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45 Commits

Author SHA1 Message Date
github-actions[bot] 588cd0f0b9 Release 0.10.2 (#1861)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-04-18 17:14:21 +07:00
Huu Le 7ca9ddff86 feat: Add generate UI workflow to server (#1862)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
Co-authored-by: Thuc Pham <51660321+thucpn@users.noreply.github.com>
2025-04-18 16:59:44 +07:00
Thuc Pham 3310eaae29 chore: bump chat-ui 0.4.0 (#1868) 2025-04-18 15:33:08 +07:00
Peter Goldstein 96dac4ddfd feat: Add Gemini 2.5 Flash Preview (#1866) 2025-04-18 15:30:06 +07:00
Logan f9ee683593 docs: remove fake chat (#1867) 2025-04-17 17:14:38 -07:00
Peter Goldstein e5c3f95c6e Update o4-mini to allow reasoning parameters and exclude temperature (#1859) 2025-04-17 13:51:27 +07:00
Thuc Pham b155c8cf2c chore: make llamaindex as peer deps of server (#1860) 2025-04-17 13:50:28 +07:00
github-actions[bot] be6fead71a Release 0.10.1 (#1858)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: himself65 <14026360+himself65@users.noreply.github.com>
2025-04-16 19:15:34 -07:00
Peter Goldstein 96dd79853a Add o3 and o4-mini models (#1857) 2025-04-16 13:28:39 -07:00
Fuma Nama f49366c9af make docs great again (#1855)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
Co-authored-by: Alex Yang <himself65@outlook.com>
2025-04-16 11:19:25 -07:00
github-actions[bot] cde403be58 Release 0.10.0 (#1854)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-04-16 17:02:34 +07:00
Parham Saidi e9bf4424e2 fix: update the tool call schema for nova (#1850)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2025-04-16 16:52:29 +07:00
Thuc Pham edb8b87d86 fix: shadcn components cannot be used in next server (#1853) 2025-04-16 15:57:25 +07:00
Thuc Pham 6cf928f390 chore: use bunchee for llamaindex (#1821) 2025-04-16 15:47:30 +07:00
Alex Yang 8e27fd2009 fix(docs): sha on edit page (#1852) 2025-04-15 23:51:38 -07:00
Alex Yang c84036bbdd fix(doc): use install shortcut (#1849) 2025-04-15 09:08:32 -07:00
github-actions[bot] f43406fc9b Release @llamaindex/community@0.0.95 (#1848)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
2025-04-15 16:00:59 +07:00
Peter Goldstein 411dceaa41 Add Nova Premier model. Add EU endpoints for Nova models (#1841) 2025-04-15 15:48:11 +07:00
Alex Yang 2447384f31 chore: bump fumadocs & next & react (#1845) 2025-04-15 01:20:29 -07:00
github-actions[bot] 5f3eb457e6 Release 0.9.19 (#1844)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-04-15 00:31:31 -07:00
Peter Goldstein d365eb2e54 Add GPT-4.1 models to OpenAI (#1842) 2025-04-15 09:07:38 +02:00
Thuc Pham bb34ade6d4 feat: support cn utils for server UI (#1843) 2025-04-15 09:06:39 +02:00
github-actions[bot] c540df5069 Release 0.9.18 (#1836)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-04-14 20:52:09 +07:00
Marcus Schiesser 400b3b54bf feat: use full-source code with import statements for custom comps (#1838)
Co-authored-by: thucpn <thucsh2@gmail.com>
Co-authored-by: Thuc Pham <51660321+thucpn@users.noreply.github.com>
2025-04-14 13:48:21 +02:00
Marcus Schiesser 88b7046c68 chore: Move zod to peer deps (#1837) 2025-04-10 18:17:26 +07:00
Zhanghao 2ffdb274f2 docs: correct the CondenseQuestionChatEngine path (#1834) 2025-04-10 16:07:07 +07:00
github-actions[bot] 139eb050f9 Release @llamaindex/server@0.1.0 (#1835)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
2025-04-10 15:38:40 +07:00
Thuc Pham 3ffee26b77 feat: enhance config params for LlamaIndexServer (#1833) 2025-04-10 15:21:51 +07:00
Marcus Schiesser dc6e774d78 chore: remove deepresearch events (#1831) 2025-04-09 20:45:49 +07:00
github-actions[bot] 6716188e10 Release @llamaindex/server@0.0.9 (#1830)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
2025-04-09 17:44:13 +07:00
Thuc Pham 0b75bd6d92 feat: component dir in llamaindex server (#1828) 2025-04-09 17:25:21 +07:00
github-actions[bot] 045b267d1b Release 0.9.17 (#1823)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: himself65 <14026360+himself65@users.noreply.github.com>
2025-04-08 17:35:55 -07:00
Alex Yang 41191d074a fix(parse): file input (#1829) 2025-04-08 14:15:07 -07:00
Marcus Schiesser 8b2914c8b7 docs: reorganize modules structure in docs (#1827) 2025-04-08 22:42:00 +07:00
Marcus Schiesser 4c24dfcbce docs: Move framework docs to installation directory and simplify gett… (#1826) 2025-04-07 22:54:12 +07:00
r3rer3 0dfa371fc9 Add "thinking" and "thinking_signature" to chat response, and "thinking_signature" to chat stream (#1825) 2025-04-07 21:57:55 +07:00
Peter Goldstein 0d852d6fdc Add the Gemini 2.5 Pro Preview model (#1822) 2025-04-07 16:08:40 +07:00
ANKIT VARSHNEY 2410527e64 feat: reader for postgres (#1813)
Co-authored-by: Marcus Schiesser <mail@marcusschiesser.de>
2025-04-07 15:57:14 +07:00
Marcus Schiesser 7d2be8c640 fix: mcp test 2025-04-07 10:44:54 +02:00
Thuc Pham 3534c373f2 feat: support multi-resolution compatibility (#1816) 2025-04-05 18:41:39 +07:00
github-actions[bot] 2cbdf71669 Release 0.9.16 (#1811)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: marcusschiesser <17126+marcusschiesser@users.noreply.github.com>
2025-04-04 11:12:27 +02:00
Huu Le ead657aedd feat: add MCP tools integration and example usage (#1819) 2025-04-04 11:03:10 +02:00
Marcus Schiesser f5e4d098b0 chore: remove gpt-tokenizer (#1815) 2025-04-03 14:23:31 +02:00
dependabot[bot] 4d97226e50 chore(deps): bump next from 15.2.3 to 15.2.4 (#1812)
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2025-04-03 13:57:39 +07:00
Marcus Schiesser 4999df18cc chore: bump nextjs to "^15.2.3" (#1810) 2025-04-02 21:24:57 +07:00
347 changed files with 15791 additions and 7238 deletions
+71
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@@ -1,5 +1,76 @@
# @llamaindex/doc
## 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
+2
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@@ -0,0 +1,2 @@
// fallback for `fs` usage in `web-tree-sitter`
module.exports = {};
+6 -10
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@@ -1,5 +1,4 @@
import { createMDX } from "fumadocs-mdx/next";
import MonacoWebpackPlugin from "monaco-editor-webpack-plugin";
const withMDX = createMDX();
/** @type {import('next').NextConfig} */
@@ -16,7 +15,12 @@ const config = {
"twoslash",
"typescript",
],
webpack: (config, { isServer }) => {
turbopack: {
resolveAlias: {
fs: { browser: "./fallback.js" },
},
},
webpack: (config) => {
if (Array.isArray(config.target) && config.target.includes("web")) {
config.target = ["web", "es2020"];
}
@@ -28,14 +32,6 @@ 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;
},
+20 -17
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@@ -1,19 +1,21 @@
{
"name": "@llamaindex/doc",
"version": "0.2.4",
"version": "0.2.13",
"private": true,
"scripts": {
"postinstall": "fumadocs-mdx",
"prebuild": "pnpm run build:docs",
"build": "next build",
"dev": "next dev",
"dev": "next dev --turbo",
"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"
},
"dependencies": {
"@huggingface/transformers": "^3.5.0",
"@icons-pack/react-simple-icons": "^10.1.0",
"@llama-flow/docs": "0.0.3",
"@llamaindex/chat-ui": "0.2.0",
"@llamaindex/cloud": "workspace:*",
"@llamaindex/core": "workspace:*",
@@ -22,6 +24,7 @@
"@llamaindex/readers": "workspace:*",
"@llamaindex/workflow": "workspace:*",
"@mdx-js/mdx": "^3.1.0",
"@monaco-editor/react": "^4.7.0",
"@number-flow/react": "^0.3.4",
"@radix-ui/react-dialog": "^1.1.2",
"@radix-ui/react-icons": "^1.3.2",
@@ -36,22 +39,21 @@
"clsx": "2.1.1",
"foxact": "^0.2.41",
"framer-motion": "^11.11.17",
"fumadocs-core": "^15.0.15",
"fumadocs-core": "^15.2.7",
"fumadocs-docgen": "^2.0.0",
"fumadocs-mdx": "^11.5.6",
"fumadocs-openapi": "^6.3.0",
"fumadocs-twoslash": "^3.1.0",
"fumadocs-typescript": "^3.1.0",
"fumadocs-ui": "^15.0.15",
"fumadocs-mdx": "^11.6.0",
"fumadocs-openapi": "^8.0.1",
"fumadocs-twoslash": "^3.1.1",
"fumadocs-typescript": "^4.0.2",
"fumadocs-ui": "^15.2.7",
"hast-util-to-jsx-runtime": "^2.3.2",
"llamaindex": "workspace:*",
"lucide-react": "^0.460.0",
"next": "^15.2.1",
"next": "^15.3.0",
"next-themes": "^0.4.3",
"react": "^19.0.0",
"react-dom": "^19.0.0",
"react": "^19.1.0",
"react-dom": "^19.1.0",
"react-icons": "^5.3.0",
"react-monaco-editor": "^0.56.2",
"react-use-measure": "^2.1.1",
"rehype-katex": "^7.0.1",
"remark-math": "^6.0.0",
@@ -63,12 +65,14 @@
"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": "^3.23.8"
},
"devDependencies": {
"@next/env": "^15.2.1",
"@next/env": "^15.3.0",
"@tailwindcss/postcss": "^4.0.9",
"@types/mdx": "^2.0.13",
"@types/node": "22.9.0",
@@ -78,7 +82,6 @@
"cross-env": "^7.0.3",
"fast-glob": "^3.3.2",
"gray-matter": "^4.0.3",
"monaco-editor-webpack-plugin": "^7.1.0",
"postcss": "^8.5.3",
"raw-loader": "^4.0.2",
"remark": "^15.0.1",
@@ -87,9 +90,9 @@
"remark-stringify": "^11.0.0",
"tailwindcss": "^4.0.9",
"tsx": "^4.19.3",
"typedoc": "0.27.4",
"typedoc-plugin-markdown": "^4.3.1",
"typedoc-plugin-merge-modules": "^6.1.0",
"typedoc": "0.28.2",
"typedoc-plugin-markdown": "^4.6.2",
"typedoc-plugin-merge-modules": "^7.0.0",
"typescript": "^5.7.3"
}
}

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+6 -2
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@@ -1,9 +1,13 @@
import { generateFiles as openapiGenerateFiles } from "fumadocs-openapi";
import { generateFiles as typescriptGenerateFiles } from "fumadocs-typescript";
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";
@@ -20,7 +24,7 @@ void openapiGenerateFiles({
groupBy: "tag",
});
void typescriptGenerateFiles({
void typescriptGenerateFiles(generator, {
input: ["./src/content/docs/api/**/*.mdx"],
output: (file) => path.resolve(path.dirname(file), path.basename(file)),
transformOutput,
+4 -1
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@@ -7,7 +7,10 @@ import rehypeKatex from "rehype-katex";
import remarkMath from "remark-math";
export const docs = defineDocs({
dir: "./src/content/docs",
dir: ["./src/content/docs", "./node_modules/@llama-flow/docs"],
docs: {
async: true,
},
});
export default defineConfig({
+51 -67
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@@ -10,16 +10,55 @@ import { MagicMove } from "@/components/magic-move";
import { NpmInstall } from "@/components/npm-install";
import { Supports } from "@/components/supports";
import { Button } from "@/components/ui/button";
import { Skeleton } from "@/components/ui/skeleton";
import { LEGACY_DOCUMENT_URL } from "@/lib/const";
import { 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";
import { Suspense } from "react";
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";
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";
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}\`);`,
];
export default function HomePage() {
return (
@@ -39,7 +78,7 @@ export default function HomePage() {
</div>
<div className="flex flex-wrap justify-center gap-4">
<Link href={LEGACY_DOCUMENT_URL}>
<Link href={DOCUMENT_URL}>
<Button variant="outline">Get Started</Button>
</Link>
<NpmInstall />
@@ -62,65 +101,10 @@ export default function HomePage() {
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."
>
<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/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";
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";
import { openai } from "@llamaindex/openai";
const analyseAgent = agent({
name: "AnalyseAgent",
llm: openai({ model: "gpt-4o" }),
tools: [analyseTools],
});
const reporterAgent = agent({
name: "ReporterAgent",
llm: openai({ model: "gpt-4o" }),
tools: [reporterTools],
canHandoffTo: [analyseAgent],
});
const agents = multiAgent({
agents: [analyseAgent, reporterAgent],
rootAgent: reporterAgent,
});
const response = await agents.run(\`Analyse the given data:
\${data}\`);`,
]}
/>
</Suspense>
<MagicMove
placeholder={<CodeBlock lang="ts" code={codes[0]} />}
code={codes}
/>
</Feature>
<Feature
icon={Bot}
+9 -1
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@@ -1,4 +1,12 @@
import { source } from "@/lib/source";
import { structure } from "fumadocs-core/mdx-plugins";
import { createFromSource } from "fumadocs-core/search/server";
export const { GET } = createFromSource(source);
// 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.url,
title: page.data.title,
description: page.data.description,
url: page.url,
structuredData: structure(page.data.content),
}));
+25 -7
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@@ -1,7 +1,14 @@
import { ChatDemoRSC } from "@/components/demo/chat/rsc/demo";
import * as demos from "@/components/demo/lazy";
import { createMetadata, metadataImage } from "@/lib/metadata";
import { openapi, source } from "@/lib/source";
import * as Icons from "@icons-pack/react-simple-icons";
import { APIPage } from "fumadocs-openapi/ui";
import { Popup, PopupContent, PopupTrigger } from "fumadocs-twoslash/ui";
import { createTypeTable } from "fumadocs-typescript/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 defaultMdxComponents from "fumadocs-ui/mdx";
import {
DocsBody,
@@ -11,6 +18,8 @@ import {
} from "fumadocs-ui/page";
import { notFound } from "next/navigation";
const generator = createGenerator();
export const revalidate = false;
export default async function Page(props: {
@@ -20,17 +29,17 @@ export default async function Page(props: {
const page = source.getPage(params.slug);
if (!page) notFound();
const { AutoTypeTable } = createTypeTable();
const MDX = page.data.body;
const { body: MDX, toc, lastModified } = await page.data.load();
return (
<DocsPage
toc={page.data.toc}
toc={toc}
full={page.data.full}
lastUpdate={page.data.lastModified}
lastUpdate={lastModified}
editOnGithub={{
owner: "run-llama",
repo: "LlamaIndexTS",
sha: "main",
path: `apps/next/src/content/docs/${page.file.path}`,
}}
>
@@ -39,12 +48,21 @@ export default async function Page(props: {
<DocsBody>
<MDX
components={{
...Icons,
...defaultMdxComponents,
APIPage: openapi.APIPage,
...demos,
ChatDemoRSC,
Accordion,
Accordions,
APIPage: (props) => <APIPage {...openapi.getAPIPageProps(props)} />,
Tab,
Tabs,
Popup,
PopupContent,
PopupTrigger,
AutoTypeTable,
AutoTypeTable: (props) => (
<AutoTypeTable generator={generator} {...props} />
),
}}
/>
</DocsBody>
-19
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@@ -1,11 +1,7 @@
import { baseOptions } from "@/app/layout.config";
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 }) {
@@ -15,21 +11,6 @@ export default function Layout({ children }: { children: ReactNode }) {
{...baseOptions}
nav={{
...baseOptions.nav,
children: (
<AITrigger
className={cn(
buttonVariants({
variant: "secondary",
size: "xs",
className:
"text-fd-muted-foreground ms-2 gap-1.5 rounded-full px-2 md:flex-1",
}),
)}
>
<MessageCircle className="size-3" />
Ask LlamaCloud
</AITrigger>
),
}}
>
{children}
+1 -1
View File
@@ -1,7 +1,7 @@
@import "tailwindcss";
@import "fumadocs-ui/css/neutral.css";
@import "fumadocs-ui/css/preset.css";
@import "../../node_modules/fumadocs-twoslash/dist/twoslash.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",
+2 -2
View File
@@ -1,4 +1,4 @@
import { LEGACY_DOCUMENT_URL } from "@/lib/const";
import { DOCUMENT_URL } from "@/lib/const";
import type { BaseLayoutProps } from "fumadocs-ui/layouts/shared";
import Image from "next/image";
@@ -28,7 +28,7 @@ export const baseOptions: BaseLayoutProps = {
links: [
{
text: "Docs",
url: LEGACY_DOCUMENT_URL,
url: DOCUMENT_URL,
active: "nested-url",
},
],
@@ -1,24 +1,26 @@
"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") {
promise = Parser.init({
locateFile(scriptName: string) {
return "/" + scriptName;
},
}).then(async () => {
async function run() {
const { default: Parser } = await import("web-tree-sitter");
await Parser.init({
locateFile(scriptName: string) {
return "/" + scriptName;
},
});
const parser = new Parser();
const Lang = await Parser.Language.load("/tree-sitter-typescript.wasm");
parser.setLanguage(Lang);
@@ -26,7 +28,9 @@ if (typeof window !== "undefined") {
getParser: () => parser,
maxChars: 100,
});
});
}
promise = run();
}
const [SliderProvider, useSlider, useSetSlider] = createContextState(100);
@@ -48,8 +52,6 @@ const john: Person = {
console.log(greet(john));`);
const Editor = lazy(() => import("react-monaco-editor"));
export const IDE = () => {
const codeSplitter = use(promise);
const code = useCode();
@@ -73,21 +75,6 @@ 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,
@@ -97,7 +84,9 @@ export const IDE = () => {
height="100%"
width="100%"
language="typescript"
onChange={setCode}
onChange={(v) => {
if (v) setCode(v);
}}
value={code}
/>
</div>
+18
View File
@@ -0,0 +1,18 @@
"use client";
import dynamic from "next/dynamic";
// lazy load client components
export const ChatDemo = dynamic(() =>
import("@/components/demo/chat/api/demo").then((mod) => mod.ChatDemo),
);
export const CodeNodeParserDemo = dynamic(() =>
import("@/components/demo/code-node-parser").then(
(mod) => mod.CodeNodeParserDemo,
),
);
export const WorkflowStreamingDemo = dynamic(() =>
import("@/components/demo/workflow-streaming-ui").then(
(mod) => mod.WorkflowStreamingDemo,
),
);
+26 -21
View File
@@ -1,25 +1,27 @@
"use client";
import { Button } from "@/components/ui/button";
import { cn } from "@/lib/utils";
import { CodeBlock, Pre } from "fumadocs-ui/components/codeblock";
import { CodeBlock } from "fumadocs-ui/components/codeblock";
import { RotateCcw } from "lucide-react";
import { useTheme } from "next-themes";
import { use, useCallback, useEffect, useState } from "react";
import { getSingletonHighlighter } from "shiki";
import { type ReactNode, use, useCallback, useEffect, useState } from "react";
import { createJavaScriptRegexEngine, getSingletonHighlighter } from "shiki";
import { ShikiMagicMove } from "shiki-magic-move/react";
import { createOnigurumaEngine } from "shiki/engine/oniguruma";
const engine = createJavaScriptRegexEngine();
const highlighterPromise = getSingletonHighlighter({
engine: createOnigurumaEngine(() => import("shiki/wasm")),
engine,
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);
@@ -38,24 +40,27 @@ export function MagicMove(props: MagicMoveProps) {
}
}, [animate, move, props.code]);
useEffect(() => {
setMounted(true);
}, []);
if (!mounted) return props.placeholder;
return (
<CodeBlock allowCopy={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>
)}
<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,
}}
/>
<Button
className={cn(
"absolute bottom-2 right-2",
@@ -18,4 +18,4 @@ npm run dev
to start the development server. You can then visit [http://localhost:3000](http://localhost:3000) to see your app, which should look something like this:
![create-llama interface](./images/create_llama.png)
![create-llama interface](/images/create_llama.png)
@@ -11,7 +11,7 @@ It may be useful to check out all the examples at once so you can try them out l
```bash npm2yarn
npx degit run-llama/LlamaIndexTS/examples my-new-project
cd my-new-project
npm install
npm i
```
Then you can run any example in the folder with `tsx`, e.g.:
@@ -1,42 +0,0 @@
---
title: Frameworks
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/frameworks/node" />
<Card title={
<>
<SiTypescript className="inline" color="#3178C6" /> TypeScript
</>
} href="/docs/llamaindex/getting_started/frameworks/typescript" />
<Card title={
<>
<SiVite className='inline' color='#646CFF' /> Vite
</>
} href="/docs/llamaindex/getting_started/frameworks/vite" />
<Card
title={
<>
<SiNextdotjs className='inline' /> Next.js (React Server Component)
</>
}
href="/docs/llamaindex/getting_started/frameworks/next"
/>
<Card title={
<>
<SiCloudflareworkers className='inline' color='#F38020' /> Cloudflare Workers
</>
} href="/docs/llamaindex/getting_started/frameworks/cloudflare" />
</Cards>
@@ -1,6 +0,0 @@
{
"title": "Framework",
"description": "The setup guide",
"defaultOpen": true,
"pages": ["node", "typescript", "next", "vite", "cloudflare"]
}
@@ -1,56 +0,0 @@
---
title: Installation
description: How to install llamaindex packages.
---
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
To install llamaindex, run the following command:
<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>
In most cases, you'll also need an LLM package to use LlamaIndex. For example, to use the OpenAI LLM, you would install the following:
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install @llamaindex/openai
```
```shell tab="yarn"
yarn add @llamaindex/openai
```
```shell tab="pnpm"
pnpm add @llamaindex/openai
```
</Tabs>
Go to [LLM APIs](/docs/llamaindex/modules/llms) to find out how to use other LLMs.
## 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/rag"
/>
<Card
title="Show me code examples"
description="Explore code examples using LlamaIndex.TS."
href="/docs/llamaindex/getting_started/examples"
/>
</Cards>
@@ -3,18 +3,11 @@ 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/frameworks/node"
href="/docs/llamaindex/getting_started/installation/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>.
@@ -69,7 +62,7 @@ export default {
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.
- You are recommend to design your code using network request, such as use `fetch` API to communicate with database, instead of a long-running process in Node.js.
- Some of LlamaIndex.TS packages are not available in Cloudflare Worker, for example `@llamaindex/readers` and `@llamaindex/huggingface`.
- The main `llamaindex` 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.
@@ -0,0 +1,69 @@
---
title: Installation
description: How to install llamaindex packages.
---
To install llamaindex, run the following command:
```package-install
npm i llamaindex
```
In most cases, you'll also need an LLM package to use LlamaIndex. For example, to use the OpenAI LLM, you would install the following:
```package-install
npm i @llamaindex/openai
```
Go to [LLM APIs](/docs/llamaindex/modules/models/llms) to find out how to use other LLMs.
## Frameworks
LlamaIndex supports a wide range of frameworks and runtimes. Click on the card below to learn more.
<Cards>
<Card title={
<>
<SiNodedotjs className="inline" color="#5FA04E" /> Node.js
</>
} href="/docs/llamaindex/getting_started/installation/node" />
<Card title={
<>
<SiTypescript className="inline" color="#3178C6" /> TypeScript
</>
} href="/docs/llamaindex/getting_started/installation/typescript" />
<Card title={
<>
<SiVite className='inline' color='#646CFF' /> Vite
</>
} href="/docs/llamaindex/getting_started/installation/vite" />
<Card
title={
<>
<SiNextdotjs className='inline' /> Next.js (React Server Component)
</>
}
href="/docs/llamaindex/getting_started/installation/next"
/>
<Card title={
<>
<SiCloudflareworkers className='inline' color='#F38020' /> Cloudflare Workers
</>
} href="/docs/llamaindex/getting_started/installation/cloudflare" />
</Cards>
## 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/rag"
/>
<Card
title="Show me code examples"
description="Explore code examples using LlamaIndex.TS."
href="/docs/llamaindex/getting_started/examples"
/>
</Cards>
@@ -0,0 +1,4 @@
{
"title": "Installation",
"pages": ["node", "typescript", "next", "vite", "cloudflare"]
}
@@ -7,7 +7,7 @@ Before you start, make sure you have try LlamaIndex.TS in Node.js to make sure y
<Card
title="Getting Started with LlamaIndex.TS in Node.js"
href="/docs/llamaindex/getting_started/frameworks/node"
href="/docs/llamaindex/getting_started/installation/node"
/>
## Differences between Node.js and Next.js
@@ -17,9 +17,9 @@ This means that you need to be careful when using LlamaIndex.TS in Next.js.
Don't leak the import data like API keys to the client side.
Also, in Next.js, there is build time and runtime. Some computations can be done at build time like Document embedding could be done at build time for better performance.
LlamaIndex.TS has lots of upstream dependencies, some of them are not compatible with Next.js.
Where as the `llamaindex` package is working with Next.js, some provider packages like `@llamaindex/huggingface` are not working well with Next.js. This is due to the upstream dependencies used by the provider package.
You might need to use `withNext` to make sure that LlamaIndex.TS works well with Next.js.
Make sure to use `withLlamaIndex` to make sure that LlamaIndex.TS works well with Next.js.
```js
// next.config.mjs / next.config.ts
@@ -35,7 +35,7 @@ If you see any dependency issues, you are welcome to open an issue on the GitHub
## Edge Runtime
[Vercel Edge Runtime](https://edge-runtime.vercel.app/) is a subset of Node.js APIs. Similar to [Cloudflare Workers](/docs/llamaindex/getting_started/frameworks/cloudflare#difference-between-nodejs-and-cloudflare-worker),
[Vercel Edge Runtime](https://edge-runtime.vercel.app/) is a subset of Node.js APIs. Similar to [Cloudflare Workers](/docs/llamaindex/getting_started/installation/cloudflare#difference-between-nodejs-and-cloudflare-worker),
it is a serverless platform that runs your code on the edge.
Not all features of Node.js are supported in Vercel Edge Runtime, so does LlamaIndex.TS, we are working on more compatibility with all JavaScript runtimes.
@@ -3,8 +3,6 @@ title: With Node.js/Bun/Deno
description: In this guide, you'll learn how to use LlamaIndex with Node.js, Bun, and Deno.
---
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
## Adding environment variables
By default, LlamaIndex uses OpenAI provider, which requires an API key. You can set the `OPENAI_API_KEY` environment variable to authenticate with OpenAI.
@@ -28,19 +26,9 @@ For more information, see the [How to read environment variables from Node.js](h
By the default, we are using `js-tiktoken` for tokenization. You can install `gpt-tokenizer` which is then automatically used by LlamaIndex to get a 60x speedup for tokenization:
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install gpt-tokenizer
```
```shell tab="yarn"
yarn add gpt-tokenizer
```
```shell tab="pnpm"
pnpm add gpt-tokenizer
```
</Tabs>
```package-install
npm i gpt-tokenizer
```
**Note**: This only works for Node.js
@@ -48,5 +36,5 @@ By the default, we are using `js-tiktoken` for tokenization. You can install `gp
<Card
title="Getting Started with LlamaIndex.TS in TypeScript"
href="/docs/llamaindex/getting_started/frameworks/typescript"
href="/docs/llamaindex/getting_started/installation/typescript"
/>
@@ -2,11 +2,10 @@
title: With TypeScript
description: In this guide, you'll learn how to use LlamaIndex with TypeScript
---
import { Accordion, Accordions } from 'fumadocs-ui/components/accordion';
LlamaIndex.TS is written in TypeScript and designed to be used in TypeScript projects.
We do lots of work on strong typing to make sure you have a great typing experience with LlamaIndex.TS.
We put a lot of work on strong typing to make sure you have a great typing experience with code completion such as:
```ts twoslash
import { PromptTemplate } from 'llamaindex'
@@ -28,70 +27,32 @@ promptTemplate.format({
})
```
```ts twoslash
import { FunctionTool } from 'llamaindex'
import { z } from 'zod'
// ---cut-before---
const inputSchema = z.object({
time: z.string(),
city: z.string(),
})
type Input = z.infer<typeof inputSchema>
FunctionTool.from<Input>((input) => {
// @noErrors
input.t
// ^|
}, {
name: 'getWeather',
description: 'Get the weather information',
parameters: inputSchema,
})
```
## Enable TypeScript
Make sure to set [moduleResolution](https://www.typescriptlang.org/docs/handbook/modules/theory.html#module-resolution) in your `tsconfig.json` file:
```json5
{
compilerOptions: {
// ⬇️ add this line to your tsconfig.json
moduleResolution: "bundler", // or "node16"
moduleResolution: "bundler", // or "nodenext" | "node16" | "node"
},
}
```
<Accordions>
<Accordion
title="Why modify tsconfig.json"
>
We recommend using `bundler` or `nodenext`, but due to popularity of `node`, we still added support for it, but with import path limitations.
We are shipping both ESM and CJS module, and compatible with Vercel Edge, Cloudflare Workers, and other serverless platforms.
So you may encounter type errors when importing sub paths from the `llamaindex` package like:
So we are using [conditional exports](https://nodejs.org/api/packages.html#conditional-exports) to support all environments.
This is a kind of modern way of shipping packages, but might cause TypeScript type check to fail because of legacy module resolution.
Imaging you put output file into `/dist/openai.js` but you are importing `llamaindex/openai` in your code, and set `package.json` like this:
```json5
{
"exports": {
"./openai": "./dist/openai.js"
}
}
```ts
import { Settings } from "llamaindex";
```
In old module resolution, TypeScript will not be able to find the module because it is not following the file structure, even you run `node index.js` successfully. (on Node.js >=16)
The simplest way to fix this without changing `moduleResolution` is to import directly from `llamaindex`:
See more about [moduleResolution](https://www.typescriptlang.org/docs/handbook/modules/theory.html#module-resolution) or
[TypeScript 5.0 blog](https://devblogs.microsoft.com/typescript/announcing-typescript-5-0/#--moduleresolution-bundler7).
</Accordion>
</Accordions>
```ts
import { Settings } from "llamaindex";
```
## Enable AsyncIterable for `Web Stream` API
@@ -7,7 +7,7 @@ Before you start, make sure you have try LlamaIndex.TS in Node.js to make sure y
<Card
title="Getting Started with LlamaIndex.TS in Node.js"
href="/docs/llamaindex/getting_started/frameworks/node"
href="/docs/llamaindex/getting_started/installation/node"
/>
Also, make sure you have a basic understanding of [Vite](https://vitejs.dev/).
@@ -1,4 +1,4 @@
{
"title": "Getting Started",
"pages": ["index", "create_llama", "examples", "frameworks"]
"pages": ["installation", "create_llama", "examples"]
}
@@ -3,13 +3,6 @@ title: What is LlamaIndex.TS
description: LlamaIndex is the leading data framework for building LLM applications
---
import {
SiNodedotjs,
SiDeno,
SiBun,
SiCloudflareworkers,
} from "@icons-pack/react-simple-icons";
LlamaIndex is a framework for building context-augmented generative AI applications with LLMs including agents and workflows.
The TypeScript implementation is designed for JavaScript server side applications using <SiNodedotjs className="inline" color="#5FA04E" /> Node.js, <SiDeno className="inline" color="#70FFAF" /> Deno, <SiBun className="inline" /> Bun, <SiCloudflareworkers className="inline" color="#F38020" /> Cloudflare Workers, and more.
@@ -2,7 +2,6 @@
title: Langtrace
description: Learn how to integrate LlamaIndex.TS with Langtrace.
---
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
Enhance your observability with Langtrace, a robust open-source tool supports OpenTelemetry and is designed to trace, evaluate, and manage LLM applications seamlessly. Langtrace integrates directly with LlamaIndex, offering detailed, real-time insights into performance metrics such as accuracy, evaluations, and latency.
@@ -10,19 +9,9 @@ Enhance your observability with Langtrace, a robust open-source tool supports Op
- Self-host or sign-up and generate an API key using [Langtrace](https://www.langtrace.ai) Cloud
<Tabs groupId="install-langtrase" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install @langtrase/typescript-sdk
```
```shell tab="yarn"
yarn add @langtrase/typescript-sdk
```
```shell tab="pnpm"
pnpm add @langtrase/typescript-sdk
```
</Tabs>
```package-install
npm i @langtrase/typescript-sdk
```
## Initialize
@@ -2,27 +2,15 @@
title: OpenLLMetry
description: Learn how to integrate LlamaIndex.TS with OpenLLMetry.
---
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
[OpenLLMetry](https://github.com/traceloop/openllmetry-js) is an open-source project based on OpenTelemetry for tracing and monitoring
LLM applications. It connects to [all major observability platforms](https://www.traceloop.com/docs/openllmetry/integrations/introduction) and installs in minutes.
### Usage Pattern
<Tabs groupId="install-traceloop" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install @traceloop/node-server-sdk
```
```shell tab="yarn"
yarn add @traceloop/node-server-sdk
```
```shell tab="pnpm"
pnpm add @traceloop/node-server-sdk
```
</Tabs>
```package-install
npm i @traceloop/node-server-sdk
```
```js
import * as traceloop from "@traceloop/node-server-sdk";
@@ -11,8 +11,8 @@ LlamaIndex provides integration with Vercel's AI SDK, allowing you to create pow
First, install the required dependencies:
```bash
npm install @llamaindex/vercel ai
```package-install
npm i @llamaindex/vercel ai
```
## Using Vercel AI's Model Providers
@@ -2,8 +2,6 @@
title: Migrating from v0.8 to v0.9
---
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
Version 0.9 of LlamaIndex.TS introduces significant architectural changes to improve package size and runtime compatibility. The main goals of this release are:
1. Reduce the package size of the main `llamaindex` package by moving dependencies into provider packages, making it more suitable for serverless environments
@@ -33,21 +31,11 @@ import { OpenAI } from "@llamaindex/openai";
> Note: This examples requires installing the `@llamaindex/openai` package:
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install @llamaindex/openai
```
```package-install
npm i @llamaindex/openai
```
```shell tab="yarn"
yarn add @llamaindex/openai
```
```shell tab="pnpm"
pnpm add @llamaindex/openai
```
</Tabs>
For more details on available AI model providers and their configuration, see the [LLMs documentation](/docs/llamaindex/modules/llms) and the [Embedding Models documentation](/docs/llamaindex/modules/embeddings).
For more details on available AI model providers and their configuration, see the [LLMs documentation](/docs/llamaindex/modules/models/llms) and the [Embedding Models documentation](/docs/llamaindex/modules/models/embeddings).
### 2. Storage Providers
@@ -61,7 +49,7 @@ Now:
import { PineconeVectorStore } from "@llamaindex/pinecone";
```
For more information about available storage options, refer to the [Data Stores documentation](/docs/llamaindex/modules/data_stores).
For more information about available storage options, refer to the [Data Stores documentation](/docs/llamaindex/modules/data/stores).
### 3. Data Loaders
@@ -75,7 +63,7 @@ Now:
import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
```
For more details about available data loaders and their usage, check the [Loading Data](/docs/llamaindex/modules/loading).
For more details about available data loaders and their usage, check the [Loading Data](/docs/llamaindex/modules/data/readers).
### 4. Prefer using `llamaindex` instead of `@llamaindex/core`
@@ -2,7 +2,7 @@
title: Agents
---
**Note**: Agents are deprecated, use [Agent Workflows](/docs/llamaindex/modules/agent_workflow) instead.
**Note**: Agents are deprecated, use [Agent Workflows](/docs/llamaindex/modules/agents/agent_workflow) instead.
An “agent” is an automated reasoning and decision engine. It takes in a user input/query and can make internal decisions for executing that query in order to return the correct result. The key agent components can include, but are not limited to:
@@ -3,7 +3,7 @@ title: Agent Workflows
---
Agent Workflows are a powerful system that enables you to create and orchestrate one or multiple agents with tools to perform specific tasks. It's built on top of the base [`Workflow`](/docs/llamaindex/modules/workflows) system and provides a streamlined interface for agent interactions.
Agent Workflows are a powerful system that enables you to create and orchestrate one or multiple agents with tools to perform specific tasks. It's built on top of the base [`Workflow`](/docs/llamaindex/modules/agents/workflows) system and provides a streamlined interface for agent interactions.
## Usage
@@ -0,0 +1,4 @@
{
"title": "Agents",
"pages": ["tool", "agent_workflow", "workflows"]
}
@@ -2,9 +2,6 @@
title: Workflows
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../examples/workflow/joke.ts";
A `Workflow` in LlamaIndexTS is an event-driven abstraction used to chain together several events. Workflows are made up of `steps`, with each step responsible for handling certain event types and emitting new events.
Workflows in LlamaIndexTS work by defining step functions that handle specific event types and emit new events.
@@ -13,27 +10,16 @@ When a step function is added to a workflow, you need to specify the input and o
You can create a `Workflow` to do anything! Build an agent, a RAG flow, an extraction flow, or anything else you want.
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install @llamaindex/workflow
```
```shell tab="yarn"
yarn add @llamaindex/workflow
```
```shell tab="pnpm"
pnpm add @llamaindex/workflow
```
</Tabs>
```package-install
npm i @llamaindex/workflow
```
## Getting Started
As an illustrative example, let's consider a naive workflow where a joke is generated and then critiqued.
<DynamicCodeBlock lang="ts" code={CodeSource} />
<include cwd>../../examples/workflow/joke.ts</include>
There's a few moving pieces here, so let's go through this piece by piece.
@@ -2,7 +2,8 @@
title: Index
---
An index is the basic container and organization for your data. LlamaIndex.TS supports three indexes:
An index is the basic container for organizing your data. Besides managed indexes using [LlamaCloud](/docs/llamaindex/modules/data/data_index/managed), LlamaIndex.TS supports three indexes:
- `VectorStoreIndex` - will send the top-k `Node`s to the LLM when generating a response. The default top-k is 2.
- `SummaryIndex` - will send every `Node` in the index to the LLM in order to generate a response
@@ -0,0 +1,32 @@
---
title: Managed Index
description: Managed index using LlamaCloud
---
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.
LlamaCloud supports
- Managed Ingestion API, handling parsing and document management
- Managed Retrieval API, configuring optimal retrieval for your RAG system
## Access
Visit [LlamaCloud](https://cloud.llamaindex.ai) to sign in and get an API key.
## Create a Managed Index
Here's an example of how to create a managed index by ingesting a couple of documents:
<include cwd>../../examples/cloud/chat.ts</include>
## Use a Managed Index
Here's an example of how to use a managed index together with a chat engine:
<include cwd>../../examples/cloud/from-documents.ts</include>
## API Reference
- [LlamaCloudIndex](/docs/api/classes/LlamaCloudIndex)
- [LlamaCloudRetriever](/docs/api/classes/LlamaCloudRetriever)
@@ -0,0 +1,17 @@
---
title: Documents and Nodes
description: Data structure for storing data in LlamaIndex
---
`Document`s and `Node`s are the basic building blocks of data in LlamaIndexTS. While the API for these objects is similar, `Document` objects represent entire files, while `Node`s are smaller pieces of that original document, that are suitable for an LLM and Q&A.
```typescript
import { Document } from "llamaindex";
document = new Document({ text: "text", metadata: { key: "val" } });
```
## API Reference
- [Document](/docs/api/classes/Document)
- [TextNode](/docs/api/classes/TextNode)
@@ -7,21 +7,9 @@ These `Transformations` are applied to your input data, and the resulting nodes
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/openai @llamaindex/qdrant
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/openai @llamaindex/qdrant
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/openai @llamaindex/qdrant
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/openai @llamaindex/qdrant
```
## Usage Pattern
@@ -6,9 +6,9 @@ A transformation is something that takes a list of nodes as an input, and return
Currently, the following components are Transformation objects:
- [SentenceSplitter](/docs/api/classes/SentenceSplitter)
- [MetadataExtractor](/docs/llamaindex/modules/documents_and_nodes/metadata_extraction)
- [Embeddings](/docs/llamaindex/modules/embeddings)
- [SentenceSplitter](/docs/llamaindex/modules/data/ingestion_pipeline/transformations/node-parser)
- [MetadataExtractor](/docs/llamaindex/modules/data/ingestion_pipeline/transformations/metadata_extraction)
- [Embeddings](/docs/llamaindex/modules/models/embeddings)
## Usage Pattern
@@ -1,5 +1,5 @@
---
title: Metadata Extraction Usage Pattern
title: Metadata Extraction
---
You can use LLMs to automate metadata extraction with our `Metadata Extractor` modules.
@@ -2,17 +2,15 @@
title: Node Parsers / Text Splitters
description: Learn how to use Node Parsers and Text Splitters to extract data from documents.
---
import { CodeNodeParserDemo } from '../../../../../components/demo/code-node-parser.tsx';
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
Node parsers are a simple abstraction that take a list of documents, and chunk them into `Node` objects, such that each node is a specific chunk of the parent document. When a document is broken into nodes, all of it's attributes are inherited to the children nodes (i.e. `metadata`, text and metadata templates, etc.). You can read more about `Node` and `Document` properties [here](/docs/llamaindex/modules/loading).
## NodeParser
The `NodeParser` in LlamaIndex is responsible for splitting `Document` objects into more manageable `Node` objects.
Node parsers are a simple abstraction that take a list of `Document` objects, and chunk them into `Node` objects, such that each node is a specific chunk of the parent document. When a document is broken into nodes, all of it's attributes are inherited to the children nodes (i.e. `metadata`, text and metadata templates, etc.). You can read more about `Node` and `Document` properties [here](/docs/llamaindex/modules/data).
By default, we will use `Settings.nodeParser` to split the document into nodes. You can also assign a custom `NodeParser` to the `Settings` object.
## SentenceSplitter
The `SentenceSplitter` is the default `NodeParser` in LlamaIndex. It will split the text from a `Document` into sentences.
```ts twoslash
import { TextFileReader } from '@llamaindex/readers/text'
import { SentenceSplitter } from 'llamaindex';
@@ -23,8 +21,6 @@ Settings.nodeParser = nodeParser;
// ^?
```
## TextSplitter
The underlying text splitter will split text by sentences. It can also be used as a standalone module for splitting raw text.
```ts twoslash
@@ -68,6 +64,46 @@ The `MarkdownNodeParser` is a more advanced `NodeParser` that can handle markdow
```
</Tabs>
The output metadata will be something like:
```bash
[
TextNode {
id_: '008e41a8-b097-487c-bee8-bd88b9455844',
metadata: { 'Header 1': 'Main Header' },
excludedEmbedMetadataKeys: [],
excludedLlmMetadataKeys: [],
relationships: { PARENT: [Array] },
hash: 'KJ5e/um/RkHaNR6bonj9ormtZY7I8i4XBPVYHXv1A5M=',
text: 'Main Header\nMain content',
textTemplate: '',
metadataSeparator: '\n'
},
TextNode {
id_: '0f5679b3-ba63-4aff-aedc-830c4208d0b5',
metadata: { 'Header 1': 'Header 2' },
excludedEmbedMetadataKeys: [],
excludedLlmMetadataKeys: [],
relationships: { PARENT: [Array] },
hash: 'IP/g/dIld3DcbK+uHzDpyeZ9IdOXY4brxhOIe7wc488=',
text: 'Header 2\nHeader 2 content',
textTemplate: '',
metadataSeparator: '\n'
},
TextNode {
id_: 'e81e9bd0-121c-4ead-8ca7-1639d65fdf90',
metadata: { 'Header 1': 'Header 2', 'Header 2': 'Sub-header' },
excludedEmbedMetadataKeys: [],
excludedLlmMetadataKeys: [],
relationships: { PARENT: [Array] },
hash: 'B3kYNnxaYi9ghtAgwza0ZEVKF4MozobkNUlcekDL7JQ=',
text: 'Sub-header\nSub-header content',
textTemplate: '',
metadataSeparator: '\n'
}
]
```
## CodeSplitter
The `CodeSplitter` is a more advanced `NodeParser` that can handle code documents.
@@ -113,8 +149,6 @@ Try it out ⬇️
<CodeNodeParserDemo/>
import { Accordion, Accordions } from 'fumadocs-ui/components/accordion';
<Accordions>
<Accordion title="Use it in browser">
You might setup WASM files for `web-tree-sitter` and use it in the browser.
@@ -155,3 +189,9 @@ import { Accordion, Accordions } from 'fumadocs-ui/components/accordion';
```
</Accordion>
</Accordions>
## API Reference
- [SentenceSplitter](/docs/api/classes/SentenceSplitter)
- [MarkdownNodeParser](/docs/api/classes/MarkdownNodeParser)
- [CodeSplitter](/docs/api/classes/CodeSplitter)
@@ -0,0 +1,4 @@
{
"title": "Data",
"pages": ["index", "readers", "data_index", "ingestion_pipeline", "stores"]
}
@@ -2,9 +2,6 @@
title: DiscordReader
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../../examples/readers/src/discord";
DiscordReader is a simple data loader that reads all messages in a given Discord channel and returns them as Document objects.
It uses the [@discordjs/rest](https://github.com/discordjs/discord.js/tree/main/packages/rest) library to fetch the messages.
@@ -15,7 +12,7 @@ In your Discord Application, go to the `OAuth2` tab and generate an invite URL b
This will invite the bot with the necessary permissions to read messages.
Copy the URL in your browser and select the server you want your bot to join.
<DynamicCodeBlock lang="ts" code={CodeSource} />
<include cwd>../../examples/readers/src/discord.ts</include>
### Params
@@ -0,0 +1,127 @@
---
title: Loading Data
description: Loading data using Readers into Documents
---
Before you can start indexing your documents, you need to load them into memory.
A reader is a module that loads data from a file into a `Document` object.
To install readers call:
<Accordions>
<Accordion title="Install @llamaindex/readers">
If you want to use the reader module, you need to install `@llamaindex/readers`
```package-install
npm i @llamaindex/readers
```
</Accordion>
</Accordions>
We offer readers for different file formats.
```ts twoslash
import { CSVReader } from '@llamaindex/readers/csv'
import { PDFReader } from '@llamaindex/readers/pdf'
import { JSONReader } from '@llamaindex/readers/json'
import { MarkdownReader } from '@llamaindex/readers/markdown'
import { HTMLReader } from '@llamaindex/readers/html'
// you can find more readers in the documentation
```
Additionally the following loaders exist without separate documentation:
- `AssemblyAIReader` transcribes audio using [AssemblyAI](https://www.assemblyai.com/).
- [AudioTranscriptReader](/docs/api/classes/AudioTranscriptReader): loads entire transcript as a single document.
- [AudioTranscriptParagraphsReader](/docs/api/classes/AudioTranscriptParagraphsReader): creates a document per paragraph.
- [AudioTranscriptSentencesReader](/docs/api/classes/AudioTranscriptSentencesReader): creates a document per sentence.
- [AudioSubtitlesReader](/docs/api/classes/AudioTranscriptParagraphsReader): creates a document containing the subtitles of a transcript.
- [NotionReader](/docs/api/classes/NotionReader) loads [Notion](https://www.notion.so/) pages.
- [SimpleMongoReader](/docs/api/classes/SimpleMongoReader) loads data from a [MongoDB](https://www.mongodb.com/).
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
## SimpleDirectoryReader
[Open in StackBlitz](https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples/readers?file=src/simple-directory-reader.ts&title=Simple%20Directory%20Reader)
LlamaIndex.TS supports easy loading of files from folders using the `SimpleDirectoryReader` class.
It is a simple reader that reads all files from a directory and its subdirectories and delegates the actual reading to the reader specified in the `fileExtToReader` map.
<include cwd>../../examples/readers/src/simple-directory-reader.ts</include>
Currently, the following readers are mapped to specific file types:
- [TextFileReader](/docs/api/classes/TextFileReader): `.txt`
- [PDFReader](/docs/api/classes/PDFReader): `.pdf`
- [CSVReader](/docs/api/classes/CSVReader): `.csv`
- [MarkdownReader](/docs/api/classes/MarkdownReader): `.md`
- [DocxReader](/docs/api/classes/DocxReader): `.docx`
- [HTMLReader](/docs/api/classes/HTMLReader): `.htm`, `.html`
- [ImageReader](/docs/api/classes/ImageReader): `.jpg`, `.jpeg`, `.png`, `.gif`
You can modify the reader three different ways:
- `overrideReader` overrides the reader for all file types, including unsupported ones.
- `fileExtToReader` maps a reader to a specific file type. Can override reader for existing file types or add support for new file types.
- `defaultReader` sets a fallback reader for files with unsupported extensions. By default it is `TextFileReader`.
SimpleDirectoryReader supports up to 9 concurrent requests. Use the `numWorkers` option to set the number of concurrent requests. By default it runs in sequential mode, i.e. set to 1.
### Example
<include cwd>../../examples/readers/src/custom-simple-directory-reader.ts</include>
## Tips when using in non-Node.js environments
When using `@llamaindex/readers` in a non-Node.js environment (such as Vercel Edge, Cloudflare Workers, etc.)
Some classes are not exported from top-level entry file.
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`).
If you need any of those classes, you have to import them instead directly through their file path in the package.
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/directory";
import { LlamaParseReader } from "@llamaindex/cloud";
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 explicitly 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
## Load file natively using Node.js Customization Hooks
We have a helper utility to allow you to import a file in Node.js script.
```shell
node --import @llamaindex/readers/node ./script.js
```
```ts
import csv from './path/to/data.csv';
const text = csv.getText()
```
## API Reference
- [SimpleDirectoryReader](/docs/api/classes/SimpleDirectoryReader)
@@ -8,21 +8,9 @@ Supports streaming of large JSON data using [@discoveryjs/json-ext](https://gith
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/readers
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/readers
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/readers
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/readers
```
## Usage
@@ -6,21 +6,9 @@ LlamaParse `json` mode supports extracting any images found in a page object by
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/cloud @llamaindex/openai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/cloud @llamaindex/openai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/cloud @llamaindex/openai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/cloud @llamaindex/openai
```
## Usage
@@ -2,10 +2,6 @@
title: LlamaParse
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../../../examples/readers/src/llamaparse";
import CodeSource2 from "!raw-loader!../../../../../../../../../examples/readers/src/simple-directory-reader-with-llamaparse.ts";
LlamaParse is an API created by LlamaIndex to efficiently parse files, e.g. it's great at converting PDF tables into markdown.
To use it, first login and get an API key from https://cloud.llamaindex.ai. Make sure to store the key as `apiKey` parameter or in the environment variable `LLAMA_CLOUD_API_KEY`.
@@ -17,7 +13,7 @@ Official documentation for LlamaParse can be found [here](https://docs.cloud.lla
You can then use the `LlamaParseReader` class to load local files and convert them into a parsed document that can be used by LlamaIndex.
See [reader.ts](https://github.com/run-llama/LlamaIndexTS/blob/main/packages/cloud/src/reader.ts) for a list of supported file types:
<DynamicCodeBlock lang="ts" code={CodeSource} />
<include cwd>../../examples/readers/src/llamaparse.ts</include>
### Params
@@ -60,7 +56,7 @@ They can be divided into two groups.
Below a full example of `LlamaParse` integrated in `SimpleDirectoryReader` with additional options.
<DynamicCodeBlock lang="ts" code={CodeSource2} />
<include cwd>../../examples/readers/src/simple-directory-reader-with-llamaparse.ts</include>
## API Reference
@@ -6,21 +6,9 @@ In JSON mode, LlamaParse will return a data structure representing the parsed ob
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/cloud
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/cloud
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/cloud
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/cloud
```
## Usage
@@ -6,7 +6,7 @@ Chat stores manage chat history by storing sequences of messages in a structured
## Available Chat Stores
- [SimpleChatStore](/docs/api/classes/SimpleChatStore): A simple in-memory chat store with support for [persisting](/docs/llamaindex/modules/data_stores#local-storage) data to disk.
- [SimpleChatStore](/docs/api/classes/SimpleChatStore): A simple in-memory chat store with support for [persisting](/docs/llamaindex/modules/data/stores#local-storage) data to disk.
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
@@ -2,32 +2,20 @@
title: Document Stores
---
Document stores contain ingested document chunks, i.e. [Node](/docs/llamaindex/modules/documents_and_nodes)s.
Document stores contain ingested document chunks, i.e. [Node](/docs/llamaindex/modules/data)s.
## Available Document Stores
- [SimpleDocumentStore](/docs/api/classes/SimpleDocumentStore): A simple in-memory document store with support for [persisting](/docs/llamaindex/modules/data_stores#local-storage) data to disk.
- [PostgresDocumentStore](/docs/api/classes/PostgresDocumentStore): A PostgreSQL document store, see [PostgreSQL Storage](/docs/llamaindex/modules/data_stores#postgresql-storage).
- [SimpleDocumentStore](/docs/api/classes/SimpleDocumentStore): A simple in-memory document store with support for [persisting](/docs/llamaindex/modules/data/stores#local-storage) data to disk.
- [PostgresDocumentStore](/docs/api/classes/PostgresDocumentStore): A PostgreSQL document store, see [PostgreSQL Storage](/docs/llamaindex/modules/data/stores#postgresql-storage).
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
## Using PostgreSQL as Document Store
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/postgres
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/postgres
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/postgres
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/postgres
```
You can configure the `schemaName`, `tableName`, `namespace`, and
`connectionString`. If a `connectionString` is not
@@ -2,32 +2,20 @@
title: Index Stores
---
Index stores are underlying storage components that contain metadata(i.e. information created when indexing) about the [index](/docs/llamaindex/modules/data_index) itself.
Index stores are underlying storage components that contain metadata(i.e. information created when indexing) about the [index](/docs/llamaindex/modules/data/data_index) itself.
## Available Index Stores
- [SimpleIndexStore](/docs/api/classes/SimpleIndexStore): A simple in-memory index store with support for [persisting](/docs/llamaindex/modules/data_stores#local-storage) data to disk.
- [PostgresIndexStore](/docs/api/classes/PostgresIndexStore): A PostgreSQL index store, , see [PostgreSQL Storage](/docs/llamaindex/modules/data_stores#postgresql-storage).
- [SimpleIndexStore](/docs/api/classes/SimpleIndexStore): A simple in-memory index store with support for [persisting](/docs/llamaindex/modules/data/stores#local-storage) data to disk.
- [PostgresIndexStore](/docs/api/classes/PostgresIndexStore): A PostgreSQL index store, , see [PostgreSQL Storage](/docs/llamaindex/modules/data/stores#postgresql-storage).
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
## Using PostgreSQL as Index Store
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/postgres
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/postgres
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/postgres
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/postgres
```
You can configure the `schemaName`, `tableName`, `namespace`, and
`connectionString`. If a `connectionString` is not
@@ -2,12 +2,12 @@
title: Key-Value Stores
---
Key-Value Stores represent underlying storage components used in [Document Stores](/docs/llamaindex/modules/data_stores/doc_stores) and [Index Stores](/docs/llamaindex/modules/data_stores/index_stores)
Key-Value Stores represent underlying storage components used in [Document Stores](/docs/llamaindex/modules/data/stores/doc_stores) and [Index Stores](/docs/llamaindex/modules/data/stores/index_stores)
## Available Key-Value Stores
- [SimpleKVStore](/docs/api/classes/SimpleKVStore): A simple Key-Value store with support of [persisting](/docs/llamaindex/modules/data_stores#local-storage) data to disk.
- [PostgresKVStore](/docs/api/classes/PostgresKVStore): A PostgreSQL Key-Value store, see [PostgreSQL Storage](/docs/llamaindex/modules/data_stores#postgresql-storage).
- [SimpleKVStore](/docs/api/classes/SimpleKVStore): A simple Key-Value store with support of [persisting](/docs/llamaindex/modules/data/stores#local-storage) data to disk.
- [PostgresKVStore](/docs/api/classes/PostgresKVStore): A PostgreSQL Key-Value store, see [PostgreSQL Storage](/docs/llamaindex/modules/data/stores#postgresql-storage).
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
@@ -8,7 +8,7 @@ Vector stores save embedding vectors of your ingested document chunks.
Available Vector Stores are shown on the sidebar to the left. Additionally the following integrations exist without separate documentation:
- [SimpleVectorStore](/docs/api/classes/SimpleVectorStore): A simple in-memory vector store with optional [persistance](/docs/llamaindex/modules/data_stores#local-storage) to disk.
- [SimpleVectorStore](/docs/api/classes/SimpleVectorStore): A simple in-memory vector store with optional [persistance](/docs/llamaindex/modules/data/stores#local-storage) to disk.
- [AstraDBVectorStore](/docs/api/classes/AstraDBVectorStore): A cloud-native, scalable Database-as-a-Service built on Apache Cassandra, see [datastax.com](https://www.datastax.com/products/datastax-astra)
- [ChromaVectorStore](/docs/api/classes/ChromaVectorStore): An open-source vector database, focused on ease of use and performance, see [trychroma.com](https://www.trychroma.com/)
- [MilvusVectorStore](/docs/api/classes/MilvusVectorStore): An open-source, high-performance, highly scalable vector database, see [milvus.io](https://milvus.io/)
@@ -13,21 +13,9 @@ docker run -p 6333:6333 qdrant/qdrant
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/qdrant
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/qdrant
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/qdrant
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/qdrant
```
## Importing the modules
@@ -8,21 +8,9 @@ To use this vector store, you need a Supabase project. You can create one at [su
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/supabase
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/supabase
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/supabase
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/supabase
```
## Database Setup
@@ -1,58 +0,0 @@
---
title: Loader
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../../examples/readers/src/simple-directory-reader";
import CodeSource2 from "!raw-loader!../../../../../../../../examples/readers/src/custom-simple-directory-reader";
Before you can start indexing your documents, you need to load them into memory.
All "basic" data loaders can be seen below, mapped to their respective filetypes in `SimpleDirectoryReader`. More loaders are shown in the sidebar on the left.
Additionally the following loaders exist without separate documentation:
- `AssemblyAIReader` transcribes audio using [AssemblyAI](https://www.assemblyai.com/).
- [AudioTranscriptReader](/docs/api/classes/AudioTranscriptReader): loads entire transcript as a single document.
- [AudioTranscriptParagraphsReader](/docs/api/classes/AudioTranscriptParagraphsReader): creates a document per paragraph.
- [AudioTranscriptSentencesReader](/docs/api/classes/AudioTranscriptSentencesReader): creates a document per sentence.
- [AudioSubtitlesReader](/docs/api/classes/AudioTranscriptParagraphsReader): creates a document containing the subtitles of a transcript.
- [NotionReader](/docs/api/classes/NotionReader) loads [Notion](https://www.notion.so/) pages.
- [SimpleMongoReader](/docs/api/classes/SimpleMongoReader) loads data from a [MongoDB](https://www.mongodb.com/).
Check the [LlamaIndexTS Github](https://github.com/run-llama/LlamaIndexTS) for the most up to date overview of integrations.
## SimpleDirectoryReader
[Open in StackBlitz](https://stackblitz.com/github/run-llama/LlamaIndexTS/tree/main/examples/readers?file=src/simple-directory-reader.ts&title=Simple%20Directory%20Reader)
LlamaIndex.TS supports easy loading of files from folders using the `SimpleDirectoryReader` class.
It is a simple reader that reads all files from a directory and its subdirectories.
<DynamicCodeBlock lang="ts" code={CodeSource} />
Currently, the following readers are mapped to specific file types:
- [TextFileReader](/docs/api/classes/TextFileReader): `.txt`
- [PDFReader](/docs/api/classes/PDFReader): `.pdf`
- [CSVReader](/docs/api/classes/CSVReader): `.csv`
- [MarkdownReader](/docs/api/classes/MarkdownReader): `.md`
- [DocxReader](/docs/api/classes/DocxReader): `.docx`
- [HTMLReader](/docs/api/classes/HTMLReader): `.htm`, `.html`
- [ImageReader](/docs/api/classes/ImageReader): `.jpg`, `.jpeg`, `.png`, `.gif`
You can modify the reader three different ways:
- `overrideReader` overrides the reader for all file types, including unsupported ones.
- `fileExtToReader` maps a reader to a specific file type. Can override reader for existing file types or add support for new file types.
- `defaultReader` sets a fallback reader for files with unsupported extensions. By default it is `TextFileReader`.
SimpleDirectoryReader supports up to 9 concurrent requests. Use the `numWorkers` option to set the number of concurrent requests. By default it runs in sequential mode, i.e. set to 1.
### Example
<DynamicCodeBlock lang="ts" code={CodeSource2} />
## API Reference
- [SimpleDirectoryReader](/docs/api/classes/SimpleDirectoryReader)
@@ -1,16 +0,0 @@
---
title: Documents and Nodes
---
`Document`s and `Node`s are the basic building blocks of any index. While the API for these objects is similar, `Document` objects represent entire files, while `Node`s are smaller pieces of that original document, that are suitable for an LLM and Q&A.
```typescript
import { Document } from "llamaindex";
document = new Document({ text: "text", metadata: { key: "val" } });
```
## API Reference
- [Document](/docs/api/classes/Document)
- [TextNode](/docs/api/classes/TextNode)
@@ -10,21 +10,9 @@ This is useful for measuring if the response was correct. The evaluator returns
Firstly, you need to install the package:
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/openai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/openai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/openai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/openai
```
Set the OpenAI API key:
@@ -12,22 +12,9 @@ This is useful for measuring if the response was hallucinated. The evaluator ret
Firstly, you need to install the package:
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/openai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/openai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/openai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/openai
```
Set the OpenAI API key:
@@ -10,22 +10,9 @@ It is useful for measuring if the response was relevant to the query. The evalua
Firstly, you need to install the package:
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/openai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/openai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/openai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/openai
```
Set the OpenAI API key:
@@ -1,34 +0,0 @@
---
title: LlamaCloud
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../examples/cloud/chat.ts";
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.
Currently, LlamaCloud supports
- Managed Ingestion API, handling parsing and document management
- Managed Retrieval API, configuring optimal retrieval for your RAG system
## Access
We are opening up a private beta to a limited set of enterprise partners for the managed ingestion and retrieval API. If youre interested in centralizing your data pipelines and spending more time working on your actual RAG use cases, come [talk to us.](https://www.llamaindex.ai/contact)
If you have access to LlamaCloud, you can visit [LlamaCloud](https://cloud.llamaindex.ai) to sign in and get an API key.
## Create a Managed Index
Currently, you can't create a managed index on LlamaCloud using LlamaIndexTS, but you can use an existing managed index for retrieval that was created by the Python version of LlamaIndex. See [the LlamaCloudIndex documentation](https://docs.llamaindex.ai/en/stable/module_guides/indexing/llama_cloud_index.html#usage) for more information on how to create a managed index.
## Use a Managed Index
Here's an example of how to use a managed index together with a chat engine:
<DynamicCodeBlock lang="ts" code={CodeSource} />
## API Reference
- [LlamaCloudIndex](/docs/api/classes/LlamaCloudIndex)
- [LlamaCloudRetriever](/docs/api/classes/LlamaCloudRetriever)
@@ -1,106 +0,0 @@
---
title: Document and Nodes
description: llamaindex readers is a collection of readers for different file formats.
---
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
import { Accordion, Accordions } from 'fumadocs-ui/components/accordion';
<Accordions>
<Accordion title="Install @llamaindex/readers">
If you want to use the reader module, you need to install `@llamaindex/readers`
<Tabs groupId="install-llamaindex" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install @llamaindex/readers
```
```shell tab="yarn"
yarn add @llamaindex/readers
```
```shell tab="pnpm"
pnpm add @llamaindex/readers
```
</Tabs>
</Accordion>
</Accordions>
We offer readers for different file formats.
```ts twoslash
import { CSVReader } from '@llamaindex/readers/csv'
import { PDFReader } from '@llamaindex/readers/pdf'
import { JSONReader } from '@llamaindex/readers/json'
import { MarkdownReader } from '@llamaindex/readers/markdown'
import { HTMLReader } from '@llamaindex/readers/html'
// you can find more readers in the documentation
```
## SimpleDirectoryReader
`SimpleDirectoryReader` is the simplest way to load data from local files into LlamaIndex.
```ts twoslash
import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
const reader = new SimpleDirectoryReader()
const documents = await reader.loadData("./data")
// ^?
const texts = documents.map(doc => doc.getText())
// ^?
```
## Tips when using in non-Node.js environments
When using `@llamaindex/readers` in a non-Node.js environment (such as Vercel Edge, Cloudflare Workers, etc.)
Some classes are not exported from top-level entry file.
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`).
If you need any of those classes, you have to import them instead directly through their file path in the package.
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/directory";
import { LlamaParseReader } from "@llamaindex/cloud";
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 explicitly 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
## Load file natively using Node.js Customization Hooks
We have a helper utility to allow you to import a file in Node.js script.
```shell
node --import @llamaindex/readers/node ./script.js
```
```ts
import csv from './path/to/data.csv';
const text = csv.getText()
```
@@ -1,5 +0,0 @@
{
"title": "Loading Data",
"description": "Loading Data using LlamaIndex.TS",
"pages": ["index", "node-parser"]
}
@@ -0,0 +1,4 @@
{
"title": "Modules",
"pages": ["models", "agents", "data", "rag", "ui", "evaluation"]
}
@@ -7,21 +7,9 @@ Check out available embedding models [here](https://deepinfra.com/models/embeddi
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/deepinfra
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/deepinfra
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/deepinfra
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/deepinfra
```
```ts
import { Document, Settings, VectorStoreIndex } from "llamaindex";
@@ -6,21 +6,9 @@ To use Gemini embeddings, you need to import `GeminiEmbedding` from `@llamaindex
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/google
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/google
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/google
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/google
```
```ts
import { Document, Settings, VectorStoreIndex } from "llamaindex";
@@ -6,21 +6,9 @@ To use HuggingFace embeddings, you need to import `HuggingFaceEmbedding` from `@
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/huggingface
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/huggingface
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/huggingface
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/huggingface
```
```ts
import { Document, Settings, VectorStoreIndex } from "llamaindex";
@@ -8,21 +8,9 @@ This can be explicitly updated through `Settings.embedModel`.
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/openai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/openai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/openai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/openai
```
```typescript
import { OpenAIEmbedding } from "@llamaindex/openai";
@@ -35,7 +23,7 @@ Settings.embedModel = new OpenAIEmbedding({
## Local Embedding
For local embeddings, you can use the [HuggingFace](/docs/llamaindex/modules/embeddings/huggingface) embedding model.
For local embeddings, you can use the [HuggingFace](/docs/llamaindex/modules/models/embeddings/huggingface) embedding model.
## Local Ollama Embeddings With Remote Host
@@ -6,21 +6,9 @@ To use MistralAI embeddings, you need to import `MistralAIEmbedding` from `@llam
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/mistral
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/mistral
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/mistral
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/mistral
```
```ts
import { Document, Settings, VectorStoreIndex } from "llamaindex";
@@ -14,22 +14,9 @@ To find out more about the latest features, updates, and available models, visit
## Setup
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/mixedbread
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/mixedbread
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/mixedbread
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/mixedbread
```
Next, sign up for an API key at [mixedbread.ai](https://mixedbread.ai/). Once you have your API key, you can import the necessary modules and create a new instance of the `MixedbreadAIEmbeddings` class.
@@ -14,21 +14,9 @@ ollama pull nomic-embed-text
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/ollama
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/ollama
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/ollama
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/ollama
```
```ts
import { OllamaEmbedding } from "@llamaindex/ollama";
@@ -6,21 +6,9 @@ To use OpenAI embeddings, you need to import `OpenAIEmbedding` from `@llamaindex
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/openai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/openai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/openai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/openai
```
```ts
import { OpenAIEmbedding } from "@llamaindex/openai";
@@ -6,21 +6,9 @@ To use VoyageAI embeddings, you need to import `VoyageAIEmbedding` from `@llamai
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/voyage-ai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/voyage-ai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/voyage-ai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/voyage-ai
```
```ts
import { VoyageAIEmbedding } from "@llamaindex/voyage-ai";
@@ -4,21 +4,9 @@ title: Anthropic
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/anthropic
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/anthropic
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/anthropic
```
</Tabs>
```shell tab="npm"
npm i llamaindex @llamaindex/anthropic
```
## Usage
@@ -16,21 +16,9 @@ export AZURE_OPENAI_DEPLOYMENT="gpt-4" # or some other deployment name
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/openai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/openai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/openai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/openai
```
## Usage
@@ -4,21 +4,9 @@ title: Bedrock
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/community
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/community
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/community
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/community
```
## Usage
@@ -57,6 +45,7 @@ META_LLAMA3_2_1B_INSTRUCT = "meta.llama3-2-1b-instruct-v1:0"; // only available
META_LLAMA3_2_3B_INSTRUCT = "meta.llama3-2-3b-instruct-v1:0"; // only available via inference endpoints (see below)
META_LLAMA3_2_11B_INSTRUCT = "meta.llama3-2-11b-instruct-v1:0"; // only available via inference endpoints (see below), multimodal and function call supported
META_LLAMA3_2_90B_INSTRUCT = "meta.llama3-2-90b-instruct-v1:0"; // only available via inference endpoints (see below), multimodal and function call supported
AMAZON_NOVA_PREMIER_1 = "amazon.nova-premier-v1:0";
AMAZON_NOVA_PRO_1 = "amazon.nova-pro-v1:0";
AMAZON_NOVA_LITE_1 = "amazon.nova-lite-v1:0";
AMAZON_NOVA_MICRO_1 = "amazon.nova-micro-v1:0";
@@ -76,6 +65,7 @@ US_META_LLAMA_3_2_1B_INSTRUCT = "us.meta.llama3-2-1b-instruct-v1:0";
US_META_LLAMA_3_2_3B_INSTRUCT = "us.meta.llama3-2-3b-instruct-v1:0";
US_META_LLAMA_3_2_11B_INSTRUCT = "us.meta.llama3-2-11b-instruct-v1:0";
US_META_LLAMA_3_2_90B_INSTRUCT = "us.meta.llama3-2-90b-instruct-v1:0";
US_AMAZON_NOVA_PRO_1 = "us.amazon.nova-premier-v1:0";
US_AMAZON_NOVA_PRO_1 = "us.amazon.nova-pro-v1:0";
US_AMAZON_NOVA_LITE_1 = "us.amazon.nova-lite-v1:0";
US_AMAZON_NOVA_MICRO_1 = "us.amazon.nova-micro-v1:0";
@@ -86,6 +76,10 @@ EU_ANTHROPIC_CLAUDE_3_SONNET = "eu.anthropic.claude-3-sonnet-20240229-v1:0";
EU_ANTHROPIC_CLAUDE_3_5_SONNET = "eu.anthropic.claude-3-5-sonnet-20240620-v1:0";
EU_META_LLAMA_3_2_1B_INSTRUCT = "eu.meta.llama3-2-1b-instruct-v1:0";
EU_META_LLAMA_3_2_3B_INSTRUCT = "eu.meta.llama3-2-3b-instruct-v1:0";
EU_AMAZON_NOVA_PRO_1 = "eu.amazon.nova-premier-v1:0";
EU_AMAZON_NOVA_PRO_1 = "eu.amazon.nova-pro-v1:0";
EU_AMAZON_NOVA_LITE_1 = "eu.amazon.nova-lite-v1:0";
EU_AMAZON_NOVA_MICRO_1 = "eu.amazon.nova-micro-v1:0";
```
Sonnet, Haiku and Opus are multimodal, image_url only supports base64 data url format, e.g. `data:image/jpeg;base64,SGVsbG8sIFdvcmxkIQ==`
@@ -6,21 +6,9 @@ Check out available LLMs [here](https://deepinfra.com/models/text-generation).
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/deepinfra
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/deepinfra
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/deepinfra
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/deepinfra
```
```ts
import { DeepInfra } from "@llamaindex/deepinfra";
@@ -4,21 +4,9 @@ title: Gemini
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/google
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/google
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/google
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/google
```
## Usage
@@ -69,7 +57,7 @@ const gemini = new Gemini({
To authenticate for local development:
```bash
npm install @google-cloud/vertexai
npm i @google-cloud/vertexai
gcloud auth application-default login
```
@@ -2,26 +2,11 @@
title: Groq
---
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
import CodeSource from "!raw-loader!../../../../../../../../examples/groq.ts";
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/groq
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/groq
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/groq
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/groq
```
## Usage
@@ -70,7 +55,7 @@ const results = await queryEngine.query({
## Full Example
<DynamicCodeBlock lang="ts" code={CodeSource} />
<include cwd>../../examples/groq.ts</include>
## API Reference
@@ -8,21 +8,9 @@ The LLM can be explicitly updated through `Settings`.
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/openai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/openai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/openai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/openai
```
```typescript
import { OpenAI } from "@llamaindex/openai";
@@ -45,7 +33,7 @@ export AZURE_OPENAI_DEPLOYMENT="gpt-4" # or some other deployment name
## Local LLM
For local LLMs, currently we recommend the use of [Ollama](/docs/llamaindex/modules/llms/ollama) LLM.
For local LLMs, currently we recommend the use of [Ollama](/docs/llamaindex/modules/models/llms/ollama) LLM.
## Available LLMs
@@ -4,21 +4,9 @@ title: LLama2
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/replicate
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/replicate
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/replicate
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/replicate
```
## Usage
@@ -4,21 +4,9 @@ title: Mistral
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/mistral
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/mistral
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/mistral
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/mistral
```
## Usage
@@ -4,22 +4,9 @@ title: Ollama
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/ollama
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/ollama
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/ollama
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/ollama
```
## Usage
@@ -4,22 +4,9 @@ title: OpenAI
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/openai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/openai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/openai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/openai
```
```ts
import { OpenAI } from "@llamaindex/openai";
@@ -4,21 +4,9 @@ title: Perplexity LLM
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install @llamaindex/perplexity
```
```shell tab="yarn"
yarn add @llamaindex/perplexity
```
```shell tab="pnpm"
pnpm add @llamaindex/perplexity
```
</Tabs>
```package-install
npm i @llamaindex/perplexity
```
## Usage
@@ -4,22 +4,9 @@ title: Portkey LLM
## Installation
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
```shell tab="npm"
npm install llamaindex @llamaindex/portkey-ai
```
```shell tab="yarn"
yarn add llamaindex @llamaindex/portkey-ai
```
```shell tab="pnpm"
pnpm add llamaindex @llamaindex/portkey-ai
```
</Tabs>
```package-install
npm i llamaindex @llamaindex/portkey-ai
```
## Usage

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