import uvicorn
from gradio.processing_utils import encode_pil_to_base64, decode_base64_to_file, decode_base64_to_image
from fastapi import APIRouter, HTTPException
import modules.shared as shared
from modules.api.models import *
from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
from modules.sd_samplers import all_samplers
from modules.extras import run_extras

def upscaler_to_index(name: str):
    try:
        return [x.name.lower() for x in shared.sd_upscalers].index(name.lower())
    except:
        raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be on of these: {' , '.join([x.name for x in sd_upscalers])}")

sampler_to_index = lambda name: next(filter(lambda row: name.lower() == row[1].name.lower(), enumerate(all_samplers)), None)

def setUpscalers(req: dict):
    reqDict = vars(req)
    reqDict['extras_upscaler_1'] = upscaler_to_index(req.upscaler_1)
    reqDict['extras_upscaler_2'] = upscaler_to_index(req.upscaler_2)
    reqDict.pop('upscaler_1')
    reqDict.pop('upscaler_2')
    return reqDict

class Api:
    def __init__(self, app, queue_lock):
        self.router = APIRouter()
        self.app = app
        self.queue_lock = queue_lock
        self.app.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=TextToImageResponse)
        self.app.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=ImageToImageResponse)
        self.app.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse)
        self.app.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse)

    def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
        sampler_index = sampler_to_index(txt2imgreq.sampler_index)
        
        if sampler_index is None:
            raise HTTPException(status_code=404, detail="Sampler not found") 
        
        populate = txt2imgreq.copy(update={ # Override __init__ params
            "sd_model": shared.sd_model, 
            "sampler_index": sampler_index[0],
            "do_not_save_samples": True,
            "do_not_save_grid": True
            }
        )
        p = StableDiffusionProcessingTxt2Img(**vars(populate))
        # Override object param
        with self.queue_lock:
            processed = process_images(p)
        
        b64images = list(map(encode_pil_to_base64, processed.images))
        
        return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())

    def img2imgapi(self, img2imgreq: StableDiffusionImg2ImgProcessingAPI):
        sampler_index = sampler_to_index(img2imgreq.sampler_index)
        
        if sampler_index is None:
            raise HTTPException(status_code=404, detail="Sampler not found") 


        init_images = img2imgreq.init_images
        if init_images is None:
            raise HTTPException(status_code=404, detail="Init image not found") 

        mask = img2imgreq.mask
        if mask:
            mask = decode_base64_to_image(mask)

        
        populate = img2imgreq.copy(update={ # Override __init__ params
            "sd_model": shared.sd_model, 
            "sampler_index": sampler_index[0],
            "do_not_save_samples": True,
            "do_not_save_grid": True, 
            "mask": mask
            }
        )
        p = StableDiffusionProcessingImg2Img(**vars(populate))

        imgs = []
        for img in init_images:
            img = decode_base64_to_image(img)
            imgs = [img] * p.batch_size

        p.init_images = imgs
        # Override object param
        with self.queue_lock:
            processed = process_images(p)
        
        b64images = list(map(encode_pil_to_base64, processed.images))

        if (not img2imgreq.include_init_images):
            img2imgreq.init_images = None
            img2imgreq.mask = None
       
        return ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js())

    def extras_single_image_api(self, req: ExtrasSingleImageRequest):
        reqDict = setUpscalers(req)

        reqDict['image'] = decode_base64_to_image(reqDict['image'])

        with self.queue_lock:
            result = run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", **reqDict)

        return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1])

    def extras_batch_images_api(self, req: ExtrasBatchImagesRequest):
        reqDict = setUpscalers(req)

        def prepareFiles(file):
            file = decode_base64_to_file(file.data, file_path=file.name)
            file.orig_name = file.name
            return file

        reqDict['image_folder'] = list(map(prepareFiles, reqDict['imageList']))
        reqDict.pop('imageList')

        with self.queue_lock:
            result = run_extras(extras_mode=1, image="", input_dir="", output_dir="", **reqDict)

        return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
    
    def pnginfoapi(self):
        raise NotImplementedError

    def launch(self, server_name, port):
        self.app.include_router(self.router)
        uvicorn.run(self.app, host=server_name, port=port)