Release 0.8.28 (#1559)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: himself65 <himself65@users.noreply.github.com>

.eslintrc.cjs

@@ -1,84 +0,0 @@
-const { join } = require("node:path");
-
-module.exports = {
-  root: true,
-  extends: [
-    "turbo",
-    "prettier",
-    "plugin:@typescript-eslint/recommended-type-checked-only",
-  ],
-  parserOptions: {
-    project: join(__dirname, "tsconfig.eslint.json"),
-    __tsconfigRootDir: __dirname,
-  },
-  settings: {
-    react: {
-      version: "999.999.999",
-    },
-  },
-  rules: {
-    "max-params": ["error", 4],
-    "prefer-const": "error",
-    "@typescript-eslint/no-floating-promises": [
-      "error",
-      {
-        ignoreIIFE: true,
-      },
-    ],
-    "no-debugger": "error",
-    "@typescript-eslint/await-thenable": "off",
-    "@typescript-eslint/ban-ts-comment": "off",
-    "@typescript-eslint/ban-types": "off",
-    "no-array-constructor": "off",
-    "@typescript-eslint/no-array-constructor": "off",
-    "@typescript-eslint/no-base-to-string": [
-      "error",
-      {
-        ignoredTypeNames: ["Error", "RegExp", "URL", "URLSearchParams"],
-      },
-    ],
-    "@typescript-eslint/no-duplicate-enum-values": "off",
-    "@typescript-eslint/no-duplicate-type-constituents": "off",
-    "@typescript-eslint/no-explicit-any": "off",
-    "@typescript-eslint/no-extra-non-null-assertion": "off",
-    "@typescript-eslint/no-for-in-array": "off",
-    "no-implied-eval": "off",
-    "@typescript-eslint/no-implied-eval": "off",
-    "no-loss-of-precision": "off",
-    "@typescript-eslint/no-loss-of-precision": "off",
-    "@typescript-eslint/no-misused-new": "off",
-    "@typescript-eslint/no-misused-promises": "off",
-    "@typescript-eslint/no-namespace": "off",
-    "@typescript-eslint/no-non-null-asserted-optional-chain": "off",
-    "@typescript-eslint/no-redundant-type-constituents": "off",
-    "@typescript-eslint/no-this-alias": "off",
-    "@typescript-eslint/no-unnecessary-type-assertion": "off",
-    "@typescript-eslint/no-unnecessary-type-constraint": "off",
-    "@typescript-eslint/no-unsafe-argument": "off",
-    "@typescript-eslint/no-unsafe-assignment": "off",
-    "@typescript-eslint/no-unsafe-call": "off",
-    "@typescript-eslint/no-unsafe-declaration-merging": "off",
-    "@typescript-eslint/no-unsafe-enum-comparison": "off",
-    "@typescript-eslint/no-unsafe-member-access": "off",
-    "@typescript-eslint/no-unsafe-return": "off",
-    "no-unused-vars": "off",
-    "@typescript-eslint/no-unused-vars": "off",
-    "@typescript-eslint/no-var-requires": "off",
-    "@typescript-eslint/prefer-as-const": "off",
-    "require-await": "off",
-    "@typescript-eslint/require-await": "off",
-    "@typescript-eslint/restrict-plus-operands": "off",
-    "@typescript-eslint/restrict-template-expressions": "off",
-    "@typescript-eslint/triple-slash-reference": "off",
-    "@typescript-eslint/unbound-method": "off",
-  },
-  overrides: [
-    {
-      files: ["examples/**/*.ts"],
-      rules: {
-        "turbo/no-undeclared-env-vars": "off",
-      },
-    },
-  ],
-  ignorePatterns: ["dist/", "lib/", "deps/"],
-};

.github/workflows/test.yml

@@ -23,7 +23,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        node-version: [18.x, 20.x, 22.x]
+        node-version: [18.x, 20.x, 22.x, 23.x]
     name: E2E on Node.js ${{ matrix.node-version }}
     runs-on: ubuntu-latest
     steps:
@@ -53,7 +53,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        node-version: [18.x, 20.x, 22.x]
+        node-version: [18.x, 20.x, 22.x, 23.x]
     name: Test on Node.js ${{ matrix.node-version }}
     runs-on: ubuntu-latest
     steps:
@@ -84,7 +84,9 @@ jobs:
       - name: Build
         run: pnpm run build
       - name: Use Build For Examples
-        run: pnpm link ../packages/llamaindex/
+        run: |
+          pnpm link ../packages/llamaindex/
+          cd readers && pnpm link ../../packages/llamaindex/
         working-directory: ./examples
       - name: Run Type Check
         run: pnpm run type-check
@@ -117,7 +119,7 @@ jobs:
         run: pnpm run build
       - name: Build ${{ matrix.packages }}
         run: pnpm run build
-        working-directory: packages/llamaindex/e2e/examples/${{ matrix.packages }}
+        working-directory: e2e/examples/${{ matrix.packages }}
 
   typecheck-examples:
     runs-on: ubuntu-latest

.prettierignore

@@ -5,3 +5,5 @@ lib/
 dist/
 .docusaurus/
 .source/
+# prttier doesn't support mdx3 we are using
+*.mdx

CONTRIBUTING.md

@@ -2,86 +2,58 @@
 
 ## Structure
 
-This is a monorepo built with Turborepo
+LlamaIndex.TS uses pnpm monorepo.
 
-Right now, for first-time contributors, these three packages are of the highest importance:
+We recommend you to understand the basics of Node.js, TypeScript, pnpm, and of course, LLM before contributing.
 
-- `packages/llamaindex` which is the main NPM library `llamaindex`
-- `examples` is where the demo code lives
-- `apps/docs` is where the code for the documentation of https://ts.llamaindex.ai/ is located
+There are some important folders in the repository:
 
-### Turborepo docs
-
-You can checkout how Turborepo works using the default [README-turborepo.md](/README-turborepo.md)
+- `packages/*`: Contains the source code of the packages. Each package is a separate npm package.
+  - `llamaindex`: The starter package for LlamaIndex.TS, which contains the all sub-packages.
+  - `core`: The core package of LlamaIndex.TS, which contains the abstract classes and interfaces. It is designed for
+    all JS runtime environments.
+  - `env`: The environment package of LlamaIndex.TS, which contains the environment-specific classes and interfaces. It
+    includes compatibility layers for Node.js, Deno, Vercel Edge Runtime, Cloudflare Workers...
+- `apps/*`: The applications based on LlamaIndex.TS.
+  - `next`: Our documentation website based on Next.js.
+- `examples`: The code examples of LlamaIndex.TS using Node.js.
 
 ## Getting Started
 
-Install NodeJS. Preferably v18 using nvm or n.
-
-Inside the LlamaIndexTS directory:
+Make sure you have Node.js LIS (Long-term Support) installed. You can check your Node.js version by running:
 
+```shell
+node -v
+# v20.x.x
 ```
-npm i -g pnpm ts-node
+
+### Use pnpm
+
+```shell
+corepack enable
+```
+
+### Install dependencies
+
+```shell
 pnpm install
 ```
 
-Note: we use pnpm in this repo, which has a lot of the same functionality and CLI options as npm but it does do some things better in a monorepo, like centralizing dependencies and caching.
+### Build the packages
 
-PNPM's has documentation on its [workspace feature](https://pnpm.io/workspaces) and Turborepo had some [useful documentation also](https://turbo.build/repo/docs/core-concepts/monorepos/running-tasks).
-
-### Running Typescript
-
-When we publish to NPM we will have a tsc compiled version of the library in JS. For now, the easiest thing to do is use ts-node.
-
-### Test cases
-
-To run them, run
-
-```
-pnpm run test
-```
-
-To write new test cases write them in [packages/llamaindex/tests](/packages/llamaindex/tests)
-
-We use Vitest https://vitest.dev to write our test cases. Vitest comes with a bunch of built-in assertions using the expect function: https://vitest.dev/api/expect.html#expect
-
-### Demo applications
-
-There is an existing ["example"](/examples/README.md) demos folder with mainly NodeJS scripts. Feel free to add additional demos to that folder. If you would like to try out your changes in the `llamaindex` package with a new demo, you need to run the build command in the README.
-
-You can create new demo applications in the apps folder. Just run pnpm init in the folder after you create it to create its own package.json
-
-### Installing packages
-
-To install packages for a specific package or demo application, run
-
-```
-pnpm add [NPM Package] --filter [package or application i.e. llamaindex or docs]
-```
-
-To install packages for every package or application run
-
-```
-pnpm add -w [NPM Package]
+```shell
+# Build all packages
+turbo build --filter "./packages/*"
 ```
 
 ### Docs
 
-To contribute to the docs, go to the docs website folder and run the Docusaurus instance.
-
-```bash
-cd apps/docs
-pnpm install
-pnpm start
-```
-
-That should start a webserver which will serve the docs on https://localhost:3000
-
-Any changes you make should be reflected in the browser. If you need to regenerate the API docs and find that your TSDoc isn't getting the updates, feel free to remove apps/docs/api. It will automatically regenerate itself when you run pnpm start again.
+See the [docs](./apps/next/README.md) for more information.
 
 ## Changeset
 
-We use [changesets](https://github.com/changesets/changesets) for managing versions and changelogs. To create a new changeset, run in the root folder:
+We use [changesets](https://github.com/changesets/changesets) for managing versions and changelogs. To create a new
+changeset, run in the root folder:
 
 ```
 pnpm changeset
@@ -95,6 +67,6 @@ The [Release Github Action](.github/workflows/release.yml) is automatically gene
 PR called "Release {version}".
 
 This PR will update the `package.json` and `CHANGELOG.md` files of each package according to
-the current changesets in the [.changeset](.changeset/) folder.
+the current changesets in the [.changeset](.changeset) folder.
 
 If this PR is merged it will automatically add version tags to the repository and publish the updated packages to NPM.

README.md

@@ -1,12 +1,16 @@
-# LlamaIndex.TS
+<p align="center">
+  <img height="100" width="100" alt="LlamaIndex logo" src="https://ts.llamaindex.ai/square.svg" />
+</p>
+<h1 align="center">LlamaIndex.TS</h1>
+<h3 align="center">
+  Data framework for your LLM application.
+</h3>
 
 [![NPM Version](https://img.shields.io/npm/v/llamaindex)](https://www.npmjs.com/package/llamaindex)
 [![NPM License](https://img.shields.io/npm/l/llamaindex)](https://www.npmjs.com/package/llamaindex)
 [![NPM Downloads](https://img.shields.io/npm/dm/llamaindex)](https://www.npmjs.com/package/llamaindex)
 [![Discord](https://img.shields.io/discord/1059199217496772688)](https://discord.com/invite/eN6D2HQ4aX)
 
-LlamaIndex is a data framework for your LLM application.
-
 Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in JS runtime environments with TypeScript support.
 
 Documentation: https://ts.llamaindex.ai/
@@ -25,7 +29,7 @@ LlamaIndex.TS aims to be a lightweight, easy to use set of libraries to help you
 
 LlamaIndex.TS supports multiple JS environments, including:
 
-- Node.js (18, 20, 22) ✅
+- Node.js >= 20 ✅
 - Deno ✅
 - Bun ✅
 - Nitro ✅
@@ -57,213 +61,9 @@ pnpm install llamaindex
 yarn add llamaindex
 ```
 
-### Setup TypeScript
+### Setup in Node.js, Deno, Bun, TypeScript...?
 
-```json5
-{
-  compilerOptions: {
-    // ⬇️ add this line to your tsconfig.json
-    moduleResolution: "bundler", // or "node16"
-  },
-}
-```
-
-<details>
-   <summary>Why?</summary>
-  We are shipping both ESM and CJS module, and compatible with Vercel Edge, Cloudflare Workers, and other serverless platforms.
-
-So we are using [conditional exports](https://nodejs.org/api/packages.html#conditional-exports) to support all environments.
-
-This is a kind of modern way of shipping packages, but might cause TypeScript type check to fail because of legacy module resolution.
-
-Imaging you put output file into `/dist/openai.js` but you are importing `llamaindex/openai` in your code, and set `package.json` like this:
-
-```json
-{
-  "exports": {
-    "./openai": "./dist/openai.js"
-  }
-}
-```
-
-In old module resolution, TypeScript will not be able to find the module because it is not follow the file structure, even you run `node index.js` successfully. (on Node.js >=16)
-
-See more about [moduleResolution](https://www.typescriptlang.org/docs/handbook/modules/theory.html#module-resolution) or
-[TypeScript 5.0 blog](https://devblogs.microsoft.com/typescript/announcing-typescript-5-0/#--moduleresolution-bundler7).
-
-</details>
-
-### Node.js
-
-```ts
-import fs from "node:fs/promises";
-import { Document, VectorStoreIndex } from "llamaindex";
-
-async function main() {
-  // Load essay from abramov.txt in Node
-  const essay = await fs.readFile(
-    "node_modules/llamaindex/examples/abramov.txt",
-    "utf-8",
-  );
-
-  // Create Document object with essay
-  const document = new Document({ text: essay });
-
-  // Split text and create embeddings. Store them in a VectorStoreIndex
-  const index = await VectorStoreIndex.fromDocuments([document]);
-
-  // Query the index
-  const queryEngine = index.asQueryEngine();
-  const response = await queryEngine.query({
-    query: "What did the author do in college?",
-  });
-
-  // Output response
-  console.log(response.toString());
-}
-
-main();
-```
-
-```bash
-# `pnpm install tsx` before running the script
-node --import tsx ./main.ts
-```
-
-### Next.js
-
-You will need to add a llamaindex plugin to your Next.js project.
-
-```js
-// next.config.js
-const withLlamaIndex = require("llamaindex/next");
-
-module.exports = withLlamaIndex({
-  // your next.js config
-});
-```
-
-### React Server Actions
-
-You can combine `ai` with `llamaindex` in Next.js, Waku or Redwood.js with RSC (React Server Components).
-
-```tsx
-"use client";
-import { chatWithAgent } from "@/actions";
-import type { JSX } from "react";
-import { useActionState } from "react";
-
-export default function Home() {
-  const [ui, action] = useActionState<JSX.Element | null>(async () => {
-    return chatWithAgent("hello!", []);
-  }, null);
-  return (
-    <main>
-      {ui}
-      <form action={action}>
-        <button>Chat</button>
-      </form>
-    </main>
-  );
-}
-```
-
-```tsx
-// src/actions/index.ts
-"use server";
-import { createStreamableUI } from "ai/rsc";
-import { OpenAIAgent } from "llamaindex";
-import type { ChatMessage } from "llamaindex/llm/types";
-
-export async function chatWithAgent(
-  question: string,
-  prevMessages: ChatMessage[] = [],
-) {
-  const agent = new OpenAIAgent({
-    tools: [
-      // ... adding your tools here
-    ],
-  });
-  const responseStream = await agent.chat(
-    {
-      message: question,
-      chatHistory: prevMessages,
-    },
-    true,
-  );
-  const uiStream = createStreamableUI(<div>loading...</div>);
-  responseStream
-    .pipeTo(
-      new WritableStream({
-        start: () => {
-          uiStream.update("response:");
-        },
-        write: async (message) => {
-          uiStream.append(message.response.delta);
-        },
-      }),
-    )
-    .catch(console.error);
-  return uiStream.value;
-}
-```
-
-### Cloudflare Workers
-
-> [!TIP]
-> Some modules are not supported in Cloudflare Workers which require Node.js APIs.
-
-```ts
-// add `OPENAI_API_KEY` to the `.dev.vars` file
-interface Env {
-  OPENAI_API_KEY: string;
-}
-
-export default {
-  async fetch(
-    request: Request,
-    env: Env,
-    ctx: ExecutionContext,
-  ): Promise<Response> {
-    const { OpenAIAgent, OpenAI } = await import("@llamaindex/openai");
-    const text = await request.text();
-    const agent = new OpenAIAgent({
-      llm: new OpenAI({
-        apiKey: env.OPENAI_API_KEY,
-      }),
-      tools: [],
-    });
-    const responseStream = await agent.chat({
-      stream: true,
-      message: text,
-    });
-    const textEncoder = new TextEncoder();
-    const response = responseStream.pipeThrough<Uint8Array>(
-      new TransformStream({
-        transform: (chunk, controller) => {
-          controller.enqueue(textEncoder.encode(chunk.delta));
-        },
-      }),
-    );
-    return new Response(response);
-  },
-};
-```
-
-### Vite
-
-We have some wasm dependencies for better performance. You can use `vite-plugin-wasm` to load them.
-
-```ts
-import wasm from "vite-plugin-wasm";
-
-export default {
-  plugins: [wasm()],
-  ssr: {
-    external: ["tiktoken"],
-  },
-};
-```
+See our official document: <https://ts.llamaindex.ai/docs/llamaindex/setup/getting-started>
 
 ### Tips when using in non-Node.js environments
 

apps/docs/CHANGELOG.md

@@ -1,5 +1,241 @@
 # docs
 
+## 0.0.134
+
+### Patch Changes
+
+- llamaindex@0.8.28
+- @llamaindex/examples@0.0.21
+
+## 0.0.133
+
+### Patch Changes
+
+- c1850ee: feat: Amazon Nova support via Bedrock
+- Updated dependencies [b504303]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+  - @llamaindex/examples@0.0.20
+
+## 0.0.132
+
+### Patch Changes
+
+- Updated dependencies [3d1808b]
+  - llamaindex@0.8.26
+  - @llamaindex/examples@0.0.19
+
+## 0.0.131
+
+### Patch Changes
+
+- llamaindex@0.8.25
+- @llamaindex/examples@0.0.18
+
+## 0.0.130
+
+### Patch Changes
+
+- Updated dependencies [fd38a25]
+  - @llamaindex/examples@0.0.17
+
+## 0.0.129
+
+### Patch Changes
+
+- Updated dependencies [515f2c1]
+  - llamaindex@0.8.24
+
+## 0.0.128
+
+### Patch Changes
+
+- llamaindex@0.8.23
+
+## 0.0.127
+
+### Patch Changes
+
+- Updated dependencies [819af45]
+  - llamaindex@0.8.22
+
+## 0.0.126
+
+### Patch Changes
+
+- Updated dependencies [83c3897]
+- Updated dependencies [efa2211]
+  - llamaindex@0.8.21
+
+## 0.0.125
+
+### Patch Changes
+
+- Updated dependencies [02b22da]
+  - llamaindex@0.8.20
+
+## 0.0.124
+
+### Patch Changes
+
+- Updated dependencies [90d265c]
+  - llamaindex@0.8.19
+
+## 0.0.123
+
+### Patch Changes
+
+- Updated dependencies [d17450f]
+  - llamaindex@0.8.18
+
+## 0.0.122
+
+### Patch Changes
+
+- llamaindex@0.8.17
+
+## 0.0.121
+
+### Patch Changes
+
+- llamaindex@0.8.16
+
+## 0.0.120
+
+### Patch Changes
+
+- Updated dependencies [3d503cb]
+- Updated dependencies [5dae534]
+  - llamaindex@0.8.15
+
+## 0.0.119
+
+### Patch Changes
+
+- Updated dependencies [630b425]
+  - llamaindex@0.8.14
+
+## 0.0.118
+
+### Patch Changes
+
+- llamaindex@0.8.13
+- @llamaindex/examples@0.0.16
+
+## 0.0.117
+
+### Patch Changes
+
+- @llamaindex/examples@0.0.15
+
+## 0.0.116
+
+### Patch Changes
+
+- llamaindex@0.8.12
+
+## 0.0.115
+
+### Patch Changes
+
+- llamaindex@0.8.11
+
+## 0.0.114
+
+### Patch Changes
+
+- Updated dependencies [f066e50]
+  - llamaindex@0.8.10
+  - @llamaindex/examples@0.0.14
+
+## 0.0.113
+
+### Patch Changes
+
+- Updated dependencies [4fc001c]
+- Updated dependencies [4d4cd8a]
+  - llamaindex@0.8.9
+
+## 0.0.112
+
+### Patch Changes
+
+- Updated dependencies [ad85bd0]
+  - llamaindex@0.8.8
+  - @llamaindex/examples@0.0.13
+
+## 0.0.111
+
+### Patch Changes
+
+- llamaindex@0.8.7
+
+## 0.0.110
+
+### Patch Changes
+
+- Updated dependencies [95a5cc6]
+  - llamaindex@0.8.6
+
+## 0.0.109
+
+### Patch Changes
+
+- Updated dependencies [14cc9eb]
+- Updated dependencies [a6db5dd]
+- Updated dependencies [396b1e1]
+  - llamaindex@0.8.5
+
+## 0.0.108
+
+### Patch Changes
+
+- Updated dependencies [35430d3]
+  - llamaindex@0.8.4
+
+## 0.0.107
+
+### Patch Changes
+
+- llamaindex@0.8.3
+
+## 0.0.106
+
+### Patch Changes
+
+- @llamaindex/examples@0.0.12
+
+## 0.0.105
+
+### Patch Changes
+
+- Updated dependencies [c7a918c]
+  - llamaindex@0.8.2
+
+## 0.0.104
+
+### Patch Changes
+
+- llamaindex@0.8.1
+
+## 0.0.103
+
+### Patch Changes
+
+- Updated dependencies [359fd33]
+- Updated dependencies [efb7e1b]
+- Updated dependencies [98ba1e7]
+- Updated dependencies [620c63c]
+  - llamaindex@0.8.0
+  - @llamaindex/examples@0.0.11
+
+## 0.0.102
+
+### Patch Changes
+
+- Updated dependencies [9df9a8f]
+  - llamaindex@0.7.10
+
 ## 0.0.101
 
 ### Patch Changes

apps/docs/docs/examples/context_aware_agent.mdx

@@ -0,0 +1,63 @@
+---
+sidebar_position: 14
+---
+
+# Context-Aware Agent
+
+The Context-Aware Agent enhances the capabilities of standard LLM agents by incorporating relevant context from a retriever for each query. This allows the agent to provide more informed and specific responses based on the available information.
+
+## Usage
+
+Here's a simple example of how to use the Context-Aware Agent:
+
+```typescript
+import {
+  Document,
+  VectorStoreIndex,
+  OpenAIContextAwareAgent,
+  OpenAI,
+} from "llamaindex";
+
+async function createContextAwareAgent() {
+  // Create and index some documents
+  const documents = [
+    new Document({
+      text: "LlamaIndex is a data framework for LLM applications.",
+      id_: "doc1",
+    }),
+    new Document({
+      text: "The Eiffel Tower is located in Paris, France.",
+      id_: "doc2",
+    }),
+  ];
+
+  const index = await VectorStoreIndex.fromDocuments(documents);
+  const retriever = index.asRetriever({ similarityTopK: 1 });
+
+  // Create the Context-Aware Agent
+  const agent = new OpenAIContextAwareAgent({
+    llm: new OpenAI({ model: "gpt-3.5-turbo" }),
+    contextRetriever: retriever,
+  });
+
+  // Use the agent to answer queries
+  const response = await agent.chat({
+    message: "What is LlamaIndex used for?",
+  });
+
+  console.log("Agent Response:", response.response);
+}
+
+createContextAwareAgent().catch(console.error);
+```
+
+In this example, the Context-Aware Agent uses the retriever to fetch relevant context for each query, allowing it to provide more accurate and informed responses based on the indexed documents.
+
+## Key Components
+
+- `contextRetriever`: A retriever (e.g., from a VectorStoreIndex) that fetches relevant documents or passages for each query.
+
+## Available Context-Aware Agents
+
+- `OpenAIContextAwareAgent`: A context-aware agent using OpenAI's models.
+- `AnthropicContextAwareAgent`: A context-aware agent using Anthropic's models.

apps/docs/docs/guides/agents/4_agentic_rag.mdx

@@ -4,22 +4,23 @@ While an agent that can perform math is nifty (LLMs are usually not very good at
 
 To learn more about RAG, we recommend this [introduction](https://docs.llamaindex.ai/en/stable/getting_started/concepts/) from our Python docs. We'll assume you know the basics:
 
-- You need to parse your source data into chunks of text
-- You need to encode that text as numbers, called embeddings
-- You need to search your embeddings for the most relevant chunks of text
-- You feed your relevant chunks and a query to an LLM to answer a question
+- Parse your source data into chunks of text.
+- Encode that text as numbers, called embeddings.
+- Search your embeddings for the most relevant chunks of text.
+- Use the relevant chunks along with a query to ask an LLM to generate an answer.
 
 We're going to start with the same agent we [built in step 1](https://github.com/run-llama/ts-agents/blob/main/1_agent/agent.ts), but make a few changes. You can find the finished version [in the repository](https://github.com/run-llama/ts-agents/blob/main/2_agentic_rag/agent.ts).
 
 ### New dependencies
 
-We'll be bringing in `SimpleDirectoryReader`, `HuggingFaceEmbedding`, `VectorStoreIndex`, and `QueryEngineTool` from LlamaIndex.TS, as well as the dependencies we previously used.
+We'll be bringing in `SimpleDirectoryReader`, `HuggingFaceEmbedding`, `VectorStoreIndex`, and `QueryEngineTool`, `OpenAIContextAwareAgent` from LlamaIndex.TS, as well as the dependencies we previously used.
 
 ```javascript
 import {
   OpenAI,
   FunctionTool,
   OpenAIAgent,
+  OpenAIContextAwareAgent,
   Settings,
   SimpleDirectoryReader,
   HuggingFaceEmbedding,
@@ -41,7 +42,7 @@ Settings.embedModel = new HuggingFaceEmbedding({
 
 ### Load data using SimpleDirectoryReader
 
-SimpleDirectoryReader is a flexible tool that can read a variety of file formats. We're going to point it at our data directory, which contains just the single PDF file, and get it to return a set of documents.
+`SimpleDirectoryReader` is a flexible tool that can read various file formats. We will point it at our data directory, which contains a single PDF file, and retrieve a set of documents.
 
 ```javascript
 const reader = new SimpleDirectoryReader();
@@ -50,7 +51,7 @@ const documents = await reader.loadData("../data");
 
 ### Index our data
 
-Now we turn our text into embeddings. The `VectorStoreIndex` class takes care of this for us when we use the `fromDocuments` method (it uses the embedding model we defined in `Settings` earlier).
+We will convert our text into embeddings using the `VectorStoreIndex` class through the `fromDocuments` method, which utilizes the embedding model defined earlier in `Settings`.
 
 ```javascript
 const index = await VectorStoreIndex.fromDocuments(documents);
@@ -72,21 +73,35 @@ By default LlamaIndex will retrieve just the 2 most relevant chunks of text. Thi
 retriever.similarityTopK = 10;
 ```
 
-### Create a query engine
+### Approach 1: Create a Context-Aware Agent
 
-And our final step in creating a RAG pipeline is to create a query engine that will use the retriever to find the most relevant chunks of text, and then use the LLM to answer the question.
+With the retriever ready, you can create a **context-aware agent**.
 
 ```javascript
-const queryEngine = await index.asQueryEngine({
-  retriever,
+const agent = new OpenAIContextAwareAgent({
+  contextRetriever: retriever,
 });
+
+// Example query to the context-aware agent
+let response = await agent.chat({
+  message: `What's the budget of San Francisco in 2023-2024?`,
+});
+
+console.log(response);
 ```
 
-### Define the query engine as a tool
+**Expected Output:**
 
-Just as before we created a `FunctionTool`, we're going to create a `QueryEngineTool` that uses our `queryEngine`.
+```md
+The total budget for the City and County of San Francisco for the fiscal year 2023-2024 is $14.6 billion. This represents a $611.8 million, or 4.4 percent, increase over the previous fiscal year's budget. The budget covers various expenditures across different departments and services, including significant allocations to public works, transportation, commerce, public protection, and health services.
+```
+
+### Approach 2: Using QueryEngineTool (Alternative Approach)
+
+If you prefer more flexibility and don't mind additional complexity, you can create a `QueryEngineTool`. This approach allows you to define the query logic, providing a more tailored way to interact with the data, but note that it introduces a delay due to the extra tool call.
 
 ```javascript
+const queryEngine = await index.asQueryEngine({ retriever });
 const tools = [
   new QueryEngineTool({
     queryEngine: queryEngine,
@@ -96,28 +111,18 @@ const tools = [
     },
   }),
 ];
-```
 
-As before, we've created an array of tools with just one tool in it. The metadata is slightly different: we don't need to define our parameters, we just give the tool a name and a natural-language description.
-
-### Create the agent as before
-
-Creating the agent and asking a question is exactly the same as before, but we'll ask a different question.
-
-```javascript
-// create the agent
+// Create an agent using the tools array
 const agent = new OpenAIAgent({ tools });
 
-let response = await agent.chat({
+let toolResponse = await agent.chat({
   message: "What's the budget of San Francisco in 2023-2024?",
 });
 
-console.log(response);
+console.log(toolResponse);
 ```
 
-Once again we'll run `npx tsx agent.ts` and see what we get:
-
-**_Output_**
+**Expected Output:**
 
 ```javascript
 {
@@ -138,28 +143,12 @@ Once again we'll run `npx tsx agent.ts` and see what we get:
 }
 ```
 
-```javascript
-{
-  response: {
-    raw: {
-      id: 'chatcmpl-9KxUkwizVCYCmxwFQcZFSHrInzNFU',
-      object: 'chat.completion',
-      created: 1714782286,
-      model: 'gpt-4-turbo-2024-04-09',
-      choices: [Array],
-      usage: [Object],
-      system_fingerprint: 'fp_ea6eb70039'
-    },
-    message: {
-      content: "The total budget for the City and County of San Francisco for the fiscal year 2023-2024 is $14.6 billion. This represents a $611.8 million, or 4.4 percent, increase over the previous fiscal year's budget. The budget covers various expenditures across different departments and services, including significant allocations to public works, transportation, commerce, public protection, and health services.",
-      role: 'assistant',
-      options: {}
-    }
-  },
-  sources: [Getter]
-}
-```
-
 Once again we see a `toolResult`. You can see the query the LLM decided to send to the query engine ("total budget"), and the output the engine returned. In `response.message` you see that the LLM has returned the output from the tool almost verbatim, although it trimmed out the bit about 2024-2025 since we didn't ask about that year.
 
+### Comparison of Approaches
+
+The `OpenAIContextAwareAgent` approach simplifies the setup by allowing you to directly link the retriever to the agent, making it straightforward to access relevant context for your queries. This is ideal for situations where you want easy integration with existing data sources, like a context chat engine.
+
+On the other hand, using the `QueryEngineTool` offers more flexibility and power. This method allows for customization in how queries are constructed and executed, enabling you to query data from various storages and process them in different ways. However, this added flexibility comes with increased complexity and response time due to the separate tool call and queryEngine generating tool output by LLM that is then passed to the agent.
+
 So now we have an agent that can index complicated documents and answer questions about them. Let's [combine our math agent and our RAG agent](rag_and_tools)!

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

@@ -25,6 +25,7 @@ ANTHROPIC_CLAUDE_3_SONNET = "anthropic.claude-3-sonnet-20240229-v1:0";
 ANTHROPIC_CLAUDE_3_HAIKU = "anthropic.claude-3-haiku-20240307-v1:0";
 ANTHROPIC_CLAUDE_3_OPUS = "anthropic.claude-3-opus-20240229-v1:0"; // available on us-west-2
 ANTHROPIC_CLAUDE_3_5_SONNET = "anthropic.claude-3-5-sonnet-20240620-v1:0";
+ANTHROPIC_CLAUDE_3_5_HAIKU = "anthropic.claude-3-5-haiku-20241022-v1:0";
 META_LLAMA2_13B_CHAT = "meta.llama2-13b-chat-v1";
 META_LLAMA2_70B_CHAT = "meta.llama2-70b-chat-v1";
 META_LLAMA3_8B_INSTRUCT = "meta.llama3-8b-instruct-v1:0";
@@ -36,6 +37,9 @@ META_LLAMA3_2_1B_INSTRUCT = "meta.llama3-2-1b-instruct-v1:0"; // only available
 META_LLAMA3_2_3B_INSTRUCT = "meta.llama3-2-3b-instruct-v1:0"; // only available via inference endpoints (see below)
 META_LLAMA3_2_11B_INSTRUCT = "meta.llama3-2-11b-instruct-v1:0"; // only available via inference endpoints (see below), multimodal and function call supported
 META_LLAMA3_2_90B_INSTRUCT = "meta.llama3-2-90b-instruct-v1:0"; // only available via inference endpoints (see below), multimodal and function call supported
+AMAZON_NOVA_PRO_1 = "amazon.nova-pro-v1:0";
+AMAZON_NOVA_LITE_1 = "amazon.nova-lite-v1:0";
+AMAZON_NOVA_MICRO_1 = "amazon.nova-micro-v1:0";
 ```
 
 You can also use Bedrock's Inference endpoints by using the model names:
@@ -52,6 +56,9 @@ US_META_LLAMA_3_2_1B_INSTRUCT = "us.meta.llama3-2-1b-instruct-v1:0";
 US_META_LLAMA_3_2_3B_INSTRUCT = "us.meta.llama3-2-3b-instruct-v1:0";
 US_META_LLAMA_3_2_11B_INSTRUCT = "us.meta.llama3-2-11b-instruct-v1:0";
 US_META_LLAMA_3_2_90B_INSTRUCT = "us.meta.llama3-2-90b-instruct-v1:0";
+US_AMAZON_NOVA_PRO_1 = "us.amazon.nova-pro-v1:0";
+US_AMAZON_NOVA_LITE_1 = "us.amazon.nova-lite-v1:0";
+US_AMAZON_NOVA_MICRO_1 = "us.amazon.nova-micro-v1:0";
 
 // EU
 EU_ANTHROPIC_CLAUDE_3_HAIKU = "eu.anthropic.claude-3-haiku-20240307-v1:0";

apps/docs/docusaurus.config.js

@@ -1,6 +1,7 @@
 // @ts-check
 // Note: type annotations allow type checking and IDEs autocompletion
 
+// eslint-disable-next-line @typescript-eslint/no-require-imports
 const renderer = require("prism-react-renderer");
 const lightCodeTheme = renderer.themes.github;
 const darkCodeTheme = renderer.themes.dracula;
@@ -39,6 +40,7 @@ const config = {
           // editUrl:
           //   "https://github.com/facebook/docusaurus/tree/main/packages/create-docusaurus/templates/shared/",
           remarkPlugins: [
+            // eslint-disable-next-line @typescript-eslint/no-require-imports
             [require("@docusaurus/remark-plugin-npm2yarn"), { sync: true }],
           ],
         },
@@ -60,6 +62,12 @@ const config = {
     ({
       // Replace with your project's social card
       image: "img/favicon.png", // TODO change this
+      announcementBar: {
+        id: "migrate_to_next",
+        content:
+          'We are migrating to Next.js based documentation. Check it out <a href="https://ts.llamaindex.ai/docs/llamaindex">here</a>!',
+        isCloseable: false,
+      },
       navbar: {
         title: "LlamaIndex.TS",
         logo: {

apps/docs/package.json

@@ -1,6 +1,6 @@
 {
   "name": "docs",
-  "version": "0.0.101",
+  "version": "0.0.134",
   "private": true,
   "scripts": {
     "docusaurus": "docusaurus",
@@ -15,29 +15,29 @@
     "typecheck": "tsc"
   },
   "dependencies": {
-    "@docusaurus/core": "3.5.2",
-    "@docusaurus/remark-plugin-npm2yarn": "3.5.2",
+    "@docusaurus/core": "3.6.1",
+    "@docusaurus/remark-plugin-npm2yarn": "3.6.1",
     "@llamaindex/examples": "workspace:*",
-    "@mdx-js/react": "3.0.1",
-    "clsx": "2.1.1",
+    "@mdx-js/react": "^3.1.0",
+    "clsx": "^2.1.1",
     "llamaindex": "workspace:*",
-    "postcss": "8.4.41",
-    "prism-react-renderer": "2.4.0",
-    "raw-loader": "4.0.2",
-    "react": "18.3.1",
+    "postcss": "^8.4.49",
+    "prism-react-renderer": "^2.4.0",
+    "raw-loader": "^4.0.2",
+    "react": "^18.3.1",
     "react-dom": "18.3.1"
   },
   "devDependencies": {
-    "@docusaurus/module-type-aliases": "3.5.2",
-    "@docusaurus/preset-classic": "3.5.2",
-    "@docusaurus/theme-classic": "3.5.2",
-    "@docusaurus/types": "3.5.2",
+    "@docusaurus/module-type-aliases": "3.6.1",
+    "@docusaurus/preset-classic": "3.6.1",
+    "@docusaurus/theme-classic": "3.6.1",
+    "@docusaurus/types": "3.6.1",
     "@tsconfig/docusaurus": "2.0.3",
-    "@types/node": "^22.5.1",
+    "@types/node": "^22.9.0",
     "docusaurus-plugin-typedoc": "1.0.5",
-    "typedoc": "0.26.6",
-    "typedoc-plugin-markdown": "4.2.6",
-    "typescript": "^5.6.2"
+    "typedoc": "0.26.11",
+    "typedoc-plugin-markdown": "4.2.10",
+    "typescript": "^5.6.3"
   },
   "browserslist": {
     "production": [
@@ -52,6 +52,6 @@
     ]
   },
   "engines": {
-    "node": ">=18"
+    "node": ">=20.0.0"
   }
 }

apps/docs/src/components/HomepageFeatures/index.tsx

@@ -11,16 +11,19 @@ type FeatureItem = {
 const FeatureList: FeatureItem[] = [
   {
     title: "Data Driven",
+    // eslint-disable-next-line @typescript-eslint/no-require-imports
     Svg: require("@site/static/img/undraw_docusaurus_mountain.svg").default,
     description: <>LlamaIndex.TS is all about using your data with LLMs.</>,
   },
   {
     title: "Typescript Native",
+    // eslint-disable-next-line @typescript-eslint/no-require-imports
     Svg: require("@site/static/img/undraw_docusaurus_tree.svg").default,
     description: <>We ❤️ Typescript, and so do our users.</>,
   },
   {
     title: "Built by the Community",
+    // eslint-disable-next-line @typescript-eslint/no-require-imports
     Svg: require("@site/static/img/undraw_docusaurus_react.svg").default,
     description: (
       <>

apps/next/.gitignore

@@ -29,3 +29,5 @@ next-env.d.ts
 
 # build
 /src/content/docs/cloud/api
+/src/content/docs/api
+./types

apps/next/CHANGELOG.md

@@ -0,0 +1,347 @@
+# @llamaindex/doc
+
+## 0.0.32
+
+### Patch Changes
+
+- a9b5b99: feat: build api reference pages for new documentation site
+- Updated dependencies [a9b5b99]
+  - @llamaindex/core@0.4.19
+  - @llamaindex/readers@1.0.21
+  - @llamaindex/cloud@2.0.19
+  - llamaindex@0.8.28
+  - @llamaindex/node-parser@0.0.20
+  - @llamaindex/openai@0.1.44
+
+## 0.0.31
+
+### Patch Changes
+
+- Updated dependencies [b504303]
+- Updated dependencies [e0f6cc3]
+- Updated dependencies [a0e6f57]
+  - llamaindex@0.8.27
+  - @llamaindex/core@0.4.18
+  - @llamaindex/cloud@2.0.18
+  - @llamaindex/node-parser@0.0.19
+  - @llamaindex/openai@0.1.43
+  - @llamaindex/readers@1.0.20
+  - @llamaindex/workflow@0.0.8
+
+## 0.0.30
+
+### Patch Changes
+
+- Updated dependencies [3d1808b]
+  - @llamaindex/core@0.4.17
+  - llamaindex@0.8.26
+  - @llamaindex/openai@0.1.42
+  - @llamaindex/cloud@2.0.17
+  - @llamaindex/node-parser@0.0.18
+  - @llamaindex/readers@1.0.19
+
+## 0.0.29
+
+### Patch Changes
+
+- Updated dependencies [7e8230b]
+- Updated dependencies [8be4589]
+  - @llamaindex/readers@1.0.18
+  - @llamaindex/cloud@2.0.16
+  - @llamaindex/core@0.4.16
+  - @llamaindex/node-parser@0.0.17
+  - @llamaindex/openai@0.1.41
+  - @llamaindex/workflow@0.0.7
+  - llamaindex@0.8.25
+
+## 0.0.28
+
+### Patch Changes
+
+- fd38a25: Add vercel tool adapter to use query engine tool
+
+## 0.0.27
+
+### Patch Changes
+
+- Updated dependencies [515f2c1]
+  - llamaindex@0.8.24
+
+## 0.0.26
+
+### Patch Changes
+
+- @llamaindex/cloud@2.0.15
+- @llamaindex/core@0.4.15
+- llamaindex@0.8.23
+- @llamaindex/node-parser@0.0.16
+- @llamaindex/openai@0.1.40
+- @llamaindex/readers@1.0.17
+
+## 0.0.25
+
+### Patch Changes
+
+- Updated dependencies [819af45]
+  - llamaindex@0.8.22
+  - @llamaindex/cloud@2.0.14
+  - @llamaindex/core@0.4.14
+  - @llamaindex/node-parser@0.0.15
+  - @llamaindex/openai@0.1.39
+  - @llamaindex/readers@1.0.16
+
+## 0.0.24
+
+### Patch Changes
+
+- Updated dependencies [83c3897]
+- Updated dependencies [efa2211]
+  - llamaindex@0.8.21
+
+## 0.0.23
+
+### Patch Changes
+
+- Updated dependencies [02b22da]
+  - llamaindex@0.8.20
+
+## 0.0.22
+
+### Patch Changes
+
+- Updated dependencies [90d265c]
+  - @llamaindex/cloud@2.0.13
+  - @llamaindex/core@0.4.13
+  - llamaindex@0.8.19
+  - @llamaindex/node-parser@0.0.14
+  - @llamaindex/readers@1.0.15
+  - @llamaindex/openai@0.1.38
+
+## 0.0.21
+
+### Patch Changes
+
+- Updated dependencies [d17450f]
+- Updated dependencies [ef4f63d]
+  - llamaindex@0.8.18
+  - @llamaindex/core@0.4.12
+  - @llamaindex/cloud@2.0.12
+  - @llamaindex/node-parser@0.0.13
+  - @llamaindex/openai@0.1.37
+  - @llamaindex/readers@1.0.14
+
+## 0.0.20
+
+### Patch Changes
+
+- Updated dependencies [6d22fa2]
+  - @llamaindex/core@0.4.11
+  - @llamaindex/cloud@2.0.11
+  - llamaindex@0.8.17
+  - @llamaindex/node-parser@0.0.12
+  - @llamaindex/openai@0.1.36
+  - @llamaindex/readers@1.0.13
+
+## 0.0.19
+
+### Patch Changes
+
+- Updated dependencies [e60328b]
+  - @llamaindex/readers@1.0.12
+  - llamaindex@0.8.16
+
+## 0.0.18
+
+### Patch Changes
+
+- Updated dependencies [3d503cb]
+- Updated dependencies [5dae534]
+  - llamaindex@0.8.15
+
+## 0.0.17
+
+### Patch Changes
+
+- Updated dependencies [630b425]
+  - llamaindex@0.8.14
+
+## 0.0.16
+
+### Patch Changes
+
+- Updated dependencies [a7b0ac3]
+- Updated dependencies [ee20c44]
+- Updated dependencies [c69605f]
+  - @llamaindex/core@0.4.10
+  - @llamaindex/workflow@0.0.6
+  - llamaindex@0.8.13
+  - @llamaindex/cloud@2.0.10
+  - @llamaindex/node-parser@0.0.11
+  - @llamaindex/openai@0.1.35
+  - @llamaindex/readers@1.0.11
+
+## 0.0.15
+
+### Patch Changes
+
+- Updated dependencies [ea92b69]
+- Updated dependencies [fadc8b8]
+  - @llamaindex/workflow@0.0.5
+
+## 0.0.14
+
+### Patch Changes
+
+- Updated dependencies [7ae6eaa]
+  - @llamaindex/core@0.4.9
+  - @llamaindex/openai@0.1.34
+  - @llamaindex/cloud@2.0.9
+  - llamaindex@0.8.12
+  - @llamaindex/node-parser@0.0.10
+  - @llamaindex/readers@1.0.10
+
+## 0.0.13
+
+### Patch Changes
+
+- Updated dependencies [f865c98]
+  - @llamaindex/core@0.4.8
+  - @llamaindex/cloud@2.0.8
+  - llamaindex@0.8.11
+  - @llamaindex/node-parser@0.0.9
+  - @llamaindex/openai@0.1.33
+  - @llamaindex/readers@1.0.9
+
+## 0.0.12
+
+### Patch Changes
+
+- Updated dependencies [f066e50]
+- Updated dependencies [d89ebe0]
+- Updated dependencies [fd8c882]
+- Updated dependencies [fd8c882]
+  - llamaindex@0.8.10
+  - @llamaindex/core@0.4.7
+  - @llamaindex/workflow@0.0.4
+  - @llamaindex/cloud@2.0.7
+  - @llamaindex/node-parser@0.0.8
+  - @llamaindex/openai@0.1.32
+  - @llamaindex/readers@1.0.8
+
+## 0.0.11
+
+### Patch Changes
+
+- Updated dependencies [4fc001c]
+- Updated dependencies [4d4cd8a]
+  - llamaindex@0.8.9
+  - @llamaindex/cloud@2.0.6
+  - @llamaindex/core@0.4.6
+  - @llamaindex/node-parser@0.0.7
+  - @llamaindex/openai@0.1.31
+  - @llamaindex/readers@1.0.7
+
+## 0.0.10
+
+### Patch Changes
+
+- Updated dependencies [ad85bd0]
+  - @llamaindex/core@0.4.5
+  - llamaindex@0.8.8
+  - @llamaindex/node-parser@0.0.6
+  - @llamaindex/workflow@0.0.3
+  - @llamaindex/cloud@2.0.5
+  - @llamaindex/openai@0.1.30
+  - @llamaindex/readers@1.0.6
+
+## 0.0.9
+
+### Patch Changes
+
+- @llamaindex/cloud@2.0.4
+- @llamaindex/core@0.4.4
+- llamaindex@0.8.7
+- @llamaindex/node-parser@0.0.5
+- @llamaindex/openai@0.1.29
+- @llamaindex/readers@1.0.5
+
+## 0.0.8
+
+### Patch Changes
+
+- Updated dependencies [95a5cc6]
+  - @llamaindex/core@0.4.3
+  - llamaindex@0.8.6
+  - @llamaindex/cloud@2.0.3
+  - @llamaindex/node-parser@0.0.4
+  - @llamaindex/openai@0.1.28
+  - @llamaindex/readers@1.0.4
+
+## 0.0.7
+
+### Patch Changes
+
+- Updated dependencies [14cc9eb]
+- Updated dependencies [a6db5dd]
+- Updated dependencies [396b1e1]
+  - llamaindex@0.8.5
+  - @llamaindex/cloud@2.0.2
+  - @llamaindex/core@0.4.2
+  - @llamaindex/node-parser@0.0.3
+  - @llamaindex/openai@0.1.27
+  - @llamaindex/readers@1.0.3
+
+## 0.0.6
+
+### Patch Changes
+
+- Updated dependencies [35430d3]
+  - llamaindex@0.8.4
+  - @llamaindex/readers@1.0.2
+
+## 0.0.5
+
+### Patch Changes
+
+- Updated dependencies [2ff0a89]
+  - @llamaindex/node-parser@0.0.2
+  - llamaindex@0.8.3
+
+## 0.0.4
+
+### Patch Changes
+
+- Updated dependencies [0765742]
+  - @llamaindex/workflow@0.0.2
+
+## 0.0.3
+
+### Patch Changes
+
+- Updated dependencies [c7a918c]
+  - llamaindex@0.8.2
+
+## 0.0.2
+
+### Patch Changes
+
+- Updated dependencies [9c73f0a]
+  - @llamaindex/core@0.4.1
+  - @llamaindex/cloud@2.0.1
+  - llamaindex@0.8.1
+  - @llamaindex/openai@0.1.26
+  - @llamaindex/readers@1.0.1
+
+## 0.0.1
+
+### Patch Changes
+
+- Updated dependencies [359fd33]
+- Updated dependencies [efb7e1b]
+- Updated dependencies [98ba1e7]
+- Updated dependencies [620c63c]
+  - @llamaindex/core@0.4.0
+  - llamaindex@0.8.0
+  - @llamaindex/cloud@2.0.0
+  - @llamaindex/openai@0.1.25
+  - @llamaindex/readers@1.0.0

apps/next/README.md

@@ -1,4 +1,4 @@
-# next
+# Docs
 
 This is a Next.js application generated with
 [Create Fumadocs](https://github.com/fuma-nama/fumadocs).
@@ -6,15 +6,10 @@ This is a Next.js application generated with
 Run development server:
 
 ```bash
-npm run dev
-# or
-pnpm dev
-# or
-yarn dev
+turbo run dev
+# turbo will build all required packages before running the dev server
 ```
 
-Open http://localhost:3000 with your browser to see the result.
-
 ## Learn More
 
 To learn more about Next.js and Fumadocs, take a look at the following

apps/next/next.config.mjs

@@ -1,10 +1,35 @@
 import { createMDX } from "fumadocs-mdx/next";
-
+import MonacoWebpackPlugin from "monaco-editor-webpack-plugin";
 const withMDX = createMDX();
 
 /** @type {import('next').NextConfig} */
 const config = {
   reactStrictMode: true,
+  transpilePackages: ["monaco-editor"],
+  serverExternalPackages: ["@huggingface/transformers"],
+  webpack: (config, { isServer }) => {
+    if (Array.isArray(config.target) && config.target.includes("web")) {
+      config.target = ["web", "es2020"];
+    }
+
+    config.resolve.alias = {
+      ...config.resolve.alias,
+      sharp$: false,
+      "onnxruntime-node$": false,
+    };
+    config.resolve.fallback ??= {};
+    config.resolve.fallback.fs = false;
+    if (!isServer) {
+      config.plugins.push(
+        new MonacoWebpackPlugin({
+          languages: ["typescript"],
+          filename: "static/[name].worker.js",
+        }),
+      );
+    }
+    config.resolve.alias["replicate"] = false;
+    return config;
+  },
 };
 
 export default withMDX(config);

apps/next/package.json

@@ -1,45 +1,91 @@
 {
   "name": "@llamaindex/doc",
-  "version": "0.0.0",
+  "version": "0.0.32",
   "private": true,
   "scripts": {
     "build": "pnpm run build:docs && next build",
     "dev": "next dev",
     "start": "next start",
-    "postinstall": "fumadocs-mdx",
-    "build:docs": "node ./scripts/generate-docs.mjs"
+    "postdev": "fumadocs-mdx",
+    "postbuild": "fumadocs-mdx && tsx scripts/post-build.mts",
+    "build:docs": "cross-env NODE_OPTIONS=\"--max-old-space-size=8192\" typedoc && node ./scripts/generate-docs.mjs"
   },
   "dependencies": {
     "@icons-pack/react-simple-icons": "^10.1.0",
-    "@radix-ui/react-icons": "^1.3.0",
+    "@llamaindex/chat-ui": "0.0.9",
+    "@llamaindex/cloud": "workspace:*",
+    "@llamaindex/core": "workspace:*",
+    "@llamaindex/node-parser": "workspace:*",
+    "@llamaindex/openai": "workspace:*",
+    "@llamaindex/readers": "workspace:*",
+    "@llamaindex/workflow": "workspace:*",
+    "@mdx-js/mdx": "^3.1.0",
+    "@number-flow/react": "^0.3.4",
+    "@radix-ui/react-dialog": "^1.1.2",
+    "@radix-ui/react-icons": "^1.3.2",
+    "@radix-ui/react-label": "^2.1.0",
+    "@radix-ui/react-slider": "^1.2.1",
     "@radix-ui/react-slot": "^1.1.0",
+    "@radix-ui/react-tooltip": "^1.1.4",
+    "@vercel/functions": "^1.5.0",
+    "ai": "^3.4.33",
     "class-variance-authority": "^0.7.0",
     "clsx": "2.1.1",
-    "foxact": "^0.2.39",
-    "fumadocs-core": "14.0.2",
-    "fumadocs-mdx": "11.0.0",
-    "fumadocs-openapi": "^5.5.3",
-    "fumadocs-ui": "14.0.2",
+    "foxact": "^0.2.41",
+    "framer-motion": "^11.11.17",
+    "fumadocs-core": "^14.6.0",
+    "fumadocs-docgen": "^1.3.2",
+    "fumadocs-mdx": "^11.1.2",
+    "fumadocs-openapi": "^5.8.2",
+    "fumadocs-twoslash": "^2.0.2",
+    "fumadocs-typescript": "^3.0.2",
+    "fumadocs-ui": "^14.6.0",
     "hast-util-to-jsx-runtime": "^2.3.2",
-    "lucide-react": "^0.436.0",
-    "next": "15.0.0",
+    "llamaindex": "workspace:*",
+    "lucide-react": "^0.460.0",
+    "next": "15.0.3",
+    "next-themes": "^0.4.3",
     "react": "^18.3.1",
     "react-dom": "^18.3.1",
     "react-icons": "^5.3.0",
+    "react-monaco-editor": "^0.56.2",
     "react-text-transition": "^3.1.0",
+    "react-use-measure": "^2.1.1",
+    "rehype-katex": "^7.0.1",
+    "remark-math": "^6.0.0",
     "rimraf": "^6.0.1",
-    "shiki": "^1.22.0",
+    "shiki": "^1.23.1",
+    "shiki-magic-move": "^0.5.0",
+    "swr": "^2.2.5",
     "tailwind-merge": "^2.5.2",
-    "tailwindcss-animate": "^1.0.7"
+    "tailwindcss-animate": "^1.0.7",
+    "tree-sitter": "^0.22.1",
+    "tree-sitter-typescript": "^0.23.2",
+    "use-stick-to-bottom": "^1.0.42",
+    "web-tree-sitter": "^0.24.4",
+    "zod": "^3.23.8"
   },
   "devDependencies": {
+    "@next/env": "^15.0.3",
     "@types/mdx": "^2.0.13",
-    "@types/node": "22.7.8",
+    "@types/node": "22.9.0",
     "@types/react": "^18.3.12",
     "@types/react-dom": "^18.3.1",
     "autoprefixer": "^10.4.20",
-    "postcss": "^8.4.47",
-    "tailwindcss": "^3.4.14",
+    "cross-env": "^7.0.3",
+    "fast-glob": "^3.3.2",
+    "gray-matter": "^4.0.3",
+    "monaco-editor-webpack-plugin": "^7.1.0",
+    "postcss": "^8.4.49",
+    "remark": "^15.0.1",
+    "remark-gfm": "^4.0.0",
+    "remark-mdx": "^3.1.0",
+    "remark-stringify": "^11.0.0",
+    "tailwindcss": "^3.4.15",
+    "tsx": "^4.19.2",
+    "typedoc": "^0.26.11",
+    "typedoc-plugin-markdown": "^4.3.1",
+    "typedoc-plugin-merge-modules": "^6.1.0",
     "typescript": "^5.6.3"
   }
 }

apps/next/public/icons/Amazon_Web_Services_Logo.svg

@@ -0,0 +1,38 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 19.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 304 182" style="enable-background:new 0 0 304 182;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:#252F3E;}
+	.st1{fill-rule:evenodd;clip-rule:evenodd;fill:#FF9900;}
+</style>
+<g>
+	<path class="st0" d="M86.4,66.4c0,3.7,0.4,6.7,1.1,8.9c0.8,2.2,1.8,4.6,3.2,7.2c0.5,0.8,0.7,1.6,0.7,2.3c0,1-0.6,2-1.9,3l-6.3,4.2
+		c-0.9,0.6-1.8,0.9-2.6,0.9c-1,0-2-0.5-3-1.4C76.2,90,75,88.4,74,86.8c-1-1.7-2-3.6-3.1-5.9c-7.8,9.2-17.6,13.8-29.4,13.8
+		c-8.4,0-15.1-2.4-20-7.2c-4.9-4.8-7.4-11.2-7.4-19.2c0-8.5,3-15.4,9.1-20.6c6.1-5.2,14.2-7.8,24.5-7.8c3.4,0,6.9,0.3,10.6,0.8
+		c3.7,0.5,7.5,1.3,11.5,2.2v-7.3c0-7.6-1.6-12.9-4.7-16c-3.2-3.1-8.6-4.6-16.3-4.6c-3.5,0-7.1,0.4-10.8,1.3c-3.7,0.9-7.3,2-10.8,3.4
+		c-1.6,0.7-2.8,1.1-3.5,1.3c-0.7,0.2-1.2,0.3-1.6,0.3c-1.4,0-2.1-1-2.1-3.1v-4.9c0-1.6,0.2-2.8,0.7-3.5c0.5-0.7,1.4-1.4,2.8-2.1
+		c3.5-1.8,7.7-3.3,12.6-4.5c4.9-1.3,10.1-1.9,15.6-1.9c11.9,0,20.6,2.7,26.2,8.1c5.5,5.4,8.3,13.6,8.3,24.6V66.4z M45.8,81.6
+		c3.3,0,6.7-0.6,10.3-1.8c3.6-1.2,6.8-3.4,9.5-6.4c1.6-1.9,2.8-4,3.4-6.4c0.6-2.4,1-5.3,1-8.7v-4.2c-2.9-0.7-6-1.3-9.2-1.7
+		c-3.2-0.4-6.3-0.6-9.4-0.6c-6.7,0-11.6,1.3-14.9,4c-3.3,2.7-4.9,6.5-4.9,11.5c0,4.7,1.2,8.2,3.7,10.6
+		C37.7,80.4,41.2,81.6,45.8,81.6z M126.1,92.4c-1.8,0-3-0.3-3.8-1c-0.8-0.6-1.5-2-2.1-3.9L96.7,10.2c-0.6-2-0.9-3.3-0.9-4
+		c0-1.6,0.8-2.5,2.4-2.5h9.8c1.9,0,3.2,0.3,3.9,1c0.8,0.6,1.4,2,2,3.9l16.8,66.2l15.6-66.2c0.5-2,1.1-3.3,1.9-3.9c0.8-0.6,2.2-1,4-1
+		h8c1.9,0,3.2,0.3,4,1c0.8,0.6,1.5,2,1.9,3.9l15.8,67l17.3-67c0.6-2,1.3-3.3,2-3.9c0.8-0.6,2.1-1,3.9-1h9.3c1.6,0,2.5,0.8,2.5,2.5
+		c0,0.5-0.1,1-0.2,1.6c-0.1,0.6-0.3,1.4-0.7,2.5l-24.1,77.3c-0.6,2-1.3,3.3-2.1,3.9c-0.8,0.6-2.1,1-3.8,1h-8.6c-1.9,0-3.2-0.3-4-1
+		c-0.8-0.7-1.5-2-1.9-4L156,23l-15.4,64.4c-0.5,2-1.1,3.3-1.9,4c-0.8,0.7-2.2,1-4,1H126.1z M254.6,95.1c-5.2,0-10.4-0.6-15.4-1.8
+		c-5-1.2-8.9-2.5-11.5-4c-1.6-0.9-2.7-1.9-3.1-2.8c-0.4-0.9-0.6-1.9-0.6-2.8v-5.1c0-2.1,0.8-3.1,2.3-3.1c0.6,0,1.2,0.1,1.8,0.3
+		c0.6,0.2,1.5,0.6,2.5,1c3.4,1.5,7.1,2.7,11,3.5c4,0.8,7.9,1.2,11.9,1.2c6.3,0,11.2-1.1,14.6-3.3c3.4-2.2,5.2-5.4,5.2-9.5
+		c0-2.8-0.9-5.1-2.7-7c-1.8-1.9-5.2-3.6-10.1-5.2L246,52c-7.3-2.3-12.7-5.7-16-10.2c-3.3-4.4-5-9.3-5-14.5c0-4.2,0.9-7.9,2.7-11.1
+		c1.8-3.2,4.2-6,7.2-8.2c3-2.3,6.4-4,10.4-5.2c4-1.2,8.2-1.7,12.6-1.7c2.2,0,4.5,0.1,6.7,0.4c2.3,0.3,4.4,0.7,6.5,1.1
+		c2,0.5,3.9,1,5.7,1.6c1.8,0.6,3.2,1.2,4.2,1.8c1.4,0.8,2.4,1.6,3,2.5c0.6,0.8,0.9,1.9,0.9,3.3v4.7c0,2.1-0.8,3.2-2.3,3.2
+		c-0.8,0-2.1-0.4-3.8-1.2c-5.7-2.6-12.1-3.9-19.2-3.9c-5.7,0-10.2,0.9-13.3,2.8c-3.1,1.9-4.7,4.8-4.7,8.9c0,2.8,1,5.2,3,7.1
+		c2,1.9,5.7,3.8,11,5.5l14.2,4.5c7.2,2.3,12.4,5.5,15.5,9.6c3.1,4.1,4.6,8.8,4.6,14c0,4.3-0.9,8.2-2.6,11.6
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+	<g>
+		<path class="st1" d="M273.5,143.7c-32.9,24.3-80.7,37.2-121.8,37.2c-57.6,0-109.5-21.3-148.7-56.7c-3.1-2.8-0.3-6.6,3.4-4.4
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+		<path class="st1" d="M287.2,128.1c-4.2-5.4-27.8-2.6-38.5-1.3c-3.2,0.4-3.7-2.4-0.8-4.5c18.8-13.2,49.7-9.4,53.3-5
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+	</g>
+</g>
+</svg>

apps/next/public/icons/Google_2015_logo.svg

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8" standalone="no"?>
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 272 92" width="272" height="92"><path fill="#EA4335" d="M115.75 47.18c0 12.77-9.99 22.18-22.25 22.18s-22.25-9.41-22.25-22.18C71.25 34.32 81.24 25 93.5 25s22.25 9.32 22.25 22.18zm-9.74 0c0-7.98-5.79-13.44-12.51-13.44S80.99 39.2 80.99 47.18c0 7.9 5.79 13.44 12.51 13.44s12.51-5.55 12.51-13.44z"/><path fill="#FBBC05" d="M163.75 47.18c0 12.77-9.99 22.18-22.25 22.18s-22.25-9.41-22.25-22.18c0-12.85 9.99-22.18 22.25-22.18s22.25 9.32 22.25 22.18zm-9.74 0c0-7.98-5.79-13.44-12.51-13.44s-12.51 5.46-12.51 13.44c0 7.9 5.79 13.44 12.51 13.44s12.51-5.55 12.51-13.44z"/><path fill="#4285F4" d="M209.75 26.34v39.82c0 16.38-9.66 23.07-21.08 23.07-10.75 0-17.22-7.19-19.66-13.07l8.48-3.53c1.51 3.61 5.21 7.87 11.17 7.87 7.31 0 11.84-4.51 11.84-13v-3.19h-.34c-2.18 2.69-6.38 5.04-11.68 5.04-11.09 0-21.25-9.66-21.25-22.09 0-12.52 10.16-22.26 21.25-22.26 5.29 0 9.49 2.35 11.68 4.96h.34v-3.61h9.25zm-8.56 20.92c0-7.81-5.21-13.52-11.84-13.52-6.72 0-12.35 5.71-12.35 13.52 0 7.73 5.63 13.36 12.35 13.36 6.63 0 11.84-5.63 11.84-13.36z"/><path fill="#34A853" d="M225 3v65h-9.5V3h9.5z"/><path fill="#EA4335" d="M262.02 54.48l7.56 5.04c-2.44 3.61-8.32 9.83-18.48 9.83-12.6 0-22.01-9.74-22.01-22.18 0-13.19 9.49-22.18 20.92-22.18 11.51 0 17.14 9.16 18.98 14.11l1.01 2.52-29.65 12.28c2.27 4.45 5.8 6.72 10.75 6.72 4.96 0 8.4-2.44 10.92-6.14zm-23.27-7.98l19.82-8.23c-1.09-2.77-4.37-4.7-8.23-4.7-4.95 0-11.84 4.37-11.59 12.93z"/><path fill="#4285F4" d="M35.29 41.41V32H67c.31 1.64.47 3.58.47 5.68 0 7.06-1.93 15.79-8.15 22.01-6.05 6.3-13.78 9.66-24.02 9.66C16.32 69.35.36 53.89.36 34.91.36 15.93 16.32.47 35.3.47c10.5 0 17.98 4.12 23.6 9.49l-6.64 6.64c-4.03-3.78-9.49-6.72-16.97-6.72-13.86 0-24.7 11.17-24.7 25.03 0 13.86 10.84 25.03 24.7 25.03 8.99 0 14.11-3.61 17.39-6.89 2.66-2.66 4.41-6.46 5.1-11.65l-22.49.01z"/></svg>

apps/next/public/icons/Groq_Logo.svg

@@ -0,0 +1,654 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 28.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<!DOCTYPE svg [
+	<!ENTITY ns_extend "http://ns.adobe.com/Extensibility/1.0/">
+	<!ENTITY ns_ai "http://ns.adobe.com/AdobeIllustrator/10.0/">
+	<!ENTITY ns_graphs "http://ns.adobe.com/Graphs/1.0/">
+	<!ENTITY ns_vars "http://ns.adobe.com/Variables/1.0/">
+	<!ENTITY ns_imrep "http://ns.adobe.com/ImageReplacement/1.0/">
+	<!ENTITY ns_sfw "http://ns.adobe.com/SaveForWeb/1.0/">
+	<!ENTITY ns_custom "http://ns.adobe.com/GenericCustomNamespace/1.0/">
+	<!ENTITY ns_adobe_xpath "http://ns.adobe.com/XPath/1.0/">
+]>
+<svg version="1.2" baseProfile="tiny" id="Layer_1" xmlns:x="&ns_extend;" xmlns:i="&ns_ai;" xmlns:graph="&ns_graphs;"
+	 xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px" viewBox="0 0 1000 341.5"
+	 overflow="visible" xml:space="preserve">
+<switch>
+	<foreignObject requiredExtensions="&ns_ai;" x="0" y="0" width="1" height="1">
+		<i:aipgfRef  xlink:href="#adobe_illustrator_pgf">
+		</i:aipgfRef>
+	</foreignObject>
+	<g i:extraneous="self">
+		<path d="M556,7.1c-62.1,0-112.4,50.3-112.4,112.4S493.9,232,556,232s112.4-50.3,112.4-112.4c0,0,0,0,0,0
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+<path fill-rule="evenodd" clip-rule="evenodd" d="M48.9815 14L40.7359 18.7622L23.7198 15.0296L3.80271 23.139L0.484375 14L12.6067 7L24.7327 0L36.8553 7L48.9815 14Z" fill="#7589BE"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M0.484375 13.9994L8.73004 18.7616L13.5099 32.9769L29.6488 45.89L24.733 55.9994L12.6071 48.999L0.484375 41.999V13.9994Z" fill="#B2BFE8"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M30.201 38.4209L24.7344 46.4799V56.0006L32.4913 51.525L36.4881 45.5569" fill="#24386C"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M24.7368 36.9622L16.9766 23.5262L18.6481 19.0731L25.0025 15.9922L32.4904 23.5265L24.7368 36.9622Z" fill="#7589BE"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M16.9756 23.5254L24.7326 28.001V36.9595L17.5584 37.2682L13.2188 31.727L16.9756 23.5254Z" fill="#B2BFE8"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M24.7344 27.9996L32.4913 23.5244L37.7705 32.3147L31.382 37.5931L24.7344 36.9585V27.9996Z" fill="#24386C"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M32.49 51.524L40.7357 56V18.7622L32.7326 14.1433L24.7331 9.52441L16.7299 14.1433L8.73047 18.7622V37.2411L16.7299 41.86L24.7331 46.4793L32.49 41.9996V51.524ZM32.49 32.4789L24.7331 36.9582L16.9761 32.4789V23.524L24.7331 19.0448L32.49 23.524V32.4789Z" fill="#DC244C"/>
+<path d="M24.7361 46.4828V36.9606L17.0195 32.5195V42.0259L24.7361 46.4828Z" fill="url(#paint0_linear_4688_32443)"/>
+</g>
+<defs>
+<linearGradient id="paint0_linear_4688_32443" x1="23.3133" y1="38.7809" x2="15.6239" y2="38.7809" gradientUnits="userSpaceOnUse">
+<stop stop-color="#FF3364"/>
+<stop offset="1" stop-color="#C91540" stop-opacity="0"/>
+</linearGradient>
+<clipPath id="clip0_4688_32443">
+<rect width="166.03" height="56" fill="white" transform="translate(0.484375)"/>
+</clipPath>
+</defs>
+</svg>

apps/next/scripts/generate-docs.mjs

@@ -1,8 +1,12 @@
 import * as OpenAPI from "fumadocs-openapi";
+import { generateFiles } from "fumadocs-typescript";
+import fs from "node:fs";
+import * as path from "node:path";
 import { fileURLToPath } from "node:url";
 import { rimrafSync } from "rimraf";
 
 const out = "./src/content/docs/cloud/api";
+const apiRefOut = "./src/content/docs/api";
 
 // clean generated files
 rimrafSync(out, {
@@ -20,3 +24,63 @@ void OpenAPI.generateFiles({
   output: out,
   groupBy: "tag",
 });
+
+void generateFiles({
+  input: ["./src/content/docs/api/**/*.mdx"],
+  output: (file) => path.resolve(path.dirname(file), path.basename(file)),
+  transformOutput,
+});
+
+function transformOutput(filePath, content) {
+  const fileName = path.basename(filePath);
+  let title = fileName.split(".")[0];
+  let pageContent = content;
+  if (title === "index") title = "LlamaIndex API Reference";
+  return `---\ntitle: ${title}\n---\n\n${transformAbsoluteUrl(pageContent, filePath)}`;
+}
+
+/**
+ * Transforms the content by converting relative MDX links to absolute docs API links
+ * Example: [text](../type-aliases/TaskHandler.mdx) -> [text](/docs/api/type-aliases/TaskHandler)
+ * [text](BaseChatEngine.mdx) -> [text](/docs/api/classes/BaseChatEngine)
+ * [text](BaseVectorStore.mdx#constructors) -> [text](/docs/api/classes/BaseVectorStore#constructors)
+ * [text](TaskStep.mdx) -> [text](/docs/api/type-aliases/TaskStep)
+ */
+function transformAbsoluteUrl(content, filePath) {
+  const group = path.dirname(filePath).split(path.sep).pop();
+  return content.replace(
+    /\]\(([^)]+)\.mdx([^)]*)\)/g,
+    (match, slug, anchor) => {
+      const slugParts = slug.split("/");
+      const fileName = slugParts[slugParts.length - 1];
+      const fileGroup = slugParts[slugParts.length - 2] ?? group;
+      const result = ["/docs/api", fileGroup, fileName, anchor]
+        .filter(Boolean)
+        .join("/");
+      return `](${result})`;
+    },
+  );
+}
+
+// append meta.json for API page
+fs.writeFileSync(
+  path.resolve(apiRefOut, "meta.json"),
+  JSON.stringify(
+    {
+      title: "API Reference",
+      description: "LlamaIndex API Reference",
+      root: true,
+      pages: [
+        "index",
+        "classes",
+        "enumerations",
+        "functions",
+        "interfaces",
+        "type-aliases",
+        "variables",
+      ],
+    },
+    null,
+    2,
+  ),
+);

apps/next/scripts/post-build.mts

@@ -0,0 +1,7 @@
+import env from "@next/env";
+
+import { updateLlamaCloud } from "./update-llamacloud.mjs";
+
+env.loadEnvConfig(process.cwd());
+
+await updateLlamaCloud();

apps/next/scripts/update-llamacloud.mts

@@ -0,0 +1,107 @@
+import { upsertBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPut } from "@llamaindex/cloud/api";
+import fg from "fast-glob";
+import {
+  fileGenerator,
+  remarkDocGen,
+  remarkInstall,
+  typescriptGenerator,
+} from "fumadocs-docgen";
+import matter from "gray-matter";
+import * as fs from "node:fs/promises";
+import path, { relative } from "node:path";
+import { fileURLToPath } from "node:url";
+import { remark } from "remark";
+import remarkGfm from "remark-gfm";
+import remarkMdx from "remark-mdx";
+import remarkStringify from "remark-stringify";
+
+const baseDir = fileURLToPath(new URL("../src/content", import.meta.url));
+
+async function processContent(content: string): Promise<string> {
+  const file = await remark()
+    .use(remarkMdx)
+    .use(remarkGfm)
+    .use(remarkDocGen, { generators: [typescriptGenerator(), fileGenerator()] })
+    .use(remarkInstall, { persist: { id: "package-manager" } })
+    .use(remarkStringify)
+    .process(content);
+
+  return String(file);
+}
+
+export async function updateLlamaCloud(): Promise<void> {
+  const apiKey = process.env.LLAMA_CLOUD_API_KEY;
+
+  const index = process.env.LLAMA_CLOUD_PIPELINE_ID;
+
+  if (!apiKey || !index) {
+    console.log("no api key for LlamaCloud found, skipping");
+    return;
+  }
+
+  const files = await fg([
+    "./src/content/docs/**/*.mdx",
+    "!./src/content/docs/cloud/api/**/*",
+  ]);
+
+  const records: {
+    id: string;
+    title: string;
+    description: string;
+    content: string;
+    category: string | undefined;
+  }[] = [];
+
+  console.log("processing documents for AI");
+  const scan = files.map(async (file) => {
+    const fileContent = await fs.readFile(file);
+    const { content, data } = matter(fileContent.toString());
+
+    const dir = path.dirname(file).split(path.sep).at(3);
+    const category = {
+      cloud: "LlamaCloud",
+      llamaindex: "LlamaIndex.TS",
+    }[dir ?? ""];
+
+    if (data._mdx?.mirror) {
+      return;
+    }
+
+    const processed = await processContent(content);
+    const id = relative(baseDir, file);
+    records.push({
+      id,
+      title: data.title as string,
+      description: data.description as string,
+      content: processed,
+      category,
+    });
+  });
+
+  await Promise.all(scan);
+
+  console.log(`added ${records.length} records`);
+
+  await upsertBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPut({
+    baseUrl: "https://api.cloud.llamaindex.ai/",
+    body: records.map((record) => ({
+      id: record.id,
+      metadata: {
+        title: record.title,
+        description: record.description,
+        documentUrl: record.id,
+        category: record.category,
+      },
+      text: record.content,
+    })),
+    path: {
+      pipeline_id: index,
+    },
+    throwOnError: true,
+    headers: {
+      Authorization: `Bearer ${apiKey}`,
+    },
+  });
+
+  console.log("done");
+}

apps/next/source.config.ts

@@ -1,7 +1,50 @@
+import { rehypeCodeDefaultOptions } from "fumadocs-core/mdx-plugins";
+import { fileGenerator, remarkDocGen, remarkInstall } from "fumadocs-docgen";
 import { defineConfig, defineDocs } from "fumadocs-mdx/config";
+import { transformerTwoslash } from "fumadocs-twoslash";
+import rehypeKatex from "rehype-katex";
+import remarkMath from "remark-math";
 
 export const { docs, meta } = defineDocs({
   dir: "./src/content/docs",
 });
 
-export default defineConfig();
+export default defineConfig({
+  lastModifiedTime: "git",
+  mdxOptions: {
+    rehypeCodeOptions: {
+      inline: "tailing-curly-colon",
+      themes: {
+        light: "catppuccin-latte",
+        dark: "catppuccin-mocha",
+      },
+      transformers: [
+        ...(rehypeCodeDefaultOptions.transformers ?? []),
+        transformerTwoslash(),
+        {
+          name: "transformers:remove-notation-escape",
+          code(hast) {
+            for (const line of hast.children) {
+              if (line.type !== "element") continue;
+
+              const lastSpan = line.children.findLast(
+                (v) => v.type === "element",
+              );
+
+              const head = lastSpan?.children[0];
+              if (head?.type !== "text") return;
+
+              head.value = head.value.replace(/\[\\!code/g, "[!code");
+            }
+          },
+        },
+      ],
+    },
+    remarkPlugins: [
+      remarkMath,
+      [remarkInstall, { persist: { id: "package-manager" } }],
+      [remarkDocGen, { generators: [fileGenerator()] }],
+    ],
+    rehypePlugins: (v) => [rehypeKatex, ...v],
+  },
+});

apps/next/src/actions/index.tsx

@@ -0,0 +1,109 @@
+import { ClientMDXContent } from "@/components/mdx";
+import { BotMessage } from "@/components/message";
+import { Skeleton } from "@/components/ui/skeleton";
+import { LlamaCloudRetriever } from "@/deps/cloud";
+import { ContextChatEngine } from "@llamaindex/core/chat-engine";
+import { Settings } from "@llamaindex/core/global";
+import { ChatMessage } from "@llamaindex/core/llms";
+import { OpenAI } from "@llamaindex/openai";
+import { createAI, createStreamableUI, getMutableAIState } from "ai/rsc";
+import { ReactNode } from "react";
+
+Settings.llm = new OpenAI({
+  model: "gpt-4o",
+});
+
+const retriever = new LlamaCloudRetriever({
+  apiKey: process.env.LLAMA_CLOUD_API_KEY!,
+  baseUrl: "https://api.cloud.llamaindex.ai/",
+
+  pipelineId: process.env.LLAMA_CLOUD_PIPELINE_ID!,
+});
+
+const initialAIState = {
+  messages: [],
+} as {
+  messages: ChatMessage[];
+};
+
+export type UIMessage = {
+  id: number;
+  display: ReactNode;
+};
+
+const initialUIState = {
+  messages: [],
+} as {
+  messages: UIMessage[];
+};
+
+// eslint-disable-next-line @typescript-eslint/no-explicit-any
+const runAsyncFnWithoutBlocking = (fn: (...args: any) => Promise<any>) => {
+  fn().catch((error) => {
+    console.error(error);
+  });
+};
+
+export const AIProvider = createAI({
+  initialAIState,
+  initialUIState,
+  actions: {
+    query: async (message: string): Promise<UIMessage> => {
+      "use server";
+      const chatEngine = new ContextChatEngine({ retriever });
+
+      const id = Date.now();
+      const aiState = getMutableAIState<typeof AIProvider>();
+      aiState.update({
+        ...aiState.get(),
+        messages: [
+          ...aiState.get().messages,
+          {
+            role: "user",
+            content: message,
+          },
+        ],
+      });
+
+      const ui = createStreamableUI(
+        <div className="space-y-2">
+          <Skeleton className="h-4 w-full" />
+          <Skeleton className="h-4 w-full" />
+        </div>,
+      );
+
+      runAsyncFnWithoutBlocking(async () => {
+        const response = await chatEngine.chat({
+          message,
+          chatHistory: aiState.get().messages,
+          stream: true,
+        });
+
+        let content = "";
+
+        for await (const { delta } of response) {
+          content += delta;
+          ui.update(<ClientMDXContent id={id} content={content} />);
+        }
+
+        ui.done();
+
+        aiState.done({
+          ...aiState.get(),
+          messages: [
+            ...aiState.get().messages,
+            {
+              role: "assistant",
+              content,
+            },
+          ],
+        });
+      });
+
+      return {
+        id,
+        display: <BotMessage>{ui.value}</BotMessage>,
+      };
+    },
+  },
+});

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

@@ -2,31 +2,44 @@ import { CodeBlock } from "@/components/code-block";
 import { Contributing } from "@/components/contribution";
 import { CreateAppAnimation } from "@/components/create-app-animation";
 import { Feature } from "@/components/feature";
+import {
+  InfiniteLLMProviders,
+  InfiniteVectorStoreProviders,
+} from "@/components/infinite-providers";
+import { MagicMove } from "@/components/magic-move";
 import { NpmInstall } from "@/components/npm-install";
 import { TextEffect } from "@/components/text-effect";
 import { Button } from "@/components/ui/button";
+import { Skeleton } from "@/components/ui/skeleton";
+import { LEGACY_DOCUMENT_URL } from "@/lib/const";
 import { SiStackblitz } from "@icons-pack/react-simple-icons";
-import { Bot, Terminal } from "lucide-react";
+import {
+  CodeBlock as FumaCodeBlock,
+  Pre,
+} from "fumadocs-ui/components/codeblock";
+import { Blocks, Bot, Footprints, Terminal } from "lucide-react";
 import Link from "next/link";
+import { Suspense } from "react";
 
 export default function HomePage() {
   return (
     <main className="container mx-auto px-4 py-12">
       <h1 className="text-4xl md:text-6xl font-bold text-center mb-4">
-        Build RAG Web App using
+        Build context-augmented web apps using
         <br /> <span className="text-blue-500">LlamaIndex.TS</span>
       </h1>
       <p className="text-xl text-center text-fd-muted-foreground mb-12 ">
-        LlamaIndex.TS is the JS/TS library from our popular Python library
-        llama-index for building LLM applications
+        LlamaIndex.TS is the JS/TS version of{" "}
+        <a href="https://llamaindex.ai">LlamaIndex</a>, the framework for
+        building agentic generative AI applications connected to your data.
       </p>
       <div className="text-center text-lg text-fd-muted-foreground mb-12">
-        <span>Designed for building web applications under </span>
+        <span>Designed for building web applications in </span>
         <TextEffect />
       </div>
 
       <div className="flex flex-wrap justify-center gap-4">
-        <Link href="/docs/llamaindex">
+        <Link href={LEGACY_DOCUMENT_URL}>
           <Button variant="outline">Get Started</Button>
         </Link>
         <NpmInstall />
@@ -43,15 +56,70 @@ export default function HomePage() {
       </div>
       <div className="mt-4" />
       <div className="grid grid-cols-1 border-r md:grid-cols-2">
+        <Feature
+          icon={Footprints}
+          subheading="Progressive"
+          heading="From the simplest to the most complex"
+          description="LlamaIndex.TS is designed to be simple to get started, but powerful enough to build complex, agentic AI applications."
+        >
+          <Suspense
+            fallback={
+              <FumaCodeBlock allowCopy={false}>
+                <Pre>
+                  <div className="space-y-2">
+                    <Skeleton className="h-4 w-[250px]" />
+                    <Skeleton className="h-4 w-[200px]" />
+                  </div>
+                </Pre>
+              </FumaCodeBlock>
+            }
+          >
+            <MagicMove
+              code={[
+                `import { OpenAI } from "llamaindex";
+const llm = new OpenAI();
+const response = await llm.complete({ prompt: "How are you?" });`,
+                `import { OpenAI } from "llamaindex";
+const llm = new OpenAI();
+const response = await llm.chat({
+  messages: [{ content: "Tell me a joke.", role: "user" }],
+});`,
+                `import { OpenAI, ChatMemoryBuffer } from "llamaindex";
+const llm = new OpenAI({ model: 'gpt4o-turbo' });
+const buffer = new ChatMemoryBuffer({
+  tokenLimit: 128_000,
+})
+buffer.put({ content: "Tell me a joke.", role: "user" })
+const response = await llm.chat({
+  messages: buffer.getMessages(),
+  stream: true
+});`,
+                `import { OpenAIAgent, ChatMemoryBuffer } from "llamaindex";
+const agent = new OpenAIAgent({
+  llm,
+  tools: [...myTools]
+  systemPrompt,
+});
+const buffer = new ChatMemoryBuffer({
+  tokenLimit: 128_000,
+})
+buffer.put({ content: "Analysis the data based on the given data.", role: "user" })
+buffer.put({ content: \`\${data}\`, role: "user" })
+const response = await agent.chat({
+  message: buffer.getMessages(),
+});`,
+              ]}
+            />
+          </Suspense>
+        </Feature>
         <Feature
           icon={Bot}
-          subheading="Agent"
-          heading="Build agent for RAG"
-          description="Build agents for RAG using LlamaIndex.TS. Agents are the core building blocks of RAG applications."
+          subheading="Agents"
+          heading="Build agentic RAG applications"
+          description="Truly powerful retrieval-augmented generation applications use agentic techniques, and LlamaIndex.TS makes it easy to build them."
         >
           <CodeBlock
-            code={`
-import { FunctionTool } from "llamaindex";
+            code={`import { FunctionTool } from "llamaindex";
 import { OpenAIAgent } from "@llamaindex/openai";
 
 const interpreterTool = FunctionTool.from(...);
@@ -67,10 +135,31 @@ await agent.chat('...');`}
             lang="ts"
           />
         </Feature>
+        <Feature
+          icon={Blocks}
+          subheading="Providers"
+          heading="LLMs, Data Loaders, Vector Stores and more!"
+          description="LlamaIndex.TS has hundreds of integrations to connect to your data, index it, and query it with LLMs."
+        >
+          <div className="mt-8 flex flex-col gap-8">
+            <div>
+              <h3 className="text-lg font-semibold text-fd-muted-foreground mb-2">
+                LLMs
+              </h3>
+              <InfiniteLLMProviders />
+            </div>
+            <div>
+              <h3 className="text-lg font-semibold text-fd-muted-foreground mb-2">
+                Vector Stores
+              </h3>
+              <InfiniteVectorStoreProviders />
+            </div>
+          </div>
+        </Feature>
         <Feature
           icon={Terminal}
-          subheading="Create Llama CLI"
-          heading="CLI for starting RAG app with one line"
+          subheading="create-llama CLI"
+          heading="Build a RAG app with a single command"
           description="A command line tool to generate LlamaIndex apps, the easiest way to get started with LlamaIndex."
         >
           <div className="my-6">

apps/next/src/app/[...any]/page.tsx

@@ -0,0 +1,11 @@
+import { LEGACY_DOCUMENT_URL } from "@/lib/const";
+import { redirect } from "next/navigation";
+
+export default async function Page(props: {
+  params: Promise<{
+    any: string[];
+  }>;
+}) {
+  const path = await props.params.then(({ any }) => any.join("/"));
+  return redirect(new URL(path, LEGACY_DOCUMENT_URL).toString());
+}

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

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

apps/next/src/app/docs/[[...slug]]/page.tsx

@@ -1,4 +1,7 @@
+import { createMetadata, metadataImage } from "@/lib/metadata";
 import { openapi, source } from "@/lib/source";
+import { Popup, PopupContent, PopupTrigger } from "fumadocs-twoslash/ui";
+import { createTypeTable } from "fumadocs-typescript/ui";
 import defaultMdxComponents from "fumadocs-ui/mdx";
 import {
   DocsBody,
@@ -8,6 +11,8 @@ import {
 } from "fumadocs-ui/page";
 import { notFound } from "next/navigation";
 
+const { AutoTypeTable } = createTypeTable();
+
 export default async function Page(props: {
   params: Promise<{ slug?: string[] }>;
 }) {
@@ -18,7 +23,16 @@ export default async function Page(props: {
   const MDX = page.data.body;
 
   return (
-    <DocsPage toc={page.data.toc} full={page.data.full}>
+    <DocsPage
+      toc={page.data.toc}
+      full={page.data.full}
+      editOnGithub={{
+        owner: "run-llama",
+        repo: "LlamaIndexTS",
+        sha: "main",
+        path: `apps/next/src/content/docs/${page.file.path}`,
+      }}
+    >
       <DocsTitle>{page.data.title}</DocsTitle>
       <DocsDescription>{page.data.description}</DocsDescription>
       <DocsBody>
@@ -26,6 +40,10 @@ export default async function Page(props: {
           components={{
             ...defaultMdxComponents,
             APIPage: openapi.APIPage,
+            Popup,
+            PopupContent,
+            PopupTrigger,
+            AutoTypeTable,
           }}
         />
       </DocsBody>
@@ -44,8 +62,13 @@ export async function generateMetadata(props: {
   const page = source.getPage(params.slug);
   if (!page) notFound();
 
-  return {
-    title: page.data.title,
-    description: page.data.description,
-  };
+  return createMetadata(
+    metadataImage.withImage(page.slugs, {
+      title: page.data.title,
+      description: page.data.description,
+      openGraph: {
+        url: `/docs/${page.slugs.join("/")}`,
+      },
+    }),
+  );
 }

apps/next/src/app/docs/layout.tsx

@@ -1,12 +1,54 @@
 import { baseOptions } from "@/app/layout.config";
+import { AITrigger } from "@/components/ai-chat";
+import { buttonVariants } from "@/components/ui/button";
+import { LEGACY_DOCUMENT_URL } from "@/lib/const";
 import { source } from "@/lib/source";
+import { cn } from "@/lib/utils";
+import "fumadocs-twoslash/twoslash.css";
+import { Banner } from "fumadocs-ui/components/banner";
 import { DocsLayout } from "fumadocs-ui/layouts/docs";
+import { MessageCircle } from "lucide-react";
 import type { ReactNode } from "react";
 
 export default function Layout({ children }: { children: ReactNode }) {
   return (
-    <DocsLayout tree={source.pageTree} {...baseOptions}>
-      {children}
-    </DocsLayout>
+    <>
+      <Banner variant="rainbow" id="welcome">
+        Welcome to the new LlamaIndex.TS documentation! 🎉 If you are looking
+        for the old documentation
+        <a
+          className="underline text-blue-500 ml-1"
+          target="_blank"
+          href={LEGACY_DOCUMENT_URL}
+        >
+          check it here
+        </a>
+        .
+      </Banner>
+      <DocsLayout
+        tree={source.pageTree}
+        {...baseOptions}
+        nav={{
+          ...baseOptions.nav,
+          children: (
+            <AITrigger
+              className={cn(
+                buttonVariants({
+                  variant: "secondary",
+                  size: "xs",
+                  className:
+                    "md:flex-1 px-2 ms-2 gap-1.5 text-fd-muted-foreground rounded-full",
+                }),
+              )}
+            >
+              <MessageCircle className="size-3" />
+              Ask LlamaCloud
+            </AITrigger>
+          ),
+        }}
+      >
+        {children}
+      </DocsLayout>
+    </>
   );
 }

apps/next/src/app/global.css

@@ -94,4 +94,33 @@
   body {
     @apply bg-background text-foreground;
   }
+
+  /*
+  * Override default styles for Markdown
+  */
+  .prose
+    :where(blockquote):not(
+      :where([class~="not-prose"], [class~="not-prose"] *)
+    ) {
+    font-style: normal !important;
+  }
+
+  .prose
+    :where(blockquote p:first-of-type):not(
+      :where([class~="not-prose"], [class~="not-prose"] *)
+    ):before {
+    content: none !important;
+  }
+
+  .prose
+    :where(blockquote p:first-of-type):not(
+      :where([class~="not-prose"], [class~="not-prose"] *)
+    ):after {
+    content: none !important;
+  }
+
+  .prose
+    :where(code):not(:where([class~="not-prose"], [class~="not-prose"] *)) {
+    @apply text-blue-600 !important;
+  }
 }

apps/next/src/app/layout.config.tsx

@@ -1,4 +1,16 @@
+import { LEGACY_DOCUMENT_URL } from "@/lib/const";
 import type { BaseLayoutProps } from "fumadocs-ui/layouts/shared";
+import Image from "next/image";
+
+const logo = (
+  <Image
+    src="/logo-large.png"
+    alt="Logo"
+    className="size-8"
+    width={147}
+    height={147}
+  />
+);
 
 /**
  * Shared layout configurations
@@ -9,12 +21,14 @@ import type { BaseLayoutProps } from "fumadocs-ui/layouts/shared";
  */
 export const baseOptions: BaseLayoutProps = {
   nav: {
-    title: "LlamaIndex.TS",
+    title: logo,
+    transparentMode: "top",
   },
+  githubUrl: "https://github.com/run-llama/LlamaIndexTS",
   links: [
     {
-      text: "Documentation",
-      url: "/docs/llamaindex",
+      text: "Docs",
+      url: LEGACY_DOCUMENT_URL,
       active: "nested-url",
     },
   ],

apps/next/src/app/layout.tsx

@@ -1,6 +1,9 @@
+import { AIProvider } from "@/actions";
+import { TooltipProvider } from "@/components/ui/tooltip";
 import { RootProvider } from "fumadocs-ui/provider";
 import { Inter } from "next/font/google";
 import type { ReactNode } from "react";
+import "shiki-magic-move/dist/style.css";
 import "./global.css";
 
 const inter = Inter({
@@ -30,7 +33,11 @@ export default function Layout({ children }: { children: ReactNode }) {
         />
       </head>
       <body className="flex flex-col min-h-screen">
-        <RootProvider>{children}</RootProvider>
+        <TooltipProvider>
+          <AIProvider>
+            <RootProvider>{children}</RootProvider>
+          </AIProvider>
+        </TooltipProvider>
       </body>
     </html>
   );

apps/next/src/app/og/[...slug]/og.tsx

@@ -0,0 +1,180 @@
+import type { ImageResponseOptions } from "next/dist/compiled/@vercel/og/types";
+import { ImageResponse } from "next/og";
+import type { ReactElement, ReactNode } from "react";
+
+interface GenerateProps {
+  title: ReactNode;
+  description?: ReactNode;
+  icon?: ReactNode;
+  primaryColor?: string;
+  primaryTextColor?: string;
+  site?: ReactNode;
+}
+
+export function generateOGImage(
+  options: GenerateProps & ImageResponseOptions,
+): ImageResponse {
+  const {
+    title,
+    description,
+    icon,
+    site,
+    primaryColor,
+    primaryTextColor,
+    ...rest
+  } = options;
+
+  return new ImageResponse(
+    generate({
+      title,
+      description,
+      icon,
+      site,
+      primaryTextColor,
+      primaryColor,
+    }),
+    {
+      width: 1200,
+      height: 630,
+      ...rest,
+    },
+  );
+}
+
+export function generate({
+  primaryColor = "rgba(255,150,255,0.5)",
+  primaryTextColor = "rgb(255,150,255)",
+  ...props
+}: GenerateProps): ReactElement {
+  return (
+    <div
+      style={{
+        display: "flex",
+        flexDirection: "column",
+        width: "100%",
+        height: "100%",
+        color: "white",
+        backgroundColor: "#0c0c0c",
+        backgroundImage: `linear-gradient(to right top, ${primaryColor}, ${primaryColor})`,
+      }}
+    >
+      <div
+        style={{
+          display: "flex",
+          flexDirection: "column",
+          width: "100%",
+          height: "100%",
+          padding: "4rem",
+        }}
+      >
+        <div
+          style={{
+            display: "flex",
+            flexDirection: "row",
+            alignItems: "center",
+            gap: "16px",
+            marginBottom: "12px",
+            color: primaryTextColor,
+          }}
+        >
+          {props.icon}
+          <p
+            style={{
+              fontSize: "56px",
+              fontWeight: 600,
+            }}
+          >
+            {props.site}
+          </p>
+        </div>
+
+        <p
+          style={{
+            fontWeight: 800,
+            fontSize: "82px",
+          }}
+        >
+          {props.title}
+        </p>
+        <p
+          style={{
+            fontSize: "52px",
+            color: "rgba(240,240,240,0.7)",
+          }}
+        >
+          {props.description}
+        </p>
+      </div>
+    </div>
+  );
+}
+
+interface GridPatternProps {
+  width?: number;
+  height?: number;
+  x?: number;
+  y?: number;
+  squares?: [x: number, y: number][];
+  strokeDasharray?: number;
+  className?: string;
+}
+
+export function GridPattern({
+  width = 100,
+  height = 100,
+  x = -1,
+  y = -1,
+  squares,
+  strokeDasharray,
+  ...props
+}: GridPatternProps): ReactElement {
+  return (
+    <svg
+      fill="rgba(156, 163, 175, 0.2)"
+      stroke="rgba(156, 163, 175, 0.2)"
+      style={{
+        position: "absolute",
+        width: "100%",
+        height: "100%",
+        top: 0,
+        maskImage: "radial-gradient(circle at 0% 100%, white, transparent)",
+      }}
+      viewBox="0 0 600 400"
+      {...props}
+    >
+      <defs>
+        <pattern
+          id="og-pattern"
+          width={width}
+          height={height}
+          patternUnits="userSpaceOnUse"
+        >
+          <path
+            d={`M.5 ${height.toString()}V.5H${width.toString()}`}
+            fill="none"
+            strokeWidth={1}
+            strokeDasharray={strokeDasharray}
+          />
+        </pattern>
+      </defs>
+      <rect
+        width="600"
+        height="600"
+        strokeWidth={0}
+        fill="url(#og-pattern)"
+        x={x}
+        y={y}
+      />
+      {squares?.map(([itemX, itemY]) => (
+        <rect
+          strokeWidth="0"
+          key={`${itemX.toString()}-${itemY.toString()}`}
+          width={width - 1}
+          height={height}
+          x={itemX * width + 1}
+          y={itemY * (height + 1)}
+        />
+      ))}
+    </svg>
+  );
+}

apps/next/src/components/ai-chat.tsx

@@ -0,0 +1,143 @@
+"use client";
+import type { AIProvider, UIMessage } from "@/actions";
+import { UserMessage } from "@/components/message";
+import { useActions, useUIState } from "ai/rsc";
+import { Info } from "lucide-react";
+import { ButtonHTMLAttributes, useState } from "react";
+import { Alert, AlertDescription, AlertTitle } from "./ui/alert";
+import { Button } from "./ui/button";
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogHeader,
+  DialogOverlay,
+  DialogPortal,
+  DialogTitle,
+  DialogTrigger,
+} from "./ui/dialog";
+import { Textarea } from "./ui/textarea";
+import { Tooltip, TooltipContent, TooltipTrigger } from "./ui/tooltip";
+
+type AITriggerProps = ButtonHTMLAttributes<HTMLButtonElement>;
+
+function ChatList({ messages }: { messages: UIMessage[] }) {
+  if (messages.length === 0) {
+    return null;
+  }
+
+  return (
+    <div className="relative mx-auto w-full px-4">
+      {messages.map((message, index) => (
+        <div key={index} className="pb-4">
+          {message.display}
+        </div>
+      ))}
+    </div>
+  );
+}
+
+export const AITrigger = (props: AITriggerProps) => {
+  const [{ messages }, setUIState] = useUIState<typeof AIProvider>();
+  const { query } = useActions<typeof AIProvider>();
+  const [inputValue, setInputValue] = useState("");
+  return (
+    <Dialog>
+      <DialogTrigger {...props} />
+      <DialogPortal>
+        <DialogOverlay className="fixed inset-0 z-50 bg-fd-background/50 backdrop-blur-sm data-[state=closed]:animate-fd-fade-out data-[state=open]:animate-fd-fade-in" />
+        <DialogContent
+          onOpenAutoFocus={(e) => {
+            document.getElementById("nd-ai-input")?.focus();
+            e.preventDefault();
+          }}
+          className="fixed left-1/2 z-50 my-[5vh] flex max-h-[90dvh] w-[98vw] max-w-[860px] origin-left -translate-x-1/2 flex-col rounded-lg border bg-fd-popover text-fd-popover-foreground shadow-lg focus-visible:outline-none data-[state=closed]:animate-fd-dialog-out data-[state=open]:animate-fd-dialog-in"
+        >
+          <DialogHeader>
+            <DialogTitle className="sr-only">Search AI</DialogTitle>
+            <DialogDescription className="sr-only">
+              Ask AI some questions.
+            </DialogDescription>
+            <Alert>
+              <Info className="size-4" />
+              <AlertTitle>Heads up!</AlertTitle>
+              <AlertDescription>
+                Answers from LlamaCloud may be inaccurate, please use with
+                discretion.
+              </AlertDescription>
+            </Alert>
+          </DialogHeader>
+          <div className="overflow-scroll flex-grow mt-4">
+            <ChatList messages={messages} />
+          </div>
+          <form
+            className="px-4 py-2 space-y-4"
+            action={async () => {
+              const value = inputValue.trim();
+              setInputValue("");
+              if (!value) return;
+
+              // Add user message UI
+              setUIState((state) => ({
+                ...state,
+                messages: [
+                  ...state.messages,
+                  {
+                    id: Date.now(),
+                    display: <UserMessage>{value}</UserMessage>,
+                  },
+                ],
+              }));
+
+              try {
+                // Submit and get response message
+                const responseMessage = await query(value);
+                setUIState((state) => ({
+                  ...state,
+                  messages: [...state.messages, responseMessage],
+                }));
+              } catch (error) {
+                // You may want to show a toast or trigger an error state.
+                console.error(error);
+              }
+            }}
+          >
+            <div className="flex flex-row w-full items-center gap-2">
+              <Textarea
+                tabIndex={0}
+                placeholder="Ask AI about documentation."
+                className="w-full resize-none bg-transparent px-4 focus-within:outline-none sm:text-sm"
+                onKeyDown={(event) => {
+                  if (event.key === "Enter" && !event.shiftKey) {
+                    event.preventDefault();
+                    event.currentTarget.form?.requestSubmit(null);
+                  }
+                }}
+                autoFocus
+                spellCheck={false}
+                autoComplete="off"
+                autoCorrect="off"
+                name="message"
+                rows={1}
+                value={inputValue}
+                onChange={(e) => setInputValue(e.target.value)}
+              />
+              <Tooltip>
+                <TooltipTrigger asChild>
+                  <Button
+                    type="submit"
+                    size="icon"
+                    disabled={inputValue === ""}
+                  >
+                    <span className="sr-only">Send message</span>
+                  </Button>
+                </TooltipTrigger>
+                <TooltipContent>Send message</TooltipContent>
+              </Tooltip>
+            </div>
+          </form>
+        </DialogContent>
+      </DialogPortal>
+    </Dialog>
+  );
+};

apps/next/src/components/contribution.tsx

@@ -7,9 +7,8 @@ import { ReactElement } from "react";
 export function Contributing(): ReactElement {
   return (
     <div className="flex flex-col items-center border-x border-t px-4 py-16 text-center">
-      <Heart className="mb-4" />
       <h2 className="mb-4 text-xl font-semibold sm:text-2xl">
-        Made Possible by You.
+        Made possible by you <Heart className="inline align-middle" />
       </h2>
       <p className="mb-4 text-fd-muted-foreground">
         LlamaIndex.TS is powered by the open source community.

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

@@ -53,9 +53,6 @@ export default async function ContributorCounter({
           </div>
         ) : null}
       </div>
-      <div className="text-center text-sm text-fd-muted-foreground">
-        Some of our best contributors.
-      </div>
     </div>
   );
 }

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

@@ -0,0 +1,16 @@
+"use client";
+import { ChatInput, ChatMessages, ChatSection } from "@llamaindex/chat-ui";
+import { useChat } from "ai/react";
+
+export const ChatDemo = () => {
+  const handler = useChat();
+  return (
+    <ChatSection handler={handler}>
+      <ChatMessages>
+        <ChatMessages.List className="h-auto max-h-[400px]" />
+        <ChatMessages.Actions />
+      </ChatMessages>
+      <ChatInput />
+    </ChatSection>
+  );
+};

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

@@ -0,0 +1,57 @@
+import { Markdown } from "@llamaindex/chat-ui/widgets";
+import { MockLLM } from "@llamaindex/core/utils";
+import { generateId, Message } from "ai";
+import { createAI, createStreamableUI, getMutableAIState } from "ai/rsc";
+import { type ChatMessage, Settings, SimpleChatEngine } from "llamaindex";
+import { ReactNode } from "react";
+
+type ServerState = Message[];
+type FrontendState = Array<Message & { display: ReactNode }>;
+type Actions = {
+  chat: (message: Message) => Promise<Message & { display: ReactNode }>;
+};
+
+Settings.llm = new MockLLM(); // config your LLM here
+
+export const AI = createAI<ServerState, FrontendState, Actions>({
+  initialAIState: [],
+  initialUIState: [],
+  actions: {
+    chat: async (message: Message) => {
+      "use server";
+
+      const aiState = getMutableAIState<typeof AI>();
+      aiState.update((prev) => [...prev, message]);
+
+      const uiStream = createStreamableUI();
+      const chatEngine = new SimpleChatEngine();
+      const assistantMessage: Message = {
+        id: generateId(),
+        role: "assistant",
+        content: "",
+      };
+
+      // run the async function without blocking
+      (async () => {
+        const chatResponse = await chatEngine.chat({
+          stream: true,
+          message: message.content,
+          chatHistory: aiState.get() as ChatMessage[],
+        });
+
+        for await (const chunk of chatResponse) {
+          assistantMessage.content += chunk.delta;
+          uiStream.update(<Markdown content={assistantMessage.content} />);
+        }
+
+        aiState.done([...aiState.get(), assistantMessage]);
+        uiStream.done();
+      })();
+
+      return {
+        ...assistantMessage,
+        display: uiStream.value,
+      };
+    },
+  },
+});

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

@@ -0,0 +1,33 @@
+"use client";
+
+import {
+  ChatInput,
+  ChatMessage,
+  ChatMessages,
+  ChatSection as ChatSectionUI,
+} from "@llamaindex/chat-ui";
+import { useChatRSC } from "./use-chat-rsc";
+
+export const ChatSectionRSC = () => {
+  const handler = useChatRSC();
+  return (
+    <ChatSectionUI handler={handler}>
+      <ChatMessages>
+        <ChatMessages.List className="h-auto max-h-[400px]">
+          {handler.messages.map((message, index) => (
+            <ChatMessage
+              key={index}
+              message={message}
+              isLast={index === handler.messages.length - 1}
+            >
+              <ChatMessage.Avatar />
+              <ChatMessage.Content>{message.display}</ChatMessage.Content>
+            </ChatMessage>
+          ))}
+          <ChatMessages.Loading />
+        </ChatMessages.List>
+      </ChatMessages>
+      <ChatInput />
+    </ChatSectionUI>
+  );
+};

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

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

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

@@ -0,0 +1,41 @@
+"use client";
+
+import { useActions } from "ai/rsc";
+
+import { generateId, Message } from "ai";
+import { useUIState } from "ai/rsc";
+import { useState } from "react";
+import { AI } from "./ai-action";
+
+export function useChatRSC() {
+  const [input, setInput] = useState<string>("");
+  const [isLoading, setIsLoading] = useState<boolean>(false);
+  const [messages, setMessages] = useUIState<typeof AI>();
+  const { chat } = useActions<typeof AI>();
+
+  const append = async (message: Omit<Message, "id">) => {
+    const newMsg: Message = { ...message, id: generateId() };
+
+    setIsLoading(true);
+    try {
+      setMessages((prev) => [...prev, { ...newMsg, display: message.content }]);
+      const assistantMsg = await chat(newMsg);
+      setMessages((prev) => [...prev, assistantMsg]);
+    } catch (error) {
+      console.error(error);
+    }
+    setIsLoading(false);
+    setInput("");
+
+    return message.content;
+  };
+
+  return {
+    input,
+    setInput,
+    isLoading,
+    messages,
+    setMessages,
+    append,
+  };
+}

apps/next/src/components/demo/code-node-parser.tsx

@@ -0,0 +1,182 @@
+"use client";
+import { createContextState } from "foxact/context-state";
+import { useIsClient } from "foxact/use-is-client";
+import { useShiki } from "fumadocs-core/utils/use-shiki";
+import { CodeBlock, Pre } from "fumadocs-ui/components/codeblock";
+import { lazy, Suspense, use, useMemo } from "react";
+import { StickToBottom, useStickToBottomContext } from "use-stick-to-bottom";
+import Parser from "web-tree-sitter";
+
+import { Label } from "@/components/ui/label";
+import { Skeleton } from "@/components/ui/skeleton";
+import { Slider } from "@/components/ui/slider";
+import { CodeSplitter } from "@llamaindex/node-parser/code";
+
+let promise: Promise<CodeSplitter>;
+if (typeof window !== "undefined") {
+  promise = Parser.init({
+    locateFile(scriptName: string) {
+      return "/" + scriptName;
+    },
+  }).then(async () => {
+    const parser = new Parser();
+    const Lang = await Parser.Language.load("/tree-sitter-typescript.wasm");
+    parser.setLanguage(Lang);
+    return new CodeSplitter({
+      getParser: () => parser,
+      maxChars: 100,
+    });
+  });
+}
+
+const [SliderProvider, useSlider, useSetSlider] = createContextState(100);
+
+const [CodeProvider, useCode, useSetCode] =
+  createContextState(`interface Person {
+  name: string;
+  age: number;
+}
+
+function greet(person: Person): string {
+  return \`Hello, \${person.name}! You are \${person.age} years old.\`;
+}
+
+const john: Person = {
+  name: "John Doe",
+  age: 30
+};
+
+console.log(greet(john));`);
+
+const Editor = lazy(() => import("react-monaco-editor"));
+
+export const IDE = () => {
+  const codeSplitter = use(promise);
+  const code = useCode();
+  const setCode = useSetCode();
+  const maxChars = useSlider();
+  const useSetMaxChars = useSetSlider();
+  return (
+    <div className="flex flex-col p-4 border-r max-h-96 overflow-scroll">
+      <div>
+        <Label>Max Chars {maxChars}</Label>
+        <Slider
+          className="my-4"
+          min={10}
+          max={300}
+          step={10}
+          value={[maxChars]}
+          onValueChange={(value) => {
+            useSetMaxChars(value[0]);
+            codeSplitter.maxChars = value[0];
+          }}
+        />
+      </div>
+      <Editor
+        editorWillMount={() => {}}
+        editorDidMount={() => {
+          window.MonacoEnvironment!.getWorkerUrl = (
+            _moduleId: string,
+            label: string,
+          ) => {
+            if (label === "json") return "/_next/static/json.worker.js";
+            if (label === "css") return "/_next/static/css.worker.js";
+            if (label === "html") return "/_next/static/html.worker.js";
+            if (label === "typescript" || label === "javascript")
+              return "/_next/static/ts.worker.js";
+            return "/_next/static/editor.worker.js";
+          };
+        }}
+        editorWillUnmount={() => {}}
+        options={{
+          minimap: {
+            enabled: false,
+          },
+        }}
+        theme="vs-dark"
+        height="100%"
+        width="100%"
+        language="typescript"
+        onChange={setCode}
+        value={code}
+      />
+    </div>
+  );
+};
+
+const Preview = ({ text }: { text: string }) => {
+  const rendered = useShiki(text, {
+    lang: "ts",
+    components: {
+      pre: (props) => {
+        return <Pre {...props}>{props.children}</Pre>;
+      },
+    },
+  });
+  return <CodeBlock className="py-0 m-2">{rendered}</CodeBlock>;
+};
+
+function ScrollToBottom() {
+  const { isAtBottom, scrollToBottom } = useStickToBottomContext();
+
+  return (
+    !isAtBottom && (
+      <button
+        className="absolute i-ph-arrow-circle-down-fill text-4xl rounded-lg left-[50%] translate-x-[-50%] bottom-0"
+        onClick={() => scrollToBottom()}
+      />
+    )
+  );
+}
+
+export const NodePreview = () => {
+  const parser = use(promise);
+  const code = useCode();
+  const maxChars = useSlider();
+  const textChunks = useMemo(() => parser.splitText(code), [code, maxChars]);
+  return (
+    <StickToBottom
+      className="block relative max-h-96 overflow-scroll"
+      resize="smooth"
+      initial="smooth"
+    >
+      <StickToBottom.Content>
+        {textChunks.map((chunk, i) => (
+          <Preview key={i} text={chunk} />
+        ))}
+      </StickToBottom.Content>
+      <ScrollToBottom />
+    </StickToBottom>
+  );
+};
+
+export const CodeNodeParserDemo = () => {
+  const isClient = useIsClient();
+  if (!isClient) {
+    return (
+      <div className="my-2 grid grid-cols-1 md:grid-cols-2 gap-2 border rounded-xl w-full max-h-96">
+        <Skeleton className="h-96" />
+        <Skeleton className="h-96" />
+      </div>
+    );
+  }
+  return (
+    <SliderProvider>
+      <CodeProvider>
+        <Suspense
+          fallback={
+            <div className="my-2 grid grid-cols-1 md:grid-cols-2 gap-2 border rounded-xl w-full max-h-96">
+              <Skeleton className="h-96" />
+              <Skeleton className="h-96" />
+            </div>
+          }
+        >
+          <div className="my-2 grid grid-cols-1 md:grid-cols-2 gap-2 border rounded-xl w-full max-h-96">
+            <IDE />
+            <NodePreview />
+          </div>
+        </Suspense>
+      </CodeProvider>
+    </SliderProvider>
+  );
+};

apps/next/src/components/demo/workflow-streaming-ui.tsx

@@ -0,0 +1,152 @@
+"use client";
+import FlowInput from "@/components/flow-input";
+import { Button } from "@/components/ui/button";
+import {
+  StartEvent,
+  StopEvent,
+  Workflow,
+  WorkflowEvent,
+} from "@llamaindex/workflow";
+import { ReactNode, startTransition, useState } from "react";
+import { StickToBottom, useStickToBottomContext } from "use-stick-to-bottom";
+
+class ComputeEvent extends WorkflowEvent<number> {
+  constructor(data: number) {
+    super(data);
+  }
+}
+
+class ComputeResultEvent extends WorkflowEvent<number> {
+  constructor(data: number) {
+    super(data);
+  }
+}
+
+type ContextData = {
+  sum: number;
+};
+
+const workflow = new Workflow<ContextData, number, number>();
+
+const max = 1000;
+const min = 100;
+
+workflow.addStep(
+  {
+    inputs: [StartEvent<number>],
+    outputs: [StopEvent<number>],
+  },
+  async (context, event) => {
+    const total = event.data;
+    for (let i = 0; i < total; i++) {
+      context.sendEvent(new ComputeEvent(i));
+    }
+    console.log("waiting");
+    const computeResults = await Promise.all(
+      Array.from({ length: total }).map(() =>
+        context.requireEvent(ComputeResultEvent),
+      ),
+    );
+    context.data.sum = computeResults.reduce(
+      (acc, result) => acc + result.data,
+      0,
+    );
+    console.log("stop");
+    return new StopEvent(context.data.sum);
+  },
+);
+
+workflow.addStep(
+  {
+    inputs: [ComputeEvent],
+    outputs: [ComputeResultEvent],
+  },
+  async (context, event) => {
+    await new Promise((resolve) =>
+      setTimeout(resolve, Math.floor(Math.random() * (max - min + 1) + min)),
+    );
+    return new ComputeResultEvent(event.data);
+  },
+);
+
+function ScrollToBottom() {
+  const { isAtBottom, scrollToBottom } = useStickToBottomContext();
+
+  return (
+    !isAtBottom && (
+      <button
+        className="absolute i-ph-arrow-circle-down-fill text-4xl rounded-lg left-[50%] translate-x-[-50%] bottom-0"
+        onClick={() => scrollToBottom()}
+      />
+    )
+  );
+}
+
+export function WorkflowStreamingDemo() {
+  const [ui, setUI] = useState<ReactNode[]>([
+    <div key={0} className="bg-gray-100 dark:bg-gray-800">
+      Waiting for workflow to start
+    </div>,
+  ]);
+  const [total, setTotal] = useState<number>(10);
+
+  return (
+    <div className="flex flex-col items-start w-full gap-2">
+      <div className="flex flex-row justify-center items-center">
+        <div className="text-lg mr-2">Compute total</div>{" "}
+        <FlowInput value={total} onChange={(value) => setTotal(value)} />
+      </div>
+      <Button
+        onClick={async () => {
+          startTransition(() => {
+            setUI([]);
+          });
+          const context = workflow.run(total, {
+            sum: 0,
+          });
+          let i = 0;
+          for await (const event of context) {
+            console.log(event);
+            if (event instanceof ComputeEvent) {
+              setUI((ui) => [
+                ...ui,
+                <div key={i++} className="bg-yellow-100 dark:bg-yellow-800">
+                  Computing task id: {event.data}
+                </div>,
+              ]);
+            } else if (event instanceof ComputeResultEvent) {
+              setUI((ui) => [
+                ...ui,
+                <div key={i++} className="bg-green-100 dark:bg-green-800">
+                  Computed task id: {event.data}
+                </div>,
+              ]);
+            } else if (event instanceof StartEvent) {
+              setUI((ui) => [
+                ...ui,
+                <div key={i++} className="bg-blue-100 dark:bg-blue-800">
+                  Started workflow with total {event.data}
+                </div>,
+              ]);
+            } else if (event instanceof StopEvent) {
+              setUI((ui) => [
+                ...ui,
+                <div key={i++} className="bg-red-100 dark:bg-red-800">
+                  Workflow stopped
+                </div>,
+              ]);
+            }
+          }
+        }}
+      >
+        Start Workflow
+      </Button>
+      <StickToBottom className="w-full flex flex-col gap-2 p-2 border border-gray-200 rounded-lg max-h-96 overflow-y-auto">
+        <StickToBottom.Content className="flex flex-col gap-2">
+          {ui}
+        </StickToBottom.Content>
+        <ScrollToBottom />
+      </StickToBottom>
+    </div>
+  );
+}

apps/next/src/components/flow-input.tsx

@@ -0,0 +1,98 @@
+import NumberFlow from "@number-flow/react";
+import clsx from "clsx/lite";
+import { Minus, Plus } from "lucide-react";
+import * as React from "react";
+
+type Props = {
+  value?: number;
+  min?: number;
+  max?: number;
+  onChange?: (value: number) => void;
+};
+export default function FlowInput({
+  value = 0,
+  min = -Infinity,
+  max = Infinity,
+  onChange,
+}: Props) {
+  const defaultValue = React.useRef(value);
+  const inputRef = React.useRef<HTMLInputElement>(null);
+  const [animated, setAnimated] = React.useState(true);
+  const [showCaret, setShowCaret] = React.useState(true);
+  const handleInput: React.ChangeEventHandler<HTMLInputElement> = ({
+    currentTarget: el,
+  }) => {
+    setAnimated(false);
+    let next = value;
+    if (el.value === "") {
+      next = defaultValue.current;
+    } else {
+      const num = parseInt(el.value);
+      if (!isNaN(num) && min <= num && num <= max) next = num;
+    }
+    el.value = String(next);
+    onChange?.(next);
+  };
+  const handlePointerDown =
+    (diff: number) => (event: React.PointerEvent<HTMLButtonElement>) => {
+      setAnimated(true);
+      if (event.pointerType === "mouse") {
+        event?.preventDefault();
+        inputRef.current?.focus();
+      }
+      const newVal = Math.min(Math.max(value + diff, min), max);
+      onChange?.(newVal);
+    };
+  return (
+    <div className="group flex items-stretch rounded-md text-lg font-semibold ring ring-zinc-200 transition-[box-shadow] focus-within:ring-2 focus-within:ring-blue-500 dark:ring-zinc-800">
+      <button
+        aria-hidden
+        tabIndex={-1}
+        className="flex items-center pl-[.5em] pr-[.325em]"
+        disabled={min != null && value <= min}
+        onPointerDown={handlePointerDown(-1)}
+      >
+        <Minus className="size-4" absoluteStrokeWidth strokeWidth={3.5} />
+      </button>
+      <div className="relative grid items-center justify-items-center text-center [grid-template-areas:'overlap'] *:[grid-area:overlap]">
+        <input
+          ref={inputRef}
+          className={clsx(
+            showCaret ? "caret-primary" : "caret-transparent",
+            "spin-hide w-[1.5em] bg-transparent py-2 text-center font-[inherit] text-transparent outline-none",
+            "[appearance:textfield] [&::-webkit-outer-spin-button]:appearance-none [&::-webkit-inner-spin-button]:appearance-none",
+          )}
+          // Make sure to disable kerning, to match NumberFlow:
+          style={{ fontKerning: "none" }}
+          type="number"
+          min={min}
+          step={1}
+          autoComplete="off"
+          inputMode="numeric"
+          max={max}
+          value={value}
+          onInput={handleInput}
+        />
+        <NumberFlow
+          value={value}
+          format={{ useGrouping: false }}
+          aria-hidden
+          animated={animated}
+          onAnimationsStart={() => setShowCaret(false)}
+          onAnimationsFinish={() => setShowCaret(true)}
+          className="pointer-events-none"
+          willChange
+        />
+      </div>
+      <button
+        aria-hidden
+        tabIndex={-1}
+        className="flex items-center pl-[.325em] pr-[.5em]"
+        disabled={max != null && value >= max}
+        onPointerDown={handlePointerDown(1)}
+      >
+        <Plus className="size-4" absoluteStrokeWidth strokeWidth={3.5} />
+      </button>
+    </div>
+  );
+}

apps/next/src/components/infinite-providers.tsx

@@ -0,0 +1,82 @@
+import { InfiniteSlider } from "@/components/ui/infinite-slider";
+import { SiAnthropic, SiOpenai } from "@icons-pack/react-simple-icons";
+import Image from "next/image";
+
+export function InfiniteLLMProviders() {
+  return (
+    <InfiniteSlider gap={24} reverse>
+      <SiOpenai className="h-[60px] w-auto" />
+      <Image
+        src="/icons/Google_2015_logo.svg"
+        alt="Google"
+        width={60}
+        height={60}
+        className="h-[60px] w-auto"
+      />
+      <Image
+        src="/icons/Microsoft_Azure.svg"
+        alt="Microsoft Azure"
+        width={60}
+        height={60}
+        className="h-[60px] w-auto"
+      />
+      <SiAnthropic className="h-[60px] w-auto" />
+      <Image
+        src="/icons/Amazon_Web_Services_Logo.svg"
+        alt="Amazon Web Services"
+        width={60}
+        height={60}
+        className="h-[60px] w-auto"
+      />
+      <Image
+        src="/icons/Groq_Logo.svg"
+        alt="Groq"
+        width={60}
+        height={60}
+        className="h-[60px] w-auto"
+      />
+    </InfiniteSlider>
+  );
+}
+
+export function InfiniteVectorStoreProviders() {
+  return (
+    <InfiniteSlider gap={24}>
+      <Image
+        src="/icons/postgresql-ar21.svg"
+        alt="PostgreSQL"
+        width={60}
+        height={60}
+        className="h-[60px] w-auto"
+      />
+      <Image
+        src="/icons/Datastax_logo.svg"
+        alt="Datastax"
+        width={60}
+        height={60}
+        className="h-[60px] w-auto"
+      />
+      <Image
+        src="/icons/chroma.svg"
+        alt="Chroma"
+        width={60}
+        height={60}
+        className="h-[60px] w-auto"
+      />
+      <Image
+        src="/icons/weaviate-nav-logo-light.svg"
+        alt="Weaviate"
+        width={60}
+        height={60}
+        className="h-[60px] w-auto"
+      />
+      <Image
+        src="/icons/qdrant-logo.svg"
+        alt="Qdrant"
+        width={60}
+        height={60}
+        className="h-[60px] w-auto"
+      />
+    </InfiniteSlider>
+  );
+}

apps/next/src/components/magic-move.tsx

@@ -0,0 +1,73 @@
+"use client";
+import { Button } from "@/components/ui/button";
+import { cn } from "@/lib/utils";
+import { CodeBlock, Pre } from "fumadocs-ui/components/codeblock";
+import { RotateCcw } from "lucide-react";
+import { useTheme } from "next-themes";
+import { use, useCallback, useEffect, useState } from "react";
+import { getSingletonHighlighter } from "shiki";
+import { ShikiMagicMove } from "shiki-magic-move/react";
+import { createOnigurumaEngine } from "shiki/engine/oniguruma";
+
+const highlighterPromise = getSingletonHighlighter({
+  engine: createOnigurumaEngine(() => import("shiki/wasm")),
+  themes: ["vesper", "github-light"],
+  langs: ["js", "ts", "tsx"],
+});
+
+export type MagicMoveProps = {
+  code: string[];
+};
+
+export function MagicMove(props: MagicMoveProps) {
+  const [move, setMove] = useState<number>(0);
+  const currentCode = props.code[move];
+  const highlighter = use(highlighterPromise);
+  const { resolvedTheme } = useTheme();
+
+  const animate = useCallback(() => {
+    setMove((move) => (move + 1) % props.code.length);
+  }, [props.code]);
+
+  useEffect(() => {
+    if (move === props.code.length - 1) {
+      return;
+    } else {
+      const interval = setInterval(animate, 3000);
+      return () => clearInterval(interval);
+    }
+  }, [animate, move, props.code]);
+
+  return (
+    <CodeBlock allowCopy={false}>
+      {highlighter && (
+        <Pre>
+          <ShikiMagicMove
+            lang="ts"
+            theme={resolvedTheme === "dark" ? "vesper" : "github-light"}
+            highlighter={highlighter}
+            code={currentCode}
+            options={{
+              duration: 800,
+              stagger: 0.3,
+              lineNumbers: false,
+              containerStyle: false,
+            }}
+          />
+        </Pre>
+      )}
+      <Button
+        className={cn(
+          "absolute bottom-2 right-2",
+          move !== props.code.length - 1 ? "hidden" : "",
+        )}
+        variant="ghost"
+        size="icon"
+        disabled={move !== props.code.length - 1}
+        onClick={animate}
+      >
+        <RotateCcw />
+      </Button>
+    </CodeBlock>
+  );
+}

apps/next/src/components/mdx.tsx

@@ -0,0 +1,41 @@
+"use client";
+import { createProcessor, run } from "@mdx-js/mdx";
+import defaultMdxComponents from "fumadocs-ui/mdx";
+import { ReactNode, useDeferredValue } from "react";
+import * as runtime from "react/jsx-runtime";
+import useSWR from "swr";
+
+const processor = createProcessor({
+  outputFormat: "function-body",
+});
+
+export function ClientMDXContent({
+  content,
+  id,
+}: {
+  content: string;
+  id: number;
+}): ReactNode {
+  const deferredContent = useDeferredValue(content);
+  const { data: jsx } = useSWR(["mdx", id, deferredContent], {
+    fetcher: async () => {
+      const code = await processor
+        .process(deferredContent)
+        .then((vfile) => vfile.value);
+      const { default: Content } = await run(code, {
+        ...runtime,
+        baseUrl: import.meta.url,
+      });
+      return (
+        <Content
+          components={{
+            ...defaultMdxComponents,
+          }}
+        />
+      );
+    },
+    suspense: true,
+  });
+
+  return jsx;
+}

apps/next/src/components/message.tsx

@@ -0,0 +1,78 @@
+"use client";
+
+import { cn } from "@/lib/utils";
+import Image from "next/image";
+import { ReactNode } from "react";
+import { IconAI, IconUser } from "./ui/icons";
+
+export function UserMessage({ children }: { children: ReactNode }) {
+  return (
+    <div className="group relative flex items-start">
+      <div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm bg-background">
+        <IconUser />
+      </div>
+      <div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
+        {children}
+      </div>
+    </div>
+  );
+}
+
+export function BotMessage({
+  children,
+  className,
+}: {
+  children: ReactNode;
+  className?: string;
+}) {
+  return (
+    <div className={cn("group relative flex items-start", className)}>
+      <div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm">
+        <Image
+          src="/logo-large.png"
+          alt="Logo"
+          className="size-4"
+          width={147}
+          height={147}
+        />
+      </div>
+      <div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
+        {children}
+      </div>
+    </div>
+  );
+}
+
+export function BotCard({
+  children,
+  showAvatar = true,
+}: {
+  children: ReactNode;
+  showAvatar?: boolean;
+}) {
+  return (
+    <div className="group relative flex items-start md:-ml-12">
+      <div
+        className={cn(
+          "flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm bg-primary text-primary-foreground",
+          !showAvatar && "invisible",
+        )}
+      >
+        <IconAI />
+      </div>
+      <div className="ml-4 flex-1 px-1">{children}</div>
+    </div>
+  );
+}
+
+export function SystemMessage({ children }: { children: React.ReactNode }) {
+  return (
+    <div
+      className={
+        "mt-2 flex items-center justify-center gap-2 text-xs text-gray-500"
+      }
+    >
+      <div className={"max-w-[600px] flex-initial px-2 py-2"}>{children}</div>
+    </div>
+  );
+}

apps/next/src/components/ui/alert.tsx

@@ -0,0 +1,59 @@
+import { cva, type VariantProps } from "class-variance-authority";
+import * as React from "react";
+
+import { cn } from "@/lib/utils";
+
+const alertVariants = cva(
+  "relative w-full rounded-lg border px-4 py-3 text-sm [&>svg+div]:translate-y-[-3px] [&>svg]:absolute [&>svg]:left-4 [&>svg]:top-4 [&>svg]:text-foreground [&>svg~*]:pl-7",
+  {
+    variants: {
+      variant: {
+        default: "bg-background text-foreground",
+        destructive:
+          "border-destructive/50 text-destructive dark:border-destructive [&>svg]:text-destructive",
+      },
+    },
+    defaultVariants: {
+      variant: "default",
+    },
+  },
+);
+
+const Alert = React.forwardRef<
+  HTMLDivElement,
+  React.HTMLAttributes<HTMLDivElement> & VariantProps<typeof alertVariants>
+>(({ className, variant, ...props }, ref) => (
+  <div
+    ref={ref}
+    role="alert"
+    className={cn(alertVariants({ variant }), className)}
+    {...props}
+  />
+));
+Alert.displayName = "Alert";
+
+const AlertTitle = React.forwardRef<
+  HTMLParagraphElement,
+  React.HTMLAttributes<HTMLHeadingElement>
+>(({ className, ...props }, ref) => (
+  <h5
+    ref={ref}
+    className={cn("mb-1 font-medium leading-none tracking-tight", className)}
+    {...props}
+  />
+));
+AlertTitle.displayName = "AlertTitle";
+
+const AlertDescription = React.forwardRef<
+  HTMLParagraphElement,
+  React.HTMLAttributes<HTMLParagraphElement>
+>(({ className, ...props }, ref) => (
+  <div
+    ref={ref}
+    className={cn("text-sm [&_p]:leading-relaxed", className)}
+    {...props}
+  />
+));
+AlertDescription.displayName = "AlertDescription";
+
+export { Alert, AlertDescription, AlertTitle };

apps/next/src/components/ui/badge.tsx

@@ -0,0 +1,36 @@
+import { cva, type VariantProps } from "class-variance-authority";
+import * as React from "react";
+
+import { cn } from "@/lib/utils";
+
+const badgeVariants = cva(
+  "inline-flex items-center rounded-md border px-2.5 py-0.5 text-xs font-semibold transition-colors focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2",
+  {
+    variants: {
+      variant: {
+        default:
+          "border-transparent bg-primary text-primary-foreground shadow hover:bg-primary/80",
+        secondary:
+          "border-transparent bg-secondary text-secondary-foreground hover:bg-secondary/80",
+        destructive:
+          "border-transparent bg-destructive text-destructive-foreground shadow hover:bg-destructive/80",
+        outline: "text-foreground",
+      },
+    },
+    defaultVariants: {
+      variant: "default",
+    },
+  },
+);
+
+export interface BadgeProps
+  extends React.HTMLAttributes<HTMLDivElement>,
+    VariantProps<typeof badgeVariants> {}
+
+function Badge({ className, variant, ...props }: BadgeProps) {
+  return (
+    <div className={cn(badgeVariants({ variant }), className)} {...props} />
+  );
+}
+
+export { Badge, badgeVariants };

apps/next/src/components/ui/button.tsx

@@ -24,6 +24,7 @@ const buttonVariants = cva(
         default: "h-9 px-4 py-2",
         sm: "h-8 rounded-md px-3 text-xs",
         lg: "h-10 rounded-md px-8",
+        xs: "px-1.5 py-0.5 text-xs",
         icon: "h-9 w-9",
       },
     },

apps/next/src/components/ui/dialog.tsx

@@ -0,0 +1,122 @@
+"use client";
+
+import * as DialogPrimitive from "@radix-ui/react-dialog";
+import { Cross2Icon } from "@radix-ui/react-icons";
+import * as React from "react";
+
+import { cn } from "@/lib/utils";
+
+const Dialog = DialogPrimitive.Root;
+
+const DialogTrigger = DialogPrimitive.Trigger;
+
+const DialogPortal = DialogPrimitive.Portal;
+
+const DialogClose = DialogPrimitive.Close;
+
+const DialogOverlay = React.forwardRef<
+  React.ElementRef<typeof DialogPrimitive.Overlay>,
+  React.ComponentPropsWithoutRef<typeof DialogPrimitive.Overlay>
+>(({ className, ...props }, ref) => (
+  <DialogPrimitive.Overlay
+    ref={ref}
+    className={cn(
+      "fixed inset-0 z-50 bg-black/80  data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0",
+      className,
+    )}
+    {...props}
+  />
+));
+DialogOverlay.displayName = DialogPrimitive.Overlay.displayName;
+
+const DialogContent = React.forwardRef<
+  React.ElementRef<typeof DialogPrimitive.Content>,
+  React.ComponentPropsWithoutRef<typeof DialogPrimitive.Content>
+>(({ className, children, ...props }, ref) => (
+  <DialogPortal>
+    <DialogOverlay />
+    <DialogPrimitive.Content
+      ref={ref}
+      className={cn(
+        "fixed left-[50%] top-[50%] z-50 grid w-full max-w-lg translate-x-[-50%] translate-y-[-50%] gap-4 border bg-background p-6 shadow-lg duration-200 data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[state=closed]:slide-out-to-left-1/2 data-[state=closed]:slide-out-to-top-[48%] data-[state=open]:slide-in-from-left-1/2 data-[state=open]:slide-in-from-top-[48%] sm:rounded-lg",
+        className,
+      )}
+      {...props}
+    >
+      {children}
+      <DialogPrimitive.Close className="absolute right-4 top-4 rounded-sm opacity-70 ring-offset-background transition-opacity hover:opacity-100 focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2 disabled:pointer-events-none data-[state=open]:bg-accent data-[state=open]:text-muted-foreground">
+        <Cross2Icon className="h-4 w-4" />
+        <span className="sr-only">Close</span>
+      </DialogPrimitive.Close>
+    </DialogPrimitive.Content>
+  </DialogPortal>
+));
+DialogContent.displayName = DialogPrimitive.Content.displayName;
+
+const DialogHeader = ({
+  className,
+  ...props
+}: React.HTMLAttributes<HTMLDivElement>) => (
+  <div
+    className={cn(
+      "flex flex-col space-y-1.5 text-center sm:text-left",
+      className,
+    )}
+    {...props}
+  />
+);
+DialogHeader.displayName = "DialogHeader";
+
+const DialogFooter = ({
+  className,
+  ...props
+}: React.HTMLAttributes<HTMLDivElement>) => (
+  <div
+    className={cn(
+      "flex flex-col-reverse sm:flex-row sm:justify-end sm:space-x-2",
+      className,
+    )}
+    {...props}
+  />
+);
+DialogFooter.displayName = "DialogFooter";
+
+const DialogTitle = React.forwardRef<
+  React.ElementRef<typeof DialogPrimitive.Title>,
+  React.ComponentPropsWithoutRef<typeof DialogPrimitive.Title>
+>(({ className, ...props }, ref) => (
+  <DialogPrimitive.Title
+    ref={ref}
+    className={cn(
+      "text-lg font-semibold leading-none tracking-tight",
+      className,
+    )}
+    {...props}
+  />
+));
+DialogTitle.displayName = DialogPrimitive.Title.displayName;
+
+const DialogDescription = React.forwardRef<
+  React.ElementRef<typeof DialogPrimitive.Description>,
+  React.ComponentPropsWithoutRef<typeof DialogPrimitive.Description>
+>(({ className, ...props }, ref) => (
+  <DialogPrimitive.Description
+    ref={ref}
+    className={cn("text-sm text-muted-foreground", className)}
+    {...props}
+  />
+));
+DialogDescription.displayName = DialogPrimitive.Description.displayName;
+
+export {
+  Dialog,
+  DialogClose,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogOverlay,
+  DialogPortal,
+  DialogTitle,
+  DialogTrigger,
+};

apps/next/src/components/ui/icons.tsx

@@ -0,0 +1,30 @@
+import { cn } from "@/lib/utils";
+
+export function IconAI({ className, ...props }: React.ComponentProps<"svg">) {
+  return (
+    <svg
+      fill="currentColor"
+      viewBox="0 0 256 256"
+      role="img"
+      xmlns="http://www.w3.org/2000/svg"
+      className={cn("h-4 w-4", className)}
+      {...props}
+    >
+      <path d="M197.58,129.06l-51.61-19-19-51.65a15.92,15.92,0,0,0-29.88,0L78.07,110l-51.65,19a15.92,15.92,0,0,0,0,29.88L78,178l19,51.62a15.92,15.92,0,0,0,29.88,0l19-51.61,51.65-19a15.92,15.92,0,0,0,0-29.88ZM140.39,163a15.87,15.87,0,0,0-9.43,9.43l-19,51.46L93,172.39A15.87,15.87,0,0,0,83.61,163h0L32.15,144l51.46-19A15.87,15.87,0,0,0,93,115.61l19-51.46,19,51.46a15.87,15.87,0,0,0,9.43,9.43l51.46,19ZM144,40a8,8,0,0,1,8-8h16V16a8,8,0,0,1,16,0V32h16a8,8,0,0,1,0,16H184V64a8,8,0,0,1-16,0V48H152A8,8,0,0,1,144,40ZM248,88a8,8,0,0,1-8,8h-8v8a8,8,0,0,1-16,0V96h-8a8,8,0,0,1,0-16h8V72a8,8,0,0,1,16,0v8h8A8,8,0,0,1,248,88Z"></path>
+    </svg>
+  );
+}
+
+export function IconUser({ className, ...props }: React.ComponentProps<"svg">) {
+  return (
+    <svg
+      xmlns="http://www.w3.org/2000/svg"
+      viewBox="0 0 256 256"
+      fill="currentColor"
+      className={cn("h-4 w-4", className)}
+      {...props}
+    >
+      <path d="M230.92 212c-15.23-26.33-38.7-45.21-66.09-54.16a72 72 0 1 0-73.66 0c-27.39 8.94-50.86 27.82-66.09 54.16a8 8 0 1 0 13.85 8c18.84-32.56 52.14-52 89.07-52s70.23 19.44 89.07 52a8 8 0 1 0 13.85-8ZM72 96a56 56 0 1 1 56 56 56.06 56.06 0 0 1-56-56Z" />
+    </svg>
+  );
+}

apps/next/src/components/ui/infinite-slider.tsx

@@ -0,0 +1,107 @@
+"use client";
+import { cn } from "@/lib/utils";
+import { animate, motion, useMotionValue } from "framer-motion";
+import { useEffect, useState } from "react";
+import useMeasure from "react-use-measure";
+
+type InfiniteSliderProps = {
+  children: React.ReactNode;
+  gap?: number;
+  duration?: number;
+  durationOnHover?: number;
+  direction?: "horizontal" | "vertical";
+  reverse?: boolean;
+  className?: string;
+};
+
+export function InfiniteSlider({
+  children,
+  gap = 16,
+  duration = 25,
+  durationOnHover,
+  direction = "horizontal",
+  reverse = false,
+  className,
+}: InfiniteSliderProps) {
+  const [currentDuration, setCurrentDuration] = useState(duration);
+  const [ref, { width, height }] = useMeasure();
+  const translation = useMotionValue(0);
+  const [isTransitioning, setIsTransitioning] = useState(false);
+  const [key, setKey] = useState(0);
+
+  useEffect(() => {
+    let controls;
+    const size = direction === "horizontal" ? width : height;
+    const contentSize = size + gap;
+    const from = reverse ? -contentSize / 2 : 0;
+    const to = reverse ? 0 : -contentSize / 2;
+
+    if (isTransitioning) {
+      controls = animate(translation, [translation.get(), to], {
+        ease: "linear",
+        duration:
+          currentDuration * Math.abs((translation.get() - to) / contentSize),
+        onComplete: () => {
+          setIsTransitioning(false);
+          setKey((prevKey) => prevKey + 1);
+        },
+      });
+    } else {
+      controls = animate(translation, [from, to], {
+        ease: "linear",
+        duration: currentDuration,
+        repeat: Infinity,
+        repeatType: "loop",
+        repeatDelay: 0,
+        onRepeat: () => {
+          translation.set(from);
+        },
+      });
+    }
+
+    return controls?.stop;
+  }, [
+    key,
+    translation,
+    currentDuration,
+    width,
+    height,
+    gap,
+    isTransitioning,
+    direction,
+    reverse,
+  ]);
+
+  const hoverProps = durationOnHover
+    ? {
+        onHoverStart: () => {
+          setIsTransitioning(true);
+          setCurrentDuration(durationOnHover);
+        },
+        onHoverEnd: () => {
+          setIsTransitioning(true);
+          setCurrentDuration(duration);
+        },
+      }
+    : {};
+
+  return (
+    <div className={cn("overflow-hidden", className)}>
+      <motion.div
+        className="flex w-max items-center"
+        style={{
+          ...(direction === "horizontal"
+            ? { x: translation }
+            : { y: translation }),
+          gap: `${gap}px`,
+          flexDirection: direction === "horizontal" ? "row" : "column",
+        }}
+        ref={ref}
+        {...hoverProps}
+      >
+        {children}
+        {children}
+      </motion.div>
+    </div>
+  );
+}

apps/next/src/components/ui/input.tsx

@@ -2,8 +2,7 @@ import * as React from "react";
 
 import { cn } from "@/lib/utils";
 
-export interface InputProps
-  extends React.InputHTMLAttributes<HTMLInputElement> {}
+export type InputProps = React.InputHTMLAttributes<HTMLInputElement>;
 
 const Input = React.forwardRef<HTMLInputElement, InputProps>(
   ({ className, type, ...props }, ref) => {

apps/next/src/components/ui/label.tsx

@@ -0,0 +1,26 @@
+"use client";
+
+import * as LabelPrimitive from "@radix-ui/react-label";
+import { cva, type VariantProps } from "class-variance-authority";
+import * as React from "react";
+
+import { cn } from "@/lib/utils";
+
+const labelVariants = cva(
+  "text-sm font-medium leading-none peer-disabled:cursor-not-allowed peer-disabled:opacity-70",
+);
+
+const Label = React.forwardRef<
+  React.ElementRef<typeof LabelPrimitive.Root>,
+  React.ComponentPropsWithoutRef<typeof LabelPrimitive.Root> &
+    VariantProps<typeof labelVariants>
+>(({ className, ...props }, ref) => (
+  <LabelPrimitive.Root
+    ref={ref}
+    className={cn(labelVariants(), className)}
+    {...props}
+  />
+));
+Label.displayName = LabelPrimitive.Root.displayName;
+
+export { Label };

apps/next/src/components/ui/skeleton.tsx

@@ -0,0 +1,15 @@
+import { cn } from "@/lib/utils";
+
+function Skeleton({
+  className,
+  ...props
+}: React.HTMLAttributes<HTMLDivElement>) {
+  return (
+    <div
+      className={cn("animate-pulse rounded-md bg-primary/10", className)}
+      {...props}
+    />
+  );
+}
+
+export { Skeleton };

apps/next/src/components/ui/slider.tsx

@@ -0,0 +1,28 @@
+"use client";
+
+import * as SliderPrimitive from "@radix-ui/react-slider";
+import * as React from "react";
+
+import { cn } from "@/lib/utils";
+
+const Slider = React.forwardRef<
+  React.ElementRef<typeof SliderPrimitive.Root>,
+  React.ComponentPropsWithoutRef<typeof SliderPrimitive.Root>
+>(({ className, ...props }, ref) => (
+  <SliderPrimitive.Root
+    ref={ref}
+    className={cn(
+      "relative flex w-full touch-none select-none items-center",
+      className,
+    )}
+    {...props}
+  >
+    <SliderPrimitive.Track className="relative h-1.5 w-full grow overflow-hidden rounded-full bg-primary/20">
+      <SliderPrimitive.Range className="absolute h-full bg-primary" />
+    </SliderPrimitive.Track>
+    <SliderPrimitive.Thumb className="block h-4 w-4 rounded-full border border-primary/50 bg-background shadow transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:pointer-events-none disabled:opacity-50" />
+  </SliderPrimitive.Root>
+));
+Slider.displayName = SliderPrimitive.Root.displayName;
+
+export { Slider };

apps/next/src/components/ui/textarea.tsx

@@ -0,0 +1,23 @@
+import * as React from "react";
+
+import { cn } from "@/lib/utils";
+
+export type TextareaProps = React.TextareaHTMLAttributes<HTMLTextAreaElement>;
+
+const Textarea = React.forwardRef<HTMLTextAreaElement, TextareaProps>(
+  ({ className, ...props }, ref) => {
+    return (
+      <textarea
+        className={cn(
+          "flex min-h-[60px] w-full rounded-md border border-input bg-transparent px-3 py-2 text-sm shadow-sm placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:cursor-not-allowed disabled:opacity-50",
+          className,
+        )}
+        ref={ref}
+        {...props}
+      />
+    );
+  },
+);
+Textarea.displayName = "Textarea";
+
+export { Textarea };

apps/next/src/components/ui/tooltip.tsx

@@ -0,0 +1,32 @@
+"use client";
+
+import * as TooltipPrimitive from "@radix-ui/react-tooltip";
+import * as React from "react";
+
+import { cn } from "@/lib/utils";
+
+const TooltipProvider = TooltipPrimitive.Provider;
+
+const Tooltip = TooltipPrimitive.Root;
+
+const TooltipTrigger = TooltipPrimitive.Trigger;
+
+const TooltipContent = React.forwardRef<
+  React.ElementRef<typeof TooltipPrimitive.Content>,
+  React.ComponentPropsWithoutRef<typeof TooltipPrimitive.Content>
+>(({ className, sideOffset = 4, ...props }, ref) => (
+  <TooltipPrimitive.Portal>
+    <TooltipPrimitive.Content
+      ref={ref}
+      sideOffset={sideOffset}
+      className={cn(
+        "z-50 overflow-hidden rounded-md bg-primary px-3 py-1.5 text-xs text-primary-foreground animate-in fade-in-0 zoom-in-95 data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=closed]:zoom-out-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2",
+        className,
+      )}
+      {...props}
+    />
+  </TooltipPrimitive.Portal>
+));
+TooltipContent.displayName = TooltipPrimitive.Content.displayName;
+
+export { Tooltip, TooltipContent, TooltipProvider, TooltipTrigger };

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

@@ -85,6 +85,33 @@ const Footer = () => {
                   <Text as="span">SharePoint</Text>
                 </a>
               </li>
+              <li>
+                <a
+                  href="https://llamaindex.ai/llamacloud-aws-s3-data-loading-for-generative-ai"
+                  data-tracking-variant="link"
+                  data-tracking-section="footer"
+                >
+                  <Text as="span">AWS S3</Text>
+                </a>
+              </li>
+              <li>
+                <a
+                  href="https://llamaindex.ai/llamacloud-azure-blob-storage-data-loading-for-generative-ai"
+                  data-tracking-variant="link"
+                  data-tracking-section="footer"
+                >
+                  <Text as="span">Azure Blob Storage</Text>
+                </a>
+              </li>
+              <li>
+                <a
+                  href="https://llamaindex.ai/llamacloud-google-drive-data-loading-for-generative-ai"
+                  data-tracking-variant="link"
+                  data-tracking-section="footer"
+                >
+                  <Text as="span">Google Drive</Text>
+                </a>
+              </li>
             </ul>
           </div>
           <div>
@@ -171,11 +198,6 @@ const Footer = () => {
                   <Text as="span">SEC Insights</Text>
                 </a>
               </li>
-              <li>
-                <a href="https://chat.llamaindex.ai/">
-                  <Text as="span">Chat LlamaIndex</Text>
-                </a>
-              </li>
               <li>
                 <a href="https://github.com/run-llama/llamabot">
                   <Text as="span">LlamaBot</Text>

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

@@ -12,7 +12,9 @@ export interface TextProps {
   weight?: 400 | 500 | 600;
   children?: ReactNode;
   className?: string;
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
   as?: any;
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
   maximumWidth?: any;
 }
 

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

@@ -0,0 +1,47 @@
+---
+title: Using API Route
+description: Chat interface for your LlamaIndexTS application using API Route
+---
+import { ChatDemo } from '../../../../../components/demo/chat/api/demo';
+import "@llamaindex/chat-ui/styles/code.css";
+import "@llamaindex/chat-ui/styles/katex.css";
+
+Using [chat-ui](https://github.com/run-llama/chat-ui), it's easy to add a chat interface to your LlamaIndexTS application.
+You just need to create an API route that provides an `api/chat` endpoint and a chat component to consume the API.
+
+## API route
+
+As an example, this is an API route for the Next.js App Router. Copy the following code into your `app/api/chat/route.ts` file to get started:
+
+```json doc-gen:file
+{
+  "file": "./src/app/api/chat/route.ts",
+	"codeblock": true
+}
+```
+
+## Chat UI
+
+This is the simplest way to add a chat interface to your application. Copy the following code into your application to consume the API:
+
+```json doc-gen:file
+{
+  "file": "./src/components/demo/chat/api/demo.tsx",
+	"codeblock": true
+}
+```
+
+## Try it out ⬇️
+
+Combining both, you're getting a fully functional chat interface:
+
+<ChatDemo />
+
+
+## Next Steps
+
+The steps above are the bare minimum to get a chat interface working. From here, you can go two ways:
+
+1. Use [create-llama](https://github.com/run-llama/create-llama) to scaffold a new LlamaIndexTS project including complex API routes and chat interfaces or
+2. Learn more about [chat-ui](https://github.com/run-llama/chat-ui) and [LlamaIndexTS](https://github.com/run-llama/llamaindex-ts) to customize the chat interface and API routes to your needs.
+

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

@@ -0,0 +1,6 @@
+{
+  "title": "Chat-UI",
+  "description": "Use chat-ui to add a chat interface to your LlamaIndexTS application.",
+  "defaultOpen": false,
+  "pages": ["chat", "rsc"]
+}

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

@@ -0,0 +1,68 @@
+---
+title: Using Next.js RSC
+description: Chat interface for your LlamaIndexTS application using Next.js RSC
+---
+import { ChatDemoRSC } from '../../../../../components/demo/chat/rsc/demo';
+import "@llamaindex/chat-ui/styles/code.css";
+import "@llamaindex/chat-ui/styles/katex.css";
+
+Using [chat-ui](https://github.com/run-llama/chat-ui), it's easy to add a chat interface to your LlamaIndexTS application using [Next.js RSC](https://nextjs.org/docs/app/building-your-application/rendering/server-components) and [Vercel AI RSC](https://sdk.vercel.ai/docs/ai-sdk-rsc/overview).
+
+With RSC, the chat messages are not returned as JSON from the server (like when using an [API route](./chat)), instead the chat message components are rendered on the server side.
+This is for example useful for rendering a whole chat history on the server before sending it to the client. [Check here](https://sdk.vercel.ai/docs/getting-started/navigating-the-library#when-to-use-ai-sdk-rsc), for a discussion of when to use use RSC.
+
+For implementing a chat interface with RSC, you need to create an AI action and then connect the chat interface to use it.
+
+## Create an AI action
+
+First, define an [AI context provider](https://sdk.vercel.ai/examples/rsc/state-management/ai-ui-states) with a chat server action:
+
+```json doc-gen:file
+{
+  "file": "./src/components/demo/chat/rsc/ai-action.tsx",
+	"codeblock": true
+}
+```
+
+The chat server action is using LlamaIndexTS to generate a response based on the chat history and the user input.
+
+## Create the chat UI
+
+The entrypoint of our application initializes the AI provider for the application and adds a `ChatSection` component:
+
+```json doc-gen:file
+{
+  "file": "./src/components/demo/chat/rsc/demo.tsx",
+	"codeblock": true
+}
+```
+
+The `ChatSection` component is created by using chat components from @llamaindex/chat-ui:
+
+```json doc-gen:file
+{
+  "file": "./src/components/demo/chat/rsc/chat-section.tsx",
+	"codeblock": true
+}
+```
+
+It is using a `useChatRSC` hook to conntect the chat interface to the `chat` AI action that we defined earlier:
+
+```json doc-gen:file
+{
+  "file": "./src/components/demo/chat/rsc/use-chat-rsc.tsx",
+	"codeblock": true
+}
+```
+
+## Try RSC Chat ⬇️
+
+<ChatDemoRSC />
+
+## Next Steps
+
+The steps above are the bare minimum to get a chat interface working with RSC. From here, you can go two ways:
+
+1. Use our [full-stack RSC example](https://github.com/run-llama/nextjs-rsc) based on [create-llama](https://github.com/run-llama/create-llama) to get started quickly with a fully working chat interface or
+2. Learn more about [AI RSC](https://sdk.vercel.ai/examples/rsc), [chat-ui](https://github.com/run-llama/chat-ui) and [LlamaIndexTS](https://github.com/run-llama/llamaindex-ts) to customize the chat interface and AI actions to your needs.
+

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

@@ -0,0 +1,5 @@
+{
+  "title": "Guide",
+  "description": "See our guide",
+  "pages": ["workflow", "chat"]
+}

apps/next/src/content/docs/llamaindex/guide/workflow/different-inputs-outputs.mdx

@@ -0,0 +1,226 @@
+---
+title: Inputs / Outputs
+description: Learn how to use different inputs and outputs in your workflows.
+---
+
+Inputs and outputs are the way to communicate between steps in a workflow. In the previous example,
+we used `StartEvent` and `StopEvent` to communicate between steps. However, you can use any type of event to communicate between steps.
+
+## Multiple inputs
+
+You can define multiple inputs for a step.
+
+In the following example, we define a complex workflow with multiple inputs and outputs.
+
+```ts twoslash
+import { Workflow, StartEvent, StopEvent, WorkflowEvent } from '@llamaindex/workflow';
+
+class AEvent extends WorkflowEvent<string> {
+	constructor(data: string) {
+		super(data);
+	}
+}
+
+class BEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+
+class ResultEvent extends WorkflowEvent<string> {
+	constructor(data: string) {
+		super(data);
+	}
+}
+```
+
+First, let's define the events that we will use in the workflow.
+
+```ts twoslash
+import { Workflow, StartEvent, StopEvent, WorkflowEvent } from '@llamaindex/workflow';
+
+class AEvent extends WorkflowEvent<string> {
+	constructor(data: string) {
+		super(data);
+	}
+}
+
+class BEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+
+class ResultEvent extends WorkflowEvent<string> {
+	constructor(data: string) {
+		super(data);
+	}
+}
+
+const workflow = new Workflow<never, string, string>();
+
+workflow.addStep({
+	inputs: [StartEvent<string>],
+	outputs: [StopEvent<string>]
+}, async (
+	context,
+	startEvent
+) => {
+	const input = startEvent.data;
+	const aEvent = await context.requireEvent(AEvent);
+	const bEvent = await context.requireEvent(BEvent);
+	const a = aEvent.data;
+	const b = bEvent.data;
+	return new StopEvent(`Hello, ${input}! A: ${a}, B: ${b}`);
+});
+
+// ---cut---
+workflow.addStep({
+	inputs: [AEvent, BEvent],
+	outputs: [ResultEvent]
+}, async (
+	context,
+	aEvent,
+	bEvent
+) => {
+	const a = aEvent.data;
+	const b = bEvent.data;
+	return new ResultEvent(`A: ${a}, B: ${b}`);
+});
+```
+
+This step means that it requires two events: `AEvent` and `BEvent`. It will return a `ResultEvent` with the data `A: ${a}, B: ${b}`.
+
+## A or B input
+
+If we want to have a step that can accept either `AEvent` or `BEvent`, we can define the step like this:
+
+```ts twoslash
+import { Workflow, StartEvent, StopEvent, WorkflowEvent } from '@llamaindex/workflow';
+
+class AEvent extends WorkflowEvent<string> {
+	constructor(data: string) {
+		super(data);
+	}
+}
+
+class BEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+
+class ResultEvent extends WorkflowEvent<string> {
+	constructor(data: string) {
+		super(data);
+	}
+}
+
+const workflow = new Workflow<never, string, string>();
+
+workflow.addStep({
+	inputs: [StartEvent<string>],
+	outputs: [StopEvent<string>]
+}, async (
+	context,
+	startEvent
+) => {
+	const input = startEvent.data;
+	const aEvent = await context.requireEvent(AEvent);
+	const bEvent = await context.requireEvent(BEvent);
+	const a = aEvent.data;
+	const b = bEvent.data;
+	return new StopEvent(`Hello, ${input}! A: ${a}, B: ${b}`);
+});
+
+// ---cut---
+workflow.addStep({
+	inputs: [WorkflowEvent.or(AEvent, BEvent)],
+	outputs: [ResultEvent]
+}, async (
+	context,
+	aOrBEvent
+) => {
+	if (aOrBEvent instanceof AEvent) {
+		// ^?
+
+
+		const a = aOrBEvent.data;
+		//        ^?
+
+
+		return new ResultEvent(`A: ${a}`);
+	} else {
+		const b = aOrBEvent.data;
+		//        ^?
+
+
+		return new ResultEvent(`B: ${b}`);
+	}
+});
+```
+
+This step means that it requires either `AEvent` or `BEvent`. It will return a `ResultEvent` with the data `A: ${a}` or `B: ${b}`.
+
+You can still combine the logic with `context.requireEvent` to get the data from the event.
+
+import { Accordion, Accordions } from 'fumadocs-ui/components/accordion';
+
+<Accordions>
+	<Accordion title="Under the hood">
+		We use JavaScript Inheritance and the prototype chain to implement the `or` logic.
+		The `or` method creates a new class that extends the two classes that you pass to it.
+
+		<a
+			target="_blank"
+			href="https://developer.mozilla.org/en-US/docs/Web/JavaScript/Inheritance_and_the_prototype_chain"
+		>
+			MDN - Inheritance and the prototype chain
+		</a>
+	</Accordion>
+</Accordions>
+
+## Multiple outputs
+
+You can define multiple outputs for a step.
+
+```ts twoslash
+import { Workflow, StartEvent, StopEvent, WorkflowEvent } from '@llamaindex/workflow';
+
+class AEvent extends WorkflowEvent<string> {
+	constructor(data: string) {
+		super(data);
+	}
+}
+
+class BEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+
+class ResultEvent extends WorkflowEvent<string> {
+	constructor(data: string) {
+		super(data);
+	}
+}
+
+const workflow = new Workflow<never, string, string>();
+// ---cut---
+workflow.addStep({
+	inputs: [StartEvent<string>],
+	outputs: [AEvent, BEvent]
+}, async (
+	context,
+	startEvent
+) => {
+	const input = startEvent.data;
+	if (Math.random() > 0.5) {
+		return new AEvent(`Hello, ${input}!`);
+	} else {
+		return new BEvent(42);
+	}
+});
+```
+
+This step will return either an `AEvent` or a `BEvent` based on a random number.

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

@@ -0,0 +1,208 @@
+---
+title: Basic Usage
+description: Learn how to use the LlamaIndex workflow.
+---
+
+A `Workflow` in LlamaIndex.TS is an event-driven abstraction used to chain together several events.
+Workflows are made up of steps, with each step responsible for handling certain event types and emitting new events.
+
+Workflows are designed for any cases that benefit from event-driven programming, not only for LLM and AI tasks.
+
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install @llamaindex/workflow
+	```
+
+	```shell tab="yarn"
+	yarn add @llamaindex/workflow
+	```
+
+	```shell tab="pnpm"
+	pnpm add @llamaindex/workflow
+	```
+</Tabs>
+
+## Start from scratch
+
+Let's start from a Hello World workflow.
+
+```ts twoslash
+import { Workflow } from '@llamaindex/workflow';
+
+type ContextData = {
+	counter: number;
+}
+// ---cut---
+const contextData: ContextData = { counter: 0 };
+
+const workflow = new Workflow<ContextData, string, string>();
+//     ^?
+
+
+
+```
+
+First, we define a workflow with 3 generic types: `ContextData`, `Input`, and `Output`.
+
+In general, `ContextData` is used to store the shared data between steps, `Input` is the type of the input event, and `Output` is the type of the output event.
+
+In you code logic, you should **share state between steps via `ContextData`**.
+
+```ts twoslash
+import { Workflow, StartEvent, StopEvent } from '@llamaindex/workflow';
+
+type ContextData = {
+	counter: number;
+}
+
+const contextData: ContextData = { counter: 0 };
+
+const workflow = new Workflow<ContextData, string, string>();
+// ---cut---
+workflow.addStep({
+	inputs: [StartEvent<string>],
+	outputs: [StopEvent<string>]
+}, async (context, startEvent) => {
+	const input = startEvent.data;
+	context.data.counter++;
+	return new StopEvent(`Hello, ${input}!`);
+});
+```
+
+In the workflow, we add a step that listens to `StartEvent<string>` and emits `StopEvent<string>`.
+
+The step is an async function that takes two arguments: `context` and `event`.
+
+### `context` type
+
+<AutoTypeTable path="./src/deps/type.ts" name="HandlerContext" />
+
+There are two more properties in `HandlerContext`:
+
+- `sendEvent`: invoke another event in the workflow, other than `StartEvent`, `StopEvent`, or the current event. (Or there will have circular reference)
+- `requireEvent`: wait for a specific event to be emitted.
+
+You can use `sendEvent` and `requireEvent` to build complex workflows.
+
+```ts twoslash
+import { Workflow, StartEvent, StopEvent, WorkflowEvent } from '@llamaindex/workflow';
+
+type ContextData = {
+	counter: number;
+}
+
+const contextData: ContextData = { counter: 0 };
+
+const workflow = new Workflow<ContextData, string, string>();
+
+// ---cut---
+class AnalysisStartEvent extends WorkflowEvent<string> {}
+class AnalysisStopEvent extends WorkflowEvent<boolean> {}
+workflow.addStep({
+	inputs: [AnalysisStartEvent],
+	outputs: [AnalysisStopEvent]
+}, async (...args) => {
+	// do some analysis
+	return new AnalysisStopEvent(true);
+})
+workflow.addStep({
+	inputs: [StartEvent<string>],
+	outputs: [StopEvent<string>]
+}, async (context, startEvent) => {
+	const input = startEvent.data;
+	context.sendEvent(new AnalysisStartEvent('start'));
+	context.data.counter++;
+	const { data } = await context.requireEvent(AnalysisStopEvent);
+	return new StopEvent(`Hello, ${input}! Analysis result: ${data ? 'success' : 'fail'}`);
+});
+```
+
+For example, you can compile `requireEvent` with `waitUntil` in [Vercel Functions](https://vercel.com/docs/functions/functions-api-reference#waituntil) or [Cloudflare Worker](https://developers.cloudflare.com/workers/runtime-apis/context/#waituntil)
+
+```ts twoslash
+import { waitUntil } from '@vercel/functions';
+import { Workflow, StartEvent, StopEvent, WorkflowEvent } from '@llamaindex/workflow';
+
+type ContextData = {
+	counter: number;
+}
+
+const contextData: ContextData = { counter: 0 };
+
+const workflow = new Workflow<ContextData, string, string>();
+
+class AnalysisStartEvent extends WorkflowEvent<string> {}
+class AnalysisStopEvent extends WorkflowEvent<boolean> {}
+
+// ---cut---
+workflow.addStep({
+	inputs: [StartEvent<string>],
+	outputs: [StopEvent<string>]
+}, async (context, startEvent) => {
+	const input = startEvent.data;
+	context.sendEvent(new AnalysisStartEvent('start'));
+	context.data.counter++;
+	waitUntil(context.requireEvent(AnalysisStopEvent));
+	// note that `waitUntil` is not a promise, it will extend the lifetime of the workflow
+	// you can wait for some background tasks to finish
+	return new StopEvent(`Hello, ${input}!`);
+});
+```
+
+## Multiple runs
+
+You can run the same workflow multiple times with different inputs.
+
+```ts twoslash
+import { Workflow, StartEvent, StopEvent } from '@llamaindex/workflow';
+
+type ContextData = {
+	counter: number;
+}
+
+const contextData: ContextData = { counter: 0 };
+
+const workflow = new Workflow<ContextData, string, string>();
+
+workflow.addStep({
+	inputs: [StartEvent<string>],
+	outputs: [StopEvent<string>]
+}, async (context, startEvent) => {
+	const input = startEvent.data;
+	context.data.counter++;
+	return new StopEvent(`Hello, ${input}!`);
+});
+
+// ---cut---
+{
+	const ret = await workflow.run('Alex', contextData);
+	console.log(ret.data); // Hello, Alex!
+}
+
+{
+	const ret = await workflow.run('World', contextData);
+	console.log(ret.data); // Hello, World!
+}
+```
+
+Context is shared between runs, so the counter will be increased.
+
+Ideally, it should be serializable to make sure it can be recovered from HTTP requests or other storage.
+
+### Full example
+
+<iframe
+	className="w-full h-[440px]"
+	aria-label="Workflow example"
+	src="https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples?file=node/workflow/basic.ts"
+/>
+
+## `Workflow` type
+
+<AutoTypeTable path="./src/deps/type.ts" name="Workflow" />
+
+## `WorkflowContext` type
+
+<AutoTypeTable path="./src/deps/type.ts" name="WorkflowContext" />

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

@@ -0,0 +1,6 @@
+{
+  "title": "Workflow",
+  "description": "See how to use @llamaindex/workflow",
+  "defaultOpen": false,
+  "pages": ["index", "different-inputs-outputs", "streaming"]
+}

apps/next/src/content/docs/llamaindex/guide/workflow/streaming.mdx

@@ -0,0 +1,199 @@
+---
+title: Streaming
+description: Learn how to use the LlamaIndex workflow with streaming.
+---
+import { WorkflowStreamingDemo } from '../../../../../components/demo/workflow-streaming-ui';
+
+`Workflow` API by default is designed for streaming data. In this guide, we will show you how to use the `Workflow` API with streaming data.
+
+Each `workflow.run` call returns `WorkflowContext`, which implements `AsyncIterable` interface. You can use it to stream data.
+
+```ts twoslash
+import { Workflow, WorkflowEvent, StartEvent, StopEvent } from '@llamaindex/workflow';
+class ComputeEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+class ComputeResultEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+
+type ContextData = {
+	sum: number;
+}
+
+const workflow = new Workflow<ContextData, number, number>();
+workflow.addStep({
+	inputs: [StartEvent<number>],
+	outputs: [StopEvent<number>]
+}, async (context, startEvent) => {
+	const total = startEvent.data;
+	for (let i = 0; i < total; i++) {
+		context.sendEvent(new ComputeEvent(i));
+	}
+	const computeResults = await Promise.all(Array.from({ length: total }).map(() => context.requireEvent(ComputeResultEvent)));
+	// Workflow API allows you to start events in parallel and wait for all of them to finish
+	context.data.sum = computeResults.reduce((acc, curr) => acc + curr.data, 0);
+	return new StopEvent(context.data.sum);
+});
+```
+
+We define a parallel computation workflow that computes the sum of numbers from 0 to `total`.
+
+The workflow sends `ComputeEvent` events for each number and waits for `ComputeResultEvent` events. After receiving all `ComputeResultEvent` events, the workflow returns the sum as a `StopEvent`.
+
+What if we want cutoff if the sum exceeds a certain value?
+
+## Streaming
+
+```ts twoslash
+import { Workflow, WorkflowEvent, StartEvent, StopEvent } from '@llamaindex/workflow';
+import { StopCircle } from 'lucide-react';
+class ComputeEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+class ComputeResultEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+
+
+type ContextData = {
+	sum: number;
+}
+
+const workflow = new Workflow<ContextData, number, number>();
+// ---cut---
+const context = workflow.run(1000, {
+	sum: 0
+});
+
+for await (const event of context) {
+	if (event instanceof ComputeEvent) {
+		if (context.data.sum > 100) {
+			throw new Error('Sum exceeds 100');
+		}
+	}
+	if (event instanceof StopEvent) {
+		console.log('result', event.data);
+	}
+}
+```
+
+You can define more custom logic using `AsyncIterable` interface.
+
+For example. I just want to stop the workflow if I get a `ComputeResultEvent`
+
+
+```ts twoslash
+import { Workflow, WorkflowEvent, StartEvent, StopEvent } from '@llamaindex/workflow';
+import { StopCircle } from 'lucide-react';
+class ComputeEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+class ComputeResultEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+
+
+type ContextData = {
+	sum: number;
+}
+
+const workflow = new Workflow<ContextData, number, number>();
+// ---cut---
+async function compute() {
+	const context = workflow.run(1000, {
+		sum: 0
+	});
+	for await (const event of context) {
+		if (event instanceof ComputeResultEvent) {
+			return event.data;
+		}
+	}
+	throw new Error('UNREACHABLE');
+}
+
+const result = await compute();
+```
+
+### Streaming with UI
+
+You can use the `Workflow` API with UI libraries like React.
+
+```tsx twoslash
+// @filename: utils.ts
+export async function runWithoutBlocking(fn: () => Promise<void>) {
+	fn();
+}
+// @filename: action.ts
+// ---cut---
+'use server';
+// "use server" is required to enable server side feature in React
+import { createStreamableUI } from 'ai/rsc';
+import { runWithoutBlocking } from './utils';
+// ---cut-start---
+import { Workflow, WorkflowEvent, StartEvent, StopEvent } from '@llamaindex/workflow';
+class ComputeEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+class ComputeResultEvent extends WorkflowEvent<number> {
+	constructor(data: number) {
+		super(data);
+	}
+}
+
+
+type ContextData = {
+	sum: number;
+}
+
+const workflow = new Workflow<ContextData, number, number>();
+const min = 100;
+const max = 1000;
+workflow.addStep(
+	{
+		inputs: [ComputeEvent],
+		outputs: [ComputeResultEvent]
+	},
+	async (context, event) => {
+		await new Promise((resolve) =>
+			setTimeout(resolve, Math.floor(Math.random() * (max - min + 1) + min))
+		);
+		return new ComputeResultEvent(event.data);
+	}
+);
+// ---cut-end---
+export async function compute() {
+	'use server';
+	const ui = createStreamableUI();
+	const context = workflow.run(100, {
+		sum: 0
+	});
+	runWithoutBlocking(async () => {
+		for await (const event of context) {
+			if (event instanceof ComputeResultEvent) {
+				// Update UI
+			} else if (event instanceof StopEvent) {
+				// Update UI
+			}
+			// ...
+		}
+	});
+	return ui.value;
+}
+```
+
+<WorkflowStreamingDemo />

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

@@ -1,95 +1,35 @@
 ---
-title: What is LlamaIndex?
-description: LlamaIndex is a framework for building LLM-powered applications.
+title: Getting Started with LlamaIndex.TS
+description: Install llamaindex by running a single command.
 ---
 
-import {
-  SiGithub,
-  SiNpm,
-  SiX,
-  SiDiscord,
-} from "@icons-pack/react-simple-icons";
-import { CodeBlock, Pre } from "fumadocs-ui/components/codeblock";
 import { Tab, Tabs } from "fumadocs-ui/components/tabs";
 
-LlamaIndex helps you ingest, structure, and access private or domain-specific data. It's available [as a Python package](https://docs.llamaindex.ai/en/stable/) and in TypeScript (this package).
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install llamaindex
+	```
 
-LlamaIndex.TS offers the core features of LlamaIndex for JS Runtime-agnostic (Node.js, Deno, and Bun) applications.
+	```shell tab="yarn"
+	yarn add llamaindex
+	```
 
-## 🚀 Why LlamaIndex.TS?
-
-LLMs offer a natural language interface between humans and inferred data. Widely available models come pre-trained on huge amounts of publicly available data, from Wikipedia and mailing lists to textbooks and source code.
-
-Applications built on top of LLMs often require augmenting these models with private or domain-specific data. That data is often distributed across siloed applications and data stores. It's behind APIs, in SQL databases, or trapped in PDFs and slide decks.
-
-LlamaIndex.TS helps you unlock that data and then build powerful applications with it.
-
-## 🦙 What is LlamaIndex for?
-
-LlamaIndex.TS handles several major use cases:
-
-- **Structured Data Extraction**: turning complex, unstructured and semi-structured data into uniform, programmatically accessible formats.
-- **Retrieval-Augmented Generation (RAG)**: answering queries across your internal data by providing LLMs with up-to-date, semantically relevant context including Question and Answer systems and chat bots.
-- **Autonomous Agents**: building software that is capable of intelligently selecting and using tools to accomplish tasks in an interactive, unsupervised manner.
-
-## 👨‍👩‍👧‍👦 Who is LlamaIndex for?
-
-LlamaIndex targets the "AI Engineer": developers building software in any domain that can be enhanced by LLM-powered functionality, without needing to be an expert in machine learning or natural language processing.
-
-Our high-level API allows beginner users to use LlamaIndex.TS to ingest, index, and query their data in just a few lines of code.
-
-For more complex applications, our lower-level APIs allow advanced users to customize and extend any module—data connectors, indices, retrievers, and query engines, to fit their needs.
-
-## Getting Started
-
-<Tabs items={["npm", "yarn", "pnpm"]}>
-  <Tab value="npm">
-    <CodeBlock language="shell">
-      <Pre>npm install llamaindex</Pre>
-    </CodeBlock>
-  </Tab>
-  <Tab value="yarn">
-    <CodeBlock language="shell">
-      <Pre>yarn add llamaindex</Pre>
-    </CodeBlock>
-  </Tab>
-  <Tab value="pnpm">
-    <CodeBlock language="shell">
-      <Pre>pnpm add llamaindex</Pre>
-    </CodeBlock>
-  </Tab>
+	```shell tab="pnpm"
+	pnpm add llamaindex
+	```
 </Tabs>
 
-Our documentation includes [Installation Instructions](./getting_started/installation.mdx) and a [Starter Tutorial](./getting_started/starter_tutorial/retrieval_augmented_generation.mdx) to build your first application.
-
-Once you're up and running, [High-Level Concepts](./getting_started/concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our Examples section on the sidebar.
-
-## 🗺️ Ecosystem
-
-To download or contribute, find LlamaIndex on:
+## What's next?
 
 <Cards>
-  <Card
-    icon={<SiGithub />}
-    title="GitHub"
-    href="https://github.com/run-llama/LlamaIndexTS"
-  />
-  <Card
-    icon={<SiNpm />}
-    title="NPM"
-    href="https://www.npmjs.com/package/llamaindex"
-  />
-</Cards>
-
-## Community
-
-Need help? Have a feature suggestion? Join the LlamaIndex community:
-
-<Cards>
-  <Card icon={<SiX />} title="Twitter" href="https://twitter.com/llama_index" />
-  <Card
-    icon={<SiDiscord />}
-    title="Discord"
-    href="https://discord.gg/dGcwcsnxhU"
-  />
+	<Card
+		title="I want to try LlamaIndex.TS"
+		description="Learn how to use LlamaIndex.TS with different JS runtime and frameworks."
+		href="/docs/llamaindex/setup/getting-started"
+	/>
+	<Card
+		title="Show me code examples"
+		description="Explore code examples using LlamaIndex.TS."
+		href="https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples?file=README.md"
+	/>
 </Cards>

apps/next/src/content/docs/llamaindex/integration/lang-trace.mdx

@@ -0,0 +1,39 @@
+---
+title: Langtrace
+description: Learn how to integrate LlamaIndex.TS with Langtrace.
+---
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+Enhance your observability with Langtrace, a robust open-source tool supports OpenTelemetry and is designed to trace, evaluate, and manage LLM applications seamlessly. Langtrace integrates directly with LlamaIndex, offering detailed, real-time insights into performance metrics such as accuracy, evaluations, and latency.
+
+## Install
+
+- Self-host or sign-up and generate an API key using [Langtrace](https://www.langtrace.ai) Cloud
+
+<Tabs groupId="install-langtrase" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install @langtrase/typescript-sdk
+	```
+
+	```shell tab="yarn"
+	yarn add @langtrase/typescript-sdk
+	```
+
+	```shell tab="pnpm"
+	pnpm add @langtrase/typescript-sdk
+	```
+</Tabs>
+
+## Initialize
+
+```js
+import * as Langtrace from "@langtrase/typescript-sdk";
+Langtrace.init({ api_key: "<YOUR_API_KEY>" });
+```
+
+Features:
+
+- OpenTelemetry compliant, ensuring broad compatibility with observability platforms.
+- Provides comprehensive logs and detailed traces of all components.
+- Real-time monitoring of accuracy, evaluations, usage, costs, and latency.
+- For more configuration options and details, visit [Langtrace Docs](https://docs.langtrace.ai/introduction).

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

@@ -0,0 +1,5 @@
+{
+  "title": "Integration",
+  "description": "See our integrations",
+  "pages": ["open-llm-metry", "lang-trace", "vercel"]
+}

apps/next/src/content/docs/llamaindex/integration/open-llm-metry.mdx

@@ -0,0 +1,34 @@
+---
+title: OpenLLMetry
+description: Learn how to integrate LlamaIndex.TS with OpenLLMetry.
+---
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+[OpenLLMetry](https://github.com/traceloop/openllmetry-js) is an open-source project based on OpenTelemetry for tracing and monitoring
+LLM applications. It connects to [all major observability platforms](https://www.traceloop.com/docs/openllmetry/integrations/introduction) and installs in minutes.
+
+### Usage Pattern
+
+
+<Tabs groupId="install-traceloop" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install @traceloop/node-server-sdk
+	```
+
+	```shell tab="yarn"
+	yarn add @traceloop/node-server-sdk
+	```
+
+	```shell tab="pnpm"
+	pnpm add @traceloop/node-server-sdk
+	```
+</Tabs>
+
+```js
+import * as traceloop from "@traceloop/node-server-sdk";
+
+traceloop.initialize({
+  apiKey: process.env.TRACELOOP_API_KEY,
+  disableBatch: true
+});
+```

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

@@ -0,0 +1,101 @@
+---
+title: Vercel
+description: Integrate LlamaIndex with Vercel's AI SDK
+---
+
+LlamaIndex provides integration with Vercel's AI SDK, allowing you to create powerful search and retrieval applications. You can:
+- Use any of Vercel AI's [model providers](https://sdk.vercel.ai/docs/foundations/providers-and-models) as LLMs in LlamaIndex
+- Use indexes (e.g. VectorStoreIndex, LlamaCloudIndex) from LlamaIndexTS in your Vercel AI applications
+
+## Setup
+
+First, install the required dependencies:
+
+```bash
+npm install @llamaindex/vercel ai
+```
+
+## Using Vercel AI's Model Providers 
+
+Using the `VercelLLM` adapter, it's easy to use any of Vercel AI's [model providers](https://sdk.vercel.ai/docs/foundations/providers-and-models) as LLMs in LlamaIndex. Here's an example of how to use OpenAI's GPT-4o model:
+
+```typescript
+const llm = new VercelLLM({ model: openai("gpt-4o") });
+const result = await llm.complete({
+  prompt: "What is the capital of France?",
+  stream: false, // Set to true if you want streaming responses
+});
+console.log(result.text);
+```
+
+## Use Indexes
+
+### Using VectorStoreIndex
+
+Here's how to create a simple vector store index and query it using Vercel's AI SDK:
+
+```typescript
+import { openai } from "@ai-sdk/openai";
+import { llamaindex } from "@llamaindex/vercel";
+import { streamText } from "ai";
+import { Document, VectorStoreIndex } from "llamaindex";
+
+// Create an index from your documents
+const document = new Document({ text: yourText, id_: "unique-id" });
+const index = await VectorStoreIndex.fromDocuments([document]);
+
+// Create a query tool
+const queryTool = llamaindex({
+  model: openai("gpt-4"),
+  index,
+  description: "Search through the documents", // optional
+});
+
+// Use the tool with Vercel's AI SDK
+streamText({
+  model: openai("gpt-4"),
+  prompt: "Your question here",
+  tools: { queryTool },
+  onFinish({ response }) {
+    console.log("Response:", response.messages); // log the response
+  },
+}).toDataStream();
+```
+
+> Note: the Vercel AI model referenced in the `llamaindex` function is used by the response synthesizer to generate a response for the tool call.
+
+### Using LlamaCloud
+
+For production deployments, you can use LlamaCloud to store and manage your documents:
+
+```typescript
+import { LlamaCloudIndex } from "llamaindex";
+
+// Create a LlamaCloud index
+const index = await LlamaCloudIndex.fromDocuments({
+  documents: [document],
+  name: "your-index-name",
+  projectName: "your-project",
+  apiKey: process.env.LLAMA_CLOUD_API_KEY,
+});
+
+// Use it the same way as VectorStoreIndex
+const queryTool = llamaindex({
+  model: openai("gpt-4"),
+  index,
+  description: "Search through the documents",
+});
+
+// Use the tool with Vercel's AI SDK
+streamText({
+  model: openai("gpt-4"),
+  prompt: "Your question here",
+  tools: { queryTool },
+}).toDataStream();
+```
+
+## Next Steps
+
+1. Explore [LlamaCloud](https://cloud.llamaindex.ai/) for managed document storage and retrieval
+2. Join our [Discord community](https://discord.gg/dGcwcsnxhU) for support and discussions
+

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

@@ -0,0 +1,105 @@
+---
+title: Document and Nodes
+description: llamaindex readers is a collection of readers for different file formats.
+---
+
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+import { Accordion, Accordions } from 'fumadocs-ui/components/accordion';
+
+<Accordions>
+	<Accordion title="Install @llamaindex/readers">
+
+		If you want to only use reader modules, you can install `@llamaindex/readers`
+
+		<Tabs groupId="install-llamaindex" items={["npm", "yarn", "pnpm"]} persist>
+			```shell tab="npm"
+			npm install @llamaindex/readers
+			```
+
+			```shell tab="yarn"
+			yarn add @llamaindex/readers
+			```
+
+			```shell tab="pnpm"
+			pnpm add @llamaindex/readers
+			```
+
+		</Tabs>
+	</Accordion>
+</Accordions>
+
+We offer readers for different file formats.
+
+<Tabs groupId="llamaindex-or-readers" items={["llamaindex", "@llamaindex/readers"]} persist>
+	```ts twoslash tab="llamaindex"
+	import { CSVReader } from 'llamaindex'
+	import { PDFReader } from 'llamaindex'
+	import { JSONReader } from 'llamaindex'
+	import { MarkdownReader } from 'llamaindex'
+	import { HTMLReader } from 'llamaindex'
+	// you can find more readers in the documentation
+	```
+
+	```ts twoslash tab="@llamaindex/readers"
+	import { CSVReader } from '@llamaindex/readers/csv'
+	import { PDFReader } from '@llamaindex/readers/pdf'
+	import { JSONReader } from '@llamaindex/readers/json'
+	import { MarkdownReader } from '@llamaindex/readers/markdown'
+	import { HTMLReader } from '@llamaindex/readers/html'
+	// you can find more readers in the documentation
+	```
+
+</Tabs>
+
+## SimpleDirectoryReader
+
+`SimpleDirectoryReader` is the simplest way to load data from local files into LlamaIndex.
+
+<Tabs groupId="llamaindex-or-readers" items={["llamaindex", "@llamaindex/readers"]} persist>
+
+	```ts twoslash tab="llamaindex"
+	import { SimpleDirectoryReader } from "llamaindex";
+
+	const reader = new SimpleDirectoryReader()
+	const documents = await reader.loadData("./data")
+	//    ^?
+
+
+	const texts = documents.map(doc => doc.getText())
+	//    ^?
+	```
+
+	```ts twoslash tab="@llamaindex/readers"
+	import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
+
+	const reader = new SimpleDirectoryReader()
+	const documents = await reader.loadData("./data")
+	//    ^?
+
+
+	const texts = documents.map(doc => doc.getText())
+	//    ^?
+	```
+
+</Tabs>
+
+## Load file natively using Node.js Customization Hooks
+
+We have a helper utility to allow you to import a file in Node.js script.
+
+<Tabs groupId="llamaindex-or-readers" items={["llamaindex", "@llamaindex/readers"]} persist>
+	```shell tab="llamaindex"
+	node --import llamaindex/register ./script.js
+	```
+
+	```shell tab="@llamaindex/readers"
+	node --import @llamaindex/readers/node ./script.js
+	```
+</Tabs>
+
+```ts
+import csv from './path/to/data.csv';
+
+const text = csv.getText()
+```

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

@@ -0,0 +1,5 @@
+{
+  "title": "Loading Data",
+  "description": "Loading Data using LlamaIndex.TS",
+  "pages": ["index", "node-parser"]
+}

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

@@ -0,0 +1,158 @@
+---
+title: Node Parsers / Text Splitters
+description: Learn how to use Node Parsers and Text Splitters to extract data from documents.
+---
+import { CodeNodeParserDemo } from '../../../../components/demo/code-node-parser';
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+Node parsers are a simple abstraction that take a list of documents, and chunk them into `Node` objects, such that each node is a specific chunk of the parent document. When a document is broken into nodes, all of it's attributes are inherited to the children nodes (i.e. `metadata`, text and metadata templates, etc.). You can read more about `Node` and `Document` properties [here](./).
+
+## NodeParser
+
+The `NodeParser` in LlamaIndex is responsible for splitting `Document` objects into more manageable `Node` objects.
+
+By default, we will use `Settings.nodeParser` to split the document into nodes. You can also assign a custom `NodeParser` to the `Settings` object.
+
+```ts twoslash
+import { TextFileReader } from '@llamaindex/readers/text'
+import { SentenceSplitter } from '@llamaindex/core/node-parser';
+import { Settings } from 'llamaindex';
+
+const nodeParser = new SentenceSplitter();
+Settings.nodeParser = nodeParser;
+//		     ^?
+```
+
+## TextSplitter
+
+The underlying text splitter will split text by sentences. It can also be used as a standalone module for splitting raw text.
+
+```ts twoslash
+import { SentenceSplitter } from "@llamaindex/core/node-parser";
+
+const splitter = new SentenceSplitter({ chunkSize: 1 });
+
+const texts = splitter.splitText("Hello World");
+//     ^?
+```
+
+## MarkdownNodeParser
+
+The `MarkdownNodeParser` is a more advanced `NodeParser` that can handle markdown documents. It will split the markdown into nodes and then parse the nodes into a `Document` object.
+
+<Tabs items={["with reader", "with node:fs"]}>
+	```ts twoslash tab="with reader"
+	import { MarkdownNodeParser } from "@llamaindex/core/node-parser";
+	import { MarkdownReader } from '@llamaindex/readers/markdown'
+
+	const reader = new MarkdownReader();
+	const markdownNodeParser = new MarkdownNodeParser();
+
+	const documents = await reader.loadData('path/to/file.md');
+	const parsedDocuments = markdownNodeParser(documents);
+	//      ^?
+
+	```
+
+	```ts twoslash tab="with node:fs"
+	import fs from 'node:fs/promises';
+	import { MarkdownNodeParser } from "@llamaindex/core/node-parser";
+	import { Document } from '@llamaindex/core/schema';
+
+	const markdownNodeParser = new MarkdownNodeParser();
+	const text = await fs.readFile('path/to/file.md', 'utf-8');
+	const document = new Document({ text });
+
+	const parsedDocuments = markdownNodeParser([document]);
+	//		  ^?
+
+	```
+</Tabs>
+
+## CodeSplitter
+
+The `CodeSplitter` is a more advanced `NodeParser` that can handle code documents.
+It will split the code by AST nodes and then parse the nodes into a `Document` object.
+
+<Tabs items={["with reader", "with node:fs"]}>
+	```ts twoslash tab="with reader"
+	import { TextFileReader } from '@llamaindex/readers/text'
+	import { CodeSplitter } from '@llamaindex/node-parser/code'
+	import Parser from "tree-sitter";
+	import TS from "tree-sitter-typescript";
+
+	const parser = new Parser();
+	parser.setLanguage(TS.typescript);
+	const codeSplitter = new CodeSplitter({
+		getParser: () => parser,
+	});
+	const reader = new TextFileReader();
+	const documents = await reader.loadData('path/to/file.ts');
+
+	const parsedDocuments = codeSplitter(documents);
+	//			  ^?
+	```
+
+	```ts twoslash tab="with node:fs"
+	import fs from 'node:fs/promises';
+	import { CodeSplitter } from '@llamaindex/node-parser/code'
+	import Parser from "tree-sitter";
+	import TS from "tree-sitter-typescript";
+
+	const parser = new Parser();
+	parser.setLanguage(TS.typescript);
+	const codeSplitter = new CodeSplitter({
+	  getParser: () => parser,
+	});
+
+	const parsedDocuments = codeSplitter.splitText(await fs.readFile('path/to/file.ts', 'utf-8'));
+	//			 ^?
+	```
+</Tabs>
+
+Try it out ⬇️
+
+<CodeNodeParserDemo/>
+
+import { Accordion, Accordions } from 'fumadocs-ui/components/accordion';
+
+<Accordions>
+	<Accordion title="Use it in browser">
+		You might setup WASM files for `web-tree-sitter` and use it in the browser.
+
+		```ts
+		import Parser from 'web-tree-sitter';
+
+		Parser.init({
+			locateFile(scriptName: string) {
+			return '/' + scriptName
+		},
+		}).then(async () => {
+			const parser = new Parser();
+			const Lang = await Parser.Language.load('/tree-sitter-typescript.wasm');
+			parser.setLanguage(Lang);
+			return new CodeSplitter({
+				getParser: () => parser,
+				maxChars: 100
+			});
+		});
+		```
+
+		In this example, you should put `tree-sitter-typescript.wasm` to the `public` folder for Next.js.
+
+		And also update the `next.config.js` to make `@llamaindex/env` work properly.
+
+		```js
+		const config = {
+			webpack: (config) => {
+				if (Array.isArray(config.target) && config.target.includes('web')) {
+					config.target = ["web", "es2020"];
+				}
+				return config;
+			}
+		}
+
+		export default config;
+		```
+	</Accordion>
+</Accordions>

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

@@ -2,5 +2,14 @@
   "title": "LlamaIndex",
   "description": "The Data framework for LLM",
   "root": true,
-  "pages": ["---Guide---", "index"]
+  "pages": [
+    "---Guide---",
+    "what-is-llamaindex",
+    "index",
+    "setup",
+    "starter",
+    "loading",
+    "guide",
+    "integration"
+  ]
 }

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

@@ -0,0 +1,41 @@
+---
+title: More
+description: More
+---
+
+import {
+  SiGithub,
+  SiNpm,
+  SiX,
+  SiDiscord,
+} from "@icons-pack/react-simple-icons";
+
+## 🗺️ Ecosystem
+
+To download or contribute, find LlamaIndex on:
+
+<Cards>
+  <Card
+    icon={<SiGithub />}
+    title="GitHub"
+    href="https://github.com/run-llama/LlamaIndexTS"
+  />
+  <Card
+    icon={<SiNpm />}
+    title="NPM"
+    href="https://www.npmjs.com/package/llamaindex"
+  />
+</Cards>
+
+## Community
+
+Need help? Have a feature suggestion? Join the LlamaIndex community:
+
+<Cards>
+  <Card icon={<SiX />} title="Twitter" href="https://twitter.com/llama_index" />
+  <Card
+    icon={<SiDiscord />}
+    title="Discord"
+    href="https://discord.gg/dGcwcsnxhU"
+  />
+</Cards>

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

@@ -0,0 +1,79 @@
+---
+title: With Cloudflare Worker
+description: In this guide, you'll learn how to use LlamaIndex with CloudFlare Worker
+---
+
+import {
+  SiNodedotjs,
+  SiDeno,
+  SiBun,
+  SiCloudflareworkers,
+} from "@icons-pack/react-simple-icons";
+
+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/setup/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, insteadof a long-running process in Node.js.
+- Some of LlamaIndex.TS modules are not available in Cloudflare Worker, for example `SimpleDirectoryReader` (requires `node:fs`), Some multimodal API that relies on [`onnxruntime-node`](https://www.npmjs.com/package/onnxruntime-node)(we might port to HTTP based module in the future).
+- `@llamaindex/core` is designed to work in all JavaScript environment, including Cloudflare Worker. If you find any issue, please report to us.
+- `@llamaindex/env` is a JS environment binding module, which polyfill some Node.js/Modern Web API (for example, we have a memory based `fs` module, and Crypto API polyfill). It is designed to work in all JavaScript environment, including Cloudflare Worker.
+
+## Known issues
+
+- `llamaindex` not work perfectly in Cloudflare Worker, bundle size will be larger than 1MB, which is the limit of Cloudflare Worker. You will need import submodule instead of the whole `llamaindex` module.

apps/next/src/content/docs/llamaindex/setup/getting-started.mdx

@@ -0,0 +1,42 @@
+---
+title: Getting Started
+description: We support multiple JS runtime and frameworks, bundlers.
+---
+import {
+	SiNodedotjs,
+	SiTypescript,
+	SiNextdotjs,
+	SiCloudflareworkers,
+	SiVite
+} from "@icons-pack/react-simple-icons";
+
+<Cards>
+	<Card title={
+		<>
+			<SiNodedotjs className="inline" color="#5FA04E" /> Node.js
+		</>
+	} href="/docs/llamaindex/setup/node" />
+	<Card title={
+		<>
+			<SiTypescript className="inline" color="#3178C6" /> TypeScript
+		</>
+	} href="/docs/llamaindex/setup/typescript" />
+	<Card title={
+		<>
+			<SiVite className='inline' color='#646CFF' /> Vite
+		</>
+	} href="/docs/llamaindex/setup/vite" />
+	<Card
+		title={
+			<>
+				<SiNextdotjs className='inline' /> Next.js (React Server Component)
+			</>
+		}
+		href="/docs/llamaindex/setup/next"
+	/>
+	<Card title={
+		<>
+			<SiCloudflareworkers className='inline' color='#F38020' /> Cloudflare Workers
+		</>
+	} href="/docs/llamaindex/setup/cloudflare" />
+</Cards>

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

@@ -0,0 +1,13 @@
+{
+  "title": "Setup",
+  "description": "The setup guide",
+  "defaultOpen": true,
+  "pages": [
+    "getting-started",
+    "next",
+    "node",
+    "typescript",
+    "vite",
+    "cloudflare"
+  ]
+}

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

@@ -0,0 +1,41 @@
+---
+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/setup/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.
+LlamaIndex.TS has lots of upstream dependencies, some of them are not compatible with Next.js.
+
+You might need to use `withNext` 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](./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.

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

@@ -0,0 +1,30 @@
+---
+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).
+
+## TypeScript support
+
+<Card
+	title="Getting Started with LlamaIndex.TS in TypeScript"
+	href="/docs/llamaindex/setup/typescript"
+/>

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

@@ -0,0 +1,132 @@
+---
+title: With TypeScript
+description: In this guide, you'll learn how to use LlamaIndex with TypeScript
+---
+import { Accordion, Accordions } from 'fumadocs-ui/components/accordion';
+
+LlamaIndex.TS is written in TypeScript and designed to be used in TypeScript projects.
+
+We do lots of work on strong typing to make sure you have a great typing experience with LlamaIndex.TS.
+
+```ts twoslash
+import { PromptTemplate } from '@llamaindex/core/prompts'
+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
+//^|
+})
+```
+
+```ts twoslash
+import { FunctionTool } from '@llamaindex/core/tools'
+import { z } from 'zod'
+
+// ---cut-before---
+const inputSchema = z.object({
+	time: z.string(),
+	city: z.string(),
+})
+
+type Input = z.infer<typeof inputSchema>
+
+FunctionTool.from<Input>((input) => {
+// @noErrors
+	input.t
+//      ^|
+}, {
+	name: 'getWeather',
+	description: 'Get the weather information',
+	parameters: inputSchema,
+})
+```
+
+## Enable TypeScript
+
+
+```json5
+{
+  compilerOptions: {
+    // ⬇️ add this line to your tsconfig.json
+    moduleResolution: "bundler", // or "node16"
+  },
+}
+```
+
+<Accordions>
+	<Accordion
+		title="Why modify tsconfig.json"
+	>
+
+We are shipping both ESM and CJS module, and compatible with Vercel Edge, Cloudflare Workers, and other serverless platforms.
+
+So we are using [conditional exports](https://nodejs.org/api/packages.html#conditional-exports) to support all environments.
+
+This is a kind of modern way of shipping packages, but might cause TypeScript type check to fail because of legacy module resolution.
+
+Imaging you put output file into `/dist/openai.js` but you are importing `llamaindex/openai` in your code, and set `package.json` like this:
+
+```json5
+{
+	"exports": {
+		"./openai": "./dist/openai.js"
+	}
+}
+```
+
+In old module resolution, TypeScript will not be able to find the module because it is not following the file structure, even you run `node index.js` successfully. (on Node.js >=16)
+
+See more about [moduleResolution](https://www.typescriptlang.org/docs/handbook/modules/theory.html#module-resolution) or
+[TypeScript 5.0 blog](https://devblogs.microsoft.com/typescript/announcing-typescript-5-0/#--moduleresolution-bundler7).
+
+
+	</Accordion>
+</Accordions>
+
+## Enable AsyncIterable for `Web Stream` API
+
+Some modules uses `Web Stream` API like `ReadableStream` and `WritableStream`, you need to enable `DOM.AsyncIterable` in your `tsconfig.json`.
+
+```json5
+{
+  compilerOptions: {
+    // ⬇️ add this lib to your tsconfig.json
+    lib: ["DOM.AsyncIterable"],
+  },
+}
+```
+
+```ts twoslash
+import { OpenAIAgent } from '@llamaindex/openai'
+
+const agent = new OpenAIAgent({
+  tools: []
+})
+
+const response = await agent.chat({
+  message: 'Hello, how are you?',
+  stream: true
+})
+for await (const _ of response) {
+                      //^?
+  // ...
+}
+```
+
+## Run TypeScript Script in Node.js
+
+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
+```