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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 | |
| # 🌳🤖 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=""" | |
| This AI is designed with the following: | |
| 📱 Portability - Universal access via any device & link sharing | |
| ⚡ Speed of Build - Rapid deployments (< 2min to production) | |
| 🔗 Linkiness - Programmatic access to major AI knowledge sources | |
| 🎯 Abstractive - Core stays lean by isolating high-maintenance components | |
| 🧠 Memory - Shareable flows with deep-linked research paths | |
| 👤 Personalized - Rapidly adapts knowledge base to user needs | |
| """ | |
| 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 = [] | |
| 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 = """ | |
| # 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) | |
| 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 | |
| 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, should_save) | |
| 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("🔄 Rerun", 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.title("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) | |
| all_terms = terms1 + terms2 | |
| col1, col2, col3, col4 = st.columns(4) | |
| 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("# Multiplayer Games and MMOs") | |
| st.markdown(Multiplayer_Custom_Hosting_Game_Servers_For_Simulated_Worlds) | |
| with col4: | |
| st.markdown("# Multiplayer Game and MMO Links") | |
| display_terms_with_links(terms2) | |
| if __name__ == "__main__": | |
| main() |