v1.1.0: AI分析历史记录 + 数据源详情页(/analysis/<id>)，展示大模型参考的RAG新闻/概况/指标/评级/持仓/提示词

app.py

@@ -61,6 +61,12 @@ def page_stock(code):
                            service=SERVICE_NAME, is_mock=IS_MOCK)
 
 
+@app.route("/analysis/<int:aid>")
+def page_analysis(aid):
+    return render_template("analysis_detail.html", aid=aid,
+                           service=SERVICE_NAME, is_mock=IS_MOCK)
+
+
 # ===================================================================== 公共
 def _indicators(code):
     rows = query("SELECT date,open,high,low,close,volume FROM stock_daily "
@@ -365,13 +371,32 @@ def api_analyze(code):
 def api_analyze_status(code):
     from engine import analyst
     st = analyst.report_status(code)
-    if not st:
+    if st:
-        cached = analyst.get_cached_report(code)
+        return jsonify(st)
-        if cached:
+    # 无运行中任务：返回最近一次历史分析
-            return jsonify({"status": "done", "report": cached["report"],
+    hist = analyst.list_history(code, limit=1)
-                            "cached": True, "created_at": cached["created_at"]})
+    if hist:
-        return jsonify({"status": "idle"})
+        detail = analyst.get_history(hist[0]["id"])
-    return jsonify(st)
+        return jsonify({"status": "done", "report": detail["report"],
+                        "history_id": detail["id"], "created_at": detail["created_at"],
+                        "cached": True})
+    return jsonify({"status": "idle"})
+
+
+@app.route("/api/stock/<code>/analyses")
+def api_stock_analyses(code):
+    from engine import analyst
+    return jsonify({"items": analyst.list_history(code)})
+
+
+@app.route("/api/analyses/<int:aid>")
+def api_analysis_detail(aid):
+    from engine import analyst
+    d = analyst.get_history(aid)
+    if not d:
+        return jsonify({"error": "记录不存在"}), 404
+    stock = query_one("SELECT code, name, industry, board FROM stocks WHERE code=?", (d["code"],))
+    return jsonify({"analysis": d, "stock": stock})
 
 
 # ------------------------------------------------------------------ 自选

database.py

@@ -100,6 +100,17 @@ CREATE TABLE IF NOT EXISTS analysis_cache (
   created_at TEXT DEFAULT (datetime('now','localtime'))
 );
 
+CREATE TABLE IF NOT EXISTS analysis_history (
+  id INTEGER PRIMARY KEY AUTOINCREMENT,
+  code TEXT NOT NULL,
+  stock_name TEXT DEFAULT '',
+  focus TEXT DEFAULT '',
+  report TEXT,
+  sources TEXT DEFAULT '{}',        -- JSON：大模型参考的数据源（RAG新闻/概况/指标/评级/持仓/提示词）
+  created_at TEXT DEFAULT (datetime('now','localtime'))
+);
+CREATE INDEX IF NOT EXISTS idx_history_code ON analysis_history(code);
+
 CREATE TABLE IF NOT EXISTS market_index (
   date TEXT PRIMARY KEY,
   sh REAL DEFAULT 0,   -- 上证指数（点）
@@ -165,7 +176,8 @@ def table_count(name):
 def wipe_all():
     """清空业务表（保留结构）+ 重置自增序列，用于重灌数据"""
     for t in ("stock_daily", "inst_ratings", "fund_holdings", "news",
-              "institutions", "stocks", "watchlist", "analysis_cache", "market_index"):
+              "institutions", "stocks", "watchlist", "analysis_cache", "analysis_history",
+              "market_index"):
         with db() as conn:
             conn.execute(f'DELETE FROM "{t}"')
     with db() as conn:

engine/analyst.py

@@ -59,6 +59,7 @@ def _rag_news(code, stock_name, query_text, top_k=6):
                 "date": m.get("date", ""),
                 "sentiment": m.get("sentiment", 0),
                 "text": h.get("document", "")[:400],
+                "distance": round(h.get("distance", 0), 3),
             })
         return out
     except Exception as e:
@@ -140,7 +141,8 @@ def _build_prompt(stock, ind, news_hits, profile, ratings, holdings, score, focu
 
 
 def generate_report_sync(code, focus=""):
-    """同步生成报告（后台线程调用）"""
+    """同步生成报告（后台线程调用），并记录历史 + 数据源"""
+    import json
     stock = query_one("SELECT * FROM stocks WHERE code=?", (code,))
     if not stock:
         return {"error": "股票不存在"}
@@ -150,6 +152,17 @@ def generate_report_sync(code, focus=""):
     profile = _rag_profile(code)
     ratings, holdings = _inst_summary(code)
     prompt = _build_prompt(stock, ind, hits, profile, ratings, holdings, score, focus)
+    # 记录大模型参考的数据源（供详情页展示）
+    sources = {
+        "focus": focus,
+        "score": score,
+        "indicators": _fmt_indicators(ind),
+        "profile": profile or stock.get("description", ""),
+        "news": hits,
+        "ratings": ratings,
+        "holdings": holdings,
+        "prompt": prompt,
+    }
     try:
         report = llm_chat([
             {"role": "system", "content": "你是一名严谨专业的A股投资顾问，输出结构化、简洁、可执行的研报。"},
@@ -160,6 +173,10 @@ def generate_report_sync(code, focus=""):
             raise RuntimeError("LLM 返回为空")
         execute("INSERT OR REPLACE INTO analysis_cache(code, report, created_at) VALUES(?,?,datetime('now','localtime'))",
                 (code, report))
+        execute(
+            "INSERT INTO analysis_history(code, stock_name, focus, report, sources, created_at) "
+            "VALUES(?,?,?,?,?,datetime('now','localtime'))",
+            (code, stock["name"], focus, report, json.dumps(sources, ensure_ascii=False)))
         return {"report": report, "ts": time.time()}
     except Exception as e:
         log.exception("gen report fail")
@@ -221,3 +238,43 @@ def report_status(code):
 
 def get_cached_report(code):
     return query_one("SELECT report, created_at FROM analysis_cache WHERE code=?", (code,))
+
+
+# ------------------------------------------------------------------ 历史记录
+def list_history(code, limit=20):
+    """某股票的历史 AI 分析记录（不含正文，只返回摘要）"""
+    rows = query(
+        "SELECT id, code, stock_name, focus, created_at, sources, LENGTH(report) AS len, "
+        "SUBSTR(report, 1, 60) AS excerpt FROM analysis_history "
+        "WHERE code=? ORDER BY id DESC LIMIT ?", (code, limit))
+    out = []
+    for r in rows:
+        try:
+            import json
+            src = json.loads(r.get("sources") or "{}")
+        except Exception:
+            src = {}
+        out.append({
+            "id": r["id"], "code": r["code"], "stock_name": r["stock_name"],
+            "focus": r["focus"], "created_at": r["created_at"],
+            "chars": r["len"], "excerpt": (r["excerpt"] or "").strip(),
+            "news_count": len(src.get("news") or []),
+        })
+    return out
+
+
+def get_history(aid):
+    """单条分析详情：正文 + 数据源 JSON"""
+    import json
+    row = query_one("SELECT * FROM analysis_history WHERE id=?", (aid,))
+    if not row:
+        return None
+    try:
+        src = json.loads(row.get("sources") or "{}")
+    except Exception:
+        src = {}
+    return {
+        "id": row["id"], "code": row["code"], "stock_name": row["stock_name"],
+        "focus": row["focus"], "report": row["report"], "created_at": row["created_at"],
+        "sources": src,
+    }

static/css/style.css

@@ -208,3 +208,17 @@ tr:hover td { background: rgba(59,130,246,.05); }
 .score-bar .sb-track { flex: 1; height: 6px; background: #262d3a; border-radius: 3px; overflow: hidden; }
 .score-bar .sb-fill { height: 100%; background: linear-gradient(90deg, #3b82f6, #8b5cf6); border-radius: 3px; }
 .score-bar .sb-val { width: 28px; text-align: right; color: var(--text); }
+
+/* ===== 数据源区块（分析详情页） ===== */
+.src-block { border: 1px solid var(--border); border-radius: 10px; margin-bottom: 10px; background: var(--bg2); overflow: hidden; }
+.src-block summary { cursor: pointer; padding: 11px 14px; font-weight: 600; font-size: 13px; user-select: none; list-style: none; }
+.src-block summary::-webkit-details-marker { display: none; }
+.src-block summary:hover { background: rgba(59,130,246,.06); }
+.src-count { float: right; color: var(--accent); font-weight: 700; }
+.src-body { padding: 0 14px 12px; border-top: 1px solid #1f2630; }
+.src-news { padding: 10px 0; border-bottom: 1px dashed #1f2630; }
+.src-news:last-child { border-bottom: none; }
+.src-news-title { font-weight: 600; margin-bottom: 5px; font-size: 13px; }
+.src-news-meta { display: flex; gap: 10px; align-items: center; font-size: 12px; color: var(--muted); margin-bottom: 5px; flex-wrap: wrap; }
+.src-news-text { font-size: 12px; color: var(--text2); line-height: 1.7; }
+.src-pre { white-space: pre-wrap; word-break: break-word; font-size: 12px; color: var(--text2); line-height: 1.7; background: #0d1117; border: 1px solid #1f2630; border-radius: 8px; padding: 10px; overflow-x: auto; }

static/js/analysis_detail.js

@@ -0,0 +1,89 @@
+/* AI 分析详情页：研报正文 + 数据源 */
+const CODE_AID = parseInt(location.pathname.split('/').pop(), 10);
+
+async function load() {
+  try {
+    const d = await api('/api/analyses/' + CODE_AID);
+    const a = d.analysis, stock = d.stock || {};
+    $('#aStock').textContent = a.stock_name || stock.name || '—';
+    $('#aCode').textContent = a.code;
+    $('#aIndustry').textContent = stock ? (stock.name + ' · ' + (stock.industry || '') + ' · ' + (stock.board || '')) : '';
+    $('#aTime').textContent = a.created_at;
+    $('#aFocus').textContent = a.focus || '整体投资价值';
+    $('#reportBox').innerHTML = mdRender(a.report);
+    renderSources(a.sources || {});
+  } catch (e) {
+    $('#reportBox').innerHTML = '<div class="empty">加载失败：' + escapeHtml(e.message) + '</div>';
+  }
+}
+
+function srcBlock(title, icon, inner, count) {
+  return `<details class="src-block" ${inner ? 'open' : ''}>
+    <summary>${icon} ${title} ${count !== undefined ? `<span class="src-count">${count}</span>` : ''}</summary>
+    <div class="src-body">${inner || '<div class="empty">无</div>'}</div>
+  </details>`;
+}
+
+function renderSources(s) {
+  let html = '';
+
+  // 1. RAG 相关资讯
+  const news = s.news || [];
+  html += srcBlock('RAG 相关资讯（向量检索命中）', '📰', news.map(n => `
+    <div class="src-news">
+      <div class="src-news-title">${escapeHtml(n.title)}</div>
+      <div class="src-news-meta">
+        <span>${n.date || '—'}</span>
+        <span class="tag tag-${n.sentiment > 0 ? '正' : n.sentiment < 0 ? '负' : '平'}">情感 ${Number(n.sentiment).toFixed(2)}</span>
+        <span style="color:var(--muted)">相似度 ${(1 - (n.distance || 0)).toFixed(3)}</span>
+      </div>
+      <div class="src-news-text">${escapeHtml(n.text)}</div>
+    </div>`).join(''), news.length);
+
+  // 2. 公司概况
+  html += srcBlock('公司概况（RAG 检索）', '🏢', s.profile ? `<p>${escapeHtml(s.profile)}</p>` : '', s.profile ? 1 : 0);
+
+  // 3. 技术指标
+  html += srcBlock('技术指标', '📈', s.indicators ? `<pre class="src-pre">${escapeHtml(s.indicators)}</pre>` : '', s.indicators ? 1 : 0);
+
+  // 4. 综合评分
+  if (s.score) {
+    const sc = s.score;
+    html += srcBlock('综合评分', '🎯', `
+      <div class="mini-stats" style="gap:14px">
+        <div class="mini-stat"><div class="ms-label">总分</div><div class="ms-value" style="color:${sc.total >= 68 ? '#f59e0b' : '#3b82f6'}">${sc.total}</div></div>
+        <div class="mini-stat"><div class="ms-label">评级</div><div class="ms-value"><span class="tag tag-${sc.rating}">${sc.rating}</span></div></div>
+        <div class="mini-stat"><div class="ms-label">趋势</div><div class="ms-value">${sc.trend}</div></div>
+        <div class="mini-stat"><div class="ms-label">动量</div><div class="ms-value">${sc.momentum}</div></div>
+        <div class="mini-stat"><div class="ms-label">技术</div><div class="ms-value">${sc.technical}</div></div>
+        <div class="mini-stat"><div class="ms-label">量能</div><div class="ms-value">${sc.volume}</div></div>
+        <div class="mini-stat"><div class="ms-label">消息</div><div class="ms-value">${sc.news}</div></div>
+        <div class="mini-stat"><div class="ms-label">机构</div><div class="ms-value">${sc.institutional}</div></div>
+      </div>`, 1);
+  }
+
+  // 5. 机构评级
+  const ratings = s.ratings || [];
+  html += srcBlock('机构评级', '🏦', ratings.length ? `<table>
+    <tr><th>机构</th><th>评级</th><th>目标价</th><th>日期</th></tr>
+    ${ratings.map(r => `<tr><td>${escapeHtml(r.inst_name)}</td>
+      <td><span class="tag tag-${r.rating}">${r.rating}</span></td>
+      <td class="num">${r.target_price}</td><td>${r.rating_date}</td></tr>`).join('')}
+  </table>` : '', ratings.length);
+
+  // 6. 基金持仓
+  const holdings = s.holdings || [];
+  html += srcBlock('基金持仓', '💼', holdings.length ? `<table>
+    <tr><th>机构</th><th>季度</th><th>持仓市值</th><th>环比</th></tr>
+    ${holdings.map(h => `<tr><td>${escapeHtml(h.inst_name)}</td><td>${h.quarter}</td>
+      <td class="num">${fmtNum(h.hold_value)}</td>
+      <td class="num ${pctClass(h.change_pct)}">${fmtPct(h.change_pct)}</td></tr>`).join('')}
+  </table>` : '', holdings.length);
+
+  // 7. 完整提示词
+  html += srcBlock('完整提示词（Prompt）', '🧠', s.prompt ? `<pre class="src-pre">${escapeHtml(s.prompt)}</pre>` : '', s.prompt ? 1 : 0);
+
+  $('#sourceBox').innerHTML = html;
+}
+
+load();

static/js/stock_detail.js

@@ -232,7 +232,9 @@ async function pollReport() {
         clearInterval(timer);
         $('#analyzeBtn').disabled = false;
         $('#reportBox').innerHTML = `<div class="markdown-body">${mdRender(d.report)}</div>
-          <div style="color:var(--muted);font-size:12px;margin-top:12px">${d.cached ? '（缓存报告 ' + d.created_at + '）' : '生成耗时 ' + Math.round((Date.now() - t0) / 1000) + ' 秒'}</div>`;
+          <div style="color:var(--muted);font-size:12px;margin-top:12px">${d.cached ? '（最近一次分析记录，' + d.created_at + '）' : '生成耗时 ' + Math.round((Date.now() - t0) / 1000) + ' 秒'}
+          ${d.history_id ? ` · <a href="/analysis/${d.history_id}" target="_blank">查看数据源详情 ↗</a>` : ''}</div>`;
+        loadHistory();
       } else if (d.status === 'error') {
         clearInterval(timer);
         $('#analyzeBtn').disabled = false;
@@ -246,7 +248,32 @@ async function pollReport() {
   }, 4000);
 }
 
+/* 历史分析记录 */
+async function loadHistory() {
+  try {
+    const d = await api(`/api/stock/${CODE}/analyses`);
+    const items = d.items || [];
+    if (!items.length) {
+      $('#historyBox').innerHTML = '<div class="empty">暂无历史分析，点击上方「生成研报」开始</div>';
+      return;
+    }
+    $('#historyBox').innerHTML = `<table>
+      <tr><th>时间</th><th>关注点</th><th>引用资讯</th><th>报告摘要</th><th>操作</th></tr>
+      ${items.map(h => `<tr>
+        <td style="color:var(--muted)">${h.created_at}</td>
+        <td>${escapeHtml(h.focus || '整体投资价值')}</td>
+        <td class="num">${h.news_count} 条</td>
+        <td style="max-width:300px;white-space:normal;color:var(--text2)">${escapeHtml(h.excerpt)}…</td>
+        <td><button class="btn btn-primary" onclick="window.open('/analysis/${h.id}','_blank')">查看详情 ↗</button></td>
+      </tr>`).join('')}
+    </table>`;
+  } catch (e) {
+    $('#historyBox').innerHTML = '<div class="empty">历史记录加载失败</div>';
+  }
+}
+
 $('#analyzeBtn').onclick = generateReport;
 $('#focusInput').addEventListener('keydown', e => { if (e.key === 'Enter') generateReport(); });
 
 load();
+loadHistory();

templates/analysis_detail.html

@@ -0,0 +1,37 @@
+{% extends "base.html" %}
+{% block title %}AI 分析详情{% endblock %}
+{% block page_title %}AI 深度分析详情{% endblock %}
+{% block content %}
+<div id="topCard" class="card">
+  <div class="flex between wrap">
+    <div class="flex">
+      <div>
+        <div style="font-size:20px;font-weight:800"><span id="aStock">—</span> <span id="aCode" style="color:var(--muted);font-size:14px"></span></div>
+        <div class="mt8 flex" style="gap:14px;color:var(--muted);font-size:13px">
+          <span id="aIndustry">—</span>
+          <span>生成时间 <b id="aTime" style="color:var(--text)"></b></span>
+          <span>关注点 <b id="aFocus" style="color:var(--text)"></b></span>
+        </div>
+      </div>
+    </div>
+    <div class="flex">
+      <button class="btn" onclick="location.href='/stock/' + CODE">← 返回股票页</button>
+      <button class="btn btn-primary" onclick="location.href='/stock/' + CODE + '?analyze=1'">🤖 生成新分析</button>
+    </div>
+  </div>
+</div>
+
+<div class="grid grid-2-1 mt16">
+  <div class="card">
+    <div class="card-title"><span class="bar"></span>研报正文</div>
+    <div id="reportBox" class="markdown-body"><div class="loading">加载中…</div></div>
+  </div>
+  <div class="card">
+    <div class="card-title"><span class="bar" style="background:var(--gold)"></span>数据源（大模型参考内容）</div>
+    <div id="sourceBox" style="max-height:70vh;overflow:auto;padding-right:6px"><div class="loading">加载中…</div></div>
+  </div>
+</div>
+{% endblock %}
+{% block scripts %}
+<script src="{{ url_for('static', filename='js/analysis_detail.js') }}"></script>
+{% endblock %}

templates/stock_detail.html

@@ -71,6 +71,8 @@
   <div id="reportBox" class="mt16">
     <div class="empty">点击「生成研报」，系统将基于 新闻RAG检索 + 技术指标 + 机构数据 调用 DeepSeek 生成结构化研报（首次生成约需 30-90 秒）</div>
   </div>
+  <div class="card-title mt16" style="font-size:14px"><span class="bar" style="background:var(--cyan)"></span>历史分析记录</div>
+  <div id="historyBox"><div class="loading">加载中…</div></div>
 </div>
 
 <div class="card mt16">