diff --git a/.gitignore b/.gitignore index 2c9a7e2..59c8729 100644 --- a/.gitignore +++ b/.gitignore @@ -37,3 +37,5 @@ yarn-error.log* /localdata/ /venv/ /embeddings_backup.npz +/AGENTS.md +/CLAUDE.md diff --git a/Onboarding Wireframes.pdf b/Onboarding Wireframes.pdf new file mode 100644 index 0000000..027a040 Binary files /dev/null and b/Onboarding Wireframes.pdf differ diff --git a/app/api/sample-genotype/route.ts b/app/api/sample-genotype/route.ts new file mode 100644 index 0000000..d0a0370 --- /dev/null +++ b/app/api/sample-genotype/route.ts @@ -0,0 +1,195 @@ +import { NextResponse } from 'next/server'; +import { inflateRawSync } from 'node:zlib'; + +const SAMPLE_DATA_URL = 'https://drive.google.com/uc?export=download&id=1WK3zZbqmu3_m6LvoQCylyIbWBkoO5pGI'; + +const textDecoder = new TextDecoder(); + +function isZipPayload(bytes: Uint8Array): boolean { + return bytes.length >= 4 + && bytes[0] === 0x50 + && bytes[1] === 0x4b + && bytes[2] === 0x03 + && bytes[3] === 0x04; +} + +function findEndOfCentralDirectory(bytes: Uint8Array): number { + const minOffset = Math.max(0, bytes.length - 0xffff - 22); + + for (let offset = bytes.length - 22; offset >= minOffset; offset -= 1) { + if ( + bytes[offset] === 0x50 + && bytes[offset + 1] === 0x4b + && bytes[offset + 2] === 0x05 + && bytes[offset + 3] === 0x06 + ) { + return offset; + } + } + + return -1; +} + +function extractFirstZipEntry(bytes: Uint8Array): { filename: string; data: Uint8Array } | null { + const view = new DataView(bytes.buffer, bytes.byteOffset, bytes.byteLength); + const eocdOffset = findEndOfCentralDirectory(bytes); + + if (eocdOffset < 0) return null; + + const centralDirectoryOffset = view.getUint32(eocdOffset + 16, true); + if (centralDirectoryOffset + 46 > bytes.length) return null; + if (view.getUint32(centralDirectoryOffset, true) !== 0x02014b50) return null; + + const compressionMethod = view.getUint16(centralDirectoryOffset + 10, true); + const compressedSize = view.getUint32(centralDirectoryOffset + 20, true); + const fileNameLength = view.getUint16(centralDirectoryOffset + 28, true); + const extraLength = view.getUint16(centralDirectoryOffset + 30, true); + const commentLength = view.getUint16(centralDirectoryOffset + 32, true); + const localHeaderOffset = view.getUint32(centralDirectoryOffset + 42, true); + const filenameStart = centralDirectoryOffset + 46; + const filenameEnd = filenameStart + fileNameLength; + + if (filenameEnd > bytes.length) return null; + + const filename = textDecoder.decode(bytes.slice(filenameStart, filenameEnd)); + const nextEntryOffset = filenameEnd + extraLength + commentLength; + if (nextEntryOffset > bytes.length) return null; + + if (localHeaderOffset + 30 > bytes.length) return null; + if (view.getUint32(localHeaderOffset, true) !== 0x04034b50) return null; + + const localNameLength = view.getUint16(localHeaderOffset + 26, true); + const localExtraLength = view.getUint16(localHeaderOffset + 28, true); + const dataStart = localHeaderOffset + 30 + localNameLength + localExtraLength; + const dataEnd = dataStart + compressedSize; + + if (dataEnd > bytes.length) return null; + + const compressed = bytes.slice(dataStart, dataEnd); + + if (compressionMethod === 0) { + return { filename, data: compressed }; + } + + if (compressionMethod === 8) { + return { filename, data: inflateRawSync(compressed) }; + } + + return null; +} + +function collectCookieHeader(response: Response): string { + const header = response.headers.get('set-cookie'); + if (!header) return ''; + return header + .split(/,(?=[^;]+=[^;]+)/) + .map((cookie) => cookie.split(';')[0]?.trim()) + .filter(Boolean) + .join('; '); +} + +function extractConfirmedDownloadUrl(html: string): string | null { + const formMatch = html.match(/]+id="download-form"[^>]+action="([^"]+)"/i); + if (formMatch) { + const action = formMatch[1]; + const url = new URL(action, 'https://drive.google.com'); + const inputRegex = /]+type="hidden"[^>]+name="([^"]+)"[^>]+value="([^"]*)"/gi; + let inputMatch: RegExpExecArray | null; + + while ((inputMatch = inputRegex.exec(html)) !== null) { + url.searchParams.set(inputMatch[1], inputMatch[2]); + } + + return url.toString(); + } + + const hrefMatch = html.match(/href="(\/uc\?export=download[^"]+)"/i); + if (hrefMatch) { + return new URL(hrefMatch[1].replace(/&/g, '&'), 'https://drive.google.com').toString(); + } + + return null; +} + +export async function GET() { + try { + let upstream = await fetch(SAMPLE_DATA_URL, { + method: 'GET', + redirect: 'follow', + cache: 'no-store', + }); + + if (!upstream.ok) { + return NextResponse.json( + { error: `Sample data upstream failed with status ${upstream.status}` }, + { status: 502 } + ); + } + + let contentType = upstream.headers.get('content-type') || 'text/plain; charset=utf-8'; + + if (contentType.includes('text/html')) { + const html = await upstream.text(); + const confirmedUrl = extractConfirmedDownloadUrl(html); + + if (!confirmedUrl) { + return NextResponse.json( + { error: 'Sample data upstream returned an HTML confirmation page instead of the genotype file.' }, + { status: 502 } + ); + } + + upstream = await fetch(confirmedUrl, { + method: 'GET', + redirect: 'follow', + cache: 'no-store', + headers: { + Cookie: collectCookieHeader(upstream), + }, + }); + + if (!upstream.ok) { + return NextResponse.json( + { error: `Sample data confirmed download failed with status ${upstream.status}` }, + { status: 502 } + ); + } + + contentType = upstream.headers.get('content-type') || 'text/plain; charset=utf-8'; + } + + const data = await upstream.arrayBuffer(); + let outputBytes = new Uint8Array(data); + let outputFileName = 'monadicdna-sample-data.txt'; + + if (isZipPayload(outputBytes)) { + const extracted = extractFirstZipEntry(outputBytes); + + if (!extracted) { + return NextResponse.json( + { error: 'Sample data upstream returned a ZIP archive that could not be unpacked.' }, + { status: 502 } + ); + } + + outputBytes = new Uint8Array(extracted.data) as unknown as Uint8Array; + outputFileName = extracted.filename || outputFileName; + contentType = 'text/plain; charset=utf-8'; + } + + return new NextResponse(outputBytes, { + status: 200, + headers: { + 'Content-Type': contentType, + 'Content-Disposition': `inline; filename="${outputFileName}"`, + 'Cache-Control': 'no-store', + }, + }); + } catch (error) { + console.error('[sample-genotype] Failed to fetch sample data:', error); + return NextResponse.json( + { error: error instanceof Error ? error.message : 'Failed to fetch sample genotype data' }, + { status: 500 } + ); + } +} diff --git a/app/api/stripe/create-checkout/route.ts b/app/api/stripe/create-checkout/route.ts index 9bcccc5..02655f6 100644 --- a/app/api/stripe/create-checkout/route.ts +++ b/app/api/stripe/create-checkout/route.ts @@ -5,8 +5,6 @@ const stripe = new Stripe(process.env.STRIPE_SECRET_KEY || 'sk_test_placeholder' apiVersion: '2025-02-24.acacia', }); -const DAYS_PER_MONTH = 30; - export async function POST(request: NextRequest) { try { const { walletAddress, couponCode } = await request.json(); @@ -99,8 +97,8 @@ export async function POST(request: NextRequest) { }, ], discounts, - success_url: `${origin}/payment/success?session_id={CHECKOUT_SESSION_ID}`, - cancel_url: `${origin}/payment/cancel`, + success_url: `${origin}/subscribe/confirmed?session_id={CHECKOUT_SESSION_ID}`, + cancel_url: `${origin}/subscribe?payment=cancelled`, metadata: { walletAddress: walletAddress.toLowerCase(), }, diff --git a/app/api/studies/route.ts b/app/api/studies/route.ts index c97b396..e0a56c3 100644 --- a/app/api/studies/route.ts +++ b/app/api/studies/route.ts @@ -54,6 +54,47 @@ type Study = RawStudy & { nonAnalyzableReason?: string; }; +function getSearchTerms(search: string): string[] { + const tokens = Array.from( + new Set( + search + .trim() + .split(/\s+/) + .map((token) => token.trim().toLowerCase()) + .filter(Boolean) + ) + ); + + return tokens.length > 1 ? tokens : [search.trim().toLowerCase()]; +} + +function rowMatchesSearchTerms( + row: Pick< + RawStudy, + "study" | "disease_trait" | "mapped_trait" | "first_author" | "mapped_gene" | "study_accession" | "snps" + >, + searchTerms: string[], +): boolean { + if (searchTerms.length === 0) { + return false; + } + + const haystack = [ + row.study, + row.disease_trait, + row.mapped_trait, + row.first_author, + row.mapped_gene, + row.study_accession, + row.snps, + ] + .filter(Boolean) + .join(" ") + .toLowerCase(); + + return searchTerms.every((term) => haystack.includes(term)); +} + function normalizeYear(value: string): number | null { const numeric = Number(value); if (!Number.isFinite(numeric)) { @@ -195,6 +236,57 @@ function parseInteger(value: string | null): number | null { return Number.isFinite(numeric) ? numeric : null; } +function buildKeywordSearchClause(search: string, startParamIndex: number) { + const trimmed = search.trim(); + const searchTerms = getSearchTerms(search); + const candidateSubqueries: string[] = []; + const params: string[] = []; + let paramIndex = startParamIndex; + + const studyTsQueryPlaceholder = `$${paramIndex}`; + paramIndex += 1; + params.push(trimmed); + candidateSubqueries.push( + `SELECT id FROM gwas_catalog WHERE to_tsvector('english', study) @@ websearch_to_tsquery('english', ${studyTsQueryPlaceholder})` + ); + + const traitTsQueryPlaceholder = `$${paramIndex}`; + paramIndex += 1; + params.push(trimmed); + candidateSubqueries.push( + `SELECT id FROM gwas_catalog WHERE to_tsvector('english', COALESCE(disease_trait, '') || ' ' || COALESCE(mapped_trait, '')) @@ websearch_to_tsquery('english', ${traitTsQueryPlaceholder})` + ); + + if (searchTerms.length === 1) { + const exactTermPlaceholder = `$${paramIndex}`; + paramIndex += 1; + params.push(trimmed); + candidateSubqueries.push( + `SELECT id FROM gwas_catalog WHERE study_accession = UPPER(${exactTermPlaceholder})` + ); + + const snpTermPlaceholder = `$${paramIndex}`; + paramIndex += 1; + params.push(trimmed); + candidateSubqueries.push( + `SELECT id FROM gwas_catalog WHERE snps = LOWER(${snpTermPlaceholder})` + ); + + const geneTermPlaceholder = `$${paramIndex}`; + paramIndex += 1; + params.push(trimmed); + candidateSubqueries.push( + `SELECT id FROM gwas_catalog WHERE mapped_gene = UPPER(${geneTermPlaceholder})` + ); + } + + return { + clause: `gc.id IN (${candidateSubqueries.join(" UNION ")})`, + params, + nextParamIndex: paramIndex, + }; +} + function determineConfidenceBand( sampleSize: number | null, pValue: number | null, @@ -239,6 +331,7 @@ export async function GET(request: NextRequest) { const searchParams = request.nextUrl.searchParams; const search = searchParams.get("search")?.trim(); + const searchTerms = search ? getSearchTerms(search) : []; const trait = searchParams.get("trait")?.trim(); const searchMode = searchParams.get("searchMode") ?? "similarity"; // "similarity" or "exact" const useSemanticSearch = searchMode === "similarity"; // Use semantic search only for similarity mode @@ -269,6 +362,7 @@ export async function GET(request: NextRequest) { let orderByClause = ""; let useSemanticQuery = false; let queryEmbedding: number[] = []; + let keywordMatchedIds = new Set(); // Semantic search: Generate embedding for query if (search && useSemanticSearch) { @@ -291,12 +385,10 @@ export async function GET(request: NextRequest) { // Build search filters if (search && !useSemanticQuery) { // Keyword search (fallback or when semantic is disabled) - const wildcard = `%${search}%`; - filters.push( - `(gc.study LIKE $${paramIndex} OR gc.disease_trait LIKE $${paramIndex+1} OR gc.mapped_trait LIKE $${paramIndex+2} OR gc.first_author LIKE $${paramIndex+3} OR gc.mapped_gene LIKE $${paramIndex+4} OR gc.study_accession LIKE $${paramIndex+5} OR gc.snps LIKE $${paramIndex+6})`, - ); - params.push(wildcard, wildcard, wildcard, wildcard, wildcard, wildcard, wildcard); - paramIndex += 7; + const keywordSearch = buildKeywordSearchClause(search, paramIndex); + filters.push(keywordSearch.clause); + params.push(...keywordSearch.params); + paramIndex = keywordSearch.nextParamIndex; } else if (useSemanticQuery) { // Semantic search: Use separate study_embeddings table // PostgreSQL: Semantic search handled in FROM clause subquery @@ -469,12 +561,10 @@ export async function GET(request: NextRequest) { // Re-add search as keyword search if (search) { - const wildcard = `%${search}%`; - fallbackFilters.push( - `(gc.study LIKE $${fallbackParamIndex} OR gc.disease_trait LIKE $${fallbackParamIndex+1} OR gc.mapped_trait LIKE $${fallbackParamIndex+2} OR gc.first_author LIKE $${fallbackParamIndex+3} OR gc.mapped_gene LIKE $${fallbackParamIndex+4} OR gc.study_accession LIKE $${fallbackParamIndex+5} OR gc.snps LIKE $${fallbackParamIndex+6})`, - ); - fallbackParams.push(wildcard, wildcard, wildcard, wildcard, wildcard, wildcard, wildcard); - fallbackParamIndex += 7; + const keywordSearch = buildKeywordSearchClause(search, fallbackParamIndex); + fallbackFilters.push(keywordSearch.clause); + fallbackParams.push(...keywordSearch.params); + fallbackParamIndex = keywordSearch.nextParamIndex; } if (trait) { @@ -563,6 +653,98 @@ export async function GET(request: NextRequest) { } } + if (useSemanticQuery && search) { + keywordMatchedIds = new Set( + rawRows.filter((row) => rowMatchesSearchTerms(row, searchTerms)).map((row) => row.id) + ); + + if (keywordMatchedIds.size === 0) { + const keywordFilters: string[] = []; + const keywordParams: unknown[] = []; + let keywordParamIndex = 1; + + const keywordSearch = buildKeywordSearchClause(search, keywordParamIndex); + keywordFilters.push(keywordSearch.clause); + keywordParams.push(...keywordSearch.params); + keywordParamIndex = keywordSearch.nextParamIndex; + + if (trait) { + keywordFilters.push(`(gc.mapped_trait = $${keywordParamIndex} OR gc.disease_trait = $${keywordParamIndex + 1})`); + keywordParams.push(trait, trait); + keywordParamIndex += 2; + } + + if (fetchAll) { + keywordFilters.push("(gc.snps IS NOT NULL AND gc.snps != '')"); + keywordFilters.push("(gc.strongest_snp_risk_allele IS NOT NULL AND gc.strongest_snp_risk_allele != '')"); + } + + if (minSampleSize !== null) { + keywordFilters.push(`((NULLIF(regexp_replace((regexp_match(gc.initial_sample_size, '[0-9,]+'))[1], ',', '', 'g'), '')::numeric >= $${keywordParamIndex}::numeric) OR (NULLIF(regexp_replace((regexp_match(gc.replication_sample_size, '[0-9,]+'))[1], ',', '', 'g'), '')::numeric >= $${keywordParamIndex + 1}::numeric))`); + keywordParams.push(minSampleSize, minSampleSize); + keywordParamIndex += 2; + } + + if (maxPValue !== null) { + const minLogPFromMaxP = -Math.log10(maxPValue); + keywordFilters.push(`(gc.pvalue_mlog IS NULL OR gc.pvalue_mlog::numeric >= $${keywordParamIndex}::numeric)`); + keywordParams.push(minLogPFromMaxP); + keywordParamIndex += 1; + } + + if (minLogP !== null) { + keywordFilters.push(`gc.pvalue_mlog::numeric >= $${keywordParamIndex}::numeric`); + keywordParams.push(minLogP); + keywordParamIndex += 1; + } + + if (excludeMissingGenotype) { + keywordFilters.push("(gc.strongest_snp_risk_allele IS NOT NULL AND gc.strongest_snp_risk_allele != '' AND gc.strongest_snp_risk_allele != '?' AND gc.strongest_snp_risk_allele != 'NR' AND gc.strongest_snp_risk_allele NOT LIKE '%?%')"); + } + + const keywordWhereClause = keywordFilters.length ? `WHERE ${keywordFilters.join(" AND ")}` : ""; + const keywordRescueLimit = Math.min(Math.max(limit, 25), 200); + const keywordQuery = `SELECT ${idSelection}, + gc.study_accession, + gc.study, + gc.disease_trait, + gc.mapped_trait, + gc.mapped_trait_uri, + gc.mapped_gene, + gc.first_author, + gc.date, + gc.journal, + gc.pubmedid, + gc.link, + gc.initial_sample_size, + gc.replication_sample_size, + gc.p_value, + gc.pvalue_mlog, + gc.or_or_beta, + gc.ci_text, + gc.risk_allele_frequency, + gc.strongest_snp_risk_allele, + gc.snps + FROM gwas_catalog gc + ${keywordWhereClause} + ORDER BY gc.pvalue_mlog::numeric DESC NULLS LAST + LIMIT ${keywordRescueLimit}`; + + const keywordRows = await executeQuery(keywordQuery, keywordParams); + keywordMatchedIds = new Set(keywordRows.map((row) => row.id)); + + if (keywordRows.length > 0) { + const mergedRows = new Map(); + keywordRows.forEach((row) => mergedRows.set(row.id, row)); + rawRows.forEach((row) => { + const existing = mergedRows.get(row.id); + mergedRows.set(row.id, existing ? { ...row, ...existing, similarity: row.similarity ?? existing.similarity } : row); + }); + rawRows = Array.from(mergedRows.values()); + } + } + } + try { const studies: Study[] = rawRows @@ -619,23 +801,41 @@ export async function GET(request: NextRequest) { // Get source count (may fail if numeric overflow in WHERE clause, that's ok) let sourceCount = 0; - try { - const countQuery = useSemanticQuery - ? `SELECT COUNT(*) as count ${fromClause} ${whereClause}` - : `SELECT COUNT(*) as count FROM gwas_catalog gc ${whereClause}`; - const countResult = await executeQuerySingle<{ count: number }>(countQuery, params); - sourceCount = countResult?.count ?? 0; - } catch (error: any) { - console.warn('[Query] Count query failed:', error?.message || 'Unknown error'); - console.warn('[Query] Using result length as count instead'); + const skipExactCount = Boolean(search); + + if (skipExactCount) { sourceCount = rawRows.length; + } else { + try { + const countQuery = useSemanticQuery + ? `SELECT COUNT(*) as count ${fromClause} ${whereClause}` + : `SELECT COUNT(*) as count FROM gwas_catalog gc ${whereClause}`; + const countResult = await executeQuerySingle<{ count: number }>(countQuery, params); + sourceCount = countResult?.count ?? 0; + } catch (error: any) { + console.warn('[Query] Count query failed:', error?.message || 'Unknown error'); + console.warn('[Query] Using result length as count instead'); + sourceCount = rawRows.length; + } } + sourceCount = Math.max(sourceCount, rawRows.length); + const sortedStudies = [...studies]; const directionFactor = direction === "asc" ? 1 : -1; - // Skip client-side sorting if semantic search already ordered by relevance - if (!useSemanticQuery) { + if (useSemanticQuery) { + sortedStudies.sort((a, b) => { + const aKeyword = keywordMatchedIds.has(a.id) ? 1 : 0; + const bKeyword = keywordMatchedIds.has(b.id) ? 1 : 0; + + if (aKeyword !== bKeyword) { + return bKeyword - aKeyword; + } + + return (b.similarity ?? -Infinity) - (a.similarity ?? -Infinity); + }); + } else { switch (sort) { case "power": sortedStudies.sort((a, b) => directionFactor * ((a.sampleSize ?? 0) - (b.sampleSize ?? 0))); diff --git a/app/components/AuthProvider.tsx b/app/components/AuthProvider.tsx index 0591ad2..a0c9772 100644 --- a/app/components/AuthProvider.tsx +++ b/app/components/AuthProvider.tsx @@ -4,7 +4,7 @@ import { DynamicContextProvider, DynamicWidget, useDynamicContext } from '@dynam import { EthereumWalletConnectors } from '@dynamic-labs/ethereum'; import { ZeroDevSmartWalletConnectors } from '@dynamic-labs/ethereum-aa'; import { createContext, useContext, useEffect, useState, useCallback, ReactNode } from 'react'; -import { trackUserLoggedIn } from '@/lib/analytics'; +import { trackSignInStarted, trackUserLoggedIn } from '@/lib/analytics'; import { hasValidPromoAccess } from '@/lib/promo-access'; interface SubscriptionData { @@ -84,11 +84,20 @@ export function AuthProvider({ children }: { children: ReactNode }) { const [checkingSubscription, setCheckingSubscription] = useState(false); // Changed default to false const [isDynamicInitialized, setIsDynamicInitialized] = useState(false); const [openAuthModalFn, setOpenAuthModalFn] = useState<(() => void) | null>(null); + const [pendingAuthModalOpen, setPendingAuthModalOpen] = useState(false); // If environment ID is not set, render without Dynamic (useful for CI/CD builds) const environmentId = process.env.NEXT_PUBLIC_DYNAMIC_ENVIRONMENT_ID; const isDynamicEnabled = !!environmentId; + // Eagerly initialize Dynamic on mount so restored sessions are picked up + // before the user clicks any auth-gated button. + useEffect(() => { + if (isDynamicEnabled) { + setIsDynamicInitialized(true); + } + }, [isDynamicEnabled]); + const checkSubscription = useCallback(async (walletAddress: string) => { try { console.log('[AuthProvider] Checking subscription for:', walletAddress); @@ -236,11 +245,35 @@ export function AuthProvider({ children }: { children: ReactNode }) { setOpenAuthModalFn(() => openFn); }, []); + useEffect(() => { + if (!pendingAuthModalOpen || !isDynamicInitialized || !openAuthModalFn) { + return; + } + + openAuthModalFn(); + setPendingAuthModalOpen(false); + }, [isDynamicInitialized, openAuthModalFn, pendingAuthModalOpen]); + const openAuthModal = useCallback(() => { + if (!isDynamicEnabled) { + return; + } + + trackSignInStarted(); + + if (!isDynamicInitialized) { + setPendingAuthModalOpen(true); + initializeDynamic(); + return; + } + if (openAuthModalFn) { openAuthModalFn(); + return; } - }, [openAuthModalFn]); + + setPendingAuthModalOpen(true); + }, [initializeDynamic, isDynamicEnabled, isDynamicInitialized, openAuthModalFn]); // If Dynamic is not enabled (no environment ID), render children with default auth context if (!isDynamicEnabled) { diff --git a/app/components/ConversionOnboarding.tsx b/app/components/ConversionOnboarding.tsx new file mode 100644 index 0000000..f50f2c3 --- /dev/null +++ b/app/components/ConversionOnboarding.tsx @@ -0,0 +1,1190 @@ +"use client"; + +import { useCallback, useEffect, useMemo, useRef, useState } from "react"; +import { createPortal } from "react-dom"; +import ReactMarkdown from "react-markdown"; +import remarkGfm from "remark-gfm"; +import { SavedResult } from "@/lib/results-manager"; +import { runAllAnalysisOnboarding, type OnboardingRunAllProgress } from "@/lib/run-all-onboarding"; +import { useGenotype } from "./UserDataUpload"; +import { useResults } from "./ResultsContext"; +import LLMCommentaryModal from "./LLMCommentaryModal"; +import NilAIConsentModal from "./NilAIConsentModal"; +import { callLLM, getLLMDescription } from "@/lib/llm-client"; +import { + trackAIConsentDeclined, + trackAIConsentGiven, + trackLLMQuestionAsked, + trackOnboardingAction, + trackOnboardingCompleted, + trackOnboardingDismissed, + trackOnboardingPathChosen, + trackOnboardingStarted, + trackOnboardingStepViewed, + trackRunAllCompleted, + trackRunAllFailed, + trackRunAllStarted, + trackSampleDataFailed, + trackSampleDataLoaded, + trackSampleDataStarted, +} from "@/lib/analytics"; + +type FlowMode = "guided" | "instant_preview"; +type OnboardingStep = "intro" | "path" | "need_file" | "need_sequencing" | "sample_data" | "upload" | "run_all" | "traits" | "responses"; +type CompletionPath = "own_dna" | "own_dna_needs_help" | "own_dna_no_test"; + +type PreviewChatAnswer = { + question: string; + answer: string; + studiesUsed: number; +}; + +type SampleLoadPhase = "idle" | "downloading" | "ingesting" | "complete"; + +type SampleLoadProgress = { + phase: SampleLoadPhase; + downloadedBytes: number; + totalBytes: number; +}; + +interface ConversionOnboardingProps { + isOpen: boolean; + onComplete: () => void; + onDismiss?: () => void; + mode?: FlowMode; +} + +const CONSENT_STORAGE_KEY = "nilai_llm_consent_accepted"; +const SAMPLE_DATA_URL = "/api/sample-genotype"; +const GUIDE_23ANDME_URL = "https://monadicdna.com/guide/23andme"; +const GUIDE_ANCESTRY_URL = "https://monadicdna.com/guide/ancestry"; +const SEQUENCING_URL = + "https://docs.google.com/forms/d/e/1FAIpQLSdHFDpsyU0t6PlaXEkbHX-pwF_y7icuPJeOHyGHMDpe11XigQ/viewform?usp=sharing&ouid=117844628488835974298"; +const REQUIRED_TRAIT_COUNT = 6; +const CURATED_ONBOARDING_TRAITS = [ + { traitName: "Sleep Quality", gwasId: "GCST012034", matchedSnp: "rs8095104" }, + { traitName: "Spicy food liking", gwasId: "GCST90094846", matchedSnp: "rs6882046" }, + { traitName: "Body Mass Index", gwasId: "GCST004559", matchedSnp: "rs12446632" }, + { traitName: "Aging Rate", gwasId: "GCST011011", matchedSnp: "rs13107325" }, + { traitName: "Facial Skin Hydration", gwasId: "GCST90104592", matchedSnp: "rs79885808" }, + { traitName: "Motion Sickness", gwasId: "GCST002759", matchedSnp: "rs1195218" }, +] as const; +const CHAT_PREVIEW_QUESTIONS = [ + "How's my sleep profile?", + "Which sports are ideal for me?", + "What kinds of foods do you think I will like best?", + "Which learning styles are best for me?", + "What do my genetics imply for my skincare routine?", +]; +const HAPPY_PATH_STEP_INDEX: Partial> = { + intro: 1, + path: 2, + need_file: 2, + need_sequencing: 2, + sample_data: 2, + upload: 3, + run_all: 4, + traits: 5, + responses: 6, +}; + +const INITIAL_SAMPLE_LOAD_PROGRESS: SampleLoadProgress = { + phase: "idle", + downloadedBytes: 0, + totalBytes: 0, +}; + +function dedupeStudyResults(results: SavedResult[]): SavedResult[] { + const seen = new Set(); + return results.filter((result) => { + if (seen.has(result.studyId)) return false; + seen.add(result.studyId); + return true; + }); +} + +function normalizeOnboardingKey(value: string | undefined): string { + return (value || "").trim().toLowerCase(); +} + +function formatSampleBytes(bytes: number): string { + if (bytes <= 0) return "0 MB"; + if (bytes < 1024 * 1024) return `${(bytes / 1024).toFixed(0)} KB`; + return `${(bytes / (1024 * 1024)).toFixed(1)} MB`; +} + +function buildTraitCandidates(results: SavedResult[]): SavedResult[] { + const deduped = dedupeStudyResults(results); + return CURATED_ONBOARDING_TRAITS + .map((target) => { + const match = deduped.find( + (result) => + normalizeOnboardingKey(result.gwasId) === normalizeOnboardingKey(target.gwasId) && + normalizeOnboardingKey(result.matchedSnp) === normalizeOnboardingKey(target.matchedSnp) + ); + + return match + ? { + ...match, + traitName: target.traitName, + } + : null; + }) + .filter((result) => result !== null) as SavedResult[]; +} + +function formatRiskScore(score: number, level: string, effectType?: string): string { + if (level === "neutral") return effectType === "beta" ? "baseline" : "1.0x"; + if (effectType === "beta") { + return `β=${score >= 0 ? "+" : ""}${score.toFixed(3)} units`; + } + return `${score.toFixed(2)}x`; +} + +function formatRiskHeadline(result: SavedResult): string { + if (result.effectType === "beta") { + if (result.riskLevel === "neutral") return "No measurable shift in this study"; + return result.riskLevel === "increased" + ? "Associated with higher values for this trait" + : "Associated with lower values for this trait"; + } + + if (result.riskLevel === "neutral" || Math.abs(result.riskScore - 1) < 0.001) { + return "Baseline odds in this study"; + } + + const delta = result.riskLevel === "increased" + ? (result.riskScore - 1) * 100 + : (1 - result.riskScore) * 100; + const formatted = Math.abs(delta).toFixed(Math.abs(delta) >= 10 ? 0 : 1); + + return result.riskLevel === "increased" + ? `${formatted}% higher relative odds` + : `${formatted}% lower relative odds`; +} + +function getRiskTone(result: SavedResult): "warm" | "cool" | "neutral" { + if (result.riskLevel === "increased") return "warm"; + if (result.riskLevel === "decreased") return "cool"; + return "neutral"; +} + +function getProgressTitle(progress: OnboardingRunAllProgress): string { + switch (progress.phase) { + case "downloading": + return "Downloading the preview catalog"; + case "decompressing": + return "Preparing the onboarding dataset"; + case "analyzing": + return "Matching your uploaded genotypes"; + case "complete": + return "Preview analysis complete"; + case "error": + return "Preview analysis failed"; + default: + return "Running preview analysis"; + } +} + +function getProgressFraction(progress: OnboardingRunAllProgress): number { + if (progress.phase === "decompressing") return 0.55; + if (progress.phase === "complete") return 1; + if (progress.total <= 0) return 0; + return Math.max(0, Math.min(progress.loaded / progress.total, 1)); +} + +function getBackStep(step: OnboardingStep, completionPath: CompletionPath): OnboardingStep | null { + switch (step) { + case "path": + return "intro"; + case "need_file": + case "need_sequencing": + return "path"; + case "sample_data": + return completionPath === "own_dna_no_test" ? "need_sequencing" : "need_file"; + case "upload": + return completionPath === "own_dna" ? "path" : "sample_data"; + case "run_all": + return "upload"; + case "traits": + return "run_all"; + case "responses": + return "traits"; + default: + return null; + } +} + +export default function ConversionOnboarding({ + isOpen, + onComplete, + onDismiss, + mode = "guided", +}: ConversionOnboardingProps) { + const { genotypeData, isUploaded, isLoading, error, originalFileName, uploadGenotype } = useGenotype(); + const { addResultsBatch, savedResults, getTopResultsByRelevance } = useResults(); + + const [mounted, setMounted] = useState(false); + const [currentStep, setCurrentStep] = useState("intro"); + const [completionPath, setCompletionPath] = useState("own_dna"); + const [showConsentModal, setShowConsentModal] = useState(false); + const [hasConsent, setHasConsent] = useState(false); + const [traitCandidates, setTraitCandidates] = useState([]); + const [selectedTraitIds, setSelectedTraitIds] = useState([]); + const [previewResponses, setPreviewResponses] = useState([]); + const [analysisError, setAnalysisError] = useState(null); + const [responseError, setResponseError] = useState(null); + const [responsesLoading, setResponsesLoading] = useState(false); + const [sampleDataError, setSampleDataError] = useState(null); + const [isSampleLoading, setIsSampleLoading] = useState(false); + const [sampleLoadProgress, setSampleLoadProgress] = useState(INITIAL_SAMPLE_LOAD_PROGRESS); + const [detailResult, setDetailResult] = useState(null); + const [expandedTraitId, setExpandedTraitId] = useState(null); + const [commentaryResult, setCommentaryResult] = useState(null); + const [pendingQuestion, setPendingQuestion] = useState(null); + const [activeQuestion, setActiveQuestion] = useState(null); + const [runAllProgress, setRunAllProgress] = useState({ + phase: "downloading", + loaded: 0, + total: 100, + elapsedSeconds: 0, + processedStudies: 0, + matchCount: 0, + message: "Downloading the lightweight study catalog for your preview.", + }); + + const fileInputRef = useRef(null); + const frameRef = useRef(null); + const analysisStartedRef = useRef(false); + + useEffect(() => { + setMounted(true); + if (typeof window !== "undefined") { + setHasConsent(localStorage.getItem(CONSENT_STORAGE_KEY) === "true"); + } + }, []); + + useEffect(() => { + if (!isOpen) return; + + analysisStartedRef.current = false; + setCurrentStep(mode === "instant_preview" ? "run_all" : "intro"); + setCompletionPath("own_dna"); + setTraitCandidates([]); + setSelectedTraitIds([]); + setPreviewResponses([]); + setAnalysisError(null); + setResponseError(null); + setResponsesLoading(false); + setSampleDataError(null); + setIsSampleLoading(false); + setSampleLoadProgress(INITIAL_SAMPLE_LOAD_PROGRESS); + setDetailResult(null); + setExpandedTraitId(null); + setCommentaryResult(null); + setPendingQuestion(null); + setActiveQuestion(null); + setShowConsentModal(false); + setRunAllProgress({ + phase: "downloading", + loaded: 0, + total: 100, + elapsedSeconds: 0, + processedStudies: 0, + matchCount: 0, + message: "Downloading the lightweight study catalog for your preview.", + }); + trackOnboardingStarted(mode); + }, [isOpen, mode]); + + useEffect(() => { + if (isOpen && mounted) { + trackOnboardingStepViewed(currentStep, { + stepNumber: HAPPY_PATH_STEP_INDEX[currentStep] || 1, + totalSteps: 6, + mode, + userPath: completionPath, + }); + } + }, [completionPath, currentStep, isOpen, mode, mounted]); + + useEffect(() => { + if (typeof window === "undefined" || commentaryResult) return; + setHasConsent(localStorage.getItem(CONSENT_STORAGE_KEY) === "true"); + }, [commentaryResult]); + + const selectedTraitResults = useMemo( + () => traitCandidates.filter((result) => selectedTraitIds.includes(result.studyId)), + [selectedTraitIds, traitCandidates] + ); + const sampleDownloadFraction = sampleLoadProgress.totalBytes > 0 + ? Math.max(0, Math.min(sampleLoadProgress.downloadedBytes / sampleLoadProgress.totalBytes, 1)) + : sampleLoadProgress.phase === "downloading" + ? 0 + : sampleLoadProgress.phase === "idle" + ? 0 + : 1; + const sampleIngestFraction = sampleLoadProgress.phase === "complete" + ? 1 + : sampleLoadProgress.phase === "ingesting" + ? 0.7 + : 0; + const sampleReadyFraction = sampleLoadProgress.phase === "complete" ? 1 : 0; + + const completeFlow = useCallback(() => { + localStorage.setItem("conversion_onboarding_completed", "true"); + localStorage.setItem("user_path", completionPath); + trackOnboardingCompleted(completionPath); + onComplete(); + }, [completionPath, onComplete]); + + const generateSecureResponses = useCallback(async (question: string) => { + setResponsesLoading(true); + setResponseError(null); + setActiveQuestion(question); + + try { + const relevantResults = await getTopResultsByRelevance(question, 500); + const llmDescription = getLLMDescription(); + const contextResults = relevantResults + .map( + (result, index) => `${index + 1}. ${result.traitName} (${result.studyTitle}): + - Your genotype: ${result.userGenotype} + - Risk allele: ${result.riskAllele} + - Risk score: ${formatRiskScore(result.riskScore, result.riskLevel, result.effectType)} (${result.riskLevel}) + - SNP: ${result.matchedSnp}` + ) + .join("\n\n"); + + const systemPrompt = `You are an expert providing personalized, holistic insights about GWAS results. ${llmDescription} + +IMPORTANT CONTEXT: +- The user has uploaded their DNA file and analyzed it against thousands of GWAS studies +- They have ${savedResults.length.toLocaleString()} total results in memory +- You will be provided with the top ${relevantResults.length} most relevant results for this question based on semantic similarity + +YOUR MOST RELEVANT RESULTS FOR THIS QUERY: +${contextResults} + +USER'S SPECIFIC QUESTION: +"${question}" + +⚠️ CRITICAL - STAY ON TOPIC: +- Refuse to answer questions not related to the user's genetic data. +- Answer ONLY the specific trait or theme asked about in the question. +- Do NOT discuss unrelated traits from the context unless directly relevant. +- Any health recommendations are based on LLM training data and may be subject to hallucinations and errors, so the user should consult a physician if they have real health concerns. + +RESPONSE STRUCTURE: +- Use short headers (##) when useful. +- Keep the answer focused, specific, and readable. +- Explain findings in plain language. +- Include a short practical takeaway section. +- Do NOT use markdown tables. +- Prefer short paragraphs and flat bullet lists. +- Keep the total answer compact enough to fit comfortably in an in-app preview. +- This is educational, not medical advice.`; + + const response = await callLLM( + [ + { + role: "system", + content: systemPrompt, + }, + { + role: "user", + content: question, + }, + ], + { + maxTokens: 2200, + temperature: 0.7, + reasoningEffort: "medium", + } + ); + + const answer = response.content.trim(); + if (!answer) { + throw new Error("The DNA Chat preview returned an empty response."); + } + + setPreviewResponses((prev) => { + const withoutCurrent = prev.filter((item) => item.question !== question); + return [...withoutCurrent, { question, answer, studiesUsed: relevantResults.length }]; + }); + setActiveQuestion(question); + trackLLMQuestionAsked(); + } catch (generationError) { + console.error("[ConversionOnboarding] Secure responses failed:", generationError); + setResponseError( + generationError instanceof Error + ? generationError.message + : "The DNA Chat preview could not be generated right now." + ); + } finally { + setResponsesLoading(false); + } + }, [getTopResultsByRelevance, savedResults.length]); + + const loadSampleData = useCallback(async () => { + if (isSampleLoading) return; + + setSampleDataError(null); + setIsSampleLoading(true); + trackSampleDataStarted("onboarding"); + setSampleLoadProgress({ + phase: "downloading", + downloadedBytes: 0, + totalBytes: 0, + }); + + try { + const response = await fetch(SAMPLE_DATA_URL, { + method: "GET", + }); + + if (!response.ok) { + throw new Error(`Sample data download failed with status ${response.status}.`); + } + + const totalBytes = Number(response.headers.get("content-length") || "0"); + let blob: Blob; + + if (response.body) { + const reader = response.body.getReader(); + const chunks: Uint8Array[] = []; + let downloadedBytes = 0; + + while (true) { + const { done, value } = await reader.read(); + if (done) break; + if (!value) continue; + + chunks.push(value); + downloadedBytes += value.byteLength; + setSampleLoadProgress({ + phase: "downloading", + downloadedBytes, + totalBytes, + }); + } + + blob = new Blob(chunks as unknown as BlobPart[], { type: "text/plain" }); + } else { + blob = await response.blob(); + } + + const resolvedTotalBytes = totalBytes || blob.size; + setSampleLoadProgress({ + phase: "ingesting", + downloadedBytes: resolvedTotalBytes, + totalBytes: resolvedTotalBytes, + }); + + const sampleFile = new File([blob], "monadicdna-sample-data.txt", { type: "text/plain" }); + const uploaded = await uploadGenotype(sampleFile); + + if (!uploaded) { + throw new Error("The sample data could not be loaded into the app."); + } + + trackSampleDataLoaded("onboarding", sampleFile.size); + setSampleLoadProgress({ + phase: "complete", + downloadedBytes: resolvedTotalBytes, + totalBytes: resolvedTotalBytes, + }); + + await new Promise((resolve) => window.setTimeout(resolve, 250)); + setCurrentStep("run_all"); + } catch (sampleError) { + console.error("[ConversionOnboarding] Sample data load failed:", sampleError); + trackSampleDataFailed( + "onboarding", + sampleError instanceof Error ? sampleError.message : "sample_data_failed" + ); + setSampleDataError( + sampleError instanceof Error + ? sampleError.message + : "The sample data could not be loaded right now." + ); + } finally { + setIsSampleLoading(false); + } + }, [isSampleLoading, uploadGenotype]); + + const startRunAll = useCallback(async () => { + if (!genotypeData) return; + + try { + setAnalysisError(null); + trackRunAllStarted(0); + + const results = await runAllAnalysisOnboarding( + genotypeData, + (progress) => setRunAllProgress(progress), + (studyId) => savedResults.some((result) => result.studyId === studyId) + ); + + await addResultsBatch(results); + + const mergedResults = dedupeStudyResults([...savedResults, ...results]); + const candidates = buildTraitCandidates(mergedResults); + + if (!candidates.length) { + throw new Error("The preview run completed, but there were not enough matched traits to build the next screen."); + } + + setTraitCandidates(candidates); + setSelectedTraitIds(candidates.slice(0, Math.min(REQUIRED_TRAIT_COUNT, candidates.length)).map((result) => result.studyId)); + setRunAllProgress((prev) => ({ + ...prev, + phase: "complete", + loaded: prev.processedStudies || prev.loaded, + total: prev.processedStudies || prev.total, + message: "Preview analysis complete.", + })); + trackRunAllCompleted(0, results.length, candidates.length, "onboarding"); + } catch (runError) { + console.error("[ConversionOnboarding] Onboarding preview failed:", runError); + const message = runError instanceof Error ? runError.message : "The onboarding preview did not complete cleanly."; + trackRunAllFailed("onboarding", message); + setAnalysisError(message); + setRunAllProgress((prev) => ({ + ...prev, + phase: "error", + message, + })); + } + }, [addResultsBatch, genotypeData, savedResults]); + + useEffect(() => { + if (!isOpen || currentStep !== "run_all" || !genotypeData || genotypeData.size === 0 || analysisStartedRef.current) { + return; + } + + analysisStartedRef.current = true; + void startRunAll(); + }, [currentStep, genotypeData, isOpen, startRunAll]); + + useEffect(() => { + frameRef.current?.scrollTo({ top: 0, behavior: "smooth" }); + }, [currentStep]); + + const goToResponses = useCallback(() => { + setPreviewResponses([]); + setResponseError(null); + setResponsesLoading(false); + setDetailResult(null); + setPendingQuestion(null); + setActiveQuestion(null); + + setCurrentStep("responses"); + }, []); + + const slideNumber = HAPPY_PATH_STEP_INDEX[currentStep] || 1; + const progressFraction = getProgressFraction(runAllProgress); + const backStep = getBackStep(currentStep, completionPath); + + if (!isOpen || !mounted) return null; + + return createPortal( + <> + {commentaryResult && ( + setCommentaryResult(null)} + currentResult={commentaryResult} + allResults={savedResults} + skipPersonalizationPrompt + /> + )} + + { + localStorage.setItem(CONSENT_STORAGE_KEY, "true"); + setHasConsent(true); + setShowConsentModal(false); + trackAIConsentGiven(); + if (pendingQuestion) { + const nextQuestion = pendingQuestion; + setPendingQuestion(null); + void generateSecureResponses(nextQuestion); + return; + } + }} + onDecline={() => { + setPendingQuestion(null); + setShowConsentModal(false); + trackAIConsentDeclined(); + }} + /> + +
+
+
+ {onDismiss && ( + + )} +
Step {slideNumber} of 6
+ + {currentStep === "intro" && ( +
+

Monadic DNA Explorer uses 1m+ scientifically vetted genetic traits to help you understand your health, diet and exercise.

+

We do not store or look at your DNA or sell it to third parties.

+ + + +
+ )} + + {currentStep === "path" && ( +
+

Let's get you ready to use Explorer. Pick the option which best applies to you:

+
+ + + +
+
+ )} + + {currentStep === "need_file" && ( +
+

Click on your DNA testing provider for instructions on how to download a copy of your DNA data

+
+ + +
+

While you're waiting for your data, let's give you a taste of what you will be able to do with your data.

+
+ +
+
+ )} + + {currentStep === "need_sequencing" && ( +
+

We are working on an app called Batcher for letting you privately and anonymously get your DNA sequenced.

+

Use the link below to sign up and get notified as soon as the service is ready.

+
+ +
+

While you're waiting to get sequenced, let's give you a taste of what you will be able to do with your data.

+
+ +
+
+ )} + + {currentStep === "sample_data" && ( +
+

Downloading and uploading some sample data to help you explore this product!

+

+ Your data never leaves your device. Explorer stores it in the IndexedDB of your browser. +

+

We not do not transmit your data to our servers or snoop on it in any way.

+ {(isSampleLoading || sampleLoadProgress.phase === "complete") && ( +
+
+
+ Downloading sample dataset + + {sampleLoadProgress.phase === "downloading" + ? sampleLoadProgress.totalBytes > 0 + ? `${Math.round(sampleDownloadFraction * 100)}% downloaded (${formatSampleBytes(sampleLoadProgress.downloadedBytes)} / ${formatSampleBytes(sampleLoadProgress.totalBytes)})` + : `${formatSampleBytes(sampleLoadProgress.downloadedBytes)} downloaded` + : "Download complete"} + +
+
+ +
+
+ +
+
+ Loading sample data into your browser + + {sampleLoadProgress.phase === "complete" + ? "Sample data loaded into the app" + : sampleLoadProgress.phase === "ingesting" + ? "Parsing and preparing the sample file locally" + : "Waiting for download to finish"} + +
+
+ +
+
+ +
+
+ Ready to analyze + + {sampleLoadProgress.phase === "complete" + ? "Sample data is ready. Starting the preview analysis now" + : "This will unlock the onboarding preview as soon as loading finishes"} + +
+
+ +
+
+
+ )} +
+ +
+ {(sampleDataError || error) && ( +
+ Sample data issue + {sampleDataError || error} +
+ )} +
+ )} + + {currentStep === "upload" && ( +
+

Upload your DNA data to get started!

+

Your data never leaves your device. Explorer stores it in the IndexedDB of your browser.

+

We not do not transmit your data to our servers or snoop on it in any way.

+ +
+ + + { + const file = event.target.files?.[0]; + if (!file) return; + const uploaded = await uploadGenotype(file, "onboarding_upload"); + if (uploaded) { + trackOnboardingAction("own_data_uploaded"); + } + event.target.value = ""; + }} + /> + + {originalFileName &&

{originalFileName}

} + {error &&

{error}

} +
+ + {isUploaded && genotypeData && genotypeData.size > 0 && ( +

Your data has been uploaded and is now ready for analysis!

+ )} +
+ )} + + {currentStep === "run_all" && ( +
+

Let's analyze your data fully locally in your browser.

+ {runAllProgress.phase === "downloading" &&

Downloading one million scientifically vetted traits from the GWAS Catalog..

} + {runAllProgress.phase === "decompressing" &&

Preparing the GWAS Catalog data in your browser..

} + {(runAllProgress.phase === "analyzing" || runAllProgress.phase === "complete") && ( +

Running your data against the GWAS Catalog to find all matches..

+ )} + +
+
+

{getProgressTitle(runAllProgress)}

+ +
+ +
+ +
+ {runAllProgress.phase === "downloading" && ( + <> +
{Math.round(progressFraction * 100)}% Downloaded
+ + )} + + {runAllProgress.phase === "decompressing" && ( + <> +
{Math.round(progressFraction * 100)}% Loaded..
+ + )} + + {runAllProgress.phase === "analyzing" && ( + <> +
{Math.round(progressFraction * 100)}% Processed
+
{runAllProgress.processedStudies.toLocaleString()} studies scanned
+ + )} + + {runAllProgress.phase === "complete" && ( + <> +
We found {runAllProgress.matchCount.toLocaleString()} matched traits. Let's look at some traits!
+ + )} + + {runAllProgress.phase === "error" &&
{analysisError || runAllProgress.message}
} +
+
+ + {runAllProgress.phase === "complete" && traitCandidates.length > 0 && ( + + )} + + {analysisError && ( +
+ Preview issue + {analysisError} +
+ )} +
+ )} + + {currentStep === "traits" && ( +
+

Here are {selectedTraitResults.length} curated traits from your data.

+

Using the Explore tab in at app, you can filter through and explore all {savedResults.length.toLocaleString()} of your results!

+ +
+ {selectedTraitResults.map((result) => { + const isOpen = expandedTraitId === result.studyId; + const isExpanded = detailResult?.studyId === result.studyId; + return ( +
+ + + {isOpen && ( +
+
+
+ Study Title: {result.studyTitle} + {result.mappedGene && Gene: {result.mappedGene}} + SNP: {result.matchedSnp} +
+
+ + +
+
+ {isExpanded && ( +
+
+ Your genotype + {result.userGenotype} +
+
+ Your result + {formatRiskHeadline(result)} + {formatRiskScore(result.riskScore, result.riskLevel, result.effectType)} for your genotype +
+
+ )} +
+ )} +
+ ); + })} +
+ +
+ Next Step + Now ask questions about your whole dataset with secure AI. +

Use premium LLM analysis to answer broader questions using the most relevant traits from your uploaded DNA data.

+ +
+
+ )} + + {currentStep === "responses" && ( +
+

Here is an advance look at DNA Chat.

+

Tap one of these starter questions to see how DNA Chat answers with the most relevant traits from your full dataset.

+ +
+ {CHAT_PREVIEW_QUESTIONS.map((question) => { + const response = previewResponses.find((item) => item.question === question); + const isOpen = activeQuestion === question; + const isLoadingCurrent = responsesLoading && activeQuestion === question; + + return ( +
+ + + {isOpen && ( +
+ {isLoadingCurrent && ( +
+
+ Running DNA Chat preview + Searching your matched results for this question +
+ +
+ )} + + {!isLoadingCurrent && responseError && !response && ( +
+ Secure preview issue + {responseError} +
+ )} + + {!isLoadingCurrent && response && ( +
+
+ + {response.answer} + +
+
Used {response.studiesUsed.toLocaleString()} relevant genetic results
+
+ )} +
+ )} +
+ ); + })} +
+ + {!responsesLoading && !responseError && previewResponses.length > 0 && ( + <> +

Use promo code FREEWEEK for a free week of premium features.

+

Personalize your answers by entering your demographics, history, reports documents in the app.

+

Nobody apart from you can ever look at your chat logs or personalization information.

+

You're now ready to start using the app to unlock your diet, lifestyle and health insights!

+ + )} + + +
+ )} + +
+ {backStep ? ( + + ) : ( + + )} + {slideNumber} / 6 +
+
+
+
+ , + document.body + ); +} diff --git a/app/components/Footer.tsx b/app/components/Footer.tsx index b4ab834..38caebd 100644 --- a/app/components/Footer.tsx +++ b/app/components/Footer.tsx @@ -2,60 +2,43 @@ export default function Footer() { return (