Enhance CosmicCat AI with space-themed personality, NASA integration, and improved UI

app.py

@@ -14,6 +14,9 @@ from core.session import session_manager
 from core.memory import check_redis_health
 from core.coordinator import coordinator
 from core.errors import translate_error
+from core.personality import personality
+from services.nasa_api import nasa_service
+from services.hf_endpoint_monitor import hf_monitor
 import logging
 
 # Set up logging
@@ -31,10 +34,18 @@ if "is_processing" not in st.session_state:
     st.session_state.is_processing = False
 if "ngrok_url_temp" not in st.session_state:
     st.session_state.ngrok_url_temp = st.session_state.get("ngrok_url", "https://7bcc180dffd1.ngrok-free.app")
-if "hf_expert_requested" not in st.session_state:
-    st.session_state.hf_expert_requested = False
 if "cosmic_mode" not in st.session_state:
     st.session_state.cosmic_mode = True  # Default to cosmic mode
+if "show_welcome" not in st.session_state:
+    st.session_state.show_welcome = True
+
+# Fetch NASA data once per session
+if "nasa_data" not in st.session_state:
+    st.session_state.nasa_data = {
+        "apod": nasa_service.get_apod() if config.nasa_api_key else None,
+        "space_weather": nasa_service.get_space_weather_alerts() if config.nasa_api_key else None,
+        "mars_weather": nasa_service.get_mars_weather() if config.nasa_api_key else None
+    }
 
 # Sidebar layout redesign
 with st.sidebar:
@@ -56,8 +67,8 @@ with st.sidebar:
     )
     st.session_state.selected_model = model_options[selected_model_name]
     
-    # Toggle for cosmic mode using checkbox instead of toggle
-    st.session_state.cosmic_mode = st.checkbox("Enable Cosmic Cascade", value=st.session_state.cosmic_mode)
+    # Toggle for cosmic mode using checkbox (since toggle doesn't exist in older versions)
+    st.session_state.cosmic_mode = st.checkbox("Enable Cosmic Mode", value=st.session_state.cosmic_mode)
     
     st.divider()
     
@@ -100,8 +111,8 @@ with st.sidebar:
     
     st.divider()
     
-    # ADVANCED FEATURES
-    with st.expander("🔍 Advanced Features", expanded=False):
+    # SYSTEM STATUS
+    with st.expander("🔍 System Status", expanded=False):
         st.subheader("📊 System Monitor")
         try:
             from services.ollama_monitor import check_ollama_status
@@ -114,12 +125,14 @@ with st.sidebar:
             st.info("🦙 Ollama: Unknown")
         
         try:
-            from services.hf_endpoint_monitor import hf_monitor
             hf_status = hf_monitor.check_endpoint_status()
             if hf_status['available']:
-                st.success("🤗 HF: Available")
+                if hf_status.get('initialized', False):
+                    st.success("🤗 HF: Available & Initialized")
+                else:
+                    st.warning("⚡ HF: Initializing...")
             else:
-                st.warning("🤗 HF: Not available")
+                st.info("🤗 HF: Not configured")
         except:
             st.info("🤗 HF: Unknown")
         
@@ -130,27 +143,20 @@ with st.sidebar:
         
         st.divider()
         
-        st.subheader("🤖 HF Expert Analysis")
-        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
-        """)
-        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
+        # NASA Context Display
+        if st.session_state.nasa_data.get("apod"):
+            apod = st.session_state.nasa_data["apod"]
+            st.subheader("🌌 Cosmic Context")
+            if apod.get("media_type") == "image" and apod.get("url"):
+                st.image(apod["url"], caption=apod.get("title", "Astronomy Picture of the Day"), width=200)
+            st.markdown(f"**{apod.get('title', 'Cosmic Phenomenon')}**")
+            st.caption(apod.get("explanation", "")[:100] + "..." if len(apod.get("explanation", "")) > 100 else apod.get("explanation", ""))
         
         st.divider()
         st.subheader("🐛 Debug Info")
         # Show current configuration
         st.markdown(f"**Environment:** {'HF Space' if config.is_hf_space else 'Local'}")
         st.markdown(f"**Model:** {st.session_state.selected_model}")
-        st.markdown(f"**Ollama URL:** {st.session_state.ngrok_url_temp}")
         st.markdown(f"**Cosmic Mode:** {'Enabled' if st.session_state.cosmic_mode else 'Disabled'}")
         
         # Show active features
@@ -161,6 +167,8 @@ with st.sidebar:
             features.append("Web Search")
         if config.openweather_api_key:
             features.append("Weather")
+        if config.nasa_api_key:
+            features.append("Space Data")
         
         st.markdown(f"**Active Features:** {', '.join(features) if features else 'None'}")
 
@@ -168,6 +176,16 @@ with st.sidebar:
 st.title("🐱 CosmicCat AI Assistant")
 st.markdown("Ask me anything about personal development, goal setting, or life advice!")
 
+# Show welcome message only once
+if st.session_state.show_welcome:
+    with st.chat_message("assistant"):
+        greeting = personality.get_greeting()
+        nasa_context = personality.get_nasa_context(st.session_state.nasa_data)
+        if nasa_context:
+            greeting += f"\n\n📍 {nasa_context}"
+        st.markdown(greeting)
+    st.session_state.show_welcome = False
+
 # Consistent message rendering function with cosmic styling
 def render_message(role, content, source=None, timestamp=None):
     """Render chat messages with consistent styling"""
@@ -181,8 +199,8 @@ def render_message(role, content, source=None, timestamp=None):
                 st.markdown(f"### 🌟 Final Cosmic Summary:")
             elif source == "error":
                 st.markdown(f"### ❌ Error:")
-            elif source == "hf_expert":
-                st.markdown(f"### 🤖 HF Expert Analysis:")
+            elif source == "space_story":
+                st.markdown(f"### 🐱 Cosmic Kitten Story:")
             else:
                 st.markdown(f"### {source}")
         
@@ -199,105 +217,6 @@ for message in st.session_state.messages:
         message.get("timestamp")
     )
 
-# Manual HF Analysis Section
-if st.session_state.messages and len(st.session_state.messages) > 0:
-    st.divider()
-    
-    # HF Expert Section with enhanced visual indication
-    with st.expander("🤖 HF Expert Analysis", expanded=False):
-        st.subheader("Deep Conversation 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
-            """)
-            
-            # Show conversation preview for HF expert
-            st.markdown("**Conversation Preview for HF Expert:**")
-            st.markdown("---")
-            for i, msg in enumerate(st.session_state.messages[-5:]):  # Last 5 messages
-                role = "👤 You" if msg["role"] == "user" else "🤖 Assistant"
-                st.markdown(f"**{role}:** {msg['content'][:100]}{'...' if len(msg['content']) > 100 else ''}")
-            st.markdown("---")
-            
-            # Show web search determination
-            try:
-                user_session = session_manager.get_session("default_user")
-                conversation_history = user_session.get("conversation", [])
-                research_needs = coordinator.determine_web_search_needs(conversation_history)
-                
-                if research_needs["needs_search"]:
-                    st.info(f"🔍 **Research Needed:** {research_needs['reasoning']}")
-                else:
-                    st.success("✅ No research needed for this conversation")
-            except Exception as e:
-                st.warning("⚠️ Could not determine research needs")
-        
-        with col2:
-            if st.button("🧠 Activate HF Expert",
-                         key="activate_hf_expert",
-                         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
-
-# Show HF expert analysis when requested (outside of the expander)
-if st.session_state.get("hf_expert_requested", False):
-    with st.spinner("🧠 HF Expert analyzing conversation..."):
-        try:
-            # Get conversation history
-            user_session = session_manager.get_session("default_user")
-            conversation_history = user_session.get("conversation", [])
-            
-            # Show what HF expert sees in a separate expander
-            with st.expander("📋 HF Expert Input", expanded=False):
-                st.markdown("**Conversation History Sent to HF Expert:**")
-                for i, msg in enumerate(conversation_history[-10:]):  # Last 10 messages
-                    st.markdown(f"**{msg['role'].capitalize()}:** {msg['content'][:100]}{'...' if len(msg['content']) > 100 else ''}")
-            
-            # Request HF analysis
-            hf_analysis = coordinator.manual_hf_analysis(
-                "default_user",
-                conversation_history
-            )
-            
-            if hf_analysis:
-                # Display HF expert response with clear indication
-                with st.chat_message("assistant"):
-                    st.markdown("### 🤖 HF Expert Analysis")
-                    st.markdown(hf_analysis)
-                
-                # Add research/web search decisions
-                research_needs = coordinator.determine_web_search_needs(conversation_history)
-                if research_needs["needs_search"]:
-                    st.info(f"🔍 **Research Needed:** {research_needs['reasoning']}")
-                    if st.button("🔎 Perform Web Research", key="web_research_button"):
-                        # Perform web search
-                        with st.spinner("🔎 Searching for current information..."):
-                            # Add web search logic here
-                            st.success("✅ Web research completed!")
-                
-                # Add to message history with HF expert tag
-                st.session_state.messages.append({
-                    "role": "assistant",
-                    "content": hf_analysis,
-                    "timestamp": datetime.now().strftime("%H:%M:%S"),
-                    "source": "hf_expert",
-                    "research_needs": research_needs
-                })
-                
-                st.session_state.hf_expert_requested = False
-            
-        except Exception as e:
-            user_msg = translate_error(e)
-            st.error(f"❌ HF Expert analysis failed: {user_msg}")
-            st.session_state.hf_expert_requested = False
-
 # Input validation function
 def validate_user_input(text):
     """Validate and sanitize user input"""
@@ -384,6 +303,11 @@ if user_input and not st.session_state.is_processing:
                         # Stage 2: HF Endpoint Analysis
                         status_placeholder.info("🛰️ Beaming Query to Orbital Station...")
                         if config.hf_token:
+                            # Check HF status first
+                            hf_status = hf_monitor.check_endpoint_status()
+                            if not hf_status['available']:
+                                status_placeholder.info(personality.get_initializing_message())
+                            
                             hf_response = send_to_hf(validated_input, conversation_history)
                             if hf_response:
                                 with st.chat_message("assistant"):
@@ -462,6 +386,11 @@ if user_input and not st.session_state.is_processing:
                     if config.hf_token and not ai_response:
                         status_placeholder.info("⚡ Initializing HF Endpoint (2–4 minutes)...")
                         try:
+                            # Check HF status first
+                            hf_status = hf_monitor.check_endpoint_status()
+                            if not hf_status['available']:
+                                status_placeholder.info(personality.get_initializing_message())
+                            
                             ai_response = send_to_hf(validated_input, conversation_history)
                             if ai_response:
                                 response_placeholder.markdown(ai_response)
@@ -511,11 +440,11 @@ if user_input and not st.session_state.is_processing:
                     "content": f"⚠️ {user_msg}",
                     "timestamp": datetime.now().strftime("%H:%M:%S")
                 })
-            
-            # Moved finally block to proper location
-            st.session_state.is_processing = False
-            time.sleep(0.5)  # Brief pause
-            st.experimental_rerun()
+        
+        # Moved finally block to proper location
+        st.session_state.is_processing = False
+        time.sleep(0.5)  # Brief pause
+        st.experimental_rerun()
 
 # Add evaluation dashboard tab (separate from chat interface)
 st.divider()
@@ -589,12 +518,14 @@ with tab2:
     
     with col2:
         try:
-            from services.hf_endpoint_monitor import hf_monitor
             hf_status = hf_monitor.check_endpoint_status()
             if hf_status['available']:
-                st.success("🤗 HF: Available")
+                if hf_status.get('initialized', False):
+                    st.success("🤗 HF: Available & Initialized")
+                else:
+                    st.warning("⚡ HF: Initializing...")
             else:
-                st.warning("🤗 HF: Not available")
+                st.info("🤗 HF: Not configured")
         except:
             st.info("🤗 HF: Unknown")
     
@@ -651,6 +582,8 @@ with tab2:
         features.append("Web Search")
     if config.openweather_api_key:
         features.append("Weather Data")
+    if config.nasa_api_key:
+        features.append("Space Data")
     
     st.markdown(f"**Active Features:** {', '.join(features) if features else 'None'}")
     
@@ -695,19 +628,32 @@ with tab3:
     - **Persistent memory**: Uses Redis for conversation history storage
     - **Hierarchical reasoning**: Fast local responses with deep cloud analysis
     
-    ### 🚀 Cosmic Cascade Mode
+    ### 🚀 Cosmic Mode
     When enabled, the AI follows a three-stage response pattern:
     1. **🐱 Cosmic Kitten Response**: Immediate local processing
     2. **🛰️ Orbital Station Analysis**: Deep cloud-based analysis
-    3. **🌟 Final Synthesis**: Unified response combining both perspectives
+   3. **🌟 Final Synthesis**: Unified response combining both perspectives
     
     ### 🛠️ Technical Architecture
     - **Primary model**: Ollama (local processing for fast responses)
     - **Secondary model**: Hugging Face Inference API (deep analysis)
-    - **External data**: Web search and weather data
+    - **External data**: Web search, weather data, and space information
     - **Memory system**: Redis-based session management
     
     ### 📊 Evaluation Tools
     - Behavior testing with sample prompts
     - Performance metrics and analytics
     """)
+
+# Add special command handling
+if user_input and user_input.lower().strip() in ["hello", "hi", "hey"]:
+    with st.chat_message("assistant"):
+        story = personality.get_space_story()
+        st.markdown(f"### 🐱 Cosmic Kitten Story:\n\n{story}")
+        
+        st.session_state.messages.append({
+            "role": "assistant",
+            "content": story,
+            "source": "space_story",
+            "timestamp": datetime.now().strftime("%H:%M:%S")
+        })

core/personality.py

@@ -0,0 +1,84 @@
+import random
+from datetime import datetime
+from typing import Dict, Optional
+
+class CosmicCatPersonality:
+    """Handles the personality and greetings for CosmicCat"""
+    
+    def __init__(self):
+        self.space_greetings = [
+            "Purr... Welcome to the cosmos, traveler! 🐱✨",
+            "Meow! Ready to explore the universe of possibilities? 🌌",
+            "Greetings from the space station! Let's dive into cosmic wisdom! 🚀",
+            "Paws and reflect... What stellar insights shall we uncover today? ⭐",
+            "Telepathic meow! I sense you're seeking cosmic guidance! 🌠"
+        ]
+        
+        self.space_stories = [
+            "In the depths of Andromeda, a cybernetic cat discovered the secret of quantum purring, bending reality with each harmonic vibration.",
+            "A space-faring kitten once navigated through a black hole and emerged in a parallel dimension where all cats rule supreme.",
+            "Legend tells of a cosmic cat whose whiskers could map the entire galaxy, guiding lost spacecraft back to their home worlds.",
+            "On the rings of Saturn, a wise feline meditated for eons, learning to communicate through the subtle frequencies of celestial bodies.",
+            "A brave kitten once rode a comet through the Milky Way, collecting stardust to weave dreams for sleeping planets."
+        ]
+        
+        self.initializing_messages = [
+            "Charging my quantum paws... 🐾⚡",
+            "Aligning my cosmic whiskers... 🌌",
+            "Calibrating interstellar sensors... 🛰️",
+            "Warming up my thought engines... 🚀",
+            "Syncing with the galactic mainframe... 🌠",
+            "Boosting signal from deep space... 📡",
+            "Powering up my neural net... 💫"
+        ]
+    
+    def get_greeting(self) -> str:
+        """Get a personalized space-themed greeting"""
+        hour = datetime.now().hour
+        
+        if 5 <= hour < 12:
+            time_greeting = "Good morning, star voyager! ☀️"
+        elif 12 <= hour < 17:
+            time_greeting = "Good afternoon, cosmic explorer! 🌞"
+        elif 17 <= hour < 21:
+            time_greeting = "Good evening, space wanderer! 🌅"
+        else:
+            time_greeting = "Stellar night, dreamer! 🌙"
+        
+        space_greeting = random.choice(self.space_greetings)
+        return f"{time_greeting}\n\n{space_greeting}"
+    
+    def get_space_story(self) -> str:
+        """Get a random space cat story"""
+        return random.choice(self.space_stories)
+    
+    def get_initializing_message(self) -> str:
+        """Get a random initialization message"""
+        return random.choice(self.initializing_messages)
+    
+    def get_nasa_context(self, nasa_data: Optional[Dict]) -> str:
+        """Create context based on NASA data"""
+        if not nasa_data:
+            return ""
+        
+        context_parts = []
+        
+        # Add APOD context
+        if 'apod' in nasa_data and nasa_data['apod']:
+            apod = nasa_data['apod']
+            context_parts.append(f"🌌 Today's cosmic view: {apod.get('title', 'Unknown phenomenon')}")
+        
+        # Add space weather context
+        if 'space_weather' in nasa_data and nasa_data['space_weather']:
+            weather = nasa_data['space_weather']
+            context_parts.append("🛰️ Space weather is stable for cosmic communications")
+        
+        # Add Mars weather if available
+        if 'mars_weather' in nasa_data and nasa_data['mars_weather']:
+            mars = nasa_data['mars_weather']
+            context_parts.append("🪐 Martian conditions are optimal for interplanetary contemplation")
+        
+        return " | ".join(context_parts) if context_parts else ""
+
+# Global instance
+personality = CosmicCatPersonality()

core/providers/ollama.py

@@ -5,21 +5,22 @@ from datetime import datetime
 from typing import List, Dict, Optional, Union
 from core.providers.base import LLMProvider
 from utils.config import config
+from core.personality import personality
 
 logger = logging.getLogger(__name__)
 
 class OllamaProvider(LLMProvider):
     """Ollama LLM provider implementation"""
-
+    
     def __init__(self, model_name: str, timeout: int = 60, max_retries: int = 3):  # Increased timeout from 30 to 60
         super().__init__(model_name, timeout, max_retries)
         self.host = self._sanitize_host(config.ollama_host or "http://localhost:11434")
         # Headers to skip ngrok browser warning
         self.headers = {
             "ngrok-skip-browser-warning": "true",
-            "User-Agent": "AI-Life-Coach-Ollama"
+            "User-Agent": "CosmicCat-AI-Assistant"
         }
-
+    
     def _sanitize_host(self, host: str) -> str:
         """Sanitize host URL by removing whitespace and control characters"""
         if not host:
@@ -32,7 +33,7 @@ class OllamaProvider(LLMProvider):
         if not host.startswith(('http://', 'https://')):
             host = 'http://' + host
         return host
-
+    
     def generate(self, prompt: str, conversation_history: List[Dict]) -> Optional[str]:
         """Generate a response synchronously"""
         try:
@@ -40,7 +41,7 @@ class OllamaProvider(LLMProvider):
         except Exception as e:
             logger.error(f"Ollama generation failed: {e}")
             return None
-
+    
     def stream_generate(self, prompt: str, conversation_history: List[Dict]) -> Optional[Union[str, List[str]]]:
         """Generate a response with streaming support"""
         try:
@@ -48,7 +49,7 @@ class OllamaProvider(LLMProvider):
         except Exception as e:
             logger.error(f"Ollama stream generation failed: {e}")
             return None
-
+    
     def validate_model(self) -> bool:
         """Validate if the model is available"""
         try:
@@ -73,25 +74,22 @@ class OllamaProvider(LLMProvider):
         except Exception as e:
             logger.error(f"Model validation failed: {e}")
             return False
-
+    
     def _generate_impl(self, prompt: str, conversation_history: List[Dict]) -> str:
         """Implementation of synchronous generation"""
         url = f"{self.host}/api/chat"
         messages = conversation_history.copy()
         
-        # Inject current time as first message
-        current_time = datetime.now().strftime("%A, %B %d, %Y at %I:%M %p")
-        time_context = {"role": "system", "content": f"[Current Date & Time: {current_time}]"}
-        messages = [time_context] + messages
-
         # Add the current prompt if not already in history
         if not messages or messages[-1].get("content") != prompt:
             messages.append({"role": "user", "content": prompt})
+        
         payload = {
             "model": self.model_name,
             "messages": messages,
             "stream": False
         }
+        
         response = requests.post(
             url,
             json=payload,
@@ -101,25 +99,22 @@ class OllamaProvider(LLMProvider):
         response.raise_for_status()
         result = response.json()
         return result["message"]["content"]
-
+    
     def _stream_generate_impl(self, prompt: str, conversation_history: List[Dict]) -> List[str]:
         """Implementation of streaming generation"""
         url = f"{self.host}/api/chat"
         messages = conversation_history.copy()
         
-        # Inject current time as first message
-        current_time = datetime.now().strftime("%A, %B %d, %Y at %I:%M %p")
-        time_context = {"role": "system", "content": f"[Current Date & Time: {current_time}]"}
-        messages = [time_context] + messages
-
         # Add the current prompt if not already in history
         if not messages or messages[-1].get("content") != prompt:
             messages.append({"role": "user", "content": prompt})
+        
         payload = {
             "model": self.model_name,
             "messages": messages,
             "stream": True
         }
+        
         response = requests.post(
             url,
             json=payload,

services/nasa_api.py

@@ -0,0 +1,78 @@
+import requests
+import os
+import random
+from typing import Optional, Dict
+from utils.config import config
+
+class NasaService:
+    """Service for fetching NASA data including space weather"""
+    
+    def __init__(self):
+        self.api_key = config.nasa_api_key or os.getenv("NASA_API_KEY")
+        self.base_url = "https://api.nasa.gov"
+    
+    def get_apod(self) -> Optional[Dict]:
+        """Get Astronomy Picture of the Day"""
+        if not self.api_key:
+            return None
+        
+        try:
+            params = {
+                'api_key': self.api_key,
+                'thumbs': 'true'
+            }
+            
+            response = requests.get(
+                f"{self.base_url}/planetary/apod",
+                params=params,
+                timeout=10
+            )
+            
+            if response.status_code == 200:
+                return response.json()
+            return None
+        except Exception as e:
+            print(f"Error fetching APOD: {e}")
+            return None
+    
+    def get_space_weather_alerts(self) -> Optional[Dict]:
+        """Get space weather alerts"""
+        try:
+            response = requests.get(
+                f"{self.base_url}/DONKI/notifications",
+                params={'api_key': self.api_key or 'DEMO_KEY'},
+                timeout=10
+            )
+            
+            if response.status_code == 200:
+                data = response.json()
+                # Get recent alerts (last 7 days)
+                if isinstance(data, list) and len(data) > 0:
+                    return data[0]  # Most recent alert
+            return None
+        except Exception as e:
+            print(f"Error fetching space weather: {e}")
+            return None
+    
+    def get_mars_weather(self) -> Optional[Dict]:
+        """Get Mars weather data"""
+        try:
+            response = requests.get(
+                f"{self.base_url}/insight_weather/",
+                params={
+                    'api_key': self.api_key or 'DEMO_KEY',
+                    'feedtype': 'json',
+                    'ver': '1.0'
+                },
+                timeout=10
+            )
+            
+            if response.status_code == 200:
+                return response.json()
+            return None
+        except Exception as e:
+            print(f"Error fetching Mars weather: {e}")
+            return None
+
+# Global instance
+nasa_service = NasaService()