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studybot.py
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import streamlit as st
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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# Load Phi-2 model and tokenizer
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MODEL_NAME = "microsoft/phi-2"
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
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model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
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def get_response(user_input):
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input_ids = tokenizer(user_input, return_tensors="pt").input_ids
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with torch.no_grad():
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output = model.generate(input_ids, max_length=200)
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response = tokenizer.decode(output[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
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return response
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# Streamlit UI
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st.title("Study Buddy Chatbot 📚")
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st.write("Ask a question or type a topic, and I'll help you learn!")
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user_input = st.text_input("Type your question or topic:")
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if user_input:
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response = get_response(user_input)
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st.write("🤖 Chatbot:", response)
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