waifuwave/waifuwave.py

import os
import random
import sys
from typing import Sequence, Mapping, Any, Union
import torch
import boto3
from flask import Flask, jsonify, request 


app = Flask(__name__)


def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any:
    """Returns the value at the given index of a sequence or mapping.

    If the object is a sequence (like list or string), returns the value at the given index.
    If the object is a mapping (like a dictionary), returns the value at the index-th key.

    Some return a dictionary, in these cases, we look for the "results" key

    Args:
        obj (Union[Sequence, Mapping]): The object to retrieve the value from.
        index (int): The index of the value to retrieve.

    Returns:
        Any: The value at the given index.

    Raises:
        IndexError: If the index is out of bounds for the object and the object is not a mapping.
    """
    try:
        return obj[index]
    except KeyError:
        return obj["result"][index]


def find_path(name: str, path: str = None) -> str:
    """
    Recursively looks at parent folders starting from the given path until it finds the given name.
    Returns the path as a Path object if found, or None otherwise.
    """
    # If no path is given, use the current working directory
    if path is None:
        path = os.getcwd()

    # Check if the current directory contains the name
    if name in os.listdir(path):
        path_name = os.path.join(path, name)
        print(f"{name} found: {path_name}")
        return path_name

    # Get the parent directory
    parent_directory = os.path.dirname(path)

    # If the parent directory is the same as the current directory, we've reached the root and stop the search
    if parent_directory == path:
        return None

    # Recursively call the function with the parent directory
    return find_path(name, parent_directory)


def add_comfyui_directory_to_sys_path() -> None:
    """
    Add 'ComfyUI' to the sys.path
    """
    comfyui_path = find_path("ComfyUI")
    if comfyui_path is not None and os.path.isdir(comfyui_path):
        sys.path.append(comfyui_path)
        print(f"'{comfyui_path}' added to sys.path")


def add_extra_model_paths() -> None:
    """
    Parse the optional extra_model_paths.yaml file and add the parsed paths to the sys.path.
    """
    try:
        from server import load_extra_path_config
    except ImportError:
        print(
            "Could not import load_extra_path_config from main.py. Looking in utils.extra_config instead."
        )
        try:
            from utils.extra_config import load_extra_path_config
        except ImportError:
            return


    extra_model_paths = find_path("extra_model_paths.yaml")

    if extra_model_paths is not None:
        load_extra_path_config(extra_model_paths)
    else:
        print("Could not find the extra_model_paths config file.")


add_comfyui_directory_to_sys_path()
add_extra_model_paths()


def import_custom_nodes() -> None:
    """Find all custom nodes in the custom_nodes folder and add those node objects to NODE_CLASS_MAPPINGS

    This function sets up a new asyncio event loop, initializes the PromptServer,
    creates a PromptQueue, and initializes the custom nodes.
    """
    import asyncio
    import execution
    from nodes import init_extra_nodes
    import server

    # Creating a new event loop and setting it as the default loop
    loop = asyncio.new_event_loop()
    asyncio.set_event_loop(loop)

    # Creating an instance of PromptServer with the loop
    server_instance = server.PromptServer(loop)
    execution.PromptQueue(server_instance)

    # Initializing custom nodes
    init_extra_nodes()


from nodes import (
    VAEDecode,
    KSampler,
    NODE_CLASS_MAPPINGS,
    VAELoader,
    VAEEncode,
    CheckpointLoaderSimple,
    CLIPTextEncode,
    EmptyLatentImage,
    LoraLoader,
)


def generate_image(prompt: str, negative_prompt: str):
    import_custom_nodes()
    with torch.inference_mode():
        checkpointloadersimple = CheckpointLoaderSimple()
        checkpointloadersimple_4 = checkpointloadersimple.load_checkpoint(
            ckpt_name="counterfeitV30_v30.safetensors"
        )

        emptylatentimage = EmptyLatentImage()
        emptylatentimage_5 = emptylatentimage.generate(
            width=768, height=384, batch_size=1
        )

        loraloader = LoraLoader()
        loraloader_51 = loraloader.load_lora(
            lora_name="pastelMixStylizedAnime_pastelMixLoraVersion.safetensors",
            strength_model=1,
            strength_clip=1,
            model=get_value_at_index(checkpointloadersimple_4, 0),
            clip=get_value_at_index(checkpointloadersimple_4, 1),
        )

        loraloader_61 = loraloader.load_lora(
            lora_name="ligne_claire_anime.safetensors",
            strength_model=1,
            strength_clip=1,
            model=get_value_at_index(loraloader_51, 0),
            clip=get_value_at_index(loraloader_51, 1),
        )

        cliptextencode = CLIPTextEncode()
        cliptextencode_6 = cliptextencode.encode(
            text=f"(masterpiece, best quality), {prompt}",
            clip=get_value_at_index(loraloader_61, 1),
        )

        vaeloader = VAELoader()
        vaeloader_12 = vaeloader.load_vae(vae_name="sdVAEForAnime_v10.pt")

        cliptextencode_38 = cliptextencode.encode(
            text=f"embedding:easynegative, embedding:negative_hand-neg, embedding:7dirtywords, {negative_prompt}",
            clip=get_value_at_index(loraloader_61, 1),
        )

        ksampler = KSampler()
        ksampler_3 = ksampler.sample(
            seed=random.randint(1, 2**64),
            steps=26,
            cfg=6,
            sampler_name="dpmpp_2m",
            scheduler="karras",
            denoise=1,
            model=get_value_at_index(loraloader_61, 0),
            positive=get_value_at_index(cliptextencode_6, 0),
            negative=get_value_at_index(cliptextencode_38, 0),
            latent_image=get_value_at_index(emptylatentimage_5, 0),
        )

        vaedecode = VAEDecode()
        vaedecode_47 = vaedecode.decode(
            samples=get_value_at_index(ksampler_3, 0),
            vae=get_value_at_index(vaeloader_12, 0),
        )

        imagesharpen = NODE_CLASS_MAPPINGS["ImageSharpen"]()
        imagesharpen_85 = imagesharpen.sharpen(
            sharpen_radius=1,
            sigma=1,
            alpha=1,
            image=get_value_at_index(vaedecode_47, 0),
        )

        vaeencode = VAEEncode()
        vaeencode_86 = vaeencode.encode(
            pixels=get_value_at_index(imagesharpen_85, 0),
            vae=get_value_at_index(vaeloader_12, 0),
        )

        nnlatentupscale = NODE_CLASS_MAPPINGS["NNLatentUpscale"]()
        saveimages3 = NODE_CLASS_MAPPINGS["SaveImageS3"]()

        nnlatentupscale_31 = nnlatentupscale.upscale(
            version="SD 1.x",
            upscale=1.5,
            latent=get_value_at_index(vaeencode_86, 0),
        )

        ksampler_53 = ksampler.sample(
            seed=random.randint(1, 2**64),
            steps=30,
            cfg=6,
            sampler_name="dpmpp_2m",
            scheduler="karras",
            denoise=1,
            model=get_value_at_index(loraloader_61, 0),
            positive=get_value_at_index(cliptextencode_6, 0),
            negative=get_value_at_index(cliptextencode_38, 0),
            latent_image=get_value_at_index(nnlatentupscale_31, 0),
        )

        vaedecode_42 = vaedecode.decode(
            samples=get_value_at_index(ksampler_53, 0),
            vae=get_value_at_index(vaeloader_12, 0),
        )

        saveimages3_89 = saveimages3.save_images(
            filename_prefix="waifu", images=get_value_at_index(vaedecode_42, 0)
        )

        return get_value_at_index(saveimages3_89, 0)
    

def generate_presigned_url(bucket_name: str, object_name: str, expiration: int = 3600):
    s3_client = boto3.client(
        "s3",
        aws_access_key_id=os.environ["AWS_ACCESS_KEY_ID"],
        aws_secret_access_key=os.environ["AWS_SECRET_ACCESS_KEY"],
        endpoint_url=os.environ["AWS_ENDPOINT_URL_S3"],
        region_name=os.environ.get("AWS_REGION", None),
    )

    try:
        response = s3_client.generate_presigned_url(
            "get_object",
            Params={"Bucket": bucket_name, "Key": object_name},
            ExpiresIn=expiration,
        )
    except Exception as e:
        print(f"Error generating presigned URL: {e}")
        return None

    return response


@app.route("/", methods=["GET"])
def read_root():
    return jsonify({"Hello": "World"})


@app.route("/health-check", methods=["GET"])
def health_check():
    return jsonify({"status": "READY"})


@app.route("/generate", methods=["POST"])
def generate():
    content_type = request.headers.get('Content-Type')
    if (content_type == 'application/json'):
        json = request.json
    else:
        return 'Content-Type not supported!'
    
    image_response = generate_image(json["prompt"], json["negative_prompt"])

    return jsonify({
        "fname": image_response,
        "url": generate_presigned_url(
            os.getenv("BUCKET_NAME", "comfyui"), image_response[0]
        ),
    })


if __name__ == "__main__":
    app.run(host="0.0.0.0", port=8080)