TIANHE
@@ -26,6 +26,7 @@ def register_routes(app: Flask):
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from app.routes.fast_analysis import fast_analysis_bp
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from app.routes.billing import billing_bp
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from app.routes.quick_trade import quick_trade_bp
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from app.routes.polymarket import polymarket_bp
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app.register_blueprint(health_bp)
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app.register_blueprint(auth_bp, url_prefix='/api/auth') # Auth routes
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@@ -46,4 +47,5 @@ def register_routes(app: Flask):
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app.register_blueprint(community_bp, url_prefix='/api/community')
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app.register_blueprint(fast_analysis_bp, url_prefix='/api/fast-analysis')
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app.register_blueprint(billing_bp, url_prefix='/api/billing')
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app.register_blueprint(quick_trade_bp, url_prefix='/api/quick-trade')
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app.register_blueprint(quick_trade_bp, url_prefix='/api/quick-trade')
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app.register_blueprint(polymarket_bp, url_prefix='/api/polymarket')
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@@ -1837,11 +1837,61 @@ def _analyze_opportunities_forex(opportunities: list):
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})
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def _analyze_opportunities_polymarket(opportunities: list):
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"""扫描预测市场机会"""
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try:
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from app.data_sources.polymarket import PolymarketDataSource
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from app.services.polymarket_analyzer import PolymarketAnalyzer
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polymarket_source = PolymarketDataSource()
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analyzer = PolymarketAnalyzer()
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# 获取热门市场
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markets = polymarket_source.get_trending_markets(limit=20)
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for market in markets:
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try:
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# AI分析
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analysis = analyzer.analyze_market(market['market_id'])
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if analysis.get('error'):
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continue
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# 只添加高分机会
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if analysis.get('opportunity_score', 0) > 75:
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opportunities.append({
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"symbol": market['question'][:50], # 简化显示
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"name": market['question'],
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"price": market['current_probability'],
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"change_24h": 0, # 预测市场没有24h涨跌幅概念
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"signal": "prediction_opportunity",
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"strength": "strong" if analysis.get('opportunity_score', 0) > 85 else "medium",
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"reason": f"AI预测概率{analysis.get('ai_predicted_probability', 0):.1f}%，市场概率{market['current_probability']:.1f}%，差异{analysis.get('divergence', 0):.1f}%",
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"impact": "bullish" if analysis.get('recommendation') == "YES" else "bearish",
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"market": "PredictionMarket",
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"market_id": market['market_id'],
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"ai_analysis": {
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"predicted_probability": analysis.get('ai_predicted_probability', 0),
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"recommendation": analysis.get('recommendation', 'HOLD'),
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"confidence_score": analysis.get('confidence_score', 0),
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"opportunity_score": analysis.get('opportunity_score', 0)
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},
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"timestamp": int(time.time())
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})
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except Exception as e:
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logger.debug(f"Failed to analyze polymarket {market.get('market_id')}: {e}")
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continue
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except Exception as e:
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logger.error(f"_analyze_opportunities_polymarket failed: {e}")
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@global_market_bp.route("/opportunities", methods=["GET"])
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@login_required
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def trading_opportunities():
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"""
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Scan for trading opportunities across Crypto, US Stocks, and Forex.
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Note: Prediction Markets are excluded as they have their own dedicated page.
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Cached for 1 hour. Pass ?force=true to skip cache.
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"""
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try:
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@@ -1878,6 +1928,9 @@ def trading_opportunities():
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except Exception as e:
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logger.error(f"Failed to analyze forex opportunities: {e}", exc_info=True)
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# Note: Prediction Markets are excluded from trading opportunities radar
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# as they have their own dedicated page at /polymarket
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# Sort by absolute change descending
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opportunities.sort(key=lambda x: abs(x.get("change_24h", 0)), reverse=True)
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@@ -185,7 +185,7 @@ def save_indicator():
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description = (data.get("description") or "").strip()
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publish_to_community = 1 if data.get("publishToCommunity") or data.get("publish_to_community") else 0
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pricing_type = (data.get("pricingType") or data.get("pricing_type") or "free").strip() or "free"
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vip_free = 1 if (data.get("vipFree") or data.get("vip_free")) else 0
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vip_free = bool(data.get("vipFree") or data.get("vip_free"))
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try:
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price = float(data.get("price") or 0)
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except Exception:
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@@ -265,7 +265,7 @@ def save_indicator():
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UPDATE qd_indicator_codes
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SET name = ?, code = ?, description = ?,
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publish_to_community = ?, pricing_type = ?, price = ?, preview_image = ?,
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vip_free = 0,
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vip_free = FALSE,
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review_status = NULL, review_note = '', reviewed_at = NULL, reviewed_by = NULL,
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updatetime = ?, updated_at = NOW()
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WHERE id = ? AND user_id = ? AND (is_buy IS NULL OR is_buy = 0)
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@@ -0,0 +1,442 @@
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"""
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Polymarket预测市场API路由
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提供预测市场数据和分析接口（只读，不涉及交易）
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"""
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from flask import Blueprint, jsonify, request, g
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from app.utils.auth import login_required
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from app.utils.logger import get_logger
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from app.data_sources.polymarket import PolymarketDataSource
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from app.utils.db import get_db_connection
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import json
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from datetime import datetime, timedelta
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logger = get_logger(__name__)
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polymarket_bp = Blueprint('polymarket', __name__)
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# 初始化服务
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polymarket_source = PolymarketDataSource()
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@polymarket_bp.route("/markets", methods=["GET"])
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@login_required
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def get_markets():
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"""
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获取预测市场列表
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Query params:
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category: crypto/politics/economics/sports (optional)
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sort_by: volume_24h/ai_score/probability_change (default: volume_24h)
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limit: 数量 (default: 20)
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"""
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try:
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category = request.args.get("category")
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sort_by = request.args.get("sort_by", "volume_24h")
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limit = int(request.args.get("limit", 20))
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# 获取市场列表
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markets = polymarket_source.get_trending_markets(category, limit * 2)
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logger.info(f"Fetched {len(markets)} markets from PolymarketDataSource (category={category}, limit={limit})")
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if not markets:
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logger.warning(f"No markets returned from PolymarketDataSource. This may indicate API issues or empty cache.")
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return jsonify({
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"code": 1,
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"msg": "success",
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"data": [],
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"warning": "No markets available. API may be unavailable or cache is empty."
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})
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# 从数据库读取缓存的AI分析结果（由后台任务批量分析生成）
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# 只读取30分钟内的分析结果
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try:
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with get_db_connection() as db:
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cur = db.cursor()
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market_ids = [m.get('market_id') for m in markets if m.get('market_id')]
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if market_ids:
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# 查询30分钟内的分析结果
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from datetime import datetime, timedelta
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cache_cutoff = datetime.now() - timedelta(minutes=30)
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placeholders = ','.join(['%s'] * len(market_ids))
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cur.execute(f"""
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SELECT market_id, ai_predicted_probability, market_probability, divergence,
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recommendation, confidence_score, opportunity_score, reasoning, key_factors
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FROM qd_polymarket_ai_analysis
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WHERE market_id IN ({placeholders})
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AND user_id IS NULL
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AND created_at > %s
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ORDER BY opportunity_score DESC
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""", market_ids + [cache_cutoff])
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rows = cur.fetchall()
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cur.close()
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# 构建分析结果映射
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analysis_map = {}
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for row in rows:
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market_id = row.get('market_id')
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if market_id:
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key_factors_raw = row.get('key_factors')
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key_factors = []
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if key_factors_raw:
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try:
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if isinstance(key_factors_raw, str):
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key_factors = json.loads(key_factors_raw)
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else:
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key_factors = key_factors_raw if isinstance(key_factors_raw, list) else []
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except:
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key_factors = []
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analysis_map[market_id] = {
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'predicted_probability': float(row.get('ai_predicted_probability') or 0),
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'recommendation': row.get('recommendation') or 'HOLD',
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'confidence_score': float(row.get('confidence_score') or 0),
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'opportunity_score': float(row.get('opportunity_score') or 0),
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'divergence': float(row.get('divergence') or 0),
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'reasoning': row.get('reasoning') or '',
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'key_factors': key_factors
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}
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# 为每个市场添加分析结果
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for market in markets:
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market_id = market.get('market_id')
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if market_id and market_id in analysis_map:
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market['ai_analysis'] = analysis_map[market_id]
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else:
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market['ai_analysis'] = None
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else:
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# 如果没有市场ID，设置分析为None
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for market in markets:
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market['ai_analysis'] = None
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except Exception as e:
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logger.warning(f"Failed to load cached analysis: {e}")
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# 出错时，所有市场都没有分析结果
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for market in markets:
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market['ai_analysis'] = None
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# 筛选：优先返回有交易机会的市场，但也包含其他活跃市场
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# 重点：不是简单复制数据，而是找到交易机会，但也要保证有足够的数据展示
|
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opportunity_markets = []
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other_markets = []
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for market in markets:
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ai_analysis = market.get('ai_analysis')
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volume = market.get('volume_24h', 0) or 0
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prob = market.get('current_probability', 50.0) or 50.0
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if ai_analysis:
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opportunity_score = ai_analysis.get('opportunity_score', 0) or 0
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divergence = abs(ai_analysis.get('divergence', 0) or 0)
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confidence = ai_analysis.get('confidence_score', 0) or 0
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# 筛选条件：机会评分>60 或 (差异>15% 且 置信度>70) 或 (差异>10% 且 置信度>60)
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if opportunity_score > 60 or (divergence > 15 and confidence > 70) or (divergence > 10 and confidence > 60):
|
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opportunity_markets.append(market)
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elif volume > 5000: # 交易量较大的也作为备选
|
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other_markets.append(market)
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else:
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# 如果没有AI分析，但交易量大且概率不是50%（说明有明确的市场共识），也包含
|
||||
if volume > 5000 and abs(prob - 50.0) > 5: # 降低阈值，包含更多市场
|
||||
other_markets.append(market)
|
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||||
# 合并结果：优先显示机会市场，然后补充其他活跃市场
|
||||
if opportunity_markets:
|
||||
# 如果有机会市场，优先显示它们，然后补充其他市场直到达到limit
|
||||
result_markets = opportunity_markets[:limit]
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remaining = limit - len(result_markets)
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if remaining > 0 and other_markets:
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result_markets.extend(other_markets[:remaining])
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||||
opportunity_markets = result_markets
|
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elif other_markets:
|
||||
# 如果没有机会市场，至少返回高交易量的市场
|
||||
opportunity_markets = other_markets[:limit]
|
||||
else:
|
||||
# 如果都没有，返回原始市场列表的前几个
|
||||
opportunity_markets = markets[:min(limit, len(markets))]
|
||||
|
||||
# 排序和筛选
|
||||
if sort_by == "ai_score":
|
||||
# 按AI机会评分排序（高概率/高回报比优先）
|
||||
opportunity_markets.sort(
|
||||
key=lambda x: (
|
||||
x.get('ai_analysis', {}).get('opportunity_score', 0) or 0,
|
||||
abs(x.get('ai_analysis', {}).get('divergence', 0) or 0), # 差异越大越好
|
||||
x.get('ai_analysis', {}).get('confidence_score', 0) or 0 # 置信度越高越好
|
||||
),
|
||||
reverse=True
|
||||
)
|
||||
elif sort_by == "high_probability":
|
||||
# 高概率机会：AI预测概率 > 市场概率 + 10%
|
||||
opportunity_markets.sort(
|
||||
key=lambda x: (
|
||||
x.get('ai_analysis', {}).get('ai_predicted_probability', 0) or 0,
|
||||
x.get('ai_analysis', {}).get('confidence_score', 0) or 0
|
||||
),
|
||||
reverse=True
|
||||
)
|
||||
elif sort_by == "high_return":
|
||||
# 高回报比机会：AI与市场差异大且置信度高
|
||||
opportunity_markets.sort(
|
||||
key=lambda x: (
|
||||
abs(x.get('ai_analysis', {}).get('divergence', 0) or 0) *
|
||||
(x.get('ai_analysis', {}).get('confidence_score', 0) or 0) / 100,
|
||||
x.get('ai_analysis', {}).get('opportunity_score', 0) or 0
|
||||
),
|
||||
reverse=True
|
||||
)
|
||||
elif sort_by == "probability_change":
|
||||
# 需要历史数据，暂时按volume排序
|
||||
opportunity_markets.sort(key=lambda x: x.get('volume_24h', 0), reverse=True)
|
||||
else:
|
||||
opportunity_markets.sort(key=lambda x: x.get('volume_24h', 0), reverse=True)
|
||||
|
||||
return jsonify({
|
||||
"code": 1,
|
||||
"msg": "success",
|
||||
"data": opportunity_markets[:limit],
|
||||
"total_opportunities": len(opportunity_markets),
|
||||
"total_markets": len(markets)
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"get_markets failed: {e}", exc_info=True)
|
||||
return jsonify({
|
||||
"code": 0,
|
||||
"msg": str(e),
|
||||
"data": None
|
||||
}), 500
|
||||
|
||||
|
||||
@polymarket_bp.route("/markets/<market_id>", methods=["GET"])
|
||||
@login_required
|
||||
def get_market_detail(market_id: str):
|
||||
"""
|
||||
获取单个市场详情和AI分析
|
||||
|
||||
支持通过market ID或slug查询
|
||||
"""
|
||||
try:
|
||||
# 确保market_id是字符串
|
||||
market_id = str(market_id).strip()
|
||||
# 获取市场数据
|
||||
market = polymarket_source.get_market_details(market_id)
|
||||
if not market:
|
||||
return jsonify({
|
||||
"code": 0,
|
||||
"msg": "Market not found",
|
||||
"data": None
|
||||
}), 404
|
||||
|
||||
# 从数据库读取缓存的AI分析结果（30分钟内）
|
||||
analysis = None
|
||||
try:
|
||||
with get_db_connection() as db:
|
||||
cur = db.cursor()
|
||||
cache_cutoff = datetime.now() - timedelta(minutes=30)
|
||||
|
||||
cur.execute("""
|
||||
SELECT ai_predicted_probability, market_probability, divergence,
|
||||
recommendation, confidence_score, opportunity_score,
|
||||
reasoning, key_factors, related_assets, created_at
|
||||
FROM qd_polymarket_ai_analysis
|
||||
WHERE market_id = %s AND user_id IS NULL AND created_at > %s
|
||||
ORDER BY created_at DESC LIMIT 1
|
||||
""", (market_id, cache_cutoff))
|
||||
|
||||
row = cur.fetchone()
|
||||
cur.close()
|
||||
|
||||
if row:
|
||||
key_factors_raw = row.get('key_factors')
|
||||
key_factors = []
|
||||
if key_factors_raw:
|
||||
try:
|
||||
if isinstance(key_factors_raw, str):
|
||||
key_factors = json.loads(key_factors_raw)
|
||||
else:
|
||||
key_factors = key_factors_raw if isinstance(key_factors_raw, list) else []
|
||||
except:
|
||||
key_factors = []
|
||||
|
||||
analysis = {
|
||||
"ai_predicted_probability": float(row.get('ai_predicted_probability') or 0),
|
||||
"market_probability": float(row.get('market_probability') or 0),
|
||||
"divergence": float(row.get('divergence') or 0),
|
||||
"recommendation": row.get('recommendation') or 'HOLD',
|
||||
"confidence_score": float(row.get('confidence_score') or 0),
|
||||
"opportunity_score": float(row.get('opportunity_score') or 0),
|
||||
"reasoning": row.get('reasoning') or '',
|
||||
"key_factors": key_factors,
|
||||
"related_assets": row.get('related_assets') if row.get('related_assets') else []
|
||||
}
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to load cached analysis for market {market_id}: {e}")
|
||||
|
||||
# 资产交易机会（暂时返回空，可以后续实现）
|
||||
asset_opportunities = []
|
||||
|
||||
return jsonify({
|
||||
"code": 1,
|
||||
"msg": "success",
|
||||
"data": {
|
||||
"market": market,
|
||||
"ai_analysis": analysis,
|
||||
"asset_opportunities": asset_opportunities
|
||||
}
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"get_market_detail failed: {e}", exc_info=True)
|
||||
return jsonify({
|
||||
"code": 0,
|
||||
"msg": str(e),
|
||||
"data": None
|
||||
}), 500
|
||||
|
||||
|
||||
@polymarket_bp.route("/markets/<market_id>/opportunities", methods=["GET"])
|
||||
@login_required
|
||||
def get_market_opportunities(market_id: str):
|
||||
"""获取基于该预测市场的资产交易机会（暂时返回空，后续可扩展）"""
|
||||
try:
|
||||
# 暂时返回空列表，可以后续实现基于预测市场的资产推荐
|
||||
opportunities = []
|
||||
|
||||
return jsonify({
|
||||
"code": 1,
|
||||
"msg": "success",
|
||||
"data": opportunities
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"get_market_opportunities failed: {e}", exc_info=True)
|
||||
return jsonify({
|
||||
"code": 0,
|
||||
"msg": str(e),
|
||||
"data": None
|
||||
}), 500
|
||||
|
||||
|
||||
@polymarket_bp.route("/recommendations", methods=["GET"])
|
||||
@login_required
|
||||
def get_recommendations():
|
||||
"""
|
||||
获取AI推荐的高价值预测市场
|
||||
|
||||
Query params:
|
||||
limit: 数量 (default: 10)
|
||||
"""
|
||||
try:
|
||||
limit = int(request.args.get("limit", 10))
|
||||
|
||||
# 获取所有活跃市场
|
||||
all_markets = polymarket_source.get_trending_markets(limit=100)
|
||||
|
||||
# 从数据库读取缓存的AI分析结果（30分钟内，按机会评分排序）
|
||||
recommendations = []
|
||||
try:
|
||||
with get_db_connection() as db:
|
||||
cur = db.cursor()
|
||||
cache_cutoff = datetime.now() - timedelta(minutes=30)
|
||||
market_ids = [m.get('market_id') for m in all_markets if m.get('market_id')]
|
||||
|
||||
if market_ids:
|
||||
placeholders = ','.join(['%s'] * len(market_ids))
|
||||
cur.execute(f"""
|
||||
SELECT a.market_id, a.opportunity_score, a.recommendation,
|
||||
a.confidence_score, a.reasoning, a.key_factors,
|
||||
m.question, m.current_probability, m.volume_24h, m.category
|
||||
FROM qd_polymarket_ai_analysis a
|
||||
JOIN qd_polymarket_markets m ON a.market_id = m.market_id
|
||||
WHERE a.market_id IN ({placeholders})
|
||||
AND a.user_id IS NULL
|
||||
AND a.created_at > %s
|
||||
AND a.opportunity_score > 70
|
||||
ORDER BY a.opportunity_score DESC
|
||||
LIMIT %s
|
||||
""", market_ids + [cache_cutoff, limit])
|
||||
|
||||
rows = cur.fetchall()
|
||||
cur.close()
|
||||
|
||||
for row in rows:
|
||||
key_factors_raw = row.get('key_factors')
|
||||
key_factors = []
|
||||
if key_factors_raw:
|
||||
try:
|
||||
if isinstance(key_factors_raw, str):
|
||||
key_factors = json.loads(key_factors_raw)
|
||||
else:
|
||||
key_factors = key_factors_raw if isinstance(key_factors_raw, list) else []
|
||||
except:
|
||||
key_factors = []
|
||||
|
||||
recommendations.append({
|
||||
"market_id": row.get('market_id'),
|
||||
"question": row.get('question'),
|
||||
"current_probability": float(row.get('current_probability') or 0),
|
||||
"volume_24h": float(row.get('volume_24h') or 0),
|
||||
"category": row.get('category'),
|
||||
"ai_analysis": {
|
||||
"opportunity_score": float(row.get('opportunity_score') or 0),
|
||||
"recommendation": row.get('recommendation') or 'HOLD',
|
||||
"confidence_score": float(row.get('confidence_score') or 0),
|
||||
"reasoning": row.get('reasoning') or '',
|
||||
"key_factors": key_factors
|
||||
}
|
||||
})
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to load recommendations: {e}")
|
||||
|
||||
# 如果没有缓存结果，返回空列表（等待后台任务分析）
|
||||
|
||||
return jsonify({
|
||||
"code": 1,
|
||||
"msg": "success",
|
||||
"data": recommendations[:limit]
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"get_recommendations failed: {e}", exc_info=True)
|
||||
return jsonify({
|
||||
"code": 0,
|
||||
"msg": str(e),
|
||||
"data": None
|
||||
}), 500
|
||||
|
||||
|
||||
@polymarket_bp.route("/search", methods=["GET"])
|
||||
@login_required
|
||||
def search_markets():
|
||||
"""搜索预测市场"""
|
||||
try:
|
||||
keyword = request.args.get("q", "").strip()
|
||||
if not keyword:
|
||||
return jsonify({
|
||||
"code": 0,
|
||||
"msg": "Keyword required",
|
||||
"data": None
|
||||
}), 400
|
||||
|
||||
limit = int(request.args.get("limit", 20))
|
||||
|
||||
markets = polymarket_source.search_markets(keyword, limit)
|
||||
|
||||
return jsonify({
|
||||
"code": 1,
|
||||
"msg": "success",
|
||||
"data": markets
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"search_markets failed: {e}", exc_info=True)
|
||||
return jsonify({
|
||||
"code": 0,
|
||||
"msg": str(e),
|
||||
"data": None
|
||||
}), 500
|
||||
Reference in New Issue
Block a user