qchen34--tradingagents
wehub-resource-sync
423 行
16 KiB
Python
423 行
16 KiB
Python
from __future__ import annotations
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import html
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from datetime import datetime
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import streamlit as st
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try:
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from markdown_it import MarkdownIt
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except ImportError: # 极简环境可回退为原始 Markdown
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MarkdownIt = None # type: ignore[misc, assignment]
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from web.services.market_data import (
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INDEX_SUBTITLE_CN,
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SECTOR_SUBTITLE_CN,
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load_dashboard_display,
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refresh_dashboard_cache,
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)
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# 指标卡第 4 行「描述」文案来源（勿与 tradingagents 底层混淆；均在 web/services/market_data.py）：
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# - 主要指数：字典 INDEX_SUBTITLE_CN（各 ticker 对应中文说明）
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# - 宏观与利率：常量 MACRO_ENTRIES 每项第 3 个元素 hint，经 get_macro_strip() 写入 macro_strip[].hint
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STANCE_LABEL_CN = {
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"bullish": "看多",
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"bearish": "看空",
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"neutral": "中性",
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"unknown": "未评估",
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}
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STANCE_CLASS = {
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"bullish": "ta-stance-bull",
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"bearish": "ta-stance-bear",
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"neutral": "ta-stance-neut",
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"unknown": "ta-stance-unknown",
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}
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def _metric_label_ticker(ticker: str) -> str:
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return "VIX" if ticker == "^VIX" else ticker
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def _e(s: object) -> str:
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return html.escape(str(s), quote=True)
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def _delta_direction(change_pct: float | None) -> bool | None:
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if change_pct is None:
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return None
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if change_pct > 0:
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return True
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if change_pct < 0:
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return False
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return None
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def _stat_card_html(
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code: str,
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value: str,
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change_vs_prev: str,
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description: str,
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*,
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positive: bool | None = None,
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) -> str:
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"""单卡四层：标的代码 → 数值 → 较昨收涨跌 → 描述（左对齐，内联样式）。"""
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if positive is True:
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ch_color = "#22c55e"
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elif positive is False:
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ch_color = "#ef4444"
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else:
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ch_color = "#94a3b8"
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card = (
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"flex:1 1 148px;min-width:min(148px,100%);box-sizing:border-box;"
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"background:rgba(248,250,252,0.04);border:1px solid rgba(148,163,184,0.22);"
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"border-radius:12px;padding:14px 16px 12px 16px;text-align:left;"
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)
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return (
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f'<div style="{card}">'
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'<div style="font-size:0.82rem;font-weight:600;color:#94a3b8;margin:0 0 6px 0;line-height:1.3;">'
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f"{_e(code)}</div>"
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'<div style="font-size:1.5rem;font-weight:700;color:#f8fafc;margin:0 0 6px 0;'
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'line-height:1.15;letter-spacing:-0.03em;">'
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f"{_e(value)}</div>"
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f'<div style="font-size:0.88rem;font-weight:600;color:{ch_color};margin:0 0 8px 0;line-height:1.3;">'
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f"{_e(change_vs_prev)}</div>"
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'<div style="font-size:0.76rem;font-weight:400;color:#64748b;margin:0;line-height:1.45;">'
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f"{_e(description)}</div>"
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"</div>"
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)
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def _stat_row_wrap(inner: str) -> str:
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row = (
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"display:flex;flex-wrap:wrap;gap:0.65rem;margin-top:0.35rem;"
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"align-items:stretch;width:100%;"
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)
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return f'<div style="{row}">{inner}</div>'
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def _render_stat_row(html_fragment: str) -> None:
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"""优先 st.html（对自定义 HTML/CSS 限制更少）；否则回退 markdown。"""
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html_fn = getattr(st, "html", None)
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if callable(html_fn):
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html_fn(html_fragment, width="stretch")
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else:
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st.markdown(html_fragment, unsafe_allow_html=True)
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def _render_macro_two_rows(card_html_parts: list[str], per_row: int = 3) -> None:
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"""宏观指标固定为两排：每排 per_row 张（默认 3+3）。"""
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rows: list[str] = []
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for i in range(0, len(card_html_parts), per_row):
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rows.append(_stat_row_wrap("".join(card_html_parts[i : i + per_row])))
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outer = (
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'<div style="display:flex;flex-direction:column;gap:0.65rem;width:100%;">'
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+ "".join(rows)
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+ "</div>"
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)
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_render_stat_row(outer)
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def _parse_h5_sections(md: str) -> list[tuple[str, str]]:
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"""按五级标题 `##### ` 切分。首个 `#####` 之前的正文会合并进第一节，避免「经济数据」漂在折叠区外。"""
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lines = md.splitlines()
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sections: list[tuple[str, str]] = []
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buf: list[str] = []
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pending_title: str | None = None
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lead_before_first: list[str] = []
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for line in lines:
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stripped = line.strip()
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if stripped.startswith("##### ") and not stripped.startswith("######"):
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title = stripped[6:].strip()
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if pending_title is not None:
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body = "\n".join(buf).strip()
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if len(sections) == 0 and lead_before_first:
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pre = "\n".join(lead_before_first).strip()
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if pre:
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body = (pre + "\n\n" + body).strip() if body else pre
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lead_before_first = []
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sections.append((pending_title, body))
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buf = []
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else:
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lead_before_first = list(buf)
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buf = []
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pending_title = title
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else:
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buf.append(line)
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if pending_title is not None:
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body = "\n".join(buf).strip()
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if len(sections) == 0 and lead_before_first:
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pre = "\n".join(lead_before_first).strip()
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if pre:
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body = (pre + "\n\n" + body).strip() if body else pre
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sections.append((pending_title, body))
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return sections
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def _render_digest_markdown(digest: str) -> None:
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"""整段 Markdown → HTML 单容器（无 ##### 分节时使用）。"""
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if MarkdownIt is None:
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st.markdown(digest)
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return
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inner = MarkdownIt().enable("table").render(digest)
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wrap = (
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'<div class="ta-digest-prose ta-digest-prose--block" style="'
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"background:rgba(15,23,42,0.6);border:1px solid rgba(148,163,184,0.22);"
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"border-radius:12px;border-left:4px solid #818cf8;padding:16px 20px 18px 20px;"
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"margin-top:6px;font-size:0.92rem;line-height:1.75;color:#e2e8f0;"
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'">'
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f'<div class="ta-digest-inner">{inner}</div></div>'
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)
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html_fn = getattr(st, "html", None)
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if callable(html_fn):
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html_fn(wrap, width="stretch")
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else:
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st.markdown(wrap, unsafe_allow_html=True)
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def _render_digest_subsections_details(
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sections: list[tuple[str, str]],
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*,
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open_first: bool = True,
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) -> None:
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"""各 ##### 分节统一用 <details>；首节可默认展开（open），避免第一节单独用边框区与后续不一致。"""
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for i, (title, body) in enumerate(sections):
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label = (title or "").strip() or "分节"
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raw = body.strip() or "_（本节无正文）_"
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open_attr = ' open' if (open_first and i == 0) else ""
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if MarkdownIt is not None:
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inner = MarkdownIt().enable("table").render(raw)
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frag = (
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f'<details class="ta-digest-details"{open_attr}>'
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f'<summary class="ta-digest-summary">{_e(label)}</summary>'
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f'<div class="ta-digest-inner ta-digest-details-body">{inner}</div>'
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"</details>"
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)
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else:
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frag = (
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f'<details class="ta-digest-details"{open_attr}>'
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f'<summary class="ta-digest-summary">{_e(label)}</summary>'
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f'<div class="ta-digest-details-body"><pre style="white-space:pre-wrap;margin:0;">'
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f"{_e(raw)}</pre></div></details>"
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)
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html_fn = getattr(st, "html", None)
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if callable(html_fn):
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html_fn(frag, width="stretch")
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else:
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st.markdown(frag, unsafe_allow_html=True)
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def _render_digest_structured(digest: str) -> None:
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"""所有 ##### 分节统一为 <details>（首节默认展开），与「其他总结」折叠样式一致。"""
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sections = _parse_h5_sections(digest)
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if not sections:
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_render_digest_markdown(digest)
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return
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_render_digest_subsections_details(sections, open_first=True)
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def _format_asof_line(data: dict) -> str:
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"""仪表盘顶部：优先展示上次手动点击「更新」的 UTC 时间。"""
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fa = (data.get("fetched_at_utc") or "").strip()
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if fa:
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try:
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dt = datetime.fromisoformat(fa.replace("Z", "+00:00"))
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utc_s = dt.strftime("%Y-%m-%d %H:%M UTC")
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local_s = dt.astimezone().strftime("%Y-%m-%d %H:%M")
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return f"当前页数据对应上次手动更新时间：{utc_s}（本地 {local_s}）"
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except ValueError:
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return f"当前页数据对应上次手动更新时间：{fa}"
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et = (data.get("last_updated_et") or "").strip()
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if et:
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return (
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f"快照行情观察时间（ET）：{et}。"
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"尚未记录手动更新 UTC（请重新点击「更新市场数据」以写入归档时间）。"
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)
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return "暂无更新时间记录；请点击「更新市场数据」。"
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def _news_article_html(n: dict) -> str:
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"""速览卡片：外链「阅读原文」。"""
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title = html.escape(str(n.get("title", "N/A")))
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pub = (n.get("published_at") or "").strip()
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date_html = f'<span class="ta-news-date"> · {html.escape(pub)}</span>' if pub else ""
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prov = html.escape(str(n.get("provider", "Unknown")))
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summary = n.get("summary")
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link = n.get("link", "") or ""
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stance = n.get("stance") or "unknown"
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stance_label = html.escape(STANCE_LABEL_CN.get(stance, "未评估"))
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stance_cls = STANCE_CLASS.get(stance, "ta-stance-unknown")
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llm_text = (n.get("llm_summary") or "").strip()
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parts = [
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'<article class="ta-news-card">',
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f'<p class="ta-news-title">{title}{date_html}</p>',
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f'<p class="ta-news-meta">{prov} · <span class="{stance_cls}">{stance_label}</span></p>',
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]
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if summary:
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parts.append(f'<p class="ta-news-body">{html.escape(str(summary))}</p>')
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if llm_text:
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parts.append('<p class="ta-llm-hdr">大模型解读</p>')
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parts.append(f'<p class="ta-llm-body">{html.escape(llm_text)}</p>')
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if link:
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safe_link = html.escape(str(link), quote=True)
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parts.append(
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'<p class="ta-news-link-row">'
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f'<a href="{safe_link}" class="ta-news-link-original" target="_blank" '
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'rel="noopener noreferrer">阅读原文</a>'
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"</p>"
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)
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else:
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parts.append('<p class="ta-news-hint">无媒体外链</p>')
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parts.append("</article>")
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return "".join(parts)
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def render_dashboard() -> None:
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st.markdown(
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'<p class="ta-page-title">仪表盘</p>'
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'<p class="ta-page-desc">市场概览与快讯；点击「更新市场数据」将拉取 Yahoo 行情与新闻，'
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"并调用 Fast 模型生成新闻解读与大盘总结。</p>",
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unsafe_allow_html=True,
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)
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col_btn, col_status = st.columns([1, 2], gap="large")
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with col_btn:
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clicked = st.button("更新市场数据", key="refresh_dashboard")
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if clicked:
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# 仪表盘 LLM 与个股分析表单的 last_params 解耦，避免沿用分析任务里的 OpenAI/gpt-5.4-mini
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data, news = refresh_dashboard_cache(limit=10)
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st.session_state.dashboard_data = data
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st.session_state.dashboard_news = news
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else:
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data = st.session_state.get("dashboard_data")
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news = st.session_state.get("dashboard_news")
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if data is None:
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cached_data, cached_news = load_dashboard_display()
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if cached_data is not None:
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data = cached_data
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news = cached_news
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st.session_state.dashboard_data = cached_data
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st.session_state.dashboard_news = cached_news
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with col_status:
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if data is None:
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st.warning("当前无缓存数据。请点击左侧「更新市场数据」拉取最新行情。")
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else:
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st.caption(
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f"市场状态 `{data.get('market_status', 'N/A')}` · "
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f"行情快照 ET `{data.get('last_updated_et', 'N/A')}`"
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)
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lm = (data.get("llm_model") or "").strip()
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lp = (data.get("llm_provider") or "").strip()
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if lp and lm:
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st.caption(f"仪表盘 LLM：`{lp}` / `{lm}`")
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elif lm:
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st.caption(f"仪表盘 LLM（Quick）：`{lm}`")
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if data is None:
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return
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st.markdown(
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f'<p class="ta-data-as-of">{html.escape(_format_asof_line(data))}</p>',
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unsafe_allow_html=True,
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)
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digest = (data.get("market_digest_md") or "").strip()
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digest_err = (data.get("llm_digest_error") or "").strip()
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with st.expander("大盘总结（大模型）", expanded=True, key="dash_exp_digest"):
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if digest:
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_render_digest_structured(digest)
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else:
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st.info("总结暂不可用：模型未返回内容，或未配置密钥/调用失败。")
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if digest_err:
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st.code(digest_err, language="text")
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macro = data.get("macro_strip") or []
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if macro:
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with st.expander("宏观经济数据", expanded=True, key="dash_exp_macro"):
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st.caption("以下为市场可交易品种或收益率指数，非劳工部 CPI、非农等官方发布序列。")
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macro_cards = []
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for m in macro:
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ch = m.get("change_pct")
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dv = str(m.get("display_value", "N/A"))
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tk = str(m.get("ticker", ""))
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hint = str(m.get("hint", "")).strip()
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ch_s = f"{ch:+.2f}%" if ch is not None else "—"
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change_line = f"较昨收 {ch_s}"
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code = tk or "—"
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macro_cards.append(
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_stat_card_html(
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code,
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dv,
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change_line,
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hint or "（无说明）",
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positive=_delta_direction(ch),
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)
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)
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_render_macro_two_rows(macro_cards, per_row=3)
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with st.expander("主要指数", expanded=True, key="dash_exp_idx"):
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rows = data.get("indexes", [])
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if not rows:
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st.info("暂无指数数据。")
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else:
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idx_cards = []
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for row in rows:
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price = f"{row.price:.2f}" if row.price is not None else "N/A"
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ch = row.change_pct
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ch_s = f"{ch:+.2f}%" if ch is not None else "—"
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desc = (INDEX_SUBTITLE_CN.get(row.ticker) or "").strip() or "（无说明）"
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idx_cards.append(
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_stat_card_html(
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_metric_label_ticker(row.ticker),
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price,
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f"较昨收 {ch_s}",
|
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desc,
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positive=_delta_direction(ch),
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)
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)
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_render_stat_row(_stat_row_wrap("".join(idx_cards)))
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with st.expander("板块强弱 Top 3（代理 ETF）", expanded=True, key="dash_exp_sector"):
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sec = data.get("top3_sectors") or []
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if not sec:
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st.info("当前不可用，稍后重试。")
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else:
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sec_cards = []
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for row in sec[:3]:
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price = f"{row.price:.2f}" if row.price is not None else "N/A"
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ch = row.change_pct
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ch_s = f"{ch:+.2f}%" if ch is not None else "—"
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desc = (
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SECTOR_SUBTITLE_CN.get(row.ticker, f"{row.ticker} 板块/主题 ETF（代理）")
|
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).strip()
|
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sec_cards.append(
|
||
_stat_card_html(
|
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row.ticker,
|
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price,
|
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f"较昨收 {ch_s}",
|
||
desc or "（无说明）",
|
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positive=_delta_direction(ch),
|
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)
|
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)
|
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_render_stat_row(_stat_row_wrap("".join(sec_cards)))
|
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|
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news_list = news or st.session_state.get("dashboard_news") or []
|
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news_err = (data.get("llm_news_error") or "").strip()
|
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|
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with st.expander("Top 10 财经新闻", expanded=True, key="dash_exp_news"):
|
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if news_err:
|
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st.warning("新闻情绪解读未完全成功，以下为服务端返回摘要：" + news_err[:280])
|
||
if not news_list:
|
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st.info("暂无新闻数据（点击「更新市场数据」后可拉取）。")
|
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else:
|
||
cells = "".join(_news_article_html(n) for n in news_list[:10])
|
||
st.markdown(
|
||
f'<div class="ta-news-grid" role="list">{cells}</div>',
|
||
unsafe_allow_html=True,
|
||
)
|