コードを追加

app.py

@@ -0,0 +1,43 @@
+import re
+import unicodedata
+
+import streamlit as st
+
+from generator import generate_response
+from scraper import get_stock_info
+
+st.title("株価お知らせBot")
+
+stock_code = st.text_input("株コード", placeholder="株コード", max_chars=4, help='4桁の数字')
+
+if "content" not in st.session_state:
+    st.write("はじめに、株コードを指定してください。")
+
+if st.button("株決定"):
+    content = get_stock_info(stock_code)
+    content = unicodedata.normalize('NFKD', content)
+    st.session_state.content = re.sub('[\r\t\n]+', ' ', content)
+
+# 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(st, prompt)
+            st.write(response)
+    message = {"role": "assistant", "content": response}
+    st.session_state.messages.append(message)

generator.py

@@ -0,0 +1,16 @@
+from transformers import AutoTokenizer
+from transformers import AutoModelForQuestionAnswering
+from transformers import QuestionAnsweringPipeline
+
+model_name = 'KoichiYasuoka/bert-base-japanese-wikipedia-ud-head'
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForQuestionAnswering.from_pretrained(model_name)
+qap = QuestionAnsweringPipeline(tokenizer=tokenizer, model=model)
+
+def generate_response(st, prompt):
+    # Transformersで回答を作成
+    answer = qap(context=st.session_state.content[:100], question=prompt)
+
+    return answer["answer"]
+

requirements.txt

@@ -0,0 +1,6 @@
+streamlit
+sentencepiece
+transformers
+bs4
+Cython
+torch

scraper.py

@@ -0,0 +1,10 @@
+from bs4 import BeautifulSoup
+import requests
+
+def get_stock_info(stock_code):
+    url = f"https://www.nikkei.com/nkd/company/?scode={stock_code}"
+    r = requests.get(url)
+    soup = BeautifulSoup(r.content, 'html.parser')
+    _text = soup.find('div', attrs={'class': 'm-stockInfo_top_left'})
+    content = _text.text
+    return content