Create app.py

app.py

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+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load the model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("HuggingFaceTB/SmolLM2-1.7B-Instruct")
+model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolLM2-1.7B-Instruct")
+
+# Streamlit UI
+st.title("ChatGPT Clone")
+st.write("A simple chatbot interface using SmolLM2-1.7B-Instruct")
+
+# Conversation history
+if "history" not in st.session_state:
+    st.session_state.history = []
+
+# User input
+user_input = st.text_input("You:", key="input")
+
+if st.button("Send") and user_input:
+    # Add user input to the history
+    st.session_state.history.append({"role": "user", "content": user_input})
+
+    # Tokenize input and generate a response
+    inputs = tokenizer(user_input, return_tensors="pt", padding=True, truncation=True)
+    outputs = model.generate(**inputs, max_length=150, do_sample=True, top_p=0.95, top_k=50)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    # Add response to the history
+    st.session_state.history.append({"role": "bot", "content": response})
+
+# Display conversation history
+for message in st.session_state.history:
+    role = "User" if message["role"] == "user" else "Bot"
+    st.markdown(f"**{role}:** {message['content']}")
+
+# Reset chat button
+if st.button("Reset Chat"):
+    st.session_state.history = []