256 lines
8.7 KiB
Python
256 lines
8.7 KiB
Python
"""Recommendation and lifecycle-facing DB API."""
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from datetime import datetime, timedelta
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from app.db.recommendation_commands import apply_recommendation_state_transition
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from app.db.recommendation_state import (
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classify_recommendation_result as _classify_recommendation_result,
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derive_execution_fields as _derive_execution_fields,
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is_actionable_execution_status as _is_actionable_execution_status,
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)
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from app.db.push_queries import get_recommendation_for_push, log_push, should_push
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from app.db.schema import get_conn
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from app.db.tracking_queries import update_recommendation_tracking
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from app.services.llm_insights import attach_recommendation_insights
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def get_active_recommendations(actionable_only: bool = False):
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"""获取所有 active 推荐。"""
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conn = get_conn()
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rows = conn.execute(
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"""
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SELECT * FROM recommendation
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WHERE status='active' AND COALESCE(display_bucket,'watch_pool') != 'history'
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ORDER BY rec_time DESC
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"""
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).fetchall()
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conn.close()
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result = []
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for row in rows:
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item = _derive_execution_fields(dict(row))
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if actionable_only and not _is_actionable_execution_status(item.get("execution_status")):
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continue
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result.append(item)
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return _attach_onchain_context(result)
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def _attach_onchain_context(items):
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if not items:
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return items
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symbols = sorted({item.get("symbol") for item in items if item.get("symbol")})
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if not symbols:
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return items
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placeholders = ",".join(["%s"] * len(symbols))
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try:
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conn = get_conn()
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rows = conn.execute(
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f"""
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SELECT m.*
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FROM onchain_token_metrics m
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JOIN (
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SELECT symbol, MAX(metric_time) AS max_time
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FROM onchain_token_metrics
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WHERE symbol IN ({placeholders})
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GROUP BY symbol
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) latest ON latest.symbol=m.symbol AND latest.max_time=m.metric_time
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""",
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tuple(symbols),
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).fetchall()
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events = conn.execute(
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f"""
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SELECT *
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FROM onchain_events
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WHERE symbol IN ({placeholders})
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AND detected_at >= %s
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ORDER BY detected_at::timestamp DESC, id DESC
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""",
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(*symbols, (datetime.now() - timedelta(hours=24)).isoformat()),
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).fetchall()
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conn.close()
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except Exception:
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return items
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metrics = {row["symbol"]: dict(row) for row in rows}
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by_symbol = {}
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for row in events:
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by_symbol.setdefault(row["symbol"], []).append(dict(row))
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for item in items:
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metric = metrics.get(item.get("symbol")) or {}
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evs = by_symbol.get(item.get("symbol")) or []
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if not metric and not evs:
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continue
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risk_events = [e for e in evs if e.get("direction") == "risk"]
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positive_events = [e for e in evs if e.get("direction") == "positive"]
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if risk_events:
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headline = risk_events[0].get("signal_label") or "链上风险升温"
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elif positive_events:
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headline = positive_events[0].get("signal_label") or "链上资金异动"
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else:
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headline = "链上异动"
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item["onchain_context"] = {
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"headline": headline,
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"chain": metric.get("chain") or (evs[0].get("chain") if evs else ""),
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"onchain_score": metric.get("onchain_score") or 0,
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"risk_score": metric.get("risk_score") or 0,
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"dex_volume_usd": metric.get("dex_volume_usd") or 0,
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"liquidity_usd": metric.get("liquidity_usd") or 0,
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"event_count_24h": len(evs),
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"risk_event_count_24h": len(risk_events),
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"top_events": [
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{
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"signal_code": e.get("signal_code"),
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"signal_label": e.get("signal_label"),
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"direction": e.get("direction"),
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"value_usd": e.get("value_usd") or 0,
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"detected_at": e.get("detected_at"),
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}
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for e in evs[:3]
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],
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}
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return items
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def get_active_recommendations_deduped(
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actionable_only: bool = True,
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version: str = "",
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hours: float = 0,
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watch_symbols=None,
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limit: int = 0,
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offset: int = 0,
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with_meta: bool = False,
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):
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"""同 symbol 只保留最新 active 推荐，并附带派生执行状态。"""
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conn = get_conn()
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where = "status='active' AND COALESCE(display_bucket,'watch_pool') != 'history'"
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params = []
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version = str(version or "").strip()
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if version:
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where += " AND strategy_version=%s"
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params.append(version)
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if watch_symbols:
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symbols = [str(s).strip().upper() for s in watch_symbols if str(s).strip()]
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if symbols:
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where += " AND symbol IN (" + ",".join(["%s"] * len(symbols)) + ")"
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params.extend(symbols)
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try:
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hours = float(hours or 0)
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except Exception:
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hours = 0
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if hours > 0:
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where += " AND rec_time >= %s"
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params.append((datetime.now() - timedelta(hours=hours)).isoformat())
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try:
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limit = max(0, int(limit or 0))
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except Exception:
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limit = 0
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try:
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offset = max(0, int(offset or 0))
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except Exception:
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offset = 0
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rows = conn.execute(
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f"""
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SELECT r.*,
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lpc.price AS latest_cache_price,
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lpc.updated_at AS latest_cache_updated_at
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FROM recommendation r
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LEFT JOIN latest_price_cache lpc ON lpc.symbol = r.symbol
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JOIN (
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SELECT symbol, MAX(id) AS max_id
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FROM recommendation
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WHERE {where}
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GROUP BY symbol
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) latest ON latest.max_id = r.id
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ORDER BY r.rec_time DESC
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""",
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tuple(params),
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).fetchall()
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conn.close()
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all_items = []
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summary = {
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"buy_now": 0,
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"wait_pullback": 0,
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"observe": 0,
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"observe_strong": 0,
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"observe_weak": 0,
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"expired": 0,
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"total": 0,
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"discovery_burst": 0,
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"executable_now": 0,
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"planned_entry": 0,
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"watch_pool": 0,
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}
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now = datetime.now()
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for row in rows:
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item = dict(row)
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rec_result, rec_result_label = _classify_recommendation_result(item)
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item["recommendation_result"] = rec_result
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item["recommendation_result_label"] = rec_result_label
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_derive_execution_fields(item)
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is_expired = False
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if hours > 0:
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try:
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rec_time = item.get("rec_time")
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if rec_time:
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is_expired = (now - datetime.fromisoformat(str(rec_time))).total_seconds() > hours * 3600
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except Exception:
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is_expired = False
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if item.get("execution_status") == "invalid" or item.get("status") in ("invalid", "expired", "archived") or item.get("display_bucket") == "history":
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is_expired = True
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if is_expired:
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summary["expired"] += 1
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continue
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if actionable_only and not _is_actionable_execution_status(item.get("execution_status")):
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continue
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all_items.append(item)
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if item.get("is_discovery_burst"):
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summary["discovery_burst"] += 1
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if item.get("is_executable_now"):
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summary["executable_now"] += 1
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if item.get("execution_status") == "wait_pullback":
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summary["planned_entry"] += 1
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if item.get("is_watch_pool"):
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summary["watch_pool"] += 1
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if item.get("execution_status") == "buy_now":
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summary["buy_now"] += 1
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elif item.get("execution_status") == "wait_pullback":
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summary["wait_pullback"] += 1
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else:
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summary["observe"] += 1
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if item.get("observe_tier") == "weak":
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summary["observe_weak"] += 1
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else:
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summary["observe_strong"] += 1
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summary["total"] = len(all_items)
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summary["expired_filtered"] = summary.pop("expired", 0)
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if not with_meta:
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_attach_onchain_context(all_items)
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return attach_recommendation_insights(all_items)
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page_items = all_items[offset : offset + limit] if limit else all_items[offset:]
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_attach_onchain_context(page_items)
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attach_recommendation_insights(page_items)
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return {
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"items": page_items,
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"total": len(all_items),
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"limit": limit,
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"offset": offset,
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"has_more": bool(limit and offset + len(page_items) < len(all_items)),
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"summary": summary,
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}
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__all__ = [
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"apply_recommendation_state_transition",
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"get_active_recommendations",
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"get_active_recommendations_deduped",
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"get_recommendation_for_push",
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"log_push",
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"should_push",
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"update_recommendation_tracking",
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]
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