Update app.py

app.py

@@ -4,20 +4,31 @@ from huggingface_hub import InferenceClient
 # Initialize the InferenceClient
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p,):
-    
-    messages = [{"role": "system", "content": system_message}]
+# Streamlit app configuration
+st.set_page_config(page_title="Health Care ChatBot", layout="wide")
+st.title("Health Care ChatBot")
+
+# Initialize session state for messages if not present
+if 'messages' not in st.session_state:
+    st.session_state.messages = [
+        {"role": "system", "content": "You are a knowledgeable and empathetic medical assistant providing accurate and compassionate health advice based on user input."}
+    ]
+
+def respond(message, history, max_tokens, temperature, top_p):
+    # Prepare the list of messages for the chat completion
+    messages = [{"role": "system", "content": st.session_state.messages[0]["content"]}]
 
     for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+        if val["role"] == "user":
+            messages.append({"role": "user", "content": val["content"]})
+        elif val["role"] == "assistant":
+            messages.append({"role": "assistant", "content": val["content"]})
 
     messages.append({"role": "user", "content": message})
 
+    # Generate response
     response = ""
-    response_container = st.empty()  # Placeholder to update the response text
+    response_container = st.empty()  # Placeholder to update the response text dynamically
 
     for message in client.chat_completion(
         messages,
@@ -27,41 +38,41 @@ def respond(message, history: list[tuple[str, str]], system_message, max_tokens,
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
-        response_container.text(response)  # Dynamically update the response
+        response_container.text(response)  # Stream the response
 
-# Streamlit interface
-st.title("Health Care ChatBot")
+    return response
 
+# Sidebar for parameters
 with st.sidebar:
-    # User inputs
     max_tokens = st.slider("Max new tokens", 1, 2048, 512)
     temperature = st.slider("Temperature", 0.1, 4.0, 0.7)
     top_p = st.slider("Top-p (nucleus sampling)", 0.1, 1.0, 0.95)
 
+# Display chat messages from history
+for message in st.session_state.messages:
+    if message["role"] == "user":
+        with st.chat_message("user"):
+            st.write(message["content"])
+        
+    elif message["role"] == "assistant":
+        with st.chat_message("assistant"):
+            st.write(message["content"])
 
-# A placeholder for chat history
-history = st.session_state.get('history', [])
-#system message
-system_message = "You are a knowledgeable and empathetic medical assistant providing accurate and compassionate health advice based on user input."
-#input message
-message = st.text_input("User message", key="user_message")
+# Get user input
+user_input = st.text_input("You:", key="user_message")
 
-# Submit button
-if st.button("Send"):
-    if message:
-        # Append the new message to the history
-        history.append((message, ""))  # No assistant response yet
-        
-        # Call the respond function and update the history with the assistant's reply
-        for response in respond(message, history, system_message, max_tokens, temperature, top_p):
-            history[-1] = (message, response)
-        
-        # Save updated history in session state
-        st.session_state['history'] = history
+if user_input:
+    # Append user message to the chat history
+    st.session_state.messages.append({"role": "user", "content": user_input})
 
-# Display the chat history
-for user_msg, bot_msg in history:
-    # st.write(f"**User**: {user_msg}")
-    st.markdown(f"**Assistant**: {bot_msg}")
+    # Generate assistant response
+    response = respond(user_input, st.session_state.messages, max_tokens, temperature, top_p)
+    st.session_state.messages.append({"role": "assistant", "content": response})
+
+    # Display the latest messages
+    with st.chat_message("user"):
+        st.write(user_input)
+    
+    with st.chat_message("assistant"):
+        st.write(response)