[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_226":227,"_228":229},"routes/_app.x.$handle.$name",{"_11":12,"_13":14,"_15":-7,"_18":19,"_17":-7,"_167":-5,"_20":168,"_22":169,"_170":171,"_172":173,"_26":174,"_24":175,"_176":177,"_178":179,"_180":51,"_181":182,"_183":68,"_184":-5,"_185":-5,"_186":187},"routes/_app.x.$handle.$name.code.$",{"_11":12,"_13":14,"_15":16,"_17":-7,"_18":19,"_20":21,"_22":23,"_24":25,"_26":27,"_28":29,"_30":-5,"_31":32,"_33":34,"_35":-5},"handle","hanspagel","name","analyze-github-issues","branchName","main","version","path","index.html","project",{"_36":123,"_13":14,"_38":124,"_49":-5,"_125":51,"_52":53,"_126":53,"_127":-5,"_128":-5,"_129":130,"_131":100,"_132":68,"_133":68,"_134":-5,"_135":32,"_56":136,"_137":-5,"_138":-5,"_139":-5,"_140":-5,"_141":142,"_143":142,"_144":145,"_146":145,"_147":145,"_148":142,"_149":142,"_150":151,"_152":153,"_154":155,"_50":51},"tree",[76,77,78,79,80,81],"file",{"_36":59,"_13":19,"_60":61,"_62":-5,"_63":64,"_65":66,"_67":68,"_38":69,"_17":32,"_70":24,"_71":72,"_73":51,"_74":-5,"_18":75},"contents",[],"upstream",{"_36":37,"_38":39,"_40":41,"_13":16,"_42":43,"_17":44,"_45":-5,"_46":-5,"_47":48,"_49":-5,"_50":51,"_52":53,"_54":55,"_56":57,"_58":14},"pull","ahead",0,"behind",2,"envVars","id","c29e8b40-61f2-11f0-93e9-0224a6c84d84","createdAt",["D",1752635572357],"updatedAt",["D",1753136679631],"projectId","c29e33a2-61f2-11f0-93e9-0224a6c84d84",174,"forkedBranchId","forkedBranchVersion","lockfileKey","1764008520208-esm.town_v_charmaine_analyze-github-issues@174-main","deletedAt","isOwned",false,"privacy","public","userHandle","charmaine","orgId","2019e55b-c541-4c51-bef0-008eef10ef88","projectName","f4ffa89e-6620-11f0-8e6c-0224a6c84d84","fileId","702519ab-3ce9-483a-a20e-a8e4eda7f44e","parentId","branchId","f4fac892-6620-11f0-8e6c-0224a6c84d84","branchVersion",1,"latest",true,["D",1753095218306],"fileType","content","\n\n\n \n \n GitHub Issues Analyzer\n \n\n\n

GitHub Issues Analyzer

\n \n \n

🔍 Analyzing repository...

This may take a few minutes for large repositories.

\n\n \n\n","deleted","label",[19],{"_36":116,"_13":117,"_60":118,"_62":-5,"_63":64,"_65":66,"_67":68,"_38":119,"_17":32,"_70":24,"_71":120,"_73":51,"_74":-5,"_88":121,"_18":122},{"_36":109,"_13":110,"_60":111,"_62":-5,"_63":64,"_65":66,"_67":68,"_38":112,"_17":32,"_70":86,"_71":113,"_73":51,"_74":-5,"_88":114,"_18":115},{"_36":59,"_13":19,"_60":61,"_62":-5,"_63":64,"_65":66,"_67":68,"_38":106,"_17":32,"_70":24,"_71":72,"_73":51,"_74":-5,"_88":107,"_18":108},{"_36":98,"_13":99,"_60":100,"_62":-5,"_63":64,"_65":66,"_67":68,"_38":101,"_17":32,"_70":102,"_71":103,"_73":51,"_74":-5,"_88":104,"_18":105},{"_36":91,"_13":92,"_60":93,"_62":-5,"_63":64,"_65":66,"_67":68,"_38":94,"_17":32,"_70":86,"_71":95,"_73":51,"_74":-5,"_88":96,"_18":97},{"_36":82,"_13":83,"_60":84,"_62":-5,"_63":64,"_65":66,"_67":68,"_38":85,"_17":32,"_70":86,"_71":87,"_73":51,"_74":-5,"_88":89,"_18":90},"f4ffba14-6620-11f0-8e6c-0224a6c84d84","utils.ts","1e477666-1516-4885-9f38-f9cfd4eed445",["D",1753095218306],"script","import { getAllIssues } from './github.ts'\n\ninterface Issue {\n number: number\n title: string\n body: string\n}\n\ninterface Subcategory {\n issues: Issue[]\n count: number\n}\n\ninterface Topic {\n name: string\n subcategories: {\n \"Big ticket\": Subcategory\n \"Bugs\": Subcategory\n \"Enhancements\": Subcategory\n \"Nice to haves\": Subcategory\n }\n}\n\nconst createBatches = (array: T[], size: number): T[][] => \n Array.from({ length: Math.ceil(array.length / size) }, (_, i) => \n array.slice(i * size, i * size + size))\n\nconst mergeTopicResults = (allBatchTopics: any[]) => {\n const topicMap = new Map()\n \n for (const { topics } of allBatchTopics) {\n for (const topic of topics) {\n const existing = topicMap.get(topic.name)\n \n if (existing) {\n Object.keys(topic.subcategories).forEach(key => {\n existing.subcategories[key].push(...topic.subcategories[key])\n })\n } else {\n topicMap.set(topic.name, {\n name: topic.name,\n subcategories: Object.fromEntries(\n Object.entries(topic.subcategories).map(([key, values]) => [key, [...values as any[]]])\n )\n })\n }\n }\n }\n \n return { topics: Array.from(topicMap.values()) }\n}\n\nasync function categorizeBatch(issues: any[]) {\n const processedIssues = issues.map(issue => ({\n number: issue.number,\n title: issue.title,\n body: issue.body?.substring(0, 500) || ''\n }))\n\n const { categorizeIssues: categorizeWithAI } = await import('./openai.ts')\n return categorizeWithAI(processedIssues)\n}\n\nasync function categorizeIssues(issues: any[], batchSize = 30) {\n if (issues.length === 0) return { topics: [] }\n if (issues.length <= batchSize) return categorizeBatch(issues)\n \n const batches = createBatches(issues, batchSize)\n console.log(`Processing ${issues.length} issues in ${batches.length} batches`)\n \n const allBatchTopics = []\n for (let i = 0; i < batches.length; i++) {\n console.log(`Processing batch ${i + 1}/${batches.length} (${batches[i].length} issues)`)\n \n allBatchTopics.push(await categorizeBatch(batches[i]))\n \n if (i < batches.length - 1) {\n await new Promise(resolve => setTimeout(resolve, 1000))\n }\n }\n \n return mergeTopicResults(allBatchTopics)\n}\n\nexport async function extractTopics(issues: Issue[]): Promise {\n if (issues.length === 0) return []\n\n const aiCategorization = await categorizeIssues(issues)\n \n const topics: Topic[] = aiCategorization.topics.map((topic: any) => {\n const subcategories = Object.fromEntries(\n [\"Big ticket\", \"Bugs\", \"Enhancements\", \"Nice to haves\"].map(categoryName => {\n const topicIssues = issues.filter(issue => topic.subcategories[categoryName].includes(issue.number))\n return [categoryName, {\n issues: topicIssues,\n count: topicIssues.length\n }]\n })\n ) as Topic['subcategories']\n \n return {\n name: topic.name,\n subcategories\n }\n })\n\n const totalCount = (topic: Topic) => Object.values(topic.subcategories).reduce((sum, category) => sum + category.count, 0)\n return topics.filter(topic => totalCount(topic) > 0).sort((a, b) => totalCount(b) - totalCount(a))\n}\n\nexport async function analyzeRepository(repo: string) {\n const issues = await getAllIssues(repo)\n const topics = await extractTopics(issues)\n \n return {\n repository: repo,\n totalIssues: issues.length,\n topics: topics.map(topic => ({\n name: topic.name,\n subcategories: Object.fromEntries(\n Object.entries(topic.subcategories).map(([name, category]: [string, any]) => [\n name,\n {\n count: category.count,\n issues: category.issues.map((issue: any) => ({\n number: issue.number,\n title: issue.title\n }))\n }\n ])\n )\n }))\n }\n}\n\nexport function formatAsMarkdown(result: any): string {\n const { repository, topics } = result\n \n return topics.map((topic: any) => {\n let markdown = `# ${topic.name}\\n\\n`\n \n [\"Big ticket\", \"Bugs\", \"Enhancements\", \"Nice to haves\"].forEach(categoryName => {\n const category = topic.subcategories[categoryName]\n if (category.count > 0) {\n markdown += `**${categoryName}**\\n\\n`\n category.issues.forEach((issue: any) => {\n markdown += `* [${issue.title} #${issue.number}](https://github.com/${repository}/issues/${issue.number})\\n`\n })\n markdown += '\\n'\n }\n })\n \n return markdown\n }).join('\\n---\\n\\n')\n}","children",[],[83],"f4ffb708-6620-11f0-8e6c-0224a6c84d84","openai.ts","5bfc140e-8c04-462c-8505-3c3363fdd8cc",["D",1753095218306],"import OpenAI from 'npm:openai'\n\nconst openai = new OpenAI({\n apiKey: Deno.env.get('OPENAI_API_KEY')\n})\n\nexport async function categorizeIssues(issues: any[]) {\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [{ role: \"user\", content: `Analyze these GitHub issues and categorize them into a two-level system:\n\n1. First identify 3-6 main topic areas (e.g., Authentication, Performance, UI/UX, API, etc.)\n2. Within each main topic, categorize issues into exactly these 4 subcategories:\n - \"Big ticket\": Major features, architectural changes, complex implementations\n - \"Bugs\": Bug fixes, errors, broken functionality\n - \"Enhancements\": Improvements to existing features, optimizations\n - \"Nice to haves\": Optional features, quality of life improvements\n\nIssues:\n${issues.map(issue => `#${issue.number}: ${issue.title}\\nBody: ${issue.body}\\n---`).join('\\n')}\n\nReturn a JSON object with:\n- topics: array of main topic objects, each containing:\n - name: descriptive main topic name (e.g., \"Authentication\", \"Performance\")\n - subcategories: object with exactly these 4 keys:\n - \"Big ticket\": array of issue numbers\n - \"Bugs\": array of issue numbers \n - \"Enhancements\": array of issue numbers\n - \"Nice to haves\": array of issue numbers\n\nEvery issue should be assigned to exactly one main topic and one subcategory within that topic.` }],\n response_format: { type: \"json_object\" },\n temperature: 0.3,\n max_tokens: 4000\n })\n\n const aiResponse = completion.choices[0].message.content\n if (!aiResponse) throw new Error('OpenAI returned empty response')\n \n try {\n return JSON.parse(aiResponse)\n } catch (error) {\n console.error('Failed to parse OpenAI response:', aiResponse.substring(0, 1000) + '...')\n \n // Try to repair truncated JSON by finding the last complete array\n try {\n const truncatedResponse = aiResponse.substring(0, aiResponse.lastIndexOf('],'))\n const repairedResponse = truncatedResponse + ']}}]}'\n return JSON.parse(repairedResponse)\n } catch (repairError) {\n throw new Error(`Invalid JSON response from OpenAI: ${error.message}`)\n }\n }\n}",[],[92],"f4ffb596-6620-11f0-8e6c-0224a6c84d84","main.ts","34ebe5ab-ccfc-444c-aded-cf408c196505",["D",1753095218306],"http","import { Hono } from 'npm:hono'\nimport { serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\"\nimport { analyzeRepository, formatAsMarkdown } from './utils.ts'\n\nconst app = new Hono()\n\napp.get('/', async (c) => {\n return serveFile('./index.html', import.meta.url)\n})\n\napp.post('/analyze-issues', async (c) => {\n const { repo } = await c.req.json()\n return c.json(await analyzeRepository(repo))\n})\n\napp.post('/analyze-issues/markdown', async (c) => {\n const { repo } = await c.req.json()\n const result = await analyzeRepository(repo)\n return c.text(formatAsMarkdown(result), 200, { 'Content-Type': 'text/plain; charset=utf-8' })\n})\n\napp.get('/analyze/:owner/:repo/markdown', async (c) => {\n const fullRepo = `${c.req.param('owner')}/${c.req.param('repo')}`\n const result = await analyzeRepository(fullRepo)\n return c.text(formatAsMarkdown(result), 200, { 'Content-Type': 'text/plain; charset=utf-8' })\n})\n\nexport default app.fetch",[],[99],["D",1753095218306],[],[19],"f4ffa61e-6620-11f0-8e6c-0224a6c84d84","github.ts","4881cbbb-0412-4986-8b8b-989cc87134a4",["D",1753095218306],"import { fetch } from \"https://esm.town/v/std/fetch\";\n\nexport async function getAllIssues(repo: string) {\n const issues = []\n let currentPage = 1\n \n while (true) {\n const response = await fetch(\n `https://api.github.com/repos/${repo}/issues?per_page=100&page=${currentPage}&state=open`\n )\n \n if (!response.ok) {\n console.error(`GitHub API error: ${response.status} ${response.statusText}`)\n break\n }\n \n const apiResponse = await response.json()\n \n if (!Array.isArray(apiResponse) || apiResponse.length === 0) break\n \n // GitHub clumps PRs and issues together, so need to filter\n const filteredIssues = apiResponse.filter((issue: any) => !issue.pull_request)\n \n issues.push(...filteredIssues.map((issue: any) => ({\n number: issue.number,\n title: issue.title,\n body: issue.body || ''\n })))\n \n currentPage++\n }\n \n return issues\n}\n\n",[],[110],"f4ff8648-6620-11f0-8e6c-0224a6c84d84","README.md","de95ca3b-6b4d-45ab-bf47-2e10fde0dc9f",["D",1753095218306],"# GitHub Issues Analyzer\n\nAutomatically categorizes GitHub issues into topics and subcategories using AI.\n\n![](https://filedumpthing.val.run/blob/blob_file_1752785055909_CleanShot%202025-07-17%20at%2016.42.08.gif)\n\n## Setup\n\n1. **Remix this val** (top right)\n\n2. **Environment Variables** (left sidebar)\n ```bash\n OPENAI_API_KEY=your_openai_api_key_here\n ```\n\n## Customization\n\nEdit the system prompt in `openai.ts` to change how issues are categorized.\n\n## Output\n\nIssues are grouped into:\n- **Big ticket**: Major features, architectural changes\n- **Bugs**: Bug fixes, errors \n- **Enhancements**: Improvements to existing features\n- **Nice to haves**: Optional features\n\nEach topic gets its own markdown section with clickable GitHub 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