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✨ Switch to nodenext resolution (#1026)
Seems necessary for #1025 - also handle #1001 (only for tasks at the moment) cc @martin-gorner also so that https://arethetypeswrong.github.io/?p=@huggingface/tasks is :heavy_check_mark: cc @Pierrci - in addition to the .cts exports And finally export snippets types (https://github.com/huggingface-internal/moon-landing/pull/10998/files#r1841375306) Types pass: https://arethetypeswrong.github.io/?p=%40huggingface%2Ftasks%400.13.0-test5 !
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‎packages/gguf/src/gguf.spec.ts

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@@ -33,7 +33,7 @@ describe("gguf", () => {
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const arrayBuf = await res.arrayBuffer();
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fs.writeFileSync(".cache/model.gguf", Buffer.from(arrayBuf));
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}
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});
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}, 30_000);
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it("should parse a llama2 7b", async () => {
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const { metadata, tensorInfos } = await gguf(URL_LLAMA);

‎packages/tasks/package.json

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},
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"main": "./dist/index.cjs",
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"module": "./dist/index.js",
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"types": "./dist/src/index.d.ts",
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"types": "./dist/index.d.ts",
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"exports": {
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".": {
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"types": "./dist/src/index.d.ts",
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"require": "./dist/index.cjs",
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"import": "./dist/index.js"
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}
@@ -24,13 +23,14 @@
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"format": "prettier --write .",
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"format:check": "prettier --check .",
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"prepublishOnly": "pnpm run inference-codegen && git diff --name-only --exit-code src && pnpm run build",
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"build": "tsup src/index.ts --format cjs,esm --clean && tsc --emitDeclarationOnly --declaration",
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"build": "tsup src/index.ts --format cjs,esm --clean && tsc --emitDeclarationOnly --declaration && pnpm run generate-cts",
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"watch:export": "tsup src/index.ts --format cjs,esm --watch",
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"watch:types": "tsc --emitDeclarationOnly --declaration --watch",
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"watch": "npm-run-all --parallel watch:export watch:types",
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"prepare": "pnpm run build",
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"check": "tsc",
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"test": "vitest run",
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"generate-cts": "tsx scripts/generate-cts.ts",
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"inference-codegen": "tsx scripts/inference-codegen.ts && prettier --write src/tasks/*/inference.ts",
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"inference-tgi-import": "tsx scripts/inference-tgi-import.ts && prettier --write src/tasks/text-generation/spec/*.json && prettier --write src/tasks/chat-completion/spec/*.json",
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"inference-tei-import": "tsx scripts/inference-tei-import.ts && prettier --write src/tasks/feature-extraction/spec/*.json"

‎packages/tasks/scripts/generate-cts.ts

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// Just copy over the already generated .d.ts and .d.ts.map files to .d.cts and .d.cts.map files
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import { readdirSync, readFileSync, statSync, writeFileSync } from "node:fs";
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import { join } from "node:path";
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function recursiveCopy(path: string) {
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for (const item of readdirSync(path)) {
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if (item.endsWith(".d.ts")) {
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const content = readFileSync(join(path, item), "utf-8");
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writeFileSync(join(path, item.replace(".d.ts", ".d.cts")), content.replaceAll(".d.ts.map", ".d.cts.map"));
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} else if (item.endsWith(".d.ts.map")) {
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const content = readFileSync(join(path, item), "utf-8");
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writeFileSync(join(path, item.replace(".d.ts.map", ".d.cts.map")), content.replaceAll(".d.ts", ".d.cts"));
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} else if (statSync(join(path, item)).isDirectory()) {
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recursiveCopy(join(path, item));
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}
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}
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}
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recursiveCopy("dist");

‎packages/tasks/src/default-widget-inputs.ts

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@@ -1,5 +1,5 @@
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import type { WidgetExample } from "./widget-example";
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import type { WidgetType } from "./pipelines";
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import type { WidgetExample } from "./widget-example.js";
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import type { WidgetType } from "./pipelines.js";
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type LanguageCode = string;
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‎packages/tasks/src/index.ts

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@@ -1,7 +1,7 @@
1-
export { LIBRARY_TASK_MAPPING } from "./library-to-tasks";
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export { MAPPING_DEFAULT_WIDGET } from "./default-widget-inputs";
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export type { TaskData, TaskDemo, TaskDemoEntry, ExampleRepo } from "./tasks";
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export * from "./tasks";
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export { LIBRARY_TASK_MAPPING } from "./library-to-tasks.js";
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export { MAPPING_DEFAULT_WIDGET } from "./default-widget-inputs.js";
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export type { TaskData, TaskDemo, TaskDemoEntry, ExampleRepo } from "./tasks/index.js";
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export * from "./tasks/index.js";
55
export {
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PIPELINE_DATA,
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PIPELINE_TYPES,
@@ -13,11 +13,15 @@ export {
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MODALITY_LABELS,
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SUBTASK_TYPES,
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PIPELINE_TYPES_SET,
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} from "./pipelines";
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export { ALL_DISPLAY_MODEL_LIBRARY_KEYS, ALL_MODEL_LIBRARY_KEYS, MODEL_LIBRARIES_UI_ELEMENTS } from "./model-libraries";
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export type { LibraryUiElement, ModelLibraryKey } from "./model-libraries";
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export type { ModelData, TransformersInfo } from "./model-data";
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export type { AddedToken, SpecialTokensMap, TokenizerConfig } from "./tokenizer-data";
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} from "./pipelines.js";
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export {
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ALL_DISPLAY_MODEL_LIBRARY_KEYS,
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ALL_MODEL_LIBRARY_KEYS,
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MODEL_LIBRARIES_UI_ELEMENTS,
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} from "./model-libraries.js";
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export type { LibraryUiElement, ModelLibraryKey } from "./model-libraries.js";
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export type { ModelData, TransformersInfo } from "./model-data.js";
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export type { AddedToken, SpecialTokensMap, TokenizerConfig } from "./tokenizer-data.js";
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export type {
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WidgetExample,
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WidgetExampleAttribute,
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WidgetExampleOutputLabels,
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WidgetExampleOutputAnswerScore,
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WidgetExampleOutputText,
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} from "./widget-example";
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export { SPECIAL_TOKENS_ATTRIBUTES } from "./tokenizer-data";
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} from "./widget-example.js";
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export { SPECIAL_TOKENS_ATTRIBUTES } from "./tokenizer-data.js";
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import * as snippets from "./snippets";
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export * from "./gguf";
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import * as snippets from "./snippets/index.js";
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export * from "./gguf.js";
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export { snippets };
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export { SKUS, DEFAULT_MEMORY_OPTIONS } from "./hardware";
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export type { HardwareSpec, SkuType } from "./hardware";
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export { LOCAL_APPS } from "./local-apps";
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export type { LocalApp, LocalAppKey, LocalAppSnippet } from "./local-apps";
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export { SKUS, DEFAULT_MEMORY_OPTIONS } from "./hardware.js";
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export type { HardwareSpec, SkuType } from "./hardware.js";
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export { LOCAL_APPS } from "./local-apps.js";
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export type { LocalApp, LocalAppKey, LocalAppSnippet } from "./local-apps.js";
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export { DATASET_LIBRARIES_UI_ELEMENTS } from "./dataset-libraries";
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export type { DatasetLibraryUiElement, DatasetLibraryKey } from "./dataset-libraries";
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export { DATASET_LIBRARIES_UI_ELEMENTS } from "./dataset-libraries.js";
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export type { DatasetLibraryUiElement, DatasetLibraryKey } from "./dataset-libraries.js";

‎packages/tasks/src/library-to-tasks.ts

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import type { ModelLibraryKey } from "./model-libraries";
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import type { PipelineType } from "./pipelines";
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import type { ModelLibraryKey } from "./model-libraries.js";
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import type { PipelineType } from "./pipelines.js";
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/**
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* Mapping from library name to its supported tasks.

‎packages/tasks/src/local-apps.ts

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import { parseGGUFQuantLabel } from "./gguf";
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import type { ModelData } from "./model-data";
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import type { PipelineType } from "./pipelines";
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import { parseGGUFQuantLabel } from "./gguf.js";
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import type { ModelData } from "./model-data.js";
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import type { PipelineType } from "./pipelines.js";
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export interface LocalAppSnippet {
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/**

‎packages/tasks/src/model-data.ts

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import type { PipelineType } from "./pipelines";
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import type { WidgetExample } from "./widget-example";
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import type { TokenizerConfig } from "./tokenizer-data";
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import type { PipelineType } from "./pipelines.js";
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import type { WidgetExample } from "./widget-example.js";
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import type { TokenizerConfig } from "./tokenizer-data.js";
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/**
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* Public interface for model metadata

‎packages/tasks/src/model-libraries-snippets.ts

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import type { ModelData } from "./model-data";
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import type { WidgetExampleTextInput, WidgetExampleSentenceSimilarityInput } from "./widget-example";
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import { LIBRARY_TASK_MAPPING } from "./library-to-tasks";
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import type { ModelData } from "./model-data.js";
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import type { WidgetExampleTextInput, WidgetExampleSentenceSimilarityInput } from "./widget-example.js";
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import { LIBRARY_TASK_MAPPING } from "./library-to-tasks.js";
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const TAG_CUSTOM_CODE = "custom_code";
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‎packages/tasks/src/model-libraries.ts

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import * as snippets from "./model-libraries-snippets";
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import type { ModelData } from "./model-data";
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import type { ElasticSearchQuery } from "./model-libraries-downloads";
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import * as snippets from "./model-libraries-snippets.js";
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import type { ModelData } from "./model-data.js";
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import type { ElasticSearchQuery } from "./model-libraries-downloads.js";
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/**
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* Elements configurable by a model library.

‎packages/tasks/src/snippets/common.ts

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import type { ChatCompletionInputMessage, GenerationParameters } from "../tasks";
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import type { ChatCompletionInputMessage, GenerationParameters } from "../tasks/index.js";
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export function stringifyMessages(
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messages: ChatCompletionInputMessage[],

‎packages/tasks/src/snippets/curl.spec.ts

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1-
import type { ModelDataMinimal } from "./types";
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import type { ModelDataMinimal } from "./types.js";
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import { describe, expect, it } from "vitest";
3-
import { getCurlInferenceSnippet } from "./curl";
3+
import { getCurlInferenceSnippet } from "./curl.js";
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describe("inference API snippets", () => {
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it("conversational llm", async () => {

‎packages/tasks/src/snippets/index.ts

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import * as inputs from "./inputs";
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import * as curl from "./curl";
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import * as python from "./python";
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import * as js from "./js";
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import * as inputs from "./inputs.js";
2+
import * as curl from "./curl.js";
3+
import * as python from "./python.js";
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import * as js from "./js.js";
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export * from "./types.js";
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export { inputs, curl, python, js };

‎packages/tasks/src/snippets/inputs.ts

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import type { PipelineType } from "../pipelines";
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import type { ChatCompletionInputMessage } from "../tasks";
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import type { ModelDataMinimal } from "./types";
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import type { PipelineType } from "../pipelines.js";
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import type { ChatCompletionInputMessage } from "../tasks/index.js";
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import type { ModelDataMinimal } from "./types.js";
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const inputsZeroShotClassification = () =>
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`"Hi, I recently bought a device from your company but it is not working as advertised and I would like to get reimbursed!"`;

‎packages/tasks/src/snippets/js.spec.ts

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import type { InferenceSnippet, ModelDataMinimal } from "./types";
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import type { InferenceSnippet, ModelDataMinimal } from "./types.js";
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import { describe, expect, it } from "vitest";
3-
import { getJsInferenceSnippet } from "./js";
3+
import { getJsInferenceSnippet } from "./js.js";
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describe("inference API snippets", () => {
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it("conversational llm", async () => {

‎packages/tasks/src/snippets/python.spec.ts

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import type { InferenceSnippet, ModelDataMinimal } from "./types";
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import type { InferenceSnippet, ModelDataMinimal } from "./types.js";
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import { describe, expect, it } from "vitest";
3-
import { getPythonInferenceSnippet } from "./python";
3+
import { getPythonInferenceSnippet } from "./python.js";
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describe("inference API snippets", () => {
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it("conversational llm", async () => {

‎packages/tasks/src/snippets/types.ts

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import type { ModelData } from "../model-data";
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import type { ModelData } from "../model-data.js";
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/**
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* Minimal model data required for snippets.

‎packages/tasks/src/tasks/audio-classification/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/audio-to-audio/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/automatic-speech-recognition/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/depth-estimation/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/document-question-answering/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/feature-extraction/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/fill-mask/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/image-classification/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/image-feature-extraction/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/image-segmentation/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/image-text-to-text/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/image-to-3d/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/image-to-image/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

‎packages/tasks/src/tasks/image-to-text/data.ts

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import type { TaskDataCustom } from "..";
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import type { TaskDataCustom } from "../index.js";
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const taskData: TaskDataCustom = {
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datasets: [

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