import fal_client
import pandas as pd
from prompt_gen import prompt_gen
import requests
import os

nv_prompt_file = pd.read_excel('汉服-女词库.xlsx')
na_prompt_file = pd.read_excel('汉服-男词库.xlsx')
nv_prompt = nv_prompt_file.to_string(index=False)
na_prompt = na_prompt_file.to_string(index=False)


def cloth_gen(advice, gender):
    lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NA.safetensors"
    if gender == "男":
        lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NA.safetensors"
    elif gender == "女":
        lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NV.safetensors"

    prompt = prompt_gen(advice, gender)
    start_index = prompt.find("prompt" or "Prompt")
    intro_index = prompt.find("服饰风格介绍")
    cloth_intro = ""
    promptGen = ""
    if start_index != -1:
        start_index += len("prompt\n")
        end_index = prompt.find("promptEnd")
        if end_index != -1:
            extracted_content = prompt[start_index:end_index]
            promptGen = extracted_content
            print(extracted_content)
        else:
            print("No 'promptEnd' found after 'prompt'.")
    else:
        print("No 'prompt' found in the text.")
    if intro_index != -1:
        intro_index += len("服饰风格介绍\n")
        cloth_intro = ("汉服，是汉民族的传统服饰。又称衣冠、衣裳、汉装。汉服是中国“衣冠上国”“礼仪之邦”“锦绣中华”的体现，承载了中国的染织绣等杰出"
                       "工艺和美学，传承了30多项中国非物质文化遗产以及受保护的中国工艺美术。\n") + prompt[intro_index:]
        print(cloth_intro)
    else:
        print("No '服饰风格介绍' found.")

    handler = fal_client.submit(
        "fal-ai/fast-sdxl",
        arguments={
            "prompt": promptGen,
            "negative_prompt": "human, people, person, man, woman, child, model, face, head, eyes, hands, arms, legs, "
                               "feet, hair, portrait, worst quality, low quality, normal quality, lowres, signature, "
                               "watermark, jpeg artifacts, logo, monochrome, grayscale, ugly",
            "image_size": "portrait_4_3",
            "num_inference_steps": 28,
            "guidance_scale": 7.5,
            "num_images": 6,
            "loras": [{"path": lora_path, "scale": 0.7}],
            "embeddings": [],
            "safety_checker_version": "v1",
            "format": "jpeg"
        },
    )

    request_id = handler.request_id
    result = fal_client.result("fal-ai/fast-sdxl", request_id)
    cloth_image = []
    save_directory = "downloads"
    image_index = 1
    for image in result['images']:
        response = requests.get(image['url'])
        if response.status_code == 200:
            filename = os.path.join(save_directory, f"gen_cloth_{image_index}.jpeg")
            cloth_image.append(filename)
            with open(filename, 'wb') as f:
                f.write(response.content)
            image_index += 1
        else:
            print(f"Failed to download image from {image['url']}")
    return cloth_image, cloth_image[0], cloth_intro