Upload app.py

app.py

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