Create app.py

app.py

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+#!/usr/bin/env python3
+
+import os
+import re
+import glob
+import json
+import base64
+import zipfile
+import random
+import requests
+import openai
+from PIL import Image
+from urllib.parse import quote
+
+import streamlit as st
+import streamlit.components.v1 as components
+
+# For demonstration, we'll import from huggingface_hub
+# (You can omit if you're not using HF or adapt your own client)
+from huggingface_hub import InferenceClient
+
+# ----------------------------
+# Placeholder data structures
+# ----------------------------
+
+# Example placeholders for prompt prefixes
+PromptPrefix = "AI-Search: "
+PromptPrefix2 = "AI-Refine: "
+PromptPrefix3 = "AI-JS: "
+
+# Minimal example of a roleplaying glossary
+roleplaying_glossary = {
+    "Core Rulebooks": {
+        "Dungeons and Dragons": ["Player's Handbook", "Dungeon Master's Guide", "Monster Manual"],
+        "GURPS": ["Basic Set Characters", "Basic Set Campaigns"]
+    },
+    "Campaigns & Adventures": {
+        "Pathfinder": ["Rise of the Runelords", "Curse of the Crimson Throne"]
+    }
+}
+
+# Minimal example of a transhuman glossary
+transhuman_glossary = {
+    "Neural Interfaces": ["Cortex Jack", "Mind-Machine Fusion"],
+    "Cybernetics": ["Robotic Limbs", "Augmented Eyes"],
+}
+
+# Just to demonstrate how your "search_arxiv" or "SpeechSynthesis" etc. might be placeholders
+def process_text(text):
+    st.write(f"process_text called with: {text}")
+
+def process_text2(text_input):
+    return f"[process_text2 placeholder] Received: {text_input}"
+
+def search_arxiv(text):
+    st.write(f"search_arxiv called with: {text}")
+
+def SpeechSynthesis(text):
+    st.write(f"SpeechSynthesis called with: {text}")
+
+def process_image(image_file, prompt):
+    return f"[process_image placeholder] Processing {image_file} with prompt: {prompt}"
+
+def process_video(video_file, seconds_per_frame):
+    st.write(f"[process_video placeholder] Video: {video_file}, seconds/frame: {seconds_per_frame}")
+
+def search_glossary(content):
+    st.write(f"search_glossary called with: {content}")
+
+# If you have HF Inference endpoint, set them here, else placeholders
+API_URL = "https://huggingface-inference-endpoint-placeholder"
+API_KEY = "hf_XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
+
+@st.cache_resource
+def InferenceLLM(prompt):
+    return f"[InferenceLLM placeholder response to prompt: {prompt}]"
+
+
+# --------------------------------------
+# Display Entities & Glossary Functions
+# --------------------------------------
+@st.cache_resource
+def display_glossary_entity(k):
+    """
+    Example of how you'd create multiple links for a glossary entity.
+    This was in your original snippet. We'll keep it short.
+    """
+    search_urls = {
+        "🚀🌌ArXiv": lambda k: f"/?q={quote(k)}",
+        "🃏Analyst": lambda k: f"/?q={quote(k)}-{quote(PromptPrefix)}",
+        "📚PyCoder": lambda k: f"/?q={quote(k)}-{quote(PromptPrefix2)}",
+        "🔬JSCoder": lambda k: f"/?q={quote(k)}-{quote(PromptPrefix3)}",
+        "📖": 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.bing.com/search?q={quote(k)}",
+        "🎥": lambda k: f"https://www.youtube.com/results?search_query={quote(k)}",
+        "🐦": lambda k: f"https://twitter.com/search?q={quote(k)}",
+    }
+    links_md = ' '.join([f"[{emoji}]({url(k)})" for emoji, url in search_urls.items()])
+    st.markdown(f"**{k}** <small>{links_md}</small>", unsafe_allow_html=True)
+
+
+@st.cache_resource
+def display_glossary_grid(roleplaying_glossary):
+    """
+    Displays a glossary in columns with multiple link emojis.
+    """
+    search_urls = {
+        "🚀🌌ArXiv": lambda k: f"/?q={quote(k)}",
+        "🃏Analyst": lambda k: f"/?q={quote(k)}-{quote(PromptPrefix)}",
+        "📚PyCoder": lambda k: f"/?q={quote(k)}-{quote(PromptPrefix2)}",
+        "🔬JSCoder": lambda k: f"/?q={quote(k)}-{quote(PromptPrefix3)}",
+        "📖": 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.bing.com/search?q={quote(k)}",
+        "🎥": lambda k: f"https://www.youtube.com/results?search_query={quote(k)}",
+        "🐦": lambda k: f"https://twitter.com/search?q={quote(k)}",
+    }
+
+    for category, details in roleplaying_glossary.items():
+        st.write(f"### {category}")
+        cols = st.columns(len(details))
+        for idx, (game, terms) in enumerate(details.items()):
+            with cols[idx]:
+                st.markdown(f"#### {game}")
+                for term in terms:
+                    links_md = ' '.join([f"[{emoji}]({url(term)})" for emoji, url in search_urls.items()])
+                    st.markdown(f"**{term}** <small>{links_md}</small>", unsafe_allow_html=True)
+
+
+# --------------------
+# File-Handling Logic
+# --------------------
+def load_file(file_path):
+    try:
+        with open(file_path, "r", encoding='utf-8') as f:
+            return f.read()
+    except:
+        return ""
+
+@st.cache_resource
+def create_zip_of_files(files):
+    zip_name = "Arxiv-Paper-Search-QA-RAG-Streamlit-Gradio-AP.zip"
+    with zipfile.ZipFile(zip_name, 'w') as zipf:
+        for file in files:
+            zipf.write(file)
+    return zip_name
+
+@st.cache_resource
+def get_zip_download_link(zip_file):
+    with open(zip_file, 'rb') as f:
+        data = f.read()
+    b64 = base64.b64encode(data).decode()
+    href = f'<a href="data:application/zip;base64,{b64}" download="{zip_file}">Download All</a>'
+    return href
+
+def get_table_download_link(file_path):
+    """
+    Creates a download link for a single file from your snippet.
+    """
+    try:
+        with open(file_path, 'r', encoding='utf-8') as file:
+            data = file.read()
+        b64 = base64.b64encode(data.encode()).decode()
+        file_name = os.path.basename(file_path)
+        ext = os.path.splitext(file_name)[1]
+        mime_map = {
+            '.txt': 'text/plain',
+            '.py': 'text/plain',
+            '.xlsx': 'text/plain',
+            '.csv': 'text/plain',
+            '.htm': 'text/html',
+            '.md': 'text/markdown',
+            '.wav': 'audio/wav'
+        }
+        mime_type = mime_map.get(ext, 'application/octet-stream')
+        href = f'<a href="data:{mime_type};base64,{b64}" target="_blank" download="{file_name}">{file_name}</a>'
+        return href
+    except:
+        return ''
+
+def get_file_size(file_path):
+    return os.path.getsize(file_path)
+
+def compare_and_delete_files(files):
+    """
+    Compare file sizes. If duplicates exist, keep only the latest.
+    """
+    if not files:
+        st.warning("No files to compare.")
+        return
+    file_sizes = {}
+    for file in files:
+        size = os.path.getsize(file)
+        file_sizes.setdefault(size, []).append(file)
+    # Remove all but the latest file for each size
+    for size, paths in file_sizes.items():
+        if len(paths) > 1:
+            latest_file = max(paths, key=os.path.getmtime)
+            for file in paths:
+                if file != latest_file:
+                    os.remove(file)
+                    st.success(f"Deleted {file} as a duplicate.")
+    st.rerun()
+
+def FileSidebar():
+    """
+    Renders the file sidebar with all the open/view/run/delete logic.
+    """
+    all_files = glob.glob("*.md")
+    # Example logic filtering filenames
+    all_files = [file for file in all_files if len(os.path.splitext(file)[0]) >= 5]
+    all_files.sort(key=lambda x: (os.path.splitext(x)[1], x), reverse=True)
+
+    # Buttons for "Delete All" and "Download"
+    Files1, Files2 = st.sidebar.columns(2)
+    with Files1:
+        if st.button("🗑 Delete All"):
+            for file in all_files:
+                os.remove(file)
+            st.rerun()
+    with Files2:
+        if st.button("⬇️ Download"):
+            zip_file = create_zip_of_files(all_files)
+            st.sidebar.markdown(get_zip_download_link(zip_file), unsafe_allow_html=True)
+
+    file_contents = ''
+    file_name = ''
+    next_action = ''
+
+    # Each file row
+    for file in all_files:
+        col1, col2, col3, col4, col5 = st.sidebar.columns([1,6,1,1,1])
+        with col1:
+            # Show an emoji button to do "md"
+            if st.button("🌐", key="md_"+file):
+                file_contents = load_file(file)
+                file_name = file
+                next_action = 'md'
+                st.session_state['next_action'] = next_action
+        with col2:
+            st.markdown(get_table_download_link(file), unsafe_allow_html=True)
+        with col3:
+            if st.button("📂", key="open_"+file):
+                file_contents = load_file(file)
+                file_name = file
+                next_action = 'open'
+                st.session_state['lastfilename'] = file
+                st.session_state['filename'] = file
+                st.session_state['filetext'] = file_contents
+                st.session_state['next_action'] = next_action
+        with col4:
+            if st.button("▶️", key="read_"+file):
+                file_contents = load_file(file)
+                file_name = file
+                next_action = 'search'
+                st.session_state['next_action'] = next_action
+        with col5:
+            if st.button("🗑", key="delete_"+file):
+                os.remove(file)
+                file_name = file
+                st.rerun()
+                next_action = 'delete'
+                st.session_state['next_action'] = next_action
+
+    # Duplicate detection
+    file_sizes = [get_file_size(file) for file in all_files]
+    previous_size = None
+    st.sidebar.title("File Operations")
+    for file, size in zip(all_files, file_sizes):
+        duplicate_flag = "🚩" if size == previous_size else ""
+        with st.sidebar.expander(f"File: {file} {duplicate_flag}"):
+            st.text(f"Size: {size} bytes")
+            if st.button("View", key=f"view_{file}"):
+                try:
+                    with open(file, "r", encoding='utf-8') as f:
+                        file_content = f.read()
+                    st.code(file_content, language="markdown")
+                except UnicodeDecodeError:
+                    st.error("Failed to decode the file with UTF-8.")
+            if st.button("Delete", key=f"delete3_{file}"):
+                os.remove(file)
+                st.rerun()
+        previous_size = size
+
+    # If we have loaded something
+    if len(file_contents) > 0:
+        if next_action == 'open':
+            open1, open2 = st.columns([0.8, 0.2])
+            with open1:
+                file_name_input = st.text_input('File Name:', file_name, key='file_name_input', on_change=None)
+                file_content_area = st.text_area('File Contents:', file_contents, height=300, key='file_content_area')
+
+                # Minimal “Save” stubs
+                if st.button('💾 Save File'):
+                    with open(file_name_input, 'w', encoding='utf-8') as f:
+                        f.write(file_content_area)
+                    st.markdown(f'Saved {file_name_input} successfully.')
+
+        elif next_action == 'search':
+            # Example usage
+            file_content_area = st.text_area("File Contents:", file_contents, height=500)
+            user_prompt = PromptPrefix2 + file_contents
+            st.markdown(user_prompt)
+            if st.button('🔍Re-Code'):
+                search_arxiv(file_contents)
+
+        elif next_action == 'md':
+            st.markdown(file_contents)
+            SpeechSynthesis(file_contents)
+            if st.button('🔍Run'):
+                st.write("Running GPT logic placeholder...")
+
+# ---------------------------
+# Basic Scoring / Glossaries
+# ---------------------------
+score_dir = "scores"
+os.makedirs(score_dir, exist_ok=True)
+
+def generate_key(label, header, idx):
+    return f"{header}_{label}_{idx}_key"
+
+def update_score(key, increment=1):
+    score_file = os.path.join(score_dir, f"{key}.json")
+    if os.path.exists(score_file):
+        with open(score_file, "r") as file:
+            score_data = json.load(file)
+    else:
+        score_data = {"clicks": 0, "score": 0}
+    score_data["clicks"] += increment
+    score_data["score"] += increment
+    with open(score_file, "w") as file:
+        json.dump(score_data, file)
+    return score_data["score"]
+
+def load_score(key):
+    score_file = os.path.join(score_dir, f"{key}.json")
+    if os.path.exists(score_file):
+        with open(score_file, "r") as file:
+            score_data = json.load(file)
+        return score_data["score"]
+    return 0
+
+def display_buttons_with_scores(num_columns_text):
+    """
+    Show buttons that track a 'score' from your glossary data.
+    """
+    game_emojis = {
+        "Dungeons and Dragons": "🐉",
+        "Call of Cthulhu": "🐙",
+        "GURPS": "🎲",
+        "Pathfinder": "🗺️",
+        "Kindred of the East": "🌅",
+        "Changeling": "🍃",
+    }
+
+    topic_emojis = {
+        "Core Rulebooks": "📚",
+        "Maps & Settings": "🗺️",
+        "Game Mechanics & Tools": "⚙️",
+        "Monsters & Adversaries": "👹",
+        "Campaigns & Adventures": "📜",
+        "Creatives & Assets": "🎨",
+        "Game Master Resources": "🛠️",
+        "Lore & Background": "📖",
+        "Character Development": "🧍",
+        "Homebrew Content": "🔧",
+        "General Topics": "🌍",
+    }
+
+    for category, games in roleplaying_glossary.items():
+        category_emoji = topic_emojis.get(category, "🔍")
+        st.markdown(f"## {category_emoji} {category}")
+        for game, terms in games.items():
+            game_emoji = game_emojis.get(game, "🎮")
+            for term in terms:
+                key = f"{category}_{game}_{term}".replace(' ', '_').lower()
+                score = load_score(key)
+                if st.button(f"{game_emoji} {category} {game} {term} {score}", key=key):
+                    newscore = update_score(key.replace('?',''))
+                    st.markdown(f"Scored **{category} - {game} - {term}** -> {newscore}")
+
+# --------------------
+# Image & Video Grids
+# --------------------
+def display_images_and_wikipedia_summaries(num_columns=4):
+    """
+    Display all .png images in the current directory in a grid, referencing the name as a 'keyword'.
+    """
+    image_files = [f for f in os.listdir('.') if f.endswith('.png')]
+    if not image_files:
+        st.write("No PNG images found in the current directory.")
+        return
+
+    # Sort by length of filename, just as an example
+    image_files_sorted = sorted(image_files, key=lambda x: len(x.split('.')[0]))
+    cols = st.columns(num_columns)
+    col_index = 0
+
+    for image_file in image_files_sorted:
+        with cols[col_index % num_columns]:
+            try:
+                image = Image.open(image_file)
+                st.image(image, use_column_width=True)
+                k = image_file.split('.')[0]
+                display_glossary_entity(k)
+                # Provide a text input for user interactions
+                image_text_input = st.text_input(f"Prompt for {image_file}", key=f"image_prompt_{image_file}")
+                if len(image_text_input) > 0:
+                    response = process_image(image_file, image_text_input)
+                    st.markdown(response)
+            except:
+                st.write(f"Could not open {image_file}")
+        col_index += 1
+
+def display_videos_and_links(num_columns=4):
+    """
+    Displays all .mp4 or .webm videos found in the current directory in a grid.
+    """
+    video_files = [f for f in os.listdir('.') if f.endswith(('.mp4', '.webm'))]
+    if not video_files:
+        st.write("No MP4 or WEBM videos found in the current directory.")
+        return
+
+    video_files_sorted = sorted(video_files, key=lambda x: len(x.split('.')[0]))
+    cols = st.columns(num_columns)
+    col_index = 0
+
+    for video_file in video_files_sorted:
+        with cols[col_index % num_columns]:
+            k = video_file.split('.')[0]
+            st.video(video_file, format='video/mp4', start_time=0)
+            display_glossary_entity(k)
+            # Provide a text input
+            video_text_input = st.text_input(f"Video Prompt for {video_file}", key=f"video_prompt_{video_file}")
+            if video_text_input:
+                try:
+                    # Hard-coded example
+                    seconds_per_frame = 10
+                    process_video(video_file, seconds_per_frame)
+                except ValueError:
+                    st.error("Invalid input for seconds per frame!")
+        col_index += 1
+
+
+# -------------------------------------
+# Query Param Helpers from your snippet
+# -------------------------------------
+def get_all_query_params(key):
+    return st.query_params().get(key, [])
+
+def clear_query_params():
+    st.query_params()
+
+def display_content_or_image(query):
+    """
+    If a query matches something in transhuman_glossary or
+    a local image, show it. Otherwise warn no match.
+    """
+    for category, term_list in transhuman_glossary.items():
+        for term in term_list:
+            if query.lower() in term.lower():
+                st.subheader(f"Found in {category}:")
+                st.write(term)
+                return True
+    image_path = f"images/{query}.png"
+    if os.path.exists(image_path):
+        st.image(image_path, caption=f"Image for {query}")
+        return True
+    st.warning("No matching content or image found.")
+    return False
+
+
+# ------------------------------------
+# MERMAID DIAGRAM with Clickable Links
+# ------------------------------------
+def generate_mermaid_html(mermaid_code: str) -> str:
+    """
+    Returns HTML embedding a Mermaid diagram. We embed the code
+    in <div class="mermaid"> and center it with CSS.
+    """
+    return f"""
+    <html>
+    <head>
+        <script src="https://cdn.jsdelivr.net/npm/mermaid/dist/mermaid.min.js"></script>
+        <style>
+            .centered-mermaid {{
+                display: flex;
+                justify-content: center;
+                margin: 20px auto;
+            }}
+            .mermaid {{
+                /* Let the diagram scale or otherwise style as you wish */
+                max-width: 800px;
+            }}
+        </style>
+    </head>
+    <body>
+        <div class="mermaid centered-mermaid">
+            {mermaid_code}
+        </div>
+        <script>
+            mermaid.initialize({{ startOnLoad: true }});
+        </script>
+    </body>
+    </html>
+    """
+
+def append_model_param(url: str, model_selected: bool) -> str:
+    """
+    If 'Model' checkbox is selected, we append '&model=1' or '?model=1' to the URL.
+    We'll handle whether the URL already has a '?' or not.
+    """
+    if not model_selected:
+        return url
+    delimiter = "&" if "?" in url else "?"
+    return f"{url}{delimiter}model=1"
+
+
+# For demonstration, we add clickable nodes & edges:
+#   click <nodeId> "<URL>" "_self"
+# If you want edges to be clickable, you can label them as well,
+# but Mermaid typically only has a 'click' property for nodes.
+DEFAULT_MERMAID = """
+flowchart LR
+    %% Notice we have "click LLM ..." lines:
+    U((User 😎)) -- "Talk 🗣️" --> LLM[LLM Agent 🤖\\nExtract Info]
+    click U "/?q=User%20😎" _self
+    click LLM "/?q=LLM%20Agent%20Extract%20Info" _self
+
+    LLM -- "Query 🔍" --> HS[Hybrid Search 🔎\\nVector+NER+Lexical]
+    click HS "/?q=Hybrid%20Search%20Vector+NER+Lexical" _self
+
+    HS -- "Reason 🤔" --> RE[Reasoning Engine 🛠️\\nNeuralNetwork+Medical]
+    click RE "/?q=Reasoning%20Engine%20NeuralNetwork+Medical" _self
+
+    RE -- "Link 📡" --> KG((Knowledge Graph 📚\\nOntology+GAR+RAG))
+    click KG "/?q=Knowledge%20Graph%20Ontology+GAR+RAG" _self
+
+    %% If you want an "edge click" to pass ?r= something, 
+    %% Mermaid doesn't have direct 'click' for edges, 
+    %% but you can define them as nodes or use linkStyle trick, etc.
+"""
+
+
+# ---------------------------
+# Streamlit Main App
+# ---------------------------
+def main():
+    st.set_page_config(page_title="Mermaid + Clickable Links Demo", layout="wide")
+
+    # 1) Parse query strings on page load
+    query_params = st.experimental_get_query_params()
+    current_q = query_params.get("q", [""])[0]  # If present, first string
+    current_r = query_params.get("r", [""])[0]
+
+    # 2) Let user pick if they want to add the "model=1" param to clickable links
+    st.sidebar.write("## Diagram Link Settings")
+    model_selected = st.sidebar.checkbox("Append ?model=1 to each link?")
+
+    # 3) Generate a dynamic Mermaid code, appending model param if user wants
+    #    We'll do a simple string replace to incorporate the model param
+    #    For a robust approach, parse each URL carefully, then reassemble.
+    base_diagram = DEFAULT_MERMAID
+    lines = base_diagram.strip().split("\n")
+    new_lines = []
+    for line in lines:
+        if "click " in line and '"/?' in line:
+            # e.g. click LLM "/?q=LLM%20Agent" _self
+            # let's isolate the URL part
+            parts = re.split(r'click\s+\S+\s+"([^"]+)"\s+("_self")', line)
+            if len(parts) == 4:
+                # parts[0] = 'click LLM '
+                # parts[1] = '/?q=LLM%20Agent%20Extract%20Info'
+                # parts[2] = ' _self'
+                # parts[3] = '' (trailing possibly)
+                url = parts[1]
+                updated_url = append_model_param(url, model_selected)
+                # Recombine
+                new_line = f"{parts[0]}\"{updated_url}\" {parts[2]}"
+                new_lines.append(new_line)
+            else:
+                new_lines.append(line)
+        else:
+            new_lines.append(line)
+    mermaid_code = "\n".join(new_lines)
+
+    # 4) Render the top-centered Mermaid diagram
+    st.title("Top-Centered Mermaid Diagram with Clickable Links 🏺")
+    diagram_html = generate_mermaid_html(mermaid_code)
+    components.html(diagram_html, height=400, scrolling=True)
+
+    # 5) Show what the inbound ?q / ?r was
+    if current_q:
+        st.markdown(f"**Detected Query**: `?q={current_q}`")
+        display_content_or_image(current_q)
+    if current_r:
+        st.markdown(f"**Detected Relationship**: `?r={current_r}`")
+
+    # 6) Editor Columns: Markdown & Mermaid
+    left_col, right_col = st.columns(2)
+
+    # --- Left: Markdown Editor
+    with left_col:
+        st.subheader("Markdown Side 📝")
+        if "markdown_text" not in st.session_state:
+            st.session_state["markdown_text"] = "## Hello!\nType some *Markdown* here.\n"
+        # Text area
+        markdown_text = st.text_area(
+            "Edit Markdown:",
+            value=st.session_state["markdown_text"],
+            height=300
+        )
+        st.session_state["markdown_text"] = markdown_text
+
+        # Button row
+        colA, colB = st.columns(2)
+        with colA:
+            if st.button("🔄 Refresh Markdown"):
+                st.write("**Markdown** content refreshed! 🍿")
+        with colB:
+            if st.button("❌ Clear Markdown"):
+                st.session_state["markdown_text"] = ""
+                st.experimental_rerun()
+
+        # Display
+        st.markdown("---")
+        st.markdown("**Preview:**")
+        st.markdown(markdown_text)
+
+    # --- Right: Mermaid Editor
+    with right_col:
+        st.subheader("Mermaid Side 🧜‍♂️")
+
+        if "current_mermaid" not in st.session_state:
+            st.session_state["current_mermaid"] = mermaid_code
+
+        mermaid_input = st.text_area(
+            "Edit Mermaid Code:",
+            value=st.session_state["current_mermaid"],
+            height=300
+        )
+        colC, colD = st.columns(2)
+        with colC:
+            if st.button("🎨 Refresh Diagram"):
+                # Rebuild the diagram
+                st.session_state["current_mermaid"] = mermaid_input
+                st.write("**Mermaid** diagram refreshed! 🌈")
+                st.experimental_rerun()
+        with colD:
+            if st.button("❌ Clear Mermaid"):
+                st.session_state["current_mermaid"] = ""
+                st.experimental_rerun()
+
+        st.markdown("---")
+        st.markdown("**Mermaid Source:**")
+        st.code(mermaid_input, language="python", line_numbers=True)
+
+    # 7) Show Sliders & image/video galleries
+    st.markdown("---")
+    st.header("Media Galleries")
+
+    num_columns_images = st.slider("Choose Number of Image Columns", 1, 15, 5, key="num_columns_images")
+    display_images_and_wikipedia_summaries(num_columns_images)
+
+    num_columns_video = st.slider("Choose Number of Video Columns", 1, 15, 5, key="num_columns_video")
+    display_videos_and_links(num_columns_video)
+
+    # 8) Optional "Extended" UI
+    showExtendedTextInterface = False
+    if showExtendedTextInterface:
+        display_glossary_grid(roleplaying_glossary)
+        num_columns_text = st.slider("Choose Number of Text Columns", 1, 15, 4, key="num_columns_text")
+        display_buttons_with_scores(num_columns_text)
+        st.markdown("Extended text interface is on...")
+
+    # 9) Render the file sidebar
+    FileSidebar()
+
+    # 10) Random Title at bottom
+    titles = [
+        "🧠🎭 Semantic Symphonies & Episodic Encores",
+        "🌌🎼 AI Rhythms of Memory Lane",
+        "🎭🎉 Cognitive Crescendos & Neural Harmonies",
+        "🧠🎺 Mnemonic Melodies & Synaptic Grooves",
+        "🎼🎸 Straight Outta Cognition",
+        "🥁🎻 Jazzy Jambalaya of AI Memories",
+        "🏰 Semantic Soul & Episodic Essence",
+        "🥁🎻 The Music Of AI's Mind"
+    ]
+    selected_title = random.choice(titles)
+    st.markdown(f"**{selected_title}**")
+
+
+if __name__ == "__main__":
+    main()