docs(changeset): feat: abstract @llamaindex/env package

docs(changeset): build: use ESM as default
build: leave code as-is (#560 )
2026-07-09 03:23:09 -04:00 · 2024-02-23 17:45:43 -06:00 · 2024-02-23 17:45:01 -06:00 · 2024-02-23 17:39:25 -06:00 · 2024-02-23 14:55:45 +07:00 · 2024-02-23 14:45:17 +07:00
223 changed files with 3814 additions and 4407 deletions
@@ -0,0 +1,5 @@
+---
+"llamaindex": patch
+---
+
+build: use ESM as default
@@ -0,0 +1,5 @@
+---
+"llamaindex": patch
+---
+
+feat: abstract `@llamaindex/env` package
@@ -9,6 +9,7 @@ module.exports = {
  },
  rules: {
    "max-params": ["error", 4],
+    "prefer-const": "error",
  },
  ignorePatterns: ["dist/"],
 };
@@ -61,10 +61,13 @@ jobs:
        run: pnpm run build --filter llamaindex
      - name: Copy examples
        run: rsync -rv --exclude=node_modules ./examples ${{ runner.temp }}
-      - name: Pack
+      - name: Pack @llamaindex/env
+        run: pnpm pack --pack-destination ${{ runner.temp }}
+        working-directory: packages/env
+      - name: Pack llamaindex
        run: pnpm pack --pack-destination ${{ runner.temp }}
        working-directory: packages/core
-      - name: Install llamaindex
+      - name: Install
        run: npm add ${{ runner.temp }}/*.tgz
        working-directory: ${{ runner.temp }}/examples
      - name: Run Type Check
@@ -5,7 +5,6 @@
  "[xml]": {
    "editor.defaultFormatter": "redhat.vscode-xml"
  },
-  "jest.rootPath": "./packages/core",
  "[python]": {
    "editor.defaultFormatter": "ms-python.black-formatter"
  },
@@ -1,4 +1,4 @@
-import { Ollama } from "llamaindex";
+import { Ollama } from "llamaindex/llm/ollama";

 (async () => {
  const llm = new Ollama({ model: "llama2", temperature: 0.75 });
@@ -18,15 +18,12 @@
  },
  "devDependencies": {
    "@changesets/cli": "^2.27.1",
-    "@types/jest": "^29.5.12",
    "eslint": "^8.56.0",
    "eslint-config-custom": "workspace:*",
    "husky": "^9.0.10",
-    "jest": "^29.7.0",
    "lint-staged": "^15.2.2",
    "prettier": "^3.2.5",
    "prettier-plugin-organize-imports": "^3.2.4",
-    "ts-jest": "^29.1.2",
    "turbo": "^1.12.3",
    "typescript": "^5.3.3"
  },
@@ -0,0 +1,11 @@
+{
+  "jsc": {
+    "parser": {
+      "syntax": "typescript"
+    },
+    "target": "esnext"
+  },
+  "module": {
+    "type": "commonjs"
+  }
+}
@@ -0,0 +1,8 @@
+{
+  "jsc": {
+    "parser": {
+      "syntax": "typescript"
+    },
+    "target": "esnext"
+  }
+}
@@ -1,6 +0,0 @@
-/** @type {import('ts-jest').JestConfigWithTsJest} */
-module.exports = {
-  preset: "ts-jest",
-  testEnvironment: "node",
-  testPathIgnorePatterns: ["/lib/", "/node_modules/", "/dist/"],
-};
@@ -3,9 +3,13 @@
  "private": true,
  "version": "0.1.12",
  "license": "MIT",
+  "type": "module",
  "dependencies": {
    "@anthropic-ai/sdk": "^0.13.0",
+    "@aws-crypto/sha256-js": "^5.2.0",
    "@datastax/astra-db-ts": "^0.1.4",
+    "@llamaindex/cloud": "^0.0.1",
+    "@llamaindex/env": "workspace:*",
    "@mistralai/mistralai": "^0.0.10",
    "@notionhq/client": "^2.2.14",
    "@pinecone-database/pinecone": "^2.0.1",
@@ -34,171 +38,46 @@
    "wink-nlp": "^1.14.3"
  },
  "devDependencies": {
-    "@aws-crypto/sha256-js": "^5.2.0",
-    "@llamaindex/cloud": "^0.0.1",
-    "@types/edit-json-file": "^1.7.3",
-    "@types/jest": "^29.5.12",
+    "@swc/cli": "^0.3.9",
+    "@swc/core": "^1.4.2",
    "@types/lodash": "^4.14.202",
    "@types/node": "^18.19.14",
    "@types/papaparse": "^5.3.14",
    "@types/pg": "^8.11.0",
-    "bunchee": "^4.4.6",
-    "edit-json-file": "^1.8.0",
+    "concurrently": "^8.2.2",
+    "glob": "^10.3.10",
    "madge": "^6.1.0",
    "typescript": "^5.3.3"
  },
  "engines": {
    "node": ">=18.0.0"
  },
-  "types": "./dist/index.d.ts",
-  "main": "./dist/index.js",
+  "types": "./dist/type/index.d.ts",
+  "main": "./dist/cjs/index.cjs",
  "exports": {
    ".": {
-      "types": "./dist/index.d.mts",
-      "import": "./dist/index.mjs",
-      "edge-light": "./dist/index.edge-light.mjs",
-      "require": "./dist/index.js"
+      "import": {
+        "types": "./dist/type/index.d.ts",
+        "default": "./dist/index.js"
+      },
+      "edge-light": {
+        "types": "./dist/type/index.d.ts",
+        "default": "./dist/index.edge-light.js"
+      },
+      "require": {
+        "types": "./dist/type/index.d.ts",
+        "default": "./dist/cjs/index.cjs"
+      }
    },
-    "./env": {
-      "types": "./dist/env.d.mts",
-      "import": "./dist/env.mjs",
-      "edge-light": "./dist/env.edge-light.mjs",
-      "require": "./dist/env.js"
-    },
-    "./ChatEngine": {
-      "types": "./dist/ChatEngine.d.mts",
-      "import": "./dist/ChatEngine.mjs",
-      "require": "./dist/ChatEngine.js"
-    },
-    "./ChatHistory": {
-      "types": "./dist/ChatHistory.d.mts",
-      "import": "./dist/ChatHistory.mjs",
-      "require": "./dist/ChatHistory.js"
-    },
-    "./constants": {
-      "types": "./dist/constants.d.mts",
-      "import": "./dist/constants.mjs",
-      "require": "./dist/constants.js"
-    },
-    "./GlobalsHelper": {
-      "types": "./dist/GlobalsHelper.d.mts",
-      "import": "./dist/GlobalsHelper.mjs",
-      "require": "./dist/GlobalsHelper.js"
-    },
-    "./Node": {
-      "types": "./dist/Node.d.mts",
-      "import": "./dist/Node.mjs",
-      "require": "./dist/Node.js"
-    },
-    "./OutputParser": {
-      "types": "./dist/OutputParser.d.mts",
-      "import": "./dist/OutputParser.mjs",
-      "require": "./dist/OutputParser.js"
-    },
-    "./Prompt": {
-      "types": "./dist/Prompt.d.mts",
-      "import": "./dist/Prompt.mjs",
-      "require": "./dist/Prompt.js"
-    },
-    "./PromptHelper": {
-      "types": "./dist/PromptHelper.d.mts",
-      "import": "./dist/PromptHelper.mjs",
-      "require": "./dist/PromptHelper.js"
-    },
-    "./QueryEngine": {
-      "types": "./dist/QueryEngine.d.mts",
-      "import": "./dist/QueryEngine.mjs",
-      "require": "./dist/QueryEngine.js"
-    },
-    "./QuestionGenerator": {
-      "types": "./dist/QuestionGenerator.d.mts",
-      "import": "./dist/QuestionGenerator.mjs",
-      "require": "./dist/QuestionGenerator.js"
-    },
-    "./Response": {
-      "types": "./dist/Response.d.mts",
-      "import": "./dist/Response.mjs",
-      "require": "./dist/Response.js"
-    },
-    "./ServiceContext": {
-      "types": "./dist/ServiceContext.d.mts",
-      "import": "./dist/ServiceContext.mjs",
-      "require": "./dist/ServiceContext.js"
-    },
-    "./TextSplitter": {
-      "types": "./dist/TextSplitter.d.mts",
-      "import": "./dist/TextSplitter.mjs",
-      "require": "./dist/TextSplitter.js"
-    },
-    "./tools": {
-      "types": "./dist/tools.d.mts",
-      "import": "./dist/tools.mjs",
-      "require": "./dist/tools.js"
-    },
-    "./objects": {
-      "types": "./dist/objects.d.mts",
-      "import": "./dist/objects.mjs",
-      "require": "./dist/objects.js"
-    },
-    "./readers": {
-      "types": "./dist/readers.d.mts",
-      "import": "./dist/readers.mjs",
-      "require": "./dist/readers.js"
-    },
-    "./readers/AssemblyAIReader": {
-      "types": "./dist/readers/AssemblyAIReader.d.mts",
-      "import": "./dist/readers/AssemblyAIReader.mjs",
-      "require": "./dist/readers/AssemblyAIReader.js"
-    },
-    "./readers/CSVReader": {
-      "types": "./dist/readers/CSVReader.d.mts",
-      "import": "./dist/readers/CSVReader.mjs",
-      "require": "./dist/readers/CSVReader.js"
-    },
-    "./readers/DocxReader": {
-      "types": "./dist/readers/DocxReader.d.mts",
-      "import": "./dist/readers/DocxReader.mjs",
-      "require": "./dist/readers/DocxReader.js"
-    },
-    "./readers/HTMLReader": {
-      "types": "./dist/readers/HTMLReader.d.mts",
-      "import": "./dist/readers/HTMLReader.mjs",
-      "require": "./dist/readers/HTMLReader.js"
-    },
-    "./readers/ImageReader": {
-      "types": "./dist/readers/ImageReader.d.mts",
-      "import": "./dist/readers/ImageReader.mjs",
-      "require": "./dist/readers/ImageReader.js"
-    },
-    "./readers/MarkdownReader": {
-      "types": "./dist/readers/MarkdownReader.d.mts",
-      "import": "./dist/readers/MarkdownReader.mjs",
-      "require": "./dist/readers/MarkdownReader.js"
-    },
-    "./readers/NotionReader": {
-      "types": "./dist/readers/NotionReader.d.mts",
-      "import": "./dist/readers/NotionReader.mjs",
-      "require": "./dist/readers/NotionReader.js"
-    },
-    "./readers/PDFReader": {
-      "types": "./dist/readers/PDFReader.d.mts",
-      "import": "./dist/readers/PDFReader.mjs",
-      "require": "./dist/readers/PDFReader.js"
-    },
-    "./readers/SimpleDirectoryReader": {
-      "types": "./dist/readers/SimpleDirectoryReader.d.mts",
-      "import": "./dist/readers/SimpleDirectoryReader.mjs",
-      "require": "./dist/readers/SimpleDirectoryReader.js"
-    },
-    "./readers/SimpleMongoReader": {
-      "types": "./dist/readers/SimpleMongoReader.d.mts",
-      "import": "./dist/readers/SimpleMongoReader.mjs",
-      "require": "./dist/readers/SimpleMongoReader.js"
-    },
-    "./cloud": {
-      "types": "./dist/cloud.d.mts",
-      "import": "./dist/cloud.mjs",
-      "require": "./dist/cloud.js"
+    "./*": {
+      "import": {
+        "types": "./dist/type/*.d.ts",
+        "default": "./dist/*.js"
+      },
+      "require": {
+        "types": "./dist/type/*.d.ts",
+        "default": "./dist/cjs/*.cjs"
+      }
    }
  },
  "files": [
@@ -211,13 +90,11 @@
  },
  "scripts": {
    "lint": "eslint .",
-    "test": "jest",
-    "build": "rm -rf ./dist && NODE_OPTIONS=\"--max-old-space-size=12288\" bunchee",
-    "postbuild": "pnpm run copy && pnpm run modify-package-json",
-    "copy": "cp -r package.json CHANGELOG.md ../../README.md ../../LICENSE examples src dist/",
-    "modify-package-json": "node ./scripts/modify-package-json.mjs",
-    "prepublish": "pnpm run modify-package-json && echo \"please cd ./dist and run pnpm publish\" && exit 1",
-    "dev": "NODE_OPTIONS=\"--max-old-space-size=16384\" bunchee -w",
-    "circular-check": "madge -c ./src/index.ts"
+    "build": "rm -rf ./dist && pnpm run build:esm && pnpm run build:cjs && pnpm run build:type",
+    "build:esm": "swc src -d dist --strip-leading-paths --config-file .swcrc",
+    "build:cjs": "swc src -d dist/cjs --strip-leading-paths --config-file .cjs.swcrc --out-file-extension cjs",
+    "build:type": "tsc -p tsconfig.json",
+    "circular-check": "madge -c ./src/index.ts",
+    "dev": "concurrently \"pnpm run build:esm --watch\" \"pnpm run build:cjs --watch\" \"pnpm run build:type --watch\""
  }
 }
@@ -1,25 +0,0 @@
-#!/usr/bin/env node
-/**
- * This script is used to modify the package.json file in the dist folder
- * so that it can be published to npm.
- */
-import editJsonFile from "edit-json-file";
-import fs from "node:fs/promises";
-
-{
-  await fs.copyFile("./package.json", "./dist/package.json");
-  const file = editJsonFile("./dist/package.json");
-
-  file.unset("scripts");
-  file.unset("private");
-  await new Promise((resolve) => file.save(resolve));
-}
-{
-  const packageJson = await fs.readFile("./dist/package.json", "utf8");
-  const modifiedPackageJson = packageJson.replaceAll("./dist/", "./");
-  await fs.writeFile(
-    "./dist/package.json",
-    JSON.stringify(JSON.parse(modifiedPackageJson), null, 2),
-    "utf8",
-  );
-}
@@ -1,10 +1,10 @@
-import { OpenAI } from "./llm/LLM";
-import { ChatMessage, LLM, MessageType } from "./llm/types";
+import { OpenAI } from "./llm/LLM.js";
+import { ChatMessage, LLM, MessageType } from "./llm/types.js";
 import {
  defaultSummaryPrompt,
  messagesToHistoryStr,
  SummaryPrompt,
-} from "./Prompt";
+} from "./Prompt.js";

 /**
 * A ChatHistory is used to keep the state of back and forth chat messages
@@ -1,7 +1,7 @@
 import { encodingForModel } from "js-tiktoken";

-import { Event, EventTag, EventType } from "./callbacks/CallbackManager";
-import { randomUUID } from "./env";
+import { randomUUID } from "@llamaindex/env";
+import { Event, EventTag, EventType } from "./callbacks/CallbackManager.js";

 export enum Tokenizers {
  CL100K_BASE = "cl100k_base",
@@ -1,5 +1,5 @@
+import { createSHA256, path, randomUUID } from "@llamaindex/env";
 import _ from "lodash";
-import { createSHA256, path, randomUUID } from "./env";

 export enum NodeRelationship {
  SOURCE = "SOURCE",
@@ -353,10 +353,10 @@ export function splitNodesByType(nodes: BaseNode[]): {
  imageNodes: ImageNode[];
  textNodes: TextNode[];
 } {
-  let imageNodes: ImageNode[] = [];
-  let textNodes: TextNode[] = [];
+  const imageNodes: ImageNode[] = [];
+  const textNodes: TextNode[] = [];

-  for (let node of nodes) {
+  for (const node of nodes) {
    if (node instanceof ImageNode) {
      imageNodes.push(node);
    } else if (node instanceof TextNode) {
@@ -1,5 +1,5 @@
-import { SubQuestion } from "./engines/query/types";
-import { BaseOutputParser, StructuredOutput } from "./types";
+import { SubQuestion } from "./engines/query/types.js";
+import { BaseOutputParser, StructuredOutput } from "./types.js";

 /**
 * Error class for output parsing. Due to the nature of LLMs, anytime we use LLM
@@ -1,6 +1,6 @@
-import { SubQuestion } from "./engines/query/types";
-import { ChatMessage } from "./llm/types";
-import { ToolMetadata } from "./types";
+import { SubQuestion } from "./engines/query/types.js";
+import { ChatMessage } from "./llm/types.js";
+import { ToolMetadata } from "./types.js";

 /**
 * A SimplePrompt is a function that takes a dictionary of inputs and returns a string.
@@ -1,12 +1,12 @@
-import { globalsHelper } from "./GlobalsHelper";
-import { SimplePrompt } from "./Prompt";
-import { SentenceSplitter } from "./TextSplitter";
+import { globalsHelper } from "./GlobalsHelper.js";
+import { SimplePrompt } from "./Prompt.js";
+import { SentenceSplitter } from "./TextSplitter.js";
 import {
  DEFAULT_CHUNK_OVERLAP_RATIO,
  DEFAULT_CONTEXT_WINDOW,
  DEFAULT_NUM_OUTPUTS,
  DEFAULT_PADDING,
-} from "./constants";
+} from "./constants.js";

 export function getEmptyPromptTxt(prompt: SimplePrompt) {
  return prompt({});
@@ -1,14 +1,14 @@
-import { SubQuestionOutputParser } from "./OutputParser";
+import { SubQuestionOutputParser } from "./OutputParser.js";
 import {
  SubQuestionPrompt,
  buildToolsText,
  defaultSubQuestionPrompt,
-} from "./Prompt";
-import { BaseQuestionGenerator, SubQuestion } from "./engines/query/types";
-import { OpenAI } from "./llm/LLM";
-import { LLM } from "./llm/types";
-import { PromptMixin } from "./prompts";
-import { BaseOutputParser, StructuredOutput, ToolMetadata } from "./types";
+} from "./Prompt.js";
+import { BaseQuestionGenerator, SubQuestion } from "./engines/query/types.js";
+import { OpenAI } from "./llm/LLM.js";
+import { LLM } from "./llm/types.js";
+import { PromptMixin } from "./prompts/index.js";
+import { BaseOutputParser, StructuredOutput, ToolMetadata } from "./types.js";

 /**
 * LLMQuestionGenerator uses the LLM to generate new questions for the LLM using tools and a user query.
@@ -1,4 +1,4 @@
-import { BaseNode } from "./Node";
+import { BaseNode } from "./Node.js";

 /**
 * Response is the output of a LLM
@@ -1,6 +1,6 @@
-import { Event } from "./callbacks/CallbackManager";
-import { NodeWithScore } from "./Node";
-import { ServiceContext } from "./ServiceContext";
+import { Event } from "./callbacks/CallbackManager.js";
+import { NodeWithScore } from "./Node.js";
+import { ServiceContext } from "./ServiceContext.js";

 /**
 * Retrievers retrieve the nodes that most closely match our query in similarity.
@@ -1,8 +1,10 @@
-import { CallbackManager } from "./callbacks/CallbackManager";
-import { BaseEmbedding, OpenAIEmbedding } from "./embeddings";
-import { LLM, OpenAI } from "./llm";
-import { NodeParser, SimpleNodeParser } from "./nodeParsers";
-import { PromptHelper } from "./PromptHelper";
+import { PromptHelper } from "./PromptHelper.js";
+import { CallbackManager } from "./callbacks/CallbackManager.js";
+import { OpenAIEmbedding } from "./embeddings/OpenAIEmbedding.js";
+import { BaseEmbedding } from "./embeddings/types.js";
+import { LLM, OpenAI } from "./llm/index.js";
+import { SimpleNodeParser } from "./nodeParsers/SimpleNodeParser.js";
+import { NodeParser } from "./nodeParsers/types.js";

 /**
 * The ServiceContext is a collection of components that are used in different parts of the application.
@@ -1,7 +1,7 @@
-import { EOL } from "./env";
+import { EOL } from "@llamaindex/env";
 // GitHub translated
-import { globalsHelper } from "./GlobalsHelper";
-import { DEFAULT_CHUNK_OVERLAP, DEFAULT_CHUNK_SIZE } from "./constants";
+import { globalsHelper } from "./GlobalsHelper.js";
+import { DEFAULT_CHUNK_OVERLAP, DEFAULT_CHUNK_SIZE } from "./constants.js";

 class TextSplit {
  textChunk: string;
@@ -130,7 +130,7 @@ export class SentenceSplitter {

  getParagraphSplits(text: string, effectiveChunkSize?: number): string[] {
    // get paragraph splits
-    let paragraphSplits: string[] = text.split(this.paragraphSeparator);
+    const paragraphSplits: string[] = text.split(this.paragraphSeparator);
    let idx = 0;
    if (effectiveChunkSize == undefined) {
      return paragraphSplits;
@@ -155,9 +155,9 @@ export class SentenceSplitter {
  }

  getSentenceSplits(text: string, effectiveChunkSize?: number): string[] {
-    let paragraphSplits = this.getParagraphSplits(text, effectiveChunkSize);
+    const paragraphSplits = this.getParagraphSplits(text, effectiveChunkSize);
    // Next we split the text using the chunk tokenizer fn/
-    let splits = [];
+    const splits = [];
    for (const parText of paragraphSplits) {
      const sentenceSplits = this.chunkingTokenizerFn(parText);

@@ -194,9 +194,9 @@ export class SentenceSplitter {
      }));
    }

-    let newSplits: SplitRep[] = [];
+    const newSplits: SplitRep[] = [];
    for (const split of sentenceSplits) {
-      let splitTokens = this.tokenizer(split);
+      const splitTokens = this.tokenizer(split);
      const splitLen = splitTokens.length;
      if (splitLen <= effectiveChunkSize) {
        newSplits.push({ text: split, numTokens: splitLen });
@@ -219,7 +219,7 @@ export class SentenceSplitter {
    // go through sentence splits, combine to chunks that are within the chunk size

    // docs represents final list of text chunks
-    let docs: TextSplit[] = [];
+    const docs: TextSplit[] = [];
    // curChunkSentences represents the current list of sentence splits (that)
    // will be merged into a chunk
    let curChunkSentences: SplitRep[] = [];
@@ -287,18 +287,18 @@ export class SentenceSplitter {
      return [];
    }

-    let effectiveChunkSize = this.getEffectiveChunkSize(extraInfoStr);
-    let sentenceSplits = this.getSentenceSplits(text, effectiveChunkSize);
+    const effectiveChunkSize = this.getEffectiveChunkSize(extraInfoStr);
+    const sentenceSplits = this.getSentenceSplits(text, effectiveChunkSize);

    // Check if any sentences exceed the chunk size. If they don't,
    // force split by tokenizer
-    let newSentenceSplits = this.processSentenceSplits(
+    const newSentenceSplits = this.processSentenceSplits(
      sentenceSplits,
      effectiveChunkSize,
    );

    // combine sentence splits into chunks of text that can then be returned
-    let combinedTextSplits = this.combineTextSplits(
+    const combinedTextSplits = this.combineTextSplits(
      newSentenceSplits,
      effectiveChunkSize,
    );
@@ -1,5 +1,5 @@
-export * from "./openai/base";
-export * from "./openai/worker";
-export * from "./react/base";
-export * from "./react/worker";
-export * from "./types";
+export * from "./openai/base.js";
+export * from "./openai/worker.js";
+export * from "./react/base.js";
+export * from "./react/worker.js";
+export * from "./types.js";
@@ -1,9 +1,9 @@
-import { CallbackManager } from "../../callbacks/CallbackManager";
-import { ChatMessage, OpenAI } from "../../llm";
-import { ObjectRetriever } from "../../objects/base";
-import { BaseTool } from "../../types";
-import { AgentRunner } from "../runner/base";
-import { OpenAIAgentWorker } from "./worker";
+import { CallbackManager } from "../../callbacks/CallbackManager.js";
+import { ChatMessage, OpenAI } from "../../llm/index.js";
+import { ObjectRetriever } from "../../objects/base.js";
+import { BaseTool } from "../../types.js";
+import { AgentRunner } from "../runner/base.js";
+import { OpenAIAgentWorker } from "./worker.js";

 type OpenAIAgentParams = {
  tools?: BaseTool[];
@@ -1,4 +1,4 @@
-import { ToolMetadata } from "../../types";
+import { ToolMetadata } from "../../types.js";

 export type OpenAIFunction = {
  type: "function";
@@ -1,23 +1,26 @@
 // Assuming that the necessary interfaces and classes (like BaseTool, OpenAI, ChatMessage, CallbackManager, etc.) are defined elsewhere

-import { CallbackManager } from "../../callbacks/CallbackManager";
-import { AgentChatResponse, ChatResponseMode } from "../../engines/chat";
-import { randomUUID } from "../../env";
+import { randomUUID } from "@llamaindex/env";
+import { CallbackManager } from "../../callbacks/CallbackManager.js";
+import {
+  AgentChatResponse,
+  ChatResponseMode,
+} from "../../engines/chat/types.js";
 import {
  ChatMessage,
  ChatResponse,
  ChatResponseChunk,
  OpenAI,
-} from "../../llm";
-import { ChatMemoryBuffer } from "../../memory/ChatMemoryBuffer";
-import { ObjectRetriever } from "../../objects/base";
-import { ToolOutput } from "../../tools/types";
-import { callToolWithErrorHandling } from "../../tools/utils";
-import { BaseTool } from "../../types";
-import { AgentWorker, Task, TaskStep, TaskStepOutput } from "../types";
-import { addUserStepToMemory, getFunctionByName } from "../utils";
-import { OpenAIToolCall } from "./types/chat";
-import { toOpenAiTool } from "./utils";
+} from "../../llm/index.js";
+import { ChatMemoryBuffer } from "../../memory/ChatMemoryBuffer.js";
+import { ObjectRetriever } from "../../objects/base.js";
+import { ToolOutput } from "../../tools/types.js";
+import { callToolWithErrorHandling } from "../../tools/utils.js";
+import { BaseTool } from "../../types.js";
+import { AgentWorker, Task, TaskStep, TaskStepOutput } from "../types.js";
+import { addUserStepToMemory, getFunctionByName } from "../utils.js";
+import { OpenAIToolCall } from "./types/chat.js";
+import { toOpenAiTool } from "./utils.js";

 const DEFAULT_MAX_FUNCTION_CALLS = 5;

@@ -1,9 +1,9 @@
-import { CallbackManager } from "../../callbacks/CallbackManager";
-import { ChatMessage, LLM } from "../../llm";
-import { ObjectRetriever } from "../../objects/base";
-import { BaseTool } from "../../types";
-import { AgentRunner } from "../runner/base";
-import { ReActAgentWorker } from "./worker";
+import { CallbackManager } from "../../callbacks/CallbackManager.js";
+import { ChatMessage, LLM } from "../../llm/index.js";
+import { ObjectRetriever } from "../../objects/base.js";
+import { BaseTool } from "../../types.js";
+import { AgentRunner } from "../runner/base.js";
+import { ReActAgentWorker } from "./worker.js";

 type ReActAgentParams = {
  tools: BaseTool[];
@@ -1,7 +1,7 @@
-import { ChatMessage } from "../../llm";
-import { BaseTool } from "../../types";
-import { getReactChatSystemHeader } from "./prompts";
-import { BaseReasoningStep, ObservationReasoningStep } from "./types";
+import { ChatMessage } from "../../llm/index.js";
+import { BaseTool } from "../../types.js";
+import { getReactChatSystemHeader } from "./prompts.js";
+import { BaseReasoningStep, ObservationReasoningStep } from "./types.js";

 function getReactToolDescriptions(tools: BaseTool[]): string[] {
  const toolDescs: string[] = [];
@@ -3,7 +3,7 @@ import {
  BaseOutputParser,
  BaseReasoningStep,
  ResponseReasoningStep,
-} from "./types";
+} from "./types.js";

 function extractJsonStr(text: string): string {
  const pattern = /\{.*\}/s;
@@ -1,4 +1,4 @@
-import { ChatMessage } from "../../llm";
+import { ChatMessage } from "../../llm/index.js";

 export interface BaseReasoningStep {
  getContent(): string;
@@ -1,20 +1,20 @@
 import { randomUUID } from "crypto";
-import { CallbackManager } from "../../callbacks/CallbackManager";
-import { AgentChatResponse } from "../../engines/chat";
-import { ChatResponse, LLM, OpenAI } from "../../llm";
-import { ChatMemoryBuffer } from "../../memory/ChatMemoryBuffer";
-import { ObjectRetriever } from "../../objects/base";
-import { ToolOutput } from "../../tools";
-import { BaseTool } from "../../types";
-import { AgentWorker, Task, TaskStep, TaskStepOutput } from "../types";
-import { ReActChatFormatter } from "./formatter";
-import { ReActOutputParser } from "./outputParser";
+import { CallbackManager } from "../../callbacks/CallbackManager.js";
+import { AgentChatResponse } from "../../engines/chat/index.js";
+import { ChatResponse, LLM, OpenAI } from "../../llm/index.js";
+import { ChatMemoryBuffer } from "../../memory/ChatMemoryBuffer.js";
+import { ObjectRetriever } from "../../objects/base.js";
+import { ToolOutput } from "../../tools/index.js";
+import { BaseTool } from "../../types.js";
+import { AgentWorker, Task, TaskStep, TaskStepOutput } from "../types.js";
+import { ReActChatFormatter } from "./formatter.js";
+import { ReActOutputParser } from "./outputParser.js";
 import {
  ActionReasoningStep,
  BaseReasoningStep,
  ObservationReasoningStep,
  ResponseReasoningStep,
-} from "./types";
+} from "./types.js";

 type ReActAgentWorkerParams = {
  tools: BaseTool[];
@@ -1,15 +1,15 @@
 import { randomUUID } from "crypto";
-import { CallbackManager } from "../../callbacks/CallbackManager";
+import { CallbackManager } from "../../callbacks/CallbackManager.js";
 import {
  AgentChatResponse,
  ChatEngineAgentParams,
  ChatResponseMode,
-} from "../../engines/chat";
-import { ChatMessage, LLM } from "../../llm";
-import { ChatMemoryBuffer } from "../../memory/ChatMemoryBuffer";
-import { BaseMemory } from "../../memory/types";
-import { AgentWorker, Task, TaskStep, TaskStepOutput } from "../types";
-import { AgentState, BaseAgentRunner, TaskState } from "./types";
+} from "../../engines/chat/index.js";
+import { ChatMessage, LLM } from "../../llm/index.js";
+import { ChatMemoryBuffer } from "../../memory/ChatMemoryBuffer.js";
+import { BaseMemory } from "../../memory/types.js";
+import { AgentWorker, Task, TaskStep, TaskStepOutput } from "../types.js";
+import { AgentState, BaseAgentRunner, TaskState } from "./types.js";

 const validateStepFromArgs = (
  taskId: string,
@@ -1,5 +1,5 @@
-import { AgentChatResponse } from "../../engines/chat";
-import { BaseAgent, Task, TaskStep, TaskStepOutput } from "../types";
+import { AgentChatResponse } from "../../engines/chat/index.js";
+import { BaseAgent, Task, TaskStep, TaskStepOutput } from "../types.js";

 export class TaskState {
  task!: Task;
@@ -1,5 +1,8 @@
-import { AgentChatResponse, ChatEngineAgentParams } from "../engines/chat";
-import { QueryEngineParamsNonStreaming } from "../types";
+import {
+  AgentChatResponse,
+  ChatEngineAgentParams,
+} from "../engines/chat/index.js";
+import { QueryEngineParamsNonStreaming } from "../types.js";

 export interface AgentWorker {
  initializeStep(task: Task, kwargs?: any): TaskStep;
@@ -1,7 +1,7 @@
-import { ChatMessage } from "../llm";
-import { ChatMemoryBuffer } from "../memory/ChatMemoryBuffer";
-import { BaseTool } from "../types";
-import { TaskStep } from "./types";
+import { ChatMessage } from "../llm/index.js";
+import { ChatMemoryBuffer } from "../memory/ChatMemoryBuffer.js";
+import { BaseTool } from "../types.js";
+import { TaskStep } from "./types.js";

 /**
 * Adds the user's input to the memory.
@@ -1,5 +1,5 @@
 import type { Anthropic } from "@anthropic-ai/sdk";
-import { NodeWithScore } from "../Node";
+import { NodeWithScore } from "../Node.js";

 /*
  An event is a wrapper that groups related operations.
@@ -1,10 +1,10 @@
-import { BaseRetriever } from "../Retriever";
-import { RetrieverQueryEngine } from "../engines/query/RetrieverQueryEngine";
-import { BaseNodePostprocessor } from "../postprocessors";
-import { BaseSynthesizer } from "../synthesizers";
-import { BaseQueryEngine } from "../types";
-import { LlamaCloudRetriever, RetrieveParams } from "./LlamaCloudRetriever";
-import { CloudConstructorParams } from "./types";
+import { BaseRetriever } from "../Retriever.js";
+import { RetrieverQueryEngine } from "../engines/query/RetrieverQueryEngine.js";
+import { BaseNodePostprocessor } from "../postprocessors/types.js";
+import { BaseSynthesizer } from "../synthesizers/types.js";
+import { BaseQueryEngine } from "../types.js";
+import { LlamaCloudRetriever, RetrieveParams } from "./LlamaCloudRetriever.js";
+import { CloudConstructorParams } from "./types.js";

 export class LlamaCloudIndex {
  params: CloudConstructorParams;
@@ -1,15 +1,18 @@
 import { PlatformApi, PlatformApiClient } from "@llamaindex/cloud";
-import { globalsHelper } from "../GlobalsHelper";
-import { NodeWithScore, ObjectType, jsonToNode } from "../Node";
-import { BaseRetriever } from "../Retriever";
-import { ServiceContext, serviceContextFromDefaults } from "../ServiceContext";
-import { Event } from "../callbacks/CallbackManager";
+import { globalsHelper } from "../GlobalsHelper.js";
+import { NodeWithScore, ObjectType, jsonToNode } from "../Node.js";
+import { BaseRetriever } from "../Retriever.js";
+import {
+  ServiceContext,
+  serviceContextFromDefaults,
+} from "../ServiceContext.js";
+import { Event } from "../callbacks/CallbackManager.js";
 import {
  ClientParams,
  CloudConstructorParams,
  DEFAULT_PROJECT_NAME,
-} from "./types";
-import { getClient } from "./utils";
+} from "./types.js";
+import { getClient } from "./utils.js";

 export type RetrieveParams = Omit<
  PlatformApi.RetrievalParams,
@@ -1,2 +1,2 @@
-export * from "./LlamaCloudIndex";
-export * from "./LlamaCloudRetriever";
+export * from "./LlamaCloudIndex.js";
+export * from "./LlamaCloudRetriever.js";
@@ -1,4 +1,4 @@
-import { ServiceContext } from "../ServiceContext";
+import { ServiceContext } from "../ServiceContext.js";

 export const DEFAULT_PROJECT_NAME = "default";
 export const DEFAULT_BASE_URL = "https://api.cloud.llamaindex.ai";
@@ -1,5 +1,5 @@
 import { PlatformApiClient } from "@llamaindex/cloud";
-import { ClientParams, DEFAULT_BASE_URL } from "./types";
+import { ClientParams, DEFAULT_BASE_URL } from "./types.js";

 export async function getClient({
  apiKey,
@@ -1,6 +1,6 @@
-import { ImageType } from "../Node";
-import { MultiModalEmbedding } from "./MultiModalEmbedding";
-import { readImage } from "./utils";
+import { ImageType } from "../Node.js";
+import { MultiModalEmbedding } from "./MultiModalEmbedding.js";
+import { readImage } from "./utils.js";

 export enum ClipEmbeddingModelType {
  XENOVA_CLIP_VIT_BASE_PATCH32 = "Xenova/clip-vit-base-patch32",
@@ -1,4 +1,4 @@
-import { BaseEmbedding } from "./types";
+import { BaseEmbedding } from "./types.js";

 export enum HuggingFaceEmbeddingModelType {
  XENOVA_ALL_MINILM_L6_V2 = "Xenova/all-MiniLM-L6-v2",
@@ -1,5 +1,5 @@
-import { MistralAISession } from "../llm/mistral";
-import { BaseEmbedding } from "./types";
+import { MistralAISession } from "../llm/mistral.js";
+import { BaseEmbedding } from "./types.js";

 export enum MistralAIEmbeddingModelType {
  MISTRAL_EMBED = "mistral-embed",
@@ -1,5 +1,5 @@
-import { ImageType } from "../Node";
-import { BaseEmbedding } from "./types";
+import { ImageType } from "../Node.js";
+import { BaseEmbedding } from "./types.js";

 /*
 * Base class for Multi Modal embeddings.
@@ -1,5 +1,5 @@
-import { Ollama } from "../llm/ollama";
-import { BaseEmbedding } from "./types";
+import { Ollama } from "../llm/ollama.js";
+import { BaseEmbedding } from "./types.js";

 /**
 * OllamaEmbedding is an alias for Ollama that implements the BaseEmbedding interface.
@@ -5,9 +5,9 @@ import {
  getAzureConfigFromEnv,
  getAzureModel,
  shouldUseAzure,
-} from "../llm/azure";
-import { OpenAISession, getOpenAISession } from "../llm/open_ai";
-import { BaseEmbedding } from "./types";
+} from "../llm/azure.js";
+import { OpenAISession, getOpenAISession } from "../llm/open_ai.js";
+import { BaseEmbedding } from "./types.js";

 export const ALL_OPENAI_EMBEDDING_MODELS = {
  "text-embedding-ada-002": {
@@ -1,4 +1,4 @@
-import { OpenAIEmbedding } from "./OpenAIEmbedding";
+import { OpenAIEmbedding } from "./OpenAIEmbedding.js";

 export class FireworksEmbedding extends OpenAIEmbedding {
  constructor(init?: Partial<OpenAIEmbedding>) {
@@ -1,10 +1,10 @@
-export * from "./ClipEmbedding";
-export * from "./HuggingFaceEmbedding";
-export * from "./MistralAIEmbedding";
-export * from "./MultiModalEmbedding";
-export { OllamaEmbedding } from "./OllamaEmbedding";
-export * from "./OpenAIEmbedding";
-export { FireworksEmbedding } from "./fireworks";
-export { TogetherEmbedding } from "./together";
-export * from "./types";
-export * from "./utils";
+export * from "./ClipEmbedding.js";
+export * from "./HuggingFaceEmbedding.js";
+export * from "./MistralAIEmbedding.js";
+export * from "./MultiModalEmbedding.js";
+export { OllamaEmbedding } from "./OllamaEmbedding.js";
+export * from "./OpenAIEmbedding.js";
+export { FireworksEmbedding } from "./fireworks.js";
+export { TogetherEmbedding } from "./together.js";
+export * from "./types.js";
+export * from "./utils.js";
@@ -1,4 +1,4 @@
-import { OpenAIEmbedding } from "./OpenAIEmbedding";
+import { OpenAIEmbedding } from "./OpenAIEmbedding.js";

 export class TogetherEmbedding extends OpenAIEmbedding {
  constructor(init?: Partial<OpenAIEmbedding>) {
@@ -1,6 +1,6 @@
-import { BaseNode, MetadataMode } from "../Node";
-import { TransformComponent } from "../ingestion";
-import { SimilarityType, similarity } from "./utils";
+import { BaseNode, MetadataMode } from "../Node.js";
+import { TransformComponent } from "../ingestion/types.js";
+import { SimilarityType, similarity } from "./utils.js";

 const DEFAULT_EMBED_BATCH_SIZE = 10;

@@ -1,8 +1,8 @@
+import { defaultFS } from "@llamaindex/env";
 import _ from "lodash";
-import { ImageType } from "../Node";
-import { DEFAULT_SIMILARITY_TOP_K } from "../constants";
-import { defaultFS } from "../env";
-import { VectorStoreQueryMode } from "../storage/vectorStore/types";
+import { ImageType } from "../Node.js";
+import { DEFAULT_SIMILARITY_TOP_K } from "../constants.js";
+import { VectorStoreQueryMode } from "../storage/vectorStore/types.js";

 /**
 * Similarity type
@@ -46,7 +46,7 @@ export function similarity(

  switch (mode) {
    case SimilarityType.EUCLIDEAN: {
-      let difference = embedding1.map((x, i) => x - embedding2[i]);
+      const difference = embedding1.map((x, i) => x - embedding2[i]);
      return -norm(difference);
    }
    case SimilarityType.DOT_PRODUCT: {
@@ -94,7 +94,7 @@ export function getTopKEmbeddings(
    );
  }

-  let similarities: { similarity: number; id: number }[] = [];
+  const similarities: { similarity: number; id: number }[] = [];

  for (let i = 0; i < embeddings.length; i++) {
    const sim = similarity(queryEmbedding, embeddings[i]);
@@ -105,8 +105,8 @@ export function getTopKEmbeddings(

  similarities.sort((a, b) => b.similarity - a.similarity); // Reverse sort

-  let resultSimilarities: number[] = [];
-  let resultIds: any[] = [];
+  const resultSimilarities: number[] = [];
+  const resultIds: any[] = [];

  for (let i = 0; i < similarityTopK; i++) {
    if (i >= similarities.length) {
@@ -142,21 +142,21 @@ export function getTopKMMREmbeddings(
  _similarityCutoff: number | null = null,
  mmrThreshold: number | null = null,
 ): [number[], any[]] {
-  let threshold = mmrThreshold || 0.5;
+  const threshold = mmrThreshold || 0.5;
  similarityFn = similarityFn || similarity;

  if (embeddingIds === null || embeddingIds.length === 0) {
    embeddingIds = Array.from({ length: embeddings.length }, (_, i) => i);
  }
-  let fullEmbedMap = new Map(embeddingIds.map((value, i) => [value, i]));
-  let embedMap = new Map(fullEmbedMap);
-  let embedSimilarity: Map<any, number> = new Map();
+  const fullEmbedMap = new Map(embeddingIds.map((value, i) => [value, i]));
+  const embedMap = new Map(fullEmbedMap);
+  const embedSimilarity: Map<any, number> = new Map();
  let score: number = Number.NEGATIVE_INFINITY;
  let highScoreId: any | null = null;

  for (let i = 0; i < embeddings.length; i++) {
-    let emb = embeddings[i];
-    let similarity = similarityFn(queryEmbedding, emb);
+    const emb = embeddings[i];
+    const similarity = similarityFn(queryEmbedding, emb);
    embedSimilarity.set(embeddingIds[i], similarity);
    if (similarity * threshold > score) {
      highScoreId = embeddingIds[i];
@@ -164,18 +164,18 @@ export function getTopKMMREmbeddings(
    }
  }

-  let results: [number, any][] = [];
+  const results: [number, any][] = [];

-  let embeddingLength = embeddings.length;
-  let similarityTopKCount = similarityTopK || embeddingLength;
+  const embeddingLength = embeddings.length;
+  const similarityTopKCount = similarityTopK || embeddingLength;

  while (results.length < Math.min(similarityTopKCount, embeddingLength)) {
    results.push([score, highScoreId]);
    embedMap.delete(highScoreId!);
-    let recentEmbeddingId = highScoreId;
+    const recentEmbeddingId = highScoreId;
    score = Number.NEGATIVE_INFINITY;
-    for (let embedId of Array.from(embedMap.keys())) {
-      let overlapWithRecent = similarityFn(
+    for (const embedId of Array.from(embedMap.keys())) {
+      const overlapWithRecent = similarityFn(
        embeddings[embedMap.get(embedId)!],
        embeddings[fullEmbedMap.get(recentEmbeddingId!)!],
      );
@@ -192,8 +192,8 @@ export function getTopKMMREmbeddings(
    }
  }

-  let resultSimilarities = results.map(([s, _]) => s);
-  let resultIds = results.map(([_, n]) => n);
+  const resultSimilarities = results.map(([s, _]) => s);
+  const resultIds = results.map(([_, n]) => n);

  return [resultSimilarities, resultIds];
 }
@@ -1,23 +1,23 @@
-import { ChatHistory, getHistory } from "../../ChatHistory";
+import { ChatHistory, getHistory } from "../../ChatHistory.js";
 import {
  CondenseQuestionPrompt,
  defaultCondenseQuestionPrompt,
  messagesToHistoryStr,
-} from "../../Prompt";
-import { Response } from "../../Response";
+} from "../../Prompt.js";
+import { Response } from "../../Response.js";
 import {
  ServiceContext,
  serviceContextFromDefaults,
-} from "../../ServiceContext";
-import { ChatMessage, LLM } from "../../llm";
-import { extractText, streamReducer } from "../../llm/utils";
-import { PromptMixin } from "../../prompts";
-import { BaseQueryEngine } from "../../types";
+} from "../../ServiceContext.js";
+import { ChatMessage, LLM } from "../../llm/index.js";
+import { extractText, streamReducer } from "../../llm/utils.js";
+import { PromptMixin } from "../../prompts/index.js";
+import { BaseQueryEngine } from "../../types.js";
 import {
  ChatEngine,
  ChatEngineParamsNonStreaming,
  ChatEngineParamsStreaming,
-} from "./types";
+} from "./types.js";

 /**
 * CondenseQuestionChatEngine is used in conjunction with a Index (for example VectorStoreIndex).
@@ -1,21 +1,30 @@
-import { ChatHistory, getHistory } from "../../ChatHistory";
-import { ContextSystemPrompt } from "../../Prompt";
-import { Response } from "../../Response";
-import { BaseRetriever } from "../../Retriever";
-import { Event } from "../../callbacks/CallbackManager";
-import { randomUUID } from "../../env";
-import { ChatMessage, ChatResponseChunk, LLM, OpenAI } from "../../llm";
-import { MessageContent } from "../../llm/types";
-import { extractText, streamConverter, streamReducer } from "../../llm/utils";
-import { BaseNodePostprocessor } from "../../postprocessors";
-import { PromptMixin } from "../../prompts";
-import { DefaultContextGenerator } from "./DefaultContextGenerator";
+import { randomUUID } from "@llamaindex/env";
+import { ChatHistory, getHistory } from "../../ChatHistory.js";
+import { ContextSystemPrompt } from "../../Prompt.js";
+import { Response } from "../../Response.js";
+import { BaseRetriever } from "../../Retriever.js";
+import { Event } from "../../callbacks/CallbackManager.js";
+import {
+  ChatMessage,
+  ChatResponseChunk,
+  LLM,
+  OpenAI,
+} from "../../llm/index.js";
+import { MessageContent } from "../../llm/types.js";
+import {
+  extractText,
+  streamConverter,
+  streamReducer,
+} from "../../llm/utils.js";
+import { BaseNodePostprocessor } from "../../postprocessors/index.js";
+import { PromptMixin } from "../../prompts/Mixin.js";
+import { DefaultContextGenerator } from "./DefaultContextGenerator.js";
 import {
  ChatEngine,
  ChatEngineParamsNonStreaming,
  ChatEngineParamsStreaming,
  ContextGenerator,
-} from "./types";
+} from "./types.js";

 /**
 * ContextChatEngine uses the Index to get the appropriate context for each query.
@@ -1,11 +1,14 @@
-import { NodeWithScore, TextNode } from "../../Node";
-import { ContextSystemPrompt, defaultContextSystemPrompt } from "../../Prompt";
-import { BaseRetriever } from "../../Retriever";
-import { Event } from "../../callbacks/CallbackManager";
-import { randomUUID } from "../../env";
-import { BaseNodePostprocessor } from "../../postprocessors";
-import { PromptMixin } from "../../prompts";
-import { Context, ContextGenerator } from "./types";
+import { randomUUID } from "@llamaindex/env";
+import { NodeWithScore, TextNode } from "../../Node.js";
+import {
+  ContextSystemPrompt,
+  defaultContextSystemPrompt,
+} from "../../Prompt.js";
+import { BaseRetriever } from "../../Retriever.js";
+import { Event } from "../../callbacks/CallbackManager.js";
+import { BaseNodePostprocessor } from "../../postprocessors/index.js";
+import { PromptMixin } from "../../prompts/index.js";
+import { Context, ContextGenerator } from "./types.js";

 export class DefaultContextGenerator
  extends PromptMixin
@@ -1,12 +1,12 @@
-import { ChatHistory, getHistory } from "../../ChatHistory";
-import { Response } from "../../Response";
-import { ChatResponseChunk, LLM, OpenAI } from "../../llm";
-import { streamConverter, streamReducer } from "../../llm/utils";
+import { ChatHistory, getHistory } from "../../ChatHistory.js";
+import { Response } from "../../Response.js";
+import { ChatResponseChunk, LLM, OpenAI } from "../../llm/index.js";
+import { streamConverter, streamReducer } from "../../llm/utils.js";
 import {
  ChatEngine,
  ChatEngineParamsNonStreaming,
  ChatEngineParamsStreaming,
-} from "./types";
+} from "./types.js";

 /**
 * SimpleChatEngine is the simplest possible chat engine. Useful for using your own custom prompts.
@@ -1,4 +1,4 @@
-export { CondenseQuestionChatEngine } from "./CondenseQuestionChatEngine";
-export { ContextChatEngine } from "./ContextChatEngine";
-export { SimpleChatEngine } from "./SimpleChatEngine";
-export * from "./types";
+export { CondenseQuestionChatEngine } from "./CondenseQuestionChatEngine.js";
+export { ContextChatEngine } from "./ContextChatEngine.js";
+export { SimpleChatEngine } from "./SimpleChatEngine.js";
+export * from "./types.js";
@@ -1,10 +1,10 @@
-import { ChatHistory } from "../../ChatHistory";
-import { BaseNode, NodeWithScore } from "../../Node";
-import { Response } from "../../Response";
-import { Event } from "../../callbacks/CallbackManager";
-import { ChatMessage } from "../../llm";
-import { MessageContent } from "../../llm/types";
-import { ToolOutput } from "../../tools/types";
+import { ChatHistory } from "../../ChatHistory.js";
+import { BaseNode, NodeWithScore } from "../../Node.js";
+import { Response } from "../../Response.js";
+import { Event } from "../../callbacks/CallbackManager.js";
+import { ChatMessage } from "../../llm/index.js";
+import { MessageContent } from "../../llm/types.js";
+import { ToolOutput } from "../../tools/types.js";

 /**
 * Represents the base parameters for ChatEngine.
@@ -1,17 +1,20 @@
-import { NodeWithScore } from "../../Node";
-import { Response } from "../../Response";
-import { BaseRetriever } from "../../Retriever";
-import { ServiceContext } from "../../ServiceContext";
-import { Event } from "../../callbacks/CallbackManager";
-import { randomUUID } from "../../env";
-import { BaseNodePostprocessor } from "../../postprocessors";
-import { PromptMixin } from "../../prompts";
-import { BaseSynthesizer, ResponseSynthesizer } from "../../synthesizers";
+import { randomUUID } from "@llamaindex/env";
+import { NodeWithScore } from "../../Node.js";
+import { Response } from "../../Response.js";
+import { BaseRetriever } from "../../Retriever.js";
+import { ServiceContext } from "../../ServiceContext.js";
+import { Event } from "../../callbacks/CallbackManager.js";
+import { BaseNodePostprocessor } from "../../postprocessors/index.js";
+import { PromptMixin } from "../../prompts/Mixin.js";
+import {
+  BaseSynthesizer,
+  ResponseSynthesizer,
+} from "../../synthesizers/index.js";
 import {
  BaseQueryEngine,
  QueryEngineParamsNonStreaming,
  QueryEngineParamsStreaming,
-} from "../../types";
+} from "../../types.js";

 /**
 * A query engine that uses a retriever to query an index and then synthesizes the response.
@@ -1,18 +1,18 @@
-import { BaseNode } from "../../Node";
-import { Response } from "../../Response";
+import { BaseNode } from "../../Node.js";
+import { Response } from "../../Response.js";
 import {
  ServiceContext,
  serviceContextFromDefaults,
-} from "../../ServiceContext";
-import { PromptMixin } from "../../prompts";
-import { BaseSelector, LLMSingleSelector } from "../../selectors";
-import { TreeSummarize } from "../../synthesizers";
+} from "../../ServiceContext.js";
+import { PromptMixin } from "../../prompts/index.js";
+import { BaseSelector, LLMSingleSelector } from "../../selectors/index.js";
+import { TreeSummarize } from "../../synthesizers/index.js";
 import {
  BaseQueryEngine,
  QueryBundle,
  QueryEngineParamsNonStreaming,
  QueryEngineParamsStreaming,
-} from "../../types";
+} from "../../types.js";

 type RouterQueryEngineTool = {
  queryEngine: BaseQueryEngine;
@@ -1,18 +1,18 @@
-import { NodeWithScore, TextNode } from "../../Node";
-import { LLMQuestionGenerator } from "../../QuestionGenerator";
-import { Response } from "../../Response";
+import { randomUUID } from "@llamaindex/env";
+import { NodeWithScore, TextNode } from "../../Node.js";
+import { LLMQuestionGenerator } from "../../QuestionGenerator.js";
+import { Response } from "../../Response.js";
 import {
  ServiceContext,
  serviceContextFromDefaults,
-} from "../../ServiceContext";
-import { Event } from "../../callbacks/CallbackManager";
-import { randomUUID } from "../../env";
-import { PromptMixin } from "../../prompts";
+} from "../../ServiceContext.js";
+import { Event } from "../../callbacks/CallbackManager.js";
+import { PromptMixin } from "../../prompts/Mixin.js";
 import {
  BaseSynthesizer,
  CompactAndRefine,
  ResponseSynthesizer,
-} from "../../synthesizers";
+} from "../../synthesizers/index.js";

 import {
  BaseQueryEngine,
@@ -20,9 +20,9 @@ import {
  QueryEngineParamsNonStreaming,
  QueryEngineParamsStreaming,
  ToolMetadata,
-} from "../../types";
+} from "../../types.js";

-import { BaseQuestionGenerator, SubQuestion } from "./types";
+import { BaseQuestionGenerator, SubQuestion } from "./types.js";

 /**
 * SubQuestionQueryEngine decomposes a question into subquestions and then
@@ -1,3 +1,3 @@
-export * from "./RetrieverQueryEngine";
-export * from "./RouterQueryEngine";
-export * from "./SubQuestionQueryEngine";
+export * from "./RetrieverQueryEngine.js";
+export * from "./RouterQueryEngine.js";
+export * from "./SubQuestionQueryEngine.js";
@@ -1,4 +1,4 @@
-import { ToolMetadata } from "../../types";
+import { ToolMetadata } from "../../types.js";

 /**
 * QuestionGenerators generate new questions for the LLM using tools and a user query.
@@ -1,13 +1,13 @@
-import { BaseNode, MetadataMode, TextNode } from "../Node";
-import { LLM, OpenAI } from "../llm";
+import { BaseNode, MetadataMode, TextNode } from "../Node.js";
+import { LLM, OpenAI } from "../llm/index.js";
 import {
  defaultKeywordExtractorPromptTemplate,
  defaultQuestionAnswerPromptTemplate,
  defaultSummaryExtractorPromptTemplate,
  defaultTitleCombinePromptTemplate,
  defaultTitleExtractorPromptTemplate,
-} from "./prompts";
-import { BaseExtractor } from "./types";
+} from "./prompts.js";
+import { BaseExtractor } from "./types.js";

 const STRIP_REGEX = /(\r\n|\n|\r)/gm;

@@ -172,7 +172,7 @@ export class TitleExtractor extends BaseExtractor {

    if (nodesToExtractTitle.length === 0) return [];

-    let titlesCandidates: string[] = [];
+    const titlesCandidates: string[] = [];
    let title: string = "";

    for (let i = 0; i < nodesToExtractTitle.length; i++) {
@@ -411,7 +411,7 @@ export class SummaryExtractor extends BaseExtractor {
      nodes.map((node) => this.generateNodeSummary(node)),
    );

-    let metadataList: any[] = nodes.map(() => ({}));
+    const metadataList: any[] = nodes.map(() => ({}));

    for (let i = 0; i < nodes.length; i++) {
      if (i > 0 && this._prevSummary && nodeSummaries[i - 1]) {
@@ -3,5 +3,5 @@ export {
  QuestionsAnsweredExtractor,
  SummaryExtractor,
  TitleExtractor,
-} from "./MetadataExtractors";
-export { BaseExtractor } from "./types";
+} from "./MetadataExtractors.js";
+export { BaseExtractor } from "./types.js";
@@ -1,6 +1,6 @@
-import { BaseNode, MetadataMode, TextNode } from "../Node";
-import { TransformComponent } from "../ingestion";
-import { defaultNodeTextTemplate } from "./prompts";
+import { BaseNode, MetadataMode, TextNode } from "../Node.js";
+import { TransformComponent } from "../ingestion/types.js";
+import { defaultNodeTextTemplate } from "./prompts.js";

 /*
 * Abstract class for all extractors.
@@ -43,16 +43,16 @@ export abstract class BaseExtractor implements TransformComponent {
      newNodes = nodes.slice();
    }

-    let curMetadataList = await this.extract(newNodes);
+    const curMetadataList = await this.extract(newNodes);

-    for (let idx in newNodes) {
+    for (const idx in newNodes) {
      newNodes[idx].metadata = {
        ...newNodes[idx].metadata,
        ...curMetadataList[idx],
      };
    }

-    for (let idx in newNodes) {
+    for (const idx in newNodes) {
      if (excludedEmbedMetadataKeys) {
        newNodes[idx].excludedEmbedMetadataKeys.concat(
          excludedEmbedMetadataKeys,
@@ -1,31 +1,31 @@
-export * from "./ChatHistory";
-export * from "./GlobalsHelper";
-export * from "./Node";
-export * from "./OutputParser";
-export * from "./Prompt";
-export * from "./PromptHelper";
-export * from "./QuestionGenerator";
-export * from "./Response";
-export * from "./Retriever";
-export * from "./ServiceContext";
-export * from "./TextSplitter";
-export * from "./agent";
-export * from "./callbacks/CallbackManager";
-export * from "./cloud";
-export * from "./constants";
-export * from "./embeddings";
-export * from "./engines/chat";
-export * from "./engines/query";
-export * from "./extractors";
-export * from "./indices";
-export * from "./ingestion";
-export * from "./llm";
-export * from "./nodeParsers";
-export * from "./objects";
-export * from "./postprocessors";
-export * from "./prompts";
-export * from "./readers";
-export * from "./selectors";
-export * from "./storage";
-export * from "./synthesizers";
-export * from "./tools";
+export * from "./ChatHistory.js";
+export * from "./GlobalsHelper.js";
+export * from "./Node.js";
+export * from "./OutputParser.js";
+export * from "./Prompt.js";
+export * from "./PromptHelper.js";
+export * from "./QuestionGenerator.js";
+export * from "./Response.js";
+export * from "./Retriever.js";
+export * from "./ServiceContext.js";
+export * from "./TextSplitter.js";
+export * from "./agent/index.js";
+export * from "./callbacks/CallbackManager.js";
+export * from "./cloud/index.js";
+export * from "./constants.js";
+export * from "./embeddings/index.js";
+export * from "./engines/chat/index.js";
+export * from "./engines/query/index.js";
+export * from "./extractors/index.js";
+export * from "./indices/index.js";
+export * from "./ingestion/index.js";
+export * from "./llm/index.js";
+export * from "./nodeParsers/index.js";
+export * from "./objects/index.js";
+export * from "./postprocessors/index.js";
+export * from "./prompts/index.js";
+export * from "./readers/index.js";
+export * from "./selectors/index.js";
+export * from "./storage/index.js";
+export * from "./synthesizers/index.js";
+export * from "./tools/index.js";
@@ -1,112 +1,15 @@
-import { BaseNode, Document, jsonToNode } from "../Node";
-import { BaseRetriever } from "../Retriever";
-import { ServiceContext } from "../ServiceContext";
-import { randomUUID } from "../env";
-import { runTransformations } from "../ingestion";
-import { StorageContext } from "../storage/StorageContext";
-import { BaseDocumentStore } from "../storage/docStore/types";
-import { BaseIndexStore } from "../storage/indexStore/types";
-import { VectorStore } from "../storage/vectorStore/types";
-import { BaseSynthesizer } from "../synthesizers";
-import { BaseQueryEngine } from "../types";
-
-/**
- * The underlying structure of each index.
- */
-export abstract class IndexStruct {
-  indexId: string;
-  summary?: string;
-
-  constructor(indexId = randomUUID(), summary = undefined) {
-    this.indexId = indexId;
-    this.summary = summary;
-  }
-
-  toJson(): Record<string, unknown> {
-    return {
-      indexId: this.indexId,
-      summary: this.summary,
-    };
-  }
-
-  getSummary(): string {
-    if (this.summary === undefined) {
-      throw new Error("summary field of the index dict is not set");
-    }
-    return this.summary;
-  }
-}
-
-export enum IndexStructType {
-  SIMPLE_DICT = "simple_dict",
-  LIST = "list",
-  KEYWORD_TABLE = "keyword_table",
-}
-
-export class IndexDict extends IndexStruct {
-  nodesDict: Record<string, BaseNode> = {};
-  type: IndexStructType = IndexStructType.SIMPLE_DICT;
-
-  getSummary(): string {
-    if (this.summary === undefined) {
-      throw new Error("summary field of the index dict is not set");
-    }
-    return this.summary;
-  }
-
-  addNode(node: BaseNode, textId?: string) {
-    const vectorId = textId ?? node.id_;
-    this.nodesDict[vectorId] = node;
-  }
-
-  toJson(): Record<string, unknown> {
-    return {
-      ...super.toJson(),
-      nodesDict: this.nodesDict,
-      type: this.type,
-    };
-  }
-
-  delete(nodeId: string) {
-    delete this.nodesDict[nodeId];
-  }
-}
-
-export function jsonToIndexStruct(json: any): IndexStruct {
-  if (json.type === IndexStructType.LIST) {
-    const indexList = new IndexList(json.indexId, json.summary);
-    indexList.nodes = json.nodes;
-    return indexList;
-  } else if (json.type === IndexStructType.SIMPLE_DICT) {
-    const indexDict = new IndexDict(json.indexId, json.summary);
-    indexDict.nodesDict = Object.entries(json.nodesDict).reduce<
-      Record<string, BaseNode>
-    >((acc, [key, value]) => {
-      acc[key] = jsonToNode(value);
-      return acc;
-    }, {});
-    return indexDict;
-  } else {
-    throw new Error(`Unknown index struct type: ${json.type}`);
-  }
-}
-
-export class IndexList extends IndexStruct {
-  nodes: string[] = [];
-  type: IndexStructType = IndexStructType.LIST;
-
-  addNode(node: BaseNode) {
-    this.nodes.push(node.id_);
-  }
-
-  toJson(): Record<string, unknown> {
-    return {
-      ...super.toJson(),
-      nodes: this.nodes,
-      type: this.type,
-    };
-  }
-}
+import { BaseNode, Document } from "../Node.js";
+import { BaseRetriever } from "../Retriever.js";
+import { ServiceContext } from "../ServiceContext.js";
+import { runTransformations } from "../ingestion/IngestionPipeline.js";
+import { StorageContext } from "../storage/StorageContext.js";
+import { BaseDocumentStore } from "../storage/docStore/types.js";
+import { BaseIndexStore } from "../storage/indexStore/types.js";
+import { VectorStore } from "../storage/vectorStore/types.js";
+import { BaseSynthesizer } from "../synthesizers/types.js";
+import { BaseQueryEngine } from "../types.js";
+import { IndexStruct } from "./IndexStruct.js";
+import { IndexStructType } from "./json-to-index-struct.js";

 // A table of keywords mapping keywords to text chunks.
 export class KeywordTable extends IndexStruct {
@@ -0,0 +1,28 @@
+import { randomUUID } from "@llamaindex/env";
+
+/**
+ * The underlying structure of each index.
+ */
+export abstract class IndexStruct {
+  indexId: string;
+  summary?: string;
+
+  constructor(indexId = randomUUID(), summary = undefined) {
+    this.indexId = indexId;
+    this.summary = summary;
+  }
+
+  toJson(): Record<string, unknown> {
+    return {
+      indexId: this.indexId,
+      summary: this.summary,
+    };
+  }
+
+  getSummary(): string {
+    if (this.summary === undefined) {
+      throw new Error("summary field of the index dict is not set");
+    }
+    return this.summary;
+  }
+}
@@ -1,4 +1,4 @@
-export * from "./BaseIndex";
-export * from "./keyword";
-export * from "./summary";
-export * from "./vectorStore";
+export * from "./BaseIndex.js";
+export * from "./keyword/index.js";
+export * from "./summary/index.js";
+export * from "./vectorStore/index.js";
@@ -0,0 +1,71 @@
+import { BaseNode, jsonToNode } from "../Node.js";
+import { IndexStruct } from "./IndexStruct.js";
+
+export enum IndexStructType {
+  SIMPLE_DICT = "simple_dict",
+  LIST = "list",
+  KEYWORD_TABLE = "keyword_table",
+}
+export class IndexDict extends IndexStruct {
+  nodesDict: Record<string, BaseNode> = {};
+  type: IndexStructType = IndexStructType.SIMPLE_DICT;
+
+  getSummary(): string {
+    if (this.summary === undefined) {
+      throw new Error("summary field of the index dict is not set");
+    }
+    return this.summary;
+  }
+
+  addNode(node: BaseNode, textId?: string) {
+    const vectorId = textId ?? node.id_;
+    this.nodesDict[vectorId] = node;
+  }
+
+  toJson(): Record<string, unknown> {
+    return {
+      ...super.toJson(),
+      nodesDict: this.nodesDict,
+      type: this.type,
+    };
+  }
+
+  delete(nodeId: string) {
+    delete this.nodesDict[nodeId];
+  }
+}
+export function jsonToIndexStruct(json: any): IndexStruct {
+  if (json.type === IndexStructType.LIST) {
+    const indexList = new IndexList(json.indexId, json.summary);
+    indexList.nodes = json.nodes;
+    return indexList;
+  } else if (json.type === IndexStructType.SIMPLE_DICT) {
+    const indexDict = new IndexDict(json.indexId, json.summary);
+    indexDict.nodesDict = Object.entries(json.nodesDict).reduce<
+      Record<string, BaseNode>
+    >((acc, [key, value]) => {
+      acc[key] = jsonToNode(value);
+      return acc;
+    }, {});
+    return indexDict;
+  } else {
+    throw new Error(`Unknown index struct type: ${json.type}`);
+  }
+}
+
+export class IndexList extends IndexStruct {
+  nodes: string[] = [];
+  type: IndexStructType = IndexStructType.LIST;
+
+  addNode(node: BaseNode) {
+    this.nodes.push(node.id_);
+  }
+
+  toJson(): Record<string, unknown> {
+    return {
+      ...super.toJson(),
+      nodes: this.nodes,
+      type: this.type,
+    };
+  }
+}
@@ -1,278 +0,0 @@
-import { BaseNode, Document, MetadataMode } from "../../Node";
-import { defaultKeywordExtractPrompt } from "../../Prompt";
-import { BaseRetriever } from "../../Retriever";
-import {
-  ServiceContext,
-  serviceContextFromDefaults,
-} from "../../ServiceContext";
-import { RetrieverQueryEngine } from "../../engines/query";
-import { BaseNodePostprocessor } from "../../postprocessors";
-import {
-  BaseDocumentStore,
-  StorageContext,
-  storageContextFromDefaults,
-} from "../../storage";
-import { BaseSynthesizer } from "../../synthesizers";
-import { BaseQueryEngine } from "../../types";
-import {
-  BaseIndex,
-  BaseIndexInit,
-  IndexStructType,
-  KeywordTable,
-} from "../BaseIndex";
-import {
-  KeywordTableLLMRetriever,
-  KeywordTableRAKERetriever,
-  KeywordTableSimpleRetriever,
-} from "./KeywordTableIndexRetriever";
-import { extractKeywordsGivenResponse } from "./utils";
-
-export interface KeywordIndexOptions {
-  nodes?: BaseNode[];
-  indexStruct?: KeywordTable;
-  indexId?: string;
-  serviceContext?: ServiceContext;
-  storageContext?: StorageContext;
-}
-export enum KeywordTableRetrieverMode {
-  DEFAULT = "DEFAULT",
-  SIMPLE = "SIMPLE",
-  RAKE = "RAKE",
-}
-
-const KeywordTableRetrieverMap = {
-  [KeywordTableRetrieverMode.DEFAULT]: KeywordTableLLMRetriever,
-  [KeywordTableRetrieverMode.SIMPLE]: KeywordTableSimpleRetriever,
-  [KeywordTableRetrieverMode.RAKE]: KeywordTableRAKERetriever,
-};
-
-/**
- * The KeywordTableIndex, an index that extracts keywords from each Node and builds a mapping from each keyword to the corresponding Nodes of that keyword.
- */
-export class KeywordTableIndex extends BaseIndex<KeywordTable> {
-  constructor(init: BaseIndexInit<KeywordTable>) {
-    super(init);
-  }
-
-  static async init(options: KeywordIndexOptions): Promise<KeywordTableIndex> {
-    const storageContext =
-      options.storageContext ?? (await storageContextFromDefaults({}));
-    const serviceContext =
-      options.serviceContext ?? serviceContextFromDefaults({});
-    const { docStore, indexStore } = storageContext;
-
-    // Setup IndexStruct from storage
-    let indexStructs = (await indexStore.getIndexStructs()) as KeywordTable[];
-    let indexStruct: KeywordTable | null;
-
-    if (options.indexStruct && indexStructs.length > 0) {
-      throw new Error(
-        "Cannot initialize index with both indexStruct and indexStore",
-      );
-    }
-
-    if (options.indexStruct) {
-      indexStruct = options.indexStruct;
-    } else if (indexStructs.length == 1) {
-      indexStruct = indexStructs[0];
-    } else if (indexStructs.length > 1 && options.indexId) {
-      indexStruct = (await indexStore.getIndexStruct(
-        options.indexId,
-      )) as KeywordTable;
-    } else {
-      indexStruct = null;
-    }
-
-    // check indexStruct type
-    if (indexStruct && indexStruct.type !== IndexStructType.KEYWORD_TABLE) {
-      throw new Error(
-        "Attempting to initialize KeywordTableIndex with non-keyword table indexStruct",
-      );
-    }
-
-    if (indexStruct) {
-      if (options.nodes) {
-        throw new Error(
-          "Cannot initialize KeywordTableIndex with both nodes and indexStruct",
-        );
-      }
-    } else {
-      if (!options.nodes) {
-        throw new Error(
-          "Cannot initialize KeywordTableIndex without nodes or indexStruct",
-        );
-      }
-      indexStruct = await KeywordTableIndex.buildIndexFromNodes(
-        options.nodes,
-        storageContext.docStore,
-        serviceContext,
-      );
-
-      await indexStore.addIndexStruct(indexStruct);
-    }
-
-    return new KeywordTableIndex({
-      storageContext,
-      serviceContext,
-      docStore,
-      indexStore,
-      indexStruct,
-    });
-  }
-
-  asRetriever(options?: any): BaseRetriever {
-    const { mode = KeywordTableRetrieverMode.DEFAULT, ...otherOptions } =
-      options ?? {};
-    const KeywordTableRetriever =
-      KeywordTableRetrieverMap[mode as KeywordTableRetrieverMode];
-    if (KeywordTableRetriever) {
-      return new KeywordTableRetriever({ index: this, ...otherOptions });
-    }
-    throw new Error(`Unknown retriever mode: ${mode}`);
-  }
-
-  asQueryEngine(options?: {
-    retriever?: BaseRetriever;
-    responseSynthesizer?: BaseSynthesizer;
-    preFilters?: unknown;
-    nodePostprocessors?: BaseNodePostprocessor[];
-  }): BaseQueryEngine {
-    const { retriever, responseSynthesizer } = options ?? {};
-    return new RetrieverQueryEngine(
-      retriever ?? this.asRetriever(),
-      responseSynthesizer,
-      options?.preFilters,
-      options?.nodePostprocessors,
-    );
-  }
-
-  static async extractKeywords(
-    text: string,
-    serviceContext: ServiceContext,
-  ): Promise<Set<string>> {
-    const response = await serviceContext.llm.complete({
-      prompt: defaultKeywordExtractPrompt({
-        context: text,
-      }),
-    });
-    return extractKeywordsGivenResponse(response.text, "KEYWORDS:");
-  }
-
-  /**
-   * High level API: split documents, get keywords, and build index.
-   * @param documents
-   * @param storageContext
-   * @param serviceContext
-   * @returns
-   */
-  static async fromDocuments(
-    documents: Document[],
-    args: {
-      storageContext?: StorageContext;
-      serviceContext?: ServiceContext;
-    } = {},
-  ): Promise<KeywordTableIndex> {
-    let { storageContext, serviceContext } = args;
-    storageContext = storageContext ?? (await storageContextFromDefaults({}));
-    serviceContext = serviceContext ?? serviceContextFromDefaults({});
-    const docStore = storageContext.docStore;
-
-    docStore.addDocuments(documents, true);
-    for (const doc of documents) {
-      docStore.setDocumentHash(doc.id_, doc.hash);
-    }
-
-    const nodes = serviceContext.nodeParser.getNodesFromDocuments(documents);
-    const index = await KeywordTableIndex.init({
-      nodes,
-      storageContext,
-      serviceContext,
-    });
-    return index;
-  }
-
-  /**
-   * Get keywords for nodes and place them into the index.
-   * @param nodes
-   * @param serviceContext
-   * @param vectorStore
-   * @returns
-   */
-  static async buildIndexFromNodes(
-    nodes: BaseNode[],
-    docStore: BaseDocumentStore,
-    serviceContext: ServiceContext,
-  ): Promise<KeywordTable> {
-    const indexStruct = new KeywordTable();
-    await docStore.addDocuments(nodes, true);
-    for (const node of nodes) {
-      const keywords = await KeywordTableIndex.extractKeywords(
-        node.getContent(MetadataMode.LLM),
-        serviceContext,
-      );
-      indexStruct.addNode([...keywords], node.id_);
-    }
-    return indexStruct;
-  }
-
-  async insertNodes(nodes: BaseNode[]) {
-    for (let node of nodes) {
-      const keywords = await KeywordTableIndex.extractKeywords(
-        node.getContent(MetadataMode.LLM),
-        this.serviceContext,
-      );
-      this.indexStruct.addNode([...keywords], node.id_);
-    }
-  }
-
-  deleteNode(nodeId: string): void {
-    const keywordsToDelete: Set<string> = new Set();
-    for (const [keyword, existingNodeIds] of Object.entries(
-      this.indexStruct.table,
-    )) {
-      const index = existingNodeIds.indexOf(nodeId);
-      if (index !== -1) {
-        existingNodeIds.splice(index, 1);
-
-        // Delete keywords that have zero nodes
-        if (existingNodeIds.length === 0) {
-          keywordsToDelete.add(keyword);
-        }
-      }
-    }
-    this.indexStruct.deleteNode([...keywordsToDelete], nodeId);
-  }
-
-  async deleteNodes(nodeIds: string[], deleteFromDocStore: boolean) {
-    nodeIds.forEach((nodeId) => {
-      this.deleteNode(nodeId);
-    });
-
-    if (deleteFromDocStore) {
-      for (const nodeId of nodeIds) {
-        await this.docStore.deleteDocument(nodeId, false);
-      }
-    }
-
-    await this.storageContext.indexStore.addIndexStruct(this.indexStruct);
-  }
-
-  async deleteRefDoc(
-    refDocId: string,
-    deleteFromDocStore?: boolean,
-  ): Promise<void> {
-    const refDocInfo = await this.docStore.getRefDocInfo(refDocId);
-
-    if (!refDocInfo) {
-      return;
-    }
-
-    await this.deleteNodes(refDocInfo.nodeIds, false);
-
-    if (deleteFromDocStore) {
-      await this.docStore.deleteRefDoc(refDocId, false);
-    }
-
-    return;
-  }
-}
@@ -1,116 +0,0 @@
-import { NodeWithScore } from "../../Node";
-import {
-  defaultKeywordExtractPrompt,
-  defaultQueryKeywordExtractPrompt,
-  KeywordExtractPrompt,
-  QueryKeywordExtractPrompt,
-} from "../../Prompt";
-import { BaseRetriever } from "../../Retriever";
-import { ServiceContext } from "../../ServiceContext";
-import { BaseDocumentStore } from "../../storage/docStore/types";
-import { KeywordTable } from "../BaseIndex";
-import { KeywordTableIndex } from "./KeywordTableIndex";
-import {
-  extractKeywordsGivenResponse,
-  rakeExtractKeywords,
-  simpleExtractKeywords,
-} from "./utils";
-
-// Base Keyword Table Retriever
-abstract class BaseKeywordTableRetriever implements BaseRetriever {
-  protected index: KeywordTableIndex;
-  protected indexStruct: KeywordTable;
-  protected docstore: BaseDocumentStore;
-  protected serviceContext: ServiceContext;
-
-  protected maxKeywordsPerQuery: number; // Maximum number of keywords to extract from query.
-  protected numChunksPerQuery: number; // Maximum number of text chunks to query.
-  protected keywordExtractTemplate: KeywordExtractPrompt; // A Keyword Extraction Prompt
-  protected queryKeywordExtractTemplate: QueryKeywordExtractPrompt; // A Query Keyword Extraction Prompt
-
-  constructor({
-    index,
-    keywordExtractTemplate,
-    queryKeywordExtractTemplate,
-    maxKeywordsPerQuery = 10,
-    numChunksPerQuery = 10,
-  }: {
-    index: KeywordTableIndex;
-    keywordExtractTemplate?: KeywordExtractPrompt;
-    queryKeywordExtractTemplate?: QueryKeywordExtractPrompt;
-    maxKeywordsPerQuery: number;
-    numChunksPerQuery: number;
-  }) {
-    this.index = index;
-    this.indexStruct = index.indexStruct;
-    this.docstore = index.docStore;
-    this.serviceContext = index.serviceContext;
-
-    this.maxKeywordsPerQuery = maxKeywordsPerQuery;
-    this.numChunksPerQuery = numChunksPerQuery;
-    this.keywordExtractTemplate =
-      keywordExtractTemplate || defaultKeywordExtractPrompt;
-    this.queryKeywordExtractTemplate =
-      queryKeywordExtractTemplate || defaultQueryKeywordExtractPrompt;
-  }
-
-  abstract getKeywords(query: string): Promise<string[]>;
-
-  async retrieve(query: string): Promise<NodeWithScore[]> {
-    const keywords = await this.getKeywords(query);
-    const chunkIndicesCount: { [key: string]: number } = {};
-    const filteredKeywords = keywords.filter((keyword) =>
-      this.indexStruct.table.has(keyword),
-    );
-
-    for (let keyword of filteredKeywords) {
-      for (let nodeId of this.indexStruct.table.get(keyword) || []) {
-        chunkIndicesCount[nodeId] = (chunkIndicesCount[nodeId] ?? 0) + 1;
-      }
-    }
-
-    const sortedChunkIndices = Object.keys(chunkIndicesCount)
-      .sort((a, b) => chunkIndicesCount[b] - chunkIndicesCount[a])
-      .slice(0, this.numChunksPerQuery);
-
-    const sortedNodes = await this.docstore.getNodes(sortedChunkIndices);
-
-    return sortedNodes.map((node) => ({ node }));
-  }
-
-  getServiceContext(): ServiceContext {
-    return this.index.serviceContext;
-  }
-}
-
-// Extracts keywords using LLMs.
-export class KeywordTableLLMRetriever extends BaseKeywordTableRetriever {
-  async getKeywords(query: string): Promise<string[]> {
-    const response = await this.serviceContext.llm.complete({
-      prompt: this.queryKeywordExtractTemplate({
-        question: query,
-        maxKeywords: this.maxKeywordsPerQuery,
-      }),
-    });
-    const keywords = extractKeywordsGivenResponse(response.text, "KEYWORDS:");
-    return [...keywords];
-  }
-}
-
-// Extracts keywords using simple regex-based keyword extractor.
-export class KeywordTableSimpleRetriever extends BaseKeywordTableRetriever {
-  getKeywords(query: string): Promise<string[]> {
-    return Promise.resolve([
-      ...simpleExtractKeywords(query, this.maxKeywordsPerQuery),
-    ]);
-  }
-}
-
-// Extracts keywords using RAKE keyword extractor
-export class KeywordTableRAKERetriever extends BaseKeywordTableRetriever {
-  getKeywords(query: string): Promise<string[]> {
-    return Promise.resolve([
-      ...rakeExtractKeywords(query, this.maxKeywordsPerQuery),
-    ]);
-  }
-}
@@ -1,9 +1,377 @@
-export {
-  KeywordTableIndex,
-  KeywordTableRetrieverMode,
-} from "./KeywordTableIndex";
-export {
-  KeywordTableLLMRetriever,
-  KeywordTableRAKERetriever,
-  KeywordTableSimpleRetriever,
-} from "./KeywordTableIndexRetriever";
+import { BaseNode, Document, MetadataMode, NodeWithScore } from "../../Node.js";
+import {
+  KeywordExtractPrompt,
+  QueryKeywordExtractPrompt,
+  defaultKeywordExtractPrompt,
+  defaultQueryKeywordExtractPrompt,
+} from "../../Prompt.js";
+import { BaseRetriever } from "../../Retriever.js";
+import {
+  ServiceContext,
+  serviceContextFromDefaults,
+} from "../../ServiceContext.js";
+import { RetrieverQueryEngine } from "../../engines/query/index.js";
+import { BaseNodePostprocessor } from "../../postprocessors/index.js";
+import {
+  BaseDocumentStore,
+  StorageContext,
+  storageContextFromDefaults,
+} from "../../storage/index.js";
+import { BaseSynthesizer } from "../../synthesizers/index.js";
+import { BaseQueryEngine } from "../../types.js";
+import { BaseIndex, BaseIndexInit, KeywordTable } from "../BaseIndex.js";
+import { IndexStructType } from "../json-to-index-struct.js";
+import {
+  extractKeywordsGivenResponse,
+  rakeExtractKeywords,
+  simpleExtractKeywords,
+} from "./utils.js";
+
+export interface KeywordIndexOptions {
+  nodes?: BaseNode[];
+  indexStruct?: KeywordTable;
+  indexId?: string;
+  serviceContext?: ServiceContext;
+  storageContext?: StorageContext;
+}
+export enum KeywordTableRetrieverMode {
+  DEFAULT = "DEFAULT",
+  SIMPLE = "SIMPLE",
+  RAKE = "RAKE",
+}
+
+// Base Keyword Table Retriever
+abstract class BaseKeywordTableRetriever implements BaseRetriever {
+  protected index: KeywordTableIndex;
+  protected indexStruct: KeywordTable;
+  protected docstore: BaseDocumentStore;
+  protected serviceContext: ServiceContext;
+
+  protected maxKeywordsPerQuery: number; // Maximum number of keywords to extract from query.
+  protected numChunksPerQuery: number; // Maximum number of text chunks to query.
+  protected keywordExtractTemplate: KeywordExtractPrompt; // A Keyword Extraction Prompt
+  protected queryKeywordExtractTemplate: QueryKeywordExtractPrompt; // A Query Keyword Extraction Prompt
+
+  constructor({
+    index,
+    keywordExtractTemplate,
+    queryKeywordExtractTemplate,
+    maxKeywordsPerQuery = 10,
+    numChunksPerQuery = 10,
+  }: {
+    index: KeywordTableIndex;
+    keywordExtractTemplate?: KeywordExtractPrompt;
+    queryKeywordExtractTemplate?: QueryKeywordExtractPrompt;
+    maxKeywordsPerQuery: number;
+    numChunksPerQuery: number;
+  }) {
+    this.index = index;
+    this.indexStruct = index.indexStruct;
+    this.docstore = index.docStore;
+    this.serviceContext = index.serviceContext;
+
+    this.maxKeywordsPerQuery = maxKeywordsPerQuery;
+    this.numChunksPerQuery = numChunksPerQuery;
+    this.keywordExtractTemplate =
+      keywordExtractTemplate || defaultKeywordExtractPrompt;
+    this.queryKeywordExtractTemplate =
+      queryKeywordExtractTemplate || defaultQueryKeywordExtractPrompt;
+  }
+
+  abstract getKeywords(query: string): Promise<string[]>;
+
+  async retrieve(query: string): Promise<NodeWithScore[]> {
+    const keywords = await this.getKeywords(query);
+    const chunkIndicesCount: { [key: string]: number } = {};
+    const filteredKeywords = keywords.filter((keyword) =>
+      this.indexStruct.table.has(keyword),
+    );
+
+    for (const keyword of filteredKeywords) {
+      for (const nodeId of this.indexStruct.table.get(keyword) || []) {
+        chunkIndicesCount[nodeId] = (chunkIndicesCount[nodeId] ?? 0) + 1;
+      }
+    }
+
+    const sortedChunkIndices = Object.keys(chunkIndicesCount)
+      .sort((a, b) => chunkIndicesCount[b] - chunkIndicesCount[a])
+      .slice(0, this.numChunksPerQuery);
+
+    const sortedNodes = await this.docstore.getNodes(sortedChunkIndices);
+
+    return sortedNodes.map((node) => ({ node }));
+  }
+
+  getServiceContext(): ServiceContext {
+    return this.index.serviceContext;
+  }
+}
+
+// Extracts keywords using LLMs.
+export class KeywordTableLLMRetriever extends BaseKeywordTableRetriever {
+  async getKeywords(query: string): Promise<string[]> {
+    const response = await this.serviceContext.llm.complete({
+      prompt: this.queryKeywordExtractTemplate({
+        question: query,
+        maxKeywords: this.maxKeywordsPerQuery,
+      }),
+    });
+    const keywords = extractKeywordsGivenResponse(response.text, "KEYWORDS:");
+    return [...keywords];
+  }
+}
+
+// Extracts keywords using simple regex-based keyword extractor.
+export class KeywordTableSimpleRetriever extends BaseKeywordTableRetriever {
+  getKeywords(query: string): Promise<string[]> {
+    return Promise.resolve([
+      ...simpleExtractKeywords(query, this.maxKeywordsPerQuery),
+    ]);
+  }
+}
+
+// Extracts keywords using RAKE keyword extractor
+export class KeywordTableRAKERetriever extends BaseKeywordTableRetriever {
+  getKeywords(query: string): Promise<string[]> {
+    return Promise.resolve([
+      ...rakeExtractKeywords(query, this.maxKeywordsPerQuery),
+    ]);
+  }
+}
+
+const KeywordTableRetrieverMap = {
+  [KeywordTableRetrieverMode.DEFAULT]: KeywordTableLLMRetriever,
+  [KeywordTableRetrieverMode.SIMPLE]: KeywordTableSimpleRetriever,
+  [KeywordTableRetrieverMode.RAKE]: KeywordTableRAKERetriever,
+};
+
+/**
+ * The KeywordTableIndex, an index that extracts keywords from each Node and builds a mapping from each keyword to the corresponding Nodes of that keyword.
+ */
+export class KeywordTableIndex extends BaseIndex<KeywordTable> {
+  constructor(init: BaseIndexInit<KeywordTable>) {
+    super(init);
+  }
+
+  static async init(options: KeywordIndexOptions): Promise<KeywordTableIndex> {
+    const storageContext =
+      options.storageContext ?? (await storageContextFromDefaults({}));
+    const serviceContext =
+      options.serviceContext ?? serviceContextFromDefaults({});
+    const { docStore, indexStore } = storageContext;
+
+    // Setup IndexStruct from storage
+    const indexStructs = (await indexStore.getIndexStructs()) as KeywordTable[];
+    let indexStruct: KeywordTable | null;
+
+    if (options.indexStruct && indexStructs.length > 0) {
+      throw new Error(
+        "Cannot initialize index with both indexStruct and indexStore",
+      );
+    }
+
+    if (options.indexStruct) {
+      indexStruct = options.indexStruct;
+    } else if (indexStructs.length == 1) {
+      indexStruct = indexStructs[0];
+    } else if (indexStructs.length > 1 && options.indexId) {
+      indexStruct = (await indexStore.getIndexStruct(
+        options.indexId,
+      )) as KeywordTable;
+    } else {
+      indexStruct = null;
+    }
+
+    // check indexStruct type
+    if (indexStruct && indexStruct.type !== IndexStructType.KEYWORD_TABLE) {
+      throw new Error(
+        "Attempting to initialize KeywordTableIndex with non-keyword table indexStruct",
+      );
+    }
+
+    if (indexStruct) {
+      if (options.nodes) {
+        throw new Error(
+          "Cannot initialize KeywordTableIndex with both nodes and indexStruct",
+        );
+      }
+    } else {
+      if (!options.nodes) {
+        throw new Error(
+          "Cannot initialize KeywordTableIndex without nodes or indexStruct",
+        );
+      }
+      indexStruct = await KeywordTableIndex.buildIndexFromNodes(
+        options.nodes,
+        storageContext.docStore,
+        serviceContext,
+      );
+
+      await indexStore.addIndexStruct(indexStruct);
+    }
+
+    return new KeywordTableIndex({
+      storageContext,
+      serviceContext,
+      docStore,
+      indexStore,
+      indexStruct,
+    });
+  }
+
+  asRetriever(options?: any): BaseRetriever {
+    const { mode = KeywordTableRetrieverMode.DEFAULT, ...otherOptions } =
+      options ?? {};
+    const KeywordTableRetriever =
+      KeywordTableRetrieverMap[mode as KeywordTableRetrieverMode];
+    if (KeywordTableRetriever) {
+      return new KeywordTableRetriever({ index: this, ...otherOptions });
+    }
+    throw new Error(`Unknown retriever mode: ${mode}`);
+  }
+
+  asQueryEngine(options?: {
+    retriever?: BaseRetriever;
+    responseSynthesizer?: BaseSynthesizer;
+    preFilters?: unknown;
+    nodePostprocessors?: BaseNodePostprocessor[];
+  }): BaseQueryEngine {
+    const { retriever, responseSynthesizer } = options ?? {};
+    return new RetrieverQueryEngine(
+      retriever ?? this.asRetriever(),
+      responseSynthesizer,
+      options?.preFilters,
+      options?.nodePostprocessors,
+    );
+  }
+
+  static async extractKeywords(
+    text: string,
+    serviceContext: ServiceContext,
+  ): Promise<Set<string>> {
+    const response = await serviceContext.llm.complete({
+      prompt: defaultKeywordExtractPrompt({
+        context: text,
+      }),
+    });
+    return extractKeywordsGivenResponse(response.text, "KEYWORDS:");
+  }
+
+  /**
+   * High level API: split documents, get keywords, and build index.
+   * @param documents
+   * @param storageContext
+   * @param serviceContext
+   * @returns
+   */
+  static async fromDocuments(
+    documents: Document[],
+    args: {
+      storageContext?: StorageContext;
+      serviceContext?: ServiceContext;
+    } = {},
+  ): Promise<KeywordTableIndex> {
+    let { storageContext, serviceContext } = args;
+    storageContext = storageContext ?? (await storageContextFromDefaults({}));
+    serviceContext = serviceContext ?? serviceContextFromDefaults({});
+    const docStore = storageContext.docStore;
+
+    docStore.addDocuments(documents, true);
+    for (const doc of documents) {
+      docStore.setDocumentHash(doc.id_, doc.hash);
+    }
+
+    const nodes = serviceContext.nodeParser.getNodesFromDocuments(documents);
+    const index = await KeywordTableIndex.init({
+      nodes,
+      storageContext,
+      serviceContext,
+    });
+    return index;
+  }
+
+  /**
+   * Get keywords for nodes and place them into the index.
+   * @param nodes
+   * @param serviceContext
+   * @param vectorStore
+   * @returns
+   */
+  static async buildIndexFromNodes(
+    nodes: BaseNode[],
+    docStore: BaseDocumentStore,
+    serviceContext: ServiceContext,
+  ): Promise<KeywordTable> {
+    const indexStruct = new KeywordTable();
+    await docStore.addDocuments(nodes, true);
+    for (const node of nodes) {
+      const keywords = await KeywordTableIndex.extractKeywords(
+        node.getContent(MetadataMode.LLM),
+        serviceContext,
+      );
+      indexStruct.addNode([...keywords], node.id_);
+    }
+    return indexStruct;
+  }
+
+  async insertNodes(nodes: BaseNode[]) {
+    for (const node of nodes) {
+      const keywords = await KeywordTableIndex.extractKeywords(
+        node.getContent(MetadataMode.LLM),
+        this.serviceContext,
+      );
+      this.indexStruct.addNode([...keywords], node.id_);
+    }
+  }
+
+  deleteNode(nodeId: string): void {
+    const keywordsToDelete: Set<string> = new Set();
+    for (const [keyword, existingNodeIds] of Object.entries(
+      this.indexStruct.table,
+    )) {
+      const index = existingNodeIds.indexOf(nodeId);
+      if (index !== -1) {
+        existingNodeIds.splice(index, 1);
+
+        // Delete keywords that have zero nodes
+        if (existingNodeIds.length === 0) {
+          keywordsToDelete.add(keyword);
+        }
+      }
+    }
+    this.indexStruct.deleteNode([...keywordsToDelete], nodeId);
+  }
+
+  async deleteNodes(nodeIds: string[], deleteFromDocStore: boolean) {
+    nodeIds.forEach((nodeId) => {
+      this.deleteNode(nodeId);
+    });
+
+    if (deleteFromDocStore) {
+      for (const nodeId of nodeIds) {
+        await this.docStore.deleteDocument(nodeId, false);
+      }
+    }
+
+    await this.storageContext.indexStore.addIndexStruct(this.indexStruct);
+  }
+
+  async deleteRefDoc(
+    refDocId: string,
+    deleteFromDocStore?: boolean,
+  ): Promise<void> {
+    const refDocInfo = await this.docStore.getRefDocInfo(refDocId);
+
+    if (!refDocInfo) {
+      return;
+    }
+
+    await this.deleteNodes(refDocInfo.nodeIds, false);
+
+    if (deleteFromDocStore) {
+      await this.docStore.deleteRefDoc(refDocId, false);
+    }
+
+    return;
+  }
+}
@@ -6,11 +6,11 @@ export function expandTokensWithSubtokens(tokens: Set<string>): Set<string> {
  const results: Set<string> = new Set();
  const regex: RegExp = /\w+/g;

-  for (let token of tokens) {
+  for (const token of tokens) {
    results.add(token);
    const subTokens: RegExpMatchArray | null = token.match(regex);
    if (subTokens && subTokens.length > 1) {
-      for (let w of subTokens) {
+      for (const w of subTokens) {
        results.add(w);
      }
    }
@@ -31,7 +31,7 @@ export function extractKeywordsGivenResponse(
  }

  const keywords: string[] = response.split(",");
-  for (let k of keywords) {
+  for (const k of keywords) {
    let rk: string = k;
    if (lowercase) {
      rk = rk.toLowerCase();
@@ -47,13 +47,13 @@ export function simpleExtractKeywords(
  maxKeywords?: number,
 ): Set<string> {
  const regex: RegExp = /\w+/g;
-  let tokens: string[] = [...textChunk.matchAll(regex)].map((token) =>
+  const tokens: string[] = [...textChunk.matchAll(regex)].map((token) =>
    token[0].toLowerCase().trim(),
  );

  // Creating a frequency map
  const valueCounts: { [key: string]: number } = {};
-  for (let token of tokens) {
+  for (const token of tokens) {
    valueCounts[token] = (valueCounts[token] || 0) + 1;
  }

@@ -1,268 +0,0 @@
-import _ from "lodash";
-import { BaseNode, Document } from "../../Node";
-import { BaseRetriever } from "../../Retriever";
-import {
-  ServiceContext,
-  serviceContextFromDefaults,
-} from "../../ServiceContext";
-import { RetrieverQueryEngine } from "../../engines/query";
-import { BaseNodePostprocessor } from "../../postprocessors";
-import {
-  BaseDocumentStore,
-  RefDocInfo,
-  StorageContext,
-  storageContextFromDefaults,
-} from "../../storage";
-import {
-  BaseSynthesizer,
-  CompactAndRefine,
-  ResponseSynthesizer,
-} from "../../synthesizers";
-import { BaseQueryEngine } from "../../types";
-import {
-  BaseIndex,
-  BaseIndexInit,
-  IndexList,
-  IndexStructType,
-} from "../BaseIndex";
-import {
-  SummaryIndexLLMRetriever,
-  SummaryIndexRetriever,
-} from "./SummaryIndexRetriever";
-
-export enum SummaryRetrieverMode {
-  DEFAULT = "default",
-  // EMBEDDING = "embedding",
-  LLM = "llm",
-}
-
-export interface SummaryIndexOptions {
-  nodes?: BaseNode[];
-  indexStruct?: IndexList;
-  indexId?: string;
-  serviceContext?: ServiceContext;
-  storageContext?: StorageContext;
-}
-
-/**
- * A SummaryIndex keeps nodes in a sequential order for use with summarization.
- */
-export class SummaryIndex extends BaseIndex<IndexList> {
-  constructor(init: BaseIndexInit<IndexList>) {
-    super(init);
-  }
-
-  static async init(options: SummaryIndexOptions): Promise<SummaryIndex> {
-    const storageContext =
-      options.storageContext ?? (await storageContextFromDefaults({}));
-    const serviceContext =
-      options.serviceContext ?? serviceContextFromDefaults({});
-    const { docStore, indexStore } = storageContext;
-
-    // Setup IndexStruct from storage
-    let indexStructs = (await indexStore.getIndexStructs()) as IndexList[];
-    let indexStruct: IndexList | null;
-
-    if (options.indexStruct && indexStructs.length > 0) {
-      throw new Error(
-        "Cannot initialize index with both indexStruct and indexStore",
-      );
-    }
-
-    if (options.indexStruct) {
-      indexStruct = options.indexStruct;
-    } else if (indexStructs.length == 1) {
-      indexStruct = indexStructs[0];
-    } else if (indexStructs.length > 1 && options.indexId) {
-      indexStruct = (await indexStore.getIndexStruct(
-        options.indexId,
-      )) as IndexList;
-    } else {
-      indexStruct = null;
-    }
-
-    // check indexStruct type
-    if (indexStruct && indexStruct.type !== IndexStructType.LIST) {
-      throw new Error(
-        "Attempting to initialize SummaryIndex with non-list indexStruct",
-      );
-    }
-
-    if (indexStruct) {
-      if (options.nodes) {
-        throw new Error(
-          "Cannot initialize SummaryIndex with both nodes and indexStruct",
-        );
-      }
-    } else {
-      if (!options.nodes) {
-        throw new Error(
-          "Cannot initialize SummaryIndex without nodes or indexStruct",
-        );
-      }
-      indexStruct = await SummaryIndex.buildIndexFromNodes(
-        options.nodes,
-        storageContext.docStore,
-      );
-
-      await indexStore.addIndexStruct(indexStruct);
-    }
-
-    return new SummaryIndex({
-      storageContext,
-      serviceContext,
-      docStore,
-      indexStore,
-      indexStruct,
-    });
-  }
-
-  static async fromDocuments(
-    documents: Document[],
-    args: {
-      storageContext?: StorageContext;
-      serviceContext?: ServiceContext;
-    } = {},
-  ): Promise<SummaryIndex> {
-    let { storageContext, serviceContext } = args;
-    storageContext = storageContext ?? (await storageContextFromDefaults({}));
-    serviceContext = serviceContext ?? serviceContextFromDefaults({});
-    const docStore = storageContext.docStore;
-
-    docStore.addDocuments(documents, true);
-    for (const doc of documents) {
-      docStore.setDocumentHash(doc.id_, doc.hash);
-    }
-
-    const nodes = serviceContext.nodeParser.getNodesFromDocuments(documents);
-    const index = await SummaryIndex.init({
-      nodes,
-      storageContext,
-      serviceContext,
-    });
-    return index;
-  }
-
-  asRetriever(options?: { mode: SummaryRetrieverMode }): BaseRetriever {
-    const { mode = SummaryRetrieverMode.DEFAULT } = options ?? {};
-
-    switch (mode) {
-      case SummaryRetrieverMode.DEFAULT:
-        return new SummaryIndexRetriever(this);
-      case SummaryRetrieverMode.LLM:
-        return new SummaryIndexLLMRetriever(this);
-      default:
-        throw new Error(`Unknown retriever mode: ${mode}`);
-    }
-  }
-
-  asQueryEngine(options?: {
-    retriever?: BaseRetriever;
-    responseSynthesizer?: BaseSynthesizer;
-    preFilters?: unknown;
-    nodePostprocessors?: BaseNodePostprocessor[];
-  }): BaseQueryEngine {
-    let { retriever, responseSynthesizer } = options ?? {};
-
-    if (!retriever) {
-      retriever = this.asRetriever();
-    }
-
-    if (!responseSynthesizer) {
-      let responseBuilder = new CompactAndRefine(this.serviceContext);
-      responseSynthesizer = new ResponseSynthesizer({
-        serviceContext: this.serviceContext,
-        responseBuilder,
-      });
-    }
-
-    return new RetrieverQueryEngine(
-      retriever,
-      responseSynthesizer,
-      options?.preFilters,
-      options?.nodePostprocessors,
-    );
-  }
-
-  static async buildIndexFromNodes(
-    nodes: BaseNode[],
-    docStore: BaseDocumentStore,
-    indexStruct?: IndexList,
-  ): Promise<IndexList> {
-    indexStruct = indexStruct || new IndexList();
-
-    await docStore.addDocuments(nodes, true);
-    for (const node of nodes) {
-      indexStruct.addNode(node);
-    }
-
-    return indexStruct;
-  }
-
-  async insertNodes(nodes: BaseNode[]): Promise<void> {
-    for (const node of nodes) {
-      this.indexStruct.addNode(node);
-    }
-  }
-
-  async deleteRefDoc(
-    refDocId: string,
-    deleteFromDocStore?: boolean,
-  ): Promise<void> {
-    const refDocInfo = await this.docStore.getRefDocInfo(refDocId);
-
-    if (!refDocInfo) {
-      return;
-    }
-
-    await this.deleteNodes(refDocInfo.nodeIds, false);
-
-    if (deleteFromDocStore) {
-      await this.docStore.deleteRefDoc(refDocId, false);
-    }
-
-    return;
-  }
-
-  async deleteNodes(nodeIds: string[], deleteFromDocStore: boolean) {
-    this.indexStruct.nodes = this.indexStruct.nodes.filter(
-      (existingNodeId: string) => !nodeIds.includes(existingNodeId),
-    );
-
-    if (deleteFromDocStore) {
-      for (const nodeId of nodeIds) {
-        await this.docStore.deleteDocument(nodeId, false);
-      }
-    }
-
-    await this.storageContext.indexStore.addIndexStruct(this.indexStruct);
-  }
-
-  async getRefDocInfo(): Promise<Record<string, RefDocInfo>> {
-    const nodeDocIds = this.indexStruct.nodes;
-    const nodes = await this.docStore.getNodes(nodeDocIds);
-
-    const refDocInfoMap: Record<string, RefDocInfo> = {};
-
-    for (const node of nodes) {
-      const refNode = node.sourceNode;
-      if (_.isNil(refNode)) {
-        continue;
-      }
-
-      const refDocInfo = await this.docStore.getRefDocInfo(refNode.nodeId);
-
-      if (_.isNil(refDocInfo)) {
-        continue;
-      }
-
-      refDocInfoMap[refNode.nodeId] = refDocInfo;
-    }
-
-    return refDocInfoMap;
-  }
-}
-
-// Legacy
-export type ListIndex = SummaryIndex;
-export type ListRetrieverMode = SummaryRetrieverMode;
@@ -1,137 +0,0 @@
-import _ from "lodash";
-import { globalsHelper } from "../../GlobalsHelper";
-import { NodeWithScore } from "../../Node";
-import { ChoiceSelectPrompt, defaultChoiceSelectPrompt } from "../../Prompt";
-import { BaseRetriever } from "../../Retriever";
-import { ServiceContext } from "../../ServiceContext";
-import { Event } from "../../callbacks/CallbackManager";
-import { SummaryIndex } from "./SummaryIndex";
-import {
-  ChoiceSelectParserFunction,
-  NodeFormatterFunction,
-  defaultFormatNodeBatchFn,
-  defaultParseChoiceSelectAnswerFn,
-} from "./utils";
-
-/**
- * Simple retriever for SummaryIndex that returns all nodes
- */
-export class SummaryIndexRetriever implements BaseRetriever {
-  index: SummaryIndex;
-
-  constructor(index: SummaryIndex) {
-    this.index = index;
-  }
-
-  async retrieve(query: string, parentEvent?: Event): Promise<NodeWithScore[]> {
-    const nodeIds = this.index.indexStruct.nodes;
-    const nodes = await this.index.docStore.getNodes(nodeIds);
-    const result = nodes.map((node) => ({
-      node: node,
-      score: 1,
-    }));
-
-    if (this.index.serviceContext.callbackManager.onRetrieve) {
-      this.index.serviceContext.callbackManager.onRetrieve({
-        query,
-        nodes: result,
-        event: globalsHelper.createEvent({
-          parentEvent,
-          type: "retrieve",
-        }),
-      });
-    }
-
-    return result;
-  }
-
-  getServiceContext(): ServiceContext {
-    return this.index.serviceContext;
-  }
-}
-
-/**
- * LLM retriever for SummaryIndex which lets you select the most relevant chunks.
- */
-export class SummaryIndexLLMRetriever implements BaseRetriever {
-  index: SummaryIndex;
-  choiceSelectPrompt: ChoiceSelectPrompt;
-  choiceBatchSize: number;
-  formatNodeBatchFn: NodeFormatterFunction;
-  parseChoiceSelectAnswerFn: ChoiceSelectParserFunction;
-  serviceContext: ServiceContext;
-
-  // eslint-disable-next-line max-params
-  constructor(
-    index: SummaryIndex,
-    choiceSelectPrompt?: ChoiceSelectPrompt,
-    choiceBatchSize: number = 10,
-    formatNodeBatchFn?: NodeFormatterFunction,
-    parseChoiceSelectAnswerFn?: ChoiceSelectParserFunction,
-    serviceContext?: ServiceContext,
-  ) {
-    this.index = index;
-    this.choiceSelectPrompt = choiceSelectPrompt || defaultChoiceSelectPrompt;
-    this.choiceBatchSize = choiceBatchSize;
-    this.formatNodeBatchFn = formatNodeBatchFn || defaultFormatNodeBatchFn;
-    this.parseChoiceSelectAnswerFn =
-      parseChoiceSelectAnswerFn || defaultParseChoiceSelectAnswerFn;
-    this.serviceContext = serviceContext || index.serviceContext;
-  }
-
-  async retrieve(query: string, parentEvent?: Event): Promise<NodeWithScore[]> {
-    const nodeIds = this.index.indexStruct.nodes;
-    const results: NodeWithScore[] = [];
-
-    for (let idx = 0; idx < nodeIds.length; idx += this.choiceBatchSize) {
-      const nodeIdsBatch = nodeIds.slice(idx, idx + this.choiceBatchSize);
-      const nodesBatch = await this.index.docStore.getNodes(nodeIdsBatch);
-
-      const fmtBatchStr = this.formatNodeBatchFn(nodesBatch);
-      const input = { context: fmtBatchStr, query: query };
-      const rawResponse = (
-        await this.serviceContext.llm.complete({
-          prompt: this.choiceSelectPrompt(input),
-        })
-      ).text;
-
-      // parseResult is a map from doc number to relevance score
-      const parseResult = this.parseChoiceSelectAnswerFn(
-        rawResponse,
-        nodesBatch.length,
-      );
-      const choiceNodeIds = nodeIdsBatch.filter((nodeId, idx) => {
-        return `${idx}` in parseResult;
-      });
-
-      const choiceNodes = await this.index.docStore.getNodes(choiceNodeIds);
-      const nodeWithScores = choiceNodes.map((node, i) => ({
-        node: node,
-        score: _.get(parseResult, `${i + 1}`, 1),
-      }));
-
-      results.push(...nodeWithScores);
-    }
-
-    if (this.serviceContext.callbackManager.onRetrieve) {
-      this.serviceContext.callbackManager.onRetrieve({
-        query,
-        nodes: results,
-        event: globalsHelper.createEvent({
-          parentEvent,
-          type: "retrieve",
-        }),
-      });
-    }
-
-    return results;
-  }
-
-  getServiceContext(): ServiceContext {
-    return this.serviceContext;
-  }
-}
-
-// Legacy
-export type ListIndexRetriever = SummaryIndexRetriever;
-export type ListIndexLLMRetriever = SummaryIndexLLMRetriever;
@@ -1,10 +1,392 @@
-export { SummaryIndex, SummaryRetrieverMode } from "./SummaryIndex";
-export type { ListIndex, ListRetrieverMode } from "./SummaryIndex";
-export {
-  SummaryIndexLLMRetriever,
-  SummaryIndexRetriever,
-} from "./SummaryIndexRetriever";
-export type {
-  ListIndexLLMRetriever,
-  ListIndexRetriever,
-} from "./SummaryIndexRetriever";
+import _ from "lodash";
+import { globalsHelper } from "../../GlobalsHelper.js";
+import { BaseNode, Document, NodeWithScore } from "../../Node.js";
+import { ChoiceSelectPrompt, defaultChoiceSelectPrompt } from "../../Prompt.js";
+import { BaseRetriever } from "../../Retriever.js";
+import {
+  ServiceContext,
+  serviceContextFromDefaults,
+} from "../../ServiceContext.js";
+import { Event } from "../../callbacks/CallbackManager.js";
+import { RetrieverQueryEngine } from "../../engines/query/index.js";
+import { BaseNodePostprocessor } from "../../postprocessors/index.js";
+import {
+  BaseDocumentStore,
+  RefDocInfo,
+  StorageContext,
+  storageContextFromDefaults,
+} from "../../storage/index.js";
+import {
+  BaseSynthesizer,
+  CompactAndRefine,
+  ResponseSynthesizer,
+} from "../../synthesizers/index.js";
+import { BaseQueryEngine } from "../../types.js";
+import { BaseIndex, BaseIndexInit } from "../BaseIndex.js";
+import { IndexList, IndexStructType } from "../json-to-index-struct.js";
+import {
+  ChoiceSelectParserFunction,
+  NodeFormatterFunction,
+  defaultFormatNodeBatchFn,
+  defaultParseChoiceSelectAnswerFn,
+} from "./utils.js";
+
+export enum SummaryRetrieverMode {
+  DEFAULT = "default",
+  // EMBEDDING = "embedding",
+  LLM = "llm",
+}
+
+export interface SummaryIndexOptions {
+  nodes?: BaseNode[];
+  indexStruct?: IndexList;
+  indexId?: string;
+  serviceContext?: ServiceContext;
+  storageContext?: StorageContext;
+}
+
+/**
+ * A SummaryIndex keeps nodes in a sequential order for use with summarization.
+ */
+export class SummaryIndex extends BaseIndex<IndexList> {
+  constructor(init: BaseIndexInit<IndexList>) {
+    super(init);
+  }
+
+  static async init(options: SummaryIndexOptions): Promise<SummaryIndex> {
+    const storageContext =
+      options.storageContext ?? (await storageContextFromDefaults({}));
+    const serviceContext =
+      options.serviceContext ?? serviceContextFromDefaults({});
+    const { docStore, indexStore } = storageContext;
+
+    // Setup IndexStruct from storage
+    const indexStructs = (await indexStore.getIndexStructs()) as IndexList[];
+    let indexStruct: IndexList | null;
+
+    if (options.indexStruct && indexStructs.length > 0) {
+      throw new Error(
+        "Cannot initialize index with both indexStruct and indexStore",
+      );
+    }
+
+    if (options.indexStruct) {
+      indexStruct = options.indexStruct;
+    } else if (indexStructs.length == 1) {
+      indexStruct = indexStructs[0];
+    } else if (indexStructs.length > 1 && options.indexId) {
+      indexStruct = (await indexStore.getIndexStruct(
+        options.indexId,
+      )) as IndexList;
+    } else {
+      indexStruct = null;
+    }
+
+    // check indexStruct type
+    if (indexStruct && indexStruct.type !== IndexStructType.LIST) {
+      throw new Error(
+        "Attempting to initialize SummaryIndex with non-list indexStruct",
+      );
+    }
+
+    if (indexStruct) {
+      if (options.nodes) {
+        throw new Error(
+          "Cannot initialize SummaryIndex with both nodes and indexStruct",
+        );
+      }
+    } else {
+      if (!options.nodes) {
+        throw new Error(
+          "Cannot initialize SummaryIndex without nodes or indexStruct",
+        );
+      }
+      indexStruct = await SummaryIndex.buildIndexFromNodes(
+        options.nodes,
+        storageContext.docStore,
+      );
+
+      await indexStore.addIndexStruct(indexStruct);
+    }
+
+    return new SummaryIndex({
+      storageContext,
+      serviceContext,
+      docStore,
+      indexStore,
+      indexStruct,
+    });
+  }
+
+  static async fromDocuments(
+    documents: Document[],
+    args: {
+      storageContext?: StorageContext;
+      serviceContext?: ServiceContext;
+    } = {},
+  ): Promise<SummaryIndex> {
+    let { storageContext, serviceContext } = args;
+    storageContext = storageContext ?? (await storageContextFromDefaults({}));
+    serviceContext = serviceContext ?? serviceContextFromDefaults({});
+    const docStore = storageContext.docStore;
+
+    docStore.addDocuments(documents, true);
+    for (const doc of documents) {
+      docStore.setDocumentHash(doc.id_, doc.hash);
+    }
+
+    const nodes = serviceContext.nodeParser.getNodesFromDocuments(documents);
+    const index = await SummaryIndex.init({
+      nodes,
+      storageContext,
+      serviceContext,
+    });
+    return index;
+  }
+
+  asRetriever(options?: { mode: SummaryRetrieverMode }): BaseRetriever {
+    const { mode = SummaryRetrieverMode.DEFAULT } = options ?? {};
+
+    switch (mode) {
+      case SummaryRetrieverMode.DEFAULT:
+        return new SummaryIndexRetriever(this);
+      case SummaryRetrieverMode.LLM:
+        return new SummaryIndexLLMRetriever(this);
+      default:
+        throw new Error(`Unknown retriever mode: ${mode}`);
+    }
+  }
+
+  asQueryEngine(options?: {
+    retriever?: BaseRetriever;
+    responseSynthesizer?: BaseSynthesizer;
+    preFilters?: unknown;
+    nodePostprocessors?: BaseNodePostprocessor[];
+  }): BaseQueryEngine {
+    let { retriever, responseSynthesizer } = options ?? {};
+
+    if (!retriever) {
+      retriever = this.asRetriever();
+    }
+
+    if (!responseSynthesizer) {
+      const responseBuilder = new CompactAndRefine(this.serviceContext);
+      responseSynthesizer = new ResponseSynthesizer({
+        serviceContext: this.serviceContext,
+        responseBuilder,
+      });
+    }
+
+    return new RetrieverQueryEngine(
+      retriever,
+      responseSynthesizer,
+      options?.preFilters,
+      options?.nodePostprocessors,
+    );
+  }
+
+  static async buildIndexFromNodes(
+    nodes: BaseNode[],
+    docStore: BaseDocumentStore,
+    indexStruct?: IndexList,
+  ): Promise<IndexList> {
+    indexStruct = indexStruct || new IndexList();
+
+    await docStore.addDocuments(nodes, true);
+    for (const node of nodes) {
+      indexStruct.addNode(node);
+    }
+
+    return indexStruct;
+  }
+
+  async insertNodes(nodes: BaseNode[]): Promise<void> {
+    for (const node of nodes) {
+      this.indexStruct.addNode(node);
+    }
+  }
+
+  async deleteRefDoc(
+    refDocId: string,
+    deleteFromDocStore?: boolean,
+  ): Promise<void> {
+    const refDocInfo = await this.docStore.getRefDocInfo(refDocId);
+
+    if (!refDocInfo) {
+      return;
+    }
+
+    await this.deleteNodes(refDocInfo.nodeIds, false);
+
+    if (deleteFromDocStore) {
+      await this.docStore.deleteRefDoc(refDocId, false);
+    }
+
+    return;
+  }
+
+  async deleteNodes(nodeIds: string[], deleteFromDocStore: boolean) {
+    this.indexStruct.nodes = this.indexStruct.nodes.filter(
+      (existingNodeId: string) => !nodeIds.includes(existingNodeId),
+    );
+
+    if (deleteFromDocStore) {
+      for (const nodeId of nodeIds) {
+        await this.docStore.deleteDocument(nodeId, false);
+      }
+    }
+
+    await this.storageContext.indexStore.addIndexStruct(this.indexStruct);
+  }
+
+  async getRefDocInfo(): Promise<Record<string, RefDocInfo>> {
+    const nodeDocIds = this.indexStruct.nodes;
+    const nodes = await this.docStore.getNodes(nodeDocIds);
+
+    const refDocInfoMap: Record<string, RefDocInfo> = {};
+
+    for (const node of nodes) {
+      const refNode = node.sourceNode;
+      if (_.isNil(refNode)) {
+        continue;
+      }
+
+      const refDocInfo = await this.docStore.getRefDocInfo(refNode.nodeId);
+
+      if (_.isNil(refDocInfo)) {
+        continue;
+      }
+
+      refDocInfoMap[refNode.nodeId] = refDocInfo;
+    }
+
+    return refDocInfoMap;
+  }
+}
+
+// Legacy
+export type ListIndex = SummaryIndex;
+export type ListRetrieverMode = SummaryRetrieverMode;
+
+/**
+ * Simple retriever for SummaryIndex that returns all nodes
+ */
+export class SummaryIndexRetriever implements BaseRetriever {
+  index: SummaryIndex;
+
+  constructor(index: SummaryIndex) {
+    this.index = index;
+  }
+
+  async retrieve(query: string, parentEvent?: Event): Promise<NodeWithScore[]> {
+    const nodeIds = this.index.indexStruct.nodes;
+    const nodes = await this.index.docStore.getNodes(nodeIds);
+    const result = nodes.map((node) => ({
+      node: node,
+      score: 1,
+    }));
+
+    if (this.index.serviceContext.callbackManager.onRetrieve) {
+      this.index.serviceContext.callbackManager.onRetrieve({
+        query,
+        nodes: result,
+        event: globalsHelper.createEvent({
+          parentEvent,
+          type: "retrieve",
+        }),
+      });
+    }
+
+    return result;
+  }
+
+  getServiceContext(): ServiceContext {
+    return this.index.serviceContext;
+  }
+}
+
+/**
+ * LLM retriever for SummaryIndex which lets you select the most relevant chunks.
+ */
+export class SummaryIndexLLMRetriever implements BaseRetriever {
+  index: SummaryIndex;
+  choiceSelectPrompt: ChoiceSelectPrompt;
+  choiceBatchSize: number;
+  formatNodeBatchFn: NodeFormatterFunction;
+  parseChoiceSelectAnswerFn: ChoiceSelectParserFunction;
+  serviceContext: ServiceContext;
+
+  // eslint-disable-next-line max-params
+  constructor(
+    index: SummaryIndex,
+    choiceSelectPrompt?: ChoiceSelectPrompt,
+    choiceBatchSize: number = 10,
+    formatNodeBatchFn?: NodeFormatterFunction,
+    parseChoiceSelectAnswerFn?: ChoiceSelectParserFunction,
+    serviceContext?: ServiceContext,
+  ) {
+    this.index = index;
+    this.choiceSelectPrompt = choiceSelectPrompt || defaultChoiceSelectPrompt;
+    this.choiceBatchSize = choiceBatchSize;
+    this.formatNodeBatchFn = formatNodeBatchFn || defaultFormatNodeBatchFn;
+    this.parseChoiceSelectAnswerFn =
+      parseChoiceSelectAnswerFn || defaultParseChoiceSelectAnswerFn;
+    this.serviceContext = serviceContext || index.serviceContext;
+  }
+
+  async retrieve(query: string, parentEvent?: Event): Promise<NodeWithScore[]> {
+    const nodeIds = this.index.indexStruct.nodes;
+    const results: NodeWithScore[] = [];
+
+    for (let idx = 0; idx < nodeIds.length; idx += this.choiceBatchSize) {
+      const nodeIdsBatch = nodeIds.slice(idx, idx + this.choiceBatchSize);
+      const nodesBatch = await this.index.docStore.getNodes(nodeIdsBatch);
+
+      const fmtBatchStr = this.formatNodeBatchFn(nodesBatch);
+      const input = { context: fmtBatchStr, query: query };
+      const rawResponse = (
+        await this.serviceContext.llm.complete({
+          prompt: this.choiceSelectPrompt(input),
+        })
+      ).text;
+
+      // parseResult is a map from doc number to relevance score
+      const parseResult = this.parseChoiceSelectAnswerFn(
+        rawResponse,
+        nodesBatch.length,
+      );
+      const choiceNodeIds = nodeIdsBatch.filter((nodeId, idx) => {
+        return `${idx}` in parseResult;
+      });
+
+      const choiceNodes = await this.index.docStore.getNodes(choiceNodeIds);
+      const nodeWithScores = choiceNodes.map((node, i) => ({
+        node: node,
+        score: _.get(parseResult, `${i + 1}`, 1),
+      }));
+
+      results.push(...nodeWithScores);
+    }
+
+    if (this.serviceContext.callbackManager.onRetrieve) {
+      this.serviceContext.callbackManager.onRetrieve({
+        query,
+        nodes: results,
+        event: globalsHelper.createEvent({
+          parentEvent,
+          type: "retrieve",
+        }),
+      });
+    }
+
+    return results;
+  }
+
+  getServiceContext(): ServiceContext {
+    return this.serviceContext;
+  }
+}
+
+// Legacy
+export type ListIndexRetriever = SummaryIndexRetriever;
+export type ListIndexLLMRetriever = SummaryIndexLLMRetriever;
@@ -1,5 +1,5 @@
 import _ from "lodash";
-import { BaseNode, MetadataMode } from "../../Node";
+import { BaseNode, MetadataMode } from "../../Node.js";

 export type NodeFormatterFunction = (summaryNodes: BaseNode[]) => string;
 export const defaultFormatNodeBatchFn: NodeFormatterFunction = (
@@ -32,7 +32,7 @@ export const defaultParseChoiceSelectAnswerFn: ChoiceSelectParserFunction = (
  const lineTokens: string[][] = answer
    .split("\n")
    .map((line: string) => {
-      let lineTokens = line.split(",");
+      const lineTokens = line.split(",");
      if (lineTokens.length !== 2) {
        if (raiseErr) {
          throw new Error(
@@ -50,8 +50,8 @@ export const defaultParseChoiceSelectAnswerFn: ChoiceSelectParserFunction = (
  return lineTokens.reduce(
    (parseResult: ChoiceSelectParseResult, lineToken: string[]) => {
      try {
-        let docNum = parseInt(lineToken[0].split(":")[1].trim());
-        let answerRelevance = parseFloat(lineToken[1].split(":")[1].trim());
+        const docNum = parseInt(lineToken[0].split(":")[1].trim());
+        const answerRelevance = parseFloat(lineToken[1].split(":")[1].trim());
        if (docNum < 1 || docNum > numChoices) {
          if (raiseErr) {
            throw new Error(
@@ -1,149 +0,0 @@
-import { globalsHelper } from "../../GlobalsHelper";
-import { ImageNode, Metadata, NodeWithScore } from "../../Node";
-import { BaseRetriever } from "../../Retriever";
-import { ServiceContext } from "../../ServiceContext";
-import { Event } from "../../callbacks/CallbackManager";
-import { DEFAULT_SIMILARITY_TOP_K } from "../../constants";
-import { BaseEmbedding } from "../../embeddings";
-import {
-  MetadataFilters,
-  VectorStoreQuery,
-  VectorStoreQueryMode,
-  VectorStoreQueryResult,
-} from "../../storage/vectorStore/types";
-import { VectorStoreIndex } from "./VectorStoreIndex";
-
-/**
- * VectorIndexRetriever retrieves nodes from a VectorIndex.
- */
-
-export type VectorIndexRetrieverOptions = {
-  index: VectorStoreIndex;
-  similarityTopK?: number;
-  imageSimilarityTopK?: number;
-};
-
-export class VectorIndexRetriever implements BaseRetriever {
-  index: VectorStoreIndex;
-  similarityTopK: number;
-  imageSimilarityTopK: number;
-  private serviceContext: ServiceContext;
-
-  constructor({
-    index,
-    similarityTopK,
-    imageSimilarityTopK,
-  }: VectorIndexRetrieverOptions) {
-    this.index = index;
-    this.serviceContext = this.index.serviceContext;
-    this.similarityTopK = similarityTopK ?? DEFAULT_SIMILARITY_TOP_K;
-    this.imageSimilarityTopK = imageSimilarityTopK ?? DEFAULT_SIMILARITY_TOP_K;
-  }
-
-  async retrieve(
-    query: string,
-    parentEvent?: Event,
-    preFilters?: MetadataFilters,
-  ): Promise<NodeWithScore[]> {
-    let nodesWithScores = await this.textRetrieve(query, preFilters);
-    nodesWithScores = nodesWithScores.concat(
-      await this.textToImageRetrieve(query, preFilters),
-    );
-    this.sendEvent(query, nodesWithScores, parentEvent);
-    return nodesWithScores;
-  }
-
-  protected async textRetrieve(
-    query: string,
-    preFilters?: MetadataFilters,
-  ): Promise<NodeWithScore[]> {
-    const options = {};
-    const q = await this.buildVectorStoreQuery(
-      this.index.embedModel,
-      query,
-      this.similarityTopK,
-      preFilters,
-    );
-    const result = await this.index.vectorStore.query(q, options);
-    return this.buildNodeListFromQueryResult(result);
-  }
-
-  private async textToImageRetrieve(
-    query: string,
-    preFilters?: MetadataFilters,
-  ) {
-    if (!this.index.imageEmbedModel || !this.index.imageVectorStore) {
-      // no-op if image embedding and vector store are not set
-      return [];
-    }
-    const q = await this.buildVectorStoreQuery(
-      this.index.imageEmbedModel,
-      query,
-      this.imageSimilarityTopK,
-      preFilters,
-    );
-    const result = await this.index.imageVectorStore.query(q, preFilters);
-    return this.buildNodeListFromQueryResult(result);
-  }
-
-  protected sendEvent(
-    query: string,
-    nodesWithScores: NodeWithScore<Metadata>[],
-    parentEvent: Event | undefined,
-  ) {
-    if (this.serviceContext.callbackManager.onRetrieve) {
-      this.serviceContext.callbackManager.onRetrieve({
-        query,
-        nodes: nodesWithScores,
-        event: globalsHelper.createEvent({
-          parentEvent,
-          type: "retrieve",
-        }),
-      });
-    }
-  }
-
-  protected async buildVectorStoreQuery(
-    embedModel: BaseEmbedding,
-    query: string,
-    similarityTopK: number,
-    preFilters?: MetadataFilters,
-  ): Promise<VectorStoreQuery> {
-    const queryEmbedding = await embedModel.getQueryEmbedding(query);
-
-    return {
-      queryEmbedding: queryEmbedding,
-      mode: VectorStoreQueryMode.DEFAULT,
-      similarityTopK: similarityTopK,
-      filters: preFilters ?? undefined,
-    };
-  }
-
-  protected buildNodeListFromQueryResult(result: VectorStoreQueryResult) {
-    let nodesWithScores: NodeWithScore[] = [];
-    for (let i = 0; i < result.ids.length; i++) {
-      const nodeFromResult = result.nodes?.[i];
-      if (!this.index.indexStruct.nodesDict[result.ids[i]] && nodeFromResult) {
-        this.index.indexStruct.nodesDict[result.ids[i]] = nodeFromResult;
-      }
-
-      const node = this.index.indexStruct.nodesDict[result.ids[i]];
-      // XXX: Hack, if it's an image node, we reconstruct the image from the URL
-      // Alternative: Store image in doc store and retrieve it here
-      if (node instanceof ImageNode) {
-        node.image = node.getUrl();
-      }
-
-      nodesWithScores.push({
-        node: node,
-        score: result.similarities[i],
-      });
-    }
-
-    return nodesWithScores;
-  }
-
-  getServiceContext(): ServiceContext {
-    return this.serviceContext;
-  }
-}
@@ -1,398 +0,0 @@
-import {
-  BaseNode,
-  Document,
-  ImageNode,
-  MetadataMode,
-  ObjectType,
-  splitNodesByType,
-} from "../../Node";
-import { BaseRetriever } from "../../Retriever";
-import {
-  ServiceContext,
-  serviceContextFromDefaults,
-} from "../../ServiceContext";
-import {
-  BaseEmbedding,
-  ClipEmbedding,
-  MultiModalEmbedding,
-} from "../../embeddings";
-import { RetrieverQueryEngine } from "../../engines/query";
-import { runTransformations } from "../../ingestion";
-import { BaseNodePostprocessor } from "../../postprocessors";
-import {
-  BaseIndexStore,
-  MetadataFilters,
-  StorageContext,
-  VectorStore,
-  storageContextFromDefaults,
-} from "../../storage";
-import { BaseSynthesizer } from "../../synthesizers";
-import { BaseQueryEngine } from "../../types";
-import {
-  BaseIndex,
-  BaseIndexInit,
-  IndexDict,
-  IndexStructType,
-} from "../BaseIndex";
-import {
-  VectorIndexRetriever,
-  VectorIndexRetrieverOptions,
-} from "./VectorIndexRetriever";
-
-interface IndexStructOptions {
-  indexStruct?: IndexDict;
-  indexId?: string;
-}
-export interface VectorIndexOptions extends IndexStructOptions {
-  nodes?: BaseNode[];
-  serviceContext?: ServiceContext;
-  storageContext?: StorageContext;
-  imageVectorStore?: VectorStore;
-  vectorStore?: VectorStore;
-  logProgress?: boolean;
-}
-
-export interface VectorIndexConstructorProps extends BaseIndexInit<IndexDict> {
-  indexStore: BaseIndexStore;
-  imageVectorStore?: VectorStore;
-}
-
-/**
- * The VectorStoreIndex, an index that stores the nodes only according to their vector embedings.
- */
-export class VectorStoreIndex extends BaseIndex<IndexDict> {
-  vectorStore: VectorStore;
-  indexStore: BaseIndexStore;
-  embedModel: BaseEmbedding;
-  imageVectorStore?: VectorStore;
-  imageEmbedModel?: MultiModalEmbedding;
-
-  private constructor(init: VectorIndexConstructorProps) {
-    super(init);
-    this.indexStore = init.indexStore;
-    this.vectorStore = init.vectorStore ?? init.storageContext.vectorStore;
-    this.embedModel = init.serviceContext.embedModel;
-    this.imageVectorStore =
-      init.imageVectorStore ?? init.storageContext.imageVectorStore;
-    if (this.imageVectorStore) {
-      this.imageEmbedModel = new ClipEmbedding();
-    }
-  }
-
-  /**
-   * The async init function creates a new VectorStoreIndex.
-   * @param options
-   * @returns
-   */
-  public static async init(
-    options: VectorIndexOptions,
-  ): Promise<VectorStoreIndex> {
-    const storageContext =
-      options.storageContext ?? (await storageContextFromDefaults({}));
-    const serviceContext =
-      options.serviceContext ?? serviceContextFromDefaults({});
-    const indexStore = storageContext.indexStore;
-    const docStore = storageContext.docStore;
-
-    let indexStruct = await VectorStoreIndex.setupIndexStructFromStorage(
-      indexStore,
-      options,
-    );
-
-    if (!options.nodes && !indexStruct) {
-      throw new Error(
-        "Cannot initialize VectorStoreIndex without nodes or indexStruct",
-      );
-    }
-
-    indexStruct = indexStruct ?? new IndexDict();
-
-    const index = new this({
-      storageContext,
-      serviceContext,
-      docStore,
-      indexStruct,
-      indexStore,
-      vectorStore: options.vectorStore,
-      imageVectorStore: options.imageVectorStore,
-    });
-
-    if (options.nodes) {
-      // If nodes are passed in, then we need to update the index
-      await index.buildIndexFromNodes(options.nodes, {
-        logProgress: options.logProgress,
-      });
-    }
-    return index;
-  }
-
-  private static async setupIndexStructFromStorage(
-    indexStore: BaseIndexStore,
-    options: IndexStructOptions,
-  ) {
-    let indexStructs = (await indexStore.getIndexStructs()) as IndexDict[];
-    let indexStruct: IndexDict | undefined;
-
-    if (options.indexStruct && indexStructs.length > 0) {
-      throw new Error(
-        "Cannot initialize index with both indexStruct and indexStore",
-      );
-    }
-
-    if (options.indexStruct) {
-      indexStruct = options.indexStruct;
-    } else if (indexStructs.length == 1) {
-      indexStruct = indexStructs[0];
-    } else if (indexStructs.length > 1 && options.indexId) {
-      indexStruct = (await indexStore.getIndexStruct(
-        options.indexId,
-      )) as IndexDict;
-    }
-    // Check indexStruct type
-    if (indexStruct && indexStruct.type !== IndexStructType.SIMPLE_DICT) {
-      throw new Error(
-        "Attempting to initialize VectorStoreIndex with non-vector indexStruct",
-      );
-    }
-    return indexStruct;
-  }
-
-  /**
-   * Calculates the embeddings for the given nodes.
-   *
-   * @param nodes - An array of BaseNode objects representing the nodes for which embeddings are to be calculated.
-   * @param {Object} [options] - An optional object containing additional parameters.
-   *   @param {boolean} [options.logProgress] - A boolean indicating whether to log progress to the console (useful for debugging).
-   */
-  async getNodeEmbeddingResults(
-    nodes: BaseNode[],
-    options?: { logProgress?: boolean },
-  ): Promise<BaseNode[]> {
-    const texts = nodes.map((node) => node.getContent(MetadataMode.EMBED));
-    const embeddings = await this.embedModel.getTextEmbeddingsBatch(texts, {
-      logProgress: options?.logProgress,
-    });
-    return nodes.map((node, i) => {
-      node.embedding = embeddings[i];
-      return node;
-    });
-  }
-
-  /**
-   * Get embeddings for nodes and place them into the index.
-   * @param nodes
-   * @returns
-   */
-  async buildIndexFromNodes(
-    nodes: BaseNode[],
-    options?: { logProgress?: boolean },
-  ) {
-    // Check if the index already has nodes with the same hash
-    const newNodes = nodes.filter((node) =>
-      Object.entries(this.indexStruct!.nodesDict).reduce(
-        (acc, [key, value]) => {
-          if (value.hash === node.hash) {
-            acc = false;
-          }
-          return acc;
-        },
-        true,
-      ),
-    );
-
-    await this.insertNodes(newNodes, options);
-  }
-
-  /**
-   * High level API: split documents, get embeddings, and build index.
-   * @param documents
-   * @param args
-   * @returns
-   */
-  static async fromDocuments(
-    documents: Document[],
-    args: VectorIndexOptions = {},
-  ): Promise<VectorStoreIndex> {
-    args.storageContext =
-      args.storageContext ?? (await storageContextFromDefaults({}));
-    args.serviceContext = args.serviceContext ?? serviceContextFromDefaults({});
-    const docStore = args.storageContext.docStore;
-
-    for (const doc of documents) {
-      docStore.setDocumentHash(doc.id_, doc.hash);
-    }
-
-    if (args.logProgress) {
-      console.log("Using node parser on documents...");
-    }
-    args.nodes = await runTransformations(documents, [
-      args.serviceContext.nodeParser,
-    ]);
-    if (args.logProgress) {
-      console.log("Finished parsing documents.");
-    }
-    return await this.init(args);
-  }
-
-  static async fromVectorStore(
-    vectorStore: VectorStore,
-    serviceContext: ServiceContext,
-    imageVectorStore?: VectorStore,
-  ) {
-    if (!vectorStore.storesText) {
-      throw new Error(
-        "Cannot initialize from a vector store that does not store text",
-      );
-    }
-
-    const storageContext = await storageContextFromDefaults({
-      vectorStore,
-      imageVectorStore,
-    });
-
-    const index = await this.init({
-      nodes: [],
-      storageContext,
-      serviceContext,
-    });
-
-    return index;
-  }
-
-  asRetriever(
-    options?: Omit<VectorIndexRetrieverOptions, "index">,
-  ): VectorIndexRetriever {
-    return new VectorIndexRetriever({ index: this, ...options });
-  }
-
-  asQueryEngine(options?: {
-    retriever?: BaseRetriever;
-    responseSynthesizer?: BaseSynthesizer;
-    preFilters?: MetadataFilters;
-    nodePostprocessors?: BaseNodePostprocessor[];
-  }): BaseQueryEngine & RetrieverQueryEngine {
-    const { retriever, responseSynthesizer } = options ?? {};
-    return new RetrieverQueryEngine(
-      retriever ?? this.asRetriever(),
-      responseSynthesizer,
-      options?.preFilters,
-      options?.nodePostprocessors,
-    );
-  }
-
-  protected async insertNodesToStore(
-    vectorStore: VectorStore,
-    nodes: BaseNode[],
-  ): Promise<void> {
-    const newIds = await vectorStore.add(nodes);
-
-    // NOTE: if the vector store doesn't store text,
-    // we need to add the nodes to the index struct and document store
-    // NOTE: if the vector store keeps text,
-    // we only need to add image and index nodes
-    for (let i = 0; i < nodes.length; ++i) {
-      const type = nodes[i].getType();
-      if (
-        !vectorStore.storesText ||
-        type === ObjectType.INDEX ||
-        type === ObjectType.IMAGE
-      ) {
-        const nodeWithoutEmbedding = nodes[i].clone();
-        nodeWithoutEmbedding.embedding = undefined;
-        this.indexStruct.addNode(nodeWithoutEmbedding, newIds[i]);
-        await this.docStore.addDocuments([nodeWithoutEmbedding], true);
-      }
-    }
-  }
-
-  async insertNodes(
-    nodes: BaseNode[],
-    options?: { logProgress?: boolean },
-  ): Promise<void> {
-    if (!nodes || nodes.length === 0) {
-      return;
-    }
-    const { imageNodes, textNodes } = splitNodesByType(nodes);
-    if (imageNodes.length > 0) {
-      if (!this.imageVectorStore) {
-        throw new Error("Cannot insert image nodes without image vector store");
-      }
-      const imageNodesWithEmbedding = await this.getImageNodeEmbeddingResults(
-        imageNodes,
-        options,
-      );
-      await this.insertNodesToStore(
-        this.imageVectorStore,
-        imageNodesWithEmbedding,
-      );
-    }
-    const embeddingResults = await this.getNodeEmbeddingResults(
-      textNodes,
-      options,
-    );
-    await this.insertNodesToStore(this.vectorStore, embeddingResults);
-    await this.indexStore.addIndexStruct(this.indexStruct);
-  }
-
-  async deleteRefDoc(
-    refDocId: string,
-    deleteFromDocStore: boolean = true,
-  ): Promise<void> {
-    await this.deleteRefDocFromStore(this.vectorStore, refDocId);
-    if (this.imageVectorStore) {
-      await this.deleteRefDocFromStore(this.imageVectorStore, refDocId);
-    }
-
-    if (deleteFromDocStore) {
-      await this.docStore.deleteDocument(refDocId, false);
-    }
-  }
-
-  protected async deleteRefDocFromStore(
-    vectorStore: VectorStore,
-    refDocId: string,
-  ): Promise<void> {
-    vectorStore.delete(refDocId);
-
-    if (!vectorStore.storesText) {
-      const refDocInfo = await this.docStore.getRefDocInfo(refDocId);
-
-      if (refDocInfo) {
-        for (const nodeId of refDocInfo.nodeIds) {
-          this.indexStruct.delete(nodeId);
-          vectorStore.delete(nodeId);
-        }
-      }
-      await this.indexStore.addIndexStruct(this.indexStruct);
-    }
-  }
-
-  /**
-   * Calculates the embeddings for the given image nodes.
-   *
-   * @param nodes - An array of ImageNode objects representing the nodes for which embeddings are to be calculated.
-   * @param {Object} [options] - An optional object containing additional parameters.
-   *   @param {boolean} [options.logProgress] - A boolean indicating whether to log progress to the console (useful for debugging).
-   */
-  async getImageNodeEmbeddingResults(
-    nodes: ImageNode[],
-    options?: { logProgress?: boolean },
-  ): Promise<ImageNode[]> {
-    if (!this.imageEmbedModel) {
-      return [];
-    }
-
-    const nodesWithEmbeddings: ImageNode[] = [];
-
-    for (let i = 0; i < nodes.length; ++i) {
-      const node = nodes[i];
-      if (options?.logProgress) {
-        console.log(`Getting embedding for node ${i + 1}/${nodes.length}`);
-      }
-      node.embedding = await this.imageEmbedModel.getImageEmbedding(node.image);
-      nodesWithEmbeddings.push(node);
-    }
-
-    return nodesWithEmbeddings;
-  }
-}
@@ -1,2 +1,533 @@
-export { VectorIndexRetriever } from "./VectorIndexRetriever";
-export { VectorStoreIndex } from "./VectorStoreIndex";
+import { globalsHelper } from "../../GlobalsHelper.js";
+import {
+  BaseNode,
+  Document,
+  ImageNode,
+  Metadata,
+  MetadataMode,
+  NodeWithScore,
+  ObjectType,
+  splitNodesByType,
+} from "../../Node.js";
+import { BaseRetriever } from "../../Retriever.js";
+import {
+  ServiceContext,
+  serviceContextFromDefaults,
+} from "../../ServiceContext.js";
+import { Event } from "../../callbacks/CallbackManager.js";
+import { DEFAULT_SIMILARITY_TOP_K } from "../../constants.js";
+import {
+  BaseEmbedding,
+  ClipEmbedding,
+  MultiModalEmbedding,
+} from "../../embeddings/index.js";
+import { RetrieverQueryEngine } from "../../engines/query/RetrieverQueryEngine.js";
+import { runTransformations } from "../../ingestion/index.js";
+import { BaseNodePostprocessor } from "../../postprocessors/types.js";
+import {
+  BaseIndexStore,
+  MetadataFilters,
+  StorageContext,
+  VectorStore,
+  VectorStoreQuery,
+  VectorStoreQueryMode,
+  VectorStoreQueryResult,
+  storageContextFromDefaults,
+} from "../../storage/index.js";
+import { BaseSynthesizer } from "../../synthesizers/types.js";
+import { BaseQueryEngine } from "../../types.js";
+import { BaseIndex, BaseIndexInit } from "../BaseIndex.js";
+import { IndexDict, IndexStructType } from "../json-to-index-struct.js";
+
+interface IndexStructOptions {
+  indexStruct?: IndexDict;
+  indexId?: string;
+}
+export interface VectorIndexOptions extends IndexStructOptions {
+  nodes?: BaseNode[];
+  serviceContext?: ServiceContext;
+  storageContext?: StorageContext;
+  imageVectorStore?: VectorStore;
+  vectorStore?: VectorStore;
+  logProgress?: boolean;
+}
+
+export interface VectorIndexConstructorProps extends BaseIndexInit<IndexDict> {
+  indexStore: BaseIndexStore;
+  imageVectorStore?: VectorStore;
+}
+
+/**
+ * The VectorStoreIndex, an index that stores the nodes only according to their vector embedings.
+ */
+export class VectorStoreIndex extends BaseIndex<IndexDict> {
+  vectorStore: VectorStore;
+  indexStore: BaseIndexStore;
+  embedModel: BaseEmbedding;
+  imageVectorStore?: VectorStore;
+  imageEmbedModel?: MultiModalEmbedding;
+
+  private constructor(init: VectorIndexConstructorProps) {
+    super(init);
+    this.indexStore = init.indexStore;
+    this.vectorStore = init.vectorStore ?? init.storageContext.vectorStore;
+    this.embedModel = init.serviceContext.embedModel;
+    this.imageVectorStore =
+      init.imageVectorStore ?? init.storageContext.imageVectorStore;
+    if (this.imageVectorStore) {
+      this.imageEmbedModel = new ClipEmbedding();
+    }
+  }
+
+  /**
+   * The async init function creates a new VectorStoreIndex.
+   * @param options
+   * @returns
+   */
+  public static async init(
+    options: VectorIndexOptions,
+  ): Promise<VectorStoreIndex> {
+    const storageContext =
+      options.storageContext ?? (await storageContextFromDefaults({}));
+    const serviceContext =
+      options.serviceContext ?? serviceContextFromDefaults({});
+    const indexStore = storageContext.indexStore;
+    const docStore = storageContext.docStore;
+
+    let indexStruct = await VectorStoreIndex.setupIndexStructFromStorage(
+      indexStore,
+      options,
+    );
+
+    if (!options.nodes && !indexStruct) {
+      throw new Error(
+        "Cannot initialize VectorStoreIndex without nodes or indexStruct",
+      );
+    }
+
+    indexStruct = indexStruct ?? new IndexDict();
+
+    const index = new this({
+      storageContext,
+      serviceContext,
+      docStore,
+      indexStruct,
+      indexStore,
+      vectorStore: options.vectorStore,
+      imageVectorStore: options.imageVectorStore,
+    });
+
+    if (options.nodes) {
+      // If nodes are passed in, then we need to update the index
+      await index.buildIndexFromNodes(options.nodes, {
+        logProgress: options.logProgress,
+      });
+    }
+    return index;
+  }
+
+  private static async setupIndexStructFromStorage(
+    indexStore: BaseIndexStore,
+    options: IndexStructOptions,
+  ) {
+    const indexStructs = (await indexStore.getIndexStructs()) as IndexDict[];
+    let indexStruct: IndexDict | undefined;
+
+    if (options.indexStruct && indexStructs.length > 0) {
+      throw new Error(
+        "Cannot initialize index with both indexStruct and indexStore",
+      );
+    }
+
+    if (options.indexStruct) {
+      indexStruct = options.indexStruct;
+    } else if (indexStructs.length == 1) {
+      indexStruct = indexStructs[0];
+    } else if (indexStructs.length > 1 && options.indexId) {
+      indexStruct = (await indexStore.getIndexStruct(
+        options.indexId,
+      )) as IndexDict;
+    }
+    // Check indexStruct type
+    if (indexStruct && indexStruct.type !== IndexStructType.SIMPLE_DICT) {
+      throw new Error(
+        "Attempting to initialize VectorStoreIndex with non-vector indexStruct",
+      );
+    }
+    return indexStruct;
+  }
+
+  /**
+   * Calculates the embeddings for the given nodes.
+   *
+   * @param nodes - An array of BaseNode objects representing the nodes for which embeddings are to be calculated.
+   * @param {Object} [options] - An optional object containing additional parameters.
+   *   @param {boolean} [options.logProgress] - A boolean indicating whether to log progress to the console (useful for debugging).
+   */
+  async getNodeEmbeddingResults(
+    nodes: BaseNode[],
+    options?: { logProgress?: boolean },
+  ): Promise<BaseNode[]> {
+    const texts = nodes.map((node) => node.getContent(MetadataMode.EMBED));
+    const embeddings = await this.embedModel.getTextEmbeddingsBatch(texts, {
+      logProgress: options?.logProgress,
+    });
+    return nodes.map((node, i) => {
+      node.embedding = embeddings[i];
+      return node;
+    });
+  }
+
+  /**
+   * Get embeddings for nodes and place them into the index.
+   * @param nodes
+   * @returns
+   */
+  async buildIndexFromNodes(
+    nodes: BaseNode[],
+    options?: { logProgress?: boolean },
+  ) {
+    // Check if the index already has nodes with the same hash
+    const newNodes = nodes.filter((node) =>
+      Object.entries(this.indexStruct!.nodesDict).reduce(
+        (acc, [key, value]) => {
+          if (value.hash === node.hash) {
+            acc = false;
+          }
+          return acc;
+        },
+        true,
+      ),
+    );
+
+    await this.insertNodes(newNodes, options);
+  }
+
+  /**
+   * High level API: split documents, get embeddings, and build index.
+   * @param documents
+   * @param args
+   * @returns
+   */
+  static async fromDocuments(
+    documents: Document[],
+    args: VectorIndexOptions = {},
+  ): Promise<VectorStoreIndex> {
+    args.storageContext =
+      args.storageContext ?? (await storageContextFromDefaults({}));
+    args.serviceContext = args.serviceContext ?? serviceContextFromDefaults({});
+    const docStore = args.storageContext.docStore;
+
+    for (const doc of documents) {
+      docStore.setDocumentHash(doc.id_, doc.hash);
+    }
+
+    if (args.logProgress) {
+      console.log("Using node parser on documents...");
+    }
+    args.nodes = await runTransformations(documents, [
+      args.serviceContext.nodeParser,
+    ]);
+    if (args.logProgress) {
+      console.log("Finished parsing documents.");
+    }
+    return await this.init(args);
+  }
+
+  static async fromVectorStore(
+    vectorStore: VectorStore,
+    serviceContext: ServiceContext,
+    imageVectorStore?: VectorStore,
+  ) {
+    if (!vectorStore.storesText) {
+      throw new Error(
+        "Cannot initialize from a vector store that does not store text",
+      );
+    }
+
+    const storageContext = await storageContextFromDefaults({
+      vectorStore,
+      imageVectorStore,
+    });
+
+    const index = await this.init({
+      nodes: [],
+      storageContext,
+      serviceContext,
+    });
+
+    return index;
+  }
+
+  asRetriever(
+    options?: Omit<VectorIndexRetrieverOptions, "index">,
+  ): VectorIndexRetriever {
+    return new VectorIndexRetriever({ index: this, ...options });
+  }
+
+  asQueryEngine(options?: {
+    retriever?: BaseRetriever;
+    responseSynthesizer?: BaseSynthesizer;
+    preFilters?: MetadataFilters;
+    nodePostprocessors?: BaseNodePostprocessor[];
+  }): BaseQueryEngine & RetrieverQueryEngine {
+    const { retriever, responseSynthesizer } = options ?? {};
+    return new RetrieverQueryEngine(
+      retriever ?? this.asRetriever(),
+      responseSynthesizer,
+      options?.preFilters,
+      options?.nodePostprocessors,
+    );
+  }
+
+  protected async insertNodesToStore(
+    vectorStore: VectorStore,
+    nodes: BaseNode[],
+  ): Promise<void> {
+    const newIds = await vectorStore.add(nodes);
+
+    // NOTE: if the vector store doesn't store text,
+    // we need to add the nodes to the index struct and document store
+    // NOTE: if the vector store keeps text,
+    // we only need to add image and index nodes
+    for (let i = 0; i < nodes.length; ++i) {
+      const type = nodes[i].getType();
+      if (
+        !vectorStore.storesText ||
+        type === ObjectType.INDEX ||
+        type === ObjectType.IMAGE
+      ) {
+        const nodeWithoutEmbedding = nodes[i].clone();
+        nodeWithoutEmbedding.embedding = undefined;
+        this.indexStruct.addNode(nodeWithoutEmbedding, newIds[i]);
+        await this.docStore.addDocuments([nodeWithoutEmbedding], true);
+      }
+    }
+  }
+
+  async insertNodes(
+    nodes: BaseNode[],
+    options?: { logProgress?: boolean },
+  ): Promise<void> {
+    if (!nodes || nodes.length === 0) {
+      return;
+    }
+    const { imageNodes, textNodes } = splitNodesByType(nodes);
+    if (imageNodes.length > 0) {
+      if (!this.imageVectorStore) {
+        throw new Error("Cannot insert image nodes without image vector store");
+      }
+      const imageNodesWithEmbedding = await this.getImageNodeEmbeddingResults(
+        imageNodes,
+        options,
+      );
+      await this.insertNodesToStore(
+        this.imageVectorStore,
+        imageNodesWithEmbedding,
+      );
+    }
+    const embeddingResults = await this.getNodeEmbeddingResults(
+      textNodes,
+      options,
+    );
+    await this.insertNodesToStore(this.vectorStore, embeddingResults);
+    await this.indexStore.addIndexStruct(this.indexStruct);
+  }
+
+  async deleteRefDoc(
+    refDocId: string,
+    deleteFromDocStore: boolean = true,
+  ): Promise<void> {
+    await this.deleteRefDocFromStore(this.vectorStore, refDocId);
+    if (this.imageVectorStore) {
+      await this.deleteRefDocFromStore(this.imageVectorStore, refDocId);
+    }
+
+    if (deleteFromDocStore) {
+      await this.docStore.deleteDocument(refDocId, false);
+    }
+  }
+
+  protected async deleteRefDocFromStore(
+    vectorStore: VectorStore,
+    refDocId: string,
+  ): Promise<void> {
+    vectorStore.delete(refDocId);
+
+    if (!vectorStore.storesText) {
+      const refDocInfo = await this.docStore.getRefDocInfo(refDocId);
+
+      if (refDocInfo) {
+        for (const nodeId of refDocInfo.nodeIds) {
+          this.indexStruct.delete(nodeId);
+          vectorStore.delete(nodeId);
+        }
+      }
+      await this.indexStore.addIndexStruct(this.indexStruct);
+    }
+  }
+
+  /**
+   * Calculates the embeddings for the given image nodes.
+   *
+   * @param nodes - An array of ImageNode objects representing the nodes for which embeddings are to be calculated.
+   * @param {Object} [options] - An optional object containing additional parameters.
+   *   @param {boolean} [options.logProgress] - A boolean indicating whether to log progress to the console (useful for debugging).
+   */
+  async getImageNodeEmbeddingResults(
+    nodes: ImageNode[],
+    options?: { logProgress?: boolean },
+  ): Promise<ImageNode[]> {
+    if (!this.imageEmbedModel) {
+      return [];
+    }
+
+    const nodesWithEmbeddings: ImageNode[] = [];
+
+    for (let i = 0; i < nodes.length; ++i) {
+      const node = nodes[i];
+      if (options?.logProgress) {
+        console.log(`Getting embedding for node ${i + 1}/${nodes.length}`);
+      }
+      node.embedding = await this.imageEmbedModel.getImageEmbedding(node.image);
+      nodesWithEmbeddings.push(node);
+    }
+
+    return nodesWithEmbeddings;
+  }
+}
+
+/**
+ * VectorIndexRetriever retrieves nodes from a VectorIndex.
+ */
+
+export type VectorIndexRetrieverOptions = {
+  index: VectorStoreIndex;
+  similarityTopK?: number;
+  imageSimilarityTopK?: number;
+};
+
+export class VectorIndexRetriever implements BaseRetriever {
+  index: VectorStoreIndex;
+  similarityTopK: number;
+  imageSimilarityTopK: number;
+  private serviceContext: ServiceContext;
+
+  constructor({
+    index,
+    similarityTopK,
+    imageSimilarityTopK,
+  }: VectorIndexRetrieverOptions) {
+    this.index = index;
+    this.serviceContext = this.index.serviceContext;
+    this.similarityTopK = similarityTopK ?? DEFAULT_SIMILARITY_TOP_K;
+    this.imageSimilarityTopK = imageSimilarityTopK ?? DEFAULT_SIMILARITY_TOP_K;
+  }
+
+  async retrieve(
+    query: string,
+    parentEvent?: Event,
+    preFilters?: MetadataFilters,
+  ): Promise<NodeWithScore[]> {
+    let nodesWithScores = await this.textRetrieve(query, preFilters);
+    nodesWithScores = nodesWithScores.concat(
+      await this.textToImageRetrieve(query, preFilters),
+    );
+    this.sendEvent(query, nodesWithScores, parentEvent);
+    return nodesWithScores;
+  }
+
+  protected async textRetrieve(
+    query: string,
+    preFilters?: MetadataFilters,
+  ): Promise<NodeWithScore[]> {
+    const options = {};
+    const q = await this.buildVectorStoreQuery(
+      this.index.embedModel,
+      query,
+      this.similarityTopK,
+      preFilters,
+    );
+    const result = await this.index.vectorStore.query(q, options);
+    return this.buildNodeListFromQueryResult(result);
+  }
+
+  private async textToImageRetrieve(
+    query: string,
+    preFilters?: MetadataFilters,
+  ) {
+    if (!this.index.imageEmbedModel || !this.index.imageVectorStore) {
+      // no-op if image embedding and vector store are not set
+      return [];
+    }
+    const q = await this.buildVectorStoreQuery(
+      this.index.imageEmbedModel,
+      query,
+      this.imageSimilarityTopK,
+      preFilters,
+    );
+    const result = await this.index.imageVectorStore.query(q, preFilters);
+    return this.buildNodeListFromQueryResult(result);
+  }
+
+  protected sendEvent(
+    query: string,
+    nodesWithScores: NodeWithScore<Metadata>[],
+    parentEvent: Event | undefined,
+  ) {
+    if (this.serviceContext.callbackManager.onRetrieve) {
+      this.serviceContext.callbackManager.onRetrieve({
+        query,
+        nodes: nodesWithScores,
+        event: globalsHelper.createEvent({
+          parentEvent,
+          type: "retrieve",
+        }),
+      });
+    }
+  }
+
+  protected async buildVectorStoreQuery(
+    embedModel: BaseEmbedding,
+    query: string,
+    similarityTopK: number,
+    preFilters?: MetadataFilters,
+  ): Promise<VectorStoreQuery> {
+    const queryEmbedding = await embedModel.getQueryEmbedding(query);
+
+    return {
+      queryEmbedding: queryEmbedding,
+      mode: VectorStoreQueryMode.DEFAULT,
+      similarityTopK: similarityTopK,
+      filters: preFilters ?? undefined,
+    };
+  }
+
+  protected buildNodeListFromQueryResult(result: VectorStoreQueryResult) {
+    const nodesWithScores: NodeWithScore[] = [];
+    for (let i = 0; i < result.ids.length; i++) {
+      const nodeFromResult = result.nodes?.[i];
+      if (!this.index.indexStruct.nodesDict[result.ids[i]] && nodeFromResult) {
+        this.index.indexStruct.nodesDict[result.ids[i]] = nodeFromResult;
+      }
+
+      const node = this.index.indexStruct.nodesDict[result.ids[i]];
+      // XXX: Hack, if it's an image node, we reconstruct the image from the URL
+      // Alternative: Store image in doc store and retrieve it here
+      if (node instanceof ImageNode) {
+        node.image = node.getUrl();
+      }
+
+      nodesWithScores.push({
+        node: node,
+        score: result.similarities[i],
+      });
+    }
+
+    return nodesWithScores;
+  }
+
+  getServiceContext(): ServiceContext {
+    return this.serviceContext;
+  }
+}
@@ -1,12 +1,12 @@
-import { BaseNode, MetadataMode } from "../Node";
-import { createSHA256 } from "../env";
-import { docToJson, jsonToDoc } from "../storage/docStore/utils";
-import { SimpleKVStore } from "../storage/kvStore/SimpleKVStore";
-import { BaseKVStore } from "../storage/kvStore/types";
-import { TransformComponent } from "./types";
+import { createSHA256 } from "@llamaindex/env";
+import { BaseNode, MetadataMode } from "../Node.js";
+import { docToJson, jsonToDoc } from "../storage/docStore/utils.js";
+import { SimpleKVStore } from "../storage/kvStore/SimpleKVStore.js";
+import { BaseKVStore } from "../storage/kvStore/types.js";
+import { TransformComponent } from "./types.js";

 const transformToJSON = (obj: TransformComponent) => {
-  let seen: any[] = [];
+  const seen: any[] = [];

  const replacer = (key: string, value: any) => {
    if (value != null && typeof value == "object") {
@@ -1,9 +1,13 @@
-import { BaseNode, Document } from "../Node";
-import { BaseReader } from "../readers/type";
-import { BaseDocumentStore, VectorStore } from "../storage";
-import { IngestionCache, getTransformationHash } from "./IngestionCache";
-import { DocStoreStrategy, createDocStoreStrategy } from "./strategies";
-import { TransformComponent } from "./types";
+import { BaseNode, Document } from "../Node.js";
+import { BaseReader } from "../readers/type.js";
+import { BaseDocumentStore } from "../storage/docStore/types.js";
+import { VectorStore } from "../storage/vectorStore/types.js";
+import { IngestionCache, getTransformationHash } from "./IngestionCache.js";
+import {
+  DocStoreStrategy,
+  createDocStoreStrategy,
+} from "./strategies/index.js";
+import { TransformComponent } from "./types.js";

 type IngestionRunArgs = {
  documents?: Document[];
@@ -1,2 +1,2 @@
-export * from "./IngestionPipeline";
-export * from "./types";
+export * from "./IngestionPipeline.js";
+export * from "./types.js";
@@ -1,6 +1,6 @@
-import { BaseNode } from "../../Node";
-import { BaseDocumentStore } from "../../storage";
-import { TransformComponent } from "../types";
+import { BaseNode } from "../../Node.js";
+import { BaseDocumentStore } from "../../storage/docStore/types.js";
+import { TransformComponent } from "../types.js";

 /**
 * Handle doc store duplicates by checking all hashes.
@@ -1,6 +1,6 @@
-import { BaseNode } from "../../Node";
-import { BaseDocumentStore, VectorStore } from "../../storage";
-import { classify } from "./classify";
+import { BaseNode } from "../../Node.js";
+import { BaseDocumentStore, VectorStore } from "../../storage/index.js";
+import { classify } from "./classify.js";

 /**
 * Handle docstore upserts by checking hashes and ids.
@@ -1,7 +1,8 @@
-import { BaseNode } from "../../Node";
-import { BaseDocumentStore, VectorStore } from "../../storage";
-import { TransformComponent } from "../types";
-import { classify } from "./classify";
+import { BaseNode } from "../../Node.js";
+import { BaseDocumentStore } from "../../storage/docStore/types.js";
+import { VectorStore } from "../../storage/vectorStore/types.js";
+import { TransformComponent } from "../types.js";
+import { classify } from "./classify.js";

 /**
 * Handles doc store upserts by checking hashes and ids.
@@ -1,5 +1,5 @@
-import { BaseNode } from "../../Node";
-import { BaseDocumentStore } from "../../storage";
+import { BaseNode } from "../../Node.js";
+import { BaseDocumentStore } from "../../storage/docStore/types.js";

 export async function classify(docStore: BaseDocumentStore, nodes: BaseNode[]) {
  const existingDocIds = Object.values(await docStore.getAllDocumentHashes());
@@ -1,7 +1,8 @@
-import { BaseDocumentStore, VectorStore } from "../../storage";
-import { TransformComponent } from "../types";
-import { DuplicatesStrategy } from "./DuplicatesStrategy";
-import { UpsertsStrategy } from "./UpsertsStrategy";
+import { BaseDocumentStore } from "../../storage/docStore/types.js";
+import { VectorStore } from "../../storage/vectorStore/types.js";
+import { TransformComponent } from "../types.js";
+import { DuplicatesStrategy } from "./DuplicatesStrategy.js";
+import { UpsertsStrategy } from "./UpsertsStrategy.js";

 export enum DocStoreStrategy {
  UPSERTS = "upserts",
@@ -1,4 +1,4 @@
-import { BaseNode } from "../Node";
+import { BaseNode } from "../Node.js";

 export interface TransformComponent {
  transform(nodes: BaseNode[], options?: any): Promise<BaseNode[]>;
@@ -6,28 +6,28 @@ import {
  EventType,
  OpenAIStreamToken,
  StreamCallbackResponse,
-} from "../callbacks/CallbackManager";
+} from "../callbacks/CallbackManager.js";

-import { ChatCompletionMessageParam } from "openai/resources";
+import { ChatCompletionMessageParam } from "openai/resources/index.js";
 import { LLMOptions } from "portkey-ai";
-import { Tokenizers, globalsHelper } from "../GlobalsHelper";
+import { Tokenizers, globalsHelper } from "../GlobalsHelper.js";
 import {
  ANTHROPIC_AI_PROMPT,
  ANTHROPIC_HUMAN_PROMPT,
  AnthropicSession,
  getAnthropicSession,
-} from "./anthropic";
+} from "./anthropic.js";
 import {
  AzureOpenAIConfig,
  getAzureBaseUrl,
  getAzureConfigFromEnv,
  getAzureModel,
  shouldUseAzure,
-} from "./azure";
-import { BaseLLM } from "./base";
-import { OpenAISession, getOpenAISession } from "./open_ai";
-import { PortkeySession, getPortkeySession } from "./portkey";
-import { ReplicateSession } from "./replicate_ai";
+} from "./azure.js";
+import { BaseLLM } from "./base.js";
+import { OpenAISession, getOpenAISession } from "./open_ai.js";
+import { PortkeySession, getPortkeySession } from "./portkey.js";
+import { ReplicateSession } from "./replicate_ai.js";
 import {
  ChatMessage,
  ChatResponse,
@@ -36,7 +36,7 @@ import {
  LLMChatParamsStreaming,
  LLMMetadata,
  MessageType,
-} from "./types";
+} from "./types.js";

 export const GPT4_MODELS = {
  "gpt-4": { contextWindow: 8192 },
@@ -235,7 +235,7 @@ export class OpenAI extends BaseLLM {
    params: LLMChatParamsNonStreaming | LLMChatParamsStreaming,
  ): Promise<ChatResponse | AsyncIterable<ChatResponseChunk>> {
    const { messages, parentEvent, stream, tools, toolChoice } = params;
-    let baseRequestParams: OpenAILLM.Chat.ChatCompletionCreateParams = {
+    const baseRequestParams: OpenAILLM.Chat.ChatCompletionCreateParams = {
      model: this.model,
      temperature: this.temperature,
      max_tokens: this.maxTokens,
@@ -26,7 +26,7 @@ export class AnthropicSession {
 // I'm not 100% sure this is necessary vs. just starting a new session
 // every time we make a call. They say they try to reuse connections
 // so in theory this is more efficient, but we should test it in the future.
-let defaultAnthropicSession: {
+const defaultAnthropicSession: {
  session: AnthropicSession;
  options: ClientOptions;
 }[] = [];
@@ -9,8 +9,8 @@ import {
  LLMCompletionParamsNonStreaming,
  LLMCompletionParamsStreaming,
  LLMMetadata,
-} from "./types";
-import { streamConverter } from "./utils";
+} from "./types.js";
+import { streamConverter } from "./utils.js";

 export abstract class BaseLLM implements LLM {
  abstract metadata: LLMMetadata;
@@ -1,4 +1,4 @@
-import { OpenAI } from "./LLM";
+import { OpenAI } from "./LLM.js";

 export class FireworksLLM extends OpenAI {
  constructor(init?: Partial<OpenAI>) {
@@ -1,11 +1,11 @@
-export * from "./LLM";
-export { FireworksLLM } from "./fireworks";
+export * from "./LLM.js";
+export { FireworksLLM } from "./fireworks.js";
 export {
  ALL_AVAILABLE_MISTRAL_MODELS,
  MistralAI,
  MistralAISession,
-} from "./mistral";
-export { Ollama } from "./ollama";
-export * from "./open_ai";
-export { TogetherLLM } from "./together";
-export * from "./types";
+} from "./mistral.js";
+export { Ollama } from "./ollama.js";
+export * from "./open_ai.js";
+export { TogetherLLM } from "./together.js";
+export * from "./types.js";
@@ -3,15 +3,15 @@ import {
  Event,
  EventType,
  StreamCallbackResponse,
-} from "../callbacks/CallbackManager";
-import { BaseLLM } from "./base";
+} from "../callbacks/CallbackManager.js";
+import { BaseLLM } from "./base.js";
 import {
  ChatMessage,
  ChatResponse,
  ChatResponseChunk,
  LLMChatParamsNonStreaming,
  LLMChatParamsStreaming,
-} from "./types";
+} from "./types.js";

 export const ALL_AVAILABLE_MISTRAL_MODELS = {
  "mistral-tiny": { contextWindow: 32000 },
@@ -1,6 +1,6 @@
-import { CallbackManager, Event } from "../callbacks/CallbackManager";
-import { BaseEmbedding } from "../embeddings/types";
-import { ok } from "../env";
+import { ok } from "@llamaindex/env";
+import { CallbackManager, Event } from "../callbacks/CallbackManager.js";
+import { BaseEmbedding } from "../embeddings/types.js";
 import {
  ChatMessage,
  ChatResponse,
@@ -12,7 +12,7 @@ import {
  LLMCompletionParamsNonStreaming,
  LLMCompletionParamsStreaming,
  LLMMetadata,
-} from "./types";
+} from "./types.js";

 const messageAccessor = (data: any): ChatResponseChunk => {
  return {
@@ -35,8 +35,10 @@ export class OpenAISession {
 // I'm not 100% sure this is necessary vs. just starting a new session
 // every time we make a call. They say they try to reuse connections
 // so in theory this is more efficient, but we should test it in the future.
-let defaultOpenAISession: { session: OpenAISession; options: ClientOptions }[] =
-  [];
+const defaultOpenAISession: {
+  session: OpenAISession;
+  options: ClientOptions;
+}[] = [];

 /**
 * Get a session for the OpenAI API. If one already exists with the same options,
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Alex Yang	65d834615d	docs(changeset): feat: abstract `@llamaindex/env` package	2024-02-23 17:45:43 -06:00
Alex Yang	b8be4c09e2	docs(changeset): build: use ESM as default	2024-02-23 17:45:01 -06:00
Alex Yang	e5fb332538	build: leave code as-is (#560 ) Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>	2024-02-23 17:39:25 -06:00
Marcus Schiesser	491033d534	fix: lint errors	2024-02-23 14:55:45 +07:00
Marcus Schiesser	885fa316a5	chore: add prefer const lint	2024-02-23 14:45:17 +07:00