适用于带有text字段向量化配置（vectorize参数）的索引，支持多个关键词的检索。

仅列出本接口特有的参数。更多信息请参见检索公共参数。

实际检索时，最多提取前10个关键词。关键词内容的总长度不超过512字节。

• 请求参数

req_path = "/api/vikingdb/data/search/keywords"
req_body = {
    "collection_name": "test_coll_with_vectorize",
    "index_name": "idx_1",
    "keywords": ["火山", "向量", "检索", "亿"],
    "output_fields": [
        "f_text"
    ],
    "limit": 5
}

• 响应参数

{
    "code": "Success",
    "message": "The API call was executed successfully.",
    "request_id": "02175438839168500000000000000000000ffff0a003ee4fc3499",
    "result": {
        "data": [
            {
                "id": "uid_001",
                "fields": {
                    "f_text": "支持百亿级向量检索规模"
                },
                "score": 3.605649671017216,
                "ann_score": 0.34465837478637695
            },
            {
                "id": "uid_002",
                "fields": {
                    "f_text": "向量相似度检索是一种基于向量空间模型的检索方法"
                },
                "score": 2.583801264623392,
                "ann_score": 0.269525408744812,
            },
            {
                "id": "uid_003",
                "fields": {
                    "f_text": "向量是指在数学中具有一定大小和方向的量，文本、图片、音视频等非结构化数据"
                },
                "score": 0.269525408744812,
                "ann_score": 0.31852447986602783
            },
            {
                "id": "uid_004",
                "fields": {
                    "f_text": "该数据库内置多种火山引擎自研索引算法"
                },
                "score": 1.5971799596522382,
                "ann_score": 0.3151528239250183
            },
            {
                "id": "uid_005",
                "fields": {
                    "f_text": "可广泛应用于智能问答、智能搜索、推荐系统和数据去重等领域"
                },
                "score": 0.5667128028680034,
                "ann_score": 0.21270805597305298
            }
        ],
        "total_return_count": 5,
        "token_usage": {
            "doubao-embedding-vision__250328": {
                "prompt_tokens":53,
                "completion_tokens":0,
                "image_tokens":0,
                "total_tokens":53
            }
        }
    }
}

"""
pip3 install volcengine
"""
import os

from volcengine.auth.SignerV4 import SignerV4
from volcengine.Credentials import Credentials
from volcengine.base.Request import Request
import requests, json

class ClientForDataApi:
    def __init__(self, ak, sk, host):
        self.ak = ak
        self.sk = sk
        self.host = host

    def prepare_request(self, method, path, params=None, data=None):
        r = Request()
        r.set_shema("https")
        r.set_method(method)
        r.set_connection_timeout(10)
        r.set_socket_timeout(10)
        mheaders = {
            'Accept': 'application/json',
            'Content-Type': 'application/json',
            'Host': self.host,
        }
        r.set_headers(mheaders)
        if params:
            r.set_query(params)
        r.set_host(self.host)
        r.set_path(path)
        if data is not None:
            r.set_body(json.dumps(data))
        credentials = Credentials(self.ak, self.sk, 'vikingdb', 'cn-beijing')
        SignerV4.sign(r, credentials)
        return r
        
    def do_req(self, req_method, req_path, req_params, req_body):
        req = self.prepare_request(method=req_method, path=req_path, params=req_params, data=req_body)
        return requests.request(method=req.method, url="http://{}{}".format(self.host, req.path),
                                  headers=req.headers, data=req.body, timeout=10000)

if __name__ == '__main__':
    client = ClientForDataApi(
        ak = "*",#替换为您的ak
        sk = "*",#替换为您的sk
        host = "api-vikingdb.vikingdb.cn-beijing.volces.com",#替换为您所在的域名
    )
    req_method = "POST"
    req_params = None
    req_path = "/api/vikingdb/data/search/keywords"
    req_body = {
        "collection_name": "test_coll_with_vectorize",
        "index_name": "idx_1",
        "keywords": ["火山", "向量", "检索", "亿"],
        "output_fields": [
            "f_text"
        ],
        "limit": 5
    }
    result = client.do_req(req_method=req_method, req_path=req_path, req_params=req_params, req_body=req_body)
    print("req http status code: ", result.status_code)
    print("req result: \n", result.text)