@microsoft/teams-ai/lib/dataSources/TextDataSource.js

SDK focused on building AI based applications for Microsoft Teams.

"use strict";
/**
 * @module teams-ai
 */
/**
 * Copyright (c) Microsoft Corporation. All rights reserved.
 * Licensed under the MIT License.
 */
Object.defineProperty(exports, "__esModule", { value: true });
exports.TextDataSource = void 0;
/**
 * A data source that can be used to add a static block of text to a prompt.
 * @remarks
 * Primarily used for testing but could be used to inject some externally define text into a
 * prompt. The text will be truncated to fit within the `maxTokens` limit.
 */
class TextDataSource {
    _name;
    _text;
    _tokens;
    /**
     * Creates a new `TextDataSource` instance.
     * @param {string} name Name of the data source.
     * @param {string} text Text to inject into the prompt.
     */
    constructor(name, text) {
        this._name = name;
        this._text = text;
    }
    /**
     * @returns {string} Name of the data source.
     */
    get name() {
        return this._name;
    }
    /**
     * Renders the data source as a string of text.
     * @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 data source.
     * @param {number} maxTokens Maximum number of tokens allowed to be rendered.
     * @returns {Promise<RenderedPromptSection<string>>} The text to inject into the prompt as a `RenderedPromptSection` object.
     */
    renderData(context, memory, tokenizer, maxTokens) {
        // Tokenize text on first use
        if (!this._tokens) {
            this._tokens = tokenizer.encode(this._text);
        }
        // Check for max tokens
        if (this._tokens.length > maxTokens) {
            const trimmed = this._tokens.slice(0, maxTokens);
            return Promise.resolve({ output: tokenizer.decode(trimmed), length: trimmed.length, tooLong: true });
        }
        else {
            return Promise.resolve({ output: this._text, length: this._tokens.length, tooLong: false });
        }
    }
}
exports.TextDataSource = TextDataSource;
//# sourceMappingURL=TextDataSource.js.map