UniqAI/hexabot
1
0
Fork 0
mirror of https://github.com/hexastack/hexabot synced 2025-06-26 18:27:28 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

feat: update nlu llm helper to use pattern lookup

Browse Source
This commit is contained in:
Mohamed Marrouchi 2025-05-13 16:19:24 +01:00
parent 949fee281a
commit 09666efec6
2 changed files with 12 additions and 53 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

59
api/src/extensions/helpers/llm-nlu/index.helper.ts
View File

@ -12,7 +12,7 @@ import Handlebars from 'handlebars';
import { HelperService } from '@/helper/helper.service';
import BaseNlpHelper from '@/helper/lib/base-nlp-helper';
import { LLM, NLU } from '@/helper/types';
import { HelperType, LLM, NLU } from '@/helper/types';
import { LanguageService } from '@/i18n/services/language.service';
import { LoggerService } from '@/logger/logger.service';
import { NlpEntityFull } from '@/nlp/schemas/nlp-entity.schema';
@ -66,12 +66,9 @@ export default class LlmNluHelper
async buildClassifiersPrompt() {
const settings = await this.getSettings();
if (settings) {
const entities = await this.nlpEntityService.findAndPopulate({
const traitEntities = await this.nlpEntityService.findAndPopulate({
lookups: 'trait',
});
const traitEntities = entities.filter(({ lookups }) =>
lookups.includes('trait'),
);
this.traitClassifierPrompts = traitEntities.map((entity) => ({
...entity,
prompt: Handlebars.compile(settings.trait_classifier_prompt_template)({
@ -88,48 +85,9 @@ export default class LlmNluHelper
await this.buildClassifiersPrompt();
}
/**
* Finds entities in a given text based on their values and synonyms.
*
* This function takes a string of text and an array of entities, where each entity contains a value
* and a list of synonyms. It returns an array of objects, each representing an entity found in the text
* along with its start and end positions.
*
* @param text - The input text to search for entities.
* @param entities - An array of entities to search for, each containing a `value` and a list of `synonyms`.
*
* @returns An array of objects representing the found entities, with their `value`, `start`, and `end` positions.
*/
private findKeywordEntities(text: string, entity: NlpEntityFull) {
return (
entity.values
.flatMap(({ value, expressions }) => {
const allValues = [value, ...expressions];
// Filter the terms that are found in the text
return allValues
.flatMap((term) => {
const regex = new RegExp(`\\b${term}\\b`, 'g');
const matches = [...text.matchAll(regex)];
// Map matches to FoundEntity format
return matches.map((match) => ({
entity: entity.name,
value: term,
start: match.index!,
end: match.index! + term.length,
confidence: 1,
}));
})
.shift();
})
.filter((v) => !!v) || []
);
}
async predict(text: string): Promise<NLU.ParseEntities> {
const settings = await this.getSettings();
const helper = await this.helperService.getDefaultLlmHelper();
const helper = await this.helperService.getDefaultHelper(HelperType.LLM);
const defaultLanguage = await this.languageService.getDefaultLanguage();
// Detect language
const language = await helper.generateStructuredResponse<string>?.(
@ -174,13 +132,12 @@ export default class LlmNluHelper
// Perform slot filling in a deterministic way since
// it's currently a challenging task for the LLMs.
const keywordEntities = await this.nlpEntityService.findAndPopulate({
lookups: 'keywords',
const entities = await this.nlpEntityService.findAndPopulate({
lookups: { $in: ['keywords', 'pattern'] },
});
const entities = keywordEntities.flatMap((keywordEntity) =>
this.findKeywordEntities(text, keywordEntity),
) as NLU.ParseEntity[];
return { entities: traits.concat(entities) };
const slotEntities = this.runDeterministicSlotFilling(text, entities);
return { entities: traits.concat(slotEntities) };
}
}

6
frontend/src/components/nlp/components/NlpTrainForm.tsx
View File

@ -347,8 +347,10 @@ const NlpDatasetSample: FC<NlpDatasetSampleProps> = ({
label={t("label.nlp_entity")}
multiple={false}
preprocess={(options) => {
return options.filter(({ lookups }) =>
lookups.includes("keywords"),
return options.filter(
({ lookups }) =>
lookups.includes("keywords") ||
lookups.includes("pattern"),
);
}}
onChange={(_e, selected, ..._) => {