Merge main into sweep/fix-env-variable-loading

.cjs.swcrc

@@ -1,16 +0,0 @@
-{
-  "jsc": {
-    "parser": {
-      "syntax": "typescript",
-      "decorators": true
-    },
-    "target": "esnext",
-    "transform": {
-      "decoratorVersion": "2022-03"
-    }
-  },
-  "module": {
-    "type": "commonjs",
-    "ignoreDynamic": true
-  }
-}

.eslintrc.js

@@ -0,0 +1,10 @@
+module.exports = {
+  root: true,
+  // This tells ESLint to load the config from the package `eslint-config-custom`
+  extends: ["custom"],
+  settings: {
+    next: {
+      rootDir: ["apps/*/"],
+    },
+  },
+};

.gitattributes

@@ -1,2 +0,0 @@
-examples/readers/data/** binary
-examples/data/** binary

.github/ISSUE_TEMPLATE/bug_report.md

@@ -1,46 +0,0 @@
----
-name: Bug report
-about: Create a report to help us improve
-title: ""
-labels: bug
-assignees: ""
----
-
-**Describe the bug**
-A clear and concise description of what the bug is.
-
-**To Reproduce**
-Code to reproduce the behavior:
-
-```ts
-// paste the code here
-```
-
-**Expected behavior**
-A clear and concise description of what you expected to happen.
-
-**Screenshots**
-If applicable, add screenshots to help explain your problem.
-
-**Desktop (please complete the following information):**
-
-- OS: [e.g. macOS, Linux]
-- JS Runtime / Framework / Bundler (select all applicable)
-- [ ] Node.js
-- [ ] Deno
-- [ ] Bun
-- [ ] Next.js
-- [ ] ESBuild
-- [ ] Rollup
-- [ ] Webpack
-- [ ] Turbopack
-- [ ] Vite
-- [ ] Waku
-- [ ] Edge Runtime
-- [ ] AWS Lambda
-- [ ] Cloudflare Worker
-- [ ] Others (please elaborate on this)
-- Version [e.g. 22]
-
-**Additional context**
-Add any other context about the problem here.

.github/ISSUE_TEMPLATE/sweep-bugfix.yml

@@ -1,6 +1,7 @@
 name: Bugfix
-title: ""
-description: Write something like "We notice ... behavior when ... happens instead of ..." If you would like to use sweep.dev prefix with "Sweep:"
+title: "Sweep: "
+description: Write something like "We notice ... behavior when ... happens instead of ...""
+labels: sweep
 body:
   - type: textarea
     id: description

.github/ISSUE_TEMPLATE/sweep-feature.yml

@@ -1,10 +1,11 @@
 name: Feature Request
-title: ""
-description: Write something like "Write an api endpoint that does "..." in the "..." file". If you would like to use sweep.dev prefix with "Sweep:"
+title: "Sweep: "
+description: Write something like "Write an api endpoint that does "..." in the "..." file"
+labels: sweep
 body:
   - type: textarea
     id: description
     attributes:
       label: Details
-      description: More details
+      description: More details for Sweep
       placeholder: The new endpoint should use the ... class from ... file because it contains ... logic

.github/ISSUE_TEMPLATE/sweep-refactor.yml

@@ -1,10 +1,11 @@
 name: Refactor
-title: ""
-description: Write something like "Modify the ... api endpoint to use ... version and ... framework" If you would like to use sweep.dev prefix with "Sweep:"
+title: "Sweep: "
+description: Write something like "Modify the ... api endpoint to use ... version and ... framework"
+labels: sweep
 body:
   - type: textarea
     id: description
     attributes:
       label: Details
-      description: More details
+      description: More details for Sweep
       placeholder: We are migrating this function to ... version because ...

.github/workflows/lint_on_push_or_pull.yml

@@ -12,16 +12,14 @@ jobs:
   lint:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
-      - uses: pnpm/action-setup@v4
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version-file: ".nvmrc"
-          cache: "pnpm"
+      - name: Checkout code
+        uses: actions/checkout@v2
+
+      - name: Install pnpm
+        run: npm install -g pnpm
+
       - name: Install dependencies
         run: pnpm install
+
       - name: Run lint
         run: pnpm run lint
-      - name: Run Prettier
-        run: pnpm run format

.github/workflows/preview.yml

@@ -1,28 +0,0 @@
-name: Publish Preview
-on: [pull_request]
-
-jobs:
-  pre_release:
-    name: Pre Release
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout Repo
-        uses: actions/checkout@v4
-
-      - uses: pnpm/action-setup@v4
-
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version-file: ".nvmrc"
-          cache: "pnpm"
-
-      - name: Install dependencies
-        run: pnpm install
-
-      - name: Build
-        run: pnpm run build
-
-      - name: Pre Release
-        run: pnpx pkg-pr-new publish --pnpm ./packages/* ./packages/providers/* ./packages/providers/storage/*

.github/workflows/publish_github.yml

@@ -1,37 +0,0 @@
-name: Publish to GitHub Releases
-
-on:
-  push:
-    tags:
-      - "llamaindex@*"
-
-jobs:
-  build-and-publish:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout Repo
-        uses: actions/checkout@v4
-
-      - uses: pnpm/action-setup@v4
-
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version-file: ".nvmrc"
-          cache: "pnpm"
-
-      - name: Install dependencies
-        run: pnpm install
-
-      - name: Build tarball
-        run: |
-          pnpm pack
-        working-directory: packages/llamaindex
-
-      - name: Create release
-        uses: ncipollo/release-action@v1
-        with:
-          artifacts: "packages/llamaindex/llamaindex-*.tgz"
-          name: Release ${{ github.ref }}
-          bodyFile: "packages/llamaindex/CHANGELOG.md"
-          token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/release.yml

@@ -1,70 +0,0 @@
-name: Release
-
-on:
-  push:
-    branches:
-      - main
-
-concurrency: ${{ github.workflow }}-${{ github.ref }}
-
-jobs:
-  release:
-    name: Release
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout Repo
-        uses: actions/checkout@v4
-
-      - uses: pnpm/action-setup@v4
-
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version-file: ".nvmrc"
-          cache: "pnpm"
-
-      - name: Install dependencies
-        run: pnpm install
-
-      - name: Add auth token to .npmrc file
-        run: |
-          cat << EOF >> ".npmrc"
-            //registry.npmjs.org/:_authToken=$NPM_TOKEN
-          EOF
-        env:
-          NPM_TOKEN: ${{ secrets.NPM_TOKEN }}
-
-      - name: Get changeset status
-        id: get-changeset-status
-        run: |
-          pnpm changeset status --output .changeset/status.json
-          new_version=$(jq -r '.releases[] | select(.name == "llamaindex") | .newVersion' < .changeset/status.json)
-          rm -v .changeset/status.json
-          echo "new-version=${new_version}" >> "$GITHUB_OUTPUT"
-
-      - name: Create Release Pull Request or Publish to npm
-        id: changesets
-        uses: changesets/action@v1
-        with:
-          commit: Release ${{ steps.get-changeset-status.outputs.new-version }}
-          title: Release ${{ steps.get-changeset-status.outputs.new-version }}
-          # update version PR with the latest changesets
-          version: pnpm new-version
-          # build package and call changeset publish
-          publish: pnpm release
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-          NPM_TOKEN: ${{ secrets.NPM_TOKEN }}
-
-      # Refs: https://github.com/changesets/changesets/issues/421
-      - name: Update lock file
-        continue-on-error: true
-        run: pnpm install --lockfile-only
-
-      - name: Commit lock file
-        continue-on-error: true
-        uses: stefanzweifel/git-auto-commit-action@v5
-        with:
-          commit_message: "chore: update lock file"
-          branch: changeset-release/main
-          file_pattern: "pnpm-lock.yaml"

.github/workflows/test.yml

@@ -1,193 +1,24 @@
 name: Run Tests
 
-on:
-  push:
-    branches:
-      - main
-  pull_request:
-    branches:
-      - main
-
-concurrency:
-  group: ${{ github.workflow }}-${{ github.ref }}
-  cancel-in-progress: true
-
-env:
-  POSTGRES_HOST_AUTH_METHOD: trust
-  TURBO_TOKEN: ${{ secrets.TURBO_TOKEN }}
-  TURBO_TEAM: ${{ vars.TURBO_TEAM }}
-  TURBO_REMOTE_ONLY: true
+on: [push, pull_request]
 
 jobs:
-  e2e:
-    strategy:
-      fail-fast: false
-      matrix:
-        node-version: [18.x, 20.x, 22.x, 23.x]
-    name: E2E on Node.js ${{ matrix.node-version }}
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-      - uses: ankane/setup-postgres@v1
-        with:
-          database: llamaindex_node_test
-          dev-files: true
-      - run: |
-          cd /tmp
-          git clone --branch v0.7.0 https://github.com/pgvector/pgvector.git
-          cd pgvector
-          make
-          sudo make install
-      - uses: pnpm/action-setup@v4
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: ${{ matrix.node-version }}
-          cache: "pnpm"
-      - name: Install dependencies
-        run: pnpm install
-      - name: Run E2E Tests
-        run: pnpm run e2e
-
   test:
-    strategy:
-      fail-fast: false
-      matrix:
-        node-version: [18.x, 20.x, 22.x, 23.x]
-    name: Test on Node.js ${{ matrix.node-version }}
     runs-on: ubuntu-latest
+
     steps:
-      - uses: actions/checkout@v4
-      - uses: pnpm/action-setup@v4
+      - name: Checkout code
+        uses: actions/checkout@v2
+
       - name: Setup Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v2
         with:
-          node-version: ${{ matrix.node-version }}
-          cache: "pnpm"
+          node-version: "18"
+
       - name: Install dependencies
-        run: pnpm install
+        run: |
+          npm i -g pnpm
+          pnpm install
+
       - name: Run tests
         run: pnpm run test
-  typecheck:
-    runs-on: ubuntu-latest
-
-    steps:
-      - uses: actions/checkout@v4
-      - uses: pnpm/action-setup@v4
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version-file: ".nvmrc"
-          cache: "pnpm"
-      - name: Install dependencies
-        run: pnpm install
-      - name: Build
-        run: pnpm run build
-      - name: Run Type Check
-        run: pnpm run type-check
-      - name: Run Circular Dependency Check
-        run: pnpm run circular-check
-  e2e-llamaindex-examples:
-    strategy:
-      fail-fast: false
-      matrix:
-        packages:
-          - cloudflare-worker-agent
-          - nextjs-agent
-          - nextjs-edge-runtime
-          - nextjs-node-runtime
-          - waku-query-engine
-          - llama-parse-browser
-          - vite-import-llamaindex
-    runs-on: ubuntu-latest
-    name: Build LlamaIndex Example (${{ matrix.packages }})
-    steps:
-      - uses: actions/checkout@v4
-      - uses: pnpm/action-setup@v4
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version-file: ".nvmrc"
-          cache: "pnpm"
-      - name: Install dependencies
-        run: pnpm install
-      - name: Build llamaindex
-        run: pnpm run build
-      - name: Build ${{ matrix.packages }}
-        run: pnpm run build
-        working-directory: e2e/examples/${{ matrix.packages }}
-
-  size-limit:
-    runs-on: ubuntu-latest
-    if: github.event_name == 'pull_request'
-    name: Size Limit
-    steps:
-      - uses: actions/checkout@v4
-      - uses: pnpm/action-setup@v4
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version-file: ".nvmrc"
-          cache: "pnpm"
-      - name: Install dependencies
-        run: pnpm install
-      - name: Build llamaindex
-        run: pnpm run build
-      - uses: andresz1/size-limit-action@94bc357df29c36c8f8d50ea497c3e225c3c95d1d
-        with:
-          github_token: ${{ secrets.GITHUB_TOKEN }}
-          directory: e2e/examples/vite-import-llamaindex
-          skip_step: "install"
-          build_script: build
-          package_manager: pnpm
-
-  typecheck-examples:
-    runs-on: ubuntu-latest
-
-    steps:
-      - uses: actions/checkout@v4
-      - uses: pnpm/action-setup@v4
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version-file: ".nvmrc"
-          cache: "pnpm"
-      - name: Install dependencies
-        run: pnpm install
-      - name: Build
-        run: pnpm run build
-      - name: Copy examples
-        run: rsync -rv --exclude=node_modules ./examples ${{ runner.temp }}
-      - name: Pack packages
-        run: |
-          for dir in packages/*; do
-            if [ -d "$dir" ] && [ -f "$dir/package.json" ] && [[ ! "$dir" =~ autotool ]]; then
-              echo "Packing $dir"
-              pnpm pack --pack-destination ${{ runner.temp }} -C $dir
-            else
-              echo "Skipping $dir, no package.json found"
-            fi
-          done
-      - name: Pack provider packages
-        run: |
-          for dir in packages/providers/* packages/providers/storage/*; do
-            if [ -d "$dir" ] && [ -f "$dir/package.json" ]; then
-              echo "Packing $dir"
-              pnpm pack --pack-destination ${{ runner.temp }} -C $dir
-            else
-              echo "Skipping $dir, no package.json found"
-            fi
-          done
-      - name: Install
-        run: npm add ${{ runner.temp }}/*.tgz
-        working-directory: ${{ runner.temp }}/examples
-      - name: Run Type Check
-        run: npx tsc --project ./tsconfig.json
-        working-directory: ${{ runner.temp }}/examples
-      - uses: actions/upload-artifact@v4
-        if: failure()
-        with:
-          name: build-dist
-          path: |
-            ${{ runner.temp }}/*.tgz
-          if-no-files-found: error

.gitignore

@@ -37,17 +37,6 @@ yarn-error.log*
 .vercel
 
 dist/
-lib/
 
-.cache
-test-results/
-playwright-report/
-blob-report/
-playwright/.cache/
-.tsbuildinfo
-
-# intellij
-**/.idea
-
-# generated API
-packages/cloud/src/client
+# vs code
+.vscode/launch.json

.husky/pre-commit

@@ -1 +1,5 @@
-pnpm run lint-staged
+#!/usr/bin/env sh
+. "$(dirname -- "$0")/_/husky.sh"
+
+pnpm lint
+npx lint-staged

.husky/pre-push

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

.npmrc

@@ -1,5 +1 @@
 auto-install-peers = true
-enable-pre-post-scripts = true
-prefer-workspace-packages = true
-save-workspace-protocol = true
-link-workspace-packages = true

.nvmrc

@@ -1 +0,0 @@
-20

.prettierignore

@@ -1,9 +0,0 @@
-apps/docs/i18n
-apps/docs/docs/api
-pnpm-lock.yaml
-lib/
-dist/
-.docusaurus/
-.source/
-# prttier doesn't support mdx3 we are using
-*.mdx

.swcrc

@@ -1,12 +0,0 @@
-{
-  "jsc": {
-    "parser": {
-      "syntax": "typescript",
-      "decorators": true
-    },
-    "target": "esnext",
-    "transform": {
-      "decoratorVersion": "2022-03"
-    }
-  }
-}

.vscode/launch.json

@@ -1,18 +0,0 @@
-{
-  // 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",
-      "console": "integratedTerminal",
-      "cwd": "${workspaceFolder}/examples",
-      "runtimeArgs": ["npx", "tsx", "${file}"]
-    }
-  ]
-}

.vscode/ltex.dictionary.en-US.txt

@@ -1 +0,0 @@
-LlamaIndexTS

.vscode/settings.json

@@ -4,16 +4,5 @@
   "editor.defaultFormatter": "esbenp.prettier-vscode",
   "[xml]": {
     "editor.defaultFormatter": "redhat.vscode-xml"
-  },
-  "[python]": {
-    "editor.defaultFormatter": "ms-python.black-formatter"
-  },
-  "[jsonc]": {
-    "editor.defaultFormatter": "esbenp.prettier-vscode"
-  },
-  "[json]": {
-    "editor.defaultFormatter": "esbenp.prettier-vscode"
-  },
-  "prettier.prettierPath": "./node_modules/prettier",
-  "prettier.configPath": "prettier.config.mjs"
+  }
 }

CONTRIBUTING.md

@@ -2,78 +2,79 @@
 
 ## Structure
 
-LlamaIndex.TS uses pnpm monorepo.
+This is a monorepo built with Turborepo
 
-We recommend you to understand the basics of Node.js, TypeScript, pnpm, and of course, LLM before contributing.
+Right now there are two packages of importance:
 
-There are some important folders in the repository:
+packages/core which is the main NPM library llamaindex
 
-- `packages/*`: Contains the source code of the packages. Each package is a separate npm package.
-  - `llamaindex`: The starter package for LlamaIndex.TS, which contains the all sub-packages.
-  - `core`: The core package of LlamaIndex.TS, which contains the abstract classes and interfaces. It is designed for
-    all JS runtime environments.
-  - `env`: The environment package of LlamaIndex.TS, which contains the environment-specific classes and interfaces. It
-    includes compatibility layers for Node.js, Deno, Vercel Edge Runtime, Cloudflare Workers...
-- `apps/*`: The applications based on LlamaIndex.TS.
-  - `next`: Our documentation website based on Next.js.
-- `examples`: The code examples of LlamaIndex.TS using Node.js.
+apps/simple is where the demo code lives
+
+### Turborepo docs
+
+You can checkout how Turborepo works using the default [README-turborepo.md](/README-turborepo.md)
 
 ## Getting Started
 
-Make sure you have Node.js LIS (Long-term Support) installed. You can check your Node.js version by running:
+Install NodeJS. Preferably v18 using nvm or n.
+
+Inside the LlamaIndexTS directory:
 
-```shell
-node -v
-# v20.x.x
 ```
-
-### Use pnpm
-
-```shell
-corepack enable
-```
-
-### Install dependencies
-
-```shell
+npm i -g pnpm ts-node
 pnpm install
 ```
 
-### Build the packages
+Note: we use pnpm in this repo, which has a lot of the same functionality and CLI options as npm but it does do some things better in a monorepo, like centralizing dependencies and caching.
 
-You'll need Turbo to build the packages. If you don't have it, you can run it with `pnpx`.
+PNPM's has documentation on its [workspace feature](https://pnpm.io/workspaces) and Turborepo had some [useful documentation also](https://turbo.build/repo/docs/core-concepts/monorepos/running-tasks).
 
-To build all packages, run:
+### Running Typescript
 
-```shell
-# Build all packages
-pnpx turbo build --filter "./packages/*"
+When we publish to NPM we will have a tsc compiled version of the library in JS. For now, the easiest thing to do is use ts-node.
 
-# Or if you have turbo installed, you can run:
-turbo build --filter "./packages/*"
+### Test cases
+
+To run them, run
+
+```
+pnpm run test
+```
+
+To write new test cases write them in [packages/core/src/tests](/packages/core/src/tests)
+
+We use Jest https://jestjs.io/ to write our test cases. Jest comes with a bunch of built in assertions using the expect function: https://jestjs.io/docs/expect
+
+### Demo applications
+
+There is an existing ["simple"](/apps/simple/README.md) demos folder with mainly NodeJS scripts. Feel free to add additional demos to that folder. If you would like to try out your changes in the core package with a new demo, you need to run the build command in the README.
+
+You can create new demo applications in the apps folder. Just run pnpm init in the folder after you create it to create its own package.json
+
+### Installing packages
+
+To install packages for a specific package or demo application, run
+
+```
+pnpm add [NPM Package] --filter [package or application i.e. core or simple]
+```
+
+To install packages for every package or application run
+
+```
+pnpm add -w [NPM Package]
 ```
 
 ### Docs
 
-See the [docs](./apps/next/README.md) for more information.
+To contribute to the docs, go to the docs website folder and run the Docusaurus instance.
 
-## Changeset
-
-We use [changesets](https://github.com/changesets/changesets) for managing versions and changelogs. To create a new
-changeset, run in the root folder:
-
-```
-pnpm changeset
+```bash
+cd apps/docs
+pnpm install
+pnpm start
 ```
 
-Please send a descriptive changeset for each PR.
+That should start a webserver which will serve the docs on https://localhost:3000
 
-## Publishing (maintainers only)
-
-The [Release Github Action](.github/workflows/release.yml) is automatically generating and updating a
-PR called "Release {version}".
-
-This PR will update the `package.json` and `CHANGELOG.md` files of each package according to
-the current changesets in the [.changeset](.changeset) folder.
-
-If this PR is merged it will automatically add version tags to the repository and publish the updated packages to NPM.
+Any changes you make should be reflected in the browser. If you need to regenerate the API docs and find that your TSDoc isn't getting the updates, feel free to remove apps/docs/api. It will automatically regenerate itself when you run pnpm start again.

README-turborepo.md

@@ -0,0 +1,81 @@
+# Turborepo starter
+
+This is an official starter Turborepo.
+
+## Using this example
+
+Run the following command:
+
+```sh
+npx create-turbo@latest
+```
+
+## What's inside?
+
+This Turborepo includes the following packages/apps:
+
+### Apps and Packages
+
+- `docs`: a [Next.js](https://nextjs.org/) app
+- `web`: another [Next.js](https://nextjs.org/) app
+- `ui`: a stub React component library shared by both `web` and `docs` applications
+- `eslint-config-custom`: `eslint` configurations (includes `eslint-config-next` and `eslint-config-prettier`)
+- `tsconfig`: `tsconfig.json`s used throughout the monorepo
+
+Each package/app is 100% [TypeScript](https://www.typescriptlang.org/).
+
+### Utilities
+
+This Turborepo has some additional tools already setup for you:
+
+- [TypeScript](https://www.typescriptlang.org/) for static type checking
+- [ESLint](https://eslint.org/) for code linting
+- [Prettier](https://prettier.io) for code formatting
+
+### Build
+
+To build all apps and packages, run the following command:
+
+```
+cd my-turborepo
+pnpm build
+```
+
+### Develop
+
+To develop all apps and packages, run the following command:
+
+```
+cd my-turborepo
+pnpm dev
+```
+
+### Remote Caching
+
+Turborepo can use a technique known as [Remote Caching](https://turbo.build/repo/docs/core-concepts/remote-caching) to share cache artifacts across machines, enabling you to share build caches with your team and CI/CD pipelines.
+
+By default, Turborepo will cache locally. To enable Remote Caching you will need an account with Vercel. If you don't have an account you can [create one](https://vercel.com/signup), then enter the following commands:
+
+```
+cd my-turborepo
+npx turbo login
+```
+
+This will authenticate the Turborepo CLI with your [Vercel account](https://vercel.com/docs/concepts/personal-accounts/overview).
+
+Next, you can link your Turborepo to your Remote Cache by running the following command from the root of your Turborepo:
+
+```
+npx turbo link
+```
+
+## Useful Links
+
+Learn more about the power of Turborepo:
+
+- [Tasks](https://turbo.build/repo/docs/core-concepts/monorepos/running-tasks)
+- [Caching](https://turbo.build/repo/docs/core-concepts/caching)
+- [Remote Caching](https://turbo.build/repo/docs/core-concepts/remote-caching)
+- [Filtering](https://turbo.build/repo/docs/core-concepts/monorepos/filtering)
+- [Configuration Options](https://turbo.build/repo/docs/reference/configuration)
+- [CLI Usage](https://turbo.build/repo/docs/reference/command-line-reference)

README.md

@@ -1,80 +1,67 @@
-<p align="center">
-  <img height="100" width="100" alt="LlamaIndex logo" src="https://ts.llamaindex.ai/square.svg" />
-</p>
-<h1 align="center">LlamaIndex.TS</h1>
-<h3 align="center">
-  Data framework for your LLM application.
-</h3>
+# LlamaIndex.TS
 
-[![NPM Version](https://img.shields.io/npm/v/llamaindex)](https://www.npmjs.com/package/llamaindex)
-[![NPM License](https://img.shields.io/npm/l/llamaindex)](https://www.npmjs.com/package/llamaindex)
-[![NPM Downloads](https://img.shields.io/npm/dm/llamaindex)](https://www.npmjs.com/package/llamaindex)
-[![Discord](https://img.shields.io/discord/1059199217496772688)](https://discord.com/invite/eN6D2HQ4aX)
+LlamaIndex is a data framework for your LLM application.
 
-Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in JS runtime environments with TypeScript support.
+Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in Typescript and Javascript.
 
 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.
 
-## Compatibility
+## Getting started with an example:
 
-### Multiple JS Environment Support
+LlamaIndex.TS requries Node v18 or higher. You can download it from https://nodejs.org or use https://nvm.sh (our preferred option).
 
-LlamaIndex.TS supports multiple JS environments, including:
+In a new folder:
 
-- Node.js >= 20 ✅
-- Deno ✅
-- Bun ✅
-- Nitro ✅
-- Vercel Edge Runtime ✅ (with some limitations)
-- Cloudflare Workers ✅ (with some limitations)
-
-For now, browser support is limited due to the lack of support for [AsyncLocalStorage-like APIs](https://github.com/tc39/proposal-async-context)
-
-### Supported LLMs:
-
-- OpenAI LLms
-- Anthropic LLms
-- Groq LLMs
-- Llama2, Llama3, Llama3.1 LLMs
-- MistralAI LLMs
-- Fireworks LLMs
-- DeepSeek LLMs
-- ReplicateAI LLMs
-- TogetherAI LLMs
-- HuggingFace LLms
-- DeepInfra LLMs
-- Gemini LLMs
-
-## Getting started
-
-```shell
-npm install llamaindex
+```bash
+export OPENAI_API_KEY="sk-......" # Replace with your key from https://platform.openai.com/account/api-keys
+pnpm init
+pnpm install typescript
+pnpm exec tsc --init # if needed
 pnpm install llamaindex
-yarn add llamaindex
+pnpm install @types/node
 ```
 
-### Setup in Node.js, Deno, Bun, TypeScript...?
+Create the file example.ts
 
-See our official document: <https://ts.llamaindex.ai/docs/llamaindex/getting_started/>
+```ts
+// example.ts
+import fs from "fs/promises";
+import { Document, VectorStoreIndex } from "llamaindex";
 
-### Adding provider packages
+async function main() {
+  // Load essay from abramov.txt in Node
+  const essay = await fs.readFile(
+    "node_modules/llamaindex/examples/abramov.txt",
+    "utf-8",
+  );
 
-In most cases, you'll also need to install provider packages to use LlamaIndexTS. These are for adding AI models, file readers for ingestion or storing documents, e.g. in vector databases.
+  // Create Document object with essay
+  const document = new Document({ text: essay });
 
-For example, to use the OpenAI LLM, you would install the following package:
+  // Split text and create embeddings. Store them in a VectorStoreIndex
+  const index = await VectorStoreIndex.fromDocuments([document]);
 
-```shell
-npm install @llamaindex/openai
-pnpm install @llamaindex/openai
-yarn add @llamaindex/openai
+  // Query the index
+  const queryEngine = index.asQueryEngine();
+  const response = await queryEngine.query(
+    "What did the author do in college?",
+  );
+
+  // Output response
+  console.log(response.toString());
+}
+
+main();
+```
+
+Then you can run it using
+
+```bash
+pnpx ts-node example.ts
 ```
 
 ## Playground
@@ -83,25 +70,50 @@ Check out our NextJS playground at https://llama-playground.vercel.app/. The sou
 
 ## Core concepts for getting started:
 
-- [Document](/packages/llamaindex/src/Node.ts): A document represents a text file, PDF file or other contiguous piece of data.
+- [Document](/packages/core/src/Node.ts): A document represents a text file, PDF file or other contiguous piece of data.
 
-- [Node](/packages/llamaindex/src/Node.ts): The basic data building block. Most commonly, these are parts of the document split into manageable pieces that are small enough to be fed into an embedding model and LLM.
+- [Node](/packages/core/src/Node.ts): The basic data building block. Most commonly, these are parts of the document split into manageable pieces that are small enough to be fed into an embedding model and LLM.
 
-- [Embedding](/packages/llamaindex/src/embeddings/OpenAIEmbedding.ts): Embeddings are sets of floating point numbers which represent the data in a Node. By comparing the similarity of embeddings, we can derive an understanding of the similarity of two pieces of data. One use case is to compare the embedding of a question with the embeddings of our Nodes to see which Nodes may contain the data needed to answer that question. Because the default service context is OpenAI, the default embedding is `OpenAIEmbedding`. If using different models, say through Ollama, use this [Embedding](/packages/llamaindex/src/embeddings/OllamaEmbedding.ts) (see all [here](/packages/llamaindex/src/embeddings)).
+- [Embedding](/packages/core/src/Embedding.ts): Embeddings are sets of floating point numbers which represent the data in a Node. By comparing the similarity of embeddings, we can derive an understanding of the similarity of two pieces of data. One use case is to compare the embedding of a question with the embeddings of our Nodes to see which Nodes may contain the data needed to answer that quesiton.
 
-- [Indices](/packages/llamaindex/src/indices/): Indices store the Nodes and the embeddings of those nodes. QueryEngines retrieve Nodes from these Indices using embedding similarity.
+- [Indices](/packages/core/src/indices/): Indices store the Nodes and the embeddings of those nodes. QueryEngines retrieve Nodes from these Indices using embedding similarity.
 
-- [QueryEngine](/packages/llamaindex/src/engines/query/RetrieverQueryEngine.ts): Query engines are what generate the query you put in and give you back the result. Query engines generally combine a pre-built prompt with selected Nodes from your Index to give the LLM the context it needs to answer your query. To build a query engine from your Index (recommended), use the [`asQueryEngine`](/packages/llamaindex/src/indices/BaseIndex.ts) method on your Index. See all query engines [here](/packages/llamaindex/src/engines/query).
+- [QueryEngine](/packages/core/src/QueryEngine.ts): Query engines are what generate the query you put in and give you back the result. Query engines generally combine a pre-built prompt with selected Nodes from your Index to give the LLM the context it needs to answer your query.
 
-- [ChatEngine](/packages/llamaindex/src/engines/chat/SimpleChatEngine.ts): A ChatEngine helps you build a chatbot that will interact with your Indices. See all chat engines [here](/packages/llamaindex/src/engines/chat).
+- [ChatEngine](/packages/core/src/ChatEngine.ts): A ChatEngine helps you build a chatbot that will interact with your Indices.
 
-- [SimplePrompt](/packages/llamaindex/src/Prompt.ts): A simple standardized function call definition that takes in inputs and formats them in a template literal. SimplePrompts can be specialized using currying and combined using other SimplePrompt functions.
+- [SimplePrompt](/packages/core/src/Prompt.ts): A simple standardized function call definition that takes in inputs and formats them in a template literal. SimplePrompts can be specialized using currying and combined using other SimplePrompt functions.
+
+## Note: NextJS:
+
+If you're using NextJS App Router, you'll need to use the NodeJS runtime (default) and add the follow config to your next.config.js to have it use imports/exports in the same way Node does.
+
+```js
+export const runtime = "nodejs"; // default
+```
+
+```js
+// next.config.js
+/** @type {import('next').NextConfig} */
+const nextConfig = {
+  experimental: {
+    serverComponentsExternalPackages: ["pdf-parse"], // Puts pdf-parse in actual NodeJS mode with NextJS App Router
+  },
+};
+
+module.exports = nextConfig;
+```
+
+## Supported LLMs:
+
+- OpenAI GPT-3.5-turbo and GPT-4
+- Anthropic Claude Instant and Claude 2
+- Llama2 Chat LLMs (70B, 13B, and 7B parameters)
 
 ## Contributing:
 
-Please see our [contributing guide](CONTRIBUTING.md) for more information.
-You are highly encouraged to contribute to LlamaIndex.TS!
+We are in the very early days of LlamaIndex.TS. If you’re interested in hacking on it with us check out our [contributing guide](/CONTRIBUTING.md)
 
-## Community
+## Bugs? Questions?
 
 Please join our Discord! https://discord.com/invite/eN6D2HQ4aX

apps/docs/.gitignore

@@ -0,0 +1,20 @@
+# Dependencies
+/node_modules
+
+# Production
+/build
+
+# Generated files
+.docusaurus
+.cache-loader
+
+# Misc
+.DS_Store
+.env.local
+.env.development.local
+.env.test.local
+.env.production.local
+
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*

apps/docs/README-docusaurus.md

@@ -0,0 +1,47 @@
+# Website
+
+This website is built using [Docusaurus 2](https://docusaurus.io/), a modern static website generator.
+
+### Installation
+
+```
+$ pnpm
+```
+
+### Local Development
+
+```
+$ pnpm start
+```
+
+This command starts a local development server and opens up a browser window. Most changes are reflected live without having to restart the server.
+
+However, the searchbar may not function with `yarn start`. Instead, run `yarn build` and launch a server:
+
+```
+$ npx http-server ./build
+```
+
+### Build
+
+```
+$ pnpm build
+```
+
+This command generates static content into the `build` directory and can be served using any static contents hosting service.
+
+### Deployment
+
+Using SSH:
+
+```
+$ USE_SSH=true pnpm deploy
+```
+
+Not using SSH:
+
+```
+$ GIT_USER=<Your GitHub username> pnpm deploy
+```
+
+If you are using GitHub pages for hosting, this command is a convenient way to build the website and push to the `gh-pages` branch.

apps/docs/babel.config.js

@@ -0,0 +1,3 @@
+module.exports = {
+  presets: [require.resolve("@docusaurus/core/lib/babel/preset")],
+};

apps/docs/docs/.gitignore

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

apps/docs/docs/concepts.md

@@ -1,7 +1,9 @@
 ---
-title: Concepts
+sidebar_position: 3
 ---
 
+# High-Level Concepts
+
 LlamaIndex.TS helps you build LLM-powered applications (e.g. Q&A, chatbot) over custom data.
 
 In this high-level concepts guide, you will learn:
@@ -16,7 +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).
 
@@ -28,14 +30,14 @@ 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**](/docs/llamaindex/modules/data_loaders/index):
+[**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).
 
-[**Documents / Nodes**](/docs/llamaindex/modules/documents_and_nodes/index): A `Document` is a generic container around any data source - for instance, a PDF, an API output, or retrieved data from a database. A `Node` is the atomic unit of data in LlamaIndex and represents a "chunk" of a source `Document`. It's a rich representation that includes metadata and relationships (to other nodes) to enable accurate and expressive retrieval operations.
+[**Documents / Nodes**](./modules/high_level/documents_and_nodes.md): A `Document` is a generic container around any data source - for instance, a PDF, an API output, or retrieved data from a database. A `Node` is the atomic unit of data in LlamaIndex and represents a "chunk" of a source `Document`. It's a rich representation that includes metadata and relationships (to other nodes) to enable accurate and expressive retrieval operations.
 
-[**Data Indexes**](/docs/llamaindex/modules/data_index):
+[**Data Indexes**](./modules/high_level/data_index.md):
 Once you've ingested your data, LlamaIndex helps you index data into a format that's easy to retrieve.
 
 Under the hood, LlamaIndex parses the raw documents into intermediate representations, calculates vector embeddings, and stores your data in-memory or to disk.
@@ -54,23 +56,23 @@ 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
 
-[**Retrievers**](/docs/llamaindex/modules/retriever):
+[**Retrievers**](./modules/low_level/retriever.md):
 A retriever defines how to efficiently retrieve relevant context from a knowledge base (i.e. index) when given a query.
-The specific retrieval logic differs for different indices, the most popular being dense retrieval against a vector index.
+The specific retrieval logic differs for difference indices, the most popular being dense retrieval against a vector index.
 
-[**Response Synthesizers**](/docs/llamaindex/modules/response_synthesizer):
+[**Response Synthesizers**](./modules/low_level/response_synthesizer.md):
 A response synthesizer generates a response from an LLM, using a user query and a given set of retrieved text chunks.
 
 #### Pipelines
 
-[**Query Engines**](/docs/llamaindex/modules/query_engines):
+[**Query Engines**](./modules/high_level/query_engine.md):
 A query engine is an end-to-end pipeline that allow you to ask question over your data.
 It takes in a natural language query, and returns a response, along with reference context retrieved and passed to the LLM.
 
-[**Chat Engines**](/docs/llamaindex/modules/chat_engine):
+[**Chat Engines**](./modules/high_level/chat_engine.md):
 A chat engine is an end-to-end pipeline for having a conversation with your data
 (multiple back-and-forth instead of a single question & answer).

apps/docs/docs/end_to_end.md

@@ -0,0 +1,45 @@
+---
+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/apps/simple/chatEngine.ts)
+
+Read a file and chat about it with the LLM.
+
+## [Vector Index](https://github.com/run-llama/LlamaIndexTS/blob/main/apps/simple/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/apps/simple/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/apps/simple/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/apps/simple/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/apps/simple/openai.ts)
+
+Create an OpenAI LLM and directly use it for chat.
+
+## [Llama2 DeuceLLM](https://github.com/run-llama/LlamaIndexTS/blob/main/apps/simple/llamadeuce.ts)
+
+Create a Llama-2 LLM and directly use it for chat.
+
+## [SubQuestionQueryEngine](https://github.com/run-llama/LlamaIndexTS/blob/main/apps/simple/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/apps/simple/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.

apps/docs/docs/environments.md

@@ -0,0 +1,29 @@
+---
+sidebar_position: 5
+---
+
+# Environments
+
+LlamaIndex currently officially supports NodeJS 18 and NodeJS 20.
+
+## NextJS App Router
+
+If you're using NextJS App Router route handlers/serverless functions, you'll need to use the NodeJS mode:
+
+```js
+export const runtime = "nodejs"; // default
+```
+
+and you'll need to add an exception for pdf-parse in your next.config.js
+
+```js
+// next.config.js
+/** @type {import('next').NextConfig} */
+const nextConfig = {
+  experimental: {
+    serverComponentsExternalPackages: ["pdf-parse"], // Puts pdf-parse in actual NodeJS mode with NextJS App Router
+  },
+};
+
+module.exports = nextConfig;
+```

apps/docs/docs/installation.md

@@ -0,0 +1,25 @@
+---
+sidebar_position: 1
+---
+
+# Installation and Setup
+
+## Installation from NPM
+
+Make sure you have NodeJS v18 or higher.
+
+```bash npm2yarn
+npm install llamaindex
+```
+
+## Environment variables
+
+Our examples use OpenAI by default. You'll need to set up your Open AI key like so:
+
+```bash
+export OPENAI_API_KEY="sk-......" # Replace with your key from https://platform.openai.com/account/api-keys
+```
+
+If you want to have it automatically loaded every time, add it to your .zshrc/.bashrc.
+
+WARNING: do not check in your OpenAI key into version control.

apps/docs/docs/introduction.md

@@ -0,0 +1,56 @@
+---
+sidebar_position: 0
+slug: /
+---
+
+# What is LlamaIndex.TS?
+
+LlamaIndex.TS is a data framework for LLM applications to ingest, structure, and access private or domain-specific data. While a python package is also available (see [here](https://gpt-index.readthedocs.io/en/latest/)), LlamaIndex.TS offers core features in a simple package, optimized for usage with TypeScript.
+
+## 🚀 Why LlamaIndex.TS?
+
+At their core, LLMs offer a natural language interface between humans and inferred data. Widely available models come pre-trained on huge amounts of publicly available data, from Wikipedia and mailing lists to textbooks and source code.
+
+Applications built on top of LLMs often require augmenting these models with private or domain-specific data. Unfortunately, that data can be distributed across siloed applications and data stores. It's behind APIs, in SQL databases, or trapped in PDFs and slide decks.
+
+That's where **LlamaIndex.TS** comes in.
+
+## 🦙 How can LlamaIndex.TS help?
+
+LlamaIndex.TS provides the following tools:
+
+- **Data loading** ingest your existing `.txt`, `.pdf`, `.csv`, `.md` and `.docx` data directly
+- **Data indexes** structure your data in intermediate representations that are easy and performant for LLMs to consume.
+- **Engines** provide natural language access to your data. For example:
+  - Query engines are powerful retrieval interfaces for knowledge-augmented output.
+  - Chat engines are conversational interfaces for multi-message, "back and forth" interactions with your data.
+
+## 👨‍👩‍👧‍👦 Who is LlamaIndex for?
+
+LlamaIndex.TS provides a core set of tools, essential for anyone building LLM apps with JavaScript and TypeScript.
+
+Our high-level API allows beginner users to use LlamaIndex.TS to ingest and query their data.
+
+For more complex applications, our lower-level APIs allow advanced users to customize and extend any module—data connectors, indices, retrievers, and query engines, to fit their needs.
+
+## Getting Started
+
+`npm install llamaindex`
+
+Our documentation includes [Installation Instructions](./installation.md) 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).
+
+## 🗺️ Ecosystem
+
+To download or contribute, find LlamaIndex on:
+
+- Github: https://github.com/run-llama/LlamaIndexTS
+- NPM: https://www.npmjs.com/package/llamaindex
+
+## Community
+
+Need help? Have a feature suggestion? Join the LlamaIndex community:
+
+- Twitter: https://twitter.com/llama_index
+- Discord https://discord.gg/dGcwcsnxhU

apps/docs/docs/modules/_category_.yml

@@ -0,0 +1,3 @@
+label: "Modules"
+collapsed: false
+position: 5

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

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

apps/docs/docs/modules/high_level/chat_engine.md

@@ -0,0 +1,20 @@
+---
+sidebar_position: 4
+---
+
+# ChatEngine
+
+The chat engine is a quick and simple way to chat with the data in your index.
+
+```typescript
+const retriever = index.asRetriever();
+const chatEngine = new ContextChatEngine({ retriever });
+
+// start chatting
+const response = await chatEngine.chat(query);
+```
+
+## Api References
+
+- [ContextChatEngine](../../api/classes/ContextChatEngine.md)
+- [CondenseQuestionChatEngine](../../api/classes/ContextChatEngine.md)

apps/docs/docs/modules/high_level/data_index.md

@@ -1,12 +1,13 @@
 ---
-title: Index
+sidebar_position: 2
 ---
 
+# Index
+
 An index is the basic container and organization for your data. LlamaIndex.TS supports two indexes:
 
 - `VectorStoreIndex` - will send the top-k `Node`s to the LLM when generating a response. The default top-k is 2.
 - `SummaryIndex` - will send every `Node` in the index to the LLM in order to generate a response
-- `KeywordTableIndex` extracts and provides keywords from `Node`s to the LLM
 
 ```typescript
 import { Document, VectorStoreIndex } from "llamaindex";
@@ -18,6 +19,5 @@ const index = await VectorStoreIndex.fromDocuments([document]);
 
 ## API Reference
 
-- [SummaryIndex](/docs/api/classes/SummaryIndex)
-- [VectorStoreIndex](/docs/api/classes/VectorStoreIndex)
-- [KeywordTableIndex](/docs/api/classes/KeywordTableIndex)
+- [SummaryIndex](../../api/classes/SummaryIndex.md)
+- [VectorStoreIndex](../../api/classes/VectorStoreIndex.md)

apps/docs/docs/modules/high_level/data_loader.md

@@ -0,0 +1,17 @@
+---
+sidebar_position: 1
+---
+
+# Reader / Loader
+
+LlamaIndex.TS supports easy loading of files from folders using the `SimpleDirectoryReader` class. Currently, `.txt`, `.pdf`, `.csv`, `.md` and `.docx` files are supported, with more planned in the future!
+
+```typescript
+import { SimpleDirectoryReader } from "llamaindex";
+
+documents = new SimpleDirectoryReader().loadData("./data");
+```
+
+## API Reference
+
+- [SimpleDirectoryReader](../../api/classes/SimpleDirectoryReader.md)

apps/docs/docs/modules/high_level/documents_and_nodes.md

@@ -1,7 +1,9 @@
 ---
-title: Documents and Nodes
+sidebar_position: 0
 ---
 
+# Documents and Nodes
+
 `Document`s and `Node`s are the basic building blocks of any index. While the API for these objects is similar, `Document` objects represent entire files, while `Node`s are smaller pieces of that original document, that are suitable for an LLM and Q&A.
 
 ```typescript
@@ -12,5 +14,5 @@ document = new Document({ text: "text", metadata: { key: "val" } });
 
 ## API Reference
 
-- [Document](/docs/api/classes/Document)
-- [TextNode](/docs/api/classes/TextNode)
+- [Document](../../api/classes/Document.md)
+- [TextNode](../../api/classes/TextNode.md)

apps/docs/docs/modules/high_level/query_engine.md

@@ -1,21 +1,14 @@
 ---
-title: QueryEngine
+sidebar_position: 3
 ---
 
-A query engine wraps a `Retriever` and a `ResponseSynthesizer` into a pipeline, that will use the query string to fetch nodes and then send them to the LLM to generate a response.
+# QueryEngine
+
+A query engine wraps a `Retriever` and a `ResponseSynthesizer` into a pipeline, that will use the query string to fetech nodes and then send them to the LLM to generate a response.
 
 ```typescript
 const queryEngine = index.asQueryEngine();
-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);
-}
+const response = await queryEngine.query("query string");
 ```
 
 ## Sub Question Query Engine
@@ -24,7 +17,7 @@ The basic concept of the Sub Question Query Engine is that it splits a single qu
 
 ### Getting Started
 
-The easiest way to start trying the Sub Question Query Engine is running the subquestion.ts file in [examples](https://github.com/run-llama/LlamaIndexTS/blob/main/examples/subquestion.ts).
+The easiest way to start trying the Sub Question Query Engine is running the subquestion.ts file in [apps/simple](https://github.com/run-llama/LlamaIndexTS/blob/main/apps/simple/subquestion.ts).
 
 ```bash
 npx ts-node subquestion.ts
@@ -38,6 +31,6 @@ You can learn more about Tools by taking a look at the LlamaIndex Python documen
 
 ## API Reference
 
-- [RetrieverQueryEngine](/docs/api/classes/RetrieverQueryEngine)
-- [SubQuestionQueryEngine](/docs/api/classes/SubQuestionQueryEngine)
-- [QueryEngineTool](/docs/api/classes/QueryEngineTool)
+- [RetrieverQueryEngine](../../api/classes/RetrieverQueryEngine.md)
+- [SubQuestionQueryEngine](../../api/classes/SubQuestionQueryEngine.md)
+- [QueryEngineTool](../../api/interfaces/QueryEngineTool.md)

apps/docs/docs/modules/index.md

@@ -0,0 +1,31 @@
+# Core Modules
+
+LlamaIndex.TS offers several core modules, seperated into high-level modules for quickly getting started, and low-level modules for customizing key components as you need.
+
+## High-Level Modules
+
+- [**Document**](./high_level/documents_and_nodes.md): A document represents a text file, PDF file or other contiguous piece of data.
+
+- [**Node**](./high_level/documents_and_nodes.md): The basic data building block. Most commonly, these are parts of the document split into manageable pieces that are small enough to be fed into an embedding model and LLM.
+
+- [**Reader/Loader**](./high_level/data_loader.md): A reader or loader is something that takes in a document in the real world and transforms into a Document class that can then be used in your Index and queries. We currently support plain text files and PDFs with many many more to come.
+
+- [**Indexes**](./high_level/data_index.md): indexes store the Nodes and the embeddings of those nodes.
+
+- [**QueryEngine**](./high_level/query_engine.md): Query engines are what generate the query you put in and give you back the result. Query engines generally combine a pre-built prompt with selected nodes from your Index to give the LLM the context it needs to answer your query.
+
+- [**ChatEngine**](./high_level/chat_engine.md): A ChatEngine helps you build a chatbot that will interact with your Indexes.
+
+## Low Level Module
+
+- [**LLM**](./low_level/llm.md): The LLM class is a unified interface over a large language model provider such as OpenAI GPT-4, Anthropic Claude, or Meta LLaMA. You can subclass it to write a connector to your own large language model.
+
+- [**Embedding**](./low_level/embedding.md): An embedding is represented as a vector of floating point numbers. OpenAI's text-embedding-ada-002 is our default embedding model and each embedding it generates consists of 1,536 floating point numbers. Another popular embedding model is BERT which uses 768 floating point numbers to represent each Node. We provide a number of utilities to work with embeddings including 3 similarity calculation options and Maximum Marginal Relevance
+
+- [**TextSplitter/NodeParser**](./low_level/node_parser.md): Text splitting strategies are incredibly important to the overall efficacy of the embedding search. Currently, while we do have a default, there's no one size fits all solution. Depending on the source documents, you may want to use different splitting sizes and strategies. Currently we support spliltting by fixed size, splitting by fixed size with overlapping sections, splitting by sentence, and splitting by paragraph. The text splitter is used by the NodeParser when splitting `Document`s into `Node`s.
+
+- [**Retriever**](./low_level/retriever.md): The Retriever is what actually chooses the Nodes to retrieve from the index. Here, you may wish to try retrieving more or fewer Nodes per query, changing your similarity function, or creating your own retriever for each individual use case in your application. For example, you may wish to have a separate retriever for code content vs. text content.
+
+- [**ResponseSynthesizer**](./low_level/response_synthesizer.md): The ResponseSynthesizer is responsible for taking a query string, and using a list of `Node`s to generate a response. This can take many forms, like iterating over all the context and refining an answer, or building a tree of summaries and returning the root summary.
+
+- [**Storage**](./low_level/storage.md): At some point you're going to want to store your indexes, data and vectors instead of re-running the embedding models every time. IndexStore, DocStore, VectorStore, and KVStore are abstractions that let you do that. Combined, they form the StorageContext. Currently, we allow you to persist your embeddings in files on the filesystem (or a virtual in memory file system), but we are also actively adding integrations to Vector Databases.

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

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

apps/docs/docs/modules/low_level/embedding.md

@@ -0,0 +1,22 @@
+---
+sidebar_position: 1
+---
+
+# Embedding
+
+The embedding model in LlamaIndex is responsible for creating numerical representations of text. By default, LlamaIndex will use the `text-embedding-ada-002` model from OpenAI.
+
+This can be explicitly set in the `ServiceContext` object.
+
+```typescript
+import { OpenAIEmbedding, serviceContextFromDefaults } from "llamaindex";
+
+const openaiEmbeds = new OpenAIEmbedding();
+
+const serviceContext = serviceContextFromDefaults({ embedModel: openaiEmbeds });
+```
+
+## API Reference
+
+- [OpenAIEmbedding](../../api/classes/OpenAIEmbedding.md)
+- [ServiceContext](../../api/interfaces/ServiceContext.md)

apps/docs/docs/modules/low_level/llm.md

@@ -0,0 +1,22 @@
+---
+sidebar_position: 0
+---
+
+# LLM
+
+The LLM is responsible for reading text and generating natural language responses to queries. By default, LlamaIndex.TS uses `gpt-3.5-turbo`.
+
+The LLM can be explicitly set in the `ServiceContext` object.
+
+```typescript
+import { OpenAI, serviceContextFromDefaults } from "llamaindex";
+
+const openaiLLM = new OpenAI({ model: "gpt-3.5-turbo", temperature: 0 });
+
+const serviceContext = serviceContextFromDefaults({ llm: openaiLLM });
+```
+
+## API Reference
+
+- [OpenAI](../../api/classes/OpenAI.md)
+- [ServiceContext](../../api/interfaces/ServiceContext.md)

apps/docs/docs/modules/low_level/node_parser.md

@@ -0,0 +1,33 @@
+---
+sidebar_position: 3
+---
+
+# NodeParser
+
+The `NodeParser` in LlamaIndex is responbile for splitting `Document` objects into more manageable `Node` objects. When you call `.fromDocuments()`, the `NodeParser` from the `ServiceContext` is used to do this automatically for you. Alternatively, you can use it to split documents ahead of time.
+
+```typescript
+import { Document, SimpleNodeParser } from "llamaindex";
+
+const nodeParser = new SimpleNodeParser();
+const nodes = nodeParser.getNodesFromDocuments([
+  new Document({ text: "I am 10 years old. John is 20 years old." }),
+]);
+```
+
+## TextSplitter
+
+The underlying text splitter will split text by sentences. It can also be used as a standalone module for splitting raw text.
+
+```typescript
+import { SentenceSplitter } from "llamaindex";
+
+const splitter = new SentenceSplitter({ chunkSize: 1 });
+
+const textSplits = splitter.splitText("Hello World");
+```
+
+## API Reference
+
+- [SimpleNodeParser](../../api/classes/SimpleNodeParser.md)
+- [SentenceSplitter](../../api/classes/SentenceSplitter.md)

apps/docs/docs/modules/low_level/response_synthesizer.md

@@ -1,7 +1,9 @@
 ---
-title: ResponseSynthesizer
+sidebar_position: 6
 ---
 
+# ResponseSynthesizer
+
 The ResponseSynthesizer is responsible for sending the query, nodes, and prompt templates to the LLM to generate a response. There are a few key modes for generating a response:
 
 - `Refine`: "create and refine" an answer by sequentially going through each retrieved text chunk.
@@ -18,7 +20,7 @@ The ResponseSynthesizer is responsible for sending the query, nodes, and prompt
   chunk.
 
 ```typescript
-import { NodeWithScore, TextNode, ResponseSynthesizer } from "llamaindex";
+import { NodeWithScore, ResponseSynthesizer, TextNode } from "llamaindex";
 
 const responseSynthesizer = new ResponseSynthesizer();
 
@@ -33,30 +35,17 @@ const nodesWithScore: NodeWithScore[] = [
   },
 ];
 
-const response = await responseSynthesizer.synthesize({
-  query: "What age am I?",
+const response = await responseSynthesizer.synthesize(
+  "What age am I?",
   nodesWithScore,
-});
+);
 console.log(response.response);
 ```
 
-The `synthesize` function also supports streaming, just add `stream: true` as an option:
-
-```typescript
-const stream = await responseSynthesizer.synthesize({
-  query: "What age am I?",
-  nodesWithScore,
-  stream: true,
-});
-for await (const chunk of stream) {
-  process.stdout.write(chunk.response);
-}
-```
-
 ## API Reference
 
-- [ResponseSynthesizer](/docs/api/classes/ResponseSynthesizer)
-- [Refine](/docs/api/classes/Refine)
-- [CompactAndRefine](/docs/api/classes/CompactAndRefine)
-- [TreeSummarize](/docs/api/classes/TreeSummarize)
-- [SimpleResponseBuilder](/docs/api/classes/SimpleResponseBuilder)
+- [ResponseSynthesizer](../../api/classes/ResponseSynthesizer.md)
+- [Refine](../../api/classes/Refine.md)
+- [CompactAndRefine](../../api/classes/CompactAndRefine.md)
+- [TreeSummarize](../../api/classes/TreeSummarize.md)
+- [SimpleResponseBuilder](../../api/classes/SimpleResponseBuilder.md)

apps/docs/docs/modules/low_level/retriever.md

@@ -0,0 +1,21 @@
+---
+sidebar_position: 5
+---
+
+# Retriever
+
+A retriever in LlamaIndex is what is used to fetch `Node`s from an index using a query string. Aa `VectorIndexRetriever` will fetch the top-k most similar nodes. Meanwhile, a `SummaryIndexRetriever` will fetch all nodes no matter the query.
+
+```typescript
+const retriever = vector_index.asRetriever();
+retriever.similarityTopK = 3;
+
+// Fetch nodes!
+const nodesWithScore = await retriever.retrieve("query string");
+```
+
+## API Reference
+
+- [SummaryIndexRetriever](../../api/classes/SummaryIndexRetriever.md)
+- [SummaryIndexLLMRetriever](../../api/classes/SummaryIndexLLMRetriever.md)
+- [VectorIndexRetriever](../../api/classes/VectorIndexRetriever.md)

apps/docs/docs/modules/low_level/storage.md

@@ -0,0 +1,26 @@
+---
+sidebar_position: 7
+---
+
+# Storage
+
+Storage in LlamaIndex.TS works automatically once you've configured a `StorageContext` object. Just configure the `persistDir` and attach it to an index.
+
+Right now, only saving and loading from disk is supported, with future integrations planned!
+
+```typescript
+import { Document, VectorStoreIndex, storageContextFromDefaults } from "./src";
+
+const storageContext = await storageContextFromDefaults({
+  persistDir: "./storage",
+});
+
+const document = new Document({ text: "Test Text" });
+const index = await VectorStoreIndex.fromDocuments([document], {
+  storageContext,
+});
+```
+
+## API Reference
+
+- [StorageContext](../../api/interfaces/StorageContext.md)

apps/docs/docs/starter.md

@@ -0,0 +1,56 @@
+---
+sidebar_position: 2
+---
+
+# Starter Tutorial
+
+Once you have [installed LlamaIndex.TS using NPM](installation.md) and set up your OpenAI key, you're ready to start your first app:
+
+In a new folder:
+
+```bash npm2yarn
+npm install typescript
+npm install @types/node
+npx tsc --init # if needed
+```
+
+Create the file `example.ts`. This code will load some example data, create a document, index it (which creates embeddings using OpenAI), and then creates query engine to answer questions about the data.
+
+```ts
+// example.ts
+import fs from "fs/promises";
+import { Document, VectorStoreIndex } from "llamaindex";
+
+async function main() {
+  // Load essay from abramov.txt in Node
+  const essay = await fs.readFile(
+    "node_modules/llamaindex/examples/abramov.txt",
+    "utf-8",
+  );
+
+  // Create Document object with essay
+  const document = new Document({ text: essay });
+
+  // Split text and create embeddings. Store them in a VectorStoreIndex
+  const index = await VectorStoreIndex.fromDocuments([document]);
+
+  // Query the index
+  const queryEngine = index.asQueryEngine();
+  const response = await queryEngine.query(
+    "What did the author do in college?",
+  );
+
+  // Output response
+  console.log(response.toString());
+}
+
+main();
+```
+
+Then you can run it using
+
+```bash
+npx ts-node example.ts
+```
+
+Ready to learn more? Check out our NextJS playground at https://llama-playground.vercel.app/. The source is available at https://github.com/run-llama/ts-playground

apps/docs/docusaurus.config.js

@@ -0,0 +1,152 @@
+// @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");
+
+/** @type {import('@docusaurus/types').Config} */
+const config = {
+  title: "LlamaIndex.TS",
+  tagline: "Unleash the power of LLMs over your data in TypeScript",
+  favicon: "img/favicon.png",
+
+  // Set the production url of your site here
+  url: "https://ts.llamaindex.ai",
+  // Set the /<baseUrl>/ pathname under which your site is served
+  // For GitHub pages deployment, it is often '/<projectName>/'
+  baseUrl: "/",
+
+  // GitHub pages deployment config.
+  // If you aren't using GitHub pages, you don't need these.
+  organizationName: "run-llama", // Usually your GitHub org/user name.
+  projectName: "LlamaIndex.TS", // Usually your repo name.
+
+  onBrokenLinks: "warn",
+  onBrokenMarkdownLinks: "warn",
+
+  // Even if you don't use internalization, you can use this field to set useful
+  // metadata like html lang. For example, if your site is Chinese, you may want
+  // to replace "en" with "zh-Hans".
+  i18n: {
+    defaultLocale: "en",
+    locales: ["en"],
+  },
+
+  presets: [
+    [
+      "classic",
+      /** @type {import('@docusaurus/preset-classic').Options} */
+      ({
+        docs: {
+          routeBasePath: "/",
+          sidebarPath: require.resolve("./sidebars.js"),
+          // Please change this to your repo.
+          // Remove this to remove the "edit this page" links.
+          // editUrl:
+          //   "https://github.com/facebook/docusaurus/tree/main/packages/create-docusaurus/templates/shared/",
+          remarkPlugins: [
+            [require("@docusaurus/remark-plugin-npm2yarn"), { sync: true }],
+          ],
+        },
+        blog: false,
+      }),
+    ],
+  ],
+
+  themeConfig:
+    /** @type {import('@docusaurus/preset-classic').ThemeConfig} */
+    ({
+      // Replace with your project's social card
+      image: "img/favicon.png", // TODO change this
+      navbar: {
+        title: "LlamaIndex.TS",
+        logo: {
+          alt: "LlamaIndex.TS",
+          src: "img/favicon.png",
+        },
+        items: [
+          {
+            type: "docSidebar",
+            sidebarId: "mySidebar",
+            position: "left",
+            label: "Docs",
+          },
+          {
+            href: "https://github.com/run-llama/LlamaIndexTS",
+            label: "GitHub",
+            position: "right",
+          },
+        ],
+      },
+      footer: {
+        style: "dark",
+        links: [
+          {
+            title: "Docs",
+            items: [
+              {
+                label: "API",
+                to: "/api",
+              },
+            ],
+          },
+          {
+            title: "Community",
+            items: [
+              {
+                label: "Discord",
+                href: "https://discord.com/invite/eN6D2HQ4aX",
+              },
+              {
+                label: "Twitter",
+                href: "https://twitter.com/LlamaIndex",
+              },
+            ],
+          },
+          {
+            title: "More",
+            items: [
+              {
+                label: "GitHub",
+                href: "https://github.com/run-llama/LlamaIndexTS",
+              },
+            ],
+          },
+        ],
+        copyright: `Copyright © ${new Date().getFullYear()} LlamaIndex. Built with Docusaurus.`,
+      },
+      prism: {
+        theme: lightCodeTheme,
+        darkTheme: darkCodeTheme,
+      },
+      algolia: {
+        // The application ID provided by Algolia
+        appId: "DYKPM6G4CX",
+
+        // Public API key: it is safe to commit it
+        apiKey: "c4ff3789f20bb72a5d735082aef17719",
+
+        indexName: "ts-llamaindex",
+
+        // Optional: see doc section below
+        contextualSearch: true,
+      },
+    }),
+  plugins: [
+    [
+      "docusaurus-plugin-typedoc",
+      {
+        entryPoints: ["../../packages/core/src/index.ts"],
+        tsconfig: "../../packages/core/tsconfig.json",
+        readme: "none",
+        sourceLinkTemplate:
+          "https://github.com/run-llama/LlamaIndexTS/blob/{gitRevision}/{path}#L{line}",
+        sidebar: {
+          position: 6,
+        },
+      },
+    ],
+  ],
+};
+
+module.exports = config;

apps/docs/package.json

@@ -0,0 +1,53 @@
+{
+  "name": "docs",
+  "version": "0.0.0",
+  "private": true,
+  "scripts": {
+    "docusaurus": "docusaurus",
+    "start": "docusaurus start",
+    "build": "docusaurus build",
+    "swizzle": "docusaurus swizzle",
+    "deploy": "docusaurus deploy",
+    "clear": "docusaurus clear",
+    "serve": "docusaurus serve",
+    "write-translations": "docusaurus write-translations",
+    "write-heading-ids": "docusaurus write-heading-ids",
+    "typecheck": "tsc"
+  },
+  "dependencies": {
+    "@docusaurus/core": "2.4.3",
+    "@docusaurus/preset-classic": "2.4.3",
+    "@docusaurus/remark-plugin-npm2yarn": "^2.4.3",
+    "@mdx-js/react": "^1.6.22",
+    "clsx": "^1.2.1",
+    "postcss": "^8.4.31",
+    "prism-react-renderer": "^1.3.5",
+    "raw-loader": "^4.0.2",
+    "react": "^17.0.2",
+    "react-dom": "^17.0.2"
+  },
+  "devDependencies": {
+    "@docusaurus/module-type-aliases": "2.4.3",
+    "@docusaurus/types": "^2.4.3",
+    "@tsconfig/docusaurus": "^2.0.1",
+    "docusaurus-plugin-typedoc": "^0.19.2",
+    "typedoc": "^0.24.8",
+    "typedoc-plugin-markdown": "^3.16.0",
+    "typescript": "^4.9.5"
+  },
+  "browserslist": {
+    "production": [
+      ">0.5%",
+      "not dead",
+      "not op_mini all"
+    ],
+    "development": [
+      "last 1 chrome version",
+      "last 1 firefox version",
+      "last 1 safari version"
+    ]
+  },
+  "engines": {
+    "node": ">=16.14"
+  }
+}

apps/docs/sidebars.js

@@ -0,0 +1,33 @@
+/**
+ * Creating a sidebar enables you to:
+ - create an ordered group of docs
+ - render a sidebar for each doc of that group
+ - provide next/previous navigation
+
+ The sidebars can be generated from the filesystem, or explicitly defined here.
+
+ Create as many sidebars as you want.
+ */
+
+// @ts-check
+
+/** @type {import('@docusaurus/plugin-content-docs').SidebarsConfig} */
+const sidebars = {
+  // By default, Docusaurus generates a sidebar from the docs folder structure
+  mySidebar: [{ type: "autogenerated", dirName: "." }],
+
+  // But you can create a sidebar manually
+  /*
+  tutorialSidebar: [
+    'intro',
+    'hello',
+    {
+      type: 'category',
+      label: 'Tutorial',
+      items: ['tutorial-basics/create-a-document'],
+    },
+  ],
+   */
+};
+
+module.exports = sidebars;

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

@@ -0,0 +1,59 @@
+import clsx from "clsx";
+import React from "react";
+import styles from "./styles.module.css";
+
+type FeatureItem = {
+  title: string;
+  Svg: React.ComponentType<React.ComponentProps<"svg">>;
+  description: JSX.Element;
+};
+
+const FeatureList: FeatureItem[] = [
+  {
+    title: "Data Driven",
+    Svg: require("@site/static/img/undraw_docusaurus_mountain.svg").default,
+    description: <>LlamaIndex.TS is all about using your data with LLMs.</>,
+  },
+  {
+    title: "Typescript Native",
+    Svg: require("@site/static/img/undraw_docusaurus_tree.svg").default,
+    description: <>We ❤️ Typescript, and so do our users.</>,
+  },
+  {
+    title: "Built by the Community",
+    Svg: require("@site/static/img/undraw_docusaurus_react.svg").default,
+    description: (
+      <>
+        LlamaIndex.TS is a community project, and we welcome your contributions!
+      </>
+    ),
+  },
+];
+
+function Feature({ title, Svg, description }: FeatureItem) {
+  return (
+    <div className={clsx("col col--4")}>
+      <div className="text--center">
+        <Svg className={styles.featureSvg} role="img" />
+      </div>
+      <div className="text--center padding-horiz--md">
+        <h3>{title}</h3>
+        <p>{description}</p>
+      </div>
+    </div>
+  );
+}
+
+export default function HomepageFeatures(): JSX.Element {
+  return (
+    <section className={styles.features}>
+      <div className="container">
+        <div className="row">
+          {FeatureList.map((props, idx) => (
+            <Feature key={idx} {...props} />
+          ))}
+        </div>
+      </div>
+    </section>
+  );
+}

apps/docs/src/components/HomepageFeatures/styles.module.css

@@ -0,0 +1,11 @@
+.features {
+  display: flex;
+  align-items: center;
+  padding: 2rem 0;
+  width: 100%;
+}
+
+.featureSvg {
+  height: 200px;
+  width: 200px;
+}

apps/docs/src/css/custom.css

@@ -0,0 +1,30 @@
+/**
+ * Any CSS included here will be global. The classic template
+ * bundles Infima by default. Infima is a CSS framework designed to
+ * work well for content-centric websites.
+ */
+
+/* You can override the default Infima variables here. */
+:root {
+  --ifm-color-primary: #2e8555;
+  --ifm-color-primary-dark: #29784c;
+  --ifm-color-primary-darker: #277148;
+  --ifm-color-primary-darkest: #205d3b;
+  --ifm-color-primary-light: #33925d;
+  --ifm-color-primary-lighter: #359962;
+  --ifm-color-primary-lightest: #3cad6e;
+  --ifm-code-font-size: 95%;
+  --docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.1);
+}
+
+/* For readability concerns, you should choose a lighter palette in dark mode. */
+[data-theme="dark"] {
+  --ifm-color-primary: #25c2a0;
+  --ifm-color-primary-dark: #21af90;
+  --ifm-color-primary-darker: #1fa588;
+  --ifm-color-primary-darkest: #1a8870;
+  --ifm-color-primary-light: #29d5b0;
+  --ifm-color-primary-lighter: #32d8b4;
+  --ifm-color-primary-lightest: #4fddbf;
+  --docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.3);
+}

apps/docs/src/pages/index.module.css

@@ -0,0 +1,23 @@
+/**
+ * CSS files with the .module.css suffix will be treated as CSS modules
+ * and scoped locally.
+ */
+
+.heroBanner {
+  padding: 4rem 0;
+  text-align: center;
+  position: relative;
+  overflow: hidden;
+}
+
+@media screen and (max-width: 996px) {
+  .heroBanner {
+    padding: 2rem;
+  }
+}
+
+.buttons {
+  display: flex;
+  align-items: center;
+  justify-content: center;
+}

apps/docs/src/pages/markdown-page.md

@@ -0,0 +1,7 @@
+---
+title: Markdown page example
+---
+
+# Markdown page example
+
+You don't need React to write simple standalone pages.

apps/docs/static/img/logo.svg

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+<svg width="200" height="200" viewBox="0 0 200 200" xmlns="http://www.w3.org/2000/svg">
+  <g fill="none" fill-rule="evenodd">
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+      fill="#3ECC5F" />
+    <path
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+</svg>

apps/docs/static/img/undraw_docusaurus_mountain.svg

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+  <title>Easy to Use</title>
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apps/docs/tsconfig.json

@@ -0,0 +1,7 @@
+{
+  // This file is not used in compilation. It is here just for a nice editor experience.
+  "extends": "@tsconfig/docusaurus/tsconfig.json",
+  "compilerOptions": {
+    "baseUrl": "."
+  }
+}

apps/next/.gitignore

@@ -1,33 +0,0 @@
-# deps
-/node_modules
-
-# generated content
-.contentlayer
-.content-collections
-.source
-
-# test & build
-/coverage
-/.next/
-/out/
-/build
-*.tsbuildinfo
-
-# misc
-.DS_Store
-*.pem
-/.pnp
-.pnp.js
-npm-debug.log*
-yarn-debug.log*
-yarn-error.log*
-
-# others
-.env*.local
-.vercel
-next-env.d.ts
-
-# build
-/src/content/docs/cloud/api
-/src/content/docs/api
-./types

apps/next/CHANGELOG.md

@@ -1,578 +0,0 @@
-# @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
-
-- Updated dependencies [d952e68]
-  - @llamaindex/core@0.5.2
-  - @llamaindex/cloud@3.0.3
-  - llamaindex@0.9.3
-  - @llamaindex/node-parser@1.0.2
-  - @llamaindex/openai@0.1.54
-  - @llamaindex/readers@2.0.2
-
-## 0.1.2
-
-### Patch Changes
-
-- Updated dependencies [c902fcb]
-- Updated dependencies [88d776f]
-  - @llamaindex/cloud@3.0.2
-  - llamaindex@0.9.2
-
-## 0.1.1
-
-### Patch Changes
-
-- Updated dependencies [6d37d44]
-  - llamaindex@0.9.1
-  - @llamaindex/cloud@3.0.1
-  - @llamaindex/core@0.5.1
-  - @llamaindex/node-parser@1.0.1
-  - @llamaindex/openai@0.1.53
-  - @llamaindex/readers@2.0.1
-  - @llamaindex/workflow@0.0.11
-
-## 0.1.0
-
-### Minor Changes
-
-- 6a4a737: Remove re-exports from llamaindex main package
-- f4588bc: Remove readers package from llamaindex
-
-### Patch Changes
-
-- c7c0800: fix: fumadoc build fail
-- a87efb9: docs: update chat engine docs
-- 7bd5d93: docs: update workflow doc
-- Updated dependencies [6a4a737]
-- Updated dependencies [d924c63]
-- Updated dependencies [b490376]
-- Updated dependencies [f4588bc]
-  - llamaindex@0.9.0
-  - @llamaindex/core@0.5.0
-  - @llamaindex/cloud@3.0.0
-  - @llamaindex/node-parser@1.0.0
-  - @llamaindex/openai@0.1.52
-  - @llamaindex/readers@2.0.0
-
-## 0.0.41
-
-### Patch Changes
-
-- Updated dependencies [1c908fd]
-  - @llamaindex/openai@0.1.51
-  - @llamaindex/node-parser@0.0.24
-  - @llamaindex/workflow@0.0.10
-  - @llamaindex/readers@1.0.25
-  - @llamaindex/cloud@2.0.24
-  - @llamaindex/core@0.4.23
-  - llamaindex@0.8.37
-
-## 0.0.40
-
-### Patch Changes
-
-- Updated dependencies [cb608b5]
-  - @llamaindex/openai@0.1.50
-  - @llamaindex/node-parser@0.0.23
-  - @llamaindex/workflow@0.0.9
-  - @llamaindex/readers@1.0.24
-  - @llamaindex/cloud@2.0.23
-  - @llamaindex/core@0.4.22
-  - llamaindex@0.8.36
-
-## 0.0.39
-
-### Patch Changes
-
-- 6d4d96f: chore: update examples and docs to use unified imports
-- Updated dependencies [15563a0]
-  - @llamaindex/openai@0.1.49
-  - llamaindex@0.8.35
-
-## 0.0.38
-
-### Patch Changes
-
-- Updated dependencies [9f8ad37]
-- Updated dependencies [7265f74]
-  - llamaindex@0.8.34
-  - @llamaindex/openai@0.1.48
-
-## 0.0.37
-
-### Patch Changes
-
-- Updated dependencies [2019a04]
-  - @llamaindex/openai@0.1.47
-  - llamaindex@0.8.33
-
-## 0.0.36
-
-### Patch Changes
-
-- f02621e: Fix internal links between chapters
-- Updated dependencies [34faf48]
-- Updated dependencies [4df1fe6]
-- Updated dependencies [9456616]
-- Updated dependencies [d6c270e]
-- Updated dependencies [1892e1c]
-- Updated dependencies [1931bbc]
-  - llamaindex@0.8.32
-  - @llamaindex/core@0.4.21
-  - @llamaindex/cloud@2.0.22
-  - @llamaindex/openai@0.1.46
-  - @llamaindex/node-parser@0.0.22
-  - @llamaindex/readers@1.0.23
-
-## 0.0.35
-
-### Patch Changes
-
-- Updated dependencies [5dec9f9]
-- Updated dependencies [fd9c829]
-- Updated dependencies [d211b7a]
-- Updated dependencies [0ebbfc1]
-  - @llamaindex/cloud@2.0.21
-  - llamaindex@0.8.31
-  - @llamaindex/core@0.4.20
-  - @llamaindex/node-parser@0.0.21
-  - @llamaindex/openai@0.1.45
-  - @llamaindex/readers@1.0.22
-
-## 0.0.34
-
-### Patch Changes
-
-- Updated dependencies [012495b]
-  - @llamaindex/cloud@2.0.20
-  - llamaindex@0.8.30
-
-## 0.0.33
-
-### Patch Changes
-
-- Updated dependencies [dd596a0]
-  - llamaindex@0.8.29
-
-## 0.0.32
-
-### Patch Changes
-
-- a9b5b99: feat: build api reference pages for new documentation site
-- Updated dependencies [a9b5b99]
-  - @llamaindex/core@0.4.19
-  - @llamaindex/readers@1.0.21
-  - @llamaindex/cloud@2.0.19
-  - llamaindex@0.8.28
-  - @llamaindex/node-parser@0.0.20
-  - @llamaindex/openai@0.1.44
-
-## 0.0.31
-
-### Patch Changes
-
-- Updated dependencies [b504303]
-- Updated dependencies [e0f6cc3]
-- Updated dependencies [a0e6f57]
-  - llamaindex@0.8.27
-  - @llamaindex/core@0.4.18
-  - @llamaindex/cloud@2.0.18
-  - @llamaindex/node-parser@0.0.19
-  - @llamaindex/openai@0.1.43
-  - @llamaindex/readers@1.0.20
-  - @llamaindex/workflow@0.0.8
-
-## 0.0.30
-
-### Patch Changes
-
-- Updated dependencies [3d1808b]
-  - @llamaindex/core@0.4.17
-  - llamaindex@0.8.26
-  - @llamaindex/openai@0.1.42
-  - @llamaindex/cloud@2.0.17
-  - @llamaindex/node-parser@0.0.18
-  - @llamaindex/readers@1.0.19
-
-## 0.0.29
-
-### Patch Changes
-
-- Updated dependencies [7e8230b]
-- Updated dependencies [8be4589]
-  - @llamaindex/readers@1.0.18
-  - @llamaindex/cloud@2.0.16
-  - @llamaindex/core@0.4.16
-  - @llamaindex/node-parser@0.0.17
-  - @llamaindex/openai@0.1.41
-  - @llamaindex/workflow@0.0.7
-  - llamaindex@0.8.25
-
-## 0.0.28
-
-### Patch Changes
-
-- fd38a25: Add vercel tool adapter to use query engine tool
-
-## 0.0.27
-
-### Patch Changes
-
-- Updated dependencies [515f2c1]
-  - llamaindex@0.8.24
-
-## 0.0.26
-
-### Patch Changes
-
-- @llamaindex/cloud@2.0.15
-- @llamaindex/core@0.4.15
-- llamaindex@0.8.23
-- @llamaindex/node-parser@0.0.16
-- @llamaindex/openai@0.1.40
-- @llamaindex/readers@1.0.17
-
-## 0.0.25
-
-### Patch Changes
-
-- Updated dependencies [819af45]
-  - llamaindex@0.8.22
-  - @llamaindex/cloud@2.0.14
-  - @llamaindex/core@0.4.14
-  - @llamaindex/node-parser@0.0.15
-  - @llamaindex/openai@0.1.39
-  - @llamaindex/readers@1.0.16
-
-## 0.0.24
-
-### Patch Changes
-
-- Updated dependencies [83c3897]
-- Updated dependencies [efa2211]
-  - llamaindex@0.8.21
-
-## 0.0.23
-
-### Patch Changes
-
-- Updated dependencies [02b22da]
-  - llamaindex@0.8.20
-
-## 0.0.22
-
-### Patch Changes
-
-- Updated dependencies [90d265c]
-  - @llamaindex/cloud@2.0.13
-  - @llamaindex/core@0.4.13
-  - llamaindex@0.8.19
-  - @llamaindex/node-parser@0.0.14
-  - @llamaindex/readers@1.0.15
-  - @llamaindex/openai@0.1.38
-
-## 0.0.21
-
-### Patch Changes
-
-- Updated dependencies [d17450f]
-- Updated dependencies [ef4f63d]
-  - llamaindex@0.8.18
-  - @llamaindex/core@0.4.12
-  - @llamaindex/cloud@2.0.12
-  - @llamaindex/node-parser@0.0.13
-  - @llamaindex/openai@0.1.37
-  - @llamaindex/readers@1.0.14
-
-## 0.0.20
-
-### Patch Changes
-
-- Updated dependencies [6d22fa2]
-  - @llamaindex/core@0.4.11
-  - @llamaindex/cloud@2.0.11
-  - llamaindex@0.8.17
-  - @llamaindex/node-parser@0.0.12
-  - @llamaindex/openai@0.1.36
-  - @llamaindex/readers@1.0.13
-
-## 0.0.19
-
-### Patch Changes
-
-- Updated dependencies [e60328b]
-  - @llamaindex/readers@1.0.12
-  - llamaindex@0.8.16
-
-## 0.0.18
-
-### Patch Changes
-
-- Updated dependencies [3d503cb]
-- Updated dependencies [5dae534]
-  - llamaindex@0.8.15
-
-## 0.0.17
-
-### Patch Changes
-
-- Updated dependencies [630b425]
-  - llamaindex@0.8.14
-
-## 0.0.16
-
-### Patch Changes
-
-- Updated dependencies [a7b0ac3]
-- Updated dependencies [ee20c44]
-- Updated dependencies [c69605f]
-  - @llamaindex/core@0.4.10
-  - @llamaindex/workflow@0.0.6
-  - llamaindex@0.8.13
-  - @llamaindex/cloud@2.0.10
-  - @llamaindex/node-parser@0.0.11
-  - @llamaindex/openai@0.1.35
-  - @llamaindex/readers@1.0.11
-
-## 0.0.15
-
-### Patch Changes
-
-- Updated dependencies [ea92b69]
-- Updated dependencies [fadc8b8]
-  - @llamaindex/workflow@0.0.5
-
-## 0.0.14
-
-### Patch Changes
-
-- Updated dependencies [7ae6eaa]
-  - @llamaindex/core@0.4.9
-  - @llamaindex/openai@0.1.34
-  - @llamaindex/cloud@2.0.9
-  - llamaindex@0.8.12
-  - @llamaindex/node-parser@0.0.10
-  - @llamaindex/readers@1.0.10
-
-## 0.0.13
-
-### Patch Changes
-
-- Updated dependencies [f865c98]
-  - @llamaindex/core@0.4.8
-  - @llamaindex/cloud@2.0.8
-  - llamaindex@0.8.11
-  - @llamaindex/node-parser@0.0.9
-  - @llamaindex/openai@0.1.33
-  - @llamaindex/readers@1.0.9
-
-## 0.0.12
-
-### Patch Changes
-
-- Updated dependencies [f066e50]
-- Updated dependencies [d89ebe0]
-- Updated dependencies [fd8c882]
-- Updated dependencies [fd8c882]
-  - llamaindex@0.8.10
-  - @llamaindex/core@0.4.7
-  - @llamaindex/workflow@0.0.4
-  - @llamaindex/cloud@2.0.7
-  - @llamaindex/node-parser@0.0.8
-  - @llamaindex/openai@0.1.32
-  - @llamaindex/readers@1.0.8
-
-## 0.0.11
-
-### Patch Changes
-
-- Updated dependencies [4fc001c]
-- Updated dependencies [4d4cd8a]
-  - llamaindex@0.8.9
-  - @llamaindex/cloud@2.0.6
-  - @llamaindex/core@0.4.6
-  - @llamaindex/node-parser@0.0.7
-  - @llamaindex/openai@0.1.31
-  - @llamaindex/readers@1.0.7
-
-## 0.0.10
-
-### Patch Changes
-
-- Updated dependencies [ad85bd0]
-  - @llamaindex/core@0.4.5
-  - llamaindex@0.8.8
-  - @llamaindex/node-parser@0.0.6
-  - @llamaindex/workflow@0.0.3
-  - @llamaindex/cloud@2.0.5
-  - @llamaindex/openai@0.1.30
-  - @llamaindex/readers@1.0.6
-
-## 0.0.9
-
-### Patch Changes
-
-- @llamaindex/cloud@2.0.4
-- @llamaindex/core@0.4.4
-- llamaindex@0.8.7
-- @llamaindex/node-parser@0.0.5
-- @llamaindex/openai@0.1.29
-- @llamaindex/readers@1.0.5
-
-## 0.0.8
-
-### Patch Changes
-
-- Updated dependencies [95a5cc6]
-  - @llamaindex/core@0.4.3
-  - llamaindex@0.8.6
-  - @llamaindex/cloud@2.0.3
-  - @llamaindex/node-parser@0.0.4
-  - @llamaindex/openai@0.1.28
-  - @llamaindex/readers@1.0.4
-
-## 0.0.7
-
-### Patch Changes
-
-- Updated dependencies [14cc9eb]
-- Updated dependencies [a6db5dd]
-- Updated dependencies [396b1e1]
-  - llamaindex@0.8.5
-  - @llamaindex/cloud@2.0.2
-  - @llamaindex/core@0.4.2
-  - @llamaindex/node-parser@0.0.3
-  - @llamaindex/openai@0.1.27
-  - @llamaindex/readers@1.0.3
-
-## 0.0.6
-
-### Patch Changes
-
-- Updated dependencies [35430d3]
-  - llamaindex@0.8.4
-  - @llamaindex/readers@1.0.2
-
-## 0.0.5
-
-### Patch Changes
-
-- Updated dependencies [2ff0a89]
-  - @llamaindex/node-parser@0.0.2
-  - llamaindex@0.8.3
-
-## 0.0.4
-
-### Patch Changes
-
-- Updated dependencies [0765742]
-  - @llamaindex/workflow@0.0.2
-
-## 0.0.3
-
-### Patch Changes
-
-- Updated dependencies [c7a918c]
-  - llamaindex@0.8.2
-
-## 0.0.2
-
-### Patch Changes
-
-- Updated dependencies [9c73f0a]
-  - @llamaindex/core@0.4.1
-  - @llamaindex/cloud@2.0.1
-  - llamaindex@0.8.1
-  - @llamaindex/openai@0.1.26
-  - @llamaindex/readers@1.0.1
-
-## 0.0.1
-
-### Patch Changes
-
-- Updated dependencies [359fd33]
-- Updated dependencies [efb7e1b]
-- Updated dependencies [98ba1e7]
-- Updated dependencies [620c63c]
-  - @llamaindex/core@0.4.0
-  - llamaindex@0.8.0
-  - @llamaindex/cloud@2.0.0
-  - @llamaindex/openai@0.1.25
-  - @llamaindex/readers@1.0.0

apps/next/README.md

@@ -1,21 +0,0 @@
-# Docs
-
-This is a Next.js application generated with
-[Create Fumadocs](https://github.com/fuma-nama/fumadocs).
-
-Run development server:
-
-```bash
-turbo run dev
-# turbo will build all required packages before running the dev server
-```
-
-## Learn More
-
-To learn more about Next.js and Fumadocs, take a look at the following
-resources:
-
-- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js
-  features and API.
-- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial.
-- [Fumadocs](https://fumadocs.vercel.app) - learn about Fumadocs

apps/next/components.json

@@ -1,20 +0,0 @@
-{
-  "$schema": "https://ui.shadcn.com/schema.json",
-  "style": "new-york",
-  "rsc": true,
-  "tsx": true,
-  "tailwind": {
-    "config": "tailwind.config.js",
-    "css": "app/global.css",
-    "baseColor": "neutral",
-    "cssVariables": true,
-    "prefix": ""
-  },
-  "aliases": {
-    "components": "@/components",
-    "utils": "@/lib/utils",
-    "ui": "@/components/ui",
-    "lib": "@/lib",
-    "hooks": "@/hooks"
-  }
-}

apps/next/next.config.mjs

@@ -1,35 +0,0 @@
-import { createMDX } from "fumadocs-mdx/next";
-import MonacoWebpackPlugin from "monaco-editor-webpack-plugin";
-const withMDX = createMDX();
-
-/** @type {import('next').NextConfig} */
-const config = {
-  reactStrictMode: true,
-  transpilePackages: ["monaco-editor"],
-  serverExternalPackages: ["@huggingface/transformers"],
-  webpack: (config, { isServer }) => {
-    if (Array.isArray(config.target) && config.target.includes("web")) {
-      config.target = ["web", "es2020"];
-    }
-
-    config.resolve.alias = {
-      ...config.resolve.alias,
-      sharp$: false,
-      "onnxruntime-node$": false,
-    };
-    config.resolve.fallback ??= {};
-    config.resolve.fallback.fs = false;
-    if (!isServer) {
-      config.plugins.push(
-        new MonacoWebpackPlugin({
-          languages: ["typescript"],
-          filename: "static/[name].worker.js",
-        }),
-      );
-    }
-    config.resolve.alias["replicate"] = false;
-    return config;
-  },
-};
-
-export default withMDX(config);

apps/next/package.json

@@ -1,93 +0,0 @@
-{
-  "name": "@llamaindex/doc",
-  "version": "0.1.9",
-  "private": true,
-  "scripts": {
-    "build": "pnpm run build:docs && next build",
-    "dev": "next dev",
-    "start": "next start",
-    "postdev": "fumadocs-mdx",
-    "postbuild": "fumadocs-mdx && tsx scripts/post-build.mts",
-    "build:docs": "cross-env NODE_OPTIONS=\"--max-old-space-size=8192\" typedoc && node ./scripts/generate-docs.mjs"
-  },
-  "dependencies": {
-    "@icons-pack/react-simple-icons": "^10.1.0",
-    "@llamaindex/chat-ui": "0.0.9",
-    "@llamaindex/cloud": "workspace:*",
-    "@llamaindex/core": "workspace:*",
-    "@llamaindex/node-parser": "workspace:*",
-    "@llamaindex/openai": "workspace:*",
-    "@llamaindex/readers": "workspace:*",
-    "@llamaindex/workflow": "workspace:*",
-    "@mdx-js/mdx": "^3.1.0",
-    "@number-flow/react": "^0.3.4",
-    "@radix-ui/react-dialog": "^1.1.2",
-    "@radix-ui/react-icons": "^1.3.2",
-    "@radix-ui/react-label": "^2.1.0",
-    "@radix-ui/react-slider": "^1.2.1",
-    "@radix-ui/react-slot": "^1.1.0",
-    "@radix-ui/react-tooltip": "^1.1.4",
-    "@vercel/functions": "^1.5.0",
-    "@scalar/api-client-react": "^1.1.25",
-    "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",
-    "hast-util-to-jsx-runtime": "^2.3.2",
-    "llamaindex": "workspace:*",
-    "lucide-react": "^0.460.0",
-    "next": "15.1.7",
-    "next-themes": "^0.4.3",
-    "react": "^19.0.0",
-    "react-dom": "^19.0.0",
-    "react-icons": "^5.3.0",
-    "react-monaco-editor": "^0.56.2",
-    "react-text-transition": "^3.1.0",
-    "react-use-measure": "^2.1.1",
-    "rehype-katex": "^7.0.1",
-    "remark-math": "^6.0.0",
-    "rimraf": "^6.0.1",
-    "shiki": "^2.3.2",
-    "shiki-magic-move": "^1.0.0",
-    "swr": "^2.2.5",
-    "tailwind-merge": "^2.5.2",
-    "tailwindcss-animate": "^1.0.7",
-    "tree-sitter": "^0.22.1",
-    "tree-sitter-typescript": "^0.23.2",
-    "use-stick-to-bottom": "^1.0.42",
-    "web-tree-sitter": "^0.24.4",
-    "zod": "^3.23.8"
-  },
-  "devDependencies": {
-    "@next/env": "^15.0.3",
-    "@types/mdx": "^2.0.13",
-    "@types/node": "22.9.0",
-    "@types/react": "^18.3.12",
-    "@types/react-dom": "^18.3.1",
-    "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",
-    "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",
-    "typedoc": "0.27.4",
-    "typedoc-plugin-markdown": "^4.3.1",
-    "typedoc-plugin-merge-modules": "^6.1.0",
-    "typescript": "^5.7.2"
-  }
-}

apps/next/public/icons/Amazon_Web_Services_Logo.svg

@@ -1,38 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<!-- Generator: Adobe Illustrator 19.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
-<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
-	 viewBox="0 0 304 182" style="enable-background:new 0 0 304 182;" xml:space="preserve">
-<style type="text/css">
-	.st0{fill:#252F3E;}
-	.st1{fill-rule:evenodd;clip-rule:evenodd;fill:#FF9900;}
-</style>
-<g>
-	<path class="st0" d="M86.4,66.4c0,3.7,0.4,6.7,1.1,8.9c0.8,2.2,1.8,4.6,3.2,7.2c0.5,0.8,0.7,1.6,0.7,2.3c0,1-0.6,2-1.9,3l-6.3,4.2
-		c-0.9,0.6-1.8,0.9-2.6,0.9c-1,0-2-0.5-3-1.4C76.2,90,75,88.4,74,86.8c-1-1.7-2-3.6-3.1-5.9c-7.8,9.2-17.6,13.8-29.4,13.8
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apps/next/public/icons/Microsoft_Azure.svg

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apps/next/public/icons/chroma.svg

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apps/next/public/icons/qdrant-logo.svg

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apps/next/scripts/generate-docs.mjs

@@ -1,86 +0,0 @@
-import * as OpenAPI from "fumadocs-openapi";
-import { generateFiles } from "fumadocs-typescript";
-import fs from "node:fs";
-import * as path from "node:path";
-import { fileURLToPath } from "node:url";
-import { rimrafSync } from "rimraf";
-
-const out = "./src/content/docs/cloud/api";
-const apiRefOut = "./src/content/docs/api";
-
-// clean generated files
-rimrafSync(out, {
-  filter(v) {
-    return !v.endsWith("index.mdx") && !v.endsWith("meta.json");
-  },
-});
-
-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) {
-  const fileName = path.basename(filePath);
-  let title = fileName.split(".")[0];
-  let pageContent = content;
-  if (title === "index") title = "LlamaIndex API Reference";
-  return `---\ntitle: ${title}\n---\n\n${transformAbsoluteUrl(pageContent, filePath)}`;
-}
-
-/**
- * Transforms the content by converting relative MDX links to absolute docs API links
- * Example: [text](../type-aliases/TaskHandler.mdx) -> [text](/docs/api/type-aliases/TaskHandler)
- * [text](BaseChatEngine.mdx) -> [text](/docs/api/classes/BaseChatEngine)
- * [text](BaseVectorStore.mdx#constructors) -> [text](/docs/api/classes/BaseVectorStore#constructors)
- * [text](TaskStep.mdx) -> [text](/docs/api/type-aliases/TaskStep)
- */
-function transformAbsoluteUrl(content, filePath) {
-  const group = path.dirname(filePath).split(path.sep).pop();
-  return content.replace(
-    /\]\(([^)]+)\.mdx([^)]*)\)/g,
-    (match, slug, anchor) => {
-      const slugParts = slug.split("/");
-      const fileName = slugParts[slugParts.length - 1];
-      const fileGroup = slugParts[slugParts.length - 2] ?? group;
-      const result = ["/docs/api", fileGroup, fileName, anchor]
-        .filter(Boolean)
-        .join("/");
-      return `](${result})`;
-    },
-  );
-}
-
-// append meta.json for API page
-fs.writeFileSync(
-  path.resolve(apiRefOut, "meta.json"),
-  JSON.stringify(
-    {
-      title: "API Reference",
-      description: "LlamaIndex API Reference",
-      root: true,
-      pages: [
-        "index",
-        "classes",
-        "enumerations",
-        "functions",
-        "interfaces",
-        "type-aliases",
-        "variables",
-      ],
-    },
-    null,
-    2,
-  ),
-);

apps/next/scripts/post-build.mts

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