fix: remove openapi

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

CONTRIBUTING.md

@@ -41,8 +41,15 @@ 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/*"
 ```
 

apps/next/CHANGELOG.md

@@ -1,5 +1,79 @@
 # @llamaindex/doc
 
+## 0.1.9
+
+### Patch Changes
+
+- 4bac71d: Support binding additional argument to function tool
+- Updated dependencies [4bac71d]
+  - @llamaindex/core@0.5.7
+  - @llamaindex/cloud@3.0.8
+  - llamaindex@0.9.9
+  - @llamaindex/node-parser@1.0.7
+  - @llamaindex/openai@0.1.59
+  - @llamaindex/readers@2.0.7
+  - @llamaindex/workflow@0.0.15
+
+## 0.1.8
+
+### Patch Changes
+
+- Updated dependencies [4b49428]
+- Updated dependencies [bbc8c87]
+  - @llamaindex/workflow@0.0.14
+  - llamaindex@0.9.8
+
+## 0.1.7
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/core@0.5.6
+  - llamaindex@0.9.7
+  - @llamaindex/cloud@3.0.7
+  - @llamaindex/node-parser@1.0.6
+  - @llamaindex/openai@0.1.58
+  - @llamaindex/readers@2.0.6
+  - @llamaindex/workflow@0.0.13
+
+## 0.1.6
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+  - @llamaindex/core@0.5.5
+  - @llamaindex/workflow@0.0.12
+  - @llamaindex/cloud@3.0.6
+  - llamaindex@0.9.6
+  - @llamaindex/node-parser@1.0.5
+  - @llamaindex/openai@0.1.57
+  - @llamaindex/readers@2.0.5
+
+## 0.1.5
+
+### Patch Changes
+
+- Updated dependencies [ad3c7f1]
+  - @llamaindex/core@0.5.4
+  - @llamaindex/cloud@3.0.5
+  - llamaindex@0.9.5
+  - @llamaindex/node-parser@1.0.4
+  - @llamaindex/openai@0.1.56
+  - @llamaindex/readers@2.0.4
+
+## 0.1.4
+
+### Patch Changes
+
+- Updated dependencies [cb256f2]
+- Updated dependencies [cb021e7]
+  - @llamaindex/openai@0.1.55
+  - @llamaindex/core@0.5.3
+  - llamaindex@0.9.4
+  - @llamaindex/cloud@3.0.4
+  - @llamaindex/node-parser@1.0.3
+  - @llamaindex/readers@2.0.3
+
 ## 0.1.3
 
 ### Patch Changes

apps/next/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/doc",
-  "version": "0.1.3",
+  "version": "0.1.9",
   "private": true,
   "scripts": {
     "build": "pnpm run build:docs && next build",
@@ -8,11 +8,11 @@
     "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"
+    "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:*",
@@ -27,24 +27,24 @@
     "@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": "15.2.0",
     "next-themes": "^0.4.3",
     "react": "^19.0.0",
     "react-dom": "^19.0.0",
@@ -55,8 +55,8 @@
     "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",
@@ -68,26 +68,27 @@
   },
   "devDependencies": {
     "@next/env": "^15.0.3",
+    "@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 +1,6 @@
-import * as OpenAPI from "fumadocs-openapi";
 import { generateFiles } from "fumadocs-typescript";
 import fs from "node:fs";
 import * as path from "node:path";
-import { fileURLToPath } from "node:url";
 import { rimrafSync } from "rimraf";
 
 const out = "./src/content/docs/cloud/api";
@@ -15,28 +13,17 @@ rimrafSync(out, {
   },
 });
 
-void OpenAPI.generateFiles({
-  input: [
-    fileURLToPath(
-      new URL("../../../packages/cloud/openapi.json", import.meta.url),
-    ),
-  ],
-  output: out,
-  groupBy: "tag",
-});
-
 void generateFiles({
   input: ["./src/content/docs/api/**/*.mdx"],
   output: (file) => path.resolve(path.dirname(file), path.basename(file)),
   transformOutput,
 });
 
-function transformOutput(filePath, content) {
+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 +33,17 @@ 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/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/src/app/global.css

@@ -1,6 +1,12 @@
-@tailwind base;
-@tailwind components;
-@tailwind utilities;
+@import "tailwindcss";
+@import "fumadocs-ui/css/neutral.css";
+@import "fumadocs-ui/css/preset.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 +52,7 @@
     --chart-5: 27 87% 67%;
     --radius: 0.5rem;
   }
+
   .dark {
     --color-neutral-000: #0e0c15;
     --color-neutral-100: #252134;
@@ -87,40 +94,3 @@
     --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/components/code-block.tsx

@@ -1,5 +1,5 @@
 import * as Base from "fumadocs-ui/components/codeblock";
-import { toJsxRuntime, type Jsx } from "hast-util-to-jsx-runtime";
+import { toJsxRuntime } from "hast-util-to-jsx-runtime";
 import { Fragment } from "react";
 import { jsx, jsxs } from "react/jsx-runtime";
 import { codeToHast } from "shiki";
@@ -39,12 +39,11 @@ export async function CodeBlock({
   });
 
   const rendered = toJsxRuntime(hast, {
-    jsx: jsx as Jsx,
-    jsxs: jsxs as Jsx,
+    jsx: jsx,
+    jsxs: jsxs,
     Fragment,
-    development: false,
+    development: process.env.NODE_ENV === "development",
     components: {
-      // @ts-expect-error -- JSX component
       pre: Base.Pre,
     },
   });

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/content/docs/llamaindex/getting_started/setup/node.mdx

@@ -3,6 +3,8 @@ title: With Node.js/Bun/Deno
 description: In this guide, you'll learn how to use LlamaIndex with Node.js, Bun, and Deno.
 ---
 
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
 ## Adding environment variables
 
 By default, LlamaIndex uses OpenAI provider, which requires an API key. You can set the `OPENAI_API_KEY` environment variable to authenticate with OpenAI.
@@ -22,6 +24,26 @@ node --env-file .env your-script.js
 
 For more information, see the [How to read environment variables from Node.js](https://nodejs.org/en/learn/command-line/how-to-read-environment-variables-from-nodejs).
 
+## Performance Optimization
+
+By the default, we are using `js-tiktoken` for tokenization. You can install `gpt-tokenizer` which is then automatically used by LlamaIndex to get a 60x speedup for tokenization:
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install gpt-tokenizer
+	```
+
+	```shell tab="yarn"
+	yarn add gpt-tokenizer
+	```
+
+	```shell tab="pnpm"
+	pnpm add gpt-tokenizer
+	```
+</Tabs>
+
+> Note: This only works for Node.js
+
 ## TypeScript support
 
 <Card

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

@@ -34,6 +34,7 @@ First we'll need to pull in our dependencies. These are:
 import { FunctionTool, Settings } from "llamaindex";
 import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
 import "dotenv/config";
+import { z } from "zod";
 ```
 
 ### Initialize your LLM
@@ -86,20 +87,14 @@ This is the most complicated part of creating an agent. We need to define a `Fun
 const tool = FunctionTool.from(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"],
-  },
+  parameters: z.object({
+    a: z.number({
+      description: "First number to sum",
+    }),
+    b: z.number({
+      description: "Second number to sum",
+    }),
+  }),
 });
 ```
 

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

@@ -2,7 +2,7 @@
 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
@@ -17,24 +17,42 @@ const tools = [
   FunctionTool.from(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"],
-    },
+    parameters: z.object({
+      a: z.number({
+        description: "First number to sum",
+      }),
+      b: z.number({
+        description: "Second number to sum",
+      }),
+    }),
   }),
 ];
 ```
 
+You can also use JSON Schema to define the tool parameters as an alternative to Zod.
+
+```javascript
+FunctionTool.from(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

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

@@ -0,0 +1,139 @@
+---
+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>
+
+## Usage
+
+### Single Agent Workflow
+
+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";
+
+// Define a joke-telling tool
+const jokeTool = FunctionTool.from(
+  () => "Baby Llama is called cria",
+  {
+    name: "joke",
+    description: "Use this tool to get a joke",
+  }
+);
+
+// Create an agent workflow with the tool
+const workflow = AgentWorkflow.fromTools({
+  tools: [jokeTool],
+  llm: new OpenAI({
+    model: "gpt-4o-mini",
+  }),
+});
+
+// Run the workflow
+const result = await workflow.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:
+
+```typescript
+import { AgentToolCall, AgentStream } from "llamaindex";
+
+// Get the workflow execution context
+const context = workflow.run("Tell me something funny");
+
+// Stream and handle events
+for await (const event of context) {
+  if (event instanceof AgentToolCall) {
+    console.log(`Tool being called: ${event.data.toolName}`);
+  }
+  if (event instanceof AgentStream) {
+    process.stdout.write(event.data.delta);
+  }
+}
+```
+
+### Multi-Agent Workflow
+
+`AgentWorkflow` 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
+- `tools`: Array of tools the agent can use
+- `canHandoffTo` (optional): Array of agent names or agent instances that this agent can delegate tasks to
+
+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 { z } from "zod";
+
+// Create a weather agent
+const weatherAgent = new FunctionAgent({
+  name: "WeatherAgent",
+  description: "Provides weather information for any city",
+  tools: [
+    FunctionTool.from(
+      ({ city }: { city: string }) => `The weather in ${city} is sunny`,
+      {
+        name: "fetchWeather",
+        description: "Get weather information for a city",
+        parameters: z.object({
+          city: z.string(),
+        }),
+      }
+    ),
+  ],
+  llm: new OpenAI({ model: "gpt-4o-mini" }),
+});
+
+// Create a joke-telling agent
+const jokeAgent = new FunctionAgent({
+  name: "JokeAgent",
+  description: "Tells jokes and funny stories",
+  tools: [jokeTool], // Using the joke tool defined earlier
+  llm: new OpenAI({ model: "gpt-4o-mini" }),
+  canHandoffTo: [weatherAgent], // Can hand off to the weather agent
+});
+
+// Create the multi-agent workflow
+const workflow = new AgentWorkflow({
+  agents: [jokeAgent, weatherAgent],
+  rootAgent: jokeAgent, // Start with the joke agent
+});
+
+// Run the workflow
+const result = await workflow.run(
+  "Give me a morning greeting with a joke and the weather in San Francisco"
+);
+```
+
+The workflow will coordinate between agents, allowing them to handle different aspects of the request and hand off tasks when appropriate.
+

apps/next/src/content/docs/llamaindex/modules/embeddings/available_embeddings/jinaai.mdx

@@ -2,10 +2,11 @@
 title: Jina AI
 ---
 
-To use Jina AI embeddings, you need to import `JinaAIEmbedding` from `llamaindex`.
+To use Jina AI embeddings, you need to import `JinaAIEmbedding` from `@llamaindex/jinaai`.
 
 ```ts
-import { JinaAIEmbedding, Settings } from "llamaindex";
+import { Settings } from "llamaindex";
+import { JinaAIEmbedding } from "@llamaindex/jinaai";
 
 Settings.embedModel = new JinaAIEmbedding();
 

apps/next/src/content/docs/llamaindex/modules/embeddings/available_embeddings/together.mdx

@@ -2,10 +2,11 @@
 title: Together
 ---
 
-To use together embeddings, you need to import `TogetherEmbedding` from `llamaindex`.
+To use together embeddings, you need to import `TogetherEmbedding` from `@llamaindex/together`.
 
 ```ts
-import { TogetherEmbedding, Settings } from "llamaindex";
+import { Settings } from "llamaindex";
+import { TogetherEmbedding } from "@llamaindex/together";
 
 Settings.embedModel = new TogetherEmbedding({
   apiKey: "<YOUR_API_KEY>",

apps/next/src/content/docs/llamaindex/modules/embeddings/available_embeddings/voyageai.mdx

@@ -0,0 +1,46 @@
+---
+title: VoyageAI
+---
+
+To use VoyageAI embeddings, you need to import `VoyageAIEmbedding` from `@llamaindex/voyage-ai`.
+
+## Installation
+
+import { Tab, Tabs } from "fumadocs-ui/components/tabs";
+
+<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
+	```shell tab="npm"
+	npm install llamaindex @llamaindex/voyage-ai
+	```
+
+	```shell tab="yarn"
+	yarn add llamaindex @llamaindex/voyage-ai
+	```
+
+	```shell tab="pnpm"
+	pnpm add llamaindex @llamaindex/voyage-ai
+	```
+</Tabs>
+
+```ts
+import { VoyageAIEmbedding } from "@llamaindex/voyage-ai";
+import { Document, Settings, VectorStoreIndex } from "llamaindex";
+
+Settings.embedModel = new VoyageAIEmbedding();
+
+const document = new Document({ text: essay, id_: "essay" });
+
+const index = await VectorStoreIndex.fromDocuments([document]);
+
+const queryEngine = index.asQueryEngine();
+
+const query = "What is the meaning of life?";
+
+const results = await queryEngine.query({
+  query,
+});
+```
+
+## API Reference
+
+- [VoyageAIEmbedding](/docs/api/classes/VoyageAIEmbedding)

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

@@ -37,6 +37,31 @@ Settings.embedModel = new OpenAIEmbedding({
 
 For local embeddings, you can use the [HuggingFace](/docs/llamaindex/modules/embeddings/available_embeddings/huggingface) embedding model.
 
+## Local Ollama Embeddings With Remote Host
+
+Ollama provides a way to run embedding models locally or connect to a remote Ollama instance. This is particularly useful when you need to:
+- Run embeddings without relying on external API services
+- Use custom embedding models
+- Connect to a shared Ollama instance in your network
+
+The ENV variable method you will find elsewhere sometimes may not work with the OllamaEmbedding class. Also note, you'll need to change the host
+in the Ollama server to `0.0.0.0` to allow connections from other machines.
+
+To use Ollama embeddings with a remote host, you need to specify the host URL in the configuration like this:
+
+```typescript
+import { OllamaEmbedding } from "@llamaindex/ollama";
+import { Settings } from "llamaindex";
+
+// Configure Ollama with a remote host
+Settings.embedModel = new OllamaEmbedding({
+  model: "nomic-embed-text",
+  config: {
+    host: "http://your-ollama-host:11434"
+  }
+});
+```
+
 ## Available Embeddings
 
 Most available embeddings are listed in the sidebar on the left.

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/deepseek.mdx

@@ -7,7 +7,8 @@ title: DeepSeek LLM
 ## Usage
 
 ```ts
-import { DeepSeekLLM, Settings } from "llamaindex";
+import { Settings } from "llamaindex";
+import { DeepSeekLLM } from "@llamaindex/deepseek";
 
 Settings.llm = new DeepSeekLLM({
   apiKey: "<YOUR_API_KEY>",
@@ -18,7 +19,8 @@ Settings.llm = new DeepSeekLLM({
 ## Example
 
 ```ts
-import { DeepSeekLLM, Document, VectorStoreIndex, Settings } from "llamaindex";
+import { Document, VectorStoreIndex, Settings } from "llamaindex";
+import { DeepSeekLLM } from "@llamaindex/deepseek";
 
 const deepseekLlm = new DeepSeekLLM({
   apiKey: "<YOUR_API_KEY>",

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

@@ -7,7 +7,8 @@ title: Fireworks LLM
 ## Usage
 
 ```ts
-import { FireworksLLM, Settings } from "llamaindex";
+import { Settings } from "llamaindex";
+import { FireworksLLM } from "@llamaindex/fireworks";
 
 Settings.llm = new FireworksLLM({
   apiKey: "<YOUR_API_KEY>",

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

@@ -23,7 +23,8 @@ import { Tab, Tabs } from "fumadocs-ui/components/tabs";
 ## Usage
 
 ```ts
-import { Settings, TogetherLLM } from "llamaindex";
+import { Settings } from "llamaindex";
+import { TogetherLLM } from "@llamaindex/together";
 
 Settings.llm = new TogetherLLM({
   apiKey: "<YOUR_API_KEY>",

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

@@ -0,0 +1,55 @@
+---
+title: Tools
+---
+
+A "tool" is a utility that can be called by an agent on behalf of an LLM.
+A tool can be called to perform custom actions, or retrieve extra information based on the LLM-generated input.
+A result from a tool call can be used by subsequent steps in a workflow, or to compute a final answer.
+For example, a "weather tool" could fetch some live weather information from a geographical location.
+
+## Function tool
+
+Function tools are implemented with the `FunctionTool` class.
+A `FunctionTool` is constructed from a function with signature
+```ts
+(input: T, additionalArg?: AdditionalToolArgument) => R
+```
+where
+- `input` is generated by the LLM, `T` is the type defined by the tool `parameters`
+- `additionalArg` is an optional extra argument, see "Binding" below
+- `R` is the return type
+
+### Binding
+
+An additional argument can be bound to a tool, each tool call will be passed
+- the input provided by the LLM
+- the additional argument (extends object)
+
+Note: calling the `bind` method will return a new `FunctionTool` instance, without modifying the tool which `bind` is called on.
+
+Example to pass a `userToken` as additional argument:
+```ts
+// 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}`);
+  // ...
+};
+
+// define tool as usual
+const kbTool = FunctionTool.from(queryKnowledgeBase, {
+  name: 'queryKnowledgeBase',
+  description: 'Query knowledge base',
+  parameters: z.object({
+    question: z.string({
+      description: 'The user question',
+    }),
+  }),
+});
+
+// create an agent
+const additionalArg = { userToken: 'abcd1234' };
+const kbAgent = new LLMAgent({
+  tools: [kbTool.bind(additionalArg)],
+  // llm, systemPrompt etc
+})
+```

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: {

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 +1,44 @@
 # @llamaindex/cloudflare-worker-agent-test
 
+## 0.0.143
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.0.142
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.0.141
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 0.0.140
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 0.0.139
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 0.0.138
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
 ## 0.0.137
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/cloudflare-worker-agent-test",
-  "version": "0.0.137",
+  "version": "0.0.143",
   "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 +1,35 @@
 # @llamaindex/llama-parse-browser-test
 
+## 0.0.53
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.8
+
+## 0.0.52
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.7
+
+## 0.0.51
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.6
+
+## 0.0.50
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.5
+
+## 0.0.49
+
+### Patch Changes
+
+- @llamaindex/cloud@3.0.4
+
 ## 0.0.48
 
 ### Patch Changes

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

@@ -1,7 +1,7 @@
 {
   "name": "@llamaindex/llama-parse-browser-test",
   "private": true,
-  "version": "0.0.48",
+  "version": "0.0.53",
   "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 +1,44 @@
 # @llamaindex/next-agent-test
 
+## 0.1.143
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.1.142
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.1.141
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 0.1.140
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 0.1.139
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 0.1.138
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
 ## 0.1.137
 
 ### Patch Changes

e2e/examples/nextjs-agent/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-agent-test",
-  "version": "0.1.137",
+  "version": "0.1.143",
   "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 +1,44 @@
 # test-edge-runtime
 
+## 0.1.142
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.1.141
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.1.140
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 0.1.139
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 0.1.138
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 0.1.137
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
 ## 0.1.136
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/nextjs-edge-runtime-test",
-  "version": "0.1.136",
+  "version": "0.1.142",
   "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 +1,54 @@
 # @llamaindex/next-node-runtime
 
+## 0.1.9
+
+### Patch Changes
+
+- llamaindex@0.9.9
+- @llamaindex/huggingface@0.0.43
+- @llamaindex/readers@2.0.7
+
+## 0.1.8
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.1.7
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+  - @llamaindex/huggingface@0.0.42
+  - @llamaindex/readers@2.0.6
+
+## 0.1.6
+
+### Patch Changes
+
+- llamaindex@0.9.6
+- @llamaindex/huggingface@0.0.41
+- @llamaindex/readers@2.0.5
+
+## 0.1.5
+
+### Patch Changes
+
+- llamaindex@0.9.5
+- @llamaindex/huggingface@0.0.40
+- @llamaindex/readers@2.0.4
+
+## 0.1.4
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+  - @llamaindex/huggingface@0.0.39
+  - @llamaindex/readers@2.0.3
+
 ## 0.1.3
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/next-node-runtime-test",
-  "version": "0.1.3",
+  "version": "0.1.9",
   "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/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 +1,44 @@
 # vite-import-llamaindex
 
+## 0.0.9
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.0.8
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.0.7
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 0.0.6
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 0.0.5
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 0.0.4
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
 ## 0.0.3
 
 ### Patch Changes

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

@@ -1,7 +1,7 @@
 {
   "name": "vite-import-llamaindex",
   "private": true,
-  "version": "0.0.3",
+  "version": "0.0.9",
   "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 +1,45 @@
 # @llamaindex/waku-query-engine-test
 
+## 0.0.143
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 0.0.142
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 0.0.141
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - llamaindex@0.9.7
+
+## 0.0.140
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 0.0.139
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 0.0.138
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
 ## 0.0.137
 
 ### Patch Changes

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

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/waku-query-engine-test",
-  "version": "0.0.137",
+  "version": "0.0.143",
   "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/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 +1,223 @@
 # examples
 
+## 0.2.8
+
+### Patch Changes
+
+- Updated dependencies [58b3ee5]
+- Updated dependencies [4bac71d]
+- Updated dependencies [8bf1ca1]
+  - @llamaindex/google@0.1.0
+  - @llamaindex/core@0.5.7
+  - @llamaindex/anthropic@0.2.5
+  - @llamaindex/cloud@3.0.8
+  - llamaindex@0.9.9
+  - @llamaindex/node-parser@1.0.7
+  - @llamaindex/clip@0.0.43
+  - @llamaindex/cohere@0.0.12
+  - @llamaindex/deepinfra@0.0.43
+  - @llamaindex/huggingface@0.0.43
+  - @llamaindex/jinaai@0.0.3
+  - @llamaindex/mistral@0.0.12
+  - @llamaindex/mixedbread@0.0.12
+  - @llamaindex/ollama@0.0.47
+  - @llamaindex/openai@0.1.59
+  - @llamaindex/portkey-ai@0.0.40
+  - @llamaindex/replicate@0.0.40
+  - @llamaindex/astra@0.0.12
+  - @llamaindex/azure@0.1.7
+  - @llamaindex/chroma@0.0.12
+  - @llamaindex/firestore@1.0.5
+  - @llamaindex/milvus@0.1.7
+  - @llamaindex/mongodb@0.0.12
+  - @llamaindex/pinecone@0.0.12
+  - @llamaindex/postgres@0.0.40
+  - @llamaindex/qdrant@0.1.7
+  - @llamaindex/upstash@0.0.12
+  - @llamaindex/weaviate@0.0.12
+  - @llamaindex/vercel@0.0.18
+  - @llamaindex/voyage-ai@1.0.4
+  - @llamaindex/readers@2.0.7
+  - @llamaindex/workflow@0.0.15
+  - @llamaindex/deepseek@0.0.3
+  - @llamaindex/fireworks@0.0.3
+  - @llamaindex/groq@0.0.58
+  - @llamaindex/together@0.0.3
+  - @llamaindex/vllm@0.0.29
+
+## 0.2.7
+
+### Patch Changes
+
+- Updated dependencies [4b49428]
+- Updated dependencies [bbc8c87]
+- Updated dependencies [7ee4968]
+  - @llamaindex/workflow@0.0.14
+  - llamaindex@0.9.8
+  - @llamaindex/deepseek@0.0.2
+  - @llamaindex/fireworks@0.0.2
+  - @llamaindex/together@0.0.2
+  - @llamaindex/jinaai@0.0.2
+  - @llamaindex/google@0.0.14
+
+## 0.2.6
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - @llamaindex/env@0.1.29
+  - @llamaindex/core@0.5.6
+  - llamaindex@0.9.7
+  - @llamaindex/cloud@3.0.7
+  - @llamaindex/node-parser@1.0.6
+  - @llamaindex/anthropic@0.2.4
+  - @llamaindex/clip@0.0.42
+  - @llamaindex/cohere@0.0.11
+  - @llamaindex/deepinfra@0.0.42
+  - @llamaindex/google@0.0.13
+  - @llamaindex/groq@0.0.57
+  - @llamaindex/huggingface@0.0.42
+  - @llamaindex/mistral@0.0.11
+  - @llamaindex/mixedbread@0.0.11
+  - @llamaindex/ollama@0.0.46
+  - @llamaindex/openai@0.1.58
+  - @llamaindex/portkey-ai@0.0.39
+  - @llamaindex/replicate@0.0.39
+  - @llamaindex/astra@0.0.11
+  - @llamaindex/azure@0.1.6
+  - @llamaindex/chroma@0.0.11
+  - @llamaindex/firestore@1.0.4
+  - @llamaindex/milvus@0.1.6
+  - @llamaindex/mongodb@0.0.11
+  - @llamaindex/pinecone@0.0.11
+  - @llamaindex/postgres@0.0.39
+  - @llamaindex/qdrant@0.1.6
+  - @llamaindex/upstash@0.0.11
+  - @llamaindex/weaviate@0.0.11
+  - @llamaindex/voyage-ai@1.0.3
+  - @llamaindex/readers@2.0.6
+  - @llamaindex/workflow@0.0.13
+  - @llamaindex/vercel@0.0.17
+  - @llamaindex/vllm@0.0.28
+
+## 0.2.5
+
+### Patch Changes
+
+- Updated dependencies [5668970]
+- Updated dependencies [fd74ba4]
+  - @llamaindex/core@0.5.5
+  - @llamaindex/workflow@0.0.12
+  - @llamaindex/voyage-ai@1.0.2
+  - @llamaindex/cloud@3.0.6
+  - llamaindex@0.9.6
+  - @llamaindex/node-parser@1.0.5
+  - @llamaindex/anthropic@0.2.3
+  - @llamaindex/clip@0.0.41
+  - @llamaindex/cohere@0.0.10
+  - @llamaindex/deepinfra@0.0.41
+  - @llamaindex/google@0.0.12
+  - @llamaindex/huggingface@0.0.41
+  - @llamaindex/mistral@0.0.10
+  - @llamaindex/mixedbread@0.0.10
+  - @llamaindex/ollama@0.0.45
+  - @llamaindex/openai@0.1.57
+  - @llamaindex/portkey-ai@0.0.38
+  - @llamaindex/replicate@0.0.38
+  - @llamaindex/astra@0.0.10
+  - @llamaindex/azure@0.1.5
+  - @llamaindex/chroma@0.0.10
+  - @llamaindex/firestore@1.0.3
+  - @llamaindex/milvus@0.1.5
+  - @llamaindex/mongodb@0.0.10
+  - @llamaindex/pinecone@0.0.10
+  - @llamaindex/postgres@0.0.38
+  - @llamaindex/qdrant@0.1.5
+  - @llamaindex/upstash@0.0.10
+  - @llamaindex/weaviate@0.0.10
+  - @llamaindex/vercel@0.0.16
+  - @llamaindex/readers@2.0.5
+  - @llamaindex/groq@0.0.56
+  - @llamaindex/vllm@0.0.27
+
+## 0.2.4
+
+### Patch Changes
+
+- Updated dependencies [ad3c7f1]
+  - @llamaindex/core@0.5.4
+  - @llamaindex/cloud@3.0.5
+  - llamaindex@0.9.5
+  - @llamaindex/node-parser@1.0.4
+  - @llamaindex/anthropic@0.2.2
+  - @llamaindex/clip@0.0.40
+  - @llamaindex/cohere@0.0.9
+  - @llamaindex/deepinfra@0.0.40
+  - @llamaindex/google@0.0.11
+  - @llamaindex/huggingface@0.0.40
+  - @llamaindex/mistral@0.0.9
+  - @llamaindex/mixedbread@0.0.9
+  - @llamaindex/ollama@0.0.44
+  - @llamaindex/openai@0.1.56
+  - @llamaindex/portkey-ai@0.0.37
+  - @llamaindex/replicate@0.0.37
+  - @llamaindex/astra@0.0.9
+  - @llamaindex/azure@0.1.4
+  - @llamaindex/chroma@0.0.9
+  - @llamaindex/firestore@1.0.2
+  - @llamaindex/milvus@0.1.4
+  - @llamaindex/mongodb@0.0.9
+  - @llamaindex/pinecone@0.0.9
+  - @llamaindex/postgres@0.0.37
+  - @llamaindex/qdrant@0.1.4
+  - @llamaindex/upstash@0.0.9
+  - @llamaindex/weaviate@0.0.9
+  - @llamaindex/vercel@0.0.15
+  - @llamaindex/voyage-ai@1.0.1
+  - @llamaindex/readers@2.0.4
+  - @llamaindex/groq@0.0.55
+  - @llamaindex/vllm@0.0.26
+
+## 0.2.3
+
+### Patch Changes
+
+- Updated dependencies [cb256f2]
+- Updated dependencies [cb021e7]
+- Updated dependencies [0346391]
+  - @llamaindex/openai@0.1.55
+  - @llamaindex/core@0.5.3
+  - llamaindex@0.9.4
+  - @llamaindex/voyage-ai@1.0.0
+  - @llamaindex/clip@0.0.39
+  - @llamaindex/deepinfra@0.0.39
+  - @llamaindex/groq@0.0.54
+  - @llamaindex/huggingface@0.0.39
+  - @llamaindex/azure@0.1.3
+  - @llamaindex/milvus@0.1.3
+  - @llamaindex/qdrant@0.1.3
+  - @llamaindex/vllm@0.0.25
+  - @llamaindex/cloud@3.0.4
+  - @llamaindex/node-parser@1.0.3
+  - @llamaindex/anthropic@0.2.1
+  - @llamaindex/cohere@0.0.8
+  - @llamaindex/google@0.0.10
+  - @llamaindex/mistral@0.0.8
+  - @llamaindex/mixedbread@0.0.8
+  - @llamaindex/ollama@0.0.43
+  - @llamaindex/portkey-ai@0.0.36
+  - @llamaindex/replicate@0.0.36
+  - @llamaindex/astra@0.0.8
+  - @llamaindex/chroma@0.0.8
+  - @llamaindex/firestore@1.0.1
+  - @llamaindex/mongodb@0.0.8
+  - @llamaindex/pinecone@0.0.8
+  - @llamaindex/postgres@0.0.36
+  - @llamaindex/upstash@0.0.8
+  - @llamaindex/weaviate@0.0.8
+  - @llamaindex/vercel@0.0.14
+  - @llamaindex/readers@2.0.3
+
 ## 0.2.2
 
 ### 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 { AgentWorkflow, FunctionTool } 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 = AgentWorkflow.fromTools({
     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 { AgentWorkflow, FunctionTool } 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 = AgentWorkflow.fromTools({
     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

@@ -1,4 +1,5 @@
 import { FunctionTool } from "llamaindex";
+import { z } from "zod";
 
 export const getCurrentIDTool = FunctionTool.from(
   () => {
@@ -19,16 +20,9 @@ export const getUserInfoTool = FunctionTool.from(
   {
     name: "get_user_info",
     description: "Get user info",
-    parameters: {
-      type: "object",
-      properties: {
-        userId: {
-          type: "string",
-          description: "The user id",
-        },
-      },
-      required: ["userId"],
-    },
+    parameters: z.object({
+      userId: z.string().describe("The user id"),
+    }),
   },
 );
 
@@ -40,15 +34,8 @@ export const getWeatherTool = FunctionTool.from(
   {
     name: "get_weather",
     description: "Get the current weather for a location",
-    parameters: {
-      type: "object",
-      properties: {
-        address: {
-          type: "string",
-          description: "The address",
-        },
-      },
-      required: ["address"],
-    },
+    parameters: z.object({
+      address: z.string().describe("The address"),
+    }),
   },
 );

examples/agent/wiki.ts

@@ -1,24 +1,28 @@
-import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
+import { OpenAI } from "@llamaindex/openai";
+import { AgentStream, AgentWorkflow } 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 = AgentWorkflow.fromTools({
     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);
+    }
   }
 }
 

examples/agentworkflow/blog_writer.ts

@@ -0,0 +1,83 @@
+import { OpenAI } from "@llamaindex/openai";
+import fs from "fs";
+import {
+  AgentToolCall,
+  AgentToolCallResult,
+  AgentWorkflow,
+  FunctionAgent,
+  FunctionTool,
+} from "llamaindex";
+import os from "os";
+import { z } from "zod";
+
+import { WikipediaTool } from "../wiki";
+const llm = new OpenAI({
+  model: "gpt-4o-mini",
+});
+
+const saveFileTool = FunctionTool.from(
+  ({ content }: { content: string }) => {
+    const filePath = os.tmpdir() + "/report.md";
+    fs.writeFileSync(filePath, content);
+    return `File saved successfully at ${filePath}`;
+  },
+  {
+    name: "saveFile",
+    description:
+      "Save the written content into a file that can be downloaded by the user",
+    parameters: z.object({
+      content: z.string({
+        description: "The content to save into a file",
+      }),
+    }),
+  },
+);
+
+async function main() {
+  const reportAgent = new FunctionAgent({
+    name: "ReportAgent",
+    description:
+      "Responsible for crafting well-written blog posts based on research findings",
+    systemPrompt: `You are a professional writer. Your task is to create an engaging blog post using the research content provided. Once complete, save the post to a file using the saveFile tool.`,
+    tools: [saveFileTool],
+    llm,
+  });
+
+  const researchAgent = new FunctionAgent({
+    name: "ResearchAgent",
+    description:
+      "Responsible for gathering relevant information from the internet",
+    systemPrompt: `You are a research agent. Your role is to gather information from the internet using the provided tools and then transfer this information to the report agent for content creation.`,
+    tools: [new WikipediaTool()],
+    canHandoffTo: [reportAgent],
+    llm,
+  });
+
+  const workflow = new AgentWorkflow({
+    agents: [researchAgent, reportAgent],
+    rootAgent: researchAgent,
+  });
+
+  const context = workflow.run("Write a blog post about history of LLM");
+
+  let finalResult;
+  for await (const event of context) {
+    if (event instanceof AgentToolCall) {
+      console.log(
+        `[Agent ${event.displayName}] executing tool ${event.data.toolName} with parameters ${JSON.stringify(
+          event.data.toolKwargs,
+        )}`,
+      );
+    } else if (event instanceof AgentToolCallResult) {
+      console.log(
+        `[Agent ${event.displayName}] executed tool ${event.data.toolName} with result ${event.data.toolOutput.result}`,
+      );
+    }
+    finalResult = event;
+  }
+  console.log("Final result:", finalResult?.data);
+}
+
+main().catch((error) => {
+  console.error("Error:", error);
+});

examples/agentworkflow/multiple_agents.ts

@@ -0,0 +1,110 @@
+/**
+ * This example shows how to use AgentWorkflow with multiple agents
+ * 1. FetchWeatherAgent - Fetches the weather in a city
+ * 2. TemperatureConverterAgent - Converts the temperature from Fahrenheit to Celsius
+ */
+import { OpenAI } from "@llamaindex/openai";
+import { StopEvent } from "@llamaindex/workflow";
+import {
+  AgentInput,
+  AgentOutput,
+  AgentStream,
+  AgentToolCall,
+  AgentToolCallResult,
+  AgentWorkflow,
+  FunctionAgent,
+  FunctionTool,
+} from "llamaindex";
+import { z } from "zod";
+
+const llm = new OpenAI({
+  model: "gpt-4o-mini",
+});
+
+// Define tools for the agents
+const temperatureConverterTool = FunctionTool.from(
+  ({ temperature }: { temperature: number }) => {
+    return ((temperature - 32) * 5) / 9;
+  },
+  {
+    description: "Convert a temperature from Fahrenheit to Celsius",
+    name: "fahrenheitToCelsius",
+    parameters: z.object({
+      temperature: z.number({
+        description: "The temperature in Fahrenheit",
+      }),
+    }),
+  },
+);
+
+const temperatureFetcherTool = FunctionTool.from(
+  ({ city }: { city: string }) => {
+    const temperature = Math.floor(Math.random() * 58) + 32;
+    return `The current temperature in ${city} is ${temperature}°F`;
+  },
+  {
+    description: "Fetch the temperature (in Fahrenheit) for a city",
+    name: "fetchTemperature",
+    parameters: z.object({
+      city: z.string({
+        description: "The city to fetch the temperature for",
+      }),
+    }),
+  },
+);
+
+// Create agents
+async function multiWeatherAgent() {
+  const converterAgent = new FunctionAgent({
+    name: "TemperatureConverterAgent",
+    description:
+      "An agent that can convert temperatures from Fahrenheit to Celsius.",
+    tools: [temperatureConverterTool],
+    llm,
+  });
+
+  const weatherAgent = new FunctionAgent({
+    name: "FetchWeatherAgent",
+    description: "An agent that can get the weather in a city. ",
+    systemPrompt:
+      "If you can't answer the user question, hand off to other agents.",
+    tools: [temperatureFetcherTool],
+    llm,
+    // Define which next agents can be called next if this agent cannot complete the task
+    // Can be passed as agent name, e.g. "TemperatureConverterAgent"
+    canHandoffTo: [converterAgent],
+  });
+
+  // Create agent workflow with the agents
+  const workflow = new AgentWorkflow({
+    agents: [weatherAgent, converterAgent],
+    rootAgent: weatherAgent,
+    verbose: false,
+  });
+
+  // Ask the agent to get the weather in a city
+  const context = workflow.run(
+    "What is the weather in San Francisco in Celsius?",
+  );
+  // Stream the events
+  for await (const event of context) {
+    // These events might be useful for UI
+    if (
+      event instanceof AgentToolCall ||
+      event instanceof AgentToolCallResult ||
+      event instanceof AgentOutput ||
+      event instanceof AgentInput ||
+      event instanceof StopEvent
+    ) {
+      console.log(event);
+    } else if (event instanceof AgentStream) {
+      for (const chunk of event.data.delta) {
+        process.stdout.write(chunk);
+      }
+    }
+  }
+}
+
+multiWeatherAgent().catch((error) => {
+  console.error("Error:", error);
+});

examples/agentworkflow/single_agent.ts

@@ -0,0 +1,37 @@
+/**
+ * This example shows how to use AgentWorkflow as a single agent with tools
+ */
+import { OpenAI } from "@llamaindex/openai";
+import { AgentWorkflow } from "llamaindex";
+import { getWeatherTool } from "../agent/utils/tools";
+
+const llm = new OpenAI({
+  model: "gpt-4o",
+});
+
+async function singleWeatherAgent() {
+  const workflow = AgentWorkflow.fromTools({
+    tools: [getWeatherTool],
+    llm,
+    verbose: false,
+  });
+
+  const workflowContext = workflow.run(
+    "What's the weather like in San Francisco?",
+  );
+  const sfResult = await workflowContext;
+  // The weather in San Francisco, CA is currently sunny.
+  console.log(`${JSON.stringify(sfResult, null, 2)}`);
+
+  // Reuse the context from the previous run
+  const workflowContext2 = workflow.run("Compare it with California?", {
+    context: workflowContext.data,
+  });
+  const caResult = await workflowContext2;
+  // Both San Francisco and California are currently experiencing sunny weather.
+  console.log(`${JSON.stringify(caResult, null, 2)}`);
+}
+
+singleWeatherAgent().catch((error) => {
+  console.error("Error:", error);
+});

examples/agentworkflow/with-anthropic.ts

@@ -0,0 +1,114 @@
+import fs from "fs";
+import {
+  AgentToolCall,
+  AgentToolCallResult,
+  AgentWorkflow,
+  FunctionAgent,
+  FunctionTool,
+} from "llamaindex";
+import { z } from "zod";
+
+import { Anthropic } from "@llamaindex/anthropic";
+
+const llm = new Anthropic({
+  model: "claude-3-5-sonnet",
+});
+
+const weatherTool = FunctionTool.from(
+  (query: { location: string }) => {
+    return `The weather in ${query.location} is sunny`;
+  },
+  {
+    name: "weather",
+    description: "Get the weather",
+    parameters: z.object({
+      location: z.string({
+        description: "The location to get the weather for",
+      }),
+    }),
+  },
+);
+
+const inflationTool = FunctionTool.from(
+  (query: { location: string }) => {
+    return `The inflation in ${query.location} is 2%`;
+  },
+  {
+    name: "inflation",
+    description: "Get the inflation",
+    parameters: z.object({
+      location: z.string({
+        description: "The location to get the inflation for",
+      }),
+    }),
+  },
+);
+
+const saveFileTool = FunctionTool.from(
+  ({ content }: { content: string }) => {
+    const filePath = "./report.md";
+    fs.writeFileSync(filePath, content);
+    return `File saved successfully at ${filePath}`;
+  },
+  {
+    name: "saveFile",
+    description:
+      "Save the written content into a file that can be downloaded by the user",
+    parameters: z.object({
+      content: z.string({
+        description: "The content to save into a file",
+      }),
+    }),
+  },
+);
+
+async function main() {
+  const reportAgent = new FunctionAgent({
+    name: "ReportAgent",
+    description:
+      "Responsible for creating concise reports about weather and inflation data",
+    systemPrompt: `You are a professional writer. Your task is to create a clear and concise report summarizing the weather and inflation data provided. Once complete, save the report to a file using the saveFile tool.`,
+    tools: [saveFileTool],
+    llm,
+  });
+
+  const researchAgent = new FunctionAgent({
+    name: "ResearchAgent",
+    description:
+      "Responsible for gathering relevant information from the internet",
+    systemPrompt: `You are a research agent. Your role is to gather information about the inflation and weather in the location provided.`,
+    tools: [inflationTool, weatherTool],
+    canHandoffTo: [reportAgent],
+    llm,
+  });
+
+  const workflow = new AgentWorkflow({
+    agents: [researchAgent, reportAgent],
+    rootAgent: researchAgent,
+  });
+
+  const context = workflow.run(
+    "Write a report about New York weather and inflation",
+  );
+
+  let finalResult;
+  for await (const event of context) {
+    if (event instanceof AgentToolCall) {
+      console.log(
+        `[Agent ${event.displayName}] executing tool ${event.data.toolName} with parameters ${JSON.stringify(
+          event.data.toolKwargs,
+        )}`,
+      );
+    } else if (event instanceof AgentToolCallResult) {
+      console.log(
+        `[Agent ${event.displayName}] executed tool ${event.data.toolName} with result ${event.data.toolOutput.result}`,
+      );
+    }
+    finalResult = event;
+  }
+  console.log("Final result:", finalResult?.data);
+}
+
+main().catch((error) => {
+  console.error("Error:", error);
+});

examples/anthropic/agent.ts

@@ -1,5 +1,6 @@
 import { Anthropic, AnthropicAgent } from "@llamaindex/anthropic";
 import { FunctionTool, Settings } from "llamaindex";
+import { z } from "zod";
 import { WikipediaTool } from "../wiki";
 
 Settings.callbackManager.on("llm-tool-call", (event) => {
@@ -14,23 +15,16 @@ const anthropic = new Anthropic({
 const agent = new AnthropicAgent({
   llm: anthropic,
   tools: [
-    FunctionTool.from<{ location: string }>(
+    FunctionTool.from(
       (query) => {
         return `The weather in ${query.location} is sunny`;
       },
       {
         name: "weather",
         description: "Get the weather",
-        parameters: {
-          type: "object",
-          properties: {
-            location: {
-              type: "string",
-              description: "The location to get the weather for",
-            },
-          },
-          required: ["location"],
-        },
+        parameters: z.object({
+          location: z.string().describe("The location to get the weather for"),
+        }),
       },
     ),
     new WikipediaTool(),

examples/chat-engine/streaming.ts

@@ -0,0 +1,25 @@
+import { LLMAgent } from "llamaindex";
+import { stdin as input, stdout as output } from "node:process";
+import readline from "node:readline/promises";
+
+const agent = new LLMAgent({ tools: [] });
+
+(async () => {
+  const rl = readline.createInterface({ input, output });
+
+  while (true) {
+    const query = await rl.question("User: ");
+
+    const startTime = Date.now();
+    const stream = await agent.chat({ message: query, stream: true });
+    const timeToGetFirstChunk = Date.now() - startTime;
+    process.stdout.write(
+      `Time to get first chunk from LLMAgent: ${timeToGetFirstChunk}ms\n`,
+    );
+    process.stdout.write("Assistant with LLMAgent: ");
+    for await (const chunk of stream) {
+      process.stdout.write(chunk.response);
+    }
+    process.stdout.write("\n");
+  }
+})();

examples/deepseek.ts

@@ -0,0 +1,46 @@
+import { DeepSeekLLM } from "@llamaindex/deepseek";
+
+// process.env.DEEPSEEK_API_KEY is required
+const deepseek = new DeepSeekLLM({
+  apiKey: process.env.DEEPSEEK_API_KEY,
+  model: "deepseek-coder", // or "deepseek-chat"
+});
+
+(async () => {
+  // Example of non-streaming chat
+  const response = await deepseek.chat({
+    messages: [
+      {
+        role: "system",
+        content: "You are an AI assistant",
+      },
+      {
+        role: "user",
+        content: "Tell me about San Francisco",
+      },
+    ],
+    stream: false,
+  });
+  console.log("Response from DeepSeek AI:");
+  console.log(response);
+
+  // Example of streaming chat
+  const generator = await deepseek.chat({
+    messages: [
+      {
+        role: "system",
+        content: "You are an AI assistant",
+      },
+      {
+        role: "user",
+        content: "Write a short poem about San Francisco",
+      },
+    ],
+    stream: true,
+  });
+  console.log("\nStreaming response from DeepSeek AI...");
+  for await (const message of generator) {
+    process.stdout.write(message.delta);
+  }
+  console.log("\n");
+})();

examples/gemini/agent.ts

@@ -1,5 +1,6 @@
 import { Gemini, GEMINI_MODEL } from "@llamaindex/google";
 import { FunctionTool, LLMAgent, Settings } from "llamaindex";
+import { z } from "zod";
 
 Settings.callbackManager.on("llm-tool-call", (event) => {
   console.log(event.detail);
@@ -14,20 +15,10 @@ const sumNumbers = FunctionTool.from(
   {
     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"),
+    }),
   },
 );
 
@@ -36,20 +27,10 @@ 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"),
+    }),
   },
 );
 
@@ -58,20 +39,10 @@ const subtractNumbers = FunctionTool.from(
   {
     name: "subtractNumbers",
     description: "Use this function to subtract two numbers",
-    parameters: {
-      type: "object",
-      properties: {
-        a: {
-          type: "number",
-          description: "The number to subtract from",
-        },
-        b: {
-          type: "number",
-          description: "The number to subtract",
-        },
-      },
-      required: ["a", "b"],
-    },
+    parameters: z.object({
+      a: z.number().describe("The number to subtract from"),
+      b: z.number().describe("The number to subtract"),
+    }),
   },
 );
 

examples/multimodal/jina.ts

@@ -1,10 +1,6 @@
+import { JinaAIEmbedding } from "@llamaindex/jinaai";
 import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
-import {
-  ImageDocument,
-  JinaAIEmbedding,
-  similarity,
-  SimilarityType,
-} from "llamaindex";
+import { ImageDocument, similarity, SimilarityType } from "llamaindex";
 import path from "path";
 
 async function main() {

examples/openai.ts

@@ -1,7 +1,7 @@
 import { OpenAI, OpenAIEmbedding } from "@llamaindex/openai";
 
 (async () => {
-  const llm = new OpenAI({ model: "gpt-4-1106-preview", temperature: 0.1 });
+  const llm = new OpenAI({ model: "gpt-4.5-preview", temperature: 0.1 });
 
   // complete api
   const response1 = await llm.complete({ prompt: "How are you?" });

examples/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@llamaindex/examples",
-  "version": "0.2.2",
+  "version": "0.2.8",
   "private": true,
   "scripts": {
     "lint": "eslint .",
@@ -11,38 +11,43 @@
     "@azure/cosmos": "^4.1.1",
     "@azure/identity": "^4.4.1",
     "@azure/search-documents": "^12.1.0",
-    "@llamaindex/anthropic": "^0.2.0",
-    "@llamaindex/astra": "^0.0.7",
-    "@llamaindex/azure": "^0.1.2",
-    "@llamaindex/chroma": "^0.0.7",
-    "@llamaindex/clip": "^0.0.38",
-    "@llamaindex/cloud": "^3.0.3",
-    "@llamaindex/cohere": "^0.0.7",
-    "@llamaindex/core": "^0.5.2",
-    "@llamaindex/deepinfra": "^0.0.38",
-    "@llamaindex/env": "^0.1.28",
-    "@llamaindex/firestore": "^1.0.0",
-    "@llamaindex/google": "^0.0.9",
-    "@llamaindex/groq": "^0.0.53",
-    "@llamaindex/huggingface": "^0.0.38",
-    "@llamaindex/milvus": "^0.1.2",
-    "@llamaindex/mistral": "^0.0.7",
-    "@llamaindex/mixedbread": "^0.0.7",
-    "@llamaindex/mongodb": "^0.0.7",
-    "@llamaindex/node-parser": "^1.0.2",
-    "@llamaindex/ollama": "^0.0.42",
-    "@llamaindex/openai": "^0.1.54",
-    "@llamaindex/pinecone": "^0.0.7",
-    "@llamaindex/portkey-ai": "^0.0.35",
-    "@llamaindex/postgres": "^0.0.35",
-    "@llamaindex/qdrant": "^0.1.2",
-    "@llamaindex/readers": "^2.0.2",
-    "@llamaindex/replicate": "^0.0.35",
-    "@llamaindex/upstash": "^0.0.7",
-    "@llamaindex/vercel": "^0.0.13",
-    "@llamaindex/vllm": "^0.0.24",
-    "@llamaindex/weaviate": "^0.0.7",
-    "@llamaindex/workflow": "^0.0.11",
+    "@llamaindex/anthropic": "^0.2.5",
+    "@llamaindex/astra": "^0.0.12",
+    "@llamaindex/azure": "^0.1.7",
+    "@llamaindex/chroma": "^0.0.12",
+    "@llamaindex/clip": "^0.0.43",
+    "@llamaindex/cloud": "^3.0.8",
+    "@llamaindex/cohere": "^0.0.12",
+    "@llamaindex/core": "^0.5.7",
+    "@llamaindex/deepinfra": "^0.0.43",
+    "@llamaindex/env": "^0.1.29",
+    "@llamaindex/firestore": "^1.0.5",
+    "@llamaindex/google": "^0.1.0",
+    "@llamaindex/groq": "^0.0.58",
+    "@llamaindex/huggingface": "^0.0.43",
+    "@llamaindex/milvus": "^0.1.7",
+    "@llamaindex/mistral": "^0.0.12",
+    "@llamaindex/mixedbread": "^0.0.12",
+    "@llamaindex/mongodb": "^0.0.12",
+    "@llamaindex/node-parser": "^1.0.7",
+    "@llamaindex/ollama": "^0.0.47",
+    "@llamaindex/openai": "^0.1.59",
+    "@llamaindex/pinecone": "^0.0.12",
+    "@llamaindex/portkey-ai": "^0.0.40",
+    "@llamaindex/postgres": "^0.0.40",
+    "@llamaindex/qdrant": "^0.1.7",
+    "@llamaindex/readers": "^2.0.7",
+    "@llamaindex/replicate": "^0.0.40",
+    "@llamaindex/upstash": "^0.0.12",
+    "@llamaindex/vercel": "^0.0.18",
+    "@llamaindex/vllm": "^0.0.29",
+    "@llamaindex/voyage-ai": "^1.0.4",
+    "@llamaindex/weaviate": "^0.0.12",
+    "@llamaindex/workflow": "^0.0.15",
+    "@llamaindex/deepseek": "^0.0.3",
+    "@llamaindex/fireworks": "^0.0.3",
+    "@llamaindex/together": "^0.0.3",
+    "@llamaindex/jinaai": "^0.0.3",
     "@notionhq/client": "^2.2.15",
     "@pinecone-database/pinecone": "^4.0.0",
     "@vercel/postgres": "^0.10.0",
@@ -51,16 +56,16 @@
     "commander": "^12.1.0",
     "dotenv": "^16.4.5",
     "js-tiktoken": "^1.0.14",
-    "llamaindex": "^0.9.3",
+    "llamaindex": "^0.9.9",
     "mongodb": "6.7.0",
-    "pathe": "^1.1.2",
     "postgres": "^3.4.4",
-    "wikipedia": "^2.1.2"
+    "wikipedia": "^2.1.2",
+    "zod": "^3.23.8"
   },
   "devDependencies": {
     "@types/node": "^22.9.0",
-    "tsx": "^4.19.0",
-    "typescript": "^5.7.2"
+    "tsx": "^4.19.3",
+    "typescript": "^5.7.3"
   },
   "stackblitz": {
     "startCommand": "npm start"

examples/qdrantdb/with-gemini.ts

@@ -0,0 +1,33 @@
+import {
+  GEMINI_EMBEDDING_MODEL,
+  GeminiEmbedding,
+  GeminiSession,
+} from "@llamaindex/google";
+import { QdrantVectorStore } from "@llamaindex/qdrant";
+import {
+  Document,
+  storageContextFromDefaults,
+  VectorStoreIndex,
+} from "llamaindex";
+
+const embedding = new GeminiEmbedding({
+  model: GEMINI_EMBEDDING_MODEL.EMBEDDING_001,
+  session: new GeminiSession({
+    apiKey: process.env.GEMINI_API_KEY,
+  }),
+});
+
+async function main() {
+  const docs = [new Document({ text: "Lorem ipsum dolor sit amet" })];
+  const vectorStore = new QdrantVectorStore({
+    url: process.env.QDRANT_URL,
+    apiKey: process.env.QDRANT_API_KEY,
+    embeddingModel: embedding,
+    collectionName: "gemini_test",
+  });
+  const storageContext = await storageContextFromDefaults({ vectorStore });
+  await VectorStoreIndex.fromDocuments(docs, { storageContext });
+  console.log("Inizialized vector store successfully");
+}
+
+void main().catch((err) => console.error(err));

examples/qdrantdb/with-jina.ts

@@ -0,0 +1,27 @@
+import { JinaAIEmbedding } from "@llamaindex/jinaai";
+import { QdrantVectorStore } from "@llamaindex/qdrant";
+import {
+  Document,
+  storageContextFromDefaults,
+  VectorStoreIndex,
+} from "llamaindex";
+
+const embedding = new JinaAIEmbedding({
+  apiKey: process.env.JINAAI_API_KEY,
+  model: "jina-embeddings-v3",
+});
+
+async function main() {
+  const docs = [new Document({ text: "Lorem ipsum dolor sit amet" })];
+  const vectorStore = new QdrantVectorStore({
+    url: process.env.QDRANT_URL,
+    apiKey: process.env.QDRANT_API_KEY,
+    embeddingModel: embedding,
+    collectionName: "jina_test",
+  });
+  const storageContext = await storageContextFromDefaults({ vectorStore });
+  await VectorStoreIndex.fromDocuments(docs, { storageContext });
+  console.log("Inizialized vector store successfully");
+}
+
+void main().catch((err) => console.error(err));

examples/readers/package.json

@@ -25,7 +25,7 @@
   },
   "devDependencies": {
     "@types/node": "^22.9.0",
-    "tsx": "^4.19.0",
-    "typescript": "^5.7.2"
+    "tsx": "^4.19.3",
+    "typescript": "^5.7.3"
   }
 }

examples/readers/src/pdf_fw.ts

@@ -1,5 +1,6 @@
+import { FireworksEmbedding, FireworksLLM } from "@llamaindex/fireworks";
 import { PDFReader } from "@llamaindex/readers/pdf";
-import { FireworksEmbedding, FireworksLLM, VectorStoreIndex } from "llamaindex";
+import { VectorStoreIndex } from "llamaindex";
 
 import { Settings } from "llamaindex";
 

examples/together-ai.ts

@@ -1,4 +1,4 @@
-import { TogetherEmbedding, TogetherLLM } from "llamaindex";
+import { TogetherEmbedding, TogetherLLM } from "@llamaindex/together";
 
 // process.env.TOGETHER_API_KEY is required
 const together = new TogetherLLM({

examples/together-ai/vector-index.ts

@@ -1,12 +1,7 @@
 import fs from "node:fs/promises";
 
-import {
-  Document,
-  Settings,
-  TogetherEmbedding,
-  TogetherLLM,
-  VectorStoreIndex,
-} from "llamaindex";
+import { TogetherEmbedding, TogetherLLM } from "@llamaindex/together";
+import { Document, Settings, VectorStoreIndex } from "llamaindex";
 
 // Update llm to use TogetherAI
 Settings.llm = new TogetherLLM({

examples/toolsStream.ts

@@ -15,7 +15,7 @@ async function main() {
     tools: [
       {
         metadata: {
-          name: "wikipedia_tool",
+          name: "wikipedia_search",
           description: "A tool that uses a query engine to search Wikipedia.",
           parameters: {
             type: "object",

examples/voyage-ai/embedding.ts

@@ -0,0 +1,17 @@
+import { VoyageAIEmbedding } from "@llamaindex/voyage-ai";
+
+async function main() {
+  // API token can be provided as an environment variable too
+  // using VOYAGE_API_TOKEN variable
+  const apiKey = process.env.VOYAGE_API_TOKEN ?? "YOUR_API_TOKEN";
+  const model = "voyage-3-lite";
+  const embedModel = new VoyageAIEmbedding({
+    model,
+    apiKey,
+  });
+  const texts = ["hello", "world"];
+  const embeddings = await embedModel.getTextEmbeddingsBatch(texts);
+  console.log(`\nWe have ${embeddings.length} embeddings`);
+}
+
+main().catch(console.error);

examples/wiki.ts

@@ -14,7 +14,7 @@ type WikipediaToolParams = {
 };
 
 const DEFAULT_META_DATA: ToolMetadata<JSONSchemaType<WikipediaParameter>> = {
-  name: "wikipedia_tool",
+  name: "wikipedia_search",
   description: "A tool that uses a query engine to search Wikipedia.",
   parameters: {
     type: "object",

package.json

@@ -21,7 +21,7 @@
   },
   "devDependencies": {
     "@changesets/cli": "^2.27.5",
-    "eslint": "9.16.0",
+    "eslint": "9.22.0",
     "eslint-config-next": "^15.1.0",
     "eslint-config-prettier": "^9.1.0",
     "eslint-config-turbo": "^2.3.3",
@@ -32,8 +32,8 @@
     "madge": "^8.0.0",
     "prettier": "^3.4.2",
     "prettier-plugin-organize-imports": "^4.1.0",
-    "turbo": "^2.3.3",
-    "typescript": "^5.7.2",
+    "turbo": "^2.4.4",
+    "typescript": "^5.7.3",
     "typescript-eslint": "^8.18.0"
   },
   "packageManager": "pnpm@9.12.3",

packages/autotool/CHANGELOG.md

@@ -1,5 +1,44 @@
 # @llamaindex/autotool
 
+## 6.0.9
+
+### Patch Changes
+
+- llamaindex@0.9.9
+
+## 6.0.8
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+
+## 6.0.7
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+
+## 6.0.6
+
+### Patch Changes
+
+- llamaindex@0.9.6
+
+## 6.0.5
+
+### Patch Changes
+
+- llamaindex@0.9.5
+
+## 6.0.4
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+
 ## 6.0.3
 
 ### Patch Changes

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

@@ -1,5 +1,50 @@
 # @llamaindex/autotool-01-node-example
 
+## 0.0.90
+
+### Patch Changes
+
+- llamaindex@0.9.9
+- @llamaindex/autotool@6.0.9
+
+## 0.0.89
+
+### Patch Changes
+
+- Updated dependencies [bbc8c87]
+  - llamaindex@0.9.8
+  - @llamaindex/autotool@6.0.8
+
+## 0.0.88
+
+### Patch Changes
+
+- Updated dependencies [beb922b]
+  - llamaindex@0.9.7
+  - @llamaindex/autotool@6.0.7
+
+## 0.0.87
+
+### Patch Changes
+
+- llamaindex@0.9.6
+- @llamaindex/autotool@6.0.6
+
+## 0.0.86
+
+### Patch Changes
+
+- llamaindex@0.9.5
+- @llamaindex/autotool@6.0.5
+
+## 0.0.85
+
+### Patch Changes
+
+- Updated dependencies [cb021e7]
+  - llamaindex@0.9.4
+  - @llamaindex/autotool@6.0.4
+
 ## 0.0.84
 
 ### Patch Changes

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

@@ -8,10 +8,10 @@
     "openai": "^4.73.1"
   },
   "devDependencies": {
-    "tsx": "^4.19.0"
+    "tsx": "^4.19.3"
   },
   "scripts": {
     "start": "node --import tsx --import @llamaindex/autotool/node ./src/index.ts"
   },
-  "version": "0.0.84"
+  "version": "0.0.90"
 }

packages/autotool/examples/02_nextjs/.env.example

@@ -1,3 +0,0 @@
-# Rename this file to `.env.local` to use environment variables locally with `next dev`
-# https://nextjs.org/docs/pages/building-your-application/configuring/environment-variables
-MY_HOST="example.com"

packages/autotool/examples/02_nextjs/.gitignore

@@ -1,35 +0,0 @@
-# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
-
-# dependencies
-/node_modules
-/.pnp
-.pnp.js
-
-# testing
-/coverage
-
-# next.js
-/.next/
-/out/
-
-# production
-/build
-
-# misc
-.DS_Store
-*.pem
-
-# debug
-npm-debug.log*
-yarn-debug.log*
-yarn-error.log*
-
-# local env files
-.env*.local
-
-# vercel
-.vercel
-
-# typescript
-*.tsbuildinfo
-next-env.d.ts

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

@@ -1,30 +0,0 @@
-This is a [LlamaIndex](https://www.llamaindex.ai/) project using [Next.js](https://nextjs.org/) bootstrapped with [`create-llama`](https://github.com/run-llama/LlamaIndexTS/tree/main/packages/create-llama).
-
-## Getting Started
-
-First, install the dependencies:
-
-```
-npm install
-```
-
-Second, run the development server:
-
-```
-npm run dev
-```
-
-Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.
-
-You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file.
-
-This project uses [`next/font`](https://nextjs.org/docs/basic-features/font-optimization) to automatically optimize and load Inter, a custom Google Font.
-
-## Learn More
-
-To learn more about LlamaIndex, take a look at the following resources:
-
-- [LlamaIndex Documentation](https://docs.llamaindex.ai) - learn about LlamaIndex (Python features).
-- [LlamaIndexTS Documentation](https://ts.llamaindex.ai) - learn about LlamaIndex (Typescript features).
-
-You can check out [the LlamaIndexTS GitHub repository](https://github.com/run-llama/LlamaIndexTS) - your feedback and contributions are welcome!

packages/autotool/examples/02_nextjs/actions.ts

@@ -1,38 +0,0 @@
-"use server";
-import { OpenAIAgent } from "llamaindex";
-// import your tools on top, that's it
-import { runWithStreamableUI } from "@/context";
-import "@/tool";
-import { convertTools } from "@llamaindex/autotool";
-import { createStreamableUI } from "ai/rsc";
-import type { ReactNode } from "react";
-
-export async function chatWithAI(message: string): Promise<ReactNode> {
-  const agent = new OpenAIAgent({
-    tools: convertTools("llamaindex"),
-  });
-  const uiStream = createStreamableUI();
-  runWithStreamableUI(uiStream, () =>
-    agent
-      .chat({
-        stream: true,
-        message,
-      })
-      .then(async (responseStream) => {
-        return responseStream.pipeTo(
-          new WritableStream({
-            start: () => {
-              uiStream.append("\n");
-            },
-            write: async (message) => {
-              uiStream.append(message.response);
-            },
-            close: () => {
-              uiStream.done();
-            },
-          }),
-        );
-      }),
-  ).catch(uiStream.error);
-  return uiStream.value;
-}

packages/autotool/examples/02_nextjs/app/globals.css

@@ -1,91 +0,0 @@
-@tailwind base;
-@tailwind components;
-@tailwind utilities;
-
-@layer base {
-  :root {
-    --background: 0 0% 100%;
-    --foreground: 222.2 47.4% 11.2%;
-
-    --muted: 210 40% 96.1%;
-    --muted-foreground: 215.4 16.3% 46.9%;
-
-    --popover: 0 0% 100%;
-    --popover-foreground: 222.2 47.4% 11.2%;
-
-    --border: 214.3 31.8% 91.4%;
-    --input: 214.3 31.8% 91.4%;
-
-    --card: 0 0% 100%;
-    --card-foreground: 222.2 47.4% 11.2%;
-
-    --primary: 222.2 47.4% 11.2%;
-    --primary-foreground: 210 40% 98%;
-
-    --secondary: 210 40% 96.1%;
-    --secondary-foreground: 222.2 47.4% 11.2%;
-
-    --accent: 210 40% 96.1%;
-    --accent-foreground: 222.2 47.4% 11.2%;
-
-    --destructive: 0 100% 50%;
-    --destructive-foreground: 210 40% 98%;
-
-    --ring: 215 20.2% 65.1%;
-
-    --radius: 0.5rem;
-  }
-
-  .dark {
-    --background: 224 71% 4%;
-    --foreground: 213 31% 91%;
-
-    --muted: 223 47% 11%;
-    --muted-foreground: 215.4 16.3% 56.9%;
-
-    --accent: 216 34% 17%;
-    --accent-foreground: 210 40% 98%;
-
-    --popover: 224 71% 4%;
-    --popover-foreground: 215 20.2% 65.1%;
-
-    --border: 216 34% 17%;
-    --input: 216 34% 17%;
-
-    --card: 224 71% 4%;
-    --card-foreground: 213 31% 91%;
-
-    --primary: 210 40% 98%;
-    --primary-foreground: 222.2 47.4% 1.2%;
-
-    --secondary: 222.2 47.4% 11.2%;
-    --secondary-foreground: 210 40% 98%;
-
-    --destructive: 0 63% 31%;
-    --destructive-foreground: 210 40% 98%;
-
-    --ring: 216 34% 17%;
-
-    --radius: 0.5rem;
-  }
-}
-
-@layer base {
-  * {
-    @apply border-border;
-  }
-  body {
-    @apply bg-background text-foreground;
-    font-feature-settings:
-      "rlig" 1,
-      "calt" 1;
-  }
-  .background-gradient {
-    background-color: #fff;
-    background-image:
-      radial-gradient(at 21% 11%, rgba(186, 186, 233, 0.53) 0, transparent 50%),
-      radial-gradient(at 85% 0, hsla(46, 57%, 78%, 0.52) 0, transparent 50%),
-      radial-gradient(at 91% 36%, rgba(194, 213, 255, 0.68) 0, transparent 50%),
-      radial-gradient(at 8% 40%, rgba(251, 218, 239, 0.46) 0, transparent 50%);
-  }
-}

packages/autotool/examples/02_nextjs/app/layout.tsx

@@ -1,26 +0,0 @@
-import type { Metadata } from "next";
-import { Inter } from "next/font/google";
-import { Toaster } from "sonner";
-import "./globals.css";
-
-const inter = Inter({ subsets: ["latin"] });
-
-export const metadata: Metadata = {
-  title: "Create Llama App",
-  description: "Generated by create-llama",
-};
-
-export default function RootLayout({
-  children,
-}: {
-  children: React.ReactNode;
-}) {
-  return (
-    <html lang="en">
-      <body className={inter.className}>
-        <Toaster />
-        {children}
-      </body>
-    </html>
-  );
-}

packages/autotool/examples/02_nextjs/app/page.tsx

@@ -1,11 +0,0 @@
-import { ChatSection } from "@/components/chat-section";
-
-export const runtime = "edge";
-
-export default function Home() {
-  return (
-    <main className="flex min-h-screen flex-col items-center gap-10 p-24 background-gradient">
-      <ChatSection />
-    </main>
-  );
-}

packages/autotool/examples/02_nextjs/components/chat-section.tsx

@@ -1,35 +0,0 @@
-"use client";
-import { chatWithAI } from "@/actions";
-import { ReactNode, useActionState } from "react";
-import { toast } from "sonner";
-
-export function ChatSection() {
-  const [state, formAction] = useActionState<ReactNode | null, FormData>(
-    async (state, payload) => {
-      const input = payload.get("input") as string | null;
-      if (!input) {
-        toast.error("Please type a message");
-        return null;
-      }
-      return chatWithAI(input);
-    },
-    null,
-  );
-  return (
-    <form>
-      <div className="border border-gray-400 p-2 max-w-md">{state}</div>
-      <input
-        className="border border-gray-400 p-2"
-        type="text"
-        name="input"
-        placeholder="Type your message here"
-      />
-      <button
-        className="bg-blue-500 hover:bg-blue-700 text-white font-bold py-2 px-4 rounded"
-        formAction={formAction}
-      >
-        Chat
-      </button>
-    </form>
-  );
-}

packages/autotool/examples/02_nextjs/components/location-card.tsx

@@ -1,9 +0,0 @@
-export function LocationCard() {
-  return (
-    <div className="border border-gray-400 p-2 max-w-md">
-      <h1>Weather</h1>
-      <p>San Francisco, CA</p>
-      <p>Sunny</p>
-    </div>
-  );
-}