(re)Search tool

Research Question: ' + rq + '

';\n if (mf) html += '

Methods & Findings: ' + mf + '

';\n if (sg) html += '

Significance: ' + sg + '

';\n return html;\n }\n // default to general\n const general = structured.general || {};\n const what = escapeHtml(general.what_it_is || '');\n const details = escapeHtml(general.details || '');\n const points = Array.isArray(general.key_points) ? general.key_points : [];\n let html = '';\n if (what) html += '

What it is: ' + what + '

';\n if (points.length > 0) {\n html += '

Key points:

' + escapeHtml(p) + '

';\n }\n if (details) html += '

Details: ' + details + '

';\n return html;\n}\n\n\n// Synthesis fallback: produce results[] from mixed context (tool logs, assistant text, reasoning, existing results)\n// Only used when earlier parsing/repair yielded nothing or timed out\nexport async function synthesizeResultsFromContext(context, apiKey) {\n try {\n const {\n query = '',\n language = 'english',\n toolText = '',\n assistantText = '',\n reasoningText = '',\n existingResults = []\n } = context || {};\n\n const parts = [];\n if (query) parts.push('User query: ' + String(query));\n parts.push('Present titles and descriptions in language: ' + String(language || 'english'));\n if (Array.isArray(existingResults) && existingResults.length > 0) {\n parts.push('Existing results JSON (may be empty or partial): ' + JSON.stringify({ results: existingResults }));\n }\n if (toolText && String(toolText).trim()) parts.push('Tool logs:\\n' + String(toolText));\n if (assistantText && String(assistantText).trim()) parts.push('Assistant text:\\n' + String(assistantText));\n if (reasoningText && String(reasoningText).trim()) parts.push('Reasoning text:\\n' + String(reasoningText));\n\n const response = await fetch('https://api.groq.com/openai/v1/chat/completions', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'Authorization': `Bearer ${apiKey}`,\n },\n body: JSON.stringify({\n model: 'openai/gpt-oss-120b',\n messages: [\n {\n role: 'system',\n content: 'Synthesize a strict JSON search results list from provided context. CRITICAL: Prefer URLs that literally occur in tool logs or assistant text; avoid fabricating. Apply canonical link rules (HN item or external, PubMed PMID, arXiv /abs, DOI resolver, exact thread permalinks, precise GitHub paths). Descriptions must be clean plain text without citations (no [1], (2), L0:, †), HTML, or code fences, and must add info beyond the title. Present titles and descriptions in the requested language.'\n },\n {\n role: 'user',\n content: parts.join('\\n\\n')\n }\n ],\n response_format: {\n type: 'json_schema',\n json_schema: {\n name: 'search_results_synthesis',\n schema: {\n type: 'object',\n properties: {\n results: {\n type: 'array',\n items: {\n type: 'object',\n properties: {\n title: { type: 'string' },\n url: { type: 'string' },\n description: { type: ['string', 'null'] },\n source: { type: ['string', 'null'] },\n published_at: { type: ['string', 'null'] },\n comments: { type: ['number', 'null'] },\n pmid: { type: ['string', 'null'] },\n doi: { type: ['string', 'null'] }\n },\n required: ['title', 'url'],\n additionalProperties: false\n }\n }\n },\n required: ['results'],\n additionalProperties: false\n }\n }\n },\n stream: false\n })\n });\n if (!response.ok) {\n try { console.error('synthesizeResultsFromContext error:', await response.text()); } catch (_) {}\n return [];\n }\n const data = await response.json();\n const jsonText = data.choices?.[0]?.message?.content || '{}';\n try {\n const parsed = JSON.parse(jsonText);\n return Array.isArray(parsed?.results) ? parsed.results : [];\n } catch (_) {\n return [];\n }\n } catch (_err) {\n return [];\n }\n}\n\n// Synthesis fallback: produce concise plain-text answer from context (used when router selects text or lists fail)\nexport async function synthesizeTextFromContext(context, apiKey) {\n try {\n const {\n query = '',\n language = 'english',\n toolText = '',\n assistantText = '',\n reasoningText = ''\n } = context || {};\n\n const parts = [];\n if (query) parts.push('User query: ' + String(query));\n parts.push('Respond in language: ' + String(language || 'english'));\n if (toolText && String(toolText).trim()) parts.push('Tool logs:\\n' + String(toolText));\n if (assistantText && String(assistantText).trim()) parts.push('Assistant text:\\n' + String(assistantText));\n if (reasoningText && String(reasoningText).trim()) parts.push('Reasoning text:\\n' + String(reasoningText));\n\n const response = await fetch('https://api.groq.com/openai/v1/chat/completions', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'Authorization': `Bearer ${apiKey}`,\n },\n body: JSON.stringify({\n model: 'openai/gpt-oss-120b',\n messages: [\n {\n role: 'system',\n content: 'Answer the user clearly and concisely using only the provided context. Return plain text only (no markdown fences). Remove any citations, numbers-in-brackets, line numbers, and artifacts. If unsure, say so briefly.'\n },\n { role: 'user', content: parts.join('\\n\\n') }\n ],\n stream: false\n })\n });\n if (!response.ok) {\n try { console.error('synthesizeTextFromContext error:', await response.text()); } catch (_) {}\n return '';\n }\n const data = await response.json();\n const text = data.choices?.[0]?.message?.content || '';\n return String(text || '').trim();\n } catch (_err) {\n return '';\n }\n}",[134],"72841626-74a7-11f0-b28c-0224a6c84d84","index.html","e0d474b0-724d-11f0-94bb-0224a6c84d84",41,["D",1754692297796],9,"\n\n\n \n \n (re)Search tool\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 \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

\n \n

\n \n \n

\n \n

\n \n \n

\n \n

\n\n \n

\n \n

\n \n \n

\n\n \n

0 || isStreaming\">\n

\n \n

\n\n \n

\n \n \n \n\n \n

\n \n \n

0 && !isSearching && route !== 'text'\">\n

\n \n

\n \n \n

\n \n

\n\n\n

\n\n \n \n

\n \n

\n\n \n

\n \n \n \n github\n

\n\n",[143],"6ea86d86-74a7-11f0-a77c-0224a6c84d84","chatStreaming.js","330cd23c-73fb-11f0-adbc-0224a6c84d84",40,["D",1754692291324],4,"// Deno script and module: streaming chat completion test with SSE parsing and aggregation\n// - Reads GROQ_API_KEY from environment (when run as CLI)\n// - Exports streamChatAndAggregate(apiKey, payload, { logSse }) to allow server reuse\n// - CLI: logs raw SSE lines and prints aggregated JSON at the end\n\nimport \"jsr:@std/dotenv/load\";\n\nconst API_URL = \"https://api.groq.com/openai/v1/chat/completions\";\n\nfunction getApiKey() {\n const key = (typeof Deno !== \"undefined\") ? Deno.env.get(\"GROQ_API_KEY\") : null;\n if (!key) {\n console.error(\"Missing GROQ_API_KEY in environment.\");\n }\n return key;\n}\n\nfunction buildPayload(userQuery) {\n const prompt = typeof userQuery === \"string\" && userQuery.trim().length > 0\n ? userQuery\n : \"Stream test: please emit a short response and demonstrate reasoning and any tool usage.\";\n\n return {\n messages: [\n {\n role: \"user\",\n content: prompt,\n },\n ],\n model: \"openai/gpt-oss-120b\",\n stream: true,\n reasoning_effort: \"medium\",\n tools: [\n {\n type: \"browser_search\",\n },\n ],\n };\n}\n\n// Utility: Parse one Groq SSE JSON line (string without the leading \"data: \")\nfunction parseGroqSseJsonLine(jsonStr) {\n try {\n const obj = JSON.parse(jsonStr);\n return obj;\n } catch (_err) {\n return null;\n }\n}\n\n// Utility: Normalize a parsed chunk into events and collapsed accumulators\nfunction applyChunkToAggregates(parsed, aggregates) {\n const { events, collapsed } = aggregates;\n\n const timestamp = Date.now();\n const baseInfo = {\n id: parsed.id,\n model: parsed.model,\n created: parsed.created,\n instance_id: parsed.instance_id,\n system_fingerprint: parsed.system_fingerprint,\n timestamp,\n };\n\n if (Array.isArray(parsed.choices) && parsed.choices.length > 0) {\n const choice = parsed.choices[0];\n const delta = choice?.delta || {};\n\n if (delta.role) {\n events.push({ type: \"role\", role: delta.role, ...baseInfo });\n }\n\n if (delta.reasoning) {\n events.push({ type: \"reasoning\", content: delta.reasoning, channel: delta.channel, ...baseInfo });\n collapsed.reasoning += delta.reasoning;\n }\n\n if (delta.content) {\n events.push({ type: \"content\", content: delta.content, ...baseInfo });\n collapsed.content += delta.content;\n }\n\n if (delta.executed_tools) {\n events.push({ type: \"executed_tools\", executed_tools: delta.executed_tools, ...baseInfo });\n for (const t of delta.executed_tools) {\n collapsed.tools.push({ kind: \"executed\", ...t, timestamp });\n }\n }\n\n if (delta.tool_calls) {\n events.push({ type: \"tool_calls\", tool_calls: delta.tool_calls, ...baseInfo });\n for (const t of delta.tool_calls) {\n collapsed.tools.push({ kind: \"call\", ...t, timestamp });\n }\n }\n }\n}\n\nexport async function streamChatAndAggregate(apiKey, payload, options = {}) {\n const { logSse = false } = options;\n\n const response = await fetch(API_URL, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n Authorization: `Bearer ${apiKey}`,\n },\n body: JSON.stringify(payload),\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`HTTP ${response.status} — ${text}`);\n }\n\n const reader = response.body?.getReader();\n const aggregates = {\n events: [],\n collapsed: { reasoning: \"\", content: \"\", tools: [] },\n };\n\n if (!reader) {\n try {\n const nonStream = await response.json();\n const content = nonStream?.choices?.[0]?.message?.content || \"\";\n if (content) {\n aggregates.events.push({ type: \"content\", content, timestamp: Date.now() });\n aggregates.collapsed.content = content;\n }\n } catch (_e) {\n // ignore\n }\n console.log(\"No readable stream; returning aggregates:\");\n console.log(JSON.stringify(aggregates, null, 2));\n return;\n }\n\n const decoder = new TextDecoder();\n let buffer = \"\";\n if (logSse) console.log(\"--- BEGIN SSE ---\");\n while (true) {\n const { done, value } = await reader.read();\n if (done) break;\n buffer += decoder.decode(value, { stream: true });\n\n // Split Server-Sent Events by double newlines\n const events = buffer.split(\"\\n\\n\");\n buffer = events.pop() || \"\";\n\n for (const evt of events) {\n if (!evt.trim()) continue;\n // Extract `data:` line(s)\n const lines = evt.split(\"\\n\");\n for (const line of lines) {\n if (line.startsWith(\"data: \")) {\n const data = line.slice(6);\n if (data === \"[DONE]\") {\n if (logSse) console.log(\"[DONE]\");\n break;\n }\n if (logSse) {\n // Log raw SSE packet\n console.log(\"data:\", data);\n }\n // Parse and aggregate\n const parsed = parseGroqSseJsonLine(data);\n if (!parsed) continue;\n applyChunkToAggregates(parsed, aggregates);\n }\n }\n }\n }\n if (logSse) {\n console.log(\"--- END SSE ---\");\n console.log(\"Aggregates:\");\n console.log(JSON.stringify(aggregates, null, 2));\n }\n return aggregates;\n}\n\n// Entry point\nif (import.meta.main) {\n const apiKey = getApiKey();\n if (!apiKey) Deno.exit(1);\n\n const userQuery = Deno.args?.[0] || \"\";\n const payload = buildPayload(userQuery);\n\n streamChatAndAggregate(apiKey, payload, { logSse: true })\n .then(() => console.log(\"Stream complete.\"))\n .catch((err) => {\n console.error(\"Stream failed:\", err);\n Deno.exit(1);\n });\n}",[151],"6b8b0dde-74a7-11f0-a819-0224a6c84d84","chatCompletion.js","3d892ec2-73fb-11f0-9985-0224a6c84d84",39,["D",1754692286102],"// Minimal Groq Chat Completions client using fetch\nimport { extractOrRepairJsonResults, extractStructuredSummary, renderStructuredSummaryToHtml } from \"./jsonUtils.js\";\nexport async function groqChatCompletion(apiKey, payload) {\n console.log('>>> [groqChatCompletion] Payload:', payload);\n const response = await fetch('https://api.groq.com/openai/v1/chat/completions', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'Authorization': `Bearer ${apiKey}`,\n },\n body: JSON.stringify(payload),\n });\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`Groq API error: ${response.status} ${text}`);\n }\n console.log('>>> [groqChatCompletion] Response:', response);\n return await response.json();\n}\n\n// Use LLM to normalize any freeform output into strict JSON that matches our schema.\n// extractOrRepairJsonResults moved to ./jsonUtils.js\n\nexport function buildSearchPrompt(query, source, dateRange, language, offset) {\n // Always search in English; present in the selected language\n const presentationLanguage = (typeof language === 'string' && language.trim()) ? language : 'english';\n const languageInstruction = `IMPORTANT: Always conduct searches in English. Workflow: 1) If the user query is not in English, translate \"${query}\" into English search terms and use ONLY the English translation for searching. 2) After finding results, present all titles and descriptions in ${presentationLanguage}. Always search in English but present results in ${presentationLanguage}.`;\n\n const base = source && source.trim()\n ? `Search ${source} for: \"${query}\"`\n : `\"${query}\"`;\n\n let dateRangeText = '';\n if (dateRange) {\n dateRangeText = ({\n '1month': 'in the last month',\n '3months': 'in the last 3 months',\n '6months': 'in the last 6 months',\n '1year': 'in the last year',\n })[dateRange] || '';\n }\n\n const startResult = offset + 1;\n const endResult = offset + 5;\n const offsetInstruction = offset > 0 ? ` Skip the first ${offset} results and` : '';\n\n const searchPrompt = `${base}${dateRangeText ? ' ' + dateRangeText : ''}.${offsetInstruction} Return results ${startResult}-${endResult} (max 5 new results). Return ONLY JSON with a top-level \\\\\"results\\\\\" array. Each result must include: title and url. Optionally include: description (one concise sentence only if confidently grounded by the target page). Do NOT add or guess fields like source, published_at, comments, pmid, or doi — omit anything unknown.\\n\\nURL RULES (critical):\\n- Always provide a direct deep link to the specific item/resource — never a homepage, category page, or search results page.\\n- If the listing points to another resource, set url to the canonical content page, not the aggregator:\\n - Hacker News: prefer the external article URL if present; otherwise use the exact item permalink (https://news.ycombinator.com/item?id=...). Do not invent dates or comment counts.\\n - PubMed: use the PMID page (https://pubmed.ncbi.nlm.nih.gov/PMID/) or the publisher DOI landing page if available. Do not link to the PubMed homepage.\\n - arXiv: use https://arxiv.org/abs/ (or the PDF if explicitly asked for PDFs).\\n - DOI: use the https://doi.org/... resolver link.\\n - Reddit/Forums: use the exact thread permalink if the discussion is the result.\\n - GitHub: link to the exact repository, release, issue, or file path, not github.com root.\\n- Never return root domains (e.g., https://pubmed.ncbi.nlm.nih.gov/, https://news.ycombinator.com/). Ensure url resolves to the specific item. ${languageInstruction}`;\n return searchPrompt;\n}\n\n// Lightweight router: decide between 'links' (JSON list) and 'text' (short answer)\nexport async function routeQueryMode(apiKey, query) {\n try {\n const res = await groqChatCompletion(apiKey, {\n model: 'openai/gpt-oss-120b',\n messages: [\n { role: 'system', content: 'Classify the user request as either links or text. Respond with a single token: links or text. Use links if the user appears to want a search results list of sources; use text if the user is asking for an explanation/summary/definition.' },\n { role: 'user', content: String(query || '') }\n ],\n stream: false,\n });\n const out = (res?.choices?.[0]?.message?.content || '').trim().toLowerCase();\n if (out.includes('links')) return 'links';\n if (out.includes('text')) return 'text';\n } catch (_) { /* fall back to heuristic */ }\n // Heuristic fallback\n const q = String(query || '').trim().toLowerCase();\n const chatStarts = ['explain', 'what is', 'what are', 'how does', 'how do', 'summarize', 'overview', 'define', 'in simple terms', 'briefly', 'why is', 'compare', 'contrast'];\n if (chatStarts.some((s) => q.startsWith(s))) return 'text';\n if (q.endsWith('?') && q.length <= 200) return 'text';\n return 'links';\n}\n\nexport async function performSearch({ apiKey, query, dateRange, source, language, offset = 0, model, stream, reasoningEffort, forceLinksRoute = false }) {\n const prompt = buildSearchPrompt(query, source, dateRange, language, offset);\n const start = Date.now();\n const route = forceLinksRoute ? 'links' : await routeQueryMode(apiKey, query);\n const response = await groqChatCompletion(apiKey, {\n model,\n messages: route === 'text'\n ? [\n {\n role: 'system',\n content: `If the user is asking for an explanation or summary rather than a list of links, respond with a concise plain-text answer in ${language || 'english'} (no JSON). If the request appears to be a search for sources, return ONLY JSON with a top-level results array as previously specified. ALWAYS conduct searches in English when needed.`\n },\n { role: 'user', content: query }\n ]\n : [\n {\n role: 'system',\n content: `Return ONLY JSON matching the schema; no markdown or commentary. For every result, url MUST be a direct deep link to the specific item/resource (not a homepage, category page, or search results page). Prefer canonical targets: external article for HN listings, PubMed PMID page or publisher DOI for papers, arXiv abs page, DOI resolver, exact thread permalinks for discussions, and precise GitHub paths. Never output root domains as url. Additionally, ALWAYS conduct searches in English. If the user query is not in English, translate it to English first and use ONLY the English translation for searching. Present titles and descriptions in ${language || 'english'}.`\n },\n { role: 'user', content: prompt },\n ],\n stream: false,\n reasoning_effort: reasoningEffort,\n tools: [ { type: 'browser_search' } ],\n });\n const end = Date.now();\n const searchTime = (end - start) / 1000;\n const contentText = response.choices?.[0]?.message?.content || '';\n\n console.log('>> contentText', contentText);\n let results = [];\n if (route === 'links') {\n try {\n // Try direct parse first (in case the model already returned valid JSON)\n const stripped = String(contentText).replace(/^```json\\s*/i, '').replace(/```\\s*$/i, '');\n const parsed = JSON.parse(stripped);\n if (Array.isArray(parsed?.results)) results = parsed.results;\n } catch (_) {\n // as a fallback, attempt repair pass\n results = await extractOrRepairJsonResults(contentText, apiKey, language);\n }\n } else {\n // text mode → do not attempt to coerce content into results\n results = [];\n }\n // Also return assistant content and full response for upstream logging / fallback display\n return { results, searchTime, content: contentText, full: response, route };\n}\n\nimport { marked } from \"npm:marked\";\n\nfunction buildSummaryPrompt(url, title, language) {\n const languageInstruction = language && language !== 'english'\n ? `Please provide the summary in ${language}. `\n : '';\n\n return `Visit this URL: ${url}\n \nTitle: \"${title}\"\n\nCRITICAL INSTRUCTIONS:\n- Read the page content and produce a clean, professional summary.\n- Ignore navigation, comments, ads, headers/footers, and numerical artifacts.\n- If this is a research paper, use the RESEARCH format below.\n- If this is a news/blog/listing/discussion page (e.g., HN, Reddit, news site), use the GENERAL format below.\n- DO NOT include any citations, reference numbers, or raw scraping artifacts.\n- Write in clear prose without formatting artifacts.\n- The opening line of the summary must not simply repeat the title; avoid mirroring the title.\n\nReturn only one of the two structures below in markdown (choose based on page type). ${languageInstruction}\n\nRESEARCH FORMAT:\n

\n**Research Question:** [brief description of what the study investigates]\n\n**Methods & Findings:** [1-2 paragraphs covering methodology and key results - NO CITATIONS]\n\n**Significance:** [why this research matters and potential applications - NO CITATIONS]\n

\n\nGENERAL FORMAT:\n

\n**What it is:** [brief description of the page]\n\n**Key points:** [bullet list or short paragraphs with the main takeaways]\n\n**Details:** [1–2 short paragraphs with notable specifics]\n

`;\n}\n\nexport async function summarizeUrl({ apiKey, url, title, language, model, stream, reasoningEffort }) {\n const summaryPrompt = buildSummaryPrompt(url, title, language);\n const start = Date.now();\n const response = await groqChatCompletion(apiKey, {\n model,\n messages: [\n {\n role: 'system',\n content: 'You are a concise web content summarization expert. CRITICAL REQUIREMENTS: 1) Return ONLY the summary content within

tags - no other text, explanations, or metadata. 2) Use clean, professional markdown formatting. 3) NEVER include citations, reference numbers, line numbers, or any numerical markers like [1†, L0:, L1:, etc. 4) Write in clear prose without any formatting artifacts from source documents. 5) Adapt structure to page type and, if it is a research paper, strictly use the sections: Research Question, Methods & Findings, Significance; otherwise use the GENERAL structure.'\n },\n {\n role: 'user',\n content: summaryPrompt\n }\n ],\n stream,\n reasoning_effort: reasoningEffort,\n tools: [ { type: 'browser_search' } ],\n });\n const end = Date.now();\n const summaryTime = (end - start) / 1000;\n const responseText = response.choices[0]?.message?.content || '';\n\n // Prefer structured, JSON-cleaned summary to avoid leaking citation junk\n let cleanedHtml = '';\n try {\n const inner = (responseText.match(/

([\\s\\S]*?)<\\/summary>/) || [null, responseText])[1];\n const structured = await extractStructuredSummary(inner, apiKey);\n if (structured) {\n cleanedHtml = renderStructuredSummaryToHtml(structured);\n }\n } catch (_) {\n // ignore and fallback\n }\n if (!cleanedHtml) {\n // Final fallback: render markdown, but still try to strip outer

tags\n const match = responseText.match(/

([\\s\\S]*?)<\\/summary>/);\n const raw = match ? match[1].trim() : responseText;\n cleanedHtml = marked(raw);\n }\n\n return { summary: cleanedHtml, summaryTime };\n}",[159],"pulls",0,"forks","envVars",{"_172":166,"_174":166},"connections",{"_172":166,"_173":166},"count","unfilledCount","emptyCount",{"_20":158,"_13":159,"_119":160,"_120":-5,"_121":21,"_122":161,"_123":49,"_22":193,"_29":138,"_126":139,"_128":163,"_130":38,"_131":-5,"_181":194,"_89":195},{"_20":150,"_13":151,"_119":152,"_120":-5,"_121":21,"_122":153,"_123":49,"_22":190,"_29":155,"_126":139,"_128":156,"_130":38,"_131":-5,"_181":191,"_89":192},{"_20":142,"_13":143,"_119":144,"_120":-5,"_121":21,"_122":145,"_123":49,"_22":187,"_29":147,"_126":101,"_128":148,"_130":38,"_131":-5,"_181":188,"_89":189},{"_20":133,"_13":134,"_119":135,"_120":-5,"_121":21,"_122":136,"_123":49,"_22":184,"_29":138,"_126":139,"_128":140,"_130":38,"_131":-5,"_181":185,"_89":186},{"_20":117,"_13":118,"_119":47,"_120":-5,"_121":21,"_122":30,"_123":49,"_22":180,"_29":125,"_126":127,"_128":129,"_130":38,"_131":14,"_181":182,"_89":183},["D",1754692308865],"children",[],[118],["D",1754692278350],[],[134],["D",1754692297796],[],[143],["D",1754692291324],[],[151],["D",1754692286102],[],[159],["D",1754433916817],{"_11":12,"_87":83},{"_11":12,"_81":-5,"_82":83,"_44":45,"_84":85,"_86":38},{"_29":30,"_13":26,"_20":21,"_27":28,"_31":-5,"_32":-5,"_76":-5,"_77":-5,"_78":-5,"_79":14,"_80":12},"ctx",{"_69":-5,"_109":233,"_234":235,"_236":237,"_238":38,"_239":38,"_240":38,"_241":49,"_242":-5,"_243":-7,"_244":-7,"_245":166,"_246":38,"_247":38,"_248":-5,"_249":38,"_250":38,"_251":38,"_252":-5},"ENV",{"_204":205,"_206":207,"_208":26,"_209":210,"_211":212,"_213":214,"_215":216,"_217":218,"_219":220,"_221":222,"_223":224,"_225":226,"_227":228,"_229":230,"_231":232},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","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"]

Branches1

Branches
1