Upload training data through Azure Blob Storage
This commit is contained in:
@@ -40,3 +40,8 @@ SMTP_HOST="placeholder"
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SMTP_PORT="placeholder"
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SMTP_PORT="placeholder"
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SMTP_LOGIN="placeholder"
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SMTP_LOGIN="placeholder"
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SMTP_PASSWORD="placeholder"
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SMTP_PASSWORD="placeholder"
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# Azure credentials are necessary for uploading large training data files
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AZURE_STORAGE_ACCOUNT_NAME="placeholder"
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AZURE_STORAGE_ACCOUNT_KEY="placeholder"
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AZURE_STORAGE_CONTAINER_NAME="placeholder"
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@@ -26,6 +26,8 @@
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"dependencies": {
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"dependencies": {
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"@anthropic-ai/sdk": "^0.5.8",
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"@anthropic-ai/sdk": "^0.5.8",
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"@apidevtools/json-schema-ref-parser": "^10.1.0",
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"@apidevtools/json-schema-ref-parser": "^10.1.0",
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"@azure/identity": "^3.3.0",
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"@azure/storage-blob": "12.15.0",
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"@babel/standalone": "^7.22.9",
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"@babel/standalone": "^7.22.9",
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"@chakra-ui/anatomy": "^2.2.0",
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"@chakra-ui/anatomy": "^2.2.0",
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"@chakra-ui/next-js": "^2.1.4",
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"@chakra-ui/next-js": "^2.1.4",
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@@ -69,6 +71,7 @@
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"jsonschema": "^1.4.1",
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"jsonschema": "^1.4.1",
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"kysely": "^0.26.1",
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"kysely": "^0.26.1",
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"kysely-codegen": "^0.10.1",
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"kysely-codegen": "^0.10.1",
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"llama-tokenizer-js": "^1.1.3",
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"lodash-es": "^4.17.21",
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"lodash-es": "^4.17.21",
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"lucide-react": "^0.265.0",
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"lucide-react": "^0.265.0",
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"marked": "^7.0.3",
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"marked": "^7.0.3",
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@@ -0,0 +1,23 @@
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-- CreateEnum
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CREATE TYPE "DatasetFileUploadStatus" AS ENUM ('PENDING', 'DOWNLOADING', 'PROCESSING', 'SAVING', 'COMPLETE', 'ERROR');
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-- CreateTable
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CREATE TABLE "DatasetFileUpload" (
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"id" UUID NOT NULL,
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"datasetId" UUID NOT NULL,
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"blobName" TEXT NOT NULL,
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"fileName" TEXT NOT NULL,
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"fileSize" INTEGER NOT NULL,
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"progress" INTEGER NOT NULL DEFAULT 0,
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"status" "DatasetFileUploadStatus" NOT NULL DEFAULT 'PENDING',
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"uploadedAt" TIMESTAMP(3) NOT NULL,
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"visible" BOOLEAN NOT NULL DEFAULT true,
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"errorMessage" TEXT,
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"createdAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
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"updatedAt" TIMESTAMP(3) NOT NULL,
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CONSTRAINT "DatasetFileUpload_pkey" PRIMARY KEY ("id")
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);
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-- AddForeignKey
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ALTER TABLE "DatasetFileUpload" ADD CONSTRAINT "DatasetFileUpload_datasetId_fkey" FOREIGN KEY ("datasetId") REFERENCES "Dataset"("id") ON DELETE CASCADE ON UPDATE CASCADE;
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@@ -176,12 +176,41 @@ model OutputEvaluation {
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@@unique([modelResponseId, evaluationId])
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@@unique([modelResponseId, evaluationId])
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}
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}
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enum DatasetFileUploadStatus {
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PENDING
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DOWNLOADING
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PROCESSING
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SAVING
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COMPLETE
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ERROR
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}
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model DatasetFileUpload {
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id String @id @default(uuid()) @db.Uuid
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datasetId String @db.Uuid
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dataset Dataset @relation(fields: [datasetId], references: [id], onDelete: Cascade)
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blobName String
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fileName String
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fileSize Int
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progress Int @default(0) // Percentage
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status DatasetFileUploadStatus @default(PENDING)
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uploadedAt DateTime
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visible Boolean @default(true)
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errorMessage String?
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createdAt DateTime @default(now())
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updatedAt DateTime @updatedAt
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}
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model Dataset {
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model Dataset {
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id String @id @default(uuid()) @db.Uuid
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id String @id @default(uuid()) @db.Uuid
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name String
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name String
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datasetEntries DatasetEntry[]
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datasetEntries DatasetEntry[]
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fineTunes FineTune[]
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fineTunes FineTune[]
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datasetFileUploads DatasetFileUpload[]
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trainingRatio Float @default(0.8)
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trainingRatio Float @default(0.8)
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projectId String @db.Uuid
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projectId String @db.Uuid
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61
app/src/components/datasets/FileUploadCard.tsx
Normal file
61
app/src/components/datasets/FileUploadCard.tsx
Normal file
@@ -0,0 +1,61 @@
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import { VStack, HStack, Button, Text, Card, Progress, IconButton } from "@chakra-ui/react";
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import { BsX } from "react-icons/bs";
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import { type RouterOutputs, api } from "~/utils/api";
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import { useHandledAsyncCallback } from "~/utils/hooks";
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import { formatFileSize } from "~/utils/utils";
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type FileUpload = RouterOutputs["datasets"]["listFileUploads"][0];
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const FileUploadCard = ({ fileUpload }: { fileUpload: FileUpload }) => {
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const { id, fileName, fileSize, progress, status, errorMessage } = fileUpload;
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const utils = api.useContext();
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const hideFileUploadMutation = api.datasets.hideFileUpload.useMutation();
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const [hideFileUpload, hidingInProgress] = useHandledAsyncCallback(async () => {
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await hideFileUploadMutation.mutateAsync({ fileUploadId: id });
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await utils.datasets.listFileUploads.invalidate();
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}, [id, hideFileUploadMutation, utils]);
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const [refreshDatasetEntries] = useHandledAsyncCallback(async () => {
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await utils.datasetEntries.list.invalidate();
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}, [utils]);
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return (
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<Card w="full">
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<VStack w="full" alignItems="flex-start" p={4}>
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<HStack w="full" justifyContent="space-between">
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<Text fontWeight="bold">
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Uploading {fileName} ({formatFileSize(fileSize, 2)})
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</Text>
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<HStack spacing={0}>
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{status === "COMPLETE" && (
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<Button variant="ghost" onClick={refreshDatasetEntries} color="orange.400" size="xs">
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Refresh Table
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</Button>
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)}
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<IconButton
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aria-label="Hide file upload"
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as={BsX}
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boxSize={6}
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minW={0}
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variant="ghost"
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isLoading={hidingInProgress}
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onClick={hideFileUpload}
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cursor="pointer"
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/>
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</HStack>
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</HStack>
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<Text alignSelf="center" fontSize="xs">
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{errorMessage ? errorMessage : `${status} (${progress}%)`}
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</Text>
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<Progress w="full" value={progress} borderRadius={2} />
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</VStack>
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</Card>
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);
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};
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export default FileUploadCard;
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@@ -1,4 +1,4 @@
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import { useState, useEffect, useRef } from "react";
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import { useState, useEffect, useRef, useCallback } from "react";
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import {
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import {
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Modal,
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Modal,
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ModalOverlay,
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ModalOverlay,
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@@ -16,13 +16,15 @@ import {
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useDisclosure,
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useDisclosure,
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type UseDisclosureReturn,
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type UseDisclosureReturn,
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} from "@chakra-ui/react";
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} from "@chakra-ui/react";
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import pluralize from "pluralize";
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import { AiOutlineCloudUpload, AiOutlineFile } from "react-icons/ai";
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import { AiOutlineCloudUpload, AiOutlineFile } from "react-icons/ai";
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import { useDataset, useHandledAsyncCallback } from "~/utils/hooks";
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import { useDataset, useHandledAsyncCallback } from "~/utils/hooks";
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import { api } from "~/utils/api";
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import { api } from "~/utils/api";
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import ActionButton from "../ActionButton";
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import ActionButton from "../ActionButton";
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import { validateTrainingRows, type TrainingRow, parseJSONL } from "./validateTrainingRows";
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import { validateTrainingRows, type TrainingRow, parseJSONL } from "./validateTrainingRows";
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import pluralize from "pluralize";
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import { uploadDatasetEntryFile } from "~/utils/azure/website";
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import { formatFileSize } from "~/utils/utils";
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const ImportDataButton = () => {
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const ImportDataButton = () => {
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const disclosure = useDisclosure();
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const disclosure = useDisclosure();
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@@ -48,6 +50,7 @@ const ImportDataModal = ({ disclosure }: { disclosure: UseDisclosureReturn }) =>
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const [validationError, setValidationError] = useState<string | null>(null);
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const [validationError, setValidationError] = useState<string | null>(null);
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const [trainingRows, setTrainingRows] = useState<TrainingRow[] | null>(null);
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const [trainingRows, setTrainingRows] = useState<TrainingRow[] | null>(null);
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const [file, setFile] = useState<File | null>(null);
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const fileInputRef = useRef<HTMLInputElement>(null);
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const fileInputRef = useRef<HTMLInputElement>(null);
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@@ -67,6 +70,14 @@ const ImportDataModal = ({ disclosure }: { disclosure: UseDisclosureReturn }) =>
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};
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};
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const processFile = (file: File) => {
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const processFile = (file: File) => {
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setFile(file);
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// skip reading if file is larger than 10MB
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if (file.size > 10000000) {
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setTrainingRows(null);
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return;
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}
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const reader = new FileReader();
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const reader = new FileReader();
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reader.onload = (e: ProgressEvent<FileReader>) => {
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reader.onload = (e: ProgressEvent<FileReader>) => {
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const content = e.target?.result as string;
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const content = e.target?.result as string;
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@@ -83,7 +94,6 @@ const ImportDataModal = ({ disclosure }: { disclosure: UseDisclosureReturn }) =>
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setTrainingRows(parsedJSONL);
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setTrainingRows(parsedJSONL);
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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} catch (e: any) {
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} catch (e: any) {
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console.log("e is", e);
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setValidationError("Unable to parse JSONL file: " + (e.message as string));
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setValidationError("Unable to parse JSONL file: " + (e.message as string));
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setTrainingRows(null);
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setTrainingRows(null);
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return;
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return;
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@@ -92,28 +102,38 @@ const ImportDataModal = ({ disclosure }: { disclosure: UseDisclosureReturn }) =>
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reader.readAsText(file);
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reader.readAsText(file);
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};
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};
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const resetState = useCallback(() => {
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setValidationError(null);
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setTrainingRows(null);
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setFile(null);
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}, [setValidationError, setTrainingRows, setFile]);
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useEffect(() => {
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useEffect(() => {
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if (disclosure.isOpen) {
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if (disclosure.isOpen) {
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setTrainingRows(null);
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resetState();
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setValidationError(null);
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}
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}
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}, [disclosure.isOpen]);
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}, [disclosure.isOpen, resetState]);
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const triggerFileDownloadMutation = api.datasets.triggerFileDownload.useMutation();
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const utils = api.useContext();
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const utils = api.useContext();
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const sendJSONLMutation = api.datasetEntries.create.useMutation();
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const [sendJSONL, sendingInProgress] = useHandledAsyncCallback(async () => {
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const [sendJSONL, sendingInProgress] = useHandledAsyncCallback(async () => {
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if (!dataset || !trainingRows) return;
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if (!dataset || !file) return;
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await sendJSONLMutation.mutateAsync({
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const blobName = await uploadDatasetEntryFile(file);
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await triggerFileDownloadMutation.mutateAsync({
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datasetId: dataset.id,
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datasetId: dataset.id,
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jsonl: JSON.stringify(trainingRows),
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blobName,
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fileName: file.name,
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fileSize: file.size,
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});
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});
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await utils.datasetEntries.list.invalidate();
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await utils.datasets.listFileUploads.invalidate();
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disclosure.onClose();
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disclosure.onClose();
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}, [dataset, trainingRows, sendJSONLMutation]);
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}, [dataset, trainingRows, triggerFileDownloadMutation, file, utils]);
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return (
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return (
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<Modal size={{ base: "xl", md: "2xl" }} {...disclosure}>
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<Modal size={{ base: "xl", md: "2xl" }} {...disclosure}>
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@@ -127,7 +147,28 @@ const ImportDataModal = ({ disclosure }: { disclosure: UseDisclosureReturn }) =>
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<ModalCloseButton />
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<ModalCloseButton />
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<ModalBody maxW="unset" p={8}>
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<ModalBody maxW="unset" p={8}>
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<Box w="full" aspectRatio={1.5}>
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<Box w="full" aspectRatio={1.5}>
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{!trainingRows && !validationError && (
|
{validationError && (
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<VStack w="full" h="full" justifyContent="center" spacing={8}>
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<Icon as={AiOutlineFile} boxSize={24} color="gray.300" />
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<VStack w="full">
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<Text fontSize={32} color="gray.500" fontWeight="bold">
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Error
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</Text>
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<Text color="gray.500">{validationError}</Text>
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||||||
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</VStack>
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<Text
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|
as="span"
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textDecor="underline"
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color="gray.500"
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_hover={{ color: "orange.400" }}
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cursor="pointer"
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|
onClick={resetState}
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||||||
|
>
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||||||
|
Try again
|
||||||
|
</Text>
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||||||
|
</VStack>
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||||||
|
)}
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{!validationError && !file && (
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||||||
<VStack
|
<VStack
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||||||
w="full"
|
w="full"
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||||||
h="full"
|
h="full"
|
||||||
@@ -167,31 +208,12 @@ const ImportDataModal = ({ disclosure }: { disclosure: UseDisclosureReturn }) =>
|
|||||||
</Text>
|
</Text>
|
||||||
</VStack>
|
</VStack>
|
||||||
)}
|
)}
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||||||
{validationError && (
|
{!validationError && file && (
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||||||
<VStack w="full" h="full" justifyContent="center" spacing={8}>
|
|
||||||
<Icon as={AiOutlineFile} boxSize={24} color="gray.300" />
|
|
||||||
<VStack w="full">
|
|
||||||
<Text fontSize={32} color="gray.500" fontWeight="bold">
|
|
||||||
Error
|
|
||||||
</Text>
|
|
||||||
<Text color="gray.500">{validationError}</Text>
|
|
||||||
</VStack>
|
|
||||||
<Text
|
|
||||||
as="span"
|
|
||||||
textDecor="underline"
|
|
||||||
color="gray.500"
|
|
||||||
_hover={{ color: "orange.400" }}
|
|
||||||
cursor="pointer"
|
|
||||||
onClick={() => setValidationError(null)}
|
|
||||||
>
|
|
||||||
Try again
|
|
||||||
</Text>
|
|
||||||
</VStack>
|
|
||||||
)}
|
|
||||||
{trainingRows && !validationError && (
|
|
||||||
<VStack w="full" h="full" justifyContent="center" spacing={8}>
|
<VStack w="full" h="full" justifyContent="center" spacing={8}>
|
||||||
<JsonFileIcon />
|
<JsonFileIcon />
|
||||||
<VStack w="full">
|
<VStack w="full">
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||||||
|
{trainingRows ? (
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||||||
|
<>
|
||||||
<Text fontSize={32} color="gray.500" fontWeight="bold">
|
<Text fontSize={32} color="gray.500" fontWeight="bold">
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||||||
Success
|
Success
|
||||||
</Text>
|
</Text>
|
||||||
@@ -199,6 +221,15 @@ const ImportDataModal = ({ disclosure }: { disclosure: UseDisclosureReturn }) =>
|
|||||||
We'll upload <b>{trainingRows.length}</b>{" "}
|
We'll upload <b>{trainingRows.length}</b>{" "}
|
||||||
{pluralize("row", trainingRows.length)} into <b>{dataset?.name}</b>.{" "}
|
{pluralize("row", trainingRows.length)} into <b>{dataset?.name}</b>.{" "}
|
||||||
</Text>
|
</Text>
|
||||||
|
</>
|
||||||
|
) : (
|
||||||
|
<>
|
||||||
|
<Text fontSize={32} color="gray.500" fontWeight="bold">
|
||||||
|
{file.name}
|
||||||
|
</Text>
|
||||||
|
<Text color="gray.500">{formatFileSize(file.size)}</Text>
|
||||||
|
</>
|
||||||
|
)}
|
||||||
</VStack>
|
</VStack>
|
||||||
<Text
|
<Text
|
||||||
as="span"
|
as="span"
|
||||||
@@ -206,7 +237,7 @@ const ImportDataModal = ({ disclosure }: { disclosure: UseDisclosureReturn }) =>
|
|||||||
color="gray.500"
|
color="gray.500"
|
||||||
_hover={{ color: "orange.400" }}
|
_hover={{ color: "orange.400" }}
|
||||||
cursor="pointer"
|
cursor="pointer"
|
||||||
onClick={() => setTrainingRows(null)}
|
onClick={resetState}
|
||||||
>
|
>
|
||||||
Change file
|
Change file
|
||||||
</Text>
|
</Text>
|
||||||
@@ -224,7 +255,7 @@ const ImportDataModal = ({ disclosure }: { disclosure: UseDisclosureReturn }) =>
|
|||||||
onClick={sendJSONL}
|
onClick={sendJSONL}
|
||||||
isLoading={sendingInProgress}
|
isLoading={sendingInProgress}
|
||||||
minW={24}
|
minW={24}
|
||||||
isDisabled={!trainingRows || !!validationError}
|
isDisabled={!file || !!validationError}
|
||||||
>
|
>
|
||||||
Upload
|
Upload
|
||||||
</Button>
|
</Button>
|
||||||
|
|||||||
@@ -26,6 +26,9 @@ export const env = createEnv({
|
|||||||
SMTP_PORT: z.string().default("placeholder"),
|
SMTP_PORT: z.string().default("placeholder"),
|
||||||
SMTP_LOGIN: z.string().default("placeholder"),
|
SMTP_LOGIN: z.string().default("placeholder"),
|
||||||
SMTP_PASSWORD: z.string().default("placeholder"),
|
SMTP_PASSWORD: z.string().default("placeholder"),
|
||||||
|
AZURE_STORAGE_ACCOUNT_NAME: z.string().default("placeholder"),
|
||||||
|
AZURE_STORAGE_ACCOUNT_KEY: z.string().default("placeholder"),
|
||||||
|
AZURE_STORAGE_CONTAINER_NAME: z.string().default("placeholder"),
|
||||||
WORKER_CONCURRENCY: z
|
WORKER_CONCURRENCY: z
|
||||||
.string()
|
.string()
|
||||||
.default("10")
|
.default("10")
|
||||||
@@ -72,6 +75,9 @@ export const env = createEnv({
|
|||||||
SMTP_PORT: process.env.SMTP_PORT,
|
SMTP_PORT: process.env.SMTP_PORT,
|
||||||
SMTP_LOGIN: process.env.SMTP_LOGIN,
|
SMTP_LOGIN: process.env.SMTP_LOGIN,
|
||||||
SMTP_PASSWORD: process.env.SMTP_PASSWORD,
|
SMTP_PASSWORD: process.env.SMTP_PASSWORD,
|
||||||
|
AZURE_STORAGE_ACCOUNT_NAME: process.env.AZURE_STORAGE_ACCOUNT_NAME,
|
||||||
|
AZURE_STORAGE_ACCOUNT_KEY: process.env.AZURE_STORAGE_ACCOUNT_KEY,
|
||||||
|
AZURE_STORAGE_CONTAINER_NAME: process.env.AZURE_STORAGE_CONTAINER_NAME,
|
||||||
WORKER_CONCURRENCY: process.env.WORKER_CONCURRENCY,
|
WORKER_CONCURRENCY: process.env.WORKER_CONCURRENCY,
|
||||||
WORKER_MAX_POOL_SIZE: process.env.WORKER_MAX_POOL_SIZE,
|
WORKER_MAX_POOL_SIZE: process.env.WORKER_MAX_POOL_SIZE,
|
||||||
},
|
},
|
||||||
|
|||||||
@@ -28,6 +28,7 @@ import ExperimentButton from "~/components/datasets/ExperimentButton";
|
|||||||
import ImportDataButton from "~/components/datasets/ImportDataButton";
|
import ImportDataButton from "~/components/datasets/ImportDataButton";
|
||||||
import DownloadButton from "~/components/datasets/ExportButton";
|
import DownloadButton from "~/components/datasets/ExportButton";
|
||||||
import DeleteButton from "~/components/datasets/DeleteButton";
|
import DeleteButton from "~/components/datasets/DeleteButton";
|
||||||
|
import FileUploadCard from "~/components/datasets/FileUploadCard";
|
||||||
|
|
||||||
export default function Dataset() {
|
export default function Dataset() {
|
||||||
const utils = api.useContext();
|
const utils = api.useContext();
|
||||||
@@ -40,6 +41,19 @@ export default function Dataset() {
|
|||||||
setName(dataset.data?.name || "");
|
setName(dataset.data?.name || "");
|
||||||
}, [dataset.data?.name]);
|
}, [dataset.data?.name]);
|
||||||
|
|
||||||
|
const [fileUploadsRefetchInterval, setFileUploadsRefetchInterval] = useState<number>(500);
|
||||||
|
const fileUploads = api.datasets.listFileUploads.useQuery(
|
||||||
|
{ datasetId: dataset.data?.id as string },
|
||||||
|
{ enabled: !!dataset.data?.id, refetchInterval: fileUploadsRefetchInterval },
|
||||||
|
);
|
||||||
|
useEffect(() => {
|
||||||
|
if (fileUploads?.data?.some((fu) => fu.status !== "COMPLETE" && fu.status !== "ERROR")) {
|
||||||
|
setFileUploadsRefetchInterval(500);
|
||||||
|
} else {
|
||||||
|
setFileUploadsRefetchInterval(0);
|
||||||
|
}
|
||||||
|
}, [fileUploads]);
|
||||||
|
|
||||||
useEffect(() => {
|
useEffect(() => {
|
||||||
useAppStore.getState().sharedArgumentsEditor.loadMonaco().catch(console.error);
|
useAppStore.getState().sharedArgumentsEditor.loadMonaco().catch(console.error);
|
||||||
}, []);
|
}, []);
|
||||||
@@ -101,6 +115,13 @@ export default function Dataset() {
|
|||||||
<DatasetHeaderButtons openDrawer={drawerDisclosure.onOpen} />
|
<DatasetHeaderButtons openDrawer={drawerDisclosure.onOpen} />
|
||||||
</PageHeaderContainer>
|
</PageHeaderContainer>
|
||||||
<VStack px={8} py={8} alignItems="flex-start" spacing={4} w="full">
|
<VStack px={8} py={8} alignItems="flex-start" spacing={4} w="full">
|
||||||
|
<HStack w="full">
|
||||||
|
<VStack w="full">
|
||||||
|
{fileUploads?.data?.map((upload) => (
|
||||||
|
<FileUploadCard key={upload.id} fileUpload={upload} />
|
||||||
|
))}
|
||||||
|
</VStack>
|
||||||
|
</HStack>
|
||||||
<HStack w="full" justifyContent="flex-end">
|
<HStack w="full" justifyContent="flex-end">
|
||||||
<FineTuneButton />
|
<FineTuneButton />
|
||||||
<ImportDataButton />
|
<ImportDataButton />
|
||||||
|
|||||||
@@ -1,4 +1,3 @@
|
|||||||
import { type Prisma } from "@prisma/client";
|
|
||||||
import { z } from "zod";
|
import { z } from "zod";
|
||||||
import { v4 as uuidv4 } from "uuid";
|
import { v4 as uuidv4 } from "uuid";
|
||||||
import {
|
import {
|
||||||
@@ -7,18 +6,18 @@ import {
|
|||||||
type CreateChatCompletionRequestMessage,
|
type CreateChatCompletionRequestMessage,
|
||||||
} from "openai/resources/chat";
|
} from "openai/resources/chat";
|
||||||
import { TRPCError } from "@trpc/server";
|
import { TRPCError } from "@trpc/server";
|
||||||
import { shuffle } from "lodash-es";
|
|
||||||
import archiver from "archiver";
|
import archiver from "archiver";
|
||||||
|
import { WritableStreamBuffer } from "stream-buffers";
|
||||||
|
|
||||||
import { createTRPCRouter, protectedProcedure } from "~/server/api/trpc";
|
import { createTRPCRouter, protectedProcedure } from "~/server/api/trpc";
|
||||||
import { prisma } from "~/server/db";
|
import { prisma } from "~/server/db";
|
||||||
import { requireCanModifyProject, requireCanViewProject } from "~/utils/accessControl";
|
import { requireCanModifyProject, requireCanViewProject } from "~/utils/accessControl";
|
||||||
import { error, success } from "~/utils/errorHandling/standardResponses";
|
import { error, success } from "~/utils/errorHandling/standardResponses";
|
||||||
import { countOpenAIChatTokens } from "~/utils/countTokens";
|
import { countOpenAIChatTokens } from "~/utils/countTokens";
|
||||||
import { type TrainingRow, validateTrainingRows } from "~/components/datasets/validateTrainingRows";
|
import { type TrainingRow } from "~/components/datasets/validateTrainingRows";
|
||||||
import hashObject from "~/server/utils/hashObject";
|
import hashObject from "~/server/utils/hashObject";
|
||||||
import { type JsonValue } from "type-fest";
|
import { type JsonValue } from "type-fest";
|
||||||
import { WritableStreamBuffer } from "stream-buffers";
|
import { formatEntriesFromTrainingRows } from "~/server/utils/createEntriesFromTrainingRows";
|
||||||
|
|
||||||
export const datasetEntriesRouter = createTRPCRouter({
|
export const datasetEntriesRouter = createTRPCRouter({
|
||||||
list: protectedProcedure
|
list: protectedProcedure
|
||||||
@@ -100,7 +99,6 @@ export const datasetEntriesRouter = createTRPCRouter({
|
|||||||
})
|
})
|
||||||
.optional(),
|
.optional(),
|
||||||
loggedCallIds: z.string().array().optional(),
|
loggedCallIds: z.string().array().optional(),
|
||||||
jsonl: z.string().optional(),
|
|
||||||
}),
|
}),
|
||||||
)
|
)
|
||||||
.mutation(async ({ input, ctx }) => {
|
.mutation(async ({ input, ctx }) => {
|
||||||
@@ -121,13 +119,10 @@ export const datasetEntriesRouter = createTRPCRouter({
|
|||||||
return error("No datasetId or newDatasetParams provided");
|
return error("No datasetId or newDatasetParams provided");
|
||||||
}
|
}
|
||||||
|
|
||||||
if (!input.loggedCallIds && !input.jsonl) {
|
if (!input.loggedCallIds) {
|
||||||
return error("No loggedCallIds or jsonl provided");
|
return error("No loggedCallIds provided");
|
||||||
}
|
}
|
||||||
|
|
||||||
let trainingRows: TrainingRow[];
|
|
||||||
|
|
||||||
if (input.loggedCallIds) {
|
|
||||||
const loggedCalls = await prisma.loggedCall.findMany({
|
const loggedCalls = await prisma.loggedCall.findMany({
|
||||||
where: {
|
where: {
|
||||||
id: {
|
id: {
|
||||||
@@ -150,14 +145,12 @@ export const datasetEntriesRouter = createTRPCRouter({
|
|||||||
orderBy: { createdAt: "desc" },
|
orderBy: { createdAt: "desc" },
|
||||||
});
|
});
|
||||||
|
|
||||||
trainingRows = loggedCalls.map((loggedCall) => {
|
const trainingRows = loggedCalls.map((loggedCall) => {
|
||||||
const inputMessages = (
|
const inputMessages = (
|
||||||
loggedCall.modelResponse?.reqPayload as unknown as CompletionCreateParams
|
loggedCall.modelResponse?.reqPayload as unknown as CompletionCreateParams
|
||||||
).messages;
|
).messages;
|
||||||
let output: ChatCompletion.Choice.Message | undefined = undefined;
|
let output: ChatCompletion.Choice.Message | undefined = undefined;
|
||||||
const resp = loggedCall.modelResponse?.respPayload as unknown as
|
const resp = loggedCall.modelResponse?.respPayload as unknown as ChatCompletion | undefined;
|
||||||
| ChatCompletion
|
|
||||||
| undefined;
|
|
||||||
if (resp && resp.choices?.[0]) {
|
if (resp && resp.choices?.[0]) {
|
||||||
output = resp.choices[0].message;
|
output = resp.choices[0].message;
|
||||||
}
|
}
|
||||||
@@ -166,59 +159,8 @@ export const datasetEntriesRouter = createTRPCRouter({
|
|||||||
output: output as unknown as CreateChatCompletionRequestMessage,
|
output: output as unknown as CreateChatCompletionRequestMessage,
|
||||||
};
|
};
|
||||||
});
|
});
|
||||||
} else {
|
|
||||||
trainingRows = JSON.parse(input.jsonl as string) as TrainingRow[];
|
|
||||||
const validationError = validateTrainingRows(trainingRows);
|
|
||||||
if (validationError) {
|
|
||||||
return error(`Invalid JSONL: ${validationError}`);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
const [existingTrainingCount, existingTestingCount] = await prisma.$transaction([
|
const datasetEntriesToCreate = await formatEntriesFromTrainingRows(datasetId, trainingRows);
|
||||||
prisma.datasetEntry.count({
|
|
||||||
where: {
|
|
||||||
datasetId,
|
|
||||||
type: "TRAIN",
|
|
||||||
},
|
|
||||||
}),
|
|
||||||
prisma.datasetEntry.count({
|
|
||||||
where: {
|
|
||||||
datasetId,
|
|
||||||
type: "TEST",
|
|
||||||
},
|
|
||||||
}),
|
|
||||||
]);
|
|
||||||
|
|
||||||
const newTotalEntries = existingTrainingCount + existingTestingCount + trainingRows.length;
|
|
||||||
const numTrainingToAdd = Math.floor(trainingRatio * newTotalEntries) - existingTrainingCount;
|
|
||||||
const numTestingToAdd = trainingRows.length - numTrainingToAdd;
|
|
||||||
const typesToAssign = shuffle([
|
|
||||||
...Array(numTrainingToAdd).fill("TRAIN"),
|
|
||||||
...Array(numTestingToAdd).fill("TEST"),
|
|
||||||
]);
|
|
||||||
const datasetEntriesToCreate: Prisma.DatasetEntryCreateManyInput[] = [];
|
|
||||||
for (const row of trainingRows) {
|
|
||||||
let outputTokens = 0;
|
|
||||||
if (row.output) {
|
|
||||||
outputTokens = countOpenAIChatTokens("gpt-4-0613", [
|
|
||||||
row.output as unknown as ChatCompletion.Choice.Message,
|
|
||||||
]);
|
|
||||||
}
|
|
||||||
datasetEntriesToCreate.push({
|
|
||||||
datasetId: datasetId,
|
|
||||||
input: row.input as unknown as Prisma.InputJsonValue,
|
|
||||||
output: (row.output as unknown as Prisma.InputJsonValue) ?? {
|
|
||||||
role: "assistant",
|
|
||||||
content: "",
|
|
||||||
},
|
|
||||||
inputTokens: countOpenAIChatTokens(
|
|
||||||
"gpt-4-0613",
|
|
||||||
row.input as unknown as CreateChatCompletionRequestMessage[],
|
|
||||||
),
|
|
||||||
outputTokens,
|
|
||||||
type: typesToAssign.pop() as "TRAIN" | "TEST",
|
|
||||||
});
|
|
||||||
}
|
|
||||||
|
|
||||||
// Ensure dataset and dataset entries are created atomically
|
// Ensure dataset and dataset entries are created atomically
|
||||||
await prisma.$transaction([
|
await prisma.$transaction([
|
||||||
@@ -239,7 +181,6 @@ export const datasetEntriesRouter = createTRPCRouter({
|
|||||||
|
|
||||||
return success(datasetId);
|
return success(datasetId);
|
||||||
}),
|
}),
|
||||||
|
|
||||||
update: protectedProcedure
|
update: protectedProcedure
|
||||||
.input(
|
.input(
|
||||||
z.object({
|
z.object({
|
||||||
|
|||||||
@@ -1,8 +1,11 @@
|
|||||||
import { z } from "zod";
|
import { z } from "zod";
|
||||||
|
|
||||||
import { createTRPCRouter, protectedProcedure } from "~/server/api/trpc";
|
import { createTRPCRouter, protectedProcedure } from "~/server/api/trpc";
|
||||||
import { prisma } from "~/server/db";
|
import { prisma } from "~/server/db";
|
||||||
import { requireCanModifyProject, requireCanViewProject } from "~/utils/accessControl";
|
import { requireCanModifyProject, requireCanViewProject } from "~/utils/accessControl";
|
||||||
import { success } from "~/utils/errorHandling/standardResponses";
|
import { success } from "~/utils/errorHandling/standardResponses";
|
||||||
|
import { generateServiceClientUrl } from "~/utils/azure/server";
|
||||||
|
import { queueImportDatasetEntries } from "~/server/tasks/importDatasetEntries.task";
|
||||||
|
|
||||||
export const datasetsRouter = createTRPCRouter({
|
export const datasetsRouter = createTRPCRouter({
|
||||||
get: protectedProcedure.input(z.object({ id: z.string() })).query(async ({ input, ctx }) => {
|
get: protectedProcedure.input(z.object({ id: z.string() })).query(async ({ input, ctx }) => {
|
||||||
@@ -94,4 +97,73 @@ export const datasetsRouter = createTRPCRouter({
|
|||||||
|
|
||||||
return success("Dataset deleted");
|
return success("Dataset deleted");
|
||||||
}),
|
}),
|
||||||
|
getServiceClientUrl: protectedProcedure
|
||||||
|
.input(z.object({ projectId: z.string() }))
|
||||||
|
.query(async ({ input, ctx }) => {
|
||||||
|
// The user must at least be authenticated to get a SAS token
|
||||||
|
await requireCanModifyProject(input.projectId, ctx);
|
||||||
|
return generateServiceClientUrl();
|
||||||
|
}),
|
||||||
|
triggerFileDownload: protectedProcedure
|
||||||
|
.input(
|
||||||
|
z.object({
|
||||||
|
datasetId: z.string(),
|
||||||
|
blobName: z.string(),
|
||||||
|
fileName: z.string(),
|
||||||
|
fileSize: z.number(),
|
||||||
|
}),
|
||||||
|
)
|
||||||
|
.mutation(async ({ input, ctx }) => {
|
||||||
|
const { projectId } = await prisma.dataset.findUniqueOrThrow({
|
||||||
|
where: { id: input.datasetId },
|
||||||
|
});
|
||||||
|
await requireCanViewProject(projectId, ctx);
|
||||||
|
|
||||||
|
const { id } = await prisma.datasetFileUpload.create({
|
||||||
|
data: {
|
||||||
|
datasetId: input.datasetId,
|
||||||
|
blobName: input.blobName,
|
||||||
|
status: "PENDING",
|
||||||
|
fileName: input.fileName,
|
||||||
|
fileSize: input.fileSize,
|
||||||
|
uploadedAt: new Date(),
|
||||||
|
},
|
||||||
|
});
|
||||||
|
|
||||||
|
await queueImportDatasetEntries(id);
|
||||||
|
}),
|
||||||
|
listFileUploads: protectedProcedure
|
||||||
|
.input(z.object({ datasetId: z.string() }))
|
||||||
|
.query(async ({ input, ctx }) => {
|
||||||
|
const { projectId } = await prisma.dataset.findUniqueOrThrow({
|
||||||
|
where: { id: input.datasetId },
|
||||||
|
});
|
||||||
|
await requireCanViewProject(projectId, ctx);
|
||||||
|
|
||||||
|
return await prisma.datasetFileUpload.findMany({
|
||||||
|
where: {
|
||||||
|
datasetId: input.datasetId,
|
||||||
|
visible: true,
|
||||||
|
},
|
||||||
|
orderBy: { createdAt: "desc" },
|
||||||
|
});
|
||||||
|
}),
|
||||||
|
hideFileUpload: protectedProcedure
|
||||||
|
.input(z.object({ fileUploadId: z.string() }))
|
||||||
|
.mutation(async ({ input, ctx }) => {
|
||||||
|
const { datasetId } = await prisma.datasetFileUpload.findUniqueOrThrow({
|
||||||
|
where: { id: input.fileUploadId },
|
||||||
|
});
|
||||||
|
const { projectId } = await prisma.dataset.findUniqueOrThrow({
|
||||||
|
where: { id: datasetId },
|
||||||
|
});
|
||||||
|
await requireCanModifyProject(projectId, ctx);
|
||||||
|
|
||||||
|
await prisma.datasetFileUpload.update({
|
||||||
|
where: { id: input.fileUploadId },
|
||||||
|
data: {
|
||||||
|
visible: false,
|
||||||
|
},
|
||||||
|
});
|
||||||
|
}),
|
||||||
});
|
});
|
||||||
|
|||||||
132
app/src/server/tasks/importDatasetEntries.task.ts
Normal file
132
app/src/server/tasks/importDatasetEntries.task.ts
Normal file
@@ -0,0 +1,132 @@
|
|||||||
|
import { type DatasetFileUpload } from "@prisma/client";
|
||||||
|
import { prisma } from "~/server/db";
|
||||||
|
import defineTask from "./defineTask";
|
||||||
|
import { downloadBlobToString } from "~/utils/azure/server";
|
||||||
|
import {
|
||||||
|
type TrainingRow,
|
||||||
|
validateTrainingRows,
|
||||||
|
parseJSONL,
|
||||||
|
} from "~/components/datasets/validateTrainingRows";
|
||||||
|
import { formatEntriesFromTrainingRows } from "~/server/utils/createEntriesFromTrainingRows";
|
||||||
|
|
||||||
|
export type ImportDatasetEntriesJob = {
|
||||||
|
datasetFileUploadId: string;
|
||||||
|
};
|
||||||
|
|
||||||
|
export const importDatasetEntries = defineTask<ImportDatasetEntriesJob>(
|
||||||
|
"importDatasetEntries",
|
||||||
|
async (task) => {
|
||||||
|
const { datasetFileUploadId } = task;
|
||||||
|
const datasetFileUpload = await prisma.datasetFileUpload.findUnique({
|
||||||
|
where: { id: datasetFileUploadId },
|
||||||
|
});
|
||||||
|
if (!datasetFileUpload) {
|
||||||
|
await prisma.datasetFileUpload.update({
|
||||||
|
where: { id: datasetFileUploadId },
|
||||||
|
data: {
|
||||||
|
errorMessage: "Dataset File Upload not found",
|
||||||
|
status: "ERROR",
|
||||||
|
},
|
||||||
|
});
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
await prisma.datasetFileUpload.update({
|
||||||
|
where: { id: datasetFileUploadId },
|
||||||
|
data: {
|
||||||
|
status: "DOWNLOADING",
|
||||||
|
progress: 5,
|
||||||
|
},
|
||||||
|
});
|
||||||
|
|
||||||
|
const jsonlStr = await downloadBlobToString(datasetFileUpload.blobName);
|
||||||
|
const trainingRows = parseJSONL(jsonlStr) as TrainingRow[];
|
||||||
|
const validationError = validateTrainingRows(trainingRows);
|
||||||
|
if (validationError) {
|
||||||
|
await prisma.datasetFileUpload.update({
|
||||||
|
where: { id: datasetFileUploadId },
|
||||||
|
data: {
|
||||||
|
errorMessage: `Invalid JSONL: ${validationError}`,
|
||||||
|
status: "ERROR",
|
||||||
|
},
|
||||||
|
});
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
await prisma.datasetFileUpload.update({
|
||||||
|
where: { id: datasetFileUploadId },
|
||||||
|
data: {
|
||||||
|
status: "PROCESSING",
|
||||||
|
progress: 30,
|
||||||
|
},
|
||||||
|
});
|
||||||
|
|
||||||
|
const updatePromises: Promise<DatasetFileUpload>[] = [];
|
||||||
|
|
||||||
|
const updateCallback = async (progress: number) => {
|
||||||
|
await prisma.datasetFileUpload.update({
|
||||||
|
where: { id: datasetFileUploadId },
|
||||||
|
data: {
|
||||||
|
progress: 30 + Math.floor((progress / trainingRows.length) * 69),
|
||||||
|
},
|
||||||
|
});
|
||||||
|
};
|
||||||
|
|
||||||
|
let datasetEntriesToCreate;
|
||||||
|
try {
|
||||||
|
datasetEntriesToCreate = await formatEntriesFromTrainingRows(
|
||||||
|
datasetFileUpload.datasetId,
|
||||||
|
trainingRows,
|
||||||
|
updateCallback,
|
||||||
|
500,
|
||||||
|
);
|
||||||
|
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||||
|
} catch (e: any) {
|
||||||
|
await prisma.datasetFileUpload.update({
|
||||||
|
where: { id: datasetFileUploadId },
|
||||||
|
data: {
|
||||||
|
errorMessage: `Error formatting rows: ${e.message as string}`,
|
||||||
|
status: "ERROR",
|
||||||
|
},
|
||||||
|
});
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
await Promise.all(updatePromises);
|
||||||
|
|
||||||
|
await prisma.datasetFileUpload.update({
|
||||||
|
where: { id: datasetFileUploadId },
|
||||||
|
data: {
|
||||||
|
status: "SAVING",
|
||||||
|
progress: 99,
|
||||||
|
},
|
||||||
|
});
|
||||||
|
|
||||||
|
await prisma.datasetEntry.createMany({
|
||||||
|
data: datasetEntriesToCreate,
|
||||||
|
});
|
||||||
|
|
||||||
|
await prisma.datasetFileUpload.update({
|
||||||
|
where: { id: datasetFileUploadId },
|
||||||
|
data: {
|
||||||
|
status: "COMPLETE",
|
||||||
|
progress: 100,
|
||||||
|
},
|
||||||
|
});
|
||||||
|
},
|
||||||
|
);
|
||||||
|
|
||||||
|
export const queueImportDatasetEntries = async (datasetFileUploadId: string) => {
|
||||||
|
await Promise.all([
|
||||||
|
prisma.datasetFileUpload.update({
|
||||||
|
where: {
|
||||||
|
id: datasetFileUploadId,
|
||||||
|
},
|
||||||
|
data: {
|
||||||
|
errorMessage: null,
|
||||||
|
status: "PENDING",
|
||||||
|
},
|
||||||
|
}),
|
||||||
|
|
||||||
|
importDatasetEntries.enqueue({ datasetFileUploadId }),
|
||||||
|
]);
|
||||||
|
};
|
||||||
@@ -5,10 +5,11 @@ import "../../../sentry.server.config";
|
|||||||
import { env } from "~/env.mjs";
|
import { env } from "~/env.mjs";
|
||||||
import { queryModel } from "./queryModel.task";
|
import { queryModel } from "./queryModel.task";
|
||||||
import { runNewEval } from "./runNewEval.task";
|
import { runNewEval } from "./runNewEval.task";
|
||||||
|
import { importDatasetEntries } from "./importDatasetEntries.task";
|
||||||
|
|
||||||
console.log("Starting worker");
|
console.log("Starting worker");
|
||||||
|
|
||||||
const registeredTasks = [queryModel, runNewEval];
|
const registeredTasks = [queryModel, runNewEval, importDatasetEntries];
|
||||||
|
|
||||||
const taskList = registeredTasks.reduce((acc, task) => {
|
const taskList = registeredTasks.reduce((acc, task) => {
|
||||||
acc[task.task.identifier] = task.task.handler;
|
acc[task.task.identifier] = task.task.handler;
|
||||||
|
|||||||
70
app/src/server/utils/createEntriesFromTrainingRows.ts
Normal file
70
app/src/server/utils/createEntriesFromTrainingRows.ts
Normal file
@@ -0,0 +1,70 @@
|
|||||||
|
import { type Prisma } from "@prisma/client";
|
||||||
|
import { shuffle } from "lodash-es";
|
||||||
|
import {
|
||||||
|
type CreateChatCompletionRequestMessage,
|
||||||
|
type ChatCompletion,
|
||||||
|
} from "openai/resources/chat";
|
||||||
|
|
||||||
|
import { prisma } from "~/server/db";
|
||||||
|
import { type TrainingRow } from "~/components/datasets/validateTrainingRows";
|
||||||
|
import { countLlamaChatTokens } from "~/utils/countTokens";
|
||||||
|
|
||||||
|
export const formatEntriesFromTrainingRows = async (
|
||||||
|
datasetId: string,
|
||||||
|
trainingRows: TrainingRow[],
|
||||||
|
updateCallback?: (progress: number) => Promise<void>,
|
||||||
|
updateFrequency = 1000,
|
||||||
|
) => {
|
||||||
|
const [dataset, existingTrainingCount, existingTestingCount] = await prisma.$transaction([
|
||||||
|
prisma.dataset.findUnique({ where: { id: datasetId } }),
|
||||||
|
prisma.datasetEntry.count({
|
||||||
|
where: {
|
||||||
|
datasetId,
|
||||||
|
type: "TRAIN",
|
||||||
|
},
|
||||||
|
}),
|
||||||
|
prisma.datasetEntry.count({
|
||||||
|
where: {
|
||||||
|
datasetId,
|
||||||
|
type: "TEST",
|
||||||
|
},
|
||||||
|
}),
|
||||||
|
]);
|
||||||
|
|
||||||
|
const trainingRatio = dataset?.trainingRatio ?? 0.8;
|
||||||
|
|
||||||
|
const newTotalEntries = existingTrainingCount + existingTestingCount + trainingRows.length;
|
||||||
|
const numTrainingToAdd = Math.floor(trainingRatio * newTotalEntries) - existingTrainingCount;
|
||||||
|
const numTestingToAdd = trainingRows.length - numTrainingToAdd;
|
||||||
|
const typesToAssign = shuffle([
|
||||||
|
...Array(numTrainingToAdd).fill("TRAIN"),
|
||||||
|
...Array(numTestingToAdd).fill("TEST"),
|
||||||
|
]);
|
||||||
|
const datasetEntriesToCreate: Prisma.DatasetEntryCreateManyInput[] = [];
|
||||||
|
let i = 0;
|
||||||
|
for (const row of trainingRows) {
|
||||||
|
// console.log(row);
|
||||||
|
if (updateCallback && i % updateFrequency === 0) await updateCallback(i);
|
||||||
|
let outputTokens = 0;
|
||||||
|
if (row.output) {
|
||||||
|
outputTokens = countLlamaChatTokens([row.output as unknown as ChatCompletion.Choice.Message]);
|
||||||
|
}
|
||||||
|
// console.log("outputTokens", outputTokens);
|
||||||
|
datasetEntriesToCreate.push({
|
||||||
|
datasetId: datasetId,
|
||||||
|
input: row.input as unknown as Prisma.InputJsonValue,
|
||||||
|
output: (row.output as unknown as Prisma.InputJsonValue) ?? {
|
||||||
|
role: "assistant",
|
||||||
|
content: "",
|
||||||
|
},
|
||||||
|
inputTokens: countLlamaChatTokens(
|
||||||
|
row.input as unknown as CreateChatCompletionRequestMessage[],
|
||||||
|
),
|
||||||
|
outputTokens,
|
||||||
|
type: typesToAssign.pop() as "TRAIN" | "TEST",
|
||||||
|
});
|
||||||
|
i++;
|
||||||
|
}
|
||||||
|
|
||||||
|
return datasetEntriesToCreate;
|
||||||
|
};
|
||||||
71
app/src/utils/azure/server.ts
Normal file
71
app/src/utils/azure/server.ts
Normal file
@@ -0,0 +1,71 @@
|
|||||||
|
import {
|
||||||
|
BlobServiceClient,
|
||||||
|
generateAccountSASQueryParameters,
|
||||||
|
AccountSASPermissions,
|
||||||
|
AccountSASServices,
|
||||||
|
AccountSASResourceTypes,
|
||||||
|
StorageSharedKeyCredential,
|
||||||
|
SASProtocol,
|
||||||
|
} from "@azure/storage-blob";
|
||||||
|
import { DefaultAzureCredential } from "@azure/identity";
|
||||||
|
|
||||||
|
const accountName = process.env.AZURE_STORAGE_ACCOUNT_NAME;
|
||||||
|
if (!accountName) throw Error("Azure Storage accountName not found");
|
||||||
|
const accountKey = process.env.AZURE_STORAGE_ACCOUNT_KEY;
|
||||||
|
if (!accountKey) throw Error("Azure Storage accountKey not found");
|
||||||
|
const containerName = process.env.AZURE_STORAGE_CONTAINER_NAME;
|
||||||
|
if (!containerName) throw Error("Azure Storage containerName not found");
|
||||||
|
|
||||||
|
const sharedKeyCredential = new StorageSharedKeyCredential(accountName, accountKey);
|
||||||
|
|
||||||
|
const blobServiceClient = new BlobServiceClient(
|
||||||
|
`https://${accountName}.blob.core.windows.net`,
|
||||||
|
new DefaultAzureCredential(),
|
||||||
|
);
|
||||||
|
|
||||||
|
const containerClient = blobServiceClient.getContainerClient(containerName);
|
||||||
|
|
||||||
|
export const generateServiceClientUrl = () => {
|
||||||
|
const sasOptions = {
|
||||||
|
services: AccountSASServices.parse("b").toString(), // blobs
|
||||||
|
resourceTypes: AccountSASResourceTypes.parse("sco").toString(), // service, container, object
|
||||||
|
permissions: AccountSASPermissions.parse("w"), // write permissions
|
||||||
|
protocol: SASProtocol.Https,
|
||||||
|
startsOn: new Date(),
|
||||||
|
expiresOn: new Date(new Date().valueOf() + 10 * 60 * 1000), // 10 minutes
|
||||||
|
};
|
||||||
|
let sasToken = generateAccountSASQueryParameters(sasOptions, sharedKeyCredential).toString();
|
||||||
|
|
||||||
|
// remove leading "?"
|
||||||
|
sasToken = sasToken[0] === "?" ? sasToken.substring(1) : sasToken;
|
||||||
|
return {
|
||||||
|
serviceClientUrl: `https://${accountName}.blob.core.windows.net?${sasToken}`,
|
||||||
|
containerName,
|
||||||
|
};
|
||||||
|
};
|
||||||
|
|
||||||
|
export async function downloadBlobToString(blobName: string) {
|
||||||
|
const blobClient = containerClient.getBlobClient(blobName);
|
||||||
|
|
||||||
|
const downloadResponse = await blobClient.download();
|
||||||
|
|
||||||
|
if (!downloadResponse) throw Error("error downloading blob");
|
||||||
|
if (!downloadResponse.readableStreamBody)
|
||||||
|
throw Error("downloadResponse.readableStreamBody not found");
|
||||||
|
|
||||||
|
const downloaded = await streamToBuffer(downloadResponse.readableStreamBody);
|
||||||
|
return downloaded.toString();
|
||||||
|
}
|
||||||
|
|
||||||
|
async function streamToBuffer(readableStream: NodeJS.ReadableStream): Promise<Buffer> {
|
||||||
|
return new Promise((resolve, reject) => {
|
||||||
|
const chunks: Uint8Array[] = [];
|
||||||
|
readableStream.on("data", (data: ArrayBuffer) => {
|
||||||
|
chunks.push(data instanceof Buffer ? data : Buffer.from(data));
|
||||||
|
});
|
||||||
|
readableStream.on("end", () => {
|
||||||
|
resolve(Buffer.concat(chunks));
|
||||||
|
});
|
||||||
|
readableStream.on("error", reject);
|
||||||
|
});
|
||||||
|
}
|
||||||
30
app/src/utils/azure/website.ts
Normal file
30
app/src/utils/azure/website.ts
Normal file
@@ -0,0 +1,30 @@
|
|||||||
|
import { BlobServiceClient } from "@azure/storage-blob";
|
||||||
|
import { v4 as uuidv4 } from "uuid";
|
||||||
|
|
||||||
|
import { useAppStore } from "~/state/store";
|
||||||
|
|
||||||
|
export const uploadDatasetEntryFile = async (file: File) => {
|
||||||
|
const { selectedProjectId: projectId, api } = useAppStore.getState();
|
||||||
|
if (!projectId) throw Error("projectId not found");
|
||||||
|
if (!api) throw Error("api not initialized");
|
||||||
|
const { serviceClientUrl, containerName } = await api.client.datasets.getServiceClientUrl.query({
|
||||||
|
projectId,
|
||||||
|
});
|
||||||
|
|
||||||
|
const blobServiceClient = new BlobServiceClient(serviceClientUrl);
|
||||||
|
// create container client
|
||||||
|
const containerClient = blobServiceClient.getContainerClient(containerName);
|
||||||
|
|
||||||
|
// base name without extension
|
||||||
|
const basename = file.name.split("/").pop()?.split(".").shift();
|
||||||
|
if (!basename) throw Error("basename not found");
|
||||||
|
|
||||||
|
const blobName = `${basename}-${uuidv4()}.jsonl`;
|
||||||
|
// create blob client
|
||||||
|
const blobClient = containerClient.getBlockBlobClient(blobName);
|
||||||
|
|
||||||
|
// upload file
|
||||||
|
await blobClient.uploadData(file);
|
||||||
|
|
||||||
|
return blobName;
|
||||||
|
};
|
||||||
@@ -1,5 +1,7 @@
|
|||||||
import { type ChatCompletion } from "openai/resources/chat";
|
import { type ChatCompletion } from "openai/resources/chat";
|
||||||
import { GPTTokens } from "gpt-tokens";
|
import { GPTTokens } from "gpt-tokens";
|
||||||
|
import llamaTokenizer from "llama-tokenizer-js";
|
||||||
|
|
||||||
import { type SupportedModel } from "~/modelProviders/openai-ChatCompletion";
|
import { type SupportedModel } from "~/modelProviders/openai-ChatCompletion";
|
||||||
|
|
||||||
interface GPTTokensMessageItem {
|
interface GPTTokensMessageItem {
|
||||||
@@ -22,3 +24,11 @@ export const countOpenAIChatTokens = (
|
|||||||
messages: reformattedMessages as unknown as GPTTokensMessageItem[],
|
messages: reformattedMessages as unknown as GPTTokensMessageItem[],
|
||||||
}).usedTokens;
|
}).usedTokens;
|
||||||
};
|
};
|
||||||
|
|
||||||
|
export const countLlamaChatTokens = (messages: ChatCompletion.Choice.Message[]) => {
|
||||||
|
const stringToTokenize = messages
|
||||||
|
.map((message) => message.content || JSON.stringify(message.function_call))
|
||||||
|
.join("\n");
|
||||||
|
const tokens = llamaTokenizer.encode(stringToTokenize);
|
||||||
|
return tokens.length;
|
||||||
|
};
|
||||||
|
|||||||
@@ -52,3 +52,18 @@ export const parseableToFunctionCall = (str: string) => {
|
|||||||
|
|
||||||
return true;
|
return true;
|
||||||
};
|
};
|
||||||
|
|
||||||
|
export const formatFileSize = (bytes: number, decimals = 2) => {
|
||||||
|
if (bytes === 0) return "0 Bytes";
|
||||||
|
|
||||||
|
const k = 1024;
|
||||||
|
const dm = decimals < 0 ? 0 : decimals;
|
||||||
|
const sizes = ["Bytes", "KB", "MB", "GB", "TB"];
|
||||||
|
|
||||||
|
for (const size of sizes) {
|
||||||
|
if (bytes < k) return `${parseFloat(bytes.toFixed(dm))} ${size}`;
|
||||||
|
bytes /= k;
|
||||||
|
}
|
||||||
|
|
||||||
|
return "> 1024 TB";
|
||||||
|
};
|
||||||
|
|||||||
@@ -19,7 +19,9 @@
|
|||||||
"baseUrl": ".",
|
"baseUrl": ".",
|
||||||
"paths": {
|
"paths": {
|
||||||
"~/*": ["./src/*"]
|
"~/*": ["./src/*"]
|
||||||
}
|
},
|
||||||
|
"typeRoots": ["./types", "./node_modules/@types"],
|
||||||
|
"types": ["llama-tokenizer-js", "node"]
|
||||||
},
|
},
|
||||||
"include": [
|
"include": [
|
||||||
".eslintrc.cjs",
|
".eslintrc.cjs",
|
||||||
|
|||||||
4
app/types/llama-tokenizer-js/index.d.ts
vendored
Normal file
4
app/types/llama-tokenizer-js/index.d.ts
vendored
Normal file
@@ -0,0 +1,4 @@
|
|||||||
|
declare module "llama-tokenizer-js" {
|
||||||
|
export function encode(input: string): number[];
|
||||||
|
export function decode(input: number[]): string;
|
||||||
|
}
|
||||||
360
pnpm-lock.yaml
generated
360
pnpm-lock.yaml
generated
@@ -14,6 +14,12 @@ importers:
|
|||||||
'@apidevtools/json-schema-ref-parser':
|
'@apidevtools/json-schema-ref-parser':
|
||||||
specifier: ^10.1.0
|
specifier: ^10.1.0
|
||||||
version: 10.1.0
|
version: 10.1.0
|
||||||
|
'@azure/identity':
|
||||||
|
specifier: ^3.3.0
|
||||||
|
version: 3.3.0
|
||||||
|
'@azure/storage-blob':
|
||||||
|
specifier: 12.15.0
|
||||||
|
version: 12.15.0
|
||||||
'@babel/standalone':
|
'@babel/standalone':
|
||||||
specifier: ^7.22.9
|
specifier: ^7.22.9
|
||||||
version: 7.22.9
|
version: 7.22.9
|
||||||
@@ -143,6 +149,9 @@ importers:
|
|||||||
kysely-codegen:
|
kysely-codegen:
|
||||||
specifier: ^0.10.1
|
specifier: ^0.10.1
|
||||||
version: 0.10.1(kysely@0.26.1)(pg@8.11.2)
|
version: 0.10.1(kysely@0.26.1)(pg@8.11.2)
|
||||||
|
llama-tokenizer-js:
|
||||||
|
specifier: ^1.1.3
|
||||||
|
version: 1.1.3
|
||||||
lodash-es:
|
lodash-es:
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engines: {node: '>= 0.6.0'}
|
||||||
|
dev: false
|
||||||
|
|
||||||
/progress@2.0.3:
|
/progress@2.0.3:
|
||||||
resolution: {integrity: sha512-7PiHtLll5LdnKIMw100I+8xJXR5gW2QwWYkT6iJva0bXitZKa/XMrSbdmg3r2Xnaidz9Qumd0VPaMrZlF9V9sA==}
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|
||||||
engines: {node: '>=0.4.0'}
|
engines: {node: '>=0.4.0'}
|
||||||
@@ -8272,6 +8602,10 @@ packages:
|
|||||||
yoga-wasm-web: 0.3.3
|
yoga-wasm-web: 0.3.3
|
||||||
dev: false
|
dev: false
|
||||||
|
|
||||||
|
/sax@1.2.4:
|
||||||
|
resolution: {integrity: sha512-NqVDv9TpANUjFm0N8uM5GxL36UgKi9/atZw+x7YFnQ8ckwFGKrl4xX4yWtrey3UJm5nP1kUbnYgLopqWNSRhWw==}
|
||||||
|
dev: false
|
||||||
|
|
||||||
/scheduler@0.23.0:
|
/scheduler@0.23.0:
|
||||||
resolution: {integrity: sha512-CtuThmgHNg7zIZWAXi3AsyIzA3n4xx7aNyjwC2VJldO2LMVDhFK+63xGqq6CsJH4rTAt6/M+N4GhZiDYPx9eUw==}
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resolution: {integrity: sha512-CtuThmgHNg7zIZWAXi3AsyIzA3n4xx7aNyjwC2VJldO2LMVDhFK+63xGqq6CsJH4rTAt6/M+N4GhZiDYPx9eUw==}
|
||||||
dependencies:
|
dependencies:
|
||||||
@@ -8296,7 +8630,6 @@ packages:
|
|||||||
hasBin: true
|
hasBin: true
|
||||||
dependencies:
|
dependencies:
|
||||||
lru-cache: 6.0.0
|
lru-cache: 6.0.0
|
||||||
dev: true
|
|
||||||
|
|
||||||
/send@0.18.0:
|
/send@0.18.0:
|
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resolution: {integrity: sha512-qqWzuOjSFOuqPjFe4NOsMLafToQQwBSOEpS+FwEt3A2V3vKubTquT3vmLTQpFgMXp8AlFWFuP1qKaJZOtPpVXg==}
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resolution: {integrity: sha512-qqWzuOjSFOuqPjFe4NOsMLafToQQwBSOEpS+FwEt3A2V3vKubTquT3vmLTQpFgMXp8AlFWFuP1qKaJZOtPpVXg==}
|
||||||
@@ -8504,6 +8837,11 @@ packages:
|
|||||||
resolution: {integrity: sha512-Rz6yejtVyWnVjC1RFvNmYL10kgjC49EOghxWn0RFqlCHGFpQx+Xe7yW3I4ceK1SGrWIGMjD5Kbue8W/udkbMJg==}
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resolution: {integrity: sha512-Rz6yejtVyWnVjC1RFvNmYL10kgjC49EOghxWn0RFqlCHGFpQx+Xe7yW3I4ceK1SGrWIGMjD5Kbue8W/udkbMJg==}
|
||||||
dev: true
|
dev: true
|
||||||
|
|
||||||
|
/stoppable@1.1.0:
|
||||||
|
resolution: {integrity: sha512-KXDYZ9dszj6bzvnEMRYvxgeTHU74QBFL54XKtP3nyMuJ81CFYtABZ3bAzL2EdFUaEwJOBOgENyFj3R7oTzDyyw==}
|
||||||
|
engines: {node: '>=4', npm: '>=6'}
|
||||||
|
dev: false
|
||||||
|
|
||||||
/stream-buffers@3.0.2:
|
/stream-buffers@3.0.2:
|
||||||
resolution: {integrity: sha512-DQi1h8VEBA/lURbSwFtEHnSTb9s2/pwLEaFuNhXwy1Dx3Sa0lOuYT2yNUr4/j2fs8oCAMANtrZ5OrPZtyVs3MQ==}
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resolution: {integrity: sha512-DQi1h8VEBA/lURbSwFtEHnSTb9s2/pwLEaFuNhXwy1Dx3Sa0lOuYT2yNUr4/j2fs8oCAMANtrZ5OrPZtyVs3MQ==}
|
||||||
engines: {node: '>= 0.10.0'}
|
engines: {node: '>= 0.10.0'}
|
||||||
@@ -8876,6 +9214,11 @@ packages:
|
|||||||
safe-buffer: 5.2.1
|
safe-buffer: 5.2.1
|
||||||
dev: false
|
dev: false
|
||||||
|
|
||||||
|
/tunnel@0.0.6:
|
||||||
|
resolution: {integrity: sha512-1h/Lnq9yajKY2PEbBadPXj3VxsDDu844OnaAo52UVmIzIvwwtBPIuNvkjuzBlTWpfJyUbG3ez0KSBibQkj4ojg==}
|
||||||
|
engines: {node: '>=0.6.11 <=0.7.0 || >=0.7.3'}
|
||||||
|
dev: false
|
||||||
|
|
||||||
/tweetnacl@0.14.5:
|
/tweetnacl@0.14.5:
|
||||||
resolution: {integrity: sha512-KXXFFdAbFXY4geFIwoyNK+f5Z1b7swfXABfL7HXCmoIWMKU3dmS26672A4EeQtDzLKy7SXmfBu51JolvEKwtGA==}
|
resolution: {integrity: sha512-KXXFFdAbFXY4geFIwoyNK+f5Z1b7swfXABfL7HXCmoIWMKU3dmS26672A4EeQtDzLKy7SXmfBu51JolvEKwtGA==}
|
||||||
dev: false
|
dev: false
|
||||||
@@ -9464,6 +9807,19 @@ packages:
|
|||||||
optional: true
|
optional: true
|
||||||
dev: false
|
dev: false
|
||||||
|
|
||||||
|
/xml2js@0.5.0:
|
||||||
|
resolution: {integrity: sha512-drPFnkQJik/O+uPKpqSgr22mpuFHqKdbS835iAQrUC73L2F5WkboIRd63ai/2Yg6I1jzifPFKH2NTK+cfglkIA==}
|
||||||
|
engines: {node: '>=4.0.0'}
|
||||||
|
dependencies:
|
||||||
|
sax: 1.2.4
|
||||||
|
xmlbuilder: 11.0.1
|
||||||
|
dev: false
|
||||||
|
|
||||||
|
/xmlbuilder@11.0.1:
|
||||||
|
resolution: {integrity: sha512-fDlsI/kFEx7gLvbecc0/ohLG50fugQp8ryHzMTuW9vSa1GJ0XYWKnhsUx7oie3G98+r56aTQIUB4kht42R3JvA==}
|
||||||
|
engines: {node: '>=4.0'}
|
||||||
|
dev: false
|
||||||
|
|
||||||
/xmlhttprequest-ssl@2.0.0:
|
/xmlhttprequest-ssl@2.0.0:
|
||||||
resolution: {integrity: sha512-QKxVRxiRACQcVuQEYFsI1hhkrMlrXHPegbbd1yn9UHOmRxY+si12nQYzri3vbzt8VdTTRviqcKxcyllFas5z2A==}
|
resolution: {integrity: sha512-QKxVRxiRACQcVuQEYFsI1hhkrMlrXHPegbbd1yn9UHOmRxY+si12nQYzri3vbzt8VdTTRviqcKxcyllFas5z2A==}
|
||||||
engines: {node: '>=0.4.0'}
|
engines: {node: '>=0.4.0'}
|
||||||
|
|||||||
Reference in New Issue
Block a user