Files
FastGPT/packages/service/core/app/controller.ts
Theresa 2d3117c5da feat: update ESLint config with @typescript-eslint/consistent-type-imports (#4746)
* update: Add type

* fix: update import statement for NextApiRequest type

* fix: update imports to use type for LexicalEditor and EditorState

* Refactor imports to use 'import type' for type-only imports across multiple files

- Updated imports in various components and API files to use 'import type' for better clarity and to optimize TypeScript's type checking.
- Ensured consistent usage of type imports in files related to chat, dataset, workflow, and user management.
- Improved code readability and maintainability by distinguishing between value and type imports.

* refactor: remove old ESLint configuration and add new rules

- Deleted the old ESLint configuration file from the app project.
- Added a new ESLint configuration file with updated rules and settings.
- Changed imports to use type-only imports in various files for better clarity and performance.
- Updated TypeScript configuration to remove unnecessary options.
- Added an ESLint ignore file to exclude build and dependency directories from linting.

* fix: update imports to use 'import type' for type-only imports in schema files
2025-05-06 17:33:09 +08:00

105 lines
2.5 KiB
TypeScript

import { type AppSchema } from '@fastgpt/global/core/app/type';
import { NodeInputKeyEnum } from '@fastgpt/global/core/workflow/constants';
import { FlowNodeTypeEnum } from '@fastgpt/global/core/workflow/node/constant';
import { getLLMModel } from '../ai/model';
import { MongoApp } from './schema';
export const beforeUpdateAppFormat = <T extends AppSchema['modules'] | undefined>({
nodes,
isPlugin
}: {
nodes: T;
isPlugin: boolean;
}) => {
if (nodes) {
// Check dataset maxTokens
if (isPlugin) {
let maxTokens = 16000;
nodes.forEach((item) => {
if (
item.flowNodeType === FlowNodeTypeEnum.chatNode ||
item.flowNodeType === FlowNodeTypeEnum.tools
) {
const model =
item.inputs.find((item) => item.key === NodeInputKeyEnum.aiModel)?.value || '';
const chatModel = getLLMModel(model);
const quoteMaxToken = chatModel.quoteMaxToken || 16000;
maxTokens = Math.max(maxTokens, quoteMaxToken);
}
});
nodes.forEach((item) => {
if (item.flowNodeType === FlowNodeTypeEnum.datasetSearchNode) {
item.inputs.forEach((input) => {
if (input.key === NodeInputKeyEnum.datasetMaxTokens) {
const val = input.value as number;
if (val > maxTokens) {
input.value = maxTokens;
}
}
});
}
});
}
}
return {
nodes
};
};
/* Get apps */
export async function findAppAndAllChildren({
teamId,
appId,
fields
}: {
teamId: string;
appId: string;
fields?: string;
}): Promise<AppSchema[]> {
const find = async (id: string) => {
const children = await MongoApp.find(
{
teamId,
parentId: id
},
fields
).lean();
let apps = children;
for (const child of children) {
const grandChildrenIds = await find(child._id);
apps = apps.concat(grandChildrenIds);
}
return apps;
};
const [app, childDatasets] = await Promise.all([MongoApp.findById(appId, fields), find(appId)]);
if (!app) {
return Promise.reject('Dataset not found');
}
return [app, ...childDatasets];
}
export const getAppBasicInfoByIds = async ({ teamId, ids }: { teamId: string; ids: string[] }) => {
const apps = await MongoApp.find(
{
teamId,
_id: { $in: ids }
},
'_id name avatar'
).lean();
return apps.map((item) => ({
id: item._id,
name: item.name,
avatar: item.avatar
}));
};