"""
特征提取示例

使用 Agent 框架 + Prompt loader + 多模态支持
"""

import os
import sys
import asyncio
from pathlib import Path

# 添加项目根目录到 Python 路径
sys.path.insert(0, str(Path(__file__).parent.parent.parent))

from dotenv import load_dotenv
load_dotenv()

from agent.prompts import SimplePrompt
from agent.runner import AgentRunner
from agent.llm.providers.gemini import create_gemini_llm_call


async def main():
    # 路径配置
    base_dir = Path(__file__).parent
    prompt_path = base_dir / "test.prompt"
    feature_md_path = base_dir / "input_1" / "feature.md"
    image_path = base_dir / "input_1" / "image.png"
    output_dir = base_dir / "output_1"
    output_dir.mkdir(exist_ok=True)

    print("=" * 60)
    print("特征提取任务")
    print("=" * 60)
    print()

    # 1. 加载 prompt
    print("1. 加载 prompt...")
    prompt = SimplePrompt(prompt_path)

    # 2. 读取特征描述
    print("2. 读取特征描述...")
    with open(feature_md_path, 'r', encoding='utf-8') as f:
        feature_text = f.read()

    # 3. 构建多模态消息
    print("3. 构建多模态消息（文本 + 图片）...")
    messages = prompt.build_messages(
        text=feature_text,
        images=image_path  # 框架自动处理图片
    )

    print(f"   - 消息数量: {len(messages)}")
    print(f"   - 图片: {image_path.name}")

    # 4. 创建 Agent Runner
    print("4. 创建 Agent Runner...")
    runner = AgentRunner(
        llm_call=create_gemini_llm_call()
    )

    # 5. 调用 Agent
    print(f"5. 调用模型: {prompt.config.get('model', 'gemini-2.5-flash')}...")
    print()

    result = await runner.call(
        messages=messages,
        model=prompt.config.get('model', 'gemini-2.5-flash'),
        temperature=float(prompt.config.get('temperature', 0.3)),
        trace=False  # 暂不记录 trace
    )

    # 6. 输出结果
    print("=" * 60)
    print("模型响应:")
    print("=" * 60)
    print(result.reply)
    print("=" * 60)
    print()

    # 7. 保存结果
    output_file = output_dir / "result.txt"
    with open(output_file, 'w', encoding='utf-8') as f:
        f.write(result.reply)

    print(f"✓ 结果已保存到: {output_file}")
    print()

    # 8. 打印统计信息
    print("统计信息:")
    if result.tokens:
        print(f"  输入 tokens: {result.tokens.get('prompt', 0)}")
        print(f"  输出 tokens: {result.tokens.get('completion', 0)}")
    print(f"  费用: ${result.cost:.4f}")


if __name__ == "__main__":
    asyncio.run(main())