@microsoft/teams-ai/lib/prompts/PromptManager.d.ts

SDK focused on building AI based applications for Microsoft Teams.

/**
 * @module teams-ai
 */
/**
 * Copyright (c) Microsoft Corporation. All rights reserved.
 * Licensed under the MIT License.
 */
import { TurnContext } from 'botbuilder';
import { DataSource } from '../dataSources';
import { Memory } from '../MemoryFork';
import { Tokenizer } from '../tokenizers';
import { PromptTemplate } from './PromptTemplate';
import { PromptFunctions, PromptFunction } from './PromptFunctions';
/**
 * Options used to configure the prompt manager.
 */
export interface PromptManagerOptions {
    /**
     * Path to the filesystem folder containing all the application's prompts.
     */
    promptsFolder: string;
    /**
     * Optional. Message role to use for loaded prompts.
     * @remarks
     * Defaults to 'system'.
     */
    role?: string;
    /**
     * Optional. Maximum number of tokens of conversation history to include in prompts.
     * @remarks
     * The default is to let conversation history consume the remainder of the prompts
     * `max_input_tokens` budget. Setting this to a value greater than 1 will override that and
     * all prompts will use a fixed token budget.
     */
    max_conversation_history_tokens?: number;
    /**
     * Optional. Maximum number of messages to use when rendering conversation_history.
     * @remarks
     * This controls the automatic pruning of the conversation history that's done by the planners
     * LLMClient instance. This helps keep your memory from getting too big and defaults to a value
     * of `10` (or 5 turns.)
     */
    max_history_messages?: number;
    /**
     * Optional. Maximum number of tokens user input to include in prompts.
     * @remarks
     * This defaults to unlimited but can be set to a value greater than `1` to limit the length of
     * user input included in prompts. For example, if set to `100` then the any user input over
     * 100 tokens in length will be truncated.
     */
    max_input_tokens?: number;
}
/**
 * The configured PromptManager options.
 */
export interface ConfiguredPromptManagerOptions {
    /**
     * Path to the filesystem folder containing all the applications prompts.
     */
    promptsFolder: string;
    /**
     * Message role to use for loaded prompts.
     */
    role: string;
    /**
     * Maximum number of tokens of conversation history to include in prompts.
     */
    max_conversation_history_tokens: number;
    /**
     * Maximum number of messages to use when rendering conversation_history.
     */
    max_history_messages: number;
    /**
     * Maximum number of tokens of user input to include in prompts.
     */
    max_input_tokens: number;
}
/**
 * A filesystem based prompt manager.
 * @remarks
 * The default prompt manager uses the file system to define prompts that are compatible with
 * Microsoft's Semantic Kernel SDK (see: https://github.com/microsoft/semantic-kernel)
 *
 * Each prompt is a separate folder under a root prompts folder. The folder should contain the following files:
 *
 * - "config.json": Required. Contains the prompts configuration and is a serialized instance of `PromptTemplateConfig`.
 * - "skprompt.txt": Required. Contains the text of the prompt and supports Semantic Kernels prompt template syntax.
 * - "actions.json": Optional. Contains a list of actions that can be called by the prompt.
 *
 * Prompts can be loaded and used by name and new dynamically defined prompt templates can be
 * registered with the prompt manager.
 * @template TState Optional. Type of the applications turn state.
 */
export declare class PromptManager implements PromptFunctions {
    private readonly _options;
    private readonly _dataSources;
    private readonly _functions;
    private readonly _prompts;
    /**
     * Creates a new 'PromptManager' instance.
     * @param {PromptManagerOptions} options - Options used to configure the prompt manager.
     * @returns {PromptManager} A new prompt manager instance.
     */
    constructor(options: PromptManagerOptions);
    /**
     * Gets the configured prompt manager options.
     * @returns {ConfiguredPromptManagerOptions} The configured prompt manager options.
     */
    get options(): ConfiguredPromptManagerOptions;
    /**
     * Registers a new data source with the prompt manager.
     * @param {DataSource} dataSource - Data source to add.
     * @returns {this} The prompt manager for chaining.
     */
    addDataSource(dataSource: DataSource): this;
    /**
     * Looks up a data source by name.
     * @param {string} name - Name of the data source to lookup.
     * @returns {DataSource} The data source.
     */
    getDataSource(name: string): DataSource;
    /**
     * Checks for the existence of a named data source.
     * @param {string} name - Name of the data source to lookup.
     * @returns {boolean} True if the data source exists.
     */
    hasDataSource(name: string): boolean;
    /**
     * Registers a new prompt template function with the prompt manager.
     * @param {string} name - Name of the function to add.
     * @param {PromptFunction} fn - Function to add.
     * @returns {this} - The prompt manager for chaining.
     */
    addFunction(name: string, fn: PromptFunction): this;
    /**
     * Looks up a prompt template function by name.
     * @param {string} name - Name of the function to lookup.
     * @returns {PromptFunction} The function.
     */
    getFunction(name: string): PromptFunction;
    /**
     * Checks for the existence of a named prompt template function.
     * @param {string} name Name of the function to lookup.
     * @returns {boolean} True if the function exists.
     */
    hasFunction(name: string): boolean;
    /**
     * Invokes a prompt template function by name.
     * @param {string} name - Name of the function to invoke.
     * @param {TurnContext} context - Turn context for the current turn of conversation with the user.
     * @param {Memory} memory - An interface for accessing state values.
     * @param {Tokenizer} tokenizer - Tokenizer to use when rendering the prompt.
     * @param {string[]} args - Arguments to pass to the function.
     * @returns {Promise<any>} Value returned by the function.
     */
    invokeFunction(name: string, context: TurnContext, memory: Memory, tokenizer: Tokenizer, args: string[]): Promise<any>;
    /**
     * Registers a new prompt template with the prompt manager.
     * @param {PromptTemplate} prompt - Prompt template to add.
     * @returns {this} The prompt manager for chaining.
     */
    addPrompt(prompt: PromptTemplate): this;
    /**
     * Loads a named prompt template from the filesystem.
     * @remarks
     * The template will be pre-parsed and cached for use when the template is rendered by name.
     *
     * Any augmentations will also be added to the template.
     * @param {string} name - Name of the prompt to load.
     * @returns {Promise<PromptTemplate>} The loaded and parsed prompt template.
     */
    getPrompt(name: string): Promise<PromptTemplate>;
    /**
     * Checks for the existence of a named prompt.
     * @param {string} name - Name of the prompt to load.
     * @returns {boolean} True if the prompt exists.
     */
    hasPrompt(name: string): Promise<boolean>;
    /**
     * @param {PromptTemplate} template - The prompt template to update.
     * @private
     */
    private updateConfig;
    /**
     * @param {PromptTemplate} template - The prompt template to append augmentations to.
     * @param {PromptSection[]} sections - The prompt sections to append augmentations to.
     * @private
     */
    private appendAugmentations;
}
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