Fix typos (#2714)
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1619478250
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81e8889568
@ -79,7 +79,7 @@ common:
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securityContext: {}
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service:
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extenalLabel: {}
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externalLabel: {}
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type: ClusterIP
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port: 1337
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targetPort: 1337
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@ -193,7 +193,7 @@ common:
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securityContext: {}
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service:
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extenalLabel: {}
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externalLabel: {}
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type: ClusterIP
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port: 3000
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targetPort: 3000
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@ -60,7 +60,7 @@ const joinPath: (paths: string[]) => Promise<string> = (paths) =>
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globalThis.core.api?.joinPath(paths)
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/**
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* Retrive the basename from an url.
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* Retrieve the basename from an url.
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* @param path - The path to retrieve.
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* @returns {Promise<string>} A promise that resolves with the basename.
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*/
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@ -4,7 +4,7 @@ import { log } from './logger'
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export const getSystemResourceInfo = async (): Promise<SystemResourceInfo> => {
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const cpu = await physicalCpuCount()
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log(`[NITRO]::CPU informations - ${cpu}`)
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log(`[NITRO]::CPU information - ${cpu}`)
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return {
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numCpuPhysicalCore: cpu,
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@ -22,7 +22,7 @@ export const getSelectedText = async () => {
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/**
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* Registers a global shortcut of `accelerator`. The `callback` is called
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* with the selected text when the registered shorcut is pressed by the user
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* with the selected text when the registered shortcut is pressed by the user
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*
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* Returns `true` if the shortcut was registered successfully
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*/
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@ -3,7 +3,7 @@ import { app } from 'electron'
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export const setupCore = async () => {
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// Setup core api for main process
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global.core = {
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// Define appPath function for app to retrieve app path globaly
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// Define appPath function for app to retrieve app path globally
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appPath: () => app.getPath('userData'),
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}
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}
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@ -42,7 +42,7 @@ export default class JanInferenceNitroExtension extends LocalOAIEngine {
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/**
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* The interval id for the health check. Used to stop the health check.
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*/
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private getNitroProcesHealthIntervalId: NodeJS.Timeout | undefined = undefined
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private getNitroProcessHealthIntervalId: NodeJS.Timeout | undefined = undefined
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/**
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* Tracking the current state of nitro process.
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@ -65,7 +65,7 @@ export default class JanInferenceNitroExtension extends LocalOAIEngine {
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this.inferenceUrl = `${window.core?.api?.baseApiUrl}/v1/chat/completions`
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}
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this.getNitroProcesHealthIntervalId = setInterval(
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this.getNitroProcessHealthIntervalId = setInterval(
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() => this.periodicallyGetNitroHealth(),
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JanInferenceNitroExtension._intervalHealthCheck
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)
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@ -95,7 +95,7 @@ export default class JanInferenceNitroExtension extends LocalOAIEngine {
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override loadModel(model: Model): Promise<void> {
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if (model.engine !== this.provider) return Promise.resolve()
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this.getNitroProcesHealthIntervalId = setInterval(
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this.getNitroProcessHealthIntervalId = setInterval(
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() => this.periodicallyGetNitroHealth(),
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JanInferenceNitroExtension._intervalHealthCheck
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)
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@ -106,9 +106,9 @@ export default class JanInferenceNitroExtension extends LocalOAIEngine {
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if (model?.engine && model.engine !== this.provider) return
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// stop the periocally health check
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if (this.getNitroProcesHealthIntervalId) {
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clearInterval(this.getNitroProcesHealthIntervalId)
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this.getNitroProcesHealthIntervalId = undefined
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if (this.getNitroProcessHealthIntervalId) {
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clearInterval(this.getNitroProcessHealthIntervalId)
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this.getNitroProcessHealthIntervalId = undefined
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}
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return super.unloadModel(model)
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}
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@ -136,7 +136,7 @@ export const getCurrentLoad = () =>
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})
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/**
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* This will retrive GPU informations and persist settings.json
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* This will retrieve GPU information and persist settings.json
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* Will be called when the extension is loaded to turn on GPU acceleration if supported
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*/
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export const updateNvidiaInfo = async () => {
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@ -53,7 +53,7 @@ export class FileLogger extends Logger {
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daysToKeep?: number | undefined
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): void {
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// clear existing timeout
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// incase we rerun it with different values
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// in case we rerun it with different values
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if (this.timeout) clearTimeout(this.timeout)
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this.timeout = undefined
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@ -12,7 +12,7 @@ export async function setup() {
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if (!existsSync(appDir)) mkdirSync(appDir)
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//@ts-ignore
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global.core = {
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// Define appPath function for app to retrieve app path globaly
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// Define appPath function for app to retrieve app path globally
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appPath: () => appDir,
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}
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init({
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@ -22,7 +22,7 @@
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* This ADR aims to outline design decisions for deploying Jan in cloud native environments such as: Runpod, AWS, Azure, GCP in a fast and simple way.
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* The current code-base should not change too much.
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* The current plugins must be reusable across enviroments (Desktop, Cloud-native).
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* The current plugins must be reusable across environments (Desktop, Cloud-native).
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### Key Design Decisions
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@ -14,8 +14,8 @@ Modular Architecture w/ Plugins:
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- Jan will have an architecture similar to VSCode or k8Lens
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- "Desktop Application" whose functionality can be extended thru plugins
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- Jan's architecture will need to accomodate plugins for (a) Persistence(b) IAM(c) Teams and RBAC(d) Policy engines(e) "Apps" (i.e. higher-order business logic)(f) Themes (UI)
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- Nitro's architecture will need to accomodate plugins for different "model backends"(a) llama.cpp(b) rkwk (and others)(c) 3rd-party AIs
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- Jan's architecture will need to accommodate plugins for (a) Persistence(b) IAM(c) Teams and RBAC(d) Policy engines(e) "Apps" (i.e. higher-order business logic)(f) Themes (UI)
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- Nitro's architecture will need to accommodate plugins for different "model backends"(a) llama.cpp(b) rkwk (and others)(c) 3rd-party AIs
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## Decision
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@ -14,7 +14,7 @@ Proposed
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## Context
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What is the issue that we're seeing that is motivating this decision or change?
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- The A.I world is moving fast with multiple runtime/ prebaked environment. We or the builder cannot cover just everything but rather we should adopt it and facillitate it as much as possible within Jan.
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- The A.I world is moving fast with multiple runtime/ prebaked environment. We or the builder cannot cover just everything but rather we should adopt it and facilitate it as much as possible within Jan.
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- For `Run your own A.I`: Builder can build app on Jan (NodeJS env) and connect to external endpoint which serves the real A.I
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- e.g 1: Nitro acting as proxy to `triton-inference-server` running within a Docker container controlled by Jan app
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- e.g 2: Original models can be in many formats (pytorch, paddlepaddle). In order to run it with the most optimized version locally, there must be a step to transpile the model ([Ollama import model](https://github.com/jmorganca/ollama/blob/main/docs/import.md), Tensorrt). Btw Jan can prebuilt it and let user pull but later
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@ -62,7 +62,7 @@ export default function Error({
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>
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contact us
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</a>{' '}
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if the problem presists.
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if the problem persists.
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</p>
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<div
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className="mt-5 w-full rounded border border-red-400 bg-red-100 px-4 py-3 text-red-700"
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@ -44,8 +44,8 @@ export enum UsecaseTag {
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UsecaseDefault = 'UsecaseDefault',
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}
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export enum MiscellanousTag {
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MiscellanousDefault = 'MiscellanousDefault',
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export enum MiscellaneousTag {
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MiscellaneousDefault = 'MiscellaneousDefault',
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}
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export type TagType =
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@ -59,4 +59,4 @@ export type TagType =
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| NumOfBit
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| RamRequired
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| UsecaseTag
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| MiscellanousTag
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| MiscellaneousTag
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@ -138,7 +138,7 @@ const DropdownListSidebar = ({
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...model?.parameters,
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...model?.settings,
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}
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// Update model paramter to the thread state
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// Update model parameter to the thread state
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setThreadModelParams(activeThread.id, modelParams)
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// Update model parameter to the thread file
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@ -107,7 +107,7 @@ export default function useGetSystemResources() {
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return {
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/**
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* Fetch resource informations once
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* Fetch resource information once
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*/
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getSystemResources,
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/**
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@ -18,7 +18,7 @@ export const HuggingFaceConvertingErrorModal = () => {
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</div>
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<div className="flex flex-col items-center justify-center gap-1">
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<p className="text-center">
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An error occured while {conversionStatus} model {repoData.id}.
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An error occurred while {conversionStatus} model {repoData.id}.
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</p>
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<p>Please close this modal and try again.</p>
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</div>
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@ -21,7 +21,7 @@ export const HuggingFaceSearchModal = () => {
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return (
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<>
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<div className="flex flex-col items-center justify-center gap-1">
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<p className="text-2xl font-bold">Hugging Face Convertor</p>
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<p className="text-2xl font-bold">Hugging Face Converter</p>
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<p className="text-gray-500">Type the repository id below</p>
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</div>
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<Input
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