@dooor-ai/toolkit/src/rag/context.ts

Guards, Evals & Observability for AI applications - works seamlessly with LangChain/LangGraph

/**
 * RAGContext class for DOOOR AI Toolkit
 * Allows users to pass ephemeral documents, files, or embeddings for RAG
 */

import { RAGContextConfig, RAGStrategy, RAGFile, RAGDocument, RAGEmbedding } from "./types";

export class RAGContext {
  public readonly files: RAGFile[];
  public readonly documents: RAGDocument[];
  public readonly embeddings: RAGEmbedding[];
  public readonly embeddingProvider: string;
  public readonly strategy: RAGStrategy;
  public readonly topK: number;
  public readonly chunkSize: number;
  public readonly chunkOverlap: number;
  public readonly similarityThreshold: number;

  constructor(config: RAGContextConfig) {
    this.files = config.files || [];
    this.documents = config.documents || [];
    this.embeddings = config.embeddings || [];

    if (!config.embeddingProvider) {
      throw new Error(
        "embeddingProvider is required. Please configure an embedding provider at /settings/embeddings " +
        "and pass its internal name (e.g., 'prod-gemini', 'myGemini')"
      );
    }

    this.embeddingProvider = config.embeddingProvider;
    this.strategy = config.strategy || RAGStrategy.SIMPLE;
    this.topK = config.topK || 5;
    this.chunkSize = config.chunkSize || 1000;
    this.chunkOverlap = config.chunkOverlap || 200;
    this.similarityThreshold = config.similarityThreshold || 0.7;

    // Validate at least one source is provided
    if (this.files.length === 0 && this.documents.length === 0 && this.embeddings.length === 0) {
      throw new Error(
        "RAGContext requires at least one source: files, documents, or embeddings"
      );
    }
  }

  /**
   * Serialize RAGContext to JSON for API request
   */
  toJSON(): Record<string, any> {
    return {
      files: this.files.map(f => ({
        name: f.name,
        data: Buffer.isBuffer(f.data) ? f.data.toString('base64') : f.data,
        type: f.type,
      })),
      documents: this.documents,
      embeddings: this.embeddings,
      embedding_provider: this.embeddingProvider,
      strategy: this.strategy,
      top_k: this.topK,
      chunk_size: this.chunkSize,
      chunk_overlap: this.chunkOverlap,
      similarity_threshold: this.similarityThreshold,
    };
  }
}