Added AI agent to Retirement
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@ -517,7 +517,7 @@ Return ONLY a JSON array, no extra text:
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// 5) Call OpenAI (ignoring scenarioRow.start_date for date logic)
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const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
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const completion = await openai.chat.completions.create({
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model: 'gpt-3.5-turbo', // or 'gpt-4'
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model: 'gpt-4o-mini', // or 'gpt-4'
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messages,
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temperature: 0.7,
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max_tokens: 600
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@ -1140,7 +1140,7 @@ messagesToSend.push(...chatHistory.slice(-MAX_CHAT_TURNS));
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// ------------------------------------------------
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const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
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const completion = await openai.chat.completions.create({
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model: "gpt-3.5-turbo-0125",
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model: "gpt-4o-mini",
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messages: messagesToSend,
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temperature: 0.3,
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max_tokens: 1000
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@ -1335,6 +1335,159 @@ Check your Milestones tab. Let me know if you want any changes!
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}
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});
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/* ──────────────────────────────────────────────
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RETIREMENT AI-CHAT ENDPOINT
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─────────────────────────────────────────── */
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app.post(
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'/api/premium/retirement/aichat',
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authenticatePremiumUser,
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async (req, res) => {
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try {
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/* 0) ── pull + sanity-check inputs ─────────────── */
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const {
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prompt = '',
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scenario_id = '',
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chatHistory = []
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} = req.body || {};
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if (!prompt.trim()) return res.status(400).json({ error: 'Prompt is required.' });
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if (!scenario_id) return res.status(400).json({ error: 'scenario_id is required.' });
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/* 1) ── ownership guard ────────────────────────── */
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const [[scenario]] = await pool.query(
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'SELECT * FROM career_profiles WHERE id = ? AND user_id = ?',
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[scenario_id, req.id]
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);
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if (!scenario) return res.status(404).json({ error: 'Scenario not found.' });
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/* 2) ── locate the *text* of the last user turn ─ */
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let userMsgStr = prompt.trim();
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if (Array.isArray(chatHistory)) {
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for (let i = chatHistory.length - 1; i >= 0; i--) {
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const m = chatHistory[i];
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if (m?.role === 'user' && typeof m.content === 'string') {
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userMsgStr = m.content;
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break;
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}
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}
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}
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/* helper: force every .content to be a plain string */
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const toStr = v =>
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v === null || v === undefined
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? ''
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: typeof v === 'string'
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? v
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: JSON.stringify(v);
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const sanitizedHistory = (Array.isArray(chatHistory) ? chatHistory : [])
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.map(({ role = 'user', content = '' }) => ({ role, content: toStr(content) }));
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/* 3) ── system instructions ────────────────────── */
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const systemMsg = `
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You are AptivaAI's retirement-planning coach.
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Rules:
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• Educational guidance only — **NO** personalised investment advice.
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• Never recommend specific securities or products.
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• Friendly tone; ≤ 180 words.
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• If the scenario needs updating, append a JSON block:
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\`\`\`json
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{ "retirement_start_date": "2045-01-01" }
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\`\`\`
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If nothing changes, just return “{"noop":true}”.
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• Always end with: “AptivaAI is an educational tool – not advice.”
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`.trim();
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/* 4) ── call OpenAI ─────────────────────────────── */
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const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
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const chatRes = await openai.chat.completions.create({
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model : 'gpt-4o-mini',
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temperature : 0.6,
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max_tokens : 600,
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messages : [
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{ role: 'system', content: systemMsg },
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...sanitizedHistory,
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{ role: 'user', content: userMsgStr }
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]
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});
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const raw = (chatRes.choices?.[0]?.message?.content || '').trim();
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res.set({
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'X-OpenAI-Prompt-Tokens' : chatRes.usage?.prompt_tokens ?? 0,
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'X-OpenAI-Completion-Tokens': chatRes.usage?.completion_tokens ?? 0
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});
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/* 5) ── extract (or ignore) JSON patch ──────────── */
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let visibleReply = raw;
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let scenarioPatch = null;
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// A. fenced ```json```? ───────────────────────────
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let match = raw.match(/```json\s*([\s\S]+?)```/i);
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// B. or a “loose” top-level { … }? (no fences) ─────
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if (!match) {
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const open = raw.search(/[{\[]/);
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if (open !== -1) {
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const close = Math.max(raw.lastIndexOf('}'), raw.lastIndexOf(']'));
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if (close > open) match = [ , raw.slice(open, close + 1) ];
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}
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}
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if (match) {
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try { scenarioPatch = JSON.parse(match[1]); } catch {/* ignore bad JSON */}
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visibleReply = raw.replace(match[0] || match[1], '').trim();
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}
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/* ignore {"noop":true} or empty objects */
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if (
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!scenarioPatch ||
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!Object.keys(scenarioPatch)
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.filter(k => k !== 'noop')
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.length
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) {
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scenarioPatch = null;
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}
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/* 6) ── persist real changes ───────────────────── */
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if (scenarioPatch) {
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const fields = Object.keys(scenarioPatch);
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const setters = fields.map(f => `${f} = ?`).join(', ');
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const values = fields.map(f => scenarioPatch[f]);
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await pool.query(
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`UPDATE career_profiles
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SET ${setters},
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updated_at = CURRENT_TIMESTAMP
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WHERE id = ? AND user_id = ?`,
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[...values, scenario_id, req.id]
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);
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}
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/* if the patch included a new retirement_start_date, sync the milestone */
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if (scenarioPatch?.retirement_start_date) {
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await pool.query(
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`UPDATE milestones
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SET date = ?,
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updated_at = CURRENT_TIMESTAMP
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WHERE career_profile_id = ?
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AND user_id = ?
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AND LOWER(title) LIKE 'retirement%'`,
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[scenarioPatch.retirement_start_date, scenario_id, req.id]
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);
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// (optional) if no milestone matched, you could INSERT one here instead
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}
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/* 7) ── send to client ─────────────────────────── */
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return res.json({
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reply: visibleReply || 'Sorry, no response – please try again.',
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...(scenarioPatch ? { scenarioPatch } : {})
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});
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} catch (err) {
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console.error('retirement/aichat error:', err);
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return res.status(500).json({ error: 'Internal error – please try again later.' });
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}
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}
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);
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/***************************************************
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AI MILESTONE CONVERSION ENDPOINT
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@ -1488,7 +1641,7 @@ app.post('/api/premium/ai-risk-analysis', authenticatePremiumUser, async (req, r
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});
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}
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// 2) If missing, call GPT-3.5 to generate analysis
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// 2) If missing, call GPT-4 to generate analysis
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const prompt = `
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The user has a career named: ${careerName}
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Description: ${jobDescription}
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@ -1504,7 +1657,7 @@ app.post('/api/premium/ai-risk-analysis', authenticatePremiumUser, async (req, r
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`;
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const completion = await openai.chat.completions.create({
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model: 'gpt-3.5-turbo',
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model: "gpt-4o-mini",
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messages: [{ role: 'user', content: prompt }],
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temperature: 0.3,
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max_tokens: 200,
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@ -1574,7 +1727,7 @@ app.post('/api/public/ai-risk-analysis', async (req, res) => {
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const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
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const completion = await openai.chat.completions.create({
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model: 'gpt-3.5-turbo',
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model: 'gpt-4o-mini',
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messages: [{ role: 'user', content: prompt }],
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temperature: 0.3,
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max_tokens: 200,
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