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Emotions: Use the full context for main API

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To prevent prompt reprocessing per turn, use the full context
when prompting with the main API. Doing so keeps the preserved
prefix while adding an extra sentence rather than providing two
different prompts for each turn.

In addition, JSON schemas might need a prompt to coerce a proper
schema return from the model.

Signed-off-by: kingbri <8082010+kingbri1@users.noreply.github.com>
This commit is contained in:
kingbri
2025-06-13 21:55:02 -04:00
parent e1130e7077
commit e43e771cc5
1 changed files with 9 additions and 6 deletions
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public/scripts/extensions/expressions/index.js
+9 -6
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@@ -1,6 +1,6 @@
import { Fuse } from '../../../lib.js';
import { characters, eventSource, event_types, generateRaw, getRequestHeaders, main_api, online_status, saveSettingsDebounced, substituteParams, substituteParamsExtended, system_message_types, this_chid } from '../../../script.js';
import { characters, eventSource, event_types, generateQuietPrompt, generateRaw, getRequestHeaders, main_api, online_status, saveSettingsDebounced, substituteParams, substituteParamsExtended, system_message_types, this_chid } from '../../../script.js';
import { dragElement, isMobile } from '../../RossAscends-mods.js';
import { getContext, getApiUrl, modules, extension_settings, ModuleWorkerWrapper, doExtrasFetch, renderExtensionTemplateAsync } from '../../extensions.js';
import { loadMovingUIState, performFuzzySearch, power_user } from '../../power-user.js';
@@ -909,10 +909,6 @@ function sampleClassifyText(text) {
* @returns {Promise<string>} Prompt for the LLM API.
*/
async function getLlmPrompt(labels) {
if (isJsonSchemaSupported()) {
return '';
}
const labelsString = labels.map(x => `"${x}"`).join(', ');
const prompt = substituteParamsExtended(String(extension_settings.expressions.llmPrompt), { labels: labelsString });
return prompt;
@@ -1047,7 +1043,14 @@ export async function getExpressionLabel(text, expressionsApi = extension_settin
const expressionsList = await getExpressionsList({ filterAvailable: filterAvailable });
const prompt = substituteParamsExtended(customPrompt, { labels: expressionsList }) || await getLlmPrompt(expressionsList);
eventSource.once(event_types.TEXT_COMPLETION_SETTINGS_READY, onTextGenSettingsReady);
const emotionResponse = await generateRaw(text, main_api, false, false, prompt);
let emotionResponse;
try {
inApiCall = true;
emotionResponse = await generateQuietPrompt(prompt, false, false);
} finally {
inApiCall = false;
}
return parseLlmResponse(emotionResponse, expressionsList);
}
// Using WebLLM