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Parent(s):
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Update app.py
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app.py
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import torch
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from transformers import DistilBertTokenizer, DistilBertForSequenceClassification
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#
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import streamlit as st
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import torch
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from transformers import DistilBertTokenizer, DistilBertForSequenceClassification
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# Title and Description
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st.title("Simple DistilBERT Chatbot")
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st.write("This is a basic chatbot prototype. Ask it something!")
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# Load Model and Tokenizer
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@st.cache_resource # Cache for efficiency
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def load_model_tokenizer():
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tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')
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model = DistilBertForSequenceClassification.from_pretrained('distilbert-base-uncased')
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return tokenizer, model
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tokenizer, model = load_model_tokenizer()
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# User Input
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user_input = st.text_input("You: ")
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# Generate Response on Button Click
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if st.button("Send"):
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if not user_input:
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st.warning("Please enter some text.")
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else:
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# Preprocess and Generate Response (placeholder)
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encoded_input = preprocess_input(user_input)
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outputs = model(**encoded_input)
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# (TODO) Extract relevant info from outputs
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bot_response = "I'm still under development, but I understand you said: {}".format(user_input)
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st.write("Bot: " + bot_response)
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