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Aiproxy (#3649)

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* model config

* feat: model config ui

* perf: rename variable

* feat: custom request url

* perf: model buffer

* perf: init model

* feat: json model config

* auto login

* fix: ts

* update packages

* package

* fix: dockerfile
This commit is contained in:
Archer
2025-01-22 22:59:28 +08:00
committed by GitHub
parent 16629e32a7
commit e009be51e7
93 changed files with 2361 additions and 564 deletions
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4
packages/service/core/dataset/collection/controller.ts
View File

@@ -19,7 +19,7 @@ import { predictDataLimitLength } from '../../../../global/core/dataset/utils';
import { mongoSessionRun } from '../../../common/mongo/sessionRun';
import { createTrainingUsage } from '../../../support/wallet/usage/controller';
import { UsageSourceEnum } from '@fastgpt/global/support/wallet/usage/constants';
import { getLLMModel, getVectorModel } from '../../ai/model';
import { getLLMModel, getEmbeddingModel } from '../../ai/model';
import { pushDataListToTrainingQueue } from '../training/controller';
import { MongoImage } from '../../../common/file/image/schema';
import { hashStr } from '@fastgpt/global/common/string/tools';
@@ -93,7 +93,7 @@ export const createCollectionAndInsertData = async ({
tmbId,
appName: usageName,
billSource: UsageSourceEnum.training,
vectorModel: getVectorModel(dataset.vectorModel)?.name,
vectorModel: getEmbeddingModel(dataset.vectorModel)?.name,
agentModel: getLLMModel(dataset.agentModel)?.name,
session
});

6
packages/service/core/dataset/search/controller.ts
View File

@@ -5,7 +5,7 @@ import {
} from '@fastgpt/global/core/dataset/constants';
import { recallFromVectorStore } from '../../../common/vectorStore/controller';
import { getVectorsByText } from '../../ai/embedding';
import { getVectorModel } from '../../ai/model';
import { getEmbeddingModel, getFirstReRankModel } from '../../ai/model';
import { MongoDatasetData } from '../data/schema';
import {
DatasetDataSchemaType,
@@ -67,7 +67,7 @@ export async function searchDatasetData(props: SearchDatasetDataProps) {
/* init params */
searchMode = DatasetSearchModeMap[searchMode] ? searchMode : DatasetSearchModeEnum.embedding;
usingReRank = usingReRank && global.reRankModels.length > 0;
usingReRank = usingReRank && !!getFirstReRankModel();
// Compatible with topk limit
let set = new Set<string>();
@@ -253,7 +253,7 @@ export async function searchDatasetData(props: SearchDatasetDataProps) {
filterCollectionIdList?: string[];
}) => {
const { vectors, tokens } = await getVectorsByText({
model: getVectorModel(model),
model: getEmbeddingModel(model),
input: query,
type: 'query'
});

4
packages/service/core/dataset/training/controller.ts
View File

@@ -7,7 +7,7 @@ import type {
import { TrainingModeEnum } from '@fastgpt/global/core/dataset/constants';
import { simpleText } from '@fastgpt/global/common/string/tools';
import { ClientSession } from '../../../common/mongo';
import { getLLMModel, getVectorModel } from '../../ai/model';
import { getLLMModel, getEmbeddingModel } from '../../ai/model';
import { addLog } from '../../../common/system/log';
import { getCollectionWithDataset } from '../controller';
import { mongoSessionRun } from '../../../common/mongo/sessionRun';
@@ -70,7 +70,7 @@ export async function pushDataListToTrainingQueue({
if (!agentModelData) {
return Promise.reject(`File model ${agentModel} is inValid`);
}
const vectorModelData = getVectorModel(vectorModel);
const vectorModelData = getEmbeddingModel(vectorModel);
if (!vectorModelData) {
return Promise.reject(`Vector model ${vectorModel} is inValid`);
}