Fold agent chat into live API

api/agent-chat.js

@@ -1,168 +0,0 @@
-const MAX_HISTORY = 12;
-const MAX_POSITIONS = 10;
-const MAX_SUGGESTIONS = 8;
-
-function cleanText(value, max = 1200) {
-  return String(value || "").replace(/\s+/g, " ").trim().slice(0, max);
-}
-
-function safeNumber(value, fallback = 0) {
-  const n = Number(value);
-  return Number.isFinite(n) ? n : fallback;
-}
-
-function compactPosition(pos) {
-  return {
-    question: cleanText(pos.question, 180),
-    side: cleanText(pos.side, 8),
-    entry_price: safeNumber(pos.entry_price),
-    current_price: safeNumber(pos.current_price),
-    value: safeNumber(pos.value),
-    unrealized_pnl: safeNumber(pos.unrealized_pnl),
-    conviction: safeNumber(pos.conviction),
-    category: cleanText(pos.category, 60),
-    opened_at: cleanText(pos.opened_at, 40),
-    url: cleanText(pos.url, 240),
-  };
-}
-
-function compactSuggestion(sug) {
-  return {
-    question: cleanText(sug.question, 180),
-    side: cleanText(sug.side, 8),
-    entry_price: safeNumber(sug.entry_price),
-    conviction: safeNumber(sug.conviction),
-    edge: safeNumber(sug.edge),
-    category: cleanText(sug.category, 60),
-    rationale: cleanText(sug.rationale, 240),
-    url: cleanText(sug.url, 240),
-  };
-}
-
-function compactHistory(history) {
-  return (Array.isArray(history) ? history : []).slice(-MAX_HISTORY).map((m) => ({
-    role: m && m.role === "user" ? "user" : "assistant",
-    text: cleanText(m && m.text, 900),
-  })).filter((m) => m.text);
-}
-
-function outputText(data) {
-  if (data && typeof data.output_text === "string") return data.output_text.trim();
-  const chunks = [];
-  for (const item of data && Array.isArray(data.output) ? data.output : []) {
-    for (const content of Array.isArray(item.content) ? item.content : []) {
-      if (content.type === "output_text" && content.text) chunks.push(content.text);
-      if (content.type === "text" && content.text) chunks.push(content.text);
-    }
-  }
-  return chunks.join("\n").trim();
-}
-
-export default async function handler(req, res) {
-  res.setHeader("Cache-Control", "no-store");
-  if (req.method !== "POST") {
-    res.setHeader("Allow", "POST");
-    return res.status(405).json({ ok: false, error: "Method not allowed" });
-  }
-
-  const apiKey = process.env.OPENAI_API_KEY;
-  if (!apiKey) {
-    return res.status(501).json({
-      ok: false,
-      code: "missing_openai_key",
-      error: "Agent AI chat needs OPENAI_API_KEY in Vercel environment variables.",
-    });
-  }
-
-  const body = req.body || {};
-  const question = cleanText(body.question, 1000);
-  if (!question) return res.status(400).json({ ok: false, error: "Question is required." });
-
-  const agent = body.agent || {};
-  const portfolio = body.portfolio || {};
-  const context = {
-    agent: {
-      id: cleanText(agent.id, 40),
-      name: cleanText(agent.name, 80),
-      kind: cleanText(agent.kind, 40),
-      style: cleanText(agent.style || agent.blurb, 800),
-      voice: cleanText(agent.voice, 200),
-    },
-    portfolio: {
-      equity: safeNumber(portfolio.equity),
-      cash: safeNumber(portfolio.cash),
-      return_pct: safeNumber(portfolio.return_pct),
-      pnl: safeNumber(portfolio.pnl),
-      rank: safeNumber(portfolio.rank),
-      open_positions: safeNumber(portfolio.open_positions),
-      last_decision: cleanText(portfolio.last_decision, 700),
-      recent_actions: (Array.isArray(portfolio.recent_actions) ? portfolio.recent_actions : []).slice(-8).map((x) => cleanText(x, 260)),
-      positions: (Array.isArray(portfolio.positions) ? portfolio.positions : []).slice(0, MAX_POSITIONS).map(compactPosition),
-      snapshots: (Array.isArray(portfolio.snapshots) ? portfolio.snapshots : []).slice(-8).map((s) => ({
-        date: cleanText(s.date || s.timestamp, 40),
-        equity: safeNumber(s.equity),
-        return_pct: safeNumber(s.return_pct),
-        open_positions: safeNumber(s.open_positions),
-      })),
-    },
-    leaderboard: (Array.isArray(body.leaderboard) ? body.leaderboard : []).slice(0, 10).map((r) => ({
-      name: cleanText(r.name, 80),
-      return_pct: safeNumber(r.return_pct),
-      equity: safeNumber(r.equity),
-      rank: safeNumber(r.rank),
-    })),
-    suggestions: (Array.isArray(body.suggestions) ? body.suggestions : []).slice(0, MAX_SUGGESTIONS).map(compactSuggestion),
-    history: compactHistory(body.history),
-  };
-
-  const instructions = [
-    `You are ${context.agent.name || "a Polymarket paper-trading agent"} inside Poly Arena.`,
-    "Speak in first person as the selected agent, like a real chat partner.",
-    "Answer the user's exact question instead of repeating a generic performance summary.",
-    "Use the supplied portfolio, positions, leaderboard, suggestions, and chat history as your facts.",
-    "Be specific about trades, risk, performance, and uncertainty when the data is available.",
-    "Do not claim you can guarantee profits or force agents to make money.",
-    "Do not give personalized financial advice. Keep it framed as paper trading, research, or manual review.",
-    "If asked what you will do next, describe likely decision rules, not a guaranteed action.",
-    "Keep responses concise: 2 to 5 short paragraphs or a tight bullet list.",
-  ].join("\n");
-
-  const input = [
-    {
-      role: "user",
-      content: [{
-        type: "input_text",
-        text: `Context JSON:\n${JSON.stringify(context)}\n\nUser message:\n${question}`,
-      }],
-    },
-  ];
-
-  try {
-    const response = await fetch("https://api.openai.com/v1/responses", {
-      method: "POST",
-      headers: {
-        "Authorization": `Bearer ${apiKey}`,
-        "Content-Type": "application/json",
-      },
-      body: JSON.stringify({
-        model: process.env.OPENAI_MODEL || "gpt-5.6-luna",
-        instructions,
-        input,
-        max_output_tokens: 550,
-      }),
-    });
-
-    const data = await response.json().catch(() => ({}));
-    if (!response.ok) {
-      return res.status(response.status).json({
-        ok: false,
-        error: data && data.error && data.error.message ? data.error.message : "OpenAI chat request failed.",
-      });
-    }
-
-    const text = outputText(data);
-    return res.status(200).json({ ok: true, text: text || "I am here, but I could not form a useful answer from the current context." });
-  } catch (err) {
-    return res.status(500).json({ ok: false, error: err && err.message ? err.message : "Agent chat failed." });
-  }
-}

api/live.js

@@ -245,6 +245,163 @@ function validateIntent(intent) {
 const VALID_TICKET_STATUSES = new Set(["staged", "reviewed", "placed_manually", "skipped", "cancelled"]);
 const VALID_FILL_ACTIONS = new Set(["BUY", "SELL"]);
 const VALID_CAPITAL_ACTIONS = new Set(["DEPOSIT", "WITHDRAW", "BUY_AGENT", "SELL_AGENT"]);
+const AGENT_CHAT_MAX_HISTORY = 12;
+const AGENT_CHAT_MAX_POSITIONS = 10;
+const AGENT_CHAT_MAX_SUGGESTIONS = 8;
+
+function cleanAgentText(value, max = 1200) {
+  return String(value || "").replace(/\s+/g, " ").trim().slice(0, max);
+}
+
+function safeAgentNumber(value, fallback = 0) {
+  const n = Number(value);
+  return Number.isFinite(n) ? n : fallback;
+}
+
+function compactAgentPosition(pos) {
+  return {
+    question: cleanAgentText(pos.question, 180),
+    side: cleanAgentText(pos.side, 8),
+    entry_price: safeAgentNumber(pos.entry_price),
+    current_price: safeAgentNumber(pos.current_price),
+    value: safeAgentNumber(pos.value),
+    unrealized_pnl: safeAgentNumber(pos.unrealized_pnl),
+    conviction: safeAgentNumber(pos.conviction),
+    category: cleanAgentText(pos.category, 60),
+    opened_at: cleanAgentText(pos.opened_at, 40),
+    url: cleanAgentText(pos.url, 240),
+  };
+}
+
+function compactAgentSuggestion(sug) {
+  return {
+    question: cleanAgentText(sug.question, 180),
+    side: cleanAgentText(sug.side, 8),
+    entry_price: safeAgentNumber(sug.entry_price),
+    conviction: safeAgentNumber(sug.conviction),
+    edge: safeAgentNumber(sug.edge),
+    category: cleanAgentText(sug.category, 60),
+    rationale: cleanAgentText(sug.rationale, 240),
+    url: cleanAgentText(sug.url, 240),
+  };
+}
+
+function compactAgentHistory(history) {
+  return (Array.isArray(history) ? history : []).slice(-AGENT_CHAT_MAX_HISTORY).map((m) => ({
+    role: m && m.role === "user" ? "user" : "assistant",
+    text: cleanAgentText(m && m.text, 900),
+  })).filter((m) => m.text);
+}
+
+function openAIOutputText(data) {
+  if (data && typeof data.output_text === "string") return data.output_text.trim();
+  const chunks = [];
+  for (const item of data && Array.isArray(data.output) ? data.output : []) {
+    for (const content of Array.isArray(item.content) ? item.content : []) {
+      if (content.type === "output_text" && content.text) chunks.push(content.text);
+      if (content.type === "text" && content.text) chunks.push(content.text);
+    }
+  }
+  return chunks.join("\n").trim();
+}
+
+async function handleAgentChat(body, res) {
+  const apiKey = process.env.OPENAI_API_KEY;
+  if (!apiKey) {
+    return res.status(501).json({
+      ok: false,
+      code: "missing_openai_key",
+      error: "Agent AI chat needs OPENAI_API_KEY in Vercel environment variables.",
+    });
+  }
+
+  const question = cleanAgentText(body.question, 1000);
+  if (!question) return res.status(400).json({ ok: false, error: "Question is required." });
+
+  const agent = body.agent || {};
+  const portfolio = body.portfolio || {};
+  const context = {
+    agent: {
+      id: cleanAgentText(agent.id, 40),
+      name: cleanAgentText(agent.name, 80),
+      kind: cleanAgentText(agent.kind, 40),
+      style: cleanAgentText(agent.style || agent.blurb, 800),
+      voice: cleanAgentText(agent.voice, 200),
+    },
+    portfolio: {
+      equity: safeAgentNumber(portfolio.equity),
+      cash: safeAgentNumber(portfolio.cash),
+      return_pct: safeAgentNumber(portfolio.return_pct),
+      pnl: safeAgentNumber(portfolio.pnl),
+      rank: safeAgentNumber(portfolio.rank),
+      open_positions: safeAgentNumber(portfolio.open_positions),
+      last_decision: cleanAgentText(portfolio.last_decision, 700),
+      recent_actions: (Array.isArray(portfolio.recent_actions) ? portfolio.recent_actions : []).slice(-8).map((x) => cleanAgentText(x, 260)),
+      positions: (Array.isArray(portfolio.positions) ? portfolio.positions : []).slice(0, AGENT_CHAT_MAX_POSITIONS).map(compactAgentPosition),
+      snapshots: (Array.isArray(portfolio.snapshots) ? portfolio.snapshots : []).slice(-8).map((s) => ({
+        date: cleanAgentText(s.date || s.timestamp, 40),
+        equity: safeAgentNumber(s.equity),
+        return_pct: safeAgentNumber(s.return_pct),
+        open_positions: safeAgentNumber(s.open_positions),
+      })),
+    },
+    leaderboard: (Array.isArray(body.leaderboard) ? body.leaderboard : []).slice(0, 10).map((r) => ({
+      name: cleanAgentText(r.name, 80),
+      return_pct: safeAgentNumber(r.return_pct),
+      equity: safeAgentNumber(r.equity),
+      rank: safeAgentNumber(r.rank),
+    })),
+    suggestions: (Array.isArray(body.suggestions) ? body.suggestions : []).slice(0, AGENT_CHAT_MAX_SUGGESTIONS).map(compactAgentSuggestion),
+    history: compactAgentHistory(body.history),
+  };
+
+  const instructions = [
+    `You are ${context.agent.name || "a Polymarket paper-trading agent"} inside Poly Arena.`,
+    "Speak in first person as the selected agent, like a real chat partner.",
+    "Answer the user's exact question instead of repeating a generic performance summary.",
+    "Use the supplied portfolio, positions, leaderboard, suggestions, and chat history as your facts.",
+    "Be specific about trades, risk, performance, and uncertainty when the data is available.",
+    "Do not claim you can guarantee profits or force agents to make money.",
+    "Do not give personalized financial advice. Keep it framed as paper trading, research, or manual review.",
+    "If asked what you will do next, describe likely decision rules, not a guaranteed action.",
+    "Keep responses concise: 2 to 5 short paragraphs or a tight bullet list.",
+  ].join("\n");
+
+  try {
+    const response = await fetch("https://api.openai.com/v1/responses", {
+      method: "POST",
+      headers: {
+        "Authorization": `Bearer ${apiKey}`,
+        "Content-Type": "application/json",
+      },
+      body: JSON.stringify({
+        model: process.env.OPENAI_MODEL || "gpt-5.6-luna",
+        instructions,
+        input: [{
+          role: "user",
+          content: [{
+            type: "input_text",
+            text: `Context JSON:\n${JSON.stringify(context)}\n\nUser message:\n${question}`,
+          }],
+        }],
+        max_output_tokens: 550,
+      }),
+    });
+
+    const data = await response.json().catch(() => ({}));
+    if (!response.ok) {
+      return res.status(response.status).json({
+        ok: false,
+        error: data && data.error && data.error.message ? data.error.message : "OpenAI chat request failed.",
+      });
+    }
+
+    const text = openAIOutputText(data);
+    return res.status(200).json({ ok: true, text: text || "I am here, but I could not form a useful answer from the current context." });
+  } catch (err) {
+    return res.status(500).json({ ok: false, error: err && err.message ? err.message : "Agent chat failed." });
+  }
+}
 
 function marketSearchUrl(question) {
   return `https://polymarket.com/search?query=${encodeURIComponent(String(question || ""))}`;
@@ -366,6 +523,10 @@ export default async function handler(req, res) {
   if (req.method === "POST") {
     const body = typeof req.body === "string" ? JSON.parse(req.body || "{}") : (req.body || {});
 
+    if (body.action === "agent_chat") {
+      return handleAgentChat(body, res);
+    }
+
     if (body.action === "ticket") {
       const ticket = normalizeTicket(body);
       const ticketErrors = validateTicket(ticket);

index.html

@@ -2268,10 +2268,10 @@ function agentChatPayload(agentId,question,history=[]){
   };
 }
 async function askAgentAI(agentId,question,history=[]){
-  const r=await fetch("/api/agent-chat",{
+  const r=await fetch("/api/live",{
     method:"POST",
     headers:{"Content-Type":"application/json"},
-    body:JSON.stringify(agentChatPayload(agentId,question,history)),
+    body:JSON.stringify(Object.assign({action:"agent_chat"},agentChatPayload(agentId,question,history))),
   });
   const data=await r.json().catch(()=>({}));
   if(!r.ok||!data.ok)throw new Error(data.error||"Agent AI chat is not available yet.");