.self.project); // URL to the project page\n```\n\nHowever, it's *extremely importing* to note that `parseProject` and other Standard Library utilities ONLY RUN ON THE SERVER.\nIf you need access to this data on the client, run it in the server and pass it to the client by splicing it into the HTML page\nor by making an API request for it.\n\n## Val Town Platform Specifics\n\n- **Redirects:** Use `return new Response(null, { status: 302, headers: { Location: \"/place/to/redirect\" }})` instead of `Response.redirect` which is broken\n- **Images:** Avoid external images or base64 images. Use emojis, unicode symbols, or icon fonts/libraries instead\n- **AI Image:** To inline generate an AI image use: `

`\n- **Storage:** DO NOT use the Deno KV module for storage\n- **Browser APIs:** DO NOT use the `alert()`, `prompt()`, or `confirm()` methods\n- **Weather Data:** Use open-meteo for weather data (doesn't require API keys) unless otherwise specified\n- **View Source:** Add a view source link by importing & using `import.meta.url.replace(\"ems.sh\", \"val.town)\"` (or passing this data to the client) and include `target=\"_top\"` attribute\n- **Error Debugging:** Add `` to HTML to capture client-side errors\n- **Error Handling:** Only use try...catch when there's a clear local resolution; Avoid catches that merely log or return 500s. Let errors bubble up with full context\n- **Environment Variables:** Use `Deno.env.get('keyname')` when you need to, but generally prefer APIs that don't require keys\n- **Imports:** Use `https://esm.sh` for npm and Deno dependencies to ensure compatibility on server and browser\n- **Storage Strategy:** Only use backend storage if explicitly required; prefer simple static client-side sites\n- **React Configuration:** When using React libraries, pin versions with `?deps=react@18.2.0,react-dom@18.2.0` and start the file with `/** @jsxImportSource https://esm.sh/react@18.2.0 */`\n- Ensure all React dependencies and sub-dependencies are pinned to the same version\n- **Styling:** Default to using TailwindCSS via `` unless otherwise specified\n\n## Project Structure and Design Patterns\n\n### Recommended Directory Structure\n```\n├── backend/\n│ ├── database/\n│ │ ├── migrations.ts # Schema definitions\n│ │ ├── queries.ts # DB query functions\n│ │ └── README.md\n│ └── routes/ # Route modules\n│ ├── [route].ts\n│ └── static.ts # Static file serving\n│ ├── index.ts # Main entry point\n│ └── README.md\n├── frontend/\n│ ├── components/\n│ │ ├── App.tsx\n│ │ └── [Component].tsx\n│ ├── favicon.svg\n│ ├── index.html # Main HTML template\n│ ├── index.tsx # Frontend JS entry point\n│ ├── README.md\n│ └── style.css\n├── README.md\n└── shared/\n ├── README.md\n └── utils.ts # Shared types and functions\n```\n\n### Backend (Hono) Best Practices\n\n- Hono is the recommended API framework\n- Main entry point should be `backend/index.ts`\n- **Static asset serving:** Use the utility functions to read and serve project files:\n ```ts\n import { readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n \n // serve all files in frontend/ and shared/\n app.get(\"/frontend/*\", c => serveFile(c.req.path, import.meta.url));\n app.get(\"/shared/*\", c => serveFile(c.req.path, import.meta.url));\n \n // For index.html, often you'll want to bootstrap with initial data\n app.get(\"/\", async c => {\n let html = await readFile(\"/frontend/index.html\", import.meta.url);\n \n // Inject data to avoid extra round-trips\n const initialData = await fetchInitialData();\n const dataScript = ``;\n \n html = html.replace(\"\", `${dataScript}`);\n return c.html(html);\n });\n ```\n- Create RESTful API routes for CRUD operations\n- Always include this snippet at the top-level Hono app to re-throwing errors to see full stack traces:\n ```ts\n // Unwrap Hono errors to see original error details\n app.onError((err, c) => {\n throw err;\n });\n ```\n\n### Database Patterns\n- Run migrations on startup or comment out for performance\n- Change table names when modifying schemas rather than altering\n- Export clear query functions with proper TypeScript typing\n\n## Common Gotchas and Solutions\n\n1. **Environment Limitations:** \n - Val Town runs on Deno in a serverless context, not Node.js\n - Code in `shared/` must work in both frontend and backend environments\n - Cannot use `Deno` keyword in shared code\n - Use `https://esm.sh` for imports that work in both environments\n\n2. **SQLite Peculiarities:**\n - Limited support for ALTER TABLE operations\n - Create new tables with updated schemas and copy data when needed\n - Always run table creation before querying\n\n3. **React Configuration:**\n - All React dependencies must be pinned to 18.2.0\n - Always include `@jsxImportSource https://esm.sh/react@18.2.0` at the top of React files\n - Rendering issues often come from mismatched React versions\n\n4. **File Handling:**\n - Val Town only supports text files, not binary\n - Use the provided utilities to read files across branches and forks\n - For files in the project, use `readFile` helpers\n\n5. **API Design:**\n - `fetch` handler is the entry point for HTTP vals\n - Run the Hono app with `export default app.fetch // This is the entry point for HTTP vals`\n\n",[],[574],{"_104":582,"_95":583,"_154":584,"_156":-5,"_157":139,"_158":585,"_160":22,"_106":586,"_100":119,"_163":183,"_165":587,"_166":22,"_167":-5,"_168":588,"_98":589},"06bfa4ee-55f5-11f0-ae75-f69ea79377d9",".vtignore","269ae6e0-55f3-11f0-aaf2-f69ea79377d9",13,["D",1751317131694],".git\n.vscode\n.cursorrules\n.DS_Store\nnode_modules\nvendor\n.taskmaster\n.roo\n.windsurfrules\n.cursor\n.gitignore\n.roomodes\nscripts\n.env.example",[],[583],{"_104":591,"_95":592,"_154":593,"_156":-5,"_157":139,"_158":594,"_160":161,"_106":595,"_100":32,"_163":183,"_165":596,"_166":22,"_167":-5,"_168":597,"_98":598},"84b9bfd6-8a7c-11f0-8276-0224a6c84d84","AGENTS.md","84b9c06c-8a7c-11f0-8276-0224a6c84d84",67,["D",1757092785559],"# Task Master AI - Claude Code Integration Guide\n\n## Essential Commands\n\n### Core Workflow Commands\n\n```bash\n# Project Setup\ntask-master init # Initialize Task Master in current project\ntask-master parse-prd .taskmaster/docs/prd.txt # Generate tasks from PRD document\ntask-master models --setup # Configure AI models interactively\n\n# Daily Development Workflow\ntask-master list # Show all tasks with status\ntask-master next # Get next available task to work on\ntask-master show # View detailed task information (e.g., task-master show 1.2)\ntask-master set-status --id= --status=done # Mark task complete\n\n# Task Management\ntask-master add-task --prompt=\"description\" --research # Add new task with AI assistance\ntask-master expand --id= --research --force # Break task into subtasks\ntask-master update-task --id= --prompt=\"changes\" # Update specific task\ntask-master update --from= --prompt=\"changes\" # Update multiple tasks from ID onwards\ntask-master update-subtask --id= --prompt=\"notes\" # Add implementation notes to subtask\n\n# Analysis & Planning\ntask-master analyze-complexity --research # Analyze task complexity\ntask-master complexity-report # View complexity analysis\ntask-master expand --all --research # Expand all eligible tasks\n\n# Dependencies & Organization\ntask-master add-dependency --id= --depends-on= # Add task dependency\ntask-master move --from= --to= # Reorganize task hierarchy\ntask-master validate-dependencies # Check for dependency issues\ntask-master generate # Update task markdown files (usually auto-called)\n```\n\n## Key Files & Project Structure\n\n### Core Files\n\n- `.taskmaster/tasks/tasks.json` - Main task data file (auto-managed)\n- `.taskmaster/config.json` - AI model configuration (use `task-master models` to modify)\n- `.taskmaster/docs/prd.txt` - Product Requirements Document for parsing\n- `.taskmaster/tasks/*.txt` - Individual task files (auto-generated from tasks.json)\n- `.env` - API keys for CLI usage\n\n### Claude Code Integration Files\n\n- `CLAUDE.md` - Auto-loaded context for Claude Code (this file)\n- `.claude/settings.json` - Claude Code tool allowlist and preferences\n- `.claude/commands/` - Custom slash commands for repeated workflows\n- `.mcp.json` - MCP server configuration (project-specific)\n\n### Directory Structure\n\n```\nproject/\n├── .taskmaster/\n│ ├── tasks/ # Task files directory\n│ │ ├── tasks.json # Main task database\n│ │ ├── task-1.md # Individual task files\n│ │ └── task-2.md\n│ ├── docs/ # Documentation directory\n│ │ ├── prd.txt # Product requirements\n│ ├── reports/ # Analysis reports directory\n│ │ └── task-complexity-report.json\n│ ├── templates/ # Template files\n│ │ └── example_prd.txt # Example PRD template\n│ └── config.json # AI models & settings\n├── .claude/\n│ ├── settings.json # Claude Code configuration\n│ └── commands/ # Custom slash commands\n├── .env # API keys\n├── .mcp.json # MCP configuration\n└── CLAUDE.md # This file - auto-loaded by Claude Code\n```\n\n## MCP Integration\n\nTask Master provides an MCP server that Claude Code can connect to. Configure in `.mcp.json`:\n\n```json\n{\n \"mcpServers\": {\n \"task-master-ai\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"--package=task-master-ai\", \"task-master-ai\"],\n \"env\": {\n \"ANTHROPIC_API_KEY\": \"your_key_here\",\n \"PERPLEXITY_API_KEY\": \"your_key_here\",\n \"OPENAI_API_KEY\": \"OPENAI_API_KEY_HERE\",\n \"GOOGLE_API_KEY\": \"GOOGLE_API_KEY_HERE\",\n \"XAI_API_KEY\": \"XAI_API_KEY_HERE\",\n \"OPENROUTER_API_KEY\": \"OPENROUTER_API_KEY_HERE\",\n \"MISTRAL_API_KEY\": \"MISTRAL_API_KEY_HERE\",\n \"AZURE_OPENAI_API_KEY\": \"AZURE_OPENAI_API_KEY_HERE\",\n \"OLLAMA_API_KEY\": \"OLLAMA_API_KEY_HERE\"\n }\n }\n }\n}\n```\n\n### Essential MCP Tools\n\n```javascript\nhelp; // = shows available taskmaster commands\n// Project setup\ninitialize_project; // = task-master init\nparse_prd; // = task-master parse-prd\n\n// Daily workflow\nget_tasks; // = task-master list\nnext_task; // = task-master next\nget_task; // = task-master show \nset_task_status; // = task-master set-status\n\n// Task management\nadd_task; // = task-master add-task\nexpand_task; // = task-master expand\nupdate_task; // = task-master update-task\nupdate_subtask; // = task-master update-subtask\nupdate; // = task-master update\n\n// Analysis\nanalyze_project_complexity; // = task-master analyze-complexity\ncomplexity_report; // = task-master complexity-report\n```\n\n## Claude Code Workflow Integration\n\n### Standard Development Workflow\n\n#### 1. Project Initialization\n\n```bash\n# Initialize Task Master\ntask-master init\n\n# Create or obtain PRD, then parse it\ntask-master parse-prd .taskmaster/docs/prd.txt\n\n# Analyze complexity and expand tasks\ntask-master analyze-complexity --research\ntask-master expand --all --research\n```\n\nIf tasks already exist, another PRD can be parsed (with new information only!) using parse-prd with --append flag. This will add the generated tasks to the existing list of tasks..\n\n#### 2. Daily Development Loop\n\n```bash\n# Start each session\ntask-master next # Find next available task\ntask-master show # Review task details\n\n# During implementation, check in code context into the tasks and subtasks\ntask-master update-subtask --id= --prompt=\"implementation notes...\"\n\n# Complete tasks\ntask-master set-status --id= --status=done\n```\n\n#### 3. Multi-Claude Workflows\n\nFor complex projects, use multiple Claude Code sessions:\n\n```bash\n# Terminal 1: Main implementation\ncd project && claude\n\n# Terminal 2: Testing and validation\ncd project-test-worktree && claude\n\n# Terminal 3: Documentation updates\ncd project-docs-worktree && claude\n```\n\n### Custom Slash Commands\n\nCreate `.claude/commands/taskmaster-next.md`:\n\n```markdown\nFind the next available Task Master task and show its details.\n\nSteps:\n\n1. Run `task-master next` to get the next task\n2. If a task is available, run `task-master show ` for full details\n3. Provide a summary of what needs to be implemented\n4. Suggest the first implementation step\n```\n\nCreate `.claude/commands/taskmaster-complete.md`:\n\n```markdown\nComplete a Task Master task: $ARGUMENTS\n\nSteps:\n\n1. Review the current task with `task-master show $ARGUMENTS`\n2. Verify all implementation is complete\n3. Run any tests related to this task\n4. Mark as complete: `task-master set-status --id=$ARGUMENTS --status=done`\n5. Show the next available task with `task-master next`\n```\n\n## Tool Allowlist Recommendations\n\nAdd to `.claude/settings.json`:\n\n```json\n{\n \"allowedTools\": [\n \"Edit\",\n \"Bash(task-master *)\",\n \"Bash(git commit:*)\",\n \"Bash(git add:*)\",\n \"Bash(npm run *)\",\n \"mcp__task_master_ai__*\"\n ]\n}\n```\n\n## Configuration & Setup\n\n### API Keys Required\n\nAt least **one** of these API keys must be configured:\n\n- `ANTHROPIC_API_KEY` (Claude models) - **Recommended**\n- `PERPLEXITY_API_KEY` (Research features) - **Highly recommended**\n- `OPENAI_API_KEY` (GPT models)\n- `GOOGLE_API_KEY` (Gemini models)\n- `MISTRAL_API_KEY` (Mistral models)\n- `OPENROUTER_API_KEY` (Multiple models)\n- `XAI_API_KEY` (Grok models)\n\nAn API key is required for any provider used across any of the 3 roles defined in the `models` command.\n\n### Model Configuration\n\n```bash\n# Interactive setup (recommended)\ntask-master models --setup\n\n# Set specific models\ntask-master models --set-main claude-3-5-sonnet-20241022\ntask-master models --set-research perplexity-llama-3.1-sonar-large-128k-online\ntask-master models --set-fallback gpt-4o-mini\n```\n\n## Task Structure & IDs\n\n### Task ID Format\n\n- Main tasks: `1`, `2`, `3`, etc.\n- Subtasks: `1.1`, `1.2`, `2.1`, etc.\n- Sub-subtasks: `1.1.1`, `1.1.2`, etc.\n\n### Task Status Values\n\n- `pending` - Ready to work on\n- `in-progress` - Currently being worked on\n- `done` - Completed and verified\n- `deferred` - Postponed\n- `cancelled` - No longer needed\n- `blocked` - Waiting on external factors\n\n### Task Fields\n\n```json\n{\n \"id\": \"1.2\",\n \"title\": \"Implement user authentication\",\n \"description\": \"Set up JWT-based auth system\",\n \"status\": \"pending\",\n \"priority\": \"high\",\n \"dependencies\": [\"1.1\"],\n \"details\": \"Use bcrypt for hashing, JWT for tokens...\",\n \"testStrategy\": \"Unit tests for auth functions, integration tests for login flow\",\n \"subtasks\": []\n}\n```\n\n## Claude Code Best Practices with Task Master\n\n### Context Management\n\n- Use `/clear` between different tasks to maintain focus\n- This CLAUDE.md file is automatically loaded for context\n- Use `task-master show ` to pull specific task context when needed\n\n### Iterative Implementation\n\n1. `task-master show ` - Understand requirements\n2. Explore codebase and plan implementation\n3. `task-master update-subtask --id= --prompt=\"detailed plan\"` - Log plan\n4. `task-master set-status --id= --status=in-progress` - Start work\n5. Implement code following logged plan\n6. `task-master update-subtask --id= --prompt=\"what worked/didn't work\"` - Log progress\n7. `task-master set-status --id= --status=done` - Complete task\n\n### Complex Workflows with Checklists\n\nFor large migrations or multi-step processes:\n\n1. Create a markdown PRD file describing the new changes: `touch task-migration-checklist.md` (prds can be .txt or .md)\n2. Use Taskmaster to parse the new prd with `task-master parse-prd --append` (also available in MCP)\n3. Use Taskmaster to expand the newly generated tasks into subtasks. Consdier using `analyze-complexity` with the correct --to and --from IDs (the new ids) to identify the ideal subtask amounts for each task. Then expand them.\n4. Work through items systematically, checking them off as completed\n5. Use `task-master update-subtask` to log progress on each task/subtask and/or updating/researching them before/during implementation if getting stuck\n\n### Git Integration\n\nTask Master works well with `gh` CLI:\n\n```bash\n# Create PR for completed task\ngh pr create --title \"Complete task 1.2: User authentication\" --body \"Implements JWT auth system as specified in task 1.2\"\n\n# Reference task in commits\ngit commit -m \"feat: implement JWT auth (task 1.2)\"\n```\n\n### Parallel Development with Git Worktrees\n\n```bash\n# Create worktrees for parallel task development\ngit worktree add ../project-auth feature/auth-system\ngit worktree add ../project-api feature/api-refactor\n\n# Run Claude Code in each worktree\ncd ../project-auth && claude # Terminal 1: Auth work\ncd ../project-api && claude # Terminal 2: API work\n```\n\n## Troubleshooting\n\n### AI Commands Failing\n\n```bash\n# Check API keys are configured\ncat .env # For CLI usage\n\n# Verify model configuration\ntask-master models\n\n# Test with different model\ntask-master models --set-fallback gpt-4o-mini\n```\n\n### MCP Connection Issues\n\n- Check `.mcp.json` configuration\n- Verify Node.js installation\n- Use `--mcp-debug` flag when starting Claude Code\n- Use CLI as fallback if MCP unavailable\n\n### Task File Sync Issues\n\n```bash\n# Regenerate task files from tasks.json\ntask-master generate\n\n# Fix dependency issues\ntask-master fix-dependencies\n```\n\nDO NOT RE-INITIALIZE. That will not do anything beyond re-adding the same Taskmaster core files.\n\n## Important Notes\n\n### AI-Powered Operations\n\nThese commands make AI calls and may take up to a minute:\n\n- `parse_prd` / `task-master parse-prd`\n- `analyze_project_complexity` / `task-master analyze-complexity`\n- `expand_task` / `task-master expand`\n- `expand_all` / `task-master expand --all`\n- `add_task` / `task-master add-task`\n- `update` / `task-master update`\n- `update_task` / `task-master update-task`\n- `update_subtask` / `task-master update-subtask`\n\n### File Management\n\n- Never manually edit `tasks.json` - use commands instead\n- Never manually edit `.taskmaster/config.json` - use `task-master models`\n- Task markdown files in `tasks/` are auto-generated\n- Run `task-master generate` after manual changes to tasks.json\n\n### Claude Code Session Management\n\n- Use `/clear` frequently to maintain focused context\n- Create custom slash commands for repeated Task Master workflows\n- Configure tool allowlist to streamline permissions\n- Use headless mode for automation: `claude -p \"task-master next\"`\n\n### Multi-Task Updates\n\n- Use `update --from=` to update multiple future tasks\n- Use `update-task --id=` for single task updates\n- Use `update-subtask --id=` for implementation logging\n\n### Research Mode\n\n- Add `--research` flag for research-based AI enhancement\n- Requires a research model API key like Perplexity (`PERPLEXITY_API_KEY`) in environment\n- Provides more informed task creation and updates\n- Recommended for complex technical tasks\n\n---\n\n_This guide ensures Claude Code has immediate access to Task Master's essential functionality for agentic development workflows._\n",[],[592],{"_104":600,"_95":601,"_154":602,"_156":-5,"_157":139,"_158":603,"_160":161,"_106":604,"_100":32,"_163":183,"_165":596,"_166":22,"_167":-5,"_168":605,"_98":606},"84c01e62-8a7c-11f0-8701-0224a6c84d84","CLAUDE.md","84c01f0c-8a7c-11f0-8701-0224a6c84d84",68,["D",1757092785544],[],[601],{"_104":608,"_95":179,"_154":609,"_156":-5,"_157":139,"_158":610,"_160":22,"_106":611,"_100":32,"_163":183,"_165":612,"_166":22,"_167":-5,"_168":613,"_98":614},"268c2e2a-55f3-11f0-a3d9-f69ea79377d9","268c2ede-55f3-11f0-a3d9-f69ea79377d9",5,["D",1751316326042],"# OffX - Twitter Feed Summarizer\n\nA Val Town application that summarizes your Twitter feed using AI.\n\n## Features\n\n- Fetch tweets from your Twitter home feed\n- Organize tweets by user-defined topics\n- Generate AI-powered summaries using OpenAI\n- Deliver summaries via email or Discord\n- Web dashboard for configuration and viewing summaries\n\n## Setup Instructions\n\n### Prerequisites\n\n- [Deno](https://deno.com/) installed\n- Val Town CLI installed: `deno install -grAf jsr:@valtown/vt`\n- Val Town account\n\n### Local Development\n\n1. Clone this repository:\n ```\n vt clone @yourusername/offx\n ```\n\n2. Navigate to the project directory:\n ```\n cd offx\n ```\n\n3. Make changes to the code as needed\n\n4. Push changes to Val Town:\n ```\n vt push\n ```\n\n### Environment Variables\n\nThe following environment variables need to be set in Val Town:\n\n- `TWITTER_BEARER_TOKEN`: Your Twitter API bearer token\n- `OPENAI_API_KEY`: Your OpenAI API key\n- `AUTH_USERNAME`: Username for dashboard authentication\n- `AUTH_PASSWORD`: Password for dashboard authentication\n\n## Project Structure\n\n```\noffx/\n├── backend/\n│ ├── database/ # SQLite database operations\n│ └── routes/ # API route handlers\n├── frontend/ # Frontend HTML, CSS, and JavaScript\n├── shared/ # Shared code between frontend and backend\n├── index.ts # Main entry point\n└── README.md # This file\n```\n\n## Deployment\n\nThis project is designed to run on Val Town. After pushing your code with `vt push`, you can access the application at:\n\n```\nhttps://val.town/v/yourusername/offx\n```\n\n## Development Commands\n\n- `vt push`: Push local changes to Val Town\n- `vt pull`: Pull the latest changes from Val Town\n- `vt status`: Show working tree status\n- `vt browse`: Open the Val in a web browser\n\n## License\n\nMIT ",[],[179],{"_104":616,"_95":617,"_154":618,"_156":-5,"_157":139,"_158":619,"_160":22,"_106":620,"_100":119,"_163":183,"_165":621,"_166":22,"_167":-5,"_168":622,"_98":623},"fdfb29fa-56bc-11f0-9175-f69ea79377d9","deno.json","268f5456-55f3-11f0-9719-f69ea79377d9",29,["D",1751403016301],"{\n \"$schema\": \"https://raw.githubusercontent.com/denoland/deno/348900b8b79f4a434cab4c74b3bc8d4d2fa8ee74/cli/schemas/config-file.v1.json\",\n \"lock\": false,\n \"compilerOptions\": {\n \"noImplicitAny\": false,\n \"strict\": true,\n \"types\": [\n \"https://www.val.town/types/valtown.d.ts\"\n ],\n \"lib\": [\n \"dom\",\n \"dom.iterable\",\n \"esnext\",\n \"deno.ns\"\n ],\n \"jsx\": \"react-jsx\",\n \"jsxImportSource\": \"https://esm.sh/react@18.2.0\"\n },\n \"lint\": {\n \"files\": {\n \"include\": [\n \"deno:/https/esm.town/**/*\"\n ]\n },\n \"rules\": {\n \"exclude\": [\n \"no-explicit-any\"\n ]\n }\n },\n \"node_modules_dir\": false,\n \"experimental\": {\n \"unstable-node-globals\": true,\n \"unstable-temporal\": true,\n \"unstable-worker-options\": true,\n \"unstable-sloppy-imports\": true\n },\n \"imports\": {\n \"react\": \"https://esm.sh/react@18.2.0\",\n \"react-dom\": \"https://esm.sh/react-dom@18.2.0\",\n \"react-router-dom\": \"https://esm.sh/react-router-dom@6.22.3?deps=react@18.2.0\"\n }\n}",[],[617],{"_104":625,"_95":99,"_154":626,"_156":-5,"_157":139,"_158":627,"_160":22,"_106":628,"_100":32,"_163":193,"_165":629,"_166":22,"_167":-5,"_168":630,"_98":631},"269667fa-55f3-11f0-83aa-f69ea79377d9","2696689a-55f3-11f0-83aa-f69ea79377d9",8,["D",1751316326043],"// This script helps document the required environment variables for the OffX application\n// To set environment variables in Val Town, use the web interface or the Val Town CLI\n\nconsole.log(\"OffX Environment Variables Setup Guide\");\nconsole.log(\"======================================\");\nconsole.log(\n \"\\nThe following environment variables need to be set in Val Town:\",\n);\nconsole.log(\"\\n1. Twitter API credentials:\");\nconsole.log(\" - TWITTER_BEARER_TOKEN: Your Twitter API bearer token\");\nconsole.log(\"\\n2. OpenAI API credentials:\");\nconsole.log(\" - OPENAI_API_KEY: Your OpenAI API key\");\nconsole.log(\"\\n3. Dashboard authentication:\");\nconsole.log(\" - AUTH_USERNAME: Username for dashboard authentication\");\nconsole.log(\" - AUTH_PASSWORD: Password for dashboard authentication\");\nconsole.log(\"\\n4. Email configuration (optional):\");\nconsole.log(\" - EMAIL_TO: Email address to send summaries to\");\nconsole.log(\"\\n5. Discord configuration (optional):\");\nconsole.log(\n \" - DISCORD_WEBHOOK_URL: Discord webhook URL for sending summaries\",\n);\nconsole.log(\"\\nTo set these environment variables in Val Town:\");\nconsole.log(\"1. Go to your Val Town dashboard\");\nconsole.log(\"2. Navigate to the OffX val\");\nconsole.log(\"3. Click on 'Settings'\");\nconsole.log(\"4. Add each environment variable under 'Environment Variables'\");\nconsole.log(\n \"\\nAlternatively, you can use the Val Town CLI to set environment variables.\",\n);\n\n// Function to check if environment variables are set\nexport async function checkEnvironmentVariables() {\n const requiredVars = [\n \"TWITTER_BEARER_TOKEN\",\n \"OPENAI_API_KEY\",\n \"AUTH_USERNAME\",\n \"AUTH_PASSWORD\",\n ];\n const optionalVars = [\"EMAIL_TO\", \"DISCORD_WEBHOOK_URL\"];\n\n console.log(\"\\nChecking environment variables...\");\n\n // Check required variables\n console.log(\"\\nRequired variables:\");\n for (const varName of requiredVars) {\n const value = Deno.env.get(varName);\n if (value) {\n console.log(`✅ ${varName} is set`);\n } else {\n console.log(`❌ ${varName} is NOT set`);\n }\n }\n\n // Check optional variables\n console.log(\"\\nOptional variables:\");\n for (const varName of optionalVars) {\n const value = Deno.env.get(varName);\n if (value) {\n console.log(`✅ ${varName} is set`);\n } else {\n console.log(`⚠️ ${varName} is NOT set (optional)`);\n }\n }\n}\n\n// Run the check if this script is executed directly\nif (import.meta.main) {\n await checkEnvironmentVariables();\n}\n\nexport default { checkEnvironmentVariables 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