A robust and meticulously crafted TypeScript SDK 🚀 for seamless interaction with the ComfyUI API. This SDK significantly simplifies the complexities of building, executing, and managing ComfyUI workflows, all while providing real-time updates and supporting multiple instances. 🖼️
- 🌟 Key Features 🌟
- 📦 Installation 📦
- 🚀 Getting Started 🚀
- 📚 API Reference 📚
- 📂 Examples
- 🤝 Contributing
- 📜 License
- 💎 TypeScript Powered: Enjoy a fully typed codebase, ensuring enhanced development, maintainability, and type safety. 🛡️
- 🏗️ Workflow Builder: Construct and manipulate intricate ComfyUI workflows effortlessly using a fluent, intuitive builder pattern. 🧩
- 🤹 Multi-Instance Management: Handle a pool of ComfyUI instances with ease, employing flexible queueing strategies for optimal resource utilization. 🌐
- ⚡ Real-Time Updates: Subscribe to WebSocket events for live progress tracking, image previews, and error notifications. 🔔
- 🔑 Authentication Flexibility: Supports Basic Auth, Bearer Token, and Custom Authentication Headers, catering to diverse security requirements. 🔒
- 🔌 Extension Support: Seamlessly integrate with ComfyUI Manager and leverage system monitoring through the ComfyUI-Crystools extension. 🛠️
- 🔀 Flexible Node Bypassing: Strategically bypass specific nodes in your workflows during generation, enabling advanced customization. ⏭️
- 📚 Comprehensive Examples: Includes practical examples for Text-to-Image (T2I), Image-to-Image (I2I), and complex multi-node workflows. 📝
- 🚨 Robust Error Handling: Provides detailed error messages to facilitate debugging and graceful handling of API failures. 🐛
- 📝 Automatic Changelog: Automatically generates a changelog with each release, utilizing
auto-changelog
for transparent version tracking. 🔄
bun add @saintno/comfyui-sdk
or
npm i @saintno/comfyui-sdk
Here's a simplified example to quickly get you started:
import { ComfyApi, CallWrapper, PromptBuilder, TSamplerName, TSchedulerName, seed } from "@saintno/comfyui-sdk";
import ExampleTxt2ImgWorkflow from "./example-txt2img-workflow.json";
const api = new ComfyApi("http://localhost:8189").init();
const workflow = new PromptBuilder(
ExampleTxt2ImgWorkflow,
["positive", "negative", "checkpoint", "seed", "batch", "step", "cfg", "sampler", "sheduler", "width", "height"],
["images"]
)
.setInputNode("checkpoint", "4.inputs.ckpt_name")
.setInputNode("seed", "3.inputs.seed")
.setInputNode("batch", "5.inputs.batch_size")
.setInputNode("negative", "7.inputs.text")
.setInputNode("positive", "6.inputs.text")
.setInputNode("cfg", "3.inputs.cfg")
.setInputNode("sampler", "3.inputs.sampler_name")
.setInputNode("sheduler", "3.inputs.scheduler")
.setInputNode("step", "3.inputs.steps")
.setInputNode("width", "5.inputs.width")
.setInputNode("height", "5.inputs.height")
.setOutputNode("images", "9")
.input("checkpoint", "SDXL/realvisxlV40_v40LightningBakedvae.safetensors", api.osType)
.input("seed", seed())
.input("step", 6)
.input("cfg", 1)
.input<TSamplerName>("sampler", "dpmpp_2m_sde_gpu")
.input<TSchedulerName>("sheduler", "sgm_uniform")
.input("width", 1024)
.input("height", 1024)
.input("batch", 1)
.input("positive", "A picture of cute dog on the street");
new CallWrapper(api, workflow)
.onFinished((data) => console.log(data.images?.images.map((img: any) => api.getPathImage(img))))
.run();
- Import essential components from the SDK.
- Create and initialize the
ComfyApi
instance. - Use
PromptBuilder
to define the workflow structure and set input nodes. - Set specific input values, including the checkpoint path, seed, and prompt.
- Execute the workflow and log the generated image URLs using the
CallWrapper
.
import {
ComfyApi,
CallWrapper,
ComfyPool,
EQueueMode,
PromptBuilder,
seed,
TSamplerName,
TSchedulerName
} from "@saintno/comfyui-sdk";
import ExampleTxt2ImgWorkflow from "./example-txt2img-workflow.json";
const ApiPool = new ComfyPool(
[new ComfyApi("http://localhost:8188"), new ComfyApi("http://localhost:8189")],
EQueueMode.PICK_ZERO
)
.on("init", () => console.log("Pool in initializing"))
.on("add_job", (ev) => console.log("Job added at index", ev.detail.jobIdx, "weight:", ev.detail.weight))
.on("added", (ev) => console.log("Client added", ev.detail.clientIdx));
const generateFn = async (api: ComfyApi, clientIdx?: number) => {
const workflow = new PromptBuilder(
ExampleTxt2ImgWorkflow,
["positive", "negative", "checkpoint", "seed", "batch", "step", "cfg", "sampler", "sheduler", "width", "height"],
["images"]
)
.setInputNode("checkpoint", "4.inputs.ckpt_name")
.setInputNode("seed", "3.inputs.seed")
.setInputNode("batch", "5.inputs.batch_size")
.setInputNode("negative", "7.inputs.text")
.setInputNode("positive", "6.inputs.text")
.setInputNode("step", "3.inputs.steps")
.setInputNode("width", "5.inputs.width")
.setInputNode("height", "5.inputs.height")
.setInputNode("cfg", "3.inputs.cfg")
.setInputNode("sampler", "3.inputs.sampler_name")
.setInputNode("scheduler", "3.inputs.scheduler")
.setOutputNode("images", "9")
.input("checkpoint", "SDXL/realvisxlV40_v40LightningBakedvae.safetensors", api.osType)
.input("seed", seed())
.input("step", 6)
.input("width", 512)
.input("height", 512)
.input("batch", 2)
.input("cfg", 1)
.input<TSamplerName>("sampler", "dpmpp_2m_sde_gpu")
.input<TSchedulerName>("scheduler", "sgm_uniform")
.input("positive", "A close up picture of cute Cat")
.input("negative", "text, blurry, bad picture, nsfw");
return new Promise<string[]>((resolve) => {
new CallWrapper(api, workflow)
.onFinished((data) => {
const url = data.images?.images.map((img: any) => api.getPathImage(img));
resolve(url as string[]);
})
.run();
});
};
const jobA = ApiPool.batch(Array(5).fill(generateFn), 10).then((res) => {
console.log("Batch A done");
return res.flat();
});
const jobB = ApiPool.batch(Array(5).fill(generateFn), 0).then((res) => {
console.log("Batch B done");
return res.flat();
});
console.log(await Promise.all([jobA, jobB]).then((res) => res.flat()));
- Create a
ComfyPool
with multipleComfyApi
instances. - Set up event listeners for pool initialization, job additions, and client connections.
- Define an async function (
generateFn
) that creates a workflow, sets its inputs, and executes it with aCallWrapper
. - Use
ApiPool.batch
to run multiple jobs and wait for all batches to complete.
import { ComfyApi, BasicCredentials, BearerTokenCredentials, CustomCredentials } from "@saintno/comfyui-sdk";
// Basic Authentication
const basicAuth = new ComfyApi("http://localhost:8189", "node-id", {
credentials: { type: "basic", username: "username", password: "password" } as BasicCredentials
}).init();
// Bearer Token Authentication
const bearerAuth = new ComfyApi("http://localhost:8189", "node-id", {
credentials: { type: "bearer_token", token: "your_bearer_token" } as BearerTokenCredentials
}).init();
// Custom Header Authentication
const customAuth = new ComfyApi("http://localhost:8189", "node-id", {
credentials: { type: "custom", headers: { "X-Custom-Header": "your_custom_header" } } as CustomCredentials
}).init();
- Import the necessary types from the SDK.
- Create
ComfyApi
instances using the corresponding credential types:BasicCredentials
,BearerTokenCredentials
, andCustomCredentials
..
constructor(host: string, clientId: string, opts?: { forceWs?: boolean, wsTimeout?: number, credentials?: BasicCredentials | BearerTokenCredentials | CustomCredentials; })
host
: The base URL of your ComfyUI server.clientId
: A unique ID for WebSocket communication (optional). Defaults to a generated ID.opts
: Optional settings:forceWs
: Boolean to force WebSocket usage.wsTimeout
: Timeout for WebSocket connections (milliseconds).credentials
: Optional authentication credentials.
init(maxTries?: number, delayTime?: number)
: Initializes the client and establishes connection.on<K extends keyof TComfyAPIEventMap>(type: K, callback: (event: TComfyAPIEventMap[K]) => void, options?: AddEventListenerOptions | boolean)
: Attach an event listener.off<K extends keyof TComfyAPIEventMap>(type: K, callback: (event: TComfyAPIEventMap[K]) => void, options?: EventListenerOptions | boolean)
: Detach an event listener.removeAllListeners()
: Detach all event listeners.fetchApi(route: string, options?: FetchOptions)
: Fetch data from the API endpoint.pollStatus(timeout?: number)
: Polls the ComfyUI server status.queuePrompt(number: number | null, workflow: object)
: Queues a prompt for processing.appendPrompt(workflow: object)
: Adds a prompt to the workflow queue.getQueue()
: Retrieves the current state of the queue.getHistories(maxItems?: number)
: Retrieves the prompt execution history.getHistory(promptId: string)
: Retrieves a specific history entry by ID.getSystemStats()
: Retrieves system and device statistics.getExtensions()
: Retrieves a list of installed extensions.getEmbeddings()
: Retrieves a list of available embeddings.getCheckpoints()
: Retrieves a list of available checkpoints.getLoras()
: Retrieves a list of available Loras.getSamplerInfo()
: Retrieves sampler and scheduler information.getNodeDefs(nodeName?: string)
: Retrieves node object definitions.getUserConfig()
: Get user configuration data.createUser(username: string)
: Create new user.getSettings()
: Get all setting values for the current user.getSetting(id: string)
: Get a specific setting for the current user.storeSettings(settings: Record<string, unknown>)
: Store setting for the current user.storeSetting(id: string, value: unknown)
: Store a specific setting for the current user.uploadImage(file: Buffer | Blob, fileName: string, config?: { override?: boolean; subfolder?: string })
: Uploads an image file.uploadMask(file: Buffer | Blob, originalRef: ImageInfo)
: Uploads a mask file.freeMemory(unloadModels: boolean, freeMemory: boolean)
: Frees memory by unloading models.getPathImage(imageInfo: ImageInfo)
: Returns the path to an image.getImage(imageInfo: ImageInfo)
: Returns the blob data of image.getUserData(file: string)
: Get a user data file.storeUserData(file: string, data: unknown, options?: RequestInit & { overwrite?: boolean, stringify?: boolean, throwOnError?: boolean })
: Store a user data file.deleteUserData(file: string)
: Delete a user data file.moveUserData(source: string, dest: string, options?: RequestInit & { overwrite?: boolean })
: Move a user data file.listUserData(dir: string, recurse?: boolean, split?: boolean)
: List a user data file.interrupt()
: Interrupts the execution of the running prompt.reconnectWs(opened?: boolean)
: Reconnects to the WebSocket server.
constructor(client: ComfyApi, workflow: PromptBuilder<I, O, T>)
client
: An instance of theComfyApi
client.workflow
: An instance ofPromptBuilder
defining the workflow.
onPreview(fn: (ev: Blob, promptId?: string) => void)
: Set callback for preview events.onPending(fn: (promptId?: string) => void)
: Set callback when job is queued.onStart(fn: (promptId?: string) => void)
: Set callback when the job is started.onOutput(fn: (key: keyof PromptBuilder<I, O, T>["mapOutputKeys"], data: any, promptId?: string) => void)
: Sets a callback for when an output node is executed.onFinished(fn: (data: Record<keyof PromptBuilder<I, O, T>["mapOutputKeys"], any>, promptId?: string) => void)
: Set callback when the job is finished.onFailed(fn: (err: Error, promptId?: string) => void)
: Set callback when the job failed.onProgress(fn: (info: NodeProgress, promptId?: string) => void)
: Set callback for progress updates.run()
: Executes the workflow.
constructor(prompt: T, inputKeys: I[], outputKeys: O[])
prompt
: The initial workflow data object.inputKeys
: An array of input node keys.outputKeys
: An array of output node keys.
clone()
: Creates a newPromptBuilder
instance with the same configuration.bypass(node: keyof T | (keyof T)[]): PromptBuilder<I, O, T>
: Marks node(s) to be bypassed at generation.reinstate(node: keyof T | (keyof T)[]): PromptBuilder<I, O, T>
: Unmarks node(s) from bypass at generation.setInputNode(input: I, key: DeepKeys<T> | Array<DeepKeys<T>>)
: Sets input node path for a key.setRawInputNode(input: I, key: string | string[])
: Sets raw input node path for a key.appendInputNode(input: I, key: DeepKeys<T> | Array<DeepKeys<T>>)
: Appends a node to the input node path.appendRawInputNode(input: I, key: string | string[])
: Appends a node to the raw input node path.setOutputNode(output: O, key: DeepKeys<T>)
: Sets output node path for a key.setRawOutputNode(output: O, key: string)
: Sets raw output node path for a key.input<V = string | number | undefined>(key: I, value: V, encodeOs?: OSType)
: Sets an input value.inputRaw<V = string | number | undefined>(key: string, value: V, encodeOs?: OSType)
: Sets a raw input value with dynamic key.get workflow
: Retrieves the workflow object.get caller
: Retrieves currentPromptBuilder
object.
constructor(clients: ComfyApi[], mode: EQueueMode = EQueueMode.PICK_ZERO)
clients
: Array ofComfyApi
instances.mode
: The queue mode usingEQueueMode
enum values.
on<K extends keyof TComfyPoolEventMap>(type: K, callback: (event: TComfyPoolEventMap[K]) => void, options?: AddEventListenerOptions | boolean)
: Attach an event listener.off<K extends keyof TComfyPoolEventMap>(type: K, callback: (event: TComfyPoolEventMap[K]) => void, options?: EventListenerOptions | boolean)
: Detach an event listener.addClient(client: ComfyApi)
: Adds a new client to the pool.removeClient(client: ComfyApi)
: Removes a client from the pool.removeClientByIndex(index: number)
: Removes a client by index.changeMode(mode: EQueueMode)
: Changes the queue mode.pick(idx?: number)
: Picks a client by index.pickById(id: string)
: Picks a client by ID.run<T>(job: (client: ComfyApi, clientIdx?: number) => Promise<T>, weight?: number, clientFilter?: { includeIds?: string[]; excludeIds?: string[] })
: Run a job with priority on an available client.batch<T>(jobs: Array<(client: ComfyApi, clientIdx?: number) => Promise<T>>, weight?: number, clientFilter?: { includeIds?: string[]; excludeIds?: string[] })
: Run multiple jobs concurrently.
EQueueMode
:PICK_ZERO
: Selects the client with zero remaining queue.PICK_LOWEST
: Selects the client with the lowest remaining queue.PICK_ROUTINE
: Selects clients in a round-robin manner.
OSType
:POSIX
: For Unix-like systems.NT
: For Windows systems.JAVA
: For Java virtual machine.
TSamplerName
: A union type of all available sampler names.TSchedulerName
: A union type of all available scheduler names.
-
ManagerFeature
: Provides methods to manage ComfyUI Manager Extension.const api = new ComfyApi("http://localhost:8189").init(); await api.waitForReady(); if (api.ext.manager.isSupported) { await api.ext.manager.getExtensionList().then(console.log); // Check api.ext.manager for more methods }
-
MonitoringFeature
: Provides methods to monitor system resources using ComfyUI-Crystools Extension.const api = new ComfyApi("http://localhost:8189").init(); await api.waitForReady(); if (api.ext.monitor.isSupported) { // For subscribing to system monitor events api.ext.monitor.on("system_monitor", (ev) => { console.log(ev.detail); }); // For getting current monitor data console.log(api.ext.monitor.monitorData); }
Note: Features require respective extensions (ComfyUI-Manager and ComfyUI-Crystools) to be installed.
The examples
directory contains practical demonstrations of SDK usage:
example-i2i.ts
: Demonstrates image-to-image generation.example-pool.ts
: Demonstrates how to manage multiple ComfyUI instances usingComfyPool
.example-pool-basic-auth.ts
: Demonstrates how to useComfyPool
with HTTP Basic Authentication.example-t2i.ts
: Demonstrates text-to-image generation.example-t2i-upscaled.ts
: Demonstrates text-to-image generation with upscaling.example-img2img-workflow.json
: Example workflow for image-to-image.example-txt2img-workflow.json
: Example workflow for text-to-image.example-txt2img-upscaled-workflow.json
: Example workflow for text-to-image with upscaling.
Contributions are always welcome! Feel free to submit pull requests or create issues for bug reports and feature enhancements. 🙏
This project is licensed under the MIT License - see the LICENSE file for more details. 📄