Release 0.11.23 (#2136 )

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
feat: Add toolcall callbacks to agent workflows (#2137 )
2026-07-01 22:14:03 -04:00 · 2025-07-28 14:07:23 +08:00 · 2025-07-24 15:37:14 +08:00 · 2025-07-23 12:55:35 +08:00 · 2025-07-23 12:37:02 +08:00 · 2025-07-23 11:30:04 +08:00
242 changed files with 13420 additions and 13925 deletions
@@ -38,6 +38,7 @@ npm install -g pnpm

 ```shell
 pnpm install
+pnpm install -g tsx
 ```

 ### Build the packages
@@ -48,6 +49,56 @@ To build all packages, run:
 pnpm build
 ```

+### Start Developing
+
+You can launch the package in dev-mode by running:
+
+```shell
+pnpm dev
+```
+
+This will use turbo to run all packages in watch-mode. This means you can make changes and have them automatically built.
+
+If you want to customize what packages are built/watched, you can run turbo directly and adjust the filter:
+
+```shell
+pnpm turbo run dev --filter="./packages/core" --concurrency=100
+```
+
+In another terminal, you can write and run any script needed to quickly test your changes. For example:
+
+```typescript
+import { createMemory, staticBlock } from "@llamaindex/core/memory";
+
+// Create memory with predefined context
+const memory = createMemory({
+  memoryBlocks: [
+    staticBlock({
+      content:
+        "The user is a software engineer who loves TypeScript and LlamaIndex.",
+      messageRole: "system",
+    }),
+  ],
+});
+
+async function main() {
+  const result = await memory.getLLM();
+  console.log(result);
+}
+
+void main().catch(console.error);
+```
+
+And run it with:
+
+```shell
+pnpm exec tsx my_script.ts
+```
+
+This flow allows you to easily test your changes without having to build the entire project.
+
+Once you are happy with your changes, be sure to add tests (and confirm existing tests are passing!).
+
 ### Run tests

 #### Unit tests
@@ -92,7 +143,7 @@ Before sending a PR, make sure of the following:
 3. If you have a new feature, add a new example in the `examples` folder.
 4. You have a descriptive changeset for each PR:

-### Changesets
+### Bumping the versions of packages you've modified

 We use [changesets](https://github.com/changesets/changesets) for managing versions and changelogs. To create a new
 changeset, run in the root folder:
@@ -101,6 +152,8 @@ changeset, run in the root folder:
 pnpm changeset
 ```

+You will be prompted to choose what packages need their versions bumped, and what kind of bump (major, minor or patch) is needed. Once you carry out this operation, the bumping will be automatic after the PR is merged.
+
 ## Publishing (maintainers only)

 The [Release Github Action](.github/workflows/release.yml) is automatically generating and updating a
@@ -1,5 +1,138 @@
 # @llamaindex/doc

+## 0.2.46
+
+### Patch Changes
+
+- Updated dependencies [f29799e]
+- Updated dependencies [7224c06]
+  - @llamaindex/workflow@1.1.19
+  - @llamaindex/core@0.6.18
+  - llamaindex@0.11.23
+  - @llamaindex/cloud@4.0.27
+  - @llamaindex/node-parser@2.0.18
+  - @llamaindex/openai@0.4.13
+  - @llamaindex/readers@3.1.17
+
+## 0.2.45
+
+### Patch Changes
+
+- Updated dependencies [9ed3195]
+  - @llamaindex/workflow@1.1.18
+  - llamaindex@0.11.22
+
+## 0.2.44
+
+### Patch Changes
+
+- 38da40b: feat: VectoryMemoryBlock
+- Updated dependencies [38da40b]
+  - @llamaindex/core@0.6.17
+  - @llamaindex/cloud@4.0.26
+  - llamaindex@0.11.21
+  - @llamaindex/node-parser@2.0.17
+  - @llamaindex/openai@0.4.12
+  - @llamaindex/readers@3.1.16
+  - @llamaindex/workflow@1.1.17
+
+## 0.2.43
+
+### Patch Changes
+
+- ea15e75: Minor updates in deployment docs
+
+## 0.2.42
+
+### Patch Changes
+
+- a8ec08c: fix: ensure correct message content in agent workflow
+- Updated dependencies [a8ec08c]
+- Updated dependencies [2967d57]
+  - @llamaindex/core@0.6.16
+  - @llamaindex/workflow@1.1.16
+  - @llamaindex/cloud@4.0.25
+  - llamaindex@0.11.20
+  - @llamaindex/node-parser@2.0.16
+  - @llamaindex/openai@0.4.11
+  - @llamaindex/readers@3.1.15
+
+## 0.2.41
+
+### Patch Changes
+
+- Updated dependencies [856dd8c]
+  - @llamaindex/openai@0.4.10
+
+## 0.2.40
+
+### Patch Changes
+
+- Updated dependencies [7ad3411]
+- Updated dependencies [5da5b3c]
+- Updated dependencies [a1fdb07]
+  - @llamaindex/core@0.6.15
+  - @llamaindex/workflow@1.1.15
+  - @llamaindex/openai@0.4.9
+  - @llamaindex/cloud@4.0.24
+  - llamaindex@0.11.19
+  - @llamaindex/node-parser@2.0.15
+  - @llamaindex/readers@3.1.14
+
+## 0.2.39
+
+### Patch Changes
+
+- Updated dependencies [a1b1598]
+  - @llamaindex/cloud@4.0.23
+  - llamaindex@0.11.18
+
+## 0.2.38
+
+### Patch Changes
+
+- Updated dependencies [d2be868]
+  - @llamaindex/cloud@4.0.22
+  - llamaindex@0.11.17
+
+## 0.2.37
+
+### Patch Changes
+
+- Updated dependencies [579ca0c]
+  - @llamaindex/cloud@4.0.21
+  - llamaindex@0.11.16
+
+## 0.2.36
+
+### Patch Changes
+
+- Updated dependencies [48b0d88]
+- Updated dependencies [f185772]
+  - @llamaindex/cloud@4.0.20
+  - llamaindex@0.11.15
+
+## 0.2.35
+
+### Patch Changes
+
+- Updated dependencies [5a0ed1f]
+- Updated dependencies [5a0ed1f]
+- Updated dependencies [8eeac33]
+  - @llamaindex/cloud@4.0.19
+  - @llamaindex/core@0.6.14
+  - llamaindex@0.11.14
+  - @llamaindex/node-parser@2.0.14
+  - @llamaindex/openai@0.4.8
+  - @llamaindex/readers@3.1.13
+  - @llamaindex/workflow@1.1.14
+
+## 0.2.34
+
+### Patch Changes
+
+- 39758ab: Add title to homepage header
+
 ## 0.2.33

 ### Patch Changes
@@ -27,6 +27,33 @@ const config = {
        destination: "/docs/workflows/:path*",
        permanent: true,
      },
+      {
+        source: "/docs/llamaindex/getting_started/installation/node.mdx",
+        destination:
+          "/docs/llamaindex/getting_started/installation/server-apis.mdx",
+        permanent: true,
+      },
+      {
+        source: "/docs/llamaindex/getting_started/installation/typescript.mdx",
+        destination: "/docs/llamaindex/getting_started/installation/index.mdx",
+        permanent: true,
+      },
+      {
+        source: "/docs/llamaindex/getting_started/installation/next.mdx",
+        destination: "/docs/llamaindex/getting_started/installation/nextjs.mdx",
+        permanent: true,
+      },
+      {
+        source: "/docs/llamaindex/getting_started/installation/vite.mdx",
+        destination: "/docs/llamaindex/getting_started/installation/index.mdx",
+        permanent: true,
+      },
+      {
+        source: "/docs/llamaindex/getting_started/installation/cloudflare.mdx",
+        destination:
+          "/docs/llamaindex/getting_started/installation/serverless.mdx",
+        permanent: true,
+      },
    ];
  },
  turbopack: {
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/doc",
-  "version": "0.2.33",
+  "version": "0.2.46",
  "private": true,
  "scripts": {
    "postinstall": "fumadocs-mdx",
@@ -35,7 +35,7 @@
    "@radix-ui/react-tooltip": "^1.1.4",
    "@scalar/api-client-react": "^1.1.25",
    "@vercel/functions": "^1.5.0",
-    "ai": "^3.4.33",
+    "ai": "^4.3.17",
    "class-variance-authority": "^0.7.0",
    "clsx": "2.1.1",
    "foxact": "^0.2.41",
@@ -50,7 +50,7 @@
    "hast-util-to-jsx-runtime": "^2.3.2",
    "llamaindex": "workspace:*",
    "lucide-react": "^0.460.0",
-    "next": "^15.3.0",
+    "next": "^15.3.3",
    "next-themes": "^0.4.3",
    "react": "^19.1.0",
    "react-dom": "^19.1.0",
@@ -70,30 +70,30 @@
    "twoslash": "^0.3.1",
    "use-stick-to-bottom": "^1.0.42",
    "web-tree-sitter": "^0.24.4",
-    "zod": "^3.25.67"
+    "zod": "^3.25.76"
  },
  "devDependencies": {
    "@next/env": "^15.3.0",
    "@tailwindcss/postcss": "^4.0.9",
    "@types/mdx": "^2.0.13",
-    "@types/node": "22.9.0",
-    "@types/react": "^19.0.10",
-    "@types/react-dom": "^19.0.4",
+    "@types/node": "24.0.13",
+    "@types/react": "^19.1.8",
+    "@types/react-dom": "^19.1.6",
    "autoprefixer": "^10.4.20",
    "cross-env": "^7.0.3",
    "fast-glob": "^3.3.2",
    "gray-matter": "^4.0.3",
-    "postcss": "^8.5.3",
+    "postcss": "^8.5.6",
    "raw-loader": "^4.0.2",
    "remark": "^15.0.1",
    "remark-gfm": "^4.0.0",
    "remark-mdx": "^3.1.0",
    "remark-stringify": "^11.0.0",
-    "tailwindcss": "^4.0.9",
-    "tsx": "^4.19.3",
+    "tailwindcss": "^4.1.11",
+    "tsx": "^4.20.3",
    "typedoc": "0.28.3",
    "typedoc-plugin-markdown": "^4.6.2",
    "typedoc-plugin-merge-modules": " ^7.0.0",
-    "typescript": "^5.7.3"
+    "typescript": "^5.8.3"
  }
 }
@@ -1,4 +1,4 @@
-import { MockLLM } from "@llamaindex/core/utils";
+import { MockLLM } from "@llamaindex/core/llms/mock";
 import { LlamaIndexAdapter, type Message } from "ai";
 import { Settings, SimpleChatEngine, type ChatMessage } from "llamaindex";
 import { NextResponse, type NextRequest } from "next/server";
@@ -1,6 +1,6 @@
 import { AIProvider } from "@/actions";
 import { TooltipProvider } from "@/components/ui/tooltip";
-import { GoogleAnalytics } from "@next/third-parties/google";
+import { GoogleAnalytics, GoogleTagManager } from "@next/third-parties/google";
 import { RootProvider } from "fumadocs-ui/provider";
 import { Inter } from "next/font/google";
 import type { ReactNode } from "react";
@@ -32,7 +32,11 @@ export default function Layout({ children }: { children: ReactNode }) {
          sizes="16x16"
          href="/favicon-16x16.png"
        />
+        <title>
+          LlamaIndex.TS - Build LLM-powered document agents and workflows
+        </title>
      </head>
+      <GoogleTagManager gtmId="GTM-WWRFB36R" />
      <body className="flex min-h-screen flex-col">
        <TooltipProvider>
          <AIProvider>
@@ -19,3 +19,8 @@ npm run dev
 to start the development server. You can then visit [http://localhost:3000](http://localhost:3000) to see your app, which should look something like this:

 ![create-llama interface](/images/create_llama.png)
+
+## Learn more
+
+- [Learn more about `create-llama`](https://github.com/run-llama/create-llama)
+- [Want to use the same UI components? You can use our React components](https://ui.llamaindex.ai/)
@@ -17,7 +17,8 @@ npm i
 Then you can run any example in the folder with `tsx`, e.g.:

 ```bash npm2yarn
-npx tsx ./vectorIndex.ts
+export OPENAI_API_KEY=your-api-key
+npx tsx ./agents/agent/openai.ts
 ```

 ## Try examples online
@@ -1,70 +0,0 @@
---
-title: With Cloudflare Worker
-description: In this guide, you'll learn how to use LlamaIndex with CloudFlare Worker
---
-
-Before you start, make sure you have try LlamaIndex.TS in Node.js to make sure you understand the basics.
-
-<Card
-  title="Getting Started with LlamaIndex.TS in Node.js"
-  href="/docs/llamaindex/getting_started/installation/node"
-/>
-
-Also, you need have the basic understanding of <a href='https://developers.cloudflare.com/workers/'><SiCloudflareworkers className="inline mr-2" color="#F38020" />Cloudflare Worker</a>.
-
-## Adding environment variables
-
-```ts
-export default {
-  async fetch(request: Request, env: Env): Promise<Response> {
-    const { setEnvs } = await import("@llamaindex/env");
-    setEnvs(env);
-    const { OpenAIAgent } = await import("@llamaindex/openai");
-    // Start your code here
-    return new Response("Hello, world!");
-  },
-};
-```
-
-Then, you need create `.dev.vars` and add LLM api keys for the local development, such as `OPENAI_API_KEY` for OpenAI API key.
-
-<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:
-
- Some Node.js modules are not available in Cloudflare Worker, such as `node:fs`, `node:child_process`, `node:cluster`...
- You are recommend to design your code using network request, such as use `fetch` API to communicate with database, instead of a long-running process in Node.js.
- Some of LlamaIndex.TS packages are not available in Cloudflare Worker, for example `@llamaindex/readers` and `@llamaindex/huggingface`.
- The main `llamaindex` is designed to work in all JavaScript environment, including Cloudflare Worker. If you find any issue, please report to us.
- `@llamaindex/env` is a JS environment binding module, which polyfill some Node.js/Modern Web API (for example, we have a memory based `fs` module, and Crypto API polyfill). It is designed to work in all JavaScript environment, including Cloudflare Worker.
-
-
@@ -1,69 +1,177 @@
 ---
 title: Installation
-description: How to install llamaindex packages.
+description: How to install and set up LlamaIndex.TS for your project.
 ---

-To install llamaindex, run the following command:
+## Quick Start
+
+Install the core package:

 ```package-install
 npm i llamaindex
 ```

-In most cases, you'll also need an LLM package and the Workflow package to use LlamaIndex. For example, to use the OpenAI LLM with agents, you would install the following:
+In most cases, you'll also need an LLM provider and the Workflow package:

 ```package-install
 npm i @llamaindex/openai @llamaindex/workflow
 ```

-Go to [LLM APIs](/docs/llamaindex/modules/models/llms) to find out how to use other LLMs.
+## Environment Setup

+### API Keys

-## Frameworks
+Most LLM providers require API keys. Set your OpenAI key (or other provider):

-LlamaIndex supports a wide range of frameworks and runtimes. Click on the card below to learn more.
+```bash
+export OPENAI_API_KEY=your-api-key
+```
+
+Or use a `.env` file:
+
+```bash
+echo "OPENAI_API_KEY=your-api-key" > .env
+```
+
+<Callout type="warn">Never commit API keys to your repository.</Callout>
+
+### Loading Environment Variables
+
+For Node.js applications:
+
+```bash
+node --env-file .env your-script.js
+```
+
+For other environments, see the deployment-specific guides below.
+
+## TypeScript Configuration
+
+LlamaIndex.TS is built with TypeScript and provides excellent type safety. Add these settings to your `tsconfig.json`:
+
+```json5
+{
+  "compilerOptions": {
+    // Essential for module resolution
+    "moduleResolution": "bundler", // or "nodenext" | "node16" | "node"
+    
+    // Required for Web Stream API support
+    "lib": ["DOM.AsyncIterable"],
+    
+    // Recommended for better compatibility
+    "target": "es2020",
+    "module": "esnext"
+  }
+}
+```
+
+## Running your first agent
+
+### Set up
+
+If you don't already have a project, you can create a new one in a new folder:
+
+```package-install
+npm init
+npm i -D typescript @types/node
+npm i @llamaindex/openai @llamaindex/workflow llamaindex zod
+```
+
+### Run the agent
+
+Create the file `example.ts`. This code will:
+
+- Create two tools for use by the agent:
+  - A `sumNumbers` tool that adds two numbers
+  - A `divideNumbers` tool that divides numbers
+- Give an example of the data structure we wish to generate
+- Prompt the LLM with instructions and the example, plus a sample transcript
+
+<include cwd>../../examples/agents/agent/openai.ts</include>
+
+To run the code:
+
+```package-install
+npx tsx example.ts
+```
+
+You should expect output something like:
+
+```
+{
+  result: '5 + 5 is 10. Then, 10 divided by 2 is 5.',
+  state: {
+    memory: Memory {
+      messages: [Array],
+      tokenLimit: 30000,
+      shortTermTokenLimitRatio: 0.7,
+      memoryBlocks: [],
+      memoryCursor: 0,
+      adapters: [Object]
+    },
+    scratchpad: [],
+    currentAgentName: 'Agent',
+    agents: [ 'Agent' ],
+    nextAgentName: null
+  }
+}
+Done
+```
+
+## Performance Optimization
+
+### Tokenization Speed
+
+Install `gpt-tokenizer` for 60x faster tokenization (Node.js environments only):
+
+```package-install
+npm i gpt-tokenizer
+```
+
+LlamaIndex will automatically use this when available.
+
+## Deployment Guides
+
+Choose your deployment target:

 <Cards>
-	<Card title={
-		<>
-			<SiNodedotjs className="inline" color="#5FA04E" /> Node.js
-		</>
-	} href="/docs/llamaindex/getting_started/installation/node" />
-	<Card title={
-		<>
-			<SiTypescript className="inline" color="#3178C6" /> TypeScript
-		</>
-	} href="/docs/llamaindex/getting_started/installation/typescript" />
-	<Card title={
-		<>
-			<SiVite className='inline' color='#646CFF' /> Vite
-		</>
-	} href="/docs/llamaindex/getting_started/installation/vite" />
-	<Card
-		title={
-			<>
-				<SiNextdotjs className='inline' /> Next.js (React Server Component)
-			</>
-		}
-		href="/docs/llamaindex/getting_started/installation/next"
-	/>
-	<Card title={
-		<>
-			<SiCloudflareworkers className='inline' color='#F38020' /> Cloudflare Workers
-		</>
-	} href="/docs/llamaindex/getting_started/installation/cloudflare" />
+  <Card 
+    title="Server APIs & Backends" 
+    description="Express, Fastify, Koa, standalone Node.js servers"
+    href="/docs/llamaindex/getting_started/installation/server-apis" 
+  />
+  <Card 
+    title="Serverless Functions" 
+    description="Vercel, Netlify, AWS Lambda, Cloudflare Workers"
+    href="/docs/llamaindex/getting_started/installation/serverless" 
+  />
+  <Card 
+    title="Next.js Applications" 
+    description="API routes, server components, edge runtime"
+    href="/docs/llamaindex/getting_started/installation/nextjs" 
+  />
+  <Card 
+    title="Troubleshooting" 
+    description="Common issues, bundle optimization, compatibility"
+    href="/docs/llamaindex/getting_started/installation/troubleshooting" 
+  />
 </Cards>

-## What's next?
+## LLM/Embedding Providers
+
+Go to [LLM APIs](/docs/llamaindex/modules/models/llms) and [Embedding APIs](/docs/llamaindex/modules/models/embeddings) to find out how to use different LLM and embedding providers beyond OpenAI.
+
+## What's Next?

 <Cards>
-	<Card
-		title="Learn LlamaIndex.TS"
-		description="Learn how to use LlamaIndex.TS by starting with one of our tutorials."
-		href="/docs/llamaindex/tutorials/rag"
-	/>
-	<Card
-		title="Show me code examples"
-		description="Explore code examples using LlamaIndex.TS."
-		href="/docs/llamaindex/getting_started/examples"
-	/>
+  <Card
+    title="Learn LlamaIndex.TS"
+    description="Learn how to use LlamaIndex.TS by starting with one of our tutorials."
+    href="/docs/llamaindex/tutorials/basic_agent"
+  />
+  <Card
+    title="Show me code examples"
+    description="Explore code examples using LlamaIndex.TS."
+    href="/docs/llamaindex/getting_started/examples"
+  />
 </Cards>
@@ -1,4 +1,4 @@
 {
  "title": "Installation",
-  "pages": ["node", "typescript", "next", "vite", "cloudflare"]
+  "pages": ["server-apis", "serverless", "nextjs", "troubleshooting"]
 }
@@ -1,41 +0,0 @@
---
-title: With Next.js
-description: In this guide, you'll learn how to use LlamaIndex with Next.js.
---
-
-Before you start, make sure you have try LlamaIndex.TS in Node.js to make sure you understand the basics.
-
-<Card
-  title="Getting Started with LlamaIndex.TS in Node.js"
-  href="/docs/llamaindex/getting_started/installation/node"
-/>
-
-## Differences between Node.js and Next.js
-
-Next.js is a React framework that has both server side compatibility and client side compatibility.
-This means that you need to be careful when using LlamaIndex.TS in Next.js.
-Don't leak the import data like API keys to the client side.
-
-Also, in Next.js, there is build time and runtime. Some computations can be done at build time like Document embedding could be done at build time for better performance.
-Where as the `llamaindex` package is working with Next.js, some provider packages like `@llamaindex/huggingface` are not working well with Next.js. This is due to the upstream dependencies used by the provider package. 
-
-Make sure to use `withLlamaIndex` to make sure that LlamaIndex.TS works well with Next.js.
-
-```js
-// next.config.mjs / next.config.ts
-import withLlamaIndex from "llamaindex/next";
-
-/** @type {import('next').NextConfig} */
-const nextConfig = {};
-
-export default withLlamaIndex(nextConfig);
-```
-
-If you see any dependency issues, you are welcome to open an issue on the GitHub.
-
-## Edge Runtime
-
-[Vercel Edge Runtime](https://edge-runtime.vercel.app/) is a subset of Node.js APIs. Similar to [Cloudflare Workers](/docs/llamaindex/getting_started/installation/cloudflare#difference-between-nodejs-and-cloudflare-worker),
-it is a serverless platform that runs your code on the edge.
-
-Not all features of Node.js are supported in Vercel Edge Runtime, so does LlamaIndex.TS, we are working on more compatibility with all JavaScript runtimes.
@@ -0,0 +1,405 @@
+---
+title: Next.js Applications
+description: Deploy LlamaIndex.TS in Next.js applications with API routes, server components, and edge runtime.
+---
+
+This guide covers integrating LlamaIndex.TS agents with Next.js applications.
+
+## Essential Configuration
+
+### Next.js Config
+
+Use `withLlamaIndex` to ensure compatibility:
+
+```javascript
+// next.config.mjs
+import withLlamaIndex from "llamaindex/next";
+
+/** @type {import('next').NextConfig} */
+const nextConfig = {
+  // Your existing config
+};
+
+export default withLlamaIndex(nextConfig);
+```
+
+## API Routes
+
+### App Router (Recommended)
+
+```typescript
+// app/api/chat/route.ts
+import { agent } from "@llamaindex/workflow";
+import { tool } from "llamaindex";
+import { openai } from "@llamaindex/openai";
+import { z } from "zod";
+import { NextRequest, NextResponse } from "next/server";
+
+// Initialize agent once (consider using a singleton pattern)
+let myAgent: any = null;
+
+async function initializeAgent() {
+  if (myAgent) return myAgent;
+  
+  try {
+    const greetTool = tool({
+      name: "greet",
+      description: "Greets a user with their name",
+      parameters: z.object({
+        name: z.string(),
+      }),
+      execute: ({ name }) => `Hello, ${name}! How can I help you today?`,
+    });
+
+    myAgent = agent({
+      tools: [greetTool],
+      llm: openai({ model: "gpt-4o-mini" }),
+    });
+    
+    return myAgent;
+  } catch (error) {
+    console.error("Failed to initialize agent:", error);
+    throw error;
+  }
+}
+
+export async function POST(request: NextRequest) {
+  try {
+    const { message } = await request.json();
+    
+    if (!message || typeof message !== 'string') {
+      return NextResponse.json(
+        { error: "Message is required and must be a string" },
+        { status: 400 }
+      );
+    }
+    
+    const agent = await initializeAgent();
+    const result = await agent.run(message);
+    
+    return NextResponse.json({ response: result.data });
+  } catch (error) {
+    console.error("Chat error:", error);
+    return NextResponse.json(
+      { error: "Internal server error" },
+      { status: 500 }
+    );
+  }
+}
+```
+
+### Pages Router (Legacy)
+
+```typescript
+// pages/api/chat.ts
+import { agent } from "@llamaindex/workflow";
+import { tool } from "llamaindex";
+import { openai } from "@llamaindex/openai";
+import { z } from "zod";
+import type { NextApiRequest, NextApiResponse } from "next";
+
+let myAgent: any = null;
+
+async function initializeAgent() {
+  if (myAgent) return myAgent;
+  
+  const timeTool = tool({
+    name: "getCurrentTime",
+    description: "Gets the current time",
+    parameters: z.object({}),
+    execute: () => new Date().toISOString(),
+  });
+
+  myAgent = agent({
+    tools: [timeTool],
+    llm: openai({ model: "gpt-4o-mini" }),
+  });
+  
+  return myAgent;
+}
+
+export default async function handler(
+  req: NextApiRequest,
+  res: NextApiResponse
+) {
+  if (req.method !== "POST") {
+    return res.status(405).json({ error: "Method not allowed" });
+  }
+  
+  try {
+    const { message } = req.body;
+    
+    const agent = await initializeAgent();
+    const result = await agent.run(message);
+    
+    res.json({ response: result.data });
+  } catch (error) {
+    console.error("Chat error:", error);
+    res.status(500).json({ error: "Internal server error" });
+  }
+}
+```
+
+## Server Components
+
+Initialize agents in server components:
+
+```typescript
+// app/chat/page.tsx
+import { agent } from "@llamaindex/workflow";
+import { tool } from "llamaindex";
+import { openai } from "@llamaindex/openai";
+import { z } from "zod";
+
+async function initializeAgent() {
+  const helpTool = tool({
+    name: "getHelp",
+    description: "Provides help information",
+    parameters: z.object({
+      topic: z.string().optional(),
+    }),
+    execute: ({ topic }) => {
+      if (topic) {
+        return `Here's help for ${topic}: This is a helpful resource about ${topic}.`;
+      }
+      return "Available topics: general, troubleshooting, api, deployment";
+    },
+  });
+
+  return agent({
+    tools: [helpTool],
+    llm: openai({ model: "gpt-4o-mini" }),
+  });
+}
+
+export default async function ChatPage() {
+  const chatAgent = await initializeAgent();
+  
+  return (
+    <div>
+      <h1>Chat Interface</h1>
+      <p>Agent initialized and ready to help!</p>
+      {/* Your chat UI components */}
+    </div>
+  );
+}
+```
+
+## Edge Runtime
+
+The Edge Runtime has limited Node.js API access:
+
+```typescript
+// app/api/chat-edge/route.ts
+import { NextRequest, NextResponse } from "next/server";
+
+export const runtime = "edge";
+
+export async function POST(request: NextRequest) {
+  const { setEnvs } = await import("@llamaindex/env");
+  setEnvs(process.env);
+  
+  try {
+    const { message } = await request.json();
+    
+    const { agent } = await import("@llamaindex/workflow");
+    const { tool } = await import("llamaindex");
+    const { openai } = await import("@llamaindex/openai");
+    const { z } = await import("zod");
+
+    const timeTool = tool({
+      name: "time",
+      description: "Gets current time",
+      parameters: z.object({}),
+      execute: () => new Date().toISOString(),
+    });
+
+    const myAgent = agent({
+      tools: [timeTool],
+      llm: openai({ model: "gpt-4o-mini" }),
+    });
+
+    const result = await myAgent.run(message);
+    return NextResponse.json({ response: result.data });
+  } catch (error) {
+    return NextResponse.json({ error: error.message }, { status: 500 });
+  }
+}
+```
+
+## Streaming Responses
+
+Implement streaming for better user experience:
+
+```typescript
+// app/api/chat-stream/route.ts
+import { agent } from "@llamaindex/workflow";
+import { tool } from "llamaindex";
+import { openai } from "@llamaindex/openai";
+import { agentStreamEvent } from "@llamaindex/workflow";
+import { NextRequest } from "next/server";
+import { z } from "zod";
+
+// Initialize agent once (consider using a singleton pattern)
+let myAgent: any = null;
+
+async function initializeAgent() {
+  if (myAgent) return myAgent;
+  
+  try {
+    const greetTool = tool({
+      name: "greet",
+      description: "Greets a user with their name",
+      parameters: z.object({
+        name: z.string(),
+      }),
+      execute: ({ name }) => `Hello, ${name}! How can I help you today?`,
+    });
+
+    myAgent = agent({
+      tools: [greetTool],
+      llm: openai({ model: "gpt-4o-mini" }),
+    });
+    
+    return myAgent;
+  } catch (error) {
+    console.error("Failed to initialize agent:", error);
+    throw error;
+  }
+}
+
+export async function POST(request: NextRequest) {
+  const { message } = await request.json();
+  
+  const stream = new ReadableStream({
+    async start(controller) {
+      try {
+        const agent = await initializeAgent();
+        const events = agent.runStream(message);
+        
+        for await (const event of events) {
+          if (agentStreamEvent.include(event)) {
+            controller.enqueue(new TextEncoder().encode(event.data.delta));
+          }
+        }
+        
+        controller.close();
+      } catch (error) {
+        controller.error(error);
+      }
+    },
+  });
+  
+  return new Response(stream, {
+    headers: {
+      "Content-Type": "text/plain",
+      "Transfer-Encoding": "chunked",
+    },
+  });
+}
+```
+
+## Client-side Integration
+
+### React Hook for API Calls
+
+```typescript
+// hooks/useAgentChat.ts
+import { useState } from "react";
+
+export function useAgentChat() {
+  const [loading, setLoading] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+  const [response, setResponse] = useState<string | null>(null);
+  
+  const chat = async (message: string) => {
+    setLoading(true);
+    setError(null);
+    
+    try {
+      const res = await fetch("/api/chat", {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({ message }),
+      });
+      
+      if (!res.ok) {
+        throw new Error(`HTTP error! status: ${res.status}`);
+      }
+      
+      const data = await res.json();
+      setResponse(data.response);
+    } catch (err) {
+      setError(err instanceof Error ? err.message : "An error occurred");
+    } finally {
+      setLoading(false);
+    }
+  };
+  
+  return { chat, loading, error, response };
+}
+```
+
+### Chat Component
+
+```typescript
+// components/ChatInterface.tsx
+"use client";
+
+import { useState } from "react";
+import { useAgentChat } from "@/hooks/useAgentChat";
+
+export default function ChatInterface() {
+  const [message, setMessage] = useState("");
+  const { chat, loading, error, response } = useAgentChat();
+  
+  const handleSubmit = async (e: React.FormEvent) => {
+    e.preventDefault();
+    if (!message.trim()) return;
+    
+    await chat(message);
+    setMessage("");
+  };
+  
+  return (
+    <div className="max-w-2xl mx-auto p-4">
+      <form onSubmit={handleSubmit} className="mb-4">
+        <input
+          type="text"
+          value={message}
+          onChange={(e) => setMessage(e.target.value)}
+          placeholder="Send a message..."
+          className="w-full p-2 border rounded"
+          disabled={loading}
+        />
+        <button
+          type="submit"
+          disabled={loading || !message.trim()}
+          className="mt-2 px-4 py-2 bg-blue-500 text-white rounded disabled:opacity-50"
+        >
+          {loading ? "Thinking..." : "Send"}
+        </button>
+      </form>
+      
+      {error && (
+        <div className="p-3 mb-4 bg-red-100 border border-red-400 text-red-700 rounded">
+          Error: {error}
+        </div>
+      )}
+      
+      {response && (
+        <div className="p-3 bg-gray-100 border rounded">
+          <strong>Agent:</strong>
+          <p>{response}</p>
+        </div>
+      )}
+    </div>
+  );
+}
+```
+
+## Next Steps
+
+- Learn about [serverless deployment](/docs/llamaindex/getting_started/installation/serverless)
+- Explore [server APIs](/docs/llamaindex/getting_started/installation/server-apis)
+- Check [troubleshooting guide](/docs/llamaindex/getting_started/installation/troubleshooting) for common issues 
@@ -1,40 +0,0 @@
---
-title: With Node.js/Bun/Deno
-description: In this guide, you'll learn how to use LlamaIndex with Node.js, Bun, and Deno.
---
-
-## Adding environment variables
-
-By default, LlamaIndex uses OpenAI provider, which requires an API key. You can set the `OPENAI_API_KEY` environment variable to authenticate with OpenAI.
-
-```shell
-export OPENAI_API_KEY=your-api-key
-```
-
-Or you can use a `.env` file:
-
-```shell
-echo "OPENAI_API_KEY=your-api-key" > .env
-node --env-file .env your-script.js
-```
-
-<Callout type="warn">Do not commit the api key to git repository.</Callout>
-
-For more information, see the [How to read environment variables from Node.js](https://nodejs.org/en/learn/command-line/how-to-read-environment-variables-from-nodejs).
-
-## Performance Optimization
-
-By the default, we are using `js-tiktoken` for tokenization. You can install `gpt-tokenizer` which is then automatically used by LlamaIndex to get a 60x speedup for tokenization:
-
-```package-install
-npm i gpt-tokenizer
-```
-
-**Note**: This only works for Node.js
-
-## TypeScript support
-
-<Card
-	title="Getting Started with LlamaIndex.TS in TypeScript"
-	href="/docs/llamaindex/getting_started/installation/typescript"
-/>
@@ -0,0 +1,211 @@
+---
+title: Server APIs & Backends
+description: Deploy LlamaIndex.TS in server environments like Express, Fastify, and standalone Node.js applications.
+---
+
+This guide covers adding LlamaIndex.TS agents to traditional server environments where you have full Node.js runtime access.
+
+## Supported Runtimes
+
+LlamaIndex.TS works seamlessly with:
+
+- **Node.js** (v18+)
+- **Bun** (v1.0+)
+- **Deno** (v1.30+)
+
+## Common Server Frameworks
+
+### Express.js
+
+```typescript
+import express from 'express';
+import { agent } from '@llamaindex/workflow';
+import { tool } from 'llamaindex';
+import { openai } from '@llamaindex/openai';
+import { z } from 'zod';
+
+const app = express();
+app.use(express.json());
+
+// Initialize agent once at startup
+let myAgent: any;
+
+async function initializeAgent() {
+  // Create tools for the agent
+  const sumTool = tool({
+    name: "sum",
+    description: "Adds two numbers",
+    parameters: z.object({
+      a: z.number(),
+      b: z.number(),
+    }),
+    execute: ({ a, b }) => a + b,
+  });
+
+  const multiplyTool = tool({
+    name: "multiply",
+    description: "Multiplies two numbers",
+    parameters: z.object({
+      a: z.number(),
+      b: z.number(),
+    }),
+    execute: ({ a, b }) => a * b,
+  });
+
+  // Create the agent
+  myAgent = agent({
+    tools: [sumTool, multiplyTool],
+    llm: openai({ model: "gpt-4o-mini" }),
+  });
+}
+
+app.post('/api/chat', async (req, res) => {
+  try {
+    const { message } = req.body;
+    const result = await myAgent.run(message);
+    res.json({ response: result.data });
+  } catch (error) {
+    res.status(500).json({ error: 'Chat failed' });
+  }
+});
+
+// Initialize and start server
+initializeAgent().then(() => {
+  app.listen(3000, () => {
+    console.log('Server running on port 3000');
+  });
+});
+```
+
+### Fastify
+
+```typescript
+import Fastify from 'fastify';
+import { agent } from '@llamaindex/workflow';
+import { tool } from 'llamaindex';
+import { openai } from '@llamaindex/openai';
+import { z } from 'zod';
+
+const fastify = Fastify();
+let myAgent: any;
+
+async function initializeAgent() {
+  const sumTool = tool({
+    name: "sum",
+    description: "Adds two numbers",
+    parameters: z.object({
+      a: z.number(),
+      b: z.number(),
+    }),
+    execute: ({ a, b }) => a + b,
+  });
+
+  myAgent = agent({
+    tools: [sumTool],
+    llm: openai({ model: "gpt-4o-mini" }),
+  });
+}
+
+fastify.post('/api/chat', async (request, reply) => {
+  try {
+    const { message } = request.body as { message: string };
+    const result = await myAgent.run(message);
+    return { response: result.data };
+  } catch (error) {
+    reply.status(500).send({ error: 'Chat failed' });
+  }
+});
+
+const start = async () => {
+  await initializeAgent();
+  await fastify.listen({ port: 3000 });
+  console.log('Server running on port 3000');
+};
+
+start();
+```
+
+### Hono
+
+```typescript
+import { Hono } from "hono";
+import { agent } from "@llamaindex/workflow";
+import { tool } from "llamaindex";
+import { openai } from "@llamaindex/openai";
+import { z } from "zod";
+
+type Bindings = {
+  OPENAI_API_KEY: string;
+};
+
+const app = new Hono<{ Bindings: Bindings }>();
+
+app.post("/api/chat", async (c) => {
+  const { setEnvs } = await import("@llamaindex/env");
+  setEnvs(c.env);
+  
+  const { message } = await c.req.json();
+  
+  const greetTool = tool({
+    name: "greet",
+    description: "Greets a user",
+    parameters: z.object({
+      name: z.string(),
+    }),
+    execute: ({ name }) => `Hello, ${name}!`,
+  });
+
+  const myAgent = agent({
+    tools: [greetTool],
+    llm: openai({ model: "gpt-4o-mini" }),
+  });
+  
+  try {
+    const result = await myAgent.run(message);
+    return c.json({ response: result.data });
+  } catch (error) {
+    return c.json({ error: error.message }, 500);
+  }
+});
+
+export default app;
+```
+
+## Streaming Responses
+
+For real-time agent responses:
+
+```typescript
+import { agentStreamEvent } from "@llamaindex/workflow";
+
+app.post('/api/chat-stream', async (req, res) => {
+  const { message } = req.body;
+  
+  res.writeHead(200, {
+    'Content-Type': 'text/plain',
+    'Transfer-Encoding': 'chunked',
+  });
+  
+  try {
+    const events = myAgent.runStream(message);
+    
+    for await (const event of events) {
+      if (agentStreamEvent.include(event)) {
+        res.write(event.data.delta);
+      }
+    }
+    
+    res.end();
+  } catch (error) {
+    res.write('Error: ' + error.message);
+    res.end();
+  }
+});
+```
+
+
+## Next Steps
+
+- Learn about [serverless deployment](/docs/llamaindex/getting_started/installation/serverless)
+- Explore [Next.js integration](/docs/llamaindex/getting_started/installation/nextjs)
+- Check [troubleshooting guide](/docs/llamaindex/getting_started/installation/troubleshooting) for common issues 
@@ -0,0 +1,240 @@
+---
+title: Serverless Functions
+description: Deploy LlamaIndex.TS in serverless environments like Vercel, Netlify, AWS Lambda, and Cloudflare Workers.
+---
+
+This guide covers adding LlamaIndex.TS agents to serverless environments where you have execution time and memory constraints.
+
+## Cloudflare Workers
+
+```typescript
+export default {
+  async fetch(request: Request, env: Env): Promise<Response> {
+    const { setEnvs } = await import("@llamaindex/env");
+    setEnvs(env);
+    
+    const { agent } = await import("@llamaindex/workflow");
+    const { openai } = await import("@llamaindex/openai");
+    const { tool } = await import("llamaindex");
+    const { z } = await import("zod");
+
+    const timeTool = tool({
+      name: "getCurrentTime",
+      description: "Gets the current time",
+      parameters: z.object({}),
+      execute: () => new Date().toISOString(),
+    });
+
+    const myAgent = agent({
+      tools: [timeTool],
+      llm: openai({ model: "gpt-4o-mini" }),
+    });
+
+    try {
+      const { message } = await request.json();
+      const result = await myAgent.run(message);
+      
+      return new Response(JSON.stringify({ response: result.data }), {
+        headers: { "Content-Type": "application/json" },
+      });
+    } catch (error) {
+      return new Response(JSON.stringify({ error: error.message }), {
+        status: 500,
+        headers: { "Content-Type": "application/json" },
+      });
+    }
+  },
+};
+```
+
+
+
+## Vercel Functions
+
+### Node.js Runtime
+
+```typescript
+// pages/api/chat.ts or app/api/chat/route.ts
+import { agent } from "@llamaindex/workflow";
+import { tool } from "llamaindex";
+import { openai } from "@llamaindex/openai";
+import { z } from "zod";
+
+export default async function handler(req, res) {
+  if (req.method !== 'POST') {
+    return res.status(405).json({ error: 'Method not allowed' });
+  }
+  
+  const { message } = req.body;
+  
+  const weatherTool = tool({
+    name: "getWeather",
+    description: "Get weather information",
+    parameters: z.object({
+      city: z.string(),
+    }),
+    execute: ({ city }) => `Weather in ${city}: 72°F, sunny`,
+  });
+
+  const myAgent = agent({
+    tools: [weatherTool],
+    llm: openai({ model: "gpt-4o-mini" }),
+  });
+  
+  try {
+    const result = await myAgent.run(message);
+    res.json({ response: result.data });
+  } catch (error) {
+    res.status(500).json({ error: error.message });
+  }
+}
+```
+
+### Edge Runtime
+
+```typescript
+// app/api/chat/route.ts
+import { NextRequest, NextResponse } from "next/server";
+
+export const runtime = "edge";
+
+export async function POST(request: NextRequest) {
+  const { setEnvs } = await import("@llamaindex/env");
+  setEnvs(process.env);
+  
+  const { message } = await request.json();
+  
+  try {
+    // Use simpler tools for edge runtime
+    const { agent } = await import("@llamaindex/workflow");
+    const { tool } = await import("llamaindex");
+    const { openai } = await import("@llamaindex/openai");
+    const { z } = await import("zod");
+
+    const timeTool = tool({
+      name: "time",
+      description: "Gets current time",
+      parameters: z.object({}),
+      execute: () => new Date().toISOString(),
+    });
+
+    const myAgent = agent({
+      tools: [timeTool],
+      llm: openai({ model: "gpt-4o-mini" }),
+    });
+
+    const result = await myAgent.run(message);
+    return NextResponse.json({ response: result.data });
+  } catch (error) {
+    return NextResponse.json({ error: error.message }, { status: 500 });
+  }
+}
+```
+
+## AWS Lambda
+
+```typescript
+import { APIGatewayProxyHandler } from "aws-lambda";
+import { agent } from "@llamaindex/workflow";
+import { tool } from "llamaindex";
+import { openai } from "@llamaindex/openai";
+import { z } from "zod";
+
+export const handler: APIGatewayProxyHandler = async (event, context) => {
+  const { message } = JSON.parse(event.body || "{}");
+  
+  const calculatorTool = tool({
+    name: "calculate",
+    description: "Performs basic math",
+    parameters: z.object({
+      expression: z.string(),
+    }),
+    execute: ({ expression }) => {
+      // Simple calculator implementation
+      try {
+        return `Result: ${eval(expression)}`;
+      } catch {
+        return "Invalid expression";
+      }
+    },
+  });
+
+  const myAgent = agent({
+    tools: [calculatorTool],
+    llm: openai({ model: "gpt-4o-mini" }),
+  });
+  
+  try {
+    const result = await myAgent.run(message);
+    
+    return {
+      statusCode: 200,
+      headers: {
+        "Content-Type": "application/json",
+        "Access-Control-Allow-Origin": "*",
+      },
+      body: JSON.stringify({ response: result.data }),
+    };
+  } catch (error) {
+    return {
+      statusCode: 500,
+      body: JSON.stringify({ error: error.message }),
+    };
+  }
+};
+```
+
+## Netlify Functions
+
+```typescript
+// netlify/functions/chat.ts
+import { Handler } from "@netlify/functions";
+import { agent } from "@llamaindex/workflow";
+import { tool } from "llamaindex";
+import { openai } from "@llamaindex/openai";
+import { z } from "zod";
+
+export const handler: Handler = async (event, context) => {
+  if (event.httpMethod !== "POST") {
+    return { statusCode: 405, body: "Method Not Allowed" };
+  }
+  
+  const { message } = JSON.parse(event.body || "{}");
+  
+  const helpTool = tool({
+    name: "help",
+    description: "Provides help information",
+    parameters: z.object({
+      topic: z.string().optional(),
+    }),
+    execute: ({ topic }) => {
+      return topic ? `Help for ${topic}` : "Available help topics";
+    },
+  });
+
+  const myAgent = agent({
+    tools: [helpTool],
+    llm: openai({ model: "gpt-4o-mini" }),
+  });
+  
+  try {
+    const result = await myAgent.run(message);
+    
+    return {
+      statusCode: 200,
+      body: JSON.stringify({ response: result.data }),
+    };
+  } catch (error) {
+    return {
+      statusCode: 500,
+      body: JSON.stringify({ error: error.message }),
+    };
+  }
+};
+```
+
+## Next Steps
+
+- Learn about [Next.js integration](/docs/llamaindex/getting_started/installation/nextjs)
+- Explore [server deployment](/docs/llamaindex/getting_started/installation/server-apis)
+- Check [troubleshooting guide](/docs/llamaindex/getting_started/installation/troubleshooting) for common issues 
@@ -0,0 +1,501 @@
+---
+title: Troubleshooting
+description: Common issues and solutions when installing and deploying LlamaIndex.TS applications.
+---
+
+This guide addresses common issues you might encounter when installing and deploying LlamaIndex.TS applications across different environments.
+
+## Installation Issues
+
+### Module Resolution Errors
+
+**Problem:** Import errors or module not found errors
+
+**Solution:** Ensure your `tsconfig.json` is properly configured:
+
+```json5
+{
+  "compilerOptions": {
+    "moduleResolution": "bundler", // or "nodenext" | "node16" | "node"
+    "lib": ["DOM.AsyncIterable"],
+    "target": "es2020",
+    "module": "esnext"
+  }
+}
+```
+
+**Alternative solution:** Try different module resolution strategies:
+
+```bash
+# Clear node_modules and reinstall
+rm -rf node_modules package-lock.json
+npm install
+
+# Or try with different package manager
+pnpm install
+# or
+yarn install
+```
+
+### TypeScript Errors
+
+**Problem:** TypeScript compilation errors with LlamaIndex imports
+
+**Solution:** Ensure you have the correct TypeScript configuration:
+
+```json5
+{
+  "compilerOptions": {
+    "strict": true,
+    "skipLibCheck": true, // Skip type checking of node_modules
+    "allowSyntheticDefaultImports": true,
+    "esModuleInterop": true
+  }
+}
+```
+
+### Package Compatibility Issues
+
+**Problem:** Some packages don't work in certain environments
+
+**Common incompatibilities:**
+- `@llamaindex/readers` - May not work in serverless environments
+- `@llamaindex/huggingface` - Limited browser/edge compatibility
+- File system readers - Don't work in browser/edge environments
+
+**Solution:** Use environment-specific alternatives:
+
+```typescript
+// Instead of file system readers in serverless
+// Use remote data sources
+async function loadDocumentsFromAPI() {
+  const response = await fetch('https://api.example.com/documents');
+  const data = await response.json();
+  return data.map(doc => new Document(doc.content));
+}
+```
+
+## Runtime Issues
+
+### Memory Errors
+
+**Problem:** Out of memory errors during index creation or querying
+
+**Solution:** Optimize memory usage:
+
+```typescript
+// Batch process large document sets
+async function batchProcessDocuments(documents: Document[], batchSize = 10) {
+  const results = [];
+  
+  for (let i = 0; i < documents.length; i += batchSize) {
+    const batch = documents.slice(i, i + batchSize);
+    const batchIndex = await VectorStoreIndex.fromDocuments(batch);
+    results.push(batchIndex);
+    
+    // Optional: Add delay between batches
+    await new Promise(resolve => setTimeout(resolve, 100));
+  }
+  
+  return results;
+}
+```
+
+**For serverless environments:**
+
+```typescript
+// Use external vector stores instead of in-memory
+// TODO: Example with Pinecone, Weaviate, etc.
+// const vectorStore = new PineconeVectorStore(/* config */);
+// const index = await VectorStoreIndex.fromVectorStore(vectorStore);
+```
+
+### API Rate Limiting
+
+**Problem:** Rate limiting errors from LLM providers
+
+**Solution:** Implement retry logic with exponential backoff:
+
+```typescript
+async function queryWithRetry(queryEngine: any, question: string, maxRetries = 3) {
+  for (let i = 0; i < maxRetries; i++) {
+    try {
+      return await queryEngine.query(question);
+    } catch (error) {
+      if (error.message.includes('rate limit') && i < maxRetries - 1) {
+        const delay = Math.pow(2, i) * 1000; // Exponential backoff
+        await new Promise(resolve => setTimeout(resolve, delay));
+        continue;
+      }
+      throw error;
+    }
+  }
+}
+```
+
+### Tokenization Performance
+
+**Problem:** Slow tokenization affecting performance
+
+**Solution:** Install faster tokenizer (Node.js only):
+
+```bash
+npm install gpt-tokenizer
+```
+
+LlamaIndex will automatically use this for 60x faster tokenization.
+
+## Bundling Issues
+
+### Bundle Size Too Large
+
+**Problem:** Large bundle sizes affecting performance
+
+**Solution:** Use dynamic imports and code splitting:
+
+```typescript
+// Lazy load LlamaIndex components
+const initializeLlamaIndex = async () => {
+  const { VectorStoreIndex, SimpleDirectoryReader } = await import("llamaindex");
+  return { VectorStoreIndex, SimpleDirectoryReader };
+};
+
+// In your API route
+export async function POST(request: NextRequest) {
+  const { VectorStoreIndex, SimpleDirectoryReader } = await initializeLlamaIndex();
+  // Use the imported modules
+}
+```
+
+### Webpack/Vite Bundling Issues
+
+**Problem:** Bundler compatibility issues
+
+**Solution for Next.js:**
+
+```javascript
+// next.config.mjs
+import withLlamaIndex from "llamaindex/next";
+
+const nextConfig = {
+  webpack: (config, { isServer }) => {
+    // Custom webpack configuration if needed
+    if (!isServer) {
+      config.resolve.fallback = {
+        ...config.resolve.fallback,
+        fs: false,
+        net: false,
+        tls: false,
+      };
+    }
+    return config;
+  },
+};
+
+export default withLlamaIndex(nextConfig);
+```
+
+**Solution for Vite:**
+
+```typescript
+// vite.config.ts
+import { defineConfig } from 'vite';
+
+export default defineConfig({
+  define: {
+    global: 'globalThis',
+  },
+  resolve: {
+    alias: {
+      // Add aliases for problematic modules
+    },
+  },
+  optimizeDeps: {
+    include: ['llamaindex'],
+  },
+});
+```
+
+## Environment-Specific Issues
+
+### Node.js Version Compatibility
+
+**Problem:** Node.js version compatibility issues
+
+**Solution:** Use supported Node.js versions:
+
+```json
+{
+  "engines": {
+    "node": ">=18.0.0"
+  }
+}
+```
+
+**Check your Node.js version:**
+
+```bash
+node --version
+```
+
+### Cloudflare Workers Issues
+
+**Problem:** Module not available in Cloudflare Workers
+
+**Solution:** Use `@llamaindex/env` for environment compatibility:
+
+```typescript
+export default {
+  async fetch(request: Request, env: Env): Promise<Response> {
+    const { setEnvs } = await import("@llamaindex/env");
+    setEnvs(env);
+    
+    // Your LlamaIndex code here
+  },
+};
+```
+
+### Vercel Edge Runtime Issues
+
+**Problem:** Limited Node.js API access in Edge Runtime
+
+**Solution:** Use standard runtime or adapt code:
+
+```typescript
+// Force standard runtime
+export const runtime = "nodejs";
+
+// Or adapt for edge
+export const runtime = "edge";
+
+export async function POST(request: NextRequest) {
+  // Use edge-compatible code only
+  const { setEnvs } = await import("@llamaindex/env");
+  setEnvs(process.env);
+  
+  // Avoid file system operations
+  // Use remote data sources
+}
+```
+
+## Performance Issues
+
+### Slow Query Responses
+
+**Problem:** Slow query performance
+
+**Solution:** Implement caching and optimization:
+
+```typescript
+import { LRUCache } from 'lru-cache';
+
+const queryCache = new LRUCache<string, string>({
+  max: 100,
+  ttl: 1000 * 60 * 10, // 10 minutes
+});
+
+export async function optimizedQuery(question: string, queryEngine: any) {
+  // Check cache first
+  const cached = queryCache.get(question);
+  if (cached) return cached;
+  
+  // Query and cache result
+  const result = await queryEngine.query(question);
+  queryCache.set(question, result);
+  
+  return result;
+}
+```
+
+### Cold Start Issues
+
+**Problem:** Slow cold starts in serverless environments
+
+**Solution:** Pre-warm your functions:
+
+```typescript
+// Pre-initialize outside handler
+let cachedQueryEngine: any = null;
+
+export async function handler(event: any) {
+  if (!cachedQueryEngine) {
+    cachedQueryEngine = await initializeQueryEngine();
+  }
+  
+  // Use cached engine
+  return await cachedQueryEngine.query(question);
+}
+```
+
+## Environment Variable Issues
+
+### Missing API Keys
+
+**Problem:** API key not found or invalid
+
+**Solution:** Verify environment variable setup:
+
+```typescript
+// Check if API key is available
+if (!process.env.OPENAI_API_KEY) {
+  throw new Error('OPENAI_API_KEY environment variable is required');
+}
+
+// For debugging (remove in production)
+console.log('API Key present:', !!process.env.OPENAI_API_KEY);
+```
+
+### Environment Variable Loading
+
+**Problem:** Environment variables not loading correctly
+
+**Solution:** Use proper loading mechanisms:
+
+```typescript
+// For Node.js
+import 'dotenv/config';
+
+// For Next.js - use .env.local
+// Variables are automatically loaded
+
+// For Cloudflare Workers
+export default {
+  async fetch(request: Request, env: Env): Promise<Response> {
+    // Use env parameter, not process.env
+    const apiKey = env.OPENAI_API_KEY;
+    // ...
+  },
+};
+```
+
+## Common Error Messages
+
+### "Cannot find module 'llamaindex'"
+
+**Cause:** Package not installed or module resolution issue
+
+**Solution:**
+```bash
+npm install llamaindex
+```
+
+### "Module not found: Can't resolve 'fs'"
+
+**Cause:** File system modules used in browser/edge environment
+
+**Solution:**
+```typescript
+// Use dynamic imports with fallbacks
+const loadDocuments = async () => {
+  if (typeof window !== 'undefined') {
+    // Browser environment - use alternative
+    return await loadDocumentsFromAPI();
+  } else {
+    // Node.js environment - use file system
+    const { SimpleDirectoryReader } = await import('llamaindex');
+    return await new SimpleDirectoryReader('data').loadData();
+  }
+};
+```
+
+### "ReferenceError: global is not defined"
+
+**Cause:** Global polyfill missing in browser environments
+
+**Solution:**
+```typescript
+// Add to your app entry point
+if (typeof global === 'undefined') {
+  global = globalThis;
+}
+```
+
+### "Cannot read properties of undefined (reading 'query')"
+
+**Cause:** Query engine not properly initialized
+
+**Solution:**
+```typescript
+// Always check initialization
+if (!queryEngine) {
+  throw new Error('Query engine not initialized');
+}
+
+// Or use optional chaining
+const response = await queryEngine?.query(question);
+```
+
+## Debugging Tips
+
+### Enable Debug Logging
+
+```typescript
+// Enable debug logging
+process.env.DEBUG = "llamaindex:*";
+
+// Or specific modules
+process.env.DEBUG = "llamaindex:vector-store";
+```
+
+### Check Package Versions
+
+```bash
+npm list llamaindex
+npm list @llamaindex/openai
+```
+
+### Test in Isolation
+
+```typescript
+// Create minimal test case
+import { VectorStoreIndex } from 'llamaindex';
+
+async function testBasic() {
+  try {
+    console.log('Testing basic import...');
+    const index = new VectorStoreIndex();
+    console.log('Success!');
+  } catch (error) {
+    console.error('Error:', error);
+  }
+}
+
+testBasic();
+```
+
+## Getting Help
+
+### Before Asking for Help
+
+1. **Check this troubleshooting guide**
+2. **Search existing GitHub issues**
+3. **Try minimal reproduction**
+4. **Check your environment configuration**
+
+### When Reporting Issues
+
+Include:
+- Node.js version (`node --version`)
+- Package versions (`npm list llamaindex`)
+- Environment (Node.js, Cloudflare Workers, Vercel, etc.)
+- Minimal code reproduction
+- Full error message and stack trace
+
+### Useful Resources
+
+- [GitHub Issues](https://github.com/run-llama/LlamaIndexTS/issues)
+- [Discord Community](https://discord.gg/dGcwcsnxhU)
+- [Documentation](https://docs.llamaindex.ai/)
+
+## Next Steps
+
+If you're still experiencing issues:
+
+1. **Check specific deployment guides:**
+   - [Server APIs](/docs/llamaindex/getting_started/installation/server-apis)
+   - [Serverless Functions](/docs/llamaindex/getting_started/installation/serverless)
+   - [Next.js Applications](/docs/llamaindex/getting_started/installation/nextjs)
+
+2. **Open an issue** on GitHub with a minimal reproduction
+
+3. **Join our Discord** for community support 
@@ -1,99 +0,0 @@
---
-title: With TypeScript
-description: In this guide, you'll learn how to use LlamaIndex with TypeScript
---
-
-LlamaIndex.TS is written in TypeScript and designed to be used in TypeScript projects.
-
-We put a lot of work on strong typing to make sure you have a great typing experience with code completion such as:
-
-```ts twoslash
-import { PromptTemplate } from 'llamaindex'
-const promptTemplate = new PromptTemplate({
-  template: `Context information from multiple sources is below.
---------------------
-{context}
---------------------
-Given the information from multiple sources and not prior knowledge.
-Answer the query in the style of a Shakespeare play"
-Query: {query}
-Answer:`,
-	templateVars: ["context", "query"],
-});
-// @noErrors
-promptTemplate.format({
-	c
-//^|
-})
-```
-
-## Enable TypeScript
-
-Make sure to set [moduleResolution](https://www.typescriptlang.org/docs/handbook/modules/theory.html#module-resolution) in your `tsconfig.json` file:
-
-```json5
-{
-  compilerOptions: {
-    // ⬇️ add this line to your tsconfig.json
-    moduleResolution: "bundler", // or "nodenext" | "node16" | "node"
-  },
-}
-```
-
-We recommend using `bundler` or `nodenext`, but due to popularity of `node`, we still added support for it.
-
-## 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"],
-  },
-}
-```
-
-```typescript
-import { tool } from 'llamaindex'
-import { agent } from "@llamaindex/workflow";
-import { openai } from "@llamaindex/openai";
-
-Settings.llm = openai({
-  model: "gpt-4o-mini",
-});
-
-const addTool = tool({
-  name: "add", 
-  description: "Adds two numbers",
-  parameters: z.object({x: z.number(), y: z.number()}),
-  execute: ({ x, y }) => x + y,
-});
-
-const myAgent = agent({
-  tools: [addTool],
-});
-
-// Chat with the agent
-const context = myAgent.run("Hello, how are you?");
-
-for await (const event of context) {
-  if (event instanceof AgentStream) {
-    for (const chunk of event.data.delta) {
-      process.stdout.write(chunk); // stream response
-    }
-  } else {
-    console.log(event); // other events
-  }
-}
-
-```
-
-## Run TypeScript Script in Node.js
-
-We recommend to use [tsx](https://www.npmjs.com/package/tsx) to run TypeScript script in Node.js.
-
-```shell
-node --import tsx ./my-script.ts
-```
@@ -1,23 +0,0 @@
---
-title: With Vite
-description: In this guide, you'll learn how to use LlamaIndex with Vite
---
-
-Before you start, make sure you have try LlamaIndex.TS in Node.js to make sure you understand the basics.
-
-<Card
-  title="Getting Started with LlamaIndex.TS in Node.js"
-  href="/docs/llamaindex/getting_started/installation/node"
-/>
-
-Also, make sure you have a basic understanding of [Vite](https://vitejs.dev/).
-
-## Why mention Vite?
-
-Vite.js is widely used in building many web applications, like React.js, even for some native app like [Electron](https://www.electronjs.org/).
-
-However, it's not a ready-to-use solution for a Node.js-like application using Vite, as Vite is designed for web applications(run in browser).
-
-There's some plugin/framework based on Vite, like [Waku.gg](https://github.com/dai-shi/waku), or [Electron Vite](https://electron-vite.org/)
-
-For now, we have no clear solution for bundling LlamaIndex.TS with Vite, if you have any idea/solution, please let us know.
@@ -1,21 +1,118 @@
 ---
-title: What is LlamaIndex.TS
-description: LlamaIndex is the leading data framework for building LLM applications
+title: Welcome to LlamaIndex.TS
+description: LlamaIndex.TS is the leading framework for utilizing context engineering to build LLM applications in JavaScript and TypeScript.
 ---

-LlamaIndex is a framework for building context-augmented generative AI applications with LLMs including agents and workflows.
+LlamaIndex.TS is a **framework for utilizing context engineering to build generative AI applications** with large language models. From rapid-prototyping RAG chatbots to deploying multi-agent workflows in production, LlamaIndex gives you everything you need — all in idiomatic TypeScript.

-The TypeScript implementation is designed for JavaScript server side applications using <SiNodedotjs className="inline" color="#5FA04E" /> Node.js, <SiDeno className="inline" color="#70FFAF" /> Deno, <SiBun className="inline" /> Bun, <SiCloudflareworkers className="inline" color="#F38020" /> Cloudflare Workers, and more.
+Built for modern JavaScript runtimes like <SiNodedotjs className="inline" color="#5FA04E" /> **Node.js**, <SiDeno className="inline" color="#70FFAF" /> **Deno**, <SiBun className="inline" /> **Bun**, <SiCloudflareworkers className="inline" color="#F38020" /> **Cloudflare Workers**, and more.

-LlamaIndex.TS provides tools for beginners, advanced users, and everyone in between.
+<div className="grid grid-cols-1 gap-4 sm:grid-cols-2 lg:grid-cols-3 my-6">
+  <a href="#introduction" className="block rounded-lg border border-gray-600/40 p-4 hover:border-gray-400 hover:bg-gray-700/20 no-underline">
+    <h3 className="mb-1 text-lg font-semibold underline">Introduction</h3>
+    <p className="text-sm text-gray-400 no-underline">Context engineering, agents &amp; workflows — what do they mean?</p>
+  </a>

-Try it out with a starter example using StackBlitz:
+  <a href="#use-cases" className="block rounded-lg border border-gray-600/40 p-4 hover:border-gray-400 hover:bg-gray-700/20 no-underline">
+    <h3 className="mb-1 text-lg font-semibold underline">Use cases</h3>
+    <p className="text-sm text-gray-400 no-underline">See what you can build with LlamaIndex.TS.</p>
+  </a>
+
+  <a href="#getting-started" className="block rounded-lg border border-gray-600/40 p-4 hover:border-gray-400 hover:bg-gray-700/20 no-underline">
+    <h3 className="mb-1 text-lg font-semibold underline">Getting started</h3>
+    <p className="text-sm text-gray-400 no-underline">Your first app in 5 lines of code.</p>
+  </a>
+
+  <a href="https://docs.cloud.llamaindex.ai/" className="block rounded-lg border border-gray-600/40 p-4 hover:border-gray-400 hover:bg-gray-700/20 no-underline" target="_blank" rel="noopener noreferrer">
+    <h3 className="mb-1 text-lg font-semibold underline">LlamaCloud</h3>
+    <p className="text-sm text-gray-400 no-underline">Managed parsing, extraction &amp; retrieval pipelines.</p>
+  </a>
+
+  <a href="#community" className="block rounded-lg border border-gray-600/40 p-4 hover:border-gray-400 hover:bg-gray-700/20 no-underline">
+    <h3 className="mb-1 text-lg font-semibold underline">Community</h3>
+    <p className="text-sm text-gray-400 no-underline">Join thousands of builders on Discord, Twitter, and more.</p>
+  </a>
+
+  <a href="#related-projects" className="block rounded-lg border border-gray-600/40 p-4 hover:border-gray-400 hover:bg-gray-700/20 no-underline">
+    <h3 className="mb-1 text-lg font-semibold underline">Related projects</h3>
+    <p className="text-sm text-gray-400 no-underline">Connectors, demos &amp; starter kits.</p>
+  </a>
+</div>
+
+## Introduction
+
+### What are agents?
+
+[Agents](/docs/llamaindex/tutorials/agents/1_setup) are LLM-powered assistants that can reason, use external tools, and take actions to accomplish tasks such as research, data extraction, and automation. 
+LlamaIndex.TS provides foundational building blocks for creating and orchestrating these agents.
+
+### What are workflows?
+
+[Workflows](/docs/llamaindex/tutorials/workflows) are multi-step, event-driven processes that combine agents, data connectors, and other tools to solve complex problems. 
+With LlamaIndex.TS you can chain together retrieval, generation, and tool-calling steps and then deploy the entire pipeline as a microservice.
+
+### What is context engineering?
+
+LLMs come pre-trained on vast public corpora, but not on **your** private or domain-specific data. 
+Context engineering bridges that gap by injecting the right pieces of your data into the LLM prompt at the right time. 
+The most popular example is [Retrieval-Augmented Generation (RAG)](/docs/llamaindex/getting_started/concepts), but the same idea powers agent memory, evaluation, extraction, summarisation, and more.
+
+LlamaIndex.TS gives you:
+
+- **Data connectors** to ingest from APIs, files, SQL, and dozens more sources.
+- **Indexes & retrievers** to store and retrieve your data for LLM consumption.
+- **Agents and Engines** to query and use chat+reasoning interfaces over your data.
+- **Workflows** for fine-grained orchestration of your data and LLM-powered agents.
+- **Observability** integrations so you can iterate with confidence.
+
+You can learn more about these concepts in our [concepts guide](/docs/llamaindex/getting_started/concepts).
+
+## Use cases
+
+Popular scenarios include:
+
+- [LLM-Powered Agents](/docs/llamaindex/tutorials/agents/1_setup)
+- [Indexing and Retrieval](/docs/llamaindex/tutorials/rag)
+- [Extracting Structured Data](/docs/llamaindex/tutorials/structured_data_extraction)
+- [Custom Orchestration with Workflows](/docs/llamaindex/tutorials/workflows)
+
+## Getting started
+
+The fastest way to get started is in StackBlitz below — no local setup required:

 <iframe
  className="w-full h-[440px]"
  aria-label="LlamaIndex.TS Starter"
-  aria-description="This is a starter example for LlamaIndex.TS, it shows the basic usage of the library."
+  aria-description="Interactive starter for LlamaIndex.TS"
  src="https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples?embed=1&file=starter.ts"
 />

-You'll need an OpenAI API key to run this example. You can retrieve it from [OpenAI](https://platform.openai.com/api-keys).
+Want to learn more? We have several tutorials to get you started:
+
+- [Installation + Runtime Guide](/docs/llamaindex/getting_started/installation)
+- [Create your first agent](/docs/llamaindex/tutorials/agents/1_setup)
+- [Learn how to index data and chat with it](/docs/llamaindex/tutorials/rag)
+- [Learn how to write your own workflows and agents](/docs/llamaindex/tutorials/workflows)
+
+---
+
+## LlamaCloud
+
+Need an end-to-end managed pipeline? Check out **[LlamaCloud](https://cloud.llamaindex.ai/)**: best-in-class document parsing (LlamaParse), extraction (LlamaExtract), and indexing services with generous free tiers.
+
+---
+
+## Community
+
+- [Twitter](https://twitter.com/llama_index)
+- [Discord](https://discord.gg/dGcwcsnxhU)
+- [LinkedIn](https://www.linkedin.com/company/llamaindex/)
+
+We 💜 contributors! View our [contributing guide](https://github.com/run-llama/LlamaIndexTS/blob/main/CONTRIBUTING.md) to get started.
+
+## Related projects
+
+- [Python framework GitHub](https://github.com/run-llama/llama_index)
+- [Python docs](https://docs.llamaindex.ai/)
+- [create-llama](https://www.npmjs.com/package/create-llama) — scaffold a new project in seconds!
+- [UI Components](https://ui.llamaindex.ai/) — build chat applications with our Next.js components.
@@ -34,6 +34,7 @@ const jokeAgent = agent({
 // Run the workflow
 const result = await jokeAgent.run("Tell me something funny");
 console.log(result.data.result); // Baby Llama is called cria
+console.log(result.data.message); // { role: 'assistant', content: 'Baby Llama is called cria' }
 ```

 ### Event Streaming
@@ -0,0 +1,164 @@
+---
+title: Low-Level LLM Execution
+---
+
+Sometimes your need more control over LLM interactions than what high-level agents provide. The `llm.exec` method makes it simple for you to make a single LLM call with tools but hides the complexity of executing the tools and generating the tool messages.
+
+## When to Use `llm.exec`
+
+Use `llm.exec` when you need to:
+- Build custom agent logic in [workflow](/docs/llamaindex/modules/agents/workflows) steps
+- Have precise control over message handling and tool execution
+
+## Basic Usage
+
+The `llm.exec` method takes messages and tools as parameter and executes one LLM call.
+The LLM might either request to call one or more of the tools or generate an assistant message as result.
+For each tool call that is requested, `llm.exec` executes it and generates the two tool call messages (call and result). If no tool call is requested, just the assistant message is returned. 
+
+```ts
+import { openai } from "@llamaindex/openai";
+import { ChatMessage, tool } from "llamaindex";
+import z from "zod";
+
+const llm = openai({ model: "gpt-4.1-mini" });
+const messages = [
+  {
+    content: "What's the weather like in San Francisco?",
+    role: "user",
+  } as ChatMessage,
+];
+
+const { newMessages, toolCalls } = await llm.exec({
+  messages,
+  tools: [
+    tool({
+      name: "get_weather",
+      description: "Get the current weather for a location",
+      parameters: z.object({
+        address: z.string().describe("The address"),
+      }),
+      execute: ({ address }) => {
+        return `It's sunny in ${address}!`;
+      },
+    }),
+  ],
+});
+
+// Add the new messages (including tool calls and responses) to your conversation
+messages.push(...newMessages);
+```
+
+> `newMessages` is an array as each tool call generates two messages: a tool call message and the tool call result message.
+
+## Agent Loop Pattern
+
+A common pattern is to use `llm.exec` in a loop until the LLM stops making tool calls:
+
+```ts
+import { openai } from "@llamaindex/openai";
+import { ChatMessage, tool } from "llamaindex";
+import z from "zod";
+
+async function runAgentLoop() {
+  const llm = openai({ model: "gpt-4.1-mini" });
+  const messages = [
+    {
+      content: "What's the weather like in San Francisco?",
+      role: "user",
+    } as ChatMessage,
+  ];
+
+  let exit = false;
+  do {
+    const { newMessages, toolCalls } = await llm.exec({
+      messages,
+      tools: [
+        tool({
+          name: "get_weather",
+          description: "Get the current weather for a location",
+          parameters: z.object({
+            address: z.string().describe("The address"),
+          }),
+          execute: ({ address }) => {
+            return `It's sunny in ${address}!`;
+          },
+        }),
+      ],
+    });
+    
+    console.log(newMessages);
+    messages.push(...newMessages);
+    
+    // Exit when no more tool calls are made
+    exit = toolCalls.length === 0;
+  } while (!exit);
+}
+```
+
+## Streaming Support
+
+For real-time responses, use the `stream` option to get the assistant's response as streamed tokens:
+
+```ts
+import { openai } from "@llamaindex/openai";
+import { tool } from "llamaindex";
+import z from "zod";
+
+async function streamingAgentLoop() {
+  const llm = openai({ model: "gpt-4o-mini" });
+  const messages = [
+    {
+      content: "What's the weather like in San Francisco?",
+      role: "user",
+    } as ChatMessage,
+  ];
+
+  let exit = false;
+  do {
+    const { stream, newMessages, toolCalls } = await llm.exec({
+      messages,
+      tools: [
+        tool({
+          name: "get_weather",
+          description: "Get the current weather for a location",
+          parameters: z.object({
+            address: z.string().describe("The address"),
+          }),
+          execute: ({ address }) => {
+            return `It's sunny in ${address}!`;
+          },
+        }),
+      ],
+      stream: true,
+    });
+    
+    // Stream the response token by token
+    for await (const chunk of stream) {
+      process.stdout.write(chunk.delta);
+    }
+    
+    messages.push(...newMessages());
+    
+    exit = toolCalls.length === 0;
+  } while (!exit);
+}
+```
+
+> `newMessages` is a function when streaming. The reason is that the result only is available after streaming. Calling it before, will throw an error.
+
+## Return Values
+
+`llm.exec` returns an object with:
+
+- **`newMessages`**: Array of new chat messages including the LLM response and any tool call messages (call or result). This is a function return the array when streaming.
+- **`toolCalls`**: Array of tool calls made by the LLM
+- **`stream`**: Async iterable for streaming responses (only when `stream: true`)
+
+## Best Practices
+
+For using `llm.exec` in an agent loop, take care to:
+
+1. **Maintain message history**: Always add `newMessages` to your conversation history
+2. **Set exit conditions**: Implement proper logic to avoid infinite loops
+
@@ -1,4 +1,10 @@
 {
  "title": "Agents",
-  "pages": ["tool", "agent_workflow", "workflows", "natural_language_workflow"]
+  "pages": [
+    "tool",
+    "agent_workflow",
+    "workflows",
+    "low-level",
+    "natural_language_workflow"
+  ]
 }
@@ -106,34 +106,40 @@ const memory = createMemory({

 Long-term memory is represented as `Memory Block` objects. These objects contain information that are from previous user sessions or from the beginning of the current conversation. When memory is retrieved (by calling `getLLM`), the short-term and long-term memories are merged together within the given `tokenLimit`. 

-Currently, there are two predefined memory blocks:
+Currently, there are three predefined memory blocks:

 - `staticBlock`: A memory block that stores a static piece of information.
 - `factExtractionBlock`: A memory block that extracts facts from the chat history.
+- `vectorBlock`: A memory block that stores and retrieves chat messages from a vector database using semantic similarity search. Messages are stored individually and retrieved based on their relevance to recent conversation context. Here we've passed in the `vectorStore` to use to store and retrieve the chat messages.

 This sounds a bit complicated, but it's actually quite simple. Let's look at an example:

 ```ts
-import { createMemory, factExtractionBlock, staticBlock } from "llamaindex";
+import { createMemory, factExtractionBlock, staticBlock, vectorBlock } from "llamaindex";
+import { QdrantVectorStore } from "@llamaindex/qdrant";
+import { OpenAIEmbedding } from "@llamaindex/openai";

 const memoryBlocks= [
  staticBlock({
-    id: "core_info",
    content: "My name is Logan, and I live in Saskatoon. I work at LlamaIndex.",
  }),
  factExtractionBlock({
-    id: "user-extracted_info",
    priority: 1,
    llm: llm,
    maxFacts: 50,
  }),
+  vectorBlock({
+    vectorStore: new QdrantVectorStore({ url: "http://localhost:6333" }),
+    priority: 2,
+  }),
 ];
 ```

-Here, we've setup two memory blocks:
+Here, we've setup three memory blocks:

- `core_info`: A static memory block that stores some core information about the user. This information will always be inserted into the memory. The type used is `MessageContent` to support multi-modal content.
- `extracted_info`: An extracted memory block that will extract information from the chat history. Here we've passed in the `llm` to use to extract facts from the chat history, and set the `maxFacts` to 50. If the number of extracted facts exceeds this limit, the `maxFacts` will be automatically summarized and reduced to leave room for new information.
+- `staticBlock`: A static memory block that stores some core information about the user. This information will always be inserted into the memory. The type used is `MessageContent` to support multi-modal content.
+- `factExtractionBlock`: An extracted memory block that will extract information from the chat history. Here we've passed in the `llm` to use to extract facts from the chat history, and set the `maxFacts` to 50. If the number of extracted facts exceeds this limit, the `maxFacts` will be automatically summarized and reduced to leave room for new information.
+- `vectorBlock`: A vector memory block that will store in a vector database and retrieve them from there. Messages are stored individually and retrieved based on their relevance to recent conversation context. Here we've passed in the `vectorStore` to use to store and retrieve the chat messages.

 You'll also notice that we've set the `priority` for the `factExtractionBlock` block. This is used to determine the handling when the memory blocks content (i.e. long-term memory) + short-term memory exceeds the token limit on the `Memory` object.

@@ -158,6 +164,46 @@ When memory is retrieved (using `getLLM`), the short-term and long-term memories

 The amount of short-term memory included is specified by the `shortTermTokenLimitRatio`. If it's set to `0.7`, 70% of the `tokenLimit` is used for short-term memory (not including the static memory block).

+
+#### VectorBlock Configuration Options
+
+The `vectorBlock` offers several configuration options to customize its behavior:
+
+```ts
+vectorBlock({
+  vectorStore: new QdrantVectorStore({ url: "http://localhost:6333" }),
+  priority: 2,
+  retrievalContextWindow: 5, // Number of recent messages to use for context when retrieving
+  formatTemplate: new PromptTemplate({ template: "Context: {{ context }}" }), // Custom formatting template
+  nodePostprocessors: [/* custom postprocessors */], // Apply processing to retrieved nodes
+  queryOptions: {
+    similarityTopK: 3, // Number of top similar results to return (default: 2)
+    mode: VectorStoreQueryMode.DEFAULT, // Query mode for the vector store
+    sessionFilterKey: "session_id", // Metadata key for session filtering (default: "session_id")
+    // Custom filters can be added here - session filter is automatically included
+    filters: {
+      filters: [
+        { key: "custom_field", value: "custom_value", operator: "==" }
+      ],
+      condition: "and"
+    }
+  }
+})
+```
+
+**Key Configuration Options:**
+
+- **`retrievalContextWindow`**: Number of recent messages to consider when creating the retrieval query (default: 5). A larger window provides more context but may be less precise.
+- **`formatTemplate`**: Template for formatting retrieved information before adding to memory. Defaults to a simple context template.
+- **`nodePostprocessors`**: Array of postprocessors to apply to retrieved nodes, useful for filtering or transforming results.
+- **`queryOptions.similarityTopK`**: Number of most similar messages to retrieve from the vector store (default: 2).
+- **`queryOptions.sessionFilterKey`**: Metadata key used to isolate memory between different sessions (default: "session_id").
+- **`queryOptions.filters`**: Additional metadata filters for retrieval. The session filter is automatically added to ensure memory isolation.
+
+**Session Isolation:**
+
+The vectorBlock automatically adds a session filter using the block's ID to ensure that memories from different sessions don't interfere with each other. This filter uses the `sessionFilterKey` (default: "session_id") and can be customized if needed.
+
 ## Persistence with Snapshots

 Save and restore memory state:
@@ -5,13 +5,13 @@ title: Bedrock
 ## Installation

 ```package-install
-npm i llamaindex @llamaindex/community
+npm i llamaindex @llamaindex/aws
 ```

 ## Usage

 ```ts
-import { BEDROCK_MODELS, Bedrock } from "@llamaindex/community";
+import { BEDROCK_MODELS, Bedrock } from "@llamaindex/aws";

 Settings.llm = new Bedrock({
  model: BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU,
@@ -23,9 +23,19 @@ Settings.llm = new Bedrock({
 });
 ```

-Currently only supports Anthropic and Meta models:
+Supported models are listed below (accessible by BEDROCK_MODELS).

 ```ts
+AMAZON_TITAN_TG1_LARGE = "amazon.titan-tg1-large";
+AMAZON_TITAN_TEXT_EXPRESS_V1 = "amazon.titan-text-express-v1";
+AI21_J2_GRANDE_INSTRUCT = "ai21.j2-grande-instruct";
+AI21_J2_JUMBO_INSTRUCT = "ai21.j2-jumbo-instruct";
+AI21_J2_MID = "ai21.j2-mid";
+AI21_J2_MID_V1 = "ai21.j2-mid-v1";
+AI21_J2_ULTRA = "ai21.j2-ultra";
+AI21_J2_ULTRA_V1 = "ai21.j2-ultra-v1";
+COHERE_COMMAND_TEXT_V14 = "cohere.command-text-v14";
+
 ANTHROPIC_CLAUDE_INSTANT_1 = "anthropic.claude-instant-v1";
 ANTHROPIC_CLAUDE_2 = "anthropic.claude-v2";
 ANTHROPIC_CLAUDE_2_1 = "anthropic.claude-v2:1";
@@ -33,7 +43,12 @@ 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_SONNET_V2 = "anthropic.claude-3-5-sonnet-20241022-v2:0";
 ANTHROPIC_CLAUDE_3_5_HAIKU = "anthropic.claude-3-5-haiku-20241022-v1:0";
+ANTHROPIC_CLAUDE_3_7_SONNET = "anthropic.claude-3-7-sonnet-20250219-v1:0";
+ANTHROPIC_CLAUDE_4_SONNET = "anthropic.claude-sonnet-4-20250514-v1:0";
+ANTHROPIC_CLAUDE_4_OPUS = "anthropic.claude-opus-4-20250514-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";
@@ -45,41 +60,66 @@ 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
+META_LLAMA3_3_70B_INSTRUCT = "meta.llama3-3-70b-instruct-v1:0";
+
+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_PREMIER_1 = "amazon.nova-premier-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";
 ```

-You can also use Bedrock's Inference endpoints by using the model names:
+You can also use Bedrock's Inference endpoints by using the model names (accessible by INFERENCE_BEDROCK_MODELS).
+Note that the region must be set correctly.

 ```ts
-// US
+//US
 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 = "us.anthropic.claude-3-5-sonnet-20240620-v1:0";
-US_ANTHROPIC_CLAUDE_3_5_SONNET_V2 =
-  "us.anthropic.claude-3-5-sonnet-20241022-v2:0";
+US_ANTHROPIC_CLAUDE_3_5_SONNET_V2 = "us.anthropic.claude-3-5-sonnet-20241022-v2:0";
+US_ANTHROPIC_CLAUDE_3_7_SONNET = "us.anthropic.claude-3-7-sonnet-20250219-v1:0";
+US_ANTHROPIC_CLAUDE_4_SONNET = "us.anthropic.claude-sonnet-4-20250514-v1:0";
+US_ANTHROPIC_CLAUDE_4_OPUS = "us.anthropic.claude-opus-4-20250514-v1:0";
 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-premier-v1:0";
+US_META_LLAMA_3_3_70B_INSTRUCT = "us.meta.llama3-3-70b-instruct-v1:0";
+US_AMAZON_NOVA_PREMIER_1 = "us.amazon.nova-premier-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
 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";
+EU_ANTHROPIC_CLAUDE_3_7_SONNET = "eu.anthropic.claude-3-7-sonnet-20250219-v1:0";
+EU_ANTHROPIC_CLAUDE_4_SONNET = "eu.anthropic.claude-sonnet-4-20250514-v1:0";
+EU_ANTHROPIC_CLAUDE_4_OPUS = "eu.anthropic.claude-opus-4-20250514-v1:0";
 EU_META_LLAMA_3_2_1B_INSTRUCT = "eu.meta.llama3-2-1b-instruct-v1:0";
 EU_META_LLAMA_3_2_3B_INSTRUCT = "eu.meta.llama3-2-3b-instruct-v1:0";
-EU_AMAZON_NOVA_PRO_1 = "eu.amazon.nova-premier-v1:0";
+EU_AMAZON_NOVA_PREMIER_1 = "eu.amazon.nova-premier-v1:0";
 EU_AMAZON_NOVA_PRO_1 = "eu.amazon.nova-pro-v1:0";
 EU_AMAZON_NOVA_LITE_1 = "eu.amazon.nova-lite-v1:0";
 EU_AMAZON_NOVA_MICRO_1 = "eu.amazon.nova-micro-v1:0";
+
+//APAC
+APAC_ANTHROPIC_CLAUDE_3_5_SONNET = "apac.anthropic.claude-3-5-sonnet-20240620-v1:0";
+APAC_ANTHROPIC_CLAUDE_3_5_SONNET_V2 = "apac.anthropic.claude-3-5-sonnet-20241022-v2:0";
+APAC_ANTHROPIC_CLAUDE_3_7_SONNET = "apac.anthropic.claude-3-7-sonnet-20250219-v1:0";
+APAC_ANTHROPIC_CLAUDE_3_HAIKU = "apac.anthropic.claude-3-haiku-20240307-v1:0";
+APAC_ANTHROPIC_CLAUDE_3_SONNET = "apac.anthropic.claude-3-sonnet-20240229-v1:0";
+APAC_AMAZON_NOVA_PRO_1 = "apac.amazon.nova-pro-v1:0";
+APAC_AMAZON_NOVA_LITE_1 = "apac.amazon.nova-lite-v1:0";
+APAC_AMAZON_NOVA_MICRO_1 = "apac.amazon.nova-micro-v1:0";
 ```

 Sonnet, Haiku and Opus are multimodal, image_url only supports base64 data url format, e.g. `data:image/jpeg;base64,SGVsbG8sIFdvcmxkIQ==`
@@ -87,10 +127,11 @@ Sonnet, Haiku and Opus are multimodal, image_url only supports base64 data url f
 ## Full Example

 ```ts
-import { BEDROCK_MODELS, Bedrock } from "llamaindex";
+import { INFERENCE_BEDROCK_MODELS, Bedrock } from "@llamaindex/aws";

 Settings.llm = new Bedrock({
-  model: BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU,
+  model: INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_SONNET,
+  region: "us-east-1",
 });

 async function main() {
@@ -119,7 +160,7 @@ async function main() {
 ## Agent Example

 ```ts
-import { BEDROCK_MODELS, Bedrock } from "@llamaindex/community";
+import { BEDROCK_MODELS, Bedrock } from "@llamaindex/aws";
 import { tool } from "llamaindex";
 import { agent } from "@llamaindex/workflow";
 import { z } from "zod";
@@ -38,10 +38,13 @@ You should expect output something like:
 {
  result: '5 + 5 is 10. Then, 10 divided by 2 is 5.',
  state: {
-    memory: ChatMemoryBuffer {
-      chatStore: SimpleChatStore {},
-      chatStoreKey: 'chat_history',
-      tokenLimit: 750000
+    memory: Memory {
+      messages: [Array],
+      tokenLimit: 30000,
+      shortTermTokenLimitRatio: 0.7,
+      memoryBlocks: [],
+      memoryCursor: 0,
+      adapters: [Object]
    },
    scratchpad: [],
    currentAgentName: 'Agent',
@@ -11,7 +11,7 @@
  },
  "devDependencies": {
    "@cloudflare/workers-types": "^4.20241112.0",
-    "typescript": "^5.7.3",
+    "typescript": "^5.8.3",
    "wrangler": "^3.89.0"
  },
  "dependencies": {
@@ -1,5 +1,65 @@
 # @llamaindex/cloudflare-worker-agent-test

+## 0.0.184
+
+### Patch Changes
+
+- llamaindex@0.11.23
+
+## 0.0.183
+
+### Patch Changes
+
+- llamaindex@0.11.22
+
+## 0.0.182
+
+### Patch Changes
+
+- llamaindex@0.11.21
+
+## 0.0.181
+
+### Patch Changes
+
+- llamaindex@0.11.20
+
+## 0.0.180
+
+### Patch Changes
+
+- llamaindex@0.11.19
+
+## 0.0.179
+
+### Patch Changes
+
+- llamaindex@0.11.18
+
+## 0.0.178
+
+### Patch Changes
+
+- llamaindex@0.11.17
+
+## 0.0.177
+
+### Patch Changes
+
+- llamaindex@0.11.16
+
+## 0.0.176
+
+### Patch Changes
+
+- llamaindex@0.11.15
+
+## 0.0.175
+
+### Patch Changes
+
+- llamaindex@0.11.14
+
 ## 0.0.174

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.174",
+  "version": "0.0.184",
  "type": "module",
  "private": true,
  "scripts": {
@@ -16,7 +16,7 @@
    "@cloudflare/workers-types": "^4.20241112.0",
    "@vitest/runner": "2.1.5",
    "@vitest/snapshot": "2.1.5",
-    "typescript": "^5.7.3",
+    "typescript": "^5.8.3",
    "vitest": "2.1.5",
    "wrangler": "^3.87.0"
  },
@@ -1,5 +1,67 @@
 # @llamaindex/llama-parse-browser-test

+## 0.0.82
+
+### Patch Changes
+
+- @llamaindex/cloud@4.0.27
+
+## 0.0.81
+
+### Patch Changes
+
+- @llamaindex/cloud@4.0.26
+
+## 0.0.80
+
+### Patch Changes
+
+- Updated dependencies [2967d57]
+  - @llamaindex/cloud@4.0.25
+
+## 0.0.79
+
+### Patch Changes
+
+- @llamaindex/cloud@4.0.24
+
+## 0.0.78
+
+### Patch Changes
+
+- Updated dependencies [a1b1598]
+  - @llamaindex/cloud@4.0.23
+
+## 0.0.77
+
+### Patch Changes
+
+- Updated dependencies [d2be868]
+  - @llamaindex/cloud@4.0.22
+
+## 0.0.76
+
+### Patch Changes
+
+- Updated dependencies [579ca0c]
+  - @llamaindex/cloud@4.0.21
+
+## 0.0.75
+
+### Patch Changes
+
+- Updated dependencies [48b0d88]
+- Updated dependencies [f185772]
+  - @llamaindex/cloud@4.0.20
+
+## 0.0.74
+
+### Patch Changes
+
+- Updated dependencies [5a0ed1f]
+- Updated dependencies [5a0ed1f]
+  - @llamaindex/cloud@4.0.19
+
 ## 0.0.73

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/llama-parse-browser-test",
  "private": true,
-  "version": "0.0.73",
+  "version": "0.0.82",
  "type": "module",
  "scripts": {
    "dev": "vite",
@@ -9,7 +9,7 @@
    "preview": "vite preview"
  },
  "devDependencies": {
-    "typescript": "^5.7.3",
+    "typescript": "^5.8.3",
    "vite": "^6.3.3",
    "vite-plugin-wasm": "^3.4.1"
  },
@@ -1,5 +1,65 @@
 # @llamaindex/next-agent-test

+## 0.1.184
+
+### Patch Changes
+
+- llamaindex@0.11.23
+
+## 0.1.183
+
+### Patch Changes
+
+- llamaindex@0.11.22
+
+## 0.1.182
+
+### Patch Changes
+
+- llamaindex@0.11.21
+
+## 0.1.181
+
+### Patch Changes
+
+- llamaindex@0.11.20
+
+## 0.1.180
+
+### Patch Changes
+
+- llamaindex@0.11.19
+
+## 0.1.179
+
+### Patch Changes
+
+- llamaindex@0.11.18
+
+## 0.1.178
+
+### Patch Changes
+
+- llamaindex@0.11.17
+
+## 0.1.177
+
+### Patch Changes
+
+- llamaindex@0.11.16
+
+## 0.1.176
+
+### Patch Changes
+
+- llamaindex@0.11.15
+
+## 0.1.175
+
+### Patch Changes
+
+- llamaindex@0.11.14
+
 ## 0.1.174

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/next-agent-test",
-  "version": "0.1.174",
+  "version": "0.1.184",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -8,18 +8,18 @@
    "start": "next start"
  },
  "dependencies": {
-    "ai": "^4.0.0",
+    "ai": "^4.3.17",
    "llamaindex": "workspace:*",
-    "next": "^15.3.0",
+    "next": "^15.3.3",
    "react": "19.0.0",
    "react-dom": "19.0.0"
  },
  "devDependencies": {
-    "@types/node": "^22.9.0",
-    "@types/react": "^19.0.10",
-    "@types/react-dom": "^19.0.4",
-    "eslint": "9.16.0",
-    "eslint-config-next": "15.1.0",
-    "typescript": "^5.7.3"
+    "@types/node": "^24.0.13",
+    "@types/react": "^19.1.8",
+    "@types/react-dom": "^19.1.6",
+    "eslint": "9.30.1",
+    "eslint-config-next": "15.3.5",
+    "typescript": "^5.8.3"
  }
 }
@@ -1,5 +1,65 @@
 # test-edge-runtime

+## 0.1.183
+
+### Patch Changes
+
+- llamaindex@0.11.23
+
+## 0.1.182
+
+### Patch Changes
+
+- llamaindex@0.11.22
+
+## 0.1.181
+
+### Patch Changes
+
+- llamaindex@0.11.21
+
+## 0.1.180
+
+### Patch Changes
+
+- llamaindex@0.11.20
+
+## 0.1.179
+
+### Patch Changes
+
+- llamaindex@0.11.19
+
+## 0.1.178
+
+### Patch Changes
+
+- llamaindex@0.11.18
+
+## 0.1.177
+
+### Patch Changes
+
+- llamaindex@0.11.17
+
+## 0.1.176
+
+### Patch Changes
+
+- llamaindex@0.11.16
+
+## 0.1.175
+
+### Patch Changes
+
+- llamaindex@0.11.15
+
+## 0.1.174
+
+### Patch Changes
+
+- llamaindex@0.11.14
+
 ## 0.1.173

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.173",
+  "version": "0.1.183",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -9,14 +9,14 @@
  },
  "dependencies": {
    "llamaindex": "workspace:*",
-    "next": "^15.3.0",
+    "next": "^15.3.3",
    "react": "^19.1.0",
    "react-dom": "^19.1.0"
  },
  "devDependencies": {
-    "@types/node": "^22.9.0",
-    "@types/react": "^19.0.10",
-    "@types/react-dom": "^19.0.4",
-    "typescript": "^5.7.3"
+    "@types/node": "^24.0.13",
+    "@types/react": "^19.1.8",
+    "@types/react-dom": "^19.1.6",
+    "typescript": "^5.8.3"
  }
 }
@@ -1,5 +1,81 @@
 # @llamaindex/next-node-runtime

+## 0.1.53
+
+### Patch Changes
+
+- llamaindex@0.11.23
+- @llamaindex/huggingface@0.1.23
+- @llamaindex/readers@3.1.17
+
+## 0.1.52
+
+### Patch Changes
+
+- llamaindex@0.11.22
+
+## 0.1.51
+
+### Patch Changes
+
+- llamaindex@0.11.21
+- @llamaindex/huggingface@0.1.22
+- @llamaindex/readers@3.1.16
+
+## 0.1.50
+
+### Patch Changes
+
+- llamaindex@0.11.20
+- @llamaindex/huggingface@0.1.21
+- @llamaindex/readers@3.1.15
+
+## 0.1.49
+
+### Patch Changes
+
+- @llamaindex/huggingface@0.1.20
+
+## 0.1.48
+
+### Patch Changes
+
+- llamaindex@0.11.19
+- @llamaindex/huggingface@0.1.19
+- @llamaindex/readers@3.1.14
+
+## 0.1.47
+
+### Patch Changes
+
+- llamaindex@0.11.18
+
+## 0.1.46
+
+### Patch Changes
+
+- llamaindex@0.11.17
+
+## 0.1.45
+
+### Patch Changes
+
+- llamaindex@0.11.16
+
+## 0.1.44
+
+### Patch Changes
+
+- llamaindex@0.11.15
+
+## 0.1.43
+
+### Patch Changes
+
+- llamaindex@0.11.14
+- @llamaindex/huggingface@0.1.18
+- @llamaindex/readers@3.1.13
+
 ## 0.1.42

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.1.42",
+  "version": "0.1.53",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -11,16 +11,16 @@
    "@llamaindex/huggingface": "workspace:*",
    "@llamaindex/readers": "workspace:*",
    "llamaindex": "workspace:*",
-    "next": "^15.3.0",
+    "next": "^15.3.3",
    "react": "19.0.0",
    "react-dom": "19.0.0"
  },
  "devDependencies": {
-    "@types/node": "^22.9.0",
-    "@types/react": "^19.0.10",
-    "@types/react-dom": "^19.0.4",
-    "eslint": "9.16.0",
-    "eslint-config-next": "15.1.0",
-    "typescript": "^5.7.3"
+    "@types/node": "^24.0.13",
+    "@types/react": "^19.1.8",
+    "@types/react-dom": "^19.1.6",
+    "eslint": "9.30.1",
+    "eslint-config-next": "15.3.5",
+    "typescript": "^5.8.3"
  }
 }
@@ -1,5 +1,65 @@
 # vite-import-llamaindex

+## 0.0.50
+
+### Patch Changes
+
+- llamaindex@0.11.23
+
+## 0.0.49
+
+### Patch Changes
+
+- llamaindex@0.11.22
+
+## 0.0.48
+
+### Patch Changes
+
+- llamaindex@0.11.21
+
+## 0.0.47
+
+### Patch Changes
+
+- llamaindex@0.11.20
+
+## 0.0.46
+
+### Patch Changes
+
+- llamaindex@0.11.19
+
+## 0.0.45
+
+### Patch Changes
+
+- llamaindex@0.11.18
+
+## 0.0.44
+
+### Patch Changes
+
+- llamaindex@0.11.17
+
+## 0.0.43
+
+### Patch Changes
+
+- llamaindex@0.11.16
+
+## 0.0.42
+
+### Patch Changes
+
+- llamaindex@0.11.15
+
+## 0.0.41
+
+### Patch Changes
+
+- llamaindex@0.11.14
+
 ## 0.0.40

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "vite-import-llamaindex",
  "private": true,
-  "version": "0.0.40",
+  "version": "0.0.50",
  "type": "module",
  "scripts": {
    "build": "vite build",
@@ -15,7 +15,7 @@
  "devDependencies": {
    "@size-limit/preset-big-lib": "^11.1.6",
    "size-limit": "^11.1.6",
-    "typescript": "^5.7.3",
+    "typescript": "^5.8.3",
    "vite": "^6.3.3"
  },
  "dependencies": {
@@ -1,5 +1,65 @@
 # @llamaindex/waku-query-engine-test

+## 0.0.184
+
+### Patch Changes
+
+- llamaindex@0.11.23
+
+## 0.0.183
+
+### Patch Changes
+
+- llamaindex@0.11.22
+
+## 0.0.182
+
+### Patch Changes
+
+- llamaindex@0.11.21
+
+## 0.0.181
+
+### Patch Changes
+
+- llamaindex@0.11.20
+
+## 0.0.180
+
+### Patch Changes
+
+- llamaindex@0.11.19
+
+## 0.0.179
+
+### Patch Changes
+
+- llamaindex@0.11.18
+
+## 0.0.178
+
+### Patch Changes
+
+- llamaindex@0.11.17
+
+## 0.0.177
+
+### Patch Changes
+
+- llamaindex@0.11.16
+
+## 0.0.176
+
+### Patch Changes
+
+- llamaindex@0.11.15
+
+## 0.0.175
+
+### Patch Changes
+
+- llamaindex@0.11.14
+
 ## 0.0.174

 ### Patch Changes
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.174",
+  "version": "0.0.184",
  "type": "module",
  "private": true,
  "scripts": {
@@ -18,10 +18,10 @@
  },
  "devDependencies": {
    "@tailwindcss/postcss": "^4.1.4",
-    "@types/react": "19.0.10",
-    "@types/react-dom": "19.0.4",
+    "@types/react": "19.1.8",
+    "@types/react-dom": "19.1.6",
    "rollup": "4.38.0",
-    "tailwindcss": "^4.1.4",
-    "typescript": "5.7.3"
+    "tailwindcss": "^4.1.11",
+    "typescript": "5.8.3"
  }
 }
@@ -23,7 +23,7 @@ await test("pinecone", async (t) => {
  });

  const vectorStore = new PineconeVectorStore({
-    embeddingModel: openaiEmbedding,
+    embedModel: openaiEmbedding,
  });

  t.after(async () => {
@@ -19,14 +19,14 @@
    "@llamaindex/openai": "workspace:*",
    "@llamaindex/pinecone": "workspace:*",
    "@llamaindex/postgres": "workspace:*",
-    "@types/node": "^22.9.0",
+    "@types/node": "^24.0.13",
    "@types/pg": "^8.11.8",
    "consola": "^3.2.3",
-    "dotenv": "^16.4.5",
+    "dotenv": "^17.2.0",
    "llamaindex": "workspace:*",
    "pg": "^8.12.0",
    "pgvector": "0.2.0",
-    "tsx": "^4.19.3",
-    "zod": "^3.25.67"
+    "tsx": "^4.20.3",
+    "zod": "^3.25.76"
  }
 }
@@ -1,5 +1,303 @@
 # examples

+## 0.3.34
+
+### Patch Changes
+
+- Updated dependencies [f29799e]
+- Updated dependencies [7224c06]
+  - @llamaindex/workflow@1.1.19
+  - @llamaindex/core@0.6.18
+  - llamaindex@0.11.23
+  - @llamaindex/cloud@4.0.27
+  - @llamaindex/node-parser@2.0.18
+  - @llamaindex/anthropic@0.3.20
+  - @llamaindex/assemblyai@0.1.17
+  - @llamaindex/clip@0.0.69
+  - @llamaindex/cohere@0.0.32
+  - @llamaindex/deepinfra@0.0.69
+  - @llamaindex/discord@0.1.17
+  - @llamaindex/google@0.3.17
+  - @llamaindex/huggingface@0.1.23
+  - @llamaindex/jinaai@0.0.29
+  - @llamaindex/mistral@0.1.18
+  - @llamaindex/mixedbread@0.0.32
+  - @llamaindex/notion@0.1.17
+  - @llamaindex/ollama@0.1.18
+  - @llamaindex/openai@0.4.13
+  - @llamaindex/perplexity@0.0.26
+  - @llamaindex/portkey-ai@0.0.60
+  - @llamaindex/replicate@0.0.60
+  - @llamaindex/bm25-retriever@0.0.7
+  - @llamaindex/astra@0.0.32
+  - @llamaindex/azure@0.1.30
+  - @llamaindex/chroma@0.0.32
+  - @llamaindex/elastic-search@0.1.18
+  - @llamaindex/firestore@1.0.25
+  - @llamaindex/milvus@0.1.27
+  - @llamaindex/mongodb@0.0.33
+  - @llamaindex/pinecone@0.1.18
+  - @llamaindex/postgres@0.0.61
+  - @llamaindex/qdrant@0.1.28
+  - @llamaindex/supabase@0.1.19
+  - @llamaindex/upstash@0.0.32
+  - @llamaindex/weaviate@0.0.33
+  - @llamaindex/vercel@0.1.18
+  - @llamaindex/voyage-ai@1.0.24
+  - @llamaindex/readers@3.1.17
+  - @llamaindex/tools@0.1.8
+  - @llamaindex/deepseek@0.0.30
+  - @llamaindex/fireworks@0.0.29
+  - @llamaindex/groq@0.0.85
+  - @llamaindex/together@0.0.29
+  - @llamaindex/vllm@0.0.55
+  - @llamaindex/xai@0.0.16
+
+## 0.3.33
+
+### Patch Changes
+
+- Updated dependencies [38da40b]
+  - @llamaindex/core@0.6.17
+  - @llamaindex/cloud@4.0.26
+  - llamaindex@0.11.21
+  - @llamaindex/node-parser@2.0.17
+  - @llamaindex/anthropic@0.3.19
+  - @llamaindex/assemblyai@0.1.16
+  - @llamaindex/clip@0.0.68
+  - @llamaindex/cohere@0.0.31
+  - @llamaindex/deepinfra@0.0.68
+  - @llamaindex/discord@0.1.16
+  - @llamaindex/google@0.3.16
+  - @llamaindex/huggingface@0.1.22
+  - @llamaindex/jinaai@0.0.28
+  - @llamaindex/mistral@0.1.17
+  - @llamaindex/mixedbread@0.0.31
+  - @llamaindex/notion@0.1.16
+  - @llamaindex/ollama@0.1.17
+  - @llamaindex/openai@0.4.12
+  - @llamaindex/perplexity@0.0.25
+  - @llamaindex/portkey-ai@0.0.59
+  - @llamaindex/replicate@0.0.59
+  - @llamaindex/bm25-retriever@0.0.6
+  - @llamaindex/astra@0.0.31
+  - @llamaindex/azure@0.1.29
+  - @llamaindex/chroma@0.0.31
+  - @llamaindex/elastic-search@0.1.17
+  - @llamaindex/firestore@1.0.24
+  - @llamaindex/milvus@0.1.26
+  - @llamaindex/mongodb@0.0.32
+  - @llamaindex/pinecone@0.1.17
+  - @llamaindex/postgres@0.0.60
+  - @llamaindex/qdrant@0.1.27
+  - @llamaindex/supabase@0.1.18
+  - @llamaindex/upstash@0.0.31
+  - @llamaindex/weaviate@0.0.32
+  - @llamaindex/vercel@0.1.17
+  - @llamaindex/voyage-ai@1.0.23
+  - @llamaindex/readers@3.1.16
+  - @llamaindex/tools@0.1.7
+  - @llamaindex/workflow@1.1.17
+  - @llamaindex/deepseek@0.0.29
+  - @llamaindex/fireworks@0.0.28
+  - @llamaindex/groq@0.0.84
+  - @llamaindex/together@0.0.28
+  - @llamaindex/vllm@0.0.54
+  - @llamaindex/xai@0.0.15
+
+## 0.3.32
+
+### Patch Changes
+
+- Updated dependencies [650eeb1]
+- Updated dependencies [a8ec08c]
+- Updated dependencies [2967d57]
+  - @llamaindex/google@0.3.15
+  - @llamaindex/core@0.6.16
+  - @llamaindex/workflow@1.1.16
+  - @llamaindex/cloud@4.0.25
+  - llamaindex@0.11.20
+  - @llamaindex/node-parser@2.0.16
+  - @llamaindex/anthropic@0.3.18
+  - @llamaindex/assemblyai@0.1.15
+  - @llamaindex/clip@0.0.67
+  - @llamaindex/cohere@0.0.30
+  - @llamaindex/deepinfra@0.0.67
+  - @llamaindex/discord@0.1.15
+  - @llamaindex/huggingface@0.1.21
+  - @llamaindex/jinaai@0.0.27
+  - @llamaindex/mistral@0.1.16
+  - @llamaindex/mixedbread@0.0.30
+  - @llamaindex/notion@0.1.15
+  - @llamaindex/ollama@0.1.16
+  - @llamaindex/openai@0.4.11
+  - @llamaindex/perplexity@0.0.24
+  - @llamaindex/portkey-ai@0.0.58
+  - @llamaindex/replicate@0.0.58
+  - @llamaindex/bm25-retriever@0.0.5
+  - @llamaindex/astra@0.0.30
+  - @llamaindex/azure@0.1.28
+  - @llamaindex/chroma@0.0.30
+  - @llamaindex/elastic-search@0.1.16
+  - @llamaindex/firestore@1.0.23
+  - @llamaindex/milvus@0.1.25
+  - @llamaindex/mongodb@0.0.31
+  - @llamaindex/pinecone@0.1.16
+  - @llamaindex/postgres@0.0.59
+  - @llamaindex/qdrant@0.1.26
+  - @llamaindex/supabase@0.1.17
+  - @llamaindex/upstash@0.0.30
+  - @llamaindex/weaviate@0.0.31
+  - @llamaindex/vercel@0.1.16
+  - @llamaindex/voyage-ai@1.0.22
+  - @llamaindex/readers@3.1.15
+  - @llamaindex/tools@0.1.6
+  - @llamaindex/deepseek@0.0.28
+  - @llamaindex/fireworks@0.0.27
+  - @llamaindex/groq@0.0.83
+  - @llamaindex/together@0.0.27
+  - @llamaindex/vllm@0.0.53
+  - @llamaindex/xai@0.0.14
+
+## 0.3.31
+
+### Patch Changes
+
+- Updated dependencies [d8f4f6a]
+- Updated dependencies [856dd8c]
+  - @llamaindex/supabase@0.1.16
+  - @llamaindex/openai@0.4.10
+  - @llamaindex/clip@0.0.66
+  - @llamaindex/deepinfra@0.0.66
+  - @llamaindex/deepseek@0.0.27
+  - @llamaindex/fireworks@0.0.26
+  - @llamaindex/groq@0.0.82
+  - @llamaindex/huggingface@0.1.20
+  - @llamaindex/jinaai@0.0.26
+  - @llamaindex/perplexity@0.0.23
+  - @llamaindex/azure@0.1.27
+  - @llamaindex/together@0.0.26
+  - @llamaindex/vllm@0.0.52
+  - @llamaindex/xai@0.0.13
+
+## 0.3.30
+
+### Patch Changes
+
+- Updated dependencies [7ad3411]
+- Updated dependencies [5da5b3c]
+- Updated dependencies [a1fdb07]
+- Updated dependencies [ddc0eaf]
+  - @llamaindex/core@0.6.15
+  - @llamaindex/tools@0.1.5
+  - @llamaindex/workflow@1.1.15
+  - @llamaindex/openai@0.4.9
+  - @llamaindex/anthropic@0.3.17
+  - @llamaindex/cloud@4.0.24
+  - llamaindex@0.11.19
+  - @llamaindex/node-parser@2.0.15
+  - @llamaindex/assemblyai@0.1.14
+  - @llamaindex/clip@0.0.65
+  - @llamaindex/cohere@0.0.29
+  - @llamaindex/deepinfra@0.0.65
+  - @llamaindex/discord@0.1.14
+  - @llamaindex/google@0.3.14
+  - @llamaindex/huggingface@0.1.19
+  - @llamaindex/jinaai@0.0.25
+  - @llamaindex/mistral@0.1.15
+  - @llamaindex/mixedbread@0.0.29
+  - @llamaindex/notion@0.1.14
+  - @llamaindex/ollama@0.1.15
+  - @llamaindex/perplexity@0.0.22
+  - @llamaindex/portkey-ai@0.0.57
+  - @llamaindex/replicate@0.0.57
+  - @llamaindex/bm25-retriever@0.0.4
+  - @llamaindex/astra@0.0.29
+  - @llamaindex/azure@0.1.26
+  - @llamaindex/chroma@0.0.29
+  - @llamaindex/elastic-search@0.1.15
+  - @llamaindex/firestore@1.0.22
+  - @llamaindex/milvus@0.1.24
+  - @llamaindex/mongodb@0.0.30
+  - @llamaindex/pinecone@0.1.15
+  - @llamaindex/postgres@0.0.58
+  - @llamaindex/qdrant@0.1.25
+  - @llamaindex/supabase@0.1.15
+  - @llamaindex/upstash@0.0.29
+  - @llamaindex/weaviate@0.0.30
+  - @llamaindex/vercel@0.1.15
+  - @llamaindex/voyage-ai@1.0.21
+  - @llamaindex/readers@3.1.14
+  - @llamaindex/deepseek@0.0.26
+  - @llamaindex/fireworks@0.0.25
+  - @llamaindex/groq@0.0.81
+  - @llamaindex/together@0.0.25
+  - @llamaindex/vllm@0.0.51
+  - @llamaindex/xai@0.0.12
+
+## 0.3.29
+
+### Patch Changes
+
+- Updated dependencies [af3f866]
+  - @llamaindex/deepseek@0.0.25
+
+## 0.3.28
+
+### Patch Changes
+
+- 36773a8: Fixed start script, reverted some changes to imports
+- 891562d: Fix xai dependency in the examples
+- Updated dependencies [5a0ed1f]
+- Updated dependencies [5a0ed1f]
+- Updated dependencies [8eeac33]
+  - @llamaindex/cloud@4.0.19
+  - @llamaindex/core@0.6.14
+  - llamaindex@0.11.14
+  - @llamaindex/node-parser@2.0.14
+  - @llamaindex/anthropic@0.3.16
+  - @llamaindex/assemblyai@0.1.13
+  - @llamaindex/clip@0.0.64
+  - @llamaindex/cohere@0.0.28
+  - @llamaindex/deepinfra@0.0.64
+  - @llamaindex/discord@0.1.13
+  - @llamaindex/google@0.3.13
+  - @llamaindex/huggingface@0.1.18
+  - @llamaindex/jinaai@0.0.24
+  - @llamaindex/mistral@0.1.14
+  - @llamaindex/mixedbread@0.0.28
+  - @llamaindex/notion@0.1.13
+  - @llamaindex/ollama@0.1.14
+  - @llamaindex/openai@0.4.8
+  - @llamaindex/perplexity@0.0.21
+  - @llamaindex/portkey-ai@0.0.56
+  - @llamaindex/replicate@0.0.56
+  - @llamaindex/bm25-retriever@0.0.3
+  - @llamaindex/astra@0.0.28
+  - @llamaindex/azure@0.1.25
+  - @llamaindex/chroma@0.0.28
+  - @llamaindex/elastic-search@0.1.14
+  - @llamaindex/firestore@1.0.21
+  - @llamaindex/milvus@0.1.23
+  - @llamaindex/mongodb@0.0.29
+  - @llamaindex/pinecone@0.1.14
+  - @llamaindex/postgres@0.0.57
+  - @llamaindex/qdrant@0.1.24
+  - @llamaindex/supabase@0.1.14
+  - @llamaindex/upstash@0.0.28
+  - @llamaindex/weaviate@0.0.29
+  - @llamaindex/vercel@0.1.14
+  - @llamaindex/voyage-ai@1.0.20
+  - @llamaindex/readers@3.1.13
+  - @llamaindex/tools@0.1.4
+  - @llamaindex/workflow@1.1.14
+  - @llamaindex/deepseek@0.0.24
+  - @llamaindex/fireworks@0.0.24
+  - @llamaindex/groq@0.0.80
+  - @llamaindex/together@0.0.24
+  - @llamaindex/vllm@0.0.50
+  - @llamaindex/xai@0.0.11
+
 ## 0.3.27

 ### Patch Changes
@@ -1,9 +1,10 @@
 # LlamaIndexTS Examples

-Before running any of the code examples,
-make sure you have basic knowledge of the [LlamaIndexTS](https://ts.llamaindex.ai/).
+This package contains several examples of how to use LlamaIndexTS.

-## Usage
+Most examples will use OpenAI by default, so be sure to set your API key.
+
+## Running Examples

 ```shell
 # export your API key
@@ -12,8 +13,31 @@ export OPENAI_API_KEY="sk-..."
 npx tsx ./rag/chatEngine.ts
 ```

-## Build your own RAG app
+## Recommended Starter Examples

-```shell
-npx create llama
-```
+Agents:
+
+- [Basic OpenAI Agent with Tools](./agents/agent/openai.ts)
+- [Agent with MCP Tools](./agents/agent/mcp-tools.ts)
+- [Customizing Memory](./agents/memory/agent-memory.ts)
+
+Workflows:
+
+- [Workflow basics](./agents/workflow/joke.ts)
+- [Find more workflow examples in the `workflows-ts` repo!](https://github.com/run-llama/workflows-ts)
+
+Indexing, Retrieval, and Querying:
+
+- [Basic Vector Indexing + Query Engine](./index/vectorIndex.ts)
+- [Agent + Query Engine Tool](./agents/agent/query-tool.ts)
+
+Multimodal:
+
+- [Multimodal RAG](./multimodal/rag.ts)
+- [Multimodal Chat](./multimodal/context.ts)
+
+Some more general folders that might be useful to explore:
+
+- [storage](./storage/): Examples with various vector stores
+- [readers](./readers/): Examples of how to use the various readers
+- [models](./models/): Examples of how to use the various LLMs and embedding models from many providers
@@ -3,7 +3,7 @@
 */
 import { openai } from "@llamaindex/openai";
 import { agent } from "@llamaindex/workflow";
-import { getWeatherTool } from "../../deprecated/agents/utils/tools";
+import { getWeatherTool } from "../tools/tools";

 async function main() {
  const weatherAgent = agent({
@@ -24,6 +24,7 @@ async function main() {
    state: result.data.state,
  });
  console.log(`${JSON.stringify(caResult, null, 2)}`);
+  console.log("assistant message:", result.data.message);
 }

 main().catch((error) => {
@@ -1,6 +1,6 @@
 import { ollama } from "@llamaindex/ollama";
 import { agent } from "@llamaindex/workflow";
-import { getWeatherTool } from "../../deprecated/agents/utils/tools";
+import { getWeatherTool } from "../tools/tools";

 async function main() {
  const myAgent = agent({
@@ -0,0 +1,150 @@
+/**
+ * Example: Vector Memory Block
+ *
+ * This example demonstrates how to use the VectorMemoryBlock to store and retrieve
+ * conversation history using vector similarity search. The vector memory block
+ * stores messages in a vector store and can retrieve relevant context based on
+ * semantic similarity to recent messages.
+ */
+
+import { OpenAI, OpenAIEmbedding } from "@llamaindex/openai";
+import { QdrantVectorStore } from "@llamaindex/qdrant";
+import { createMemory, vectorBlock } from "llamaindex";
+
+// Set up the LLM and embedding model
+const llm = new OpenAI({ model: "gpt-4.1-mini" });
+const embedModel = new OpenAIEmbedding({ model: "text-embedding-3-small" });
+
+// Simulate a conversation with some context
+// This conversation has 8 messages, which is more than the token limit of 100 tokens (set below)
+// The last 4 messages are kept in to short term memory block (as their tokens are in the limit)
+// Whereas the first 5 messages are added to long term memory block (in here we will use the vector memory block with Qdrant)
+const CONVERSATION_TURNS = [
+  //// This is the first 5 messages that are added to long term memory block (vector memory block)
+  {
+    role: "user",
+    content: "Hi, I'm Sarah and I work as a data scientist at Google.",
+  },
+  {
+    role: "assistant",
+    content:
+      "Hello Sarah! It's great to meet you. Data science at Google must be exciting!",
+  },
+  {
+    role: "user",
+    content:
+      "Yes, I specialize in machine learning and natural language processing.",
+  },
+  {
+    role: "assistant",
+    content: "That's impressive! ML and NLP are fascinating fields.",
+  },
+  {
+    role: "user",
+    content:
+      "I have a PhD in Computer Science from Stanford, and I love hiking on weekends.",
+  },
+
+  //// This is the last 4 messages that are added to short term memory block
+  {
+    role: "assistant",
+    content:
+      "Wow, Stanford PhD! And hiking is a great way to unwind from tech work.",
+  },
+  {
+    role: "user",
+    content: "I also have two cats named Whiskers and Mittens.",
+  },
+  {
+    role: "assistant",
+    content:
+      "Cats make wonderful companions! Whiskers and Mittens are cute names.",
+  },
+  {
+    role: "user",
+    content: "Summary information about Sarah and her cats",
+  },
+];
+
+async function main() {
+  console.log("=== Vector Memory Block Example ===\n");
+
+  /**
+   * Create a vector store. You can quickly get a local instance of Qdrant running with Docker:
+   * ```bash
+   * docker pull qdrant/qdrant
+   * docker run -p 6333:6333 qdrant/qdrant
+   * ```
+   *
+   * Go to http://localhost:6333/dashboard#/collections to see your data
+   */
+  const vectorStore = new QdrantVectorStore({
+    url: "http://localhost:6333",
+    embedModel,
+  });
+
+  // Create a vector memory block using the factory function
+  const vectorMemoryBlock = vectorBlock({
+    vectorStore,
+    priority: 5,
+  });
+
+  // Create a memory store with the vector memory block
+  const memory = createMemory([], {
+    llm,
+    memoryBlocks: [vectorMemoryBlock],
+    tokenLimit: 100,
+    shortTermTokenLimitRatio: 0.7,
+  });
+
+  // Store the conversation history in the vector memory
+  console.log(`Adding ${CONVERSATION_TURNS.length} messages to the memory...`);
+  for (const message of CONVERSATION_TURNS) {
+    await memory.add(message);
+  }
+
+  // Retrieve relevant context for the current user request
+  console.log("Retrieving relevant context...");
+  const chatHistory = await memory.getLLM();
+
+  // You will see there's 1 generated context message from vector memory block, and 4 messages from short term memory block
+  console.log("Chat memory:", chatHistory);
+
+  // Now simulate the assistant responding with context
+  console.log("\nAssistant response with context:");
+  const response = await llm.chat({
+    messages: chatHistory,
+  });
+  console.log(response.message.content);
+
+  // Try adding more messages to the memory
+  const newMessages = [
+    {
+      role: "user",
+      content: "Write a long paragraph about weather in Tokyo",
+    },
+    {
+      role: "assistant",
+      content:
+        "The weather in Tokyo is sunny and warm. The temperature is around 20 degrees Celsius. The weather is very nice and the people are friendly.",
+    },
+    {
+      role: "user",
+      content: "What is the weather in Tokyo?",
+    },
+  ];
+  // Add the new messages to the memory
+  for (const message of newMessages) {
+    await memory.add(message);
+  }
+
+  // Try retrieving the new messages
+  const newChatHistory = await memory.getLLM();
+  // You can see now that new chat history will contain the nodes (separated by `\n`) in the
+  // context message that is generated by the vector memory block
+  // The number of retrieved nodes is set by `similarityTopK` in `queryOptions` of `vectorBlock`
+  // (default `similarityTopK` is 2)
+  console.log("New chat history:", newChatHistory);
+}
+
+main().catch(console.error);
@@ -1,7 +1,7 @@
-import { OpenAI } from "@llamaindex/openai";
+import { openai } from "@llamaindex/openai";

 async function main() {
-  const llm = new OpenAI({ model: "gpt-4-turbo" });
+  const llm = openai({ model: "gpt-4.1-mini" });
  const args: Parameters<typeof llm.chat>[0] = {
    additionalChatOptions: {
      tool_choice: "auto",
@@ -0,0 +1,46 @@
+import { openai } from "@llamaindex/openai";
+import { tool } from "llamaindex";
+import z from "zod";
+
+import { ChatMessage } from "llamaindex";
+
+async function main() {
+  const llm = openai({ model: "gpt-4.1-mini" });
+  const messages = [
+    {
+      content: `What's the weather like in San Francisco?`,
+      role: "user",
+    } as ChatMessage,
+  ];
+
+  let exit = false;
+  do {
+    const { stream, newMessages, toolCalls } = await llm.exec({
+      messages,
+      tools: [
+        tool({
+          name: "get_weather",
+          description: "Get the current weather for a location",
+          parameters: z.object({
+            address: z.string().describe("The address"),
+          }),
+          execute: ({ address }) => {
+            return `It's sunny in ${address}!`;
+          },
+        }),
+      ],
+      stream: true,
+    });
+    for await (const chunk of stream) {
+      process.stdout.write(chunk.delta);
+    }
+    messages.push(...newMessages());
+    // exit condition to stop the agent loop
+    // here we can also check for specific tool calls or limit the number of llm.exec calls
+    exit = toolCalls.length === 0;
+  } while (!exit);
+}
+
+(async function () {
+  await main();
+})();
@@ -0,0 +1,43 @@
+import { openai } from "@llamaindex/openai";
+import { ChatMessage, tool } from "llamaindex";
+import z from "zod";
+
+async function main() {
+  const llm = openai({ model: "gpt-4.1-mini" });
+  const messages = [
+    {
+      content: `What's the weather like in San Francisco?`,
+      role: "user",
+    } as ChatMessage,
+  ];
+
+  let exit = false;
+  do {
+    const { newMessages, toolCalls } = await llm.exec({
+      messages,
+      tools: [
+        tool({
+          name: "get_weather",
+          description: "Get the current weather for a location",
+          parameters: z.object({
+            address: z.string().describe("The address"),
+          }),
+          execute: ({ address }) => {
+            return `It's sunny in ${address}!`;
+          },
+        }),
+      ],
+    });
+    console.log(newMessages);
+    messages.push(...newMessages);
+    // exit condition to stop the agent loop
+    // here we can also check for specific tool calls or limit the number of llm.exec calls
+    exit = toolCalls.length === 0;
+  } while (!exit);
+}
+
+(async function () {
+  console.log("Starting...");
+  await main();
+  console.log("Done");
+})();
@@ -4,7 +4,7 @@ import {
  getCurrentIDTool,
  getUserInfoTool,
  getWeatherTool,
-} from "./utils/tools";
+} from "../../agents/tools/tools";

 async function main() {
  // Create an OpenAIAgent with the function tools
@@ -3,7 +3,7 @@ import {
  getCurrentIDTool,
  getUserInfoTool,
  getWeatherTool,
-} from "./utils/tools";
+} from "../../agents/tools/tools";

 async function main() {
  // Create an OpenAIAgent with the function tools
@@ -15,15 +15,15 @@
  },
  "devDependencies": {
    "@eslint/js": "^9.25.0",
-    "@types/react": "^19.1.2",
-    "@types/react-dom": "^19.1.2",
+    "@types/react": "^19.1.8",
+    "@types/react-dom": "^19.1.6",
    "@vitejs/plugin-react": "^4.5.2",
-    "eslint": "^9.25.0",
+    "eslint": "^9.30.1",
    "eslint-plugin-react-hooks": "^5.2.0",
    "eslint-plugin-react-refresh": "^0.4.19",
    "globals": "^16.0.0",
    "typescript": "~5.8.3",
-    "typescript-eslint": "^8.30.1",
+    "typescript-eslint": "^8.36.0",
    "vite": "^6.3.5"
  }
 }
@@ -30,6 +30,12 @@ async function main() {
  );
  // and print out the text part
  console.log(textPart?.text);
+
+  const imageId = response.message.options?.image_id;
+  if (imageId) {
+    console.log("Image ID for multi-turn generation:", imageId);
+    console.log("Use this image_id in subsequent requests to modify the image");
+  }
 }

 main().catch(console.error);
@@ -0,0 +1,89 @@
+import { openaiResponses } from "@llamaindex/openai";
+import fs from "fs";
+import { MessageContentDetail } from "llamaindex";
+
+async function main() {
+  const llm = openaiResponses({
+    model: "gpt-4.1-mini",
+    builtInTools: [{ type: "image_generation" }],
+  });
+
+  // First turn: Generate initial image
+  console.log("=== First Turn: Generate initial image ===");
+  const firstResponse = await llm.chat({
+    messages: [
+      {
+        role: "user",
+        content:
+          "Generate an image of a cute tiny llama wearing a hat playing with a cat on a meadow",
+      },
+    ],
+  });
+
+  const firstContent = firstResponse.message.content as MessageContentDetail[];
+  const firstImagePart = firstContent.find((part) => part.type === "image");
+  const firstTextPart = firstContent.find((part) => part.type === "text");
+
+  // Save the first image
+  if (firstImagePart?.data) {
+    fs.writeFileSync(
+      "llama-initial.png",
+      Buffer.from(firstImagePart.data as string, "base64"),
+    );
+    console.log("First image saved as 'llama-initial.png'");
+  }
+
+  if (firstTextPart?.text) {
+    console.log("First response:", firstTextPart.text);
+  }
+
+  // Get the image_id from the response options for multi-turn
+  const imageId = firstResponse.message.options?.image_id;
+  console.log("Image ID for multi-turn:", imageId);
+
+  if (imageId) {
+    // Second turn: Modify the image using the image_id
+    console.log("\n=== Second Turn: Modify the image ===");
+    const secondResponse = await llm.chat({
+      messages: [
+        {
+          role: "user",
+          content:
+            "Generate an image of a cute tiny llama wearing a hat playing with a cat on a meadow",
+        },
+        {
+          role: "assistant",
+          content: firstContent,
+          options: { image_id: imageId },
+        },
+        {
+          role: "user",
+          content:
+            "Now add a rainbow in the background and make the llama's hat blue",
+        },
+      ],
+    });
+
+    const secondContent = secondResponse.message
+      .content as MessageContentDetail[];
+    const secondImagePart = secondContent.find((part) => part.type === "image");
+    const secondTextPart = secondContent.find((part) => part.type === "text");
+
+    // Save the modified image
+    if (secondImagePart?.data) {
+      fs.writeFileSync(
+        "llama-modified.png",
+        Buffer.from(secondImagePart.data as string, "base64"),
+      );
+      console.log("Modified image saved as 'llama-modified.png'");
+    }
+
+    if (secondTextPart?.text) {
+      console.log("Second response:", secondTextPart.text);
+    }
+  } else {
+    console.log("No image_id received, cannot perform multi-turn generation");
+  }
+}
+
+main().catch(console.error);
@@ -1,80 +1,80 @@
 {
  "name": "@llamaindex/examples",
-  "version": "0.3.27",
+  "version": "0.3.34",
  "private": true,
  "scripts": {
    "lint": "eslint .",
-    "start": "tsx ./starter.ts"
+    "start": "echo 'To get started, run `npx tsx <path to example>`'"
  },
  "dependencies": {
    "@ai-sdk/openai": "^1.0.5",
    "@azure/cosmos": "^4.1.1",
    "@azure/identity": "^4.4.1",
    "@azure/search-documents": "^12.1.0",
-    "@llamaindex/anthropic": "^0.3.15",
-    "@llamaindex/assemblyai": "^0.1.12",
-    "@llamaindex/astra": "^0.0.27",
-    "@llamaindex/azure": "^0.1.24",
-    "@llamaindex/bm25-retriever": "^0.0.2",
-    "@llamaindex/chroma": "^0.0.27",
-    "@llamaindex/clip": "^0.0.63",
-    "@llamaindex/cloud": "^4.0.18",
-    "@llamaindex/cohere": "^0.0.27",
-    "@llamaindex/core": "^0.6.13",
-    "@llamaindex/deepinfra": "^0.0.63",
-    "@llamaindex/deepseek": "^0.0.23",
-    "@llamaindex/discord": "^0.1.12",
-    "@llamaindex/elastic-search": "^0.1.13",
+    "@llamaindex/anthropic": "^0.3.20",
+    "@llamaindex/assemblyai": "^0.1.17",
+    "@llamaindex/astra": "^0.0.32",
+    "@llamaindex/azure": "^0.1.30",
+    "@llamaindex/bm25-retriever": "^0.0.7",
+    "@llamaindex/chroma": "^0.0.32",
+    "@llamaindex/clip": "^0.0.69",
+    "@llamaindex/cloud": "^4.0.27",
+    "@llamaindex/cohere": "^0.0.32",
+    "@llamaindex/core": "^0.6.18",
+    "@llamaindex/deepinfra": "^0.0.69",
+    "@llamaindex/deepseek": "^0.0.30",
+    "@llamaindex/discord": "^0.1.17",
+    "@llamaindex/elastic-search": "^0.1.18",
    "@llamaindex/env": "^0.1.30",
-    "@llamaindex/firestore": "^1.0.20",
-    "@llamaindex/fireworks": "^0.0.23",
-    "@llamaindex/google": "^0.3.12",
-    "@llamaindex/groq": "^0.0.79",
-    "@llamaindex/huggingface": "^0.1.17",
-    "@llamaindex/jinaai": "^0.0.23",
-    "@llamaindex/milvus": "^0.1.22",
-    "@llamaindex/mistral": "^0.1.13",
-    "@llamaindex/mixedbread": "^0.0.27",
-    "@llamaindex/mongodb": "^0.0.28",
-    "@llamaindex/node-parser": "^2.0.13",
-    "@llamaindex/notion": "^0.1.12",
-    "@llamaindex/ollama": "^0.1.13",
-    "@llamaindex/openai": "^0.4.7",
-    "@llamaindex/perplexity": "^0.0.20",
-    "@llamaindex/pinecone": "^0.1.13",
-    "@llamaindex/portkey-ai": "^0.0.55",
-    "@llamaindex/postgres": "^0.0.56",
-    "@llamaindex/qdrant": "^0.1.23",
-    "@llamaindex/readers": "^3.1.12",
-    "@llamaindex/replicate": "^0.0.55",
-    "@llamaindex/supabase": "^0.1.13",
-    "@llamaindex/together": "^0.0.23",
-    "@llamaindex/tools": "^0.1.3",
-    "@llamaindex/upstash": "^0.0.27",
-    "@llamaindex/vercel": "^0.1.13",
-    "@llamaindex/vllm": "^0.0.49",
-    "@llamaindex/voyage-ai": "^1.0.19",
-    "@llamaindex/weaviate": "^0.0.28",
-    "@llamaindex/workflow": "^1.1.13",
-    "@llamaindex/xai": "workspace:^0.0.10",
-    "@notionhq/client": "^2.2.15",
+    "@llamaindex/firestore": "^1.0.25",
+    "@llamaindex/fireworks": "^0.0.29",
+    "@llamaindex/google": "^0.3.17",
+    "@llamaindex/groq": "^0.0.85",
+    "@llamaindex/huggingface": "^0.1.23",
+    "@llamaindex/jinaai": "^0.0.29",
+    "@llamaindex/milvus": "^0.1.27",
+    "@llamaindex/mistral": "^0.1.18",
+    "@llamaindex/mixedbread": "^0.0.32",
+    "@llamaindex/mongodb": "^0.0.33",
+    "@llamaindex/node-parser": "^2.0.18",
+    "@llamaindex/notion": "^0.1.17",
+    "@llamaindex/ollama": "^0.1.18",
+    "@llamaindex/openai": "^0.4.13",
+    "@llamaindex/perplexity": "^0.0.26",
+    "@llamaindex/pinecone": "^0.1.18",
+    "@llamaindex/portkey-ai": "^0.0.60",
+    "@llamaindex/postgres": "^0.0.61",
+    "@llamaindex/qdrant": "^0.1.28",
+    "@llamaindex/readers": "^3.1.17",
+    "@llamaindex/replicate": "^0.0.60",
+    "@llamaindex/supabase": "^0.1.19",
+    "@llamaindex/together": "^0.0.29",
+    "@llamaindex/tools": "^0.1.8",
+    "@llamaindex/upstash": "^0.0.32",
+    "@llamaindex/vercel": "^0.1.18",
+    "@llamaindex/vllm": "^0.0.55",
+    "@llamaindex/voyage-ai": "^1.0.24",
+    "@llamaindex/weaviate": "^0.0.33",
+    "@llamaindex/workflow": "^1.1.19",
+    "@llamaindex/xai": "^0.0.16",
+    "@notionhq/client": "^4.0.0",
    "@pinecone-database/pinecone": "^4.0.0",
    "@vercel/postgres": "^0.10.0",
-    "ai": "^4.0.0",
+    "ai": "^4.3.17",
    "ajv": "^8.17.1",
    "commander": "^12.1.0",
-    "dotenv": "^16.4.5",
+    "dotenv": "^17.2.0",
    "js-tiktoken": "^1.0.14",
-    "llamaindex": "^0.11.13",
+    "llamaindex": "^0.11.23",
    "mongodb": "6.7.0",
    "postgres": "^3.4.4",
    "wikipedia": "^2.1.2",
-    "zod": "^3.25.67"
+    "zod": "^3.25.76"
  },
  "devDependencies": {
-    "@types/node": "^22.9.0",
-    "tsx": "^4.19.3",
-    "typescript": "^5.7.3"
+    "@types/node": "^24.0.13",
+    "tsx": "^4.20.3",
+    "typescript": "^5.8.3"
  },
  "stackblitz": {
    "startCommand": "npm start"
@@ -0,0 +1,2 @@
+packages:
+  - "**"
@@ -21,13 +21,14 @@
  },
  "dependencies": {
    "@llamaindex/cloud": "workspace:* || ^2.0.24",
-    "@llamaindex/readers": "workspace:* || ^1.0.25",
    "@llamaindex/excel": "workspace:*",
+    "@llamaindex/readers": "workspace:* || ^1.0.25",
+    "@notionhq/client": "^4.0.0",
    "llamaindex": "workspace:* || ^0.8.37"
  },
  "devDependencies": {
-    "@types/node": "^22.9.0",
-    "tsx": "^4.19.3",
-    "typescript": "^5.7.3"
+    "@types/node": "^24.0.13",
+    "tsx": "^4.20.3",
+    "typescript": "^5.8.3"
  }
 }
@@ -15,7 +15,7 @@ async function main() {
  const vectorStore = new QdrantVectorStore({
    url: process.env.QDRANT_URL,
    apiKey: process.env.QDRANT_API_KEY,
-    embeddingModel: embedding,
+    embedModel: embedding,
    collectionName: "gemini_test",
  });
  const storageContext = await storageContextFromDefaults({ vectorStore });
@@ -16,7 +16,7 @@ async function main() {
  const vectorStore = new QdrantVectorStore({
    url: process.env.QDRANT_URL,
    apiKey: process.env.QDRANT_API_KEY,
-    embeddingModel: embedding,
+    embedModel: embedding,
    collectionName: "jina_test",
  });
  const storageContext = await storageContextFromDefaults({ vectorStore });
@@ -4,7 +4,7 @@
  "scripts": {
    "clean": "find . -type d \\( -name .turbo -o -name node_modules -o -name dist -o -name .next -o -name lib \\) -exec rm -rf {} +",
    "build": "turbo run build --filter=\"./packages/*\" --filter=\"./packages/providers/**\"",
-    "dev": "turbo run dev --filter=\"./packages/*\" --filter=\"./packages/providers/**\"",
+    "dev": "turbo run dev --filter=\"./packages/*\" --filter=\"./packages/providers/**\" --concurrency=100",
    "format": "prettier --ignore-unknown --cache --check .",
    "format:write": "prettier --ignore-unknown --write .",
    "lint": "turbo run lint",
@@ -17,18 +17,19 @@
    "release-snapshot": "pnpm run build && changeset publish --tag snapshot",
    "new-version": "changeset version && pnpm format:write && pnpm run build",
    "new-snapshot": "pnpm run build && changeset version --snapshot",
-    "lint-staged": "lint-staged"
+    "lint-staged": "lint-staged",
+    "preinstall": "npx only-allow pnpm"
  },
  "devDependencies": {
    "@changesets/cli": "^2.27.5",
    "@eslint/js": "^9.25.0",
    "bunchee": "6.4.0",
-    "eslint": "9.22.0",
-    "eslint-config-next": "^15.1.0",
-    "eslint-config-prettier": "^9.1.0",
-    "eslint-config-turbo": "^2.3.3",
-    "eslint-plugin-react": "7.37.2",
-    "eslint-plugin-turbo": "^2.5.0",
+    "eslint": "9.30.1",
+    "eslint-config-next": "^15.3.5",
+    "eslint-config-prettier": "^10.1.5",
+    "eslint-config-turbo": "^2.5.4",
+    "eslint-plugin-react": "7.37.5",
+    "eslint-plugin-turbo": "^2.5.4",
    "globals": "^15.12.0",
    "husky": "^9.1.7",
    "lint-staged": "^15.2.11",
@@ -37,11 +38,16 @@
    "prettier-plugin-organize-imports": "^4.1.0",
    "prettier-plugin-tailwindcss": "^0.6.11",
    "turbo": "^2.4.4",
-    "typescript": "^5.7.3",
-    "typescript-eslint": "^8.18.0",
+    "typescript": "^5.8.3",
+    "typescript-eslint": "^8.36.0",
    "vitest": "^3.1.1"
  },
  "packageManager": "pnpm@10.8.1",
+  "pnpm": {
+    "overrides": {
+      "@notionhq/client": "4.0.0"
+    }
+  },
  "lint-staged": {
    "*.{js,jsx,ts,tsx}": [
      "eslint --fix",
@@ -1,5 +1,65 @@
 # @llamaindex/autotool

+## 8.0.23
+
+### Patch Changes
+
+- llamaindex@0.11.23
+
+## 8.0.22
+
+### Patch Changes
+
+- llamaindex@0.11.22
+
+## 8.0.21
+
+### Patch Changes
+
+- llamaindex@0.11.21
+
+## 8.0.20
+
+### Patch Changes
+
+- llamaindex@0.11.20
+
+## 8.0.19
+
+### Patch Changes
+
+- llamaindex@0.11.19
+
+## 8.0.18
+
+### Patch Changes
+
+- llamaindex@0.11.18
+
+## 8.0.17
+
+### Patch Changes
+
+- llamaindex@0.11.17
+
+## 8.0.16
+
+### Patch Changes
+
+- llamaindex@0.11.16
+
+## 8.0.15
+
+### Patch Changes
+
+- llamaindex@0.11.15
+
+## 8.0.14
+
+### Patch Changes
+
+- llamaindex@0.11.14
+
 ## 8.0.13

 ### Patch Changes
@@ -1,5 +1,75 @@
 # @llamaindex/autotool-01-node-example

+## 0.0.131
+
+### Patch Changes
+
+- llamaindex@0.11.23
+- @llamaindex/autotool@8.0.23
+
+## 0.0.130
+
+### Patch Changes
+
+- llamaindex@0.11.22
+- @llamaindex/autotool@8.0.22
+
+## 0.0.129
+
+### Patch Changes
+
+- llamaindex@0.11.21
+- @llamaindex/autotool@8.0.21
+
+## 0.0.128
+
+### Patch Changes
+
+- llamaindex@0.11.20
+- @llamaindex/autotool@8.0.20
+
+## 0.0.127
+
+### Patch Changes
+
+- llamaindex@0.11.19
+- @llamaindex/autotool@8.0.19
+
+## 0.0.126
+
+### Patch Changes
+
+- llamaindex@0.11.18
+- @llamaindex/autotool@8.0.18
+
+## 0.0.125
+
+### Patch Changes
+
+- llamaindex@0.11.17
+- @llamaindex/autotool@8.0.17
+
+## 0.0.124
+
+### Patch Changes
+
+- llamaindex@0.11.16
+- @llamaindex/autotool@8.0.16
+
+## 0.0.123
+
+### Patch Changes
+
+- llamaindex@0.11.15
+- @llamaindex/autotool@8.0.15
+
+## 0.0.122
+
+### Patch Changes
+
+- llamaindex@0.11.14
+- @llamaindex/autotool@8.0.14
+
 ## 0.0.121

 ### Patch Changes
@@ -8,10 +8,10 @@
    "openai": "^4.73.1"
  },
  "devDependencies": {
-    "tsx": "^4.19.3"
+    "tsx": "^4.20.3"
  },
  "scripts": {
    "start": "node --import tsx --import @llamaindex/autotool/node ./src/index.ts"
  },
-  "version": "0.0.121"
+  "version": "0.0.131"
 }
@@ -6,7 +6,7 @@
    "url": "git+https://github.com/run-llama/LlamaIndexTS.git",
    "directory": "packages/autotool"
  },
-  "version": "8.0.13",
+  "version": "8.0.23",
  "description": "auto transpile your JS function to LLM Agent compatible",
  "files": [
    "dist",
@@ -74,12 +74,12 @@
  "devDependencies": {
    "@swc/types": "^0.1.12",
    "@types/json-schema": "^7.0.15",
-    "@types/node": "^22.9.0",
+    "@types/node": "^24.0.13",
    "llamaindex": "workspace:*",
-    "next": "^15.3.0",
+    "next": "^15.3.3",
    "rollup": "^4.28.1",
-    "tsx": "^4.19.3",
-    "typescript": "^5.7.3",
+    "tsx": "^4.20.3",
+    "typescript": "^5.8.3",
    "vitest": "^2.1.5",
    "webpack": "^5.97.1"
  }
@@ -1,5 +1,70 @@
 # @llamaindex/cloud

+## 4.0.27
+
+### Patch Changes
+
+- Updated dependencies [f29799e]
+- Updated dependencies [7224c06]
+  - @llamaindex/core@0.6.18
+
+## 4.0.26
+
+### Patch Changes
+
+- Updated dependencies [38da40b]
+  - @llamaindex/core@0.6.17
+
+## 4.0.25
+
+### Patch Changes
+
+- 2967d57: Default to \_public agent url id
+- Updated dependencies [a8ec08c]
+  - @llamaindex/core@0.6.16
+
+## 4.0.24
+
+### Patch Changes
+
+- Updated dependencies [7ad3411]
+- Updated dependencies [5da5b3c]
+  - @llamaindex/core@0.6.15
+
+## 4.0.23
+
+### Patch Changes
+
+- a1b1598: fix: add generic types into agent data responses
+
+## 4.0.22
+
+### Patch Changes
+
+- d2be868: Bug fixes for new beta agent-data cloud API
+
+## 4.0.21
+
+### Patch Changes
+
+- 579ca0c: chore: bump sdk version
+
+## 4.0.20
+
+### Patch Changes
+
+- 48b0d88: fix: exports in `api` submodule
+- f185772: fix(cloud): missing file
+
+## 4.0.19
+
+### Patch Changes
+
+- 5a0ed1f: feat: init agent api on cloud sdk
+- 5a0ed1f: feat: init agent api on cloud sdk
+- Updated dependencies [8eeac33]
+  - @llamaindex/core@0.6.14
+
 ## 4.0.18

 ### Patch Changes
@@ -0,0 +1,8 @@
+{
+  "type": "module",
+  "main": "./dist/index.cjs",
+  "module": "./dist/index.js",
+  "types": "./dist/index.d.ts",
+  "exports": "./dist/index.js",
+  "private": true
+}
@@ -2519,7 +2519,7 @@
      "get": {
        "tags": ["Organizations"],
        "summary": "Get Organization Usage",
-        "description": "Get usage for a project",
+        "description": "Get usage for a specific organization.",
        "operationId": "get_organization_usage_api_v1_organizations__organization_id__usage_get",
        "security": [
          {
@@ -2535,15 +2535,8 @@
            "in": "path",
            "required": true,
            "schema": {
-              "anyOf": [
-                {
-                  "type": "string",
-                  "format": "uuid"
-                },
-                {
-                  "type": "null"
-                }
-              ],
+              "type": "string",
+              "format": "uuid",
              "title": "Organization Id"
            }
          },
@@ -11650,7 +11643,7 @@
    },
    "/api/v1/projects/{project_id}/agents": {
      "get": {
-        "tags": ["Llama Apps"],
+        "tags": ["Agent Deployments"],
        "summary": "List Deployments",
        "description": "List all deployments for a project.",
        "operationId": "list_deployments_api_v1_projects__project_id__agents_get",
@@ -11716,7 +11709,7 @@
    },
    "/api/v1/projects/{project_id}/agents:sync": {
      "post": {
-        "tags": ["Llama Apps"],
+        "tags": ["Agent Deployments"],
        "summary": "Sync Deployments",
        "description": "Sync deployments for a project.",
        "operationId": "sync_deployments_api_v1_projects__project_id__agents_sync_post",
@@ -11780,12 +11773,12 @@
        }
      }
    },
-    "/api/v1/billing/checkout-session": {
+    "/api/v1/classifier/classify": {
      "post": {
-        "tags": ["Billing"],
-        "summary": "Create Checkout Session",
-        "description": "Create a new checkout session.",
-        "operationId": "create_checkout_session_api_v1_billing_checkout_session_post",
+        "tags": ["Classifier", "Beta", "Classifier"],
+        "summary": "Classify Documents",
+        "description": "**[BETA]** Classify documents based on provided rules - simplified classification system.\n\n**This is a Beta feature** - API may change based on user feedback.\n\nThis endpoint supports:\n- Classifying new uploaded files\n- Classifying existing files by ID\n- Both new files and existing file IDs in one request\n\n## v0 Features:\n- **Simplified Rules**: Only `type` and `description` fields needed\n- **Matching Threshold**: Confidence-based classification with configurable threshold\n- **Smart Classification**: Filename heuristics + LLM content analysis\n- **Document Type Filtering**: Automatically filters out non-document file types\n- **Fast Processing**: Uses LlamaParse fast mode + GPT-4.1-nano\n- **Optimized Performance**: Parses each file only once for all rules\n\n## Simplified Scoring Logic:\n1. **Evaluate All Rules**: Compare document against all classification rules\n2. **Best Match Selection**: Return the highest scoring rule above matching_threshold\n3. **Unknown Classification**: Return as \"unknown\" if no rules score above threshold\n\nThis ensures optimal classification by:\n- Finding the best possible match among all rules\n- Avoiding false positives with confidence thresholds\n- Maximizing performance with single-pass file parsing\n\n## Rule Format:\n```json\n[\n  {\n    \"type\": \"invoice\",\n    \"description\": \"contains invoice number, line items, and total amount\"\n  },\n  {\n    \"type\": \"receipt\",\n    \"description\": \"purchase receipt with transaction details and payment info\"\n  }\n]\n```\n\n## Classification Process:\n1. **Metadata Heuristics** (configurable via API):\n   - **Document Type Filter**: Only process document file types (PDF, DOC, DOCX, RTF, TXT, ODT, Pages, HTML, XML, Markdown)\n   - **Filename Heuristics**: Check if rule type appears in filename\n   - **Content Analysis**: Parse document content once and use LLM for semantic matching against all rules\n2. **Result**: Returns type, confidence score, and matched rule information\n\n## API Parameters:\n- `matching_threshold` (0.1-0.99, default: 0.6): Minimum confidence threshold for acceptable matches\n- `enable_metadata_heuristic` (boolean, default: true): Enable metadata-based features\n\n## Supported Document Types:\n**Text Documents**: pdf, doc, docx, rtf, txt, odt, pages\n**Web Documents**: html, htm, xml\n**Markup**: md, markdown\n\n## Limits (Beta):\n- Maximum 100 files per request\n- Maximum 10 rules per request\n- Rule descriptions: 10-500 characters\n- Document types: 1-50 characters (alphanumeric, hyphens, underscores)\n\n**Beta Notice**: This API is subject to change. Please provide feedback!",
+        "operationId": "classify_documents_api_v1_classifier_classify_post",
        "security": [
          {
            "HTTPBearer": []
@@ -11795,6 +11788,23 @@
          }
        ],
        "parameters": [
+          {
+            "name": "project_id",
+            "in": "query",
+            "required": false,
+            "schema": {
+              "anyOf": [
+                {
+                  "type": "string",
+                  "format": "uuid"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "title": "Project Id"
+            }
+          },
          {
            "name": "organization_id",
            "in": "query",
@@ -11832,9 +11842,9 @@
        "requestBody": {
          "required": true,
          "content": {
-            "application/json": {
+            "multipart/form-data": {
              "schema": {
-                "$ref": "#/components/schemas/CheckoutSessionCreatePayload"
+                "$ref": "#/components/schemas/Body_classify_documents_api_v1_classifier_classify_post"
              }
            }
          }
@@ -11845,8 +11855,7 @@
            "content": {
              "application/json": {
                "schema": {
-                  "type": "string",
-                  "title": "Response Create Checkout Session Api V1 Billing Checkout Session Post"
+                  "$ref": "#/components/schemas/ClassifyResponse"
                }
              }
            }
@@ -11948,55 +11957,6 @@
        }
      }
    },
-    "/api/v1/billing/webhook": {
-      "post": {
-        "tags": ["Billing"],
-        "summary": "Stripe Webhook",
-        "description": "Stripe webhook endpoint.",
-        "operationId": "stripe_webhook_api_v1_billing_webhook_post",
-        "parameters": [
-          {
-            "name": "stripe-signature",
-            "in": "header",
-            "required": false,
-            "schema": {
-              "type": "string",
-              "title": "Stripe-Signature"
-            }
-          }
-        ],
-        "responses": {
-          "200": {
-            "description": "Successful Response",
-            "content": {
-              "application/json": {
-                "schema": {
-                  "type": "object",
-                  "additionalProperties": {
-                    "const": "success",
-                    "type": "string"
-                  },
-                  "propertyNames": {
-                    "const": "status"
-                  },
-                  "title": "Response Stripe Webhook Api V1 Billing Webhook Post"
-                }
-              }
-            }
-          },
-          "422": {
-            "description": "Validation Error",
-            "content": {
-              "application/json": {
-                "schema": {
-                  "$ref": "#/components/schemas/HTTPValidationError"
-                }
-              }
-            }
-          }
-        }
-      }
-    },
    "/api/v1/billing/downgrade-plan": {
      "post": {
        "tags": ["Billing"],
@@ -12165,64 +12125,6 @@
        }
      }
    },
-    "/api/v1/billing/metronome-webhook": {
-      "post": {
-        "tags": ["Billing"],
-        "summary": "Metronome Webhook",
-        "description": "Metronome webhook endpoint.",
-        "operationId": "metronome_webhook_api_v1_billing_metronome_webhook_post",
-        "parameters": [
-          {
-            "name": "Metronome-Webhook-Signature",
-            "in": "header",
-            "required": false,
-            "schema": {
-              "type": "string",
-              "title": "Metronome-Webhook-Signature"
-            }
-          },
-          {
-            "name": "Date",
-            "in": "header",
-            "required": false,
-            "schema": {
-              "type": "string",
-              "title": "Date"
-            }
-          }
-        ],
-        "responses": {
-          "200": {
-            "description": "Successful Response",
-            "content": {
-              "application/json": {
-                "schema": {
-                  "type": "object",
-                  "additionalProperties": {
-                    "const": "success",
-                    "type": "string"
-                  },
-                  "propertyNames": {
-                    "const": "status"
-                  },
-                  "title": "Response Metronome Webhook Api V1 Billing Metronome Webhook Post"
-                }
-              }
-            }
-          },
-          "422": {
-            "description": "Validation Error",
-            "content": {
-              "application/json": {
-                "schema": {
-                  "$ref": "#/components/schemas/HTTPValidationError"
-                }
-              }
-            }
-          }
-        }
-      }
-    },
    "/api/v1/billing/metronome/dashboard": {
      "get": {
        "tags": ["Billing"],
@@ -15768,12 +15670,12 @@
        }
      }
    },
-    "/api/v1/beta/agent-data/": {
+    "/api/v1/beta/agent-data": {
      "post": {
        "tags": ["Beta", "Agent Data"],
        "summary": "Create Agent Data",
        "description": "Create new agent data.",
-        "operationId": "create_agent_data_api_v1_beta_agent_data__post",
+        "operationId": "create_agent_data_api_v1_beta_agent_data_post",
        "security": [
          {
            "HTTPBearer": []
@@ -18883,6 +18785,73 @@
        "required": ["start_date", "end_date"],
        "title": "BillingPeriod"
      },
+      "Body_classify_documents_api_v1_classifier_classify_post": {
+        "properties": {
+          "rules_json": {
+            "type": "string",
+            "title": "Rules Json",
+            "description": "JSON string containing classifier rules"
+          },
+          "files": {
+            "anyOf": [
+              {
+                "items": {
+                  "type": "string",
+                  "format": "binary"
+                },
+                "type": "array"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Files"
+          },
+          "file_ids": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "File Ids",
+            "description": "Comma-separated list of existing file IDs"
+          },
+          "matching_threshold": {
+            "anyOf": [
+              {
+                "type": "number",
+                "maximum": 0.99,
+                "minimum": 0.1
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Matching Threshold",
+            "description": "Minimum confidence threshold for acceptable matches (0.1-0.99, default: 0.6)",
+            "default": 0.6
+          },
+          "enable_metadata_heuristic": {
+            "anyOf": [
+              {
+                "type": "boolean"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Enable Metadata Heuristic",
+            "description": "Enable metadata-based features (document filtering + content classification, default: true)",
+            "default": true
+          }
+        },
+        "type": "object",
+        "required": ["rules_json"],
+        "title": "Body_classify_documents_api_v1_classifier_classify_post"
+      },
      "Body_create_report_api_v1_reports__post": {
        "properties": {
          "name": {
@@ -19376,6 +19345,11 @@
            ],
            "title": "Max Pages"
          },
+          "merge_tables_across_pages_in_markdown": {
+            "type": "boolean",
+            "title": "Merge Tables Across Pages In Markdown",
+            "default": false
+          },
          "outlined_table_extraction": {
            "type": "boolean",
            "title": "Outlined Table Extraction",
@@ -19857,6 +19831,11 @@
            ],
            "title": "Max Pages"
          },
+          "merge_tables_across_pages_in_markdown": {
+            "type": "boolean",
+            "title": "Merge Tables Across Pages In Markdown",
+            "default": false
+          },
          "outlined_table_extraction": {
            "type": "boolean",
            "title": "Outlined Table Extraction",
@@ -20430,30 +20409,101 @@
        "type": "object",
        "title": "ChatInputParams"
      },
-      "CheckoutSessionCreatePayload": {
-        "properties": {
-          "success_url": {
-            "type": "string",
-            "minLength": 1,
-            "format": "uri",
-            "title": "Success Url"
-          },
-          "cancel_url": {
-            "type": "string",
-            "minLength": 1,
-            "format": "uri",
-            "title": "Cancel Url"
-          }
-        },
-        "type": "object",
-        "required": ["success_url", "cancel_url"],
-        "title": "CheckoutSessionCreatePayload"
-      },
      "ChunkMode": {
        "type": "string",
        "enum": ["PAGE", "DOCUMENT", "SECTION", "GROUPED_PAGES"],
        "title": "ChunkMode"
      },
+      "ClassificationResult": {
+        "properties": {
+          "file_id": {
+            "type": "string",
+            "format": "uuid",
+            "title": "File Id",
+            "description": "The ID of the classified file"
+          },
+          "type": {
+            "type": "string",
+            "title": "Type",
+            "description": "The assigned document type ('unknown' if no rules matched)",
+            "examples": ["invoice", "receipt", "contract", "unknown"]
+          },
+          "confidence": {
+            "type": "number",
+            "maximum": 1.0,
+            "minimum": 0.0,
+            "title": "Confidence",
+            "description": "Confidence score of the classification (0.0-1.0)"
+          },
+          "matched_rule": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Matched Rule",
+            "description": "Description of the rule that matched, or method used (e.g., 'auto: filename contains invoice')",
+            "examples": [
+              "contains invoice number, line items, and total",
+              "auto: filename contains 'invoice'",
+              null
+            ]
+          }
+        },
+        "type": "object",
+        "required": ["file_id", "type", "confidence", "matched_rule"],
+        "title": "ClassificationResult",
+        "description": "Result of classifying a single file.\n\nContains the classification outcome with confidence score and matched rule info."
+      },
+      "ClassifyResponse": {
+        "properties": {
+          "items": {
+            "items": {
+              "$ref": "#/components/schemas/ClassificationResult"
+            },
+            "type": "array",
+            "title": "Items",
+            "description": "The list of items."
+          },
+          "next_page_token": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Next Page Token",
+            "description": "A token, which can be sent as page_token to retrieve the next page. If this field is omitted, there are no subsequent pages."
+          },
+          "total_size": {
+            "anyOf": [
+              {
+                "type": "integer"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Total Size",
+            "description": "The total number of items available. This is only populated when specifically requested. The value may be an estimate and can be used for display purposes only."
+          },
+          "unknown_count": {
+            "type": "integer",
+            "minimum": 0.0,
+            "title": "Unknown Count",
+            "description": "Number of files that couldn't be classified"
+          }
+        },
+        "type": "object",
+        "required": ["items", "unknown_count"],
+        "title": "ClassifyResponse",
+        "description": "Response model for the classify endpoint following AIP-132 pagination standard.\n\nContains classification results with pagination support and summary statistics."
+      },
      "CloudAzStorageBlobDataSource": {
        "properties": {
          "supports_access_control": {
@@ -21941,6 +21991,7 @@
          },
          "query": {
            "type": "string",
+            "minLength": 1,
            "title": "Query",
            "description": "The query to retrieve against."
          }
@@ -22457,14 +22508,12 @@
          "version_metadata": {
            "anyOf": [
              {
-                "additionalProperties": true,
-                "type": "object"
+                "$ref": "#/components/schemas/DataSourceReaderVersionMetadata"
              },
              {
                "type": "null"
              }
            ],
-            "title": "Version Metadata",
            "description": "Version metadata for the data source"
          },
          "project_id": {
@@ -22570,6 +22619,24 @@
        "title": "DataSourceCreate",
        "description": "Schema for creating a data source."
      },
+      "DataSourceReaderVersionMetadata": {
+        "properties": {
+          "reader_version": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Reader Version",
+            "description": "The version of the reader to use for this data source."
+          }
+        },
+        "type": "object",
+        "title": "DataSourceReaderVersionMetadata"
+      },
      "DataSourceUpdate": {
        "properties": {
          "name": {
@@ -22841,6 +22908,7 @@
          },
          "query": {
            "type": "string",
+            "minLength": 1,
            "title": "Query",
            "description": "The query to retrieve against."
          },
@@ -23799,7 +23867,7 @@
      },
      "ExtractMode": {
        "type": "string",
-        "enum": ["FAST", "BALANCED", "PREMIUM", "MULTIMODAL", "ACCURATE"],
+        "enum": ["FAST", "BALANCED", "PREMIUM", "MULTIMODAL"],
        "title": "ExtractMode"
      },
      "ExtractModels": {
@@ -26210,6 +26278,19 @@
            "description": "Whether to try to extract outlined tables",
            "default": false
          },
+          "mergeTablesAcrossPagesInMarkdown": {
+            "anyOf": [
+              {
+                "type": "boolean"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Mergetablesacrosspagesinmarkdown",
+            "description": "Whether to merge tables across pages in markdown",
+            "default": false
+          },
          "saveImages": {
            "anyOf": [
              {
@@ -27070,6 +27151,7 @@
              "disable_image_extraction": false,
              "invalidate_cache": false,
              "outlined_table_extraction": false,
+              "merge_tables_across_pages_in_markdown": false,
              "output_pdf_of_document": false,
              "do_not_cache": false,
              "fast_mode": false,
@@ -27246,6 +27328,18 @@
            "title": "Outlined Table Extraction",
            "default": false
          },
+          "merge_tables_across_pages_in_markdown": {
+            "anyOf": [
+              {
+                "type": "boolean"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Merge Tables Across Pages In Markdown",
+            "default": false
+          },
          "output_pdf_of_document": {
            "anyOf": [
              {
@@ -29406,6 +29500,18 @@
            "title": "Outlined Table Extraction",
            "default": false
          },
+          "merge_tables_across_pages_in_markdown": {
+            "anyOf": [
+              {
+                "type": "boolean"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Merge Tables Across Pages In Markdown",
+            "default": false
+          },
          "output_pdf_of_document": {
            "anyOf": [
              {
@@ -31334,14 +31440,12 @@
          "version_metadata": {
            "anyOf": [
              {
-                "additionalProperties": true,
-                "type": "object"
+                "$ref": "#/components/schemas/DataSourceReaderVersionMetadata"
              },
              {
                "type": "null"
              }
            ],
-            "title": "Version Metadata",
            "description": "Version metadata for the data source"
          },
          "project_id": {
@@ -32129,12 +32233,6 @@
            "title": "Data Source Project File Changed",
            "description": "Whether the data source project file has changed",
            "default": false
-          },
-          "should_migrate_pipeline_file_to_external_file_id": {
-            "type": "boolean",
-            "title": "Should Migrate Pipeline File To External File Id",
-            "description": "Whether to migrate the pipeline file to the external file id",
-            "default": false
          }
        },
        "type": "object",
@@ -34239,19 +34337,6 @@
            "title": "Name",
            "description": "A name for the role."
          },
-          "organization_id": {
-            "anyOf": [
-              {
-                "type": "string",
-                "format": "uuid"
-              },
-              {
-                "type": "null"
-              }
-            ],
-            "title": "Organization Id",
-            "description": "The organization's ID."
-          },
          "permissions": {
            "items": {
              "$ref": "#/components/schemas/Permission"
@@ -34262,7 +34347,7 @@
          }
        },
        "type": "object",
-        "required": ["id", "name", "organization_id", "permissions"],
+        "required": ["id", "name", "permissions"],
        "title": "Role",
        "description": "Schema for a role."
      },
@@ -35134,19 +35219,13 @@
            "title": "Project Ids",
            "description": "The project ID scope."
          },
-          "role_id": {
-            "type": "string",
-            "format": "uuid",
-            "title": "Role Id",
-            "description": "The role's ID."
-          },
          "role": {
            "$ref": "#/components/schemas/Role",
            "description": "The role."
          }
        },
        "type": "object",
-        "required": ["id", "user_id", "organization_id", "role_id", "role"],
+        "required": ["id", "user_id", "organization_id", "role"],
        "title": "UserOrganizationRole",
        "description": "Schema for a user's role in an organization."
      },
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/cloud",
-  "version": "4.0.18",
+  "version": "4.0.27",
  "type": "module",
  "license": "MIT",
  "scripts": {
@@ -11,10 +11,23 @@
  "files": [
    "openapi.json",
    "./api",
-    "./reader"
+    "./reader",
+    "./parse",
+    "./beta/agent"
  ],
  "exports": {
    "./openapi.json": "./openapi.json",
+    "./beta/agent": {
+      "require": {
+        "types": "./beta/agent/dist/index.d.cts",
+        "default": "./beta/agent/dist/index.cjs"
+      },
+      "import": {
+        "types": "./beta/agent/dist/index.d.ts",
+        "default": "./beta/agent/dist/index.js"
+      },
+      "default": "./beta/agent/dist/index.js"
+    },
    "./api": {
      "require": {
        "types": "./api/dist/index.d.cts",
@@ -79,6 +92,6 @@
  },
  "dependencies": {
    "p-retry": "^6.2.1",
-    "zod": "^3.25.67"
+    "zod": "^3.25.76"
  }
 }
@@ -0,0 +1,329 @@
+import { createClient, createConfig } from "@hey-api/client-fetch";
+import { getEnv } from "@llamaindex/env";
+import {
+  aggregateAgentDataApiV1BetaAgentDataAggregatePost,
+  createAgentDataApiV1BetaAgentDataPost,
+  deleteAgentDataApiV1BetaAgentDataItemIdDelete,
+  getAgentDataApiV1BetaAgentDataItemIdGet,
+  searchAgentDataApiV1BetaAgentDataSearchPost,
+  updateAgentDataApiV1BetaAgentDataItemIdPut,
+  type AgentData,
+  type AggregateGroup,
+} from "../../client";
+import type {
+  AggregateAgentDataOptions,
+  SearchAgentDataOptions,
+  TypedAgentData,
+  TypedAgentDataItems,
+  TypedAggregateGroup,
+  TypedAggregateGroupItems,
+} from "./types";
+
+/**
+ * Async client for agent data operations
+ */
+export class AgentClient<T = unknown> {
+  private client: ReturnType<typeof createClient>;
+  private baseUrl: string;
+  private headers: Record<string, string>;
+  private collection: string;
+  private agentUrlId: string;
+
+  constructor({
+    apiKey = getEnv("LLAMA_CLOUD_API_KEY"),
+    baseUrl = "https://api.cloud.llamaindex.ai/",
+    collection = "default",
+    agentUrlId = "_public",
+  }: {
+    apiKey?: string;
+    baseUrl?: string;
+    collection?: string;
+    agentUrlId?: string;
+  }) {
+    this.baseUrl = baseUrl;
+
+    this.headers = {
+      "X-SDK-Name": "llamaindex-ts",
+      ...(apiKey && { Authorization: `Bearer ${apiKey}` }),
+    };
+
+    this.client = createClient(
+      createConfig({
+        baseUrl: this.baseUrl,
+        headers: this.headers,
+      }),
+    );
+
+    this.collection = collection;
+    this.agentUrlId = agentUrlId;
+  }
+
+  /**
+   * Create new agent data
+   */
+  async createItem(data: T): Promise<TypedAgentData<T>> {
+    const response = await createAgentDataApiV1BetaAgentDataPost({
+      throwOnError: true,
+      body: {
+        agent_slug: this.agentUrlId,
+        collection: this.collection,
+        data: data as Record<string, unknown>,
+      },
+      client: this.client,
+    });
+
+    return this.transformResponse(response.data);
+  }
+
+  /**
+   * Get agent data by ID
+   */
+  async getItem(id: string): Promise<TypedAgentData<T> | null> {
+    try {
+      const response = await getAgentDataApiV1BetaAgentDataItemIdGet({
+        throwOnError: true,
+        path: { item_id: id },
+        client: this.client,
+      });
+
+      return this.transformResponse(response.data);
+    } catch (error) {
+      if (
+        error instanceof Error &&
+        "response" in error &&
+        (error as { response?: { status?: number } }).response?.status === 404
+      ) {
+        return null;
+      }
+      throw error;
+    }
+  }
+
+  /**
+   * Update agent data
+   */
+  async updateItem(id: string, data: T): Promise<TypedAgentData<T>> {
+    const response = await updateAgentDataApiV1BetaAgentDataItemIdPut({
+      throwOnError: true,
+      path: { item_id: id },
+      body: {
+        data: data as Record<string, unknown>,
+      },
+      client: this.client,
+    });
+
+    return this.transformResponse(response.data);
+  }
+
+  /**
+   * Delete agent data
+   */
+  async deleteItem(id: string): Promise<void> {
+    await deleteAgentDataApiV1BetaAgentDataItemIdDelete({
+      throwOnError: true,
+      path: { item_id: id },
+      client: this.client,
+    });
+  }
+
+  /**
+   * Search agent data
+   */
+  async search(
+    options: SearchAgentDataOptions,
+  ): Promise<TypedAgentDataItems<T>> {
+    const response = await searchAgentDataApiV1BetaAgentDataSearchPost({
+      throwOnError: true,
+      body: {
+        agent_slug: this.agentUrlId,
+        ...(this.collection !== undefined && {
+          collection: this.collection,
+        }),
+        ...(options.filter !== undefined && { filter: options.filter }),
+        ...(options.orderBy !== undefined && { order_by: options.orderBy }),
+        ...(options.pageSize !== undefined && { page_size: options.pageSize }),
+        ...(options.offset !== undefined && { offset: options.offset }),
+        ...(options.includeTotal !== undefined && {
+          include_total: options.includeTotal,
+        }),
+      },
+      client: this.client,
+    });
+
+    const result: TypedAgentDataItems<T> = {
+      items: response.data.items.map((item: AgentData) =>
+        this.transformResponse(item),
+      ),
+    };
+
+    if (
+      response.data.total_size !== null &&
+      response.data.total_size !== undefined
+    ) {
+      result.totalSize = response.data.total_size;
+    }
+
+    if (
+      response.data.next_page_token !== null &&
+      response.data.next_page_token !== undefined
+    ) {
+      result.nextPageToken = response.data.next_page_token;
+    }
+
+    return result;
+  }
+
+  /**
+   * Aggregate agent data into groups
+   */
+  async aggregate(
+    options: AggregateAgentDataOptions,
+  ): Promise<TypedAggregateGroupItems<T>> {
+    const response = await aggregateAgentDataApiV1BetaAgentDataAggregatePost({
+      throwOnError: true,
+      body: {
+        agent_slug: this.agentUrlId,
+        ...(this.collection !== undefined && {
+          collection: this.collection,
+        }),
+        ...(options.filter !== undefined && { filter: options.filter }),
+        ...(options.groupBy !== undefined && { group_by: options.groupBy }),
+        ...(options.count !== undefined && { count: options.count }),
+        ...(options.first !== undefined && { first: options.first }),
+        ...(options.orderBy !== undefined && { order_by: options.orderBy }),
+        ...(options.offset !== undefined && { offset: options.offset }),
+        ...(options.pageSize !== undefined && { page_size: options.pageSize }),
+      },
+      client: this.client,
+    });
+
+    const result: TypedAggregateGroupItems<T> = {
+      items: response.data.items.map((item) =>
+        this.transformAggregateResponse(item),
+      ),
+    };
+
+    if (
+      response.data.total_size !== null &&
+      response.data.total_size !== undefined
+    ) {
+      result.totalSize = response.data.total_size;
+    }
+
+    if (
+      response.data.next_page_token !== null &&
+      response.data.next_page_token !== undefined
+    ) {
+      result.nextPageToken = response.data.next_page_token;
+    }
+
+    return result;
+  }
+
+  /**
+   * Transform API response to typed data
+   */
+  private transformResponse(data: AgentData): TypedAgentData<T> {
+    const result: TypedAgentData<T> = {
+      id: data.id!,
+      agentUrlId: data.agent_slug,
+      data: data.data as T,
+      createdAt: new Date(data.created_at!),
+      updatedAt: new Date(data.updated_at!),
+    };
+
+    if (data.collection !== undefined) {
+      result.collection = data.collection;
+    }
+
+    return result;
+  }
+
+  /**
+   * Transform API aggregate response to typed data
+   */
+  private transformAggregateResponse(
+    data: AggregateGroup,
+  ): TypedAggregateGroup<T> {
+    const result: TypedAggregateGroup<T> = {
+      groupKey: data.group_key,
+    };
+
+    if (data.count !== null && data.count !== undefined) {
+      result.count = data.count;
+    }
+
+    if (data.first_item !== null && data.first_item !== undefined) {
+      result.firstItem = data.first_item as T;
+    }
+
+    return result;
+  }
+}
+
+export interface AgentDataClientOptions<T = unknown> {
+  /** API key for the client */
+  apiKey?: string;
+  /** Base URL for the client */
+  /** Base URL of the llama cloud api */
+  baseUrl?: string;
+  /** If running in an agent runtime, optionally provide the window url to infer the agent url id */
+  windowUrl?: string;
+  /** Agent URL ID for the client, if not provided, it will be inferred from the window url, or fall back to "default" */
+  agentUrlId?: string;
+  /** Collection name for the client, defaults to "default" */
+  collection?: string;
+}
+/**
+ * Create a new AsyncAgentDataClient instance. Does it's best to infer an agent url id from environment.
+ * Pass in the window url and/or env to infer the agent url id from them.
+ * @param options - The options for the client
+ * @returns A new AgentClient instance
+ */
+export function createAgentDataClient<T = unknown>({
+  apiKey,
+  baseUrl,
+  windowUrl,
+  env,
+  agentUrlId,
+  collection = "default",
+}: {
+  apiKey?: string;
+  baseUrl?: string;
+  windowUrl?: string;
+  env?: Record<string, string>;
+  agentUrlId?: string;
+  collection?: string;
+} = {}): AgentClient<T> {
+  if (env && !agentUrlId) {
+    agentUrlId =
+      env.LLAMA_DEPLOY_DEPLOYMENT_NAME ||
+      env.NEXT_PUBLIC_LLAMA_DEPLOY_DEPLOYMENT_NAME ||
+      env.VITE_LLAMA_DEPLOY_DEPLOYMENT_NAME;
+  }
+  if (windowUrl && !agentUrlId) {
+    try {
+      const url = new URL(windowUrl);
+      const path = url.pathname;
+      const isLocalhost = // local agents should default to _public, otherwise a full deployment is required
+        url.hostname.includes("localhost") ||
+        url.hostname.includes("127.0.0.1");
+      if (path.startsWith("/deployments/") && !isLocalhost) {
+        // /deployments/<agent-url-id>/ui/ -> ["", "deployments", "<agent-url-id>", "ui"]
+        agentUrlId = path.split("/")[2];
+      }
+    } catch (error) {
+      console.warn(
+        "Failed to infer agent url id from window url, falling back to default",
+        error,
+      );
+    }
+  }
+
+  return new AgentClient({
+    ...(apiKey && { apiKey }),
+    ...(baseUrl && { baseUrl }),
+    ...(agentUrlId && { agentUrlId }),
+    collection,
+  });
+}
@@ -0,0 +1,16 @@
+export { AgentClient, createAgentDataClient } from "./client";
+
+export type {
+  AggregateAgentDataOptions,
+  ComparisonOperator,
+  ExtractedData,
+  FilterOperation,
+  SearchAgentDataOptions,
+  StatusType,
+  TypedAgentData,
+  TypedAgentDataItems,
+  TypedAggregateGroup,
+  TypedAggregateGroupItems,
+} from "./types";
+
+export { StatusType as StatusTypeEnum } from "./types";
@@ -0,0 +1,138 @@
+import type { FilterOperation as RawFilterOperation } from "../../client/types.gen";
+/**
+ * Status types for agent data processing
+ */
+export const StatusType = {
+  ERROR: "error",
+  ACCEPTED: "accepted",
+  REJECTED: "rejected",
+  PENDING_REVIEW: "pending_review",
+} as const;
+
+export type StatusType = (typeof StatusType)[keyof typeof StatusType];
+
+export const ComparisonOperator = {
+  GT: "gt",
+  GTE: "gte",
+  LT: "lt",
+  LTE: "lte",
+  EQ: "eq",
+  INCLUDES: "includes",
+} as const;
+
+export type ComparisonOperator =
+  (typeof ComparisonOperator)[keyof typeof ComparisonOperator];
+
+/**
+ * Filter operation for searching/filtering agent data
+ */
+export type FilterOperation = RawFilterOperation;
+
+/**
+ * Base extracted data interface
+ */
+export interface ExtractedData<T = unknown> {
+  /** The original data that was extracted from the document. For tracking changes. Should not be updated. */
+  original_data: T;
+  /** The latest state of the data. Will differ if data has been updated. */
+  data?: T;
+  /** The status of the extracted data. Prefer to use the StatusType values, but any string is allowed. */
+  status: StatusType | string;
+  /** Confidence scores, if any, for each primitive field in the original_data data. */
+  confidence?: Record<string, unknown>;
+  /** The ID of the file that was used to extract the data. */
+  file_id?: string;
+  /** The name of the file that was used to extract the data. */
+  file_name?: string;
+  /** The hash of the file that was used to extract the data. */
+  file_hash?: string;
+  /** Additional metadata about the extracted data, such as errors, tokens, etc. */
+  metadata?: Record<string, unknown>;
+}
+
+/**
+ * TypedAgentData interface for typed agent data
+ */
+export interface TypedAgentData<T = unknown> {
+  /** The unique ID of the agent data record. */
+  id: string;
+  /** The ID of the agent that created the data. */
+  agentUrlId: string;
+  /** The collection of the agent data. */
+  collection?: string;
+  /** The data of the agent data. Usually an ExtractedData&lt;SomeOtherType&gt; */
+  data: T;
+  /** The date and time the data was created. */
+  createdAt: Date;
+  /** The date and time the data was last updated. */
+  updatedAt: Date;
+}
+
+/**
+ * Paginated response of typed agent data items
+ */
+export interface TypedAgentDataItems<T = unknown> {
+  items: TypedAgentData<T>[];
+  totalSize?: number;
+  nextPageToken?: string;
+}
+
+/**
+ * Options for listing agent data
+ */
+export interface SearchAgentDataOptions {
+  /** Filter options for the list. */
+  filter?: Record<string, FilterOperation>;
+  /** Order by options for the list. */
+  orderBy?: string;
+  /** Page size for the list. */
+  pageSize?: number;
+  /** Offset for the list. */
+  offset?: number;
+  /**
+   * Whether to include the total number of items in the response.
+   * Should use only for first request to build total pagination, and not subsequent requests.
+   */
+  includeTotal?: boolean;
+}
+
+/**
+ * Options for aggregating agent data
+ */
+export interface AggregateAgentDataOptions {
+  /** Filter options for the aggregation. */
+  filter?: Record<string, FilterOperation>;
+  /** Fields to group by. */
+  groupBy?: string[];
+  /** Whether to count the number of items in each group. */
+  count?: boolean;
+  /** Whether to return the first item in each group. */
+  first?: boolean;
+  /** Order by options for the aggregation. */
+  orderBy?: string;
+  /** Offset for the aggregation. */
+  offset?: number;
+  /** Page size for the aggregation. */
+  pageSize?: number;
+}
+
+/**
+ * Single aggregation group result
+ */
+export interface TypedAggregateGroup<T = unknown> {
+  /** The group key values */
+  groupKey: Record<string, unknown>;
+  /** Count of items in the group */
+  count?: number;
+  /** First item in the group */
+  firstItem?: T;
+}
+
+/**
+ * Paginated response of aggregated agent data
+ */
+export interface TypedAggregateGroupItems<T = unknown> {
+  items: TypedAggregateGroup<T>[];
+  totalSize?: number;
+  nextPageToken?: string;
+}
@@ -179,6 +179,7 @@ export class LlamaParseReader extends FileReader {
  page_header_suffix?: string | undefined;
  page_footer_prefix?: string | undefined;
  page_footer_suffix?: string | undefined;
+  merge_tables_across_pages_in_markdown?: boolean | undefined;

  constructor(
    params: Partial<Omit<LlamaParseReader, "language" | "apiKey">> & {
@@ -368,6 +369,8 @@ export class LlamaParseReader extends FileReader {
      page_header_suffix: this.page_header_suffix,
      page_footer_prefix: this.page_footer_prefix,
      page_footer_suffix: this.page_footer_suffix,
+      merge_tables_across_pages_in_markdown:
+        this.merge_tables_across_pages_in_markdown,
    } satisfies {
      [Key in keyof BodyUploadFileApiParsingUploadPost]-?:
        | BodyUploadFileApiParsingUploadPost[Key]
@@ -0,0 +1,770 @@
+# @llamaindex/community
+
+## 0.0.100
+
+### Patch Changes
+
+- Updated dependencies [f29799e]
+- Updated dependencies [7224c06]
+  - @llamaindex/core@0.6.18
+
+## 0.0.99
+
+### Patch Changes
+
+- c65a2dc: Deprecate community package and link to AWS package
+
+## 0.0.98
+
+### Patch Changes
+
+- Updated dependencies [9b2e25a]
+  - @llamaindex/core@0.6.4
+  - @llamaindex/env@0.1.30
+
+## 0.0.97
+
+### Patch Changes
+
+- Updated dependencies [3ee8c83]
+  - @llamaindex/core@0.6.3
+
+## 0.0.96
+
+### Patch Changes
+
+- e9bf442: fix: update the tool call schema for nova
+
+## 0.0.95
+
+### Patch Changes
+
+- 411dcea: Add Nova Premier to AWS Nova models. Add EU endpoints
+
+## 0.0.94
+
+### Patch Changes
+
+- Updated dependencies [9c63f3f]
+  - @llamaindex/core@0.6.2
+
+## 0.0.93
+
+### Patch Changes
+
+- Updated dependencies [1b6f368]
+- Updated dependencies [eaf326e]
+  - @llamaindex/core@0.6.1
+
+## 0.0.92
+
+### Patch Changes
+
+- 1325178: fix: stringify all tool results for anthropic on bedrock
+
+## 0.0.91
+
+### Patch Changes
+
+- 5189b44: fix: add retry handling logic to parser reader and fix lint issues
+- 3fd4cc3: feat: use google's new gen ai library to support multimodal output
+- Updated dependencies [21bebfc]
+- Updated dependencies [93bc0ff]
+- Updated dependencies [91a18e7]
+- Updated dependencies [5189b44]
+  - @llamaindex/core@0.6.0
+
+## 0.0.90
+
+### Patch Changes
+
+- Updated dependencies [40ee761]
+  - @llamaindex/core@0.5.8
+
+## 0.0.89
+
+### Patch Changes
+
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+
+## 0.0.88
+
+### Patch Changes
+
+- e28c29d: Added Llama 3.3 70B Instruct support
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+
+## 0.0.87
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+
+## 0.0.86
+
+### Patch Changes
+
+- Updated dependencies [ad3c7f1]
+  - @llamaindex/core@0.5.4
+
+## 0.0.85
+
+### Patch Changes
+
+- 1914b52: Added Claude 3.7 Sonnet support
+- Updated dependencies [cb021e7]
+  - @llamaindex/core@0.5.3
+
+## 0.0.84
+
+### Patch Changes
+
+- Updated dependencies [d952e68]
+  - @llamaindex/core@0.5.2
+
+## 0.0.83
+
+### Patch Changes
+
+- Updated dependencies [cc50c9c]
+  - @llamaindex/env@0.1.28
+  - @llamaindex/core@0.5.1
+
+## 0.0.82
+
+### Patch Changes
+
+- Updated dependencies [6a4a737]
+- Updated dependencies [d924c63]
+  - @llamaindex/core@0.5.0
+
+## 0.0.81
+
+### Patch Changes
+
+- 1c908fd: Revert previous release (not working with CJS)
+- Updated dependencies [1c908fd]
+  - @llamaindex/core@0.4.23
+  - @llamaindex/env@0.1.27
+
+## 0.0.80
+
+### Patch Changes
+
+- cb608b5: fix: bundle output incorrect
+- Updated dependencies [cb608b5]
+  - @llamaindex/core@0.4.22
+  - @llamaindex/env@0.1.26
+
+## 0.0.79
+
+### Patch Changes
+
+- Updated dependencies [9456616]
+- Updated dependencies [1931bbc]
+  - @llamaindex/core@0.4.21
+
+## 0.0.78
+
+### Patch Changes
+
+- Updated dependencies [d211b7a]
+  - @llamaindex/core@0.4.20
+
+## 0.0.77
+
+### Patch Changes
+
+- 24caf93: fix: added inference profile mapping for nova models"
+- Updated dependencies [a9b5b99]
+  - @llamaindex/core@0.4.19
+
+## 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
+
+- Updated dependencies [9c73f0a]
+  - @llamaindex/core@0.4.1
+
+## 0.0.57
+
+### Patch Changes
+
+- Updated dependencies [359fd33]
+- Updated dependencies [efb7e1b]
+- Updated dependencies [98ba1e7]
+- Updated dependencies [620c63c]
+  - @llamaindex/core@0.4.0
+
+## 0.0.56
+
+### Patch Changes
+
+- Updated dependencies [60b185f]
+  - @llamaindex/core@0.3.7
+
+## 0.0.55
+
+### Patch Changes
+
+- Updated dependencies [691c5bc]
+  - @llamaindex/core@0.3.6
+
+## 0.0.54
+
+### Patch Changes
+
+- Updated dependencies [fa60fc6]
+  - @llamaindex/env@0.1.16
+  - @llamaindex/core@0.3.5
+
+## 0.0.53
+
+### Patch Changes
+
+- Updated dependencies [e2a0876]
+  - @llamaindex/core@0.3.4
+
+## 0.0.52
+
+### Patch Changes
+
+- a5a75f6: feat: added sonnet 3.5 v2
+
+## 0.0.51
+
+### Patch Changes
+
+- Updated dependencies [0493f67]
+  - @llamaindex/core@0.3.3
+
+## 0.0.50
+
+### Patch Changes
+
+- Updated dependencies [4ba2cfe]
+  - @llamaindex/env@0.1.15
+  - @llamaindex/core@0.3.2
+
+## 0.0.49
+
+### Patch Changes
+
+- a75af83: refactor: move some llm and embedding to single package
+- Updated dependencies [ae49ff4]
+- Updated dependencies [a75af83]
+  - @llamaindex/env@0.1.14
+  - @llamaindex/core@0.3.1
+
+## 0.0.48
+
+### Patch Changes
+
+- Updated dependencies [1364e8e]
+- Updated dependencies [96fc69c]
+  - @llamaindex/core@0.3.0
+
+## 0.0.47
+
+### Patch Changes
+
+- Updated dependencies [5f67820]
+  - @llamaindex/core@0.2.12
+
+## 0.0.46
+
+### Patch Changes
+
+- Updated dependencies [ee697fb]
+  - @llamaindex/core@0.2.11
+
+## 0.0.45
+
+### Patch Changes
+
+- Updated dependencies [3489e7d]
+- Updated dependencies [468bda5]
+  - @llamaindex/core@0.2.10
+
+## 0.0.44
+
+### Patch Changes
+
+- Updated dependencies [b17d439]
+  - @llamaindex/core@0.2.9
+
+## 0.0.43
+
+### Patch Changes
+
+- 2774e80: feat: added meta3.2 support via Bedrock including vision, tool call and inference region support
+
+## 0.0.42
+
+### Patch Changes
+
+- df441e2: fix: consoleLogger is missing from `@llamaindex/env`
+- Updated dependencies [df441e2]
+  - @llamaindex/core@0.2.8
+  - @llamaindex/env@0.1.13
+
+## 0.0.41
+
+### Patch Changes
+
+- Updated dependencies [6cce3b1]
+  - @llamaindex/core@0.2.7
+
+## 0.0.40
+
+### Patch Changes
+
+- 50e6b57: feat: add Amazon Bedrock Retriever
+- Updated dependencies [8b7fdba]
+  - @llamaindex/core@0.2.6
+
+## 0.0.39
+
+### Patch Changes
+
+- Updated dependencies [d902cc3]
+  - @llamaindex/core@0.2.5
+
+## 0.0.38
+
+### Patch Changes
+
+- Updated dependencies [b48bcc3]
+  - @llamaindex/core@0.2.4
+  - @llamaindex/env@0.1.12
+
+## 0.0.37
+
+### Patch Changes
+
+- Updated dependencies [2cd1383]
+  - @llamaindex/core@0.2.3
+
+## 0.0.36
+
+### Patch Changes
+
+- Updated dependencies [749b43a]
+  - @llamaindex/core@0.2.2
+
+## 0.0.35
+
+### Patch Changes
+
+- Updated dependencies [ac07e3c]
+- Updated dependencies [70ccb4a]
+- Updated dependencies [1a6137b]
+- Updated dependencies [ac07e3c]
+  - @llamaindex/core@0.2.1
+  - @llamaindex/env@0.1.11
+
+## 0.0.34
+
+### Patch Changes
+
+- Updated dependencies [11feef8]
+  - @llamaindex/core@0.2.0
+
+## 0.0.33
+
+### Patch Changes
+
+- Updated dependencies [711c814]
+  - @llamaindex/core@0.1.12
+
+## 0.0.32
+
+### Patch Changes
+
+- Updated dependencies [4648da6]
+  - @llamaindex/env@0.1.10
+  - @llamaindex/core@0.1.11
+
+## 0.0.31
+
+### Patch Changes
+
+- Updated dependencies [0148354]
+  - @llamaindex/core@0.1.10
+
+## 0.0.30
+
+### Patch Changes
+
+- Updated dependencies [e27e7dd]
+  - @llamaindex/core@0.1.9
+
+## 0.0.29
+
+### Patch Changes
+
+- 58abc57: fix: align version
+- Updated dependencies [58abc57]
+  - @llamaindex/core@0.1.8
+  - @llamaindex/env@0.1.9
+
+## 0.0.28
+
+### Patch Changes
+
+- Updated dependencies [04b2f8e]
+  - @llamaindex/core@0.1.7
+
+## 0.0.27
+
+### Patch Changes
+
+- Updated dependencies [0452af9]
+  - @llamaindex/core@0.1.6
+
+## 0.0.26
+
+### Patch Changes
+
+- 224d507: fix: prevent tool calling getting mixed with conversation
+- 376d29a: feat: added tool calling and agent support for llama3.1 504B
+
+## 0.0.25
+
+### Patch Changes
+
+- Updated dependencies [91d02a4]
+  - @llamaindex/core@0.1.5
+
+## 0.0.24
+
+### Patch Changes
+
+- 3d9a802: feat: added llama 3.1
+- Updated dependencies [15962b3]
+  - @llamaindex/core@0.1.4
+
+## 0.0.23
+
+### Patch Changes
+
+- Updated dependencies [6cf6ae6]
+  - @llamaindex/core@0.1.3
+
+## 0.0.22
+
+### Patch Changes
+
+- Updated dependencies [b974eea]
+  - @llamaindex/core@0.1.2
+
+## 0.0.21
+
+### Patch Changes
+
+- Updated dependencies [b3681bf]
+  - @llamaindex/core@0.1.1
+
+## 0.0.20
+
+### Patch Changes
+
+- 56746c2: fix: llama3 patched to handle empty content (can happen with system) and added max tokens export
+
+## 0.0.19
+
+### Patch Changes
+
+- 16ef5dd: refactor: depends on core pacakge instead of llamaindex
+- Updated dependencies [16ef5dd]
+- Updated dependencies [16ef5dd]
+  - @llamaindex/core@0.1.0
+
+## 0.0.18
+
+### Patch Changes
+
+- llamaindex@0.4.14
+
+## 0.0.17
+
+### Patch Changes
+
+- Updated dependencies [e8f8bea]
+- Updated dependencies [304484b]
+  - llamaindex@0.4.13
+
+## 0.0.16
+
+### Patch Changes
+
+- f326ab8: chore: bump version
+- Updated dependencies [f326ab8]
+  - llamaindex@0.4.12
+
+## 0.0.15
+
+### Patch Changes
+
+- Updated dependencies [8bf5b4a]
+  - llamaindex@0.4.11
+
+## 0.0.14
+
+### Patch Changes
+
+- Updated dependencies [7dce3d2]
+  - llamaindex@0.4.10
+
+## 0.0.13
+
+### Patch Changes
+
+- Updated dependencies [3a96a48]
+  - llamaindex@0.4.9
+
+## 0.0.12
+
+### Patch Changes
+
+- Updated dependencies [83ebdfb]
+  - llamaindex@0.4.8
+
+## 0.0.11
+
+### Patch Changes
+
+- Updated dependencies [41fe871]
+- Updated dependencies [321c39d]
+- Updated dependencies [f7f1af0]
+  - llamaindex@0.4.7
+
+## 0.0.10
+
+### Patch Changes
+
+- Updated dependencies [1feb23b]
+- Updated dependencies [08c55ec]
+  - llamaindex@0.4.6
+
+## 0.0.9
+
+### Patch Changes
+
+- Updated dependencies [6c3e5d0]
+  - llamaindex@0.4.5
+
+## 0.0.8
+
+### Patch Changes
+
+- Updated dependencies [42eb73a]
+  - llamaindex@0.4.4
+
+## 0.0.7
+
+### Patch Changes
+
+- Updated dependencies [2ef62a9]
+  - llamaindex@0.4.3
+
+## 0.0.6
+
+### Patch Changes
+
+- a87a4d1: feat: added tool support calling for Bedrock's Calude and general llm support for agents
+- Updated dependencies [a87a4d1]
+- Updated dependencies [0730140]
+  - llamaindex@0.4.2
+
+## 0.0.5
+
+### Patch Changes
+
+- ed467a9: Add model ids for Anthropic Claude 3.5 Sonnet model on Anthropic and Bedrock
+- Updated dependencies [3c47910]
+- Updated dependencies [ed467a9]
+- Updated dependencies [cba5406]
+  - llamaindex@0.4.1
+
+## 0.0.4
+
+### Patch Changes
+
+- b1a4a74: docs: updated Bedrock Opus region and added a basic README
+- Updated dependencies [436bc41]
+- Updated dependencies [a44e54f]
+- Updated dependencies [a51ed8d]
+- Updated dependencies [d3b635b]
+  - llamaindex@0.4.0
+
+## 0.0.3
+
+### Patch Changes
+
+- Updated dependencies [6bc5bdd]
+- Updated dependencies [bf25ff6]
+- Updated dependencies [e6d6576]
+  - llamaindex@0.3.17
+
+## 0.0.2
+
+### Patch Changes
+
+- 8832669: Community bedrock support added
+- Updated dependencies [11ae926]
+- Updated dependencies [631f000]
+- Updated dependencies [1378ec4]
+- Updated dependencies [6b1ded4]
+- Updated dependencies [4d4bd85]
+- Updated dependencies [24a9d1e]
+- Updated dependencies [45952de]
+- Updated dependencies [54230f0]
+- Updated dependencies [a29d835]
+- Updated dependencies [73819bf]
+  - llamaindex@0.3.16
@@ -0,0 +1,17 @@
+# @llamaindex/community
+
+AWS package for LlamaIndexTS, deprecated, use [@llamaindex/aws](https://www.npmjs.com/package/@llamaindex/aws) instead.
+
+## Current Features:
+
+- Bedrock support for Amazon Nova models Pro, Lite and Micro
+- Bedrock support for the Anthropic Claude Models [usage](https://ts.llamaindex.ai/docs/llamaindex/modules/llms/bedrock) including the latest Sonnet 3.5 v2 and Haiku 3.5
+- Bedrock support for the Meta LLama 2, 3, 3.1 and 3.2 Models [usage](https://ts.llamaindex.ai/docs/llamaindex/modules/llms/bedrock)
+- Meta LLama3.1 405b and Llama3.2 tool call support
+- Meta 3.2 11B and 90B vision support
+- Bedrock support for querying Knowledge Base
+- Bedrock: [Supported Regions and models for cross-region inference](https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference-support.html)
+
+## LICENSE
+
+MIT
@@ -0,0 +1,53 @@
+{
+  "name": "@llamaindex/community",
+  "description": "Community package for LlamaIndexTS",
+  "version": "0.0.100",
+  "type": "module",
+  "types": "dist/type/index.d.ts",
+  "main": "dist/cjs/index.js",
+  "exports": {
+    ".": {
+      "import": {
+        "types": "./dist/type/index.d.ts",
+        "default": "./dist/index.js"
+      },
+      "require": {
+        "types": "./dist/type/index.d.ts",
+        "default": "./dist/index.cjs"
+      }
+    },
+    "./llm/bedrock": {
+      "import": {
+        "types": "./dist/type/llm/bedrock.d.ts",
+        "default": "./dist/llm/bedrock/index.js"
+      },
+      "require": {
+        "types": "./dist/type/llm/bedrock.d.ts",
+        "default": "./dist/llm/bedrock/index.cjs"
+      }
+    }
+  },
+  "files": [
+    "dist",
+    "CHANGELOG.md",
+    "!**/*.tsbuildinfo"
+  ],
+  "repository": {
+    "type": "git",
+    "url": "git+https://github.com/run-llama/LlamaIndexTS.git",
+    "directory": "packages/community"
+  },
+  "scripts": {
+    "build": "bunchee",
+    "dev": "bunchee --watch"
+  },
+  "devDependencies": {
+    "@types/node": "^22.9.0"
+  },
+  "dependencies": {
+    "@aws-sdk/client-bedrock-agent-runtime": "^3.706.0",
+    "@aws-sdk/client-bedrock-runtime": "^3.706.0",
+    "@llamaindex/core": "workspace:*",
+    "@llamaindex/env": "workspace:*"
+  }
+}
@@ -0,0 +1,8 @@
+export {
+  BEDROCK_MODELS,
+  BEDROCK_MODEL_MAX_TOKENS,
+  Bedrock,
+  INFERENCE_BEDROCK_MODELS,
+  INFERENCE_TO_BEDROCK_MAP,
+} from "./llm/bedrock/index.js";
+export { AmazonKnowledgeBaseRetriever } from "./retrievers/bedrock.js";
@@ -0,0 +1,134 @@
+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> {
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  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 {
+    const 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),
+    };
+  }
+}
@@ -0,0 +1,5 @@
+import type { ConverseRequest, Message } from "@aws-sdk/client-bedrock-runtime";
+
+export type AmazonMessages = ConverseRequest["messages"];
+
+export type AmazonMessage = Message;
@@ -0,0 +1,141 @@
+import type {
+  ImageBlock,
+  ImageFormat,
+  Message,
+  Tool,
+} from "@aws-sdk/client-bedrock-runtime";
+import type {
+  BaseTool,
+  ChatMessage,
+  MessageContentDetail,
+  ToolCallLLMMessageOptions,
+} from "@llamaindex/core/llms";
+import { extractDataUrlComponents } from "../utils";
+
+import type { JSONObject } from "@llamaindex/core/global";
+import { mapMessageContentToMessageContentDetails } from "../../utils";
+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-expect-error: 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: {
+          json: parameters,
+        },
+      },
+    } as Tool;
+  });
+};
@@ -0,0 +1,156 @@
+import {
+  type InvokeModelCommandInput,
+  type InvokeModelWithResponseStreamCommandInput,
+  ResponseStream,
+} from "@aws-sdk/client-bedrock-runtime";
+import type {
+  BaseTool,
+  ChatMessage,
+  LLMMetadata,
+  PartialToolCall,
+  ToolCall,
+  ToolCallLLMMessageOptions,
+} from "@llamaindex/core/llms";
+import { type BedrockChatStreamResponse, Provider } from "../provider";
+import { toUtf8 } from "../utils";
+import type {
+  AnthropicAdditionalChatOptions,
+  AnthropicNoneStreamingResponse,
+  AnthropicStreamEvent,
+  AnthropicTextContent,
+  ToolBlock,
+} from "./types";
+
+import {
+  mapBaseToolsToAnthropicTools,
+  mapChatMessagesToAnthropicMessages,
+} from "./utils";
+
+export class AnthropicProvider extends Provider<AnthropicStreamEvent> {
+  getResultFromResponse(
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    response: Record<string, any>,
+  ): AnthropicNoneStreamingResponse {
+    return JSON.parse(toUtf8(response.body));
+  }
+
+  getToolsFromResponse<AnthropicToolContent>(
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    response: Record<string, any>,
+  ): AnthropicToolContent[] {
+    const result = this.getResultFromResponse(response);
+    return result.content
+      .filter((item) => item.type === "tool_use")
+      .map((item) => item as AnthropicToolContent);
+  }
+
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  getTextFromResponse(response: Record<string, any>): string {
+    const result = this.getResultFromResponse(response);
+    return result.content
+      .filter((item) => item.type === "text")
+      .map((item) => (item as AnthropicTextContent).text)
+      .join(" ");
+  }
+
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  getTextFromStreamResponse(response: Record<string, any>): string {
+    const event = this.getStreamingEventResponse(response);
+    if (event?.type === "content_block_delta") {
+      if (event.delta.type === "text_delta") return event.delta.text;
+      if (event.delta.type === "input_json_delta")
+        return event.delta.partial_json;
+    }
+    return "";
+  }
+
+  async *reduceStream(
+    stream: AsyncIterable<ResponseStream>,
+  ): BedrockChatStreamResponse {
+    let collecting = [];
+    let tool: ToolBlock | undefined = undefined;
+    // #TODO this should be broken down into a separate consumer
+    for await (const response of stream) {
+      const delta = this.getTextFromStreamResponse(response);
+      const event = this.getStreamingEventResponse(response);
+      if (
+        event?.type === "content_block_start" &&
+        event.content_block.type === "tool_use"
+      ) {
+        tool = event.content_block;
+        continue;
+      }
+
+      if (
+        event?.type === "content_block_delta" &&
+        event.delta.type === "input_json_delta"
+      ) {
+        collecting.push(event.delta.partial_json);
+      }
+
+      let options: undefined | ToolCallLLMMessageOptions = undefined;
+      if (tool && collecting.length) {
+        const input = collecting.filter((item) => item).join("");
+        // We have all we need to parse the tool_use json
+        if (event?.type === "content_block_stop") {
+          options = {
+            toolCall: [
+              {
+                id: tool.id,
+                name: tool.name,
+                input: JSON.parse(input),
+              } as ToolCall,
+            ],
+          };
+          // reset the collection/tool
+          collecting = [];
+          tool = undefined;
+        } else {
+          options = {
+            toolCall: [
+              {
+                id: tool.id,
+                name: tool.name,
+                input,
+              } as PartialToolCall,
+            ],
+          };
+        }
+      }
+      if (!delta && !options) continue;
+
+      yield {
+        delta: options ? "" : delta,
+        options,
+        raw: response,
+      };
+    }
+  }
+
+  getRequestBody<T extends ChatMessage<ToolCallLLMMessageOptions>>(
+    metadata: LLMMetadata,
+    messages: T[],
+    tools?: BaseTool[],
+    options?: AnthropicAdditionalChatOptions,
+  ): InvokeModelCommandInput | InvokeModelWithResponseStreamCommandInput {
+    const extra: Record<string, unknown> = {};
+    if (options?.toolChoice) {
+      extra["tool_choice"] = options?.toolChoice;
+    }
+    const mapped = mapChatMessagesToAnthropicMessages(messages);
+    return {
+      modelId: metadata.model,
+      contentType: "application/json",
+      accept: "application/json",
+      body: JSON.stringify({
+        anthropic_version: "bedrock-2023-05-31",
+        messages: mapped,
+        tools: mapBaseToolsToAnthropicTools(tools),
+        max_tokens: metadata.maxTokens,
+        temperature: metadata.temperature,
+        top_p: metadata.topP,
+        ...extra,
+      }),
+    };
+  }
+}
@@ -0,0 +1,161 @@
+import type { ToolMetadata } from "@llamaindex/core/llms";
+import type { InvocationMetrics } from "../types";
+
+export type ToolChoice =
+  | { type: "any" }
+  | { type: "auto" }
+  | { type: "tool"; name: string };
+
+export interface ThinkingConfigDisabled {
+  type: "disabled";
+}
+
+export interface ThinkingConfigEnabled {
+  budget_tokens: number;
+  type: "enabled";
+}
+
+export type AnthropicAdditionalChatOptions = {
+  toolChoice: ToolChoice;
+  thinking?: ThinkingConfigDisabled | ThinkingConfigEnabled;
+};
+
+type Usage = {
+  input_tokens: number;
+  output_tokens: number;
+};
+
+type Message = {
+  id: string;
+  type: string;
+  role: string;
+  content: string[];
+  model: string;
+  stop_reason: string | null;
+  stop_sequence: string | null;
+  usage: Usage;
+};
+
+export type ToolBlock = {
+  id: string;
+  input: unknown;
+  name: string;
+  type: "tool_use";
+};
+
+export type TextBlock = {
+  type: "text";
+  text: string;
+};
+
+type ContentBlockStart = {
+  type: "content_block_start";
+  index: number;
+  content_block: ToolBlock | TextBlock;
+};
+
+type Delta =
+  | {
+      type: "text_delta";
+      text: string;
+    }
+  | {
+      type: "input_json_delta";
+      partial_json: string;
+    };
+
+type ContentBlockDelta = {
+  type: "content_block_delta";
+  index: number;
+  delta: Delta;
+};
+
+type ContentBlockStop = {
+  type: "content_block_stop";
+  index: number;
+};
+
+type MessageDelta = {
+  type: "message_delta";
+  delta: {
+    stop_reason: string;
+    stop_sequence: string | null;
+  };
+  usage: Usage;
+};
+
+export type MessageStop = {
+  type: "message_stop";
+  "amazon-bedrock-invocationMetrics": InvocationMetrics;
+};
+
+export type AnthropicStreamEvent =
+  | { type: "message_start"; message: Message }
+  | ContentBlockStart
+  | ContentBlockDelta
+  | ContentBlockStop
+  | MessageDelta
+  | MessageStop;
+
+export type AnthropicContent =
+  | AnthropicTextContent
+  | AnthropicImageContent
+  | AnthropicToolContent
+  | AnthropicToolResultContent;
+
+export type AnthropicTextContent = {
+  type: "text";
+  text: string;
+};
+
+export type AnthropicToolContent = {
+  type: "tool_use";
+  id: string;
+  name: string;
+  input: Record<string, unknown>;
+};
+
+export type AnthropicToolResultContent = {
+  type: "tool_result";
+  tool_use_id: string;
+  content: string;
+};
+
+export type AnthropicMediaTypes =
+  | "image/jpeg"
+  | "image/png"
+  | "image/webp"
+  | "image/gif";
+
+export type AnthropicImageSource = {
+  type: "base64";
+  media_type: AnthropicMediaTypes;
+  data: string; // base64 encoded image bytes
+};
+
+export type AnthropicImageContent = {
+  type: "image";
+  source: AnthropicImageSource;
+};
+
+export type AnthropicMessage = {
+  role: "user" | "assistant";
+  content: AnthropicContent[];
+};
+
+export type AnthropicNoneStreamingResponse = {
+  id: string;
+  type: "message";
+  role: "assistant";
+  content: AnthropicContent[];
+  model: string;
+  stop_reason: "end_turn" | "max_tokens" | "stop_sequence";
+  stop_sequence?: string;
+  usage: { input_tokens: number; output_tokens: number };
+};
+
+export type AnthropicTool = {
+  name: string;
+  description: string;
+  input_schema: ToolMetadata["parameters"];
+};
@@ -0,0 +1,166 @@
+import type { JSONObject } from "@llamaindex/core/global";
+import type {
+  BaseTool,
+  ChatMessage,
+  MessageContent,
+  MessageContentDetail,
+  ToolCallLLMMessageOptions,
+} from "@llamaindex/core/llms";
+import { mapMessageContentToMessageContentDetails } from "../../utils";
+import { extractDataUrlComponents } from "../utils";
+import type {
+  AnthropicContent,
+  AnthropicImageContent,
+  AnthropicMediaTypes,
+  AnthropicMessage,
+  AnthropicTextContent,
+  AnthropicTool,
+} from "./types.js";
+
+const ACCEPTED_IMAGE_MIME_TYPES = [
+  "image/jpeg",
+  "image/png",
+  "image/webp",
+  "image/gif",
+];
+
+export const mergeNeighboringSameRoleMessages = (
+  messages: AnthropicMessage[],
+): AnthropicMessage[] => {
+  return messages.reduce(
+    (result: AnthropicMessage[], current: AnthropicMessage, index: number) => {
+      if (index > 0 && messages[index - 1]!.role === current.role) {
+        result[result.length - 1]!.content = [
+          ...result[result.length - 1]!.content,
+          ...current.content,
+        ];
+      } else {
+        result.push(current);
+      }
+      return result;
+    },
+    [],
+  );
+};
+
+export const mapMessageContentDetailToAnthropicContent = <
+  T extends MessageContentDetail,
+>(
+  detail: T,
+): AnthropicContent => {
+  let content: AnthropicContent;
+
+  if (detail.type === "text") {
+    content = mapTextContent(detail.text);
+  } else if (detail.type === "image_url") {
+    content = mapImageContent(detail.image_url.url);
+  } else {
+    throw new Error("Unsupported content detail type");
+  }
+  return content;
+};
+
+export const mapMessageContentToAnthropicContent = <T extends MessageContent>(
+  content: T,
+): AnthropicContent[] => {
+  return mapMessageContentToMessageContentDetails(content).map(
+    mapMessageContentDetailToAnthropicContent,
+  );
+};
+
+export const mapBaseToolsToAnthropicTools = (
+  tools?: BaseTool[],
+): AnthropicTool[] => {
+  if (!tools) return [];
+  return tools.map((tool: BaseTool) => {
+    const {
+      metadata: { parameters, ...options },
+    } = tool;
+    return {
+      ...options,
+      input_schema: parameters,
+    };
+  });
+};
+
+export const mapChatMessagesToAnthropicMessages = <
+  T extends ChatMessage<ToolCallLLMMessageOptions>,
+>(
+  messages: T[],
+): AnthropicMessage[] => {
+  const mapped = messages
+    .flatMap((msg: T): AnthropicMessage[] => {
+      if (msg.options && "toolCall" in msg.options) {
+        return [
+          {
+            role: "assistant",
+            content: msg.options.toolCall.map((call) => ({
+              type: "tool_use",
+              id: call.id,
+              name: call.name,
+              input: call.input as JSONObject,
+            })),
+          },
+        ];
+      }
+      if (msg.options && "toolResult" in msg.options) {
+        return [
+          {
+            role: "user",
+            content: [
+              {
+                type: "tool_result",
+                tool_use_id: msg.options.toolResult.id,
+                content: JSON.stringify(msg.options.toolResult.result),
+              },
+            ],
+          },
+        ];
+      }
+      return mapMessageContentToMessageContentDetails(msg.content).map(
+        (detail: MessageContentDetail): AnthropicMessage => {
+          const content = mapMessageContentDetailToAnthropicContent(detail);
+
+          return {
+            role: msg.role === "assistant" ? "assistant" : "user",
+            content: [content],
+          };
+        },
+      );
+    })
+    .filter((message: AnthropicMessage) => {
+      const content = message.content[0]!;
+      if (content.type === "text" && !content.text) return false;
+      if (content.type === "image" && !content.source.data) return false;
+      if (content.type === "image" && message.role === "assistant")
+        return false;
+      return true;
+    });
+
+  return mergeNeighboringSameRoleMessages(mapped);
+};
+
+export const mapTextContent = (text: string): AnthropicTextContent => {
+  return { type: "text", text };
+};
+
+export const mapImageContent = (imageUrl: string): AnthropicImageContent => {
+  if (!imageUrl.startsWith("data:"))
+    throw new Error(
+      "For Anthropic 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))
+    throw new Error(
+      `Anthropic only accepts the following mimeTypes: ${ACCEPTED_IMAGE_MIME_TYPES.join("\n")}`,
+    );
+
+  return {
+    type: "image",
+    source: {
+      type: "base64",
+      media_type: mimeType as AnthropicMediaTypes,
+      data,
+    },
+  };
+};
@@ -0,0 +1,513 @@
+import {
+  BedrockRuntimeClient,
+  type BedrockRuntimeClientConfig,
+  InvokeModelCommand,
+  InvokeModelWithResponseStreamCommand,
+} from "@aws-sdk/client-bedrock-runtime";
+import {
+  type ChatMessage,
+  type ChatResponse,
+  type CompletionResponse,
+  type LLMChatParamsNonStreaming,
+  type LLMChatParamsStreaming,
+  type LLMCompletionParamsNonStreaming,
+  type LLMCompletionParamsStreaming,
+  type LLMMetadata,
+  ToolCallLLM,
+  type ToolCallLLMMessageOptions,
+} from "@llamaindex/core/llms";
+import { streamConverter } from "@llamaindex/core/utils";
+import {
+  type BedrockAdditionalChatOptions,
+  type BedrockChatStreamResponse,
+  Provider,
+} from "./provider";
+
+import { wrapLLMEvent } from "@llamaindex/core/decorator";
+import { mapMessageContentToMessageContentDetails } from "../utils";
+import { AmazonProvider } from "./amazon/provider";
+import { AnthropicProvider } from "./anthropic/provider";
+import { MetaProvider } from "./meta/provider";
+
+// Other providers should go here
+export const PROVIDERS: { [key: string]: Provider } = {
+  anthropic: new AnthropicProvider(),
+  meta: new MetaProvider(),
+  amazon: new AmazonProvider(),
+};
+
+export type BedrockChatParamsStreaming = LLMChatParamsStreaming<
+  BedrockAdditionalChatOptions,
+  ToolCallLLMMessageOptions
+>;
+
+export type BedrockChatParamsNonStreaming = LLMChatParamsNonStreaming<
+  BedrockAdditionalChatOptions,
+  ToolCallLLMMessageOptions
+>;
+
+export type BedrockChatNonStreamResponse =
+  ChatResponse<ToolCallLLMMessageOptions>;
+
+export const BEDROCK_MODELS = {
+  AMAZON_TITAN_TG1_LARGE: "amazon.titan-tg1-large",
+  AMAZON_TITAN_TEXT_EXPRESS_V1: "amazon.titan-text-express-v1",
+  AI21_J2_GRANDE_INSTRUCT: "ai21.j2-grande-instruct",
+  AI21_J2_JUMBO_INSTRUCT: "ai21.j2-jumbo-instruct",
+  AI21_J2_MID: "ai21.j2-mid",
+  AI21_J2_MID_V1: "ai21.j2-mid-v1",
+  AI21_J2_ULTRA: "ai21.j2-ultra",
+  AI21_J2_ULTRA_V1: "ai21.j2-ultra-v1",
+  COHERE_COMMAND_TEXT_V14: "cohere.command-text-v14",
+  ANTHROPIC_CLAUDE_INSTANT_1: "anthropic.claude-instant-v1",
+  ANTHROPIC_CLAUDE_1: "anthropic.claude-v1", // EOF: No longer supported
+  ANTHROPIC_CLAUDE_2: "anthropic.claude-v2",
+  ANTHROPIC_CLAUDE_2_1: "anthropic.claude-v2:1",
+  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",
+  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",
+  ANTHROPIC_CLAUDE_3_7_SONNET: "anthropic.claude-3-7-sonnet-20250219-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",
+  META_LLAMA3_70B_INSTRUCT: "meta.llama3-70b-instruct-v1:0",
+  META_LLAMA3_1_8B_INSTRUCT: "meta.llama3-1-8b-instruct-v1:0",
+  META_LLAMA3_1_70B_INSTRUCT: "meta.llama3-1-70b-instruct-v1:0",
+  META_LLAMA3_1_405B_INSTRUCT: "meta.llama3-1-405b-instruct-v1:0",
+  META_LLAMA3_2_1B_INSTRUCT: "meta.llama3-2-1b-instruct-v1:0",
+  META_LLAMA3_2_3B_INSTRUCT: "meta.llama3-2-3b-instruct-v1:0",
+  META_LLAMA3_2_11B_INSTRUCT: "meta.llama3-2-11b-instruct-v1:0",
+  META_LLAMA3_2_90B_INSTRUCT: "meta.llama3-2-90b-instruct-v1:0",
+  META_LLAMA3_3_70B_INSTRUCT: "meta.llama3-3-70b-instruct-v1:0",
+  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_PREMIER_1: "amazon.nova-premier-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:
+    "us.anthropic.claude-3-5-sonnet-20240620-v1:0",
+  US_ANTHROPIC_CLAUDE_3_5_SONNET_V2:
+    "us.anthropic.claude-3-5-sonnet-20241022-v2:0",
+  US_ANTHROPIC_CLAUDE_3_7_SONNET:
+    "us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+  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_META_LLAMA_3_3_70B_INSTRUCT: "us.meta.llama3-3-70b-instruct-v1:0",
+  US_AMAZON_NOVA_PREMIER_1: "us.amazon.nova-premier-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",
+  EU_ANTHROPIC_CLAUDE_3_7_SONNET:
+    "eu.anthropic.claude-3-7-sonnet-20250219-v1:0",
+  EU_META_LLAMA_3_2_1B_INSTRUCT: "eu.meta.llama3-2-1b-instruct-v1:0",
+  EU_META_LLAMA_3_2_3B_INSTRUCT: "eu.meta.llama3-2-3b-instruct-v1:0",
+  EU_AMAZON_NOVA_PREMIER_1: "eu.amazon.nova-premier-v1:0",
+  EU_AMAZON_NOVA_PRO_1: "eu.amazon.nova-pro-v1:0",
+  EU_AMAZON_NOVA_LITE_1: "eu.amazon.nova-lite-v1:0",
+  EU_AMAZON_NOVA_MICRO_1: "eu.amazon.nova-micro-v1:0",
+};
+
+export type INFERENCE_BEDROCK_MODELS =
+  (typeof INFERENCE_BEDROCK_MODELS)[keyof typeof INFERENCE_BEDROCK_MODELS];
+
+export const INFERENCE_TO_BEDROCK_MAP: Record<
+  INFERENCE_BEDROCK_MODELS,
+  BEDROCK_MODELS
+> = {
+  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_HAIKU]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU,
+  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_OPUS]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_OPUS,
+  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_SONNET]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_SONNET,
+  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_5_SONNET]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET,
+  [INFERENCE_BEDROCK_MODELS.US_ANTHROPIC_CLAUDE_3_7_SONNET]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_7_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]:
+    BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT,
+  [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_2_11B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT,
+  [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_2_90B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT,
+  [INFERENCE_BEDROCK_MODELS.US_META_LLAMA_3_3_70B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_3_70B_INSTRUCT,
+
+  [INFERENCE_BEDROCK_MODELS.US_AMAZON_NOVA_PREMIER_1]:
+    BEDROCK_MODELS.AMAZON_NOVA_PREMIER_1,
+  [INFERENCE_BEDROCK_MODELS.US_AMAZON_NOVA_PRO_1]:
+    BEDROCK_MODELS.AMAZON_NOVA_PRO_1,
+  [INFERENCE_BEDROCK_MODELS.US_AMAZON_NOVA_LITE_1]:
+    BEDROCK_MODELS.AMAZON_NOVA_LITE_1,
+  [INFERENCE_BEDROCK_MODELS.US_AMAZON_NOVA_MICRO_1]:
+    BEDROCK_MODELS.AMAZON_NOVA_MICRO_1,
+
+  [INFERENCE_BEDROCK_MODELS.EU_ANTHROPIC_CLAUDE_3_HAIKU]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU,
+  [INFERENCE_BEDROCK_MODELS.EU_ANTHROPIC_CLAUDE_3_SONNET]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_SONNET,
+  [INFERENCE_BEDROCK_MODELS.EU_ANTHROPIC_CLAUDE_3_5_SONNET]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_5_SONNET,
+  [INFERENCE_BEDROCK_MODELS.EU_ANTHROPIC_CLAUDE_3_7_SONNET]:
+    BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_7_SONNET,
+  [INFERENCE_BEDROCK_MODELS.EU_META_LLAMA_3_2_1B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT,
+  [INFERENCE_BEDROCK_MODELS.EU_META_LLAMA_3_2_3B_INSTRUCT]:
+    BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT,
+
+  [INFERENCE_BEDROCK_MODELS.EU_AMAZON_NOVA_PREMIER_1]:
+    BEDROCK_MODELS.AMAZON_NOVA_PREMIER_1,
+  [INFERENCE_BEDROCK_MODELS.EU_AMAZON_NOVA_PRO_1]:
+    BEDROCK_MODELS.AMAZON_NOVA_PRO_1,
+  [INFERENCE_BEDROCK_MODELS.EU_AMAZON_NOVA_LITE_1]:
+    BEDROCK_MODELS.AMAZON_NOVA_LITE_1,
+  [INFERENCE_BEDROCK_MODELS.EU_AMAZON_NOVA_MICRO_1]:
+    BEDROCK_MODELS.AMAZON_NOVA_MICRO_1,
+};
+
+/*
+ * Values taken from https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters.html#model-parameters-claude
+ */
+
+const COMPLETION_MODELS = {
+  [BEDROCK_MODELS.AMAZON_TITAN_TG1_LARGE]: 8000,
+  [BEDROCK_MODELS.AMAZON_TITAN_TEXT_EXPRESS_V1]: 8000,
+  [BEDROCK_MODELS.AI21_J2_GRANDE_INSTRUCT]: 8000,
+  [BEDROCK_MODELS.AI21_J2_JUMBO_INSTRUCT]: 8000,
+  [BEDROCK_MODELS.AI21_J2_MID]: 8000,
+  [BEDROCK_MODELS.AI21_J2_MID_V1]: 8000,
+  [BEDROCK_MODELS.AI21_J2_ULTRA]: 8000,
+  [BEDROCK_MODELS.AI21_J2_ULTRA_V1]: 8000,
+  [BEDROCK_MODELS.COHERE_COMMAND_TEXT_V14]: 4096,
+};
+
+const CHAT_ONLY_MODELS = {
+  [BEDROCK_MODELS.ANTHROPIC_CLAUDE_INSTANT_1]: 100000,
+  [BEDROCK_MODELS.ANTHROPIC_CLAUDE_1]: 100000,
+  [BEDROCK_MODELS.ANTHROPIC_CLAUDE_2]: 100000,
+  [BEDROCK_MODELS.ANTHROPIC_CLAUDE_2_1]: 200000,
+  [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_SONNET]: 200000,
+  [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU]: 200000,
+  [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.ANTHROPIC_CLAUDE_3_7_SONNET]: 200000,
+  [BEDROCK_MODELS.META_LLAMA2_13B_CHAT]: 2048,
+  [BEDROCK_MODELS.META_LLAMA2_70B_CHAT]: 4096,
+  [BEDROCK_MODELS.META_LLAMA3_8B_INSTRUCT]: 8192,
+  [BEDROCK_MODELS.META_LLAMA3_70B_INSTRUCT]: 8192,
+  [BEDROCK_MODELS.META_LLAMA3_1_8B_INSTRUCT]: 128000,
+  [BEDROCK_MODELS.META_LLAMA3_1_70B_INSTRUCT]: 128000,
+  [BEDROCK_MODELS.META_LLAMA3_1_405B_INSTRUCT]: 128000,
+  [BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT]: 131000,
+  [BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT]: 131000,
+  [BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT]: 128000,
+  [BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT]: 128000,
+  [BEDROCK_MODELS.META_LLAMA3_3_70B_INSTRUCT]: 128000,
+  [BEDROCK_MODELS.MISTRAL_7B_INSTRUCT]: 32000,
+  [BEDROCK_MODELS.MISTRAL_MIXTRAL_7B_INSTRUCT]: 32000,
+  [BEDROCK_MODELS.MISTRAL_MIXTRAL_LARGE_2402]: 32000,
+  [BEDROCK_MODELS.AMAZON_NOVA_PREMIER_1]: 300000,
+  [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 };
+
+/*
+ * Only the following models support streaming as
+ * per result of Bedrock.Client.list_foundation_models
+ * https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/bedrock/client/list_foundation_models.html
+ */
+export const STREAMING_MODELS = new Set([
+  BEDROCK_MODELS.AMAZON_TITAN_TG1_LARGE,
+  BEDROCK_MODELS.AMAZON_TITAN_TEXT_EXPRESS_V1,
+  BEDROCK_MODELS.ANTHROPIC_CLAUDE_INSTANT_1,
+  BEDROCK_MODELS.ANTHROPIC_CLAUDE_1,
+  BEDROCK_MODELS.ANTHROPIC_CLAUDE_2,
+  BEDROCK_MODELS.ANTHROPIC_CLAUDE_2_1,
+  BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_SONNET,
+  BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU,
+  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.ANTHROPIC_CLAUDE_3_7_SONNET,
+  BEDROCK_MODELS.META_LLAMA2_13B_CHAT,
+  BEDROCK_MODELS.META_LLAMA2_70B_CHAT,
+  BEDROCK_MODELS.META_LLAMA3_8B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_70B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_1_8B_INSTRUCT,
+  BEDROCK_MODELS.META_LLAMA3_1_70B_INSTRUCT,
+  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.META_LLAMA3_3_70B_INSTRUCT,
+  BEDROCK_MODELS.MISTRAL_7B_INSTRUCT,
+  BEDROCK_MODELS.MISTRAL_MIXTRAL_7B_INSTRUCT,
+  BEDROCK_MODELS.MISTRAL_MIXTRAL_LARGE_2402,
+  BEDROCK_MODELS.AMAZON_NOVA_PREMIER_1,
+  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[] = [
+  BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_SONNET,
+  BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_HAIKU,
+  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.ANTHROPIC_CLAUDE_3_7_SONNET,
+  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.META_LLAMA3_3_70B_INSTRUCT,
+  BEDROCK_MODELS.AMAZON_NOVA_PREMIER_1,
+  BEDROCK_MODELS.AMAZON_NOVA_PRO_1,
+  BEDROCK_MODELS.AMAZON_NOVA_LITE_1,
+  BEDROCK_MODELS.AMAZON_NOVA_MICRO_1,
+];
+
+const getProvider = (model: string): Provider => {
+  const providerName = model.split(".")[0];
+  if (!providerName) {
+    throw new Error(`Model ${model} is not supported`);
+  }
+  if (!(providerName in PROVIDERS)) {
+    throw new Error(
+      `Provider ${providerName} for model ${model} is not supported`,
+    );
+  }
+  return PROVIDERS[providerName]!;
+};
+
+export type BedrockModelParams = {
+  model: BEDROCK_MODELS | INFERENCE_BEDROCK_MODELS;
+  temperature?: number;
+  topP?: number;
+  maxTokens?: number;
+};
+
+export const BEDROCK_MODEL_MAX_TOKENS: Partial<Record<BEDROCK_MODELS, number>> =
+  {
+    [BEDROCK_MODELS.ANTHROPIC_CLAUDE_3_SONNET]: 4096,
+    [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_7_SONNET]: 8192,
+    [BEDROCK_MODELS.META_LLAMA2_13B_CHAT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA2_70B_CHAT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_8B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_70B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_1_8B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_1_70B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_1_405B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_2_1B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_2_3B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_2_11B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_2_90B_INSTRUCT]: 2048,
+    [BEDROCK_MODELS.META_LLAMA3_3_70B_INSTRUCT]: 2048,
+  };
+
+const DEFAULT_BEDROCK_PARAMS = {
+  temperature: 0.1,
+  topP: 1,
+  maxTokens: 1024, // required by anthropic
+};
+
+export type BedrockParams = BedrockRuntimeClientConfig & BedrockModelParams;
+
+/**
+ * ToolCallLLM for Bedrock
+ */
+export class Bedrock extends ToolCallLLM<BedrockAdditionalChatOptions> {
+  private client: BedrockRuntimeClient;
+  protected actualModel: BEDROCK_MODELS | INFERENCE_BEDROCK_MODELS;
+  model: BEDROCK_MODELS;
+  temperature: number;
+  topP: number;
+  maxTokens?: number;
+  provider: Provider;
+  topK?: number;
+
+  // there should be no check for env variables. Bedrock can be authenticated in various ways
+  // AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY and AWS_REGION are the env variables used directly by the sdk
+  constructor({
+    temperature,
+    topP,
+    maxTokens,
+    model,
+    ...params
+  }: BedrockParams) {
+    super();
+    this.actualModel = model;
+    this.model = INFERENCE_TO_BEDROCK_MAP[model] ?? model;
+    this.provider = getProvider(this.model);
+    this.maxTokens = maxTokens ?? DEFAULT_BEDROCK_PARAMS.maxTokens;
+    this.temperature = temperature ?? DEFAULT_BEDROCK_PARAMS.temperature;
+    this.topP = topP ?? DEFAULT_BEDROCK_PARAMS.topP;
+    this.client = new BedrockRuntimeClient(params);
+  }
+
+  get supportToolCall(): boolean {
+    return TOOL_CALL_MODELS.includes(this.model);
+  }
+
+  get metadata(): LLMMetadata {
+    // NOTE, Anthropic supports top_k but LLMMetadata does not
+    return {
+      model: this.model,
+      temperature: this.temperature,
+      topP: this.topP,
+      maxTokens: this.maxTokens,
+      contextWindow: BEDROCK_FOUNDATION_LLMS[this.model] ?? 128000,
+      tokenizer: undefined,
+      structuredOutput: false,
+    };
+  }
+
+  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,
+      params.tools,
+      params.additionalChatOptions,
+    );
+    const command = new InvokeModelCommand(input);
+    command.input.modelId = this.actualModel;
+
+    const response = await this.client.send(command);
+    let options: ToolCallLLMMessageOptions = {};
+    if (this.supportToolCall) {
+      const tools = this.provider.getToolsFromResponse(response);
+      if (tools.length) {
+        options = { toolCall: tools };
+      }
+    }
+    return {
+      raw: response,
+      message: {
+        role: "assistant",
+        content: this.provider.getTextFromResponse(response),
+        options,
+      },
+    };
+  }
+
+  protected async *streamChat(
+    params: BedrockChatParamsStreaming,
+  ): BedrockChatStreamResponse {
+    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,
+      params.tools,
+      params.additionalChatOptions,
+    );
+    const command = new InvokeModelWithResponseStreamCommand(input);
+    command.input.modelId = this.actualModel;
+
+    const response = await this.client.send(command);
+    if (response.body) yield* this.provider.reduceStream(response.body);
+  }
+
+  chat(params: BedrockChatParamsStreaming): Promise<BedrockChatStreamResponse>;
+  chat(
+    params: BedrockChatParamsNonStreaming,
+  ): Promise<BedrockChatNonStreamResponse>;
+  @wrapLLMEvent
+  async chat(
+    params: BedrockChatParamsStreaming | BedrockChatParamsNonStreaming,
+  ): Promise<BedrockChatStreamResponse | BedrockChatNonStreamResponse> {
+    if (params.stream) {
+      return this.streamChat(params);
+    }
+    return this.nonStreamChat(params);
+  }
+
+  complete(
+    params: LLMCompletionParamsStreaming,
+  ): Promise<AsyncIterable<CompletionResponse>>;
+  complete(
+    params: LLMCompletionParamsNonStreaming,
+  ): Promise<CompletionResponse>;
+  async complete(
+    params: LLMCompletionParamsStreaming | LLMCompletionParamsNonStreaming,
+  ): Promise<CompletionResponse | AsyncIterable<CompletionResponse>> {
+    const message: ChatMessage = {
+      role: "user",
+      content: mapMessageContentToMessageContentDetails(params.prompt),
+    };
+
+    const input = this.provider.getRequestBody(this.metadata, [message]);
+
+    if (params.stream) {
+      const command = new InvokeModelWithResponseStreamCommand(input);
+      const response = await this.client.send(command);
+      if (response.body)
+        return streamConverter(response.body, (response) => {
+          return {
+            text: this.provider.getTextFromStreamResponse(response),
+            raw: response,
+          };
+        });
+    }
+
+    const command = new InvokeModelCommand(input);
+    const response = await this.client.send(command);
+    return {
+      text: this.provider.getTextFromResponse(response),
+      raw: response,
+    };
+  }
+}
@@ -0,0 +1,3 @@
+export const TOKENS = {
+  TOOL_CALL: "<|python_tag|>",
+};
@@ -0,0 +1,153 @@
+import type {
+  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 type { MetaNoneStreamingResponse, MetaStreamEvent } from "./types";
+
+import { randomUUID } from "@llamaindex/env";
+import { Provider, type BedrockChatStreamResponse } from "../provider";
+import { TOKENS } from "./constants";
+import {
+  mapChatMessagesToMetaLlama2Messages,
+  mapChatMessagesToMetaLlama3Messages,
+} from "./utils";
+
+export class MetaProvider extends Provider<MetaStreamEvent> {
+  getResultFromResponse(
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    response: Record<string, any>,
+  ): MetaNoneStreamingResponse {
+    return JSON.parse(toUtf8(response.body));
+  }
+
+  getToolsFromResponse<ToolContent>(
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    response: Record<string, any>,
+  ): ToolContent[] {
+    const result = this.getResultFromResponse(response);
+    if (!result.generation.trim().startsWith(TOKENS.TOOL_CALL)) return [];
+    const tool = JSON.parse(
+      result.generation.trim().split(TOKENS.TOOL_CALL)[1]!,
+    );
+    return [
+      {
+        id: randomUUID(),
+        name: tool.name,
+        input: tool.parameters,
+      } as ToolContent,
+    ];
+  }
+
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  getTextFromResponse(response: Record<string, any>): string {
+    const result = this.getResultFromResponse(response);
+    if (result.generation.trim().startsWith(TOKENS.TOOL_CALL)) return "";
+    return result.generation;
+  }
+
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  getTextFromStreamResponse(response: Record<string, any>): string {
+    const event = this.getStreamingEventResponse(response);
+    if (event?.generation) {
+      return event.generation;
+    }
+    return "";
+  }
+
+  async *reduceStream(
+    stream: AsyncIterable<ResponseStream>,
+  ): BedrockChatStreamResponse {
+    const collecting: string[] = [];
+    let toolId: string | undefined = undefined;
+    for await (const response of stream) {
+      const event = this.getStreamingEventResponse(response);
+      const delta = this.getTextFromStreamResponse(response);
+
+      // odd quirk of llama3.1, start token is \n\n
+      if (
+        !toolId &&
+        !event?.generation.trim() &&
+        event?.generation_token_count === 1 &&
+        event?.prompt_token_count !== null
+      )
+        continue;
+
+      if (delta.startsWith(TOKENS.TOOL_CALL)) {
+        toolId = randomUUID();
+        const parts = delta.split(TOKENS.TOOL_CALL).filter((part) => part);
+        collecting.push(...parts);
+        continue;
+      }
+
+      let options: undefined | ToolCallLLMMessageOptions = undefined;
+      if (toolId && event?.stop_reason === "stop") {
+        if (delta) collecting.push(delta);
+        const tool = JSON.parse(collecting.join(""));
+        options = {
+          toolCall: [
+            {
+              id: toolId,
+              name: tool.name,
+              input: tool.parameters,
+            } as ToolCall,
+          ],
+        };
+      } else if (toolId && !event?.stop_reason) {
+        collecting.push(delta);
+        continue;
+      }
+
+      if (!delta && !options) continue;
+
+      yield {
+        delta: options ? "" : delta,
+        options,
+        raw: response,
+      };
+    }
+  }
+
+  getRequestBody<T extends ChatMessage>(
+    metadata: LLMMetadata,
+    messages: T[],
+    tools: BaseTool[] = [],
+  ): InvokeModelCommandInput | InvokeModelWithResponseStreamCommandInput {
+    let prompt: string = "";
+    let images: string[] = [];
+    if (metadata.model.startsWith("meta.llama3")) {
+      const mapped = mapChatMessagesToMetaLlama3Messages({
+        messages,
+        tools,
+        model: metadata.model,
+      });
+      prompt = mapped.prompt;
+      images = mapped.images;
+    } else if (metadata.model.startsWith("meta.llama2")) {
+      prompt = mapChatMessagesToMetaLlama2Messages(messages);
+    } else {
+      throw new Error(`Meta model ${metadata.model} is not supported`);
+    }
+
+    return {
+      modelId: metadata.model,
+      contentType: "application/json",
+      accept: "application/json",
+      body: JSON.stringify({
+        prompt,
+        images: images.length ? images : undefined,
+        max_gen_len: metadata.maxTokens,
+        temperature: metadata.temperature,
+        top_p: metadata.topP,
+      }),
+    };
+  }
+}
@@ -0,0 +1,21 @@
+import type { InvocationMetrics } from "../types";
+
+export type MetaTextContent = string;
+
+export type MetaMessage = {
+  role: "user" | "assistant" | "system" | "ipython";
+  content: MetaTextContent;
+};
+
+type MetaResponse = {
+  generation: string;
+  prompt_token_count: number;
+  generation_token_count: number;
+  stop_reason: "stop" | "length";
+};
+
+export type MetaStreamEvent = MetaResponse & {
+  "amazon-bedrock-invocationMetrics": InvocationMetrics;
+};
+
+export type MetaNoneStreamingResponse = MetaResponse;
@@ -0,0 +1,273 @@
+import type {
+  BaseTool,
+  ChatMessage,
+  LLMMetadata,
+  MessageContentTextDetail,
+  ToolCallLLMMessageOptions,
+} from "@llamaindex/core/llms";
+import { extractDataUrlComponents } from "../utils";
+import { TOKENS } from "./constants";
+import type { MetaMessage } from "./types";
+
+const getToolCallInstructionString = (tool: BaseTool): string => {
+  return `Use the function '${tool.metadata.name}' to '${tool.metadata.description}'`;
+};
+
+const getToolCallParametersString = (tool: BaseTool): string => {
+  return JSON.stringify({
+    name: tool.metadata.name,
+    description: tool.metadata.description,
+    parameters: tool.metadata.parameters
+      ? Object.entries(tool.metadata.parameters.properties).map(
+          ([name, definition]) => ({ [name]: definition }),
+        )
+      : {},
+  });
+};
+
+// ported from https://github.com/meta-llama/llama-agentic-system/blob/main/llama_agentic_system/system_prompt.py
+// NOTE: using json instead of the above xml style tool calling works more reliability
+export const getToolsPrompt_3_1 = (tools?: BaseTool[]) => {
+  if (!tools?.length) return "";
+
+  const customToolParams = tools.map((tool) => {
+    return [
+      getToolCallInstructionString(tool),
+      getToolCallParametersString(tool),
+    ].join("\n\n");
+  });
+
+  return `
+Environment: node
+
+# Tool Instructions
+- Never use ipython, always use javascript in node
+
+Cutting Knowledge Date: December 2023
+Today Date: ${new Date().toLocaleString("en-US", { year: "numeric", month: "long" })} 
+
+You have access to the following functions:
+
+${customToolParams}
+
+Think very carefully before calling functions.
+
+If a you choose to call a function ONLY reply in the following json format:
+{
+  "name": function_name,
+  "parameters": parameters,
+}
+where
+
+{
+  "name": function_name,
+  "parameters": parameters, => a JSON dict with the function argument name as key and function argument value as value.
+}
+
+Here is an example,
+
+{
+  "name": "example_function_name",
+  "parameters": {"example_name": "example_value"}
+}
+
+Reminder:
+- Function calls MUST follow the specified format
+- Required parameters MUST be specified
+- Only call one function at a time
+- Put the entire function call reply on one line
+- Always add your sources when using search results to answer the user query
+  `;
+};
+
+export const getToolsPrompt_3_2 = (tools?: BaseTool[]) => {
+  if (!tools?.length) return "";
+  return `
+You are an expert in composing functions. You are given a question and a set of possible functions.
+Based on the question, you will need to make one or more function/tool calls to achieve the purpose.
+If none of the function can be used, point it out. If the given question lacks the parameters required by the function,
+also point it out. You should only return the function call in tools call sections.
+
+If you decide to invoke any of the function(s), you MUST put it in the format of and start with the token: ${TOKENS.TOOL_CALL}:
+{
+  "name": function_name,
+  "parameters": parameters,
+}
+where
+
+{
+  "name": function_name,
+  "parameters": parameters, => a JSON dict with the function argument name as key and function argument value as value.
+}
+
+Here is an example,
+
+{
+  "name": "example_function_name",
+  "parameters": {"example_name": "example_value"}
+}
+
+Reminder:
+- Function calls MUST follow the specified format
+- Required parameters MUST be specified
+- Only call one function at a time
+- You SHOULD NOT include any other text in the response
+- Put the entire function call reply on one line
+
+Here is a list of functions in JSON format that you can invoke.
+
+${JSON.stringify(tools)}
+`;
+};
+
+export const mapChatRoleToMetaRole = (
+  role: ChatMessage["role"],
+): MetaMessage["role"] => {
+  if (role === "assistant") return "assistant";
+  if (role === "user") return "user";
+  return "system";
+};
+
+export const mapChatMessagesToMetaMessages = <
+  T extends ChatMessage<ToolCallLLMMessageOptions>,
+>(
+  messages: T[],
+): MetaMessage[] => {
+  return messages.flatMap((msg) => {
+    if (msg.options && "toolCall" in msg.options) {
+      return msg.options.toolCall.map((call) => ({
+        role: "assistant",
+        content: JSON.stringify({
+          id: call.id,
+          name: call.name,
+          parameters: call.input,
+        }),
+      }));
+    }
+
+    if (msg.options && "toolResult" in msg.options) {
+      return {
+        role: "ipython",
+        content: JSON.stringify(msg.options.toolResult),
+      };
+    }
+
+    let content: string = "";
+    if (typeof msg.content === "string") {
+      content = msg.content;
+    } else if (msg.content.length) {
+      content = (msg.content[0] as MessageContentTextDetail).text;
+    }
+    return {
+      role: mapChatRoleToMetaRole(msg.role),
+      content,
+    };
+  });
+};
+
+/**
+ * Documentation at https://llama.meta.com/docs/model-cards-and-prompt-formats/meta-llama-3
+ */
+export const mapChatMessagesToMetaLlama3Messages = <T extends ChatMessage>({
+  messages,
+  model,
+  tools,
+}: {
+  messages: T[];
+  model: LLMMetadata["model"];
+  tools?: BaseTool[];
+}): { prompt: string; images: string[] } => {
+  const images: string[] = [];
+  const textMessages: T[] = [];
+
+  messages.forEach((message) => {
+    if (Array.isArray(message.content)) {
+      message.content.forEach((content) => {
+        if (content.type === "image_url") {
+          const { base64 } = extractDataUrlComponents(content.image_url.url);
+          images.push(base64);
+        } else {
+          textMessages.push(message);
+        }
+      });
+    } else {
+      textMessages.push(message);
+    }
+  });
+
+  const parts: string[] = [];
+
+  let toolsPrompt = "";
+  if (model.startsWith("meta.llama3-2")) {
+    toolsPrompt = getToolsPrompt_3_2(tools);
+  } else if (model.startsWith("meta.llama3-1")) {
+    toolsPrompt = getToolsPrompt_3_1(tools);
+  }
+  if (toolsPrompt) {
+    parts.push(
+      "<|begin_of_text|>",
+      "<|start_header_id|>system<|end_header_id|>",
+      toolsPrompt,
+      "<|eot_id|>",
+    );
+  }
+
+  const mapped = mapChatMessagesToMetaMessages(messages).map((message) => {
+    return [
+      "<|start_header_id|>",
+      message.role,
+      "<|end_header_id|>",
+      message.content,
+      "<|eot_id|>",
+    ].join("\n");
+  });
+
+  parts.push(
+    "<|begin_of_text|>",
+    ...mapped,
+    "<|start_header_id|>assistant<|end_header_id|>",
+  );
+
+  const prompt = parts.join("\n");
+  return { prompt, images };
+};
+
+/**
+ * Documentation at https://llama.meta.com/docs/model-cards-and-prompt-formats/meta-llama-2
+ */
+export const mapChatMessagesToMetaLlama2Messages = <T extends ChatMessage>(
+  messages: T[],
+): string => {
+  const mapped = mapChatMessagesToMetaMessages(messages);
+  let output = "<s>";
+  let insideInst = false;
+  let needsStartAgain = false;
+  for (const message of mapped) {
+    if (needsStartAgain) {
+      output += "<s>";
+      needsStartAgain = false;
+    }
+    const text = message.content;
+    if (message.role === "system") {
+      if (!insideInst) {
+        output += "[INST] ";
+        insideInst = true;
+      }
+      output += `<<SYS>>\n${text}\n<</SYS>>\n`;
+    } else if (message.role === "user") {
+      output += text;
+      if (insideInst) {
+        output += " [/INST]";
+        insideInst = false;
+      }
+    } else if (message.role === "assistant") {
+      if (insideInst) {
+        output += " [/INST]";
+        insideInst = false;
+      }
+      output += ` ${text} </s>\n`;
+      needsStartAgain = true;
+    }
+  }
+  return output;
+};
@@ -0,0 +1,63 @@
+import {
+  type InvokeModelCommandInput,
+  type InvokeModelWithResponseStreamCommandInput,
+  ResponseStream,
+} from "@aws-sdk/client-bedrock-runtime";
+import {
+  type BaseTool,
+  type ChatMessage,
+  type ChatResponseChunk,
+  type LLMMetadata,
+  type ToolCallLLMMessageOptions,
+} from "@llamaindex/core/llms";
+import { streamConverter } from "@llamaindex/core/utils";
+import { toUtf8 } from "./utils";
+
+export type BedrockAdditionalChatOptions = Record<string, unknown>;
+
+export type BedrockChatStreamResponse = AsyncIterable<
+  ChatResponseChunk<ToolCallLLMMessageOptions>
+>;
+
+export abstract class Provider<ProviderStreamEvent extends object = object> {
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  abstract getTextFromResponse(response: Record<string, any>): string;
+
+  // Return tool calls from none streaming calls
+  abstract getToolsFromResponse<T extends object = object>(
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    response: Record<string, any>,
+  ): T[];
+
+  getStreamingEventResponse(
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    response: Record<string, any>,
+  ): ProviderStreamEvent | undefined {
+    return response.chunk?.bytes
+      ? (JSON.parse(toUtf8(response.chunk?.bytes)) as ProviderStreamEvent)
+      : undefined;
+  }
+
+  async *reduceStream(
+    stream: AsyncIterable<ResponseStream>,
+  ): BedrockChatStreamResponse {
+    yield* streamConverter(stream, (response) => {
+      return {
+        delta: this.getTextFromStreamResponse(response),
+        raw: response,
+      };
+    });
+  }
+
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  getTextFromStreamResponse(response: Record<string, any>): string {
+    return this.getTextFromResponse(response);
+  }
+
+  abstract getRequestBody<T extends ChatMessage>(
+    metadata: LLMMetadata,
+    messages: T[],
+    tools?: BaseTool[],
+    options?: BedrockAdditionalChatOptions,
+  ): InvokeModelCommandInput | InvokeModelWithResponseStreamCommandInput;
+}
@@ -0,0 +1,6 @@
+export type InvocationMetrics = {
+  inputTokenCount: number;
+  outputTokenCount: number;
+  invocationLatency: number;
+  firstByteLatency: number;
+};
@@ -0,0 +1,23 @@
+export const toUtf8 = (input: Uint8Array): string =>
+  new TextDecoder("utf-8").decode(input);
+
+export const extractDataUrlComponents = (
+  dataUrl: string,
+): {
+  mimeType: string;
+  base64: string;
+} => {
+  const parts = dataUrl.split(";base64,");
+
+  if (parts.length !== 2 || !parts[0]!.startsWith("data:")) {
+    throw new Error("Invalid data URL");
+  }
+
+  const mimeType = parts[0]!.slice(5);
+  const base64 = parts[1]!;
+
+  return {
+    mimeType,
+    base64,
+  };
+};
@@ -0,0 +1,10 @@
+import type {
+  MessageContent,
+  MessageContentDetail,
+} from "@llamaindex/core/llms";
+
+export const mapMessageContentToMessageContentDetails = (
+  content: MessageContent,
+): MessageContentDetail[] => {
+  return Array.isArray(content) ? content : [{ type: "text", text: content }];
+};
@@ -0,0 +1,165 @@
+import type { KnowledgeBaseVectorSearchConfiguration } from "@aws-sdk/client-bedrock-agent-runtime";
+import {
+  BedrockAgentRuntimeClient,
+  type BedrockAgentRuntimeClientConfig,
+  type RetrievalFilter,
+  RetrieveCommand,
+  type SearchType,
+} from "@aws-sdk/client-bedrock-agent-runtime";
+import type { QueryBundle } from "@llamaindex/core/query-engine";
+import { BaseRetriever } from "@llamaindex/core/retriever";
+import { Document, type NodeWithScore } from "@llamaindex/core/schema";
+import { extractText } from "@llamaindex/core/utils";
+
+/**
+ * Interface for the arguments required to initialize an
+ * AmazonKnowledgeBaseRetriever instance.
+ */
+export interface AmazonKnowledgeBaseRetrieverArgs {
+  knowledgeBaseId: string;
+  topK: number;
+  region: string;
+  clientOptions?: BedrockAgentRuntimeClientConfig;
+  filter?: RetrievalFilter;
+  overrideSearchType?: SearchType;
+}
+
+/**
+ * Class for interacting with Amazon Bedrock Knowledge Bases, a RAG workflow oriented service
+ * Extends the BaseRetriever class.
+ * @example
+ * ```typescript
+ * const retriever = new AmazonKnowledgeBaseRetriever({
+ *   topK: 10,
+ *   knowledgeBaseId: "YOUR_KNOWLEDGE_BASE_ID",
+ *   region: "us-east-2",
+ *   clientOptions: {
+ *     credentials: {
+ *       accessKeyId: "YOUR_ACCESS_KEY_ID",
+ *       secretAccessKey: "YOUR_SECRET_ACCESS_KEY",
+ *     },
+ *   },
+ * });
+ *
+ * const docs = await retriever.retrieve({query: "How are clouds formed?"});
+ * ```
+ */
+export class AmazonKnowledgeBaseRetriever extends BaseRetriever {
+  static lc_name() {
+    return "AmazonKnowledgeBaseRetriever";
+  }
+
+  lc_namespace = ["llamaindex", "retrievers", "amazon_bedrock_knowledge_base"];
+
+  knowledgeBaseId: string;
+
+  topK: number;
+
+  bedrockAgentRuntimeClient: BedrockAgentRuntimeClient;
+
+  filter: RetrievalFilter | undefined;
+
+  overrideSearchType: SearchType | undefined;
+
+  constructor({
+    knowledgeBaseId,
+    topK = 10,
+    clientOptions,
+    region,
+    filter,
+    overrideSearchType,
+  }: AmazonKnowledgeBaseRetrieverArgs) {
+    super();
+
+    this.topK = topK;
+    this.filter = filter;
+    this.overrideSearchType = overrideSearchType;
+    this.bedrockAgentRuntimeClient = new BedrockAgentRuntimeClient({
+      region,
+      ...clientOptions,
+    });
+    this.knowledgeBaseId = knowledgeBaseId;
+  }
+
+  /**
+   * Cleans the result text by replacing sequences of whitespace with a
+   * single space and removing ellipses.
+   * @param resText The result text to clean.
+   * @returns The cleaned result text.
+   */
+  cleanResult(resText: string) {
+    const res = resText.replace(/\s+/g, " ").replace(/\.\.\./g, "");
+    return res;
+  }
+
+  async queryKnowledgeBase(
+    query: QueryBundle,
+    topK: number,
+    filter?: RetrievalFilter,
+    overrideSearchType?: SearchType,
+  ): Promise<NodeWithScore[]> {
+    const retrieveCommand = new RetrieveCommand({
+      knowledgeBaseId: this.knowledgeBaseId,
+      retrievalQuery: {
+        text: extractText(query),
+      },
+      retrievalConfiguration: {
+        vectorSearchConfiguration: {
+          numberOfResults: topK,
+          overrideSearchType,
+          filter,
+        } as KnowledgeBaseVectorSearchConfiguration,
+      },
+    });
+
+    const retrieveResponse =
+      await this.bedrockAgentRuntimeClient.send(retrieveCommand);
+
+    return (
+      retrieveResponse.retrievalResults?.map((result) => {
+        let source;
+        switch (result.location?.type) {
+          case "CONFLUENCE":
+            source = result.location?.confluenceLocation?.url;
+            break;
+          case "S3":
+            source = result.location?.s3Location?.uri;
+            break;
+          case "SALESFORCE":
+            source = result.location?.salesforceLocation?.url;
+            break;
+          case "SHAREPOINT":
+            source = result.location?.sharePointLocation?.url;
+            break;
+          case "WEB":
+            source = result.location?.webLocation?.url;
+            break;
+          default:
+            source = result.location?.s3Location?.uri;
+            break;
+        }
+
+        return {
+          node: new Document({
+            text: this.cleanResult(result.content?.text || ""),
+            metadata: {
+              source,
+              score: result.score,
+              ...result.metadata,
+            },
+          }),
+          score: result.score ?? 1.0,
+        };
+      }) ?? []
+    );
+  }
+
+  async _retrieve(query: QueryBundle): Promise<NodeWithScore[]> {
+    return await this.queryKnowledgeBase(
+      query,
+      this.topK,
+      this.filter,
+      this.overrideSearchType,
+    );
+  }
+}
@@ -0,0 +1,19 @@
+{
+  "extends": "../../tsconfig.json",
+  "compilerOptions": {
+    "rootDir": "./src",
+    "outDir": "./dist/type",
+    "tsBuildInfoFile": "./dist/.tsbuildinfo",
+    "emitDeclarationOnly": true,
+    "module": "ESNext",
+    "moduleResolution": "bundler",
+    "types": ["node"]
+  },
+  "include": ["./src"],
+  "exclude": ["node_modules"],
+  "references": [
+    {
+      "path": "../llamaindex/tsconfig.json"
+    }
+  ]
+}
@@ -1,5 +1,37 @@
 # @llamaindex/core

+## 0.6.18
+
+### Patch Changes
+
+- f29799e: Add toolcall callbacks to agent workflows
+- 7224c06: Add logger and callbacks to llm.exec
+
+## 0.6.17
+
+### Patch Changes
+
+- 38da40b: feat: VectoryMemoryBlock
+
+## 0.6.16
+
+### Patch Changes
+
+- a8ec08c: fix: ensure correct message content in agent workflow
+
+## 0.6.15
+
+### Patch Changes
+
+- 7ad3411: feat: add llm.exec
+- 5da5b3c: add progress callback to embeddings
+
+## 0.6.14
+
+### Patch Changes
+
+- 8eeac33: Fix createMemory factory when parsing options
+
 ## 0.6.13

 ### Patch Changes
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/core",
  "type": "module",
-  "version": "0.6.13",
+  "version": "0.6.18",
  "description": "LlamaIndex Core Module",
  "exports": {
    "./agent": {
@@ -59,6 +59,17 @@
      },
      "default": "./llms/dist/index.js"
    },
+    "./llms/mock": {
+      "require": {
+        "types": "./llms/mock/dist/index.d.cts",
+        "default": "./llms/mock/dist/index.cjs"
+      },
+      "import": {
+        "types": "./llms/mock/dist/index.d.ts",
+        "default": "./llms/mock/dist/index.js"
+      },
+      "default": "./llms/mock/dist/index.js"
+    },
    "./decorator": {
      "require": {
        "types": "./decorator/dist/index.d.cts",
@@ -310,9 +321,9 @@
  },
  "dependencies": {
    "@llamaindex/env": "workspace:*",
-    "@types/node": "^22.9.0",
+    "@types/node": "^24.0.13",
    "magic-bytes.js": "^1.10.0",
-    "zod": "^3.25.67",
+    "zod": "^3.25.76",
    "zod-to-json-schema": "^3.24.6"
  }
 }
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
github-actions[bot]	38487da65d	Release 0.11.23 (#2136 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-07-28 14:07:23 +08:00
Marcus Schiesser	f29799e385	feat: Add toolcall callbacks to agent workflows (#2137 )	2025-07-24 15:37:14 +08:00
Marcus Schiesser	9bca30620b	fix: docs build	2025-07-23 12:55:35 +08:00
Marcus Schiesser	7224c06409	feat: Add logger and callbacks to llm.exec (#2135 )	2025-07-23 12:37:02 +08:00
github-actions[bot]	29c7cf0989	Release 0.11.22 (#2131 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>	2025-07-23 11:30:04 +08:00
Marcus Schiesser	c65a2dc4a7	chore: Deprecate community package and link to AWS package (#2134 )	2025-07-23 11:05:50 +08:00
Terence Sim	f1c5079290	docs: updated bedrock import and supported models (#2129 ) Co-authored-by: Terence Sim <40583743+InTheAxis@users.noreply.github.com>	2025-07-23 10:40:49 +08:00
Terence Sim	9ed31958a7	chore: add logger as param to AgentWorkflow constructor (#2130 ) Co-authored-by: Terence Sim <40583743+InTheAxis@users.noreply.github.com> Co-authored-by: Marcus Schiesser <marcus.schiesser@googlemail.com>	2025-07-22 16:35:28 +08:00
github-actions[bot]	e4c7113614	Release 0.11.21 (#2128 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-07-22 12:23:58 +08:00
Thuc Pham	38da40bc98	feat: VectoryMemoryBlock (#2110 ) Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>	2025-07-22 12:18:09 +08:00
Marcus Schiesser	4d50ca4d84	chore: add streamchat test (#2122 )	2025-07-22 11:30:01 +08:00
github-actions[bot]	8b5253a297	Release (#2127 )	2025-07-21 15:40:31 -06:00
Logan	ea15e75c89	deployment docs nits (#2126 )	2025-07-21 15:30:37 -06:00
github-actions[bot]	3be87d4670	Release 0.11.20 (#2121 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: himself65 <14026360+himself65@users.noreply.github.com>	2025-07-21 09:37:44 -07:00
Terence Sim	94da13db0d	fix: azure openai streamchat empty delta throw TypeError (#2118 ) Co-authored-by: Terence Sim <40583743+InTheAxis@users.noreply.github.com>	2025-07-21 09:16:09 -07:00
Terence Sim	acd50ea99f	chore: replaced console.log with logger type from @llamaindex/env (#2123 ) Co-authored-by: Terence Sim <40583743+InTheAxis@users.noreply.github.com>	2025-07-21 09:14:06 -07:00
Adrian Lyjak	2967d57ac0	feat: default to _public agent data (#2117 )	2025-07-21 09:07:15 -07:00
Thuc Pham	a8ec08c682	fix: ensure correct message content in agent workflow (#2114 ) Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>	2025-07-21 15:13:27 +08:00
Terence Sim	678b327051	feat: added apac bedrock models (#2119 ) Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>	2025-07-21 12:13:37 +08:00
Jeremy B. Merrill	650eeb1df3	fix: GeminiEmbedding should send batches of max 100 (#2099 ) Co-authored-by: Marcus Schiesser <marcus.schiesser@googlemail.com>	2025-07-21 12:12:42 +08:00
Laurie Voss	50f6747758	Instrumenting with Google Tag Manager (in addition to Google Analytics) (#2116 )	2025-07-20 13:18:09 -07:00
github-actions[bot]	12414a6836	Release (#2113 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-07-18 13:54:38 +08:00
Marcus Schiesser	856dd8cca8	fix: assume new models are function call models (#2112 )	2025-07-18 12:52:43 +08:00
Jerry Cheng	d8f4f6a859	Update SupabaseVectorStore.ts to fix score calculating error (#2109 ) Co-authored-by: Marcus Schiesser <marcus.schiesser@googlemail.com>	2025-07-18 12:48:47 +08:00
Logan	f594d7034f	revamp getting started flow and main index page (#2079 ) Co-authored-by: Thuc Pham <51660321+thucpn@users.noreply.github.com> Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de> Co-authored-by: thucpn <thucsh2@gmail.com>	2025-07-17 16:27:28 +08:00
github-actions[bot]	c1c58feed2	Release 0.11.19 (#2105 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-07-17 15:44:22 +08:00
Marcus Schiesser	7ad3411766	feat: add llm.exec (#2078 )	2025-07-17 15:36:56 +08:00
Neha Prasad	a1fdb07b96	feat: multi-turn image generation support (#2106 ) Co-authored-by: Marcus Schiesser <marcus.schiesser@googlemail.com>	2025-07-17 10:30:39 +08:00
Jeremy B. Merrill	5da5b3c89c	feat: add progress callback to embeddings (#2098 ) Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>	2025-07-16 13:49:49 +08:00
r3rer3	ddc0eafbaa	feat(anthropic): stream partial tool calls (#2100 )	2025-07-15 10:06:17 -07:00
github-actions[bot]	1782554488	Release 0.11.18 (#2103 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>	2025-07-14 15:53:20 -07:00
Adrian Lyjak	a1b1598bc6	fix(cloud): add generic types into agent data responses (#2102 ) Co-authored-by: Alex Yang <himself65@outlook.com>	2025-07-14 12:01:56 -07:00
Terry Zhao	b02847ae91	fix(notion): resolve @notionhq/client dependency conflict (#2097 )	2025-07-12 11:04:06 -07:00
Alex Yang	50acb4821e	feat(cloud): use camelCase (#2096 )	2025-07-12 10:59:46 -07:00
github-actions[bot]	47a5b94b0c	Release 0.11.17 (#2095 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>	2025-07-11 21:57:02 -07:00
Alex Yang	d2be868b93	feat(cloud): missing agent api (#2094 )	2025-07-11 20:45:22 -07:00
github-actions[bot]	50d42c4129	Release 0.11.16 (#2093 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>	2025-07-11 20:13:37 -07:00
github-actions[bot]	848b97d4d0	Release 0.11.16 (#2092 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>	2025-07-11 18:19:17 -07:00
Alex Yang	c5796b8d2d	fix: only allow pnpm (#2091 )	2025-07-11 18:17:47 -07:00
Alex Yang	579ca0cf60	chore: bump sdk version (#2090 )	2025-07-11 18:10:15 -07:00
Alex Yang	f7e670c8d9	fix: sdk type improvement (#2089 )	2025-07-11 17:56:41 -07:00
Alex Yang	9ff971435c	fix(cloud): agent sdk (#2088 )	2025-07-11 17:41:25 -07:00
github-actions[bot]	7c9d0e24c4	Release (#2086 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-07-11 12:30:04 -07:00
NIEDASEN	af3f86694b	feat: add supportToolCall getter to DeepSeekLLM class (#2085 ) Co-authored-by: Marcus Schiesser <marcus.schiesser@googlemail.com>	2025-07-11 16:11:22 +08:00
github-actions[bot]	5cce681f62	Release 0.11.15 (#2084 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>	2025-07-10 19:08:05 -07:00
Alex Yang	48b0d88941	chore: bump dev deps (#2082 )	2025-07-10 19:00:37 -07:00
Alex Yang	f18577263a	fix(cloud): missing file (#2083 )	2025-07-10 18:33:41 -07:00
github-actions[bot]	214e133e92	Release 0.11.14 (#2068 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: himself65 <14026360+himself65@users.noreply.github.com>	2025-07-10 17:10:02 -07:00
Alex Yang	ae58862669	fix: missing `agent` entry (#2081 )	2025-07-10 11:39:07 -07:00
Alex Yang	5a0ed1f990	feat: init agent api on cloud sdk (#2069 )	2025-07-10 10:00:53 -07:00
Logan	36773a82b6	fix examples scripts (#2077 )	2025-07-09 11:24:07 +08:00
Logan	891562d598	remove workspace from examples package.json (#2075 )	2025-07-08 16:36:33 -07:00
Alex Yang	93852e15fd	chore: bump zod (#2074 )	2025-07-08 13:58:52 -07:00
Clelia (Astra) Bertelli	e1320b08a8	fix: adding more details in the contribution guidelines about changesets (#2073 )	2025-07-08 13:58:36 -07:00
Logan	8eeac3310f	fix memory factory (#2066 )	2025-07-08 10:01:19 +07:00
Logan	984a573068	docs: update contributing instructions (#2067 )	2025-07-07 16:38:26 -07:00
github-actions[bot]	f0160d9646	Release (#2065 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>	2025-07-07 12:15:33 -06:00
Logan	39758ab018	add title to root layout (#2064 )	2025-07-07 12:06:13 -06:00
dependabot[bot]	f631d4f7d6	chore(deps): bump next from 15.3.0 to 15.3.3 (#2063 )	2025-07-07 12:40:42 +07:00