Release 0.11.29 (#2188 )

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: support zod v4 & v3 (#2186 )
2026-07-01 22:14:03 -04:00 · 2025-09-11 10:44:29 +08:00 · 2025-09-11 10:34:45 +08:00 · 2025-09-10 18:09:47 +08:00 · 2025-09-10 11:45:12 +08:00 · 2025-09-10 11:44:57 +08:00
298 changed files with 15093 additions and 2237 deletions
@@ -105,6 +105,7 @@ jobs:
        run: |
          pnpm pack --pack-destination ${{ runner.temp }} -C packages/llamaindex
          pnpm pack --pack-destination ${{ runner.temp }} -C packages/workflow
+          pnpm pack --pack-destination ${{ runner.temp }} -C packages/core
      - name: Install packed packages
        run: npm add ${{ runner.temp }}/*.tgz
        working-directory: e2e/npm
@@ -162,7 +163,7 @@ jobs:
          github_token: ${{ secrets.GITHUB_TOKEN }}
          directory: e2e/examples/vite-import-llamaindex
          skip_step: "install"
-          build_script: build
+          build_script: ci-build
          package_manager: pnpm

  typecheck-examples:
@@ -203,7 +204,7 @@ jobs:
            fi
          done
      - name: Install
-        run: npm add ${{ runner.temp }}/*.tgz
+        run: npm add ${{ runner.temp }}/*.tgz --legacy-peer-deps
        working-directory: ${{ runner.temp }}/examples
      - name: Run Type Check
        run: npx tsc --project ./tsconfig.json
@@ -1,5 +1,184 @@
 # @llamaindex/doc

+## 0.2.54
+
+### Patch Changes
+
+- ed37c64: Addition of APAC_ANTHROPIC_CLAUDE_4_SONNET type/record in @llamaindex/aws for APAC support for claude 4 sonnet per issue 2184.
+- Updated dependencies [8929dcf]
+- Updated dependencies [5da1cda]
+  - llamaindex@0.11.29
+  - @llamaindex/core@0.6.21
+  - @llamaindex/workflow@1.1.23
+  - @llamaindex/openai@0.4.19
+  - @llamaindex/cloud@4.1.3
+  - @llamaindex/node-parser@2.0.21
+  - @llamaindex/readers@3.1.20
+
+## 0.2.53
+
+### Patch Changes
+
+- Updated dependencies [1995b38]
+- Updated dependencies [001a515]
+- Updated dependencies [9d7d205]
+  - @llamaindex/workflow@1.1.22
+  - @llamaindex/openai@0.4.18
+  - llamaindex@0.11.28
+
+## 0.2.52
+
+### Patch Changes
+
+- Updated dependencies [0267bb0]
+  - @llamaindex/core@0.6.20
+  - @llamaindex/cloud@4.1.2
+  - llamaindex@0.11.27
+  - @llamaindex/node-parser@2.0.20
+  - @llamaindex/openai@0.4.17
+  - @llamaindex/readers@3.1.19
+  - @llamaindex/workflow@1.1.21
+
+## 0.2.51
+
+### Patch Changes
+
+- Updated dependencies [4c70376]
+  - @llamaindex/openai@0.4.16
+
+## 0.2.50
+
+### Patch Changes
+
+- Updated dependencies [b6409b6]
+  - @llamaindex/openai@0.4.15
+
+## 0.2.49
+
+### Patch Changes
+
+- Updated dependencies [4b51791]
+  - @llamaindex/cloud@4.1.1
+  - llamaindex@0.11.26
+
+## 0.2.48
+
+### Patch Changes
+
+- Updated dependencies [049471b]
+- Updated dependencies [049471b]
+  - @llamaindex/cloud@4.1.0
+  - llamaindex@0.11.25
+
+## 0.2.47
+
+### Patch Changes
+
+- Updated dependencies [c3bf3c7]
+- Updated dependencies [f9f1de9]
+  - @llamaindex/cloud@4.0.28
+  - @llamaindex/core@0.6.19
+  - llamaindex@0.11.24
+  - @llamaindex/node-parser@2.0.19
+  - @llamaindex/openai@0.4.14
+  - @llamaindex/readers@3.1.18
+  - @llamaindex/workflow@1.1.20
+
+## 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
@@ -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": "0.2.37",
+  "version": "0.2.54",
  "private": true,
  "scripts": {
    "postinstall": "fumadocs-mdx",
@@ -15,7 +15,7 @@
  "dependencies": {
    "@huggingface/transformers": "^3.5.0",
    "@icons-pack/react-simple-icons": "^10.1.0",
-    "@llamaindex/chat-ui-docs": "^0.0.5",
+    "@llamaindex/chat-ui-docs": "^0.1.0",
    "@llamaindex/cloud": "workspace:*",
    "@llamaindex/core": "workspace:*",
    "@llamaindex/node-parser": "workspace:*",
@@ -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";
@@ -36,6 +36,7 @@ export default function Layout({ children }: { children: ReactNode }) {
          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.
@@ -0,0 +1,85 @@
+---
+title: MCP Toolbox For Databases
+description: MCP Toolbox for Databases is an open source MCP server for databases.
+---
+
+# MCP Toolbox for Databases
+
+[MCP Toolbox for Databases](https://github.com/googleapis/genai-toolbox) is an open source MCP server for databases. It was designed with enterprise-grade and production-quality in mind. It enables you to develop tools easier, faster, and more securely by handling the complexities such as connection pooling, authentication, and more.
+
+Toolbox Tools can be seemlessly integrated with LlamaIndex applications. For more
+information on [getting
+started](https://googleapis.github.io/genai-toolbox/getting-started/local_quickstart_js/) or
+[configuring](https://googleapis.github.io/genai-toolbox/getting-started/configure/)
+Toolbox, see the
+[documentation](https://googleapis.github.io/genai-toolbox/getting-started/introduction/).
+
+![architecture](/images/mcp_db_toolbox.png)
+
+### Configure and deploy
+
+Toolbox is an open source server that you deploy and manage yourself. For more
+instructions on deploying and configuring, see the official Toolbox
+documentation:
+
+* [Installing the Server](https://googleapis.github.io/genai-toolbox/getting-started/introduction/#installing-the-server)
+* [Configuring Toolbox](https://googleapis.github.io/genai-toolbox/getting-started/configure/)
+
+### Install client SDK
+
+LlamaIndex relies on the `@toolbox-sdk/core` node package to use Toolbox. Install the
+package before getting started:
+
+```shell
+npm install @toolbox-sdk/core
+```
+
+### Loading Toolbox Tools
+
+Once your Toolbox server is configured and up and running, you can load tools
+from your server using the SDK:
+
+```javascript
+import { gemini, GEMINI_MODEL } from "@llamaindex/google";
+import { agent } from "@llamaindex/workflow";
+import { tool } from "llamaindex";
+import { ToolboxClient } from "@toolbox-sdk/core";
+
+// Initialize LLM
+const llm = gemini({
+  model: GEMINI_MODEL.GEMINI_2_0_FLASH,
+  apiKey: process.env.GOOGLE_API_KEY,
+});
+
+// Replace with your Toolbox Server URL
+const URL = 'https://127.0.0.1:5000';
+
+const client = new ToolboxClient("http://127.0.0.1:5000");
+const toolboxTools = await client.loadToolset("my-toolset");
+
+const getTool = (toolboxTool) => tool({
+  name: toolboxTool.getName(),
+  description: toolboxTool.getDescription(),
+  parameters: toolboxTool.getParamSchema(),
+  execute: toolboxTool
+});
+const tools = toolboxTools.map(getTool);
+
+const myAgent = agent({
+  tools: tools,
+  llm,
+  memory,
+  systemPrompt: prompt,
+});
+const result = await myAgent.run(query);
+console.log(result);
+```
+
+### Advanced Toolbox Features
+
+Toolbox has a variety of features to make developing Gen AI tools for databases seamless.
+For more information, read more about the following:
+
+- [Authenticated Parameters](https://googleapis.github.io/genai-toolbox/resources/tools/#authenticated-parameters): bind tool inputs to values from OIDC tokens automatically, making it easy to run sensitive queries without potentially leaking data
+- [Authorized Invocations](https://googleapis.github.io/genai-toolbox/resources/tools/#authorized-invocations): restrict access to use a tool based on the users Auth token
+- [OpenTelemetry](https://googleapis.github.io/genai-toolbox/how-to/export_telemetry/): get metrics and tracing from Toolbox with [OpenTelemetry](https://opentelemetry.io/docs/)
@@ -1,5 +1,5 @@
 {
  "title": "Integration",
  "description": "See our integrations",
-  "pages": ["open-llm-metry", "lang-trace", "vercel"]
+  "pages": ["open-llm-metry", "lang-trace", "mcp-toolbox", "vercel"]
 }
@@ -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"
+  ]
 }
@@ -101,6 +101,9 @@ const agent = agent({
 });
 ```

+You can also use [MCP Toolbox for
+Databases](/docs/llamaindex/integration/mcp-toolbox) to interact with MCP tools.
+

 ## Function tool

@@ -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 +60,67 @@ 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_4_SONNET = "apac.anthropic.claude-sonnet-4-20250514-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 +128,11 @@ 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 +161,7 @@ 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',
@@ -0,0 +1,47 @@
+---
+title: Custom Model Per Request 
+---
+
+There are scenarios, such as the case of a multi-tenant backend API, where it may be required to handle each request with a custom model.
+
+In such a scenario, modifying the `Settings` object directly as follows is not recommended:
+
+```typescript
+import { Settings } from 'llamaindex';
+import { OpenAIEmbedding } from '@llamaindex/embeddings-openai';
+
+Settings.embedModel = new OpenAIEmbedding({ apiKey: 'CLIENT_API_KEY' });
+Settings.llm = openai({ apiKey: key,  model: 'gpt-4o' })
+```
+
+Setting `llm` and `embedModel` directly will lead to unpredictable responses, since `Settings` is global and mutable.
+This can lead to race conditions, as each request modifies `Settings.embedModel` or `Settings.llm`.
+
+The recommended approach is to use `Settings.withEmbedModel` or `Settings.withLLM` as follows:
+
+```typescript
+const embedModel = new OpenAIEmbedding({
+  apiKey: process.env.OPENAI_API_KEY,
+});
+const llm = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
+
+const llmResponse = await Settings.withEmbedModel(embedModel, async () => {
+  return Settings.withLLM(llm, async () => {
+    const path = "node_modules/llamaindex/examples/abramov.txt";
+    const essay = await fs.readFile(path, "utf-8");
+    // Create Document object with essay
+    const document = new Document({ text: essay, id_: path });
+    // Split text and create embeddings. Store them in a VectorStoreIndex
+    const index = await VectorStoreIndex.fromDocuments([document]);
+    // Query the index
+    const queryEngine = index.asQueryEngine();
+    const { message, sourceNodes } = await queryEngine.query({
+      query: "What did the author do in college?",
+    });
+    // Return response with sources
+    return message.content;
+  });
+});
+```
+
+The full example can be found [here](https://github.com/run-llama/LlamaIndexTS/tree/main/examples/local-settings).
@@ -93,4 +93,4 @@ async function main() {
 main().catch(console.error);
 ```

-You can see the [full example file](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/vectorIndexLocal.ts).
+You can see the [full example file](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/index/vectorIndexLocal.ts).
@@ -7,6 +7,7 @@
    "workflows",
    "local_llm",
    "chatbot",
-    "structured_data_extraction"
+    "structured_data_extraction",
+    "custom_model_per_request"
  ]
 }
@@ -46,3 +46,31 @@ You should expect output something like:
  ]
 }
 ```
+
+## Using the `exec` method
+
+Many LLMs do not natively support structured output, and often rely exclusively on prompt or context engineering.
+
+In this sense, we proved you with an alternative for structured data extraction, using the `exec` method with `responseFormat`.
+
+For example, you can, in a new folder, install our Anthropic integration and `zod` v3:
+
+```package-install
+npm init
+npm i -D typescript @types/node
+npm i @llamaindex/anthropic zod@3.25.76
+```
+
+And then try extracting data with this code:
+
+<include cwd>../../examples/agents/tools/response-format-exec.ts</include>
+
+The output should look like this:
+
+```json
+{
+  "title": "La Divina Commedia",
+  "author": "Dante Alighieri",
+  "year": 1321
+}
+```
@@ -1,5 +1,85 @@
 # @llamaindex/cloudflare-worker-agent-test

+## 0.0.190
+
+### Patch Changes
+
+- Updated dependencies [8929dcf]
+  - llamaindex@0.11.29
+
+## 0.0.189
+
+### Patch Changes
+
+- llamaindex@0.11.28
+
+## 0.0.188
+
+### Patch Changes
+
+- llamaindex@0.11.27
+
+## 0.0.187
+
+### Patch Changes
+
+- llamaindex@0.11.26
+
+## 0.0.186
+
+### Patch Changes
+
+- Updated dependencies [049471b]
+  - llamaindex@0.11.25
+
+## 0.0.185
+
+### Patch Changes
+
+- llamaindex@0.11.24
+
+## 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
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.177",
+  "version": "0.0.190",
  "type": "module",
  "private": true,
  "scripts": {
@@ -1,5 +1,77 @@
 # @llamaindex/llama-parse-browser-test

+## 0.0.87
+
+### Patch Changes
+
+- @llamaindex/cloud@4.1.3
+
+## 0.0.86
+
+### Patch Changes
+
+- @llamaindex/cloud@4.1.2
+
+## 0.0.85
+
+### Patch Changes
+
+- Updated dependencies [4b51791]
+  - @llamaindex/cloud@4.1.1
+
+## 0.0.84
+
+### Patch Changes
+
+- Updated dependencies [049471b]
+  - @llamaindex/cloud@4.1.0
+
+## 0.0.83
+
+### Patch Changes
+
+- Updated dependencies [c3bf3c7]
+  - @llamaindex/cloud@4.0.28
+
+## 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
@@ -1,7 +1,7 @@
 {
  "name": "@llamaindex/llama-parse-browser-test",
  "private": true,
-  "version": "0.0.76",
+  "version": "0.0.87",
  "type": "module",
  "scripts": {
    "dev": "vite",
@@ -10,7 +10,7 @@
  },
  "devDependencies": {
    "typescript": "^5.8.3",
-    "vite": "^6.3.3",
+    "vite": "^6.3.6",
    "vite-plugin-wasm": "^3.4.1"
  },
  "dependencies": {
@@ -1,5 +1,85 @@
 # @llamaindex/next-agent-test

+## 0.1.190
+
+### Patch Changes
+
+- Updated dependencies [8929dcf]
+  - llamaindex@0.11.29
+
+## 0.1.189
+
+### Patch Changes
+
+- llamaindex@0.11.28
+
+## 0.1.188
+
+### Patch Changes
+
+- llamaindex@0.11.27
+
+## 0.1.187
+
+### Patch Changes
+
+- llamaindex@0.11.26
+
+## 0.1.186
+
+### Patch Changes
+
+- Updated dependencies [049471b]
+  - llamaindex@0.11.25
+
+## 0.1.185
+
+### Patch Changes
+
+- llamaindex@0.11.24
+
+## 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
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/next-agent-test",
-  "version": "0.1.177",
+  "version": "0.1.190",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -1,5 +1,85 @@
 # test-edge-runtime

+## 0.1.189
+
+### Patch Changes
+
+- Updated dependencies [8929dcf]
+  - llamaindex@0.11.29
+
+## 0.1.188
+
+### Patch Changes
+
+- llamaindex@0.11.28
+
+## 0.1.187
+
+### Patch Changes
+
+- llamaindex@0.11.27
+
+## 0.1.186
+
+### Patch Changes
+
+- llamaindex@0.11.26
+
+## 0.1.185
+
+### Patch Changes
+
+- Updated dependencies [049471b]
+  - llamaindex@0.11.25
+
+## 0.1.184
+
+### Patch Changes
+
+- llamaindex@0.11.24
+
+## 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
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.176",
+  "version": "0.1.189",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -1,5 +1,118 @@
 # @llamaindex/next-node-runtime

+## 0.1.61
+
+### Patch Changes
+
+- Updated dependencies [8929dcf]
+  - llamaindex@0.11.29
+  - @llamaindex/huggingface@0.1.29
+  - @llamaindex/readers@3.1.20
+
+## 0.1.60
+
+### Patch Changes
+
+- llamaindex@0.11.28
+- @llamaindex/huggingface@0.1.28
+
+## 0.1.59
+
+### Patch Changes
+
+- llamaindex@0.11.27
+- @llamaindex/huggingface@0.1.27
+- @llamaindex/readers@3.1.19
+
+## 0.1.58
+
+### Patch Changes
+
+- @llamaindex/huggingface@0.1.26
+
+## 0.1.57
+
+### Patch Changes
+
+- @llamaindex/huggingface@0.1.25
+
+## 0.1.56
+
+### Patch Changes
+
+- llamaindex@0.11.26
+
+## 0.1.55
+
+### Patch Changes
+
+- Updated dependencies [049471b]
+  - llamaindex@0.11.25
+
+## 0.1.54
+
+### Patch Changes
+
+- llamaindex@0.11.24
+- @llamaindex/huggingface@0.1.24
+- @llamaindex/readers@3.1.18
+
+## 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
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.1.45",
+  "version": "0.1.61",
  "private": true,
  "scripts": {
    "dev": "next dev",
@@ -1,5 +1,85 @@
 # vite-import-llamaindex

+## 0.0.56
+
+### Patch Changes
+
+- Updated dependencies [8929dcf]
+  - llamaindex@0.11.29
+
+## 0.0.55
+
+### Patch Changes
+
+- llamaindex@0.11.28
+
+## 0.0.54
+
+### Patch Changes
+
+- llamaindex@0.11.27
+
+## 0.0.53
+
+### Patch Changes
+
+- llamaindex@0.11.26
+
+## 0.0.52
+
+### Patch Changes
+
+- Updated dependencies [049471b]
+  - llamaindex@0.11.25
+
+## 0.0.51
+
+### Patch Changes
+
+- llamaindex@0.11.24
+
+## 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
@@ -1,11 +1,12 @@
 {
  "name": "vite-import-llamaindex",
  "private": true,
-  "version": "0.0.43",
+  "version": "0.0.56",
  "type": "module",
  "scripts": {
    "build": "vite build",
-    "size-limit": "size-limit"
+    "size-limit": "size-limit",
+    "ci-build": "pnpm -C ../../../ build && vite build"
  },
  "size-limit": [
    {
@@ -16,7 +17,7 @@
    "@size-limit/preset-big-lib": "^11.1.6",
    "size-limit": "^11.1.6",
    "typescript": "^5.8.3",
-    "vite": "^6.3.3"
+    "vite": "^6.3.6"
  },
  "dependencies": {
    "llamaindex": "workspace:*"
@@ -1,5 +1,85 @@
 # @llamaindex/waku-query-engine-test

+## 0.0.190
+
+### Patch Changes
+
+- Updated dependencies [8929dcf]
+  - llamaindex@0.11.29
+
+## 0.0.189
+
+### Patch Changes
+
+- llamaindex@0.11.28
+
+## 0.0.188
+
+### Patch Changes
+
+- llamaindex@0.11.27
+
+## 0.0.187
+
+### Patch Changes
+
+- llamaindex@0.11.26
+
+## 0.0.186
+
+### Patch Changes
+
+- Updated dependencies [049471b]
+  - llamaindex@0.11.25
+
+## 0.0.185
+
+### Patch Changes
+
+- llamaindex@0.11.24
+
+## 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
@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.177",
+  "version": "0.0.190",
  "type": "module",
  "private": true,
  "scripts": {
@@ -44,9 +44,7 @@ export const getWeatherTool = FunctionTool.from(
    name: "getWeather",
    description: "Get the weather for a city",
    parameters: z.object({
-      city: z.string({
-        description: "The city to get the weather for",
-      }),
+      city: z.string().describe("The city to get the weather for"),
    }),
  },
 );
@@ -23,7 +23,7 @@ await test("pinecone", async (t) => {
  });

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

  t.after(async () => {
@@ -1,5 +1,476 @@
 # examples

+## 0.3.41
+
+### Patch Changes
+
+- Updated dependencies [8929dcf]
+- Updated dependencies [5da1cda]
+- Updated dependencies [5d5cd44]
+- Updated dependencies [c40adaf]
+  - llamaindex@0.11.29
+  - @llamaindex/core@0.6.21
+  - @llamaindex/tools@0.1.11
+  - @llamaindex/workflow@1.1.23
+  - @llamaindex/ollama@0.1.22
+  - @llamaindex/openai@0.4.19
+  - @llamaindex/vercel@0.1.21
+  - @llamaindex/anthropic@0.3.24
+  - @llamaindex/google@0.3.21
+  - @llamaindex/cloud@4.1.3
+  - @llamaindex/node-parser@2.0.21
+  - @llamaindex/assemblyai@0.1.20
+  - @llamaindex/clip@0.0.75
+  - @llamaindex/cohere@0.0.35
+  - @llamaindex/deepinfra@0.0.75
+  - @llamaindex/discord@0.1.20
+  - @llamaindex/huggingface@0.1.29
+  - @llamaindex/jinaai@0.0.35
+  - @llamaindex/mistral@0.1.21
+  - @llamaindex/mixedbread@0.0.35
+  - @llamaindex/notion@0.1.20
+  - @llamaindex/perplexity@0.0.32
+  - @llamaindex/portkey-ai@0.0.63
+  - @llamaindex/replicate@0.0.63
+  - @llamaindex/bm25-retriever@0.0.10
+  - @llamaindex/astra@0.0.35
+  - @llamaindex/azure@0.1.36
+  - @llamaindex/chroma@0.0.35
+  - @llamaindex/elastic-search@0.1.21
+  - @llamaindex/firestore@1.0.28
+  - @llamaindex/milvus@0.1.30
+  - @llamaindex/mongodb@0.0.36
+  - @llamaindex/pinecone@0.1.21
+  - @llamaindex/postgres@0.0.64
+  - @llamaindex/qdrant@0.1.31
+  - @llamaindex/supabase@0.1.22
+  - @llamaindex/upstash@0.0.35
+  - @llamaindex/weaviate@0.0.36
+  - @llamaindex/voyage-ai@1.0.27
+  - @llamaindex/readers@3.1.20
+  - @llamaindex/deepseek@0.0.37
+  - @llamaindex/fireworks@0.0.35
+  - @llamaindex/groq@0.0.91
+  - @llamaindex/together@0.0.35
+  - @llamaindex/vllm@0.0.61
+  - @llamaindex/xai@0.0.22
+
+## 0.3.40
+
+### Patch Changes
+
+- Updated dependencies [1995b38]
+- Updated dependencies [001a515]
+- Updated dependencies [9d7d205]
+  - @llamaindex/workflow@1.1.22
+  - @llamaindex/openai@0.4.18
+  - llamaindex@0.11.28
+  - @llamaindex/clip@0.0.74
+  - @llamaindex/deepinfra@0.0.74
+  - @llamaindex/deepseek@0.0.36
+  - @llamaindex/fireworks@0.0.34
+  - @llamaindex/groq@0.0.90
+  - @llamaindex/huggingface@0.1.28
+  - @llamaindex/jinaai@0.0.34
+  - @llamaindex/perplexity@0.0.31
+  - @llamaindex/azure@0.1.35
+  - @llamaindex/together@0.0.34
+  - @llamaindex/vllm@0.0.60
+  - @llamaindex/xai@0.0.21
+
+## 0.3.39
+
+### Patch Changes
+
+- Updated dependencies [0267bb0]
+  - @llamaindex/core@0.6.20
+  - @llamaindex/cloud@4.1.2
+  - llamaindex@0.11.27
+  - @llamaindex/node-parser@2.0.20
+  - @llamaindex/anthropic@0.3.23
+  - @llamaindex/assemblyai@0.1.19
+  - @llamaindex/clip@0.0.73
+  - @llamaindex/cohere@0.0.34
+  - @llamaindex/deepinfra@0.0.73
+  - @llamaindex/discord@0.1.19
+  - @llamaindex/google@0.3.20
+  - @llamaindex/huggingface@0.1.27
+  - @llamaindex/jinaai@0.0.33
+  - @llamaindex/mistral@0.1.20
+  - @llamaindex/mixedbread@0.0.34
+  - @llamaindex/notion@0.1.19
+  - @llamaindex/ollama@0.1.21
+  - @llamaindex/openai@0.4.17
+  - @llamaindex/perplexity@0.0.30
+  - @llamaindex/portkey-ai@0.0.62
+  - @llamaindex/replicate@0.0.62
+  - @llamaindex/bm25-retriever@0.0.9
+  - @llamaindex/astra@0.0.34
+  - @llamaindex/azure@0.1.34
+  - @llamaindex/chroma@0.0.34
+  - @llamaindex/elastic-search@0.1.20
+  - @llamaindex/firestore@1.0.27
+  - @llamaindex/milvus@0.1.29
+  - @llamaindex/mongodb@0.0.35
+  - @llamaindex/pinecone@0.1.20
+  - @llamaindex/postgres@0.0.63
+  - @llamaindex/qdrant@0.1.30
+  - @llamaindex/supabase@0.1.21
+  - @llamaindex/upstash@0.0.34
+  - @llamaindex/weaviate@0.0.35
+  - @llamaindex/vercel@0.1.20
+  - @llamaindex/voyage-ai@1.0.26
+  - @llamaindex/readers@3.1.19
+  - @llamaindex/tools@0.1.10
+  - @llamaindex/workflow@1.1.21
+  - @llamaindex/deepseek@0.0.35
+  - @llamaindex/fireworks@0.0.33
+  - @llamaindex/groq@0.0.89
+  - @llamaindex/together@0.0.33
+  - @llamaindex/vllm@0.0.59
+  - @llamaindex/xai@0.0.20
+
+## 0.3.38
+
+### Patch Changes
+
+- Updated dependencies [4c70376]
+  - @llamaindex/openai@0.4.16
+  - @llamaindex/clip@0.0.72
+  - @llamaindex/deepinfra@0.0.72
+  - @llamaindex/deepseek@0.0.34
+  - @llamaindex/fireworks@0.0.32
+  - @llamaindex/groq@0.0.88
+  - @llamaindex/huggingface@0.1.26
+  - @llamaindex/jinaai@0.0.32
+  - @llamaindex/perplexity@0.0.29
+  - @llamaindex/azure@0.1.33
+  - @llamaindex/together@0.0.32
+  - @llamaindex/vllm@0.0.58
+  - @llamaindex/xai@0.0.19
+
+## 0.3.37
+
+### Patch Changes
+
+- Updated dependencies [47a6f5f]
+- Updated dependencies [b80f33e]
+- Updated dependencies [b6409b6]
+- Updated dependencies [b80f33e]
+  - @llamaindex/ollama@0.1.20
+  - @llamaindex/anthropic@0.3.22
+  - @llamaindex/openai@0.4.15
+  - @llamaindex/clip@0.0.71
+  - @llamaindex/deepinfra@0.0.71
+  - @llamaindex/deepseek@0.0.33
+  - @llamaindex/fireworks@0.0.31
+  - @llamaindex/groq@0.0.87
+  - @llamaindex/huggingface@0.1.25
+  - @llamaindex/jinaai@0.0.31
+  - @llamaindex/perplexity@0.0.28
+  - @llamaindex/azure@0.1.32
+  - @llamaindex/together@0.0.31
+  - @llamaindex/vllm@0.0.57
+  - @llamaindex/xai@0.0.18
+
+## 0.3.36
+
+### Patch Changes
+
+- Updated dependencies [4b51791]
+- Updated dependencies [971d37c]
+  - @llamaindex/cloud@4.1.1
+  - @llamaindex/deepseek@0.0.32
+  - llamaindex@0.11.26
+
+## 0.3.35
+
+### Patch Changes
+
+- Updated dependencies [c3bf3c7]
+- Updated dependencies [f9f1de9]
+  - @llamaindex/cloud@4.0.28
+  - @llamaindex/core@0.6.19
+  - llamaindex@0.11.24
+  - @llamaindex/node-parser@2.0.19
+  - @llamaindex/anthropic@0.3.21
+  - @llamaindex/assemblyai@0.1.18
+  - @llamaindex/clip@0.0.70
+  - @llamaindex/cohere@0.0.33
+  - @llamaindex/deepinfra@0.0.70
+  - @llamaindex/discord@0.1.18
+  - @llamaindex/google@0.3.18
+  - @llamaindex/huggingface@0.1.24
+  - @llamaindex/jinaai@0.0.30
+  - @llamaindex/mistral@0.1.19
+  - @llamaindex/mixedbread@0.0.33
+  - @llamaindex/notion@0.1.18
+  - @llamaindex/ollama@0.1.19
+  - @llamaindex/openai@0.4.14
+  - @llamaindex/perplexity@0.0.27
+  - @llamaindex/portkey-ai@0.0.61
+  - @llamaindex/replicate@0.0.61
+  - @llamaindex/bm25-retriever@0.0.8
+  - @llamaindex/astra@0.0.33
+  - @llamaindex/azure@0.1.31
+  - @llamaindex/chroma@0.0.33
+  - @llamaindex/elastic-search@0.1.19
+  - @llamaindex/firestore@1.0.26
+  - @llamaindex/milvus@0.1.28
+  - @llamaindex/mongodb@0.0.34
+  - @llamaindex/pinecone@0.1.19
+  - @llamaindex/postgres@0.0.62
+  - @llamaindex/qdrant@0.1.29
+  - @llamaindex/supabase@0.1.20
+  - @llamaindex/upstash@0.0.33
+  - @llamaindex/weaviate@0.0.34
+  - @llamaindex/vercel@0.1.19
+  - @llamaindex/voyage-ai@1.0.25
+  - @llamaindex/readers@3.1.18
+  - @llamaindex/tools@0.1.9
+  - @llamaindex/workflow@1.1.20
+  - @llamaindex/deepseek@0.0.31
+  - @llamaindex/fireworks@0.0.30
+  - @llamaindex/groq@0.0.86
+  - @llamaindex/together@0.0.30
+  - @llamaindex/vllm@0.0.56
+  - @llamaindex/xai@0.0.17
+
+## 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
@@ -20,9 +20,7 @@ const saveFileTool = tool({
  description:
    "Save the written content into a file that can be downloaded by the user",
  parameters: z.object({
-    content: z.string({
-      description: "The content to save into a file",
-    }),
+    content: z.string().describe("The content to save into a file"),
  }),
  execute: ({ content }: { content: string }) => {
    const filePath = os.tmpdir() + "/report.md";
@@ -17,9 +17,7 @@ const userQuestion = "which are the best comedies after 2010?";
    description:
      "Execute python code in a Jupyter notebook cell and return any result, stdout, stderr, display_data, and error.",
    parameters: z.object({
-      code: z.string({
-        description: "The python code to execute in a single cell.",
-      }),
+      code: z.string().describe("The python code to execute in a single cell."),
    }),
    execute: ({ code }) => {
      console.log(
@@ -26,9 +26,7 @@ const temperatureConverterTool = tool({
  description: "Convert a temperature from Fahrenheit to Celsius",
  name: "fahrenheitToCelsius",
  parameters: z.object({
-    temperature: z.number({
-      description: "The temperature in Fahrenheit",
-    }),
+    temperature: z.number().describe("The temperature in Fahrenheit"),
  }),
  execute: ({ temperature }) => {
    return ((temperature - 32) * 5) / 9;
@@ -39,9 +37,7 @@ const temperatureFetcherTool = tool({
  description: "Fetch the temperature (in Fahrenheit) for a city",
  name: "fetchTemperature",
  parameters: z.object({
-    city: z.string({
-      description: "The city to fetch the temperature for",
-    }),
+    city: z.string().describe("The city to fetch the temperature for"),
  }),
  execute: ({ city }) => {
    const temperature = Math.floor(Math.random() * 58) + 32;
@@ -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) => {
@@ -14,9 +14,7 @@ const weatherTool = tool({
  name: "weather",
  description: "Get the weather",
  parameters: z.object({
-    location: z.string({
-      description: "The location to get the weather for",
-    }),
+    location: z.string().describe("The location to get the weather for"),
  }),
  execute: ({ location }) => {
    return `The weather in ${location} is sunny`;
@@ -27,9 +25,7 @@ const inflationTool = tool({
  name: "inflation",
  description: "Get the inflation",
  parameters: z.object({
-    location: z.string({
-      description: "The location to get the inflation for",
-    }),
+    location: z.string().describe("The location to get the inflation for"),
  }),
  execute: ({ location }) => {
    return `The inflation in ${location} is 2%`;
@@ -41,9 +37,7 @@ const saveFileTool = tool({
  description:
    "Save the written content into a file that can be downloaded by the user",
  parameters: z.object({
-    content: z.string({
-      description: "The content to save into a file",
-    }),
+    content: z.string().describe("The content to save into a file"),
  }),
  execute: ({ content }) => {
    const filePath = "./report.md";
@@ -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);
@@ -14,11 +14,8 @@ const writeJokeSchema = z.object({
    .describe("The topic to write a joke or describe the joke to improve."),
  writtenJoke: z.optional(z.string()).describe("The written joke."),
  retriedTimes: z
-    .number()
-    .default(0)
-    .describe(
-      "The retried times for writing the joke. Always increase this from the input retriedTimes.",
-    ),
+    .optional(z.number().default(0))
+    .describe("The retried times for writing the joke."),
 });

 const critiqueSchema = z.object({
@@ -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");
+})();
@@ -0,0 +1,39 @@
+import { Anthropic } from "@llamaindex/anthropic";
+import { ChatMessage, ToolCall } from "llamaindex";
+import { z } from "zod";
+
+const llm = new Anthropic({ model: "claude-4-0-sonnet" });
+
+const responseSchema = z.object({
+  title: z.string().describe("The title of the book"),
+  author: z.string().describe("The author of the book"),
+  year: z.number().describe("The publication year"),
+});
+
+async function main() {
+  const messages: ChatMessage[] = [];
+  let toolCalls: ToolCall[] = [];
+  do {
+    const result = await llm.exec({
+      messages: [
+        {
+          role: "system",
+          content: `You are a book expert. Your task is, given a user message, extract the title, author and publication year of the book and output them in JSON format.`,
+        },
+        {
+          role: "user",
+          content: `I have been reading La Divina Commedia by Dante Alighieri, published in 1321, which tells the story of a guy who goes through Hell, Purgatory and Heaven just to meet his beloved ex-girlfriend.`,
+        },
+      ],
+      responseFormat: responseSchema,
+    });
+    console.log(result.newMessages[0].content);
+    messages.push(...result.newMessages);
+    toolCalls = result.toolCalls;
+  } while (toolCalls.length == 0);
+
+  console.log(messages[1].content);
+  console.log(toolCalls);
+}
+
+main().catch(console.error);
@@ -22,7 +22,7 @@ const { withState, getContext } = createStatefulMiddleware(() => ({
 const jokeFlow = withState(createWorkflow());

 // Define handlers for each step
-jokeFlow.handle([startEvent], async (event) => {
+jokeFlow.handle([startEvent], async (context, event) => {
  // Prompt the LLM to write a joke
  const prompt = `Write your best joke about ${event.data}. Write the joke between <joke> and </joke> tags.`;
  const response = await llm.complete({ prompt });
@@ -34,7 +34,7 @@ jokeFlow.handle([startEvent], async (event) => {
  return jokeEvent.with({ joke: joke });
 });

-jokeFlow.handle([jokeEvent], async (event) => {
+jokeFlow.handle([jokeEvent], async (context, event) => {
  // Prompt the LLM to critique the joke
  const prompt = `Give a thorough critique of the following joke. If the joke needs improvement, put "IMPROVE" somewhere in the critique: ${event.data.joke}`;
  const response = await llm.complete({ prompt });
@@ -50,9 +50,9 @@ jokeFlow.handle([jokeEvent], async (event) => {
  return resultEvent.with({ joke: event.data.joke, critique: response.text });
 });

-jokeFlow.handle([critiqueEvent], async (event) => {
+jokeFlow.handle([critiqueEvent], async (context, event) => {
  // Keep track of the number of iterations
-  const state = getContext().state;
+  const state = context.state;
  state.numIterations++;

  // Write a new joke based on the previous joke and critique
@@ -29,9 +29,9 @@ async function callLLM(init: { model: string }) {
      description:
        "Execute python code in a Jupyter notebook cell and return any result, stdout, stderr, display_data, and error.",
      parameters: z.object({
-        code: z.string({
-          description: "The python code to execute in a single cell.",
-        }),
+        code: z
+          .string()
+          .describe("The python code to execute in a single cell."),
      }),
    },
  );
@@ -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
@@ -0,0 +1,69 @@
+import { OpenAI, OpenAIEmbedding } from "@llamaindex/openai";
+import express, { Request, Response } from "express";
+import fs from "fs/promises";
+import { Document, Settings, VectorStoreIndex } from "llamaindex";
+
+const app = express();
+const port = 3000;
+
+app.get("/default", async (req: Request, res: Response) => {
+  const embedModel = new OpenAIEmbedding({
+    apiKey: process.env.OPENAI_API_KEY,
+  });
+  const llm = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
+
+  const llmResponse = await Settings.withEmbedModel(embedModel, async () => {
+    return Settings.withLLM(llm, async () => {
+      const path = "node_modules/llamaindex/examples/abramov.txt";
+      const essay = await fs.readFile(path, "utf-8");
+      // Create Document object with essay
+      const document = new Document({ text: essay, id_: path });
+      // Split text and create embeddings. Store them in a VectorStoreIndex
+      const index = await VectorStoreIndex.fromDocuments([document]);
+      // Query the index
+      const queryEngine = index.asQueryEngine();
+      const { message, sourceNodes } = await queryEngine.query({
+        query: "What did the author do in college?",
+      });
+      // Return response with sources
+      return message.content;
+    });
+  });
+  // res.send(message.content)
+  res.send(llmResponse);
+});
+
+app.get("/custom", async (req: Request, res: Response) => {
+  const embedModel = new OpenAIEmbedding({
+    apiKey: process.env.OPENAI_API_KEY,
+    model: "text-embedding-3-small",
+  });
+  const llm = new OpenAI({
+    apiKey: process.env.OPENAI_API_KEY,
+    model: "gpt-3.5-turbo",
+  });
+
+  const llmResponse = await Settings.withEmbedModel(embedModel, async () => {
+    return Settings.withLLM(llm, async () => {
+      const path = "node_modules/llamaindex/examples/abramov.txt";
+      const essay = await fs.readFile(path, "utf-8");
+      // Create Document object with essay
+      const document = new Document({ text: essay, id_: path });
+      // Split text and create embeddings. Store them in a VectorStoreIndex
+      const index = await VectorStoreIndex.fromDocuments([document]);
+      // Query the index
+      const queryEngine = index.asQueryEngine();
+      const { message, sourceNodes } = await queryEngine.query({
+        query: "What did the author do in college?",
+      });
+      // Return response with sources
+      return message.content;
+    });
+  });
+  // res.send(message.content)
+  res.send(llmResponse);
+});
+
+app.listen(port, () => {
+  console.log(`Example app listening on port ${port}`);
+});
@@ -0,0 +1,22 @@
+{
+  "name": "local-settings",
+  "version": "1.0.0",
+  "main": "index.js",
+  "private": "true",
+  "scripts": {
+    "test": "echo \"No tests for example package\""
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC",
+  "description": "",
+  "devDependencies": {
+    "@types/express": "^5.0.3",
+    "typescript": "^5.9.2"
+  },
+  "dependencies": {
+    "@llamaindex/openai": "^0.4.16",
+    "express": "^5.1.0",
+    "llamaindex": "^0.11.26"
+  }
+}
@@ -0,0 +1,8 @@
+{
+  "extends": "../tsconfig.json",
+  "compilerOptions": {
+    "moduleResolution": "node",
+    "types": ["node", "express"]
+  },
+  "include": ["*.ts"]
+}
@@ -0,0 +1,14 @@
+import { anthropic } from "@llamaindex/anthropic";
+import { agent } from "@llamaindex/workflow";
+
+(async function () {
+  const workflow = agent({
+    llm: anthropic({
+      model: "claude-4-1-opus",
+    }),
+  });
+  const result = await workflow.run(
+    "What are three compounds we should consider investigating to advance research into new antibiotics? Why should we consider them?",
+  );
+  console.log(result.data.result);
+})();
@@ -8,9 +8,7 @@ const weatherTool = tool({
  name: "weather",
  description: "Get the weather",
  parameters: z.object({
-    location: z.string({
-      description: "The location to get the weather for",
-    }),
+    location: z.string().describe("The location to get the weather for"),
  }),
  execute: ({ location }) => {
    return `The weather in ${location} is rainy`;
@@ -0,0 +1,9 @@
+import { ollama } from "@llamaindex/ollama";
+
+(async () => {
+  const llm = ollama({
+    model: "gpt-oss:20b",
+  });
+  const response = await llm.complete({ prompt: "How are you?" });
+  console.log("Response:", response.text);
+})();
@@ -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);
@@ -7,9 +7,7 @@ async function main() {
    name: "weather",
    description: "Get the weather",
    parameters: z.object({
-      location: z.string({
-        description: "The location to get the weather for",
-      }),
+      location: z.string().describe("The location to get the weather for"),
    }),
    execute: ({ location }) => {
      return `The weather in ${location} is sunny`;
@@ -1,6 +1,6 @@
 import { openai } from "@ai-sdk/openai";
 import { llamaindex } from "@llamaindex/vercel";
-import { streamText } from "ai";
+import { stepCountIs, streamText } from "ai";
 import { Document, LlamaCloudIndex } from "llamaindex";
 import fs from "node:fs/promises";

@@ -28,7 +28,7 @@ async function main() {
          "get information from your knowledge base to answer questions.", // optional description
      }),
    },
-    maxSteps: 5,
+    stopWhen: stepCountIs(5),
  });

  for await (const textPart of result.textStream) {
@@ -1,6 +1,6 @@
 import { openai } from "@ai-sdk/openai";
 import { llamaindex } from "@llamaindex/vercel";
-import { streamText } from "ai";
+import { stepCountIs, streamText } from "ai";
 import { Document, VectorStoreIndex } from "llamaindex";

 import fs from "node:fs/promises";
@@ -24,7 +24,7 @@ async function main() {
          "get information from your knowledge base to answer questions.", // optional description
      }),
    },
-    maxSteps: 5,
+    stopWhen: stepCountIs(5),
  });

  for await (const textPart of result.textStream) {
@@ -1,77 +1,78 @@
 {
  "name": "@llamaindex/examples",
-  "version": "0.3.29",
+  "version": "0.3.41",
  "private": true,
  "scripts": {
    "lint": "eslint .",
    "start": "echo 'To get started, run `npx tsx <path to example>`'"
  },
  "dependencies": {
-    "@ai-sdk/openai": "^1.0.5",
+    "@ai-sdk/openai": "^2.0.27",
    "@azure/cosmos": "^4.1.1",
    "@azure/identity": "^4.4.1",
    "@azure/search-documents": "^12.1.0",
-    "@llamaindex/anthropic": "^0.3.16",
-    "@llamaindex/assemblyai": "^0.1.13",
-    "@llamaindex/astra": "^0.0.28",
-    "@llamaindex/azure": "^0.1.25",
-    "@llamaindex/bm25-retriever": "^0.0.3",
-    "@llamaindex/chroma": "^0.0.28",
-    "@llamaindex/clip": "^0.0.64",
-    "@llamaindex/cloud": "^4.0.19",
-    "@llamaindex/cohere": "^0.0.28",
-    "@llamaindex/core": "^0.6.14",
-    "@llamaindex/deepinfra": "^0.0.64",
-    "@llamaindex/deepseek": "^0.0.25",
-    "@llamaindex/discord": "^0.1.13",
-    "@llamaindex/elastic-search": "^0.1.14",
+    "@llamaindex/anthropic": "^0.3.24",
+    "@llamaindex/assemblyai": "^0.1.20",
+    "@llamaindex/astra": "^0.0.35",
+    "@llamaindex/azure": "^0.1.36",
+    "@llamaindex/bm25-retriever": "^0.0.10",
+    "@llamaindex/chroma": "^0.0.35",
+    "@llamaindex/clip": "^0.0.75",
+    "@llamaindex/cloud": "^4.1.3",
+    "@llamaindex/cohere": "^0.0.35",
+    "@llamaindex/core": "^0.6.21",
+    "@llamaindex/deepinfra": "^0.0.75",
+    "@llamaindex/deepseek": "^0.0.37",
+    "@llamaindex/discord": "^0.1.20",
+    "@llamaindex/elastic-search": "^0.1.21",
    "@llamaindex/env": "^0.1.30",
-    "@llamaindex/firestore": "^1.0.21",
-    "@llamaindex/fireworks": "^0.0.24",
-    "@llamaindex/google": "^0.3.13",
-    "@llamaindex/groq": "^0.0.80",
-    "@llamaindex/huggingface": "^0.1.18",
-    "@llamaindex/jinaai": "^0.0.24",
-    "@llamaindex/milvus": "^0.1.23",
-    "@llamaindex/mistral": "^0.1.14",
-    "@llamaindex/mixedbread": "^0.0.28",
-    "@llamaindex/mongodb": "^0.0.29",
-    "@llamaindex/node-parser": "^2.0.14",
-    "@llamaindex/notion": "^0.1.13",
-    "@llamaindex/ollama": "^0.1.14",
-    "@llamaindex/openai": "^0.4.8",
-    "@llamaindex/perplexity": "^0.0.21",
-    "@llamaindex/pinecone": "^0.1.14",
-    "@llamaindex/portkey-ai": "^0.0.56",
-    "@llamaindex/postgres": "^0.0.57",
-    "@llamaindex/qdrant": "^0.1.24",
-    "@llamaindex/readers": "^3.1.13",
-    "@llamaindex/replicate": "^0.0.56",
-    "@llamaindex/supabase": "^0.1.14",
-    "@llamaindex/together": "^0.0.24",
-    "@llamaindex/tools": "^0.1.4",
-    "@llamaindex/upstash": "^0.0.28",
-    "@llamaindex/vercel": "^0.1.14",
-    "@llamaindex/vllm": "^0.0.50",
-    "@llamaindex/voyage-ai": "^1.0.20",
-    "@llamaindex/weaviate": "^0.0.29",
-    "@llamaindex/workflow": "^1.1.14",
-    "@llamaindex/xai": "^0.0.11",
+    "@llamaindex/firestore": "^1.0.28",
+    "@llamaindex/fireworks": "^0.0.35",
+    "@llamaindex/google": "^0.3.21",
+    "@llamaindex/groq": "^0.0.91",
+    "@llamaindex/huggingface": "^0.1.29",
+    "@llamaindex/jinaai": "^0.0.35",
+    "@llamaindex/milvus": "^0.1.30",
+    "@llamaindex/mistral": "^0.1.21",
+    "@llamaindex/mixedbread": "^0.0.35",
+    "@llamaindex/mongodb": "^0.0.36",
+    "@llamaindex/node-parser": "^2.0.21",
+    "@llamaindex/notion": "^0.1.20",
+    "@llamaindex/ollama": "^0.1.22",
+    "@llamaindex/openai": "^0.4.19",
+    "@llamaindex/perplexity": "^0.0.32",
+    "@llamaindex/pinecone": "^0.1.21",
+    "@llamaindex/portkey-ai": "^0.0.63",
+    "@llamaindex/postgres": "^0.0.64",
+    "@llamaindex/qdrant": "^0.1.31",
+    "@llamaindex/readers": "^3.1.20",
+    "@llamaindex/replicate": "^0.0.63",
+    "@llamaindex/supabase": "^0.1.22",
+    "@llamaindex/together": "^0.0.35",
+    "@llamaindex/tools": "^0.1.11",
+    "@llamaindex/upstash": "^0.0.35",
+    "@llamaindex/vercel": "^0.1.21",
+    "@llamaindex/vllm": "^0.0.61",
+    "@llamaindex/voyage-ai": "^1.0.27",
+    "@llamaindex/weaviate": "^0.0.36",
+    "@llamaindex/workflow": "^1.1.23",
+    "@llamaindex/xai": "^0.0.22",
    "@notionhq/client": "^4.0.0",
    "@pinecone-database/pinecone": "^4.0.0",
    "@vercel/postgres": "^0.10.0",
-    "ai": "^4.3.17",
+    "ai": "^5.0.39",
    "ajv": "^8.17.1",
    "commander": "^12.1.0",
    "dotenv": "^17.2.0",
    "js-tiktoken": "^1.0.14",
-    "llamaindex": "^0.11.14",
+    "llamaindex": "^0.11.29",
    "mongodb": "6.7.0",
    "postgres": "^3.4.4",
    "wikipedia": "^2.1.2",
-    "zod": "^3.25.76"
+    "zod": "^4.1.5"
  },
  "devDependencies": {
+    "@types/express": "^5.0.3",
    "@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 });
@@ -43,6 +43,11 @@
    "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 +1,85 @@
 # @llamaindex/autotool

+## 8.0.29
+
+### Patch Changes
+
+- Updated dependencies [8929dcf]
+  - llamaindex@0.11.29
+
+## 8.0.28
+
+### Patch Changes
+
+- llamaindex@0.11.28
+
+## 8.0.27
+
+### Patch Changes
+
+- llamaindex@0.11.27
+
+## 8.0.26
+
+### Patch Changes
+
+- llamaindex@0.11.26
+
+## 8.0.25
+
+### Patch Changes
+
+- Updated dependencies [049471b]
+  - llamaindex@0.11.25
+
+## 8.0.24
+
+### Patch Changes
+
+- llamaindex@0.11.24
+
+## 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
@@ -1,5 +1,98 @@
 # @llamaindex/autotool-01-node-example

+## 0.0.137
+
+### Patch Changes
+
+- Updated dependencies [8929dcf]
+  - llamaindex@0.11.29
+  - @llamaindex/autotool@8.0.29
+
+## 0.0.136
+
+### Patch Changes
+
+- llamaindex@0.11.28
+- @llamaindex/autotool@8.0.28
+
+## 0.0.135
+
+### Patch Changes
+
+- llamaindex@0.11.27
+- @llamaindex/autotool@8.0.27
+
+## 0.0.134
+
+### Patch Changes
+
+- llamaindex@0.11.26
+- @llamaindex/autotool@8.0.26
+
+## 0.0.133
+
+### Patch Changes
+
+- Updated dependencies [049471b]
+  - llamaindex@0.11.25
+  - @llamaindex/autotool@8.0.25
+
+## 0.0.132
+
+### Patch Changes
+
+- llamaindex@0.11.24
+- @llamaindex/autotool@8.0.24
+
+## 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
@@ -13,5 +13,5 @@
  "scripts": {
    "start": "node --import tsx --import @llamaindex/autotool/node ./src/index.ts"
  },
-  "version": "0.0.124"
+  "version": "0.0.137"
 }
@@ -6,7 +6,7 @@
    "url": "git+https://github.com/run-llama/LlamaIndexTS.git",
    "directory": "packages/autotool"
  },
-  "version": "8.0.16",
+  "version": "8.0.29",
  "description": "auto transpile your JS function to LLM Agent compatible",
  "files": [
    "dist",
@@ -1,5 +1,82 @@
 # @llamaindex/cloud

+## 4.1.3
+
+### Patch Changes
+
+- Updated dependencies [5da1cda]
+  - @llamaindex/core@0.6.21
+
+## 4.1.2
+
+### Patch Changes
+
+- Updated dependencies [0267bb0]
+  - @llamaindex/core@0.6.20
+
+## 4.1.1
+
+### Patch Changes
+
+- 4b51791: Add deprecation to README
+
+## 4.1.0
+
+### Minor Changes
+
+- 049471b: Add deprecation warning
+
+## 4.0.28
+
+### Patch Changes
+
+- c3bf3c7: Adding support for citations to beta agent data schema
+- Updated dependencies [f9f1de9]
+  - @llamaindex/core@0.6.19
+
+## 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
@@ -1,8 +1,9 @@
 # @llamaindex/cloud

-> LlamaCloud is a new generation of managed parsing, ingestion, and retrieval services, designed to bring production-grade context-augmentation to your LLM and RAG applications.
-
-For more information, see the [API documentation](https://docs.cloud.llamaindex.ai/).
+> [!WARNING]  
+> This package has been deprecated since version 4.1.0.
+> Please migrate to [llama-cloud-services](https://www.npmjs.com/package/llama-cloud-services).
+> See the documentation: https://docs.cloud.llamaindex.ai

 ## License

@@ -1,6 +1,6 @@
 {
  "name": "@llamaindex/cloud",
-  "version": "4.0.21",
+  "version": "4.1.3",
  "type": "module",
  "license": "MIT",
  "scripts": {
@@ -13,20 +13,20 @@
    "./api",
    "./reader",
    "./parse",
-    "./agent"
+    "./beta/agent"
  ],
  "exports": {
    "./openapi.json": "./openapi.json",
-    "./agent": {
+    "./beta/agent": {
      "require": {
-        "types": "./agent/dist/index.d.cts",
-        "default": "./agent/dist/index.cjs"
+        "types": "./beta/agent/dist/index.d.cts",
+        "default": "./beta/agent/dist/index.cjs"
      },
      "import": {
-        "types": "./agent/dist/index.d.ts",
-        "default": "./agent/dist/index.js"
+        "types": "./beta/agent/dist/index.d.ts",
+        "default": "./beta/agent/dist/index.js"
      },
-      "default": "./agent/dist/index.js"
+      "default": "./beta/agent/dist/index.js"
    },
    "./api": {
      "require": {
@@ -1,136 +0,0 @@
-import { createClient, createConfig } from "@hey-api/client-fetch";
-import { getEnv } from "@llamaindex/env";
-import {
-  createAgentDataApiV1BetaAgentDataPost,
-  deleteAgentDataApiV1BetaAgentDataItemIdDelete,
-  getAgentDataApiV1BetaAgentDataItemIdGet,
-  searchAgentDataApiV1BetaAgentDataSearchPost,
-  updateAgentDataApiV1BetaAgentDataItemIdPut,
-  type AgentData,
-  type PaginatedResponseAgentData,
-  type SearchRequest,
-} from "../client";
-
-type AgentClientOptions = {
-  apiKey?: string;
-  baseUrl?: string;
-  collection: string;
-  agentUrlId: string;
-};
-
-/**
- * Async client for agent data operations
- */
-export class AgentClient {
-  private client: ReturnType<typeof createClient>;
-  private baseUrl: string;
-  private headers: Record<string, string>;
-  private collection: string;
-  private agentUrlId: string;
-
-  constructor(options: AgentClientOptions) {
-    this.collection = options.collection;
-    this.agentUrlId = options.agentUrlId;
-    const apiKey = options?.apiKey || getEnv("LLAMA_CLOUD_API_KEY");
-    this.baseUrl = options?.baseUrl || "https://api.cloud.llamaindex.ai/";
-
-    this.headers = {
-      "X-SDK-Name": "llamaindex-ts",
-      ...(apiKey && { Authorization: `Bearer ${apiKey}` }),
-    };
-
-    this.client = createClient(
-      createConfig({
-        baseUrl: this.baseUrl,
-        headers: this.headers,
-      }),
-    );
-  }
-
-  /**
-   * Create new agent data
-   */
-  async createItem<T>(data: T): Promise<AgentData> {
-    const response = await createAgentDataApiV1BetaAgentDataPost({
-      throwOnError: true,
-      body: {
-        collection: this.collection,
-        agent_slug: this.agentUrlId,
-        data: data as Record<string, unknown>,
-      },
-      client: this.client,
-    });
-
-    return response.data;
-  }
-
-  /**
-   * Get agent data by ID
-   */
-  async getItem(id: string): Promise<AgentData | null> {
-    try {
-      const response = await getAgentDataApiV1BetaAgentDataItemIdGet({
-        throwOnError: true,
-        path: { item_id: id },
-        client: this.client,
-      });
-
-      return 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<T>(id: string, data: T): Promise<AgentData> {
-    const response = await updateAgentDataApiV1BetaAgentDataItemIdPut({
-      throwOnError: true,
-      path: { item_id: id },
-      body: {
-        data: data as Record<string, unknown>,
-      },
-      client: this.client,
-    });
-
-    return response.data;
-  }
-
-  /**
-   * Delete agent data
-   */
-  async delete(id: string): Promise<void> {
-    await deleteAgentDataApiV1BetaAgentDataItemIdDelete({
-      throwOnError: true,
-      path: { item_id: id },
-      client: this.client,
-    });
-  }
-
-  /**
-   * List agent data
-   */
-  async list(options: SearchRequest): Promise<PaginatedResponseAgentData> {
-    const response = await searchAgentDataApiV1BetaAgentDataSearchPost({
-      throwOnError: true,
-      body: {
-        ...options,
-      },
-      client: this.client,
-    });
-
-    return response.data;
-  }
-}
-
-export function createAgentClient(options: AgentClientOptions): AgentClient {
-  return new AgentClient(options);
-}
@@ -1 +0,0 @@
-export { AgentClient, createAgentClient } from "./client";
@@ -1,3 +1,10 @@
+// Deprecation warning
+console.warn(`
+The package @llamaindex/cloud has been deprecated since version 4.1.0
+ * Please migrate to llama-cloud-services.
+ * See the documentation: https://docs.cloud.llamaindex.ai
+`);
+
 import { client } from "./client/client.gen";

 client.setConfig({
@@ -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 +1,23 @@
+// Deprecation warning
+console.warn(`
+The package @llamaindex/cloud has been deprecated since version 4.1.0
+ * Please migrate to llama-cloud-services.
+ * See the documentation: https://docs.cloud.llamaindex.ai
+`);
+
+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 +1,163 @@
+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;
+
+/**
+ * Metadata for an extracted field, including confidence and citation information
+ */
+export interface ExtractedFieldMetadata {
+  /** The confidence score for the field, combined with parsing confidence if applicable */
+  confidence?: number;
+  /** The confidence score for the field based on the extracted text only */
+  extracted_confidence?: number;
+  /** The page number that the field occurred on */
+  page_number?: number;
+  /** The original text this field's value was derived from */
+  matching_text?: string;
+}
+
+/**
+ * Dictionary mapping field names to their metadata
+ * Values can be ExtractedFieldMetadata objects, nested dictionaries, or arrays
+ */
+export type ExtractedFieldMetadataDict = Record<
+  string,
+  ExtractedFieldMetadata | Record<string, unknown> | unknown[]
+>;
+
+/**
+ * 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;
+  /** The overall confidence score for the extracted data. */
+  overall_confidence?: number;
+  /** Page links, and perhaps eventually bounding boxes, for individual fields in the extracted data. */
+  field_metadata?: ExtractedFieldMetadataDict;
+  /** 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;
+}
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
github-actions[bot]	5b4a53177e	Release 0.11.29 (#2188 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-09-11 10:44:29 +08:00
Thuc Pham	5da1cda939	feat: support zod v4 & v3 (#2186 ) Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>	2025-09-11 10:34:45 +08:00
Thuc Pham	1285e381bd	feat: add ci-build script for size limit testing (#2194 )	2025-09-10 18:09:47 +08:00
Neha Prasad	5d5cd44276	fix: anthropic temperature parameter not respecting value 0 (#2190 ) Co-authored-by: Marcus Schiesser <marcus.schiesser@googlemail.com>	2025-09-10 11:45:12 +08:00
hunter	ed37c645af	chore: addition of apac claude 4 sonnet to aws records (#2189 )	2025-09-10 11:44:57 +08:00
hunter	c40adafecc	chore: add latest google models (#2191 )	2025-09-10 11:44:30 +08:00
dependabot[bot]	995b465205	chore(deps-dev): bump vite from 6.3.3 to 6.3.6 (#2193 ) Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>	2025-09-10 10:46:55 +08:00
Jeremy B. Merrill	8929dcf1dd	vectorStoreIndex has new option progressCallback (#2187 ) Co-authored-by: Marcus Schiesser <marcus.schiesser@googlemail.com>	2025-09-05 10:37:22 +08:00
github-actions[bot]	af0b79f1cd	Release 0.11.28 (#2174 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-08-28 17:28:15 +08:00
Thuc Pham	1995b38660	chore: bump @llamaindex/workflow-core in @llamaindex/workflow package (#2181 )	2025-08-27 17:30:09 +08:00
Raj Shrestha	001a5159cf	chore: add minimal reasoning effort for gpt5 (#2177 ) Co-authored-by: Raj Shrestha <raj.shrestha@carelon.com>	2025-08-27 11:52:58 +08:00
Zhanghao	9d7d2052e7	fix: fix the problem that the usage field in the streaming response was not handled correctly (#2173 )	2025-08-24 12:33:14 +08:00
Orry	fd90e25f0e	Docs settings per request (#2166 ) Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de> Co-authored-by: Marcus Schiesser <marcus.schiesser@googlemail.com>	2025-08-20 16:31:26 +08:00
github-actions[bot]	97c00d67c3	Release 0.11.27 (#2169 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-08-19 12:11:06 +08:00
Daniel	6ebd7c2f13	fix: bedrock complete using actual modelId (#2172 )	2025-08-19 11:04:32 +08:00
Clelia (Astra) Bertelli	0267bb0e8e	feat: add responseFormat to llm.exec (#2167 )	2025-08-13 12:39:37 +08:00
Marcus Schiesser	7875ee91e6	chore: update chat-ui docs (#2168 )	2025-08-13 12:26:22 +08:00
Orry	e3405fca44	chore: point the local llm full example to the correct URL (#2162 ) Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>	2025-08-08 14:56:35 +08:00
github-actions[bot]	f3bc2b61e7	Release (#2164 )	2025-08-07 15:18:42 -06:00
Logan	4c703767b7	Adding GPT-5 support (#2163 )	2025-08-07 13:39:47 -06:00
github-actions[bot]	a27648200d	Release (#2161 )	2025-08-07 13:39:20 -06:00
abdeliibrahim	c93bb02002	#2159 Remove unneeded console logs from gemini stream (#2160 ) Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>	2025-08-07 11:38:35 +08:00
github-actions[bot]	e9ded4e65f	Release (#2154 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-08-06 12:18:06 +08:00
Marcus Schiesser	47a6f5fe5a	chore: bump ollama (#2156 )	2025-08-06 12:11:17 +08:00
Marcus Schiesser	b80f33e264	chore: add opus 4.1 and fix prompt caching (#2155 )	2025-08-06 11:54:27 +08:00
Alex Yang	b6409b6823	chore: bump openai (#2152 ) Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>	2025-08-06 10:58:45 +08:00
github-actions[bot]	db3f556cb4	Release 0.11.26 (#2149 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-08-05 12:00:17 +08:00
Marcus Schiesser	4b5179169b	chore: add deprecation to readme (#2150 )	2025-08-05 11:53:35 +08:00
abdeliibrahim	971d37ceba	fix(deepseek): add 'as const' assertion to DEEPSEEK_MODELS for correct TypeScript inference (#2148 ) Co-authored-by: Marcus Schiesser <marcus.schiesser@googlemail.com>	2025-08-05 10:30:13 +08:00
github-actions[bot]	3e0ffdc688	Release 0.11.25 (#2144 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>	2025-07-31 12:18:18 +08:00
Marcus Schiesser	049471bade	chore: deprecate cloud packages (#2143 )	2025-07-31 12:12:56 +08:00
github-actions[bot]	1e296ebe72	Release 0.11.24 (#2141 ) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>	2025-07-30 12:56:45 -04:00
Marcus Schiesser	f9f1de9516	chore: use Logger for core (#2139 )	2025-07-30 11:43:45 +08:00
Twisha Bansal	f576812e7a	docs: Using MCP Toolbox for Databases with LlamaIndex (#2138 )	2025-07-30 11:19:34 +08:00
Adrian Lyjak	c3bf3c7178	Adding support for page citations, and refactor the confidence into the field metadata (#2140 )	2025-07-30 10:25:19 +08:00
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
				`@@ -1 +0,0 @@`
				`export { AgentClient, createAgentClient } from "./client";`