From 56fdea31359f583b556881487ff39091e7397752 Mon Sep 17 00:00:00 2001 From: Rihan Date: Tue, 18 Jun 2024 22:52:50 +0000 Subject: [PATCH 01/53] feat: support specifying account id to wrangler --- src/module.ts | 1 + src/types/module.ts | 6 ++++++ src/utils/wrangler.ts | 6 +++++- 3 files changed, 12 insertions(+), 1 deletion(-) diff --git a/src/module.ts b/src/module.ts index 7751d8d4..586f74ac 100644 --- a/src/module.ts +++ b/src/module.ts @@ -30,6 +30,7 @@ export default defineNuxtModule({ remoteArg = (remoteArg === '' ? 'true' : remoteArg) const runtimeConfig = nuxt.options.runtimeConfig const hub = defu(runtimeConfig.hub || {}, options, { + accountId: process.env.CLOUDFLARE_ACCOUNT_ID || '', // Self-hosted project projectUrl: process.env.NUXT_HUB_PROJECT_URL || '', projectSecretKey: process.env.NUXT_HUB_PROJECT_SECRET_KEY || '', diff --git a/src/types/module.ts b/src/types/module.ts index bfa4b5a1..5c0ee710 100644 --- a/src/types/module.ts +++ b/src/types/module.ts @@ -80,4 +80,10 @@ export interface ModuleOptions { * @default '.data/hub' */ dir?: string + /** + * The account ID of the Cloudflare account to use for local development. + * Only necessary if using AI and logged-in user has access to multiple accounts. + * @default process.env.CLOUDFLARE_ACCOUNT_ID + */ + accountId?: string } diff --git a/src/utils/wrangler.ts b/src/utils/wrangler.ts index af25be9b..a92cddc7 100644 --- a/src/utils/wrangler.ts +++ b/src/utils/wrangler.ts @@ -1,8 +1,12 @@ import { stringifyTOML } from 'confbox' -export function generateWrangler(hub: { kv: boolean, database: boolean, blob: boolean, analytics: boolean, ai: boolean }) { +export function generateWrangler(hub: { kv: boolean, database: boolean, blob: boolean, analytics: boolean, ai: boolean, accountId?: string }) { const wrangler: { [key: string]: any } = {} + if (hub.accountId) { + wrangler['account_id'] = hub.accountId + } + if (hub.ai) { wrangler['ai'] = { binding: 'AI' From 94b30b7581ac5f8ec63ba0dbf17f2f5835507b8d Mon Sep 17 00:00:00 2001 From: Rihan Date: Wed, 19 Jun 2024 14:51:39 +0000 Subject: [PATCH 02/53] feat: vectorize --- playground/nuxt.config.ts | 3 +- src/features.ts | 7 ++++ src/module.ts | 6 ++-- src/runtime/utils/features.ts | 3 ++ .../vectorize/server/utils/vectorize.ts | 34 +++++++++++++++++++ src/types/index.ts | 1 + src/types/module.ts | 6 ++++ src/types/vectorize.ts | 1 + src/utils/build.ts | 3 +- src/utils/wrangler.ts | 9 ++++- 10 files changed, 68 insertions(+), 5 deletions(-) create mode 100644 src/runtime/vectorize/server/utils/vectorize.ts create mode 100644 src/types/vectorize.ts diff --git a/playground/nuxt.config.ts b/playground/nuxt.config.ts index b3e37b62..f022ec53 100644 --- a/playground/nuxt.config.ts +++ b/playground/nuxt.config.ts @@ -16,7 +16,8 @@ export default defineNuxtConfig({ database: true, kv: true, blob: true, - cache: true + cache: true, + vectorize: true // projectUrl: ({ branch }) => branch === 'main' ? 'https://playground.nuxt.dev' : `https://${encodeHost(branch).replace(/\//g, '-')}.playground-to39.pages.dev` }, diff --git a/src/features.ts b/src/features.ts index 7f5b0b51..69e6fab0 100644 --- a/src/features.ts +++ b/src/features.ts @@ -26,6 +26,7 @@ export interface HubConfig { cache?: boolean database?: boolean kv?: boolean + vectorize?: boolean remoteManifest?: { version: string @@ -125,6 +126,12 @@ export function setupKV(_nuxt: Nuxt) { addServerImportsDir(resolve('./runtime/kv/server/utils')) } +export function setupVectorize(_nuxt: Nuxt) { + // Add Server scanning + addServerScanDir(resolve('./runtime/vectorize/server')) + addServerImportsDir(resolve('./runtime/vectorize/server/utils')) +} + export function setupOpenAPI(nuxt: Nuxt) { // Fallback to custom placeholder when openAPI is disabled nuxt.options.alias['#hub/openapi'] = nuxt.options.nitro?.experimental?.openAPI === true diff --git a/src/module.ts b/src/module.ts index 586f74ac..eb8d151c 100644 --- a/src/module.ts +++ b/src/module.ts @@ -7,7 +7,7 @@ import { findWorkspaceDir } from 'pkg-types' import { parseArgs } from 'citty' import { version } from '../package.json' import { generateWrangler } from './utils/wrangler' -import { setupAI, setupCache, setupAnalytics, setupBlob, setupOpenAPI, setupDatabase, setupKV, setupBase, setupRemote } from './features' +import { setupAI, setupCache, setupAnalytics, setupBlob, setupOpenAPI, setupDatabase, setupKV, setupVectorize, setupBase, setupRemote } from './features' import type { ModuleOptions } from './types/module' import { addBuildHooks } from './utils/build' @@ -50,6 +50,7 @@ export default defineNuxtModule({ cache: false, database: false, kv: false, + vectorize: false, // Other options version, env: process.env.NUXT_HUB_ENV || 'production', @@ -83,6 +84,7 @@ export default defineNuxtModule({ hub.cache && setupCache(nuxt) hub.database && setupDatabase(nuxt) hub.kv && setupKV(nuxt) + hub.vectorize && setupVectorize(nuxt) // nuxt prepare, stop here if (nuxt.options._prepare) { @@ -138,7 +140,7 @@ export default defineNuxtModule({ await writeFile(gitignorePath, `${gitignore ? gitignore + '\n' : gitignore}.data`, 'utf-8') } - const needWrangler = Boolean(hub.ai || hub.analytics || hub.blob || hub.database || hub.kv) + const needWrangler = Boolean(hub.ai || hub.analytics || hub.blob || hub.database || hub.kv || hub.vectorize) if (needWrangler) { // Generate the wrangler.toml file const wranglerPath = join(hubDir, './wrangler.toml') diff --git a/src/runtime/utils/features.ts b/src/runtime/utils/features.ts index d96fec91..cd6113ce 100644 --- a/src/runtime/utils/features.ts +++ b/src/runtime/utils/features.ts @@ -22,6 +22,9 @@ const featureMessages = { kv: [ 'NuxtHub KV is not enabled, set `hub.kv = true` in your `nuxt.config.ts`', 'Read more at `https://hub.nuxt.com/docs/features/kv`' + ].join('\n'), + vectorize: [ + 'NuxtHub Vectorize is not enabled, set `hub.vectorize = true` in your `nuxt.config.ts`' ].join('\n') } diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts new file mode 100644 index 00000000..a6d99d1a --- /dev/null +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -0,0 +1,34 @@ +import { createError } from 'h3' +import type { VectorizeIndex } from '@nuxthub/core' +import { requireNuxtHubFeature } from '../../../utils/features' + +let _vectorize: VectorizeIndex + +/** + * Access the Vectorize database. + * + * @example ```ts + * const vectorize = hubVectorize() + * let vectorsToInsert = [ + * {id: "123", values: [32.4, 6.5, 11.2, 10.3, 87.9]}, + * {id: "456", values: [2.5, 7.8, 9.1, 76.9, 8.5]}, + * ] + * let inserted = await vectorize.insert(vectorsToInsert) + * ``` + * + * @see https://developers.cloudflare.com/vectorize/reference/client-api/ + */ +export function hubVectorize(): VectorizeIndex { + requireNuxtHubFeature('vectorize') + + if (_vectorize) { + return _vectorize + } + // @ts-expect-error globalThis.__env__ is not defined + const binding = process.env.VECTORIZE || globalThis.__env__?.VECTORIZE || globalThis.VECTORIZE + if (binding) { + _vectorize = binding as VectorizeIndex + return _vectorize + } + throw createError('Missing Cloudflare DB binding (Vectorize)') +} diff --git a/src/types/index.ts b/src/types/index.ts index 0c3882b4..191c8799 100644 --- a/src/types/index.ts +++ b/src/types/index.ts @@ -2,3 +2,4 @@ export * from './blob' export * from './database' export * from './kv' export * from './module' +export * from './vectorize' diff --git a/src/types/module.ts b/src/types/module.ts index 5c0ee710..0840cf36 100644 --- a/src/types/module.ts +++ b/src/types/module.ts @@ -49,6 +49,12 @@ export interface ModuleOptions { * @default process.env.NUXT_HUB_REMOTE or --remote option when running `nuxt dev` * @see https://hub.nuxt.com/docs/getting-started/remote-storage */ + /** + * Set `true` to enable the database for the project. + * + * @default false + */ + vectorize?: boolean remote?: boolean | 'production' | 'preview' /** * The URL of the NuxtHub Admin diff --git a/src/types/vectorize.ts b/src/types/vectorize.ts new file mode 100644 index 00000000..77e4afc1 --- /dev/null +++ b/src/types/vectorize.ts @@ -0,0 +1 @@ +export type { VectorizeIndex } from '@cloudflare/workers-types/experimental' diff --git a/src/utils/build.ts b/src/utils/build.ts index 6c06e2b0..f1e3a328 100644 --- a/src/utils/build.ts +++ b/src/utils/build.ts @@ -101,7 +101,8 @@ export function addBuildHooks(nuxt: Nuxt, hub: HubConfig) { blob: hub.blob, cache: hub.cache, database: hub.database, - kv: hub.kv + kv: hub.kv, + vectorize: hub.vectorize } await writeFile(join(nitro.options.output.publicDir, 'hub.config.json'), JSON.stringify(hubConfig, null, 2), 'utf-8') }) diff --git a/src/utils/wrangler.ts b/src/utils/wrangler.ts index a92cddc7..acb4494f 100644 --- a/src/utils/wrangler.ts +++ b/src/utils/wrangler.ts @@ -1,6 +1,6 @@ import { stringifyTOML } from 'confbox' -export function generateWrangler(hub: { kv: boolean, database: boolean, blob: boolean, analytics: boolean, ai: boolean, accountId?: string }) { +export function generateWrangler(hub: { kv: boolean, database: boolean, blob: boolean, analytics: boolean, ai: boolean, accountId?: string, vectorize: boolean }) { const wrangler: { [key: string]: any } = {} if (hub.accountId) { @@ -42,5 +42,12 @@ export function generateWrangler(hub: { kv: boolean, database: boolean, blob: bo }] } + if (hub.vectorize) { + wrangler['vectorize'] = [{ + binding: 'VECTORIZE', + index_name: 'default', + }] + } + return stringifyTOML(wrangler) } From 544cd0f1821fcc53a985e75c5888b92e1c64e31d Mon Sep 17 00:00:00 2001 From: Rihan Date: Thu, 20 Jun 2024 10:02:21 +0000 Subject: [PATCH 03/53] fix: typo in error message --- src/runtime/vectorize/server/utils/vectorize.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts index a6d99d1a..1ae97c76 100644 --- a/src/runtime/vectorize/server/utils/vectorize.ts +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -30,5 +30,5 @@ export function hubVectorize(): VectorizeIndex { _vectorize = binding as VectorizeIndex return _vectorize } - throw createError('Missing Cloudflare DB binding (Vectorize)') + throw createError('Missing Cloudflare Vectorize binding (Vectorize)') } From 16a363a1537d816c7f758973ff99521a15bd2498 Mon Sep 17 00:00:00 2001 From: Rihan Date: Thu, 20 Jun 2024 12:37:52 +0000 Subject: [PATCH 04/53] feat: vectorize via proxy --- .../api/_hub/vectorize/[command].post.ts | 53 +++++++++++++ .../api/_hub/vectorize/query.post.ts | 22 ++++++ .../vectorize/server/utils/vectorize.ts | 75 ++++++++++++++++++- 3 files changed, 149 insertions(+), 1 deletion(-) create mode 100644 src/runtime/vectorize/api/_hub/vectorize/[command].post.ts create mode 100644 src/runtime/vectorize/api/_hub/vectorize/query.post.ts diff --git a/src/runtime/vectorize/api/_hub/vectorize/[command].post.ts b/src/runtime/vectorize/api/_hub/vectorize/[command].post.ts new file mode 100644 index 00000000..97f6e7a5 --- /dev/null +++ b/src/runtime/vectorize/api/_hub/vectorize/[command].post.ts @@ -0,0 +1,53 @@ +import { eventHandler, getValidatedRouterParams, readValidatedBody } from 'h3' +import { z } from 'zod' +import { hubVectorize } from '../../../server/utils/vectorize' +import { requireNuxtHubAuthorization } from '../../../../utils/auth' +import { requireNuxtHubFeature } from '../../../../utils/features' + +export default eventHandler(async (event) => { + await requireNuxtHubAuthorization(event) + requireNuxtHubFeature('vectorize') + + // https://developers.cloudflare.com/vectorize/reference/client-api/ + const { command } = await getValidatedRouterParams(event, z.object({ + command: z.enum(['insert', 'upsert', 'query', 'getByIds', 'deleteByIds', 'describe']) + }).parse) + const vectorize = hubVectorize() + + if (command === 'insert' || command === 'upsert') { + const { vectors } = await readValidatedBody(event, z.object({ + vectors: z.array(z.object({ + id: z.string().min(1).max(256), + namespace: z.string().optional(), + values: z.array(z.number()), + metadata: z.record(z.string(), z.any()).optional() + })) + }).parse) + return vectorize[command](vectors) + } + + if (command === 'query') { + const { query, params } = await readValidatedBody(event, z.object({ + query: z.array(z.number()), + params: z.object({ + topK: z.number().optional(), + namespace: z.string().optional(), + returnValues: z.boolean().optional(), + returnMetadata: z.boolean().optional(), + filter: z.record(z.string(), z.any()).optional() + }) + }).parse) + return vectorize.query(query, params) + } + + if (command === 'getByIds' || command === 'deleteByIds') { + const { ids } = await readValidatedBody(event, z.object({ + ids: z.array(z.string().min(1).max(256)) + }).parse) + return vectorize[command](ids) + } + + if (command === 'describe') { + return vectorize.describe() + } +}) diff --git a/src/runtime/vectorize/api/_hub/vectorize/query.post.ts b/src/runtime/vectorize/api/_hub/vectorize/query.post.ts new file mode 100644 index 00000000..1fb13c02 --- /dev/null +++ b/src/runtime/vectorize/api/_hub/vectorize/query.post.ts @@ -0,0 +1,22 @@ +import { eventHandler, readValidatedBody } from 'h3' +import { z } from 'zod' +import { hubVectorize } from '../../../server/utils/vectorize' +import { requireNuxtHubAuthorization } from '../../../../utils/auth' +import { requireNuxtHubFeature } from '../../../../utils/features' + +export default eventHandler(async (event) => { + await requireNuxtHubAuthorization(event) + requireNuxtHubFeature('vectorize') + + const { query, params } = await readValidatedBody(event, z.object({ + query: z.array(z.number()), + params: z.object({ + topK: z.number().optional(), + namespace: z.string().optional(), + returnValues: z.boolean().optional(), + returnMetadata: z.boolean().optional(), + filter: z.record(z.string(), z.any()).optional() + }) + }).parse) + return hubVectorize().query(query, params) +}) diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts index 1ae97c76..5df9cc9b 100644 --- a/src/runtime/vectorize/server/utils/vectorize.ts +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -1,6 +1,10 @@ +import { ofetch } from 'ofetch' +import { joinURL } from 'ufo' import { createError } from 'h3' -import type { VectorizeIndex } from '@nuxthub/core' +import type { H3Error } from 'h3' +import type { VectorizeIndex } from '../../../../types/vectorize' import { requireNuxtHubFeature } from '../../../utils/features' +import { useRuntimeConfig } from '#imports' let _vectorize: VectorizeIndex @@ -16,6 +20,8 @@ let _vectorize: VectorizeIndex * let inserted = await vectorize.insert(vectorsToInsert) * ``` * + * Vectorize is currently only supported with `--remote`. See https://developers.cloudflare.com/workers/testing/local-development/#supported-resource-bindings-in-different-environments for details. + * * @see https://developers.cloudflare.com/vectorize/reference/client-api/ */ export function hubVectorize(): VectorizeIndex { @@ -24,11 +30,78 @@ export function hubVectorize(): VectorizeIndex { if (_vectorize) { return _vectorize } + const hub = useRuntimeConfig().hub // @ts-expect-error globalThis.__env__ is not defined const binding = process.env.VECTORIZE || globalThis.__env__?.VECTORIZE || globalThis.VECTORIZE + if (hub.remote && hub.projectUrl && !binding) { + _vectorize = proxyHubVectorize(hub.projectUrl, hub.projectSecretKey || hub.userToken) + return _vectorize + } if (binding) { _vectorize = binding as VectorizeIndex return _vectorize } throw createError('Missing Cloudflare Vectorize binding (Vectorize)') } + +/** + * Access the remote Vectorize database. + * + * @param projectUrl The project URL (e.g. https://my-deployed-project.nuxt.dev) + * @param secretKey The secret key to authenticate to the remote endpoint + * + * @example ```ts + * const db = proxyHubVectorize('https://my-deployed-project.nuxt.dev', 'my-secret-key') + * let vectorsToInsert = [ + * {id: "123", values: [32.4, 6.5, 11.2, 10.3, 87.9]}, + * {id: "456", values: [2.5, 7.8, 9.1, 76.9, 8.5]}, + * ] + * let inserted = await vectorize.insert(vectorsToInsert) + * ``` + * + * @see https://developers.cloudflare.com/vectorize/reference/client-api/ + */ +export function proxyHubVectorize(projectUrl: string, secretKey?: string): VectorizeIndex { + requireNuxtHubFeature('vectorize') + + const vectorizeAPI = ofetch.create({ + baseURL: joinURL(projectUrl, '/api/_hub/vectorize'), + method: 'POST', + headers: { + Authorization: `Bearer ${secretKey}` + } + }) + return { + async insert(vectors: { id: string, namespace?: string, values: number[], metadata?: Record }[]) { + return vectorizeAPI('/insert', { body: { vectors } }).catch(handleProxyError) + }, + + async upsert(vectors: { id: string, namespace?: string, values: number[], metadata?: Record }[]) { + return vectorizeAPI('/upsert', { body: { vectors } }).catch(handleProxyError) + }, + + async query(query: number[], params: { topK?: number, namespace?: string, returnValues?: boolean, returnMetadata?: boolean, filter?: Record }) { + return vectorizeAPI('/query', { body: { query, params } }).catch(handleProxyError) + }, + + async getByIds(ids: string[], namespace?: string) { + return vectorizeAPI('/getByIds', { body: { ids, namespace } }).catch(handleProxyError) + }, + + async deleteByIds(ids: string[], namespace?: string) { + return vectorizeAPI('/deleteByIds', { body: { ids, namespace } }).catch(handleProxyError) + }, + + async describe() { + return vectorizeAPI('/describe').catch(handleProxyError) + } + } as VectorizeIndex +} + +function handleProxyError(err: H3Error) { + throw createError({ + statusCode: err.statusCode, + // @ts-expect-error not aware of data property + message: err.data?.message || err.message + }) +} From 6847c0d8442757d5892cad14c4144bfc1edb3009 Mon Sep 17 00:00:00 2001 From: Rihan Date: Thu, 20 Jun 2024 12:43:57 +0000 Subject: [PATCH 05/53] feat: include vectorize in build hook --- src/utils/build.ts | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/utils/build.ts b/src/utils/build.ts index f1e3a328..77be151b 100644 --- a/src/utils/build.ts +++ b/src/utils/build.ts @@ -27,7 +27,8 @@ export function addBuildHooks(nuxt: Nuxt, hub: HubConfig) { blob: hub.blob, cache: hub.cache, database: hub.database, - kv: hub.kv + kv: hub.kv, + vectorize: hub.vectorize } }).catch((e) => { if (e.response?._data?.message) { From 6b7813aa2cf83797afe0288abc2037ec186c3223 Mon Sep 17 00:00:00 2001 From: Rihan Date: Tue, 25 Jun 2024 11:09:24 +0000 Subject: [PATCH 06/53] feat: include vectorize and ai in manifest --- src/runtime/base/server/api/_hub/manifest.get.ts | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/src/runtime/base/server/api/_hub/manifest.get.ts b/src/runtime/base/server/api/_hub/manifest.get.ts index 484fe90b..2b4a0210 100644 --- a/src/runtime/base/server/api/_hub/manifest.get.ts +++ b/src/runtime/base/server/api/_hub/manifest.get.ts @@ -3,17 +3,19 @@ import { hubAI } from '../../../../ai/server/utils/ai' import { hubDatabase } from '../../../../database/server/utils/database' import { hubKV } from '../../../../kv/server/utils/kv' import { hubBlob } from '../../../../blob/server/utils/blob' +import { hubVectorize } from '../../../../vectorize/server/utils/vectorize' import { requireNuxtHubAuthorization } from '../../../../utils/auth' import { useRuntimeConfig } from '#imports' export default eventHandler(async (event) => { await requireNuxtHubAuthorization(event) - const { version, cache, ai, analytics, blob, kv, database } = useRuntimeConfig().hub - const [aiCheck, dbCheck, kvCheck, blobCheck] = await Promise.all([ + const { version, cache, ai, analytics, blob, kv, database, vectorize } = useRuntimeConfig().hub + const [aiCheck, dbCheck, kvCheck, blobCheck, vectorizeCheck] = await Promise.all([ falseIfFail(() => ai && hubAI().run('@cf/baai/bge-small-en-v1.5', { text: 'check' })), falseIfFail(() => database && hubDatabase().exec('PRAGMA table_list')), falseIfFail(() => kv && hubKV().getKeys('__check__')), - falseIfFail(() => blob && hubBlob().list({ prefix: '__check__' })) + falseIfFail(() => blob && hubBlob().list({ prefix: '__check__' })), + falseIfFail(() => vectorize && hubVectorize().describe()) ]) return { @@ -21,7 +23,8 @@ export default eventHandler(async (event) => { storage: { database: Boolean(dbCheck), kv: Array.isArray(kvCheck), - blob: Array.isArray(blobCheck?.blobs) + blob: Array.isArray(blobCheck?.blobs), + vectorize: Boolean(vectorizeCheck) }, features: { ai: Boolean(aiCheck), From 1b1a2c717ce5cbe5623eb409c882f7246c702324 Mon Sep 17 00:00:00 2001 From: Rihan Date: Tue, 25 Jun 2024 15:11:50 +0000 Subject: [PATCH 07/53] fix: put server routes in correct directory --- .../{ => server}/api/_hub/vectorize/[command].post.ts | 6 +++--- .../vectorize/{ => server}/api/_hub/vectorize/query.post.ts | 6 +++--- 2 files changed, 6 insertions(+), 6 deletions(-) rename src/runtime/vectorize/{ => server}/api/_hub/vectorize/[command].post.ts (88%) rename src/runtime/vectorize/{ => server}/api/_hub/vectorize/query.post.ts (74%) diff --git a/src/runtime/vectorize/api/_hub/vectorize/[command].post.ts b/src/runtime/vectorize/server/api/_hub/vectorize/[command].post.ts similarity index 88% rename from src/runtime/vectorize/api/_hub/vectorize/[command].post.ts rename to src/runtime/vectorize/server/api/_hub/vectorize/[command].post.ts index 97f6e7a5..7e8334ed 100644 --- a/src/runtime/vectorize/api/_hub/vectorize/[command].post.ts +++ b/src/runtime/vectorize/server/api/_hub/vectorize/[command].post.ts @@ -1,8 +1,8 @@ import { eventHandler, getValidatedRouterParams, readValidatedBody } from 'h3' import { z } from 'zod' -import { hubVectorize } from '../../../server/utils/vectorize' -import { requireNuxtHubAuthorization } from '../../../../utils/auth' -import { requireNuxtHubFeature } from '../../../../utils/features' +import { hubVectorize } from '../../../../server/utils/vectorize' +import { requireNuxtHubAuthorization } from '../../../../../utils/auth' +import { requireNuxtHubFeature } from '../../../../../utils/features' export default eventHandler(async (event) => { await requireNuxtHubAuthorization(event) diff --git a/src/runtime/vectorize/api/_hub/vectorize/query.post.ts b/src/runtime/vectorize/server/api/_hub/vectorize/query.post.ts similarity index 74% rename from src/runtime/vectorize/api/_hub/vectorize/query.post.ts rename to src/runtime/vectorize/server/api/_hub/vectorize/query.post.ts index 1fb13c02..bae683cf 100644 --- a/src/runtime/vectorize/api/_hub/vectorize/query.post.ts +++ b/src/runtime/vectorize/server/api/_hub/vectorize/query.post.ts @@ -1,8 +1,8 @@ import { eventHandler, readValidatedBody } from 'h3' import { z } from 'zod' -import { hubVectorize } from '../../../server/utils/vectorize' -import { requireNuxtHubAuthorization } from '../../../../utils/auth' -import { requireNuxtHubFeature } from '../../../../utils/features' +import { hubVectorize } from '../../../../server/utils/vectorize' +import { requireNuxtHubAuthorization } from '../../../../../utils/auth' +import { requireNuxtHubFeature } from '../../../../../utils/features' export default eventHandler(async (event) => { await requireNuxtHubAuthorization(event) From aeb96f056b77970f5d201bcea525103766100abf Mon Sep 17 00:00:00 2001 From: "autofix-ci[bot]" <114827586+autofix-ci[bot]@users.noreply.github.com> Date: Tue, 25 Jun 2024 15:13:37 +0000 Subject: [PATCH 08/53] [autofix.ci] apply automated fixes --- package.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/package.json b/package.json index ca5f0c5c..f3cc7848 100644 --- a/package.json +++ b/package.json @@ -63,7 +63,7 @@ "@nuxt/module-builder": "^0.8.3", "@nuxt/schema": "^3.12.4", "@nuxt/test-utils": "^3.14.1", - "@nuxthub/core": "link:.", + "@nuxthub/core": "https://pkg.pr.new/nuxt-hub/core/@nuxthub/core@aedb7c2", "@types/node": "^22.3.0", "changelogen": "^0.5.5", "eslint": "^9.9.0", From 79a488e45230b0a967ce3001e60c733e3d9d8450 Mon Sep 17 00:00:00 2001 From: Rihan Date: Wed, 26 Jun 2024 09:17:43 +0000 Subject: [PATCH 09/53] fix: remove unused param from vectorize.getByIds proxy wrapper --- src/runtime/vectorize/server/utils/vectorize.ts | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts index 5df9cc9b..a49bafdf 100644 --- a/src/runtime/vectorize/server/utils/vectorize.ts +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -84,12 +84,12 @@ export function proxyHubVectorize(projectUrl: string, secretKey?: string): Vecto return vectorizeAPI('/query', { body: { query, params } }).catch(handleProxyError) }, - async getByIds(ids: string[], namespace?: string) { - return vectorizeAPI('/getByIds', { body: { ids, namespace } }).catch(handleProxyError) + async getByIds(ids: string[]) { + return vectorizeAPI('/getByIds', { body: { ids } }).catch(handleProxyError) }, - async deleteByIds(ids: string[], namespace?: string) { - return vectorizeAPI('/deleteByIds', { body: { ids, namespace } }).catch(handleProxyError) + async deleteByIds(ids: string[]) { + return vectorizeAPI('/deleteByIds', { body: { ids } }).catch(handleProxyError) }, async describe() { From b89097911f4520ffe1d92020b3ea367ef5734752 Mon Sep 17 00:00:00 2001 From: Rihan Date: Wed, 26 Jun 2024 09:18:40 +0000 Subject: [PATCH 10/53] feat: match namespace length limits in proxy wrapper validator --- .../vectorize/server/api/_hub/vectorize/[command].post.ts | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/runtime/vectorize/server/api/_hub/vectorize/[command].post.ts b/src/runtime/vectorize/server/api/_hub/vectorize/[command].post.ts index 7e8334ed..e0e7c345 100644 --- a/src/runtime/vectorize/server/api/_hub/vectorize/[command].post.ts +++ b/src/runtime/vectorize/server/api/_hub/vectorize/[command].post.ts @@ -18,7 +18,7 @@ export default eventHandler(async (event) => { const { vectors } = await readValidatedBody(event, z.object({ vectors: z.array(z.object({ id: z.string().min(1).max(256), - namespace: z.string().optional(), + namespace: z.string().min(1).max(63).optional(), values: z.array(z.number()), metadata: z.record(z.string(), z.any()).optional() })) @@ -31,7 +31,7 @@ export default eventHandler(async (event) => { query: z.array(z.number()), params: z.object({ topK: z.number().optional(), - namespace: z.string().optional(), + namespace: z.string().min(1).max(63).optional(), returnValues: z.boolean().optional(), returnMetadata: z.boolean().optional(), filter: z.record(z.string(), z.any()).optional() From 844b009a20613107f257879097e31a975d04c212 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Sat, 31 Aug 2024 02:57:19 +0100 Subject: [PATCH 11/53] fix: make dev:prepare work on windows --- package.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/package.json b/package.json index b67aeb12..492e502e 100644 --- a/package.json +++ b/package.json @@ -26,7 +26,7 @@ ], "scripts": { "prepack": "nuxt-module-build build", - "dev:prepare": "nuxt-module-build build --stub; nuxt-module-build prepare; nuxi prepare playground", + "dev:prepare": "nuxt-module-build build --stub && nuxt-module-build prepare && nuxi prepare playground", "dev": "nuxi dev playground", "dev:build": "nuxi build playground", "docs": "PORT=4000 nuxi dev docs", From 959ee2fd156c44831404419905b493843b8cdfb1 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Sat, 31 Aug 2024 03:00:27 +0100 Subject: [PATCH 12/53] refactor: remove account id vectorize currently doesn't support local bindings so it will use remote via nuxthub link --- src/module.ts | 1 - src/types/module.ts | 6 ------ src/utils/wrangler.ts | 6 +----- 3 files changed, 1 insertion(+), 12 deletions(-) diff --git a/src/module.ts b/src/module.ts index f29533d9..b38baa97 100644 --- a/src/module.ts +++ b/src/module.ts @@ -38,7 +38,6 @@ export default defineNuxtModule({ remoteArg = (remoteArg === '' ? 'true' : remoteArg) const runtimeConfig = nuxt.options.runtimeConfig const hub = defu(runtimeConfig.hub || {}, options, { - accountId: process.env.CLOUDFLARE_ACCOUNT_ID || '', // Self-hosted project projectUrl: process.env.NUXT_HUB_PROJECT_URL || '', projectSecretKey: process.env.NUXT_HUB_PROJECT_SECRET_KEY || '', diff --git a/src/types/module.ts b/src/types/module.ts index b461dfc1..81fe0d59 100644 --- a/src/types/module.ts +++ b/src/types/module.ts @@ -112,10 +112,4 @@ export interface ModuleOptions { [key: string]: string } } - /** - * The account ID of the Cloudflare account to use for local development. - * Only necessary if using AI and logged-in user has access to multiple accounts. - * @default process.env.CLOUDFLARE_ACCOUNT_ID - */ - accountId?: string } diff --git a/src/utils/wrangler.ts b/src/utils/wrangler.ts index 53414f43..0153b409 100644 --- a/src/utils/wrangler.ts +++ b/src/utils/wrangler.ts @@ -5,10 +5,6 @@ import type { HubConfig } from '../features' export function generateWrangler(nuxt: Nuxt, hub: HubConfig) { const wrangler: { [key: string]: any } = {} - if (hub.accountId) { - wrangler['account_id'] = hub.accountId - } - if (hub.ai) { wrangler['ai'] = { binding: 'AI' @@ -47,7 +43,7 @@ export function generateWrangler(nuxt: Nuxt, hub: HubConfig) { if (hub.vectorize) { wrangler['vectorize'] = [{ binding: 'VECTORIZE', - index_name: 'default', + index_name: 'default' }] } From 0c6adccd3153ebef5155ab7b734e02615d4d8c3e Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Sat, 31 Aug 2024 03:01:22 +0100 Subject: [PATCH 13/53] fix: use new vectorize types cloudflare replaced alpha VectorizeIndex type with new Vectorize type. the old one will be deprecated. --- src/runtime/vectorize/server/utils/vectorize.ts | 12 ++++++------ src/types/vectorize.ts | 2 +- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts index a49bafdf..3bcd1e7b 100644 --- a/src/runtime/vectorize/server/utils/vectorize.ts +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -2,11 +2,11 @@ import { ofetch } from 'ofetch' import { joinURL } from 'ufo' import { createError } from 'h3' import type { H3Error } from 'h3' -import type { VectorizeIndex } from '../../../../types/vectorize' +import type { Vectorize } from '../../../../types/vectorize' import { requireNuxtHubFeature } from '../../../utils/features' import { useRuntimeConfig } from '#imports' -let _vectorize: VectorizeIndex +let _vectorize: Vectorize /** * Access the Vectorize database. @@ -24,7 +24,7 @@ let _vectorize: VectorizeIndex * * @see https://developers.cloudflare.com/vectorize/reference/client-api/ */ -export function hubVectorize(): VectorizeIndex { +export function hubVectorize(): Vectorize { requireNuxtHubFeature('vectorize') if (_vectorize) { @@ -38,7 +38,7 @@ export function hubVectorize(): VectorizeIndex { return _vectorize } if (binding) { - _vectorize = binding as VectorizeIndex + _vectorize = binding as Vectorize return _vectorize } throw createError('Missing Cloudflare Vectorize binding (Vectorize)') @@ -61,7 +61,7 @@ export function hubVectorize(): VectorizeIndex { * * @see https://developers.cloudflare.com/vectorize/reference/client-api/ */ -export function proxyHubVectorize(projectUrl: string, secretKey?: string): VectorizeIndex { +export function proxyHubVectorize(projectUrl: string, secretKey?: string): Vectorize { requireNuxtHubFeature('vectorize') const vectorizeAPI = ofetch.create({ @@ -95,7 +95,7 @@ export function proxyHubVectorize(projectUrl: string, secretKey?: string): Vecto async describe() { return vectorizeAPI('/describe').catch(handleProxyError) } - } as VectorizeIndex + } as Vectorize } function handleProxyError(err: H3Error) { diff --git a/src/types/vectorize.ts b/src/types/vectorize.ts index 77e4afc1..ca5eebe7 100644 --- a/src/types/vectorize.ts +++ b/src/types/vectorize.ts @@ -1 +1 @@ -export type { VectorizeIndex } from '@cloudflare/workers-types/experimental' +export type { Vectorize } from '@cloudflare/workers-types/experimental' From 1b1563aa316df6eb219fbf3310cfc10e641fbed2 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Tue, 17 Sep 2024 14:58:44 +0100 Subject: [PATCH 14/53] feat: support multiple vectorize indexes and metadata indexes --- src/features.ts | 10 +++++- src/module.ts | 4 +-- src/runtime/utils/features.ts | 3 +- .../vectorize/server/utils/vectorize.ts | 33 ++++++++++------- src/types/module.ts | 35 ++++++++++++++++--- 5 files changed, 65 insertions(+), 20 deletions(-) diff --git a/src/features.ts b/src/features.ts index 446ee5c2..95645da1 100644 --- a/src/features.ts +++ b/src/features.ts @@ -27,7 +27,15 @@ export interface HubConfig { cache?: boolean database?: boolean kv?: boolean - vectorize?: boolean + vectorize?: { + [key: string]: { + metric: 'cosine' | 'euclidean' | 'dot-product' + dimensions: number + metadata_indexes: { + [index: string]: string | number | boolean + } & { length: 10 } + } + } bindings?: { compatibilityDate?: string diff --git a/src/module.ts b/src/module.ts index a0ab9bcf..e293e031 100644 --- a/src/module.ts +++ b/src/module.ts @@ -59,7 +59,7 @@ export default defineNuxtModule({ cache: false, database: false, kv: false, - vectorize: false, + vectorize: {}, // Other options version, env: process.env.NUXT_HUB_ENV || 'production', @@ -181,7 +181,7 @@ export default defineNuxtModule({ await writeFile(gitignorePath, `${gitignore ? gitignore + '\n' : gitignore}.data`, 'utf-8') } - const needWrangler = Boolean(hub.ai || hub.analytics || hub.blob || hub.database || hub.kv || hub.vectorize) + const needWrangler = Boolean(hub.ai || hub.analytics || hub.blob || hub.database || hub.kv) // const needWrangler = Boolean(hub.ai || hub.analytics || hub.blob || hub.database || hub.kv || Object.keys(hub.bindings.hyperdrive).length > 0) if (needWrangler) { // Generate the wrangler.toml file diff --git a/src/runtime/utils/features.ts b/src/runtime/utils/features.ts index cd6113ce..2c6e3367 100644 --- a/src/runtime/utils/features.ts +++ b/src/runtime/utils/features.ts @@ -24,7 +24,8 @@ const featureMessages = { 'Read more at `https://hub.nuxt.com/docs/features/kv`' ].join('\n'), vectorize: [ - 'NuxtHub Vectorize is not enabled, set `hub.vectorize = true` in your `nuxt.config.ts`' + 'NuxtHub Vectorize is not enabled, refer to the documentation.', + 'Read more at `https://hub.nuxt.com/docs/features/vectorize`' ].join('\n') } diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts index 3bcd1e7b..80cb2f7b 100644 --- a/src/runtime/vectorize/server/utils/vectorize.ts +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -2,17 +2,22 @@ import { ofetch } from 'ofetch' import { joinURL } from 'ufo' import { createError } from 'h3' import type { H3Error } from 'h3' +import type { RuntimeConfig } from 'nuxt/schema' import type { Vectorize } from '../../../../types/vectorize' import { requireNuxtHubFeature } from '../../../utils/features' import { useRuntimeConfig } from '#imports' -let _vectorize: Vectorize +const _vectorize: Record = {} + +type VectorizeIndexes = keyof RuntimeConfig['hub']['vectorize'] & string /** * Access the Vectorize database. * + * @param index The Vectorize index to access + * * @example ```ts - * const vectorize = hubVectorize() + * const vectorize = hubVectorize('products') * let vectorsToInsert = [ * {id: "123", values: [32.4, 6.5, 11.2, 10.3, 87.9]}, * {id: "456", values: [2.5, 7.8, 9.1, 76.9, 8.5]}, @@ -22,26 +27,30 @@ let _vectorize: Vectorize * * Vectorize is currently only supported with `--remote`. See https://developers.cloudflare.com/workers/testing/local-development/#supported-resource-bindings-in-different-environments for details. * - * @see https://developers.cloudflare.com/vectorize/reference/client-api/ + * @see https://hub.nuxt.com/docs/features/vectorize */ -export function hubVectorize(): Vectorize { +export function hubVectorize(index: VectorizeIndexes): Vectorize { + // todo: autosuggest indexes for hubVectorize based on what's set in nuxt.config.ts.hub.vectorize[index] requireNuxtHubFeature('vectorize') - if (_vectorize) { - return _vectorize + if (_vectorize[index]) { + return _vectorize[index] } + const hub = useRuntimeConfig().hub + const bindingName = `VECTORIZE_${index.toUpperCase}` + // @ts-expect-error globalThis.__env__ is not defined - const binding = process.env.VECTORIZE || globalThis.__env__?.VECTORIZE || globalThis.VECTORIZE + const binding = process.env[bindingName] || globalThis.__env__?.[bindingName] || globalThis[bindingName] if (hub.remote && hub.projectUrl && !binding) { - _vectorize = proxyHubVectorize(hub.projectUrl, hub.projectSecretKey || hub.userToken) - return _vectorize + _vectorize[index] = proxyHubVectorize(hub.projectUrl, hub.projectSecretKey || hub.userToken) + return _vectorize[index] } if (binding) { - _vectorize = binding as Vectorize - return _vectorize + _vectorize[index] = binding as Vectorize + return _vectorize[index] } - throw createError('Missing Cloudflare Vectorize binding (Vectorize)') + throw createError(`Missing Cloudflare Vectorize binding (${bindingName})`) } /** diff --git a/src/types/module.ts b/src/types/module.ts index ea381095..da5c0efd 100644 --- a/src/types/module.ts +++ b/src/types/module.ts @@ -50,11 +50,38 @@ export interface ModuleOptions { */ kv?: boolean /** - * Set `true` to enable the database for the project. + * Set Vectorize indexes for the project. * - * @default false - */ - vectorize?: boolean + * Currently there is a limit of 10 metadata indexes per vectorize index. + * + * @default {} + * @see https://hub.nuxt.com/docs/features/vectorize + * + * @example + * ```ts + * vectorize: { + * products: { + * metric: 'cosine', + * dimensions: '768', + * metadata_indexes: { name: 'string', price: 'number', isActive: 'boolean' } + * }, + * reviews: { + * metric: 'cosine', + * dimensions: '768', + * metadata_indexes: { rating: 'number' } + * } + * } + * ``` + */ + vectorize: { + [key: string]: { + metric: 'cosine' | 'euclidean' | 'dot-product' + dimensions: number + metadata_indexes: { + [index: string]: 'string' | 'number' | 'boolean' + } & { length: 10 } + } + } /** * Set to `true`, 'preview' or 'production' to use the remote storage. * Only set the value on a project you are deploying outside of NuxtHub or Cloudflare. From 943c4796854caa4cdbe04e764d8b7de4e4c17b29 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Tue, 17 Sep 2024 14:59:20 +0100 Subject: [PATCH 15/53] fix: don't include vectorize in generated wrangler file --- src/utils/wrangler.ts | 7 ------- 1 file changed, 7 deletions(-) diff --git a/src/utils/wrangler.ts b/src/utils/wrangler.ts index daa37d7c..12377c11 100644 --- a/src/utils/wrangler.ts +++ b/src/utils/wrangler.ts @@ -42,13 +42,6 @@ export function generateWrangler(nuxt: Nuxt, hub: HubConfig) { }] } - if (hub.vectorize) { - wrangler['vectorize'] = [{ - binding: 'VECTORIZE', - index_name: 'default' - }] - } - // Disabled until getPlatformProxy() returns the hyperdrive binding // if (hub.bindings?.hyperdrive) { // wrangler['hyperdrive'] = Object.entries(hub.bindings.hyperdrive).map(([key, value]) => { From 65a66120516ea9503cf667c3f22eb38fa0781138 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Tue, 17 Sep 2024 16:35:26 +0100 Subject: [PATCH 16/53] feat: support multiple indexes on remote proxy --- .../vectorize/{ => [index]}/[command].post.ts | 11 +++++----- .../server/api/_hub/vectorize/query.post.ts | 22 ------------------- .../vectorize/server/utils/vectorize.ts | 7 +++--- 3 files changed, 10 insertions(+), 30 deletions(-) rename src/runtime/vectorize/server/api/_hub/vectorize/{ => [index]}/[command].post.ts (80%) delete mode 100644 src/runtime/vectorize/server/api/_hub/vectorize/query.post.ts diff --git a/src/runtime/vectorize/server/api/_hub/vectorize/[command].post.ts b/src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts similarity index 80% rename from src/runtime/vectorize/server/api/_hub/vectorize/[command].post.ts rename to src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts index e0e7c345..35b170f5 100644 --- a/src/runtime/vectorize/server/api/_hub/vectorize/[command].post.ts +++ b/src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts @@ -1,18 +1,19 @@ import { eventHandler, getValidatedRouterParams, readValidatedBody } from 'h3' import { z } from 'zod' -import { hubVectorize } from '../../../../server/utils/vectorize' -import { requireNuxtHubAuthorization } from '../../../../../utils/auth' -import { requireNuxtHubFeature } from '../../../../../utils/features' +import { hubVectorize } from '../../../../utils/vectorize' +import { requireNuxtHubAuthorization } from '../../../../../../utils/auth' +import { requireNuxtHubFeature } from '../../../../../../utils/features' export default eventHandler(async (event) => { await requireNuxtHubAuthorization(event) requireNuxtHubFeature('vectorize') // https://developers.cloudflare.com/vectorize/reference/client-api/ - const { command } = await getValidatedRouterParams(event, z.object({ + const { index, command } = await getValidatedRouterParams(event, z.object({ + index: z.string().min(1).max(64).regex(/^[a-z-]$/), command: z.enum(['insert', 'upsert', 'query', 'getByIds', 'deleteByIds', 'describe']) }).parse) - const vectorize = hubVectorize() + const vectorize = hubVectorize(index) if (command === 'insert' || command === 'upsert') { const { vectors } = await readValidatedBody(event, z.object({ diff --git a/src/runtime/vectorize/server/api/_hub/vectorize/query.post.ts b/src/runtime/vectorize/server/api/_hub/vectorize/query.post.ts deleted file mode 100644 index bae683cf..00000000 --- a/src/runtime/vectorize/server/api/_hub/vectorize/query.post.ts +++ /dev/null @@ -1,22 +0,0 @@ -import { eventHandler, readValidatedBody } from 'h3' -import { z } from 'zod' -import { hubVectorize } from '../../../../server/utils/vectorize' -import { requireNuxtHubAuthorization } from '../../../../../utils/auth' -import { requireNuxtHubFeature } from '../../../../../utils/features' - -export default eventHandler(async (event) => { - await requireNuxtHubAuthorization(event) - requireNuxtHubFeature('vectorize') - - const { query, params } = await readValidatedBody(event, z.object({ - query: z.array(z.number()), - params: z.object({ - topK: z.number().optional(), - namespace: z.string().optional(), - returnValues: z.boolean().optional(), - returnMetadata: z.boolean().optional(), - filter: z.record(z.string(), z.any()).optional() - }) - }).parse) - return hubVectorize().query(query, params) -}) diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts index 80cb2f7b..a22f64f2 100644 --- a/src/runtime/vectorize/server/utils/vectorize.ts +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -43,7 +43,7 @@ export function hubVectorize(index: VectorizeIndexes): Vectorize { // @ts-expect-error globalThis.__env__ is not defined const binding = process.env[bindingName] || globalThis.__env__?.[bindingName] || globalThis[bindingName] if (hub.remote && hub.projectUrl && !binding) { - _vectorize[index] = proxyHubVectorize(hub.projectUrl, hub.projectSecretKey || hub.userToken) + _vectorize[index] = proxyHubVectorize(index, hub.projectUrl, hub.projectSecretKey || hub.userToken) return _vectorize[index] } if (binding) { @@ -56,6 +56,7 @@ export function hubVectorize(index: VectorizeIndexes): Vectorize { /** * Access the remote Vectorize database. * + * @param index The Vectorize index to access * @param projectUrl The project URL (e.g. https://my-deployed-project.nuxt.dev) * @param secretKey The secret key to authenticate to the remote endpoint * @@ -70,11 +71,11 @@ export function hubVectorize(index: VectorizeIndexes): Vectorize { * * @see https://developers.cloudflare.com/vectorize/reference/client-api/ */ -export function proxyHubVectorize(projectUrl: string, secretKey?: string): Vectorize { +export function proxyHubVectorize(index: VectorizeIndexes, projectUrl: string, secretKey?: string): Vectorize { requireNuxtHubFeature('vectorize') const vectorizeAPI = ofetch.create({ - baseURL: joinURL(projectUrl, '/api/_hub/vectorize'), + baseURL: joinURL(projectUrl, `/api/_hub/vectorize/${index}`), method: 'POST', headers: { Authorization: `Bearer ${secretKey}` From 8f7edc7b0df1ab85de8165c79cdf81b5564c0e0f Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Tue, 17 Sep 2024 16:39:23 +0100 Subject: [PATCH 17/53] feat: use vectorize v2 returnMetadata options --- .../server/api/_hub/vectorize/[index]/[command].post.ts | 2 +- src/runtime/vectorize/server/utils/vectorize.ts | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts b/src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts index 35b170f5..78100861 100644 --- a/src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts +++ b/src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts @@ -34,7 +34,7 @@ export default eventHandler(async (event) => { topK: z.number().optional(), namespace: z.string().min(1).max(63).optional(), returnValues: z.boolean().optional(), - returnMetadata: z.boolean().optional(), + returnMetadata: z.union([z.literal('none'), z.literal('indexed'), z.literal('all')]).optional(), filter: z.record(z.string(), z.any()).optional() }) }).parse) diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts index a22f64f2..a391dd97 100644 --- a/src/runtime/vectorize/server/utils/vectorize.ts +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -90,7 +90,7 @@ export function proxyHubVectorize(index: VectorizeIndexes, projectUrl: string, s return vectorizeAPI('/upsert', { body: { vectors } }).catch(handleProxyError) }, - async query(query: number[], params: { topK?: number, namespace?: string, returnValues?: boolean, returnMetadata?: boolean, filter?: Record }) { + async query(query: number[], params: { topK?: number, namespace?: string, returnValues?: boolean, returnMetadata?: 'none' | 'indexed' | 'all', filter?: Record }) { return vectorizeAPI('/query', { body: { query, params } }).catch(handleProxyError) }, From 76c4b5ce195e5a5b8f29ac9f0f142a88f0ae445f Mon Sep 17 00:00:00 2001 From: "autofix-ci[bot]" <114827586+autofix-ci[bot]@users.noreply.github.com> Date: Tue, 17 Sep 2024 15:41:00 +0000 Subject: [PATCH 18/53] [autofix.ci] apply automated fixes From e997b26ed8b1e954ef54e0984f7437f01ea3a0c8 Mon Sep 17 00:00:00 2001 From: "autofix-ci[bot]" <114827586+autofix-ci[bot]@users.noreply.github.com> Date: Tue, 17 Sep 2024 15:42:27 +0000 Subject: [PATCH 19/53] [autofix.ci] apply automated fixes (attempt 2/3) From c34e54f0bae94f5e6cfb821213be4938052d6328 Mon Sep 17 00:00:00 2001 From: "autofix-ci[bot]" <114827586+autofix-ci[bot]@users.noreply.github.com> Date: Tue, 17 Sep 2024 15:43:57 +0000 Subject: [PATCH 20/53] [autofix.ci] apply automated fixes (attempt 3/3) From d12853bdcf6d6d8867dae71256c7155f14db7c10 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Wed, 18 Sep 2024 00:16:28 +0100 Subject: [PATCH 21/53] fix: support multiple bindings syntax in manifest check --- src/runtime/base/server/api/_hub/manifest.get.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/runtime/base/server/api/_hub/manifest.get.ts b/src/runtime/base/server/api/_hub/manifest.get.ts index faaaa8a8..3a60022d 100644 --- a/src/runtime/base/server/api/_hub/manifest.get.ts +++ b/src/runtime/base/server/api/_hub/manifest.get.ts @@ -15,7 +15,7 @@ export default eventHandler(async (event) => { falseIfFail(() => database && hubDatabase().exec('PRAGMA table_list')), falseIfFail(() => kv && hubKV().getKeys('__check__')), falseIfFail(() => blob && hubBlob().list({ prefix: '__check__' })), - falseIfFail(() => vectorize && hubVectorize().describe()) + falseIfFail(() => Object.keys(vectorize).length && hubVectorize(Object.keys(vectorize)[0]).describe()) ]) return { From 5bd8b5f56c85eeb845127cc71cb744e919c95698 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Thu, 19 Sep 2024 12:36:52 +0100 Subject: [PATCH 22/53] fix: correct case styles --- src/features.ts | 2 +- src/types/module.ts | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/src/features.ts b/src/features.ts index 95645da1..f3c8a9db 100644 --- a/src/features.ts +++ b/src/features.ts @@ -31,7 +31,7 @@ export interface HubConfig { [key: string]: { metric: 'cosine' | 'euclidean' | 'dot-product' dimensions: number - metadata_indexes: { + metadataIndexes: { [index: string]: string | number | boolean } & { length: 10 } } diff --git a/src/types/module.ts b/src/types/module.ts index da5c0efd..711ae468 100644 --- a/src/types/module.ts +++ b/src/types/module.ts @@ -63,12 +63,12 @@ export interface ModuleOptions { * products: { * metric: 'cosine', * dimensions: '768', - * metadata_indexes: { name: 'string', price: 'number', isActive: 'boolean' } + * metadataIndexes: { name: 'string', price: 'number', isActive: 'boolean' } * }, * reviews: { * metric: 'cosine', * dimensions: '768', - * metadata_indexes: { rating: 'number' } + * metadataIndexes: { rating: 'number' } * } * } * ``` @@ -77,7 +77,7 @@ export interface ModuleOptions { [key: string]: { metric: 'cosine' | 'euclidean' | 'dot-product' dimensions: number - metadata_indexes: { + metadataIndexes: { [index: string]: 'string' | 'number' | 'boolean' } & { length: 10 } } From c25c178958b8ae619338730681aae4111a9b1db0 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Thu, 19 Sep 2024 13:12:36 +0100 Subject: [PATCH 23/53] refactor: simplify type --- src/features.ts | 4 +--- src/types/module.ts | 4 +--- 2 files changed, 2 insertions(+), 6 deletions(-) diff --git a/src/features.ts b/src/features.ts index f3c8a9db..3e39b3ff 100644 --- a/src/features.ts +++ b/src/features.ts @@ -31,9 +31,7 @@ export interface HubConfig { [key: string]: { metric: 'cosine' | 'euclidean' | 'dot-product' dimensions: number - metadataIndexes: { - [index: string]: string | number | boolean - } & { length: 10 } + metadataIndexes: Record } } diff --git a/src/types/module.ts b/src/types/module.ts index 711ae468..fa62645c 100644 --- a/src/types/module.ts +++ b/src/types/module.ts @@ -77,9 +77,7 @@ export interface ModuleOptions { [key: string]: { metric: 'cosine' | 'euclidean' | 'dot-product' dimensions: number - metadataIndexes: { - [index: string]: 'string' | 'number' | 'boolean' - } & { length: 10 } + metadataIndexes: Record } } /** From 311bee7c85a93c7b144ce59e46b5eda9b49d226e Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Thu, 19 Sep 2024 13:18:31 +0100 Subject: [PATCH 24/53] fix: make metadataIndexes optional --- src/features.ts | 2 +- src/types/module.ts | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/features.ts b/src/features.ts index 3e39b3ff..e388991f 100644 --- a/src/features.ts +++ b/src/features.ts @@ -31,7 +31,7 @@ export interface HubConfig { [key: string]: { metric: 'cosine' | 'euclidean' | 'dot-product' dimensions: number - metadataIndexes: Record + metadataIndexes?: Record } } diff --git a/src/types/module.ts b/src/types/module.ts index fa62645c..c97da0d4 100644 --- a/src/types/module.ts +++ b/src/types/module.ts @@ -77,7 +77,7 @@ export interface ModuleOptions { [key: string]: { metric: 'cosine' | 'euclidean' | 'dot-product' dimensions: number - metadataIndexes: Record + metadataIndexes?: Record } } /** From debceb90588dd54e4171cf0afa01698b36b299e9 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Fri, 20 Sep 2024 21:34:39 +0100 Subject: [PATCH 25/53] feat: include enabled vectorize indexes in manifest --- src/runtime/base/server/api/_hub/manifest.get.ts | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/src/runtime/base/server/api/_hub/manifest.get.ts b/src/runtime/base/server/api/_hub/manifest.get.ts index 3a60022d..5fbce7f2 100644 --- a/src/runtime/base/server/api/_hub/manifest.get.ts +++ b/src/runtime/base/server/api/_hub/manifest.get.ts @@ -15,16 +15,23 @@ export default eventHandler(async (event) => { falseIfFail(() => database && hubDatabase().exec('PRAGMA table_list')), falseIfFail(() => kv && hubKV().getKeys('__check__')), falseIfFail(() => blob && hubBlob().list({ prefix: '__check__' })), - falseIfFail(() => Object.keys(vectorize).length && hubVectorize(Object.keys(vectorize)[0]).describe()) + // vectorize check should verify all indexes. return the index name + Promise.all(Object.keys(vectorize).map(async (index) => { + const vectorizeIndex = hubVectorize(index) + const describe = await falseIfFail(() => vectorizeIndex.describe()) + return [index, Boolean(describe)] + })) ]) + const enabledVectorizeIndexes = Object.fromEntries(Object.entries(vectorize).filter(([index]) => vectorizeCheck.find(([name, enabled]) => name === index && enabled))) + return { version, storage: { database: Boolean(dbCheck), kv: Array.isArray(kvCheck), blob: Array.isArray(blobCheck?.blobs), - vectorize: Boolean(vectorizeCheck) + vectorize: enabledVectorizeIndexes }, features: { ai: Boolean(aiCheck), From 0b33a315c94c3c725a1a8cc1fb62263991aa2045 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Tue, 24 Sep 2024 19:16:50 +0100 Subject: [PATCH 26/53] fix: only setup vectorize if indexes configured --- src/module.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/module.ts b/src/module.ts index e293e031..cf003346 100644 --- a/src/module.ts +++ b/src/module.ts @@ -98,7 +98,7 @@ export default defineNuxtModule({ hub.cache && setupCache(nuxt) hub.database && setupDatabase(nuxt) hub.kv && setupKV(nuxt) - hub.vectorize && setupVectorize(nuxt) + Object.keys(hub.vectorize || {}).length && setupVectorize(nuxt) // nuxt prepare, stop here if (nuxt.options._prepare) { From 76c5afeef8a9bae18e71901911d47e9e0b0de101 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Tue, 24 Sep 2024 21:10:32 +0100 Subject: [PATCH 27/53] revert: "fix: make dev:prepare work on windows" This reverts commit 844b009a20613107f257879097e31a975d04c212. --- package.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/package.json b/package.json index f9da9877..360e8edb 100644 --- a/package.json +++ b/package.json @@ -26,7 +26,7 @@ ], "scripts": { "prepack": "nuxt-module-build build", - "dev:prepare": "nuxt-module-build build --stub && nuxt-module-build prepare && nuxi prepare playground", + "dev:prepare": "nuxt-module-build build --stub; nuxt-module-build prepare; nuxi prepare playground", "dev": "nuxi dev playground", "dev:build": "nuxi build playground", "docs": "PORT=4000 nuxi dev docs", From 388434ccac62a021a479ebf1c5174172f07702d3 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Tue, 24 Sep 2024 22:25:46 +0100 Subject: [PATCH 28/53] fix: don't directly export type from @cloudflare/workers-types directly re-exporting the type causes the module's generated types file to only be re-exported types and nothing else. --- src/types/vectorize.ts | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/types/vectorize.ts b/src/types/vectorize.ts index ca5eebe7..74ee7b01 100644 --- a/src/types/vectorize.ts +++ b/src/types/vectorize.ts @@ -1 +1,3 @@ -export type { Vectorize } from '@cloudflare/workers-types/experimental' +import type { Vectorize as CFVectorize } from '@cloudflare/workers-types/experimental' + +export type Vectorize = CFVectorize From ad3098e4699a66e4bf6353aa1d8a93bcbaf4e9fc Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Tue, 24 Sep 2024 22:30:06 +0100 Subject: [PATCH 29/53] refactor: clean up code --- src/module.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/module.ts b/src/module.ts index cf003346..05fe81d4 100644 --- a/src/module.ts +++ b/src/module.ts @@ -98,7 +98,7 @@ export default defineNuxtModule({ hub.cache && setupCache(nuxt) hub.database && setupDatabase(nuxt) hub.kv && setupKV(nuxt) - Object.keys(hub.vectorize || {}).length && setupVectorize(nuxt) + Object.keys(hub.vectorize).length && setupVectorize(nuxt) // nuxt prepare, stop here if (nuxt.options._prepare) { From 0b07ec2dac55134582a3a84cd1560997b16e6a8c Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Mon, 30 Sep 2024 03:06:55 +0100 Subject: [PATCH 30/53] fix: correctly call function --- src/runtime/vectorize/server/utils/vectorize.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts index a391dd97..7baa2e28 100644 --- a/src/runtime/vectorize/server/utils/vectorize.ts +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -38,7 +38,7 @@ export function hubVectorize(index: VectorizeIndexes): Vectorize { } const hub = useRuntimeConfig().hub - const bindingName = `VECTORIZE_${index.toUpperCase}` + const bindingName = `VECTORIZE_${index.toUpperCase()}` // @ts-expect-error globalThis.__env__ is not defined const binding = process.env[bindingName] || globalThis.__env__?.[bindingName] || globalThis[bindingName] From cc3bb38637da68f3bb6f5d9ce48da6b73d7f3799 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Mon, 30 Sep 2024 03:52:02 +0100 Subject: [PATCH 31/53] fix: improve regex for index name requirements --- .../server/api/_hub/vectorize/[index]/[command].post.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts b/src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts index 78100861..a067c8e3 100644 --- a/src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts +++ b/src/runtime/vectorize/server/api/_hub/vectorize/[index]/[command].post.ts @@ -10,7 +10,7 @@ export default eventHandler(async (event) => { // https://developers.cloudflare.com/vectorize/reference/client-api/ const { index, command } = await getValidatedRouterParams(event, z.object({ - index: z.string().min(1).max(64).regex(/^[a-z-]$/), + index: z.string().min(1).max(64).regex(/^[a-z]+(-[a-z]+)*$/), command: z.enum(['insert', 'upsert', 'query', 'getByIds', 'deleteByIds', 'describe']) }).parse) const vectorize = hubVectorize(index) From 7e704e6e80165764bad5a6eaa4caa9fe7559a546 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Mon, 30 Sep 2024 15:34:42 +0100 Subject: [PATCH 32/53] feat: warn if local dev or if remote vectorize config changed --- src/features.ts | 32 +++++++++++++++++++++++++++++--- src/module.ts | 2 +- 2 files changed, 30 insertions(+), 4 deletions(-) diff --git a/src/features.ts b/src/features.ts index 241fa147..fdd13ea7 100644 --- a/src/features.ts +++ b/src/features.ts @@ -46,8 +46,8 @@ export interface HubConfig { remoteManifest?: { version: string storage: { - [key: string]: boolean - } + vectorize?: HubConfig['vectorize'] + } & Record } } @@ -182,7 +182,33 @@ export function setupKV(_nuxt: Nuxt) { addServerImportsDir(resolve('./runtime/kv/server/utils')) } -export function setupVectorize(_nuxt: Nuxt) { +export function setupVectorize(nuxt: Nuxt, hub: HubConfig) { + if (nuxt.options.dev && !hub.remote) { + log.warn('`hubVectorize()` is disabled: it is currently only supported with `--remote`.') + return + } + + // warn if index configuration has changed compared to deployed version + if (nuxt.options.dev && hub.projectKey) { + $fetch('/api/_hub/manifest', { + baseURL: hub.projectUrl as string, + headers: { + authorization: `Bearer ${hub.projectSecretKey || hub.userToken}` + } + }) + .then((remoteManifest) => { + const localVectorize = hub.vectorize || {} + const remoteVectorize = remoteManifest?.storage.vectorize || {} + Object.keys(localVectorize).forEach((key) => { + const isDimensionsChanged = localVectorize[key].dimensions !== remoteVectorize[key].dimensions + const isMetricChanged = localVectorize[key].metric !== remoteVectorize[key].metric + if (isDimensionsChanged || isMetricChanged) { + log.warn(`Configuration for existing Vectorize index '${key}' has been modified. If deploying, NuxtHub will unlink the old index and create a new index with the new configuration.`) + } + }) + }) + .catch(() => {}) // ignore if fails + } // Add Server scanning addServerScanDir(resolve('./runtime/vectorize/server')) addServerImportsDir(resolve('./runtime/vectorize/server/utils')) diff --git a/src/module.ts b/src/module.ts index 96443919..a84675f2 100644 --- a/src/module.ts +++ b/src/module.ts @@ -109,7 +109,7 @@ export default defineNuxtModule({ hub.cache && setupCache(nuxt) hub.database && setupDatabase(nuxt) hub.kv && setupKV(nuxt) - Object.keys(hub.vectorize).length && setupVectorize(nuxt) + Object.keys(hub.vectorize).length && setupVectorize(nuxt, hub) // nuxt prepare, stop here if (nuxt.options._prepare) { From 29e908b1d82073c1df027db09093f22a5b5386da Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Mon, 30 Sep 2024 15:39:16 +0100 Subject: [PATCH 33/53] style: capitalisation --- src/features.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/features.ts b/src/features.ts index fdd13ea7..a90ed34a 100644 --- a/src/features.ts +++ b/src/features.ts @@ -188,7 +188,7 @@ export function setupVectorize(nuxt: Nuxt, hub: HubConfig) { return } - // warn if index configuration has changed compared to deployed version + // Warn if index configuration has changed compared to deployed version if (nuxt.options.dev && hub.projectKey) { $fetch('/api/_hub/manifest', { baseURL: hub.projectUrl as string, From 5fdec82cc68cd81438aa1abffac0a4ae056a8975 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Mon, 30 Sep 2024 15:59:33 +0100 Subject: [PATCH 34/53] feat: list available remote vectorize indexes --- src/features.ts | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/src/features.ts b/src/features.ts index a90ed34a..f16cadc1 100644 --- a/src/features.ts +++ b/src/features.ts @@ -335,7 +335,14 @@ export async function setupRemote(_nuxt: Nuxt, hub: HubConfig) { const availableStorages = Object.keys(remoteManifest?.storage || {}).filter(k => hub[k as keyof typeof hub] && remoteManifest?.storage[k]) if (availableStorages.length > 0) { - logger.info(`Remote storage available: ${availableStorages.map(k => `\`${k}\``).join(', ')} `) + const storageDescriptions = availableStorages.map((storage) => { + if (storage === 'vectorize' && hub.vectorize) { + const indexes = Object.keys(remoteManifest!.storage.vectorize!).join(', ') + return `\`${storage} (${indexes})\`` + } + return `\`${storage}\`` + }) + logger.info(`Remote storage available: ${storageDescriptions.join(', ')}`) } else { log.fatal('No remote storage available: make sure to enable at least one of the storage options in your `nuxt.config.ts` and deploy new version before using remote storage. Read more at https://hub.nuxt.com/docs/getting-started/remote-storage') process.exit(1) From 10ffe4981badcb5eeb1db90b5d88e059904c91c7 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Mon, 30 Sep 2024 20:12:02 +0100 Subject: [PATCH 35/53] refactor: vectorize manifest check --- src/features.ts | 42 ++++++++++++++++++++---------------------- src/module.ts | 3 ++- 2 files changed, 22 insertions(+), 23 deletions(-) diff --git a/src/features.ts b/src/features.ts index f16cadc1..45abe68c 100644 --- a/src/features.ts +++ b/src/features.ts @@ -1,4 +1,5 @@ import { execSync } from 'node:child_process' +import type { ConsolaInstance } from 'consola' import type { Nuxt } from '@nuxt/schema' import { logger, addImportsDir, addServerImportsDir, addServerScanDir, createResolver } from '@nuxt/kit' import { joinURL } from 'ufo' @@ -187,33 +188,30 @@ export function setupVectorize(nuxt: Nuxt, hub: HubConfig) { log.warn('`hubVectorize()` is disabled: it is currently only supported with `--remote`.') return } - - // Warn if index configuration has changed compared to deployed version - if (nuxt.options.dev && hub.projectKey) { - $fetch('/api/_hub/manifest', { - baseURL: hub.projectUrl as string, - headers: { - authorization: `Bearer ${hub.projectSecretKey || hub.userToken}` - } - }) - .then((remoteManifest) => { - const localVectorize = hub.vectorize || {} - const remoteVectorize = remoteManifest?.storage.vectorize || {} - Object.keys(localVectorize).forEach((key) => { - const isDimensionsChanged = localVectorize[key].dimensions !== remoteVectorize[key].dimensions - const isMetricChanged = localVectorize[key].metric !== remoteVectorize[key].metric - if (isDimensionsChanged || isMetricChanged) { - log.warn(`Configuration for existing Vectorize index '${key}' has been modified. If deploying, NuxtHub will unlink the old index and create a new index with the new configuration.`) - } - }) - }) - .catch(() => {}) // ignore if fails - } // Add Server scanning addServerScanDir(resolve('./runtime/vectorize/server')) addServerImportsDir(resolve('./runtime/vectorize/server/utils')) } +export function vectorizeRemoteCheck(hub: HubConfig, log: ConsolaInstance) { + let isIndexConfigurationChanged = false + const localVectorize = hub.vectorize || {} + const remoteVectorize = hub.remoteManifest?.storage.vectorize || {} + + Object.keys(localVectorize).forEach((key) => { + const isDimensionsChanged = localVectorize[key].dimensions !== remoteVectorize[key].dimensions + const isMetricChanged = localVectorize[key].metric !== remoteVectorize[key].metric + if (isDimensionsChanged || isMetricChanged) { + log.warn(`Vectorize index \`${key}\` configuration changed\nRemote: \`${remoteVectorize[key].dimensions}\` dimensions - \`${remoteVectorize[key].metric}\` metric \nLocal: \`${localVectorize[key].dimensions}\` dimensions - \`${localVectorize[key].metric}\` metric`) + isIndexConfigurationChanged = true + } + }) + + if (isIndexConfigurationChanged) { + log.warn('Modified Vectorize index(es) will be recreated with new configuration on deployment and existing data will not be migrated!') + } +} + export function setupOpenAPI(nuxt: Nuxt) { // Fallback to custom placeholder when openAPI is disabled nuxt.options.alias['#hub/openapi'] = nuxt.options.nitro?.experimental?.openAPI === true diff --git a/src/module.ts b/src/module.ts index a84675f2..2b6e3119 100644 --- a/src/module.ts +++ b/src/module.ts @@ -8,7 +8,7 @@ import { parseArgs } from 'citty' import type { Nuxt } from '@nuxt/schema' import { version } from '../package.json' import { generateWrangler } from './utils/wrangler' -import { setupAI, setupCache, setupAnalytics, setupBlob, setupBrowser, setupOpenAPI, setupDatabase, setupKV, setupVectorize, setupBase, setupRemote } from './features' +import { setupAI, setupCache, setupAnalytics, setupBlob, setupBrowser, setupOpenAPI, setupDatabase, setupKV, setupVectorize, setupBase, setupRemote, vectorizeRemoteCheck } from './features' import type { ModuleOptions } from './types/module' import { addBuildHooks } from './utils/build' @@ -141,6 +141,7 @@ export default defineNuxtModule({ if (hub.remote) { await setupRemote(nuxt, hub) + vectorizeRemoteCheck(hub, log) return } From 34a67e3946875c97210f88211fbba1441f62751c Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Mon, 30 Sep 2024 21:51:01 +0100 Subject: [PATCH 36/53] chore: clean up code --- src/runtime/vectorize/server/utils/vectorize.ts | 1 - 1 file changed, 1 deletion(-) diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts index 7baa2e28..d727599d 100644 --- a/src/runtime/vectorize/server/utils/vectorize.ts +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -30,7 +30,6 @@ type VectorizeIndexes = keyof RuntimeConfig['hub']['vectorize'] & string * @see https://hub.nuxt.com/docs/features/vectorize */ export function hubVectorize(index: VectorizeIndexes): Vectorize { - // todo: autosuggest indexes for hubVectorize based on what's set in nuxt.config.ts.hub.vectorize[index] requireNuxtHubFeature('vectorize') if (_vectorize[index]) { From bb30ac1bedf26e5f4b0419549769912030a609ff Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Tue, 1 Oct 2024 03:54:35 +0100 Subject: [PATCH 37/53] docs: vectorize --- docs/content/1.docs/2.features/vectorize.md | 456 ++++++++++++++++++++ 1 file changed, 456 insertions(+) create mode 100644 docs/content/1.docs/2.features/vectorize.md diff --git a/docs/content/1.docs/2.features/vectorize.md b/docs/content/1.docs/2.features/vectorize.md new file mode 100644 index 00000000..919f14e8 --- /dev/null +++ b/docs/content/1.docs/2.features/vectorize.md @@ -0,0 +1,456 @@ +--- +title: Vectorize (Vector Database) +navigation.title: Vectorize +description: Access a globally distributed vector database to build AI-powered applications in Nuxt. +--- + +::note{to=https://developers.cloudflare.com/vectorize/reference/what-is-a-vector-database/} +Learn what vector databases are on Cloudflare's documentation +:: + +## Getting Started + +Create Vectorize indexes in your NuxtHub project within the `vectorize` property to the `hub` object in your `nuxt.config.ts` file. + +Index names can only contain lowercase characters, hyphens (-), and are limited to 51 characters. + +```ts [nuxt.config.ts] +export default defineNuxtConfig({ + hub: { + vectorize: { + : { + dimensions: , + metric: "dot-product" | "cosine" | "euclidean", + metadataIndexes: { + : "string" | "number" | "boolean" + } + } + } + } +}) +``` + +::collapsible{name="example"} + +```ts [nuxt.config.ts] +export default defineNuxtConfig({ + hub: { + vectorize: { + products: { + metric: 'cosine', + dimensions: '768', + metadataIndexes: { + name: 'string', + price: 'number' + } + }, + reviews: { + metric: 'euclidean', + dimensions: '1024', + metadataIndexes: { + rating: 'number' + } + }, + } + } +}) +``` +:: + +TODO: creating index guide from Vectorize best practises docs + +::note +[Cloudflare Vectorize](https://developers.cloudflare.com/d1) indexes will be created for your project when you [deploy it](/docs/getting-started/deploy). +:: + +::warning +Vectorize is current unavailable during local development. To develop with Vectorize, create an index inside `nuxt.config.ts`, deploy the application and develop using [`nuxt dev --remote`](/docs/getting-started/remote-storage). +:: + +## `hubVectorize()` + +Server composable that returns a [Vectorize index](https://developers.cloudflare.com/vectorize/reference/client-api/). + +```ts +const index = hubVectorize("") +``` + +::callout +This documentation is a small reflection of the [Cloudflare Vectorize documentation](https://developers.cloudflare.com/vectorize/reference/client-api/). We recommend reading it to understand the full potential of Vectorize. +:: + +### `insert()` + +Inserts vectors into the index. + +```ts +const vectorsToInsert = [ + { id: "123", values: [32.4, 6.5, 11.2, 10.3, 87.9] }, + { id: "456", values: [2.5, 7.8, 9.1, 76.9, 8.5] }, +]; +const inserted = await index.insert(vectorsToInsert); +``` + +If vectors with the same vector ID already exist in the index, only the vectors with new IDs will be inserted. + +::callout +Vectorize inserts are asynchronous and the insert operation returns a mutation identifier unique for that operation. It typically takes a few seconds for inserted vectors to be available for querying in an index. +:: + +If you need to update existing vectors, use the [upsert](#upsert) operation. + +::note +**Insert vs Upsert** If the same vector id is inserted twice in a Vectorize index, the index would reflect the vector that was added first. + +If the same vector id is upserted twice in a Vectorize index, the index would reflect the vector that was added second. + +Use the upsert operation if you want to overwrite the vector value for a vector id that already exists in an index. +:: + +### `upsert()` + +Upserts vectors into an index. + +```ts +const vectorsToUpsert = [ + { id: "123", values: [32.4, 6.5, 11.2, 10.3, 87.9] }, + { id: "456", values: [2.5, 7.8, 9.1, 76.9, 8.5] }, + { id: "768", values: [29.1, 5.7, 12.9, 15.4, 1.1] }, +]; +const upserted = await index.upsert(vectorsToUpsert); +``` + +An upsert operation will insert vectors into the index if vectors with the same ID do not exist, and overwrite vectors with the same ID. + +::note +Upserting does not merge or combine the values or metadata of an existing vector with the upserted vector: the upserted vector replaces the existing vector in full. +:: + +::callout +Vectorize upserts are asynchronous and the upsert operation returns a mutation identifier unique for that operation. It typically takes a few seconds for upserted vectors to be available for querying in an index. +:: + +### `query()` + +Query an index with the provided vector, returning the score(s) of the closest vectors based on the configured distance metric. + +```ts +const queryVector = [32.4, 6.55, 11.2, 10.3, 87.9]; +const matches = await index.query(queryVector); + +console.log(matches) +/* +[] +*/ +``` + +- Configure the number of returned matches by setting `topK` (default: 5) +- Return vector values by setting `returnValues: true` (default: false) +- Return vector metadata by setting `returnMetadata: 'indexed'` or `returnMetadata: 'all'` (default: 'none') + +```ts +const matches = await index.query(queryVector, { + topK: 5, + returnValues: true, + returnMetadata: "all", +}); +``` + +#### topK + +The `topK` can be configured to specify the number of matches returned by the query operation. Vectorize now supports an upper limit of `100` for the `topK` value. However, for a query operation with `returnValues` set to `true` or `returnMetadata` set to `all`, `topK` would be limited to a maximum value of `20`. + +#### returnMetadata + +The `returnMetadata` field provides three ways to fetch vector metadata while querying: + +1. `none`: Do not fetch metadata. +2. `indexed`: Fetched metadata only for the indexed metadata fields. There is no latency overhead with this option, but long text fields may be truncated. +3. `all`: Fetch all metadata associated with a vector. Queries may run slower with this option, and `topK` would be limited to 20. + +### `getByIds()` + +Retrieves the specified vectors by their ID, including values and metadata. + +```ts +const ids = ["11", "22", "33", "44"]; +const vectors = await index.getByIds(ids); +``` + +### `deleteByIds()` + +Deletes the vector IDs provided from the current index. + +```ts +const idsToDelete = ["11", "22", "33", "44"]; +const deleted = await index.deleteByIds(idsToDelete); +``` + +::callout +Vectorize deletes are asynchronous and the delete operation returns a mutation identifier unique for that operation. It typically takes a few seconds for vectors to be removed from the Vectorize index. +:: + +### `describe()` + +Retrieves the configuration of a given index directly, including its configured `dimensions` and distance `metric`. + +```ts +const details = await index.describe(); +``` + +## Vectors + +A vector represents the vector embedding output from a machine learning model. + +- `id` - a unique `string` identifying the vector in the index. This should map back to the ID of the document, object or database identifier that the vector values were generated from. +- `namespace` - an optional partition key within a index. Operations are performed per-namespace, so this can be used to create isolated segments within a larger index. +- `values` - an array of `number`, `Float32Array`, or `Float64Array` as the vector embedding itself. This must be a dense array, and the length of this array must match the `dimensions` configured on the index. +- `metadata` - an optional set of key-value pairs that can be used to store additional metadata alongside a vector. + +```ts +let vectorExample = { + id: "12345", + values: [32.4, 6.55, 11.2, 10.3, 87.9], + metadata: { + key: "value", + hello: "world", + url: "r2://bucket/some/object.json", + }, +}; +``` + +## Metadata filtering + +::callout +Vectorize currently supports a maximum of 10 metadata indexes per Vectorize index. Learn more at https://developers.cloudflare.com/vectorize/platform/limits/. +:: + +::note[Enable metadata filtering] +Vectorize requires metadata indexes to be specified before vectors are inserted to support metadata filtering. `string`, `number` and `boolean` metadata indexes are supported. Please refer to [Create metadata indexes](https://developers.cloudflare.com/vectorize/get-started/intro/#4-optional-create-metadata-indexes) for details. + +Vectorize supports [namespace](https://developers.cloudflare.com/vectorize/best-practices/insert-vectors/#namespaces) filtering by default. +:: + +In addition to providing an input vector to your query, you can also filter by [vector metadata](https://developers.cloudflare.com/vectorize/best-practices/insert-vectors/#metadata) associated with every vector. Query results only include vectors that match `filter` criteria, meaning that `filter` is applied first, and `topK` results are taken from the filtered set. + +By using metadata filtering to limit the scope of a query, you can filter by specific customer IDs, tenant, product category or any other metadata you associate with your vectors. + +### Limits + +You can store up to 10KiB of metadata per vector, and create up to 10 metadata indexes per Vectorize index. + +For metadata indexes of type `number`, the indexed number precision is that of float64. + +For metadata indexes of type `string`, each vector indexes the first 64B of the string data truncated on UTF-8 character boundaries to the longest well-formed UTF-8 substring within that limit, so vectors are filterable on the first 64B of their value for each indexed property. + +See [Vectorize Limits](https://developers.cloudflare.com/vectorize/platform/limits/) for a complete list of limits. + +### Supported operations + +Optional `filter` property on `query()` method specifies metadata filter: + +| Operator | Description | +| -------- | ----------- | +| `$eq` | Equals | +| `$ne` | Not equals | + +- `filter` must be non-empty object whose compact JSON representation must be less than 2048 bytes. +- `filter` object keys cannot be empty, contain `" | .` (dot is reserved for nesting), start with `$`, or be longer than 512 characters. +- `filter` object non-nested values can be `string`, `number`, `boolean`, or `null` values. + +#### Namespace versus metadata filtering + +Both [namespaces](https://developers.cloudflare.com/vectorize/best-practices/insert-vectors/#namespaces) and metadata filtering narrow the vector search space for a query. Consider the following when evaluating both filter types: + +- A namespace filter is applied before metadata filter(s). +- A vector can only be part of a single namespace with the documented [limits](https://developers.cloudflare.com/vectorize/platform/limits/). Vector metadata can contain multiple key-value pairs up to [metadata per vector limits](https://developers.cloudflare.com/vectorize/platform/limits/). Metadata values support different types (`string`, `boolean`, and others), therefore offering more flexibility. + +#### Valid `filter` examples + +##### Implicit `$eq` operator + +```json +{ "streaming_platform": "netflix" } +``` + +##### Explicit operator + +```json +{ "someKey": { "$ne": true } } +``` + +##### Implicit logical `AND` with multiple keys + +```json +{ "pandas.nice": 42, "someKey": { "$ne": true } } +``` + +##### Keys define nesting with `.` (dot) + +```json +{ "pandas.nice": 42 } + +// looks for { "pandas": { "nice": 42 } } +``` + +### Examples + +#### Add metadata + +With the following index definition: + +```ts [nuxt.config.ts] +export default defineNuxtConfig({ + hub: { + vectorize: { + tutorial: { + dimensions: 32, + metric: "cosine", + metadataIndexes: { + streaming_platform: "string" + } + } + } + } +}) +``` + +Metadata can be added when [inserting or upserting vectors](#insert). + +```ts +const index = hubVectorize("tutorial") + +const newMetadataVectors: Array = [ + { + id: "1", + values: [32.4, 74.1, 3.2, ...], + metadata: { url: "/products/sku/13913913", streaming_platform: "netflix" }, + }, + { + id: "2", + values: [15.1, 19.2, 15.8, ...], + metadata: { url: "/products/sku/10148191", streaming_platform: "hbo" }, + }, + { + id: "3", + values: [0.16, 1.2, 3.8, ...], + metadata: { url: "/products/sku/97913813", streaming_platform: "amazon" }, + }, + { + id: "4", + values: [75.1, 67.1, 29.9, ...], + metadata: { url: "/products/sku/418313", streaming_platform: "netflix" }, + }, + { + id: "5", + values: [58.8, 6.7, 3.4, ...], + metadata: { url: "/products/sku/55519183", streaming_platform: "hbo" }, + }, +]; + +// Upsert vectors with added metadata, returning a count of the vectors upserted and their vector IDs +let upserted = await index.upsert(newMetadataVectors); +``` + +#### Query examples + +Use the `query()` method: + +```ts +let queryVector: Array = [54.8, 5.5, 3.1, ...]; +let originalMatches = await index.query(queryVector, { + topK: 3, + returnValues: true, + returnMetadata: 'all', +}); +``` + +Results without metadata filtering: + +```json +{ + "matches": [ + { + "id": "5", + "score": 0.999909486, + "values": [58.79999923706055, 6.699999809265137, 3.4000000953674316], + "metadata": { + "url": "/products/sku/55519183", + "streaming_platform": "hbo" + } + }, + { + "id": "4", + "score": 0.789848214, + "values": [75.0999984741211, 67.0999984741211, 29.899999618530273], + "metadata": { + "url": "/products/sku/418313", + "streaming_platform": "netflix" + } + }, + { + "id": "2", + "score": 0.611976262, + "values": [15.100000381469727, 19.200000762939453, 15.800000190734863], + "metadata": { + "url": "/products/sku/10148191", + "streaming_platform": "hbo" + } + } + ] +} +``` + +The same `query()` method with a `filter` property supports metadata filtering. + +```ts +let queryVector: Array = [54.8, 5.5, 3.1, ...]; +let metadataMatches = await index.query(queryVector, { + topK: 3, + filter: { streaming_platform: "netflix" }, + returnValues: true, + returnMetadata: 'all', +}); +``` + +Results with metadata filtering: + +```json +{ + "matches": [ + { + "id": "4", + "score": 0.789848214, + "values": [75.0999984741211, 67.0999984741211, 29.899999618530273], + "metadata": { + "url": "/products/sku/418313", + "streaming_platform": "netflix" + } + }, + { + "id": "1", + "score": 0.491185264, + "values": [32.400001525878906, 74.0999984741211, 3.200000047683716], + "metadata": { + "url": "/products/sku/13913913", + "streaming_platform": "netflix" + } + } + ] +} +``` + +### Limitations + +- As of now, metadata indexes need to be created for Vectorize indexes _before_ vectors can be inserted to support metadata filtering. +- Only indexes created on or after 2023-12-06 support metadata filtering. Previously created indexes cannot be migrated to support metadata filtering. + +## Read more + +::callout +Read more on [Cloudflare Vectorize documentation](https://developers.cloudflare.com/vectorize/reference/client-api/). +:: + +::callout{to=https://developers.cloudflare.com/reference-architecture/diagrams/ai/ai-rag/} +[Retrieval Augmented Generation (RAG)](https://developers.cloudflare.com/reference-architecture/diagrams/ai/ai-rag/): Retrieval-Augmented Generation (RAG) is an innovative approach in natural language processing that integrates retrieval mechanisms with generative models to enhance text generation. +:: From 11c441862719363ddfe06697183932f660d5c7f7 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Tue, 1 Oct 2024 17:16:15 +0100 Subject: [PATCH 38/53] docs: add vectorize pricing --- docs/content/3.pricing.yml | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/docs/content/3.pricing.yml b/docs/content/3.pricing.yml index 27e60493..328f0782 100644 --- a/docs/content/3.pricing.yml +++ b/docs/content/3.pricing.yml @@ -222,6 +222,25 @@ cloudflare: - title: 'Neurons' free: '10,000 / day' paid: '10,000 / day + $0.011/1,000 neurons' + - label: 'Vectorize' + icon: i-ph-circles-three-fill + buttons: + - label: 'Cloudflare Vectorize pricing' + to: 'https://developers.cloudflare.com/vectorize/platform/pricing/' + columns: + - key: 'title' + label: '' + - key: 'free' + label: 'Free Tier' + - key: 'paid' + label: 'Pricing' + rows: + - title: 'Queried vector dimensions' + free: '30 million / month' + paid: '50 million / month + $0.01/million' + - title: 'Stored vector dimensions' + free: '5 million / month' + paid: '10 million / month + $0.05/100 million' button: label: 'Discover Cloudflare pricing' external: true From a5f3068a34fb16d60322d5537482ccf34d2c6db1 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Thu, 3 Oct 2024 13:12:18 +0100 Subject: [PATCH 39/53] docs: include free writes on docs --- docs/content/3.pricing.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docs/content/3.pricing.yml b/docs/content/3.pricing.yml index 328f0782..376ae16a 100644 --- a/docs/content/3.pricing.yml +++ b/docs/content/3.pricing.yml @@ -235,6 +235,9 @@ cloudflare: - key: 'paid' label: 'Pricing' rows: + - title: 'Writes' + free: 'Free' + paid: 'Free' - title: 'Queried vector dimensions' free: '30 million / month' paid: '50 million / month + $0.01/million' From 44100b15657e24ea6a61d9dcad23b8ce564e1b1b Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Thu, 3 Oct 2024 18:15:32 +0100 Subject: [PATCH 40/53] feat: vectorize playground --- playground/nuxt.config.ts | 8 +++++++- playground/server/api/vectorize/index.get.ts | 7 +++++++ playground/server/api/vectorize/index.post.ts | 7 +++++++ 3 files changed, 21 insertions(+), 1 deletion(-) create mode 100644 playground/server/api/vectorize/index.get.ts create mode 100644 playground/server/api/vectorize/index.post.ts diff --git a/playground/nuxt.config.ts b/playground/nuxt.config.ts index 71b46739..b9856aaf 100644 --- a/playground/nuxt.config.ts +++ b/playground/nuxt.config.ts @@ -19,7 +19,13 @@ export default defineNuxtConfig({ browser: true, kv: true, cache: true, - vectorize: true, + vectorize: { + example: { + metric: 'cosine', + dimensions: 768, + metadataIndexes: { name: 'string', price: 'number' } + } + }, bindings: { // compatibilityFlags: ['nodejs_compat_v2'] // Used for /api/hyperdrive diff --git a/playground/server/api/vectorize/index.get.ts b/playground/server/api/vectorize/index.get.ts new file mode 100644 index 00000000..fa50ec19 --- /dev/null +++ b/playground/server/api/vectorize/index.get.ts @@ -0,0 +1,7 @@ +export default eventHandler(async (event) => { + const { query } = await getValidatedQuery(event, z.object({ + query: z.array(z.number()) + }).parse) + const index = hubVectorize('example') + return index.query(query) +}) diff --git a/playground/server/api/vectorize/index.post.ts b/playground/server/api/vectorize/index.post.ts new file mode 100644 index 00000000..585cfd80 --- /dev/null +++ b/playground/server/api/vectorize/index.post.ts @@ -0,0 +1,7 @@ +export default eventHandler(async (event) => { + const { query } = await readValidatedBody(event, z.object({ + query: z.array(z.number()) + }).parse) + const index = hubVectorize('example') + return index.query(query) +}) From dbbfd9de15f1574d35b0b3d9b7838e345814137c Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Fri, 4 Oct 2024 03:34:59 +0100 Subject: [PATCH 41/53] docs: improve vectorize docs --- docs/content/1.docs/2.features/vectorize.md | 502 +++++++++++++++++--- 1 file changed, 432 insertions(+), 70 deletions(-) diff --git a/docs/content/1.docs/2.features/vectorize.md b/docs/content/1.docs/2.features/vectorize.md index 919f14e8..cbb64432 100644 --- a/docs/content/1.docs/2.features/vectorize.md +++ b/docs/content/1.docs/2.features/vectorize.md @@ -1,18 +1,20 @@ --- title: Vectorize (Vector Database) navigation.title: Vectorize -description: Access a globally distributed vector database to build AI-powered applications in Nuxt. +description: Access a vector database to build full-stack AI-powered applications in Nuxt. --- ::note{to=https://developers.cloudflare.com/vectorize/reference/what-is-a-vector-database/} Learn what vector databases are on Cloudflare's documentation :: -## Getting Started +::warning +Vectorize is current unavailable during local development. To develop with Vectorize, create an index inside `nuxt.config.ts`, deploy the application and develop using [`nuxt dev --remot#e`](/docs/getting-started/remote-storage). +:: -Create Vectorize indexes in your NuxtHub project within the `vectorize` property to the `hub` object in your `nuxt.config.ts` file. +## Getting Started -Index names can only contain lowercase characters, hyphens (-), and are limited to 51 characters. +Vectorize indexes are managed in your NuxtHub project within the `hub.vectorize` object in your `nuxt.config.ts` file. Multiple indexes can be created using separate keys. ```ts [nuxt.config.ts] export default defineNuxtConfig({ @@ -37,16 +39,16 @@ export default defineNuxtConfig({ hub: { vectorize: { products: { - metric: 'cosine', dimensions: '768', + metric: 'cosine', metadataIndexes: { name: 'string', price: 'number' } }, reviews: { - metric: 'euclidean', dimensions: '1024', + metric: 'euclidean', metadataIndexes: { rating: 'number' } @@ -57,14 +59,42 @@ export default defineNuxtConfig({ ``` :: -TODO: creating index guide from Vectorize best practises docs +::caution +Cloudflare Vectorize index configurations cannot be changed after creation. Therefore, changing an index's dimension size or distance metric will result in modified existing indexes being disconnected from your Pages project, and a new index being created. Existing data will not be migrated. +:: + + +### Create an index + +Creating an index requires three inputs: + +- A name, for example prod-search-index or recommendations-idx-dev. +- The (fixed) [dimension size](#dimensions) of each vector, for example 384 or 1536. +- The (fixed) [distance metric](#distance-metrics) to use for calculating vector similarity. + +::callout +Index names can only contain lowercase characters, hyphens (-), and are limited to 51 characters. +:: ::note -[Cloudflare Vectorize](https://developers.cloudflare.com/d1) indexes will be created for your project when you [deploy it](/docs/getting-started/deploy). +[Cloudflare Vectorize](https://developers.cloudflare.com/vectorize) indexes will be created for your project when you [deploy it](/docs/getting-started/deploy). Created Vectorize indexes contain a unique 4 character suffix. :: -::warning -Vectorize is current unavailable during local development. To develop with Vectorize, create an index inside `nuxt.config.ts`, deploy the application and develop using [`nuxt dev --remote`](/docs/getting-started/remote-storage). +### Use existing indexes + +1. On the Cloudflare dashboard → Workers & Pages → Your Pages project +2. Go to Settings → Bindings → Add +3. Select Vectorize database + - Set the variable name to `VECTORIZE_`. The entire variable name should be capitalised. + - Select the existing Vectorize index +4. Add the index configuration to `hub.vectorize` in `nuxt.config.ts`. The name should match `` used in the variable name, and be lowercase. + +### Creating metadata indexes + +Vectorize allows you to add up to 10KiB of metadata per vector into your index, and also provides the ability to filter on that metadata while querying vectors. To do so you would need to specify a metadata field as a "metadata index" for your Vectorize index. + +::callout{to="#create-metadata-indexes"} +Learn more about [creating metadata indexes](#metadata-filtering). :: ## `hubVectorize()` @@ -75,9 +105,7 @@ Server composable that returns a [Vectorize index](https://developers.cloudflare const index = hubVectorize("") ``` -::callout -This documentation is a small reflection of the [Cloudflare Vectorize documentation](https://developers.cloudflare.com/vectorize/reference/client-api/). We recommend reading it to understand the full potential of Vectorize. -:: +IntelliSense will suggest `` based on the indexes configured in [`hub.vectorize`](#getting-started). ### `insert()` @@ -91,6 +119,8 @@ const vectorsToInsert = [ const inserted = await index.insert(vectorsToInsert); ``` +See all available properties on the [Vector object](#vector-object). + If vectors with the same vector ID already exist in the index, only the vectors with new IDs will be inserted. ::callout @@ -100,12 +130,15 @@ Vectorize inserts are asynchronous and the insert operation returns a mutation i If you need to update existing vectors, use the [upsert](#upsert) operation. ::note -**Insert vs Upsert** If the same vector id is inserted twice in a Vectorize index, the index would reflect the vector that was added first. +Insert vs Upsert +- If the same vector id is inserted twice in a Vectorize index, the index would reflect the vector that was added first. +- If the same vector id is upserted twice in a Vectorize index, the index would reflect the vector that was added second. +- Use the upsert operation if you want to overwrite the vector value for a vector id that already exists in an index. +:: -If the same vector id is upserted twice in a Vectorize index, the index would reflect the vector that was added second. +#### Return -Use the upsert operation if you want to overwrite the vector value for a vector id that already exists in an index. -:: +Returns [`VectorizeAsyncMutation`](#vectorizeasyncmutation). ### `upsert()` @@ -122,6 +155,8 @@ const upserted = await index.upsert(vectorsToUpsert); An upsert operation will insert vectors into the index if vectors with the same ID do not exist, and overwrite vectors with the same ID. +See all available properties on the [Vector object](#vector-object). + ::note Upserting does not merge or combine the values or metadata of an existing vector with the upserted vector: the upserted vector replaces the existing vector in full. :: @@ -130,6 +165,10 @@ Upserting does not merge or combine the values or metadata of an existing vector Vectorize upserts are asynchronous and the upsert operation returns a mutation identifier unique for that operation. It typically takes a few seconds for upserted vectors to be available for querying in an index. :: +#### Return + +Returns [`VectorizeAsyncMutation`](#vectorizeasyncmutation). + ### `query()` Query an index with the provided vector, returning the score(s) of the closest vectors based on the configured distance metric. @@ -140,13 +179,63 @@ const matches = await index.query(queryVector); console.log(matches) /* -[] +{ + "count": 5, + "matches": [ + { "score": 0.999909486, "id": "5" }, + { "score": 0.789848214, "id": "4" }, + { "score": 0.720476967, "id": "1234" }, + { "score": 0.463884663, "id": "6" }, + { "score": 0.378282232, "id": "1" } + ] +} */ ``` -- Configure the number of returned matches by setting `topK` (default: 5) -- Return vector values by setting `returnValues: true` (default: false) -- Return vector metadata by setting `returnMetadata: 'indexed'` or `returnMetadata: 'all'` (default: 'none') +Querying an index, or vector search, enables you to search an index by providing an input vector and returning the nearest vectors based on the [configured distance metric](#distance-metrics). + +Optionally, you can apply [metadata filters](#metadata--filtering) or a [namespace](#namespaces) to narrow the vector search space. + +#### Params + +::field-group + ::field{name="vector" type="array" required} + Input vector that will be used to drive the similarity search. + :: + + ::field{name="options" type="object"} + Query options. + ::collapsible + ::field{name="topK" type="number"} + Number of returned matches. Defaults to `5`. + + The `topK` can be configured to specify the number of matches returned by the query operation. Vectorize now supports an upper limit of `100` for the `topK` value. However, for a query operation with `returnValues` set to `true` or `returnMetadata` set to `all`, `topK` would be limited to a maximum value of `20`. + +
+ :: + ::field{name="returnValues" type="boolean"} + Return vector values. See [control over scoring precision and query accuracy](#control-over-scoring-precision-and-query-accuracy). + :: + ::field{name="returnMetadata" type="'all' | 'indexed' | 'none'"} + Return vector metadata. Defaults to `'none'`. + + The `returnMetadata` field provides three ways to fetch vector metadata while querying: + + 1. `none`: Do not fetch metadata. + 2. `indexed`: Fetched metadata only for the indexed metadata fields. There is no latency overhead with this option, but long text fields may be truncated. + 3. `all`: Fetch all metadata associated with a vector. Queries may run slower with this option, and `topK` would be limited to 20. + +
+ :: + ::field{name="namespace" type="string"} + Only return vectors within a namespace. + :: + ::field{name="filter" type="object"} + Filter by vector metadata. See [metadata filtering](#metadata-filtering) + :: + :: + :: +:: ```ts const matches = await index.query(queryVector, { @@ -156,17 +245,16 @@ const matches = await index.query(queryVector, { }); ``` -#### topK +#### Return -The `topK` can be configured to specify the number of matches returned by the query operation. Vectorize now supports an upper limit of `100` for the `topK` value. However, for a query operation with `returnValues` set to `true` or `returnMetadata` set to `all`, `topK` would be limited to a maximum value of `20`. +Returns [`VectorizeMatches`](#vectorizematches). -#### returnMetadata +#### Control over scoring precision and query accuracy -The `returnMetadata` field provides three ways to fetch vector metadata while querying: +When querying vectors, you can specify to either use high-precision scoring, thereby increasing the precision of the query matches scores as well as the accuracy of the query results, or use approximate scoring for faster response times. +Using approximate scoring, returned scores will be an approximation of the real distance/similarity between your query and the returned vectors. -1. `none`: Do not fetch metadata. -2. `indexed`: Fetched metadata only for the indexed metadata fields. There is no latency overhead with this option, but long text fields may be truncated. -3. `all`: Fetch all metadata associated with a vector. Queries may run slower with this option, and `topK` would be limited to 20. +High-precision scoring is enabled by setting `returnValues: true` on your query; this tells Vectorize to fetch and use the original vector values for your matches, which enables the computation of exact scores of matches, increasing the accuracy of the results. ### `getByIds()` @@ -177,6 +265,18 @@ const ids = ["11", "22", "33", "44"]; const vectors = await index.getByIds(ids); ``` +#### Params + +::field-group + ::field{name="ids" type="string[]" required} + List of vector ids that should be returned. + :: +:: + +#### Return + +Returns [`VectorizeVector`](#vectorizevector). + ### `deleteByIds()` Deletes the vector IDs provided from the current index. @@ -190,6 +290,18 @@ const deleted = await index.deleteByIds(idsToDelete); Vectorize deletes are asynchronous and the delete operation returns a mutation identifier unique for that operation. It typically takes a few seconds for vectors to be removed from the Vectorize index. :: +#### Params + +::field-group + ::field{name="ids" type="string[]" required} + List of vector ids that should be deleted. + :: +:: + +#### Return + +Returns [`VectorizeAsyncMutation`](#vectorizeasyncmutation). + ### `describe()` Retrieves the configuration of a given index directly, including its configured `dimensions` and distance `metric`. @@ -198,17 +310,37 @@ Retrieves the configuration of a given index directly, including its configured const details = await index.describe(); ``` +#### Return + +Returns [`VectorizeIndexDetails`](#vectorizeindexdetails). + ## Vectors + +### Vector Object + A vector represents the vector embedding output from a machine learning model. -- `id` - a unique `string` identifying the vector in the index. This should map back to the ID of the document, object or database identifier that the vector values were generated from. -- `namespace` - an optional partition key within a index. Operations are performed per-namespace, so this can be used to create isolated segments within a larger index. -- `values` - an array of `number`, `Float32Array`, or `Float64Array` as the vector embedding itself. This must be a dense array, and the length of this array must match the `dimensions` configured on the index. -- `metadata` - an optional set of key-value pairs that can be used to store additional metadata alongside a vector. +::field-group + ::field{name="id" type="string" required} + A unique `string` identifying the vector in the index. This should map back to the ID of the document, object or database identifier that the vector values were generated from. + :: + + ::field{name="namespace" type="object"} + An optional partition key within a index. Operations are performed per-namespace, so this can be used to create isolated segments within a larger index. + :: + + ::field{name="values" type="number[] | Float32Array | Float64Array" required} + An array of `number`, `Float32Array`, or `Float64Array` as the vector embedding itself. This must be a dense array, and the length of this array must match the `dimensions` configured on the index. + :: + + ::field{name="metadata" type="Record"} + An optional set of key-value pairs that can be used to store additional metadata alongside a vector. + :: +:: ```ts -let vectorExample = { +const vectorExample = { id: "12345", values: [32.4, 6.55, 11.2, 10.3, 87.9], metadata: { @@ -219,31 +351,125 @@ let vectorExample = { }; ``` -## Metadata filtering +### Dimensions -::callout -Vectorize currently supports a maximum of 10 metadata indexes per Vectorize index. Learn more at https://developers.cloudflare.com/vectorize/platform/limits/. +Dimensions are determined from the output size of the machine learning (ML) model used to generate them, and are a function of how the model encodes and describes features into a vector embedding. + +The number of output dimensions can determine vector search accuracy, search performance (latency), and the overall size of the index. Smaller output dimensions can be faster to search across, which can be useful for user-facing applications. Larger output dimensions can provide more accurate search, especially over larger datasets and/or datasets with substantially similar inputs. + +The number of dimensions an index is created for cannot change. Indexes expect to receive dense vectors with the same number of dimensions. + +The following table highlights some example embeddings models and their output dimensions: + +| Model / Embeddings API | Output dimensions | Use-case | +| ---------------------------------------- | ----------------- | -------------------------- | +| Workers AI - `@cf/baai/bge-base-en-v1.5` | 768 | Text | +| OpenAI - `ada-002` | 1536 | Text | +| Cohere - `embed-multilingual-v2.0` | 768 | Text | +| Google Cloud - `multimodalembedding` | 1408 | Multi-modal (text, images) | + +::note +Refer to the [Workers AI documentation](https://developers.cloudflare.com/workers-ai/models/#text-embeddings) to learn about its built-in embedding models. :: -::note[Enable metadata filtering] -Vectorize requires metadata indexes to be specified before vectors are inserted to support metadata filtering. `string`, `number` and `boolean` metadata indexes are supported. Please refer to [Create metadata indexes](https://developers.cloudflare.com/vectorize/get-started/intro/#4-optional-create-metadata-indexes) for details. +### Distance metrics + +Distance metrics are functions that determine how close vectors are from each other. Vectorize indexes support the following distance metrics: + +| Metric | Details | +| ------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `cosine` | Distance is measured between `-1` (most dissimilar) to `1` (identical). `0` denotes an orthogonal vector. | +| `euclidean` | Euclidean (L2) distance. `0` denotes identical vectors. The larger the positive number, the further the vectors are apart. | +| `dot-product` | Negative dot product. Larger negative values _or_ smaller positive values denote more similar vectors. A score of `-1000` is more similar than `-500`, and a score of `15` more similar than `50`. | -Vectorize supports [namespace](https://developers.cloudflare.com/vectorize/best-practices/insert-vectors/#namespaces) filtering by default. +Determining the similarity between vectors can be subjective based on how the machine-learning model that represents features in the resulting vector embeddings. For example, a score of `0.8511` when using a `cosine` metric means that two vectors are close in distance, but whether data they represent is _similar_ is a function of how well the model is able to represent the original content. + +When querying vectors, you can specify Vectorize to use either: + +- High-precision scoring, which increases the precision of the query matches scores as well as the accuracy of the query results. +- Approximate scoring for faster response times. Using approximate scoring, returned scores will be an approximation of the real distance/similarity between your query and the returned vectors. Refer to [Control over scoring precision and query accuracy](/vectorize/best-practices/query-vectors/#control-over-scoring-precision-and-query-accuracy). + +Distance metrics cannot be changed after index creation, and that each metric has a different scoring function. + +### Supported vector formats + +Vectorize supports vectors in three formats: + +- An array of floating point numbers (converted into a JavaScript `number[]` array). +- A [Float32Array](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float32Array) +- A [Float64Array](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float64Array) + +In most cases, a `number[]` array is the easiest when dealing with other APIs, and is the return type of most machine-learning APIs. + +## Metadata & filtering + +Metadata is an optional set of key-value pairs that can be attached to a vector on insert or upsert, and allows you to embed or co-locate data about the vector itself. + +::callout +Metadata keys cannot be empty, contain the dot character (`.`), contain the double-quote character (`"`), or start with the dollar character (`$`). :: -In addition to providing an input vector to your query, you can also filter by [vector metadata](https://developers.cloudflare.com/vectorize/best-practices/insert-vectors/#metadata) associated with every vector. Query results only include vectors that match `filter` criteria, meaning that `filter` is applied first, and `topK` results are taken from the filtered set. +Metadata can be used to: + +- Include the object storage key, database UUID or other identifier to look up the content the vector embedding represents. +- The raw content (up to the [metadata limits](/vectorize/platform/limits/)), which can allow you to skip additional lookups for smaller content. +- Dates, timestamps, or other metadata that describes when the vector embedding was generated or how it was generated. + +For example, a vector embedding representing an image could include the path to the [R2 object](/r2/) it was generated from, the format, and a category lookup: + +```ts +{ id: '1', values: [32.4, 74.1, 3.2, ...], metadata: { path: 'r2://bucket-name/path/to/image.png', format: 'png', category: 'profile_image' } } +``` + +### Metadata filtering + +In addition to providing an input vector to your query, you can also filter by [vector metadata](#metadata) associated with every vector. Query results only include vectors that match `filter` criteria, meaning that `filter` is applied first, and `topK` results are taken from the filtered set. By using metadata filtering to limit the scope of a query, you can filter by specific customer IDs, tenant, product category or any other metadata you associate with your vectors. -### Limits +::warning +Vectorize requires metadata indexes to be specified before vectors are inserted to support metadata filtering. `string`, `number` and `boolean` metadata indexes are supported. Please refer to [Create metadata indexes](#create-metadata-indexes) for details.

-You can store up to 10KiB of metadata per vector, and create up to 10 metadata indexes per Vectorize index. +Vectorize supports [namespace](#namespaces) filtering by default. +:: -For metadata indexes of type `number`, the indexed number precision is that of float64. +### Create metadata indexes -For metadata indexes of type `string`, each vector indexes the first 64B of the string data truncated on UTF-8 character boundaries to the longest well-formed UTF-8 substring within that limit, so vectors are filterable on the first 64B of their value for each indexed property. +Metadata indexes are all managed within the `metadataIndexes` object within your index configuration in `nuxt.config.ts`. -See [Vectorize Limits](https://developers.cloudflare.com/vectorize/platform/limits/) for a complete list of limits. +```ts [nuxt.config.ts] +export default defineNuxtConfig({ + hub: { + vectorize: { + tutorial: { + dimensions: 32, + metric: "cosine", + metadataIndexes: { + // : "string" | "number" | "boolean" + url: "string", + "nested.property": "boolean" + } + } + } + } +}) +``` + +Supported metadata index property types are `string`, `number` and `boolean` types. + +Define nested properties using `.` (dot). + +::callout +Vectorize currently supports a maximum of 10 metadata indexes per Vectorize index. Learn more at https://developers.cloudflare.com/vectorize/platform/limits/. +:: + +For metadata indexes of type number, the indexed number precision is that of float64. + +For metadata indexes of type string, each vector indexes the first 64B of the string data truncated on UTF-8 character boundaries to the longest well-formed UTF-8 substring within that limit, so vectors are filterable on the first 64B of their value for each indexed property. + +::note +As of today, the metadata fields on which vectors can be filtered need to be specified before the vectors are inserted, and it is recommended that these metadata fields are specified right after the creation of a Vectorize index. +:: ### Supported operations @@ -258,13 +484,6 @@ Optional `filter` property on `query()` method specifies metadata filter: - `filter` object keys cannot be empty, contain `" | .` (dot is reserved for nesting), start with `$`, or be longer than 512 characters. - `filter` object non-nested values can be `string`, `number`, `boolean`, or `null` values. -#### Namespace versus metadata filtering - -Both [namespaces](https://developers.cloudflare.com/vectorize/best-practices/insert-vectors/#namespaces) and metadata filtering narrow the vector search space for a query. Consider the following when evaluating both filter types: - -- A namespace filter is applied before metadata filter(s). -- A vector can only be part of a single namespace with the documented [limits](https://developers.cloudflare.com/vectorize/platform/limits/). Vector metadata can contain multiple key-value pairs up to [metadata per vector limits](https://developers.cloudflare.com/vectorize/platform/limits/). Metadata values support different types (`string`, `boolean`, and others), therefore offering more flexibility. - #### Valid `filter` examples ##### Implicit `$eq` operator @@ -293,6 +512,16 @@ Both [namespaces](https://developers.cloudflare.com/vectorize/best-practices/ins // looks for { "pandas": { "nice": 42 } } ``` +### Limits + +You can store up to 10KiB of metadata per vector, and create up to 10 metadata indexes per Vectorize index. + +For metadata indexes of type `number`, the indexed number precision is that of float64. + +For metadata indexes of type `string`, each vector indexes the first 64B of the string data truncated on UTF-8 character boundaries to the longest well-formed UTF-8 substring within that limit, so vectors are filterable on the first 64B of their value for each indexed property. + +See [Vectorize Limits](https://developers.cloudflare.com/vectorize/platform/limits/) for a complete list of limits. + ### Examples #### Add metadata @@ -307,7 +536,8 @@ export default defineNuxtConfig({ dimensions: 32, metric: "cosine", metadataIndexes: { - streaming_platform: "string" + streaming_platform: "string", + "property.nested": "boolean" } } } @@ -349,16 +579,16 @@ const newMetadataVectors: Array = [ ]; // Upsert vectors with added metadata, returning a count of the vectors upserted and their vector IDs -let upserted = await index.upsert(newMetadataVectors); +const upserted = await index.upsert(newMetadataVectors); ``` #### Query examples -Use the `query()` method: +Use the [`query()`](#query) method: ```ts -let queryVector: Array = [54.8, 5.5, 3.1, ...]; -let originalMatches = await index.query(queryVector, { +const queryVector: Array = [54.8, 5.5, 3.1, ...]; +const originalMatches = await index.query(queryVector, { topK: 3, returnValues: true, returnMetadata: 'all', @@ -401,11 +631,11 @@ Results without metadata filtering: } ``` -The same `query()` method with a `filter` property supports metadata filtering. +The same [`query()`](#query) method with a `filter` property supports metadata filtering. ```ts -let queryVector: Array = [54.8, 5.5, 3.1, ...]; -let metadataMatches = await index.query(queryVector, { +const queryVector: Array = [54.8, 5.5, 3.1, ...]; +const metadataMatches = await index.query(queryVector, { topK: 3, filter: { streaming_platform: "netflix" }, returnValues: true, @@ -440,17 +670,149 @@ Results with metadata filtering: } ``` -### Limitations +## Namespaces -- As of now, metadata indexes need to be created for Vectorize indexes _before_ vectors can be inserted to support metadata filtering. -- Only indexes created on or after 2023-12-06 support metadata filtering. Previously created indexes cannot be migrated to support metadata filtering. +Namespaces provide a way to segment the vectors within your index. For example, by customer, merchant or store ID. -## Read more +To associate vectors with a namespace, you can optionally provide a `namespace: string` value when performing an insert or upsert operation. When querying, you can pass the namespace to search within as an optional parameter to your query. -::callout -Read more on [Cloudflare Vectorize documentation](https://developers.cloudflare.com/vectorize/reference/client-api/). -:: +A namespace can be up to 64 characters (bytes) in length and you can have up to 1,000 namespaces per index. Refer to the [Limits](/vectorize/platform/limits/) documentation for more details. -::callout{to=https://developers.cloudflare.com/reference-architecture/diagrams/ai/ai-rag/} -[Retrieval Augmented Generation (RAG)](https://developers.cloudflare.com/reference-architecture/diagrams/ai/ai-rag/): Retrieval-Augmented Generation (RAG) is an innovative approach in natural language processing that integrates retrieval mechanisms with generative models to enhance text generation. -:: +When a namespace is specified in a query operation, only vectors within that namespace are used for the search. Namespace filtering is applied before vector search, not after. + +#### Insert vectors with a namespace + +```ts +// Mock vectors +// Vectors from a machine-learning model are typically ~100 to 1536 dimensions +// wide (or wider still). +const sampleVectors: Array = [ + { + id: "1", + values: [32.4, 74.1, 3.2, ...], + namespace: "text", + }, + { + id: "2", + values: [15.1, 19.2, 15.8, ...], + namespace: "images", + }, + { + id: "3", + values: [0.16, 1.2, 3.8, ...], + namespace: "pdfs", + }, +]; + +// Insert your vectors, returning a count of the vectors inserted and their vector IDs. +const inserted = await index.insert(sampleVectors); +``` + +#### Query vectors within a namespace + +```ts +// Your queryVector will be searched against vectors within the namespace (only) +const matches = await index.query(queryVector, { + namespace: "images", +}); +``` + +### Namespace versus metadata filtering + +Both [namespaces](https://developers.cloudflare.com/vectorize/best-practices/insert-vectors/#namespaces) and metadata filtering narrow the vector search space for a query. Consider the following when evaluating both filter types: + +- A namespace filter is applied before metadata filter(s). +- A vector can only be part of a single namespace with the documented [limits](https://developers.cloudflare.com/vectorize/platform/limits/). Vector metadata can contain multiple key-value pairs up to [metadata per vector limits](https://developers.cloudflare.com/vectorize/platform/limits/). Metadata values support different types (`string`, `boolean`, and others), therefore offering more flexibility. + +## Limits + +| Feature | Current Limit | +| ------------------------------------------------------------- | ---------------------------------------------------------------- | +| Indexes per account | 100 indexes | +| Maximum dimensions per vector | 1536 dimensions | +| Maximum vector ID length | 51 bytes | +| Metadata per vector | 10KiB | +| Maximum returned results (`topK`) with values or metadata | 20 | +| Maximum returned results (`topK`) without values and metadata | 100 | +| Maximum upsert batch size (per batch) | 1000 | +| Maximum index name length | 64 bytes | +| Maximum vectors per index | 5,000,000 | +| Maximum namespaces per index | 1000 namespaces | +| Maximum namespace name length | 64 bytes | +| Maximum vectors upload size | 100 MB | +| Maximum metadata indexes per Vectorize index | 10 | +| Maximum indexed data per metadata index per vector | 64 bytes | + +Learn more about [Cloudflare Vectorize limits](https://developers.cloudflare.com/vectorize/platform/limits/). + +## Types + +### `VectorizeVector` + +See [vector object](#vector-object). + +```ts +interface VectorizeVector { + /** The ID for the vector. This can be user-defined, and must be unique. It should uniquely identify the object, and is best set based on the ID of what the vector represents. */ + id: string; + /** The vector values */ + values: VectorFloatArray | number[]; + /** The namespace this vector belongs to. */ + namespace?: string; + /** Metadata associated with the vector. Includes the values of other fields and potentially additional details. */ + metadata?: Record; +} +``` + +### `VectorizeMatches` + +A set of matching [VectorizeMatch](#vectorizematch) for a particular query. + +```ts +interface VectorizeMatches { + matches: VectorizeMatch[]; + count: number; +} +``` + +### `VectorizeMatch` + +Represents a matched vector for a query along with its score and (if specified) the matching vector information. + +```ts +type VectorizeMatch = Pick, "values"> & + Omit & { + /** The score or rank for similarity, when returned as a result */ + score: number; + }; +``` + +### `VectorizeAsyncMutation` + +Result type indicating a mutation on the Vectorize Index. Actual mutations are processed async where the `mutationId` is the unique identifier for the operation. + +```ts +interface VectorizeAsyncMutation { + /** The unique identifier for the async mutation operation containing the changeset. */ + mutationId: string; +} +``` + +### `VectorizeIndexInfo` + +Metadata about an existing index. + +```ts +interface VectorizeIndexInfo { + /** The number of records containing vectors within the index. */ + vectorsCount: number; + /** Number of dimensions the index has been configured for. */ + dimensions: number; + /** ISO 8601 datetime of the last processed mutation on in the index. All changes before this mutation will be reflected in the index state. */ + processedUpToDatetime: number; + /** UUIDv4 of the last mutation processed by the index. All changes before this mutation will be reflected in the index state. */ + processedUpToMutation: number; +} +``` + + From ee4b12e81f8642c53121e079a6c457097f2f6129 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Fri, 4 Oct 2024 03:35:40 +0100 Subject: [PATCH 42/53] docs: update changelog --- docs/content/4.changelog/hub-vectorize.md | 90 +++++++++++++++++++++++ 1 file changed, 90 insertions(+) create mode 100644 docs/content/4.changelog/hub-vectorize.md diff --git a/docs/content/4.changelog/hub-vectorize.md b/docs/content/4.changelog/hub-vectorize.md new file mode 100644 index 00000000..ecc42f59 --- /dev/null +++ b/docs/content/4.changelog/hub-vectorize.md @@ -0,0 +1,90 @@ +--- +title: Introducing hubVectorize() +description: "Run machine learning models, such as LLMs in your Nuxt application, with minimal setup." +date: 2024-10-03 +image: '/images/changelog/hub-vectorize.png' +category: Core +authors: + - name: Rihan Arfan + avatar: + src: https://avatars.githubusercontent.com/u/20425781?v=4 + to: https://x.com/RihanArfan + username: RihanArfan +--- + +::tip +This feature is available on both [free and pro plans](/pricing) and in [`@nuxthub/core >= v0.0.0`](https://github.com/nuxt-hub/core/releases/tag/v0.0.0). +:: + +We are excited to introduce [`hubVectorize()`](/docs/features/vectorize), which gives you access to a globally distributed vector database from Nuxt. Paired with [`hubAI()`](/docs/features/ai), it makes Nuxt a perfect framework for easily building full-stack AI-powered applications. + +## What is a vector database? +Vector databases allows you to querying embeddings, which are representations of values or objects like text, images, audio that are designed to be consumed by machine learning models and semantic search algorithms. + +Some key use cases of vector databases include: +- Semantic search, used to return results similar to the input of the query. +- Classification, used to return the grouping (or groupings) closest to the input query. +- Recommendation engines, used to return content similar to the input based on different criteria (for example previous product sales, or user history). + +Vector databases are commonly used for [Retrieval-Augmented Generation (RAG)](https://developers.cloudflare.com/reference-architecture/diagrams/ai/ai-rag/), which is a technique that enhances language models by retrieving relevant information from an external knowledge base before generating a response. + +Learn more about vector databases on [Cloudflare's documentation](https://developers.cloudflare.com/vectorize/reference/what-is-a-vector-database/). + +## How to use hubAI() + +1. Update `@nuxthub/core` to the latest version (`v0.0.0` or later) + +2. Configure a Vectorize index in `hub.vectorize` in your `nuxt.config.ts` + +```ts [nuxt.config.ts] +export default defineNuxtConfig({ + hub: { + vectorize: { + tutorial: { + dimensions: 768, + metric: "cosine" + } + } + } +}) +``` + +3. Run `npx nuxthub link` to link a NuxtHub project or create a new one + +4. Deploy the project to NuxtHub with `npx nuxthub deploy` + +5. Start Nuxt and connect to [remote storage](/docs/getting-started/remote-storage) by running [`npx nuxt dev --remote`](/docs/getting-started/remote-storage) + +5. You can now use [`hubVectorize('')`](/docs/features/vectorize) in your server routes + +```ts [server/api/vectorize-search.ts] +export default defineEventHandler(async (event) => { + const { query, limit } = getQuery(event) + const embeddings = await hubAI().run('@cf/baai/bge-base-en-v1.5', { + text: query + }) + const queryVector = embeddings.data[0] + + const index = hubVectorize('tutorial') + return await vectorize.query(vectors, { + topK: limit, + }) +}) +``` + +Read the [full documentation](/docs/features/vectorize) to learn more about `hubVectorize()`. + +::important +**If you already have a NuxtHub account**, make sure to add the `Vectorize` permission on your Cloudflare API token. + +- Open [Cloudflare User API Tokens](https://dash.cloudflare.com/profile/api-tokens) +- Find the NuxtHub token(s) +- Add the `Account > Vectorize > Edit` permission +- Save the changes + +Another solution is to link again your Cloudflare account from your NuxtHub team settings by clicking on `Link a new account` > `Create a token with required permissions`. +:: + +::note +This feature has been implemented in [nuxt-hub/core#177](https://github.com/nuxt-hub/core/pull/177). +:: From 2a2d0f4f7107ea53ec72673ba704373574b7d801 Mon Sep 17 00:00:00 2001 From: Rihan Arfan Date: Fri, 4 Oct 2024 04:34:06 +0100 Subject: [PATCH 43/53] docs: add examples --- docs/content/1.docs/2.features/vectorize.md | 128 +++++++++++++++++++- 1 file changed, 124 insertions(+), 4 deletions(-) diff --git a/docs/content/1.docs/2.features/vectorize.md b/docs/content/1.docs/2.features/vectorize.md index cbb64432..ba2cea74 100644 --- a/docs/content/1.docs/2.features/vectorize.md +++ b/docs/content/1.docs/2.features/vectorize.md @@ -387,7 +387,7 @@ Determining the similarity between vectors can be subjective based on how the ma When querying vectors, you can specify Vectorize to use either: - High-precision scoring, which increases the precision of the query matches scores as well as the accuracy of the query results. -- Approximate scoring for faster response times. Using approximate scoring, returned scores will be an approximation of the real distance/similarity between your query and the returned vectors. Refer to [Control over scoring precision and query accuracy](/vectorize/best-practices/query-vectors/#control-over-scoring-precision-and-query-accuracy). +- Approximate scoring for faster response times. Using approximate scoring, returned scores will be an approximation of the real distance/similarity between your query and the returned vectors. Refer to [Control over scoring precision and query accuracy](#control-over-scoring-precision-and-query-accuracy). Distance metrics cannot be changed after index creation, and that each metric has a different scoring function. @@ -412,10 +412,10 @@ Metadata keys cannot be empty, contain the dot character (`.`), contain the doub Metadata can be used to: - Include the object storage key, database UUID or other identifier to look up the content the vector embedding represents. -- The raw content (up to the [metadata limits](/vectorize/platform/limits/)), which can allow you to skip additional lookups for smaller content. +- The raw content (up to the [metadata limits](https://developers.cloudflare.com/vectorize/platform/limits/)), which can allow you to skip additional lookups for smaller content. - Dates, timestamps, or other metadata that describes when the vector embedding was generated or how it was generated. -For example, a vector embedding representing an image could include the path to the [R2 object](/r2/) it was generated from, the format, and a category lookup: +For example, a vector embedding representing an image could include the path to the [blob](/docs/features/blob) it was generated from, the format, and a category lookup: ```ts { id: '1', values: [32.4, 74.1, 3.2, ...], metadata: { path: 'r2://bucket-name/path/to/image.png', format: 'png', category: 'profile_image' } } @@ -676,7 +676,7 @@ Namespaces provide a way to segment the vectors within your index. For example, To associate vectors with a namespace, you can optionally provide a `namespace: string` value when performing an insert or upsert operation. When querying, you can pass the namespace to search within as an optional parameter to your query. -A namespace can be up to 64 characters (bytes) in length and you can have up to 1,000 namespaces per index. Refer to the [Limits](/vectorize/platform/limits/) documentation for more details. +A namespace can be up to 64 characters (bytes) in length and you can have up to 1,000 namespaces per index. Refer to the [Limits](https://developers.cloudflare.com/vectorize/platform/limits/) documentation for more details. When a namespace is specified in a query operation, only vectors within that namespace are used for the search. Namespace filtering is applied before vector search, not after. @@ -815,4 +815,124 @@ interface VectorizeIndexInfo { } ``` +## Examples + +### Vector search + +In this example: +1. An embeddings vector is generated from the search query. +2. The Vectorize index is queried with the embeddings vector. +3. Then the original source data is retrieved by querying the database for the IDs returned by Vectorize. + +Learn more at https://developers.cloudflare.com/vectorize/reference/what-is-a-vector-database/#vector-search + +::collapsible{name="code"} +```ts [server/api/search.get.ts] +import { z } from "zod"; + +interface EmbeddingResponse { + shape: number[]; + data: number[][]; +} + +const Query = z.object({ + query: z.string().min(1).max(256), + limit: z.coerce.number().int().min(1).max(20).default(10), +}); + +export default defineEventHandler(async (event) => { + const { query, limit } = await getValidatedQuery(event, Query.parse); + + // 1. generate embeddings for search query + const embeddings: EmbeddingResponse = await hubAI().run("@cf/baai/bge-base-en-v1.5", { text: [query] }); + const vectors = embeddings.data[0]; + + // 2. query vectorize to find similar results + const vectorize: VectorizeIndex = hubVectorize('jobs'); + const { matches } = await vectorize.query(vectors, { topK: limit }); + + // 3. get details for matching items + const jobMatches = await useDrizzle().query.jobs.findMany({ + where: (jobs, { inArray }) => inArray(jobs.id, matches.map((match) => match.id)), + with: { + department: true, + subDepartment: true, + }, + }); + + // 4. add score to matches + const jobMatchesWithScore = jobMatches.map((job) => { + const match = matches.find((match) => match.id === job.id); + return { ...job, score: match!.score }; + }); + + // 5. sort by score + return jobMatchesWithScore.sort((a, b) => b.score - a.score); +}); +``` +:: + +### Bulk generation and import + +This example bulk generates vectors using a text embeddings AI model for all data within a database table, using [Nitro tasks](https://nitro.unjs.io/guide/tasks). You can run the task via Nuxt DevTools. + +::collapsible{name="code"} +```ts [server/tasks/generate-embeddings.ts] +import { jobs } from "../database/schema"; +import { asc, count } from "drizzle-orm"; + +export default defineTask({ + meta: { + name: "vectorize:seed", + description: "Generate text embeddings vectors", + }, + async run() { + console.log("Running Vectorize seed task..."); + const jobCount = (await useDrizzle().select({ count: count() }).from(tables.jobs))[0].count; + + // process in chunks of 100 as that's the maximum supported by workers ai + const INCREMENT_AMOUNT = 100; + + const totalBatches = Math.ceil(jobCount / INCREMENT_AMOUNT); + console.log(`Total items: ${jobCount} (${totalBatches} batches)`); + + for (let i = 0; i < jobCount; i += INCREMENT_AMOUNT) { + console.log(`⏳ Processing items ${i} - ${i + INCREMENT_AMOUNT}...`); + + const jobsChunk = await useDrizzle() + .select() + .from(tables.jobs) + .orderBy(asc(jobs.id)) + .limit(INCREMENT_AMOUNT) + .offset(i); + + // generate embeddings for job titles + const ai = hubAi(); + const embeddings = await ai.run( + "@cf/baai/bge-base-en-v1.5", + { text: jobsChunk.map((job) => job.jobTitle) }, + { gateway: { id: "new-role" } }, + ); + const vectors = embeddings.data; + + const formattedEmbeddings = jobsChunk.map(({ id, ...metadata }, index) => ({ + id, + metadata: { ...metadata }, + values: vectors[index], + })); + + // save vector embeddings to index + const index = hubVectorize('jobs'); + await index.upsert(formattedEmbeddings); + + console.log(`✅ Processed items ${i} - ${i + INCREMENT_AMOUNT}...`); + } + + console.log("Vectorize seed task completed!"); + return { result: "success" }; + }, +}); +``` +:: + From 1add42ba73c28c98975cd833bff26b6db703286d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Chopin?= Date: Fri, 4 Oct 2024 18:41:11 +0200 Subject: [PATCH 44/53] docs: update --- docs/pages/pricing.vue | 16 +++++++++++----- 1 file changed, 11 insertions(+), 5 deletions(-) diff --git a/docs/pages/pricing.vue b/docs/pages/pricing.vue index f6388172..e9ab1f92 100644 --- a/docs/pages/pricing.vue +++ b/docs/pages/pricing.vue @@ -103,8 +103,9 @@ onMounted(() => { - -
- -
{ + @@ -176,6 +174,14 @@ onMounted(() => { class="hidden dark:block" lazy /> +

From 26498106dcaf2a304846315be6e2b22308940da5 Mon Sep 17 00:00:00 2001 From: Rihan Date: Fri, 4 Oct 2024 17:42:10 +0100 Subject: [PATCH 45/53] docs: remove unnecessary link in comment MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Sébastien Chopin --- src/runtime/vectorize/server/utils/vectorize.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/runtime/vectorize/server/utils/vectorize.ts b/src/runtime/vectorize/server/utils/vectorize.ts index d727599d..4a115c78 100644 --- a/src/runtime/vectorize/server/utils/vectorize.ts +++ b/src/runtime/vectorize/server/utils/vectorize.ts @@ -25,7 +25,7 @@ type VectorizeIndexes = keyof RuntimeConfig['hub']['vectorize'] & string * let inserted = await vectorize.insert(vectorsToInsert) * ``` * - * Vectorize is currently only supported with `--remote`. See https://developers.cloudflare.com/workers/testing/local-development/#supported-resource-bindings-in-different-environments for details. + * Vectorize is currently only supported with `--remote`. * * @see https://hub.nuxt.com/docs/features/vectorize */ From 6d38572034928f0ec12b1850ac6814269dddb292 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Chopin?= Date: Fri, 4 Oct 2024 18:51:48 +0200 Subject: [PATCH 46/53] docs: small updates --- docs/content/1.docs/2.features/vectorize.md | 4 ++-- docs/content/4.changelog/hub-vectorize.md | 1 + 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/docs/content/1.docs/2.features/vectorize.md b/docs/content/1.docs/2.features/vectorize.md index ba2cea74..d7ba56d1 100644 --- a/docs/content/1.docs/2.features/vectorize.md +++ b/docs/content/1.docs/2.features/vectorize.md @@ -9,7 +9,7 @@ Learn what vector databases are on Cloudflare's documentation :: ::warning -Vectorize is current unavailable during local development. To develop with Vectorize, create an index inside `nuxt.config.ts`, deploy the application and develop using [`nuxt dev --remot#e`](/docs/getting-started/remote-storage). +Vectorize is current unavailable during local development. To develop with Vectorize, create an index inside `nuxt.config.ts`, deploy the application and develop using [`nuxt dev --remote`](/docs/getting-started/remote-storage). :: ## Getting Started @@ -194,7 +194,7 @@ console.log(matches) Querying an index, or vector search, enables you to search an index by providing an input vector and returning the nearest vectors based on the [configured distance metric](#distance-metrics). -Optionally, you can apply [metadata filters](#metadata--filtering) or a [namespace](#namespaces) to narrow the vector search space. +Optionally, you can apply [metadata filters](#metadata-filtering) or a [namespace](#namespaces) to narrow the vector search space. #### Params diff --git a/docs/content/4.changelog/hub-vectorize.md b/docs/content/4.changelog/hub-vectorize.md index ecc42f59..13cf8c05 100644 --- a/docs/content/4.changelog/hub-vectorize.md +++ b/docs/content/4.changelog/hub-vectorize.md @@ -19,6 +19,7 @@ This feature is available on both [free and pro plans](/pricing) and in [`@nuxth We are excited to introduce [`hubVectorize()`](/docs/features/vectorize), which gives you access to a globally distributed vector database from Nuxt. Paired with [`hubAI()`](/docs/features/ai), it makes Nuxt a perfect framework for easily building full-stack AI-powered applications. ## What is a vector database? + Vector databases allows you to querying embeddings, which are representations of values or objects like text, images, audio that are designed to be consumed by machine learning models and semantic search algorithms. Some key use cases of vector databases include: From 768c4db4f4e6f9f5e8cd96350db0ce9b47afa1f2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Chopin?= Date: Fri, 4 Oct 2024 20:07:51 +0200 Subject: [PATCH 47/53] docs: improvements --- docs/content/1.docs/2.features/vectorize.md | 11 +++++++---- docs/content/4.changelog/hub-vectorize.md | 6 +++--- 2 files changed, 10 insertions(+), 7 deletions(-) diff --git a/docs/content/1.docs/2.features/vectorize.md b/docs/content/1.docs/2.features/vectorize.md index d7ba56d1..77863231 100644 --- a/docs/content/1.docs/2.features/vectorize.md +++ b/docs/content/1.docs/2.features/vectorize.md @@ -9,7 +9,7 @@ Learn what vector databases are on Cloudflare's documentation :: ::warning -Vectorize is current unavailable during local development. To develop with Vectorize, create an index inside `nuxt.config.ts`, deploy the application and develop using [`nuxt dev --remote`](/docs/getting-started/remote-storage). +Vectorize is only available in local development when using [remote storage](/docs/getting-started/remote-storage). :: ## Getting Started @@ -59,10 +59,13 @@ export default defineNuxtConfig({ ``` :: -::caution -Cloudflare Vectorize index configurations cannot be changed after creation. Therefore, changing an index's dimension size or distance metric will result in modified existing indexes being disconnected from your Pages project, and a new index being created. Existing data will not be migrated. -:: +Then, make sure to [deploy your project](/docs/getting-started/deploy) to create the indexes. + +Once deployed, you can use the `hubVectorize()` server composable to interact with the vector databases using [remote storage](/docs/getting-started/remote-storage) with the `npx nuxt dev --remote` command. +::important +Cloudflare Vectorize index configurations are immutable after creation. Modifying an index's dimension size or distance metric will disconnect the modified existing index from your deployed project and create a new index. Existing data will not be migrated. Consider your index configuration carefully before creation to avoid data loss and reconnection issues. +:: ### Create an index diff --git a/docs/content/4.changelog/hub-vectorize.md b/docs/content/4.changelog/hub-vectorize.md index 13cf8c05..1e6b590e 100644 --- a/docs/content/4.changelog/hub-vectorize.md +++ b/docs/content/4.changelog/hub-vectorize.md @@ -13,7 +13,7 @@ authors: --- ::tip -This feature is available on both [free and pro plans](/pricing) and in [`@nuxthub/core >= v0.0.0`](https://github.com/nuxt-hub/core/releases/tag/v0.0.0). +This feature is available on both [free and pro plans](/pricing) and in [`@nuxthub/core >= v0.8.0`](https://github.com/nuxt-hub/core/releases/tag/v0.8.0). :: We are excited to introduce [`hubVectorize()`](/docs/features/vectorize), which gives you access to a globally distributed vector database from Nuxt. Paired with [`hubAI()`](/docs/features/ai), it makes Nuxt a perfect framework for easily building full-stack AI-powered applications. @@ -31,9 +31,9 @@ Vector databases are commonly used for [Retrieval-Augmented Generation (RAG)](ht Learn more about vector databases on [Cloudflare's documentation](https://developers.cloudflare.com/vectorize/reference/what-is-a-vector-database/). -## How to use hubAI() +## How to use hubVectorize() -1. Update `@nuxthub/core` to the latest version (`v0.0.0` or later) +1. Update `@nuxthub/core` to the latest version (`v0.8.0` or later) 2. Configure a Vectorize index in `hub.vectorize` in your `nuxt.config.ts` From b1a25aee0c07d31684ca047fa8b871c4601042b1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Chopin?= Date: Fri, 4 Oct 2024 20:33:33 +0200 Subject: [PATCH 48/53] fix: add condition when data is not available yet --- src/features.ts | 6 +++++- src/module.ts | 2 +- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/src/features.ts b/src/features.ts index 45abe68c..6e6ecc65 100644 --- a/src/features.ts +++ b/src/features.ts @@ -193,12 +193,16 @@ export function setupVectorize(nuxt: Nuxt, hub: HubConfig) { addServerImportsDir(resolve('./runtime/vectorize/server/utils')) } -export function vectorizeRemoteCheck(hub: HubConfig, log: ConsolaInstance) { +export function vectorizeRemoteCheck(hub: HubConfig) { let isIndexConfigurationChanged = false const localVectorize = hub.vectorize || {} const remoteVectorize = hub.remoteManifest?.storage.vectorize || {} Object.keys(localVectorize).forEach((key) => { + // Index does not exist in remote project yet + if (!remoteVectorize[key]) { + return + } const isDimensionsChanged = localVectorize[key].dimensions !== remoteVectorize[key].dimensions const isMetricChanged = localVectorize[key].metric !== remoteVectorize[key].metric if (isDimensionsChanged || isMetricChanged) { diff --git a/src/module.ts b/src/module.ts index 89327f73..d781c285 100644 --- a/src/module.ts +++ b/src/module.ts @@ -141,7 +141,7 @@ export default defineNuxtModule({ if (hub.remote) { await setupRemote(nuxt, hub) - vectorizeRemoteCheck(hub, log) + vectorizeRemoteCheck(hub) return } From 763a6767e835e5e350cd401338bcec148311a6d7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Chopin?= Date: Fri, 4 Oct 2024 20:40:53 +0200 Subject: [PATCH 49/53] update doc for self deployment --- .../1.docs/1.getting-started/3.deploy.md | 29 ++++++++++--------- 1 file changed, 15 insertions(+), 14 deletions(-) diff --git a/docs/content/1.docs/1.getting-started/3.deploy.md b/docs/content/1.docs/1.getting-started/3.deploy.md index 58286998..cafc747d 100644 --- a/docs/content/1.docs/1.getting-started/3.deploy.md +++ b/docs/content/1.docs/1.getting-started/3.deploy.md @@ -138,20 +138,21 @@ You only need to create these resources if you have explicitly enabled them in t Then, create a [Cloudflare Pages project](https://dash.cloudflare.com/?to=/:account/pages/new/provider/github) and link your GitHub or Gitlab repository and choose the Nuxt Framework preset in the build settings. -Once your project is created, open the `Settings -> Functions` tab and set: -- KV namespace bindings - - Set the variable name as `KV` and select your KV namespace created - - Set the variable name as `CACHE` and select your KV namespace for caching created -- R2 bucket bindings - - Set the variable name as `BLOB` and select your R2 bucket created -- D1 database bindings - - Set the variable name as `DB` and select your D1 database created -- AI bindings - - Set the variable name as `AI` -- Browser bindings - - Set the variable name as `BROWSER` -- Compatibility flags - - Add the `nodejs_compat` and `nodejs_als` flags +Once your project is created, open the `Settings` tab and set: +- Runtime > Compatibility flags + - Add the `nodejs_compat` flag +- Bindings + - KV namespace: `KV` and select your KV namespace created + - KV namespace: `CACHE` and select your KV namespace for caching created + - R2 bucket: `BLOB` and select your R2 bucket created + - D1 database: `DB` and select your D1 database created + - AI: `AI` + - Browser: `BROWSER` + - Vectorize: `VECTORIZE_` and select your Vectorize index created :br + ```bash + # Create the Vectorize index manually using + npx wrangler vectorize create --dimensions= --metric= + ``` Go back to the `Deployment` tab and retry the last deployment by clicking on `...` then `Retry deployment`. From c893a21cde6788719e03f282c2e6d879c377b4f1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Chopin?= Date: Fri, 4 Oct 2024 20:41:25 +0200 Subject: [PATCH 50/53] lint fix --- src/features.ts | 1 - 1 file changed, 1 deletion(-) diff --git a/src/features.ts b/src/features.ts index 6e6ecc65..de97bc7f 100644 --- a/src/features.ts +++ b/src/features.ts @@ -1,5 +1,4 @@ import { execSync } from 'node:child_process' -import type { ConsolaInstance } from 'consola' import type { Nuxt } from '@nuxt/schema' import { logger, addImportsDir, addServerImportsDir, addServerScanDir, createResolver } from '@nuxt/kit' import { joinURL } from 'ufo' From 5544f32e23064bdb4742a55391e5b0370d8b3579 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Chopin?= Date: Fri, 4 Oct 2024 20:44:45 +0200 Subject: [PATCH 51/53] up --- docs/content/1.docs/1.getting-started/3.deploy.md | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/docs/content/1.docs/1.getting-started/3.deploy.md b/docs/content/1.docs/1.getting-started/3.deploy.md index cafc747d..10d2fdf5 100644 --- a/docs/content/1.docs/1.getting-started/3.deploy.md +++ b/docs/content/1.docs/1.getting-started/3.deploy.md @@ -126,11 +126,7 @@ That's it! NuxtHub will automatically configure the necessary resources and envi You can deploy your project on your own Cloudflare account without using the NuxtHub Admin. -For that, you need to create the necessary resources in your Cloudflare account and configure your project to use them: - -- One [D1 database](https://dash.cloudflare.com/?to=/:account/workers/d1) -- Two [KV namespaces](https://dash.cloudflare.com/?to=/:account/workers/kv/namespaces) (one for `hubKV()` and one for [server caching](/docs/features/cache)) -- One [R2 bucket](https://dash.cloudflare.com/?to=/:account/r2/new) +For that, you need to create the necessary resources in your Cloudflare account and configure your project to use them ([D1](https://dash.cloudflare.com/?to=/:account/workers/d1), [KV](https://dash.cloudflare.com/?to=/:account/workers/kv/namespaces), [R2](https://dash.cloudflare.com/?to=/:account/r2/new), etc.). ::note You only need to create these resources if you have explicitly enabled them in the Hub Config. From 1a22a5ebc4795a30b072de8030ca50a5866d6d6e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Chopin?= Date: Sat, 5 Oct 2024 00:31:23 +0200 Subject: [PATCH 52/53] up --- docs/content/1.docs/2.features/vectorize.md | 4 ---- 1 file changed, 4 deletions(-) diff --git a/docs/content/1.docs/2.features/vectorize.md b/docs/content/1.docs/2.features/vectorize.md index 77863231..7d927d0b 100644 --- a/docs/content/1.docs/2.features/vectorize.md +++ b/docs/content/1.docs/2.features/vectorize.md @@ -829,7 +829,6 @@ In this example: Learn more at https://developers.cloudflare.com/vectorize/reference/what-is-a-vector-database/#vector-search -::collapsible{name="code"} ```ts [server/api/search.get.ts] import { z } from "zod"; @@ -873,13 +872,11 @@ export default defineEventHandler(async (event) => { return jobMatchesWithScore.sort((a, b) => b.score - a.score); }); ``` -:: ### Bulk generation and import This example bulk generates vectors using a text embeddings AI model for all data within a database table, using [Nitro tasks](https://nitro.unjs.io/guide/tasks). You can run the task via Nuxt DevTools. -::collapsible{name="code"} ```ts [server/tasks/generate-embeddings.ts] import { jobs } from "../database/schema"; import { asc, count } from "drizzle-orm"; @@ -936,6 +933,5 @@ export default defineTask({ }, }); ``` -:: From cf33615ea68274e66c087e1975a34e3a235a4c77 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Chopin?= Date: Sat, 5 Oct 2024 02:21:40 +0200 Subject: [PATCH 53/53] docs: og-image --- docs/content/0.index.yml | 4 ++-- docs/content/4.changelog/hub-vectorize.md | 4 +++- .../images/changelog/nuxthub-vectorize.png | Bin 0 -> 591551 bytes 3 files changed, 5 insertions(+), 3 deletions(-) create mode 100644 docs/public/images/changelog/nuxthub-vectorize.png diff --git a/docs/content/0.index.yml b/docs/content/0.index.yml index 06795d72..ff174bc4 100644 --- a/docs/content/0.index.yml +++ b/docs/content/0.index.yml @@ -10,8 +10,8 @@ hero: light: '/images/landing/hero-light.svg' dark: '/images/landing/hero-dark.svg' headline: - label: "`nuxthub preview` command" - to: /changelog/nuxthub-preview + label: "Introducing hubVectorize()" + to: /changelog/hub-vectorize icon: i-ph-arrow-right links: - label: Start reading docs diff --git a/docs/content/4.changelog/hub-vectorize.md b/docs/content/4.changelog/hub-vectorize.md index 1e6b590e..44fc3fb7 100644 --- a/docs/content/4.changelog/hub-vectorize.md +++ b/docs/content/4.changelog/hub-vectorize.md @@ -2,7 +2,7 @@ title: Introducing hubVectorize() description: "Run machine learning models, such as LLMs in your Nuxt application, with minimal setup." date: 2024-10-03 -image: '/images/changelog/hub-vectorize.png' +image: '/images/changelog/nuxthub-vectorize.png' category: Core authors: - name: Rihan Arfan @@ -18,6 +18,8 @@ This feature is available on both [free and pro plans](/pricing) and in [`@nuxth We are excited to introduce [`hubVectorize()`](/docs/features/vectorize), which gives you access to a globally distributed vector database from Nuxt. Paired with [`hubAI()`](/docs/features/ai), it makes Nuxt a perfect framework for easily building full-stack AI-powered applications. +:nuxt-img{src="/images/changelog/nuxthub-vectorize.png" alt="NuxtHub Vectorize command" width="915" height="515"} + ## What is a vector database? 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