*: v2 support (#13)

This PR contains:

* Everything you need to do a v2 txt2img generation
* Automatic testing with Actions
* Updated `README.md`

.github/workflows/validate.yml

@@ -1,18 +1,22 @@
-name: Validate Formatting & Types
+name: Formatting, Types, & Test
 
 on: [push, pull_request]
 
 jobs:
-  validate:
-    runs-on: ubuntu-latest
-
-    steps:
-      - uses: actions/checkout@v3
+    validate:
+        runs-on: ubuntu-latest
 
-      - uses: denoland/setup-deno@v1
-        with:
-          deno-version: v1.x
+        steps:
+            - uses: actions/checkout@v3
 
-      - run: deno fmt --check
+            - uses: denoland/setup-deno@v1
+              with:
+                  deno-version: v1.x
 
-      - run: deno check prodia.ts
+            - run: deno fmt --check
+
+            - run: deno check prodia.ts
+
+            - run: deno test --allow-env --allow-net
+              env:
+                  PRODIA_TOKEN: ${{ secrets.PRODIA_TOKEN }}

readme.md

@@ -5,8 +5,8 @@
 
 Official TypeScript library for Prodia's AI inference API.
 
-- [Get an API Key](https://app.prodia.com/api)
-
+- [Get an v1 API Key or v2 Token](https://app.prodia.com/api)
+- [v2 API Explorer](https://app.prodia.com/explorer)
 - [View Docs + Pricing](https://docs.prodia.com/reference/getting-started)
 
 ## Usage
@@ -15,6 +15,34 @@ Official TypeScript library for Prodia's AI inference API.
 npm install prodia --save
 ```
 
+## v2
+
+As of _October 2024_, we require users to have a **Pro+** or **Enterprise** subscription with us to use our v2 API. This is to ensure quality of service. However, we expect to revisit this by EOY and make it available more broadly.
+
+```javascript
+import { createProdia } from "prodia/v2"; // v2 :)
+
+const prodia = createProdia({
+	token: "...", // grab a token from https://app.prodia.com/api
+});
+
+(async () => {
+	// run a flux dev generation
+	const job = await client.job({
+		"type": "inference.flux.dev.txt2img.v1",
+		"config": {
+			"prompt": "puppies in a cloud, 4k",
+			"steps": 25,
+		},
+	});
+
+	const image = await job.arrayBuffer();
+	// display your image
+})();
+```
+
+## v1 Legacy API
+
 ```javascript
 import { createProdia } from "prodia";
 
@@ -32,3 +60,7 @@ const prodia = createProdia({
 	// check status and view your image :)
 })();
 ```
+
+## help
+
+Email us at [[email protected]](mailto:[email protected]).

test/v2.test.ts

@@ -0,0 +1,34 @@
+import { assertEquals } from "jsr:@std/assert";
+import { createProdia } from "../v2/index.ts";
+
+const token = Deno.env.get("PRODIA_TOKEN");
+
+if (typeof token !== "string") {
+	throw new Error("PRODIA_TOKEN is not set");
+}
+
+const isJpeg = (image: ArrayBuffer): boolean => {
+	const view = new Uint8Array(image);
+
+	return view[0] === 0xFF && view[1] === 0xD8;
+};
+
+await Deno.test("Example Job: JPEG Output", async () => {
+	const client = createProdia({
+		token,
+	});
+
+	const job = await client.job({
+		"type": "inference.flux.dev.txt2img.v1",
+		"config": {
+			"prompt": "puppies in a cloud, 4k",
+			"steps": 1,
+			"width": 1024,
+			"height": 1024,
+		},
+	});
+
+	const image = await job.arrayBuffer();
+
+	assertEquals(isJpeg(image), true, "Image should be a JPEG");
+});

tsconfig.json

@@ -11,5 +11,5 @@
 		"baseUrl": ".",
 		"declaration": true
 	},
-	"files": ["prodia.ts"]
+	"files": ["prodia.ts", "v2/index.ts"]
 }

v2/index.ts

@@ -0,0 +1,117 @@
+type JsonObject =
+	& { [Key in string]: JsonValue }
+	& { [Key in string]?: JsonValue | undefined };
+type JsonArray = JsonValue[] | readonly JsonValue[];
+type JsonPrimitive = string | number | boolean | null;
+type JsonValue = JsonPrimitive | JsonObject | JsonArray;
+
+/* job and job configuration */
+
+export type ProdiaJob = Record<string, JsonValue>;
+
+export type ProdiaJobOptions = {
+	accept:
+		| "image/png"
+		| "image/jpeg"
+		| "image/webp"
+		| "multipart/form-data"
+		| "video/mp4";
+};
+
+const defaultJobOptions: ProdiaJobOptions = {
+	accept: "image/jpeg",
+};
+
+export type ProdiaJobResponse = {
+	arrayBuffer: () => Promise<ArrayBuffer>; // we only support direct image response now
+};
+
+/* client & client configuration*/
+
+export type Prodia = {
+	job: (
+		params: ProdiaJob,
+		options?: Partial<ProdiaJobOptions>,
+	) => Promise<ProdiaJobResponse>;
+};
+
+export type CreateProdiaOptions = {
+	token: string;
+	baseUrl?: string;
+	maxErrors?: number;
+	maxRetries?: number;
+};
+
+/* error types */
+
+export class ProdiaCapacityError extends Error {}
+export class ProdiaBadResponseError extends Error {}
+
+export const createProdia = ({
+	token,
+	baseUrl = "https://inference.prodia.com/v2",
+	maxErrors = 1,
+	maxRetries = Infinity,
+}: CreateProdiaOptions): Prodia => {
+	const job = async (
+		params: ProdiaJob,
+		_options?: Partial<ProdiaJobOptions>,
+	) => {
+		const options = {
+			...defaultJobOptions,
+			..._options,
+		};
+
+		let response: Response;
+
+		let errors = 0;
+		let retries = 0;
+
+		do {
+			response = await fetch(`${baseUrl}/job`, {
+				method: "POST",
+				headers: {
+					"Authorization": `Bearer ${token}`,
+					"Accept": options.accept,
+					"Content-Type": "application/json",
+				},
+				body: JSON.stringify(params),
+			});
+
+			if (response.status === 429) {
+				retries += 1;
+			} else if (response.status < 200 || response.status > 299) {
+				errors += 1;
+			}
+
+			const retryAfter = Number(response.headers.get("Retry-After")) || 1;
+			await new Promise((resolve) =>
+				setTimeout(resolve, retryAfter * 1000)
+			);
+		} while (
+			(response.status < 200 || response.status > 299) &&
+			errors <= maxErrors &&
+			retries <= maxRetries
+		);
+
+		if (response.status === 429) {
+			throw new ProdiaCapacityError(
+				"ProdiaCapacityError: Unable to schedule job with current token",
+			);
+		}
+
+		if (response.status < 200 || response.status > 299) {
+			throw new ProdiaBadResponseError(
+				`ProdiaBadResponseError: ${response.status} ${response.statusText}`,
+			);
+		}
+
+		return {
+			arrayBuffer: () => response.arrayBuffer(),
+		};
+	};
+
+	return {
+		job,
+	};
+};