from huggingface_hub import hf_hub_download

import os
import time
import gradio as gr
import yt_dlp
import sys
import uuid
import traceback
import tensorflow
import csv

embed_html1 = '<iframe width="560" height="315" src="https://www.youtube.com/embed/'
embed_html2 = '" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>'
# NO GPU
# os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"

# tensorflow.config.threading.set_intra_op_parallelism_threads(8)
# tensorflow.config.threading.set_inter_op_parallelism_threads(8)
print(tensorflow.config.list_physical_devices("GPU"))
#
python_path = hf_hub_download(
    repo_id=os.environ["REPO_ID"],
    repo_type="space",
    filename=os.environ["MODEL_FILE"],
    use_auth_token=os.environ["TOKEN"],
)
# print("PATH : ", python_path)
sys.path.append(os.environ["PRIVATE_DIR"])
from models import *

max_results = 100
max_output = 50

# global (faster)
ind = get_index()
ind_filenames = get_audio_names()
catalog = get_catalog()
url_dict = get_durl_myma()
dict_catalog = get_dict_catalog()


def download_audio_(link):
    file_name = f"{uuid.uuid4()}.mp3"
    with yt_dlp.YoutubeDL(
        {"extract_audio": True, "format": "bestaudio", "outtmpl": file_name}
    ) as video:
        video.download(link)
        return file_name


def download_audio(id_video):
    id = id_video.split("?v=")[-1][:11]
    file_name = download_audio_(id_video)
    embed_html_all = embed_html1 + id + embed_html2
    return file_name, embed_html_all


def process_url(input_path):
    # setup the client
    # try :
    file_name, embed_html_all = download_audio(input_path)
    return process(file_name, embed_html_all)
    # except:
    #    return "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", ""


def process_file(input_path):
    return process(input_path, "")[1:]


def process(file_name, embed_html_all):
    """try :"""
    emb, _ = get_embed(file_name)
    try:
        os.remove(file_name)
    except:
        print(traceback.format_exc())

    # => global

    timestart = time.time()
    _, I = do_search(emb, ind)
    print("search time :", time.time() - timestart)

    tops = get_topN(I, ind_filenames, url_dict, catalog, max_results)
    formated = []
    output_csv = f"{file_name}_results.csv"
    with open(output_csv, "w") as w:
        writer = csv.writer(w)
        num_results = 0
        header = False
        for top in tops:
            if num_results > max_output:
                break

            file = os.path.splitext(os.path.basename(top))[0]
            if file in dict_catalog:
                if not header:
                    writer.writerow(list(dict_catalog[file].keys()))
                    header = True
                writer.writerow(dict_catalog[file].values())
            else:
                writer.writerow([file, "no metadata provided"])

            formated.append(file)
            formated.append(top)
            num_results += 1

    return (embed_html_all, output_csv, *formated)
    """except:
        return embed_html_all, "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", "", "Erreur Input", ""
    """


with gr.Blocks() as demo:
    tops = []
    with gr.Row():
        with gr.Column():
            with gr.Row():
                # gr.HTML(embed_html)
                html = gr.HTML()

            with gr.Row():
                with gr.Column():
                    audio_url_input = gr.Textbox(
                        placeholder="YouTube video URL", label="YouTube video URL"
                    )
                    analyze_url_btn = gr.Button("Search from URL")

            with gr.Row():
                with gr.Column():
                    audio_input_file = gr.Audio(type="filepath", label="Audio Input")
                    analyze_file_btn = gr.Button("Search from file")

            with gr.Row():
                with gr.Column():
                    results = gr.File()

            with gr.Row():
                with gr.Column():
                    for i in range(max_output):
                        tops.append(
                            gr.Textbox(label=f"top{i} track name", show_label=True)
                        )
                        tops.append(gr.Audio(label=f"top{i}", show_label=False))

    analyze_url_btn.click(
        process_url, inputs=[audio_url_input], outputs=[html, results] + tops
    )
    gr.Examples(
        examples=[
            "https://www.youtube.com/watch?v=aNzCDt2eidg",
            "https://www.youtube.com/watch?v=NBE-uBgtINg",
            "https://www.youtube.com/watch?v=5NV6Rdv1a3I",
            "https://www.youtube.com/watch?v=OiC1rgCPmUQ",  #
            "https://www.youtube.com/watch?v=dRX0wDNK6S4",  #
            "https://www.youtube.com/watch?v=Guzu9aAeDIc",
        ],
        inputs=[audio_url_input],
        outputs=[html, results] + tops,
        fn=process_url,
        cache_examples=False,
    )
    analyze_file_btn.click(
        process_file,
        inputs=[audio_input_file],
        outputs=[results] + tops,
    )


demo.launch(debug=False)