qwen1_5_7B_ORPO_character_instruction_gradio.py

#### pip install gradio==3.50.2
import gradio as gr
import pandas as pd
import numpy as np
import os
import json
import re
from functools import partial

from rapidfuzz import fuzz
import imagehash
from datasets import load_dataset
from PIL import Image

character_img_ds = load_dataset("svjack/genshin-impact-character-image")
character_img_dict = dict(pd.Series(character_img_ds["train"]).map(lambda x: (x["name"], x["img"])).values.tolist())

partial_order_list = [
 '那维莱特',
 "芙宁娜",
 '魈',

 "可莉",
 "提纳里",
 "行秋", "柯莱", "凝光", "北斗", "五郎",

 '钟离',
 '纳西妲',
 '刻晴',
 '优菈',
 '八重神子',
 #'可莉',
 '夜兰',
 '妮露',
 '娜维娅',
 '宵宫',
 #'提纳里',
 '林尼',
 '枫原万叶',
 '流浪者',
 '温迪',
 '珊瑚宫心海',
 '琴',
 '甘雨',
 '申鹤',
 '白术',
 '神里绫人',
 '神里绫华',
 '胡桃',
 '艾尔海森',
 #'芙宁娜',
 '荒泷一斗',
 '莫娜',
 '莱欧斯利',
 '赛诺',
 '达达利亚',
 '迪卢克',
 '迪希雅',
 '阿贝多',
 '雷电将军',
 '七七'
 ]

im_list_a = []
im_list_b = []
for character_name, character_img in character_img_dict.items():
    if character_name in partial_order_list:
        im_list_a.append(character_img)
    else:
        im_list_b.append(character_img)
assert len(im_list_a) == len(partial_order_list)
im_list = pd.Series(partial_order_list).map(lambda x: character_img_dict[x]).values.tolist() + im_list_b

import jieba
def repeat_to_one_f(x):
    req = None
    for token in jieba.lcut(x):
        #print("req :", req)

        if len(set(token)) == 1:
            token = token[0]
        if req is None:
            req = token
        else:

            if token in req:
                continue
            else:
                while req.endswith(token[0]):
                    token = token[1:]
                req = req + token
    return req.strip()

def repeat_to_one_fb(x):
    return sorted(map(repeat_to_one_f, [x, "".join(jieba.lcut(x)[::-1])]),
                 key = len
                 )[0]

repeat_to_one = repeat_to_one_fb

def process_row(x, names):
    assert type(names) == type([])
    x = x.strip()
    if not x:
        return x
    first_char = x[0]
    if first_char in map(lambda y: y[0], names):
        return x
    if first_char in ["：", ":"]:
        return x[1:]
    if first_char in "".join(names):
        req = {}
        for name in names:
            merged = name
            find_it = False
            for ele in jieba.lcut(x):
                if merged.endswith(ele) and not find_it:
                    continue
                else:
                    find_it = True
                merged += ele
            if find_it:
                req[name] = merged
        #print(req)
        return sorted(req.items(), key = lambda t2: len(t2[1][len(t2[0]):]))[0][1]
    return x

def process_info(x, maintain_chars = ",.。，;:：；?？\n——"):
    req = re.findall(u"[0-9\u4e00-\u9fa5{}]+".format(maintain_chars) ,x)
    return "".join(req)

from huggingface_hub import snapshot_download

if not os.path.exists("genshin-impact-character"):
    path = snapshot_download(
        repo_id="svjack/genshin-impact-character",
        repo_type="dataset",
        local_dir="genshin-impact-character",
        local_dir_use_symlinks = False
    )

info_df = pd.read_csv("genshin-impact-character/genshin_impact_background_settings_constrained.csv")
info_df["info"] = info_df["info"].map(eval)

with open("genshin-impact-character/genshin_impact_character_setting.json", "r") as f:
    character_setting_total_dict = json.load(f)

req_dict = {}
for k, v_dict in character_setting_total_dict.items():
    req_dict[k] = {}
    for kk, vv in v_dict.items():
        if kk != "元素力":
            req_dict[k][kk] = vv
character_setting_total_dict = req_dict

def get_character_background_list(info_dict):
    text = []
    if "角色详细" in info_dict["描述"]:
        text.append(info_dict["描述"]["角色详细"])
    if "更多描述" in info_dict["描述"]:
        text.append(info_dict["描述"]["更多描述"])
    return list(map(lambda x: x.replace(" ", "").replace("\n\n", "\n"), text))
def get_character_background(info_dict):
    return "\n".join(get_character_background_list(info_dict))

pd.DataFrame(
pd.Series(character_setting_total_dict.values()).map(
    lambda x: {
        "性别": x['性别'],
        "国籍": x["国籍"]
    }
).values.tolist()).apply(lambda x: set(x), axis = 0).to_dict()


character_setting_total_dist_dict = {
 '姓名': "",
 '性别': {'少女女性', '少年男性', '成年女性', '成年男性'},
 '国籍': {'枫丹', '璃月', '稻妻', '至冬', '蒙德', '须弥'},
 '身份': "",
 '性格特征': "",
 '角色介绍': "",
 }

def get_character_setting_total_dict(name):
    from copy import deepcopy
    req = deepcopy(character_setting_total_dist_dict)
    if name in character_setting_total_dict:
        for k, v in character_setting_total_dict[name].items():
            req[k] = v
        info_dict = dict(info_df[["title", "info"]].values.tolist())[name]
        req["角色介绍"] = get_character_background(info_dict)
    req["姓名"] = name
    return req

prompt_format_dict = {
    "Basic_Info": ["性别", "国籍", "身份", "性格特征"],

    "两人同属{}": ["国籍"],
    "{}来自{},{}来自{}。": ["姓名", "国籍", "姓名", "国籍"],

    "下面是{}的一些基本信息\n{}": ["姓名", "Basic_Info"],
    "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"],

    "续写下面的角色介绍，下面是角色介绍的开头。{}是{}。{}": ["姓名", "身份", "Text"],
    "续写下面的角色故事，下面是角色故事的开头。{}是{}。{}": ["姓名", "身份", "Text"],
    "续写下面获得神之眼的过程，下面是开头。{}是{}。{}": ["姓名", "身份", "Text"],
    "{}给你写了一封信，信主题是{}，信的内容是这样的。": ["姓名", "Text"],

    "{}在进行有关{}的聊天时会说什么？": ["姓名", "Text"],
    "{}在{}的时候会说什么？": ["姓名", "Text"],
    "{}在{}时会说什么？": ["姓名", "Text"],
    "关于{}，{}会说什么?": ["Text", "姓名"],
    "当你想要了解{}时": ["姓名"],

    "关于{}，{}会说什么?": ["姓名", "姓名"],
    "从{}那里，可以获得哪些关于{}的信息？": ["姓名", "姓名"]
}

def single_character_prompt_func(name,
    used_prompt_format_dict,
    character_setting_rewrite_dict = {},
    Text = "",
    ):
    assert type(used_prompt_format_dict) == type({})
    assert type(character_setting_rewrite_dict) == type({})
    character_setting_total_dict = get_character_setting_total_dict(name)
    for k, v in character_setting_rewrite_dict.items():
        if k in character_setting_total_dict:
            character_setting_total_dict[k] = v
    key = list(used_prompt_format_dict.keys())[0]
    assert key in prompt_format_dict
    if key == "Basic_Info":
        return "\n".join(
        map(lambda k: "{}:{}".format(k, character_setting_total_dict[k]), prompt_format_dict[key])
        )
    elif key == "两人同属{}":
        return "两人同属{}".format(character_setting_total_dict["国籍"])
    elif key == "下面是{}的一些基本信息\n{}":
        return "下面是{}的一些基本信息\n{}".format(name,
            single_character_prompt_func(name,
                {
                    "Basic_Info": ["性别", "国籍", "身份", "性格特征"]
                },
                character_setting_rewrite_dict
            )
        )
    elif key == "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}":
        return "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}".format(
            name,
            single_character_prompt_func(name,
                {
                    "Basic_Info": ["性别", "国籍", "身份", "性格特征"]
                },
                character_setting_rewrite_dict
            ),
            character_setting_total_dict["角色介绍"]
        )
    elif key == "续写下面的角色介绍，下面是角色介绍的开头。{}是{}。{}":
        return "续写下面的角色介绍，下面是角色介绍的开头。{}是{}。{}".format(
            name,
            character_setting_total_dict["身份"],
            Text
        )
    elif key == "续写下面的角色故事，下面是角色故事的开头。{}是{}。{}":
        return "续写下面的角色故事，下面是角色介绍的开头。{}是{}。{}".format(
            name,
            character_setting_total_dict["身份"],
            Text
        )
    elif key == "续写下面获得神之眼的过程，下面是开头。{}是{}。{}":
        return "续写下面获得神之眼的过程，下面是开头。{}是{}。{}".format(
            name,
            character_setting_total_dict["身份"],
            Text
        )
    elif key == "{}给你写了一封信，信主题是{}，信的内容是这样的。":
        return "{}给你写了一封信，信主题是{}，信的内容是这样的。".format(
            name,
            Text
        )
    elif key == "{}在进行有关{}的聊天时会说什么？":
        return "{}在进行有关{}的聊天时会说什么？".format(
            name,
            Text
        )
    elif key == "{}在{}的时候会说什么？":
        return "{}在{}的时候会说什么？".format(
            name,
            Text
        )
    elif key == "{}在{}时会说什么？":
        return "{}在{}时会说什么？".format(
            name,
            Text
        )
    elif key == "关于{}，{}会说什么?":
        return "关于{}，{}会说什么?".format(
            Text,
            name,
        )
    elif key == "当你想要了解{}时":
        return "当你想要了解{}时".format(
            name,
        )
    return 1 / 0

def two_character_prompt_func(
    name_1,
    name_2,
    used_prompt_format_dict,
    character_setting_rewrite_dict_1 = {},
    character_setting_rewrite_dict_2 = {},
    ):
    assert type(character_setting_rewrite_dict_1) == type({})
    character_setting_total_dict_1 = get_character_setting_total_dict(name_1)
    for k, v in character_setting_rewrite_dict_1.items():
        if k in character_setting_total_dict_1:
            character_setting_total_dict_1[k] = v
    character_setting_total_dict_2 = get_character_setting_total_dict(name_2)
    for k, v in character_setting_rewrite_dict_2.items():
        if k in character_setting_total_dict_2:
            character_setting_total_dict_2[k] = v
    key = list(used_prompt_format_dict.keys())[0]
    assert key in prompt_format_dict
    if key == "关于{}，{}会说什么?":
        return "关于{}，{}会说什么?".format(name_1, name_2)
    elif key == "从{}那里，可以获得哪些关于{}的信息？":
        return "从{}那里，可以获得哪些关于{}的信息？".format(name_1, name_2)
    elif key == "{}来自{},{}来自{}。":
        return "{}来自{},{}来自{}。".format(name_1, character_setting_total_dict_1["国籍"],
        name_2, character_setting_total_dict_2["国籍"],
        )
    return 1 / 0

def main_single_character_prompt_func(name,
    used_prompt_format_dict,
    character_setting_rewrite_dict = {},
    Text = "",
    ):
    key = list(used_prompt_format_dict.keys())[0]
    assert key in prompt_format_dict
    if key == "续写下面的角色介绍，下面是角色介绍的开头。{}是{}。{}":
        task_prompt = single_character_prompt_func(
            name,
            used_prompt_format_dict,
            character_setting_rewrite_dict,
            Text
        )
        info_prompt = single_character_prompt_func(
            name,
            {
                "下面是{}的一些基本信息\n{}": ["姓名", "Basic_Info"]
            },
            character_setting_rewrite_dict,
            Text
        )
    elif key == "续写下面的角色故事，下面是角色故事的开头。{}是{}。{}":
        task_prompt = single_character_prompt_func(
            name,
            used_prompt_format_dict,
            character_setting_rewrite_dict,
            Text
        )
        info_prompt = single_character_prompt_func(
            name,
            {
            "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"]
            },
            character_setting_rewrite_dict,
            Text
            )

    elif key == "续写下面获得神之眼的过程，下面是开头。{}是{}。{}":
        task_prompt = single_character_prompt_func(
            name,
            used_prompt_format_dict,
            character_setting_rewrite_dict,
            Text
        )
        info_prompt = single_character_prompt_func(
            name,
            {
            "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"]
            },
            character_setting_rewrite_dict,
            Text
            )

    elif key == "{}给你写了一封信，信主题是{}，信的内容是这样的。":
        task_prompt = single_character_prompt_func(
            name,
            used_prompt_format_dict,
            character_setting_rewrite_dict,
            Text
        )
        info_prompt = single_character_prompt_func(
            name,
            {
            "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"]
            },
            character_setting_rewrite_dict,
            Text
            )
    elif key == "{}在进行有关{}的聊天时会说什么？":
        task_prompt = single_character_prompt_func(
            name,
            used_prompt_format_dict,
            character_setting_rewrite_dict,
            Text
        )
        info_prompt = single_character_prompt_func(
            name,
            {
            "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"]
            },
            character_setting_rewrite_dict,
            Text
            )
    elif key == "{}在{}的时候会说什么？":
        task_prompt = single_character_prompt_func(
            name,
            used_prompt_format_dict,
            character_setting_rewrite_dict,
            Text
        )
        info_prompt = single_character_prompt_func(
            name,
            {
            "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"]
            },
            character_setting_rewrite_dict,
            Text
            )
    elif key == "{}在{}时会说什么？":
        task_prompt = single_character_prompt_func(
            name,
            used_prompt_format_dict,
            character_setting_rewrite_dict,
            Text
        )
        info_prompt = single_character_prompt_func(
            name,
            {
            "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"]
            },
            character_setting_rewrite_dict,
            Text
            )
    elif key == "关于{}，{}会说什么?":
        task_prompt = single_character_prompt_func(
            name,
            used_prompt_format_dict,
            character_setting_rewrite_dict,
            Text
        )
        info_prompt = single_character_prompt_func(
            name,
            {
            "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"]
            },
            character_setting_rewrite_dict,
            Text
            )
    elif key == "当你想要了解{}时":
        task_prompt = single_character_prompt_func(
            name,
            used_prompt_format_dict,
            character_setting_rewrite_dict,
            Text
        )
        info_prompt = single_character_prompt_func(
            name,
            {
            "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"]
            },
            character_setting_rewrite_dict,
            Text
            )
    return task_prompt, info_prompt

def main_two_character_prompt_func(
    name_1,
    name_2,
    used_prompt_format_dict,
    character_setting_rewrite_dict_1 = {},
    character_setting_rewrite_dict_2 = {},
    ):
    task_prompt = two_character_prompt_func(
        name_1,
        name_2,
        used_prompt_format_dict,
        character_setting_rewrite_dict_1,
        character_setting_rewrite_dict_2)
    info_prompt_1 = single_character_prompt_func(
        name_1,
        {
            "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"]
        },
        character_setting_rewrite_dict_1,
        )
    info_prompt_2 = single_character_prompt_func(
        name_2,
        {
            "下面是{}的一些基本信息\n{}\n这些是一段角色介绍\n{}": ["姓名", "Basic_Info", "角色介绍"]
        },
        character_setting_rewrite_dict_2,
        )
    character_setting_total_dict_1 = get_character_setting_total_dict(name_1)
    for k, v in character_setting_rewrite_dict_1.items():
        if k in character_setting_total_dict_1:
            character_setting_total_dict_1[k] = v
    character_setting_total_dict_2 = get_character_setting_total_dict(name_2)
    for k, v in character_setting_rewrite_dict_2.items():
        if k in character_setting_total_dict_2:
            character_setting_total_dict_2[k] = v

    country_prompt = ""
    same_country = character_setting_total_dict_1["国籍"] == character_setting_total_dict_2["国籍"]
    if same_country:
        country_prompt = single_character_prompt_func(
            name_1,
            {
                "两人同属{}": ["国籍"]
            },
            character_setting_rewrite_dict_1,
            )
    else:
        country_prompt = two_character_prompt_func(
                name_1,
                name_2,
                {
                "{}来自{},{}来自{}。": ["姓名", "国籍", "姓名", "国籍"]
                },
                character_setting_rewrite_dict_1,
                character_setting_rewrite_dict_2,
            )
    info_prompt = "\n".join(
        [info_prompt_1, info_prompt_2, country_prompt]
    )
    return task_prompt, info_prompt

def main_single_character_prompt_func_cls(
    name,
    task,
    character_setting_rewrite_dict = {},
    Text = "",
):
    assert task in ["介绍", "故事", "信", "聊天", "时候", "关于", "了解"]
    if task == "介绍":
        return main_single_character_prompt_func(
            name,
            {
            "续写下面的角色介绍，下面是角色介绍的开头。{}是{}。{}": ["姓名", "身份", "Text"],
            },
            character_setting_rewrite_dict = character_setting_rewrite_dict,
            Text = Text,
        )
    elif task == "故事":
        return main_single_character_prompt_func(
            name,
            {
            "续写下面的角色故事，下面是角色故事的开头。{}是{}。{}": ["姓名", "身份", "Text"],
            },
            character_setting_rewrite_dict = character_setting_rewrite_dict,
            Text = Text,
        )
    elif task == "神之眼":
        return main_single_character_prompt_func(
            name,
            {
            "续写下面获得神之眼的过程，下面是开头。{}是{}。{}": ["姓名", "身份", "Text"],
            },
            character_setting_rewrite_dict = character_setting_rewrite_dict,
            Text = Text,
        )
    elif task == "信":
        return main_single_character_prompt_func(
            name,
            {
            "{}给你写了一封信，信主题是{}，信的内容是这样的。": ["姓名", "Text"],
            },
            character_setting_rewrite_dict = character_setting_rewrite_dict,
            Text = Text,
        )
    elif task == "聊天":
        return main_single_character_prompt_func(
            name,
            {
            "{}在进行有关{}的聊天时会说什么？": ["姓名", "Text"],
            },
            character_setting_rewrite_dict = character_setting_rewrite_dict,
            Text = Text,
        )
    elif task == "时候":
        return main_single_character_prompt_func(
            name,
            {
            "{}在{}的时候会说什么？": ["姓名", "Text"],
            },
            character_setting_rewrite_dict = character_setting_rewrite_dict,
            Text = Text,
        )
    elif task == "关于":
        return main_single_character_prompt_func(
            name,
            {
            "关于{}，{}会说什么?": ["Text", "姓名"],
            },
            character_setting_rewrite_dict = character_setting_rewrite_dict,
            Text = Text,
        )
    elif task == "了解":
        return main_single_character_prompt_func(
            name,
            {
            "当你想要了解{}时": ["姓名"],
            },
            character_setting_rewrite_dict = character_setting_rewrite_dict,
            Text = Text,
        )
    return 1 / 0

def main_two_character_prompt_func_cls(
    name_1,
    name_2,
    task,
    character_setting_rewrite_dict_1 = {},
    character_setting_rewrite_dict_2 = {},
    ):
    assert task in ["会说什么", "哪些信息"]
    if task == "会说什么":
        return main_two_character_prompt_func(
            name_1,
            name_2,
            {
            "关于{}，{}会说什么?": ["姓名", "姓名"],
            },
            character_setting_rewrite_dict_1,
            character_setting_rewrite_dict_2
        )
    elif task == "哪些信息":
        return main_two_character_prompt_func(
            name_1,
            name_2,
            {
            "从{}那里，可以获得哪些关于{}的信息？": ["姓名", "姓名"]
            },
            character_setting_rewrite_dict_1,
            character_setting_rewrite_dict_2
        )
    return 1 / 0

character_setting_total_dist_dict = {
 '姓名': "",
 '性别': {'少女女性', '少年男性', '成年女性', '成年男性'},
 '国籍': {'枫丹', '璃月', '稻妻', '至冬', '蒙德', '须弥'},
 '身份': "",
 '性格特征': "",
 '角色介绍': "",
 }

all_single_task = ["介绍", "故事", "信", "聊天", "时候", "关于", "了解"]
all_two_task = ["会说什么", "哪些信息"]

all_genders = ['少女女性', '少年男性', '成年女性', '成年男性']
all_countries = ['蒙德','璃月', '稻妻', '须弥','枫丹', '至冬']

def get_single_name(images, evt: gr.SelectData, repo_card_im_dict = character_img_dict):
    img_selected = images[evt.index]
    #print(img_selected)
    im_data = img_selected["name"]
    im = Image.open(im_data)
    im_hash = imagehash.average_hash(
        im, hash_size = 1024
    )
    min_diff = int(1e10)
    min_repo_name = ""
    for repo_name, repo_card_image in repo_card_im_dict.items():
        repo_img = repo_card_image
        repo_img_hash = imagehash.average_hash(
            repo_img, hash_size = 1024
        )
        diff = im_hash - repo_img_hash
        if diff < min_diff:
            min_diff = diff
            min_repo_name = repo_name
    print(im_data ,min_repo_name, min_diff)
    assert len(min_repo_name) > 0
    single_name = min_repo_name
    return single_name

#def change_single_name(single_name):
def change_single_name(images, evt: gr.SelectData,):
    single_name = get_single_name(images, evt)

    if hasattr(single_name, "value"):
        single_name_ = single_name.value
    else:
        single_name_ = single_name
    character_setting_total_dict = get_character_setting_total_dict(single_name)
    character_setting_total_dict = dict(map(lambda t2: (t2[0] ,t2[1] if type(t2[1]) == type("") else ""),
        character_setting_total_dict.items()))
    return character_setting_total_dict["姓名"], \
    gr.Dropdown.update(value = character_setting_total_dict["性别"], choices = all_genders), \
    gr.Dropdown.update(value = character_setting_total_dict["国籍"], choices = all_countries), \
        character_setting_total_dict["身份"], \
        character_setting_total_dict["性格特征"], character_setting_total_dict["角色介绍"]

def get_single_prompt(
    single_name, select_gender, select_country, single_identity, single_disposition,
    select_task, Text, single_introduction
):
    if hasattr(single_name, "value"):
        single_name_ = single_name.value
    else:
        single_name_ = single_name
    if hasattr(select_gender, "value"):
        select_gender_ = select_gender.value
    else:
        select_gender_ = select_gender
    if hasattr(select_country, "value"):
        select_country_ = select_country.value
    else:
        select_country_ = select_country
    if hasattr(single_identity, "value"):
        single_identity_ = single_identity.value
    else:
        single_identity_ = single_identity
    if hasattr(single_disposition, "value"):
        single_disposition_ = single_disposition.value
    else:
        single_disposition_ = single_disposition
    if hasattr(select_task, "value"):
        select_task_ = select_task.value
    else:
        select_task_ = select_task
    if hasattr(Text, "value"):
        Text_ = Text.value
    else:
        Text_ = Text
    if hasattr(single_introduction, "value"):
        single_introduction_ = single_introduction.value
    else:
        single_introduction_ = single_introduction
    character_setting_rewrite_dict = {
     '姓名': single_name_,
     '性别': select_gender_,
     '国籍': select_country_,
     '身份': single_identity_,
     '性格特征': single_disposition_,
     '角色介绍': single_introduction_,
     }
    a, b = main_single_character_prompt_func_cls(
        single_name_,
        select_task_,
        character_setting_rewrite_dict = character_setting_rewrite_dict,
        Text = Text,
        )
    #a = a.replace("?", "").replace("？", "")
    a = a.replace("？", "?")
    req = "\n".join([b, a])
    req = process_info(req)
    return req
    #return "\n".join([b, a])

def get_two_prompt(
    single_name_1, select_gender_1, select_country_1, single_identity_1, single_disposition_1,
    single_introduction_1,
    single_name_2, select_gender_2, select_country_2, single_identity_2, single_disposition_2,
    single_introduction_2, two_task,
):
    assert two_task in ["会说什么", "哪些信息"]
    if hasattr(single_name_1, "value"):
        single_name_1_ = single_name_1.value
    else:
        single_name_1_ = single_name_1
    if hasattr(select_gender_1, "value"):
        select_gender_1_ = select_gender_1.value
    else:
        select_gender_1_ = select_gender_1
    if hasattr(select_country_1, "value"):
        select_country_1_ = select_country_1.value
    else:
        select_country_1_ = select_country_1
    if hasattr(single_identity_1, "value"):
        single_identity_1_ = single_identity_1.value
    else:
        single_identity_1_ = single_identity_1
    if hasattr(single_disposition_1, "value"):
        single_disposition_1_ = single_disposition_1.value
    else:
        single_disposition_1_ = single_disposition_1
    if hasattr(single_introduction_1, "value"):
        single_introduction_1_ = single_introduction_1.value
    else:
        single_introduction_1_ = single_introduction_1

    if hasattr(single_name_2, "value"):
        single_name_2_ = single_name_2.value
    else:
        single_name_2_ = single_name_2
    if hasattr(select_gender_2, "value"):
        select_gender_2_ = select_gender_2.value
    else:
        select_gender_2_ = select_gender_2
    if hasattr(select_country_2, "value"):
        select_country_2_ = select_country_2.value
    else:
        select_country_2_ = select_country_2
    if hasattr(single_identity_2, "value"):
        single_identity_2_ = single_identity_2.value
    else:
        single_identity_2_ = single_identity_2
    if hasattr(single_disposition_2, "value"):
        single_disposition_2_ = single_disposition_2.value
    else:
        single_disposition_2_ = single_disposition_2
    if hasattr(single_introduction_2, "value"):
        single_introduction_2_ = single_introduction_2.value
    else:
        single_introduction_2_ = single_introduction_2
    character_setting_rewrite_dict_1 = {
     '姓名': single_name_1_,
     '性别': select_gender_1_,
     '国籍': select_country_1_,
     '身份': single_identity_1_,
     '性格特征': single_disposition_1_,
     '角色介绍': single_introduction_1_,
     }
    character_setting_rewrite_dict_2 = {
     '姓名': single_name_2_,
     '性别': select_gender_2_,
     '国籍': select_country_2_,
     '身份': single_identity_2_,
     '性格特征': single_disposition_2_,
     '角色介绍': single_introduction_2_,
     }

    a, b = main_two_character_prompt_func_cls(
        single_name_1_,
        single_name_2_,
        two_task,
        character_setting_rewrite_dict_1 = character_setting_rewrite_dict_1,
        character_setting_rewrite_dict_2 = character_setting_rewrite_dict_2,
        )
    #a = a.replace("?", "").replace("？", "")
    a = a.replace("？", "?")
    req = "\n".join([b, a])
    req = process_info(req)
    return req
    #return "\n".join([b, a])

from pathlib import Path
import pandas as pd

import re
def retrieve_sent_split(sent,
                       stops_split_pattern = "|".join(map(lambda x: r"\{}".format(x),
                                                                 ",." + "，。" + ":" + "n"))
                       ):
    if not sent.strip():
        return []

    split_list = re.split(stops_split_pattern, sent)
    split_list = list(filter(lambda x: x.strip() ,split_list))
    return split_list

def stop_criteria(sent, min_sub_len = 4):
    #### chunk rec stop
    split_list = retrieve_sent_split(sent)
    split_list = list(filter(lambda x: len(x) >= min_sub_len,split_list))
    if split_list:
        if pd.Series(split_list).value_counts().max() >= 2:
            print("stop in : {}".format(sent))
            return "stop"
    #### row rec stop
    if list(filter(lambda x: x ,map(lambda x: x.strip(),sent.split("\n")))) and pd.Series(list(filter(lambda x: x ,map(lambda x: x.strip(),sent.split("\n"))))).value_counts().max() >= 2:
        return "stop"
    return "continue"

from transformers import TextStreamer, AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen1.5-7B-Chat",)
qw_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen1.5-7B-Chat", load_in_4bit = True)
qw_model = PeftModel.from_pretrained(qw_model, "svjack/DPO_Genshin_Impact_Inst_ORPO_Qwen1_5_7B_Chat_lora_small")
qw_model = qw_model.eval()

streamer = TextStreamer(tokenizer)

def qwen_hf_predict(messages, qw_model = qw_model,
    tokenizer = tokenizer, streamer = streamer,
    do_sample = True,
    top_p = 0.95,
    top_k = 40,
    max_new_tokens = 512,
    max_input_length = 3500,
    temperature = 0.9,
    repetition_penalty = 1.0,
    device = "cuda"):

    encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt",
        add_generation_prompt=True
    )
    model_inputs = encodeds.to(device)

    generated_ids = qw_model.generate(model_inputs, max_new_tokens=max_new_tokens,
                                do_sample=do_sample,
                                  streamer = streamer,
                                  top_p = top_p,
                                  top_k = top_k,
                                  temperature = temperature,
                                  repetition_penalty = repetition_penalty,
                                  )
    out = tokenizer.batch_decode(generated_ids)[0].split("<|im_start|>assistant")[-1].replace("<|im_end|>", "").strip()
    return out

def repeat_cmp_process(x, ratio_threshold = 0.3):
    l = x.split("\n")
    l = list(filter(lambda y: y.strip(), l))
    req = []
    for ele in l:
        one_ele = repeat_to_one(ele)
        if ele.strip() and (len(one_ele) / len(ele)) <= ratio_threshold:
            req.append(one_ele)
        else:
            req.append(ele)
    return "\n".join(req)

def text_process_before_yield(x, add_repeat_process = True):
    import re
    x = x.strip()
    if len(x.split("\n")) <= 1:
        #return repeat_to_one_fb(x)
        if add_repeat_process:
            return repeat_cmp_process(x)
        return x
    zh_list = re.findall(u"[\u4e00-\u9fa5]+" ,x)
    if zh_list:
        last_zh = zh_list[-1]
        l = list(map(lambda y: y.strip() ,x.split("\n")))
        l_rev = l[::-1]
        l_rev_collect = []
        find_it = False
        for ele in l_rev:
            if not ele.endswith(last_zh):
                find_it = True
            else:
                pass
            if find_it:
                l_rev_collect.append(ele)
        l_collect = l_rev_collect[::-1]
        #print(l_collect)
        req = "\n".join(l_collect)
        '''
        zh_list = re.findall(u"[\u4e00-\u9fa5]+" ,x)
        if zh_list:
            req = req[req.find(zh_list[0]):]
        '''
        #return repeat_to_one_fb(req)
        if add_repeat_process:
            return repeat_cmp_process(req)
        return req
    return ""

def chat_messages(message, history = [],
    max_length = 128, show_process = True,
    temperature = 0.5, top_p = 0.95, top_k = 40, do_sample = True,
):
    assert type(message) == type("")
    messages = [
        {
            "role": "user",
            "content": message
        }
    ]
    out = qwen_hf_predict(messages,
        do_sample = do_sample,
        top_p = top_p,
        top_k = top_k,
        max_new_tokens = max_length,
        max_input_length = 3500,
        temperature = temperature,
        repetition_penalty = 1.1,
        device = "cuda")
    for i in range(len(out)):
        response = out[:i]
        yield text_process_before_yield(response)

def process_text(x):
    rp_list = ["[/INST]","/INST]","[/INST","/INST","[/INST>","INST","[/CHARACTER]"]
    for ele in rp_list:
        x = x.replace(ele, " ")
    return x

def run_single(
    single_name, select_gender, select_country, single_identity, single_disposition,
    select_task, Text, single_introduction,
    gen_times, max_length, top_p, temperature):
    prompt = get_single_prompt(
        single_name, select_gender, select_country, single_identity, single_disposition,
        select_task, Text, single_introduction
    )
    req = []
    for i in range(gen_times):
        for ele in chat_messages(prompt,
            max_length = max_length,
            top_p = top_p,
            temperature = temperature
        ):
            pass
        #yield ele
        if len(ele.strip()) >= 3:
            req.append(ele)
    #print(req)
    #req = sorted(set(filter(lambda x: x.strip(), req)), key = lambda y: -1 * len(y))
    if hasattr(Text, "value"):
        Text_ = Text.value
    else:
        Text_ = Text
    if Text_.strip():
        req = sorted(set(filter(lambda x: x.strip(), req)), key = lambda y: -1 * fuzz.ratio(y, Text_))
    else:
        req = sorted(set(filter(lambda x: x.strip(), req)), key = lambda y: -1 * len(y))

    req = "\n\n".join(map(lambda t2: "结果{}:\n{}".format(t2[0], t2[1]), enumerate(req)))
    req = process_text(req)
    req = process_info(req)
    return req

def run_two(
    single_name_1, select_gender_1, select_country_1, single_identity_1, single_disposition_1,
    single_introduction_1,
    single_name_2, select_gender_2, select_country_2, single_identity_2, single_disposition_2,
    single_introduction_2,
    gen_times, max_length, top_p, temperature):
    if hasattr(single_name_1, "value"):
        single_name_1_ = single_name_1.value
    else:
        single_name_1_ = single_name_1
    if hasattr(single_name_2, "value"):
        single_name_2_ = single_name_2.value
    else:
        single_name_2_ = single_name_2
    two_prompt = partial(get_two_prompt, two_task = "哪些信息")(
        single_name_1, select_gender_1, select_country_1, single_identity_1, single_disposition_1,
        single_introduction_1,
        single_name_2, select_gender_2, select_country_2, single_identity_2, single_disposition_2,
        single_introduction_2
    )
    req = []
    for i in range(gen_times):
        for ele in chat_messages(two_prompt,
            max_length = max_length,
            top_p = top_p,
            temperature = temperature
        ):
            pass
        #yield ele
        ele = process_row(ele, [single_name_1_, single_name_2_]).strip()
        req.append(ele)
    #print(req)
    req = sorted(set(filter(lambda x: x.strip(), req)), key = lambda y: -1 * len(y))
    req = "\n\n".join(map(lambda t2: "结果{}:\n{}".format(t2[0], t2[1].strip()), enumerate(req)))
    req = process_text(req)
    req = process_info(req)
    l = req.split("\n\n")
    def process_head(y):
        ll = y.split("\n")
        if len(ll) >= 2:
            if len(ll[1].strip()) == 1:
                return "\n".join([ll[0]] + ll[2:]).strip()
            else:
                return y.strip()
        else:
            return y.strip()
    req = "\n\n".join(map(process_head, l))
    return req

all_single_task = ["介绍", "故事", "信", "聊天", "时候", "关于", "了解"]
all_two_task = ["会说什么", "哪些信息"]

with gr.Blocks() as demo:
    title = gr.HTML(
            """<h1 align="center"> <font size="+3"> Genshin Impact Character Qwen1.5 7B ORPO Instruction 📚 </font> </h1>""",
            elem_id="title",
    )

    with gr.Tab("单个角色任务指令"):
        with gr.Row():
            with gr.Column(0.5):
                select_name = gr.Gallery(im_list, elem_id="gallery",
                        #scale = 0.1,
                        columns=[5], object_fit="contain",
                        height=512+128,
                        allow_preview = False,
                        label="选择角色",
                        info = "可选择。原神沉玉谷前的内建角色"
                        )
                select_task = gr.Dropdown(label="选择任务",
                        choices=all_single_task,
                        info = "可选择",
                        value=all_single_task[0], interactive = True)
                Text = gr.Text(label = "任务追加信息", interactive = True, lines = 4,
                    info = "可编辑。这些信息除了‘了解’任务外不应该为空。对于不同任务填入的值不同。"
                    "（介绍->前缀 故事->前缀 信->主题 聊天->主题 时候->事件 关于->看法 了解->了解角色自身）"
                )

            with gr.Column(0.5):
                single_name = gr.Text(label = "角色姓名",
                                            info = "可编辑。角色姓名会重写选择角色，用这个选项可以新建角色",
                                            interactive = True)
                #with gr.Row():
                select_gender = gr.Dropdown(label="性别",
                                            choices=all_genders,
                                            info = "可选择",
                                            value=all_genders[0], interactive = True)
                select_country = gr.Dropdown(label="国籍",
                                            choices=all_countries,
                                            info = "可选择",
                                            value=all_countries[0], interactive = True)
                                    #with gr.Column():
                single_identity = gr.Text(label = "身份", info = "可编辑", interactive = True)
                single_disposition = gr.Text(label = "性格特征", info = "可编辑", interactive = True)

                single_introduction = gr.Text(label = "角色介绍", info = "可编辑",
                interactive = True, lines = 15)

        with gr.Row():
            single_prompt_run_button = gr.Button("得到任务结果")
            output = gr.Text(label = "任务生成结果", info = "可编辑", lines = 2, scale = 5.0)

    with gr.Tab("两个角色看法指令"):
        with gr.Row():
            with gr.Column(0.5):
                with gr.Column():
                    select_name_1 = gr.Gallery(im_list, elem_id="gallery",
                                            #scale = 0.1,
                                            columns=[5], object_fit="contain",
                                            #height=2048 + 1024,
                                            height=512+128,
                                            allow_preview = False,
                                            label="选择角色",
                                            info = "可选择。原神沉玉谷前的内建角色"
                                            )
                    single_name_1 = gr.Text(label = "角色姓名",
                            info = "可编辑。角色姓名会重写选择角色，用这个选项可以新建角色",
                            interactive = True)
                with gr.Row():
                    select_gender_1 = gr.Dropdown(label="性别",
                            choices=all_genders,
                            info = "可选择",
                            value=all_genders[0], interactive = True)
                    select_country_1 = gr.Dropdown(label="国籍",
                            choices=all_countries,
                            info = "可选择",
                            value=all_countries[0], interactive = True)
                    #with gr.Column():
                single_identity_1 = gr.Text(label = "身份", info = "可编辑", interactive = True)
                single_disposition_1 = gr.Text(label = "性格特征", info = "可编辑", interactive = True)
                single_introduction_1 = gr.Text(label = "角色介绍", info = "可编辑",
                interactive = True, lines = 36)

            with gr.Column(0.5):
                with gr.Column():
                    select_name_2 = gr.Gallery(im_list, elem_id="gallery",
                                                                #scale = 0.1,
                                                                columns=[5], object_fit="contain",
                                                                #height=2048 + 1024,
                                                                height=512+128,
                                                                allow_preview = False,
                                                                label="选择角色",
                                                                info = "可选择。原神沉玉谷前的内建角色"
                                                                )
                    single_name_2 = gr.Text(label = "角色姓名",
                            info = "可编辑。角色姓名会重写选择角色，用这个选项可以新建角色",
                            interactive = True)
                with gr.Row():
                    select_gender_2 = gr.Dropdown(label="性别",
                            choices=all_genders,
                            info = "可选择",
                            value=all_genders[0], interactive = True)
                    select_country_2 = gr.Dropdown(label="国籍",
                            choices=all_countries,
                            info = "可选择",
                            value=all_countries[0], interactive = True)
                    #with gr.Column():
                single_identity_2 = gr.Text(label = "身份", info = "可编辑", interactive = True)
                single_disposition_2 = gr.Text(label = "性格特征", info = "可编辑", interactive = True)
                single_introduction_2 = gr.Text(label = "角色介绍", info = "可编辑",
                interactive = True, lines = 36)

        with gr.Row():
            two_prompt_run_button = gr.Button("得到角色间看法")
            two_output = gr.Text(label = "角色间看法结果", info = "可编辑", lines = 2, scale = 5.0)

    with gr.Row():
        gen_times = gr.Slider(1, 10, value=5, step=1.0, label="Generate Num", interactive=True)
        max_length = gr.Slider(0, 32768, value=512, step=1.0, label="Maximum length", interactive=True)
        top_p = gr.Slider(0, 1, value=0.8, step=0.01, label="Top P", interactive=True)
        temperature = gr.Slider(0.01, 1, value=0.6, step=0.01, label="Temperature", interactive=True)

    with gr.Row():
        gr.HTML(
            """<h2 align="center"> <font size="+0"> 例子（这里面涉及推荐选择的需要从左面或上面的角色图片集里面点按选取） </font> </h2>""",
            elem_id="title",
    )

    with gr.Row():
        gr.Examples(
            [
            ["这里推荐从左面选择：行秋",  "介绍"],
            ],
            inputs = [single_name, select_task],
            label = "单个角色任务指令例子"
        )

    with gr.Row():
        gr.Examples(
            [
            ["这里推荐从左面选择：柯莱" ,"信", "鸟语花香"],
            ["这里推荐从左面选择：魈" ,"聊天", "美味的杏仁豆腐"],
            ["这里推荐从左面选择：凝光" ,"时候", "品尝璃月香茗"],
            ["这里推荐从左面选择：可莉" ,"关于", "如何制造蹦蹦炸弹"],
            ["这里推荐从左面选择：北斗" ,"故事", "一天行秋在绝云间练剑。"],
            ["这里推荐从左面选择：北斗" ,"了解", ""],
            ],
            inputs = [single_name ,select_task, Text],
            label = "单个角色任务指令例子"
        )


    with gr.Row():
        gr.Examples(
            [
            ["大慈树王",  "故事", "大慈树王到须弥沙漠上播种，并跟沙漠的统治者赤王交朋友。",
            "成年女性", "须弥", "须弥的统治者",
            "爱民如子，带领雨林的人民战胜灾厄",
            '''
            草神之所以也被称之为“智慧之神”，正是因为她的意识连接着世界之树。在须弥人眼里，她是智慧的化身、仁慈与无所不能的象征，但她却在几百年前的灾难中消失了。
在漫长的历史当中，须弥历经浩劫，种种险情都被大慈树王一一化解。大慈树王创造出雨林，使得须弥人能获得安宁的生活。而须弥最初的教令院，便是由长久地去追随大慈树王的学者组成，他们各司其职，协助大慈树王管理须弥。最能理解大慈树王的力量和哲思的，只能是教令院了。
            '''
            ],
            ["大慈树王",  "关于", "教令院",
            "成年女性", "须弥", "须弥的统治者",
            "爱民如子，带领雨林的人民战胜灾厄",
            '''
            草神之所以也被称之为“智慧之神”，正是因为她的意识连接着世界之树。在须弥人眼里，她是智慧的化身、仁慈与无所不能的象征，但她却在几百年前的灾难中消失了。
在漫长的历史当中，须弥历经浩劫，种种险情都被大慈树王一一化解。大慈树王创造出雨林，使得须弥人能获得安宁的生活。而须弥最初的教令院，便是由长久地去追随大慈树王的学者组成，他们各司其职，协助大慈树王管理须弥。最能理解大慈树王的力量和哲思的，只能是教令院了。
            '''
            ],
            ],
            inputs = [single_name, select_task, Text, select_gender, select_country, single_identity,
            single_disposition, single_introduction
            ],
            label = "单个角色任务指令例子"
        )

    with gr.Row():
        gr.Examples(
            [
                ["这里推荐从上面选择：芙宁娜", "这里推荐从上面选择：那维莱特"]
            ],
            inputs = [single_name_1, single_name_2],
            label = "两个角色看法指令例子"
        )

    with gr.Row():
        gr.Examples(
            [
            ["这里推荐从上面选择：提纳里" ,"大慈树王",
            "成年女性", "须弥", "须弥的统治者",
            "爱民如子，带领雨林的人民战胜灾厄",
                        '''
                        草神之所以也被称之为“智慧之神”，正是因为她的意识连接着世界之树。在须弥人眼里，她是智慧的化身、仁慈与无所不能的象征，但她却在几百年前的灾难中消失了。
            在漫长的历史当中，须弥历经浩劫，种种险情都被大慈树王一一化解。大慈树王创造出雨林，使得须弥人能获得安宁的生活。而须弥最初的教令院，便是由长久地去追随大慈树王的学者组成，他们各司其职，协助大慈树王管理须弥。最能理解大慈树王的力量和哲思的，只能是教令院了。
                        '''
            ],
            ],
            inputs = [single_name_1 ,single_name_2,
            select_gender_2, select_country_2, single_identity_2,
            single_disposition_2, single_introduction_2
            ],
            label = "两个角色看法指令例子"
        )

    select_name.select(get_single_name,
            inputs = select_name,
            outputs = single_name
            )

    select_name_1.select(
        get_single_name, select_name_1, single_name_1
    )

    select_name_2.select(
        get_single_name, select_name_2, single_name_2
    )

    select_name.select(change_single_name,
        inputs = select_name,
        outputs = [
                    single_name, select_gender, select_country,
                    single_identity, single_disposition, single_introduction
                ],
        )

    select_name_1.select(
        change_single_name, select_name_1,
            [single_name_1, select_gender_1, select_country_1,
            single_identity_1, single_disposition_1, single_introduction_1
            ]
    )

    select_name_2.select(
        change_single_name, select_name_2,
            [single_name_2, select_gender_2, select_country_2,
            single_identity_2, single_disposition_2, single_introduction_2
            ]
    )

    single_prompt_run_button.click(run_single, [
        single_name, select_gender, select_country, single_identity, single_disposition,
        select_task, Text, single_introduction,
    gen_times, max_length, top_p, temperature
    ], output)
    two_prompt_run_button.click(run_two, [
    single_name_1, select_gender_1, select_country_1, single_identity_1, single_disposition_1,
    single_introduction_1,
    single_name_2, select_gender_2, select_country_2, single_identity_2, single_disposition_2,
    single_introduction_2,
    gen_times, max_length, top_p, temperature], two_output)

#demo.launch("0.0.0.0", show_api=False, share = True)
demo.queue(max_size=4, concurrency_count=1).launch(debug=True, show_api=False, share = True)