Create aap.pyyy

aap.pyyy

@@ -0,0 +1,1230 @@
+import streamlit as st
+import requests
+import os
+from datetime import datetime, timedelta
+import re
+import hashlib
+import json
+
+# ===============================
+# HUGGING FACE API KEY HANDLING
+# ===============================
+# Try to get API key from Hugging Face secrets first
+try:
+    # For Hugging Face Spaces
+    from huggingface_hub import HfFolder
+    api_key = HfFolder.get_token()
+    if not api_key:
+        # Try environment variable
+        api_key = os.environ.get("DEEPSEEK_API_KEY", "")
+except ImportError:
+    # huggingface_hub not installed
+    api_key = os.environ.get("DEEPSEEK_API_KEY", "")
+except:
+    # Any other error
+    api_key = os.environ.get("DEEPSEEK_API_KEY", "")
+
+# ===============================
+# HUGGING FACE COMPATIBLE CACHE CLASS
+# ===============================
+class HybridCache:
+    def __init__(self, ttl_hours=24, max_entries=100):
+        """
+        In-memory only cache for Hugging Face Spaces
+        - No file system access needed
+        - Works within session only
+        """
+        self.ttl_hours = ttl_hours
+        self.max_entries = max_entries
+        self.cache = {}  # Simple dictionary for in-memory storage
+        
+    def get(self, cache_key):
+        """Get cached answer if not expired"""
+        if cache_key in self.cache:
+            entry = self.cache[cache_key]
+            created_at = entry.get('created_at')
+            
+            if isinstance(created_at, str):
+                created_at = datetime.fromisoformat(created_at)
+            
+            # Check TTL (in hours for Hugging Face)
+            if created_at and (datetime.now() - created_at).seconds < (self.ttl_hours * 3600):
+                # Update access time
+                entry['last_accessed'] = datetime.now().isoformat()
+                entry['access_count'] = entry.get('access_count', 0) + 1
+                return entry
+            else:
+                # Remove expired entry
+                del self.cache[cache_key]
+        
+        return None
+    
+    def set(self, cache_key, data):
+        """Add or update cache entry"""
+        data['created_at'] = datetime.now().isoformat()
+        data['last_accessed'] = data['created_at']
+        data['access_count'] = 1
+        
+        self.cache[cache_key] = data
+        
+        # Enforce max entries limit
+        if len(self.cache) > self.max_entries:
+            # Remove oldest entries (by access time)
+            sorted_keys = sorted(
+                self.cache.keys(),
+                key=lambda k: self.cache[k].get('last_accessed', ''),
+                reverse=True
+            )
+            for key in sorted_keys[self.max_entries:]:
+                del self.cache[key]
+    
+    def clear_expired(self):
+        """Manually clear expired entries"""
+        current_time = datetime.now()
+        expired_keys = []
+        
+        for key, entry in self.cache.items():
+            created_at = entry.get('created_at')
+            if isinstance(created_at, str):
+                created_at = datetime.fromisoformat(created_at)
+            
+            if created_at and (current_time - created_at).seconds >= (self.ttl_hours * 3600):
+                expired_keys.append(key)
+        
+        for key in expired_keys:
+            del self.cache[key]
+        
+        return len(expired_keys)
+    
+    def clear_all(self):
+        """Clear all cache entries"""
+        self.cache = {}
+    
+    def get_stats(self):
+        """Get cache statistics"""
+        total_saved_tokens = sum(entry.get('tokens', 0) for entry in self.cache.values())
+        total_access_count = sum(entry.get('access_count', 0) for entry in self.cache.values())
+        avg_age_hours = 0
+        
+        if self.cache:
+            current_time = datetime.now()
+            ages = []
+            for entry in self.cache.values():
+                created_at = entry.get('created_at')
+                if isinstance(created_at, str):
+                    created_at = datetime.fromisoformat(created_at)
+                if created_at:
+                    ages.append((current_time - created_at).seconds / 3600)  # in hours
+            avg_age_hours = sum(ages) / len(ages) if ages else 0
+        
+        return {
+            'total_entries': len(self.cache),
+            'total_saved_tokens': total_saved_tokens,
+            'total_access_count': total_access_count,
+            'average_age_hours': round(avg_age_hours, 1),
+            'ttl_hours': self.ttl_hours,
+            'max_entries': self.max_entries,
+            'storage_mode': 'In-Memory (Hugging Face)'
+        }
+
+# Page config - must be first Streamlit command
+st.set_page_config(
+    page_title="SEBA দশম শ্ৰেণীৰ AI টিউটাৰ",
+    page_icon="🎓",
+    layout="wide",
+    initial_sidebar_state="collapsed"
+)
+
+# Simplified CSS with reduced spacing (50% of original)
+st.markdown("""
+<style>
+    /* Assamese-friendly fonts */
+    @import url('https://fonts.googleapis.com/css2?family=Noto+Sans+Bengali:wght@400;500;600;700;800&family=Hind+Siliguri:wght@300;400;500;600;700&display=swap');
+    
+    * {
+        font-family: 'Noto Sans Bengali', 'Hind Siliguri', 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+    }
+
+    /* Reduced spacing header */
+    .header-container {
+        background: linear-gradient(135deg, #0d47a1 0%, #1565c0 50%, #1976d2 100%);
+        padding: 1.25rem;
+        border-radius: 15px;
+        margin-bottom: 1rem;
+        color: white;
+        position: relative;
+        overflow: hidden;
+        border: 1px solid rgba(255,255,255,0.1);
+        box-shadow: 0 5px 15px rgba(13,71,161,0.2);
+    }
+
+    /* The top rainbow line */
+    .header-container::before {
+        content: '';
+        position: absolute;
+        top: 0;
+        left: 0;
+        right: 0;
+        height: 3px;
+        background: linear-gradient(90deg, #FF5722, #FF9800, #4CAF50);
+    }
+
+    /* Header text */
+    .header-container h1 {
+        color: #ffffff;
+        font-size: 1.5rem;
+        font-weight: 800;
+        text-shadow: 0px 1px 3px rgba(0,0,0,0.5);
+        margin: 0;
+        line-height: 1.2;
+    }
+
+    .header-container p {
+        color: #f6f9ff;
+        font-weight: 600;
+        font-size: 0.95rem;
+        opacity: 1 !important;
+        text-shadow: 0px 1px 2px rgba(0,0,0,0.4);
+        margin-top: .2rem;
+    }
+
+    .subject-card {
+        background: linear-gradient(145deg, #ffffff 0%, #f0f7ff 100%);
+        padding: 0.75rem;
+        border-radius: 10px;
+        box-shadow: 0 3px 8px rgba(0, 0, 0, 0.08);
+        border-left: 4px solid #2196F3;
+        margin: 0.5rem 0;
+        transition: all 0.3s ease;
+        border: 1px solid #e3f2fd;
+    }
+    
+    .subject-card:hover {
+        transform: translateY(-3px);
+        box-shadow: 0 5px 12px rgba(33, 150, 243, 0.15);
+    }
+    
+    .answer-box {
+        background: linear-gradient(145deg, #f8fdff 0%, #ffffff 100%);
+        padding: 1rem;
+        border-radius: 10px;
+        border: 1px solid #e1f5fe;
+        margin: 0.75rem 0;
+        box-shadow: 0 3px 8px rgba(0, 0, 0, 0.05);
+        position: relative;
+    }
+    
+    .stButton > button {
+        background: linear-gradient(135deg, #FF5722 0%, #FF9800 100%);
+        color: white;
+        border: none;
+        padding: 0.4rem 1rem;
+        border-radius: 8px;
+        font-weight: 600;
+        font-size: 0.9rem;
+        transition: all 0.3s;
+        box-shadow: 0 2px 6px rgba(255, 87, 34, 0.3);
+    }
+    
+    .stButton > button:hover {
+        transform: translateY(-1px);
+        box-shadow: 0 3px 9px rgba(255, 87, 34, 0.4);
+    }
+    
+    .sidebar-section {
+        background: linear-gradient(145deg, #f8f9fa 0%, #e3f2fd 100%);
+        padding: 0.75rem;
+        border-radius: 10px;
+        margin-bottom: 0.75rem;
+        border: 1px solid #bbdefb;
+        box-shadow: 0 2px 6px rgba(0, 0, 0, 0.05);
+    }
+    
+    .assamese-highlight {
+    background: linear-gradient(120deg, #FFF176 0%, #FFEB3B 100%);
+    background-repeat: no-repeat;
+    background-size: 100% 0.3em;
+    background-position: 0 90%;
+    padding: 0.1rem 0.2rem;
+    font-weight: 700;
+    color: #FF6F00;
+}
+    
+    .assamese-text {
+        font-family: 'Noto Sans Bengali', sans-serif;
+        font-weight: 500;
+        color: #0d47a1;
+        line-height: 1.4;
+    }
+    
+    .assamese-title {
+        font-family: 'Noto Sans Bengali', sans-serif;
+        font-weight: 700;
+        color: #1565c0;
+    }
+    
+    /* Chat bubble styling */
+    .user-bubble {
+        background: linear-gradient(135deg, #2196F3 0%, #0d47a1 100%) !important;
+        color: white;
+        padding: 0.5rem 0.75rem;
+        border-radius: 12px 12px 0 12px;
+        max-width: 80%;
+        box-shadow: 0 2px 6px rgba(33, 150, 243, 0.2);
+        margin-left: auto;
+    }
+    
+    .ai-bubble {
+        background: linear-gradient(135deg, #f5f5f5 0%, #ffffff 100%) !important;
+        padding: 0.75rem;
+        border-radius: 12px 12px 12px 0;
+        border: 1px solid #e0e0e0;
+        box-shadow: 0 2px 6px rgba(0,0,0,0.05);
+    }
+    
+    /* Chat container */
+    .chat-container {
+        margin-bottom: 1rem;
+    }
+    
+    .chat-message {
+        margin-bottom: 0.75rem;
+        animation: fadeIn 0.3s ease-in;
+    }
+    
+    @keyframes fadeIn {
+        from { opacity: 0; transform: translateY(5px); }
+        to { opacity: 1; transform: translateY(0); }
+    }
+    
+    /* LaTeX equation styling */
+    .katex {
+        font-size: 1em !important;
+        padding: 0.1rem 0.25rem;
+        background: rgba(33, 150, 243, 0.1);
+        border-radius: 3px;
+        margin: 0.1rem 0;
+    }
+    
+    /* Control panel styling */
+    .control-panel {
+        background: linear-gradient(145deg, #f8f9fa 0%, #e3f2fd 100%);
+        padding: 1rem;
+        border-radius: 15px;
+        margin: 1rem 0;
+        border: 1px solid #bbdefb;
+        box-shadow: 0 4px 12px rgba(0, 0, 0, 0.08);
+    }
+    
+    /* Streaming text animation */
+    .streaming-text {
+        display: inline-block;
+    }
+    
+    .streaming-text::after {
+        content: '▋';
+        animation: cursor-blink 1s infinite;
+        font-weight: bold;
+        color: #2196F3;
+    }
+    
+    @keyframes cursor-blink {
+        0%, 100% { opacity: 1; }
+        50% { opacity: 0; }
+    }
+    
+    /* Progress indicator */
+    .progress-indicator {
+        display: flex;
+        align-items: center;
+        justify-content: center;
+        gap: 0.5rem;
+        color: #0d47a1;
+        font-weight: 600;
+        padding: 0.5rem;
+    }
+    
+    .thinking-dots {
+        display: flex;
+        gap: 0.2rem;
+    }
+    
+    .thinking-dots span {
+        width: 0.4rem;
+        height: 0.4rem;
+        border-radius: 50%;
+        background: #2196F3;
+        animation: thinking 1.4s infinite ease-in-out;
+    }
+    
+    .thinking-dots span:nth-child(1) { animation-delay: -0.32s; }
+    .thinking-dots span:nth-child(2) { animation-delay: -0.16s; }
+    .thinking-dots span:nth-child(3) { animation-delay: 0s; }
+    
+    @keyframes thinking {
+        0%, 80%, 100% { transform: scale(0); }
+        40% { transform: scale(1); }
+    }
+    
+    /* Cache indicator styling */
+    .cache-badge {
+        background: linear-gradient(135deg, #4CAF50 0%, #2E7D32 100%);
+        color: white;
+        padding: 0.2rem 0.5rem;
+        border-radius: 12px;
+        font-size: 0.75rem;
+        font-weight: 600;
+        display: inline-flex;
+        align-items: center;
+        gap: 0.2rem;
+    }
+    
+    /* Responsive adjustments */
+    @media (max-width: 768px) {
+        .header-container {
+            padding: 0.75rem;
+        }
+        .subject-card {
+            padding: 0.5rem;
+        }
+        .user-bubble, .ai-bubble {
+            max-width: 90%;
+        }
+        .control-panel {
+            padding: 0.75rem;
+        }
+    }
+</style>
+""", unsafe_allow_html=True)
+
+# ===============================
+# SEBA CURRICULUM DATA
+# ===============================
+SEBA_CURRICULUM = {
+    "📐 গণিত (Mathematics)": {
+        "অধ্যায় ১": "বাস্তৱ সংখ্যা (Real Numbers)",
+        "অধ্যায় ২": "বহুপদ (Polynomials)",
+        "অধ্যায় ৩": "দ্বিঘাত সমীকৰণ (Quadratic Equations)",
+        "অধ্যায় ৪": "সামান্তৰিক শ্রেণী (Arithmetic Progressions)",
+        "অধ্যায় ৫": "ত্ৰিভুজ (Triangles)",
+        "অধ্যায় ৬": "ত্রিকোণমিতি (Trigonometry)",
+        "অধ্যায় ৭": "বৃত্ত (Circles)",
+        "অধ্যায় ৮": "স্থানাঙ্ক জ্যামিতি (Coordinate Geometry)",
+        "অধ্যায় ৯": "ক্ষেত্রফল আৰু আয়তন (Areas and Volumes)",
+        "অধ্যায় ১০": "পৰিসংখ্যা (Statistics)",
+        "অধ্যায় ১১": "সম্ভাৱিতা (Probability)"
+    },
+    "🔬 বিজ্ঞান (Science)": {
+        "অধ্যায় ১": "ৰাসায়নিক বিক্রিয়া আৰু সমীকৰণ",
+        "অধ্যায় ২": "এছিড, ক্ষাৰক আৰু লৱণ",
+        "অধ্যায় ৩": "ধাতু আৰু অধাতু",
+        "অধ্যায় ৪": "কার্বন আৰু তাৰ যৌগ",
+        "অধ্যায় ৫": "পৰ্যাবৃত্ত শ্রেণীবিভাজন",
+        "অধ্যায় ৬": "জীৱন প্ৰক্ৰিয়া",
+        "অধ্যায় ৭": "নিয়ন্ত্ৰণ আৰু সমন্বয়",
+        "অধ্যায় ৮": "জীৱই কেনেদৰে বংশবিস্তাৰ কৰে",
+        "অধ্যায় ৯": "আনুভূমিক আৰু ঊর্ধ্বমুখী বংশগতি",
+        "অধ্যায় ১০": "পোহৰ-প্ৰতিফলন আৰু প্ৰতিসৰণ",
+        "অধ্যায় ১১": "মানুহৰ চকু আৰু বৰ্ণিল পৃথিৱী",
+        "অধ্যায় ১২": "বিদ্যুৎ",
+        "অধ্যায় ১৩": "বিদ্যুৎ-চুম্বকীয় প্ৰভাৱ",
+        "অধ্যায় ১৪": "শক্তিৰ উৎসসমূহ",
+        "অধ্যায় ১৫": "আমাৰ পৰিৱেশ",
+        "অধ্যায় ১৬": "প্রাকৃতিক সম্পদৰ ব্যৱস্থাপনা"
+    },
+    "🌍 সমাজ বিজ্ঞান (Social Science)": {
+        "অধ্যায় ১": "ইউৰোপত ৰাষ্ট্ৰবাদৰ উত্থান",
+        "অধ্যায় ২": "ভাৰতীয় জাতীয়তাবাদৰ উত্থান",
+        "অধ্যায় ৩": "ভূগোল-প্রাকৃতিক আৰু মানৱ",
+        "অধ্যায় ৪": "অৰ্থনীতি-উন্নয়ন",
+        "অধ্যায় ৫": "লোকসাধাৰণৰ সংস্কৃতি আৰু জাতীয়তাবাদ",
+        "অধ্যায় ৬": "উদ্যোগ",
+        "অধ্যায় ৭": "অৰ্থনৈতিক অৱস্থা",
+        "অধ্যায় ৮": "ৰাজনৈতিক দল",
+        "অধ্যায় ৯": "ক্ষমতাৰ ভাগ-বতৰা",
+        "অধ্যায় ১০": "জনসম্পদ"
+    },
+    "📖 ইংৰাজী (English)": {
+        "পাঠ ১": "A Letter to God",
+        "পাঠ ২": "Nelson Mandela: Long Walk to Freedom",
+        "পাঠ ৩": "Two Stories about Flying",
+        "পাঠ ৪": "From the Diary of Anne Frank",
+        "পাঠ ৫": "The Hundred Dresses – I",
+        "পাঠ ৬": "The Hundred Dresses – II",
+        "পাঠ ৭": "Glimpses of India",
+        "পাঠ ৮": "Mijbil the Otter",
+        "পাঠ ৯": "Madam Rides the Bus",
+        "পাঠ ১০": "The Sermon at Benares",
+        "পাঠ ১১": "The Proposal"
+    },
+    "📜 অসমীয়া (Assamese)": {
+        "পাঠ ১": "বৰগীত",
+        "পাঠ ২": "জীৱন-সঙ্গীত",
+        "পাঠ ৩": "প্রশস্তি",
+        "পাঠ ৪": "মোৰ মৰমি জনমভূমি",
+        "পাঠ ৫": "অসমীয়া ভাষাৰ উন্নতি",
+        "পাঠ ৬": "অসমৰ লোক-সংস্কৃতি",
+        "পাঠ ৭": "আমাৰ ঋতু",
+        "পাঠ ৮": "বহাগ বিহু",
+        "পাঠ ৯": "মহাপুরুষীয়া ধৰ্ম",
+        "পাঠ ১০": "সাহিত্যৰ ৰূপ"
+    },
+    "📘 হিন্দী (Hindi)": {
+        "पाठ १": "साखी",
+        "पाठ २": "पद",
+        "पाठ ३": "दोहे",
+        "पाठ ४": "मनुष्यता",
+        "पाठ ५": "पर्वत प्रदेश में पावस",
+        "पाठ ६": "मधुर-मधुर मेरे दीपक जल",
+        "पाठ ७": "तोप",
+        "पाठ ८": "कर चले हम फ़िदा",
+        "पाठ ९": "आत्मत्राण",
+        "पाठ १०": "बड़े भाई साहब"
+    }
+}
+
+# Subject-wise prompt templates
+SUBJECT_PROMPTS = {
+    "📐 গণিত (Mathematics)": {
+        "base_prompt": """তুমি এজন বিশেষজ্ঞ গণিত শিক্ষক। SEBA দশম শ্ৰেণীৰ গণিতৰ পাঠ্যপুথিৰ {chapter_name} অধ্যায়ত থকা সকলো ধাৰণা, সূত্ৰ, আৰু উদাহৰণ তুমি ভালকৈ জানা।
+
+**গণিতৰ বিশেষ নিৰ্দেশনা:**
+১. **সকলো সূত্ৰ LaTeX ফৰ্মেটত দিবা**: $formula$ (দুয়োটা $ চিহ্নৰ মাজত)
+২. **ধাপে ধাপে সমাধান দেখুৱাবা**
+৩. **প্ৰতিটো ধাপৰ ব্যাখ্যা দিবা**
+৪. **সহজ পদ্ধতিৰে বুজাবা**
+৫. **পৰীক্ষাৰ বাবে গুৰুত্বপূৰ্ণ সূত্ৰবোৰ পৃথকৈ দেখুৱাবা**
+৬. **সকলো গাণিতিক সমীকৰণ আৰু সূতৰবোৰ `$` চিহ্নৰ মাজত লিখিবা, আলোচনাৰ বাহিৰত পৃথক লাইনত দেখুৱাবা।**
+
+**গণিতৰ সূত্ৰৰ উদাহৰণ (LaTeX ফৰ্মেটত):**
+- দ্বিঘাত সমীকৰণ: $ax^2 + bx + c = 0$
+- বৃত্তৰ কালি: $A = \\pi r^2$
+- সম্ভাৱিতা: $P(E) = \\frac{{n(E)}}{{n(S)}}$
+- পাইথাগোৰাছৰ উপপাদ্য: $a^2 + b^2 = c^2$
+
+**বক্তব্য শৈলী:**
+"চিন্তা নকৰিব, এই গণিতৰ সমস্যাটো সহজ।"
+"ধাপে ধাপে শিকো আহক..."
+"এই সূত্ৰটো মনত ৰাখিব - পৰীক্ষাত আহিব পাৰে!" """,
+        
+        "guidance": "সমীকৰণ, সূত্ৰ আৰু গাণিতিক প্ৰক্ৰিয়া LaTeX ফৰ্মেটত দেখুৱাব লাগে।"
+    },
+    
+    "🔬 বিজ্ঞান (Science)": {
+        "base_prompt": """তুমি এজন বিজ্ঞান শিক্ষক। SEBA দশম শ্ৰেণীৰ বিজ্ঞানৰ {chapter_name} অধ্যায়ৰ স��লো বৈজ্ঞানিক ধাৰণা, প্ৰক্ৰয়া, আৰু নীতি তুমি জানা।
+
+**বিজ্ঞানৰ বিশেষ নিৰ্দেশনা:**
+১. **বৈজ্ঞানিক প্ৰক্ৰিয়া ধাপে ধাপে বুজাবা**
+২. **ৰাসায়নিক সমীকৰণ সঠিকভাৱে দিবা**
+৩. **জীৱবিজ্ঞানৰ চিত্ৰ/ৰেখাচিত্ৰৰ বৰ্ণনা দিবা**
+৪. **পদাৰ্থবিজ্ঞানৰ সূত্ৰ LaTeX ফৰ্মেটত দিবা**
+
+**ৰাসায়নিক উদাহৰণ:**
+$2H_2 + O_2 \\rightarrow 2H_2O$
+
+**পদাৰ্থবিজ্ঞান সূত্ৰ:**
+$F = ma$, $v = u + at$
+
+**বক্তব্য শৈলী:**
+"এই বৈজ্ঞানিক ধাৰণাটো বুজোৱাৰ বাবে এটা সাধাৰণ উদাহৰণ চাওঁ..."
+"প্ৰকতিৰ এই ৰহস্যবোৰ মন কৰিছিল নেকি?" """,
+        
+        "guidance": "ৰাসায়নিক সমীকৰণ আৰু পদাৰ্থবিজ্ঞানৰ সূত্ৰ LaTeX ফৰ্মেটত দিব লাগে।"
+    },
+    
+    "🌍 সমাজ বিজ্ঞান (Social Science)": {
+        "base_prompt": """তুমি এজন সমাজ বিজ্ঞান শিক্ষক। SEBA দশম শ্ৰেণীৰ {chapter_name} অধ্যায়ৰ ঐতিহাসিক ঘটনা, ভৌগোলিক ধাৰণা, অৰ্থনৈতিক নীতি, আৰু ৰাজনৈতিক গঠন তুমি জানা।
+
+**সমাজ বিজ্ঞানৰ বিশেষ নিৰ্দেশনা:**
+১. **সহজ অসমীয়া ভাষা ব্যৱহাৰ কৰিবা**
+২. **প্ৰশ্ন অনুসৰি উত্তৰ দিবা**""",
+        
+        "guidance": "তথ্য আৰু বিশ্লেষণ স্পষ্টকৈ দিব লাগে।"
+    },
+    
+    "📖 ইংৰাজী (English)": {
+        "base_prompt": """তুমি এজন ইংৰাজী শিক্ষক। SEBA দশম শ্ৰেণীৰ {chapter_name} পাঠটোৰ সকলো সাহিত্যিক উপাদান, ব্যাকৰণ, আৰু ভাষা কৌশল তুমি জানা।
+
+**ইংৰাজীৰ বিশেষ নিৰ্দেশনা:**
+১. Answer in English with Assamese translation""",
+        
+        "guidance": "ইংৰাজী বাক্যৰ সৈতে অসমীয়া ব্যাখ্যা দিব লাগে।"
+    },
+    
+    "📜 অসমীয়া (Assamese)": {
+        "base_prompt": """তুমি এজন অসমীয়া সাহিত্য শিক্ষক। SEBA দশম শ্ৰেণীৰ {chapter_name} পাঠটোৰ সাহিত্যিক মুল্য, ভাষা বৈশিষ্ট্য, আৰু সাংস্কৃতিক প্ৰসংগ তুমি জানা।
+
+**অসমীয়াৰ বিশেষ নিৰ্দেশনা:**
+১. **সাহিত্যিক বিশ্লেষণ অসমীয়াত দিবা**
+২. **প্ৰশ্ন অনুসৰি উত্তৰ দিবা**""",
+        
+        "guidance": "অসমীয়া ভাষাৰ সৌন্দৰ্য্য আৰু গভীৰতা দেখুৱাব লাগে।"
+    },
+    
+    "📘 হিন্দী (Hindi)": {
+        "base_prompt": """तुम एक हिंदी शिक्षक हो। SEBA दशम श्रेणी के {chapter_name} पाठ के सभी साहित्यिक तत्व, व्याकरण, और भाषा कौशल तुम जानते हो।
+
+**हिंदी के विशेष निर्देश:**
+१. **साहित्यिक विश्लेषण हिंदी में देना, साथ असमिया व्याख्या देना**
+२. **प्रश्न के अनुसार उत्तर देना**""",
+        
+        "guidance": "हिंदी वाक्य के साथ असमिया व्याख्या देना"
+    }
+}
+
+# ===============================
+# HELPER FUNCTIONS
+# ===============================
+def create_cache_key(question, subject, chapter_name):
+    """Create a unique cache key for the question"""
+    # Normalize the question for better caching
+    normalized_question = question.strip().lower()
+    # Remove extra whitespace and special characters
+    normalized_question = re.sub(r'\s+', ' ', normalized_question)
+    normalized_question = normalized_question[:200]  # Limit length
+    
+    # Create a hash-based key for better performance
+    key_string = f"{subject}|{chapter_name}|{normalized_question}"
+    cache_key = hashlib.md5(key_string.encode()).hexdigest()
+    
+    return cache_key
+
+def get_question_guidance(question, subject, chapter_name):
+    question_lower = question.lower()
+    
+    simple_keywords = [
+        "সংজ্ঞা", "কি", "কাক কয়", "মানে", "definition", "what is", 
+        "নাম", "কেইটা", "কিমান", "count", "number", "কি নাম", "কাক বোলে"
+    ]
+    
+    moderate_keywords = [
+        "কেনেকৈ", "কেনেকুৱা", "কিয়", "বুজাই দিয়ক", "explain", "how", 
+        "why", "difference", "পাৰ্থক্য", "উদাহৰণ", "example", "সমাধান", 
+        "solve", "কোনবোৰ", "তুলনা", "compare", "সাদৃশ্য", "similarity"
+    ]
+    
+    complex_keywords = [
+        "বিশ্লেষণ", "আলোচনা", "মূল্যায়ন", "বৰ্ণনা", "discuss", 
+        "analyze", "evaluate", "describe", "প্ৰমাণ", "prove", 
+        "সমাধান কৰি দেখুৱাওক", "solve and show", "step by step",
+        "ধাপে ধাপে", "সম্পূৰ্ণ", "সম্পূৰ্ণ বিৱৰণ", "full explanation",
+        "সবিশেষ", "in detail", "detailed", "সবিস্তাৰে"
+    ]
+    
+    guidance_text = ""
+    
+    if "📐 গণিত" in subject:
+        guidance_text = "গণিতৰ সমস্যাৰ বাবে ধাপে ধাপে সমাধান দিব লাগে। "
+    elif "🔬 বিজ্ঞান" in subject:
+        guidance_text = "বিজ্ঞানৰ উত্তৰ বৈজ্ঞানিকভাৱে সঠিক হ'ব লাগে। "
+    elif "🌍 সমাজ বিজ্ঞান" in subject:
+        guidance_text = "তথ্য সঠিক আৰু বিশ্লেষণাত্মক হ'ব লাগে। "
+    
+    if any(keyword in question_lower for keyword in complex_keywords):
+        return f"{guidance_text} প্ৰশ্নটো জটিল, গতিকে বিশদ উত্তৰ দিবা।"
+    elif any(keyword in question_lower for keyword in moderate_keywords):
+        return f"{guidance_text} প্ৰশ্নটো মধ্যমীয়া, গতিকে সম্পূৰ্ণ উত্তৰ দিবা।"
+    elif any(keyword in question_lower for keyword in simple_keywords):
+        return f"{guidance_text} প্ৰশ্নটো সৰল, গতিকে সংক্ষিপ্ত উত্তৰ দিবা।"
+    else:
+        return f"{guidance_text} প্ৰশ্নৰ প্ৰকৃতি অনুসৰি উত্তৰ দিবা।"
+
+def get_subject_prompt(subject, chapter_name, question):
+    if subject not in SUBJECT_PROMPTS:
+        subject = "📐 গণিত (Mathematics)"
+    
+    prompt_template = SUBJECT_PROMPTS[subject]
+    base_prompt = prompt_template["base_prompt"].format(chapter_name=chapter_name)
+    guidance = prompt_template["guidance"]
+    
+    if subject == "📐 গণিত (Mathematics)" or subject == "🔬 বিজ্ঞান (Science)":
+        latex_instruction = "\n\n**গুৰুত্বপূৰ্ণ**: সকলো গাণিতিক সূত্ৰ, সমীকৰণ LaTeX ফৰ্মেটত দিবা ($ চিহ্নৰ মাজত)।"
+    else:
+        latex_instruction = ""
+    
+    question_guidance = get_question_guidance(question, subject, chapter_name)
+    
+    full_prompt = f"""{base_prompt}
+
+{guidance}{latex_instruction}
+
+**উত্তৰৰ নিৰ্দেশনা:**
+{question_guidance}
+**উত্তৰ যিমান দৰকাৰী সিমান দীঘল হ'ব লাগে।**
+
+**ছাত্ৰক মাতি লওঁ:**
+"বন্ধু, এইটো এনেদৰে বুজিব লাগে..."
+"চিন্তা নকৰিব, এইটো সহজ..."
+
+এতিয়া এই প্ৰশ্নটোৰ উত্তৰ দিয়া: {question}"""
+    
+    return full_prompt
+
+# ===============================
+# STREAMLIT STREAMING RESPONSE FUNCTION
+# ===============================
+def stream_deepseek_response(prompt, question, subject, chapter_name):
+    headers = {
+        "Authorization": f"Bearer {api_key}",
+        "Content-Type": "application/json"
+    }
+    
+    payload = {
+        "model": "deepseek-chat",
+        "messages": [
+            {"role": "system", "content": "তুমি এজন বিশেষজ্ঞ SEBA দশম শ্ৰেণীৰ শিক্ষক।"},
+            {"role": "user", "content": prompt}
+        ],
+        "temperature": 0.3,
+        "stream": True
+    }
+    
+    try:
+        # Make streaming request
+        response = requests.post(
+            "https://api.deepseek.com/v1/chat/completions",
+            headers=headers,
+            json=payload,
+            stream=True,
+            timeout=180
+        )
+        
+        if response.status_code == 200:
+            full_response = ""
+            tokens_used = 0
+            
+            # Create a placeholder for streaming text
+            streaming_placeholder = st.empty()
+            
+            # Process streaming response
+            for line in response.iter_lines():
+                if line:
+                    line = line.decode('utf-8')
+                    if line.startswith('data: '):
+                        data = line[6:]  # Remove 'data: ' prefix
+                        if data == '[DONE]':
+                            break
+                        
+                        try:
+                            import json
+                            chunk = json.loads(data)
+                            if 'choices' in chunk and len(chunk['choices']) > 0:
+                                delta = chunk['choices'][0].get('delta', {})
+                                if 'content' in delta:
+                                    content = delta['content']
+                                    full_response += content
+                                    
+                                    # Update streaming display - Streamlit will auto-render LaTeX
+                                    streaming_placeholder.markdown(
+                                        f"{full_response}<span style='animation: cursor-blink 1s infinite;'>▋</span>",
+                                        unsafe_allow_html=True
+                                    )
+                                
+                                # Track tokens
+                                if 'usage' in chunk:
+                                    tokens_used = chunk['usage'].get('total_tokens', 0)
+                        except json.JSONDecodeError:
+                            continue
+            
+            # Clear streaming cursor after completion
+            streaming_placeholder.empty()
+            
+            # Render the final answer - Streamlit will handle LaTeX automatically
+            st.markdown(full_response)
+            
+            # Store the complete response
+            st.session_state.last_answer = full_response
+            st.session_state.tokens_used = tokens_used
+            
+            # Save to cache using manager
+            cache_key = create_cache_key(question, subject, chapter_name)
+            st.session_state.cache_manager.set(cache_key, {
+                'answer': full_response,
+                'tokens': tokens_used,
+                'subject': subject,
+                'chapter': chapter_name,
+                'question': question[:200]
+            })
+            
+            # Add to history
+            history_entry = {
+                'subject': subject,
+                'chapter': chapter_name,
+                'question': question[:100],
+                'timestamp': datetime.now().strftime("%H:%M"),
+                'tokens': tokens_used,
+                'cached': False  # Not cached (new response)
+            }
+            st.session_state.history.append(history_entry)
+            
+        else:
+            st.error(f"API ত্ৰুটি {response.status_code}: {response.text}")
+            
+    except Exception as e:
+        st.error(f"সংযোগ ত্ৰুটি: {str(e)}")
+
+# ===============================
+# INITIALIZE SESSION STATE
+# ===============================
+if 'history' not in st.session_state:
+    st.session_state.history = []
+if 'current_subject' not in st.session_state:
+    st.session_state.current_subject = "📐 গণিত (Mathematics)"
+if 'current_chapter' not in st.session_state:
+    st.session_state.current_chapter = "অধ্যায় ১"
+if 'processing' not in st.session_state:
+    st.session_state.processing = False
+if 'last_answer' not in st.session_state:
+    st.session_state.last_answer = None
+if 'question_text' not in st.session_state:
+    st.session_state.question_text = ""
+if 'streaming_answer' not in st.session_state:
+    st.session_state.streaming_answer = ""
+if 'tokens_used' not in st.session_state:
+    st.session_state.tokens_used = 0
+if 'cache_manager' not in st.session_state:
+    st.session_state.cache_manager = HybridCache(ttl_hours=24, max_entries=100)
+if 'show_cached_answer' not in st.session_state:
+    st.session_state.show_cached_answer = False
+if 'cached_answer_data' not in st.session_state:
+    st.session_state.cached_answer_data = None
+if 'current_cache_key' not in st.session_state:
+    st.session_state.current_cache_key = None
+
+# ===============================
+# HEADER SECTION
+# ===============================
+st.markdown("""
+<div class="header-container">
+    <div style="display: flex; align-items: center; gap: 1rem; margin-bottom: 0.5rem;">
+        <div style="font-size: 2rem;">🎓</div>
+        <div>
+            <h1 class="assamese-title">
+                নমস্কাৰ! মই আপোনাৰ দশম শ্ৰেণীৰ AI শিক্ষক
+            </h1>
+            <p class="assamese-text">
+                <span class="assamese-highlight">SEBAৰ সকলো বিষয় মই জানো</span> – গণিত, বিজ্ঞান, সমাজ বিজ্ঞান, ইংৰাজী, অসমীয়া, হিন্দী ইত্যাদি।
+            </p>
+        </div>
+    </div>
+</div>
+""", unsafe_allow_html=True)
+
+# ===============================
+# CONTROL PANEL SECTION
+# ===============================
+st.markdown('<div class="control-panel">', unsafe_allow_html=True)
+
+control_col1, control_col2 = st.columns(2)
+with control_col1:
+    st.markdown("#### 📚 বিষয় বাছনি কৰক")
+    subject_list = list(SEBA_CURRICULUM.keys())
+    current_subject = st.session_state.current_subject
+    current_index = subject_list.index(current_subject) if current_subject in subject_list else 0
+    
+    selected_subject = st.selectbox(
+        "আপুনি কোনটো বিষয় শিকিব বিচাৰে?",
+        subject_list,
+        index=current_index,
+        key="subject_selector",
+        label_visibility="collapsed"
+    )
+    
+    if selected_subject != st.session_state.current_subject:
+        st.session_state.current_subject = selected_subject
+        chapters = SEBA_CURRICULUM[selected_subject]
+        st.session_state.current_chapter = list(chapters.keys())[0]
+
+with control_col2:
+    st.markdown("#### 📖 অধ্যায় বাছনি কৰক")
+    chapters = SEBA_CURRICULUM[selected_subject]
+    
+    chapter_options = []
+    chapter_display_map = {}
+    for chap_num, chap_name in chapters.items():
+        display_text = f"{chap_num}: {chap_name}"
+        chapter_options.append(display_text)
+        chapter_display_map[display_text] = chap_num
+    
+    current_chapter = st.session_state.current_chapter
+    current_chap_display = next((disp for disp, num in chapter_display_map.items() if num == current_chapter), chapter_options[0])
+    current_chap_index = chapter_options.index(current_chap_display) if current_chap_display in chapter_options else 0
+    
+    selected_chapter_display = st.selectbox(
+        "কোন অধ্যায়ৰ পৰা প্ৰশ্ন সুধিব?",
+        chapter_options,
+        index=current_chap_index,
+        key="chapter_selector",
+        label_visibility="collapsed"
+    )
+    
+    selected_chapter_key = chapter_display_map[selected_chapter_display]
+    if selected_chapter_key != st.session_state.current_chapter:
+        st.session_state.current_chapter = selected_chapter_key
+
+st.markdown('</div>', unsafe_allow_html=True)
+
+# ===============================
+# CURRENT SELECTION INFO
+# ===============================
+current_chapter_name = chapters[selected_chapter_key]
+st.info(f"""
+**📚 বৰ্তমানৰ বিষয়:** {selected_subject}
+**📖 বৰ্তমানৰ অধ্যায়:** {current_chapter_name}
+""")
+
+# ===============================
+# SAMPLE QUESTIONS SECTION (SKIPPED - ADD FROM YOUR SIDE)
+# ===============================
+# [Add your sample questions code here]
+
+# ===============================
+# QUESTION INPUT AREA
+# ===============================
+st.markdown("---")
+st.markdown("#### ✍️ আপোনাৰ প্ৰশ্নটো ইয়াত লিখক")
+
+question = st.text_area(
+    "আপোনাৰ প্ৰশ্নটো ইয়াত লিখক:",
+    value=st.session_state.question_text,
+    height=100,
+    placeholder=f"উদাহৰণ: '{current_chapter_name}' অধ্যায়টো মোৰ বাবে বুজাই দিয়ক...",
+    key="question_input",
+    label_visibility="collapsed"
+)
+
+if question != st.session_state.question_text:
+    st.session_state.question_text = question
+
+# Show API key status
+if not api_key:
+    st.error("""
+    ⚠️ **API কি ছেট আপ কৰক:**
+    
+    **Hugging Face Spaces:**
+    ১. Space Settings → Repository secrets
+    ২. `DEEPSEEK_API_KEY` যোগ কৰক
+    ৩. আপোনাৰ DeepSeek API কি দিয়ক
+    
+    **স্থানীয়ভাবে:**
+    ```bash
+    export DEEPSEEK_API_KEY="your-api-key-here"
+    ```
+    """)
+
+# ===============================
+# CACHE CHECK AND SUBMIT BUTTON
+# ===============================
+submit_disabled = not (question.strip() and api_key)
+col1, col2, col3 = st.columns([1, 2, 1])
+with col2:
+    if st.button(
+        "🚀 উত্তৰ দিবলৈ দিয়ক!", 
+        type="primary", 
+        use_container_width=True,
+        disabled=submit_disabled
+    ):
+        if not question.strip():
+            st.error("❌ অনুগ্ৰহ কৰি প্ৰশ্নটো লিখক!")
+        elif not api_key:
+            st.error("❌ API কি ছেট আপ কৰক!")
+        else:
+            # Check cache first
+            cache_key = create_cache_key(question, selected_subject, current_chapter_name)
+            cached_entry = st.session_state.cache_manager.get(cache_key)
+            
+            if cached_entry:
+                # Load from cache
+                st.session_state.last_answer = cached_entry['answer']
+                st.session_state.tokens_used = cached_entry['tokens']
+                
+                # Add to history with cache flag
+                history_entry = {
+                    'subject': selected_subject,
+                    'chapter': current_chapter_name,
+                    'question': question[:100],
+                    'timestamp': datetime.now().strftime("%H:%M"),
+                    'tokens': cached_entry['tokens'],
+                    'cached': True
+                }
+                st.session_state.history.append(history_entry)
+                
+                # Show cached answer
+                st.session_state.show_cached_answer = True
+                st.session_state.cached_answer_data = cached_entry
+                st.session_state.current_cache_key = cache_key
+                st.session_state.processing = False
+            else:
+                # Not in cache, proceed with API call
+                st.session_state.processing = True
+                st.session_state.current_cache_key = cache_key
+
+# ===============================
+# DISPLAY CACHED ANSWER
+# ===============================
+if hasattr(st.session_state, 'show_cached_answer') and st.session_state.show_cached_answer:
+    st.markdown("---")
+    
+    # User question
+    st.markdown(f"""
+    <div style="margin-bottom: 1rem;">
+        <div style="display: flex; justify-content: flex-end; margin-bottom: 0.3rem;">
+            <div class="user-bubble">
+                <div style="font-weight: 600; margin-bottom: 0.2rem;">👤 আপুনি:</div>
+                <div>{question}</div>
+            </div>
+        </div>
+    </div>
+    """, unsafe_allow_html=True)
+    
+    # Cached answer with indicator
+    cached_data = st.session_state.cached_answer_data
+    
+    st.markdown(f"""
+    <div style="margin-bottom: 0.5rem;">
+        <div style="display: flex; align-items: flex-start; margin-bottom: 0.3rem;">
+            <div style="margin-right: 0.5rem; font-size: 1.2rem;">🤖</div>
+            <div style="flex: 1;">
+                <div class="ai-bubble">
+                    <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 0.5rem; padding-bottom: 0.5rem; border-bottom: 2px solid #4CAF50;">
+                        <div style="display: flex; align-items: center;">
+                            <div style="background: #4CAF50; color: white; padding: 0.2rem 0.5rem; border-radius: 8px; 
+                                        font-weight: 600; font-size: 0.8rem; margin-right: 0.5rem;">
+                                <span style="margin-right: 0.3rem;">⚡</span> Cached
+                            </div>
+                            <div style="font-weight: 600; color: #0d47a1; font-size: 0.9rem;">
+                                {selected_subject} • {current_chapter_name}
+                            </div>
+                        </div>
+                        <div style="font-size: 0.75rem; color: #666; background: #f1f8e9; padding: 0.2rem 0.5rem; border-radius: 4px;">
+                            <span style="margin-right: 0.3rem;">💾</span> Cache Hit
+                        </div>
+                    </div>
+                    <div style="color: #333; line-height: 1.5; font-size: 0.95rem;">
+                        {cached_data['answer']}
+                    </div>
+                </div>
+            </div>
+        </div>
+    </div>
+    """, unsafe_allow_html=True)
+    
+    # Show cache info
+    with st.expander("📊 Cache Information"):
+        cache_stats = st.session_state.cache_manager.get_stats()
+        estimated_cost = cached_data.get('tokens', 0) * 0.0000014  # $0.14 per 100K tokens
+        st.info(f"""
+        **Cache Benefits:**
+        - ⚡ Instant response (no API call)
+        - 💰 No token cost (saved {cached_data.get('tokens', 0):,} tokens)
+        - 💵 Estimated savings: ${estimated_cost:.4f}
+        - 🌿 Environmentally friendly
+        
+        **Cache Details:**
+        - Cache entries: {cache_stats['total_entries']}
+        - Total tokens saved: {cache_stats['total_saved_tokens']:,}
+        - Cache hit count: {cached_data.get('access_count', 1)}
+        - Cache TTL: {cache_stats['ttl_hours']} hours
+        - Storage: {cache_stats['storage_mode']}
+        """)
+        
+        # Cache management buttons
+        col1, col2 = st.columns(2)
+        with col1:
+            if st.button("🗑️ Clear this cached answer", type="secondary", use_container_width=True):
+                if st.session_state.current_cache_key in st.session_state.cache_manager.cache:
+                    st.session_state.cache_manager.cache.pop(st.session_state.current_cache_key)
+                    st.success("Cache entry cleared!")
+                    st.session_state.show_cached_answer = False
+                    st.rerun()
+        
+        with col2:
+            if st.button("🧹 Clear all cache", type="secondary", use_container_width=True):
+                st.session_state.cache_manager.clear_all()
+                st.success("All cache cleared!")
+                st.session_state.show_cached_answer = False
+                st.rerun()
+    
+    # Show token usage
+    if cached_data.get('tokens', 0) > 0:
+        st.caption(f"📊 Original token cost (saved): {cached_data['tokens']:,}")
+    
+    # Reset flag
+    st.session_state.show_cached_answer = False
+    del st.session_state.cached_answer_data
+    del st.session_state.current_cache_key
+
+# ===============================
+# PROCESS QUESTION WITH STREAMING
+# ===============================
+if st.session_state.get('processing') and question and api_key and not st.session_state.get('show_cached_answer', False):
+    st.markdown("---")
+    
+    # User question
+    st.markdown(f"""
+    <div style="margin-bottom: 1rem;">
+        <div style="display: flex; justify-content: flex-end; margin-bottom: 0.3rem;">
+            <div class="user-bubble">
+                <div style="font-weight: 600; margin-bottom: 0.2rem;">👤 আপুনি:</div>
+                <div>{question}</div>
+            </div>
+        </div>
+    </div>
+    """, unsafe_allow_html=True)
+    
+    # AI answer header (with thinking animation)
+    st.markdown(f"""
+    <div style="margin-bottom: 0.5rem;">
+        <div style="display: flex; align-items: flex-start; margin-bottom: 0.3rem;">
+            <div style="margin-right: 0.5rem; font-size: 1.2rem;">🤖</div>
+            <div style="flex: 1;">
+                <div class="ai-bubble">
+                    <div style="display: flex; align-items: center; margin-bottom: 0.5rem; padding-bottom: 0.5rem; border-bottom: 2px solid #2196F3;">
+                        <div style="background: #2196F3; color: white; padding: 0.2rem 0.5rem; border-radius: 8px; 
+                                    font-weight: 600; font-size: 0.8rem; margin-right: 0.5rem;">
+                            AI টিউটাৰ
+                        </div>
+                        <div style="font-weight: 600; color: #0d47a1; font-size: 0.9rem;">
+                            {selected_subject} • {current_chapter_name}
+                        </div>
+                    </div>
+                    <div style="color: #333; line-height: 1.5; font-size: 0.95rem; min-height: 100px;">
+    """, unsafe_allow_html=True)
+    
+    # Show thinking animation while preparing response
+    thinking_placeholder = st.empty()
+    thinking_placeholder.markdown("""
+    <div class="progress-indicator">
+        <span>উত্তৰ প্ৰস্তুত কৰি আছো...</span>
+        <div class="thinking-dots">
+            <span></span>
+            <span></span>
+            <span></span>
+        </div>
+    </div>
+    """, unsafe_allow_html=True)
+    
+    # Get the prompt and stream the response
+    system_prompt = get_subject_prompt(selected_subject, current_chapter_name, question)
+    
+    # Clear thinking animation and start streaming
+    thinking_placeholder.empty()
+    
+    # Stream the response
+    stream_deepseek_response(system_prompt, question, selected_subject, current_chapter_name)
+    
+    # Close the AI bubble div
+    st.markdown("""
+                    </div>
+                </div>
+            </div>
+        </div>
+    </div>
+    """, unsafe_allow_html=True)
+    
+    # Show token usage
+    if st.session_state.tokens_used > 0:
+        st.caption(f"📊 ট'কেন ব্যৱহৃত: {st.session_state.tokens_used:,}")
+    
+    st.session_state.processing = False
+
+# ===============================
+# HISTORY
+# ===============================
+if st.session_state.history:
+    st.markdown("---")
+    st.markdown("#### 📜 আজিৰ প্ৰশ্নাৱলী")
+    
+    for i, item in enumerate(reversed(st.session_state.history[-3:]), 1):
+        cache_indicator = " ⚡" if item.get('cached') else ""
+        with st.expander(f"প্ৰশ্ন {i}: {item['question']} ({item['timestamp']}{cache_indicator})"):
+            st.write(f"**বিষয়:** {item['subject']}")
+            st.write(f"**অধ্যায়:** {item['chapter']}")
+            st.write(f"**ট'কেন:** {item.get('tokens', 0):,}")
+            if item.get('cached'):
+                st.caption("⚡ This answer was served from cache")
+
+# ===============================
+# CACHE STATISTICS SIDEBAR
+# ===============================
+with st.sidebar:
+    st.markdown("---")
+    st.markdown("#### 💾 Cache Statistics")
+    
+    cache_stats = st.session_state.cache_manager.get_stats()
+    
+    if cache_stats['total_entries'] > 0:
+        # Cache info
+        st.caption(f"⚡ **Storage:** {cache_stats['storage_mode']}")
+        
+        # Cache stats metrics
+        col1, col2 = st.columns(2)
+        with col1:
+            st.metric("Entries", cache_stats['total_entries'])
+            st.metric("Avg Age", f"{cache_stats['average_age_hours']}h")
+        
+        with col2:
+            st.metric("Tokens Saved", f"{cache_stats['total_saved_tokens']:,}")
+            st.metric("TTL", f"{cache_stats['ttl_hours']}h")
+        
+        # Cost savings
+        estimated_cost = cache_stats['total_saved_tokens'] * 0.0000014  # $0.14 per 100K tokens
+        st.metric("💰 Cost Saved", f"${estimated_cost:.4f}")
+        
+        # Cache management
+        st.markdown("#### 🛠️ Cache Management")
+        
+        col1, col2 = st.columns(2)
+        with col1:
+            if st.button("🗑️ Clear Expired", use_container_width=True):
+                cleared = st.session_state.cache_manager.clear_expired()
+                if cleared > 0:
+                    st.success(f"Cleared {cleared} expired entries!")
+                else:
+                    st.info("No expired entries found")
+                st.rerun()
+        
+        with col2:
+            if st.button("🧹 Clear All", use_container_width=True):
+                st.session_state.cache_manager.clear_all()
+                st.success("All cache cleared!")
+                st.rerun()
+        
+        # View recent cached questions
+        with st.expander("📋 Recent Cached Questions"):
+            recent_entries = list(st.session_state.cache_manager.cache.items())[:5]
+            for key, entry in recent_entries:
+                question_text = entry.get('question', 'N/A')[:40] + "..."
+                age_hours = round((datetime.now() - datetime.fromisoformat(entry.get('created_at', datetime.now().isoformat()))).seconds / 3600, 1)
+                st.caption(f"• {question_text}")
+                st.write(f"  📚 {entry.get('subject', 'N/A').split()[0]} • 🔢 {entry.get('access_count', 1)}x • ⏳ {age_hours}h ago")
+    else:
+        st.info("Cache is empty. Ask some questions to build cache!")
+    
+    # Cache performance note
+    st.markdown("---")
+    st.caption("""
+    **💡 Cache Performance:**
+    - Cache persists for 24 hours
+    - In-memory storage (no file access)
+    - Automatic cleanup of old entries
+    - Works within browser session
+    """)
+
+# ===============================
+# FOOTER
+# ===============================
+st.markdown("---")
+st.markdown("""
+<div style="text-align: center; padding: 0.5rem;">
+    <h3 style="color: #0d47a1; margin-bottom: 0.5rem;">
+        🎓 আপোনাৰ সফলতাৰ বাবে মই সদায় আছো!
+    </h3>
+</div>
+""", unsafe_allow_html=True)
+
+st.markdown("""
+<div style="text-align: center; padding: 0.5rem; margin-top: 1rem; color: #1976D2; font-size: 0.8rem;">
+    <p style="margin: 0;">© 2025 Jajabor AI. All rights reserved.</p>
+</div>
+""", unsafe_allow_html=True)