import gradio as gr
from huggingface_hub import HfApi, hf_hub_url
import os
from pathlib import Path
import gc
import requests
from requests.adapters import HTTPAdapter
from urllib3.util import Retry
from utils import get_token, set_token, is_repo_exists, get_user_agent, get_download_file


def upload_safetensors_to_repo(filename, repo_id, repo_type, is_private, progress=gr.Progress(track_tqdm=True)):
    output_filename = Path(filename).name
    hf_token = get_token()
    api = HfApi(token=hf_token)
    try:
        if not is_repo_exists(repo_id, repo_type): api.create_repo(repo_id=repo_id, repo_type=repo_type, token=hf_token, private=is_private)
        progress(0, desc="Start uploading...")
        api.upload_file(path_or_fileobj=filename, path_in_repo=output_filename, repo_type=repo_type, revision="main", token=hf_token, repo_id=repo_id)
        progress(1, desc="Uploaded.")
        url = hf_hub_url(repo_id=repo_id, repo_type=repo_type, filename=output_filename)
    except Exception as e:
        print(f"Error: Failed to upload to {repo_id}. {e}")
        gr.Warning(f"Error: Failed to upload to {repo_id}. {e}")
        return None
    return url


def download_file(dl_url, civitai_key, progress=gr.Progress(track_tqdm=True)):
    download_dir = "."
    progress(0, desc="Start downloading...")
    output_filename = get_download_file(download_dir, dl_url, civitai_key)
    return output_filename


def download_civitai(dl_url, civitai_key, hf_token, urls, 
                     newrepo_id, repo_type="model", is_private=True, progress=gr.Progress(track_tqdm=True)):
    if hf_token: set_token(hf_token)
    else: set_token(os.environ.get("HF_TOKEN"))
    if not civitai_key: civitai_key = os.environ.get("CIVITAI_API_KEY")
    if not hf_token or not civitai_key: raise gr.Error("HF write token and Civitai API key is required.")
    file = download_file(dl_url, civitai_key)
    if not urls: urls = []
    url = upload_safetensors_to_repo(file, newrepo_id, repo_type, is_private)
    progress(1, desc="Processing...")
    if url: urls.append(url)
    Path(file).unlink()
    md = ""
    for u in urls:
        md += f"[Uploaded {str(u)}]({str(u)})<br>"
    gc.collect()
    return gr.update(value=urls, choices=urls), gr.update(value=md)


CIVITAI_TYPE = ["Checkpoint", "TextualInversion", "Hypernetwork", "AestheticGradient", "LORA", "Controlnet", "Poses"]
CIVITAI_BASEMODEL = ["Pony", "SD 1.5", "SDXL 1.0", "Flux.1 D", "Flux.1 S"]
CIVITAI_SORT = ["Highest Rated", "Most Downloaded", "Newest"]
CIVITAI_PERIOD = ["AllTime", "Year", "Month", "Week", "Day"]


def search_on_civitai(query: str, types: list[str], allow_model: list[str] = [], limit: int = 100,
                           sort: str = "Highest Rated", period: str = "AllTime", tag: str = ""):

    user_agent = get_user_agent()
    headers = {'User-Agent': user_agent, 'content-type': 'application/json'}
    base_url = 'https://civitai.com/api/v1/models'
    params = {'sort': sort, 'period': period, 'limit': limit, 'nsfw': 'true'}
    if len(types) != 0: params["types"] = types
    if query: params["query"] = query
    if tag: params["tag"] = tag
    session = requests.Session()
    retries = Retry(total=5, backoff_factor=1, status_forcelist=[500, 502, 503, 504])
    session.mount("https://", HTTPAdapter(max_retries=retries))
    try:
        r = session.get(base_url, params=params, headers=headers, stream=True, timeout=(3.0, 30))
    except Exception as e:
        print(e)
        return None
    else:
        if not r.ok: return None
        json = r.json()
        if 'items' not in json: return None
        items = []
        for j in json['items']:
            for model in j['modelVersions']:
                item = {}
                if len(allow_model) != 0 and model['baseModel'] not in set(allow_model): continue
                item['name'] = j['name']
                item['creator'] = j['creator']['username']
                item['tags'] = j['tags']
                item['model_name'] = model['name']
                item['base_model'] = model['baseModel']
                item['dl_url'] = model['downloadUrl']
                item['md'] = f'<img src="{model["images"][0]["url"]}" alt="thumbnail" width="150" height="240"><br>[LoRA Model URL](https://civitai.com/models/{j["id"]})'
                items.append(item)
        return items


civitai_last_results = {}


def search_civitai(query, types, base_model=[], sort=CIVITAI_SORT[0], period=CIVITAI_PERIOD[0], tag=""):
    global civitai_last_results
    items = search_on_civitai(query, types, base_model, 100, sort, period, tag)
    if not items: return gr.update(choices=[("", "")], value="", visible=False),\
          gr.update(value="", visible=False), gr.update(visible=True), gr.update(visible=True)
    civitai_last_results = {}
    choices = []
    for item in items:
        base_model_name = "Pony🐴" if item['base_model'] == "Pony" else item['base_model']
        name = f"{item['name']} (for {base_model_name} / By: {item['creator']} / Tags: {', '.join(item['tags'])})"
        value = item['dl_url']
        choices.append((name, value))
        civitai_last_results[value] = item
    if not choices: return gr.update(choices=[("", "")], value="", visible=False),\
          gr.update(value="", visible=False), gr.update(visible=True), gr.update(visible=True)
    result = civitai_last_results.get(choices[0][1], "None")
    md = result['md'] if result else ""
    return gr.update(choices=choices, value=choices[0][1], visible=True), gr.update(value=md, visible=True),\
          gr.update(visible=True), gr.update(visible=True)


def select_civitai_item(search_result):
    if not "http" in search_result: return gr.update(value=""), gr.update(value="None", visible=True)
    result = civitai_last_results.get(search_result, "None")
    md = result['md'] if result else ""
    return gr.update(value=search_result), gr.update(value=md, visible=True)