diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..47b69f7 --- /dev/null +++ b/.env.example @@ -0,0 +1,12 @@ +# Step 6 (vector search) is optional and requires an embedding provider. +# Copy to .env and set ONE of the following, then re-warm: POST /Catalog/ + +# Option A — OpenAI +# EMBEDDING_PROVIDER=openai +# OPENAI_API_KEY=sk-... +# OPENAI_EMBEDDING_MODEL=text-embedding-3-small + +# Option B — Ollama (local) +# EMBEDDING_PROVIDER=ollama +# OLLAMA_URL=http://localhost:11434 +# OLLAMA_EMBEDDING_MODEL=nomic-embed-text diff --git a/.gitignore b/.gitignore index 12ac647..6e267fc 100644 --- a/.gitignore +++ b/.gitignore @@ -1,2 +1,3 @@ node_modules/ -.DS_Store \ No newline at end of file +.DS_Store +.env diff --git a/README.md b/README.md index 3d6e83e..58fd8dd 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,261 @@ -# Harper Learn: [Caching with Harper](https//docs.harperdb.io/learn/developers/caching-with-harper) +# Edge API Cache → Data Layer -This repository is intended for use alongside the Harper Learn ["Developers / Caching with Harper"](https//docs.harperdb.io/learn/developers/caching-with-harper) guide. +Turn any external JSON API into a **low-latency, queryable data layer** at the edge. + +This template starts as a minimally-invasive drop-in cache and grows, one step at +a time, into a full data platform, without ever changing where the data comes from. +The point: **an API cache of structured data is already a database.** Once Harper +holds the records, you can query them, reshape them, relate them, stream them live, +and search them semantically, all capabilities the origin API never offered. + +Each step is a single commit, so `git log -p` reads as a guided tour. + +| Step | Capability | What you gain | +| ---- | ---------- | ------------- | +| 1 | **Cache** | Drop-in read-through cache with TTL + stampede protection | +| 2 | **Query** | Filter, sort, paginate the cache with Harper's REST query language | +| 3 | **Transform** | Reshape upstream data at the edge (a BFF, for free) | +| 4 | **Relate** | Join across cached resources with `@relationship` | +| 5 | **Stream** | Real-time updates + push invalidation over WebSocket/SSE | +| 6 | **Vector** | Semantic search over cached content with an HNSW index | + +The upstream in this template is the public [DummyJSON products API](https://dummyjson.com/docs/products) +(no API key required), but the pattern applies to any REST/JSON source: your own +microservices, a SaaS API, a legacy backend. + +## Running it + +```bash +npm install +harper run . # or: harper dev . +``` + +Then hit the endpoints below. By default Harper serves on port `9926`; requests +use HTTP Basic auth with your instance's admin credentials. + +```bash +npm test # Steps 1-5 (Step 6 is skipped without a provider) +EMBEDDING_PROVIDER=ollama npm test # include Step 6's vector search +``` + +--- + +## Step 1 — Cache a structured JSON API + +Define a cache table with a TTL and point it at an upstream source. + +```graphql +# schema.graphql +type ProductCache @table(expiration: 3600) { + id: Int @primaryKey + title: String + price: Float + # ... +} +``` + +```js +// resources.js +class ProductAPI extends Resource { + async get() { + const response = await fetch(`https://dummyjson.com/products/${this.getId()}`); + return response.json(); + } +} +tables.ProductCache.sourcedFrom(ProductAPI); +export class ProductCache extends tables.ProductCache {} +``` + +```bash +# First read fetches from upstream and caches it; every read after is local. +curl localhost:9926/ProductCache/1 +``` + +Harper coalesces concurrent misses for the same id into one upstream request, and +serves all subsequent reads from local storage until the entry's TTL expires. That +is the entire "land": no schema migration upstream, no rewrite, just faster reads. + +--- + +## Step 2 — Query your cache + +Read-through caching stores one record per request. To make the *whole* catalog +queryable, warm it once from the upstream collection endpoint, then mark the +fields you filter and sort on as `@indexed`. + +```graphql +# schema.graphql — index the fields we query on +category: String @indexed +price: Float @indexed +rating: Float @indexed +``` + +```js +// resources.js — warm the cache from the upstream collection +export class Catalog extends Resource { + async post() { + const { products } = await (await fetch('https://dummyjson.com/products?limit=0')).json(); + for (const product of products) await tables.ProductCache.put(toProduct(product)); + return { loaded: products.length }; + } +} +``` + +```bash +curl -X POST localhost:9926/Catalog/ # warm the cache + +# Now query it: filter, sort, paginate, project, at the edge: +curl 'localhost:9926/ProductCache/?price=le=50&sort(-rating)&limit(10)&select(id,title,price,rating)' +``` + +The cache is now a database. Harper's [REST query language](https://docs.harperdb.io) +gives you FIQL filters (`=gt=`, `=le=`, `=ct=`), `sort()`, `limit()`, `select()`, +and boolean grouping, over data whose origin API may have offered none of it. + +--- + +## Step 3 — Transform (a BFF, for free) + +Reshape upstream data at the edge with `@computed` fields. They are resolved from +the record's own attributes on read: no upstream change, no extra storage, and +they are queryable and selectable like any other field. + +```graphql +# schema.graphql +salePrice: Float @computed(from: "price - price * (discountPercentage || 0) / 100") +inStock: Boolean @computed(from: "stock > 0") +``` + +```bash +curl 'localhost:9926/ProductCache/1?select(title,price,salePrice,inStock)' +# { "title": "...", "price": 9.99, "salePrice": 8.94, "inStock": true } +``` + +This is a backend-for-frontend in two lines: the client gets exactly the shape it +needs. For richer reshaping (renaming, nesting, merging multiple sources) extend +the table class and override `get()`. + +--- + +## Step 4 — Relate (join two cached APIs) + +Cache a second resource and link them with `@relationship`. Now you can embed +related records and filter by related fields, a join across two independently +cached upstreams. + +```graphql +# schema.graphql +type ProductCache @table(expiration: 3600) { + categoryInfo: CategoryCache @relationship(from: "category") +} +type CategoryCache @table(expiration: 86400) { + slug: ID @primaryKey + name: String +} +``` + +```bash +curl -X POST localhost:9926/Catalog/ # warms products *and* categories + +# Embed the related category (braces select the related fields): +curl 'localhost:9926/ProductCache/1?select(title,categoryInfo{slug,name})' + +# Filter products by a related-category field (a join): +curl 'localhost:9926/ProductCache/?categoryInfo.slug=beauty&limit(5)' +``` + +Normalize where it helps, keep low-latency reads, and let Harper resolve the +relationship, with no N+1 round-trips to the origin. + +--- + +## Step 5 — Stream (real-time + push invalidation) + +An exported table publishes a WebSocket/SSE endpoint at the same path as its REST +endpoint, so you get live updates with no extra code. Pair that with **push +invalidation** so the cache reflects upstream changes the moment they happen. + +```js +// resources.js — drop a cached entry on demand; next read refetches +static async post(target, data) { + const body = await data; + if (body?.action === 'invalidate') { + await this.invalidate(target); + return { status: 'invalidated' }; + } +} +``` + +Subscribe to a record and react to every change (Node 22+ / browser): + +```js +const ws = new WebSocket('ws://localhost:9926/ProductCache/5'); +ws.onmessage = (e) => console.log('product 5 changed:', JSON.parse(e.data)); +// ...or SSE: fetch('/ProductCache/5', { headers: { Accept: 'text/event-stream' } }) +``` + +```bash +# Tell Harper the upstream changed; subscribers are notified, next read is fresh: +curl -X POST localhost:9926/ProductCache/5 -d '{"action":"invalidate"}' +``` + +REST for reads, the same model streamed live over WebSocket/MQTT/SSE: a +combination very few platforms offer from a single resource definition. + +--- + +## Step 6 — Vector (semantic search over your cache) + +The same cached records, now searchable by meaning. Add an HNSW vector index, +embed each product during warm-up, and search with a natural-language query, with +no separate vector database. + +This step needs an embedding provider. Copy `.env.example` to `.env` and set one: + +```bash +EMBEDDING_PROVIDER=ollama # local; or "openai" with OPENAI_API_KEY +``` + +```graphql +# schema.graphql +embedding: [Float] @indexed(type: "HNSW", distance: "cosine") +``` + +```js +// resources.js +export class ProductSearch extends Resource { + async post(data) { + const { query, limit = 5 } = await data; + const target = await embed(query); + return tables.ProductCache.search({ + select: ['id', 'title', 'price', '$distance'], + sort: { attribute: 'embedding', target }, + limit, + }); + } +} +``` + +```bash +curl -X POST localhost:9926/Catalog/ # warms + embeds +curl -X POST localhost:9926/ProductSearch/ -d '{"query":"something to keep my drink cold"}' +# -> tumblers, coolers, water bottles, matched by meaning, ranked by $distance +``` + +Generating the embeddings is the one piece that currently reaches outside the +database: `embed()` calls an external provider (OpenAI, a local Ollama model) to +turn text into vectors, and Harper stores and searches them. That gap is closing. +Built-in embedding generation on Fabric is coming +([harper#510](https://github.com/HarperFast/harper/issues/510)), which moves the +embedding step in-process alongside the storage and search. + +--- + +## Where you landed + +You started with a one-method read-through cache and finished with a queryable, +relational, real-time, semantically-searchable data layer, all over data that +still lives in someone else's API. That is the whole pitch: **the easy "land" of +an API cache and the deep "expand" of a database are the same system.** Each step +above was a few lines, and none required touching the origin. -The `main` branch is the starting point, and the numbered branches follow the guide progressively. diff --git a/embeddings.js b/embeddings.js new file mode 100644 index 0000000..bce306b --- /dev/null +++ b/embeddings.js @@ -0,0 +1,56 @@ +/** + * Step 6 — pluggable embedding generation. + * + * Set EMBEDDING_PROVIDER to enable vector search. With no provider configured, + * embeddings are skipped and every other step still works. + * + * EMBEDDING_PROVIDER=openai OPENAI_API_KEY=sk-... + * EMBEDDING_PROVIDER=ollama OLLAMA_URL=http://localhost:11434 + * + * No SDKs required — both providers are called over plain HTTP. + */ +const PROVIDER = process.env.EMBEDDING_PROVIDER; +export const EMBEDDINGS_ENABLED = Boolean(PROVIDER); + +const OPENAI_MODEL = process.env.OPENAI_EMBEDDING_MODEL || 'text-embedding-3-small'; +const OLLAMA_URL = process.env.OLLAMA_URL || 'http://localhost:11434'; +const OLLAMA_MODEL = process.env.OLLAMA_EMBEDDING_MODEL || 'nomic-embed-text'; + +/** Returns a numeric embedding vector for `text`, or null if no provider is set. */ +export async function embed(text) { + switch (PROVIDER) { + case undefined: + return null; + case 'openai': + return embedOpenAI(text); + case 'ollama': + return embedOllama(text); + default: + throw new Error(`Unknown EMBEDDING_PROVIDER: ${PROVIDER} (use "openai" or "ollama")`); + } +} + +async function embedOpenAI(text) { + const res = await fetch('https://api.openai.com/v1/embeddings', { + method: 'POST', + headers: { + 'Content-Type': 'application/json', + Authorization: `Bearer ${process.env.OPENAI_API_KEY}`, + }, + body: JSON.stringify({ model: OPENAI_MODEL, input: text }), + }); + if (!res.ok) throw new Error(`OpenAI embeddings failed (${res.status})`); + const json = await res.json(); + return json.data[0].embedding; +} + +async function embedOllama(text) { + const res = await fetch(`${OLLAMA_URL}/api/embeddings`, { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ model: OLLAMA_MODEL, prompt: text }), + }); + if (!res.ok) throw new Error(`Ollama embeddings failed (${res.status})`); + const json = await res.json(); + return json.embedding; +} diff --git a/integrationTests/01-cache.test.ts b/integrationTests/01-cache.test.ts new file mode 100644 index 0000000..8c1b1f3 --- /dev/null +++ b/integrationTests/01-cache.test.ts @@ -0,0 +1,48 @@ +/** + * Step 1 — Cache a structured JSON API. + * + * A GET for an uncached id triggers a single upstream fetch and stores the + * structured result in ProductCache; subsequent GETs are served from the cache. + */ +import { suite, test, before, after } from 'node:test'; +import { strictEqual, ok } from 'node:assert/strict'; +import { setupHarperWithFixture, teardownHarper, type ContextWithHarper } from '@harperfast/integration-testing'; +import { resolve, dirname } from 'node:path'; +import { fileURLToPath } from 'node:url'; +import { authedFetch } from './helpers.ts'; + +const __dirname = dirname(fileURLToPath(import.meta.url)); +const fixtureDir = resolve(__dirname, '..'); + +suite('Step 1 — cache a structured JSON API', (ctx: ContextWithHarper) => { + before(async () => { + await setupHarperWithFixture(ctx, fixtureDir); + }); + + after(async () => { + await teardownHarper(ctx); + }); + + test('GET /ProductCache/:id fetches and caches a product from the upstream API', async () => { + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + + const res = await api('/ProductCache/1'); + strictEqual(res.status, 200); + + const body = (await res.json()) as Record; + strictEqual(body.id, 1); + ok(body.title, `expected a title, got: ${JSON.stringify(body)}`); + ok(typeof body.price === 'number', 'expected a numeric price'); + }); + + test('GET /ProductCache/:id returns the same record from cache on a second read', async () => { + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + + const first = (await (await api('/ProductCache/2')).json()) as Record; + const second = (await (await api('/ProductCache/2')).json()) as Record; + + strictEqual(second.title, first.title, 'cached read should match the first read'); + }); +}); diff --git a/integrationTests/02-query.test.ts b/integrationTests/02-query.test.ts new file mode 100644 index 0000000..e68cfc7 --- /dev/null +++ b/integrationTests/02-query.test.ts @@ -0,0 +1,53 @@ +/** + * Step 2 — Query your cache. + * + * After warming the catalog (POST /Catalog/), the cache is a queryable table: + * filter, sort, paginate, and project fields with Harper's REST query language. + */ +import { suite, test, before, after } from 'node:test'; +import { strictEqual, ok } from 'node:assert/strict'; +import { setupHarperWithFixture, teardownHarper, type ContextWithHarper } from '@harperfast/integration-testing'; +import { resolve, dirname } from 'node:path'; +import { fileURLToPath } from 'node:url'; +import { authedFetch } from './helpers.ts'; + +const __dirname = dirname(fileURLToPath(import.meta.url)); +const fixtureDir = resolve(__dirname, '..'); + +suite('Step 2 — query the cache', (ctx: ContextWithHarper) => { + before(async () => { + await setupHarperWithFixture(ctx, fixtureDir); + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + const res = await api('/Catalog/', { method: 'POST' }); + const body = (await res.json()) as { loaded: number }; + ok(body.loaded > 0, `catalog warm-up should load records, got ${JSON.stringify(body)}`); + }); + + after(async () => { + await teardownHarper(ctx); + }); + + test('filters and sorts cached records with the REST query language', async () => { + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + + const res = await api('/ProductCache/?price=le=50&sort(-rating)&limit(5)&select(id,title,price,rating)'); + strictEqual(res.status, 200); + + const rows = (await res.json()) as Array>; + ok(Array.isArray(rows) && rows.length > 0 && rows.length <= 5, `expected 1-5 rows, got ${rows.length}`); + + // Filter honored. + for (const row of rows) { + ok((row.price as number) <= 50, `price ${row.price} should be <= 50`); + // Projection honored: no description field requested. + strictEqual(row.description, undefined); + } + + // Sort honored (rating descending). + for (let i = 1; i < rows.length; i++) { + ok((rows[i - 1].rating as number) >= (rows[i].rating as number), 'results should be sorted by rating desc'); + } + }); +}); diff --git a/integrationTests/03-transform.test.ts b/integrationTests/03-transform.test.ts new file mode 100644 index 0000000..8220d87 --- /dev/null +++ b/integrationTests/03-transform.test.ts @@ -0,0 +1,55 @@ +/** + * Step 3 — Transform (reshape at the edge). + * + * `@computed` fields derive new attributes from the cached record at read time — + * a backend-for-frontend, with no upstream change and no extra storage. + */ +import { suite, test, before, after } from 'node:test'; +import { strictEqual, ok } from 'node:assert/strict'; +import { setupHarperWithFixture, teardownHarper, type ContextWithHarper } from '@harperfast/integration-testing'; +import { resolve, dirname } from 'node:path'; +import { fileURLToPath } from 'node:url'; +import { authedFetch } from './helpers.ts'; + +const __dirname = dirname(fileURLToPath(import.meta.url)); +const fixtureDir = resolve(__dirname, '..'); + +suite('Step 3 — transform with @computed', (ctx: ContextWithHarper) => { + before(async () => { + await setupHarperWithFixture(ctx, fixtureDir); + const { admin, httpURL } = ctx.harper; + await authedFetch(httpURL, admin.username, admin.password)('/Catalog/', { method: 'POST' }); + }); + + after(async () => { + await teardownHarper(ctx); + }); + + test('a single record exposes computed salePrice and inStock', async () => { + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + + const p = (await ( + await api('/ProductCache/1?select(price,discountPercentage,stock,salePrice,inStock)') + ).json()) as Record; + const expectedSale = (p.price as number) - (p.price as number) * (((p.discountPercentage as number) || 0) / 100); + + ok(Math.abs((p.salePrice as number) - expectedSale) < 0.01, `salePrice ${p.salePrice} ≈ ${expectedSale}`); + strictEqual(p.inStock, (p.stock as number) > 0); + }); + + test('computed fields are selectable in queries', async () => { + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + + const rows = (await ( + await api('/ProductCache/?stock=gt=0&select(id,price,discountPercentage,salePrice,inStock)&limit(3)') + ).json()) as Array>; + + ok(rows.length > 0, 'expected some in-stock rows'); + for (const row of rows) { + strictEqual(row.inStock, true, 'filtered to in-stock items'); + ok(typeof row.salePrice === 'number', 'salePrice should be present and numeric'); + } + }); +}); diff --git a/integrationTests/04-relate.test.ts b/integrationTests/04-relate.test.ts new file mode 100644 index 0000000..d1920d5 --- /dev/null +++ b/integrationTests/04-relate.test.ts @@ -0,0 +1,55 @@ +/** + * Step 4 — Relate (join across cached resources). + * + * A `@relationship` links each product to its category by slug. Harper resolves + * the related record on read and lets you filter by related fields with dot + * syntax — joins over two independently-cached APIs. + */ +import { suite, test, before, after } from 'node:test'; +import { strictEqual, ok } from 'node:assert/strict'; +import { setupHarperWithFixture, teardownHarper, type ContextWithHarper } from '@harperfast/integration-testing'; +import { resolve, dirname } from 'node:path'; +import { fileURLToPath } from 'node:url'; +import { authedFetch } from './helpers.ts'; + +const __dirname = dirname(fileURLToPath(import.meta.url)); +const fixtureDir = resolve(__dirname, '..'); + +suite('Step 4 — relate with @relationship', (ctx: ContextWithHarper) => { + before(async () => { + await setupHarperWithFixture(ctx, fixtureDir); + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + const body = (await (await api('/Catalog/', { method: 'POST' })).json()) as { categories: number }; + ok(body.categories > 0, `expected categories to be warmed, got ${JSON.stringify(body)}`); + }); + + after(async () => { + await teardownHarper(ctx); + }); + + test('embeds the related category record via select()', async () => { + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + + const row = (await ( + await api('/ProductCache/1?select(id,category,categoryInfo{slug,name})') + ).json()) as Record; + + ok(row?.categoryInfo, `expected an embedded categoryInfo, got ${JSON.stringify(row)}`); + strictEqual(row.categoryInfo.slug, row.category, 'related slug should match the product category'); + ok(row.categoryInfo.name, 'related category should carry a display name'); + }); + + test('filters products by a related-category field (a join)', async () => { + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + + const rows = (await ( + await api('/ProductCache/?categoryInfo.slug=beauty&select(id,category)&limit(5)') + ).json()) as Array>; + + ok(rows.length > 0, 'expected products in the beauty category'); + for (const row of rows) strictEqual(row.category, 'beauty'); + }); +}); diff --git a/integrationTests/05-realtime.test.ts b/integrationTests/05-realtime.test.ts new file mode 100644 index 0000000..6725cb2 --- /dev/null +++ b/integrationTests/05-realtime.test.ts @@ -0,0 +1,62 @@ +/** + * Step 5 — Real-time (stream + push invalidation). + * + * Push invalidation is tested here over HTTP: POST {action:"invalidate"} drops a + * cached entry so the next read refetches fresh. Live streaming comes free with + * the exported table (WebSocket/SSE at the same path) and is shown in the README. + */ +import { suite, test, before, after } from 'node:test'; +import { strictEqual, ok } from 'node:assert/strict'; +import { setupHarperWithFixture, teardownHarper, type ContextWithHarper } from '@harperfast/integration-testing'; +import { resolve, dirname } from 'node:path'; +import { fileURLToPath } from 'node:url'; +import { authedFetch } from './helpers.ts'; + +const __dirname = dirname(fileURLToPath(import.meta.url)); +const fixtureDir = resolve(__dirname, '..'); + +suite('Step 5 — real-time invalidation', (ctx: ContextWithHarper) => { + before(async () => { + await setupHarperWithFixture(ctx, fixtureDir); + }); + + after(async () => { + await teardownHarper(ctx); + }); + + test('POST {action:"invalidate"} drops the cached entry', async () => { + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + + // Cache the record first. + const cached = await api('/ProductCache/5'); + strictEqual(cached.status, 200); + + const res = await api('/ProductCache/5', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ action: 'invalidate' }), + }); + strictEqual(res.status, 200); + const body = (await res.json()) as { status: string }; + strictEqual(body.status, 'invalidated'); + + // The entry is still readable — Harper refetches it transparently. + const after = await api('/ProductCache/5'); + strictEqual(after.status, 200); + const product = (await after.json()) as Record; + strictEqual(product.id, 5); + }); + + test('an unsupported action is rejected', async () => { + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + + const res = await api('/ProductCache/5', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ action: 'nope' }), + }); + ok(res.status >= 400, `unsupported action should error, got ${res.status}`); + }); +}); diff --git a/integrationTests/06-vector.test.ts b/integrationTests/06-vector.test.ts new file mode 100644 index 0000000..c11fd18 --- /dev/null +++ b/integrationTests/06-vector.test.ts @@ -0,0 +1,57 @@ +/** + * Step 6 — Vector (semantic search). + * + * Requires an embedding provider, so the suite is skipped unless EMBEDDING_PROVIDER + * is set. With one configured, warming the catalog also embeds each product, and + * ProductSearch finds items by meaning rather than keywords. + * + * EMBEDDING_PROVIDER=ollama npm test + */ +import { suite, test, before, after } from 'node:test'; +import { ok } from 'node:assert/strict'; +import { setupHarperWithFixture, teardownHarper, type ContextWithHarper } from '@harperfast/integration-testing'; +import { resolve, dirname } from 'node:path'; +import { fileURLToPath } from 'node:url'; +import { authedFetch } from './helpers.ts'; + +const __dirname = dirname(fileURLToPath(import.meta.url)); +const fixtureDir = resolve(__dirname, '..'); +const providerSet = Boolean(process.env.EMBEDDING_PROVIDER); + +suite( + 'Step 6 — semantic search', + { skip: providerSet ? false : 'set EMBEDDING_PROVIDER (openai|ollama) to run' }, + (ctx: ContextWithHarper) => { + before(async () => { + await setupHarperWithFixture(ctx, fixtureDir); + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + await api('/Catalog/', { method: 'POST' }); // warms + embeds the catalog + }); + + after(async () => { + await teardownHarper(ctx); + }); + + test('finds products by meaning, ranked by distance', async () => { + const { admin, httpURL } = ctx.harper; + const api = authedFetch(httpURL, admin.username, admin.password); + + const res = await api('/ProductSearch/', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ query: 'makeup for long eyelashes', limit: 5 }), + }); + const rows = (await res.json()) as Array>; + + ok(rows.length > 0 && rows.length <= 5, `expected 1-5 matches, got ${rows.length}`); + ok('$distance' in rows[0], 'results should include a $distance'); + for (let i = 1; i < rows.length; i++) { + ok( + (rows[i - 1].$distance as number) <= (rows[i].$distance as number), + 'results should be ordered by ascending distance', + ); + } + }); + }, +); diff --git a/integrationTests/helpers.ts b/integrationTests/helpers.ts new file mode 100644 index 0000000..d10e5ec --- /dev/null +++ b/integrationTests/helpers.ts @@ -0,0 +1,15 @@ +/** Shared helpers for the integration tests. */ + +export function basicAuth(username: string, password: string): string { + return 'Basic ' + Buffer.from(`${username}:${password}`).toString('base64'); +} + +/** Builds an authed fetch bound to a Harper test instance. */ +export function authedFetch(httpURL: string, username: string, password: string) { + const auth = basicAuth(username, password); + return (path: string, init: RequestInit = {}) => + fetch(`${httpURL}${path}`, { + ...init, + headers: { Authorization: auth, ...(init.headers ?? {}) }, + }); +} diff --git a/package-lock.json b/package-lock.json new file mode 100644 index 0000000..e4cf301 --- /dev/null +++ b/package-lock.json @@ -0,0 +1,6724 @@ +{ + "name": "edge-api-cache-template", + "version": "1.0.0", + "lockfileVersion": 3, + "requires": true, + 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"HARPER_INTEGRATION_TEST_INSTALL_SCRIPT=./node_modules/harper/dist/bin/harper.js HARPER_INTEGRATION_TEST_CONCURRENCY=1 harper-integration-test-run --isolation=none \"integrationTests/**/*.test.ts\"" + }, + "dependencies": { + "harper": "^5.0.11" + }, + "devDependencies": { + "@harperfast/integration-testing": "^0.3.1", + "@types/node": "^22.0.0" + } +} diff --git a/resources.js b/resources.js index ed4c5e4..d99a8d1 100644 --- a/resources.js +++ b/resources.js @@ -1,16 +1,143 @@ -const jokeAPI = { - async get(id) { - const response = await fetch(`https://official-joke-api.appspot.com/jokes/${id}`); - return response.json(); - }, -}; -tables.JokeCache.sourcedFrom(jokeAPI); -export class JokeCache extends tables.JokeCache { +import { Resource, tables } from 'harper'; +import { embed, EMBEDDINGS_ENABLED } from './embeddings.js'; + +/** + * Step 1 — Cache a structured JSON API (the "land"). + * + * `ProductAPI` is the upstream source. Harper calls `get()` only on a cache + * miss or when an entry has gone stale, then stores the structured result in + * the `ProductCache` table. Concurrent misses for the same id are coalesced + * into a single upstream request — cache-stampede protection is built in. + * + * This is the minimally-invasive drop-in: point reads at Harper and every + * request after the first is served locally, at memory speed, close to users. + */ +const UPSTREAM = 'https://dummyjson.com/products'; + +// Project the upstream payload down to the fields we cache. Caching only what +// you need keeps records small and the schema meaningful. +function toProduct(p) { + return { + id: p.id, + title: p.title, + description: p.description, + category: p.category, + brand: p.brand, + price: p.price, + discountPercentage: p.discountPercentage, + rating: p.rating, + stock: p.stock, + tags: p.tags, + }; +} + +class ProductAPI extends Resource { + async get() { + const id = this.getId(); + const response = await fetch(`${UPSTREAM}/${id}`); + if (!response.ok) { + if (response.status === 404) return null; + throw new Error(`Upstream fetch failed (${response.status}) for product ${id}`); + } + return toProduct(await response.json()); + } + + // The upstream is read-only, so write-through is a no-op: warming the cache + // (Step 2) only populates Harper's local copy. If your source accepts writes, + // implement put()/patch() here for true write-through caching. + put() {} +} + +// Wire the upstream source to the cache table. +tables.ProductCache.sourcedFrom(ProductAPI); + +// Exporting the table class publishes its REST endpoints (e.g. /ProductCache/1) +// AND a WebSocket/SSE endpoint at the same path — real-time streaming for free. +export class ProductCache extends tables.ProductCache { + /** + * Step 5 — push invalidation. + * + * When the upstream record changes, tell Harper to drop the cached entry; + * the next read transparently refetches fresh data from the source. The + * write also notifies any WebSocket/SSE subscribers to this record. + * + * POST /ProductCache/5 {"action":"invalidate"} + */ static async post(target, data) { const body = await data; if (body?.action === 'invalidate') { - this.invalidate(target); - return { status: 200, data: { message: 'invalidated' } }; + await this.invalidate(target); + return { status: 'invalidated' }; + } + throw new Error('Unsupported action; send {"action":"invalidate"}'); + } +} + +/** + * Step 2 — Query your cache. + * + * Read-through caching populates one record per request. To make the *whole* + * catalog queryable, warm it once from the upstream collection endpoint. After + * this runs, the cache is a queryable table: filter, sort, and paginate it with + * Harper's REST query language — even though the origin API never exposed those + * capabilities. + * + * POST /Catalog/ -> loads the full catalog into ProductCache + * GET /ProductCache/?price=le=50&sort(-rating)&limit(10)&select(title,price) + */ +const CATALOG_URL = `${UPSTREAM}?limit=0`; +const CATEGORIES_URL = `${UPSTREAM}/categories`; + +export class Catalog extends Resource { + async post() { + const response = await fetch(CATALOG_URL); + if (!response.ok) { + throw new Error(`Catalog fetch failed (${response.status})`); + } + const { products } = await response.json(); + for (const product of products) { + const record = toProduct(product); + // Step 6 — embed each product so it can be found by meaning, not just + // keywords. Skipped automatically when no provider is configured. + if (EMBEDDINGS_ENABLED) { + record.embedding = await embed(`${record.title}. ${record.description}`); + } + await tables.ProductCache.put(record); + } + + // Step 4 — warm the category resource so products can be joined to it. + const categories = await (await fetch(CATEGORIES_URL)).json(); + for (const category of categories) { + await tables.CategoryCache.put(category); + } + + return { loaded: products.length, categories: categories.length }; + } +} + +/** + * Step 6 — Vector (semantic search over your cache). + * + * The same cached records, now searchable by meaning. Embed the query, run an + * HNSW nearest-neighbor search over the products, and return the closest matches + * with their similarity `$distance`. No separate vector database required. + * + * POST /ProductSearch/ {"query": "something to keep my drink cold", "limit": 5} + */ +export class ProductSearch extends Resource { + async post(data) { + const body = await data; + if (!body?.query) { + throw new Error('Provide {"query": "..."}'); + } + if (!EMBEDDINGS_ENABLED) { + throw new Error('Set EMBEDDING_PROVIDER (openai|ollama) and re-warm the catalog to enable vector search'); } + const target = await embed(body.query); + return tables.ProductCache.search({ + select: ['id', 'title', 'category', 'price', '$distance'], + sort: { attribute: 'embedding', target }, + limit: body.limit ?? 5, + }); } } diff --git a/schema.graphql b/schema.graphql index ccd7c37..2eef345 100644 --- a/schema.graphql +++ b/schema.graphql @@ -1,5 +1,38 @@ -type JokeCache @table(expiration: 60) { - id: ID @primaryKey - setup: String - punchline: String +# ProductCache mirrors records from an upstream products API. `expiration` +# sets a 1-hour TTL: Harper serves reads from the cache and lazily refetches +# an entry from the source once it goes stale. +# +# Step 2 adds `@indexed` to the fields we filter and sort on. +# Step 3 adds `@computed` fields that reshape upstream data at read time. +# Step 4 adds a `@relationship` so two cached resources can be joined. +# Step 6 adds an HNSW vector index for semantic search. +type ProductCache @table(expiration: 3600) { + id: Int @primaryKey + title: String + description: String + category: String @indexed + brand: String @indexed + price: Float @indexed + discountPercentage: Float + rating: Float @indexed + stock: Int + tags: [String] + + # Step 3 — derived fields, computed on read. + salePrice: Float @computed(from: "price - price * (discountPercentage || 0) / 100") + inStock: Boolean @computed(from: "stock > 0") + + # Step 4 — join to the category resource by its slug. + categoryInfo: CategoryCache @relationship(from: "category") + + # Step 6 — vector embedding for semantic search. Populated during catalog + # warm-up when an embedding provider is configured (see embeddings.js). + embedding: [Float] @indexed(type: "HNSW", distance: "cosine") +} + +# A second cached resource. Products reference it by `category` (the slug). +type CategoryCache @table(expiration: 86400) { + slug: ID @primaryKey + name: String + url: String } diff --git a/tsconfig.json b/tsconfig.json new file mode 100644 index 0000000..e31351e --- /dev/null +++ b/tsconfig.json @@ -0,0 +1,13 @@ +{ + "compilerOptions": { + "target": "ES2022", + "module": "NodeNext", + "moduleResolution": "NodeNext", + "strict": true, + "allowImportingTsExtensions": true, + "noEmit": true, + "erasableSyntaxOnly": true, + "types": ["node"] + }, + "include": ["integrationTests/**/*.ts"] +}