Update app.py

app.py

@@ -20,7 +20,7 @@ st.set_page_config(page_title="HAL - NASA ChatBot", page_icon="🚀")
 
 # --- Initialize Session State Variables ---
 if "chat_history" not in st.session_state:
-    # Initial greeting stored in chat history
+    # The initial greeting is stored in chat_history
     st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
 
 if "response_ready" not in st.session_state:
@@ -40,7 +40,7 @@ sentiment_analyzer = pipeline(
 )
 
 def get_llm_hf_inference(model_id=model_id, max_new_tokens=128, temperature=0.7):
-    # Specify task="text-generation" so that the endpoint uses the right model function.
+    # Specify task="text-generation" so that the endpoint uses the correct function.
     return HuggingFaceEndpoint(
         repo_id=model_id,
         max_new_tokens=max_new_tokens,
@@ -82,7 +82,7 @@ def generate_follow_up(user_text):
 def get_response(system_message, chat_history, user_text, max_new_tokens=256):
     """
     Generates HAL's response in a friendly, conversational manner.
-    The prompt instructs the model to ignore previous greetings and focus on the new user question.
+    This version filters out the initial greeting from chat_history to prevent repetition.
     """
     sentiment = analyze_sentiment(user_text)
     action = predict_action(user_text)
@@ -92,14 +92,19 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=256):
         response = f"**{nasa_title}**\n\n{nasa_explanation}"
         chat_history.append({'role': 'user', 'content': user_text})
         chat_history.append({'role': 'assistant', 'content': response})
-        
         follow_up = generate_follow_up(user_text)
         chat_history.append({'role': 'assistant', 'content': follow_up})
         return response, follow_up, chat_history, nasa_url
 
     hf = get_llm_hf_inference(max_new_tokens=max_new_tokens, temperature=0.9)
 
-    # Updated prompt: Instruct the model not to repeat previous greetings.
+    # Build a filtered conversation history excluding the initial greeting
+    filtered_history = ""
+    for message in chat_history:
+        if message["role"] == "assistant" and message["content"].strip() == "Hello! How can I assist you today?":
+            continue
+        filtered_history += f"{message['role']}: {message['content']}\n"
+
     prompt = PromptTemplate.from_template(
         (
             "[INST] {system_message}\n\nCurrent Conversation:\n{chat_history}\n\n"
@@ -109,8 +114,9 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=256):
             "'Certainly!', 'Of course!', or 'Great question!'.\nHAL:"
         )
     )
+
     chat = prompt | hf.bind(skip_prompt=True) | StrOutputParser(output_key='content')
-    response = chat.invoke(input=dict(system_message=system_message, user_text=user_text, chat_history=chat_history))
+    response = chat.invoke(input=dict(system_message=system_message, user_text=user_text, chat_history=filtered_history))
     response = response.split("HAL:")[-1].strip()
 
     chat_history.append({'role': 'user', 'content': user_text})
@@ -167,15 +173,6 @@ st.markdown("""
     </style>
 """, unsafe_allow_html=True)
 
-# Chat History Display
-st.markdown("<div class='container'>", unsafe_allow_html=True)
-for message in st.session_state.chat_history:
-    if message["role"] == "user":
-        st.markdown(f"<div class='user-msg'><strong>You:</strong> {message['content']}</div>", unsafe_allow_html=True)
-    else:
-        st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {message['content']}</div>", unsafe_allow_html=True)
-st.markdown("</div>", unsafe_allow_html=True)
-
 # --- Single Input Box for Both Initial and Follow-Up Messages ---
 user_input = st.chat_input("Type your message here...")  # Only ONE chat_input()
 
@@ -186,14 +183,18 @@ if user_input:
         chat_history=st.session_state.chat_history
     )
 
-    st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {response}</div>", unsafe_allow_html=True)
-
     if image_url:
         st.image(image_url, caption="NASA Image of the Day")
 
     st.session_state.follow_up = follow_up
     st.session_state.response_ready = True
 
-if st.session_state.response_ready and st.session_state.follow_up:
-    st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {st.session_state.follow_up}</div>", unsafe_allow_html=True)
-    st.session_state.response_ready = False
+# Now render the entire chat history after processing new input.
+st.markdown("<div class='container'>", unsafe_allow_html=True)
+for message in st.session_state.chat_history:
+    if message["role"] == "user":
+        st.markdown(f"<div class='user-msg'><strong>You:</strong> {message['content']}</div>", unsafe_allow_html=True)
+    else:
+        st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {message['content']}</div>", unsafe_allow_html=True)
+st.markdown("</div>", unsafe_allow_html=True)
+