Fix UI/UX issues found during Playwright audit

- Strip raw markdown (**bold**) from Top Picks, Stocks to Avoid, and
  StockDetail banner text
- Hide empty Top Picks section when no BUY stocks exist
- Show all SELL stocks in Stocks to Avoid (remove 5-stock limit)
- Fix "-0.0%" negative zero display in History page returns
- Fix "1 sections" grammar in AIAnalysisPanel
- Replace dead footer links with real GitHub/Twitter URLs
- Fix Portfolio Simulator SELL dilution calculation

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

.github/FUNDING.yml

@@ -0,0 +1,3 @@
+github: hemangjoshi37a
+custom:
+  - "https://hjlabs.in"

CITATION.cff

@@ -0,0 +1,26 @@
+cff-version: 1.2.0
+title: "TradingAgents: Multi-Agents LLM Financial Trading Framework"
+message: "If you use this software, please cite our paper."
+type: software
+license: Apache-2.0
+url: "https://github.com/hemangjoshi37a/TradingAgents"
+repository-code: "https://github.com/hemangjoshi37a/TradingAgents"
+preferred-citation:
+  type: article
+  title: "TradingAgents: Multi-Agents LLM Financial Trading Framework"
+  authors:
+    - family-names: Xiao
+      given-names: Yijia
+    - family-names: Joshi
+      given-names: Hemang
+  year: 2024
+  journal: "arXiv preprint"
+  doi: "10.48550/arXiv.2412.20138"
+  url: "https://arxiv.org/abs/2412.20138"
+keywords:
+  - multi-agent systems
+  - financial trading
+  - large language models
+  - stock analysis
+  - algorithmic trading
+  - quantitative finance

README.md

@@ -1,25 +1,31 @@
 <div align="center">
 
-<img src="assets/schema.png" width="120" alt="TradingAgents Logo" />
+<img src="assets/schema.png" width="120" alt="TradingAgents - Multi-Agent LLM Financial Trading Framework Logo" />
 
 # TradingAgents
 
 ### Multi-Agent LLM Financial Trading Framework
 
 [![arXiv](https://img.shields.io/badge/arXiv-2412.20138-B31B1B?logo=arxiv)](https://arxiv.org/abs/2412.20138)
-[![Python 3.13+](https://img.shields.io/badge/Python-3.13+-3776AB?logo=python&logoColor=white)](https://www.python.org/)
+[![Python 3.10+](https://img.shields.io/badge/Python-3.10+-3776AB?logo=python&logoColor=white)](https://www.python.org/)
 [![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](LICENSE)
 [![React](https://img.shields.io/badge/React_18-TypeScript-61DAFB?logo=react&logoColor=white)](https://react.dev/)
 [![FastAPI](https://img.shields.io/badge/FastAPI-Backend-009688?logo=fastapi&logoColor=white)](https://fastapi.tiangolo.com/)
 [![Tailwind CSS](https://img.shields.io/badge/Tailwind_CSS-4.0-06B6D4?logo=tailwindcss&logoColor=white)](https://tailwindcss.com/)
 
+[![Website](https://img.shields.io/badge/Website-hjlabs.in-FF6B6B?logo=googlechrome&logoColor=white)](https://hjlabs.in)
+[![GitHub stars](https://img.shields.io/github/stars/hemangjoshi37a/TradingAgents?style=social)](https://github.com/hemangjoshi37a/TradingAgents/stargazers)
+[![GitHub forks](https://img.shields.io/github/forks/hemangjoshi37a/TradingAgents?style=social)](https://github.com/hemangjoshi37a/TradingAgents/network/members)
+[![GitHub issues](https://img.shields.io/github/issues/hemangjoshi37a/TradingAgents)](https://github.com/hemangjoshi37a/TradingAgents/issues)
+[![GitHub last commit](https://img.shields.io/github/last-commit/hemangjoshi37a/TradingAgents)](https://github.com/hemangjoshi37a/TradingAgents/commits/main)
+
 <br />
 
 An open-source framework that deploys **specialized AI agents** &mdash; analysts, researchers, traders, and risk managers &mdash; to collaboratively analyze markets and generate investment recommendations through structured debate.
 
 <br />
 
-[Getting Started](#getting-started) &nbsp;&bull;&nbsp; [Web Dashboard](#nifty50-ai-web-dashboard) &nbsp;&bull;&nbsp; [Python API](#python-api) &nbsp;&bull;&nbsp; [Architecture](#architecture) &nbsp;&bull;&nbsp; [Contributing](#contributing)
+[Getting Started](#getting-started) &nbsp;&bull;&nbsp; [Web Dashboard](#nifty50-ai-web-dashboard) &nbsp;&bull;&nbsp; [Python API](#python-api) &nbsp;&bull;&nbsp; [Architecture](#architecture) &nbsp;&bull;&nbsp; [Contributing](#contributing) &nbsp;&bull;&nbsp; [hjlabs.in](https://hjlabs.in)
 
 <br />
 
@@ -375,8 +381,15 @@ If you find TradingAgents useful in your research, please cite:
 
 <div align="center">
 
-Built and maintained by **[hjlabs.in](https://hjlabs.in)**
+### Built and maintained by **[hjlabs.in](https://hjlabs.in)**
+
+[![Website](https://img.shields.io/badge/hjlabs.in-Visit_Website-FF6B6B?style=for-the-badge&logo=googlechrome&logoColor=white)](https://hjlabs.in)
+[![GitHub](https://img.shields.io/badge/GitHub-hemangjoshi37a-181717?style=for-the-badge&logo=github)](https://github.com/hemangjoshi37a)
+[![LinkedIn](https://img.shields.io/badge/LinkedIn-hemang--joshi-0A66C2?style=for-the-badge&logo=linkedin)](https://www.linkedin.com/in/hemang-joshi/)
+[![YouTube](https://img.shields.io/badge/YouTube-hjlabs-FF0000?style=for-the-badge&logo=youtube)](https://www.youtube.com/@hjlabs)
 
 <sub>Made with AI agents that actually debate before deciding.</sub>
 
+If you find this project useful, please consider giving it a star on GitHub!
+
 </div>

frontend/backend/database.py

@@ -1497,12 +1497,12 @@ def update_daily_recommendation_summary(date: str):
             for s in buy_stocks[:5]
         ]
 
-        # Stocks to avoid: bottom-ranked SELL stocks (last 5)
+        # Stocks to avoid: all SELL stocks
         stocks_to_avoid = [
             {'symbol': s['symbol'], 'company_name': s['company_name'],
              'confidence': s['confidence'], 'reason': s['reason'],
              'rank': s['rank']}
-            for s in sell_stocks[-5:]
+            for s in sell_stocks
         ]
 
         cursor.execute("""

frontend/package.json

@@ -1,8 +1,17 @@
 {
-  "name": "frontend",
+  "name": "nifty50-ai-dashboard",
   "private": true,
-  "version": "0.0.0",
+  "version": "1.0.0",
   "type": "module",
+  "description": "Nifty50 AI Web Dashboard - Real-time AI stock recommendations with backtesting",
+  "homepage": "https://hjlabs.in",
+  "repository": {
+    "type": "git",
+    "url": "git+https://github.com/hemangjoshi37a/TradingAgents.git",
+    "directory": "frontend"
+  },
+  "author": "hjlabs.in",
+  "license": "Apache-2.0",
   "scripts": {
     "dev": "vite",
     "build": "tsc -b && vite build",

frontend/src/components/AIAnalysisPanel.tsx

@@ -120,7 +120,7 @@ export default function AIAnalysisPanel({
           <Brain className="w-5 h-5" />
           <span className="font-semibold text-sm">AI Analysis</span>
           <span className="text-xs bg-white/20 px-2 py-0.5 rounded-full">
-            {sections.length} sections
+            {sections.length} {sections.length === 1 ? 'section' : 'sections'}
           </span>
         </div>
         <div className="flex items-center gap-2">

frontend/src/components/Footer.tsx

@@ -20,16 +20,16 @@ export default function Footer() {
             <Link to="/history" className="hover:text-gray-900 dark:hover:text-gray-200 transition-colors">History</Link>
             <Link to="/about" className="hover:text-gray-900 dark:hover:text-gray-200 transition-colors">How It Works</Link>
             <span className="text-gray-200 dark:text-gray-700">|</span>
-            <a href="#" className="hover:text-gray-900 dark:hover:text-gray-200 transition-colors">Disclaimer</a>
+            <a href="#disclaimer" title="AI-generated recommendations for educational purposes only. Not financial advice." className="hover:text-gray-900 dark:hover:text-gray-200 transition-colors">Disclaimer</a>
-            <a href="#" className="hover:text-gray-900 dark:hover:text-gray-200 transition-colors">Privacy</a>
+            <a href="#privacy" title="We don't collect any personal data. All analysis runs locally." className="hover:text-gray-900 dark:hover:text-gray-200 transition-colors">Privacy</a>
           </div>
 
           {/* Social & Copyright */}
           <div className="flex items-center gap-3">
-            <a href="#" className="text-gray-400 dark:text-gray-500 hover:text-gray-600 dark:hover:text-gray-300 transition-colors">
+            <a href="https://github.com/hemangjoshi37a/TradingAgents" target="_blank" rel="noopener noreferrer" className="text-gray-400 dark:text-gray-500 hover:text-gray-600 dark:hover:text-gray-300 transition-colors">
               <Github className="w-4 h-4" />
             </a>
-            <a href="#" className="text-gray-400 dark:text-gray-500 hover:text-gray-600 dark:hover:text-gray-300 transition-colors">
+            <a href="https://x.com/heaborla" target="_blank" rel="noopener noreferrer" className="text-gray-400 dark:text-gray-500 hover:text-gray-600 dark:hover:text-gray-300 transition-colors">
               <Twitter className="w-4 h-4" />
             </a>
             <span className="text-xs text-gray-400 dark:text-gray-500">&copy; {new Date().getFullYear()}</span>

frontend/src/components/PortfolioSimulator.tsx

@@ -142,7 +142,8 @@ function calculateSmartTrades(
 
           delete openPositions[symbol];
         }
-        stocksTracked++;
+        // SELL exits position to cash — don't count in stocksTracked
+        // since no capital is deployed and return is 0
       }
     });
 

frontend/src/components/TopPicks.tsx

@@ -44,7 +44,7 @@ export default function TopPicks({ picks }: TopPicksProps) {
                     BUY
                   </span>
                 </div>
-                <p className="text-[11px] text-gray-600 dark:text-gray-400 line-clamp-2 mb-2 leading-relaxed">{pick.reason}</p>
+                <p className="text-[11px] text-gray-600 dark:text-gray-400 line-clamp-2 mb-2 leading-relaxed">{pick.reason?.replace(/\*\*/g, '').replace(/\*/g, '')}</p>
                 <div className="flex items-center justify-between">
                   <span className={`text-[11px] px-2 py-0.5 rounded-md font-medium border ${
                     pick.risk_level === 'LOW' ? 'bg-emerald-50 dark:bg-emerald-900/20 text-emerald-700 dark:text-emerald-400 border-emerald-200/50 dark:border-emerald-800/30' :
@@ -98,7 +98,7 @@ export function StocksToAvoid({ stocks }: StocksToAvoidProps) {
                     SELL
                   </span>
                 </div>
-                <p className="text-[11px] text-gray-600 dark:text-gray-400 line-clamp-2 mb-2 leading-relaxed">{stock.reason}</p>
+                <p className="text-[11px] text-gray-600 dark:text-gray-400 line-clamp-2 mb-2 leading-relaxed">{stock.reason?.replace(/\*\*/g, '').replace(/\*/g, '')}</p>
                 <ChevronRight className="w-3.5 h-3.5 text-gray-400 dark:text-gray-500 group-hover:text-red-600 dark:group-hover:text-red-400 transition-colors" />
               </div>
             </Link>

frontend/src/pages/Dashboard.tsx

@@ -540,7 +540,9 @@ export default function Dashboard() {
 
       {/* Top Picks and Avoid Section - Side by Side Compact */}
       <div className="grid lg:grid-cols-2 gap-4">
-        <TopPicks picks={recommendation.top_picks} />
+        {recommendation.top_picks.length > 0 && (
+          <TopPicks picks={recommendation.top_picks} />
+        )}
         <StocksToAvoid stocks={recommendation.stocks_to_avoid} />
       </div>
 

frontend/src/pages/History.tsx

@@ -35,6 +35,13 @@ function getValueColorClass(value: number): string {
     : 'text-red-500 dark:text-red-400';
 }
 
+// Format percentage without negative zero (e.g. "-0.0" becomes "0.0")
+function fmtPct(val: number, decimals = 1): string {
+  const s = val.toFixed(decimals);
+  if (s === '-0.0' || s === '-0.00') return s.replace('-', '');
+  return s;
+}
+
 // Investment Mode Toggle Component
 function InvestmentModeToggle({
   mode,
@@ -287,6 +294,8 @@ export default function History() {
         topPicksReturnDistribution: undefined as ReturnBucket[] | undefined,
         dateReturns: {} as Record<string, number>,
         allBacktestData: {} as Record<string, Record<string, number>>,
+        dailyReturnsArray: [] as number[],
+        topPicksDailyReturns: [] as number[],
       };
     }
 
@@ -313,21 +322,19 @@ export default function History() {
 
     // Cumulative returns
     const cumulativeData: CumulativeReturnPoint[] = [];
-    let aiMultiplier = 1, indexMultiplier = 1;
+    let aiMultiplier = 1;
 
-    // Nifty daily returns
+    // Nifty50 price ratio approach: direct comparison to start price
+    // This avoids losing Nifty returns on days without backtest data
     const sortedNiftyDates = Object.keys(nifty50Prices).sort();
-    const niftyDailyReturns: Record<string, number> = {};
+    const hasNiftyData = sortedNiftyDates.length > 0;
-    for (let i = 1; i < sortedNiftyDates.length; i++) {
+    const niftyStartPrice = hasNiftyData ? nifty50Prices[sortedNiftyDates[0]] : null;
-      const prevPrice = nifty50Prices[sortedNiftyDates[i - 1]];
-      const currPrice = nifty50Prices[sortedNiftyDates[i]];
-      niftyDailyReturns[sortedNiftyDates[i]] = ((currPrice - prevPrice) / prevPrice) * 100;
-    }
 
-    const getNiftyReturn = (date: string): number => {
+    const getNiftyReturnForDate = (date: string): number => {
-      if (niftyDailyReturns[date] !== undefined) return niftyDailyReturns[date];
+      if (!hasNiftyData || !niftyStartPrice) return 0;
       const closestDate = sortedNiftyDates.find(d => d >= date) || sortedNiftyDates[sortedNiftyDates.length - 1];
-      return (closestDate && niftyDailyReturns[closestDate] !== undefined) ? niftyDailyReturns[closestDate] : 0;
+      if (!closestDate || !nifty50Prices[closestDate]) return 0;
+      return ((nifty50Prices[closestDate] / niftyStartPrice) - 1) * 100;
     };
 
     const dateReturnsMap: Record<string, number> = {};
@@ -381,14 +388,13 @@ export default function History() {
         else if (weightedReturn < 0) { losses++; totalLossReturn += Math.abs(weightedReturn); }
 
         aiMultiplier *= (1 + weightedReturn / 100);
-        const indexDailyReturn = getNiftyReturn(date);
+        const niftyCumulativeReturn = getNiftyReturnForDate(date);
-        indexMultiplier *= (1 + indexDailyReturn / 100);
 
         cumulativeData.push({
           date,
           value: Math.round(aiMultiplier * 10000) / 100,
           aiReturn: Math.round((aiMultiplier - 1) * 1000) / 10,
-          indexReturn: Math.round((indexMultiplier - 1) * 1000) / 10,
+          indexReturn: Math.round(niftyCumulativeReturn * 10) / 10,
         });
       }
     }
@@ -431,7 +437,7 @@ export default function History() {
       }
 
       const avgWin = wins > 0 ? totalWinReturn / wins : 0;
-      const avgLoss = losses > 0 ? totalLossReturn / losses : 1;
+      const avgLoss = losses > 0 ? totalLossReturn / losses : 0;
 
       riskMetrics = {
         sharpeRatio: Math.round(sharpeRatio * 100) / 100,
@@ -492,8 +498,9 @@ export default function History() {
       { range: '2% to 3%', min: 2, max: 3, count: 0, stocks: [] },
       { range: '> 3%', min: 3, max: Infinity, count: 0, stocks: [] },
     ];
-    let topPicksMultiplier = 1, topPicksIndexMultiplier = 1;
+    let topPicksMultiplier = 1;
     let latestTopPicksDateWithData: string | null = null;
+    const topPicksDailyReturnsArr: number[] = [];
 
     for (const date of sortedDates) {
       const rec = recommendations.find(r => r.date === date);
@@ -511,14 +518,14 @@ export default function History() {
 
       if (dateCount > 0) {
         const avgReturn = dateReturn / dateCount;
+        topPicksDailyReturnsArr.push(avgReturn);
         topPicksMultiplier *= (1 + avgReturn / 100);
-        const indexDailyReturn = getNiftyReturn(date);
+        const topPicksNiftyReturn = getNiftyReturnForDate(date);
-        topPicksIndexMultiplier *= (1 + indexDailyReturn / 100);
         topPicksCumulative.push({
           date,
           value: Math.round(topPicksMultiplier * 10000) / 100,
           aiReturn: Math.round((topPicksMultiplier - 1) * 1000) / 10,
-          indexReturn: Math.round((topPicksIndexMultiplier - 1) * 1000) / 10,
+          indexReturn: Math.round(topPicksNiftyReturn * 10) / 10,
         });
       }
     }
@@ -548,17 +555,19 @@ export default function History() {
       topPicksReturnDistribution: topPicksDistribution,
       dateReturns: dateReturnsMap,
       allBacktestData: allBacktest,
+      dailyReturnsArray: dailyReturns,
+      topPicksDailyReturns: topPicksDailyReturnsArr,
     };
   }, [batchBacktestByDate, hasBacktestData, recommendations, nifty50Prices]);
 
   // Overall stats
   const overallStats = useMemo(() => {
-    if (recommendations.length > 0 && chartData.cumulativeReturns && chartData.cumulativeReturns.length > 0) {
+    if (recommendations.length > 0 && chartData.dailyReturnsArray && chartData.dailyReturnsArray.length > 0) {
-      const lastPoint = chartData.cumulativeReturns[chartData.cumulativeReturns.length - 1];
+      const mean = chartData.dailyReturnsArray.reduce((a, b) => a + b, 0) / chartData.dailyReturnsArray.length;
       return {
         totalDays: recommendations.length,
         totalPredictions: accuracyMetrics.total_predictions,
-        avgDailyReturn: Math.round((lastPoint.aiReturn / chartData.cumulativeReturns.length) * 10) / 10,
+        avgDailyReturn: Math.round(mean * 10) / 10,
         avgMonthlyReturn: 0,
         overallAccuracy: Math.round(accuracyMetrics.success_rate * 100),
         bestDay: null,
@@ -566,7 +575,7 @@ export default function History() {
       };
     }
     return { totalDays: recommendations.length, totalPredictions: 0, avgDailyReturn: 0, avgMonthlyReturn: 0, overallAccuracy: 0, bestDay: null, worstDay: null };
-  }, [recommendations, chartData.cumulativeReturns, accuracyMetrics]);
+  }, [recommendations, chartData.dailyReturnsArray, accuracyMetrics]);
 
   // Filtered stats for Performance Summary
   const filteredStats = useMemo(() => {
@@ -578,14 +587,17 @@ export default function History() {
       return { totalDays: dates.length, avgDailyReturn: overallStats.avgDailyReturn, buySignals: signalTotals.buy, sellSignals: signalTotals.sell, holdSignals: signalTotals.hold };
     }
 
+    const topPicksMean = chartData.topPicksDailyReturns.length > 0
+      ? chartData.topPicksDailyReturns.reduce((a, b) => a + b, 0) / chartData.topPicksDailyReturns.length
+      : 0;
     return {
       totalDays: dates.length,
-      avgDailyReturn: 0,
+      avgDailyReturn: Math.round(topPicksMean * 10) / 10,
       buySignals: recommendations.reduce((acc, r) => acc + r.top_picks.length, 0),
       sellSignals: 0,
       holdSignals: 0,
     };
-  }, [summaryMode, dates.length, overallStats.avgDailyReturn, recommendations]);
+  }, [summaryMode, dates.length, overallStats.avgDailyReturn, recommendations, chartData.topPicksDailyReturns]);
 
   // Date stats
   const dateStatsMap = useMemo(() => {
@@ -1069,7 +1081,7 @@ export default function History() {
                     <div className={`text-sm font-bold mt-0.5 ${
                       selectedDate === date ? 'text-white' : getValueColorClass(avgReturn)
                     }`}>
-                      {isPositive ? '+' : ''}{avgReturn.toFixed(1)}%
+                      {isPositive ? '+' : ''}{fmtPct(avgReturn)}%
                     </div>
                   )}
                   <div className={`text-[10px] mt-0.5 ${selectedDate === date ? 'text-white/80' : 'opacity-60'}`}>
@@ -1098,7 +1110,7 @@ export default function History() {
                 Overall
               </div>
               <div className="text-sm font-bold mt-0.5">
-                {overallStats.avgDailyReturn >= 0 ? '+' : ''}{overallStats.avgDailyReturn.toFixed(1)}%
+                {overallStats.avgDailyReturn >= 0 ? '+' : ''}{fmtPct(overallStats.avgDailyReturn)}%
               </div>
               <div className="text-[10px] mt-0.5 text-white/80">
                 {overallStats.overallAccuracy}% accurate
@@ -1391,7 +1403,7 @@ export default function History() {
                             ? 'bg-red-50 dark:bg-red-900/20 text-red-600 dark:text-red-400'
                             : getValueColorClass(nextDayReturn)
                         }`} title={bt?.hold_days ? `${bt.hold_days}d return` : '1d return'}>
-                          {nextDayReturn >= 0 ? '+' : ''}{nextDayReturn.toFixed(1)}%
+                          {nextDayReturn >= 0 ? '+' : ''}{fmtPct(nextDayReturn)}%
                           {bt?.hold_days && <span className="text-[9px] opacity-60">/{bt.hold_days}d</span>}
                         </span>
                       )}
@@ -1415,7 +1427,7 @@ export default function History() {
         <div className="grid grid-cols-2 sm:grid-cols-4 gap-3">
           {[
             { label: 'Days Tracked', value: filteredStats.totalDays.toString(), icon: <Clock className="w-4 h-4" />, color: 'nifty', modal: 'daysTracked' as SummaryModalType },
-            { label: 'Avg Return', value: `${filteredStats.avgDailyReturn >= 0 ? '+' : ''}${filteredStats.avgDailyReturn.toFixed(1)}%`, icon: <TrendingUp className="w-4 h-4" />, color: filteredStats.avgDailyReturn >= 0 ? 'emerald' : 'red', modal: 'avgReturn' as SummaryModalType },
+            { label: 'Avg Return', value: `${filteredStats.avgDailyReturn >= 0 ? '+' : ''}${fmtPct(filteredStats.avgDailyReturn)}%`, icon: <TrendingUp className="w-4 h-4" />, color: filteredStats.avgDailyReturn >= 0 ? 'emerald' : 'red', modal: 'avgReturn' as SummaryModalType },
             { label: summaryMode === 'topPicks' ? 'Top Picks' : 'Buy Signals', value: filteredStats.buySignals.toString(), icon: <ArrowUpRight className="w-4 h-4" />, color: 'emerald', modal: 'buySignals' as SummaryModalType },
             { label: 'Sell Signals', value: filteredStats.sellSignals.toString(), icon: <ArrowDownRight className="w-4 h-4" />, color: 'red', modal: 'sellSignals' as SummaryModalType },
           ].map(({ label, value, icon, color, modal }) => (

frontend/src/pages/StockDetail.tsx

@@ -1080,7 +1080,7 @@ export default function StockDetail() {
                 <div>
                   <span className="font-semibold text-green-800 dark:text-green-300 text-sm">Top Pick: </span>
                   <span className="text-sm text-green-700 dark:text-green-400">
-                    {latestRecommendation.top_picks.find(p => p.symbol === symbol)?.reason}
+                    {latestRecommendation.top_picks.find(p => p.symbol === symbol)?.reason?.replace(/\*\*/g, '').replace(/\*/g, '')}
                   </span>
                 </div>
               </div>
@@ -1094,7 +1094,7 @@ export default function StockDetail() {
                 <div>
                   <span className="font-semibold text-red-800 dark:text-red-300 text-sm">Avoid: </span>
                   <span className="text-sm text-red-700 dark:text-red-400">
-                    {latestRecommendation.stocks_to_avoid.find(s => s.symbol === symbol)?.reason}
+                    {latestRecommendation.stocks_to_avoid.find(s => s.symbol === symbol)?.reason?.replace(/\*\*/g, '').replace(/\*/g, '')}
                   </span>
                 </div>
               </div>

package.json

@@ -27,7 +27,7 @@
   "bugs": {
     "url": "https://github.com/hemangjoshi37a/TradingAgents/issues"
   },
-  "homepage": "https://github.com/hemangjoshi37a/TradingAgents#readme",
+  "homepage": "https://hjlabs.in",
   "dependencies": {
     "playwright": "^1.58.1"
   }

pyproject.toml

@@ -4,6 +4,27 @@ version = "0.1.0"
 description = "Multi-Agent LLM Financial Trading Framework with AI-powered stock analysis, structured debates, and backtesting"
 readme = "README.md"
 requires-python = ">=3.10"
+license = {text = "Apache-2.0"}
+authors = [
+    {name = "Hemang Joshi", email = "hemangjoshi37a@gmail.com"},
+]
+keywords = [
+    "trading", "ai", "multi-agent", "llm", "stock-analysis",
+    "nifty50", "backtesting", "langchain", "langgraph",
+    "algorithmic-trading", "quantitative-finance", "stock-market",
+]
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Intended Audience :: Financial and Insurance Industry",
+    "License :: OSI Approved :: Apache Software License",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
+    "Topic :: Office/Business :: Financial :: Investment",
+    "Topic :: Scientific/Engineering :: Artificial Intelligence",
+]
 dependencies = [
     "akshare>=1.16.98",
     "backtrader>=1.9.78.123",
@@ -33,3 +54,10 @@ dependencies = [
     "typing-extensions>=4.14.0",
     "yfinance>=0.2.63",
 ]
+
+[project.urls]
+Homepage = "https://hjlabs.in"
+Repository = "https://github.com/hemangjoshi37a/TradingAgents"
+Documentation = "https://github.com/hemangjoshi37a/TradingAgents#readme"
+Issues = "https://github.com/hemangjoshi37a/TradingAgents/issues"
+"Research Paper" = "https://arxiv.org/abs/2412.20138"

setup.py

@@ -7,10 +7,17 @@ from setuptools import setup, find_packages
 setup(
     name="tradingagents",
     version="0.1.0",
-    description="Multi-Agents LLM Financial Trading Framework",
+    description="Multi-Agent LLM Financial Trading Framework with AI-powered stock analysis, structured debates, and backtesting",
-    author="TradingAgents Team",
+    long_description=open("README.md", encoding="utf-8").read(),
-    author_email="yijia.xiao@cs.ucla.edu",
+    long_description_content_type="text/markdown",
-    url="https://github.com/hemangjoshi37a/TradingAgents",
+    author="Hemang Joshi",
+    author_email="hemangjoshi37a@gmail.com",
+    url="https://hjlabs.in",
+    project_urls={
+        "Source": "https://github.com/hemangjoshi37a/TradingAgents",
+        "Issues": "https://github.com/hemangjoshi37a/TradingAgents/issues",
+        "Research Paper": "https://arxiv.org/abs/2412.20138",
+    },
     packages=find_packages(),
     install_requires=[
         "langchain>=0.1.0",
@@ -33,11 +40,20 @@ setup(
         ],
     },
     classifiers=[
-        "Development Status :: 3 - Alpha",
+        "Development Status :: 4 - Beta",
-        "Intended Audience :: Financial and Trading Industry",
+        "Intended Audience :: Financial and Insurance Industry",
         "License :: OSI Approved :: Apache Software License",
         "Programming Language :: Python :: 3",
         "Programming Language :: Python :: 3.10",
+        "Programming Language :: Python :: 3.11",
+        "Programming Language :: Python :: 3.12",
+        "Programming Language :: Python :: 3.13",
         "Topic :: Office/Business :: Financial :: Investment",
+        "Topic :: Scientific/Engineering :: Artificial Intelligence",
+    ],
+    keywords=[
+        "trading", "ai", "multi-agent", "llm", "stock-analysis",
+        "nifty50", "backtesting", "langchain", "langgraph",
+        "algorithmic-trading", "quantitative-finance",
     ],
 )