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perf: vector generate (#1748)

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This commit is contained in:
Archer
2024-06-12 16:42:46 +08:00
committed by GitHub
parent d0085a23e6
commit 05611df056
2 changed files with 109 additions and 109 deletions
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129
projects/app/src/service/events/generateVector.ts
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@@ -158,27 +158,69 @@ const rebuildData = async ({
const deleteVectorIdList = mongoData.indexes.map((index) => index.dataId);
const { tokens } = await mongoSessionRun(async (session) => {
// update vector, update dataset.data rebuilding status, delete data from training
const updateResult = await Promise.all(
mongoData.indexes.map(async (index, i) => {
const result = await insertDatasetDataVector({
query: index.text,
model: getVectorModel(trainingData.model),
teamId: mongoData.teamId,
datasetId: mongoData.datasetId,
collectionId: mongoData.collectionId
});
mongoData.indexes[i].dataId = result.insertId;
return result;
})
);
// Find next rebuilding data to insert training queue
await mongoSessionRun(async (session) => {
// get new mongoData insert to training
const newRebuildingData = await MongoDatasetData.findOneAndUpdate(
{
teamId: mongoData.teamId,
datasetId: mongoData.datasetId,
rebuilding: true
},
{
$unset: {
rebuilding: null
},
updateTime: new Date()
},
{ session }
).select({
_id: 1,
collectionId: 1
});
// Ensure that the training data is deleted after the Mongo update is successful
if (newRebuildingData) {
await MongoDatasetTraining.create(
[
{
teamId: mongoData.teamId,
tmbId: trainingData.tmbId,
datasetId: mongoData.datasetId,
collectionId: newRebuildingData.collectionId,
billId: trainingData.billId,
mode: TrainingModeEnum.chunk,
model: trainingData.model,
q: '1',
dataId: newRebuildingData._id
}
],
{ session }
);
}
});
// update vector, update dataset_data rebuilding status, delete data from training
// 1. Insert new vector to dataset_data
const updateResult = await Promise.all(
mongoData.indexes.map(async (index, i) => {
const result = await insertDatasetDataVector({
query: index.text,
model: getVectorModel(trainingData.model),
teamId: mongoData.teamId,
datasetId: mongoData.datasetId,
collectionId: mongoData.collectionId
});
mongoData.indexes[i].dataId = result.insertId;
return result;
})
);
const { tokens } = await mongoSessionRun(async (session) => {
// 2. Ensure that the training data is deleted after the Mongo update is successful
await mongoData.save({ session });
// 3. Delete the training data
await trainingData.deleteOne({ session });
// delete old vector
// 4. Delete old vector
await deleteDatasetDataVector({
teamId: mongoData.teamId,
idList: deleteVectorIdList
@@ -189,59 +231,6 @@ const rebuildData = async ({
};
});
// find next data insert to training queue
const arr = new Array(5).fill(0);
for await (const _ of arr) {
try {
const hasNextData = await mongoSessionRun(async (session) => {
// get new mongoData insert to training
const newRebuildingData = await MongoDatasetData.findOneAndUpdate(
{
teamId: mongoData.teamId,
datasetId: mongoData.datasetId,
rebuilding: true
},
{
$unset: {
rebuilding: null
},
updateTime: new Date()
},
{ session }
).select({
_id: 1,
collectionId: 1
});
if (newRebuildingData) {
await MongoDatasetTraining.create(
[
{
teamId: mongoData.teamId,
tmbId: trainingData.tmbId,
datasetId: mongoData.datasetId,
collectionId: newRebuildingData.collectionId,
billId: trainingData.billId,
mode: TrainingModeEnum.chunk,
model: trainingData.model,
q: '1',
dataId: newRebuildingData._id
}
],
{ session }
);
}
return !!newRebuildingData;
});
if (!hasNextData) {
break;
}
} catch (error) {}
}
return { tokens };
};