Agent/run_search_agent.py

"""
Search Agent 统一入口

简化为薄壳，所有逻辑委托给 application 层。
"""

from __future__ import annotations

import asyncio
import logging
import os
from uuid import uuid4

from dotenv import load_dotenv

from src.config.settings import get_config
from src.application import ApplicationRunner
from src.harness.search_agent import (
    finalize_search_agent_log,
    log_environment_profile,
    load_environment_profile,
    print_run_plan,
    setup_search_agent_logging,
    validate_prerequisites,
)

load_dotenv()
setup_search_agent_logging()
logging.getLogger("agent").setLevel(logging.CRITICAL)
logger = logging.getLogger(__name__)


async def main() -> None:
    """主入口"""
    # 前置检查
    validate_prerequisites()

    # 加载配置
    config = get_config()
    environment = load_environment_profile()
    log_environment_profile(environment)

    # 读取参数
    query = os.getenv("PIPELINE_QUERY", "当谈到毛主席的生平、丰功伟绩、伟人伟绩、老年人会关注什么？")
    demand_id = os.getenv("PIPELINE_DEMAND_ID", "1")
    trace_id = str(uuid4())

    logger.info("Trace ID: %s", trace_id)

    # 打印运行计划
    from src.application.runner import AgentBudget
    budget = AgentBudget.from_config(config)
    budget.validate()

    run_plan = print_run_plan(query=query, demand_id=demand_id, budget=budget, trace_id=trace_id)
    run_plan["environment"] = {
        "env_name": environment.env_name,
        "use_db_policy": environment.use_db_policy,
        "strategy_source": environment.strategy_source,
    }

    # 执行
    runner = ApplicationRunner(config)
    summary = await runner.run(
        query=query,
        demand_id=demand_id,
        trace_id=trace_id,
        use_db_policy=environment.use_db_policy,
        policy_override=environment.strategy_override,
    )

    # 输出摘要
    summary.log()
    finalize_search_agent_log(trace_id)

    # 自动触发知识总结
    if os.getenv("ENABLE_KNOWLEDGE_SUMMARY", "false").lower() == "true":
        try:
            from agent.llm.openrouter import openrouter_llm_call
            from src.knowledge import trigger_knowledge_summary
            logger.info("触发知识总结...")
            await trigger_knowledge_summary(llm_call=openrouter_llm_call)
        except Exception as exc:
            logger.warning("知识总结失败: %s", exc)

    if not summary.success:
        raise SystemExit(1)


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