feat: mo_alphasift_bridge v2 — async mode + source tracking (date/strategy/notes)

mo_alphasift_bridge.py

@@ -3,20 +3,19 @@
 mo_alphasift_bridge.py — AlphaSift 选股 → MoFin 自选池自动对接
 
 流程：
-1. 调用 DSA AlphaSift API → 获取候选股列表
+1. 提交 AlphaSift 异步选股任务 → 轮询结果
-2. 过滤（评分阈值 + 去重自选池/持仓）
+2. 过滤（评分阈值 + 去重）
-3. 写入 MoFin watchlist.json
+3. 写入 MoFin watchlist.json（含来源/日期/策略备注）
-4. 调用 regenerate_all() 生成策略 → decisions.json
+4. 调用 regenerate_all() 生成策略
-5. price_monitor 自动接管监控
+5. price_monitor 自动接管
 
 用法：
-  python3 mo_alphasift_bridge.py                    # 默认策略 balanced_alpha
+  python3 mo_alphasift_bridge.py                     # 默认策略
-  python3 mo_alphasift_bridge.py --strategy dual_low  # 指定策略
   python3 mo_alphasift_bridge.py --dry-run            # 只看不写
-  python3 mo_alphasift_bridge.py --min-score 6       # 最低评分阈值
+  python3 mo_alphasift_bridge.py --min-score 6        # 最低评分
+  python3 mo_alphasift_bridge.py --strategy list      # 列出所有策略
 
-集成到 cron:
+cron: 0 10 * * 1-5 cd /home/hmo/MoFin && python3 mo_alphasift_bridge.py
-  0 10 * * 1-5 cd /home/hmo/MoFin && python3 mo_alphasift_bridge.py
 """
 
 import sys, os, json, argparse, urllib.request, time
@@ -33,8 +32,10 @@ PORTFOLIO_PATH = MOFIN_DATA / "portfolio.json"
 DEFAULT_STRATEGY = "balanced_alpha"
 DEFAULT_MARKET = "cn"
 DEFAULT_MAX = 15
-MIN_SCORE = 5       # 最低评分
+MIN_SCORE = 5
-MAX_ADD = 5         # 每次最多加几只
+MAX_ADD = 5
+POLL_INTERVAL = 5
+POLL_TIMEOUT = 300
 
 
 def load_json(path):
@@ -49,135 +50,191 @@ def save_json(path, data):
     path.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
 
 
-def call_api(endpoint, method="GET", body=None):
+def api(endpoint, method="GET", body=None):
     url = f"{DSA_API}{endpoint}"
     data = json.dumps(body).encode() if body else None
     req = urllib.request.Request(url, data=data, method=method,
                                   headers={"Content-Type": "application/json"})
     try:
-        with urllib.request.urlopen(req, timeout=120) as r:
+        with urllib.request.urlopen(req, timeout=30) as r:
             return json.loads(r.read())
     except Exception as e:
-        print(f"API 错误: {e}")
+        print(f"  API 错误: {e}")
         return None
 
 
-# ── 核心逻辑 ─────────────────────────────────────────────────────────
+def get_existing_codes():
+    codes = set()
+    for path in [WATCHLIST_PATH, PORTFOLIO_PATH]:
+        data = load_json(path)
+        if not data:
+            continue
+        key = "stocks" if "watchlist" in str(path) else "holdings"
+        for item in data.get(key, []):
+            c = str(item.get("code", "")).strip()
+            if c:
+                codes.add(c)
+    return codes
+
 
 def run_screen(strategy, market, max_results, dry_run=False):
-    """运行 AlphaSift 选股并写入 MoFin 自选池"""
+    now = datetime.now()
+    date_str = now.strftime("%Y-%m-%d")
+    time_str = now.strftime("%Y-%m-%d %H:%M")
     
-    # 1. AlphaSift 选股
+    # 1. 提交异步任务
-    print(f"🔍 AlphaSift 选股: 策略={strategy} 市场={market}", flush=True)
+    print(f"AlphaSift 选股: {strategy} (异步)", flush=True)
-    result = call_api("/api/v1/alphasift/screen", "POST", {
+    task = api("/api/v1/alphasift/screen/tasks", "POST", {
         "strategy": strategy, "market": market, "max_results": max_results
     })
-    
+    if not task or not task.get("task_id"):
-    if not result or not result.get("candidates"):
+        print("  FAIL: 提交任务失败")
-        print("  ❌ 无候选股或 AlphaSift 返回空")
         return
     
-    candidates = result["candidates"]
+    task_id = task["task_id"]
-    print(f"  AlphaSift 返回 {len(candidates)} 只候选股")
+    print(f"  任务ID: {task_id[:12]}...", flush=True)
-    if result.get("llm_market_view"):
-        print(f"  市场观点: {result['llm_market_view'][:80]}...")
     
-    # 2. 加载现有自选池和持仓，去重
+    # 2. 轮询
-    wl = load_json(WATCHLIST_PATH) or {"stocks": []}
+    waited = 0
-    pf = load_json(PORTFOLIO_PATH) or {"holdings": []}
+    result = None
+    while waited < POLL_TIMEOUT:
+        time.sleep(POLL_INTERVAL)
+        waited += POLL_INTERVAL
+        status = api(f"/api/v1/alphasift/screen/tasks/{task_id}")
+        if not status:
+            continue
+        s = status.get("status", "")
+        if s == "completed":
+            print(f"  完成 ({waited}s)")
+            result = status.get("result", {})
+            break
+        elif s == "failed":
+            print(f"  FAIL: {status.get('error', '')}")
+            return
+        else:
+            pct = status.get("progress", 0)
+            print(f"  ...{s} ({pct}%)", flush=True)
+    else:
+        print(f"  FAIL: 超时 ({POLL_TIMEOUT}s)")
+        return
     
-    existing_codes = set()
+    candidates = result.get("candidates", [])
-    for s in wl.get("stocks", []):
+    if not candidates:
-        existing_codes.add(str(s.get("code", "")).strip())
+        print("  无候选股")
-    for h in pf.get("holdings", []):
+        return
-        existing_codes.add(str(h.get("code", "")).strip())
     
-    # 3. 过滤：评分达标 + 不在现有自选/持仓中
+    market_view = result.get("llm_market_view", "")
+    print(f"  返回 {len(candidates)} 只候选股")
+    if market_view:
+        print(f"  市场观点: {market_view[:100]}...")
+    
+    # 3. 过滤 + 去重
+    existing = get_existing_codes()
     new_stocks = []
+    skipped = 0
+    
     for c in candidates:
         code = str(c.get("code", "")).strip()
         score = c.get("score", 0) or c.get("llm_score", 0) or 0
-        name = c.get("name", "") or c.get("llm_thesis", "")[:20] or code
+        name = c.get("name", "") or c.get("title", "") or code
+        reason = c.get("reason", "") or c.get("llm_thesis", "")
+        catalysts = c.get("llm_catalysts", "")
+        risks = c.get("llm_risks", "")
         
         if score < MIN_SCORE:
+            skipped += 1
             continue
-        if code in existing_codes:
+        if code in existing:
-            print(f"  ⏭  {code} {name} (已在自选/持仓中)")
             continue
         
-        entry = {
+        notes_parts = [f"AlphaSift/{strategy} 评分{score}"]
+        if reason:
+            notes_parts.append(reason[:150])
+        if catalysts:
+            notes_parts.append(f"催化剂:{catalysts[:100]}")
+        
+        new_stocks.append({
             "code": code,
             "name": name,
             "price": c.get("price", 0),
-            "tag": f"alpha_sift_{strategy}",
             "source": "alpha_sift",
-            "added_at": datetime.now().strftime("%Y-%m-%d %H:%M"),
+            "source_detail": {
-            "alpha_score": score,
+                "strategy": strategy,
-            "alpha_reason": (c.get("reason", "") or c.get("llm_thesis", ""))[:200],
+                "score": score,
+                "date": date_str,
+                "reason": reason[:300],
+                "catalysts": catalysts[:200] if catalysts else "",
+                "risks": risks[:200] if risks else "",
+                "market_view": market_view[:300] if market_view else "",
+            },
+            "notes": " | ".join(notes_parts),
+            "added_at": time_str,
+            "added_by": "AlphaSift",
             "analysis": {},
-        }
+        })
-        new_stocks.append(entry)
+        existing.add(code)
-        existing_codes.add(code)
+    
+    print(f"  过滤: {len(new_stocks)} 新标的 (跳过{skipped}只评分不足)")
     
     if not new_stocks:
-        print("  ℹ️  没有符合条件的新标的")
+        print("  无符合条件的新标的")
         return
     
-    # 限制数量
     new_stocks = new_stocks[:MAX_ADD]
-    print(f"\n  ✅ 新增 {len(new_stocks)} 只到自选池:")
+    
+    print(f"\n  新增 {len(new_stocks)} 只到自选池:")
     for s in new_stocks:
-        print(f"     {s['code']} {s['name']} (评分{s['alpha_score']})")
+        print(f"    {s['code']} {s['name']} (评分{s['source_detail']['score']})")
+        if s['source_detail'].get('reason'):
+            print(f"      {s['source_detail']['reason'][:120]}")
     
     if dry_run:
-        print("\n  [DRY RUN] 未实际写入")
+        print("\n  [DRY RUN] 未写入")
         return
     
-    # 4. 写入 watchlist.json
+    # 4. 写入
+    wl = load_json(WATCHLIST_PATH) or {"stocks": []}
     wl["stocks"].extend(new_stocks)
-    wl["updated_at"] = datetime.now().strftime("%Y-%m-%d %H:%M")
+    wl["updated_at"] = time_str
     save_json(WATCHLIST_PATH, wl)
-    print(f"  已写入 {WATCHLIST_PATH}")
+    print(f"\n  已写入 {WATCHLIST_PATH}")
     
-    # 5. 触发策略生成
+    # 5. 策略生成
-    print("\n🔄 调用 regenerate_all() 生成策略...")
+    print("\n  调用 regenerate_all() 生成策略...")
     try:
         sys.path.insert(0, str(MOFIN_DATA.parent))
         from strategy_lifecycle import regenerate_all
-        result = regenerate_all(stdout=True)
+        r = regenerate_all(stdout=True)
-        if result:
+        if r:
-            print(f"  策略生成完成: total={result.get('total',0)} ok={result.get('ok',0)}")
+            print(f"  完成: {r.get('ok',0)}/{r.get('total',0)} 只策略已生成")
+            print(f"  price_monitor 将在 2 分钟内自动开始监控")
     except Exception as e:
-        print(f"  ⚠️ regenerate_all() 失败: {e}")
+        print(f"  WARN: regenerate_all 失败: {e}")
-        print("  新股票已加入自选池，下次 cron 会自动生成策略")
+        print(f"  股票已加入自选池，下次 cron 会自动处理")
 
 
-# ── CLI ──────────────────────────────────────────────────────────────
+def list_strategies():
+    r = api("/api/v1/alphasift/strategies")
+    if r and r.get("strategies"):
+        print("AlphaSift 策略:")
+        for s in r["strategies"]:
+            print(f"  {s['id']:20s} {s.get('name','?'):15s} {s.get('description','')[:60]}")
+
 
 def main():
-    parser = argparse.ArgumentParser(description="AlphaSift → MoFin 自动对接")
+    global MIN_SCORE
-    parser.add_argument("--strategy", default=DEFAULT_STRATEGY,
+    parser = argparse.ArgumentParser(description="AlphaSift → MoFin")
-                        help=f"选股策略 (默认: {DEFAULT_STRATEGY})")
+    parser.add_argument("--strategy", default=DEFAULT_STRATEGY)
-    parser.add_argument("--market", default=DEFAULT_MARKET,
+    parser.add_argument("--market", default=DEFAULT_MARKET)
-                        help=f"市场 (默认: {DEFAULT_MARKET})")
+    parser.add_argument("--max", type=int, default=DEFAULT_MAX)
-    parser.add_argument("--max", type=int, default=DEFAULT_MAX,
+    parser.add_argument("--min-score", type=int, default=MIN_SCORE)
-                        help=f"AlphaSift 最多返回 (默认: {DEFAULT_MAX})")
+    parser.add_argument("--dry-run", action="store_true")
-    parser.add_argument("--min-score", type=int, default=MIN_SCORE,
-                        help=f"最低评分 (默认: {MIN_SCORE})")
-    parser.add_argument("--dry-run", action="store_true",
-                        help="只看不写")
-    
     args = parser.parse_args()
+    MIN_SCORE = args.min_score
     
-    # 列出可用策略
     if args.strategy == "list":
-        r = call_api("/api/v1/alphasift/strategies")
+        list_strategies()
-        if r and r.get("strategies"):
-            print("可用策略:")
-            for s in r["strategies"]:
-                print(f"  {s['id']}: {s.get('name','?')} - {s.get('description','')[:60]}")
         return
-    
     run_screen(args.strategy, args.market, args.max, args.dry_run)