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digest of all my unread Feedbin","imageUrl","3ee322c5-8742-48e0-86c7-5f3ae129683b","pinnedFileId","pinPreview",true,"pinMigrated","screenshotVersion","likeCount","f427167a-3263-4778-81d8-f79626323ff5","tursoName","tursoHostname","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm",{"_95":96,"_136":137},"profileImageUrl","https://img.clerk.com/eyJ0eXBlIjoicHJveHkiLCJzcmMiOiJodHRwczovL2ltYWdlcy5jbGVyay5kZXYvb2F1dGhfZ2l0aHViL2ltZ18yaVpXT3l1d2hWSFdtWTNoZFIwZ0lFUUhOd2oifQ","org",{"_95":96,"_140":137,"_14":116,"_141":142},"avatar","tier","pro","branch",{"_102":145,"_97":45,"_105":146,"_147":106,"_148":-5,"_149":-5,"_150":-5,"_151":-5,"_152":-5,"_153":98,"_154":96},47,"5021610e-275b-11f0-86ff-569c3dd06744","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","isOwned","tree",[158,179,190,201],{"_105":159,"_97":160,"_161":162,"_163":-5,"_164":146,"_165":166,"_167":119,"_107":168,"_102":169,"_170":171,"_172":173,"_174":22,"_175":-5,"_176":177,"_100":178},"7141e93e-e75f-11f0-b535-42dde27851f2","README.md","fileId","50240094-275b-11f0-86ff-569c3dd06744","parentId","branchId","branchVersion",41,"latest",["D",1767305755641],1,"fileType","file","content","This Val automatically sends a message to your slack a daily digest of your\nunread Feedbin articles, summarized by Claude!","deleted","label","children",[],[160],{"_105":180,"_97":181,"_161":182,"_163":-5,"_164":146,"_165":183,"_167":119,"_107":184,"_102":185,"_170":186,"_172":187,"_174":22,"_175":-5,"_176":188,"_100":189},"1ed7a610-e760-11f0-ae32-42dde27851f2","feedbinUnreads.ts","0ce08fbc-e760-11f0-9ce5-42dde27851f2",44,["D",1767306046873],2,"script","import { Buffer } from \"node:buffer\";\n\n// String format: eamil:password\nconst AUTH_STRING = Deno.env.get(\"FEEDBIN_USER\");\nconst BASE_URL = \"https://api.feedbin.com/v2/\";\n\nexport async function getFeedbinUnreadEntries() {\n const authString = Buffer.from(AUTH_STRING).toString(\"base64\");\n\n const headers = {\n \"Authorization\": `Basic ${authString}`,\n \"Content-Type\": \"application/json\",\n };\n\n // Step 1: Get unread entries ids\n const unreadResponse = await fetch(`${BASE_URL}unread_entries.json`, {\n method: \"GET\",\n headers: headers,\n });\n if (!unreadResponse.ok) {\n throw new Error(`Failed to fetch unread entries: ${unreadResponse.status}`);\n }\n\n const unreadEntryIds = await unreadResponse.json();\n if (unreadEntryIds.length === 0) {\n return { message: \"No unread entries found.\" };\n }\n\n // Step 2: Get entry details\n const entriesResponse = await fetch(\n `${BASE_URL}entries.json?ids=${unreadEntryIds.slice(0, 100).join(\",\")}`,\n {\n method: \"GET\",\n headers: headers,\n },\n );\n\n if (!entriesResponse.ok) {\n throw new Error(`Failed to fetch entry details: ${entriesResponse.status}`);\n }\n\n const unreadEntries = await entriesResponse.json();\n console.log(\"Unread Entries =>\", unreadEntries);\n\n // Step 3: Get feed information\n const feedsResponse = await fetch(`${BASE_URL}subscriptions.json`, {\n method: \"GET\",\n headers: headers,\n });\n\n if (!feedsResponse.ok) {\n throw new Error(\n `Failed to fetch feed information: ${feedsResponse.status}`,\n );\n }\n\n const feeds = await feedsResponse.json();\n const feedMap = {};\n\n feeds.forEach((feed) => {\n feedMap[feed.feed_id] = feed.title;\n });\n\n // Combine entry data with feed names\n const result = unreadEntries.map((entry) => {\n return {\n feed: feedMap[entry.feed_id] ?? \"Unknown Feed\",\n title: entry.title,\n url: entry.url,\n published: entry.published,\n content: entry.content,\n summary: entry.summary,\n };\n });\n\n return result;\n}",[],[181],{"_105":191,"_97":192,"_161":193,"_163":-5,"_164":146,"_165":194,"_167":119,"_107":195,"_102":196,"_170":197,"_172":198,"_174":22,"_175":-5,"_176":199,"_100":200},"5d3d5248-e75f-11f0-aa24-42dde27851f2","main.tsx","5023fc0c-275b-11f0-86ff-569c3dd06744",40,["D",1767305722062],36,"interval","import { postMessage } from \"https://esm.town/v/kamalnrf/sendMessageToSlack\";\nimport { summarizeFeedbinEntries } from \"./summarizeFeedbinEntries.ts\";\n\nexport async function dailyFeedbinDigest() {\n const result = await summarizeFeedbinEntries();\n\n if (!result.summaries || result.summaries.length === 0) {\n console.log(\"No unread entries to summarize.\");\n return { message: \"No unread entries to summarize.\" };\n }\n\n const summaries = result.summaries;\n\n // Create main message\n const mainMessageBlocks = [\n {\n \"type\": \"header\",\n \"text\": {\n \"type\": \"plain_text\",\n \"text\": `📰 Your Daily Feedbin Digest`,\n \"emoji\": true,\n },\n },\n {\n \"type\": \"context\",\n \"elements\": [\n {\n \"type\": \"plain_text\",\n \"text\": `${summaries.length} articles • ${\n new Date().toLocaleDateString(\"en-US\", {\n weekday: \"long\",\n month: \"long\",\n day: \"numeric\",\n })\n }`,\n \"emoji\": true,\n },\n ],\n },\n {\n \"type\": \"section\",\n \"text\": {\n \"type\": \"mrkdwn\",\n \"text\": `*Today's articles:*\\n${\n summaries.map((article, index) =>\n `${\n index + 1\n }. <${article.url}|${article.title}> - _${article.source}_`\n )\n .join(\"\\n\")\n }`,\n },\n },\n {\n \"type\": \"context\",\n \"elements\": [\n {\n \"type\": \"mrkdwn\",\n \"text\": \"💬 Full summaries available in thread\",\n },\n ],\n },\n ];\n\n // Post main message and get thread timestamp\n const mainResponse = await postMessage({\n blocks: mainMessageBlocks,\n });\n const threadTs = mainResponse.ts;\n\n // Send each article as a separate message in the thread\n for (const article of summaries) {\n const articleBlocks = [\n {\n \"type\": \"section\",\n \"text\": {\n \"type\": \"mrkdwn\",\n \"text\":\n `*<${article.url}|${article.title}>*\\n_From ${article.source}_`,\n },\n },\n {\n \"type\": \"section\",\n \"text\": {\n \"type\": \"mrkdwn\",\n \"text\": article.summary.tldr,\n },\n },\n {\n \"type\": \"section\",\n \"fields\": [\n {\n \"type\": \"mrkdwn\",\n \"text\": `*Key Points:*\\n${\n article.summary.keyPoints.map((point) => `• ${point}`).join(\"\\n\")\n }`,\n },\n ],\n },\n {\n \"type\": \"context\",\n \"elements\": [\n {\n \"type\": \"mrkdwn\",\n \"text\": `*Why It Matters:* ${article.summary.whyValuable}`,\n },\n ],\n },\n ];\n\n // Send thread reply\n await postMessage({\n blocks: articleBlocks,\n thread_ts: threadTs,\n });\n\n // Add a small delay between messages to avoid rate limiting\n await new Promise((resolve) => setTimeout(resolve, 500));\n }\n\n return {\n status: \"success\",\n message:\n `Slack message sent with ${summaries.length} article summaries in thread`,\n };\n}",[],[192],{"_105":202,"_97":101,"_161":203,"_163":-5,"_164":146,"_165":145,"_167":119,"_107":204,"_102":205,"_170":186,"_172":206,"_174":22,"_175":-5,"_176":207,"_100":208},"319af0a4-faed-11f0-9410-42dde27851f2","3c694f18-e75f-11f0-a4da-42dde27851f2",["D",1769455709480],5,"import { anthropic } from \"npm:@ai-sdk/anthropic\";\nimport { generateObject } from \"npm:ai\";\nimport { z } from \"npm:zod\";\nimport { getFeedbinUnreadEntries } from \"./feedbinUnreads.ts\";\n\nconst schema = z.object({\n tldr: z.string(),\n keyPoints: z.array(z.string()),\n whyValuable: z.string(),\n});\n\ntype Entry = {\n title: string;\n feed: string;\n url: string;\n published: string;\n content: string;\n};\n\ntype SuccessfulSummary = {\n success: true;\n summary: z.infer;\n entry: Entry;\n};\n\ntype FailedSummary = {\n success: false;\n entry: Entry;\n error: string;\n};\n\nconst model = anthropic(\"claude-haiku-4-5\");\n\nconst SYSTEM_PROMPT = `\nYou are an AI summarization assistant that extracts key information from articles into structured data.\n\nCRITICAL INSTRUCTIONS:\n- Summarize ALL articles provided\n- NEVER ask if the user wants you to continue\n- NEVER mention how many articles you've processed\n- NEVER say \"I'll summarize\" or similar phrases\n- NEVER add ANY text before the first summary or after the last summary\n- Format each summary as: ## [Title] ([Source]) followed by summary content\n- Include NO introduction and NO conclusion\n- End after the last summary with NO additional text\n\nFFORMAT FOR EACH SUMMARY:\n1. tldr: A concise 2-3 sentence summary (max 60 words) that captures the essence of the article\n2. keyPoints: 3-5 key takeaways from the article\n3. whyValuable: A brief explanation (1-2 sentences) of why this article is significant or useful to readers\n\nGUIDELINES:\n- Be factual and objective in your summaries\n- Highlight the most important information from the article\n- Use clear, straightforward language\n- Keep the entire summary between 100-150 words total\n- Avoid technical jargon unless necessary for the topic\n- Focus only on summarizing the content, not on the process\n`;\n\nexport async function summarizeFeedbinEntries() {\n try {\n const entries = await getFeedbinUnreadEntries();\n if (entries.length === 0) {\n return { message: \"No unread entries to summarize.\" };\n }\n\n // Prepare and filter entries\n const entriesForSummary = entries\n .map((entry) => {\n const cleanContent = stripHtml(entry.content);\n return {\n title: entry.title,\n feed: entry.feed,\n url: entry.url,\n published: entry.published,\n content: cleanContent,\n contentLength: cleanContent.length,\n };\n })\n .filter((entry) => entry.contentLength > 100);\n\n if (entriesForSummary.length === 0) {\n return { message: \"No entries with sufficient content to summarize.\" };\n }\n\n const MAX_ARTICLES = 10;\n const articlesToProcess = entriesForSummary.slice(0, MAX_ARTICLES);\n\n // Process each article\n const summaryPromises = articlesToProcess.map(async (entry) => {\n const singleArticlePrompt = `\n Summarize this article:\n \n Title: ${entry.title}\n Source: ${entry.feed}\n Published: ${new Date(entry.published).toLocaleDateString()}\n URL: ${entry.url}\n \n Content:\n ${entry.content}\n `;\n\n try {\n const { object: summary } = await generateObject({\n model,\n schema,\n prompt: singleArticlePrompt,\n system: SYSTEM_PROMPT,\n });\n\n console.log(summary);\n\n return {\n success: true,\n summary,\n entry,\n } as SuccessfulSummary;\n } catch (error) {\n console.log(\n `Error summarizing article \"${entry.title}\": ${error.message}`,\n );\n return {\n success: false,\n entry,\n error: error.message,\n } as FailedSummary;\n }\n });\n\n const summaryResults = await Promise.all(summaryPromises);\n const successfulResults = summaryResults.filter((\n result,\n ): result is SuccessfulSummary => result.success === true);\n\n const combinedSummaries = successfulResults.map(({ summary, entry }) => ({\n title: entry.title,\n source: entry.feed,\n url: entry.url,\n published: entry.published,\n summary,\n }));\n console.log(combinedSummaries);\n\n return {\n processedEntries: articlesToProcess.length,\n successfulEntries: successfulResults.length,\n summaries: combinedSummaries,\n };\n } catch (error) {\n console.log(\"Error =>\", error);\n return { error: error.message };\n }\n}\n\n// Helper function to strip HTML tags\nfunction stripHtml(html?: string) {\n if (!html || typeof html !== \"string\") {\n return \"\";\n }\n return html.replace(/<[^>]*>?/gm, \" \").replace(/\\s+/g, \" \").trim();\n}\n\n// await summarizeFeedbinEntries();",[],[101],"files",[158,179,190,201],"counts",{"_213":33,"_214":169,"_215":33,"_216":217,"_221":222},"pulls","branches","forks","envVars",{"_218":219,"_220":33},"count",7,"emptyCount","connections",{"_218":33,"_223":33},"unfilledCount","contents",[],{"_105":202,"_164":146,"_161":203,"_97":101,"_172":206,"_170":186,"_102":205,"_163":-5,"_107":227,"_165":145,"_175":-5,"_100":228},["D",1769455709480],[101],"upstreamProject","upstreamBranch","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.branch.$branch.history_.$",{"_95":96,"_97":98,"_99":45,"_100":101,"_103":237,"_171":242,"_245":246,"_275":276,"_284":-7,"_285":33,"_286":22},{"_105":106,"_97":98,"_107":238,"_109":-5,"_110":22,"_111":112,"_113":114,"_115":-5,"_14":116,"_117":-5,"_118":119,"_120":-5,"_121":-5,"_122":33,"_16":123,"_124":-5,"_125":-5,"_126":127,"_128":127,"_129":130,"_131":130,"_132":130,"_133":127,"_134":127,"_23":239,"_138":240,"_143":241,"_155":22},["D",1746193358831],{"_95":96,"_136":137},{"_95":96,"_140":137,"_14":116,"_141":142},{"_102":145,"_97":45,"_105":146,"_147":106,"_148":-5,"_149":-5,"_150":-5,"_151":-5,"_152":-5,"_153":98,"_154":96},{"_105":202,"_97":101,"_161":203,"_163":-5,"_164":146,"_165":145,"_167":119,"_107":243,"_102":205,"_170":186,"_172":206,"_174":22,"_175":-5,"_100":244},["D",1769455709480],[101],"history",[247,249,255,261,266,270],{"_105":202,"_164":146,"_161":203,"_97":101,"_172":206,"_170":186,"_102":205,"_163":-5,"_107":248,"_165":145,"_175":-5},["D",1769455709480],{"_105":250,"_164":146,"_161":203,"_97":101,"_172":251,"_170":186,"_102":252,"_163":-5,"_107":253,"_165":254,"_175":-5},"651862cc-e760-11f0-9828-42dde27851f2","import { anthropic } from \"npm:@ai-sdk/anthropic\";\nimport { generateObject } from \"npm:ai\";\nimport { z } from \"npm:zod\";\nimport { getFeedbinUnreadEntries } from \"./feedbinUnreads.ts\";\n\nconst schema = z.object({\n tldr: z.string(),\n keyPoints: z.array(z.string()),\n whyValuable: z.string(),\n});\n\ntype Entry = {\n title: string;\n feed: string;\n url: string;\n published: string;\n content: string;\n};\n\ntype SuccessfulSummary = {\n success: true;\n summary: z.infer;\n entry: Entry;\n};\n\ntype FailedSummary = {\n success: false;\n entry: Entry;\n error: string;\n};\n\nconst model = anthropic(\"claude-3-5-haiku-latest\");\n\nconst SYSTEM_PROMPT = `\nYou are an AI summarization assistant that extracts key information from articles into structured data.\n\nCRITICAL INSTRUCTIONS:\n- Summarize ALL articles provided\n- NEVER ask if the user wants you to continue\n- NEVER mention how many articles you've processed\n- NEVER say \"I'll summarize\" or similar phrases\n- NEVER add ANY text before the first summary or after the last summary\n- Format each summary as: ## [Title] ([Source]) followed by summary content\n- Include NO introduction and NO conclusion\n- End after the last summary with NO additional text\n\nFFORMAT FOR EACH SUMMARY:\n1. tldr: A concise 2-3 sentence summary (max 60 words) that captures the essence of the article\n2. keyPoints: 3-5 key takeaways from the article\n3. whyValuable: A brief explanation (1-2 sentences) of why this article is significant or useful to readers\n\nGUIDELINES:\n- Be factual and objective in your summaries\n- Highlight the most important information from the article\n- Use clear, straightforward language\n- Keep the entire summary between 100-150 words total\n- Avoid technical jargon unless necessary for the topic\n- Focus only on summarizing the content, not on the process\n`;\n\nexport async function summarizeFeedbinEntries() {\n try {\n const entries = await getFeedbinUnreadEntries();\n if (entries.length === 0) {\n return { message: \"No unread entries to summarize.\" };\n }\n\n // Prepare and filter entries\n const entriesForSummary = entries\n .map((entry) => {\n const cleanContent = stripHtml(entry.content);\n return {\n title: entry.title,\n feed: entry.feed,\n url: entry.url,\n published: entry.published,\n content: cleanContent,\n contentLength: cleanContent.length,\n };\n })\n .filter((entry) => entry.contentLength > 100);\n\n if (entriesForSummary.length === 0) {\n return { message: \"No entries with sufficient content to summarize.\" };\n }\n\n const MAX_ARTICLES = 10;\n const articlesToProcess = entriesForSummary.slice(0, MAX_ARTICLES);\n\n // Process each article\n const summaryPromises = articlesToProcess.map(async (entry) => {\n const singleArticlePrompt = `\n Summarize this article:\n \n Title: ${entry.title}\n Source: ${entry.feed}\n Published: ${new Date(entry.published).toLocaleDateString()}\n URL: ${entry.url}\n \n Content:\n ${entry.content}\n `;\n\n try {\n const { object: summary } = await generateObject({\n model,\n schema,\n prompt: singleArticlePrompt,\n system: SYSTEM_PROMPT,\n });\n\n console.log(summary);\n\n return {\n success: true,\n summary,\n entry,\n } as SuccessfulSummary;\n } catch (error) {\n console.log(\n `Error summarizing article \"${entry.title}\": ${error.message}`,\n );\n return {\n success: false,\n entry,\n error: error.message,\n } as FailedSummary;\n }\n });\n\n const summaryResults = await Promise.all(summaryPromises);\n const successfulResults = summaryResults.filter((\n result,\n ): result is SuccessfulSummary => result.success === true);\n\n const combinedSummaries = successfulResults.map(({ summary, entry }) => ({\n title: entry.title,\n source: entry.feed,\n url: entry.url,\n published: entry.published,\n summary,\n }));\n console.log(combinedSummaries);\n\n return {\n processedEntries: articlesToProcess.length,\n successfulEntries: successfulResults.length,\n summaries: combinedSummaries,\n };\n } catch (error) {\n console.log(\"Error =>\", error);\n return { error: error.message };\n }\n}\n\n// Helper function to strip HTML tags\nfunction stripHtml(html?: string) {\n if (!html || typeof html !== \"string\") {\n return \"\";\n }\n return html.replace(/<[^>]*>?/gm, \" \").replace(/\\s+/g, \" \").trim();\n}\n\n// await summarizeFeedbinEntries();",4,["D",1767306164735],46,{"_105":256,"_164":146,"_161":203,"_97":101,"_172":257,"_170":186,"_102":258,"_163":-5,"_107":259,"_165":260,"_175":-5},"3c6285ce-e760-11f0-b8d6-42dde27851f2","import { anthropic } from \"npm:@ai-sdk/anthropic\";\nimport { generateObject } from \"npm:ai\";\nimport { z } from \"npm:zod\";\nimport { getFeedbinUnreadEntries } from \"./feedbinUnreads.ts\";\n\nconst schema = z.object({\n tldr: z.string(),\n keyPoints: z.array(z.string()),\n whyValuable: z.string(),\n});\n\ntype Entry = {\n title: string;\n feed: string;\n url: string;\n published: string;\n content: string;\n};\n\ntype SuccessfulSummary = {\n success: true;\n summary: z.infer;\n entry: Entry;\n};\n\ntype FailedSummary = {\n success: false;\n entry: Entry;\n error: string;\n};\n\nconst model = anthropic(\"claude-3-5-haiku-latest\");\n\nconst SYSTEM_PROMPT = `\nYou are an AI summarization assistant that extracts key information from articles into structured data.\n\nCRITICAL INSTRUCTIONS:\n- Summarize ALL articles provided\n- NEVER ask if the user wants you to continue\n- NEVER mention how many articles you've processed\n- NEVER say \"I'll summarize\" or similar phrases\n- NEVER add ANY text before the first summary or after the last summary\n- Format each summary as: ## [Title] ([Source]) followed by summary content\n- Include NO introduction and NO conclusion\n- End after the last summary with NO additional text\n\nFFORMAT FOR EACH SUMMARY:\n1. tldr: A concise 2-3 sentence summary (max 60 words) that captures the essence of the article\n2. keyPoints: 3-5 key takeaways from the article\n3. whyValuable: A brief explanation (1-2 sentences) of why this article is significant or useful to readers\n\nGUIDELINES:\n- Be factual and objective in your summaries\n- Highlight the most important information from the article\n- Use clear, straightforward language\n- Keep the entire summary between 100-150 words total\n- Avoid technical jargon unless necessary for the topic\n- Focus only on summarizing the content, not on the process\n`;\n\nexport async function summarizeFeedbinEntries() {\n try {\n const entries = await getFeedbinUnreadEntries();\n if (entries.length === 0) {\n return { message: \"No unread entries to summarize.\" };\n }\n\n // Prepare and filter entries\n const entriesForSummary = entries\n .map((entry) => {\n const cleanContent = stripHtml(entry.content);\n return {\n title: entry.title,\n feed: entry.feed,\n url: entry.url,\n published: entry.published,\n content: cleanContent,\n contentLength: cleanContent.length,\n };\n })\n .filter((entry) => entry.contentLength > 100);\n\n if (entriesForSummary.length === 0) {\n return { message: \"No entries with sufficient content to summarize.\" };\n }\n\n const MAX_ARTICLES = 10;\n const articlesToProcess = entriesForSummary.slice(0, MAX_ARTICLES);\n\n // Process each article\n const summaryPromises = articlesToProcess.map(async (entry) => {\n const singleArticlePrompt = `\n Summarize this article:\n \n Title: ${entry.title}\n Source: ${entry.feed}\n Published: ${new Date(entry.published).toLocaleDateString()}\n URL: ${entry.url}\n \n Content:\n ${entry.content}\n `;\n\n try {\n const { object: summary } = await generateObject({\n model,\n schema,\n prompt: singleArticlePrompt,\n system: SYSTEM_PROMPT,\n });\n\n console.log(summary);\n\n return {\n success: true,\n summary,\n entry,\n } as SuccessfulSummary;\n } catch (error) {\n console.log(\n `Error summarizing article \"${entry.title}\": ${error.message}`,\n );\n return {\n success: false,\n entry,\n error: error.message,\n } as FailedSummary;\n }\n });\n\n const summaryResults = await Promise.all(summaryPromises);\n const successfulResults = summaryResults.filter((\n result,\n ): result is SuccessfulSummary => result.success === true);\n\n const combinedSummaries = successfulResults.map(({ summary, entry }) => ({\n title: entry.title,\n source: entry.feed,\n url: entry.url,\n published: entry.published,\n summary,\n }));\n console.log(combinedSummaries);\n\n return {\n processedEntries: articlesToProcess.length,\n successfulEntries: successfulResults.length,\n summaries: combinedSummaries,\n };\n } catch (error) {\n console.log(\"Error =>\", error);\n return { error: error.message };\n }\n}\n\n// Helper function to strip HTML tags\nfunction stripHtml(html?: string) {\n if (!html || typeof html !== \"string\") {\n return \"\";\n }\n return html.replace(/<[^>]*>?/gm, \" \").replace(/\\s+/g, \" \").trim();\n}\n\nawait summarizeFeedbinEntries();",3,["D",1767306096438],45,{"_105":262,"_164":146,"_161":203,"_97":101,"_172":263,"_170":186,"_102":185,"_163":-5,"_107":264,"_165":265,"_175":-5},"4ca8d498-e75f-11f0-93ee-42dde27851f2","import { anthropic } from \"npm:@ai-sdk/anthropic\";\nimport { generateObject } from \"npm:ai\";\nimport { z } from \"npm:zod\";\n\nconst schema = z.object({\n tldr: z.string(),\n keyPoints: z.array(z.string()),\n whyValuable: z.string(),\n});\n\ntype Entry = {\n title: string;\n feed: string;\n url: string;\n published: string;\n content: string;\n};\n\ntype SuccessfulSummary = {\n success: true;\n summary: z.infer;\n entry: Entry;\n};\n\ntype FailedSummary = {\n success: false;\n entry: Entry;\n error: string;\n};\n\nconst model = anthropic(\"claude-3-5-haiku-latest\");\n\nconst SYSTEM_PROMPT = `\nYou are an AI summarization assistant that extracts key information from articles into structured data.\n\nCRITICAL INSTRUCTIONS:\n- Summarize ALL articles provided\n- NEVER ask if the user wants you to continue\n- NEVER mention how many articles you've processed\n- NEVER say \"I'll summarize\" or similar phrases\n- NEVER add ANY text before the first summary or after the last summary\n- Format each summary as: ## [Title] ([Source]) followed by summary content\n- Include NO introduction and NO conclusion\n- End after the last summary with NO additional text\n\nFFORMAT FOR EACH SUMMARY:\n1. tldr: A concise 2-3 sentence summary (max 60 words) that captures the essence of the article\n2. keyPoints: 3-5 key takeaways from the article\n3. whyValuable: A brief explanation (1-2 sentences) of why this article is significant or useful to readers\n\nGUIDELINES:\n- Be factual and objective in your summaries\n- Highlight the most important information from the article\n- Use clear, straightforward language\n- Keep the entire summary between 100-150 words total\n- Avoid technical jargon unless necessary for the topic\n- Focus only on summarizing the content, not on the process\n`;\n\nasync function feedbinUnreadEntries() {\n const { result } =\n await (await fetch(\"https://kamalnrf-feedbinunreads.web.val.run\")).json();\n return result ?? [];\n}\n\nexport async function summarizeFeedbinEntries() {\n try {\n const entries = await feedbinUnreadEntries();\n if (entries.length === 0) {\n return { message: \"No unread entries to summarize.\" };\n }\n\n // Prepare and filter entries\n const entriesForSummary = entries\n .map((entry) => {\n const cleanContent = stripHtml(entry.content);\n return {\n title: entry.title,\n feed: entry.feed,\n url: entry.url,\n published: entry.published,\n content: cleanContent,\n contentLength: cleanContent.length,\n };\n })\n .filter((entry) => entry.contentLength > 100);\n\n if (entriesForSummary.length === 0) {\n return { message: \"No entries with sufficient content to summarize.\" };\n }\n\n const MAX_ARTICLES = 10;\n const articlesToProcess = entriesForSummary.slice(0, MAX_ARTICLES);\n\n // Process each article\n const summaryPromises = articlesToProcess.map(async (entry) => {\n const singleArticlePrompt = `\n Summarize this article:\n \n Title: ${entry.title}\n Source: ${entry.feed}\n Published: ${new Date(entry.published).toLocaleDateString()}\n URL: ${entry.url}\n \n Content:\n ${entry.content}\n `;\n\n try {\n const { object: summary } = await generateObject({\n model,\n schema,\n prompt: singleArticlePrompt,\n system: SYSTEM_PROMPT,\n });\n\n console.log(summary);\n\n return {\n success: true,\n summary,\n entry,\n } as SuccessfulSummary;\n } catch (error) {\n console.log(\n `Error summarizing article \"${entry.title}\": ${error.message}`,\n );\n return {\n success: false,\n entry,\n error: error.message,\n } as FailedSummary;\n }\n });\n\n const summaryResults = await Promise.all(summaryPromises);\n const successfulResults = summaryResults.filter((\n result,\n ): result is SuccessfulSummary => result.success === true);\n\n const combinedSummaries = successfulResults.map(({ summary, entry }) => ({\n title: entry.title,\n source: entry.feed,\n url: entry.url,\n published: entry.published,\n summary,\n }));\n console.log(combinedSummaries);\n\n return {\n processedEntries: articlesToProcess.length,\n successfulEntries: successfulResults.length,\n summaries: combinedSummaries,\n };\n } catch (error) {\n console.log(\"Error =>\", error);\n return { error: error.message };\n }\n}\n\n// Helper function to strip HTML tags\nfunction stripHtml(html?: string) {\n if (!html || typeof html !== \"string\") {\n return \"\";\n }\n return html.replace(/<[^>]*>?/gm, \" \").replace(/\\s+/g, \" \").trim();\n}\n\nawait summarizeFeedbinEntries();",["D",1767305694244],39,{"_105":267,"_164":146,"_161":203,"_97":101,"_172":74,"_170":186,"_102":169,"_163":-5,"_107":268,"_165":269,"_175":-5},"3eaaf902-e75f-11f0-b7ed-42dde27851f2",["D",1767305670770],38,{"_105":271,"_164":146,"_161":203,"_97":272,"_172":74,"_170":186,"_102":33,"_163":-5,"_107":273,"_165":274,"_175":-5},"3c694e78-e75f-11f0-a4da-42dde27851f2","new-file-8975.ts",["D",1767305666987],37,"versions",[277,279,280,281,282,283],{"_171":247,"_278":249},"previous",{"_171":249,"_278":255},{"_171":255,"_278":261},{"_171":261,"_278":266},{"_171":266,"_278":270},{"_171":270,"_278":-5},"versionNumber","page","hasNext","actionData","errors"]

kamalnrf

dailyFeedbinDigest

History for summarizeFeedbinEntries.ts