Update app.py

app.py

@@ -11,15 +11,14 @@ from urllib.parse import quote
 from gradio_client import Client
 from datetime import datetime
 
-# 🌳🤖 AIKnowledgeTreeBuilder - Because every app needs a good costume!
-
+# Page configuration
 Site_Name = 'AI Knowledge Tree Builder 📈🌿 Grow Smarter with Every Click'
 title = "🌳✨AI Knowledge Tree Builder🛠️🤓"
 helpURL = 'https://huggingface.co/spaces/awacke1/AIKnowledgeTreeBuilder/'
 bugURL = 'https://huggingface.co/spaces/awacke1/AIKnowledgeTreeBuilder/'
 icons = '🌳✨🛠️🤓'
 
-SidebarOutline="""🌳🤖 Designed with the following tenets:
+SidebarOutline = """🌳🤖 Designed with the following tenets:
 1 📱 **Portability** - Universal access via any device & link sharing
 2. ⚡ **Speed of Build** - Rapid deployments < 2min to production
 3. 🔗 **Linkiness** - Programmatic access to AI knowledge sources
@@ -43,7 +42,6 @@ st.set_page_config(
 
 st.sidebar.markdown(SidebarOutline)
 
-
 # Initialize session state variables
 if 'selected_file' not in st.session_state:
     st.session_state.selected_file = None
@@ -52,519 +50,7 @@ if 'view_mode' not in st.session_state:
 if 'files' not in st.session_state:
     st.session_state.files = []
 
-
-BiologyAndLevel36MagicUsers="""
-0. Biology Core Rules and Future Exceptions
-1. Central Dogma DNA RNA Protein
-- Current CRISPR RNA editing 🧪
-- Research Gene therapy siRNA 🔬
-- Future Programmable genetics 🚀
-
-2. Cell Origin
-- Current iPSCs organoids 🦠
-- Research Synthetic cells 🔬
-- Future De novo cell creation 🚀
-
-3. Form Function
-- Current Bioprinting 🫀
-- Research 4D printing 🔬
-- Future Self assembling structures 🚀
-
-4. Homeostasis
-- Current Artificial pancreas 🤖
-- Research Nanorobots 🔬
-- Future Autonomous regulation 🚀
-
-5. Evolution
-- Current Directed evolution 🧫
-- Research Synthetic biology 🔬
-- Future Accelerated adaptation 🚀
-
-6. Energy Conservation
-- Current Biofuel cells ⚡
-- Research Quantum biology 🔬
-- Future Biological perpetual motion 🚀
-
-7. Cellular Life
-- Current Organoid systems 🔮
-- Research Hybrid cells 🔬
-- Future Silicon based life 🚀
-
-8. Inheritance Patterns
-- Current Gene drives 🧩
-- Research Epigenetic control 🔬
-- Future Designed inheritance 🚀
-
-9. Energy Requirements
-- Current Metabolic engineering 🔋
-- Research Synthetic photosynthesis 🔬
-- Future Zero energy life 🚀
-
-10. Random Mutation
-- Current Base editing 🎯
-- Research Mutation prediction 🔬
-- Future Controlled evolution 🚀
-
-11. Carbon Based Life
-- Current Alternative biochemistry 💎
-- Research Silicon biology 🔬
-- Future Non carbon life 🚀
-
-12. Size Limitations
-- Current Nanostructures 📏
-- Research Quantum biology 🔬
-- Future Scalable organisms 🚀
-
-13. Species Interdependence
-- Current Synthetic ecosystems 🌿
-- Research Artificial symbiosis 🔬
-- Future Independent life 🚀
-
-14. Stimulus Response
-- Current Brain computer interfaces 🧠
-- Research Neural engineering 🔬
-- Future Direct consciousness control 🚀
-
-15. Development Complexity
-- Current Accelerated growth 🌱
-- Research Development control 🔬
-- Future Instant maturation 🚀
-
-16. Population Growth
-- Current Population control 📊
-- Research Sustainable ecosystems 🔬
-- Future Perfect equilibrium 🚀
-
-17. Energy Flow
-- Current Enhanced photosynthesis 🌞
-- Research Energy optimization 🔬
-- Future Perpetual systems 🚀
-
-18. Environmental Adaptation
-- Current Climate resistance 🌍
-- Research Universal adaptation 🔬
-- Future Environment independence 🚀
-
-19. Genetic Inheritance
-- Current Gene editing 🧬
-- Research Trait programming 🔬
-- Future Perfect inheritance 🚀
-
-20. Reproduction
-- Current Artificial wombs 👶
-- Research Cloning advances 🔬
-- Future Asexual human reproduction 🚀
-
-21. Aging Death
-- Current Longevity therapy ⏰
-- Research Age reversal 🔬
-- Future Biological immortality 🚀
-"""
-
-AITopicsToInnovate1="""
-1. Major AI Industry Players 🌐
-   1. Research Leaders 🎯
-      - OpenAI: GPT-4 DALL-E Foundation Models 🔵
-      - Google: PaLM Gemini LLMs 🟦
-      - Anthropic: Claude Constitutional AI ⚡
-      - Meta: LLaMA Open Source LLMs 👤
-      - xAI: Grok Conversational AI 🤖
-   
-2. Technical AI Development 🛠️
-   1. Architecture Advances 💫
-      - Transformer Models Attention Mechanisms 🧠
-      - Mixture of Experts MoE Architecture 🎪
-      - Sparse Neural Networks 🕸️
-      - Multi-modal LLM Systems 🌈
-      - Flash Attention Optimization ⚔️
-   
-   2. Training Methodologies 📚
-      - LLM Supervised Fine-tuning 👨‍🏫
-      - RLHF Reward Models 🤝
-      - Constitutional AI Training 📜
-      - RLAIF Feedback Models 🔄
-      - Synthetic Data LLM Training 🎲
-      - Chain of Thought Prompting 🧩
-      - Tree of Thoughts Reasoning 🌳
-   
-   3. Post-Training Implementation 🔧
-      - Neural Network Distillation 🧪
-      - LLM Quantization Methods 📊
-      - Neural Network Pruning ���️
-      - Knowledge Distillation Transfer 📖
-      - Few-shot LLM Learning 🎯
-
-3. Mechanistic Interpretability 🔬
-   1. Core Concepts 💡
-      - Neural Network Growth Analysis 🌱
-      - LLM Architecture Analysis 🏗️
-      - Training Loss Optimization 🎨
-      - Neural Network Analogies 🧬
-   
-   2. Technical Features 📐
-      - LLM Linear Representations ➡️
-      - Neural Vector Arithmetic 🔢
-      - Neural Activation Patterns 🌊
-      - LLM Feature Detection 🔍
-      - Neural Sparse Autoencoders 🎭
-   
-   3. Network Analysis 🕵️
-      - LLM Induction Heads 👀
-      - Transformer Attention Analysis 🎪
-      - Neural Circuit Analysis 🔌
-      - LLM Feature Visualization 📈
-      - Neural Concept Directions 🎳
-
-4. Future AI Developments 🚀
-   1. AGI Timeline ⏰
-      - AGI Capability Projections 📅
-      - Neural Hardware Scaling 💾
-      - LLM Training Data Limits 📉
-      - AI Compute Resources 🗺️
-   
-   2. Integration Fields 🎡
-      - AI Biology Integration 🔮
-      - AI Drug Discovery Systems 💊
-      - AI Clinical Trial Analysis 🏥
-      - AI Code Generation 🤹
-      - AI Scientific Discovery 🧮
-
-5. Industry Best Practices 💎
-   1. AI Team Building 🏢
-      - AI Talent Development 👥
-      - AI Research Alignment 🎪
-      - AI Team Scaling 📊
-      - AI Research Culture 🌟
-   
-   2. AI Research Qualities 🎓
-      - AI Research Methodology 🧭
-      - AI Experimentation Protocols 🗝️
-      - AI Innovation Thinking 💫
-      - AI Testing Framework ⚖️
-   
-   3. AI Safety Standards 🛡️
-      - LLM Behavioral Specifications 📋
-      - AI Safety Guidelines 🎮
-      - AI Ethics Framework ⛑️
-      - AI Industry Standards 🤲
-
-6. Emerging Research Areas 🔮
-   1. Technical Focus 🎯
-      - LLM Long Context Learning ⏳
-      - LLM Multi-agent Interaction 👾
-      - AI Evaluation Metrics 📌
-      - Neural Interpretability Methods 🔭
-   
-   2. AI Applications 💼
-      - AI Automated Research 🧫
-      - AI Code Synthesis ⌨️
-      - AI Biological Modeling 🧯
-      - AI Medical Diagnostics 💉
-
-7. Model Intelligence 🧿
-   1. LLM System Development 🎪
-      - LLM Prompt Engineering 📝
-      - LLM Response Generation ♟️
-      - LLM Behavioral Training 🎹
-      - LLM Personality Development 🎪
-   
-   2. LLM User Interaction 🎭
-      - LLM Autonomy Alignment 🎪
-      - LLM Safety Boundaries 🔒
-      - LLM Communication Patterns 🗣️
-      - LLM Performance Tuning 🎢
-"""
-
-Multiplayer_Custom_Hosting_Game_Servers_For_Simulated_Worlds = """
-
-
-0. Fantasy Domain Introduction
-1. Setting the Scene
-- Current Create a high-fantasy realm with unique ecosystems, magical phenomena, and cultural diversity 🏞️
-- Research Add domain-specific entities like mythical creatures, enchanted terrains, or ancient artifacts 🧝‍♂️
-- Future Fully AI-generated interactive worldbuilding 🚀
-
-2. Archetypal Overview
-- Current Write a summary of a classic D&D character archetype 🗡️
-- Research Add roles, special abilities, and motivations for NPC creation 🔮
-- Future AI-enhanced roleplay character dynamics 🚀
-
-3. Entity-Focused Narrative Creation
-1. Monster Mythology
-- Current Create monsters with unique traits like ‘Crimson Obelisk Wurm’ 🐉
-- Research Add lore and origin stories with detailed classifications 🔬
-- Future Dynamic AI monster lore generators 🚀
-2. Artifact Legacy
-- Current Describe legendary artifacts like ‘The Aetherflame Prism’ 🧙‍♂️
-- Research Add historical narratives and effects on wielders 🔬
-- Future AI-designed item crafting 🚀
-3. Heroic Figures
-- Current Write backstories for heroic figures like ‘Syran Stormblade’ ⚔️
-- Research Integrate figures into broader campaigns and their achievements 🔬
-- Future Procedurally generated heroes 🚀
-
-4. Immersive Dialogues and Roleplay
-1. NPC Conversations
-- Current Generate realistic NPC dialogues like in ‘The Ghostwood Forest’ 🗨️
-- Research Add depth to NPC motivations and interactions 🔬
-- Future AI-led adaptive NPC behavior 🚀
-2. Villain Confrontations
-- Current Design confrontations with unique villains like ‘Eldrazar the Timeless’ 👹
-- Research Layer villains with complex personalities and backstories 🔬
-- Future AI-driven antagonist strategy generation 🚀
-
-5. World-Building
-1. Cultural Narratives
-- Current Describe civilizations like ‘The Emberkin’ 🌋
-- Research Add societal structures and traditions 🔬
-- Future AI-created evolving societies 🚀
-2. Mythic Locations
-- Current Create locations like ‘The Whispering Wastes’ 🏜️
-- Research Integrate locations into broader world lore 🔬
-- Future Fully explorable AI worlds 🚀
-3. Dimensional Realms
-- Current Design parallel dimensions like ‘The Veil of Shadows’ 🌌
-- Research Add magical laws and inhabitants 🔬
-- Future AI-generated multiverses 🚀
-
-6. Quests and Campaigns
-1. Campaign Arcs
-- Current Design multi-part campaigns like retrieving ‘The Obsidian Crown’ 🎯
-- Research Add NPC, obstacle, and objective integration 🔬
-- Future AI-created campaign blueprints 🚀
-2. Encounter Design
-- Current Create encounters like facing ‘The Frostbane Golem’ 🧊
-- Research Add detailed strategies and reward systems 🔬
-- Future AI-led encounter simulations 🚀
-3. Legendary Betrayals
-- Current Write scenarios with plot twists, e.g., ‘Thane Vorthak’s betrayal’ 🤔
-- Research Add motivations and dramatic tension 🔬
-- Future AI-generated unpredictable twists 🚀
-
-7. AI Collaboration for Dual Perspectives
-1. Scene Duality
-- Current Generate battle scenes like adventurers vs. a Beholder 🛡️
-- Research Rewrite scenes from different perspectives 🔬
-- Future AI-enhanced multi-perspective storytelling 🚀
-2. Tag Comparison
-- Current Classify entities like MON, LOC, ART using NER tags 🏷️
-- Research Refine classifications with AI collaboration 🔬
-- Future Real-time AI entity extraction 🚀
-
-8. Experimental Storytelling Techniques
-1. Lore Fusion
-- Current Combine legends like ‘Stormcallers’ and ‘Voidseers’ 🌀
-- Research Create shared histories with dynamic lore layers 🔬
-- Future AI-driven mythos merging 🚀
-2. Procedural Creativity
-- Current Generate tables of random D&D entities 📊
-- Research Add adaptive tags for dynamic storytelling 🔬
-- Future Procedural AI entity generation 🚀
-
-9. Advanced NER Applications
-1. Custom Tags
-- Current Create tags like SPELL and TRAP for dungeon-specific entities 🔗
-- Research Train AI on niche tags for unique entity extraction 🔬
-- Future AI-driven custom tag creation 🚀
-2. Entity Extraction
-- Current Extract entities from passages like ‘The Sunken Crypts’ 🏚️
-- Research Add advanced AI classification accuracy 🔬
-- Future Automated fine-tuning for AI models 🚀
-3. Dimensional Entities
-- Current Classify niche entities like ‘Voidwalkers’ 🌠
-- Research Train models for multi-dimensional lore 🔬
-- Future AI multiverse exploration 🚀
-
-
-
-
-
-Active Multiplayer Games 2024 🎮
-
-1 Traditional MMORPGs 🗡️
-
-1.1 Major MMORPGs 🏰
-- Final Fantasy XIV Dawntrail 2024 ⚔️
-  - Advanced Job System Rework 🎭
-  - Cross Platform Integration 🎪
-  - New Housing Districts 🏘️
-
-- World of Warcraft 2024 Season 🐲
-  - Dragon Combat System 🦋
-  - Cross Faction Features ⚜️
-  - Mythic Plus Seasons 🏆
-
-- Elder Scrolls Online Gold Road 🗝️
-  - Dynamic Event System 🌟
-  - Housing Construction 🏛️
-  - Champion System 2.0 📊
-
-- Lost Ark Western T4 Update ⚡
-  - Legion Raid Content 👾
-  - Island Adventure System 🏝️
-  - Class Balance Rework 🔰
-
-- Black Desert Online Remaster 🎪
-  - Combat System Update 🎯
-  - Node Empire System 🏹
-  - Life Skill Evolution 🌳
-
-1.2 Emerging MMORPGs 🌠
-- Throne and Liberty Launch 👑
-  - Weather Combat System 🌦️
-  - Territory Wars 🗺️
-  - Transformation System 🐉
-
-- Pax Dei Medieval MMO ⚔️
-  - City Management 🏰
-  - Faith Based Magic ✨
-  - Global Trading 💎
-
-- Blue Protocol Western Release 🌌
-  - Action Combat Design 🎭
-  - Class Change System ⚡
-  - Dungeon Scaling 🗼
-
-2 Survival MMOs 🏹
-
-2.1 Established Survival 🛡️
-- Rust 2024 Updates 🦾
-  - Electricity Programming 💡
-  - Vehicle System Update 🚗
-  - Automated Defenses ⚡
-
-- ARK Survival Ascended 🦖
-  - Cross ARK System 🌐
-  - Creature Breeding 2.0 🥚
-  - Base Defense Network 🏰
-
-- DayZ 2024 Content 🧟
-  - Medical System Update 💉
-  - Disease Mechanics 🦠
-  - Base Building 2.0 🏗️
-
-- 7 Days to Die Alpha 22 🏚️
-  - Physics Engine Update 💥
-  - AI Pathfinding System 🧠
-  - Vehicle Customization 🚙
-
-2.2 New Survival MMOs 🆕
-- Once Human Launch 🧬
-  - Mutation System 🧪
-  - Base Building Tech 🏭
-  - Weather Impact System 🌪️
-
-- Nightingale Release 🌙
-  - Portal Realm System 🌌
-  - Victorian Crafting 🎩
-  - Fae World Design 🧚
-
-3 Hybrid MMOs 🎯
-
-3.1 Looter Shooters 🔫
-- Destiny 2 2024 Season 🛸
-  - Build System 3.0 🛠️
-  - Raid Mechanics ⭐
-  - Season Structure 📈
-
-- The Division 2 Year 6 🏙️
-  - Loadout Expansion 🎒
-  - Dark Zone Update 🌃
-  - Manhunt System 🎯
-
-- Warframe 2024 Update 🤖
-  - Movement Tech 2.0 🏃
-  - Mod System Rework ⚙️
-  - Open World Expansion 🌅
-
-3.2 Action RPG MMOs 💫
-- Path of Exile 2 Beta 💎
-  - Gem System Rework 💫
-  - New Skill Tree 🌲
-  - League Content 🏆
-
-- Diablo 4 Season Structure 😈
-  - Season Journey System 🎭
-  - World Boss Events 🐲
-  - PvP Territories 🗡️
-
-4 Simulation MMOs 🌍
-
-4.1 Space Simulation 🚀
-- EVE Online 2024 🛸
-  - Corporation Warfare 🏴‍☠️
-  - Market System Update 📊
-  - Fleet Operations 🚢
-
-- Elite Dangerous Update 🌌
-  - Ground Combat System 👨‍🚀
-  - Fleet Carrier Content ⭐
-  - Planet Exploration 🪐
-
-- Star Citizen Alpha 🛸
-  - Persistent Universe 🌍
-  - Ship Combat Update ⚔️
-  - Trading System 2.0 💰
-
-4.2 World Simulation 🌎
-- New World Eternal 🗺️
-  - Territory System 🏰
-  - Crafting Update 🛠️
-  - War System 2.0 ⚔️
-
-- Albion Online 2024 🏹
-  - Guild Warfare Update ⚔️
-  - Economy System 2.0 💰
-  - Territory Control 🏰
-
-5 Unique Multiplayer Games 🎲
-
-5.1 Adventure Multiplayer 🗺️
-- Sea of Thieves 2024 ⛵
-  - Ship Combat Physics 🌊
-  - Crew Management 🏴‍☠️
-  - World Events 🎪
-
-- Valheim Updates ⚡
-  - Building System 2.0 🏗️
-  - Boss Progression 👹
-  - Exploration Update 🗺️
-
-5.2 Combat Focused 🗡️
-- Mordhau 2024 ⚔️
-  - Combat Physics Update 🤺
-  - Map System Rework 🏰
-  - Tournament System 🏆
-
-- For Honor Year 8 🛡️
-  - Faction War Update ⚔️
-  - Hero Rework System 🎭
-  - Seasonal Content 🌟
-
-6 Upcoming 2024 Games 🔮
-
-6.1 Launching Soon 📅
-- Gray Zone Warfare 🎖️
-  - Tactical Systems 🎯
-  - Base Operations 🏢
-  - Territory Control 🗺️
-
-- Fractured Online 🌟
-  - City Building 🏗️
-  - Knowledge System 📚
-  - Player Economy 💰
-
-6.2 In Development 🛠️
-- Ashes of Creation 🏰
-  - Node System 🌱
-  - Castle Siege ⚔️
-  - Caravan System 🐪
-
-- Pantheon Rise of the Fallen 🌅
-  - Climate System 🌦️
-  - Group Content Focus 👥
-  - Perception System 👁️
-"""
+# --- Utility Functions ---
 
 def get_display_name(filename):
     """Extract text from parentheses or return filename as is."""
@@ -582,30 +68,19 @@ def get_time_display(filename):
 
 def sanitize_filename(text):
     """Create a safe filename from text while preserving spaces."""
-    # First replace unsafe characters with spaces
     safe_text = re.sub(r'[^\w\s-]', ' ', text)
-    # Remove any multiple spaces
     safe_text = re.sub(r'\s+', ' ', safe_text)
-    # Trim leading/trailing spaces
     safe_text = safe_text.strip()
-    return safe_text[:50]  # Limit length to 50 chars
+    return safe_text[:50]
 
 def generate_timestamp_filename(query):
     """Generate filename with format: 1103AM 11032024 (Query).md"""
-    # Get current time in Central timezone
     central = pytz.timezone('US/Central')
     current_time = datetime.now(central)
-    
-    # Format the timestamp parts
-    time_str = current_time.strftime("%I%M%p")  # 1103AM format
-    date_str = current_time.strftime("%m%d%Y")  # 11032024 format
-    
-    # Clean up the query for filename - now preserving spaces
+    time_str = current_time.strftime("%I%M%p")
+    date_str = current_time.strftime("%m%d%Y")
     safe_query = sanitize_filename(query)
-    
-    # Construct filename: "1103AM 11032024 (Input with spaces).md"
     filename = f"{time_str} {date_str} ({safe_query}).md"
-    
     return filename
 
 def delete_file(file_path):
@@ -620,8 +95,6 @@ def delete_file(file_path):
 def save_ai_interaction(query, ai_result, is_rerun=False):
     """Save AI interaction to a markdown file with new filename format."""
     filename = generate_timestamp_filename(query)
-    
-    # Format the content differently for rerun vs normal query
     if is_rerun:
         content = f"""# Rerun Query
 Original file content used for rerun:
@@ -637,8 +110,6 @@ Original file content used for rerun:
 ## AI Response
 {ai_result}
 """
-    
-    # Save to file
     try:
         with open(filename, 'w', encoding='utf-8') as f:
             f.write(content)
@@ -659,50 +130,139 @@ def get_file_download_link(file_path):
         st.error(f"Error creating download link: {e}")
         return None
 
-def extract_terms(markdown_text):
-    """Parse markdown text and extract terms."""
-    lines = markdown_text.strip().split('\n')
-    terms = []
+# --- New Functions for Markdown File Parsing and Link Tree ---
+
+def clean_item_text(line):
+    """
+    Remove emoji and numbered prefix from a line.
+    E.g., "🔧 1. Low-level system integrations compilers Cplusplus" becomes
+    "Low-level system integrations compilers Cplusplus".
+    Also remove any bold markdown markers.
+    """
+    # Remove leading emoji and number+period
+    cleaned = re.sub(r'^[^\w]*(\d+\.\s*)', '', line)
+    # Remove any remaining emoji (simple unicode range) and ** markers
+    cleaned = re.sub(r'[\U0001F300-\U0001FAFF]', '', cleaned)
+    cleaned = cleaned.replace("**", "")
+    return cleaned.strip()
+
+def clean_header_text(header_line):
+    """
+    Extract header text from a markdown header line.
+    E.g., "🔧 **Systems, Infrastructure & Low-Level Engineering**" becomes
+    "Systems, Infrastructure & Low-Level Engineering".
+    """
+    match = re.search(r'\*\*(.*?)\*\*', header_line)
+    if match:
+        return match.group(1).strip()
+    return header_line.strip()
+
+def parse_markdown_sections(md_text):
+    """
+    Parse markdown text into sections.
+    Each section starts with a header line containing bold text.
+    Returns a list of dicts with keys: 'header' and 'items' (list of lines).
+    Skips any content before the first header.
+    """
+    sections = []
+    current_section = None
+    lines = md_text.splitlines()
     for line in lines:
-        line = re.sub(r'^[#*\->\d\.\s]+', '', line).strip()
-        if line:
-            terms.append(line)
-    return terms
+        if line.strip() == "":
+            continue
+        # Check if line is a header (contains bold markdown and an emoji)
+        if '**' in line:
+            header = clean_header_text(line)
+            current_section = {'header': header, 'raw': line, 'items': []}
+            sections.append(current_section)
+        elif current_section is not None:
+            # Only add lines that appear to be list items (start with an emoji and number)
+            if re.match(r'^[^\w]*\d+\.\s+', line):
+                current_section['items'].append(line)
+            else:
+                if current_section['items']:
+                    current_section['items'][-1] += " " + line.strip()
+                else:
+                    current_section['items'].append(line)
+    return sections
+
+def display_section_items(items):
+    """
+    Display list of items as links.
+    For each item, clean the text and generate search links using your original link set.
+    """
+    search_urls = {
+        "📚📖ArXiv": lambda k: f"/?q={quote(k)}",            
+        "🔮<sup>Google</sup>": lambda k: f"https://www.google.com/search?q={quote(k)}",    
+        "📺<sup>Youtube</sup>": lambda k: f"https://www.youtube.com/results?search_query={quote(k)}", 
+        "🔭<sup>Bing</sup>": lambda k: f"https://www.bing.com/search?q={quote(k)}",        
+        "💡<sup>Truth</sup>": lambda k: f"https://truthsocial.com/search?q={quote(k)}",    
+        "📱X": lambda k: f"https://twitter.com/search?q={quote(k)}",
+    }
+    for item in items:
+        cleaned_text = clean_item_text(item)
+        links_md = ' '.join([f"[{emoji}]({url(cleaned_text)})" for emoji, url in search_urls.items()])
+        st.markdown(f"- **{cleaned_text}** {links_md}", unsafe_allow_html=True)
+
+def display_markdown_tree():
+    """
+    Allow user to upload a .md file or load README.md.
+    Parse the markdown into sections and display each section in a collapsed expander
+    with the original markdown and a link tree of items.
+    """
+    st.markdown("## Markdown Tree Parser")
+    uploaded_file = st.file_uploader("Upload a Markdown file", type=["md"])
+    if uploaded_file is not None:
+        md_content = uploaded_file.read().decode("utf-8")
+    else:
+        if os.path.exists("README.md"):
+            with open("README.md", "r", encoding="utf-8") as f:
+                md_content = f.read()
+        else:
+            st.info("No Markdown file uploaded and README.md not found.")
+            return
 
-def extract_urls(text):
-    try:
-        date_pattern = re.compile(r'### (\d{2} \w{3} \d{4})')
-        abs_link_pattern = re.compile(r'\[(.*?)\]\((https://arxiv\.org/abs/\d+\.\d+)\)')
-        pdf_link_pattern = re.compile(r'\[⬇️\]\((https://arxiv\.org/pdf/\d+\.\d+)\)')
-        title_pattern = re.compile(r'### \d{2} \w{3} \d{4} \| \[(.*?)\]')
-        date_matches = date_pattern.findall(text)
-        abs_link_matches = abs_link_pattern.findall(text)
-        pdf_link_matches = pdf_link_pattern.findall(text)
-        title_matches = title_pattern.findall(text)
-
-        # markdown with the extracted fields
-        markdown_text = ""
-        for i in range(len(date_matches)):
-            date = date_matches[i]
-            title = title_matches[i]
-            abs_link = abs_link_matches[i][1]
-            pdf_link = pdf_link_matches[i]
-            markdown_text += f"**Date:** {date}\n\n"
-            markdown_text += f"**Title:** {title}\n\n"
-            markdown_text += f"**Abstract Link:** [{abs_link}]({abs_link})\n\n"
-            markdown_text += f"**PDF Link:** [{pdf_link}]({pdf_link})\n\n"
-            markdown_text += "---\n\n"
-        return markdown_text
-    
-    except:
-        st.write('.')
-        return ''
+    sections = parse_markdown_sections(md_content)
+    if not sections:
+        st.info("No sections found in the markdown file.")
+        return
+
+    for sec in sections:
+        with st.expander(sec['header'], expanded=False):
+            st.markdown(f"**Original Markdown:**\n\n{sec['raw']}\n")
+            if sec['items']:
+                st.markdown("**Link Tree:**")
+                display_section_items(sec['items'])
+            else:
+                st.write("No items found in this section.")
 
+# --- Existing AI and File Management Functions ---
+
+def search_arxiv(query):
+    st.write("Performing AI Lookup...")
+    client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
+    result1 = client.predict(
+        prompt=query,
+        llm_model_picked="mistralai/Mixtral-8x7B-Instruct-v0.1",
+        stream_outputs=True,
+        api_name="/ask_llm"
+    )
+    st.markdown("### Mixtral-8x7B-Instruct-v0.1 Result")
+    st.markdown(result1)
+    result2 = client.predict(
+        prompt=query,
+        llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
+        stream_outputs=True,
+        api_name="/ask_llm"
+    )
+    st.markdown("### Mistral-7B-Instruct-v0.2 Result")
+    st.markdown(result2)
+    combined_result = f"{result1}\n\n{result2}"
+    return combined_result
 
-# HTML5 based Speech Synthesis (Text to Speech in Browser)
 @st.cache_resource
 def SpeechSynthesis(result):
-    documentHTML5='''
+    documentHTML5 = '''
     <!DOCTYPE html>
     <html>
     <head>
@@ -719,8 +279,8 @@ def SpeechSynthesis(result):
         <h1>🔊 Read It Aloud</h1>
         <textarea id="textArea" rows="10" cols="80">
     '''
-    documentHTML5 = documentHTML5 + result
-    documentHTML5 = documentHTML5 + '''
+    documentHTML5 += result
+    documentHTML5 += '''
         </textarea>
         <br>
         <button onclick="readAloud()">🔊 Read Aloud</button>
@@ -729,124 +289,20 @@ def SpeechSynthesis(result):
     '''
     components.html(documentHTML5, width=1280, height=300)
 
-def display_terms_with_links(terms):
-    """Display terms with various search links."""
-    search_urls = {
-        "📚📖ArXiv": lambda k: f"/?q={quote(k)}",            # Academic/paper theme
-        "🔮<sup>Google</sup>": lambda k: f"https://www.google.com/search?q={quote(k)}",    # Crystal ball for search
-        "📺<sup>Youtube</sup>": lambda k: f"https://www.youtube.com/results?search_query={quote(k)}", # TV for videos
-        "🔭<sup>Bing</sup>": lambda k: f"https://www.bing.com/search?q={quote(k)}",        # Telescope for search
-        "💡<sup>Truth</sup>": lambda k: f"https://truthsocial.com/search?q={quote(k)}",    # Light bulb for insight
-        "📱X": lambda k: f"https://twitter.com/search?q={quote(k)}",                        # Phone for social media
-    }
-    for term in terms:
-        links_md = ' '.join([f"[{emoji}]({url(term)})" for emoji, url in search_urls.items()])
-        st.markdown(f"- **{term}** {links_md}", unsafe_allow_html=True)
-
-def search_arxiv(query):
-    
-    st.write("Performing AI Lookup...")
-    client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
-    
-    result1 = client.predict(
-        prompt=query,
-        llm_model_picked="mistralai/Mixtral-8x7B-Instruct-v0.1",
-        stream_outputs=True,
-        api_name="/ask_llm"
-    )
-    st.markdown("### Mixtral-8x7B-Instruct-v0.1 Result")
-    st.markdown(result1)
-
-    result2 = client.predict(
-        prompt=query,
-        llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
-        stream_outputs=True,
-        api_name="/ask_llm"
-    )
-    st.markdown("### Mistral-7B-Instruct-v0.2 Result")
-    st.markdown(result2)
-    combined_result = f"{result1}\n\n{result2}"
-    #return combined_result
-
-    return responseall
-
-# Function to generate a filename based on prompt and time (because names matter 🕒)
-def generate_filename(prompt, file_type):
-    central = pytz.timezone('US/Central')
-    safe_date_time = datetime.now(central).strftime("%m%d_%H%M")
-    safe_prompt = re.sub(r'\W+', '_', prompt)[:90]
-    return f"{safe_date_time}_{safe_prompt}.{file_type}"
-
-# Function to create and save a file (and avoid the black hole of lost data 🕳)
-def create_file(filename, prompt, response):
-    with open(filename, 'w', encoding='utf-8') as file:
-        file.write(prompt + "\n\n" + response)
-
-    
-
-def perform_ai_lookup(query):
-    start_time = time.strftime("%Y-%m-%d %H:%M:%S")
-    client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
-    response1 = client.predict(
-        query,
-        20,
-        "Semantic Search",
-        "mistralai/Mixtral-8x7B-Instruct-v0.1",
-        api_name="/update_with_rag_md"
-    )
-    Question = '### 🔎 ' + query + '\r\n'  # Format for markdown display with links
-    References =  response1[0]  
-    ReferenceLinks = extract_urls(References)
-
-    RunSecondQuery = True
-    results=''
-    if RunSecondQuery:
-        # Search 2 - Retrieve the Summary with Papers Context and Original Query
-        response2 = client.predict(
-            query,
-            "mistralai/Mixtral-8x7B-Instruct-v0.1",
-            True,
-            api_name="/ask_llm"
-        )
-        if len(response2) > 10:
-            Answer = response2
-            SpeechSynthesis(Answer)
-            # Restructure results to follow format of Question, Answer, References, ReferenceLinks
-            results = Question + '\r\n' + Answer + '\r\n' + References + '\r\n' + ReferenceLinks
-            st.markdown(results)
-
-    st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
-    end_time = time.strftime("%Y-%m-%d %H:%M:%S")
-    start_timestamp = time.mktime(time.strptime(start_time, "%Y-%m-%d %H:%M:%S"))
-    end_timestamp = time.mktime(time.strptime(end_time, "%Y-%m-%d %H:%M:%S"))
-    elapsed_seconds = end_timestamp - start_timestamp
-    st.write(f"Start time: {start_time}")
-    st.write(f"Finish time: {end_time}")
-    st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
-
-    
-    filename = generate_filename(query, "md")
-    create_file(filename, query, results)
-    return results
-
 def display_file_content(file_path):
     """Display file content with editing capabilities."""
     try:
         with open(file_path, 'r', encoding='utf-8') as f:
             content = f.read()
-        
         if st.session_state.view_mode == 'view':
-            # Display as markdown when viewing
             st.markdown(content)
         else:
-            # Edit functionality
             edited_content = st.text_area(
                 "Edit content",
                 content,
                 height=400,
                 key=f"edit_{os.path.basename(file_path)}"
             )
-            
             if st.button("Save Changes", key=f"save_{os.path.basename(file_path)}"):
                 try:
                     with open(file_path, 'w', encoding='utf-8') as f:
@@ -860,62 +316,43 @@ def display_file_content(file_path):
 def file_management_sidebar():
     """Redesigned sidebar with improved layout and additional functionality."""
     st.sidebar.title("📁 File Management")
-
-    # Get list of .md files excluding README.md
     md_files = [file for file in glob.glob("*.md") if file.lower() != 'readme.md']
     md_files.sort()
     st.session_state.files = md_files
-    
     if md_files:
         st.sidebar.markdown("### Saved Files")
         for idx, file in enumerate(md_files):
-            st.sidebar.markdown("---")  # Separator between files
-            
-            # Display time
+            st.sidebar.markdown("---")
             st.sidebar.text(get_time_display(file))
-            
-            # Display download link with simplified text
             download_link = get_file_download_link(file)
             if download_link:
                 st.sidebar.markdown(download_link, unsafe_allow_html=True)
-            
-            # Action buttons in a row
             col1, col2, col3, col4 = st.sidebar.columns(4)
-            
             with col1:
                 if st.button("📄View", key=f"view_{idx}"):
                     st.session_state.selected_file = file
                     st.session_state.view_mode = 'view'
-            
             with col2:
                 if st.button("✏️Edit", key=f"edit_{idx}"):
                     st.session_state.selected_file = file
                     st.session_state.view_mode = 'edit'
-            
             with col3:
                 if st.button("🔄Run", key=f"rerun_{idx}"):
                     try:
                         with open(file, 'r', encoding='utf-8') as f:
                             content = f.read()
-                            
-                        # Prepare the prompt with the prefix
                         rerun_prefix = """For the markdown below reduce the text to a humorous fun outline with emojis and markdown outline levels in outline that convey all the facts and adds wise quotes and funny statements to engage the reader:
 
 """
                         full_prompt = rerun_prefix + content
-                        
-                        # Perform AI lookup and save results
                         ai_result = perform_ai_lookup(full_prompt)
                         saved_file = save_ai_interaction(content, ai_result, is_rerun=True)
-                        
                         if saved_file:
                             st.success(f"Created fun version in {saved_file}")
                             st.session_state.selected_file = saved_file
                             st.session_state.view_mode = 'view'
-                            
                     except Exception as e:
                         st.error(f"Error during rerun: {e}")
-            
             with col4:
                 if st.button("🗑️Delete", key=f"delete_{idx}"):
                     if delete_file(file):
@@ -923,9 +360,7 @@ def file_management_sidebar():
                         st.rerun()
                     else:
                         st.error(f"Failed to delete {file}")
-
         st.sidebar.markdown("---")
-        # Option to create a new markdown file
         if st.sidebar.button("📝 Create New Note"):
             filename = generate_timestamp_filename("New Note")
             with open(filename, 'w', encoding='utf-8') as f:
@@ -943,22 +378,68 @@ def file_management_sidebar():
             st.session_state.selected_file = filename
             st.session_state.view_mode = 'edit'
 
+def perform_ai_lookup(query):
+    start_time = time.strftime("%Y-%m-%d %H:%M:%S")
+    client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
+    response1 = client.predict(
+        query,
+        20,
+        "Semantic Search",
+        "mistralai/Mixtral-8x7B-Instruct-v0.1",
+        api_name="/update_with_rag_md"
+    )
+    Question = '### 🔎 ' + query + '\r\n'
+    References =  response1[0]
+    ReferenceLinks = ""
+    results = ""
+    RunSecondQuery = True
+    if RunSecondQuery:
+        response2 = client.predict(
+            query,
+            "mistralai/Mixtral-8x7B-Instruct-v0.1",
+            True,
+            api_name="/ask_llm"
+        )
+        if len(response2) > 10:
+            Answer = response2
+            SpeechSynthesis(Answer)
+            results = Question + '\r\n' + Answer + '\r\n' + References + '\r\n' + ReferenceLinks
+            st.markdown(results)
+    st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
+    end_time = time.strftime("%Y-%m-%d %H:%M:%S")
+    start_timestamp = time.mktime(time.strptime(start_time, "%Y-%m-%d %H:%M:%S"))
+    end_timestamp = time.mktime(time.strptime(end_time, "%Y-%m-%d %H:%M:%S"))
+    elapsed_seconds = end_timestamp - start_timestamp
+    st.write(f"Start time: {start_time}")
+    st.write(f"Finish time: {end_time}")
+    st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
+    filename = generate_filename(query, "md")
+    create_file(filename, query, results)
+    return results
+
+def generate_filename(prompt, file_type):
+    central = pytz.timezone('US/Central')
+    safe_date_time = datetime.now(central).strftime("%m%d_%H%M")
+    safe_prompt = re.sub(r'\W+', '_', prompt)[:90]
+    return f"{safe_date_time}_{safe_prompt}.{file_type}"
+
+def create_file(filename, prompt, response):
+    with open(filename, 'w', encoding='utf-8') as file:
+        file.write(prompt + "\n\n" + response)
+
+# --- Main Application ---
+
 def main():
     st.markdown("### AI Knowledge Tree Builder 🧠🌱 Cultivate Your AI Mindscape!")
-
-    # Process query parameters and AI lookup first
     query_params = st.query_params
     query = query_params.get('q', '')
-    show_initial_content = True  # Flag to control initial content display
+    show_initial_content = True
     
-    # First priority: Handle active query
     if query:
-        show_initial_content = False  # Hide initial content when showing query results
+        show_initial_content = False
         st.write(f"### Search query received: {query}")
         try:
             ai_result = perform_ai_lookup(query)
-            
-            # Save the interaction
             saved_file = save_ai_interaction(query, ai_result)
             if saved_file:
                 st.success(f"Saved interaction to {saved_file}")
@@ -967,12 +448,10 @@ def main():
         except Exception as e:
             st.error(f"Error during AI lookup: {e}")
 
-    # File management sidebar
     file_management_sidebar()
-
-    # Second priority: Display selected file content if any
+    
     if st.session_state.selected_file:
-        show_initial_content = False  # Hide initial content when showing file content
+        show_initial_content = False
         if os.path.exists(st.session_state.selected_file):
             st.markdown(f"### Current File: {st.session_state.selected_file}")
             display_file_content(st.session_state.selected_file)
@@ -981,35 +460,8 @@ def main():
             st.session_state.selected_file = None
             st.rerun()
 
-# Show initial content: Either when first landing or when no interactive elements are active
     if show_initial_content:
-        # First show the clickable terms with links
-        terms1 = extract_terms(AITopicsToInnovate1)
-        terms2 = extract_terms(Multiplayer_Custom_Hosting_Game_Servers_For_Simulated_Worlds)
-        terms3 = extract_terms(BiologyAndLevel36MagicUsers)
-        
-        all_terms = terms1 + terms2 + terms3
-
-        col1, col2, col3, col4, col5, col6 = st.columns(6)
-        
-        with col1:
-            st.markdown("#### AI Topics to Innovate With")
-            st.markdown(AITopicsToInnovate1)
-        with col2:
-            st.markdown("#### AI Agent Links")
-            display_terms_with_links(terms1)
-        with col3:
-            st.markdown("#### Biology Innovation with Data Science and AI Solutions")
-            st.markdown(BiologyAndLevel36MagicUsers)
-        with col4:
-            st.markdown("#### Biology Innovation Agent Links")
-            display_terms_with_links(terms3)
-        with col5:
-            st.markdown("#### Multiplayer Games and MMOs")
-            st.markdown(Multiplayer_Custom_Hosting_Game_Servers_For_Simulated_Worlds)
-        with col6:
-            st.markdown("#### Multiplayer Game and MMO Links")
-            display_terms_with_links(terms2)
+        display_markdown_tree()
 
 if __name__ == "__main__":
-    main()
+    main()