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langextract

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A TypeScript library for extracting structured and grounded information from text using LLMs

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/** * Copyright 2025 kmbro. * * This is a TypeScript translation of the original Python LangExtract library * by Google LLC (https://github.com/google/langextract). * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ import { ExampleData, FormatType } from "./types"; export declare class PromptBuilderError extends Error { constructor(message: string); } export declare class ParseError extends PromptBuilderError { constructor(message: string); } export interface PromptTemplateStructured { description: string; examples: ExampleData[]; } /** * Reads a structured prompt template from a file. */ export declare function readPromptTemplateStructuredFromFile(promptPath: string): PromptTemplateStructured; export interface QAPromptGenerator { template: PromptTemplateStructured; formatType: FormatType; attributeSuffix: string; examplesHeading: string; questionPrefix: string; answerPrefix: string; fenceOutput: boolean; } export declare class QAPromptGeneratorImpl implements QAPromptGenerator { template: PromptTemplateStructured; formatType: FormatType; attributeSuffix: string; examplesHeading: string; questionPrefix: string; answerPrefix: string; fenceOutput: boolean; constructor(template: PromptTemplateStructured); formatExampleAsText(example: ExampleData): string; render(question: string, additionalContext?: string): string; toString(): string; } //# sourceMappingURL=prompting.d.ts.map