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{ Hono } from 'https://deno.land/x/hono@v3.11.12/mod.ts';\nimport \"jsr:@std/dotenv/load\";\n\nimport { registerStaticRoutes } from './routes/static.js';\nimport { registerSystemRoutes } from './routes/system.js';\nimport { registerSearchRoutes } from './routes/search.js';\nimport { registerChatStreamRoute } from './routes/chatStream.js';\nimport { registerChatStreamSSERoute } from './routes/chatStreamSSE.js';\n\nexport function createApp(importMetaUrl) {\n const app = new Hono();\n\n // Unwrap Hono errors to see original error details\n app.onError((err) => { throw err; });\n\n // Register route modules\n registerSystemRoutes(app);\n registerStaticRoutes(app, importMetaUrl);\n registerSearchRoutes(app);\n registerChatStreamRoute(app);\n registerChatStreamSSERoute(app);\n\n return app;\n}\n\n\n","import { Hono } from 'https://deno.land/x/hono@v3.11.12/mod.ts';\nimport \"jsr:@std/dotenv/load\";\n\nimport { registerStaticRoutes } from './routes/static.js';\nimport { registerSystemRoutes } from './routes/system.js';\nimport { registerSearchRoutes } from './routes/search.js';\nimport { registerChatStreamRoute } from './routes/chatStream.js';\nimport { registerChatStreamSSERoute } from './routes/chatStreamSSE.js';\nimport { readFileContent } from './utils.js';\n\nexport function createApp(importMetaUrl) {\n const app = new Hono();\n\n // Unwrap Hono errors to see original error details\n app.onError((err) => { throw err; });\n\n // Register route modules\n registerSystemRoutes(app);\n registerStaticRoutes(app, importMetaUrl);\n registerSearchRoutes(app);\n registerChatStreamRoute(app);\n registerChatStreamSSERoute(app);\n\n // Settings page route\n app.get('/settings', async (c) => {\n try {\n const html = await readFileContent('index.html', importMetaUrl);\n return c.html(html);\n } catch (err) {\n console.error('Error reading index.html:', err);\n return c.text('Error loading page', 500);\n }\n });\n\n // Deep-link route for chats: supports \"/123\" and 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(re)Search — Groq demo\n\nTiny, no-nonsense demo for Groq: search the web and papers, then get clean summaries.\n\n- Search with optional source/date filters\n- Streams model reasoning/tools (SSE)\n- Returns tight JSON (deep links + one-line descriptions)\n- One‑click page summaries in your language\n\n### Run\n\n```sh\ndeno run -A smallweb/re-search/main.js \n```\n\nOpen http://localhost:8000 and paste your API key if the server doesn’t have one.\n\nPowered by Groq — get a key at [groq.com](https://groq.com).\n","label",[143],"a03294e6-7b21-11f0-943c-0224a6c84d84","notes.md","041e99e6-7758-11f0-81b1-0224a6c84d84",54,["D",1755404480017],3,"random features\n- save / load / import to restore all data\n- branching tree chats / multiple chat trees?\n- system prompt templates\n - crud system\n- move settings to a right slide bar\n- position send area relative to bottom and float on top of everything; make the text output naturally flow with the document instead of a scroll area right now\n- duplicate button in left bar\n- notes area is nice in side bar\n- show model name by response?\n- system message should NOT be auto generatlized across all; should be specific to chat \n - special system message template interface?\n- copy entire page / thread / export entire thread data\n- template for repeat phrasing (like the buttons/user prompts initially in chat gpt; but you can program them to push a button and it'll show at the bottom to click, like a quick way to enter stuff repeatedly)\n- system settings\n - text size slider (four options)\n - system color\n - font choices\n\n\n\nmedium features\n- switch out llm url, including localhost\n- context preservation\n - summarizer: summarizes key things succinctly into system prompt\n - trailing: feed summarizer and k-latest prompts\n- nicer upload area\n - add image upload\n - add file upload?\n - voice? \n - use the much nicer invoice one\n - add whisper transcription (from another val)\n- self-writing summary/notes system\n - has own system prompt, model selector, etc\n- long-term memory / offload memory?\n - durable object or valtown based link sharing?\n- mcp support?\n- support for \"re-search\" tool from before?\n\n\n\n- different interfaces\n - text notes\n - jan-like \"assistants\"\n - templates w/ preset prompts, settings, and variable input forms you type in, for future generations, like parameters\n - spin-off / sub-bot / picture in picture; eg spin another one up as a temp to ask some questions; an untracked one?\n\nbig features\n- multiplayer chats? i guess id-based consistent, resumable session chats\n\n\n\n\ndone\n- [x] branching / forking into another chat instance\n- [x] edit button instead of double click to edit\n - [x] editing the user thing changes the width; can it somehow edit in place without changing the width / flow?\n- [x] refactor research app\n- [x] make left settings folder/new/hide into icons\n - [x] fix the hidden icon bug\n- [x] create a new chat in sidebar\n- [x] folders in sidebar\n- [x] resizable sidebar\n- [x] delete below\n- [x] delete individual messages\n- [x] re-run a user prompt / re-run an ai response\n- [~] [nah] save/discard for editing, like lmstudio? \n- [x] \"delete below\" should delete anything below, but not the current message\n",[153],"0439f510-7758-11f0-93f7-0224a6c84d84","main.js",33,["D",1754988036009],2,"http","import \"jsr:@std/dotenv/load\";\nimport { createApp } from './backend/index.js';\n\nconst app = createApp(import.meta.url);\n\n// Export app.fetch for Val Town, otherwise export app — this is only for hono apps\nexport default (typeof Deno !== \"undefined\" && Deno.env.get(\"valtown\")) ? app.fetch : app;\n\n\n",[161],"f77b21ce-7616-11f0-8f0c-0224a6c84d84","jsonUtils.js","f77b22e6-7616-11f0-8f0c-0224a6c84d84",15,["D",1754850144846],"// General JSON extraction/repair helper using Groq Chat Completions\n// Converts arbitrary text into a strict JSON object and returns the `results` array\nexport async function extractOrRepairJsonResults(rawText, apiKey, language = 'english') {\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:\n 'You convert arbitrary text into a strict JSON object with a top-level `results` array. Return ONLY JSON, no markdown or comments. Output must already be sanitized: descriptions must be clean plain text with no citations (e.g., [1], (2)), no line numbers (e.g., L0:), no dagger symbols (†), no HTML, no code blocks, and no section headers. Descriptions must add new information beyond the title — never repeat or mirror the title. If a description would equal or start with the title, remove the title portion and ensure the remaining text adds value; if nothing remains, set description to null. Keep prose concise and readable.'\n },\n {\n role: 'user',\n content:\n 'Convert the following into ONLY valid JSON that matches the schema. If fields are missing, use null. Do not include markdown fences. In description, output plain text only (no citations, numbers-in-brackets, line numbers, or HTML). Present titles and descriptions in language: ' + String(language || 'english') + '\\n---\\n' + rawText\n }\n ],\n response_format: {\n type: 'json_schema',\n json_schema: {\n name: 'search_results',\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 const text = await response.text();\n throw new Error(`Groq API error: ${response.status} ${text}`);\n }\n const data = await response.json();\n const jsonText = data.choices?.[0]?.message?.content || '{}';\n try {\n const parsed = JSON.parse(jsonText);\n let results = Array.isArray(parsed?.results) ? parsed.results : [];\n return results;\n } catch (_) {\n return [];\n }\n}\n\n// Extract results strictly from tool outputs (ground truth URLs only)\n// The tool logs may include lines like \"URL: ...\", markdown lists, tables, or raw text.\n// This helper instructs the model to ONLY use URLs that appear in the provided text and never invent new ones.\nexport async function extractResultsFromToolOutputs(toolText, apiKey, language = 'english') {\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:\n 'You will receive raw logs from browser tool executions that include titles and URLs. Critically: ONLY use URLs that literally appear in the logs. Do not fabricate or guess any URL. Produce a strict JSON object with a top-level `results` array. Each result should map a meaningful title to one of the URLs present in the logs. Prefer canonical deep links by rule: Hacker News → exact item permalink or the external article if explicitly listed; PubMed → PMID page; arXiv → /abs/; DOI → https://doi.org/...; Reddit/forums → exact thread permalink; GitHub → exact path to repo/issue/file/release. If a suitable title is not obvious, derive a concise one from nearby text. If description can be inferred, include a short clean sentence with no citations or artifacts; otherwise set description to null. Never include any URL not present in the logs.'\n },\n {\n role: 'user',\n content:\n 'From the following tool logs, extract results using ONLY URLs that occur in the text. Return ONLY valid JSON matching the schema. If fields are missing, use null. No markdown fences. Present titles and descriptions in language: ' + String(language || 'english') + '\\n---\\n' + toolText\n }\n ],\n response_format: {\n type: 'json_schema',\n json_schema: {\n name: 'search_results_from_tools',\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 const text = await response.text();\n throw new Error(`Groq API error: ${response.status} ${text}`);\n }\n const data = await response.json();\n const jsonText = data.choices?.[0]?.message?.content || '{}';\n try {\n const parsed = JSON.parse(jsonText);\n const results = Array.isArray(parsed?.results) ? parsed.results : [];\n return results;\n } catch (_) {\n return [];\n }\n}\n\n// Remove null/undefined optional fields so UI never shows pmid: null or doi: null\nexport function sanitizeResults(results) {\n if (!Array.isArray(results)) return [];\n return results.map((r) => {\n const cleaned = { ...r };\n for (const key of ['pmid', 'doi', 'description', 'source', 'published_at', 'comments']) {\n if (cleaned[key] === null || cleaned[key] === undefined) {\n delete cleaned[key];\n }\n }\n return cleaned;\n });\n}\n\n\n\n// Structured summary extraction to eliminate citation artifacts and enforce clean fields\nexport async function extractStructuredSummary(rawText, apiKey) {\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:\n 'You convert arbitrary summary-like text into a strict JSON object describing the content. Return ONLY JSON, no markdown. Remove all citation artifacts (e.g., [1], (2), †), line numbers (e.g., L0:), and scraped UI fragments. Keep clean prose. Choose one type: research or general. For research, populate research_question, methods_and_findings, significance. For general, populate what_it_is, key_points (short bullet strings), and details. If any field would repeat or mirror the title or adds no value, set it to null. Keep text concise.'\n },\n {\n role: 'user',\n content:\n 'Normalize the following text into ONLY valid JSON matching the schema. No markdown fences, no HTML. Remove citations, numbers-in-brackets, line numbers, and artifacts.\\n---\\n' + rawText\n }\n ],\n response_format: {\n type: 'json_schema',\n json_schema: {\n name: 'structured_summary',\n schema: {\n type: 'object',\n properties: {\n type: { type: 'string', enum: ['general', 'research'] },\n general: {\n type: 'object',\n properties: {\n what_it_is: { type: 'string' },\n key_points: { type: 'array', items: { type: 'string' } },\n details: { type: 'string' }\n },\n additionalProperties: false\n },\n research: {\n type: 'object',\n properties: {\n research_question: { type: 'string' },\n methods_and_findings: { type: 'string' },\n significance: { type: 'string' }\n },\n additionalProperties: false\n }\n },\n required: ['type'],\n additionalProperties: false\n }\n }\n },\n stream: false\n }),\n });\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`Groq API error: ${response.status} ${text}`);\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 parsed && typeof parsed === 'object' ? parsed : null;\n } catch (_) {\n return null;\n }\n}\n\nfunction escapeHtml(str) {\n if (!str) return '';\n return String(str)\n .replace(/&/g, '&')\n .replace(//g, '>')\n .replace(/\"/g, '"')\n .replace(/'/g, ''');\n}\n\n// Deterministic HTML renderer for structured summary\nexport function renderStructuredSummaryToHtml(structured) {\n if (!structured || typeof structured !== 'object') return '';\n const type = structured.type;\n if (type === 'research' && structured.research) {\n const rq = escapeHtml(structured.research.research_question || '');\n const mf = escapeHtml(structured.research.methods_and_findings || '');\n const sg = escapeHtml(structured.research.significance || '');\n let html = '';\n if (rq) html += '

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. 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Chatter

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{ 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}\n\n\n",[197],"042a27e8-7758-11f0-a8bc-0224a6c84d84","chatCompletion.js","f6661672-7616-11f0-b3f9-0224a6c84d84",31,["D",1754988035907],"// 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 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Research utilities extracted from researchApp\n\nexport function getDisplaySourceName(selectedSource, customSource) {\n const sourceMap = {\n 'pubmed': 'PubMed',\n 'biorxiv': 'bioRxiv',\n 'arxiv': 'arXiv',\n 'medrxiv': 'medRxiv',\n 'researchgate': 'ResearchGate',\n 'google scholar': 'Google Scholar',\n 'hacker news': 'Hacker News',\n 'reddit': 'Reddit',\n 'news': 'News'\n };\n if (selectedSource === 'custom' && customSource) return customSource;\n return sourceMap[selectedSource] || selectedSource || '';\n}\n\nexport function getActualSearchSource(selectedSource, customSource) {\n if (selectedSource === 'custom' && customSource) return `on ${customSource}`;\n if (selectedSource === 'pubmed') return 'PubMed';\n if (selectedSource === 'biorxiv') return 'bioRxiv';\n if (selectedSource === 'arxiv') return 'arXiv';\n if (selectedSource === 'medrxiv') return 'medRxiv';\n if (selectedSource === 'researchgate') return 'ResearchGate';\n if (selectedSource === 'google scholar') return 'Google Scholar';\n return '';\n}\n\nexport function getActualSearchSourceName(selectedSource, customSource) {\n if (selectedSource === 'custom' && customSource) return customSource;\n if (selectedSource === 'pubmed') return 'PubMed';\n if (selectedSource === 'biorxiv') return 'bioRxiv';\n if (selectedSource === 'arxiv') return 'arXiv';\n if (selectedSource === 'medrxiv') return 'medRxiv';\n if (selectedSource === 'researchgate') return 'ResearchGate';\n if (selectedSource === 'google scholar') return 'Google Scholar';\n if (selectedSource === 'hacker news') return 'Hacker News';\n if (selectedSource === 'reddit') return 'Reddit';\n if (selectedSource === 'news') return 'News';\n return '';\n}\n\n\n",[],[226,320],"a0292cb2-7b21-11f0-88bb-0224a6c84d84","researchApp.js","f6940d20-7616-11f0-a338-0224a6c84d84",53,["D",1755404479954],5,"import { getI18n, getDateRangeText as i18nDateRangeText } from './i18n.js';\nimport { getDisplaySourceName, getActualSearchSource, getActualSearchSourceName } from './researchLib.js';\nimport { checkServerKey as apiCheckServerKey, summarizePaper as apiSummarizePaper, postChatStreamSSE, postChatStream, postGroqChat } from './apiClient.js';\nimport {\n initDb,\n loadChats as coreLoadChats,\n loadFolders as coreLoadFolders,\n createFolder as coreCreateFolder,\n startEditingFolder as coreStartEditingFolder,\n commitEditingFolder as coreCommitEditingFolder,\n cancelEditingFolder as coreCancelEditingFolder,\n toggleFolderCollapsed as coreToggleFolderCollapsed,\n moveChatToFolder as coreMoveChatToFolder,\n baseChats as coreBaseChats,\n chatsInFolder as coreChatsInFolder,\n createNewChat as coreCreateNewChat,\n selectChat as coreSelectChat,\n startEditingChat as coreStartEditingChat,\n commitEditingChat as coreCommitEditingChat,\n cancelEditingChat as coreCancelEditingChat,\n deleteChat as coreDeleteChat,\n duplicateChat as coreDuplicateChat,\n ensureChatExistsForEdits as coreEnsureChatExistsForEdits,\n ensureMessagePersisted as coreEnsureMessagePersisted,\n persistMessageAtIndex as corePersistMessageAtIndex,\n deleteMessage as coreDeleteMessage,\n deleteMessagesBelow as coreDeleteMessagesBelow,\n rerunFromUser as coreRerunFromUser,\n sendMessage as coreSendMessage\n} from './core/chatCore.js';\nimport { isStreamingForCurrent as expIsStreamingForCurrent, streamAssistant as expStreamAssistant } from './experimental/streaming.js';\n\nexport default function researchApp() {\n return {\n searchQuery: '',\n dateRange: '',\n selectedSource: '',\n customSource: '',\n selectedLanguage: 'english',\n results: [],\n assistantContent: '',\n route: 'links',\n isSearching: false,\n isLoadingMore: false,\n hasSearched: false,\n currentOffset: 0,\n hasMoreResults: true,\n errorMessage: '',\n summaryStates: {},\n hasServerKey: true,\n userApiKey: '',\n apiKeyInput: '',\n // Model selection\n selectedModel: 'openai/gpt-oss-120b',\n // Browser search tool toggle\n useBrowserSearch: true,\n useCodeInterpreter: false,\n // System prompt state\n systemPrompt: '',\n systemPromptOpen: false,\n systemPromptDebounceId: null,\n // Generation settings\n temperature: 1,\n maxTokens: 8192,\n reasoningEffort: 'medium',\n streamEnabled: true,\n jsonMode: false,\n // Custom chat completions endpoint (e.g., http://localhost:11434 or http://localhost:1234)\n customChatBaseUrl: '',\n // Stream test state\n streamPrompt: '',\n isStreaming: false,\n streamError: '',\n streamAggregates: null,\n streamOpen: true,\n eventsOpen: false,\n // Trace log state\n traceEvents: [],\n traceExpanded: false,\n expandedToolMap: {},\n copyEventsText: 'copy json',\n copyEventsTimeoutId: null,\n \n // Timer state\n timerStartMs: null,\n timerIntervalId: null,\n timerFrozenText: '',\n timerElapsedMs: 0,\n \n // Chat state\n messages: [],\n chatInput: '',\n // Streaming session guards to prevent cross-chat bleed and allow concurrency by chat\n currentStreamToken: null,\n streamChatId: null,\n streamingChats: {}, // chatId -> { token, startedAt }\n // Streaming reasoning state per assistant message\n messageReasoningMap: {},\n expandedReasoningMap: {},\n // UI ephemeral state\n copiedMap: {}, // idx -> boolean\n _copiedTimeouts: {},\n \n // Inline message editing state\n editingMessageIdx: null,\n editingMessageId: null,\n editingMessageText: '',\n editingMessageOriginal: '',\n editingDebounceId: null,\n\n // (removed) confirmation modal state\n \n // Typewriter effect variables\n hasUserInteracted: false,\n typewriterActive: false,\n typewriterTimeouts: [],\n currentLanguageIndex: 0,\n currentCharIndex: 0,\n isTyping: false,\n lastTypewriterText: '',\n \n // Testing override - if set to a string, will replace typewriter effect\n testOverride: '', // Set to null or '' to disable override\n\n // Sidebar + chats (Dexie-backed)\n sidebarOpen: false, // mobile overlay\n sidebarCollapsed: false, // desktop collapse\n sidebarTransitioning: false,\n sidebarAnimMs: 300,\n // Right settings panel (nested inside main)\n settingsOpen: false, // visibility toggle\n settingsWidth: 340,\n minSettingsWidth: 260,\n maxSettingsWidth: 560,\n isResizingSettings: false,\n settingsResizeStartX: 0,\n settingsResizeStartWidth: 340,\n // Resizable sidebar\n sidebarWidth: 256,\n minSidebarWidth: 180,\n maxSidebarWidth: 520,\n isResizingSidebar: false,\n resizeStartX: 0,\n resizeStartWidth: 256,\n activeSearchId: null,\n ephemeralChatId: '__ephemeral__',\n chats: [], // { id, title, createdAt, folderId? }\n currentChatId: null,\n db: null,\n editingChatId: null,\n editingChatTitle: '',\n // Folders state\n folders: [], // { id, name, createdAt, order, collapsed }\n editingFolderId: null,\n editingFolderName: '',\n // Drag & drop state\n draggingChatId: null,\n dragOverFolderId: null,\n dragOverBase: false,\n\n async init() {\n console.log('🔧 Chat app initializing...');\n \n // Load API key from localStorage\n const storedApiKey = localStorage.getItem('groq_api_key');\n if (storedApiKey) {\n this.userApiKey = storedApiKey;\n }\n // Load preferred model\n try {\n const storedModel = localStorage.getItem('groq_model');\n if (storedModel && typeof storedModel === 'string') {\n this.selectedModel = storedModel;\n }\n const storedBase = localStorage.getItem('chat_base_url');\n if (storedBase && typeof storedBase === 'string') {\n this.customChatBaseUrl = storedBase;\n }\n const storedUse = localStorage.getItem('use_browser_search');\n if (storedUse === '0') this.useBrowserSearch = false;\n if (storedUse === '1') this.useBrowserSearch = true;\n const storedCI = localStorage.getItem('use_code_interpreter');\n if (storedCI === '1') this.useCodeInterpreter = true;\n if (storedCI === '0') this.useCodeInterpreter = false;\n const sp = localStorage.getItem('system_prompt');\n if (typeof sp === 'string') this.systemPrompt = sp;\n const spOpen = localStorage.getItem('system_prompt_open');\n if (spOpen === '1') this.systemPromptOpen = true;\n const t = localStorage.getItem('temperature');\n if (t != null && t !== '' && !Number.isNaN(Number(t))) this.temperature = Math.max(0, Math.min(2, Number(t)));\n const mt = localStorage.getItem('max_tokens');\n if (mt != null && mt !== '' && !Number.isNaN(Number(mt))) this.maxTokens = Math.max(1, Number(mt));\n const re = localStorage.getItem('reasoning_effort');\n if (re === 'low' || re === 'medium' || re === 'high') this.reasoningEffort = re;\n const se = localStorage.getItem('stream_enabled');\n if (se === '0') this.streamEnabled = false; if (se === '1') this.streamEnabled = true;\n const jm = localStorage.getItem('json_mode');\n if (jm === '1') this.jsonMode = true; if (jm === '0') this.jsonMode = false;\n } catch (_) { /* ignore */ }\n \n // Check if server has API key\n await this.checkServerKey();\n \n await initDb(this);\n await this.loadFolders();\n await this.loadChats();\n // Start with an ephemeral chat; persist if/when content is edited or a message is sent\n this.currentChatId = null;\n this.activeSearchId = this.ephemeralChatId;\n this.messages = [{ role: 'assistant', content: 'Hi! How can I help you today?', createdAt: Date.now() }];\n this.sidebarOpen = false;\n // Load persisted sidebar width\n try {\n const sw = Number(localStorage.getItem('sidebar_width'));\n if (Number.isFinite(sw) && sw >= 120 && sw <= 800) this.sidebarWidth = sw;\n const rw = Number(localStorage.getItem('settings_width'));\n if (Number.isFinite(rw) && rw >= 200 && rw <= 800) this.settingsWidth = rw;\n const so = localStorage.getItem('settings_open');\n if (so === '1') this.settingsOpen = true;\n } catch (_) { /* ignore */ }\n this.$nextTick(() => this.scrollToBottom());\n console.log('✅ Chat app initialized');\n },\n\n // Sidebar helpers\n toggleSidebar() { this.sidebarOpen = !this.sidebarOpen; },\n // Settings panel helpers\n toggleSettingsPanel() {\n this.settingsOpen = !this.settingsOpen;\n try { localStorage.setItem('settings_open', this.settingsOpen ? '1' : '0'); } catch (_) { /* ignore */ }\n },\n startSettingsResize(e) {\n if (!this.settingsOpen) return;\n this.isResizingSettings = true;\n this.settingsResizeStartX = e.clientX || 0;\n this.settingsResizeStartWidth = this.settingsWidth;\n try { document.body.classList.add('select-none'); } catch (_) {}\n try {\n window.addEventListener('mousemove', this.onSettingsResizeMove);\n window.addEventListener('mouseup', this.stopSettingsResize, { once: true });\n } catch (_) {}\n },\n onSettingsResizeMove(e) {\n if (!this.isResizingSettings) return;\n const dx = (this.settingsResizeStartX || 0) - (e.clientX || 0);\n let next = Math.round((this.settingsResizeStartWidth || 0) + dx);\n next = Math.max(this.minSettingsWidth, Math.min(this.maxSettingsWidth, next));\n this.settingsWidth = next;\n },\n stopSettingsResize() {\n if (!this.isResizingSettings) return;\n this.isResizingSettings = false;\n try { localStorage.setItem('settings_width', String(this.settingsWidth)); } catch (_) {}\n try { document.body.classList.remove('select-none'); } catch (_) {}\n try { window.removeEventListener('mousemove', this.onSettingsResizeMove); } catch (_) {}\n },\n collapseSidebar() {\n // Trigger width animation immediately but delay the expand-control reveal\n this.sidebarTransitioning = true;\n this.sidebarCollapsed = true;\n setTimeout(() => { this.sidebarTransitioning = false; }, this.sidebarAnimMs);\n },\n expandSidebar() {\n // Trigger width animation immediately and hide expand-control during transition\n this.sidebarTransitioning = true;\n this.sidebarCollapsed = false;\n setTimeout(() => { this.sidebarTransitioning = false; }, this.sidebarAnimMs);\n },\n // Sidebar resizing handlers (desktop)\n startSidebarResize(e) {\n if (this.sidebarCollapsed) return;\n this.isResizingSidebar = true;\n this.resizeStartX = e.clientX || 0;\n this.resizeStartWidth = this.sidebarWidth;\n // Disable text selection while resizing\n try { document.body.classList.add('select-none'); } catch (_) {}\n // Attach move/up listeners as a fallback in case global Alpine listeners miss events\n try {\n window.addEventListener('mousemove', this.onSidebarResizeMove);\n window.addEventListener('mouseup', this.stopSidebarResize, { once: true });\n } catch (_) {}\n },\n onSidebarResizeMove(e) {\n if (!this.isResizingSidebar) return;\n const dx = (e.clientX || 0) - this.resizeStartX;\n let next = Math.round(this.resizeStartWidth + dx);\n next = Math.max(this.minSidebarWidth, Math.min(this.maxSidebarWidth, next));\n this.sidebarWidth = next;\n },\n stopSidebarResize() {\n if (!this.isResizingSidebar) return;\n this.isResizingSidebar = false;\n try { localStorage.setItem('sidebar_width', String(this.sidebarWidth)); } catch (_) {}\n try { document.body.classList.remove('select-none'); } catch (_) {}\n try {\n window.removeEventListener('mousemove', this.onSidebarResizeMove);\n } catch (_) {}\n },\n async loadChats() { await coreLoadChats(this); },\n async loadFolders() { await coreLoadFolders(this); },\n async createFolder() { await coreCreateFolder(this); },\n startEditingFolder(id, currentName) { coreStartEditingFolder(this, id, currentName); },\n async commitEditingFolder() { await coreCommitEditingFolder(this); },\n cancelEditingFolder() { coreCancelEditingFolder(this); },\n async toggleFolderCollapsed(id) { await coreToggleFolderCollapsed(this, id); },\n // Drag & drop helpers\n onChatDragStart(e, chatId) {\n try {\n if (e && e.dataTransfer) {\n e.dataTransfer.setData('text/plain', String(chatId));\n e.dataTransfer.effectAllowed = 'move';\n }\n } catch (_) {}\n this.draggingChatId = chatId;\n },\n onChatDragEnd() {\n this.draggingChatId = null;\n this.dragOverFolderId = null;\n this.dragOverBase = false;\n },\n onFolderDragOver(e, folderId) {\n e.preventDefault();\n this.dragOverFolderId = folderId;\n this.dragOverBase = false;\n },\n onFolderDragLeave(e, folderId) {\n if (this.dragOverFolderId === folderId) this.dragOverFolderId = null;\n },\n async onFolderDrop(e, folderId) {\n e.preventDefault();\n const raw = (() => { try { return e.dataTransfer?.getData('text/plain') } catch { return null } })();\n const id = Number(raw || this.draggingChatId);\n await this.moveChatToFolder(id, folderId);\n this.dragOverFolderId = null;\n this.dragOverBase = false;\n },\n onBaseDragOver(e) {\n e.preventDefault();\n this.dragOverBase = true;\n this.dragOverFolderId = null;\n },\n onBaseDragLeave() {\n this.dragOverBase = false;\n },\n async onBaseDrop(e) {\n e.preventDefault();\n const raw = (() => { try { return e.dataTransfer?.getData('text/plain') } catch { return null } })();\n const id = Number(raw || this.draggingChatId);\n await this.moveChatToFolder(id, null);\n this.dragOverBase = false;\n this.dragOverFolderId = null;\n },\n async moveChatToFolder(chatId, folderId) { await coreMoveChatToFolder(this, chatId, folderId); },\n baseChats() { return coreBaseChats(this); },\n chatsInFolder(folderId) { return coreChatsInFolder(this, folderId); },\n async createNewChat() { await coreCreateNewChat(this); },\n async selectChat(id) { await coreSelectChat(this, id); },\n startEditingChat(id, currentTitle) { coreStartEditingChat(this, id, currentTitle); },\n async commitEditingChat() { await coreCommitEditingChat(this); },\n cancelEditingChat() { coreCancelEditingChat(this); },\n async deleteChat(id) { await coreDeleteChat(this, id); },\n async onDeleteChat(id) { try { const chatId = typeof id === 'string' ? Number(id) : id; await this.deleteChat(chatId); } catch (_) {} },\n async duplicateChat(id) { await coreDuplicateChat(this, id); },\n async onDuplicateChat(id) { try { const chatId = typeof id === 'string' ? Number(id) : id; await this.duplicateChat(chatId); } catch (_) {} },\n\n async checkServerKey() {\n try {\n const data = await apiCheckServerKey();\n this.hasServerKey = !!data.hasServerKey;\n } catch (error) {\n console.error('Error checking server key:', error);\n this.hasServerKey = false;\n }\n },\n\n setApiKey() {\n if (this.apiKeyInput.trim()) {\n this.userApiKey = this.apiKeyInput.trim();\n localStorage.setItem('groq_api_key', this.userApiKey);\n this.apiKeyInput = '';\n }\n },\n\n changeApiKey() {\n this.userApiKey = '';\n },\n\n clearApiKey() {\n this.userApiKey = '';\n localStorage.removeItem('groq_api_key');\n },\n\n onModelChange() {\n try { localStorage.setItem('groq_model', this.selectedModel || 'openai/gpt-oss-120b'); } catch (_) { /* ignore */ }\n const isOss = !!(this.selectedModel && this.selectedModel.startsWith('openai/gpt-oss'));\n if (!isOss) { this.useBrowserSearch = false; this.useCodeInterpreter = false; }\n // If custom is selected, focus the custom endpoint input\n if (this.selectedModel === 'custom') {\n try {\n this.$nextTick(() => {\n const el = this.$refs && this.$refs.customBaseUrlInput;\n if (el && typeof el.focus === 'function') el.focus();\n });\n } catch (_) { /* ignore */ }\n }\n },\n onUseBrowserSearchChange() {\n try { localStorage.setItem('use_browser_search', this.useBrowserSearch ? '1' : '0'); } catch (_) { /* ignore */ }\n },\n onUseCodeInterpreterChange() {\n try { localStorage.setItem('use_code_interpreter', this.useCodeInterpreter ? '1' : '0'); } catch (_) { /* ignore */ }\n },\n\n toggleSystemPromptOpen() {\n this.systemPromptOpen = !this.systemPromptOpen;\n try { localStorage.setItem('system_prompt_open', this.systemPromptOpen ? '1' : '0'); } catch (_) { /* ignore */ }\n },\n onSystemPromptInput(e) {\n try {\n const el = e && e.target; if (el) this.autoResize({ target: el });\n } catch (_) { /* ignore */ }\n const text = typeof this.systemPrompt === 'string' ? this.systemPrompt : '';\n if (this.systemPromptDebounceId) clearTimeout(this.systemPromptDebounceId);\n this.systemPromptDebounceId = setTimeout(() => {\n try { localStorage.setItem('system_prompt', text); } catch (_) { /* ignore */ }\n this.systemPromptDebounceId = null;\n }, 300);\n },\n\n onTemperatureChange() {\n const v = Number(this.temperature);\n this.temperature = Number.isFinite(v) ? Math.max(0, Math.min(2, v)) : 1;\n try { localStorage.setItem('temperature', String(this.temperature)); } catch (_) { /* ignore */ }\n },\n onMaxTokensChange() {\n const v = Math.max(1, Math.floor(Number(this.maxTokens) || 0));\n this.maxTokens = v;\n try { localStorage.setItem('max_tokens', String(this.maxTokens)); } catch (_) { /* ignore */ }\n },\n onReasoningChange() {\n const v = this.reasoningEffort;\n const ok = v === 'low' || v === 'medium' || v === 'high';\n if (!ok) this.reasoningEffort = 'medium';\n try { localStorage.setItem('reasoning_effort', this.reasoningEffort); } catch (_) { /* ignore */ }\n },\n onStreamToggle() {\n try { localStorage.setItem('stream_enabled', this.streamEnabled ? '1' : '0'); } catch (_) { /* ignore */ }\n },\n onJsonModeToggle() {\n try { localStorage.setItem('json_mode', this.jsonMode ? '1' : '0'); } catch (_) { /* ignore */ }\n },\n onCustomChatBaseUrlChange() {\n try { localStorage.setItem('chat_base_url', this.customChatBaseUrl || ''); } catch (_) { /* ignore */ }\n },\n\n get maskedApiKey() {\n if (!this.userApiKey) return '';\n const key = this.userApiKey;\n return key.substring(0, 8) + '*'.repeat(Math.max(0, key.length - 12)) + key.substring(key.length - 4);\n },\n\n get displaySourceName() {\n return getDisplaySourceName(this.selectedSource, this.customSource);\n },\n\n // Internationalization system\n get i18n() {\n return getI18n(this.selectedLanguage);\n },\n\n getSummaryTitle() {\n return this.i18n.summary;\n },\n\n getSearchButtonText() {\n return `${this.i18n.search} ${this.displaySourceName}`;\n },\n\n getSearchingButtonText() {\n return `${this.i18n.searching} ${this.displaySourceName}...`;\n },\n\n get loadingMessage() {\n // Use the last typewriter text if available, otherwise fall back to current searchQuery\n const queryText = this.lastTypewriterText || this.searchQuery;\n const dateRangeText = this.dateRange ? this.getDateRangeText() : '';\n \n // Get the actual source being searched (matches backend logic)\n const actualSource = this.getActualSearchSourceName();\n \n // Use language-specific template\n const template = this.isLoadingMore ? this.i18n.loadingMoreTemplate : this.i18n.searchingTemplate;\n return template(actualSource, queryText, dateRangeText);\n },\n\n // Timer computed display\n get displayTimerText() {\n if (this.timerFrozenText) return this.timerFrozenText;\n if (!this.timerStartMs) return '';\n const elapsed = this.timerElapsedMs / 1000;\n const seconds = Math.floor(elapsed);\n const hundredths = Math.floor((elapsed - seconds) * 100);\n const s = String(seconds).padStart(2, '0');\n const h = String(hundredths).padStart(2, '0');\n return `${s}.${h}s`;\n },\n\n getDateRangeText() {\n return i18nDateRangeText(this.dateRange, this.i18n);\n },\n\n getActualSearchSource() {\n return getActualSearchSource(this.selectedSource, this.customSource);\n },\n\n getActualSearchSourceName() {\n return getActualSearchSourceName(this.selectedSource, this.customSource);\n },\n\n handleSourceChange() {},\n\n startTypewriter() {},\n\n typewriterCycle() {},\n\n typeText() {},\n\n clearAllTimeouts() {\n this.typewriterTimeouts.forEach(timeout => clearTimeout(timeout));\n this.typewriterTimeouts = [];\n },\n\n stopTypewriter() {},\n\n // Timer controls\n startTimer() {\n this.stopTimer();\n this.timerFrozenText = '';\n this.timerStartMs = Date.now();\n this.timerElapsedMs = 0;\n // Update every 30ms for smooth hundredths\n this.timerIntervalId = setInterval(() => {\n this.timerElapsedMs = Date.now() - this.timerStartMs;\n }, 30);\n },\n stopTimer() {\n if (this.timerIntervalId) {\n clearInterval(this.timerIntervalId);\n this.timerIntervalId = null;\n }\n if (this.timerStartMs) {\n const elapsed = (this.timerElapsedMs || (Date.now() - this.timerStartMs)) / 1000;\n const seconds = Math.floor(elapsed);\n const hundredths = Math.floor((elapsed - seconds) * 100);\n const s = String(seconds).padStart(2, '0');\n const h = String(hundredths).padStart(2, '0');\n this.timerFrozenText = `${s}.${h}s...done`;\n }\n this.timerStartMs = null;\n this.timerElapsedMs = 0;\n },\n\n handleSearchClick() {},\n \n async searchResearch() {},\n\n async summarizePaper(url, title, index) {\n console.log('📄 Summary triggered for:', title, 'at index:', index);\n // Initialize summary state for this paper\n if (!this.summaryStates[index]) {\n this.summaryStates[index] = {};\n }\n \n this.summaryStates[index].loading = true;\n this.summaryStates[index].summary = '';\n\n try {\n const data = await apiSummarizePaper({ url, title, language: this.selectedLanguage, userApiKey: this.userApiKey });\n \n if (data.error) {\n this.summaryStates[index].summary = 'Error: ' + data.error;\n } else {\n this.summaryStates[index].summary = data.summary;\n }\n } catch (error) {\n this.summaryStates[index].summary = 'Error analyzing paper: ' + error.message;\n } finally {\n this.summaryStates[index].loading = false;\n }\n },\n async runStreamTest() {},\n // Pretty-print assistant content if it's valid JSON, else return as-is\n formatAssistantContent() {\n const text = this.assistantContent || '';\n if (!text) return '';\n const trimmed = text.trim();\n if ((trimmed.startsWith('{') || trimmed.startsWith('['))) {\n try {\n const obj = JSON.parse(trimmed);\n return JSON.stringify(obj, null, 2);\n } catch (_) {\n return text;\n }\n }\n return text;\n },\n // Render assistant content as HTML using marked + DOMPurify (safe markdown rendering)\n renderAssistantContent() {\n const raw = this.formatAssistantContent();\n try {\n // If it is JSON (from formatAssistantContent), keep as a code block\n if (raw && (raw.trim().startsWith('{') || raw.trim().startsWith('['))) {\n const escaped = raw.replace(/&/g, '&').replace(//g, '>');\n return `

${escaped}

`;\n }\n const html = (window.marked ? window.marked.parse(raw) : raw);\n return (window.DOMPurify ? window.DOMPurify.sanitize(html) : html);\n } catch (_) {\n return raw;\n }\n },\n // Trace helpers\n computeTraceMaxHeight() {\n return this.traceExpanded ? '' : 'max-height: 100px';\n },\n toggleTool(idx) {\n this.expandedToolMap[idx] = !this.expandedToolMap[idx];\n this.queueScrollToBottom();\n },\n toggleReasoning(messageId) {\n if (messageId == null) return;\n this.expandedReasoningMap[messageId] = !this.expandedReasoningMap[messageId];\n this.queueScrollReasoningById(messageId);\n },\n prettify(obj) {\n try { return JSON.stringify(obj, null, 2); } catch (_) { return String(obj); }\n },\n async copyEventsJson() {\n try {\n const json = JSON.stringify(this.traceEvents || [], null, 2);\n await navigator.clipboard.writeText(json);\n this.copyEventsText = 'copied';\n if (this.copyEventsTimeoutId) clearTimeout(this.copyEventsTimeoutId);\n this.copyEventsTimeoutId = setTimeout(() => {\n this.copyEventsText = 'copy json';\n this.copyEventsTimeoutId = null;\n }, 3000);\n } catch (_) {\n // no-op\n }\n },\n // Smoothly ensure the trace scroller is at bottom after DOM updates\n queueScrollToBottom() {\n try {\n const el = this.$refs && this.$refs.traceContainer;\n if (!el) return;\n const doScroll = () => { el.scrollTop = el.scrollHeight; };\n if (typeof this.$nextTick === 'function') {\n this.$nextTick(doScroll);\n } else {\n requestAnimationFrame(doScroll);\n }\n } catch (_) {\n // no-op\n }\n },\n // Smoothly keep the per-message reasoning panel scrolled to bottom\n queueScrollReasoningById(messageId) {\n try {\n const el = document.querySelector('[data-reasoning-id=\"' + messageId + '\"]');\n if (!el) return;\n const doScroll = () => { el.scrollTop = el.scrollHeight; };\n if (typeof this.$nextTick === 'function') {\n this.$nextTick(doScroll);\n } else {\n requestAnimationFrame(doScroll);\n }\n } catch (_) { /* ignore */ }\n },\n\n // Chat helpers\n renderMarkdown(text) {\n const raw = String(text || '');\n try {\n const html = (window.marked ? window.marked.parse(raw) : raw);\n return (window.DOMPurify ? window.DOMPurify.sanitize(html) : html);\n } catch (_) { return raw; }\n },\n async copyMessage(idx) {\n try {\n if (!Array.isArray(this.messages) || idx == null || idx < 0 || idx >= this.messages.length) return;\n const m = this.messages[idx];\n const text = String(m?.content || '');\n await navigator.clipboard.writeText(text);\n // transient copied state per-index\n this.copiedMap[idx] = true;\n if (this._copiedTimeouts == null) this._copiedTimeouts = {};\n if (this._copiedTimeouts[idx]) clearTimeout(this._copiedTimeouts[idx]);\n this._copiedTimeouts[idx] = setTimeout(() => {\n this.copiedMap[idx] = false;\n delete this._copiedTimeouts[idx];\n }, 2000);\n } catch (_) { /* ignore */ }\n },\n async deleteMessage(idx) {\n try {\n if (!Array.isArray(this.messages) || idx == null || idx < 0 || idx >= this.messages.length) return;\n const msg = this.messages[idx];\n const messageId = msg && msg.id != null ? msg.id : null;\n // Remove from DB first (if persisted)\n try {\n if (this.db && messageId != null) {\n await this.db.messages.delete(messageId);\n }\n } catch (_) { /* ignore */ }\n // Clear assistant reasoning state if present\n try {\n if (messageId != null) {\n if (this.messageReasoningMap && this.messageReasoningMap[messageId] != null) {\n delete this.messageReasoningMap[messageId];\n }\n if (this.expandedReasoningMap && this.expandedReasoningMap[messageId] != null) {\n delete this.expandedReasoningMap[messageId];\n }\n }\n } catch (_) { /* ignore */ }\n // Remove from local array and clean up transient UI state\n try {\n this.messages.splice(idx, 1);\n if (this.copiedMap && this.copiedMap[idx]) delete this.copiedMap[idx];\n } catch (_) { /* ignore */ }\n // Adjust editing state if necessary\n if (this.editingMessageIdx === idx) {\n this.editingMessageIdx = null;\n this.editingMessageId = null;\n this.editingMessageText = '';\n this.editingMessageOriginal = '';\n } else if (typeof this.editingMessageIdx === 'number' && this.editingMessageIdx > idx) {\n this.editingMessageIdx = this.editingMessageIdx - 1;\n }\n } catch (_) { /* ignore */ }\n },\n async deleteMessagesBelow(idx) {\n try {\n if (!Array.isArray(this.messages) || idx == null || idx < 0 || idx >= this.messages.length) return;\n const thisChatId = this.currentChatId;\n const toRemove = (this.messages || []).slice(idx + 1);\n // Remove from DB first (if persisted)\n try {\n if (this.db) {\n for (const msg of toRemove) {\n const messageId = msg && msg.id != null ? msg.id : null;\n if (messageId != null) {\n try { await this.db.messages.delete(messageId); } catch (_) { /* ignore */ }\n }\n if (messageId != null) {\n if (this.messageReasoningMap && this.messageReasoningMap[messageId] != null) {\n delete this.messageReasoningMap[messageId];\n }\n if (this.expandedReasoningMap && this.expandedReasoningMap[messageId] != null) {\n delete this.expandedReasoningMap[messageId];\n }\n }\n }\n }\n } catch (_) { /* ignore */ }\n // Truncate in-memory messages and clean up transient UI state\n try {\n this.messages = (this.messages || []).slice(0, idx + 1);\n if (this.copiedMap) {\n try {\n const keys = Object.keys(this.copiedMap);\n for (const k of keys) {\n const i = Number(k);\n if (Number.isFinite(i) && i > idx) delete this.copiedMap[i];\n }\n } catch (_) { /* ignore */ }\n }\n } catch (_) { /* ignore */ }\n // Reset editing state if it pointed to a deleted index\n if (typeof this.editingMessageIdx === 'number' && this.editingMessageIdx > idx) {\n this.editingMessageIdx = null;\n this.editingMessageId = null;\n this.editingMessageText = '';\n this.editingMessageOriginal = '';\n }\n // If a stream is active for this chat, cancel it\n try {\n if (this.streamingChats && thisChatId && this.streamingChats[thisChatId]) {\n delete this.streamingChats[thisChatId];\n }\n } catch (_) { /* ignore */ }\n this.scrollToBottom();\n } catch (_) { /* ignore */ }\n },\n async rerunFromUser(idx) {\n try {\n if (this.isStreamingForCurrent) return;\n if (!Array.isArray(this.messages) || idx == null || idx < 0 || idx >= this.messages.length) return;\n const m = this.messages[idx];\n if (!m || m.role !== 'user') return;\n const text = String(m.content || '').trim();\n if (!text) return;\n // Remove all messages after this user message both in-memory and in DB\n try {\n const toRemove = (this.messages || []).slice(idx + 1);\n if (this.db) {\n for (const msg of toRemove) {\n if (msg && msg.id != null) {\n try { await this.db.messages.delete(msg.id); } catch (_) { /* ignore */ }\n }\n }\n }\n } catch (_) { /* ignore */ }\n this.messages = (this.messages || []).slice(0, idx + 1);\n // Ensure chat exists\n if (!this.currentChatId) {\n try {\n const base = text || 'New chat';\n const title = base.substring(0, 60);\n const createdAt = Date.now();\n const id = await this.db.chats.add({ title, createdAt });\n await this.loadChats();\n this.currentChatId = id;\n this.activeSearchId = id;\n } catch (_) { /* ignore */ }\n }\n this.scrollToBottom();\n // Trigger streaming new assistant response\n this.streamAssistant();\n } catch (_) { /* ignore */ }\n },\n autoResize(e) {\n try {\n const el = e && e.target; if (!el) return;\n el.style.height = 'auto';\n el.style.height = Math.min(el.scrollHeight, 320) + 'px';\n } catch (_) {}\n },\n async ensureChatExistsForEdits() { return coreEnsureChatExistsForEdits(this); },\n async ensureMessagePersisted(idx) { return coreEnsureMessagePersisted(this, idx); },\n async persistMessageAtIndex(idx) { return corePersistMessageAtIndex(this, idx); },\n // Inline editing: start editing a message at index\n async startEditingMessage(idx) {\n try {\n if (!Array.isArray(this.messages) || idx < 0 || idx >= this.messages.length) return;\n const m = this.messages[idx] || {};\n this.editingMessageIdx = idx;\n this.editingMessageId = m.id || null;\n this.editingMessageOriginal = String(m.content || '');\n this.editingMessageText = this.editingMessageOriginal;\n // If message isn't persisted yet (e.g., initial assistant greeting), create it now\n try {\n const ensured = await this.ensureMessagePersisted(idx);\n if (ensured) this.editingMessageId = ensured;\n } catch (_) { /* ignore */ }\n // focus editor on next tick and prefill content\n setTimeout(() => {\n try {\n const el = document.querySelector('[data-editing-idx=\"' + idx + '\"]');\n if (el) {\n // Prefill for contenteditable or textarea inputs\n if (el.getAttribute && el.getAttribute('contenteditable') === 'true') {\n el.textContent = this.editingMessageText || '';\n el.focus();\n try {\n const sel = window.getSelection && window.getSelection();\n const range = document.createRange && document.createRange();\n if (sel && range) {\n range.selectNodeContents(el);\n range.collapse(false);\n sel.removeAllRanges();\n sel.addRange(range);\n }\n } catch (_) { /* ignore */ }\n } else {\n try { el.value = this.editingMessageText || ''; } catch (_) { /* ignore */ }\n el.focus();\n this.autoResize({ target: el });\n el.select && el.select();\n }\n }\n } catch (_) {}\n }, 30);\n } catch (_) { /* no-op */ }\n },\n // Debounced input handler for editing\n async onEditingInput(e) {\n try {\n const text = typeof this.editingMessageText === 'string' ? this.editingMessageText : '';\n const i = this.editingMessageIdx;\n if (i != null && i >= 0 && i < this.messages.length) {\n this.messages[i].content = text;\n }\n if (this.editingDebounceId) clearTimeout(this.editingDebounceId);\n this.editingDebounceId = setTimeout(async () => {\n try {\n const id = await this.persistMessageAtIndex(i);\n if (id) this.editingMessageId = id;\n } catch (_) { /* ignore */ }\n }, 400);\n } catch (_) { /* ignore */ }\n },\n // Commit the edit and exit editing mode\n async commitEditingMessage() {\n try {\n if (this.editingDebounceId) { clearTimeout(this.editingDebounceId); this.editingDebounceId = null; }\n const text = (this.editingMessageText || '').trim();\n const i = this.editingMessageIdx;\n if (i != null && i >= 0 && i < this.messages.length) {\n this.messages[i].content = text;\n }\n try { await this.persistMessageAtIndex(i); } catch (_) { /* ignore */ }\n } finally {\n this.editingMessageIdx = null;\n this.editingMessageId = null;\n this.editingMessageText = '';\n this.editingMessageOriginal = '';\n }\n },\n // Cancel the edit, revert content locally and in DB\n async cancelEditingMessage() {\n try {\n if (this.editingDebounceId) { clearTimeout(this.editingDebounceId); this.editingDebounceId = null; }\n const original = String(this.editingMessageOriginal || '');\n const i = this.editingMessageIdx;\n if (i != null && i >= 0 && i < this.messages.length) {\n this.messages[i].content = original;\n }\n const id = this.editingMessageId;\n try {\n if (id && this.db) {\n await this.db.messages.update(id, { content: original });\n }\n } catch (_) { /* ignore */ }\n } finally {\n this.editingMessageIdx = null;\n this.editingMessageId = null;\n this.editingMessageText = '';\n this.editingMessageOriginal = '';\n }\n },\n maybeSendOnEnter(e) {\n if (e.shiftKey) {\n try {\n const el = e.target;\n const start = el.selectionStart;\n const end = el.selectionEnd;\n const value = el.value;\n el.value = value.slice(0, start) + '\\n' + value.slice(end);\n this.chatInput = el.value;\n el.selectionStart = el.selectionEnd = start + 1;\n this.$nextTick(() => this.autoResize({ target: el }));\n } catch (_) {}\n return;\n }\n this.sendMessage();\n },\n scrollToBottom() {\n try {\n const el = this.$refs && this.$refs.messagesContainer; if (!el) return;\n const doScroll = () => { el.scrollTop = el.scrollHeight; };\n if (typeof this.$nextTick === 'function') this.$nextTick(doScroll); else requestAnimationFrame(doScroll);\n } catch (_) {}\n },\n async sendMessage() { await coreSendMessage(this); },\n get isStreamingForCurrent() { return expIsStreamingForCurrent(this); },\n\n async streamAssistant() { await expStreamAssistant(this); }\n };\n}\n\n\n",[],[226,328],"a08d19a2-7b21-11f0-9126-0224a6c84d84","init.js","f6847112-7616-11f0-9927-0224a6c84d84",57,["D",1755404479961],"import researchApp from './researchApp.js';\n\n// Expose globally so existing x-data=\"researchApp()\" continues to work\nwindow.researchApp = researchApp;\n\n// Register with Alpine when ready\nif (window.Alpine && typeof window.Alpine.data === 'function') {\n window.Alpine.data('researchApp', researchApp);\n} else {\n document.addEventListener('alpine:init', () => {\n try {\n if (window.Alpine && typeof window.Alpine.data === 'function') {\n window.Alpine.data('researchApp', researchApp);\n }\n // Register a lightweight autosize directive for textareas\n if (window.Alpine && typeof window.Alpine.directive === 'function') {\n window.Alpine.directive('autosize', (el, _binding, { cleanup }) => {\n if (!el || el.tagName !== 'TEXTAREA') return;\n const resize = () => {\n try {\n el.style.height = 'auto';\n el.style.overflowY = 'hidden';\n // Use scrollHeight to fit content\n el.style.height = `${el.scrollHeight}px`;\n } catch (_) { /* no-op */ }\n };\n // Store reference for cleanup\n el.__autosize__ = resize;\n // Initial and queued resizes for cases when content is set after init\n const scheduleInitialResizes = () => {\n resize();\n try { requestAnimationFrame(resize); } catch (_) {}\n setTimeout(resize, 0);\n setTimeout(resize, 50);\n if (window.Alpine && typeof window.Alpine.nextTick === 'function') {\n try { window.Alpine.nextTick(resize); } catch (_) {}\n }\n // Keep adjusting for a short burst to catch async model hydration\n let attempts = 0;\n const maxAttempts = 20; // ~1s @ 50ms\n const initialInterval = setInterval(() => {\n attempts += 1;\n resize();\n if (attempts >= maxAttempts) {\n clearInterval(initialInterval);\n }\n }, 50);\n // Store for cleanup\n el.__autosizeInterval__ = initialInterval;\n };\n scheduleInitialResizes();\n // Recalculate on input and when x-show reveals the element\n el.addEventListener('input', resize);\n el.addEventListener('alpine:show', resize);\n // Also on window load to catch late-filled values\n const onWindowLoad = () => resize();\n window.addEventListener('load', onWindowLoad, { once: true });\n // In case Alpine finishes initializing after this directive\n const onAlpineInitialized = () => resize();\n document.addEventListener('alpine:initialized', onAlpineInitialized, { once: true });\n const onWindowResize = () => resize();\n window.addEventListener('resize', onWindowResize, { passive: true });\n cleanup(() => {\n el.removeEventListener('input', resize);\n el.removeEventListener('alpine:show', resize);\n window.removeEventListener('load', onWindowLoad);\n document.removeEventListener('alpine:initialized', onAlpineInitialized);\n window.removeEventListener('resize', onWindowResize);\n delete el.__autosize__;\n try { if (el.__autosizeInterval__) clearInterval(el.__autosizeInterval__); } catch (_) {}\n delete el.__autosizeInterval__;\n });\n });\n }\n } catch (_) { /* no-op */ }\n });\n}\n\n// If Alpine was deferred via window.deferLoadingAlpine, start it now\ntry { if (typeof window._startAlpine === 'function') window._startAlpine(); } catch (_) {}\n\n\n",[],[226,337],"900be234-78f1-11f0-a5a1-0224a6c84d84","i18n.js","900be31a-78f1-11f0-a5a1-0224a6c84d84",51,["D",1755163934594],"// Internationalization utilities extracted from researchApp\n// Exports a single function getI18n(selectedLanguage) returning the language pack\n\nexport function getI18n(selectedLanguage) {\n const translations = {\n 'english': {\n title: '(re)Search',\n subtitle: 'Search the web and academic sources with multilingual summaries',\n apiKey: 'API Key:',\n change: 'Change',\n clear: 'Clear',\n getKeyHere: 'Get your free key here',\n language: 'language',\n researchQuery: 'search query',\n dateRange: 'Choose a date range (optional)',\n source: 'Choose a source (optional)',\n enterTopic: 'Enter your research topic...',\n customSource: 'e.g., Nature, Science, Cell, Hacker News...',\n customSourceOption: 'Custom source...',\n chooseDateRange: 'Choose a date range (optional)',\n chooseSource: 'Choose a source (optional)',\n lastMonth: 'Last month',\n last3Months: 'Last 3 months',\n last6Months: 'Last 6 months',\n lastYear: 'Last year',\n allTime: 'All time',\n search: 'Search',\n searching: 'Searching',\n streaming: 'Streaming...',\n searchMore: '(Re)(Re)Search',\n summarize: 'Summarize',\n analyzing: 'Analyzing...',\n openPaper: 'Open',\n foundResults: 'Found',\n results: 'results',\n loading: 'Searching',\n loadingMore: 'Loading more results',\n aiAnalyzing: 'AI is analyzing the paper...',\n analysisTime: 'This may take 10-30 seconds depending on paper length',\n noResultsOrError: 'No results found or a server error occurred.',\n searchingTemplate: (source, query, dateRange) => {\n let msg = `Searching ${source}`;\n if (query) msg += ` for \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n loadingMoreTemplate: (source, query, dateRange) => {\n let msg = `Loading more results from ${source}`;\n if (query) msg += ` for \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n pleaseAddApiKey: 'please add api key',\n pleaseEnterQuery: 'please enter a search query',\n summary: 'Summary:'\n },\n 'french': {\n title: '(re)Recherche',\n subtitle: 'Rechercher dans plusieurs bases de données académiques avec des résumés multilingues',\n apiKey: 'Clé API :',\n change: 'Modifier',\n clear: 'Effacer',\n getKeyHere: 'Obtenez votre clé gratuite ici',\n language: 'langue',\n researchQuery: 'requête de recherche',\n dateRange: 'Choisir une plage de dates (facultative)',\n source: 'Choisir une source (facultative)',\n enterTopic: 'Entrez votre sujet de recherche...',\n customSource: 'ex. Nature, Science, Cell...',\n customSourceOption: 'Source personnalisée...',\n chooseDateRange: 'Choisir une plage de dates (facultative)',\n chooseSource: 'Choisir une source (facultative)',\n lastMonth: 'Le mois dernier',\n last3Months: 'Les 3 derniers mois',\n last6Months: 'Les 6 derniers mois',\n lastYear: 'La dernière année',\n allTime: 'Tout le temps',\n search: '(re)Rechercher',\n searching: '(re)Recherche',\n streaming: 'Diffusion...',\n searchMore: '(Re)(Re)Recherche',\n summarize: 'Résumer',\n analyzing: 'Analyse...',\n openPaper: 'Ouvrir',\n foundResults: 'Trouvé',\n results: 'résultats',\n loading: 'Recherche',\n loadingMore: 'Chargement de plus de résultats',\n aiAnalyzing: 'L\\'IA analyse l\\'article...',\n analysisTime: 'Cela peut prendre 10 à 30 secondes selon la longueur de l\\'article',\n noResultsOrError: 'Aucun résultat trouvé ou une erreur du serveur s\\'est produite.',\n searchingTemplate: (source, query, dateRange) => {\n let msg = `Recherche sur ${source}`;\n if (query) msg += ` pour \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n loadingMoreTemplate: (source, query, dateRange) => {\n let msg = `Chargement de plus de résultats de ${source}`;\n if (query) msg += ` pour \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n pleaseAddApiKey: 'veuillez ajouter la clé api',\n pleaseEnterQuery: 'veuillez entrer une requête de recherche',\n summary: 'Résumé :'\n },\n 'spanish': {\n title: '(re)Buscar',\n subtitle: 'Buscar en múltiples bases de datos académicas con resúmenes multilingües',\n apiKey: 'Clave API:',\n change: 'Cambiar',\n clear: 'Limpiar',\n getKeyHere: 'Obtén tu clave gratuita aquí',\n language: 'idioma',\n researchQuery: 'consulta de investigación',\n dateRange: 'Elegir un rango de fechas (opcional)',\n source: 'Elegir una fuente (opcional)',\n enterTopic: 'Ingresa tu tema de investigación...',\n customSource: 'ej. Nature, Science, Cell...',\n customSourceOption: 'Fuente personalizada...',\n chooseDateRange: 'Elegir un rango de fechas (opcional)',\n chooseSource: 'Elegir una fuente (opcional)',\n lastMonth: 'Último mes',\n last3Months: 'Últimos 3 meses',\n last6Months: 'Últimos 6 meses',\n lastYear: 'Último año',\n allTime: 'Todo el tiempo',\n search: '(re)Buscar',\n searching: '(re)Buscando',\n streaming: 'Transmitiendo...',\n searchMore: '(Re)(Re)Buscar',\n summarize: 'Resumir',\n analyzing: 'Analizando...',\n openPaper: 'Abrir',\n foundResults: 'Encontrado',\n results: 'resultados',\n loading: 'Buscando',\n loadingMore: 'Cargando más resultados',\n aiAnalyzing: 'La IA está analizando el artículo...',\n analysisTime: 'Esto puede tomar 10-30 segundos dependiendo de la longitud del artículo',\n noResultsOrError: 'No se encontraron resultados o ocurrió un error del servidor.',\n searchingTemplate: (source, query, dateRange) => {\n let msg = `Buscando en ${source}`;\n if (query) msg += ` por \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n loadingMoreTemplate: (source, query, dateRange) => {\n let msg = `Cargando más resultados de ${source}`;\n if (query) msg += ` por \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n pleaseAddApiKey: 'por favor agrega clave api',\n pleaseEnterQuery: 'por favor ingresa una consulta de búsqueda',\n summary: 'Resumen:'\n },\n 'german': {\n title: '(re)Suchen',\n subtitle: 'Durchsuchen Sie mehrere akademische Datenbanken mit mehrsprachigen Zusammenfassungen',\n apiKey: 'API-Schlüssel:',\n change: 'Ändern',\n clear: 'Löschen',\n getKeyHere: 'Holen Sie sich Ihren kostenlosen Schlüssel hier',\n language: 'sprache',\n researchQuery: 'suchanfrage',\n dateRange: 'Datumsbereich wählen (optional)',\n source: 'Quelle wählen (optional)',\n enterTopic: 'Geben Sie Ihr Forschungsthema ein...',\n customSource: 'z.B. Nature, Science, Cell...',\n customSourceOption: 'Benutzerdefinierte Quelle...',\n chooseDateRange: 'Datumsbereich wählen (optional)',\n chooseSource: 'Quelle wählen (optional)',\n lastMonth: 'Letzter Monat',\n last3Months: 'Letzte 3 Monate',\n last6Months: 'Letzte 6 Monate',\n lastYear: 'Letztes Jahr',\n allTime: 'Alle Zeit',\n search: '(re)Suchen',\n searching: '(re)Suchen',\n streaming: 'Streaming...',\n searchMore: '(Re)(Re)Suchen',\n summarize: 'Zusammenfassen',\n analyzing: 'Analysiere...',\n openPaper: 'Öffnen',\n foundResults: 'Gefunden',\n results: 'ergebnisse',\n loading: 'Suchen',\n loadingMore: 'Lade weitere Ergebnisse',\n aiAnalyzing: 'KI analysiert den Artikel...',\n analysisTime: 'Dies kann 10-30 Sekunden dauern, abhängig von der Artikellänge',\n noResultsOrError: 'Keine Ergebnisse gefunden oder ein Serverfehler ist aufgetreten.',\n searchingTemplate: (source, query, dateRange) => {\n let msg = `Suche in ${source}`;\n if (query) msg += ` nach \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n loadingMoreTemplate: (source, query, dateRange) => {\n let msg = `Lade weitere Ergebnisse von ${source}`;\n if (query) msg += ` nach \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n pleaseAddApiKey: 'bitte api-schlüssel hinzufügen',\n pleaseEnterQuery: 'bitte suchanfrage eingeben',\n summary: 'Zusammenfassung:'\n },\n 'japanese': {\n title: '(re)検索',\n subtitle: '多言語要約付きの複数の学術データベースを検索',\n apiKey: 'APIキー:',\n change: '変更',\n clear: 'クリア',\n getKeyHere: '無料キーを取得する',\n language: '言語',\n researchQuery: '研究クエリ',\n dateRange: '日付範囲を選択 (任意)',\n source: 'ソースを選択 (任意)',\n enterTopic: '研究トピックを入力...',\n customSource: '例：Nature、Science、Cell...',\n customSourceOption: 'カスタムソース...',\n chooseDateRange: '日付範囲を選択 (任意)',\n chooseSource: 'ソースを選択 (任意)',\n lastMonth: '先月',\n last3Months: '過去3ヶ月',\n last6Months: '過去6ヶ月',\n lastYear: '昨年',\n allTime: '全期間',\n search: '(re)検索',\n searching: '(re)検索中',\n streaming: 'ストリーミング中...',\n searchMore: '(再)(再)検索',\n summarize: '要約',\n analyzing: '分析中...',\n openPaper: '開く',\n foundResults: '見つかった',\n results: '件の結果',\n loading: '検索中',\n loadingMore: 'より多くの結果を読み込み中',\n aiAnalyzing: 'AIが論文を分析中...',\n analysisTime: '論文の長さによって10〜30秒かかることがあります',\n noResultsOrError: '結果が見つからないか、サーバーエラーが発生しました。',\n searchingTemplate: (source, query, dateRange) => {\n let msg = `${source}で検索中`;\n if (query) msg += `「${query}」`;\n if (dateRange) msg += `(${dateRange})`;\n return msg + '...';\n },\n loadingMoreTemplate: (source, query, dateRange) => {\n let msg = `${source}からさらに結果を読み込み中`;\n if (query) msg += `「${query}」`;\n if (dateRange) msg += `(${dateRange})`;\n return msg + '...';\n },\n pleaseAddApiKey: 'apiキーを追加してください',\n pleaseEnterQuery: '検索クエリを入力してください',\n summary: '要約:'\n },\n 'korean': {\n title: '(re)검색',\n subtitle: '다국어 요약과 함께 여러 학술 데이터베이스 검색',\n apiKey: 'API 키:',\n change: '변경',\n clear: '지우기',\n getKeyHere: '여기서 무료 키 받기',\n language: '언어',\n researchQuery: '연구 쿼리',\n dateRange: '날짜 범위 선택 (선택 사항)',\n source: '소스 선택 (선택 사항)',\n enterTopic: '연구 주제를 입력하세요...',\n customSource: '예: Nature, Science, Cell...',\n customSourceOption: '사용자 정의 소스...',\n chooseDateRange: '날짜 범위 선택 (선택 사항)',\n chooseSource: '소스 선택 (선택 사항)',\n lastMonth: '지난 달',\n last3Months: '지난 3개월',\n last6Months: '지난 6개월',\n lastYear: '작년',\n allTime: '전체 기간',\n search: '(re)검색',\n searching: '(re)검색 중',\n streaming: '스트리밍 중...',\n searchMore: '(재)(재)검색',\n summarize: '요약',\n analyzing: '분석 중...',\n openPaper: '열기',\n foundResults: '발견된',\n results: '개 결과',\n loading: '검색 중',\n loadingMore: '더 많은 결과 로딩 중',\n aiAnalyzing: 'AI가 논문을 분석 중...',\n analysisTime: '논문 길이에 따라 10-30초가 걸릴 수 있습니다',\n noResultsOrError: '결과가 없거나 서버 오류가 발생했습니다.',\n searchingTemplate: (source, query, dateRange) => {\n let msg = `${source}에서 검색 중`;\n if (query) msg += ` \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n loadingMoreTemplate: (source, query, dateRange) => {\n let msg = `${source}에서 더 많은 결과 로딩 중`;\n if (query) msg += ` \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n pleaseAddApiKey: 'api 키를 추가해 주세요',\n pleaseEnterQuery: '검색 쿼리를 입력해 주세요',\n summary: '요약:'\n },\n 'chinese': {\n title: '(re)搜索',\n subtitle: '搜索多个学术数据库并提供多语言摘要',\n apiKey: 'API密钥:',\n change: '更改',\n clear: '清除',\n getKeyHere: '在此获取免费密钥',\n language: '语言',\n researchQuery: '研究查询',\n dateRange: '选择日期范围 (可选)',\n source: '选择来源 (可选)',\n enterTopic: '输入您的研究主题...',\n customSource: '例如：Nature、Science、Cell...',\n customSourceOption: '自定义来源...',\n chooseDateRange: '选择日期范围 (可选)',\n chooseSource: '选择来源 (可选)',\n lastMonth: '上个月',\n last3Months: '最近3个月',\n last6Months: '最近6个月',\n lastYear: '去年',\n allTime: '全部时间',\n search: '(re)搜索',\n searching: '(re)搜索中',\n streaming: '流式传输中...',\n searchMore: '(再)(再)搜索',\n summarize: '总结',\n analyzing: '分析中...',\n openPaper: '打开',\n foundResults: '找到',\n results: '个结果',\n loading: '搜索中',\n loadingMore: '加载更多结果',\n aiAnalyzing: 'AI正在分析论文...',\n analysisTime: '根据论文长度，这可能需要10-30秒',\n noResultsOrError: '未找到结果或发生服务器错误。',\n searchingTemplate: (source, query, dateRange) => {\n let msg = `正在${source}中搜索`;\n if (query) msg += `“${query}”`;\n if (dateRange) msg += `(${dateRange})`;\n return msg + '...';\n },\n loadingMoreTemplate: (source, query, dateRange) => {\n let msg = `正在从${source}加载更多结果`;\n if (query) msg += `“${query}”`;\n if (dateRange) msg += `(${dateRange})`;\n return msg + '...';\n },\n pleaseAddApiKey: '请添加api密钥',\n pleaseEnterQuery: '请输入搜索查询',\n summary: '摘要:'\n },\n 'portuguese': {\n title: '(re)Pesquisar',\n subtitle: 'Pesquise em múltiplas bases de dados acadêmicas com resumos multilíngues',\n apiKey: 'Chave API:',\n change: 'Alterar',\n clear: 'Limpar',\n getKeyHere: 'Obtenha sua chave gratuita aqui',\n language: 'idioma',\n researchQuery: 'consulta de pesquisa',\n dateRange: 'Escolher intervalo de datas (opcional)',\n source: 'Escolher fonte (opcional)',\n enterTopic: 'Digite seu tópico de pesquisa...',\n customSource: 'ex. Nature, Science, Cell...',\n customSourceOption: 'Fonte personalizada...',\n chooseDateRange: 'Escolher intervalo de datas (opcional)',\n chooseSource: 'Escolher fonte (opcional)',\n lastMonth: 'Último mês',\n last3Months: 'Últimos 3 meses',\n last6Months: 'Últimos 6 meses',\n lastYear: 'Último ano',\n allTime: 'Todo o tempo',\n search: '(re)Pesquisar',\n searching: '(re)Pesquisando',\n streaming: 'Transmitindo...',\n searchMore: '(Re)(Re)Pesquisar',\n summarize: 'Resumir',\n analyzing: 'Analisando...',\n openPaper: 'Abrir',\n foundResults: 'Encontrado',\n results: 'resultados',\n loading: 'Pesquisando',\n loadingMore: 'Carregando mais resultados',\n aiAnalyzing: 'IA está analisando o artigo...',\n analysisTime: 'Isso pode levar 10-30 segundos dependendo do comprimento do artigo',\n noResultsOrError: 'Nenhum resultado encontrado ou ocorreu um erro no servidor.',\n searchingTemplate: (source, query, dateRange) => {\n let msg = `Pesquisando no ${source}`;\n if (query) msg += ` por \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n loadingMoreTemplate: (source, query, dateRange) => {\n let msg = `Carregando mais resultados do ${source}`;\n if (query) msg += ` por \"${query}\"`;\n if (dateRange) msg += ` (${dateRange})`;\n return msg + '...';\n },\n pleaseAddApiKey: 'por favor adicione chave api',\n pleaseEnterQuery: 'por favor digite uma consulta de pesquisa',\n summary: 'Resumo:'\n }\n };\n\n return translations[selectedLanguage] || translations['english'];\n}\n\nexport function getDateRangeText(dateRange, i18n) {\n const map = {\n '1month': (i18n.lastMonth || '').toLowerCase(),\n '3months': (i18n.last3Months || '').toLowerCase(),\n '6months': (i18n.last6Months || '').toLowerCase(),\n '1year': (i18n.lastYear || '').toLowerCase()\n };\n return map[dateRange] || '';\n}\n\n\n",[],[226,345],"8feabae6-78f1-11f0-b1f8-0224a6c84d84","apiClient.js","8feabba4-78f1-11f0-b1f8-0224a6c84d84",44,["D",1755163934540],"// Centralized API client for frontend calls used by researchApp\n\nexport async function checkServerKey() {\n const res = await fetch('/api/check-key');\n if (!res.ok) throw new Error('Failed to check server key');\n return res.json();\n}\n\nexport async function summarizePaper({ url, title, language, userApiKey }) {\n const res = await fetch('/api/search', {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ url, title, language, userApiKey })\n });\n if (!res.ok) throw new Error('Summary failed: ' + res.statusText);\n return res.json();\n}\n\nexport async function postChatStreamSSE(payload) {\n // Returns the raw Response so caller can stream\n return fetch('/api/chatStreamSSE', {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(payload)\n });\n}\n\nexport async function postChatStream(payload) {\n const res = await fetch('/api/chatStream', {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(payload)\n });\n return res;\n}\n\nexport async function postGroqChat({ apiKey, body }) {\n const res = await fetch('https://api.groq.com/openai/v1/chat/completions', {\n method: 'POST',\n headers: { 'Content-Type': 'application/json', 'Authorization': 'Bearer ' + apiKey },\n body: JSON.stringify(body)\n });\n return res;\n}\n\n\n",[],[226,353],"7e5eb5c8-7f9c-11f0-ad38-0224a6c84d84","streaming.js","8ff7d352-78f1-11f0-89f1-0224a6c84d84","8fcad140-78f1-11f0-831a-0224a6c84d84",59,["D",1755897055999],"// Experimental streaming-related helpers extracted from researchApp\n\nexport function isStreamingForCurrent(state) {\n const cid = state.currentChatId; if (!cid) return false;\n return !!(state.streamingChats && state.streamingChats[cid]);\n}\n\nexport function registerStream(state, chatId, token) {\n state.currentStreamToken = token;\n state.streamChatId = chatId;\n state.streamingChats[chatId] = { token, startedAt: Date.now() };\n}\n\nexport function unregisterStream(state, chatId, token) {\n const active = state.streamingChats[chatId];\n if (active && active.token === token) delete state.streamingChats[chatId];\n}\n\nimport { postChatStreamSSE, postChatStream, postGroqChat } from '../apiClient.js';\nimport { persistMessageAtIndex as corePersistMessageAtIndex } from '../core/chatCore.js';\n\n// Main streaming routine extracted from researchApp\nexport async function streamAssistant(state) {\n const thisChatId = state.currentChatId; if (!thisChatId) return;\n if (state.streamingChats[thisChatId]) return;\n if (state.selectedModel === 'custom') {\n const url = (state.customChatBaseUrl || '').trim();\n if (!url) { state.errorMessage = 'please set custom endpoint url'; return; }\n }\n const token = String(Date.now()) + '-' + Math.random();\n registerStream(state, thisChatId, token);\n const assistantCreatedAt = Date.now();\n const assistantIndex = state.messages.push({ role: 'assistant', content: '', createdAt: assistantCreatedAt, chatId: thisChatId }) - 1;\n try {\n const id = await corePersistMessageAtIndex(state, assistantIndex);\n if (id) state.messages[assistantIndex].id = id;\n } catch (_) {}\n const assistantMessageId = state.messages?.[assistantIndex]?.id || null;\n let fullAssistantContent = '';\n let fullReasoningContent = '';\n if (assistantMessageId != null) {\n state.messageReasoningMap[assistantMessageId] = state.messageReasoningMap[assistantMessageId] || '';\n state.expandedReasoningMap[assistantMessageId] = state.expandedReasoningMap[assistantMessageId] || false;\n }\n try {\n const payload = {\n userApiKey: state.userApiKey,\n model: state.selectedModel,\n messages: (() => {\n const chatMessages = state.messages.map(m => ({ role: m.role, content: m.content }));\n const sp = (state.systemPrompt || '').trim();\n return sp ? [{ role: 'system', content: sp }, ...chatMessages] : chatMessages;\n })(),\n tools: (() => {\n const list = [];\n const isOss = !!(state.selectedModel && state.selectedModel.startsWith('openai/gpt-oss'));\n if (isOss) {\n if (state.useBrowserSearch) list.push({ type: 'browser_search' });\n if (state.useCodeInterpreter) list.push({ type: 'code_interpreter' });\n }\n return list;\n })(),\n stream: state.streamEnabled,\n temperature: state.temperature,\n ...(state.maxTokens ? { max_tokens: state.maxTokens } : {}),\n reasoning_effort: state.reasoningEffort,\n ...(state.jsonMode ? { response_format: { type: 'json_object' } } : {}),\n ...((state.selectedModel === 'custom' && state.customChatBaseUrl) ? { base_url: state.customChatBaseUrl } : {})\n };\n const response = await postChatStreamSSE(payload);\n if (!response.ok || !response.body) {\n let txt = ''; try { txt = await response.text(); } catch (_) {}\n throw new Error(txt || response.statusText);\n }\n const reader = response.body.getReader();\n const decoder = new TextDecoder();\n let buffer = '';\n while (true) {\n const { done, value } = await reader.read(); if (done) break;\n const active = state.streamingChats[thisChatId];\n if (!active || active.token !== token) { break; }\n buffer += decoder.decode(value, { stream: true });\n const chunks = buffer.split('\\n\\n'); buffer = chunks.pop() || '';\n for (const chunk of chunks) {\n if (!chunk.trim()) continue;\n const lines = chunk.split('\\n'); let currentEvent = 'message';\n for (const line of lines) {\n if (line.startsWith('event: ')) { currentEvent = line.slice(7).trim(); continue; }\n if (!line.startsWith('data: ')) continue;\n const data = line.slice(6);\n if (data === '[DONE]') continue;\n let parsed = null; try { parsed = JSON.parse(data); } catch (_) { parsed = null; }\n if (!parsed) continue;\n if (currentEvent === 'results') continue;\n const stillActive = state.streamingChats[thisChatId];\n if (!stillActive || stillActive.token !== token) { break; }\n const choice = Array.isArray(parsed.choices) ? parsed.choices[0] : null;\n const delta = choice && choice.delta ? choice.delta : {};\n if (delta.content) {\n fullAssistantContent += delta.content;\n if (assistantMessageId && state.db) {\n try {\n await state.db.messages.put({ id: assistantMessageId, chatId: thisChatId, createdAt: assistantCreatedAt, role: 'assistant', content: fullAssistantContent, reasoning: fullReasoningContent });\n } catch (_) {}\n }\n if (state.currentChatId === thisChatId) {\n const idx = (state.messages || []).findIndex(m => m && m.id === assistantMessageId);\n if (idx >= 0) state.messages[idx].content = fullAssistantContent;\n }\n }\n if (delta.reasoning) {\n const addition = String(delta.reasoning || '');\n fullReasoningContent += addition;\n if (assistantMessageId && state.db) {\n try {\n await state.db.messages.put({ id: assistantMessageId, chatId: thisChatId, createdAt: assistantCreatedAt, role: 'assistant', content: fullAssistantContent, reasoning: fullReasoningContent });\n } catch (_) {}\n }\n if (state.currentChatId === thisChatId && assistantMessageId != null) {\n const prev = state.messageReasoningMap[assistantMessageId] || '';\n state.messageReasoningMap[assistantMessageId] = prev + addition;\n state.queueScrollReasoningById && state.queueScrollReasoningById(assistantMessageId);\n }\n }\n const appendToolEvent = async (prefix, t) => {\n try {\n const name = t?.name || t?.tool || t?.function?.name || 'tool';\n const args = t?.arguments ?? t?.input ?? t?.params ?? null;\n const output = t?.output ?? t?.result ?? t?.content ?? null;\n const argsStr = args ? (typeof args === 'string' ? args : JSON.stringify(args)) : '';\n const outStr = output ? (typeof output === 'string' ? output : JSON.stringify(output)) : '';\n const maxLen = 400;\n const trimmedArgs = argsStr.length > maxLen ? (argsStr.slice(0, maxLen) + '…') : argsStr;\n const trimmedOut = outStr.length > maxLen ? (outStr.slice(0, maxLen) + '…') : outStr;\n const line = `[${prefix}] ${name}` + (trimmedArgs ? ` args: ${trimmedArgs}` : '') + (trimmedOut ? `\\n→ ${trimmedOut}` : '') + '\\n';\n fullReasoningContent += line;\n if (assistantMessageId && state.db) {\n try {\n await state.db.messages.put({ id: assistantMessageId, chatId: thisChatId, createdAt: assistantCreatedAt, role: 'assistant', content: fullAssistantContent, reasoning: fullReasoningContent });\n } catch (_) {}\n }\n if (state.currentChatId === thisChatId && assistantMessageId != null) {\n const prev = state.messageReasoningMap[assistantMessageId] || '';\n state.messageReasoningMap[assistantMessageId] = prev + line;\n state.queueScrollReasoningById && state.queueScrollReasoningById(assistantMessageId);\n }\n } catch (_) { /* ignore */ }\n };\n if (Array.isArray(delta.executed_tools)) { for (const t of delta.executed_tools) appendToolEvent('executed', t); }\n if (Array.isArray(delta.tool_calls)) { for (const t of delta.tool_calls) appendToolEvent('call', t); }\n }\n }\n }\n } catch (e) {\n state.errorMessage = e.message || String(e);\n } finally {\n unregisterStream(state, thisChatId, token);\n const stillActive = state.streamingChats[thisChatId];\n if (stillActive && stillActive.token !== token) return;\n try {\n const finalContent = String(fullAssistantContent || '').trim();\n const finalReasoning = String(fullReasoningContent || '');\n if (!finalContent) {\n state.errorMessage = state.errorMessage || 'no response from model';\n if (assistantMessageId && state.db) { try { await state.db.messages.delete(assistantMessageId); } catch (_) {} }\n try { const idx = (state.messages || []).findIndex(m => m && m.id === assistantMessageId); if (idx >= 0) state.messages.splice(idx, 1); } catch (_) {}\n return;\n }\n if (state.db && assistantMessageId) {\n await state.db.messages.update(assistantMessageId, { content: finalContent, reasoning: finalReasoning });\n }\n if (state.currentChatId === thisChatId) {\n const idx = (state.messages || []).findIndex(m => m && m.id === assistantMessageId);\n if (idx >= 0) {\n state.messages[idx].content = finalContent;\n const prev = state.messageReasoningMap[idx] || '';\n if (!prev || finalReasoning.length > prev.length) state.messageReasoningMap[assistantMessageId] = finalReasoning;\n }\n }\n } catch (_) {}\n try {\n const chatMeta = thisChatId ? await state.db.chats.get(thisChatId) : null;\n const hasDefault = !chatMeta?.title || /^new chat$/i.test(chatMeta.title);\n if (hasDefault) {\n const apiKey = state.userApiKey || null;\n const titlePrompt = (state.messages || []).slice(0, 8).map((m) => `${m.role}: ${m.content}`).join('\\n').slice(0, 1000);\n if (apiKey && titlePrompt.trim()) {\n let generated = '';\n try {\n const res = await postChatStream({\n userApiKey: apiKey,\n model: 'llama-3.1-8b-instant',\n stream: false,\n ...((state.selectedModel === 'custom' && state.customChatBaseUrl) ? { base_url: state.customChatBaseUrl } : {}),\n messages: [\n { role: 'system', content: 'Return ONLY a chat title of 2-3 words. No punctuation, no quotes, no emojis.' },\n { role: 'user', content: titlePrompt }\n ]\n });\n if (res.ok) {\n const data = await res.json();\n generated = (data?.collapsed?.content || '').trim();\n }\n } catch (_) { /* fall back to direct */ }\n if (!generated) {\n try {\n const res2 = await postGroqChat({\n apiKey,\n body: {\n model: 'llama-3.1-8b-instant',\n stream: false,\n messages: [\n { role: 'system', content: 'Return ONLY a chat title of 2-3 words. No punctuation, no quotes, no emojis.' },\n { role: 'user', content: titlePrompt }\n ]\n }\n });\n if (res2.ok) {\n const json2 = await res2.json();\n generated = (json2?.choices?.[0]?.message?.content || '').trim();\n }\n } catch (_) { /* ignore */ }\n }\n if (generated) {\n const cleaned = generated.replace(/^[\"'\\s]+|[\"'\\s]+$/g, '').split(/\\s+/).slice(0, 3).join(' ') || 'New chat';\n const id = thisChatId;\n const prev = id ? await state.db.chats.get(id) : null;\n if (id) {\n const defaultNewSlug = (typeof state.slugifyTitle === 'function') ? state.slugifyTitle('New chat') : 'new-chat';\n const prevSlug = prev?.slug ? String(prev.slug) : '';\n const computedSlug = (typeof state.slugifyTitle === 'function') ? state.slugifyTitle(cleaned) : cleaned.toLowerCase().replace(/[^a-z0-9]+/g, '-').replace(/^-+|-+$/g, '').replace(/-{2,}/g, '-');\n const slug = (!prevSlug || prevSlug === defaultNewSlug) ? computedSlug : prevSlug;\n await state.db.chats.put({ id, title: cleaned, slug, createdAt: prev?.createdAt || Date.now() });\n await (state.loadChats ? state.loadChats() : Promise.resolve());\n state.activeSearchId = id;\n try { state.navigateToChatPath && state.navigateToChatPath(id, true); } catch (_) { /* ignore */ }\n }\n }\n }\n }\n } catch (_) {}\n state.scrollToBottom && state.scrollToBottom();\n }\n}\n\n\n",[],[226,369,361],"experimental","8fcad05a-78f1-11f0-831a-0224a6c84d84",42,["D",1755163934328],[268],[226,369],"7e63236a-7f9c-11f0-8e72-0224a6c84d84","chatCore.js","8feeae30-78f1-11f0-aafe-0224a6c84d84","8fdb7fc2-78f1-11f0-bbe7-0224a6c84d84",60,["D",1755897056030],"// Core chat + DB helpers extracted from researchApp\n\nexport async function initDb(state) {\n try {\n state.db = new window.Dexie('chat_db');\n state.db.version(1).stores({ chats: '++id,title,createdAt' });\n state.db.version(2).stores({ chats: '++id,title,createdAt', messages: '++id,chatId,createdAt,role,content' });\n state.db.version(3).stores({ chats: '++id,title,createdAt,folderId', messages: '++id,chatId,createdAt,role,content', folders: '++id,name,createdAt,order,collapsed' });\n // v4: add stable slug support to chats\n state.db.version(4).stores({ chats: '++id,title,slug,createdAt,folderId', messages: '++id,chatId,createdAt,role,content', folders: '++id,name,createdAt,order,collapsed' });\n } catch (e) {\n console.error('Dexie init error', e);\n }\n}\n\nexport async function loadChats(state) {\n try {\n const rows = await state.db.chats.orderBy('createdAt').reverse().toArray();\n state.chats = rows.map(r => ({ id: r.id, title: r.title, slug: r.slug || null, createdAt: r.createdAt, folderId: r.folderId || null }));\n } catch (_) { state.chats = []; }\n}\n\nexport async function loadFolders(state) {\n try {\n const rows = await state.db.folders.orderBy('order').toArray();\n state.folders = rows.map(r => ({ id: r.id, name: r.name || 'folder', createdAt: r.createdAt || Date.now(), order: r.order ?? r.id, collapsed: !!r.collapsed }));\n } catch (_) { state.folders = []; }\n}\n\nexport async function createFolder(state) {\n try {\n const createdAt = Date.now();\n const name = 'folder';\n const order = (state.folders[state.folders.length - 1]?.order || 0) + 1;\n const id = await state.db.folders.add({ name, createdAt, order, collapsed: false });\n await loadFolders(state);\n // Immediately enter rename mode\n startEditingFolder(state, id, name);\n } catch (_) { /* ignore */ }\n}\n\nexport function startEditingFolder(state, id, currentName) {\n state.editingFolderId = id;\n state.editingFolderName = currentName || '';\n setTimeout(() => {\n try {\n const el = document.querySelector('input[data-folder-id=\"' + id + '\"]');\n if (el) { el.focus(); el.select(); }\n } catch (_) {}\n }, 30);\n}\n\nexport async function commitEditingFolder(state) {\n const rawId = state.editingFolderId;\n const id = typeof rawId === 'string' ? Number(rawId) : rawId;\n if (!id) return cancelEditingFolder(state);\n const name = (state.editingFolderName || '').trim() || 'folder';\n try {\n const prev = await state.db.folders.get(id);\n await state.db.folders.put({ id, name, createdAt: prev?.createdAt || Date.now(), order: prev?.order ?? id, collapsed: !!prev?.collapsed });\n await loadFolders(state);\n } catch (_) { /* ignore */ }\n state.editingFolderId = null;\n state.editingFolderName = '';\n}\n\nexport function cancelEditingFolder(state) {\n state.editingFolderId = null;\n state.editingFolderName = '';\n}\n\nexport async function toggleFolderCollapsed(state, id) {\n try {\n const f = await state.db.folders.get(id);\n if (!f) return;\n await state.db.folders.put({ ...f, collapsed: !f.collapsed });\n await loadFolders(state);\n } catch (_) { /* ignore */ }\n}\n\nexport async function moveChatToFolder(state, chatId, folderId) {\n try {\n if (!chatId) return;\n const prev = await state.db.chats.get(chatId);\n if (!prev) return;\n await state.db.chats.put({ id: chatId, title: prev.title, slug: prev.slug || null, createdAt: prev.createdAt, folderId: folderId ?? null });\n await loadChats(state);\n } catch (_) { /* ignore */ }\n}\n\nexport function baseChats(state) {\n try {\n const list = (state.chats || []).filter(c => !c.folderId);\n return [{ id: state.ephemeralChatId, title: 'New chat', createdAt: 0, folderId: null, isEphemeral: true }, ...list];\n } catch (_) { return state.chats || []; }\n}\n\nexport function chatsInFolder(state, folderId) {\n try { return (state.chats || []).filter(c => c.folderId === folderId); } catch (_) { return []; }\n}\n\nexport async function createNewChat(state) {\n const base = (state.chatInput && state.chatInput.trim()) || 'New chat';\n const title = base.substring(0, 60);\n const slug = slugifyTitle(title);\n const createdAt = Date.now();\n const id = await state.db.chats.add({ title, slug, createdAt, folderId: null });\n await loadChats(state);\n await selectChat(state, id);\n}\n\nexport async function selectChat(state, id) {\n if (id === state.ephemeralChatId) {\n state.currentChatId = null;\n state.activeSearchId = state.ephemeralChatId;\n state.messages = [{ role: 'assistant', content: 'Hi! How can I help you today?', createdAt: Date.now() }];\n state.sidebarOpen = false;\n state.$nextTick && state.$nextTick(() => state.scrollToBottom && state.scrollToBottom());\n return;\n }\n state.currentChatId = id;\n state.activeSearchId = id;\n try {\n const rows = await state.db.messages.where('chatId').equals(id).sortBy('createdAt');\n state.messages = rows.map(r => ({ id: r.id, chatId: r.chatId, role: r.role, content: r.content, reasoning: r.reasoning, createdAt: r.createdAt }));\n for (const row of rows) {\n if (row.id != null && row.reasoning && !state.messageReasoningMap[row.id]) {\n state.messageReasoningMap[row.id] = row.reasoning;\n }\n }\n } catch (_) {\n state.messages = [];\n }\n if (!state.messages.length) {\n const createdAt = Date.now();\n const greeting = { role: 'assistant', content: 'Hi! How can I help you today?', createdAt };\n state.messages = [greeting];\n try {\n const chatId = await ensureChatExistsForEdits(state);\n if (chatId && state.db) {\n const newId = await state.db.messages.add({ chatId, createdAt, role: 'assistant', content: greeting.content, reasoning: '' });\n state.messages[0].id = newId;\n state.messages[0].chatId = chatId;\n }\n } catch (_) { /* ignore */ }\n }\n state.sidebarOpen = false;\n state.$nextTick && state.$nextTick(() => state.scrollToBottom && state.scrollToBottom());\n}\n\nexport function startEditingChat(state, id, currentTitle) {\n state.editingChatId = id;\n state.editingChatTitle = currentTitle || '';\n try {\n setTimeout(() => {\n const el = document.querySelector('input[data-chat-id=\"' + id + '\"]');\n if (el) { el.focus(); el.select(); }\n }, 50);\n } catch (_) {}\n}\n\nexport async function commitEditingChat(state) {\n const rawId = state.editingChatId;\n const id = typeof rawId === 'string' ? Number(rawId) : rawId;\n if (!id) return cancelEditingChat(state);\n const title = (state.editingChatTitle || '').trim() || 'New chat';\n try {\n if (state.db) {\n const prev = await state.db.chats.get(id);\n const slug = prev?.slug || slugifyTitle(title);\n await state.db.chats.put({ id, title, slug, createdAt: prev?.createdAt || Date.now() });\n }\n await loadChats(state);\n state.activeSearchId = id;\n } catch (_) { /* no-op */ }\n state.editingChatId = null;\n state.editingChatTitle = '';\n}\n\nexport function cancelEditingChat(state) {\n state.editingChatId = null;\n state.editingChatTitle = '';\n}\n\nexport async function deleteChat(state, id) {\n try {\n if (!state.db) return;\n const chatId = typeof id === 'string' ? Number(id) : id;\n try { await state.db.messages.where('chatId').equals(chatId).delete(); } catch (_) {\n try { await state.db.messages.filter(m => m.chatId === chatId).delete(); } catch (_) { /* ignore */ }\n }\n try { await state.db.chats.delete(chatId); } catch (_) { /* ignore */ }\n await loadChats(state);\n if (state.currentChatId === chatId) {\n const next = state.chats[0]?.id;\n if (next) {\n await selectChat(state, next);\n } else {\n await createNewChat(state);\n }\n }\n } catch (_) { /* ignore */ }\n}\n\nexport async function duplicateChat(state, id) {\n try {\n if (!state || !state.db) return;\n const chatId = typeof id === 'string' ? Number(id) : id;\n if (!Number.isFinite(chatId)) return;\n const orig = await state.db.chats.get(chatId);\n if (!orig) return;\n const title = String(orig.title || 'New chat') + ' (copy)';\n const createdAt = Date.now();\n const folderId = orig.folderId ?? null;\n const slug = (orig.slug && String(orig.slug)) || slugifyTitle(title);\n const newChatId = await state.db.chats.add({ title, slug, createdAt, folderId });\n try {\n const msgs = await state.db.messages.where('chatId').equals(chatId).sortBy('createdAt');\n if (Array.isArray(msgs) && msgs.length) {\n const rows = msgs.map(m => ({ chatId: newChatId, createdAt: m.createdAt, role: m.role, content: m.content, reasoning: m.reasoning || '' }));\n try { await state.db.messages.bulkAdd(rows); } catch (_) {\n for (const row of rows) { try { await state.db.messages.add(row); } catch (_) { /* ignore single add */ } }\n }\n }\n } catch (_) { /* ignore */ }\n await loadChats(state);\n } catch (_) { /* ignore */ }\n}\n\nexport async function ensureChatExistsForEdits(state) {\n try {\n if (state.currentChatId && state.db) return state.currentChatId;\n if (!state.db) return null;\n const base = (state.chatInput && state.chatInput.trim()) || 'New chat';\n const title = base.substring(0, 60);\n const slug = slugifyTitle(title);\n const createdAt = Date.now();\n const id = await state.db.chats.add({ title, slug, createdAt });\n await loadChats(state);\n state.currentChatId = id;\n state.activeSearchId = id;\n return id;\n } catch (_) { return null; }\n}\n\nexport async function ensureMessagePersisted(state, idx) {\n try {\n const m = state.messages?.[idx];\n if (!m) return null;\n if (m.id && state.db) return m.id;\n const chatId = await ensureChatExistsForEdits(state);\n if (!chatId || !state.db) return null;\n const createdAt = m.createdAt || Date.now();\n const role = m.role || 'assistant';\n const content = String(m.content || '');\n const reasoning = String(m.reasoning || '');\n const newId = await state.db.messages.add({ chatId, createdAt, role, content, reasoning });\n state.messages[idx].id = newId;\n state.messages[idx].chatId = chatId;\n state.messages[idx].createdAt = createdAt;\n return newId;\n } catch (_) { return null; }\n}\n\nexport async function persistMessageAtIndex(state, idx) {\n try {\n const m = state.messages?.[idx];\n if (!m || !state.db) return null;\n let chatId = state.currentChatId;\n if (!chatId) chatId = await ensureChatExistsForEdits(state);\n if (!chatId) return null;\n const createdAt = m.createdAt || Date.now();\n const role = m.role || 'assistant';\n const content = String(m.content || '');\n const reasoning = String(m.reasoning || '');\n const row = { id: m.id, chatId, createdAt, role, content, reasoning };\n const newId = await state.db.messages.put(row);\n if (!m.id) { state.messages[idx].id = newId; }\n state.messages[idx].chatId = chatId;\n state.messages[idx].createdAt = createdAt;\n return newId || m.id || null;\n } catch (_) { return null; }\n}\n\nexport async function deleteMessage(state, idx) {\n try {\n if (!Array.isArray(state.messages) || idx == null || idx < 0 || idx >= state.messages.length) return;\n const msg = state.messages[idx];\n const messageId = msg && msg.id != null ? msg.id : null;\n try {\n if (state.db && messageId != null) {\n await state.db.messages.delete(messageId);\n }\n } catch (_) { /* ignore */ }\n try {\n if (messageId != null) {\n if (state.messageReasoningMap && state.messageReasoningMap[messageId] != null) delete state.messageReasoningMap[messageId];\n if (state.expandedReasoningMap && state.expandedReasoningMap[messageId] != null) delete state.expandedReasoningMap[messageId];\n }\n } catch (_) { /* ignore */ }\n try {\n state.messages.splice(idx, 1);\n if (state.copiedMap && state.copiedMap[idx]) delete state.copiedMap[idx];\n } catch (_) { /* ignore */ }\n if (state.editingMessageIdx === idx) {\n state.editingMessageIdx = null;\n state.editingMessageId = null;\n state.editingMessageText = '';\n state.editingMessageOriginal = '';\n } else if (typeof state.editingMessageIdx === 'number' && state.editingMessageIdx > idx) {\n state.editingMessageIdx = state.editingMessageIdx - 1;\n }\n } catch (_) { /* ignore */ }\n}\n\nexport async function deleteMessagesBelow(state, idx) {\n try {\n if (!Array.isArray(state.messages) || idx == null || idx < 0 || idx >= state.messages.length) return;\n const thisChatId = state.currentChatId;\n const toRemove = (state.messages || []).slice(idx + 1);\n try {\n if (state.db) {\n for (const msg of toRemove) {\n const messageId = msg && msg.id != null ? msg.id : null;\n if (messageId != null) {\n try { await state.db.messages.delete(messageId); } catch (_) { /* ignore */ }\n }\n if (messageId != null) {\n if (state.messageReasoningMap && state.messageReasoningMap[messageId] != null) delete state.messageReasoningMap[messageId];\n if (state.expandedReasoningMap && state.expandedReasoningMap[messageId] != null) delete state.expandedReasoningMap[messageId];\n }\n }\n }\n } catch (_) { /* ignore */ }\n try {\n state.messages = (state.messages || []).slice(0, idx + 1);\n if (state.copiedMap) {\n try {\n const keys = Object.keys(state.copiedMap);\n for (const k of keys) {\n const i = Number(k);\n if (Number.isFinite(i) && i > idx) delete state.copiedMap[i];\n }\n } catch (_) { /* ignore */ }\n }\n } catch (_) { /* ignore */ }\n if (typeof state.editingMessageIdx === 'number' && state.editingMessageIdx > idx) {\n state.editingMessageIdx = null;\n state.editingMessageId = null;\n state.editingMessageText = '';\n state.editingMessageOriginal = '';\n }\n try {\n if (state.streamingChats && thisChatId && state.streamingChats[thisChatId]) {\n delete state.streamingChats[thisChatId];\n }\n } catch (_) { /* ignore */ }\n state.scrollToBottom && state.scrollToBottom();\n } catch (_) { /* ignore */ }\n}\n\nexport async function rerunFromUser(state, idx) {\n try {\n if (state.isStreamingForCurrent) return;\n if (!Array.isArray(state.messages) || idx == null || idx < 0 || idx >= state.messages.length) return;\n const m = state.messages[idx];\n if (!m || m.role !== 'user') return;\n const text = String(m.content || '').trim();\n if (!text) return;\n try {\n const toRemove = (state.messages || []).slice(idx + 1);\n if (state.db) {\n for (const msg of toRemove) {\n if (msg && msg.id != null) { try { await state.db.messages.delete(msg.id); } catch (_) { /* ignore */ } }\n }\n }\n } catch (_) { /* ignore */ }\n state.messages = (state.messages || []).slice(0, idx + 1);\n if (!state.currentChatId) {\n try {\n const base = text || 'New chat';\n const title = base.substring(0, 60);\n const slug = slugifyTitle(title);\n const createdAt = Date.now();\n const id = await state.db.chats.add({ title, slug, createdAt });\n await loadChats(state);\n state.currentChatId = id;\n state.activeSearchId = id;\n } catch (_) { /* ignore */ }\n }\n state.scrollToBottom && state.scrollToBottom();\n state.streamAssistant && state.streamAssistant();\n } catch (_) { /* ignore */ }\n}\n\nexport async function sendMessage(state) {\n const text = (state.chatInput || '').trim();\n if (!text) return;\n state.errorMessage = '';\n if (!state.hasServerKey && !state.userApiKey) {\n state.errorMessage = 'please add api key';\n return;\n }\n if (!state.currentChatId) {\n try {\n const base = (state.chatInput && state.chatInput.trim()) || 'New chat';\n const title = base.substring(0, 60);\n const slug = slugifyTitle(title);\n const createdAt = Date.now();\n const id = await state.db.chats.add({ title, slug, createdAt });\n await loadChats(state);\n state.currentChatId = id;\n state.activeSearchId = id;\n } catch (_) { /* ignore */ }\n }\n const createdAt = Date.now();\n const userIndex = state.messages.push({ role: 'user', content: text, createdAt, chatId: state.currentChatId }) - 1;\n try {\n if (state.currentChatId && state.db) {\n const newId = await state.db.messages.add({ chatId: state.currentChatId, createdAt, role: 'user', content: text });\n state.messages[userIndex].id = newId;\n }\n } catch (_) {}\n state.chatInput = '';\n try { const ta = document.querySelector('textarea'); if (ta) { ta.style.height = 'auto'; ta.rows = 1; } } catch (_) {}\n state.scrollToBottom && state.scrollToBottom();\n state.streamAssistant && state.streamAssistant();\n}\n\nfunction slugifyTitle(title) {\n try {\n const s = String(title || '').toLowerCase();\n let out = s.replace(/[^a-z0-9]+/g, '-').replace(/^-+|-+$/g, '').replace(/-{2,}/g, '-');\n if (out.length > 60) out = out.slice(0, 60).replace(/-+$/g, '');\n return out;\n } catch (_) { return ''; }\n}\n\n\n// --- Data export/import helpers ---\n\nexport async function exportAllData(state) {\n try {\n if (!state || !state.db) {\n return { meta: { type: 'chatter-export', schemaVersion: 0, exportedAt: Date.now() }, data: { chats: [], messages: [], folders: [] } };\n }\n const [chats, messages, folders] = await Promise.all([\n state.db.chats.toArray().catch(() => []),\n state.db.messages.toArray().catch(() => []),\n state.db.folders.toArray().catch(() => []),\n ]);\n return {\n meta: {\n type: 'chatter-export',\n schemaVersion: Number(state.db.verno || 0),\n exportedAt: Date.now(),\n },\n data: { chats, messages, folders },\n };\n } catch (_) {\n return { meta: { type: 'chatter-export', schemaVersion: 0, exportedAt: Date.now() }, data: { chats: [], messages: [], folders: [] } };\n }\n}\n\nexport async function importDataReplace(state, input) {\n const parsed = (() => {\n try {\n if (!input) return {};\n if (typeof input === 'string') return JSON.parse(input);\n return input;\n } catch (_) { return {}; }\n })();\n const data = parsed && parsed.data ? parsed.data : parsed;\n const folders = Array.isArray(data?.folders) ? data.folders : [];\n const chats = Array.isArray(data?.chats) ? data.chats : [];\n const messages = Array.isArray(data?.messages) ? data.messages : [];\n let counts = { foldersAdded: 0, chatsAdded: 0, messagesAdded: 0 };\n try {\n if (!state || !state.db) return counts;\n await state.db.transaction('rw', state.db.folders, state.db.chats, state.db.messages, async () => {\n await state.db.messages.clear();\n await state.db.chats.clear();\n await state.db.folders.clear();\n if (folders.length) {\n try { await state.db.folders.bulkAdd(folders); counts.foldersAdded = folders.length; } catch (_) {\n for (const f of folders) { try { await state.db.folders.add(f); counts.foldersAdded += 1; } catch (_) {} }\n }\n }\n if (chats.length) {\n try { await state.db.chats.bulkAdd(chats); counts.chatsAdded = chats.length; } catch (_) {\n for (const c of chats) { try { await state.db.chats.add(c); counts.chatsAdded += 1; } catch (_) {} }\n }\n }\n if (messages.length) {\n try { await state.db.messages.bulkAdd(messages); counts.messagesAdded = messages.length; } catch (_) {\n for (const m of messages) { try { await state.db.messages.add(m); counts.messagesAdded += 1; } catch (_) {} }\n }\n }\n });\n } catch (_) { /* ignore */ }\n return counts;\n}\n\nexport async function importDataAppend(state, input) {\n const parsed = (() => {\n try {\n if (!input) return {};\n if (typeof input === 'string') return JSON.parse(input);\n return input;\n } catch (_) { return {}; }\n })();\n const data = parsed && parsed.data ? parsed.data : parsed;\n const folders = Array.isArray(data?.folders) ? data.folders : [];\n const chats = Array.isArray(data?.chats) ? data.chats : [];\n const messages = Array.isArray(data?.messages) ? data.messages : [];\n let counts = { foldersAdded: 0, chatsAdded: 0, messagesAdded: 0 };\n const folderIdMap = {};\n const chatIdMap = {};\n try {\n if (!state || !state.db) return counts;\n await state.db.transaction('rw', state.db.folders, state.db.chats, state.db.messages, async () => {\n // Append folders, remapping IDs\n for (const f of folders) {\n try {\n const row = {\n name: f?.name || 'folder',\n createdAt: Number(f?.createdAt) || Date.now(),\n order: (typeof f?.order === 'number') ? f.order : undefined,\n collapsed: !!f?.collapsed,\n };\n const newId = await state.db.folders.add(row);\n if (f && f.id != null) folderIdMap[String(f.id)] = newId;\n counts.foldersAdded += 1;\n } catch (_) { /* ignore single add */ }\n }\n // Append chats, remapping folderId\n for (const c of chats) {\n try {\n const title = (c?.title && String(c.title)) || 'New chat';\n const slug = (c?.slug && String(c.slug)) || slugifyTitle(title);\n const oldFolderId = (c && c.folderId != null) ? String(c.folderId) : null;\n const newFolderId = oldFolderId != null ? (folderIdMap[oldFolderId] ?? null) : null;\n const row = {\n title,\n slug,\n createdAt: Number(c?.createdAt) || Date.now(),\n folderId: newFolderId ?? null,\n };\n const newId = await state.db.chats.add(row);\n if (c && c.id != null) chatIdMap[String(c.id)] = newId;\n counts.chatsAdded += 1;\n } catch (_) { /* ignore */ }\n }\n // Append messages, remapping chatId\n for (const m of messages) {\n try {\n const oldChatId = m && m.chatId != null ? String(m.chatId) : null;\n if (oldChatId == null) continue;\n const newChatId = chatIdMap[oldChatId];\n if (!newChatId) continue;\n const row = {\n chatId: newChatId,\n createdAt: Number(m?.createdAt) || Date.now(),\n role: m?.role || 'assistant',\n content: String(m?.content || ''),\n reasoning: String(m?.reasoning || ''),\n };\n await state.db.messages.add(row);\n counts.messagesAdded += 1;\n } catch (_) { /* ignore */ }\n }\n });\n } catch (_) { /* ignore */ }\n return counts;\n}\n\n\n",[],[226,384,376],"core","8fdb7f04-78f1-11f0-bbe7-0224a6c84d84",43,["D",1755163934439],[266],[226,384],["D",1754850144183],[265,267,269,270,271,272,273],[226],"f6c114b4-7616-11f0-a8a8-0224a6c84d84","f6c11568-7616-11f0-a8a8-0224a6c84d84",11,["D",1754850144822],"\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

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0 || isStreaming\">\n

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

\n \n

\n \n \n

\n \n

\n\n \n

\n \n \n \n github\n

\n \n\n",[],[232,176],["D",1754850144279],[263],[232],"03ff8ede-7758-11f0-82e2-0224a6c84d84","utils.js","03ff8fc4-7758-11f0-82e2-0224a6c84d84",24,["D",1754988035595],"// Environment-aware file utilities for serving project assets\nimport { readFile as vtReadFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n\nexport async function readFileContent(filePath, importMetaUrl) {\n if (typeof Deno !== \"undefined\" && Deno.env?.get && Deno.env.get(\"valtown\")) {\n return await vtReadFile(filePath, importMetaUrl);\n }\n return await Deno.readTextFile(filePath);\n}\n\nexport function textResponse(text, contentType = \"text/plain; charset=utf-8\") {\n return new Response(text, { headers: { \"Content-Type\": contentType } });\n}\n\n\n",[],[237,404],"7e67ef44-7f9c-11f0-94b5-0224a6c84d84",["D",1755897056034],[],[237,34],"045dcbe8-7758-11f0-8c27-0224a6c84d84","config.js","045dccce-7758-11f0-8c27-0224a6c84d84",35,["D",1754988035604],"// Centralized app configuration\nimport \"jsr:@std/dotenv/load\";\n\nexport const settings = {\n model: \"openai/gpt-oss-120b\",\n stream: false,\n reasoningEffort: \"low\",\n};\n\n// Prefer server-side key via env if present\nexport const serverApiKey = (typeof Deno !== \"undefined\" && Deno.env?.get)\n ? (Deno.env.get(\"GROQ_API_KEY\") || null)\n : null;\n\n\n",[],[237,416],"040d7a6c-7758-11f0-81b1-0224a6c84d84","system.js","040d7c74-7758-11f0-81b1-0224a6c84d84","03e5ad66-7758-11f0-a4e6-0224a6c84d84",26,["D",1754988035724],"// System/health endpoints\nimport { serverApiKey } from \"../config.js\";\n\nexport function registerSystemRoutes(app) {\n app.get('/api/check-key', (c) => {\n return c.json({ hasServerKey: !!serverApiKey });\n });\n}\n\n\n",[],[237,432,424],"routes","8fffa97e-78f1-11f0-aafe-0224a6c84d84","static.js","04247c80-7758-11f0-a6db-0224a6c84d84",49,["D",1755163934663],"// Static file routes (no static middleware)\nimport { readFileContent, textResponse } from \"../utils.js\";\n\nexport function registerStaticRoutes(app, importMetaUrl) {\n // Root HTML\n app.get('/', async (c) => {\n try {\n const html = await readFileContent('index.html', importMetaUrl);\n return c.html(html);\n } catch (err) {\n console.error('Error reading index.html:', err);\n return c.text('Error loading page', 500);\n }\n });\n\n // Frontend modules\n app.get('/frontend/researchApp.js', async (c) => {\n try {\n const js = await readFileContent('frontend/researchApp.js', importMetaUrl);\n return textResponse(js, 'application/javascript; charset=utf-8');\n } catch (err) {\n console.error('Error reading researchApp.js:', err);\n return c.text('Not found', 404);\n }\n });\n\n app.get('/frontend/init.js', async (c) => {\n try {\n const js = await readFileContent('frontend/init.js', importMetaUrl);\n return textResponse(js, 'application/javascript; charset=utf-8');\n } catch (err) {\n console.error('Error reading init.js:', err);\n return c.text('Not found', 404);\n }\n });\n\n // Generic frontend file handler to serve other ESM modules\n app.get('/frontend/*', async (c) => {\n try {\n const path = c.req.path;\n if (!path.startsWith('/frontend/')) return c.text('Not found', 404);\n const rel = path.slice(1); // strip leading '/'\n const text = await readFileContent(rel, importMetaUrl);\n const contentType = rel.endsWith('.js') ? 'application/javascript; charset=utf-8' : 'text/plain; charset=utf-8';\n return textResponse(text, contentType);\n } catch (err) {\n console.error('Error reading frontend asset:', err);\n return c.text('Not found', 404);\n }\n });\n}\n\n\n",[],[237,432,434],"04178a98-7758-11f0-85fd-0224a6c84d84","search.js","04178b4c-7758-11f0-85fd-0224a6c84d84",28,["D",1754988035790],"// Search and URL summarization endpoint\nimport { performSearch, summarizeUrl } from \"../../chatCompletion.js\";\nimport { sanitizeResults, synthesizeResultsFromContext, synthesizeTextFromContext } from \"../../jsonUtils.js\";\nimport { serverApiKey, settings } from \"../config.js\";\n\nexport function registerSearchRoutes(app) {\n app.post('/api/search', async (c) => {\n try {\n const body = await c.req.json();\n const { query, dateRange, source, language, userApiKey, offset = 0, url, title } = body || {};\n\n const apiKey = serverApiKey || userApiKey;\n if (!apiKey) {\n return c.json({ error: 'No Groq API key available. Please provide your own key.' }, 400);\n }\n\n // If URL present, run summary; otherwise require query and run search\n if (url && typeof url === 'string' && url.trim()) {\n const { summary, summaryTime } = await summarizeUrl({\n apiKey,\n url,\n title,\n language,\n model: settings.model,\n stream: settings.stream,\n reasoningEffort: settings.reasoningEffort,\n });\n return c.json({ summary, summaryTime, url, title, language });\n }\n\n if (!query || !query.trim()) {\n return c.json({ error: 'No search query provided' }, 400);\n }\n\n const { results, searchTime, content: assistantContent, full: fullResponse, route } = await performSearch({\n apiKey,\n query,\n dateRange,\n source,\n language,\n offset,\n model: settings.model,\n stream: settings.stream,\n reasoningEffort: settings.reasoningEffort,\n forceLinksRoute: !!source,\n });\n\n try { console.log('>> [performSearch] fullResponse:', JSON.stringify(fullResponse)); } catch (_) {\n console.log('>> [performSearch] fullResponse: ');\n }\n try { console.log('>> [performSearch] assistantContent:', typeof assistantContent === 'string' ? assistantContent : JSON.stringify(assistantContent)); } catch (_) {\n console.log('>> [performSearch] assistantContent: ');\n }\n let outResults = sanitizeResults(results);\n let outAssistant = assistantContent;\n // Fallback synthesis: if route is links and results empty, synthesize from available context\n if ((route !== 'text') && (!outResults || outResults.length === 0)) {\n try {\n const synthesized = await synthesizeResultsFromContext({\n query,\n language,\n toolText: '',\n assistantText: String(assistantContent || ''),\n reasoningText: '',\n existingResults: outResults || []\n }, apiKey);\n if (Array.isArray(synthesized) && synthesized.length > 0) {\n outResults = sanitizeResults(synthesized);\n }\n } catch (_) { /* ignore */ }\n }\n // If router chose text but model returned nothing, synthesize concise text\n if (route === 'text' && (!outAssistant || !String(outAssistant).trim())) {\n try {\n const synthesizedText = await synthesizeTextFromContext({\n query,\n language,\n toolText: '',\n assistantText: '',\n reasoningText: ''\n }, apiKey);\n if (synthesizedText) outAssistant = synthesizedText;\n } catch (_) { /* ignore */ }\n }\n console.log('>> [performSearch] results (sanitized):', outResults);\n return c.json({\n results: outResults,\n searchTime,\n assistantContent: outAssistant,\n route,\n query,\n dateRange,\n source,\n language,\n offset,\n });\n } catch (error) {\n console.error('Server error:', error);\n return c.json({ error: 'Server error: ' + error.message }, 500);\n }\n });\n}\n\n\n",[],[237,432,442],"f1dc65b6-78e1-11f0-954a-0224a6c84d84","chatStreamSSE.js","04111032-7758-11f0-98a6-0224a6c84d84",39,["D",1755157226897],"// True SSE passthrough for chat completions (browser consumes incrementally)\nimport { buildSearchPrompt, routeQueryMode } from \"../../chatCompletion.js\";\nimport { extractOrRepairJsonResults, sanitizeResults, synthesizeResultsFromContext, extractResultsFromToolOutputs } from \"../../jsonUtils.js\";\nimport { serverApiKey } from \"../config.js\";\n\nfunction collectToolTextFromArray(toolArray) {\n if (!Array.isArray(toolArray)) return '';\n const parts = [];\n for (const t of toolArray) {\n try {\n const name = t?.name || t?.tool || t?.function?.name || t?.id || '';\n const args = t?.arguments || t?.input || t?.params || null;\n const output = t?.output || t?.result || t?.content || null;\n const searchResults = t?.search_results || t?.results || null;\n if (name) parts.push('name: ' + String(name));\n if (args) parts.push('arguments: ' + (typeof args === 'string' ? args : JSON.stringify(args)));\n if (output) parts.push('output: ' + (typeof output === 'string' ? output : JSON.stringify(output)));\n if (searchResults) parts.push('search_results: ' + (typeof searchResults === 'string' ? searchResults : JSON.stringify(searchResults)));\n } catch (_) { /* ignore */ }\n }\n return parts.join('\\n');\n}\n\nexport function registerChatStreamSSERoute(app) {\n app.post('/api/chatStreamSSE', async (c) => {\n try {\n let body = {};\n try { body = await c.req.json(); } catch (_) { body = {}; }\n\n const {\n userApiKey,\n messages,\n query,\n dateRange,\n source,\n language,\n offset = 0,\n model = 'openai/gpt-oss-120b',\n reasoning_effort = 'medium',\n tools = [],\n temperature,\n top_p,\n stop,\n max_tokens,\n response_format,\n stream: clientStream,\n base_url,\n } = body || {};\n\n const apiKey = serverApiKey || userApiKey || (typeof Deno !== 'undefined' ? Deno.env.get('GROQ_API_KEY') : null);\n if (!apiKey && !base_url) {\n return c.json({ error: 'No Groq API key available. Please provide your own key.' }, 400);\n }\n\n const isGptOss = typeof model === 'string' && model.startsWith('openai/gpt-oss');\n const supportsReasoning = isGptOss;\n const supportsTools = isGptOss;\n const wantsStreaming = (clientStream === false) ? false : true;\n\n let finalMessages = Array.isArray(messages) && messages.length > 0\n ? messages\n : (typeof query === 'string' && query.trim().length > 0\n ? [\n { role: 'system', 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. ALWAYS conduct searches in English; if the query is not in English, translate to English for search and present outputs in the requested language.' },\n { role: 'user', content: buildSearchPrompt(query, source, dateRange, language, offset) }\n ]\n : [{ role: 'user', content: 'go to https://news.ycombinator.com/ and give me the first 5 stories' }]);\n\n let selectedRoute = 'links';\n try {\n if (typeof query === 'string' && query.trim()) {\n const route = await routeQueryMode(apiKey, query);\n selectedRoute = source ? 'links' : (route || 'links');\n if (source) {\n finalMessages = [\n { role: 'system', 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. ALWAYS conduct searches in English; if the query is not in English, translate to English for search and present outputs in the requested language.' },\n { role: 'user', content: buildSearchPrompt(query, source, dateRange, language, offset) }\n ];\n } else if (selectedRoute === 'text') {\n finalMessages = [\n { role: 'system', 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 the requested language (no JSON). Do not use markdown fences.' },\n { role: 'user', content: query }\n ];\n }\n } else if (Array.isArray(finalMessages) && finalMessages.length > 0) {\n let lastUser = '';\n for (let i = finalMessages.length - 1; i >= 0; i--) {\n const m = finalMessages[i];\n if (m && m.role === 'user' && m.content && String(m.content).trim()) { lastUser = String(m.content); break; }\n }\n if (lastUser) {\n const route = await routeQueryMode(apiKey, lastUser);\n selectedRoute = source ? 'links' : (route || 'links');\n }\n }\n } catch (_) { /* ignore */ }\n\n if (supportsTools && Array.isArray(messages) && messages.length > 0 && Array.isArray(finalMessages) && Array.isArray(tools) && tools.length > 0) {\n const toolPreamble = {\n role: 'system',\n content: 'You have access to a web browsing tool named \"browser_search\". Use it for real-time information, for finding additional sources when the user says things like \"continue\" or \"find more\", and for verification. Prefer calling the tool rather than guessing. Answer concisely and include relevant markdown links.'\n };\n finalMessages = [toolPreamble, ...finalMessages];\n }\n\n const payload = {\n model,\n messages: finalMessages,\n stream: wantsStreaming,\n ...(supportsReasoning ? { reasoning_effort } : {}),\n ...(supportsTools && Array.isArray(tools) && tools.length > 0 ? { tools, tool_choice: 'auto' } : {}),\n ...(temperature !== undefined ? { temperature } : {}),\n ...(top_p !== undefined ? { top_p } : {}),\n ...(stop !== undefined ? { stop } : {}),\n ...(max_tokens !== undefined ? { max_tokens } : {}),\n ...(response_format ? { response_format } : {}),\n };\n\n const encoder = new TextEncoder();\n const baseUrl = (typeof base_url === 'string' && base_url.trim()) ? base_url.trim().replace(/\\/$/, '') : '';\n let endpoint = 'https://api.groq.com/openai/v1/chat/completions';\n if (baseUrl) {\n if (/(\\/v\\d+)?\\/(chat\\/)?completions$/i.test(baseUrl)) {\n endpoint = baseUrl;\n } else if (/\\/v\\d+$/i.test(baseUrl)) {\n endpoint = baseUrl + '/chat/completions';\n } else {\n endpoint = baseUrl + '/v1/chat/completions';\n }\n }\n const stream = new ReadableStream({\n start: async (controller) => {\n try {\n const headers = {\n 'Content-Type': 'application/json',\n ...(apiKey ? { 'Authorization': 'Bearer ' + apiKey } : {}),\n };\n const upstream = await fetch(endpoint, {\n method: 'POST',\n headers,\n body: JSON.stringify(payload),\n });\n\n if (!upstream.ok || !upstream.body) {\n let txt = '';\n try { txt = await upstream.text(); } catch (_) {}\n controller.enqueue(encoder.encode('event: error\\n'));\n controller.enqueue(encoder.encode('data: ' + JSON.stringify({ status: upstream.status, message: txt }) + '\\n\\n'));\n controller.enqueue(encoder.encode('data: [DONE]\\n\\n'));\n controller.close();\n return;\n }\n\n const ct = upstream.headers.get('content-type') || '';\n const isSse = /text\\/event-stream/i.test(ct);\n\n if (!isSse) {\n try {\n const nonStream = await upstream.json();\n const choice0 = Array.isArray(nonStream.choices) ? nonStream.choices[0] : null;\n const finalContent = (choice0?.message?.content || choice0?.delta?.content || '') || '';\n if (finalContent) {\n controller.enqueue(encoder.encode('data: ' + JSON.stringify({ choices: [{ delta: { content: finalContent } }] }) + '\\n\\n'));\n }\n try {\n let results = [];\n if (selectedRoute !== 'text') {\n if (finalContent && finalContent.trim()) {\n results = await extractOrRepairJsonResults(finalContent, apiKey, language);\n }\n if ((!results || results.length === 0)) {\n const synthesized = await synthesizeResultsFromContext({\n query,\n language,\n toolText: '',\n assistantText: String(finalContent || ''),\n reasoningText: '',\n existingResults: []\n }, apiKey);\n if (Array.isArray(synthesized) && synthesized.length > 0) {\n results = synthesized;\n }\n }\n }\n controller.enqueue(encoder.encode('event: results\\n'));\n controller.enqueue(encoder.encode('data: ' + JSON.stringify({ route: selectedRoute, results: sanitizeResults(results) }) + '\\n\\n'));\n } catch (_) { /* ignore extraction errors */ }\n controller.enqueue(encoder.encode('data: [DONE]\\n\\n'));\n } catch (e) {\n controller.enqueue(encoder.encode('event: error\\n'));\n controller.enqueue(encoder.encode('data: ' + JSON.stringify({ message: e?.message || String(e) }) + '\\n\\n'));\n controller.enqueue(encoder.encode('data: [DONE]\\n\\n'));\n } finally {\n try { controller.close(); } catch (_) {}\n }\n return;\n }\n\n const reader = upstream.body.getReader();\n const decoder = new TextDecoder();\n let buffer = '';\n let collapsedContent = '';\n let collapsedReasoning = '';\n let collectedTools = [];\n\n try { controller.enqueue(encoder.encode(': connected\\n\\n')); } catch (_) {}\n try {\n controller.enqueue(encoder.encode('event: route\\n'));\n controller.enqueue(encoder.encode('data: ' + JSON.stringify({ route: selectedRoute }) + '\\n\\n'));\n } catch (_) {}\n\n const keepAliveId = setInterval(() => {\n try { controller.enqueue(encoder.encode(': keep-alive\\n\\n')); } catch (_) {}\n }, 15000);\n\n try {\n while (true) {\n const { done, value } = await reader.read();\n if (done) break;\n buffer += decoder.decode(value, { stream: true });\n const events = buffer.split('\\n\\n');\n buffer = events.pop() || '';\n for (const evt of events) {\n if (!evt.trim()) continue;\n const lines = evt.split('\\n');\n for (const line of lines) {\n if (!line.startsWith('data: ')) continue;\n const data = line.slice(6);\n controller.enqueue(encoder.encode('data: ' + data + '\\n\\n'));\n try {\n const parsed = JSON.parse(data);\n const choice = Array.isArray(parsed.choices) ? parsed.choices[0] : null;\n const delta = choice?.delta || {};\n if (delta.reasoning) collapsedReasoning += delta.reasoning;\n if (delta.content) collapsedContent += delta.content;\n if (Array.isArray(delta.executed_tools)) collectedTools.push(...delta.executed_tools);\n if (Array.isArray(delta.tool_calls)) collectedTools.push(...delta.tool_calls);\n } catch (_) { /* ignore non-JSON payloads */ }\n }\n }\n }\n try {\n let results = [];\n if (selectedRoute !== 'text') {\n try {\n const toolText = collectToolTextFromArray(collectedTools);\n const textForExtraction = (collapsedContent && collapsedContent.trim()) ? collapsedContent : ((collapsedReasoning && collapsedReasoning.trim()) ? collapsedReasoning : '');\n if (toolText && toolText.trim()) {\n results = await extractResultsFromToolOutputs(toolText, apiKey, language);\n }\n if ((!results || results.length === 0) && textForExtraction) {\n results = await extractOrRepairJsonResults(textForExtraction, apiKey, language);\n }\n if ((!results || results.length === 0)) {\n const synthesized = await synthesizeResultsFromContext({\n query,\n language,\n toolText,\n assistantText: String(collapsedContent || ''),\n reasoningText: String(collapsedReasoning || ''),\n existingResults: []\n }, apiKey);\n if (Array.isArray(synthesized) && synthesized.length > 0) {\n results = synthesized;\n }\n }\n } catch (_) {}\n }\n controller.enqueue(encoder.encode('event: results\\n'));\n controller.enqueue(encoder.encode('data: ' + JSON.stringify({ route: selectedRoute, results: sanitizeResults(results) }) + '\\n\\n'));\n } catch (_) {}\n controller.enqueue(encoder.encode('data: [DONE]\\n\\n'));\n } catch (err) {\n controller.enqueue(encoder.encode('event: error\\n'));\n controller.enqueue(encoder.encode('data: ' + JSON.stringify({ message: err?.message || String(err) }) + '\\n\\n'));\n } finally {\n try { clearInterval(keepAliveId); } catch (_) {}\n try { controller.close(); } catch (_) {}\n }\n } catch (outerErr) {\n try {\n controller.enqueue(encoder.encode('event: error\\n'));\n controller.enqueue(encoder.encode('data: ' + JSON.stringify({ message: outerErr?.message || String(outerErr) }) + '\\n\\n'));\n controller.enqueue(encoder.encode('data: [DONE]\\n\\n'));\n } catch (_) {}\n try { controller.close(); } catch (_) {}\n }\n }\n });\n\n return new Response(stream, {\n headers: {\n 'Content-Type': 'text/event-stream',\n 'Cache-Control': 'no-cache, no-transform',\n 'Connection': 'keep-alive',\n },\n });\n } catch (error) {\n console.error('chatStreamSSE error:', error);\n return c.json({ error: 'chatStreamSSE error: ' + error.message }, 500);\n }\n });\n}\n\n\n",[],[237,432,450],"f1d82a46-78e1-11f0-a761-0224a6c84d84","chatStream.js","0404255c-7758-11f0-ab1c-0224a6c84d84",38,["D",1755157226883],"// Aggregated chat stream endpoint (returns collapsed + extracted results)\nimport { streamChatAndAggregate } from \"../../chatStreaming.js\";\nimport { buildSearchPrompt, routeQueryMode } from \"../../chatCompletion.js\";\nimport { extractOrRepairJsonResults, extractResultsFromToolOutputs, sanitizeResults, synthesizeResultsFromContext } from \"../../jsonUtils.js\";\nimport { serverApiKey } from \"../config.js\";\n\nfunction collectToolTextFromArray(toolArray) {\n if (!Array.isArray(toolArray)) return '';\n const parts = [];\n for (const t of toolArray) {\n try {\n const name = t?.name || t?.tool || t?.function?.name || t?.id || '';\n const args = t?.arguments || t?.input || t?.params || null;\n const output = t?.output || t?.result || t?.content || null;\n const searchResults = t?.search_results || t?.results || null;\n if (name) parts.push('name: ' + String(name));\n if (args) parts.push('arguments: ' + (typeof args === 'string' ? args : JSON.stringify(args)));\n if (output) parts.push('output: ' + (typeof output === 'string' ? output : JSON.stringify(output)));\n if (searchResults) parts.push('search_results: ' + (typeof searchResults === 'string' ? searchResults : JSON.stringify(searchResults)));\n } catch (_) { /* ignore */ }\n }\n return parts.join('\\n');\n}\n\nexport function registerChatStreamRoute(app) {\n app.post('/api/chatStream', async (c) => {\n try {\n let body = {};\n try { body = await c.req.json(); } catch (_) { body = {}; }\n\n const {\n userApiKey,\n messages,\n query,\n dateRange,\n source,\n language,\n offset = 0,\n model = 'openai/gpt-oss-120b',\n reasoning_effort = 'medium',\n tools,\n temperature,\n top_p,\n stop,\n max_tokens,\n response_format,\n stream: clientStream,\n base_url,\n } = body || {};\n\n const apiKey = serverApiKey || userApiKey || (typeof Deno !== 'undefined' ? Deno.env.get('GROQ_API_KEY') : null);\n if (!apiKey && !base_url) {\n return c.json({ error: 'No Groq API key available. Please provide your own key.' }, 400);\n }\n\n const isGptOss = typeof model === 'string' && model.startsWith('openai/gpt-oss');\n const supportsReasoning = isGptOss;\n const supportsTools = isGptOss;\n\n let finalMessages = Array.isArray(messages) && messages.length > 0\n ? messages\n : (typeof query === 'string' && query.trim().length > 0\n ? [\n { role: 'system', 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. ALWAYS conduct searches in English; if the query is not in English, translate to English for search and present outputs in the requested language.' },\n { role: 'user', content: buildSearchPrompt(query, source, dateRange, language, offset) }\n ]\n : null);\n\n try {\n if (typeof query === 'string' && query.trim()) {\n const route = await routeQueryMode(apiKey, query);\n if (source) {\n finalMessages = [\n { role: 'system', 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. ALWAYS conduct searches in English; if the query is not in English, translate to English for search and present outputs in the requested language.' },\n { role: 'user', content: buildSearchPrompt(query, source, dateRange, language, offset) }\n ];\n } else if (route === 'text') {\n finalMessages = [\n { role: 'system', 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 the requested language (no JSON). Do not use markdown fences.' },\n { role: 'user', content: query }\n ];\n }\n } else if (Array.isArray(finalMessages) && finalMessages.length > 0) {\n // optional: try to infer route from last user message for logging\n let lastUser = '';\n for (let i = finalMessages.length - 1; i >= 0; i--) {\n const m = finalMessages[i];\n if (m && m.role === 'user' && m.content && String(m.content).trim()) { lastUser = String(m.content); break; }\n }\n if (lastUser) {\n try { await routeQueryMode(apiKey, lastUser); } catch (_) {}\n }\n }\n } catch (_) { /* ignore */ }\n\n if (supportsTools && Array.isArray(messages) && messages.length > 0 && Array.isArray(finalMessages)) {\n const toolPreamble = {\n role: 'system',\n content: 'You have access to a web browsing tool named \"browser_search\". Use it for fresh information, finding more sources, verification, and when the user says things like \"continue\", \"find more\", or asks for links. Prefer calling the tool rather than guessing. Answer concisely and include relevant markdown links.'\n };\n finalMessages = [toolPreamble, ...finalMessages];\n }\n if (!finalMessages) {\n finalMessages = [{ role: 'user', content: 'go to https://news.ycombinator.com/ and give me the first 5 stories' }];\n }\n\n const payload = {\n model,\n messages: finalMessages,\n stream: (clientStream === false) ? false : true,\n ...(supportsReasoning ? { reasoning_effort } : {}),\n ...(supportsTools && Array.isArray(tools) && tools.length > 0 ? { tools, tool_choice: 'auto' } : {}),\n ...(temperature !== undefined ? { temperature } : {}),\n ...(top_p !== undefined ? { top_p } : {}),\n ...(stop !== undefined ? { stop } : {}),\n ...(max_tokens !== undefined ? { max_tokens } : {}),\n ...(response_format ? { response_format } : {}),\n };\n\n const baseUrl = (typeof base_url === 'string' && base_url.trim()) ? base_url.trim().replace(/\\/$/, '') : '';\n let endpoint = undefined;\n if (baseUrl) {\n if (/(\\/v\\d+)?\\/(chat\\/)?completions$/i.test(baseUrl)) {\n endpoint = baseUrl;\n } else if (/\\/v\\d+$/i.test(baseUrl)) {\n endpoint = baseUrl + '/chat/completions';\n } else {\n endpoint = baseUrl + '/v1/chat/completions';\n }\n }\n const aggregates = await streamChatAndAggregate(apiKey, payload, { logSse: false, endpoint });\n let results = [];\n let textContent = '';\n let reasoningText = '';\n let toolText = '';\n try {\n textContent = aggregates?.collapsed?.content || '';\n reasoningText = aggregates?.collapsed?.reasoning || '';\n toolText = collectToolTextFromArray(aggregates?.collapsed?.tools || []);\n if (toolText && toolText.trim()) {\n results = await extractResultsFromToolOutputs(toolText, apiKey, language);\n }\n if ((!results || results.length === 0) && textContent && textContent.trim()) {\n results = await extractOrRepairJsonResults(textContent, apiKey, language);\n }\n if ((!results || results.length === 0) && reasoningText && reasoningText.trim()) {\n results = await extractOrRepairJsonResults(reasoningText, apiKey, language);\n }\n if ((!results || results.length === 0)) {\n const synthesized = await synthesizeResultsFromContext({\n query,\n language,\n toolText,\n assistantText: String(textContent || ''),\n reasoningText: String(reasoningText || ''),\n existingResults: []\n }, apiKey);\n if (Array.isArray(synthesized) && synthesized.length > 0) {\n results = synthesized;\n }\n }\n } catch (_e) { /* best-effort parsing */ }\n console.log('>> [chatStream] textContent:', textContent);\n return c.json({ model, ...aggregates, results: sanitizeResults(results) });\n } catch (error) {\n console.error('chatStream error:', error);\n return c.json({ error: 'chatStream error: ' + error.message }, 500);\n }\n });\n}\n\n\n",[],[237,432,458],"03e5ac9e-7758-11f0-a4e6-0224a6c84d84",22,["D",1754988035458],[254,255,256,257,258],[237,432],["D",1754988035289],[253,259,260,261],[237],["D",1754850041617],{"_99":98,"_106":102},{"_99":98,"_100":-5,"_101":102,"_18":57,"_103":104,"_105":25},{"_13":88,"_33":89,"_45":44,"_90":46,"_91":-5,"_92":-5,"_93":-5,"_94":-5,"_95":-5,"_96":47,"_97":98},"ctx",{"_81":-5,"_125":510,"_511":512,"_513":514,"_515":25,"_516":25,"_517":25,"_518":61,"_519":-5,"_520":-7,"_521":-7,"_522":65,"_523":25,"_524":25,"_525":-5,"_526":25,"_527":25,"_528":25,"_529":-5},"ENV",{"_481":482,"_483":484,"_485":89,"_486":487,"_488":489,"_490":491,"_492":493,"_494":495,"_496":497,"_498":499,"_500":501,"_502":503,"_504":505,"_506":507,"_508":509},"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"]

Diff · v61