app.py

import re
import unicodedata

import requests
import streamlit as st
from bs4 import BeautifulSoup
from transformers import (
    AutoModelForQuestionAnswering,
    AutoTokenizer,
    QuestionAnsweringPipeline,
)

model_name = "KoichiYasuoka/bert-base-japanese-wikipedia-ud-head"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForQuestionAnswering.from_pretrained(model_name)
qa_pipeline = QuestionAnsweringPipeline(model=model, tokenizer=tokenizer)


st.title("株価お知らせBot")
stock_code = st.text_input(
    "株価を知りたい企業の証券コードを入力してください",
    placeholder="証券コード",
    max_chars=4,
    help="4桁の数字",
)

if "content" not in st.session_state:
    st.write("株価を知りたい企業の証券コードを入力してください")

if st.button("株価を知りたい"):
    url = f"https://www.nikkei.com/nkd/company/?scode={stock_code}"
    res = requests.get(url)
    soup = BeautifulSoup(res.text, "html.parser")

    print(soup)

    _text = soup.find("div", attrs={"class": "m-stockInfo_top_left"})

    print(_text)

    _text = _text.text

    print(_text)

    content = unicodedata.normalize("NFKD", _text)
    st.session_state.content = re.sub("[\r\t\n]+", " ", content)


# Transformersで回答を作成
def generate_response(prompt, max_length=50):
    # input_ids = tokenizer.encode(prompt, return_tensors="pt")
    # Generate response
    answer = qa_pipeline(context=st.session_state.content[:100], question=prompt)

    return answer["answer"]


# メッセージがない時
if "messages" not in st.session_state.keys():
    st.session_state.messages = [{"role": "assistant", "content": "何か御用ですか？"}]

# チャット内容の表示
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.write(message["content"])

# ユーザーの質問
if prompt := st.chat_input():
    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.write(prompt)

# AIによる回答
if st.session_state.messages[-1]["role"] != "assistant":
    with st.chat_message("assistant"):
        with st.spinner("考え中..."):
            response = generate_response(prompt)
            st.write(response)
    message = {"role": "assistant", "content": response}
    st.session_state.messages.append(message)