mirror of
https://github.com/run-llama/LlamaIndexTS.git
synced 2026-07-11 00:04:07 -04:00
Compare commits
54 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| c4356f22a2 | |||
| f24a9dfe00 | |||
| e31d6ba472 | |||
| d212240d64 | |||
| cb73f77bb8 | |||
| 8bf1ca1701 | |||
| 58b3ee52e0 | |||
| 4bac71d6a2 | |||
| a3cbcb31a2 | |||
| bbc8c8787d | |||
| 4b49428f57 | |||
| 7ee4968b06 | |||
| 0111f5c8b0 | |||
| beb922b743 | |||
| e28c29d1f5 | |||
| 008cccd9f1 | |||
| 081698d68c | |||
| ab5fe5d7a0 | |||
| 56689707d3 | |||
| fd74ba4bf1 | |||
| b2634e47ca | |||
| ad3c7f1ec1 | |||
| 335f2df626 | |||
| ee963644bf | |||
| cb256f24ae | |||
| 1ccc04ecb5 | |||
| 034639153b | |||
| 1914b52708 | |||
| cb021e7196 | |||
| c2aa836b35 | |||
| 3b0f55f1ea | |||
| a9c6144eec | |||
| 3564244ced | |||
| d952e68ec4 | |||
| 5c026e839f | |||
| 9c1c5b4d50 | |||
| c902fcbc33 | |||
| 88d776f392 | |||
| 6fcc6bcb84 | |||
| be74207945 | |||
| 6be223dfad | |||
| 4cbfdb5f5c | |||
| 9767d1c004 | |||
| e831b28627 | |||
| cc50c9c2d4 | |||
| 954140776e | |||
| 6d37d440a6 | |||
| e724f7e9f2 | |||
| 1b029ae525 | |||
| d1db2189c9 | |||
| 2c5b4030c9 | |||
| 96eb597059 | |||
| 04098d55ff | |||
| 335a6b9e88 |
@@ -98,6 +98,7 @@ jobs:
|
||||
- nextjs-node-runtime
|
||||
- waku-query-engine
|
||||
- llama-parse-browser
|
||||
- vite-import-llamaindex
|
||||
runs-on: ubuntu-latest
|
||||
name: Build LlamaIndex Example (${{ matrix.packages }})
|
||||
steps:
|
||||
@@ -116,6 +117,30 @@ jobs:
|
||||
run: pnpm run build
|
||||
working-directory: e2e/examples/${{ matrix.packages }}
|
||||
|
||||
size-limit:
|
||||
runs-on: ubuntu-latest
|
||||
if: github.event_name == 'pull_request'
|
||||
name: Size Limit
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: pnpm/action-setup@v4
|
||||
- name: Setup Node.js
|
||||
uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version-file: ".nvmrc"
|
||||
cache: "pnpm"
|
||||
- name: Install dependencies
|
||||
run: pnpm install
|
||||
- name: Build llamaindex
|
||||
run: pnpm run build
|
||||
- uses: andresz1/size-limit-action@94bc357df29c36c8f8d50ea497c3e225c3c95d1d
|
||||
with:
|
||||
github_token: ${{ secrets.GITHUB_TOKEN }}
|
||||
directory: e2e/examples/vite-import-llamaindex
|
||||
skip_step: "install"
|
||||
build_script: build
|
||||
package_manager: pnpm
|
||||
|
||||
typecheck-examples:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
|
||||
@@ -41,8 +41,15 @@ pnpm install
|
||||
|
||||
### Build the packages
|
||||
|
||||
You'll need Turbo to build the packages. If you don't have it, you can run it with `pnpx`.
|
||||
|
||||
To build all packages, run:
|
||||
|
||||
```shell
|
||||
# Build all packages
|
||||
pnpx turbo build --filter "./packages/*"
|
||||
|
||||
# Or if you have turbo installed, you can run:
|
||||
turbo build --filter "./packages/*"
|
||||
```
|
||||
|
||||
|
||||
@@ -1,5 +1,113 @@
|
||||
# @llamaindex/doc
|
||||
|
||||
## 0.1.9
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 4bac71d: Support binding additional argument to function tool
|
||||
- Updated dependencies [4bac71d]
|
||||
- @llamaindex/core@0.5.7
|
||||
- @llamaindex/cloud@3.0.8
|
||||
- llamaindex@0.9.9
|
||||
- @llamaindex/node-parser@1.0.7
|
||||
- @llamaindex/openai@0.1.59
|
||||
- @llamaindex/readers@2.0.7
|
||||
- @llamaindex/workflow@0.0.15
|
||||
|
||||
## 0.1.8
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [4b49428]
|
||||
- Updated dependencies [bbc8c87]
|
||||
- @llamaindex/workflow@0.0.14
|
||||
- llamaindex@0.9.8
|
||||
|
||||
## 0.1.7
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [beb922b]
|
||||
- @llamaindex/core@0.5.6
|
||||
- llamaindex@0.9.7
|
||||
- @llamaindex/cloud@3.0.7
|
||||
- @llamaindex/node-parser@1.0.6
|
||||
- @llamaindex/openai@0.1.58
|
||||
- @llamaindex/readers@2.0.6
|
||||
- @llamaindex/workflow@0.0.13
|
||||
|
||||
## 0.1.6
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [5668970]
|
||||
- @llamaindex/core@0.5.5
|
||||
- @llamaindex/workflow@0.0.12
|
||||
- @llamaindex/cloud@3.0.6
|
||||
- llamaindex@0.9.6
|
||||
- @llamaindex/node-parser@1.0.5
|
||||
- @llamaindex/openai@0.1.57
|
||||
- @llamaindex/readers@2.0.5
|
||||
|
||||
## 0.1.5
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [ad3c7f1]
|
||||
- @llamaindex/core@0.5.4
|
||||
- @llamaindex/cloud@3.0.5
|
||||
- llamaindex@0.9.5
|
||||
- @llamaindex/node-parser@1.0.4
|
||||
- @llamaindex/openai@0.1.56
|
||||
- @llamaindex/readers@2.0.4
|
||||
|
||||
## 0.1.4
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [cb256f2]
|
||||
- Updated dependencies [cb021e7]
|
||||
- @llamaindex/openai@0.1.55
|
||||
- @llamaindex/core@0.5.3
|
||||
- llamaindex@0.9.4
|
||||
- @llamaindex/cloud@3.0.4
|
||||
- @llamaindex/node-parser@1.0.3
|
||||
- @llamaindex/readers@2.0.3
|
||||
|
||||
## 0.1.3
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [d952e68]
|
||||
- @llamaindex/core@0.5.2
|
||||
- @llamaindex/cloud@3.0.3
|
||||
- llamaindex@0.9.3
|
||||
- @llamaindex/node-parser@1.0.2
|
||||
- @llamaindex/openai@0.1.54
|
||||
- @llamaindex/readers@2.0.2
|
||||
|
||||
## 0.1.2
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [c902fcb]
|
||||
- Updated dependencies [88d776f]
|
||||
- @llamaindex/cloud@3.0.2
|
||||
- llamaindex@0.9.2
|
||||
|
||||
## 0.1.1
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [6d37d44]
|
||||
- llamaindex@0.9.1
|
||||
- @llamaindex/cloud@3.0.1
|
||||
- @llamaindex/core@0.5.1
|
||||
- @llamaindex/node-parser@1.0.1
|
||||
- @llamaindex/openai@0.1.53
|
||||
- @llamaindex/readers@2.0.1
|
||||
- @llamaindex/workflow@0.0.11
|
||||
|
||||
## 0.1.0
|
||||
|
||||
### Minor Changes
|
||||
|
||||
@@ -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"];
|
||||
|
||||
+28
-26
@@ -1,18 +1,19 @@
|
||||
{
|
||||
"name": "@llamaindex/doc",
|
||||
"version": "0.1.0",
|
||||
"version": "0.1.9",
|
||||
"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:*",
|
||||
@@ -27,27 +28,27 @@
|
||||
"@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": "15.0.3",
|
||||
"next": "^15.2.1",
|
||||
"next-themes": "^0.4.3",
|
||||
"react": "^18.3.1",
|
||||
"react-dom": "^18.3.1",
|
||||
"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",
|
||||
@@ -55,8 +56,8 @@
|
||||
"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 +68,28 @@
|
||||
"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
|
||||
@@ -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);
|
||||
|
||||
@@ -5,7 +5,7 @@ import { transformerTwoslash } from "fumadocs-twoslash";
|
||||
import rehypeKatex from "rehype-katex";
|
||||
import remarkMath from "remark-math";
|
||||
|
||||
export const { docs, meta } = defineDocs({
|
||||
export const docs = defineDocs({
|
||||
dir: "./src/content/docs",
|
||||
});
|
||||
|
||||
|
||||
@@ -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());
|
||||
}
|
||||
@@ -29,7 +29,6 @@ export default async function Page(props: {
|
||||
editOnGithub={{
|
||||
owner: "run-llama",
|
||||
repo: "LlamaIndexTS",
|
||||
sha: "main",
|
||||
path: `apps/next/src/content/docs/${page.file.path}`,
|
||||
}}
|
||||
>
|
||||
@@ -64,6 +63,7 @@ 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: {
|
||||
|
||||
@@ -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;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -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,
|
||||
},
|
||||
});
|
||||
|
||||
@@ -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 />
|
||||
|
||||
@@ -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 +1,139 @@
|
||||
---
|
||||
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";
|
||||
|
||||
`AgentWorkflow` is 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.
|
||||
|
||||
## Installation
|
||||
|
||||
You'll need to install the `@llamaindex/workflow` package:
|
||||
|
||||
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
|
||||
```shell tab="npm"
|
||||
npm install @llamaindex/workflow
|
||||
```
|
||||
|
||||
```shell tab="yarn"
|
||||
yarn add @llamaindex/workflow
|
||||
```
|
||||
|
||||
```shell tab="pnpm"
|
||||
pnpm add @llamaindex/workflow
|
||||
```
|
||||
</Tabs>
|
||||
|
||||
## 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 { AgentWorkflow, 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 agent workflow with the tool
|
||||
const workflow = AgentWorkflow.fromTools({
|
||||
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
|
||||
|
||||
`AgentWorkflow` provides 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
|
||||
|
||||
`AgentWorkflow` 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 { AgentWorkflow, FunctionAgent, FunctionTool } from "llamaindex";
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import { z } from "zod";
|
||||
|
||||
// Create a weather agent
|
||||
const weatherAgent = new FunctionAgent({
|
||||
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 = new FunctionAgent({
|
||||
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 = new AgentWorkflow({
|
||||
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>",
|
||||
|
||||
+46
@@ -0,0 +1,46 @@
|
||||
---
|
||||
title: VoyageAI
|
||||
---
|
||||
|
||||
To use VoyageAI embeddings, you need to import `VoyageAIEmbedding` from `@llamaindex/voyage-ai`.
|
||||
|
||||
## Installation
|
||||
|
||||
import { Tab, Tabs } from "fumadocs-ui/components/tabs";
|
||||
|
||||
<Tabs groupId="install" items={["npm", "yarn", "pnpm"]} persist>
|
||||
```shell tab="npm"
|
||||
npm install llamaindex @llamaindex/voyage-ai
|
||||
```
|
||||
|
||||
```shell tab="yarn"
|
||||
yarn add llamaindex @llamaindex/voyage-ai
|
||||
```
|
||||
|
||||
```shell tab="pnpm"
|
||||
pnpm add llamaindex @llamaindex/voyage-ai
|
||||
```
|
||||
</Tabs>
|
||||
|
||||
```ts
|
||||
import { VoyageAIEmbedding } from "@llamaindex/voyage-ai";
|
||||
import { Document, Settings, VectorStoreIndex } from "llamaindex";
|
||||
|
||||
Settings.embedModel = new VoyageAIEmbedding();
|
||||
|
||||
const document = new Document({ text: essay, id_: "essay" });
|
||||
|
||||
const index = await VectorStoreIndex.fromDocuments([document]);
|
||||
|
||||
const queryEngine = index.asQueryEngine();
|
||||
|
||||
const query = "What is the meaning of life?";
|
||||
|
||||
const results = await queryEngine.query({
|
||||
query,
|
||||
});
|
||||
```
|
||||
|
||||
## API Reference
|
||||
|
||||
- [VoyageAIEmbedding](/docs/api/classes/VoyageAIEmbedding)
|
||||
@@ -37,6 +37,31 @@ Settings.embedModel = new OpenAIEmbedding({
|
||||
|
||||
For local embeddings, you can use the [HuggingFace](/docs/llamaindex/modules/embeddings/available_embeddings/huggingface) embedding model.
|
||||
|
||||
## Local Ollama Embeddings With Remote Host
|
||||
|
||||
Ollama provides a way to run embedding models locally or connect to a remote Ollama instance. This is particularly useful when you need to:
|
||||
- Run embeddings without relying on external API services
|
||||
- Use custom embedding models
|
||||
- Connect to a shared Ollama instance in your network
|
||||
|
||||
The ENV variable method you will find elsewhere sometimes may not work with the OllamaEmbedding class. Also note, you'll need to change the host
|
||||
in the Ollama server to `0.0.0.0` to allow connections from other machines.
|
||||
|
||||
To use Ollama embeddings with a remote host, you need to specify the host URL in the configuration like this:
|
||||
|
||||
```typescript
|
||||
import { OllamaEmbedding } from "@llamaindex/ollama";
|
||||
import { Settings } from "llamaindex";
|
||||
|
||||
// Configure Ollama with a remote host
|
||||
Settings.embedModel = new OllamaEmbedding({
|
||||
model: "nomic-embed-text",
|
||||
config: {
|
||||
host: "http://your-ollama-host:11434"
|
||||
}
|
||||
});
|
||||
```
|
||||
|
||||
## Available Embeddings
|
||||
|
||||
Most available embeddings are listed in the sidebar on the left.
|
||||
|
||||
@@ -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
|
||||
})
|
||||
```
|
||||
@@ -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": [
|
||||
{
|
||||
|
||||
@@ -1,6 +1,13 @@
|
||||
{
|
||||
"plugin": ["typedoc-plugin-markdown", "typedoc-plugin-merge-modules"],
|
||||
"entryPoints": ["../../packages/llamaindex/src/index.ts"],
|
||||
"entryPoints": ["../../packages/**/src/index.ts"],
|
||||
"exclude": [
|
||||
"../../packages/autotool/**/src/index.ts",
|
||||
"**/node_modules/**",
|
||||
"**/dist/**",
|
||||
"**/test/**",
|
||||
"**/tests/**"
|
||||
],
|
||||
"tsconfig": "../../tsconfig.json",
|
||||
"readme": "none",
|
||||
"sourceLinkTemplate": "https://github.com/run-llama/LlamaIndexTS/blob/{gitRevision}/{path}#L{line}",
|
||||
|
||||
@@ -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 +1,64 @@
|
||||
# @llamaindex/cloudflare-worker-agent-test
|
||||
|
||||
## 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
|
||||
|
||||
- llamaindex@0.9.5
|
||||
|
||||
## 0.0.138
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [cb021e7]
|
||||
- llamaindex@0.9.4
|
||||
|
||||
## 0.0.137
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.3
|
||||
|
||||
## 0.0.136
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [88d776f]
|
||||
- llamaindex@0.9.2
|
||||
|
||||
## 0.0.135
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [6d37d44]
|
||||
- llamaindex@0.9.1
|
||||
|
||||
## 0.0.134
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/cloudflare-worker-agent-test",
|
||||
"version": "0.0.134",
|
||||
"version": "0.0.143",
|
||||
"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 +1,54 @@
|
||||
# @llamaindex/llama-parse-browser-test
|
||||
|
||||
## 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
|
||||
|
||||
- @llamaindex/cloud@3.0.5
|
||||
|
||||
## 0.0.49
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/cloud@3.0.4
|
||||
|
||||
## 0.0.48
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/cloud@3.0.3
|
||||
|
||||
## 0.0.47
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [c902fcb]
|
||||
- @llamaindex/cloud@3.0.2
|
||||
|
||||
## 0.0.46
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/cloud@3.0.1
|
||||
|
||||
## 0.0.45
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "@llamaindex/llama-parse-browser-test",
|
||||
"private": true,
|
||||
"version": "0.0.45",
|
||||
"version": "0.0.53",
|
||||
"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 +1,64 @@
|
||||
# @llamaindex/next-agent-test
|
||||
|
||||
## 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
|
||||
|
||||
- llamaindex@0.9.5
|
||||
|
||||
## 0.1.138
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [cb021e7]
|
||||
- llamaindex@0.9.4
|
||||
|
||||
## 0.1.137
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.3
|
||||
|
||||
## 0.1.136
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [88d776f]
|
||||
- llamaindex@0.9.2
|
||||
|
||||
## 0.1.135
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [6d37d44]
|
||||
- llamaindex@0.9.1
|
||||
|
||||
## 0.1.134
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/next-agent-test",
|
||||
"version": "0.1.134",
|
||||
"version": "0.1.143",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
@@ -10,18 +10,16 @@
|
||||
"dependencies": {
|
||||
"ai": "^4.0.0",
|
||||
"llamaindex": "workspace:*",
|
||||
"next": "15.0.3",
|
||||
"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",
|
||||
"@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 +1,64 @@
|
||||
# test-edge-runtime
|
||||
|
||||
## 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
|
||||
|
||||
- llamaindex@0.9.5
|
||||
|
||||
## 0.1.137
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [cb021e7]
|
||||
- llamaindex@0.9.4
|
||||
|
||||
## 0.1.136
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.3
|
||||
|
||||
## 0.1.135
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [88d776f]
|
||||
- llamaindex@0.9.2
|
||||
|
||||
## 0.1.134
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [6d37d44]
|
||||
- llamaindex@0.9.1
|
||||
|
||||
## 0.1.133
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/nextjs-edge-runtime-test",
|
||||
"version": "0.1.133",
|
||||
"version": "0.1.142",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
@@ -9,14 +9,14 @@
|
||||
},
|
||||
"dependencies": {
|
||||
"llamaindex": "workspace:*",
|
||||
"next": "15.0.3",
|
||||
"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 +1,78 @@
|
||||
# @llamaindex/next-node-runtime
|
||||
|
||||
## 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
|
||||
|
||||
- llamaindex@0.9.5
|
||||
- @llamaindex/huggingface@0.0.40
|
||||
- @llamaindex/readers@2.0.4
|
||||
|
||||
## 0.1.4
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [cb021e7]
|
||||
- llamaindex@0.9.4
|
||||
- @llamaindex/huggingface@0.0.39
|
||||
- @llamaindex/readers@2.0.3
|
||||
|
||||
## 0.1.3
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.3
|
||||
- @llamaindex/huggingface@0.0.38
|
||||
- @llamaindex/readers@2.0.2
|
||||
|
||||
## 0.1.2
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [88d776f]
|
||||
- llamaindex@0.9.2
|
||||
|
||||
## 0.1.1
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [6d37d44]
|
||||
- llamaindex@0.9.1
|
||||
- @llamaindex/huggingface@0.0.37
|
||||
- @llamaindex/readers@2.0.1
|
||||
|
||||
## 0.1.0
|
||||
|
||||
### Minor Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/next-node-runtime-test",
|
||||
"version": "0.1.0",
|
||||
"version": "0.1.9",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
@@ -8,21 +8,19 @@
|
||||
"start": "next start"
|
||||
},
|
||||
"dependencies": {
|
||||
"llamaindex": "workspace:*",
|
||||
"@llamaindex/huggingface": "workspace:*",
|
||||
"@llamaindex/readers": "workspace:*",
|
||||
"next": "15.0.3",
|
||||
"react": "18.3.1",
|
||||
"react-dom": "18.3.1"
|
||||
"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;
|
||||
@@ -1,3 +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;
|
||||
@@ -0,0 +1,24 @@
|
||||
# Logs
|
||||
logs
|
||||
*.log
|
||||
npm-debug.log*
|
||||
yarn-debug.log*
|
||||
yarn-error.log*
|
||||
pnpm-debug.log*
|
||||
lerna-debug.log*
|
||||
|
||||
node_modules
|
||||
dist
|
||||
dist-ssr
|
||||
*.local
|
||||
|
||||
# Editor directories and files
|
||||
.vscode/*
|
||||
!.vscode/extensions.json
|
||||
.idea
|
||||
.DS_Store
|
||||
*.suo
|
||||
*.ntvs*
|
||||
*.njsproj
|
||||
*.sln
|
||||
*.sw?
|
||||
@@ -0,0 +1,60 @@
|
||||
# vite-import-llamaindex
|
||||
|
||||
## 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
|
||||
|
||||
- llamaindex@0.9.5
|
||||
|
||||
## 0.0.4
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [cb021e7]
|
||||
- llamaindex@0.9.4
|
||||
|
||||
## 0.0.3
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.3
|
||||
|
||||
## 0.0.2
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [88d776f]
|
||||
- llamaindex@0.9.2
|
||||
|
||||
## 0.0.1
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [6d37d44]
|
||||
- llamaindex@0.9.1
|
||||
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"name": "vite-import-llamaindex",
|
||||
"private": true,
|
||||
"version": "0.0.9",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"build": "vite build",
|
||||
"size-limit": "size-limit"
|
||||
},
|
||||
"size-limit": [
|
||||
{
|
||||
"path": "dist/LlamaIndexImportTest.js"
|
||||
}
|
||||
],
|
||||
"devDependencies": {
|
||||
"@size-limit/preset-big-lib": "^11.1.6",
|
||||
"size-limit": "^11.1.6",
|
||||
"typescript": "^5.7.3",
|
||||
"vite": "^6.1.0"
|
||||
},
|
||||
"dependencies": {
|
||||
"llamaindex": "workspace:*"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 257"><defs><linearGradient id="IconifyId1813088fe1fbc01fb466" x1="-.828%" x2="57.636%" y1="7.652%" y2="78.411%"><stop offset="0%" stop-color="#41D1FF"></stop><stop offset="100%" stop-color="#BD34FE"></stop></linearGradient><linearGradient id="IconifyId1813088fe1fbc01fb467" x1="43.376%" x2="50.316%" y1="2.242%" y2="89.03%"><stop offset="0%" stop-color="#FFEA83"></stop><stop offset="8.333%" stop-color="#FFDD35"></stop><stop offset="100%" stop-color="#FFA800"></stop></linearGradient></defs><path fill="url(#IconifyId1813088fe1fbc01fb466)" d="M255.153 37.938L134.897 252.976c-2.483 4.44-8.862 4.466-11.382.048L.875 37.958c-2.746-4.814 1.371-10.646 6.827-9.67l120.385 21.517a6.537 6.537 0 0 0 2.322-.004l117.867-21.483c5.438-.991 9.574 4.796 6.877 9.62Z"></path><path fill="url(#IconifyId1813088fe1fbc01fb467)" d="M185.432.063L96.44 17.501a3.268 3.268 0 0 0-2.634 3.014l-5.474 92.456a3.268 3.268 0 0 0 3.997 3.378l24.777-5.718c2.318-.535 4.413 1.507 3.936 3.838l-7.361 36.047c-.495 2.426 1.782 4.5 4.151 3.78l15.304-4.649c2.372-.72 4.652 1.36 4.15 3.788l-11.698 56.621c-.732 3.542 3.979 5.473 5.943 2.437l1.313-2.028l72.516-144.72c1.215-2.423-.88-5.186-3.54-4.672l-25.505 4.922c-2.396.462-4.435-1.77-3.759-4.114l16.646-57.705c.677-2.35-1.37-4.583-3.769-4.113Z"></path></svg>
|
||||
|
After Width: | Height: | Size: 1.5 KiB |
@@ -0,0 +1,7 @@
|
||||
import "llamaindex";
|
||||
|
||||
document.querySelector<HTMLDivElement>("#app")!.innerHTML = `
|
||||
<div>
|
||||
Hello World!
|
||||
</div>
|
||||
`;
|
||||
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"compilerOptions": {
|
||||
"target": "ES2020",
|
||||
"useDefineForClassFields": true,
|
||||
"module": "ESNext",
|
||||
"lib": ["ES2020", "DOM", "DOM.Iterable"],
|
||||
"skipLibCheck": true,
|
||||
|
||||
/* Bundler mode */
|
||||
"moduleResolution": "bundler",
|
||||
"allowImportingTsExtensions": true,
|
||||
"isolatedModules": true,
|
||||
"moduleDetection": "force",
|
||||
"noEmit": true,
|
||||
|
||||
/* Linting */
|
||||
"strict": true,
|
||||
"noUnusedLocals": true,
|
||||
"noUnusedParameters": true,
|
||||
"noFallthroughCasesInSwitch": true,
|
||||
"noUncheckedSideEffectImports": true
|
||||
},
|
||||
"include": ["src", "vite.config.ts"]
|
||||
}
|
||||
@@ -0,0 +1,16 @@
|
||||
import { dirname, resolve } from "node:path";
|
||||
import { fileURLToPath } from "node:url";
|
||||
import { defineConfig } from "vite";
|
||||
|
||||
const __dirname = dirname(fileURLToPath(import.meta.url));
|
||||
|
||||
export default defineConfig({
|
||||
build: {
|
||||
lib: {
|
||||
entry: resolve(__dirname, "src/main.ts"),
|
||||
name: "LlamaIndexImportTest",
|
||||
fileName: "LlamaIndexImportTest",
|
||||
formats: ["es", "cjs"],
|
||||
},
|
||||
},
|
||||
});
|
||||
@@ -5,3 +5,4 @@ dist
|
||||
.cache
|
||||
.DS_Store
|
||||
*.pem
|
||||
/src/pages.gen.ts
|
||||
|
||||
@@ -1,5 +1,67 @@
|
||||
# @llamaindex/waku-query-engine-test
|
||||
|
||||
## 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
|
||||
|
||||
- llamaindex@0.9.5
|
||||
|
||||
## 0.0.138
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [cb021e7]
|
||||
- llamaindex@0.9.4
|
||||
|
||||
## 0.0.137
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.9.3
|
||||
|
||||
## 0.0.136
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [88d776f]
|
||||
- llamaindex@0.9.2
|
||||
|
||||
## 0.0.135
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [cc50c9c]
|
||||
- Updated dependencies [6d37d44]
|
||||
- @llamaindex/env@0.1.28
|
||||
- llamaindex@0.9.1
|
||||
|
||||
## 0.0.134
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/waku-query-engine-test",
|
||||
"version": "0.0.134",
|
||||
"version": "0.0.143",
|
||||
"type": "module",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
@@ -11,16 +11,16 @@
|
||||
"dependencies": {
|
||||
"@llamaindex/env": "workspace:*",
|
||||
"llamaindex": "workspace:*",
|
||||
"react": "19.0.0-rc-5c56b873-20241107",
|
||||
"react-dom": "19.0.0-rc-5c56b873-20241107",
|
||||
"react-server-dom-webpack": "19.0.0-rc-5c56b873-20241107",
|
||||
"waku": "0.21.6"
|
||||
"react": "19.0.0",
|
||||
"react-dom": "19.0.0",
|
||||
"react-server-dom-webpack": "19.0.0",
|
||||
"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": {},
|
||||
},
|
||||
};
|
||||
@@ -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",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
+30
-11
@@ -1,5 +1,7 @@
|
||||
import assert from "node:assert";
|
||||
import { execSync } from "node:child_process";
|
||||
import { mkdir, rm, writeFile } from "node:fs/promises";
|
||||
import { mkdir, readFile, rm, writeFile } from "node:fs/promises";
|
||||
import { createRequire } from "node:module";
|
||||
import { resolve } from "node:path";
|
||||
import { test } from "node:test";
|
||||
import { testRootDir } from "./utils.js";
|
||||
@@ -14,17 +16,17 @@ const { Document, MetadataMode, VectorStoreIndex } = require('llamaindex')
|
||||
const { OpenAIEmbedding } = require('@llamaindex/openai')
|
||||
const { Settings } = require('@llamaindex/core/global')`;
|
||||
const mainCode = `
|
||||
async function main() {
|
||||
Settings.embedModel = new OpenAIEmbedding({
|
||||
model: 'text-embedding-3-small',
|
||||
apiKey: '${process.env.OPENAI_API_KEY}',
|
||||
})
|
||||
const model = Settings.embedModel
|
||||
if (model == null) {
|
||||
process.exit(-1)
|
||||
}
|
||||
Settings.embedModel = new OpenAIEmbedding({
|
||||
model: 'text-embedding-3-small',
|
||||
apiKey: '${process.env.OPENAI_API_KEY}',
|
||||
})
|
||||
const model = Settings.embedModel
|
||||
if (model == null) {
|
||||
process.exit(-1)
|
||||
}
|
||||
main().catch(console.error)`;
|
||||
const document = new Document({ text: 'Hello, world!' })
|
||||
const index = await VectorStoreIndex.fromDocuments([document])
|
||||
`;
|
||||
t.before(async () => {
|
||||
await mkdir(resolve(testRootDir, ".temp"), {
|
||||
recursive: true,
|
||||
@@ -84,3 +86,20 @@ main().catch(console.error)`;
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
test('no extra deps in "@llamaindex/env" cjs module', async () => {
|
||||
const modules = ["@aws-crypto/sha256-js"];
|
||||
const require = createRequire(import.meta.url);
|
||||
const envPackage = require.resolve("@llamaindex/env");
|
||||
const file = await readFile(envPackage, "utf-8");
|
||||
for (const module of modules) {
|
||||
assert.ok(!file.includes(module));
|
||||
}
|
||||
});
|
||||
|
||||
test('no error when require "llamaindex" in CJS', async () => {
|
||||
const code = `require('llamaindex')`;
|
||||
execSync(`${process.argv[0]} -e "${code}"`, {
|
||||
cwd: process.cwd(),
|
||||
});
|
||||
});
|
||||
|
||||
+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 +1,305 @@
|
||||
# examples
|
||||
|
||||
## 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
|
||||
|
||||
- Updated dependencies [ad3c7f1]
|
||||
- @llamaindex/core@0.5.4
|
||||
- @llamaindex/cloud@3.0.5
|
||||
- llamaindex@0.9.5
|
||||
- @llamaindex/node-parser@1.0.4
|
||||
- @llamaindex/anthropic@0.2.2
|
||||
- @llamaindex/clip@0.0.40
|
||||
- @llamaindex/cohere@0.0.9
|
||||
- @llamaindex/deepinfra@0.0.40
|
||||
- @llamaindex/google@0.0.11
|
||||
- @llamaindex/huggingface@0.0.40
|
||||
- @llamaindex/mistral@0.0.9
|
||||
- @llamaindex/mixedbread@0.0.9
|
||||
- @llamaindex/ollama@0.0.44
|
||||
- @llamaindex/openai@0.1.56
|
||||
- @llamaindex/portkey-ai@0.0.37
|
||||
- @llamaindex/replicate@0.0.37
|
||||
- @llamaindex/astra@0.0.9
|
||||
- @llamaindex/azure@0.1.4
|
||||
- @llamaindex/chroma@0.0.9
|
||||
- @llamaindex/firestore@1.0.2
|
||||
- @llamaindex/milvus@0.1.4
|
||||
- @llamaindex/mongodb@0.0.9
|
||||
- @llamaindex/pinecone@0.0.9
|
||||
- @llamaindex/postgres@0.0.37
|
||||
- @llamaindex/qdrant@0.1.4
|
||||
- @llamaindex/upstash@0.0.9
|
||||
- @llamaindex/weaviate@0.0.9
|
||||
- @llamaindex/vercel@0.0.15
|
||||
- @llamaindex/voyage-ai@1.0.1
|
||||
- @llamaindex/readers@2.0.4
|
||||
- @llamaindex/groq@0.0.55
|
||||
- @llamaindex/vllm@0.0.26
|
||||
|
||||
## 0.2.3
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [cb256f2]
|
||||
- Updated dependencies [cb021e7]
|
||||
- Updated dependencies [0346391]
|
||||
- @llamaindex/openai@0.1.55
|
||||
- @llamaindex/core@0.5.3
|
||||
- llamaindex@0.9.4
|
||||
- @llamaindex/voyage-ai@1.0.0
|
||||
- @llamaindex/clip@0.0.39
|
||||
- @llamaindex/deepinfra@0.0.39
|
||||
- @llamaindex/groq@0.0.54
|
||||
- @llamaindex/huggingface@0.0.39
|
||||
- @llamaindex/azure@0.1.3
|
||||
- @llamaindex/milvus@0.1.3
|
||||
- @llamaindex/qdrant@0.1.3
|
||||
- @llamaindex/vllm@0.0.25
|
||||
- @llamaindex/cloud@3.0.4
|
||||
- @llamaindex/node-parser@1.0.3
|
||||
- @llamaindex/anthropic@0.2.1
|
||||
- @llamaindex/cohere@0.0.8
|
||||
- @llamaindex/google@0.0.10
|
||||
- @llamaindex/mistral@0.0.8
|
||||
- @llamaindex/mixedbread@0.0.8
|
||||
- @llamaindex/ollama@0.0.43
|
||||
- @llamaindex/portkey-ai@0.0.36
|
||||
- @llamaindex/replicate@0.0.36
|
||||
- @llamaindex/astra@0.0.8
|
||||
- @llamaindex/chroma@0.0.8
|
||||
- @llamaindex/firestore@1.0.1
|
||||
- @llamaindex/mongodb@0.0.8
|
||||
- @llamaindex/pinecone@0.0.8
|
||||
- @llamaindex/postgres@0.0.36
|
||||
- @llamaindex/upstash@0.0.8
|
||||
- @llamaindex/weaviate@0.0.8
|
||||
- @llamaindex/vercel@0.0.14
|
||||
- @llamaindex/readers@2.0.3
|
||||
|
||||
## 0.2.2
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 3564244: Add support for claude 3.7 thinking (and set default temperature to 1)
|
||||
- 3564244: add support for claude 3.7
|
||||
- Updated dependencies [d952e68]
|
||||
- Updated dependencies [a9c6144]
|
||||
- Updated dependencies [5c026e8]
|
||||
- Updated dependencies [3564244]
|
||||
- Updated dependencies [3564244]
|
||||
- @llamaindex/core@0.5.2
|
||||
- @llamaindex/anthropic@0.2.0
|
||||
- @llamaindex/firestore@1.0.0
|
||||
- @llamaindex/cloud@3.0.3
|
||||
- llamaindex@0.9.3
|
||||
- @llamaindex/node-parser@1.0.2
|
||||
- @llamaindex/clip@0.0.38
|
||||
- @llamaindex/cohere@0.0.7
|
||||
- @llamaindex/deepinfra@0.0.38
|
||||
- @llamaindex/google@0.0.9
|
||||
- @llamaindex/huggingface@0.0.38
|
||||
- @llamaindex/mistral@0.0.7
|
||||
- @llamaindex/mixedbread@0.0.7
|
||||
- @llamaindex/ollama@0.0.42
|
||||
- @llamaindex/openai@0.1.54
|
||||
- @llamaindex/portkey-ai@0.0.35
|
||||
- @llamaindex/replicate@0.0.35
|
||||
- @llamaindex/astra@0.0.7
|
||||
- @llamaindex/azure@0.1.2
|
||||
- @llamaindex/chroma@0.0.7
|
||||
- @llamaindex/milvus@0.1.2
|
||||
- @llamaindex/mongodb@0.0.7
|
||||
- @llamaindex/pinecone@0.0.7
|
||||
- @llamaindex/postgres@0.0.35
|
||||
- @llamaindex/qdrant@0.1.2
|
||||
- @llamaindex/upstash@0.0.7
|
||||
- @llamaindex/weaviate@0.0.7
|
||||
- @llamaindex/vercel@0.0.13
|
||||
- @llamaindex/readers@2.0.2
|
||||
- @llamaindex/groq@0.0.53
|
||||
- @llamaindex/vllm@0.0.24
|
||||
|
||||
## 0.2.1
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [cc50c9c]
|
||||
- Updated dependencies [6d37d44]
|
||||
- @llamaindex/env@0.1.28
|
||||
- llamaindex@0.9.1
|
||||
- @llamaindex/cloud@3.0.1
|
||||
- @llamaindex/core@0.5.1
|
||||
- @llamaindex/node-parser@1.0.1
|
||||
- @llamaindex/anthropic@0.1.1
|
||||
- @llamaindex/clip@0.0.37
|
||||
- @llamaindex/cohere@0.0.6
|
||||
- @llamaindex/deepinfra@0.0.37
|
||||
- @llamaindex/google@0.0.8
|
||||
- @llamaindex/groq@0.0.52
|
||||
- @llamaindex/huggingface@0.0.37
|
||||
- @llamaindex/mistral@0.0.6
|
||||
- @llamaindex/mixedbread@0.0.6
|
||||
- @llamaindex/ollama@0.0.41
|
||||
- @llamaindex/openai@0.1.53
|
||||
- @llamaindex/portkey-ai@0.0.34
|
||||
- @llamaindex/replicate@0.0.34
|
||||
- @llamaindex/astra@0.0.6
|
||||
- @llamaindex/azure@0.1.1
|
||||
- @llamaindex/chroma@0.0.6
|
||||
- @llamaindex/milvus@0.1.1
|
||||
- @llamaindex/mongodb@0.0.6
|
||||
- @llamaindex/pinecone@0.0.6
|
||||
- @llamaindex/postgres@0.0.34
|
||||
- @llamaindex/qdrant@0.1.1
|
||||
- @llamaindex/upstash@0.0.6
|
||||
- @llamaindex/weaviate@0.0.6
|
||||
- @llamaindex/readers@2.0.1
|
||||
- @llamaindex/workflow@0.0.11
|
||||
- @llamaindex/vercel@0.0.12
|
||||
- @llamaindex/vllm@0.0.23
|
||||
|
||||
## 0.2.0
|
||||
|
||||
### Minor Changes
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
import { OpenAI, OpenAIAgent } from "@llamaindex/openai";
|
||||
import { FunctionTool } from "llamaindex";
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import { AgentWorkflow, FunctionTool } 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 = AgentWorkflow.fromTools({
|
||||
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${csvData}`,
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
console.log(result);
|
||||
})();
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import { FunctionTool, ToolCallOptions } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
(async () => {
|
||||
// The tool call will generate a partial JSON for `gpt-4-turbo`
|
||||
@@ -27,16 +28,11 @@ async function callLLM(init: { model: string }) {
|
||||
name: "interpreter",
|
||||
description:
|
||||
"Execute python code in a Jupyter notebook cell and return any result, stdout, stderr, display_data, and error.",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
code: {
|
||||
type: "string",
|
||||
description: "The python code to execute in a single cell.",
|
||||
},
|
||||
},
|
||||
required: ["code"],
|
||||
},
|
||||
parameters: z.object({
|
||||
code: z.string({
|
||||
description: "The python code to execute in a single cell.",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
|
||||
+16
-36
@@ -1,25 +1,16 @@
|
||||
import { OpenAIAgent } from "@llamaindex/openai";
|
||||
import { FunctionTool } from "llamaindex";
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import { AgentWorkflow, FunctionTool } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
const sumNumbers = FunctionTool.from(
|
||||
({ a, b }: { a: number; b: number }) => `${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 = AgentWorkflow.fromTools({
|
||||
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, AgentWorkflow } 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 = AgentWorkflow.fromTools({
|
||||
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 +1,83 @@
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import fs from "fs";
|
||||
import {
|
||||
AgentToolCall,
|
||||
AgentToolCallResult,
|
||||
AgentWorkflow,
|
||||
FunctionAgent,
|
||||
FunctionTool,
|
||||
} from "llamaindex";
|
||||
import os from "os";
|
||||
import { z } from "zod";
|
||||
|
||||
import { WikipediaTool } from "../wiki";
|
||||
const llm = new OpenAI({
|
||||
model: "gpt-4o-mini",
|
||||
});
|
||||
|
||||
const saveFileTool = FunctionTool.from(
|
||||
({ content }: { content: string }) => {
|
||||
const filePath = os.tmpdir() + "/report.md";
|
||||
fs.writeFileSync(filePath, content);
|
||||
return `File saved successfully at ${filePath}`;
|
||||
},
|
||||
{
|
||||
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",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
async function main() {
|
||||
const reportAgent = new FunctionAgent({
|
||||
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 = new FunctionAgent({
|
||||
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 = new AgentWorkflow({
|
||||
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 +1,110 @@
|
||||
/**
|
||||
* 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 { StopEvent } from "@llamaindex/workflow";
|
||||
import {
|
||||
AgentInput,
|
||||
AgentOutput,
|
||||
AgentStream,
|
||||
AgentToolCall,
|
||||
AgentToolCallResult,
|
||||
AgentWorkflow,
|
||||
FunctionAgent,
|
||||
FunctionTool,
|
||||
} from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
const llm = new OpenAI({
|
||||
model: "gpt-4o-mini",
|
||||
});
|
||||
|
||||
// Define tools for the agents
|
||||
const temperatureConverterTool = FunctionTool.from(
|
||||
({ temperature }: { temperature: number }) => {
|
||||
return ((temperature - 32) * 5) / 9;
|
||||
},
|
||||
{
|
||||
description: "Convert a temperature from Fahrenheit to Celsius",
|
||||
name: "fahrenheitToCelsius",
|
||||
parameters: z.object({
|
||||
temperature: z.number({
|
||||
description: "The temperature in Fahrenheit",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
const temperatureFetcherTool = FunctionTool.from(
|
||||
({ city }: { city: string }) => {
|
||||
const temperature = Math.floor(Math.random() * 58) + 32;
|
||||
return `The current temperature in ${city} is ${temperature}°F`;
|
||||
},
|
||||
{
|
||||
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",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
// Create agents
|
||||
async function multiWeatherAgent() {
|
||||
const converterAgent = new FunctionAgent({
|
||||
name: "TemperatureConverterAgent",
|
||||
description:
|
||||
"An agent that can convert temperatures from Fahrenheit to Celsius.",
|
||||
tools: [temperatureConverterTool],
|
||||
llm,
|
||||
});
|
||||
|
||||
const weatherAgent = new FunctionAgent({
|
||||
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 = new AgentWorkflow({
|
||||
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 +1,37 @@
|
||||
/**
|
||||
* This example shows how to use AgentWorkflow as a single agent with tools
|
||||
*/
|
||||
import { OpenAI } from "@llamaindex/openai";
|
||||
import { AgentWorkflow } from "llamaindex";
|
||||
import { getWeatherTool } from "../agent/utils/tools";
|
||||
|
||||
const llm = new OpenAI({
|
||||
model: "gpt-4o",
|
||||
});
|
||||
|
||||
async function singleWeatherAgent() {
|
||||
const workflow = AgentWorkflow.fromTools({
|
||||
tools: [getWeatherTool],
|
||||
llm,
|
||||
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);
|
||||
});
|
||||
@@ -0,0 +1,114 @@
|
||||
import fs from "fs";
|
||||
import {
|
||||
AgentToolCall,
|
||||
AgentToolCallResult,
|
||||
AgentWorkflow,
|
||||
FunctionAgent,
|
||||
FunctionTool,
|
||||
} from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
import { Anthropic } from "@llamaindex/anthropic";
|
||||
|
||||
const llm = new Anthropic({
|
||||
model: "claude-3-5-sonnet",
|
||||
});
|
||||
|
||||
const weatherTool = FunctionTool.from(
|
||||
(query: { location: string }) => {
|
||||
return `The weather in ${query.location} is sunny`;
|
||||
},
|
||||
{
|
||||
name: "weather",
|
||||
description: "Get the weather",
|
||||
parameters: z.object({
|
||||
location: z.string({
|
||||
description: "The location to get the weather for",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
const inflationTool = FunctionTool.from(
|
||||
(query: { location: string }) => {
|
||||
return `The inflation in ${query.location} is 2%`;
|
||||
},
|
||||
{
|
||||
name: "inflation",
|
||||
description: "Get the inflation",
|
||||
parameters: z.object({
|
||||
location: z.string({
|
||||
description: "The location to get the inflation for",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
const saveFileTool = FunctionTool.from(
|
||||
({ content }: { content: string }) => {
|
||||
const filePath = "./report.md";
|
||||
fs.writeFileSync(filePath, content);
|
||||
return `File saved successfully at ${filePath}`;
|
||||
},
|
||||
{
|
||||
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",
|
||||
}),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
async function main() {
|
||||
const reportAgent = new FunctionAgent({
|
||||
name: "ReportAgent",
|
||||
description:
|
||||
"Responsible for creating concise reports about weather and inflation data",
|
||||
systemPrompt: `You are a professional writer. Your task is to create a clear and concise report summarizing the weather and inflation data provided. Once complete, save the report to a file using the saveFile tool.`,
|
||||
tools: [saveFileTool],
|
||||
llm,
|
||||
});
|
||||
|
||||
const researchAgent = new FunctionAgent({
|
||||
name: "ResearchAgent",
|
||||
description:
|
||||
"Responsible for gathering relevant information from the internet",
|
||||
systemPrompt: `You are a research agent. Your role is to gather information about the inflation and weather in the location provided.`,
|
||||
tools: [inflationTool, weatherTool],
|
||||
canHandoffTo: [reportAgent],
|
||||
llm,
|
||||
});
|
||||
|
||||
const workflow = new AgentWorkflow({
|
||||
agents: [researchAgent, reportAgent],
|
||||
rootAgent: researchAgent,
|
||||
});
|
||||
|
||||
const context = workflow.run(
|
||||
"Write a report about New York weather and inflation",
|
||||
);
|
||||
|
||||
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);
|
||||
});
|
||||
@@ -1,5 +1,6 @@
|
||||
import { Anthropic, AnthropicAgent } from "@llamaindex/anthropic";
|
||||
import { FunctionTool, Settings } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
import { WikipediaTool } from "../wiki";
|
||||
|
||||
Settings.callbackManager.on("llm-tool-call", (event) => {
|
||||
@@ -8,29 +9,22 @@ Settings.callbackManager.on("llm-tool-call", (event) => {
|
||||
|
||||
const anthropic = new Anthropic({
|
||||
apiKey: process.env.ANTHROPIC_API_KEY,
|
||||
model: "claude-3-5-sonnet",
|
||||
model: "claude-3-7-sonnet",
|
||||
});
|
||||
|
||||
const agent = new AnthropicAgent({
|
||||
llm: anthropic,
|
||||
tools: [
|
||||
FunctionTool.from<{ location: string }>(
|
||||
FunctionTool.from(
|
||||
(query) => {
|
||||
return `The weather in ${query.location} is sunny`;
|
||||
},
|
||||
{
|
||||
name: "weather",
|
||||
description: "Get the weather",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
location: {
|
||||
type: "string",
|
||||
description: "The location to get the weather for",
|
||||
},
|
||||
},
|
||||
required: ["location"],
|
||||
},
|
||||
parameters: z.object({
|
||||
location: z.string().describe("The location to get the weather for"),
|
||||
}),
|
||||
},
|
||||
),
|
||||
new WikipediaTool(),
|
||||
|
||||
@@ -3,7 +3,7 @@ import { Anthropic } from "@llamaindex/anthropic";
|
||||
(async () => {
|
||||
const anthropic = new Anthropic({
|
||||
apiKey: process.env.ANTHROPIC_API_KEY,
|
||||
model: "claude-3-opus",
|
||||
model: "claude-3-7-sonnet",
|
||||
});
|
||||
const result = await anthropic.chat({
|
||||
messages: [
|
||||
@@ -15,5 +15,5 @@ import { Anthropic } from "@llamaindex/anthropic";
|
||||
},
|
||||
],
|
||||
});
|
||||
console.log(result);
|
||||
console.log(result.message.content);
|
||||
})();
|
||||
|
||||
@@ -6,7 +6,7 @@ import readline from "node:readline/promises";
|
||||
(async () => {
|
||||
const llm = new Anthropic({
|
||||
apiKey: process.env.ANTHROPIC_API_KEY,
|
||||
model: "claude-3-opus",
|
||||
model: "claude-3-7-sonnet",
|
||||
});
|
||||
// chatHistory will store all the messages in the conversation
|
||||
const chatHistory = new ChatMemoryBuffer({
|
||||
|
||||
@@ -2,7 +2,7 @@ import { Anthropic } from "@llamaindex/anthropic";
|
||||
|
||||
async function main() {
|
||||
const anthropic = new Anthropic({
|
||||
model: "claude-3-5-sonnet-20241022",
|
||||
model: "claude-3-7-sonnet",
|
||||
});
|
||||
|
||||
const entireBook = await fetch(
|
||||
|
||||
@@ -3,7 +3,7 @@ import { Anthropic } from "@llamaindex/anthropic";
|
||||
(async () => {
|
||||
const anthropic = new Anthropic({
|
||||
apiKey: process.env.ANTHROPIC_API_KEY,
|
||||
model: "claude-3-5-sonnet",
|
||||
model: "claude-3-7-sonnet",
|
||||
});
|
||||
const stream = await anthropic.chat({
|
||||
messages: [
|
||||
|
||||
@@ -0,0 +1,32 @@
|
||||
import { Anthropic } from "@llamaindex/anthropic";
|
||||
|
||||
(async () => {
|
||||
const anthropic = new Anthropic({
|
||||
model: "claude-3-7-sonnet",
|
||||
maxTokens: 20000,
|
||||
additionalChatOptions: {
|
||||
thinking: {
|
||||
type: "enabled",
|
||||
budget_tokens: 16000,
|
||||
},
|
||||
},
|
||||
});
|
||||
const result = await anthropic.chat({
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content:
|
||||
"Are there an infinite number of prime numbers such that n mod 4 == 3?",
|
||||
},
|
||||
],
|
||||
stream: true,
|
||||
});
|
||||
console.log("Thinking...");
|
||||
for await (const chunk of result) {
|
||||
if (chunk.delta) {
|
||||
process.stdout.write(chunk.delta);
|
||||
} else if (chunk.options?.thinking) {
|
||||
process.stdout.write(chunk.options.thinking);
|
||||
}
|
||||
}
|
||||
})();
|
||||
@@ -0,0 +1,25 @@
|
||||
import { LLMAgent } from "llamaindex";
|
||||
import { stdin as input, stdout as output } from "node:process";
|
||||
import readline from "node:readline/promises";
|
||||
|
||||
const agent = new LLMAgent({ tools: [] });
|
||||
|
||||
(async () => {
|
||||
const rl = readline.createInterface({ input, output });
|
||||
|
||||
while (true) {
|
||||
const query = await rl.question("User: ");
|
||||
|
||||
const startTime = Date.now();
|
||||
const stream = await agent.chat({ message: query, stream: true });
|
||||
const timeToGetFirstChunk = Date.now() - startTime;
|
||||
process.stdout.write(
|
||||
`Time to get first chunk from LLMAgent: ${timeToGetFirstChunk}ms\n`,
|
||||
);
|
||||
process.stdout.write("Assistant with LLMAgent: ");
|
||||
for await (const chunk of stream) {
|
||||
process.stdout.write(chunk.response);
|
||||
}
|
||||
process.stdout.write("\n");
|
||||
}
|
||||
})();
|
||||
@@ -0,0 +1,46 @@
|
||||
import { DeepSeekLLM } from "@llamaindex/deepseek";
|
||||
|
||||
// process.env.DEEPSEEK_API_KEY is required
|
||||
const deepseek = new DeepSeekLLM({
|
||||
apiKey: process.env.DEEPSEEK_API_KEY,
|
||||
model: "deepseek-coder", // or "deepseek-chat"
|
||||
});
|
||||
|
||||
(async () => {
|
||||
// Example of non-streaming chat
|
||||
const response = await deepseek.chat({
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: "You are an AI assistant",
|
||||
},
|
||||
{
|
||||
role: "user",
|
||||
content: "Tell me about San Francisco",
|
||||
},
|
||||
],
|
||||
stream: false,
|
||||
});
|
||||
console.log("Response from DeepSeek AI:");
|
||||
console.log(response);
|
||||
|
||||
// Example of streaming chat
|
||||
const generator = await deepseek.chat({
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: "You are an AI assistant",
|
||||
},
|
||||
{
|
||||
role: "user",
|
||||
content: "Write a short poem about San Francisco",
|
||||
},
|
||||
],
|
||||
stream: true,
|
||||
});
|
||||
console.log("\nStreaming response from DeepSeek AI...");
|
||||
for await (const message of generator) {
|
||||
process.stdout.write(message.delta);
|
||||
}
|
||||
console.log("\n");
|
||||
})();
|
||||
@@ -0,0 +1,4 @@
|
||||
GCP_PROJECT_ID=
|
||||
GCP_CREDENTIALS=
|
||||
FIRESTORE_DB=
|
||||
OPENAI_API_KEY=
|
||||
@@ -0,0 +1,35 @@
|
||||
# Firestore Vector Store
|
||||
|
||||
Here are some sample scripts which work with loading and querying data from a Firestore Vector Store.
|
||||
|
||||
## Prerequisites
|
||||
|
||||
- A Firestore Database
|
||||
- Hosted https://console.firebase.google.com/
|
||||
- An OpenAI API Key
|
||||
|
||||
## Setup
|
||||
|
||||
1. Set your env variables:
|
||||
|
||||
- `FIRESTORE_DB`: Name of your Firestore database
|
||||
- `GCP_PROJECT_ID`: Your GCP project ID
|
||||
- `GCP_CREDENTIALS`: Your GCP credentials JSON
|
||||
- `OPENAI_API_KEY`: Your OpenAI key
|
||||
|
||||
2. `cd` Into the `examples` directory
|
||||
3. run `npm i`
|
||||
|
||||
## Load the data
|
||||
|
||||
This sample loads the same dataset of movie reviews as sample dataset
|
||||
|
||||
run `npx tsx firestore/load.ts`
|
||||
|
||||
## Use RAG to Query the data
|
||||
|
||||
run `npx tsx firestore/query.ts`
|
||||
|
||||
## Delete the data
|
||||
|
||||
run `npx tsx firestore/delete.ts`
|
||||
@@ -0,0 +1,32 @@
|
||||
import { CollectionReference } from "@google-cloud/firestore";
|
||||
import "dotenv/config";
|
||||
|
||||
import { FirestoreVectorStore } from "@llamaindex/firestore";
|
||||
import { OpenAIEmbedding, Settings } from "llamaindex";
|
||||
|
||||
const indexName = "MovieReviews";
|
||||
|
||||
Settings.embedModel = new OpenAIEmbedding();
|
||||
|
||||
async function main() {
|
||||
try {
|
||||
const vectorStore = new FirestoreVectorStore({
|
||||
clientOptions: {
|
||||
credentials: JSON.parse(process.env.GCP_CREDENTIALS!),
|
||||
projectId: process.env.GCP_PROJECT_ID!,
|
||||
databaseId: process.env.FIRESTORE_DB!,
|
||||
ignoreUndefinedProperties: true,
|
||||
},
|
||||
collectionName: indexName,
|
||||
customCollectionReference: (rootCollection: CollectionReference) => {
|
||||
return rootCollection.doc("accountId-123").collection("vectors");
|
||||
},
|
||||
});
|
||||
|
||||
vectorStore.delete("movie_reviews.csv");
|
||||
} catch (e) {
|
||||
console.error(e);
|
||||
}
|
||||
}
|
||||
|
||||
void main();
|
||||
@@ -0,0 +1,44 @@
|
||||
import { CollectionReference } from "@google-cloud/firestore";
|
||||
import { CSVReader } from "@llamaindex/readers/csv";
|
||||
import "dotenv/config";
|
||||
|
||||
import {
|
||||
OpenAIEmbedding,
|
||||
Settings,
|
||||
storageContextFromDefaults,
|
||||
VectorStoreIndex,
|
||||
} from "llamaindex";
|
||||
|
||||
import { FirestoreVectorStore } from "@llamaindex/firestore";
|
||||
|
||||
const indexName = "MovieReviews";
|
||||
|
||||
Settings.embedModel = new OpenAIEmbedding();
|
||||
|
||||
async function main() {
|
||||
try {
|
||||
const reader = new CSVReader(false);
|
||||
const docs = await reader.loadData("./data/movie_reviews.csv");
|
||||
|
||||
const vectorStore = new FirestoreVectorStore({
|
||||
clientOptions: {
|
||||
credentials: JSON.parse(process.env.GCP_CREDENTIALS!),
|
||||
projectId: process.env.GCP_PROJECT_ID!,
|
||||
databaseId: process.env.FIRESTORE_DB!,
|
||||
ignoreUndefinedProperties: true,
|
||||
},
|
||||
collectionName: indexName,
|
||||
customCollectionReference: (rootCollection: CollectionReference) => {
|
||||
return rootCollection.doc("accountId-123").collection("vectors");
|
||||
},
|
||||
});
|
||||
|
||||
const storageContext = await storageContextFromDefaults({ vectorStore });
|
||||
|
||||
await VectorStoreIndex.fromDocuments(docs, { storageContext });
|
||||
} catch (e) {
|
||||
console.error(e);
|
||||
}
|
||||
}
|
||||
|
||||
void main();
|
||||
@@ -0,0 +1,58 @@
|
||||
import "dotenv/config";
|
||||
|
||||
import { OpenAIEmbedding, Settings, VectorStoreIndex } from "llamaindex";
|
||||
|
||||
import { CollectionReference } from "@google-cloud/firestore";
|
||||
import { FirestoreVectorStore } from "@llamaindex/firestore";
|
||||
|
||||
const indexName = "MovieReviews";
|
||||
|
||||
Settings.embedModel = new OpenAIEmbedding();
|
||||
|
||||
async function main() {
|
||||
try {
|
||||
const vectorStore = new FirestoreVectorStore({
|
||||
clientOptions: {
|
||||
credentials: JSON.parse(process.env.GCP_CREDENTIALS!),
|
||||
projectId: process.env.GCP_PROJECT_ID!,
|
||||
databaseId: process.env.FIRESTORE_DB!,
|
||||
ignoreUndefinedProperties: true,
|
||||
},
|
||||
collectionName: indexName,
|
||||
customCollectionReference: (rootCollection: CollectionReference) => {
|
||||
return rootCollection.doc("accountId-123").collection("vectors");
|
||||
},
|
||||
});
|
||||
const index = await VectorStoreIndex.fromVectorStore(vectorStore);
|
||||
const retriever = index.asRetriever({ similarityTopK: 20 });
|
||||
|
||||
const queryEngine = index.asQueryEngine({ retriever });
|
||||
const query = "Get all movie titles.";
|
||||
const results = await queryEngine.query({ query });
|
||||
console.log(`Query from ${results.sourceNodes?.length} nodes`);
|
||||
console.log(results.response);
|
||||
|
||||
console.log("\n=====\nQuerying the index with filters");
|
||||
const queryEngineWithFilters = index.asQueryEngine({
|
||||
retriever,
|
||||
preFilters: {
|
||||
filters: [
|
||||
{
|
||||
key: "file_name",
|
||||
value: "movie_reviews.csv",
|
||||
operator: "==",
|
||||
},
|
||||
],
|
||||
},
|
||||
});
|
||||
const resultAfterFilter = await queryEngineWithFilters.query({
|
||||
query: "Get all movie titles.",
|
||||
});
|
||||
console.log(`Query from ${resultAfterFilter.sourceNodes?.length} nodes`);
|
||||
console.log(resultAfterFilter.response);
|
||||
} catch (e) {
|
||||
console.error(e);
|
||||
}
|
||||
}
|
||||
|
||||
void main();
|
||||
+13
-42
@@ -1,5 +1,6 @@
|
||||
import { Gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import { FunctionTool, LLMAgent, Settings } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
Settings.callbackManager.on("llm-tool-call", (event) => {
|
||||
console.log(event.detail);
|
||||
@@ -14,20 +15,10 @@ const sumNumbers = FunctionTool.from(
|
||||
{
|
||||
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"),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
@@ -36,20 +27,10 @@ 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"),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
@@ -58,20 +39,10 @@ const subtractNumbers = FunctionTool.from(
|
||||
{
|
||||
name: "subtractNumbers",
|
||||
description: "Use this function to subtract two numbers",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
a: {
|
||||
type: "number",
|
||||
description: "The number to subtract from",
|
||||
},
|
||||
b: {
|
||||
type: "number",
|
||||
description: "The number to subtract",
|
||||
},
|
||||
},
|
||||
required: ["a", "b"],
|
||||
},
|
||||
parameters: z.object({
|
||||
a: z.number().describe("The number to subtract from"),
|
||||
b: z.number().describe("The number to subtract"),
|
||||
}),
|
||||
},
|
||||
);
|
||||
|
||||
|
||||
@@ -1,10 +1,6 @@
|
||||
import { JinaAIEmbedding } from "@llamaindex/jinaai";
|
||||
import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
|
||||
import {
|
||||
ImageDocument,
|
||||
JinaAIEmbedding,
|
||||
similarity,
|
||||
SimilarityType,
|
||||
} from "llamaindex";
|
||||
import { ImageDocument, similarity, SimilarityType } from "llamaindex";
|
||||
import path from "path";
|
||||
|
||||
async function main() {
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user