ci: typo

.github/workflows/build-doc.yml

@@ -0,0 +1,40 @@
+name: Build Docs
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+env:
+  TURBO_TOKEN: ${{ secrets.TURBO_TOKEN }}
+  TURBO_TEAM: ${{ vars.TURBO_TEAM }}
+  TURBO_REMOTE_ONLY: true
+
+jobs:
+  doc:
+    strategy:
+      fail-fast: false
+      matrix:
+        node-version: [20.x, 21.x, 22.x, 23.x]
+        os: [ubuntu-latest, macos-latest, windows-latest]
+    name: Build Docs on Node.js ${{ matrix.node-version }} (${{ matrix.os }})
+    runs-on: ${{ matrix.os }}
+    steps:
+      - uses: actions/checkout@v4
+      - uses: pnpm/action-setup@v4
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: ${{ matrix.node-version }}
+          cache: "pnpm"
+      - name: Install dependencies
+        run: pnpm install
+      - name: Run Build
+        run: pnpx turbo run build --filter @llamaindex/doc

.github/workflows/test.yml

@@ -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

CONTRIBUTING.md

@@ -2,58 +2,78 @@
 
 ## 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/next` 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
 pnpm install
 ```
 
-### Build the packages
+### Running Typescript
 
-```shell
-# Build all packages
-turbo build --filter "./packages/*"
+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
 ```
 
-### Docs
+To write new test cases write them in [packages/llamaindex/tests](/packages/llamaindex/tests)
 
-See the [docs](./apps/next/README.md) for more information.
+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]
+```
+
+### Doc
+
+To contribute to the docs, go to the docs website folder and run the Next.js server:
+
+```bash
+# run this if you are first time
+pnpx turbo run build --filter @llamaindex/doc
+cd apps/next
+pnpm run dev
+```
 
 ## 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 +87,6 @@ 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.

README.md

@@ -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/

apps/docs/CHANGELOG.md

@@ -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

apps/docs/docs/modules/llms/available_llms/bedrock.md

@@ -25,7 +25,6 @@ ANTHROPIC_CLAUDE_3_SONNET = "anthropic.claude-3-sonnet-20240229-v1:0";
 ANTHROPIC_CLAUDE_3_HAIKU = "anthropic.claude-3-haiku-20240307-v1:0";
 ANTHROPIC_CLAUDE_3_OPUS = "anthropic.claude-3-opus-20240229-v1:0"; // available on us-west-2
 ANTHROPIC_CLAUDE_3_5_SONNET = "anthropic.claude-3-5-sonnet-20240620-v1:0";
-ANTHROPIC_CLAUDE_3_5_HAIKU = "anthropic.claude-3-5-haiku-20241022-v1:0";
 META_LLAMA2_13B_CHAT = "meta.llama2-13b-chat-v1";
 META_LLAMA2_70B_CHAT = "meta.llama2-70b-chat-v1";
 META_LLAMA3_8B_INSTRUCT = "meta.llama3-8b-instruct-v1:0";
@@ -37,9 +36,6 @@ 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 +52,6 @@ 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";

apps/docs/docusaurus.config.js

@@ -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: {

apps/docs/package.json

@@ -1,6 +1,6 @@
 {
   "name": "docs",
-  "version": "0.0.133",
+  "version": "0.0.108",
   "private": true,
   "scripts": {
     "docusaurus": "docusaurus",
@@ -15,29 +15,29 @@
     "typecheck": "tsc"
   },
   "dependencies": {
-    "@docusaurus/core": "3.6.1",
-    "@docusaurus/remark-plugin-npm2yarn": "3.6.1",
+    "@docusaurus/core": "3.5.2",
+    "@docusaurus/remark-plugin-npm2yarn": "3.5.2",
     "@llamaindex/examples": "workspace:*",
-    "@mdx-js/react": "^3.1.0",
-    "clsx": "^2.1.1",
+    "@mdx-js/react": "3.0.1",
+    "clsx": "2.1.1",
     "llamaindex": "workspace:*",
-    "postcss": "^8.4.49",
-    "prism-react-renderer": "^2.4.0",
-    "raw-loader": "^4.0.2",
-    "react": "^18.3.1",
+    "postcss": "8.4.41",
+    "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": "3.5.2",
+    "@docusaurus/preset-classic": "3.5.2",
+    "@docusaurus/theme-classic": "3.5.2",
+    "@docusaurus/types": "3.5.2",
     "@tsconfig/docusaurus": "2.0.3",
-    "@types/node": "^22.9.0",
+    "@types/node": "^22.8.4",
     "docusaurus-plugin-typedoc": "1.0.5",
-    "typedoc": "0.26.11",
-    "typedoc-plugin-markdown": "4.2.10",
-    "typescript": "^5.6.3"
+    "typedoc": "0.26.6",
+    "typedoc-plugin-markdown": "4.2.6",
+    "typescript": "^5.6.2"
   },
   "browserslist": {
     "production": [

apps/next/CHANGELOG.md

@@ -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

apps/next/README.md

@@ -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

apps/next/next.config.mjs

@@ -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;
   },
 };

apps/next/package.json

@@ -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 +12,6 @@
   },
   "dependencies": {
     "@icons-pack/react-simple-icons": "^10.1.0",
-    "@llamaindex/chat-ui": "0.0.9",
     "@llamaindex/cloud": "workspace:*",
     "@llamaindex/core": "workspace:*",
     "@llamaindex/node-parser": "workspace:*",
@@ -20,31 +19,31 @@
     "@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",
@@ -54,33 +53,33 @@
     "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/node": "22.8.6",
     "@types/react": "^18.3.12",
     "@types/react-dom": "^18.3.1",
     "autoprefixer": "^10.4.20",
     "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"
   }

apps/next/scripts/update-llamacloud.mts

@@ -1,4 +1,4 @@
-import { upsertBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPut } from "@llamaindex/cloud/api";
+import { PipelinesService } from "@llamaindex/cloud/api";
 import fg from "fast-glob";
 import {
   fileGenerator,
@@ -30,8 +30,9 @@ async function processContent(content: string): Promise<string> {
 }
 
 export async function updateLlamaCloud(): Promise<void> {
+  // eslint-disable-next-line turbo/no-undeclared-env-vars
   const apiKey = process.env.LLAMA_CLOUD_API_KEY;
-
+  // eslint-disable-next-line turbo/no-undeclared-env-vars
   const index = process.env.LLAMA_CLOUD_PIPELINE_ID;
 
   if (!apiKey || !index) {
@@ -82,26 +83,28 @@ export async function updateLlamaCloud(): Promise<void> {
 
   console.log(`added ${records.length} records`);
 
-  await upsertBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPut({
-    baseUrl: "https://api.cloud.llamaindex.ai/",
-    body: records.map((record) => ({
-      id: record.id,
-      metadata: {
-        title: record.title,
-        description: record.description,
-        documentUrl: record.id,
-        category: record.category,
+  await PipelinesService.upsertBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPut(
+    {
+      baseUrl: "https://api.cloud.llamaindex.ai/",
+      body: records.map((record) => ({
+        id: record.id,
+        metadata: {
+          title: record.title,
+          description: record.description,
+          documentUrl: record.id,
+          category: record.category,
+        },
+        text: record.content,
+      })),
+      path: {
+        pipeline_id: index,
+      },
+      throwOnError: true,
+      headers: {
+        Authorization: `Bearer ${apiKey}`,
       },
-      text: record.content,
-    })),
-    path: {
-      pipeline_id: index,
     },
-    throwOnError: true,
-    headers: {
-      Authorization: `Bearer ${apiKey}`,
-    },
-  });
+  );
 
   console.log("done");
 }

apps/next/src/app/(home)/page.tsx

@@ -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">

apps/next/src/app/api/chat/route.ts

@@ -1,33 +0,0 @@
-import { MockLLM } from "@llamaindex/core/utils";
-import { LlamaIndexAdapter, type Message } from "ai";
-import { Settings, 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[] };
-    const userMessage = messages[messages.length - 1];
-    if (!userMessage || userMessage.role !== "user") {
-      return NextResponse.json(
-        { detail: "Last message is not a user message" },
-        { status: 400 },
-      );
-    }
-
-    const chatEngine = new SimpleChatEngine();
-
-    return LlamaIndexAdapter.toDataStreamResponse(
-      await chatEngine.chat({
-        message: userMessage.content,
-        chatHistory: messages as ChatMessage[],
-        stream: true,
-      }),
-      {},
-    );
-  } catch (error) {
-    const detail = (error as Error).message;
-    return NextResponse.json({ detail }, { status: 500 });
-  }
-}

apps/next/src/components/contribution.tsx

@@ -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.

apps/next/src/components/contributor-count.tsx

@@ -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>
   );
 }

apps/next/src/components/demo/chat/api/demo.tsx

@@ -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>
-  );
-};

apps/next/src/components/demo/chat/rsc/ai-action.tsx

@@ -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,
-      };
-    },
-  },
-});

apps/next/src/components/demo/chat/rsc/chat-section.tsx

@@ -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>
-  );
-};

apps/next/src/components/demo/chat/rsc/demo.tsx

@@ -1,8 +0,0 @@
-import { AI } from "./ai-action";
-import { ChatSectionRSC } from "./chat-section";
-
-export const ChatDemoRSC = () => (
-  <AI>
-    <ChatSectionRSC />
-  </AI>
-);

apps/next/src/components/demo/chat/rsc/use-chat-rsc.tsx

@@ -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,
-  };
-}

apps/next/src/components/website/Footer.tsx

@@ -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>

apps/next/src/content/docs/llamaindex/guide/chat/chat.mdx

@@ -1,47 +0,0 @@
----
-title: Using API Route
-description: Chat interface for your LlamaIndexTS application using API Route
----
-import { ChatDemo } from '../../../../../components/demo/chat/api/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.
-You just need to create an API route that provides an `api/chat` endpoint and a chat component to consume the API.
-
-## API route
-
-As an example, this is an API route for the Next.js App Router. Copy the following code into your `app/api/chat/route.ts` file to get started:
-
-```json doc-gen:file
-{
-  "file": "./src/app/api/chat/route.ts",
-	"codeblock": true
-}
-```
-
-## Chat UI
-
-This is the simplest way to add a chat interface to your application. Copy the following code into your application to consume the API:
-
-```json doc-gen:file
-{
-  "file": "./src/components/demo/chat/api/demo.tsx",
-	"codeblock": true
-}
-```
-
-## Try it out ⬇️
-
-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. Use [create-llama](https://github.com/run-llama/create-llama) to scaffold a new LlamaIndexTS project including complex API routes and chat interfaces or
-2. Learn more about [chat-ui](https://github.com/run-llama/chat-ui) and [LlamaIndexTS](https://github.com/run-llama/llamaindex-ts) to customize the chat interface and API routes to your needs.
-

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

@@ -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"]
-}

apps/next/src/content/docs/llamaindex/guide/chat/rsc.mdx

@@ -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.
-

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

@@ -1,5 +1,5 @@
 {
   "title": "Guide",
   "description": "See our guide",
-  "pages": ["workflow", "chat"]
+  "pages": ["workflow"]
 }

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

@@ -1,5 +1,5 @@
 {
   "title": "Integration",
   "description": "See our integrations",
-  "pages": ["open-llm-metry", "lang-trace", "vercel"]
+  "pages": ["open-llm-metry", "lang-trace"]
 }

apps/next/src/content/docs/llamaindex/integration/vercel.mdx

@@ -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
-

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

@@ -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.

apps/next/src/content/docs/llamaindex/setup/typescript.mdx

@@ -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
 

apps/next/src/deps/cloud.ts

@@ -1,8 +1,8 @@
 import {
   type MetadataFilter,
   type MetadataFilters,
+  PipelinesService,
   type RetrievalParams,
-  runSearchApiV1PipelinesPipelineIdRetrievePost,
   type TextNodeWithScore,
 } from "@llamaindex/cloud/api";
 import { QueryBundle } from "@llamaindex/core/query-engine";
@@ -74,7 +74,7 @@ export class LlamaCloudRetriever extends BaseRetriever {
     const pipelineId = this.pipelineId;
 
     const { data: results } =
-      await runSearchApiV1PipelinesPipelineIdRetrievePost({
+      await PipelinesService.runSearchApiV1PipelinesPipelineIdRetrievePost({
         throwOnError: true,
         path: {
           pipeline_id: pipelineId,

apps/next/tailwind.config.js

@@ -10,7 +10,6 @@ export default {
     "./src/mdx-components.{ts,tsx}",
     "./node_modules/fumadocs-ui/dist/**/*.js",
     "./node_modules/fumadocs-openapi/dist/**/*.js",
-    "./node_modules/@llamaindex/chat-ui/**/*.{ts,tsx}",
   ],
   presets: [createPreset()],
   // eslint-disable-next-line @typescript-eslint/no-require-imports

apps/next/turbo.json

@@ -1,16 +0,0 @@
-{
-  "extends": ["//"],
-  "tasks": {
-    "build": {
-      "outputs": [
-        ".next",
-        ".source",
-        "next-env.d.ts",
-        "src/content/docs/cloud/api/**"
-      ]
-    },
-    "dev": {
-      "dependsOn": ["^build"]
-    }
-  }
-}

e2e/.env.ci

@@ -1,4 +0,0 @@
-POSTGRES_USER=runner
-PINECONE_API_KEY=
-PINECONE_INDEX_NAME=
-PINECONE_NAMESPACE=

e2e/examples/cloudflare-hono/.gitignore

@@ -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/

e2e/examples/cloudflare-hono/package.json

@@ -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"
-  }
-}

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

@@ -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,
-};

e2e/examples/cloudflare-hono/tsconfig.json

@@ -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"]
-}

e2e/examples/cloudflare-hono/worker-configuration.d.ts

@@ -1,4 +0,0 @@
-// Generated by Wrangler by running `wrangler types`
-
-// eslint-disable-next-line @typescript-eslint/no-empty-object-type
-interface Env {}

e2e/examples/cloudflare-hono/wrangler.toml

@@ -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

e2e/fixtures/llm/ollama.ts

@@ -1,3 +0,0 @@
-import { OpenAI } from "./openai.js";
-
-export class Ollama extends OpenAI {}

e2e/node/ollama.e2e.ts

@@ -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");
-    }
-  });
-});

e2e/node/snapshot/#1281.snap

@@ -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",
-              "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_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": "The"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": " result"
-      }
-    },
-    {
-      "id": "PRESERVE_1",
-      "chunk": {
-        "raw": null,
-        "options": {},
-        "delta": " of"
-      }
-    },
-    {
-      "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": "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": ""
-      }
-    }
-  ]
-}

e2e/node/snapshot/ollama.snap

@@ -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": []
-}

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

@@ -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",
-    );
-  });
-});

examples/CHANGELOG.md

@@ -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

examples/anthropic/prompt-caching.ts

@@ -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);

examples/azure-cosmosdb.ts

@@ -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 });
-})();

examples/cosmosdb/loadVectorData.ts

@@ -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}.`,

examples/cosmosdb/queryVectorData.ts

@@ -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 });

examples/cosmosdb/utils.ts

@@ -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 };
-};

examples/package.json

@@ -1,35 +1,32 @@
 {
   "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"
   },
   "devDependencies": {
-    "@types/node": "^22.9.0",
+    "@types/node": "^22.8.4",
     "tsx": "^4.19.0",
-    "typescript": "^5.6.3"
+    "typescript": "^5.6.2"
   },
   "scripts": {
     "lint": "eslint ."

examples/pipeline/ingestion.ts

@@ -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);

examples/readers/package.json

@@ -15,16 +15,15 @@
     "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": "*",
     "llamaindex": "*"
   },
   "devDependencies": {
-    "@types/node": "^22.9.0",
+    "@types/node": "^22.8.4",
     "tsx": "^4.19.0",
-    "typescript": "^5.6.3"
+    "typescript": "^5.6.2"
   }
 }

examples/readers/src/obsidian.ts

@@ -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());
-  });
-});

examples/vectorIndexLocal.ts

@@ -14,6 +14,7 @@ Settings.llm = new Ollama({
 
 Settings.embedModel = new HuggingFaceEmbedding({
   modelType: "BAAI/bge-small-en-v1.5",
+  quantized: false,
 });
 
 async function main() {

examples/vercel/README.md

@@ -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).

examples/vercel/llamacloud.ts

@@ -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);

examples/vercel/llm.ts

@@ -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);

examples/vercel/vector-store.ts

@@ -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);

examples/vllm.ts

@@ -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);

examples/workflow/app-creator.ts

@@ -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);

examples/workflow/collect-events.ts

@@ -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);

examples/workflow/joke.ts

@@ -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);

examples/workflow/stream-events.ts

@@ -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);

examples/workflow/timeout.ts

@@ -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();
 }
 

examples/workflow/validation.ts

@@ -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();
 }
 

package.json

@@ -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": "9.13.0",
+    "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",
+    "globals": "^15.11.0",
+    "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",
-    "typescript": "^5.6.3",
-    "typescript-eslint": "^8.15.0"
+    "turbo": "^2.2.3",
+    "typescript": "^5.6.2",
+    "typescript-eslint": "^8.12.2"
+  },
+  "packageManager": "pnpm@9.5.0",
+  "pnpm": {
+    "overrides": {
+      "trim": "1.0.1",
+      "protobufjs": "7.2.6"
+    }
   },
-  "packageManager": "pnpm@9.12.3",
   "lint-staged": {
     "(!apps/docs/i18n/**/docusaurus-plugin-content-docs/current/api/*).{js,jsx,ts,tsx,md}": "prettier --write"
   }

packages/autotool/CHANGELOG.md

@@ -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

packages/autotool/examples/01_node/CHANGELOG.md

@@ -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

packages/autotool/examples/01_node/package.json

@@ -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"
 }

packages/autotool/examples/02_nextjs/CHANGELOG.md

@@ -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

packages/autotool/examples/02_nextjs/package.json

@@ -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",
@@ -10,28 +10,28 @@
   "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": "14.3.0-canary.51",
     "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": {
-    "@types/node": "^22.9.0",
+    "@types/node": "^22.8.4",
     "@types/react": "^18.3.12",
     "@types/react-dom": "^18.3.1",
     "@types/react-syntax-highlighter": "^15.5.11",
     "autoprefixer": "^10.4.20",
     "cross-env": "^7.0.3",
-    "postcss": "^8.4.49",
-    "tailwindcss": "^3.4.15",
-    "typescript": "^5.6.3"
+    "postcss": "^8.4.41",
+    "tailwindcss": "^3.4.10",
+    "typescript": "^5.6.2"
   }
 }

packages/autotool/package.json

@@ -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",
-    "typedoc": "^0.26.11",
-    "unplugin": "^1.16.0"
+    "@swc/core": "^1.7.22",
+    "jotai": "2.8.4",
+    "typedoc": "^0.26.6",
+    "unplugin": "^1.12.2"
   },
   "peerDependencies": {
     "llamaindex": "workspace:*",
@@ -69,14 +69,14 @@
   "devDependencies": {
     "@swc/types": "^0.1.12",
     "@types/json-schema": "^7.0.15",
-    "@types/node": "^22.9.0",
-    "bunchee": "5.6.1",
+    "@types/node": "^22.8.4",
+    "bunchee": "5.5.1",
     "llamaindex": "workspace:*",
-    "next": "15.0.3",
-    "rollup": "^4.27.3",
+    "next": "14.2.11",
+    "rollup": "^4.21.2",
     "tsx": "^4.19.0",
-    "typescript": "^5.6.3",
-    "vitest": "^2.1.5",
+    "typescript": "^5.6.2",
+    "vitest": "^2.0.5",
     "webpack": "^5.94.0"
   }
 }

packages/autotool/src/internal/index.ts

@@ -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>>({});

packages/cloud/CHANGELOG.md

@@ -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

packages/cloud/openapi-ts.config.ts

@@ -10,6 +10,9 @@ export default defineConfig({
     format: "prettier",
     lint: "eslint",
   },
+  services: {
+    asClass: true,
+  },
   types: {
     enums: "javascript",
   },

packages/cloud/package.json

@@ -1,10 +1,10 @@
 {
   "name": "@llamaindex/cloud",
-  "version": "2.0.18",
+  "version": "2.0.1",
   "type": "module",
   "license": "MIT",
   "scripts": {
-    "generate": "./node_modules/.bin/openapi-ts",
+    "generate": "pnpx @hey-api/openapi-ts@0.53.11",
     "build": "pnpm run generate && bunchee",
     "dev": "bunchee --watch"
   },
@@ -50,11 +50,11 @@
     "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": "^0.53.11",
     "@llamaindex/core": "workspace:*",
     "@llamaindex/env": "workspace:*",
-    "bunchee": "5.6.1"
+    "bunchee": "5.5.1"
   },
   "peerDependencies": {
     "@llamaindex/core": "workspace:*",

packages/cloud/src/reader.ts

@@ -4,12 +4,7 @@ import { fs, getEnv, path } from "@llamaindex/env";
 import {
   type Body_upload_file_api_v1_parsing_upload_post,
   type ParserLanguages,
-  getJobApiV1ParsingJobJobIdGet,
-  getJobImageResultApiV1ParsingJobJobIdResultImageNameGet,
-  getJobJsonResultApiV1ParsingJobJobIdResultJsonGet,
-  getJobResultApiV1ParsingJobJobIdResultMarkdownGet,
-  getJobTextResultApiV1ParsingJobJobIdResultTextGet,
-  uploadFileApiV1ParsingUploadPost,
+  ParsingService,
 } from "./api";
 import { sleep } from "./utils";
 
@@ -206,7 +201,7 @@ export class LlamaParseReader extends FileReader {
         | undefined;
     } as unknown as Body_upload_file_api_v1_parsing_upload_post;
 
-    const response = await uploadFileApiV1ParsingUploadPost({
+    const response = await ParsingService.uploadFileApiV1ParsingUploadPost({
       client: this.#client,
       throwOnError: true,
       signal: AbortSignal.timeout(this.maxTimeout * 1000),
@@ -228,7 +223,7 @@ export class LlamaParseReader extends FileReader {
       await sleep(this.checkInterval * 1000);
 
       // Check the job status. If unsuccessful response, checks if maximum timeout has been reached. If reached, throws an error
-      const result = await getJobApiV1ParsingJobJobIdGet({
+      const result = await ParsingService.getJobApiV1ParsingJobJobIdGet({
         client: this.#client,
         throwOnError: true,
         path: {
@@ -244,36 +239,45 @@ export class LlamaParseReader extends FileReader {
         let result;
         switch (resultType) {
           case "json": {
-            result = await getJobJsonResultApiV1ParsingJobJobIdResultJsonGet({
-              client: this.#client,
-              throwOnError: true,
-              path: {
-                job_id: jobId,
-              },
-              signal,
-            });
+            result =
+              await ParsingService.getJobJsonResultApiV1ParsingJobJobIdResultJsonGet(
+                {
+                  client: this.#client,
+                  throwOnError: true,
+                  path: {
+                    job_id: jobId,
+                  },
+                  signal,
+                },
+              );
             break;
           }
           case "markdown": {
-            result = await getJobResultApiV1ParsingJobJobIdResultMarkdownGet({
-              client: this.#client,
-              throwOnError: true,
-              path: {
-                job_id: jobId,
-              },
-              signal,
-            });
+            result =
+              await ParsingService.getJobResultApiV1ParsingJobJobIdResultMarkdownGet(
+                {
+                  client: this.#client,
+                  throwOnError: true,
+                  path: {
+                    job_id: jobId,
+                  },
+                  signal,
+                },
+              );
             break;
           }
           case "text": {
-            result = await getJobTextResultApiV1ParsingJobJobIdResultTextGet({
-              client: this.#client,
-              throwOnError: true,
-              path: {
-                job_id: jobId,
-              },
-              signal,
-            });
+            result =
+              await ParsingService.getJobTextResultApiV1ParsingJobJobIdResultTextGet(
+                {
+                  client: this.#client,
+                  throwOnError: true,
+                  path: {
+                    job_id: jobId,
+                  },
+                  signal,
+                },
+              );
             break;
           }
         }
@@ -455,13 +459,15 @@ export class LlamaParseReader extends FileReader {
     jobId: string,
   ): Promise<void> {
     const response =
-      await getJobImageResultApiV1ParsingJobJobIdResultImageNameGet({
-        client: this.#client,
-        path: {
-          job_id: jobId,
-          name: imageName,
+      await ParsingService.getJobImageResultApiV1ParsingJobJobIdResultImageNameGet(
+        {
+          client: this.#client,
+          path: {
+            job_id: jobId,
+            name: imageName,
+          },
         },
-      });
+      );
     if (response.error) {
       throw new Error(`Failed to download image: ${response.error.detail}`);
     }

packages/cloud/tsconfig.json

@@ -8,6 +8,7 @@
     "moduleResolution": "Bundler",
     "skipLibCheck": true,
     "strict": true,
+    "lib": ["DOM", "ESNext"],
     "types": []
   },
   "include": ["./src"],

packages/community/CHANGELOG.md

@@ -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

packages/community/README.md

@@ -4,8 +4,7 @@
 
 ## 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 Anthropic Claude Models [usage](https://ts.llamaindex.ai/modules/llms/available_llms/bedrock) including the latest Sonnet 3.5 v2
 - 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
 - Meta 3.2 11B and 90B vision support

packages/community/package.json

@@ -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",
@@ -42,12 +42,12 @@
     "dev": "bunchee --watch"
   },
   "devDependencies": {
-    "@types/node": "^22.9.0",
-    "bunchee": "5.6.1"
+    "@types/node": "^22.8.4",
+    "bunchee": "5.5.1"
   },
   "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:*"
   }

packages/community/src/llm/bedrock/amazon/provider.ts

@@ -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),
-    };
-  }
-}

packages/community/src/llm/bedrock/amazon/types.ts

@@ -1,5 +0,0 @@
-import type { ConverseRequest, Message } from "@aws-sdk/client-bedrock-runtime";
-
-export type AmazonMessages = ConverseRequest["messages"];
-
-export type AmazonMessage = Message;

packages/community/src/llm/bedrock/amazon/utils.ts

@@ -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;
-  });
-};

packages/community/src/llm/bedrock/anthropic/provider.ts

@@ -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) {

packages/community/src/llm/bedrock/anthropic/types.ts

@@ -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;

packages/community/src/llm/bedrock/index.ts

@@ -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<
@@ -68,7 +66,6 @@ export const BEDROCK_MODELS = {
   ANTHROPIC_CLAUDE_3_OPUS: "anthropic.claude-3-opus-20240229-v1:0",
   ANTHROPIC_CLAUDE_3_5_SONNET: "anthropic.claude-3-5-sonnet-20240620-v1:0",
   ANTHROPIC_CLAUDE_3_5_SONNET_V2: "anthropic.claude-3-5-sonnet-20241022-v2:0",
-  ANTHROPIC_CLAUDE_3_5_HAIKU: "anthropic.claude-3-5-haiku-20241022-v1:0",
   META_LLAMA2_13B_CHAT: "meta.llama2-13b-chat-v1",
   META_LLAMA2_70B_CHAT: "meta.llama2-70b-chat-v1",
   META_LLAMA3_8B_INSTRUCT: "meta.llama3-8b-instruct-v1:0",
@@ -83,17 +80,12 @@ 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 +96,8 @@ 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 +122,6 @@ 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]:
@@ -183,7 +169,6 @@ const CHAT_ONLY_MODELS = {
   [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_OPUS]: 200000,
   [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET]: 200000,
   [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET_V2]: 200000,
-  [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_HAIKU]: 200000,
   [BEDROCK_MODELS.META_LLAMA2_13B_CHAT]: 2048,
   [BEDROCK_MODELS.META_LLAMA2_70B_CHAT]: 4096,
   [BEDROCK_MODELS.META_LLAMA3_8B_INSTRUCT]: 8192,
@@ -198,9 +183,6 @@ 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 };
@@ -222,7 +204,6 @@ export const STREAMING_MODELS = new Set([
   BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_OPUS,
   BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET,
   BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET_V2,
-  BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_HAIKU,
   BEDROCK_MODELS.META_LLAMA2_13B_CHAT,
   BEDROCK_MODELS.META_LLAMA2_70B_CHAT,
   BEDROCK_MODELS.META_LLAMA3_8B_INSTRUCT,
@@ -237,9 +218,6 @@ 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[] = [
@@ -248,15 +226,11 @@ export const TOOL_CALL_MODELS: BEDROCK_MODELS[] = [
   BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_OPUS,
   BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET,
   BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET_V2,
-  BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_HAIKU,
   BEDROCK_MODELS.META_LLAMA3_1_405B_INSTRUCT,
   BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT,
   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 => {
@@ -285,8 +259,7 @@ export const BEDROCK_MODEL_MAX_TOKENS: Partial<Record<BEDROCK_MODELS, number>> =
     [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU]: 4096,
     [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_OPUS]: 4096,
     [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET]: 4096,
-    [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET_V2]: 8192,
-    [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_HAIKU]: 8192,
+    [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET_V2]: 4096,
     [BEDROCK_MODELS.META_LLAMA2_13B_CHAT]: 2048,
     [BEDROCK_MODELS.META_LLAMA2_70B_CHAT]: 2048,
     [BEDROCK_MODELS.META_LLAMA3_8B_INSTRUCT]: 2048,
@@ -338,6 +311,10 @@ 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 +336,6 @@ 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 +369,6 @@ 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 +379,7 @@ 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);
   }
 

packages/community/src/llm/bedrock/provider.ts

@@ -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>

packages/community/src/llm/bedrock/types.ts

@@ -4,3 +4,8 @@ export type InvocationMetrics = {
   invocationLatency: number;
   firstByteLatency: number;
 };
+
+export type ToolChoice =
+  | { type: "any" }
+  | { type: "auto" }
+  | { type: "tool"; name: string };

packages/core/CHANGELOG.md

@@ -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

packages/core/package.json

@@ -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",
@@ -389,15 +347,15 @@
     "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",
+    "bunchee": "5.5.1",
+    "happy-dom": "^15.7.4",
     "natural": "^8.0.1"
   },
   "dependencies": {
     "@llamaindex/env": "workspace:*",
-    "@types/node": "^22.9.0",
+    "@types/node": "^22.8.4",
     "magic-bytes.js": "^1.10.0",
     "zod": "^3.23.8",
     "zod-to-json-schema": "^3.23.3"

packages/core/src/agent/base.ts

@@ -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));

packages/core/src/agent/llm.ts

@@ -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)

packages/core/src/agent/types.ts

@@ -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>;
 

packages/core/src/agent/utils.ts

@@ -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);
         });
       }

packages/core/src/chat-engine/base.ts

@@ -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 {