chore: bump version

Releases:
  create-llama@0.0.19

[skip ci]

.changeset/curly-mangos-brake.md

@@ -0,0 +1,5 @@
+---
+"llamaindex": patch
+---
+
+update dependencies

.changeset/silly-bugs-fold.md

@@ -1,5 +0,0 @@
----
-"create-llama": patch
----
-
-Added option to automatically install dependencies (for Python and TS)

.devcontainer/devcontainer.json

@@ -4,6 +4,6 @@
     "ghcr.io/devcontainers/features/node:1": {},
     "ghcr.io/devcontainers-contrib/features/turborepo-npm:1": {},
     "ghcr.io/devcontainers-contrib/features/typescript:2": {},
-    "ghcr.io/devcontainers-contrib/features/pnpm:2": {}
-  }
+    "ghcr.io/devcontainers-contrib/features/pnpm:2": {},
+  },
 }

.eslintrc.js

@@ -7,4 +7,8 @@ module.exports = {
       rootDir: ["apps/*/"],
     },
   },
+  rules: {
+    "max-params": ["error", 4],
+  },
+  ignorePatterns: ["dist/"],
 };

.github/workflows/e2e.yml

@@ -21,6 +21,9 @@ jobs:
         node-version: [18, 20]
         python-version: ["3.11"]
         os: [macos-latest, windows-latest]
+    defaults:
+      run:
+        shell: bash
     runs-on: ${{ matrix.os }}
     steps:
       - uses: actions/checkout@v4

.github/workflows/lint_on_push_or_pull.yml

@@ -14,6 +14,8 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - uses: pnpm/action-setup@v2
+        with:
+          version: latest
       - name: Setup Node.js
         uses: actions/setup-node@v4
         with:

.gitignore

@@ -39,9 +39,6 @@ yarn-error.log*
 dist/
 lib/
 
-# vs code
-.vscode/launch.json
-
 .cache
 test-results/
 playwright-report/

.husky/pre-commit

@@ -1,6 +1,3 @@
-#!/usr/bin/env sh
-. "$(dirname -- "$0")/_/husky.sh"
-
 pnpm format
 pnpm lint
 npx lint-staged

.husky/pre-push

@@ -1,4 +1 @@
-#!/usr/bin/env sh
-. "$(dirname -- "$0")/_/husky.sh"
-
 pnpm test

.npmrc

@@ -1 +1,2 @@
 auto-install-peers = true
+enable-pre-post-scripts = true

.prettierignore

@@ -1,4 +1,6 @@
 apps/docs/i18n
+apps/docs/docs/api
 pnpm-lock.yaml
 lib/
 dist/
+.docusaurus/

.vscode/launch.json

@@ -0,0 +1,17 @@
+{
+  // Use IntelliSense to learn about possible attributes.
+  // Hover to view descriptions of existing attributes.
+  // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+  "version": "0.2.0",
+  "configurations": [
+    {
+      "type": "node",
+      "request": "launch",
+      "name": "Debug Example",
+      "skipFiles": ["<node_internals>/**"],
+      "runtimeExecutable": "pnpm",
+      "cwd": "${workspaceFolder}/examples",
+      "runtimeArgs": ["ts-node", "${fileBasename}"]
+    }
+  ]
+}

README.md

@@ -11,6 +11,10 @@ Use your own data with large language models (LLMs, OpenAI ChatGPT and others) i
 
 Documentation: https://ts.llamaindex.ai/
 
+Try examples online:
+
+[![Open in Stackblitz](https://developer.stackblitz.com/img/open_in_stackblitz.svg)](https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples)
+
 ## What is LlamaIndex.TS?
 
 LlamaIndex.TS aims to be a lightweight, easy to use set of libraries to help you integrate large language models into your applications with your own data.
@@ -52,9 +56,9 @@ async function main() {
 
   // Query the index
   const queryEngine = index.asQueryEngine();
-  const response = await queryEngine.query(
-    "What did the author do in college?",
-  );
+  const response = await queryEngine.query({
+    query: "What did the author do in college?",
+  });
 
   // Output response
   console.log(response.toString());
@@ -106,7 +110,6 @@ const nextConfig = {
       ...config.resolve.alias,
       sharp$: false,
       "onnxruntime-node$": false,
-      mongodb$: false,
     };
     return config;
   },

apps/demo-edge-runtime/.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"

apps/demo-edge-runtime/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!

apps/demo-edge-runtime/app/api/chat/engine/constants.mjs

@@ -1,4 +0,0 @@
-export const STORAGE_DIR = "./data";
-export const STORAGE_CACHE_DIR = "./cache";
-export const CHUNK_SIZE = 512;
-export const CHUNK_OVERLAP = 20;

apps/demo-edge-runtime/app/api/chat/engine/generate.mjs

@@ -1,53 +0,0 @@
-import {
-  serviceContextFromDefaults,
-  SimpleDirectoryReader,
-  storageContextFromDefaults,
-  VectorStoreIndex,
-} from "llamaindex";
-
-import * as dotenv from "dotenv";
-
-import {
-  CHUNK_OVERLAP,
-  CHUNK_SIZE,
-  STORAGE_CACHE_DIR,
-  STORAGE_DIR,
-} from "./constants.mjs";
-
-// Load environment variables from local .env file
-dotenv.config();
-
-async function getRuntime(func) {
-  const start = Date.now();
-  await func();
-  const end = Date.now();
-  return end - start;
-}
-
-async function generateDatasource(serviceContext) {
-  console.log(`Generating storage context...`);
-  // Split documents, create embeddings and store them in the storage context
-  const ms = await getRuntime(async () => {
-    const storageContext = await storageContextFromDefaults({
-      persistDir: STORAGE_CACHE_DIR,
-    });
-    const documents = await new SimpleDirectoryReader().loadData({
-      directoryPath: STORAGE_DIR,
-    });
-    await VectorStoreIndex.fromDocuments(documents, {
-      storageContext,
-      serviceContext,
-    });
-  });
-  console.log(`Storage context successfully generated in ${ms / 1000}s.`);
-}
-
-(async () => {
-  const serviceContext = serviceContextFromDefaults({
-    chunkSize: CHUNK_SIZE,
-    chunkOverlap: CHUNK_OVERLAP,
-  });
-
-  await generateDatasource(serviceContext);
-  console.log("Finished generating storage.");
-})();

apps/demo-edge-runtime/app/api/chat/engine/index.ts

@@ -1,59 +0,0 @@
-import {
-  ContextChatEngine,
-  LLM,
-  SimpleDocumentStore,
-  VectorStoreIndex,
-  genericFileSystem,
-  serviceContextFromDefaults,
-  storageContextFromDefaults,
-} from "llamaindex";
-import { CHUNK_OVERLAP, CHUNK_SIZE, STORAGE_CACHE_DIR } from "./constants.mjs";
-
-async function getDataSource(llm: LLM) {
-  const fs = genericFileSystem;
-  await fs.writeFile(
-    `${STORAGE_CACHE_DIR}/doc_store.json`,
-    JSON.stringify(await import("../../../../cache/doc_store.json")),
-  );
-  await fs.writeFile(
-    `${STORAGE_CACHE_DIR}/index_store.json`,
-    JSON.stringify(await import("../../../../cache/index_store.json")),
-  );
-  await fs.writeFile(
-    `${STORAGE_CACHE_DIR}/vector_store.json`,
-    JSON.stringify(await import("../../../../cache/vector_store.json")),
-  );
-
-  const serviceContext = serviceContextFromDefaults({
-    llm,
-    chunkSize: CHUNK_SIZE,
-    chunkOverlap: CHUNK_OVERLAP,
-  });
-  let storageContext = await storageContextFromDefaults({
-    persistDir: `${STORAGE_CACHE_DIR}`,
-  });
-
-  const numberOfDocs = Object.keys(
-    (storageContext.docStore as SimpleDocumentStore).toDict(),
-  ).length;
-  if (numberOfDocs === 0) {
-    throw new Error(
-      `StorageContext is empty - call 'npm run generate' to generate the storage first`,
-    );
-  }
-  return await VectorStoreIndex.init({
-    storageContext,
-    serviceContext,
-  });
-}
-
-export async function createChatEngine(llm: LLM) {
-  const index = await getDataSource(llm);
-  const retriever = index.asRetriever();
-  retriever.similarityTopK = 5;
-
-  return new ContextChatEngine({
-    chatModel: llm,
-    retriever,
-  });
-}

apps/demo-edge-runtime/app/api/chat/llamaindex-stream.ts

@@ -1,66 +0,0 @@
-import {
-  JSONValue,
-  createCallbacksTransformer,
-  createStreamDataTransformer,
-  experimental_StreamData,
-  trimStartOfStreamHelper,
-  type AIStreamCallbacksAndOptions,
-} from "ai";
-
-type ParserOptions = {
-  image_url?: string;
-};
-
-function createParser(
-  res: AsyncGenerator<any>,
-  data: experimental_StreamData,
-  opts?: ParserOptions,
-) {
-  const trimStartOfStream = trimStartOfStreamHelper();
-  return new ReadableStream<string>({
-    start() {
-      // if image_url is provided, send it via the data stream
-      if (opts?.image_url) {
-        const message: JSONValue = {
-          type: "image_url",
-          image_url: {
-            url: opts.image_url,
-          },
-        };
-        data.append(message);
-      } else {
-        data.append({}); // send an empty image response for the user's message
-      }
-    },
-    async pull(controller): Promise<void> {
-      const { value, done } = await res.next();
-      if (done) {
-        controller.close();
-        data.append({}); // send an empty image response for the assistant's message
-        data.close();
-        return;
-      }
-
-      const text = trimStartOfStream(value ?? "");
-      if (text) {
-        controller.enqueue(text);
-      }
-    },
-  });
-}
-
-export function LlamaIndexStream(
-  res: AsyncGenerator<any>,
-  opts?: {
-    callbacks?: AIStreamCallbacksAndOptions;
-    parserOptions?: ParserOptions;
-  },
-): { stream: ReadableStream; data: experimental_StreamData } {
-  const data = new experimental_StreamData();
-  return {
-    stream: createParser(res, data, opts?.parserOptions)
-      .pipeThrough(createCallbacksTransformer(opts?.callbacks))
-      .pipeThrough(createStreamDataTransformer(true)),
-    data,
-  };
-}

apps/demo-edge-runtime/app/api/chat/route.ts

@@ -1,82 +0,0 @@
-import { Message, StreamingTextResponse } from "ai";
-import { ChatMessage, MessageContent, OpenAI } from "llamaindex";
-import { NextRequest, NextResponse } from "next/server";
-import { createChatEngine } from "./engine";
-import { LlamaIndexStream } from "./llamaindex-stream";
-
-export const runtime = "edge";
-export const dynamic = "force-dynamic";
-
-const getLastMessageContent = (
-  textMessage: string,
-  imageUrl: string | undefined,
-): MessageContent => {
-  if (!imageUrl) return textMessage;
-  return [
-    {
-      type: "text",
-      text: textMessage,
-    },
-    {
-      type: "image_url",
-      image_url: {
-        url: imageUrl,
-      },
-    },
-  ];
-};
-
-export async function POST(request: NextRequest) {
-  try {
-    const body = await request.json();
-    const { messages, data }: { messages: Message[]; data: any } = body;
-    const lastMessage = messages.pop();
-    if (!messages || !lastMessage || lastMessage.role !== "user") {
-      return NextResponse.json(
-        {
-          error:
-            "messages are required in the request body and the last message must be from the user",
-        },
-        { status: 400 },
-      );
-    }
-
-    const llm = new OpenAI({
-      model: (process.env.MODEL as any) ?? "gpt-3.5-turbo",
-      maxTokens: 512,
-    });
-
-    const chatEngine = await createChatEngine(llm);
-
-    const lastMessageContent = getLastMessageContent(
-      lastMessage.content,
-      data?.imageUrl,
-    );
-
-    const response = await chatEngine.chat(
-      lastMessageContent as MessageContent,
-      messages as ChatMessage[],
-      true,
-    );
-
-    // Transform the response into a readable stream
-    const { stream, data: streamData } = LlamaIndexStream(response, {
-      parserOptions: {
-        image_url: data?.imageUrl,
-      },
-    });
-
-    // Return a StreamingTextResponse, which can be consumed by the client
-    return new StreamingTextResponse(stream, {}, streamData);
-  } catch (error) {
-    console.error("[LlamaIndex]", error);
-    return NextResponse.json(
-      {
-        error: (error as Error).message,
-      },
-      {
-        status: 500,
-      },
-    );
-  }
-}

apps/demo-edge-runtime/app/components/chat-section.tsx

@@ -1,46 +0,0 @@
-"use client";
-
-import { useChat } from "ai/react";
-import { useMemo } from "react";
-import { insertDataIntoMessages } from "./transform";
-import { ChatInput, ChatMessages } from "./ui/chat";
-
-export default function ChatSection() {
-  const {
-    messages,
-    input,
-    isLoading,
-    handleSubmit,
-    handleInputChange,
-    reload,
-    stop,
-    data,
-  } = useChat({
-    api: process.env.NEXT_PUBLIC_CHAT_API,
-    headers: {
-      "Content-Type": "application/json", // using JSON because of vercel/ai 2.2.26
-    },
-  });
-
-  const transformedMessages = useMemo(() => {
-    return insertDataIntoMessages(messages, data);
-  }, [messages, data]);
-
-  return (
-    <div className="space-y-4 max-w-5xl w-full">
-      <ChatMessages
-        messages={transformedMessages}
-        isLoading={isLoading}
-        reload={reload}
-        stop={stop}
-      />
-      <ChatInput
-        input={input}
-        handleSubmit={handleSubmit}
-        handleInputChange={handleInputChange}
-        isLoading={isLoading}
-        multiModal={process.env.NEXT_PUBLIC_MODEL === "gpt-4-vision-preview"}
-      />
-    </div>
-  );
-}

apps/demo-edge-runtime/app/components/header.tsx

@@ -1,28 +0,0 @@
-import Image from "next/image";
-
-export default function Header() {
-  return (
-    <div className="z-10 max-w-5xl w-full items-center justify-between font-mono text-sm lg:flex">
-      <p className="fixed left-0 top-0 flex w-full justify-center border-b border-gray-300 bg-gradient-to-b from-zinc-200 pb-6 pt-8 backdrop-blur-2xl dark:border-neutral-800 dark:bg-zinc-800/30 dark:from-inherit lg:static lg:w-auto  lg:rounded-xl lg:border lg:bg-gray-200 lg:p-4 lg:dark:bg-zinc-800/30">
-        Get started by editing&nbsp;
-        <code className="font-mono font-bold">app/page.tsx</code>
-      </p>
-      <div className="fixed bottom-0 left-0 flex h-48 w-full items-end justify-center bg-gradient-to-t from-white via-white dark:from-black dark:via-black lg:static lg:h-auto lg:w-auto lg:bg-none">
-        <a
-          href="https://www.llamaindex.ai/"
-          className="flex items-center justify-center font-nunito text-lg font-bold gap-2"
-        >
-          <span>Built by LlamaIndex</span>
-          <Image
-            className="rounded-xl"
-            src="/llama.png"
-            alt="Llama Logo"
-            width={40}
-            height={40}
-            priority
-          />
-        </a>
-      </div>
-    </div>
-  );
-}

apps/demo-edge-runtime/app/components/transform.ts

@@ -1,19 +0,0 @@
-import { JSONValue, Message } from "ai";
-
-export const isValidMessageData = (rawData: JSONValue | undefined) => {
-  if (!rawData || typeof rawData !== "object") return false;
-  if (Object.keys(rawData).length === 0) return false;
-  return true;
-};
-
-export const insertDataIntoMessages = (
-  messages: Message[],
-  data: JSONValue[] | undefined,
-) => {
-  if (!data) return messages;
-  messages.forEach((message, i) => {
-    const rawData = data[i];
-    if (isValidMessageData(rawData)) message.data = rawData;
-  });
-  return messages;
-};

apps/demo-edge-runtime/app/components/ui/chat/chat-avatar.tsx

@@ -1,34 +0,0 @@
-"use client";
-
-import Image from "next/image";
-import { Message } from "./chat-messages";
-
-export default function ChatAvatar(message: Message) {
-  if (message.role === "user") {
-    return (
-      <div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow bg-background">
-        <svg
-          xmlns="http://www.w3.org/2000/svg"
-          viewBox="0 0 256 256"
-          fill="currentColor"
-          className="h-4 w-4"
-        >
-          <path d="M230.92 212c-15.23-26.33-38.7-45.21-66.09-54.16a72 72 0 1 0-73.66 0c-27.39 8.94-50.86 27.82-66.09 54.16a8 8 0 1 0 13.85 8c18.84-32.56 52.14-52 89.07-52s70.23 19.44 89.07 52a8 8 0 1 0 13.85-8ZM72 96a56 56 0 1 1 56 56 56.06 56.06 0 0 1-56-56Z"></path>
-        </svg>
-      </div>
-    );
-  }
-
-  return (
-    <div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border  bg-black text-white">
-      <Image
-        className="rounded-md"
-        src="/llama.png"
-        alt="Llama Logo"
-        width={24}
-        height={24}
-        priority
-      />
-    </div>
-  );
-}

apps/demo-edge-runtime/app/components/ui/chat/chat-input.tsx

@@ -1,43 +0,0 @@
-"use client";
-
-export interface ChatInputProps {
-  /** The current value of the input */
-  input?: string;
-  /** An input/textarea-ready onChange handler to control the value of the input */
-  handleInputChange?: (
-    e:
-      | React.ChangeEvent<HTMLInputElement>
-      | React.ChangeEvent<HTMLTextAreaElement>,
-  ) => void;
-  /** Form submission handler to automatically reset input and append a user message  */
-  handleSubmit: (e: React.FormEvent<HTMLFormElement>) => void;
-  isLoading: boolean;
-  multiModal?: boolean;
-}
-
-export default function ChatInput(props: ChatInputProps) {
-  return (
-    <>
-      <form
-        onSubmit={props.handleSubmit}
-        className="flex items-start justify-between w-full max-w-5xl p-4 bg-white rounded-xl shadow-xl gap-4"
-      >
-        <input
-          autoFocus
-          name="message"
-          placeholder="Type a message"
-          className="w-full p-4 rounded-xl shadow-inner flex-1"
-          value={props.input}
-          onChange={props.handleInputChange}
-        />
-        <button
-          disabled={props.isLoading}
-          type="submit"
-          className="p-4 text-white rounded-xl shadow-xl bg-gradient-to-r from-cyan-500 to-sky-500 disabled:opacity-50 disabled:cursor-not-allowed"
-        >
-          Send message
-        </button>
-      </form>
-    </>
-  );
-}

apps/demo-edge-runtime/app/components/ui/chat/chat-item.tsx

@@ -1,13 +0,0 @@
-"use client";
-
-import ChatAvatar from "./chat-avatar";
-import { Message } from "./chat-messages";
-
-export default function ChatItem(message: Message) {
-  return (
-    <div className="flex items-start gap-4 pt-5">
-      <ChatAvatar {...message} />
-      <p className="break-words">{message.content}</p>
-    </div>
-  );
-}

apps/demo-edge-runtime/app/components/ui/chat/chat-messages.tsx

@@ -1,48 +0,0 @@
-"use client";
-
-import { useEffect, useRef } from "react";
-import ChatItem from "./chat-item";
-
-export interface Message {
-  id: string;
-  content: string;
-  role: string;
-}
-
-export default function ChatMessages({
-  messages,
-  isLoading,
-  reload,
-  stop,
-}: {
-  messages: Message[];
-  isLoading?: boolean;
-  stop?: () => void;
-  reload?: () => void;
-}) {
-  const scrollableChatContainerRef = useRef<HTMLDivElement>(null);
-
-  const scrollToBottom = () => {
-    if (scrollableChatContainerRef.current) {
-      scrollableChatContainerRef.current.scrollTop =
-        scrollableChatContainerRef.current.scrollHeight;
-    }
-  };
-
-  useEffect(() => {
-    scrollToBottom();
-  }, [messages.length]);
-
-  return (
-    <div className="w-full max-w-5xl p-4 bg-white rounded-xl shadow-xl">
-      <div
-        className="flex flex-col gap-5 divide-y h-[50vh] overflow-auto"
-        ref={scrollableChatContainerRef}
-      >
-        {messages.map((m: Message) => (
-          <ChatItem key={m.id} {...m} />
-        ))}
-      </div>
-    </div>
-  );
-}

apps/demo-edge-runtime/app/components/ui/chat/index.ts

@@ -1,6 +0,0 @@
-import ChatInput from "./chat-input";
-import ChatMessages from "./chat-messages";
-
-export type { ChatInputProps } from "./chat-input";
-export type { Message } from "./chat-messages";
-export { ChatInput, ChatMessages };

apps/demo-edge-runtime/app/globals.css

@@ -1,94 +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%);
-  }
-}

apps/demo-edge-runtime/app/layout.tsx

@@ -1,22 +0,0 @@
-import type { Metadata } from "next";
-import { Inter } from "next/font/google";
-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}>{children}</body>
-    </html>
-  );
-}

apps/demo-edge-runtime/app/page.tsx

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

apps/demo-edge-runtime/next-env.d.ts

@@ -1,5 +0,0 @@
-/// <reference types="next" />
-/// <reference types="next/image-types/global" />
-
-// NOTE: This file should not be edited
-// see https://nextjs.org/docs/basic-features/typescript for more information.

apps/demo-edge-runtime/next.config.js

@@ -1,4 +0,0 @@
-/** @type {import('next').NextConfig} */
-const nextConfig = {};
-
-module.exports = nextConfig;

apps/demo-edge-runtime/package.json

@@ -1,32 +0,0 @@
-{
-  "name": "demo-edge-runtime",
-  "version": "0.1.0",
-  "scripts": {
-    "dev": "next dev",
-    "build": "next build",
-    "start": "next start",
-    "lint": "next lint",
-    "generate": "node app/api/chat/engine/generate.mjs"
-  },
-  "dependencies": {
-    "ai": "^2.2.27",
-    "dotenv": "^16.3.1",
-    "llamaindex": "0.0.46",
-    "next": "^14.0.4",
-    "react": "^18.2.0",
-    "react-dom": "^18.2.0",
-    "supports-color": "^9.4.0"
-  },
-  "devDependencies": {
-    "@types/node": "^20.10.3",
-    "@types/react": "^18.2.42",
-    "@types/react-dom": "^18.2.17",
-    "autoprefixer": "^10.4.16",
-    "eslint": "^8.55.0",
-    "eslint-config-next": "^14.0.3",
-    "postcss": "^8.4.32",
-    "tailwindcss": "^3.3.6",
-    "typescript": "^5.3.2",
-    "cross-env": "^7.0.3"
-  }
-}

apps/demo-edge-runtime/postcss.config.js

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

apps/demo-edge-runtime/tailwind.config.ts

@@ -1,78 +0,0 @@
-import type { Config } from "tailwindcss";
-import { fontFamily } from "tailwindcss/defaultTheme";
-
-const config: Config = {
-  darkMode: ["class"],
-  content: ["app/**/*.{ts,tsx}", "components/**/*.{ts,tsx}"],
-  theme: {
-    container: {
-      center: true,
-      padding: "2rem",
-      screens: {
-        "2xl": "1400px",
-      },
-    },
-    extend: {
-      colors: {
-        border: "hsl(var(--border))",
-        input: "hsl(var(--input))",
-        ring: "hsl(var(--ring))",
-        background: "hsl(var(--background))",
-        foreground: "hsl(var(--foreground))",
-        primary: {
-          DEFAULT: "hsl(var(--primary))",
-          foreground: "hsl(var(--primary-foreground))",
-        },
-        secondary: {
-          DEFAULT: "hsl(var(--secondary))",
-          foreground: "hsl(var(--secondary-foreground))",
-        },
-        destructive: {
-          DEFAULT: "hsl(var(--destructive) / <alpha-value>)",
-          foreground: "hsl(var(--destructive-foreground) / <alpha-value>)",
-        },
-        muted: {
-          DEFAULT: "hsl(var(--muted))",
-          foreground: "hsl(var(--muted-foreground))",
-        },
-        accent: {
-          DEFAULT: "hsl(var(--accent))",
-          foreground: "hsl(var(--accent-foreground))",
-        },
-        popover: {
-          DEFAULT: "hsl(var(--popover))",
-          foreground: "hsl(var(--popover-foreground))",
-        },
-        card: {
-          DEFAULT: "hsl(var(--card))",
-          foreground: "hsl(var(--card-foreground))",
-        },
-      },
-      borderRadius: {
-        xl: `calc(var(--radius) + 4px)`,
-        lg: `var(--radius)`,
-        md: `calc(var(--radius) - 2px)`,
-        sm: "calc(var(--radius) - 4px)",
-      },
-      fontFamily: {
-        sans: ["var(--font-sans)", ...fontFamily.sans],
-      },
-      keyframes: {
-        "accordion-down": {
-          from: { height: "0" },
-          to: { height: "var(--radix-accordion-content-height)" },
-        },
-        "accordion-up": {
-          from: { height: "var(--radix-accordion-content-height)" },
-          to: { height: "0" },
-        },
-      },
-      animation: {
-        "accordion-down": "accordion-down 0.2s ease-out",
-        "accordion-up": "accordion-up 0.2s ease-out",
-      },
-    },
-  },
-  plugins: [],
-};
-export default config;

apps/demo-edge-runtime/tsconfig.json

@@ -1,28 +0,0 @@
-{
-  "compilerOptions": {
-    "target": "es5",
-    "lib": ["dom", "dom.iterable", "esnext"],
-    "allowJs": true,
-    "skipLibCheck": true,
-    "strict": true,
-    "noEmit": true,
-    "esModuleInterop": true,
-    "module": "esnext",
-    "moduleResolution": "bundler",
-    "resolveJsonModule": true,
-    "isolatedModules": true,
-    "jsx": "preserve",
-    "incremental": true,
-    "plugins": [
-      {
-        "name": "next"
-      }
-    ],
-    "paths": {
-      "@/*": ["./*"]
-    },
-    "forceConsistentCasingInFileNames": true
-  },
-  "include": ["next-env.d.ts", "**/*.ts", "**/*.tsx", ".next/types/**/*.ts"],
-  "exclude": ["node_modules"]
-}

apps/docs/CHANGELOG.md

@@ -0,0 +1,7 @@
+# docs
+
+## 0.0.1
+
+### Patch Changes
+
+- 3154f52: chore: add qdrant readme

apps/docs/docs/end_to_end.md

@@ -1,49 +0,0 @@
----
-sidebar_position: 4
----
-
-# End to End Examples
-
-We include several end-to-end examples using LlamaIndex.TS in the repository
-
-Check out the examples below or try them out and complete them in minutes with interactive Github Codespace tutorials provided by Dev-Docs [here](https://codespaces.new/team-dev-docs/lits-dev-docs-playground?devcontainer_path=.devcontainer%2Fjavascript_ltsquickstart%2Fdevcontainer.json):
-
-## [Chat Engine](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/chatEngine.ts)
-
-Read a file and chat about it with the LLM.
-
-## [Vector Index](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/vectorIndex.ts)
-
-Create a vector index and query it. The vector index will use embeddings to fetch the top k most relevant nodes. By default, the top k is 2.
-
-## [Summary Index](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/summaryIndex.ts)
-
-Create a list index and query it. This example also use the `LLMRetriever`, which will use the LLM to select the best nodes to use when generating answer.
-
-## [Save / Load an Index](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/storageContext.ts)
-
-Create and load a vector index. Persistance to disk in LlamaIndex.TS happens automatically once a storage context object is created.
-
-## [Customized Vector Index](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/vectorIndexCustomize.ts)
-
-Create a vector index and query it, while also configuring the the `LLM`, the `ServiceContext`, and the `similarity_top_k`.
-
-## [OpenAI LLM](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/openai.ts)
-
-Create an OpenAI LLM and directly use it for chat.
-
-## [Llama2 DeuceLLM](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/llamadeuce.ts)
-
-Create a Llama-2 LLM and directly use it for chat.
-
-## [SubQuestionQueryEngine](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/subquestion.ts)
-
-Uses the `SubQuestionQueryEngine`, which breaks complex queries into multiple questions, and then aggreates a response across the answers to all sub-questions.
-
-## [Low Level Modules](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/lowlevel.ts)
-
-This example uses several low-level components, which removes the need for an actual query engine. These components can be used anywhere, in any application, or customized and sub-classed to meet your own needs.
-
-## [JSON Entity Extraction](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/jsonExtract.ts)
-
-Features OpenAI's chat API (using [`json_mode`](https://platform.openai.com/docs/guides/text-generation/json-mode)) to extract a JSON object from a sales call transcript.

apps/docs/docs/examples/_category_.yml

@@ -0,0 +1,2 @@
+label: Examples
+position: 2

apps/docs/docs/examples/chat_engine.mdx

@@ -0,0 +1,12 @@
+---
+sidebar_position: 1
+---
+
+import CodeBlock from "@theme/CodeBlock";
+import CodeSource from "!raw-loader!../../../../examples/chatEngine";
+
+# Chat Engine
+
+Chat Engine is a class that allows you to create a chatbot from a retriever. It is a wrapper around a retriever that allows you to chat with it in a conversational manner.
+
+<CodeBlock language="ts">{CodeSource}</CodeBlock>

apps/docs/docs/examples/more_examples.mdx

@@ -0,0 +1,7 @@
+---
+sidebar_position: 5
+---
+
+# More examples
+
+You can check out more examples in the [examples](https://github.com/run-llama/LlamaIndexTS/tree/main/examples) folder of the repository.

apps/docs/docs/examples/save_load_index.mdx

@@ -0,0 +1,10 @@
+---
+sidebar_position: 4
+---
+
+import CodeBlock from "@theme/CodeBlock";
+import CodeSource from "!raw-loader!../../../../examples/storageContext";
+
+# Save/Load an Index
+
+<CodeBlock language="ts">{CodeSource}</CodeBlock>

apps/docs/docs/examples/summary_index.mdx

@@ -0,0 +1,10 @@
+---
+sidebar_position: 3
+---
+
+import CodeBlock from "@theme/CodeBlock";
+import CodeSource from "!raw-loader!../../../../examples/summaryIndex";
+
+# Summary Index
+
+<CodeBlock language="ts">{CodeSource}</CodeBlock>

apps/docs/docs/examples/vector_index.mdx

@@ -0,0 +1,10 @@
+---
+sidebar_position: 2
+---
+
+import CodeBlock from "@theme/CodeBlock";
+import CodeSource from "!raw-loader!../../../../examples/vectorIndex";
+
+# Vector Index
+
+<CodeBlock language="ts">{CodeSource}</CodeBlock>

apps/docs/docs/getting_started/_category_.yml

@@ -0,0 +1,2 @@
+label: Getting Started
+position: 1

apps/docs/docs/getting_started/concepts.md

@@ -2,7 +2,7 @@
 sidebar_position: 3
 ---
 
-# High-Level Concepts
+# Concepts
 
 LlamaIndex.TS helps you build LLM-powered applications (e.g. Q&A, chatbot) over custom data.
 
@@ -18,7 +18,7 @@ LlamaIndex uses a two stage method when using an LLM with your data:
 1. **indexing stage**: preparing a knowledge base, and
 2. **querying stage**: retrieving relevant context from the knowledge to assist the LLM in responding to a question
 
-![](./_static/concepts/rag.jpg)
+![](../_static/concepts/rag.jpg)
 
 This process is also known as Retrieval Augmented Generation (RAG).
 
@@ -30,7 +30,7 @@ Let's explore each stage in detail.
 
 LlamaIndex.TS help you prepare the knowledge base with a suite of data connectors and indexes.
 
-![](./_static/concepts/indexing.jpg)
+![](../_static/concepts/indexing.jpg)
 
 [**Data Loaders**](./modules/high_level/data_loader.md):
 A data connector (i.e. `Reader`) ingest data from different data sources and data formats into a simple `Document` representation (text and simple metadata).
@@ -56,7 +56,7 @@ LlamaIndex provides composable modules that help you build and integrate RAG pip
 
 These building blocks can be customized to reflect ranking preferences, as well as composed to reason over multiple knowledge bases in a structured way.
 
-![](./_static/concepts/querying.jpg)
+![](../_static/concepts/querying.jpg)
 
 #### Building Blocks
 

apps/docs/docs/getting_started/environments.md

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 5
+sidebar_position: 2
 ---
 
 # Environments

apps/docs/docs/getting_started/installation.mdx

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 1
+sidebar_position: 0
 ---
 
 # Installation and Setup

apps/docs/docs/getting_started/starter.md

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 2
+sidebar_position: 1
 ---
 
 # Starter Tutorial

apps/docs/docs/introduction.md

@@ -39,7 +39,7 @@ For more complex applications, our lower-level APIs allow advanced users to cust
 
 Our documentation includes [Installation Instructions](./installation.mdx) and a [Starter Tutorial](./starter.md) to build your first application.
 
-Once you're up and running, [High-Level Concepts](./concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our [End-to-End Tutorials](./end_to_end.md).
+Once you're up and running, [High-Level Concepts](./getting_started/concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our [End-to-End Tutorials](./end_to_end.md).
 
 ## 🗺️ Ecosystem
 

apps/docs/docs/modules/chat_engine.md

@@ -11,7 +11,16 @@ const retriever = index.asRetriever();
 const chatEngine = new ContextChatEngine({ retriever });
 
 // start chatting
-const response = await chatEngine.chat(query);
+const response = await chatEngine.chat({ message: query });
+```
+
+The `chat` function also supports streaming, just add `stream: true` as an option:
+
+```typescript
+const stream = await chatEngine.chat({ message: query, stream: true });
+for await (const chunk of stream) {
+  process.stdout.write(chunk.response);
+}
 ```
 
 ## Api References

apps/docs/docs/modules/documents_and_nodes.md

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 0
+sidebar_position: 1
 ---
 
 # Documents and Nodes

apps/docs/docs/modules/high_level/_category_.yml

@@ -1 +0,0 @@
-label: High-Level Modules

apps/docs/docs/modules/llm.md

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 0
+sidebar_position: 1
 ---
 
 # LLM

apps/docs/docs/modules/low_level/_category_.yml

@@ -1 +0,0 @@
-label: Low-Level Modules

apps/docs/docs/modules/query_engine.md

@@ -8,7 +8,16 @@ A query engine wraps a `Retriever` and a `ResponseSynthesizer` into a pipeline,
 
 ```typescript
 const queryEngine = index.asQueryEngine();
-const response = await queryEngine.query("query string");
+const response = await queryEngine.query({ query: "query string" });
+```
+
+The `query` function also supports streaming, just add `stream: true` as an option:
+
+```typescript
+const stream = await queryEngine.query({ query: "query string", stream: true });
+for await (const chunk of stream) {
+  process.stdout.write(chunk.response);
+}
 ```
 
 ## Sub Question Query Engine

apps/docs/docs/modules/vectorStores/_category_.yml

@@ -0,0 +1,2 @@
+label: "Vector Stores"
+position: 0

apps/docs/docs/modules/vectorStores/qdrant.md

@@ -0,0 +1,88 @@
+# Qdrant Vector Store
+
+To run this example, you need to have a Qdrant instance running. You can run it with Docker:
+
+```bash
+docker pull qdrant/qdrant
+docker run -p 6333:6333 qdrant/qdrant
+```
+
+## Importing the modules
+
+```ts
+import fs from "node:fs/promises";
+import { Document, VectorStoreIndex, QdrantVectorStore } from "llamaindex";
+```
+
+## Load the documents
+
+```ts
+const path = "node_modules/llamaindex/examples/abramov.txt";
+const essay = await fs.readFile(path, "utf-8");
+```
+
+## Setup Qdrant
+
+```ts
+const vectorStore = new QdrantVectorStore({
+  url: "http://localhost:6333",
+  port: 6333,
+});
+```
+
+## Setup the index
+
+```ts
+const document = new Document({ text: essay, id_: path });
+
+const index = await VectorStoreIndex.fromDocuments([document], {
+  vectorStore,
+});
+```
+
+## Query the index
+
+```ts
+const queryEngine = index.asQueryEngine();
+
+const response = await queryEngine.query({
+  query: "What did the author do in college?",
+});
+
+// Output response
+console.log(response.toString());
+```
+
+## Full code
+
+```ts
+import fs from "node:fs/promises";
+import { Document, VectorStoreIndex, QdrantVectorStore } from "llamaindex";
+
+async function main() {
+  const path = "node_modules/llamaindex/examples/abramov.txt";
+  const essay = await fs.readFile(path, "utf-8");
+
+  const vectorStore = new QdrantVectorStore({
+    url: "http://localhost:6333",
+    port: 6333,
+  });
+
+  const document = new Document({ text: essay, id_: path });
+
+  const index = await VectorStoreIndex.fromDocuments([document], {
+    vectorStore,
+  });
+
+  const queryEngine = index.asQueryEngine();
+
+  const response = await queryEngine.query({
+    query: "What did the author do in college?",
+  });
+
+  // Output response
+  console.log(response.toString());
+}
+
+main().catch(console.error);
+```

apps/docs/docs/observability/_category_.yml

@@ -1 +1,2 @@
 label: Observability
+position: 5

apps/docs/docusaurus.config.js

@@ -1,8 +1,9 @@
 // @ts-check
 // Note: type annotations allow type checking and IDEs autocompletion
 
-const lightCodeTheme = require("prism-react-renderer/themes/github");
-const darkCodeTheme = require("prism-react-renderer/themes/dracula");
+const renderer = require("prism-react-renderer");
+const lightCodeTheme = renderer.themes.github;
+const darkCodeTheme = renderer.themes.dracula;
 
 /** @type {import('@docusaurus/types').Config} */
 const config = {
@@ -50,10 +51,11 @@ const config = {
 
   presets: [
     [
-      "classic",
+      "@docusaurus/preset-classic",
       /** @type {import('@docusaurus/preset-classic').Options} */
       ({
         docs: {
+          path: "docs",
           routeBasePath: "/",
           sidebarPath: require.resolve("./sidebars.js"),
           // Please change this to your repo.
@@ -171,6 +173,9 @@ const config = {
       },
     ],
   ],
+  markdown: {
+    format: "detect",
+  },
 };
 
 module.exports = config;

apps/docs/i18n/ar/docusaurus-plugin-content-docs/current/api

@@ -1 +0,0 @@
-../../../../docs/api

apps/docs/i18n/ar/docusaurus-plugin-content-docs/current/api

@@ -0,0 +1 @@
+../../../../docs/api

apps/docs/i18n/ar/docusaurus-plugin-content-docs/current/installation.mdx

@@ -2,15 +2,12 @@
 sidebar_position: 1
 ---
 
-
 # التثبيت والإعداد
 
-```تمت ترجمة هذه الوثيقة تلقائيًا وقد تحتوي على أخطاء. لا تتردد في فتح طلب سحب لاقتراح تغييرات.```
-
+`تمت ترجمة هذه الوثيقة تلقائيًا وقد تحتوي على أخطاء. لا تتردد في فتح طلب سحب لاقتراح تغييرات.`
 
 تأكد من أن لديك NodeJS v18 أو أحدث.
 
-
 ## باستخدام create-llama
 
 أسهل طريقة للبدء مع LlamaIndex هي باستخدام `create-llama`. هذه الأداة سطر الأوامر تمكنك من بدء بناء تطبيق LlamaIndex جديد بسرعة، مع كل شيء معد لك.
@@ -48,13 +45,13 @@ npm run dev
 ```
 
 لبدء خادم التطوير. يمكنك ثم زيارة [http://localhost:3000](http://localhost:3000) لرؤية تطبيقك.
+
 ## التثبيت من NPM
 
 ```bash npm2yarn
 npm install llamaindex
 ```
 
-
 ### المتغيرات البيئية
 
 تستخدم أمثلتنا OpenAI افتراضيًا. ستحتاج إلى إعداد مفتاح Open AI الخاص بك على النحو التالي:
@@ -67,5 +64,4 @@ export OPENAI_API_KEY="sk-......" # استبدله بالمفتاح الخاص
 
 تحذير: لا تقم بإضافة مفتاح OpenAI الخاص بك إلى نظام التحكم في الإصدارات.
 
-
 "

apps/docs/i18n/ar/docusaurus-plugin-content-docs/current/introduction.md

@@ -41,7 +41,7 @@ LlamaIndex.TS هو إطار بيانات لتطبيقات LLM لاستيعاب
 
 تتضمن وثائقنا [تعليمات التثبيت](./installation.mdx) و[دليل البداية](./starter.md) لبناء تطبيقك الأول.
 
-بمجرد أن تكون جاهزًا وتعمل ، يحتوي [مفاهيم عالية المستوى](./concepts.md) على نظرة عامة على الهندسة المعمارية المتعددة المستويات لـ LlamaIndex. لمزيد من الأمثلة العملية التفصيلية ، يمكنك الاطلاع على [دروس النهاية إلى النهاية](./end_to_end.md).
+بمجرد أن تكون جاهزًا وتعمل ، يحتوي [مفاهيم عالية المستوى](./getting_started/concepts.md) على نظرة عامة على الهندسة المعمارية المتعددة المستويات لـ LlamaIndex. لمزيد من الأمثلة العملية التفصيلية ، يمكنك الاطلاع على [دروس النهاية إلى النهاية](./end_to_end.md).
 
 ## 🗺️ النظام البيئي
 

apps/docs/i18n/bg/docusaurus-plugin-content-docs/current/api

@@ -1 +0,0 @@
-../../../../docs/api

apps/docs/i18n/bg/docusaurus-plugin-content-docs/current/api

@@ -0,0 +1 @@
+../../../../docs/api

apps/docs/i18n/bg/docusaurus-plugin-content-docs/current/environments.md

@@ -15,4 +15,3 @@ LlamaIndex в момента официално поддържа NodeJS 18 и No
 ```js
 export const runtime = "nodejs"; // по подразбиране
 ```
-

apps/docs/i18n/bg/docusaurus-plugin-content-docs/current/installation.mdx

@@ -2,15 +2,12 @@
 sidebar_position: 1
 ---
 
-
 # Инсталация и настройка
 
-```Тази документация е преведена автоматично и може да съдържа грешки. Не се колебайте да отворите Pull Request, за да предложите промени.```
-
+`Тази документация е преведена автоматично и може да съдържа грешки. Не се колебайте да отворите Pull Request, за да предложите промени.`
 
 Уверете се, че имате NodeJS v18 или по-нова версия.
 
-
 ## Използване на create-llama
 
 Най-лесният начин да започнете с LlamaIndex е чрез използването на `create-llama`. Този инструмент с команден ред ви позволява бързо да започнете да създавате ново приложение LlamaIndex, като всичко е настроено за вас.
@@ -48,13 +45,13 @@ npm run dev
 ```
 
 за да стартирате сървъра за разработка. След това можете да посетите [http://localhost:3000](http://localhost:3000), за да видите вашето приложение.
+
 ## Инсталация от NPM
 
 ```bash npm2yarn
 npm install llamaindex
 ```
 
-
 ### Променливи на средата
 
 Нашият пример използва OpenAI по подразбиране. Ще трябва да настроите вашия Open AI ключ по следния начин:

apps/docs/i18n/bg/docusaurus-plugin-content-docs/current/introduction.md

@@ -43,7 +43,7 @@ LlamaIndex.TS предоставя основен набор от инструм
 
 Документацията ни включва [Инструкции за инсталиране](./installation.mdx) и [Урок за начинаещи](./starter.md), за да построите първото си приложение.
 
-След като сте готови, [Високо ниво концепции](./concepts.md) представя общ преглед на модулната архитектура на LlamaIndex. За повече практически примери, разгледайте нашите [Уроци от начало до край](./end_to_end.md).
+След като сте готови, [Високо ниво концепции](./getting_started/concepts.md) представя общ преглед на модулната архитектура на LlamaIndex. За повече практически примери, разгледайте нашите [Уроци от начало до край](./end_to_end.md).
 
 ## 🗺️ Екосистема
 

apps/docs/i18n/cat/docusaurus-plugin-content-docs/current/api

@@ -1 +0,0 @@
-../../../../docs/api

apps/docs/i18n/cat/docusaurus-plugin-content-docs/current/api

@@ -0,0 +1 @@
+../../../../docs/api

apps/docs/i18n/cat/docusaurus-plugin-content-docs/current/installation.mdx

@@ -2,15 +2,12 @@
 sidebar_position: 1
 ---
 
-
 # Instal·lació i configuració
 
-```Aquesta documentació s'ha traduït automàticament i pot contenir errors. No dubteu a obrir una Pull Request per suggerir canvis.```
-
+`Aquesta documentació s'ha traduït automàticament i pot contenir errors. No dubteu a obrir una Pull Request per suggerir canvis.`
 
 Assegureu-vos de tenir NodeJS v18 o superior.
 
-
 ## Utilitzant create-llama
 
 La manera més senzilla de començar amb LlamaIndex és utilitzant `create-llama`. Aquesta eina de línia de comandes us permet començar ràpidament a construir una nova aplicació LlamaIndex, amb tot configurat per a vosaltres.
@@ -48,13 +45,13 @@ npm run dev
 ```
 
 per iniciar el servidor de desenvolupament. A continuació, podeu visitar [http://localhost:3000](http://localhost:3000) per veure la vostra aplicació.
+
 ## Instal·lació des de NPM
 
 ```bash npm2yarn
 npm install llamaindex
 ```
 
-
 ### Variables d'entorn
 
 Els nostres exemples utilitzen OpenAI per defecte. Hauràs de configurar la teva clau d'Open AI de la següent manera:

apps/docs/i18n/cat/docusaurus-plugin-content-docs/current/introduction.md

@@ -41,7 +41,7 @@ Per a aplicacions més complexes, les nostres API de nivell inferior permeten al
 
 La nostra documentació inclou [Instruccions d'Instal·lació](./installation.mdx) i un [Tutorial d'Inici](./starter.md) per a construir la vostra primera aplicació.
 
-Un cop tingueu tot a punt, [Conceptes de Nivell Alt](./concepts.md) ofereix una visió general de l'arquitectura modular de LlamaIndex. Per a més exemples pràctics, consulteu els nostres [Tutorials de Principi a Fi](./end_to_end.md).
+Un cop tingueu tot a punt, [Conceptes de Nivell Alt](./getting_started/concepts.md) ofereix una visió general de l'arquitectura modular de LlamaIndex. Per a més exemples pràctics, consulteu els nostres [Tutorials de Principi a Fi](./end_to_end.md).
 
 ## 🗺️ Ecosistema
 

apps/docs/i18n/cs/docusaurus-plugin-content-docs/current/api

@@ -1 +0,0 @@
-../../../../docs/api

apps/docs/i18n/cs/docusaurus-plugin-content-docs/current/api

@@ -0,0 +1 @@
+../../../../docs/api

apps/docs/i18n/cs/docusaurus-plugin-content-docs/current/installation.mdx

@@ -2,15 +2,12 @@
 sidebar_position: 1
 ---
 
-
 # Instalace a nastavení
 
-```Tato dokumentace byla automaticky přeložena a může obsahovat chyby. Neváhejte otevřít Pull Request pro navrhování změn.```
-
+`Tato dokumentace byla automaticky přeložena a může obsahovat chyby. Neváhejte otevřít Pull Request pro navrhování změn.`
 
 Ujistěte se, že máte nainstalovaný NodeJS ve verzi 18 nebo vyšší.
 
-
 ## Použití create-llama
 
 Nejjednodušší způsob, jak začít s LlamaIndexem, je použití `create-llama`. Tento nástroj příkazového řádku vám umožní rychle začít s vytvářením nové aplikace LlamaIndex s přednastaveným prostředím.
@@ -48,13 +45,13 @@ npm run dev
 ```
 
 pro spuštění vývojového serveru. Poté můžete navštívit [http://localhost:3000](http://localhost:3000), abyste viděli vaši aplikaci.
+
 ## Instalace pomocí NPM
 
 ```bash npm2yarn
 npm install llamaindex
 ```
 
-
 ### Proměnné prostředí
 
 Naše příklady výchozí používají OpenAI. Budete potřebovat nastavit svůj Open AI klíč následovně:

apps/docs/i18n/cs/docusaurus-plugin-content-docs/current/introduction.md

@@ -41,7 +41,7 @@ Pro složitější aplikace naše API na nižší úrovni umožňuje pokročilý
 
 Naše dokumentace obsahuje [Návod k instalaci](./installation.mdx) a [Úvodní tutoriál](./starter.md) pro vytvoření vaší první aplikace.
 
-Jakmile jste připraveni, [Vysokoúrovňové koncepty](./concepts.md) poskytují přehled o modulární architektuře LlamaIndexu. Pro více praktických příkladů se podívejte na naše [Tutoriály od začátku do konce](./end_to_end.md).
+Jakmile jste připraveni, [Vysokoúrovňové koncepty](./getting_started/concepts.md) poskytují přehled o modulární architektuře LlamaIndexu. Pro více praktických příkladů se podívejte na naše [Tutoriály od začátku do konce](./end_to_end.md).
 
 ## 🗺️ Ekosystém
 

apps/docs/i18n/da/docusaurus-plugin-content-docs/current/api

@@ -1 +0,0 @@
-../../../../docs/api

apps/docs/i18n/da/docusaurus-plugin-content-docs/current/api

@@ -0,0 +1 @@
+../../../../docs/api

apps/docs/i18n/da/docusaurus-plugin-content-docs/current/installation.mdx

@@ -2,15 +2,12 @@
 sidebar_position: 1
 ---
 
-
 # Installation og opsætning
 
-```Denne dokumentation er blevet automatisk oversat og kan indeholde fejl. Tøv ikke med at åbne en Pull Request for at foreslå ændringer.```
-
+`Denne dokumentation er blevet automatisk oversat og kan indeholde fejl. Tøv ikke med at åbne en Pull Request for at foreslå ændringer.`
 
 Sørg for at have NodeJS v18 eller nyere.
 
-
 ## Brug af create-llama
 
 Den nemmeste måde at komme i gang med LlamaIndex er ved at bruge `create-llama`. Dette CLI-værktøj gør det muligt for dig at hurtigt starte med at bygge en ny LlamaIndex-applikation, hvor alt er sat op for dig.
@@ -48,13 +45,13 @@ npm run dev
 ```
 
 for at starte udviklingsserveren. Du kan derefter besøge [http://localhost:3000](http://localhost:3000) for at se din app.
+
 ## Installation fra NPM
 
 ```bash npm2yarn
 npm install llamaindex
 ```
 
-
 ### Miljøvariabler
 
 Vores eksempler bruger som standard OpenAI. Du skal konfigurere din Open AI-nøgle som følger:

apps/docs/i18n/da/docusaurus-plugin-content-docs/current/introduction.md

@@ -41,7 +41,7 @@ Til mere komplekse applikationer giver vores API'er på lavere niveau avancerede
 
 Vores dokumentation inkluderer [Installationsinstruktioner](./installation.mdx) og en [Starter Tutorial](./starter.md) til at bygge din første applikation.
 
-Når du er i gang, giver [Højniveaukoncepter](./concepts.md) et overblik over LlamaIndex's modulære arkitektur. For flere praktiske eksempler, kan du kigge igennem vores [End-to-End Tutorials](./end_to_end.md).
+Når du er i gang, giver [Højniveaukoncepter](./getting_started/concepts.md) et overblik over LlamaIndex's modulære arkitektur. For flere praktiske eksempler, kan du kigge igennem vores [End-to-End Tutorials](./end_to_end.md).
 
 ## 🗺️ Økosystem
 

apps/docs/i18n/de/docusaurus-plugin-content-docs/current/api

@@ -1 +0,0 @@
-../../../../docs/api

apps/docs/i18n/de/docusaurus-plugin-content-docs/current/api

@@ -0,0 +1 @@
+../../../../docs/api

apps/docs/i18n/de/docusaurus-plugin-content-docs/current/installation.mdx

@@ -2,15 +2,12 @@
 sidebar_position: 1
 ---
 
-
 # Installation und Einrichtung
 
-```Diese Dokumentation wurde automatisch übersetzt und kann Fehler enthalten. Zögern Sie nicht, einen Pull Request zu öffnen, um Änderungen vorzuschlagen.```
-
+`Diese Dokumentation wurde automatisch übersetzt und kann Fehler enthalten. Zögern Sie nicht, einen Pull Request zu öffnen, um Änderungen vorzuschlagen.`
 
 Stellen Sie sicher, dass Sie NodeJS Version 18 oder höher installiert haben.
 
-
 ## Verwendung von create-llama
 
 Der einfachste Weg, um mit LlamaIndex zu beginnen, besteht darin, `create-llama` zu verwenden. Dieses CLI-Tool ermöglicht es Ihnen, schnell eine neue LlamaIndex-Anwendung zu erstellen, bei der alles für Sie eingerichtet ist.
@@ -48,13 +45,13 @@ npm run dev
 ```
 
 um den Entwicklungsserver zu starten. Sie können dann [http://localhost:3000](http://localhost:3000) besuchen, um Ihre App zu sehen.
+
 ## Installation über NPM
 
 ```bash npm2yarn
 npm install llamaindex
 ```
 
-
 ### Umgebungsvariablen
 
 Unsere Beispiele verwenden standardmäßig OpenAI. Sie müssen Ihren OpenAI-Schlüssel wie folgt einrichten:

apps/docs/i18n/de/docusaurus-plugin-content-docs/current/introduction.md

@@ -41,7 +41,7 @@ Für komplexere Anwendungen ermöglichen unsere APIs auf niedrigerer Ebene fortg
 
 Unsere Dokumentation enthält [Installationsanweisungen](./installation.mdx) und ein [Einführungstutorial](./starter.md), um Ihre erste Anwendung zu erstellen.
 
-Sobald Sie bereit sind, bietet [High-Level-Konzepte](./concepts.md) einen Überblick über die modulare Architektur von LlamaIndex. Für praktische Beispiele schauen Sie sich unsere [End-to-End-Tutorials](./end_to_end.md) an.
+Sobald Sie bereit sind, bietet [High-Level-Konzepte](./getting_started/concepts.md) einen Überblick über die modulare Architektur von LlamaIndex. Für praktische Beispiele schauen Sie sich unsere [End-to-End-Tutorials](./end_to_end.md) an.
 
 ## 🗺️ Ökosystem
 

apps/docs/i18n/el/docusaurus-plugin-content-docs/current/api

@@ -1 +0,0 @@
-../../../../docs/api

apps/docs/i18n/el/docusaurus-plugin-content-docs/current/api

@@ -0,0 +1 @@
+../../../../docs/api

apps/docs/i18n/el/docusaurus-plugin-content-docs/current/installation.mdx

@@ -2,15 +2,12 @@
 sidebar_position: 1
 ---
 
-
 # Εγκατάσταση και Ρύθμιση
 
-```Αυτό το έγγραφο έχει μεταφραστεί αυτόματα και μπορεί να περιέχει λάθη. Μη διστάσετε να ανοίξετε ένα Pull Request για να προτείνετε αλλαγές.```
-
+`Αυτό το έγγραφο έχει μεταφραστεί αυτόματα και μπορεί να περιέχει λάθη. Μη διστάσετε να ανοίξετε ένα Pull Request για να προτείνετε αλλαγές.`
 
 Βεβαιωθείτε ότι έχετε το NodeJS v18 ή νεότερη έκδοση.
 
-
 ## Χρήση του create-llama
 
 Ο ευκολότερος τρόπος για να ξεκινήσετε με το LlamaIndex είναι να χρησιμοποιήσετε το `create-llama`. Αυτό το εργαλείο γραμμής εντολών σας επιτρέπει να ξεκινήσετε γρήγορα τη δημιουργία μιας νέας εφαρμογής LlamaIndex, με όλα τα απαραίτητα προεπιλεγμένα ρυθμισμένα για εσάς.
@@ -48,13 +45,13 @@ npm run dev
 ```
 
 για να ξεκινήσετε τον διακομιστή ανάπτυξης. Στη συνέχεια, μπορείτε να επισκεφθείτε τη διεύθυνση [http://localhost:3000](http://localhost:3000) για να δείτε την εφαρμογή σας.
+
 ## Εγκατάσταση από το NPM
 
 ```bash npm2yarn
 npm install llamaindex
 ```
 
-
 ### Μεταβλητές περιβάλλοντος
 
 Τα παραδείγματά μας χρησιμοποιούν το OpenAI από προεπιλογή. Θα πρέπει να ρυθμίσετε το κλειδί σας για το Open AI ως εξής: