Release 0.9.11 (#1734)

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>

CONTRIBUTING.md

@@ -14,13 +14,14 @@ There are some important folders in the repository:
     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...
+  - `providers/*`: The providers package of LlamaIndex.TS, which contains the providers for LLM and other services.
 - `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
 
-Make sure you have Node.js LIS (Long-term Support) installed. You can check your Node.js version by running:
+Make sure you have Node.js LTS (Long-term Support) installed. You can check your Node.js version by running:
 
 ```shell
 node -v
@@ -30,7 +31,7 @@ node -v
 ### Use pnpm
 
 ```shell
-corepack enable
+npm install -g pnpm
 ```
 
 ### Install dependencies
@@ -41,33 +42,65 @@ pnpm install
 
 ### Build the packages
 
-You'll need Turbo to build the packages. If you don't have it, you can run it with `pnpx`.
-
 To build all packages, run:
 
 ```shell
-# Build all packages
-pnpx turbo build --filter "./packages/*"
-
-# Or if you have turbo installed, you can run:
-turbo build --filter "./packages/*"
+pnpm build
 ```
 
+### Run tests
+
+#### Unit tests
+
+After build, to run all unit tests, call:
+
+```shell
+pnpm test
+```
+
+Unit tests are located in the `tests` folder of each package. They are using their own package (e.g. `@llamaindex/core-tests` for `@llamaindex/core`). The tests are importing the package under test and the test package is not published.
+
+#### E2E tests
+
+To run all E2E tests, call:
+
+```shell
+pnpm e2e
+```
+
+All E2E tests are in the `e2e` folder.
+
 ### Docs
 
 See the [docs](./apps/next/README.md) for more information.
 
-## Changeset
+## Adding a new package
+
+Please follow these steps to add a new package:
+
+1. Only add new packages to the `packages/providers` folder.
+2. Use the `package.json` and `tsconfig.json` of an existing packages as template.
+3. Reference your new package in the root `tsconfig.json` file
+4. Add your package to the `examples/package.json` file if you add a new example.
+
+## Before sending a PR
+
+Before sending a PR, make sure of the following:
+
+1. Tests are all running and you added meaningful tests for your change.
+2. If you have a new feature, document it in the `apps/next` docs folder.
+3. If you have a new feature, add a new example in the `examples` folder.
+4. You have a descriptive changeset for each PR:
+
+### Changesets
 
 We use [changesets](https://github.com/changesets/changesets) for managing versions and changelogs. To create a new
 changeset, run in the root folder:
 
-```
+```shell
 pnpm changeset
 ```
 
-Please send a descriptive changeset for each PR.
-
 ## Publishing (maintainers only)
 
 The [Release Github Action](.github/workflows/release.yml) is automatically generating and updating a

apps/next/CHANGELOG.md

@@ -1,5 +1,33 @@
 # @llamaindex/doc
 
+## 0.1.11
+
+### Patch Changes
+
+- a8c0637: feat: simplify to provide base URL to OpenAI
+- a654f58: Added docs for using perplexity
+- 98eebf7: Add RequestOptions parameter passing to support Gemini proxy calls.
+  Add a usage example for the RequestOptions parameter.
+- Updated dependencies [a8c0637]
+  - @llamaindex/openai@0.1.61
+  - llamaindex@0.9.11
+
+## 0.1.10
+
+### Patch Changes
+
+- Updated dependencies [aea550a]
+- Updated dependencies [c1b5be5]
+- Updated dependencies [40ee761]
+- Updated dependencies [40ee761]
+  - @llamaindex/openai@0.1.60
+  - llamaindex@0.9.10
+  - @llamaindex/workflow@0.0.16
+  - @llamaindex/core@0.5.8
+  - @llamaindex/cloud@3.0.9
+  - @llamaindex/node-parser@1.0.8
+  - @llamaindex/readers@2.0.8
+
 ## 0.1.9
 
 ### Patch Changes

apps/next/README.md

@@ -6,8 +6,7 @@ This is a Next.js application generated with
 Run development server:
 
 ```bash
-turbo run dev
-# turbo will build all required packages before running the dev server
+pnpm run dev
 ```
 
 ## Learn More

apps/next/next.config.mjs

@@ -5,8 +5,15 @@ const withMDX = createMDX();
 /** @type {import('next').NextConfig} */
 const config = {
   reactStrictMode: true,
+  eslint: {
+    ignoreDuringBuilds: true,
+  },
   transpilePackages: ["monaco-editor"],
-  serverExternalPackages: ["@huggingface/transformers"],
+  serverExternalPackages: [
+    "@huggingface/transformers",
+    "twoslash",
+    "typescript",
+  ],
   webpack: (config, { isServer }) => {
     if (Array.isArray(config.target) && config.target.includes("web")) {
       config.target = ["web", "es2020"];

apps/next/package.json

@@ -1,18 +1,19 @@
 {
   "name": "@llamaindex/doc",
-  "version": "0.1.9",
+  "version": "0.1.11",
   "private": true,
   "scripts": {
-    "build": "pnpm run build:docs && next build",
+    "postinstall": "fumadocs-mdx",
+    "prebuild": "pnpm run build:docs",
+    "build": "next build",
     "dev": "next dev",
     "start": "next start",
-    "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"
+    "postbuild": "tsx scripts/post-build.mts",
+    "build:docs": "cross-env NODE_OPTIONS=\"--max-old-space-size=8192\" typedoc && tsx scripts/generate-docs.mts"
   },
   "dependencies": {
     "@icons-pack/react-simple-icons": "^10.1.0",
-    "@llamaindex/chat-ui": "0.0.9",
+    "@llamaindex/chat-ui": "0.2.0",
     "@llamaindex/cloud": "workspace:*",
     "@llamaindex/core": "workspace:*",
     "@llamaindex/node-parser": "workspace:*",
@@ -27,36 +28,35 @@
     "@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",
     "@scalar/api-client-react": "^1.1.25",
+    "@vercel/functions": "^1.5.0",
     "ai": "^3.4.33",
     "class-variance-authority": "^0.7.0",
     "clsx": "2.1.1",
     "foxact": "^0.2.41",
     "framer-motion": "^11.11.17",
-    "fumadocs-core": "^14.7.7",
-    "fumadocs-docgen": "^1.3.7",
-    "fumadocs-mdx": "^11.5.3",
-    "fumadocs-openapi": "^5.12.0",
-    "fumadocs-twoslash": "^2.0.3",
-    "fumadocs-typescript": "^3.0.3",
-    "fumadocs-ui": "^14.7.7",
+    "fumadocs-core": "^15.0.15",
+    "fumadocs-docgen": "^2.0.0",
+    "fumadocs-mdx": "^11.5.6",
+    "fumadocs-openapi": "^6.3.0",
+    "fumadocs-twoslash": "^3.1.0",
+    "fumadocs-typescript": "^3.1.0",
+    "fumadocs-ui": "^15.0.15",
     "hast-util-to-jsx-runtime": "^2.3.2",
     "llamaindex": "workspace:*",
     "lucide-react": "^0.460.0",
-    "next": "15.1.7",
+    "next": "^15.2.1",
     "next-themes": "^0.4.3",
     "react": "^19.0.0",
     "react-dom": "^19.0.0",
     "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": "^2.3.2",
-    "shiki-magic-move": "^1.0.0",
+    "shiki": "^3.1.0",
+    "shiki-magic-move": "^1.0.1",
     "swr": "^2.2.5",
     "tailwind-merge": "^2.5.2",
     "tailwindcss-animate": "^1.0.7",
@@ -67,27 +67,28 @@
     "zod": "^3.23.8"
   },
   "devDependencies": {
-    "@next/env": "^15.0.3",
+    "@next/env": "^15.2.1",
+    "@tailwindcss/postcss": "^4.0.9",
     "@types/mdx": "^2.0.13",
     "@types/node": "22.9.0",
-    "@types/react": "^18.3.12",
-    "@types/react-dom": "^18.3.1",
+    "@types/react": "^19.0.10",
+    "@types/react-dom": "^19.0.4",
     "autoprefixer": "^10.4.20",
     "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",
+    "postcss": "^8.5.3",
     "raw-loader": "^4.0.2",
     "remark": "^15.0.1",
     "remark-gfm": "^4.0.0",
     "remark-mdx": "^3.1.0",
     "remark-stringify": "^11.0.0",
-    "tailwindcss": "^3.4.15",
-    "tsx": "^4.19.2",
+    "tailwindcss": "^4.0.9",
+    "tsx": "^4.19.3",
     "typedoc": "0.27.4",
     "typedoc-plugin-markdown": "^4.3.1",
     "typedoc-plugin-merge-modules": "^6.1.0",
-    "typescript": "^5.7.2"
+    "typescript": "^5.7.3"
   }
 }

apps/next/postcss.config.js

@@ -1,6 +0,0 @@
-module.exports = {
-  plugins: {
-    tailwindcss: {},
-    autoprefixer: {},
-  },
-};

apps/next/postcss.config.mjs

@@ -0,0 +1,5 @@
+export default {
+  plugins: {
+    "@tailwindcss/postcss": {},
+  },
+};

apps/next/scripts/generate-docs.mts

@@ -1,8 +1,7 @@
-import * as OpenAPI from "fumadocs-openapi";
-import { generateFiles } from "fumadocs-typescript";
+import { generateFiles as openapiGenerateFiles } from "fumadocs-openapi";
+import { generateFiles as typescriptGenerateFiles } 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";
@@ -15,28 +14,23 @@ rimrafSync(out, {
   },
 });
 
-void OpenAPI.generateFiles({
-  input: [
-    fileURLToPath(
-      new URL("../../../packages/cloud/openapi.json", import.meta.url),
-    ),
-  ],
-  output: out,
+void openapiGenerateFiles({
+  input: ["../../packages/cloud/openapi.json"],
+  output: "./src/content/docs/cloud/api",
   groupBy: "tag",
 });
 
-void generateFiles({
+void typescriptGenerateFiles({
   input: ["./src/content/docs/api/**/*.mdx"],
   output: (file) => path.resolve(path.dirname(file), path.basename(file)),
   transformOutput,
 });
 
-function transformOutput(filePath, content) {
+function transformOutput(filePath: string, content: string) {
   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)}`;
+  return `---\ntitle: ${title}\n---\n\n${transformAbsoluteUrl(content, filePath)}`;
 }
 
 /**
@@ -46,20 +40,17 @@ function transformOutput(filePath, content) {
  * [text](BaseVectorStore.mdx#constructors) -> [text](/docs/api/classes/BaseVectorStore#constructors)
  * [text](TaskStep.mdx) -> [text](/docs/api/type-aliases/TaskStep)
  */
-function transformAbsoluteUrl(content, filePath) {
+function transformAbsoluteUrl(content: string, filePath: string) {
   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})`;
-    },
-  );
+  return content.replace(/\]\(([^)]+)\.mdx([^)]*)\)/g, (_, 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

apps/next/scripts/post-build.mts

@@ -4,4 +4,8 @@ import { updateLlamaCloud } from "./update-llamacloud.mjs";
 
 env.loadEnvConfig(process.cwd());
 
-await updateLlamaCloud();
+if (process.env.VERCEL_ENV === "production") {
+  updateLlamaCloud().catch((error) => {
+    console.error(error);
+  });
+}

apps/next/scripts/update-llamacloud.mts

@@ -1,11 +1,7 @@
 import { upsertBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPut } from "@llamaindex/cloud/api";
 import fg from "fast-glob";
-import {
-  fileGenerator,
-  remarkDocGen,
-  remarkInstall,
-  typescriptGenerator,
-} from "fumadocs-docgen";
+import { fileGenerator, remarkDocGen, remarkInstall } from "fumadocs-docgen";
+import { remarkAutoTypeTable } from "fumadocs-typescript";
 import matter from "gray-matter";
 import * as fs from "node:fs/promises";
 import path, { relative } from "node:path";
@@ -21,7 +17,8 @@ async function processContent(content: string): Promise<string> {
   const file = await remark()
     .use(remarkMdx)
     .use(remarkGfm)
-    .use(remarkDocGen, { generators: [typescriptGenerator(), fileGenerator()] })
+    .use(remarkAutoTypeTable)
+    .use(remarkDocGen, { generators: [fileGenerator()] })
     .use(remarkInstall, { persist: { id: "package-manager" } })
     .use(remarkStringify)
     .process(content);

apps/next/source.config.ts

@@ -2,10 +2,11 @@ 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 { createFileSystemTypesCache } from "fumadocs-twoslash/cache-fs";
 import rehypeKatex from "rehype-katex";
 import remarkMath from "remark-math";
 
-export const { docs, meta } = defineDocs({
+export const docs = defineDocs({
   dir: "./src/content/docs",
 });
 
@@ -20,7 +21,11 @@ export default defineConfig({
       },
       transformers: [
         ...(rehypeCodeDefaultOptions.transformers ?? []),
-        transformerTwoslash(),
+        transformerTwoslash({
+          typesCache: createFileSystemTypesCache({
+            dir: ".next/cache/twoslash",
+          }),
+        }),
         {
           name: "transformers:remove-notation-escape",
           code(hast) {

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

@@ -8,7 +8,7 @@ import {
 } from "@/components/infinite-providers";
 import { MagicMove } from "@/components/magic-move";
 import { NpmInstall } from "@/components/npm-install";
-import { TextEffect } from "@/components/text-effect";
+import { Supports } from "@/components/supports";
 import { Button } from "@/components/ui/button";
 import { Skeleton } from "@/components/ui/skeleton";
 import { LEGACY_DOCUMENT_URL } from "@/lib/const";
@@ -24,18 +24,18 @@ 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">
+      <h1 className="mb-4 text-center text-4xl font-bold md:text-6xl">
         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 ">
+      <p className="text-fd-muted-foreground mb-12 text-center text-xl">
         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">
+      <div className="text-fd-muted-foreground mb-12 text-center text-lg">
         <span>Designed for building web applications in </span>
-        <TextEffect />
+        <Supports />
       </div>
 
       <div className="flex flex-wrap justify-center gap-4">
@@ -60,7 +60,7 @@ export default function HomePage() {
           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."
+          description="LlamaIndex.TS is designed to be simple to get started, but powerful enough to build complex, agentic AI applications using multi-agents."
         >
           <Suspense
             fallback={
@@ -76,44 +76,48 @@ export default function HomePage() {
           >
             <MagicMove
               code={[
-                `import { OpenAI } from "@llamaindex/openai";
+                `import { openai } from "@llamaindex/openai";
 
-const llm = new OpenAI();
+const llm = openai();
 const response = await llm.complete({ prompt: "How are you?" });`,
-                `import { OpenAI } from "@llamaindex/openai";
+                `import { openai } from "@llamaindex/openai";
 
-const llm = new OpenAI();
+const llm = openai();
 const response = await llm.chat({
   messages: [{ content: "Tell me a joke.", role: "user" }],
 });`,
-                `import { ChatMemoryBuffer } from "llamaindex";
-import { OpenAI } from "@llamaindex/openai";
+                `import { agent } from "llamaindex";
+import { openai } from "@llamaindex/openai";
 
-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 { ChatMemoryBuffer } from "llamaindex";
-import { OpenAIAgent } from "@llamaindex/openai";
-
-const agent = new OpenAIAgent({
-  llm,
-  tools: [...myTools]
+const analyseAgent = agent({
+  llm: openai({ model: "gpt-4o" }),
+  tools: [analyseTools],
   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(),
-});`,
+const response = await analyseAgent.run(\`Analyse the given data:
+\${data}\`);`,
+                `import { agent, multiAgent } from "llamaindex";
+import { openai } from "@llamaindex/openai";
+
+const analyseAgent = agent({
+  name: "AnalyseAgent",
+  llm: openai({ model: "gpt-4o" }),
+  tools: [analyseTools],
+});
+const reporterAgent = agent({
+  name: "ReporterAgent",
+  llm: openai({ model: "gpt-4o" }),
+  tools: [reporterTools],
+  canHandoffTo: [analyseAgent],
+});
+
+const agents = multiAgent({
+  agents: [analyseAgent, reporterAgent],
+  rootAgent: reporterAgent,
+});
+
+const response = await agents.run(\`Analyse the given data:
+\${data}\`);`,
               ]}
             />
           </Suspense>
@@ -125,19 +129,20 @@ const response = await agent.chat({
           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";
-import { OpenAIAgent } from "@llamaindex/openai";
+            code={`import { agent, SimpleDirectoryReader, VectorStoreIndex } from "llamaindex";
+import { openai } from "@llamaindex/openai";
 
-const interpreterTool = FunctionTool.from(...);
-const systemPrompt = \`...\`;
+// load documents from current directoy into an index
+const reader = new SimpleDirectoryReader();
+const documents = await reader.loadData(currentDir);
+const index = await VectorStoreIndex.fromDocuments(documents);
 
-const agent = new OpenAIAgent({
-  llm,
-  tools: [interpreterTool],
-  systemPrompt,
+const myAgent = agent({
+  llm: openai({ model: "gpt-4o" }),
+  tools: [index.queryTool()],
 });
 
-await agent.chat('...');`}
+await myAgent.run('...');`}
             lang="ts"
           />
         </Feature>
@@ -149,13 +154,13 @@ await agent.chat('...');`}
         >
           <div className="mt-8 flex flex-col gap-8">
             <div>
-              <h3 className="text-lg font-semibold text-fd-muted-foreground mb-2">
+              <h3 className="text-fd-muted-foreground mb-2 text-lg font-semibold">
                 LLMs
               </h3>
               <InfiniteLLMProviders />
             </div>
             <div>
-              <h3 className="text-lg font-semibold text-fd-muted-foreground mb-2">
+              <h3 className="text-fd-muted-foreground mb-2 text-lg font-semibold">
                 Vector Stores
               </h3>
               <InfiniteVectorStoreProviders />

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

@@ -1,11 +0,0 @@
-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/docs/[[...slug]]/page.tsx

@@ -13,6 +13,8 @@ import { notFound } from "next/navigation";
 
 const { AutoTypeTable } = createTypeTable();
 
+export const revalidate = false;
+
 export default async function Page(props: {
   params: Promise<{ slug?: string[] }>;
 }) {
@@ -26,10 +28,10 @@ export default async function Page(props: {
     <DocsPage
       toc={page.data.toc}
       full={page.data.full}
+      lastUpdate={page.data.lastModified}
       editOnGithub={{
         owner: "run-llama",
         repo: "LlamaIndexTS",
-        sha: "main",
         path: `apps/next/src/content/docs/${page.file.path}`,
       }}
     >
@@ -64,6 +66,7 @@ export async function generateMetadata(props: {
 
   return createMetadata(
     metadataImage.withImage(page.slugs, {
+      metadataBase: new URL("https://ts.llamaindex.ai"),
       title: page.data.title,
       description: page.data.description,
       openGraph: {

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

@@ -22,7 +22,7 @@ export default function Layout({ children }: { children: ReactNode }) {
                 variant: "secondary",
                 size: "xs",
                 className:
-                  "md:flex-1 px-2 ms-2 gap-1.5 text-fd-muted-foreground rounded-full",
+                  "text-fd-muted-foreground ms-2 gap-1.5 rounded-full px-2 md:flex-1",
               }),
             )}
           >

apps/next/src/app/global.css

@@ -1,6 +1,13 @@
-@tailwind base;
-@tailwind components;
-@tailwind utilities;
+@import "tailwindcss";
+@import "fumadocs-ui/css/neutral.css";
+@import "fumadocs-ui/css/preset.css";
+@import "../../node_modules/fumadocs-twoslash/dist/twoslash.css";
+@plugin "tailwindcss-animate";
+@source '../../node_modules/fumadocs-ui/dist/**/*.js';
+@source "../../node_modules/fumadocs-openapi/dist/**/*.js",
+@source '../../node_modules/@llamaindex/chat-ui/dist/**/*.js';
+@config "../../tailwind.config.mjs";
+
 @layer base {
   :root {
     --page-max-width: 1840px;
@@ -46,6 +53,7 @@
     --chart-5: 27 87% 67%;
     --radius: 0.5rem;
   }
+
   .dark {
     --color-neutral-000: #0e0c15;
     --color-neutral-100: #252134;
@@ -87,40 +95,3 @@
     --chart-5: 340 75% 55%;
   }
 }
-@layer base {
-  * {
-    @apply border-border;
-  }
-  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.tsx

@@ -32,7 +32,7 @@ export default function Layout({ children }: { children: ReactNode }) {
           href="/favicon-16x16.png"
         />
       </head>
-      <body className="flex flex-col min-h-screen">
+      <body className="flex min-h-screen flex-col">
         <TooltipProvider>
           <AIProvider>
             <RootProvider>{children}</RootProvider>

apps/next/src/app/llms.txt/route.ts

@@ -0,0 +1,62 @@
+import fg from "fast-glob";
+import { fileGenerator, remarkDocGen, remarkInstall } from "fumadocs-docgen";
+import { remarkInclude } from "fumadocs-mdx/config";
+import { remarkAutoTypeTable } from "fumadocs-typescript";
+import matter from "gray-matter";
+import * as fs from "node:fs/promises";
+import path from "node:path";
+import { remark } from "remark";
+import remarkGfm from "remark-gfm";
+import remarkMdx from "remark-mdx";
+import remarkStringify from "remark-stringify";
+
+export const revalidate = false;
+
+export async function GET() {
+  const files = await fg([
+    "./src/content/docs/**/*.mdx",
+    // remove generated openapi files
+    "!./src/content/docs/cloud/api/**/*",
+  ]);
+
+  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(4);
+    const category = {
+      llamaindex: "LlamaIndexTS Framework",
+      api: "LlamaIndexTS API",
+      cloud: "LlamaCloud Service",
+    }[dir ?? ""];
+
+    const processed = await processContent(file, content);
+    return `file: ${file}
+# ${category}: ${data.title}
+
+${data.description}
+        
+${processed}`;
+  });
+
+  const scanned = await Promise.all(scan);
+
+  return new Response(scanned.join("\n\n"));
+}
+
+async function processContent(path: string, content: string): Promise<string> {
+  const file = await remark()
+    .use(remarkMdx)
+    .use(remarkInclude)
+    .use(remarkGfm)
+    .use(remarkAutoTypeTable)
+    .use(remarkDocGen, { generators: [fileGenerator()] })
+    .use(remarkInstall, { persist: { id: "package-manager" } })
+    .use(remarkStringify)
+    .process({
+      path,
+      value: content,
+    });
+
+  return String(file);
+}

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

@@ -45,13 +45,13 @@ export const AITrigger = (props: AITriggerProps) => {
     <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" />
+        <DialogOverlay className="bg-fd-background/50 data-[state=closed]:animate-fd-fade-out data-[state=open]:animate-fd-fade-in fixed inset-0 z-50 backdrop-blur-sm" />
         <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"
+          className="bg-fd-popover text-fd-popover-foreground data-[state=closed]:animate-fd-dialog-out data-[state=open]:animate-fd-dialog-in 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 shadow-lg focus-visible:outline-none"
         >
           <DialogHeader>
             <DialogTitle className="sr-only">Search AI</DialogTitle>
@@ -67,11 +67,11 @@ export const AITrigger = (props: AITriggerProps) => {
               </AlertDescription>
             </Alert>
           </DialogHeader>
-          <div className="overflow-scroll flex-grow mt-4">
+          <div className="mt-4 flex-grow overflow-scroll">
             <ChatList messages={messages} />
           </div>
           <form
-            className="px-4 py-2 space-y-4"
+            className="space-y-4 px-4 py-2"
             action={async () => {
               const value = inputValue.trim();
               setInputValue("");
@@ -102,7 +102,7 @@ export const AITrigger = (props: AITriggerProps) => {
               }
             }}
           >
-            <div className="flex flex-row w-full items-center gap-2">
+            <div className="flex w-full flex-row items-center gap-2">
               <Textarea
                 tabIndex={0}
                 placeholder="Ask AI about documentation."

apps/next/src/components/code-block.tsx

@@ -1,50 +1,21 @@
+import { highlight } from "fumadocs-core/highlight";
 import * as Base from "fumadocs-ui/components/codeblock";
-import { toJsxRuntime, type Jsx } from "hast-util-to-jsx-runtime";
-import { Fragment } from "react";
-import { jsx, jsxs } from "react/jsx-runtime";
-import { codeToHast } from "shiki";
+import type { BundledLanguage } from "shiki";
 
 export interface CodeBlockProps {
   code: string;
   wrapper?: Base.CodeBlockProps;
-  lang: "bash" | "ts" | "tsx";
+  lang: BundledLanguage;
 }
 
-export async function CodeBlock({
-  code,
-  lang,
-  wrapper,
-}: CodeBlockProps): Promise<React.ReactElement> {
-  const hast = await codeToHast(code, {
+export async function CodeBlock({ code, lang, wrapper }: CodeBlockProps) {
+  const rendered = await highlight(code, {
     lang,
-    defaultColor: false,
     themes: {
       light: "github-light",
       dark: "vesper",
     },
-    transformers: [
-      {
-        name: "rehype-code:pre-process",
-        line(node) {
-          if (node.children.length === 0) {
-            // Keep the empty lines when using grid layout
-            node.children.push({
-              type: "text",
-              value: " ",
-            });
-          }
-        },
-      },
-    ],
-  });
-
-  const rendered = toJsxRuntime(hast, {
-    jsx: jsx as Jsx,
-    jsxs: jsxs as Jsx,
-    Fragment,
-    development: false,
     components: {
-      // @ts-expect-error -- JSX component
       pre: Base.Pre,
     },
   });

apps/next/src/components/contribution.tsx

@@ -10,7 +10,7 @@ export function Contributing(): ReactElement {
       <h2 className="mb-4 text-xl font-semibold sm:text-2xl">
         Made possible by you <Heart className="inline align-middle" />
       </h2>
-      <p className="mb-4 text-fd-muted-foreground">
+      <p className="text-fd-muted-foreground mb-4">
         LlamaIndex.TS is powered by the open source community.
       </p>
       <div className="mb-8 flex flex-row items-center gap-2">

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

@@ -33,7 +33,7 @@ export default async function ContributorCounter({
             href={`https://github.com/${contributor.login}`}
             rel="noreferrer noopener"
             target="_blank"
-            className="size-10 overflow-hidden rounded-full border-4 border-fd-background bg-fd-background md:-mr-4 md:size-12"
+            className="border-fd-background bg-fd-background size-10 overflow-hidden rounded-full border-4 md:-mr-4 md:size-12"
             style={{
               zIndex: topContributors.length - i,
             }}
@@ -48,7 +48,7 @@ export default async function ContributorCounter({
           </a>
         ))}
         {displayCount < contributors.length ? (
-          <div className="size-12 content-center rounded-full bg-fd-secondary text-center">
+          <div className="bg-fd-secondary size-12 content-center rounded-full text-center">
             +{contributors.length - displayCount}
           </div>
         ) : null}

apps/next/src/components/create-app-animation.tsx

@@ -83,7 +83,7 @@ export function CreateAppAnimation(): React.ReactElement {
       }}
     >
       {tick > timeWindowOpen && (
-        <LaunchAppWindow className="absolute bottom-5 right-4 z-10 animate-in fade-in slide-in-from-top-10" />
+        <LaunchAppWindow className="animate-in fade-in slide-in-from-top-10 absolute bottom-5 right-4 z-10" />
       )}
       <pre className="overflow-hidden rounded-xl border text-xs">
         <div className="flex flex-row items-center gap-2 border-b px-4 py-2">
@@ -92,7 +92,7 @@ export function CreateAppAnimation(): React.ReactElement {
           <div className="grow" />
           <div className="size-2 rounded-full bg-red-400" />
         </div>
-        <div className="min-h-[200px] bg-gradient-to-b from-fd-secondary [mask-image:linear-gradient(to_bottom,white,transparent)]">
+        <div className="from-fd-secondary min-h-[200px] bg-gradient-to-b [mask-image:linear-gradient(to_bottom,white,transparent)]">
           <code className="grid p-4">{lines}</code>
         </div>
       </pre>
@@ -103,7 +103,7 @@ export function CreateAppAnimation(): React.ReactElement {
 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">
+      <div className="bg-background flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm">
         <IconUser />
       </div>
       <div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
@@ -122,7 +122,7 @@ function BotMessage({
 }) {
   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 bg-primary text-primary-foreground">
+      <div className="bg-primary text-primary-foreground flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm">
         <IconAI />
       </div>
       <div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
@@ -164,7 +164,7 @@ export function ChatExample() {
 
   return (
     <div className="max-w-64">
-      <div className="flex flex-col px-4 gap-2">
+      <div className="flex flex-col gap-2 px-4">
         {userMessageLength === userMessageFull.length && (
           <UserMessage>
             <span>{userMessageFull}</span>
@@ -204,11 +204,11 @@ function LaunchAppWindow(
     <div
       {...props}
       className={cn(
-        "overflow-hidden rounded-md border bg-fd-background shadow-xl",
+        "bg-fd-background overflow-hidden rounded-md border shadow-xl",
         props.className,
       )}
     >
-      <div className="relative flex h-6 flex-row items-center border-b bg-fd-muted px-4 text-xs text-fd-muted-foreground">
+      <div className="bg-fd-muted text-fd-muted-foreground relative flex h-6 flex-row items-center border-b px-4 text-xs">
         <p className="absolute inset-x-0 text-center">localhost:8080</p>
       </div>
       <div className="p-4 text-sm">

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

@@ -1,11 +1,16 @@
 "use client";
-import { ChatInput, ChatMessages, ChatSection } from "@llamaindex/chat-ui";
+import {
+  ChatHandler,
+  ChatInput,
+  ChatMessages,
+  ChatSection,
+} from "@llamaindex/chat-ui";
 import { useChat } from "ai/react";
 
 export const ChatDemo = () => {
   const handler = useChat();
   return (
-    <ChatSection handler={handler}>
+    <ChatSection handler={handler as ChatHandler}>
       <ChatMessages>
         <ChatMessages.List className="h-auto max-h-[400px]" />
         <ChatMessages.Actions />

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

@@ -1,23 +1,25 @@
 "use client";
 
 import {
+  ChatHandler,
   ChatInput,
   ChatMessage,
   ChatMessages,
   ChatSection as ChatSectionUI,
+  Message,
 } from "@llamaindex/chat-ui";
 import { useChatRSC } from "./use-chat-rsc";
 
 export const ChatSectionRSC = () => {
   const handler = useChatRSC();
   return (
-    <ChatSectionUI handler={handler}>
+    <ChatSectionUI handler={handler as ChatHandler}>
       <ChatMessages>
         <ChatMessages.List className="h-auto max-h-[400px]">
           {handler.messages.map((message, index) => (
             <ChatMessage
               key={index}
-              message={message}
+              message={message as Message}
               isLast={index === handler.messages.length - 1}
             >
               <ChatMessage.Avatar />

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

@@ -57,7 +57,7 @@ export const IDE = () => {
   const maxChars = useSlider();
   const useSetMaxChars = useSetSlider();
   return (
-    <div className="flex flex-col p-4 border-r max-h-96 overflow-scroll">
+    <div className="flex max-h-96 flex-col overflow-scroll border-r p-4">
       <div>
         <Label>Max Chars {maxChars}</Label>
         <Slider
@@ -113,7 +113,7 @@ const Preview = ({ text }: { text: string }) => {
       },
     },
   });
-  return <CodeBlock className="py-0 m-2">{rendered}</CodeBlock>;
+  return <CodeBlock className="m-2 py-0">{rendered}</CodeBlock>;
 };
 
 function ScrollToBottom() {
@@ -122,7 +122,7 @@ function ScrollToBottom() {
   return (
     !isAtBottom && (
       <button
-        className="absolute i-ph-arrow-circle-down-fill text-4xl rounded-lg left-[50%] translate-x-[-50%] bottom-0"
+        className="i-ph-arrow-circle-down-fill absolute bottom-0 left-[50%] translate-x-[-50%] rounded-lg text-4xl"
         onClick={() => scrollToBottom()}
       />
     )
@@ -136,7 +136,7 @@ export const NodePreview = () => {
   const textChunks = useMemo(() => parser.splitText(code), [code, maxChars]);
   return (
     <StickToBottom
-      className="block relative max-h-96 overflow-scroll"
+      className="relative block max-h-96 overflow-scroll"
       resize="smooth"
       initial="smooth"
     >
@@ -154,7 +154,7 @@ 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">
+      <div className="my-2 grid max-h-96 w-full grid-cols-1 gap-2 rounded-xl border md:grid-cols-2">
         <Skeleton className="h-96" />
         <Skeleton className="h-96" />
       </div>
@@ -165,13 +165,13 @@ export const CodeNodeParserDemo = () => {
       <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">
+            <div className="my-2 grid max-h-96 w-full grid-cols-1 gap-2 rounded-xl border md:grid-cols-2">
               <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">
+          <div className="my-2 grid max-h-96 w-full grid-cols-1 gap-2 rounded-xl border md:grid-cols-2">
             <IDE />
             <NodePreview />
           </div>

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

@@ -75,7 +75,7 @@ function ScrollToBottom() {
   return (
     !isAtBottom && (
       <button
-        className="absolute i-ph-arrow-circle-down-fill text-4xl rounded-lg left-[50%] translate-x-[-50%] bottom-0"
+        className="i-ph-arrow-circle-down-fill absolute bottom-0 left-[50%] translate-x-[-50%] rounded-lg text-4xl"
         onClick={() => scrollToBottom()}
       />
     )
@@ -91,9 +91,9 @@ export function WorkflowStreamingDemo() {
   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>{" "}
+    <div className="flex w-full flex-col items-start gap-2">
+      <div className="flex flex-row items-center justify-center">
+        <div className="mr-2 text-lg">Compute total</div>{" "}
         <FlowInput value={total} onChange={(value) => setTotal(value)} />
       </div>
       <Button
@@ -141,7 +141,7 @@ export function WorkflowStreamingDemo() {
       >
         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 className="flex max-h-96 w-full flex-col gap-2 overflow-y-auto rounded-lg border border-gray-200 p-2">
         <StickToBottom.Content className="flex flex-col gap-2">
           {ui}
         </StickToBottom.Content>

apps/next/src/components/feature.tsx

@@ -20,7 +20,7 @@ export function Feature({
       className={cn("border-l border-t px-6 py-12 md:py-16", className)}
       {...props}
     >
-      <div className="mb-4 inline-flex items-center gap-2 text-sm font-medium text-fd-muted-foreground">
+      <div className="text-fd-muted-foreground mb-4 inline-flex items-center gap-2 text-sm font-medium">
         <Icon className="size-4" />
         <p>{subheading}</p>
       </div>

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

@@ -60,7 +60,7 @@ export default function FlowInput({
           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",
+            "[appearance:textfield] [&::-webkit-inner-spin-button]:appearance-none [&::-webkit-outer-spin-button]:appearance-none",
           )}
           // Make sure to disable kerning, to match NumberFlow:
           style={{ fontKerning: "none" }}

apps/next/src/components/message.tsx

@@ -8,7 +8,7 @@ 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">
+      <div className="bg-background flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm">
         <IconUser />
       </div>
       <div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
@@ -54,7 +54,7 @@ export function BotCard({
     <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",
+          "bg-primary text-primary-foreground flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm",
           !showAvatar && "invisible",
         )}
       >

apps/next/src/components/npm-install.tsx

@@ -25,7 +25,7 @@ export const NpmInstall = () => {
       className="flex flex-row items-center justify-center"
     >
       <code className="mr-2">$ npm i llamaindex</code>
-      <div className="relative cursor-pointer bg-transparent w-4 h-4">
+      <div className="relative h-4 w-4 cursor-pointer bg-transparent">
         <div
           className={`absolute inset-0 transform transition-all duration-300 ${
             hasCheckIcon ? "scale-0 opacity-0" : "scale-100 opacity-100"

apps/next/src/components/reactbits/rotating-text.tsx

@@ -0,0 +1,268 @@
+import { cn } from "@/lib/utils";
+import {
+  AnimatePresence,
+  motion,
+  Transition,
+  type AnimationControls,
+  type Target,
+  type TargetAndTransition,
+  type VariantLabels,
+} from "framer-motion";
+import React, {
+  forwardRef,
+  useCallback,
+  useEffect,
+  useImperativeHandle,
+  useMemo,
+  useState,
+} from "react";
+
+export interface RotatingTextRef {
+  next: () => void;
+  previous: () => void;
+  jumpTo: (index: number) => void;
+  reset: () => void;
+}
+
+export interface RotatingTextProps
+  extends Omit<
+    React.ComponentPropsWithoutRef<typeof motion.span>,
+    "children" | "transition" | "initial" | "animate" | "exit"
+  > {
+  texts: string[];
+  transition?: Transition;
+  initial?: boolean | Target | VariantLabels;
+  animate?: boolean | VariantLabels | AnimationControls | TargetAndTransition;
+  exit?: Target | VariantLabels;
+  animatePresenceMode?: "sync" | "wait";
+  animatePresenceInitial?: boolean;
+  rotationInterval?: number;
+  staggerDuration?: number;
+  staggerFrom?: "first" | "last" | "center" | "random" | number;
+  loop?: boolean;
+  auto?: boolean;
+  splitBy?: string;
+  onNext?: (index: number) => void;
+  mainClassName?: string;
+  splitLevelClassName?: string;
+  elementLevelClassName?: string;
+}
+
+export const RotatingText = forwardRef<RotatingTextRef, RotatingTextProps>(
+  (
+    {
+      texts,
+      transition = { type: "spring", damping: 25, stiffness: 300 },
+      initial = { y: "100%", opacity: 0 },
+      animate = { y: 0, opacity: 1 },
+      exit = { y: "-120%", opacity: 0 },
+      animatePresenceMode = "wait",
+      animatePresenceInitial = false,
+      rotationInterval = 2000,
+      staggerDuration = 0,
+      staggerFrom = "first",
+      loop = true,
+      auto = true,
+      splitBy = "characters",
+      onNext,
+      mainClassName,
+      splitLevelClassName,
+      elementLevelClassName,
+      ...rest
+    },
+    ref,
+  ) => {
+    const [currentTextIndex, setCurrentTextIndex] = useState<number>(0);
+
+    const splitIntoCharacters = (text: string): string[] => {
+      if (typeof Intl !== "undefined" && Intl.Segmenter) {
+        const segmenter = new Intl.Segmenter("en", { granularity: "grapheme" });
+        return Array.from(
+          segmenter.segment(text),
+          (segment) => segment.segment,
+        );
+      }
+      return Array.from(text);
+    };
+
+    const elements = useMemo(() => {
+      const currentText: string = texts[currentTextIndex];
+      if (splitBy === "characters") {
+        const words = currentText.split(" ");
+        return words.map((word, i) => ({
+          characters: splitIntoCharacters(word),
+          needsSpace: i !== words.length - 1,
+        }));
+      }
+      if (splitBy === "words") {
+        return currentText.split(" ").map((word, i, arr) => ({
+          characters: [word],
+          needsSpace: i !== arr.length - 1,
+        }));
+      }
+      if (splitBy === "lines") {
+        return currentText.split("\n").map((line, i, arr) => ({
+          characters: [line],
+          needsSpace: i !== arr.length - 1,
+        }));
+      }
+
+      return currentText.split(splitBy).map((part, i, arr) => ({
+        characters: [part],
+        needsSpace: i !== arr.length - 1,
+      }));
+    }, [texts, currentTextIndex, splitBy]);
+
+    const getStaggerDelay = useCallback(
+      (index: number, totalChars: number): number => {
+        const total = totalChars;
+        if (staggerFrom === "first") return index * staggerDuration;
+        if (staggerFrom === "last")
+          return (total - 1 - index) * staggerDuration;
+        if (staggerFrom === "center") {
+          const center = Math.floor(total / 2);
+          return Math.abs(center - index) * staggerDuration;
+        }
+        if (staggerFrom === "random") {
+          const randomIndex = Math.floor(Math.random() * total);
+          return Math.abs(randomIndex - index) * staggerDuration;
+        }
+        return Math.abs((staggerFrom as number) - index) * staggerDuration;
+      },
+      [staggerFrom, staggerDuration],
+    );
+
+    const handleIndexChange = useCallback(
+      (newIndex: number) => {
+        setCurrentTextIndex(newIndex);
+        if (onNext) onNext(newIndex);
+      },
+      [onNext],
+    );
+
+    const next = useCallback(() => {
+      const nextIndex =
+        currentTextIndex === texts.length - 1
+          ? loop
+            ? 0
+            : currentTextIndex
+          : currentTextIndex + 1;
+      if (nextIndex !== currentTextIndex) {
+        handleIndexChange(nextIndex);
+      }
+    }, [currentTextIndex, texts.length, loop, handleIndexChange]);
+
+    const previous = useCallback(() => {
+      const prevIndex =
+        currentTextIndex === 0
+          ? loop
+            ? texts.length - 1
+            : currentTextIndex
+          : currentTextIndex - 1;
+      if (prevIndex !== currentTextIndex) {
+        handleIndexChange(prevIndex);
+      }
+    }, [currentTextIndex, texts.length, loop, handleIndexChange]);
+
+    const jumpTo = useCallback(
+      (index: number) => {
+        const validIndex = Math.max(0, Math.min(index, texts.length - 1));
+        if (validIndex !== currentTextIndex) {
+          handleIndexChange(validIndex);
+        }
+      },
+      [texts.length, currentTextIndex, handleIndexChange],
+    );
+
+    const reset = useCallback(() => {
+      if (currentTextIndex !== 0) {
+        handleIndexChange(0);
+      }
+    }, [currentTextIndex, handleIndexChange]);
+
+    useImperativeHandle(
+      ref,
+      () => ({
+        next,
+        previous,
+        jumpTo,
+        reset,
+      }),
+      [next, previous, jumpTo, reset],
+    );
+
+    useEffect(() => {
+      if (!auto) return;
+      const intervalId = setInterval(next, rotationInterval);
+      return () => clearInterval(intervalId);
+    }, [next, rotationInterval, auto]);
+
+    return (
+      <motion.span
+        className={cn(
+          "relative flex flex-wrap whitespace-pre-wrap",
+          mainClassName,
+        )}
+        {...rest}
+        layout
+        transition={transition}
+      >
+        <span className="sr-only">{texts[currentTextIndex]}</span>
+        <AnimatePresence
+          mode={animatePresenceMode}
+          initial={animatePresenceInitial}
+        >
+          <motion.div
+            key={currentTextIndex}
+            className={cn(
+              splitBy === "lines"
+                ? "flex w-full flex-col"
+                : "relative flex flex-wrap whitespace-pre-wrap",
+            )}
+            layout
+            aria-hidden="true"
+          >
+            {elements.map((wordObj, wordIndex, array) => {
+              const previousCharsCount = array
+                .slice(0, wordIndex)
+                .reduce((sum, word) => sum + word.characters.length, 0);
+              return (
+                <span
+                  key={wordIndex}
+                  className={cn("inline-flex", splitLevelClassName)}
+                >
+                  {wordObj.characters.map((char, charIndex) => (
+                    <motion.span
+                      key={charIndex}
+                      initial={initial}
+                      animate={animate}
+                      exit={exit}
+                      transition={{
+                        ...transition,
+                        delay: getStaggerDelay(
+                          previousCharsCount + charIndex,
+                          array.reduce(
+                            (sum, word) => sum + word.characters.length,
+                            0,
+                          ),
+                        ),
+                      }}
+                      className={cn("inline-block", elementLevelClassName)}
+                    >
+                      {char}
+                    </motion.span>
+                  ))}
+                  {wordObj.needsSpace && (
+                    <span className="whitespace-pre"> </span>
+                  )}
+                </span>
+              );
+            })}
+          </motion.div>
+        </AnimatePresence>
+      </motion.span>
+    );
+  },
+);
+
+RotatingText.displayName = "RotatingText";

apps/next/src/components/supports.tsx

@@ -0,0 +1,27 @@
+"use client";
+import { RotatingText } from "@/components/reactbits/rotating-text";
+
+const supports = [
+  "Next.js",
+  "Node.js",
+  "Hono",
+  "Express.js",
+  "Deno",
+  "Nest.js",
+  "Waku",
+];
+
+export const Supports = () => {
+  return (
+    <RotatingText
+      texts={supports}
+      mainClassName="inline-flex bg-transparent overflow-hidden justify-center"
+      initial={{ y: "100%" }}
+      animate={{ y: 0 }}
+      exit={{ y: "-120%" }}
+      staggerDuration={0.025}
+      transition={{ type: "spring", damping: 30, stiffness: 400 }}
+      rotationInterval={2000}
+    />
+  );
+};

apps/next/src/components/text-effect.tsx

@@ -1,28 +0,0 @@
-"use client";
-import { useEffect, useState } from "react";
-import ReactTextTransition from "react-text-transition";
-
-const supports = [
-  "Next.js",
-  "Node.js",
-  "Hono",
-  "Express.js",
-  "Deno",
-  "Nest.js",
-  "Waku",
-];
-
-export const TextEffect = () => {
-  const [counter, setCounter] = useState(0);
-  useEffect(() => {
-    const id = setInterval(() => {
-      setCounter(
-        (Math.floor(Math.random() * supports.length) + 1) % supports.length,
-      );
-    }, 4000);
-    return () => {
-      clearInterval(id);
-    };
-  }, []);
-  return <ReactTextTransition inline>{supports[counter]}</ReactTextTransition>;
-};

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

@@ -21,7 +21,7 @@ const DialogOverlay = React.forwardRef<
   <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",
+      "data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 fixed inset-0 z-50 bg-black/80",
       className,
     )}
     {...props}
@@ -38,13 +38,13 @@ const DialogContent = React.forwardRef<
     <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",
+        "bg-background 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%] fixed left-[50%] top-[50%] z-50 grid w-full max-w-lg translate-x-[-50%] translate-y-[-50%] gap-4 border p-6 shadow-lg duration-200 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">
+      <DialogPrimitive.Close className="ring-offset-background focus:ring-ring data-[state=open]:bg-accent data-[state=open]:text-muted-foreground absolute right-4 top-4 rounded-sm opacity-70 transition-opacity hover:opacity-100 focus:outline-none focus:ring-2 focus:ring-offset-2 disabled:pointer-events-none">
         <Cross2Icon className="h-4 w-4" />
         <span className="sr-only">Close</span>
       </DialogPrimitive.Close>
@@ -102,7 +102,7 @@ const DialogDescription = React.forwardRef<
 >(({ className, ...props }, ref) => (
   <DialogPrimitive.Description
     ref={ref}
-    className={cn("text-sm text-muted-foreground", className)}
+    className={cn("text-muted-foreground text-sm", className)}
     {...props}
   />
 ));

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

@@ -10,7 +10,7 @@ const Input = React.forwardRef<HTMLInputElement, InputProps>(
       <input
         type={type}
         className={cn(
-          "flex h-9 w-full rounded-md border border-input bg-transparent px-3 py-1 text-sm shadow-sm transition-colors file:border-0 file:bg-transparent file:text-sm file:font-medium file:text-foreground placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:cursor-not-allowed disabled:opacity-50",
+          "border-input file:text-foreground placeholder:text-muted-foreground focus-visible:ring-ring flex h-9 w-full rounded-md border bg-transparent px-3 py-1 text-sm shadow-sm transition-colors file:border-0 file:bg-transparent file:text-sm file:font-medium focus-visible:outline-none focus-visible:ring-1 disabled:cursor-not-allowed disabled:opacity-50",
           className,
         )}
         ref={ref}

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

@@ -6,7 +6,7 @@ function Skeleton({
 }: React.HTMLAttributes<HTMLDivElement>) {
   return (
     <div
-      className={cn("animate-pulse rounded-md bg-primary/10", className)}
+      className={cn("bg-primary/10 animate-pulse rounded-md", className)}
       {...props}
     />
   );

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

@@ -17,10 +17,10 @@ const Slider = React.forwardRef<
     )}
     {...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 className="bg-primary/20 relative h-1.5 w-full grow overflow-hidden rounded-full">
+      <SliderPrimitive.Range className="bg-primary absolute h-full" />
     </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.Thumb className="border-primary/50 bg-background focus-visible:ring-ring block h-4 w-4 rounded-full border shadow transition-colors focus-visible:outline-none focus-visible:ring-1 disabled:pointer-events-none disabled:opacity-50" />
   </SliderPrimitive.Root>
 ));
 Slider.displayName = SliderPrimitive.Root.displayName;

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

@@ -9,7 +9,7 @@ const Textarea = React.forwardRef<HTMLTextAreaElement, TextareaProps>(
     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",
+          "border-input placeholder:text-muted-foreground focus-visible:ring-ring flex min-h-[60px] w-full rounded-md border bg-transparent px-3 py-2 text-sm shadow-sm focus-visible:outline-none focus-visible:ring-1 disabled:cursor-not-allowed disabled:opacity-50",
           className,
         )}
         ref={ref}

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

@@ -20,7 +20,7 @@ const TooltipContent = React.forwardRef<
       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",
+        "bg-primary 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 z-50 overflow-hidden rounded-md px-3 py-1.5 text-xs",
         className,
       )}
       {...props}

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

@@ -2,5 +2,5 @@
   "title": "LlamaCloud",
   "description": "The Cloud framework for LLM",
   "root": true,
-  "pages": ["---Guide---", "index", "api"]
+  "pages": ["---Guide---", "index", "..."]
 }

apps/next/src/content/docs/llamaindex/examples/other_llms.mdx

@@ -7,7 +7,7 @@ import CodeSource from "!raw-loader!../../../../../../../examples/mistral";
 
 By default LlamaIndex.TS uses OpenAI's LLMs and embedding models, but we support [lots of other LLMs](../modules/llms) including models from Mistral (Mistral, Mixtral), Anthropic (Claude) and Google (Gemini).
 
-If you don't want to use an API at all you can [run a local model](../../examples/local_llm).
+If you don't want to use an API at all you can [run a local model](./local_llm).
 
 This example runs you through the process of setting up a Mistral model:
 

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

@@ -106,21 +106,38 @@ Some modules uses `Web Stream` API like `ReadableStream` and `WritableStream`, y
 }
 ```
 
-```ts twoslash
-import { OpenAIAgent } from '@llamaindex/openai'
+```typescript
+import { agent, tool } from 'llamaindex'
+import { openai } from "@llamaindex/openai";
 
-const agent = new OpenAIAgent({
-  tools: []
-})
+Settings.llm = openai({
+  model: "gpt-4o-mini",
+});
 
-const response = await agent.chat({
-  message: 'Hello, how are you?',
-  stream: true
-})
-for await (const _ of response) {
-                      //^?
-  // ...
+const addTool = tool({
+  name: "add", 
+  description: "Adds two numbers",
+  parameters: z.object({x: z.number(), y: z.number()}),
+  execute: ({ x, y }) => x + y,
+});
+
+const myAgent = agent({
+  tools: [addTool],
+});
+
+// Chat with the agent
+const context = myAgent.run("Hello, how are you?");
+
+for await (const event of context) {
+  if (event instanceof AgentStream) {
+    for (const chunk of event.data.delta) {
+      process.stdout.write(chunk); // stream response
+    }
+  } else {
+    console.log(event); // other events
+  }
 }
+
 ```
 
 ## Run TypeScript Script in Node.js

apps/next/src/content/docs/llamaindex/guide/agents/2_create_agent.mdx

@@ -25,15 +25,22 @@ npx tsx example.ts
 First we'll need to pull in our dependencies. These are:
 
 - The OpenAI class to use the OpenAI LLM
-- FunctionTool to provide tools to our agent
-- OpenAIAgent to create the agent itself
+- tool to provide tools to our agent
+- agent to create the single agent
 - Settings to define some global settings for the library
 - Dotenv to load our API key from the .env file
+- Zod to define the schema for our tool
 
 ```javascript
-import { FunctionTool, Settings } from "llamaindex";
-import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
 import "dotenv/config";
+import {
+  agent,
+  AgentStream,
+  tool,
+  openai,
+  Settings,
+} from "llamaindex";
+import { z } from "zod";
 ```
 
 ### Initialize your LLM
@@ -41,25 +48,12 @@ import "dotenv/config";
 We need to tell our OpenAI class where its API key is, and which of OpenAI's models to use. We'll be using `gpt-4o`, which is capable while still being pretty cheap. This is a global setting, so anywhere an LLM is needed will use the same model.
 
 ```javascript
-Settings.llm = new OpenAI({
+Settings.llm = openai({
   apiKey: process.env.OPENAI_API_KEY,
   model: "gpt-4o",
 });
 ```
 
-### Turn on logging
-
-We want to see what our agent is up to, so we're going to hook into some events that the library generates and print them out. There are several events possible, but we'll specifically tune in to `llm-tool-call` (when a tool is called) and `llm-tool-result` (when it responds).
-
-```javascript
-Settings.callbackManager.on("llm-tool-call", (event) => {
-  console.log(event.detail);
-});
-Settings.callbackManager.on("llm-tool-result", (event) => {
-  console.log(event.detail);
-});
-```
-
 ### Create a function
 
 We're going to create a very simple function that adds two numbers together. This will be the tool we ask our agent to use.
@@ -74,7 +68,7 @@ Note that we're passing in an object with two named parameters, `a` and `b`. Thi
 
 ### Turn the function into a tool for the agent
 
-This is the most complicated part of creating an agent. We need to define a `FunctionTool`. We have to pass in:
+This is the most complicated part of creating an agent. We need to define a `tool`. We have to pass in:
 
 - The function itself (`sumNumbers`)
 - A name for the function, which the LLM will use to call it
@@ -83,30 +77,25 @@ This is the most complicated part of creating an agent. We need to define a `Fun
 - You can see [more examples of function schemas](https://cookbook.openai.com/examples/how_to_call_functions_with_chat_models).
 
 ```javascript
-const tool = FunctionTool.from(sumNumbers, {
+const addTool = tool({
   name: "sumNumbers",
   description: "Use this function to sum two numbers",
-  parameters: {
-    type: "object",
-    properties: {
-      a: {
-        type: "number",
-        description: "First number to sum",
-      },
-      b: {
-        type: "number",
-        description: "Second number to sum",
-      },
-    },
-    required: ["a", "b"],
-  },
+  parameters: z.object({
+    a: z.number({
+      description: "First number to sum",
+    }),
+    b: z.number({
+      description: "Second number to sum",
+    }),
+  }),
+  execute: sumNumbers,
 });
 ```
 
 We then wrap up the tools into an array. We could provide lots of tools this way, but for this example we're just using the one.
 
 ```javascript
-const tools = [tool];
+const tools = [addTool];
 ```
 
 ### Create the agent
@@ -114,7 +103,7 @@ const tools = [tool];
 With your LLM already set up and your tools defined, creating an agent is simple:
 
 ```javascript
-const agent = new OpenAIAgent({ tools });
+const myAgent = agent({ tools });
 ```
 
 ### Ask the agent a question
@@ -122,61 +111,109 @@ const agent = new OpenAIAgent({ tools });
 We can use the `chat` interface to ask our agent a question, and it will use the tools we've defined to find an answer.
 
 ```javascript
-let response = await agent.chat({
-  message: "Add 101 and 303",
-});
+const context = myAgent.run("Sum 101 and 303");
+const result = await context;
+console.log(result.data);
+```
+You will see the following output:
 
-console.log(response);
+**_Output_**
+
+```
+{ result: 'The sum of 101 and 303 is 404.' }
+```
+
+To stream the response, you can use the `AgentStream` event which provides chunks of the response as they become available. This allows you to display the response incrementally rather than waiting for the full response:
+
+```javascript
+const context = myAgent.run("Add 101 and 303");
+for await (const event of context) {
+  if (event instanceof AgentStream) {
+    process.stdout.write(event.data.delta);
+  }
+}
+```
+
+**_Streaming Output_**
+
+```
+The sum of 101 and 303 is 404.
+```
+
+### Logging workflow events
+
+To log the workflow events, you can check the event type and log the event data.
+
+```javascript
+const context = myAgent.run("Sum 202 and 404");
+for await (const event of context) {
+  if (event instanceof AgentStream) {
+    // Stream the response
+    for (const chunk of event.data.delta) {
+      process.stdout.write(chunk);
+    }
+  } else {
+    // Log other events
+    console.log("\nWorkflow event:", JSON.stringify(event, null, 2));
+  }
+}
 ```
 
 Let's see what running this looks like using `npx tsx agent.ts`
 
 **_Output_**
 
-```javascript
-{
-  toolCall: {
-    id: 'call_ze6A8C3mOUBG4zmXO8Z4CPB5',
-    name: 'sumNumbers',
-    input: { a: 101, b: 303 }
+```
+Workflow event: {
+  "data": {
+    "userInput": "Sum 202 and 404"
   },
-  toolResult: {
-    tool: FunctionTool { _fn: [Function: sumNumbers], _metadata: [Object] },
-    input: { a: 101, b: 303 },
-    output: '404',
-    isError: false
-  }
+  "displayName": "StartEvent"
 }
+
+Workflow event: {
+  "data": {
+    "input": [
+      {
+        "role": "user",
+        "content": "Sum 202 and 404"
+      }
+    ],
+    "currentAgentName": "Agent"
+  },
+  "displayName": "AgentInput"
+}
+
+Workflow event: {
+  "data": {
+    "input": [
+      {
+        "role": "system",
+        "content": "You are a helpful assistant. Use the provided tools to answer questions."
+      },
+      {
+        "role": "user",
+        "content": "Sum 202 and 404"
+      }
+    ],
+    "currentAgentName": "Agent"
+  },
+  "displayName": "AgentSetup"
+}
+
+....
+
 ```
 
-```javascript
-{
-  response: {
-    raw: {
-      id: 'chatcmpl-9KwauZku3QOvH78MNvxJs81mDvQYK',
-      object: 'chat.completion',
-      created: 1714778824,
-      model: 'gpt-4-turbo-2024-04-09',
-      choices: [Array],
-      usage: [Object],
-      system_fingerprint: 'fp_ea6eb70039'
-    },
-    message: {
-      content: 'The sum of 101 and 303 is 404.',
-      role: 'assistant',
-      options: {}
-    }
-  },
-  sources: [Getter]
-}
-```
+We're seeing several workflow events being logged:
 
-We're seeing two pieces of output here. The first is our callback firing when the tool is called. You can see in `toolResult` that the LLM has correctly passed `101` and `303` to our `sumNumbers` function, which adds them up and returns `404`.
+1. `AgentToolCall` - Shows the agent preparing to call our tool with the numbers 202 and 404
+2. `AgentToolCallResult` - Shows the result of calling the tool, which returned "606"
+3. `AgentInput` - Shows the original user input
+4. `AgentOutput` - Shows the agent's response
 
-The second piece of output is the response from the LLM itself, where the `message.content` key is giving us the answer.
+Great! We've built an agent that can understand requests and use tools to fulfill them. Next you can:
 
-Great! We've built an agent with tool use! Next you can:
-
-- [See the full code](https://github.com/run-llama/ts-agents/blob/main/1_agent/agent.ts)
+- [See the full code](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/agentworkflow/blog-writer.ts)
 - [Switch to a local LLM](3_local_model)
 - Move on to [add Retrieval-Augmented Generation to your agent](4_agentic_rag)

apps/next/src/content/docs/llamaindex/guide/agents/3_local_model.mdx

@@ -23,70 +23,27 @@ The first time you run it will also automatically download and install the model
 There are two changes you need to make to the code we already wrote in `1_agent` to get Mixtral 8x7b to work. First, you need to switch to that model. Replace the call to `Settings.llm` with this:
 
 ```javascript
-Settings.llm = new Ollama({
+Settings.llm = ollama({
   model: "mixtral:8x7b",
 });
 ```
 
-### Swap to a ReActAgent
+### Run local agent
 
-In our original code we used a specific OpenAIAgent, so we'll need to switch to a more generic agent pattern, the ReAct pattern. This is simple: change the `const agent` line in your code to read
+You can also create local agent by importing `agent` from `llamaindex`.
 
 ```javascript
-const agent = new ReActAgent({ tools });
+import { agent } from "llamaindex";
+
+const workflow = agent({
+  tools: [getWeatherTool],
+});
+
+const workflowContext = workflow.run(
+  "What's the weather like in San Francisco?",
+);
 ```
 
-(You will also need to bring in `Ollama` and `ReActAgent` in your imports)
-
-### Run your totally local agent
-
-Because your embeddings were already local, your agent can now run entirely locally without making any API calls.
-
-```bash
-node agent.mjs
-```
-
-Note that your model will probably run a lot slower than OpenAI, so be prepared to wait a while!
-
-**_Output_**
-
-```javascript
-{
-  response: {
-    message: {
-      role: 'assistant',
-      content: ' Thought: I need to use a tool to add the numbers 101 and 303.\n' +
-        'Action: sumNumbers\n' +
-        'Action Input: {"a": 101, "b": 303}\n' +
-        '\n' +
-        'Observation: 404\n' +
-        '\n' +
-        'Thought: I can answer without using any more tools.\n' +
-        'Answer: The sum of 101 and 303 is 404.'
-    },
-    raw: {
-      model: 'mixtral:8x7b',
-      created_at: '2024-05-09T00:24:30.339473Z',
-      message: [Object],
-      done: true,
-      total_duration: 64678371209,
-      load_duration: 57394551334,
-      prompt_eval_count: 475,
-      prompt_eval_duration: 4163981000,
-      eval_count: 94,
-      eval_duration: 3116692000
-    }
-  },
-  sources: [Getter]
-}
-```
-
-Tada! You can see all of this in the folder `1a_mixtral`.
-
-### Extending to other examples
-
-You can use a ReActAgent instead of an OpenAIAgent in any of the further examples below, but keep in mind that GPT-4 is a lot more capable than Mixtral 8x7b, so you may see more errors or failures in reasoning if you are using an entirely local setup.
-
 ### Next steps
 
 Now you've got a local agent, you can [add Retrieval-Augmented Generation to your agent](4_agentic_rag).

apps/next/src/content/docs/llamaindex/guide/agents/4_agentic_rag.mdx

@@ -37,7 +37,7 @@ import { Tab, Tabs } from "fumadocs-ui/components/tabs";
 We'll be bringing in `SimpleDirectoryReader`, `HuggingFaceEmbedding`, `VectorStoreIndex`, and `QueryEngineTool`, `OpenAIContextAwareAgent` from LlamaIndex.TS, as well as the dependencies we previously used.
 
 ```javascript
-import { FunctionTool, QueryEngineTool, Settings, VectorStoreIndex } from "llamaindex";
+import { QueryEngineTool, Settings, VectorStoreIndex } from "llamaindex";
 import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
 import { HuggingFaceEmbedding } from "@llamaindex/huggingface";
 import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
@@ -115,10 +115,8 @@ The total budget for the City and County of San Francisco for the fiscal year 20
 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,
+  index.queryTool({
     metadata: {
       name: "san_francisco_budget_tool",
       description: `This tool can answer detailed questions about the individual components of the budget of San Francisco in 2023-2024.`,
@@ -127,11 +125,9 @@ const tools = [
 ];
 
 // Create an agent using the tools array
-const agent = new OpenAIAgent({ tools });
+const myAgent = agent({ tools });
 
-let toolResponse = await agent.chat({
-  message: "What's the budget of San Francisco in 2023-2024?",
-});
+let toolResponse = await myAgent.run("What's the budget of San Francisco in 2023-2024?");
 
 console.log(toolResponse);
 ```

apps/next/src/content/docs/llamaindex/guide/agents/5_rag_and_tools.mdx

@@ -2,58 +2,67 @@
 title: A RAG agent that does math
 ---
 
-In [our third iteration of the agent](https://github.com/run-llama/ts-agents/blob/main/3_rag_and_tools/agent.ts) we've combined the two previous agents, so we've defined both `sumNumbers` and a `QueryEngineTool` and created an array of two tools:
+In [our third iteration of the agent](https://github.com/run-llama/ts-agents/blob/main/3_rag_and_tools/agent.ts) we've combined the two previous agents, so we've defined both `sumNumbers` and a `QueryEngineTool` and created an array of two tools. The tools support both Zod and JSON Schema for parameter definition:
 
 ```javascript
 // define the query engine as a tool
 const tools = [
-  new QueryEngineTool({
-    queryEngine: queryEngine,
+  index.queryTool({
     metadata: {
       name: "san_francisco_budget_tool",
       description: `This tool can answer detailed questions about the individual components of the budget of San Francisco in 2023-2024.`,
     },
   }),
-  FunctionTool.from(sumNumbers, {
+  tool({
     name: "sumNumbers",
     description: "Use this function to sum two numbers",
-    parameters: {
-      type: "object",
-      properties: {
-        a: {
-          type: "number",
-          description: "First number to sum",
-        },
-        b: {
-          type: "number",
-          description: "Second number to sum",
-        },
-      },
-      required: ["a", "b"],
-    },
+    parameters: z.object({
+      a: z.number({
+        description: "First number to sum",
+      }),
+      b: z.number({
+        description: "Second number to sum",
+      }),
+    }),
+    execute: ({ a, b }) => `${a + b}`,
   }),
 ];
 ```
 
+You can also use JSON Schema to define the tool parameters as an alternative to Zod. 
+
+```javascript
+tool(sumNumbers, {
+  name: "sumNumbers",
+  description: "Use this function to sum two numbers",
+  parameters: {
+    type: "object",
+    properties: {
+      a: {
+        type: "number",
+        description: "First number to sum",
+      },
+      b: {
+        type: "number",
+        description: "Second number to sum",
+      },
+    },
+    required: ["a", "b"],
+  },
+}),
+```
+
+
 These tool descriptions are identical to the ones we previously defined. Now let's ask it 3 questions in a row:
 
 ```javascript
-let response = await agent.chat({
-  message:
-    "What's the budget of San Francisco for community health in 2023-24?",
-});
+let response = await agent.run("What's the budget of San Francisco for community health in 2023-24?");
 console.log(response);
 
-let response2 = await agent.chat({
-  message:
-    "What's the budget of San Francisco for public protection in 2023-24?",
-});
+let response2 = await agent.run("What's the budget of San Francisco for public protection in 2023-24?");
 console.log(response2);
 
-let response3 = await agent.chat({
-  message:
-    "What's the combined budget of San Francisco for community health and public protection in 2023-24?",
-});
+let response3 = await agent.run("What's the combined budget of San Francisco for community health and public protection in 2023-24?");
 console.log(response3);
 ```
 

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

@@ -3,8 +3,6 @@ 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.

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

@@ -0,0 +1,22 @@
+---
+title: Install @llamaindex/chat
+description: Chat interface for your LlamaIndexTS application
+---
+
+## Quick Start
+
+You can quickly add a chatbot to your project by using Shadcn CLI command:
+
+```sh
+npx shadcn@latest add https://ui.llamaindex.ai/r/chat.json
+```
+
+## Manual Installation
+
+To install the package, run the following command in your project directory:
+
+```sh
+npm install @llamaindex/chat-ui
+```
+
+For more information, check out the [github.comrun-llama/chat-ui](https://github.com/run-llama/chat-ui)

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

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

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

@@ -3,8 +3,6 @@ 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).
 

apps/next/src/content/docs/llamaindex/modules/agent_workflow.mdx

@@ -2,29 +2,8 @@
 title: Agent Workflow
 ---
 
-import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
-import CodeSource from "!raw-loader!../../../../../../../examples/agentworkflow/blog_writer.ts";
-import { Tab, Tabs } from "fumadocs-ui/components/tabs";
 
-`AgentWorkflow` is a powerful system that enables you to create and orchestrate one or multiple agents with tools to perform specific tasks. It's built on top of the base `Workflow` system and provides a streamlined interface for agent interactions.
-
-## Installation
-
-You'll need to install the `@llamaindex/workflow` package:
-
-<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>
+Agent Workflows are a powerful system that enables you to create and orchestrate one or multiple agents with tools to perform specific tasks. It's built on top of the base `Workflow` system and provides a streamlined interface for agent interactions.
 
 ## Usage
 
@@ -33,11 +12,11 @@ You'll need to install the `@llamaindex/workflow` package:
 The simplest use case is creating a single agent with specific tools. Here's an example of creating an assistant that tells jokes:
 
 ```typescript
-import { AgentWorkflow, FunctionTool } from "llamaindex";
-import { OpenAI } from "@llamaindex/openai";
+import { agent, tool } from "llamaindex";
+import { openai } from "@llamaindex/openai";
 
 // Define a joke-telling tool
-const jokeTool = FunctionTool.from(
+const jokeTool = tool(
   () => "Baby Llama is called cria",
   {
     name: "joke",
@@ -45,22 +24,20 @@ const jokeTool = FunctionTool.from(
   }
 );
 
-// Create an agent workflow with the tool
-const workflow = AgentWorkflow.fromTools({
+// Create an single agent workflow with the tool
+const jokeAgent = agent({
   tools: [jokeTool],
-  llm: new OpenAI({
-    model: "gpt-4o-mini",
-  }),
+  llm: openai({ model: "gpt-4o-mini" }),
 });
 
 // Run the workflow
-const result = await workflow.run("Tell me something funny");
+const result = await jokeAgent.run("Tell me something funny");
 console.log(result); // Baby Llama is called cria
 ```
 
 ### Event Streaming
 
-`AgentWorkflow` provides a unified interface for event streaming, making it easy to track and respond to different events during execution:
+Agent Workflows provide a unified interface for event streaming, making it easy to track and respond to different events during execution:
 
 ```typescript
 import { AgentToolCall, AgentStream } from "llamaindex";
@@ -81,7 +58,7 @@ for await (const event of context) {
 
 ### Multi-Agent Workflow
 
-`AgentWorkflow` can orchestrate multiple agents, enabling complex interactions and task handoffs. Each agent in a multi-agent workflow requires:
+An Agent Workflow can orchestrate multiple agents, enabling complex interactions and task handoffs. Each agent in a multi-agent workflow requires:
 
 - `name`: Unique identifier for the agent
 - `description`: Purpose description used for task routing
@@ -91,46 +68,46 @@ for await (const event of context) {
 Here's an example of a multi-agent system that combines joke-telling and weather information:
 
 ```typescript
-import { AgentWorkflow, FunctionAgent, FunctionTool } from "llamaindex";
-import { OpenAI } from "@llamaindex/openai";
+import { multiAgent, agent, tool } from "llamaindex";
+import { openai } from "@llamaindex/openai";
 import { z } from "zod";
 
 // Create a weather agent
-const weatherAgent = new FunctionAgent({
+const weatherAgent = agent({
   name: "WeatherAgent",
   description: "Provides weather information for any city",
   tools: [
-    FunctionTool.from(
-      ({ city }: { city: string }) => `The weather in ${city} is sunny`,
+    tool(
       {
         name: "fetchWeather",
         description: "Get weather information for a city",
         parameters: z.object({
           city: z.string(),
         }),
+        execute: ({ city }) => `The weather in ${city} is sunny`,
       }
     ),
   ],
-  llm: new OpenAI({ model: "gpt-4o-mini" }),
+  llm: openai({ model: "gpt-4o-mini" }),
 });
 
 // Create a joke-telling agent
-const jokeAgent = new FunctionAgent({
+const jokeAgent = agent({
   name: "JokeAgent",
   description: "Tells jokes and funny stories",
   tools: [jokeTool], // Using the joke tool defined earlier
-  llm: new OpenAI({ model: "gpt-4o-mini" }),
+  llm: openai({ model: "gpt-4o-mini" }),
   canHandoffTo: [weatherAgent], // Can hand off to the weather agent
 });
 
 // Create the multi-agent workflow
-const workflow = new AgentWorkflow({
+const agents = multiAgent({
   agents: [jokeAgent, weatherAgent],
   rootAgent: jokeAgent, // Start with the joke agent
 });
 
 // Run the workflow
-const result = await workflow.run(
+const result = await agents.run(
   "Give me a morning greeting with a joke and the weather in San Francisco"
 );
 ```

apps/next/src/content/docs/llamaindex/modules/llms/available_llms/bedrock.mdx

@@ -127,26 +127,21 @@ async function main() {
 ```ts
 import { BEDROCK_MODELS, Bedrock } from "@llamaindex/community";
 import { FunctionTool, LLMAgent } from "llamaindex";
+import { z } from "zod";
 
 const sumNumbers = FunctionTool.from(
   ({ a, b }: { a: number; b: number }) => `${a + b}`,
   {
     name: "sumNumbers",
     description: "Use this function to sum two numbers",
-    parameters: {
-      type: "object",
-      properties: {
-        a: {
-          type: "number",
-          description: "The first number",
-        },
-        b: {
-          type: "number",
-          description: "The second number",
-        },
-      },
-      required: ["a", "b"],
-    },
+    parameters: z.object({
+      a: z.number({
+        description: "The first number",
+      }),
+      b: z.number({
+        description: "The second number",
+      }),
+    }),
   },
 );
 
@@ -155,20 +150,14 @@ const divideNumbers = FunctionTool.from(
   {
     name: "divideNumbers",
     description: "Use this function to divide two numbers",
-    parameters: {
-      type: "object",
-      properties: {
-        a: {
-          type: "number",
-          description: "The dividend a to divide",
-        },
-        b: {
-          type: "number",
-          description: "The divisor b to divide by",
-        },
-      },
-      required: ["a", "b"],
-    },
+    parameters: z.object({
+      a: z.number({
+        description: "The dividend a to divide",
+      }),
+      b: z.number({
+        description: "The divisor b to divide by",
+      }),
+    }),
   },
 );
 

apps/next/src/content/docs/llamaindex/modules/llms/available_llms/gemini.mdx

@@ -31,6 +31,20 @@ Settings.llm = new Gemini({
 });
 ```
 
+## Usage with Proxy
+
+```ts
+import { Gemini, GEMINI_MODEL } from "@llamaindex/google";
+import { Settings } from "llamaindex";
+
+Settings.llm = new Gemini({
+  model: GEMINI_MODEL.GEMINI_PRO,
+  requestOptions: {
+    baseUrl: <YOUR_PROXY_URL>   // optional, but useful for custom endpoints
+  }
+});
+```
+
 ### Usage with Vertex AI
 
 To use Gemini via Vertex AI you can use `GeminiVertexSession`.

apps/next/src/content/docs/llamaindex/modules/llms/available_llms/openai.mdx

@@ -34,6 +34,18 @@ You can setup the apiKey on the environment variables, like:
 export OPENAI_API_KEY="<YOUR_API_KEY>"
 ```
 
+You can optionally set a custom base URL, like:
+
+```bash
+export OPENAI_BASE_URL="https://api.scaleway.ai/v1"
+```
+
+or
+
+```ts
+Settings.llm = new OpenAI({ model: "gpt-3.5-turbo", temperature: 0, apiKey: <YOUR_API_KEY>, baseURL: "https://api.scaleway.ai/v1" });
+```
+
 ## Load and index documents
 
 For this example, we will use a single document. In a real-world scenario, you would have multiple documents to index.

apps/next/src/content/docs/llamaindex/modules/llms/available_llms/perplexity.mdx

@@ -0,0 +1,116 @@
+---
+title: Perplexity LLM
+---
+## Usage
+
+
+```ts
+import { Settings } from "llamaindex";
+import { perplexity } from "@llamaindex/perplexity";
+Settings.llm = perplexity({
+apiKey: "<YOUR_API_KEY>",
+model: "sonar", // or available models 
+});
+```
+
+## Example
+
+```ts
+import { perplexity } from "@llamaindex/perplexity";
+
+const perplexityLlm = perplexity({
+  apiKey: "<YOUR_API_KEY>",
+  model: "sonar", // or avaiable models
+});
+
+async function main() {
+  const response = await perplexityLlm.chat({
+    messages: [
+      {
+        role: "system",
+        content: "You are an AI assistant",
+      },
+      {
+        role: "user",
+        content: "Tell me about San Francisco",
+      },
+    ],
+    stream: false,
+  });
+  console.log(response);
+
+  const stream = await perplexityLlm.chat({
+    messages: [
+      {
+        role: "system",
+        content: "You are a creative AI assistant that tells engaging stories",
+      },
+      {
+        role: "user",
+        content: "Tell me a short story",
+      },
+    ],
+    stream: true,
+  });
+
+  console.log("\nStreaming response:");
+  for await (const chunk of stream) {
+    process.stdout.write(chunk.delta);
+  }
+}
+```
+
+## Full Example
+
+```ts
+import { perplexity } from "@llamaindex/perplexity";
+import { Document, Settings, VectorStoreIndex } from "llamaindex";
+
+// Use the perplexity LLM
+Settings.llm = perplexity({ model: "sonar", apiKey: "<YOUR_API_KEY>" });
+
+async function main() {
+  const document = new Document({ text: essay, id_: "essay" });
+
+  // Load and index documents
+  const index = await VectorStoreIndex.fromDocuments([document]);
+
+  // get retriever
+  const retriever = index.asRetriever();
+
+  // Create a query engine
+  const queryEngine = index.asQueryEngine({
+    retriever,
+  });
+
+  const query = "What is the meaning of life?";
+
+  // Query
+  const response = await queryEngine.query({
+    query,
+  });
+
+  // Log the response
+  console.log(response.response);
+}
+```
+
+## Available Models
+
+The following models are available:
+
+- `sonar`: 128k context window
+- `sonar-pro`: 200k context window
+- `sonar-deep-research`: 128k context window
+- `sonar-reasoning`: 128k context window
+- `sonar-reasoning-pro`: 128k context window
+- `r1-1776`: 128k context window
+
+
+# Limitations
+
+Currently does not support function calling.
+
+## API Reference
+
+- [Perplexity](/docs/api/classes/Perplexity)

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

@@ -29,6 +29,8 @@ Note: calling the `bind` method will return a new `FunctionTool` instance, witho
 
 Example to pass a `userToken` as additional argument:
 ```ts
+import { agent, tool } from "llamaindex";
+
 // first arg is LLM input, second is bound arg
 const queryKnowledgeBase = async ({ question }, { userToken }) => {
   const response = await fetch(`https://knowledge-base.com?token=${userToken}&query=${question}`);
@@ -36,24 +38,19 @@ const queryKnowledgeBase = async ({ question }, { userToken }) => {
 };
 
 // define tool as usual
-const kbTool = FunctionTool.from(queryKnowledgeBase, {
+const kbTool = tool(queryKnowledgeBase, {
   name: 'queryKnowledgeBase',
   description: 'Query knowledge base',
-  parameters: {
-    type: 'object',
-    properties: {
-      question: {
-        type: 'string',
-        description: 'The user question',
-      },
-    },
-    required: ['question'],
-  },
+  parameters: z.object({
+    question: z.string({
+      description: 'The user question',
+    }),
+  }),
 });
 
 // create an agent
 const additionalArg = { userToken: 'abcd1234' };
-const kbAgent = new LLMAgent({
+const workflow = agent({
   tools: [kbTool.bind(additionalArg)],
   // llm, systemPrompt etc
 })

apps/next/src/content/docs/llamaindex/modules/workflows.mdx

@@ -119,7 +119,7 @@ Lastly, we run the workflow. The `.run()` method is async, so we use await here
 Optionally, you can choose to use a shared context between steps by specifying a context type when creating the workflow. Here's an example where multiple steps access a shared state:
 
 ```typescript
-import { HandlerContext } from "@llamaindex/workflow";
+import { HandlerContext } from "llamaindex";
 
 type MyContextData = {
   query: string;

apps/next/src/lib/source.ts

@@ -1,11 +1,10 @@
-import { docs, meta } from '../../.source';
-import { createMDXSource } from 'fumadocs-mdx';
+import { docs } from '@/.source';
 import { loader } from 'fumadocs-core/source';
 import { createOpenAPI } from "fumadocs-openapi/server";
 
 export const source = loader({
   baseUrl: '/docs',
-  source: createMDXSource(docs, meta),
+  source: docs.toFumadocsSource(),
 });
 
 export const openapi = createOpenAPI();

apps/next/tailwind.config.mjs

@@ -1,5 +1,3 @@
-import { createPreset } from "fumadocs-ui/tailwind-plugin";
-
 /** @type {import('tailwindcss').Config} */
 export default {
   darkMode: ["class"],
@@ -8,13 +6,7 @@ export default {
     "./src/app/**/*.{ts,tsx}",
     "./src/content/**/*.{md,mdx}",
     "./src/mdx-components.{ts,tsx}",
-    "./node_modules/fumadocs-ui/dist/**/*.js",
-    "./node_modules/fumadocs-openapi/dist/**/*.js",
-    "./node_modules/@llamaindex/chat-ui/**/*.{ts,tsx}",
   ],
-  presets: [createPreset()],
-  // eslint-disable-next-line @typescript-eslint/no-require-imports
-  plugins: [require("tailwindcss-animate")],
   theme: {
     extend: {
       borderRadius: {

apps/next/tsconfig.json

@@ -16,7 +16,8 @@
     "jsx": "preserve",
     "incremental": true,
     "paths": {
-      "@/*": ["./src/*"]
+      "@/*": ["./src/*"],
+      "@/.source": ["./.source/index.ts"]
     },
     "plugins": [
       {

apps/next/turbo.json

@@ -1,4 +1,5 @@
 {
+  "$schema": "https://turbo.build/schema.json",
   "extends": ["//"],
   "tasks": {
     "build": {
@@ -8,6 +9,11 @@
         "next-env.d.ts",
         "src/content/docs/cloud/api/**",
         "src/content/docs/api/**"
+      ],
+      "env": [
+        "LLAMA_CLOUD_API_KEY",
+        "LLAMA_CLOUD_PIPELINE_ID",
+        "OPENAI_API_KEY"
       ]
     },
     "dev": {

e2e/examples/cloudflare-hono/package.json

@@ -11,7 +11,7 @@
   },
   "devDependencies": {
     "@cloudflare/workers-types": "^4.20241112.0",
-    "typescript": "^5.7.2",
+    "typescript": "^5.7.3",
     "wrangler": "^3.89.0"
   },
   "dependencies": {

e2e/examples/cloudflare-worker-agent/CHANGELOG.md

@@ -1,5 +1,20 @@
 # @llamaindex/cloudflare-worker-agent-test
 
+## 0.0.145
+
+### Patch Changes
+
+- llamaindex@0.9.11
+
+## 0.0.144
+
+### Patch Changes
+
+- Updated dependencies [c1b5be5]
+- Updated dependencies [40ee761]
+- Updated dependencies [40ee761]
+  - llamaindex@0.9.10
+
 ## 0.0.143
 
 ### Patch Changes

e2e/examples/cloudflare-worker-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.143",
+  "version": "0.0.145",
   "type": "module",
   "private": true,
   "scripts": {
@@ -16,7 +16,7 @@
     "@cloudflare/workers-types": "^4.20241112.0",
     "@vitest/runner": "2.1.5",
     "@vitest/snapshot": "2.1.5",
-    "typescript": "^5.7.2",
+    "typescript": "^5.7.3",
     "vitest": "2.1.5",
     "wrangler": "^3.87.0"
   },

e2e/examples/llama-parse-browser/CHANGELOG.md

@@ -1,5 +1,11 @@
 # @llamaindex/llama-parse-browser-test
 
+## 0.0.54
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.9
+
 ## 0.0.53
 
 ### Patch Changes

e2e/examples/llama-parse-browser/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/llama-parse-browser-test",
   "private": true,
-  "version": "0.0.53",
+  "version": "0.0.54",
   "type": "module",
   "scripts": {
     "dev": "vite",
@@ -9,7 +9,7 @@
     "preview": "vite preview"
   },
   "devDependencies": {
-    "typescript": "^5.7.2",
+    "typescript": "^5.7.3",
     "vite": "^5.4.12",
     "vite-plugin-wasm": "^3.3.0"
   },

e2e/examples/nextjs-agent/CHANGELOG.md

@@ -1,5 +1,20 @@
 # @llamaindex/next-agent-test
 
+## 0.1.145
+
+### Patch Changes
+
+- llamaindex@0.9.11
+
+## 0.1.144
+
+### Patch Changes
+
+- Updated dependencies [c1b5be5]
+- Updated dependencies [40ee761]
+- Updated dependencies [40ee761]
+  - llamaindex@0.9.10
+
 ## 0.1.143
 
 ### Patch Changes

e2e/examples/nextjs-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-agent-test",
-  "version": "0.1.143",
+  "version": "0.1.145",
   "private": true,
   "scripts": {
     "dev": "next dev",
@@ -10,18 +10,16 @@
   "dependencies": {
     "ai": "^4.0.0",
     "llamaindex": "workspace:*",
-    "next": "15.1.7",
+    "next": "15.2.0",
     "react": "19.0.0",
     "react-dom": "19.0.0"
   },
   "devDependencies": {
     "@types/node": "^22.9.0",
-    "@types/react": "^18.3.12",
-    "@types/react-dom": "^18.3.1",
+    "@types/react": "^19.0.10",
+    "@types/react-dom": "^19.0.4",
     "eslint": "9.16.0",
     "eslint-config-next": "15.1.0",
-    "postcss": "^8.4.49",
-    "tailwindcss": "^3.4.15",
-    "typescript": "^5.7.2"
+    "typescript": "^5.7.3"
   }
 }

e2e/examples/nextjs-agent/postcss.config.mjs

@@ -1,8 +0,0 @@
-/** @type {import('postcss-load-config').Config} */
-const config = {
-  plugins: {
-    tailwindcss: {},
-  },
-};
-
-export default config;

e2e/examples/nextjs-agent/src/app/globals.css

@@ -1,3 +0,0 @@
-@tailwind base;
-@tailwind components;
-@tailwind utilities;

e2e/examples/nextjs-agent/src/app/layout.tsx

@@ -1,6 +1,5 @@
 import type { Metadata } from "next";
 import { Inter } from "next/font/google";
-import "./globals.css";
 
 const inter = Inter({ subsets: ["latin"] });
 

e2e/examples/nextjs-agent/tailwind.config.ts

@@ -1,20 +0,0 @@
-import type { Config } from "tailwindcss";
-
-const config: Config = {
-  content: [
-    "./src/pages/**/*.{js,ts,jsx,tsx,mdx}",
-    "./src/components/**/*.{js,ts,jsx,tsx,mdx}",
-    "./src/app/**/*.{js,ts,jsx,tsx,mdx}",
-  ],
-  theme: {
-    extend: {
-      backgroundImage: {
-        "gradient-radial": "radial-gradient(var(--tw-gradient-stops))",
-        "gradient-conic":
-          "conic-gradient(from 180deg at 50% 50%, var(--tw-gradient-stops))",
-      },
-    },
-  },
-  plugins: [],
-};
-export default config;

e2e/examples/nextjs-edge-runtime/CHANGELOG.md

@@ -1,5 +1,20 @@
 # test-edge-runtime
 
+## 0.1.144
+
+### Patch Changes
+
+- llamaindex@0.9.11
+
+## 0.1.143
+
+### Patch Changes
+
+- Updated dependencies [c1b5be5]
+- Updated dependencies [40ee761]
+- Updated dependencies [40ee761]
+  - llamaindex@0.9.10
+
 ## 0.1.142
 
 ### Patch Changes

e2e/examples/nextjs-edge-runtime/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.142",
+  "version": "0.1.144",
   "private": true,
   "scripts": {
     "dev": "next dev",
@@ -9,14 +9,14 @@
   },
   "dependencies": {
     "llamaindex": "workspace:*",
-    "next": "15.1.7",
-    "react": "^18.3.1",
-    "react-dom": "^18.3.1"
+    "next": "15.2.0",
+    "react": "^19.0.0",
+    "react-dom": "^19.0.0"
   },
   "devDependencies": {
     "@types/node": "^22.9.0",
-    "@types/react": "^18.3.12",
-    "@types/react-dom": "^18.3.1",
-    "typescript": "^5.7.2"
+    "@types/react": "^19.0.10",
+    "@types/react-dom": "^19.0.4",
+    "typescript": "^5.7.3"
   }
 }

e2e/examples/nextjs-node-runtime/CHANGELOG.md

@@ -1,5 +1,24 @@
 # @llamaindex/next-node-runtime
 
+## 0.1.11
+
+### Patch Changes
+
+- llamaindex@0.9.11
+- @llamaindex/huggingface@0.0.45
+
+## 0.1.10
+
+### Patch Changes
+
+- Updated dependencies [aea550a]
+- Updated dependencies [c1b5be5]
+- Updated dependencies [40ee761]
+- Updated dependencies [40ee761]
+  - @llamaindex/huggingface@0.0.44
+  - llamaindex@0.9.10
+  - @llamaindex/readers@2.0.8
+
 ## 0.1.9
 
 ### Patch Changes

e2e/examples/nextjs-node-runtime/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.1.9",
+  "version": "0.1.11",
   "private": true,
   "scripts": {
     "dev": "next dev",
@@ -8,21 +8,19 @@
     "start": "next start"
   },
   "dependencies": {
-    "llamaindex": "workspace:*",
     "@llamaindex/huggingface": "workspace:*",
     "@llamaindex/readers": "workspace:*",
-    "next": "15.1.7",
+    "llamaindex": "workspace:*",
+    "next": "15.2.0",
     "react": "19.0.0",
     "react-dom": "19.0.0"
   },
   "devDependencies": {
     "@types/node": "^22.9.0",
-    "@types/react": "^18.3.12",
-    "@types/react-dom": "^18.3.1",
+    "@types/react": "^19.0.10",
+    "@types/react-dom": "^19.0.4",
     "eslint": "9.16.0",
     "eslint-config-next": "15.1.0",
-    "postcss": "^8.4.49",
-    "tailwindcss": "^3.4.15",
-    "typescript": "^5.7.2"
+    "typescript": "^5.7.3"
   }
 }

e2e/examples/nextjs-node-runtime/postcss.config.mjs

@@ -1,8 +0,0 @@
-/** @type {import('postcss-load-config').Config} */
-const config = {
-  plugins: {
-    tailwindcss: {},
-  },
-};
-
-export default config;

e2e/examples/nextjs-node-runtime/src/actions/openai.ts

@@ -1,13 +1,7 @@
 "use server";
 import { HuggingFaceEmbedding } from "@llamaindex/huggingface";
 import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
-import {
-  OpenAI,
-  OpenAIAgent,
-  QueryEngineTool,
-  Settings,
-  VectorStoreIndex,
-} from "llamaindex";
+import { OpenAI, OpenAIAgent, Settings, VectorStoreIndex } from "llamaindex";
 
 Settings.llm = new OpenAI({
   apiKey: process.env.NEXT_PUBLIC_OPENAI_KEY ?? "FAKE_KEY_TO_PASS_TESTS",
@@ -31,23 +25,20 @@ export async function getOpenAIModelRequest(query: string) {
     const reader = new SimpleDirectoryReader();
     const documents = await reader.loadData(currentDir);
     const index = await VectorStoreIndex.fromDocuments(documents);
-    const retriever = index.asRetriever({
-      similarityTopK: 10,
-    });
-    const queryEngine = index.asQueryEngine({
-      retriever,
-    });
 
     // define the query engine as a tool
     const tools = [
-      new QueryEngineTool({
-        queryEngine: queryEngine,
+      index.queryTool({
+        options: {
+          similarityTopK: 10,
+        },
         metadata: {
           name: "deployment_details_per_env",
           description: `This tool can answer detailed questions about deployments happened in various environments.`,
         },
       }),
     ];
+
     // create the agent
     const agent = new OpenAIAgent({ tools });
 

e2e/examples/nextjs-node-runtime/src/app/globals.css

@@ -1,3 +0,0 @@
-@tailwind base;
-@tailwind components;
-@tailwind utilities;

e2e/examples/nextjs-node-runtime/src/app/layout.tsx

@@ -1,6 +1,5 @@
 import type { Metadata } from "next";
 import { Inter } from "next/font/google";
-import "./globals.css";
 
 const inter = Inter({ subsets: ["latin"] });
 

e2e/examples/nextjs-node-runtime/tailwind.config.ts

@@ -1,20 +0,0 @@
-import type { Config } from "tailwindcss";
-
-const config: Config = {
-  content: [
-    "./src/pages/**/*.{js,ts,jsx,tsx,mdx}",
-    "./src/components/**/*.{js,ts,jsx,tsx,mdx}",
-    "./src/app/**/*.{js,ts,jsx,tsx,mdx}",
-  ],
-  theme: {
-    extend: {
-      backgroundImage: {
-        "gradient-radial": "radial-gradient(var(--tw-gradient-stops))",
-        "gradient-conic":
-          "conic-gradient(from 180deg at 50% 50%, var(--tw-gradient-stops))",
-      },
-    },
-  },
-  plugins: [],
-};
-export default config;

e2e/examples/vite-import-llamaindex/CHANGELOG.md

@@ -1,5 +1,20 @@
 # vite-import-llamaindex
 
+## 0.0.11
+
+### Patch Changes
+
+- llamaindex@0.9.11
+
+## 0.0.10
+
+### Patch Changes
+
+- Updated dependencies [c1b5be5]
+- Updated dependencies [40ee761]
+- Updated dependencies [40ee761]
+  - llamaindex@0.9.10
+
 ## 0.0.9
 
 ### Patch Changes

e2e/examples/vite-import-llamaindex/package.json

@@ -1,7 +1,7 @@
 {
   "name": "vite-import-llamaindex",
   "private": true,
-  "version": "0.0.9",
+  "version": "0.0.11",
   "type": "module",
   "scripts": {
     "build": "vite build",
@@ -15,7 +15,7 @@
   "devDependencies": {
     "@size-limit/preset-big-lib": "^11.1.6",
     "size-limit": "^11.1.6",
-    "typescript": "^5.7.2",
+    "typescript": "^5.7.3",
     "vite": "^6.1.0"
   },
   "dependencies": {

e2e/examples/waku-query-engine/CHANGELOG.md

@@ -1,5 +1,20 @@
 # @llamaindex/waku-query-engine-test
 
+## 0.0.145
+
+### Patch Changes
+
+- llamaindex@0.9.11
+
+## 0.0.144
+
+### Patch Changes
+
+- Updated dependencies [c1b5be5]
+- Updated dependencies [40ee761]
+- Updated dependencies [40ee761]
+  - llamaindex@0.9.10
+
 ## 0.0.143
 
 ### Patch Changes

e2e/examples/waku-query-engine/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.143",
+  "version": "0.0.145",
   "type": "module",
   "private": true,
   "scripts": {
@@ -17,10 +17,10 @@
     "waku": "0.21.20"
   },
   "devDependencies": {
-    "@types/react": "18.3.12",
-    "@types/react-dom": "18.3.1",
+    "@types/react": "19.0.10",
+    "@types/react-dom": "19.0.4",
     "autoprefixer": "^10.4.20",
-    "tailwindcss": "^3.4.15",
-    "typescript": "5.7.2"
+    "tailwindcss": "^4.0.9",
+    "typescript": "5.7.3"
   }
 }

e2e/examples/waku-query-engine/postcss.config.js

@@ -1,7 +0,0 @@
-/** @type {import('postcss-load-config').Config} */
-export default {
-  plugins: {
-    tailwindcss: {},
-    autoprefixer: {},
-  },
-};

e2e/examples/waku-query-engine/postcss.config.mjs

@@ -0,0 +1,5 @@
+export default {
+  plugins: {
+    "@tailwindcss/postcss": {},
+  },
+};

e2e/examples/waku-query-engine/src/components/chat.tsx

@@ -10,10 +10,10 @@ export const Chat = (props: ChatProps) => {
   const [response, setResponse] = useState<string | null>(null);
 
   return (
-    <section className="border-blue-400 -mx-4 mt-4 rounded border border-dashed p-4">
+    <section className="-mx-4 mt-4 rounded border border-dashed border-blue-400 p-4">
       <h2 className="text-lg font-bold">Chat with AI</h2>
       {response ? (
-        <p className="text-sm text-gray-600 max-w-sm">{response}</p>
+        <p className="max-w-sm text-sm text-gray-600">{response}</p>
       ) : null}
       <form
         action={async (formData) => {
@@ -26,7 +26,7 @@ export const Chat = (props: ChatProps) => {
         <input
           type="text"
           name="question"
-          className="border border-gray-400 rounded-sm px-2 py-0.5 text-sm"
+          className="rounded-sm border border-gray-400 px-2 py-0.5 text-sm"
         />
         <button className="rounded-sm bg-black px-2 py-0.5 text-sm text-white">
           Ask

e2e/examples/waku-query-engine/src/styles.css

@@ -1,4 +1,2 @@
 @import url("https://fonts.googleapis.com/css2?family=Nunito:ital,wght@0,400;0,700;1,400;1,700&display=swap");
-@tailwind base;
-@tailwind components;
-@tailwind utilities;
+@import "tailwindcss";

e2e/node/fixtures/tools.ts

@@ -1,4 +1,5 @@
 import { FunctionTool } from "llamaindex";
+import { z } from "zod";
 
 function sumNumbers({ a, b }: { a: number; b: number }) {
   return `${a + b}`;
@@ -11,39 +12,27 @@ function divideNumbers({ a, b }: { a: number; b: number }) {
 export const sumNumbersTool = FunctionTool.from(sumNumbers, {
   name: "sumNumbers",
   description: "Use this function to sum two numbers",
-  parameters: {
-    type: "object",
-    properties: {
-      a: {
-        type: "number",
-        description: "The first number",
-      },
-      b: {
-        type: "number",
-        description: "The second number",
-      },
-    },
-    required: ["a", "b"],
-  },
+  parameters: z.object({
+    a: z.number({
+      description: "The first number",
+    }),
+    b: z.number({
+      description: "The second number",
+    }),
+  }),
 });
 
 export const divideNumbersTool = FunctionTool.from(divideNumbers, {
   name: "divideNumbers",
   description: "Use this function to divide two numbers",
-  parameters: {
-    type: "object",
-    properties: {
-      a: {
-        type: "number",
-        description: "The first number",
-      },
-      b: {
-        type: "number",
-        description: "The second number",
-      },
-    },
-    required: ["a", "b"],
-  },
+  parameters: z.object({
+    a: z.number({
+      description: "The first number",
+    }),
+    b: z.number({
+      description: "The second number",
+    }),
+  }),
 });
 
 // should always return the 72 degrees
@@ -54,15 +43,10 @@ export const getWeatherTool = FunctionTool.from(
   {
     name: "getWeather",
     description: "Get the weather for a city",
-    parameters: {
-      type: "object",
-      properties: {
-        city: {
-          type: "string",
-          description: "The city to get the weather for",
-        },
-      },
-      required: ["city"],
-    },
+    parameters: z.object({
+      city: z.string({
+        description: "The city to get the weather for",
+      }),
+    }),
   },
 );

e2e/package.json

@@ -10,22 +10,23 @@
   },
   "devDependencies": {
     "@faker-js/faker": "^9.2.0",
+    "@huggingface/transformers": "^3.0.2",
+    "@llamaindex/anthropic": "workspace:*",
+    "@llamaindex/clip": "workspace:*",
     "@llamaindex/core": "workspace:*",
     "@llamaindex/env": "workspace:*",
     "@llamaindex/ollama": "workspace:*",
     "@llamaindex/openai": "workspace:*",
     "@llamaindex/pinecone": "workspace:*",
     "@llamaindex/postgres": "workspace:*",
-    "@llamaindex/clip": "workspace:*",
-    "@llamaindex/anthropic": "workspace:*",
     "@types/node": "^22.9.0",
     "@types/pg": "^8.11.8",
-    "@huggingface/transformers": "^3.0.2",
     "consola": "^3.2.3",
     "dotenv": "^16.4.5",
     "llamaindex": "workspace:*",
     "pg": "^8.12.0",
     "pgvector": "0.2.0",
-    "tsx": "^4.19.0"
+    "tsx": "^4.19.3",
+    "zod": "^3.24.2"
   }
 }

examples/CHANGELOG.md

@@ -1,5 +1,78 @@
 # examples
 
+## 0.2.10
+
+### Patch Changes
+
+- 1587e48: Added support for Perplexity api
+- Updated dependencies [387a192]
+- Updated dependencies [a8c0637]
+- Updated dependencies [1587e48]
+- Updated dependencies [98eebf7]
+  - @llamaindex/mistral@0.0.14
+  - @llamaindex/openai@0.1.61
+  - @llamaindex/perplexity@0.0.2
+  - @llamaindex/google@0.1.2
+  - llamaindex@0.9.11
+  - @llamaindex/clip@0.0.45
+  - @llamaindex/deepinfra@0.0.45
+  - @llamaindex/deepseek@0.0.5
+  - @llamaindex/fireworks@0.0.5
+  - @llamaindex/groq@0.0.60
+  - @llamaindex/huggingface@0.0.45
+  - @llamaindex/jinaai@0.0.5
+  - @llamaindex/together@0.0.5
+  - @llamaindex/vllm@0.0.31
+
+## 0.2.9
+
+### Patch Changes
+
+- aea550a: Add factory convenience factory for each LLM provider, e.g. you can use openai instead of 'new OpenAI'
+- Updated dependencies [c14a21b]
+- Updated dependencies [33f9856]
+- Updated dependencies [aea550a]
+- Updated dependencies [c1b5be5]
+- Updated dependencies [40ee761]
+- Updated dependencies [40ee761]
+  - @llamaindex/azure@0.1.8
+  - @llamaindex/google@0.1.1
+  - @llamaindex/huggingface@0.0.44
+  - @llamaindex/portkey-ai@0.0.41
+  - @llamaindex/anthropic@0.2.6
+  - @llamaindex/deepinfra@0.0.44
+  - @llamaindex/fireworks@0.0.4
+  - @llamaindex/replicate@0.0.41
+  - @llamaindex/deepseek@0.0.4
+  - @llamaindex/together@0.0.4
+  - @llamaindex/mistral@0.0.13
+  - @llamaindex/ollama@0.0.48
+  - @llamaindex/openai@0.1.60
+  - @llamaindex/vercel@0.0.19
+  - @llamaindex/groq@0.0.59
+  - @llamaindex/vllm@0.0.30
+  - llamaindex@0.9.10
+  - @llamaindex/workflow@0.0.16
+  - @llamaindex/core@0.5.8
+  - @llamaindex/clip@0.0.44
+  - @llamaindex/jinaai@0.0.4
+  - @llamaindex/milvus@0.1.8
+  - @llamaindex/qdrant@0.1.8
+  - @llamaindex/cloud@3.0.9
+  - @llamaindex/node-parser@1.0.8
+  - @llamaindex/cohere@0.0.13
+  - @llamaindex/mixedbread@0.0.13
+  - @llamaindex/astra@0.0.13
+  - @llamaindex/chroma@0.0.13
+  - @llamaindex/firestore@1.0.6
+  - @llamaindex/mongodb@0.0.13
+  - @llamaindex/pinecone@0.0.13
+  - @llamaindex/postgres@0.0.41
+  - @llamaindex/upstash@0.0.13
+  - @llamaindex/weaviate@0.0.13
+  - @llamaindex/voyage-ai@1.0.5
+  - @llamaindex/readers@2.0.8
+
 ## 0.2.8
 
 ### Patch Changes

examples/agent/large_toolcall.ts

@@ -1,5 +1,6 @@
-import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
-import { FunctionTool } from "llamaindex";
+import { OpenAI } from "@llamaindex/openai";
+import { FunctionTool, agent } from "llamaindex";
+import { z } from "zod";
 
 const csvData =
   "TITLE,RELEASE_YEAR,SCORE,NUMBER_OF_VOTES,DURATION,MAIN_GENRE,MAIN_PRODUCTION\nDavid Attenborough: A Life on Our Planet,2020,9,31180,83,documentary,GB\nInception,2010,8.8,2268288,148,scifi,GB\nForrest Gump,1994,8.8,1994599,142,drama,US\nAnbe Sivam,2003,8.7,20595,160,comedy,IN\nBo Burnham: Inside,2021,8.7,44074,87,comedy,US\nSaving Private Ryan,1998,8.6,1346020,169,drama,US\nDjango Unchained,2012,8.4,1472668,165,western,US\nDangal,2016,8.4,180247,161,action,IN\nBo Burnham: Make Happy,2016,8.4,14356,60,comedy,US\nLouis C.K.: Hilarious,2010,8.4,11973,84,comedy,US\nDave Chappelle: Sticks & Stones,2019,8.4,25687,65,comedy,US\n3 Idiots,2009,8.4,385782,170,comedy,IN\nBlack Friday,2004,8.4,20611,143,crime,IN\nSuper Deluxe,2019,8.4,13680,176,thriller,IN\nWinter on Fire: Ukraine's Fight for Freedom,2015,8.3,17710,98,documentary,UA\nOnce Upon a Time in America,1984,8.3,342335,229,drama,US\nTaxi Driver,1976,8.3,795222,113,crime,US\nLike Stars on Earth,2007,8.3,188234,165,drama,IN\nBo Burnham: What.,2013,8.3,11488,60,comedy,US\nFull Metal Jacket,1987,8.3,723306,116,drama,GB\nWarrior,2011,8.2,463276,140,drama,US\nDrishyam,2015,8.2,79075,163,thriller,IN\nQueen,2014,8.2,64805,146,drama,IN\nPaan Singh Tomar,2012,8.2,35888,135,drama,IN";
@@ -8,13 +9,9 @@ const userQuestion = "which are the best comedies after 2010?";
 
 (async () => {
   // The agent will succeed if we increase `maxTokens` to 1024
-  const llm = new OpenAI({ model: "gpt-4-turbo", maxTokens: 256 });
+  const llm = new OpenAI({ model: "gpt-4-turbo", maxTokens: 1024 });
 
-  type Input = {
-    code: string;
-  };
-  // initiate fake code interpreter
-  const interpreterTool = FunctionTool.from<Input>(
+  const interpreterTool = FunctionTool.from(
     ({ code }) => {
       console.log(
         `To answer the user's question, call the following code:\n${code}`,
@@ -25,41 +22,34 @@ const userQuestion = "which are the best comedies after 2010?";
       name: "interpreter",
       description:
         "Execute python code in a Jupyter notebook cell and return any result, stdout, stderr, display_data, and error.",
-      parameters: {
-        type: "object",
-        properties: {
-          code: {
-            type: "string",
-            description: "The python code to execute in a single cell.",
-          },
-        },
-        required: ["code"],
-      },
+      parameters: z.object({
+        code: z.string({
+          description: "The python code to execute in a single cell.",
+        }),
+      }),
     },
   );
 
   const systemPrompt =
     "You are a Python interpreter.\n        - You are given tasks to complete and you run python code to solve them.\n        - The python code runs in a Jupyter notebook. Every time you call $(interpreter) tool, the python code is executed in a separate cell. It's okay to make multiple calls to $(interpreter).\n        - Display visualizations using matplotlib or any other visualization library directly in the notebook. Shouldn't save the visualizations to a file, just return the base64 encoded data.\n        - You can install any pip package (if it exists) if you need to but the usual packages for data analysis are already preinstalled.\n        - You can run any python code you want in a secure environment.";
 
-  const agent = new OpenAIAgent({
-    llm,
+  const workflow = agent({
     tools: [interpreterTool],
+    llm,
+    verbose: false,
     systemPrompt,
-    verbose: true,
   });
 
   console.log(`User question: ${userQuestion}\n`);
 
-  await agent.chat({
-    message: [
+  const result = await workflow.run(userQuestion, {
+    chatHistory: [
       {
-        type: "text",
-        text: userQuestion,
-      },
-      {
-        type: "text",
-        text: `Use data from following CSV raw contents:\n${csvData}`,
+        role: "user",
+        content: `Use data from following CSV raw contents:\n${csvData}`,
       },
     ],
   });
+
+  console.log(result);
 })();

examples/agent/large_toolcall_with_gpt4o.ts

@@ -1,5 +1,6 @@
 import { OpenAI } from "@llamaindex/openai";
 import { FunctionTool, ToolCallOptions } from "llamaindex";
+import { z } from "zod";
 
 (async () => {
   // The tool call will generate a partial JSON for `gpt-4-turbo`
@@ -27,16 +28,11 @@ async function callLLM(init: { model: string }) {
       name: "interpreter",
       description:
         "Execute python code in a Jupyter notebook cell and return any result, stdout, stderr, display_data, and error.",
-      parameters: {
-        type: "object",
-        properties: {
-          code: {
-            type: "string",
-            description: "The python code to execute in a single cell.",
-          },
-        },
-        required: ["code"],
-      },
+      parameters: z.object({
+        code: z.string({
+          description: "The python code to execute in a single cell.",
+        }),
+      }),
     },
   );
 

examples/agent/openai.ts

@@ -1,25 +1,16 @@
-import { OpenAIAgent } from "@llamaindex/openai";
-import { FunctionTool } from "llamaindex";
+import { OpenAI } from "@llamaindex/openai";
+import { FunctionTool, agent } from "llamaindex";
+import { z } from "zod";
 
 const sumNumbers = FunctionTool.from(
   ({ a, b }: { a: number; b: number }) => `${a + b}`,
   {
     name: "sumNumbers",
     description: "Use this function to sum two numbers",
-    parameters: {
-      type: "object",
-      properties: {
-        a: {
-          type: "number",
-          description: "The first number",
-        },
-        b: {
-          type: "number",
-          description: "The second number",
-        },
-      },
-      required: ["a", "b"],
-    },
+    parameters: z.object({
+      a: z.number().describe("The first number"),
+      b: z.number().describe("The second number"),
+    }),
   },
 );
 
@@ -28,33 +19,22 @@ const divideNumbers = FunctionTool.from(
   {
     name: "divideNumbers",
     description: "Use this function to divide two numbers",
-    parameters: {
-      type: "object",
-      properties: {
-        a: {
-          type: "number",
-          description: "The dividend a to divide",
-        },
-        b: {
-          type: "number",
-          description: "The divisor b to divide by",
-        },
-      },
-      required: ["a", "b"],
-    },
+    parameters: z.object({
+      a: z.number().describe("The dividend a to divide"),
+      b: z.number().describe("The divisor b to divide by"),
+    }),
   },
 );
 
 async function main() {
-  const agent = new OpenAIAgent({
+  const workflow = agent({
     tools: [sumNumbers, divideNumbers],
+    llm: new OpenAI({ model: "gpt-4o-mini" }),
+    verbose: false,
   });
 
-  const response = await agent.chat({
-    message: "How much is 5 + 5? then divide by 2",
-  });
-
-  console.log(response.message);
+  const response = await workflow.run("How much is 5 + 5? then divide by 2");
+  console.log(response.data);
 }
 
 void main().then(() => {

examples/agent/retriever_openai_agent.ts

@@ -6,6 +6,7 @@ import {
   NodeWithScore,
   VectorStoreIndex,
 } from "llamaindex";
+import { z } from "zod";
 
 async function main() {
   // Load the documents
@@ -32,16 +33,9 @@ async function main() {
     {
       name: "get_abramov_info",
       description: "Get information about the Abramov documents",
-      parameters: {
-        type: "object",
-        properties: {
-          query: {
-            type: "string",
-            description: "The query about Abramov",
-          },
-        },
-        required: ["query"],
-      },
+      parameters: z.object({
+        query: z.string().describe("The query about Abramov"),
+      }),
     },
   );
 

examples/agent/stream_openai_agent.ts

@@ -1,5 +1,6 @@
 import { OpenAIAgent } from "@llamaindex/openai";
 import { FunctionTool } from "llamaindex";
+import { z } from "zod";
 
 // Define a function to sum two numbers
 function sumNumbers({ a, b }: { a: number; b: number }) {
@@ -11,50 +12,29 @@ function divideNumbers({ a, b }: { a: number; b: number }) {
   return `${a / b}`;
 }
 
-// Define the parameters of the sum function as a JSON schema
-const sumJSON = {
-  type: "object",
-  properties: {
-    a: {
-      type: "number",
-      description: "The first number",
-    },
-    b: {
-      type: "number",
-      description: "The second number",
-    },
-  },
-  required: ["a", "b"],
-} as const;
+const sumSchema = z.object({
+  a: z.number().describe("The first number"),
+  b: z.number().describe("The second number"),
+});
 
-const divideJSON = {
-  type: "object",
-  properties: {
-    a: {
-      type: "number",
-      description: "The dividend",
-    },
-    b: {
-      type: "number",
-      description: "The divisor",
-    },
-  },
-  required: ["a", "b"],
-} as const;
+const divideSchema = z.object({
+  a: z.number().describe("The dividend"),
+  b: z.number().describe("The divisor"),
+});
 
 async function main() {
   // Create a function tool from the sum function
   const functionTool = FunctionTool.from(sumNumbers, {
     name: "sumNumbers",
     description: "Use this function to sum two numbers",
-    parameters: sumJSON,
+    parameters: sumSchema,
   });
 
   // Create a function tool from the divide function
   const functionTool2 = FunctionTool.from(divideNumbers, {
     name: "divideNumbers",
     description: "Use this function to divide two numbers",
-    parameters: divideJSON,
+    parameters: divideSchema,
   });
 
   // Create an OpenAIAgent with the function tools

examples/agent/utils/tools.ts

@@ -1,54 +1,31 @@
-import { FunctionTool } from "llamaindex";
+import { tool } from "llamaindex";
+import { z } from "zod";
 
-export const getCurrentIDTool = FunctionTool.from(
-  () => {
+export const getCurrentIDTool = tool({
+  name: "get_user_id",
+  description: "Get a random user id",
+  parameters: z.object({}),
+  execute: () => {
     console.log("Getting user id...");
     return crypto.randomUUID();
   },
-  {
-    name: "get_user_id",
-    description: "Get a random user id",
-  },
-);
+});
 
-export const getUserInfoTool = FunctionTool.from(
-  ({ userId }: { userId: string }) => {
-    console.log("Getting user info...", userId);
-    return `Name: Alex; Address: 1234 Main St, CA; User ID: ${userId}`;
-  },
-  {
-    name: "get_user_info",
-    description: "Get user info",
-    parameters: {
-      type: "object",
-      properties: {
-        userId: {
-          type: "string",
-          description: "The user id",
-        },
-      },
-      required: ["userId"],
-    },
-  },
-);
+export const getUserInfoTool = tool({
+  name: "get_user_info",
+  description: "Get user info",
+  parameters: z.object({
+    userId: z.string().describe("The user id"),
+  }),
+  execute: ({ userId }) =>
+    `Name: Alex; Address: 1234 Main St, CA; User ID: ${userId}`,
+});
 
-export const getWeatherTool = FunctionTool.from(
-  ({ address }: { address: string }) => {
-    console.log("Getting weather...", address);
-    return `${address} is in a sunny location!`;
-  },
-  {
-    name: "get_weather",
-    description: "Get the current weather for a location",
-    parameters: {
-      type: "object",
-      properties: {
-        address: {
-          type: "string",
-          description: "The address",
-        },
-      },
-      required: ["address"],
-    },
-  },
-);
+export const getWeatherTool = tool({
+  name: "get_weather",
+  description: "Get the current weather for a location",
+  parameters: z.object({
+    address: z.string().describe("The address"),
+  }),
+  execute: ({ address }) => `${address} is in a sunny location!`,
+});

examples/agent/wiki.ts

@@ -1,24 +1,28 @@
-import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
+import { OpenAI } from "@llamaindex/openai";
+import { AgentStream, agent } from "llamaindex";
 import { WikipediaTool } from "../wiki";
 
 async function main() {
   const llm = new OpenAI({ model: "gpt-4-turbo" });
   const wikiTool = new WikipediaTool();
 
-  // Create an OpenAIAgent with the Wikipedia tool
-  const agent = new OpenAIAgent({
-    llm,
+  const workflow = agent({
     tools: [wikiTool],
+    llm,
+    verbose: false,
   });
 
   // Chat with the agent
-  const response = await agent.chat({
-    message: "Who was Goethe?",
-    stream: true,
-  });
+  const context = workflow.run("Who was Goethe?");
 
-  for await (const { delta } of response) {
-    process.stdout.write(delta);
+  for await (const event of context) {
+    if (event instanceof AgentStream) {
+      for (const chunk of event.data.delta) {
+        process.stdout.write(chunk);
+      }
+    } else {
+      console.log(event);
+    }
   }
 }