aigc-test/ai_tag_task.py

import os
import shutil
import json
import datetime
import time
import traceback
import requests
from threading import Timer
from utils import data_check, get_feature_data, asr_validity_discrimination
from whisper_asr import get_whisper_asr
from gpt_tag import request_gpt
from config import set_config
from log import Log
from ReadXlsxFile import getVideoInfoInXlxs

from result_save import insert_content
from result_save import insert_content
config_ = set_config()
log_ = Log()
features = ['videoid', 'title', 'video_path']


def get_video_ai_tags(video_id, video_info):
    try:
        st_time = time.time()
        log_message = {
            'videoId': int(video_id),
        }
        title = video_info.get('title')
        log_message['videoPath'] = video_info.get('video_path')
        log_message['title'] = video_info.get('title')
        # 1. 获取asr结果
        asr_res_initial = video_info.get('asr_res', '')
        log_message['asrRes'] = asr_res_initial
        # 2. 判断asr识别的文本是否有效
        validity = asr_validity_discrimination(text=asr_res_initial)
        log_message['asrValidity'] = validity
        if validity is True:
            # 3. 对asr结果进行清洗
            asr_res = asr_res_initial.replace('\n', '')
            for stop_word in config_.STOP_WORDS:
                asr_res = asr_res.replace(stop_word, '')
            # token限制: 字数 <= 2500
            asr_res = asr_res[-2500:]

            # 4. gpt产出结果
            # 4.1 gpt产出summary, keywords,
            prompt1 = f"{config_.GPT_PROMPT['tags']['prompt6']}{asr_res.strip()}"
            log_message['gptPromptSummaryKeywords'] = prompt1
            gpt_res1 = request_gpt(prompt=prompt1)
            log_message['gptResSummaryKeywords'] = gpt_res1
            if gpt_res1 is not None:
                # 4.2 获取summary, keywords, title进行分类
                try:
                    gpt_res1_json = json.loads(gpt_res1)
                    summary = gpt_res1_json['summary']
                    keywords = gpt_res1_json['keywords']
                    log_message['summary'] = summary
                    log_message['keywords'] = str(keywords)

                    # TODO 三个 prompt 拆分成三个请求
                    prompt2_param = f"标题：{title}\n概况：{summary}\n关键词：{keywords}"
                    prompt2 = f"{config_.GPT_PROMPT['tags']['prompt8']}{prompt2_param}"
                    log_message['gptPrompt2'] = prompt2
                    gpt_res2 = request_gpt(prompt=prompt2)
                    log_message['gptRes2'] = gpt_res2
                    prompt3 = f"{config_.GPT_PROMPT['tags']['prompt9']}{prompt2_param}"
                    log_message['gptPrompt3'] = prompt3
                    gpt_res3 = request_gpt(prompt=prompt3)
                    log_message['gptRes3'] = gpt_res3
                    prompt4 = f"{config_.GPT_PROMPT['tags']['prompt10']}{prompt2_param}"
                    log_message['gptPrompt4'] = prompt4
                    gpt_res4 = request_gpt(prompt=prompt4)
                    log_message['gptRes4'] = gpt_res4
                    # 5. 解析gpt产出结果
                    parseRes = praseGptRes(gpt_res2, gpt_res3, gpt_res4)
                    parseRes['video_id'] = video_id
                    log_message.update(parseRes)

                    # 6. 保存结果
                    insert_content(parseRes)

                except:
                    log_.error(traceback.format_exc())
                    pass
        else:
            pass
        log_message['executeTime'] = (time.time() - st_time) * 1000
        log_.info(log_message)
    except Exception as e:
        log_.error(e)
        log_.error(traceback.format_exc())


def praseGptRes(gpt_res2, gpt_res3, gpt_res4):
    result = {}
    if gpt_res2 is not None:
        try:
            res2 = json.loads(gpt_res2)
            result['key_words'] = res2['key_words']
            result['search_keys'] = res2['search_keys']
            result['extra_keys'] = res2['extra_keys']
        except:
            pass
    if gpt_res3 is not None:
        try:
            res3 = json.loads(gpt_res3)
            result['tone'] = res3['tone']
            result['target_audience'] = res3['target_audience']
            result['target_age'] = res3['target_age']
        except:
            pass
    if gpt_res4 is not None:
        try:
            res4 = json.loads(gpt_res4)
            result['category'] = res4['category']
            result['target_gender'] = res4['target_gender']
            result['address'] = res4['address']
            result['theme'] = res4['theme']
        except:
            pass
    return result


def process(video_id, video_info, download_folder):
    if video_info.get(video_id, None) is None:
        shutil.rmtree(os.path.join(download_folder, video_id))
    else:
        video_folder = os.path.join(download_folder, video_id)
        for filename in os.listdir(video_folder):
            video_type = filename.split('.')[-1]
            if video_type in ['mp4', 'm3u8']:
                video_file = os.path.join(video_folder, filename)
                get_video_ai_tags(
                    video_id=video_id, video_file=video_file, video_info=video_info.get(video_id))
                # 将处理过的视频进行删除
                shutil.rmtree(os.path.join(download_folder, video_id))
            else:
                shutil.rmtree(os.path.join(download_folder, video_id))


def ai_tags(project, table, dt):
    # 获取特征数据
    feature_df = get_feature_data(
        project=project, table=table, dt=dt, features=features)
    video_id_list = feature_df['videoid'].to_list()
    video_info = {}
    for video_id in video_id_list:
        title = feature_df[feature_df['videoid']
                           == video_id]['title'].values[0]
        video_path = feature_df[feature_df['videoid']
                                == video_id]['video_path'].values[0]
        if title is None:
            continue
        title = title.strip()
        if len(title) > 0:
            video_info[video_id] = {'title': title, 'video_path': video_path}
            # print(video_id, title)
    print(len(video_info))
    # 获取已下载视频
    download_folder = 'videos'
    retry = 0
    while retry < 3:
        video_folder_list = os.listdir(download_folder)
        if len(video_folder_list) < 2:
            retry += 1
            time.sleep(60)
            continue
        # pool = multiprocessing.Pool(processes=5)
        # for video_id in video_folder_list:
        #     if video_id not in video_id_list:
        #         continue
        #     pool.apply_async(
        #         func=process,
        #         args=(video_id, video_info, download_folder)
        #     )
        # pool.close()
        # pool.join()
        for video_id in video_folder_list:
            if video_id not in video_id_list:
                continue
            if video_info.get(video_id, None) is None:
                shutil.rmtree(os.path.join(download_folder, video_id))
            else:
                video_folder = os.path.join(download_folder, video_id)
                for filename in os.listdir(video_folder):
                    video_type = filename.split('.')[-1]
                    if video_type in ['mp4', 'm3u8']:
                        video_file = os.path.join(video_folder, filename)
                        get_video_ai_tags(
                            video_id=video_id, video_file=video_file, video_info=video_info.get(video_id))
                        # 将处理过的视频进行删除
                        shutil.rmtree(os.path.join(download_folder, video_id))
                    else:
                        shutil.rmtree(os.path.join(download_folder, video_id))


def get_asr_res(video_id):
    # URL of the API endpoint
    url = 'http://61.48.133.26:5999/video_to_text'

    # Headers for the request
    headers = {
        'Content-Type': 'application/json'
    }

    # Data to be sent in the request
    data = {
        "video_id": f"{video_id}"
    }

    # Making the POST request
    response = requests.post(url, headers=headers, json=data)

    # Checking if the request was successful
    if response.status_code == 200:
        # Extracting the 'text' field from the JSON response
        result_text = response.json().get('text', '无内容')
        return result_text
    else:
        return '无内容'


def ai_tags_new(project, table, dt):
    # 获取特征数据
    feature_df = get_feature_data(
        project=project, table=table, dt=dt, features=features)
    video_id_list = feature_df['videoid'].to_list()
    video_info = {}
    for video_id in video_id_list:
        title = feature_df[feature_df['videoid']
                           == video_id]['title'].values[0]
        video_path = feature_df[feature_df['videoid']
                                == video_id]['video_path'].values[0]
        if title is None:
            continue
        title = title.strip()
        if len(title) < 1:
            continue
        # 获取asr结果
        asr_res = get_asr_res(video_id)

        video_info[video_id] = {'title': title,
                                'video_path': video_path, 'asr_res': asr_res}
        get_video_ai_tags(video_id=video_id,
                          video_info=video_info.get(video_id))


def timer_check():
    try:
        project = config_.DAILY_VIDEO['project']
        table = config_.DAILY_VIDEO['table']
        now_date = datetime.datetime.today()
        print(f"now_date: {datetime.datetime.strftime(now_date, '%Y%m%d')}")
        dt = datetime.datetime.strftime(
            now_date-datetime.timedelta(days=1), '%Y%m%d')
        # 查看数据是否已准备好
        data_count = data_check(project=project, table=table, dt=dt)
        if data_count > 0:
            print(f'videos count = {data_count}')
            asr_folder = 'asr_res'
            if not os.path.exists(asr_folder):
                # 1分钟后重新检查
                Timer(60, timer_check).start()
            else:
                # 数据准备好，进行aiTag
                ai_tags_new(project=project, table=table, dt=dt)
                print(f"videos ai tag finished!")

        else:
            # 数据没准备好，1分钟后重新检查
            Timer(60, timer_check).start()
    except Exception as e:
        print(
            f"视频ai打标签失败, exception: {e}, traceback: {traceback.format_exc()}")


if __name__ == '__main__':
    # timer_check()
    feature_df = getVideoInfoInXlxs('aigc-test/past_videos.xlsx')
    video_id_list = feature_df['videoid'].to_list()
    video_info = {}
    for video_id in video_id_list:
        title = feature_df[feature_df['videoid']
                           == video_id]['title'].values[0]
        video_path = feature_df[feature_df['videoid']
                                == video_id]['video_path'].values[0]
        if title is None:
            continue
        title = title.strip()
        if len(title) < 1:
            continue
        # 获取asr结果
        asr_res = get_asr_res(video_id)

        video_info[video_id] = {'title': title,
                                'video_path': video_path, 'asr_res': asr_res}
        get_video_ai_tags(video_id=video_id,
                          video_info=video_info.get(video_id))