> ## Documentation Index
> Fetch the complete documentation index at: https://dripart-feat-openapi-i18n.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# API Examples

> Three common patterns for calling the ComfyUI Server API

This page demonstrates three ways to interact with the ComfyUI Server API, from a simple HTTP submission to a full WebSocket integration with real-time image output.

All examples use the [default SD1.5 workflow](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples) for illustration. Before using the API, you need to export your workflow in [API format](/development/api-development/workflow-api-format).

<Note>
  These examples use Python with the standard library and the `websocket-client` package (`pip install websocket-client`). The underlying API protocol is the same regardless of language — see the [Cloud API Reference](/development/cloud/api-reference) for TypeScript and curl equivalents.
</Note>

***

## Method 1: Submit and Forget (HTTP only)

Source: [`basic_api_example.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples/basic_api_example.py)

The simplest approach: submit a workflow and don't wait for results. Useful for fire-and-forget jobs where you check outputs later.

```python theme={null}
"""basic_api_example.py — Submit a workflow via HTTP only."""

import json
from urllib import request

SERVER_ADDRESS = "127.0.0.1:8188"


def queue_prompt(prompt):
    p = {"prompt": prompt}
    data = json.dumps(p).encode("utf-8")
    req = request.Request(
        f"http://{SERVER_ADDRESS}/prompt", data=data
    )
    request.urlopen(req)


if __name__ == "__main__":
    # Load a workflow exported in API format
    prompt_text = """{
        "3": {
            "class_type": "KSampler",
            "inputs": {
                "cfg": 8, "denoise": 1,
                "latent_image": ["5", 0],
                "model": ["4", 0],
                "negative": ["7", 0],
                "positive": ["6", 0],
                "sampler_name": "euler",
                "scheduler": "normal",
                "seed": 8566257, "steps": 20
            }
        },
        "4": {
            "class_type": "CheckpointLoaderSimple",
            "inputs": {"ckpt_name": "v1-5-pruned-emaonly.safetensors"}
        },
        "5": {
            "class_type": "EmptyLatentImage",
            "inputs": {"batch_size": 1, "height": 512, "width": 512}
        },
        "6": {
            "class_type": "CLIPTextEncode",
            "inputs": {"clip": ["4", 1], "text": "masterpiece best quality man"}
        },
        "7": {
            "class_type": "CLIPTextEncode",
            "inputs": {"clip": ["4", 1], "text": "bad hands"}
        },
        "8": {
            "class_type": "VAEDecode",
            "inputs": {"samples": ["3", 0], "vae": ["4", 2]}
        },
        "9": {
            "class_type": "SaveImage",
            "inputs": {"filename_prefix": "ComfyUI", "images": ["8", 0]}
        }
    }"""

    prompt = json.loads(prompt_text)
    # Modify inputs before submitting
    prompt["3"]["inputs"]["seed"] = 5
    prompt["6"]["inputs"]["text"] = "masterpiece best quality man"

    queue_prompt(prompt)
    print("Prompt submitted successfully.")
```

<Info>
  This method uses the `SaveImage` node, which saves images to disk on the server. To retrieve them, you'd need to follow up with a call to `GET /view?filename=...`.
</Info>

***

## Method 2: WebSocket + History (Monitor Completion)

Source: [`websockets_api_example.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples/websockets_api_example.py)

Use WebSocket to wait for execution to finish, then retrieve outputs via the `/history` endpoint. This is the recommended pattern for most use cases.

```python theme={null}
"""websockets_api_example.py — Monitor execution via WebSocket, download via /history."""

import websocket  # pip install websocket-client
import uuid
import json
import urllib.request
import urllib.parse

SERVER_ADDRESS = "127.0.0.1:8188"
client_id = str(uuid.uuid4())


def queue_prompt(prompt, prompt_id):
    p = {"prompt": prompt, "client_id": client_id, "prompt_id": prompt_id}
    data = json.dumps(p).encode("utf-8")
    req = urllib.request.Request(
        f"http://{SERVER_ADDRESS}/prompt", data=data
    )
    urllib.request.urlopen(req)


def get_image(filename, subfolder, folder_type):
    params = urllib.parse.urlencode({
        "filename": filename,
        "subfolder": subfolder,
        "type": folder_type,
    })
    with urllib.request.urlopen(
        f"http://{SERVER_ADDRESS}/view?{params}"
    ) as response:
        return response.read()


def get_history(prompt_id):
    with urllib.request.urlopen(
        f"http://{SERVER_ADDRESS}/history/{prompt_id}"
    ) as response:
        return json.loads(response.read())


def get_images(ws, prompt):
    prompt_id = str(uuid.uuid4())
    queue_prompt(prompt, prompt_id)

    while True:
        out = ws.recv()
        if isinstance(out, str):
            message = json.loads(out)
            if message["type"] == "executing":
                data = message["data"]
                if data["node"] is None and data["prompt_id"] == prompt_id:
                    break  # Execution done
        # Binary frames are preview images — skip them here
        continue

    history = get_history(prompt_id)[prompt_id]
    output_images = {}
    for node_id in history["outputs"]:
        node_output = history["outputs"][node_id]
        images_output = []
        if "images" in node_output:
            for image in node_output["images"]:
                image_data = get_image(
                    image["filename"], image["subfolder"], image["type"]
                )
                images_output.append(image_data)
        output_images[node_id] = images_output
    return output_images


if __name__ == "__main__":
    prompt_text = """{
        "3": { ... }, "4": { ... }, "5": { ... },
        "6": { ... }, "7": { ... }, "8": { ... },
        "9": { "class_type": "SaveImage", "inputs": { ... } }
    }"""
    prompt = json.loads(prompt_text)
    prompt["3"]["inputs"]["seed"] = 5
    prompt["6"]["inputs"]["text"] = "masterpiece best quality man"

    ws = websocket.WebSocket()
    ws.connect(f"ws://{SERVER_ADDRESS}/ws?clientId={client_id}")
    images = get_images(ws, prompt)
    ws.close()

    print(f"Got {len(images)} output node(s) with images.")

    # Display the images (requires Pillow):
    # for node_id in images:
    #     for image_data in images[node_id]:
    #         from PIL import Image
    #         import io
    #         img = Image.open(io.BytesIO(image_data))
    #         img.show()
```

<Tip>
  The WebSocket binary frames contain in-progress preview images during generation. You can decode them for live previews (see the [Server Messages](/development/comfyui-server/comms_messages) page for the binary format).
</Tip>

***

## Method 3: WebSocket with SaveImageWebsocket (Real-time Images)

Source: [`websockets_api_example_ws_images.py`](https://github.com/Comfy-Org/ComfyUI/blob/master/script_examples/websockets_api_example_ws_images.py)

For scenarios where you don't want images saved to disk, use the `SaveImageWebsocket` node. Images are delivered directly via WebSocket binary frames.

```python theme={null}
"""websockets_api_example_ws_images.py — Receive images directly via WebSocket."""

import websocket  # pip install websocket-client
import uuid
import json
import urllib.request
import urllib.parse

SERVER_ADDRESS = "127.0.0.1:8188"
client_id = str(uuid.uuid4())


def queue_prompt(prompt):
    p = {"prompt": prompt, "client_id": client_id}
    data = json.dumps(p).encode("utf-8")
    req = urllib.request.Request(
        f"http://{SERVER_ADDRESS}/prompt", data=data
    )
    return json.loads(urllib.request.urlopen(req).read())


def get_images(ws, prompt):
    prompt_id = queue_prompt(prompt)["prompt_id"]
    output_images = {}
    current_node = ""

    while True:
        out = ws.recv()
        if isinstance(out, str):
            message = json.loads(out)
            if message["type"] == "executing":
                data = message["data"]
                if data["prompt_id"] == prompt_id:
                    if data["node"] is None:
                        break  # Execution done
                    current_node = data["node"]
        else:
            # Binary frame — image data from SaveImageWebsocket
            if current_node == "save_image_websocket_node":
                images_output = output_images.get(current_node, [])
                # The first 8 bytes are type/meta, rest is image data
                images_output.append(out[8:])
                output_images[current_node] = images_output

    return output_images


if __name__ == "__main__":
    prompt_text = """{
        "3": { "class_type": "KSampler", "inputs": { ... } },
        ...
        "save_image_websocket_node": {
            "class_type": "SaveImageWebsocket",
            "inputs": {"images": ["8", 0]}
        }
    }"""
    prompt = json.loads(prompt_text)
    prompt["3"]["inputs"]["seed"] = 5

    ws = websocket.WebSocket()
    ws.connect(f"ws://{SERVER_ADDRESS}/ws?clientId={client_id}")
    images = get_images(ws, prompt)
    ws.close()

    print(f"Received {len(images)} image(s) via WebSocket.")

    # Display (requires Pillow):
    # for image_data in images.get("save_image_websocket_node", []):
    #     from PIL import Image
    #     import io
    #     img = Image.open(io.BytesIO(image_data))
    #     img.show()
```

<Info>
  The workflow must use a node with `class_type: "SaveImageWebsocket"` (a built-in node) instead of the regular `SaveImage` node.
</Info>

***

## Which Method Should I Use?

<CardGroup cols={3}>
  <Card title="Method 1: HTTP Only" icon="paper-plane">
    **Fire and forget.** Use when you don't need immediate output, or when retrieving results later is acceptable.
  </Card>

  <Card title="Method 2: WebSocket + History" icon="chart-line" href="#method-2-websocket--history-monitor-completion">
    **Recommended.** Wait for completion, then download outputs. Best balance of simplicity and reliability.
  </Card>

  <Card title="Method 3: SaveImageWebsocket" icon="images" href="#method-3-websocket-with-saveimagewebsocket-real-time-images">
    **Real-time images.** Best for interactive apps where you want images delivered without disk writes.
  </Card>
</CardGroup>

For the full API reference (endpoints, payload formats, error handling), see the [Server Routes](/development/comfyui-server/comms_routes) and [Server Messages](/development/comfyui-server/comms_messages) pages.