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| 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 | |
| # ๐ณ๐ค AIKnowledgeTreeBuilder - Because every app needs a good costume! | |
| Site_Name = 'AI Knowledge Tree Builder ๐๐ฟ Grow Smarter with Every Click' | |
| title = "๐ณโจAI Knowledge Tree Builder๐ ๏ธ๐ค" | |
| helpURL = 'https://huggingface.co/spaces/awacke1/AIKnowledgeTreeBuilder/' | |
| bugURL = 'https://huggingface.co/spaces/awacke1/AIKnowledgeTreeBuilder/' | |
| icons = '๐ณโจ๐ ๏ธ๐ค' | |
| SidebarOutline="""๐ณ๐ค Designed with the following tenets: | |
| 1 ๐ฑ **Portability** - Universal access via any device & link sharing | |
| 2. โก **Speed of Build** - Rapid deployments < 2min to production | |
| 3. ๐ **Linkiness** - Programmatic access to AI knowledge sources | |
| 4. ๐ฏ **Abstractive** - Core stays lean isolating high-maintenance components | |
| 5. ๐ง **Memory** - Shareable flows deep-linked research paths | |
| 6. ๐ค **Personalized** - Rapidly adapts knowledge base to user needs | |
| 7. ๐ฆ **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 ๐งช | |
| - Research Gene therapy siRNA ๐ฌ | |
| - Future Programmable genetics ๐ | |
| 2. Cell Origin | |
| - Current iPSCs organoids ๐ฆ | |
| - Research Synthetic cells ๐ฌ | |
| - Future De novo cell creation ๐ | |
| 3. Form Function | |
| - Current Bioprinting ๐ซ | |
| - Research 4D printing ๐ฌ | |
| - Future Self assembling structures ๐ | |
| 4. Homeostasis | |
| - Current Artificial pancreas ๐ค | |
| - Research Nanorobots ๐ฌ | |
| - Future Autonomous regulation ๐ | |
| 5. Evolution | |
| - Current Directed evolution ๐งซ | |
| - Research Synthetic biology ๐ฌ | |
| - Future Accelerated adaptation ๐ | |
| 6. Energy Conservation | |
| - Current Biofuel cells โก | |
| - Research Quantum biology ๐ฌ | |
| - Future Biological perpetual motion ๐ | |
| 7. Cellular Life | |
| - Current Organoid systems ๐ฎ | |
| - Research Hybrid cells ๐ฌ | |
| - Future Silicon based life ๐ | |
| 8. Inheritance Patterns | |
| - Current Gene drives ๐งฉ | |
| - Research Epigenetic control ๐ฌ | |
| - Future Designed inheritance ๐ | |
| 9. Energy Requirements | |
| - Current Metabolic engineering ๐ | |
| - Research Synthetic photosynthesis ๐ฌ | |
| - Future Zero energy life ๐ | |
| 10. Random Mutation | |
| - Current Base editing ๐ฏ | |
| - Research Mutation prediction ๐ฌ | |
| - Future Controlled evolution ๐ | |
| 11. Carbon Based Life | |
| - Current Alternative biochemistry ๐ | |
| - Research Silicon biology ๐ฌ | |
| - Future Non carbon life ๐ | |
| 12. Size Limitations | |
| - Current Nanostructures ๐ | |
| - Research Quantum biology ๐ฌ | |
| - Future Scalable organisms ๐ | |
| 13. Species Interdependence | |
| - Current Synthetic ecosystems ๐ฟ | |
| - Research Artificial symbiosis ๐ฌ | |
| - Future Independent life ๐ | |
| 14. Stimulus Response | |
| - Current Brain computer interfaces ๐ง | |
| - Research Neural engineering ๐ฌ | |
| - Future Direct consciousness control ๐ | |
| 15. Development Complexity | |
| - Current Accelerated growth ๐ฑ | |
| - Research Development control ๐ฌ | |
| - Future Instant maturation ๐ | |
| 16. Population Growth | |
| - Current Population control ๐ | |
| - Research Sustainable ecosystems ๐ฌ | |
| - Future Perfect equilibrium ๐ | |
| 17. Energy Flow | |
| - Current Enhanced photosynthesis ๐ | |
| - Research Energy optimization ๐ฌ | |
| - Future Perpetual systems ๐ | |
| 18. Environmental Adaptation | |
| - Current Climate resistance ๐ | |
| - Research Universal adaptation ๐ฌ | |
| - Future Environment independence ๐ | |
| 19. Genetic Inheritance | |
| - Current Gene editing ๐งฌ | |
| - Research Trait programming ๐ฌ | |
| - Future Perfect inheritance ๐ | |
| 20. Reproduction | |
| - Current Artificial wombs ๐ถ | |
| - Research Cloning advances ๐ฌ | |
| - Future Asexual human reproduction ๐ | |
| 21. Aging Death | |
| - Current Longevity therapy โฐ | |
| - Research Age reversal ๐ฌ | |
| - Future Biological immortality ๐ | |
| """ | |
| AITopicsToInnovate1=""" | |
| 1. Major AI Industry Players ๐ | |
| 1. Research Leaders ๐ฏ | |
| - OpenAI: GPT-4 DALL-E Foundation Models ๐ต | |
| - Google: PaLM Gemini LLMs ๐ฆ | |
| - Anthropic: Claude Constitutional AI โก | |
| - Meta: LLaMA Open Source LLMs ๐ค | |
| - xAI: Grok Conversational AI ๐ค | |
| 2. Technical AI Development ๐ ๏ธ | |
| 1. Architecture Advances ๐ซ | |
| - Transformer Models Attention Mechanisms ๐ง | |
| - Mixture of Experts MoE Architecture ๐ช | |
| - Sparse Neural Networks ๐ธ๏ธ | |
| - Multi-modal LLM Systems ๐ | |
| - Flash Attention Optimization โ๏ธ | |
| 2. Training Methodologies ๐ | |
| - LLM Supervised Fine-tuning ๐จโ๐ซ | |
| - RLHF Reward Models ๐ค | |
| - Constitutional AI Training ๐ | |
| - RLAIF Feedback Models ๐ | |
| - Synthetic Data LLM Training ๐ฒ | |
| - Chain of Thought Prompting ๐งฉ | |
| - Tree of Thoughts Reasoning ๐ณ | |
| 3. Post-Training Implementation ๐ง | |
| - Neural Network Distillation ๐งช | |
| - LLM Quantization Methods ๐ | |
| - Neural Network Pruning โ๏ธ | |
| - Knowledge Distillation Transfer ๐ | |
| - Few-shot LLM Learning ๐ฏ | |
| 3. Mechanistic Interpretability ๐ฌ | |
| 1. Core Concepts ๐ก | |
| - Neural Network Growth Analysis ๐ฑ | |
| - LLM Architecture Analysis ๐๏ธ | |
| - Training Loss Optimization ๐จ | |
| - Neural Network Analogies ๐งฌ | |
| 2. Technical Features ๐ | |
| - LLM Linear Representations โก๏ธ | |
| - Neural Vector Arithmetic ๐ข | |
| - Neural Activation Patterns ๐ | |
| - LLM Feature Detection ๐ | |
| - Neural Sparse Autoencoders ๐ญ | |
| 3. Network Analysis ๐ต๏ธ | |
| - LLM Induction Heads ๐ | |
| - Transformer Attention Analysis ๐ช | |
| - Neural Circuit Analysis ๐ | |
| - LLM Feature Visualization ๐ | |
| - Neural Concept Directions ๐ณ | |
| 4. Future AI Developments ๐ | |
| 1. AGI Timeline โฐ | |
| - AGI Capability Projections ๐ | |
| - Neural Hardware Scaling ๐พ | |
| - LLM Training Data Limits ๐ | |
| - AI Compute Resources ๐บ๏ธ | |
| 2. Integration Fields ๐ก | |
| - AI Biology Integration ๐ฎ | |
| - AI Drug Discovery Systems ๐ | |
| - AI Clinical Trial Analysis ๐ฅ | |
| - AI Code Generation ๐คน | |
| - AI Scientific Discovery ๐งฎ | |
| 5. Industry Best Practices ๐ | |
| 1. AI Team Building ๐ข | |
| - AI Talent Development ๐ฅ | |
| - AI Research Alignment ๐ช | |
| - AI Team Scaling ๐ | |
| - AI Research Culture ๐ | |
| 2. AI Research Qualities ๐ | |
| - AI Research Methodology ๐งญ | |
| - AI Experimentation Protocols ๐๏ธ | |
| - AI Innovation Thinking ๐ซ | |
| - AI Testing Framework โ๏ธ | |
| 3. AI Safety Standards ๐ก๏ธ | |
| - LLM Behavioral Specifications ๐ | |
| - AI Safety Guidelines ๐ฎ | |
| - AI Ethics Framework โ๏ธ | |
| - AI Industry Standards ๐คฒ | |
| 6. Emerging Research Areas ๐ฎ | |
| 1. Technical Focus ๐ฏ | |
| - LLM Long Context Learning โณ | |
| - LLM Multi-agent Interaction ๐พ | |
| - AI Evaluation Metrics ๐ | |
| - Neural Interpretability Methods ๐ญ | |
| 2. AI Applications ๐ผ | |
| - AI Automated Research ๐งซ | |
| - AI Code Synthesis โจ๏ธ | |
| - AI Biological Modeling ๐งฏ | |
| - AI Medical Diagnostics ๐ | |
| 7. Model Intelligence ๐งฟ | |
| 1. LLM System Development ๐ช | |
| - LLM Prompt Engineering ๐ | |
| - LLM Response Generation โ๏ธ | |
| - LLM Behavioral Training ๐น | |
| - LLM Personality Development ๐ช | |
| 2. LLM User Interaction ๐ญ | |
| - LLM Autonomy Alignment ๐ช | |
| - LLM Safety Boundaries ๐ | |
| - LLM Communication Patterns ๐ฃ๏ธ | |
| - LLM Performance Tuning ๐ข | |
| """ | |
| 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 ๐๏ธ | |
| - Research Add domain-specific entities like mythical creatures, enchanted terrains, or ancient artifacts ๐งโโ๏ธ | |
| - Future Fully AI-generated interactive worldbuilding ๐ | |
| 2. Archetypal Overview | |
| - Current Write a summary of a classic D&D character archetype ๐ก๏ธ | |
| - Research Add roles, special abilities, and motivations for NPC creation ๐ฎ | |
| - Future AI-enhanced roleplay character dynamics ๐ | |
| 3. Entity-Focused Narrative Creation | |
| 1. Monster Mythology | |
| - Current Create monsters with unique traits like โCrimson Obelisk Wurmโ ๐ | |
| - Research Add lore and origin stories with detailed classifications ๐ฌ | |
| - Future Dynamic AI monster lore generators ๐ | |
| 2. Artifact Legacy | |
| - Current Describe legendary artifacts like โThe Aetherflame Prismโ ๐งโโ๏ธ | |
| - Research Add historical narratives and effects on wielders ๐ฌ | |
| - Future AI-designed item crafting ๐ | |
| 3. Heroic Figures | |
| - Current Write backstories for heroic figures like โSyran Stormbladeโ โ๏ธ | |
| - Research Integrate figures into broader campaigns and their achievements ๐ฌ | |
| - Future Procedurally generated heroes ๐ | |
| 4. Immersive Dialogues and Roleplay | |
| 1. NPC Conversations | |
| - Current Generate realistic NPC dialogues like in โThe Ghostwood Forestโ ๐จ๏ธ | |
| - Research Add depth to NPC motivations and interactions ๐ฌ | |
| - Future AI-led adaptive NPC behavior ๐ | |
| 2. Villain Confrontations | |
| - Current Design confrontations with unique villains like โEldrazar the Timelessโ ๐น | |
| - Research Layer villains with complex personalities and backstories ๐ฌ | |
| - Future AI-driven antagonist strategy generation ๐ | |
| 5. World-Building | |
| 1. Cultural Narratives | |
| - Current Describe civilizations like โThe Emberkinโ ๐ | |
| - Research Add societal structures and traditions ๐ฌ | |
| - Future AI-created evolving societies ๐ | |
| 2. Mythic Locations | |
| - Current Create locations like โThe Whispering Wastesโ ๐๏ธ | |
| - Research Integrate locations into broader world lore ๐ฌ | |
| - Future Fully explorable AI worlds ๐ | |
| 3. Dimensional Realms | |
| - Current Design parallel dimensions like โThe Veil of Shadowsโ ๐ | |
| - Research Add magical laws and inhabitants ๐ฌ | |
| - Future AI-generated multiverses ๐ | |
| 6. Quests and Campaigns | |
| 1. Campaign Arcs | |
| - Current Design multi-part campaigns like retrieving โThe Obsidian Crownโ ๐ฏ | |
| - Research Add NPC, obstacle, and objective integration ๐ฌ | |
| - Future AI-created campaign blueprints ๐ | |
| 2. Encounter Design | |
| - Current Create encounters like facing โThe Frostbane Golemโ ๐ง | |
| - Research Add detailed strategies and reward systems ๐ฌ | |
| - Future AI-led encounter simulations ๐ | |
| 3. Legendary Betrayals | |
| - Current Write scenarios with plot twists, e.g., โThane Vorthakโs betrayalโ ๐ค | |
| - Research Add motivations and dramatic tension ๐ฌ | |
| - Future AI-generated unpredictable twists ๐ | |
| 7. AI Collaboration for Dual Perspectives | |
| 1. Scene Duality | |
| - Current Generate battle scenes like adventurers vs. a Beholder ๐ก๏ธ | |
| - Research Rewrite scenes from different perspectives ๐ฌ | |
| - Future AI-enhanced multi-perspective storytelling ๐ | |
| 2. Tag Comparison | |
| - Current Classify entities like MON, LOC, ART using NER tags ๐ท๏ธ | |
| - Research Refine classifications with AI collaboration ๐ฌ | |
| - Future Real-time AI entity extraction ๐ | |
| 8. Experimental Storytelling Techniques | |
| 1. Lore Fusion | |
| - Current Combine legends like โStormcallersโ and โVoidseersโ ๐ | |
| - Research Create shared histories with dynamic lore layers ๐ฌ | |
| - Future AI-driven mythos merging ๐ | |
| 2. Procedural Creativity | |
| - Current Generate tables of random D&D entities ๐ | |
| - Research Add adaptive tags for dynamic storytelling ๐ฌ | |
| - Future Procedural AI entity generation ๐ | |
| 9. Advanced NER Applications | |
| 1. Custom Tags | |
| - Current Create tags like SPELL and TRAP for dungeon-specific entities ๐ | |
| - Research Train AI on niche tags for unique entity extraction ๐ฌ | |
| - Future AI-driven custom tag creation ๐ | |
| 2. Entity Extraction | |
| - Current Extract entities from passages like โThe Sunken Cryptsโ ๐๏ธ | |
| - Research Add advanced AI classification accuracy ๐ฌ | |
| - Future Automated fine-tuning for AI models ๐ | |
| 3. Dimensional Entities | |
| - Current Classify niche entities like โVoidwalkersโ ๐ | |
| - Research Train models for multi-dimensional lore ๐ฌ | |
| - Future AI multiverse exploration ๐ | |
| Active Multiplayer Games 2024 ๐ฎ | |
| 1 Traditional MMORPGs ๐ก๏ธ | |
| 1.1 Major MMORPGs ๐ฐ | |
| - Final Fantasy XIV Dawntrail 2024 โ๏ธ | |
| - Advanced Job System Rework ๐ญ | |
| - Cross Platform Integration ๐ช | |
| - New Housing Districts ๐๏ธ | |
| - World of Warcraft 2024 Season ๐ฒ | |
| - Dragon Combat System ๐ฆ | |
| - Cross Faction Features โ๏ธ | |
| - Mythic Plus Seasons ๐ | |
| - Elder Scrolls Online Gold Road ๐๏ธ | |
| - Dynamic Event System ๐ | |
| - Housing Construction ๐๏ธ | |
| - Champion System 2.0 ๐ | |
| - Lost Ark Western T4 Update โก | |
| - Legion Raid Content ๐พ | |
| - Island Adventure System ๐๏ธ | |
| - Class Balance Rework ๐ฐ | |
| - Black Desert Online Remaster ๐ช | |
| - Combat System Update ๐ฏ | |
| - Node Empire System ๐น | |
| - Life Skill Evolution ๐ณ | |
| 1.2 Emerging MMORPGs ๐ | |
| - Throne and Liberty Launch ๐ | |
| - Weather Combat System ๐ฆ๏ธ | |
| - Territory Wars ๐บ๏ธ | |
| - Transformation System ๐ | |
| - Pax Dei Medieval MMO โ๏ธ | |
| - City Management ๐ฐ | |
| - Faith Based Magic โจ | |
| - Global Trading ๐ | |
| - Blue Protocol Western Release ๐ | |
| - Action Combat Design ๐ญ | |
| - Class Change System โก | |
| - Dungeon Scaling ๐ผ | |
| 2 Survival MMOs ๐น | |
| 2.1 Established Survival ๐ก๏ธ | |
| - Rust 2024 Updates ๐ฆพ | |
| - Electricity Programming ๐ก | |
| - Vehicle System Update ๐ | |
| - Automated Defenses โก | |
| - ARK Survival Ascended ๐ฆ | |
| - Cross ARK System ๐ | |
| - Creature Breeding 2.0 ๐ฅ | |
| - Base Defense Network ๐ฐ | |
| - DayZ 2024 Content ๐ง | |
| - Medical System Update ๐ | |
| - Disease Mechanics ๐ฆ | |
| - Base Building 2.0 ๐๏ธ | |
| - 7 Days to Die Alpha 22 ๐๏ธ | |
| - Physics Engine Update ๐ฅ | |
| - AI Pathfinding System ๐ง | |
| - Vehicle Customization ๐ | |
| 2.2 New Survival MMOs ๐ | |
| - Once Human Launch ๐งฌ | |
| - Mutation System ๐งช | |
| - Base Building Tech ๐ญ | |
| - Weather Impact System ๐ช๏ธ | |
| - Nightingale Release ๐ | |
| - Portal Realm System ๐ | |
| - Victorian Crafting ๐ฉ | |
| - Fae World Design ๐ง | |
| 3 Hybrid MMOs ๐ฏ | |
| 3.1 Looter Shooters ๐ซ | |
| - Destiny 2 2024 Season ๐ธ | |
| - Build System 3.0 ๐ ๏ธ | |
| - Raid Mechanics โญ | |
| - Season Structure ๐ | |
| - The Division 2 Year 6 ๐๏ธ | |
| - Loadout Expansion ๐ | |
| - Dark Zone Update ๐ | |
| - Manhunt System ๐ฏ | |
| - Warframe 2024 Update ๐ค | |
| - Movement Tech 2.0 ๐ | |
| - Mod System Rework โ๏ธ | |
| - Open World Expansion ๐ | |
| 3.2 Action RPG MMOs ๐ซ | |
| - Path of Exile 2 Beta ๐ | |
| - Gem System Rework ๐ซ | |
| - New Skill Tree ๐ฒ | |
| - League Content ๐ | |
| - Diablo 4 Season Structure ๐ | |
| - Season Journey System ๐ญ | |
| - World Boss Events ๐ฒ | |
| - PvP Territories ๐ก๏ธ | |
| 4 Simulation MMOs ๐ | |
| 4.1 Space Simulation ๐ | |
| - EVE Online 2024 ๐ธ | |
| - Corporation Warfare ๐ดโโ ๏ธ | |
| - Market System Update ๐ | |
| - Fleet Operations ๐ข | |
| - Elite Dangerous Update ๐ | |
| - Ground Combat System ๐จโ๐ | |
| - Fleet Carrier Content โญ | |
| - Planet Exploration ๐ช | |
| - Star Citizen Alpha ๐ธ | |
| - Persistent Universe ๐ | |
| - Ship Combat Update โ๏ธ | |
| - Trading System 2.0 ๐ฐ | |
| 4.2 World Simulation ๐ | |
| - New World Eternal ๐บ๏ธ | |
| - Territory System ๐ฐ | |
| - Crafting Update ๐ ๏ธ | |
| - War System 2.0 โ๏ธ | |
| - Albion Online 2024 ๐น | |
| - Guild Warfare Update โ๏ธ | |
| - Economy System 2.0 ๐ฐ | |
| - Territory Control ๐ฐ | |
| 5 Unique Multiplayer Games ๐ฒ | |
| 5.1 Adventure Multiplayer ๐บ๏ธ | |
| - Sea of Thieves 2024 โต | |
| - Ship Combat Physics ๐ | |
| - Crew Management ๐ดโโ ๏ธ | |
| - World Events ๐ช | |
| - Valheim Updates โก | |
| - Building System 2.0 ๐๏ธ | |
| - Boss Progression ๐น | |
| - Exploration Update ๐บ๏ธ | |
| 5.2 Combat Focused ๐ก๏ธ | |
| - Mordhau 2024 โ๏ธ | |
| - Combat Physics Update ๐คบ | |
| - Map System Rework ๐ฐ | |
| - Tournament System ๐ | |
| - For Honor Year 8 ๐ก๏ธ | |
| - Faction War Update โ๏ธ | |
| - Hero Rework System ๐ญ | |
| - Seasonal Content ๐ | |
| 6 Upcoming 2024 Games ๐ฎ | |
| 6.1 Launching Soon ๐ | |
| - Gray Zone Warfare ๐๏ธ | |
| - Tactical Systems ๐ฏ | |
| - Base Operations ๐ข | |
| - Territory Control ๐บ๏ธ | |
| - Fractured Online ๐ | |
| - City Building ๐๏ธ | |
| - Knowledge System ๐ | |
| - Player Economy ๐ฐ | |
| 6.2 In Development ๐ ๏ธ | |
| - Ashes of Creation ๐ฐ | |
| - Node System ๐ฑ | |
| - Castle Siege โ๏ธ | |
| - Caravan System ๐ช | |
| - Pantheon Rise of the Fallen ๐ | |
| - Climate System ๐ฆ๏ธ | |
| - Group Content Focus ๐ฅ | |
| - Perception System ๐๏ธ | |
| """ | |
| 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'\[โฌ๏ธ\]\((https://arxiv\.org/pdf/\d+\.\d+)\)') | |
| 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) | |
| 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>๐ Read It Aloud</h1> | |
| <textarea id="textArea" rows="10" cols="80"> | |
| ''' | |
| documentHTML5 = documentHTML5 + result | |
| documentHTML5 = documentHTML5 + ''' | |
| </textarea> | |
| <br> | |
| <button onclick="readAloud()">๐ 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 = { | |
| "๐๐ArXiv": lambda k: f"/?q={quote(k)}", # Academic/paper theme | |
| "๐ฎ<sup>Google</sup>": lambda k: f"https://www.google.com/search?q={quote(k)}", # Crystal ball for search | |
| "๐บ<sup>Youtube</sup>": lambda k: f"https://www.youtube.com/results?search_query={quote(k)}", # TV for videos | |
| "๐ญ<sup>Bing</sup>": lambda k: f"https://www.bing.com/search?q={quote(k)}", # Telescope for search | |
| "๐ก<sup>Truth</sup>": lambda k: f"https://truthsocial.com/search?q={quote(k)}", # Light bulb for insight | |
| "๐ฑX": 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 ๐) | |
| 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 ๐ณ) | |
| 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 = '### ๐ ' + 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('๐Run 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("๐ 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("๐View", key=f"view_{idx}"): | |
| st.session_state.selected_file = file | |
| st.session_state.view_mode = 'view' | |
| with col2: | |
| if st.button("โ๏ธEdit", key=f"edit_{idx}"): | |
| st.session_state.selected_file = file | |
| st.session_state.view_mode = 'edit' | |
| with col3: | |
| if st.button("๐Run", 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("๐๏ธDelete", 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("๐ 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("๐ 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 ๐ง ๐ฑ 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() |