Release 0.9.6 (#1698)

Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>

.github/workflows/preview.yml

@@ -25,4 +25,4 @@ jobs:
         run: pnpm run build
 
       - name: Pre Release
-        run: pnpx pkg-pr-new publish ./packages/* ./packages/providers/*
+        run: pnpx pkg-pr-new publish --pnpm ./packages/* ./packages/providers/* ./packages/providers/storage/*

.github/workflows/test.yml

@@ -83,11 +83,6 @@ jobs:
         run: pnpm install
       - name: Build
         run: pnpm run build
-      - name: Use Build For Examples
-        run: |
-          pnpm link ../packages/llamaindex/
-          cd readers && pnpm link ../../packages/llamaindex/
-        working-directory: ./examples
       - name: Run Type Check
         run: pnpm run type-check
       - name: Run Circular Dependency Check
@@ -103,6 +98,7 @@ jobs:
           - nextjs-node-runtime
           - waku-query-engine
           - llama-parse-browser
+          - vite-import-llamaindex
     runs-on: ubuntu-latest
     name: Build LlamaIndex Example (${{ matrix.packages }})
     steps:
@@ -121,6 +117,30 @@ jobs:
         run: pnpm run build
         working-directory: e2e/examples/${{ matrix.packages }}
 
+  size-limit:
+    runs-on: ubuntu-latest
+    if: github.event_name == 'pull_request'
+    name: Size Limit
+    steps:
+      - uses: actions/checkout@v4
+      - uses: pnpm/action-setup@v4
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version-file: ".nvmrc"
+          cache: "pnpm"
+      - name: Install dependencies
+        run: pnpm install
+      - name: Build llamaindex
+        run: pnpm run build
+      - uses: andresz1/size-limit-action@94bc357df29c36c8f8d50ea497c3e225c3c95d1d
+        with:
+          github_token: ${{ secrets.GITHUB_TOKEN }}
+          directory: e2e/examples/vite-import-llamaindex
+          skip_step: "install"
+          build_script: build
+          package_manager: pnpm
+
   typecheck-examples:
     runs-on: ubuntu-latest
 

.husky/pre-commit

@@ -1,3 +1 @@
-pnpm format
-pnpm lint
-npx lint-staged
+pnpm run lint-staged

.vscode/ltex.dictionary.en-US.txt

@@ -0,0 +1 @@
+LlamaIndexTS

.vscode/settings.json

@@ -14,5 +14,6 @@
   "[json]": {
     "editor.defaultFormatter": "esbenp.prettier-vscode"
   },
-  "prettier.prettierPath": "./node_modules/prettier"
+  "prettier.prettierPath": "./node_modules/prettier",
+  "prettier.configPath": "prettier.config.mjs"
 }

CONTRIBUTING.md

@@ -41,8 +41,15 @@ pnpm install
 
 ### Build the packages
 
+You'll need Turbo to build the packages. If you don't have it, you can run it with `pnpx`.
+
+To build all packages, run:
+
 ```shell
 # Build all packages
+pnpx turbo build --filter "./packages/*"
+
+# Or if you have turbo installed, you can run:
 turbo build --filter "./packages/*"
 ```
 

README.md

@@ -65,44 +65,18 @@ yarn add llamaindex
 
 See our official document: <https://ts.llamaindex.ai/docs/llamaindex/getting_started/>
 
-### Tips when using in non-Node.js environments
+### Adding provider packages
 
-When you are importing `llamaindex` in a non-Node.js environment(such as Vercel Edge, Cloudflare Workers, etc.)
-Some classes are not exported from top-level entry file.
+In most cases, you'll also need to install provider packages to use LlamaIndexTS. These are for adding AI models, file readers for ingestion or storing documents, e.g. in vector databases.
 
-The reason is that some classes are only compatible with Node.js runtime,(e.g. `PDFReader`) which uses Node.js specific APIs(like `fs`, `child_process`, `crypto`).
+For example, to use the OpenAI LLM, you would install the following package:
 
-If you need any of those classes, you have to import them instead directly though their file path in the package.
-Here's an example for importing the `PineconeVectorStore` class:
-
-```typescript
-import { PineconeVectorStore } from "llamaindex/vector-store/PineconeVectorStore";
+```shell
+npm install @llamaindex/openai
+pnpm install @llamaindex/openai
+yarn add @llamaindex/openai
 ```
 
-As the `PDFReader` is not working with the Edge runtime, here's how to use the `SimpleDirectoryReader` with the `LlamaParseReader` to load PDFs:
-
-```typescript
-import { SimpleDirectoryReader } from "llamaindex/readers/SimpleDirectoryReader";
-import { LlamaParseReader } from "llamaindex/readers/LlamaParseReader";
-
-export const DATA_DIR = "./data";
-
-export async function getDocuments() {
-  const reader = new SimpleDirectoryReader();
-  // Load PDFs using LlamaParseReader
-  return await reader.loadData({
-    directoryPath: DATA_DIR,
-    fileExtToReader: {
-      pdf: new LlamaParseReader({ resultType: "markdown" }),
-    },
-  });
-}
-```
-
-> _Note_: Reader classes have to be added explictly to the `fileExtToReader` map in the Edge version of the `SimpleDirectoryReader`.
-
-You'll find a complete example with LlamaIndexTS here: https://github.com/run-llama/create_llama_projects/tree/main/nextjs-edge-llamaparse
-
 ## Playground
 
 Check out our NextJS playground at https://llama-playground.vercel.app/. The source is available at https://github.com/run-llama/ts-playground

apps/next/CHANGELOG.md

@@ -1,5 +1,100 @@
 # @llamaindex/doc
 
+## 0.1.6
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+  - @llamaindex/workflow@0.0.12
+  - @llamaindex/cloud@3.0.6
+  - llamaindex@0.9.6
+  - @llamaindex/node-parser@1.0.5
+  - @llamaindex/openai@0.1.57
+  - @llamaindex/readers@2.0.5
+
+## 0.1.5
+
+### Patch Changes
+
+- Updated dependencies [ad3c7f1]
+  - @llamaindex/core@0.5.4
+  - @llamaindex/cloud@3.0.5
+  - llamaindex@0.9.5
+  - @llamaindex/node-parser@1.0.4
+  - @llamaindex/openai@0.1.56
+  - @llamaindex/readers@2.0.4
+
+## 0.1.4
+
+### Patch Changes
+
+- Updated dependencies [cb256f2]
+- Updated dependencies [cb021e7]
+  - @llamaindex/openai@0.1.55
+  - @llamaindex/core@0.5.3
+  - llamaindex@0.9.4
+  - @llamaindex/cloud@3.0.4
+  - @llamaindex/node-parser@1.0.3
+  - @llamaindex/readers@2.0.3
+
+## 0.1.3
+
+### Patch Changes
+
+- Updated dependencies [d952e68]
+  - @llamaindex/core@0.5.2
+  - @llamaindex/cloud@3.0.3
+  - llamaindex@0.9.3
+  - @llamaindex/node-parser@1.0.2
+  - @llamaindex/openai@0.1.54
+  - @llamaindex/readers@2.0.2
+
+## 0.1.2
+
+### Patch Changes
+
+- Updated dependencies [c902fcb]
+- Updated dependencies [88d776f]
+  - @llamaindex/cloud@3.0.2
+  - llamaindex@0.9.2
+
+## 0.1.1
+
+### Patch Changes
+
+- Updated dependencies [6d37d44]
+  - llamaindex@0.9.1
+  - @llamaindex/cloud@3.0.1
+  - @llamaindex/core@0.5.1
+  - @llamaindex/node-parser@1.0.1
+  - @llamaindex/openai@0.1.53
+  - @llamaindex/readers@2.0.1
+  - @llamaindex/workflow@0.0.11
+
+## 0.1.0
+
+### Minor Changes
+
+- 6a4a737: Remove re-exports from llamaindex main package
+- f4588bc: Remove readers package from llamaindex
+
+### Patch Changes
+
+- c7c0800: fix: fumadoc build fail
+- a87efb9: docs: update chat engine docs
+- 7bd5d93: docs: update workflow doc
+- Updated dependencies [6a4a737]
+- Updated dependencies [d924c63]
+- Updated dependencies [b490376]
+- Updated dependencies [f4588bc]
+  - llamaindex@0.9.0
+  - @llamaindex/core@0.5.0
+  - @llamaindex/cloud@3.0.0
+  - @llamaindex/node-parser@1.0.0
+  - @llamaindex/openai@0.1.52
+  - @llamaindex/readers@2.0.0
+
 ## 0.0.41
 
 ### Patch Changes

apps/next/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/doc",
-  "version": "0.0.41",
+  "version": "0.1.6",
   "private": true,
   "scripts": {
     "build": "pnpm run build:docs && next build",
@@ -28,25 +28,26 @@
     "@radix-ui/react-slot": "^1.1.0",
     "@radix-ui/react-tooltip": "^1.1.4",
     "@vercel/functions": "^1.5.0",
+    "@scalar/api-client-react": "^1.1.25",
     "ai": "^3.4.33",
     "class-variance-authority": "^0.7.0",
     "clsx": "2.1.1",
     "foxact": "^0.2.41",
     "framer-motion": "^11.11.17",
-    "fumadocs-core": "14.6.0",
-    "fumadocs-docgen": "1.3.2",
-    "fumadocs-mdx": "^11.1.2",
-    "fumadocs-openapi": "^5.8.2",
-    "fumadocs-twoslash": "^2.0.2",
-    "fumadocs-typescript": "^3.0.2",
-    "fumadocs-ui": "14.6.0",
+    "fumadocs-core": "^14.7.7",
+    "fumadocs-docgen": "^1.3.7",
+    "fumadocs-mdx": "^11.5.3",
+    "fumadocs-openapi": "^5.12.0",
+    "fumadocs-twoslash": "^2.0.3",
+    "fumadocs-typescript": "^3.0.3",
+    "fumadocs-ui": "^14.7.7",
     "hast-util-to-jsx-runtime": "^2.3.2",
     "llamaindex": "workspace:*",
     "lucide-react": "^0.460.0",
-    "next": "15.0.3",
+    "next": "15.1.7",
     "next-themes": "^0.4.3",
-    "react": "^18.3.1",
-    "react-dom": "^18.3.1",
+    "react": "^19.0.0",
+    "react-dom": "^19.0.0",
     "react-icons": "^5.3.0",
     "react-monaco-editor": "^0.56.2",
     "react-text-transition": "^3.1.0",
@@ -54,8 +55,8 @@
     "rehype-katex": "^7.0.1",
     "remark-math": "^6.0.0",
     "rimraf": "^6.0.1",
-    "shiki": "1.23.1",
-    "shiki-magic-move": "^0.5.0",
+    "shiki": "^2.3.2",
+    "shiki-magic-move": "^1.0.0",
     "swr": "^2.2.5",
     "tailwind-merge": "^2.5.2",
     "tailwindcss-animate": "^1.0.7",

apps/next/src/content/docs/llamaindex/examples/context_aware_agent.mdx

@@ -57,4 +57,3 @@ In this example, the Context-Aware Agent uses the retriever to fetch relevant co
 ## Available Context-Aware Agents
 
 - `OpenAIContextAwareAgent`: A context-aware agent using OpenAI's models.
-- `AnthropicContextAwareAgent`: A context-aware agent using Anthropic's models.

apps/next/src/content/docs/llamaindex/examples/local_llm.mdx

@@ -2,6 +2,8 @@
 title: Local LLMs
 ---
 
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
 LlamaIndex.TS supports OpenAI and [other remote LLM APIs](other_llms). You can also run a local LLM on your machine!
 
 ## Using a local model via Ollama
@@ -24,7 +26,23 @@ The first time you run it will also automatically download and install the model
 
 ### Switch the LLM in your code
 
-To tell LlamaIndex to use a local LLM, use the `Settings` object:
+To switch the LLM in your code, you first need to make sure to install the package for the Ollama model provider:
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install @llamaindex/ollama
+	```
+
+	```shell tab="yarn"
+	yarn add @llamaindex/ollama
+	```
+
+	```shell tab="pnpm"
+	pnpm add @llamaindex/ollama
+	```
+</Tabs>
+
+Then, to tell LlamaIndex to use a local LLM, use the `Settings` object:
 
 ```javascript
 Settings.llm = new Ollama({
@@ -34,7 +52,25 @@ Settings.llm = new Ollama({
 
 ### Use local embeddings
 
-If you're doing retrieval-augmented generation, LlamaIndex.TS will also call out to OpenAI to index and embed your data. To be entirely local, you can use a local embedding model like this:
+If you're doing retrieval-augmented generation, LlamaIndex.TS will also call out to OpenAI to index and embed your data. To be entirely local, you can use a local embedding model from Huggingface like this:
+
+First install the Huggingface model provider package: 
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install @llamaindex/huggingface
+	```
+
+	```shell tab="yarn"
+	yarn add @llamaindex/huggingface
+	```
+
+	```shell tab="pnpm"
+	pnpm add @llamaindex/huggingface
+	```
+</Tabs>
+
+And then set the embedding model in your code:
 
 ```javascript
 Settings.embedModel = new HuggingFaceEmbedding({

apps/next/src/content/docs/llamaindex/getting_started/index.mdx

@@ -1,6 +1,6 @@
 ---
 title: Installation
-description: Install llamaindex by running a single command.
+description: How to install llamaindex packages.
 ---
 
 import { Tab, Tabs } from "fumadocs-ui/components/tabs";

apps/next/src/content/docs/llamaindex/getting_started/setup/cloudflare.mdx

@@ -70,10 +70,8 @@ In Cloudflare Worker and similar serverless JS environment, you need to be aware
 
 - Some Node.js modules are not available in Cloudflare Worker, such as `node:fs`, `node:child_process`, `node:cluster`...
 - You are recommend to design your code using network request, such as use `fetch` API to communicate with database, insteadof a long-running process in Node.js.
-- Some of LlamaIndex.TS modules are not available in Cloudflare Worker, for example `SimpleDirectoryReader` (requires `node:fs`), Some multimodal API that relies on [`onnxruntime-node`](https://www.npmjs.com/package/onnxruntime-node)(we might port to HTTP based module in the future).
-- `@llamaindex/core` is designed to work in all JavaScript environment, including Cloudflare Worker. If you find any issue, please report to us.
+- Some of LlamaIndex.TS packages are not available in Cloudflare Worker, for example `@llamaindex/readers` and `@llamaindex/huggingface`.
+- The main `llamaindex` is designed to work in all JavaScript environment, including Cloudflare Worker. If you find any issue, please report to us.
 - `@llamaindex/env` is a JS environment binding module, which polyfill some Node.js/Modern Web API (for example, we have a memory based `fs` module, and Crypto API polyfill). It is designed to work in all JavaScript environment, including Cloudflare Worker.
 
-## Known issues
 
-- `llamaindex` not work perfectly in Cloudflare Worker, bundle size will be larger than 1MB, which is the limit of Cloudflare Worker. You will need import submodule instead of the whole `llamaindex` module.

apps/next/src/content/docs/llamaindex/guide/agents/1_setup.mdx

@@ -15,7 +15,7 @@ In LlamaIndex, an agent is a semi-autonomous piece of software powered by an LLM
 You'll need to have a recent version of [Node.js](https://nodejs.org/en) installed. Then you can install LlamaIndex.TS by running
 
 ```bash
-npm install llamaindex
+npm install llamaindex @llamaindex/openai @llamaindex/readers @llamaindex/huggingface
 ```
 
 ## Choose your model

apps/next/src/content/docs/llamaindex/guide/agents/4_agentic_rag.mdx

@@ -40,7 +40,7 @@ We'll be bringing in `SimpleDirectoryReader`, `HuggingFaceEmbedding`, `VectorSto
 import { FunctionTool, QueryEngineTool, Settings, VectorStoreIndex } from "llamaindex";
 import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
 import { HuggingFaceEmbedding } from "@llamaindex/huggingface";
-import { SimpleDirectoryReader } from "llamaindex";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 ```
 
 ### Add an embedding model

apps/next/src/content/docs/llamaindex/guide/loading/index.mdx

@@ -10,7 +10,7 @@ import { Accordion, Accordions } from 'fumadocs-ui/components/accordion';
 <Accordions>
 	<Accordion title="Install @llamaindex/readers">
 
-		If you want to only use reader modules, you can install `@llamaindex/readers`
+		If you want to use the reader module, you need to install `@llamaindex/readers`
 
 		<Tabs groupId="install-llamaindex" items={["npm", "yarn", "pnpm"]} persist>
 			```shell tab="npm"
@@ -31,72 +31,73 @@ import { Accordion, Accordions } from 'fumadocs-ui/components/accordion';
 
 We offer readers for different file formats.
 
-<Tabs groupId="llamaindex-or-readers" items={["llamaindex", "@llamaindex/readers"]} persist>
-	```ts twoslash tab="llamaindex"
-	import { CSVReader } from '@llamaindex/readers/csv'
-	import { PDFReader } from '@llamaindex/readers/pdf'
-	import { JSONReader } from '@llamaindex/readers/json'
-	import { MarkdownReader } from '@llamaindex/readers/markdown'
-	import { HTMLReader } from '@llamaindex/readers/html'
-	// you can find more readers in the documentation
-	```
-
-	```ts twoslash tab="@llamaindex/readers"
-	import { CSVReader } from '@llamaindex/readers/csv'
-	import { PDFReader } from '@llamaindex/readers/pdf'
-	import { JSONReader } from '@llamaindex/readers/json'
-	import { MarkdownReader } from '@llamaindex/readers/markdown'
-	import { HTMLReader } from '@llamaindex/readers/html'
-	// you can find more readers in the documentation
-	```
-
-</Tabs>
+```ts twoslash 
+import { CSVReader } from '@llamaindex/readers/csv'
+import { PDFReader } from '@llamaindex/readers/pdf'
+import { JSONReader } from '@llamaindex/readers/json'
+import { MarkdownReader } from '@llamaindex/readers/markdown'
+import { HTMLReader } from '@llamaindex/readers/html'
+// you can find more readers in the documentation
+```
 
 ## SimpleDirectoryReader
 
 `SimpleDirectoryReader` is the simplest way to load data from local files into LlamaIndex.
 
-<Tabs groupId="llamaindex-or-readers" items={["llamaindex", "@llamaindex/readers"]} persist>
+```ts twoslash 
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 
-	```ts twoslash tab="llamaindex"
-	import { SimpleDirectoryReader } from "llamaindex";
-
-	const reader = new SimpleDirectoryReader()
-	const documents = await reader.loadData("./data")
-	//    ^?
+const reader = new SimpleDirectoryReader()
+const documents = await reader.loadData("./data")
+//    ^?
 
 
-	const texts = documents.map(doc => doc.getText())
-	//    ^?
-	```
-
-	```ts twoslash tab="@llamaindex/readers"
-	import { SimpleDirectoryReader } from "llamaindex";
-
-	const reader = new SimpleDirectoryReader()
-	const documents = await reader.loadData("./data")
-	//    ^?
+const texts = documents.map(doc => doc.getText())
+//    ^?
+```
 
 
-	const texts = documents.map(doc => doc.getText())
-	//    ^?
-	```
+## Tips when using in non-Node.js environments
+
+When using `@llamaindex/readers` in a non-Node.js environment (such as Vercel Edge, Cloudflare Workers, etc.)
+Some classes are not exported from top-level entry file.
+
+The reason is that some classes are only compatible with Node.js runtime, (e.g. `PDFReader`) which uses Node.js specific APIs (like `fs`, `child_process`, `crypto`).
+
+If you need any of those classes, you have to import them instead directly through their file path in the package.
+
+As the `PDFReader` is not working with the Edge runtime, here's how to use the `SimpleDirectoryReader` with the `LlamaParseReader` to load PDFs:
+
+```typescript
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
+import { LlamaParseReader } from "@llamaindex/cloud";
+
+export const DATA_DIR = "./data";
+
+export async function getDocuments() {
+  const reader = new SimpleDirectoryReader();
+  // Load PDFs using LlamaParseReader
+  return await reader.loadData({
+    directoryPath: DATA_DIR,
+    fileExtToReader: {
+      pdf: new LlamaParseReader({ resultType: "markdown" }),
+    },
+  });
+}
+```
+
+> _Note_: Reader classes have to be added explicitly to the `fileExtToReader` map in the Edge version of the `SimpleDirectoryReader`.
+
+You'll find a complete example with LlamaIndexTS here: https://github.com/run-llama/create_llama_projects/tree/main/nextjs-edge-llamaparse
 
-</Tabs>
 
 ## Load file natively using Node.js Customization Hooks
 
 We have a helper utility to allow you to import a file in Node.js script.
 
-<Tabs groupId="llamaindex-or-readers" items={["llamaindex", "@llamaindex/readers"]} persist>
-	```shell tab="llamaindex"
-	node --import llamaindex/register ./script.js
-	```
-
-	```shell tab="@llamaindex/readers"
-	node --import @llamaindex/readers/node ./script.js
-	```
-</Tabs>
+```shell 
+node --import @llamaindex/readers/node ./script.js
+```
 
 ```ts
 import csv from './path/to/data.csv';

apps/next/src/content/docs/llamaindex/guide/loading/node-parser.mdx

@@ -81,7 +81,7 @@ It will split the code by AST nodes and then parse the nodes into a `Document` o
 	import TS from "tree-sitter-typescript";
 
 	const parser = new Parser();
-	parser.setLanguage(TS.typescript);
+	parser.setLanguage(TS.typescript as Parser.Language);
 	const codeSplitter = new CodeSplitter({
 		getParser: () => parser,
 	});
@@ -99,7 +99,7 @@ It will split the code by AST nodes and then parse the nodes into a `Document` o
 	import TS from "tree-sitter-typescript";
 
 	const parser = new Parser();
-	parser.setLanguage(TS.typescript);
+	parser.setLanguage(TS.typescript as Parser.Language);
 	const codeSplitter = new CodeSplitter({
 	  getParser: () => parser,
 	});

apps/next/src/content/docs/llamaindex/index.mdx

@@ -20,5 +20,5 @@ LlamaIndex.TS provides tools for beginners, advanced users, and everyone in betw
   className="w-full h-[440px]"
   aria-label="LlamaIndex.TS Starter"
   aria-description="This is a starter example for LlamaIndex.TS, it shows the basic usage of the library."
-  src="https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples?file=starter.ts"
+  src="https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples?embed=1&file=starter.ts"
 />

apps/next/src/content/docs/llamaindex/meta.json

@@ -7,6 +7,7 @@
     "what-is-llamaindex",
     "index",
     "getting_started",
+    "migration",
     "guide",
     "examples",
     "modules",

apps/next/src/content/docs/llamaindex/migration/0.8-to-0.9.mdx

@@ -0,0 +1,97 @@
+---
+title: Migrating from v0.8 to v0.9
+---
+
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+Version 0.9 of LlamaIndex.TS introduces significant architectural changes to improve package size and runtime compatibility. The main goals of this release are:
+
+1. Reduce the package size of the main `llamaindex` package by moving dependencies into provider packages, making it more suitable for serverless environments
+2. Enable consistent code across different environments by using unified imports (no separate imports for Node.js and Edge runtimes)
+
+## Major Changes
+
+### Installing Provider Packages
+
+In v0.9, you need to explicitly install the provider packages you want to use. The main `llamaindex` package no longer includes these dependencies by default.
+
+### Updating Imports
+
+You'll need to update your imports to get classes directly from their respective provider packages. Here's how to migrate different components:
+
+### 1. AI Model Providers
+
+Previously:
+```typescript
+import { OpenAI } from "llamaindex";
+```
+
+Now:
+```typescript
+import { OpenAI } from "@llamaindex/openai";
+```
+
+> Note: This examples requires installing the `@llamaindex/openai` package: 
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install @llamaindex/openai
+	```
+
+	```shell tab="yarn"
+	yarn add @llamaindex/openai
+	```
+
+	```shell tab="pnpm"
+	pnpm add @llamaindex/openai
+	```
+</Tabs>
+
+For more details on available AI model providers and their configuration, see the [LLMs documentation](/docs/llamaindex/modules/llms) and the [Embedding Models documentation](/docs/llamaindex/modules/embeddings).
+
+### 2. Storage Providers
+
+Previously:
+```typescript
+import { PineconeVectorStore } from "llamaindex";
+```
+
+Now:
+```typescript
+import { PineconeVectorStore } from "@llamaindex/pinecone";
+```
+
+For more information about available storage options, refer to the [Data Stores documentation](/docs/llamaindex/modules/data_stores).
+
+### 3. Data Loaders
+
+Previously:
+```typescript
+import { SimpleDirectoryReader } from "llamaindex";
+```
+
+Now:
+```typescript
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
+```
+
+For more details about available data loaders and their usage, check the [Loading Data](/docs/llamaindex/guide/loading).
+
+### 4. Prefer using `llamaindex` instead of `@llamaindex/core`
+
+`llamaindex` is now re-exporting most of `@llamaindex/core`. To simplify imports, just use `import { ... } from "llamaindex"` instead of `import { ... } from "@llamaindex/core"`. This is possible because `llamaindex` is now a smaller package.
+
+We might change imports internally in `@llamaindex/core` in the future. Let us know if you're missing something. 
+
+## Benefits of the Changes
+
+- **Smaller Bundle Size**: By moving dependencies to separate packages, your application only includes the features you actually use
+- **Runtime Consistency**: The same code works across different environments without environment-specific imports
+- **Improved Serverless Support**: Reduced package size makes it easier to deploy to serverless environments with size limitations
+
+## Need Help?
+
+If you encounter any issues during migration, please:
+1. Check our [GitHub repository](https://github.com/run-llama/LlamaIndexTS) for the latest updates
+2. Join our [Discord community](https://discord.gg/dGcwcsnxhU) for support
+3. Open an issue on GitHub if you find a bug or have a feature request

apps/next/src/content/docs/llamaindex/migration/meta.json

@@ -0,0 +1,5 @@
+{
+  "title": "Migration",
+  "description": "Migration between different versions",
+  "pages": ["0.8-to-0.9"]
+}

apps/next/src/content/docs/llamaindex/modules/agent_workflow.mdx

@@ -0,0 +1,139 @@
+---
+title: Agent Workflow
+---
+
+import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
+import CodeSource from "!raw-loader!../../../../../../../examples/agentworkflow/blog_writer.ts";
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+`AgentWorkflow` is a powerful system that enables you to create and orchestrate one or multiple agents with tools to perform specific tasks. It's built on top of the base `Workflow` system and provides a streamlined interface for agent interactions.
+
+## Installation
+
+You'll need to install the `@llamaindex/workflow` package:
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install @llamaindex/workflow
+	```
+
+	```shell tab="yarn"
+	yarn add @llamaindex/workflow
+	```
+
+	```shell tab="pnpm"
+	pnpm add @llamaindex/workflow
+	```
+</Tabs>
+
+## Usage
+
+### Single Agent Workflow
+
+The simplest use case is creating a single agent with specific tools. Here's an example of creating an assistant that tells jokes:
+
+```typescript
+import { AgentWorkflow, FunctionTool } from "llamaindex";
+import { OpenAI } from "@llamaindex/openai";
+
+// Define a joke-telling tool
+const jokeTool = FunctionTool.from(
+  () => "Baby Llama is called cria",
+  {
+    name: "joke",
+    description: "Use this tool to get a joke",
+  }
+);
+
+// Create an agent workflow with the tool
+const workflow = AgentWorkflow.fromTools({
+  tools: [jokeTool],
+  llm: new OpenAI({
+    model: "gpt-4o-mini",
+  }),
+});
+
+// Run the workflow
+const result = await workflow.run("Tell me something funny");
+console.log(result); // Baby Llama is called cria
+```
+
+### Event Streaming
+
+`AgentWorkflow` provides a unified interface for event streaming, making it easy to track and respond to different events during execution:
+
+```typescript
+import { AgentToolCall, AgentStream } from "llamaindex";
+
+// Get the workflow execution context
+const context = workflow.run("Tell me something funny");
+
+// Stream and handle events
+for await (const event of context) {
+  if (event instanceof AgentToolCall) {
+    console.log(`Tool being called: ${event.data.toolName}`);
+  }
+  if (event instanceof AgentStream) {
+    process.stdout.write(event.data.delta);
+  }
+}
+```
+
+### Multi-Agent Workflow
+
+`AgentWorkflow` can orchestrate multiple agents, enabling complex interactions and task handoffs. Each agent in a multi-agent workflow requires:
+
+- `name`: Unique identifier for the agent
+- `description`: Purpose description used for task routing
+- `tools`: Array of tools the agent can use
+- `canHandoffTo` (optional): Array of agent names or agent instances that this agent can delegate tasks to
+
+Here's an example of a multi-agent system that combines joke-telling and weather information:
+
+```typescript
+import { AgentWorkflow, FunctionAgent, FunctionTool } from "llamaindex";
+import { OpenAI } from "@llamaindex/openai";
+import { z } from "zod";
+
+// Create a weather agent
+const weatherAgent = new FunctionAgent({
+  name: "WeatherAgent",
+  description: "Provides weather information for any city",
+  tools: [
+    FunctionTool.from(
+      ({ city }: { city: string }) => `The weather in ${city} is sunny`,
+      {
+        name: "fetchWeather",
+        description: "Get weather information for a city",
+        parameters: z.object({
+          city: z.string(),
+        }),
+      }
+    ),
+  ],
+  llm: new OpenAI({ model: "gpt-4o-mini" }),
+});
+
+// Create a joke-telling agent
+const jokeAgent = new FunctionAgent({
+  name: "JokeAgent",
+  description: "Tells jokes and funny stories",
+  tools: [jokeTool], // Using the joke tool defined earlier
+  llm: new OpenAI({ model: "gpt-4o-mini" }),
+  canHandoffTo: [weatherAgent], // Can hand off to the weather agent
+});
+
+// Create the multi-agent workflow
+const workflow = new AgentWorkflow({
+  agents: [jokeAgent, weatherAgent],
+  rootAgent: jokeAgent, // Start with the joke agent
+});
+
+// Run the workflow
+const result = await workflow.run(
+  "Give me a morning greeting with a joke and the weather in San Francisco"
+);
+```
+
+The workflow will coordinate between agents, allowing them to handle different aspects of the request and hand off tasks when appropriate.
+

apps/next/src/content/docs/llamaindex/modules/chat_engine.mdx

@@ -12,9 +12,26 @@ const chatEngine = new ContextChatEngine({ retriever });
 const response = await chatEngine.chat({ message: query });
 ```
 
+In short, you can use the chat engine by calling `index.asChatEngine()`. It will return a `ContextChatEngine` to start chatting.
+
+```typescript
+const chatEngine = index.asChatEngine();
+```
+
+You can also pass in options to the chat engine.
+
+```typescript
+const chatEngine = index.asChatEngine({
+  similarityTopK: 5,
+  systemPrompt: "You are a helpful assistant.",
+});
+```
+
+
 The `chat` function also supports streaming, just add `stream: true` as an option:
 
 ```typescript
+const chatEngine = index.asChatEngine();
 const stream = await chatEngine.chat({ message: query, stream: true });
 for await (const chunk of stream) {
   process.stdout.write(chunk.response);

apps/next/src/content/docs/llamaindex/modules/embeddings/available_embeddings/voyageai.mdx

@@ -0,0 +1,46 @@
+---
+title: VoyageAI
+---
+
+To use VoyageAI embeddings, you need to import `VoyageAIEmbedding` from `@llamaindex/voyage-ai`.
+
+## Installation
+
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install llamaindex @llamaindex/voyage-ai
+	```
+
+	```shell tab="yarn"
+	yarn add llamaindex @llamaindex/voyage-ai
+	```
+
+	```shell tab="pnpm"
+	pnpm add llamaindex @llamaindex/voyage-ai
+	```
+</Tabs>
+
+```ts
+import { VoyageAIEmbedding } from "@llamaindex/voyage-ai";
+import { Document, Settings, VectorStoreIndex } from "llamaindex";
+
+Settings.embedModel = new VoyageAIEmbedding();
+
+const document = new Document({ text: essay, id_: "essay" });
+
+const index = await VectorStoreIndex.fromDocuments([document]);
+
+const queryEngine = index.asQueryEngine();
+
+const query = "What is the meaning of life?";
+
+const results = await queryEngine.query({
+  query,
+});
+```
+
+## API Reference
+
+- [VoyageAIEmbedding](/docs/api/classes/VoyageAIEmbedding)

apps/next/src/content/docs/llamaindex/modules/embeddings/index.mdx

@@ -37,6 +37,31 @@ Settings.embedModel = new OpenAIEmbedding({
 
 For local embeddings, you can use the [HuggingFace](/docs/llamaindex/modules/embeddings/available_embeddings/huggingface) embedding model.
 
+## Local Ollama Embeddings With Remote Host
+
+Ollama provides a way to run embedding models locally or connect to a remote Ollama instance. This is particularly useful when you need to:
+- Run embeddings without relying on external API services
+- Use custom embedding models
+- Connect to a shared Ollama instance in your network
+
+The ENV variable method you will find elsewhere sometimes may not work with the OllamaEmbedding class. Also note, you'll need to change the host
+in the Ollama server to `0.0.0.0` to allow connections from other machines.
+
+To use Ollama embeddings with a remote host, you need to specify the host URL in the configuration like this:
+
+```typescript
+import { OllamaEmbedding } from "@llamaindex/ollama";
+import { Settings } from "llamaindex";
+
+// Configure Ollama with a remote host
+Settings.embedModel = new OllamaEmbedding({
+  model: "nomic-embed-text",
+  config: {
+    host: "http://your-ollama-host:11434"
+  }
+});
+```
+
 ## Available Embeddings
 
 Most available embeddings are listed in the sidebar on the left.

apps/next/src/content/docs/llamaindex/modules/query_engines/router_query_engine.mdx

@@ -34,7 +34,7 @@ import {
   Settings,
 } from "llamaindex";
 import { OpenAI } from "@llamaindex/openai";
-import { SimpleDirectoryReader } from "llamaindex";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 ```
 
 ## Loading Data
@@ -124,7 +124,7 @@ import {
   Settings,
 } from "llamaindex";
 import { OpenAI } from "@llamaindex/openai";
-import { SimpleDirectoryReader } from "llamaindex";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 
 Settings.llm = new OpenAI();
 Settings.nodeParser = new SentenceSplitter({

apps/next/src/content/docs/llamaindex/modules/workflows.mdx

@@ -13,6 +13,22 @@ When a step function is added to a workflow, you need to specify the input and o
 
 You can create a `Workflow` to do anything! Build an agent, a RAG flow, an extraction flow, or anything else you want.
 
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install @llamaindex/workflow
+	```
+
+	```shell tab="yarn"
+	yarn add @llamaindex/workflow
+	```
+
+	```shell tab="pnpm"
+	pnpm add @llamaindex/workflow
+	```
+</Tabs>
+
 ## Getting Started
 
 As an illustrative example, let's consider a naive workflow where a joke is generated and then critiqued.
@@ -34,51 +50,59 @@ Events are user-defined classes that extend `WorkflowEvent` and contain arbitrar
 ```typescript
 const llm = new OpenAI();
 ...
-const jokeFlow = new Workflow({ verbose: true });
+const jokeFlow = new Workflow<unknown, string, string>();
 ```
 
-Our workflow is implemented by initiating the `Workflow` class. For simplicity, we created a `OpenAI` llm instance.
+Our workflow is implemented by initiating the `Workflow` class with three generic types: the context type (unknown), input type (string), and output type (string). The context type is `unknown`, as we're not using a shared context in this example.
+
+For simplicity, we created an `OpenAI` llm instance that we're using for inference in our workflow.
 
 ### Workflow Entry Points
 
 ```typescript
-const generateJoke = async (_context: Context, ev: StartEvent) => {
-  const prompt = `Write your best joke about ${ev.data.input}.`;
+const generateJoke = async (_: unknown, ev: StartEvent<string>) => {
+  const prompt = `Write your best joke about ${ev.data}.`;
   const response = await llm.complete({ prompt });
   return new JokeEvent({ joke: response.text });
 };
 ```
 
-Here, we come to the entry-point of our workflow. While events are user-defined, there are two special-case events, the `StartEvent` and the `StopEvent`. Here, the `StartEvent` signifies where to send the initial workflow input.
+Here, we come to the entry-point of our workflow. While events are user-defined, there are two special-case events, the `StartEvent` and the `StopEvent`. These events are predefined, but we can specify the payload type using generic types. We're using `StartEvent<string>` to indicate that we're going to send an input of type string.
 
-The `StartEvent` is a bit of a special object since it can hold arbitrary attributes. Here, we accessed the topic with `ev.data.input`.
-
-At this point, you may have noticed that we haven't explicitly told the workflow what events are handled by which steps.
-
-To do so, we use the `addStep` method which adds a step to the workflow. The first argument is the event type that the step will handle, and the second argument is the previously defined step function:
+To add this step to the workflow, we use the `addStep` method with an object specifying the input and output event types:
 
 ```typescript
-jokeFlow.addStep(StartEvent, generateJoke);
+jokeFlow.addStep(
+  {
+    inputs: [StartEvent<string>],
+    outputs: [JokeEvent],
+  },
+  generateJoke
+);
 ```
 
 ### Workflow Exit Points
 
 ```typescript
-const critiqueJoke = async (_context: Context, ev: JokeEvent) => {
+const critiqueJoke = async (_: unknown, ev: JokeEvent) => {
   const prompt = `Give a thorough critique of the following joke: ${ev.data.joke}`;
   const response = await llm.complete({ prompt });
-  return new StopEvent({ result: response.text });
+  return new StopEvent(response.text);
 };
 ```
 
-Here, we have our second, and last step, in the workflow. We know its the last step because the special `StopEvent` is returned. When the workflow encounters a returned `StopEvent`, it immediately stops the workflow and returns whatever the result was.
+Here, we have our second and last step in the workflow. We know it's the last step because the special `StopEvent` is returned. When the workflow encounters a returned `StopEvent`, it immediately stops the workflow and returns the result. Note that we're using the generic type `StopEvent<string>` to indicate that we're returning a string.
 
-In this case, the result is a string, but it could be a map, array, or any other object.
-
-Don't forget to add the step to the workflow:
+Add this step to the workflow:
 
 ```typescript
-jokeFlow.addStep(JokeEvent, critiqueJoke);
+jokeFlow.addStep(
+  {
+    inputs: [JokeEvent],
+    outputs: [StopEvent<string>],
+  },
+  critiqueJoke
+);
 ```
 
 ### Running the Workflow
@@ -90,42 +114,25 @@ console.log(result.data.result);
 
 Lastly, we run the workflow. The `.run()` method is async, so we use await here to wait for the result.
 
-### Validating Workflows
+## Working with Shared Context/State
 
-To tell the workflow what events are produced by each step, you can optionally provide a third argument to `addStep` to specify the output event type:
+Optionally, you can choose to use a shared context between steps by specifying a context type when creating the workflow. Here's an example where multiple steps access a shared state:
 
 ```typescript
-jokeFlow.addStep(StartEvent, generateJoke, { outputs: JokeEvent });
-jokeFlow.addStep(JokeEvent, critiqueJoke, { outputs: StopEvent });
-```
+import { HandlerContext } from "@llamaindex/workflow";
 
-To validate a workflow, you need to call the `validate` method:
+type MyContextData = {
+  query: string;
+  intermediateResults: any[];
+}
 
-```typescript
-jokeFlow.validate();
-```
-
-To automatically validate a workflow when you run it, you can set the `validate` flag to `true` at initialization:
-
-```typescript
-const jokeFlow = new Workflow({ verbose: true, validate: true });
-```
-
-## Working with Global Context/State
-
-Optionally, you can choose to use global context between steps. For example, maybe multiple steps access the original `query` input from the user. You can store this in global context so that every step has access.
-
-```typescript
-import { Context } from "llamaindex";
-
-const query = async (context: Context, ev: MyEvent) => {
+const query = async (context: HandlerContext<MyContextData>, ev: MyEvent) => {
   // get the query from the context
-  const query = context.get("query");
+  const query = context.data.query;
   // do something with context and event
   const val = ...
-  const result = ...
   // store in context
-  context.set("key", val);
+  context.data.intermediateResults.push(val);
 
   return new StopEvent({ result });
 };
@@ -138,28 +145,15 @@ The context does more than just hold data, it also provides utilities to buffer
 For example, you might have a step that waits for a query and retrieved nodes before synthesizing a response:
 
 ```typescript
-const synthesize = async (context: Context, ev: QueryEvent | RetrieveEvent) => {
-  const events = context.collectEvents(ev, [QueryEvent | RetrieveEvent]);
-  if (!events) {
-    return;
-  }
-  const prompt = events
-    .map((event) => {
-      if (event instanceof QueryEvent) {
-        return `Answer this query using the context provided: ${event.data.query}`;
-      } else if (event instanceof RetrieveEvent) {
-        return `Context: ${event.data.context}`;
-      }
-      return "";
-    })
-    .join("\n");
-
+const synthesize = async (context: Context, ev1: QueryEvent, ev2: RetrieveEvent) => {
+  const subPrompts = [`Answer this query using the context provided: ${ev1.data.query}`, `Context: ${ev2.data.context}`];
+  const prompt = subPrompts.join("\n");
   const response = await llm.complete({ prompt });
   return new StopEvent({ result: response.text });
 };
 ```
 
-Using `ctx.collectEvents()` we can buffer and wait for ALL expected events to arrive. This function will only return events (in the requested order) once all events have arrived.
+Passing multiple events, we can buffer and wait for ALL expected events to arrive. The receiving step function will only be called once all events have arrived.
 
 ## Manually Triggering Events
 

apps/next/typedoc.json

@@ -1,6 +1,13 @@
 {
   "plugin": ["typedoc-plugin-markdown", "typedoc-plugin-merge-modules"],
-  "entryPoints": ["../../packages/llamaindex/src/index.ts"],
+  "entryPoints": ["../../packages/**/src/index.ts"],
+  "exclude": [
+    "../../packages/autotool/**/src/index.ts",
+    "**/node_modules/**",
+    "**/dist/**",
+    "**/test/**",
+    "**/tests/**"
+  ],
   "tsconfig": "../../tsconfig.json",
   "readme": "none",
   "sourceLinkTemplate": "https://github.com/run-llama/LlamaIndexTS/blob/{gitRevision}/{path}#L{line}",

e2e/.gitignore

@@ -1 +1,2 @@
 logs
+.temp

e2e/CHANGELOG.md

@@ -1,5 +1,11 @@
 # @llamaindex/core-e2e
 
+## 0.1.0
+
+### Minor Changes
+
+- 6a4a737: Remove re-exports from llamaindex main package
+
 ## 0.0.8
 
 ### Patch Changes

e2e/examples/cloudflare-hono/CHANGELOG.md

@@ -0,0 +1,11 @@
+# @llamaindex/cloudflare-hono
+
+## 0.1.0
+
+### Minor Changes
+
+- 6a4a737: Remove re-exports from llamaindex main package
+
+### Patch Changes
+
+- b490376: Remove deprecated ServiceContext

e2e/examples/cloudflare-hono/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloudflare-hono",
-  "version": "0.0.0",
+  "version": "0.1.0",
   "private": true,
   "scripts": {
     "deploy": "wrangler deploy",

e2e/examples/cloudflare-hono/src/index.ts

@@ -17,23 +17,21 @@ app.post("/llm", async (c) => {
 
   const { message } = await c.req.json();
 
-  const { extractText } = await import("@llamaindex/core/utils");
-
   const {
+    extractText,
     QueryEngineTool,
-    serviceContextFromDefaults,
     VectorStoreIndex,
-    OpenAIAgent,
     Settings,
-    OpenAI,
-    OpenAIEmbedding,
+    SentenceSplitter,
   } = await import("llamaindex");
 
-  const { PineconeVectorStore } = await import(
-    "llamaindex/vector-store/PineconeVectorStore"
+  const { OpenAIAgent, OpenAI, OpenAIEmbedding } = await import(
+    "@llamaindex/openai"
   );
 
-  const llm = new OpenAI({
+  const { PineconeVectorStore } = await import("@llamaindex/pinecone");
+
+  Settings.llm = new OpenAI({
     model: "gpt-4o-mini",
     apiKey: c.env.OPENAI_API_KEY,
   });
@@ -43,8 +41,7 @@ app.post("/llm", async (c) => {
     apiKey: c.env.OPENAI_API_KEY,
   });
 
-  const serviceContext = serviceContextFromDefaults({
-    llm,
+  Settings.nodeParser = new SentenceSplitter({
     chunkSize: 8191,
     chunkOverlap: 0,
   });
@@ -53,7 +50,7 @@ app.post("/llm", async (c) => {
     namespace: "8xolsn4ulEQGdhnhP76yCzfLHdOZ",
   });
 
-  const index = await VectorStoreIndex.fromVectorStore(store, serviceContext);
+  const index = await VectorStoreIndex.fromVectorStore(store);
 
   const retriever = index.asRetriever({
     similarityTopK: 3,

e2e/examples/cloudflare-worker-agent/CHANGELOG.md

@@ -1,5 +1,54 @@
 # @llamaindex/cloudflare-worker-agent-test
 
+## 0.0.140
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 0.0.139
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 0.0.138
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
+## 0.0.137
+
+### Patch Changes
+
+- llamaindex@0.9.3
+
+## 0.0.136
+
+### Patch Changes
+
+- Updated dependencies [88d776f]
+  - llamaindex@0.9.2
+
+## 0.0.135
+
+### Patch Changes
+
+- Updated dependencies [6d37d44]
+  - llamaindex@0.9.1
+
+## 0.0.134
+
+### Patch Changes
+
+- Updated dependencies [6a4a737]
+- Updated dependencies [d924c63]
+- Updated dependencies [b490376]
+- Updated dependencies [f4588bc]
+  - llamaindex@0.9.0
+
 ## 0.0.133
 
 ### Patch Changes

e2e/examples/cloudflare-worker-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.133",
+  "version": "0.0.140",
   "type": "module",
   "private": true,
   "scripts": {

e2e/examples/llama-parse-browser/CHANGELOG.md

@@ -1,5 +1,48 @@
 # @llamaindex/llama-parse-browser-test
 
+## 0.0.51
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.6
+
+## 0.0.50
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.5
+
+## 0.0.49
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.4
+
+## 0.0.48
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.3
+
+## 0.0.47
+
+### Patch Changes
+
+- Updated dependencies [c902fcb]
+  - @llamaindex/cloud@3.0.2
+
+## 0.0.46
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.1
+
+## 0.0.45
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.0
+
 ## 0.0.44
 
 ### Patch Changes

e2e/examples/llama-parse-browser/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/llama-parse-browser-test",
   "private": true,
-  "version": "0.0.44",
+  "version": "0.0.51",
   "type": "module",
   "scripts": {
     "dev": "vite",

e2e/examples/nextjs-agent/CHANGELOG.md

@@ -1,5 +1,54 @@
 # @llamaindex/next-agent-test
 
+## 0.1.140
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 0.1.139
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 0.1.138
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
+## 0.1.137
+
+### Patch Changes
+
+- llamaindex@0.9.3
+
+## 0.1.136
+
+### Patch Changes
+
+- Updated dependencies [88d776f]
+  - llamaindex@0.9.2
+
+## 0.1.135
+
+### Patch Changes
+
+- Updated dependencies [6d37d44]
+  - llamaindex@0.9.1
+
+## 0.1.134
+
+### Patch Changes
+
+- Updated dependencies [6a4a737]
+- Updated dependencies [d924c63]
+- Updated dependencies [b490376]
+- Updated dependencies [f4588bc]
+  - llamaindex@0.9.0
+
 ## 0.1.133
 
 ### Patch Changes

e2e/examples/nextjs-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-agent-test",
-  "version": "0.1.133",
+  "version": "0.1.140",
   "private": true,
   "scripts": {
     "dev": "next dev",
@@ -10,9 +10,9 @@
   "dependencies": {
     "ai": "^4.0.0",
     "llamaindex": "workspace:*",
-    "next": "15.0.3",
-    "react": "18.3.1",
-    "react-dom": "18.3.1"
+    "next": "15.1.7",
+    "react": "19.0.0",
+    "react-dom": "19.0.0"
   },
   "devDependencies": {
     "@types/node": "^22.9.0",

e2e/examples/nextjs-edge-runtime/CHANGELOG.md

@@ -1,5 +1,54 @@
 # test-edge-runtime
 
+## 0.1.139
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 0.1.138
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 0.1.137
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
+## 0.1.136
+
+### Patch Changes
+
+- llamaindex@0.9.3
+
+## 0.1.135
+
+### Patch Changes
+
+- Updated dependencies [88d776f]
+  - llamaindex@0.9.2
+
+## 0.1.134
+
+### Patch Changes
+
+- Updated dependencies [6d37d44]
+  - llamaindex@0.9.1
+
+## 0.1.133
+
+### Patch Changes
+
+- Updated dependencies [6a4a737]
+- Updated dependencies [d924c63]
+- Updated dependencies [b490376]
+- Updated dependencies [f4588bc]
+  - llamaindex@0.9.0
+
 ## 0.1.132
 
 ### Patch Changes

e2e/examples/nextjs-edge-runtime/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.132",
+  "version": "0.1.139",
   "private": true,
   "scripts": {
     "dev": "next dev",
@@ -9,7 +9,7 @@
   },
   "dependencies": {
     "llamaindex": "workspace:*",
-    "next": "15.0.3",
+    "next": "15.1.7",
     "react": "^18.3.1",
     "react-dom": "^18.3.1"
   },

e2e/examples/nextjs-node-runtime/CHANGELOG.md

@@ -1,5 +1,70 @@
 # @llamaindex/next-node-runtime
 
+## 0.1.6
+
+### Patch Changes
+
+- llamaindex@0.9.6
+- @llamaindex/huggingface@0.0.41
+- @llamaindex/readers@2.0.5
+
+## 0.1.5
+
+### Patch Changes
+
+- llamaindex@0.9.5
+- @llamaindex/huggingface@0.0.40
+- @llamaindex/readers@2.0.4
+
+## 0.1.4
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+  - @llamaindex/huggingface@0.0.39
+  - @llamaindex/readers@2.0.3
+
+## 0.1.3
+
+### Patch Changes
+
+- llamaindex@0.9.3
+- @llamaindex/huggingface@0.0.38
+- @llamaindex/readers@2.0.2
+
+## 0.1.2
+
+### Patch Changes
+
+- Updated dependencies [88d776f]
+  - llamaindex@0.9.2
+
+## 0.1.1
+
+### Patch Changes
+
+- Updated dependencies [6d37d44]
+  - llamaindex@0.9.1
+  - @llamaindex/huggingface@0.0.37
+  - @llamaindex/readers@2.0.1
+
+## 0.1.0
+
+### Minor Changes
+
+- 6a4a737: Remove re-exports from llamaindex main package
+
+### Patch Changes
+
+- Updated dependencies [6a4a737]
+- Updated dependencies [d924c63]
+- Updated dependencies [b490376]
+- Updated dependencies [f4588bc]
+  - llamaindex@0.9.0
+  - @llamaindex/huggingface@0.0.36
+  - @llamaindex/readers@2.0.0
+
 ## 0.0.114
 
 ### Patch Changes

e2e/examples/nextjs-node-runtime/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.0.114",
+  "version": "0.1.6",
   "private": true,
   "scripts": {
     "dev": "next dev",
@@ -9,9 +9,11 @@
   },
   "dependencies": {
     "llamaindex": "workspace:*",
-    "next": "15.0.3",
-    "react": "18.3.1",
-    "react-dom": "18.3.1"
+    "@llamaindex/huggingface": "workspace:*",
+    "@llamaindex/readers": "workspace:*",
+    "next": "15.1.7",
+    "react": "19.0.0",
+    "react-dom": "19.0.0"
   },
   "devDependencies": {
     "@types/node": "^22.9.0",

e2e/examples/nextjs-node-runtime/src/actions/openai.ts

@@ -1,13 +1,13 @@
 "use server";
+import { HuggingFaceEmbedding } from "@llamaindex/huggingface";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 import {
   OpenAI,
   OpenAIAgent,
   QueryEngineTool,
   Settings,
-  SimpleDirectoryReader,
   VectorStoreIndex,
 } from "llamaindex";
-import { HuggingFaceEmbedding } from "llamaindex/embeddings/HuggingFaceEmbedding";
 
 Settings.llm = new OpenAI({
   apiKey: process.env.NEXT_PUBLIC_OPENAI_KEY ?? "FAKE_KEY_TO_PASS_TESTS",

e2e/examples/vite-import-llamaindex/.gitignore

@@ -0,0 +1,24 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?

e2e/examples/vite-import-llamaindex/CHANGELOG.md

@@ -0,0 +1,40 @@
+# vite-import-llamaindex
+
+## 0.0.6
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 0.0.5
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 0.0.4
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
+## 0.0.3
+
+### Patch Changes
+
+- llamaindex@0.9.3
+
+## 0.0.2
+
+### Patch Changes
+
+- Updated dependencies [88d776f]
+  - llamaindex@0.9.2
+
+## 0.0.1
+
+### Patch Changes
+
+- Updated dependencies [6d37d44]
+  - llamaindex@0.9.1

e2e/examples/vite-import-llamaindex/package.json

@@ -0,0 +1,24 @@
+{
+  "name": "vite-import-llamaindex",
+  "private": true,
+  "version": "0.0.6",
+  "type": "module",
+  "scripts": {
+    "build": "vite build",
+    "size-limit": "size-limit"
+  },
+  "size-limit": [
+    {
+      "path": "dist/LlamaIndexImportTest.js"
+    }
+  ],
+  "devDependencies": {
+    "@size-limit/preset-big-lib": "^11.1.6",
+    "size-limit": "^11.1.6",
+    "typescript": "^5.7.2",
+    "vite": "^6.1.0"
+  },
+  "dependencies": {
+    "llamaindex": "workspace:*"
+  }
+}

e2e/examples/vite-import-llamaindex/public/vite.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 257"><defs><linearGradient id="IconifyId1813088fe1fbc01fb466" x1="-.828%" x2="57.636%" y1="7.652%" y2="78.411%"><stop offset="0%" stop-color="#41D1FF"></stop><stop offset="100%" stop-color="#BD34FE"></stop></linearGradient><linearGradient id="IconifyId1813088fe1fbc01fb467" x1="43.376%" x2="50.316%" y1="2.242%" y2="89.03%"><stop offset="0%" stop-color="#FFEA83"></stop><stop offset="8.333%" stop-color="#FFDD35"></stop><stop offset="100%" stop-color="#FFA800"></stop></linearGradient></defs><path fill="url(#IconifyId1813088fe1fbc01fb466)" d="M255.153 37.938L134.897 252.976c-2.483 4.44-8.862 4.466-11.382.048L.875 37.958c-2.746-4.814 1.371-10.646 6.827-9.67l120.385 21.517a6.537 6.537 0 0 0 2.322-.004l117.867-21.483c5.438-.991 9.574 4.796 6.877 9.62Z"></path><path fill="url(#IconifyId1813088fe1fbc01fb467)" d="M185.432.063L96.44 17.501a3.268 3.268 0 0 0-2.634 3.014l-5.474 92.456a3.268 3.268 0 0 0 3.997 3.378l24.777-5.718c2.318-.535 4.413 1.507 3.936 3.838l-7.361 36.047c-.495 2.426 1.782 4.5 4.151 3.78l15.304-4.649c2.372-.72 4.652 1.36 4.15 3.788l-11.698 56.621c-.732 3.542 3.979 5.473 5.943 2.437l1.313-2.028l72.516-144.72c1.215-2.423-.88-5.186-3.54-4.672l-25.505 4.922c-2.396.462-4.435-1.77-3.759-4.114l16.646-57.705c.677-2.35-1.37-4.583-3.769-4.113Z"></path></svg>

e2e/examples/vite-import-llamaindex/src/main.ts

@@ -0,0 +1,7 @@
+import "llamaindex";
+
+document.querySelector<HTMLDivElement>("#app")!.innerHTML = `
+  <div>
+    Hello World!
+  </div>
+`;

e2e/examples/vite-import-llamaindex/tsconfig.json

@@ -0,0 +1,24 @@
+{
+  "compilerOptions": {
+    "target": "ES2020",
+    "useDefineForClassFields": true,
+    "module": "ESNext",
+    "lib": ["ES2020", "DOM", "DOM.Iterable"],
+    "skipLibCheck": true,
+
+    /* Bundler mode */
+    "moduleResolution": "bundler",
+    "allowImportingTsExtensions": true,
+    "isolatedModules": true,
+    "moduleDetection": "force",
+    "noEmit": true,
+
+    /* Linting */
+    "strict": true,
+    "noUnusedLocals": true,
+    "noUnusedParameters": true,
+    "noFallthroughCasesInSwitch": true,
+    "noUncheckedSideEffectImports": true
+  },
+  "include": ["src", "vite.config.ts"]
+}

e2e/examples/vite-import-llamaindex/vite.config.ts

@@ -0,0 +1,16 @@
+import { dirname, resolve } from "node:path";
+import { fileURLToPath } from "node:url";
+import { defineConfig } from "vite";
+
+const __dirname = dirname(fileURLToPath(import.meta.url));
+
+export default defineConfig({
+  build: {
+    lib: {
+      entry: resolve(__dirname, "src/main.ts"),
+      name: "LlamaIndexImportTest",
+      fileName: "LlamaIndexImportTest",
+      formats: ["es", "cjs"],
+    },
+  },
+});

e2e/examples/waku-query-engine/.gitignore

@@ -5,3 +5,4 @@ dist
 .cache
 .DS_Store
 *.pem
+/src/pages.gen.ts

e2e/examples/waku-query-engine/CHANGELOG.md

@@ -1,5 +1,56 @@
 # @llamaindex/waku-query-engine-test
 
+## 0.0.140
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 0.0.139
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 0.0.138
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
+## 0.0.137
+
+### Patch Changes
+
+- llamaindex@0.9.3
+
+## 0.0.136
+
+### Patch Changes
+
+- Updated dependencies [88d776f]
+  - llamaindex@0.9.2
+
+## 0.0.135
+
+### Patch Changes
+
+- Updated dependencies [cc50c9c]
+- Updated dependencies [6d37d44]
+  - @llamaindex/env@0.1.28
+  - llamaindex@0.9.1
+
+## 0.0.134
+
+### Patch Changes
+
+- Updated dependencies [6a4a737]
+- Updated dependencies [d924c63]
+- Updated dependencies [b490376]
+- Updated dependencies [f4588bc]
+  - llamaindex@0.9.0
+
 ## 0.0.133
 
 ### Patch Changes

e2e/examples/waku-query-engine/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.133",
+  "version": "0.0.140",
   "type": "module",
   "private": true,
   "scripts": {
@@ -9,11 +9,12 @@
     "start": "waku start"
   },
   "dependencies": {
+    "@llamaindex/env": "workspace:*",
     "llamaindex": "workspace:*",
-    "react": "19.0.0-rc-5c56b873-20241107",
-    "react-dom": "19.0.0-rc-5c56b873-20241107",
-    "react-server-dom-webpack": "19.0.0-rc-5c56b873-20241107",
-    "waku": "0.21.6"
+    "react": "19.0.0",
+    "react-dom": "19.0.0",
+    "react-server-dom-webpack": "19.0.0",
+    "waku": "0.21.20"
   },
   "devDependencies": {
     "@types/react": "18.3.12",

e2e/examples/waku-query-engine/src/actions.ts

@@ -1,13 +1,14 @@
 "use server";
+import { fs } from "@llamaindex/env";
 import { BaseQueryEngine, Document, VectorStoreIndex } from "llamaindex";
-import { readFile } from "node:fs/promises";
+
 let _queryEngine: BaseQueryEngine;
 
 async function lazyLoadQueryEngine() {
   if (!_queryEngine) {
     const path = "node_modules/llamaindex/examples/abramov.txt";
 
-    const essay = await readFile(path, "utf-8");
+    const essay = await fs.readFile(path, "utf-8");
 
     // Create Document object with essay
     const document = new Document({ text: essay, id_: path });

e2e/node/claude.e2e.ts

@@ -1,7 +1,7 @@
+import { Anthropic, AnthropicAgent } from "@llamaindex/anthropic";
 import { extractText } from "@llamaindex/core/utils";
 import { consola } from "consola";
-import { Anthropic, FunctionTool, Settings, type LLM } from "llamaindex";
-import { AnthropicAgent } from "llamaindex/agent/anthropic";
+import { FunctionTool, Settings, type LLM } from "llamaindex";
 import { ok } from "node:assert";
 import { beforeEach, test } from "node:test";
 import { getWeatherTool, sumNumbersTool } from "./fixtures/tools.js";

e2e/node/embedding/clip.e2e.ts

@@ -1,6 +1,7 @@
+import { ClipEmbedding } from "@llamaindex/clip";
 import type { LoadTransformerEvent } from "@llamaindex/env/multi-model";
 import { setTransformers } from "@llamaindex/env/multi-model";
-import { ClipEmbedding, ImageNode, Settings } from "llamaindex";
+import { ImageNode, Settings } from "llamaindex";
 import assert from "node:assert";
 import { type Mock, test } from "node:test";
 

e2e/node/smoke.e2e.ts

@@ -0,0 +1,105 @@
+import assert from "node:assert";
+import { execSync } from "node:child_process";
+import { mkdir, readFile, rm, writeFile } from "node:fs/promises";
+import { createRequire } from "node:module";
+import { resolve } from "node:path";
+import { test } from "node:test";
+import { testRootDir } from "./utils.js";
+
+await test("cjs/esm dual module check", async (t) => {
+  const esmImports = `import fs from 'node:fs/promises'
+import { Document, MetadataMode, VectorStoreIndex } from 'llamaindex'
+import { OpenAIEmbedding } from '@llamaindex/openai'
+import { Settings } from '@llamaindex/core/global'`;
+  const cjsRequire = `const fs = require('fs').promises
+const { Document, MetadataMode, VectorStoreIndex } = require('llamaindex')
+const { OpenAIEmbedding } = require('@llamaindex/openai')
+const { Settings } = require('@llamaindex/core/global')`;
+  const mainCode = `
+Settings.embedModel = new OpenAIEmbedding({
+  model: 'text-embedding-3-small',
+  apiKey: '${process.env.OPENAI_API_KEY}',
+})
+const model = Settings.embedModel
+if (model == null) {
+  process.exit(-1)
+}
+const document = new Document({ text: 'Hello, world!' })
+const index = await VectorStoreIndex.fromDocuments([document])
+`;
+  t.before(async () => {
+    await mkdir(resolve(testRootDir, ".temp"), {
+      recursive: true,
+      mode: 0o755,
+    });
+  });
+
+  t.after(async () => {
+    await rm(resolve(testRootDir, ".temp"), {
+      recursive: true,
+      force: true,
+    });
+  });
+
+  await t.test("cjs", async () => {
+    const cjsCode = `${cjsRequire}\n${mainCode}`;
+    const filePath = resolve(
+      testRootDir,
+      ".temp",
+      `${crypto.randomUUID()}.cjs`,
+    );
+    await writeFile(filePath, cjsCode, "utf-8");
+
+    execSync(`${process.argv[0]} ${filePath}`, {
+      cwd: process.cwd(),
+    });
+  });
+
+  await t.test("esm", async () => {
+    const esmCode = `${esmImports}\n${mainCode}`;
+    const filePath = resolve(
+      testRootDir,
+      ".temp",
+      `${crypto.randomUUID()}.mjs`,
+    );
+    await writeFile(filePath, esmCode, "utf-8");
+
+    execSync(`${process.argv[0]} ${filePath}`, {
+      cwd: process.cwd(),
+    });
+  });
+
+  const specialConditions = ["edge-light", "workerd", "react-server"];
+  for (const condition of specialConditions) {
+    await t.test(condition, async () => {
+      const esmCode = `${esmImports}\n${mainCode}`;
+      const filePath = resolve(
+        testRootDir,
+        ".temp",
+        `${crypto.randomUUID()}.mjs`,
+      );
+      await writeFile(filePath, esmCode, "utf-8");
+
+      execSync(`${process.argv[0]} ${filePath} -C ${condition}`, {
+        cwd: process.cwd(),
+      });
+    });
+  }
+});
+
+test('no extra deps in "@llamaindex/env" cjs module', async () => {
+  const modules = ["@aws-crypto/sha256-js"];
+  const require = createRequire(import.meta.url);
+  const envPackage = require.resolve("@llamaindex/env");
+  const file = await readFile(envPackage, "utf-8");
+  for (const module of modules) {
+    assert.ok(!file.includes(module));
+  }
+});
+
+test('no error when require "llamaindex" in CJS', async () => {
+  const code = `require('llamaindex')`;
+  execSync(`${process.argv[0]} -e "${code}"`, {
+    cwd: process.cwd(),
+  });
+});

e2e/node/vector-store/pg-vector-store.e2e.ts

@@ -1,6 +1,6 @@
+import { PGVectorStore } from "@llamaindex/postgres";
 import { config } from "dotenv";
 import { Document, VectorStoreQueryMode } from "llamaindex";
-import { PGVectorStore } from "llamaindex/vector-store/PGVectorStore";
 import assert from "node:assert";
 import { test } from "node:test";
 import pg from "pg";

e2e/node/vector-store/pinecone.e2e.ts

@@ -1,10 +1,8 @@
 import { Document, MetadataMode } from "@llamaindex/core/schema";
+import { OpenAIEmbedding } from "@llamaindex/openai";
+import { PineconeVectorStore } from "@llamaindex/pinecone";
 import { config } from "dotenv";
-import {
-  OpenAIEmbedding,
-  PineconeVectorStore,
-  VectorStoreIndex,
-} from "llamaindex";
+import { VectorStoreIndex } from "llamaindex";
 import assert from "node:assert";
 import { test } from "node:test";
 

e2e/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/e2e",
   "private": true,
-  "version": "0.0.8",
+  "version": "0.1.0",
   "type": "module",
   "scripts": {
     "e2e": "node --import tsx --import ./mock-register.js --test ./node/**/*.e2e.ts",
@@ -14,6 +14,10 @@
     "@llamaindex/env": "workspace:*",
     "@llamaindex/ollama": "workspace:*",
     "@llamaindex/openai": "workspace:*",
+    "@llamaindex/pinecone": "workspace:*",
+    "@llamaindex/postgres": "workspace:*",
+    "@llamaindex/clip": "workspace:*",
+    "@llamaindex/anthropic": "workspace:*",
     "@types/node": "^22.9.0",
     "@types/pg": "^8.11.8",
     "@huggingface/transformers": "^3.0.2",

examples/CHANGELOG.md

@@ -1,5 +1,249 @@
 # examples
 
+## 0.2.5
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+- Updated dependencies [fd74ba4]
+  - @llamaindex/core@0.5.5
+  - @llamaindex/workflow@0.0.12
+  - @llamaindex/voyage-ai@1.0.2
+  - @llamaindex/cloud@3.0.6
+  - llamaindex@0.9.6
+  - @llamaindex/node-parser@1.0.5
+  - @llamaindex/anthropic@0.2.3
+  - @llamaindex/clip@0.0.41
+  - @llamaindex/cohere@0.0.10
+  - @llamaindex/deepinfra@0.0.41
+  - @llamaindex/google@0.0.12
+  - @llamaindex/huggingface@0.0.41
+  - @llamaindex/mistral@0.0.10
+  - @llamaindex/mixedbread@0.0.10
+  - @llamaindex/ollama@0.0.45
+  - @llamaindex/openai@0.1.57
+  - @llamaindex/portkey-ai@0.0.38
+  - @llamaindex/replicate@0.0.38
+  - @llamaindex/astra@0.0.10
+  - @llamaindex/azure@0.1.5
+  - @llamaindex/chroma@0.0.10
+  - @llamaindex/firestore@1.0.3
+  - @llamaindex/milvus@0.1.5
+  - @llamaindex/mongodb@0.0.10
+  - @llamaindex/pinecone@0.0.10
+  - @llamaindex/postgres@0.0.38
+  - @llamaindex/qdrant@0.1.5
+  - @llamaindex/upstash@0.0.10
+  - @llamaindex/weaviate@0.0.10
+  - @llamaindex/vercel@0.0.16
+  - @llamaindex/readers@2.0.5
+  - @llamaindex/groq@0.0.56
+  - @llamaindex/vllm@0.0.27
+
+## 0.2.4
+
+### Patch Changes
+
+- Updated dependencies [ad3c7f1]
+  - @llamaindex/core@0.5.4
+  - @llamaindex/cloud@3.0.5
+  - llamaindex@0.9.5
+  - @llamaindex/node-parser@1.0.4
+  - @llamaindex/anthropic@0.2.2
+  - @llamaindex/clip@0.0.40
+  - @llamaindex/cohere@0.0.9
+  - @llamaindex/deepinfra@0.0.40
+  - @llamaindex/google@0.0.11
+  - @llamaindex/huggingface@0.0.40
+  - @llamaindex/mistral@0.0.9
+  - @llamaindex/mixedbread@0.0.9
+  - @llamaindex/ollama@0.0.44
+  - @llamaindex/openai@0.1.56
+  - @llamaindex/portkey-ai@0.0.37
+  - @llamaindex/replicate@0.0.37
+  - @llamaindex/astra@0.0.9
+  - @llamaindex/azure@0.1.4
+  - @llamaindex/chroma@0.0.9
+  - @llamaindex/firestore@1.0.2
+  - @llamaindex/milvus@0.1.4
+  - @llamaindex/mongodb@0.0.9
+  - @llamaindex/pinecone@0.0.9
+  - @llamaindex/postgres@0.0.37
+  - @llamaindex/qdrant@0.1.4
+  - @llamaindex/upstash@0.0.9
+  - @llamaindex/weaviate@0.0.9
+  - @llamaindex/vercel@0.0.15
+  - @llamaindex/voyage-ai@1.0.1
+  - @llamaindex/readers@2.0.4
+  - @llamaindex/groq@0.0.55
+  - @llamaindex/vllm@0.0.26
+
+## 0.2.3
+
+### Patch Changes
+
+- Updated dependencies [cb256f2]
+- Updated dependencies [cb021e7]
+- Updated dependencies [0346391]
+  - @llamaindex/openai@0.1.55
+  - @llamaindex/core@0.5.3
+  - llamaindex@0.9.4
+  - @llamaindex/voyage-ai@1.0.0
+  - @llamaindex/clip@0.0.39
+  - @llamaindex/deepinfra@0.0.39
+  - @llamaindex/groq@0.0.54
+  - @llamaindex/huggingface@0.0.39
+  - @llamaindex/azure@0.1.3
+  - @llamaindex/milvus@0.1.3
+  - @llamaindex/qdrant@0.1.3
+  - @llamaindex/vllm@0.0.25
+  - @llamaindex/cloud@3.0.4
+  - @llamaindex/node-parser@1.0.3
+  - @llamaindex/anthropic@0.2.1
+  - @llamaindex/cohere@0.0.8
+  - @llamaindex/google@0.0.10
+  - @llamaindex/mistral@0.0.8
+  - @llamaindex/mixedbread@0.0.8
+  - @llamaindex/ollama@0.0.43
+  - @llamaindex/portkey-ai@0.0.36
+  - @llamaindex/replicate@0.0.36
+  - @llamaindex/astra@0.0.8
+  - @llamaindex/chroma@0.0.8
+  - @llamaindex/firestore@1.0.1
+  - @llamaindex/mongodb@0.0.8
+  - @llamaindex/pinecone@0.0.8
+  - @llamaindex/postgres@0.0.36
+  - @llamaindex/upstash@0.0.8
+  - @llamaindex/weaviate@0.0.8
+  - @llamaindex/vercel@0.0.14
+  - @llamaindex/readers@2.0.3
+
+## 0.2.2
+
+### Patch Changes
+
+- 3564244: Add support for claude 3.7 thinking (and set default temperature to 1)
+- 3564244: add support for claude 3.7
+- Updated dependencies [d952e68]
+- Updated dependencies [a9c6144]
+- Updated dependencies [5c026e8]
+- Updated dependencies [3564244]
+- Updated dependencies [3564244]
+  - @llamaindex/core@0.5.2
+  - @llamaindex/anthropic@0.2.0
+  - @llamaindex/firestore@1.0.0
+  - @llamaindex/cloud@3.0.3
+  - llamaindex@0.9.3
+  - @llamaindex/node-parser@1.0.2
+  - @llamaindex/clip@0.0.38
+  - @llamaindex/cohere@0.0.7
+  - @llamaindex/deepinfra@0.0.38
+  - @llamaindex/google@0.0.9
+  - @llamaindex/huggingface@0.0.38
+  - @llamaindex/mistral@0.0.7
+  - @llamaindex/mixedbread@0.0.7
+  - @llamaindex/ollama@0.0.42
+  - @llamaindex/openai@0.1.54
+  - @llamaindex/portkey-ai@0.0.35
+  - @llamaindex/replicate@0.0.35
+  - @llamaindex/astra@0.0.7
+  - @llamaindex/azure@0.1.2
+  - @llamaindex/chroma@0.0.7
+  - @llamaindex/milvus@0.1.2
+  - @llamaindex/mongodb@0.0.7
+  - @llamaindex/pinecone@0.0.7
+  - @llamaindex/postgres@0.0.35
+  - @llamaindex/qdrant@0.1.2
+  - @llamaindex/upstash@0.0.7
+  - @llamaindex/weaviate@0.0.7
+  - @llamaindex/vercel@0.0.13
+  - @llamaindex/readers@2.0.2
+  - @llamaindex/groq@0.0.53
+  - @llamaindex/vllm@0.0.24
+
+## 0.2.1
+
+### Patch Changes
+
+- Updated dependencies [cc50c9c]
+- Updated dependencies [6d37d44]
+  - @llamaindex/env@0.1.28
+  - llamaindex@0.9.1
+  - @llamaindex/cloud@3.0.1
+  - @llamaindex/core@0.5.1
+  - @llamaindex/node-parser@1.0.1
+  - @llamaindex/anthropic@0.1.1
+  - @llamaindex/clip@0.0.37
+  - @llamaindex/cohere@0.0.6
+  - @llamaindex/deepinfra@0.0.37
+  - @llamaindex/google@0.0.8
+  - @llamaindex/groq@0.0.52
+  - @llamaindex/huggingface@0.0.37
+  - @llamaindex/mistral@0.0.6
+  - @llamaindex/mixedbread@0.0.6
+  - @llamaindex/ollama@0.0.41
+  - @llamaindex/openai@0.1.53
+  - @llamaindex/portkey-ai@0.0.34
+  - @llamaindex/replicate@0.0.34
+  - @llamaindex/astra@0.0.6
+  - @llamaindex/azure@0.1.1
+  - @llamaindex/chroma@0.0.6
+  - @llamaindex/milvus@0.1.1
+  - @llamaindex/mongodb@0.0.6
+  - @llamaindex/pinecone@0.0.6
+  - @llamaindex/postgres@0.0.34
+  - @llamaindex/qdrant@0.1.1
+  - @llamaindex/upstash@0.0.6
+  - @llamaindex/weaviate@0.0.6
+  - @llamaindex/readers@2.0.1
+  - @llamaindex/workflow@0.0.11
+  - @llamaindex/vercel@0.0.12
+  - @llamaindex/vllm@0.0.23
+
+## 0.2.0
+
+### Minor Changes
+
+- 6a4a737: Remove re-exports from llamaindex main package
+- f4588bc: Remove readers package from llamaindex
+
+### Patch Changes
+
+- b490376: Remove deprecated ServiceContext
+- Updated dependencies [6a4a737]
+- Updated dependencies [d924c63]
+- Updated dependencies [b490376]
+- Updated dependencies [f4588bc]
+  - @llamaindex/milvus@0.1.0
+  - @llamaindex/qdrant@0.1.0
+  - @llamaindex/azure@0.1.0
+  - @llamaindex/anthropic@0.1.0
+  - llamaindex@0.9.0
+  - @llamaindex/cloud@3.0.0
+  - @llamaindex/node-parser@1.0.0
+  - @llamaindex/clip@0.0.36
+  - @llamaindex/cohere@0.0.5
+  - @llamaindex/deepinfra@0.0.36
+  - @llamaindex/google@0.0.7
+  - @llamaindex/huggingface@0.0.36
+  - @llamaindex/mistral@0.0.5
+  - @llamaindex/mixedbread@0.0.5
+  - @llamaindex/ollama@0.0.40
+  - @llamaindex/openai@0.1.52
+  - @llamaindex/portkey-ai@0.0.33
+  - @llamaindex/replicate@0.0.33
+  - @llamaindex/astra@0.0.5
+  - @llamaindex/chroma@0.0.5
+  - @llamaindex/mongodb@0.0.5
+  - @llamaindex/pinecone@0.0.5
+  - @llamaindex/postgres@0.0.33
+  - @llamaindex/upstash@0.0.5
+  - @llamaindex/weaviate@0.0.5
+  - @llamaindex/vercel@0.0.11
+  - @llamaindex/readers@2.0.0
+  - @llamaindex/groq@0.0.51
+  - @llamaindex/vllm@0.0.22
+
 ## 0.1.3
 
 ### Patch Changes

examples/agent/query_openai_agent.ts

@@ -1,9 +1,6 @@
 import { OpenAIAgent } from "@llamaindex/openai";
-import {
-  QueryEngineTool,
-  SimpleDirectoryReader,
-  VectorStoreIndex,
-} from "llamaindex";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
+import { QueryEngineTool, VectorStoreIndex } from "llamaindex";
 
 async function main() {
   // Load the documents

examples/agent/retriever_openai_agent.ts

@@ -1,9 +1,9 @@
 import { OpenAIAgent } from "@llamaindex/openai";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 import {
   FunctionTool,
   MetadataMode,
   NodeWithScore,
-  SimpleDirectoryReader,
   VectorStoreIndex,
 } from "llamaindex";
 

examples/agent/step_wise_query_tool.ts

@@ -1,9 +1,6 @@
 import { OpenAIAgent } from "@llamaindex/openai";
-import {
-  QueryEngineTool,
-  SimpleDirectoryReader,
-  VectorStoreIndex,
-} from "llamaindex";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
+import { QueryEngineTool, VectorStoreIndex } from "llamaindex";
 
 async function main() {
   // Load the documents

examples/agentworkflow/blog_writer.ts

@@ -0,0 +1,83 @@
+import { OpenAI } from "@llamaindex/openai";
+import fs from "fs";
+import {
+  AgentToolCall,
+  AgentToolCallResult,
+  AgentWorkflow,
+  FunctionAgent,
+  FunctionTool,
+} from "llamaindex";
+import os from "os";
+import { z } from "zod";
+
+import { WikipediaTool } from "../wiki";
+const llm = new OpenAI({
+  model: "gpt-4o-mini",
+});
+
+const saveFileTool = FunctionTool.from(
+  ({ content }: { content: string }) => {
+    const filePath = os.tmpdir() + "/report.md";
+    fs.writeFileSync(filePath, content);
+    return `File saved successfully at ${filePath}`;
+  },
+  {
+    name: "saveFile",
+    description:
+      "Save the written content into a file that can be downloaded by the user",
+    parameters: z.object({
+      content: z.string({
+        description: "The content to save into a file",
+      }),
+    }),
+  },
+);
+
+async function main() {
+  const reportAgent = new FunctionAgent({
+    name: "ReportAgent",
+    description:
+      "Responsible for crafting well-written blog posts based on research findings",
+    systemPrompt: `You are a professional writer. Your task is to create an engaging blog post using the research content provided. Once complete, save the post to a file using the saveFile tool.`,
+    tools: [saveFileTool],
+    llm,
+  });
+
+  const researchAgent = new FunctionAgent({
+    name: "ResearchAgent",
+    description:
+      "Responsible for gathering relevant information from the internet",
+    systemPrompt: `You are a research agent. Your role is to gather information from the internet using the provided tools and then transfer this information to the report agent for content creation.`,
+    tools: [new WikipediaTool()],
+    canHandoffTo: [reportAgent],
+    llm,
+  });
+
+  const workflow = new AgentWorkflow({
+    agents: [researchAgent, reportAgent],
+    rootAgent: researchAgent,
+  });
+
+  const context = workflow.run("Write a blog post about history of LLM");
+
+  let finalResult;
+  for await (const event of context) {
+    if (event instanceof AgentToolCall) {
+      console.log(
+        `[Agent ${event.displayName}] executing tool ${event.data.toolName} with parameters ${JSON.stringify(
+          event.data.toolKwargs,
+        )}`,
+      );
+    } else if (event instanceof AgentToolCallResult) {
+      console.log(
+        `[Agent ${event.displayName}] executed tool ${event.data.toolName} with result ${event.data.toolOutput.result}`,
+      );
+    }
+    finalResult = event;
+  }
+  console.log("Final result:", finalResult?.data);
+}
+
+main().catch((error) => {
+  console.error("Error:", error);
+});

examples/agentworkflow/multiple_agents.ts

@@ -0,0 +1,110 @@
+/**
+ * This example shows how to use AgentWorkflow with multiple agents
+ * 1. FetchWeatherAgent - Fetches the weather in a city
+ * 2. TemperatureConverterAgent - Converts the temperature from Fahrenheit to Celsius
+ */
+import { OpenAI } from "@llamaindex/openai";
+import { StopEvent } from "@llamaindex/workflow";
+import {
+  AgentInput,
+  AgentOutput,
+  AgentStream,
+  AgentToolCall,
+  AgentToolCallResult,
+  AgentWorkflow,
+  FunctionAgent,
+  FunctionTool,
+} from "llamaindex";
+import { z } from "zod";
+
+const llm = new OpenAI({
+  model: "gpt-4o-mini",
+});
+
+// Define tools for the agents
+const temperatureConverterTool = FunctionTool.from(
+  ({ temperature }: { temperature: number }) => {
+    return ((temperature - 32) * 5) / 9;
+  },
+  {
+    description: "Convert a temperature from Fahrenheit to Celsius",
+    name: "fahrenheitToCelsius",
+    parameters: z.object({
+      temperature: z.number({
+        description: "The temperature in Fahrenheit",
+      }),
+    }),
+  },
+);
+
+const temperatureFetcherTool = FunctionTool.from(
+  ({ city }: { city: string }) => {
+    const temperature = Math.floor(Math.random() * 58) + 32;
+    return `The current temperature in ${city} is ${temperature}°F`;
+  },
+  {
+    description: "Fetch the temperature (in Fahrenheit) for a city",
+    name: "fetchTemperature",
+    parameters: z.object({
+      city: z.string({
+        description: "The city to fetch the temperature for",
+      }),
+    }),
+  },
+);
+
+// Create agents
+async function multiWeatherAgent() {
+  const converterAgent = new FunctionAgent({
+    name: "TemperatureConverterAgent",
+    description:
+      "An agent that can convert temperatures from Fahrenheit to Celsius.",
+    tools: [temperatureConverterTool],
+    llm,
+  });
+
+  const weatherAgent = new FunctionAgent({
+    name: "FetchWeatherAgent",
+    description: "An agent that can get the weather in a city. ",
+    systemPrompt:
+      "If you can't answer the user question, hand off to other agents.",
+    tools: [temperatureFetcherTool],
+    llm,
+    // Define which next agents can be called next if this agent cannot complete the task
+    // Can be passed as agent name, e.g. "TemperatureConverterAgent"
+    canHandoffTo: [converterAgent],
+  });
+
+  // Create agent workflow with the agents
+  const workflow = new AgentWorkflow({
+    agents: [weatherAgent, converterAgent],
+    rootAgent: weatherAgent,
+    verbose: false,
+  });
+
+  // Ask the agent to get the weather in a city
+  const context = workflow.run(
+    "What is the weather in San Francisco in Celsius?",
+  );
+  // Stream the events
+  for await (const event of context) {
+    // These events might be useful for UI
+    if (
+      event instanceof AgentToolCall ||
+      event instanceof AgentToolCallResult ||
+      event instanceof AgentOutput ||
+      event instanceof AgentInput ||
+      event instanceof StopEvent
+    ) {
+      console.log(event);
+    } else if (event instanceof AgentStream) {
+      for (const chunk of event.data.delta) {
+        process.stdout.write(chunk);
+      }
+    }
+  }
+}
+
+multiWeatherAgent().catch((error) => {
+  console.error("Error:", error);
+});

examples/agentworkflow/single_agent.ts

@@ -0,0 +1,37 @@
+/**
+ * This example shows how to use AgentWorkflow as a single agent with tools
+ */
+import { OpenAI } from "@llamaindex/openai";
+import { AgentWorkflow } from "llamaindex";
+import { getWeatherTool } from "../agent/utils/tools";
+
+const llm = new OpenAI({
+  model: "gpt-4o",
+});
+
+async function singleWeatherAgent() {
+  const workflow = AgentWorkflow.fromTools({
+    tools: [getWeatherTool],
+    llm,
+    verbose: false,
+  });
+
+  const workflowContext = workflow.run(
+    "What's the weather like in San Francisco?",
+  );
+  const sfResult = await workflowContext;
+  // The weather in San Francisco, CA is currently sunny.
+  console.log(`${JSON.stringify(sfResult, null, 2)}`);
+
+  // Reuse the context from the previous run
+  const workflowContext2 = workflow.run("Compare it with California?", {
+    context: workflowContext.data,
+  });
+  const caResult = await workflowContext2;
+  // Both San Francisco and California are currently experiencing sunny weather.
+  console.log(`${JSON.stringify(caResult, null, 2)}`);
+}
+
+singleWeatherAgent().catch((error) => {
+  console.error("Error:", error);
+});

examples/anthropic/agent.ts

@@ -8,7 +8,7 @@ Settings.callbackManager.on("llm-tool-call", (event) => {
 
 const anthropic = new Anthropic({
   apiKey: process.env.ANTHROPIC_API_KEY,
-  model: "claude-3-5-sonnet",
+  model: "claude-3-7-sonnet",
 });
 
 const agent = new AnthropicAgent({

examples/anthropic/chat.ts

@@ -3,7 +3,7 @@ import { Anthropic } from "@llamaindex/anthropic";
 (async () => {
   const anthropic = new Anthropic({
     apiKey: process.env.ANTHROPIC_API_KEY,
-    model: "claude-3-opus",
+    model: "claude-3-7-sonnet",
   });
   const result = await anthropic.chat({
     messages: [
@@ -15,5 +15,5 @@ import { Anthropic } from "@llamaindex/anthropic";
       },
     ],
   });
-  console.log(result);
+  console.log(result.message.content);
 })();

examples/anthropic/chat_interactive.ts

@@ -6,7 +6,7 @@ import readline from "node:readline/promises";
 (async () => {
   const llm = new Anthropic({
     apiKey: process.env.ANTHROPIC_API_KEY,
-    model: "claude-3-opus",
+    model: "claude-3-7-sonnet",
   });
   // chatHistory will store all the messages in the conversation
   const chatHistory = new ChatMemoryBuffer({

examples/anthropic/prompt-caching.ts

@@ -2,7 +2,7 @@ import { Anthropic } from "@llamaindex/anthropic";
 
 async function main() {
   const anthropic = new Anthropic({
-    model: "claude-3-5-sonnet-20241022",
+    model: "claude-3-7-sonnet",
   });
 
   const entireBook = await fetch(

examples/anthropic/stream.ts

@@ -3,7 +3,7 @@ import { Anthropic } from "@llamaindex/anthropic";
 (async () => {
   const anthropic = new Anthropic({
     apiKey: process.env.ANTHROPIC_API_KEY,
-    model: "claude-3-5-sonnet",
+    model: "claude-3-7-sonnet",
   });
   const stream = await anthropic.chat({
     messages: [

examples/anthropic/thinking.ts

@@ -0,0 +1,32 @@
+import { Anthropic } from "@llamaindex/anthropic";
+
+(async () => {
+  const anthropic = new Anthropic({
+    model: "claude-3-7-sonnet",
+    maxTokens: 20000,
+    additionalChatOptions: {
+      thinking: {
+        type: "enabled",
+        budget_tokens: 16000,
+      },
+    },
+  });
+  const result = await anthropic.chat({
+    messages: [
+      {
+        role: "user",
+        content:
+          "Are there an infinite number of prime numbers such that n mod 4 == 3?",
+      },
+    ],
+    stream: true,
+  });
+  console.log("Thinking...");
+  for await (const chunk of result) {
+    if (chunk.delta) {
+      process.stdout.write(chunk.delta);
+    } else if (chunk.options?.thinking) {
+      process.stdout.write(chunk.options.thinking);
+    }
+  }
+})();

examples/astradb/query.ts

@@ -1,5 +1,5 @@
 import { AstraDBVectorStore } from "@llamaindex/astra";
-import { VectorStoreIndex, serviceContextFromDefaults } from "llamaindex";
+import { VectorStoreIndex } from "llamaindex";
 
 const collectionName = "movie_reviews";
 
@@ -8,8 +8,7 @@ async function main() {
     const astraVS = new AstraDBVectorStore({ contentKey: "reviewtext" });
     await astraVS.connect(collectionName);
 
-    const ctx = serviceContextFromDefaults();
-    const index = await VectorStoreIndex.fromVectorStore(astraVS, ctx);
+    const index = await VectorStoreIndex.fromVectorStore(astraVS);
 
     const retriever = await index.asRetriever({ similarityTopK: 20 });
 

examples/chat-engine/keyword-index.ts

@@ -0,0 +1,15 @@
+import { Document, KeywordTableIndex } from "llamaindex";
+import essay from "../essay";
+
+async function main() {
+  const document = new Document({ text: essay });
+  const index = await KeywordTableIndex.fromDocuments([document]);
+  const chatEngine = index.asChatEngine();
+
+  const response = await chatEngine.chat({
+    message: "What is Harsh Mistress?",
+  });
+  console.log(response.message.content);
+}
+
+main().catch(console.error);

examples/chat-engine/streaming.ts

@@ -0,0 +1,25 @@
+import { LLMAgent } from "llamaindex";
+import { stdin as input, stdout as output } from "node:process";
+import readline from "node:readline/promises";
+
+const agent = new LLMAgent({ tools: [] });
+
+(async () => {
+  const rl = readline.createInterface({ input, output });
+
+  while (true) {
+    const query = await rl.question("User: ");
+
+    const startTime = Date.now();
+    const stream = await agent.chat({ message: query, stream: true });
+    const timeToGetFirstChunk = Date.now() - startTime;
+    process.stdout.write(
+      `Time to get first chunk from LLMAgent: ${timeToGetFirstChunk}ms\n`,
+    );
+    process.stdout.write("Assistant with LLMAgent: ");
+    for await (const chunk of stream) {
+      process.stdout.write(chunk.response);
+    }
+    process.stdout.write("\n");
+  }
+})();

examples/chat-engine/summary-index.ts

@@ -0,0 +1,17 @@
+import { Document, SummaryIndex, SummaryRetrieverMode } from "llamaindex";
+import essay from "../essay";
+
+async function main() {
+  const document = new Document({ text: essay });
+  const index = await SummaryIndex.fromDocuments([document]);
+  const chatEngine = index.asChatEngine({
+    mode: SummaryRetrieverMode.LLM,
+  });
+
+  const response = await chatEngine.chat({
+    message: "Summary about the author",
+  });
+  console.log(response.message.content);
+}
+
+main().catch(console.error);

examples/chat-engine/vector-store-index.ts

@@ -0,0 +1,15 @@
+import { Document, VectorStoreIndex } from "llamaindex";
+import essay from "../essay";
+
+async function main() {
+  const document = new Document({ text: essay });
+  const index = await VectorStoreIndex.fromDocuments([document]);
+  const chatEngine = index.asChatEngine({ similarityTopK: 5 });
+
+  const response = await chatEngine.chat({
+    message: "What did I work on in February 2021?",
+  });
+  console.log(response.message.content);
+}
+
+main().catch(console.error);

examples/directory.ts

@@ -1,4 +1,4 @@
-import { SimpleDirectoryReader } from "llamaindex";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 
 function callback(
   category: string,

examples/firestore/.env.template

@@ -0,0 +1,4 @@
+GCP_PROJECT_ID=
+GCP_CREDENTIALS=
+FIRESTORE_DB=
+OPENAI_API_KEY=

examples/firestore/README.md

@@ -0,0 +1,35 @@
+# Firestore Vector Store
+
+Here are some sample scripts which work with loading and querying data from a Firestore Vector Store.
+
+## Prerequisites
+
+- A Firestore Database
+  - Hosted https://console.firebase.google.com/
+- An OpenAI API Key
+
+## Setup
+
+1. Set your env variables:
+
+- `FIRESTORE_DB`: Name of your Firestore database
+- `GCP_PROJECT_ID`: Your GCP project ID
+- `GCP_CREDENTIALS`: Your GCP credentials JSON
+- `OPENAI_API_KEY`: Your OpenAI key
+
+2. `cd` Into the `examples` directory
+3. run `npm i`
+
+## Load the data
+
+This sample loads the same dataset of movie reviews as sample dataset
+
+run `npx tsx firestore/load.ts`
+
+## Use RAG to Query the data
+
+run `npx tsx firestore/query.ts`
+
+## Delete the data
+
+run `npx tsx firestore/delete.ts`

examples/firestore/delete.ts

@@ -0,0 +1,32 @@
+import { CollectionReference } from "@google-cloud/firestore";
+import "dotenv/config";
+
+import { FirestoreVectorStore } from "@llamaindex/firestore";
+import { OpenAIEmbedding, Settings } from "llamaindex";
+
+const indexName = "MovieReviews";
+
+Settings.embedModel = new OpenAIEmbedding();
+
+async function main() {
+  try {
+    const vectorStore = new FirestoreVectorStore({
+      clientOptions: {
+        credentials: JSON.parse(process.env.GCP_CREDENTIALS!),
+        projectId: process.env.GCP_PROJECT_ID!,
+        databaseId: process.env.FIRESTORE_DB!,
+        ignoreUndefinedProperties: true,
+      },
+      collectionName: indexName,
+      customCollectionReference: (rootCollection: CollectionReference) => {
+        return rootCollection.doc("accountId-123").collection("vectors");
+      },
+    });
+
+    vectorStore.delete("movie_reviews.csv");
+  } catch (e) {
+    console.error(e);
+  }
+}
+
+void main();

examples/firestore/load.ts

@@ -0,0 +1,44 @@
+import { CollectionReference } from "@google-cloud/firestore";
+import { CSVReader } from "@llamaindex/readers/csv";
+import "dotenv/config";
+
+import {
+  OpenAIEmbedding,
+  Settings,
+  storageContextFromDefaults,
+  VectorStoreIndex,
+} from "llamaindex";
+
+import { FirestoreVectorStore } from "@llamaindex/firestore";
+
+const indexName = "MovieReviews";
+
+Settings.embedModel = new OpenAIEmbedding();
+
+async function main() {
+  try {
+    const reader = new CSVReader(false);
+    const docs = await reader.loadData("./data/movie_reviews.csv");
+
+    const vectorStore = new FirestoreVectorStore({
+      clientOptions: {
+        credentials: JSON.parse(process.env.GCP_CREDENTIALS!),
+        projectId: process.env.GCP_PROJECT_ID!,
+        databaseId: process.env.FIRESTORE_DB!,
+        ignoreUndefinedProperties: true,
+      },
+      collectionName: indexName,
+      customCollectionReference: (rootCollection: CollectionReference) => {
+        return rootCollection.doc("accountId-123").collection("vectors");
+      },
+    });
+
+    const storageContext = await storageContextFromDefaults({ vectorStore });
+
+    await VectorStoreIndex.fromDocuments(docs, { storageContext });
+  } catch (e) {
+    console.error(e);
+  }
+}
+
+void main();

examples/firestore/query.ts

@@ -0,0 +1,58 @@
+import "dotenv/config";
+
+import { OpenAIEmbedding, Settings, VectorStoreIndex } from "llamaindex";
+
+import { CollectionReference } from "@google-cloud/firestore";
+import { FirestoreVectorStore } from "@llamaindex/firestore";
+
+const indexName = "MovieReviews";
+
+Settings.embedModel = new OpenAIEmbedding();
+
+async function main() {
+  try {
+    const vectorStore = new FirestoreVectorStore({
+      clientOptions: {
+        credentials: JSON.parse(process.env.GCP_CREDENTIALS!),
+        projectId: process.env.GCP_PROJECT_ID!,
+        databaseId: process.env.FIRESTORE_DB!,
+        ignoreUndefinedProperties: true,
+      },
+      collectionName: indexName,
+      customCollectionReference: (rootCollection: CollectionReference) => {
+        return rootCollection.doc("accountId-123").collection("vectors");
+      },
+    });
+    const index = await VectorStoreIndex.fromVectorStore(vectorStore);
+    const retriever = index.asRetriever({ similarityTopK: 20 });
+
+    const queryEngine = index.asQueryEngine({ retriever });
+    const query = "Get all movie titles.";
+    const results = await queryEngine.query({ query });
+    console.log(`Query from ${results.sourceNodes?.length} nodes`);
+    console.log(results.response);
+
+    console.log("\n=====\nQuerying the index with filters");
+    const queryEngineWithFilters = index.asQueryEngine({
+      retriever,
+      preFilters: {
+        filters: [
+          {
+            key: "file_name",
+            value: "movie_reviews.csv",
+            operator: "==",
+          },
+        ],
+      },
+    });
+    const resultAfterFilter = await queryEngineWithFilters.query({
+      query: "Get all movie titles.",
+    });
+    console.log(`Query from ${resultAfterFilter.sourceNodes?.length} nodes`);
+    console.log(resultAfterFilter.response);
+  } catch (e) {
+    console.error(e);
+  }
+}
+
+void main();

examples/mongo.ts

@@ -30,13 +30,12 @@ async function main() {
 
   // Split text and create embeddings. Store them in a VectorStoreIndex
   // var storageContext = await storageContextFromDefaults({});
-  // var serviceContext = serviceContextFromDefaults({});
   // const docStore = storageContext.docStore;
 
   // for (const doc of documents) {
   //   docStore.setDocumentHash(doc.id_, doc.hash);
   // }
-  // const nodes = serviceContext.nodeParser.getNodesFromDocuments(documents);
+  // const nodes = Settings.nodeParser.getNodesFromDocuments(documents);
   // console.log(nodes);
 
   //

examples/multimodal/jina.ts

@@ -1,9 +1,9 @@
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 import {
   ImageDocument,
   JinaAIEmbedding,
   similarity,
   SimilarityType,
-  SimpleDirectoryReader,
 } from "llamaindex";
 import path from "path";
 

examples/multimodal/load.ts

@@ -1,4 +1,5 @@
-import { Settings, SimpleDirectoryReader, VectorStoreIndex } from "llamaindex";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
+import { Settings, VectorStoreIndex } from "llamaindex";
 import path from "path";
 import { getStorageContext } from "./storage";
 

examples/multimodal/storage.ts

@@ -1,17 +1,16 @@
-import { storageContextFromDefaults } from "llamaindex";
+import { ClipEmbedding } from "@llamaindex/clip";
+import { path } from "@llamaindex/env";
+import { SimpleVectorStore, storageContextFromDefaults } from "llamaindex";
 
 // set up store context with two vector stores, one for text, the other for images
 export async function getStorageContext() {
   return await storageContextFromDefaults({
     persistDir: "storage",
-    storeImages: true,
-    // if storeImages is true, the following vector store will be added
-    // vectorStores: {
-    //   IMAGE: SimpleVectorStore.fromPersistDir(
-    //     `${persistDir}/images`,
-    //     fs,
-    //     new ClipEmbedding(),
-    //   ),
-    // },
+    vectorStores: {
+      IMAGE: await SimpleVectorStore.fromPersistDir(
+        path.join("storage", "images"),
+        new ClipEmbedding(),
+      ),
+    },
   });
 }

examples/ollama.ts

@@ -1,5 +1,4 @@
-import { OllamaEmbedding } from "@llamaindex/ollama";
-import { Ollama } from "llamaindex/llm/ollama";
+import { Ollama, OllamaEmbedding } from "@llamaindex/ollama";
 
 (async () => {
   const llm = new Ollama({

examples/openai.ts

@@ -1,7 +1,7 @@
 import { OpenAI, OpenAIEmbedding } from "@llamaindex/openai";
 
 (async () => {
-  const llm = new OpenAI({ model: "gpt-4-1106-preview", temperature: 0.1 });
+  const llm = new OpenAI({ model: "gpt-4.5-preview", temperature: 0.1 });
 
   // complete api
   const response1 = await llm.complete({ prompt: "How are you?" });

examples/package.json

@@ -1,63 +1,69 @@
 {
   "name": "@llamaindex/examples",
+  "version": "0.2.5",
   "private": true,
-  "version": "0.1.3",
+  "scripts": {
+    "lint": "eslint .",
+    "start": "tsx ./starter.ts"
+  },
   "dependencies": {
     "@ai-sdk/openai": "^1.0.5",
     "@azure/cosmos": "^4.1.1",
     "@azure/identity": "^4.4.1",
     "@azure/search-documents": "^12.1.0",
-    "@llamaindex/vercel": "^0.0.10",
-    "@llamaindex/workflow": "^0.0.10",
+    "@llamaindex/anthropic": "^0.2.3",
+    "@llamaindex/astra": "^0.0.10",
+    "@llamaindex/azure": "^0.1.5",
+    "@llamaindex/chroma": "^0.0.10",
+    "@llamaindex/clip": "^0.0.41",
+    "@llamaindex/cloud": "^3.0.6",
+    "@llamaindex/cohere": "^0.0.10",
+    "@llamaindex/core": "^0.5.5",
+    "@llamaindex/deepinfra": "^0.0.41",
+    "@llamaindex/env": "^0.1.28",
+    "@llamaindex/firestore": "^1.0.3",
+    "@llamaindex/google": "^0.0.12",
+    "@llamaindex/groq": "^0.0.56",
+    "@llamaindex/huggingface": "^0.0.41",
+    "@llamaindex/milvus": "^0.1.5",
+    "@llamaindex/mistral": "^0.0.10",
+    "@llamaindex/mixedbread": "^0.0.10",
+    "@llamaindex/mongodb": "^0.0.10",
+    "@llamaindex/node-parser": "^1.0.5",
+    "@llamaindex/ollama": "^0.0.45",
+    "@llamaindex/openai": "^0.1.57",
+    "@llamaindex/pinecone": "^0.0.10",
+    "@llamaindex/portkey-ai": "^0.0.38",
+    "@llamaindex/postgres": "^0.0.38",
+    "@llamaindex/qdrant": "^0.1.5",
+    "@llamaindex/readers": "^2.0.5",
+    "@llamaindex/replicate": "^0.0.38",
+    "@llamaindex/upstash": "^0.0.10",
+    "@llamaindex/vercel": "^0.0.16",
+    "@llamaindex/vllm": "^0.0.27",
+    "@llamaindex/voyage-ai": "^1.0.2",
+    "@llamaindex/weaviate": "^0.0.10",
+    "@llamaindex/workflow": "^0.0.12",
     "@notionhq/client": "^2.2.15",
     "@pinecone-database/pinecone": "^4.0.0",
     "@vercel/postgres": "^0.10.0",
     "ai": "^4.0.0",
+    "ajv": "^8.17.1",
     "commander": "^12.1.0",
     "dotenv": "^16.4.5",
     "js-tiktoken": "^1.0.14",
-    "llamaindex": "^0.8.37",
+    "llamaindex": "^0.9.6",
     "mongodb": "6.7.0",
+    "pathe": "^1.1.2",
     "postgres": "^3.4.4",
-    "ajv": "^8.17.1",
     "wikipedia": "^2.1.2",
-    "@llamaindex/openai": "workspace:*",
-    "@llamaindex/cloud": "workspace:*",
-    "@llamaindex/anthropic": "workspace:*",
-    "@llamaindex/clip": "workspace:*",
-    "@llamaindex/azure": "workspace:*",
-    "@llamaindex/deepinfra": "workspace:*",
-    "@llamaindex/groq": "workspace:*",
-    "@llamaindex/huggingface": "workspace:*",
-    "@llamaindex/node-parser": "workspace:*",
-    "@llamaindex/ollama": "workspace:*",
-    "@llamaindex/portkey-ai": "workspace:*",
-    "@llamaindex/readers": "workspace:*",
-    "@llamaindex/replicate": "workspace:*",
-    "@llamaindex/vllm": "workspace:*",
-    "@llamaindex/postgres": "workspace:*",
-    "@llamaindex/astra": "workspace:*",
-    "@llamaindex/milvus": "workspace:*",
-    "@llamaindex/chroma": "workspace:*",
-    "@llamaindex/mongodb": "workspace:*",
-    "@llamaindex/pinecone": "workspace:*",
-    "@llamaindex/qdrant": "workspace:*",
-    "@llamaindex/upstash": "workspace:*",
-    "@llamaindex/weaviate": "workspace:*",
-    "@llamaindex/google": "workspace:*",
-    "@llamaindex/mistral": "workspace:*",
-    "@llamaindex/mixedbread": "workspace:*",
-    "@llamaindex/cohere": "workspace:*"
+    "zod": "^3.23.8"
   },
   "devDependencies": {
     "@types/node": "^22.9.0",
     "tsx": "^4.19.0",
     "typescript": "^5.7.2"
   },
-  "scripts": {
-    "lint": "eslint .",
-    "start": "tsx ./starter.ts"
-  },
   "stackblitz": {
     "startCommand": "npm start"
   }

examples/pinecone-vector-store/load-docs.ts

@@ -1,11 +1,8 @@
 // load-docs.ts
 import { PineconeVectorStore } from "@llamaindex/pinecone";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 import fs from "fs/promises";
-import {
-  SimpleDirectoryReader,
-  storageContextFromDefaults,
-  VectorStoreIndex,
-} from "llamaindex";
+import { storageContextFromDefaults, VectorStoreIndex } from "llamaindex";
 
 async function getSourceFilenames(sourceDir: string) {
   return await fs

examples/readers/package.json

@@ -19,9 +19,9 @@
     "start:obsidian": "node --import tsx ./src/obsidian.ts"
   },
   "dependencies": {
-    "@llamaindex/readers": "*",
-    "llamaindex": "*",
-    "@llamaindex/cloud": "*"
+    "@llamaindex/cloud": "workspace:* || ^2.0.24",
+    "@llamaindex/readers": "workspace:* || ^1.0.25",
+    "llamaindex": "workspace:* || ^0.8.37"
   },
   "devDependencies": {
     "@types/node": "^22.9.0",

examples/readers/src/custom-simple-directory-reader.ts

@@ -1,10 +1,10 @@
-import { TextFileReader } from "@llamaindex/readers/text";
-import type { Document, Metadata } from "llamaindex";
 import {
   FILE_EXT_TO_READER,
-  FileReader,
   SimpleDirectoryReader,
-} from "llamaindex";
+} from "@llamaindex/readers/directory";
+import { TextFileReader } from "@llamaindex/readers/text";
+import type { Document, Metadata } from "llamaindex";
+import { FileReader } from "llamaindex";
 
 class ZipReader extends FileReader {
   loadDataAsContent(fileContent: Uint8Array): Promise<Document<Metadata>[]> {

examples/readers/src/simple-directory-reader-with-llamaparse.ts

@@ -1,5 +1,6 @@
 import { LlamaParseReader } from "@llamaindex/cloud";
-import { SimpleDirectoryReader, VectorStoreIndex } from "llamaindex";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
+import { VectorStoreIndex } from "llamaindex";
 
 async function main() {
   const reader = new SimpleDirectoryReader();

examples/readers/src/simple-directory-reader.ts

@@ -1,6 +1,4 @@
-import { SimpleDirectoryReader } from "llamaindex";
-// or
-// import { SimpleDirectoryReader } from 'llamaindex'
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 
 const reader = new SimpleDirectoryReader();
 const documents = await reader.loadData("../data");

examples/routerQueryEngine.ts

@@ -1,9 +1,9 @@
 import { OpenAI } from "@llamaindex/openai";
+import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
 import {
   RouterQueryEngine,
   SentenceSplitter,
   Settings,
-  SimpleDirectoryReader,
   SummaryIndex,
   VectorStoreIndex,
 } from "llamaindex";

examples/starter.ts

@@ -3,6 +3,18 @@ import fs from "node:fs/promises";
 import { createInterface } from "node:readline/promises";
 
 async function main() {
+  const rl = createInterface({ input: process.stdin, output: process.stdout });
+
+  if (!process.env.OPENAI_API_KEY) {
+    console.log("OpenAI API key not found in environment variables.");
+    console.log(
+      "You can get an API key at https://platform.openai.com/account/api-keys",
+    );
+    process.env.OPENAI_API_KEY = await rl.question(
+      "Please enter your OpenAI API key: ",
+    );
+  }
+
   const path = "node_modules/llamaindex/examples/abramov.txt";
   const essay = await fs.readFile(path, "utf-8");
   const document = new Document({ text: essay, id_: path });
@@ -10,8 +22,6 @@ async function main() {
   const index = await VectorStoreIndex.fromDocuments([document]);
   const queryEngine = index.asQueryEngine();
 
-  const rl = createInterface({ input: process.stdin, output: process.stdout });
-
   console.log(
     "Try asking a question about the essay: https://github.com/run-llama/LlamaIndexTS/blob/main/packages/llamaindex/examples/abramov.txt",
     "\nExample: When did the author graduate from high school?",

examples/toolsStream.ts

@@ -15,7 +15,7 @@ async function main() {
     tools: [
       {
         metadata: {
-          name: "wikipedia_tool",
+          name: "wikipedia_search",
           description: "A tool that uses a query engine to search Wikipedia.",
           parameters: {
             type: "object",