lanyuanxiaoyao/ai-analysis
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

完成全部功能，优化图表和对话

Browse Source
This commit is contained in:
兰缘小妖
2025-03-01 18:44:27 +08:00
parent bfffbc9868
commit d90029e7c2
15 changed files with 9338 additions and 75 deletions
Download Patch File Download Diff File Expand all files Collapse all files

37
.idea/csv-editor.xml generated Normal file
View File

@@ -0,0 +1,37 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="CsvFileAttributes">
<option name="attributeMap">
<map>
<entry key="/dumpDataPreview">
<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
<entry key="/knowledge/data.csv">
<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
<entry key="/knowledge/data2.csv">
<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
<entry key="/knowledge/host_assets.csv">
<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
</map>
</option>
</component>
</project>

10
.idea/jarRepositories.xml generated
View File

@@ -6,6 +6,16 @@
<option name="name" value="Central Repository" />
<option name="url" value="https://repo.maven.apache.org/maven2" />
</remote-repository>
<remote-repository>
<option name="id" value="local-releases" />
<option name="name" value="Local Releases" />
<option name="url" value="http://localhost:3105/threepartrepo" />
</remote-repository>
<remote-repository>
<option name="id" value="central" />
<option name="name" value="Central Repository" />
<option name="url" value="http://localhost:3105/threepartrepo" />
</remote-repository>
<remote-repository>
<option name="id" value="central" />
<option name="name" value="Maven Central repository" />

1
.idea/sqldialects.xml generated
View File

@@ -1,6 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="SqlDialectMappings">
<file url="file://$PROJECT_DIR$/knowledge/host_assets.sql" dialect="MySQL" />
<file url="PROJECT" dialect="MySQL" />
</component>
</project>

21
client/src/App.vue
View File

@@ -6,7 +6,7 @@ import * as echarts from 'echarts'
import {CategoryScale, Chart, LinearScale, LineController, LineElement, PointElement, Title,} from 'chart.js'
import 'chartjs-adapter-moment'
import mermaid from 'mermaid'
import {each, isEqual, isJson, nextTick} from 'licia'
import {each, isEqual, isNull, nextTick} from 'licia'
Chart.register(
LineController,
@@ -35,14 +35,19 @@ md.use(function (md) {
const content = tokens[idx].content
// 此处判断是否为 echarts 代码块
if (tokens[idx].info === 'echarts') {
if (isJson(content)) {
chartsMap.value.echarts[idx] = JSON.parse(content) //此处表示将内容存起来，存到当前页面的变量去
try {
chartsMap.value.echarts[idx] = JSON.parse(content)
console.log('ok', content)
} catch (e) {
console.error(e, content)
}
return `<div id="echarts-${idx}" style="width: 600px;height:400px;"></div>`
} else if (tokens[idx].info === 'chartjs') {
// 此处判断是否为 chartjs 代码块
if (isJson(content)) {
try {
chartsMap.value.chartjs[idx] = JSON.parse(content)
} catch (e) {
console.error(e, content)
}
return `<canvas id="chartjs-${idx}"></canvas>`
} else if (tokens[idx].info === 'mermaid') {
@@ -97,6 +102,7 @@ const handleSubmit = async () => {
mermaid: {},
}
let eventSource
try {
const url = 'http://localhost:7891/chat/stream'
const formData = new FormData()
@@ -112,7 +118,7 @@ const handleSubmit = async () => {
formData.append('database_name', databaseName.value)
}
const eventSource = createEventSource({
eventSource = createEventSource({
url: url,
method: 'POST',
body: formData,
@@ -131,6 +137,9 @@ const handleSubmit = async () => {
answer.value = '抱歉，请求出现错误'
renderedAnswer.value = answer.value
showToastMessage('请求失败，请检查服务器连接', 'error')
if (!isNull(eventSource)) {
eventSource.close()
}
} finally {
loading.value = false
}
@@ -224,7 +233,7 @@ onMounted(() => {
<template>
<div class="chat-container">
<div class="chat-header">
<h1>数据库助手</h1>
<h1>知识库助手</h1>
</div>
<div class="messages-container">

4469
knowledge/host_assets.csv Normal file
View File

File diff suppressed because it is too large Load Diff

30
knowledge/host_assets.sql Normal file
View File

@@ -0,0 +1,30 @@
CREATE TABLE `host_assets`
(
`id` bigint NOT NULL AUTO_INCREMENT COMMENT 'ID',
`host_ip` varchar(100) DEFAULT NULL COMMENT '业务IP地址，该地址表示对外暴露业务的主机IP，通常业务由1个或多个主机共同提供服务，其他不对外暴露的主机的IP记录在all_ip字段中',
`all_ip` varchar(500) DEFAULT NULL COMMENT '提供业务支撑的所有主机的IP',
`system_name` varchar(255) DEFAULT NULL COMMENT '所属业务系统名称',
`location` varchar(255) DEFAULT NULL COMMENT '主机所在机房具体地址',
`manager_ip` varchar(100) DEFAULT NULL COMMENT '如果业务提供对外的管理控制台，则控制台的IP地址记录在这里，如果没有则记录为空',
`host_name` varchar(100) DEFAULT NULL COMMENT '主机host名称',
`host_os` varchar(100) DEFAULT NULL COMMENT '主机操作系统',
`manufacturer` varchar(255) DEFAULT NULL COMMENT '主机设备制造厂商',
`host_model` varchar(255) DEFAULT NULL COMMENT '主机设备型号',
`host_sn` varchar(100) DEFAULT NULL COMMENT '主机序列号',
`cpu_model` varchar(100) DEFAULT NULL COMMENT 'cpu型号',
`cpu_num` varchar(100) DEFAULT NULL COMMENT 'cpu数量',
`memory` varchar(100) DEFAULT NULL COMMENT '内存大小，除非该字段记录标明单位，否则默认单位为GB',
`system_disk` varchar(100) DEFAULT NULL COMMENT '系统盘容量，除非该字段记录标明单位，否则默认单位为GB',
`data_disk` varchar(100) DEFAULT NULL COMMENT '数据盘容量，除非该字段记录标明单位，否则默认单位为GB',
`start_date` varchar(100) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci DEFAULT NULL COMMENT '设备生产日期',
`monitor` varchar(100) DEFAULT NULL COMMENT '是否使用基础监控',
`component` varchar(100) DEFAULT NULL COMMENT '主机上部署了哪些应用组件',
`host_state` varchar(100) DEFAULT NULL COMMENT '主机状态',
`state_remark` varchar(255) DEFAULT NULL COMMENT '主机状态详细说明',
`responsible_person` varchar(100) DEFAULT NULL COMMENT '主机责任人',
`manager` varchar(100) DEFAULT NULL COMMENT '主机所属业务的业务经理',
PRIMARY KEY (`id`)
) ENGINE = InnoDB
AUTO_INCREMENT = 8532
DEFAULT CHARSET = utf8mb4
COLLATE = utf8mb4_0900_ai_ci COMMENT ='主机资产表，该表记录了主机的详细信息，包括配置、部署组件、业务等'

4469
knowledge/host_assets_backup.csv Normal file
View File

File diff suppressed because it is too large Load Diff

40
pom.xml
View File

@@ -47,6 +47,46 @@
<artifactId>hutool-all</artifactId>
<version>5.8.32</version>
</dependency>
<dependency>
<groupId>net.datafaker</groupId>
<artifactId>datafaker</artifactId>
<version>2.4.2</version>
</dependency>
<!--<dependency>
<groupId>io.projectreactor.netty</groupId>
<artifactId>reactor-netty-http</artifactId>
<version>1.2.3</version>
</dependency>-->
<!--<dependency>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-reactive-httpclient</artifactId>
<version>4.0.8</version>
</dependency>-->
<!--<dependency>
<groupId>org.apache.httpcomponents.client5</groupId>
<artifactId>httpclient5</artifactId>
<version>5.4.2</version>
</dependency>-->
<!--<dependency>
<groupId>org.apache.httpcomponents.core5</groupId>
<artifactId>httpcore5-reactive</artifactId>
<version>5.3.3</version>
</dependency>-->
<!--<dependency>
<groupId>com.openai</groupId>
<artifactId>openai-java</artifactId>
<version>0.30.0</version>
</dependency>-->
<!--<dependency>
<groupId>com.agentsflex</groupId>
<artifactId>agents-flex-bom</artifactId>
<version>1.0.0-rc.6</version>
</dependency>
<dependency>
<groupId>com.agentsflex</groupId>
<artifactId>agents-flex-spring-boot-starter</artifactId>
<version>1.0.0-rc.6</version>
</dependency>-->
<!-- <dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-qdrant-store-spring-boot-starter</artifactId>

26
src/main/java/com/lanyuanxiaoyao/ai/analysis/AnalysisApplication.java
View File

@@ -1,11 +1,35 @@
package com.lanyuanxiaoyao.ai.analysis;
import java.net.http.HttpClient;
import lombok.extern.slf4j.Slf4j;
import org.springframework.boot.ApplicationArguments;
import org.springframework.boot.ApplicationRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Primary;
import org.springframework.http.client.JdkClientHttpRequestFactory;
import org.springframework.web.client.RestClient;
@Slf4j
@SpringBootApplication
public class AnalysisApplication {
public class AnalysisApplication implements ApplicationRunner {
public static void main(String[] args) {
SpringApplication.run(AnalysisApplication.class, args);
}
@Override
public void run(ApplicationArguments args) {
}
@Bean
@Primary
public RestClient.Builder clientBuilder() {
return RestClient.builder()
.requestFactory(new JdkClientHttpRequestFactory(
HttpClient.newBuilder()
.version(HttpClient.Version.HTTP_1_1)
.build()
));
}
}

203
src/main/java/com/lanyuanxiaoyao/ai/analysis/controller/ChatController.java
View File

@@ -1,10 +1,8 @@
package com.lanyuanxiaoyao.ai.analysis.controller;
import cn.hutool.core.util.IdUtil;
import cn.hutool.core.util.StrUtil;
import com.lanyuanxiaoyao.ai.analysis.tools.DatabaseTools;
import com.lanyuanxiaoyao.ai.analysis.tools.DatetimeTools;
import com.lanyuanxiaoyao.ai.analysis.tools.PromptTools;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
@@ -16,7 +14,6 @@ import org.springframework.web.bind.annotation.CrossOrigin;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.ResponseBody;
import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
@Slf4j
@@ -30,25 +27,6 @@ public class ChatController {
this.client = builder.build();
}
@ResponseBody
@PostMapping(value = "", produces = MediaType.TEXT_PLAIN_VALUE)
public String chat(
@RequestParam("prompt") String prompt,
@RequestParam(value = "use_tw", defaultValue = "false") Boolean useTw,
@RequestParam(value = "use_database", defaultValue = "false") Boolean useDatabase,
@RequestParam(value = "database_url", required = false) String databaseUrl,
@RequestParam(value = "database_username", required = false) String databaseUsername,
@RequestParam(value = "database_password", required = false) String databasePassword,
@RequestParam(value = "database_name", required = false) String databaseName
) {
logParameters(prompt, useTw, useDatabase, databaseUrl, databaseUsername, databasePassword, databaseName);
return client.prompt()
.system("始终在中文语境下回答")
.user(prompt)
.call()
.content();
}
@PostMapping(value = "stream", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
public SseEmitter chatStream(
@RequestParam("prompt") String prompt,
@@ -58,29 +36,161 @@ public class ChatController {
@RequestParam(value = "database_username", required = false) String databaseUsername,
@RequestParam(value = "database_password", required = false) String databasePassword,
@RequestParam(value = "database_name", required = false) String databaseName
) {
log.info("chatStream");
logParameters(prompt, useTw, useDatabase, databaseUrl, databaseUsername, databasePassword, databaseName);
) throws IOException {
log.info("prompt: {}", prompt);
log.info("use_tw: {}", useTw);
log.info("use_database: {}", useDatabase);
if (useDatabase) {
log.info("database_url: {}", databaseUrl);
log.info("database_username: {}", databaseUsername);
log.info("database_password: {}", databasePassword);
log.info("database_name: {}", databaseName);
}
SseEmitter emitter = new SseEmitter();
StringBuilder systemPrompt = new StringBuilder("始终在中文语境下回答\n\n");
systemPrompt
.append("当遇到数据对比、占比、趋势等场景相关的提问，优先考虑使用mermaid绘制图表，图文结合来回答")
.append(PromptTools.MERMAID_PROMPT)
.append("\n\n");
List<Object> tools = new ArrayList<>();
tools.add(new DatetimeTools());
List<String> prompts = new ArrayList<>();
// language=TEXT
prompts.add("""
你是一名服务器主机运维管理员，对于用户提出的问题，你会尝试从多个方面思考分析，通过多种角度进行研究，使用尽可能多的数据对比对用户的问题进行回答
你会积极使用表格、echarts图表等形式对数据进行分类、统计，力求能直观表达数据之间的关系和趋势，尤其是用户问题中出现“趋势”、“占比”、“对比”等字眼的时候
你始终会在中文语境下回答，对于用户的每个问题，先提出4个和用户提问最为相关的问题，针对以上5个问题分别进行回答
对于echarts图表，严格按照如下格式进行绘制，这部份代码必须新起一段
```echarts
(这里是echarts的json配置)
```
你能够生成echarts json配置以在回答中可视化数据。当您认为图表能更好地说明信息或增强回答的可理解性时，应创建相应的echarts json配置。
请遵循以下步骤生成配置：
1. 确定是否需要图表：评估用户的问题或任务是否涉及数据可视化，例如比较数据、展示趋势或比例。
2. 选择合适的图表类型：根据数据特性和表达目的选择图表类型。例如：
- 柱状图（bar）：适合比较分类数据，如不同国家的销量。
- 折线图（line）：适合展示时间序列或趋势，如温度变化。
- 饼图（pie）：适合展示比例或百分比，如市场份额。
3. 准备数据：将数据组织成echarts可理解的格式。例如：
- 柱状图/折线图：x轴为类别或时间点，y轴为数值。
- 饼图：包含名称（name）和值（value）的数组。
4. 生成json配置：基于echarts的配置规则，创建有效的json对象，包括标题（title）、轴（xAxis/yAxis，如适用）、系列（series）等必要组件。
5. 正确格式化输出：确保json配置是有效的字符串，使用双引号包裹字符串值，数值不加引号。
以下是不同图表类型的示例，帮助您理解如何构建配置：
示例1：柱状图
场景：展示2023年五个城市的销售额。
数据：北京5000、上海4500、广州3000、深圳2800、杭州2000。
输出：
```echarts
{
"title": {
"text": "2023 年城市销售额"
},
"xAxis": {
"type": "category",
"data": ["北京", "上海", "广州", "深圳", "杭州"]
},
"yAxis": {
"type": "value",
"axisLabel": {
"formatter": "{value} 万"
}
},
"series": [
{
"data": [5000, 4500, 3000, 2800, 2000],
"type": "bar"
}
]
}
```
示例2：折线图
场景：展示某地区过去6个月的平均温度。
数据：1月 5°C、2月 8°C、3月 12°C、4月 18°C、5月 22°C、6月 25°C。
输出：
```echarts
{
"title": {
"text": "过去 6 个月平均温度"
},
"xAxis": {
"type": "category",
"data": ["1月", "2月", "3月", "4月", "5月", "6月"]
},
"yAxis": {
"type": "value",
"axisLabel": {
"formatter": "{value} °C"
}
},
"series": [
{
"data": [5, 8, 12, 18, 22, 25],
"type": "line"
}
]
}
```
示例3：饼图
场景：展示三种水果的市场份额。
数据：苹果40%、橙子35%、香蕉25%。
输出：
```echarts
{
"title": {
"text": "水果市场份额"
},
"series": [
{
"type": "pie",
"radius": "50%",
"data": [
{ "name": "苹果", "value": 40 },
{ "name": "橙子", "value": 35 },
{ "name": "香蕉", "value": 25 }
],
"label": {
"formatter": "{b}: {c}%"
}
}
]
}
```
注意事项
json格式：字符串值使用双引号（如"text"），数值不加引号（如5000），不能使用任何注释。
有效性：确保json配置语法正确，可直接用于echarts。
相关性：仅在图表能为回答增添价值时生成配置，避免不必要的可视化。""");
if (useDatabase) {
log.info("use database");
DatabaseTools databaseTools = new DatabaseTools(databaseUrl, databaseUsername, databasePassword);
systemPrompt.append("以下是Hudi数据库中已有表的详细信息，包含表名、表描述、字段名和字段描述，任何与这些表数据相关的问题，都优先查询数据库获取答案\n");
systemPrompt.append(databaseTools.getTableInformation(databaseName)).append("\n");
systemPrompt.append("任何使用Hudi数据库的数据的回答都必须从实际的数据中获取，严禁虚构任何下列信息中不存在的表或表字段，没有描述的表或字段可以从表名或字段名中推测，如果找不到答案，就回复从数据库中没有找到相关数据\n");
// language=TEXT
prompts.add("""
你将所管理的主机信息记录在据数据库中schema名为main、表名为host_assets的MySQL表中，任何关于主机的数据的回答都必须从实际的数据中获取，严禁虚构任何不存在的表或表字段，没有描述的表或字段可以从表名或字段名中推测，如果找不到答案，就回复“数据库中没有找到相关数据”
任何时候你都只能查询数据库，不会对数据库进行任何修改操作，也不会查询除host_assets外的任何表，数据库查询结果中出现null表示没有数据
用户问题中提到的关键词通常不是精准的字段名或字段内容，你需要结合精确匹配或模糊匹配等等多种方式综合查询数据，必要的时候可以多次查询数据库综合查询数据
以下是host_assets表的详细信息，包含表名、表描述、字段名和字段描述""");
prompts.add(databaseTools.getTableInformation(databaseName));
prompts.add("");
tools.add(databaseTools);
}
client.prompt()
.system(systemPrompt.toString())
String content = client.prompt()
.system(String.join("\n", prompts))
.user(prompt)
.tools(tools.toArray(new Object[]{}))
.call()
.content();
log.info("{}", content);
for (String line : content.split("\n")) {
emitter.send(StrUtil.format("#/#{}#/#", line));
emitter.send(StrUtil.format("#/#{}#/#", "\n"));
}
emitter.send("#CLOSE#");
emitter.complete();
/* client.prompt()
.system(String.join("\n", prompts))
.user(prompt)
.tools(tools.toArray(new Object[]{}))
.stream()
@@ -94,20 +204,15 @@ public class ChatController {
}
},
emitter::completeWithError,
emitter::complete
);
() -> {
try {
emitter.send("#CLOSE#");
emitter.complete();
} catch (IOException e) {
emitter.completeWithError(e);
}
}
); */
return emitter;
}
private void logParameters(String prompt, Boolean useTw, Boolean useDatabase, String databaseUrl, String databaseUsername, String databasePassword, String databaseName) {
log.info("prompt: {}", prompt);
log.info("use_tw: {}", useTw);
log.info("use_database: {}", useDatabase);
if (useDatabase) {
log.info("database_url: {}", databaseUrl);
log.info("database_username: {}", databaseUsername);
log.info("database_password: {}", databasePassword);
log.info("database_name: {}", databaseName);
}
}
}

1
src/main/java/com/lanyuanxiaoyao/ai/analysis/tools/DatabaseTools.java
View File

@@ -52,6 +52,7 @@ public class DatabaseTools {
}
builder.append("\n");
}
log.info("\n{}", builder);
return builder.toString();
} catch (SQLException e) {
return StrUtil.format("查询失败，失败提示：{}", e.getMessage());

7
src/main/java/com/lanyuanxiaoyao/ai/analysis/tools/DatetimeTools.java
View File

@@ -3,7 +3,6 @@ package com.lanyuanxiaoyao.ai.analysis.tools;
import java.time.LocalDateTime;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.tool.annotation.Tool;
import org.springframework.ai.tool.function.FunctionToolCallback;
/**
* @author lanyuanxiaoyao
@@ -11,14 +10,8 @@ import org.springframework.ai.tool.function.FunctionToolCallback;
*/
@Slf4j
public class DatetimeTools {
public static final FunctionToolCallback<Void, LocalDateTime> call = FunctionToolCallback.builder("current_time", () -> LocalDateTime.now())
.description("返回当前的日期时间")
.inputType(Void.class)
.build();
@Tool(description = "返回当前的日期时间")
public String currentTime() {
return LocalDateTime.now().toString();
}
}

32
src/main/resources/application.yml
View File

@@ -4,12 +4,32 @@ spring:
application:
name: ai-analysis
ai:
# openai:
# base-url: https://api.deepseek.com
# api-key: "sk-c338699912bb4ad891874a9ab713e735"
# chat:
# options:
# model: "deepseek-chat"
# ai:
# openai:
# base-url: http://132.121.116.79:31348
# api-key: "nopassword"
# chat:
# options:
# model: "deepseek-coder"
# openai:
# base-url: http://132.121.116.70:31409
# api-key: "nopassword"
# chat:
# options:
# model: "telechat2-7B"
openai:
base-url: https://api.siliconflow.cn
api-key: "sk-xrguybusoqndpqvgzgvllddzgjamksuecyqdaygdwnrnqfwo"
base-url: https://open.bigmodel.cn/api/paas/v4
api-key: "d1e97306540d12bb2f834be961fcacb1.SNBShlCxWYJCx0qZ"
chat:
completions-path: /chat/completions
options:
model: "Qwen/Qwen2.5-32B-Instruct"
model: "glm-4-flash"
ollama:
chat:
model: "qwen2.5:7b"
@@ -20,12 +40,10 @@ spring:
chat:
options:
model: "glm-4-flash"
# openai:
# base-url: http://173.0.59.240:8093
# api-key: test
mvc:
async:
request-timeout: -1
logging:
level:
org.springframework.ai: trace
# root: debug
org.springframework.ai: debug

51
src/test/java/com/lanyuanxiaoyao/ai/analysis/FakeData.java Normal file
View File

@@ -0,0 +1,51 @@
package com.lanyuanxiaoyao.ai.analysis;
import cn.hutool.core.util.RandomUtil;
import cn.hutool.core.util.StrUtil;
import cn.hutool.db.DbUtil;
import cn.hutool.db.Entity;
import cn.hutool.db.Session;
import cn.hutool.db.ds.simple.SimpleDataSource;
import java.sql.SQLException;
import java.sql.Statement;
import java.util.ArrayList;
import java.util.List;
import java.util.Locale;
import lombok.extern.slf4j.Slf4j;
import net.datafaker.Faker;
/**
* @author lanyuanxiaoyao
* @version 20250301
*/
@Slf4j
public class FakeData {
public static void main(String[] args) {
Faker faker = new Faker(new Locale("zh-CN"));
try (Session session = DbUtil.newSession(new SimpleDataSource("jdbc:mysql://localhost:3307/main", "test", "test"))) {
String fieldName = "system_name";
List<String> items = new ArrayList<>();
List<Entity> entities = session.query(StrUtil.format("select distinct {} as name from host_assets where {} is not null", fieldName, fieldName));
for (Entity entity : entities) {
/* Set<String> fields = entity.getFieldNames();
for (String field : fields) {
items.add(entity.get(field).toString());
} */
items.add(entity.getStr("name"));
}
for (String item : items) {
List<String> tags = List.of("数据治理", "数据安全管控", "区块链应用", "标签管理", "数据集市");
String shadow = StrUtil.format("大数据湖{}-{}", RandomUtil.randomInt(50), tags.get(RandomUtil.randomInt(tags.size())));
String domain = StrUtil.format("b{}.hdp.dc", RandomUtil.randomInt(10));
String sql = StrUtil.format("update host_assets set {} = '{}', host_name = '{}' where {} = '{}'", fieldName, shadow, domain, fieldName, item);
log.info("{}", sql);
try (Statement statement = session.getConnection().createStatement()) {
statement.execute(sql);
}
}
} catch (SQLException e) {
log.error(e.getMessage(), e);
}
}
}

10
test.http
View File

@@ -1,5 +1,11 @@
### Chat
POST http://localhost:7891/chat/stream
POST http://localhost:7891/chat
Content-Type: application/x-www-form-urlencoded
prompt=tb_app_collect_table_info中src_schema字段各有多少记录&use_database=true&database_url=jdbc:mysql://localhost:3307/main&database_username=test&database_password=test&database_name=main
prompt=你好
### Test local
POST http://132.121.116.79:31348/v1/chat/completions
Content-Type: application/json
{"messages":[{"content":"你好","role":"user"}],"model":"deepseek-coder","stream":true,"temperature":0.7}