1// Advanced RAG Pipeline with Multi-Agent Orchestration
2import { OpenAI } from "openai";
3import { PineconeStore } from "@langchain/pinecone";
4import { OpenAIEmbeddings } from "@langchain/openai";
5import { RecursiveCharacterTextSplitter } from "langchain/text_splitter";
6import { createClient } from "redis";
7import { z } from "zod";
8
9interface RAGConfig {
10  vectorStore: PineconeStore;
11  llm: OpenAI;
12  cache: ReturnType<typeof createClient>;
13  embeddingModel: OpenAIEmbeddings;
14}
15
16class AdvancedRAGPipeline {
17  private config: RAGConfig;
18  private semanticRouter: SemanticRouter;
19  private queryRewriter: QueryRewriter;
20  
21  constructor(config: RAGConfig) {
22    this.config = config;
23    this.semanticRouter = new SemanticRouter(config.embeddingModel);
24    this.queryRewriter = new QueryRewriter(config.llm);
25  }
26
27  async processQuery(query: string, context?: AgentContext): Promise<RAGResponse> {
28    // Multi-step query processing with semantic routing
29    const routingResult = await this.semanticRouter.route(query);
30    const rewrittenQueries = await this.queryRewriter.expandQuery(query, routingResult);
31    
32    // Parallel retrieval with fusion scoring
33    const retrievalPromises = rewrittenQueries.map(async (q) => {
34      const cacheKey = await this.generateCacheKey(q, context);
35      const cached = await this.config.cache.get(cacheKey);
36      if (cached) return JSON.parse(cached);
37      
38      return this.hybridRetrieval(q, {
39        alpha: 0.7, // Vector search weight
40        beta: 0.3,  // Keyword search weight
41        minSimilarity: 0.75,
42        maxResults: 20
43      });
44    });
45    
46    const retrievalResults = await Promise.all(retrievalPromises);
47    const fusedResults = this.fusionRanking(retrievalResults, rewrittenQueries);
48    
49    // Context-aware generation with citation tracking
50    return this.generateWithCitations(query, fusedResults, context);
51  }
52
53  private async hybridRetrieval(query: string, params: RetrievalParams) {
54    const [vectorResults, keywordResults] = await Promise.all([
55      this.vectorSearch(query, params.maxResults),
56      this.keywordSearch(query, params.maxResults)
57    ]);
58    
59    // RRF (Reciprocal Rank Fusion) scoring
60    return this.reciprocalRankFusion(vectorResults, keywordResults, params);
61  }
62
63  private fusionRanking(results: DocumentChunk[][], queries: string[]): DocumentChunk[] {
64    const scoreMap = new Map<string, { doc: DocumentChunk; totalScore: number }>();
65    
66    results.forEach((resultSet, queryIndex) => {
67      const queryWeight = 1 / (queryIndex + 1); // Decay for expanded queries
68      
69      resultSet.forEach((doc, rank) => {
70        const rrf = 1 / (rank + 60); // RRF with k=60
71        const existing = scoreMap.get(doc.id);
72        
73        if (existing) {
74          existing.totalScore += rrf * queryWeight;
75        } else {
76          scoreMap.set(doc.id, { doc, totalScore: rrf * queryWeight });
77        }
78      });
79    });
80    
81    return Array.from(scoreMap.values())
82      .sort((a, b) => b.totalScore - a.totalScore)
83      .slice(0, 10)
84      .map(item => item.doc);
85  }
86}