Update app.py

app.py

@@ -104,7 +104,20 @@ def generate_follow_up(user_text):
     return cleaned_output
 
 # ✅ Main Response Function
-def get_response(system_message, chat_history, user_text, max_new_tokens=800):
+# ✅ Main Response Function
+def get_response(system_message, user_text, max_new_tokens=800):
+    """
+    Generates a response from the chatbot, ensures conversation history is updated, and includes a follow-up question.
+    """
+    
+    # ✅ Ensure Chat History is Initialized
+    if "chat_history" not in st.session_state:
+        st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
+
+    # ✅ Get Chat History Reference
+    chat_history = st.session_state.chat_history  
+
+    # ✅ Detect Intent (NASA query vs General AI chat)
     action = predict_action(user_text)
 
     # ✅ Handle NASA-Specific Queries
@@ -112,18 +125,24 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=800):
         nasa_url, nasa_title, nasa_explanation = get_nasa_apod()
         response = f"**{nasa_title}**\n\n{nasa_explanation}"
         follow_up = generate_follow_up(user_text)
-        chat_history.extend([
-            {'role': 'user', 'content': user_text},
-            {'role': 'assistant', 'content': response},
-            {'role': 'assistant', 'content': follow_up}
-        ])
-        return response, follow_up, chat_history, nasa_url
 
-    # ✅ Invoke Hugging Face Model
-    hf = get_llm_hf_inference(max_new_tokens=max_new_tokens, temperature=0.7)
+        # ✅ Append to chat history
+        chat_history.append({'role': 'user', 'content': user_text})
+        chat_history.append({'role': 'assistant', 'content': response})
+        chat_history.append({'role': 'assistant', 'content': follow_up})
+
+        # ✅ Update `st.session_state.chat_history`
+        st.session_state.chat_history = chat_history
 
-    filtered_history = "\n".join(f"{msg['role']}: {msg['content']}" for msg in chat_history)
+        return response, follow_up, chat_history, nasa_url  # ✅ Always return 4 values
 
+    # ✅ Format Conversation History for Model Input
+    formatted_chat_history = "\n".join(f"{msg['role']}: {msg['content']}" for msg in chat_history)
+
+    # ✅ Invoke Hugging Face Model
+    hf = get_llm_hf_inference(max_new_tokens=max_new_tokens, temperature=0.9)
+
+    # ✅ Define the Chat Prompt Template
     prompt = PromptTemplate.from_template(
         "[INST] You are a helpful AI assistant.\n\nCurrent Conversation:\n{chat_history}\n\n"
         "User: {user_text}.\n [/INST]\n"
@@ -133,23 +152,33 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=800):
         "\nHAL:"
     )
 
+    # ✅ Generate AI Response
     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=filtered_history))
+    response = chat.invoke(input=dict(system_message=system_message, user_text=user_text, chat_history=formatted_chat_history))
+
+    # ✅ Extract and Clean Response
     response = response.split("HAL:")[-1].strip() if "HAL:" in response else response.strip()
 
+    # ✅ Ensure Response is in English
     response = ensure_english(response)
 
+    # ✅ Fallback Response Handling
     if not response:
         response = "I'm sorry, but I couldn't generate a response. Can you rephrase your question?"
 
+    # ✅ Generate Follow-Up Question
     follow_up = generate_follow_up(user_text)
 
-     # ✅ Preserve conversation history
-    st.session_state.chat_history.append({'role': 'user', 'content': user_text})
-    st.session_state.chat_history.append({'role': 'assistant', 'content': response})
-    st.session_state.chat_history.append({'role': 'assistant', 'content': follow_up})
+    # ✅ Append Conversation History
+    chat_history.append({'role': 'user', 'content': user_text})
+    chat_history.append({'role': 'assistant', 'content': response})
+    chat_history.append({'role': 'assistant', 'content': follow_up})
+
+    # ✅ Update the Global Session State to Preserve History
+    st.session_state.chat_history = chat_history  
+
+    return response, follow_up, chat_history, None  # ✅ Ensure 4 values are returned
 
-    return response, follow_up, chat_history, None
 
 # ✅ Streamlit UI
 st.title("🚀 HAL - NASA AI Assistant")