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析言GBI最佳实践

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本文基于析言GBI的API实现了智能数据问答功能。旨在帮助您快速熟悉API的使用，以便在实际项目中灵活运用API。

前提条件

操作步骤

JAVA

步骤1：安装析言GBI的JAVA SDK

  1. 获取析言GBI JAVA SDK最新版本号。

  2. 打开您的Maven项目的pom.xml文件。

  3. 在<dependencies>标签内添加以下依赖信息，并将<version></version>标签中的版本号替换为最新的版本号。

     <dependency>
            <groupId>com.aliyun</groupId>
            <artifactId>alibabacloud-dataanalysisgbi20240823</artifactId>
            <version>1.0.0</version>
        </dependency>

  4. 保存pom.xml文件。

  5. 更新项目依赖，将SDK添加到您的项目中。

步骤2：实现智能数据问答功能

基于析言GBI的RunDataAnalysis - Chat对话接口（例如：本示例中的RunDataAnalysisRequest类），通过实现智能数问场景来帮助您熟悉API的使用。

请将代码示例中的accessKeyId、accessKeySecret及workspaceId替换为实际值，以确保代码正常运行并返回正确的结果。

package com.alibaba.iic.llmsolution.gbi.util;

import com.aliyun.auth.credentials.Credential;
import com.aliyun.auth.credentials.provider.StaticCredentialProvider;
import com.aliyun.sdk.gateway.pop.Configuration;
import com.aliyun.sdk.gateway.pop.auth.SignatureVersion;
import com.aliyun.sdk.service.dataanalysisgbi20240823.AsyncClient;
import com.aliyun.sdk.service.dataanalysisgbi20240823.models.RunDataAnalysisRequest;
import com.aliyun.sdk.service.dataanalysisgbi20240823.models.RunDataAnalysisResponseBody;
import com.google.gson.Gson;
import darabonba.core.ResponseIterable;
import darabonba.core.ResponseIterator;
import darabonba.core.client.ClientOverrideConfiguration;

public class CommonExample {
    public static void main(String[] args) throws Exception {

        StaticCredentialProvider provider = StaticCredentialProvider.create(
                Credential.builder()
                        .accessKeyId("accessKeyId")
                        .accessKeySecret("accessKeySecret")
                        .build()
        );

        AsyncClient client = AsyncClient.builder()
                .region("cn-beijing")
                .credentialsProvider(provider)
                .serviceConfiguration(Configuration.create()
                        .setSignatureVersion(SignatureVersion.V3)
                )
                .overrideConfiguration(
                        ClientOverrideConfiguration.create()
                                .setProtocol("HTTPS")
                                .setEndpointOverride("dataanalysisgbi.cn-beijing.aliyuncs.com")
                )
                .build();
        // 进行对话分析时，整体的参数控制
        RunDataAnalysisRequest request = RunDataAnalysisRequest.builder()
                // 当前对话请求所使用的业务空间id
                .workspaceId("workspaceId")
                // 当前对话请求的用户问题
                .query("查询销量最高的五个产品")
                // 当前对话请求所希望使用的版本，如未购买所指定的版本则会使用默认业务空间的版本
                .specificationType("STANDARD_MIX")
                // 当前对话请求是否只生成sql,跳过后续的可视化模块
                .generateSqlOnly(true)
                .build();

        // 获取流式内容，并进行解析处理
        ResponseIterable<RunDataAnalysisResponseBody> x = client.runDataAnalysisWithResponseIterable(request);
        ResponseIterator<RunDataAnalysisResponseBody> iterator = x.iterator();
        while (iterator.hasNext()) {
            RunDataAnalysisResponseBody event = iterator.next();
            System.out.println(new Gson().toJson(event.getData()));
            // sql_part为sql流式输出事件，流式获取生成的sql内容
            if (event.getData().getEvent().equals("sql_part")) {
                System.out.println(event.getData().getSql());
            }
            // sql为最终的sql生成事件，非流式，直接获取最终sql
            if (event.getData().getEvent().equals("sql")) {
                System.out.println(event.getData().getSql());
            }
            // 当前请求的结果中,包含可视化模型执行结果，可进行渲染
            if (event.getData().getVisualization() != null) {
                System.out.println("当前对话分析内容，包含可视化模块内容，可进行渲染");
            }
        }
        System.out.println("ALL***********************");
        System.out.println("请求成功的请求头值：");
        System.out.println(x.getStatusCode());
        System.out.println(x.getHeaders());
    }

}

返回结果示例

参数说明请参见RunDataAnalysis - Chat对话接口的返回参数。

{"event":"rewrite","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6"}
{"event":"selector","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6"}
{"event":"evidence","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"]}
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"sql"}
sql
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":""}

{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT"}
SELECT
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity)"}
SELECT p.product_name, SUM(o.quantity)
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales "}
SELECT p.product_name, SUM(o.quantity) AS total_sales 
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p "}
SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p 
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON"}
SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id \u003d"}
SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id =
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id \u003d o.product_id "}
SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id = o.product_id 
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id \u003d o.product_id GROUP BY p.product"}
SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id = o.product_id GROUP BY p.product
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id \u003d o.product_id GROUP BY p.product_name ORDER BY"}
SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id = o.product_id GROUP BY p.product_name ORDER BY
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id \u003d o.product_id GROUP BY p.product_name ORDER BY total_sales DESC "}
SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id = o.product_id GROUP BY p.product_name ORDER BY total_sales DESC 
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id \u003d o.product_id GROUP BY p.product_name ORDER BY total_sales DESC LIMIT 5; "}
SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id = o.product_id GROUP BY p.product_name ORDER BY total_sales DESC LIMIT 5; 
{"event":"sql_part","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id \u003d o.product_id GROUP BY p.product_name ORDER BY total_sales DESC LIMIT 5; "}
SELECT p.product_name, SUM(o.quantity) AS total_sales FROM products p JOIN orders o ON p.product_id = o.product_id GROUP BY p.product_name ORDER BY total_sales DESC LIMIT 5; 
{"event":"sql","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales\nFROM products p\nJOIN orders o ON p.product_id \u003d o.product_id\nGROUP BY p.product_name\nORDER BY total_sales DESC\nLIMIT 5;\n"}
SELECT p.product_name, SUM(o.quantity) AS total_sales
FROM products p
JOIN orders o ON p.product_id = o.product_id
GROUP BY p.product_name
ORDER BY total_sales DESC
LIMIT 5;

{"event":"sql_data","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales\nFROM products p\nJOIN orders o ON p.product_id \u003d o.product_id\nGROUP BY p.product_name\nORDER BY total_sales DESC\nLIMIT 5;\n","sqlData":{"column":["product_name","total_sales"],"data":[{"total_sales":"265","product_name":"丝巾"},{"total_sales":"197","product_name":"男士电动化妆刷套装"},{"total_sales":"158","product_name":"女士电动化妆刷套装"},{"total_sales":"157","product_name":"戒指"},{"total_sales":"136","product_name":"真皮皮包"}]}}
{"event":"result","evidence":"对于所有的指标（metric），如果没有对所有维度（dimension）都进行了限制，就要进行求和SUM再进行其他聚合或是筛选","requestId":"8499A3E6-C1B2-5D2E-845F-2F63F8795B4D","rewrite":"查询销量最高的五个产品及其销量","selector":["products","orders"],"sessionId":"8db26af8-721c-49bd-95f5-cceb0053ecf6","sql":"SELECT p.product_name, SUM(o.quantity) AS total_sales\nFROM products p\nJOIN orders o ON p.product_id \u003d o.product_id\nGROUP BY p.product_name\nORDER BY total_sales DESC\nLIMIT 5;\n","sqlData":{"column":["product_name","total_sales"],"data":[{"total_sales":"265","product_name":"丝巾"},{"total_sales":"197","product_name":"男士电动化妆刷套装"},{"total_sales":"158","product_name":"女士电动化妆刷套装"},{"total_sales":"157","product_name":"戒指"},{"total_sales":"136","product_name":"真皮皮包"}]},"visualization":{"data":{"plotType":"bar","xAxis":["product_name"],"yAxis":["total_sales"]},"text":"销量最高的五个产品及其销量分别是：丝巾，总销量为265件；男士电动化妆刷套装，销量为197件；女士电动化妆刷套装，销量为158件；戒指，销量为157件；真皮皮包，销量为136件。"}}
ALL***********************
请求成功的请求头值：
200
{Transfer-Encoding=chunked, Keep-Alive=timeout=25, Access-Control-Expose-Headers=*, Access-Control-Allow-Origin=*, x-acs-request-id=8499A3E6-C1B2-5D2E-845F-2F63F8795B4D, Connection=keep-alive, Date=Thu, 14 Nov 2024 08:16:49 GMT, Content-Type=text/event-stream;charset=utf-8, x-acs-trace-id=26e2559443d87082911aa44f656072df}

如果未授权连接数据库，会返回以下结果：

{"errorMessage":"data source is empty","event":"error"}
ALL***********************
请求成功的请求头值：
200
{Transfer-Encoding=chunked, Keep-Alive=timeout=25, Access-Control-Expose-Headers=*, Access-Control-Allow-Origin=*, x-acs-request-id=CB1F6A3B-43DC-5D9D-8FDC-57A9474B0DF3, Connection=keep-alive, Date=Thu, 14 Nov 2024 06:20:33 GMT, Content-Type=text/event-stream;charset=utf-8, x-acs-trace-id=dfa7db76cf65dcc933292999274fa687}

Python

步骤1：安装依赖

pip install alibabacloud-tea-openapi-sse==1.0.2

步骤2：实现智能数据问答功能

基于析言GBI的RunDataAnalysis - Chat对话接口的API代码示例如下。

请将代码示例中的accessKeyId、accessKeySecret及workspaceId替换为实际值，以确保代码正常运行并返回正确的结果。

from alibabacloud_tea_openapi_sse.client import Client as OpenApiClient
from alibabacloud_tea_openapi_sse import models as open_api_models
from alibabacloud_tea_util_sse import models as util_models
import asyncio
import json

class RunDataAnalysis:
    def __init__(self) -> None:
        self.endpoint = None
        self._client = None
        self._api_info = self._create_api_info()
        self._runtime = util_models.RuntimeOptions(read_timeout=1000 * 100)
        self._init_app()

    def _init_app(self):
        endpoint = 'dataanalysisgbi.cn-beijing.aliyuncs.com'
        access_key_id = '${access_key_id}'
        access_key_secret = '${access_key_secret}'
        assert endpoint is not None and access_key_id is not None and access_key_secret is not None

        self._client = self._create_client(access_key_id, access_key_secret, endpoint)

    def _create_client(
            self,
            access_key_id: str,
            access_key_secret: str,
            endpoint: str,
    ) -> OpenApiClient:
        config = open_api_models.Config(
            access_key_id=access_key_id,
            access_key_secret=access_key_secret
        )
        config.endpoint = endpoint if endpoint is not None else 'dataanalysisgbi.cn-beijing.aliyuncs.com'
        return OpenApiClient(config)

    def _create_api_info(self) -> open_api_models.Params:
        """
        API 相关
        @param path: params
        @return: OpenApi.Params
        """
        params = open_api_models.Params(
            # 接口名称
            action='RunDataAnalysis',
            # 接口版本
            version='2024-08-23',
            # 接口协议
            protocol='HTTPS',
            # 接口 HTTP 方法
            method='POST',
            auth_type='AK',
            style='RPC',
            # 接口 PATH,
            pathname='/${workspaceId}/gbi/runDataAnalysis',
            # 接口请求体内容格式,
            req_body_type='json',
            # 接口响应体内容格式,
            body_type='sse'
        )
        return params

    async def do_sse_query(self, query: str):
        assert self._client is not None
        assert isinstance(query, str), '"query" is mandatory and should be str'

        body = {
            'specificationType': 'STANDARD_MIX',
            'query': query,
        }
        request = open_api_models.OpenApiRequest(
            body=body
        )
        sse_receiver = self._client.call_sse_api_async(params=self._api_info, request=request, runtime=self._runtime)
        return sse_receiver


# 模型初始化

async def query():
    xiyan_gbi = RunDataAnalysis()
    frame_count = 0
    async for res in await xiyan_gbi.do_sse_query('查询全部关键字数据，并用饼图展示'):
        try:
            data = json.loads(res.get('event').data)
            print(data)
        except json.JSONDecodeError:
            print('------json.JSONDecodeError--------')
            print(res.get('headers'))
            print(res.get('event').data)
            print('------json.JSONDecodeError-end--------')
            continue
    print('------end--------')


if __name__ == '__main__':
    asyncio.run(query())

返回结果示例

参数说明请参见RunDataAnalysis - Chat对话接口的返回参数。

{'data': {'requestId': '93DE1D26-153E-5386-BA8F-9D2E2F8B3381', 'sessionId': '10148716_1f8ebf09-df4b-4b0c-9493-66a1895a9ba4', 'event': 'rewrite', 'rewrite': '查询user表中的全部数据，并用饼图展示'}}
{'data': {'requestId': '93DE1D26-153E-5386-BA8F-9D2E2F8B3381', 'selector': ['user'], 'sessionId': '10148716_1f8ebf09-df4b-4b0c-9493-66a1895a9ba4', 'event': 'selector', 'rewrite': '查询er表中的全部数据，并用饼图展示'}}
{'data': {'evidence': 'KKK是指客单价。KKK=总销售额/订单总数，保留2位小数。', 'selector': ['user'], 'event': 'evidence', 'rewrite': '查询user表中的全部数据，并用饼图展示'}}
{'data': {'evidence': 'KKK是指客单价。KKK=总销售额/订单总数，保留2位小数。', 'requestId': '93DE1D26-153E-5386-BA8F-9D2E2F8B3381', 'selector': ['user'], 'sessionId': '10148716_1f8ebf09-5a9ba4', 'event': 'sql_part', 'rewrite': '查询user表中的全部数据，并用饼图展示', 'sql': ''}}
{'data': {'evidence': 'KKK是指客单价。KKK=总销售额/订单总数，保留2位小数。', 'requestId': '93DE1D26-153E-5386-BA8F-9D2E2F8B3381', 'selector': ['user'], 'sessionId': '10148716_1f8ebf09-5a9ba4', 'event': 'sql_part', 'rewrite': '查询user表中的全部数据，并用饼图展示', 'sql': 'select *'}}
{'data': {'evidence': 'KKK是指客单价。KKK=总销售额/订单总数，保留2位小数。', 'requestId': '93DE1D26-153E-5386-BA8F-9D2E2F8B3381', 'selector': ['user'], 'sessionId': '10148716_1f8ebf09-5a9ba4', 'event': 'sql_part', 'rewrite': '查询user表中的全部数据，并用饼图展示', 'sql': 'select * from user '}}
{'data': {'evidence': 'KKK是指客单价。KKK=总销售额/订单总数，保留2位小数。', 'requestId': '93DE1D26-153E-5386-BA8F-9D2E2F8B3381', 'selector': ['user'], 'sessionId': '10148716_1f8ebf09-5a9ba4', 'event': 'sql_part', 'rewrite': '查询user表中的全部数据，并用饼图展示', 'sql': 'select * from user '}}
{'data': {'evidence': 'KKK是指客单价。KKK=总销售额/订单总数，保留2位小数。', 'requestId': '93DE1D26-153E-5386-BA8F-9D2E2F8B3381', 'selector': ['user'], 'sessionId': '10148716_1f8ebf09-5a9ba4', 'event': 'sql', 'rewrite': '查询user表中的全部数据，并用饼图展示', 'sql': 'select * from user\n'}}
{'data': {'evidence': 'KKK是指客单价。KKK=总销售额/订单总数，保留2位小数。', 'requestId': '93DE1D26-153E-5386-BA8F-9D2E2F8B3381', 'selector': ['user'], 'sqlData': {}, 'sessionId': '101b0c-9493-66a1895a9ba4', 'event': 'sql_data', 'rewrite': '查询user表中的全部数据，并用饼图展示', 'sql': 'select * from user\n'}}
{'data': {'evidence': 'KKK是指客单价。KKK=总销售额/订单总数，保留2位小数。', 'requestId': '93DE1D26-153E-5386-BA8F-9D2E2F8B3381', 'selector': ['user'], 'sqlData': {}, 'sessionId': '101b0c-9493-66a1895a9ba4', 'event': 'result', 'rewrite': '查询user表中的全部数据，并用饼图展示', 'sql': 'select * from user\n'}}
------end--------

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