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perf: file encoding;perf: leave team code;@c121914yu perf: full text search code (#3528)

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* perf: text encoding

* perf: leave team code

* perf: full text search code

* fix: http status

* perf: embedding search and vector avatar
This commit is contained in:
Archer
2025-01-05 14:40:02 +08:00
committed by archer
parent 5465ca642f
commit 2bf1fce32a
24 changed files with 345 additions and 100 deletions
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174
packages/service/core/dataset/search/controller.ts
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@@ -289,20 +289,22 @@ export async function searchDatasetData(props: SearchDatasetDataProps) {
).lean()
]);
const formatResult = dataList
.map((data, index) => {
const collection = collections.find((col) => String(col._id) === String(data.collectionId));
const formatResult = results
.map((item, index) => {
const collection = collections.find((col) => String(col._id) === String(item.collectionId));
if (!collection) {
console.log('Collection is not found', data);
console.log('Collection is not found', item);
return;
}
const data = dataList.find((data) =>
data.indexes.some((index) => index.dataId === item.id)
);
if (!data) {
console.log('Data is not found', item);
return;
}
// add score to data(It's already sorted. The first one is the one with the most points)
const dataIdList = data.indexes.map((item) => item.dataId);
const maxScoreResult = results.find((item) => {
return dataIdList.includes(item.id);
});
const score = maxScoreResult?.score || 0;
const score = item?.score || 0;
const result: SearchDataResponseItemType = {
id: String(data._id),
@@ -320,8 +322,6 @@ export async function searchDatasetData(props: SearchDatasetDataProps) {
})
.filter(Boolean) as SearchDataResponseItemType[];
formatResult.sort((a, b) => b.score[0].value - a.score[0].value);
return {
embeddingRecallResults: formatResult,
tokens
@@ -411,22 +411,6 @@ export async function searchDatasetData(props: SearchDatasetDataProps) {
'_id name fileId rawLink externalFileId externalFileUrl',
{ ...readFromSecondary }
).lean();
// const [dataList, collections] = await Promise.all([
// MongoDatasetData.find(
// {
// _id: { $in: searchResults.map((item) => item.dataId) }
// },
// '_id datasetId collectionId updateTime q a chunkIndex indexes',
// { ...readFromSecondary }
// ).lean(),
// MongoDatasetCollection.find(
// {
// _id: { $in: searchResults.map((item) => item.collectionId) }
// },
// '_id name fileId rawLink externalFileId externalFileUrl',
// { ...readFromSecondary }
// ).lean()
// ]);
return {
fullTextRecallResults: searchResults
@@ -439,9 +423,6 @@ export async function searchDatasetData(props: SearchDatasetDataProps) {
return;
}
// const score =
// searchResults.find((item) => String(item.dataId) === String(data._id))?.score || 0;
return {
id: String(data._id),
datasetId: String(data.datasetId),
@@ -459,6 +440,135 @@ export async function searchDatasetData(props: SearchDatasetDataProps) {
tokenLen: 0
};
};
const fullTextRecall2 = async ({
query,
limit,
filterCollectionIdList,
forbidCollectionIdList
}: {
query: string;
limit: number;
filterCollectionIdList?: string[];
forbidCollectionIdList: string[];
}): Promise<{
fullTextRecallResults: SearchDataResponseItemType[];
tokenLen: number;
}> => {
if (limit === 0) {
return {
fullTextRecallResults: [],
tokenLen: 0
};
}
const searchResults = (
await Promise.all(
datasetIds.map(async (id) => {
return MongoDatasetDataText.aggregate(
[
{
$match: {
teamId: new Types.ObjectId(teamId),
datasetId: new Types.ObjectId(id),
$text: { $search: jiebaSplit({ text: query }) },
...(filterCollectionIdList
? {
collectionId: {
$in: filterCollectionIdList.map((id) => new Types.ObjectId(id))
}
}
: {}),
...(forbidCollectionIdList && forbidCollectionIdList.length > 0
? {
collectionId: {
$nin: forbidCollectionIdList.map((id) => new Types.ObjectId(id))
}
}
: {})
}
},
{
$sort: {
score: { $meta: 'textScore' }
}
},
{
$limit: limit
},
{
$project: {
_id: 1,
collectionId: 1,
dataId: 1,
score: { $meta: 'textScore' }
}
}
],
{
...readFromSecondary
}
);
})
)
).flat() as (DatasetDataTextSchemaType & { score: number })[];
// Get data and collections
const [dataList, collections] = await Promise.all([
MongoDatasetData.find(
{
_id: { $in: searchResults.map((item) => item.dataId) }
},
'_id datasetId collectionId updateTime q a chunkIndex indexes',
{ ...readFromSecondary }
).lean(),
MongoDatasetCollection.find(
{
_id: { $in: searchResults.map((item) => item.collectionId) }
},
'_id name fileId rawLink externalFileId externalFileUrl',
{ ...readFromSecondary }
).lean()
]);
return {
fullTextRecallResults: searchResults
.map((item, index) => {
const collection = collections.find(
(col) => String(col._id) === String(item.collectionId)
);
if (!collection) {
console.log('Collection is not found', item);
return;
}
const data = dataList.find((data) => String(data._id) === String(item.dataId));
if (!data) {
console.log('Data is not found', item);
return;
}
return {
id: String(data._id),
datasetId: String(data.datasetId),
collectionId: String(data.collectionId),
updateTime: data.updateTime,
q: data.q,
a: data.a,
chunkIndex: data.chunkIndex,
indexes: data.indexes,
...getCollectionSourceData(collection),
score: [
{
type: SearchScoreTypeEnum.fullText,
value: item.score || 0,
index
}
]
};
})
.filter(Boolean) as SearchDataResponseItemType[],
tokenLen: 0
};
};
const reRankSearchResult = async ({
data,
query
@@ -526,7 +636,7 @@ export async function searchDatasetData(props: SearchDatasetDataProps) {
forbidCollectionIdList,
filterCollectionIdList
}),
fullTextRecall({
fullTextRecall2({
query,
limit: fullTextLimit,
filterCollectionIdList,