294 lines
10 KiB
Python
294 lines
10 KiB
Python
"""
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Signals page — today's recommendation cards with rich visual indicators.
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Each signal is displayed as a data-dense card with strategy badges,
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confidence bars, and expandable thesis sections.
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"""
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from datetime import datetime
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import pandas as pd
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import plotly.graph_objects as go
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import streamlit as st
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from tradingagents.ui.theme import COLORS, get_plotly_template, page_header, signal_card
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from tradingagents.ui.utils import load_recommendations
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TIMEFRAME_LOOKBACK_DAYS = {
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"7D": 7,
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"1M": 30,
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"3M": 90,
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"6M": 180,
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"1Y": 365,
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}
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@st.cache_data(ttl=3600)
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def _load_price_history(ticker: str, period: str) -> pd.DataFrame:
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try:
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from tradingagents.dataflows.y_finance import download_history
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except Exception:
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return pd.DataFrame()
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data = download_history(
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ticker,
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period=period,
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interval="1d",
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auto_adjust=True,
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progress=False,
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)
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if data is None or data.empty:
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return pd.DataFrame()
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if isinstance(data.columns, pd.MultiIndex):
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tickers = data.columns.get_level_values(1).unique()
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target = ticker if ticker in tickers else tickers[0]
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data = data.xs(target, level=1, axis=1).copy()
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data = data.reset_index()
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date_col = "Date" if "Date" in data.columns else data.columns[0]
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close_col = "Close" if "Close" in data.columns else "Adj Close"
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if close_col not in data.columns:
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return pd.DataFrame()
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history = data[[date_col, close_col]].rename(columns={date_col: "date", close_col: "close"})
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history["date"] = pd.to_datetime(history["date"])
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history = history.dropna(subset=["close"]).sort_values("date")
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return history
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def _slice_history_window(history: pd.DataFrame, timeframe: str) -> pd.DataFrame:
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days = TIMEFRAME_LOOKBACK_DAYS.get(timeframe)
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if history.empty or days is None:
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return pd.DataFrame()
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latest_date = history["date"].max()
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cutoff = latest_date - pd.Timedelta(days=days)
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window = history[history["date"] >= cutoff].copy()
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if len(window) < 2:
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return pd.DataFrame()
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return window
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def _format_move_pct(window: pd.DataFrame) -> str:
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first_close = float(window["close"].iloc[0])
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last_close = float(window["close"].iloc[-1])
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if first_close == 0:
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return "0.00%"
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move = ((last_close - first_close) / first_close) * 100
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return f"{move:+.2f}%"
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def _build_dynamic_chart(history: pd.DataFrame, timeframe: str) -> tuple[go.Figure, str, str]:
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window = _slice_history_window(history, timeframe)
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if window.empty:
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return go.Figure(), "N/A", COLORS["text_muted"]
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first_close = float(window["close"].iloc[0])
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last_close = float(window["close"].iloc[-1])
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line_color = COLORS["green"] if last_close >= first_close else COLORS["red"]
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move_text = _format_move_pct(window)
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template = dict(get_plotly_template())
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fig = go.Figure()
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fig.add_trace(
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go.Scatter(
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x=history["date"],
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y=history["close"],
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mode="lines",
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line=dict(color="rgba(148,163,184,0.22)", width=1.1),
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hovertemplate="%{x|%b %d, %Y}<br>$%{y:.2f}<extra></extra>",
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name="History",
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)
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)
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fig.add_trace(
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go.Scatter(
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x=window["date"],
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y=window["close"],
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mode="lines",
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line=dict(color=line_color, width=2.8),
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fill="tozeroy",
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fillcolor=(
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"rgba(34,197,94,0.18)" if line_color == COLORS["green"] else "rgba(239,68,68,0.18)"
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),
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hovertemplate=f"{timeframe}<br>%{{x|%b %d, %Y}}<br>$%{{y:.2f}}<extra></extra>",
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name=f"{timeframe} Focus",
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)
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)
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# Override template keys before expansion to avoid duplicate keyword args.
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template["height"] = 210
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template["showlegend"] = False
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template["margin"] = dict(l=0, r=0, t=10, b=0)
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fig.update_layout(**template)
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# Tighten Y-axis to selected timeframe range for better signal visibility.
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y_min = float(window["close"].min())
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y_max = float(window["close"].max())
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if y_min == y_max:
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pad = max(0.5, y_min * 0.01)
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else:
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pad = max((y_max - y_min) * 0.08, y_max * 0.01)
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fig.update_xaxes(
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showticklabels=False,
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showgrid=False,
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range=[window["date"].min(), history["date"].max()],
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rangeslider=dict(visible=False),
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)
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fig.update_yaxes(
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showgrid=True,
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gridcolor="rgba(42,53,72,0.28)",
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tickprefix="$",
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nticks=5,
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range=[y_min - pad, y_max + pad],
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)
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return fig, move_text, line_color
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def _render_single_dynamic_chart(ticker: str, timeframe: str) -> None:
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base_history = _load_price_history(ticker, "1y")
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if base_history.empty:
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st.caption("No price history available for this ticker.")
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return
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window = _slice_history_window(base_history, timeframe)
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if window.empty:
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st.caption(f"Not enough data to render {timeframe} window.")
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return
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fig, move_text, move_color = _build_dynamic_chart(base_history, timeframe)
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st.markdown(
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f"""
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<div style="margin-top:0.4rem;margin-bottom:0.45rem;padding:0.45rem 0.6rem;
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border:1px solid {COLORS['border']};border-radius:8px;
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background:linear-gradient(120deg, rgba(6,182,212,0.10), rgba(59,130,246,0.05));
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display:flex;justify-content:space-between;align-items:center;">
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<span style="font-family:'JetBrains Mono',monospace;font-size:0.68rem;
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text-transform:uppercase;letter-spacing:0.07em;color:{COLORS['text_secondary']};">
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Dynamic Price View • {timeframe}
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</span>
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<span style="font-family:'JetBrains Mono',monospace;font-size:0.72rem;
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font-weight:700;color:{move_color};">{move_text}</span>
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</div>
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""",
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unsafe_allow_html=True,
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)
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st.plotly_chart(fig, width="stretch", config={"displayModeBar": False})
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def render():
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today = datetime.now().strftime("%Y-%m-%d")
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recommendations, meta = load_recommendations(today, return_meta=True)
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display_date = meta.get("date", today) if meta else today
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st.markdown(
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page_header("Signals", f"Recommendations for {display_date}"),
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unsafe_allow_html=True,
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)
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if not recommendations:
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st.warning(f"No recommendations for {today}.")
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return
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if meta.get("is_fallback") and meta.get("date"):
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st.info(f"Showing latest signals from **{meta['date']}** (none for today).")
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# ---- Controls row ----
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ctrl_cols = st.columns([1, 1, 1, 1])
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with ctrl_cols[0]:
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pipelines = sorted(
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set(
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(r.get("pipeline") or r.get("strategy_match") or "unknown") for r in recommendations
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)
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)
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pipeline_filter = st.multiselect("Strategy", pipelines, default=pipelines)
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with ctrl_cols[1]:
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min_confidence = st.slider("Min Confidence", 1, 10, 1)
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with ctrl_cols[2]:
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min_score = st.slider("Min Score", 0, 100, 0)
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with ctrl_cols[3]:
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show_charts = st.checkbox("Price Charts", value=False)
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# Apply filters
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filtered = [
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r
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for r in recommendations
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if (r.get("pipeline") or r.get("strategy_match") or "unknown") in pipeline_filter
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and r.get("confidence", 0) >= min_confidence
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and r.get("final_score", 0) >= min_score
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]
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# ---- Summary bar ----
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st.markdown(
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f"""
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<div style="display:flex;justify-content:space-between;align-items:center;
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padding:0.5rem 0;margin-bottom:0.75rem;border-bottom:1px solid {COLORS['border']};">
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<span style="font-family:'JetBrains Mono',monospace;font-size:0.8rem;
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color:{COLORS['text_secondary']};">
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Showing <span style="color:{COLORS['text_primary']};font-weight:700;">
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{len(filtered)}</span> of {len(recommendations)} signals
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</span>
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<span style="font-family:'JetBrains Mono',monospace;font-size:0.7rem;
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color:{COLORS['text_muted']};">
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{display_date}
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</span>
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</div>
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""",
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unsafe_allow_html=True,
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)
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# ---- Signal cards in 2-column grid ----
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for i in range(0, len(filtered), 2):
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cols = st.columns(2)
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for j, col in enumerate(cols):
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idx = i + j
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if idx >= len(filtered):
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break
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rec = filtered[idx]
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ticker = rec.get("ticker", "UNKNOWN")
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rank = rec.get("rank", idx + 1)
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score = rec.get("final_score", 0)
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confidence = rec.get("confidence", 0)
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strategy = (rec.get("pipeline") or rec.get("strategy_match") or "unknown").title()
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entry_price = rec.get("entry_price", 0)
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reason = rec.get("reason", "No thesis provided.")
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with col:
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st.markdown(
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signal_card(rank, ticker, score, confidence, strategy, entry_price, reason),
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unsafe_allow_html=True,
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)
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if show_charts:
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st.markdown(
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f"""
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<div style="margin-top:0.35rem;margin-bottom:0.25rem;
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font-family:'JetBrains Mono',monospace;font-size:0.66rem;
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text-transform:uppercase;letter-spacing:0.06em;
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color:{COLORS['text_muted']};">
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Chart Timeframe
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</div>
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""",
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unsafe_allow_html=True,
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)
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chart_timeframe = st.radio(
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f"Timeframe for {ticker}",
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list(TIMEFRAME_LOOKBACK_DAYS.keys()),
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index=2,
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horizontal=True,
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label_visibility="collapsed",
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key=f"chart_tf_{ticker}_{idx}",
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)
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_render_single_dynamic_chart(ticker, chart_timeframe)
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# Action buttons
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btn_cols = st.columns(2)
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with btn_cols[0]:
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if st.button("Enter Position", key=f"enter_{ticker}_{idx}"):
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st.info(f"Position entry for {ticker} (TODO)")
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with btn_cols[1]:
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if st.button("Watchlist", key=f"watch_{ticker}_{idx}"):
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st.success(f"Added {ticker} to watchlist")
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