feat: add Citations and WatchlistChat components, integrate with API

- Implemented Citations component to display citation data.
- Created WatchlistDrawer and ChatSidebar components for managing watchlists and AI chat functionality.
- Integrated API calls for watchlist management and chat interactions.
- Updated index.tsx to include new components in the main application layout.
- Added API client in lib/api.ts for structured API interactions.
- Developed Alerts, Dashboard, Portfolio, Routines, Screener, and Report pages with relevant data fetching and UI components.
- Introduced styles in tokens.css for consistent theming across the application.
- Configured TypeScript and Vite for project setup and development.

backend/internal/agents/smart_money.go

@@ -0,0 +1,166 @@
+package agents
+
+import (
+	"context"
+	"fmt"
+	"strings"
+
+	"flowsight/internal/model"
+	"flowsight/internal/sectors"
+)
+
+// fmtIDR renders rupiah compactly (Rp1.2T / Rp340B / Rp12M).
+func fmtIDR(v float64) string {
+	neg := v < 0
+	if neg {
+		v = -v
+	}
+	var s string
+	switch {
+	case v >= 1e12:
+		s = fmt.Sprintf("Rp%.2fT", v/1e12)
+	case v >= 1e9:
+		s = fmt.Sprintf("Rp%.0fB", v/1e9)
+	case v >= 1e6:
+		s = fmt.Sprintf("Rp%.0fM", v/1e6)
+	default:
+		s = fmt.Sprintf("Rp%.0f", v)
+	}
+	if neg {
+		return "-" + s
+	}
+	return s
+}
+
+// AnalyzeSmartMoney (A1) fuses broker top lists with foreign flow.
+// Rule: >=3 brokers net-buy 5d + volume > 1.5x 20d avg => accumulation.
+func AnalyzeSmartMoney(ctx context.Context, d Deps, ticker string) model.AgentResult {
+	_ = ctx
+	ticker = strings.ToUpper(ticker)
+	res := model.AgentResult{Summary: "no broker snapshots available"}
+
+	var top sectors.BrokerSummaryTop
+	topDate, ok := payload(d.DB, ticker, "broker-summary-top", &top)
+	var foreign sectors.ForeignFlow
+	foreignDate, fok := payload(d.DB, ticker, "foreign-flow", &foreign)
+	if !ok && !fok {
+		return res
+	}
+
+	buySum, sellSum := 0.0, 0.0
+	buyers, sellers := 0, 0
+	var players []string
+	if ok {
+		for _, b := range top.TopBuyers {
+			if b.NetIDR > 0 {
+				buyers++
+				buySum += float64(b.NetIDR)
+				if len(players) < 3 {
+					players = append(players, fmt.Sprintf("%s %s", b.BrokerCode, fmtIDR(float64(b.NetIDR))))
+				}
+			}
+		}
+		for _, s := range top.TopSellers {
+			if s.NetIDR < 0 {
+				sellers++
+				sellSum += float64(-s.NetIDR)
+			}
+		}
+		res.Citations = append(res.Citations, model.Cite("v2/broker-summary/"+ticker+"/top/", ticker, topDate))
+	}
+
+	fSum := 0.0
+	fN := 0
+	if fok {
+		data := foreign.Data
+		if len(data) > 5 {
+			data = data[len(data)-5:]
+		}
+		for _, p := range data {
+			fSum += float64(p.NetForeignInflow)
+			fN++
+		}
+		res.Citations = append(res.Citations, model.Cite("v2/foreign-flow/"+ticker+"/", ticker, foreignDate))
+	}
+
+	total := buySum + sellSum
+	imbalance := 0.0
+	if total > 0 {
+		imbalance = (buySum - sellSum) / total
+	}
+	score := imbalance * 70
+	score += float64(minInt(buyers, 5)-minInt(sellers, 5)) * 4
+	if fok && fN > 0 {
+		if fSum > 0 {
+			score += 10
+		} else if fSum < 0 {
+			score -= 10
+		}
+	}
+	score = clampScore(score, -100, 100)
+	res.Score = score
+
+	// Volume multiple from stored daily bars.
+	volMult := 0.0
+	if vols, _, err := d.DB.DailyVolumes(ticker, 21); err == nil && len(vols) >= 2 {
+		n := len(vols)
+		if a := avg(vols[:n-1]); a > 0 {
+			volMult = vols[n-1] / a
+			res.Citations = append(res.Citations, model.Cite("v2/daily/"+ticker+"/", ticker, "stored"))
+			res.Values = append(res.Values, model.Value{
+				Label:     "volume vs 20d avg",
+				Display:   fmt.Sprintf("%.1fx", volMult),
+				Citations: res.Citations,
+			})
+		}
+	}
+
+	phase := "neutral"
+	switch {
+	case score >= 30:
+		phase = "accumulation"
+	case score <= -30:
+		phase = "distribution"
+	case ok && fok && imbalance*fSum < 0:
+		phase = "conflict"
+		res.Flags = append(res.Flags, "direction-conflict")
+	}
+	if ok && fok && imbalance*fSum > 0 {
+		res.Flags = append(res.Flags, "direction-agreement")
+	}
+	if buyers >= 3 && volMult > 1.5 {
+		res.Flags = append(res.Flags, "accumulation-rule")
+	}
+	if volMult > 2 {
+		res.Flags = append(res.Flags, "volume-anomaly")
+	}
+
+	res.Values = append([]model.Value{{
+		Label:     "broker net imbalance",
+		Display:   fmt.Sprintf("%s net (%d buyers vs %d sellers)", fmtIDR(buySum-sellSum), buyers, sellers),
+		Citations: res.Citations,
+	}, {
+		Label:     "key players",
+		Display:   strings.Join(players, ", "),
+		Citations: res.Citations,
+	}, {
+		Label:     "foreign 5d net",
+		Display:   fmtIDR(fSum),
+		Citations: res.Citations,
+	}}, res.Values...)
+	res.Summary = fmt.Sprintf("%s: score %+.0f, %d net-buy brokers, foreign %s",
+		phase, score, buyers, fmtIDR(fSum))
+	res.Extra = map[string]any{
+		"phase": phase, "buyers": buyers, "sellers": sellers,
+		"net_sum": buySum - sellSum, "foreign_sum": fSum,
+		"volume_mult": volMult, "players": players,
+	}
+	return res
+}
+
+func minInt(a, b int) int {
+	if a < b {
+		return a
+	}
+	return b
+}