iov_ana/demo.py

"""
演示脚本 —— 创建示例数据，运行四层架构分析
"""
import os
import sys
import sqlite3
import random
from datetime import datetime, timedelta

sys.path.insert(0, os.path.dirname(__file__))

from config import DB_PATH, LLM_CONFIG
from agent import DataAnalysisAgent


def create_demo_data(db_path: str):
    """创建示例数据库：电商订单 + 用户 + 商品"""
    if os.path.exists(db_path):
        os.remove(db_path)

    conn = sqlite3.connect(db_path)
    cur = conn.cursor()

    cur.execute("""
        CREATE TABLE users (
            id INTEGER PRIMARY KEY,
            name TEXT NOT NULL,
            region TEXT NOT NULL,
            tier TEXT NOT NULL,
            created_at TEXT NOT NULL
        )
    """)

    cur.execute("""
        CREATE TABLE products (
            id INTEGER PRIMARY KEY,
            name TEXT NOT NULL,
            category TEXT NOT NULL,
            price REAL NOT NULL
        )
    """)

    cur.execute("""
        CREATE TABLE orders (
            id INTEGER PRIMARY KEY,
            user_id INTEGER NOT NULL,
            product_id INTEGER NOT NULL,
            amount REAL NOT NULL,
            quantity INTEGER NOT NULL,
            status TEXT NOT NULL,
            region TEXT NOT NULL,
            order_date TEXT NOT NULL,
            FOREIGN KEY (user_id) REFERENCES users(id),
            FOREIGN KEY (product_id) REFERENCES products(id)
        )
    """)

    regions = ["华东", "华南", "华北", "西南", "华中", "东北"]
    tiers = ["普通", "银卡", "金卡", "钻石"]
    categories = ["电子产品", "服饰", "食品", "家居", "图书", "美妆"]
    statuses = ["已完成", "已发货", "待发货", "已取消", "退款中"]

    users = []
    for i in range(1, 2001):
        reg = random.choice(regions)
        tier = random.choices(tiers, weights=[50, 25, 15, 10])[0]
        created = datetime(2024, 1, 1) + timedelta(days=random.randint(0, 400))
        users.append((i, f"用户{i}", reg, tier, created.strftime("%Y-%m-%d")))
    cur.executemany("INSERT INTO users VALUES (?, ?, ?, ?, ?)", users)

    products = []
    for i in range(1, 201):
        cat = random.choice(categories)
        price = round(random.uniform(9.9, 9999.99), 2)
        products.append((i, f"商品{i}", cat, price))
    cur.executemany("INSERT INTO products VALUES (?, ?, ?, ?)", products)

    orders = []
    for i in range(1, 50001):
        uid = random.randint(1, 2000)
        pid = random.randint(1, 200)
        qty = random.choices([1, 2, 3, 4, 5], weights=[50, 25, 15, 7, 3])[0]
        status = random.choices(statuses, weights=[60, 15, 10, 10, 5])[0]
        region = random.choices(regions, weights=[35, 25, 15, 10, 10, 5])[0]
        order_date = datetime(2025, 1, 1) + timedelta(days=random.randint(0, 440))
        cur.execute("SELECT price FROM products WHERE id = ?", (pid,))
        price = cur.fetchone()[0]
        amount = round(price * qty, 2)
        orders.append((i, uid, pid, amount, qty, status, region, order_date.strftime("%Y-%m-%d")))
    cur.executemany("INSERT INTO orders VALUES (?, ?, ?, ?, ?, ?, ?, ?)", orders)

    conn.commit()
    conn.close()
    print(f"✅ 示例数据库已创建: {db_path}")
    print(f"   - users: 2,000 条")
    print(f"   - products: 200 条")
    print(f"   - orders: 50,000 条")


def main():
    print("=" * 60)
    print("  🤖 数据分析 Agent —— 四层架构自适应分析")
    print("=" * 60)

    if not LLM_CONFIG["api_key"]:
        print("\n⚠️  未配置 LLM_API_KEY，请设置环境变量：")
        print()
        print("  # OpenAI")
        print("  export LLM_API_KEY=sk-xxx")
        print("  export LLM_BASE_URL=https://api.openai.com/v1")
        print("  export LLM_MODEL=gpt-4o")
        print()
        print("  # Ollama (本地)")
        print("  export LLM_API_KEY=ollama")
        print("  export LLM_BASE_URL=http://localhost:11434/v1")
        print("  export LLM_MODEL=qwen2.5-coder:7b")
        print()
        sys.exit(1)

    print(f"\n🔗 LLM: {LLM_CONFIG['model']} @ {LLM_CONFIG['base_url']}")

    if not os.path.exists(DB_PATH):
        create_demo_data(DB_PATH)
    else:
        print(f"\n📂 使用已有数据库: {DB_PATH}")

    # 初始化 Agent（自动加载 Schema）
    agent = DataAnalysisAgent(DB_PATH)

    print("\n" + "=" * 60)
    print("  ⬆️  AI 只看到 Schema：表结构 + 数据画像")
    print("  ⬇️  四层架构分析：规划 → 探索 → 洞察 → 报告")
    print("=" * 60)

    questions = [
        "各地区的销售表现如何？帮我全面分析一下",
        "不同商品类别的销售情况和利润贡献",
        "整体订单的完成率怎么样？有没有什么异常需要关注？",
    ]

    for q in questions:
        try:
            report = agent.analyze(q)
            print("\n" + report)
            print("\n" + "~" * 60)
        except Exception as e:
            print(f"\n❌ 分析出错: {e}")
            import traceback
            traceback.print_exc()

    # 最终审计
    print("\n📋 会话审计:")
    print(agent.get_audit())
    print("\n📋 分析历史:")
    print(agent.get_history())
    print("\n✅ 演示完成！")


if __name__ == "__main__":
    main()