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import streamlit as st |
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from transformers import pipeline |
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@st.cache_resource |
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def load_model(): |
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chatbot = pipeline("conversational", model="facebook/blenderbot-400M-distill") |
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return chatbot |
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st.title("Український Чат-бот") |
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if "history" not in st.session_state: |
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st.session_state.history = [] |
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user_input = st.text_input("Ви:", "") |
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if st.button("Надіслати"): |
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chatbot = load_model() |
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response = chatbot(st.session_state.history + [{"role": "user", "content": user_input}]) |
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st.session_state.history.extend([{"role": "user", "content": user_input}, {"role": "assistant", "content": response.generated_responses[0]}]) |
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if st.session_state.history: |
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for message in st.session_state.history: |
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if message["role"] == "user": |
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st.write(f"Ви: {message['content']}") |
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else: |
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st.write(f"Бот: {message['content']}") |
