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Sleeping
| import streamlit as st | |
| import os | |
| import glob | |
| import re | |
| import base64 | |
| import pytz | |
| 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 = '🌳✨🛠️🤓' | |
| 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 | |
| } | |
| ) | |
| # 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 🎢 | |
| """ | |
| DarioAmodeiKnowledge=""" | |
| 1. Major AI Industry Players 🌐 | |
| 1. Research Leaders 🎯 | |
| - OpenAI: GPT-4 DALL-E 🔵 | |
| - Google: PaLM Gemini 🟦 | |
| - Anthropic: Claude ⚡ | |
| - Meta: LLaMA 👤 | |
| - xAI: Grok 🤖 | |
| 2. Technical AI Development 🛠️ | |
| 1. Architecture Advances 💫 | |
| - Transformer Models 🧠 | |
| - Mixture of Experts 🎪 | |
| - Sparse Architectures 🕸️ | |
| - Multi-modal Models 🌈 | |
| - Flash Attention ⚔️ | |
| 2. Training Methodologies 📚 | |
| - Supervised Fine-tuning 👨🏫 | |
| - RLHF Human Feedback 🤝 | |
| - Constitutional AI 📜 | |
| - RLAIF AI Feedback 🔄 | |
| - Synthetic Data Generation 🎲 | |
| - Chain of Thought 🧩 | |
| - Tree of Thoughts 🌳 | |
| 3. Post-Training Implementation 🔧 | |
| - Model Distillation 🧪 | |
| - Quantization 📊 | |
| - Pruning ✂️ | |
| - Knowledge Distillation 📖 | |
| - Few-shot Learning 🎯 | |
| 3. Mechanistic Interpretability 🔬 | |
| 1. Core Concepts 💡 | |
| - Neural Network Growth Patterns 🌱 | |
| - Architecture Scaffolding 🏗️ | |
| - Training Objective Guidance 🎨 | |
| - Biological System Analogies 🧬 | |
| 2. Technical Features 📐 | |
| - Linear Representations ➡️ | |
| - Vector Arithmetic 🔢 | |
| - Activation Patterns 🌊 | |
| - Feature Detection 🔍 | |
| - Sparse Autoencoders 🎭 | |
| 3. Network Analysis 🕵️ | |
| - Induction Heads 👀 | |
| - Attention Mechanisms 🎪 | |
| - Circuit Analysis 🔌 | |
| - Feature Visualization 📈 | |
| - Concept Directions 🎳 | |
| 4. Future AI Developments 🚀 | |
| 1. AGI Timeline ⏰ | |
| - 2026-2027 Capability Projections 📅 | |
| - Hardware Scaling 💾 | |
| - Data Limitations 📉 | |
| - Geopolitical Factors 🗺️ | |
| 2. Integration Fields 🎡 | |
| - Biology Research 🔮 | |
| - Drug Discovery 💊 | |
| - Clinical Trials 🏥 | |
| - Programming Automation 🤹 | |
| - Scientific Research 🧮 | |
| 5. Industry Best Practices 💎 | |
| 1. Team Building 🏢 | |
| - Talent Density Focus 👥 | |
| - Mission Alignment 🎪 | |
| - Rapid Scaling Management 📊 | |
| - Culture Development 🌟 | |
| 2. Research Qualities 🎓 | |
| - Scientific Mindset 🧭 | |
| - Experimental Approach 🗝️ | |
| - Unconventional Thinking 💫 | |
| - Rapid Testing ⚖️ | |
| 3. Safety Standards 🛡️ | |
| - Model Specifications 📋 | |
| - Behavioral Guidelines 🎮 | |
| - Ethics Implementation ⛑️ | |
| - Industry Collaboration 🤲 | |
| 6. Emerging Research Areas 🔮 | |
| 1. Technical Focus 🎯 | |
| - Long Horizon Learning ⏳ | |
| - Multi-agent Systems 👾 | |
| - Evaluation Systems 📌 | |
| - Interpretability Research 🔭 | |
| 2. Applications 💼 | |
| - Automated Science 🧫 | |
| - AI Programming Tools ⌨️ | |
| - Biological Simulation 🧯 | |
| - Clinical Applications 💉 | |
| 7. Model Intelligence 🧿 | |
| 1. System Development 🎪 | |
| - Prompt Engineering 📝 | |
| - Response Patterns ♟️ | |
| - Behavioral Modification 🎹 | |
| - Character Development 🎪 | |
| 2. User Interaction 🎭 | |
| - Autonomy Respect 🎪 | |
| - Safety Boundaries 🔒 | |
| - Communication Adaptation 🗣️ | |
| - Performance Optimization 🎢 | |
| """ | |
| # Define the markdown variables | |
| Boxing_and_MMA_Commentary_and_Knowledge = """ | |
| # Boxing and UFC Study of 1971 - 2024 The Greatest Fights History | |
| 1. In Boxing, the most heart breaking fight in Boxing was the Boom Boom Mancini fight with Duku Kim. | |
| 2. After changes to Boxing made it more safe due to the heart break. | |
| 3. Rehydration of the brain after weight ins loss preparation for a match is life saving change. | |
| 4. Fighting went from 15 rounds to 12. | |
| # UFC By Contrast.. | |
| 1. 5 Rounds of 5 Minutes each. | |
| 2. Greatest UFC Fighters: | |
| - Jon Jones could be the greatest of all time (GOAT) since he never lost. | |
| - George St. Pierre | |
| - BJ Penn | |
| - Anderson Silva | |
| - Mighty Mouse MMA's heart at 125 pounds | |
| - Kabib retired 29 and 0 | |
| - Fedor Milliano | |
| - Alex Pereira | |
| - James Tony | |
| - Randy Couture | |
| 3. You have to Judge them in their Championship Peak | |
| 4. Chris Weidman | |
| 5. Connor McGregor | |
| 6. Leg Breaking - Shin calcification and breaking baseball bats | |
| # References: | |
| 1. Joe Rogan - Interview #2219 | |
| 2. Donald J Trump | |
| """ | |
| Multiplayer_Custom_Hosting_Game_Servers_For_Simulated_Worlds = """ | |
| # Multiplayer Simulated Worlds | |
| # Farming Simulator 25 Prompt Features with Emojis: | |
| # Top Multiplayer and MMO Games 2024 | |
| ## 1. Top Multiplayer Survival & Simulation Games 2024 🎮 | |
| ### 1.1 Survival Games 🏹 | |
| - **Rust** 🦾 | |
| * Advanced Base Building Physics | |
| * Electricity & Automation Systems | |
| * Dynamic Player-driven Economy | |
| - **ARK: Survival Evolved** 🦖 | |
| * Dinosaur Taming & Breeding | |
| * Tek Tier Technology System | |
| * Cross-map Resource Networks | |
| - **Valheim** ⚔️ | |
| * Norse Mythology Building System | |
| * Boss-progression World Evolution | |
| * Structural Integrity Physics | |
| - **DayZ** 🧟 | |
| * Realistic Medical System | |
| * Dynamic Disease Mechanics | |
| * Advanced Ballistics Simulation | |
| - **7 Days to Die** 🏰 | |
| * Voxel Destruction Physics | |
| * Dynamic Horde AI System | |
| * Advanced Base Engineering | |
| ### 1.2 Simulation & Building Games 🏗️ | |
| - **Satisfactory** 🏭 | |
| * 3D Factory Automation | |
| * Vertical Building Systems | |
| * Multi-tier Production Chains | |
| - **Factorio** ⚙️ | |
| * Complex Logistics Networks | |
| * Modular Factory Design | |
| * Advanced Train Systems | |
| - **Space Engineers** 🚀 | |
| * Physics-based Construction | |
| * Programmable Block System | |
| * Zero-G Engineering | |
| - **Farming Simulator 22** 🚜 | |
| * Real Brand Machinery | |
| * Complex Production Chains | |
| * Season-based Agriculture | |
| - **Eco** 🌍 | |
| * Economic Simulation | |
| * Environmental Impact System | |
| * Government Creation Tools | |
| ## 2. Top MMO Games 2024 🌐 | |
| ### 2.1 Fantasy MMORPGs 🗡️ | |
| - **Final Fantasy XIV** ✨ | |
| * Job System Flexibility | |
| * Story-driven Content | |
| * Cross-platform Raids | |
| - **World of Warcraft** 🐲 | |
| * Dragonflight Flying System | |
| * Mythic+ Challenge System | |
| * Cross-faction Activities | |
| - **Elder Scrolls Online** 🏹 | |
| * One Tamriel Level Scaling | |
| * Housing Construction | |
| * Champion Point System | |
| - **Lost Ark** ⚔️ | |
| * Combat Skill System | |
| * Island Content System | |
| * Legion Raid Mechanics | |
| - **Black Desert Online** 🎭 | |
| * Action Combat System | |
| * Life Skill Systems | |
| * Node Management | |
| ### 2.2 Modern/Sci-Fi MMOs 🛸 | |
| - **Destiny 2** 👽 | |
| * Buildcrafting System | |
| * Raid Mechanics | |
| * Season Narrative Structure | |
| - **Star Wars: The Old Republic** 🌟 | |
| * Story Choice System | |
| * Legacy System | |
| * Companion Influence | |
| - **Warframe** 🤖 | |
| * Movement System | |
| * Frame Customization | |
| * Open World Integration | |
| - **The Division 2** 🏙️ | |
| * Cover Combat System | |
| * Dark Zone Mechanics | |
| * Recalibration System | |
| - **Path of Exile** ⚡ | |
| * Skill Gem System | |
| * Passive Tree Complexity | |
| * League Mechanics | |
| ## 3. Notable Crossplay Games 🎯 | |
| - **Minecraft** 📦 | |
| * Cross-platform Building | |
| * Redstone Engineering | |
| * Modded Servers | |
| - **Sea of Thieves** 🏴☠️ | |
| * Ship Combat Physics | |
| * Crew Coordination | |
| * World Events | |
| - **No Man's Sky** 🪐 | |
| * Procedural Planets | |
| * Base Building Network | |
| * Multiplayer Expeditions | |
| """ | |
| 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 display_terms_with_links(terms): | |
| """Display terms with various search links.""" | |
| search_urls = { | |
| "🚀🌌ArXiv": lambda k: f"/?q={quote(k)}", | |
| "📖": lambda k: f"https://en.wikipedia.org/wiki/{quote(k)}", | |
| "🔍": lambda k: f"https://www.google.com/search?q={quote(k)}", | |
| "▶️": lambda k: f"https://www.youtube.com/results?search_query={quote(k)}", | |
| "🔎": lambda k: f"https://www.bing.com/search?q={quote(k)}", | |
| "🐦": lambda k: f"https://twitter.com/search?q={quote(k)}", | |
| } | |
| 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 perform_ai_lookup(query): | |
| """Perform AI lookup using Gradio client.""" | |
| 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 | |
| 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() |