import os

'''
os.system("pip uninstall httpx -y")
os.system("pip uninstall pydantic -y")
os.system("pip uninstall gradio -y")
os.system("pip install -U gradio")
'''

os.system("pip install transformers==4.30.2")

'''
import subprocess 

out = subprocess.check_output("pip --help")
print(out.decode())

out = subprocess.check_output("pip --version")
print(out.decode())
'''

os.system("pip install huggingface_hub")

from huggingface_hub import space_info

import sys
import re

from flair.models import SequenceTagger
from flair.data import Sentence

flair_ner_model_path = "flair_model"
assert os.path.exists(flair_ner_model_path)
loaded_model: SequenceTagger = SequenceTagger.load(os.path.join(flair_ner_model_path ,"best-model.pt"))

def one_item_process(r, loaded_model):
    #assert type(r) == type(pd.Series())
    zh = r["question"]
    zh = zh.replace(" ", "").strip()
    sentence = Sentence(" ".join(list(zh)))
    loaded_model.predict(sentence)
    sentence_str = str(sentence)
    ask_spans = re.findall(r'\["(.+?)"/ASK\]', sentence_str)
    sentence = re.findall(r'Sentence: "(.+?)"', sentence_str)
    if ask_spans:
        ask_spans = ask_spans[0]
    else:
        ask_spans = ""
    if sentence:
        sentence = sentence[0]
    else:
        sentence = ""
    ask_spans, sentence = map(lambda x: x.replace(" ", "").strip(), [ask_spans, sentence])
    return ask_spans, sentence

import gradio as gr

example_sample = [
    "宁波在哪个省份？",
    "美国的通货是什么？",
]

def demo_func(question):
    assert type(question) == type("")
    ask_spans, sentence = one_item_process(
        {"question": question},
        loaded_model
    )
    return {
        "Question words": ask_spans
    }

markdown_exp_size = "##"
lora_repo = "svjack/chatglm3-few-shot"
lora_repo_link = "svjack/chatglm3-few-shot/?input_list_index=2"
emoji_info = space_info(lora_repo).__dict__["cardData"]["emoji"]
space_cnt = 1
task_name = "[---Chinese Question Words extractor---]"
description = f"{markdown_exp_size} {task_name} few shot prompt in ChatGLM3 Few Shot space repo (click submit to activate) : [{lora_repo_link}](https://huggingface.co/spaces/{lora_repo_link}) {emoji_info}"

demo = gr.Interface(
        fn=demo_func,
        inputs="text",
        outputs="json",
        title=f"Chinese Question Words extractor 🐱 demonstration",
        #description = description,
        examples=example_sample if example_sample else None,
        cache_examples = False
    )

with demo:
    gr.HTML(
    '''
                <div style="justify-content: center; display: flex;">
                <iframe
                src="https://svjack-chatglm3-few-shot-demo.hf.space/?input_list_index=2"
                frameborder="0"
                width="1400"
                height="768"
                ></iframe>
                </div>
    '''
    )

demo.launch(server_name=None, server_port=None)