Reference implementation: Set expressions with function calling
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@ -1,14 +1,15 @@
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import { callPopup, eventSource, event_types, generateQuietPrompt, getRequestHeaders, saveSettingsDebounced, substituteParams } from '../../../script.js';
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import { callPopup, eventSource, event_types, generateQuietPrompt, getRequestHeaders, online_status, saveSettingsDebounced, substituteParams } from '../../../script.js';
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import { dragElement, isMobile } from '../../RossAscends-mods.js';
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import { getContext, getApiUrl, modules, extension_settings, ModuleWorkerWrapper, doExtrasFetch, renderExtensionTemplateAsync } from '../../extensions.js';
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import { loadMovingUIState, power_user } from '../../power-user.js';
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import { onlyUnique, debounce, getCharaFilename, trimToEndSentence, trimToStartSentence } from '../../utils.js';
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import { onlyUnique, debounce, getCharaFilename, trimToEndSentence, trimToStartSentence, waitUntilCondition } from '../../utils.js';
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import { hideMutedSprites } from '../../group-chats.js';
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import { isJsonSchemaSupported } from '../../textgen-settings.js';
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import { debounce_timeout } from '../../constants.js';
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import { SlashCommandParser } from '../../slash-commands/SlashCommandParser.js';
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import { SlashCommand } from '../../slash-commands/SlashCommand.js';
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import { ARGUMENT_TYPE, SlashCommandArgument } from '../../slash-commands/SlashCommandArgument.js';
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import { isFunctionCallingSupported } from '../../openai.js';
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export { MODULE_NAME };
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const MODULE_NAME = 'expressions';
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@ -16,6 +17,7 @@ const UPDATE_INTERVAL = 2000;
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const STREAMING_UPDATE_INTERVAL = 10000;
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const TALKINGCHECK_UPDATE_INTERVAL = 500;
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const DEFAULT_FALLBACK_EXPRESSION = 'joy';
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const FUNCTION_NAME = 'set_emotion';
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const DEFAULT_LLM_PROMPT = 'Pause your roleplay. Classify the emotion of the last message. Output just one word, e.g. "joy" or "anger". Choose only one of the following labels: {{labels}}';
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const DEFAULT_EXPRESSIONS = [
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'talkinghead',
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@ -1001,6 +1003,10 @@ async function getLlmPrompt(labels) {
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return '';
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}
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if (isFunctionCallingSupported()) {
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return '';
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}
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const labelsString = labels.map(x => `"${x}"`).join(', ');
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const prompt = substituteParams(String(extension_settings.expressions.llmPrompt))
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.replace(/{{labels}}/gi, labelsString);
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@ -1018,7 +1024,13 @@ function parseLlmResponse(emotionResponse, labels) {
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try {
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const parsedEmotion = JSON.parse(emotionResponse);
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return parsedEmotion?.emotion ?? fallbackExpression;
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const response = parsedEmotion?.emotion;
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if (!response || !labels.includes(response)) {
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return fallbackExpression;
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}
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return response;
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} catch {
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const fuse = new Fuse(labels, { includeScore: true });
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console.debug('Using fuzzy search in labels:', labels);
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@ -1032,6 +1044,40 @@ function parseLlmResponse(emotionResponse, labels) {
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throw new Error('Could not parse emotion response ' + emotionResponse);
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}
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/**
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* Registers the function tool for the LLM API.
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* @param {FunctionToolRegister} args Function tool register arguments.
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*/
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function onFunctionToolRegister(args) {
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if (inApiCall && extension_settings.expressions.api === EXPRESSION_API.llm && isFunctionCallingSupported()) {
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// Only trigger on quiet mode
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if (args.type !== 'quiet') {
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return;
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}
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const emotions = DEFAULT_EXPRESSIONS.filter((e) => e != 'talkinghead');
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const jsonSchema = {
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$schema: 'http://json-schema.org/draft-04/schema#',
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type: 'object',
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properties: {
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emotion: {
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type: 'string',
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enum: emotions,
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},
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},
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required: [
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'emotion',
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],
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};
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args.registerFunctionTool(
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FUNCTION_NAME,
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substituteParams('Sets the label that best describes the current emotional state of {{char}}. Only select one of the enumerated values.'),
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jsonSchema,
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true,
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);
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}
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}
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function onTextGenSettingsReady(args) {
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// Only call if inside an API call
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if (inApiCall && extension_settings.expressions.api === EXPRESSION_API.llm && isJsonSchemaSupported()) {
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@ -1087,11 +1133,27 @@ async function getExpressionLabel(text) {
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} break;
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// Using LLM
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case EXPRESSION_API.llm: {
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try {
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await waitUntilCondition(() => online_status !== 'no_connection', 3000, 250);
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} catch (error) {
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console.warn('No LLM connection. Using fallback expression', error);
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return getFallbackExpression();
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}
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const expressionsList = await getExpressionsList();
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const prompt = await getLlmPrompt(expressionsList);
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let functionResult = null;
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eventSource.once(event_types.TEXT_COMPLETION_SETTINGS_READY, onTextGenSettingsReady);
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eventSource.once(event_types.LLM_FUNCTION_TOOL_REGISTER, onFunctionToolRegister);
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eventSource.once(event_types.LLM_FUNCTION_TOOL_CALL, (/** @type {FunctionToolCall} */ args) => {
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if (args.name !== FUNCTION_NAME) {
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return;
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}
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functionResult = args?.arguments;
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});
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const emotionResponse = await generateQuietPrompt(prompt, false, false);
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return parseLlmResponse(emotionResponse, expressionsList);
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return parseLlmResponse(functionResult || emotionResponse, expressionsList);
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}
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// Extras
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default: {
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@ -34,7 +34,7 @@
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<i class="fa-solid fa-clock-rotate-left fa-sm"></i>
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</div>
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</label>
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<small>Will be used if the API doesn't support JSON schemas.</small>
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<small>Will be used if the API doesn't support JSON schemas or function calling.</small>
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<textarea id="expression_llm_prompt" type="text" class="text_pole textarea_compact" rows="2" placeholder="Use {{labels}} special macro."></textarea>
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</div>
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<div class="expression_fallback_block m-b-1 m-t-1">
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