Files
FastGPT/packages/service/core/app/utils.ts
Archer e25d7efb5b feature: V4.11.1 (#5350)
* perf: system toolset & mcp (#5200)

* feat: support system toolset

* fix: type

* fix: system tool config

* chore: mcptool config migrate

* refactor: mcp toolset

* fix: fe type error

* fix: type error

* fix: show version

* chore: support extract tool's secretInputConfig out of inputs

* chore: compatible with old version mcp

* chore: adjust

* deps: update dependency @fastgpt-skd/plugin

* fix: version

* fix: some bug (#5316)

* chore: compatible with old version mcp

* fix: version

* fix: compatible bug

* fix: mcp object params

* fix: type error

* chore: update test cases

* chore: remove log

* fix: toolset node name

* optimize app logs sort (#5310)

* log keys config modal

* multiple select

* api

* fontsize

* code

* chatid

* fix build

* fix

* fix component

* change name

* log keys config

* fix

* delete unused

* fix

* perf: log code

* perf: send auth code modal enter press

* fix log (#5328)

* perf: mcp toolset comment

* perf: log ui

* remove log (#5347)

* doc

* fix: action

* remove log

* fix: Table Optimization (#5319)

* feat: table test: 1

* feat: table test: 2

* feat: table test: 3

* feat: table test: 4

* feat: table test : 5 把maxSize改回chunkSize

* feat: table test : 6 都删了,只看maxSize

* feat: table test : 7 恢复初始,接下来删除标签功能

* feat: table test : 8 删除标签功能

* feat: table test : 9 删除标签功能成功

* feat: table test : 10 继续调试,修改trainingStates

* feat: table test : 11 修改第一步

* feat: table test : 12 修改第二步

* feat: table test : 13 修改了HtmlTable2Md

* feat: table test : 14 修改表头分块规则

* feat: table test : 15 前面表格分的太细了

* feat: table test : 16 改着改着表头又不加了

* feat: table test : 17 用CUSTOM_SPLIT_SIGN不行,重新改

* feat: table test : 18 表头仍然还会多加,但现在分块搞的合理了终于

* feat: table test : 19 还是需要搞好表头问题,先保存一下调试情况

* feat: table test : 20 调试结束,看一下replace有没有问题,没问题就pr

* feat: table test : 21 先把注释删了

* feat: table test : 21 注释replace都改了,下面切main分支看看情况

* feat: table test : 22 修改旧文件

* feat: table test : 23 修改测试文件

* feat: table test : 24 xlsx表格处理

* feat: table test : 25 刚才没保存先com了

* feat: table test : 26 fix

* feat: table test : 27 先com一版调试

* feat: table test : 28 试试放format2csv里

* feat: table test : 29 xlsx解决

* feat: table test : 30 tablesplit解决

* feat: table test : 31

* feat: table test : 32

* perf: table split

* perf: mcp old version compatibility (#5342)

* fix: system-tool secret inputs

* fix: rewrite runtime node i18n for system tool

* perf: mcp old version compatibility

* fix: splitPluginId

* fix: old mcp toolId

* fix: filter secret key

* feat: support system toolset activation

* chore: remove log

* perf: mcp update

* perf: rewrite toolset

* fix:delete variable id (#5335)

* perf: variable update

* fix: multiple select ui

* perf: model config move to plugin

* fix: var conflit

* perf: variable checker

* Avoid empty number

* update doc time

* fix: test

* fix: mcp object

* update count app

* update count app

---------

Co-authored-by: Finley Ge <32237950+FinleyGe@users.noreply.github.com>
Co-authored-by: heheer <heheer@sealos.io>
Co-authored-by: heheer <zhiyu44@qq.com>
Co-authored-by: colnii <1286949794@qq.com>
Co-authored-by: dreamer6680 <1468683855@qq.com>
2025-08-01 16:08:20 +08:00

204 lines
6.2 KiB
TypeScript

import { MongoDataset } from '../dataset/schema';
import { getEmbeddingModel } from '../ai/model';
import { FlowNodeTypeEnum } from '@fastgpt/global/core/workflow/node/constant';
import { NodeInputKeyEnum } from '@fastgpt/global/core/workflow/constants';
import type { StoreNodeItemType } from '@fastgpt/global/core/workflow/type/node';
import { getChildAppPreviewNode } from './plugin/controller';
import { PluginSourceEnum } from '@fastgpt/global/core/app/plugin/constants';
import { authAppByTmbId } from '../../support/permission/app/auth';
import { ReadPermissionVal } from '@fastgpt/global/support/permission/constant';
import { getErrText } from '@fastgpt/global/common/error/utils';
import { splitCombinePluginId } from '@fastgpt/global/core/app/plugin/utils';
import type { localeType } from '@fastgpt/global/common/i18n/type';
export async function listAppDatasetDataByTeamIdAndDatasetIds({
teamId,
datasetIdList
}: {
teamId?: string;
datasetIdList: string[];
}) {
const myDatasets = await MongoDataset.find({
_id: { $in: datasetIdList },
...(teamId && { teamId })
}).lean();
return myDatasets.map((item) => ({
datasetId: String(item._id),
avatar: item.avatar,
name: item.name,
vectorModel: getEmbeddingModel(item.vectorModel)
}));
}
export async function rewriteAppWorkflowToDetail({
nodes,
teamId,
isRoot,
ownerTmbId,
lang
}: {
nodes: StoreNodeItemType[];
teamId: string;
isRoot: boolean;
ownerTmbId: string;
lang?: localeType;
}) {
const datasetIdSet = new Set<string>();
/* Add node(App Type) versionlabel and latest sign ==== */
await Promise.all(
nodes.map(async (node) => {
if (!node.pluginId) return;
const { source, pluginId } = splitCombinePluginId(node.pluginId);
try {
const [preview] = await Promise.all([
getChildAppPreviewNode({
appId: node.pluginId,
versionId: node.version,
lang
}),
...(source === PluginSourceEnum.personal
? [
authAppByTmbId({
tmbId: ownerTmbId,
appId: pluginId,
per: ReadPermissionVal
})
]
: [])
]);
node.pluginData = {
diagram: preview.diagram,
userGuide: preview.userGuide,
courseUrl: preview.courseUrl,
name: preview.name,
avatar: preview.avatar
};
node.versionLabel = preview.versionLabel;
node.isLatestVersion = preview.isLatestVersion;
node.version = preview.version;
node.currentCost = preview.currentCost;
node.hasTokenFee = preview.hasTokenFee;
node.hasSystemSecret = preview.hasSystemSecret;
node.toolConfig = preview.toolConfig;
// Latest version
if (!node.version) {
const inputsMap = new Map(node.inputs.map((item) => [item.key, item]));
const outputsMap = new Map(node.outputs.map((item) => [item.key, item]));
node.inputs = preview.inputs.map((item) => {
const input = inputsMap.get(item.key);
return {
...item,
value: input?.value,
selectedTypeIndex: input?.selectedTypeIndex
};
});
node.outputs = preview.outputs.map((item) => {
const output = outputsMap.get(item.key);
return {
...item,
value: output?.value
};
});
}
} catch (error) {
node.pluginData = {
error: getErrText(error)
};
}
})
);
// Get all dataset ids from nodes
nodes.forEach((node) => {
if (node.flowNodeType !== FlowNodeTypeEnum.datasetSearchNode) return;
const input = node.inputs.find((item) => item.key === NodeInputKeyEnum.datasetSelectList);
if (!input) return;
const rawValue = input.value as undefined | { datasetId: string }[] | { datasetId: string };
if (!rawValue) return;
const datasetIds = Array.isArray(rawValue)
? rawValue.map((v) => v?.datasetId).filter((id) => !!id && typeof id === 'string')
: rawValue?.datasetId
? [String(rawValue.datasetId)]
: [];
datasetIds.forEach((id) => datasetIdSet.add(id));
});
if (datasetIdSet.size === 0) return;
// Load dataset list
const datasetList = await listAppDatasetDataByTeamIdAndDatasetIds({
teamId: isRoot ? undefined : teamId,
datasetIdList: Array.from(datasetIdSet)
});
const datasetMap = new Map(datasetList.map((ds) => [String(ds.datasetId), ds]));
// Rewrite dataset ids, add dataset info to nodes
if (datasetList.length > 0) {
nodes.forEach((node) => {
if (node.flowNodeType !== FlowNodeTypeEnum.datasetSearchNode) return;
node.inputs.forEach((item) => {
if (item.key !== NodeInputKeyEnum.datasetSelectList) return;
const val = item.value as undefined | { datasetId: string }[] | { datasetId: string };
if (Array.isArray(val)) {
item.value = val
.map((v) => {
const data = datasetMap.get(String(v.datasetId));
if (!data)
return {
datasetId: v.datasetId,
avatar: '',
name: 'Dataset not found',
vectorModel: ''
};
return {
datasetId: data.datasetId,
avatar: data.avatar,
name: data.name,
vectorModel: data.vectorModel
};
})
.filter(Boolean);
} else if (typeof val === 'object' && val !== null) {
const data = datasetMap.get(String(val.datasetId));
if (!data) {
item.value = [
{
datasetId: val.datasetId,
avatar: '',
name: 'Dataset not found',
vectorModel: ''
}
];
} else {
item.value = [
{
datasetId: data.datasetId,
avatar: data.avatar,
name: data.name,
vectorModel: data.vectorModel
}
];
}
}
});
});
}
return nodes;
}