@promptbook/azure-openai
Version:
Promptbook: Run AI apps in plain human language across multiple models and platforms
54 lines (53 loc) • 2.01 kB
TypeScript
import type { FormatCommand } from '../../commands/FORMAT/FormatCommand';
import { ExpectError } from '../../errors/ExpectError';
import type { Expectations } from '../../pipeline/PipelineJson/Expectations';
import type { string_postprocessing_function_name } from '../../types/typeAliases';
/**
* Options for validating a prompt result
*/
export interface ValidatePromptResultOptions {
/**
* The result string to validate
*/
resultString: string;
/**
* Expectations for the result (word count, sentence count, etc.)
*/
expectations?: Expectations;
/**
* Expected format of the result (e.g., 'JSON')
*/
format?: FormatCommand['format'];
/**
* List of postprocessing function names that should be applied
* Note: This is for validation purposes only - postprocessing should be done before calling this function
*/
postprocessingFunctionNames?: ReadonlyArray<string_postprocessing_function_name>;
}
/**
* Result of prompt result validation
*/
export interface ValidatePromptResultResult {
/**
* Whether the result is valid (passes all expectations and format checks)
*/
isValid: boolean;
/**
* The processed result string (may be modified if format extraction was needed)
*/
processedResultString: string;
/**
* Error that occurred during validation, if any
*/
error?: ExpectError;
}
/**
* Validates a prompt result against expectations and format requirements.
* This function provides a common abstraction for result validation that can be used
* by both execution logic and caching logic to ensure consistency.
*
* @param options - The validation options including result string, expectations, and format
* @returns Validation result with processed string and validity status
* @private internal function of `createPipelineExecutor` and `cacheLlmTools`
*/
export declare function validatePromptResult(options: ValidatePromptResultOptions): ValidatePromptResultResult;