mirror of
https://github.com/run-llama/LlamaIndexTS.git
synced 2026-07-01 22:14:03 -04:00
Compare commits
32 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 5478ba88b1 | |||
| aea550aff4 | |||
| e66c6e25fb | |||
| 40ee7610b2 | |||
| c14a21bc0b | |||
| 33f98565ab | |||
| b5cb35a732 | |||
| c1b5be5182 | |||
| 6f8b68ac5f | |||
| e075643b50 | |||
| f71b143ceb | |||
| ead4a80a3a | |||
| da78689e24 | |||
| f24a9dfe00 | |||
| e31d6ba472 | |||
| d212240d64 | |||
| cb73f77bb8 | |||
| 8bf1ca1701 | |||
| 58b3ee52e0 | |||
| 4bac71d6a2 | |||
| a3cbcb31a2 | |||
| bbc8c8787d | |||
| 4b49428f57 | |||
| 7ee4968b06 | |||
| 0111f5c8b0 | |||
| beb922b743 | |||
| e28c29d1f5 | |||
| 008cccd9f1 | |||
| 081698d68c | |||
| ab5fe5d7a0 | |||
| 56689707d3 | |||
| fd74ba4bf1 |
@@ -1,5 +1,70 @@
|
||||
# @llamaindex/doc
|
||||
|
||||
## 0.1.10
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [aea550a]
|
||||
- Updated dependencies [c1b5be5]
|
||||
- Updated dependencies [40ee761]
|
||||
- Updated dependencies [40ee761]
|
||||
- @llamaindex/openai@0.1.60
|
||||
- llamaindex@0.9.10
|
||||
- @llamaindex/workflow@0.0.16
|
||||
- @llamaindex/core@0.5.8
|
||||
- @llamaindex/cloud@3.0.9
|
||||
- @llamaindex/node-parser@1.0.8
|
||||
- @llamaindex/readers@2.0.8
|
||||
|
||||
## 0.1.9
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 4bac71d: Support binding additional argument to function tool
|
||||
- Updated dependencies [4bac71d]
|
||||
- @llamaindex/core@0.5.7
|
||||
- @llamaindex/cloud@3.0.8
|
||||
- llamaindex@0.9.9
|
||||
- @llamaindex/node-parser@1.0.7
|
||||
- @llamaindex/openai@0.1.59
|
||||
- @llamaindex/readers@2.0.7
|
||||
- @llamaindex/workflow@0.0.15
|
||||
|
||||
## 0.1.8
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [4b49428]
|
||||
- Updated dependencies [bbc8c87]
|
||||
- @llamaindex/workflow@0.0.14
|
||||
- llamaindex@0.9.8
|
||||
|
||||
## 0.1.7
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [beb922b]
|
||||
- @llamaindex/core@0.5.6
|
||||
- llamaindex@0.9.7
|
||||
- @llamaindex/cloud@3.0.7
|
||||
- @llamaindex/node-parser@1.0.6
|
||||
- @llamaindex/openai@0.1.58
|
||||
- @llamaindex/readers@2.0.6
|
||||
- @llamaindex/workflow@0.0.13
|
||||
|
||||
## 0.1.6
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [5668970]
|
||||
- @llamaindex/core@0.5.5
|
||||
- @llamaindex/workflow@0.0.12
|
||||
- @llamaindex/cloud@3.0.6
|
||||
- llamaindex@0.9.6
|
||||
- @llamaindex/node-parser@1.0.5
|
||||
- @llamaindex/openai@0.1.57
|
||||
- @llamaindex/readers@2.0.5
|
||||
|
||||
## 0.1.5
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -5,8 +5,15 @@ const withMDX = createMDX();
|
||||
/** @type {import('next').NextConfig} */
|
||||
const config = {
|
||||
reactStrictMode: true,
|
||||
eslint: {
|
||||
ignoreDuringBuilds: true,
|
||||
},
|
||||
transpilePackages: ["monaco-editor"],
|
||||
serverExternalPackages: ["@huggingface/transformers"],
|
||||
serverExternalPackages: [
|
||||
"@huggingface/transformers",
|
||||
"twoslash",
|
||||
"typescript",
|
||||
],
|
||||
webpack: (config, { isServer }) => {
|
||||
if (Array.isArray(config.target) && config.target.includes("web")) {
|
||||
config.target = ["web", "es2020"];
|
||||
|
||||
+26
-25
@@ -1,18 +1,19 @@
|
||||
{
|
||||
"name": "@llamaindex/doc",
|
||||
"version": "0.1.5",
|
||||
"version": "0.1.10",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"build": "pnpm run build:docs && next build",
|
||||
"postinstall": "fumadocs-mdx",
|
||||
"prebuild": "pnpm run build:docs",
|
||||
"build": "next build",
|
||||
"dev": "next dev",
|
||||
"start": "next start",
|
||||
"postdev": "fumadocs-mdx",
|
||||
"postbuild": "fumadocs-mdx && tsx scripts/post-build.mts",
|
||||
"build:docs": "cross-env NODE_OPTIONS=\"--max-old-space-size=8192\" typedoc && node ./scripts/generate-docs.mjs"
|
||||
"postbuild": "tsx scripts/post-build.mts",
|
||||
"build:docs": "cross-env NODE_OPTIONS=\"--max-old-space-size=8192\" typedoc && tsx scripts/generate-docs.mts"
|
||||
},
|
||||
"dependencies": {
|
||||
"@icons-pack/react-simple-icons": "^10.1.0",
|
||||
"@llamaindex/chat-ui": "0.0.9",
|
||||
"@llamaindex/chat-ui": "0.2.0",
|
||||
"@llamaindex/cloud": "workspace:*",
|
||||
"@llamaindex/core": "workspace:*",
|
||||
"@llamaindex/node-parser": "workspace:*",
|
||||
@@ -27,36 +28,35 @@
|
||||
"@radix-ui/react-slider": "^1.2.1",
|
||||
"@radix-ui/react-slot": "^1.1.0",
|
||||
"@radix-ui/react-tooltip": "^1.1.4",
|
||||
"@vercel/functions": "^1.5.0",
|
||||
"@scalar/api-client-react": "^1.1.25",
|
||||
"@vercel/functions": "^1.5.0",
|
||||
"ai": "^3.4.33",
|
||||
"class-variance-authority": "^0.7.0",
|
||||
"clsx": "2.1.1",
|
||||
"foxact": "^0.2.41",
|
||||
"framer-motion": "^11.11.17",
|
||||
"fumadocs-core": "^14.7.7",
|
||||
"fumadocs-docgen": "^1.3.7",
|
||||
"fumadocs-mdx": "^11.5.3",
|
||||
"fumadocs-openapi": "^5.12.0",
|
||||
"fumadocs-twoslash": "^2.0.3",
|
||||
"fumadocs-typescript": "^3.0.3",
|
||||
"fumadocs-ui": "^14.7.7",
|
||||
"fumadocs-core": "^15.0.15",
|
||||
"fumadocs-docgen": "^2.0.0",
|
||||
"fumadocs-mdx": "^11.5.6",
|
||||
"fumadocs-openapi": "^6.3.0",
|
||||
"fumadocs-twoslash": "^3.1.0",
|
||||
"fumadocs-typescript": "^3.1.0",
|
||||
"fumadocs-ui": "^15.0.15",
|
||||
"hast-util-to-jsx-runtime": "^2.3.2",
|
||||
"llamaindex": "workspace:*",
|
||||
"lucide-react": "^0.460.0",
|
||||
"next": "15.1.7",
|
||||
"next": "^15.2.1",
|
||||
"next-themes": "^0.4.3",
|
||||
"react": "^19.0.0",
|
||||
"react-dom": "^19.0.0",
|
||||
"react-icons": "^5.3.0",
|
||||
"react-monaco-editor": "^0.56.2",
|
||||
"react-text-transition": "^3.1.0",
|
||||
"react-use-measure": "^2.1.1",
|
||||
"rehype-katex": "^7.0.1",
|
||||
"remark-math": "^6.0.0",
|
||||
"rimraf": "^6.0.1",
|
||||
"shiki": "^2.3.2",
|
||||
"shiki-magic-move": "^1.0.0",
|
||||
"shiki": "^3.1.0",
|
||||
"shiki-magic-move": "^1.0.1",
|
||||
"swr": "^2.2.5",
|
||||
"tailwind-merge": "^2.5.2",
|
||||
"tailwindcss-animate": "^1.0.7",
|
||||
@@ -67,27 +67,28 @@
|
||||
"zod": "^3.23.8"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@next/env": "^15.0.3",
|
||||
"@next/env": "^15.2.1",
|
||||
"@tailwindcss/postcss": "^4.0.9",
|
||||
"@types/mdx": "^2.0.13",
|
||||
"@types/node": "22.9.0",
|
||||
"@types/react": "^18.3.12",
|
||||
"@types/react-dom": "^18.3.1",
|
||||
"@types/react": "^19.0.10",
|
||||
"@types/react-dom": "^19.0.4",
|
||||
"autoprefixer": "^10.4.20",
|
||||
"cross-env": "^7.0.3",
|
||||
"fast-glob": "^3.3.2",
|
||||
"gray-matter": "^4.0.3",
|
||||
"monaco-editor-webpack-plugin": "^7.1.0",
|
||||
"postcss": "^8.4.49",
|
||||
"postcss": "^8.5.3",
|
||||
"raw-loader": "^4.0.2",
|
||||
"remark": "^15.0.1",
|
||||
"remark-gfm": "^4.0.0",
|
||||
"remark-mdx": "^3.1.0",
|
||||
"remark-stringify": "^11.0.0",
|
||||
"tailwindcss": "^3.4.15",
|
||||
"tsx": "^4.19.2",
|
||||
"tailwindcss": "^4.0.9",
|
||||
"tsx": "^4.19.3",
|
||||
"typedoc": "0.27.4",
|
||||
"typedoc-plugin-markdown": "^4.3.1",
|
||||
"typedoc-plugin-merge-modules": "^6.1.0",
|
||||
"typescript": "^5.7.2"
|
||||
"typescript": "^5.7.3"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,6 +0,0 @@
|
||||
module.exports = {
|
||||
plugins: {
|
||||
tailwindcss: {},
|
||||
autoprefixer: {},
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,5 @@
|
||||
export default {
|
||||
plugins: {
|
||||
"@tailwindcss/postcss": {},
|
||||
},
|
||||
};
|
||||
@@ -1,8 +1,7 @@
|
||||
import * as OpenAPI from "fumadocs-openapi";
|
||||
import { generateFiles } from "fumadocs-typescript";
|
||||
import { generateFiles as openapiGenerateFiles } from "fumadocs-openapi";
|
||||
import { generateFiles as typescriptGenerateFiles } from "fumadocs-typescript";
|
||||
import fs from "node:fs";
|
||||
import * as path from "node:path";
|
||||
import { fileURLToPath } from "node:url";
|
||||
import { rimrafSync } from "rimraf";
|
||||
|
||||
const out = "./src/content/docs/cloud/api";
|
||||
@@ -15,28 +14,23 @@ rimrafSync(out, {
|
||||
},
|
||||
});
|
||||
|
||||
void OpenAPI.generateFiles({
|
||||
input: [
|
||||
fileURLToPath(
|
||||
new URL("../../../packages/cloud/openapi.json", import.meta.url),
|
||||
),
|
||||
],
|
||||
output: out,
|
||||
void openapiGenerateFiles({
|
||||
input: ["../../packages/cloud/openapi.json"],
|
||||
output: "./src/content/docs/cloud/api",
|
||||
groupBy: "tag",
|
||||
});
|
||||
|
||||
void generateFiles({
|
||||
void typescriptGenerateFiles({
|
||||
input: ["./src/content/docs/api/**/*.mdx"],
|
||||
output: (file) => path.resolve(path.dirname(file), path.basename(file)),
|
||||
transformOutput,
|
||||
});
|
||||
|
||||
function transformOutput(filePath, content) {
|
||||
function transformOutput(filePath: string, content: string) {
|
||||
const fileName = path.basename(filePath);
|
||||
let title = fileName.split(".")[0];
|
||||
let pageContent = content;
|
||||
if (title === "index") title = "LlamaIndex API Reference";
|
||||
return `---\ntitle: ${title}\n---\n\n${transformAbsoluteUrl(pageContent, filePath)}`;
|
||||
return `---\ntitle: ${title}\n---\n\n${transformAbsoluteUrl(content, filePath)}`;
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -46,20 +40,17 @@ function transformOutput(filePath, content) {
|
||||
* [text](BaseVectorStore.mdx#constructors) -> [text](/docs/api/classes/BaseVectorStore#constructors)
|
||||
* [text](TaskStep.mdx) -> [text](/docs/api/type-aliases/TaskStep)
|
||||
*/
|
||||
function transformAbsoluteUrl(content, filePath) {
|
||||
function transformAbsoluteUrl(content: string, filePath: string) {
|
||||
const group = path.dirname(filePath).split(path.sep).pop();
|
||||
return content.replace(
|
||||
/\]\(([^)]+)\.mdx([^)]*)\)/g,
|
||||
(match, slug, anchor) => {
|
||||
const slugParts = slug.split("/");
|
||||
const fileName = slugParts[slugParts.length - 1];
|
||||
const fileGroup = slugParts[slugParts.length - 2] ?? group;
|
||||
const result = ["/docs/api", fileGroup, fileName, anchor]
|
||||
.filter(Boolean)
|
||||
.join("/");
|
||||
return `](${result})`;
|
||||
},
|
||||
);
|
||||
return content.replace(/\]\(([^)]+)\.mdx([^)]*)\)/g, (_, slug, anchor) => {
|
||||
const slugParts = slug.split("/");
|
||||
const fileName = slugParts[slugParts.length - 1];
|
||||
const fileGroup = slugParts[slugParts.length - 2] ?? group;
|
||||
const result = ["/docs/api", fileGroup, fileName, anchor]
|
||||
.filter(Boolean)
|
||||
.join("/");
|
||||
return `](${result})`;
|
||||
});
|
||||
}
|
||||
|
||||
// append meta.json for API page
|
||||
@@ -4,4 +4,8 @@ import { updateLlamaCloud } from "./update-llamacloud.mjs";
|
||||
|
||||
env.loadEnvConfig(process.cwd());
|
||||
|
||||
await updateLlamaCloud();
|
||||
if (process.env.VERCEL_ENV === "production") {
|
||||
updateLlamaCloud().catch((error) => {
|
||||
console.error(error);
|
||||
});
|
||||
}
|
||||
|
||||
@@ -1,11 +1,7 @@
|
||||
import { upsertBatchPipelineDocumentsApiV1PipelinesPipelineIdDocumentsPut } from "@llamaindex/cloud/api";
|
||||
import fg from "fast-glob";
|
||||
import {
|
||||
fileGenerator,
|
||||
remarkDocGen,
|
||||
remarkInstall,
|
||||
typescriptGenerator,
|
||||
} from "fumadocs-docgen";
|
||||
import { fileGenerator, remarkDocGen, remarkInstall } from "fumadocs-docgen";
|
||||
import { remarkAutoTypeTable } from "fumadocs-typescript";
|
||||
import matter from "gray-matter";
|
||||
import * as fs from "node:fs/promises";
|
||||
import path, { relative } from "node:path";
|
||||
@@ -21,7 +17,8 @@ async function processContent(content: string): Promise<string> {
|
||||
const file = await remark()
|
||||
.use(remarkMdx)
|
||||
.use(remarkGfm)
|
||||
.use(remarkDocGen, { generators: [typescriptGenerator(), fileGenerator()] })
|
||||
.use(remarkAutoTypeTable)
|
||||
.use(remarkDocGen, { generators: [fileGenerator()] })
|
||||
.use(remarkInstall, { persist: { id: "package-manager" } })
|
||||
.use(remarkStringify)
|
||||
.process(content);
|
||||
|
||||
@@ -2,10 +2,11 @@ import { rehypeCodeDefaultOptions } from "fumadocs-core/mdx-plugins";
|
||||
import { fileGenerator, remarkDocGen, remarkInstall } from "fumadocs-docgen";
|
||||
import { defineConfig, defineDocs } from "fumadocs-mdx/config";
|
||||
import { transformerTwoslash } from "fumadocs-twoslash";
|
||||
import { createFileSystemTypesCache } from "fumadocs-twoslash/cache-fs";
|
||||
import rehypeKatex from "rehype-katex";
|
||||
import remarkMath from "remark-math";
|
||||
|
||||
export const { docs, meta } = defineDocs({
|
||||
export const docs = defineDocs({
|
||||
dir: "./src/content/docs",
|
||||
});
|
||||
|
||||
@@ -20,7 +21,11 @@ export default defineConfig({
|
||||
},
|
||||
transformers: [
|
||||
...(rehypeCodeDefaultOptions.transformers ?? []),
|
||||
transformerTwoslash(),
|
||||
transformerTwoslash({
|
||||
typesCache: createFileSystemTypesCache({
|
||||
dir: ".next/cache/twoslash",
|
||||
}),
|
||||
}),
|
||||
{
|
||||
name: "transformers:remove-notation-escape",
|
||||
code(hast) {
|
||||
|
||||
@@ -8,7 +8,7 @@ import {
|
||||
} from "@/components/infinite-providers";
|
||||
import { MagicMove } from "@/components/magic-move";
|
||||
import { NpmInstall } from "@/components/npm-install";
|
||||
import { TextEffect } from "@/components/text-effect";
|
||||
import { Supports } from "@/components/supports";
|
||||
import { Button } from "@/components/ui/button";
|
||||
import { Skeleton } from "@/components/ui/skeleton";
|
||||
import { LEGACY_DOCUMENT_URL } from "@/lib/const";
|
||||
@@ -24,18 +24,18 @@ import { Suspense } from "react";
|
||||
export default function HomePage() {
|
||||
return (
|
||||
<main className="container mx-auto px-4 py-12">
|
||||
<h1 className="text-4xl md:text-6xl font-bold text-center mb-4">
|
||||
<h1 className="mb-4 text-center text-4xl font-bold md:text-6xl">
|
||||
Build context-augmented web apps using
|
||||
<br /> <span className="text-blue-500">LlamaIndex.TS</span>
|
||||
</h1>
|
||||
<p className="text-xl text-center text-fd-muted-foreground mb-12 ">
|
||||
<p className="text-fd-muted-foreground mb-12 text-center text-xl">
|
||||
LlamaIndex.TS is the JS/TS version of{" "}
|
||||
<a href="https://llamaindex.ai">LlamaIndex</a>, the framework for
|
||||
building agentic generative AI applications connected to your data.
|
||||
</p>
|
||||
<div className="text-center text-lg text-fd-muted-foreground mb-12">
|
||||
<div className="text-fd-muted-foreground mb-12 text-center text-lg">
|
||||
<span>Designed for building web applications in </span>
|
||||
<TextEffect />
|
||||
<Supports />
|
||||
</div>
|
||||
|
||||
<div className="flex flex-wrap justify-center gap-4">
|
||||
@@ -125,19 +125,20 @@ const response = await agent.chat({
|
||||
description="Truly powerful retrieval-augmented generation applications use agentic techniques, and LlamaIndex.TS makes it easy to build them."
|
||||
>
|
||||
<CodeBlock
|
||||
code={`import { FunctionTool } from "llamaindex";
|
||||
import { OpenAIAgent } from "@llamaindex/openai";
|
||||
code={`import { agent } from "llamaindex";
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
|
||||
const interpreterTool = FunctionTool.from(...);
|
||||
const systemPrompt = \`...\`;
|
||||
// using a previously created LlamaIndex index to query information from
|
||||
const queryTool = index.queryTool();
|
||||
|
||||
const agent = new OpenAIAgent({
|
||||
llm,
|
||||
tools: [interpreterTool],
|
||||
systemPrompt,
|
||||
const agent = agent({
|
||||
llm: new OpenAI({
|
||||
model: "gpt-4o",
|
||||
}),
|
||||
tools: [queryTool],
|
||||
});
|
||||
|
||||
await agent.chat('...');`}
|
||||
await agent.run('...');`}
|
||||
lang="ts"
|
||||
/>
|
||||
</Feature>
|
||||
@@ -149,13 +150,13 @@ await agent.chat('...');`}
|
||||
>
|
||||
<div className="mt-8 flex flex-col gap-8">
|
||||
<div>
|
||||
<h3 className="text-lg font-semibold text-fd-muted-foreground mb-2">
|
||||
<h3 className="text-fd-muted-foreground mb-2 text-lg font-semibold">
|
||||
LLMs
|
||||
</h3>
|
||||
<InfiniteLLMProviders />
|
||||
</div>
|
||||
<div>
|
||||
<h3 className="text-lg font-semibold text-fd-muted-foreground mb-2">
|
||||
<h3 className="text-fd-muted-foreground mb-2 text-lg font-semibold">
|
||||
Vector Stores
|
||||
</h3>
|
||||
<InfiniteVectorStoreProviders />
|
||||
|
||||
@@ -1,11 +0,0 @@
|
||||
import { LEGACY_DOCUMENT_URL } from "@/lib/const";
|
||||
import { redirect } from "next/navigation";
|
||||
|
||||
export default async function Page(props: {
|
||||
params: Promise<{
|
||||
any: string[];
|
||||
}>;
|
||||
}) {
|
||||
const path = await props.params.then(({ any }) => any.join("/"));
|
||||
return redirect(new URL(path, LEGACY_DOCUMENT_URL).toString());
|
||||
}
|
||||
@@ -13,6 +13,8 @@ import { notFound } from "next/navigation";
|
||||
|
||||
const { AutoTypeTable } = createTypeTable();
|
||||
|
||||
export const revalidate = false;
|
||||
|
||||
export default async function Page(props: {
|
||||
params: Promise<{ slug?: string[] }>;
|
||||
}) {
|
||||
@@ -26,10 +28,10 @@ export default async function Page(props: {
|
||||
<DocsPage
|
||||
toc={page.data.toc}
|
||||
full={page.data.full}
|
||||
lastUpdate={page.data.lastModified}
|
||||
editOnGithub={{
|
||||
owner: "run-llama",
|
||||
repo: "LlamaIndexTS",
|
||||
sha: "main",
|
||||
path: `apps/next/src/content/docs/${page.file.path}`,
|
||||
}}
|
||||
>
|
||||
@@ -64,6 +66,7 @@ export async function generateMetadata(props: {
|
||||
|
||||
return createMetadata(
|
||||
metadataImage.withImage(page.slugs, {
|
||||
metadataBase: new URL("https://ts.llamaindex.ai"),
|
||||
title: page.data.title,
|
||||
description: page.data.description,
|
||||
openGraph: {
|
||||
|
||||
@@ -22,7 +22,7 @@ export default function Layout({ children }: { children: ReactNode }) {
|
||||
variant: "secondary",
|
||||
size: "xs",
|
||||
className:
|
||||
"md:flex-1 px-2 ms-2 gap-1.5 text-fd-muted-foreground rounded-full",
|
||||
"text-fd-muted-foreground ms-2 gap-1.5 rounded-full px-2 md:flex-1",
|
||||
}),
|
||||
)}
|
||||
>
|
||||
|
||||
@@ -1,6 +1,13 @@
|
||||
@tailwind base;
|
||||
@tailwind components;
|
||||
@tailwind utilities;
|
||||
@import "tailwindcss";
|
||||
@import "fumadocs-ui/css/neutral.css";
|
||||
@import "fumadocs-ui/css/preset.css";
|
||||
@import "../../node_modules/fumadocs-twoslash/dist/twoslash.css";
|
||||
@plugin "tailwindcss-animate";
|
||||
@source '../../node_modules/fumadocs-ui/dist/**/*.js';
|
||||
@source "../../node_modules/fumadocs-openapi/dist/**/*.js",
|
||||
@source '../../node_modules/@llamaindex/chat-ui/dist/**/*.js';
|
||||
@config "../../tailwind.config.mjs";
|
||||
|
||||
@layer base {
|
||||
:root {
|
||||
--page-max-width: 1840px;
|
||||
@@ -46,6 +53,7 @@
|
||||
--chart-5: 27 87% 67%;
|
||||
--radius: 0.5rem;
|
||||
}
|
||||
|
||||
.dark {
|
||||
--color-neutral-000: #0e0c15;
|
||||
--color-neutral-100: #252134;
|
||||
@@ -87,40 +95,3 @@
|
||||
--chart-5: 340 75% 55%;
|
||||
}
|
||||
}
|
||||
@layer base {
|
||||
* {
|
||||
@apply border-border;
|
||||
}
|
||||
body {
|
||||
@apply bg-background text-foreground;
|
||||
}
|
||||
|
||||
/*
|
||||
* Override default styles for Markdown
|
||||
*/
|
||||
.prose
|
||||
:where(blockquote):not(
|
||||
:where([class~="not-prose"], [class~="not-prose"] *)
|
||||
) {
|
||||
font-style: normal !important;
|
||||
}
|
||||
|
||||
.prose
|
||||
:where(blockquote p:first-of-type):not(
|
||||
:where([class~="not-prose"], [class~="not-prose"] *)
|
||||
):before {
|
||||
content: none !important;
|
||||
}
|
||||
|
||||
.prose
|
||||
:where(blockquote p:first-of-type):not(
|
||||
:where([class~="not-prose"], [class~="not-prose"] *)
|
||||
):after {
|
||||
content: none !important;
|
||||
}
|
||||
|
||||
.prose
|
||||
:where(code):not(:where([class~="not-prose"], [class~="not-prose"] *)) {
|
||||
@apply text-blue-600 !important;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -32,7 +32,7 @@ export default function Layout({ children }: { children: ReactNode }) {
|
||||
href="/favicon-16x16.png"
|
||||
/>
|
||||
</head>
|
||||
<body className="flex flex-col min-h-screen">
|
||||
<body className="flex min-h-screen flex-col">
|
||||
<TooltipProvider>
|
||||
<AIProvider>
|
||||
<RootProvider>{children}</RootProvider>
|
||||
|
||||
@@ -0,0 +1,62 @@
|
||||
import fg from "fast-glob";
|
||||
import { fileGenerator, remarkDocGen, remarkInstall } from "fumadocs-docgen";
|
||||
import { remarkInclude } from "fumadocs-mdx/config";
|
||||
import { remarkAutoTypeTable } from "fumadocs-typescript";
|
||||
import matter from "gray-matter";
|
||||
import * as fs from "node:fs/promises";
|
||||
import path from "node:path";
|
||||
import { remark } from "remark";
|
||||
import remarkGfm from "remark-gfm";
|
||||
import remarkMdx from "remark-mdx";
|
||||
import remarkStringify from "remark-stringify";
|
||||
|
||||
export const revalidate = false;
|
||||
|
||||
export async function GET() {
|
||||
const files = await fg([
|
||||
"./src/content/docs/**/*.mdx",
|
||||
// remove generated openapi files
|
||||
"!./src/content/docs/cloud/api/**/*",
|
||||
]);
|
||||
|
||||
const scan = files.map(async (file) => {
|
||||
const fileContent = await fs.readFile(file);
|
||||
const { content, data } = matter(fileContent.toString());
|
||||
|
||||
const dir = path.dirname(file).split(path.sep).at(4);
|
||||
const category = {
|
||||
llamaindex: "LlamaIndexTS Framework",
|
||||
api: "LlamaIndexTS API",
|
||||
cloud: "LlamaCloud Service",
|
||||
}[dir ?? ""];
|
||||
|
||||
const processed = await processContent(file, content);
|
||||
return `file: ${file}
|
||||
# ${category}: ${data.title}
|
||||
|
||||
${data.description}
|
||||
|
||||
${processed}`;
|
||||
});
|
||||
|
||||
const scanned = await Promise.all(scan);
|
||||
|
||||
return new Response(scanned.join("\n\n"));
|
||||
}
|
||||
|
||||
async function processContent(path: string, content: string): Promise<string> {
|
||||
const file = await remark()
|
||||
.use(remarkMdx)
|
||||
.use(remarkInclude)
|
||||
.use(remarkGfm)
|
||||
.use(remarkAutoTypeTable)
|
||||
.use(remarkDocGen, { generators: [fileGenerator()] })
|
||||
.use(remarkInstall, { persist: { id: "package-manager" } })
|
||||
.use(remarkStringify)
|
||||
.process({
|
||||
path,
|
||||
value: content,
|
||||
});
|
||||
|
||||
return String(file);
|
||||
}
|
||||
@@ -45,13 +45,13 @@ export const AITrigger = (props: AITriggerProps) => {
|
||||
<Dialog>
|
||||
<DialogTrigger {...props} />
|
||||
<DialogPortal>
|
||||
<DialogOverlay className="fixed inset-0 z-50 bg-fd-background/50 backdrop-blur-sm data-[state=closed]:animate-fd-fade-out data-[state=open]:animate-fd-fade-in" />
|
||||
<DialogOverlay className="bg-fd-background/50 data-[state=closed]:animate-fd-fade-out data-[state=open]:animate-fd-fade-in fixed inset-0 z-50 backdrop-blur-sm" />
|
||||
<DialogContent
|
||||
onOpenAutoFocus={(e) => {
|
||||
document.getElementById("nd-ai-input")?.focus();
|
||||
e.preventDefault();
|
||||
}}
|
||||
className="fixed left-1/2 z-50 my-[5vh] flex max-h-[90dvh] w-[98vw] max-w-[860px] origin-left -translate-x-1/2 flex-col rounded-lg border bg-fd-popover text-fd-popover-foreground shadow-lg focus-visible:outline-none data-[state=closed]:animate-fd-dialog-out data-[state=open]:animate-fd-dialog-in"
|
||||
className="bg-fd-popover text-fd-popover-foreground data-[state=closed]:animate-fd-dialog-out data-[state=open]:animate-fd-dialog-in fixed left-1/2 z-50 my-[5vh] flex max-h-[90dvh] w-[98vw] max-w-[860px] origin-left -translate-x-1/2 flex-col rounded-lg border shadow-lg focus-visible:outline-none"
|
||||
>
|
||||
<DialogHeader>
|
||||
<DialogTitle className="sr-only">Search AI</DialogTitle>
|
||||
@@ -67,11 +67,11 @@ export const AITrigger = (props: AITriggerProps) => {
|
||||
</AlertDescription>
|
||||
</Alert>
|
||||
</DialogHeader>
|
||||
<div className="overflow-scroll flex-grow mt-4">
|
||||
<div className="mt-4 flex-grow overflow-scroll">
|
||||
<ChatList messages={messages} />
|
||||
</div>
|
||||
<form
|
||||
className="px-4 py-2 space-y-4"
|
||||
className="space-y-4 px-4 py-2"
|
||||
action={async () => {
|
||||
const value = inputValue.trim();
|
||||
setInputValue("");
|
||||
@@ -102,7 +102,7 @@ export const AITrigger = (props: AITriggerProps) => {
|
||||
}
|
||||
}}
|
||||
>
|
||||
<div className="flex flex-row w-full items-center gap-2">
|
||||
<div className="flex w-full flex-row items-center gap-2">
|
||||
<Textarea
|
||||
tabIndex={0}
|
||||
placeholder="Ask AI about documentation."
|
||||
|
||||
@@ -1,50 +1,21 @@
|
||||
import { highlight } from "fumadocs-core/highlight";
|
||||
import * as Base from "fumadocs-ui/components/codeblock";
|
||||
import { toJsxRuntime, type Jsx } from "hast-util-to-jsx-runtime";
|
||||
import { Fragment } from "react";
|
||||
import { jsx, jsxs } from "react/jsx-runtime";
|
||||
import { codeToHast } from "shiki";
|
||||
import type { BundledLanguage } from "shiki";
|
||||
|
||||
export interface CodeBlockProps {
|
||||
code: string;
|
||||
wrapper?: Base.CodeBlockProps;
|
||||
lang: "bash" | "ts" | "tsx";
|
||||
lang: BundledLanguage;
|
||||
}
|
||||
|
||||
export async function CodeBlock({
|
||||
code,
|
||||
lang,
|
||||
wrapper,
|
||||
}: CodeBlockProps): Promise<React.ReactElement> {
|
||||
const hast = await codeToHast(code, {
|
||||
export async function CodeBlock({ code, lang, wrapper }: CodeBlockProps) {
|
||||
const rendered = await highlight(code, {
|
||||
lang,
|
||||
defaultColor: false,
|
||||
themes: {
|
||||
light: "github-light",
|
||||
dark: "vesper",
|
||||
},
|
||||
transformers: [
|
||||
{
|
||||
name: "rehype-code:pre-process",
|
||||
line(node) {
|
||||
if (node.children.length === 0) {
|
||||
// Keep the empty lines when using grid layout
|
||||
node.children.push({
|
||||
type: "text",
|
||||
value: " ",
|
||||
});
|
||||
}
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
const rendered = toJsxRuntime(hast, {
|
||||
jsx: jsx as Jsx,
|
||||
jsxs: jsxs as Jsx,
|
||||
Fragment,
|
||||
development: false,
|
||||
components: {
|
||||
// @ts-expect-error -- JSX component
|
||||
pre: Base.Pre,
|
||||
},
|
||||
});
|
||||
|
||||
@@ -10,7 +10,7 @@ export function Contributing(): ReactElement {
|
||||
<h2 className="mb-4 text-xl font-semibold sm:text-2xl">
|
||||
Made possible by you <Heart className="inline align-middle" />
|
||||
</h2>
|
||||
<p className="mb-4 text-fd-muted-foreground">
|
||||
<p className="text-fd-muted-foreground mb-4">
|
||||
LlamaIndex.TS is powered by the open source community.
|
||||
</p>
|
||||
<div className="mb-8 flex flex-row items-center gap-2">
|
||||
|
||||
@@ -33,7 +33,7 @@ export default async function ContributorCounter({
|
||||
href={`https://github.com/${contributor.login}`}
|
||||
rel="noreferrer noopener"
|
||||
target="_blank"
|
||||
className="size-10 overflow-hidden rounded-full border-4 border-fd-background bg-fd-background md:-mr-4 md:size-12"
|
||||
className="border-fd-background bg-fd-background size-10 overflow-hidden rounded-full border-4 md:-mr-4 md:size-12"
|
||||
style={{
|
||||
zIndex: topContributors.length - i,
|
||||
}}
|
||||
@@ -48,7 +48,7 @@ export default async function ContributorCounter({
|
||||
</a>
|
||||
))}
|
||||
{displayCount < contributors.length ? (
|
||||
<div className="size-12 content-center rounded-full bg-fd-secondary text-center">
|
||||
<div className="bg-fd-secondary size-12 content-center rounded-full text-center">
|
||||
+{contributors.length - displayCount}
|
||||
</div>
|
||||
) : null}
|
||||
|
||||
@@ -83,7 +83,7 @@ export function CreateAppAnimation(): React.ReactElement {
|
||||
}}
|
||||
>
|
||||
{tick > timeWindowOpen && (
|
||||
<LaunchAppWindow className="absolute bottom-5 right-4 z-10 animate-in fade-in slide-in-from-top-10" />
|
||||
<LaunchAppWindow className="animate-in fade-in slide-in-from-top-10 absolute bottom-5 right-4 z-10" />
|
||||
)}
|
||||
<pre className="overflow-hidden rounded-xl border text-xs">
|
||||
<div className="flex flex-row items-center gap-2 border-b px-4 py-2">
|
||||
@@ -92,7 +92,7 @@ export function CreateAppAnimation(): React.ReactElement {
|
||||
<div className="grow" />
|
||||
<div className="size-2 rounded-full bg-red-400" />
|
||||
</div>
|
||||
<div className="min-h-[200px] bg-gradient-to-b from-fd-secondary [mask-image:linear-gradient(to_bottom,white,transparent)]">
|
||||
<div className="from-fd-secondary min-h-[200px] bg-gradient-to-b [mask-image:linear-gradient(to_bottom,white,transparent)]">
|
||||
<code className="grid p-4">{lines}</code>
|
||||
</div>
|
||||
</pre>
|
||||
@@ -103,7 +103,7 @@ export function CreateAppAnimation(): React.ReactElement {
|
||||
function UserMessage({ children }: { children: ReactNode }) {
|
||||
return (
|
||||
<div className="group relative flex items-start">
|
||||
<div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm bg-background">
|
||||
<div className="bg-background flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm">
|
||||
<IconUser />
|
||||
</div>
|
||||
<div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
|
||||
@@ -122,7 +122,7 @@ function BotMessage({
|
||||
}) {
|
||||
return (
|
||||
<div className={cn("group relative flex items-start", className)}>
|
||||
<div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm bg-primary text-primary-foreground">
|
||||
<div className="bg-primary text-primary-foreground flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm">
|
||||
<IconAI />
|
||||
</div>
|
||||
<div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
|
||||
@@ -164,7 +164,7 @@ export function ChatExample() {
|
||||
|
||||
return (
|
||||
<div className="max-w-64">
|
||||
<div className="flex flex-col px-4 gap-2">
|
||||
<div className="flex flex-col gap-2 px-4">
|
||||
{userMessageLength === userMessageFull.length && (
|
||||
<UserMessage>
|
||||
<span>{userMessageFull}</span>
|
||||
@@ -204,11 +204,11 @@ function LaunchAppWindow(
|
||||
<div
|
||||
{...props}
|
||||
className={cn(
|
||||
"overflow-hidden rounded-md border bg-fd-background shadow-xl",
|
||||
"bg-fd-background overflow-hidden rounded-md border shadow-xl",
|
||||
props.className,
|
||||
)}
|
||||
>
|
||||
<div className="relative flex h-6 flex-row items-center border-b bg-fd-muted px-4 text-xs text-fd-muted-foreground">
|
||||
<div className="bg-fd-muted text-fd-muted-foreground relative flex h-6 flex-row items-center border-b px-4 text-xs">
|
||||
<p className="absolute inset-x-0 text-center">localhost:8080</p>
|
||||
</div>
|
||||
<div className="p-4 text-sm">
|
||||
|
||||
@@ -1,11 +1,16 @@
|
||||
"use client";
|
||||
import { ChatInput, ChatMessages, ChatSection } from "@llamaindex/chat-ui";
|
||||
import {
|
||||
ChatHandler,
|
||||
ChatInput,
|
||||
ChatMessages,
|
||||
ChatSection,
|
||||
} from "@llamaindex/chat-ui";
|
||||
import { useChat } from "ai/react";
|
||||
|
||||
export const ChatDemo = () => {
|
||||
const handler = useChat();
|
||||
return (
|
||||
<ChatSection handler={handler}>
|
||||
<ChatSection handler={handler as ChatHandler}>
|
||||
<ChatMessages>
|
||||
<ChatMessages.List className="h-auto max-h-[400px]" />
|
||||
<ChatMessages.Actions />
|
||||
|
||||
@@ -1,23 +1,25 @@
|
||||
"use client";
|
||||
|
||||
import {
|
||||
ChatHandler,
|
||||
ChatInput,
|
||||
ChatMessage,
|
||||
ChatMessages,
|
||||
ChatSection as ChatSectionUI,
|
||||
Message,
|
||||
} from "@llamaindex/chat-ui";
|
||||
import { useChatRSC } from "./use-chat-rsc";
|
||||
|
||||
export const ChatSectionRSC = () => {
|
||||
const handler = useChatRSC();
|
||||
return (
|
||||
<ChatSectionUI handler={handler}>
|
||||
<ChatSectionUI handler={handler as ChatHandler}>
|
||||
<ChatMessages>
|
||||
<ChatMessages.List className="h-auto max-h-[400px]">
|
||||
{handler.messages.map((message, index) => (
|
||||
<ChatMessage
|
||||
key={index}
|
||||
message={message}
|
||||
message={message as Message}
|
||||
isLast={index === handler.messages.length - 1}
|
||||
>
|
||||
<ChatMessage.Avatar />
|
||||
|
||||
@@ -57,7 +57,7 @@ export const IDE = () => {
|
||||
const maxChars = useSlider();
|
||||
const useSetMaxChars = useSetSlider();
|
||||
return (
|
||||
<div className="flex flex-col p-4 border-r max-h-96 overflow-scroll">
|
||||
<div className="flex max-h-96 flex-col overflow-scroll border-r p-4">
|
||||
<div>
|
||||
<Label>Max Chars {maxChars}</Label>
|
||||
<Slider
|
||||
@@ -113,7 +113,7 @@ const Preview = ({ text }: { text: string }) => {
|
||||
},
|
||||
},
|
||||
});
|
||||
return <CodeBlock className="py-0 m-2">{rendered}</CodeBlock>;
|
||||
return <CodeBlock className="m-2 py-0">{rendered}</CodeBlock>;
|
||||
};
|
||||
|
||||
function ScrollToBottom() {
|
||||
@@ -122,7 +122,7 @@ function ScrollToBottom() {
|
||||
return (
|
||||
!isAtBottom && (
|
||||
<button
|
||||
className="absolute i-ph-arrow-circle-down-fill text-4xl rounded-lg left-[50%] translate-x-[-50%] bottom-0"
|
||||
className="i-ph-arrow-circle-down-fill absolute bottom-0 left-[50%] translate-x-[-50%] rounded-lg text-4xl"
|
||||
onClick={() => scrollToBottom()}
|
||||
/>
|
||||
)
|
||||
@@ -136,7 +136,7 @@ export const NodePreview = () => {
|
||||
const textChunks = useMemo(() => parser.splitText(code), [code, maxChars]);
|
||||
return (
|
||||
<StickToBottom
|
||||
className="block relative max-h-96 overflow-scroll"
|
||||
className="relative block max-h-96 overflow-scroll"
|
||||
resize="smooth"
|
||||
initial="smooth"
|
||||
>
|
||||
@@ -154,7 +154,7 @@ export const CodeNodeParserDemo = () => {
|
||||
const isClient = useIsClient();
|
||||
if (!isClient) {
|
||||
return (
|
||||
<div className="my-2 grid grid-cols-1 md:grid-cols-2 gap-2 border rounded-xl w-full max-h-96">
|
||||
<div className="my-2 grid max-h-96 w-full grid-cols-1 gap-2 rounded-xl border md:grid-cols-2">
|
||||
<Skeleton className="h-96" />
|
||||
<Skeleton className="h-96" />
|
||||
</div>
|
||||
@@ -165,13 +165,13 @@ export const CodeNodeParserDemo = () => {
|
||||
<CodeProvider>
|
||||
<Suspense
|
||||
fallback={
|
||||
<div className="my-2 grid grid-cols-1 md:grid-cols-2 gap-2 border rounded-xl w-full max-h-96">
|
||||
<div className="my-2 grid max-h-96 w-full grid-cols-1 gap-2 rounded-xl border md:grid-cols-2">
|
||||
<Skeleton className="h-96" />
|
||||
<Skeleton className="h-96" />
|
||||
</div>
|
||||
}
|
||||
>
|
||||
<div className="my-2 grid grid-cols-1 md:grid-cols-2 gap-2 border rounded-xl w-full max-h-96">
|
||||
<div className="my-2 grid max-h-96 w-full grid-cols-1 gap-2 rounded-xl border md:grid-cols-2">
|
||||
<IDE />
|
||||
<NodePreview />
|
||||
</div>
|
||||
|
||||
@@ -75,7 +75,7 @@ function ScrollToBottom() {
|
||||
return (
|
||||
!isAtBottom && (
|
||||
<button
|
||||
className="absolute i-ph-arrow-circle-down-fill text-4xl rounded-lg left-[50%] translate-x-[-50%] bottom-0"
|
||||
className="i-ph-arrow-circle-down-fill absolute bottom-0 left-[50%] translate-x-[-50%] rounded-lg text-4xl"
|
||||
onClick={() => scrollToBottom()}
|
||||
/>
|
||||
)
|
||||
@@ -91,9 +91,9 @@ export function WorkflowStreamingDemo() {
|
||||
const [total, setTotal] = useState<number>(10);
|
||||
|
||||
return (
|
||||
<div className="flex flex-col items-start w-full gap-2">
|
||||
<div className="flex flex-row justify-center items-center">
|
||||
<div className="text-lg mr-2">Compute total</div>{" "}
|
||||
<div className="flex w-full flex-col items-start gap-2">
|
||||
<div className="flex flex-row items-center justify-center">
|
||||
<div className="mr-2 text-lg">Compute total</div>{" "}
|
||||
<FlowInput value={total} onChange={(value) => setTotal(value)} />
|
||||
</div>
|
||||
<Button
|
||||
@@ -141,7 +141,7 @@ export function WorkflowStreamingDemo() {
|
||||
>
|
||||
Start Workflow
|
||||
</Button>
|
||||
<StickToBottom className="w-full flex flex-col gap-2 p-2 border border-gray-200 rounded-lg max-h-96 overflow-y-auto">
|
||||
<StickToBottom className="flex max-h-96 w-full flex-col gap-2 overflow-y-auto rounded-lg border border-gray-200 p-2">
|
||||
<StickToBottom.Content className="flex flex-col gap-2">
|
||||
{ui}
|
||||
</StickToBottom.Content>
|
||||
|
||||
@@ -20,7 +20,7 @@ export function Feature({
|
||||
className={cn("border-l border-t px-6 py-12 md:py-16", className)}
|
||||
{...props}
|
||||
>
|
||||
<div className="mb-4 inline-flex items-center gap-2 text-sm font-medium text-fd-muted-foreground">
|
||||
<div className="text-fd-muted-foreground mb-4 inline-flex items-center gap-2 text-sm font-medium">
|
||||
<Icon className="size-4" />
|
||||
<p>{subheading}</p>
|
||||
</div>
|
||||
|
||||
@@ -60,7 +60,7 @@ export default function FlowInput({
|
||||
className={clsx(
|
||||
showCaret ? "caret-primary" : "caret-transparent",
|
||||
"spin-hide w-[1.5em] bg-transparent py-2 text-center font-[inherit] text-transparent outline-none",
|
||||
"[appearance:textfield] [&::-webkit-outer-spin-button]:appearance-none [&::-webkit-inner-spin-button]:appearance-none",
|
||||
"[appearance:textfield] [&::-webkit-inner-spin-button]:appearance-none [&::-webkit-outer-spin-button]:appearance-none",
|
||||
)}
|
||||
// Make sure to disable kerning, to match NumberFlow:
|
||||
style={{ fontKerning: "none" }}
|
||||
|
||||
@@ -8,7 +8,7 @@ import { IconAI, IconUser } from "./ui/icons";
|
||||
export function UserMessage({ children }: { children: ReactNode }) {
|
||||
return (
|
||||
<div className="group relative flex items-start">
|
||||
<div className="flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm bg-background">
|
||||
<div className="bg-background flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm">
|
||||
<IconUser />
|
||||
</div>
|
||||
<div className="ml-4 flex-1 space-y-2 overflow-hidden px-1">
|
||||
@@ -54,7 +54,7 @@ export function BotCard({
|
||||
<div className="group relative flex items-start md:-ml-12">
|
||||
<div
|
||||
className={cn(
|
||||
"flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm bg-primary text-primary-foreground",
|
||||
"bg-primary text-primary-foreground flex h-8 w-8 shrink-0 select-none items-center justify-center rounded-md border shadow-sm",
|
||||
!showAvatar && "invisible",
|
||||
)}
|
||||
>
|
||||
|
||||
@@ -25,7 +25,7 @@ export const NpmInstall = () => {
|
||||
className="flex flex-row items-center justify-center"
|
||||
>
|
||||
<code className="mr-2">$ npm i llamaindex</code>
|
||||
<div className="relative cursor-pointer bg-transparent w-4 h-4">
|
||||
<div className="relative h-4 w-4 cursor-pointer bg-transparent">
|
||||
<div
|
||||
className={`absolute inset-0 transform transition-all duration-300 ${
|
||||
hasCheckIcon ? "scale-0 opacity-0" : "scale-100 opacity-100"
|
||||
|
||||
@@ -0,0 +1,268 @@
|
||||
import { cn } from "@/lib/utils";
|
||||
import {
|
||||
AnimatePresence,
|
||||
motion,
|
||||
Transition,
|
||||
type AnimationControls,
|
||||
type Target,
|
||||
type TargetAndTransition,
|
||||
type VariantLabels,
|
||||
} from "framer-motion";
|
||||
import React, {
|
||||
forwardRef,
|
||||
useCallback,
|
||||
useEffect,
|
||||
useImperativeHandle,
|
||||
useMemo,
|
||||
useState,
|
||||
} from "react";
|
||||
|
||||
export interface RotatingTextRef {
|
||||
next: () => void;
|
||||
previous: () => void;
|
||||
jumpTo: (index: number) => void;
|
||||
reset: () => void;
|
||||
}
|
||||
|
||||
export interface RotatingTextProps
|
||||
extends Omit<
|
||||
React.ComponentPropsWithoutRef<typeof motion.span>,
|
||||
"children" | "transition" | "initial" | "animate" | "exit"
|
||||
> {
|
||||
texts: string[];
|
||||
transition?: Transition;
|
||||
initial?: boolean | Target | VariantLabels;
|
||||
animate?: boolean | VariantLabels | AnimationControls | TargetAndTransition;
|
||||
exit?: Target | VariantLabels;
|
||||
animatePresenceMode?: "sync" | "wait";
|
||||
animatePresenceInitial?: boolean;
|
||||
rotationInterval?: number;
|
||||
staggerDuration?: number;
|
||||
staggerFrom?: "first" | "last" | "center" | "random" | number;
|
||||
loop?: boolean;
|
||||
auto?: boolean;
|
||||
splitBy?: string;
|
||||
onNext?: (index: number) => void;
|
||||
mainClassName?: string;
|
||||
splitLevelClassName?: string;
|
||||
elementLevelClassName?: string;
|
||||
}
|
||||
|
||||
export const RotatingText = forwardRef<RotatingTextRef, RotatingTextProps>(
|
||||
(
|
||||
{
|
||||
texts,
|
||||
transition = { type: "spring", damping: 25, stiffness: 300 },
|
||||
initial = { y: "100%", opacity: 0 },
|
||||
animate = { y: 0, opacity: 1 },
|
||||
exit = { y: "-120%", opacity: 0 },
|
||||
animatePresenceMode = "wait",
|
||||
animatePresenceInitial = false,
|
||||
rotationInterval = 2000,
|
||||
staggerDuration = 0,
|
||||
staggerFrom = "first",
|
||||
loop = true,
|
||||
auto = true,
|
||||
splitBy = "characters",
|
||||
onNext,
|
||||
mainClassName,
|
||||
splitLevelClassName,
|
||||
elementLevelClassName,
|
||||
...rest
|
||||
},
|
||||
ref,
|
||||
) => {
|
||||
const [currentTextIndex, setCurrentTextIndex] = useState<number>(0);
|
||||
|
||||
const splitIntoCharacters = (text: string): string[] => {
|
||||
if (typeof Intl !== "undefined" && Intl.Segmenter) {
|
||||
const segmenter = new Intl.Segmenter("en", { granularity: "grapheme" });
|
||||
return Array.from(
|
||||
segmenter.segment(text),
|
||||
(segment) => segment.segment,
|
||||
);
|
||||
}
|
||||
return Array.from(text);
|
||||
};
|
||||
|
||||
const elements = useMemo(() => {
|
||||
const currentText: string = texts[currentTextIndex];
|
||||
if (splitBy === "characters") {
|
||||
const words = currentText.split(" ");
|
||||
return words.map((word, i) => ({
|
||||
characters: splitIntoCharacters(word),
|
||||
needsSpace: i !== words.length - 1,
|
||||
}));
|
||||
}
|
||||
if (splitBy === "words") {
|
||||
return currentText.split(" ").map((word, i, arr) => ({
|
||||
characters: [word],
|
||||
needsSpace: i !== arr.length - 1,
|
||||
}));
|
||||
}
|
||||
if (splitBy === "lines") {
|
||||
return currentText.split("\n").map((line, i, arr) => ({
|
||||
characters: [line],
|
||||
needsSpace: i !== arr.length - 1,
|
||||
}));
|
||||
}
|
||||
|
||||
return currentText.split(splitBy).map((part, i, arr) => ({
|
||||
characters: [part],
|
||||
needsSpace: i !== arr.length - 1,
|
||||
}));
|
||||
}, [texts, currentTextIndex, splitBy]);
|
||||
|
||||
const getStaggerDelay = useCallback(
|
||||
(index: number, totalChars: number): number => {
|
||||
const total = totalChars;
|
||||
if (staggerFrom === "first") return index * staggerDuration;
|
||||
if (staggerFrom === "last")
|
||||
return (total - 1 - index) * staggerDuration;
|
||||
if (staggerFrom === "center") {
|
||||
const center = Math.floor(total / 2);
|
||||
return Math.abs(center - index) * staggerDuration;
|
||||
}
|
||||
if (staggerFrom === "random") {
|
||||
const randomIndex = Math.floor(Math.random() * total);
|
||||
return Math.abs(randomIndex - index) * staggerDuration;
|
||||
}
|
||||
return Math.abs((staggerFrom as number) - index) * staggerDuration;
|
||||
},
|
||||
[staggerFrom, staggerDuration],
|
||||
);
|
||||
|
||||
const handleIndexChange = useCallback(
|
||||
(newIndex: number) => {
|
||||
setCurrentTextIndex(newIndex);
|
||||
if (onNext) onNext(newIndex);
|
||||
},
|
||||
[onNext],
|
||||
);
|
||||
|
||||
const next = useCallback(() => {
|
||||
const nextIndex =
|
||||
currentTextIndex === texts.length - 1
|
||||
? loop
|
||||
? 0
|
||||
: currentTextIndex
|
||||
: currentTextIndex + 1;
|
||||
if (nextIndex !== currentTextIndex) {
|
||||
handleIndexChange(nextIndex);
|
||||
}
|
||||
}, [currentTextIndex, texts.length, loop, handleIndexChange]);
|
||||
|
||||
const previous = useCallback(() => {
|
||||
const prevIndex =
|
||||
currentTextIndex === 0
|
||||
? loop
|
||||
? texts.length - 1
|
||||
: currentTextIndex
|
||||
: currentTextIndex - 1;
|
||||
if (prevIndex !== currentTextIndex) {
|
||||
handleIndexChange(prevIndex);
|
||||
}
|
||||
}, [currentTextIndex, texts.length, loop, handleIndexChange]);
|
||||
|
||||
const jumpTo = useCallback(
|
||||
(index: number) => {
|
||||
const validIndex = Math.max(0, Math.min(index, texts.length - 1));
|
||||
if (validIndex !== currentTextIndex) {
|
||||
handleIndexChange(validIndex);
|
||||
}
|
||||
},
|
||||
[texts.length, currentTextIndex, handleIndexChange],
|
||||
);
|
||||
|
||||
const reset = useCallback(() => {
|
||||
if (currentTextIndex !== 0) {
|
||||
handleIndexChange(0);
|
||||
}
|
||||
}, [currentTextIndex, handleIndexChange]);
|
||||
|
||||
useImperativeHandle(
|
||||
ref,
|
||||
() => ({
|
||||
next,
|
||||
previous,
|
||||
jumpTo,
|
||||
reset,
|
||||
}),
|
||||
[next, previous, jumpTo, reset],
|
||||
);
|
||||
|
||||
useEffect(() => {
|
||||
if (!auto) return;
|
||||
const intervalId = setInterval(next, rotationInterval);
|
||||
return () => clearInterval(intervalId);
|
||||
}, [next, rotationInterval, auto]);
|
||||
|
||||
return (
|
||||
<motion.span
|
||||
className={cn(
|
||||
"relative flex flex-wrap whitespace-pre-wrap",
|
||||
mainClassName,
|
||||
)}
|
||||
{...rest}
|
||||
layout
|
||||
transition={transition}
|
||||
>
|
||||
<span className="sr-only">{texts[currentTextIndex]}</span>
|
||||
<AnimatePresence
|
||||
mode={animatePresenceMode}
|
||||
initial={animatePresenceInitial}
|
||||
>
|
||||
<motion.div
|
||||
key={currentTextIndex}
|
||||
className={cn(
|
||||
splitBy === "lines"
|
||||
? "flex w-full flex-col"
|
||||
: "relative flex flex-wrap whitespace-pre-wrap",
|
||||
)}
|
||||
layout
|
||||
aria-hidden="true"
|
||||
>
|
||||
{elements.map((wordObj, wordIndex, array) => {
|
||||
const previousCharsCount = array
|
||||
.slice(0, wordIndex)
|
||||
.reduce((sum, word) => sum + word.characters.length, 0);
|
||||
return (
|
||||
<span
|
||||
key={wordIndex}
|
||||
className={cn("inline-flex", splitLevelClassName)}
|
||||
>
|
||||
{wordObj.characters.map((char, charIndex) => (
|
||||
<motion.span
|
||||
key={charIndex}
|
||||
initial={initial}
|
||||
animate={animate}
|
||||
exit={exit}
|
||||
transition={{
|
||||
...transition,
|
||||
delay: getStaggerDelay(
|
||||
previousCharsCount + charIndex,
|
||||
array.reduce(
|
||||
(sum, word) => sum + word.characters.length,
|
||||
0,
|
||||
),
|
||||
),
|
||||
}}
|
||||
className={cn("inline-block", elementLevelClassName)}
|
||||
>
|
||||
{char}
|
||||
</motion.span>
|
||||
))}
|
||||
{wordObj.needsSpace && (
|
||||
<span className="whitespace-pre"> </span>
|
||||
)}
|
||||
</span>
|
||||
);
|
||||
})}
|
||||
</motion.div>
|
||||
</AnimatePresence>
|
||||
</motion.span>
|
||||
);
|
||||
},
|
||||
);
|
||||
|
||||
RotatingText.displayName = "RotatingText";
|
||||
@@ -0,0 +1,27 @@
|
||||
"use client";
|
||||
import { RotatingText } from "@/components/reactbits/rotating-text";
|
||||
|
||||
const supports = [
|
||||
"Next.js",
|
||||
"Node.js",
|
||||
"Hono",
|
||||
"Express.js",
|
||||
"Deno",
|
||||
"Nest.js",
|
||||
"Waku",
|
||||
];
|
||||
|
||||
export const Supports = () => {
|
||||
return (
|
||||
<RotatingText
|
||||
texts={supports}
|
||||
mainClassName="inline-flex bg-transparent overflow-hidden justify-center"
|
||||
initial={{ y: "100%" }}
|
||||
animate={{ y: 0 }}
|
||||
exit={{ y: "-120%" }}
|
||||
staggerDuration={0.025}
|
||||
transition={{ type: "spring", damping: 30, stiffness: 400 }}
|
||||
rotationInterval={2000}
|
||||
/>
|
||||
);
|
||||
};
|
||||
@@ -1,28 +0,0 @@
|
||||
"use client";
|
||||
import { useEffect, useState } from "react";
|
||||
import ReactTextTransition from "react-text-transition";
|
||||
|
||||
const supports = [
|
||||
"Next.js",
|
||||
"Node.js",
|
||||
"Hono",
|
||||
"Express.js",
|
||||
"Deno",
|
||||
"Nest.js",
|
||||
"Waku",
|
||||
];
|
||||
|
||||
export const TextEffect = () => {
|
||||
const [counter, setCounter] = useState(0);
|
||||
useEffect(() => {
|
||||
const id = setInterval(() => {
|
||||
setCounter(
|
||||
(Math.floor(Math.random() * supports.length) + 1) % supports.length,
|
||||
);
|
||||
}, 4000);
|
||||
return () => {
|
||||
clearInterval(id);
|
||||
};
|
||||
}, []);
|
||||
return <ReactTextTransition inline>{supports[counter]}</ReactTextTransition>;
|
||||
};
|
||||
@@ -21,7 +21,7 @@ const DialogOverlay = React.forwardRef<
|
||||
<DialogPrimitive.Overlay
|
||||
ref={ref}
|
||||
className={cn(
|
||||
"fixed inset-0 z-50 bg-black/80 data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0",
|
||||
"data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 fixed inset-0 z-50 bg-black/80",
|
||||
className,
|
||||
)}
|
||||
{...props}
|
||||
@@ -38,13 +38,13 @@ const DialogContent = React.forwardRef<
|
||||
<DialogPrimitive.Content
|
||||
ref={ref}
|
||||
className={cn(
|
||||
"fixed left-[50%] top-[50%] z-50 grid w-full max-w-lg translate-x-[-50%] translate-y-[-50%] gap-4 border bg-background p-6 shadow-lg duration-200 data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[state=closed]:slide-out-to-left-1/2 data-[state=closed]:slide-out-to-top-[48%] data-[state=open]:slide-in-from-left-1/2 data-[state=open]:slide-in-from-top-[48%] sm:rounded-lg",
|
||||
"bg-background data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[state=closed]:slide-out-to-left-1/2 data-[state=closed]:slide-out-to-top-[48%] data-[state=open]:slide-in-from-left-1/2 data-[state=open]:slide-in-from-top-[48%] fixed left-[50%] top-[50%] z-50 grid w-full max-w-lg translate-x-[-50%] translate-y-[-50%] gap-4 border p-6 shadow-lg duration-200 sm:rounded-lg",
|
||||
className,
|
||||
)}
|
||||
{...props}
|
||||
>
|
||||
{children}
|
||||
<DialogPrimitive.Close className="absolute right-4 top-4 rounded-sm opacity-70 ring-offset-background transition-opacity hover:opacity-100 focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2 disabled:pointer-events-none data-[state=open]:bg-accent data-[state=open]:text-muted-foreground">
|
||||
<DialogPrimitive.Close className="ring-offset-background focus:ring-ring data-[state=open]:bg-accent data-[state=open]:text-muted-foreground absolute right-4 top-4 rounded-sm opacity-70 transition-opacity hover:opacity-100 focus:outline-none focus:ring-2 focus:ring-offset-2 disabled:pointer-events-none">
|
||||
<Cross2Icon className="h-4 w-4" />
|
||||
<span className="sr-only">Close</span>
|
||||
</DialogPrimitive.Close>
|
||||
@@ -102,7 +102,7 @@ const DialogDescription = React.forwardRef<
|
||||
>(({ className, ...props }, ref) => (
|
||||
<DialogPrimitive.Description
|
||||
ref={ref}
|
||||
className={cn("text-sm text-muted-foreground", className)}
|
||||
className={cn("text-muted-foreground text-sm", className)}
|
||||
{...props}
|
||||
/>
|
||||
));
|
||||
|
||||
@@ -10,7 +10,7 @@ const Input = React.forwardRef<HTMLInputElement, InputProps>(
|
||||
<input
|
||||
type={type}
|
||||
className={cn(
|
||||
"flex h-9 w-full rounded-md border border-input bg-transparent px-3 py-1 text-sm shadow-sm transition-colors file:border-0 file:bg-transparent file:text-sm file:font-medium file:text-foreground placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:cursor-not-allowed disabled:opacity-50",
|
||||
"border-input file:text-foreground placeholder:text-muted-foreground focus-visible:ring-ring flex h-9 w-full rounded-md border bg-transparent px-3 py-1 text-sm shadow-sm transition-colors file:border-0 file:bg-transparent file:text-sm file:font-medium focus-visible:outline-none focus-visible:ring-1 disabled:cursor-not-allowed disabled:opacity-50",
|
||||
className,
|
||||
)}
|
||||
ref={ref}
|
||||
|
||||
@@ -6,7 +6,7 @@ function Skeleton({
|
||||
}: React.HTMLAttributes<HTMLDivElement>) {
|
||||
return (
|
||||
<div
|
||||
className={cn("animate-pulse rounded-md bg-primary/10", className)}
|
||||
className={cn("bg-primary/10 animate-pulse rounded-md", className)}
|
||||
{...props}
|
||||
/>
|
||||
);
|
||||
|
||||
@@ -17,10 +17,10 @@ const Slider = React.forwardRef<
|
||||
)}
|
||||
{...props}
|
||||
>
|
||||
<SliderPrimitive.Track className="relative h-1.5 w-full grow overflow-hidden rounded-full bg-primary/20">
|
||||
<SliderPrimitive.Range className="absolute h-full bg-primary" />
|
||||
<SliderPrimitive.Track className="bg-primary/20 relative h-1.5 w-full grow overflow-hidden rounded-full">
|
||||
<SliderPrimitive.Range className="bg-primary absolute h-full" />
|
||||
</SliderPrimitive.Track>
|
||||
<SliderPrimitive.Thumb className="block h-4 w-4 rounded-full border border-primary/50 bg-background shadow transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:pointer-events-none disabled:opacity-50" />
|
||||
<SliderPrimitive.Thumb className="border-primary/50 bg-background focus-visible:ring-ring block h-4 w-4 rounded-full border shadow transition-colors focus-visible:outline-none focus-visible:ring-1 disabled:pointer-events-none disabled:opacity-50" />
|
||||
</SliderPrimitive.Root>
|
||||
));
|
||||
Slider.displayName = SliderPrimitive.Root.displayName;
|
||||
|
||||
@@ -9,7 +9,7 @@ const Textarea = React.forwardRef<HTMLTextAreaElement, TextareaProps>(
|
||||
return (
|
||||
<textarea
|
||||
className={cn(
|
||||
"flex min-h-[60px] w-full rounded-md border border-input bg-transparent px-3 py-2 text-sm shadow-sm placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:cursor-not-allowed disabled:opacity-50",
|
||||
"border-input placeholder:text-muted-foreground focus-visible:ring-ring flex min-h-[60px] w-full rounded-md border bg-transparent px-3 py-2 text-sm shadow-sm focus-visible:outline-none focus-visible:ring-1 disabled:cursor-not-allowed disabled:opacity-50",
|
||||
className,
|
||||
)}
|
||||
ref={ref}
|
||||
|
||||
@@ -20,7 +20,7 @@ const TooltipContent = React.forwardRef<
|
||||
ref={ref}
|
||||
sideOffset={sideOffset}
|
||||
className={cn(
|
||||
"z-50 overflow-hidden rounded-md bg-primary px-3 py-1.5 text-xs text-primary-foreground animate-in fade-in-0 zoom-in-95 data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=closed]:zoom-out-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2",
|
||||
"bg-primary text-primary-foreground animate-in fade-in-0 zoom-in-95 data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=closed]:zoom-out-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 z-50 overflow-hidden rounded-md px-3 py-1.5 text-xs",
|
||||
className,
|
||||
)}
|
||||
{...props}
|
||||
|
||||
@@ -2,5 +2,5 @@
|
||||
"title": "LlamaCloud",
|
||||
"description": "The Cloud framework for LLM",
|
||||
"root": true,
|
||||
"pages": ["---Guide---", "index", "api"]
|
||||
"pages": ["---Guide---", "index", "..."]
|
||||
}
|
||||
|
||||
@@ -3,6 +3,8 @@ title: With Node.js/Bun/Deno
|
||||
description: In this guide, you'll learn how to use LlamaIndex with Node.js, Bun, and Deno.
|
||||
---
|
||||
|
||||
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
|
||||
|
||||
## Adding environment variables
|
||||
|
||||
By default, LlamaIndex uses OpenAI provider, which requires an API key. You can set the `OPENAI_API_KEY` environment variable to authenticate with OpenAI.
|
||||
@@ -22,6 +24,26 @@ node --env-file .env your-script.js
|
||||
|
||||
For more information, see the [How to read environment variables from Node.js](https://nodejs.org/en/learn/command-line/how-to-read-environment-variables-from-nodejs).
|
||||
|
||||
## Performance Optimization
|
||||
|
||||
By the default, we are using `js-tiktoken` for tokenization. You can install `gpt-tokenizer` which is then automatically used by LlamaIndex to get a 60x speedup for tokenization:
|
||||
|
||||
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
|
||||
```shell tab="npm"
|
||||
npm install gpt-tokenizer
|
||||
```
|
||||
|
||||
```shell tab="yarn"
|
||||
yarn add gpt-tokenizer
|
||||
```
|
||||
|
||||
```shell tab="pnpm"
|
||||
pnpm add gpt-tokenizer
|
||||
```
|
||||
</Tabs>
|
||||
|
||||
> Note: This only works for Node.js
|
||||
|
||||
## TypeScript support
|
||||
|
||||
<Card
|
||||
|
||||
@@ -34,6 +34,7 @@ First we'll need to pull in our dependencies. These are:
|
||||
import { FunctionTool, Settings } from "llamaindex";
|
||||
import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
|
||||
import "dotenv/config";
|
||||
import { z } from "zod";
|
||||
```
|
||||
|
||||
### Initialize your LLM
|
||||
@@ -86,20 +87,14 @@ This is the most complicated part of creating an agent. We need to define a `Fun
|
||||
const tool = FunctionTool.from(sumNumbers, {
|
||||
name: "sumNumbers",
|
||||
description: "Use this function to sum two numbers",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "First number to sum",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "Second number to sum",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
},
|
||||
parameters: z.object({
|
||||
a: z.number({
|
||||
description: "First number to sum",
|
||||
}),
|
||||
b: z.number({
|
||||
description: "Second number to sum",
|
||||
}),
|
||||
}),
|
||||
});
|
||||
```
|
||||
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
title: A RAG agent that does math
|
||||
---
|
||||
|
||||
In [our third iteration of the agent](https://github.com/run-llama/ts-agents/blob/main/3_rag_and_tools/agent.ts) we've combined the two previous agents, so we've defined both `sumNumbers` and a `QueryEngineTool` and created an array of two tools:
|
||||
In [our third iteration of the agent](https://github.com/run-llama/ts-agents/blob/main/3_rag_and_tools/agent.ts) we've combined the two previous agents, so we've defined both `sumNumbers` and a `QueryEngineTool` and created an array of two tools. The tools support both Zod and JSON Schema for parameter definition:
|
||||
|
||||
```javascript
|
||||
// define the query engine as a tool
|
||||
@@ -17,24 +17,42 @@ const tools = [
|
||||
FunctionTool.from(sumNumbers, {
|
||||
name: "sumNumbers",
|
||||
description: "Use this function to sum two numbers",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "First number to sum",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "Second number to sum",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
},
|
||||
parameters: z.object({
|
||||
a: z.number({
|
||||
description: "First number to sum",
|
||||
}),
|
||||
b: z.number({
|
||||
description: "Second number to sum",
|
||||
}),
|
||||
}),
|
||||
}),
|
||||
];
|
||||
```
|
||||
|
||||
You can also use JSON Schema to define the tool parameters as an alternative to Zod.
|
||||
|
||||
```javascript
|
||||
FunctionTool.from(sumNumbers, {
|
||||
name: "sumNumbers",
|
||||
description: "Use this function to sum two numbers",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "First number to sum",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "Second number to sum",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
},
|
||||
}),
|
||||
```
|
||||
|
||||
|
||||
These tool descriptions are identical to the ones we previously defined. Now let's ask it 3 questions in a row:
|
||||
|
||||
```javascript
|
||||
|
||||
@@ -3,8 +3,6 @@ title: Using API Route
|
||||
description: Chat interface for your LlamaIndexTS application using API Route
|
||||
---
|
||||
import { ChatDemo } from '../../../../../components/demo/chat/api/demo';
|
||||
import "@llamaindex/chat-ui/styles/code.css";
|
||||
import "@llamaindex/chat-ui/styles/katex.css";
|
||||
|
||||
Using [chat-ui](https://github.com/run-llama/chat-ui), it's easy to add a chat interface to your LlamaIndexTS application.
|
||||
You just need to create an API route that provides an `api/chat` endpoint and a chat component to consume the API.
|
||||
|
||||
@@ -0,0 +1,22 @@
|
||||
---
|
||||
title: Install @llamaindex/chat
|
||||
description: Chat interface for your LlamaIndexTS application
|
||||
---
|
||||
|
||||
## Quick Start
|
||||
|
||||
You can quickly add a chatbot to your project by using Shadcn CLI command:
|
||||
|
||||
```sh
|
||||
npx shadcn@latest add https://ui.llamaindex.ai/r/chat.json
|
||||
```
|
||||
|
||||
## Manual Installation
|
||||
|
||||
To install the package, run the following command in your project directory:
|
||||
|
||||
```sh
|
||||
npm install @llamaindex/chat-ui
|
||||
```
|
||||
|
||||
For more information, check out the [github.comrun-llama/chat-ui](https://github.com/run-llama/chat-ui)
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"title": "Chat-UI",
|
||||
"title": "Chat UI",
|
||||
"description": "Use chat-ui to add a chat interface to your LlamaIndexTS application.",
|
||||
"defaultOpen": false,
|
||||
"pages": ["chat", "rsc"]
|
||||
"pages": ["install", "chat", "rsc"]
|
||||
}
|
||||
|
||||
@@ -3,8 +3,6 @@ title: Using Next.js RSC
|
||||
description: Chat interface for your LlamaIndexTS application using Next.js RSC
|
||||
---
|
||||
import { ChatDemoRSC } from '../../../../../components/demo/chat/rsc/demo';
|
||||
import "@llamaindex/chat-ui/styles/code.css";
|
||||
import "@llamaindex/chat-ui/styles/katex.css";
|
||||
|
||||
Using [chat-ui](https://github.com/run-llama/chat-ui), it's easy to add a chat interface to your LlamaIndexTS application using [Next.js RSC](https://nextjs.org/docs/app/building-your-application/rendering/server-components) and [Vercel AI RSC](https://sdk.vercel.ai/docs/ai-sdk-rsc/overview).
|
||||
|
||||
|
||||
@@ -0,0 +1,121 @@
|
||||
---
|
||||
title: Agent Workflow
|
||||
---
|
||||
|
||||
import { DynamicCodeBlock } from 'fumadocs-ui/components/dynamic-codeblock';
|
||||
import CodeSource from "!raw-loader!../../../../../../../examples/agentworkflow/blog-writer.ts";
|
||||
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
|
||||
|
||||
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` system and provides a streamlined interface for agent interactions.
|
||||
|
||||
## Usage
|
||||
|
||||
### Single Agent Workflow
|
||||
|
||||
The simplest use case is creating a single agent with specific tools. Here's an example of creating an assistant that tells jokes:
|
||||
|
||||
```typescript
|
||||
import { agent, FunctionTool } from "llamaindex";
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
|
||||
// Define a joke-telling tool
|
||||
const jokeTool = FunctionTool.from(
|
||||
() => "Baby Llama is called cria",
|
||||
{
|
||||
name: "joke",
|
||||
description: "Use this tool to get a joke",
|
||||
}
|
||||
);
|
||||
|
||||
// Create an single agent workflow with the tool
|
||||
const workflow = agent({
|
||||
tools: [jokeTool],
|
||||
llm: new OpenAI({
|
||||
model: "gpt-4o-mini",
|
||||
}),
|
||||
});
|
||||
|
||||
// Run the workflow
|
||||
const result = await workflow.run("Tell me something funny");
|
||||
console.log(result); // Baby Llama is called cria
|
||||
```
|
||||
|
||||
### Event Streaming
|
||||
|
||||
Agent Workflows provide a unified interface for event streaming, making it easy to track and respond to different events during execution:
|
||||
|
||||
```typescript
|
||||
import { AgentToolCall, AgentStream } from "llamaindex";
|
||||
|
||||
// Get the workflow execution context
|
||||
const context = workflow.run("Tell me something funny");
|
||||
|
||||
// Stream and handle events
|
||||
for await (const event of context) {
|
||||
if (event instanceof AgentToolCall) {
|
||||
console.log(`Tool being called: ${event.data.toolName}`);
|
||||
}
|
||||
if (event instanceof AgentStream) {
|
||||
process.stdout.write(event.data.delta);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Multi-Agent Workflow
|
||||
|
||||
An Agent Workflow can orchestrate multiple agents, enabling complex interactions and task handoffs. Each agent in a multi-agent workflow requires:
|
||||
|
||||
- `name`: Unique identifier for the agent
|
||||
- `description`: Purpose description used for task routing
|
||||
- `tools`: Array of tools the agent can use
|
||||
- `canHandoffTo` (optional): Array of agent names or agent instances that this agent can delegate tasks to
|
||||
|
||||
Here's an example of a multi-agent system that combines joke-telling and weather information:
|
||||
|
||||
```typescript
|
||||
import { multiAgent, agent, FunctionTool } from "llamaindex";
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import { z } from "zod";
|
||||
|
||||
// Create a weather agent
|
||||
const weatherAgent = agent({
|
||||
name: "WeatherAgent",
|
||||
description: "Provides weather information for any city",
|
||||
tools: [
|
||||
FunctionTool.from(
|
||||
({ city }: { city: string }) => `The weather in ${city} is sunny`,
|
||||
{
|
||||
name: "fetchWeather",
|
||||
description: "Get weather information for a city",
|
||||
parameters: z.object({
|
||||
city: z.string(),
|
||||
}),
|
||||
}
|
||||
),
|
||||
],
|
||||
llm: new OpenAI({ model: "gpt-4o-mini" }),
|
||||
});
|
||||
|
||||
// Create a joke-telling agent
|
||||
const jokeAgent = agent({
|
||||
name: "JokeAgent",
|
||||
description: "Tells jokes and funny stories",
|
||||
tools: [jokeTool], // Using the joke tool defined earlier
|
||||
llm: new OpenAI({ model: "gpt-4o-mini" }),
|
||||
canHandoffTo: [weatherAgent], // Can hand off to the weather agent
|
||||
});
|
||||
|
||||
// Create the multi-agent workflow
|
||||
const workflow = multiAgent({
|
||||
agents: [jokeAgent, weatherAgent],
|
||||
rootAgent: jokeAgent, // Start with the joke agent
|
||||
});
|
||||
|
||||
// Run the workflow
|
||||
const result = await workflow.run(
|
||||
"Give me a morning greeting with a joke and the weather in San Francisco"
|
||||
);
|
||||
```
|
||||
|
||||
The workflow will coordinate between agents, allowing them to handle different aspects of the request and hand off tasks when appropriate.
|
||||
|
||||
+3
-2
@@ -2,10 +2,11 @@
|
||||
title: Jina AI
|
||||
---
|
||||
|
||||
To use Jina AI embeddings, you need to import `JinaAIEmbedding` from `llamaindex`.
|
||||
To use Jina AI embeddings, you need to import `JinaAIEmbedding` from `@llamaindex/jinaai`.
|
||||
|
||||
```ts
|
||||
import { JinaAIEmbedding, Settings } from "llamaindex";
|
||||
import { Settings } from "llamaindex";
|
||||
import { JinaAIEmbedding } from "@llamaindex/jinaai";
|
||||
|
||||
Settings.embedModel = new JinaAIEmbedding();
|
||||
|
||||
|
||||
+3
-2
@@ -2,10 +2,11 @@
|
||||
title: Together
|
||||
---
|
||||
|
||||
To use together embeddings, you need to import `TogetherEmbedding` from `llamaindex`.
|
||||
To use together embeddings, you need to import `TogetherEmbedding` from `@llamaindex/together`.
|
||||
|
||||
```ts
|
||||
import { TogetherEmbedding, Settings } from "llamaindex";
|
||||
import { Settings } from "llamaindex";
|
||||
import { TogetherEmbedding } from "@llamaindex/together";
|
||||
|
||||
Settings.embedModel = new TogetherEmbedding({
|
||||
apiKey: "<YOUR_API_KEY>",
|
||||
|
||||
@@ -127,26 +127,21 @@ async function main() {
|
||||
```ts
|
||||
import { BEDROCK_MODELS, Bedrock } from "@llamaindex/community";
|
||||
import { FunctionTool, LLMAgent } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
const sumNumbers = FunctionTool.from(
|
||||
({ a, b }: { a: number; b: number }) => `${a + b}`,
|
||||
{
|
||||
name: "sumNumbers",
|
||||
description: "Use this function to sum two numbers",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "The first number",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "The second number",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
},
|
||||
parameters: z.object({
|
||||
a: z.number({
|
||||
description: "The first number",
|
||||
}),
|
||||
b: z.number({
|
||||
description: "The second number",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
@@ -155,20 +150,14 @@ const divideNumbers = FunctionTool.from(
|
||||
{
|
||||
name: "divideNumbers",
|
||||
description: "Use this function to divide two numbers",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "The dividend a to divide",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "The divisor b to divide by",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
},
|
||||
parameters: z.object({
|
||||
a: z.number({
|
||||
description: "The dividend a to divide",
|
||||
}),
|
||||
b: z.number({
|
||||
description: "The divisor b to divide by",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
|
||||
@@ -7,7 +7,8 @@ title: DeepSeek LLM
|
||||
## Usage
|
||||
|
||||
```ts
|
||||
import { DeepSeekLLM, Settings } from "llamaindex";
|
||||
import { Settings } from "llamaindex";
|
||||
import { DeepSeekLLM } from "@llamaindex/deepseek";
|
||||
|
||||
Settings.llm = new DeepSeekLLM({
|
||||
apiKey: "<YOUR_API_KEY>",
|
||||
@@ -18,7 +19,8 @@ Settings.llm = new DeepSeekLLM({
|
||||
## Example
|
||||
|
||||
```ts
|
||||
import { DeepSeekLLM, Document, VectorStoreIndex, Settings } from "llamaindex";
|
||||
import { Document, VectorStoreIndex, Settings } from "llamaindex";
|
||||
import { DeepSeekLLM } from "@llamaindex/deepseek";
|
||||
|
||||
const deepseekLlm = new DeepSeekLLM({
|
||||
apiKey: "<YOUR_API_KEY>",
|
||||
|
||||
@@ -7,7 +7,8 @@ title: Fireworks LLM
|
||||
## Usage
|
||||
|
||||
```ts
|
||||
import { FireworksLLM, Settings } from "llamaindex";
|
||||
import { Settings } from "llamaindex";
|
||||
import { FireworksLLM } from "@llamaindex/fireworks";
|
||||
|
||||
Settings.llm = new FireworksLLM({
|
||||
apiKey: "<YOUR_API_KEY>",
|
||||
|
||||
@@ -23,7 +23,8 @@ import { Tab, Tabs } from "fumadocs-ui/components/tabs";
|
||||
## Usage
|
||||
|
||||
```ts
|
||||
import { Settings, TogetherLLM } from "llamaindex";
|
||||
import { Settings } from "llamaindex";
|
||||
import { TogetherLLM } from "@llamaindex/together";
|
||||
|
||||
Settings.llm = new TogetherLLM({
|
||||
apiKey: "<YOUR_API_KEY>",
|
||||
|
||||
@@ -0,0 +1,55 @@
|
||||
---
|
||||
title: Tools
|
||||
---
|
||||
|
||||
A "tool" is a utility that can be called by an agent on behalf of an LLM.
|
||||
A tool can be called to perform custom actions, or retrieve extra information based on the LLM-generated input.
|
||||
A result from a tool call can be used by subsequent steps in a workflow, or to compute a final answer.
|
||||
For example, a "weather tool" could fetch some live weather information from a geographical location.
|
||||
|
||||
## Function tool
|
||||
|
||||
Function tools are implemented with the `FunctionTool` class.
|
||||
A `FunctionTool` is constructed from a function with signature
|
||||
```ts
|
||||
(input: T, additionalArg?: AdditionalToolArgument) => R
|
||||
```
|
||||
where
|
||||
- `input` is generated by the LLM, `T` is the type defined by the tool `parameters`
|
||||
- `additionalArg` is an optional extra argument, see "Binding" below
|
||||
- `R` is the return type
|
||||
|
||||
### Binding
|
||||
|
||||
An additional argument can be bound to a tool, each tool call will be passed
|
||||
- the input provided by the LLM
|
||||
- the additional argument (extends object)
|
||||
|
||||
Note: calling the `bind` method will return a new `FunctionTool` instance, without modifying the tool which `bind` is called on.
|
||||
|
||||
Example to pass a `userToken` as additional argument:
|
||||
```ts
|
||||
// first arg is LLM input, second is bound arg
|
||||
const queryKnowledgeBase = async ({ question }, { userToken }) => {
|
||||
const response = await fetch(`https://knowledge-base.com?token=${userToken}&query=${question}`);
|
||||
// ...
|
||||
};
|
||||
|
||||
// define tool as usual
|
||||
const kbTool = FunctionTool.from(queryKnowledgeBase, {
|
||||
name: 'queryKnowledgeBase',
|
||||
description: 'Query knowledge base',
|
||||
parameters: z.object({
|
||||
question: z.string({
|
||||
description: 'The user question',
|
||||
}),
|
||||
}),
|
||||
});
|
||||
|
||||
// create an agent
|
||||
const additionalArg = { userToken: 'abcd1234' };
|
||||
const kbAgent = new LLMAgent({
|
||||
tools: [kbTool.bind(additionalArg)],
|
||||
// llm, systemPrompt etc
|
||||
})
|
||||
```
|
||||
@@ -119,7 +119,7 @@ Lastly, we run the workflow. The `.run()` method is async, so we use await here
|
||||
Optionally, you can choose to use a shared context between steps by specifying a context type when creating the workflow. Here's an example where multiple steps access a shared state:
|
||||
|
||||
```typescript
|
||||
import { HandlerContext } from "@llamaindex/workflow";
|
||||
import { HandlerContext } from "llamaindex";
|
||||
|
||||
type MyContextData = {
|
||||
query: string;
|
||||
|
||||
@@ -1,11 +1,10 @@
|
||||
import { docs, meta } from '../../.source';
|
||||
import { createMDXSource } from 'fumadocs-mdx';
|
||||
import { docs } from '@/.source';
|
||||
import { loader } from 'fumadocs-core/source';
|
||||
import { createOpenAPI } from "fumadocs-openapi/server";
|
||||
|
||||
export const source = loader({
|
||||
baseUrl: '/docs',
|
||||
source: createMDXSource(docs, meta),
|
||||
source: docs.toFumadocsSource(),
|
||||
});
|
||||
|
||||
export const openapi = createOpenAPI();
|
||||
|
||||
@@ -1,5 +1,3 @@
|
||||
import { createPreset } from "fumadocs-ui/tailwind-plugin";
|
||||
|
||||
/** @type {import('tailwindcss').Config} */
|
||||
export default {
|
||||
darkMode: ["class"],
|
||||
@@ -8,13 +6,7 @@ export default {
|
||||
"./src/app/**/*.{ts,tsx}",
|
||||
"./src/content/**/*.{md,mdx}",
|
||||
"./src/mdx-components.{ts,tsx}",
|
||||
"./node_modules/fumadocs-ui/dist/**/*.js",
|
||||
"./node_modules/fumadocs-openapi/dist/**/*.js",
|
||||
"./node_modules/@llamaindex/chat-ui/**/*.{ts,tsx}",
|
||||
],
|
||||
presets: [createPreset()],
|
||||
// eslint-disable-next-line @typescript-eslint/no-require-imports
|
||||
plugins: [require("tailwindcss-animate")],
|
||||
theme: {
|
||||
extend: {
|
||||
borderRadius: {
|
||||
@@ -16,7 +16,8 @@
|
||||
"jsx": "preserve",
|
||||
"incremental": true,
|
||||
"paths": {
|
||||
"@/*": ["./src/*"]
|
||||
"@/*": ["./src/*"],
|
||||
"@/.source": ["./.source/index.ts"]
|
||||
},
|
||||
"plugins": [
|
||||
{
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
{
|
||||
"$schema": "https://turbo.build/schema.json",
|
||||
"extends": ["//"],
|
||||
"tasks": {
|
||||
"build": {
|
||||
@@ -8,6 +9,11 @@
|
||||
"next-env.d.ts",
|
||||
"src/content/docs/cloud/api/**",
|
||||
"src/content/docs/api/**"
|
||||
],
|
||||
"env": [
|
||||
"LLAMA_CLOUD_API_KEY",
|
||||
"LLAMA_CLOUD_PIPELINE_ID",
|
||||
"OPENAI_API_KEY"
|
||||
]
|
||||
},
|
||||
"dev": {
|
||||
|
||||
@@ -11,7 +11,7 @@
|
||||
},
|
||||
"devDependencies": {
|
||||
"@cloudflare/workers-types": "^4.20241112.0",
|
||||
"typescript": "^5.7.2",
|
||||
"typescript": "^5.7.3",
|
||||
"wrangler": "^3.89.0"
|
||||
},
|
||||
"dependencies": {
|
||||
|
||||
@@ -1,5 +1,40 @@
|
||||
# @llamaindex/cloudflare-worker-agent-test
|
||||
|
||||
## 0.0.144
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [c1b5be5]
|
||||
- Updated dependencies [40ee761]
|
||||
- Updated dependencies [40ee761]
|
||||
- llamaindex@0.9.10
|
||||
|
||||
## 0.0.143
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.9
|
||||
|
||||
## 0.0.142
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [bbc8c87]
|
||||
- llamaindex@0.9.8
|
||||
|
||||
## 0.0.141
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [beb922b]
|
||||
- llamaindex@0.9.7
|
||||
|
||||
## 0.0.140
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.6
|
||||
|
||||
## 0.0.139
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/cloudflare-worker-agent-test",
|
||||
"version": "0.0.139",
|
||||
"version": "0.0.144",
|
||||
"type": "module",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
@@ -16,7 +16,7 @@
|
||||
"@cloudflare/workers-types": "^4.20241112.0",
|
||||
"@vitest/runner": "2.1.5",
|
||||
"@vitest/snapshot": "2.1.5",
|
||||
"typescript": "^5.7.2",
|
||||
"typescript": "^5.7.3",
|
||||
"vitest": "2.1.5",
|
||||
"wrangler": "^3.87.0"
|
||||
},
|
||||
|
||||
@@ -1,5 +1,29 @@
|
||||
# @llamaindex/llama-parse-browser-test
|
||||
|
||||
## 0.0.54
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/cloud@3.0.9
|
||||
|
||||
## 0.0.53
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/cloud@3.0.8
|
||||
|
||||
## 0.0.52
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/cloud@3.0.7
|
||||
|
||||
## 0.0.51
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/cloud@3.0.6
|
||||
|
||||
## 0.0.50
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "@llamaindex/llama-parse-browser-test",
|
||||
"private": true,
|
||||
"version": "0.0.50",
|
||||
"version": "0.0.54",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
@@ -9,7 +9,7 @@
|
||||
"preview": "vite preview"
|
||||
},
|
||||
"devDependencies": {
|
||||
"typescript": "^5.7.2",
|
||||
"typescript": "^5.7.3",
|
||||
"vite": "^5.4.12",
|
||||
"vite-plugin-wasm": "^3.3.0"
|
||||
},
|
||||
|
||||
@@ -1,5 +1,40 @@
|
||||
# @llamaindex/next-agent-test
|
||||
|
||||
## 0.1.144
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [c1b5be5]
|
||||
- Updated dependencies [40ee761]
|
||||
- Updated dependencies [40ee761]
|
||||
- llamaindex@0.9.10
|
||||
|
||||
## 0.1.143
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.9
|
||||
|
||||
## 0.1.142
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [bbc8c87]
|
||||
- llamaindex@0.9.8
|
||||
|
||||
## 0.1.141
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [beb922b]
|
||||
- llamaindex@0.9.7
|
||||
|
||||
## 0.1.140
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.6
|
||||
|
||||
## 0.1.139
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/next-agent-test",
|
||||
"version": "0.1.139",
|
||||
"version": "0.1.144",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
@@ -10,18 +10,16 @@
|
||||
"dependencies": {
|
||||
"ai": "^4.0.0",
|
||||
"llamaindex": "workspace:*",
|
||||
"next": "15.1.7",
|
||||
"next": "15.2.0",
|
||||
"react": "19.0.0",
|
||||
"react-dom": "19.0.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^22.9.0",
|
||||
"@types/react": "^18.3.12",
|
||||
"@types/react-dom": "^18.3.1",
|
||||
"@types/react": "^19.0.10",
|
||||
"@types/react-dom": "^19.0.4",
|
||||
"eslint": "9.16.0",
|
||||
"eslint-config-next": "15.1.0",
|
||||
"postcss": "^8.4.49",
|
||||
"tailwindcss": "^3.4.15",
|
||||
"typescript": "^5.7.2"
|
||||
"typescript": "^5.7.3"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,8 +0,0 @@
|
||||
/** @type {import('postcss-load-config').Config} */
|
||||
const config = {
|
||||
plugins: {
|
||||
tailwindcss: {},
|
||||
},
|
||||
};
|
||||
|
||||
export default config;
|
||||
@@ -1,3 +0,0 @@
|
||||
@tailwind base;
|
||||
@tailwind components;
|
||||
@tailwind utilities;
|
||||
@@ -1,6 +1,5 @@
|
||||
import type { Metadata } from "next";
|
||||
import { Inter } from "next/font/google";
|
||||
import "./globals.css";
|
||||
|
||||
const inter = Inter({ subsets: ["latin"] });
|
||||
|
||||
|
||||
@@ -1,20 +0,0 @@
|
||||
import type { Config } from "tailwindcss";
|
||||
|
||||
const config: Config = {
|
||||
content: [
|
||||
"./src/pages/**/*.{js,ts,jsx,tsx,mdx}",
|
||||
"./src/components/**/*.{js,ts,jsx,tsx,mdx}",
|
||||
"./src/app/**/*.{js,ts,jsx,tsx,mdx}",
|
||||
],
|
||||
theme: {
|
||||
extend: {
|
||||
backgroundImage: {
|
||||
"gradient-radial": "radial-gradient(var(--tw-gradient-stops))",
|
||||
"gradient-conic":
|
||||
"conic-gradient(from 180deg at 50% 50%, var(--tw-gradient-stops))",
|
||||
},
|
||||
},
|
||||
},
|
||||
plugins: [],
|
||||
};
|
||||
export default config;
|
||||
@@ -1,5 +1,40 @@
|
||||
# test-edge-runtime
|
||||
|
||||
## 0.1.143
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [c1b5be5]
|
||||
- Updated dependencies [40ee761]
|
||||
- Updated dependencies [40ee761]
|
||||
- llamaindex@0.9.10
|
||||
|
||||
## 0.1.142
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.9
|
||||
|
||||
## 0.1.141
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [bbc8c87]
|
||||
- llamaindex@0.9.8
|
||||
|
||||
## 0.1.140
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [beb922b]
|
||||
- llamaindex@0.9.7
|
||||
|
||||
## 0.1.139
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.6
|
||||
|
||||
## 0.1.138
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/nextjs-edge-runtime-test",
|
||||
"version": "0.1.138",
|
||||
"version": "0.1.143",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
@@ -9,14 +9,14 @@
|
||||
},
|
||||
"dependencies": {
|
||||
"llamaindex": "workspace:*",
|
||||
"next": "15.1.7",
|
||||
"react": "^18.3.1",
|
||||
"react-dom": "^18.3.1"
|
||||
"next": "15.2.0",
|
||||
"react": "^19.0.0",
|
||||
"react-dom": "^19.0.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^22.9.0",
|
||||
"@types/react": "^18.3.12",
|
||||
"@types/react-dom": "^18.3.1",
|
||||
"typescript": "^5.7.2"
|
||||
"@types/react": "^19.0.10",
|
||||
"@types/react-dom": "^19.0.4",
|
||||
"typescript": "^5.7.3"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,5 +1,49 @@
|
||||
# @llamaindex/next-node-runtime
|
||||
|
||||
## 0.1.10
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [aea550a]
|
||||
- Updated dependencies [c1b5be5]
|
||||
- Updated dependencies [40ee761]
|
||||
- Updated dependencies [40ee761]
|
||||
- @llamaindex/huggingface@0.0.44
|
||||
- llamaindex@0.9.10
|
||||
- @llamaindex/readers@2.0.8
|
||||
|
||||
## 0.1.9
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.9
|
||||
- @llamaindex/huggingface@0.0.43
|
||||
- @llamaindex/readers@2.0.7
|
||||
|
||||
## 0.1.8
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [bbc8c87]
|
||||
- llamaindex@0.9.8
|
||||
|
||||
## 0.1.7
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [beb922b]
|
||||
- llamaindex@0.9.7
|
||||
- @llamaindex/huggingface@0.0.42
|
||||
- @llamaindex/readers@2.0.6
|
||||
|
||||
## 0.1.6
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.6
|
||||
- @llamaindex/huggingface@0.0.41
|
||||
- @llamaindex/readers@2.0.5
|
||||
|
||||
## 0.1.5
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/next-node-runtime-test",
|
||||
"version": "0.1.5",
|
||||
"version": "0.1.10",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
@@ -8,21 +8,19 @@
|
||||
"start": "next start"
|
||||
},
|
||||
"dependencies": {
|
||||
"llamaindex": "workspace:*",
|
||||
"@llamaindex/huggingface": "workspace:*",
|
||||
"@llamaindex/readers": "workspace:*",
|
||||
"next": "15.1.7",
|
||||
"llamaindex": "workspace:*",
|
||||
"next": "15.2.0",
|
||||
"react": "19.0.0",
|
||||
"react-dom": "19.0.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^22.9.0",
|
||||
"@types/react": "^18.3.12",
|
||||
"@types/react-dom": "^18.3.1",
|
||||
"@types/react": "^19.0.10",
|
||||
"@types/react-dom": "^19.0.4",
|
||||
"eslint": "9.16.0",
|
||||
"eslint-config-next": "15.1.0",
|
||||
"postcss": "^8.4.49",
|
||||
"tailwindcss": "^3.4.15",
|
||||
"typescript": "^5.7.2"
|
||||
"typescript": "^5.7.3"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,8 +0,0 @@
|
||||
/** @type {import('postcss-load-config').Config} */
|
||||
const config = {
|
||||
plugins: {
|
||||
tailwindcss: {},
|
||||
},
|
||||
};
|
||||
|
||||
export default config;
|
||||
@@ -1,13 +1,7 @@
|
||||
"use server";
|
||||
import { HuggingFaceEmbedding } from "@llamaindex/huggingface";
|
||||
import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
|
||||
import {
|
||||
OpenAI,
|
||||
OpenAIAgent,
|
||||
QueryEngineTool,
|
||||
Settings,
|
||||
VectorStoreIndex,
|
||||
} from "llamaindex";
|
||||
import { OpenAI, OpenAIAgent, Settings, VectorStoreIndex } from "llamaindex";
|
||||
|
||||
Settings.llm = new OpenAI({
|
||||
apiKey: process.env.NEXT_PUBLIC_OPENAI_KEY ?? "FAKE_KEY_TO_PASS_TESTS",
|
||||
@@ -31,23 +25,20 @@ export async function getOpenAIModelRequest(query: string) {
|
||||
const reader = new SimpleDirectoryReader();
|
||||
const documents = await reader.loadData(currentDir);
|
||||
const index = await VectorStoreIndex.fromDocuments(documents);
|
||||
const retriever = index.asRetriever({
|
||||
similarityTopK: 10,
|
||||
});
|
||||
const queryEngine = index.asQueryEngine({
|
||||
retriever,
|
||||
});
|
||||
|
||||
// define the query engine as a tool
|
||||
const tools = [
|
||||
new QueryEngineTool({
|
||||
queryEngine: queryEngine,
|
||||
index.queryTool({
|
||||
options: {
|
||||
similarityTopK: 10,
|
||||
},
|
||||
metadata: {
|
||||
name: "deployment_details_per_env",
|
||||
description: `This tool can answer detailed questions about deployments happened in various environments.`,
|
||||
},
|
||||
}),
|
||||
];
|
||||
|
||||
// create the agent
|
||||
const agent = new OpenAIAgent({ tools });
|
||||
|
||||
|
||||
@@ -1,3 +0,0 @@
|
||||
@tailwind base;
|
||||
@tailwind components;
|
||||
@tailwind utilities;
|
||||
@@ -1,6 +1,5 @@
|
||||
import type { Metadata } from "next";
|
||||
import { Inter } from "next/font/google";
|
||||
import "./globals.css";
|
||||
|
||||
const inter = Inter({ subsets: ["latin"] });
|
||||
|
||||
|
||||
@@ -1,20 +0,0 @@
|
||||
import type { Config } from "tailwindcss";
|
||||
|
||||
const config: Config = {
|
||||
content: [
|
||||
"./src/pages/**/*.{js,ts,jsx,tsx,mdx}",
|
||||
"./src/components/**/*.{js,ts,jsx,tsx,mdx}",
|
||||
"./src/app/**/*.{js,ts,jsx,tsx,mdx}",
|
||||
],
|
||||
theme: {
|
||||
extend: {
|
||||
backgroundImage: {
|
||||
"gradient-radial": "radial-gradient(var(--tw-gradient-stops))",
|
||||
"gradient-conic":
|
||||
"conic-gradient(from 180deg at 50% 50%, var(--tw-gradient-stops))",
|
||||
},
|
||||
},
|
||||
},
|
||||
plugins: [],
|
||||
};
|
||||
export default config;
|
||||
@@ -1,5 +1,40 @@
|
||||
# vite-import-llamaindex
|
||||
|
||||
## 0.0.10
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [c1b5be5]
|
||||
- Updated dependencies [40ee761]
|
||||
- Updated dependencies [40ee761]
|
||||
- llamaindex@0.9.10
|
||||
|
||||
## 0.0.9
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.9
|
||||
|
||||
## 0.0.8
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [bbc8c87]
|
||||
- llamaindex@0.9.8
|
||||
|
||||
## 0.0.7
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [beb922b]
|
||||
- llamaindex@0.9.7
|
||||
|
||||
## 0.0.6
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.6
|
||||
|
||||
## 0.0.5
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "vite-import-llamaindex",
|
||||
"private": true,
|
||||
"version": "0.0.5",
|
||||
"version": "0.0.10",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"build": "vite build",
|
||||
@@ -15,7 +15,7 @@
|
||||
"devDependencies": {
|
||||
"@size-limit/preset-big-lib": "^11.1.6",
|
||||
"size-limit": "^11.1.6",
|
||||
"typescript": "^5.7.2",
|
||||
"typescript": "^5.7.3",
|
||||
"vite": "^6.1.0"
|
||||
},
|
||||
"dependencies": {
|
||||
|
||||
@@ -1,5 +1,41 @@
|
||||
# @llamaindex/waku-query-engine-test
|
||||
|
||||
## 0.0.144
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [c1b5be5]
|
||||
- Updated dependencies [40ee761]
|
||||
- Updated dependencies [40ee761]
|
||||
- llamaindex@0.9.10
|
||||
|
||||
## 0.0.143
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.9
|
||||
|
||||
## 0.0.142
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [bbc8c87]
|
||||
- llamaindex@0.9.8
|
||||
|
||||
## 0.0.141
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [beb922b]
|
||||
- @llamaindex/env@0.1.29
|
||||
- llamaindex@0.9.7
|
||||
|
||||
## 0.0.140
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.6
|
||||
|
||||
## 0.0.139
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/waku-query-engine-test",
|
||||
"version": "0.0.139",
|
||||
"version": "0.0.144",
|
||||
"type": "module",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
@@ -17,10 +17,10 @@
|
||||
"waku": "0.21.20"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/react": "18.3.12",
|
||||
"@types/react-dom": "18.3.1",
|
||||
"@types/react": "19.0.10",
|
||||
"@types/react-dom": "19.0.4",
|
||||
"autoprefixer": "^10.4.20",
|
||||
"tailwindcss": "^3.4.15",
|
||||
"typescript": "5.7.2"
|
||||
"tailwindcss": "^4.0.9",
|
||||
"typescript": "5.7.3"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,7 +0,0 @@
|
||||
/** @type {import('postcss-load-config').Config} */
|
||||
export default {
|
||||
plugins: {
|
||||
tailwindcss: {},
|
||||
autoprefixer: {},
|
||||
},
|
||||
};
|
||||
@@ -0,0 +1,5 @@
|
||||
export default {
|
||||
plugins: {
|
||||
"@tailwindcss/postcss": {},
|
||||
},
|
||||
};
|
||||
@@ -10,10 +10,10 @@ export const Chat = (props: ChatProps) => {
|
||||
const [response, setResponse] = useState<string | null>(null);
|
||||
|
||||
return (
|
||||
<section className="border-blue-400 -mx-4 mt-4 rounded border border-dashed p-4">
|
||||
<section className="-mx-4 mt-4 rounded border border-dashed border-blue-400 p-4">
|
||||
<h2 className="text-lg font-bold">Chat with AI</h2>
|
||||
{response ? (
|
||||
<p className="text-sm text-gray-600 max-w-sm">{response}</p>
|
||||
<p className="max-w-sm text-sm text-gray-600">{response}</p>
|
||||
) : null}
|
||||
<form
|
||||
action={async (formData) => {
|
||||
@@ -26,7 +26,7 @@ export const Chat = (props: ChatProps) => {
|
||||
<input
|
||||
type="text"
|
||||
name="question"
|
||||
className="border border-gray-400 rounded-sm px-2 py-0.5 text-sm"
|
||||
className="rounded-sm border border-gray-400 px-2 py-0.5 text-sm"
|
||||
/>
|
||||
<button className="rounded-sm bg-black px-2 py-0.5 text-sm text-white">
|
||||
Ask
|
||||
|
||||
@@ -1,4 +1,2 @@
|
||||
@import url("https://fonts.googleapis.com/css2?family=Nunito:ital,wght@0,400;0,700;1,400;1,700&display=swap");
|
||||
@tailwind base;
|
||||
@tailwind components;
|
||||
@tailwind utilities;
|
||||
@import "tailwindcss";
|
||||
|
||||
+22
-38
@@ -1,4 +1,5 @@
|
||||
import { FunctionTool } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
function sumNumbers({ a, b }: { a: number; b: number }) {
|
||||
return `${a + b}`;
|
||||
@@ -11,39 +12,27 @@ function divideNumbers({ a, b }: { a: number; b: number }) {
|
||||
export const sumNumbersTool = FunctionTool.from(sumNumbers, {
|
||||
name: "sumNumbers",
|
||||
description: "Use this function to sum two numbers",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "The first number",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "The second number",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
},
|
||||
parameters: z.object({
|
||||
a: z.number({
|
||||
description: "The first number",
|
||||
}),
|
||||
b: z.number({
|
||||
description: "The second number",
|
||||
}),
|
||||
}),
|
||||
});
|
||||
|
||||
export const divideNumbersTool = FunctionTool.from(divideNumbers, {
|
||||
name: "divideNumbers",
|
||||
description: "Use this function to divide two numbers",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "The first number",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "The second number",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
},
|
||||
parameters: z.object({
|
||||
a: z.number({
|
||||
description: "The first number",
|
||||
}),
|
||||
b: z.number({
|
||||
description: "The second number",
|
||||
}),
|
||||
}),
|
||||
});
|
||||
|
||||
// should always return the 72 degrees
|
||||
@@ -54,15 +43,10 @@ export const getWeatherTool = FunctionTool.from(
|
||||
{
|
||||
name: "getWeather",
|
||||
description: "Get the weather for a city",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
city: {
|
||||
type: "string",
|
||||
description: "The city to get the weather for",
|
||||
},
|
||||
},
|
||||
required: ["city"],
|
||||
},
|
||||
parameters: z.object({
|
||||
city: z.string({
|
||||
description: "The city to get the weather for",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
+5
-4
@@ -10,22 +10,23 @@
|
||||
},
|
||||
"devDependencies": {
|
||||
"@faker-js/faker": "^9.2.0",
|
||||
"@huggingface/transformers": "^3.0.2",
|
||||
"@llamaindex/anthropic": "workspace:*",
|
||||
"@llamaindex/clip": "workspace:*",
|
||||
"@llamaindex/core": "workspace:*",
|
||||
"@llamaindex/env": "workspace:*",
|
||||
"@llamaindex/ollama": "workspace:*",
|
||||
"@llamaindex/openai": "workspace:*",
|
||||
"@llamaindex/pinecone": "workspace:*",
|
||||
"@llamaindex/postgres": "workspace:*",
|
||||
"@llamaindex/clip": "workspace:*",
|
||||
"@llamaindex/anthropic": "workspace:*",
|
||||
"@types/node": "^22.9.0",
|
||||
"@types/pg": "^8.11.8",
|
||||
"@huggingface/transformers": "^3.0.2",
|
||||
"consola": "^3.2.3",
|
||||
"dotenv": "^16.4.5",
|
||||
"llamaindex": "workspace:*",
|
||||
"pg": "^8.12.0",
|
||||
"pgvector": "0.2.0",
|
||||
"tsx": "^4.19.0"
|
||||
"tsx": "^4.19.3",
|
||||
"zod": "^3.24.2"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,5 +1,194 @@
|
||||
# examples
|
||||
|
||||
## 0.2.9
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- aea550a: Add factory convenience factory for each LLM provider, e.g. you can use openai instead of 'new OpenAI'
|
||||
- Updated dependencies [c14a21b]
|
||||
- Updated dependencies [33f9856]
|
||||
- Updated dependencies [aea550a]
|
||||
- Updated dependencies [c1b5be5]
|
||||
- Updated dependencies [40ee761]
|
||||
- Updated dependencies [40ee761]
|
||||
- @llamaindex/azure@0.1.8
|
||||
- @llamaindex/google@0.1.1
|
||||
- @llamaindex/huggingface@0.0.44
|
||||
- @llamaindex/portkey-ai@0.0.41
|
||||
- @llamaindex/anthropic@0.2.6
|
||||
- @llamaindex/deepinfra@0.0.44
|
||||
- @llamaindex/fireworks@0.0.4
|
||||
- @llamaindex/replicate@0.0.41
|
||||
- @llamaindex/deepseek@0.0.4
|
||||
- @llamaindex/together@0.0.4
|
||||
- @llamaindex/mistral@0.0.13
|
||||
- @llamaindex/ollama@0.0.48
|
||||
- @llamaindex/openai@0.1.60
|
||||
- @llamaindex/vercel@0.0.19
|
||||
- @llamaindex/groq@0.0.59
|
||||
- @llamaindex/vllm@0.0.30
|
||||
- llamaindex@0.9.10
|
||||
- @llamaindex/workflow@0.0.16
|
||||
- @llamaindex/core@0.5.8
|
||||
- @llamaindex/clip@0.0.44
|
||||
- @llamaindex/jinaai@0.0.4
|
||||
- @llamaindex/milvus@0.1.8
|
||||
- @llamaindex/qdrant@0.1.8
|
||||
- @llamaindex/cloud@3.0.9
|
||||
- @llamaindex/node-parser@1.0.8
|
||||
- @llamaindex/cohere@0.0.13
|
||||
- @llamaindex/mixedbread@0.0.13
|
||||
- @llamaindex/astra@0.0.13
|
||||
- @llamaindex/chroma@0.0.13
|
||||
- @llamaindex/firestore@1.0.6
|
||||
- @llamaindex/mongodb@0.0.13
|
||||
- @llamaindex/pinecone@0.0.13
|
||||
- @llamaindex/postgres@0.0.41
|
||||
- @llamaindex/upstash@0.0.13
|
||||
- @llamaindex/weaviate@0.0.13
|
||||
- @llamaindex/voyage-ai@1.0.5
|
||||
- @llamaindex/readers@2.0.8
|
||||
|
||||
## 0.2.8
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [58b3ee5]
|
||||
- Updated dependencies [4bac71d]
|
||||
- Updated dependencies [8bf1ca1]
|
||||
- @llamaindex/google@0.1.0
|
||||
- @llamaindex/core@0.5.7
|
||||
- @llamaindex/anthropic@0.2.5
|
||||
- @llamaindex/cloud@3.0.8
|
||||
- llamaindex@0.9.9
|
||||
- @llamaindex/node-parser@1.0.7
|
||||
- @llamaindex/clip@0.0.43
|
||||
- @llamaindex/cohere@0.0.12
|
||||
- @llamaindex/deepinfra@0.0.43
|
||||
- @llamaindex/huggingface@0.0.43
|
||||
- @llamaindex/jinaai@0.0.3
|
||||
- @llamaindex/mistral@0.0.12
|
||||
- @llamaindex/mixedbread@0.0.12
|
||||
- @llamaindex/ollama@0.0.47
|
||||
- @llamaindex/openai@0.1.59
|
||||
- @llamaindex/portkey-ai@0.0.40
|
||||
- @llamaindex/replicate@0.0.40
|
||||
- @llamaindex/astra@0.0.12
|
||||
- @llamaindex/azure@0.1.7
|
||||
- @llamaindex/chroma@0.0.12
|
||||
- @llamaindex/firestore@1.0.5
|
||||
- @llamaindex/milvus@0.1.7
|
||||
- @llamaindex/mongodb@0.0.12
|
||||
- @llamaindex/pinecone@0.0.12
|
||||
- @llamaindex/postgres@0.0.40
|
||||
- @llamaindex/qdrant@0.1.7
|
||||
- @llamaindex/upstash@0.0.12
|
||||
- @llamaindex/weaviate@0.0.12
|
||||
- @llamaindex/vercel@0.0.18
|
||||
- @llamaindex/voyage-ai@1.0.4
|
||||
- @llamaindex/readers@2.0.7
|
||||
- @llamaindex/workflow@0.0.15
|
||||
- @llamaindex/deepseek@0.0.3
|
||||
- @llamaindex/fireworks@0.0.3
|
||||
- @llamaindex/groq@0.0.58
|
||||
- @llamaindex/together@0.0.3
|
||||
- @llamaindex/vllm@0.0.29
|
||||
|
||||
## 0.2.7
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [4b49428]
|
||||
- Updated dependencies [bbc8c87]
|
||||
- Updated dependencies [7ee4968]
|
||||
- @llamaindex/workflow@0.0.14
|
||||
- llamaindex@0.9.8
|
||||
- @llamaindex/deepseek@0.0.2
|
||||
- @llamaindex/fireworks@0.0.2
|
||||
- @llamaindex/together@0.0.2
|
||||
- @llamaindex/jinaai@0.0.2
|
||||
- @llamaindex/google@0.0.14
|
||||
|
||||
## 0.2.6
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [beb922b]
|
||||
- @llamaindex/env@0.1.29
|
||||
- @llamaindex/core@0.5.6
|
||||
- llamaindex@0.9.7
|
||||
- @llamaindex/cloud@3.0.7
|
||||
- @llamaindex/node-parser@1.0.6
|
||||
- @llamaindex/anthropic@0.2.4
|
||||
- @llamaindex/clip@0.0.42
|
||||
- @llamaindex/cohere@0.0.11
|
||||
- @llamaindex/deepinfra@0.0.42
|
||||
- @llamaindex/google@0.0.13
|
||||
- @llamaindex/groq@0.0.57
|
||||
- @llamaindex/huggingface@0.0.42
|
||||
- @llamaindex/mistral@0.0.11
|
||||
- @llamaindex/mixedbread@0.0.11
|
||||
- @llamaindex/ollama@0.0.46
|
||||
- @llamaindex/openai@0.1.58
|
||||
- @llamaindex/portkey-ai@0.0.39
|
||||
- @llamaindex/replicate@0.0.39
|
||||
- @llamaindex/astra@0.0.11
|
||||
- @llamaindex/azure@0.1.6
|
||||
- @llamaindex/chroma@0.0.11
|
||||
- @llamaindex/firestore@1.0.4
|
||||
- @llamaindex/milvus@0.1.6
|
||||
- @llamaindex/mongodb@0.0.11
|
||||
- @llamaindex/pinecone@0.0.11
|
||||
- @llamaindex/postgres@0.0.39
|
||||
- @llamaindex/qdrant@0.1.6
|
||||
- @llamaindex/upstash@0.0.11
|
||||
- @llamaindex/weaviate@0.0.11
|
||||
- @llamaindex/voyage-ai@1.0.3
|
||||
- @llamaindex/readers@2.0.6
|
||||
- @llamaindex/workflow@0.0.13
|
||||
- @llamaindex/vercel@0.0.17
|
||||
- @llamaindex/vllm@0.0.28
|
||||
|
||||
## 0.2.5
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [5668970]
|
||||
- Updated dependencies [fd74ba4]
|
||||
- @llamaindex/core@0.5.5
|
||||
- @llamaindex/workflow@0.0.12
|
||||
- @llamaindex/voyage-ai@1.0.2
|
||||
- @llamaindex/cloud@3.0.6
|
||||
- llamaindex@0.9.6
|
||||
- @llamaindex/node-parser@1.0.5
|
||||
- @llamaindex/anthropic@0.2.3
|
||||
- @llamaindex/clip@0.0.41
|
||||
- @llamaindex/cohere@0.0.10
|
||||
- @llamaindex/deepinfra@0.0.41
|
||||
- @llamaindex/google@0.0.12
|
||||
- @llamaindex/huggingface@0.0.41
|
||||
- @llamaindex/mistral@0.0.10
|
||||
- @llamaindex/mixedbread@0.0.10
|
||||
- @llamaindex/ollama@0.0.45
|
||||
- @llamaindex/openai@0.1.57
|
||||
- @llamaindex/portkey-ai@0.0.38
|
||||
- @llamaindex/replicate@0.0.38
|
||||
- @llamaindex/astra@0.0.10
|
||||
- @llamaindex/azure@0.1.5
|
||||
- @llamaindex/chroma@0.0.10
|
||||
- @llamaindex/firestore@1.0.3
|
||||
- @llamaindex/milvus@0.1.5
|
||||
- @llamaindex/mongodb@0.0.10
|
||||
- @llamaindex/pinecone@0.0.10
|
||||
- @llamaindex/postgres@0.0.38
|
||||
- @llamaindex/qdrant@0.1.5
|
||||
- @llamaindex/upstash@0.0.10
|
||||
- @llamaindex/weaviate@0.0.10
|
||||
- @llamaindex/vercel@0.0.16
|
||||
- @llamaindex/readers@2.0.5
|
||||
- @llamaindex/groq@0.0.56
|
||||
- @llamaindex/vllm@0.0.27
|
||||
|
||||
## 0.2.4
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
|
||||
import { FunctionTool } from "llamaindex";
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import { FunctionTool, agent } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
const csvData =
|
||||
"TITLE,RELEASE_YEAR,SCORE,NUMBER_OF_VOTES,DURATION,MAIN_GENRE,MAIN_PRODUCTION\nDavid Attenborough: A Life on Our Planet,2020,9,31180,83,documentary,GB\nInception,2010,8.8,2268288,148,scifi,GB\nForrest Gump,1994,8.8,1994599,142,drama,US\nAnbe Sivam,2003,8.7,20595,160,comedy,IN\nBo Burnham: Inside,2021,8.7,44074,87,comedy,US\nSaving Private Ryan,1998,8.6,1346020,169,drama,US\nDjango Unchained,2012,8.4,1472668,165,western,US\nDangal,2016,8.4,180247,161,action,IN\nBo Burnham: Make Happy,2016,8.4,14356,60,comedy,US\nLouis C.K.: Hilarious,2010,8.4,11973,84,comedy,US\nDave Chappelle: Sticks & Stones,2019,8.4,25687,65,comedy,US\n3 Idiots,2009,8.4,385782,170,comedy,IN\nBlack Friday,2004,8.4,20611,143,crime,IN\nSuper Deluxe,2019,8.4,13680,176,thriller,IN\nWinter on Fire: Ukraine's Fight for Freedom,2015,8.3,17710,98,documentary,UA\nOnce Upon a Time in America,1984,8.3,342335,229,drama,US\nTaxi Driver,1976,8.3,795222,113,crime,US\nLike Stars on Earth,2007,8.3,188234,165,drama,IN\nBo Burnham: What.,2013,8.3,11488,60,comedy,US\nFull Metal Jacket,1987,8.3,723306,116,drama,GB\nWarrior,2011,8.2,463276,140,drama,US\nDrishyam,2015,8.2,79075,163,thriller,IN\nQueen,2014,8.2,64805,146,drama,IN\nPaan Singh Tomar,2012,8.2,35888,135,drama,IN";
|
||||
@@ -8,13 +9,9 @@ const userQuestion = "which are the best comedies after 2010?";
|
||||
|
||||
(async () => {
|
||||
// The agent will succeed if we increase `maxTokens` to 1024
|
||||
const llm = new OpenAI({ model: "gpt-4-turbo", maxTokens: 256 });
|
||||
const llm = new OpenAI({ model: "gpt-4-turbo", maxTokens: 1024 });
|
||||
|
||||
type Input = {
|
||||
code: string;
|
||||
};
|
||||
// initiate fake code interpreter
|
||||
const interpreterTool = FunctionTool.from<Input>(
|
||||
const interpreterTool = FunctionTool.from(
|
||||
({ code }) => {
|
||||
console.log(
|
||||
`To answer the user's question, call the following code:\n${code}`,
|
||||
@@ -25,41 +22,34 @@ const userQuestion = "which are the best comedies after 2010?";
|
||||
name: "interpreter",
|
||||
description:
|
||||
"Execute python code in a Jupyter notebook cell and return any result, stdout, stderr, display_data, and error.",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
code: {
|
||||
type: "string",
|
||||
description: "The python code to execute in a single cell.",
|
||||
},
|
||||
},
|
||||
required: ["code"],
|
||||
},
|
||||
parameters: z.object({
|
||||
code: z.string({
|
||||
description: "The python code to execute in a single cell.",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
const systemPrompt =
|
||||
"You are a Python interpreter.\n - You are given tasks to complete and you run python code to solve them.\n - The python code runs in a Jupyter notebook. Every time you call $(interpreter) tool, the python code is executed in a separate cell. It's okay to make multiple calls to $(interpreter).\n - Display visualizations using matplotlib or any other visualization library directly in the notebook. Shouldn't save the visualizations to a file, just return the base64 encoded data.\n - You can install any pip package (if it exists) if you need to but the usual packages for data analysis are already preinstalled.\n - You can run any python code you want in a secure environment.";
|
||||
|
||||
const agent = new OpenAIAgent({
|
||||
llm,
|
||||
const workflow = agent({
|
||||
tools: [interpreterTool],
|
||||
llm,
|
||||
verbose: false,
|
||||
systemPrompt,
|
||||
verbose: true,
|
||||
});
|
||||
|
||||
console.log(`User question: ${userQuestion}\n`);
|
||||
|
||||
await agent.chat({
|
||||
message: [
|
||||
const result = await workflow.run(userQuestion, {
|
||||
chatHistory: [
|
||||
{
|
||||
type: "text",
|
||||
text: userQuestion,
|
||||
},
|
||||
{
|
||||
type: "text",
|
||||
text: `Use data from following CSV raw contents:\n${csvData}`,
|
||||
role: "user",
|
||||
content: `Use data from following CSV raw contents:\n${csvData}`,
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
console.log(result);
|
||||
})();
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import { FunctionTool, ToolCallOptions } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
(async () => {
|
||||
// The tool call will generate a partial JSON for `gpt-4-turbo`
|
||||
@@ -27,16 +28,11 @@ async function callLLM(init: { model: string }) {
|
||||
name: "interpreter",
|
||||
description:
|
||||
"Execute python code in a Jupyter notebook cell and return any result, stdout, stderr, display_data, and error.",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
code: {
|
||||
type: "string",
|
||||
description: "The python code to execute in a single cell.",
|
||||
},
|
||||
},
|
||||
required: ["code"],
|
||||
},
|
||||
parameters: z.object({
|
||||
code: z.string({
|
||||
description: "The python code to execute in a single cell.",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
|
||||
+16
-36
@@ -1,25 +1,16 @@
|
||||
import { OpenAIAgent } from "@llamaindex/openai";
|
||||
import { FunctionTool } from "llamaindex";
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import { FunctionTool, agent } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
const sumNumbers = FunctionTool.from(
|
||||
({ a, b }: { a: number; b: number }) => `${a + b}`,
|
||||
{
|
||||
name: "sumNumbers",
|
||||
description: "Use this function to sum two numbers",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "The first number",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "The second number",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
},
|
||||
parameters: z.object({
|
||||
a: z.number().describe("The first number"),
|
||||
b: z.number().describe("The second number"),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
@@ -28,33 +19,22 @@ const divideNumbers = FunctionTool.from(
|
||||
{
|
||||
name: "divideNumbers",
|
||||
description: "Use this function to divide two numbers",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "The dividend a to divide",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "The divisor b to divide by",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
},
|
||||
parameters: z.object({
|
||||
a: z.number().describe("The dividend a to divide"),
|
||||
b: z.number().describe("The divisor b to divide by"),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
async function main() {
|
||||
const agent = new OpenAIAgent({
|
||||
const workflow = agent({
|
||||
tools: [sumNumbers, divideNumbers],
|
||||
llm: new OpenAI({ model: "gpt-4o-mini" }),
|
||||
verbose: false,
|
||||
});
|
||||
|
||||
const response = await agent.chat({
|
||||
message: "How much is 5 + 5? then divide by 2",
|
||||
});
|
||||
|
||||
console.log(response.message);
|
||||
const response = await workflow.run("How much is 5 + 5? then divide by 2");
|
||||
console.log(response.data);
|
||||
}
|
||||
|
||||
void main().then(() => {
|
||||
|
||||
@@ -6,6 +6,7 @@ import {
|
||||
NodeWithScore,
|
||||
VectorStoreIndex,
|
||||
} from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
async function main() {
|
||||
// Load the documents
|
||||
@@ -32,16 +33,9 @@ async function main() {
|
||||
{
|
||||
name: "get_abramov_info",
|
||||
description: "Get information about the Abramov documents",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
query: {
|
||||
type: "string",
|
||||
description: "The query about Abramov",
|
||||
},
|
||||
},
|
||||
required: ["query"],
|
||||
},
|
||||
parameters: z.object({
|
||||
query: z.string().describe("The query about Abramov"),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
import { OpenAIAgent } from "@llamaindex/openai";
|
||||
import { FunctionTool } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
// Define a function to sum two numbers
|
||||
function sumNumbers({ a, b }: { a: number; b: number }) {
|
||||
@@ -11,50 +12,29 @@ function divideNumbers({ a, b }: { a: number; b: number }) {
|
||||
return `${a / b}`;
|
||||
}
|
||||
|
||||
// Define the parameters of the sum function as a JSON schema
|
||||
const sumJSON = {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "The first number",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "The second number",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
} as const;
|
||||
const sumSchema = z.object({
|
||||
a: z.number().describe("The first number"),
|
||||
b: z.number().describe("The second number"),
|
||||
});
|
||||
|
||||
const divideJSON = {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "The dividend",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "The divisor",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
} as const;
|
||||
const divideSchema = z.object({
|
||||
a: z.number().describe("The dividend"),
|
||||
b: z.number().describe("The divisor"),
|
||||
});
|
||||
|
||||
async function main() {
|
||||
// Create a function tool from the sum function
|
||||
const functionTool = FunctionTool.from(sumNumbers, {
|
||||
name: "sumNumbers",
|
||||
description: "Use this function to sum two numbers",
|
||||
parameters: sumJSON,
|
||||
parameters: sumSchema,
|
||||
});
|
||||
|
||||
// Create a function tool from the divide function
|
||||
const functionTool2 = FunctionTool.from(divideNumbers, {
|
||||
name: "divideNumbers",
|
||||
description: "Use this function to divide two numbers",
|
||||
parameters: divideJSON,
|
||||
parameters: divideSchema,
|
||||
});
|
||||
|
||||
// Create an OpenAIAgent with the function tools
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
import { FunctionTool } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
export const getCurrentIDTool = FunctionTool.from(
|
||||
() => {
|
||||
@@ -19,16 +20,9 @@ export const getUserInfoTool = FunctionTool.from(
|
||||
{
|
||||
name: "get_user_info",
|
||||
description: "Get user info",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
userId: {
|
||||
type: "string",
|
||||
description: "The user id",
|
||||
},
|
||||
},
|
||||
required: ["userId"],
|
||||
},
|
||||
parameters: z.object({
|
||||
userId: z.string().describe("The user id"),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
@@ -40,15 +34,8 @@ export const getWeatherTool = FunctionTool.from(
|
||||
{
|
||||
name: "get_weather",
|
||||
description: "Get the current weather for a location",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
address: {
|
||||
type: "string",
|
||||
description: "The address",
|
||||
},
|
||||
},
|
||||
required: ["address"],
|
||||
},
|
||||
parameters: z.object({
|
||||
address: z.string().describe("The address"),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
+14
-10
@@ -1,24 +1,28 @@
|
||||
import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import { AgentStream, agent } from "llamaindex";
|
||||
import { WikipediaTool } from "../wiki";
|
||||
|
||||
async function main() {
|
||||
const llm = new OpenAI({ model: "gpt-4-turbo" });
|
||||
const wikiTool = new WikipediaTool();
|
||||
|
||||
// Create an OpenAIAgent with the Wikipedia tool
|
||||
const agent = new OpenAIAgent({
|
||||
llm,
|
||||
const workflow = agent({
|
||||
tools: [wikiTool],
|
||||
llm,
|
||||
verbose: false,
|
||||
});
|
||||
|
||||
// Chat with the agent
|
||||
const response = await agent.chat({
|
||||
message: "Who was Goethe?",
|
||||
stream: true,
|
||||
});
|
||||
const context = workflow.run("Who was Goethe?");
|
||||
|
||||
for await (const { delta } of response) {
|
||||
process.stdout.write(delta);
|
||||
for await (const event of context) {
|
||||
if (event instanceof AgentStream) {
|
||||
for (const chunk of event.data.delta) {
|
||||
process.stdout.write(chunk);
|
||||
}
|
||||
} else {
|
||||
console.log(event);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -0,0 +1,81 @@
|
||||
import { openai } from "@llamaindex/openai";
|
||||
import fs from "fs";
|
||||
import {
|
||||
agent,
|
||||
AgentToolCall,
|
||||
AgentToolCallResult,
|
||||
multiAgent,
|
||||
tool,
|
||||
} from "llamaindex";
|
||||
import os from "os";
|
||||
import { z } from "zod";
|
||||
|
||||
import { WikipediaTool } from "../wiki";
|
||||
const llm = openai({
|
||||
model: "gpt-4o-mini",
|
||||
});
|
||||
|
||||
const saveFileTool = tool({
|
||||
name: "saveFile",
|
||||
description:
|
||||
"Save the written content into a file that can be downloaded by the user",
|
||||
parameters: z.object({
|
||||
content: z.string({
|
||||
description: "The content to save into a file",
|
||||
}),
|
||||
}),
|
||||
execute: ({ content }: { content: string }) => {
|
||||
const filePath = os.tmpdir() + "/report.md";
|
||||
fs.writeFileSync(filePath, content);
|
||||
return `File saved successfully at ${filePath}`;
|
||||
},
|
||||
});
|
||||
|
||||
async function main() {
|
||||
const reportAgent = agent({
|
||||
name: "ReportAgent",
|
||||
description:
|
||||
"Responsible for crafting well-written blog posts based on research findings",
|
||||
systemPrompt: `You are a professional writer. Your task is to create an engaging blog post using the research content provided. Once complete, save the post to a file using the saveFile tool.`,
|
||||
tools: [saveFileTool],
|
||||
llm,
|
||||
});
|
||||
|
||||
const researchAgent = agent({
|
||||
name: "ResearchAgent",
|
||||
description:
|
||||
"Responsible for gathering relevant information from the internet",
|
||||
systemPrompt: `You are a research agent. Your role is to gather information from the internet using the provided tools and then transfer this information to the report agent for content creation.`,
|
||||
tools: [new WikipediaTool()],
|
||||
canHandoffTo: [reportAgent],
|
||||
llm,
|
||||
});
|
||||
|
||||
const workflow = multiAgent({
|
||||
agents: [researchAgent, reportAgent],
|
||||
rootAgent: researchAgent,
|
||||
});
|
||||
|
||||
const context = workflow.run("Write a blog post about history of LLM");
|
||||
|
||||
let finalResult;
|
||||
for await (const event of context) {
|
||||
if (event instanceof AgentToolCall) {
|
||||
console.log(
|
||||
`[Agent ${event.displayName}] executing tool ${event.data.toolName} with parameters ${JSON.stringify(
|
||||
event.data.toolKwargs,
|
||||
)}`,
|
||||
);
|
||||
} else if (event instanceof AgentToolCallResult) {
|
||||
console.log(
|
||||
`[Agent ${event.displayName}] executed tool ${event.data.toolName} with result ${event.data.toolOutput.result}`,
|
||||
);
|
||||
}
|
||||
finalResult = event;
|
||||
}
|
||||
console.log("Final result:", finalResult?.data);
|
||||
}
|
||||
|
||||
main().catch((error) => {
|
||||
console.error("Error:", error);
|
||||
});
|
||||
@@ -0,0 +1,106 @@
|
||||
/**
|
||||
* This example shows how to use AgentWorkflow with multiple agents
|
||||
* 1. FetchWeatherAgent - Fetches the weather in a city
|
||||
* 2. TemperatureConverterAgent - Converts the temperature from Fahrenheit to Celsius
|
||||
*/
|
||||
import { openai } from "@llamaindex/openai";
|
||||
import {
|
||||
agent,
|
||||
AgentInput,
|
||||
AgentOutput,
|
||||
AgentStream,
|
||||
AgentToolCall,
|
||||
AgentToolCallResult,
|
||||
multiAgent,
|
||||
StopEvent,
|
||||
tool,
|
||||
} from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
const llm = openai({
|
||||
model: "gpt-4o-mini",
|
||||
});
|
||||
|
||||
// Define tools for the agents
|
||||
const temperatureConverterTool = tool({
|
||||
description: "Convert a temperature from Fahrenheit to Celsius",
|
||||
name: "fahrenheitToCelsius",
|
||||
parameters: z.object({
|
||||
temperature: z.number({
|
||||
description: "The temperature in Fahrenheit",
|
||||
}),
|
||||
}),
|
||||
execute: ({ temperature }) => {
|
||||
return ((temperature - 32) * 5) / 9;
|
||||
},
|
||||
});
|
||||
|
||||
const temperatureFetcherTool = tool({
|
||||
description: "Fetch the temperature (in Fahrenheit) for a city",
|
||||
name: "fetchTemperature",
|
||||
parameters: z.object({
|
||||
city: z.string({
|
||||
description: "The city to fetch the temperature for",
|
||||
}),
|
||||
}),
|
||||
execute: ({ city }) => {
|
||||
const temperature = Math.floor(Math.random() * 58) + 32;
|
||||
return `The current temperature in ${city} is ${temperature}°F`;
|
||||
},
|
||||
});
|
||||
|
||||
// Create agents
|
||||
async function multiWeatherAgent() {
|
||||
const converterAgent = agent({
|
||||
name: "TemperatureConverterAgent",
|
||||
description:
|
||||
"An agent that can convert temperatures from Fahrenheit to Celsius.",
|
||||
tools: [temperatureConverterTool],
|
||||
llm,
|
||||
});
|
||||
|
||||
const weatherAgent = agent({
|
||||
name: "FetchWeatherAgent",
|
||||
description: "An agent that can get the weather in a city. ",
|
||||
systemPrompt:
|
||||
"If you can't answer the user question, hand off to other agents.",
|
||||
tools: [temperatureFetcherTool],
|
||||
llm,
|
||||
// Define which next agents can be called next if this agent cannot complete the task
|
||||
// Can be passed as agent name, e.g. "TemperatureConverterAgent"
|
||||
canHandoffTo: [converterAgent],
|
||||
});
|
||||
|
||||
// Create agent workflow with the agents
|
||||
const workflow = multiAgent({
|
||||
agents: [weatherAgent, converterAgent],
|
||||
rootAgent: weatherAgent,
|
||||
verbose: false,
|
||||
});
|
||||
|
||||
// Ask the agent to get the weather in a city
|
||||
const context = workflow.run(
|
||||
"What is the weather in San Francisco in Celsius?",
|
||||
);
|
||||
// Stream the events
|
||||
for await (const event of context) {
|
||||
// These events might be useful for UI
|
||||
if (
|
||||
event instanceof AgentToolCall ||
|
||||
event instanceof AgentToolCallResult ||
|
||||
event instanceof AgentOutput ||
|
||||
event instanceof AgentInput ||
|
||||
event instanceof StopEvent
|
||||
) {
|
||||
console.log(event);
|
||||
} else if (event instanceof AgentStream) {
|
||||
for (const chunk of event.data.delta) {
|
||||
process.stdout.write(chunk);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
multiWeatherAgent().catch((error) => {
|
||||
console.error("Error:", error);
|
||||
});
|
||||
@@ -0,0 +1,36 @@
|
||||
/**
|
||||
* This example shows how to use AgentWorkflow as a single agent with tools
|
||||
*/
|
||||
import { openai } from "@llamaindex/openai";
|
||||
import { Settings, agent } from "llamaindex";
|
||||
import { getWeatherTool } from "../agent/utils/tools";
|
||||
|
||||
Settings.llm = openai({
|
||||
model: "gpt-4o",
|
||||
});
|
||||
|
||||
async function singleWeatherAgent() {
|
||||
const workflow = agent({
|
||||
tools: [getWeatherTool],
|
||||
verbose: false,
|
||||
});
|
||||
|
||||
const workflowContext = workflow.run(
|
||||
"What's the weather like in San Francisco?",
|
||||
);
|
||||
const sfResult = await workflowContext;
|
||||
// The weather in San Francisco, CA is currently sunny.
|
||||
console.log(`${JSON.stringify(sfResult, null, 2)}`);
|
||||
|
||||
// Reuse the context from the previous run
|
||||
const workflowContext2 = workflow.run("Compare it with California?", {
|
||||
context: workflowContext.data,
|
||||
});
|
||||
const caResult = await workflowContext2;
|
||||
// Both San Francisco and California are currently experiencing sunny weather.
|
||||
console.log(`${JSON.stringify(caResult, null, 2)}`);
|
||||
}
|
||||
|
||||
singleWeatherAgent().catch((error) => {
|
||||
console.error("Error:", error);
|
||||
});
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user