Implement UX enhancements: redesigned sidebar layout, stage-aware processing feedback, and user-friendly error messages

AI-Life-Coach-Streamlit2

@@ -0,0 +1 @@
+Subproject commit ac83e06dd776b60459bb531d961b4f327d1e6a41

app.py

@@ -13,6 +13,7 @@ from core.llm import send_to_ollama, send_to_hf
 from core.session import session_manager
 from core.memory import check_redis_health
 from core.coordinator import coordinator
+from core.errors import translate_error
 import logging
 
 # Set up logging
@@ -21,6 +22,15 @@ logger = logging.getLogger(__name__)
 
 st.set_page_config(page_title="AI Life Coach", page_icon="🧠", layout="wide")
 
+# Processing stage labels for better user feedback
+PROCESSING_STAGES = {
+    "ollama": "🦙 Contacting Ollama...",
+    "hf_init": "⚡ Initializing HF Endpoint (2–4 minutes)...",
+    "hf_thinking": "🧠 HF Expert Thinking...",
+    "hf_complete": "🎯 HF Analysis Complete!",
+    "error": "⚠️ Something went wrong – trying again..."
+}
+
 # Initialize session state
 if "messages" not in st.session_state:
     st.session_state.messages = []
@@ -33,12 +43,13 @@ if "ngrok_url_temp" not in st.session_state:
 if "hf_expert_requested" not in st.session_state:
     st.session_state.hf_expert_requested = False
 
-# Sidebar
+# Sidebar layout redesign
 with st.sidebar:
-    st.title("AI Life Coach 🧠")
+    st.title("🧠 AI Life Coach")
     st.markdown("Your personal AI-powered life development assistant")
     
-    # Model selection
+    # PRIMARY ACTIONS
+    st.subheader("💬 Primary Actions")
     model_options = {
         "Mistral 7B (Local)": "mistral:latest",
         "Llama 2 7B (Local)": "llama2:latest",
@@ -47,24 +58,26 @@ with st.sidebar:
     selected_model_name = st.selectbox(
         "Select Model",
         options=list(model_options.keys()),
-        index=0
+        index=0,
+        key="sidebar_model_select"
     )
     st.session_state.selected_model = model_options[selected_model_name]
     
-    # Ollama URL input
-    st.subheader("Ollama Configuration")
+    st.divider()
+    
+    # CONFIGURATION
+    st.subheader("⚙️ Configuration")
     ngrok_url_input = st.text_input(
         "Ollama Server URL",
         value=st.session_state.ngrok_url_temp,
         help="Enter your ngrok URL",
-        key="ngrok_url_input"
+        key="sidebar_ngrok_url"
     )
     
     if ngrok_url_input != st.session_state.ngrok_url_temp:
         st.session_state.ngrok_url_temp = ngrok_url_input
         st.success("✅ URL updated!")
     
-    # Test connection button
     if st.button("📡 Test Connection"):
         try:
             import requests
@@ -85,22 +98,15 @@ with st.sidebar:
         except Exception as e:
             st.error(f"❌ Error: {str(e)[:50]}...")
     
-    # Conversation history
-    st.subheader("Conversation History")
     if st.button("🗑️ Clear History"):
         st.session_state.messages = []
         st.success("History cleared!")
     
-    if st.session_state.messages:
-        user_msgs = len([m for m in st.session_state.messages if m["role"] == "user"])
-        ai_msgs = len([m for m in st.session_state.messages if m["role"] == "assistant"])
-        st.caption(f"💬 {user_msgs} user, {ai_msgs} AI messages")
+    st.divider()
     
-    # Advanced Debug Panel (now properly collapsible)
-    with st.expander("🔍 System Monitor", expanded=False):
-        st.subheader("📊 Status")
-        
-        # Ollama Status
+    # ADVANCED FEATURES
+    with st.expander("🔍 Advanced Features", expanded=False):
+        st.subheader("📊 System Monitor")
         try:
             from services.ollama_monitor import check_ollama_status
             ollama_status = check_ollama_status()
@@ -111,7 +117,6 @@ with st.sidebar:
         except:
             st.info("🦙 Ollama: Unknown")
         
-        # HF Status
         try:
             from services.hf_endpoint_monitor import hf_monitor
             hf_status = hf_monitor.check_endpoint_status()
@@ -122,11 +127,30 @@ with st.sidebar:
         except:
             st.info("🤗 HF: Unknown")
         
-        # Redis Status
         if check_redis_health():
             st.success("💾 Redis: Connected")
         else:
             st.error("💾 Redis: Disconnected")
+        
+        st.divider()
+        
+        st.subheader("🤖 HF Expert Analysis")
+        col1, col2 = st.columns([3, 1])
+        with col1:
+            st.markdown("""
+                **HF Expert Features:**
+                - Analyzes entire conversation history
+                - Performs web research when needed
+                - Provides deep insights and recommendations
+                - Acts as expert consultant in your conversation
+            """)
+        with col2:
+            if st.button("🧠 Activate HF Expert",
+                         key="activate_hf_expert_sidebar",
+                         help="Send conversation to HF endpoint for deep analysis",
+                         use_container_width=True,
+                         disabled=st.session_state.is_processing):
+                st.session_state.hf_expert_requested = True
 
 # Main interface
 st.title("🧠 AI Life Coach")
@@ -155,16 +179,15 @@ if st.session_state.messages and len(st.session_state.messages) > 0:
         col1, col2 = st.columns([3, 1])
         with col1:
             st.markdown("""
-            **HF Expert Features:**
-            - Analyzes entire conversation history
-            - Performs web research when needed
-            - Provides deep insights and recommendations
-            - Acts as expert consultant in your conversation
+                **HF Expert Features:**
+                - Analyzes entire conversation history
+                - Performs web research when needed
+                - Provides deep insights and recommendations
+                - Acts as expert consultant in your conversation
             """)
             
             # Show conversation preview
             st.markdown("**Conversation Preview for HF Expert:**")
-            # Create a container-like appearance without using the border parameter
             st.markdown("---")
             for i, msg in enumerate(st.session_state.messages[-5:]):  # Last 5 messages
                 role = "👤 You" if msg["role"] == "user" else "🤖 Assistant"
@@ -227,7 +250,8 @@ if st.session_state.messages and len(st.session_state.messages) > 0:
                         st.session_state.hf_expert_requested = False
                 
                 except Exception as e:
-                    st.error(f"❌ HF Expert analysis failed: {str(e)}")
+                    user_msg = translate_error(e)
+                    st.error(f"❌ HF Expert analysis failed: {user_msg}")
                     st.session_state.hf_expert_requested = False
 
 # Chat input - FIXED VERSION
@@ -260,7 +284,7 @@ if user_input and not st.session_state.is_processing:
             conversation_history.append({"role": "user", "content": user_input})
             
             # Try Ollama with proper error handling
-            status_placeholder.info("🦙 Contacting Ollama...")
+            status_placeholder.info(PROCESSING_STAGES["ollama"])
             ai_response = None
             
             try:
@@ -278,20 +302,22 @@ if user_input and not st.session_state.is_processing:
                     status_placeholder.warning("⚠️ Empty response from Ollama")
             
             except Exception as ollama_error:
-                status_placeholder.error(f"❌ Ollama error: {str(ollama_error)[:50]}...")
-                
-                # Fallback to HF if available
-                if config.hf_token:
-                    status_placeholder.info("🔄 Trying Hugging Face...")
-                    try:
-                        ai_response = send_to_hf(user_input, conversation_history)
-                        if ai_response:
-                            response_placeholder.markdown(ai_response)
-                            status_placeholder.success("✅ HF response received!")
-                        else:
-                            status_placeholder.error("❌ No response from HF")
-                    except Exception as hf_error:
-                        status_placeholder.error(f"❌ HF also failed: {str(hf_error)[:50]}...")
+                user_msg = translate_error(ollama_error)
+                status_placeholder.error(f"⚠️ {user_msg}")
+            
+            # Fallback to HF if available
+            if config.hf_token and not ai_response:
+                status_placeholder.info(PROCESSING_STAGES["hf_init"])
+                try:
+                    ai_response = send_to_hf(user_input, conversation_history)
+                    if ai_response:
+                        response_placeholder.markdown(ai_response)
+                        status_placeholder.success("✅ HF response received!")
+                    else:
+                        status_placeholder.error("❌ No response from HF")
+                except Exception as hf_error:
+                    user_msg = translate_error(hf_error)
+                    status_placeholder.error(f"⚠️ {user_msg}")
             
             # Save response if successful
             if ai_response:
@@ -315,11 +341,11 @@ if user_input and not st.session_state.is_processing:
                 })
         
         except Exception as e:
-            error_msg = f"System error: {str(e)}"
-            response_placeholder.error(error_msg)
+            user_msg = translate_error(e)
+            response_placeholder.error(f"⚠️ {user_msg}")
             st.session_state.messages.append({
                 "role": "assistant",
-                "content": error_msg,
+                "content": f"⚠️ {user_msg}",
                 "timestamp": datetime.now().strftime("%H:%M:%S")
             })
         finally:

core/errors.py

@@ -0,0 +1,23 @@
+# core/errors.py
+
+USER_FRIENDLY_ERRORS = {
+    "connection refused": "Unable to connect to the local AI server. Is Ollama running?",
+    "503 service unavailable": "The advanced model is warming up (may take 2–4 minutes). Please try again shortly.",
+    "timeout": "Request took too long. Check your internet connection or try again later.",
+    "invalid token": "Authentication failed. Please verify your API keys are correct.",
+    "model not found": "Selected model isn't loaded. Try pulling it with 'ollama pull <model>'."
+}
+
+def translate_error(exception: Exception) -> str:
+    """
+    Translate raw exception into a user-friendly message.
+    Falls back to original message if no match.
+    """
+    exc_str = str(exception).lower()
+    
+    for key_phrase, friendly_msg in USER_FRIENDLY_ERRORS.items():
+        if key_phrase in exc_str:
+            return friendly_msg
+            
+    # Default fallback - show original error but in a friendlier way
+    return f"Something unexpected happened: {str(exception)[:100]}{'...' if len(str(exception)) > 100 else ''}"