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DinQuant/backend_api_python/app/routes/fast_analysis.py
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dinger 9473e50d59 feat: AI 即时分析计费/共识/校准与 Docker 前端构建
- 即时分析:先扣费、防重入(429)、失败退款;记忆库与离线校准 worker
- 多周期共识、客观分与设置项 AI_ANALYSIS_CONSENSUS_TIMEFRAMES
- Docker:前端多阶段构建(QuantDinger-Vue-src)、根目录 .dockerignore、compose 调整
- 同步 frontend/dist 静态资源

Made-with: Cursor
2026-03-20 21:08:26 +08:00

592 lines
20 KiB
Python

"""
Fast Analysis API Routes
New high-performance analysis endpoints that replace the slow multi-agent system.
"""
from flask import Blueprint, request, jsonify, g
import threading
import time
from app.utils.auth import login_required
from app.utils.logger import get_logger
from app.services.fast_analysis import get_fast_analysis_service
from app.services.analysis_memory import get_analysis_memory
from app.services.billing_service import get_billing_service
logger = get_logger(__name__)
fast_analysis_bp = Blueprint('fast_analysis', __name__)
# In-memory in-flight guard to avoid duplicate analysis charges caused by rapid repeated clicks.
_analysis_inflight_lock = threading.Lock()
_analysis_inflight = {} # key -> expire_ts
def _build_inflight_key(user_id: int, market: str, symbol: str, timeframe: str) -> str:
return f"{int(user_id)}|{str(market or '').strip().upper()}|{str(symbol or '').strip().upper()}|{str(timeframe or '').strip().upper()}"
def _acquire_inflight(key: str, ttl_sec: int = 90) -> bool:
now = time.time()
with _analysis_inflight_lock:
# Cleanup stale entries
stale = [k for k, exp in _analysis_inflight.items() if float(exp) <= now]
for k in stale[:1024]:
_analysis_inflight.pop(k, None)
if key in _analysis_inflight and float(_analysis_inflight.get(key) or 0) > now:
return False
_analysis_inflight[key] = now + int(ttl_sec)
return True
def _release_inflight(key: str):
with _analysis_inflight_lock:
_analysis_inflight.pop(key, None)
@fast_analysis_bp.route('/analyze', methods=['POST'])
@login_required
def analyze():
"""
Fast AI analysis for any symbol.
POST /api/fast-analysis/analyze
Body: {
"market": "Crypto" | "USStock" | "Forex" | ...,
"symbol": "BTC/USDT" | "AAPL" | ...,
"language": "zh-CN" | "en-US" (optional),
"model": "openai/gpt-4o" (optional),
"timeframe": "1D" (optional)
}
Returns:
Fast analysis result with actionable recommendations.
"""
try:
data = request.get_json() or {}
market = (data.get('market') or '').strip()
symbol = (data.get('symbol') or '').strip()
language = data.get('language', 'en-US')
model = data.get('model')
timeframe = data.get('timeframe', '1D')
if not market or not symbol:
return jsonify({
'code': 0,
'msg': 'market and symbol are required',
'data': None
}), 400
# Get current user's ID to associate analysis with user
user_id = getattr(g, 'user_id', None)
if not user_id:
return jsonify({'code': 0, 'msg': 'Unauthorized', 'data': None}), 401
inflight_key = _build_inflight_key(user_id, market, symbol, timeframe)
if not _acquire_inflight(inflight_key, ttl_sec=90):
return jsonify({
'code': 0,
'msg': 'Analysis already in progress for this symbol/timeframe. Please wait.',
'data': {'in_progress': True}
}), 429
# Billing / credits (best-effort, consistent with polymarket deep analysis)
credits_charged = 0
remaining_credits = None
billing_consumed = False
billing = None
try:
billing = get_billing_service()
if billing.is_billing_enabled():
credits_charged = int(billing.get_feature_cost('ai_analysis') or 0)
if credits_charged > 0:
ok, msg = billing.check_and_consume(
user_id=int(user_id),
feature='ai_analysis',
reference_id=f"fast_analysis_{market}:{symbol}:{timeframe}"
)
if not ok:
# Standardize insufficient credits message
if str(msg or "").startswith('insufficient_credits'):
# Format: insufficient_credits:<current>:<cost>
parts = str(msg).split(':')
cur = float(parts[1]) if len(parts) >= 2 else 0.0
req = float(parts[2]) if len(parts) >= 3 else float(credits_charged)
return jsonify({
'code': 0,
'msg': 'Insufficient credits',
'data': {
'required': req,
'current': cur,
'shortage': max(0.0, req - cur),
}
}), 400
return jsonify({'code': 0, 'msg': f'Failed to deduct credits: {msg}', 'data': None}), 500
billing_consumed = True
# Query remaining credits after successful consumption
try:
remaining_credits = float(billing.get_user_credits(int(user_id)))
except Exception:
remaining_credits = None
except Exception as e:
# Billing failure should not crash analysis by default, but should be visible in logs.
logger.warning(f"Billing check failed (skipped): {e}", exc_info=True)
service = get_fast_analysis_service()
result = service.analyze(
market=market,
symbol=symbol,
language=language,
model=model,
timeframe=timeframe,
user_id=user_id
)
if result.get('error'):
# Best-effort refund if we already charged but analysis failed.
if billing_consumed and billing and credits_charged > 0:
try:
billing.add_credits(
user_id=int(user_id),
amount=int(credits_charged),
action='refund',
remark=f'Auto refund: fast-analysis failed ({market}:{symbol}:{timeframe})'
)
remaining_credits = float(billing.get_user_credits(int(user_id)))
except Exception as re:
logger.error(f"Auto refund failed: {re}", exc_info=True)
return jsonify({
'code': 0,
'msg': result['error'],
'data': result
}), 500
# memory_id is already set in service.analyze() -> _store_analysis_memory()
# No need to store again here (would create duplicates)
return jsonify({
'code': 1,
'msg': 'success',
'data': {
**(result or {}),
'credits_charged': credits_charged,
'remaining_credits': remaining_credits,
}
})
except Exception as e:
# Best-effort refund on unexpected error after charge.
try:
if 'billing_consumed' in locals() and billing_consumed and 'billing' in locals() and billing and credits_charged > 0 and 'user_id' in locals() and user_id:
billing.add_credits(
user_id=int(user_id),
amount=int(credits_charged),
action='refund',
remark=f'Auto refund: fast-analysis exception ({market}:{symbol}:{timeframe})'
)
except Exception:
pass
logger.error(f"Fast analysis API failed: {e}", exc_info=True)
return jsonify({
'code': 0,
'msg': str(e),
'data': None
}), 500
finally:
try:
if 'inflight_key' in locals() and inflight_key:
_release_inflight(inflight_key)
except Exception:
pass
@fast_analysis_bp.route('/analyze-legacy', methods=['POST'])
@login_required
def analyze_legacy():
"""
Fast analysis with legacy format output.
For backward compatibility with existing frontend.
POST /api/fast-analysis/analyze-legacy
Body: Same as /analyze
Returns:
Result in multi-agent format for frontend compatibility.
"""
try:
data = request.get_json() or {}
market = (data.get('market') or '').strip()
symbol = (data.get('symbol') or '').strip()
language = data.get('language', 'en-US')
model = data.get('model')
timeframe = data.get('timeframe', '1D')
if not market or not symbol:
return jsonify({
'code': 0,
'msg': 'market and symbol are required',
'data': None
}), 400
# Billing / credits (same behavior as /analyze)
user_id = getattr(g, 'user_id', None)
if not user_id:
return jsonify({'code': 0, 'msg': 'Unauthorized', 'data': None}), 401
inflight_key = _build_inflight_key(user_id, market, symbol, timeframe)
if not _acquire_inflight(inflight_key, ttl_sec=90):
return jsonify({
'code': 0,
'msg': 'Analysis already in progress for this symbol/timeframe. Please wait.',
'data': {'in_progress': True}
}), 429
credits_charged = 0
remaining_credits = None
billing_consumed = False
billing = None
try:
billing = get_billing_service()
if billing.is_billing_enabled():
credits_charged = int(billing.get_feature_cost('ai_analysis') or 0)
if credits_charged > 0:
ok, msg = billing.check_and_consume(
user_id=int(user_id),
feature='ai_analysis',
reference_id=f"fast_analysis_legacy_{market}:{symbol}:{timeframe}"
)
if not ok:
if str(msg or "").startswith('insufficient_credits'):
parts = str(msg).split(':')
cur = float(parts[1]) if len(parts) >= 2 else 0.0
req = float(parts[2]) if len(parts) >= 3 else float(credits_charged)
return jsonify({
'code': 0,
'msg': 'Insufficient credits',
'data': {
'required': req,
'current': cur,
'shortage': max(0.0, req - cur),
}
}), 400
return jsonify({'code': 0, 'msg': f'Failed to deduct credits: {msg}', 'data': None}), 500
billing_consumed = True
try:
remaining_credits = float(billing.get_user_credits(int(user_id)))
except Exception:
remaining_credits = None
except Exception as e:
logger.warning(f"Billing check failed (skipped): {e}", exc_info=True)
service = get_fast_analysis_service()
result = service.analyze_legacy_format(
market=market,
symbol=symbol,
language=language,
model=model,
timeframe=timeframe
)
if result.get('error'):
if billing_consumed and billing and credits_charged > 0:
try:
billing.add_credits(
user_id=int(user_id),
amount=int(credits_charged),
action='refund',
remark=f'Auto refund: fast-analysis-legacy failed ({market}:{symbol}:{timeframe})'
)
remaining_credits = float(billing.get_user_credits(int(user_id)))
except Exception as re:
logger.error(f"Auto refund failed (legacy): {re}", exc_info=True)
return jsonify({
'code': 0,
'msg': result['error'],
'data': result
}), 500
return jsonify({
'code': 1,
'msg': 'success',
'data': {
**(result or {}),
'credits_charged': credits_charged,
'remaining_credits': remaining_credits,
}
})
except Exception as e:
try:
if 'billing_consumed' in locals() and billing_consumed and 'billing' in locals() and billing and credits_charged > 0 and 'user_id' in locals() and user_id:
billing.add_credits(
user_id=int(user_id),
amount=int(credits_charged),
action='refund',
remark=f'Auto refund: fast-analysis-legacy exception ({market}:{symbol}:{timeframe})'
)
except Exception:
pass
logger.error(f"Fast analysis legacy API failed: {e}", exc_info=True)
return jsonify({
'code': 0,
'msg': str(e),
'data': None
}), 500
finally:
try:
if 'inflight_key' in locals() and inflight_key:
_release_inflight(inflight_key)
except Exception:
pass
@fast_analysis_bp.route('/history', methods=['GET'])
@login_required
def get_history():
"""
Get analysis history for a symbol.
GET /api/fast-analysis/history?market=Crypto&symbol=BTC/USDT&days=7&limit=10
"""
try:
market = request.args.get('market', '').strip()
symbol = request.args.get('symbol', '').strip()
days = int(request.args.get('days', 7))
limit = min(int(request.args.get('limit', 10)), 50)
if not market or not symbol:
return jsonify({
'code': 0,
'msg': 'market and symbol are required',
'data': None
}), 400
memory = get_analysis_memory()
history = memory.get_recent(market, symbol, days, limit)
return jsonify({
'code': 1,
'msg': 'success',
'data': {
'items': history,
'total': len(history)
}
})
except Exception as e:
logger.error(f"Get history failed: {e}")
return jsonify({
'code': 0,
'msg': str(e),
'data': None
}), 500
@fast_analysis_bp.route('/history/all', methods=['GET'])
@login_required
def get_all_history():
"""
Get all analysis history with pagination.
GET /api/fast-analysis/history/all?page=1&pagesize=20
"""
try:
page = int(request.args.get('page', 1))
pagesize = min(int(request.args.get('pagesize', 20)), 50)
# Get current user's ID to filter history
user_id = getattr(g, 'user_id', None)
memory = get_analysis_memory()
result = memory.get_all_history(user_id=user_id, page=page, page_size=pagesize)
return jsonify({
'code': 1,
'msg': 'success',
'data': {
'list': result['items'],
'total': result['total'],
'page': result['page'],
'pagesize': result['page_size']
}
})
except Exception as e:
logger.error(f"Get all history failed: {e}")
return jsonify({
'code': 0,
'msg': str(e),
'data': None
}), 500
@fast_analysis_bp.route('/history/<int:memory_id>', methods=['DELETE'])
@login_required
def delete_history(memory_id: int):
"""
Delete a history record.
DELETE /api/fast-analysis/history/123
"""
try:
# Get current user's ID to ensure they can only delete their own records
user_id = getattr(g, 'user_id', None)
memory = get_analysis_memory()
success = memory.delete_history(memory_id, user_id=user_id)
if success:
return jsonify({
'code': 1,
'msg': 'Deleted successfully',
'data': None
})
else:
return jsonify({
'code': 0,
'msg': 'Record not found or no permission',
'data': None
}), 404
except Exception as e:
logger.error(f"Delete history failed: {e}")
return jsonify({
'code': 0,
'msg': str(e),
'data': None
}), 500
@fast_analysis_bp.route('/feedback', methods=['POST'])
@login_required
def submit_feedback():
"""
Submit user feedback on an analysis.
POST /api/fast-analysis/feedback
Body: {
"memory_id": 123,
"feedback": "helpful" | "not_helpful" | "accurate" | "inaccurate"
}
"""
try:
data = request.get_json() or {}
memory_id = int(data.get('memory_id', 0))
feedback = (data.get('feedback') or '').strip()
if not memory_id or not feedback:
return jsonify({
'code': 0,
'msg': 'memory_id and feedback are required',
'data': None
}), 400
valid_feedback = ['helpful', 'not_helpful', 'accurate', 'inaccurate']
if feedback not in valid_feedback:
return jsonify({
'code': 0,
'msg': f'feedback must be one of: {valid_feedback}',
'data': None
}), 400
memory = get_analysis_memory()
success = memory.record_feedback(memory_id, feedback)
return jsonify({
'code': 1 if success else 0,
'msg': 'success' if success else 'failed',
'data': None
})
except Exception as e:
logger.error(f"Submit feedback failed: {e}")
return jsonify({
'code': 0,
'msg': str(e),
'data': None
}), 500
@fast_analysis_bp.route('/performance', methods=['GET'])
@login_required
def get_performance():
"""
Get AI analysis performance statistics.
GET /api/fast-analysis/performance?market=Crypto&symbol=BTC/USDT&days=30
"""
try:
market = request.args.get('market', '').strip() or None
symbol = request.args.get('symbol', '').strip() or None
days = int(request.args.get('days', 30))
memory = get_analysis_memory()
stats = memory.get_performance_stats(market, symbol, days)
return jsonify({
'code': 1,
'msg': 'success',
'data': stats
})
except Exception as e:
logger.error(f"Get performance failed: {e}")
return jsonify({
'code': 0,
'msg': str(e),
'data': None
}), 500
@fast_analysis_bp.route('/similar-patterns', methods=['GET'])
@login_required
def get_similar_patterns():
"""
Get similar historical patterns for current market conditions.
GET /api/fast-analysis/similar-patterns?market=Crypto&symbol=BTC/USDT
"""
try:
market = request.args.get('market', '').strip()
symbol = request.args.get('symbol', '').strip()
if not market or not symbol:
return jsonify({
'code': 0,
'msg': 'market and symbol are required',
'data': None
}), 400
# Get current indicators
service = get_fast_analysis_service()
data = service._collect_market_data(market, symbol)
indicators = data.get('indicators', {})
# Find similar patterns
memory = get_analysis_memory()
patterns = memory.get_similar_patterns(market, symbol, indicators)
return jsonify({
'code': 1,
'msg': 'success',
'data': {
'patterns': patterns,
'current_indicators': {
'rsi': indicators.get('rsi', {}).get('value'),
'macd_signal': indicators.get('macd', {}).get('signal'),
'trend': indicators.get('moving_averages', {}).get('trend'),
}
}
})
except Exception as e:
logger.error(f"Get similar patterns failed: {e}")
return jsonify({
'code': 0,
'msg': str(e),
'data': None
}), 500