package com.ai.aiagent.rag;

import org.springframework.ai.chat.client.advisor.api.Advisor;
import org.springframework.ai.rag.advisor.RetrievalAugmentationAdvisor;
import org.springframework.ai.rag.retrieval.search.DocumentRetriever;
import org.springframework.ai.rag.retrieval.search.VectorStoreDocumentRetriever;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.ai.vectorstore.filter.Filter;
import org.springframework.ai.vectorstore.filter.FilterExpressionBuilder;

public class LoveAppRagCustomAdvisorFactory {
    public static Advisor createLoveAppRagCustomAdvisor(VectorStore vectorStore,String status){
        Filter.Expression expression=new FilterExpressionBuilder()
                .eq("status",status)
                .build();
        DocumentRetriever documentRetriever= VectorStoreDocumentRetriever.builder()
                .vectorStore(vectorStore)
                .filterExpression(expression)
                .similarityThreshold(0.5)
                .topK(3)
                .build();
        return RetrievalAugmentationAdvisor.builder()
                .documentRetriever(documentRetriever)
                .queryAugmenter(LoveAppContextualQueryAugmenterFactory.createInstance())
                .build();
    }
}