Rename streamlit_app.py to app.py

app.py

@@ -0,0 +1,22 @@
+import streamlit as st
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+# Load custom trained model and tokenizer
+model = GPT2LMHeadModel.from_pretrained('https://huggingface.co/spaces/SoniR/chatbotllm/blob/main/config.json')
+tokenizer = GPT2Tokenizer.from_pretrained('https://huggingface.co/spaces/SoniR/chatbotllm/blob/main/pytorch_model.bin')
+
+# Streamlit app title
+st.title("Custom Trained Chatbot")
+
+# Function to generate chatbot response
+def generate_response(user_input):
+    input_ids = tokenizer.encode(user_input, return_tensors='pt')
+    output = model.generate(input_ids, max_length=50, num_return_sequences=1)
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    return response
+
+# Main UI components
+user_input = st.text_input("You:", key="user_input")
+if st.button("Send"):
+    bot_response = generate_response(user_input)
+    st.write("Bot:", bot_response)