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#This is an example that uses the websockets api and the SaveImageWebsocket node to get images directly without
#them being saved to disk

import websocket #NOTE: websocket-client (https://github.com/websocket-client/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("http://{}/prompt".format(server_address), data=data)
    return json.loads(urllib.request.urlopen(req).read())

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

def get_history(prompt_id):
    with urllib.request.urlopen("http://{}/history/{}".format(server_address, prompt_id)) as response:
        return json.loads(response.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 is done
                    else:
                        current_node = data['node']
        else:
            if current_node == 'save_image_websocket_node':
                images_output = output_images.get(current_node, [])
                images_output.append(out[8:])
                output_images[current_node] = images_output

    return output_images

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.ckpt"

        }

    },

    "5": {

        "class_type": "EmptyLatentImage",

        "inputs": {

            "batch_size": 1,

            "height": 512,

            "width": 512

        }

    },

    "6": {

        "class_type": "CLIPTextEncode",

        "inputs": {

            "clip": [

                "4",

                1

            ],

            "text": "masterpiece best quality girl"

        }

    },

    "7": {

        "class_type": "CLIPTextEncode",

        "inputs": {

            "clip": [

                "4",

                1

            ],

            "text": "bad hands"

        }

    },

    "8": {

        "class_type": "VAEDecode",

        "inputs": {

            "samples": [

                "3",

                0

            ],

            "vae": [

                "4",

                2

            ]

        }

    },

    "save_image_websocket_node": {

        "class_type": "SaveImageWebsocket",

        "inputs": {

            "images": [

                "8",

                0

            ]

        }

    }

}

"""

prompt = json.loads(prompt_text)
#set the text prompt for our positive CLIPTextEncode
prompt["6"]["inputs"]["text"] = "masterpiece best quality man"

#set the seed for our KSampler node
prompt["3"]["inputs"]["seed"] = 5

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

#Commented out code to display the output images:

# for node_id in images:
#     for image_data in images[node_id]:
#         from PIL import Image
#         import io
#         image = Image.open(io.BytesIO(image_data))
#         image.show()