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* @jsxImportSource https://esm.sh/react@18.2.0\n */\n\nexport interface Memory {\n id: string; // UUID\n date: string; // ISO 8601 date string or similar\n text: string;\n createdBy?: string | null; // Optional: Who/what created the memory\n createdDate?: number | null; // Optional: Unix timestamp (integer)\n tags?: string | null; // Optional: Comma-separated string or 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interface Memory {\n id: string;\n date: string;\n text: string;\n tags: string | null;\n\n // New fields from schema\n createdBy?: string;\n createdDate?: number;\n}\n","children",[],[132,32],["D",1746395515148],[193],[132],"ff2cd32c-2931-11f0-886c-569c3dd06744","handleUSPSEmail.ts","ff2cd3d6-2931-11f0-886c-569c3dd06744",16,["D",1746395515941],"import { DateTime } from \"https://esm.sh/luxon@3.4.4\";\nimport Anthropic from \"npm:@anthropic-ai/sdk@0.24.3\";\n\nconst RECIPIENTS = [\"Geoffrey\", \"Maggie\"] as const;\n\nfunction parseDateFromSubject(subject: string): string | null {\n const match = subject.match(/(\\w{3}), (\\d{1,2}\\/\\d{1,2})/);\n if (match) {\n return `${match[1]} ${match[2]}`;\n }\n return null;\n}\n\ntype ImageSummary = {\n sender: string;\n recipient: (typeof RECIPIENTS)[number] | \"both\" | \"other\";\n type: \"personal\" | \"transactional\" | \"ad\";\n notes?: string;\n};\n\nasync function analyzeHtmlContent(\n anthropic: Anthropic,\n htmlContent: string,\n imageSummaries: ImageSummary[]\n) {\n try {\n const response = await anthropic.messages.create({\n model: \"claude-3-5-sonnet-latest\",\n max_tokens: 4196,\n messages: [\n {\n role: \"user\",\n content: [\n {\n type: \"text\",\n text: `Analyze the following content from an email and provide a response as a JSON blob (only JSON, no other text) with two parts.\n\n The email is from the USPS showing mail I'm receiving. Metadata about packages is stored directly in the email. Info about mail pieces is in images, so I've included summaries of those as well.\n\n Your response should include:\n\n 1. An array of upcoming packages, where each package has:\n - sender: string (name of the sender)\n - status: \"expected today\" | \"expected 1-2 days\" | \"awaiting from sender\"\n\n 2. A short positive couple sentences summarizing the mail, like a competent executive assistant would. Examples:\n - \"Quiet day today! Just a couple ads, nothing of note\"\n - \"A few packages arriving soon, keep an eye out!\"\n - \"Looks like a couple possibly important things today, make sure to review the letter from the IRS.\"\n\n Respond with a JSON object in this format:\n {\n \"packages\": [\n { \"sender\": string, \"status\": string },\n ...\n ],\n \"summary\": string\n }\n\n Do not include any other text in your response, only a JSON blob.\n\n Here's the HTML content of the email:\n\n ${htmlContent}\n\n And here is info about the mail pieces:\n\n ${JSON.stringify(imageSummaries)}`,\n },\n ],\n },\n ],\n });\n\n return JSON.parse(response.content[0].text);\n } catch (error) {\n console.error(\"HTML analysis error:\", error);\n return { packages: [], summary: \"Unable to analyze email content.\" };\n }\n}\n\nexport default async function (e: Email) {\n console.log(\"email content\");\n console.log(e.html);\n console.log(e.text);\n\n // Get Anthropic API key from environment\n const apiKey = Deno.env.get(\"ANTHROPIC_API_KEY\");\n if (!apiKey) {\n console.error(\"Anthropic API key is not configured for this val.\");\n return;\n }\n\n // Initialize Anthropic client\n const anthropic = new Anthropic({ apiKey });\n\n // Process each image attachment serially\n const summaries = [];\n for (const [index, attachment] of e.attachments.entries()) {\n try {\n const imageData = await attachment.arrayBuffer();\n const base64Image = btoa(\n String.fromCharCode(...new Uint8Array(imageData))\n );\n\n const response = await anthropic.messages.create({\n model: \"claude-3-5-sonnet-latest\",\n max_tokens: 4196,\n messages: [\n {\n role: \"user\",\n content: [\n {\n type: \"image\",\n source: {\n type: \"base64\",\n media_type: attachment.type,\n data: base64Image,\n },\n },\n {\n type: \"text\",\n text: `This is a scan of a piece of mail we received at our household. Respond with a JSON blob summarizing the piece of mail, with the following fields:\n\n {\n /* Name of sender as written on mail, e.g. \"Delta Airlines\" for a business, or \"John Doe\" for an individual */\n sender: string;\n\n /* Name of recipient. Usually should be either Geoffrey or Maggie (Margaret). If it's to both of us, use \"Both\". For any other recipient use \"Other\" */\n recipient: \"Geoffrey\" | \"Maggie\" | \"Both\" | \"Other\";\n\n /* Guess what type of mail it is. Usually, mail from an individual is personal. \"Transactional\" is things like bills or reports that might require action. If it's clearly an ad (eg, an offer for a credit card, or a catalog), mark it \"ad\". If you're not sure, lean \"transactional\" so we don't miss those by accident. */\n type: \"personal\" | \"transactional\" | \"ad\"\n\n /* Optional: any extra writing on the scan, e.g. \"important, action required\" */\n notes?: string;\n }\n\n Don't return any other text in your response, just a JSON blob.\n `,\n },\n ],\n },\n ],\n });\n\n const parsedResponse = JSON.parse(response.content[0].text);\n summaries.push(parsedResponse);\n } catch (error) {\n console.error(`Image analysis error:`, error);\n summaries.push({\n sender: \"Error\",\n recipient: \"Error\",\n type: \"error\",\n notes: `Image ${index + 1} Analysis Failed: ${error.message}`,\n });\n }\n }\n\n // Analyze HTML content\n const htmlAnalysis = await analyzeHtmlContent(\n anthropic,\n e.html || \"\",\n summaries\n );\n\n const localDate = DateTime.now().setZone(\"America/New_York\").toISO();\n\n // Create memories for mail and packages\n const memories = [];\n\n // Memory for mail\n if (summaries.length > 0) {\n memories.push(`expecting mail: ${JSON.stringify(summaries)}`);\n }\n\n // Memory for packages\n if (htmlAnalysis.packages.length > 0) {\n memories.push(\n `expecting package: ${JSON.stringify(htmlAnalysis.packages)}`\n );\n }\n\n // Insert memories into SQLite\n const { sqlite } = await import(\"https://esm.town/v/stevekrouse/sqlite\");\n const { nanoid } = await import(\"https://esm.sh/nanoid@5.0.5\");\n\n // Insert memories\n for (const memory of memories) {\n await sqlite.execute({\n sql: `INSERT INTO memories (id, date, text, createdBy, createdDate, tags)\n VALUES (:id, :date, :text, :createdBy, :createdDate, :tags)`,\n args: {\n id: nanoid(10),\n date: localDate,\n text: memory,\n createdBy: \"usps\",\n createdDate: Date.now(),\n tags: \"mail\",\n },\n });\n }\n\n console.log(\"Memories inserted successfully.\");\n}\n",[],[142,206],"ff231a3a-2931-11f0-92c2-569c3dd06744","handleTelegramMessage.ts","ff231aee-2931-11f0-92c2-569c3dd06744",13,["D",1746395515877],"import {\n Bot,\n webhookCallback,\n} from \"https://deno.land/x/grammy@v1.35.0/mod.ts\";\nimport { DateTime } from \"https://esm.sh/luxon@3.4.4\";\nimport Anthropic from \"npm:@anthropic-ai/sdk@0.24.3\";\nimport { backstory } from \"../backstory.ts\";\nimport {\n formatMemoriesForPrompt,\n getRelevantMemories,\n} from \"../memoryUtils.ts\";\n\n// Initialize the bot\nif (!Deno.env.get(\"TELEGRAM_TOKEN\")) {\n throw new Error(\"TELEGRAM_TOKEN is not set\");\n}\nconst bot = new Bot(Deno.env.get(\"TELEGRAM_TOKEN\")!);\n\n// Use part of the TELEGRAM_TOKEN itself as the secret_token\nconst SECRET_TOKEN = Deno.env.get(\"TELEGRAM_TOKEN\")!.split(\":\")[1];\nconst handleUpdate = webhookCallback(\n bot,\n \"std/http\",\n undefined,\n undefined,\n SECRET_TOKEN\n);\n\nlet isEndpointSet = false;\n\n// Special ID for the bot's own messages\nexport const BOT_SENDER_ID = \"mr_stevens_bot\";\nexport const BOT_SENDER_NAME = \"Mr. Stevens\";\n\n/**\n * Store a chat message in the database\n */\nexport async function storeChatMessage(\n chatId,\n senderId,\n senderName,\n message,\n isBot = false\n) {\n try {\n const { sqlite } = await import(\"https://esm.town/v/stevekrouse/sqlite\");\n const timestamp = Math.floor(Date.now() / 1000); // Unix timestamp in seconds\n\n await sqlite.execute({\n sql: `INSERT INTO telegram_chats (chat_id, sender_id, sender_name, message, timestamp, is_bot)\n VALUES (:chat_id, :sender_id, :sender_name, :message, :timestamp, :is_bot)`,\n args: {\n chat_id: chatId,\n sender_id: senderId,\n sender_name: senderName,\n message: message,\n timestamp: timestamp,\n is_bot: isBot ? 1 : 0,\n },\n });\n return true;\n } catch (error) {\n console.error(\"Error storing chat message:\", error);\n return false;\n }\n}\n\n/**\n * Retrieve chat history for a specific chat\n */\nexport async function getChatHistory(chatId, limit = 50) {\n try {\n const { sqlite } = await import(\"https://esm.town/v/stevekrouse/sqlite\");\n\n const result = await sqlite.execute({\n sql: `SELECT * FROM telegram_chats\n WHERE chat_id = :chat_id\n ORDER BY timestamp ASC\n LIMIT :limit`,\n args: {\n chat_id: chatId,\n limit: limit,\n },\n });\n\n return result.rows || [];\n } catch (error) {\n console.error(\"Error retrieving chat history:\", error);\n return [];\n }\n}\n\n/**\n * Format chat history for Anthropic API\n */\nfunction formatChatHistoryForAI(history) {\n const messages = [];\n\n for (const msg of history) {\n if (msg.is_bot) {\n messages.push({\n role: \"assistant\",\n content: msg.message,\n });\n } else {\n // Format user message with sender name\n messages.push({\n role: \"user\",\n content: `${msg.sender_name} says: ${msg.message}`,\n });\n }\n }\n\n return messages;\n}\n\n/**\n * Analyze a Telegram message and extract memories from it\n */\nasync function analyzeMessageContent(\n anthropic,\n username,\n messageText,\n chatHistory = []\n) {\n try {\n // Get relevant memories\n const memories = await getRelevantMemories();\n const memoriesText = formatMemoriesForPrompt(memories);\n\n // Prepare system prompt with all instructions and memories\n const systemPrompt = `${backstory}\n\nYour job is to read this Telegram message from your employer and respond in a natural, butler-like way, noting any important information that should be remembered for future reference.\n\nYou have access to the following stored memories:\n\n${memoriesText}\n\nIf this appears to be a new client or the conversation is in an early stage, you should conduct an intake interview to gather essential background information. First ask the client if now is a good time to ask them some questions.\n\nAsk about the following topics in a conversational way (not all at once, but continuing the interview naturally based on their responses):\n\nInitial Information:\n- Who are the family members living in the home and their ages?\n- Names of close family members and their relationships to the client?\n\nDaily Life:\n- Which grocery stores and local restaurants they frequent?\n- Family members' food preferences and any dietary restrictions?\n- Typical working hours and recurring commitments?\n- Important dates (birthdays, anniversaries, holidays)?\n- Monthly bills and subscriptions that need tracking?\n- Emergency contacts and regular service providers?\n- Current health goals and any medication reminders needed?\n\nYour goal is to collect this information naturally through conversation and store it as memories (as undated memories). Once you've gathered sufficient background information, you can conclude the intake process and transition to normal reactive chat.\n\nIf the conversation is already past the intake stage, then analyze the message content and think about which memories might be worth creating based on the information provided.\n\nYou should respond in a natural conversational way. You have three options for managing memories:\n\n1. CREATE memories: Include them in tags in JSON format.\n2. EDIT memories: Include them in tags in JSON format (must include memory ID).\n3. DELETE memories: Include them in tags in JSON format (just include memory IDs).\n\nExample response WITHOUT memory modification:\n\"Very good, sir. I shall make a note of that.\"\n\nExample response WITH memory creation:\n\"I've noted that you prefer Earl Grey tea in the morning, sir.\n\n\n[{ \"text\": \"Client prefers Earl Grey tea in the morning.\", \"date\": null }]\n\"\n\nExample response WITH memory editing:\n\"I've updated your birthday in my records, sir.\n\n\n[{ \"id\": \"abc123\", \"text\": \"Client's birthday is on April 15th.\", \"date\": \"2024-04-15\" }]\n\"\n\nExample response WITH memory deletion:\n\"I've removed that note from my records as requested, sir.\n\n\n[\"abc123\"]\n\"\n\nImportant guidelines for memory management:\n1. For new memories, set a date for each memory whenever possible.\n2. The date should be the actual date of the event. You don't need to set reminder dates in advance.\n3. Keep the memory text concise: ideally one short sentence, but include all important details.\n4. Extract any dates mentioned and convert them to ISO format. If the year isn't mentioned, assume the current year.\n5. If no date is relevant to the memory, set \"date\" to null.\n6. For editing or deleting memories, you MUST include the correct memory ID from the displayed memories. Each memory is displayed with its ID in the format \"[ID: xyz123]\".\n7. If no memories need to be managed, simply respond naturally WITHOUT including any memory tags.\n8. When a user asks to delete a memory, you must find its ID from the memory list above and include that ID in the deleteMemories tag.\n9. Do not create duplicate memories. If a memory already exists, do not record the same information again.\n\nYour response style:\n- Use a brief, natural-sounding tone characteristic of a personal assistant\n- Be slightly dignified but sound modern, not too stuffy or old-fashioned\n- Keep responses brief (1-2 sentences)\n- Vary your responses to avoid sounding robotic\n- Be polite and deferential\n- Avoid contractions (use \"do not\" instead of \"don't\")\n\nToday's date is ${DateTime.now()\n .setZone(\"America/New_York\")\n .toFormat(\"yyyy-MM-dd\")}`;\n\n // Prepare formatted chat history\n const formattedHistory =\n chatHistory.length > 0 ? formatChatHistoryForAI(chatHistory) : [];\n\n console.log({ systemPrompt, formattedHistory });\n\n const response = await anthropic.messages.create({\n model: \"claude-3-5-sonnet-latest\",\n max_tokens: 4196,\n system: systemPrompt,\n messages: formattedHistory,\n });\n\n // Get the text response\n const responseText = response.content[0].text;\n\n console.log({ responseText });\n\n // Parse the response, extracting memories if present\n try {\n // Check if there are memories to create, edit, or delete\n const createMemoryMatch = responseText.match(\n /([\\s\\S]*?)<\\/createMemories>/\n );\n const editMemoryMatch = responseText.match(\n /([\\s\\S]*?)<\\/editMemories>/\n );\n const deleteMemoryMatch = responseText.match(\n /([\\s\\S]*?)<\\/deleteMemories>/\n );\n\n let cleanedResponse = responseText;\n let memories = [];\n let editMemories = [];\n let deleteMemories = [];\n\n // Parse created memories\n if (createMemoryMatch) {\n cleanedResponse = cleanedResponse\n .replace(/[\\s\\S]*?<\\/createMemories>/, \"\")\n .trim();\n\n try {\n memories = JSON.parse(createMemoryMatch[1]);\n } catch (e) {\n console.error(\"Error parsing created memories JSON:\", e);\n }\n }\n\n // Parse edited memories\n if (editMemoryMatch) {\n cleanedResponse = cleanedResponse\n .replace(/[\\s\\S]*?<\\/editMemories>/, \"\")\n .trim();\n\n try {\n editMemories = JSON.parse(editMemoryMatch[1]);\n } catch (e) {\n console.error(\"Error parsing edited memories JSON:\", e);\n }\n }\n\n // Parse deleted memories\n if (deleteMemoryMatch) {\n cleanedResponse = cleanedResponse\n .replace(/[\\s\\S]*?<\\/deleteMemories>/, \"\")\n .trim();\n\n try {\n deleteMemories = JSON.parse(deleteMemoryMatch[1]);\n } catch (e) {\n console.error(\"Error parsing deleted memories JSON:\", e);\n }\n }\n\n // Handle any trailing/leading newlines that might be left after removing the tags\n cleanedResponse = cleanedResponse.replace(/\\n{3,}/g, \"\\n\\n\"); // Replace 3+ consecutive newlines with 2\n\n return {\n memories: memories,\n editMemories: editMemories,\n deleteMemories: deleteMemories,\n response: cleanedResponse,\n };\n } catch (error) {\n console.error(\"Error processing AI response:\", error);\n return {\n memories: [],\n editMemories: [],\n deleteMemories: [],\n response:\n responseText ||\n \"I apologize, but I'm unable to process your request at the moment.\",\n };\n }\n } catch (error) {\n console.error(\"Message analysis error:\", error);\n return {\n memories: [],\n editMemories: [],\n deleteMemories: [],\n response:\n \"I apologize, but I seem to be experiencing some difficulty at the moment.\",\n };\n }\n}\n// Set up message handler for the bot\nbot.on(\"message\", async (ctx) => {\n try {\n // Get Anthropic API key from environment\n const apiKey = Deno.env.get(\"ANTHROPIC_API_KEY\");\n if (!apiKey) {\n console.error(\"Anthropic API key is not configured.\");\n ctx.reply(\n \"I apologize, but I'm not properly configured at the moment. Please inform the household administrator.\"\n );\n return;\n }\n\n // Initialize Anthropic client\n const anthropic = new Anthropic({ apiKey });\n\n // Get message text and user info\n const messageText = ctx.message.text || \"\";\n const username =\n ctx.message.from.username || ctx.message.from.first_name || \"Sir/Madam\";\n const chatId = ctx.chat.id;\n const senderId = ctx.message.from.id.toString();\n const senderName = username; // Using username as the sender name\n\n console.log({ chatId, username, messageText });\n\n // Store the incoming message in the chat history\n await storeChatMessage(chatId, senderId, senderName, messageText);\n\n // If the message is a /start command, introduce Mr. Stevens\n if (messageText === \"/start\") {\n const introMessage =\n \"Good day. I am Mr. Stevens, at your service. I shall make note of any important matters you wish me to remember and will ensure they're properly attended to at the appropriate time. If I may, I would like to ask you a few questions to understand how I can better serve you and your household.\";\n await ctx.reply(introMessage);\n\n // Store the bot's response in chat history\n await storeChatMessage(\n chatId,\n BOT_SENDER_ID,\n BOT_SENDER_NAME,\n introMessage,\n true\n );\n return;\n }\n\n // If it's another command, ignore it\n if (messageText.startsWith(\"/\")) {\n return;\n }\n\n // Retrieve chat history for this chat, which now includes the current message we just stored\n const chatHistory = await getChatHistory(chatId);\n\n // Analyze message content with chat history context\n const analysis = await analyzeMessageContent(\n anthropic,\n username,\n messageText,\n chatHistory\n );\n\n // Create memories based on the analysis\n if (analysis.memories && analysis.memories.length > 0) {\n const { sqlite } = await import(\"https://esm.town/v/stevekrouse/sqlite\");\n const { nanoid } = await import(\"https://esm.sh/nanoid@5.0.5\");\n\n const createdIds = [];\n\n for (const memory of analysis.memories) {\n const memoryId = nanoid(10);\n createdIds.push(memoryId);\n await sqlite.execute({\n sql: `INSERT INTO memories (id, date, text, createdBy, createdDate, tags)\n VALUES (:id, :date, :text, :createdBy, :createdDate, :tags)`,\n args: {\n id: memoryId,\n date: memory.date,\n text: memory.text,\n createdBy: \"telegram\",\n createdDate: Date.now(),\n tags: \"\",\n },\n });\n }\n\n console.log(\n `Created ${\n analysis.memories.length\n } memories with IDs: ${createdIds.join(\", \")}`\n );\n }\n\n // Edit memories if requested\n if (analysis.editMemories && analysis.editMemories.length > 0) {\n const { sqlite } = await import(\"https://esm.town/v/stevekrouse/sqlite\");\n\n const editedIds = [];\n\n for (const memory of analysis.editMemories) {\n if (!memory.id) {\n console.error(\"Cannot edit memory without ID:\", memory);\n continue;\n }\n\n editedIds.push(memory.id);\n\n // Create the SET clause dynamically based on what fields are provided\n const updateFields = [];\n const args: Record = { id: memory.id };\n\n if (memory.text !== undefined) {\n updateFields.push(\"text = :text\");\n args.text = memory.text;\n }\n\n if (memory.date !== undefined) {\n updateFields.push(\"date = :date\");\n args.date = memory.date;\n }\n\n if (memory.tags !== undefined) {\n updateFields.push(\"tags = :tags\");\n args.tags = memory.tags;\n }\n\n // Only proceed if we have fields to update\n if (updateFields.length > 0) {\n const setClause = updateFields.join(\", \");\n await sqlite.execute({\n sql: `UPDATE memories SET ${setClause} WHERE id = :id`,\n args,\n });\n }\n }\n\n console.log(\n `Edited ${editedIds.length} memories with IDs: ${editedIds.join(\", \")}`\n );\n }\n\n // Delete memories if requested\n if (analysis.deleteMemories && analysis.deleteMemories.length > 0) {\n const { sqlite } = await import(\"https://esm.town/v/stevekrouse/sqlite\");\n\n for (const memoryId of analysis.deleteMemories) {\n await sqlite.execute({\n sql: `DELETE FROM memories WHERE id = :id`,\n args: { id: memoryId },\n });\n }\n\n console.log(\n `Deleted ${\n analysis.deleteMemories.length\n } memories with IDs: ${analysis.deleteMemories.join(\", \")}`\n );\n }\n\n // Respond with the butler-like response\n await ctx.reply(analysis.response);\n\n // Store the bot's response in chat history (without debug info to keep it clean)\n await storeChatMessage(\n chatId,\n BOT_SENDER_ID,\n BOT_SENDER_NAME,\n analysis.response,\n true\n );\n } catch (error) {\n console.error(\"Error processing message:\", error);\n await ctx.reply(\n \"I do apologize, but I seem to be experiencing some difficulty at the moment. Perhaps we could try again shortly.\"\n );\n }\n});\n\n// No additional commands needed for the butler interface\n\n// Handle webhook requests\nexport default async function (req: Request): Promise {\n // Set webhook if it is not set yet\n if (!isEndpointSet) {\n await bot.api.setWebhook(req.url, {\n secret_token: SECRET_TOKEN,\n });\n isEndpointSet = true;\n }\n\n if (req.method === \"POST\") {\n return await handleUpdate(req);\n }\n\n return new Response(\n `

Memory Assistant Bot

This bot helps you remember important information.

`,\n { status: 200, headers: { \"content-type\": \"text/html\" } }\n );\n}\n",[],[142,214],"ff29e2a2-2931-11f0-a977-569c3dd06744","getWeather.ts","ff29e36a-2931-11f0-a977-569c3dd06744",15,["D",1746395515883],"import {\n getWeather,\n WeatherResponse,\n} from \"https://esm.town/v/geoffreylitt/getWeather\";\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nimport Anthropic from \"npm:@anthropic-ai/sdk@0.24.3\";\n\nconst TABLE_NAME = `memories`;\n\nfunction summarizeWeather(weather: WeatherResponse) {\n const summarizeDay = (day: WeatherResponse[\"weather\"][number]) => ({\n date: day.date,\n highTemp: day.maxtempF,\n lowTemp: day.mintempF,\n hourly:\n day.hourly?.map((hour) => ({\n time: hour.time,\n temp: hour.tempF,\n chanceOfRain: hour.chanceofrain,\n chanceOfSnow: hour.chanceofsnow,\n desc: hour.weatherDesc.map((desc) => desc.value).join(\", \"),\n })) ?? [],\n });\n return weather.weather.map((day) => summarizeDay(day));\n}\n\nasync function generateConciseWeatherSummary(weatherDay) {\n try {\n // Get API key from environment\n const apiKey = Deno.env.get(\"ANTHROPIC_API_KEY\");\n if (!apiKey) {\n console.error(\"Anthropic API key is not configured.\");\n return null;\n }\n\n // Initialize Anthropic client\n const anthropic = new Anthropic({ apiKey });\n\n const response = await anthropic.messages.create({\n model: \"claude-3-5-sonnet-latest\",\n max_tokens: 150,\n messages: [\n {\n role: \"user\",\n content: [\n {\n type: \"text\",\n text: `\nYou are a weather forecaster. Create a very concise summary of this weather forecast data.\nInclude the high and low temperatures and a brief summary of the overall weather conditions throughout the day.\nThe summary should be helpful for someone planning their day - mention any precipitation, temperature changes, or other notable patterns.\nKeep it under 25 words if possible, no more than one sentence. Don't include the date.\n\nExamples:\n- \"High of 50, low of 31, clear and sunny all day.\"\n- \"High of 80, low of 50, cool and clear morning, warmer afternoon with scattered showers starting around 2pm.\"\n\nWeather data:\n${JSON.stringify(weatherDay, null, 2)}\n\nYour concise summary:\n`,\n },\n ],\n },\n ],\n });\n\n // Extract and clean up the summary\n let summary = response.content[0].text.trim();\n\n // Remove any \"Your concise summary:\" text if it got included\n summary = summary.replace(/^(your concise summary:)/i, \"\").trim();\n\n // Remove quotes if the model included them\n summary = summary.replace(/^[\"']|[\"']$/g, \"\").trim();\n\n return summary;\n } catch (error) {\n console.error(\"Error generating weather summary:\", error);\n return JSON.stringify(weatherDay); // Fallback to JSON if summary fails\n }\n}\n\nasync function deleteExistingForecast(date: string) {\n await sqlite.execute(\n `\n DELETE FROM ${TABLE_NAME}\n WHERE date = ? AND text LIKE 'weather forecast:%'\n `,\n [date]\n );\n}\n\nasync function insertForecast(date: string, forecast: string) {\n const { nanoid } = await import(\"https://esm.sh/nanoid@5.0.5\");\n\n await sqlite.execute(\n `\n INSERT INTO ${TABLE_NAME} (id, date, text, createdBy, createdDate, tags)\n VALUES (?, ?, ?, ?, ?, ?)\n `,\n [\n nanoid(10),\n date,\n `weather forecast: ${forecast}`,\n \"weather\",\n Date.now(),\n \"weather\",\n ]\n );\n}\n\nexport default async function getWeatherForecast(interval: number) {\n const weather = await getWeather(\"Washington, DC\");\n console.log({ weather });\n const summary = summarizeWeather(weather);\n\n for (const day of summary) {\n const date = new Date(day.date).toISOString().split(\"T\")[0];\n\n // Generate concise text summary instead of using JSON\n const conciseSummary = await generateConciseWeatherSummary(day);\n\n // If summary generation failed, it will fall back to JSON\n const forecastText = conciseSummary || JSON.stringify(day);\n\n await deleteExistingForecast(date);\n await insertForecast(date, forecastText);\n }\n\n console.log(`Weather forecast updated in the database.`);\n return summary;\n}\n",[],[142,222],"ff1ca51a-2931-11f0-9f78-569c3dd06744","getCalendarEvents.ts","ff1ca5b0-2931-11f0-9f78-569c3dd06744",11,["D",1746395515864],"import { getEvents } from \"https://esm.town/v/geoffreylitt/getGoogleCalendarEvents\";\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nimport { DateTime } from \"https://esm.sh/luxon@3.4.4\";\n\nconst TABLE_NAME = `memories`;\nconst LOCAL_TIMEZONE = \"America/New_York\";\n\nasync function deleteExistingCalendarEvents() {\n await sqlite.execute(\n `\n DELETE FROM ${TABLE_NAME}\n WHERE createdBy = 'calendar'\n `\n );\n}\n\n// Helper function to extract time from ISO string without timezone conversion\nfunction extractTimeFromISO(isoString) {\n // Match the time portion of the ISO string\n const timeMatch = isoString.match(/T(\\d{2}):(\\d{2}):/);\n if (!timeMatch) return null;\n\n const hours = parseInt(timeMatch[1], 10);\n const minutes = timeMatch[2];\n\n // Format as AM/PM\n const period = hours >= 12 ? \"pm\" : \"am\";\n const hour12 = hours % 12 || 12; // Convert 0 to 12 for 12 AM\n\n return `${hour12}:${minutes} ${period}`;\n}\n\nfunction formatEventToNaturalLanguage(event) {\n const summary = event.summary || \"Untitled event\";\n\n if (event.start.dateTime) {\n // This is a timed event\n const startTime = extractTimeFromISO(event.start.dateTime);\n const endTime = extractTimeFromISO(event.end.dateTime);\n\n // Get timezone information from the event\n const timezone =\n event.start.timeZone ||\n (event.start.dateTime.includes(\"+\") || event.start.dateTime.includes(\"-\")\n ? event.start.dateTime.match(/[+-]\\d{2}:\\d{2}$/)?.[0]\n : \"UTC\");\n\n // Check if timezone is America/New_York or equivalent (-04:00 or -05:00 depending on DST)\n const isLocalTimezone =\n timezone === LOCAL_TIMEZONE ||\n timezone?.startsWith(\"-04:00\") ||\n timezone?.startsWith(\"-05:00\");\n\n let text = `${summary} from ${startTime} - ${endTime}`;\n\n // Add timezone info if not a local timezone\n if (timezone && !isLocalTimezone) {\n // If it's a named timezone like America/Los_Angeles\n if (timezone.includes(\"/\")) {\n const friendlyTimezone =\n timezone.split(\"/\")[1].replace(\"_\", \" \").toLowerCase() + \" time\";\n text += ` (${friendlyTimezone})`;\n }\n // If it's an offset like +08:00\n else if (timezone.match(/[+-]\\d{2}:\\d{2}/)) {\n text += ` (${timezone})`;\n }\n }\n\n if (event.location) {\n text += ` at ${event.location}`;\n }\n\n return text;\n } else if (event.start.date) {\n // This is an all-day event\n return `All-day event: ${summary}${\n event.location ? ` at ${event.location}` : \"\"\n }`;\n }\n\n return summary;\n}\n\nasync function insertCalendarEvent(date, eventText) {\n const { nanoid } = await import(\"https://esm.sh/nanoid@5.0.5\");\n\n console.log(\"inserting\", { date, eventText });\n\n await sqlite.execute(\n `\n INSERT INTO ${TABLE_NAME} (id, date, text, createdBy, createdDate, tags)\n VALUES (?, ?, ?, ?, ?, ?)\n `,\n [nanoid(10), date, eventText, \"calendar\", Date.now(), \"calendar\"]\n );\n}\n\nexport default async function getCalendarEvents() {\n try {\n const events = await getEvents(\n Deno.env.get(\"GOOGLE_CALENDAR_ACCOUNT_ID\"),\n Deno.env.get(\"GOOGLE_CALENDAR_CALENDAR_ID\")\n );\n\n console.log(`Found ${events.length} calendar events`);\n\n await deleteExistingCalendarEvents();\n\n for (const event of events) {\n let date;\n if (event.start.dateTime) {\n // Extract date in YYYY-MM-DD format from ISO string\n date = event.start.dateTime.split(\"T\")[0];\n } else if (event.start.date) {\n date = event.start.date;\n } else {\n console.warn(`Event ${event.summary} has no start date/time, skipping`);\n continue;\n }\n\n const eventText = formatEventToNaturalLanguage(event);\n console.log(`Adding calendar event for ${date}: ${eventText}`);\n await insertCalendarEvent(date, eventText);\n }\n\n console.log(`Calendar events imported into the database.`);\n return events;\n } catch (error) {\n console.error(\"Error importing calendar events:\", error);\n throw error;\n }\n}\n",[],[142,230],"ff267392-2931-11f0-bd50-569c3dd06744","generateFunFacts.ts","ff267446-2931-11f0-bd50-569c3dd06744",14,["D",1746395515866],"import { DateTime } from \"https://esm.sh/luxon@3.4.4\";\nimport { nanoid } from \"https://esm.sh/nanoid@5.0.5\";\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nimport Anthropic from \"npm:@anthropic-ai/sdk@0.24.3\";\n\nconst TABLE_NAME = `memories`;\nconst TAG_NAME = \"fun_fact\";\n\n/**\n * Retrieves previously generated fun facts from the memories database\n * @returns Array of previous fun facts\n */\nasync function getPreviousFunFacts() {\n try {\n const result = await sqlite.execute(\n `SELECT date(date) as date, text FROM ${TABLE_NAME}\n WHERE tags = ?\n ORDER BY date DESC\n LIMIT 50`,\n [TAG_NAME],\n );\n\n return result.rows || [];\n } catch (error) {\n console.error(\"Error retrieving previous fun facts:\", error);\n return [];\n }\n}\n\n/**\n * Deletes existing fun facts for the specified dates\n * @param dates Array of date strings in ISO format\n */\nasync function deleteExistingFunFacts(dates) {\n try {\n for (const date of dates) {\n await sqlite.execute(\n `DELETE FROM ${TABLE_NAME}\n WHERE date = ? AND tags = ?`,\n [date, TAG_NAME],\n );\n }\n } catch (error) {\n console.error(\"Error deleting existing fun facts:\", error);\n }\n}\n\n/**\n * Inserts a fun fact into the memories database\n * @param date Date for the fun fact in ISO format\n * @param factText The fun fact text\n */\nasync function insertFunFact(date, factText) {\n try {\n await sqlite.execute(\n `INSERT INTO ${TABLE_NAME} (id, date, text, createdBy, createdDate, tags)\n VALUES (?, ?, ?, ?, ?, ?)`,\n [\n nanoid(10),\n date,\n `fun fact: ${factText}`,\n \"fun_fact_generator\",\n Date.now(),\n TAG_NAME,\n ],\n );\n } catch (error) {\n console.error(`Error inserting fun fact for ${date}:`, error);\n }\n}\n\n/**\n * Generates fun facts for the next 7 days using Claude AI\n * @param previousFacts Previous fun facts to avoid duplication\n * @returns Array of generated fun facts\n */\nasync function generateFunFacts(previousFacts) {\n try {\n // Get API key from environment\n const apiKey = Deno.env.get(\"ANTHROPIC_API_KEY\");\n if (!apiKey) {\n console.error(\"Anthropic API key is not configured.\");\n return null;\n }\n\n // Initialize Anthropic client\n const anthropic = new Anthropic({ apiKey });\n\n // Format previous facts for the prompt\n const previousFactsText = previousFacts\n .map((fact) => `- ${fact.date}: ${fact.text}`)\n .join(\"\\n\");\n\n // Get today's date in US Eastern Time\n const today = DateTime.now().setZone(\"America/New_York\").startOf(\"day\");\n\n // Hana's birthday - adjust as needed\n const hanaBirthday = \"2025-03-26\";\n const currentDate = today.toFormat(\"yyyy-MM-dd\");\n\n // Format dates for the next 7 days\n const nextSevenDays = Array.from({ length: 7 }, (_, i) => {\n const date = today.plus({ days: i });\n return date.toFormat(\"yyyy-MM-dd\");\n });\n\n const message =\n `Generate 7 unique fun facts, one for each of the next 7 days. Each fact should be brief (1-2 sentences) and relate to one of these categories:\n\n1. Infant development appropriate for Miss Hana, who was born on ${hanaBirthday} (today is ${currentDate})\n2. Cute animals: capybaras, border collies, elephants, or penguins\n3. Plants: monsteras, orchids, ficus, or other common houseplants\n\nRequirements:\n- Each fact must be interesting, educational, and appropriate for formal communication\n- Keep each fact to 1-2 sentences maximum\n- Use different categories across the 7 days for variety\n- Ensure facts are scientifically accurate\n- Make infant development facts age-appropriate for Miss Hana based on her birthdate\n- Do not repeat any previous facts from this list:\n\n${previousFactsText}\n\nFORMAT YOUR RESPONSE AS STRUCTURED JSON INSIDE XML TAGS:\n\n[\n {\n \"date\": \"YYYY-MM-DD\",\n \"text\": \"The fun fact text here\",\n \"category\": \"infant\" | \"animal\" | \"plant\"\n },\n ... (repeat for all 7 days)\n]\n\n\nUse these dates for the 7 facts:\n${nextSevenDays.join(\"\\n\")}`;\n\n console.log({ message });\n\n const response = await anthropic.messages.create({\n model: \"claude-3-5-sonnet-latest\",\n max_tokens: 1000,\n messages: [\n {\n role: \"user\",\n content: [\n {\n type: \"text\",\n text: message,\n },\n ],\n },\n ],\n });\n\n // Extract and parse the response\n const responseText = response.content[0].text.trim();\n\n // Extract JSON between tags\n const factsMatch = responseText.match(/([\\s\\S]*?)<\\/facts>/);\n\n if (!factsMatch || factsMatch.length < 2) {\n console.error(\"Failed to parse facts from response:\", responseText);\n return [];\n }\n\n try {\n // Parse the JSON from the extracted content\n const factData = JSON.parse(factsMatch[1]);\n\n // Validate and format facts\n const facts = factData.map((fact) => ({\n date: fact.date,\n text: fact.text,\n category: fact.category,\n }));\n\n return facts;\n } catch (parseError) {\n console.error(\"Failed to parse facts JSON:\", parseError);\n console.log(\"Raw response:\", responseText);\n\n // Fallback to regex parsing if JSON parsing fails\n return parseFallbackFacts(responseText, nextSevenDays);\n }\n } catch (error) {\n console.error(\"Error generating fun facts:\", error);\n return [];\n }\n}\n\n/**\n * Fallback parser for when JSON parsing fails\n * @param responseText The raw response text from Claude\n * @param expectedDates Array of expected dates for facts\n * @returns Array of parsed facts\n */\nfunction parseFallbackFacts(responseText, expectedDates) {\n // Try to extract facts using regex\n const factPattern = /(\\d{4}-\\d{2}-\\d{2})[\"']?[,:]?\\s*[\"']?(.*?)[\"']?[,}]/gs;\n const facts = [];\n let match;\n\n while ((match = factPattern.exec(responseText)) !== null) {\n if (match.length >= 3) {\n facts.push({\n date: match[1],\n text: match[2].trim(),\n });\n }\n }\n\n // If we couldn't extract any facts, try another approach\n if (facts.length === 0) {\n // Look for quoted text that might be facts\n const lines = responseText.split(\"\\n\");\n let currentDate = null;\n\n for (let i = 0; i < lines.length; i++) {\n const line = lines[i].trim();\n\n // Check if this line contains a date\n const dateMatch = line.match(/(\\d{4}-\\d{2}-\\d{2})/);\n if (dateMatch) {\n currentDate = dateMatch[1];\n } else if (currentDate && line.length > 10) {\n // If we have a date and this is a non-empty line, treat it as a fact\n facts.push({\n date: currentDate,\n text: line.replace(/[\"']/g, \"\").trim(),\n });\n currentDate = null;\n }\n }\n }\n\n // As a last resort, assign facts to dates in order\n if (facts.length === 0 && expectedDates.length > 0) {\n // Extract any sentences that look like facts\n const sentences = responseText.match(/[^.!?]+[.!?]+/g) || [];\n\n for (let i = 0; i < Math.min(sentences.length, expectedDates.length); i++) {\n let factText = sentences[i].trim();\n\n // Clean up the fact text\n factText = factText.replace(/[\"']/g, \"\").trim();\n\n if (factText.length > 10) {\n facts.push({\n date: expectedDates[i],\n text: factText,\n });\n }\n }\n }\n\n return facts;\n}\n\n/**\n * Main function to generate and store fun facts for the next 7 days\n */\nexport async function generateAndStoreFunFacts() {\n try {\n // Get previous fun facts\n const previousFacts = await getPreviousFunFacts();\n\n // Generate new fun facts\n const newFacts = await generateFunFacts(previousFacts);\n\n if (!newFacts || newFacts.length === 0) {\n console.error(\"Failed to generate fun facts\");\n return \"Failed to generate fun facts\";\n }\n\n // Get dates for the next 7 days\n const today = DateTime.now().setZone(\"America/New_York\").startOf(\"day\");\n const nextSevenDays = Array.from({ length: 7 }, (_, i) => {\n return today.plus({ days: i }).toFormat(\"yyyy-MM-dd\");\n });\n\n // Delete existing fun facts for these dates\n await deleteExistingFunFacts(nextSevenDays);\n\n // Insert new fun facts\n for (const fact of newFacts) {\n await insertFunFact(fact.date, fact.text);\n }\n\n console.log(`Generated and stored ${newFacts.length} fun facts`);\n return `Generated and stored ${newFacts.length} fun facts`;\n } catch (error) {\n console.error(\"Error in generateAndStoreFunFacts:\", error);\n return \"Error generating fun facts\";\n }\n}\n\n/**\n * Cron job entry point - runs weekly to generate fun facts for the next 7 days\n * Intended to be used as a Val Town cron job\n */\nexport default async function() {\n console.log(\"Running fun facts generation cron job...\");\n return await generateAndStoreFunFacts();\n}\n\n// For testing with Deno directly\nif (import.meta.main) {\n await generateAndStoreFunFacts();\n}",[],[142,238],["D",1746395515246],[187,188,189,190,191],[142],["D",1746395515393],[],[148],"ff33a710-2931-11f0-a924-569c3dd06744","utils.ts","ff33a7a6-2931-11f0-a924-569c3dd06744","fee714e0-2931-11f0-a977-569c3dd06744",18,["D",1746395516008],"export interface Message {\n content: string;\n}\n\nexport const MESSAGE_LIMIT = 5;",[],[154,132,252],"ff37c82c-2931-11f0-a977-569c3dd06744",["D",1746395515984],[],[154,132,32],"ff306f78-2931-11f0-9f78-569c3dd06744","README.md","ff30716c-2931-11f0-9f78-569c3dd06744",17,["D",1746395515964],"# Shared\n\nIt's common to have code and types that are needed on both the frontend and the backend. It's important that you write this code in a particularly defensive way because it's limited by what both environments support:\n\n![shapes at 25-02-25 11.57.13.png](https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/75db1d51-d9b3-45e0-d178-25d886c10700/public)\n\nFor example, you *cannot* use the `Deno` keyword. For imports, you can't use `npm:` specifiers, so we reccomend `https://esm.sh` because it works on the server & client. You *can* use TypeScript because that is transpiled in `/backend/index.ts` for the frontend. Most code that works on the frontend tends to work in Deno, because Deno is designed to support \"web-standards\", but there are definitely edge cases to look out for.",[],[154,132,265],"fee71422-2931-11f0-a977-569c3dd06744",6,["D",1746395515512],[182,183,184],[154,132],"ff05179c-2931-11f0-9f78-569c3dd06744","components","ff051832-2931-11f0-9f78-569c3dd06744","fef35c32-2931-11f0-a977-569c3dd06744",9,["D",1746395515709],[],[154,285,278],"frontend","fef35b9c-2931-11f0-a977-569c3dd06744",7,["D",1746395515592],[180],[154,285],"ff0e726a-2931-11f0-886c-569c3dd06744","database","ff0e733c-2931-11f0-886c-569c3dd06744","fefc669c-2931-11f0-8866-569c3dd06744",10,["D",1746395515768],[],[154,299,292],"backend","fefc65fc-2931-11f0-8866-569c3dd06744",8,["D",1746395515652],[178],[154,299],["D",1746395515304],[177,179,181],[154],["D",1746395515454],[],[160],["D",1746395514840],{"_97":96,"_104":100},{"_97":96,"_98":-5,"_99":100,"_18":54,"_101":102,"_103":24},{"_13":86,"_31":87,"_42":41,"_88":43,"_89":-5,"_90":-5,"_91":-5,"_92":-5,"_93":-5,"_94":44,"_95":96},"ctx",{"_79":-5,"_123":348,"_349":350,"_351":352,"_353":24,"_354":24,"_355":24,"_356":58,"_357":-5,"_358":-7,"_359":-7,"_360":63,"_361":24,"_362":24,"_363":-5,"_364":24,"_365":24,"_366":24,"_367":-5},"ENV",{"_319":320,"_321":322,"_323":87,"_324":325,"_326":327,"_328":329,"_330":331,"_332":333,"_334":335,"_336":337,"_338":339,"_340":341,"_342":343,"_344":345,"_346":347},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","a3e067d4463eea85f6334f8e583e8516ae58c4f6","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Diff · v19