old2/modules/events/sdxl_events.py

import spaces
import gradio as gr
from huggingface_hub import ModelCard

from modules.helpers.common_helpers import ControlNetReq, BaseReq, BaseImg2ImgReq, BaseInpaintReq
from modules.helpers.sdxl_helpers import gen_img
from config import sdxl_loras

loras = sdxl_loras

# Event functions
def update_fast_generation(fast_generation):
    if fast_generation:
        return (
            gr.update(
                value=0.0
            ),
            gr.update(
                value=8
            )
        )
    else:
        return (
            gr.update(
                value=7.0
            ),
            gr.update(
                value=20
            )
        )


def add_to_enabled_loras(selected_lora, enabled_loras):
    lora_data = loras
    try:
        selected_lora = int(selected_lora)
        
        if 0 <= selected_lora: # is the index of the lora in the gallery
            lora_info = lora_data[selected_lora]
            enabled_loras.append({
                "repo_id": lora_info["repo"],
                "trigger_word": lora_info["trigger_word"]
            })
    except ValueError:
        link = selected_lora.split("/")
        if len(link) == 2:
            model_card = ModelCard.load(selected_lora)
            trigger_word = model_card.data.get("instance_prompt", "")
            enabled_loras.append({
                "repo_id": selected_lora,
                "trigger_word": trigger_word
            })
    
    return (
        gr.update( # selected_lora
            value=""
        ),
        gr.update( # custom_lora_info
            value="",
            visible=False
        ),
        gr.update( # enabled_loras
            value=enabled_loras
        )
    )


@spaces.GPU(duration=75)
def generate_image(
    model, prompt, negative_prompt, fast_generation, enabled_loras, enabled_embeddings, # type: ignore
    lora_slider_0, lora_slider_1, lora_slider_2, lora_slider_3, lora_slider_4, lora_slider_5, # type: ignore
    img2img_image, inpaint_image, canny_image, pose_image, depth_image, scribble_image, # type: ignore
    img2img_strength, inpaint_strength, canny_strength, pose_strength, depth_strength, scribble_strength, # type: ignore
    resize_mode,
    scheduler, image_height, image_width, image_num_images_per_prompt, # type: ignore
    image_num_inference_steps, image_clip_skip, image_guidance_scale, image_seed, # type: ignore
    refiner, vae
):
    try:
        base_args = {
            "model": model,
            "prompt": prompt,
            "negative_prompt": negative_prompt,
            "fast_generation": fast_generation,
            "loras": None,
            "embeddings": None,
            "resize_mode": resize_mode,
            "scheduler": scheduler,
            "height": image_height,
            "width": image_width,
            "num_images_per_prompt": image_num_images_per_prompt,
            "num_inference_steps": image_num_inference_steps,
            "clip_skip": image_clip_skip,
            "guidance_scale": image_guidance_scale,
            "seed": image_seed,
            "refiner": refiner,
            "vae": vae,
            "controlnet_config": None,
        }
        base_args = BaseReq(**base_args)
        
        if len(enabled_loras) > 0:
            base_args.loras = []
            for enabled_lora, slider in zip(enabled_loras, [lora_slider_0, lora_slider_1, lora_slider_2, lora_slider_3, lora_slider_4, lora_slider_5]):
                if enabled_lora["repo_id"]:
                    base_args.loras.append({
                        "repo_id": enabled_lora["repo_id"],
                        "weight": slider
                    })
        
        if len(enabled_embeddings) > 0:
            base_args.embeddings = enabled_embeddings
        
        image = None
        mask_image = None
        strength = None
        
        if img2img_image:
            image = img2img_image
            strength = float(img2img_strength)
            
            base_args = BaseImg2ImgReq(
                **base_args.__dict__,
                image=image,
                strength=strength
            )
        elif inpaint_image:
            image = inpaint_image['background'] if not all(pixel == (0, 0, 0) for pixel in list(inpaint_image['background'].getdata())) else None
            mask_image = inpaint_image['layers'][0] if image else None
            strength = float(inpaint_strength)
            
            if image and mask_image:
                base_args = BaseInpaintReq(
                    **base_args.__dict__,
                    image=image,
                    mask_image=mask_image,
                    strength=strength
                )
        elif any([canny_image, pose_image, depth_image]):
            base_args.controlnet_config = ControlNetReq(
                controlnets=[],
                control_images=[],
                controlnet_conditioning_scale=[]
            )
            
            if canny_image:
                base_args.controlnet_config.controlnets.append("canny")
                base_args.controlnet_config.control_images.append(canny_image)
                base_args.controlnet_config.controlnet_conditioning_scale.append(float(canny_strength))
            if pose_image:
                base_args.controlnet_config.controlnets.append("pose")
                base_args.controlnet_config.control_images.append(pose_image)
                base_args.controlnet_config.controlnet_conditioning_scale.append(float(pose_strength))
            if depth_image:
                base_args.controlnet_config.controlnets.append("depth")
                base_args.controlnet_config.control_images.append(depth_image)
                base_args.controlnet_config.controlnet_conditioning_scale.append(float(depth_strength))
            if scribble_image:
                base_args.controlnet_config.controlnets.append("scribble")
                base_args.controlnet_config.control_images.append(scribble_image)
                base_args.controlnet_config.controlnet_conditioning_scale.append(float(scribble_strength))
        else:
            base_args = BaseReq(**base_args.__dict__)
        
        return gr.update(
            value=gen_img(base_args),
            interactive=True
        )
    except Exception as e:
        raise gr.Error(f"Error: {e}") from e