app.py

import gradio as gr
import re
import torch.nn.utils.prune as prune
from torch import nn
import torch
from transformers import T5Tokenizer
from transformers import AutoModelForCausalLM


model_name = "rinna/japanese-gpt-1b"
model = AutoModelForCausalLM.from_pretrained(model_name)

tokenizer = T5Tokenizer.from_pretrained(model_name)

model = torch.quantization.quantize_dynamic(
    model, {torch.nn.Linear}, dtype=torch.qint8)


PRUNE_RATE = 0.2


def prune_transform(model: nn.Module) -> nn.Module:
    for name, module in model.named_modules():
        if isinstance(module, torch.nn.Linear):
            prune.l1_unstructured(module, name='weight', amount=PRUNE_RATE)
            prune.remove(module, "weight")
    return model


model = prune_transform(model)

class Lady():

    name = "レイテ"
    hobby = "ゲーム"
    work = "お嬢様"

    def name_text(self):
        name = self.name
        name_text = f"👣あなたは{name}で、名前は{name}といいます。{name}:「わたくしの名前は{name}ですわ〜。{name}と呼んでくださいまし!」"
        return name_text

    def hobby_text(self):
        name = self.name
        hobby = self.hobby
        hobby_text = f"{name}の趣味は{hobby}で、休日は{hobby}をして過ごしています。{name}:「わたくしは{hobby}が大好きなんですの。休日は{hobby}をしていますわ」"
        return hobby_text

    def work_text(self):
        name = self.name
        work = self.work
        work_text = f"{name}は{work}で、普段は{work}として生活しています。{name}:「わたくしは{work}ですわ!{work}として生活していますの」"
        return work_text

    def question_text(self):
        name = self.name
        question_text = f"人間:「話題を変えましょう」{name}:「そんなことより聞いてくださいます?」"
        return question_text


class King():

    name = "ネロ"
    hobby = "戦車競技"
    work = "ローマ皇帝"

    def name_text(self) -> str:
        name = self.name
        name_text = f"👣あなたは{name}で、名前は{name}といいます。{name}:「我が名は{name}である。{name}と呼んでくれたまえ」"
        return name_text

    def hobby_text(self) -> str:
        name = self.name
        hobby = self.hobby
        hobby_text = f"趣味は{hobby}で、休日は{hobby}をして過ごしています。{name}:「私は{hobby}を嗜んでいる。まさに{hobby}こそ人生の意味ではないか」"
        return hobby_text

    def work_text(self) -> str:
        name = self.name
        work = self.work
        work_text = f"{name}は{work}で、普段は{work}として生活しています。{name}:「私は{work}。{work}として生活している。」"
        return work_text

    def question_text(self) -> str:
        name = self.name
        question_text = f"人間:「話題を変えましょう」{name}:「そんなことより聞いてくれないか」"
        return question_text


class Robot():

    name = "ネロ"
    hobby = "戦車競技"
    work = "ローマ皇帝"

    def name_text(self) -> str:
        name = self.name
        name_text = f"👣あなたは{name}で、名前は{name}といいます。{name}:「私は{name}です。{name}と呼んでください」"
        return name_text

    def hobby_text(self) -> str:
        name = self.name
        hobby = self.hobby
        hobby_text = f"趣味は{hobby}で、休日は{hobby}をして過ごしています。{name}:「私の趣味は{hobby}です。{hobby}をしていると楽しいです」"
        return hobby_text

    def work_text(self) -> str:
        name = self.name
        work = self.work
        work_text = f"{name}は{work}で、普段は{work}として生活しています。{name}:「私は{work}。{work}として生活しています」"
        return work_text

    def question_text(self) -> str:
        name = self.name
        question_text = f"人間:「話題を変えましょう」{name}:「そんなことより聞いてください」"
        return question_text


class Friend():

    name = "ホメロス"
    hobby = "戦車競技"
    work = "ローマ皇帝"

    def name_text(self) -> str:
        name = self.name
        name_text = f"👣あなたは{name}で、名前は{name}といいます。{name}:「僕は{name}!{name}って呼んでね~」"
        return name_text

    def hobby_text(self) -> str:
        name = self.name
        hobby = self.hobby
        hobby_text = f"趣味は{hobby}で、休日は{hobby}をして過ごしています。{name}:「好きなことは{hobby}だね。たいくつな時は{hobby}をしてるよ」"
        return hobby_text

    def work_text(self) -> str:
        name = self.name
        work = self.work
        work_text = f"{name}は{work}で、普段は{work}として生活しています。{name}:「僕は{work}。{work}として暮らしてるんだ!」"
        return work_text

    def question_text(self) -> str:
        name = self.name
        question_text = f"人間:「話題を変えましょう」{name}:「そんなことより聞いてよ〜」"
        return question_text


settingText = ""

adult_list = [
    "エロビデオ",
    "エロムービー",
    "エロ漫画",
    "エロマンガ",
    "パパ活",
    "援交",
    "調教",
    "不倫",
    "ソープ",
    "オフパコ",
    "ビッチ",
    "dildo",
    "エロ同人",
    "寝取られ",
    "エロ画像",
    "エロい",
    "おっぱい",
    "ちんぽ",
    "ちんこ",
    "中出し",
    "アダルト",
    "セフレ",
    "人妻",
    "巨乳",
    "素人ナンパ",
    "爆乳",
    "熟女",
    "レイプ",
    "Hな",
    "痴漢",
    "痴女",
    "デカ乳",
    "AV女優",
    "セ●クス",
    "お●ぱい",
    "エチエチ",
    "エ□",
    "ヤリサー",
    "オ●ニー",
    "オナニー",
    "セ〇クス",
    "セックス",
    "ウルトラマンコスモス", "ウルトラマンコスモス",
    "マンコ",
    "個人撮影",
    "アナル",
    "工ロ",
    "まんこ",
    "乳首",
    "貧乳",
    "スケベ",
    "勃起",
    "エッチ",
    "童貞",
    "射精",
    "チンコ",
    "盗撮",
    "ハッテン",
    "チンポ",
    "亀頭",
    "肉棒",
    "ケツ穴",
    "ハメ撮り",
    "淫乱",
    "巨根",
    "メス堕ち",
    "カフェラテ", "カフェラテ",
    "ペニス",
    "正常位",
    "騎乗位",
    "オナホ",
    "我慢汁",
    "ザーメン",
    "ふたなり",
    "ビッチ",
    "アヘ顔",
    "おちんちん",
    "イラマチオ",
    "生ハメ",
    "パイズリ",
    "クリトリス",
    "快楽堕ち",
    "寝取り",
    "寝取られ",
    "えっち",
    "足コキ",
    "手コキ",
    "おねショタ",
    "フェラ",
    "クンニ",
    "近親相姦",
    "乱交",
    "青姦",
    "寝取る",
    "ヤリマン",
    "犯される",
    "セックス"
]
political_list = [
    "政治家",
    "政策",
    "会談",
    "同省",
    "自民",
    "総理",
    "与党",
    "民主",
    "政党",
    "首相",
    "議員",
    "財政",
    "行政",
    "野党",
    "右翼",
    "左翼"
]
hate_list = [

    "ツイッタラー",
    "黒人",
    "白人",
    "ネトウヨ",
    "韓国人",
    "中国人",
    "火病",
    "ダセェ",
    "そいつ",
    "こいつ",
    "やがれ",
    "アンチ",
    "クソ",
    "野郎",
    "フェミ",
    "フェミニズム",
    "ヤフコメ",
    "老害",
    "反日",
    "馬鹿",
    "あんた",
    "やれよ",
    "ニヤニヤ",
    "売国奴",
    "売国",
    "バカ",
    "パヨク",
    "ポリコレ",
    "統一教会",
    "ぶっ倒そう",
    "お前",
    "信者",
    "拝金",
    "ぶっ壊し",
    "アホ"
]
sp_list = ["〇〇", "○○", "^👣", "^〜", "UNK", "@@"]
all_list = adult_list + political_list + hate_list + sp_list
bad_code = "|".join(all_list)




def makeMessage(text):
    output = generate(text)
    # 半角正則化
    text = text.translate(str.maketrans(
        {chr(0xFF01 + i): chr(0x21 + i) for i in range(94)}))
    # 今回の応答より前を取得
    output = output.replace(text, "")
    # 最初の」までを分割する
    outputList = []
    o_append = outputList.append
    for l in output:
        o_append(l)
        if l == "」":
            break
    outputSentence = "".join(outputList)
    text += outputSentence + "人間:「"
    message = outputSentence.replace("」", "")
    return message, text


# 文章生成を行う関数。元になる文章、最大文字数、最小文字数を引数にもつ。


def generate(text):
    token_ids = tokenizer.encode(
        text, add_special_tokens=False, return_tensors="pt")
    with torch.no_grad():
        output_ids = model.generate(
            token_ids.to(model.device),
            max_new_tokens=10,
            min_new_tokens=7,
            do_sample=True,
            use_cache=True,
            top_k=500,
            top_p=0.95,
            length_penalty=1.5,
            padding="do_not_pad",
            pad_token_id=tokenizer.pad_token_id,
            bos_token_id=tokenizer.bos_token_id,
            eos_token_id=tokenizer.eos_token_id,
            bad_word_ids=[[tokenizer.unk_token_id],
                          [2070,    3],
                          [5378]]
        )
        output = tokenizer.decode(output_ids.tolist()[0])
        return output


def chat(character: int,
         name: str,
         hobby: str,
         work: str,
         setting: str,
         history: str,
         input: str,
         state):

    lady, friend, robot, king = Lady(), Friend(), Robot(), King()

    model_dic = {
        1: lady,
        2: friend,
        3: robot,
        4: king
    }
    if character in model_dic:
        model = model_dic[character]
    else:
        model = King()

    model.name, model.hobby, model.work, settingText = name, hobby, work, setting

    text_list = []
    text_append = text_list.append

    text_append(model.name_text())
    text_append(model.hobby_text())
    text_append(model.work_text())
    text_append(model.question_text())
    text_append(settingText)
    text_append(f"以下は人間と{name}の会話です。人間:「")

    base_text = "".join(text_list)

    if history == "":
        history = f"{base_text}"
    else:
        history = base_text + history

    text = history
    text += input + f"」{name}:「"
    result = makeMessage(text)
    message = result[0]
    print(result[0])
    while re.search("〇〇|○○|s>|^👣|^〜|</s>|UNK|@@", message):
        count = 0
        text = history
        input = "何か質問してください"
        text += input + f"」{name}:「"
        result = makeMessage(text)
        message = result[0]
        count += 1

        if count > 2:
            message = "話題を変えましょう"
            break
    text = result[1]
    text = text.replace(base_text, "")

    return message, text, state

tokenizer.special_tokens_map



textbox = gr.Textbox()
historybox = gr.Textbox()
iface = gr.Interface(
    fn=chat,
    inputs=["number", "text", "text", "text", "text", "text", textbox, "state"],
    outputs=["text", historybox, "state"],
    css=".footer {display:none !important}",
    allow_flagging="never",
    title="Loyal-AI-Chat"
)

iface.launch(inline=True, height=800)