ANSWER CACHING AND KNOWLEDGE CURATION IN RETRIEVAL-AUGMENTED GENERATION APPLICATIONS

1 . A method comprising:

generating, based on a question from a user, an answer using a knowledge base;

determining, based on feedback from the user, refined knowledge, wherein the feedback is associated with the answer;

causing the refined knowledge to be stored in a question and answer (Q&A) source of the knowledge base;

generating, based on a manual question associated with a subject matter expert (SME), manual knowledge, wherein the manual question is generated by the SME; and

causing the manual knowledge to be stored in the Q&A source of the knowledge base.

2 . The method of claim 1 , wherein generating the answer comprises:

determining a semantic similarity between the question and previously processed questions stored in the knowledge base; and

retrieving one or more curated answers based on the semantic similarity.

3 . The method of claim 1 , wherein generating the answer further comprises:

identifying relevant information from other knowledge base sources; and

combining the relevant information with the retrieved curated answers.

4 . The method of claim 1 , wherein receiving the feedback comprises receiving a rating of the answer's quality from the user.

5 . The method of claim 1 , wherein sending the answer and the feedback for review comprises sending the answer and the feedback to the SME for manual review.

6 . The method of claim 1 , further comprising generating auto-generated answers based on the manual question and the manual knowledge.

7 . The method of claim 6 , further comprising:

determining, based on the auto-generated answers, additional refined knowledge; and

causing the additional refined knowledge to be stored in the Q&A source of the knowledge base.

8 . The method of claim 1 , wherein causing the refined knowledge to be stored comprises:

converting the refined knowledge into embeddings; and

storing the embeddings in a vector database associated with the knowledge base.

9 . The method of claim 1 , further comprising:

receiving a new question from a user;

determining a semantic similarity between the new question and the stored refined knowledge; and

generating a new answer based on the semantic similarity.

10 . The method of claim 1 , wherein the knowledge base comprises the Q&A source containing the refined knowledge and the manual knowledge and other knowledge base sources containing additional information.

11 . An apparatus comprising:

a processor; and

a memory storing instructions that, when executed by the processor, cause the apparatus to:

receive a question from a user;

generate, based on the question, an answer using a knowledge base;

receive feedback from the user regarding the answer;

send the answer and the feedback for review;

determine, based on the review, refined knowledge;

cause the refined knowledge to be stored in a question and answer (Q&A) source of the knowledge base;

receive a manual question from a subject matter expert (SME);

generate manual knowledge based on the manual question; and

cause the manual knowledge to be stored in the Q&A source of the knowledge base.

12 . The apparatus of claim 11 , wherein the instructions to generate the answer comprise instructions to:

determine a semantic similarity between the question and previously processed questions stored in the knowledge base; and

retrieve one or more curated answers based on the semantic similarity.

13 . The apparatus of claim 11 , wherein the instructions to generate the answer further comprise instructions to:

identify relevant information from other knowledge base sources; and

combine the relevant information with the retrieved curated answers.

14 . The apparatus of claim 11 , wherein the instructions to receive the feedback comprise instructions to receive a rating of the answer's quality from the user.

15 . The apparatus of claim 11 , wherein the instructions to send the answer and the feedback for review comprise instructions to send the answer and the feedback to the SME for manual review.

16 . The apparatus of claim 11 , wherein the memory stores further instructions that, when executed by the processor, cause the apparatus to generate auto-generated answers based on the manual question and the manual knowledge.

17 . The apparatus of claim 16 , wherein the memory stores further instructions that, when executed by the processor, cause the apparatus to:

determine, based on the auto-generated answers, additional refined knowledge; and

cause the additional refined knowledge to be stored in the Q&A source of the knowledge base.

18 . The apparatus of claim 11 , wherein the instructions to cause the refined knowledge to be stored comprise instructions to:

convert the refined knowledge into embeddings; and

store the embeddings in a vector database associated with the knowledge base.

19 . The apparatus of claim 11 , wherein the memory stores further instructions that, when executed by the processor, cause the apparatus to:

receive a new question from a user;

determine a semantic similarity between the new question and the stored refined knowledge; and

generate a new answer based on the semantic similarity.

20 . The apparatus of claim 11 , wherein the knowledge base comprises the Q&A source containing the refined knowledge and the manual knowledge and other knowledge base sources containing additional information.