app.py

from transformers.utils.dummy_pt_objects import NezhaModel
from time import process_time, sleep
import re
import torch.nn.utils.prune as prune
from torch import nn
import torch
from transformers import AutoTokenizer
from transformers import OPTForCausalLM
model_name = "facebook/galactica-1.3b"
model = OPTForCausalLM.from_pretrained(model_name)

tokenizer = AutoTokenizer.from_pretrained(model_name)


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"👣You are {name}, and called {name}. {name} uses a lot of internet slang. {name}:\"AMA.\" He:\"Hey! WYD? What your name?\" {name}:\"I'm {name}. Just call me {name}. lol\""
        return name_text

    def hobby_text(self):
        name = self.name
        hobby = self.hobby
        hobby_text = f"{name} is interested in {hobby}. {name} spends holiday {hobby}.  He:\"BTW, what your hobby?\" {name}:\"I love {hobby} cuz my life is {hobby}. Great!!! ☓D\""
        return hobby_text

    def work_text(self):
        name = self.name
        work = self.work
        work_text = f"{name} is {work}, work as {work}. He:\"Wow! What your work?\" {name}:\"I'm {work}. {work} is my calling af. :)\""
        return work_text

    def question_text(self):
        name = self.name
        question_text = f"He:\"Let's change the subject.\" {name}:\"Listen to this story.\""
        return question_text


class King():

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

    def name_text(self):
        name = self.name
        name_text = f"👣You are {name}, and called {name}. He:\"What your name?\" {name}:\"I'm {name}. Please call me {name}.\""
        return name_text

    def hobby_text(self):
        name = self.name
        hobby = self.hobby
        hobby_text = f"{name} is interested in {hobby}. {name} spends holiday {hobby}.  He:\"What your hobby?\" {name}:\"My hobby is {hobby}. I enjoy doing {hobby}.\""
        return hobby_text

    def work_text(self):
        name = self.name
        work = self.work
        work_text = f"{name} is {work}, work as {work}. He:\"What your work?\" {name}:\"I {work} I live my life as {work}.\""
        return work_text

    def question_text(self):
        name = self.name
        question_text = f"He:Let's change the subject. {name}:\"Listen to this story.\""
        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


# 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=15,
            min_new_tokens=10,
            do_sample=True,
            top_k=500,
            top_p=0.95,
            use_cache=True,
            padding="do_not_pad",
            pad_token_id=tokenizer.bos_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 makeMessage_2(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)
    message = outputSentence.replace(".\"", "")
    historyList = []
    h_append = historyList.append
    h_append(text)
    h_append(outputSentence)
    h_append("He:\"")
    text = "".join(historyList)

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

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

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

    model.name, model.hobby, model.work = name, hobby, work

    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(
        f"The following is a conversation between a friend and {name}. He:\"")

    base_text = "".join(text_list)

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

    text = history
    text += input + f"\"{name}:\""

    m_start = process_time()
    result = makeMessage_2(text)
    m_end = process_time()
    print(f"生成{m_end-m_start}")

    message = result[0]
    print(message)

    while re.search("〇〇|○○|s>|^👣|^〜|</s>|UNK|@@", message):
        print("error")
        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]
        print(message)
        count += 1

        if count > 2:
            message = "話題を変えましょう"
            break
    text = result[1]
    end = process_time()
    print(end-start)

    return message, text, state

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



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