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2 Commits

Author SHA1 Message Date
thucpn d751af3ba1 fix: use tsx 2024-12-20 17:15:41 +07:00
thucpn 6e0bf26566 fix: add start command for stackblitz 2024-12-20 17:11:32 +07:00
1234 changed files with 28281 additions and 92340 deletions
@@ -8,11 +8,6 @@ on:
branches:
- main
env:
TURBO_TOKEN: ${{ secrets.TURBO_TOKEN }}
TURBO_TEAM: ${{ vars.TURBO_TEAM }}
TURBO_REMOTE_ONLY: true
jobs:
lint:
runs-on: ubuntu-latest
+1 -6
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@@ -1,11 +1,6 @@
name: Publish Preview
on: [pull_request]
env:
TURBO_TOKEN: ${{ secrets.TURBO_TOKEN }}
TURBO_TEAM: ${{ vars.TURBO_TEAM }}
TURBO_REMOTE_ONLY: true
jobs:
pre_release:
name: Pre Release
@@ -30,4 +25,4 @@ jobs:
run: pnpm run build
- name: Pre Release
run: pnpx pkg-pr-new publish --pnpm ./packages/* ./packages/providers/* ./packages/providers/storage/*
run: pnpx pkg-pr-new publish ./packages/* ./packages/providers/*
+8 -52
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@@ -23,7 +23,7 @@ jobs:
strategy:
fail-fast: false
matrix:
node-version: [20.x, 22.x, 23.x]
node-version: [18.x, 20.x, 22.x, 23.x]
name: E2E on Node.js ${{ matrix.node-version }}
runs-on: ubuntu-latest
steps:
@@ -53,7 +53,7 @@ jobs:
strategy:
fail-fast: false
matrix:
node-version: [20.x, 22.x, 23.x]
node-version: [18.x, 20.x, 22.x, 23.x]
name: Test on Node.js ${{ matrix.node-version }}
runs-on: ubuntu-latest
steps:
@@ -83,34 +83,15 @@ jobs:
run: pnpm install
- name: Build
run: pnpm run build
- name: Use Build For Examples
run: |
pnpm link ../packages/llamaindex/
cd readers && pnpm link ../../packages/llamaindex/
working-directory: ./examples
- name: Run Type Check
run: pnpm run type-check
- name: Run Circular Dependency Check
run: pnpm run circular-check
e2e-npm:
runs-on: ubuntu-latest
name: Test using packages with npm
steps:
- uses: actions/checkout@v4
- uses: pnpm/action-setup@v4
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version-file: ".nvmrc"
- name: Install dependencies
run: pnpm install
- name: Build packages
run: pnpm run build
- name: Pack packages
run: |
pnpm pack --pack-destination ${{ runner.temp }} -C packages/llamaindex
pnpm pack --pack-destination ${{ runner.temp }} -C packages/workflow
- name: Install packed packages
run: npm add ${{ runner.temp }}/*.tgz
working-directory: e2e/npm
- name: Run tests
run: npm test
working-directory: e2e/npm
e2e-llamaindex-examples:
strategy:
fail-fast: false
@@ -122,7 +103,6 @@ jobs:
- nextjs-node-runtime
- waku-query-engine
- llama-parse-browser
- vite-import-llamaindex
runs-on: ubuntu-latest
name: Build LlamaIndex Example (${{ matrix.packages }})
steps:
@@ -141,30 +121,6 @@ jobs:
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: ${{ secrets.GITHUB_TOKEN }}
directory: e2e/examples/vite-import-llamaindex
skip_step: "install"
build_script: build
package_manager: pnpm
typecheck-examples:
runs-on: ubuntu-latest
@@ -194,7 +150,7 @@ jobs:
done
- name: Pack provider packages
run: |
for dir in packages/providers/* packages/providers/storage/*; do
for dir in packages/providers/*; do
if [ -d "$dir" ] && [ -f "$dir/package.json" ]; then
echo "Packing $dir"
pnpm pack --pack-destination ${{ runner.temp }} -C $dir
+3 -1
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@@ -1 +1,3 @@
pnpm run lint-staged
pnpm format
pnpm lint
npx lint-staged
+1 -1
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@@ -1 +1 @@
22
20
-1
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@@ -7,4 +7,3 @@ dist/
.source/
# prttier doesn't support mdx3 we are using
*.mdx
packages/server/server/
-1
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@@ -1 +0,0 @@
LlamaIndexTS
+1 -2
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@@ -14,6 +14,5 @@
"[json]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"prettier.prettierPath": "./node_modules/prettier",
"prettier.configPath": "prettier.config.mjs"
"prettier.prettierPath": "./node_modules/prettier"
}
-92
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@@ -1,92 +0,0 @@
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Development Commands
This project uses pnpm as the package manager and Turbo for build orchestration:
- `pnpm install` - Install all dependencies
- `pnpm build` - Build all packages using Turbo
- `pnpm dev` - Start development mode for all packages
- `pnpm test` - Run all unit tests
- `pnpm e2e` - Run end-to-end tests
- `pnpm lint` - Run ESLint across all packages
- `pnpm type-check` - Run TypeScript type checking across workspace
- `pnpm format` - Check code formatting with Prettier
- `pnpm format:write` - Auto-fix formatting issues
- `pnpm circular-check` - Check for circular dependencies using madge
For individual package development:
- `turbo run build --filter="@llamaindex/core"` - Build specific package
- `turbo run test --filter="@llamaindex/core"` - Test specific package
- Navigate to specific package directory and run `pnpm test` for focused testing
- `pnpm clean` - Remove all build artifacts and node_modules across workspace
## Architecture Overview
LlamaIndex.TS is a TypeScript data framework for LLM applications organized as a pnpm monorepo with multiple runtime environment support (Node.js, Deno, Bun, Vercel Edge, Cloudflare Workers).
### Package Structure
**Core Packages:**
- `packages/core/` - Abstract base classes and interfaces for all runtime environments
- `packages/llamaindex/` - Main package that aggregates core functionality
- `packages/env/` - Environment-specific compatibility layers for different JS runtimes
**Provider Packages (`packages/providers/`):**
- LLM providers: `openai/`, `anthropic/`, `ollama/`, `google/`, `groq/`, etc.
- Vector stores: `storage/pinecone/`, `storage/chroma/`, `storage/qdrant/`, etc.
- Embeddings: Various embedding providers integrated within LLM packages
- Readers: `assemblyai/`, `discord/`, `notion/` for data ingestion
**Specialized Packages:**
- `packages/cloud/` - LlamaCloud integration for managed services
- `packages/tools/` - Function calling tools and utilities
- `packages/workflow/` - Agent workflow orchestration
- `packages/readers/` - File format readers (PDF, DOCX, etc.)
### Key Architectural Patterns
**Runtime Abstraction:** Core functionality is runtime-agnostic, with environment-specific implementations in separate entry points (`index.ts`, `index.edge.ts`, `index.workerd.ts`).
**Provider Pattern:** LLMs, embeddings, and vector stores implement common interfaces from `@llamaindex/core`, allowing easy swapping between providers.
**Modular Design:** Each provider is a separate package to minimize bundle size - users install only what they need.
**Data Flow:** Document → NodeParser → Embedding → VectorStore → Retriever → QueryEngine → Response
### Core Components
- **Agents and Workflows:** Abstractions for building agentic workflows and agents in `packages/workflow`
- **Chat Engines:** Conversational interfaces in `core/chat-engine/`
- **Query Engines:** Document querying with retrieval in `core/query-engine/`
- **Indices:** VectorStoreIndex, SummaryIndex, KeywordTable in `llamaindex/indices/`
- **Node Parsers:** Text splitting and chunking in `core/node-parser/`
- **Ingestion Pipeline:** Document processing workflows in `llamaindex/ingestion/`
- **Storage:** Chat stores, document stores, index stores, and KV stores in `core/storage/`
### Deprecated Components
- **Agents:** ReAct and function calling agents in `core/agent/` and `llamaindex/agent/`
### Testing Structure
- Unit tests in each package's `tests/` directory
- E2E tests in `e2e/` directory with runtime-specific examples
- Tests depend on build artifacts, so always run `pnpm build` before testing
### Multi-Runtime Support
The codebase supports multiple JavaScript runtimes through conditional exports and separate entry points. When making changes, consider compatibility across Node.js, Deno, Bun, and edge runtimes.
### Development Notes
- The project uses Husky for git hooks with lint-staged for pre-commit formatting and linting
- All packages use bunchee for building with dual CJS/ESM support
- Core package exports are organized as sub-modules (e.g., `@llamaindex/core/llms`, `@llamaindex/core/embeddings`)
- Always run `pnpm build` before running tests, as tests depend on build artifacts
+8 -101
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@@ -14,145 +14,52 @@ There are some important folders in the repository:
all JS runtime environments.
- `env`: The environment package of LlamaIndex.TS, which contains the environment-specific classes and interfaces. It
includes compatibility layers for Node.js, Deno, Vercel Edge Runtime, Cloudflare Workers...
- `providers/*`: The providers package of LlamaIndex.TS, which contains the providers for LLM and other services.
- `apps/*`: The applications based on LlamaIndex.TS.
- `next`: Our documentation website based on Next.js.
- `examples`: The code examples of LlamaIndex.TS using Node.js.
## Getting Started
Make sure you have Node.js LTS (Long-term Support) installed. You can check your Node.js version by running:
Make sure you have Node.js LIS (Long-term Support) installed. You can check your Node.js version by running:
```shell
node -v
# v22.x.x
# v20.x.x
```
### Use pnpm
```shell
npm install -g pnpm
corepack enable
```
### Install dependencies
```shell
pnpm install
pnpm install -g tsx
```
### Build the packages
To build all packages, run:
```shell
pnpm build
# Build all packages
turbo build --filter "./packages/*"
```
### Start Developing
You can launch the package in dev-mode by running:
```shell
pnpm dev
```
This will use turbo to run all packages in watch-mode. This means you can make changes and have them automatically built.
If you want to customize what packages are built/watched, you can run turbo directly and adjust the filter:
```shell
pnpm turbo run dev --filter="./packages/core" --concurrency=100
```
In another terminal, you can write and run any script needed to quickly test your changes. For example:
```typescript
import { createMemory, staticBlock } from "@llamaindex/core/memory";
// Create memory with predefined context
const memory = createMemory({
memoryBlocks: [
staticBlock({
content:
"The user is a software engineer who loves TypeScript and LlamaIndex.",
messageRole: "system",
}),
],
});
async function main() {
const result = await memory.getLLM();
console.log(result);
}
void main().catch(console.error);
```
And run it with:
```shell
pnpm exec tsx my_script.ts
```
This flow allows you to easily test your changes without having to build the entire project.
Once you are happy with your changes, be sure to add tests (and confirm existing tests are passing!).
### Run tests
#### Unit tests
After build, to run all unit tests, call:
```shell
pnpm test
```
Unit tests are located in the `tests` folder of each package. They are using their own package (e.g. `@llamaindex/core-tests` for `@llamaindex/core`). The tests are importing the package under test and the test package is not published.
#### E2E tests
To run all E2E tests, call:
```shell
pnpm e2e
```
All E2E tests are in the `e2e` folder.
### Docs
See the [docs](./apps/next/README.md) for more information.
## Adding a new package
Please follow these steps to add a new package:
1. Only add new packages to the `packages/providers` folder.
2. Use the `package.json` and `tsconfig.json` of an existing packages as template.
3. Reference your new package in the root `tsconfig.json` file
4. Add your package to the `examples/package.json` file if you add a new example.
## Before sending a PR
Before sending a PR, make sure of the following:
1. Tests are all running and you added meaningful tests for your change.
2. If you have a new feature, document it in the `apps/next` docs folder.
3. If you have a new feature, add a new example in the `examples` folder.
4. You have a descriptive changeset for each PR:
### Bumping the versions of packages you've modified
## Changeset
We use [changesets](https://github.com/changesets/changesets) for managing versions and changelogs. To create a new
changeset, run in the root folder:
```shell
```
pnpm changeset
```
You will be prompted to choose what packages need their versions bumped, and what kind of bump (major, minor or patch) is needed. Once you carry out this operation, the bumping will be automatic after the PR is merged.
Please send a descriptive changeset for each PR.
## Publishing (maintainers only)
+48 -11
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@@ -7,10 +7,9 @@
</h3>
[![NPM Version](https://img.shields.io/npm/v/llamaindex)](https://www.npmjs.com/package/llamaindex)
[![NPM License](https://img.shields.io/npm/l/llamaindex)](https://github.com/run-llama/LlamaIndexTS/blob/main/LICENSE)
[![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)
[![Twitter](https://img.shields.io/twitter/follow/llama_index)](https://x.com/llama_index)
Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in JS runtime environments with TypeScript support.
@@ -64,27 +63,65 @@ yarn add llamaindex
### Setup in Node.js, Deno, Bun, TypeScript...?
See our official document: https://ts.llamaindex.ai/docs/llamaindex/getting_started
See our official document: <https://ts.llamaindex.ai/docs/llamaindex/getting_started/>
### Adding provider packages
### Tips when using in non-Node.js environments
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.
When you are importing `llamaindex` in a non-Node.js environment(such as Vercel Edge, Cloudflare Workers, etc.)
Some classes are not exported from top-level entry file.
For example, to use the OpenAI LLM, you would install the following package:
The reason is that some classes are only compatible with Node.js runtime,(e.g. `PDFReader`) which uses Node.js specific APIs(like `fs`, `child_process`, `crypto`).
```shell
npm install @llamaindex/openai
pnpm install @llamaindex/openai
yarn add @llamaindex/openai
If you need any of those classes, you have to import them instead directly though their file path in the package.
Here's an example for importing the `PineconeVectorStore` class:
```typescript
import { PineconeVectorStore } from "llamaindex/storage/vectorStore/PineconeVectorStore";
```
As the `PDFReader` is not working with the Edge runtime, here's how to use the `SimpleDirectoryReader` with the `LlamaParseReader` to load PDFs:
```typescript
import { SimpleDirectoryReader } from "llamaindex/readers/SimpleDirectoryReader";
import { LlamaParseReader } from "llamaindex/readers/LlamaParseReader";
export const DATA_DIR = "./data";
export async function getDocuments() {
const reader = new SimpleDirectoryReader();
// Load PDFs using LlamaParseReader
return await reader.loadData({
directoryPath: DATA_DIR,
fileExtToReader: {
pdf: new LlamaParseReader({ resultType: "markdown" }),
},
});
}
```
> _Note_: Reader classes have to be added explictly to the `fileExtToReader` map in the Edge version of the `SimpleDirectoryReader`.
You'll find a complete example with LlamaIndexTS here: https://github.com/run-llama/create_llama_projects/tree/main/nextjs-edge-llamaparse
## Playground
Check out our NextJS playground at https://llama-playground.vercel.app/. The source is available at https://github.com/run-llama/ts-playground
## Core concepts for getting started:
See our documentation: https://ts.llamaindex.ai/docs/llamaindex/getting_started/concepts
- [Document](/packages/llamaindex/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.
- [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)).
- [Indices](/packages/llamaindex/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).
- [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).
- [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.
## Contributing:
-777
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@@ -1,782 +1,5 @@
# @llamaindex/doc
## 0.2.48
### Patch Changes
- Updated dependencies [049471b]
- Updated dependencies [049471b]
- @llamaindex/cloud@4.1.0
- llamaindex@0.11.25
## 0.2.47
### Patch Changes
- Updated dependencies [c3bf3c7]
- Updated dependencies [f9f1de9]
- @llamaindex/cloud@4.0.28
- @llamaindex/core@0.6.19
- llamaindex@0.11.24
- @llamaindex/node-parser@2.0.19
- @llamaindex/openai@0.4.14
- @llamaindex/readers@3.1.18
- @llamaindex/workflow@1.1.20
## 0.2.46
### Patch Changes
- Updated dependencies [f29799e]
- Updated dependencies [7224c06]
- @llamaindex/workflow@1.1.19
- @llamaindex/core@0.6.18
- llamaindex@0.11.23
- @llamaindex/cloud@4.0.27
- @llamaindex/node-parser@2.0.18
- @llamaindex/openai@0.4.13
- @llamaindex/readers@3.1.17
## 0.2.45
### Patch Changes
- Updated dependencies [9ed3195]
- @llamaindex/workflow@1.1.18
- llamaindex@0.11.22
## 0.2.44
### Patch Changes
- 38da40b: feat: VectoryMemoryBlock
- Updated dependencies [38da40b]
- @llamaindex/core@0.6.17
- @llamaindex/cloud@4.0.26
- llamaindex@0.11.21
- @llamaindex/node-parser@2.0.17
- @llamaindex/openai@0.4.12
- @llamaindex/readers@3.1.16
- @llamaindex/workflow@1.1.17
## 0.2.43
### Patch Changes
- ea15e75: Minor updates in deployment docs
## 0.2.42
### Patch Changes
- a8ec08c: fix: ensure correct message content in agent workflow
- Updated dependencies [a8ec08c]
- Updated dependencies [2967d57]
- @llamaindex/core@0.6.16
- @llamaindex/workflow@1.1.16
- @llamaindex/cloud@4.0.25
- llamaindex@0.11.20
- @llamaindex/node-parser@2.0.16
- @llamaindex/openai@0.4.11
- @llamaindex/readers@3.1.15
## 0.2.41
### Patch Changes
- Updated dependencies [856dd8c]
- @llamaindex/openai@0.4.10
## 0.2.40
### Patch Changes
- Updated dependencies [7ad3411]
- Updated dependencies [5da5b3c]
- Updated dependencies [a1fdb07]
- @llamaindex/core@0.6.15
- @llamaindex/workflow@1.1.15
- @llamaindex/openai@0.4.9
- @llamaindex/cloud@4.0.24
- llamaindex@0.11.19
- @llamaindex/node-parser@2.0.15
- @llamaindex/readers@3.1.14
## 0.2.39
### Patch Changes
- Updated dependencies [a1b1598]
- @llamaindex/cloud@4.0.23
- llamaindex@0.11.18
## 0.2.38
### Patch Changes
- Updated dependencies [d2be868]
- @llamaindex/cloud@4.0.22
- llamaindex@0.11.17
## 0.2.37
### Patch Changes
- Updated dependencies [579ca0c]
- @llamaindex/cloud@4.0.21
- llamaindex@0.11.16
## 0.2.36
### Patch Changes
- Updated dependencies [48b0d88]
- Updated dependencies [f185772]
- @llamaindex/cloud@4.0.20
- llamaindex@0.11.15
## 0.2.35
### Patch Changes
- Updated dependencies [5a0ed1f]
- Updated dependencies [5a0ed1f]
- Updated dependencies [8eeac33]
- @llamaindex/cloud@4.0.19
- @llamaindex/core@0.6.14
- llamaindex@0.11.14
- @llamaindex/node-parser@2.0.14
- @llamaindex/openai@0.4.8
- @llamaindex/readers@3.1.13
- @llamaindex/workflow@1.1.14
## 0.2.34
### Patch Changes
- 39758ab: Add title to homepage header
## 0.2.33
### Patch Changes
- Updated dependencies [47a7555]
- @llamaindex/cloud@4.0.18
- llamaindex@0.11.13
## 0.2.32
### Patch Changes
- Updated dependencies [d578889]
- Updated dependencies [0fcc92f]
- Updated dependencies [515a8b9]
- @llamaindex/core@0.6.13
- llamaindex@0.11.12
- @llamaindex/cloud@4.0.17
- @llamaindex/node-parser@2.0.13
- @llamaindex/openai@0.4.7
- @llamaindex/readers@3.1.12
- @llamaindex/workflow@1.1.13
## 0.2.31
### Patch Changes
- Updated dependencies [7039e1a]
- Updated dependencies [7039e1a]
- llamaindex@0.11.11
- @llamaindex/core@0.6.12
- @llamaindex/cloud@4.0.16
- @llamaindex/node-parser@2.0.12
- @llamaindex/openai@0.4.6
- @llamaindex/readers@3.1.11
- @llamaindex/workflow@1.1.12
## 0.2.30
### Patch Changes
- Updated dependencies [f7ec293]
- @llamaindex/workflow@1.1.11
- llamaindex@0.11.10
## 0.2.29
### Patch Changes
- Updated dependencies [c5846bd]
- @llamaindex/readers@3.1.10
## 0.2.28
### Patch Changes
- Updated dependencies [a89e187]
- Updated dependencies [62699b7]
- Updated dependencies [c5b2691]
- Updated dependencies [d8ac8d3]
- @llamaindex/core@0.6.11
- @llamaindex/openai@0.4.5
- @llamaindex/cloud@4.0.15
- llamaindex@0.11.9
- @llamaindex/node-parser@2.0.11
- @llamaindex/readers@3.1.9
- @llamaindex/workflow@1.1.10
## 0.2.27
### Patch Changes
- 8a51c16: Add natural language agent page
- Updated dependencies [8a51c16]
- Updated dependencies [1b5af14]
- @llamaindex/workflow@1.1.9
- @llamaindex/core@0.6.10
- llamaindex@0.11.8
- @llamaindex/cloud@4.0.14
- @llamaindex/node-parser@2.0.10
- @llamaindex/openai@0.4.4
- @llamaindex/readers@3.1.8
## 0.2.26
### Patch Changes
- a4d394f: fix: correct SimpleDirectoryReader import path in documentation example
- Updated dependencies [dbd857f]
- Updated dependencies [3c857f4]
- @llamaindex/workflow@1.1.8
- llamaindex@0.11.7
## 0.2.25
### Patch Changes
- Updated dependencies [40161fe]
- @llamaindex/workflow@1.1.7
- llamaindex@0.11.6
## 0.2.24
### Patch Changes
- Updated dependencies [766054b]
- Updated dependencies [71598f8]
- @llamaindex/workflow@1.1.6
- @llamaindex/core@0.6.9
- llamaindex@0.11.5
- @llamaindex/cloud@4.0.13
- @llamaindex/node-parser@2.0.9
- @llamaindex/openai@0.4.3
- @llamaindex/readers@3.1.7
## 0.2.23
### Patch Changes
- Updated dependencies [c927457]
- @llamaindex/openai@0.4.2
- @llamaindex/core@0.6.8
- @llamaindex/cloud@4.0.12
- llamaindex@0.11.4
- @llamaindex/node-parser@2.0.8
- @llamaindex/readers@3.1.6
- @llamaindex/workflow@1.1.5
## 0.2.22
### Patch Changes
- Updated dependencies [76ff23d]
- @llamaindex/cloud@4.0.11
- llamaindex@0.11.3
## 0.2.21
### Patch Changes
- Updated dependencies [59601dd]
- @llamaindex/openai@0.4.1
- @llamaindex/core@0.6.7
- @llamaindex/cloud@4.0.10
- llamaindex@0.11.2
- @llamaindex/node-parser@2.0.7
- @llamaindex/readers@3.1.5
- @llamaindex/workflow@1.1.4
## 0.2.20
### Patch Changes
- Updated dependencies [3703f90]
- @llamaindex/cloud@4.0.9
- llamaindex@0.11.1
## 0.2.19
### Patch Changes
- Updated dependencies [680b529]
- Updated dependencies [b0cd530]
- Updated dependencies [361a685]
- Updated dependencies [3e66ddc]
- @llamaindex/workflow@1.1.3
- @llamaindex/core@0.6.6
- llamaindex@0.11.0
- @llamaindex/openai@0.4.0
- @llamaindex/cloud@4.0.8
- @llamaindex/node-parser@2.0.6
- @llamaindex/readers@3.1.4
## 0.2.18
### Patch Changes
- d671ed6: Add functionality for search params when querying Qdrant vector store.
- Updated dependencies [76c9a80]
- Updated dependencies [168d11f]
- Updated dependencies [d671ed6]
- Updated dependencies [40f5f41]
- @llamaindex/openai@0.3.7
- @llamaindex/workflow@1.1.2
- @llamaindex/core@0.6.5
- @llamaindex/cloud@4.0.7
- llamaindex@0.10.6
- @llamaindex/node-parser@2.0.5
- @llamaindex/readers@3.1.3
## 0.2.17
### Patch Changes
- Updated dependencies [9b2e25a]
- @llamaindex/openai@0.3.6
- @llamaindex/core@0.6.4
- llamaindex@0.10.5
- @llamaindex/cloud@4.0.6
- @llamaindex/node-parser@2.0.4
- @llamaindex/readers@3.1.2
- @llamaindex/workflow@1.1.1
## 0.2.16
### Patch Changes
- Updated dependencies [7e8e454]
- Updated dependencies [2225ffd]
- Updated dependencies [6ddf1c1]
- Updated dependencies [bc53342]
- Updated dependencies [41953a3]
- @llamaindex/workflow@1.1.0
- @llamaindex/cloud@4.0.5
- llamaindex@0.10.4
## 0.2.15
### Patch Changes
- Updated dependencies [3ee8c83]
- @llamaindex/core@0.6.3
- llamaindex@0.10.3
- @llamaindex/openai@0.3.5
- @llamaindex/cloud@4.0.4
- @llamaindex/node-parser@2.0.3
- @llamaindex/readers@3.1.1
- @llamaindex/workflow@1.0.4
## 0.2.14
### Patch Changes
- Updated dependencies [1e59695]
- @llamaindex/readers@3.1.0
## 0.2.13
### Patch Changes
- Updated dependencies [e5c3f95]
- @llamaindex/openai@0.3.4
- llamaindex@0.10.2
## 0.2.12
### Patch Changes
- Updated dependencies [96dd798]
- @llamaindex/openai@0.3.3
- llamaindex@0.10.1
## 0.2.11
### Patch Changes
- 6cf928f: chore: use bunchee for llamaindex
- Updated dependencies [6cf928f]
- llamaindex@0.10.0
## 0.2.10
### Patch Changes
- 411dcea: Add Nova Premier to AWS Nova models. Add EU endpoints
## 0.2.9
### Patch Changes
- Updated dependencies [d365eb2]
- @llamaindex/openai@0.3.2
- llamaindex@0.9.19
## 0.2.8
### Patch Changes
- 2ffdb27: docs: correct the CondenseQuestionChatEngine path
- Updated dependencies [88b7046]
- @llamaindex/openai@0.3.1
- llamaindex@0.9.18
## 0.2.7
### Patch Changes
- 3ffee26: feat: enhance config params for LlamaIndexServer
## 0.2.6
### Patch Changes
- Updated dependencies [3534c37]
- Updated dependencies [41191d0]
- llamaindex@0.9.17
- @llamaindex/workflow@1.0.3
- @llamaindex/cloud@4.0.3
## 0.2.5
### Patch Changes
- 4999df1: bump nextjs
- Updated dependencies [f5e4d09]
- llamaindex@0.9.16
## 0.2.4
### Patch Changes
- 9c63f3f: Add support for openai responses api
- Updated dependencies [9c63f3f]
- Updated dependencies [c515a32]
- @llamaindex/openai@0.3.0
- @llamaindex/core@0.6.2
- @llamaindex/workflow@1.0.2
- llamaindex@0.9.15
- @llamaindex/cloud@4.0.2
- @llamaindex/node-parser@2.0.2
- @llamaindex/readers@3.0.2
## 0.2.3
### Patch Changes
- 648cfb5: Add support for supabase vector store
Added doc for the supbase vector store
- Updated dependencies [1b6f368]
- Updated dependencies [eaf326e]
- Updated dependencies [9d951b2]
- @llamaindex/core@0.6.1
- llamaindex@0.9.14
- @llamaindex/cloud@4.0.1
- @llamaindex/node-parser@2.0.1
- @llamaindex/openai@0.2.1
- @llamaindex/readers@3.0.1
- @llamaindex/workflow@1.0.1
## 0.2.2
### Patch Changes
- e98033e: docs: correct the number of indexes
## 0.2.1
### Patch Changes
- Updated dependencies [75d6e29]
- llamaindex@0.9.13
## 0.2.0
### Minor Changes
- f1db9b3: Adding an options parameter to vercel tool to tailor responses
### Patch Changes
- 21bebfc: Expose more content to fix the issue with unavailable documentation links, and adjust the documentation based on the latest code.
- 2b39cef: Added documentation for structured output in openai and ollama
- Updated dependencies [21bebfc]
- Updated dependencies [93bc0ff]
- Updated dependencies [91a18e7]
- Updated dependencies [bf56fc0]
- Updated dependencies [f8a86e4]
- Updated dependencies [5189b44]
- Updated dependencies [58a9446]
- @llamaindex/readers@3.0.0
- @llamaindex/core@0.6.0
- @llamaindex/openai@0.2.0
- @llamaindex/cloud@4.0.0
- @llamaindex/workflow@1.0.0
- llamaindex@0.9.12
- @llamaindex/node-parser@2.0.0
## 0.1.11
### Patch Changes
- a8c0637: feat: simplify to provide base URL to OpenAI
- a654f58: Added docs for using perplexity
- 98eebf7: Add RequestOptions parameter passing to support Gemini proxy calls.
Add a usage example for the RequestOptions parameter.
- Updated dependencies [a8c0637]
- @llamaindex/openai@0.1.61
- llamaindex@0.9.11
## 0.1.10
### Patch Changes
- Updated dependencies [aea550a]
- Updated dependencies [c1b5be5]
- Updated dependencies [40ee761]
- Updated dependencies [40ee761]
- @llamaindex/openai@0.1.60
- llamaindex@0.9.10
- @llamaindex/workflow@0.0.16
- @llamaindex/core@0.5.8
- @llamaindex/cloud@3.0.9
- @llamaindex/node-parser@1.0.8
- @llamaindex/readers@2.0.8
## 0.1.9
### Patch Changes
- 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
-143
View File
@@ -1,143 +0,0 @@
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with the LlamaIndex.TS documentation site.
## Application Overview
This is a Next.js documentation site (`@llamaindex/doc`) that serves as the official documentation for LlamaIndex.TS. It's built using Fumadocs, a modern documentation framework, and includes interactive features, API documentation generation, and AI-powered chat functionality.
## Development Commands
From this directory (`apps/next/`):
- `pnpm dev` - Start development server with Turbo
- `pnpm build` - Build the documentation site (includes `prebuild` step)
- `pnpm start` - Start production server
- `pnpm build:docs` - Generate API documentation from TypeScript source
- `pnpm validate-links` - Validate all internal and external links
Key build process:
1. `prebuild` runs `build:docs` to generate API documentation using TypeDoc
2. `build` runs Next.js build process
3. `postbuild` runs post-processing scripts and link validation
## Architecture
### Framework Stack
- **Next.js 15.3** - React framework with App Router
- **Fumadocs** - Documentation framework with MDX support
- **React Server Components** - AI chat functionality with server actions
- **Tailwind CSS** - Styling with custom design system
- **TypeScript** - Full type safety
### Key Dependencies
- **Fumadocs ecosystem**: `fumadocs-ui`, `fumadocs-mdx`, `fumadocs-core`, `fumadocs-openapi`
- **AI features**: `ai` package for React Server Components chat
- **Code features**: Monaco Editor, Shiki syntax highlighting, Twoslash TypeScript integration
- **UI components**: Radix UI primitives, Framer Motion animations
- **Content processing**: MDX, remark/rehype plugins, TypeDoc for API generation
### Directory Structure
**Content Management:**
- `src/content/docs/` - MDX documentation files organized by topic
- `src/content/docs/api/` - Auto-generated API documentation from TypeScript
- `scripts/` - Build-time documentation generation and validation
**Application Code:**
- `src/app/` - Next.js App Router pages and API routes
- `src/components/` - Reusable React components including UI library
- `src/lib/` - Utilities, constants, and configuration
**Configuration:**
- `source.config.ts` - Fumadocs MDX configuration with plugins
- `next.config.mjs` - Next.js configuration with MDX integration
- `tailwind.config.mjs` - Tailwind CSS customization
### Key Features
**Documentation Features:**
- MDX-based content with TypeScript code highlighting
- Auto-generated API documentation from TypeScript source
- Interactive code examples with Monaco Editor
- Math equation support with KaTeX
- Link validation and build-time checks
**Interactive Features:**
- AI-powered chat interface using React Server Components
- Code demos with live TypeScript execution
- Interactive UI components and animations
- Search functionality across all documentation
**Build Process:**
- TypeDoc generates API documentation from workspace packages
- Custom scripts transform and validate generated content
- Link checking ensures all internal/external links work
- Static site generation with 10-minute timeout for large documentation set
### Configuration Files
**source.config.ts**: Defines MDX processing pipeline with:
- Code highlighting themes (Catppuccin)
- Twoslash TypeScript integration
- Remark/rehype plugins for enhanced Markdown
- Content directories including external docs
**next.config.mjs**: Next.js configuration with:
- Extended static generation timeout (10 minutes)
- Monaco Editor transpilation
- Server external packages for build optimization
- Webpack/Turbopack aliases for browser compatibility
### Content Organization
**Documentation Structure:**
- `/docs/llamaindex/` - Core LlamaIndex.TS documentation
- `/docs/cloud/` - LlamaCloud integration guides
- `/docs/api/` - Auto-generated TypeScript API reference
**Content Sources:**
- Local MDX files in `src/content/docs/`
- External docs from `@llamaindex/workflow-docs` package
- Generated API docs from TypeScript source
### Development Notes
- Documentation content is sourced from multiple locations including external packages
- API documentation is regenerated on each build from TypeScript source
- The site uses advanced MDX features including custom transformers and plugins
- Build process includes comprehensive link validation
- Large memory allocation needed for TypeDoc generation (`--max-old-space-size=8192`)
- Chat functionality uses React Server Components with streaming responses
### AI Chat Integration
The documentation includes an AI chat feature that:
- Uses React Server Components for server-side AI processing
- Integrates with LlamaIndex.TS packages for demonstrations
- Provides interactive examples and code generation
- Streams responses for better user experience
### Content Authoring
When adding new documentation:
- Create MDX files in appropriate `src/content/docs/` subdirectories
- Follow existing content structure and frontmatter conventions
- Use Fumadocs MDX features like code blocks, callouts, and tabs
- API documentation is auto-generated - edit TypeScript source comments instead
- Run `pnpm validate-links` to check all links before publishing
+2 -3
View File
@@ -3,12 +3,11 @@
This is a Next.js application generated with
[Create Fumadocs](https://github.com/fuma-nama/fumadocs).
> Note: Before running the development server, make sure to build the whole project first, see [CONTRIBUTING.md](../../CONTRIBUTING.md) for more details.
Run development server:
```bash
pnpm run dev
turbo run dev
# turbo will build all required packages before running the dev server
```
## Learn More
+2 -2
View File
@@ -12,9 +12,9 @@
},
"aliases": {
"components": "@/components",
"utils": "@/libs/utils",
"utils": "@/lib/utils",
"ui": "@/components/ui",
"lib": "@/libs",
"lib": "@/lib",
"hooks": "@/hooks"
}
}
-2
View File
@@ -1,2 +0,0 @@
// fallback for `fs` usage in `web-tree-sitter`
module.exports = {};
+11 -57
View File
@@ -1,67 +1,13 @@
import { createMDX } from "fumadocs-mdx/next";
import MonacoWebpackPlugin from "monaco-editor-webpack-plugin";
const withMDX = createMDX();
/** @type {import('next').NextConfig} */
const config = {
// default timeout for static generation is 60s, but we need to increase it to 10 minutes due to the large number of document pages
staticPageGenerationTimeout: 600,
reactStrictMode: true,
eslint: {
ignoreDuringBuilds: true,
},
transpilePackages: ["monaco-editor"],
serverExternalPackages: [
"@huggingface/transformers",
"twoslash",
"typescript",
],
async redirects() {
return [
{
source: "/docs/chat-ui/:path*.mdx",
destination: "/docs/chat-ui/:path*",
permanent: true,
},
{
source: "/docs/workflows/:path*.mdx",
destination: "/docs/workflows/:path*",
permanent: true,
},
{
source: "/docs/llamaindex/getting_started/installation/node.mdx",
destination:
"/docs/llamaindex/getting_started/installation/server-apis.mdx",
permanent: true,
},
{
source: "/docs/llamaindex/getting_started/installation/typescript.mdx",
destination: "/docs/llamaindex/getting_started/installation/index.mdx",
permanent: true,
},
{
source: "/docs/llamaindex/getting_started/installation/next.mdx",
destination: "/docs/llamaindex/getting_started/installation/nextjs.mdx",
permanent: true,
},
{
source: "/docs/llamaindex/getting_started/installation/vite.mdx",
destination: "/docs/llamaindex/getting_started/installation/index.mdx",
permanent: true,
},
{
source: "/docs/llamaindex/getting_started/installation/cloudflare.mdx",
destination:
"/docs/llamaindex/getting_started/installation/serverless.mdx",
permanent: true,
},
];
},
turbopack: {
resolveAlias: {
fs: { browser: "./fallback.js" },
},
},
webpack: (config) => {
serverExternalPackages: ["@huggingface/transformers"],
webpack: (config, { isServer }) => {
if (Array.isArray(config.target) && config.target.includes("web")) {
config.target = ["web", "es2020"];
}
@@ -73,6 +19,14 @@ const config = {
};
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;
},
+35 -42
View File
@@ -1,31 +1,25 @@
{
"name": "@llamaindex/doc",
"version": "0.2.48",
"version": "0.0.34",
"private": true,
"scripts": {
"postinstall": "fumadocs-mdx",
"prebuild": "pnpm run build:docs",
"build": "next build",
"dev": "next dev --turbo",
"build": "pnpm run build:docs && next build",
"dev": "next dev",
"start": "next start",
"postbuild": "tsx scripts/post-build.mts && tsx scripts/validate-links.mts",
"build:docs": "cross-env NODE_OPTIONS=\"--max-old-space-size=8192\" typedoc && tsx scripts/generate-docs.mts",
"validate-links": "tsx scripts/validate-links.mts"
"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": {
"@huggingface/transformers": "^3.5.0",
"@icons-pack/react-simple-icons": "^10.1.0",
"@llamaindex/chat-ui-docs": "^0.0.5",
"@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:*",
"@llamaindex/workflow-docs": "0.1.1",
"@mdx-js/mdx": "^3.1.0",
"@monaco-editor/react": "^4.7.0",
"@next/third-parties": "^15.3.4",
"@number-flow/react": "^0.3.4",
"@radix-ui/react-dialog": "^1.1.2",
"@radix-ui/react-icons": "^1.3.2",
@@ -33,67 +27,66 @@
"@radix-ui/react-slider": "^1.2.1",
"@radix-ui/react-slot": "^1.1.0",
"@radix-ui/react-tooltip": "^1.1.4",
"@scalar/api-client-react": "^1.1.25",
"@vercel/functions": "^1.5.0",
"ai": "^4.3.17",
"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": "^15.5.0",
"fumadocs-docgen": "^2.0.0",
"fumadocs-mdx": "^11.6.6",
"fumadocs-openapi": "^9.0.5",
"fumadocs-twoslash": "^3.1.3",
"fumadocs-typescript": "^4.0.5",
"fumadocs-ui": "^15.5.0",
"fumadocs-core": "14.6.0",
"fumadocs-docgen": "1.3.2",
"fumadocs-mdx": "^11.1.2",
"fumadocs-openapi": "^5.8.2",
"fumadocs-twoslash": "^2.0.2",
"fumadocs-typescript": "^3.0.2",
"fumadocs-ui": "14.6.0",
"hast-util-to-jsx-runtime": "^2.3.2",
"llamaindex": "workspace:*",
"lucide-react": "^0.460.0",
"next": "^15.3.3",
"next": "15.0.3",
"next-themes": "^0.4.3",
"react": "^19.1.0",
"react-dom": "^19.1.0",
"react": "^18.3.1",
"react-dom": "^18.3.1",
"react-icons": "^5.3.0",
"react-monaco-editor": "^0.56.2",
"react-text-transition": "^3.1.0",
"react-use-measure": "^2.1.1",
"rehype-katex": "^7.0.1",
"remark-math": "^6.0.0",
"rimraf": "^6.0.1",
"shiki": "^3.1.0",
"shiki-magic-move": "^1.0.1",
"shiki": "1.23.1",
"shiki-magic-move": "^0.5.0",
"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",
"ts-morph": "^25.0.1",
"twoslash": "^0.3.1",
"use-stick-to-bottom": "^1.0.42",
"web-tree-sitter": "^0.24.4",
"zod": "^3.25.76"
"zod": "^3.23.8"
},
"devDependencies": {
"@next/env": "^15.3.0",
"@tailwindcss/postcss": "^4.0.9",
"@next/env": "^15.0.3",
"@types/mdx": "^2.0.13",
"@types/node": "24.0.13",
"@types/react": "^19.1.8",
"@types/react-dom": "^19.1.6",
"@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",
"postcss": "^8.5.6",
"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": "^4.1.11",
"tsx": "^4.20.3",
"typedoc": "0.28.3",
"typedoc-plugin-markdown": "^4.6.2",
"typedoc-plugin-merge-modules": " ^7.0.0",
"typescript": "^5.8.3"
"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"
}
}
+6
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@@ -0,0 +1,6 @@
module.exports = {
plugins: {
tailwindcss: {},
autoprefixer: {},
},
};
-5
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@@ -1,5 +0,0 @@
export default {
plugins: {
"@tailwindcss/postcss": {},
},
};
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+86
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@@ -0,0 +1,86 @@
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,
),
);
-77
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@@ -1,77 +0,0 @@
import {
createGenerator,
generateFiles as typescriptGenerateFiles,
} from "fumadocs-typescript";
import fs from "node:fs";
import * as path from "node:path";
import { rimrafSync } from "rimraf";
const generator = createGenerator();
const out = "./src/content/docs/cloud/api";
const apiRefOut = "./src/content/docs/api";
// clean generated files
rimrafSync(out, {
filter(v) {
return !v.endsWith("index.md") && !v.endsWith("meta.json");
},
});
void typescriptGenerateFiles(generator, {
input: ["./src/content/docs/api/**/*.md"],
output: (file) => path.resolve(path.dirname(file), path.basename(file)),
transformOutput,
});
function transformOutput(filePath: string, content: string) {
const fileName = path.basename(filePath);
let title = fileName.split(".")[0];
if (title === "index") title = "LlamaIndex API Reference";
return `---\ntitle: ${title}\n---\n\n${transformAbsoluteUrl(
content.replace(/(?<!\\)\{([^}]+)(?<!\\)}/g, "\\{$1\\}"),
filePath,
)}`;
}
/**
* Transforms the content by converting relative MD links to absolute docs API links
* Example: [text](../type-aliases/TaskHandler.md) -> [text](/docs/api/type-aliases/TaskHandler)
* [text](BaseChatEngine.md) -> [text](/docs/api/classes/BaseChatEngine)
* [text](BaseVectorStore.md#constructors) -> [text](/docs/api/classes/BaseVectorStore#constructors)
* [text](TaskStep.md) -> [text](/docs/api/type-aliases/TaskStep)
*/
function transformAbsoluteUrl(content: string, filePath: string) {
const group = path.dirname(filePath).split(path.sep).pop();
return content.replace(/\]\(([^)]+)\.md([^)]*)\)/g, (_, slug, anchor) => {
const slugParts = slug.split("/");
const fileName = slugParts[slugParts.length - 1];
const fileGroup = slugParts[slugParts.length - 2] ?? group;
const result = ["/docs/api", fileGroup, fileName, anchor]
.filter(Boolean)
.join("/");
return `](${result})`;
});
}
// append meta.json for API page
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,
),
);
+1 -5
View File
@@ -4,8 +4,4 @@ import { updateLlamaCloud } from "./update-llamacloud.mjs";
env.loadEnvConfig(process.cwd());
if (process.env.VERCEL_ENV === "production") {
updateLlamaCloud().catch((error) => {
console.error(error);
});
}
await updateLlamaCloud();
+7 -4
View File
@@ -1,7 +1,11 @@
import { upsertBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPut } from "@llamaindex/cloud/api";
import fg from "fast-glob";
import { fileGenerator, remarkDocGen, remarkInstall } from "fumadocs-docgen";
import { remarkAutoTypeTable } from "fumadocs-typescript";
import {
fileGenerator,
remarkDocGen,
remarkInstall,
typescriptGenerator,
} from "fumadocs-docgen";
import matter from "gray-matter";
import * as fs from "node:fs/promises";
import path, { relative } from "node:path";
@@ -17,8 +21,7 @@ async function processContent(content: string): Promise<string> {
const file = await remark()
.use(remarkMdx)
.use(remarkGfm)
.use(remarkAutoTypeTable)
.use(remarkDocGen, { generators: [fileGenerator()] })
.use(remarkDocGen, { generators: [typescriptGenerator(), fileGenerator()] })
.use(remarkInstall, { persist: { id: "package-manager" } })
.use(remarkStringify)
.process(content);
-252
View File
@@ -1,252 +0,0 @@
import glob from "fast-glob";
import fs from "fs";
import matter from "gray-matter";
import path from "path";
const CONTENT_DIR = path.join(process.cwd(), "src/content/docs");
// Regular expression to find internal links
// This captures Markdown links [text](/docs/path) and href attributes href="/docs/path"
const INTERNAL_LINK_REGEX = /(?:(?:\]\(|\bhref=["'])\/docs\/([^")]+))/g;
// Regular expression to find relative links
// This captures relative links like [text](./path) or ![alt](../images/image.png)
const RELATIVE_LINK_REGEX = /(?:\]\()(?:\s*)(?:\.\.?)\//g;
const ALLOWED_LINKS = ["/docs/workflows", "/docs/chat-ui"];
interface LinkValidationResult {
file: string;
invalidLinks: Array<{ link: string; line: number }>;
}
interface RelativeLinkResult {
file: string;
relativeLinks: Array<{ line: number; lineContent: string }>;
}
/**
* Get all valid documentation routes from the content directory
*/
async function getValidRoutes(): Promise<Set<string>> {
const mdxFiles = await glob("**/*.{md,mdx}", { cwd: CONTENT_DIR });
const routes = new Set<string>();
// Add each MDX file as a valid route
for (const file of mdxFiles) {
// Remove .mdx extension and normalize to route format
let route = file.replace(/\.mdx?$/, "");
// Handle index files
if (route.endsWith("/index")) {
route = route.replace(/\/index$/, "");
} else if (route === "index") {
route = "";
}
routes.add(route);
}
return routes;
}
/**
* Extract internal links from a MDX file
*/
function extractLinksFromFile(
filePath: string,
): Array<{ link: string; line: number }> {
const content = fs.readFileSync(filePath, "utf-8");
const { content: mdxContent } = matter(content);
const lines = mdxContent.split("\n");
const links: Array<{ link: string; line: number }> = [];
lines.forEach((line, lineNumber) => {
let match;
while ((match = INTERNAL_LINK_REGEX.exec(line)) !== null) {
if (match[1]) {
links.push({
link: match[1],
line: lineNumber + 1, // 1-based line numbers
});
}
}
});
return links;
}
/**
* Check if a link is an image link
*/
function isImageLink(link: string): boolean {
// Check for image extensions
const imageExtensions = [".png", ".jpg", ".jpeg", ".gif", ".svg", ".webp"];
const hasImageExtension = imageExtensions.some((ext) =>
link.toLowerCase().endsWith(ext),
);
// Check for markdown image syntax: ![alt](./path)
const isMarkdownImage = link.trim().startsWith("!");
return hasImageExtension || isMarkdownImage;
}
/**
* Extract relative links from a MDX file
*/
function findRelativeLinksInFile(
filePath: string,
): Array<{ line: number; lineContent: string }> {
const content = fs.readFileSync(filePath, "utf-8");
const { content: mdxContent } = matter(content);
const lines = mdxContent.split("\n");
const relativeLinks: Array<{ line: number; lineContent: string }> = [];
lines.forEach((line, lineNumber) => {
// Check for relative links
if (RELATIVE_LINK_REGEX.test(line)) {
// Reset the regex lastIndex to start from the beginning of the line
RELATIVE_LINK_REGEX.lastIndex = 0;
// Skip image links
if (!isImageLink(line)) {
relativeLinks.push({
line: lineNumber + 1, // 1-based line numbers
lineContent: line.trim(),
});
}
}
});
return relativeLinks;
}
/**
* Find relative links in all MDX files
*/
async function findRelativeLinks(): Promise<RelativeLinkResult[]> {
const mdxFiles = await glob("**/*.mdx", { cwd: CONTENT_DIR });
const results: RelativeLinkResult[] = [];
for (const file of mdxFiles) {
const filePath = path.join(CONTENT_DIR, file);
const relativeLinks = findRelativeLinksInFile(filePath);
if (relativeLinks.length > 0) {
results.push({
file,
relativeLinks,
});
}
}
return results;
}
async function validateLinks(): Promise<LinkValidationResult[]> {
const mdxFiles = await glob("**/*.mdx", { cwd: CONTENT_DIR });
const validRoutes = await getValidRoutes();
const results: LinkValidationResult[] = [];
for (const file of mdxFiles) {
const filePath = path.join(CONTENT_DIR, file);
const links = extractLinksFromFile(filePath);
const invalidLinks = links.filter(({ link }) => {
// Check if the link is in the allowed list
if (ALLOWED_LINKS.includes(`/docs/${link}`)) {
return false;
}
// Check if the link exists in valid routes
// First normalize the link (remove any query string or hash)
const baseLink = link.split("?")[0].split("#")[0];
// Remove the trailing slash if present.
// This works with links like "api/interfaces/MetadataFilter#operator" and "api/interfaces/MetadataFilter/#operator".
const normalizedLink = baseLink.endsWith("/")
? baseLink.slice(0, -1)
: baseLink;
// Remove llamaindex/ prefix if it exists as it's the root of the docs
let routePath = normalizedLink;
if (routePath.startsWith("llamaindex/")) {
routePath = routePath.substring("llamaindex/".length);
}
return !validRoutes.has(normalizedLink) && !validRoutes.has(routePath);
});
if (invalidLinks.length > 0) {
results.push({
file,
invalidLinks,
});
}
}
return results;
}
/**
* Main function to validate links and report errors
*/
async function main() {
console.log("🔍 Validating links in documentation...");
try {
// Check for invalid internal links
const validationResults: LinkValidationResult[] = await validateLinks();
// Check for relative links
const relativeLinksResults = await findRelativeLinks();
let hasErrors = false;
// Report invalid internal links
if (validationResults.length > 0) {
console.error("❌ Found invalid internal links:");
hasErrors = true;
for (const result of validationResults) {
console.error(`\nFile: ${result.file}`);
for (const { link, line } of result.invalidLinks) {
console.error(` - Line ${line}: /docs/${link}`);
}
}
}
// Report relative links
if (relativeLinksResults.length > 0) {
console.error("\n❌ Found relative links (use absolute paths instead):");
hasErrors = true;
for (const result of relativeLinksResults) {
console.error(`\nFile: ${result.file}`);
for (const { line, lineContent } of result.relativeLinks) {
console.error(` - Line ${line}: ${lineContent}`);
}
}
}
if (hasErrors) {
// Exit with error code to fail the build
process.exit(1);
} else {
console.log("✅ All links are valid!");
}
} catch (error) {
console.error("Error validating links:", error);
process.exit(1);
}
}
main().catch((error) => {
console.error("Unhandled error:", error);
process.exit(1);
});
+3 -19
View File
@@ -1,27 +1,12 @@
import {
rehypeCodeDefaultOptions,
remarkStructure,
} from "fumadocs-core/mdx-plugins";
import { rehypeCodeDefaultOptions } from "fumadocs-core/mdx-plugins";
import { fileGenerator, remarkDocGen, remarkInstall } from "fumadocs-docgen";
import { defineConfig, defineDocs } from "fumadocs-mdx/config";
import { transformerTwoslash } from "fumadocs-twoslash";
import rehypeKatex from "rehype-katex";
import remarkMath from "remark-math";
export const docs = defineDocs({
dir: [
"./src/content/docs",
"./node_modules/@llamaindex/workflow-docs",
"./node_modules/@llamaindex/chat-ui-docs",
// NOTE: When adding external docs (like chat-ui or workflow-docs above),
// make sure to also update:
// 1. scripts/validate-links.mts - add to ALLOWED_LINKS array
// 2. next.config.mjs - add redirect for .mdx files
// 3. src/content/docs/meta.json - add to pages array
],
docs: {
async: true,
},
export const { docs, meta } = defineDocs({
dir: "./src/content/docs",
});
export default defineConfig({
@@ -56,7 +41,6 @@ export default defineConfig({
],
},
remarkPlugins: [
remarkStructure,
remarkMath,
[remarkInstall, { persist: { id: "package-manager" } }],
[remarkDocGen, { generators: [fileGenerator()] }],
+74 -71
View File
@@ -8,77 +8,38 @@ import {
} from "@/components/infinite-providers";
import { MagicMove } from "@/components/magic-move";
import { NpmInstall } from "@/components/npm-install";
import { Supports } from "@/components/supports";
import { TextEffect } from "@/components/text-effect";
import { Button } from "@/components/ui/button";
import { DOCUMENT_URL } from "@/libs/const";
import { Skeleton } from "@/components/ui/skeleton";
import { LEGACY_DOCUMENT_URL } from "@/lib/const";
import { SiStackblitz } from "@icons-pack/react-simple-icons";
import {
CodeBlock as FumaCodeBlock,
Pre,
} from "fumadocs-ui/components/codeblock";
import { Blocks, Bot, Footprints, Terminal } from "lucide-react";
import Link from "next/link";
const codes = [
`import { openai } from "@llamaindex/openai";
const llm = openai();
const response = await llm.complete({ prompt: "How are you?" });`,
`import { openai } from "@llamaindex/openai";
const llm = openai();
const response = await llm.chat({
messages: [{ content: "Tell me a joke.", role: "user" }],
});`,
`import { agent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";
const analyseAgent = agent({
llm: openai({ model: "gpt-4o" }),
tools: [analyseTools],
systemPrompt,
});
const response = await analyseAgent.run(\`Analyse the given data:
\${data}\`);`,
`import { agent, multiAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";
const analyseAgent = agent({
name: "AnalyseAgent",
llm: openai({ model: "gpt-4o" }),
tools: [analyseTools],
});
const reporterAgent = agent({
name: "ReporterAgent",
llm: openai({ model: "gpt-4o" }),
tools: [reporterTools],
canHandoffTo: [analyseAgent],
});
const agents = multiAgent({
agents: [analyseAgent, reporterAgent],
rootAgent: reporterAgent,
});
const response = await agents.run(\`Analyse the given data:
\${data}\`);`,
];
import { Suspense } from "react";
export default function HomePage() {
return (
<main className="container mx-auto px-4 py-12">
<h1 className="mb-4 text-center text-4xl font-bold md:text-6xl">
<h1 className="text-4xl md:text-6xl font-bold text-center mb-4">
Build context-augmented web apps using
<br /> <span className="text-blue-500">LlamaIndex.TS</span>
</h1>
<p className="text-fd-muted-foreground mb-12 text-center text-xl">
<p className="text-xl text-center text-fd-muted-foreground mb-12 ">
LlamaIndex.TS is the JS/TS version of{" "}
<a href="https://llamaindex.ai">LlamaIndex</a>, the framework for
building agentic generative AI applications connected to your data.
</p>
<div className="text-fd-muted-foreground mb-12 text-center text-lg">
<div className="text-center text-lg text-fd-muted-foreground mb-12">
<span>Designed for building web applications in </span>
<Supports />
<TextEffect />
</div>
<div className="flex flex-wrap justify-center gap-4">
<Link href={DOCUMENT_URL}>
<Link href={LEGACY_DOCUMENT_URL}>
<Button variant="outline">Get Started</Button>
</Link>
<NpmInstall />
@@ -99,12 +60,57 @@ export default function HomePage() {
icon={Footprints}
subheading="Progressive"
heading="From the simplest to the most complex"
description="LlamaIndex.TS is designed to be simple to get started, but powerful enough to build complex, agentic AI applications using multi-agents."
description="LlamaIndex.TS is designed to be simple to get started, but powerful enough to build complex, agentic AI applications."
>
<MagicMove
placeholder={<CodeBlock lang="ts" code={codes[0]} />}
code={codes}
/>
<Suspense
fallback={
<FumaCodeBlock allowCopy={false}>
<Pre>
<div className="space-y-2">
<Skeleton className="h-4 w-[250px]" />
<Skeleton className="h-4 w-[200px]" />
</div>
</Pre>
</FumaCodeBlock>
}
>
<MagicMove
code={[
`import { OpenAI } from "llamaindex";
const llm = new OpenAI();
const response = await llm.complete({ prompt: "How are you?" });`,
`import { OpenAI } from "llamaindex";
const llm = new OpenAI();
const response = await llm.chat({
messages: [{ content: "Tell me a joke.", role: "user" }],
});`,
`import { OpenAI, ChatMemoryBuffer } from "llamaindex";
const llm = new OpenAI({ model: 'gpt4o-turbo' });
const buffer = new ChatMemoryBuffer({
tokenLimit: 128_000,
})
buffer.put({ content: "Tell me a joke.", role: "user" })
const response = await llm.chat({
messages: buffer.getMessages(),
stream: true
});`,
`import { OpenAIAgent, ChatMemoryBuffer } from "llamaindex";
const agent = new OpenAIAgent({
llm,
tools: [...myTools]
systemPrompt,
});
const buffer = new ChatMemoryBuffer({
tokenLimit: 128_000,
})
buffer.put({ content: "Analysis the data based on the given data.", role: "user" })
buffer.put({ content: \`\${data}\`, role: "user" })
const response = await agent.chat({
message: buffer.getMessages(),
});`,
]}
/>
</Suspense>
</Feature>
<Feature
icon={Bot}
@@ -113,22 +119,19 @@ export default function HomePage() {
description="Truly powerful retrieval-augmented generation applications use agentic techniques, and LlamaIndex.TS makes it easy to build them."
>
<CodeBlock
code={`import { VectorStoreIndex } from "llamaindex";
import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
import { openai } from "@llamaindex/openai";
import { agent } from "@llamaindex/workflow";
code={`import { FunctionTool } from "llamaindex";
import { OpenAIAgent } from "@llamaindex/openai";
// load documents from current directoy into an index
const reader = new SimpleDirectoryReader();
const documents = await reader.loadData(currentDir);
const index = await VectorStoreIndex.fromDocuments(documents);
const interpreterTool = FunctionTool.from(...);
const systemPrompt = \`...\`;
const myAgent = agent({
llm: openai({ model: "gpt-4o" }),
tools: [index.queryTool()],
const agent = new OpenAIAgent({
llm,
tools: [interpreterTool],
systemPrompt,
});
await myAgent.run('...');`}
await agent.chat('...');`}
lang="ts"
/>
</Feature>
@@ -140,13 +143,13 @@ await myAgent.run('...');`}
>
<div className="mt-8 flex flex-col gap-8">
<div>
<h3 className="text-fd-muted-foreground mb-2 text-lg font-semibold">
<h3 className="text-lg font-semibold text-fd-muted-foreground mb-2">
LLMs
</h3>
<InfiniteLLMProviders />
</div>
<div>
<h3 className="text-fd-muted-foreground mb-2 text-lg font-semibold">
<h3 className="text-lg font-semibold text-fd-muted-foreground mb-2">
Vector Stores
</h3>
<InfiniteVectorStoreProviders />
+11
View File
@@ -0,0 +1,11 @@
import { LEGACY_DOCUMENT_URL } from "@/lib/const";
import { redirect } from "next/navigation";
export default async function Page(props: {
params: Promise<{
any: string[];
}>;
}) {
const path = await props.params.then(({ any }) => any.join("/"));
return redirect(new URL(path, LEGACY_DOCUMENT_URL).toString());
}
+1 -1
View File
@@ -1,4 +1,4 @@
import { MockLLM } from "@llamaindex/core/llms/mock";
import { MockLLM } from "@llamaindex/core/utils";
import { LlamaIndexAdapter, type Message } from "ai";
import { Settings, SimpleChatEngine, type ChatMessage } from "llamaindex";
import { NextResponse, type NextRequest } from "next/server";
+2 -10
View File
@@ -1,12 +1,4 @@
import { source } from "@/libs/source";
import { structure } from "fumadocs-core/mdx-plugins";
import { source } from "@/lib/source";
import { createFromSource } from "fumadocs-core/search/server";
// TODO: migrate to another search service, I don't think Vercel can handle that many of documents.
export const { GET } = createFromSource(source, (page) => ({
id: page.file.path,
title: page.data.title,
description: page.data.description,
url: page.url,
structuredData: structure(page.data.content),
}));
export const { GET } = createFromSource(source);
+8 -26
View File
@@ -1,13 +1,7 @@
import * as demos from "@/components/demo/lazy";
import { createMetadata, metadataImage } from "@/libs/metadata";
import { openapi, source } from "@/libs/source";
import * as Icons from "@icons-pack/react-simple-icons";
import { APIPage } from "fumadocs-openapi/ui";
import { createMetadata, metadataImage } from "@/lib/metadata";
import { openapi, source } from "@/lib/source";
import { Popup, PopupContent, PopupTrigger } from "fumadocs-twoslash/ui";
import { createGenerator } from "fumadocs-typescript";
import { AutoTypeTable } from "fumadocs-typescript/ui";
import { Accordion, Accordions } from "fumadocs-ui/components/accordion";
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
import { createTypeTable } from "fumadocs-typescript/ui";
import defaultMdxComponents from "fumadocs-ui/mdx";
import {
DocsBody,
@@ -17,9 +11,7 @@ import {
} from "fumadocs-ui/page";
import { notFound } from "next/navigation";
const generator = createGenerator();
export const revalidate = false;
const { AutoTypeTable } = createTypeTable();
export default async function Page(props: {
params: Promise<{ slug?: string[] }>;
@@ -28,13 +20,12 @@ export default async function Page(props: {
const page = source.getPage(params.slug);
if (!page) notFound();
const { body: MDX, toc, lastModified } = await page.data.load();
const MDX = page.data.body;
return (
<DocsPage
toc={toc}
toc={page.data.toc}
full={page.data.full}
lastUpdate={lastModified}
editOnGithub={{
owner: "run-llama",
repo: "LlamaIndexTS",
@@ -47,20 +38,12 @@ export default async function Page(props: {
<DocsBody>
<MDX
components={{
...Icons,
...defaultMdxComponents,
...demos,
Accordion,
Accordions,
APIPage: (props) => <APIPage {...openapi.getAPIPageProps(props)} />,
Tab,
Tabs,
APIPage: openapi.APIPage,
Popup,
PopupContent,
PopupTrigger,
AutoTypeTable: (props) => (
<AutoTypeTable generator={generator} {...props} />
),
AutoTypeTable,
}}
/>
</DocsBody>
@@ -81,7 +64,6 @@ export async function generateMetadata(props: {
return createMetadata(
metadataImage.withImage(page.slugs, {
metadataBase: new URL("https://ts.llamaindex.ai"),
title: page.data.title,
description: page.data.description,
openGraph: {
+20 -2
View File
@@ -1,7 +1,11 @@
import { baseOptions } from "@/app/layout.config";
import { source } from "@/libs/source";
import { AITrigger } from "@/components/ai-chat";
import { buttonVariants } from "@/components/ui/button";
import { source } from "@/lib/source";
import { cn } from "@/lib/utils";
import "fumadocs-twoslash/twoslash.css";
import { DocsLayout } from "fumadocs-ui/layouts/docs";
import { MessageCircle } from "lucide-react";
import type { ReactNode } from "react";
export default function Layout({ children }: { children: ReactNode }) {
@@ -9,9 +13,23 @@ export default function Layout({ children }: { children: ReactNode }) {
<DocsLayout
tree={source.pageTree}
{...baseOptions}
links={[]}
nav={{
...baseOptions.nav,
children: (
<AITrigger
className={cn(
buttonVariants({
variant: "secondary",
size: "xs",
className:
"md:flex-1 px-2 ms-2 gap-1.5 text-fd-muted-foreground rounded-full",
}),
)}
>
<MessageCircle className="size-3" />
Ask LlamaCloud
</AITrigger>
),
}}
>
{children}
+40 -11
View File
@@ -1,13 +1,6 @@
@import "tailwindcss";
@import "fumadocs-ui/css/neutral.css";
@import "fumadocs-ui/css/preset.css";
@import "../../node_modules/fumadocs-twoslash/styles/twoslash.css";
@plugin "tailwindcss-animate";
@source '../../node_modules/fumadocs-ui/dist/**/*.js';
@source "../../node_modules/fumadocs-openapi/dist/**/*.js",
@source '../../node_modules/@llamaindex/chat-ui/dist/**/*.js';
@config "../../tailwind.config.mjs";
@tailwind base;
@tailwind components;
@tailwind utilities;
@layer base {
:root {
--page-max-width: 1840px;
@@ -53,7 +46,6 @@
--chart-5: 27 87% 67%;
--radius: 0.5rem;
}
.dark {
--color-neutral-000: #0e0c15;
--color-neutral-100: #252134;
@@ -95,3 +87,40 @@
--chart-5: 340 75% 55%;
}
}
@layer base {
* {
@apply border-border;
}
body {
@apply bg-background text-foreground;
}
/*
* Override default styles for Markdown
*/
.prose
:where(blockquote):not(
:where([class~="not-prose"], [class~="not-prose"] *)
) {
font-style: normal !important;
}
.prose
:where(blockquote p:first-of-type):not(
:where([class~="not-prose"], [class~="not-prose"] *)
):before {
content: none !important;
}
.prose
:where(blockquote p:first-of-type):not(
:where([class~="not-prose"], [class~="not-prose"] *)
):after {
content: none !important;
}
.prose
:where(code):not(:where([class~="not-prose"], [class~="not-prose"] *)) {
@apply text-blue-600 !important;
}
}
+3 -13
View File
@@ -1,4 +1,4 @@
import { DOCUMENT_URL } from "@/libs/const";
import { LEGACY_DOCUMENT_URL } from "@/lib/const";
import type { BaseLayoutProps } from "fumadocs-ui/layouts/shared";
import Image from "next/image";
@@ -27,19 +27,9 @@ export const baseOptions: BaseLayoutProps = {
githubUrl: "https://github.com/run-llama/LlamaIndexTS",
links: [
{
text: "TypeScript",
url: DOCUMENT_URL,
text: "Docs",
url: LEGACY_DOCUMENT_URL,
active: "nested-url",
},
{
text: "Python",
url: "https://docs.llamaindex.ai",
active: "url",
},
{
text: "LlamaCloud",
url: "https://docs.cloud.llamaindex.ai/",
active: "url",
},
],
};
+1 -7
View File
@@ -1,6 +1,5 @@
import { AIProvider } from "@/actions";
import { TooltipProvider } from "@/components/ui/tooltip";
import { GoogleAnalytics, GoogleTagManager } from "@next/third-parties/google";
import { RootProvider } from "fumadocs-ui/provider";
import { Inter } from "next/font/google";
import type { ReactNode } from "react";
@@ -32,19 +31,14 @@ export default function Layout({ children }: { children: ReactNode }) {
sizes="16x16"
href="/favicon-16x16.png"
/>
<title>
LlamaIndex.TS - Build LLM-powered document agents and workflows
</title>
</head>
<GoogleTagManager gtmId="GTM-WWRFB36R" />
<body className="flex min-h-screen flex-col">
<body className="flex flex-col min-h-screen">
<TooltipProvider>
<AIProvider>
<RootProvider>{children}</RootProvider>
</AIProvider>
</TooltipProvider>
</body>
<GoogleAnalytics gaId="G-NB9B8LW9W5" />
</html>
);
}
-58
View File
@@ -1,58 +0,0 @@
import fg from "fast-glob";
import { fileGenerator, remarkDocGen, remarkInstall } from "fumadocs-docgen";
import { remarkInclude } from "fumadocs-mdx/config";
import { remarkAutoTypeTable } from "fumadocs-typescript";
import matter from "gray-matter";
import * as fs from "node:fs/promises";
import path from "node:path";
import { remark } from "remark";
import remarkGfm from "remark-gfm";
import remarkMdx from "remark-mdx";
import remarkStringify from "remark-stringify";
export const revalidate = false;
export async function GET() {
const files = await fg(["./src/content/docs/**/*.mdx"]);
const scan = files.map(async (file) => {
const fileContent = await fs.readFile(file);
const { content, data } = matter(fileContent.toString());
const dir = path.dirname(file).split(path.sep).at(4);
const category = {
llamaindex: "LlamaIndexTS Framework",
api: "LlamaIndexTS API",
cloud: "LlamaCloud Service",
}[dir ?? ""];
const processed = await processContent(file, content);
return `file: ${file}
# ${category}: ${data.title}
${data.description}
${processed}`;
});
const scanned = await Promise.all(scan);
return new Response(scanned.join("\n\n"));
}
async function processContent(path: string, content: string): Promise<string> {
const file = await remark()
.use(remarkMdx)
.use(remarkInclude)
.use(remarkGfm)
.use(remarkAutoTypeTable)
.use(remarkDocGen, { generators: [fileGenerator()] })
.use(remarkInstall, { persist: { id: "package-manager" } })
.use(remarkStringify)
.process({
path,
value: content,
});
return String(file);
}
+1 -1
View File
@@ -1,5 +1,5 @@
import { generateOGImage } from "@/app/og/[...slug]/og";
import { metadataImage } from "@/libs/metadata";
import { metadataImage } from "@/lib/metadata";
import { type ImageResponse } from "next/og";
import { readFileSync } from "node:fs";
+5 -5
View File
@@ -45,13 +45,13 @@ export const AITrigger = (props: AITriggerProps) => {
<Dialog>
<DialogTrigger {...props} />
<DialogPortal>
<DialogOverlay className="bg-fd-background/50 data-[state=closed]:animate-fd-fade-out data-[state=open]:animate-fd-fade-in fixed inset-0 z-50 backdrop-blur-sm" />
<DialogOverlay className="fixed inset-0 z-50 bg-fd-background/50 backdrop-blur-sm data-[state=closed]:animate-fd-fade-out data-[state=open]:animate-fd-fade-in" />
<DialogContent
onOpenAutoFocus={(e) => {
document.getElementById("nd-ai-input")?.focus();
e.preventDefault();
}}
className="bg-fd-popover text-fd-popover-foreground data-[state=closed]:animate-fd-dialog-out data-[state=open]:animate-fd-dialog-in fixed left-1/2 z-50 my-[5vh] flex max-h-[90dvh] w-[98vw] max-w-[860px] origin-left -translate-x-1/2 flex-col rounded-lg border shadow-lg focus-visible:outline-none"
className="fixed left-1/2 z-50 my-[5vh] flex max-h-[90dvh] w-[98vw] max-w-[860px] origin-left -translate-x-1/2 flex-col rounded-lg border bg-fd-popover text-fd-popover-foreground shadow-lg focus-visible:outline-none data-[state=closed]:animate-fd-dialog-out data-[state=open]:animate-fd-dialog-in"
>
<DialogHeader>
<DialogTitle className="sr-only">Search AI</DialogTitle>
@@ -67,11 +67,11 @@ export const AITrigger = (props: AITriggerProps) => {
</AlertDescription>
</Alert>
</DialogHeader>
<div className="mt-4 flex-grow overflow-scroll">
<div className="overflow-scroll flex-grow mt-4">
<ChatList messages={messages} />
</div>
<form
className="space-y-4 px-4 py-2"
className="px-4 py-2 space-y-4"
action={async () => {
const value = inputValue.trim();
setInputValue("");
@@ -102,7 +102,7 @@ export const AITrigger = (props: AITriggerProps) => {
}
}}
>
<div className="flex w-full flex-row items-center gap-2">
<div className="flex flex-row w-full items-center gap-2">
<Textarea
tabIndex={0}
placeholder="Ask AI about documentation."
+34 -5
View File
@@ -1,21 +1,50 @@
import { highlight } from "fumadocs-core/highlight";
import * as Base from "fumadocs-ui/components/codeblock";
import type { BundledLanguage } from "shiki";
import { toJsxRuntime, type Jsx } from "hast-util-to-jsx-runtime";
import { Fragment } from "react";
import { jsx, jsxs } from "react/jsx-runtime";
import { codeToHast } from "shiki";
export interface CodeBlockProps {
code: string;
wrapper?: Base.CodeBlockProps;
lang: BundledLanguage;
lang: "bash" | "ts" | "tsx";
}
export async function CodeBlock({ code, lang, wrapper }: CodeBlockProps) {
const rendered = await highlight(code, {
export async function CodeBlock({
code,
lang,
wrapper,
}: CodeBlockProps): Promise<React.ReactElement> {
const hast = await codeToHast(code, {
lang,
defaultColor: false,
themes: {
light: "github-light",
dark: "vesper",
},
transformers: [
{
name: "rehype-code:pre-process",
line(node) {
if (node.children.length === 0) {
// Keep the empty lines when using grid layout
node.children.push({
type: "text",
value: " ",
});
}
},
},
],
});
const rendered = toJsxRuntime(hast, {
jsx: jsx as Jsx,
jsxs: jsxs as Jsx,
Fragment,
development: false,
components: {
// @ts-expect-error -- JSX component
pre: Base.Pre,
},
});
+2 -2
View File
@@ -1,6 +1,6 @@
import ContributorCounter from "@/components/contributor-count";
import { buttonVariants } from "@/components/ui/button";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
import { Heart } from "lucide-react";
import { ReactElement } from "react";
@@ -10,7 +10,7 @@ export function Contributing(): ReactElement {
<h2 className="mb-4 text-xl font-semibold sm:text-2xl">
Made possible by you <Heart className="inline align-middle" />
</h2>
<p className="text-fd-muted-foreground mb-4">
<p className="mb-4 text-fd-muted-foreground">
LlamaIndex.TS is powered by the open source community.
</p>
<div className="mb-8 flex flex-row items-center gap-2">
@@ -1,5 +1,5 @@
import { fetchContributors } from "@/libs/get-contributors";
import { cn } from "@/libs/utils";
import { fetchContributors } from "@/lib/get-contributors";
import { cn } from "@/lib/utils";
import Image from "next/image";
import type { HTMLAttributes, ReactElement } from "react";
@@ -33,7 +33,7 @@ export default async function ContributorCounter({
href={`https://github.com/${contributor.login}`}
rel="noreferrer noopener"
target="_blank"
className="border-fd-background bg-fd-background size-10 overflow-hidden rounded-full border-4 md:-mr-4 md:size-12"
className="size-10 overflow-hidden rounded-full border-4 border-fd-background bg-fd-background md:-mr-4 md:size-12"
style={{
zIndex: topContributors.length - i,
}}
@@ -48,7 +48,7 @@ export default async function ContributorCounter({
</a>
))}
{displayCount < contributors.length ? (
<div className="bg-fd-secondary size-12 content-center rounded-full text-center">
<div className="size-12 content-center rounded-full bg-fd-secondary text-center">
+{contributors.length - displayCount}
</div>
) : null}
@@ -1,5 +1,5 @@
"use client";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
import { TerminalIcon } from "lucide-react";
import {
Fragment,
@@ -83,7 +83,7 @@ export function CreateAppAnimation(): React.ReactElement {
}}
>
{tick > timeWindowOpen && (
<LaunchAppWindow className="animate-in fade-in slide-in-from-top-10 absolute bottom-5 right-4 z-10" />
<LaunchAppWindow className="absolute bottom-5 right-4 z-10 animate-in fade-in slide-in-from-top-10" />
)}
<pre className="overflow-hidden rounded-xl border text-xs">
<div className="flex flex-row items-center gap-2 border-b px-4 py-2">
@@ -92,7 +92,7 @@ export function CreateAppAnimation(): React.ReactElement {
<div className="grow" />
<div className="size-2 rounded-full bg-red-400" />
</div>
<div className="from-fd-secondary min-h-[200px] bg-gradient-to-b [mask-image:linear-gradient(to_bottom,white,transparent)]">
<div className="min-h-[200px] bg-gradient-to-b from-fd-secondary [mask-image:linear-gradient(to_bottom,white,transparent)]">
<code className="grid p-4">{lines}</code>
</div>
</pre>
@@ -103,7 +103,7 @@ export function CreateAppAnimation(): React.ReactElement {
function UserMessage({ children }: { children: ReactNode }) {
return (
<div className="group relative flex items-start">
<div className="bg-background flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm">
<div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm bg-background">
<IconUser />
</div>
<div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
@@ -122,7 +122,7 @@ function BotMessage({
}) {
return (
<div className={cn("group relative flex items-start", className)}>
<div className="bg-primary text-primary-foreground flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm">
<div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm bg-primary text-primary-foreground">
<IconAI />
</div>
<div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
@@ -164,7 +164,7 @@ export function ChatExample() {
return (
<div className="max-w-64">
<div className="flex flex-col gap-2 px-4">
<div className="flex flex-col px-4 gap-2">
{userMessageLength === userMessageFull.length && (
<UserMessage>
<span>{userMessageFull}</span>
@@ -204,11 +204,11 @@ function LaunchAppWindow(
<div
{...props}
className={cn(
"bg-fd-background overflow-hidden rounded-md border shadow-xl",
"overflow-hidden rounded-md border bg-fd-background shadow-xl",
props.className,
)}
>
<div className="bg-fd-muted text-fd-muted-foreground relative flex h-6 flex-row items-center border-b px-4 text-xs">
<div className="relative flex h-6 flex-row items-center border-b bg-fd-muted px-4 text-xs text-fd-muted-foreground">
<p className="absolute inset-x-0 text-center">localhost:8080</p>
</div>
<div className="p-4 text-sm">
@@ -0,0 +1,16 @@
"use client";
import { ChatInput, ChatMessages, ChatSection } from "@llamaindex/chat-ui";
import { useChat } from "ai/react";
export const ChatDemo = () => {
const handler = useChat();
return (
<ChatSection handler={handler}>
<ChatMessages>
<ChatMessages.List className="h-auto max-h-[400px]" />
<ChatMessages.Actions />
</ChatMessages>
<ChatInput />
</ChatSection>
);
};
@@ -0,0 +1,57 @@
import { Markdown } from "@llamaindex/chat-ui/widgets";
import { MockLLM } from "@llamaindex/core/utils";
import { generateId, Message } from "ai";
import { createAI, createStreamableUI, getMutableAIState } from "ai/rsc";
import { type ChatMessage, Settings, SimpleChatEngine } from "llamaindex";
import { ReactNode } from "react";
type ServerState = Message[];
type FrontendState = Array<Message & { display: ReactNode }>;
type Actions = {
chat: (message: Message) => Promise<Message & { display: ReactNode }>;
};
Settings.llm = new MockLLM(); // config your LLM here
export const AI = createAI<ServerState, FrontendState, Actions>({
initialAIState: [],
initialUIState: [],
actions: {
chat: async (message: Message) => {
"use server";
const aiState = getMutableAIState<typeof AI>();
aiState.update((prev) => [...prev, message]);
const uiStream = createStreamableUI();
const chatEngine = new SimpleChatEngine();
const assistantMessage: Message = {
id: generateId(),
role: "assistant",
content: "",
};
// run the async function without blocking
(async () => {
const chatResponse = await chatEngine.chat({
stream: true,
message: message.content,
chatHistory: aiState.get() as ChatMessage[],
});
for await (const chunk of chatResponse) {
assistantMessage.content += chunk.delta;
uiStream.update(<Markdown content={assistantMessage.content} />);
}
aiState.done([...aiState.get(), assistantMessage]);
uiStream.done();
})();
return {
...assistantMessage,
display: uiStream.value,
};
},
},
});
@@ -0,0 +1,33 @@
"use client";
import {
ChatInput,
ChatMessage,
ChatMessages,
ChatSection as ChatSectionUI,
} from "@llamaindex/chat-ui";
import { useChatRSC } from "./use-chat-rsc";
export const ChatSectionRSC = () => {
const handler = useChatRSC();
return (
<ChatSectionUI handler={handler}>
<ChatMessages>
<ChatMessages.List className="h-auto max-h-[400px]">
{handler.messages.map((message, index) => (
<ChatMessage
key={index}
message={message}
isLast={index === handler.messages.length - 1}
>
<ChatMessage.Avatar />
<ChatMessage.Content>{message.display}</ChatMessage.Content>
</ChatMessage>
))}
<ChatMessages.Loading />
</ChatMessages.List>
</ChatMessages>
<ChatInput />
</ChatSectionUI>
);
};
@@ -0,0 +1,8 @@
import { AI } from "./ai-action";
import { ChatSectionRSC } from "./chat-section";
export const ChatDemoRSC = () => (
<AI>
<ChatSectionRSC />
</AI>
);
@@ -0,0 +1,41 @@
"use client";
import { useActions } from "ai/rsc";
import { generateId, Message } from "ai";
import { useUIState } from "ai/rsc";
import { useState } from "react";
import { AI } from "./ai-action";
export function useChatRSC() {
const [input, setInput] = useState<string>("");
const [isLoading, setIsLoading] = useState<boolean>(false);
const [messages, setMessages] = useUIState<typeof AI>();
const { chat } = useActions<typeof AI>();
const append = async (message: Omit<Message, "id">) => {
const newMsg: Message = { ...message, id: generateId() };
setIsLoading(true);
try {
setMessages((prev) => [...prev, { ...newMsg, display: message.content }]);
const assistantMsg = await chat(newMsg);
setMessages((prev) => [...prev, assistantMsg]);
} catch (error) {
console.error(error);
}
setIsLoading(false);
setInput("");
return message.content;
};
return {
input,
setInput,
isLoading,
messages,
setMessages,
append,
};
}
@@ -1,26 +1,24 @@
"use client";
import { createContextState } from "foxact/context-state";
import { useIsClient } from "foxact/use-is-client";
import { useShiki } from "fumadocs-core/utils/use-shiki";
import { CodeBlock, Pre } from "fumadocs-ui/components/codeblock";
import { lazy, Suspense, use, useMemo } from "react";
import { StickToBottom, useStickToBottomContext } from "use-stick-to-bottom";
import Parser from "web-tree-sitter";
import { Label } from "@/components/ui/label";
import { Skeleton } from "@/components/ui/skeleton";
import { Slider } from "@/components/ui/slider";
import { CodeSplitter } from "@llamaindex/node-parser/code";
import { Editor } from "@monaco-editor/react";
import { createContextState } from "foxact/context-state";
import { useIsClient } from "foxact/use-is-client";
import { useShiki } from "fumadocs-core/highlight/client";
import { CodeBlock, Pre } from "fumadocs-ui/components/codeblock";
import { Suspense, use, useMemo } from "react";
import { StickToBottom, useStickToBottomContext } from "use-stick-to-bottom";
let promise: Promise<CodeSplitter>;
if (typeof window !== "undefined") {
async function run() {
const { default: Parser } = await import("web-tree-sitter");
await Parser.init({
locateFile(scriptName: string) {
return "/" + scriptName;
},
});
promise = Parser.init({
locateFile(scriptName: string) {
return "/" + scriptName;
},
}).then(async () => {
const parser = new Parser();
const Lang = await Parser.Language.load("/tree-sitter-typescript.wasm");
parser.setLanguage(Lang);
@@ -28,9 +26,7 @@ if (typeof window !== "undefined") {
getParser: () => parser,
maxChars: 100,
});
}
promise = run();
});
}
const [SliderProvider, useSlider, useSetSlider] = createContextState(100);
@@ -52,6 +48,8 @@ const john: Person = {
console.log(greet(john));`);
const Editor = lazy(() => import("react-monaco-editor"));
export const IDE = () => {
const codeSplitter = use(promise);
const code = useCode();
@@ -59,7 +57,7 @@ export const IDE = () => {
const maxChars = useSlider();
const useSetMaxChars = useSetSlider();
return (
<div className="flex max-h-96 flex-col overflow-scroll border-r p-4">
<div className="flex flex-col p-4 border-r max-h-96 overflow-scroll">
<div>
<Label>Max Chars {maxChars}</Label>
<Slider
@@ -75,6 +73,21 @@ export const IDE = () => {
/>
</div>
<Editor
editorWillMount={() => {}}
editorDidMount={() => {
window.MonacoEnvironment!.getWorkerUrl = (
_moduleId: string,
label: string,
) => {
if (label === "json") return "/_next/static/json.worker.js";
if (label === "css") return "/_next/static/css.worker.js";
if (label === "html") return "/_next/static/html.worker.js";
if (label === "typescript" || label === "javascript")
return "/_next/static/ts.worker.js";
return "/_next/static/editor.worker.js";
};
}}
editorWillUnmount={() => {}}
options={{
minimap: {
enabled: false,
@@ -84,9 +97,7 @@ export const IDE = () => {
height="100%"
width="100%"
language="typescript"
onChange={(v) => {
if (v) setCode(v);
}}
onChange={setCode}
value={code}
/>
</div>
@@ -102,7 +113,7 @@ const Preview = ({ text }: { text: string }) => {
},
},
});
return <CodeBlock className="m-2 py-0">{rendered}</CodeBlock>;
return <CodeBlock className="py-0 m-2">{rendered}</CodeBlock>;
};
function ScrollToBottom() {
@@ -111,7 +122,7 @@ function ScrollToBottom() {
return (
!isAtBottom && (
<button
className="i-ph-arrow-circle-down-fill absolute bottom-0 left-[50%] translate-x-[-50%] rounded-lg text-4xl"
className="absolute i-ph-arrow-circle-down-fill text-4xl rounded-lg left-[50%] translate-x-[-50%] bottom-0"
onClick={() => scrollToBottom()}
/>
)
@@ -125,7 +136,7 @@ export const NodePreview = () => {
const textChunks = useMemo(() => parser.splitText(code), [code, maxChars]);
return (
<StickToBottom
className="relative block max-h-96 overflow-scroll"
className="block relative max-h-96 overflow-scroll"
resize="smooth"
initial="smooth"
>
@@ -143,7 +154,7 @@ export const CodeNodeParserDemo = () => {
const isClient = useIsClient();
if (!isClient) {
return (
<div className="my-2 grid max-h-96 w-full grid-cols-1 gap-2 rounded-xl border md:grid-cols-2">
<div className="my-2 grid grid-cols-1 md:grid-cols-2 gap-2 border rounded-xl w-full max-h-96">
<Skeleton className="h-96" />
<Skeleton className="h-96" />
</div>
@@ -154,13 +165,13 @@ export const CodeNodeParserDemo = () => {
<CodeProvider>
<Suspense
fallback={
<div className="my-2 grid max-h-96 w-full grid-cols-1 gap-2 rounded-xl border md:grid-cols-2">
<div className="my-2 grid grid-cols-1 md:grid-cols-2 gap-2 border rounded-xl w-full max-h-96">
<Skeleton className="h-96" />
<Skeleton className="h-96" />
</div>
}
>
<div className="my-2 grid max-h-96 w-full grid-cols-1 gap-2 rounded-xl border md:grid-cols-2">
<div className="my-2 grid grid-cols-1 md:grid-cols-2 gap-2 border rounded-xl w-full max-h-96">
<IDE />
<NodePreview />
</div>
-8
View File
@@ -1,8 +0,0 @@
"use client";
import dynamic from "next/dynamic";
export const CodeNodeParserDemo = dynamic(() =>
import("@/components/demo/code-node-parser").then(
(mod) => mod.CodeNodeParserDemo,
),
);
@@ -0,0 +1,152 @@
"use client";
import FlowInput from "@/components/flow-input";
import { Button } from "@/components/ui/button";
import {
StartEvent,
StopEvent,
Workflow,
WorkflowEvent,
} from "@llamaindex/workflow";
import { ReactNode, startTransition, useState } from "react";
import { StickToBottom, useStickToBottomContext } from "use-stick-to-bottom";
class ComputeEvent extends WorkflowEvent<number> {
constructor(data: number) {
super(data);
}
}
class ComputeResultEvent extends WorkflowEvent<number> {
constructor(data: number) {
super(data);
}
}
type ContextData = {
sum: number;
};
const workflow = new Workflow<ContextData, number, number>();
const max = 1000;
const min = 100;
workflow.addStep(
{
inputs: [StartEvent<number>],
outputs: [StopEvent<number>],
},
async (context, event) => {
const total = event.data;
for (let i = 0; i < total; i++) {
context.sendEvent(new ComputeEvent(i));
}
console.log("waiting");
const computeResults = await Promise.all(
Array.from({ length: total }).map(() =>
context.requireEvent(ComputeResultEvent),
),
);
context.data.sum = computeResults.reduce(
(acc, result) => acc + result.data,
0,
);
console.log("stop");
return new StopEvent(context.data.sum);
},
);
workflow.addStep(
{
inputs: [ComputeEvent],
outputs: [ComputeResultEvent],
},
async (context, event) => {
await new Promise((resolve) =>
setTimeout(resolve, Math.floor(Math.random() * (max - min + 1) + min)),
);
return new ComputeResultEvent(event.data);
},
);
function ScrollToBottom() {
const { isAtBottom, scrollToBottom } = useStickToBottomContext();
return (
!isAtBottom && (
<button
className="absolute i-ph-arrow-circle-down-fill text-4xl rounded-lg left-[50%] translate-x-[-50%] bottom-0"
onClick={() => scrollToBottom()}
/>
)
);
}
export function WorkflowStreamingDemo() {
const [ui, setUI] = useState<ReactNode[]>([
<div key={0} className="bg-gray-100 dark:bg-gray-800">
Waiting for workflow to start
</div>,
]);
const [total, setTotal] = useState<number>(10);
return (
<div className="flex flex-col items-start w-full gap-2">
<div className="flex flex-row justify-center items-center">
<div className="text-lg mr-2">Compute total</div>{" "}
<FlowInput value={total} onChange={(value) => setTotal(value)} />
</div>
<Button
onClick={async () => {
startTransition(() => {
setUI([]);
});
const context = workflow.run(total, {
sum: 0,
});
let i = 0;
for await (const event of context) {
console.log(event);
if (event instanceof ComputeEvent) {
setUI((ui) => [
...ui,
<div key={i++} className="bg-yellow-100 dark:bg-yellow-800">
Computing task id: {event.data}
</div>,
]);
} else if (event instanceof ComputeResultEvent) {
setUI((ui) => [
...ui,
<div key={i++} className="bg-green-100 dark:bg-green-800">
Computed task id: {event.data}
</div>,
]);
} else if (event instanceof StartEvent) {
setUI((ui) => [
...ui,
<div key={i++} className="bg-blue-100 dark:bg-blue-800">
Started workflow with total {event.data}
</div>,
]);
} else if (event instanceof StopEvent) {
setUI((ui) => [
...ui,
<div key={i++} className="bg-red-100 dark:bg-red-800">
Workflow stopped
</div>,
]);
}
}
}}
>
Start Workflow
</Button>
<StickToBottom className="w-full flex flex-col gap-2 p-2 border border-gray-200 rounded-lg max-h-96 overflow-y-auto">
<StickToBottom.Content className="flex flex-col gap-2">
{ui}
</StickToBottom.Content>
<ScrollToBottom />
</StickToBottom>
</div>
);
}
+2 -2
View File
@@ -1,4 +1,4 @@
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
import { LucideIcon } from "lucide-react";
import { HTMLAttributes, ReactElement, ReactNode } from "react";
@@ -20,7 +20,7 @@ export function Feature({
className={cn("border-l border-t px-6 py-12 md:py-16", className)}
{...props}
>
<div className="text-fd-muted-foreground mb-4 inline-flex items-center gap-2 text-sm font-medium">
<div className="mb-4 inline-flex items-center gap-2 text-sm font-medium text-fd-muted-foreground">
<Icon className="size-4" />
<p>{subheading}</p>
</div>
+1 -1
View File
@@ -60,7 +60,7 @@ export default function FlowInput({
className={clsx(
showCaret ? "caret-primary" : "caret-transparent",
"spin-hide w-[1.5em] bg-transparent py-2 text-center font-[inherit] text-transparent outline-none",
"[appearance:textfield] [&::-webkit-inner-spin-button]:appearance-none [&::-webkit-outer-spin-button]:appearance-none",
"[appearance:textfield] [&::-webkit-outer-spin-button]:appearance-none [&::-webkit-inner-spin-button]:appearance-none",
)}
// Make sure to disable kerning, to match NumberFlow:
style={{ fontKerning: "none" }}
+22 -27
View File
@@ -1,27 +1,25 @@
"use client";
import { Button } from "@/components/ui/button";
import { cn } from "@/libs/utils";
import { CodeBlock } from "fumadocs-ui/components/codeblock";
import { cn } from "@/lib/utils";
import { CodeBlock, Pre } from "fumadocs-ui/components/codeblock";
import { RotateCcw } from "lucide-react";
import { useTheme } from "next-themes";
import { type ReactNode, use, useCallback, useEffect, useState } from "react";
import { createJavaScriptRegexEngine, getSingletonHighlighter } from "shiki";
import { use, useCallback, useEffect, useState } from "react";
import { getSingletonHighlighter } from "shiki";
import { ShikiMagicMove } from "shiki-magic-move/react";
import { createOnigurumaEngine } from "shiki/engine/oniguruma";
const engine = createJavaScriptRegexEngine();
const highlighterPromise = getSingletonHighlighter({
engine,
engine: createOnigurumaEngine(() => import("shiki/wasm")),
themes: ["vesper", "github-light"],
langs: ["js", "ts", "tsx"],
});
export type MagicMoveProps = {
code: string[];
placeholder: ReactNode;
};
export function MagicMove(props: MagicMoveProps) {
const [mounted, setMounted] = useState(false);
const [move, setMove] = useState<number>(0);
const currentCode = props.code[move];
const highlighter = use(highlighterPromise);
@@ -40,27 +38,24 @@ export function MagicMove(props: MagicMoveProps) {
}
}, [animate, move, props.code]);
useEffect(() => {
setMounted(true);
}, []);
if (!mounted) return props.placeholder;
return (
<CodeBlock allowCopy={false}>
<ShikiMagicMove
className="shiki !block p-4 *:!inline"
lang="ts"
theme={resolvedTheme === "dark" ? "vesper" : "github-light"}
highlighter={highlighter}
code={currentCode}
options={{
duration: 800,
stagger: 0.3,
lineNumbers: false,
containerStyle: false,
}}
/>
{highlighter && (
<Pre>
<ShikiMagicMove
lang="ts"
theme={resolvedTheme === "dark" ? "vesper" : "github-light"}
highlighter={highlighter}
code={currentCode}
options={{
duration: 800,
stagger: 0.3,
lineNumbers: false,
containerStyle: false,
}}
/>
</Pre>
)}
<Button
className={cn(
"absolute bottom-2 right-2",
+3 -3
View File
@@ -1,6 +1,6 @@
"use client";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
import Image from "next/image";
import { ReactNode } from "react";
import { IconAI, IconUser } from "./ui/icons";
@@ -8,7 +8,7 @@ import { IconAI, IconUser } from "./ui/icons";
export function UserMessage({ children }: { children: ReactNode }) {
return (
<div className="group relative flex items-start">
<div className="bg-background flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm">
<div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm bg-background">
<IconUser />
</div>
<div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
@@ -54,7 +54,7 @@ export function BotCard({
<div className="group relative flex items-start md:-ml-12">
<div
className={cn(
"bg-primary text-primary-foreground flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm",
"flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm bg-primary text-primary-foreground",
!showAvatar && "invisible",
)}
>
+1 -1
View File
@@ -25,7 +25,7 @@ export const NpmInstall = () => {
className="flex flex-row items-center justify-center"
>
<code className="mr-2">$ npm i llamaindex</code>
<div className="relative h-4 w-4 cursor-pointer bg-transparent">
<div className="relative cursor-pointer bg-transparent w-4 h-4">
<div
className={`absolute inset-0 transform transition-all duration-300 ${
hasCheckIcon ? "scale-0 opacity-0" : "scale-100 opacity-100"
@@ -1,268 +0,0 @@
import { cn } from "@/libs/utils";
import {
AnimatePresence,
motion,
Transition,
type AnimationControls,
type Target,
type TargetAndTransition,
type VariantLabels,
} from "framer-motion";
import React, {
forwardRef,
useCallback,
useEffect,
useImperativeHandle,
useMemo,
useState,
} from "react";
export interface RotatingTextRef {
next: () => void;
previous: () => void;
jumpTo: (index: number) => void;
reset: () => void;
}
export interface RotatingTextProps
extends Omit<
React.ComponentPropsWithoutRef<typeof motion.span>,
"children" | "transition" | "initial" | "animate" | "exit"
> {
texts: string[];
transition?: Transition;
initial?: boolean | Target | VariantLabels;
animate?: boolean | VariantLabels | AnimationControls | TargetAndTransition;
exit?: Target | VariantLabels;
animatePresenceMode?: "sync" | "wait";
animatePresenceInitial?: boolean;
rotationInterval?: number;
staggerDuration?: number;
staggerFrom?: "first" | "last" | "center" | "random" | number;
loop?: boolean;
auto?: boolean;
splitBy?: string;
onNext?: (index: number) => void;
mainClassName?: string;
splitLevelClassName?: string;
elementLevelClassName?: string;
}
export const RotatingText = forwardRef<RotatingTextRef, RotatingTextProps>(
(
{
texts,
transition = { type: "spring", damping: 25, stiffness: 300 },
initial = { y: "100%", opacity: 0 },
animate = { y: 0, opacity: 1 },
exit = { y: "-120%", opacity: 0 },
animatePresenceMode = "wait",
animatePresenceInitial = false,
rotationInterval = 2000,
staggerDuration = 0,
staggerFrom = "first",
loop = true,
auto = true,
splitBy = "characters",
onNext,
mainClassName,
splitLevelClassName,
elementLevelClassName,
...rest
},
ref,
) => {
const [currentTextIndex, setCurrentTextIndex] = useState<number>(0);
const splitIntoCharacters = (text: string): string[] => {
if (typeof Intl !== "undefined" && Intl.Segmenter) {
const segmenter = new Intl.Segmenter("en", { granularity: "grapheme" });
return Array.from(
segmenter.segment(text),
(segment) => segment.segment,
);
}
return Array.from(text);
};
const elements = useMemo(() => {
const currentText: string = texts[currentTextIndex];
if (splitBy === "characters") {
const words = currentText.split(" ");
return words.map((word, i) => ({
characters: splitIntoCharacters(word),
needsSpace: i !== words.length - 1,
}));
}
if (splitBy === "words") {
return currentText.split(" ").map((word, i, arr) => ({
characters: [word],
needsSpace: i !== arr.length - 1,
}));
}
if (splitBy === "lines") {
return currentText.split("\n").map((line, i, arr) => ({
characters: [line],
needsSpace: i !== arr.length - 1,
}));
}
return currentText.split(splitBy).map((part, i, arr) => ({
characters: [part],
needsSpace: i !== arr.length - 1,
}));
}, [texts, currentTextIndex, splitBy]);
const getStaggerDelay = useCallback(
(index: number, totalChars: number): number => {
const total = totalChars;
if (staggerFrom === "first") return index * staggerDuration;
if (staggerFrom === "last")
return (total - 1 - index) * staggerDuration;
if (staggerFrom === "center") {
const center = Math.floor(total / 2);
return Math.abs(center - index) * staggerDuration;
}
if (staggerFrom === "random") {
const randomIndex = Math.floor(Math.random() * total);
return Math.abs(randomIndex - index) * staggerDuration;
}
return Math.abs((staggerFrom as number) - index) * staggerDuration;
},
[staggerFrom, staggerDuration],
);
const handleIndexChange = useCallback(
(newIndex: number) => {
setCurrentTextIndex(newIndex);
if (onNext) onNext(newIndex);
},
[onNext],
);
const next = useCallback(() => {
const nextIndex =
currentTextIndex === texts.length - 1
? loop
? 0
: currentTextIndex
: currentTextIndex + 1;
if (nextIndex !== currentTextIndex) {
handleIndexChange(nextIndex);
}
}, [currentTextIndex, texts.length, loop, handleIndexChange]);
const previous = useCallback(() => {
const prevIndex =
currentTextIndex === 0
? loop
? texts.length - 1
: currentTextIndex
: currentTextIndex - 1;
if (prevIndex !== currentTextIndex) {
handleIndexChange(prevIndex);
}
}, [currentTextIndex, texts.length, loop, handleIndexChange]);
const jumpTo = useCallback(
(index: number) => {
const validIndex = Math.max(0, Math.min(index, texts.length - 1));
if (validIndex !== currentTextIndex) {
handleIndexChange(validIndex);
}
},
[texts.length, currentTextIndex, handleIndexChange],
);
const reset = useCallback(() => {
if (currentTextIndex !== 0) {
handleIndexChange(0);
}
}, [currentTextIndex, handleIndexChange]);
useImperativeHandle(
ref,
() => ({
next,
previous,
jumpTo,
reset,
}),
[next, previous, jumpTo, reset],
);
useEffect(() => {
if (!auto) return;
const intervalId = setInterval(next, rotationInterval);
return () => clearInterval(intervalId);
}, [next, rotationInterval, auto]);
return (
<motion.span
className={cn(
"relative flex flex-wrap whitespace-pre-wrap",
mainClassName,
)}
{...rest}
layout
transition={transition}
>
<span className="sr-only">{texts[currentTextIndex]}</span>
<AnimatePresence
mode={animatePresenceMode}
initial={animatePresenceInitial}
>
<motion.div
key={currentTextIndex}
className={cn(
splitBy === "lines"
? "flex w-full flex-col"
: "relative flex flex-wrap whitespace-pre-wrap",
)}
layout
aria-hidden="true"
>
{elements.map((wordObj, wordIndex, array) => {
const previousCharsCount = array
.slice(0, wordIndex)
.reduce((sum, word) => sum + word.characters.length, 0);
return (
<span
key={wordIndex}
className={cn("inline-flex", splitLevelClassName)}
>
{wordObj.characters.map((char, charIndex) => (
<motion.span
key={charIndex}
initial={initial}
animate={animate}
exit={exit}
transition={{
...transition,
delay: getStaggerDelay(
previousCharsCount + charIndex,
array.reduce(
(sum, word) => sum + word.characters.length,
0,
),
),
}}
className={cn("inline-block", elementLevelClassName)}
>
{char}
</motion.span>
))}
{wordObj.needsSpace && (
<span className="whitespace-pre"> </span>
)}
</span>
);
})}
</motion.div>
</AnimatePresence>
</motion.span>
);
},
);
RotatingText.displayName = "RotatingText";
-27
View File
@@ -1,27 +0,0 @@
"use client";
import { RotatingText } from "@/components/reactbits/rotating-text";
const supports = [
"Next.js",
"Node.js",
"Hono",
"Express.js",
"Deno",
"Nest.js",
"Waku",
];
export const Supports = () => {
return (
<RotatingText
texts={supports}
mainClassName="inline-flex bg-transparent overflow-hidden justify-center"
initial={{ y: "100%" }}
animate={{ y: 0 }}
exit={{ y: "-120%" }}
staggerDuration={0.025}
transition={{ type: "spring", damping: 30, stiffness: 400 }}
rotationInterval={2000}
/>
);
};
+28
View File
@@ -0,0 +1,28 @@
"use client";
import { useEffect, useState } from "react";
import ReactTextTransition from "react-text-transition";
const supports = [
"Next.js",
"Node.js",
"Hono",
"Express.js",
"Deno",
"Nest.js",
"Waku",
];
export const TextEffect = () => {
const [counter, setCounter] = useState(0);
useEffect(() => {
const id = setInterval(() => {
setCounter(
(Math.floor(Math.random() * supports.length) + 1) % supports.length,
);
}, 4000);
return () => {
clearInterval(id);
};
}, []);
return <ReactTextTransition inline>{supports[counter]}</ReactTextTransition>;
};
+1 -1
View File
@@ -1,7 +1,7 @@
import { cva, type VariantProps } from "class-variance-authority";
import * as React from "react";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
const alertVariants = cva(
"relative w-full rounded-lg border px-4 py-3 text-sm [&>svg+div]:translate-y-[-3px] [&>svg]:absolute [&>svg]:left-4 [&>svg]:top-4 [&>svg]:text-foreground [&>svg~*]:pl-7",
+1 -1
View File
@@ -1,7 +1,7 @@
import { cva, type VariantProps } from "class-variance-authority";
import * as React from "react";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
const badgeVariants = cva(
"inline-flex items-center rounded-md border px-2.5 py-0.5 text-xs font-semibold transition-colors focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2",
+1 -1
View File
@@ -2,7 +2,7 @@ import { Slot } from "@radix-ui/react-slot";
import { cva, type VariantProps } from "class-variance-authority";
import * as React from "react";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
const buttonVariants = cva(
"inline-flex items-center justify-center gap-2 whitespace-nowrap rounded-md text-sm font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:pointer-events-none disabled:opacity-50 [&_svg]:pointer-events-none [&_svg]:size-4 [&_svg]:shrink-0",
+5 -5
View File
@@ -4,7 +4,7 @@ import * as DialogPrimitive from "@radix-ui/react-dialog";
import { Cross2Icon } from "@radix-ui/react-icons";
import * as React from "react";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
const Dialog = DialogPrimitive.Root;
@@ -21,7 +21,7 @@ const DialogOverlay = React.forwardRef<
<DialogPrimitive.Overlay
ref={ref}
className={cn(
"data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 fixed inset-0 z-50 bg-black/80",
"fixed inset-0 z-50 bg-black/80 data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0",
className,
)}
{...props}
@@ -38,13 +38,13 @@ const DialogContent = React.forwardRef<
<DialogPrimitive.Content
ref={ref}
className={cn(
"bg-background data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[state=closed]:slide-out-to-left-1/2 data-[state=closed]:slide-out-to-top-[48%] data-[state=open]:slide-in-from-left-1/2 data-[state=open]:slide-in-from-top-[48%] fixed left-[50%] top-[50%] z-50 grid w-full max-w-lg translate-x-[-50%] translate-y-[-50%] gap-4 border p-6 shadow-lg duration-200 sm:rounded-lg",
"fixed left-[50%] top-[50%] z-50 grid w-full max-w-lg translate-x-[-50%] translate-y-[-50%] gap-4 border bg-background p-6 shadow-lg duration-200 data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[state=closed]:slide-out-to-left-1/2 data-[state=closed]:slide-out-to-top-[48%] data-[state=open]:slide-in-from-left-1/2 data-[state=open]:slide-in-from-top-[48%] sm:rounded-lg",
className,
)}
{...props}
>
{children}
<DialogPrimitive.Close className="ring-offset-background focus:ring-ring data-[state=open]:bg-accent data-[state=open]:text-muted-foreground absolute right-4 top-4 rounded-sm opacity-70 transition-opacity hover:opacity-100 focus:outline-none focus:ring-2 focus:ring-offset-2 disabled:pointer-events-none">
<DialogPrimitive.Close className="absolute right-4 top-4 rounded-sm opacity-70 ring-offset-background transition-opacity hover:opacity-100 focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2 disabled:pointer-events-none data-[state=open]:bg-accent data-[state=open]:text-muted-foreground">
<Cross2Icon className="h-4 w-4" />
<span className="sr-only">Close</span>
</DialogPrimitive.Close>
@@ -102,7 +102,7 @@ const DialogDescription = React.forwardRef<
>(({ className, ...props }, ref) => (
<DialogPrimitive.Description
ref={ref}
className={cn("text-muted-foreground text-sm", className)}
className={cn("text-sm text-muted-foreground", className)}
{...props}
/>
));
+1 -1
View File
@@ -1,4 +1,4 @@
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
export function IconAI({ className, ...props }: React.ComponentProps<"svg">) {
return (
@@ -1,5 +1,5 @@
"use client";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
import { animate, motion, useMotionValue } from "framer-motion";
import { useEffect, useState } from "react";
import useMeasure from "react-use-measure";
+2 -2
View File
@@ -1,6 +1,6 @@
import * as React from "react";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
export type InputProps = React.InputHTMLAttributes<HTMLInputElement>;
@@ -10,7 +10,7 @@ const Input = React.forwardRef<HTMLInputElement, InputProps>(
<input
type={type}
className={cn(
"border-input file:text-foreground placeholder:text-muted-foreground focus-visible:ring-ring flex h-9 w-full rounded-md border bg-transparent px-3 py-1 text-sm shadow-sm transition-colors file:border-0 file:bg-transparent file:text-sm file:font-medium focus-visible:outline-none focus-visible:ring-1 disabled:cursor-not-allowed disabled:opacity-50",
"flex h-9 w-full rounded-md border border-input bg-transparent px-3 py-1 text-sm shadow-sm transition-colors file:border-0 file:bg-transparent file:text-sm file:font-medium file:text-foreground placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:cursor-not-allowed disabled:opacity-50",
className,
)}
ref={ref}
+1 -1
View File
@@ -4,7 +4,7 @@ import * as LabelPrimitive from "@radix-ui/react-label";
import { cva, type VariantProps } from "class-variance-authority";
import * as React from "react";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
const labelVariants = cva(
"text-sm font-medium leading-none peer-disabled:cursor-not-allowed peer-disabled:opacity-70",
+2 -2
View File
@@ -1,4 +1,4 @@
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
function Skeleton({
className,
@@ -6,7 +6,7 @@ function Skeleton({
}: React.HTMLAttributes<HTMLDivElement>) {
return (
<div
className={cn("bg-primary/10 animate-pulse rounded-md", className)}
className={cn("animate-pulse rounded-md bg-primary/10", className)}
{...props}
/>
);
+4 -4
View File
@@ -3,7 +3,7 @@
import * as SliderPrimitive from "@radix-ui/react-slider";
import * as React from "react";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
const Slider = React.forwardRef<
React.ElementRef<typeof SliderPrimitive.Root>,
@@ -17,10 +17,10 @@ const Slider = React.forwardRef<
)}
{...props}
>
<SliderPrimitive.Track className="bg-primary/20 relative h-1.5 w-full grow overflow-hidden rounded-full">
<SliderPrimitive.Range className="bg-primary absolute h-full" />
<SliderPrimitive.Track className="relative h-1.5 w-full grow overflow-hidden rounded-full bg-primary/20">
<SliderPrimitive.Range className="absolute h-full bg-primary" />
</SliderPrimitive.Track>
<SliderPrimitive.Thumb className="border-primary/50 bg-background focus-visible:ring-ring block h-4 w-4 rounded-full border shadow transition-colors focus-visible:outline-none focus-visible:ring-1 disabled:pointer-events-none disabled:opacity-50" />
<SliderPrimitive.Thumb className="block h-4 w-4 rounded-full border border-primary/50 bg-background shadow transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:pointer-events-none disabled:opacity-50" />
</SliderPrimitive.Root>
));
Slider.displayName = SliderPrimitive.Root.displayName;
+2 -2
View File
@@ -1,6 +1,6 @@
import * as React from "react";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
export type TextareaProps = React.TextareaHTMLAttributes<HTMLTextAreaElement>;
@@ -9,7 +9,7 @@ const Textarea = React.forwardRef<HTMLTextAreaElement, TextareaProps>(
return (
<textarea
className={cn(
"border-input placeholder:text-muted-foreground focus-visible:ring-ring flex min-h-[60px] w-full rounded-md border bg-transparent px-3 py-2 text-sm shadow-sm focus-visible:outline-none focus-visible:ring-1 disabled:cursor-not-allowed disabled:opacity-50",
"flex min-h-[60px] w-full rounded-md border border-input bg-transparent px-3 py-2 text-sm shadow-sm placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:cursor-not-allowed disabled:opacity-50",
className,
)}
ref={ref}
+2 -2
View File
@@ -3,7 +3,7 @@
import * as TooltipPrimitive from "@radix-ui/react-tooltip";
import * as React from "react";
import { cn } from "@/libs/utils";
import { cn } from "@/lib/utils";
const TooltipProvider = TooltipPrimitive.Provider;
@@ -20,7 +20,7 @@ const TooltipContent = React.forwardRef<
ref={ref}
sideOffset={sideOffset}
className={cn(
"bg-primary text-primary-foreground animate-in fade-in-0 zoom-in-95 data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=closed]:zoom-out-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 z-50 overflow-hidden rounded-md px-3 py-1.5 text-xs",
"z-50 overflow-hidden rounded-md bg-primary px-3 py-1.5 text-xs text-primary-foreground animate-in fade-in-0 zoom-in-95 data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=closed]:zoom-out-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2",
className,
)}
{...props}
@@ -0,0 +1,8 @@
---
title: LlamaCloud
description: LlamaCloud is a new generation of managed parsing, ingestion, and retrieval services, designed to bring production-grade context-augmentation to your LLM and RAG applications.
---
This is TypeScript binding for LlamaCloud API. It provides a simple way to interact with LlamaCloud API.
If you are looking for the official documentation, please visit the [Official Document](https://docs.cloud.llamaindex.ai/)
@@ -0,0 +1,6 @@
{
"title": "LlamaCloud",
"description": "The Cloud framework for LLM",
"root": true,
"pages": ["---Guide---", "index", "api"]
}

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@@ -0,0 +1,12 @@
---
title: Agents
---
A built-in agent that can take decisions and reasoning based on the tools provided to it.
## OpenAI Agent
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../examples/agent/openai";
<DynamicCodeBlock lang="ts" code={CodeSource} />
@@ -0,0 +1,8 @@
---
title: Gemini Agent
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSourceGemini from "!raw-loader!../../../../../../../examples/gemini/agent.ts";
<DynamicCodeBlock lang="ts" code={CodeSourceGemini} />
@@ -0,0 +1,10 @@
---
title: Chat Engine
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../examples/chatEngine";
Chat Engine is a class that allows you to create a chatbot from a retriever. It is a wrapper around a retriever that allows you to chat with it in a conversational manner.
<DynamicCodeBlock lang="ts" code={CodeSource} />
@@ -0,0 +1,61 @@
---
title: Context-Aware Agent
---
The Context-Aware Agent enhances the capabilities of standard LLM agents by incorporating relevant context from a retriever for each query. This allows the agent to provide more informed and specific responses based on the available information.
## Usage
Here's a simple example of how to use the Context-Aware Agent:
```typescript
import {
Document,
VectorStoreIndex,
OpenAIContextAwareAgent,
OpenAI,
} from "llamaindex";
async function createContextAwareAgent() {
// Create and index some documents
const documents = [
new Document({
text: "LlamaIndex is a data framework for LLM applications.",
id_: "doc1",
}),
new Document({
text: "The Eiffel Tower is located in Paris, France.",
id_: "doc2",
}),
];
const index = await VectorStoreIndex.fromDocuments(documents);
const retriever = index.asRetriever({ similarityTopK: 1 });
// Create the Context-Aware Agent
const agent = new OpenAIContextAwareAgent({
llm: new OpenAI({ model: "gpt-3.5-turbo" }),
contextRetriever: retriever,
});
// Use the agent to answer queries
const response = await agent.chat({
message: "What is LlamaIndex used for?",
});
console.log("Agent Response:", response.response);
}
createContextAwareAgent().catch(console.error);
```
In this example, the Context-Aware Agent uses the retriever to fetch relevant context for each query, allowing it to provide more accurate and informed responses based on the indexed documents.
## Key Components
- `contextRetriever`: A retriever (e.g., from a VectorStoreIndex) that fetches relevant documents or passages for each query.
## Available Context-Aware Agents
- `OpenAIContextAwareAgent`: A context-aware agent using OpenAI's models.
- `AnthropicContextAwareAgent`: A context-aware agent using Anthropic's models.
@@ -2,7 +2,7 @@
title: Local LLMs
---
LlamaIndex.TS supports OpenAI and [other remote LLM APIs](/docs/llamaindex/modules/models/llms). You can also run a local LLM on your machine!
LlamaIndex.TS supports OpenAI and [other remote LLM APIs](other_llms). You can also run a local LLM on your machine!
## Using a local model via Ollama
@@ -24,34 +24,17 @@ The first time you run it will also automatically download and install the model
### Switch the LLM in your code
To switch the LLM in your code, you first need to make sure to install the package for the Ollama model provider:
```package-install
npm i @llamaindex/ollama
```
Then, to tell LlamaIndex to use a local LLM, use the `Settings` object:
To tell LlamaIndex to use a local LLM, use the `Settings` object:
```javascript
import { Settings } from "llamaindex";
import { ollama } from "@llamaindex/ollama";
Settings.llm = ollama({
Settings.llm = new Ollama({
model: "mixtral:8x7b",
});
```
### Use local embeddings
If you're doing retrieval-augmented generation, LlamaIndex.TS will also call out to OpenAI to index and embed your data. To be entirely local, you can use a local embedding model from Huggingface like this:
First install the Huggingface model provider package:
```package-install
npm i @llamaindex/huggingface
```
And then set the embedding model in your code:
If you're doing retrieval-augmented generation, LlamaIndex.TS will also call out to OpenAI to index and embed your data. To be entirely local, you can use a local embedding model like this:
```javascript
Settings.embedModel = new HuggingFaceEmbedding({
@@ -0,0 +1,15 @@
{
"title": "Examples",
"pages": [
"more_examples",
"chat_engine",
"vector_index",
"summary_index",
"save_load_index",
"context_aware_agent",
"agent",
"agent_gemini",
"local_llm",
"other_llms"
]
}
@@ -1,33 +1,21 @@
---
title: Code examples
title: See all examples
---
Our GitHub repository has a wealth of examples to explore and try out. You can check out our [examples folder](https://github.com/run-llama/LlamaIndexTS/tree/main/examples) to see them all at once, or browse the pages in this section for some selected highlights.
## Use examples locally
## Check out all examples
It may be useful to check out all the examples at once so you can try them out locally. To do this into a folder called `my-new-project`, run these commands:
```bash npm2yarn
npx degit run-llama/LlamaIndexTS/examples my-new-project
cd my-new-project
npm i
npm install
```
Then you can run any example in the folder with `tsx`, e.g.:
```bash npm2yarn
export OPENAI_API_KEY=your-api-key
npx tsx ./agents/agent/openai.ts
npx tsx ./vectorIndex.ts
```
## Try examples online
You can also try the examples online using StackBlitz:
<iframe
className="w-full h-[440px]"
aria-label="LlamaIndex.TS Examples"
aria-description="This is a list of examples for LlamaIndex.TS."
src="https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples?file=README.md"
/>
@@ -0,0 +1,43 @@
---
title: Using other LLM APIs
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../examples/mistral";
By default LlamaIndex.TS uses OpenAI's LLMs and embedding models, but we support [lots of other LLMs](../modules/llms) including models from Mistral (Mistral, Mixtral), Anthropic (Claude) and Google (Gemini).
If you don't want to use an API at all you can [run a local model](../../examples/local_llm)
## Using another LLM
You can specify what LLM LlamaIndex.TS will use on the `Settings` object, like this:
```typescript
import { MistralAI, Settings } from "llamaindex";
Settings.llm = new MistralAI({
model: "mistral-tiny",
apiKey: "<YOUR_API_KEY>",
});
```
You can see examples of other APIs we support by checking out "Available LLMs" in the sidebar of our [LLMs section](../modules/llms).
## Using another embedding model
A frequent gotcha when trying to use a different API as your LLM is that LlamaIndex will also by default index and embed your data using OpenAI's embeddings. To completely switch away from OpenAI you will need to set your embedding model as well, for example:
```typescript
import { MistralAIEmbedding, Settings } from "llamaindex";
Settings.embedModel = new MistralAIEmbedding();
```
We support [many different embeddings](../modules/embeddings).
## Full example
This example uses Mistral's `mistral-tiny` model as the LLM and Mistral for embeddings as well.
<DynamicCodeBlock lang="ts" code={CodeSource} />
@@ -0,0 +1,8 @@
---
title: Save/Load an Index
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../examples/storageContext";
<DynamicCodeBlock lang="ts" code={CodeSource} />
@@ -0,0 +1,8 @@
---
title: Summary Index
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../examples/summaryIndex";
<DynamicCodeBlock lang="ts" code={CodeSource} />
@@ -0,0 +1,8 @@
---
title: Vector Index
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../examples/vectorIndex";
<DynamicCodeBlock lang="ts" code={CodeSource} />
@@ -1,60 +1,76 @@
---
title: High-Level Concepts
title: Concepts
---
This is a quick guide to the high-level concepts you'll encounter frequently when building LLM applications.
LlamaIndex.TS helps you build LLM-powered applications (e.g. Q&A, chatbot) over custom data.
## Large Language Models (LLMs)
In this high-level concepts guide, you will learn:
LLMs are the fundamental innovation that launched LlamaIndex. They are an artificial intelligence (AI) computer system that can understand, generate, and manipulate natural language, including answering questions based on their training data or data provided to them at query time.
- how an LLM can answer questions using your own data.
- key concepts and modules in LlamaIndex.TS for composing your own query pipeline.
## Agentic Applications
## Answering Questions Across Your Data
When an LLM is used within an application, it is often used to make decisions, take actions, and/or interact with the world. This is the core definition of an **agentic application**.
LlamaIndex uses a two stage method when using an LLM with your data:
While the definition of an agentic application is broad, there are several key characteristics that define an agentic application:
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
- **LLM Augmentation**: The LLM is augmented with tools (i.e. arbitrary callable functions in code), memory, and/or dynamic prompts.
- **Prompt Chaining**: Several LLM calls are used that build on each other, with the output of one LLM call being used as the input to the next.
- **Routing**: The LLM is used to route the application to the next appropriate step or state in the application.
- **Parallelism**: The application can perform multiple steps or actions in parallel.
- **Orchestration**: A hierarchical structure of LLMs is used to orchestrate lower-level actions and LLMs.
- **Reflection**: The LLM is used to reflect and validate outputs of previous steps or LLM calls, which can be used to guide the application to the next appropriate step or state.
![](../_static/concepts/rag.jpg)
In LlamaIndex, you can build agentic applications by using the workflows to orchestrate a sequence of steps and LLMs. You can [learn more about workflows](/docs/llamaindex/tutorials/workflows).
This process is also known as Retrieval Augmented Generation (RAG).
## Agents
LlamaIndex.TS provides the essential toolkit for making both steps super easy.
We define an agent as a specific instance of an "agentic application". An agent is a piece of software that semi-autonomously performs tasks by combining LLMs with other tools and memory, orchestrated in a reasoning loop that decides which tool to use next (if any).
Let's explore each stage in detail.
What this means in practice, is something like:
- An agent receives a user message
- The agent uses an LLM to determine the next appropriate action to take using the previous chat history, tools, and the latest user message
- The agent may invoke one or more tools to assist in the users request
- If tools are used, the agent will then interpret the tool outputs and use them to inform the next action
- Once the agent stops taking actions, it returns the final output to the user
### Indexing Stage
You can [learn more about agents](/docs/llamaindex/tutorials/basic_agent).
LlamaIndex.TS help you prepare the knowledge base with a suite of data connectors and indexes.
## Retrieval Augmented Generation (RAG)
![](../_static/concepts/indexing.jpg)
Retrieval-Augmented Generation (RAG) is a core technique for building data-backed LLM applications with LlamaIndex. It allows LLMs to answer questions about your private data by providing it to the LLM at query time, rather than training the LLM on your data. To avoid sending **all** of your data to the LLM every time, RAG indexes your data and selectively sends only the relevant parts along with your query. You can [learn more about RAG](/docs/llamaindex/tutorials/rag).
[**Data Loaders**](/docs/llamaindex/modules/data_loaders/index):
A data connector (i.e. `Reader`) ingest data from different data sources and data formats into a simple `Document` representation (text and simple metadata).
## Use cases
[**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.
There are endless use cases for data-backed LLM applications but they can be roughly grouped into four categories:
[**Data Indexes**](/docs/llamaindex/modules/data_index):
Once you've ingested your data, LlamaIndex helps you index data into a format that's easy to retrieve.
[**Agents**](/docs/llamaindex/tutorials/basic_agent):
An agent is an automated decision-maker powered by an LLM that interacts with the world via a set of [tools](/docs/llamaindex/modules/agents/tool). Agents can take an arbitrary number of steps to complete a given task, dynamically deciding on the best course of action rather than following pre-determined steps. This gives it additional flexibility to tackle more complex tasks.
Under the hood, LlamaIndex parses the raw documents into intermediate representations, calculates vector embeddings, and stores your data in-memory or to disk.
[**Workflows**](/docs/llamaindex/tutorials/workflows):
A Workflow in LlamaIndex is a specific event-driven abstraction that allows you to orchestrate a sequence of steps and LLMs calls. Workflows can be used to implement any agentic application, and are a core component of LlamaIndex.
### Querying Stage
[**Structured Data Extraction**](/docs/llamaindex/tutorials/structured_data_extraction):
Pydantic extractors allow you to specify a precise data structure to extract from your data and use LLMs to fill in the missing pieces in a type-safe way. This is useful for extracting structured data from unstructured sources like PDFs, websites, and more, and is key to automating workflows.
In the querying stage, the query pipeline retrieves the most relevant context given a user query,
and pass that to the LLM (along with the query) to synthesize a response.
[**Query Engines**](/docs/llamaindex/modules/rag/query_engines):
A query engine is an end-to-end flow that allows you to ask questions over your data. It takes in a natural language query, and returns a response, along with reference context retrieved and passed to the LLM.
This gives the LLM up-to-date knowledge that is not in its original training data,
(also reducing hallucination).
[**Chat Engines**](/docs/llamaindex/modules/rag/chat_engine):
A chat engine is an end-to-end flow for having a conversation with your data (multiple back-and-forth instead of a single question-and-answer).
The key challenge in the querying stage is retrieval, orchestration, and reasoning over (potentially many) knowledge bases.
LlamaIndex provides composable modules that help you build and integrate RAG pipelines for Q&A (query engine), chatbot (chat engine), or as part of an agent.
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)
#### Building Blocks
[**Retrievers**](/docs/llamaindex/modules/retriever):
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.
[**Response Synthesizers**](/docs/llamaindex/modules/response_synthesizer):
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):
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):
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).
@@ -0,0 +1,35 @@
---
title: Installation
description: Install llamaindex by running a single command.
---
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex
```
```shell tab="yarn"
yarn add llamaindex
```
```shell tab="pnpm"
pnpm add llamaindex
```
</Tabs>
## What's next?
<Cards>
<Card
title="I want to try LlamaIndex.TS"
description="Learn how to use LlamaIndex.TS with different JS runtime and frameworks."
href="/docs/llamaindex/getting_started/setup"
/>
<Card
title="Show me code examples"
description="Explore code examples using LlamaIndex.TS."
href="https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples?file=README.md"
/>
</Cards>
@@ -1,177 +0,0 @@
---
title: Installation
description: How to install and set up LlamaIndex.TS for your project.
---
## Quick Start
Install the core package:
```package-install
npm i llamaindex
```
In most cases, you'll also need an LLM provider and the Workflow package:
```package-install
npm i @llamaindex/openai @llamaindex/workflow
```
## Environment Setup
### API Keys
Most LLM providers require API keys. Set your OpenAI key (or other provider):
```bash
export OPENAI_API_KEY=your-api-key
```
Or use a `.env` file:
```bash
echo "OPENAI_API_KEY=your-api-key" > .env
```
<Callout type="warn">Never commit API keys to your repository.</Callout>
### Loading Environment Variables
For Node.js applications:
```bash
node --env-file .env your-script.js
```
For other environments, see the deployment-specific guides below.
## TypeScript Configuration
LlamaIndex.TS is built with TypeScript and provides excellent type safety. Add these settings to your `tsconfig.json`:
```json5
{
"compilerOptions": {
// Essential for module resolution
"moduleResolution": "bundler", // or "nodenext" | "node16" | "node"
// Required for Web Stream API support
"lib": ["DOM.AsyncIterable"],
// Recommended for better compatibility
"target": "es2020",
"module": "esnext"
}
}
```
## Running your first agent
### Set up
If you don't already have a project, you can create a new one in a new folder:
```package-install
npm init
npm i -D typescript @types/node
npm i @llamaindex/openai @llamaindex/workflow llamaindex zod
```
### Run the agent
Create the file `example.ts`. This code will:
- Create two tools for use by the agent:
- A `sumNumbers` tool that adds two numbers
- A `divideNumbers` tool that divides numbers
- Give an example of the data structure we wish to generate
- Prompt the LLM with instructions and the example, plus a sample transcript
<include cwd>../../examples/agents/agent/openai.ts</include>
To run the code:
```package-install
npx tsx example.ts
```
You should expect output something like:
```
{
result: '5 + 5 is 10. Then, 10 divided by 2 is 5.',
state: {
memory: Memory {
messages: [Array],
tokenLimit: 30000,
shortTermTokenLimitRatio: 0.7,
memoryBlocks: [],
memoryCursor: 0,
adapters: [Object]
},
scratchpad: [],
currentAgentName: 'Agent',
agents: [ 'Agent' ],
nextAgentName: null
}
}
Done
```
## Performance Optimization
### Tokenization Speed
Install `gpt-tokenizer` for 60x faster tokenization (Node.js environments only):
```package-install
npm i gpt-tokenizer
```
LlamaIndex will automatically use this when available.
## Deployment Guides
Choose your deployment target:
<Cards>
<Card
title="Server APIs & Backends"
description="Express, Fastify, Koa, standalone Node.js servers"
href="/docs/llamaindex/getting_started/installation/server-apis"
/>
<Card
title="Serverless Functions"
description="Vercel, Netlify, AWS Lambda, Cloudflare Workers"
href="/docs/llamaindex/getting_started/installation/serverless"
/>
<Card
title="Next.js Applications"
description="API routes, server components, edge runtime"
href="/docs/llamaindex/getting_started/installation/nextjs"
/>
<Card
title="Troubleshooting"
description="Common issues, bundle optimization, compatibility"
href="/docs/llamaindex/getting_started/installation/troubleshooting"
/>
</Cards>
## LLM/Embedding Providers
Go to [LLM APIs](/docs/llamaindex/modules/models/llms) and [Embedding APIs](/docs/llamaindex/modules/models/embeddings) to find out how to use different LLM and embedding providers beyond OpenAI.
## What's Next?
<Cards>
<Card
title="Learn LlamaIndex.TS"
description="Learn how to use LlamaIndex.TS by starting with one of our tutorials."
href="/docs/llamaindex/tutorials/basic_agent"
/>
<Card
title="Show me code examples"
description="Explore code examples using LlamaIndex.TS."
href="/docs/llamaindex/getting_started/examples"
/>
</Cards>
@@ -1,4 +0,0 @@
{
"title": "Installation",
"pages": ["server-apis", "serverless", "nextjs", "troubleshooting"]
}
@@ -1,405 +0,0 @@
---
title: Next.js Applications
description: Deploy LlamaIndex.TS in Next.js applications with API routes, server components, and edge runtime.
---
This guide covers integrating LlamaIndex.TS agents with Next.js applications.
## Essential Configuration
### Next.js Config
Use `withLlamaIndex` to ensure compatibility:
```javascript
// next.config.mjs
import withLlamaIndex from "llamaindex/next";
/** @type {import('next').NextConfig} */
const nextConfig = {
// Your existing config
};
export default withLlamaIndex(nextConfig);
```
## API Routes
### App Router (Recommended)
```typescript
// app/api/chat/route.ts
import { agent } from "@llamaindex/workflow";
import { tool } from "llamaindex";
import { openai } from "@llamaindex/openai";
import { z } from "zod";
import { NextRequest, NextResponse } from "next/server";
// Initialize agent once (consider using a singleton pattern)
let myAgent: any = null;
async function initializeAgent() {
if (myAgent) return myAgent;
try {
const greetTool = tool({
name: "greet",
description: "Greets a user with their name",
parameters: z.object({
name: z.string(),
}),
execute: ({ name }) => `Hello, ${name}! How can I help you today?`,
});
myAgent = agent({
tools: [greetTool],
llm: openai({ model: "gpt-4o-mini" }),
});
return myAgent;
} catch (error) {
console.error("Failed to initialize agent:", error);
throw error;
}
}
export async function POST(request: NextRequest) {
try {
const { message } = await request.json();
if (!message || typeof message !== 'string') {
return NextResponse.json(
{ error: "Message is required and must be a string" },
{ status: 400 }
);
}
const agent = await initializeAgent();
const result = await agent.run(message);
return NextResponse.json({ response: result.data });
} catch (error) {
console.error("Chat error:", error);
return NextResponse.json(
{ error: "Internal server error" },
{ status: 500 }
);
}
}
```
### Pages Router (Legacy)
```typescript
// pages/api/chat.ts
import { agent } from "@llamaindex/workflow";
import { tool } from "llamaindex";
import { openai } from "@llamaindex/openai";
import { z } from "zod";
import type { NextApiRequest, NextApiResponse } from "next";
let myAgent: any = null;
async function initializeAgent() {
if (myAgent) return myAgent;
const timeTool = tool({
name: "getCurrentTime",
description: "Gets the current time",
parameters: z.object({}),
execute: () => new Date().toISOString(),
});
myAgent = agent({
tools: [timeTool],
llm: openai({ model: "gpt-4o-mini" }),
});
return myAgent;
}
export default async function handler(
req: NextApiRequest,
res: NextApiResponse
) {
if (req.method !== "POST") {
return res.status(405).json({ error: "Method not allowed" });
}
try {
const { message } = req.body;
const agent = await initializeAgent();
const result = await agent.run(message);
res.json({ response: result.data });
} catch (error) {
console.error("Chat error:", error);
res.status(500).json({ error: "Internal server error" });
}
}
```
## Server Components
Initialize agents in server components:
```typescript
// app/chat/page.tsx
import { agent } from "@llamaindex/workflow";
import { tool } from "llamaindex";
import { openai } from "@llamaindex/openai";
import { z } from "zod";
async function initializeAgent() {
const helpTool = tool({
name: "getHelp",
description: "Provides help information",
parameters: z.object({
topic: z.string().optional(),
}),
execute: ({ topic }) => {
if (topic) {
return `Here's help for ${topic}: This is a helpful resource about ${topic}.`;
}
return "Available topics: general, troubleshooting, api, deployment";
},
});
return agent({
tools: [helpTool],
llm: openai({ model: "gpt-4o-mini" }),
});
}
export default async function ChatPage() {
const chatAgent = await initializeAgent();
return (
<div>
<h1>Chat Interface</h1>
<p>Agent initialized and ready to help!</p>
{/* Your chat UI components */}
</div>
);
}
```
## Edge Runtime
The Edge Runtime has limited Node.js API access:
```typescript
// app/api/chat-edge/route.ts
import { NextRequest, NextResponse } from "next/server";
export const runtime = "edge";
export async function POST(request: NextRequest) {
const { setEnvs } = await import("@llamaindex/env");
setEnvs(process.env);
try {
const { message } = await request.json();
const { agent } = await import("@llamaindex/workflow");
const { tool } = await import("llamaindex");
const { openai } = await import("@llamaindex/openai");
const { z } = await import("zod");
const timeTool = tool({
name: "time",
description: "Gets current time",
parameters: z.object({}),
execute: () => new Date().toISOString(),
});
const myAgent = agent({
tools: [timeTool],
llm: openai({ model: "gpt-4o-mini" }),
});
const result = await myAgent.run(message);
return NextResponse.json({ response: result.data });
} catch (error) {
return NextResponse.json({ error: error.message }, { status: 500 });
}
}
```
## Streaming Responses
Implement streaming for better user experience:
```typescript
// app/api/chat-stream/route.ts
import { agent } from "@llamaindex/workflow";
import { tool } from "llamaindex";
import { openai } from "@llamaindex/openai";
import { agentStreamEvent } from "@llamaindex/workflow";
import { NextRequest } from "next/server";
import { z } from "zod";
// Initialize agent once (consider using a singleton pattern)
let myAgent: any = null;
async function initializeAgent() {
if (myAgent) return myAgent;
try {
const greetTool = tool({
name: "greet",
description: "Greets a user with their name",
parameters: z.object({
name: z.string(),
}),
execute: ({ name }) => `Hello, ${name}! How can I help you today?`,
});
myAgent = agent({
tools: [greetTool],
llm: openai({ model: "gpt-4o-mini" }),
});
return myAgent;
} catch (error) {
console.error("Failed to initialize agent:", error);
throw error;
}
}
export async function POST(request: NextRequest) {
const { message } = await request.json();
const stream = new ReadableStream({
async start(controller) {
try {
const agent = await initializeAgent();
const events = agent.runStream(message);
for await (const event of events) {
if (agentStreamEvent.include(event)) {
controller.enqueue(new TextEncoder().encode(event.data.delta));
}
}
controller.close();
} catch (error) {
controller.error(error);
}
},
});
return new Response(stream, {
headers: {
"Content-Type": "text/plain",
"Transfer-Encoding": "chunked",
},
});
}
```
## Client-side Integration
### React Hook for API Calls
```typescript
// hooks/useAgentChat.ts
import { useState } from "react";
export function useAgentChat() {
const [loading, setLoading] = useState(false);
const [error, setError] = useState<string | null>(null);
const [response, setResponse] = useState<string | null>(null);
const chat = async (message: string) => {
setLoading(true);
setError(null);
try {
const res = await fetch("/api/chat", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ message }),
});
if (!res.ok) {
throw new Error(`HTTP error! status: ${res.status}`);
}
const data = await res.json();
setResponse(data.response);
} catch (err) {
setError(err instanceof Error ? err.message : "An error occurred");
} finally {
setLoading(false);
}
};
return { chat, loading, error, response };
}
```
### Chat Component
```typescript
// components/ChatInterface.tsx
"use client";
import { useState } from "react";
import { useAgentChat } from "@/hooks/useAgentChat";
export default function ChatInterface() {
const [message, setMessage] = useState("");
const { chat, loading, error, response } = useAgentChat();
const handleSubmit = async (e: React.FormEvent) => {
e.preventDefault();
if (!message.trim()) return;
await chat(message);
setMessage("");
};
return (
<div className="max-w-2xl mx-auto p-4">
<form onSubmit={handleSubmit} className="mb-4">
<input
type="text"
value={message}
onChange={(e) => setMessage(e.target.value)}
placeholder="Send a message..."
className="w-full p-2 border rounded"
disabled={loading}
/>
<button
type="submit"
disabled={loading || !message.trim()}
className="mt-2 px-4 py-2 bg-blue-500 text-white rounded disabled:opacity-50"
>
{loading ? "Thinking..." : "Send"}
</button>
</form>
{error && (
<div className="p-3 mb-4 bg-red-100 border border-red-400 text-red-700 rounded">
Error: {error}
</div>
)}
{response && (
<div className="p-3 bg-gray-100 border rounded">
<strong>Agent:</strong>
<p>{response}</p>
</div>
)}
</div>
);
}
```
## Next Steps
- Learn about [serverless deployment](/docs/llamaindex/getting_started/installation/serverless)
- Explore [server APIs](/docs/llamaindex/getting_started/installation/server-apis)
- Check [troubleshooting guide](/docs/llamaindex/getting_started/installation/troubleshooting) for common issues
@@ -1,211 +0,0 @@
---
title: Server APIs & Backends
description: Deploy LlamaIndex.TS in server environments like Express, Fastify, and standalone Node.js applications.
---
This guide covers adding LlamaIndex.TS agents to traditional server environments where you have full Node.js runtime access.
## Supported Runtimes
LlamaIndex.TS works seamlessly with:
- **Node.js** (v18+)
- **Bun** (v1.0+)
- **Deno** (v1.30+)
## Common Server Frameworks
### Express.js
```typescript
import express from 'express';
import { agent } from '@llamaindex/workflow';
import { tool } from 'llamaindex';
import { openai } from '@llamaindex/openai';
import { z } from 'zod';
const app = express();
app.use(express.json());
// Initialize agent once at startup
let myAgent: any;
async function initializeAgent() {
// Create tools for the agent
const sumTool = tool({
name: "sum",
description: "Adds two numbers",
parameters: z.object({
a: z.number(),
b: z.number(),
}),
execute: ({ a, b }) => a + b,
});
const multiplyTool = tool({
name: "multiply",
description: "Multiplies two numbers",
parameters: z.object({
a: z.number(),
b: z.number(),
}),
execute: ({ a, b }) => a * b,
});
// Create the agent
myAgent = agent({
tools: [sumTool, multiplyTool],
llm: openai({ model: "gpt-4o-mini" }),
});
}
app.post('/api/chat', async (req, res) => {
try {
const { message } = req.body;
const result = await myAgent.run(message);
res.json({ response: result.data });
} catch (error) {
res.status(500).json({ error: 'Chat failed' });
}
});
// Initialize and start server
initializeAgent().then(() => {
app.listen(3000, () => {
console.log('Server running on port 3000');
});
});
```
### Fastify
```typescript
import Fastify from 'fastify';
import { agent } from '@llamaindex/workflow';
import { tool } from 'llamaindex';
import { openai } from '@llamaindex/openai';
import { z } from 'zod';
const fastify = Fastify();
let myAgent: any;
async function initializeAgent() {
const sumTool = tool({
name: "sum",
description: "Adds two numbers",
parameters: z.object({
a: z.number(),
b: z.number(),
}),
execute: ({ a, b }) => a + b,
});
myAgent = agent({
tools: [sumTool],
llm: openai({ model: "gpt-4o-mini" }),
});
}
fastify.post('/api/chat', async (request, reply) => {
try {
const { message } = request.body as { message: string };
const result = await myAgent.run(message);
return { response: result.data };
} catch (error) {
reply.status(500).send({ error: 'Chat failed' });
}
});
const start = async () => {
await initializeAgent();
await fastify.listen({ port: 3000 });
console.log('Server running on port 3000');
};
start();
```
### Hono
```typescript
import { Hono } from "hono";
import { agent } from "@llamaindex/workflow";
import { tool } from "llamaindex";
import { openai } from "@llamaindex/openai";
import { z } from "zod";
type Bindings = {
OPENAI_API_KEY: string;
};
const app = new Hono<{ Bindings: Bindings }>();
app.post("/api/chat", async (c) => {
const { setEnvs } = await import("@llamaindex/env");
setEnvs(c.env);
const { message } = await c.req.json();
const greetTool = tool({
name: "greet",
description: "Greets a user",
parameters: z.object({
name: z.string(),
}),
execute: ({ name }) => `Hello, ${name}!`,
});
const myAgent = agent({
tools: [greetTool],
llm: openai({ model: "gpt-4o-mini" }),
});
try {
const result = await myAgent.run(message);
return c.json({ response: result.data });
} catch (error) {
return c.json({ error: error.message }, 500);
}
});
export default app;
```
## Streaming Responses
For real-time agent responses:
```typescript
import { agentStreamEvent } from "@llamaindex/workflow";
app.post('/api/chat-stream', async (req, res) => {
const { message } = req.body;
res.writeHead(200, {
'Content-Type': 'text/plain',
'Transfer-Encoding': 'chunked',
});
try {
const events = myAgent.runStream(message);
for await (const event of events) {
if (agentStreamEvent.include(event)) {
res.write(event.data.delta);
}
}
res.end();
} catch (error) {
res.write('Error: ' + error.message);
res.end();
}
});
```
## Next Steps
- Learn about [serverless deployment](/docs/llamaindex/getting_started/installation/serverless)
- Explore [Next.js integration](/docs/llamaindex/getting_started/installation/nextjs)
- Check [troubleshooting guide](/docs/llamaindex/getting_started/installation/troubleshooting) for common issues
@@ -1,240 +0,0 @@
---
title: Serverless Functions
description: Deploy LlamaIndex.TS in serverless environments like Vercel, Netlify, AWS Lambda, and Cloudflare Workers.
---
This guide covers adding LlamaIndex.TS agents to serverless environments where you have execution time and memory constraints.
## Cloudflare Workers
```typescript
export default {
async fetch(request: Request, env: Env): Promise<Response> {
const { setEnvs } = await import("@llamaindex/env");
setEnvs(env);
const { agent } = await import("@llamaindex/workflow");
const { openai } = await import("@llamaindex/openai");
const { tool } = await import("llamaindex");
const { z } = await import("zod");
const timeTool = tool({
name: "getCurrentTime",
description: "Gets the current time",
parameters: z.object({}),
execute: () => new Date().toISOString(),
});
const myAgent = agent({
tools: [timeTool],
llm: openai({ model: "gpt-4o-mini" }),
});
try {
const { message } = await request.json();
const result = await myAgent.run(message);
return new Response(JSON.stringify({ response: result.data }), {
headers: { "Content-Type": "application/json" },
});
} catch (error) {
return new Response(JSON.stringify({ error: error.message }), {
status: 500,
headers: { "Content-Type": "application/json" },
});
}
},
};
```
## Vercel Functions
### Node.js Runtime
```typescript
// pages/api/chat.ts or app/api/chat/route.ts
import { agent } from "@llamaindex/workflow";
import { tool } from "llamaindex";
import { openai } from "@llamaindex/openai";
import { z } from "zod";
export default async function handler(req, res) {
if (req.method !== 'POST') {
return res.status(405).json({ error: 'Method not allowed' });
}
const { message } = req.body;
const weatherTool = tool({
name: "getWeather",
description: "Get weather information",
parameters: z.object({
city: z.string(),
}),
execute: ({ city }) => `Weather in ${city}: 72°F, sunny`,
});
const myAgent = agent({
tools: [weatherTool],
llm: openai({ model: "gpt-4o-mini" }),
});
try {
const result = await myAgent.run(message);
res.json({ response: result.data });
} catch (error) {
res.status(500).json({ error: error.message });
}
}
```
### Edge Runtime
```typescript
// app/api/chat/route.ts
import { NextRequest, NextResponse } from "next/server";
export const runtime = "edge";
export async function POST(request: NextRequest) {
const { setEnvs } = await import("@llamaindex/env");
setEnvs(process.env);
const { message } = await request.json();
try {
// Use simpler tools for edge runtime
const { agent } = await import("@llamaindex/workflow");
const { tool } = await import("llamaindex");
const { openai } = await import("@llamaindex/openai");
const { z } = await import("zod");
const timeTool = tool({
name: "time",
description: "Gets current time",
parameters: z.object({}),
execute: () => new Date().toISOString(),
});
const myAgent = agent({
tools: [timeTool],
llm: openai({ model: "gpt-4o-mini" }),
});
const result = await myAgent.run(message);
return NextResponse.json({ response: result.data });
} catch (error) {
return NextResponse.json({ error: error.message }, { status: 500 });
}
}
```
## AWS Lambda
```typescript
import { APIGatewayProxyHandler } from "aws-lambda";
import { agent } from "@llamaindex/workflow";
import { tool } from "llamaindex";
import { openai } from "@llamaindex/openai";
import { z } from "zod";
export const handler: APIGatewayProxyHandler = async (event, context) => {
const { message } = JSON.parse(event.body || "{}");
const calculatorTool = tool({
name: "calculate",
description: "Performs basic math",
parameters: z.object({
expression: z.string(),
}),
execute: ({ expression }) => {
// Simple calculator implementation
try {
return `Result: ${eval(expression)}`;
} catch {
return "Invalid expression";
}
},
});
const myAgent = agent({
tools: [calculatorTool],
llm: openai({ model: "gpt-4o-mini" }),
});
try {
const result = await myAgent.run(message);
return {
statusCode: 200,
headers: {
"Content-Type": "application/json",
"Access-Control-Allow-Origin": "*",
},
body: JSON.stringify({ response: result.data }),
};
} catch (error) {
return {
statusCode: 500,
body: JSON.stringify({ error: error.message }),
};
}
};
```
## Netlify Functions
```typescript
// netlify/functions/chat.ts
import { Handler } from "@netlify/functions";
import { agent } from "@llamaindex/workflow";
import { tool } from "llamaindex";
import { openai } from "@llamaindex/openai";
import { z } from "zod";
export const handler: Handler = async (event, context) => {
if (event.httpMethod !== "POST") {
return { statusCode: 405, body: "Method Not Allowed" };
}
const { message } = JSON.parse(event.body || "{}");
const helpTool = tool({
name: "help",
description: "Provides help information",
parameters: z.object({
topic: z.string().optional(),
}),
execute: ({ topic }) => {
return topic ? `Help for ${topic}` : "Available help topics";
},
});
const myAgent = agent({
tools: [helpTool],
llm: openai({ model: "gpt-4o-mini" }),
});
try {
const result = await myAgent.run(message);
return {
statusCode: 200,
body: JSON.stringify({ response: result.data }),
};
} catch (error) {
return {
statusCode: 500,
body: JSON.stringify({ error: error.message }),
};
}
};
```
## Next Steps
- Learn about [Next.js integration](/docs/llamaindex/getting_started/installation/nextjs)
- Explore [server deployment](/docs/llamaindex/getting_started/installation/server-apis)
- Check [troubleshooting guide](/docs/llamaindex/getting_started/installation/troubleshooting) for common issues
@@ -1,501 +0,0 @@
---
title: Troubleshooting
description: Common issues and solutions when installing and deploying LlamaIndex.TS applications.
---
This guide addresses common issues you might encounter when installing and deploying LlamaIndex.TS applications across different environments.
## Installation Issues
### Module Resolution Errors
**Problem:** Import errors or module not found errors
**Solution:** Ensure your `tsconfig.json` is properly configured:
```json5
{
"compilerOptions": {
"moduleResolution": "bundler", // or "nodenext" | "node16" | "node"
"lib": ["DOM.AsyncIterable"],
"target": "es2020",
"module": "esnext"
}
}
```
**Alternative solution:** Try different module resolution strategies:
```bash
# Clear node_modules and reinstall
rm -rf node_modules package-lock.json
npm install
# Or try with different package manager
pnpm install
# or
yarn install
```
### TypeScript Errors
**Problem:** TypeScript compilation errors with LlamaIndex imports
**Solution:** Ensure you have the correct TypeScript configuration:
```json5
{
"compilerOptions": {
"strict": true,
"skipLibCheck": true, // Skip type checking of node_modules
"allowSyntheticDefaultImports": true,
"esModuleInterop": true
}
}
```
### Package Compatibility Issues
**Problem:** Some packages don't work in certain environments
**Common incompatibilities:**
- `@llamaindex/readers` - May not work in serverless environments
- `@llamaindex/huggingface` - Limited browser/edge compatibility
- File system readers - Don't work in browser/edge environments
**Solution:** Use environment-specific alternatives:
```typescript
// Instead of file system readers in serverless
// Use remote data sources
async function loadDocumentsFromAPI() {
const response = await fetch('https://api.example.com/documents');
const data = await response.json();
return data.map(doc => new Document(doc.content));
}
```
## Runtime Issues
### Memory Errors
**Problem:** Out of memory errors during index creation or querying
**Solution:** Optimize memory usage:
```typescript
// Batch process large document sets
async function batchProcessDocuments(documents: Document[], batchSize = 10) {
const results = [];
for (let i = 0; i < documents.length; i += batchSize) {
const batch = documents.slice(i, i + batchSize);
const batchIndex = await VectorStoreIndex.fromDocuments(batch);
results.push(batchIndex);
// Optional: Add delay between batches
await new Promise(resolve => setTimeout(resolve, 100));
}
return results;
}
```
**For serverless environments:**
```typescript
// Use external vector stores instead of in-memory
// TODO: Example with Pinecone, Weaviate, etc.
// const vectorStore = new PineconeVectorStore(/* config */);
// const index = await VectorStoreIndex.fromVectorStore(vectorStore);
```
### API Rate Limiting
**Problem:** Rate limiting errors from LLM providers
**Solution:** Implement retry logic with exponential backoff:
```typescript
async function queryWithRetry(queryEngine: any, question: string, maxRetries = 3) {
for (let i = 0; i < maxRetries; i++) {
try {
return await queryEngine.query(question);
} catch (error) {
if (error.message.includes('rate limit') && i < maxRetries - 1) {
const delay = Math.pow(2, i) * 1000; // Exponential backoff
await new Promise(resolve => setTimeout(resolve, delay));
continue;
}
throw error;
}
}
}
```
### Tokenization Performance
**Problem:** Slow tokenization affecting performance
**Solution:** Install faster tokenizer (Node.js only):
```bash
npm install gpt-tokenizer
```
LlamaIndex will automatically use this for 60x faster tokenization.
## Bundling Issues
### Bundle Size Too Large
**Problem:** Large bundle sizes affecting performance
**Solution:** Use dynamic imports and code splitting:
```typescript
// Lazy load LlamaIndex components
const initializeLlamaIndex = async () => {
const { VectorStoreIndex, SimpleDirectoryReader } = await import("llamaindex");
return { VectorStoreIndex, SimpleDirectoryReader };
};
// In your API route
export async function POST(request: NextRequest) {
const { VectorStoreIndex, SimpleDirectoryReader } = await initializeLlamaIndex();
// Use the imported modules
}
```
### Webpack/Vite Bundling Issues
**Problem:** Bundler compatibility issues
**Solution for Next.js:**
```javascript
// next.config.mjs
import withLlamaIndex from "llamaindex/next";
const nextConfig = {
webpack: (config, { isServer }) => {
// Custom webpack configuration if needed
if (!isServer) {
config.resolve.fallback = {
...config.resolve.fallback,
fs: false,
net: false,
tls: false,
};
}
return config;
},
};
export default withLlamaIndex(nextConfig);
```
**Solution for Vite:**
```typescript
// vite.config.ts
import { defineConfig } from 'vite';
export default defineConfig({
define: {
global: 'globalThis',
},
resolve: {
alias: {
// Add aliases for problematic modules
},
},
optimizeDeps: {
include: ['llamaindex'],
},
});
```
## Environment-Specific Issues
### Node.js Version Compatibility
**Problem:** Node.js version compatibility issues
**Solution:** Use supported Node.js versions:
```json
{
"engines": {
"node": ">=18.0.0"
}
}
```
**Check your Node.js version:**
```bash
node --version
```
### Cloudflare Workers Issues
**Problem:** Module not available in Cloudflare Workers
**Solution:** Use `@llamaindex/env` for environment compatibility:
```typescript
export default {
async fetch(request: Request, env: Env): Promise<Response> {
const { setEnvs } = await import("@llamaindex/env");
setEnvs(env);
// Your LlamaIndex code here
},
};
```
### Vercel Edge Runtime Issues
**Problem:** Limited Node.js API access in Edge Runtime
**Solution:** Use standard runtime or adapt code:
```typescript
// Force standard runtime
export const runtime = "nodejs";
// Or adapt for edge
export const runtime = "edge";
export async function POST(request: NextRequest) {
// Use edge-compatible code only
const { setEnvs } = await import("@llamaindex/env");
setEnvs(process.env);
// Avoid file system operations
// Use remote data sources
}
```
## Performance Issues
### Slow Query Responses
**Problem:** Slow query performance
**Solution:** Implement caching and optimization:
```typescript
import { LRUCache } from 'lru-cache';
const queryCache = new LRUCache<string, string>({
max: 100,
ttl: 1000 * 60 * 10, // 10 minutes
});
export async function optimizedQuery(question: string, queryEngine: any) {
// Check cache first
const cached = queryCache.get(question);
if (cached) return cached;
// Query and cache result
const result = await queryEngine.query(question);
queryCache.set(question, result);
return result;
}
```
### Cold Start Issues
**Problem:** Slow cold starts in serverless environments
**Solution:** Pre-warm your functions:
```typescript
// Pre-initialize outside handler
let cachedQueryEngine: any = null;
export async function handler(event: any) {
if (!cachedQueryEngine) {
cachedQueryEngine = await initializeQueryEngine();
}
// Use cached engine
return await cachedQueryEngine.query(question);
}
```
## Environment Variable Issues
### Missing API Keys
**Problem:** API key not found or invalid
**Solution:** Verify environment variable setup:
```typescript
// Check if API key is available
if (!process.env.OPENAI_API_KEY) {
throw new Error('OPENAI_API_KEY environment variable is required');
}
// For debugging (remove in production)
console.log('API Key present:', !!process.env.OPENAI_API_KEY);
```
### Environment Variable Loading
**Problem:** Environment variables not loading correctly
**Solution:** Use proper loading mechanisms:
```typescript
// For Node.js
import 'dotenv/config';
// For Next.js - use .env.local
// Variables are automatically loaded
// For Cloudflare Workers
export default {
async fetch(request: Request, env: Env): Promise<Response> {
// Use env parameter, not process.env
const apiKey = env.OPENAI_API_KEY;
// ...
},
};
```
## Common Error Messages
### "Cannot find module 'llamaindex'"
**Cause:** Package not installed or module resolution issue
**Solution:**
```bash
npm install llamaindex
```
### "Module not found: Can't resolve 'fs'"
**Cause:** File system modules used in browser/edge environment
**Solution:**
```typescript
// Use dynamic imports with fallbacks
const loadDocuments = async () => {
if (typeof window !== 'undefined') {
// Browser environment - use alternative
return await loadDocumentsFromAPI();
} else {
// Node.js environment - use file system
const { SimpleDirectoryReader } = await import('llamaindex');
return await new SimpleDirectoryReader('data').loadData();
}
};
```
### "ReferenceError: global is not defined"
**Cause:** Global polyfill missing in browser environments
**Solution:**
```typescript
// Add to your app entry point
if (typeof global === 'undefined') {
global = globalThis;
}
```
### "Cannot read properties of undefined (reading 'query')"
**Cause:** Query engine not properly initialized
**Solution:**
```typescript
// Always check initialization
if (!queryEngine) {
throw new Error('Query engine not initialized');
}
// Or use optional chaining
const response = await queryEngine?.query(question);
```
## Debugging Tips
### Enable Debug Logging
```typescript
// Enable debug logging
process.env.DEBUG = "llamaindex:*";
// Or specific modules
process.env.DEBUG = "llamaindex:vector-store";
```
### Check Package Versions
```bash
npm list llamaindex
npm list @llamaindex/openai
```
### Test in Isolation
```typescript
// Create minimal test case
import { VectorStoreIndex } from 'llamaindex';
async function testBasic() {
try {
console.log('Testing basic import...');
const index = new VectorStoreIndex();
console.log('Success!');
} catch (error) {
console.error('Error:', error);
}
}
testBasic();
```
## Getting Help
### Before Asking for Help
1. **Check this troubleshooting guide**
2. **Search existing GitHub issues**
3. **Try minimal reproduction**
4. **Check your environment configuration**
### When Reporting Issues
Include:
- Node.js version (`node --version`)
- Package versions (`npm list llamaindex`)
- Environment (Node.js, Cloudflare Workers, Vercel, etc.)
- Minimal code reproduction
- Full error message and stack trace
### Useful Resources
- [GitHub Issues](https://github.com/run-llama/LlamaIndexTS/issues)
- [Discord Community](https://discord.gg/dGcwcsnxhU)
- [Documentation](https://docs.llamaindex.ai/)
## Next Steps
If you're still experiencing issues:
1. **Check specific deployment guides:**
- [Server APIs](/docs/llamaindex/getting_started/installation/server-apis)
- [Serverless Functions](/docs/llamaindex/getting_started/installation/serverless)
- [Next.js Applications](/docs/llamaindex/getting_started/installation/nextjs)
2. **Open an issue** on GitHub with a minimal reproduction
3. **Join our Discord** for community support
@@ -1,4 +1,4 @@
{
"title": "Getting Started",
"pages": ["concepts", "installation", "create_llama", "examples"]
"pages": ["index", "setup", "starter_tutorial", "environments", "concepts"]
}
@@ -0,0 +1,79 @@
---
title: With Cloudflare Worker
description: In this guide, you'll learn how to use LlamaIndex with CloudFlare Worker
---
import {
SiNodedotjs,
SiDeno,
SiBun,
SiCloudflareworkers,
} from "@icons-pack/react-simple-icons";
Before you start, make sure you have try LlamaIndex.TS in Node.js to make sure you understand the basics.
<Card
title="Getting Started with LlamaIndex.TS in Node.js"
href="/docs/llamaindex/getting_started/setup/node"
/>
Also, you need have the basic understanding of <a href='https://developers.cloudflare.com/workers/'><SiCloudflareworkers className="inline mr-2" color="#F38020" />Cloudflare Worker</a>.
## Adding environment variables
```ts
export default {
async fetch(request: Request, env: Env): Promise<Response> {
const { setEnvs } = await import("@llamaindex/env");
setEnvs(env);
const { OpenAIAgent } = await import("@llamaindex/openai");
// Start your code here
return new Response("Hello, world!");
},
};
```
Then, you need create `.dev.vars` and add LLM api keys for the local development, such as `OPENAI_API_KEY` for OpenAI API key.
<Callout type="warn">Do not commit the api key to git repository.</Callout>
## Integrating with Hono
```ts
import { Hono } from "hono";
type Bindings = {
OPENAI_API_KEY: string;
};
const app = new Hono<{
Bindings: Bindings;
}>();
app.post("/llm", async (c) => {
const { setEnvs } = await import("@llamaindex/env");
setEnvs(c.env);
// ...
return new Response('Hello, world!');
})
export default {
fetch: app.fetch,
};
```
## Difference between Node.js and Cloudflare Worker
In Cloudflare Worker and similar serverless JS environment, you need to be aware of the following differences:
- Some Node.js modules are not available in Cloudflare Worker, such as `node:fs`, `node:child_process`, `node:cluster`...
- You are recommend to design your code using network request, such as use `fetch` API to communicate with database, insteadof a long-running process in Node.js.
- Some of LlamaIndex.TS modules are not available in Cloudflare Worker, for example `SimpleDirectoryReader` (requires `node:fs`), Some multimodal API that relies on [`onnxruntime-node`](https://www.npmjs.com/package/onnxruntime-node)(we might port to HTTP based module in the future).
- `@llamaindex/core` is designed to work in all JavaScript environment, including Cloudflare Worker. If you find any issue, please report to us.
- `@llamaindex/env` is a JS environment binding module, which polyfill some Node.js/Modern Web API (for example, we have a memory based `fs` module, and Crypto API polyfill). It is designed to work in all JavaScript environment, including Cloudflare Worker.
## Known issues
- `llamaindex` not work perfectly in Cloudflare Worker, bundle size will be larger than 1MB, which is the limit of Cloudflare Worker. You will need import submodule instead of the whole `llamaindex` module.
@@ -0,0 +1,42 @@
---
title: Choose Framework
description: We support multiple JS runtime and frameworks, bundlers.
---
import {
SiNodedotjs,
SiTypescript,
SiNextdotjs,
SiCloudflareworkers,
SiVite
} from "@icons-pack/react-simple-icons";
<Cards>
<Card title={
<>
<SiNodedotjs className="inline" color="#5FA04E" /> Node.js
</>
} href="/docs/llamaindex/getting_started/setup/node" />
<Card title={
<>
<SiTypescript className="inline" color="#3178C6" /> TypeScript
</>
} href="/docs/llamaindex/getting_started/setup/typescript" />
<Card title={
<>
<SiVite className='inline' color='#646CFF' /> Vite
</>
} href="/docs/llamaindex/getting_started/setup/vite" />
<Card
title={
<>
<SiNextdotjs className='inline' /> Next.js (React Server Component)
</>
}
href="/docs/llamaindex/getting_started/setup/next"
/>
<Card title={
<>
<SiCloudflareworkers className='inline' color='#F38020' /> Cloudflare Workers
</>
} href="/docs/llamaindex/getting_started/setup/cloudflare" />
</Cards>
@@ -0,0 +1,6 @@
{
"title": "Setup",
"description": "The setup guide",
"defaultOpen": true,
"pages": ["index", "next", "node", "typescript", "vite", "cloudflare"]
}

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