Update app.py

app.py

@@ -12,8 +12,7 @@ def query(payload):
     response = requests.post(API_URL, headers=headers, json=payload)
     return response.json()
 
-# Streamlit UI
-st.title("Chat App with Hugging Face")
+
 
 # Input textbox
 user_input = st.text_input("You:", "")
@@ -30,33 +29,13 @@ if st.button("Send"):
         else:
             st.error("No response from the model")
 
-# Description
-st.markdown("""
-Language models can be conditioned to act like dialogue agents through a conversational prompt that typically takes the form:
-User: <utterance>
-Assistant: <utterance>
-User: <utterance>
-Assistant: <utterance>
-...
-In this app, you can explore the outputs of multiple LLMs when prompted in this way.
-""")
-
-# CSS styles
-st.markdown(
-    """
-    <style>
-        #col_container {margin-left: auto; margin-right: auto;}
-        #chatbot {height: 520px; overflow: auto;}
-    </style>
-    """,
-    unsafe_allow_html=True
-)
+
+
+
 
 # Title and description
 st.title("Large Language Model Chat API")
-st.markdown("""
-<div align="center">Powered by: <a href=https://github.com/huggingface/text-generation-inference>Text Generation Inference</a></div>
-""")
+
 
 # Model selection
 model = st.radio(
@@ -73,7 +52,7 @@ model = st.radio(
 )
 
 # Input textbox
-input_text = st.text_input(label="Type an input and press Enter", placeholder="Hi there!")
+input_text = st.text_input(label="Type an input and press Enter", placeholder="What is Deep Learning?")
 
 # Parameters
 with st.expander("Parameters", expanded=False):