ctag.py

import gradio as gr
import pandas as pd
import json
import requests
from requests.adapters import HTTPAdapter
from urllib3.util import Retry
from pykakasi import kakasi


MODELS = ["Animagine 3.1", "NoobAI XL", "Illustrious"]
DEFAULT_DF = pd.DataFrame({"Character": ["oomuro sakurako (yuru yuri) (NoobAI XL)", "kafuu chino (gochuumon wa usagi desu ka?) (Animagine 3.1)"]})


kks = kakasi()


def to_roman(s: str):
    try:
        return "".join([i.get("hepburn", "") for i in kks.convert(s)])
    except Exception as e:
        print(e)
        return s


def get_user_agent():
    return 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:127.0) Gecko/20100101 Firefox/127.0'


def get_series_wiki_dict():
    user_agent = get_user_agent()
    headers = {'User-Agent': user_agent, 'content-type': 'application/json'}
    base_url = 'https://www.animecharactersdatabase.com/api_series_characters.php?title_wiki_links'
    params = {}
    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=(5.0, 15))
        if not r.ok: return {}
        j = dict(r.json())
        if "titles" not in j: return {}
        return {str(i["anime_id"]): i["wikipedia_url"] for i in j["titles"]}
    except Exception as e:
        print(e)
        return {}


series_wiki_dict = get_series_wiki_dict()


def find_char_info(query: str):
    user_agent = get_user_agent()
    headers = {'User-Agent': user_agent, 'content-type': 'application/json'}
    base_url = 'https://www.animecharactersdatabase.com/api_series_characters.php'
    params = {"character_q": query}
    params2 = {"character_q": " ".join(list(reversed(query.split(" "))))}
    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=(5.0, 15))
        if not r.ok or r.json() == -1:
            r = session.get(base_url, params=params2, headers=headers, stream=True, timeout=(5.0, 15))
            if not r.ok or r.json() == -1: return None
        j = dict(r.json())
        if "search_results" not in j or len(j["search_results"]) == 0: return None
        d = {}
        i = j["search_results"][0]
        d["name"] = i["name"]
        d["series"] = i["anime_name"]
        d["gender"] = i["gender"]
        d["image"] = i["character_image"]
        d["desc"] = i["desc"]
        aid = str(i["anime_id"])
        if aid in series_wiki_dict.keys(): d["wiki"] = series_wiki_dict[aid]
        return d
    except Exception as e:
        print(e)
        return None


def load_json(filename: str):
    try:
        with open(filename, encoding="utf-8") as f:
            d = json.load(f)
        return dict(d)
    except Exception as e:
        print(e)
        return {}


def load_char_dict():
    d = {}
    d["Animagine 3.1"] = load_json("data/animagine.json")
    d["Illustrious"] = load_json("data/illustrious.json")
    d["NoobAI XL"] = load_json("data/noob_danbooru.json") | load_json("data/noob_e621.json")
    return d


def create_char_df(char_dict: dict):
    d = {}
    m = {}
    tags = []
    for model, value in char_dict.items():
        for name, v in value.items():
            tag = f'{v["name"]} ({v["series"]}) ({model})' if v["series"] else f'{v["name"]} ({model})'
            tags.append(tag)
            d[tag] = v.copy()
            m[tag] = model
    df = pd.DataFrame({"Character": tags})
    return df, d, m


char_dict = load_char_dict()
char_df, tag_dict, model_dict = create_char_df(char_dict)


def search_char_dict(q: str, models: list[str], progress=gr.Progress(track_tqdm=True)):
    try:
        MAX_COLS = 50
        if q.strip():
            #search_results = df[df["Character"].str.contains(to_roman(q).lower(), regex=False, na=False) & df["Character"].str.contains("(?: \\(" + "\\))|(?: \\(".join(models) + "\\))", regex=True, na=False)]
            l = char_df["Character"].tolist()
            rq = to_roman(q).lower()
            mt = tuple([f" ({s})" for s in models])
            search_results = pd.DataFrame({"Character": [s for s in l if rq in s and s.endswith(mt)]})
        else:
            return DEFAULT_DF
        if len(search_results.columns) > MAX_COLS:
            search_results = search_results.iloc[:, :MAX_COLS]
        return search_results
    except Exception as e:
        print(e)


def on_select_df(df: pd.DataFrame, is_detail: bool, evt: gr.SelectData):
    d = tag_dict.get(evt.value, None)
    if d is None: return ""
    #print(d) #
    if is_detail: info = find_char_info(d["name"])
    else: info = None
    #print(info) #
    if info is not None:
        md = f'## [{info["name"]}]({info["wiki"]}) / [{info["series"]}]({info["wiki"]}) / {info["gender"]}\n![{info["name"]}]({info["image"]}#center)\n[{info["desc"]}]({info["wiki"]})'
    else: md = f'## {d["name"]} / {d["series"]}' if d["series"] else f'## {d["name"]}'
    md += f'\n<br>Tag is for {model_dict[evt.value]}.'
    return d["tag"], model_dict[evt.value], md