fix: apply feedback

api/docs/nlp/README.md

@@ -1,102 +0,0 @@
-# NLP Block Scoring
-## Purpose
-
-**NLP Block Scoring** is a mechanism used to select the most relevant response block based on:
-
-- Matching patterns between user input and block definitions
-- Configurable weights assigned to each entity type
-- Confidence values provided by the NLU engine for detected entities
-
-It enables more intelligent and context-aware block selection in conversational flows.
-
-## Core Use Cases
-### Standard Matching
-
-A user input contains entities that directly match a block’s patterns.
-```ts
-Example: Input: intent = enquiry & subject = claim
-Block A: Patterns: intent: enquiry & subject: claim
-Block A will be selected.
-```
-
-### High Confidence, Partial Match
-
-A block may match only some patterns but have high-confidence input on those matched ones, making it a better candidate than others with full matches but low-confidence entities.
-**Note: Confidence is multiplied by a pre-defined weight for each entity type.**
-
-```ts
-Example:
-Input: intent = issue (confidence: 0.92) & subject = claim (confidence: 0.65)
-Block A: Pattern: intent: issue
-Block B: Pattern: subject: claim
-➤ Block A gets a high score based on confidence × weight (assuming both weights are equal to 1).
-```
-
-### Multiple Blocks with Similar Patterns
-
-```ts
-Input: intent = issue & subject = insurance
-Block A: intent = enquiry & subject = insurance
-Block B: subject = insurance
-➤ Block B is selected — Block A mismatches on intent.
-```
-
-### Exclusion Due to Extra Patterns
-
-If a block contains patterns that require entities not present in the user input, the block is excluded from scoring altogether. No penalties are applied — the block simply isn't considered a valid candidate.
-
-```ts
-Input: intent = issue & subject = insurance
-Block A: intent = enquiry & subject = insurance & location = office
-Block B: subject = insurance & time = morning
-➤ Neither block is selected due to unmatched required patterns (`location`, `time`)
-```
-
-### Tie-Breaking with Penalty Factors
-
-When multiple blocks receive similar scores, penalty factors can help break the tie — especially in cases where patterns are less specific (e.g., using `Any` as a value).
-
-```ts
-Input: intent = enquiry & subject = insurance
-
-Block A: intent = enquiry & subject = Any
-Block B: intent = enquiry & subject = insurance
-Block C: subject = insurance
-
-Scoring Summary:
-- Block A matches both patterns, but subject = Any is considered less specific.
-- Block B has a redundant but fully specific match.
-- Block C matches only one pattern.
-
-➤ Block A and Block B have similar raw scores.
-➤ A penalty factor is applied to Block A due to its use of Any, reducing its final score.
-➤ Block B is selected.
-```
-
-## How Scoring Works
-### Matching and Confidence
-
-For each entity in the block's pattern:
-- If the entity `matches` an entity in the user input:
-    - the score is increased by: `confidence × weight`
-        - `Confidence` is a value between 0 and 1, returned by the NLU engine.
-        - `Weight` (default value is `1`) is a configured importance factor for that specific entity type.
-- If the match is a wildcard (i.e., the block accepts any value):
-    - A **penalty factor** is applied to slightly reduce its contribution:
-    ``confidence × weight × penaltyFactor``. This encourages more specific matches when available.
-
-### Scoring Formula Summary
-
-For each matched entity: 
-
-```ts
-score += confidence × weight × [optional penalty factor if wildcard]
-```
-
-The total block score is the sum of all matched patterns in that block.
-
-### Penalty Factor
-
-The **penalty factor** is a global multiplier (typically less than `1`, e.g., `0.8`) applied when the match type is less specific — such as wildcard or loose entity type matches. It allows the system to:
-- Break ties in favor of more precise blocks
-- Discourage overly generic blocks from being selected when better matches are available

api/src/chat/services/block.service.ts

@@ -305,7 +305,7 @@ export class BlockService extends BaseService<
       return undefined;
     }
 
-    const nlpPatterns = block.patterns?.filter((p) => {
+    const nlpPatterns = block.patterns.filter((p) => {
       return Array.isArray(p);
     }) as NlpPattern[][];
     // No nlp patterns found
@@ -313,7 +313,7 @@ export class BlockService extends BaseService<
       return undefined;
     }
 
-    // Find NLP pattern match based on best guessed entities
+    // Filter NLP patterns match based on best guessed entities
     return nlpPatterns.filter((entities: NlpPattern[]) => {
       return entities.every((ev: NlpPattern) => {
         if (ev.match === 'value') {

api/src/nlp/services/nlp-entity.service.spec.ts

@@ -9,6 +9,7 @@
 import { CACHE_MANAGER } from '@nestjs/cache-manager';
 import { MongooseModule } from '@nestjs/mongoose';
 
+import { NOT_FOUND_ID } from '@/utils/constants/mock';
 import { nlpEntityFixtures } from '@/utils/test/fixtures/nlpentity';
 import { installNlpValueFixtures } from '@/utils/test/fixtures/nlpvalue';
 import { getPageQuery } from '@/utils/test/pagination';
@@ -152,7 +153,7 @@ describe('nlpEntityService', () => {
     });
 
     it('should handle updating weight of non-existent entity', async () => {
-      const nonExistentId = '507f1f77bcf86cd799439011'; // Example MongoDB ObjectId
+      const nonExistentId = NOT_FOUND_ID;
 
       try {
         await nlpEntityService.updateWeight(nonExistentId, 5);

api/src/nlp/services/nlp-entity.service.ts

@@ -158,12 +158,11 @@ export class NlpEntityService extends BaseService<
   /**
    * Retrieves NLP entity lookup information for the given list of entity names.
    *
-   * This method queries the database for lookups that match any of the provided
-   * entity names, transforms the result into a map structure where each key is
+   * This method queries the database for nlp entities,
+   * transforms the result into a map structure where each key is
    * the entity name and each value contains metadata (id, weight, and list of values),
    * and caches the result using the configured cache key.
    *
-   * @param entityNames - Array of entity names to retrieve lookup data for.
    * @returns A Promise that resolves to a map of entity name to its corresponding lookup metadata.
    */
   @Cacheable(NLP_MAP_CACHE_KEY)