feat: AI analysis engine refactor, dark theme polish & virtual position management
Core changes: - Refactor FastAnalysisService: single LLM multi-factor analysis replaces 7-agent pipeline; add multi-timeframe consensus, threshold calibration, confidence calibration, multi-model ensemble voting - Add RAG memory injection and reflection validation (analysis_memory + reflection worker) - Simplify billing config: remove unused strategy_run/backtest/portfolio_monitor, add ai_code_gen separate billing (different token consumption scale) - Settings hot-reload after save, no backend restart needed Frontend: - Global dark theme overhaul: pure black palette replacing blue-tinted colors across sidebar/header/dashboard/analysis/K-line/user-manage/profile/settings/billing - Fix USDT payment modal dark theme (portal rendering broke CSS selectors) - Refactor position modal: direction + quantity + entry price, remove add/reduce logic, show raw DB values on re-open, save exactly what user inputs - Fix Polymarket prediction market dark text - i18n for position modal title Backend: - Position management: one record per symbol (DELETE+INSERT replacing ON CONFLICT with side), fixes PnL showing 0 when switching long/short - MarketDataCollector data fetching optimization - portfolio_monitor scheduled monitoring improvements - env.example reorganized: common config first, advanced config last Documentation: - README architecture diagram updated to FastAnalysisService flow - Add virtual position, AI tuning config, billing items documentation - Add INDICATOR_DEFINITIONS_CN.md, FRONTEND_FAST_ANALYSIS.md Made-with: Cursor
This commit is contained in:
Dinger
@@ -5,10 +5,12 @@ Admin-only endpoints for system configuration management.
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"""
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import os
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import re
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import importlib
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from flask import Blueprint, request, jsonify
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from app.utils.logger import get_logger
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from app.utils.config_loader import clear_config_cache
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from app.utils.auth import login_required, admin_required
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from dotenv import load_dotenv
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logger = get_logger(__name__)
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@@ -17,6 +19,55 @@ settings_bp = Blueprint('settings', __name__)
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# .env 文件路径
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ENV_FILE_PATH = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(__file__))), '.env')
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def _reload_runtime_env() -> None:
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"""
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Reload .env into current process so settings take effect immediately.
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Priority keeps backend_api_python/.env over repo-root/.env.
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"""
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backend_dir = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
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root_dir = os.path.dirname(backend_dir)
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# Load root first, then backend .env to keep backend file higher priority
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load_dotenv(os.path.join(root_dir, '.env'), override=True)
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load_dotenv(os.path.join(backend_dir, '.env'), override=True)
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def _refresh_runtime_services() -> None:
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"""
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Reset singleton services so new env/config is picked up lazily
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on next request without restarting the Python process.
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"""
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# Prefer dedicated reset function where available.
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try:
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search_mod = importlib.import_module('app.services.search')
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if hasattr(search_mod, 'reset_search_service'):
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search_mod.reset_search_service()
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except Exception as e:
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logger.warning(f"reset_search_service skipped: {e}")
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# Generic singleton fields used across services.
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singleton_fields = [
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('app.services.fast_analysis', '_fast_analysis_service'),
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('app.services.billing_service', '_billing_service'),
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('app.services.security_service', '_security_service'),
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('app.services.oauth_service', '_oauth_service'),
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('app.services.user_service', '_user_service'),
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('app.services.email_service', '_email_service'),
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('app.services.community_service', '_community_service'),
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('app.services.usdt_payment_service', '_svc'),
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('app.services.usdt_payment_service', '_worker'),
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('app.services.analysis_memory', '_memory_instance'),
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]
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for module_name, field_name in singleton_fields:
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try:
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mod = importlib.import_module(module_name)
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if hasattr(mod, field_name):
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setattr(mod, field_name, None)
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except Exception as e:
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logger.warning(f"Singleton reset skipped: {module_name}.{field_name}: {e}")
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# 配置项定义（分组）- 按功能模块划分，每个配置项包含描述
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# ---------------------------------------------------------------
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# 精简原则：
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@@ -439,19 +490,75 @@ CONFIG_SCHEMA = {
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'icon': 'experiment',
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'order': 7,
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'items': [
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{
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'key': 'ENABLE_AGENT_MEMORY',
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'label': 'Enable Agent Memory',
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'type': 'boolean',
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'default': 'True',
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'description': 'Enable AI agent memory for learning from past trades'
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},
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{
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'key': 'ENABLE_REFLECTION_WORKER',
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'label': 'Enable Auto Reflection',
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'type': 'boolean',
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'default': 'False',
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'description': 'Enable background worker for automatic trade reflection'
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'description': 'Enable background worker for automatic trade reflection and calibration'
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},
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{
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'key': 'REFLECTION_WORKER_INTERVAL_SEC',
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'label': 'Reflection Interval (sec)',
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'type': 'number',
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'default': '86400',
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'description': 'Reflection worker run interval in seconds (86400 = 1 day)'
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},
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{
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'key': 'REFLECTION_MIN_AGE_DAYS',
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'label': 'Min Age for Validation (days)',
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'type': 'number',
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'default': '7',
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'description': 'Only validate analyses older than N days'
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},
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{
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'key': 'REFLECTION_VALIDATE_LIMIT',
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'label': 'Validation Batch Limit',
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'type': 'number',
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'default': '200',
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'description': 'Max records to validate per reflection cycle'
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},
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{
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'key': 'ENABLE_CONFIDENCE_CALIBRATION',
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'label': 'Enable Confidence Calibration',
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'type': 'boolean',
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'default': 'False',
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'description': 'Adjust confidence by historical accuracy in each bucket'
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},
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{
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'key': 'ENABLE_AI_ENSEMBLE',
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'label': 'Enable Multi-Model Voting',
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'type': 'boolean',
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'default': 'False',
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'description': 'Use 2-3 models and majority vote for more stable decisions'
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},
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{
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'key': 'AI_ENSEMBLE_MODELS',
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'label': 'Ensemble Models',
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'type': 'text',
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'default': 'openai/gpt-4o,openai/gpt-4o-mini',
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'description': 'Comma-separated model IDs for ensemble voting'
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},
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{
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'key': 'AI_CALIBRATION_MARKETS',
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'label': 'Calibration Markets',
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'type': 'text',
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'default': 'Crypto',
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'description': 'Comma-separated markets to run threshold calibration'
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},
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{
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'key': 'AI_CALIBRATION_LOOKBACK_DAYS',
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'label': 'Calibration Lookback (days)',
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'type': 'number',
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'default': '30',
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'description': 'Days of validated data for calibration'
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},
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{
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'key': 'AI_CALIBRATION_MIN_SAMPLES',
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'label': 'Calibration Min Samples',
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'type': 'number',
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'default': '80',
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'description': 'Minimum validated samples required for calibration'
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},
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]
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},
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@@ -661,31 +768,17 @@ CONFIG_SCHEMA = {
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},
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{
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'key': 'BILLING_COST_AI_ANALYSIS',
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'label': 'AI Analysis Cost',
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'label': 'AI Analysis Cost (per symbol)',
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'type': 'number',
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'default': '10',
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'description': 'Credits per AI analysis request'
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'description': 'Credits per symbol (instant analysis, AI filter, scheduled tasks all use this price)'
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},
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{
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'key': 'BILLING_COST_STRATEGY_RUN',
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'label': 'Strategy Run Cost',
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'key': 'BILLING_COST_AI_CODE_GEN',
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'label': 'AI Code Generation Cost',
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'type': 'number',
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'default': '5',
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'description': 'Credits per strategy start'
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},
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{
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'key': 'BILLING_COST_BACKTEST',
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'label': 'Backtest Cost',
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'type': 'number',
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'default': '3',
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'description': 'Credits per backtest run'
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},
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{
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'key': 'BILLING_COST_PORTFOLIO_MONITOR',
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'label': 'Portfolio Monitor Cost',
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'type': 'number',
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'default': '8',
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'description': 'Credits per portfolio AI monitoring run'
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'default': '30',
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'description': 'Credits per AI strategy/indicator code generation (higher token usage)'
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},
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{
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'key': 'CREDITS_REGISTER_BONUS',
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@@ -873,13 +966,19 @@ def save_settings():
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if write_env_file(current_env):
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# 清除配置缓存
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clear_config_cache()
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# 热重载运行时环境变量（无需重启进程）
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_reload_runtime_env()
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# 重置依赖配置的服务单例（下次请求自动按新配置重建）
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_refresh_runtime_services()
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return jsonify({
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'code': 1,
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'msg': 'Settings saved successfully',
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'data': {
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'updated_keys': list(updates.keys()),
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'requires_restart': True # 标记需要重启
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'requires_restart': False,
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'hot_reloaded': True,
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'services_refreshed': True
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}
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})
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else:
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