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import os |
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from dotenv import load_dotenv |
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import openai |
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import streamlit as st |
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from langchain_openai import ChatOpenAI |
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from langchain.chains import RetrievalQA |
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from langchain_openai import OpenAIEmbeddings |
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from langchain_community.vectorstores import FAISS |
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load_dotenv() |
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openai.api_key = os.environ["OPENAI_API_KEY"] |
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MODEL_NAME = "gpt-3.5-turbo-16k-0613" |
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MODEL_TEMPERATURE = 0.9 |
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st.title("Welcome to TOKAI Chatbot.ver8 🔰") |
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st.markdown("お困りになっていることを教えてください。") |
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vectoreStore = FAISS.load_local("faiss_index/", OpenAIEmbeddings(), allow_dangerous_deserialization=True) |
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retriever = vectoreStore.as_retriever(search_type="similarity", search_kwargs={"k": 3}) |
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if "messages" not in st.session_state: |
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st.session_state.messages = [] |
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for message in st.session_state.messages: |
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with st.chat_message(message["role"]): |
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st.markdown(message["content"]) |
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if prompt := st.chat_input("ここに質問事項を入力してください。"): |
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st.session_state.messages.append({"role": "user", "content": prompt}) |
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with st.chat_message("user"): |
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st.markdown(prompt) |
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qa = RetrievalQA.from_chain_type( |
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llm=ChatOpenAI(temperature=MODEL_TEMPERATURE, model_name=MODEL_NAME), |
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chain_type="stuff", |
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retriever=retriever, |
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return_source_documents=False |
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) |
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query = f"東海大学の授業要覧以外に関する質問には答えないでください。次の質問に答えてください。:{prompt}" |
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res = qa.run(query) |
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st.session_state.messages.append({"role": "assistant", "content": res}) |
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with st.chat_message("assistant"): |
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st.markdown(res) |
