获取多重搜索/Fetch multi-type search
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获取多重搜索/Fetch multi-type search
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获取多重搜索/Fetch multi-type search
[中文]
用途:
- 获取抖音 App 中多种类型(视频、用户、音乐、话题等)的综合搜索结果。
备注:
- 初次请求
cursor传 0,search_id传空字符串。 - 返回内容丰富,适合搭建搜索聚合页、推荐页等场景。
参数:
- keyword: 搜索关键词,如 "人工智能"
- cursor: 翻页游标(首次请求传 0,翻页时使用上次响应的 cursor)
- sort_type: 排序方式
0: 综合排序1: 最多点赞2: 最新发布
- publish_time: 发布时间筛选
0: 不限1: 最近一天7: 最近一周180: 最近半年
- filter_duration: 视频时长筛选
0: 不限0-1: 1 分钟以内1-5: 1-5 分钟5-10000: 5 分钟以上
- content_type: 内容类型筛选
0: 不限1: 视频2: 图片3: 文章
- search_id: 搜索ID(分页时使用)
请求体示例:
payload = {
"keyword": "人工智能",
"cursor": 0,
"sort_type": "0",
"publish_time": "0",
"filter_duration": "0",
"content_type": "0",
"search_id": ""
}
返回(部分常用字段,实际返回字段更多,一切以实际响应为准):
-
cursor: 下一页翻页游标 -
has_more: 是否还有更多数据(1=有,0=无) -
business_data[]: 搜索结果列表data_id: 结果数据编号type: 结果类型1: 视频(aweme_info)2: 用户(user_info)4: 音乐(music_info)6: 话题(cha_info)
data: 具体数据内容,按type类型解析- 如果 type = 1(视频):
aweme_info:aweme_id: 视频IDdesc: 视频描述author: 作者信息uid: 用户IDnickname: 用户昵称avatar_thumb.url_list: 小头像is_verified: 是否认证region: 地区
music: 音乐信息id_str: 音乐IDtitle: 音乐标题
video: 视频播放与封面信息play_addr.url_list: 播放地址cover.url_list: 封面duration: 视频时长(毫秒)
statistics:comment_count: 评论数digg_count: 点赞数share_count: 分享数play_count: 播放数
status:is_delete: 是否被删除is_private: 是否私密
share_url: 视频外链
- 如果 type = 2(用户):
user_info:uid: 用户IDnickname: 用户昵称signature: 个人签名follower_count: 粉丝数avatar_thumb.url_list: 小头像region: 地区is_verified: 是否认证
- 如果 type = 4(音乐):
music_info:id_str: 音乐IDtitle: 音乐标题author: 作者名play_url.url_list: 播放地址
- 如果 type = 6(话题):
cha_info:cha_name: 话题名desc: 话题描述share_url: 话题分享链接user_count: 话题参与人数view_count: 话题浏览次数
- 如果 type = 1(视频):
-
extra:now: 当前服务器时间戳logid: 请求日志ID
[English]
Purpose:
- Fetch multiple types of search results (videos, users, music, hashtags, etc.) from Douyin App.
Notes:
- Set
cursorto 0 andsearch_idto an empty string for the first request. - Suitable for search aggregation pages, discovery modules, and recommendations.
Parameters:
- keyword: Search keyword, e.g., "Artificial Intelligence"
- cursor: Pagination cursor (0 for the first page, use the last response cursor for subsequent pages)
- sort_type: Sorting method
0: Comprehensive1: Most likes2: Latest
- publish_time: Publish time filter
0: Unlimited1: Last day7: Last week180: Last half year
- filter_duration: Video duration filter
0: Unlimited0-1: Within 1 minute1-5: 1 to 5 minutes5-10000: More than 5 minutes
- content_type: Content type filter
0: Unlimited1: Video2: Picture3: Article
- search_id: Search ID used for pagination
Request Body Example:
payload = {
"keyword": "Artificial Intelligence",
"cursor": 0,
"sort_type": "0",
"publish_time": "0",
"filter_duration": "0",
"content_type": "0",
"search_id": ""
}
Response (common fields, actual response may contain more fields):
-
cursor: Cursor for the next page -
has_more: Whether there are more results (1=Yes, 0=No) -
business_data[]: List of search result itemsdata_id: Data IDtype: Result type1: Video (aweme_info)2: User (user_info)4: Music (music_info)6: Hashtag (cha_info)
data: Content depending ontype- if type = 1 (video):
aweme_info: Detailed video info
- if type = 2 (user):
user_info: Detailed user info
- if type = 4 (music):
music_info: Music details
- if type = 6 (hashtag):
cha_info: Hashtag details
- if type = 1 (video):
-
extra:now: Current server timestamplogid: Request log ID
Imported from a validated TikHub OpenAPI document. Pricing must be reviewed before enabling.
Try 获取多重搜索/Fetch multi-type search
Test this model in the Sandbase Playground with your own prompts.
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