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.
This commit is contained in:
asepharyana
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package agents
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import (
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"context"
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"fmt"
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"sort"
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"strings"
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"time"
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"flowsight/internal/model"
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"flowsight/internal/sectors"
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)
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// AnalyzeCatalyst (A6) builds the catalyst calendar: ex-div, earnings, AGM.
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// Opportunity score = yield x certainty - earnings-risk, 0-100.
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func AnalyzeCatalyst(ctx context.Context, d Deps, ticker string) model.AgentResult {
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ticker = strings.ToUpper(ticker)
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now := d.Now
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if now.IsZero() {
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now = time.Now()
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}
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res := model.AgentResult{Summary: "no catalyst snapshots available"}
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var wrapped struct {
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Symbol string `json:"symbol"`
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CorporateActions sectors.CorporateActions `json:"corporate_actions"`
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// Unwrapped shape (client return) also accepted.
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Dividend []sectors.DividendEvent `json:"dividend"`
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UpcomingDividend []sectors.DividendEvent `json:"upcoming_dividend"`
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AGM []sectors.DividendEvent `json:"agm"`
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StockSplit []sectors.DividendEvent `json:"stock_split"`
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}
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var ipo sectors.ListingPerformance
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ipoDate, ipoOK := payload(d.DB, ticker, "listing-performance", &ipo)
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actDate, actOK := payload(d.DB, ticker, "corporate-actions", &wrapped)
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actions := wrapped.CorporateActions
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if len(actions.UpcomingDividend) == 0 {
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actions.UpcomingDividend = wrapped.UpcomingDividend
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}
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if len(actions.Dividend) == 0 {
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actions.Dividend = wrapped.Dividend
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}
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if len(actions.AGM) == 0 {
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actions.AGM = wrapped.AGM
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}
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if len(actions.StockSplit) == 0 {
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actions.StockSplit = wrapped.StockSplit
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}
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if ipoOK {
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res.Citations = append(res.Citations, model.Cite("v2/listing-performance/"+ticker+"/", ticker, ipoDate))
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}
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var qdates []sectors.QuarterlyDate
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qdDate, qdOK := payload(d.DB, ticker, "quarterly-dates", &qdates)
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if !qdOK || len(qdates) == 0 {
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// Legacy universe shape: [{symbol, date, year}] from
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// companies/quarterly-financial-dates.
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var uni []sectors.QuarterlyDateRow
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if ud, uok := payload(d.DB, ticker, "quarterly-dates", &uni); uok {
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qdDate, qdOK = ud, true
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for _, r := range uni {
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qdates = append(qdates, sectors.QuarterlyDate{ReportDate: r.Date})
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}
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}
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}
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if !actOK && !qdOK {
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return res
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}
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if actOK {
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res.Citations = append(res.Citations, model.Cite("v2/company/corporate-actions/"+ticker+"/", ticker, actDate))
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}
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if qdOK {
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res.Citations = append(res.Citations, model.Cite("v2/company/get_quarterly_financial_dates/"+ticker+"/", ticker, qdDate))
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}
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type cal struct {
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event string
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date string
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days int
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extra string
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}
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var rows []cal
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closePx, _, _ := d.DB.LatestClose(ticker)
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for _, ev := range actions.UpcomingDividend {
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if dt := strAt(ev, "ex_date", "exDate", "date"); len(dt) >= 10 {
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if t, err := time.Parse("2006-01-02", dt[:10]); err == nil {
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days := int(t.Sub(now).Hours() / 24)
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rows = append(rows, cal{"ex-div", dt[:10], days, yieldLine(ev, closePx)})
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}
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}
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}
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for _, ev := range actions.Dividend {
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if dt := strAt(ev, "ex_date", "exDate", "date"); len(dt) >= 10 {
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if t, err := time.Parse("2006-01-02", dt[:10]); err == nil && t.After(now.AddDate(0, 0, -370)) {
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days := int(t.Sub(now).Hours() / 24)
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if days >= -30 { // recent history for payout context
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rows = append(rows, cal{"div-paid", dt[:10], days, yieldLine(ev, closePx)})
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}
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}
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}
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}
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for _, ev := range actions.AGM {
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if dt := strAt(ev, "date", "agm_date"); len(dt) >= 10 {
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if t, err := time.Parse("2006-01-02", dt[:10]); err == nil {
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if days := int(t.Sub(now).Hours() / 24); days >= 0 {
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rows = append(rows, cal{"AGM", dt[:10], days, ""})
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}
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}
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}
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}
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for _, ev := range actions.StockSplit {
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if dt := strAt(ev, "date", "ex_date", "split_date"); len(dt) >= 10 {
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if t, err := time.Parse("2006-01-02", dt[:10]); err == nil {
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if days := int(t.Sub(now).Hours() / 24); days >= -30 {
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rows = append(rows, cal{"split", dt[:10], days, ratioLine(ev)})
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}
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}
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}
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}
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// IPO-window context for recent listings (<=365d): anniversary + 30d drift.
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if ipoOK && len(ipo.ListingDate) >= 10 {
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if t, err := time.Parse("2006-01-02", ipo.ListingDate[:10]); err == nil {
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age := int(now.Sub(t).Hours() / 24)
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if age >= 0 && age <= 365 {
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rows = append(rows, cal{"IPO-window", ipo.ListingDate[:10], -age, ipoLine(&ipo)})
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}
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}
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}
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// Next earnings estimate: last report + ~90d unless universe dates show newer.
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if len(qdates) > 0 {
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sort.Slice(qdates, func(i, j int) bool { return qdates[i].ReportDate > qdates[j].ReportDate })
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last := qdates[0].ReportDate
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if len(last) >= 10 {
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if t, err := time.Parse("2006-01-02", last[:10]); err == nil {
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next := t.AddDate(0, 0, 90)
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rows = append(rows, cal{"earnings-est", next.Format("2006-01-02"), int(next.Sub(now).Hours() / 24), "from last " + last[:10]})
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}
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}
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}
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sort.Slice(rows, func(i, j int) bool { return rows[i].days < rows[j].days })
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opp := 0.0
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var lines []string
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for _, r := range rows {
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h := fmt.Sprintf("H%+d", r.days)
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if r.days >= 0 {
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h = fmt.Sprintf("H-%d", r.days)
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}
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line := fmt.Sprintf("%s %s %s", r.event, r.date, h)
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if r.extra != "" {
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line += " (" + r.extra + ")"
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}
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lines = append(lines, line)
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// Near-term certain events lift the opportunity score.
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if r.days >= 0 && r.days <= 30 {
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w := 30.0
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if r.event == "ex-div" {
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w = 45
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}
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opp += w * (1 - float64(r.days)/30)
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}
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}
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// Earnings within 7d adds risk (results can invalidate the thesis).
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for _, r := range rows {
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if r.event == "earnings-est" && r.days >= 0 && r.days <= 7 {
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opp -= 15
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res.Flags = append(res.Flags, "earnings-risk")
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}
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}
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res.Score = clampScore(opp, 0, 100)
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if len(lines) == 0 {
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res.Summary = "no upcoming catalysts in window"
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} else {
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res.Values = []model.Value{{
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Label: "catalyst calendar",
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Display: strings.Join(lines, " | "),
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Citations: res.Citations,
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}}
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res.Summary = fmt.Sprintf("%d catalysts, opportunity %.0f", len(lines), res.Score)
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}
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res.Extra = map[string]any{"calendar": lines}
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return res
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}
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// strAt returns the first present string key.
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func strAt(ev map[string]any, keys ...string) string {
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for _, k := range keys {
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for ek, v := range ev {
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if strings.EqualFold(ek, k) {
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if s, ok := v.(string); ok && s != "" {
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return s
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}
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}
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}
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}
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return ""
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}
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// ratioLine renders "a-for-b" when a split ratio is present.
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func ratioLine(ev map[string]any) string {
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a := numAt(ev, "ratio", "split_ratio", "ratio_from")
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b := numAt(ev, "ratio_to", "ratio_denominator", "new_shares")
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if a > 0 && b > 0 {
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return fmt.Sprintf("%.0f-for-%.0f", a, b)
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}
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return "split"
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}
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// ipoLine renders listing age + 30d drift when present.
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func ipoLine(ipo *sectors.ListingPerformance) string {
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if ipo.Chg30d != nil {
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return fmt.Sprintf("30d %+.1f%%", *ipo.Chg30d*100)
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}
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return "recent listing"
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}
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// yieldLine renders "DPS x, yield y%" when figures are present.
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func yieldLine(ev map[string]any, closePx float64) string {
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dps := numAt(ev, "dividend_per_share", "dps", "cash_dividend")
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if dps <= 0 {
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return ""
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}
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if closePx > 0 {
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return fmt.Sprintf("DPS %.0f, yield %.1f%%", dps, dps/closePx*100)
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}
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return fmt.Sprintf("DPS %.0f", dps)
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}
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