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# -*- coding: utf-8 -*-
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"""
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===================================
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A股自选股智能分析系统 - 环境验证测试
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===================================
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用于验证 .env 配置是否正确，包括：
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1. 配置加载测试
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2. 数据库查看
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3. 数据源测试
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4. LLM 调用测试
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5. 通知推送测试
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使用方法：
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python test_env.py # 运行所有测试
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python test_env.py --db # 仅查看数据库
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python test_env.py --llm # 仅测试 LLM
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python test_env.py --fetch # 仅测试数据获取
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python test_env.py --notify # 仅测试通知
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"""
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import os
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os.environ["http_proxy"] = "http://127.0.0.1:10809"
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os.environ["https_proxy"] = "http://127.0.0.1:10809"
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import argparse
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import logging
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import sys
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from datetime import datetime, date, timedelta
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from typing import Optional
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# 配置日志
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s | %(levelname)-8s | %(message)s',
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datefmt='%H:%M:%S'
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)
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logger = logging.getLogger(__name__)
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def print_header(title: str):
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"""打印标题"""
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print("\n" + "=" * 60)
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print(f" {title}")
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print("=" * 60)
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def print_section(title: str):
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"""打印小节"""
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print(f"\n--- {title} ---")
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def test_config():
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"""测试配置加载"""
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print_header("1. 配置加载测试")
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from src.config import get_config
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config = get_config()
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print_section("基础配置")
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print(f" 股票列表: {config.stock_list}")
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print(f" 数据库路径: {config.database_path}")
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print(f" 最大并发数: {config.max_workers}")
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print(f" 调试模式: {config.debug}")
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print_section("API 配置")
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print(f" Tushare Token: {'已配置 ✓' if config.tushare_token else '未配置 ✗'}")
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if config.tushare_token:
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print(f" Token 前8位: {config.tushare_token[:8]}...")
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print(f" Gemini API Key: {'已配置 ✓' if config.gemini_api_key else '未配置 ✗'}")
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if config.gemini_api_key:
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print(f" Key 前8位: {config.gemini_api_key[:8]}...")
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print(f" Gemini 主模型: {config.gemini_model}")
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print(f" Gemini 备选模型: {config.gemini_model_fallback}")
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print(f" 企业微信 Webhook: {'已配置 ✓' if config.wechat_webhook_url else '未配置 ✗'}")
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print_section("配置验证")
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warnings = config.validate()
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if warnings:
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for w in warnings:
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print(f" ⚠ {w}")
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else:
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print(" ✓ 所有配置项验证通过")
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return True
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def view_database():
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"""查看数据库内容"""
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print_header("2. 数据库内容查看")
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from src.storage import get_db
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from sqlalchemy import text
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db = get_db()
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print_section("数据库连接")
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print(f" ✓ 连接成功")
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# 使用独立的 session 查询
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session = db.get_session()
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try:
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# 统计信息
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result = session.execute(text("""
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SELECT
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code,
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COUNT(*) as count,
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MIN(date) as min_date,
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MAX(date) as max_date,
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data_source
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FROM stock_daily
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GROUP BY code
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ORDER BY code
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"""))
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stocks = result.fetchall()
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print_section(f"已存储股票数据 (共 {len(stocks)} 只)")
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if stocks:
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print(f" {'代码':<10} {'记录数':<8} {'起始日期':<12} {'最新日期':<12} {'数据源'}")
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print(" " + "-" * 60)
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for row in stocks:
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print(f" {row[0]:<10} {row[1]:<8} {row[2]!s:<12} {row[3]!s:<12} {row[4] or 'Unknown'}")
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else:
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print(" 暂无数据")
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# 查询今日数据
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today = date.today()
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result = session.execute(text("""
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SELECT code, date, open, high, low, close, pct_chg, volume, ma5, ma10, ma20, volume_ratio
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FROM stock_daily
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WHERE date = :today
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ORDER BY code
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"""), {"today": today})
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today_data = result.fetchall()
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print_section(f"今日数据 ({today})")
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if today_data:
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for row in today_data:
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code, dt, open_, high, low, close, pct_chg, volume, ma5, ma10, ma20, vol_ratio = row
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print(f"\n 【{code}】")
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print(f" 开盘: {open_:.2f} 最高: {high:.2f} 最低: {low:.2f} 收盘: {close:.2f}")
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print(f" 涨跌幅: {pct_chg:.2f}% 成交量: {volume/10000:.2f}万股")
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print(f" MA5: {ma5:.2f} MA10: {ma10:.2f} MA20: {ma20:.2f} 量比: {vol_ratio:.2f}")
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else:
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print(" 今日暂无数据")
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# 查询最近10条数据
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result = session.execute(text("""
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SELECT code, date, close, pct_chg, volume, data_source
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FROM stock_daily
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ORDER BY date DESC, code
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LIMIT 10
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"""))
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recent = result.fetchall()
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print_section("最近10条记录")
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if recent:
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print(f" {'代码':<10} {'日期':<12} {'收盘':<10} {'涨跌%':<8} {'成交量':<15} {'来源'}")
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print(" " + "-" * 70)
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for row in recent:
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vol_str = f"{row[4]/10000:.2f}万" if row[4] else "N/A"
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print(f" {row[0]:<10} {row[1]!s:<12} {row[2]:<10.2f} {row[3]:<8.2f} {vol_str:<15} {row[5] or 'Unknown'}")
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finally:
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session.close()
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return True
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def test_data_fetch(stock_code: str = "600519"):
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"""测试数据获取"""
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print_header("3. 数据获取测试")
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from data_provider import DataFetcherManager
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manager = DataFetcherManager()
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print_section("数据源列表")
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for i, name in enumerate(manager.available_fetchers, 1):
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print(f" {i}. {name}")
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print_section(f"获取 {stock_code} 数据")
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print(f" 正在获取（可能需要几秒钟）...")
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try:
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df, source = manager.get_daily_data(stock_code, days=5)
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print(f" ✓ 获取成功")
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print(f" 数据源: {source}")
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print(f" 记录数: {len(df)}")
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print_section("数据预览（最近5条）")
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if not df.empty:
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preview_cols = ['date', 'open', 'high', 'low', 'close', 'pct_chg', 'volume']
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existing_cols = [c for c in preview_cols if c in df.columns]
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print(df[existing_cols].tail().to_string(index=False))
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return True
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except Exception as e:
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print(f" ✗ 获取失败: {e}")
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return False
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def test_llm():
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"""测试 LLM 调用"""
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print_header("4. LLM (Gemini) 调用测试")
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from src.analyzer import GeminiAnalyzer
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from src.config import get_config
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import time
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config = get_config()
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print_section("模型配置")
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print(f" 主模型: {config.gemini_model}")
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print(f" 备选模型: {config.gemini_model_fallback}")
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# 检查网络连接
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print_section("网络连接检查")
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try:
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import socket
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socket.setdefaulttimeout(10)
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socket.socket(socket.AF_INET, socket.SOCK_STREAM).connect(("generativelanguage.googleapis.com", 443))
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print(f" ✓ 可以连接到 Google API 服务器")
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except Exception as e:
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print(f" ✗ 无法连接到 Google API 服务器: {e}")
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print(f" 提示: 请检查网络连接或配置代理")
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print(f" 提示: 可以设置环境变量 HTTPS_PROXY=http://your-proxy:port")
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return False
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analyzer = GeminiAnalyzer()
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print_section("模型初始化")
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if analyzer.is_available():
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print(f" ✓ 模型初始化成功")
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else:
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print(f" ✗ 模型初始化失败（请检查 API Key）")
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return False
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# 构造测试上下文
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test_context = {
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'code': '600519',
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'date': date.today().isoformat(),
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'today': {
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'open': 1420.0,
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'high': 1435.0,
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'low': 1415.0,
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'close': 1428.0,
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'volume': 5000000,
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'amount': 7140000000,
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'pct_chg': 0.56,
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'ma5': 1425.0,
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'ma10': 1418.0,
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'ma20': 1410.0,
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'volume_ratio': 1.1,
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},
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'ma_status': '多头排列 📈',
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'volume_change_ratio': 1.05,
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'price_change_ratio': 0.56,
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}
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print_section("发送测试请求")
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print(f" 测试股票: 贵州茅台 (600519)")
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print(f" 正在调用 Gemini API（超时: 60秒）...")
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start_time = time.time()
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try:
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result = analyzer.analyze(test_context)
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elapsed = time.time() - start_time
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print(f"\n ✓ API 调用成功 (耗时: {elapsed:.2f}秒)")
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print_section("分析结果")
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print(f" 情绪评分: {result.sentiment_score}/100")
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print(f" 趋势预测: {result.trend_prediction}")
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print(f" 操作建议: {result.operation_advice}")
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print(f" 技术分析: {result.technical_analysis[:80]}..." if len(result.technical_analysis) > 80 else f" 技术分析: {result.technical_analysis}")
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print(f" 消息面: {result.news_summary[:80]}..." if len(result.news_summary) > 80 else f" 消息面: {result.news_summary}")
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print(f" 综合摘要: {result.analysis_summary}")
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if not result.success:
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print(f"\n ⚠ 注意: {result.error_message}")
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return result.success
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except Exception as e:
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elapsed = time.time() - start_time
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print(f"\n ✗ API 调用失败 (耗时: {elapsed:.2f}秒)")
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print(f" 错误: {e}")
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# 提供更详细的错误提示
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error_str = str(e).lower()
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if 'timeout' in error_str or 'unavailable' in error_str:
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print(f"\n 诊断: 网络超时，可能原因:")
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print(f" 1. 网络不通（需要代理访问 Google）")
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print(f" 2. API 服务暂时不可用")
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print(f" 3. 请求量过大被限流")
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elif 'invalid' in error_str or 'api key' in error_str:
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print(f"\n 诊断: API Key 可能无效")
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elif 'model' in error_str:
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print(f"\n 诊断: 模型名称可能不正确，尝试修改 .env 中的 GEMINI_MODEL")
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return False
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def test_notification():
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"""测试通知推送"""
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print_header("5. 通知推送测试")
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from src.notification import NotificationService
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from src.config import get_config
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config = get_config()
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service = NotificationService()
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print_section("配置检查")
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if service.is_available():
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print(f" ✓ 企业微信 Webhook 已配置")
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webhook_preview = config.wechat_webhook_url[:50] + "..." if len(config.wechat_webhook_url) > 50 else config.wechat_webhook_url
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print(f" URL: {webhook_preview}")
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else:
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print(f" ✗ 企业微信 Webhook 未配置")
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return False
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print_section("发送测试消息")
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test_message = f"""## 🧪 系统测试消息
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这是一条来自 **A股自选股智能分析系统** 的测试消息。
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- 测试时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
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- 测试目的: 验证企业微信 Webhook 配置
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如果您收到此消息，说明通知功能配置正确 ✓"""
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print(f" 正在发送...")
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try:
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success = service.send_to_wechat(test_message)
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if success:
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print(f" ✓ 消息发送成功，请检查企业微信")
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else:
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print(f" ✗ 消息发送失败")
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return success
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except Exception as e:
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print(f" ✗ 发送异常: {e}")
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return False
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def run_all_tests():
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"""运行所有测试"""
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print("\n" + "🚀" * 20)
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print(" A股自选股智能分析系统 - 环境验证")
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print(" " + datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
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print("🚀" * 20)
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results = {}
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# 1. 配置测试
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try:
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results['配置加载'] = test_config()
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except Exception as e:
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print(f" ✗ 配置测试失败: {e}")
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results['配置加载'] = False
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# 2. 数据库查看
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try:
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results['数据库'] = view_database()
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except Exception as e:
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print(f" ✗ 数据库测试失败: {e}")
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results['数据库'] = False
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# 3. 数据获取（跳过，避免太慢）
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# results['数据获取'] = test_data_fetch()
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# 4. LLM 测试（可选）
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# results['LLM调用'] = test_llm()
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# 汇总
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print_header("测试结果汇总")
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for name, passed in results.items():
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status = "✓ 通过" if passed else "✗ 失败"
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print(f" {status}: {name}")
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print(f"\n提示: 使用 --llm 参数单独测试 LLM 调用")
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print(f"提示: 使用 --fetch 参数单独测试数据获取")
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print(f"提示: 使用 --notify 参数单独测试通知推送")
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def query_stock_data(stock_code: str, days: int = 10):
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"""查询指定股票的数据"""
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print_header(f"查询股票数据: {stock_code}")
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from src.storage import get_db
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from sqlalchemy import text
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db = get_db()
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session = db.get_session()
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try:
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result = session.execute(text("""
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SELECT date, open, high, low, close, pct_chg, volume, amount, ma5, ma10, ma20, volume_ratio
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FROM stock_daily
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WHERE code = :code
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ORDER BY date DESC
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LIMIT :limit
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"""), {"code": stock_code, "limit": days})
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rows = result.fetchall()
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if rows:
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print(f"\n 最近 {len(rows)} 条记录:\n")
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print(f" {'日期':<12} {'开盘':<10} {'最高':<10} {'最低':<10} {'收盘':<10} {'涨跌%':<8} {'MA5':<10} {'MA10':<10} {'量比':<8}")
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print(" " + "-" * 100)
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for row in rows:
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dt, open_, high, low, close, pct_chg, vol, amt, ma5, ma10, ma20, vol_ratio = row
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print(f" {dt!s:<12} {open_:<10.2f} {high:<10.2f} {low:<10.2f} {close:<10.2f} {pct_chg:<8.2f} {ma5:<10.2f} {ma10:<10.2f} {vol_ratio:<8.2f}")
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else:
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print(f" 未找到 {stock_code} 的数据")
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finally:
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session.close()
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def main():
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parser = argparse.ArgumentParser(
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description='A股自选股智能分析系统 - 环境验证测试',
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formatter_class=argparse.RawDescriptionHelpFormatter,
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)
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parser.add_argument('--db', action='store_true', help='查看数据库内容')
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parser.add_argument('--llm', action='store_true', help='测试 LLM 调用')
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parser.add_argument('--fetch', action='store_true', help='测试数据获取')
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parser.add_argument('--notify', action='store_true', help='测试通知推送')
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parser.add_argument('--config', action='store_true', help='查看配置')
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parser.add_argument('--stock', type=str, help='查询指定股票数据，如 --stock 600519')
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parser.add_argument('--all', action='store_true', help='运行所有测试（包括 LLM）')
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args = parser.parse_args()
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# 如果没有指定任何参数，运行基础测试
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if not any([args.db, args.llm, args.fetch, args.notify, args.config, args.stock, args.all]):
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run_all_tests()
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|
|
return 0
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|
|
|
|
|
# 根据参数运行指定测试
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|
|
if args.config:
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|
test_config()
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|
|
if args.db:
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|
view_database()
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|
|
if args.stock:
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|
|
query_stock_data(args.stock)
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|
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|
|
if args.fetch:
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|
test_data_fetch()
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|
if args.llm:
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|
test_llm()
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|
|
if args.notify:
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|
test_notification()
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|
|
if args.all:
|
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|
test_config()
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|
|
view_database()
|
|
|
test_data_fetch()
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|
|
test_llm()
|
|
|
test_notification()
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|
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|
|
return 0
|
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|
|
if __name__ == "__main__":
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|
sys.exit(main())
|
