"""
Signals page — today's recommendation cards with rich visual indicators.
Each signal is displayed as a data-dense card with strategy badges,
confidence bars, and expandable thesis sections.
"""
from datetime import datetime
import pandas as pd
import plotly.graph_objects as go
import streamlit as st
from tradingagents.ui.theme import COLORS, get_plotly_template, page_header, signal_card
from tradingagents.ui.utils import load_recommendations
TIMEFRAME_LOOKBACK_DAYS = {
"1D": 1,
"7D": 7,
"1M": 30,
"3M": 90,
"6M": 180,
"1Y": 365,
}
def _get_interval_for_timeframe(timeframe: str) -> str:
"""Return appropriate data interval for a given timeframe."""
if timeframe == "1D":
return "5m" # 5-minute for intraday detail
elif timeframe == "7D":
return "1h" # Hourly for smooth 7-day view
else:
return "1d" # Daily for longer timeframes
@st.cache_data(ttl=3600)
def _load_price_history(ticker: str, period: str, interval: str = "1d") -> pd.DataFrame:
try:
from tradingagents.dataflows.y_finance import download_history
except Exception:
return pd.DataFrame()
data = download_history(
ticker,
period=period,
interval=interval,
auto_adjust=True,
progress=False,
)
if data is None or data.empty:
return pd.DataFrame()
if isinstance(data.columns, pd.MultiIndex):
tickers = data.columns.get_level_values(1).unique()
target = ticker if ticker in tickers else tickers[0]
data = data.xs(target, level=1, axis=1).copy()
data = data.reset_index()
# yfinance uses "Datetime" for intraday and "Date" for daily data
date_col = next(
(c for c in ("Datetime", "Date") if c in data.columns),
data.columns[0],
)
close_col = "Close" if "Close" in data.columns else "Adj Close"
if close_col not in data.columns:
return pd.DataFrame()
history = data[[date_col, close_col]].rename(columns={date_col: "date", close_col: "close"})
history["date"] = pd.to_datetime(history["date"], utc=True).dt.tz_localize(None)
history = history.dropna(subset=["close"]).sort_values("date")
return history
def _slice_history_window(history: pd.DataFrame, timeframe: str) -> pd.DataFrame:
days = TIMEFRAME_LOOKBACK_DAYS.get(timeframe)
if history.empty or days is None:
return pd.DataFrame()
latest_date = history["date"].max()
cutoff = latest_date - pd.Timedelta(days=days)
window = history[history["date"] >= cutoff].copy()
if len(window) < 2:
return pd.DataFrame()
return window
def _format_move_pct(window: pd.DataFrame) -> str:
first_close = float(window["close"].iloc[0])
last_close = float(window["close"].iloc[-1])
if first_close == 0:
return "0.00%"
move = ((last_close - first_close) / first_close) * 100
return f"{move:+.2f}%"
def _get_daily_movement(ticker: str) -> str:
"""Get today's intraday price movement percentage."""
try:
from tradingagents.dataflows.y_finance import download_history
today_data = download_history(
ticker,
period="1d",
interval="1d",
auto_adjust=True,
progress=False,
)
if today_data is None or today_data.empty:
return "N/A"
if isinstance(today_data.columns, pd.MultiIndex):
tickers = today_data.columns.get_level_values(1).unique()
if ticker not in tickers:
ticker = tickers[0]
today_data = today_data.xs(ticker, level=1, axis=1)
close_col = "Close" if "Close" in today_data.columns else "Adj Close"
if close_col not in today_data.columns:
return "N/A"
today_close = float(today_data[close_col].iloc[-1])
today_open = float(today_data.get("Open", today_data[close_col]).iloc[-1])
if today_open != 0:
daily_move = ((today_close - today_open) / today_open) * 100
return f"{daily_move:+.2f}%"
except Exception:
pass
return "N/A"
def _is_intraday(timeframe: str) -> bool:
"""Return True for timeframes that use intraday (sub-daily) data."""
return timeframe in ("1D", "7D")
def _build_dynamic_chart(
history: pd.DataFrame, timeframe: str, ticker: str = ""
) -> tuple[go.Figure, str, str, str]:
window = _slice_history_window(history, timeframe)
if window.empty:
return go.Figure(), "N/A", COLORS["text_muted"], "N/A"
first_close = float(window["close"].iloc[0])
last_close = float(window["close"].iloc[-1])
line_color = COLORS["green"] if last_close >= first_close else COLORS["red"]
move_text = _format_move_pct(window)
daily_move_text = _get_daily_movement(ticker) if ticker else "N/A"
intraday = _is_intraday(timeframe)
template = dict(get_plotly_template())
fig = go.Figure()
if intraday:
# For intraday charts, plot against a sequential index to eliminate
# overnight and weekend gaps. Use customdata for hover timestamps.
window = window.reset_index(drop=True)
x_vals = list(range(len(window)))
# Build tick labels: show date at the start of each trading day
tick_vals = []
tick_labels = []
prev_day = None
for i, row in window.iterrows():
day = row["date"].date()
if day != prev_day:
tick_vals.append(i)
tick_labels.append(row["date"].strftime("%b %d"))
prev_day = day
fig.add_trace(
go.Scatter(
x=x_vals,
y=window["close"],
mode="lines",
line=dict(color=line_color, width=2.4),
fill="tozeroy",
fillcolor=(
"rgba(34,197,94,0.18)"
if line_color == COLORS["green"]
else "rgba(239,68,68,0.18)"
),
customdata=window["date"],
hovertemplate="%{customdata|%b %d %H:%M}
$%{y:.2f}",
name=f"{timeframe} Focus",
)
)
else:
# For daily charts, keep the original two-trace approach
fig.add_trace(
go.Scatter(
x=history["date"],
y=history["close"],
mode="lines",
line=dict(color="rgba(148,163,184,0.22)", width=1.1),
hovertemplate="%{x|%b %d, %Y}
$%{y:.2f}",
name="History",
)
)
fig.add_trace(
go.Scatter(
x=window["date"],
y=window["close"],
mode="lines",
line=dict(color=line_color, width=2.8),
fill="tozeroy",
fillcolor=(
"rgba(34,197,94,0.18)"
if line_color == COLORS["green"]
else "rgba(239,68,68,0.18)"
),
hovertemplate=f"{timeframe}
%{{x|%b %d, %Y}}
$%{{y:.2f}}",
name=f"{timeframe} Focus",
)
)
# Override template keys before expansion to avoid duplicate keyword args.
template["height"] = 210
template["showlegend"] = False
template["margin"] = dict(l=0, r=0, t=10, b=0)
fig.update_layout(**template)
# Tighten Y-axis to selected timeframe range for better signal visibility.
y_min = float(window["close"].min())
y_max = float(window["close"].max())
if y_min == y_max:
pad = max(0.5, y_min * 0.01)
else:
pad = max((y_max - y_min) * 0.08, y_max * 0.01)
if intraday:
fig.update_xaxes(
showticklabels=True,
showgrid=False,
tickvals=tick_vals,
ticktext=tick_labels,
tickfont=dict(size=9, color=COLORS["text_muted"]),
rangeslider=dict(visible=False),
)
else:
fig.update_xaxes(
showticklabels=False,
showgrid=False,
range=[window["date"].min(), history["date"].max()],
rangeslider=dict(visible=False),
)
fig.update_yaxes(
showgrid=True,
gridcolor="rgba(42,53,72,0.28)",
tickprefix="$",
nticks=5,
range=[y_min - pad, y_max + pad],
)
return fig, move_text, line_color, daily_move_text
def _render_single_dynamic_chart(ticker: str, timeframe: str) -> None:
# Load base history with daily data for context (full year)
base_history = _load_price_history(ticker, "1y", interval="1d")
if base_history.empty:
st.caption("No price history available for this ticker.")
return
# For 1D and 7D, load higher granularity (intraday) data
intraday = _is_intraday(timeframe)
if intraday:
# Map timeframe to yfinance period: 1D -> "1d", 7D -> "7d"
yf_period = {"1D": "1d", "7D": "7d"}[timeframe]
interval = _get_interval_for_timeframe(timeframe)
history_for_chart = _load_price_history(ticker, yf_period, interval=interval)
if history_for_chart.empty or len(history_for_chart) < 2:
# Fallback to daily data
history_for_chart = base_history
intraday = False
if intraday:
# Use all loaded intraday data directly — yfinance already
# returned exactly the period we asked for.
window = history_for_chart
else:
window = _slice_history_window(history_for_chart, timeframe)
else:
history_for_chart = base_history
window = _slice_history_window(history_for_chart, timeframe)
if window.empty or len(window) < 2:
# Last-resort fallback: use all available data
if len(history_for_chart) >= 2:
window = history_for_chart.copy()
else:
st.caption(f"Not enough data to render {timeframe} window.")
return
fig, move_text, move_color, daily_move_text = _build_dynamic_chart(
history_for_chart, timeframe, ticker
)
# Determine daily movement color
try:
daily_move_val = float(daily_move_text.strip().rstrip("%"))
daily_color = COLORS["green"] if daily_move_val >= 0 else COLORS["red"]
except (ValueError, AttributeError):
daily_color = COLORS["text_muted"]
st.markdown(
f"""
Dynamic Price View • {timeframe}
Daily: {daily_move_text}
{move_text}
""",
unsafe_allow_html=True,
)
st.plotly_chart(fig, width="stretch", config={"displayModeBar": False})
def render():
today = datetime.now().strftime("%Y-%m-%d")
recommendations, meta = load_recommendations(today, return_meta=True)
display_date = meta.get("date", today) if meta else today
st.markdown(
page_header("Signals", f"Recommendations for {display_date}"),
unsafe_allow_html=True,
)
if not recommendations:
st.warning(f"No recommendations for {today}.")
return
if meta.get("is_fallback") and meta.get("date"):
st.info(f"Showing latest signals from **{meta['date']}** (none for today).")
# ---- Controls row ----
ctrl_cols = st.columns([1, 1, 1, 1])
with ctrl_cols[0]:
pipelines = sorted(
set(
(r.get("strategy_match") or r.get("pipeline") or "unknown") for r in recommendations
)
)
pipeline_filter = st.multiselect("Strategy", pipelines, default=pipelines)
with ctrl_cols[1]:
min_confidence = st.slider("Min Confidence", 1, 10, 1)
with ctrl_cols[2]:
min_score = st.slider("Min Score", 0, 100, 0)
with ctrl_cols[3]:
show_charts = st.checkbox("Price Charts", value=False)
# Apply filters
filtered = [
r
for r in recommendations
if (r.get("strategy_match") or r.get("pipeline") or "unknown") in pipeline_filter
and r.get("confidence", 0) >= min_confidence
and r.get("final_score", 0) >= min_score
]
# ---- Summary bar ----
st.markdown(
f"""
Showing
{len(filtered)} of {len(recommendations)} signals
{display_date}
""",
unsafe_allow_html=True,
)
# ---- Signal cards in 2-column grid ----
for i in range(0, len(filtered), 2):
cols = st.columns(2)
for j, col in enumerate(cols):
idx = i + j
if idx >= len(filtered):
break
rec = filtered[idx]
ticker = rec.get("ticker", "UNKNOWN")
rank = rec.get("rank", idx + 1)
score = rec.get("final_score", 0)
confidence = rec.get("confidence", 0)
strategy = (
(rec.get("strategy_match") or rec.get("pipeline") or "unknown")
.replace("_", " ")
.title()
)
entry_price = rec.get("entry_price", 0)
reason = rec.get("reason", "No thesis provided.")
company_name = rec.get("company_name", "")
description = rec.get("description", "")
risk_level = rec.get("risk_level", "")
with col:
st.markdown(
signal_card(
rank,
ticker,
score,
confidence,
strategy,
entry_price,
reason,
company_name,
description,
risk_level,
),
unsafe_allow_html=True,
)
if show_charts:
st.markdown(
f"""
Chart Timeframe
""",
unsafe_allow_html=True,
)
chart_timeframe = st.radio(
f"Timeframe for {ticker}",
list(TIMEFRAME_LOOKBACK_DAYS.keys()),
index=3,
horizontal=True,
label_visibility="collapsed",
key=f"chart_tf_{ticker}_{idx}",
)
_render_single_dynamic_chart(ticker, chart_timeframe)
# Action buttons
btn_cols = st.columns(2)
with btn_cols[0]:
if st.button("Enter Position", key=f"enter_{ticker}_{idx}"):
st.info(f"Position entry for {ticker} (TODO)")
with btn_cols[1]:
if st.button("Watchlist", key=f"watch_{ticker}_{idx}"):
st.success(f"Added {ticker} to watchlist")