@aigur/client - npm Package Compare versions

Comparing version 0.30.0 to 0.30.1

819

dist/index.js

		@@ -1,812 +0,7 @@
		var __defProp = Object.defineProperty;
		var __getOwnPropDesc = Object.getOwnPropertyDescriptor;
		var __getOwnPropNames = Object.getOwnPropertyNames;
		var __hasOwnProp = Object.prototype.hasOwnProperty;
		var __export = (target, all) => {
		for (var name in all)
		__defProp(target, name, { get: all[name], enumerable: true });
		};
		var __copyProps = (to, from, except, desc) => {
		if (from && typeof from === "object" \|\| typeof from === "function") {
		for (let key of __getOwnPropNames(from))
		if (!__hasOwnProp.call(to, key) && key !== except)
		__defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) \|\| desc.enumerable });
		}
		return to;
		};
		var __toCommonJS = (mod) => __copyProps(__defProp({}, "__esModule", { value: true }), mod);

		// src/index.ts
		var src_exports = {};
		__export(src_exports, {
		createClient: () => createClient
		});
		module.exports = __toCommonJS(src_exports);

		// src/makeid.ts
		function makeid(length = 16) {
		let result = "";
		const characters = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789";
		const charactersLength = characters.length;
		for (let i = 0; i < length; i++) {
		result += characters.charAt(Math.floor(Math.random() * charactersLength));
		}
		return result;
		}

		// src/getInputByContext.ts
		function getInputByContext(inputPlaceholders, values) {
		if (typeof inputPlaceholders === "string") {
		return handleSingleValue(inputPlaceholders);
		}
		const input = { ...inputPlaceholders };
		return getInputContextInner(input);
		function getInputContextInner(input2) {
		for (const key in input2) {
		input2[key] = handleSingleValue(input2[key]);
		}
		return input2;
		}
		function handleSingleValue(value) {
		if (Array.isArray(value)) {
		return value.map((item) => getInputContextInner(item));
		}
		if (typeof value === "object" && value !== null) {
		return getInputContextInner(value);
		}
		let newValue = value;
		const contextReferences = getContextReferences(value);
		for (let ref of contextReferences) {
		const contextValue = values[ref.nodeId];
		const propertyValue = contextValue[ref.property];
		if (propertyValue instanceof ArrayBuffer) {
		newValue = propertyValue;
		continue;
		}
		newValue = newValue?.replace(new RegExp(escapeRegExp(ref.value)), propertyValue);
		if (newValue === "undefined") {
		newValue = void 0;
		} else if (newValue !== propertyValue && newValue === propertyValue.toString()) {
		newValue = propertyValue;
		}
		}
		return newValue;
		}
		function getContextReferences(value) {
		if (typeof value !== "string")
		return [];
		const contextRegex = /\$context\.(\d+\|input)\.(\w+)\$/g;
		const matches = value.matchAll(contextRegex);
		const references = [];
		for (let match of matches) {
		references.push({
		value: match[0],
		nodeId: match[1],
		property: match[2]
		});
		}
		return references;
		}
		function escapeRegExp(string) {
		return string.replace(/[.*+?^${}()\|[\]\\]/g, "\\$&");
		}
		}

		// src/delay.ts
		function delay(time) {
		return new Promise((resolve) => setTimeout(resolve, time));
		}

		// src/Pipeline.ts
		var DEFAULT_RETRIES = 2;
		var RETRY_DELAY_IN_MS = 350;
		var Pipeline = class {
		constructor(conf, flow, apiKeys) {
		this.conf = conf;
		this.flow = flow;
		this.apiKeys = apiKeys;
		this.onProgressListeners = /* @__PURE__ */ new Map();
		this.onStartListeners = /* @__PURE__ */ new Map();
		this.onFinishListeners = /* @__PURE__ */ new Map();
		this.vercel = {
		invoke: (input) => {
		return this.invokeRemote(`/api/pipelines/${this.conf.id}`, input);
		},
		invokeStream: (input, cb) => {
		return this.invokeStream(`/api/pipelines/${this.conf.id}`, input, cb);
		}
		};
		this.listenToEvents();
		}
		invoke(input) {
		return this.processPipeline(this.conf, input);
		}
		invokeRemote(endpoint2, input) {
		return fetch(endpoint2, {
		method: "POST",
		headers: {
		"Content-Type": "application/json"
		},
		body: JSON.stringify(input)
		}).then((res) => res.json());
		}
		async invokeStream(endpoint2, input, cb) {
		const response = await fetch(endpoint2, {
		method: "POST",
		headers: {
		"Content-Type": "application/json"
		},
		body: JSON.stringify(input)
		});
		if (!response.ok) {
		throw new Error(response.statusText);
		}
		const data = response.body;
		if (!data) {
		return;
		}
		const reader = data.getReader();
		const decoder = new TextDecoder();
		let done = false;
		while (!done) {
		const { value, done: doneReading } = await reader.read();
		done = doneReading;
		const chunkValue = decoder.decode(value);
		cb(chunkValue);
		}
		}
		onProgress(cb) {
		const id = makeid();
		this.onProgressListeners.set(id, cb);
		return () => {
		this.onProgressListeners.delete(id);
		};
		}
		onStart(cb) {
		const id = makeid();
		this.onStartListeners.set(id, cb);
		return () => {
		this.onStartListeners.delete(id);
		};
		}
		onFinish(cb) {
		const id = makeid();
		this.onFinishListeners.set(id, cb);
		return () => {
		this.onFinishListeners.delete(id);
		};
		}
		listenToEvents() {
		if (!this.conf.updateProgress \|\| typeof window === "undefined" \|\| !this.apiKeys?.ablySubscribe) {
		return;
		}
		const dataEndpoint = `https://realtime.ably.io/event-stream?channels=aigur-client&v=1.2&key=${this.apiKeys.ablySubscribe}&enveloped=false`;
		const eventSource = new EventSource(dataEndpoint);
		eventSource.onmessage = (event) => {
		const e = JSON.parse(event.data);
		if (e.type === "pipeline:start") {
		this.triggerListeners(this.onStartListeners);
		} else if (e.type === "pipeline:finish") {
		this.triggerListeners(this.onFinishListeners);
		} else if (e.type === "node:start" \|\| e.type === "node:finish") {
		this.triggerListeners(this.onProgressListeners, { ...e.data, type: e.type });
		}
		};
		}
		triggerListeners(listeners, ...args) {
		for (let listener of listeners.values()) {
		listener(...args);
		}
		}
		async processPipeline(pipeline, input) {
		const retriesCount = this.conf.retries ?? DEFAULT_RETRIES;
		try {
		await this.notifyEvent("pipeline:start");
		pipeline.input.parse(input);
		const values = { input };
		let output = {};
		const nodes = this.flow.getNodes();
		let startProgressPromise;
		for (let i = 0; i < nodes.length; i++) {
		startProgressPromise = this.notifyEvent("node:start", { node: nodes[i], index: i });
		let attemptCount = 0;
		let isSuccess = false;
		do {
		attemptCount++;
		try {
		output = await this.executeAction(nodes, i, values);
		values[i] = output;
		isSuccess = true;
		} catch (e) {
		if (attemptCount > retriesCount) {
		throw e;
		}
		await delay((this.conf.retryDelayInMs ?? RETRY_DELAY_IN_MS) * attemptCount);
		}
		} while (!isSuccess && attemptCount <= retriesCount);
		await startProgressPromise;
		await this.notifyEvent("node:finish", { node: nodes[i], index: i });
		}
		await this.notifyEvent("pipeline:finish");
		return output;
		} catch (e) {
		console.error(e);
		throw e;
		}
		}
		async executeAction(nodes, index, values) {
		const { action: action10, schema, input } = nodes[index];
		const inputByContext = getInputByContext(input, values);
		return action10(inputByContext, this.apiKeys);
		}
		notifyEvent(type, data) {
		if (!this.conf.updateProgress \|\| !this.apiKeys.ablyPublish) {
		return;
		}
		return fetch("https://rest.ably.io/channels/aigur-client/messages?enveloped=false ", {
		method: "POST",
		headers: {
		"Content-Type": "application/json",
		Authorization: `Basic ${btoa(this.apiKeys.ablyPublish)}`
		},
		body: JSON.stringify({
		type,
		data
		})
		});
		}
		};

		// src/nodes/text/prediction/gpt3.stream.ts
		var import_zod2 = require("zod");
		var import_eventsource_parser = require("eventsource-parser");

		// src/nodes/text/prediction/gpt3.ts
		var import_zod = require("zod");
		var inputSchema = import_zod.z.object({
		prompt: import_zod.z.string(),
		model: import_zod.z.string().default("text-davinci-003"),
		temperature: import_zod.z.number().default(0.7),
		top_p: import_zod.z.number().default(1),
		frequency_penalty: import_zod.z.number().default(0),
		presence_penalty: import_zod.z.number().default(0),
		max_tokens: import_zod.z.number().default(200),
		n: import_zod.z.number().default(1)
		});
		var outputSchema = import_zod.z.object({
		text: import_zod.z.string()
		});
		async function action(input, apiKeys) {
		const payload = inputSchema.parse(input);
		const response = await fetch("https://api.openai.com/v1/completions", {
		headers: {
		"Content-Type": "application/json",
		Authorization: `Bearer ${apiKeys.openai}`
		},
		method: "POST",
		body: JSON.stringify(payload)
		});
		const output = await response.json();
		return { text: output.choices[0]?.text.replace(/^(?:\n)+/gm, "") };
		}
		var gpt3PredictionNode = {
		id: "text.prediction.gpt3",
		schema: {
		input: inputSchema,
		output: outputSchema
		},
		action
		};

		// src/nodes/text/prediction/gpt3.stream.ts
		var inputSchema2 = inputSchema.merge(
		import_zod2.z.object({
		stream: import_zod2.z.literal(true).optional().default(true)
		})
		);
		var outputSchema2 = import_zod2.z.object({ stream: import_zod2.z.instanceof(globalThis.ReadableStream ?? Object) });
		async function action2(input, apiKeys) {
		const payload = inputSchema2.parse(input);
		const response = await fetch("https://api.openai.com/v1/completions", {
		headers: {
		"Content-Type": "application/json",
		Authorization: `Bearer ${apiKeys.openai}`
		},
		method: "POST",
		body: JSON.stringify(payload)
		});
		const stream = await OpenAIStream(response);
		return { stream };
		}
		var gpt3PredictionStreamNode = {
		id: "text.prediction.gpt3.stream",
		schema: {
		input: inputSchema2,
		output: outputSchema2
		},
		action: action2
		};
		async function OpenAIStream(response) {
		const encoder = new TextEncoder();
		const decoder = new TextDecoder();
		let counter = 0;
		const stream = new ReadableStream({
		async start(controller) {
		function onParse(event) {
		if (event.type === "event") {
		const data = event.data;
		if (data === "[DONE]") {
		controller.close();
		return;
		}
		try {
		const json = JSON.parse(data);
		const text = json.choices[0].text;
		if (counter < 2 && (text.match(/\n/) \|\| []).length) {
		return;
		}
		const queue = encoder.encode(text);
		controller.enqueue(queue);
		counter++;
		} catch (e) {
		controller.error(e);
		}
		}
		}
		const parser = (0, import_eventsource_parser.createParser)(onParse);
		for await (const chunk of response.body) {
		parser.feed(decoder.decode(chunk));
		}
		}
		});
		return stream;
		}

		// src/nodes/output/output.ts
		var import_zod3 = require("zod");
		var outputNode = () => ({
		id: "output",
		schema: {
		input: import_zod3.z.object({}),
		output: import_zod3.z.object({})
		},
		async action(input) {
		return input;
		}
		});

		// src/nodes/image/labeling/googleVision.ts
		var import_zod4 = require("zod");
		var inputSchema3 = import_zod4.z.object({
		image: import_zod4.z.string()
		// base64
		});
		var outputSchema3 = import_zod4.z.object({
		labels: import_zod4.z.array(import_zod4.z.string())
		});
		async function action3(input, apiKeys) {
		const payload = inputSchema3.parse(input);
		const endpoint2 = `https://vision.googleapis.com/v1/images:annotate?key=${apiKeys.googleapis}`;
		const request = {
		requests: [
		{
		image: {
		content: payload.image
		},
		features: [
		{
		type: "LABEL_DETECTION"
		}
		]
		}
		]
		};
		const response = await fetch(endpoint2, {
		method: "POST",
		body: JSON.stringify(request)
		});
		const data = await response.json();
		return {
		labels: data.responses[0].labelAnnotations.map((label) => label.description)
		};
		}
		var googleVisionNode = {
		id: "image.labeling.googleVision",
		schema: {
		input: inputSchema3,
		output: outputSchema3
		},
		action: action3
		};

		// src/nodes/image/textToImage/stability.ts
		var import_zod5 = require("zod");
		var inputSchema4 = import_zod5.z.object({
		text_prompts: import_zod5.z.array(
		import_zod5.z.object({
		text: import_zod5.z.string(),
		weight: import_zod5.z.number().min(-1).max(1).optional().default(1)
		})
		).refine((val) => val.length > 0, "Must have at least one text prompt"),
		model: import_zod5.z.enum(["stable-diffusion-v1-5", "stable-diffusion-512-v2-1", "stable-diffusion-768-v2-1"]).optional().default("stable-diffusion-v1-5"),
		clip_guidance_preset: import_zod5.z.enum(["NONE", "FAST_BLUE", "FAST_GREEN", "SIMPLE", "SLOW", "SLOWER", "SLOWEST"]).optional(),
		steps: import_zod5.z.number().optional(),
		sampler: import_zod5.z.enum(["one", "two"]).optional(),
		samples: import_zod5.z.number().optional(),
		cfg_scale: import_zod5.z.number().optional(),
		seed: import_zod5.z.number().optional(),
		height: import_zod5.z.number().min(128).optional().refine(
		(val) => typeof val !== "undefined" ? val % 64 === 0 : true,
		"Must be a multiple of 64"
		),
		width: import_zod5.z.number().min(128).optional().refine(
		(val) => typeof val !== "undefined" ? val % 64 === 0 : true,
		"Must be a multiple of 64"
		)
		});
		var outputSchema4 = import_zod5.z.object({
		result: import_zod5.z.instanceof(ArrayBuffer)
		});
		async function action4(input, apiKeys) {
		const payload = inputSchema4.parse(input);
		const endpoint2 = `https://api.stability.ai/v1beta/generation/${payload.model}/text-to-image`;
		const response = await fetch(endpoint2, {
		headers: {
		"Content-Type": "application/json",
		Accept: "image/png",
		Authorization: apiKeys.stability
		},
		method: "POST",
		body: JSON.stringify(payload)
		});
		const image = await response.arrayBuffer();
		return {
		result: image
		};
		}
		var stabilityTextToImageNode = {
		id: "image.textToImage.stableDiffusion.stability",
		schema: {
		input: inputSchema4,
		output: outputSchema4
		},
		action: action4
		};

		// src/nodes/text/modify/enhanceWithKeywords.ts
		var import_zod6 = require("zod");
		var inputSchema5 = import_zod6.z.object({
		text: import_zod6.z.string(),
		amount: import_zod6.z.number().optional().default(8)
		});
		var outputSchema5 = import_zod6.z.object({
		text: import_zod6.z.string()
		});
		var examples = {
		"Colonial-style home": "Colonial, traditional, classic, historical, timeless, elegant, regal, grand, spacious, architectural, wood-framed, brick-exterior, symmetrical, gabled roof, columns, portico, fireplace, formal, ornate, landscaped".split(
		", "
		),
		"High-end penthouse apartment": "Luxury, high-end, penthouse, apartment, upscale, contemporary, modern, stylish, designer, elite, high-rise, rooftop, panoramic, views, spacious, open-plan, top-floor, amenities, concierge, service, exclusive".split(
		", "
		)
		};
		function getExamples(amountOfKeys) {
		return Object.entries(examples).map(
		([key, value]) => `Title: ${key}
		Description: ${value.slice(0, amountOfKeys).join(", ")}
		`
		).join("\n");
		}
		async function action5(input) {
		const payload = inputSchema5.parse(input);
		const enhancedText = `Write a maximum of ${payload.amount} keywords in a csv list that describes the following
		${getExamples(payload.amount)}
		Title: ${payload.text}
		Description:`;
		return {
		text: enhancedText
		};
		}
		var enhanceWithKeywordsNode = {
		id: "text.modify.enhanceWithKeywords",
		schema: {
		input: inputSchema5,
		output: outputSchema5
		},
		action: action5
		};

		// src/nodes/text/modify/simple.ts
		var import_zod7 = require("zod");
		var inputSchema6 = import_zod7.z.object({
		text: import_zod7.z.string().or(import_zod7.z.array(import_zod7.z.string())),
		modifier: import_zod7.z.string()
		});
		var outputSchema6 = import_zod7.z.object({
		text: import_zod7.z.string()
		});
		async function action6(input) {
		const payload = inputSchema6.parse(input);
		return {
		text: payload.modifier.replace(
		/\$$text$\$/gm,
		Array.isArray(payload.text) ? payload.text.join(", ") : payload.text
		)
		};
		}
		var simpleModificationNode = {
		id: "text.modify.simple",
		schema: {
		input: inputSchema6,
		output: outputSchema6
		},
		action: action6
		};

		// src/nodes/voice/transcribe/whisper/whisperapi.ts
		var import_zod8 = require("zod");
		var endpoint = "https://transcribe.whisperapi.com";
		var inputSchema7 = import_zod8.z.object({
		audioUrl: import_zod8.z.string().url()
		});
		var outputSchema7 = import_zod8.z.object({
		text: import_zod8.z.string()
		});
		async function action7(input, apiKeys) {
		const payload = inputSchema7.parse(input);
		const form = new FormData();
		form.append("url", payload.audioUrl);
		form.append("language", "en");
		form.append("fileType", "mp3");
		form.append("task", "transcribe");
		const result = await fetch(endpoint, {
		method: "POST",
		headers: {
		contentType: "application/json",
		Authorization: "Bearer " + apiKeys.whisperapi
		},
		body: form
		});
		if (!result.ok) {
		throw new Error(result.statusText);
		}
		const data = await result.json();
		return { text: data.text.trim() };
		}
		var whisperApiNode = {
		id: "voice.transcribe.whisper.whisperapi",
		schema: {
		input: inputSchema7,
		output: outputSchema7
		},
		action: action7
		};

		// src/nodes/transformation/stringToArrayBuffer.ts
		var import_zod9 = require("zod");
		var inputSchema8 = import_zod9.z.object({
		string: import_zod9.z.string()
		});
		var outputSchema8 = import_zod9.z.object({
		arrayBuffer: import_zod9.z.instanceof(ArrayBuffer)
		});
		async function action8(input) {
		const payload = inputSchema8.parse(input);
		const typedArray = Uint8Array.from(atob(payload.string), (c) => c.charCodeAt(0));
		return {
		arrayBuffer: typedArray.buffer
		};
		}
		var stringToArrayBufferNode = {
		id: "text.transformation.stringToArrayBuffer",
		schema: {
		input: inputSchema8,
		output: outputSchema8
		},
		action: action8
		};

		// src/nodes/voice/textToSpeech/googleTextToSpeech.ts
		var import_zod10 = require("zod");
		var inputSchema9 = import_zod10.z.object({
		text: import_zod10.z.string(),
		speakingRate: import_zod10.z.number().min(0.25).max(4).optional().default(1),
		pitch: import_zod10.z.number().min(-20).max(20).optional().default(0),
		encoding: import_zod10.z.enum([
		"MP3",
		"FLAC",
		"LINEAR16",
		"MULAW",
		"AMR",
		"AMR_WB",
		"OGG_OPUS",
		"SPEEX_WITH_HEADER_BYTE",
		"WEBM_OPUS"
		]).optional().default("MP3"),
		voice: import_zod10.z.object({
		language: import_zod10.z.string().optional().default("en-US"),
		name: import_zod10.z.enum([
		"en-US-Standard-A",
		"en-US-Standard-C",
		"en-US-Standard-D",
		"en-US-Standard-E",
		"en-US-Standard-F",
		"en-US-Standard-G",
		"en-US-Standard-H",
		"en-US-Standard-I",
		"en-US-Standard-J",
		"en-US-Studio-M",
		"en-US-Studio-O",
		"en-US-Wavenet-A",
		"en-US-Wavenet-B",
		"en-US-Wavenet-C",
		"en-US-Wavenet-D",
		"en-US-Wavenet-E",
		"en-US-Wavenet-F",
		"en-US-Wavenet-G",
		"en-US-Wavenet-H",
		"en-US-Wavenet-I",
		"en-US-Wavenet-J",
		"en-US-News-K",
		"en-US-News-L",
		"en-US-News-M",
		"en-US-News-N",
		"en-US-Standard-A",
		"en-US-Standard-B",
		"en-US-Standard-C",
		"en-US-Standard-D",
		"en-US-Standard-E",
		"en-US-Standard-F",
		"en-US-Standard-G",
		"en-US-Standard-H",
		"en-US-Standard-I",
		"en-US-Standard-J"
		]).or(import_zod10.z.string()).optional().default("en-US-Neural2-C")
		}).optional().default({
		language: "en-US",
		name: "en-US-Neural2-C"
		})
		});
		var outputSchema9 = import_zod10.z.object({
		audio: import_zod10.z.string()
		// base64
		});
		async function action9(input, apiKeys) {
		const parsedInput = inputSchema9.parse(input);
		const endpoint2 = `https://us-central1-texttospeech.googleapis.com/v1beta1/text:synthesize?key=${apiKeys.googleapis}`;
		const payload = {
		input: {
		text: parsedInput.text
		},
		voice: {
		languageCode: parsedInput.voice.language,
		name: parsedInput.voice.name
		},
		audioConfig: {
		audioEncoding: parsedInput.encoding,
		speakingRate: parsedInput.speakingRate,
		pitch: parsedInput.pitch
		}
		};
		const result = await fetch(endpoint2, {
		method: "POST",
		headers: {
		"Content-Type": "application/json"
		},
		body: JSON.stringify(payload)
		});
		const data = await result.json();
		return {
		audio: data.audioContent
		};
		}
		var googleTextToSpeechNode = {
		id: "voice.textToSpeech.google",
		schema: {
		input: inputSchema9,
		output: outputSchema9
		},
		action: action9
		};

		// src/builder.ts
		var Builder = class {
		constructor(input, nodes) {
		this.input = input;
		this.nodes = nodes;
		this.voice = {
		textToSpeech: {
		google: this.nodeFactory(googleTextToSpeechNode)
		},
		transcribe: {
		whisper: {
		whisperapi: this.nodeFactory(whisperApiNode)
		}
		}
		};
		this.text = {
		modify: {
		enhanceWithKeywords: this.nodeFactory(enhanceWithKeywordsNode),
		simple: this.nodeFactory(simpleModificationNode)
		},
		prediction: {
		gpt3: this.nodeFactory(gpt3PredictionNode),
		gpt3Stream: this.nodeFactory(gpt3PredictionStreamNode)
		}
		};
		this.image = {
		textToImage: {
		stableDiffusion: {
		stability: this.nodeFactory(stabilityTextToImageNode)
		}
		},
		labeling: {
		googleVision: this.nodeFactory(googleVisionNode)
		}
		};
		this.output = this.nodeFactory(outputNode());
		this.transformation = {
		stringToArrayBuffer: this.nodeFactory(stringToArrayBufferNode)
		};
		}
		static create(input) {
		return new Builder(input, []);
		}
		nodeFactory(nodeDefinition) {
		return (getUserInput) => {
		const input = this.setPlaceholderValues(this.input.keyof().options, "input");
		const prev = this.nodes.length > 0 ? this.nodes[this.nodes.length - 1] : input;
		const node = {
		...nodeDefinition,
		input: getUserInput({
		nodes: this.nodes,
		prev: prev.output,
		input
		}),
		output: nodeDefinition.schema.output.keyof ? this.setPlaceholderValues(
		nodeDefinition.schema.output.keyof().options,
		this.nodes.length
		) : nodeDefinition.schema.output
		};
		this.nodes.push(node);
		return this;
		};
		}
		setPlaceholderValues(outputKeys, index) {
		const placeholderedOutput = {};
		for (let key of outputKeys) {
		placeholderedOutput[key] = `$context.${index}.${key}$`;
		}
		return placeholderedOutput;
		}
		custom(node) {
		return this.nodeFactory(node);
		}
		getNodes() {
		return this.nodes;
		}
		};

		// src/Aigur.ts
		var DEFAULT_RETRIES2 = 2;
		var RETRY_DELAY_IN_MS2 = 350;
		var createClient = (opts) => {
		const { apiKeys } = opts;
		return {
		pipeline: {
		create: (conf) => {
		const pipelineConf = {
		...conf,
		retries: conf.retries ?? DEFAULT_RETRIES2,
		retryDelayInMs: conf.retryDelayInMs ?? RETRY_DELAY_IN_MS2
		};
		const flow = conf.flow(new Builder(conf.input, []));
		return new Pipeline(pipelineConf, flow, apiKeys);
		}
		}
		};
		};
		// Annotate the CommonJS export names for ESM import in node:
		0 && (module.exports = {
		createClient
		});
		var A=Object.defineProperty;var H=Object.getOwnPropertyDescriptor;var q=Object.getOwnPropertyNames;var Y=Object.prototype.hasOwnProperty;var X=(n,e)=>{for(var t in e)A(n,t,{get:e[t],enumerable:!0})},Q=(n,e,t,o)=>{if(e&&typeof e=="object"\|\|typeof e=="function")for(let i of q(e))!Y.call(n,i)&&i!==t&&A(n,i,{get:()=>e[i],enumerable:!(o=H(e,i))\|\|o.enumerable});return n};var ee=n=>Q(A({},"__esModule",{value:!0}),n);var Oe={};X(Oe,{createClient:()=>Te});module.exports=ee(Oe);function P(n=16){let e="",t="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789",o=t.length;for(let i=0;i<n;i++)e+=t.charAt(Math.floor(Math.random()o));return e}function k(n,e){if(typeof n=="string")return i(n);let t={...n};return o(t);function o(a){for(let r in a)a[r]=i(a[r]);return a}function i(a){if(Array.isArray(a))return a.map(u=>o(u));if(typeof a=="object"&&a!==null)return o(a);let r=a,d=s(a);for(let u of d){let y=e[u.nodeId][u.property];if(y instanceof ArrayBuffer){r=y;continue}r=r?.replace(new RegExp(c(u.value)),y),r==="undefined"?r=void 0:r!==y&&r===y.toString()&&(r=y)}return r}function s(a){if(typeof a!="string")return[];let r=/\$context\.(\d+\|input)\.(\w+)\$/g,d=a.matchAll(r),u=[];for(let f of d)u.push({value:f[0],nodeId:f[1],property:f[2]});return u}function c(a){return a.replace(/[.+?^${}()\|[\]\\]/g,"\\$&")}}function D(n){return new Promise(e=>setTimeout(e,n))}var te=2,ne=350,w=class{constructor(e,t,o){this.conf=e;this.flow=t;this.apiKeys=o;this.onProgressListeners=new Map;this.onStartListeners=new Map;this.onFinishListeners=new Map;this.vercel={invoke:e=>this.invokeRemote(`/api/pipelines/${this.conf.id}`,e),invokeStream:(e,t)=>this.invokeStream(`/api/pipelines/${this.conf.id}`,e,t)};this.listenToEvents()}invoke(e){return this.processPipeline(this.conf,e)}invokeRemote(e,t){return fetch(e,{method:"POST",headers:{"Content-Type":"application/json"},body:JSON.stringify(t)}).then(o=>o.json())}async invokeStream(e,t,o){let i=await fetch(e,{method:"POST",headers:{"Content-Type":"application/json"},body:JSON.stringify(t)});if(!i.ok)throw new Error(i.statusText);let s=i.body;if(!s)return;let c=s.getReader(),a=new TextDecoder,r=!1;for(;!r;){let{value:d,done:u}=await c.read();r=u;let f=a.decode(d);o(f)}}onProgress(e){let t=P();return this.onProgressListeners.set(t,e),()=>{this.onProgressListeners.delete(t)}}onStart(e){let t=P();return this.onStartListeners.set(t,e),()=>{this.onStartListeners.delete(t)}}onFinish(e){let t=P();return this.onFinishListeners.set(t,e),()=>{this.onFinishListeners.delete(t)}}listenToEvents(){if(!this.conf.updateProgress\|\|typeof window>"u"\|\|!this.apiKeys?.ablySubscribe)return;let e=`https://realtime.ably.io/event-stream?channels=aigur-client&v=1.2&key=${this.apiKeys.ablySubscribe}&enveloped=false`,t=new EventSource(e);t.onmessage=o=>{let i=JSON.parse(o.data);i.type==="pipeline:start"?this.triggerListeners(this.onStartListeners):i.type==="pipeline:finish"?this.triggerListeners(this.onFinishListeners):(i.type==="node:start"\|\|i.type==="node:finish")&&this.triggerListeners(this.onProgressListeners,{...i.data,type:i.type})}}triggerListeners(e,...t){for(let o of e.values())o(...t)}async processPipeline(e,t){let o=this.conf.retries??te;try{await this.notifyEvent("pipeline:start"),e.input.parse(t);let i={input:t},s={},c=this.flow.getNodes(),a;for(let r=0;r<c.length;r++){a=this.notifyEvent("node:start",{node:c[r],index:r});let d=0,u=!1;do{d++;try{s=await this.executeAction(c,r,i),i[r]=s,u=!0}catch(f){if(d>o)throw f;await D((this.conf.retryDelayInMs??ne)*d)}}while(!u&&d<=o);await a,await this.notifyEvent("node:finish",{node:c[r],index:r})}return await this.notifyEvent("pipeline:finish"),s}catch(i){throw console.error(i),i}}async executeAction(e,t,o){let{action:i,schema:s,input:c}=e[t],a=k(c,o);return i(a,this.apiKeys)}notifyEvent(e,t){if(!(!this.conf.updateProgress\|\|!this.apiKeys.ablyPublish))return fetch("https://rest.ably.io/channels/aigur-client/messages?enveloped=false ",{method:"POST",headers:{"Content-Type":"application/json",Authorization:`Basic ${btoa(this.apiKeys.ablyPublish)}`},body:JSON.stringify({type:e,data:t})})}};var x=require("zod"),K=require("eventsource-parser");var m=require("zod"),I=m.z.object({prompt:m.z.string(),model:m.z.string().default("text-davinci-003"),temperature:m.z.number().default(.7),top_p:m.z.number().default(1),frequency_penalty:m.z.number().default(0),presence_penalty:m.z.number().default(0),max_tokens:m.z.number().default(200),n:m.z.number().default(1)}),oe=m.z.object({text:m.z.string()});async function ie(n,e){let t=I.parse(n);return{text:(await(await fetch("https://api.openai.com/v1/completions",{headers:{"Content-Type":"application/json",Authorization:`Bearer ${e.openai}`},method:"POST",body:JSON.stringify(t)})).json()).choices[0]?.text.replace(/^(?:\n)+/gm,"")}}var T={id:"text.prediction.gpt3",schema:{input:I,output:oe},action:ie};var B=I.merge(x.z.object({stream:x.z.literal(!0).optional().default(!0)})),re=x.z.object({stream:x.z.instanceof(globalThis.ReadableStream??Object)});async function ae(n,e){let t=B.parse(n),o=await fetch("https://api.openai.com/v1/completions",{headers:{"Content-Type":"application/json",Authorization:`Bearer ${e.openai}`},method:"POST",body:JSON.stringify(t)});return{stream:await se(o)}}var M={id:"text.prediction.gpt3.stream",schema:{input:B,output:re},action:ae};async function se(n){let e=new TextEncoder,t=new TextDecoder,o=0;return new ReadableStream({async start(s){function c(r){if(r.type==="event"){let d=r.data;if(d==="[DONE]"){s.close();return}try{let f=JSON.parse(d).choices[0].text;if(o<2&&(f.match(/\n/)\|\|[]).length)return;let y=e.encode(f);s.enqueue(y),o++}catch(u){s.error(u)}}}let a=(0,K.createParser)(c);for await(let r of n.body)a.feed(t.decode(r))}})}var O=require("zod"),F=()=>({id:"output",schema:{input:O.z.object({}),output:O.z.object({})},async action(n){return n}});var g=require("zod"),W=g.z.object({image:g.z.string()}),pe=g.z.object({labels:g.z.array(g.z.string())});async function ue(n,e){let t=W.parse(n),o=`https://vision.googleapis.com/v1/images:annotate?key=${e.googleapis}`,i={requests:[{image:{content:t.image},features:[{type:"LABEL_DETECTION"}]}]};return{labels:(await(await fetch(o,{method:"POST",body:JSON.stringify(i)})).json()).responses[0].labelAnnotations.map(a=>a.description)}}var z={id:"image.labeling.googleVision",schema:{input:W,output:pe},action:ue};var p=require("zod"),Z=p.z.object({text_prompts:p.z.array(p.z.object({text:p.z.string(),weight:p.z.number().min(-1).max(1).optional().default(1)})).refine(n=>n.length>0,"Must have at least one text prompt"),model:p.z.enum(["stable-diffusion-v1-5","stable-diffusion-512-v2-1","stable-diffusion-768-v2-1"]).optional().default("stable-diffusion-v1-5"),clip_guidance_preset:p.z.enum(["NONE","FAST_BLUE","FAST_GREEN","SIMPLE","SLOW","SLOWER","SLOWEST"]).optional(),steps:p.z.number().optional(),sampler:p.z.enum(["one","two"]).optional(),samples:p.z.number().optional(),cfg_scale:p.z.number().optional(),seed:p.z.number().optional(),height:p.z.number().min(128).optional().refine(n=>typeof n<"u"?n%64===0:!0,"Must be a multiple of 64"),width:p.z.number().min(128).optional().refine(n=>typeof n<"u"?n%64===0:!0,"Must be a multiple of 64")}),ce=p.z.object({result:p.z.instanceof(ArrayBuffer)});async function de(n,e){let t=Z.parse(n),o=`https://api.stability.ai/v1beta/generation/${t.model}/text-to-image`;return{result:await(await fetch(o,{headers:{"Content-Type":"application/json",Accept:"image/png",Authorization:e.stability},method:"POST",body:JSON.stringify(t)})).arrayBuffer()}}var j={id:"image.textToImage.stableDiffusion.stability",schema:{input:Z,output:ce},action:de};var S=require("zod"),_=S.z.object({text:S.z.string(),amount:S.z.number().optional().default(8)}),me=S.z.object({text:S.z.string()}),le={"Colonial-style home":"Colonial, traditional, classic, historical, timeless, elegant, regal, grand, spacious, architectural, wood-framed, brick-exterior, symmetrical, gabled roof, columns, portico, fireplace, formal, ornate, landscaped".split(", "),"High-end penthouse apartment":"Luxury, high-end, penthouse, apartment, upscale, contemporary, modern, stylish, designer, elite, high-rise, rooftop, panoramic, views, spacious, open-plan, top-floor, amenities, concierge, service, exclusive".split(", ")};function fe(n){return Object.entries(le).map(([e,t])=>`Title: ${e}
		Description: ${t.slice(0,n).join(", ")}
		`).join(`
		`)}async function ye(n){let e=_.parse(n);return{text:`Write a maximum of ${e.amount} keywords in a csv list that describes the following
		${fe(e.amount)}
		Title: ${e.text}
		Description:`}}var E={id:"text.modify.enhanceWithKeywords",schema:{input:_,output:me},action:ye};var h=require("zod"),$=h.z.object({text:h.z.string().or(h.z.array(h.z.string())),modifier:h.z.string()}),he=h.z.object({text:h.z.string()});async function ge(n){let e=$.parse(n);return{text:e.modifier.replace(/\$$text$\$/gm,Array.isArray(e.text)?e.text.join(", "):e.text)}}var C={id:"text.modify.simple",schema:{input:$,output:he},action:ge};var N=require("zod"),Se="https://transcribe.whisperapi.com",V=N.z.object({audioUrl:N.z.string().url()}),be=N.z.object({text:N.z.string()});async function xe(n,e){let t=V.parse(n),o=new FormData;o.append("url",t.audioUrl),o.append("language","en"),o.append("fileType","mp3"),o.append("task","transcribe");let i=await fetch(Se,{method:"POST",headers:{contentType:"application/json",Authorization:"Bearer "+e.whisperapi},body:o});if(!i.ok)throw new Error(i.statusText);return{text:(await i.json()).text.trim()}}var U={id:"voice.transcribe.whisper.whisperapi",schema:{input:V,output:be},action:xe};var v=require("zod"),J=v.z.object({string:v.z.string()}),Ne=v.z.object({arrayBuffer:v.z.instanceof(ArrayBuffer)});async function ve(n){let e=J.parse(n);return{arrayBuffer:Uint8Array.from(atob(e.string),o=>o.charCodeAt(0)).buffer}}var R={id:"text.transformation.stringToArrayBuffer",schema:{input:J,output:Ne},action:ve};var l=require("zod"),G=l.z.object({text:l.z.string(),speakingRate:l.z.number().min(.25).max(4).optional().default(1),pitch:l.z.number().min(-20).max(20).optional().default(0),encoding:l.z.enum(["MP3","FLAC","LINEAR16","MULAW","AMR","AMR_WB","OGG_OPUS","SPEEX_WITH_HEADER_BYTE","WEBM_OPUS"]).optional().default("MP3"),voice:l.z.object({language:l.z.string().optional().default("en-US"),name:l.z.enum(["en-US-Standard-A","en-US-Standard-C","en-US-Standard-D","en-US-Standard-E","en-US-Standard-F","en-US-Standard-G","en-US-Standard-H","en-US-Standard-I","en-US-Standard-J","en-US-Studio-M","en-US-Studio-O","en-US-Wavenet-A","en-US-Wavenet-B","en-US-Wavenet-C","en-US-Wavenet-D","en-US-Wavenet-E","en-US-Wavenet-F","en-US-Wavenet-G","en-US-Wavenet-H","en-US-Wavenet-I","en-US-Wavenet-J","en-US-News-K","en-US-News-L","en-US-News-M","en-US-News-N","en-US-Standard-A","en-US-Standard-B","en-US-Standard-C","en-US-Standard-D","en-US-Standard-E","en-US-Standard-F","en-US-Standard-G","en-US-Standard-H","en-US-Standard-I","en-US-Standard-J"]).or(l.z.string()).optional().default("en-US-Neural2-C")}).optional().default({language:"en-US",name:"en-US-Neural2-C"})}),Pe=l.z.object({audio:l.z.string()});async function we(n,e){let t=G.parse(n),o=`https://us-central1-texttospeech.googleapis.com/v1beta1/text:synthesize?key=${e.googleapis}`,i={input:{text:t.text},voice:{languageCode:t.voice.language,name:t.voice.name},audioConfig:{audioEncoding:t.encoding,speakingRate:t.speakingRate,pitch:t.pitch}};return{audio:(await(await fetch(o,{method:"POST",headers:{"Content-Type":"application/json"},body:JSON.stringify(i)})).json()).audioContent}}var L={id:"voice.textToSpeech.google",schema:{input:G,output:Pe},action:we};var b=class{constructor(e,t){this.input=e;this.nodes=t;this.voice={textToSpeech:{google:this.nodeFactory(L)},transcribe:{whisper:{whisperapi:this.nodeFactory(U)}}};this.text={modify:{enhanceWithKeywords:this.nodeFactory(E),simple:this.nodeFactory(C)},prediction:{gpt3:this.nodeFactory(T),gpt3Stream:this.nodeFactory(M)}};this.image={textToImage:{stableDiffusion:{stability:this.nodeFactory(j)}},labeling:{googleVision:this.nodeFactory(z)}};this.output=this.nodeFactory(F());this.transformation={stringToArrayBuffer:this.nodeFactory(R)}}static create(e){return new b(e,[])}nodeFactory(e){return t=>{let o=this.setPlaceholderValues(this.input.keyof().options,"input"),i=this.nodes.length>0?this.nodes[this.nodes.length-1]:o,s={...e,input:t({nodes:this.nodes,prev:i.output,input:o}),output:e.schema.output.keyof?this.setPlaceholderValues(e.schema.output.keyof().options,this.nodes.length):e.schema.output};return this.nodes.push(s),this}}setPlaceholderValues(e,t){let o={};for(let i of e)o[i]=`$context.${t}.${i}$`;return o}custom(e){return this.nodeFactory(e)}getNodes(){return this.nodes}};var Ie=2,Ae=350,Te=n=>{let{apiKeys:e}=n;return{pipeline:{create:t=>{let o={...t,retries:t.retries??Ie,retryDelayInMs:t.retryDelayInMs??Ae},i=t.flow(new b(t.input,[]));return new w(o,i,e)}}}};0&&(module.exports={createClient});

package.json

		{
		"name": "@aigur/client",
		"version": "0.30.0",
		"version": "0.30.1",
		"description": "",
		@@ -5,0 +5,0 @@ "main": "dist/index.js",

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