knowledge-agent/tools/agent_tools.py

import os
import sys
import json
from typing import Any, Dict, List, Optional

sys.path.append(os.path.dirname(os.path.abspath(__file__)))

from utils.logging_config import get_logger
from utils.mysql_db import MysqlHelper
from indentify.indentify import ContentIdentifier
from structure import StructureProcessor

logger = get_logger('AgentTools')


class QueryDataTool:
    """查询 knowledge_crawl_content 获取 data 列表中的 crawl_data 字段"""

    @staticmethod
    def fetch_crawl_data_list(request_id: str) -> List[Dict[str, Any]]:
        sql = "SELECT * FROM knowledge_crawl_content WHERE request_id = %s ORDER BY id ASC"
        rows = MysqlHelper.get_values(sql, (request_id,))
        if not rows:
            logger.info(f"request_id={request_id} 未查询到数据，使用默认值")
            # 返回默认数据
            default_data = [{
                "request_id": request_id,
                "content_id": "1",
                "id": 1,
                "task_id": 1,
                "crawl_data": {
                    "channel": 1,
                    "channel_content_id": "684a789b000000002202a61b",
                    "content_link": "https://www.xiaohongshu.com/explore/684a789b000000002202a61b",
                    "wx_sn": None,
                    "title": "一个视频学会，5个剪辑工具，超详细教程",
                    "content_type": "video",
                    "body_text": "#剪辑教程[话题]# #剪辑[话题]# #手机剪辑[话题]# #视频制作[话题]# #视频剪辑[话题]# #自学剪辑[话题]# #原创视频[话题]# #新手小白学剪辑[话题]#",
                    "location": "未知",
                    "source_url": None,
                    "mini_program": None,
                    "topic_list": [],
                    "image_url_list": [
                        {
                            "image_type": 2,
                            "image_url": "http://rescdn.yishihui.com/pipeline/image/5be8f08a-4691-41b6-8dda-0b63cc2c1056.jpg"
                        }
                    ],
                    "video_url_list": [
                        # {
                        #     "video_url": "http://rescdn.yishihui.com/pipeline/video/9e38400e-21dc-4063-bab5-47c1667bb59d.mp4",
                        #     "video_duration": 615
                        # }
                    ],
                    "bgm_data": None,
                    "ad_info": None,
                    "is_original": False,
                    "voice_data": None,
                    "channel_account_id": "670a10ac000000001d0216ec",
                    "channel_account_name": "小伍剪辑视频",
                    "channel_account_avatar": "https://sns-avatar-qc.xhscdn.com/avatar/1040g2jo31e469dkq0e005poa22m7c5ncbtuk1g0?imageView2/2/w/80/format/jpg",
                    "item_index": None,
                    "view_count": None,
                    "play_count": None,
                    "like_count": 692,
                    "collect_count": 996,
                    "comment_count": 37,
                    "share_count": None,
                    "looking_count": None,
                    "publish_timestamp": 1749711589000,
                    "modify_timestamp": 1749711589000,
                    "update_timestamp": 1755239186502
                }
            },{
                 "request_id": request_id,
                "content_id": "2",
                "id": 2,
                "task_id": 2,
                "crawl_data": {
                    "channel": 1,
                    "channel_content_id": "684a789b000000002202a61b",
                    "content_link": "https://www.xiaohongshu.com/explore/684a789b000000002202a61b",
                    "wx_sn": None,
                    "title": "一个视频学会，5个剪辑工具，超详细教程",
                    "content_type": "video",
                    "body_text": "#剪辑教程[话题]# #剪辑[话题]# #手机剪辑[话题]# #视频制作[话题]# #视频剪辑[话题]# #自学剪辑[话题]# #原创视频[话题]# #新手小白学剪辑[话题]#",
                    "location": "未知",
                    "source_url": None,
                    "mini_program": None,
                    "topic_list": [],
                    "image_url_list": [
                        {
                            "image_type": 2,
                            "image_url": "http://rescdn.yishihui.com/pipeline/image/5be8f08a-4691-41b6-8dda-0b63cc2c1056.jpg"
                        }
                    ],
                    "video_url_list": [
                        {
                            "video_url": "http://rescdn.yishihui.com/pipeline/video/9e38400e-21dc-4063-bab5-47c1667bb59d.mp4",
                            "video_duration": 615
                        }
                    ],
                    "bgm_data": None,
                    "ad_info": None,
                    "is_original": False,
                    "voice_data": None,
                    "channel_account_id": "670a10ac000000001d0216ec",
                    "channel_account_name": "小伍剪辑视频",
                    "channel_account_avatar": "https://sns-avatar-qc.xhscdn.com/avatar/1040g2jo31e469dkq0e005poa22m7c5ncbtuk1g0?imageView2/2/w/80/format/jpg",
                    "item_index": None,
                    "view_count": None,
                    "play_count": None,
                    "like_count": 692,
                    "collect_count": 996,
                    "comment_count": 37,
                    "share_count": None,
                    "looking_count": None,
                    "publish_timestamp": 1749711589000,
                    "modify_timestamp": 1749711589000,
                    "update_timestamp": 1755239186502
                }
            }]
            return []

        results: List[Dict[str, Any]] = []
        for row in rows:
            data_cell = row
            if not data_cell:
                continue
            try:
                parsed = json.loads(data_cell) if isinstance(data_cell, (str, bytes)) else data_cell
                # logger.info(f"parsed: {parsed}")
                
                # 处理元组类型（数据库查询结果）
                if isinstance(parsed, tuple) and len(parsed) > 4:
                    # 假设第4个元素是JSON字符串
                    json_str = parsed[4]
                    content_id = parsed[1]
                    if isinstance(json_str, str):
                        try:
                            json_data = json.loads(json_str)
                            if isinstance(json_data, dict):
                                results.append({"crawl_data": json_data, "content_id": content_id, "raw": parsed})
                            elif isinstance(json_data, list):
                                for item in json_data:
                                    if isinstance(item, dict):
                                        results.append({"crawl_data": item, "content_id": content_id, "raw": parsed})
                        except json.JSONDecodeError:
                            logger.warning(f"元组中第4个元素不是有效的JSON: {json_str}")
                    else:
                        logger.warning(f"元组中第4个元素不是字符串: {type(json_str)}")
                
                # 处理列表类型
                elif isinstance(parsed, list):
                    for item in parsed:
                        if isinstance(item, dict):
                            crawl_data = item.get('crawl_data')
                            content_id = item.get('content_id')
                            if isinstance(crawl_data, (dict, list)):
                                results.append({"crawl_data": crawl_data, "content_id": content_id, "raw": item})
                            else:
                                results.append({"crawl_data": item, "content_id": content_id, "raw": item})
                
                # 处理字典类型
                elif isinstance(parsed, dict):
                    crawl_data = parsed.get('crawl_data')
                    content_id = parsed.get('content_id')
                    if isinstance(crawl_data, (dict, list)):
                        results.append({"crawl_data": crawl_data, "content_id": content_id, "raw": parsed})
                    else:
                        results.append({"crawl_data": parsed, "content_id": content_id, "raw": parsed})
                
                else:
                    logger.warning(f"data 字段非期望的数据结构: {type(parsed)}, 已跳过一行")
            except Exception as e:
                logger.error(f"解析 data JSON 失败: {e}")
        logger.info(f"request_id={request_id} 提取 crawl_data 数量: {len(results)}")
        return results


class IdentifyTool:
    """调用 indentify 内部能力，完成图像/视频识别"""

    def __init__(self) -> None:
        self.identifier = ContentIdentifier()

    def run(self, crawl_data: Dict[str, Any]) -> Dict[str, Any]:
        try:
            formatted_content = self.identifier.parse_formatted_content(crawl_data)
            recognition_result = self.identifier.process_content_recognition(formatted_content)

            title = formatted_content.get('title') or ''
            content = formatted_content.get('body_text') or ''
            channel = formatted_content.get('channel') or ''
            author = formatted_content.get('channel_account_name') or ''
            like_count = formatted_content.get('like_count') or 0
            collect_count = formatted_content.get('collect_count') or 0
            comment_count = formatted_content.get('comment_count') or 0
            view_count = formatted_content.get('view_count') or 0
            publish_time = formatted_content.get('publish_time') or ''
            update_timestamp = formatted_content.get('update_timestamp') or ''
            content_link = formatted_content.get('content_link') or ''
            content_id = formatted_content.get('channel_content_id') or ''

            complete_result = {
                'channel': channel,
                'title': title,
                'content': content,
                'images': recognition_result.get('image_analysis', {}).get('images_comprehension', []),
                'videos': recognition_result.get('video_analysis', {}),
                'meta': {
                    'author': author,
                    'like_count': like_count,
                    'collect_count': collect_count,
                    'comment_count': comment_count,
                    'view_count': view_count,
                    'publish_time': publish_time,
                    'update_timestamp': update_timestamp,
                    'content_link': content_link,
                    'content_id': content_id,
                }
            }
            return complete_result
        except Exception as e:
            logger.error(f"识别失败: {e}")
            return {
                'channel': '',
                'title': '',
                'content': '',
                'images': [],
                'videos': [],
                'meta': {},
                'error': str(e)
            }


class UpdateDataTool:
    """
    结构化工具：按照既定的结构将识别结果与原始 crawl_data 组合，
    并存入 knowledge_parsing_content 表。
    """
    
    @staticmethod
    def store_indentify_result(request_id: str, crawl_raw: Dict[str, Any], identify_result: Dict[str, Any]) -> Optional[int]:
        """
        存储解析结果到 knowledge_parsing_content 表
        
        Args:
            request_id: 请求ID
            crawl_raw: 原始爬取数据
            identify_result: 识别结果
            
        Returns:
            插入的行ID，失败返回None
        """
        try:
            logger.info(f"存储识别结果: request_id={request_id}, crawl_raw={crawl_raw}, identify_result={identify_result}")
            # 从原始数据中提取必要字段
            content_id = crawl_raw.get('content_id') or ''
            task_id = crawl_raw.get('task_id') or ''  # 默认任务ID，可根据需要调整
            
            # 构建存储数据
            
            sql = (
                "INSERT INTO knowledge_parsing_content "
                "(content_id, request_id, task_id, indentify_data, create_time, status) "
                "VALUES (%s, %s, %s, %s, NOW(), %s)"
            )
            
            # 状态：2 表示处理完成
            status = 2
            params = (
                content_id, 
                request_id, 
                task_id, 
                json.dumps(identify_result, ensure_ascii=False),
                status
            )
            
            result = MysqlHelper.insert_and_get_id(sql, params)
            if result:
                logger.info(f"存储解析结果成功: request_id={request_id}, content_id={content_id}, insert_id={result}")
            return result
            
        except Exception as e:
            logger.error(f"存储解析结果失败: request_id={request_id}, error={e}")
            return None
    @staticmethod
    def store_parsing_result(request_id: str, crawl_raw: Dict[str, Any], parsing_result: Dict[str, Any]) -> Optional[int]:
        """
        存储解析结果到 knowledge_parsing_content 表
        
        Args:
            request_id: 请求ID
            crawl_raw: 原始爬取数据
            parsing_result: 结构化的结果（建议传入 StructureTool.process_content_structure 的返回值）
            
        Returns:
            受影响的行数，失败返回None
        """
        try:
            # 从原始数据中提取必要字段
            content_id = crawl_raw.get('content_id') or ''
            
            # 只提取result字段的内容，如果不存在则使用整个对象
            structured_content = parsing_result.get('structured_content', {})
            if isinstance(structured_content, dict) and 'result' in structured_content:
                # 如果structured_content是字典且包含result字段，只存储result字段
                parsing_payload = structured_content['result']
            else:
                # 否则存储整个structured_content
                parsing_payload = structured_content
            
            # 更新数据
            sql = (
                "UPDATE knowledge_parsing_content "
                "SET parsing_data = %s, status = %s "
                "WHERE content_id = %s AND id = %s"
            )
            
            # 状态：5 表示结构化处理完成
            status = 5
            # 判断是否需要序列化为字符串
            if isinstance(parsing_payload, (dict, list)):
                parsing_payload = json.dumps(parsing_payload, ensure_ascii=False)
            params = (
                parsing_payload,
                status,
                content_id,
                crawl_raw.get('id') or ''
            )
            
            result = MysqlHelper.update_values(sql, params)
            if result:
                logger.info(f"存储解析结果成功: request_id={request_id}, content_id={content_id}")
            return result
            
        except Exception as e:
            logger.error(f"存储解析结果失败: request_id={request_id}, error={e}")
            return None

class StructureTool:
    """
    内容结构化工具：调用tools/structure内部的方法进行内容结构化处理
    """
    
    def __init__(self):
        """初始化结构化工具"""
        self.structure_processor = StructureProcessor()
    
    def process_content_structure(self, content_data: Dict[str, Any]) -> Dict[str, Any]:
        """
        处理内容结构化
        
        Args:
            content_data: 包含识别结果的内容数据，格式如下：
            {
                'channel': str,
                'title': str,
                'content': str,
                'images': List[str],
                'videos': Dict,
                'meta': Dict
            }
            
        Returns:
            Dict[str, Any]: 结构化处理后的结果
        """
        try:
            # 结构化输入规范化
            structure_input = {
                "title": content_data.get('title', ''),
                "body_text": content_data.get('content', ''),
                "images_comprehension": content_data.get('images', [])
            }
            
            # 调用结构化处理器
            structured_content = self.structure_processor.process_content(structure_input)
            
            # 若返回为字符串或字典，直接封装；不访问 .result
            result = {
                'original_data': content_data,
                'structured_content': structured_content,
                'structure_status': 'success',
                'process_time': self._get_current_timestamp()
            }
            
            logger.info(f"内容结构化处理成功: title={content_data.get('title', '')}")
            return result
            
        except Exception as e:
            logger.error(f"内容结构化处理失败: {e}")
            return {
                'original_data': content_data,
                'structured_content': '',
                'structure_status': 'failed',
                'error': str(e),
                'process_time': self._get_current_timestamp()
            }
    
    def _get_current_timestamp(self) -> str:
        """获取当前时间戳字符串"""
        from datetime import datetime
        return datetime.now().strftime('%Y-%m-%d %H:%M:%S')