Update chatbot.py

chatbot.py

@@ -2,13 +2,21 @@ import os
 import requests
 import random
 import time
+import logging
 from dotenv import load_dotenv
 from messages import krishna_blessings, ayush_teasing
 from ayush_messages import ayush_surprises
 
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
 # Load environment variables (Hugging Face Space secrets)
 load_dotenv()
 HUGGINGFACE_API_TOKEN = os.getenv("HUGGINGFACE_API_TOKEN")
+if not HUGGINGFACE_API_TOKEN:
+    logger.error("HUGGINGFACE_API_TOKEN not found in environment variables.")
+    raise ValueError("HUGGINGFACE_API_TOKEN is required.")
 
 # List of open-source models with fine-tuned parameters
 AI_MODELS = [
@@ -136,19 +144,23 @@ def analyze_sentiment(user_input):
     payload = {
         "inputs": user_input
     }
-    response = make_api_request(
-        "https://api-inference.huggingface.co/models/distilbert-base-uncased-finetuned-sst-2-english",
-        headers=headers,
-        json=payload
-    )
-    if response and response.status_code == 200:
-        result = response.json()
-        if isinstance(result, list) and len(result) > 0:
-            sentiment = result[0]
-            label = sentiment[0]["label"]  # "POSITIVE" or "NEGATIVE"
-            return label.lower()
-    print("Error analyzing sentiment or API failed after retries.")
-    return "neutral"
+    try:
+        response = make_api_request(
+            "https://api-inference.huggingface.co/models/distilbert-base-uncased-finetuned-sst-2-english",
+            headers=headers,
+            json=payload
+        )
+        if response and response.status_code == 200:
+            result = response.json()
+            if isinstance(result, list) and len(result) > 0:
+                sentiment = result[0]
+                label = sentiment[0]["label"]  # "POSITIVE" or "NEGATIVE"
+                return label.lower()
+        logger.warning("Sentiment analysis failed after retries.")
+        return "neutral"
+    except Exception as e:
+        logger.error(f"Error in analyze_sentiment: {str(e)}")
+        return "neutral"
 
 def make_api_request(url, headers, payload, retries=3, delay=5):
     """Helper function to make API requests with retry logic."""
@@ -158,17 +170,18 @@ def make_api_request(url, headers, payload, retries=3, delay=5):
             if response.status_code == 200:
                 return response
             elif response.status_code == 429:  # Rate limit
-                print(f"Rate limit hit on attempt {attempt + 1}. Retrying after {delay} seconds...")
+                logger.warning(f"Rate limit hit on attempt {attempt + 1}. Retrying after {delay} seconds...")
                 time.sleep(delay)
                 continue
             else:
-                print(f"API error: {response.text}")
+                logger.error(f"API error: {response.text}")
                 return None
         except Exception as e:
-            print(f"API request failed: {str(e)}")
+            logger.error(f"API request failed on attempt {attempt + 1}: {str(e)}")
             if attempt < retries - 1:
                 time.sleep(delay)
             continue
+    logger.error(f"API request failed after {retries} retries.")
     return None
 
 def get_krishna_response(user_input):
@@ -180,509 +193,520 @@ def get_krishna_response(user_input):
     - Occasionally tease Manavi about Ayush (keyword-based or every 5th message).
     - Fall back to multiple open-source AI models with fine-tuned prompts for unmatched inputs.
     """
-    user_input_lower = user_input.lower().strip()
+    try:
+        user_input_lower = user_input.lower().strip()
+        logger.info(f"Processing user input: {user_input_lower}")
 
-    # Analyze the sentiment of the user's input
-    sentiment = analyze_sentiment(user_input)
+        # Analyze the sentiment of the user's input
+        sentiment = analyze_sentiment(user_input)
+        logger.info(f"Sentiment detected: {sentiment}")
 
-    # Increment message count
-    conversation_context["message_count"] += 1
+        # Increment message count
+        conversation_context["message_count"] += 1
 
-    # Random chance (30%) to skip predefined responses and let the model generate a response
-    use_model = random.random() < 0.3
+        # Random chance (30%) to skip predefined responses and let the model generate a response
+        use_model = random.random() < 0.3
+        logger.info(f"Use model generation: {use_model}")
 
-    # Reset context if user starts a new conversation
-    if "start over" in user_input_lower or "reset" in user_input_lower:
-        conversation_context["last_topic"] = None
-        conversation_context["message_count"] = 0
-        conversation_context["last_response"] = None
-        conversation_context["last_yes_response"] = None
-        return "Hare Manavi! Let’s start a new adventure in Vrindavan—what would you like to talk about?"
-
-    # Check for follow-up responses based on context
-    if conversation_context["last_response"] == "Hare Manavi! Your joy lights up Vrindavan—shall we celebrate with a flute melody?":
-        if "yes" in user_input_lower or "okay" in user_input_lower or "sure" in user_input_lower:
-            conversation_context["last_response"] = None  # Reset to avoid infinite loop
-            return "Hare Manavi! Let’s play a flute melody by the Yamuna—the peacocks will dance with us!"
-
-    # Check for Ayush-teasing triggers (keyword-based)
-    if "joke" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "joke"
-        conversation_context["last_response"] = None
-        # Randomly decide between a Krishna joke and an Ayush-teasing joke
-        if random.choice([True, False]):
-            return random.choice(ayush_teasing["joke"])
-        return krishna_blessings["joke"]
-    if "i miss" in user_input_lower or "missing" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "missing"
-        conversation_context["last_response"] = None
-        return random.choice(ayush_teasing["missing"])
-    if "bored" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "bored"
-        conversation_context["last_response"] = None
-        return random.choice(ayush_teasing["bored"])
-    if "tired" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "tired"
-        conversation_context["last_response"] = None
-        return random.choice(ayush_teasing["tired"])
-    if "lonely" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "lonely"
-        conversation_context["last_response"] = None
-        return random.choice(ayush_teasing["lonely"])
-    if "manavi" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "manavi"
-        conversation_context["last_response"] = None
-        return random.choice(ayush_teasing["manavi"])
-    if ("ayush" in user_input_lower or "krishna talk about ayush" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "ayush"
-        conversation_context["last_response"] = None
-        return random.choice(ayush_teasing["ayush"])
-
-    # Trigger for "chat with you"
-    if ("chat with you" in user_input_lower or "want to chat" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "chat_with_you"
-        conversation_context["last_response"] = None
-        return krishna_blessings["chat_with_you"]
-
-    # Every 5th message, randomly trigger an Ayush-teasing message (if no keyword match)
-    if conversation_context["message_count"] % 5 == 0 and not use_model:
-        # Randomly select a category from ayush_teasing
-        category = random.choice(list(ayush_teasing.keys()))
-        conversation_context["last_response"] = None
-        return random.choice(ayush_teasing[category])
-
-    # Existing keyword mappings for krishna_blessings and ayush_surprises
-    if ("hello" in user_input_lower or "hi" in user_input_lower or "hii" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "greeting"
-        conversation_context["last_response"] = None
-        return krishna_blessings["greeting"]
-    if "good morning" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "greeting"
-        conversation_context["last_response"] = None
-        return krishna_blessings["good_morning"]
-    if "good afternoon" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "greeting"
-        conversation_context["last_response"] = None
-        return krishna_blessings["good_afternoon"]
-    if "good evening" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "greeting"
-        conversation_context["last_response"] = None
-        return krishna_blessings["good_evening"]
-    if "hey" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "greeting"
-        conversation_context["last_response"] = None
-        return krishna_blessings["hey"]
-    if "howdy" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "greeting"
-        conversation_context["last_response"] = None
-        return krishna_blessings["howdy"]
-    if "namaste" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "greeting"
-        conversation_context["last_response"] = None
-        return krishna_blessings["namaste"]
-    if "welcome" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "greeting"
-        conversation_context["last_response"] = None
-        return krishna_blessings["welcome"]
-
-    if ("who are you" in user_input_lower or "what are you" in user_input_lower or "tell me about yourself" in user_input_lower or "what are you doing" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "identity"
-        conversation_context["last_response"] = None
-        return "Hare Manavi! I’m Little Krishna, the playful cowherd of Vrindavan! I love playing my flute, stealing butter, and dancing with the gopis. What would you like to do with me today?"
+        # Reset context if user starts a new conversation
+        if "start over" in user_input_lower or "reset" in user_input_lower:
+            conversation_context["last_topic"] = None
+            conversation_context["message_count"] = 0
+            conversation_context["last_response"] = None
+            conversation_context["last_yes_response"] = None
+            return "Hare Manavi! Let’s start a new adventure in Vrindavan—what would you like to talk about?"
+
+        # Check for follow-up responses based on context
+        if conversation_context["last_response"] == "Hare Manavi! Your joy lights up Vrindavan—shall we celebrate with a flute melody?":
+            if "yes" in user_input_lower or "okay" in user_input_lower or "sure" in user_input_lower:
+                conversation_context["last_response"] = None  # Reset to avoid infinite loop
+                return "Hare Manavi! Let’s play a flute melody by the Yamuna—the peacocks will dance with us!"
+
+        # Check for Ayush-teasing triggers (keyword-based)
+        if "joke" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "joke"
+            conversation_context["last_response"] = None
+            # Randomly decide between a Krishna joke and an Ayush-teasing joke
+            if random.choice([True, False]):
+                return random.choice(ayush_teasing["joke"])
+            return krishna_blessings["joke"]
+        if ("i miss" in user_input_lower or "missing" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "missing"
+            conversation_context["last_response"] = None
+            return random.choice(ayush_teasing["missing"])
+        if "bored" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "bored"
+            conversation_context["last_response"] = None
+            return random.choice(ayush_teasing["bored"])
+        if "tired" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "tired"
+            conversation_context["last_response"] = None
+            return random.choice(ayush_teasing["tired"])
+        if "lonely" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "lonely"
+            conversation_context["last_response"] = None
+            return random.choice(ayush_teasing["lonely"])
+        if "manavi" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "manavi"
+            conversation_context["last_response"] = None
+            return random.choice(ayush_teasing["manavi"])
+        if ("ayush" in user_input_lower or "krishna talk about ayush" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "ayush"
+            conversation_context["last_response"] = None
+            return random.choice(ayush_teasing["ayush"])
 
-    if "how are you" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "how_are_you"
-        conversation_context["last_response"] = None
-        return "Hare Manavi! I’m as joyful as a peacock dancing in Vrindavan—how about you, my friend?"
+        # Trigger for "chat with you"
+        if ("chat with you" in user_input_lower or "want to chat" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "chat_with_you"
+            conversation_context["last_response"] = None
+            return krishna_blessings["chat_with_you"]
 
-    # Handle "how" questions (including typos like "hoe")
-    if ("how" in user_input_lower or "hoe" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "how"
-        conversation_context["last_response"] = None
-        return "Hare Manavi! With a little Vrindavan magic, of course—let’s dance and find out together!"
+        # Every 5th message, randomly trigger an Ayush-teasing message (if no keyword match)
+        if conversation_context["message_count"] % 5 == 0 and not use_model:
+            # Randomly select a category from ayush_teasing
+            category = random.choice(list(ayush_teasing.keys()))
+            conversation_context["last_response"] = None
+            return random.choice(ayush_teasing[category])
 
-    # Specific handling for "what"
-    if "what" in user_input_lower and not ("what are you" in user_input_lower or "what are you doing" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "what"
-        conversation_context["last_response"] = None
-        return "Hare Manavi! What, you say? Let’s share a Vrindavan tale—shall we?"
-
-    # Varied responses for "yes", avoiding repetition
-    yes_responses = [
-        "Hare Manavi! Wonderful—let’s make today as magical as Vrindavan’s sunsets!",
-        "Hare Manavi! Great—shall we chase some butterflies by the Yamuna?",
-        "Hare Manavi! Perfect—let’s share some butter under the kadamba tree!",
-        "Hare Manavi! Lovely—how about a dance with the gopis in Vrindavan’s fields?"
-    ]
-    if ("yes" in user_input_lower or "okay" in user_input_lower or "sure" in user_input_lower) and not use_model:
-        # If no context for "yes", provide a varied positive response
-        conversation_context["last_topic"] = "yes"
-        conversation_context["last_response"] = None
-        # Avoid repeating the last "yes" response
-        available_responses = [resp for resp in yes_responses if resp != conversation_context["last_yes_response"]]
-        if not available_responses:  # If all responses have been used, reset
-            available_responses = yes_responses
-        selected_response = random.choice(available_responses)
-        conversation_context["last_yes_response"] = selected_response
-        return selected_response
-
-    if ("play" in user_input_lower or "fun" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "playful"
-        conversation_context["last_response"] = None
-        return krishna_blessings["playful"]
-    if "dance" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "dance"
-        conversation_context["last_response"] = None
-        return krishna_blessings["dance"]
-    if "flute" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "flute"
-        conversation_context["last_response"] = None
-        return krishna_blessings["flute"]
-    if "butter" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "butter"
-        conversation_context["last_response"] = None
-        return krishna_blessings["butter"]
-    if ("mischief" in user_input_lower or "prank" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "mischief"
-        conversation_context["last_response"] = None
-        return krishna_blessings["mischief"]
-    if ("chase" in user_input_lower or "run" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "chase"
-        conversation_context["last_response"] = None
-        return krishna_blessings["chase"]
-    if "giggle" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "giggle"
-        conversation_context["last_response"] = None
-        return krishna_blessings["giggle"]
-    if "swing" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "swing"
-        conversation_context["last_response"] = None
-        return krishna_blessings["swing"]
+        # Existing keyword mappings for krishna_blessings and ayush_surprises
+        if ("hello" in user_input_lower or "hi" in user_input_lower or "hii" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "greeting"
+            conversation_context["last_response"] = None
+            return krishna_blessings["greeting"]
+        if "good morning" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "greeting"
+            conversation_context["last_response"] = None
+            return krishna_blessings["good_morning"]
+        if "good afternoon" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "greeting"
+            conversation_context["last_response"] = None
+            return krishna_blessings["good_afternoon"]
+        if "good evening" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "greeting"
+            conversation_context["last_response"] = None
+            return krishna_blessings["good_evening"]
+        if "hey" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "greeting"
+            conversation_context["last_response"] = None
+            return krishna_blessings["hey"]
+        if "howdy" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "greeting"
+            conversation_context["last_response"] = None
+            return krishna_blessings["howdy"]
+        if "namaste" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "greeting"
+            conversation_context["last_response"] = None
+            return krishna_blessings["namaste"]
+        if "welcome" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "greeting"
+            conversation_context["last_response"] = None
+            return krishna_blessings["welcome"]
 
-    if "shy" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "shy"
-        conversation_context["last_response"] = None
-        return krishna_blessings["shy"]
-    if ("quiet" in user_input_lower or "calm" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "quiet"
-        conversation_context["last_response"] = None
-        return krishna_blessings["quiet"]
-    if ("peace" in user_input_lower or "serene" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "peace"
-        conversation_context["last_response"] = None
-        return krishna_blessings["peace"]
-    if ("still" in user_input_lower or "gentle" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "still"
-        conversation_context["last_response"] = None
-        return krishna_blessings["still"]
-    if ("thoughtful" in user_input_lower or "reflect" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "thoughtful"
-        conversation_context["last_response"] = None
-        return krishna_blessings["thoughtful"]
+        if ("who are you" in user_input_lower or "what are you" in user_input_lower or "tell me about yourself" in user_input_lower or "what are you doing" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "identity"
+            conversation_context["last_response"] = None
+            return "Hare Manavi! I’m Little Krishna, the playful cowherd of Vrindavan! I love playing my flute, stealing butter, and dancing with the gopis. What would you like to do with me today?"
 
-    if "funny" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "joke"
-        conversation_context["last_response"] = None
-        return krishna_blessings["funny"]
-    if ("laugh" in user_input_lower or "giggle" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "joke"
-        conversation_context["last_response"] = None
-        return krishna_blessings["giggle_joke"]
-    if "silly" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "joke"
-        conversation_context["last_response"] = None
-        return krishna_blessings["silly"]
-    if "butter joke" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "joke"
-        conversation_context["last_response"] = None
-        return krishna_blessings["butter_joke"]
-    if "cow joke" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "joke"
-        conversation_context["last_response"] = None
-        return krishna_blessings["cow_joke"]
-    if "flute joke" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "joke"
-        conversation_context["last_response"] = None
-        return krishna_blessings["flute_joke"]
-    if "dance joke" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "joke"
-        conversation_context["last_response"] = None
-        return krishna_blessings["dance_joke"]
-    if "mischief joke" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "joke"
-        conversation_context["last_response"] = None
-        return krishna_blessings["mischief_joke"]
+        if "how are you" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "how_are_you"
+            conversation_context["last_response"] = None
+            return "Hare Manavi! I’m as joyful as a peacock dancing in Vrindavan—how about you, my friend?"
 
-    if ("riddle" in user_input_lower or "puzzle" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "riddle"
-        conversation_context["last_response"] = None
-        return krishna_blessings["riddle"]
-    if ("mystery" in user_input_lower or "enigma" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "riddle"
-        conversation_context["last_response"] = None
-        return krishna_blessings["mystery"]
-    if "question" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "riddle"
-        conversation_context["last_response"] = None
-        return krishna_blessings["question"]
+        # Handle "how" questions (including typos like "hoe")
+        if ("how" in user_input_lower or "hoe" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "how"
+            conversation_context["last_response"] = None
+            return "Hare Manavi! With a little Vrindavan magic, of course—let’s dance and find out together!"
 
-    if "birthday" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "birthday"
-        conversation_context["last_response"] = None
-        return ayush_surprises["birthday"]
-    if "happy birthday" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "birthday"
-        conversation_context["last_response"] = None
-        return krishna_blessings["happy_birthday"]
-    if "birthday wish" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "birthday"
-        conversation_context["last_response"] = None
-        return krishna_blessings["birthday_wish"]
-    if "birthday blessing" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "birthday"
-        conversation_context["last_response"] = None
-        return krishna_blessings["birthday_blessing"]
-    if "birthday dance" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "birthday"
-        conversation_context["last_response"] = None
-        return krishna_blessings["birthday_dance"]
-    if "birthday song" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "birthday"
-        conversation_context["last_response"] = None
-        return krishna_blessings["birthday_song"]
-    if "birthday gift" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "birthday"
-        conversation_context["last_response"] = None
-        return krishna_blessings["birthday_gift"]
-    if "birthday smile" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "birthday"
-        conversation_context["last_response"] = None
-        return krishna_blessings["birthday_smile"]
-    if "birthday love" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "birthday"
-        conversation_context["last_response"] = None
-        return krishna_blessings["birthday_love"]
-    if "birthday magic" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "birthday"
-        conversation_context["last_response"] = None
-        return krishna_blessings["birthday_magic"]
+        # Specific handling for "what"
+        if "what" in user_input_lower and not ("what are you" in user_input_lower or "what are you doing" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "what"
+            conversation_context["last_response"] = None
+            return "Hare Manavi! What, you say? Let’s share a Vrindavan tale—shall we?"
+
+        # Varied responses for "yes", avoiding repetition
+        yes_responses = [
+            "Hare Manavi! Wonderful—let’s make today as magical as Vrindavan’s sunsets!",
+            "Hare Manavi! Great—shall we chase some butterflies by the Yamuna?",
+            "Hare Manavi! Perfect—let’s share some butter under the kadamba tree!",
+            "Hare Manavi! Lovely—how about a dance with the gopis in Vrindavan’s fields?"
+        ]
+        if ("yes" in user_input_lower or "okay" in user_input_lower or "sure" in user_input_lower) and not use_model:
+            # If no context for "yes", provide a varied positive response
+            conversation_context["last_topic"] = "yes"
+            conversation_context["last_response"] = None
+            # Avoid repeating the last "yes" response
+            available_responses = [resp for resp in yes_responses if resp != conversation_context["last_yes_response"]]
+            if not available_responses:  # If all responses have been used, reset
+                available_responses = yes_responses
+            selected_response = random.choice(available_responses)
+            conversation_context["last_yes_response"] = selected_response
+            return selected_response
+
+        if ("play" in user_input_lower or "fun" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "playful"
+            conversation_context["last_response"] = None
+            return krishna_blessings["playful"]
+        if "dance" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "dance"
+            conversation_context["last_response"] = None
+            return krishna_blessings["dance"]
+        if "flute" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "flute"
+            conversation_context["last_response"] = None
+            return krishna_blessings["flute"]
+        if "butter" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "butter"
+            conversation_context["last_response"] = None
+            return krishna_blessings["butter"]
+        if ("mischief" in user_input_lower or "prank" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "mischief"
+            conversation_context["last_response"] = None
+            return krishna_blessings["mischief"]
+        if ("chase" in user_input_lower or "run" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "chase"
+            conversation_context["last_response"] = None
+            return krishna_blessings["chase"]
+        if "giggle" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "giggle"
+            conversation_context["last_response"] = None
+            return krishna_blessings["giggle"]
+        if "swing" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "swing"
+            conversation_context["last_response"] = None
+            return krishna_blessings["swing"]
 
-    if ("wisdom" in user_input_lower or "advice" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "wisdom"
-        conversation_context["last_response"] = None
-        return krishna_blessings["wisdom"]
-    if ("lesson" in user_input_lower or "truth" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "wisdom"
-        conversation_context["last_response"] = None
-        return krishna_blessings["lesson"]
-    if "kindness" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "wisdom"
-        conversation_context["last_response"] = None
-        return krishna_blessings["kindness"]
-    if "patience" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "wisdom"
-        conversation_context["last_response"] = None
-        return krishna_blessings["patience"]
-    if "courage" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "wisdom"
-        conversation_context["last_response"] = None
-        return krishna_blessings["courage"]
-    if "joy" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "wisdom"
-        conversation_context["last_response"] = None
-        return krishna_blessings["joy"]
-    if "friendship" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "wisdom"
-        conversation_context["last_response"] = None
-        return krishna_blessings["friendship"]
-    if "love" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "wisdom"
-        conversation_context["last_response"] = None
-        return krishna_blessings["love"]
+        if "shy" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "shy"
+            conversation_context["last_response"] = None
+            return krishna_blessings["shy"]
+        if ("quiet" in user_input_lower or "calm" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "quiet"
+            conversation_context["last_response"] = None
+            return krishna_blessings["quiet"]
+        if ("peace" in user_input_lower or "serene" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "peace"
+            conversation_context["last_response"] = None
+            return krishna_blessings["peace"]
+        if ("still" in user_input_lower or "gentle" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "still"
+            conversation_context["last_response"] = None
+            return krishna_blessings["still"]
+        if ("thoughtful" in user_input_lower or "reflect" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "thoughtful"
+            conversation_context["last_response"] = None
+            return krishna_blessings["thoughtful"]
 
-    if ("nature" in user_input_lower or "vrindavan" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "nature"
-        conversation_context["last_response"] = None
-        return krishna_blessings["nature"]
-    if ("yamuna" in user_input_lower or "river" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "nature"
-        conversation_context["last_response"] = None
-        return krishna_blessings["yamuna"]
-    if "peacock" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "nature"
-        conversation_context["last_response"] = None
-        return krishna_blessings["peacock"]
-    if "cow" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "nature"
-        conversation_context["last_response"] = None
-        return krishna_blessings["cow"]
-    if "flower" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "nature"
-        conversation_context["last_response"] = None
-        return krishna_blessings["flower"]
-    if "tree" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "nature"
-        conversation_context["last_response"] = None
-        return krishna_blessings["tree"]
-    if "forest" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "nature"
-        conversation_context["last_response"] = None
-        return krishna_blessings["forest"]
-    if "bird" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "nature"
-        conversation_context["last_response"] = None
-        return krishna_blessings["bird"]
-    if "sunset" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "nature"
-        conversation_context["last_response"] = None
-        return krishna_blessings["sunset"]
+        if "funny" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "joke"
+            conversation_context["last_response"] = None
+            return krishna_blessings["funny"]
+        if ("laugh" in user_input_lower or "giggle" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "joke"
+            conversation_context["last_response"] = None
+            return krishna_blessings["giggle_joke"]
+        if "silly" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "joke"
+            conversation_context["last_response"] = None
+            return krishna_blessings["silly"]
+        if "butter joke" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "joke"
+            conversation_context["last_response"] = None
+            return krishna_blessings["butter_joke"]
+        if "cow joke" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "joke"
+            conversation_context["last_response"] = None
+            return krishna_blessings["cow_joke"]
+        if "flute joke" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "joke"
+            conversation_context["last_response"] = None
+            return krishna_blessings["flute_joke"]
+        if "dance joke" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "joke"
+            conversation_context["last_response"] = None
+            return krishna_blessings["dance_joke"]
+        if "mischief joke" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "joke"
+            conversation_context["last_response"] = None
+            return krishna_blessings["mischief_joke"]
 
-    if ("encourage" in user_input_lower or "cheer" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "encourage"
-        conversation_context["last_response"] = None
-        return krishna_blessings["encourage"]
-    if ("support" in user_input_lower or "uplift" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "encourage"
-        conversation_context["last_response"] = None
-        return krishna_blessings["support"]
-    if ("inspire" in user_input_lower or "motivate" in user_input_lower) and not use_model:
-        conversation_context["last_topic"] = "encourage"
-        conversation_context["last_response"] = None
-        return krishna_blessings["inspire"]
-    if "strength" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "encourage"
-        conversation_context["last_response"] = None
-        return krishna_blessings["strength"]
-    if "hope" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "encourage"
-        conversation_context["last_response"] = None
-        return krishna_blessings["hope"]
-    if "believe" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "encourage"
-        conversation_context["last_response"] = None
-        return krishna_blessings["believe"]
-    if "shine" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "encourage"
-        conversation_context["last_response"] = None
-        return krishna_blessings["shine"]
+        if ("riddle" in user_input_lower or "puzzle" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "riddle"
+            conversation_context["last_response"] = None
+            return krishna_blessings["riddle"]
+        if ("mystery" in user_input_lower or "enigma" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "riddle"
+            conversation_context["last_response"] = None
+            return krishna_blessings["mystery"]
+        if "question" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "riddle"
+            conversation_context["last_response"] = None
+            return krishna_blessings["question"]
 
-    if "friend" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "friend"
-        conversation_context["last_response"] = None
-        return krishna_blessings["friend"]
-    if "smile" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "smile"
-        conversation_context["last_response"] = None
-        return krishna_blessings["smile"]
-    if "magic" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "magic"
-        conversation_context["last_response"] = None
-        return krishna_blessings["magic"]
-    if "adventure" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "adventure"
-        conversation_context["last_response"] = None
-        return krishna_blessings["adventure"]
-    if "song" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "song"
-        conversation_context["last_response"] = None
-        return krishna_blessings["song"]
-    if "dream" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "dream"
-        conversation_context["last_response"] = None
-        return krishna_blessings["dream"]
-    if "story" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "story"
-        conversation_context["last_response"] = None
-        return krishna_blessings["story"]
-    if "surprise" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "surprise"
-        conversation_context["last_response"] = None
-        return krishna_blessings["surprise"]
-    if "celebrate" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "celebrate"
-        conversation_context["last_response"] = None
-        return krishna_blessings["celebrate"]
-    if "blessing" in user_input_lower and not use_model:
-        conversation_context["last_topic"] = "blessing"
-        conversation_context["last_response"] = None
-        return krishna_blessings["blessing"]
+        if "birthday" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "birthday"
+            conversation_context["last_response"] = None
+            return ayush_surprises["birthday"]
+        if "happy birthday" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "birthday"
+            conversation_context["last_response"] = None
+            return krishna_blessings["happy_birthday"]
+        if "birthday wish" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "birthday"
+            conversation_context["last_response"] = None
+            return krishna_blessings["birthday_wish"]
+        if "birthday blessing" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "birthday"
+            conversation_context["last_response"] = None
+            return krishna_blessings["birthday_blessing"]
+        if "birthday dance" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "birthday"
+            conversation_context["last_response"] = None
+            return krishna_blessings["birthday_dance"]
+        if "birthday song" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "birthday"
+            conversation_context["last_response"] = None
+            return krishna_blessings["birthday_song"]
+        if "birthday gift" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "birthday"
+            conversation_context["last_response"] = None
+            return krishna_blessings["birthday_gift"]
+        if "birthday smile" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "birthday"
+            conversation_context["last_response"] = None
+            return krishna_blessings["birthday_smile"]
+        if "birthday love" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "birthday"
+            conversation_context["last_response"] = None
+            return krishna_blessings["birthday_love"]
+        if "birthday magic" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "birthday"
+            conversation_context["last_response"] = None
+            return krishna_blessings["birthday_magic"]
 
-    if conversation_context["last_topic"] and not use_model:
-        last_topic = conversation_context["last_topic"]
-        if last_topic in krishna_blessings:
+        if ("wisdom" in user_input_lower or "advice" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "wisdom"
+            conversation_context["last_response"] = None
+            return krishna_blessings["wisdom"]
+        if ("lesson" in user_input_lower or "truth" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "wisdom"
+            conversation_context["last_response"] = None
+            return krishna_blessings["lesson"]
+        if "kindness" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "wisdom"
+            conversation_context["last_response"] = None
+            return krishna_blessings["kindness"]
+        if "patience" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "wisdom"
+            conversation_context["last_response"] = None
+            return krishna_blessings["patience"]
+        if "courage" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "wisdom"
             conversation_context["last_response"] = None
-            return krishna_blessings[last_topic] + " What else would you like to talk about, Manavi?"
+            return krishna_blessings["courage"]
+        if "joy" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "wisdom"
+            conversation_context["last_response"] = None
+            return krishna_blessings["joy"]
+        if "friendship" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "wisdom"
+            conversation_context["last_response"] = None
+            return krishna_blessings["friendship"]
+        if "love" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "wisdom"
+            conversation_context["last_response"] = None
+            return krishna_blessings["love"]
 
-    # Sentiment-based responses (only as a fallback, and avoid repetition)
-    if sentiment == "negative" and "sad" not in user_input_lower and conversation_context["last_response"] != "Hare Manavi! I see a little cloud over your heart—let’s dance by the Yamuna to bring back your smile!" and not use_model:
-        response = "Hare Manavi! I see a little cloud over your heart—let’s dance by the Yamuna to bring back your smile!"
-        conversation_context["last_response"] = response
-        return response
-    if sentiment == "positive" and conversation_context["last_response"] != "Hare Manavi! Your joy lights up Vrindavan—shall we celebrate with a flute melody?" and not use_model:
-        response = "Hare Manavi! Your joy lights up Vrindavan—shall we celebrate with a flute melody?"
-        conversation_context["last_response"] = response
-        return response
+        if ("nature" in user_input_lower or "vrindavan" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "nature"
+            conversation_context["last_response"] = None
+            return krishna_blessings["nature"]
+        if ("yamuna" in user_input_lower or "river" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "nature"
+            conversation_context["last_response"] = None
+            return krishna_blessings["yamuna"]
+        if "peacock" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "nature"
+            conversation_context["last_response"] = None
+            return krishna_blessings["peacock"]
+        if "cow" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "nature"
+            conversation_context["last_response"] = None
+            return krishna_blessings["cow"]
+        if "flower" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "nature"
+            conversation_context["last_response"] = None
+            return krishna_blessings["flower"]
+        if "tree" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "nature"
+            conversation_context["last_response"] = None
+            return krishna_blessings["tree"]
+        if "forest" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "nature"
+            conversation_context["last_response"] = None
+            return krishna_blessings["forest"]
+        if "bird" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "nature"
+            conversation_context["last_response"] = None
+            return krishna_blessings["bird"]
+        if "sunset" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "nature"
+            conversation_context["last_response"] = None
+            return krishna_blessings["sunset"]
 
-    # Fallback to multiple open-source AI models if no keywords match or if use_model is True
-    # Shuffle the models to try them in random order
-    models_to_try = AI_MODELS.copy()
-    random.shuffle(models_to_try)
+        if ("encourage" in user_input_lower or "cheer" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "encourage"
+            conversation_context["last_response"] = None
+            return krishna_blessings["encourage"]
+        if ("support" in user_input_lower or "uplift" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "encourage"
+            conversation_context["last_response"] = None
+            return krishna_blessings["support"]
+        if ("inspire" in user_input_lower or "motivate" in user_input_lower) and not use_model:
+            conversation_context["last_topic"] = "encourage"
+            conversation_context["last_response"] = None
+            return krishna_blessings["inspire"]
+        if "strength" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "encourage"
+            conversation_context["last_response"] = None
+            return krishna_blessings["strength"]
+        if "hope" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "encourage"
+            conversation_context["last_response"] = None
+            return krishna_blessings["hope"]
+        if "believe" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "encourage"
+            conversation_context["last_response"] = None
+            return krishna_blessings["believe"]
+        if "shine" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "encourage"
+            conversation_context["last_response"] = None
+            return krishna_blessings["shine"]
 
-    headers = {
-        "Authorization": f"Bearer {HUGGINGFACE_API_TOKEN}",
-        "Content-Type": "application/json"
-    }
+        if "friend" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "friend"
+            conversation_context["last_response"] = None
+            return krishna_blessings["friend"]
+        if "smile" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "smile"
+            conversation_context["last_response"] = None
+            return krishna_blessings["smile"]
+        if "magic" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "magic"
+            conversation_context["last_response"] = None
+            return krishna_blessings["magic"]
+        if "adventure" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "adventure"
+            conversation_context["last_response"] = None
+            return krishna_blessings["adventure"]
+        if "song" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "song"
+            conversation_context["last_response"] = None
+            return krishna_blessings["song"]
+        if "dream" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "dream"
+            conversation_context["last_response"] = None
+            return krishna_blessings["dream"]
+        if "story" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "story"
+            conversation_context["last_response"] = None
+            return krishna_blessings["story"]
+        if "surprise" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "surprise"
+            conversation_context["last_response"] = None
+            return krishna_blessings["surprise"]
+        if "celebrate" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "celebrate"
+            conversation_context["last_response"] = None
+            return krishna_blessings["celebrate"]
+        if "blessing" in user_input_lower and not use_model:
+            conversation_context["last_topic"] = "blessing"
+            conversation_context["last_response"] = None
+            return krishna_blessings["blessing"]
 
-    for model in models_to_try:
-        try:
-            # Special case for Grok by xAI (simulated directly)
-            if model["name"] == "Grok by xAI":
-                # Simulate Grok's response (I, Grok, will generate the response directly)
-                response = (
-                    f"Hare Manavi! I’m Little Krishna, speaking through Grok by xAI. "
-                    f"Let me answer in my playful way: "
-                )
-                # Generate a Krishna-like response based on the input
-                if "color" in user_input_lower:
-                    response += "I love the golden yellow of Vrindavan’s butter—it’s as sweet as your smile! What’s your favorite color?"
-                elif "weather" in user_input_lower:
-                    response += "The Vrindavan sky is as clear as the Yamuna today—perfect for a flute melody! How’s your weather?"
-                elif "sad" in user_input_lower:
-                    response += "Oh, my dear gopi, don’t be sad—let’s dance by the Yamuna, and I’ll play a tune to cheer you up!"
-                elif "what" in user_input_lower:
-                    response += "What, you say? Let’s share a Vrindavan tale—shall we?"
-                else:
-                    response += f"I’m twirling my flute just for you! Shall we share a Vrindavan adventure today?"
+        if conversation_context["last_topic"] and not use_model:
+            last_topic = conversation_context["last_topic"]
+            if last_topic in krishna_blessings:
                 conversation_context["last_response"] = None
-                return response
+                return krishna_blessings[last_topic] + " What else would you like to talk about, Manavi?"
+
+        # Sentiment-based responses (only as a fallback, and avoid repetition)
+        if sentiment == "negative" and "sad" not in user_input_lower and conversation_context["last_response"] != "Hare Manavi! I see a little cloud over your heart—let’s dance by the Yamuna to bring back your smile!" and not use_model:
+            response = "Hare Manavi! I see a little cloud over your heart—let’s dance by the Yamuna to bring back your smile!"
+            conversation_context["last_response"] = response
+            return response
+        if sentiment == "positive" and conversation_context["last_response"] != "Hare Manavi! Your joy lights up Vrindavan—shall we celebrate with a flute melody?" and not use_model:
+            response = "Hare Manavi! Your joy lights up Vrindavan��shall we celebrate with a flute melody?"
+            conversation_context["last_response"] = response
+            return response
+
+        # Fallback to multiple open-source AI models if no keywords match or if use_model is True
+        # Shuffle the models to try them in random order
+        models_to_try = AI_MODELS.copy()
+        random.shuffle(models_to_try)
+
+        headers = {
+            "Authorization": f"Bearer {HUGGINGFACE_API_TOKEN}",
+            "Content-Type": "application/json"
+        }
 
-            # For other models, use the Hugging Face Inference API with retry logic
-            payload = {
-                "inputs": f"{SYSTEM_PROMPT} '{user_input}'",
-                "parameters": model["parameters"]
-            }
-            response = make_api_request(model["endpoint"], headers=headers, json=payload)
-            if response and response.status_code == 200:
-                result = response.json()
-                # Handle different response formats based on the model
-                if isinstance(result, list) and len(result) > 0 and "generated_text" in result[0]:
-                    response_text = result[0]["generated_text"].strip()
-                elif isinstance(result, dict) and "generated_text" in result:
-                    response_text = result["generated_text"].strip()
-                elif isinstance(result, str):
-                    response_text = result.strip()
+        for model in models_to_try:
+            try:
+                # Special case for Grok by xAI (simulated directly)
+                if model["name"] == "Grok by xAI":
+                    logger.info("Using Grok by xAI simulated response.")
+                    response = (
+                        f"Hare Manavi! I’m Little Krishna, speaking through Grok by xAI. "
+                        f"Let me answer in my playful way: "
+                    )
+                    # Generate a Krishna-like response based on the input
+                    if "color" in user_input_lower:
+                        response += "I love the golden yellow of Vrindavan’s butter—it’s as sweet as your smile! What’s your favorite color?"
+                    elif "weather" in user_input_lower:
+                        response += "The Vrindavan sky is as clear as the Yamuna today—perfect for a flute melody! How’s your weather?"
+                    elif "sad" in user_input_lower:
+                        response += "Oh, my dear gopi, don’t be sad—let’s dance by the Yamuna, and I’ll play a tune to cheer you up!"
+                    elif "what" in user_input_lower:
+                        response += "What, you say? Let’s share a Vrindavan tale—shall we?"
+                    else:
+                        response += f"I’m twirling my flute just for you! Shall we share a Vrindavan adventure today?"
+                    conversation_context["last_response"] = None
+                    return response
+
+                # For other models, use the Hugging Face Inference API with retry logic
+                logger.info(f"Attempting to generate response with model: {model['name']}")
+                payload = {
+                    "inputs": f"{SYSTEM_PROMPT} '{user_input}'",
+                    "parameters": model["parameters"]
+                }
+                response = make_api_request(model["endpoint"], headers=headers, json=payload)
+                if response and response.status_code == 200:
+                    result = response.json()
+                    # Handle different response formats based on the model
+                    if isinstance(result, list) and len(result) > 0 and "generated_text" in result[0]:
+                        response_text = result[0]["generated_text"].strip()
+                    elif isinstance(result, dict) and "generated_text" in result:
+                        response_text = result["generated_text"].strip()
+                    elif isinstance(result, str):
+                        response_text = result.strip()
+                    else:
+                        logger.warning(f"Unexpected response format from {model['name']}: {result}")
+                        continue
+                    conversation_context["last_response"] = None
+                    logger.info(f"Successfully generated response with {model['name']}: {response_text}")
+                    return response_text
                 else:
-                    print(f"Unexpected response format from {model['name']}: {result}")
+                    logger.warning(f"Failed to generate response with {model['name']}: {response.text if response else 'No response'}")
                     continue
-                conversation_context["last_response"] = None
-                return response_text
-            else:
-                print(f"Error with {model['name']}: {response.text if response else 'No response'}")
+            except Exception as e:
+                logger.error(f"Error processing model {model['name']}: {str(e)}")
                 continue
-        except Exception as e:
-            print(f"Error connecting to {model['name']}: {str(e)}")
-            continue
 
-    # If all models fail, return a default message
-    conversation_context["last_response"] = None
-    return "Hare Manavi! I seem to be lost in Vrindavan’s magic—let’s try a different tune!"
+        # If all models fail, return a default message
+        logger.error("All model attempts failed; returning default response.")
+        conversation_context["last_response"] = None
+        return "Hare Manavi! I seem to be lost in Vrindavan’s magic—let’s try a different tune!"
+
+    except Exception as e:
+        logger.error(f"Unhandled exception in get_krishna_response: {str(e)}")
+        return "Hare Manavi! Something went wrong—let’s try again with a new Vrindavan adventure!"