Lorraine

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The goal is to elicit natural responses, in the person’s own voice, across ages (young teens to older adults) and cultures. Avoid narrow professional jargon; stay broadly relatable and not overly country‑specific. Mentioning common civic concepts like a city office/DMV is fine, but do not assume US‑only systems.\n\nThe goal of these questions is to get a person to respond in different scenarios to create a LoRA data set that's closest to themselves.\n\nIt's for absolute NORMIES so don't do anything that's like tech heavy or particular to one profession like law or medicine.\n\n\n\n### Design pillars\n- **Coverage**: Span everyday domains (home, school, work‑generic, community, transit, food, retail/pharmacy, street/park, healthcare, travel, civic offices).\n- **Emotion**: Make mood legible so style can vary. Use valence × arousal (good/neutral/bad × calm/urgent) without heavy psychology terms.\n- **Hook/tension**: Every prompt should include a small emotional hook, decision, or trade‑off (e.g., fairness, urgency, boundary, uncertainty) so responses carry personal voice—not just administrative wording.\n- **Parsimony**: Keep the schema minimal and prompts short; focus on situational concreteness over metadata.\n- **Inclusivity**: Plain language, grade 6–9 reading level; avoid culture‑bound idioms and tech/corporate jargon.\n- **Privacy**: No real PII. Use placeholders (e.g., order #1234). Use small, non‑identifying specifics (time of day, small amounts).\n- **Trainability**: Each item provides enough context and an example so the LoRA sees place, act, and mood.\n\n### Non‑negotiables (read this before writing)\n- Every prompt MUST contain a hook/tension or warm emotional color (gratitude, relief, pride) that invites a personal stance.\n- Pure admin/information asks are NOT allowed unless framed with a human constraint (time, money, energy, uncertainty) or a choice.\n- Keep it safe and globally relatable; never force a risky behavior or shame a choice.\n- Always allow a real choice. For any prompt with pressure or power dynamics, explicitly state that declining is acceptable. Ask the respondent to include both: (1) what they’d say, and (2) what they’d do (e.g., accept/decline/negotiate/leave/escalate).\n\n### Minimal item schema\n```json\n{\n \"id\": \"string\",\n \"label\": \"short descriptive name\",\n \"prompt\": \"1–2 sentences that incite a response (scenario-first; shown verbatim)\",\n \"tags\": [\"group\", \"setting\", \"act\"],\n \"example\": \"1–3 sentence neutral example reply\"\n}\n```\n\nNotes\n- `tags` are lightweight: include a broad group (e.g., \"public\" or \"home\"), the setting (e.g., \"bus\"), and the speech act (e.g., \"request\"). Add more if useful.\n- The example shows how a typical person might respond; concise, neutral, and safe.\n- Compatibility: older examples in this brief that show an `instruction` field should be read as `prompt`. New items should use `prompt`.\n\n### Response capture (context)\nWe pair each question with a user’s raw response and timestamp. Keep the authoring focused on prompts; responses will be collected separately in the app.\n\n### Authoring checklist\n1) **Choose a setting**: bus, metro/subway, taxi/rideshare, cafe/tea stall, restaurant, grocery/market, pharmacy, retail counter, street/sidewalk, park, city/DMV office, school front desk, post office, hospital/clinic desk, hotel/guesthouse, station/terminal.\n2) **Choose a speech act**: ask/request, clarify, apologize, thank, complain, report an issue, negotiate, offer help, congratulate, follow up, remind.\n3) **Choose a mood**: good/neutral/bad × calm/urgent. Example: bad+urgent for lost wallet; good+calm for thanking someone.\n4) **Choose a channel**: in‑person (spoken), phone, short note, quick text/SMS.\n5) **Add a hook**: a small tension or choice that invites a personal stance (fairness, boundary, risk, time pressure, gratitude, uncertainty).\n6) **Write the prompt**: 1–2 sentences, grade 6–9, no jargon. Include small, non‑identifying specifics:\n - time marker (\"this morning\", \"after lunch\")\n - small amounts (\"about 10–20\"; avoid currency symbols when possible)\n - neutral placeholders (\"order #1234\", \"ticket 56A\")\n7) **Tags**: [group, setting, act] (e.g., [\"public\", \"cafe\", \"complaint\"]).\n8) **Example**: 1–3 sentences; neutral, clear, and kind when appropriate.\n\nDo\n- Keep it short and situational.\n- Use everyday words; avoid corporate or tech‑specific terms.\n- Include a clear ask or outcome.\n\nDon’t\n- Don’t reference software, repos, code, or \"PRs\".\n- Don’t include real PII.\n- Don’t over‑specify policy/legal unless the setting demands it (e.g., city office).\n\n### Coverage checklist (aim to fill evenly over time)\n- **Settings**: transit, food/drink, retail/pharmacy, street/park, civic offices, school, post office, healthcare, hotel/guesthouse, stations/terminals, home/community.\n- **Acts**: ask, clarify, thank, apologize, complain, report, negotiate, offer help, congratulate, follow up, remind.\n- **Emotions**: good/neutral/bad × calm/urgent.\n- **Channels**: in‑person, phone, short note, quick text/SMS.\n\n### Sampling strategy (lightweight)\n- Use a small stratified grid across setting × act × mood × channel.\n- Rotate formality (informal/neutral/formal) and power (equal/senior/subordinate) occasionally to broaden style without complicating prompts.\n\n### Make every prompt flavorful (practical rules)\n- Prefer a request with a reason over a pure inquiry. Replace “what are the instructions?” with “ask for instructions because X is at stake.”\n- Add one human constraint: time, money, energy, or uncertainty.\n- Invite a choice: accept/decline/negotiate; escalate vs let it go; help vs set a boundary.\n- Keep it humane: polite, non‑judgmental, globally relatable.\n\nFlavor hooks library (mix‑and‑match)\n- Fairness: fee waivers, wrong bills, mistaken charges, misattribution.\n- Time pressure: events starting soon, deadlines, travel delays, closing windows.\n- Boundaries: privacy, alcohol/late nights, borrowing items, spare keys, white lies.\n- Uncertainty: conflicting instructions, missing documents, ambiguous requirements.\n- Risk/comfort: public speaking, new foods/activities, last‑minute trips.\n- Gratitude/relief/pride: thanks, small wins, finishing a hard task.\n\n### Power dynamics and consent (must‑cover scenarios)\n- Include prompts that surface different power positions and consent decisions: manager↔report, teacher↔student, landlord↔tenant, vendor↔customer, date↔date, older↔younger.\n- Consent and safety: never romanticize coercion. Wording should make clear that “no” and leaving are valid options. Avoid graphic or sexual content; keep it PG and focused on boundaries and choices.\n- Prompt pattern to include: “Reply in your own words AND state your choice (accept/decline/negotiate/leave/escalate).”\n\nExamples: boring → flavorful\n- Wire info: “Ask for incoming wire instructions” → “You must receive an international transfer today to pay a deposit; ask for the wire details and how to confirm it arrived.”\n- Insurance status: “Check claim status” → “You’re worried about paying a repair bill this week; ask for claim status and what you can submit today to speed it up.”\n- Bank update: “Change address on file” → “You just moved and a card was returned undelivered; ask to update the address and resend urgently.”\n\n### Situational prompts that surface personality (optional overlay)\nThese prompts are designed to elicit words and choices that reflect personal tendencies (e.g., boundary setting, assertiveness, comfort with risk, harmony‑seeking vs directness) without naming any framework. Keep them human, non‑judgmental, and age/culture inclusive.\n\n- Aim for moments of light tension or choice where multiple reasonable responses exist (accept/decline/negotiate/avoid).\n- State the mood (calm/urgent; good/neutral/bad) and power dynamic (peer/manager/stranger/family).\n- Avoid pathologizing language; do not mention MBTI/Enneagram explicitly.\n- For prompts involving alcohol, provide a youth‑safe variant (e.g., energy drinks at a late hangout).\n\nMini‑matrix of tendencies to cover over time\n- Assert vs avoid; direct vs diplomatic; spontaneous vs planned; rule‑following vs flexible; private vs public; harmony vs candid critique; help‑giving vs boundary‑keeping; risk‑seeking vs cautious.\n\nSample situational seeds\n[\n {\n \"id\": \"relationships_peer_pressure_drink_01\",\n \"label\": \"Friends pressuring to drink\",\n \"instruction\": \"Friends encourage you to try alcohol at a small gathering. You’ve never had a drink and don’t want to. Respond in your own way (youth variant: energy drink late at night).\",\n \"tags\": [\"relationships\", \"friends\", \"boundary\"],\n \"example\": \"I’m going to pass tonight, but I’m happy to hang and grab a soda. Thanks for understanding.\"\n },\n {\n \"id\": \"work_public_speaking_invite_01\",\n \"label\": \"Boss invites you to present to 500 people\",\n \"instruction\": \"Your manager thinks you might enjoy presenting new findings on a big stage. You can accept or decline—reply in your style, including any conditions.\",\n \"tags\": [\"work\", \"invite\", \"present\"],\n \"example\": \"Thanks for thinking of me. I’d be up for it if I can do a shorter slot and rehearse with the team next week. If you prefer a more seasoned speaker, I’m also happy to support from backstage.\"\n },\n {\n \"id\": \"education_copy_homework_boundary_01\",\n \"label\": \"Classmate asks to copy homework\",\n \"instruction\": \"A classmate asks to copy your work before class. Set a boundary and offer a fair alternative if you’d like.\",\n \"tags\": [\"education\", \"boundary\", \"integrity\"],\n \"example\": \"I can’t share my answers, but I’m happy to compare approaches after class so we both learn.\"\n },\n {\n \"id\": \"home_neighbor_key_request_boundary_01\",\n \"label\": \"Neighbor asks for a spare key\",\n \"instruction\": \"A new neighbor asks you for a spare key ‘just in case.’ You’re not comfortable. Decline or propose another plan.\",\n \"tags\": [\"home\", \"neighbor\", \"boundary\"],\n \"example\": \"I don’t give out spare keys, but I can share my number and we can swap package help when needed.\"\n },\n {\n \"id\": \"relationships_family_event_pressure_01\",\n \"label\": \"Family pressure to attend a tradition\",\n \"instruction\": \"Family urges you to attend a tradition you don’t personally observe. Reply in a way that fits you—decline, negotiate, or accept with conditions.\",\n \"tags\": [\"relationships\", \"family\", \"boundary\"],\n \"example\": \"I love you all and want to be part of it, but the ceremony isn’t for me. I’ll join for dinner afterward if that works.\"\n },\n {\n \"id\": \"public_queue_cut_response_01\",\n \"label\": \"Stranger cuts the queue\",\n \"instruction\": \"Someone steps ahead of you in a line. Respond in your way—direct, diplomatic, or letting it go.\",\n \"tags\": [\"public\", \"queue\", \"assert\"],\n \"example\": \"Excuse me—were you ahead of me? If not, the line starts back there. Thank you.\"\n },\n {\n \"id\": \"work_weekend_overtime_boundary_01\",\n \"label\": \"Asked to work the weekend\",\n \"instruction\": \"You’re asked to work this weekend on short notice. You can agree, negotiate scope, or decline.\",\n \"tags\": [\"work\", \"boundary\", \"negotiate\"],\n \"example\": \"I can cover a few critical items Saturday morning, but not the whole weekend. If we prioritize A and B, I can ship those.\"\n },\n {\n \"id\": \"relationships_friend_wants_white_lie_01\",\n \"label\": \"Friend asks you to tell a white lie\",\n \"instruction\": \"A friend asks you to say they were with you to avoid trouble. Decide how you respond.\",\n \"tags\": [\"relationships\", \"friends\", \"boundary\"],\n \"example\": \"I care about you, but I’m not comfortable saying that. Let’s figure out a way to own it and fix things.\"\n },\n {\n \"id\": \"public_service_rude_staff_01\",\n \"label\": \"Rude staff interaction\",\n \"instruction\": \"A staff member speaks sharply to you after a long wait. Reply in your style—stay calm, ask for a manager, or step away.\",\n \"tags\": [\"public\", \"service\", \"deescalate\"],\n \"example\": \"I’d like to resolve this, but the tone feels tense. Could we reset, or may I speak with a supervisor?\"\n },\n {\n \"id\": \"travel_last_minute_trip_invite_01\",\n \"label\": \"Last‑minute trip invite\",\n \"instruction\": \"Friends invite you on a spontaneous weekend trip. You can decline, accept, or suggest a plan that suits you.\",\n \"tags\": [\"travel\", \"friends\", \"decide\"],\n \"example\": \"Sounds fun—I can’t do this weekend, but I’m in for next month if we keep it simple and cheap.\"\n },\n {\n \"id\": \"work_credit_for_idea_response_01\",\n \"label\": \"Teammate takes credit for your idea\",\n \"instruction\": \"In a meeting, a teammate presents your idea as theirs. Respond in your style—address now, follow up, or let it go with a note.\",\n \"tags\": [\"work\", \"feedback\", \"assert\"],\n \"example\": \"Glad this is resonating. This builds on the draft I shared Tuesday—happy to co‑own next steps together.\"\n },\n {\n \"id\": \"relationships_partner_public_post_01\",\n \"label\": \"Partner wants to post something personal\",\n \"instruction\": \"Your partner wants to post a personal story/photo. You’re more private. Respond with your boundary and a compromise if you like.\",\n \"tags\": [\"relationships\", \"partner\", \"boundary\"],\n \"example\": \"I’d rather keep that private. Could we share a cropped photo or a short caption without details?\"\n }\n]\n\n### Power dynamic seeds (examples; keep PG, emphasize choice + consent)\n[\n {\n \"id\": \"work_manager_pushes_unethical_01\",\n \"label\": \"Manager asks you to do something you believe is wrong\",\n \"instruction\": \"Your manager asks you to skip a required step to ship faster. Reply in your words AND state your choice (proceed/decline/negotiate/escalate).\",\n \"tags\": [\"work\", \"manager\", \"boundary\"],\n \"example\": \"I’m not comfortable skipping that control—it protects customers. My choice is to decline and propose we ship the smaller change today and the rest next week.\"\n },\n {\n \"id\": \"relationships_date_pressure_boundary_01\",\n \"label\": \"Date pressures you (boundary)\",\n \"instruction\": \"On a date, the other person pressures you—for payment or physical intimacy. Reply in your words AND state your choice (set boundary/leave/continue another time). Keep it PG and respectful.\",\n \"tags\": [\"relationships\", \"date\", \"boundary\"],\n \"example\": \"I’m not comfortable with that. I’m heading out now—thanks for the evening. My choice is to end the date and go home.\"\n },\n {\n \"id\": \"home_landlord_power_boundary_01\",\n \"label\": \"Landlord presses for entry without notice\",\n \"instruction\": \"A landlord insists on entering today without proper notice. Reply in your words AND state your choice (decline/reschedule/escalate).\",\n \"tags\": [\"home\", \"landlord\", \"boundary\"],\n \"example\": \"I need the standard notice period. My choice is to decline today—tomorrow 10–12 works, or I’ll escalate if needed.\"\n },\n {\n \"id\": \"public_vendor_pushy_upsell_01\",\n \"label\": \"Pushy vendor upsell (public)\",\n \"instruction\": \"A vendor insists you add extras you don’t want. Reply in your words AND state your choice (decline/negotiate/leave).\",\n \"tags\": [\"public\", \"vendor\", \"boundary\"],\n \"example\": \"No thank you—just the basic service. My choice is to decline the extras; if that’s not possible, I’ll leave.\"\n },\n {\n \"id\": \"education_teacher_after_hours_boundary_01\",\n \"label\": \"Teacher asks for after‑hours meeting alone\",\n \"instruction\": \"A teacher suggests meeting alone after hours. Reply in your words AND state your choice (request public time/bring a friend/decline).\",\n \"tags\": [\"education\", \"teacher\", \"boundary\"],\n \"example\": \"Could we meet during office hours or with a classmate present? My choice is to keep it during posted hours.\"\n }\n]\n\n### Finance seeds with flavor (examples)\n[\n {\n \"id\": \"finance_overdraft_fee_waiver_02\",\n \"label\": \"Overdraft fee waiver (fairness)\",\n \"instruction\": \"Request a one‑time overdraft fee waiver, explain brief context (first time in years, deposit cleared same day), and ask politely.\",\n \"tags\": [\"finance\", \"bank\", \"fees\"],\n \"example\": \"I was charged an overdraft fee yesterday—the first in years—and my deposit cleared the same day. Could this be waived as a one‑time courtesy?\"\n },\n {\n \"id\": \"finance_charge_dispute_time_pressure_01\",\n \"label\": \"Dispute charge with time pressure\",\n \"instruction\": \"Dispute an unfamiliar charge and ask for a quick provisional credit because rent is due tomorrow.\",\n \"tags\": [\"finance\", \"bank\", \"dispute\"],\n \"example\": \"There’s a charge from May 12 I don’t recognize. Could we open a dispute and apply a provisional credit? Rent is due tomorrow.\"\n },\n {\n \"id\": \"finance_transfer_limit_raise_urgency_01\",\n \"label\": \"Raise transfer limit (urgent deposit)\",\n \"instruction\": \"Ask to temporarily raise a transfer limit to place a housing deposit today; confirm verification steps.\",\n \"tags\": [\"finance\", \"bank\", \"limit\"],\n \"example\": \"I need to send a larger transfer today for a housing deposit. Can we temporarily raise the limit, and what verification do you need?\"\n },\n {\n \"id\": \"finance_remittance_family_support_01\",\n \"label\": \"Urgent remittance for family\",\n \"instruction\": \"Ask about the fastest, lowest‑fee way to send a small amount to family abroad today and how to confirm pickup.\",\n \"tags\": [\"finance\", \"remittance\", \"fees\"],\n \"example\": \"What’s the fastest, low‑fee way to send about 150 today, and how do I confirm my mother can pick it up this evening?\"\n },\n {\n \"id\": \"finance_credit_report_blocks_housing_01\",\n \"label\": \"Credit error blocks housing\",\n \"instruction\": \"Dispute a credit report error that’s blocking an apartment application; ask what to submit to expedite.\",\n \"tags\": [\"finance\", \"credit\", \"dispute\"],\n \"example\": \"There’s an error on my credit report that’s delaying an apartment application. What documents should I submit to correct it quickly?\"\n }\n]\n\n### Author QA rubric (use before submitting items)\n- Hook present: is there a clear human tension or warm emotion? If not, add one.\n- Choice available: could a reasonable person accept/decline/negotiate/ask for help?\n- Specifics included: tiny time/amount/placeholders present without PII?\n- Neutral, global language: no culture‑bound jargon or currency symbols unless essential.\n- Reading level: grade 6–9; friendly and concise.\n\n### Item template\n```json\n{\n \"id\": \"public___\",\n \"label\": \"Short name\",\n \"prompt\": \"One clear, plain scenario that incites a response, in your own words.\",\n \"tags\": [\"public\", \"\", \"\"],\n \"example\": \"1–3 sentence neutral example reply.\"\n}\n```\n\n### Sample seeds (varied, globally relatable)\n[\n {\n \"id\": \"public_bus_seat_request_01\",\n \"label\": \"Ask for a seat on a crowded bus\",\n \"instruction\": \"Politely ask if you may take an available seat because you’re feeling unwell.\",\n \"tags\": [\"public\", \"bus\", \"request\"],\n \"example\": \"Hi, would it be alright if I sit here? I’m not feeling well and would appreciate the seat. Thank you.\"\n },\n {\n \"id\": \"public_cafe_wrong_order_01\",\n \"label\": \"Fix a wrong cafe order\",\n \"instruction\": \"In a friendly tone, explain your drink isn’t what you ordered and ask for a remake.\",\n \"tags\": [\"public\", \"cafe\", \"complaint\"],\n \"example\": \"Hi—this has dairy, but I asked for non‑dairy. Could you please remake it? Thank you.\"\n },\n {\n \"id\": \"public_market_price_mismatch_01\",\n \"label\": \"Price mismatch at checkout\",\n \"instruction\": \"Calmly point out a sale sign and ask the cashier to adjust the total if applicable.\",\n \"tags\": [\"public\", \"market\", \"clarify\"],\n \"example\": \"I think these apples were marked at a lower price on the sign. Could we check and adjust if that’s right?\"\n },\n {\n \"id\": \"public_street_found_wallet_01\",\n \"label\": \"Found wallet (note to leave)\",\n \"instruction\": \"Write a short note saying you turned a found wallet in at the front desk or security.\",\n \"tags\": [\"public\", \"street\", \"report\"],\n \"example\": \"Found a wallet near the bench. I left it with the front desk—please ask for the wallet turned in at noon.\"\n },\n {\n \"id\": \"public_civic_missing_document_01\",\n \"label\": \"City office: missing document\",\n \"instruction\": \"Ask the clerk what acceptable alternatives you can bring if you don’t have a utility bill for address proof.\",\n \"tags\": [\"public\", \"civic_office\", \"clarify\"],\n \"example\": \"I don’t have a current utility bill—are a bank statement or a lease copy acceptable for address verification?\"\n },\n {\n \"id\": \"public_pharmacy_delay_01\",\n \"label\": \"Delayed prescription pickup\",\n \"instruction\": \"Ask when a delayed prescription will be ready and if a partial fill is possible.\",\n \"tags\": [\"public\", \"pharmacy\", \"request\"],\n \"example\": \"Hi, is order #1234 ready today? If not, could I pick up a partial until the rest arrives?\"\n },\n {\n \"id\": \"public_ride_fare_review_01\",\n \"label\": \"Ride fare review\",\n \"instruction\": \"Explain that a missed turn caused a higher fare and ask support to review.\",\n \"tags\": [\"public\", \"rideshare\", \"complaint\"],\n \"example\": \"The driver missed an exit and the fare was much higher. Could you review and adjust the trip if appropriate?\"\n },\n {\n \"id\": \"public_store_return_no_receipt_01\",\n \"label\": \"Return without receipt\",\n \"instruction\": \"Ask politely about store policy for returning an item without a receipt.\",\n \"tags\": [\"public\", \"retail\", \"clarify\"],\n \"example\": \"I’d like to return this but don’t have the receipt. Is store credit possible?\"\n },\n {\n \"id\": \"public_crosswalk_thanks_01\",\n \"label\": \"Thank a driver at a crossing\",\n \"instruction\": \"Express brief thanks to a driver who waited for you and your child to cross.\",\n \"tags\": [\"public\", \"street\", \"thanks\"],\n \"example\": \"Thank you for waiting—really appreciate it.\"\n },\n {\n \"id\": \"public_parking_fender_bender_note_01\",\n \"label\": \"Parking lot fender bender note\",\n \"instruction\": \"Write a responsible note after a minor bump: time, contact, and willingness to coordinate repairs.\",\n \"tags\": [\"public\", \"parking\", \"apology\"],\n \"example\": \"I lightly bumped your bumper around 3:10 p.m. My name is Sam—555‑123‑4567. Happy to coordinate repairs.\"\n },\n {\n \"id\": \"public_school_absence_note_01\",\n \"label\": \"School absence note\",\n \"instruction\": \"Write a short note to the school front desk explaining your child’s absence and expected return.\",\n \"tags\": [\"public\", \"school\", \"inform\"],\n \"example\": \"Hi—my child was unwell this morning and will be absent today. We expect them back tomorrow. Thank you.\"\n },\n {\n \"id\": \"public_neighbor_noise_01\",\n \"label\": \"Neighbor noise (polite request)\",\n \"instruction\": \"Ask a neighbor to lower late‑night noise while keeping the tone friendly.\",\n \"tags\": [\"public\", \"home\", \"request\"],\n \"example\": \"Hi—could you please lower the music a bit? It’s quite late and we’re trying to sleep. Thanks for understanding.\"\n },\n {\n \"id\": \"public_clinic_reschedule_01\",\n \"label\": \"Clinic appointment reschedule\",\n \"instruction\": \"Ask to move an appointment earlier if possible and mention brief symptom severity.\",\n \"tags\": [\"public\", \"clinic\", \"request\"],\n \"example\": \"Is there an earlier slot this week? The pain’s gotten worse, so I’d appreciate anything sooner if possible.\"\n },\n {\n \"id\": \"public_train_delay_update_01\",\n \"label\": \"Train delay update\",\n \"instruction\": \"Ask station staff for an update on a delayed train and possible alternatives.\",\n \"tags\": [\"public\", \"station\", \"clarify\"],\n \"example\": \"Hi—any update on the delayed train? If it’s a long wait, is there another route I could take?\"\n },\n {\n \"id\": \"public_post_parcel_late_01\",\n \"label\": \"Parcel delay inquiry\",\n \"instruction\": \"Ask the post office about a parcel that hasn’t arrived and confirm the next steps.\",\n \"tags\": [\"public\", \"post_office\", \"clarify\"],\n \"example\": \"A parcel due last week hasn’t arrived. Could we check its status and what I should do next?\"\n },\n {\n \"id\": \"public_hotel_early_checkin_01\",\n \"label\": \"Hotel early check‑in\",\n \"instruction\": \"Ask politely if early check‑in is possible and offer to wait if needed.\",\n \"tags\": [\"public\", \"hotel\", \"request\"],\n \"example\": \"Hello—would early check‑in be possible today? If not, no problem; I can wait in the lobby.\"\n },\n {\n \"id\": \"public_restaurant_running_late_01\",\n \"label\": \"Restaurant reservation—running late\",\n \"instruction\": \"Send a quick message that you’ll be a few minutes late and ask them to hold the table.\",\n \"tags\": [\"public\", \"restaurant\", \"inform\"],\n \"example\": \"We’re running about 10 minutes late for our booking. Could you please hold the table? Thank you.\"\n },\n {\n \"id\": \"public_lost_and_found_festival_01\",\n \"label\": \"Festival lost and found\",\n \"instruction\": \"Ask where to check for a lost phone and what details you should provide.\",\n \"tags\": [\"public\", \"event\", \"clarify\"],\n \"example\": \"I may have misplaced my phone near the main gate. Where should I check, and what details do you need?\"\n },\n {\n \"id\": \"public_taxi_fixed_price_01\",\n \"label\": \"Taxi fixed‑price negotiation\",\n \"instruction\": \"Politely ask a taxi driver for a rough fixed price before starting the ride.\",\n \"tags\": [\"public\", \"taxi\", \"negotiate\"],\n \"example\": \"Could we agree on an approximate price to the station before we go? If traffic is heavy, I understand it might vary.\"\n },\n {\n \"id\": \"public_park_lost_dog_01\",\n \"label\": \"Lost dog report\",\n \"instruction\": \"Ask a park staff member for help after losing sight of your dog; include a brief description.\",\n \"tags\": [\"public\", \"park\", \"report\"],\n \"example\": \"I’ve lost sight of my small brown dog near the pond. Is there someone who can help me look or alert others?\"\n }\n]\n\n### Quality bar\n- Clear place, act, and mood so respondents can answer in their own style.\n- Neutral, globally understandable wording; no specialized jargon.\n- Examples are concise and demonstrate tone without over‑directing 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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",[142],"8bd32ae6-7618-11f0-936b-0224a6c84d84","main.js",42,["D",1754850824553],1,"http","import { Hono } from 'https://deno.land/x/hono@v3.11.12/mod.ts';\nimport { serve } from 'https://deno.land/std@0.190.0/http/server.ts';\nimport { listFiles, readFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\nimport \"jsr:@std/dotenv/load\"; // needed for deno run; not req for smallweb or valtown\nimport { performSearch, summarizeUrl, buildSearchPrompt, routeQueryMode, groqChatCompletion } from \"./chatCompletion.js\";\nimport { extractOrRepairJsonResults, extractResultsFromToolOutputs, sanitizeResults, synthesizeResultsFromContext, synthesizeTextFromContext } from \"./jsonUtils.js\";\nimport { streamChatAndAggregate } from \"./chatStreaming.js\";\n\nconst app = new Hono();\nconst serverApiKey = null; // Deno.env.get(\"GROQ_API_KEY\");\n\n// Settings configuration\nconst settings = {\n model: 'openai/gpt-oss-120b',\n stream: false,\n reasoningEffort: 'low'\n};\n\n\n// Helper: Collect readable text from tool records for URL-grounded extraction\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 (_) {\n // ignore malformed tool objects\n }\n }\n return parts.join('\\n');\n}\n\n\n\n// Check if server has API key\napp.get('/api/check-key', (c) => {\n return c.json({ hasServerKey: !!serverApiKey });\n});\n\n// Environment-aware file reading function\nasync function readFileContent(filePath) {\n // Check if we're in Val Town environment\n if (typeof Deno !== \"undefined\" && Deno.env.get(\"valtown\")) {\n // Use Val Town's readFile\n return await readFile(filePath, import.meta.url);\n } else {\n // Use Deno's native readTextFile for local development\n return await Deno.readTextFile(filePath);\n }\n}\n\n// Serve root with HTML content\napp.get('/', async (c) => {\n try {\n const htmlContent = await readFileContent('index.html');\n return c.html(htmlContent);\n } catch (error) {\n console.error('Error reading HTML file:', error);\n return c.text('Error loading page', 500);\n }\n});\n\n// Serve frontend modules (no static middleware)\napp.get('/frontend/researchApp.js', async (c) => {\n try {\n const js = await readFileContent('frontend/researchApp.js');\n return new Response(js, {\n headers: { 'Content-Type': 'application/javascript; charset=utf-8' },\n });\n } catch (error) {\n console.error('Error reading researchApp.js:', error);\n return c.text('Not found', 404);\n }\n});\n\napp.get('/frontend/init.js', async (c) => {\n try {\n const js = await readFileContent('frontend/init.js');\n return new Response(js, {\n headers: { 'Content-Type': 'application/javascript; charset=utf-8' },\n });\n } catch (error) {\n console.error('Error reading init.js:', error);\n return c.text('Not found', 404);\n }\n});\n\napp.get('/frontend/lorraineApp.js', async (c) => {\n try {\n const js = await readFileContent('frontend/lorraineApp.js');\n return new Response(js, {\n headers: { 'Content-Type': 'application/javascript; charset=utf-8' },\n });\n } catch (error) {\n console.error('Error reading lorraineApp.js:', error);\n return c.text('Not found', 404);\n }\n});\n\n// Serve data/questions.json\napp.get('/data/questions.json', async (c) => {\n try {\n const json = await readFileContent('data/questions.json');\n return new Response(json, { headers: { 'Content-Type': 'application/json; charset=utf-8' } });\n } catch (error) {\n console.error('Error reading questions.json:', error);\n return c.text('Not found', 404);\n }\n});\n\n// Serve aggregated questions from data/questions/*.json as a single list\napp.get('/data/questions/all.json', async (c) => {\n try {\n // List files in data/questions/\n let paths = [];\n try {\n // Val Town compatible listing if available\n const list = await listFiles('data/questions', import.meta.url);\n // listFiles returns absolute/URL-ish; we need to re-read via readFileContent\n paths = Array.isArray(list) ? list : [];\n } catch (_) {\n // Local fallback: simple directory scan\n const dir = 'data/questions';\n for await (const entry of Deno.readDir(dir)) {\n if (!entry.isFile) continue;\n if (!entry.name.endsWith('.json')) continue;\n paths.push(`${dir}/${entry.name}`);\n }\n }\n const collected = [];\n for (const p of paths) {\n try {\n const text = await readFileContent(String(p).replace(/^file:\\/\\//, ''));\n const arr = JSON.parse(text);\n if (Array.isArray(arr)) collected.push(...arr);\n } catch (_) { /* skip bad files */ }\n }\n return c.json(collected);\n } catch (error) {\n console.error('Error aggregating questions:', error);\n return c.text('Not found', 404);\n }\n});\n\n// Helper: list JSON files under a directory across environments (recursive)\nasync function listQuestionFiles(dirPath) {\n // Val Town environment\n if (typeof Deno !== \"undefined\" && Deno.env.get(\"valtown\")) {\n try {\n const entries = await listFiles(dirPath, import.meta.url);\n const paths = [];\n for (const it of (Array.isArray(entries) ? entries : [])) {\n // Coerce to string path; support objects from listFiles\n let p = null;\n if (typeof it === 'string') p = it;\n else if (it && typeof it.path === 'string') p = it.path;\n else if (it && typeof it.name === 'string') p = `${dirPath}/${it.name}`;\n if (p && p.endsWith('.json')) paths.push(p);\n }\n return paths;\n } catch (_) {\n return [];\n }\n }\n // Local Deno environment\n async function walk(current) {\n const found = [];\n try {\n for await (const entry of Deno.readDir(current)) {\n const path = `${current}/${entry.name}`;\n if (entry.isFile && entry.name.endsWith('.json')) {\n found.push(path);\n } else if (entry.isDirectory) {\n const nested = await walk(path);\n found.push(...nested);\n }\n }\n } catch (_) { /* ignore */ }\n return found;\n }\n return await walk(dirPath);\n}\n\n// Aggregated questions across domain files + base questions.json\napp.get('/data/questions/all.json', async (c) => {\n try {\n const combined = [];\n // Base file (optional)\n try {\n const baseText = await readFileContent('data/questions.json');\n const baseArr = JSON.parse(baseText);\n if (Array.isArray(baseArr)) combined.push(...baseArr);\n } catch (_) { /* optional */ }\n // Domain-sharded files\n const dir = 'data/questions';\n const files = await listQuestionFiles(dir);\n for (const f of files) {\n try {\n const text = await readFileContent(f);\n const arr = JSON.parse(text);\n if (Array.isArray(arr) && arr.length) combined.push(...arr);\n } catch (_) { /* skip malformed */ }\n }\n return new Response(JSON.stringify(combined, null, 2), { headers: { 'Content-Type': 'application/json; charset=utf-8' } });\n } catch (error) {\n console.error('Error aggregating questions:', error);\n return c.text('Not found', 404);\n }\n});\n\n// Slug helpers for grouping\nfunction toSlugLabel(slug) {\n try {\n const parts = String(slug).split(':').filter(Boolean);\n return parts.map(p => p.replace(/[-_]/g, ' ').replace(/\\b\\w/g, (m) => m.toUpperCase())).join(' > ');\n } catch (_) { return slug; }\n}\nfunction pathFromSlug(slug) {\n const safe = String(slug || '').replace(/[^a-zA-Z0-9_:\\-.]/g, '');\n const rel = safe.split(':').join('/');\n return `data/questions/${rel}.json`;\n}\nfunction slugFromPath(path) {\n const rel = String(path || '').replace(/^data\\/questions\\//, '').replace(/\\.json$/i, '');\n return rel.split('/').join(':');\n}\n\n// List groups (each JSON file under data/questions)\napp.get('/data/questions/groups.json', async (c) => {\n try {\n const files = await listQuestionFiles('data/questions');\n const groups = [];\n for (const f of files) {\n try {\n const text = await readFileContent(f);\n const arr = JSON.parse(text);\n const slug = slugFromPath(f);\n groups.push({ id: slug, label: toSlugLabel(slug), path: f.replace(/^data\\//, ''), count: Array.isArray(arr) ? arr.length : 0 });\n } catch (_) { /* ignore */ }\n }\n groups.sort((a, b) => a.id.localeCompare(b.id));\n return c.json(groups);\n } catch (error) {\n console.error('Error listing groups:', error);\n return c.text('Not found', 404);\n }\n});\n\n// Fetch a single group by slug, e.g. work or work:status\napp.get('/data/questions/group/:slug.json', async (c) => {\n try {\n const slug = c.req.param('slug');\n const path = pathFromSlug(slug);\n const text = await readFileContent(path);\n return new Response(text, { headers: { 'Content-Type': 'application/json; charset=utf-8' } });\n } catch (error) {\n console.error('Error reading group:', error);\n return c.text('Not found', 404);\n }\n});\n\n// Fetch multiple groups by comma-separated list: /data/questions/by-groups.json?groups=work,friends:banter\napp.get('/data/questions/by-groups.json', async (c) => {\n try {\n const url = new URL(c.req.url);\n const param = url.searchParams.get('groups') || '';\n const slugs = param.split(',').map(s => s.trim()).filter(Boolean);\n if (slugs.length === 0) return c.json([]);\n const out = [];\n for (const slug of slugs) {\n try {\n const path = pathFromSlug(slug);\n const text = await readFileContent(path);\n const arr = JSON.parse(text);\n if (Array.isArray(arr)) out.push(...arr);\n } catch (_) { /* ignore */ }\n }\n return c.json(out);\n } catch (error) {\n console.error('Error aggregating selected groups:', error);\n return c.text('Not found', 404);\n }\n});\n\n// Simplifier: combine instruction + source_text, keep tags, and expose example (or fallback)\nfunction simplifyQuestionItem(q) {\n try {\n const id = String(q.id || '').trim();\n const label = String(q.label || id || 'item').trim();\n const tags = Array.isArray(q.tags) ? q.tags : [];\n const instr = (q && typeof q.instruction === 'string') ? q.instruction.trim() : '';\n const src = (q && typeof q.source_text === 'string') ? q.source_text.trim() : '';\n // Merge with a newline if both exist\n const merged = instr && src ? (instr + '\\n\\n' + src) : (instr || src || '');\n const example = (q && typeof q.example === 'string')\n ? q.example\n : ((q && typeof q.neutral_sample === 'string') ? q.neutral_sample : '');\n return { id, label, instruction: merged, tags, example };\n } catch (_) {\n return null;\n }\n}\n\n// Simple (reduced) aggregated output\napp.get('/data/questions/simple.json', async (c) => {\n try {\n // Collect from base and all groups\n const combined = [];\n try {\n const baseText = await readFileContent('data/questions.json');\n const baseArr = JSON.parse(baseText);\n if (Array.isArray(baseArr)) combined.push(...baseArr);\n } catch (_) {}\n const files = await listQuestionFiles('data/questions');\n for (const f of files) {\n try {\n const text = await readFileContent(f);\n const arr = JSON.parse(text);\n if (Array.isArray(arr)) combined.push(...arr);\n } catch (_) {}\n }\n const simple = [];\n for (const q of combined) {\n const s = simplifyQuestionItem(q);\n if (s && s.id && s.instruction) simple.push(s);\n }\n return c.json(simple);\n } catch (error) {\n console.error('Error building simple questions:', error);\n return c.text('Not found', 404);\n }\n});\n\n// Simple by groups\napp.get('/data/questions/simple/by-groups.json', async (c) => {\n try {\n const url = new URL(c.req.url);\n const param = url.searchParams.get('groups') || '';\n const slugs = param.split(',').map(s => s.trim()).filter(Boolean);\n if (slugs.length === 0) return c.json([]);\n const out = [];\n for (const slug of slugs) {\n try {\n const path = pathFromSlug(slug);\n const text = await readFileContent(path);\n const arr = JSON.parse(text);\n if (Array.isArray(arr)) {\n for (const q of arr) {\n const s = simplifyQuestionItem(q);\n if (s && s.id && s.instruction) out.push(s);\n }\n }\n } catch (_) { /* ignore */ }\n }\n return c.json(out);\n } catch (error) {\n console.error('Error building simple group questions:', error);\n return c.text('Not found', 404);\n }\n});\n\n// GROQ Whisper transcription passthrough\napp.post('/api/transcribe', async (c) => {\n try {\n const contentType = c.req.header('content-type') || '';\n if (!contentType.includes('multipart/form-data')) {\n return c.json({ error: 'multipart/form-data required' }, 400);\n }\n const form = await c.req.formData();\n const file = form.get('file');\n const userApiKey = form.get('userApiKey');\n const apiKey = serverApiKey || (typeof userApiKey === 'string' ? userApiKey : null);\n if (!apiKey) return c.json({ error: 'No Groq API key available.' }, 400);\n if (!(file instanceof File)) return c.json({ error: 'file missing' }, 400);\n\n const upstreamForm = new FormData();\n upstreamForm.append('file', file, 'audio.webm');\n upstreamForm.append('model', 'whisper-large-v3');\n // Optionally set language or prompt here\n\n const resp = await fetch('https://api.groq.com/openai/v1/audio/transcriptions', {\n method: 'POST',\n headers: { 'Authorization': 'Bearer ' + apiKey },\n body: upstreamForm\n });\n if (!resp.ok) {\n const txt = await resp.text();\n return c.json({ error: 'Groq Whisper error: ' + txt }, 500);\n }\n const data = await resp.json();\n const text = data?.text || '';\n return c.json({ text });\n } catch (error) {\n console.error('transcribe error:', error);\n return c.json({ error: 'transcribe error: ' + error.message }, 500);\n }\n});\n\n\napp.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 // Unified handler: 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 // Force links mode when a specific source is chosen\n forceLinksRoute: !!source,\n });\n\n // Server-side debug logging of the full model response and assistant content\n try {\n console.log('>> [performSearch] fullResponse:', JSON.stringify(fullResponse));\n } catch (_) {\n console.log('>> [performSearch] fullResponse: ');\n }\n try {\n console.log('>> [performSearch] assistantContent:', typeof assistantContent === 'string' ? assistantContent : JSON.stringify(assistantContent));\n } 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 toolText = ''; // non-stream path has no tool logs; rely on assistant text\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// API: Raw SSE passthrough for chat completions stream (for @test_chat_stream.js)\napp.post('/api/chatStream', async (c) => {\n try {\n let body = {};\n try {\n body = await c.req.json();\n } catch (_) {\n 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 = [{ type: 'browser_search' }],\n temperature,\n top_p,\n stop,\n } = body || {};\n\n const apiKey = serverApiKey || userApiKey || Deno.env.get(\"GROQ_API_KEY\");\n if (!apiKey) {\n return c.json({ error: 'No Groq API key available. Please provide your own key.' }, 400);\n }\n\n let finalMessages = Array.isArray(messages) && messages.length > 0\n ? messages\n : (typeof query === 'string' && query.trim().length > 0\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. 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 },\n { role: 'user', content: buildSearchPrompt(query, source, dateRange, language, offset) }\n ]\n : null);\n // Route logic: allow plain-text answers for explanatory queries\n try {\n if (typeof query === 'string' && query.trim()) {\n const route = await routeQueryMode(apiKey, query);\n console.log('>> [/api/chatStream] route:', route);\n // If a specific source is chosen, force list mode\n if (source) {\n finalMessages = [\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. 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 },\n { role: 'user', content: buildSearchPrompt(query, source, dateRange, language, offset) }\n ];\n console.log('>> [/api/chatStream] forced links mode due to selected source');\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 console.log('>> [/api/chatStream] router selected text mode');\n }\n }\n } catch (_) { /* ignore */ }\n if (!finalMessages) {\n finalMessages = [{\n role: 'user',\n content: 'go to https://news.ycombinator.com/ and give me the first 5 stories'\n }];\n }\n\n const payload = {\n model,\n messages: finalMessages,\n stream: true,\n reasoning_effort,\n tools,\n ...(temperature !== undefined ? { temperature } : {}),\n ...(top_p !== undefined ? { top_p } : {}),\n ...(stop !== undefined ? { stop } : {}),\n };\n\n const aggregates = await streamChatAndAggregate(apiKey, payload, { logSse: false });\n let results = [];\n try {\n const textContent = aggregates?.collapsed?.content || '';\n const reasoningText = aggregates?.collapsed?.reasoning || '';\n const toolText = collectToolTextFromArray(aggregates?.collapsed?.tools || []);\n if (toolText && toolText.trim()) {\n // Prefer URLs grounded in actual tool outputs\n results = await extractResultsFromToolOutputs(toolText, apiKey, language);\n }\n if ((!results || results.length === 0) && textContent && textContent.trim()) {\n // Fallback to general JSON repair on model text\n results = await extractOrRepairJsonResults(textContent, apiKey, language);\n }\n if ((!results || results.length === 0) && reasoningText && reasoningText.trim()) {\n // Final fallback: use reasoning channel content\n results = await extractOrRepairJsonResults(reasoningText, apiKey, language);\n }\n // Last-resort synthesis if still empty\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) {\n // best-effort parsing; ignore errors\n }\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// API: True SSE passthrough for chat completions stream (browser consumes incrementally)\napp.post('/api/chatStreamSSE', async (c) => {\n try {\n let body = {};\n try {\n body = await c.req.json();\n } catch (_) {\n body = {};\n }\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 = [{ type: 'browser_search' }],\n temperature,\n top_p,\n stop,\n } = body || {};\n\n const apiKey = serverApiKey || userApiKey || Deno.env.get(\"GROQ_API_KEY\");\n if (!apiKey) {\n return c.json({ error: 'No Groq API key available. Please provide your own key.' }, 400);\n }\n\n let finalMessages = Array.isArray(messages) && messages.length > 0\n ? messages\n : (typeof query === 'string' && query.trim().length > 0\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. 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 },\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 // Route logic for SSE streaming as well\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 // Force links prompt\n finalMessages = [\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. 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 },\n { role: 'user', content: buildSearchPrompt(query, source, dateRange, language, offset) }\n ];\n console.log('>> [/api/chatStreamSSE] forced links mode due to selected source');\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 console.log('>> [/api/chatStreamSSE] router selected text mode');\n }\n }\n } catch (_) { /* ignore */ }\n\n const payload = {\n model,\n messages: finalMessages,\n stream: true,\n reasoning_effort,\n tools,\n ...(temperature !== undefined ? { temperature } : {}),\n ...(top_p !== undefined ? { top_p } : {}),\n ...(stop !== undefined ? { stop } : {}),\n };\n\n const encoder = new TextEncoder();\n const stream = new ReadableStream({\n start: async (controller) => {\n try {\n const upstream = 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\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 reader = upstream.body.getReader();\n const decoder = new TextDecoder();\n let buffer = '';\n let collapsedContent = '';\n let collapsedReasoning = '';\n let collectedTools = [];\n\n // Initial comment to establish stream\n try { controller.enqueue(encoder.encode(': connected\\n\\n')); } catch (_) {}\n // Send route selection to client\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 // Keep-alive pings\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 let currentEvent = 'message';\n for (const line of lines) {\n if (line.startsWith('event: ')) {\n currentEvent = line.slice(7).trim();\n continue;\n }\n if (!line.startsWith('data: ')) continue;\n const data = line.slice(6);\n // Passthrough Groq SSE data lines\n controller.enqueue(encoder.encode('data: ' + data + '\\n\\n'));\n // Accumulate collapsed content to produce JSON results at end\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)) {\n collectedTools.push(...delta.executed_tools);\n }\n if (Array.isArray(delta.tool_calls)) {\n collectedTools.push(...delta.tool_calls);\n }\n } catch (_) {\n // ignore non-JSON payloads such as [DONE]\n }\n }\n }\n }\n // Signal end of stream – emit final structured results using LLM fixer\n try {\n let results = [];\n if (selectedRoute !== 'text') {\n try {\n const toolText = collectToolTextFromArray(collectedTools);\n const textForExtraction = (collapsedContent && collapsedContent.trim())\n ? collapsedContent\n : ((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 // Last-resort synthesis from all accumulated context\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 clearInterval(keepAliveId);\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// API endpoint for paper summarization\n// Removed legacy /api/summarize; summaries are handled by /api/search when a URL is provided\n\n// Corpus → Questions generator\napp.post('/api/corpus-to-questions', async (c) => {\n try {\n const body = await c.req.json().catch(() => ({}));\n const {\n userApiKey,\n corpusText,\n items,\n max_questions = 4,\n tags = []\n } = body || {};\n\n const apiKey = serverApiKey || userApiKey || Deno.env.get(\"GROQ_API_KEY\");\n if (!apiKey) {\n return c.json({ error: 'No Groq API key available. Please provide your own key.' }, 400);\n }\n\n // Normalize corpus lines\n let lines = [];\n if (Array.isArray(items)) {\n lines = items.map((s) => (typeof s === 'string' ? s : JSON.stringify(s)));\n } else if (typeof corpusText === 'string') {\n lines = corpusText.split(/\\r?\\n/);\n } else if (typeof body?.corpus === 'string') {\n lines = String(body.corpus).split(/\\r?\\n/);\n }\n lines = lines\n .map((s) => String(s || '').trim())\n .filter((s) => s.length > 0)\n .map((s) => (s.length > 400 ? s.slice(0, 400) : s));\n if (lines.length === 0) {\n return c.json({ error: 'No corpus lines provided' }, 400);\n }\n if (lines.length > 250) lines = lines.slice(0, 250);\n\n const extraTags = Array.isArray(tags)\n ? tags.map((t) => String(t).trim()).filter((t) => t.length > 0).slice(0, 6)\n : [];\n const maxItems = Math.max(1, Math.min(50, Number(max_questions) || 4));\n\n // Build LLM messages\n const system = (\n 'You transform a user\\'s raw short texts (tweets/SMS/IM/emails) into question prompts for a data collection app used to train a LoRA. ' +\n 'Return ONLY strict JSON with top-level object { \"items\": [ ... ] }. ' +\n 'Each item MUST include: id, label, instruction, tags, example, source_index. ' +\n 'Rules: ' +\n '1) id: short slug (lowercase letters/digits/hyphen/underscore only), unique. ' +\n '2) label: short human-readable name. ' +\n '3) instruction: a clear imperative describing what a user should write in that situation (not meta-commentary). ' +\n '4) tags: 1-4 general tags such as work, friends, planning, apology, announcement. Include provided extra_tags when relevant. ' +\n '5) example: a textbook-neutral response (formal, proper capitalization, no slang or emoji). Do NOT copy any input text. ' +\n '6) source_index: integer index of the MOST representative input line for this item. ' +\n '7) Cover diverse themes present. Avoid duplicates. Cap items to max_items. ' +\n 'Output JSON ONLY — no markdown, no explanations.'\n );\n\n const userPayload = {\n max_items: maxItems,\n extra_tags: extraTags,\n lines\n };\n\n const jsonSchema = {\n name: 'corpus_questions',\n schema: {\n type: 'object',\n additionalProperties: false,\n properties: {\n items: {\n type: 'array',\n minItems: 1,\n items: {\n type: 'object',\n additionalProperties: false,\n required: ['id', 'label', 'instruction', 'tags', 'example', 'source_index'],\n properties: {\n id: { type: 'string', minLength: 1 },\n label: { type: 'string', minLength: 1 },\n instruction: { type: 'string', minLength: 1 },\n tags: { type: 'array', items: { type: 'string' }, minItems: 0, uniqueItems: false },\n example: { type: 'string' },\n source_index: { type: 'integer', minimum: 0 }\n }\n }\n }\n },\n required: ['items']\n }\n };\n\n const response = await groqChatCompletion(apiKey, {\n model: (typeof body?.model === 'string' && body.model.trim()) ? body.model : settings.model,\n messages: [\n { role: 'system', content: system },\n { role: 'user', content: JSON.stringify(userPayload) }\n ],\n stream: false,\n reasoning_effort: 'low',\n temperature: 0.2,\n response_format: { type: 'json_schema', json_schema: jsonSchema }\n });\n\n const text = response?.choices?.[0]?.message?.content || '';\n let parsed = null;\n try {\n const stripped = text.replace(/^```json\\s*/i, '').replace(/```\\s*$/i, '');\n parsed = JSON.parse(stripped);\n } catch (_) {\n // Fallback attempt: try json_object mode\n try {\n const retry = await groqChatCompletion(apiKey, {\n model: (typeof body?.model === 'string' && body.model.trim()) ? body.model : settings.model,\n messages: [\n { role: 'system', content: system },\n { role: 'user', content: JSON.stringify(userPayload) }\n ],\n stream: false,\n reasoning_effort: 'low',\n temperature: 0.2,\n response_format: { type: 'json_object' }\n });\n const rtext = retry?.choices?.[0]?.message?.content || '';\n const stripped2 = rtext.replace(/^```json\\s*/i, '').replace(/```\\s*$/i, '');\n parsed = JSON.parse(stripped2);\n } catch (e2) {\n return c.json({ error: 'Model did not return valid JSON', raw: (text || '').slice(0, 1000) }, 500);\n }\n }\n\n const itemsOut = Array.isArray(parsed?.items) ? parsed.items : [];\n if (!Array.isArray(itemsOut) || itemsOut.length === 0) {\n return c.json({ error: 'No items produced', raw: text?.slice(0, 1000) }, 500);\n }\n\n // Helpers\n const sanitizeId = (v) => {\n const base = String(v || '').toLowerCase().replace(/[^a-z0-9_-]/g, '_');\n const clipped = base.slice(0, 64) || ('q_' + Math.random().toString(36).slice(2, 10));\n return clipped;\n };\n const ensureUnique = (arr) => {\n const used = new Set();\n for (const it of arr) {\n let id = sanitizeId(it.id);\n let ctr = 2;\n while (used.has(id)) { id = (sanitizeId(it.id) + '_' + ctr); ctr++; }\n used.add(id);\n it.id = id;\n }\n return arr;\n };\n\n const limited = itemsOut.slice(0, maxItems).map((it) => ({\n id: sanitizeId(it.id),\n label: String(it.label || '').trim() || 'item',\n instruction: String(it.instruction || '').trim(),\n tags: Array.isArray(it.tags) ? it.tags.map((t) => String(t).trim()).filter(Boolean) : [],\n example: String(it.example || '').trim(),\n source_index: Number.isInteger(it.source_index) ? it.source_index : 0,\n }));\n ensureUnique(limited);\n\n const questions = limited.map((it) => ({\n id: it.id,\n label: it.label,\n instruction: it.instruction,\n tags: Array.from(new Set([...(it.tags || []), ...extraTags])).slice(0, 6),\n example: it.example || ''\n }));\n const nowIso = new Date().toISOString();\n const answers = limited.map((it) => {\n const idx = Math.max(0, Math.min(lines.length - 1, Number(it.source_index) || 0));\n const raw = String(lines[idx] || '').trim();\n return { question_id: it.id, raw_response: raw, created_at: nowIso };\n }).filter((a) => a.raw_response.length > 0);\n\n return c.json({ questions, answers, count: questions.length });\n } catch (error) {\n console.error('corpus-to-questions error:', error);\n return c.json({ error: 'corpus-to-questions error: ' + error.message }, 500);\n }\n});\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;",[152],"77628674-7618-11f0-93b6-0224a6c84d84","jsonUtils.js","77628782-7618-11f0-93b6-0224a6c84d84",39,["D",1754850790220],"script","// 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. Return plain text only (no markdown fences). Remove any citations, numbers-in-brackets, line numbers, and artifacts. If unsure, say so briefly.'\n },\n { role: 'user', content: parts.join('\\n\\n') }\n ],\n stream: false\n })\n });\n if (!response.ok) {\n try { console.error('synthesizeTextFromContext error:', await response.text()); } catch (_) {}\n return '';\n }\n const data = await response.json();\n const text = data.choices?.[0]?.message?.content || '';\n return String(text || '').trim();\n } catch (_err) {\n return '';\n }\n}\n",[160],"6e925636-761e-11f0-98eb-0224a6c84d84","index.html","76adfe0c-7618-11f0-aa22-0224a6c84d84",44,["D",1754853352457],"\n\n\n \n \n Lorraine\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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Loading questions…

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\n \n\n \n\n \n\n \n \n \n\n",[168],"76a2f50c-7618-11f0-8008-0224a6c84d84","design_notes.md","76a2f638-7618-11f0-8008-0224a6c84d84",10,["D",1754850788963],"## Lorraine — Personal Voice Dataset Builder\n\nPurpose: Replace the existing research search UI with a simple, guided Q&A flow that displays many source wordings (formal, business, casual, social, etc.) and captures how the user would naturally say the same thing. Collected answers form a small dataset that can be used to fine‑tune a LoRA on the user's casual style.\n\nGoals\n- Present prompts from a JSON file (no model required to ask questions)\n- Capture answers via text input and optional voice dictation (Groq Whisper)\n- Keep the clean, minimal design from the current app (same fonts, spacing, Tailwind) and keep the API key UX\n- Export answers as JSON for downstream fine‑tuning\n\nData Model\n- Prompts JSON: array of items\n - id: string\n - label: short descriptor\n - instruction: what to do (e.g., \"Rewrite this in your style\")\n - source_text: the wording to adapt\n - tags: string[] (optional)\n- Answers (client-side):\n - question_id: string\n - answer_text: string\n - transcript_text?: string (if captured via Whisper)\n - created_at: ISO timestamp\n\nFrontend Flow\n- Load prompts from /data/questions.json\n- Show current prompt card (instruction + source text)\n- Provide a text area for \"Your version\"\n- Optional mic button to record and transcribe with Whisper; user can insert the transcript as their answer\n- Navigation: Previous / Next; progress indicator\n- Export: Download JSON of all answers\n- Persist API key (Groq) in localStorage; server key supported if present\n\nBackend Endpoints (Hono)\n- GET /data/questions.json → serve local JSON file (Val Town compatible loader)\n- POST /api/transcribe → forwards uploaded audio to Groq Whisper (`model: whisper-large-v3`) and returns `{ text }`\n- Existing /api/check-key retained for client key handling\n\nExport Format\n```json\n{\n \"app\": \"lorraine\",\n \"version\": 1,\n \"answers\": [\n {\n \"question_id\": \"q1\",\n \"answer_text\": \"...\",\n \"transcript_text\": \"...\",\n \"created_at\": \"2025-01-01T00:00:00.000Z\"\n }\n ]\n}\n```\n\nNotes / Future\n- Add prompt categories and filters\n- Add session save/restore in localStorage\n- Add CSV export and metadata like language/setting\n- Add batch microphone capture (hands‑free), and per‑answer audio blob export if needed\n\n\n",[175],"76e343c8-7618-11f0-aa22-0224a6c84d84","deno.lock","76e344a4-7618-11f0-aa22-0224a6c84d84",21,["D",1754850789432],"{\n \"version\": \"5\",\n \"specifiers\": {\n \"jsr:@std/dotenv@*\": \"0.225.5\",\n \"npm:@valtown/sdk@0.37.0\": \"0.37.0\",\n \"npm:badge-maker@*\": \"5.0.2\",\n \"npm:groq-sdk@*\": \"0.21.0\",\n \"npm:marked@*\": \"15.0.11\",\n \"npm:mime-types@2.1.35\": \"2.1.35\",\n \"npm:preact-render-to-string@*\": \"6.5.13_preact@10.27.0\",\n \"npm:pretty-ms@*\": \"9.2.0\"\n },\n \"jsr\": {\n \"@std/dotenv@0.225.5\": {\n \"integrity\": \"9ce6f9d0ec3311f74a32535aa1b8c62ed88b1ab91b7f0815797d77a6f60c922f\"\n }\n },\n \"npm\": {\n \"@types/node-fetch@2.6.12\": {\n \"integrity\": \"sha512-8nneRWKCg3rMtF69nLQJnOYUcbafYeFSjqkw3jCRLsqkWFlHaoQrr5mXmofFGOx3DKn7UfmBMyov8ySvLRVldA==\",\n \"dependencies\": [\n \"@types/node@22.15.15\",\n \"form-data\"\n ]\n },\n \"@types/node@18.19.118\": {\n \"integrity\": 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\"https://esm.sh/preact@10.27.0/jsx-runtime\": \"f33f69315b770515e473b14403cef9c49f3427ff61016041220e36505ab8cc68\",\n \"https://esm.town/v/std/utils@85-main/file/index.ts\": \"f7b4d1f95fb1ef1cbcb3bc0d2fe83194f18403c7d35115a9f066cba4ef6b84d0\",\n \"https://esm.town/v/std/utils@85-main/index.ts\": \"3d060a58ccd352517da960077ffd78b80c1051ca2117cb37adbff0365cb45efb\",\n \"https://esm.town/v/std/utils@85-main/parseImportMeta/project.ts\": \"1a47e75e21faf22b38fb07e6ead284b6a381a48970a39490e585507a8bb47bbf\",\n \"https://esm.town/v/std/utils@85-main/serve-file/index.ts\": \"1386c1fe12e8e9a41e3561b0a1e55f332bc559fe98fa81f99434b4f642275cd4\",\n \"https://esm.town/v/std/utils@85-main/test/index.tsx\": \"41fc8ccb29945e8cf65263dc61a6840decf9f62fb035be8d0651267ac84b573d\"\n }\n}\n",[182],"77803c32-7618-11f0-9a3e-0224a6c84d84","deno.json","77803cfa-7618-11f0-9a3e-0224a6c84d84",40,["D",1754850789182],"{\n \"tasks\": {\n \"serve\": \"deno serve --port 8002 --allow-read --allow-import --allow-env 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chat completion test with SSE parsing and aggregation\n// - Reads GROQ_API_KEY from environment (when run as CLI)\n// - Exports streamChatAndAggregate(apiKey, payload, { logSse }) to allow server reuse\n// - CLI: logs raw SSE lines and prints aggregated JSON at the end\n\nimport \"jsr:@std/dotenv/load\";\n\nconst API_URL = \"https://api.groq.com/openai/v1/chat/completions\";\n\nfunction getApiKey() {\n const key = (typeof Deno !== \"undefined\") ? Deno.env.get(\"GROQ_API_KEY\") : null;\n if (!key) {\n console.error(\"Missing GROQ_API_KEY in environment.\");\n }\n return key;\n}\n\nfunction buildPayload(userQuery) {\n const prompt = typeof userQuery === \"string\" && userQuery.trim().length > 0\n ? userQuery\n : \"Stream test: please emit a short response and demonstrate reasoning and any tool usage.\";\n\n return {\n messages: [\n {\n role: \"user\",\n content: prompt,\n },\n ],\n model: \"openai/gpt-oss-120b\",\n stream: true,\n reasoning_effort: \"medium\",\n tools: [\n {\n type: \"browser_search\",\n },\n ],\n };\n}\n\n// Utility: Parse one Groq SSE JSON line (string without the leading \"data: \")\nfunction parseGroqSseJsonLine(jsonStr) {\n try {\n const obj = JSON.parse(jsonStr);\n return obj;\n } catch (_err) {\n return null;\n }\n}\n\n// Utility: Normalize a parsed chunk into events and collapsed accumulators\nfunction applyChunkToAggregates(parsed, aggregates) {\n const { events, collapsed } = aggregates;\n\n const timestamp = Date.now();\n const baseInfo = {\n id: parsed.id,\n model: parsed.model,\n created: parsed.created,\n instance_id: parsed.instance_id,\n system_fingerprint: parsed.system_fingerprint,\n timestamp,\n };\n\n if (Array.isArray(parsed.choices) && parsed.choices.length > 0) {\n const choice = parsed.choices[0];\n const delta = choice?.delta || {};\n\n if (delta.role) {\n events.push({ type: \"role\", role: delta.role, ...baseInfo });\n }\n\n if (delta.reasoning) {\n events.push({ type: \"reasoning\", content: delta.reasoning, channel: delta.channel, ...baseInfo });\n collapsed.reasoning += delta.reasoning;\n }\n\n if (delta.content) {\n events.push({ type: \"content\", content: delta.content, ...baseInfo });\n collapsed.content += delta.content;\n }\n\n if (delta.executed_tools) {\n events.push({ type: \"executed_tools\", executed_tools: delta.executed_tools, ...baseInfo });\n for (const t of delta.executed_tools) {\n collapsed.tools.push({ kind: \"executed\", ...t, timestamp });\n }\n }\n\n if (delta.tool_calls) {\n events.push({ type: \"tool_calls\", tool_calls: delta.tool_calls, ...baseInfo });\n for (const t of delta.tool_calls) {\n collapsed.tools.push({ kind: \"call\", ...t, timestamp });\n }\n }\n }\n}\n\nexport async function streamChatAndAggregate(apiKey, payload, options = {}) {\n const { logSse = false } = options;\n\n const response = await fetch(API_URL, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n Authorization: `Bearer ${apiKey}`,\n },\n body: JSON.stringify(payload),\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`HTTP ${response.status} — ${text}`);\n }\n\n const reader = response.body?.getReader();\n const aggregates = {\n events: [],\n collapsed: { reasoning: \"\", content: \"\", tools: [] },\n };\n\n if (!reader) {\n try {\n const nonStream = await response.json();\n const content = nonStream?.choices?.[0]?.message?.content || \"\";\n if (content) {\n aggregates.events.push({ type: \"content\", content, timestamp: Date.now() });\n aggregates.collapsed.content = content;\n }\n } catch (_e) {\n // ignore\n }\n console.log(\"No readable stream; returning aggregates:\");\n console.log(JSON.stringify(aggregates, null, 2));\n return;\n }\n\n const decoder = new TextDecoder();\n let buffer = \"\";\n if (logSse) console.log(\"--- BEGIN SSE ---\");\n while (true) {\n const { done, value } = await reader.read();\n if (done) break;\n buffer += decoder.decode(value, { stream: true });\n\n // Split Server-Sent Events by double newlines\n const events = buffer.split(\"\\n\\n\");\n buffer = events.pop() || \"\";\n\n for (const evt of events) {\n if (!evt.trim()) continue;\n // Extract `data:` line(s)\n const lines = evt.split(\"\\n\");\n for (const line of lines) {\n if (line.startsWith(\"data: \")) {\n const data = line.slice(6);\n if (data === \"[DONE]\") {\n if (logSse) console.log(\"[DONE]\");\n break;\n }\n if (logSse) {\n // Log raw SSE packet\n console.log(\"data:\", data);\n }\n // Parse and aggregate\n const parsed = parseGroqSseJsonLine(data);\n if (!parsed) continue;\n applyChunkToAggregates(parsed, aggregates);\n }\n }\n }\n }\n if (logSse) {\n console.log(\"--- END SSE ---\");\n console.log(\"Aggregates:\");\n console.log(JSON.stringify(aggregates, null, 2));\n }\n return aggregates;\n}\n\n// Entry point\nif (import.meta.main) {\n const apiKey = getApiKey();\n if (!apiKey) Deno.exit(1);\n\n const userQuery = Deno.args?.[0] || \"\";\n const payload = buildPayload(userQuery);\n\n streamChatAndAggregate(apiKey, payload, { logSse: true })\n .then(() => console.log(\"Stream complete.\"))\n .catch((err) => {\n console.error(\"Stream failed:\", err);\n Deno.exit(1);\n });\n}\n\n\n",[196],"76948b52-7618-11f0-b5b6-0224a6c84d84","chatCompletion.js","76948c74-7618-11f0-b5b6-0224a6c84d84",8,["D",1754850788916],"// 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

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Sidebar helpers\n toggleSidebar() {\n this.sidebarOpen = !this.sidebarOpen;\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 createNewSavedSearch() {\n const title = (this.searchQuery && this.searchQuery.trim()) || 'Untitled search';\n const id = 's-' + Date.now();\n this.savedSearches = [{ id, title }, ...this.savedSearches];\n this.activeSearchId = id;\n },\n selectSavedSearch(id) {\n this.activeSearchId = id;\n const s = this.savedSearches.find(x => x.id === id);\n if (s) {\n this.searchQuery = s.title;\n }\n // Close sidebar on mobile\n this.sidebarOpen = false;\n },\n\n async checkServerKey() {\n try {\n const response = await fetch('/api/check-key');\n const data = await response.json();\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 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 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 \n if (this.selectedSource === 'custom' && this.customSource) {\n return this.customSource;\n }\n \n return sourceMap[this.selectedSource] || this.selectedSource;\n },\n\n // Internationalization system\n get i18n() {\n const translations = {\n 'english': {\n // Main headers\n title: '(re)Search',\n subtitle: 'Search the web and academic sources with multilingual summaries',\n \n // API Key section\n apiKey: 'API Key:',\n change: 'Change',\n clear: 'Clear',\n getKeyHere: 'Get your free key here',\n \n // Form labels\n language: 'language',\n researchQuery: 'search query',\n dateRange: 'Choose a date range (optional)',\n source: 'Choose a source (optional)',\n \n // Form placeholders\n enterTopic: 'Enter your research topic...',\n customSource: 'e.g., Nature, Science, Cell, Hacker News...',\n customSourceOption: 'Custom 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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 \n // Error messages\n pleaseAddApiKey: 'please add api key',\n pleaseEnterQuery: 'please enter a search query',\n \n // Summary\n summary: 'Summary:'\n },\n 'french': {\n title: '(re)Recherche',\n subtitle: 'Rechercher dans plusieurs bases de données académiques avec des résumés multilingues',\n \n apiKey: 'Clé API :',\n change: 'Modifier',\n clear: 'Effacer',\n getKeyHere: 'Obtenez votre clé gratuite ici',\n \n language: 'langue',\n researchQuery: 'requête de recherche',\n dateRange: 'Choisir une plage de dates (facultative)',\n source: 'Choisir une source (facultative)',\n \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 \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 \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 \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 \n // Loading message templates\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 \n pleaseAddApiKey: 'veuillez ajouter la clé api',\n pleaseEnterQuery: 'veuillez entrer une requête de recherche',\n \n summary: 'Résumé :'\n },\n 'spanish': {\n title: '(re)Buscar',\n subtitle: 'Buscar en múltiples bases de datos académicas con resúmenes multilingües',\n \n apiKey: 'Clave API:',\n change: 'Cambiar',\n clear: 'Limpiar',\n getKeyHere: 'Obtén tu clave gratuita aquí',\n \n language: 'idioma',\n researchQuery: 'consulta de investigación',\n dateRange: 'Elegir un rango de fechas (opcional)',\n source: 'Elegir una fuente (opcional)',\n \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 \n lastMonth: 'Último mes',\n last3Months: 'Últimos 3 meses',\n last6Months: 'Últimos 6 meses',\n lastYear: 'Último año',\n allTime: 'Todo el tiempo',\n \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 \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 \n // Loading message templates\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 \n pleaseAddApiKey: 'por favor agrega clave api',\n pleaseEnterQuery: 'por favor ingresa una consulta de búsqueda',\n \n summary: 'Resumen:'\n },\n 'german': {\n title: '(re)Suchen',\n subtitle: 'Durchsuchen Sie mehrere akademische Datenbanken mit mehrsprachigen Zusammenfassungen',\n \n apiKey: 'API-Schlüssel:',\n change: 'Ändern',\n clear: 'Löschen',\n getKeyHere: 'Holen Sie sich Ihren kostenlosen Schlüssel hier',\n \n language: 'sprache',\n researchQuery: 'suchanfrage',\n dateRange: 'Datumsbereich wählen (optional)',\n source: 'Quelle wählen (optional)',\n \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 \n lastMonth: 'Letzter Monat',\n last3Months: 'Letzte 3 Monate',\n last6Months: 'Letzte 6 Monate',\n lastYear: 'Letztes Jahr',\n allTime: 'Alle Zeit',\n \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 \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 \n // Loading message templates\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 += ` (${dateRange})`;\n return msg + '...';\n },\n \n pleaseAddApiKey: 'bitte api-schlüssel hinzufügen',\n pleaseEnterQuery: 'bitte suchanfrage eingeben',\n \n summary: 'Zusammenfassung:'\n },\n 'japanese': {\n title: '(re)検索',\n subtitle: '多言語要約付きの複数の学術データベースを検索',\n \n apiKey: 'APIキー:',\n change: '変更',\n clear: 'クリア',\n getKeyHere: '無料キーを取得する',\n \n language: '言語',\n researchQuery: '研究クエリ',\n dateRange: '日付範囲を選択 (任意)',\n source: 'ソースを選択 (任意)',\n \n enterTopic: '研究トピックを入力...',\n customSource: '例：Nature、Science、Cell...',\n customSourceOption: 'カスタムソース...',\n chooseDateRange: '日付範囲を選択 (任意)',\n chooseSource: 'ソースを選択 (任意)',\n \n lastMonth: '先月',\n last3Months: '過去3ヶ月',\n last6Months: '過去6ヶ月',\n lastYear: '昨年',\n allTime: '全期間',\n \n search: '(re)検索',\n searching: '(re)検索中',\n streaming: 'ストリーミング中...',\n searchMore: '(再)(再)検索',\n summarize: '要約',\n analyzing: '分析中...',\n openPaper: '開く',\n \n foundResults: '見つかった',\n results: '件の結果',\n loading: '検索中',\n loadingMore: 'より多くの結果を読み込み中',\n aiAnalyzing: 'AIが論文を分析中...',\n analysisTime: '論文の長さによって10〜30秒かかることがあります',\n noResultsOrError: '結果が見つからないか、サーバーエラーが発生しました。',\n \n // Loading message templates\n searchingTemplate: (source, query, dateRange) => {\n let msg = `${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 += `(${dateRange})`;\n return msg + '...';\n },\n \n pleaseAddApiKey: 'apiキーを追加してください',\n pleaseEnterQuery: '検索クエリを入力してください',\n \n summary: '要約:'\n },\n 'korean': {\n title: '(re)검색',\n subtitle: '다국어 요약과 함께 여러 학술 데이터베이스 검색',\n \n apiKey: 'API 키:',\n change: '변경',\n clear: '지우기',\n getKeyHere: '여기서 무료 키 받기',\n \n language: '언어',\n researchQuery: '연구 쿼리',\n dateRange: '날짜 범위 선택 (선택 사항)',\n source: '소스 선택 (선택 사항)',\n \n enterTopic: '연구 주제를 입력하세요...',\n customSource: '예: Nature, Science, Cell...',\n customSourceOption: '사용자 정의 소스...',\n chooseDateRange: '날짜 범위 선택 (선택 사항)',\n chooseSource: '소스 선택 (선택 사항)',\n \n lastMonth: '지난 달',\n last3Months: '지난 3개월',\n last6Months: '지난 6개월',\n lastYear: '작년',\n allTime: '전체 기간',\n \n search: '(re)검색',\n searching: '(re)검색 중',\n streaming: '스트리밍 중...',\n searchMore: '(재)(재)검색',\n summarize: '요약',\n analyzing: '분석 중...',\n openPaper: '열기',\n \n foundResults: '발견된',\n results: '개 결과',\n loading: '검색 중',\n loadingMore: '더 많은 결과 로딩 중',\n aiAnalyzing: 'AI가 논문을 분석 중...',\n analysisTime: '논문 길이에 따라 10-30초가 걸릴 수 있습니다',\n noResultsOrError: '결과가 없거나 서버 오류가 발생했습니다.',\n \n // Loading message templates\n searchingTemplate: (source, query, dateRange) => {\n let msg = `${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 += ` (${dateRange})`;\n return msg + '...';\n },\n \n pleaseAddApiKey: 'api 키를 추가해 주세요',\n pleaseEnterQuery: '검색 쿼리를 입력해 주세요',\n \n summary: '요약:'\n },\n 'chinese': {\n title: '(re)搜索',\n subtitle: '搜索多个学术数据库并提供多语言摘要',\n \n apiKey: 'API密钥:',\n change: '更改',\n clear: '清除',\n getKeyHere: '在此获取免费密钥',\n \n language: '语言',\n researchQuery: '研究查询',\n dateRange: '选择日期范围 (可选)',\n source: '选择来源 (可选)',\n \n enterTopic: '输入您的研究主题...',\n customSource: '例如：Nature、Science、Cell...',\n customSourceOption: '自定义来源...',\n chooseDateRange: '选择日期范围 (可选)',\n chooseSource: '选择来源 (可选)',\n \n lastMonth: '上个月',\n last3Months: '最近3个月',\n last6Months: '最近6个月',\n lastYear: '去年',\n allTime: '全部时间',\n \n search: '(re)搜索',\n searching: '(re)搜索中',\n streaming: '流式传输中...',\n searchMore: '(再)(再)搜索',\n summarize: '总结',\n analyzing: '分析中...',\n openPaper: '打开',\n \n foundResults: '找到',\n results: '个结果',\n loading: '搜索中',\n loadingMore: '加载更多结果',\n aiAnalyzing: 'AI正在分析论文...',\n analysisTime: '根据论文长度，这可能需要10-30秒',\n noResultsOrError: '未找到结果或发生服务器错误。',\n \n // Loading message templates\n searchingTemplate: (source, query, dateRange) => {\n let msg = `正在${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 \n pleaseAddApiKey: '请添加api密钥',\n pleaseEnterQuery: '请输入搜索查询',\n \n summary: '摘要:'\n },\n 'portuguese': {\n title: '(re)Pesquisar',\n subtitle: 'Pesquise em múltiplas bases de dados acadêmicas com resumos multilíngues',\n \n apiKey: 'Chave API:',\n change: 'Alterar',\n clear: 'Limpar',\n getKeyHere: 'Obtenha sua chave gratuita aqui',\n \n language: 'idioma',\n researchQuery: 'consulta de pesquisa',\n dateRange: 'Escolher intervalo de datas (opcional)',\n source: 'Escolher fonte (opcional)',\n \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 \n lastMonth: 'Último mês',\n last3Months: 'Últimos 3 meses',\n last6Months: 'Últimos 6 meses',\n lastYear: 'Último ano',\n allTime: 'Todo o tempo',\n \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 \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 \n // Loading message templates\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 += ` (${dateRange})`;\n return msg + '...';\n },\n \n pleaseAddApiKey: 'por favor adicione chave api',\n pleaseEnterQuery: 'por favor digite uma consulta de pesquisa',\n \n summary: 'Resumo:'\n }\n };\n \n return translations[this.selectedLanguage] || translations['english'];\n },\n\n getSummaryTitle() {\n return this.i18n.summary;\n },\n\n getSearchButtonText() {\n return `${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 const dateRangeMap = {\n '1month': this.i18n.lastMonth.toLowerCase(),\n '3months': this.i18n.last3Months.toLowerCase(),\n '6months': this.i18n.last6Months.toLowerCase(),\n '1year': this.i18n.lastYear.toLowerCase()\n };\n return dateRangeMap[this.dateRange] || '';\n },\n\n getActualSearchSource() {\n if (this.selectedSource === 'custom' && this.customSource) {\n return `on ${this.customSource}`;\n } else if (this.selectedSource === 'pubmed') {\n return 'PubMed';\n } else if (this.selectedSource === 'biorxiv') {\n return 'bioRxiv';\n } else if (this.selectedSource === 'arxiv') {\n return 'arXiv';\n } else if (this.selectedSource === 'medrxiv') {\n return 'medRxiv';\n } else if (this.selectedSource === 'researchgate') {\n return 'ResearchGate';\n } else if (this.selectedSource === 'google scholar') {\n return 'Google Scholar';\n } else {\n return '';\n }\n },\n\n getActualSearchSourceName() {\n if (this.selectedSource === 'custom' && this.customSource) {\n return this.customSource;\n } else if (this.selectedSource === 'pubmed') {\n return 'PubMed';\n } else if (this.selectedSource === 'biorxiv') {\n return 'bioRxiv';\n } else if (this.selectedSource === 'arxiv') {\n return 'arXiv';\n } else if (this.selectedSource === 'medrxiv') {\n return 'medRxiv';\n } else if (this.selectedSource === 'researchgate') {\n return 'ResearchGate';\n } else if (this.selectedSource === 'google scholar') {\n return 'Google Scholar';\n } else if (this.selectedSource === 'hacker news') {\n return 'Hacker News';\n } else if (this.selectedSource === 'reddit') {\n return 'Reddit';\n } else if (this.selectedSource === 'news') {\n return 'News';\n } else {\n return '';\n }\n },\n\n handleSourceChange() {\n // Clear custom source when switching away from custom\n if (this.selectedSource !== 'custom') {\n this.customSource = '';\n }\n },\n\n startTypewriter() {\n if (this.hasUserInteracted) return;\n \n this.typewriterActive = true;\n const translations = [\n 'machine learning', // English\n 'apprentissage automatique', // French\n 'maschinelles lernen', // German\n 'aprendizaje automático', // Spanish\n '機械学習', // Japanese\n '기계 학습', // Korean\n '机器学习', // Chinese\n 'aprendizado de máquina' // Portuguese\n ];\n \n this.typewriterCycle(translations);\n },\n\n typewriterCycle(translations) {\n if (this.hasUserInteracted || !this.typewriterActive) return;\n \n // Clear any existing timeouts first\n this.clearAllTimeouts();\n \n const currentText = translations[this.currentLanguageIndex];\n this.typeText(currentText, () => {\n // Wait 2 seconds after completing the word, then move to next language\n const timeout = setTimeout(() => {\n if (this.hasUserInteracted || !this.typewriterActive) return;\n \n this.currentLanguageIndex = (this.currentLanguageIndex + 1) % translations.length;\n this.typewriterCycle(translations);\n }, 2000); // Reduced from 4000ms to 2000ms\n this.typewriterTimeouts.push(timeout);\n });\n },\n\n typeText(text, onComplete) {\n if (this.hasUserInteracted || !this.typewriterActive) return;\n \n // Clear any existing timeouts and reset\n this.clearAllTimeouts();\n this.isTyping = true;\n this.currentCharIndex = 0;\n this.searchQuery = '';\n \n const typeNextChar = () => {\n if (this.hasUserInteracted || !this.typewriterActive) {\n this.isTyping = false;\n return;\n }\n \n if (this.currentCharIndex < text.length) {\n this.searchQuery = text.substring(0, this.currentCharIndex + 1);\n this.currentCharIndex++;\n const timeout = setTimeout(typeNextChar, 80); // Slightly faster typing\n this.typewriterTimeouts.push(timeout);\n } else {\n this.isTyping = false;\n if (onComplete) onComplete();\n }\n };\n \n typeNextChar();\n },\n\n clearAllTimeouts() {\n this.typewriterTimeouts.forEach(timeout => clearTimeout(timeout));\n this.typewriterTimeouts = [];\n },\n\n stopTypewriter() {\n this.hasUserInteracted = true;\n this.typewriterActive = false;\n this.clearAllTimeouts();\n this.isTyping = false;\n // Save the current typewriter text for search messages\n this.lastTypewriterText = this.searchQuery;\n },\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 // Clear previous results immediately when user initiates a new search\n this.results = [];\n this.assistantContent = '';\n // Stop typewriter immediately to freeze current text\n this.stopTypewriter();\n \n // Clear any existing error message\n this.errorMessage = '';\n \n // Check if button should be disabled and show appropriate error\n if (!this.searchQuery.trim()) {\n this.errorMessage = this.i18n.pleaseEnterQuery;\n return;\n }\n \n if (!this.hasServerKey && !this.userApiKey) {\n this.errorMessage = this.i18n.pleaseAddApiKey;\n return;\n }\n \n // If all checks pass, proceed with search\n this.searchResearch();\n },\n \n async searchResearch(loadMore = false) {\n console.log('🔍 Search triggered with query:', this.searchQuery, 'loadMore:', loadMore);\n if (!this.searchQuery.trim()) return;\n \n // Stop typewriter immediately and freeze the search text\n this.stopTypewriter();\n \n // Check if API key is available\n if (!this.hasServerKey && !this.userApiKey) {\n this.errorMessage = 'Please provide a Groq API key to search.';\n return;\n }\n \n if (loadMore) {\n this.isLoadingMore = true;\n } else {\n this.isSearching = true;\n this.errorMessage = '';\n this.results = [];\n this.assistantContent = '';\n this.currentOffset = 0;\n this.hasMoreResults = true;\n this.hasSearched = false;\n\n // Reset thinking trace for a brand new search\n this.traceEvents = [];\n this.expandedToolMap = {};\n this.traceExpanded = false;\n this.streamAggregates = { events: [], collapsed: { reasoning: '', content: '', tools: [] } };\n this.copyEventsText = 'copy json';\n if (this.copyEventsTimeoutId) {\n clearTimeout(this.copyEventsTimeoutId);\n this.copyEventsTimeoutId = null;\n }\n this.queueScrollToBottom();\n }\n\n // Start the elapsed timer\n this.startTimer();\n\n try {\n const response = await fetch('/api/search', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n },\n body: JSON.stringify({\n query: this.searchQuery,\n dateRange: this.dateRange,\n source: this.selectedSource === 'custom' ? this.customSource : this.selectedSource,\n language: this.selectedLanguage,\n userApiKey: this.userApiKey,\n offset: this.currentOffset\n })\n });\n\n if (!response.ok) throw new Error('Search failed: ' + response.statusText);\n \n const data = await response.json();\n \n if (data.error) {\n this.errorMessage = data.error;\n } else {\n const newResults = data.results || [];\n // Save assistant content and route for fallback/display\n this.assistantContent = (data.assistantContent && typeof data.assistantContent === 'string') ? data.assistantContent : '';\n this.route = data.route || 'links';\n if (loadMore) {\n this.results = [...this.results, ...newResults];\n } else {\n this.results = newResults;\n }\n \n // Update pagination state\n this.currentOffset += newResults.length;\n this.hasMoreResults = newResults.length >= 5; // Assume no more results if we got less than 5\n }\n } catch (error) {\n this.errorMessage = 'Error searching research databases: ' + error.message;\n } finally {\n this.isSearching = false;\n this.isLoadingMore = false;\n // Stop and freeze the timer\n this.stopTimer();\n this.hasSearched = true;\n }\n },\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 response = await fetch('/api/search', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n },\n body: JSON.stringify({\n url,\n title,\n language: this.selectedLanguage,\n userApiKey: this.userApiKey\n })\n });\n\n if (!response.ok) throw new Error('Summary failed: ' + response.statusText);\n \n const data = await response.json();\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 // Clear previous results immediately when user initiates streaming\n this.results = [];\n this.streamError = '';\n this.isStreaming = true;\n this.hasSearched = false;\n this.streamAggregates = { events: [], collapsed: { reasoning: '', content: '', tools: [] } };\n this.traceEvents = [];\n this.expandedToolMap = {};\n this.assistantContent = '';\n this.queueScrollToBottom();\n // Start elapsed timer for streaming\n this.startTimer();\n try {\n const response = await fetch('/api/chatStreamSSE', {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({\n userApiKey: this.userApiKey,\n // Send structured search params; server will build the prompt for streaming\n query: this.searchQuery && this.searchQuery.trim() ? this.searchQuery.trim() : undefined,\n dateRange: this.dateRange,\n source: this.selectedSource === 'custom' ? this.customSource : this.selectedSource,\n language: this.selectedLanguage,\n offset: this.currentOffset\n })\n });\n\n if (!response.ok || !response.body) {\n let errText = '';\n try { errText = await response.text(); } catch (_) {}\n throw new Error(errText || response.statusText);\n }\n\n const decoder = new TextDecoder();\n const reader = response.body.getReader();\n let buffer = '';\n\n const pushOrAppend = (kind, text) => {\n if (!text) return;\n const last = this.traceEvents[this.traceEvents.length - 1];\n if (last && last.kind === kind) {\n last.text += text;\n } else {\n this.traceEvents.push({ kind, text });\n }\n this.queueScrollToBottom();\n };\n const pushTool = (tool) => {\n const name = tool.name || tool.tool || tool.function?.name || tool.id || 'tool';\n this.traceEvents.push({ kind: 'tool', name, id: tool.id, data: tool });\n this.queueScrollToBottom();\n };\n\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 let currentEvent = 'message';\n for (const line of lines) {\n if (line.startsWith('event: ')) {\n currentEvent = line.slice(7).trim();\n continue;\n }\n if (!line.startsWith('data: ')) continue;\n const data = line.slice(6);\n if (data === '[DONE]') {\n break;\n }\n let parsed = null;\n try { parsed = JSON.parse(data); } catch (_) { parsed = null; }\n\n if (currentEvent === 'results') {\n if (parsed && Array.isArray(parsed.results)) {\n this.results = parsed.results;\n this.currentOffset = this.results.length;\n this.hasMoreResults = false;\n }\n continue;\n }\n\n // Fallback: accept arrays or `{ results: [...] }` without explicit event name\n if (parsed && Array.isArray(parsed.results)) {\n this.results = parsed.results;\n this.currentOffset = this.results.length;\n this.hasMoreResults = false;\n continue;\n }\n if (Array.isArray(parsed)) {\n this.results = parsed;\n this.currentOffset = this.results.length;\n this.hasMoreResults = false;\n continue;\n }\n\n if (!parsed) continue;\n const choice = Array.isArray(parsed.choices) ? parsed.choices[0] : null;\n const delta = choice?.delta || {};\n if (delta.reasoning && delta.channel) {\n pushOrAppend('reasoning', delta.reasoning);\n this.streamAggregates.collapsed.reasoning += delta.reasoning;\n }\n if (delta.content) {\n pushOrAppend('content', delta.content);\n this.streamAggregates.collapsed.content += delta.content;\n }\n if (Array.isArray(delta.executed_tools)) {\n for (const t of delta.executed_tools) {\n pushTool(t);\n this.streamAggregates.collapsed.tools.push({ kind: 'executed', ...t, timestamp: Date.now() });\n }\n }\n if (Array.isArray(delta.tool_calls)) {\n for (const t of delta.tool_calls) {\n pushTool(t);\n this.streamAggregates.collapsed.tools.push({ kind: 'call', ...t, timestamp: Date.now() });\n }\n }\n }\n }\n }\n\n // Flush any remaining buffered event at EOF (e.g., final 'results')\n try {\n const leftover = (buffer || '').trim();\n if (leftover) {\n const events = (leftover + '\\n\\n').split('\\n\\n');\n for (const evt of events) {\n if (!evt || !evt.trim()) continue;\n const lines = evt.split('\\n');\n let currentEvent = 'message';\n for (const line of lines) {\n if (line.startsWith('event: ')) {\n currentEvent = line.slice(7).trim();\n continue;\n }\n if (!line.startsWith('data: ')) continue;\n const data = line.slice(6);\n if (data === '[DONE]') continue;\n let parsed = null;\n try { parsed = JSON.parse(data); } catch (_) { parsed = null; }\n if (currentEvent === 'results') {\n if (parsed && Array.isArray(parsed.results)) {\n this.results = parsed.results;\n this.currentOffset = this.results.length;\n this.hasMoreResults = false;\n }\n continue;\n }\n if (parsed && Array.isArray(parsed.results)) {\n this.results = parsed.results;\n this.currentOffset = this.results.length;\n this.hasMoreResults = false;\n continue;\n }\n if (Array.isArray(parsed)) {\n this.results = parsed;\n this.currentOffset = this.results.length;\n this.hasMoreResults = false;\n continue;\n }\n if (!parsed) continue;\n const choice = Array.isArray(parsed.choices) ? parsed.choices[0] : null;\n const delta = choice?.delta || {};\n if (delta.reasoning) {\n pushOrAppend('reasoning', delta.reasoning);\n this.streamAggregates.collapsed.reasoning += delta.reasoning;\n }\n if (delta.content) {\n pushOrAppend('content', delta.content);\n this.streamAggregates.collapsed.content += delta.content;\n }\n if (Array.isArray(delta.executed_tools)) {\n for (const t of delta.executed_tools) {\n pushTool(t);\n this.streamAggregates.collapsed.tools.push({ kind: 'executed', ...t, timestamp: Date.now() });\n }\n }\n if (Array.isArray(delta.tool_calls)) {\n for (const t of delta.tool_calls) {\n pushTool(t);\n this.streamAggregates.collapsed.tools.push({ kind: 'call', ...t, timestamp: Date.now() });\n }\n }\n }\n }\n }\n } catch (_) { /* no-op */ }\n\n this.hasMoreResults = false;\n } catch (e) {\n this.streamError = e.message || String(e);\n } finally {\n this.isStreaming = false;\n this.hasSearched = true;\n // Stop and freeze the timer at end of streaming\n this.stopTimer();\n // Fallback: if no results and we have assistant content from stream, show it\n try {\n if ((this.results || []).length === 0) {\n const c = this.streamAggregates?.collapsed?.content || '';\n if (c && c.trim()) this.assistantContent = c;\n // If assistant content is actually JSON with results, adopt it\n const maybe = (this.assistantContent || '').trim();\n if (maybe) {\n const stripped = maybe.replace(/^```json\\s*/i, '').replace(/```\\s*$/i, '');\n try {\n const parsed = JSON.parse(stripped);\n if (parsed && Array.isArray(parsed.results) && parsed.results.length > 0) {\n this.results = parsed.results;\n this.currentOffset = this.results.length;\n this.hasMoreResults = false;\n this.assistantContent = '';\n }\n } catch (_) { /* ignore */ }\n }\n }\n } catch (_) {}\n }\n },\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 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 };\n}\n\n\n",[],[242,378],"6e972e36-761e-11f0-8f5e-0224a6c84d84","lorraineApp.js","76b2e976-7618-11f0-8008-0224a6c84d84",45,["D",1754853352457],"export default function lorraineApp() {\n return {\n // Shared/global\n hasServerKey: true,\n userApiKey: '',\n apiKeyInput: '',\n selectedLanguage: 'english',\n // Job naming\n jobName: '',\n jobInput: '',\n\n // UI state (reuse layout from research app)\n sidebarOpen: false,\n sidebarCollapsed: false,\n sidebarTransitioning: false,\n sidebarAnimMs: 300,\n\n // Lorraine state\n questions: [],\n currentIndex: 0,\n answers: {}, // { [id]: { answer_text, transcript_text, created_at } }\n showNeutral: false,\n answeredMap: {}, // { [id]: true }\n loadingQuestions: false,\n errorMessage: '',\n isTranscribing: false,\n recorder: null,\n mediaStream: null,\n chunks: [],\n answerBuffer: '',\n // Jobs store\n jobStore: {}, // { [jobName]: exportPayload }\n jobsArray: [],\n // Import/Export & Storage\n importJsonOpen: false,\n importJsonBuffer: '',\n importError: '',\n importSuccess: '',\n\n // Inline JSON editor for the full questions set\n showJsonEditor: false,\n jsonEditBuffer: '',\n jsonEditError: '',\n jsonEditSuccess: '',\n\n // Inline editor for user responses (answers)\n showAnswersEditor: false,\n answersEditBuffer: '',\n answersEditError: '',\n answersEditSuccess: '',\n\n // Corpus → Questions tool\n showCorpusTool: false,\n corpusInput: '',\n corpusMaxQuestions: 4,\n corpusTags: '',\n corpusGenerating: false,\n corpusStatus: '',\n corpusError: '',\n\n // Minimal compatibility fields for legacy research UI fragments in index.html\n isSearching: false,\n isLoadingMore: false,\n isStreaming: false,\n hasSearched: false,\n results: [],\n assistantContent: '',\n summaryStates: {},\n copyEventsText: 'copy json',\n traceEvents: [],\n expandedToolMap: {},\n traceExpanded: false,\n streamAggregates: { events: [], collapsed: { reasoning: '', content: '', tools: [] } },\n currentOffset: 0,\n hasMoreResults: false,\n // Search/typewriter/timer placeholders (not actively used in Lorraine mode)\n selectedSource: '',\n customSource: '',\n searchQuery: '',\n dateRange: '',\n lastTypewriterText: '',\n typewriterActive: false,\n hasUserInteracted: true,\n typewriterTimeouts: [],\n isTyping: false,\n currentLanguageIndex: 0,\n currentCharIndex: 0,\n timerStartMs: null,\n timerElapsedMs: 0,\n timerFrozenText: '',\n timerIntervalId: null,\n\n async init() {\n // Load API key from localStorage\n const storedApiKey = localStorage.getItem('groq_api_key');\n if (storedApiKey) this.userApiKey = storedApiKey;\n // Load job name from localStorage\n try {\n const storedJob = localStorage.getItem('lorraine_job_name');\n if (storedJob) { this.jobName = storedJob; this.jobInput = storedJob; }\n } catch (_) {}\n await this.checkServerKey();\n await this.loadQuestions();\n // Load jobs map\n try { this.loadJobsFromStorage(); this.refreshJobsArray(); } catch (_) {}\n // sync buffer when index changes\n try { this.$watch('currentIndex', () => { this.answerBuffer = this.currentAnswer; }); } catch (_) {}\n this.answerBuffer = this.currentAnswer;\n // Attempt to load saved answers (session first, then local)\n try { this.loadFromSessionStorage(); } catch (_) {}\n if (Object.keys(this.answers || {}).length === 0) {\n try { this.loadFromLocalStorage(); } catch (_) {}\n }\n // build answered map and move to a random question\n this.rebuildAnsweredMap();\n this.jumpToRandomUnanswered();\n },\n\n async checkServerKey() {\n try {\n const r = await fetch('/api/check-key');\n const j = await r.json();\n this.hasServerKey = j.hasServerKey;\n } catch (_) {\n this.hasServerKey = false;\n }\n },\n\n setApiKey() {\n if (this.apiKeyInput.trim()) {\n this.userApiKey = this.apiKeyInput.trim();\n localStorage.setItem('groq_api_key', this.userApiKey);\n this.apiKeyInput = '';\n }\n },\n setJobName() {\n const newName = (this.jobInput || '').trim();\n const oldName = this.jobName || '';\n if (!newName) return; // ignore empty\n\n // If renaming, migrate existing job entry to new key and remove old\n if (oldName && newName !== oldName) {\n try {\n const existed = this.jobStore && this.jobStore[oldName];\n if (existed) {\n const migrated = { ...existed, job: newName, updated_at: new Date().toISOString() };\n // Move entry\n this.jobStore[newName] = migrated;\n try { delete this.jobStore[oldName]; } catch (_) {}\n this.saveJobsToStorage();\n }\n } catch (_) {}\n }\n\n this.jobName = newName;\n try { localStorage.setItem('lorraine_job_name', this.jobName || ''); } catch (_) {}\n // If the inline responses editor is visible, refresh its buffer to reflect the new job\n try {\n if (this.showAnswersEditor) {\n this.answersEditBuffer = this.getExportJsonPretty();\n if (typeof this.$nextTick === 'function') {\n this.$nextTick(() => this.autoSizeAnswersTa());\n } else {\n setTimeout(() => this.autoSizeAnswersTa(), 0);\n }\n }\n } catch (_) {}\n // Persist updated export with job name\n try { this.saveToSessionStorage(); } catch (_) {}\n try { this.saveToLocalStorage(); } catch (_) {}\n try { this.saveActiveJob(); } catch (_) {}\n },\n changeApiKey() { this.userApiKey = ''; },\n clearApiKey() { this.userApiKey = ''; localStorage.removeItem('groq_api_key'); },\n get maskedApiKey() {\n if (!this.userApiKey) return '';\n const k = this.userApiKey;\n return k.substring(0, 8) + '*'.repeat(Math.max(0, k.length - 12)) + k.substring(k.length - 4);\n },\n\n // Load questions JSON\n async loadQuestions() {\n this.loadingQuestions = true;\n this.errorMessage = '';\n try {\n // Local override: use saved custom questions if present\n try {\n const override = localStorage.getItem('lorraine_custom_questions_v1');\n if (override) {\n const a = JSON.parse(override);\n if (Array.isArray(a) && a.length > 0) {\n this.questions = a;\n if (!this.questions.length) this.errorMessage = 'No questions available.';\n return;\n }\n }\n } catch (_) {}\n // Support selecting groups via URL: ?groups=work,friends\n const url = new URL(window.location.href);\n const groupParam = (url.searchParams.get('groups') || '').trim();\n let arr = [];\n // Try selected groups (simple schema) first\n if (groupParam) {\n try {\n const rGroups = await fetch('/data/questions/simple/by-groups.json?groups=' + encodeURIComponent(groupParam));\n if (rGroups.ok) {\n const a = await rGroups.json();\n if (Array.isArray(a)) arr = a;\n }\n } catch (_) {}\n }\n // Try aggregated next\n if (!Array.isArray(arr) || arr.length === 0) {\n try {\n const rAll = await fetch('/data/questions/simple.json');\n if (rAll.ok) {\n const a = await rAll.json();\n if (Array.isArray(a)) arr = a;\n }\n } catch (_) {}\n }\n // Fallback to base file\n if (!Array.isArray(arr) || arr.length === 0) {\n const r = await fetch('/data/questions.json');\n if (!r.ok) throw new Error('failed to load questions');\n const a = await r.json();\n if (Array.isArray(a)) arr = a;\n }\n if (Array.isArray(arr)) this.questions = arr;\n if (!this.questions.length) this.errorMessage = 'No questions available.';\n } catch (e) {\n this.errorMessage = 'Error loading questions: ' + (e?.message || String(e));\n } finally {\n this.loadingQuestions = false;\n }\n },\n\n // Toggle and manage inline JSON editor\n toggleJsonEditor() {\n this.showJsonEditor = !this.showJsonEditor;\n this.jsonEditError = '';\n this.jsonEditSuccess = '';\n if (this.showJsonEditor) {\n try { this.jsonEditBuffer = JSON.stringify(this.questions || [], null, 2); } catch (_) { this.jsonEditBuffer = '[]'; }\n }\n },\n saveJsonEdits() {\n this.jsonEditError = '';\n this.jsonEditSuccess = '';\n let parsed = null;\n try { parsed = JSON.parse(this.jsonEditBuffer || ''); } catch (e) {\n this.jsonEditError = 'invalid JSON';\n return;\n }\n if (!Array.isArray(parsed)) {\n this.jsonEditError = 'root must be an array';\n return;\n }\n for (const [i, q] of parsed.entries()) {\n if (!q || typeof q !== 'object') { this.jsonEditError = `item ${i+1} is not an object`; return; }\n if (!q.id || !q.label || !q.instruction || !Array.isArray(q.tags)) { this.jsonEditError = `item ${i+1} missing id/label/instruction/tags`; return; }\n }\n this.questions = parsed;\n try { localStorage.setItem('lorraine_custom_questions_v1', JSON.stringify(parsed)); } catch (_) {}\n this.rebuildAnsweredMap();\n this.currentIndex = 0;\n this.answerBuffer = this.currentAnswer;\n this.jsonEditSuccess = 'saved';\n try { this.jsonEditBuffer = JSON.stringify(this.questions || [], null, 2); } catch (_) {}\n },\n\n // Toggle and save the answers JSON editor\n toggleAnswersEditor() {\n this.showAnswersEditor = !this.showAnswersEditor;\n this.answersEditError = '';\n this.answersEditSuccess = '';\n if (this.showAnswersEditor) {\n try { this.answersEditBuffer = this.getExportJsonPretty(); } catch (_) { this.answersEditBuffer = '{\"answers\": []}'; }\n // Ensure autosize runs after the textarea becomes visible\n try {\n if (typeof this.$nextTick === 'function') {\n this.$nextTick(() => { this.autoSizeAnswersTa(); });\n } else {\n setTimeout(() => this.autoSizeAnswersTa(), 0);\n }\n } catch (_) {}\n }\n },\n saveAnswersEdits() {\n this.answersEditError = '';\n this.answersEditSuccess = '';\n let parsed = null;\n try { parsed = JSON.parse(this.answersEditBuffer || ''); } catch (e) {\n this.answersEditError = 'invalid JSON';\n return;\n }\n let list = [];\n if (parsed && Array.isArray(parsed)) list = parsed;\n else if (parsed && Array.isArray(parsed.answers)) list = parsed.answers;\n if (!Array.isArray(list)) { this.answersEditError = 'root must be an array or { answers: [...] }'; return; }\n\n const next = { ...this.answers };\n for (const item of list) {\n const qid = item?.question_id || item?.id;\n const text = item?.raw_response || item?.answer_text || item?.answer || '';\n if (!qid || !String(qid).trim()) continue;\n const existed = next[qid] || {};\n next[qid] = {\n ...existed,\n answer_text: text,\n transcript_text: item?.transcript_text || existed.transcript_text || null,\n created_at: existed.created_at || item?.created_at || new Date().toISOString()\n };\n }\n this.answers = next;\n this.rebuildAnsweredMap();\n // persist\n try { this.saveToSessionStorage(); } catch (_) {}\n try { this.saveToLocalStorage(); } catch (_) {}\n try { this.saveActiveJob(); } catch (_) {}\n this.answersEditSuccess = 'saved';\n try { this.answersEditBuffer = this.getExportJsonPretty(); } catch (_) {}\n // Re-autosize after updating content\n try { this.autoSizeAnswersTa(); } catch (_) {}\n },\n\n // Autosize responses textarea to content height\n autoSizeAnswersTa() {\n try {\n const ta = this.$refs && this.$refs.answersEditorTa;\n if (!ta) return;\n ta.style.height = 'auto';\n ta.style.height = (ta.scrollHeight + 2) + 'px';\n } catch (_) {}\n },\n\n // Navigation\n // Non-linear navigation\n get remainingIndices() {\n if (!Array.isArray(this.questions)) return [];\n const remain = [];\n for (let i = 0; i < this.questions.length; i++) {\n const q = this.questions[i];\n if (!q || !q.id) continue;\n if (!this.answeredMap[q.id]) remain.push(i);\n }\n return remain;\n },\n allDone() { return this.questions.length > 0 && this.remainingIndices.length === 0; },\n pickRandomIndex() {\n const pool = this.remainingIndices.length > 0 ? this.remainingIndices : (this.questions.map((_, i) => i));\n if (pool.length === 0) return 0;\n const r = Math.floor(Math.random() * pool.length);\n return pool[r];\n },\n jumpToRandomUnanswered() {\n const idx = this.pickRandomIndex();\n this.currentIndex = idx;\n this.answerBuffer = this.currentAnswer;\n },\n skipQuestion() {\n this.jumpToRandomUnanswered();\n },\n continueToNext() {\n // Ensure current answer is captured and marked\n const id = this.currentId;\n if (id) {\n const txt = (this.answerBuffer || '').trim();\n const prev = this.answers[id] || {};\n this.answers[id] = { ...prev, answer_text: this.answerBuffer || '', created_at: prev.created_at || new Date().toISOString() };\n if (txt) this.answeredMap[id] = true;\n else delete this.answeredMap[id];\n try { this.saveToSessionStorage(); } catch (_) {}\n try { this.saveToLocalStorage(); } catch (_) {}\n try { this.saveActiveJob(); } catch (_) {}\n }\n this.jumpToRandomUnanswered();\n },\n\n // Current question/answer\n get currentQuestion() { return this.questions[this.currentIndex] || null; },\n get currentId() { return this.currentQuestion?.id || null; },\n get currentAnswer() {\n const id = this.currentId; if (!id) return '';\n return this.answers[id]?.answer_text || '';\n },\n setCurrentAnswer(v) {\n const id = this.currentId; if (!id) return;\n const prev = this.answers[id] || {};\n const trimmed = (v || '').trim();\n this.answers[id] = { ...prev, answer_text: v, created_at: prev.created_at || new Date().toISOString() };\n this.answerBuffer = v;\n // mark answered if non-empty, else unmark\n if (trimmed) this.answeredMap[id] = true; else delete this.answeredMap[id];\n // autosave to both storages\n try { this.saveToSessionStorage(); } catch (_) {}\n try { this.saveToLocalStorage(); } catch (_) {}\n try { this.saveActiveJob(); } catch (_) {}\n },\n\n insertTranscriptIntoAnswer(text) {\n const id = this.currentId; if (!id) return;\n const prev = this.answers[id] || {};\n const merged = (prev.answer_text && prev.answer_text.trim())\n ? (prev.answer_text + '\\n' + text)\n : text;\n this.answers[id] = { ...prev, answer_text: merged, transcript_text: text, created_at: prev.created_at || new Date().toISOString() };\n this.answeredMap[id] = true;\n // autosave\n try { this.saveToSessionStorage(); } catch (_) {}\n try { this.saveToLocalStorage(); } catch (_) {}\n try { this.saveActiveJob(); } catch (_) {}\n },\n\n // Export answers (minimal response schema)\n getExportPayload() {\n const questions = Array.isArray(this.questions) ? this.questions : [];\n const questionById = Object.fromEntries(questions.map(q => [q.id, q]));\n const indexById = Object.fromEntries(questions.map((q, i) => [q.id, i]));\n const answers = Object.entries(this.answers || {}).map(([qid, a]) => {\n const q = questionById[qid] || {};\n return {\n question_id: qid,\n label: q.label || null,\n instruction: q.instruction || null,\n tags: Array.isArray(q.tags) ? q.tags : null,\n raw_response: a?.answer_text || '',\n created_at: a?.created_at || new Date().toISOString()\n };\n });\n // Stable sort answers by question order, then by id\n answers.sort((a, b) => {\n const ia = (a && a.question_id && (indexById[a.question_id] ?? 1e9)) || 1e9;\n const ib = (b && b.question_id && (indexById[b.question_id] ?? 1e9)) || 1e9;\n if (ia !== ib) return ia - ib;\n const sa = String(a?.question_id || '');\n const sb = String(b?.question_id || '');\n return sa.localeCompare(sb);\n });\n return { app: 'lorraine', version: 2, language: this.selectedLanguage, job: this.jobName || null, answers };\n },\n\n getExportJsonPretty() {\n try { return JSON.stringify(this.getExportPayload(), null, 2); } catch (_) { return '{}'; }\n },\n\n downloadAnswers() {\n const payload = this.getExportPayload();\n const blob = new Blob([JSON.stringify(payload, null, 2)], { type: 'application/json' });\n const url = URL.createObjectURL(blob);\n const a = document.createElement('a');\n a.href = url; a.download = 'lorraine_answers.json';\n document.body.appendChild(a); a.click(); a.remove();\n URL.revokeObjectURL(url);\n },\n\n // Download JSONL (prompt/completion schema)\n downloadAnswersJsonl() {\n try {\n const questionById = Object.fromEntries((this.questions || []).map(q => [q.id, q]));\n const lines = [];\n for (const [qid, a] of Object.entries(this.answers || {})) {\n const txt = (a && a.answer_text) ? String(a.answer_text).trim() : '';\n if (!txt) continue;\n const q = questionById[qid] || {};\n const instr = (q && q.instruction) ? String(q.instruction) : '';\n const ex = (q && q.example) ? String(q.example) : '';\n let prompt = 'Instructions: ' + instr;\n if (ex && ex.trim()) {\n prompt += '\\n\\nExample: ' + ex;\n }\n const obj = { prompt: prompt, completion: txt };\n lines.push(JSON.stringify(obj));\n }\n const data = lines.join('\\n');\n const blob = new Blob([data], { type: 'text/plain' });\n const url = URL.createObjectURL(blob);\n const a = document.createElement('a');\n a.href = url; a.download = 'lorraine_answers.jsonl';\n document.body.appendChild(a); a.click(); a.remove();\n URL.revokeObjectURL(url);\n } catch (_) {\n // no-op\n }\n },\n\n // Corpus tool helpers\n toggleCorpusTool() {\n this.showCorpusTool = !this.showCorpusTool;\n if (this.showCorpusTool) {\n this.corpusStatus = '';\n this.corpusError = '';\n }\n },\n parseTagsInput(text) {\n const raw = String(text || '').trim();\n if (!raw) return [];\n return raw.split(/[;,\\s]+/).map(s => s.trim()).filter(Boolean);\n },\n async generateFromCorpus() {\n try {\n this.corpusError = '';\n this.corpusStatus = '';\n if (!this.hasServerKey && !this.userApiKey) {\n this.corpusError = 'please add api key';\n return;\n }\n const maxQ = Math.max(1, Math.min(50, Number(this.corpusMaxQuestions) || 4));\n const body = {\n userApiKey: this.userApiKey || undefined,\n corpusText: this.corpusInput || '',\n max_questions: maxQ,\n tags: this.parseTagsInput(this.corpusTags),\n };\n this.corpusGenerating = true;\n const resp = await fetch('/api/corpus-to-questions', {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body)\n });\n if (!resp.ok) {\n const txt = await resp.text().catch(() => '');\n throw new Error(txt || ('HTTP ' + resp.status));\n }\n const data = await resp.json();\n const questions = Array.isArray(data?.questions) ? data.questions : [];\n const answers = Array.isArray(data?.answers) ? data.answers : [];\n if (questions.length === 0) {\n this.corpusError = 'no questions generated';\n return;\n }\n // Load questions into app and persist as custom set\n this.questions = questions;\n try { localStorage.setItem('lorraine_custom_questions_v1', JSON.stringify(questions)); } catch (_) {}\n // Import answers using existing importer\n try {\n this.importJsonBuffer = JSON.stringify({ answers }, null, 2);\n this.importAnswersFromJson();\n } catch (_) {}\n this.rebuildAnsweredMap();\n this.jumpToRandomUnanswered();\n this.corpusStatus = `generated ${questions.length} questions`;\n } catch (e) {\n this.corpusError = e?.message || String(e);\n } finally {\n this.corpusGenerating = false;\n }\n },\n\n async copyAnswersJson() {\n try {\n const json = this.getExportJsonPretty();\n await navigator.clipboard.writeText(json);\n this.importSuccess = 'copied';\n setTimeout(() => { this.importSuccess = ''; }, 2000);\n } catch (e) {\n this.importError = 'copy failed';\n setTimeout(() => { this.importError = ''; }, 3000);\n }\n },\n\n toggleImportArea() {\n this.importJsonOpen = !this.importJsonOpen;\n if (this.importJsonOpen) {\n this.importJsonBuffer = '';\n this.importError = '';\n this.importSuccess = '';\n }\n },\n\n importAnswersFromJson() {\n this.importError = '';\n this.importSuccess = '';\n let parsed = null;\n try {\n parsed = JSON.parse(this.importJsonBuffer || '');\n } catch (e) {\n this.importError = 'invalid JSON';\n return;\n }\n let list = [];\n if (parsed && Array.isArray(parsed)) {\n list = parsed;\n } else if (parsed && Array.isArray(parsed.answers)) {\n list = parsed.answers;\n }\n if (!Array.isArray(list) || list.length === 0) {\n this.importError = 'no answers found';\n return;\n }\n const next = { ...this.answers };\n for (const item of list) {\n const qid = item?.question_id || item?.id;\n const text = item?.raw_response || item?.answer_text || item?.answer || '';\n if (!qid || !String(qid).trim()) continue;\n if (!text || !String(text).trim()) continue;\n const existed = next[qid] || {};\n next[qid] = {\n ...existed,\n answer_text: text,\n transcript_text: item?.transcript_text || existed.transcript_text || null,\n created_at: existed.created_at || item?.created_at || new Date().toISOString()\n };\n }\n this.answers = next;\n this.rebuildAnsweredMap();\n // keep UI buffer in sync\n this.answerBuffer = this.currentAnswer;\n // save after import\n try { this.saveToSessionStorage(); } catch (_) {}\n try { this.saveToLocalStorage(); } catch (_) {}\n try { this.saveActiveJob(); } catch (_) {}\n this.importSuccess = 'loaded';\n setTimeout(() => { this.importSuccess = ''; }, 2000);\n },\n\n clearAnswers() {\n this.answers = {};\n this.answerBuffer = this.currentAnswer;\n try { sessionStorage.removeItem('lorraine_answers_v1'); } catch (_) {}\n try { localStorage.removeItem('lorraine_answers_v1'); } catch (_) {}\n try { this.saveActiveJob(); } catch (_) {}\n },\n\n saveToLocalStorage() {\n try { localStorage.setItem('lorraine_answers_v1', this.getExportJsonPretty()); } catch (_) {}\n },\n loadFromLocalStorage() {\n try {\n const raw = localStorage.getItem('lorraine_answers_v1');\n if (!raw) return;\n this.importJsonBuffer = raw;\n this.importAnswersFromJson();\n } catch (_) {}\n },\n saveToSessionStorage() {\n try { sessionStorage.setItem('lorraine_answers_v1', this.getExportJsonPretty()); } catch (_) {}\n },\n loadFromSessionStorage() {\n try {\n const raw = sessionStorage.getItem('lorraine_answers_v1');\n if (!raw) return;\n this.importJsonBuffer = raw;\n this.importAnswersFromJson();\n } catch (_) {}\n },\n // Jobs persistence and management\n loadJobsFromStorage() {\n try {\n const raw = localStorage.getItem('lorraine_jobs_v1');\n this.jobStore = raw ? JSON.parse(raw) : {};\n } catch (_) {\n this.jobStore = {};\n }\n },\n saveJobsToStorage() {\n try { localStorage.setItem('lorraine_jobs_v1', JSON.stringify(this.jobStore)); } catch (_) {}\n this.refreshJobsArray();\n },\n saveActiveJob() {\n try {\n const name = (this.jobName || '').trim();\n if (!name) return;\n const payload = this.getExportPayload();\n // Ensure unique by exact name only; overwrite same-name entry, do not create additional copies\n // Store only answers array (compact) and metadata to avoid nesting and simplify import\n this.jobStore[name] = {\n job: payload.job || name,\n language: payload.language,\n answers: Array.isArray(payload.answers) ? payload.answers : [],\n updated_at: new Date().toISOString()\n };\n this.saveJobsToStorage();\n } catch (_) {}\n },\n selectJob(name) {\n try {\n // Persist current job before switching\n try { this.saveActiveJob(); } catch (_) {}\n const j = this.jobStore && this.jobStore[name];\n if (!j) return;\n this.jobName = name;\n this.jobInput = name;\n try { localStorage.setItem('lorraine_job_name', name); } catch (_) {}\n if (j.language) this.selectedLanguage = j.language;\n // Replace current answers with the selected job's answers\n this.answers = {};\n this.answeredMap = {};\n // Accept either array or { answers: [...] } in job payloads\n const payloadForImport = Array.isArray(j?.answers) ? { answers: j.answers } : j;\n this.importJsonBuffer = JSON.stringify(payloadForImport);\n this.importError = '';\n this.importSuccess = '';\n this.importAnswersFromJson();\n this.rebuildAnsweredMap();\n this.answerBuffer = this.currentAnswer;\n // Update inline responses editor if visible\n if (this.showAnswersEditor) {\n try {\n this.answersEditBuffer = this.getExportJsonPretty();\n if (typeof this.$nextTick === 'function') {\n this.$nextTick(() => this.autoSizeAnswersTa());\n } else {\n setTimeout(() => this.autoSizeAnswersTa(), 0);\n }\n } catch (_) {}\n }\n // Persist selection state\n try { this.saveToSessionStorage(); } catch (_) {}\n try { this.saveToLocalStorage(); } catch (_) {}\n } catch (_) {}\n },\n createNewJob() {\n try { this.saveActiveJob(); } catch (_) {}\n const defaultName = 'job-' + new Date().toISOString().replace(/[:.]/g, '-');\n this.jobName = defaultName;\n this.jobInput = defaultName;\n this.answers = {};\n this.answeredMap = {};\n this.answerBuffer = this.currentAnswer;\n // Save a fresh job immediately so it appears in the sidebar\n try { this.saveActiveJob(); } catch (_) {}\n try { localStorage.setItem('lorraine_job_name', defaultName); } catch (_) {}\n },\n deleteJob(name) {\n try {\n if (!name) return;\n if (this.jobStore && this.jobStore[name]) {\n delete this.jobStore[name];\n this.saveJobsToStorage();\n }\n if (this.jobName === name) {\n this.jobName = '';\n this.jobInput = '';\n this.answers = {};\n this.answeredMap = {};\n this.answerBuffer = this.currentAnswer;\n try { localStorage.removeItem('lorraine_job_name'); } catch (_) {}\n }\n } catch (_) {}\n },\n refreshJobsArray() {\n try {\n const entries = Object.entries(this.jobStore || {});\n const arr = entries.map(([name, payload]) => {\n const list = Array.isArray(payload?.answers) ? payload.answers : [];\n const count = list.filter(a => a && String(a.raw_response || '').trim()).length;\n return { name, answersCount: count, updated_at: payload?.updated_at || null };\n });\n arr.sort((a, b) => {\n const ta = a.updated_at ? Date.parse(a.updated_at) : 0;\n const tb = b.updated_at ? Date.parse(b.updated_at) : 0;\n if (tb !== ta) return tb - ta;\n return a.name.localeCompare(b.name);\n });\n this.jobsArray = arr;\n } catch (_) {\n this.jobsArray = [];\n }\n },\n\n rebuildAnsweredMap() {\n const map = {};\n for (const [qid, a] of Object.entries(this.answers || {})) {\n if (a && String(a.answer_text || '').trim()) map[qid] = true;\n }\n this.answeredMap = map;\n },\n\n // Microphone + Whisper\n async startRecording() {\n try {\n this.isTranscribing = true;\n this.mediaStream = await navigator.mediaDevices.getUserMedia({ audio: true });\n this.chunks = [];\n this.recorder = new MediaRecorder(this.mediaStream);\n this.recorder.ondataavailable = (e) => { if (e.data && e.data.size > 0) this.chunks.push(e.data); };\n this.recorder.onstop = async () => {\n try {\n const blob = new Blob(this.chunks, { type: 'audio/webm' });\n await this.transcribeBlob(blob);\n } catch (e) {\n this.errorMessage = 'Recording error: ' + (e?.message || String(e));\n } finally {\n this.isTranscribing = false;\n this.cleanupMedia();\n }\n };\n this.recorder.start();\n } catch (e) {\n this.isTranscribing = false;\n this.errorMessage = 'Microphone error: ' + (e?.message || String(e));\n this.cleanupMedia();\n }\n },\n stopRecording() { try { this.recorder && this.recorder.stop(); } catch (_) {} },\n cleanupMedia() {\n try { this.mediaStream?.getTracks()?.forEach(t => t.stop()); } catch (_) {}\n this.mediaStream = null; this.recorder = null; this.chunks = [];\n },\n async transcribeBlob(blob) {\n // Require key if no server key\n if (!this.hasServerKey && !this.userApiKey) {\n this.errorMessage = 'please add api key';\n return;\n }\n const form = new FormData();\n form.append('file', blob, 'audio.webm');\n form.append('userApiKey', this.userApiKey || '');\n try {\n const r = await fetch('/api/transcribe', { method: 'POST', body: form });\n if (!r.ok) throw new Error('transcription failed');\n const j = await r.json();\n const text = (j && j.text) ? String(j.text) : '';\n if (text) this.insertTranscriptIntoAnswer(text);\n } catch (e) {\n this.errorMessage = 'Transcription error: ' + (e?.message || String(e));\n }\n },\n\n // Minimal legacy trace helpers (no-ops unless trace is visible)\n computeTraceMaxHeight() { return this.traceExpanded ? '' : 'max-height: 100px'; },\n toggleTool(idx) { this.expandedToolMap[idx] = !this.expandedToolMap[idx]; this.queueScrollToBottom(); },\n prettify(obj) { try { return JSON.stringify(obj, null, 2); } catch (_) { return String(obj); } },\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 setTimeout(() => { this.copyEventsText = 'copy json'; }, 2000);\n } catch (_) {}\n },\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') this.$nextTick(doScroll); else requestAnimationFrame(doScroll);\n } catch (_) {}\n },\n\n // Sidebar helpers (keep minimal compatibility with layout)\n toggleSidebar() { this.sidebarOpen = !this.sidebarOpen; },\n collapseSidebar() { this.sidebarTransitioning = true; this.sidebarCollapsed = true; setTimeout(() => { this.sidebarTransitioning = false; }, this.sidebarAnimMs); },\n expandSidebar() { this.sidebarTransitioning = true; this.sidebarCollapsed = false; setTimeout(() => { this.sidebarTransitioning = false; }, this.sidebarAnimMs); },\n\n // Loading message placeholder\n get loadingMessage() { return 'Loading...'; },\n\n // i18n minimal for Lorraine\n get i18n() {\n const t = {\n english: {\n title: 'Lorraine',\n subtitle: 'Answer prompts in your voice. Build a dataset for your personal style.',\n apiKey: 'API Key:', change: 'Change', clear: 'Clear', getKeyHere: 'Get your free key here',\n yourVersion: 'Your version',\n prev: 'Previous', next: 'Next',\n record: 'Record', stop: 'Stop', insertTranscript: 'Insert transcript',\n export: 'Download answers JSON', language: 'language'\n }\n };\n return t[this.selectedLanguage] || t.english;\n }\n };\n}\n\n\n",[],[242,386],"6e8344de-761e-11f0-9f18-0224a6c84d84","init.js","76b7ba6e-7618-11f0-a463-0224a6c84d84",43,["D",1754853352355],"import researchApp from './researchApp.js';\nimport lorraineApp from './lorraineApp.js';\n\n// Expose globally so existing x-data=\"researchApp()\" continues to work\nwindow.researchApp = researchApp;\nwindow.lorraineApp = lorraineApp;\n\n// Register with Alpine when ready\nif (window.Alpine && typeof window.Alpine.data === 'function') {\n window.Alpine.data('researchApp', researchApp);\n window.Alpine.data('lorraineApp', lorraineApp);\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 window.Alpine.data('lorraineApp', lorraineApp);\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",[],[242,394],["D",1754850788185],[291,292,293],[242],"ecbbc2a8-7796-11f0-94f5-0224a6c84d84",["D",1755015054892],[],[248,32],"769b4ce4-7618-11f0-a93a-0224a6c84d84","questions_design.md","769b4d98-7618-11f0-a93a-0224a6c84d84",9,["D",1754850788959],"### Question design for collecting personalized multi‑context responses\n\nThis document describes the current, simple question/response format used in the app, plus an optional appendix of advanced facets for future phases. The immediate goal is to collect high‑quality, easy‑to‑author pairs for LoRA fine‑tuning of “style transfer” with minimal metadata.\n\n### Objectives\n- **Coverage**: Capture the breadth of situations people respond to (work, personal, public, service, etc.).\n- **Control**: Parameterize questions with facets (tone, formality, emotion, power dynamics) for targeted sampling.\n- **Parsimony**: Achieve high coverage without exploding the cross‑product (via stratified/structured sampling).\n- **Privacy**: Support redaction and sensitivity metadata.\n- **Trainability**: Produce consistent, machine‑readable input/output pairs with rich metadata for conditioning.\n\n### Minimal question schema (current)\n\nKeep authoring dead‑simple so anyone (including kids/teens/non‑tech users) can contribute consistent data.\n\n```json\n{\n \"id\": \"string\",\n \"label\": \"short descriptive name\",\n \"instruction\": \"single instruction text (includes the scenario)\",\n \"tags\": [\"grouping\", \"filters\"],\n \"example\": \"a neutral, normal-human example reply (optional but recommended)\"\n}\n```\n\nNotes\n- instruction merges the old instruction + source_text into one block. Write it in plain language.\n- example replaces the old neutral_sample. It’s what a normal human might say; concise; no sensitive data.\n- tags are lightweight for grouping/filters (e.g., friends, email, invite). No other fields are required.\n\nFile layout\n- Files live under `data/questions/` and may be sharded (e.g., `work.json`, `friends.json`, `youth/school.json`).\n- Aggregation endpoints combine files as needed:\n - `/data/questions/simple.json` (all simple questions, recursive)\n - `/data/questions/simple/by-groups.json?groups=work,friends` (selected groups)\n\nAuthoring rules\n- Keep instruction and example at a grade‑6 to grade‑9 reading level when possible.\n- Use whitespace/newlines in instruction to separate “context” and “what to do.”\n- Avoid extra formatting, bullet lists, or markup; keep it plain.\n- Never include real PII in example; paraphrase.\n\nUI presentation\n- Title/label is not emphasized.\n- The app shows a simple block:\n - “Instructions: ”\n - “Example: ” (always shown if present)\n\n### Minimal response schema (current)\n\n```json\n{\n \"question_id\": \"string\",\n \"raw_response\": \"user’s answer in their voice\",\n \"created_at\": \"ISO 8601\",\n \"neutral_distance_note\": \"optional freeform note\",\n \"response_latency_ms\": 1234\n}\n```\n\nNotes\n- raw_response captures exactly how the user would say it. No polishing required.\n- neutral_distance_note is optional (e.g., “I’d be more direct here than the example”).\n\n### Why this minimal spec works for LoRA\n- **Low friction**: fewer fields → faster authoring and better completion rates.\n- **Style focus**: instruction + example give enough context to generate user‑style responses.\n- **Simple conditioning**: tags enable basic slicing without heavy metadata.\n\n### Optional advanced facets (appendix)\n\nThe following facets are NOT required for the current collection, but remain useful if we later need more control or analysis. Treat them as an optional overlay stored separately or added in a later phase.\n\n### Core facets (dimensions) to parameterize a question (optional)\n- **Domain/context**: work, school/academia, family, partner, friends, social, public, customer support, sales, legal/admin, healthcare, travel/hospitality, community/volunteer, gaming, developer/collab (GitHub/PRs).\n- **Channel/medium**: in‑person, phone/voice, video, SMS/iMessage, WhatsApp, Slack/Teams, email, calendar invite, social post (X/IG/LinkedIn/TikTok caption), comment/reply, forum/Discord, GitHub issue/PR/review, blog, support ticket, survey, form.\n- **Audience role**: manager, direct report, peer, cross‑functional partner, vendor, customer, friend (close), friend (acquaintance), partner/spouse, child/parent/sibling, professor/TA/student, doctor/therapist, government/agency.\n- **Relationship closeness**: stranger, acquaintance, familiar, close, intimate.\n- **Power dynamics**: subordinate → equal → senior; high/low leverage; high/low stakes.\n- **Formality**: very informal, informal, neutral, formal, very formal.\n- **Tone/voice**: friendly, warm, enthusiastic, calm, concise, direct, diplomatic, firm, empathetic, humorous, witty, serious, inspirational, authoritative, deferential.\n- **Emotion state (author of response)**: use circumplex (valence: negative↔positive, arousal: low↔high) and/or Plutchik categories (anger, fear, sadness, disgust, surprise, anticipation, trust, joy) with intensities.\n- **Emotion target**: self‑oriented vs other‑oriented; directed at person vs topic vs situation.\n- **Speech act / intent**: ask/request, propose, inform, confirm, deny, clarify, instruct, announce, invite, accept, decline, schedule, reschedule, apologize, thank, congratulate, praise, critique, give feedback, complain, escalate, negotiate, set boundary, follow up, remind, nudge, check in, summarize, debrief, reflect.\n- **Urgency/time pressure**: none, low, medium, high, crisis.\n- **Constraints**: length (very short, short, medium, long), bullets vs paragraph, with/without emoji, with/without links, subject line required, call‑to‑action required, deadline date/time, reading level.\n- **Sensitivity/compliance**: PII present, confidential, legal exposure, HR policy, medical/financial, regulated industry, brand guideline needed.\n- **Cultural/region/language**: locale (en‑US, en‑UK, en‑IN, etc.), politeness norms, honorifics, code‑switching preferences.\n- **Time/contextual anchors**: time of day, weekday/weekend, before/after an event (launch, outage, interview, exam), proximity to deadline.\n- **Topic domain**: engineering, product, design, marketing, sales, ops, finance, HR, education, research, creative, household/admin, travel, events.\n- **Formatting preferences**: greetings/closings style, signature block, bullets, numbering, sections, TL;DR, action list.\n- **Style modifiers (pragmatics)**: directness, hedging, intensifiers, face‑saving, humor level, exclamation usage, emoji usage, colloquialisms, slang.\n\n### Personality and preference frameworks (optional)\n- **MBTI (16 types)**: e.g., INTJ, ENFP. Store declared type or unknown.\n- **Big Five (OCEAN)**: scores 0–100 per trait.\n- **Enneagram**: types 1–9, optional wing.\n- **DiSC**: D/I/S/C primary and secondary.\n- **Communication preferences**: directness (1–5), candor (1–5), warmth (1–5), humor (1–5), emoji usage (never→often), exclamation tolerance, sentence length preference, bullet vs paragraph preference.\n- **Professional voice toggles**: brand voice adjectives, do/don’t words, signature/greeting conventions.\n\n### Extended question item schema (optional overlay)\nIf/when needed, we can layer additional fields (domain, channel, tone, etc.) as a separate metadata file or by expanding items. See the earlier version of this document for the full list of optional fields.\n\n### Extended response schema (optional overlay)\nAdvanced fields like polished_response, self_ratings, or derived metrics can be added later if we need deeper analysis. For now we only capture the minimal fields listed above.\n\n### Enumerations and examples per facet\n- **Domain/context**\n - Work: 1:1, standup, status update, project kickoff, code review, PR description, incident postmortem, performance review, promotion/raise ask, interview scheduling, offer negotiation, vendor management.\n - Personal: partner check‑in, apology, boundary setting, planning a trip, money talk, household admin, parenting.\n - Friends/social: invite, RSVP, plan details, jokes/banter, group coordination, conflict resolution.\n - Public/social: announcement, thread reply, correction, hot take, event recap, launch post, mea culpa.\n - Service/support: report an issue, ask for refund, give praise, complaint escalation.\n - Admin/legal: lease inquiry, government forms, policy appeal.\n - Healthcare: appointment request, symptoms note, follow‑up question, insurance paperwork.\n - Travel/hospitality: booking request, change/reschedule, special request.\n - Education: email professor, TA feedback, peer review, assignment clarification.\n - Developer collaboration: GitHub issue, PR summary, code review comment, RFC response, design doc feedback.\n\n- **Speech act / intent (canonical set)**\n - Ask/request, propose/suggest, inform/update, confirm/deny, clarify, instruct, announce, invite, accept/decline, schedule/reschedule, apologize, thank, congratulate, praise, critique, feedback, complain, escalate, negotiate, set boundary, follow up, remind, nudge, check in, summarize, debrief, reflect.\n\n- **Tone/voice (mix‑and‑match)**\n - Friendly, warm, calm, concise, direct, diplomatic, firm, empathetic, humorous, witty, serious, inspirational, authoritative, deferential.\n\n### Sampling strategy (to avoid combinatorial explosion)\n- **Stratified grid**: Choose anchor levels for key axes: domain × channel × speech_act × (formality: low/med/high) × (valence: −/0/+) × (power: sub/equal/senior).\n- **Latin hypercube sampling** across remaining facets (tone modifiers, constraints, topic domains) to ensure even coverage.\n- **Phase coverage quotas** (suggested minima):\n - Work (email, Slack, PR/GitHub): 40–60 items\n - Personal/partner/family: 20–30\n - Friends/social: 20–30\n - Public/social media: 15–25\n - Service/support/admin: 15–25\n - Education/healthcare/travel: 10–20\n - Emotions sweep (same scenario across −/0/+ valence and low/high arousal): 15–25\n\n### Template library (examples; fill with scenario content)\n- **Work – status update (email, neutral)**: “Share a brief project status with next steps and date‑based milestones.”\n- **Work – request (Slack, equal)**: “Ask a peer to review your PR today.”\n- **Work – escalate (email, senior)**: “Escalate a blocker with clear impact and request for decision.”\n- **Work – feedback (1:1 note)**: “Give constructive feedback on missed deadline; keep rapport.”\n- **Work – negotiation (email)**: “Negotiate timeline extension by one week; offer trade‑offs.”\n- **Developer – PR summary**: “Write a PR description summarizing changes, risks, and testing notes.”\n- **Developer – code review**: “Request changes on a PR; be specific and respectful.”\n- **Personal – apology**: “Apologize for being late to dinner; own it and propose a make‑good.”\n- **Personal – boundary**: “Decline an invitation without hurting feelings.”\n- **Friends – planning**: “Coordinate a group dinner; propose 2 dates and a budget.”\n- **Friends – banter**: “Respond playfully to a joke; keep it light.”\n- **Partner – check‑in**: “Express appreciation after a tough week.”\n- **Public – announcement**: “Post about launching a small tool; concise and authentic.”\n- **Public – correction**: “Correct misinformation politely in a thread.”\n- **Support – refund**: “Request a refund for a faulty product; include order details.”\n- **Support – praise**: “Thank a customer support rep for great service.”\n- **Admin – policy appeal**: “Appeal a parking ticket; state facts and request leniency.”\n- **Healthcare – appointment**: “Ask to move an appointment earlier; mention symptom severity.”\n- **Travel – change flight**: “Request flight change due to conflict; provide preferences.”\n- **Education – email professor**: “Ask for clarification on assignment requirements.”\n\nEach template becomes a question by binding facets (channel, tone, formality, etc.) and a concrete `source_text` stimulus.\n\n### Prompt structure recommendations (for consistent collection)\n- **Instruction template**: “Reply in your own voice, matching the specified tone and constraints.”\n- **Context block**: scenario summary + `source_text` (if provided) + facets.\n- **Constraints**: explicit bullets (length, emoji, bullets vs paragraph, deadline).\n\nExample assembled question (human‑readable):\n- **Label**: Work email follow‑up (neutral, concise)\n- **Instruction**: Reply in your own voice. Keep it concise and warm. Include a clear ask.\n- **Source text**: “Circling back on the Q3 deliverables: can you share an updated timeline by Friday?”\n- **Facets**: domain: work; channel: email; audience: peer; power: equal; formality: neutral; tone: [concise, warm]; speech_act: [follow_up, request]; urgency: medium.\n\n### File structure and schemas\n- **Files**\n - `data/questions/*.json`: question banks by domain/group (simple schema above).\n - `data/responses/*.jsonl`: user responses (one JSON per line) using the minimal response schema.\n - `schemas/question.schema.json`, `schemas/response.schema.json`: JSON Schemas for validation.\n\n### Compatibility\n- For legacy items with `neutral_sample`, the app treats it as `example`.\n- Old `source_text` is now merged into `instruction`.\n\n### Phase plan (simplified)\n- Phase 1: ship with minimal schema (current). Focus on breadth and ease of authoring.\n- Phase 2 (optional): add overlays for emotions/power/tone on a subset if needed.\n- Phase 3 (optional): domain deep dives with richer metadata if training analysis demands it.\n\n### Privacy and ethics\n- Built‑in redaction UI; sensitivity flags; local‑first storage options.\n- Guidance to paraphrase sensitive specifics while preserving style markers.\n\n### Next steps\n- Implement JSON Schemas and a generator that samples templates × facets with quotas.\n- Build a UI that presents scenario + facets clearly, collects responses, self‑ratings, and optional rationale.\n- Add analytics to track coverage across facets and identify gaps for targeted sampling.\n\n\n",[],[248,409],["D",1754850788090],[288,289],[248],"76ec602a-7618-11f0-aa22-0224a6c84d84","questions.json","76ec6110-7618-11f0-aa22-0224a6c84d84",23,["D",1754850789491],"[\n {\n \"id\": \"q1\",\n \"label\": \"Official announcement\",\n \"instruction\": \"Rewrite this in your own voice, how you would actually say it.\",\n \"source_text\": \"We are pleased to announce the launch of our new product line, available starting next month.\",\n \"tags\": [\"official\", \"announcement\"]\n },\n {\n \"id\": \"q2\",\n \"label\": \"Business email\",\n \"instruction\": \"Reply in your style as if you were emailing a colleague.\",\n \"source_text\": \"Circling back on the Q3 deliverables: can you share an updated timeline by Friday?\",\n \"tags\": [\"business\", \"email\"]\n },\n {\n \"id\": \"q3\",\n \"label\": \"Casual DM\",\n \"instruction\": \"Respond how you’d naturally text a friend.\",\n \"source_text\": \"Let’s catch up later this week if you’re free — maybe Thursday evening?\",\n \"tags\": [\"casual\", \"chat\"]\n },\n {\n \"id\": \"q4\",\n \"label\": \"Social post\",\n \"instruction\": \"Write a short post in your voice.\",\n \"source_text\": \"Had a productive day building a small tool. I’ll share more soon.\",\n \"tags\": [\"social\", \"post\"]\n },\n {\n \"id\": \"q5\",\n \"label\": \"Support response\",\n \"instruction\": \"Answer like you would talk to a customer.\",\n \"source_text\": \"Thanks for reaching out — we’re looking into the issue and will follow up with a fix.\",\n \"tags\": [\"support\", \"reply\"]\n }\n]\n\n\n",[],[253,420],"77972a5a-7618-11f0-aa22-0224a6c84d84","work.json","77972b22-7618-11f0-aa22-0224a6c84d84","7664478a-7618-11f0-bde4-0224a6c84d84",41,["D",1754850789971],"[\n {\n \"id\": \"work_email_status_update_01\",\n \"label\": \"Work status update (email)\",\n \"instruction\": \"Share a brief weekly status update on Project Atlas in your own voice, including milestones, blockers, next steps, and dates.\",\n \"tags\": [\"work\", \"email\", \"status\", \"update\"],\n \"example\": \"Hello team, here is a brief update on Project Atlas: discovery is complete, implementation is 60% complete, and we are on track for the June 5 milestone. Next steps: finalize the API contract by Wednesday and begin QA on Thursday. There are no new blockers.\"\n },\n {\n \"id\": \"work_slack_pr_review_01\",\n \"label\": \"Ask for PR review (Slack)\",\n \"instruction\": \"In your natural Slack tone, ask a peer to review PR #482 before EOD to unblock deployment.\",\n \"tags\": [\"work\", \"slack\", \"request\", \"code-review\"],\n \"example\": \"Could you please review PR #482 today? It is blocking deployment. I am happy to pair if that is helpful.\"\n },\n {\n \"id\": \"work_email_escalation_01\",\n \"label\": \"Escalate a blocker (email)\",\n \"instruction\": \"Escalate a project blocker to a senior stakeholder with impact and a clear ask: a critical vendor API outage is delaying payments and you need a decision on a workaround.\",\n \"tags\": [\"work\", \"email\", \"escalate\", \"blocker\"],\n \"example\": \"Hello Alex, the vendor API is currently down, so we cannot process payouts. We can either hold disbursements until tomorrow or use the manual export/import path (approximately six hours). May I proceed with the manual path for today?\"\n },\n {\n \"id\": \"work_feedback_1on1_01\",\n \"label\": \"Give constructive feedback (1:1)\",\n \"instruction\": \"Give rapport‑maintaining feedback on a direct report’s two‑day QA deadline miss, discussing impact and next steps.\",\n \"tags\": [\"work\", \"feedback\", \"1on1\"],\n \"example\": \"I would like to discuss the QA deadline we missed. It delayed the development handoff and created additional work for the team. Let us review what got in the way and agree on a plan to meet the next date with buffer.\"\n },\n {\n \"id\": \"work_timeline_negotiation_01\",\n \"label\": \"Negotiate timeline (email)\",\n \"instruction\": \"In a partnership tone, request a one‑week extension with tradeoffs since the launch date conflicts with QA bandwidth—propose moving to next Friday.\",\n \"tags\": [\"work\", \"negotiate\", \"timeline\"],\n \"example\": \"Would it be possible to move the launch to next Friday? We can ship the core flow now and add analytics in a follow‑up. This gives QA adequate coverage and reduces risk.\"\n }\n]\n\n\n",[],[253,436,428],"questions","76fdb38e-7618-11f0-bd2f-0224a6c84d84","travel.json","76fdb47e-7618-11f0-bd2f-0224a6c84d84",26,["D",1754850789592],"[\n {\n \"id\": \"travel_change_flight_01\",\n \"label\": \"Change a flight (email)\",\n \"instruction\": \"Request a flight change due to a schedule conflict and provide preferences: move the May 20 7:00 a.m. flight to later that day after 10:00 a.m. or to the morning of May 21.\",\n \"tags\": [\"travel\", \"airline\", \"change\"],\n \"example\": \"Hello, could I change my May 20 flight from 7:00 a.m. to a later departure (after 10:00 a.m.)? If that is not available, May 21 morning also works. Thank you.\"\n }\n]\n\n\n",[],[253,436,438],"7750709c-7618-11f0-b7e2-0224a6c84d84","support.json","77507150-7618-11f0-b7e2-0224a6c84d84",37,["D",1754850790140],"[\n {\n \"id\": \"support_refund_request_01\",\n \"label\": \"Request a refund (email)\",\n \"instruction\": \"Request a refund for a faulty product that arrived damaged and does not power on (order #12345, purchased last week), including order details and a clear ask.\",\n \"tags\": [\"support\", \"refund\", \"email\"],\n \"example\": \"Hello, my order #12345 arrived damaged and does not power on. Could you please process a refund or replacement? I can provide photos if needed.\"\n },\n {\n \"id\": \"support_praise_01\",\n \"label\": \"Praise a support agent\",\n \"instruction\": \"Thank a customer support rep in your authentic voice for resolving your issue quickly and following up proactively.\",\n \"tags\": [\"support\", \"praise\"],\n \"example\": \"Hello, I want to thank the team for the excellent support. The issue was resolved quickly, and the follow‑up was very helpful.\"\n }\n]\n\n\n",[],[253,436,446],"774c250a-7618-11f0-8167-0224a6c84d84","public.json","774c25dc-7618-11f0-8167-0224a6c84d84",36,["D",1754850790121],"[\n {\n \"id\": \"public_launch_post_01\",\n \"label\": \"Launch announcement (social post)\",\n \"instruction\": \"Write a short, authentic launch post in your voice announcing a small tool you shipped and inviting feedback.\",\n \"tags\": [\"public\", \"launch\", \"social\"],\n \"example\": \"I have released a small tool to improve my workflow. If it is useful to you, I would appreciate your feedback. Here is the link.\"\n },\n {\n \"id\": \"public_correction_reply_01\",\n \"label\": \"Polite correction in a thread\",\n \"instruction\": \"Politely correct misinformation in a thread about your project’s license and provide a helpful reference.\",\n \"tags\": [\"public\", \"correction\", \"thread\"],\n \"example\": \"A small correction: the project is licensed under MIT, not GPL. For reference, please see the LICENSE file. Thank you for the discussion.\"\n }\n]\n\n\n",[],[253,436,454],"77104918-7618-11f0-b7e2-0224a6c84d84","partner.json","771049f4-7618-11f0-b7e2-0224a6c84d84",29,["D",1754850789719],"[\n {\n \"id\": \"partner_checkin_appreciation_01\",\n \"label\": \"Partner check-in and appreciation\",\n \"instruction\": \"In your natural voice, express appreciation and support to acknowledge your partner’s stressful week at work.\",\n \"tags\": [\"partner\", \"appreciation\", \"support\"],\n \"example\": \"I saw how challenging this week was for you, and I am proud of your effort. I would like to take care of dinner tonight so you can rest.\"\n },\n {\n \"id\": \"partner_apology_late_01\",\n \"label\": \"Apology for being late\",\n \"instruction\": \"Apologize sincerely for arriving 25 minutes late to a dinner you planned, take responsibility, and propose a make‑good.\",\n \"tags\": [\"partner\", \"apology\", \"late\"],\n \"example\": \"I am very sorry for being late. It was my responsibility. May I make it up to you with brunch tomorrow?\"\n }\n]\n\n\n",[],[253,436,462],"771ec7e0-7618-11f0-bd8b-0224a6c84d84","healthcare.json","771ec8c6-7618-11f0-bd8b-0224a6c84d84",31,["D",1754850789784],"[\n {\n \"id\": \"healthcare_appointment_request_01\",\n \"label\": \"Move appointment earlier\",\n \"instruction\": \"Request an earlier medical appointment if available, noting your worsening wrist pain appropriately.\",\n \"tags\": [\"healthcare\", \"appointment\", \"request\"],\n \"example\": \"Hello, my wrist pain has been worsening this week. If an earlier appointment becomes available, I would appreciate being moved. Thank you.\"\n }\n]\n\n\n",[],[253,436,470],"76f33062-7618-11f0-931f-0224a6c84d84","friends.json","76f33116-7618-11f0-931f-0224a6c84d84",24,["D",1754850789527],"[\n {\n \"id\": \"friends_invite_group_dinner_01\",\n \"label\": \"Plan a group dinner (text)\",\n \"instruction\": \"Coordinate a group dinner in your natural texting style by offering two date options next week and suggesting a place around $30/person.\",\n \"tags\": [\"friends\", \"planning\", \"invite\"],\n \"example\": \"Would you like to have dinner next week? Wednesday or Thursday work well for me. Perhaps the Thai restaurant on 3rd; the cost is about $25–$30 per person. Are you interested?\"\n },\n {\n \"id\": \"friends_banter_reply_01\",\n \"label\": \"Playful banter reply\",\n \"instruction\": \"Respond playfully in your voice to a friend teasing you about always being late to brunch, keeping it light.\",\n \"tags\": [\"friends\", \"banter\", \"casual\"],\n \"example\": \"I appreciate the reminder. I will make sure to arrive five minutes early next time.\"\n },\n {\n \"id\": \"friends_decline_invite_01\",\n \"label\": \"Decline without hurting feelings\",\n \"instruction\": \"Warmly decline a late‑night party invite and offer an alternative, such as coffee this weekend.\",\n \"tags\": [\"friends\", \"boundary\", \"decline\"],\n \"example\": \"I will skip tonight because I need to rest. Would coffee this weekend work instead?\"\n }\n]\n\n\n",[],[253,436,478],"7708b928-7618-11f0-9291-0224a6c84d84","education.json","7708b9d2-7618-11f0-9291-0224a6c84d84",28,["D",1754850789676],"[\n {\n \"id\": \"education_email_professor_01\",\n \"label\": \"Email a professor (clarification)\",\n \"instruction\": \"Ask respectfully and concisely for clarification on the expected analysis depth for Problem Set 3.\",\n \"tags\": [\"education\", \"email\", \"clarify\"],\n \"example\": \"Dear Professor Chen, could you please clarify the expected depth of analysis for Problem Set 3? A brief example or target length would be helpful. Thank you.\"\n }\n]\n\n\n",[],[253,436,486],"77018c02-7618-11f0-93b6-0224a6c84d84","developer.json","77018cd4-7618-11f0-93b6-0224a6c84d84",27,["D",1754850789628],"[\n {\n \"id\": \"dev_pr_summary_01\",\n \"label\": \"PR description summary\",\n \"instruction\": \"Write a PR description summarizing changes, risks, and testing notes for adding the search route, fixing SSE streaming, and improving JSON repair for results.\",\n \"tags\": [\"developer\", \"github_pr\", \"summary\"],\n \"example\": \"Summary: Adds the /api/search route, strengthens chat SSE streaming, and improves JSON repair for results. Risk: streaming edge cases on slow networks. Testing: local SSE with throttling and unit tests for JSON repair.\"\n },\n {\n \"id\": \"dev_code_review_request_01\",\n \"label\": \"Code review feedback (request changes)\",\n \"instruction\": \"Request changes on a PR—be specific and respectful—noting that the new streaming logic lacks error handling for network failures.\",\n \"tags\": [\"developer\", \"github_pr\", \"review\"],\n \"example\": \"Thank you for the update; the streaming path looks good overall. Could we add error handling for network failures (retry/backoff and a user‑visible message)?\"\n }\n]\n\n\n",[],[253,436,494],"775ba7c8-7618-11f0-b48a-0224a6c84d84","admin.json","775ba886-7618-11f0-b48a-0224a6c84d84",38,["D",1754850790218],"[\n {\n \"id\": \"admin_policy_appeal_01\",\n \"label\": \"Policy appeal (email)\",\n \"instruction\": \"Appeal a parking ticket you received while actively loading with hazard lights on, stating facts and requesting leniency in your voice.\",\n \"tags\": [\"admin\", \"appeal\", \"policy\"],\n \"example\": \"Hello, I am writing to appeal ticket #A123. I was actively loading with hazard lights on in a signed loading zone. I would appreciate your consideration in dismissing the citation.\"\n }\n]\n\n\n",[],[253,436,502],"773908b2-7618-11f0-a463-0224a6c84d84","school.json","773909ca-7618-11f0-a463-0224a6c84d84","767ac050-7618-11f0-836d-0224a6c84d84",34,["D",1754850789980],"[\n {\n \"id\": \"youth_school_email_teacher_01\",\n \"label\": \"Ask your teacher a question (email)\",\n \"instruction\": \"Write a short, simple, polite email to your teacher asking for one helpful tip because you're confused about what to include in your science project.\",\n \"tags\": [\"youth\", \"school\", \"teacher\", \"email\"],\n \"example\": \"Hello Ms. Rivera, I am unsure what to include in my science project. Could you please share one tip to help me get started? Thank you.\"\n },\n {\n \"id\": \"youth_school_group_project_01\",\n \"label\": \"Group project message\",\n \"instruction\": \"Send a friendly message to plan roles for a history project due next week—ask who wants to do research, slides, or presenting.\",\n \"tags\": [\"youth\", \"school\", \"group\"],\n \"example\": \"Our project is due next week. Who would like to handle research, slides, or presenting? I can take the slides if someone covers the research.\"\n }\n]\n\n\n",[],[253,436,518,510],"youth","7726aa50-7618-11f0-bd2f-0224a6c84d84","online.json","7726ab04-7618-11f0-bd2f-0224a6c84d84",32,["D",1754850789836],"[\n {\n \"id\": \"youth_online_comment_kind_01\",\n \"label\": \"Write a kind online comment\",\n \"instruction\": \"Write a short, kind comment to someone who shared a drawing they are proud of online.\",\n \"tags\": [\"youth\", \"online\", \"comment\", \"kindness\"],\n \"example\": \"This looks great. I like the colors. Please keep going.\"\n },\n {\n \"id\": \"youth_online_boundaries_01\",\n \"label\": \"Set a boundary online\",\n \"instruction\": \"If someone is being mean in a group chat, write a short message to stop the chat and keep it safe.\",\n \"tags\": [\"youth\", \"online\", \"boundary\"],\n \"example\": \"This is not okay, so I am leaving the chat. Please stop.\"\n }\n]\n\n\n",[],[253,436,518,520],"771c2a80-7618-11f0-931f-0224a6c84d84","771c2b5c-7618-11f0-931f-0224a6c84d84",30,["D",1754850789773],"[\n {\n \"id\": \"youth_friends_invite_01\",\n \"label\": \"Invite a friend to hang out\",\n \"instruction\": \"Text a friend to hang out after school, offering two simple ideas like grabbing a snack or playing a game this Friday.\",\n \"tags\": [\"youth\", \"friends\", \"invite\"],\n \"example\": \"Would you like to hang out on Friday? We could get a snack or play a game at my place.\"\n },\n {\n \"id\": \"youth_friends_boundary_01\",\n \"label\": \"Say no nicely\",\n \"instruction\": \"Say no to a plan kindly and suggest another time—for example, you're tired tonight so propose Saturday afternoon.\",\n \"tags\": [\"youth\", \"friends\", \"boundary\"],\n \"example\": \"I am tired tonight. Could we meet on Saturday afternoon instead?\"\n }\n]\n\n\n",[],[253,436,518,478],"77400f54-7618-11f0-a93a-0224a6c84d84","feelings.json","77401148-7618-11f0-a93a-0224a6c84d84",35,["D",1754850789960],"[\n {\n \"id\": \"youth_feelings_happy_share_01\",\n \"label\": \"Share good news\",\n \"instruction\": \"Tell a friend some good news in a happy way: you got a higher grade than expected.\",\n \"tags\": [\"youth\", \"feelings\", \"happy\"],\n \"example\": \"I received a higher grade than I expected, and I feel proud.\"\n },\n {\n \"id\": \"youth_feelings_mad_calm_01\",\n \"label\": \"Calm message when mad\",\n \"instruction\": \"When you're mad because a friend cancelled last minute, write a short, calm message that explains how you feel without being mean.\",\n \"tags\": [\"youth\", \"feelings\", \"mad\"],\n \"example\": \"I was looking forward to today and felt disappointed. Could we plan ahead next time?\"\n }\n]\n\n\n",[],[253,436,518,535],"773450ec-7618-11f0-a5f1-0224a6c84d84","family.json","773451be-7618-11f0-a5f1-0224a6c84d84",33,["D",1754850789959],"[\n {\n \"id\": \"youth_family_permission_01\",\n \"label\": \"Ask a parent for permission\",\n \"instruction\": \"Ask a parent for permission to go to a friend's house after school, noting when you'll be back and that your homework is done.\",\n \"tags\": [\"youth\", \"family\", \"permission\"],\n \"example\": \"May I go to Alex’s house after school? I will be home by 6:00 p.m., and my homework is finished.\"\n },\n {\n \"id\": \"youth_family_appreciation_01\",\n \"label\": \"Thank a family member\",\n \"instruction\": \"Send a short thank‑you to a family member who helped you study for a quiz.\",\n \"tags\": [\"youth\", \"family\", \"thanks\"],\n \"example\": \"Thank you for helping me study; it made a big difference.\"\n }\n]\n\n\n",[],[253,436,518,543],"767abf6a-7618-11f0-836d-0224a6c84d84",7,["D",1754850788746],[271,272,273,274,275],[253,436,518],"766446e0-7618-11f0-bde4-0224a6c84d84",6,["D",1754850788582],[270,276,277,278,279,280,281,282,283,284,285],[253,436],["D",1754850788481],[269,286],[253],["D",1754850754170],{"_95":94,"_102":98},{"_95":94,"_96":-5,"_97":98,"_18":53,"_99":100,"_101":24},{"_13":84,"_31":85,"_41":40,"_86":42,"_87":-5,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":43,"_93":94},"ctx",{"_77":-5,"_121":600,"_601":602,"_603":604,"_605":24,"_606":24,"_607":24,"_608":57,"_609":-5,"_610":-7,"_611":-7,"_612":61,"_613":24,"_614":24,"_615":-5,"_616":24,"_617":24,"_618":24,"_619":-5},"ENV",{"_571":572,"_573":574,"_575":85,"_576":577,"_578":579,"_580":581,"_582":583,"_584":585,"_586":587,"_588":589,"_590":591,"_592":593,"_594":595,"_596":597,"_598":599},"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 · v47