dev-QQq
qinzhenpen 2 years ago
parent 6a683e8363
commit df48a96bf0

@ -5,4 +5,4 @@ VITE_APP_TITLE = 数字营销实训系统
VITE_APP_ENV = 'development'
# 若依管理系统/开发环境
VITE_APP_BASE_API = 'http://192.168.2.28:9868'
VITE_APP_BASE_API = 'http://118.31.7.2:9868'

@ -2,7 +2,7 @@
* @Author: qinzhenpen qzp1807@126.com
* @Date: 2024-08-15 09:41:09
* @LastEditors: qinzhenpen qzp1807@126.com
* @LastEditTime: 2024-08-16 10:33:08
* @LastEditTime: 2024-08-17 11:30:38
* @FilePath: \vue3\src\store\modules\user.js
* @Description: 这是默认设置,请设置`customMade`, 打开koroFileHeader查看配置 进行设置: https://github.com/OBKoro1/koro1FileHeader/wiki/%E9%85%8D%E7%BD%AE
*/
@ -19,7 +19,7 @@ const useUserStore = defineStore(
avatar: '',
roles: [],
permissions: [],
userInfo: getUserInfo() ? JSON.parse(getUserInfo()) : {},
userInfo: getUserInfo(),
}),
actions: {
// 登录

@ -16,7 +16,7 @@ axios.defaults.headers['Content-Type'] = 'application/json;charset=utf-8'
const service = axios.create({
// axios中请求配置有baseURL选项表示请求URL公共部分
// baseURL: import.meta.env.VITE_APP_BASE_API,
baseURL:'http://192.168.2.28:9868/',
baseURL:'http://118.31.7.2:9868/',
// 超时
timeout: 10000
})
@ -43,21 +43,6 @@ service.interceptors.request.use(config => {
time: new Date().getTime()
}
const sessionObj = cache.session.getJSON('sessionObj')
if (sessionObj === undefined || sessionObj === null || sessionObj === '') {
cache.session.setJSON('sessionObj', requestObj)
} else {
const s_url = sessionObj.url; // 请求地址
const s_data = sessionObj.data; // 请求数据
const s_time = sessionObj.time; // 请求时间
const interval = 1000; // 间隔时间(ms),小于此时间视为重复提交
if (s_data === requestObj.data && requestObj.time - s_time < interval && s_url === requestObj.url) {
const message = '数据正在处理,请勿重复提交';
console.warn(`[${s_url}]: ` + message)
return Promise.reject(new Error(message))
} else {
cache.session.setJSON('sessionObj', requestObj)
}
}
}
return config
}, error => {

@ -46,12 +46,13 @@
</template>
<script setup>
import { MdPreview, MdCatalog } from "md-editor-v3";
import { getToken,getUserInfo } from '@/utils/auth'
import useUserStore from "@/store/modules/user";
import "md-editor-v3/lib/preview.css";
import * as AI from "@/api/AI.js";
import { marked } from "marked";
import "highlight.js/lib/common";
import hljs from "highlight.js";
import { getAssetsFile } from "@/utils/index.js";
import { computed, onMounted } from "vue";
const userStore = useUserStore();
const input = ref("");
const butFlag = ref(false);
const messages = reactive([]);
@ -98,6 +99,9 @@ const sendExample = (item) => {
input.value = item.text;
sendText();
};
const aiUserid=computed(()=>{
return getUserInfo() ? JSON.parse(getUserInfo()) : "";
})
const sendText = async () => {
if (input.value.trim() === "" || isRequestPending.value) return;
if (input.value.trim() === "") return;
@ -118,17 +122,17 @@ const sendText = async () => {
},
name: "",
role: "user",
userId: "512",
userId: aiUserid.value.userId,
},
];
const messageId = Date.now();
0;
const newMessage = reactive({ id: messageId, type: "ai-main", displayContent: "" });
messages.push(newMessage);
const resp = await fetch("http://192.168.2.28:9868/api/bigModule/createArticleByAi", {
const resp = await fetch("http://118.31.7.2:9868/api/bigModule/createArticleByAi", {
method: "POST",
headers: {
"Content-Type": "application/json",
Authorization: `Bearer ${getToken()}`,
},
body: JSON.stringify(sendData),
});
@ -174,7 +178,7 @@ const handleKeyDown = (event) => {
event.preventDefault();
sendText();
}
};
}
</script>
<style lang="scss" scoped>

@ -213,7 +213,7 @@ const downloadArticle=()=>{
return proxy.$modal.msgWarning("请先完成上一步")
}
answerRecord.value=2
window.open(`http://192.168.2.16:9868/api/stu/experimental/downloadImg?userId=${JSON.parse(getUserInfo()).userId}&TOKEN=${getToken()}`)
window.open(`http://118.31.7.2:9868/api/stu/experimental/downloadImg?userId=${JSON.parse(getUserInfo()).userId}&TOKEN=${getToken()}`)
}
//

@ -61,11 +61,11 @@
若以现有的蓝光光盘为计量标准那么 40ZB 的数据全部存入蓝光光盘所需要的光盘总重量将达到 424 艘尼米兹号航母的总重量而这些数据中 80% 是非结构化或半结构化类型的数据甚至更有一部分是不断变化的流数据因此数据的爆炸性增长态势以及其数据构成特点使得人们进入了大数据时代
</p>
<p> 一般认为大数据主要具有以下4个方面的典型特征即大量(Volume)多样(Variety)高速(Velocity)和价值(Value)即所谓的4V接下来通过一张图来具休描述</p>
<p><img src="../../../assets/images/szjj/u1592.png" alt=""></p>
<p><img src="@/assets/images/szjj/u1592.png" alt=""></p>
<p style="font-weight:600;"> Volume(大量)</p><p>大数据的特征首先就是数据规模大随着互联网物联网移动互联技术的发展人和事物的所有轨迹都可以被记录下来数据呈现出爆发性增长数据相关计量单位的换算关系如下表所示</p>
<p><img src="../../../assets/images/szjj/u1594.png" alt=""></p>
<p><img src="@/assets/images/szjj/u1594.png" alt=""></p>
<p>互联网每分钟产生的数据</p>
<p><img src="../../../assets/images/szjj/u1597.png" alt=""></p>
<p><img src="@/assets/images/szjj/u1597.png" alt=""></p>
<p style="font-weight:600;"> Variety(多样)</p><p>
数据来源的广泛性决定了数据形式的多样性我们把这些数据大致分为三类结构化的数据半结构化的数据和非结构化的数据<br/>
结构化的数据一般指的是关系型数据库中的数据例如MySQLOracle中的表中的数据如财务系统数据信息管理系统数据医疗系统数据等,其特点是数据间因果关系强这些数据中每一行的数据都保持着相同的数据格式有规律可循非常容易处理<br/>

@ -142,6 +142,8 @@
</template>
<script setup>
import * as API from "@/api/AI.js";
import * as marketingAlgorithmApi from "@/api/marketing-algorithm.js";
import useAlgorithmStore from "@/store/modules/algorithm.js";
import useUserStore from "@/store/modules/user";
@ -157,9 +159,6 @@ const n_dataTableQuery = ref({
const dialogVisible = ref(false);
//
const modelParams = reactive([
{
name: "统计量",
},
{
name: "平均数",
},
@ -224,15 +223,13 @@ const preProcessText = ref({
const g_modelParameter = ref([]);
//
const preProcess = (tetx) => {
marketingAlgorithmApi
.getMarketingAlgorithmPreprocessing({
mapList: analysisData.value,
method: preProcessText.value.text2,
userId: n_dataTableQuery.value.userId,
})
.then((res) => {
analysisData.value = res.data;
});
API.dataPreprocessing({
mapList: analysisData.value,
method: preProcessText.value.text2,
userId: n_dataTableQuery.value.userId,
}).then((res) => {
analysisData.value = res.data;
});
};
//
const taskSubmit = () => {

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