visactor / vmind Goto Github PK

Version

1.2.4

Link to Minimal Reproduction

null

Steps to Reproduce

Key,BP,Count\nJIRA-27358,BP1.4.1,1\nJIRA-27356,BP1.4.1,1\nJIRA-27350,BP1.5.0,1\nJIRA-27349,BP1.4.1,1\nJIRA-27348,BP1.4.1,1\nJIRA-27347,BP1.4.1,1\nJIRA-27344,BP1.5.0,1\nJIRA-27343,BP1.4.1,1\nJIRA-27339,BP1.4.1,1\nJIRA-27338,BP1.4.1,1\nJIRA-27336,BP1.4.1,1\nJIRA-27335,BP1.4.1,1\nJIRA-27334,BP1.4.1,1\nJIRA-27333,BP1.5.0,1\nJIRA-27331,BP1.4.1,1\nJIRA-27330,BP1.4.1,1\nJIRA-27322,BP1.4.1,1\nJIRA-27321,BP1.4.1,1\nJIRA-27320,BP1.4.0,1\nJIRA-27319,BP1.4.0,1\nJIRA-27316,BP1.4.0,1\nJIRA-27315,BP1.4.1,1\nJIRA-27314,BP1.5.0,1\nJIRA-27311,BP1.4.1,1\nJIRA-27310,BP1.4.1,1\nJIRA-27309,BP1.4.1,1\nJIRA-27308,BP1.4.1,1\nJIRA-27307,BP1.4.1,1\nJIRA-27306,BP1.4.1,1\nJIRA-27305,BP1.4.1,1\nJIRA-27304,BP1.4.1,1\nJIRA-27303,BP1.4.1,1\nJIRA-27302,BP1.4.1,1\nJIRA-27301,BP1.4.1,1\nJIRA-27300,BP1.4.1,1\nJIRA-27299,BP1.4.1,1\nJIRA-27297,BP1.4.1,1\nJIRA-27296,BP1.4.1,1\nJIRA-27295,BP1.4.1,1\nJIRA-27294,BP1.4.1,1\nJIRA-27293,BP1.4.1,1\nJIRA-27292,BP1.4.1,1\nJIRA-27291,BP1.4.1,1\nJIRA-27290,BP1.5.0,1\nJIRA-27289,BP1.4.1,1\nJIRA-27281,BP1.4.1,1\nJIRA-27279,BP1.4.0,1\nJIRA-27278,BP1.4.1,1\nJIRA-27277,BP1.4.0,1\nJIRA-27276,BP1.4.0,1

按照bp分类统计count之和，绘制柱状堆叠图

Current Behavior

Expected Behavior

使用聚合后的数据生成图表

Environment

- OS:
- Browser:
- Framework:

Any additional comments?

No response

图表生成允许用户指定支持的图表类型列表

• 使用JS请求open api，增加用户意图输入框

Version

1.1.0

Link to Minimal Reproduction

null

Steps to Reproduce

userPrompt: 请推荐最佳的数据可视化展现方式
GPT 3.5 and skylark2 pro all throw an error.

Current Behavior

Expected Behavior

generate chart normally

Environment

- OS:
- Browser:
- Framework:

Any additional comments?

No response

also add unit test for data aggregation

Version

1.2.3

Link to Minimal Reproduction

null

Steps to Reproduce

帮我展示不同区域各商品销售额
商品名称,region,销售额
可乐,south,2350
可乐,east,1027
可乐,west,1027
可乐,north,1027
雪碧,south,215
雪碧,east,654
雪碧,west,159
雪碧,north,28
芬达,south,345
芬达,east,654
芬达,west,2100
芬达,north,1679
醒目,south,1476
醒目,east,830
醒目,west,532
醒目,north,498

const { fieldInfo, dataset } = await vmind.current.parseCSVData(csvData, describe);
      const { spec, time } = await vmind.current.generateChart(
        describe,
        fieldInfo,
        dataset,
      );

Current Behavior

{
"sql": "SELECT Product name, region, SUM(Sales) AS total_sales FROM dataSource GROUP BY Product name, region",
"fieldInfo": [
{
"fieldName": "Product name",
"description": "Represents the name of the product."
},
{
"fieldName": "region",
"description": "Represents the region where the product is sold."
},
{
"fieldName": "total_sales",
"description": "An aggregated field representing the total sales amount of each product in each region. It is generated by summing up the sales values for each product in each region."
}
]
}
and the aggregated measure value is all 0

Expected Behavior

aggregate normally

Environment

- OS:
- Browser:
- Framework:

Any additional comments?

No response

What problem does this feature solve?

to increase the accuracy of chart generation, use vector database to query exapmles according to user's input and fill the result in chart generation prompt. This can be done when VMind has collected enough chart generation examples.

What does the proposed API look like?

queryExamples(userInput)

What problem does this feature solve?

there are 2 steps in skylark chart generation: chart type recommend and field map assign. If the second step fails, we cal also use the recommended chart type in the first step and use @visactor/chartadvisor to get the field map.

What does the proposed API look like?

none

1. 修改runApplication方法，当用户传入不支持的模型类型时，也可以采用默认策略执行任务

--data-raw '{"csvData":"filter_r,a_type_label,prr_tags,app_id,abtest_versions,r_reasons,r_tags,channel_id,region,uid,vid_int,timestamp,trace_id\r\n,,,1233,,,,112,US,7092296493822592046,,1708445808150,2024022016164529A8B0CD0A1AEBED59C1\r\n,,,1233,,,,57,US,7092296493822592046,,1708445389846,202402201609497136D67B0F97D0E072E4\r\n,,,1233,,,,81,US,7092296493822592046,,1708525298858,20240221142138A866F61C2102DE076789\r\n,,,1233,,,,112,US,7092296493822592046,,1708867031297,20240225131710A436704DA937A7C72C7E\r\n,,,1233,,,,112,US,7092296493822592046,,1708610066492,202402221354256D11E714CFF5812E5944\r\n,,,1233,,,,112,US,7092296493822592046,,1708867539587,20240225132539E1B41CFDC4CA6C7D6B23\r\n,,,1233,,,,112,US,7092296493822592046,,1708525412066,202402211423318BAA53BC0648780C1A50\r\n,,,1233,,,,112,US,7092296493822592046,,1708867378664,2024022513225849549B50310E70CCBCB0\r\n,,,1233,,,,112,US,7092296493822592046,,1708867413105,20240225132332AA2CFEF9F4DDAFC645F6\r\n,,,1233,,,,112,US,7092296493822592046,,1708867493206,20240225132452B1C06A032A58CDBE709D\r\n,,,1233,,,,81,US,7092296493822592046,,1708778690534,20240224124450B7DD2AF1F6456415B9D4\r\n,,,1233,,,,199,US,7092296493822592046,,1708446088298,20240220162127028C9A44474E820AD6D8\r\n,,,1233,,,,112,US,7092296493822592046,,1708525477107,202402211424363EB0AAE89450ADD82476\r\n,,,1233,,,,81,US,7092296493822592046,,1708866956971,20240225131556726A95F72884A245C786\r\n,,,1233,,,,81,US,7092296493822592046,,1708445383055,202402201609424EB937059B320908E945\r\n,,,1233,,,,81,US,7092296493822592046,,1708866955521,2024022513155557DCB3F6E16D834367BB\r\n,,,1233,,,,112,US,7092296493822592046,,1708866921143,20240225131520A834042EBFBFE69DEB8D\r\n,,,1233,,,,81,US,7092296493822592046,,1708445387314,20240220160947B7E58F06F01A600A1D89\r\n,,,1233,,,,57,US,7092296493822592046,,1708866705920,20240225131145BF96E65D2170CE9EDD74\r\n,,,1233,,,,81,US,7092296493822592046,,1708696269252,20240223135109AD8C4B063FF90E11DE4A\r\n,,,1233,,,,81,US,7092296493822592046,,1708525300274,202402211421406DA69D0D4B109907247B\r\n,,,1233,,,,112,US,7092296493822592046,,1708696316767,20240223135156C054F110E2DCEF2A17FF\r\n,,,1233,,,,57,US,7092296493822592046,,1708780057459,20240224130737AD1422BAA86115E48421\r\n,,,1233,,,,81,US,7092296493822592046,,1708778691908,2024022412445168962D3FED452616CBC8\r\n,,,1233,,,,112,US,7092296493822592046,,1708867293249,20240225132132E7A7B63D8806E7B2669C\r\n,,,1233,,,,57,US,7092296493822592046,,1708830915190,20240225031514DA8D786AF956F3B3151E\r\n,,,1233,,,,199,US,7092296493822592046,,1708867020337,20240225131700BA96658227C3263D9FFB\r\n,,,1233,,,,112,US,7092296493822592046,,1708610183381,202402221356226A7787CFFCB3B3114B59\r\n,,,1233,,,,112,US,7092296493822592046,,1708445377163,20240220160936953B3302117F81C114EC\r\n,,,1233,,,,112,US,7092296493822592046,,1708445576957,20240220161256D50449D1328057A6BD06\r\n,,,1233,,,,112,US,7092296493822592046,,1708829558775,20240225025237CBDEFBA79C617EBD9D1C\r\n,,,1233,,,,112,US,7092296493822592046,,1708445743592,20240220161542266C6CB4CBA382E968C2\r\n,,,1233,,,,112,US,7092296493822592046,,1708445805356,2024022016164529A8B0CD0A1AEBED59C1\r\n,,,1233,,,,112,US,7092296493822592046,,1708829643717,20240225025403D1FC6676586CB0905BA4\r\n,,,1233,,,,112,US,7092296493822592046,,1708867458566,20240225132418AA2CFEF9F4DDAFC64C08\r\n,,,1233,,,,57,US,7092296493822592046,,1708829561662,20240225025241AD1DEF6A5E605EB09A41\r\n,,,1233,,,,199,US,7092296493822592046,,1708446060872,2024022016210090140F31FA12220A7D07\r\n,,,1233,,,,57,US,7092296493822592046,,1708866924109,202402251315234A814EC71071DF0BD7BA\r\n,,,1233,,,,112,US,7092296493822592046,,1708696468585,2024022313542700D9ED5E8EF761717DB0\r\n,,,1233,,,,112,US,7092296493822592046,,1708696711378,202402231358302CEAD44D98039B2DD7F7\r\n,,,1233,,,,112,US,7092296493822592046,,1708696888515,202402231401289ACBCA53809D603CB427\r\n,,,1233,,,,112,US,7092296493822592046,,1708697684980,20240223141444F63C2904943A35394266\r\n,,,1233,,,,112,US,7092296493822592046,,1708696523386,2024022313552333351F9918D7AEFBC917\r\n,,,1233,,,,112,US,7092296493822592046,,1708778718828,20240224124518678C6C73CA659783014F\r\n,,,1233,,,,199,US,7092296493822592046,,1708867002606,202402251316421204BD6B6E8A1543DF6D\r\n,,,1233,,,,81,US,7092296493822592046,,1708610072970,20240222135432AAB3121782186419DC89\r\n,,,1233,,,,36,US,7092296493822592046,,1708615362521,20240222152241EF0B669DEEE0E496F96F\r\n,,,1233,,,,112,US,7092296493822592046,,1708778675358,2024022412443493EB0DEC9C052B74105B\r\n,,,1233,,,,81,US,7092296493822592046,,1708610087681,202402221354477146569C78F80D18EA96\r\n,,,1233,,,,112,US,7092296493822592046,,1708697729569,2024022314152925857C95174C5170FFE1\r\n,,,1233,,,,112,US,7092296493822592046,,1708830914020,20240225031512773AB90FAACEEAAB0EC3\r\n,,,1233,,,,57,US,7092296493822592046,,1708525297721,2024022114213712CCCD5815C1AD2EC79C\r\n,,,1233,,,,112,US,7092296493822592046,,1708696389687,2024022313530844B7446267116F43B927\r\n,,,1233,,,,112,US,7092296493822592046,,1708696778238,20240223135937AE668F844C9E674014AA\r\n,,,1233,,,,112,US,7092296493822592046,,1708778853424,202402241247320E708EB8477261C354EC\r\n,,,1233,,,,57,US,7092296493822592046,,1708612888542,202402221441278D67B0C690E5271CF702\r\n,,,1233,,,,112,US,7092296493822592046,,1708525497626,202402211424572C71AF81DF15F3D58A12\r\n,,,1233,,,,112,US,7092296493822592046,,1708696264074,202402231351039FE818735839B051969E\r\n,,,1233,,,,112,US,7092296493822592046,,1708696837646,202402231400365EC5C2DC236F465D4E58\r\n,,,1233,,,,112,US,7092296493822592046,,1708866686273,202402251311254A6702F97C70EFB028C9\r\n,,,1233,,,,81,US,7092296493822592046,,1708696270906,202402231351101A6B548FA0EF34105774\r\n,,,1233,,,,112,US,7092296493822592046,,1708612905678,202402221441452F5FE2073237C10F57E7\r\n,,,1233,,,,199,US,7092296493822592046,,1708446029499,20240220162029CC9A407970F27F0A4877\r\n,,,1233,,,,112,US,7092296493822592046,,1708867137922,20240225131856472BE356E5350FABC73D\r\n,,,1233,,,,112,US,7092296493822592046,,1708610245415,2024022213572577901A133CFB2CCC0B92\r\n,,,1233,,,,57,US,7092296493822592046,,1708696266988,20240223135106160FFA6ADCFEDF73CA64\r\n,,,1233,,,,112,US,7092296493822592046,,1708615460784,202402221524199564A8038AF9AA36444C\r\n,,,1233,,,,57,US,7092296493822592046,,1708778687975,20240224124447386C3BC31D8413A29048\r\n,,,1233,,,,81,US,7092296493822592046,,1708778691688,20240224124451E04E8393FD062E163F63\r\n,,,1233,,,,112,US,7092296493822592046,,1708780055058,2024022413073490F4C59A20694E5BAB87\r\n,,,1233,,,,112,US,7092296493822592046,,1708866728857,202402251312084C2A820F878915C26092\r\n,,,1233,,,,57,US,7092296493822592046,,1708610081294,202402221354413A683CB601C0DB53ED1C\r\n,,,1233,,,,112,US,7092296493822592046,,1708525451364,2024022114241123B931A468FC56D27B6C","prompt":"show me the distribution","model":"gpt-3.5-turbo"}'

can use alasql https://github.com/AlaSQL/alasql to execute sql query

1. 根据当前环境，调用VChart图片导出API生成图表图片
2. 调研canvas图表转GIF和视频方案，为VMind增加图表转gif、视频接口
   接口示例：

const res=vmind.exportChart(spec,type) //type可以是image, gif或video

Version

1.2.3

Link to Minimal Reproduction

null

Steps to Reproduce

帮我展示north区域排名前三的商品销售额

商品名称,region,销售额
可乐,south,2350
可乐,east,1027
可乐,west,1027
可乐,north,1027
雪碧,south,215
雪碧,east,654
雪碧,west,159
雪碧,north,28
芬达,south,345
芬达,east,654
芬达,west,2100
芬达,north,1679
醒目,south,1476
醒目,east,830
醒目,west,532
醒目,north,498

Current Behavior

[
{
"商品名称": "可乐",
"total_sales": 1027
},
{
"商品名称": "雪碧",
"total_sales": 28
},
{
"商品名称": "芬达",
"total_sales": 1679
}
]

Expected Behavior

dataset sort by total_sales

Environment

- OS:
- Browser:
- Framework:

Any additional comments?

No response

use @visactor/chart-advisor as a fallback plan. develop the chart-advisor task node

add chartType and cell in chart generation result

response of LLM need to be patched. We can divide this prgress into pipelines to make it more clear and improve maintainability

1. 内置几套常见的VChart主题和图表助手主题：https://www.visactor.io/vchart/theme/playground
2. VMind.generateChart接口，支持传入theme参数
3. 图表生成pipeline将theme应用到图表spec上
4. 修改默认的主题样式

describe taskNodes and applications using a meta like this:

dataset:
[
{
"year": 2013,
"GDP": 593000
},
{
"year": 2022,
"GDP": 1210000
},
{
"year": 2013,
"GDPPerCapita": 43497
},
{
"year": 2022,
"GDPPerCapita": 85698
}
]

prompt: 请绘制一个折线图，展示2013年至2022年**的GDP和人均GDP的变化情况

model：skylark-2-pro
sql: "SELECT city, SUM(sales) AS total_sales FROM VMind_data_source GROUP BY city",
user prompt: 按时间看杭州销量
fieldInfo：[
{
"fieldName": "key",
"type": "int",
"role": "measure",
"domain": [
0,
499
]
},
{
"fieldName": "id",
"type": "int",
"role": "measure",
"domain": [
1,
502
]
},
{
"fieldName": "order_id",
"type": "date",
"role": "dimension",
"domain": [
"US-2019-1357144",
"CN-2019-1973789",
"US-2019-3017568",
"CN-2018-2975416",
"CN-2017-4497736",
"CN-2016-4195213",
"CN-2019-5801711",
"CN-2017-2752724",
"US-2018-2511714",
"CN-2019-5631342",
"US-2018-4150614",
"CN-2019-4364300",
"CN-2019-3230180",
"US-2018-1966627",
"CN-2018-1190387",
"CN-2018-3216455",
"CN-2018-4690757",
"CN-2018-4674220",
"US-2018-3857264",
"CN-2018-4054371"
]
},
{
"fieldName": "order_date",
"type": "string",
"role": "dimension",
"domain": [
"2019/4/27",
"2019/6/15",
"2019/6/16",
"2019/12/9",
"2018/5/31",
"2017/10/27",
"2016/12/22",
"2019/6/1",
"2017/6/5",
"2018/11/22",
"2019/10/2",
"2019/10/3",
"2018/6/7",
"2019/12/12",
"2019/9/28",
"2018/11/19",
"2018/2/28",
"2018/9/3",
"2018/9/17",
"2018/7/2"
]
},
{
"fieldName": "delivery_date",
"type": "string",
"role": "dimension",
"domain": [
"2019/4/29",
"2019/6/16",
"2019/6/19",
"2019/12/10",
"2018/6/2",
"2017/10/31",
"2016/12/24",
"2019/6/6",
"2017/6/9",
"2018/11/25",
"2019/10/3",
"2019/10/4",
"2019/10/5",
"2018/6/14",
"2019/12/15",
"2019/10/2",
"2018/11/23",
"2018/3/1",
"2018/9/6",
"2018/9/21"
]
},
{
"fieldName": "delivery_method",
"type": "string",
"role": "dimension",
"domain": [
"二级",
"标准级",
"一级",
"当日"
]
},
{
"fieldName": "customer_id",
"type": "date",
"role": "dimension",
"domain": [
"曾惠-14485",
"许安-10165",
"宋良-17170",
"万兰-15730",
"俞明-18325",
"谢雯-21700",
"康青-19585",
"赵婵-10885",
"刘斯-20965",
"白鹄-14050",
"贾彩-10600",
"马丽-15910",
"宋栋-12310",
"巩虢-13495",
"常松-20575",
"田黎-16450",
"谭乐-17815",
"徐岱-11875",
"武杰-14815",
"吕兰-15700"
]
},
{
"fieldName": "customer_name",
"type": "string",
"role": "dimension",
"domain": [
"曾惠",
"许安",
"宋良",
"万兰",
"俞明",
"谢雯",
"康青",
"赵婵",
"刘斯云",
"白鹄",
"贾彩",
"马丽",
"宋栋",
"巩虢",
"常松",
"田黎明",
"谭乐",
"徐岱",
"武杰",
"吕兰"
]
},
{
"fieldName": "customer_type",
"type": "string",
"role": "dimension",
"domain": [
"公司",
"消费者",
"小型企业"
]
},
{
"fieldName": "city",
"type": "string",
"role": "dimension",
"domain": [
"杭州",
"内江",
"镇江",
"汕头",
"景德镇",
"榆林",
"哈尔滨",
"青岛",
"徐州",
"上海",
"温岭",
"唐山",
"宁波",
"厦门",
"宿州",
"兰州",
"淮阴",
"肇源",
"南昌",
"合肥"
]
},
{
"fieldName": "province",
"type": "string",
"role": "dimension",
"domain": [
"浙江",
"四川",
"江苏",
"广东",
"江西",
"陕西",
"黑龙江",
"山东",
"上海",
"河北",
"福建",
"安徽",
"甘肃",
"吉林",
"辽宁",
"湖北",
"河南",
"湖南",
"北京",
"重庆"
]
},
{
"fieldName": "country_or_region",
"type": "string",
"role": "dimension",
"domain": [
"**"
]
},
{
"fieldName": "area",
"type": "string",
"role": "dimension",
"domain": [
"华东",
"西南",
"中南",
"西北",
"东北",
"华北"
]
},
{
"fieldName": "product_id",
"type": "date",
"role": "dimension",
"domain": [
"办公用-用品-10002717",
"办公用-信封-10004832",
"办公用-装订-10001505",
"办公用-用品-10003746",
"办公用-器具-10003452",
"技术-设备-10001640",
"办公用-装订-10001029",
"家具-椅子-10000578",
"办公用-纸张-10001629",
"办公用-系固-10004801",
"技术-设备-10000001",
"技术-复印-10002416",
"办公用-信封-10000017",
"技术-配件-10004920",
"技术-电话-10004349",
"办公用-器具-10003582",
"办公用-标签-10004648",
"技术-配件-10001200",
"办公用-用品-10000039",
"办公用-装订-10004589"
]
},
{
"fieldName": "product_type",
"type": "string",
"role": "dimension",
"domain": [
"办公用品",
"技术",
"家具"
]
},
{
"fieldName": "product_sub_type",
"type": "string",
"role": "dimension",
"domain": [
"用品",
"信封",
"装订机",
"器具",
"设备",
"椅子",
"纸张",
"系固件",
"复印机",
"配件",
"电话",
"标签",
"书架",
"用具",
"收纳具",
"美术",
"桌子"
]
},
{
"fieldName": "product_name",
"type": "string",
"role": "dimension",
"domain": [
"Fiskars 剪刀, 蓝色",
"GlobeWeis 搭扣信封, 红色",
"Cardinal 孔加固材料, 回收",
"Kleencut 开信刀, 工业",
"KitchenAid 搅拌机, 黑色",
"柯尼卡 打印机, 红色",
"Ibico 订书机, 实惠",
"SAFCO 扶手椅, 可调",
"Green Bar 计划信息表, 多色",
"Stockwell 橡皮筋, 整包",
"爱普生 计算器, 耐用",
"惠普 墨水, 红色",
"Jiffy 局间信封, 银色",
"SanDisk 键区, 可编程",
"诺基亚 充电器, 蓝色",
"KitchenAid 冰箱, 黑色",
"Novimex 圆形标签, 红色",
"Memorex 键盘, 实惠",
"Acme 尺子, 工业",
"Avery 孔加固材料, 耐用"
]
},
{
"fieldName": "sales",
"type": "float",
"role": "measure",
"domain": [
29.4,
35621.355
]
},
{
"fieldName": "amount",
"type": "int",
"role": "measure",
"domain": [
1,
14
]
},
{
"fieldName": "discount",
"type": "float",
"role": "measure",
"domain": [
0,
0.8
]
},
{
"fieldName": "profit",
"type": "float",
"role": "measure",
"domain": [
-4988.2,
7214.76
]
}
]

What problem does this feature solve?

user must specify dimension value in their prompt, such as "帮我展示north区域排名前三的商品销售额" because LLM doesn't know dimension values when generating sql. If we add domain of dimensions in fieldInfo, user can use "帮我展示北方排名前三的商品销售额"

What does the proposed API look like?

[
{
"fieldName": "商品名称",
"type": "string",
"role": "dimension",
domain:['可乐', '雪碧', '芬达', '醒目']
},
{
"fieldName": "region",
"type": "string",
"role": "dimension",
domain:['north', 'south', 'west', 'east']
},
{
"fieldName": "销售额",
"type": "int",
"role": "measure"
}
]

Version

1.2.4-alpha.5

Link to Minimal Reproduction

null

Steps to Reproduce

see feat/node-support branch.

Current Behavior

gif size error：

Expected Behavior

gif has the same size as jpg:

Environment

- OS:
- Browser:
- Framework:

Any additional comments?

No response

user need to generate a chart only according to fields in dataset. So we can offer a function to generate a spec without dataset, and user can add their own dataset after quering data.

cells generated by LLM will only have one y field, but may use another measure fields as color. In this case, we can fold the data by these two fields and show them with 1 y-axis.

新增一个API：VMind.extractDataFromText，从文本中提取json格式的数据，并生成可以用于绘图的指令。
示例：

const text="此前《金融时报》曾报道，2023年小红书营收达到37亿美元，净利润达到5亿美元，相比2022年收入20亿美元、亏损2亿美元，小红书不仅首次实现盈利，而且营收更是上了一个台阶。这很大程度得归功于广告业务多元化、高效率，以及电商业务带来的增量。"

const {data,instruction}=vmind.extractDataFromText(text,options)
console.log(data)
/*[{"name":"个护美妆","adRevenuePercentage":18},{"name":"时尚穿搭","adRevenuePercentage":12.5},{"name":"美食饮品","adRevenuePercentage":10},{"name":"家居家装","adRevenuePercentage":8.7},{"name":"母婴","adRevenuePercentage":7},{"name":"黄金珠宝","adRevenuePercentage":6},{"name":"汽车","adRevenuePercentage":5.3},{"name":"日化百货","adRevenuePercentage":5.1}]*/
console.log(instruction)
//请绘制一个饼图，展示小红书广告收入在各个行业中的占比

VMind图表智能生成模块接入组合图，使用同一份数据集，生成common chart，多个图表组合在一张图表中展示：

What problem does this feature solve?

thoughts: 选择日期字段作为 x 轴，ctr、gmv、检测_uv 作为 y 轴，因为没有颜色字段，所以 color 为空

x: date
y: ctr, gmv, detection_uv
color:

What does the proposed API look like?

use fold in chart-advisor package to handle this situation.