Add AI-backed agent chat
This commit is contained in:
Theodore Song
@@ -83,3 +83,7 @@ RISK_ADMIN_TOKEN=
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ADMIN_ALERT_EMAIL=
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CUSTOMER_SUPPORT_EMAIL=
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RISK_ADMIN_WALLET=
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# Agent chat
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OPENAI_API_KEY=
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OPENAI_MODEL=gpt-5.6-luna
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@@ -0,0 +1,168 @@
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const MAX_HISTORY = 12;
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const MAX_POSITIONS = 10;
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const MAX_SUGGESTIONS = 8;
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function cleanText(value, max = 1200) {
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return String(value || "").replace(/\s+/g, " ").trim().slice(0, max);
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}
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function safeNumber(value, fallback = 0) {
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const n = Number(value);
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return Number.isFinite(n) ? n : fallback;
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}
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function compactPosition(pos) {
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return {
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question: cleanText(pos.question, 180),
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side: cleanText(pos.side, 8),
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entry_price: safeNumber(pos.entry_price),
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current_price: safeNumber(pos.current_price),
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value: safeNumber(pos.value),
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unrealized_pnl: safeNumber(pos.unrealized_pnl),
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conviction: safeNumber(pos.conviction),
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category: cleanText(pos.category, 60),
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opened_at: cleanText(pos.opened_at, 40),
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url: cleanText(pos.url, 240),
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};
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}
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function compactSuggestion(sug) {
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return {
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question: cleanText(sug.question, 180),
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side: cleanText(sug.side, 8),
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entry_price: safeNumber(sug.entry_price),
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conviction: safeNumber(sug.conviction),
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edge: safeNumber(sug.edge),
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category: cleanText(sug.category, 60),
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rationale: cleanText(sug.rationale, 240),
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url: cleanText(sug.url, 240),
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};
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}
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function compactHistory(history) {
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return (Array.isArray(history) ? history : []).slice(-MAX_HISTORY).map((m) => ({
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role: m && m.role === "user" ? "user" : "assistant",
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text: cleanText(m && m.text, 900),
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})).filter((m) => m.text);
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}
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function outputText(data) {
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if (data && typeof data.output_text === "string") return data.output_text.trim();
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const chunks = [];
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for (const item of data && Array.isArray(data.output) ? data.output : []) {
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for (const content of Array.isArray(item.content) ? item.content : []) {
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if (content.type === "output_text" && content.text) chunks.push(content.text);
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if (content.type === "text" && content.text) chunks.push(content.text);
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}
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}
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return chunks.join("\n").trim();
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}
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export default async function handler(req, res) {
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res.setHeader("Cache-Control", "no-store");
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if (req.method !== "POST") {
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res.setHeader("Allow", "POST");
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return res.status(405).json({ ok: false, error: "Method not allowed" });
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}
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const apiKey = process.env.OPENAI_API_KEY;
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if (!apiKey) {
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return res.status(501).json({
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ok: false,
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code: "missing_openai_key",
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error: "Agent AI chat needs OPENAI_API_KEY in Vercel environment variables.",
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});
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}
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const body = req.body || {};
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const question = cleanText(body.question, 1000);
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if (!question) return res.status(400).json({ ok: false, error: "Question is required." });
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const agent = body.agent || {};
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const portfolio = body.portfolio || {};
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const context = {
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agent: {
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id: cleanText(agent.id, 40),
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name: cleanText(agent.name, 80),
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kind: cleanText(agent.kind, 40),
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style: cleanText(agent.style || agent.blurb, 800),
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voice: cleanText(agent.voice, 200),
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},
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portfolio: {
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equity: safeNumber(portfolio.equity),
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cash: safeNumber(portfolio.cash),
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return_pct: safeNumber(portfolio.return_pct),
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pnl: safeNumber(portfolio.pnl),
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rank: safeNumber(portfolio.rank),
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open_positions: safeNumber(portfolio.open_positions),
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last_decision: cleanText(portfolio.last_decision, 700),
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recent_actions: (Array.isArray(portfolio.recent_actions) ? portfolio.recent_actions : []).slice(-8).map((x) => cleanText(x, 260)),
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positions: (Array.isArray(portfolio.positions) ? portfolio.positions : []).slice(0, MAX_POSITIONS).map(compactPosition),
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snapshots: (Array.isArray(portfolio.snapshots) ? portfolio.snapshots : []).slice(-8).map((s) => ({
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date: cleanText(s.date || s.timestamp, 40),
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equity: safeNumber(s.equity),
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return_pct: safeNumber(s.return_pct),
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open_positions: safeNumber(s.open_positions),
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})),
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},
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leaderboard: (Array.isArray(body.leaderboard) ? body.leaderboard : []).slice(0, 10).map((r) => ({
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name: cleanText(r.name, 80),
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return_pct: safeNumber(r.return_pct),
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equity: safeNumber(r.equity),
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rank: safeNumber(r.rank),
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})),
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suggestions: (Array.isArray(body.suggestions) ? body.suggestions : []).slice(0, MAX_SUGGESTIONS).map(compactSuggestion),
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history: compactHistory(body.history),
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};
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const instructions = [
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`You are ${context.agent.name || "a Polymarket paper-trading agent"} inside Poly Arena.`,
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"Speak in first person as the selected agent, like a real chat partner.",
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"Answer the user's exact question instead of repeating a generic performance summary.",
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"Use the supplied portfolio, positions, leaderboard, suggestions, and chat history as your facts.",
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"Be specific about trades, risk, performance, and uncertainty when the data is available.",
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"Do not claim you can guarantee profits or force agents to make money.",
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"Do not give personalized financial advice. Keep it framed as paper trading, research, or manual review.",
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"If asked what you will do next, describe likely decision rules, not a guaranteed action.",
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"Keep responses concise: 2 to 5 short paragraphs or a tight bullet list.",
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].join("\n");
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const input = [
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{
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role: "user",
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content: [{
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type: "input_text",
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text: `Context JSON:\n${JSON.stringify(context)}\n\nUser message:\n${question}`,
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}],
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},
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];
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try {
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const response = await fetch("https://api.openai.com/v1/responses", {
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method: "POST",
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headers: {
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"Authorization": `Bearer ${apiKey}`,
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"Content-Type": "application/json",
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},
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body: JSON.stringify({
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model: process.env.OPENAI_MODEL || "gpt-5.6-luna",
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instructions,
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input,
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max_output_tokens: 550,
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}),
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});
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const data = await response.json().catch(() => ({}));
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if (!response.ok) {
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return res.status(response.status).json({
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ok: false,
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error: data && data.error && data.error.message ? data.error.message : "OpenAI chat request failed.",
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});
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}
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const text = outputText(data);
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return res.status(200).json({ ok: true, text: text || "I am here, but I could not form a useful answer from the current context." });
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} catch (err) {
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return res.status(500).json({ ok: false, error: err && err.message ? err.message : "Agent chat failed." });
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}
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}
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+47
-4
@@ -184,6 +184,7 @@ body:not(.personal-mode) [data-tab="live"]{display:none!important}
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.chat-msg{border:1px solid var(--border);border-radius:14px;padding:11px 13px;font-size:13px;line-height:1.45;white-space:pre-wrap}
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.chat-msg.user{align-self:flex-end;max-width:82%;background:rgba(124,140,255,.16);border-color:rgba(124,140,255,.35)}
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.chat-msg.agent{align-self:flex-start;max-width:92%;background:rgba(255,255,255,.045)}
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.chat-msg.pending{color:var(--muted);font-style:italic}
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.chat-input-row{display:flex;gap:8px;margin-top:12px}
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.chat-input-row .input{flex:1}
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@media (max-width:760px){.agent-chat{grid-template-columns:1fr}.chat-msg.user,.chat-msg.agent{max-width:100%}}
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@@ -722,7 +723,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
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</section>
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<footer>
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Build 8400310+risk-tune · Paper trading only · Live prices from Polymarket's public Gamma API · Not financial advice ·
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Build ai-chat · Paper trading only · Live prices from Polymarket's public Gamma API · Not financial advice ·
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<a class="market-link" href="https://github.com/theodore-song/polymarket-analyst" target="_blank" rel="noopener">Source on GitHub</a>
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</footer>
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</div>
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@@ -2246,6 +2247,36 @@ function agentChatReply(agentId,question,history=[]){
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}
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return conversationalAgentReply(cfg,row,p,q);
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}
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function agentChatPayload(agentId,question,history=[]){
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const st=loadState(),cfg=agentById(agentId),p=st.agents[agentId]||defaultPortfolio();
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const rows=board(),row=rows.find(r=>r.c.id===agentId)||{c:cfg,p,eq:equity(p),pnl:equity(p)-p.starting_balance,ret:(equity(p)/p.starting_balance-1)*100};
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const rank=(rows.findIndex(r=>r.c.id===agentId)+1)||rows.length;
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const ranked=cfg.rank?safeRankSuggestions(cfg,(loadSuggestions().suggestions||[])):(loadSuggestions().suggestions||[]);
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return {
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agent:{id:cfg.id,name:cfg.name,kind:cfg.kind,blurb:agentPlainBlurb(cfg,st),voice:agentVoice(cfg).tone},
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question,
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history:(history||[]).slice(-12).filter(m=>!m.pending).map(m=>({role:m.role==="user"?"user":"assistant",text:m.text})),
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portfolio:{
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equity:+row.eq.toFixed(2),cash:+(p.cash||0).toFixed(2),return_pct:+row.ret.toFixed(2),pnl:+row.pnl.toFixed(2),
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rank,open_positions:(p.positions||[]).length,last_decision:decisionSummary(p),
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positions:(p.positions||[]).slice().sort((a,b)=>Math.abs(b.unrealized_pnl||0)-Math.abs(a.unrealized_pnl||0)).slice(0,10),
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recent_actions:(p.history||[]).slice(-8).map(h=>h.detail||`${h.action||"ACTION"} ${h.question||""}`),
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snapshots:(p.snapshots||[]).slice(-8),
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},
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leaderboard:rows.slice(0,10).map((r,i)=>({rank:i+1,name:r.c.name,return_pct:+r.ret.toFixed(2),equity:+r.eq.toFixed(2)})),
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suggestions:ranked.filter(s=>s.side==="YES"||s.side==="NO").slice(0,8),
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};
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}
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async function askAgentAI(agentId,question,history=[]){
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const r=await fetch("/api/agent-chat",{
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method:"POST",
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headers:{"Content-Type":"application/json"},
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body:JSON.stringify(agentChatPayload(agentId,question,history)),
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});
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const data=await r.json().catch(()=>({}));
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if(!r.ok||!data.ok)throw new Error(data.error||"Agent AI chat is not available yet.");
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return data.text||"I am here, but I do not have a strong answer from the current context.";
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}
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function renderAgentChat(agentId){
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const root=$("agentChatRoot");if(!root)return;
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const cfg=agentById(agentId),st=loadState(),p=st.agents[agentId]||defaultPortfolio(),eq=equity(p),ret=(eq/p.starting_balance-1)*100;
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@@ -2267,16 +2298,28 @@ function renderAgentChat(agentId){
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</div>
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</div>
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<div class="chat-panel">
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<div class="chat-window" id="agentChatWindow">${msgs.map(m=>`<div class="chat-msg ${m.role==="user"?"user":"agent"}">${esc(m.text)}</div>`).join("")}</div>
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<div class="chat-window" id="agentChatWindow">${msgs.map(m=>`<div class="chat-msg ${m.role==="user"?"user":"agent"} ${m.pending?"pending":""}">${esc(m.text)}</div>`).join("")}</div>
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<div class="chat-input-row"><input class="input" id="agentChatInput" placeholder="Ask ${esc(cfg.name)} about performance, trades, risk, or plans..." /><button class="btn primary" id="agentChatSend">Send</button></div>
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</div>
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</div>`;
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const send=(text)=>{
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const send=async(text)=>{
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const q=String(text||"").trim();if(!q)return;
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const next=loadAgentChats();if(!next[agentId])next[agentId]=agentChatSeed(agentId);
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const history=next[agentId].slice();
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next[agentId].push({role:"user",text:q},{role:"agent",text:agentChatReply(agentId,q,history)});
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next[agentId].push({role:"user",text:q},{role:"agent",text:"Thinking with my live portfolio context...",pending:true});
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next[agentId]=next[agentId].slice(-60);saveAgentChats(next);renderAgentChat(agentId);
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let answer;
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try{
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answer=await askAgentAI(agentId,q,history);
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}catch(e){
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const local=agentChatReply(agentId,q,history);
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answer=`${local}\n\nAI chat is not fully connected yet: ${e.message||"missing server configuration"}`;
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}
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const done=loadAgentChats();if(!done[agentId])done[agentId]=[];
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const idx=[...done[agentId]].reverse().findIndex(m=>m.pending);
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if(idx>=0)done[agentId][done[agentId].length-1-idx]={role:"agent",text:answer};
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else done[agentId].push({role:"agent",text:answer});
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done[agentId]=done[agentId].slice(-60);saveAgentChats(done);renderAgentChat(agentId);
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};
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document.querySelectorAll("[data-chat-prompt]").forEach(btn=>btn.onclick=()=>send(btn.dataset.chatPrompt));
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const input=$("agentChatInput"),sendBtn=$("agentChatSend");
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