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app.py
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import streamlit as st
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#from streamlit_chat import message as st_message
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from streamlit_chat import message as st_message
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from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration
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st.title("Chatbot Blenderbot Streamlit")
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if "history" not in st.session_state:
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st.session_state.history = []
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def get_models():
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tokenizer = BlenderbotTokenizer.from_pretrained("facebook/blenderbot-400M-distill")
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model = BlenderbotForConditionalGeneration.from_pretrained("facebook/blenderbot-400M-distill")
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return tokenizer, model
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def generate_answer():
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tokenizer, model = get_models()
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user_message = st.session_state.input_text
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inputs = tokenizer(st.session_state.input_text, return_tensors="pt")
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result = model.generate(**inputs)
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message_bot = tokenizer.decode(result[0], skip_special_tokens=True) # .replace("<s>", "").replace("</s>", "")
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st.session_state.history.append({"message": user_message, "is_user": True})
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st.session_state.history.append({"message": message_bot, "is_user": False})
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st.text_input("Response", key="input_text", on_change=generate_answer)
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for chat in st.session_state.history:
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st_message(**chat)
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