Merge branch 'main' into ms/add-chat-ui-example

feat: add chat-ui example to new docs
2026-07-10 15:53:42 -04:00 · 2024-11-07 09:36:22 -08:00 · 2024-11-07 15:27:20 +08:00 · 2024-11-07 15:12:05 +08:00 · 2024-11-05 17:21:18 +07:00
407 changed files with 7159 additions and 16180 deletions
@@ -0,0 +1,5 @@
+---
+"chat-ui": patch
+---
+
+Add example using chat-ui components
@@ -0,0 +1,5 @@
+---
+"@llamaindex/community": patch
+---
+
+feat: added support for Haiku 3.5 via Bedrock
@@ -23,7 +23,7 @@ jobs:
    strategy:
      fail-fast: false
      matrix:
-        node-version: [18.x, 20.x, 22.x, 23.x]
+        node-version: [20.x, 22.x, 23.x]
    name: E2E on Node.js ${{ matrix.node-version }}
    runs-on: ubuntu-latest
    steps:
@@ -53,7 +53,7 @@ jobs:
    strategy:
      fail-fast: false
      matrix:
-        node-version: [18.x, 20.x, 22.x, 23.x]
+        node-version: [20.x, 22.x, 23.x]
    name: Test on Node.js ${{ matrix.node-version }}
    runs-on: ubuntu-latest
    steps:
@@ -119,7 +119,7 @@ jobs:
        run: pnpm run build
      - name: Build ${{ matrix.packages }}
        run: pnpm run build
-        working-directory: e2e/examples/${{ matrix.packages }}
+        working-directory: packages/llamaindex/e2e/examples/${{ matrix.packages }}

  typecheck-examples:
    runs-on: ubuntu-latest
@@ -2,58 +2,86 @@

 ## Structure

-LlamaIndex.TS uses pnpm monorepo.
+This is a monorepo built with Turborepo

-We recommend you to understand the basics of Node.js, TypeScript, pnpm, and of course, LLM before contributing.
+Right now, for first-time contributors, these three packages are of the highest importance:

-There are some important folders in the repository:
+- `packages/llamaindex` which is the main NPM library `llamaindex`
+- `examples` is where the demo code lives
+- `apps/docs` is where the code for the documentation of https://ts.llamaindex.ai/ is located

- `packages/*`: Contains the source code of the packages. Each package is a separate npm package.
-  - `llamaindex`: The starter package for LlamaIndex.TS, which contains the all sub-packages.
-  - `core`: The core package of LlamaIndex.TS, which contains the abstract classes and interfaces. It is designed for
-    all JS runtime environments.
-  - `env`: The environment package of LlamaIndex.TS, which contains the environment-specific classes and interfaces. It
-    includes compatibility layers for Node.js, Deno, Vercel Edge Runtime, Cloudflare Workers...
- `apps/*`: The applications based on LlamaIndex.TS.
-  - `next`: Our documentation website based on Next.js.
- `examples`: The code examples of LlamaIndex.TS using Node.js.
+### Turborepo docs
+
+You can checkout how Turborepo works using the default [README-turborepo.md](/README-turborepo.md)

 ## Getting Started

-Make sure you have Node.js LIS (Long-term Support) installed. You can check your Node.js version by running:
+Install NodeJS. Preferably v18 using nvm or n.
+
+Inside the LlamaIndexTS directory:

-```shell
-node -v
-# v20.x.x
 ```
-
-### Use pnpm
-
-```shell
-corepack enable
-```
-
-### Install dependencies
-
-```shell
+npm i -g pnpm ts-node
 pnpm install
 ```

-### Build the packages
+Note: we use pnpm in this repo, which has a lot of the same functionality and CLI options as npm but it does do some things better in a monorepo, like centralizing dependencies and caching.

-```shell
-# Build all packages
-turbo build --filter "./packages/*"
+PNPM's has documentation on its [workspace feature](https://pnpm.io/workspaces) and Turborepo had some [useful documentation also](https://turbo.build/repo/docs/core-concepts/monorepos/running-tasks).
+
+### Running Typescript
+
+When we publish to NPM we will have a tsc compiled version of the library in JS. For now, the easiest thing to do is use ts-node.
+
+### Test cases
+
+To run them, run
+
+```
+pnpm run test
+```
+
+To write new test cases write them in [packages/llamaindex/tests](/packages/llamaindex/tests)
+
+We use Vitest https://vitest.dev to write our test cases. Vitest comes with a bunch of built-in assertions using the expect function: https://vitest.dev/api/expect.html#expect
+
+### Demo applications
+
+There is an existing ["example"](/examples/README.md) demos folder with mainly NodeJS scripts. Feel free to add additional demos to that folder. If you would like to try out your changes in the `llamaindex` package with a new demo, you need to run the build command in the README.
+
+You can create new demo applications in the apps folder. Just run pnpm init in the folder after you create it to create its own package.json
+
+### Installing packages
+
+To install packages for a specific package or demo application, run
+
+```
+pnpm add [NPM Package] --filter [package or application i.e. llamaindex or docs]
+```
+
+To install packages for every package or application run
+
+```
+pnpm add -w [NPM Package]
 ```

 ### Docs

-See the [docs](./apps/next/README.md) for more information.
+To contribute to the docs, go to the docs website folder and run the Docusaurus instance.
+
+```bash
+cd apps/docs
+pnpm install
+pnpm start
+```
+
+That should start a webserver which will serve the docs on https://localhost:3000
+
+Any changes you make should be reflected in the browser. If you need to regenerate the API docs and find that your TSDoc isn't getting the updates, feel free to remove apps/docs/api. It will automatically regenerate itself when you run pnpm start again.

 ## Changeset

-We use [changesets](https://github.com/changesets/changesets) for managing versions and changelogs. To create a new
-changeset, run in the root folder:
+We use [changesets](https://github.com/changesets/changesets) for managing versions and changelogs. To create a new changeset, run in the root folder:

 ```
 pnpm changeset
@@ -67,6 +95,6 @@ The [Release Github Action](.github/workflows/release.yml) is automatically gene
 PR called "Release {version}".

 This PR will update the `package.json` and `CHANGELOG.md` files of each package according to
-the current changesets in the [.changeset](.changeset) folder.
+the current changesets in the [.changeset](.changeset/) folder.

 If this PR is merged it will automatically add version tags to the repository and publish the updated packages to NPM.
@@ -1,16 +1,12 @@
-<p align="center">
-  <img height="100" width="100" alt="LlamaIndex logo" src="https://ts.llamaindex.ai/square.svg" />
-</p>
-<h1 align="center">LlamaIndex.TS</h1>
-<h3 align="center">
-  Data framework for your LLM application.
-</h3>
+# LlamaIndex.TS

 [![NPM Version](https://img.shields.io/npm/v/llamaindex)](https://www.npmjs.com/package/llamaindex)
 [![NPM License](https://img.shields.io/npm/l/llamaindex)](https://www.npmjs.com/package/llamaindex)
 [![NPM Downloads](https://img.shields.io/npm/dm/llamaindex)](https://www.npmjs.com/package/llamaindex)
 [![Discord](https://img.shields.io/discord/1059199217496772688)](https://discord.com/invite/eN6D2HQ4aX)

+LlamaIndex is a data framework for your LLM application.
+
 Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in JS runtime environments with TypeScript support.

 Documentation: https://ts.llamaindex.ai/
@@ -1,184 +1,5 @@
 # docs

-## 0.0.133
-
-### Patch Changes
-
- c1850ee: feat: Amazon Nova support via Bedrock
- Updated dependencies [b504303]
- Updated dependencies [a0e6f57]
-  - llamaindex@0.8.27
-  - @llamaindex/examples@0.0.20
-
-## 0.0.132
-
-### Patch Changes
-
- Updated dependencies [3d1808b]
-  - llamaindex@0.8.26
-  - @llamaindex/examples@0.0.19
-
-## 0.0.131
-
-### Patch Changes
-
- llamaindex@0.8.25
- @llamaindex/examples@0.0.18
-
-## 0.0.130
-
-### Patch Changes
-
- Updated dependencies [fd38a25]
-  - @llamaindex/examples@0.0.17
-
-## 0.0.129
-
-### Patch Changes
-
- Updated dependencies [515f2c1]
-  - llamaindex@0.8.24
-
-## 0.0.128
-
-### Patch Changes
-
- llamaindex@0.8.23
-
-## 0.0.127
-
-### Patch Changes
-
- Updated dependencies [819af45]
-  - llamaindex@0.8.22
-
-## 0.0.126
-
-### Patch Changes
-
- Updated dependencies [83c3897]
- Updated dependencies [efa2211]
-  - llamaindex@0.8.21
-
-## 0.0.125
-
-### Patch Changes
-
- Updated dependencies [02b22da]
-  - llamaindex@0.8.20
-
-## 0.0.124
-
-### Patch Changes
-
- Updated dependencies [90d265c]
-  - llamaindex@0.8.19
-
-## 0.0.123
-
-### Patch Changes
-
- Updated dependencies [d17450f]
-  - llamaindex@0.8.18
-
-## 0.0.122
-
-### Patch Changes
-
- llamaindex@0.8.17
-
-## 0.0.121
-
-### Patch Changes
-
- llamaindex@0.8.16
-
-## 0.0.120
-
-### Patch Changes
-
- Updated dependencies [3d503cb]
- Updated dependencies [5dae534]
-  - llamaindex@0.8.15
-
-## 0.0.119
-
-### Patch Changes
-
- Updated dependencies [630b425]
-  - llamaindex@0.8.14
-
-## 0.0.118
-
-### Patch Changes
-
- llamaindex@0.8.13
- @llamaindex/examples@0.0.16
-
-## 0.0.117
-
-### Patch Changes
-
- @llamaindex/examples@0.0.15
-
-## 0.0.116
-
-### Patch Changes
-
- llamaindex@0.8.12
-
-## 0.0.115
-
-### Patch Changes
-
- llamaindex@0.8.11
-
-## 0.0.114
-
-### Patch Changes
-
- Updated dependencies [f066e50]
-  - llamaindex@0.8.10
-  - @llamaindex/examples@0.0.14
-
-## 0.0.113
-
-### Patch Changes
-
- Updated dependencies [4fc001c]
- Updated dependencies [4d4cd8a]
-  - llamaindex@0.8.9
-
-## 0.0.112
-
-### Patch Changes
-
- Updated dependencies [ad85bd0]
-  - llamaindex@0.8.8
-  - @llamaindex/examples@0.0.13
-
-## 0.0.111
-
-### Patch Changes
-
- llamaindex@0.8.7
-
-## 0.0.110
-
-### Patch Changes
-
- Updated dependencies [95a5cc6]
-  - llamaindex@0.8.6
-
-## 0.0.109
-
-### Patch Changes
-
- Updated dependencies [14cc9eb]
- Updated dependencies [a6db5dd]
- Updated dependencies [396b1e1]
-  - llamaindex@0.8.5
-
 ## 0.0.108

 ### Patch Changes
@@ -37,9 +37,6 @@ META_LLAMA3_2_1B_INSTRUCT = "meta.llama3-2-1b-instruct-v1:0"; // only available
 META_LLAMA3_2_3B_INSTRUCT = "meta.llama3-2-3b-instruct-v1:0"; // only available via inference endpoints (see below)
 META_LLAMA3_2_11B_INSTRUCT = "meta.llama3-2-11b-instruct-v1:0"; // only available via inference endpoints (see below), multimodal and function call supported
 META_LLAMA3_2_90B_INSTRUCT = "meta.llama3-2-90b-instruct-v1:0"; // only available via inference endpoints (see below), multimodal and function call supported
-AMAZON_NOVA_PRO_1 = "amazon.nova-pro-v1:0";
-AMAZON_NOVA_LITE_1 = "amazon.nova-lite-v1:0";
-AMAZON_NOVA_MICRO_1 = "amazon.nova-micro-v1:0";
 ```

 You can also use Bedrock's Inference endpoints by using the model names:
@@ -56,9 +53,6 @@ US_META_LLAMA_3_2_1B_INSTRUCT = "us.meta.llama3-2-1b-instruct-v1:0";
 US_META_LLAMA_3_2_3B_INSTRUCT = "us.meta.llama3-2-3b-instruct-v1:0";
 US_META_LLAMA_3_2_11B_INSTRUCT = "us.meta.llama3-2-11b-instruct-v1:0";
 US_META_LLAMA_3_2_90B_INSTRUCT = "us.meta.llama3-2-90b-instruct-v1:0";
-US_AMAZON_NOVA_PRO_1 = "us.amazon.nova-pro-v1:0";
-US_AMAZON_NOVA_LITE_1 = "us.amazon.nova-lite-v1:0";
-US_AMAZON_NOVA_MICRO_1 = "us.amazon.nova-micro-v1:0";

 // EU
 EU_ANTHROPIC_CLAUDE_3_HAIKU = "eu.anthropic.claude-3-haiku-20240307-v1:0";
@@ -62,12 +62,6 @@ const config = {
    ({
      // Replace with your project's social card
      image: "img/favicon.png", // TODO change this
-      announcementBar: {
-        id: "migrate_to_next",
-        content:
-          'We are migrating to Next.js based documentation. Check it out <a href="https://ts.llamaindex.ai/docs/llamaindex">here</a>!',
-        isCloseable: false,
-      },
      navbar: {
        title: "LlamaIndex.TS",
        logo: {
@@ -1,6 +1,6 @@
 {
  "name": "docs",
-  "version": "0.0.133",
+  "version": "0.0.108",
  "private": true,
  "scripts": {
    "docusaurus": "docusaurus",
@@ -15,23 +15,23 @@
    "typecheck": "tsc"
  },
  "dependencies": {
-    "@docusaurus/core": "3.6.1",
-    "@docusaurus/remark-plugin-npm2yarn": "3.6.1",
+    "@docusaurus/core": "3.6.0",
+    "@docusaurus/remark-plugin-npm2yarn": "3.6.0",
    "@llamaindex/examples": "workspace:*",
    "@mdx-js/react": "^3.1.0",
    "clsx": "^2.1.1",
    "llamaindex": "workspace:*",
-    "postcss": "^8.4.49",
+    "postcss": "^8.4.47",
    "prism-react-renderer": "^2.4.0",
    "raw-loader": "^4.0.2",
    "react": "^18.3.1",
    "react-dom": "18.3.1"
  },
  "devDependencies": {
-    "@docusaurus/module-type-aliases": "3.6.1",
-    "@docusaurus/preset-classic": "3.6.1",
-    "@docusaurus/theme-classic": "3.6.1",
-    "@docusaurus/types": "3.6.1",
+    "@docusaurus/module-type-aliases": "3.6.0",
+    "@docusaurus/preset-classic": "3.6.0",
+    "@docusaurus/theme-classic": "3.6.0",
+    "@docusaurus/types": "3.6.0",
    "@tsconfig/docusaurus": "2.0.3",
    "@types/node": "^22.9.0",
    "docusaurus-plugin-typedoc": "1.0.5",
@@ -1,283 +1,5 @@
 # @llamaindex/doc

-## 0.0.31
-
-### Patch Changes
-
- Updated dependencies [b504303]
- Updated dependencies [e0f6cc3]
- Updated dependencies [a0e6f57]
-  - llamaindex@0.8.27
-  - @llamaindex/core@0.4.18
-  - @llamaindex/cloud@2.0.18
-  - @llamaindex/node-parser@0.0.19
-  - @llamaindex/openai@0.1.43
-  - @llamaindex/readers@1.0.20
-  - @llamaindex/workflow@0.0.8
-
-## 0.0.30
-
-### Patch Changes
-
- Updated dependencies [3d1808b]
-  - @llamaindex/core@0.4.17
-  - llamaindex@0.8.26
-  - @llamaindex/openai@0.1.42
-  - @llamaindex/cloud@2.0.17
-  - @llamaindex/node-parser@0.0.18
-  - @llamaindex/readers@1.0.19
-
-## 0.0.29
-
-### Patch Changes
-
- Updated dependencies [7e8230b]
- Updated dependencies [8be4589]
-  - @llamaindex/readers@1.0.18
-  - @llamaindex/cloud@2.0.16
-  - @llamaindex/core@0.4.16
-  - @llamaindex/node-parser@0.0.17
-  - @llamaindex/openai@0.1.41
-  - @llamaindex/workflow@0.0.7
-  - llamaindex@0.8.25
-
-## 0.0.28
-
-### Patch Changes
-
- fd38a25: Add vercel tool adapter to use query engine tool
-
-## 0.0.27
-
-### Patch Changes
-
- Updated dependencies [515f2c1]
-  - llamaindex@0.8.24
-
-## 0.0.26
-
-### Patch Changes
-
- @llamaindex/cloud@2.0.15
- @llamaindex/core@0.4.15
- llamaindex@0.8.23
- @llamaindex/node-parser@0.0.16
- @llamaindex/openai@0.1.40
- @llamaindex/readers@1.0.17
-
-## 0.0.25
-
-### Patch Changes
-
- Updated dependencies [819af45]
-  - llamaindex@0.8.22
-  - @llamaindex/cloud@2.0.14
-  - @llamaindex/core@0.4.14
-  - @llamaindex/node-parser@0.0.15
-  - @llamaindex/openai@0.1.39
-  - @llamaindex/readers@1.0.16
-
-## 0.0.24
-
-### Patch Changes
-
- Updated dependencies [83c3897]
- Updated dependencies [efa2211]
-  - llamaindex@0.8.21
-
-## 0.0.23
-
-### Patch Changes
-
- Updated dependencies [02b22da]
-  - llamaindex@0.8.20
-
-## 0.0.22
-
-### Patch Changes
-
- Updated dependencies [90d265c]
-  - @llamaindex/cloud@2.0.13
-  - @llamaindex/core@0.4.13
-  - llamaindex@0.8.19
-  - @llamaindex/node-parser@0.0.14
-  - @llamaindex/readers@1.0.15
-  - @llamaindex/openai@0.1.38
-
-## 0.0.21
-
-### Patch Changes
-
- Updated dependencies [d17450f]
- Updated dependencies [ef4f63d]
-  - llamaindex@0.8.18
-  - @llamaindex/core@0.4.12
-  - @llamaindex/cloud@2.0.12
-  - @llamaindex/node-parser@0.0.13
-  - @llamaindex/openai@0.1.37
-  - @llamaindex/readers@1.0.14
-
-## 0.0.20
-
-### Patch Changes
-
- Updated dependencies [6d22fa2]
-  - @llamaindex/core@0.4.11
-  - @llamaindex/cloud@2.0.11
-  - llamaindex@0.8.17
-  - @llamaindex/node-parser@0.0.12
-  - @llamaindex/openai@0.1.36
-  - @llamaindex/readers@1.0.13
-
-## 0.0.19
-
-### Patch Changes
-
- Updated dependencies [e60328b]
-  - @llamaindex/readers@1.0.12
-  - llamaindex@0.8.16
-
-## 0.0.18
-
-### Patch Changes
-
- Updated dependencies [3d503cb]
- Updated dependencies [5dae534]
-  - llamaindex@0.8.15
-
-## 0.0.17
-
-### Patch Changes
-
- Updated dependencies [630b425]
-  - llamaindex@0.8.14
-
-## 0.0.16
-
-### Patch Changes
-
- Updated dependencies [a7b0ac3]
- Updated dependencies [ee20c44]
- Updated dependencies [c69605f]
-  - @llamaindex/core@0.4.10
-  - @llamaindex/workflow@0.0.6
-  - llamaindex@0.8.13
-  - @llamaindex/cloud@2.0.10
-  - @llamaindex/node-parser@0.0.11
-  - @llamaindex/openai@0.1.35
-  - @llamaindex/readers@1.0.11
-
-## 0.0.15
-
-### Patch Changes
-
- Updated dependencies [ea92b69]
- Updated dependencies [fadc8b8]
-  - @llamaindex/workflow@0.0.5
-
-## 0.0.14
-
-### Patch Changes
-
- Updated dependencies [7ae6eaa]
-  - @llamaindex/core@0.4.9
-  - @llamaindex/openai@0.1.34
-  - @llamaindex/cloud@2.0.9
-  - llamaindex@0.8.12
-  - @llamaindex/node-parser@0.0.10
-  - @llamaindex/readers@1.0.10
-
-## 0.0.13
-
-### Patch Changes
-
- Updated dependencies [f865c98]
-  - @llamaindex/core@0.4.8
-  - @llamaindex/cloud@2.0.8
-  - llamaindex@0.8.11
-  - @llamaindex/node-parser@0.0.9
-  - @llamaindex/openai@0.1.33
-  - @llamaindex/readers@1.0.9
-
-## 0.0.12
-
-### Patch Changes
-
- Updated dependencies [f066e50]
- Updated dependencies [d89ebe0]
- Updated dependencies [fd8c882]
- Updated dependencies [fd8c882]
-  - llamaindex@0.8.10
-  - @llamaindex/core@0.4.7
-  - @llamaindex/workflow@0.0.4
-  - @llamaindex/cloud@2.0.7
-  - @llamaindex/node-parser@0.0.8
-  - @llamaindex/openai@0.1.32
-  - @llamaindex/readers@1.0.8
-
-## 0.0.11
-
-### Patch Changes
-
- Updated dependencies [4fc001c]
- Updated dependencies [4d4cd8a]
-  - llamaindex@0.8.9
-  - @llamaindex/cloud@2.0.6
-  - @llamaindex/core@0.4.6
-  - @llamaindex/node-parser@0.0.7
-  - @llamaindex/openai@0.1.31
-  - @llamaindex/readers@1.0.7
-
-## 0.0.10
-
-### Patch Changes
-
- Updated dependencies [ad85bd0]
-  - @llamaindex/core@0.4.5
-  - llamaindex@0.8.8
-  - @llamaindex/node-parser@0.0.6
-  - @llamaindex/workflow@0.0.3
-  - @llamaindex/cloud@2.0.5
-  - @llamaindex/openai@0.1.30
-  - @llamaindex/readers@1.0.6
-
-## 0.0.9
-
-### Patch Changes
-
- @llamaindex/cloud@2.0.4
- @llamaindex/core@0.4.4
- llamaindex@0.8.7
- @llamaindex/node-parser@0.0.5
- @llamaindex/openai@0.1.29
- @llamaindex/readers@1.0.5
-
-## 0.0.8
-
-### Patch Changes
-
- Updated dependencies [95a5cc6]
-  - @llamaindex/core@0.4.3
-  - llamaindex@0.8.6
-  - @llamaindex/cloud@2.0.3
-  - @llamaindex/node-parser@0.0.4
-  - @llamaindex/openai@0.1.28
-  - @llamaindex/readers@1.0.4
-
-## 0.0.7
-
-### Patch Changes
-
- Updated dependencies [14cc9eb]
- Updated dependencies [a6db5dd]
- Updated dependencies [396b1e1]
-  - llamaindex@0.8.5
-  - @llamaindex/cloud@2.0.2
-  - @llamaindex/core@0.4.2
-  - @llamaindex/node-parser@0.0.3
-  - @llamaindex/openai@0.1.27
-  - @llamaindex/readers@1.0.3
-
 ## 0.0.6

 ### Patch Changes
@@ -1,4 +1,4 @@
-# Docs
+# next

 This is a Next.js application generated with
 [Create Fumadocs](https://github.com/fuma-nama/fumadocs).
@@ -6,10 +6,15 @@ This is a Next.js application generated with
 Run development server:

 ```bash
-turbo run dev
-# turbo will build all required packages before running the dev server
+npm run dev
+# or
+pnpm dev
+# or
+yarn dev
 ```

+Open http://localhost:3000 with your browser to see the result.
+
 ## Learn More

 To learn more about Next.js and Fumadocs, take a look at the following
@@ -6,7 +6,6 @@ const withMDX = createMDX();
 const config = {
  reactStrictMode: true,
  transpilePackages: ["monaco-editor"],
-  serverExternalPackages: ["@huggingface/transformers"],
  webpack: (config, { isServer }) => {
    if (Array.isArray(config.target) && config.target.includes("web")) {
      config.target = ["web", "es2020"];
@@ -27,7 +26,6 @@ const config = {
        }),
      );
    }
-    config.resolve.alias["replicate"] = false;
    return config;
  },
 };
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/doc",
-  "version": "0.0.31",
+  "version": "0.0.6",
  "private": true,
  "scripts": {
    "build": "pnpm run build:docs && next build",
@@ -12,7 +12,7 @@
  },
  "dependencies": {
    "@icons-pack/react-simple-icons": "^10.1.0",
-    "@llamaindex/chat-ui": "0.0.9",
+    "@llamaindex/chat-ui": "0.0.5",
    "@llamaindex/cloud": "workspace:*",
    "@llamaindex/core": "workspace:*",
    "@llamaindex/node-parser": "workspace:*",
@@ -20,31 +20,31 @@
    "@llamaindex/readers": "workspace:*",
    "@llamaindex/workflow": "workspace:*",
    "@mdx-js/mdx": "^3.1.0",
-    "@number-flow/react": "^0.3.4",
+    "@number-flow/react": "^0.3.0",
    "@radix-ui/react-dialog": "^1.1.2",
-    "@radix-ui/react-icons": "^1.3.2",
+    "@radix-ui/react-icons": "^1.3.1",
    "@radix-ui/react-label": "^2.1.0",
    "@radix-ui/react-slider": "^1.2.1",
    "@radix-ui/react-slot": "^1.1.0",
-    "@radix-ui/react-tooltip": "^1.1.4",
+    "@radix-ui/react-tooltip": "^1.1.3",
    "@vercel/functions": "^1.5.0",
-    "ai": "^3.4.33",
+    "ai": "^3.4.31",
    "class-variance-authority": "^0.7.0",
    "clsx": "2.1.1",
-    "foxact": "^0.2.41",
-    "framer-motion": "^11.11.17",
-    "fumadocs-core": "14.4.2",
-    "fumadocs-docgen": "^1.3.2",
+    "foxact": "^0.2.40",
+    "framer-motion": "^11.11.11",
+    "fumadocs-core": "14.2.0",
+    "fumadocs-docgen": "^1.3.1",
    "fumadocs-mdx": "^11.1.1",
-    "fumadocs-openapi": "^5.7.0",
+    "fumadocs-openapi": "^5.5.6",
    "fumadocs-twoslash": "^2.0.1",
-    "fumadocs-typescript": "^3.0.2",
-    "fumadocs-ui": "14.4.2",
+    "fumadocs-typescript": "^3.0.1",
+    "fumadocs-ui": "14.2.0",
    "hast-util-to-jsx-runtime": "^2.3.2",
    "llamaindex": "workspace:*",
-    "lucide-react": "^0.460.0",
-    "next": "15.0.3",
-    "next-themes": "^0.4.3",
+    "lucide-react": "^0.454.0",
+    "next": "15.0.2",
+    "next-themes": "^0.3.0",
    "react": "^18.3.1",
    "react-dom": "^18.3.1",
    "react-icons": "^5.3.0",
@@ -54,19 +54,19 @@
    "rehype-katex": "^7.0.1",
    "remark-math": "^6.0.0",
    "rimraf": "^6.0.1",
-    "shiki": "^1.23.1",
+    "shiki": "^1.22.2",
    "shiki-magic-move": "^0.5.0",
    "swr": "^2.2.5",
    "tailwind-merge": "^2.5.2",
    "tailwindcss-animate": "^1.0.7",
-    "tree-sitter": "^0.22.1",
-    "tree-sitter-typescript": "^0.23.2",
-    "use-stick-to-bottom": "^1.0.42",
-    "web-tree-sitter": "^0.24.4",
+    "tree-sitter": "^0.22.0",
+    "tree-sitter-typescript": "^0.23.0",
+    "use-stick-to-bottom": "^1.0.41",
+    "web-tree-sitter": "^0.24.3",
    "zod": "^3.23.8"
  },
  "devDependencies": {
-    "@next/env": "^15.0.3",
+    "@next/env": "^15.0.2",
    "@types/mdx": "^2.0.13",
    "@types/node": "22.9.0",
    "@types/react": "^18.3.12",
@@ -75,12 +75,12 @@
    "fast-glob": "^3.3.2",
    "gray-matter": "^4.0.3",
    "monaco-editor-webpack-plugin": "^7.1.0",
-    "postcss": "^8.4.49",
+    "postcss": "^8.4.47",
    "remark": "^15.0.1",
    "remark-gfm": "^4.0.0",
    "remark-mdx": "^3.1.0",
    "remark-stringify": "^11.0.0",
-    "tailwindcss": "^3.4.15",
+    "tailwindcss": "^3.4.14",
    "tsx": "^4.19.2",
    "typescript": "^5.6.3"
  }
@@ -25,16 +25,15 @@ export default function HomePage() {
  return (
    <main className="container mx-auto px-4 py-12">
      <h1 className="text-4xl md:text-6xl font-bold text-center mb-4">
-        Build context-augmented web apps using
+        Build RAG Web App using
        <br /> <span className="text-blue-500">LlamaIndex.TS</span>
      </h1>
      <p className="text-xl text-center text-fd-muted-foreground mb-12 ">
-        LlamaIndex.TS is the JS/TS version of{" "}
-        <a href="https://llamaindex.ai">LlamaIndex</a>, the framework for
-        building agentic generative AI applications connected to your data.
+        LlamaIndex.TS is the JS/TS library from our popular Python library
+        llama-index for building LLM applications
      </p>
      <div className="text-center text-lg text-fd-muted-foreground mb-12">
-        <span>Designed for building web applications in </span>
+        <span>Designed for building web applications under </span>
        <TextEffect />
      </div>

@@ -59,8 +58,8 @@ export default function HomePage() {
        <Feature
          icon={Footprints}
          subheading="Progressive"
-          heading="From the simplest to the most complex"
-          description="LlamaIndex.TS is designed to be simple to get started, but powerful enough to build complex, agentic AI applications."
+          heading="Adding AI feature from simple to complex"
+          description="LlamaIndex.TS is designed to be simple to start with and can be extended to build complex AI applications."
        >
          <Suspense
            fallback={
@@ -114,9 +113,9 @@ const response = await agent.chat({
        </Feature>
        <Feature
          icon={Bot}
-          subheading="Agents"
-          heading="Build agentic RAG applications"
-          description="Truly powerful retrieval-augmented generation applications use agentic techniques, and LlamaIndex.TS makes it easy to build them."
+          subheading="Agent"
+          heading="Build agent for RAG"
+          description="Build agents for RAG using LlamaIndex.TS. Agents are the core building blocks of RAG applications."
        >
          <CodeBlock
            code={`import { FunctionTool } from "llamaindex";
@@ -138,19 +137,19 @@ await agent.chat('...');`}
        <Feature
          icon={Blocks}
          subheading="Providers"
-          heading="LLMs, Data Loaders, Vector Stores and more!"
-          description="LlamaIndex.TS has hundreds of integrations to connect to your data, index it, and query it with LLMs."
+          heading="LLM / Data Loader / Vector Store"
+          description="LlamaIndex.TS provides various providers to turn your data into valuable insights."
        >
          <div className="mt-8 flex flex-col gap-8">
            <div>
              <h3 className="text-lg font-semibold text-fd-muted-foreground mb-2">
-                LLMs
+                LLM
              </h3>
              <InfiniteLLMProviders />
            </div>
            <div>
              <h3 className="text-lg font-semibold text-fd-muted-foreground mb-2">
-                Vector Stores
+                Vector Store
              </h3>
              <InfiniteVectorStoreProviders />
            </div>
@@ -158,8 +157,8 @@ await agent.chat('...');`}
        </Feature>
        <Feature
          icon={Terminal}
-          subheading="create-llama CLI"
-          heading="Build a RAG app with a single command"
+          subheading="Create Llama CLI"
+          heading="CLI for starting RAG app with one line"
          description="A command line tool to generate LlamaIndex apps, the easiest way to get started with LlamaIndex."
        >
          <div className="my-6">
@@ -1,10 +1,7 @@
-import { MockLLM } from "@llamaindex/core/utils";
 import { LlamaIndexAdapter, type Message } from "ai";
-import { Settings, SimpleChatEngine, type ChatMessage } from "llamaindex";
+import { SimpleChatEngine, type ChatMessage } from "llamaindex";
 import { NextResponse, type NextRequest } from "next/server";

-Settings.llm = new MockLLM(); // config your LLM here
-
 export async function POST(request: NextRequest) {
  try {
    const { messages } = (await request.json()) as { messages: Message[] };
@@ -7,8 +7,9 @@ import { ReactElement } from "react";
 export function Contributing(): ReactElement {
  return (
    <div className="flex flex-col items-center border-x border-t px-4 py-16 text-center">
+      <Heart className="mb-4" />
      <h2 className="mb-4 text-xl font-semibold sm:text-2xl">
-        Made possible by you <Heart className="inline align-middle" />
+        Made Possible by You.
      </h2>
      <p className="mb-4 text-fd-muted-foreground">
        LlamaIndex.TS is powered by the open source community.
@@ -53,6 +53,9 @@ export default async function ContributorCounter({
          </div>
        ) : null}
      </div>
+      <div className="text-center text-sm text-fd-muted-foreground">
+        Some of our best contributors.
+      </div>
    </div>
  );
 }
@@ -0,0 +1,8 @@
+"use client";
+import { ChatSection } from "@llamaindex/chat-ui";
+import { useChat } from "ai/react";
+
+export const ChatDemo = () => {
+  const handler = useChat();
+  return <ChatSection handler={handler} />;
+};
@@ -1,16 +0,0 @@
-"use client";
-import { ChatInput, ChatMessages, ChatSection } from "@llamaindex/chat-ui";
-import { useChat } from "ai/react";
-
-export const ChatDemo = () => {
-  const handler = useChat();
-  return (
-    <ChatSection handler={handler}>
-      <ChatMessages>
-        <ChatMessages.List className="h-auto max-h-[400px]" />
-        <ChatMessages.Actions />
-      </ChatMessages>
-      <ChatInput />
-    </ChatSection>
-  );
-};
@@ -1,57 +0,0 @@
-import { Markdown } from "@llamaindex/chat-ui/widgets";
-import { MockLLM } from "@llamaindex/core/utils";
-import { generateId, Message } from "ai";
-import { createAI, createStreamableUI, getMutableAIState } from "ai/rsc";
-import { type ChatMessage, Settings, SimpleChatEngine } from "llamaindex";
-import { ReactNode } from "react";
-
-type ServerState = Message[];
-type FrontendState = Array<Message & { display: ReactNode }>;
-type Actions = {
-  chat: (message: Message) => Promise<Message & { display: ReactNode }>;
-};
-
-Settings.llm = new MockLLM(); // config your LLM here
-
-export const AI = createAI<ServerState, FrontendState, Actions>({
-  initialAIState: [],
-  initialUIState: [],
-  actions: {
-    chat: async (message: Message) => {
-      "use server";
-
-      const aiState = getMutableAIState<typeof AI>();
-      aiState.update((prev) => [...prev, message]);
-
-      const uiStream = createStreamableUI();
-      const chatEngine = new SimpleChatEngine();
-      const assistantMessage: Message = {
-        id: generateId(),
-        role: "assistant",
-        content: "",
-      };
-
-      // run the async function without blocking
-      (async () => {
-        const chatResponse = await chatEngine.chat({
-          stream: true,
-          message: message.content,
-          chatHistory: aiState.get() as ChatMessage[],
-        });
-
-        for await (const chunk of chatResponse) {
-          assistantMessage.content += chunk.delta;
-          uiStream.update(<Markdown content={assistantMessage.content} />);
-        }
-
-        aiState.done([...aiState.get(), assistantMessage]);
-        uiStream.done();
-      })();
-
-      return {
-        ...assistantMessage,
-        display: uiStream.value,
-      };
-    },
-  },
-});
@@ -1,33 +0,0 @@
-"use client";
-
-import {
-  ChatInput,
-  ChatMessage,
-  ChatMessages,
-  ChatSection as ChatSectionUI,
-} from "@llamaindex/chat-ui";
-import { useChatRSC } from "./use-chat-rsc";
-
-export const ChatSectionRSC = () => {
-  const handler = useChatRSC();
-  return (
-    <ChatSectionUI handler={handler}>
-      <ChatMessages>
-        <ChatMessages.List className="h-auto max-h-[400px]">
-          {handler.messages.map((message, index) => (
-            <ChatMessage
-              key={index}
-              message={message}
-              isLast={index === handler.messages.length - 1}
-            >
-              <ChatMessage.Avatar />
-              <ChatMessage.Content>{message.display}</ChatMessage.Content>
-            </ChatMessage>
-          ))}
-          <ChatMessages.Loading />
-        </ChatMessages.List>
-      </ChatMessages>
-      <ChatInput />
-    </ChatSectionUI>
-  );
-};
@@ -1,8 +0,0 @@
-import { AI } from "./ai-action";
-import { ChatSectionRSC } from "./chat-section";
-
-export const ChatDemoRSC = () => (
-  <AI>
-    <ChatSectionRSC />
-  </AI>
-);
@@ -1,41 +0,0 @@
-"use client";
-
-import { useActions } from "ai/rsc";
-
-import { generateId, Message } from "ai";
-import { useUIState } from "ai/rsc";
-import { useState } from "react";
-import { AI } from "./ai-action";
-
-export function useChatRSC() {
-  const [input, setInput] = useState<string>("");
-  const [isLoading, setIsLoading] = useState<boolean>(false);
-  const [messages, setMessages] = useUIState<typeof AI>();
-  const { chat } = useActions<typeof AI>();
-
-  const append = async (message: Omit<Message, "id">) => {
-    const newMsg: Message = { ...message, id: generateId() };
-
-    setIsLoading(true);
-    try {
-      setMessages((prev) => [...prev, { ...newMsg, display: message.content }]);
-      const assistantMsg = await chat(newMsg);
-      setMessages((prev) => [...prev, assistantMsg]);
-    } catch (error) {
-      console.error(error);
-    }
-    setIsLoading(false);
-    setInput("");
-
-    return message.content;
-  };
-
-  return {
-    input,
-    setInput,
-    isLoading,
-    messages,
-    setMessages,
-    append,
-  };
-}
@@ -85,33 +85,6 @@ const Footer = () => {
                  <Text as="span">SharePoint</Text>
                </a>
              </li>
-              <li>
-                <a
-                  href="https://llamaindex.ai/llamacloud-aws-s3-data-loading-for-generative-ai"
-                  data-tracking-variant="link"
-                  data-tracking-section="footer"
-                >
-                  <Text as="span">AWS S3</Text>
-                </a>
-              </li>
-              <li>
-                <a
-                  href="https://llamaindex.ai/llamacloud-azure-blob-storage-data-loading-for-generative-ai"
-                  data-tracking-variant="link"
-                  data-tracking-section="footer"
-                >
-                  <Text as="span">Azure Blob Storage</Text>
-                </a>
-              </li>
-              <li>
-                <a
-                  href="https://llamaindex.ai/llamacloud-google-drive-data-loading-for-generative-ai"
-                  data-tracking-variant="link"
-                  data-tracking-section="footer"
-                >
-                  <Text as="span">Google Drive</Text>
-                </a>
-              </li>
            </ul>
          </div>
          <div>
@@ -198,6 +171,11 @@ const Footer = () => {
                  <Text as="span">SEC Insights</Text>
                </a>
              </li>
+              <li>
+                <a href="https://chat.llamaindex.ai/">
+                  <Text as="span">Chat LlamaIndex</Text>
+                </a>
+              </li>
              <li>
                <a href="https://github.com/run-llama/llamabot">
                  <Text as="span">LlamaBot</Text>
@@ -1,8 +1,8 @@
 ---
-title: Using API Route
-description: Chat interface for your LlamaIndexTS application using API Route
+title: Chat-UI 
+description: Use chat-ui to add a chat interface to your LlamaIndexTS application.
 ---
-import { ChatDemo } from '../../../../../components/demo/chat/api/demo';
+import { ChatDemo } from '../../../../components/demo/chat';
 import "@llamaindex/chat-ui/styles/code.css";
 import "@llamaindex/chat-ui/styles/katex.css";

@@ -26,7 +26,7 @@ This is the simplest way to add a chat interface to your application. Copy the f

 ```json doc-gen:file
 {
-  "file": "./src/components/demo/chat/api/demo.tsx",
+  "file": "./src/components/demo/chat.tsx",
 	"codeblock": true
 }
 ```
@@ -37,7 +37,6 @@ Combining both, you're getting a fully functional chat interface:

 <ChatDemo />

-
 ## Next Steps

 The steps above are the bare minimum to get a chat interface working. From here, you can go two ways:
@@ -1,6 +0,0 @@
-{
-  "title": "Chat-UI",
-  "description": "Use chat-ui to add a chat interface to your LlamaIndexTS application.",
-  "defaultOpen": false,
-  "pages": ["chat", "rsc"]
-}
@@ -1,68 +0,0 @@
---
-title: Using Next.js RSC
-description: Chat interface for your LlamaIndexTS application using Next.js RSC
---
-import { ChatDemoRSC } from '../../../../../components/demo/chat/rsc/demo';
-import "@llamaindex/chat-ui/styles/code.css";
-import "@llamaindex/chat-ui/styles/katex.css";
-
-Using [chat-ui](https://github.com/run-llama/chat-ui), it's easy to add a chat interface to your LlamaIndexTS application using [Next.js RSC](https://nextjs.org/docs/app/building-your-application/rendering/server-components) and [Vercel AI RSC](https://sdk.vercel.ai/docs/ai-sdk-rsc/overview).
-
-With RSC, the chat messages are not returned as JSON from the server (like when using an [API route](./chat)), instead the chat message components are rendered on the server side.
-This is for example useful for rendering a whole chat history on the server before sending it to the client. [Check here](https://sdk.vercel.ai/docs/getting-started/navigating-the-library#when-to-use-ai-sdk-rsc), for a discussion of when to use use RSC.
-
-For implementing a chat interface with RSC, you need to create an AI action and then connect the chat interface to use it.
-
-## Create an AI action
-
-First, define an [AI context provider](https://sdk.vercel.ai/examples/rsc/state-management/ai-ui-states) with a chat server action:
-
-```json doc-gen:file
-{
-  "file": "./src/components/demo/chat/rsc/ai-action.tsx",
-	"codeblock": true
-}
-```
-
-The chat server action is using LlamaIndexTS to generate a response based on the chat history and the user input.
-
-## Create the chat UI
-
-The entrypoint of our application initializes the AI provider for the application and adds a `ChatSection` component:
-
-```json doc-gen:file
-{
-  "file": "./src/components/demo/chat/rsc/demo.tsx",
-	"codeblock": true
-}
-```
-
-The `ChatSection` component is created by using chat components from @llamaindex/chat-ui:
-
-```json doc-gen:file
-{
-  "file": "./src/components/demo/chat/rsc/chat-section.tsx",
-	"codeblock": true
-}
-```
-
-It is using a `useChatRSC` hook to conntect the chat interface to the `chat` AI action that we defined earlier:
-
-```json doc-gen:file
-{
-  "file": "./src/components/demo/chat/rsc/use-chat-rsc.tsx",
-	"codeblock": true
-}
-```
-
-## Try RSC Chat ⬇️
-
-<ChatDemoRSC />
-
-## Next Steps
-
-The steps above are the bare minimum to get a chat interface working with RSC. From here, you can go two ways:
-
-1. Use our [full-stack RSC example](https://github.com/run-llama/nextjs-rsc) based on [create-llama](https://github.com/run-llama/create-llama) to get started quickly with a fully working chat interface or
-2. Learn more about [AI RSC](https://sdk.vercel.ai/examples/rsc), [chat-ui](https://github.com/run-llama/chat-ui) and [LlamaIndexTS](https://github.com/run-llama/llamaindex-ts) to customize the chat interface and AI actions to your needs.
-
@@ -1,5 +1,5 @@
 {
  "title": "Integration",
  "description": "See our integrations",
-  "pages": ["open-llm-metry", "lang-trace", "vercel"]
+  "pages": ["open-llm-metry", "lang-trace"]
 }
@@ -1,101 +0,0 @@
---
-title: Vercel
-description: Integrate LlamaIndex with Vercel's AI SDK
---
-
-LlamaIndex provides integration with Vercel's AI SDK, allowing you to create powerful search and retrieval applications. You can:
- Use any of Vercel AI's [model providers](https://sdk.vercel.ai/docs/foundations/providers-and-models) as LLMs in LlamaIndex
- Use indexes (e.g. VectorStoreIndex, LlamaCloudIndex) from LlamaIndexTS in your Vercel AI applications
-
-## Setup
-
-First, install the required dependencies:
-
-```bash
-npm install @llamaindex/vercel ai
-```
-
-## Using Vercel AI's Model Providers 
-
-Using the `VercelLLM` adapter, it's easy to use any of Vercel AI's [model providers](https://sdk.vercel.ai/docs/foundations/providers-and-models) as LLMs in LlamaIndex. Here's an example of how to use OpenAI's GPT-4o model:
-
-```typescript
-const llm = new VercelLLM({ model: openai("gpt-4o") });
-const result = await llm.complete({
-  prompt: "What is the capital of France?",
-  stream: false, // Set to true if you want streaming responses
-});
-console.log(result.text);
-```
-
-## Use Indexes
-
-### Using VectorStoreIndex
-
-Here's how to create a simple vector store index and query it using Vercel's AI SDK:
-
-```typescript
-import { openai } from "@ai-sdk/openai";
-import { llamaindex } from "@llamaindex/vercel";
-import { streamText } from "ai";
-import { Document, VectorStoreIndex } from "llamaindex";
-
-// Create an index from your documents
-const document = new Document({ text: yourText, id_: "unique-id" });
-const index = await VectorStoreIndex.fromDocuments([document]);
-
-// Create a query tool
-const queryTool = llamaindex({
-  model: openai("gpt-4"),
-  index,
-  description: "Search through the documents", // optional
-});
-
-// Use the tool with Vercel's AI SDK
-streamText({
-  model: openai("gpt-4"),
-  prompt: "Your question here",
-  tools: { queryTool },
-  onFinish({ response }) {
-    console.log("Response:", response.messages); // log the response
-  },
-}).toDataStream();
-```
-
-> Note: the Vercel AI model referenced in the `llamaindex` function is used by the response synthesizer to generate a response for the tool call.
-
-### Using LlamaCloud
-
-For production deployments, you can use LlamaCloud to store and manage your documents:
-
-```typescript
-import { LlamaCloudIndex } from "llamaindex";
-
-// Create a LlamaCloud index
-const index = await LlamaCloudIndex.fromDocuments({
-  documents: [document],
-  name: "your-index-name",
-  projectName: "your-project",
-  apiKey: process.env.LLAMA_CLOUD_API_KEY,
-});
-
-// Use it the same way as VectorStoreIndex
-const queryTool = llamaindex({
-  model: openai("gpt-4"),
-  index,
-  description: "Search through the documents",
-});
-
-// Use the tool with Vercel's AI SDK
-streamText({
-  model: openai("gpt-4"),
-  prompt: "Your question here",
-  tools: { queryTool },
-}).toDataStream();
-```
-
-## Next Steps
-
-1. Explore [LlamaCloud](https://cloud.llamaindex.ai/) for managed document storage and retrieval
-2. Join our [Discord community](https://discord.gg/dGcwcsnxhU) for support and discussions
-
@@ -37,33 +37,6 @@ Then, you need create `.dev.vars` and add LLM api keys for the local development

 <Callout type="warn">Do not commit the api key to git repository.</Callout>

-## Integrating with Hono
-
-```ts
-import { Hono } from "hono";
-
-type Bindings = {
-  OPENAI_API_KEY: string;
-};
-
-const app = new Hono<{
-  Bindings: Bindings;
-}>();
-
-app.post("/llm", async (c) => {
-  const { setEnvs } = await import("@llamaindex/env");
-  setEnvs(c.env);
-
-  // ...
-
-  return new Response('Hello, world!');
-})
-
-export default {
-  fetch: app.fetch,
-};
-```
-
 ## Difference between Node.js and Cloudflare Worker

 In Cloudflare Worker and similar serverless JS environment, you need to be aware of the following differences:
@@ -73,7 +46,3 @@ In Cloudflare Worker and similar serverless JS environment, you need to be aware
 - 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.
 - `@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.
@@ -84,7 +84,7 @@ Imaging you put output file into `/dist/openai.js` but you are importing `llamai
 }
 ```

-In old module resolution, TypeScript will not be able to find the module because it is not following the file structure, even you run `node index.js` successfully. (on Node.js >=16)
+In old module resolution, TypeScript will not be able to find the module because it is not follow the file structure, even you run `node index.js` successfully. (on Node.js >=16)

 See more about [moduleResolution](https://www.typescriptlang.org/docs/handbook/modules/theory.html#module-resolution) or
 [TypeScript 5.0 blog](https://devblogs.microsoft.com/typescript/announcing-typescript-5-0/#--moduleresolution-bundler7).
@@ -93,35 +93,6 @@ See more about [moduleResolution](https://www.typescriptlang.org/docs/handbook/m
 	</Accordion>
 </Accordions>

-## Enable AsyncIterable for `Web Stream` API
-
-Some modules uses `Web Stream` API like `ReadableStream` and `WritableStream`, you need to enable `DOM.AsyncIterable` in your `tsconfig.json`.
-
-```json5
-{
-  compilerOptions: {
-    // ⬇️ add this lib to your tsconfig.json
-    lib: ["DOM.AsyncIterable"],
-  },
-}
-```
-
-```ts twoslash
-import { OpenAIAgent } from '@llamaindex/openai'
-
-const agent = new OpenAIAgent({
-  tools: []
-})
-
-const response = await agent.chat({
-  message: 'Hello, how are you?',
-  stream: true
-})
-for await (const _ of response) {
-                      //^?
-  // ...
-}
-```

 ## Run TypeScript Script in Node.js

@@ -1,16 +0,0 @@
-{
-  "extends": ["//"],
-  "tasks": {
-    "build": {
-      "outputs": [
-        ".next",
-        ".source",
-        "next-env.d.ts",
-        "src/content/docs/cloud/api/**"
-      ]
-    },
-    "dev": {
-      "dependsOn": ["^build"]
-    }
-  }
-}
@@ -1,4 +0,0 @@
-POSTGRES_USER=runner
-PINECONE_API_KEY=
-PINECONE_INDEX_NAME=
-PINECONE_NAMESPACE=
@@ -1,20 +0,0 @@
-{
-  "name": "@llamaindex/cloudflare-hono",
-  "version": "0.0.0",
-  "private": true,
-  "scripts": {
-    "deploy": "wrangler deploy",
-    "build": "wrangler deploy --dry-run --outdir dist",
-    "dev": "wrangler dev",
-    "start": "wrangler dev",
-    "cf-typegen": "wrangler types"
-  },
-  "devDependencies": {
-    "@cloudflare/workers-types": "^4.20241112.0",
-    "typescript": "^5.5.2",
-    "wrangler": "^3.89.0"
-  },
-  "dependencies": {
-    "hono": "^4.6.11"
-  }
-}
@@ -1,91 +0,0 @@
-import { Hono } from "hono";
-
-type Bindings = {
-  OPENAI_API_KEY: string;
-  PINECONE_API_KEY: string;
-};
-
-const app = new Hono<{
-  Bindings: Bindings;
-}>();
-
-app.post("/llm", async (c) => {
-  //#region init envs
-  const { setEnvs } = await import("@llamaindex/env");
-  setEnvs(c.env);
-  //#endregion
-
-  const { message } = await c.req.json();
-
-  const { extractText } = await import("@llamaindex/core/utils");
-
-  const {
-    QueryEngineTool,
-    serviceContextFromDefaults,
-    VectorStoreIndex,
-    OpenAIAgent,
-    Settings,
-    OpenAI,
-    OpenAIEmbedding,
-  } = await import("llamaindex");
-
-  const { PineconeVectorStore } = await import(
-    "llamaindex/vector-store/PineconeVectorStore"
-  );
-
-  const llm = new OpenAI({
-    model: "gpt-4o-mini",
-    apiKey: c.env.OPENAI_API_KEY,
-  });
-
-  Settings.embedModel = new OpenAIEmbedding({
-    model: "text-embedding-3-small",
-    apiKey: c.env.OPENAI_API_KEY,
-  });
-
-  const serviceContext = serviceContextFromDefaults({
-    llm,
-    chunkSize: 8191,
-    chunkOverlap: 0,
-  });
-
-  const store = new PineconeVectorStore({
-    namespace: "8xolsn4ulEQGdhnhP76yCzfLHdOZ",
-  });
-
-  const index = await VectorStoreIndex.fromVectorStore(store, serviceContext);
-
-  const retriever = index.asRetriever({
-    similarityTopK: 3,
-  });
-
-  // Create a query engine
-  const queryEngine = index.asQueryEngine({
-    retriever,
-  });
-
-  const tools = [
-    new QueryEngineTool({
-      queryEngine: queryEngine,
-      metadata: {
-        name: "business_info_tool",
-        description:
-          "This tool can answer questions based " +
-          "on business information. Return not found if you" +
-          " can't find the answer in the documents.",
-      },
-    }),
-  ];
-
-  const agent = new OpenAIAgent({ tools });
-
-  const response = await agent.chat({
-    message: message,
-  });
-
-  return new Response(extractText(response.message.content));
-});
-
-export default {
-  fetch: app.fetch,
-};
@@ -1,39 +0,0 @@
-{
-  "extends": "../../tsconfig.json",
-  "compilerOptions": {
-    /* Visit https://aka.ms/tsconfig.json to read more about this file */
-
-    /* Set the JavaScript language version for emitted JavaScript and include compatible library declarations. */
-    "target": "es2021",
-    /* Specify a set of bundled library declaration files that describe the target runtime environment. */
-    "lib": ["es2021", "DOM.AsyncIterable"],
-    /* Specify what JSX code is generated. */
-    "jsx": "react-jsx",
-    /* Specify what module code is generated. */
-    "module": "es2022",
-    /* Specify how TypeScript looks up a file from a given module specifier. */
-    "moduleResolution": "Bundler",
-    /* Specify type package names to be included without being referenced in a source file. */
-    "types": ["@cloudflare/workers-types/2023-07-01"],
-    /* Enable importing .json files */
-    "resolveJsonModule": true,
-    /* Allow JavaScript files to be a part of your program. Use the `checkJS` option to get errors from these files. */
-    "allowJs": true,
-    /* Enable error reporting in type-checked JavaScript files. */
-    "checkJs": false,
-    /* Disable emitting files from a compilation. */
-    "noEmit": true,
-    /* Ensure that each file can be safely transpiled without relying on other imports. */
-    "isolatedModules": true,
-    /* Allow 'import x from y' when a module doesn't have a default export. */
-    "allowSyntheticDefaultImports": true,
-    /* Ensure that casing is correct in imports. */
-    "forceConsistentCasingInFileNames": true,
-    /* Enable all strict type-checking options. */
-    "strict": true,
-    /* Skip type checking all .d.ts files. */
-    "skipLibCheck": true
-  },
-  "exclude": ["test"],
-  "include": ["vitest.config.mts", "worker-configuration.d.ts", "src/**/*.ts"]
-}
@@ -1,4 +0,0 @@
-// Generated by Wrangler by running `wrangler types`
-
-// eslint-disable-next-line @typescript-eslint/no-empty-object-type
-interface Env {}
@@ -1,7 +0,0 @@
-name = "llamaindex-cloudflare-hono-example"
-main = "src/index.ts"
-compatibility_date = "2024-11-12"
-compatibility_flags = ["nodejs_als"]
-
-[observability]
-enabled = true
@@ -1,172 +0,0 @@
-# Logs
-
-logs
-_.log
-npm-debug.log_
-yarn-debug.log*
-yarn-error.log*
-lerna-debug.log*
-.pnpm-debug.log*
-
-# Diagnostic reports (https://nodejs.org/api/report.html)
-
-report.[0-9]_.[0-9]_.[0-9]_.[0-9]_.json
-
-# Runtime data
-
-pids
-_.pid
-_.seed
-\*.pid.lock
-
-# Directory for instrumented libs generated by jscoverage/JSCover
-
-lib-cov
-
-# Coverage directory used by tools like istanbul
-
-coverage
-\*.lcov
-
-# nyc test coverage
-
-.nyc_output
-
-# Grunt intermediate storage (https://gruntjs.com/creating-plugins#storing-task-files)
-
-.grunt
-
-# Bower dependency directory (https://bower.io/)
-
-bower_components
-
-# node-waf configuration
-
-.lock-wscript
-
-# Compiled binary addons (https://nodejs.org/api/addons.html)
-
-build/Release
-
-# Dependency directories
-
-node_modules/
-jspm_packages/
-
-# Snowpack dependency directory (https://snowpack.dev/)
-
-web_modules/
-
-# TypeScript cache
-
-\*.tsbuildinfo
-
-# Optional npm cache directory
-
-.npm
-
-# Optional eslint cache
-
-.eslintcache
-
-# Optional stylelint cache
-
-.stylelintcache
-
-# Microbundle cache
-
-.rpt2_cache/
-.rts2_cache_cjs/
-.rts2_cache_es/
-.rts2_cache_umd/
-
-# Optional REPL history
-
-.node_repl_history
-
-# Output of 'npm pack'
-
-\*.tgz
-
-# Yarn Integrity file
-
-.yarn-integrity
-
-# dotenv environment variable files
-
-.env
-.env.development.local
-.env.test.local
-.env.production.local
-.env.local
-
-# parcel-bundler cache (https://parceljs.org/)
-
-.cache
-.parcel-cache
-
-# Next.js build output
-
-.next
-out
-
-# Nuxt.js build / generate output
-
-.nuxt
-dist
-
-# Gatsby files
-
-.cache/
-
-# Comment in the public line in if your project uses Gatsby and not Next.js
-
-# https://nextjs.org/blog/next-9-1#public-directory-support
-
-# public
-
-# vuepress build output
-
-.vuepress/dist
-
-# vuepress v2.x temp and cache directory
-
-.temp
-.cache
-
-# Docusaurus cache and generated files
-
-.docusaurus
-
-# Serverless directories
-
-.serverless/
-
-# FuseBox cache
-
-.fusebox/
-
-# DynamoDB Local files
-
-.dynamodb/
-
-# TernJS port file
-
-.tern-port
-
-# Stores VSCode versions used for testing VSCode extensions
-
-.vscode-test
-
-# yarn v2
-
-.yarn/cache
-.yarn/unplugged
-.yarn/build-state.yml
-.yarn/install-state.gz
-.pnp.\*
-
-# wrangler project
-
-.dev.vars
-.wrangler/
@@ -1,3 +0,0 @@
-import { OpenAI } from "./openai.js";
-
-export class Ollama extends OpenAI {}
@@ -1,35 +0,0 @@
-import { Ollama } from "@llamaindex/ollama";
-import assert from "node:assert";
-import { test } from "node:test";
-import { getWeatherTool } from "./fixtures/tools.js";
-import { mockLLMEvent } from "./utils.js";
-
-await test("ollama", async (t) => {
-  await mockLLMEvent(t, "ollama");
-  await t.test("ollama function call", async (t) => {
-    const llm = new Ollama({
-      model: "llama3.2",
-    });
-    const chatResponse = await llm.chat({
-      messages: [
-        {
-          role: "user",
-          content: "What is the weather in Paris?",
-        },
-      ],
-      tools: [getWeatherTool],
-    });
-    if (
-      chatResponse.message.options &&
-      "toolCall" in chatResponse.message.options
-    ) {
-      assert.equal(chatResponse.message.options.toolCall.length, 1);
-      assert.equal(
-        chatResponse.message.options.toolCall[0]!.name,
-        getWeatherTool.metadata.name,
-      );
-    } else {
-      throw new Error("Expected tool calls in response");
-    }
-  });
-});
@@ -1,393 +0,0 @@
-{
-  "llmEventStart": [
-    {
-      "id": "PRESERVE_0",
-      "messages": [
-        {
-          "role": "user",
-          "content": "calculate 2 + 2"
-        }
-      ]
-    },
-    {
-      "id": "PRESERVE_1",
-      "messages": [
-        {
-          "role": "user",
-          "content": "calculate 2 + 2"
-        },
-        {
-          "role": "assistant",
-          "content": "",
-          "options": {
-            "toolCall": [
-              {
-                "name": "sumNumbers",
-                "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
-                "input": {
-                  "a": 2,
-                  "b": 2
-                }
-              }
-            ]
-          }
-        },
-        {
-          "role": "user",
-          "content": "4",
-          "options": {
-            "toolResult": {
-              "result": "4",
-              "isError": false,
-              "id": "call_S2x0FUa475GVpNQJ796Rc9fd"
-            }
-          }
-        }
-      ]
-    }
-  ],
-  "llmEventEnd": [
-    {
-      "id": "PRESERVE_0",
-      "response": {
-        "raw": null,
-        "message": {
-          "content": "",
-          "role": "assistant",
-          "options": {
-            "toolCall": [
-              {
-                "name": "sumNumbers",
-                "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
-                "input": {
-                  "a": 2,
-                  "b": 2
-                }
-              }
-            ]
-          }
-        }
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "response": {
-        "raw": null,
-        "message": {
-          "content": "The result of \\(2 + 2\\) is \\(4\\).",
-          "role": "assistant",
-          "options": {}
-        }
-      }
-    }
-  ],
-  "llmEventStream": [
-    {
-      "id": "PRESERVE_0",
-      "chunk": {
-        "raw": null,
-        "options": {
-          "toolCall": [
-            {
-              "name": "sumNumbers",
-              "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
-              "input": "{\"a\":2,\"b\":2}"
-            }
-          ]
-        },
-        "delta": ""
-      }
-    },
-    {
-      "id": "PRESERVE_0",
-      "chunk": {
-        "raw": null,
-        "options": {
-          "toolCall": [
-            {
-              "name": "sumNumbers",
-              "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
-              "input": "{\"a\":2,\"b\":2}"
-            }
-          ]
-        },
-        "delta": ""
-      }
-    },
-    {
-      "id": "PRESERVE_0",
-      "chunk": {
-        "raw": null,
-        "options": {
-          "toolCall": [
-            {
-              "name": "sumNumbers",
-              "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
-              "input": "{\"a\":2,\"b\":2}"
-            }
-          ]
-        },
-        "delta": ""
-      }
-    },
-    {
-      "id": "PRESERVE_0",
-      "chunk": {
-        "raw": null,
-        "options": {
-          "toolCall": [
-            {
-              "name": "sumNumbers",
-              "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
-              "input": "{\"a\":2,\"b\":2}"
-            }
-          ]
-        },
-        "delta": ""
-      }
-    },
-    {
-      "id": "PRESERVE_0",
-      "chunk": {
-        "raw": null,
-        "options": {
-          "toolCall": [
-            {
-              "name": "sumNumbers",
-              "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
-              "input": "{\"a\":2,\"b\":2}"
-            }
-          ]
-        },
-        "delta": ""
-      }
-    },
-    {
-      "id": "PRESERVE_0",
-      "chunk": {
-        "raw": null,
-        "options": {
-          "toolCall": [
-            {
-              "name": "sumNumbers",
-              "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
-              "input": "{\"a\":2,\"b\":2}"
-            }
-          ]
-        },
-        "delta": ""
-      }
-    },
-    {
-      "id": "PRESERVE_0",
-      "chunk": {
-        "raw": null,
-        "options": {
-          "toolCall": [
-            {
-              "name": "sumNumbers",
-              "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
-              "input": "{\"a\":2,\"b\":2}"
-            }
-          ]
-        },
-        "delta": ""
-      }
-    },
-    {
-      "id": "PRESERVE_0",
-      "chunk": {
-        "raw": null,
-        "options": {
-          "toolCall": [
-            {
-              "name": "sumNumbers",
-              "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
-              "input": "{\"a\":2,\"b\":2}"
-            }
-          ]
-        },
-        "delta": ""
-      }
-    },
-    {
-      "id": "PRESERVE_0",
-      "chunk": {
-        "raw": null,
-        "options": {
-          "toolCall": [
-            {
-              "name": "sumNumbers",
-              "id": "call_S2x0FUa475GVpNQJ796Rc9fd",
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-            }
-          ]
-        },
-        "delta": ""
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-    },
-    {
-      "id": "PRESERVE_0",
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-    {
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-                "a": 2,
-                "b": 2
-              }
-            }
-          ]
-        },
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-      }
-    },
-    {
-      "id": "PRESERVE_1",
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-      }
-    },
-    {
-      "id": "PRESERVE_1",
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-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": " of"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": " \\("
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
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-        "options": {},
-        "delta": "2"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": " +"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": " "
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": "2"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": "\\"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": ")"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": " is"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": " \\("
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": "4"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": "\\"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": ")."
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": ""
-      }
-    }
-  ]
-}
@@ -1,37 +0,0 @@
-{
-  "llmEventStart": [
-    {
-      "id": "PRESERVE_0",
-      "messages": [
-        {
-          "role": "user",
-          "content": "What is the weather in Paris?"
-        }
-      ]
-    }
-  ],
-  "llmEventEnd": [
-    {
-      "id": "PRESERVE_0",
-      "response": {
-        "message": {
-          "role": "assistant",
-          "content": "",
-          "options": {
-            "toolCall": [
-              {
-                "name": "getWeather",
-                "input": {
-                  "city": "Paris"
-                },
-                "id": "5d198775-5268-4552-993b-9ecb4425385b"
-              }
-            ]
-          }
-        },
-        "raw": null
-      }
-    }
-  ],
-  "llmEventStream": []
-}
@@ -1,66 +0,0 @@
-import { Document, MetadataMode } from "@llamaindex/core/schema";
-import { config } from "dotenv";
-import {
-  OpenAIEmbedding,
-  PineconeVectorStore,
-  VectorStoreIndex,
-} from "llamaindex";
-import assert from "node:assert";
-import { test } from "node:test";
-
-config({ path: [".env.local", ".env", ".env.ci"] });
-
-await test("pinecone", async (t) => {
-  if (
-    !process.env.PINECONE_API_KEY ||
-    !process.env.PINECONE_NAMESPACE ||
-    !process.env.PINECONE_INDEX_NAME
-  ) {
-    return t.skip(
-      "PINECONE_API_KEY, PINECONE_NAMESPACE, and PINECONE_INDEX_NAME must be set to run this test",
-    );
-  }
-  const openaiEmbedding = new OpenAIEmbedding({
-    model: "text-embedding-3-large",
-  });
-
-  const vectorStore = new PineconeVectorStore({
-    embeddingModel: openaiEmbedding,
-  });
-
-  t.after(async () => {
-    await vectorStore.clearIndex();
-  });
-
-  const index = await VectorStoreIndex.fromVectorStore(vectorStore);
-
-  const retriever = index.asRetriever({
-    similarityTopK: 3,
-  });
-  const text = "We are open from 9am to 5pm";
-
-  await vectorStore.add([
-    new Document({
-      text,
-      embedding: await openaiEmbedding.getTextEmbedding(text),
-    }),
-  ]);
-
-  const results = await retriever.retrieve({
-    query: "When are you open?",
-  });
-  results.every((result) => {
-    assert.ok(result.node.embedding instanceof Array);
-    result.node.embedding.every((embedding, idx) =>
-      assert.ok(
-        typeof embedding === "number",
-        `Embedding at index ${idx} should be a number`,
-      ),
-    );
-    assert.ok(typeof result.score === "number", "Score should be a number");
-    assert.ok(
-      result.node.getContent(MetadataMode.NONE).length > 0,
-      "Content should not be empty",
-    );
-  });
-});
@@ -1,92 +1,5 @@
 # examples

-## 0.0.20
-
-### Patch Changes
-
- Updated dependencies [b504303]
- Updated dependencies [086a651]
- Updated dependencies [e0f6cc3]
- Updated dependencies [a0e6f57]
-  - llamaindex@0.8.27
-  - @llamaindex/vercel@0.0.5
-  - @llamaindex/core@0.4.18
-  - @llamaindex/readers@1.0.20
-  - @llamaindex/workflow@0.0.8
-
-## 0.0.19
-
-### Patch Changes
-
- Updated dependencies [3d1808b]
-  - @llamaindex/core@0.4.17
-  - llamaindex@0.8.26
-  - @llamaindex/vercel@0.0.4
-  - @llamaindex/readers@1.0.19
-
-## 0.0.18
-
-### Patch Changes
-
- Updated dependencies [7e8230b]
- Updated dependencies [8be4589]
-  - @llamaindex/readers@1.0.18
-  - @llamaindex/core@0.4.16
-  - @llamaindex/vercel@0.0.3
-  - @llamaindex/workflow@0.0.7
-  - llamaindex@0.8.25
-
-## 0.0.17
-
-### Patch Changes
-
- fd38a25: Add vercel tool adapter to use query engine tool
- Updated dependencies [fd38a25]
-  - @llamaindex/vercel@0.0.2
-
-## 0.0.16
-
-### Patch Changes
-
- Updated dependencies [a7b0ac3]
- Updated dependencies [ee20c44]
- Updated dependencies [c69605f]
-  - @llamaindex/core@0.4.10
-  - @llamaindex/workflow@0.0.6
-  - llamaindex@0.8.13
-  - @llamaindex/readers@1.0.11
-
-## 0.0.15
-
-### Patch Changes
-
- Updated dependencies [ea92b69]
- Updated dependencies [fadc8b8]
-  - @llamaindex/workflow@0.0.5
-
-## 0.0.14
-
-### Patch Changes
-
- Updated dependencies [f066e50]
- Updated dependencies [d89ebe0]
- Updated dependencies [fd8c882]
- Updated dependencies [fd8c882]
-  - llamaindex@0.8.10
-  - @llamaindex/core@0.4.7
-  - @llamaindex/workflow@0.0.4
-  - @llamaindex/readers@1.0.8
-
-## 0.0.13
-
-### Patch Changes
-
- Updated dependencies [ad85bd0]
-  - @llamaindex/core@0.4.5
-  - llamaindex@0.8.8
-  - @llamaindex/workflow@0.0.3
-  - @llamaindex/readers@1.0.6
-
 ## 0.0.12

 ### Patch Changes
@@ -1,38 +0,0 @@
-import { Anthropic } from "llamaindex";
-
-async function main() {
-  const anthropic = new Anthropic({
-    model: "claude-3-5-sonnet-20241022",
-  });
-
-  const entireBook = await fetch(
-    "https://www.gutenberg.org/files/1342/1342-0.txt",
-  ).then((response) => response.text());
-
-  const response = await anthropic.chat({
-    messages: [
-      {
-        content:
-          "You are an AI assistant tasked with analyzing literary works. Your goal is to provide insightful commentary on themes, characters, and writing style.\n",
-        role: "system",
-      },
-      {
-        content: entireBook,
-        role: "system",
-        options: {
-          cache_control: {
-            type: "ephemeral",
-          },
-        },
-      },
-      {
-        content: "analyze the major themes in Pride and Prejudice.",
-        role: "user",
-      },
-    ],
-  });
-
-  console.log(response.message.content);
-}
-
-main().catch(console.error);
@@ -1,71 +0,0 @@
-import "dotenv/config";
-
-import {
-  DefaultAzureCredential,
-  getBearerTokenProvider,
-} from "@azure/identity";
-import {
-  AzureCosmosDBNoSqlVectorStore,
-  AzureCosmosNoSqlDocumentStore,
-  AzureCosmosNoSqlIndexStore,
-  Document,
-  OpenAI,
-  OpenAIEmbedding,
-  Settings,
-  storageContextFromDefaults,
-  VectorStoreIndex,
-} from "llamaindex";
-/**
- * This example demonstrates how to use Azure CosmosDB with LlamaIndex.
- * It uses Azure CosmosDB as IndexStore, DocumentStore, and VectorStore.
- *
- * To run this example, create an .env file under /examples and set the following environment variables:
- *
- * AZURE_OPENAI_ENDPOINT="https://AOAI-ACCOUNT.openai.azure.com" // Sample Azure OpenAI endpoint.
- * AZURE_DEPLOYMENT_NAME="gpt-4o" // Sample Azure OpenAI deployment name.
- * EMBEDDING_MODEL="text-embedding-3-large" // Sample Azure OpenAI embedding model.
- * AZURE_COSMOSDB_NOSQL_ACCOUNT_ENDPOINT = "https://DB-ACCOUNT.documents.azure.com:443/" // Sample CosmosDB account endpoint.
- *
- * This example uses managed identity to authenticate with Azure CosmosDB and Azure OpenAI. Make sure to assign the required roles to the managed identity.
- * You can also use connectionString for Azure CosmosDB and Keys with Azure OpenAI for authentication.
- */
-(async () => {
-  const credential = new DefaultAzureCredential();
-  const azureADTokenProvider = getBearerTokenProvider(
-    credential,
-    "https://cognitiveservices.azure.com/.default",
-  );
-
-  const azure = {
-    azureADTokenProvider,
-    deployment: process.env.AZURE_DEPLOYMENT_NAME,
-  };
-  Settings.llm = new OpenAI({ azure });
-  Settings.embedModel = new OpenAIEmbedding({
-    model: process.env.EMBEDDING_MODEL,
-    azure: {
-      ...azure,
-      deployment: process.env.EMBEDDING_MODEL,
-    },
-  });
-  const docStore = AzureCosmosNoSqlDocumentStore.fromAadToken();
-  console.log({ docStore });
-  const indexStore = AzureCosmosNoSqlIndexStore.fromAadToken();
-  console.log({ indexStore });
-  const vectorStore = AzureCosmosDBNoSqlVectorStore.fromUriAndManagedIdentity();
-  console.log({ vectorStore });
-  const storageContext = await storageContextFromDefaults({
-    docStore,
-    indexStore,
-    vectorStore,
-  });
-  console.log({ storageContext });
-
-  const document = new Document({ text: "Test Text" });
-  const index = await VectorStoreIndex.fromDocuments([document], {
-    storageContext,
-    logProgress: true,
-  });
-
-  console.log({ index });
-})();
@@ -6,21 +6,17 @@ import {
 } from "@llamaindex/readers/cosmosdb";
 import * as dotenv from "dotenv";
 import {
-  AzureCosmosDBNoSQLConfig,
+  AzureCosmosDBNoSqlVectorStore,
  OpenAI,
  OpenAIEmbedding,
  Settings,
  storageContextFromDefaults,
  VectorStoreIndex,
 } from "llamaindex";
-import {
-  createStoresFromConnectionString,
-  createStoresFromManagedIdentity,
-} from "./utils";
 // Load environment variables from local .env file
 dotenv.config();

-const cosmosEndpoint = process.env.AZURE_COSMOSDB_NOSQL_ACCOUNT_ENDPOINT!;
+const cosmosEndpoint = process.env.AZURE_COSMOSDB_NOSQL_ENDPOINT!;
 const cosmosConnectionString =
  process.env.AZURE_COSMOSDB_NOSQL_CONNECTION_STRING!;
 const databaseName =
@@ -30,7 +26,7 @@ const collectionName =
 const vectorCollectionName =
  process.env.AZURE_COSMOSDB_VECTOR_CONTAINER_NAME || "vectorContainer";

-// This example uses Azure OpenAI llm and embedding models
+// This exampple uses Azure OpenAI llm and embedding models
 const llmInit = {
  azure: {
    apiVersion: process.env.AZURE_OPENAI_LLM_API_VERSION,
@@ -50,48 +46,24 @@ const embedModelInit = {
 Settings.llm = new OpenAI(llmInit);
 Settings.embedModel = new OpenAIEmbedding(embedModelInit);

-// Initialize the CosmosDB client
-async function initializeCosmosClient() {
-  if (cosmosConnectionString) {
-    return new CosmosClient(cosmosConnectionString);
-  } else {
-    const credential = new DefaultAzureCredential();
-    return new CosmosClient({
-      endpoint: cosmosEndpoint,
-      aadCredentials: credential,
-    });
-  }
-}
-
-// Initialize CosmosDB to be used as a vectorStore, docStore, and indexStore
-async function initializeStores() {
-  // Create a configuration object for the Azure CosmosDB NoSQL Vector Store
-  const dbConfig: AzureCosmosDBNoSQLConfig = {
-    databaseName,
-    containerName: vectorCollectionName,
-    flatMetadata: false,
-  };
-
-  if (cosmosConnectionString) {
-    return createStoresFromConnectionString(cosmosConnectionString, dbConfig);
-  } else {
-    // Use managed identity to authenticate with Azure CosmosDB
-    const credential = new DefaultAzureCredential();
-    return createStoresFromManagedIdentity(
-      cosmosEndpoint,
-      credential,
-      dbConfig,
-    );
-  }
-}
-
 async function loadVectorData() {
  if (!cosmosConnectionString && !cosmosEndpoint) {
    throw new Error(
      "Azure CosmosDB connection string or endpoint must be set.",
    );
  }
-  const cosmosClient = await initializeCosmosClient();
+
+  let cosmosClient: CosmosClient;
+  // initialize the cosmos client
+  if (cosmosConnectionString) {
+    cosmosClient = new CosmosClient(cosmosConnectionString);
+  } else {
+    cosmosClient = new CosmosClient({
+      endpoint: cosmosEndpoint,
+      aadCredentials: new DefaultAzureCredential(),
+    });
+  }
+
  const reader = new SimpleCosmosDBReader(cosmosClient);
  // create a configuration object for the reader
  const simpleCosmosReaderConfig: SimpleCosmosDBReaderLoaderConfig = {
@@ -104,15 +76,16 @@ async function loadVectorData() {

  // load objects from cosmos and convert them into LlamaIndex Document objects
  const documents = await reader.loadData(simpleCosmosReaderConfig);
-
-  // use Azure CosmosDB as a vectorStore, docStore, and indexStore
-  const { vectorStore, docStore, indexStore } = await initializeStores();
-  // Store the embeddings in the CosmosDB container
-  const storageContext = await storageContextFromDefaults({
-    vectorStore,
-    docStore,
-    indexStore,
+  // create Azure CosmosDB as a vector store
+  const vectorStore = new AzureCosmosDBNoSqlVectorStore({
+    client: cosmosClient,
+    databaseName,
+    containerName: vectorCollectionName,
+    flatMetadata: false,
  });
+
+  // Store the embeddings in the CosmosDB container
+  const storageContext = await storageContextFromDefaults({ vectorStore });
  await VectorStoreIndex.fromDocuments(documents, { storageContext });
  console.log(
    `Successfully created embeddings in the CosmosDB container ${vectorCollectionName}.`,
@@ -3,21 +3,17 @@ import { DefaultAzureCredential } from "@azure/identity";
 import * as dotenv from "dotenv";
 import {
  AzureCosmosDBNoSQLConfig,
+  AzureCosmosDBNoSqlVectorStore,
  OpenAI,
  OpenAIEmbedding,
  Settings,
-  storageContextFromDefaults,
  VectorStoreIndex,
 } from "llamaindex";
-import {
-  createStoresFromConnectionString,
-  createStoresFromManagedIdentity,
-} from "./utils";

 // Load environment variables from local .env file
 dotenv.config();

-const cosmosEndpoint = process.env.AZURE_COSMOSDB_NOSQL_ACCOUNT_ENDPOINT!;
+const cosmosEndpoint = process.env.AZURE_COSMOSDB_NOSQL_ENDPOINT!;
 const cosmosConnectionString =
  process.env.AZURE_COSMOSDB_NOSQL_CONNECTION_STRING!;
 const databaseName =
@@ -44,27 +40,6 @@ const embedModelInit = {
 Settings.llm = new OpenAI(llmInit);
 Settings.embedModel = new OpenAIEmbedding(embedModelInit);

-async function initializeStores() {
-  // Create a configuration object for the Azure CosmosDB NoSQL Vector Store
-  const dbConfig: AzureCosmosDBNoSQLConfig = {
-    databaseName,
-    containerName,
-    flatMetadata: false,
-  };
-
-  if (cosmosConnectionString) {
-    return createStoresFromConnectionString(cosmosConnectionString, dbConfig);
-  } else {
-    // Use managed identity to authenticate with Azure CosmosDB
-    const credential = new DefaultAzureCredential();
-    return createStoresFromManagedIdentity(
-      cosmosEndpoint,
-      credential,
-      dbConfig,
-    );
-  }
-}
-
 async function query() {
  if (!cosmosConnectionString && !cosmosEndpoint) {
    throw new Error(
@@ -83,18 +58,17 @@ async function query() {
    });
  }

-  // use Azure CosmosDB as a vectorStore, docStore, and indexStore
-  const { vectorStore, docStore, indexStore } = await initializeStores();
-
-  // Store the embeddings in the CosmosDB container
-  const storageContext = await storageContextFromDefaults({
-    vectorStore,
-    docStore,
-    indexStore,
-  });
+  // configure the Azure CosmosDB NoSQL Vector Store
+  const dbConfig: AzureCosmosDBNoSQLConfig = {
+    client: cosmosClient,
+    databaseName,
+    containerName,
+    flatMetadata: false,
+  };
+  const store = new AzureCosmosDBNoSqlVectorStore(dbConfig);

  // create an index from the Azure CosmosDB NoSQL Vector Store
-  const index = await VectorStoreIndex.init({ storageContext });
+  const index = await VectorStoreIndex.fromVectorStore(store);

  // create a retriever and a query engine from the index
  const retriever = index.asRetriever({ similarityTopK: 20 });
@@ -1,51 +0,0 @@
-import { TokenCredential } from "@azure/identity";
-import {
-  AzureCosmosDBNoSQLConfig,
-  AzureCosmosDBNoSqlVectorStore,
-  AzureCosmosNoSqlDocumentStore,
-  AzureCosmosNoSqlIndexStore,
-} from "llamaindex";
-
-/**
- * Util function to create AzureCosmosDB vectorStore, docStore, indexStore from connection string.
- */
-export const createStoresFromConnectionString = (
-  connectionString: string,
-  dbConfig: AzureCosmosDBNoSQLConfig,
-) => {
-  const vectorStore = AzureCosmosDBNoSqlVectorStore.fromConnectionString({
-    connectionString,
-    ...dbConfig,
-  });
-  const docStore = AzureCosmosNoSqlDocumentStore.fromConnectionString({
-    connectionString,
-  });
-  const indexStore = AzureCosmosNoSqlIndexStore.fromConnectionString({
-    connectionString,
-  });
-  return { vectorStore, docStore, indexStore };
-};
-
-/**
- * Util function to create AzureCosmosDB vectorStore, docStore, indexStore from connection string.
- */
-export const createStoresFromManagedIdentity = (
-  endpoint: string,
-  credential: TokenCredential,
-  dbConfig: AzureCosmosDBNoSQLConfig,
-) => {
-  const vectorStore = AzureCosmosDBNoSqlVectorStore.fromUriAndManagedIdentity({
-    endpoint,
-    credential,
-    ...dbConfig,
-  });
-  const docStore = AzureCosmosNoSqlDocumentStore.fromAadToken({
-    endpoint,
-    credential,
-  });
-  const indexStore = AzureCosmosNoSqlIndexStore.fromAadToken({
-    endpoint,
-    credential,
-  });
-  return { vectorStore, docStore, indexStore };
-};
@@ -1,27 +1,24 @@
 {
  "name": "@llamaindex/examples",
  "private": true,
-  "version": "0.0.20",
+  "version": "0.0.12",
  "dependencies": {
-    "@ai-sdk/openai": "^1.0.5",
    "@aws-crypto/sha256-js": "^5.2.0",
    "@azure/cosmos": "^4.1.1",
    "@azure/identity": "^4.4.1",
    "@datastax/astra-db-ts": "^1.4.1",
-    "@llamaindex/core": "^0.4.18",
-    "@llamaindex/readers": "^1.0.20",
-    "@llamaindex/workflow": "^0.0.8",
-    "@llamaindex/vercel": "^0.0.5",
+    "@llamaindex/core": "^0.4.0",
+    "@llamaindex/readers": "^1.0.0",
+    "@llamaindex/workflow": "^0.0.2",
    "@notionhq/client": "^2.2.15",
-    "@pinecone-database/pinecone": "^4.0.0",
+    "@pinecone-database/pinecone": "^3.0.2",
    "@vercel/postgres": "^0.10.0",
    "@zilliz/milvus2-sdk-node": "^2.4.6",
-    "ai": "^4.0.0",
    "chromadb": "^1.8.1",
    "commander": "^12.1.0",
    "dotenv": "^16.4.5",
    "js-tiktoken": "^1.0.14",
-    "llamaindex": "^0.8.27",
+    "llamaindex": "^0.8.0",
    "mongodb": "^6.7.0",
    "pathe": "^1.1.2",
    "postgres": "^3.4.4"
@@ -1,15 +1,16 @@
+import fs from "node:fs/promises";
+
 import {
  Document,
  IngestionPipeline,
+  MetadataMode,
  OpenAIEmbedding,
  SentenceSplitter,
-  VectorStoreIndex,
 } from "llamaindex";
-import fs from "node:fs/promises";

 async function main() {
  // Load essay from abramov.txt in Node
-  const path = "../node_modules/llamaindex/examples/abramov.txt";
+  const path = "node_modules/llamaindex/examples/abramov.txt";

  const essay = await fs.readFile(path, "utf-8");

@@ -21,23 +22,14 @@ async function main() {
      new OpenAIEmbedding(),
    ],
  });
-  console.time("Pipeline Run Time");

+  // run the pipeline
  const nodes = await pipeline.run({ documents: [document] });

-  console.timeEnd("Pipeline Run Time");
-
-  // initialize the VectorStoreIndex from nodes
-  const index = await VectorStoreIndex.init({ nodes });
-
-  // Query the index
-  const queryEngine = index.asQueryEngine();
-
-  const { message } = await queryEngine.query({
-    query: "summarize the article in three sentence",
-  });
-
-  console.log(message);
+  // print out the result of the pipeline run
+  for (const node of nodes) {
+    console.log(node.getContent(MetadataMode.NONE));
+  }
 }

 main().catch(console.error);
@@ -15,8 +15,7 @@
    "start:llamaparse-dir": "node --import tsx ./src/simple-directory-reader-with-llamaparse.ts",
    "start:llamaparse-json": "node --import tsx ./src/llamaparse-json.ts",
    "start:discord": "node --import tsx ./src/discord.ts",
-    "start:json": "node --import tsx ./src/json.ts",
-    "start:obsidian": "node --import tsx ./src/obsidian.ts"
+    "start:json": "node --import tsx ./src/json.ts"
  },
  "dependencies": {
    "@llamaindex/readers": "*",
@@ -1,12 +0,0 @@
-import { ObsidianReader } from "@llamaindex/readers/obsidian";
-
-const obsidianReader = new ObsidianReader(
-  "/Users/jingyi/Documents/jingyi-vault",
-);
-
-obsidianReader.loadData().then((documents) => {
-  console.log("documents:", documents.length);
-  documents.forEach((doc) => {
-    console.log(`document (${doc.id_}):`, doc.getText());
-  });
-});
@@ -14,6 +14,7 @@ Settings.llm = new Ollama({

 Settings.embedModel = new HuggingFaceEmbedding({
  modelType: "BAAI/bge-small-en-v1.5",
+  quantized: false,
 });

 async function main() {
@@ -1,60 +0,0 @@
-# Vercel Examples
-
-These examples demonstrate how to integrate LlamaIndexTS with Vercel's AI SDK. The examples show how to use LlamaIndex for search and retrieval in both local vector store and LlamaCloud environments.
-
-## Setup
-
-To run these examples, first install the required dependencies from the parent folder `examples`:
-
-```bash
-npm i
-```
-
-## Running the Examples
-
-Make sure to run the examples from the parent folder called `examples`. The following examples are available:
-
-### Vercel LLM Example
-
-Run the Vercel LLM example with:
-
-```bash
-npx tsx vercel/llm.ts
-```
-
-This example demonstrates using the `VercelLLM` adapter with Vercel's OpenAI model provider
-
-### Vector Store Example
-
-Run the local vector store example with:
-
-```bash
-npx tsx vercel/vector-store.ts
-```
-
-This example demonstrates:
-
- Creating a vector store index from one document
- Using Vercel's AI SDK with LlamaIndex for streaming responses
-
-### LlamaCloud Example
-
-To run the LlamaCloud example:
-
-```bash
-npx tsx vercel/llamacloud.ts
-```
-
-This example requires a LlamaCloud API key set in your environment and an embedding model set in the `EMBEDDING_MODEL` environment variable:
-
-```bash
-export LLAMA_CLOUD_API_KEY=your_api_key_here
-export EMBEDDING_MODEL="text-embedding-3-small"
-```
-
-The example demonstrates:
-
- Creating a LlamaCloud index from one document
- Streaming responses using Vercel's AI SDK
-
-For more detailed information about the Vercel integration, check out [the documentation](https://ts.llamaindex.ai/docs/llamaindex/integration/vercel).
@@ -1,39 +0,0 @@
-import { openai } from "@ai-sdk/openai";
-import { llamaindex } from "@llamaindex/vercel";
-import { streamText } from "ai";
-import { Document, LlamaCloudIndex } from "llamaindex";
-import fs from "node:fs/promises";
-
-async function main() {
-  const path = "node_modules/llamaindex/examples/abramov.txt";
-  const essay = await fs.readFile(path, "utf-8");
-  const document = new Document({ text: essay, id_: path });
-
-  const index = await LlamaCloudIndex.fromDocuments({
-    documents: [document],
-    name: "test-pipeline",
-    projectName: "Default",
-    apiKey: process.env.LLAMA_CLOUD_API_KEY,
-  });
-  console.log("Successfully created index");
-
-  const result = streamText({
-    model: openai("gpt-4o"),
-    prompt: "Cost of moving cat from Russia to UK?",
-    tools: {
-      queryTool: llamaindex({
-        model: openai("gpt-4o"),
-        index,
-        description:
-          "get information from your knowledge base to answer questions.", // optional description
-      }),
-    },
-    maxSteps: 5,
-  });
-
-  for await (const textPart of result.textStream) {
-    process.stdout.write(textPart);
-  }
-}
-
-main().catch(console.error);
@@ -1,45 +0,0 @@
-import { openai } from "@ai-sdk/openai";
-import { VercelLLM } from "@llamaindex/vercel";
-import { LLMAgent, WikipediaTool } from "llamaindex";
-
-async function main() {
-  // Create an instance of VercelLLM with the OpenAI model
-  const vercelLLM = new VercelLLM({ model: openai("gpt-4o") });
-
-  console.log("\n=== Test 1: Using complete() for single response ===");
-  const result = await vercelLLM.complete({
-    prompt: "What is the capital of France?",
-    stream: false, // Set to true if you want streaming responses
-  });
-  console.log(result.text);
-
-  console.log("\n=== Test 2: Using chat() for streaming response ===");
-  const stream = await vercelLLM.chat({
-    messages: [
-      { content: "You want to talk in rhymes.", role: "system" },
-      {
-        content:
-          "How much wood would a woodchuck chuck if a woodchuck could chuck wood?",
-        role: "user",
-      },
-    ],
-    stream: true,
-  });
-  for await (const chunk of stream) {
-    process.stdout.write(chunk.delta);
-  }
-
-  console.log("\n=== Test 3: Using LLMAgent with WikipediaTool ===");
-  const agent = new LLMAgent({
-    llm: vercelLLM,
-    tools: [new WikipediaTool()],
-  });
-
-  const { message } = await agent.chat({
-    message: "What's the history of New York from Wikipedia in 3 sentences?",
-  });
-
-  console.log(message);
-}
-
-main().catch(console.error);
@@ -1,35 +0,0 @@
-import { openai } from "@ai-sdk/openai";
-import { llamaindex } from "@llamaindex/vercel";
-import { streamText } from "ai";
-import { Document, VectorStoreIndex } from "llamaindex";
-
-import fs from "node:fs/promises";
-
-async function main() {
-  const path = "node_modules/llamaindex/examples/abramov.txt";
-  const essay = await fs.readFile(path, "utf-8");
-  const document = new Document({ text: essay, id_: path });
-
-  const index = await VectorStoreIndex.fromDocuments([document]);
-  console.log("Successfully created index");
-
-  const result = streamText({
-    model: openai("gpt-4o"),
-    prompt: "Cost of moving cat from Russia to UK?",
-    tools: {
-      queryTool: llamaindex({
-        model: openai("gpt-4o"),
-        index,
-        description:
-          "get information from your knowledge base to answer questions.", // optional description
-      }),
-    },
-    maxSteps: 5,
-  });
-
-  for await (const textPart of result.textStream) {
-    process.stdout.write(textPart);
-  }
-}
-
-main().catch(console.error);
@@ -1,16 +0,0 @@
-import { VLLM } from "llamaindex";
-
-const llm = new VLLM({
-  model: "NousResearch/Meta-Llama-3-8B-Instruct",
-});
-
-const response = await llm.chat({
-  messages: [
-    {
-      role: "user",
-      content: "Hello?",
-    },
-  ],
-});
-
-console.log(response.message.content);
@@ -1,19 +1,14 @@
 import {
-  HandlerContext,
+  Context,
  StartEvent,
  StopEvent,
  Workflow,
  WorkflowEvent,
-} from "@llamaindex/workflow";
+} from "@llamaindex/core/workflow";
 import { OpenAI } from "llamaindex";

 const MAX_REVIEWS = 3;

-type Context = {
-  specification: string;
-  numberReviews: number;
-};
-
 // Using the o1-preview model (see https://platform.openai.com/docs/guides/reasoning?reasoning-prompt-examples=coding-planning)
 const llm = new OpenAI({ model: "o1-preview", temperature: 1 });

@@ -25,9 +20,7 @@ stores the question/answer pair in the database.`;

 // Create custom event types
 export class MessageEvent extends WorkflowEvent<{ msg: string }> {}
-
 export class CodeEvent extends WorkflowEvent<{ code: string }> {}
-
 export class ReviewEvent extends WorkflowEvent<{
  review: string;
  code: string;
@@ -41,13 +34,12 @@ const truncate = (str: string) => {
 };

 // the architect is responsible for writing the structure and the initial code based on the specification
-const architect = async (
-  context: HandlerContext<Context>,
-  _: StartEvent<string>,
-) => {
-  const spec = context.data.specification;
+const architect = async (context: Context, ev: StartEvent) => {
+  // get the specification from the start event and save it to context
+  context.set("specification", ev.data.input);
+  const spec = context.get("specification");
  // write a message to send an update to the user
-  context.sendEvent(
+  context.writeEventToStream(
    new MessageEvent({
      msg: `Writing app using this specification: ${truncate(spec)}`,
    }),
@@ -58,13 +50,13 @@ const architect = async (
 };

 // the coder is responsible for updating the code based on the review
-const coder = async (context: HandlerContext<Context>, ev: ReviewEvent) => {
+const coder = async (context: Context, ev: ReviewEvent) => {
  // get the specification from the context
-  const spec = context.data.specification;
+  const spec = context.get("specification");
  // get the latest review and code
  const { review, code } = ev.data;
  // write a message to send an update to the user
-  context.sendEvent(
+  context.writeEventToStream(
    new MessageEvent({
      msg: `Update code based on review: ${truncate(review)}`,
    }),
@@ -75,35 +67,32 @@ const coder = async (context: HandlerContext<Context>, ev: ReviewEvent) => {
 };

 // the reviewer is responsible for reviewing the code and providing feedback
-const reviewer = async (context: HandlerContext<Context>, ev: CodeEvent) => {
+const reviewer = async (context: Context, ev: CodeEvent) => {
  // get the specification from the context
-  const spec = context.data.specification;
+  const spec = context.get("specification");
  // get latest code from the event
  const { code } = ev.data;
  // update and check the number of reviews
-  context.data.numberReviews++;
-  if (context.data.numberReviews > MAX_REVIEWS) {
+  const numberReviews = context.get("numberReviews", 0) + 1;
+  context.set("numberReviews", numberReviews);
+  if (numberReviews > MAX_REVIEWS) {
    // the we've done this too many times - return the code
-    context.sendEvent(
+    context.writeEventToStream(
      new MessageEvent({
-        msg: `Already reviewed ${
-          context.data.numberReviews - 1
-        } times, stopping!`,
+        msg: `Already reviewed ${numberReviews - 1} times, stopping!`,
      }),
    );
    return new StopEvent({ result: code });
  }
  // write a message to send an update to the user
-  context.sendEvent(
-    new MessageEvent({
-      msg: `Review #${context.data.numberReviews}: ${truncate(code)}`,
-    }),
+  context.writeEventToStream(
+    new MessageEvent({ msg: `Review #${numberReviews}: ${truncate(code)}` }),
  );
  const prompt = `Review this code: <code>${code}</code>. Check if the code quality and whether it correctly implements this specification: <spec>${spec}</spec>. If you're satisfied, just return 'Looks great', nothing else. If not, return a review with a list of changes you'd like to see.`;
  const review = (await llm.complete({ prompt })).text;
  if (review.includes("Looks great")) {
    // the reviewer is satisfied with the code, let's return the review
-    context.sendEvent(
+    context.writeEventToStream(
      new MessageEvent({
        msg: `Reviewer says: ${review}`,
      }),
@@ -114,44 +103,20 @@ const reviewer = async (context: HandlerContext<Context>, ev: CodeEvent) => {
  return new ReviewEvent({ review, code });
 };

-const codeAgent = new Workflow<Context, string, string>();
-codeAgent.addStep(
-  {
-    inputs: [StartEvent<string>],
-    outputs: [CodeEvent],
-  },
-  architect,
-);
-codeAgent.addStep(
-  {
-    inputs: [ReviewEvent],
-    outputs: [CodeEvent],
-  },
-  coder,
-);
-codeAgent.addStep(
-  {
-    inputs: [CodeEvent],
-    outputs: [ReviewEvent, StopEvent],
-  },
-  reviewer,
-);
+const codeAgent = new Workflow({ validate: true });
+codeAgent.addStep(StartEvent, architect, { outputs: CodeEvent });
+codeAgent.addStep(ReviewEvent, coder, { outputs: CodeEvent });
+codeAgent.addStep(CodeEvent, reviewer, { outputs: ReviewEvent });

 // Usage
 async function main() {
-  const run = codeAgent.run(specification).with({
-    specification,
-    numberReviews: 0,
-  });
-  for await (const event of run) {
-    if (event instanceof MessageEvent) {
-      const msg = (event as MessageEvent).data.msg;
-      console.log(`${msg}\n`);
-    } else if (event instanceof StopEvent) {
-      const result = (event as StopEvent<string>).data;
-      console.log("Final code:\n", result);
-    }
+  const run = codeAgent.run(specification);
+  for await (const event of codeAgent.streamEvents()) {
+    const msg = (event as MessageEvent).data.msg;
+    console.log(`${msg}\n`);
  }
+  const result = await run;
+  console.log("Final code:\n", result.data.result);
 }

 main().catch(console.error);
@@ -1,10 +1,10 @@
 import {
-  HandlerContext,
+  Context,
  StartEvent,
  StopEvent,
  Workflow,
  WorkflowEvent,
-} from "@llamaindex/workflow";
+} from "@llamaindex/core/workflow";
 import { OpenAI } from "llamaindex";

 // Create LLM instance
@@ -12,77 +12,59 @@ const llm = new OpenAI();

 // Create custom event types
 export class JokeEvent extends WorkflowEvent<{ joke: string }> {}
-
 export class CritiqueEvent extends WorkflowEvent<{ critique: string }> {}
-
 export class AnalysisEvent extends WorkflowEvent<{ analysis: string }> {}

-const generateJoke = async (_: unknown, ev: StartEvent<string>) => {
-  const prompt = `Write your best joke about ${ev.data}.`;
+const generateJoke = async (_context: Context, ev: StartEvent) => {
+  const prompt = `Write your best joke about ${ev.data.input}.`;
  const response = await llm.complete({ prompt });
  return new JokeEvent({ joke: response.text });
 };

-const critiqueJoke = async (_: unknown, ev: JokeEvent) => {
+const critiqueJoke = async (_context: Context, ev: JokeEvent) => {
  const prompt = `Give a thorough critique of the following joke: ${ev.data.joke}`;
  const response = await llm.complete({ prompt });
  return new CritiqueEvent({ critique: response.text });
 };

-const analyzeJoke = async (_: unknown, ev: JokeEvent) => {
+const analyzeJoke = async (_context: Context, ev: JokeEvent) => {
  const prompt = `Give a thorough analysis of the following joke: ${ev.data.joke}`;
  const response = await llm.complete({ prompt });
  return new AnalysisEvent({ analysis: response.text });
 };

 const reportJoke = async (
-  context: HandlerContext,
-  ev1: AnalysisEvent,
-  ev2: CritiqueEvent,
+  context: Context,
+  ev: AnalysisEvent | CritiqueEvent,
 ) => {
-  const subPrompts = [ev1.data.analysis, ev2.data.critique];
+  const events = context.collectEvents(ev, [AnalysisEvent, CritiqueEvent]);
+  if (!events) {
+    return;
+  }
+  const subPrompts = events.map((event) => {
+    if (event instanceof AnalysisEvent) {
+      return `Analysis: ${event.data.analysis}`;
+    } else if (event instanceof CritiqueEvent) {
+      return `Critique: ${event.data.critique}`;
+    }
+    return "";
+  });

-  const prompt = `Based on the following information about a joke:\n${subPrompts.join(
-    "\n",
-  )}\nProvide a comprehensive report on the joke's quality and impact.`;
+  const prompt = `Based on the following information about a joke:\n${subPrompts.join("\n")}\nProvide a comprehensive report on the joke's quality and impact.`;
  const response = await llm.complete({ prompt });
-  return new StopEvent(response.text);
+  return new StopEvent({ result: response.text });
 };

-const jokeFlow = new Workflow<unknown, string, string>();
-jokeFlow.addStep(
-  {
-    inputs: [StartEvent<string>],
-    outputs: [JokeEvent],
-  },
-  generateJoke,
-);
-jokeFlow.addStep(
-  {
-    inputs: [JokeEvent],
-    outputs: [CritiqueEvent],
-  },
-  critiqueJoke,
-);
-jokeFlow.addStep(
-  {
-    inputs: [JokeEvent],
-    outputs: [AnalysisEvent],
-  },
-  analyzeJoke,
-);
-jokeFlow.addStep(
-  {
-    inputs: [AnalysisEvent, CritiqueEvent],
-    outputs: [StopEvent<string>],
-  },
-  reportJoke,
-);
+const jokeFlow = new Workflow();
+jokeFlow.addStep(StartEvent, generateJoke);
+jokeFlow.addStep(JokeEvent, critiqueJoke);
+jokeFlow.addStep(JokeEvent, analyzeJoke);
+jokeFlow.addStep([AnalysisEvent, CritiqueEvent], reportJoke);

 // Usage
 async function main() {
  const result = await jokeFlow.run("pirates");
-  console.log(result.data);
+  console.log(result.data.result);
 }

 main().catch(console.error);
@@ -1,9 +1,10 @@
 import {
+  Context,
  StartEvent,
  StopEvent,
  Workflow,
  WorkflowEvent,
-} from "@llamaindex/workflow";
+} from "@llamaindex/core/workflow";
 import { OpenAI } from "llamaindex";

 // Create LLM instance
@@ -12,38 +13,26 @@ const llm = new OpenAI();
 // Create a custom event type
 export class JokeEvent extends WorkflowEvent<{ joke: string }> {}

-const generateJoke = async (_: unknown, ev: StartEvent<string>) => {
-  const prompt = `Write your best joke about ${ev.data}.`;
+const generateJoke = async (_context: Context, ev: StartEvent) => {
+  const prompt = `Write your best joke about ${ev.data.input}.`;
  const response = await llm.complete({ prompt });
  return new JokeEvent({ joke: response.text });
 };

-const critiqueJoke = async (_: unknown, ev: JokeEvent) => {
+const critiqueJoke = async (_context: Context, ev: JokeEvent) => {
  const prompt = `Give a thorough critique of the following joke: ${ev.data.joke}`;
  const response = await llm.complete({ prompt });
-  return new StopEvent(response.text);
+  return new StopEvent({ result: response.text });
 };

-const jokeFlow = new Workflow<unknown, string, string>();
-jokeFlow.addStep(
-  {
-    inputs: [StartEvent<string>],
-    outputs: [JokeEvent],
-  },
-  generateJoke,
-);
-jokeFlow.addStep(
-  {
-    inputs: [JokeEvent],
-    outputs: [StopEvent<string>],
-  },
-  critiqueJoke,
-);
+const jokeFlow = new Workflow({ verbose: true });
+jokeFlow.addStep(StartEvent, generateJoke);
+jokeFlow.addStep(JokeEvent, critiqueJoke);

 // Usage
 async function main() {
  const result = await jokeFlow.run("pirates");
-  console.log(result.data);
+  console.log(result.data.result);
 }

 main().catch(console.error);
@@ -1,10 +1,10 @@
 import {
-  HandlerContext,
+  Context,
  StartEvent,
  StopEvent,
  Workflow,
  WorkflowEvent,
-} from "@llamaindex/workflow";
+} from "@llamaindex/core/workflow";
 import { OpenAI } from "llamaindex";

 // Create LLM instance
@@ -12,55 +12,38 @@ const llm = new OpenAI();

 // Create custom event types
 export class JokeEvent extends WorkflowEvent<{ joke: string }> {}
-
 export class MessageEvent extends WorkflowEvent<{ msg: string }> {}

-const generateJoke = async (context: HandlerContext, ev: StartEvent) => {
-  context.sendEvent(
-    new MessageEvent({ msg: `Generating a joke about: ${ev.data}` }),
+const generateJoke = async (context: Context, ev: StartEvent) => {
+  context.writeEventToStream(
+    new MessageEvent({ msg: `Generating a joke about: ${ev.data.input}` }),
  );
-  const prompt = `Write your best joke about ${ev.data}.`;
+  const prompt = `Write your best joke about ${ev.data.input}.`;
  const response = await llm.complete({ prompt });
  return new JokeEvent({ joke: response.text });
 };

-const critiqueJoke = async (context: HandlerContext, ev: JokeEvent) => {
-  context.sendEvent(
+const critiqueJoke = async (context: Context, ev: JokeEvent) => {
+  context.writeEventToStream(
    new MessageEvent({ msg: `Write a critique of this joke: ${ev.data.joke}` }),
  );
  const prompt = `Give a thorough critique of the following joke: ${ev.data.joke}`;
  const response = await llm.complete({ prompt });
-  return new StopEvent(response.text);
+  return new StopEvent({ result: response.text });
 };

 const jokeFlow = new Workflow();
-jokeFlow.addStep(
-  {
-    inputs: [StartEvent<string>],
-    outputs: [JokeEvent],
-  },
-  generateJoke,
-);
-jokeFlow.addStep(
-  {
-    inputs: [JokeEvent],
-    outputs: [StopEvent<string>],
-  },
-  critiqueJoke,
-);
+jokeFlow.addStep(StartEvent, generateJoke);
+jokeFlow.addStep(JokeEvent, critiqueJoke);

 // Usage
 async function main() {
  const run = jokeFlow.run("pirates");
-  for await (const event of run) {
-    if (event instanceof MessageEvent) {
-      console.log("Message:");
-      console.log((event as MessageEvent).data.msg);
-    } else if (event instanceof StopEvent) {
-      console.log("Result:");
-      console.log((event as StopEvent<string>).data);
-    }
+  for await (const event of jokeFlow.streamEvents()) {
+    console.log((event as MessageEvent).data.msg);
  }
+  const result = await run;
+  console.log(result.data.result);
 }

 main().catch(console.error);
@@ -1,21 +1,19 @@
-import { StartEvent, StopEvent, Workflow } from "@llamaindex/workflow";
+import {
+  Context,
+  StartEvent,
+  StopEvent,
+  Workflow,
+} from "@llamaindex/core/workflow";

-const longRunning = async (_: unknown, ev: StartEvent<string>) => {
+const longRunning = async (_context: Context, ev: StartEvent) => {
  await new Promise((resolve) => setTimeout(resolve, 2000)); // Wait for 2 seconds
-  return new StopEvent("We waited 2 seconds");
+  return new StopEvent({ result: "We waited 2 seconds" });
 };

 async function timeout() {
-  const workflow = new Workflow<unknown, string, string>({
-    timeout: 1,
-  });
-  workflow.addStep(
-    {
-      inputs: [StartEvent<string>],
-      outputs: [StopEvent<string>],
-    },
-    longRunning,
-  );
+  const workflow = new Workflow({ verbose: true, timeout: 1 });
+  workflow.addStep(StartEvent, longRunning);
+  // This will timeout
  try {
    await workflow.run("Let's start");
  } catch (error) {
@@ -25,23 +23,14 @@ async function timeout() {

 async function notimeout() {
  // Increase timeout to 3 seconds - no timeout
-  const workflow = new Workflow<unknown, string, string>({
-    timeout: 3,
-  });
-  workflow.addStep(
-    {
-      inputs: [StartEvent<string>],
-      outputs: [StopEvent<string>],
-    },
-    longRunning,
-  );
+  const workflow = new Workflow({ verbose: true, timeout: 3 });
+  workflow.addStep(StartEvent, longRunning);
  const result = await workflow.run("Let's start");
-  console.log(result.data);
+  console.log(result.data.result);
 }

 async function main() {
  await timeout();
-  console.log("---");
  await notimeout();
 }

@@ -1,9 +1,10 @@
 import {
+  Context,
  StartEvent,
  StopEvent,
  Workflow,
  WorkflowEvent,
-} from "@llamaindex/workflow";
+} from "@llamaindex/core/workflow";
 import { OpenAI } from "llamaindex";

 // Create LLM instance
@@ -12,66 +13,40 @@ const llm = new OpenAI();
 // Create a custom event type
 export class JokeEvent extends WorkflowEvent<{ joke: string }> {}

-const generateJoke = async (_: unknown, ev: StartEvent<string>) => {
-  const prompt = `Write your best joke about ${ev.data}.`;
+const generateJoke = async (_context: Context, ev: StartEvent) => {
+  const prompt = `Write your best joke about ${ev.data.input}.`;
  const response = await llm.complete({ prompt });
  return new JokeEvent({ joke: response.text });
 };

-const critiqueJoke = async (_: unknown, ev: JokeEvent) => {
+const critiqueJoke = async (_context: Context, ev: JokeEvent) => {
  const prompt = `Give a thorough critique of the following joke: ${ev.data.joke}`;
  const response = await llm.complete({ prompt });
-  return new StopEvent(response.text);
+  return new StopEvent({ result: response.text });
 };

 async function validateFails() {
  try {
-    const jokeFlow = new Workflow();
-    jokeFlow.addStep(
-      {
-        inputs: [StartEvent<string>],
-        outputs: [StopEvent<string>],
-      },
-      // @ts-expect-error outputs should be JokeEvent
-      generateJoke,
-    );
-    jokeFlow.addStep(
-      {
-        inputs: [JokeEvent],
-        outputs: [StopEvent],
-      },
-      critiqueJoke,
-    );
-    await jokeFlow.run("pirates").strict();
+    const jokeFlow = new Workflow({ verbose: true, validate: true });
+    jokeFlow.addStep(StartEvent, generateJoke, { outputs: StopEvent });
+    jokeFlow.addStep(JokeEvent, critiqueJoke, { outputs: StopEvent });
+    await jokeFlow.run("pirates");
  } catch (e) {
    console.error("Validation failed:", e);
  }
 }

 async function validate() {
-  const jokeFlow = new Workflow();
-  jokeFlow.addStep(
-    {
-      inputs: [StartEvent<string>],
-      outputs: [JokeEvent],
-    },
-    generateJoke,
-  );
-  jokeFlow.addStep(
-    {
-      inputs: [JokeEvent],
-      outputs: [StopEvent<string>],
-    },
-    critiqueJoke,
-  );
-  const result = await jokeFlow.run("pirates").strict();
-  console.log(result.data);
+  const jokeFlow = new Workflow({ verbose: true, validate: true });
+  jokeFlow.addStep(StartEvent, generateJoke, { outputs: JokeEvent });
+  jokeFlow.addStep(JokeEvent, critiqueJoke, { outputs: StopEvent });
+  const result = await jokeFlow.run("pirates");
+  console.log(result.data.result);
 }

 // Usage
 async function main() {
  await validateFails();
-  console.log("---");
  await validate();
 }

@@ -2,8 +2,8 @@
  "name": "@llamaindex/monorepo",
  "private": true,
  "scripts": {
-    "build": "turbo run build --filter=\"./packages/*\" --filter=\"./packages/providers/*\"",
-    "dev": "turbo run dev --filter=\"./packages/*\" --filter=\"./packages/providers/*\"",
+    "build": "turbo run build --filter=\"./packages/*\"",
+    "dev": "turbo run dev --filter=\"./packages/*\"",
    "format": "prettier --ignore-unknown --cache --check .",
    "format:write": "prettier --ignore-unknown --write .",
    "lint": "turbo run lint",
@@ -19,22 +19,28 @@
  },
  "devDependencies": {
    "@changesets/cli": "^2.27.5",
-    "eslint": "9.15.0",
-    "eslint-config-next": "^15.0.3",
+    "eslint": "9.14.0",
+    "eslint-config-next": "^15.0.2",
    "eslint-config-prettier": "^9.1.0",
-    "eslint-config-turbo": "^2.3.0",
+    "eslint-config-turbo": "^2.2.3",
    "eslint-plugin-react": "7.37.2",
    "globals": "^15.12.0",
-    "husky": "^9.1.7",
+    "husky": "^9.1.6",
    "lint-staged": "^15.2.10",
    "madge": "^8.0.0",
    "prettier": "^3.3.3",
    "prettier-plugin-organize-imports": "^4.1.0",
-    "turbo": "^2.3.0",
+    "turbo": "^2.2.3",
    "typescript": "^5.6.3",
-    "typescript-eslint": "^8.15.0"
+    "typescript-eslint": "^8.13.0"
  },
  "packageManager": "pnpm@9.12.3",
+  "pnpm": {
+    "overrides": {
+      "trim": "1.0.1",
+      "protobufjs": "7.2.6"
+    }
+  },
  "lint-staged": {
    "(!apps/docs/i18n/**/docusaurus-plugin-content-docs/current/api/*).{js,jsx,ts,tsx,md}": "prettier --write"
  }
@@ -1,167 +1,5 @@
 # @llamaindex/autotool

-## 5.0.27
-
-### Patch Changes
-
- Updated dependencies [b504303]
- Updated dependencies [a0e6f57]
-  - llamaindex@0.8.27
-
-## 5.0.26
-
-### Patch Changes
-
- 3d1808b: chore: bump version
- Updated dependencies [3d1808b]
-  - llamaindex@0.8.26
-
-## 5.0.25
-
-### Patch Changes
-
- 8be4589: chore: bump version
-  - llamaindex@0.8.25
-
-## 5.0.24
-
-### Patch Changes
-
- Updated dependencies [515f2c1]
-  - llamaindex@0.8.24
-
-## 5.0.23
-
-### Patch Changes
-
- llamaindex@0.8.23
-
-## 5.0.22
-
-### Patch Changes
-
- Updated dependencies [819af45]
-  - llamaindex@0.8.22
-
-## 5.0.21
-
-### Patch Changes
-
- Updated dependencies [83c3897]
- Updated dependencies [efa2211]
-  - llamaindex@0.8.21
-
-## 5.0.20
-
-### Patch Changes
-
- Updated dependencies [02b22da]
-  - llamaindex@0.8.20
-
-## 5.0.19
-
-### Patch Changes
-
- 90d265c: chore: bump version
- Updated dependencies [90d265c]
-  - llamaindex@0.8.19
-
-## 5.0.18
-
-### Patch Changes
-
- Updated dependencies [d17450f]
-  - llamaindex@0.8.18
-
-## 5.0.17
-
-### Patch Changes
-
- llamaindex@0.8.17
-
-## 5.0.16
-
-### Patch Changes
-
- llamaindex@0.8.16
-
-## 5.0.15
-
-### Patch Changes
-
- Updated dependencies [3d503cb]
- Updated dependencies [5dae534]
-  - llamaindex@0.8.15
-
-## 5.0.14
-
-### Patch Changes
-
- Updated dependencies [630b425]
-  - llamaindex@0.8.14
-
-## 5.0.13
-
-### Patch Changes
-
- llamaindex@0.8.13
-
-## 5.0.12
-
-### Patch Changes
-
- llamaindex@0.8.12
-
-## 5.0.11
-
-### Patch Changes
-
- llamaindex@0.8.11
-
-## 5.0.10
-
-### Patch Changes
-
- Updated dependencies [f066e50]
-  - llamaindex@0.8.10
-
-## 5.0.9
-
-### Patch Changes
-
- Updated dependencies [4fc001c]
- Updated dependencies [4d4cd8a]
-  - llamaindex@0.8.9
-
-## 5.0.8
-
-### Patch Changes
-
- Updated dependencies [ad85bd0]
-  - llamaindex@0.8.8
-
-## 5.0.7
-
-### Patch Changes
-
- llamaindex@0.8.7
-
-## 5.0.6
-
-### Patch Changes
-
- Updated dependencies [95a5cc6]
-  - llamaindex@0.8.6
-
-## 5.0.5
-
-### Patch Changes
-
- Updated dependencies [14cc9eb]
- Updated dependencies [a6db5dd]
- Updated dependencies [396b1e1]
-  - llamaindex@0.8.5
-
 ## 5.0.4

 ### Patch Changes
@@ -1,188 +1,5 @@
 # @llamaindex/autotool-01-node-example

-## 0.0.70
-
-### Patch Changes
-
- Updated dependencies [b504303]
- Updated dependencies [a0e6f57]
-  - llamaindex@0.8.27
-  - @llamaindex/autotool@5.0.27
-
-## 0.0.69
-
-### Patch Changes
-
- Updated dependencies [3d1808b]
-  - @llamaindex/autotool@5.0.26
-  - llamaindex@0.8.26
-
-## 0.0.68
-
-### Patch Changes
-
- Updated dependencies [8be4589]
-  - @llamaindex/autotool@5.0.25
-  - llamaindex@0.8.25
-
-## 0.0.67
-
-### Patch Changes
-
- Updated dependencies [515f2c1]
-  - llamaindex@0.8.24
-  - @llamaindex/autotool@5.0.24
-
-## 0.0.66
-
-### Patch Changes
-
- llamaindex@0.8.23
- @llamaindex/autotool@5.0.23
-
-## 0.0.65
-
-### Patch Changes
-
- Updated dependencies [819af45]
-  - llamaindex@0.8.22
-  - @llamaindex/autotool@5.0.22
-
-## 0.0.64
-
-### Patch Changes
-
- Updated dependencies [83c3897]
- Updated dependencies [efa2211]
-  - llamaindex@0.8.21
-  - @llamaindex/autotool@5.0.21
-
-## 0.0.63
-
-### Patch Changes
-
- Updated dependencies [02b22da]
-  - llamaindex@0.8.20
-  - @llamaindex/autotool@5.0.20
-
-## 0.0.62
-
-### Patch Changes
-
- Updated dependencies [90d265c]
-  - @llamaindex/autotool@5.0.19
-  - llamaindex@0.8.19
-
-## 0.0.61
-
-### Patch Changes
-
- Updated dependencies [d17450f]
-  - llamaindex@0.8.18
-  - @llamaindex/autotool@5.0.18
-
-## 0.0.60
-
-### Patch Changes
-
- llamaindex@0.8.17
- @llamaindex/autotool@5.0.17
-
-## 0.0.59
-
-### Patch Changes
-
- llamaindex@0.8.16
- @llamaindex/autotool@5.0.16
-
-## 0.0.58
-
-### Patch Changes
-
- Updated dependencies [3d503cb]
- Updated dependencies [5dae534]
-  - llamaindex@0.8.15
-  - @llamaindex/autotool@5.0.15
-
-## 0.0.57
-
-### Patch Changes
-
- Updated dependencies [630b425]
-  - llamaindex@0.8.14
-  - @llamaindex/autotool@5.0.14
-
-## 0.0.56
-
-### Patch Changes
-
- llamaindex@0.8.13
- @llamaindex/autotool@5.0.13
-
-## 0.0.55
-
-### Patch Changes
-
- llamaindex@0.8.12
- @llamaindex/autotool@5.0.12
-
-## 0.0.54
-
-### Patch Changes
-
- llamaindex@0.8.11
- @llamaindex/autotool@5.0.11
-
-## 0.0.53
-
-### Patch Changes
-
- Updated dependencies [f066e50]
-  - llamaindex@0.8.10
-  - @llamaindex/autotool@5.0.10
-
-## 0.0.52
-
-### Patch Changes
-
- Updated dependencies [4fc001c]
- Updated dependencies [4d4cd8a]
-  - llamaindex@0.8.9
-  - @llamaindex/autotool@5.0.9
-
-## 0.0.51
-
-### Patch Changes
-
- Updated dependencies [ad85bd0]
-  - llamaindex@0.8.8
-  - @llamaindex/autotool@5.0.8
-
-## 0.0.50
-
-### Patch Changes
-
- llamaindex@0.8.7
- @llamaindex/autotool@5.0.7
-
-## 0.0.49
-
-### Patch Changes
-
- Updated dependencies [95a5cc6]
-  - llamaindex@0.8.6
-  - @llamaindex/autotool@5.0.6
-
-## 0.0.48
-
-### Patch Changes
-
- Updated dependencies [14cc9eb]
- Updated dependencies [a6db5dd]
- Updated dependencies [396b1e1]
-  - llamaindex@0.8.5
-  - @llamaindex/autotool@5.0.5
-
 ## 0.0.47

 ### Patch Changes
@@ -5,7 +5,7 @@
  "dependencies": {
    "@llamaindex/autotool": "workspace:*",
    "llamaindex": "workspace:*",
-    "openai": "^4.73.1"
+    "openai": "^4.57.0"
  },
  "devDependencies": {
    "tsx": "^4.19.0"
@@ -13,5 +13,5 @@
  "scripts": {
    "start": "node --import tsx --import @llamaindex/autotool/node ./src/index.ts"
  },
-  "version": "0.0.70"
+  "version": "0.0.47"
 }
@@ -1,188 +1,5 @@
 # @llamaindex/autotool-02-next-example

-## 0.1.114
-
-### Patch Changes
-
- Updated dependencies [b504303]
- Updated dependencies [a0e6f57]
-  - llamaindex@0.8.27
-  - @llamaindex/autotool@5.0.27
-
-## 0.1.113
-
-### Patch Changes
-
- Updated dependencies [3d1808b]
-  - @llamaindex/autotool@5.0.26
-  - llamaindex@0.8.26
-
-## 0.1.112
-
-### Patch Changes
-
- Updated dependencies [8be4589]
-  - @llamaindex/autotool@5.0.25
-  - llamaindex@0.8.25
-
-## 0.1.111
-
-### Patch Changes
-
- Updated dependencies [515f2c1]
-  - llamaindex@0.8.24
-  - @llamaindex/autotool@5.0.24
-
-## 0.1.110
-
-### Patch Changes
-
- llamaindex@0.8.23
- @llamaindex/autotool@5.0.23
-
-## 0.1.109
-
-### Patch Changes
-
- Updated dependencies [819af45]
-  - llamaindex@0.8.22
-  - @llamaindex/autotool@5.0.22
-
-## 0.1.108
-
-### Patch Changes
-
- Updated dependencies [83c3897]
- Updated dependencies [efa2211]
-  - llamaindex@0.8.21
-  - @llamaindex/autotool@5.0.21
-
-## 0.1.107
-
-### Patch Changes
-
- Updated dependencies [02b22da]
-  - llamaindex@0.8.20
-  - @llamaindex/autotool@5.0.20
-
-## 0.1.106
-
-### Patch Changes
-
- Updated dependencies [90d265c]
-  - @llamaindex/autotool@5.0.19
-  - llamaindex@0.8.19
-
-## 0.1.105
-
-### Patch Changes
-
- Updated dependencies [d17450f]
-  - llamaindex@0.8.18
-  - @llamaindex/autotool@5.0.18
-
-## 0.1.104
-
-### Patch Changes
-
- llamaindex@0.8.17
- @llamaindex/autotool@5.0.17
-
-## 0.1.103
-
-### Patch Changes
-
- llamaindex@0.8.16
- @llamaindex/autotool@5.0.16
-
-## 0.1.102
-
-### Patch Changes
-
- Updated dependencies [3d503cb]
- Updated dependencies [5dae534]
-  - llamaindex@0.8.15
-  - @llamaindex/autotool@5.0.15
-
-## 0.1.101
-
-### Patch Changes
-
- Updated dependencies [630b425]
-  - llamaindex@0.8.14
-  - @llamaindex/autotool@5.0.14
-
-## 0.1.100
-
-### Patch Changes
-
- llamaindex@0.8.13
- @llamaindex/autotool@5.0.13
-
-## 0.1.99
-
-### Patch Changes
-
- llamaindex@0.8.12
- @llamaindex/autotool@5.0.12
-
-## 0.1.98
-
-### Patch Changes
-
- llamaindex@0.8.11
- @llamaindex/autotool@5.0.11
-
-## 0.1.97
-
-### Patch Changes
-
- Updated dependencies [f066e50]
-  - llamaindex@0.8.10
-  - @llamaindex/autotool@5.0.10
-
-## 0.1.96
-
-### Patch Changes
-
- Updated dependencies [4fc001c]
- Updated dependencies [4d4cd8a]
-  - llamaindex@0.8.9
-  - @llamaindex/autotool@5.0.9
-
-## 0.1.95
-
-### Patch Changes
-
- Updated dependencies [ad85bd0]
-  - llamaindex@0.8.8
-  - @llamaindex/autotool@5.0.8
-
-## 0.1.94
-
-### Patch Changes
-
- llamaindex@0.8.7
- @llamaindex/autotool@5.0.7
-
-## 0.1.93
-
-### Patch Changes
-
- Updated dependencies [95a5cc6]
-  - llamaindex@0.8.6
-  - @llamaindex/autotool@5.0.6
-
-## 0.1.92
-
-### Patch Changes
-
- Updated dependencies [14cc9eb]
- Updated dependencies [a6db5dd]
- Updated dependencies [396b1e1]
-  - llamaindex@0.8.5
-  - @llamaindex/autotool@5.0.5
-
 ## 0.1.91

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/autotool-02-next-example",
  "private": true,
-  "version": "0.1.114",
+  "version": "0.1.91",
  "scripts": {
    "dev": "next dev",
    "build": "next build",
@@ -10,17 +10,17 @@
  "dependencies": {
    "@llamaindex/autotool": "workspace:*",
    "@radix-ui/react-slot": "^1.1.0",
-    "ai": "^4.0.0",
+    "ai": "^3.3.21",
    "class-variance-authority": "^0.7.0",
    "dotenv": "^16.3.1",
    "llamaindex": "workspace:*",
-    "lucide-react": "^0.460.0",
-    "next": "15.0.3",
+    "lucide-react": "^0.436.0",
+    "next": "15.0.2",
    "react": "^18.3.1",
    "react-dom": "^18.3.1",
    "react-markdown": "^9.0.1",
    "react-syntax-highlighter": "^15.5.0",
-    "sonner": "^1.7.0",
+    "sonner": "^1.5.0",
    "tailwind-merge": "^2.5.2"
  },
  "devDependencies": {
@@ -30,8 +30,8 @@
    "@types/react-syntax-highlighter": "^15.5.11",
    "autoprefixer": "^10.4.20",
    "cross-env": "^7.0.3",
-    "postcss": "^8.4.49",
-    "tailwindcss": "^3.4.15",
+    "postcss": "^8.4.41",
+    "tailwindcss": "^3.4.10",
    "typescript": "^5.6.3"
  }
 }
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/autotool",
  "type": "module",
-  "version": "5.0.27",
+  "version": "5.0.4",
  "description": "auto transpile your JS function to LLM Agent compatible",
  "files": [
    "dist",
@@ -45,10 +45,10 @@
    "dev": "bunchee --watch"
  },
  "dependencies": {
-    "@swc/core": "^1.9.2",
-    "jotai": "2.10.2",
+    "@swc/core": "^1.7.22",
+    "jotai": "2.8.4",
    "typedoc": "^0.26.11",
-    "unplugin": "^1.16.0"
+    "unplugin": "^1.12.2"
  },
  "peerDependencies": {
    "llamaindex": "workspace:*",
@@ -72,11 +72,11 @@
    "@types/node": "^22.9.0",
    "bunchee": "5.6.1",
    "llamaindex": "workspace:*",
-    "next": "15.0.3",
-    "rollup": "^4.27.3",
+    "next": "15.0.2",
+    "rollup": "^4.24.4",
    "tsx": "^4.19.0",
    "typescript": "^5.6.3",
-    "vitest": "^2.1.5",
+    "vitest": "^2.1.4",
    "webpack": "^5.94.0"
  }
 }
@@ -22,7 +22,7 @@ export type InfoString = {
  parameterMapping: Record<string, number>;
 };

-export const store: ReturnType<typeof createStore> = createStore();
+export const store = createStore();
 export const toolMetadataAtom = atom<[ToolMetadata, Info][]>([]);
 // eslint-disable-next-line @typescript-eslint/no-explicit-any
 export const toolsAtom = atom<Record<string, (...args: any[]) => any>>({});
@@ -1,138 +1,5 @@
 # @llamaindex/cloud

-## 2.0.18
-
-### Patch Changes
-
- Updated dependencies [b504303]
- Updated dependencies [e0f6cc3]
-  - @llamaindex/env@0.1.25
-  - @llamaindex/core@0.4.18
-
-## 2.0.17
-
-### Patch Changes
-
- Updated dependencies [3d1808b]
-  - @llamaindex/core@0.4.17
-
-## 2.0.16
-
-### Patch Changes
-
- 8be4589: chore: bump version
- Updated dependencies [8be4589]
-  - @llamaindex/core@0.4.16
-  - @llamaindex/env@0.1.24
-
-## 2.0.15
-
-### Patch Changes
-
- Updated dependencies [d2b2722]
-  - @llamaindex/env@0.1.23
-  - @llamaindex/core@0.4.15
-
-## 2.0.14
-
-### Patch Changes
-
- Updated dependencies [969365c]
-  - @llamaindex/env@0.1.22
-  - @llamaindex/core@0.4.14
-
-## 2.0.13
-
-### Patch Changes
-
- 90d265c: chore: bump version
- Updated dependencies [90d265c]
-  - @llamaindex/core@0.4.13
-  - @llamaindex/env@0.1.21
-
-## 2.0.12
-
-### Patch Changes
-
- Updated dependencies [ef4f63d]
-  - @llamaindex/core@0.4.12
-
-## 2.0.11
-
-### Patch Changes
-
- Updated dependencies [6d22fa2]
-  - @llamaindex/core@0.4.11
-
-## 2.0.10
-
-### Patch Changes
-
- Updated dependencies [a7b0ac3]
- Updated dependencies [c69605f]
-  - @llamaindex/core@0.4.10
-
-## 2.0.9
-
-### Patch Changes
-
- Updated dependencies [7ae6eaa]
-  - @llamaindex/core@0.4.9
-
-## 2.0.8
-
-### Patch Changes
-
- Updated dependencies [f865c98]
-  - @llamaindex/core@0.4.8
-
-## 2.0.7
-
-### Patch Changes
-
- Updated dependencies [d89ebe0]
- Updated dependencies [fd8c882]
-  - @llamaindex/core@0.4.7
-
-## 2.0.6
-
-### Patch Changes
-
- Updated dependencies [4fc001c]
-  - @llamaindex/env@0.1.20
-  - @llamaindex/core@0.4.6
-
-## 2.0.5
-
-### Patch Changes
-
- Updated dependencies [ad85bd0]
-  - @llamaindex/core@0.4.5
-  - @llamaindex/env@0.1.19
-
-## 2.0.4
-
-### Patch Changes
-
- Updated dependencies [a8d3fa6]
-  - @llamaindex/env@0.1.18
-  - @llamaindex/core@0.4.4
-
-## 2.0.3
-
-### Patch Changes
-
- Updated dependencies [95a5cc6]
-  - @llamaindex/core@0.4.3
-
-## 2.0.2
-
-### Patch Changes
-
- Updated dependencies [14cc9eb]
-  - @llamaindex/env@0.1.17
-  - @llamaindex/core@0.4.2
-
 ## 2.0.1

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/cloud",
-  "version": "2.0.18",
+  "version": "2.0.1",
  "type": "module",
  "license": "MIT",
  "scripts": {
@@ -50,8 +50,8 @@
    "directory": "packages/cloud"
  },
  "devDependencies": {
-    "@hey-api/client-fetch": "^0.4.4",
-    "@hey-api/openapi-ts": "^0.56.0",
+    "@hey-api/client-fetch": "^0.4.2",
+    "@hey-api/openapi-ts": "^0.54.3",
    "@llamaindex/core": "workspace:*",
    "@llamaindex/env": "workspace:*",
    "bunchee": "5.6.1"
@@ -8,6 +8,7 @@
    "moduleResolution": "Bundler",
    "skipLibCheck": true,
    "strict": true,
+    "lib": ["DOM", "ESNext"],
    "types": []
  },
  "include": ["./src"],
@@ -1,146 +1,5 @@
 # @llamaindex/community

-## 0.0.76
-
-### Patch Changes
-
- c1850ee: feat: Amazon Nova support via Bedrock
- Updated dependencies [b504303]
- Updated dependencies [e0f6cc3]
-  - @llamaindex/env@0.1.25
-  - @llamaindex/core@0.4.18
-
-## 0.0.75
-
-### Patch Changes
-
- Updated dependencies [3d1808b]
-  - @llamaindex/core@0.4.17
-
-## 0.0.74
-
-### Patch Changes
-
- 8be4589: chore: bump version
- Updated dependencies [8be4589]
-  - @llamaindex/core@0.4.16
-  - @llamaindex/env@0.1.24
-
-## 0.0.73
-
-### Patch Changes
-
- Updated dependencies [d2b2722]
-  - @llamaindex/env@0.1.23
-  - @llamaindex/core@0.4.15
-
-## 0.0.72
-
-### Patch Changes
-
- Updated dependencies [969365c]
-  - @llamaindex/env@0.1.22
-  - @llamaindex/core@0.4.14
-
-## 0.0.71
-
-### Patch Changes
-
- 90d265c: chore: bump version
- Updated dependencies [90d265c]
-  - @llamaindex/core@0.4.13
-  - @llamaindex/env@0.1.21
-
-## 0.0.70
-
-### Patch Changes
-
- Updated dependencies [ef4f63d]
-  - @llamaindex/core@0.4.12
-
-## 0.0.69
-
-### Patch Changes
-
- Updated dependencies [6d22fa2]
-  - @llamaindex/core@0.4.11
-
-## 0.0.68
-
-### Patch Changes
-
- Updated dependencies [a7b0ac3]
- Updated dependencies [c69605f]
-  - @llamaindex/core@0.4.10
-
-## 0.0.67
-
-### Patch Changes
-
- Updated dependencies [7ae6eaa]
-  - @llamaindex/core@0.4.9
-
-## 0.0.66
-
-### Patch Changes
-
- Updated dependencies [f865c98]
-  - @llamaindex/core@0.4.8
-
-## 0.0.65
-
-### Patch Changes
-
- Updated dependencies [d89ebe0]
- Updated dependencies [fd8c882]
-  - @llamaindex/core@0.4.7
-
-## 0.0.64
-
-### Patch Changes
-
- Updated dependencies [4fc001c]
-  - @llamaindex/env@0.1.20
-  - @llamaindex/core@0.4.6
-
-## 0.0.63
-
-### Patch Changes
-
- Updated dependencies [ad85bd0]
-  - @llamaindex/core@0.4.5
-  - @llamaindex/env@0.1.19
-
-## 0.0.62
-
-### Patch Changes
-
- Updated dependencies [a8d3fa6]
-  - @llamaindex/env@0.1.18
-  - @llamaindex/core@0.4.4
-
-## 0.0.61
-
-### Patch Changes
-
- 487782c: Add missing inference endpoints for Haiku 3.5
- Updated dependencies [95a5cc6]
-  - @llamaindex/core@0.4.3
-
-## 0.0.60
-
-### Patch Changes
-
- Updated dependencies [14cc9eb]
-  - @llamaindex/env@0.1.17
-  - @llamaindex/core@0.4.2
-
-## 0.0.59
-
-### Patch Changes
-
- 47a7c3e: feat: added support for Haiku 3.5 via Bedrock
-
 ## 0.0.58

 ### Patch Changes
@@ -4,7 +4,6 @@

 ## Current Features:

- Bedrock support for Amazon Nova models Pro, Lite and Micro
 - Bedrock support for the Anthropic Claude Models [usage](https://ts.llamaindex.ai/modules/llms/available_llms/bedrock) including the latest Sonnet 3.5 v2 and Haiku 3.5
 - Bedrock support for the Meta LLama 2, 3, 3.1 and 3.2 Models [usage](https://ts.llamaindex.ai/modules/llms/available_llms/bedrock)
 - Meta LLama3.1 405b and Llama3.2 tool call support
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/community",
  "description": "Community package for LlamaIndexTS",
-  "version": "0.0.76",
+  "version": "0.0.58",
  "type": "module",
  "types": "dist/type/index.d.ts",
  "main": "dist/cjs/index.js",
@@ -46,8 +46,8 @@
    "bunchee": "5.6.1"
  },
  "dependencies": {
-    "@aws-sdk/client-bedrock-agent-runtime": "^3.706.0",
-    "@aws-sdk/client-bedrock-runtime": "^3.706.0",
+    "@aws-sdk/client-bedrock-agent-runtime": "^3.642.0",
+    "@aws-sdk/client-bedrock-runtime": "^3.642.0",
    "@llamaindex/core": "workspace:*",
    "@llamaindex/env": "workspace:*"
  }
@@ -1,133 +0,0 @@
-import type {
-  ContentBlockDelta,
-  ConverseOutput,
-  ConverseRequest,
-  ConverseResponse,
-  ConverseStreamOutput,
-  InvokeModelCommandInput,
-  InvokeModelWithResponseStreamCommandInput,
-  ResponseStream,
-} from "@aws-sdk/client-bedrock-runtime";
-import type {
-  BaseTool,
-  ChatMessage,
-  LLMMetadata,
-  ToolCall,
-  ToolCallLLMMessageOptions,
-} from "@llamaindex/core/llms";
-import { toUtf8 } from "../utils";
-
-import { Provider, type BedrockChatStreamResponse } from "../provider";
-import {
-  mapBaseToolsToAmazonTools,
-  mapChatMessagesToAmazonMessages,
-} from "./utils";
-
-export class AmazonProvider extends Provider<ConverseStreamOutput> {
-  getResultFromResponse(response: Record<string, any>): ConverseResponse {
-    return JSON.parse(toUtf8(response.body));
-  }
-
-  getToolsFromResponse<ToolContent>(response: ConverseOutput): ToolContent[] {
-    return (
-      response.message?.content
-        ?.filter((item) => item.toolUse)
-        .map(
-          (item) =>
-            ({
-              id: item.toolUse!.toolUseId,
-              name: item.toolUse!.name,
-              input: item.toolUse!.input
-                ? JSON.parse(item.toolUse!.input as string)
-                : "",
-            }) as ToolContent,
-        ) ?? []
-    );
-  }
-
-  getTextFromResponse(response: ConverseResponse): string {
-    const result = this.getResultFromResponse(response);
-    const content = result.output?.message?.content ?? [];
-    return content.map((item) => item.text).join(" ");
-  }
-
-  getTextFromStreamResponse(response: ResponseStream): string {
-    let event: ConverseStreamOutput | undefined =
-      this.getStreamingEventResponse(response);
-    if (!event || !event.contentBlockDelta) return "";
-    const delta: ContentBlockDelta | undefined = event.contentBlockDelta.delta;
-    return delta?.text || "";
-  }
-
-  async *reduceStream(
-    stream: AsyncIterable<ResponseStream>,
-  ): BedrockChatStreamResponse {
-    let toolId: string | undefined = undefined;
-    let toolName: string | undefined = undefined;
-    for await (const response of stream) {
-      const event = this.getStreamingEventResponse(response);
-      const delta = this.getTextFromStreamResponse(response);
-
-      let options: undefined | ToolCallLLMMessageOptions = undefined;
-      if (event?.contentBlockStart && event.contentBlockStart.start?.toolUse) {
-        toolId = event.contentBlockStart.start?.toolUse.toolUseId;
-        toolName = event.contentBlockStart.start?.toolUse.name;
-        continue;
-      }
-      if (
-        toolId &&
-        toolName &&
-        event?.contentBlockDelta?.delta?.toolUse?.input
-      ) {
-        options = {
-          toolCall: [
-            {
-              id: toolId,
-              name: toolName,
-              input: JSON.parse(event?.contentBlockDelta?.delta?.toolUse.input),
-            } as ToolCall,
-          ],
-        };
-        toolId = undefined;
-        toolName = undefined;
-      }
-
-      if (!delta && !options) continue;
-
-      yield {
-        delta: options ? "" : delta,
-        options,
-        raw: response,
-      };
-    }
-  }
-
-  getRequestBody<T extends ChatMessage>(
-    metadata: LLMMetadata,
-    messages: T[],
-    tools: BaseTool[] = [],
-    options: Omit<ConverseRequest, "modelId" | "messages" | "inferenceConfig">,
-  ): InvokeModelCommandInput | InvokeModelWithResponseStreamCommandInput {
-    const request: Omit<ConverseRequest, "modelId"> = {
-      ...options,
-      messages: mapChatMessagesToAmazonMessages(messages),
-      inferenceConfig: {
-        maxTokens: metadata.maxTokens,
-        temperature: metadata.temperature,
-        topP: metadata.topP,
-      },
-    };
-    if (tools.length) {
-      request.toolConfig = {
-        tools: mapBaseToolsToAmazonTools(tools),
-      };
-    }
-
-    return {
-      modelId: metadata.model,
-      contentType: "application/json",
-      accept: "application/json",
-      body: JSON.stringify(request),
-    };
-  }
-}
@@ -1,5 +0,0 @@
-import type { ConverseRequest, Message } from "@aws-sdk/client-bedrock-runtime";
-
-export type AmazonMessages = ConverseRequest["messages"];
-
-export type AmazonMessage = Message;
@@ -1,141 +0,0 @@
-import type {
-  ImageBlock,
-  ImageFormat,
-  Message,
-  Tool,
-} from "@aws-sdk/client-bedrock-runtime";
-import type {
-  BaseTool,
-  ChatMessage,
-  MessageContentDetail,
-  ToolCallLLMMessageOptions,
-} from "@llamaindex/core/llms";
-import {
-  extractDataUrlComponents,
-  mapMessageContentToMessageContentDetails,
-} from "../utils";
-
-import type { JSONObject } from "@llamaindex/core/global";
-import type { AmazonMessage, AmazonMessages } from "./types";
-
-const ACCEPTED_IMAGE_MIME_TYPES = [
-  "image/jpeg",
-  "image/png",
-  "image/webp",
-  "image/gif",
-] as const;
-
-const ACCEPTED_IMAGE_MIME_TYPE_FORMAT_MAP: Record<
-  (typeof ACCEPTED_IMAGE_MIME_TYPES)[number],
-  ImageFormat
-> = {
-  "image/jpeg": "jpeg",
-  "image/png": "png",
-  "image/webp": "webp",
-  "image/gif": "gif",
-};
-
-export const mapImageContent = (imageUrl: string): ImageBlock => {
-  if (!imageUrl.startsWith("data:"))
-    throw new Error(
-      "For Amazon please only use base64 data url, e.g.: data:image/jpeg;base64,SGVsbG8sIFdvcmxkIQ==",
-    );
-  const { mimeType, base64: data } = extractDataUrlComponents(imageUrl);
-  if (
-    !ACCEPTED_IMAGE_MIME_TYPES.includes(
-      mimeType as keyof typeof ACCEPTED_IMAGE_MIME_TYPE_FORMAT_MAP,
-    )
-  )
-    throw new Error(
-      `Amazon only accepts the following mimeTypes: ${ACCEPTED_IMAGE_MIME_TYPES.join("\n")}`,
-    );
-
-  return {
-    format:
-      ACCEPTED_IMAGE_MIME_TYPE_FORMAT_MAP[
-        mimeType as keyof typeof ACCEPTED_IMAGE_MIME_TYPE_FORMAT_MAP
-      ],
-
-    // @ts-ignore: there's a mistake in the "@aws-sdk/client-bedrock-runtime" compared to the actual api
-    source: { bytes: data },
-  };
-};
-
-export const mapMessageContentDetailToAmazonContent = <
-  T extends MessageContentDetail,
->(
-  detail: T,
-): Message["content"] => {
-  let content: Message["content"] = [];
-
-  if (detail.type === "text") {
-    content = [{ text: detail.text }];
-  } else if (detail.type === "image_url") {
-    content = [{ image: mapImageContent(detail.image_url.url) }];
-  } else {
-    throw new Error("Unsupported content detail type");
-  }
-  return content;
-};
-
-export const mapChatMessagesToAmazonMessages = <
-  T extends ChatMessage<ToolCallLLMMessageOptions>,
->(
-  messages: T[],
-): AmazonMessages => {
-  return messages.flatMap((msg: T): AmazonMessage[] => {
-    return mapMessageContentToMessageContentDetails(msg.content).map(
-      (detail: MessageContentDetail): AmazonMessage => {
-        if (msg.options && "toolCall" in msg.options) {
-          return {
-            role: "assistant",
-            content: msg.options.toolCall.map((call) => ({
-              toolUse: {
-                toolUseId: call.id,
-                name: call.name,
-                input: call.input as JSONObject,
-              },
-            })),
-          };
-        }
-        if (msg.options && "toolResult" in msg.options) {
-          return {
-            role: "user",
-            content: [
-              {
-                toolResult: {
-                  toolUseId: msg.options.toolResult.id,
-                  content: [
-                    {
-                      text: msg.options.toolResult.result,
-                    },
-                  ],
-                },
-              },
-            ],
-          };
-        }
-
-        return {
-          role: msg.role === "assistant" ? "assistant" : "user",
-          content: mapMessageContentDetailToAmazonContent(detail),
-        };
-      },
-    );
-  });
-};
-
-export const mapBaseToolsToAmazonTools = (tools?: BaseTool[]): Tool[] => {
-  if (!tools) return [];
-  return tools.map((tool: BaseTool) => {
-    const {
-      metadata: { parameters, ...options },
-    } = tool;
-    return {
-      toolSpec: {
-        ...options,
-        inputSchema: parameters,
-      },
-    } as Tool;
-  });
-};
@@ -11,10 +11,13 @@ import type {
  ToolCall,
  ToolCallLLMMessageOptions,
 } from "@llamaindex/core/llms";
-import { type BedrockChatStreamResponse, Provider } from "../provider";
+import {
+  type BedrockAdditionalChatOptions,
+  type BedrockChatStreamResponse,
+  Provider,
+} from "../provider";
 import { toUtf8 } from "../utils";
 import type {
-  AnthropicAdditionalChatOptions,
  AnthropicNoneStreamingResponse,
  AnthropicStreamEvent,
  AnthropicTextContent,
@@ -131,7 +134,7 @@ export class AnthropicProvider extends Provider<AnthropicStreamEvent> {
    metadata: LLMMetadata,
    messages: T[],
    tools?: BaseTool[],
-    options?: AnthropicAdditionalChatOptions,
+    options?: BedrockAdditionalChatOptions,
  ): InvokeModelCommandInput | InvokeModelWithResponseStreamCommandInput {
    const extra: Record<string, unknown> = {};
    if (options?.toolChoice) {
@@ -1,13 +1,6 @@
 import type { ToolMetadata } from "@llamaindex/core/llms";
 import type { InvocationMetrics } from "../types";

-export type ToolChoice =
-  | { type: "any" }
-  | { type: "auto" }
-  | { type: "tool"; name: string };
-
-export type AnthropicAdditionalChatOptions = { toolChoice: ToolChoice };
-
 type Usage = {
  input_tokens: number;
  output_tokens: number;
@@ -25,7 +25,6 @@ import {
 import { mapMessageContentToMessageContentDetails } from "./utils";

 import { wrapLLMEvent } from "@llamaindex/core/decorator";
-import { AmazonProvider } from "./amazon/provider";
 import { AnthropicProvider } from "./anthropic/provider";
 import { MetaProvider } from "./meta/provider";

@@ -33,7 +32,6 @@ import { MetaProvider } from "./meta/provider";
 export const PROVIDERS: { [key: string]: Provider } = {
  anthropic: new AnthropicProvider(),
  meta: new MetaProvider(),
-  amazon: new AmazonProvider(),
 };

 export type BedrockChatParamsStreaming = LLMChatParamsStreaming<
@@ -83,17 +81,12 @@ export const BEDROCK_MODELS = {
  MISTRAL_7B_INSTRUCT: "mistral.mistral-7b-instruct-v0:2",
  MISTRAL_MIXTRAL_7B_INSTRUCT: "mistral.mixtral-8x7b-instruct-v0:1",
  MISTRAL_MIXTRAL_LARGE_2402: "mistral.mistral-large-2402-v1:0",
-  AMAZON_NOVA_PRO_1: "amazon.nova-pro-v1:0",
-  AMAZON_NOVA_LITE_1: "amazon.nova-lite-v1:0",
-  AMAZON_NOVA_MICRO_1: "amazon.nova-micro-v1:0",
 };
-
 export type BEDROCK_MODELS =
  (typeof BEDROCK_MODELS)[keyof typeof BEDROCK_MODELS];

 export const INFERENCE_BEDROCK_MODELS = {
  US_ANTHROPIC_CLAUDE_3_HAIKU: "us.anthropic.claude-3-haiku-20240307-v1:0",
-  US_ANTHROPIC_CLAUDE_3_5_HAIKU: "us.anthropic.claude-3-5-haiku-20241022-v1:0",
  US_ANTHROPIC_CLAUDE_3_OPUS: "us.anthropic.claude-3-opus-20240229-v1:0",
  US_ANTHROPIC_CLAUDE_3_SONNET: "us.anthropic.claude-3-sonnet-20240229-v1:0",
  US_ANTHROPIC_CLAUDE_3_5_SONNET:
@@ -104,12 +97,8 @@ export const INFERENCE_BEDROCK_MODELS = {
  US_META_LLAMA_3_2_3B_INSTRUCT: "us.meta.llama3-2-3b-instruct-v1:0",
  US_META_LLAMA_3_2_11B_INSTRUCT: "us.meta.llama3-2-11b-instruct-v1:0",
  US_META_LLAMA_3_2_90B_INSTRUCT: "us.meta.llama3-2-90b-instruct-v1:0",
-  US_AMAZON_NOVA_PRO_1: "us.amazon.nova-pro-v1:0",
-  US_AMAZON_NOVA_LITE_1: "us.amazon.nova-lite-v1:0",
-  US_AMAZON_NOVA_MICRO_1: "us.amazon.nova-micro-v1:0",

  EU_ANTHROPIC_CLAUDE_3_HAIKU: "eu.anthropic.claude-3-haiku-20240307-v1:0",
-  EU_ANTHROPIC_CLAUDE_3_5_HAIKU: "eu.anthropic.claude-3-5-haiku-20240307-v1:0",
  EU_ANTHROPIC_CLAUDE_3_SONNET: "eu.anthropic.claude-3-sonnet-20240229-v1:0",
  EU_ANTHROPIC_CLAUDE_3_5_SONNET:
    "eu.anthropic.claude-3-5-sonnet-20240620-v1:0",
@@ -134,8 +123,6 @@ export const INFERENCE_TO_BEDROCK_MAP: Record<
    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET,
  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_5_SONNET_V2]:
    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET_V2,
-  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_5_HAIKU]:
-    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_HAIKU,
  [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_2_1B_INSTRUCT]:
    BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT,
  [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_2_3B_INSTRUCT]:
@@ -198,9 +185,6 @@ const CHAT_ONLY_MODELS = {
  [BEDROCK_MODELS.MISTRAL_7B_INSTRUCT]: 32000,
  [BEDROCK_MODELS.MISTRAL_MIXTRAL_7B_INSTRUCT]: 32000,
  [BEDROCK_MODELS.MISTRAL_MIXTRAL_LARGE_2402]: 32000,
-  [BEDROCK_MODELS.AMAZON_NOVA_PRO_1]: 300000,
-  [BEDROCK_MODELS.AMAZON_NOVA_LITE_1]: 300000,
-  [BEDROCK_MODELS.AMAZON_NOVA_MICRO_1]: 130000,
 };

 const BEDROCK_FOUNDATION_LLMS = { ...COMPLETION_MODELS, ...CHAT_ONLY_MODELS };
@@ -237,9 +221,6 @@ export const STREAMING_MODELS = new Set([
  BEDROCK_MODELS.MISTRAL_7B_INSTRUCT,
  BEDROCK_MODELS.MISTRAL_MIXTRAL_7B_INSTRUCT,
  BEDROCK_MODELS.MISTRAL_MIXTRAL_LARGE_2402,
-  BEDROCK_MODELS.AMAZON_NOVA_PRO_1,
-  BEDROCK_MODELS.AMAZON_NOVA_LITE_1,
-  BEDROCK_MODELS.AMAZON_NOVA_MICRO_1,
 ]);

 export const TOOL_CALL_MODELS: BEDROCK_MODELS[] = [
@@ -254,9 +235,6 @@ export const TOOL_CALL_MODELS: BEDROCK_MODELS[] = [
  BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT,
  BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT,
  BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT,
-  BEDROCK_MODELS.AMAZON_NOVA_PRO_1,
-  BEDROCK_MODELS.AMAZON_NOVA_LITE_1,
-  BEDROCK_MODELS.AMAZON_NOVA_MICRO_1,
 ];

 const getProvider = (model: string): Provider => {
@@ -338,6 +316,10 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
    this.temperature = temperature ?? DEFAULT_BEDROCK_PARAMS.temperature;
    this.topP = topP ?? DEFAULT_BEDROCK_PARAMS.topP;
    this.client = new BedrockRuntimeClient(params);
+
+    if (!this.supportToolCall) {
+      console.warn(`The model "${this.model}" doesn't support ToolCall`);
+    }
  }

  get supportToolCall(): boolean {
@@ -359,9 +341,6 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
  protected async nonStreamChat(
    params: BedrockChatParamsNonStreaming,
  ): Promise<BedrockChatNonStreamResponse> {
-    if (!this.supportToolCall && params.tools?.length) {
-      console.warn(`The model "${this.model}" doesn't support ToolCall`);
-    }
    const input = this.provider.getRequestBody(
      this.metadata,
      params.messages,
@@ -395,10 +374,6 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
    if (!STREAMING_MODELS.has(this.model))
      throw new Error(`The model: ${this.model} does not support streaming`);

-    if (!this.supportToolCall && params.tools?.length) {
-      console.warn(`The model "${this.model}" doesn't support ToolCall`);
-    }
-
    const input = this.provider.getRequestBody(
      this.metadata,
      params.messages,
@@ -409,6 +384,7 @@ export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
    command.input.modelId = this.actualModel;

    const response = await this.client.send(command);
+
    if (response.body) yield* this.provider.reduceStream(response.body);
  }

@@ -11,9 +11,10 @@ import {
  type ToolCallLLMMessageOptions,
 } from "@llamaindex/core/llms";
 import { streamConverter } from "@llamaindex/core/utils";
+import type { ToolChoice } from "./types";
 import { toUtf8 } from "./utils";

-export type BedrockAdditionalChatOptions = Record<string, unknown>;
+export type BedrockAdditionalChatOptions = { toolChoice: ToolChoice };

 export type BedrockChatStreamResponse = AsyncIterable<
  ChatResponseChunk<ToolCallLLMMessageOptions>
@@ -4,3 +4,8 @@ export type InvocationMetrics = {
  invocationLatency: number;
  firstByteLatency: number;
 };
+
+export type ToolChoice =
+  | { type: "any" }
+  | { type: "auto" }
+  | { type: "tool"; name: string };
@@ -1,123 +1,5 @@
 # @llamaindex/core

-## 0.4.18
-
-### Patch Changes
-
- e0f6cc3: The compact and refine response synthesizer (retrieved by using `getResponseSynthesizer('compact')`) has been fixed to return the original source nodes that were provided to it in its response. Previous to this it was returning the compacted text chunk documents.
- Updated dependencies [b504303]
-  - @llamaindex/env@0.1.25
-
-## 0.4.17
-
-### Patch Changes
-
- 3d1808b: chore: bump version
-
-## 0.4.16
-
-### Patch Changes
-
- 8be4589: chore: bump version
- Updated dependencies [8be4589]
-  - @llamaindex/env@0.1.24
-
-## 0.4.15
-
-### Patch Changes
-
- Updated dependencies [d2b2722]
-  - @llamaindex/env@0.1.23
-
-## 0.4.14
-
-### Patch Changes
-
- Updated dependencies [969365c]
-  - @llamaindex/env@0.1.22
-
-## 0.4.13
-
-### Patch Changes
-
- 90d265c: chore: bump version
- Updated dependencies [90d265c]
-  - @llamaindex/env@0.1.21
-
-## 0.4.12
-
-### Patch Changes
-
- ef4f63d: refactor: move mockLLM to core
-
-## 0.4.11
-
-### Patch Changes
-
- 6d22fa2: Get PromptTemplate template variables at run-time
-
-## 0.4.10
-
-### Patch Changes
-
- a7b0ac3: fix: update tool call llm type
- c69605f: feat: add async support to BaseChatStore and BaseChatStoreMemory
-
-## 0.4.9
-
-### Patch Changes
-
- 7ae6eaa: feat: allow pass `additionalChatOptions` to agent
-
-## 0.4.8
-
-### Patch Changes
-
- f865c98: feat: async get message on chat store
-
-## 0.4.7
-
-### Patch Changes
-
- d89ebe0: feat: better support for zod schema
- fd8c882: chore: add warning on legacy workflow API
-
-## 0.4.6
-
-### Patch Changes
-
- Updated dependencies [4fc001c]
-  - @llamaindex/env@0.1.20
-
-## 0.4.5
-
-### Patch Changes
-
- ad85bd0: - fix agent chat message not saved into the task context when streaming
-  - fix async local storage might use `node:async_hook` in edge-light/workerd condition
- Updated dependencies [ad85bd0]
-  - @llamaindex/env@0.1.19
-
-## 0.4.4
-
-### Patch Changes
-
- Updated dependencies [a8d3fa6]
-  - @llamaindex/env@0.1.18
-
-## 0.4.3
-
-### Patch Changes
-
- 95a5cc6: refactor: move storage into core
-
-## 0.4.2
-
-### Patch Changes
-
- Updated dependencies [14cc9eb]
-  - @llamaindex/env@0.1.17
-
 ## 0.4.1

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/core",
  "type": "module",
-  "version": "0.4.18",
+  "version": "0.4.1",
  "description": "LlamaIndex Core Module",
  "exports": {
    "./agent": {
@@ -214,48 +214,6 @@
        "default": "./storage/chat-store/dist/index.js"
      }
    },
-    "./storage/doc-store": {
-      "require": {
-        "types": "./storage/doc-store/dist/index.d.cts",
-        "default": "./storage/doc-store/dist/index.cjs"
-      },
-      "import": {
-        "types": "./storage/doc-store/dist/index.d.ts",
-        "default": "./storage/doc-store/dist/index.js"
-      },
-      "default": {
-        "types": "./storage/doc-store/dist/index.d.ts",
-        "default": "./storage/doc-store/dist/index.js"
-      }
-    },
-    "./storage/index-store": {
-      "require": {
-        "types": "./storage/index-store/dist/index.d.cts",
-        "default": "./storage/index-store/dist/index.cjs"
-      },
-      "import": {
-        "types": "./storage/index-store/dist/index.d.ts",
-        "default": "./storage/index-store/dist/index.js"
-      },
-      "default": {
-        "types": "./storage/index-store/dist/index.d.ts",
-        "default": "./storage/index-store/dist/index.js"
-      }
-    },
-    "./storage/kv-store": {
-      "require": {
-        "types": "./storage/kv-store/dist/index.d.cts",
-        "default": "./storage/kv-store/dist/index.cjs"
-      },
-      "import": {
-        "types": "./storage/kv-store/dist/index.d.ts",
-        "default": "./storage/kv-store/dist/index.js"
-      },
-      "default": {
-        "types": "./storage/kv-store/dist/index.d.ts",
-        "default": "./storage/kv-store/dist/index.js"
-      }
-    },
    "./response-synthesizers": {
      "require": {
        "types": "./response-synthesizers/dist/index.d.cts",
@@ -389,10 +347,10 @@
    "url": "https://github.com/run-llama/LlamaIndexTS.git"
  },
  "devDependencies": {
-    "@edge-runtime/vm": "^4.0.4",
+    "@edge-runtime/vm": "^4.0.3",
    "ajv": "^8.17.1",
    "bunchee": "5.6.1",
-    "happy-dom": "^15.11.6",
+    "happy-dom": "^15.10.0",
    "natural": "^8.0.1"
  },
  "dependencies": {
@@ -3,7 +3,7 @@ import {
  BaseChatEngine,
  type NonStreamingChatEngineParams,
  type StreamingChatEngineParams,
-} from "../chat-engine";
+} from "../chat-engine/base";
 import { wrapEventCaller } from "../decorator";
 import { Settings } from "../global";
 import type {
@@ -106,17 +106,11 @@ export type AgentRunnerParams<
  >
    ? AdditionalMessageOptions
    : never,
-  AdditionalChatOptions extends object = object,
 > = {
  llm: AI;
  chatHistory: ChatMessage<AdditionalMessageOptions>[];
  systemPrompt: MessageContent | null;
-  runner: AgentWorker<
-    AI,
-    Store,
-    AdditionalMessageOptions,
-    AdditionalChatOptions
-  >;
+  runner: AgentWorker<AI, Store, AdditionalMessageOptions>;
  tools:
    | BaseToolWithCall[]
    | ((query: MessageContent) => Promise<BaseToolWithCall[]>);
@@ -131,7 +125,6 @@ export type AgentParamsBase<
  >
    ? AdditionalMessageOptions
    : never,
-  AdditionalChatOptions extends object = object,
 > =
  | {
      llm?: AI;
@@ -139,7 +132,6 @@ export type AgentParamsBase<
      systemPrompt?: MessageContent;
      verbose?: boolean;
      tools: BaseToolWithCall[];
-      additionalChatOptions?: AdditionalChatOptions;
    }
  | {
      llm?: AI;
@@ -147,7 +139,6 @@ export type AgentParamsBase<
      systemPrompt?: MessageContent;
      verbose?: boolean;
      toolRetriever: ObjectRetriever<BaseToolWithCall>;
-      additionalChatOptions?: AdditionalChatOptions;
    };

 /**
@@ -162,75 +153,37 @@ export abstract class AgentWorker<
  >
    ? AdditionalMessageOptions
    : never,
-  AdditionalChatOptions extends object = object,
 > {
-  #taskSet = new Set<
-    TaskStep<AI, Store, AdditionalMessageOptions, AdditionalChatOptions>
-  >();
-  abstract taskHandler: TaskHandler<
-    AI,
-    Store,
-    AdditionalMessageOptions,
-    AdditionalChatOptions
-  >;
+  #taskSet = new Set<TaskStep<AI, Store, AdditionalMessageOptions>>();
+  abstract taskHandler: TaskHandler<AI, Store, AdditionalMessageOptions>;

  public createTask(
    query: MessageContent,
-    context: AgentTaskContext<
-      AI,
-      Store,
-      AdditionalMessageOptions,
-      AdditionalChatOptions
-    >,
-  ): ReadableStream<
-    TaskStepOutput<AI, Store, AdditionalMessageOptions, AdditionalChatOptions>
-  > {
+    context: AgentTaskContext<AI, Store, AdditionalMessageOptions>,
+  ): ReadableStream<TaskStepOutput<AI, Store, AdditionalMessageOptions>> {
    context.store.messages.push({
      role: "user",
      content: query,
    });
    const taskOutputStream = createTaskOutputStream(this.taskHandler, context);
    return new ReadableStream<
-      TaskStepOutput<AI, Store, AdditionalMessageOptions, AdditionalChatOptions>
+      TaskStepOutput<AI, Store, AdditionalMessageOptions>
    >({
      start: async (controller) => {
        for await (const stepOutput of taskOutputStream) {
          this.#taskSet.add(stepOutput.taskStep);
+          controller.enqueue(stepOutput);
          if (stepOutput.isLast) {
            let currentStep: TaskStep<
              AI,
              Store,
-              AdditionalMessageOptions,
-              AdditionalChatOptions
+              AdditionalMessageOptions
            > | null = stepOutput.taskStep;
            while (currentStep) {
              this.#taskSet.delete(currentStep);
              currentStep = currentStep.prevStep;
            }
-            const { output, taskStep } = stepOutput;
-            if (output instanceof ReadableStream) {
-              const [pipStream, finalStream] = output.tee();
-              stepOutput.output = finalStream;
-              const reader = pipStream.getReader();
-              const { value } = await reader.read();
-              reader.releaseLock();
-              let content: string = value!.delta;
-              for await (const chunk of pipStream) {
-                content += chunk.delta;
-              }
-              taskStep.context.store.messages = [
-                ...taskStep.context.store.messages,
-                {
-                  role: "assistant",
-                  content,
-                  options: value!.options,
-                },
-              ];
-            }
-            controller.enqueue(stepOutput);
            controller.close();
-          } else {
-            controller.enqueue(stepOutput);
          }
        }
      },
@@ -252,7 +205,6 @@ export abstract class AgentRunner<
  >
    ? AdditionalMessageOptions
    : never,
-  AdditionalChatOptions extends object = object,
 > extends BaseChatEngine {
  readonly #llm: AI;
  readonly #tools:
@@ -260,12 +212,7 @@ export abstract class AgentRunner<
    | ((query: MessageContent) => Promise<BaseToolWithCall[]>);
  readonly #systemPrompt: MessageContent | null = null;
  #chatHistory: ChatMessage<AdditionalMessageOptions>[];
-  readonly #runner: AgentWorker<
-    AI,
-    Store,
-    AdditionalMessageOptions,
-    AdditionalChatOptions
-  >;
+  readonly #runner: AgentWorker<AI, Store, AdditionalMessageOptions>;
  readonly #verbose: boolean;

  // create extra store
@@ -276,7 +223,7 @@ export abstract class AgentRunner<
  }

  static defaultTaskHandler: TaskHandler<LLM> = async (step, enqueueOutput) => {
-    const { llm, getTools, stream, additionalChatOptions } = step.context;
+    const { llm, getTools, stream } = step.context;
    const lastMessage = step.context.store.messages.at(-1)!.content;
    const tools = await getTools(lastMessage);
    if (!stream) {
@@ -284,9 +231,8 @@ export abstract class AgentRunner<
        stream,
        tools,
        messages: [...step.context.store.messages],
-        additionalChatOptions,
      });
-      await stepTools({
+      await stepTools<LLM>({
        response,
        tools,
        step,
@@ -297,7 +243,6 @@ export abstract class AgentRunner<
        stream,
        tools,
        messages: [...step.context.store.messages],
-        additionalChatOptions,
      });
      await stepToolsStreaming<LLM>({
        response,
@@ -309,12 +254,7 @@ export abstract class AgentRunner<
  };

  protected constructor(
-    params: AgentRunnerParams<
-      AI,
-      Store,
-      AdditionalMessageOptions,
-      AdditionalChatOptions
-    >,
+    params: AgentRunnerParams<AI, Store, AdditionalMessageOptions>,
  ) {
    super();
    const { llm, chatHistory, systemPrompt, runner, tools, verbose } = params;
@@ -368,10 +308,7 @@ export abstract class AgentRunner<
    stream: boolean = false,
    verbose: boolean | undefined = undefined,
    chatHistory?: ChatMessage<AdditionalMessageOptions>[],
-    additionalChatOptions?: AdditionalChatOptions,
-  ): ReadableStream<
-    TaskStepOutput<AI, Store, AdditionalMessageOptions, AdditionalChatOptions>
-  > {
+  ) {
    const initialMessages = [...(chatHistory ?? this.#chatHistory)];
    if (this.#systemPrompt !== null) {
      const systemPrompt = this.#systemPrompt;
@@ -389,7 +326,6 @@ export abstract class AgentRunner<
      stream,
      toolCallCount: 0,
      llm: this.#llm,
-      additionalChatOptions: additionalChatOptions ?? {},
      getTools: (message) => this.getTools(message),
      store: {
        ...this.createStore(),
@@ -407,29 +343,13 @@ export abstract class AgentRunner<
    });
  }

+  async chat(params: NonStreamingChatEngineParams): Promise<EngineResponse>;
  async chat(
-    params: NonStreamingChatEngineParams<
-      AdditionalMessageOptions,
-      AdditionalChatOptions
-    >,
-  ): Promise<EngineResponse>;
-  async chat(
-    params: StreamingChatEngineParams<
-      AdditionalMessageOptions,
-      AdditionalChatOptions
-    >,
+    params: StreamingChatEngineParams,
  ): Promise<ReadableStream<EngineResponse>>;
  @wrapEventCaller
  async chat(
-    params:
-      | NonStreamingChatEngineParams<
-          AdditionalMessageOptions,
-          AdditionalChatOptions
-        >
-      | StreamingChatEngineParams<
-          AdditionalMessageOptions,
-          AdditionalChatOptions
-        >,
+    params: NonStreamingChatEngineParams | StreamingChatEngineParams,
  ): Promise<EngineResponse | ReadableStream<EngineResponse>> {
    let chatHistory: ChatMessage<AdditionalMessageOptions>[] = [];

@@ -446,7 +366,6 @@ export abstract class AgentRunner<
      !!params.stream,
      false,
      chatHistory,
-      params.chatOptions,
    );
    for await (const stepOutput of task) {
      // update chat history for each round
@@ -454,7 +373,7 @@ export abstract class AgentRunner<
      if (stepOutput.isLast) {
        const { output } = stepOutput;
        if (output instanceof ReadableStream) {
-          return output.pipeThrough(
+          return output.pipeThrough<EngineResponse>(
            new TransformStream({
              transform(chunk, controller) {
                controller.enqueue(EngineResponse.fromChatResponseChunk(chunk));
@@ -4,66 +4,24 @@ import { ObjectRetriever } from "../objects";
 import { AgentRunner, AgentWorker, type AgentParamsBase } from "./base.js";
 import { validateAgentParams } from "./utils.js";

-type LLMParamsBase<
-  AI extends LLM,
-  AdditionalMessageOptions extends object = AI extends LLM<
-    object,
-    infer AdditionalMessageOptions
-  >
-    ? AdditionalMessageOptions
-    : never,
-  AdditionalChatOptions extends object = object,
-> = AgentParamsBase<AI, AdditionalMessageOptions, AdditionalChatOptions>;
+type LLMParamsBase = AgentParamsBase<LLM>;

-type LLMParamsWithTools<
-  AI extends LLM,
-  AdditionalMessageOptions extends object = AI extends LLM<
-    object,
-    infer AdditionalMessageOptions
-  >
-    ? AdditionalMessageOptions
-    : never,
-  AdditionalChatOptions extends object = object,
-> = LLMParamsBase<AI, AdditionalMessageOptions, AdditionalChatOptions> & {
+type LLMParamsWithTools = LLMParamsBase & {
  tools: BaseToolWithCall[];
 };

-type LLMParamsWithToolRetriever<
-  AI extends LLM,
-  AdditionalMessageOptions extends object = AI extends LLM<
-    object,
-    infer AdditionalMessageOptions
-  >
-    ? AdditionalMessageOptions
-    : never,
-  AdditionalChatOptions extends object = object,
-> = LLMParamsBase<AI, AdditionalMessageOptions, AdditionalChatOptions> & {
+type LLMParamsWithToolRetriever = LLMParamsBase & {
  toolRetriever: ObjectRetriever<BaseToolWithCall>;
 };

-export type LLMAgentParams<
-  AI extends LLM,
-  AdditionalMessageOptions extends object = AI extends LLM<
-    object,
-    infer AdditionalMessageOptions
-  >
-    ? AdditionalMessageOptions
-    : never,
-  AdditionalChatOptions extends object = object,
-> =
-  | LLMParamsWithTools<AI, AdditionalMessageOptions, AdditionalChatOptions>
-  | LLMParamsWithToolRetriever<
-      AI,
-      AdditionalMessageOptions,
-      AdditionalChatOptions
-    >;
+export type LLMAgentParams = LLMParamsWithTools | LLMParamsWithToolRetriever;

 export class LLMAgentWorker extends AgentWorker<LLM> {
  taskHandler = AgentRunner.defaultTaskHandler;
 }

 export class LLMAgent extends AgentRunner<LLM> {
-  constructor(params: LLMAgentParams<LLM>) {
+  constructor(params: LLMAgentParams) {
    validateAgentParams(params);
    const llm = params.llm ?? (Settings.llm ? (Settings.llm as LLM) : null);
    if (!llm)
@@ -19,7 +19,6 @@ export type AgentTaskContext<
  >
    ? AdditionalMessageOptions
    : never,
-  AdditionalChatOptions extends object = object,
 > = {
  readonly stream: boolean;
  readonly toolCallCount: number;
@@ -27,7 +26,6 @@ export type AgentTaskContext<
  readonly getTools: (
    input: MessageContent,
  ) => BaseToolWithCall[] | Promise<BaseToolWithCall[]>;
-  readonly additionalChatOptions: Partial<AdditionalChatOptions>;
  shouldContinue: (
    taskStep: Readonly<TaskStep<Model, Store, AdditionalMessageOptions>>,
  ) => boolean;
@@ -47,26 +45,13 @@ export type TaskStep<
  >
    ? AdditionalMessageOptions
    : never,
-  AdditionalChatOptions extends object = object,
 > = {
  id: UUID;
-  context: AgentTaskContext<
-    Model,
-    Store,
-    AdditionalMessageOptions,
-    AdditionalChatOptions
-  >;
+  context: AgentTaskContext<Model, Store, AdditionalMessageOptions>;

  // linked list
-  prevStep: TaskStep<
-    Model,
-    Store,
-    AdditionalMessageOptions,
-    AdditionalChatOptions
-  > | null;
-  nextSteps: Set<
-    TaskStep<Model, Store, AdditionalMessageOptions, AdditionalChatOptions>
-  >;
+  prevStep: TaskStep<Model, Store, AdditionalMessageOptions> | null;
+  nextSteps: Set<TaskStep<Model, Store, AdditionalMessageOptions>>;
 };

 export type TaskStepOutput<
@@ -78,14 +63,8 @@ export type TaskStepOutput<
  >
    ? AdditionalMessageOptions
    : never,
-  AdditionalChatOptions extends object = object,
 > = {
-  taskStep: TaskStep<
-    Model,
-    Store,
-    AdditionalMessageOptions,
-    AdditionalChatOptions
-  >;
+  taskStep: TaskStep<Model, Store, AdditionalMessageOptions>;
  // output shows the response to the user
  output:
    | ChatResponse<AdditionalMessageOptions>
@@ -102,16 +81,10 @@ export type TaskHandler<
  >
    ? AdditionalMessageOptions
    : never,
-  AdditionalChatOptions extends object = object,
 > = (
-  step: TaskStep<Model, Store, AdditionalMessageOptions, AdditionalChatOptions>,
+  step: TaskStep<Model, Store, AdditionalMessageOptions>,
  enqueueOutput: (
-    taskOutput: TaskStepOutput<
-      Model,
-      Store,
-      AdditionalMessageOptions,
-      AdditionalChatOptions
-    >,
+    taskOutput: TaskStepOutput<Model, Store, AdditionalMessageOptions>,
  ) => void,
 ) => Promise<void>;

@@ -79,7 +79,7 @@ export async function stepToolsStreaming<Model extends LLM>({
    for await (const chunk of pipStream) {
      if (chunk.options && "toolCall" in chunk.options) {
        const toolCall = chunk.options.toolCall;
-        toolCall.forEach((toolCall: ToolCall | PartialToolCall) => {
+        toolCall.forEach((toolCall) => {
          toolCalls.set(toolCall.id, toolCall);
        });
      }
@@ -16,18 +16,14 @@ export interface BaseChatEngineParams<

 export interface StreamingChatEngineParams<
  AdditionalMessageOptions extends object = object,
-  AdditionalChatOptions extends object = object,
 > extends BaseChatEngineParams<AdditionalMessageOptions> {
  stream: true;
-  chatOptions?: AdditionalChatOptions;
 }

 export interface NonStreamingChatEngineParams<
  AdditionalMessageOptions extends object = object,
-  AdditionalChatOptions extends object = object,
 > extends BaseChatEngineParams<AdditionalMessageOptions> {
  stream?: false;
-  chatOptions?: AdditionalChatOptions;
 }

 export abstract class BaseChatEngine {
@@ -1,6 +1,5 @@
 import { randomUUID } from "@llamaindex/env";
 import type { UUID } from "../global";
-import { BaseNode } from "../schema";
 import { IndexStructType } from "./struct-type";

 export abstract class IndexStruct {
@@ -66,48 +65,3 @@ export class KeywordTable extends IndexStruct {
    };
  }
 }
-
-export class IndexDict extends IndexStruct {
-  nodesDict: Record<string, BaseNode> = {};
-  type: IndexStructType = IndexStructType.SIMPLE_DICT;
-
-  addNode(node: BaseNode, textId?: string) {
-    const vectorId = textId ?? node.id_;
-    this.nodesDict[vectorId] = node;
-  }
-
-  toJson(): Record<string, unknown> {
-    const nodesDict: Record<string, unknown> = {};
-
-    for (const [key, node] of Object.entries(this.nodesDict)) {
-      nodesDict[key] = node.toJSON();
-    }
-
-    return {
-      ...super.toJson(),
-      nodesDict,
-      type: this.type,
-    };
-  }
-
-  delete(nodeId: string) {
-    delete this.nodesDict[nodeId];
-  }
-}
-
-export class IndexList extends IndexStruct {
-  nodes: string[] = [];
-  type: IndexStructType = IndexStructType.LIST;
-
-  addNode(node: BaseNode) {
-    this.nodes.push(node.id_);
-  }
-
-  toJson(): Record<string, unknown> {
-    return {
-      ...super.toJson(),
-      nodes: this.nodes,
-      type: this.type,
-    };
-  }
-}
@@ -1,8 +1,2 @@
-export {
-  IndexDict,
-  IndexList,
-  IndexStruct,
-  KeywordTable,
-} from "./data-structs";
-export { jsonToIndexStruct } from "./json-to-index-struct";
+export { IndexStruct, KeywordTable } from "./data-structs";
 export { IndexStructType } from "./struct-type";
@@ -1,26 +0,0 @@
-import type { BaseNode } from "../schema";
-import { jsonToNode } from "../schema";
-import { IndexDict, IndexList, IndexStruct } from "./data-structs";
-import { IndexStructType } from "./struct-type";
-
-export function jsonToIndexStruct(
-  // eslint-disable-next-line @typescript-eslint/no-explicit-any
-  json: any,
-): IndexStruct {
-  if (json.type === IndexStructType.LIST) {
-    const indexList = new IndexList(json.indexId, json.summary);
-    indexList.nodes = json.nodes;
-    return indexList;
-  } else if (json.type === IndexStructType.SIMPLE_DICT) {
-    const indexDict = new IndexDict(json.indexId, json.summary);
-    indexDict.nodesDict = Object.entries(json.nodesDict).reduce<
-      Record<string, BaseNode>
-    >((acc, [key, value]) => {
-      acc[key] = jsonToNode(value);
-      return acc;
-    }, {});
-    return indexDict;
-  } else {
-    throw new Error(`Unknown index struct type: ${json.type}`);
-  }
-}
@@ -1,4 +1,4 @@
-import type { Tokenizers } from "@llamaindex/env/tokenizers";
+import { type Tokenizers } from "@llamaindex/env";
 import type { MessageContentDetail } from "../llms";
 import { BaseNode, MetadataMode, TransformComponent } from "../schema";
 import { extractSingleText } from "../utils";
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Alex Yang	8a9ae69390	Merge branch 'main' into ms/add-chat-ui-example	2024-11-07 09:36:22 -08:00
Marcus Schiesser	46cd22b716	Merge branch 'main' into ms/add-chat-ui-example	2024-11-07 15:27:20 +08:00
Marcus Schiesser	f60574c3f3	feat: add chat-ui example to new docs	2024-11-07 15:12:05 +08:00
Marcus Schiesser	b6085183fa	feat: Add example using chat-ui components	2024-11-05 17:21:18 +07:00