backup10.app.py

import streamlit as st
import os
import glob
import re
import base64
import pytz
import time
import streamlit.components.v1 as components

from urllib.parse import quote
from gradio_client import Client
from datetime import datetime

# 🌳🤖 AIKnowledgeTreeBuilder - Because every app needs a good costume!

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:
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
4. 🎯 **Abstractive** - Core stays lean isolating high-maintenance components
5. 🧠 **Memory** - Shareable flows deep-linked research paths
6. 👤 **Personalized** - Rapidly adapts knowledge base to user needs
7. 🐦 **Living Brevity** - Easily cloneable, self modify data public share results.
"""

st.set_page_config(
    page_title=title,
    page_icon=icons,
    layout="wide",
    initial_sidebar_state="auto",
    menu_items={
        'Get Help': helpURL,
        'Report a bug': bugURL,
        'About': title
    }
)

st.sidebar.markdown(SidebarOutline)


# Initialize session state variables
if 'selected_file' not in st.session_state:
    st.session_state.selected_file = None
if 'view_mode' not in st.session_state:
    st.session_state.view_mode = 'view'
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 👁️
"""

def get_display_name(filename):
    """Extract text from parentheses or return filename as is."""
    match = re.search(r'\((.*?)\)', filename)
    if match:
        return match.group(1)
    return filename

def get_time_display(filename):
    """Extract just the time portion from the filename."""
    time_match = re.match(r'(\d{2}\d{2}[AP]M)', filename)
    if time_match:
        return time_match.group(1)
    return 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

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
    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):
    """Delete a file and return success status."""
    try:
        os.remove(file_path)
        return True
    except Exception as e:
        st.error(f"Error deleting file: {e}")
        return False

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:

{query}

# AI Response (Fun Version)
{ai_result}
"""
    else:
        content = f"""# Query: {query}

## AI Response
{ai_result}
"""
    
    # Save to file
    try:
        with open(filename, 'w', encoding='utf-8') as f:
            f.write(content)
        return filename
    except Exception as e:
        st.error(f"Error saving file: {e}")
        return None

def get_file_download_link(file_path):
    """Generate a base64 download link for a file."""
    try:
        with open(file_path, 'r', encoding='utf-8') as f:
            content = f.read()
        b64 = base64.b64encode(content.encode()).decode()
        filename = os.path.basename(file_path)
        return f'<a href="data:text/markdown;base64,{b64}" download="{filename}">{get_display_name(filename)}</a>'
    except Exception as e:
        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 = []
    for line in lines:
        line = re.sub(r'^[#*\->\d\.\s]+', '', line).strip()
        if line:
            terms.append(line)
    return terms

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 ''


# HTML5 based Speech Synthesis (Text to Speech in Browser)
@st.cache_resource
def SpeechSynthesis(result):
    documentHTML5='''
    <!DOCTYPE html>
    <html>
    <head>
        <title>Read It Aloud</title>
        <script type="text/javascript">
            function readAloud() {
                const text = document.getElementById("textArea").value;
                const speech = new SpeechSynthesisUtterance(text);
                window.speechSynthesis.speak(speech);
            }
        </script>
    </head>
    <body>
        <h1>🔊 Read It Aloud</h1>
        <textarea id="textArea" rows="10" cols="80">
    '''
    documentHTML5 = documentHTML5 + result
    documentHTML5 = documentHTML5 + '''
        </textarea>
        <br>
        <button onclick="readAloud()">🔊 Read Aloud</button>
    </body>
    </html>
    '''
    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:
                        f.write(edited_content)
                    st.success(f"Successfully saved changes to {file_path}")
                except Exception as e:
                    st.error(f"Error saving changes: {e}")
    except Exception as e:
        st.error(f"Error reading file: {e}")

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.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):
                        st.success(f"Deleted {file}")
                        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:
                f.write("# New Markdown File\n")
            st.sidebar.success(f"Created: {filename}")
            st.session_state.selected_file = filename
            st.session_state.view_mode = 'edit'
    else:
        st.sidebar.write("No markdown files found.")
        if st.sidebar.button("📝 Create First Note"):
            filename = generate_timestamp_filename("New Note")
            with open(filename, 'w', encoding='utf-8') as f:
                f.write("# New Markdown File\n")
            st.sidebar.success(f"Created: {filename}")
            st.session_state.selected_file = filename
            st.session_state.view_mode = 'edit'

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
    
    # First priority: Handle active query
    if query:
        show_initial_content = False  # Hide initial content when showing query results
        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}")
                st.session_state.selected_file = saved_file
                st.session_state.view_mode = 'view'
        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
        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)
        else:
            st.error("Selected file no longer exists.")
            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)

if __name__ == "__main__":
    main()