# app.py — Flask 主应用入口
from ForumEngine import start_forum_monitoring
from QueryEngine.agent import DeepSearchAgent
from InsightEngine.agent import DeepSearchAgent
from MediaEngine.agent import DeepSearchAgent

@app.route('/analyze', methods=['POST'])
def analyze():
    query = request.json['query']
    # 启动论坛监控
    start_forum_monitoring()
    # 三个 Agent 并行启动
    run_agents_parallel(query)

# MindSpider/main.py — 爬虫主程序入口
class MindSpider:
    def __init__(self):
        self.broad_topic_path = (
            self.project_root / "BroadTopicExtraction")
        self.deep_sentiment_path = (
            self.project_root / "DeepSentimentCrawling")

# InsightEngine/tools/search.py
class MediaCrawlerDB:
    # 权重定义
    W_LIKE    = 1.0
    W_COMMENT = 5.0
    W_SHARE   = 10.0  # 高价值互动
    W_VIEW    = 0.1
    W_DANMAKU = 0.5

# MediaEngine/agent.py
class DeepSearchAgent:
    def __init__(self, config=None):
        self.llm_client = self._initialize_llm()
        self.search_agency = (
            BochaMultimodalSearch(
                api_key=self.config.BOCHA_API_KEY))

# QueryEngine/agent.py
class DeepSearchAgent:
    def __init__(self, config=None):
        self.llm_client = self._initialize_llm()
        self.search_agency = TavilyNewsAgency(
            api_key=self.config.TAVILY_API_KEY)
        # 初始化搜索、反思、总结等节点
        self._initialize_nodes()

# ForumEngine/monitor.py
class LogMonitor:
    def __init__(self, log_dir="logs"):
        self.monitored_logs = {
            'insight': self.log_dir / 'insight.log',
            'media':   self.log_dir / 'media.log',
            'query':   self.log_dir / 'query.log'
        }
        self.agent_speeches_buffer = []
        self.host_speech_threshold = 5

# ForumEngine/llm_host.py
class ForumHost:
    def generate_host_speech(self, forum_logs):
        parsed = self._parse_forum_logs(forum_logs)
        system_prompt = self._build_system_prompt()
        user_prompt = self._build_user_prompt(parsed)
        response = self._call_qwen_api(
            system_prompt, user_prompt)
        return response["content"]

# InsightEngine/nodes/summary_node.py
from utils.forum_reader import (
    get_latest_host_speech,
    format_host_speech_for_prompt
)

# 在总结节点中读取主持人发言
host_speech = get_latest_host_speech()
if host_speech:
    guidance = format_host_speech_for_prompt(
        host_speech)

# 三个 Agent 共享的节点初始化模式
def _initialize_nodes(self):
    self.first_search_node = FirstSearchNode(
        self.llm_client)
    self.reflection_node = ReflectionNode(
        self.llm_client)
    self.first_summary_node = FirstSummaryNode(
        self.llm_client)
    self.reflection_summary_node = (
        ReflectionSummaryNode(self.llm_client))
    self.report_formatting_node = (
        ReportFormattingNode(self.llm_client))

# InsightEngine/nodes/summary_node.py
class FirstSummaryNode(StateMutationNode):
    """根据搜索结果生成段落首次总结"""

    def __init__(self, llm_client):
        super().__init__(llm_client,
            "FirstSummaryNode")

    def validate_input(self, input_data):
        """验证输入数据"""
        if isinstance(input_data, str):
            data = json.loads(input_data)

# ReportEngine/core/stitcher.py
class DocumentComposer:
    """Document IR 装订器"""
    def compose(self, chapters, meta):
        doc_ir = {
            "meta": meta,
            "chapters": chapters,
            "anchors": self._build_anchors(),
            "toc": self._build_toc(chapters)
        }
        return doc_ir

# ReportEngine/agent.py
class FileCountBaseline:
    def initialize_baseline(
            self, directories) -> Dict[str, int]:
        for name, path in directories.items():
            md_files = [f for f in Path(path)
                .glob("*.md")]
            self.baseline_data[name] = len(
                md_files)
        self._save_baseline()

# .env — 切换 LLM 只需改三个参数

# Insight Agent 的 LLM
INSIGHT_ENGINE_API_KEY=sk-xxx
INSIGHT_ENGINE_BASE_URL=https://api.openai.com/v1
INSIGHT_ENGINE_MODEL_NAME=gpt-4o-mini

# 换成 DeepSeek？只改这三行：
# INSIGHT_ENGINE_API_KEY=sk-deepseek
# INSIGHT_ENGINE_BASE_URL=https://api.deepseek.com
# INSIGHT_ENGINE_MODEL_NAME=deepseek-chat

# InsightEngine/tools/custom_db_tool.py
class CustomBusinessDBTool:
    """自定义业务数据库查询工具"""

    def __init__(self):
        self.connection_config = {
            'host': config.BUSINESS_DB_HOST,
            'port': config.BUSINESS_DB_PORT,
            'user': config.BUSINESS_DB_USER,
        }

    def search_business_data(
            self, query: str, table: str):
        """查询业务数据"""
        # 实现你的业务逻辑
        pass

# 情感分析配置示例
SENTIMENT_CONFIG = {
    'model_type': 'multilingual',
    'confidence_threshold': 0.8,
    'batch_size': 32,
    'max_sequence_length': 512,
}