使用google api返回json格式的搜索结果笔记

现在ai大模型的发展很快,简直就是一个超级大脑,无所不知,但是由于ai训练的数据不是最新的,有时候无法回答你的问题,那么如果将ai接入搜索引擎,获取最新的搜索信息,然后加以总结给用户就很厉害了,这个时候就需要调用搜索引擎api接口了。
google自定义搜索提供了这样的一个api,每天可免费100次调用,超过是要交钱的,下面我记录一下申请调用流程:
1、创建自定义搜索引擎,地址:https://programmablesearchengine.google.com/controlpanel/create,

并记录下cx参数

2、申请api,地址:https://console.cloud.google.com/apis/credentials

3、最后就可以把上面申请的key和cx拼接到下面的url中访问谷歌自定义搜索api,google返回一个json格式化的数据。
https://www.googleapis.com/customsearch/v1?key=你申请的apikey&cx=创建的自定义搜索&q=关键字
返回json数据如下:
{
"kind": "customsearch#search",
"url": {
"type": "application/json",
"template": "https://www.googleapis.com/customsearch/v1?q={searchTerms}&num={count?}&start={startIndex?}&lr={language?}&safe={safe?}&cx={cx?}&sort={sort?}&filter={filter?}&gl={gl?}&cr={cr?}&googlehost={googleHost?}&c2coff={disableCnTwTranslation?}&hq={hq?}&hl={hl?}&siteSearch={siteSearch?}&siteSearchFilter={siteSearchFilter?}&exactTerms={exactTerms?}&excludeTerms={excludeTerms?}&linkSite={linkSite?}&orTerms={orTerms?}&dateRestrict={dateRestrict?}&lowRange={lowRange?}&highRange={highRange?}&searchType={searchType}&fileType={fileType?}&rights={rights?}&imgSize={imgSize?}&imgType={imgType?}&imgColorType={imgColorType?}&imgDominantColor={imgDominantColor?}&alt=json"
},
"queries": {
"request": [
{
"title": "Google Custom Search - openai新模型",
"totalResults": "14100000",
"searchTerms": "openai新模型",
"count": 10,
"startIndex": 1,
"inputEncoding": "utf8",
"outputEncoding": "utf8",
"safe": "off",
"cx": "自己的cx"
}
],
"nextPage": [
{
"title": "Google Custom Search - openai新模型",
"totalResults": "14100000",
"searchTerms": "openai新模型",
"count": 10,
"startIndex": 11,
"inputEncoding": "utf8",
"outputEncoding": "utf8",
"safe": "off",
"cx": "自己的cx"
}
]
},
"context": {
"title": "it"
},
"searchInformation": {
"searchTime": 0.444258,
"formattedSearchTime": "0.44",
"totalResults": "14100000",
"formattedTotalResults": "14,100,000"
},
"items": [
{
"kind": "customsearch#result",
"title": "终结扩散模型:OpenAI开源新模型代码,一步成图,1秒18张-36氪",
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"link": "https://m.36kr.com/p/2213338104164993",
"displayLink": "m.36kr.com",
"snippet": "Apr 13, 2023 ... 首先Consistency Models 建立在连续时间扩散模型中的概率流(PF) 常微分方程(ODE) 之上。如下图1 所示,给定一个将数据平滑地转换为噪声的PF ODE, ...",
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"htmlFormattedUrl": "https://m.36kr.com/p/2213338104164993",
"pagemap": {
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"article:published_time": "2023-04-12 23:09:46",
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"og:description": "扩散模型的时代结束了。",
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"kind": "customsearch#result",
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"link": "https://www.guruin.com/news/75570",
"displayLink": "www.guruin.com",
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