backup11.app.py

import streamlit as st
import asyncio
import websockets
import uuid
import argparse
from datetime import datetime
import os
import random
import time
import hashlib
from PIL import Image
import glob
import base64
import io
import streamlit.components.v1 as components
import edge_tts
from audio_recorder_streamlit import audio_recorder
import nest_asyncio
import re
from streamlit_paste_button import paste_image_button
import pytz
import shutil
import anthropic
import openai
from PyPDF2 import PdfReader
import threading
import json
import zipfile
from gradio_client import Client
from dotenv import load_dotenv
from streamlit_marquee import streamlit_marquee
from collections import defaultdict, Counter
import pandas as pd

# 🛠️ Patch asyncio for nesting
nest_asyncio.apply()

# 🎨 Page Config
st.set_page_config(
    page_title="🚲TalkingAIResearcher🏆",
    page_icon="🚲🏆",
    layout="wide",
    initial_sidebar_state="auto"
)

# 🌟 Static Config
icons = '🤖🧠🔬📝'
START_ROOM = "Sector 🌌"
FUN_USERNAMES = {
    "CosmicJester 🌌": "en-US-AriaNeural",
    "PixelPanda 🐼": "en-US-JennyNeural",
    "QuantumQuack 🦆": "en-GB-SoniaNeural",
    "StellarSquirrel 🐿️": "en-AU-NatashaNeural",
    "GizmoGuru ⚙️": "en-CA-ClaraNeural",
    "NebulaNinja 🌠": "en-US-GuyNeural",
    "ByteBuster 💾": "en-GB-RyanNeural",
    "GalacticGopher 🌍": "en-AU-WilliamNeural",
    "RocketRaccoon 🚀": "en-CA-LiamNeural",
    "EchoElf 🧝": "en-US-AnaNeural",
    "PhantomFox 🦊": "en-US-BrandonNeural",
    "WittyWizard 🧙": "en-GB-ThomasNeural",
    "LunarLlama 🌙": "en-AU-FreyaNeural",
    "SolarSloth ☀️": "en-CA-LindaNeural",
    "AstroAlpaca 🦙": "en-US-ChristopherNeural",
    "CyberCoyote 🐺": "en-GB-ElliotNeural",
    "MysticMoose 🦌": "en-AU-JamesNeural",
    "GlitchGnome 🧚": "en-CA-EthanNeural",
    "VortexViper 🐍": "en-US-AmberNeural",
    "ChronoChimp 🐒": "en-GB-LibbyNeural"
}
EDGE_TTS_VOICES = list(set(FUN_USERNAMES.values()))
FILE_EMOJIS = {"md": "📝", "mp3": "🎵", "wav": "🔊"}

# 📁 Directories
for d in ["chat_logs", "vote_logs", "audio_logs", "history_logs", "media_files", "audio_cache"]:
    os.makedirs(d, exist_ok=True)

CHAT_FILE = "chat_logs/global_chat.md"
HISTORY_FILE = "history_logs/chat_history.md"
MEDIA_DIR = "media_files"
AUDIO_CACHE_DIR = "audio_cache"
AUDIO_DIR = "audio_logs"

# 🔑 API Keys
load_dotenv()
anthropic_key = os.getenv('ANTHROPIC_API_KEY', st.secrets.get('ANTHROPIC_API_KEY', ""))
openai_api_key = os.getenv('OPENAI_API_KEY', st.secrets.get('OPENAI_API_KEY', ""))
openai_client = openai.OpenAI(api_key=openai_api_key)

# 🕒 Timestamp Helper
def format_timestamp_prefix(username=""):
    central = pytz.timezone('US/Central')
    now = datetime.now(central)
    return f"{now.strftime('%Y%m%d_%H%M%S')}-by-{username}"

# 📈 Performance Timer
class PerformanceTimer:
    def __init__(self, name): self.name, self.start = name, None
    def __enter__(self): 
        self.start = time.time()
        return self
    def __exit__(self, *args): 
        duration = time.time() - self.start
        st.session_state['operation_timings'][self.name] = duration
        st.session_state['performance_metrics'][self.name].append(duration)

# 🎛️ Session State Init
def init_session_state():
    defaults = {
        'server_running': False, 'server_task': None, 'active_connections': {},
        'media_notifications': [], 'last_chat_update': 0, 'displayed_chat_lines': [],
        'message_text': "", 'audio_cache': {}, 'pasted_image_data': None,
        'quote_line': None, 'refresh_rate': 5, 'base64_cache': {},
        'transcript_history': [], 'last_transcript': "", 'image_hashes': set(),
        'tts_voice': "en-US-AriaNeural", 'chat_history': [], 'marquee_settings': {
            "background": "#1E1E1E", "color": "#FFFFFF", "font-size": "14px",
            "animationDuration": "20s", "width": "100%", "lineHeight": "35px"
        }, 'operation_timings': {}, 'performance_metrics': defaultdict(list),
        'enable_audio': True, 'download_link_cache': {}, 'username': None,
        'autosend': True, 'autosearch': True, 'last_message': "", 'last_query': "",
        'mp3_files': {}  # Store MP3s with chat lines
    }
    for k, v in defaults.items():
        if k not in st.session_state: st.session_state[k] = v

# 🖌️ Marquee Helpers
def update_marquee_settings_ui():
    st.sidebar.markdown("### 🎯 Marquee Settings")
    cols = st.sidebar.columns(2)
    with cols[0]:
        st.session_state['marquee_settings']['background'] = st.color_picker("🎨 Background", "#1E1E1E")
        st.session_state['marquee_settings']['color'] = st.color_picker("✍️ Text", "#FFFFFF")
    with cols[1]:
        st.session_state['marquee_settings']['font-size'] = f"{st.slider('📏 Size', 10, 24, 14)}px"
        st.session_state['marquee_settings']['animationDuration'] = f"{st.slider('⏱️ Speed', 1, 20, 20)}s"

def display_marquee(text, settings, key_suffix=""):
    truncated = text[:280] + "..." if len(text) > 280 else text
    streamlit_marquee(content=truncated, **settings, key=f"marquee_{key_suffix}")
    st.write("")

# 📝 Text & File Helpers
def clean_text_for_tts(text): return re.sub(r'[#*!\[\]]+', '', ' '.join(text.split()))[:200] or "No text"
def clean_text_for_filename(text): return '_'.join(re.sub(r'[^\w\s-]', '', text.lower()).split())[:200]
def get_high_info_terms(text, top_n=10):
    stop_words = {'the', 'a', 'an', 'and', 'or', 'but', 'in', 'on', 'at', 'to', 'for', 'of', 'with'}
    words = re.findall(r'\b\w+(?:-\w+)*\b', text.lower())
    bi_grams = [' '.join(pair) for pair in zip(words, words[1:])]
    filtered = [t for t in words + bi_grams if t not in stop_words and len(t.split()) <= 2]
    return [t for t, _ in Counter(filtered).most_common(top_n)]

def generate_filename(prompt, response, file_type="md"):
    prefix = format_timestamp_prefix()
    terms = get_high_info_terms(prompt + " " + response, 5)
    snippet = clean_text_for_filename(prompt[:40] + " " + response[:40])
    wct, sw = len(prompt.split()), len(response.split())
    dur = round((wct + sw) / 2.5)
    base = '_'.join(list(dict.fromkeys(terms + [snippet])))[:200 - len(prefix) - len(f"_wct{wct}_sw{sw}_dur{dur}.{file_type}")]
    return f"{prefix}{base}_wct{wct}_sw{sw}_dur{dur}.{file_type}"

def create_file(prompt, response, file_type="md"):
    filename = generate_filename(prompt, response, file_type)
    with open(filename, 'w', encoding='utf-8') as f: f.write(prompt + "\n\n" + response)
    return filename

def get_download_link(file, file_type="mp3"):
    cache_key = f"dl_{file}"
    if cache_key not in st.session_state['download_link_cache']:
        with open(file, "rb") as f:
            b64 = base64.b64encode(f.read()).decode()
        st.session_state['download_link_cache'][cache_key] = f'<a href="data:audio/mpeg;base64,{b64}" download="{os.path.basename(file)}">{FILE_EMOJIS.get(file_type, "Download")} Download {os.path.basename(file)}</a>'
    return st.session_state['download_link_cache'][cache_key]

# 🎶 Audio Processing
async def async_edge_tts_generate(text, voice, username, rate=0, pitch=0, file_format="mp3"):
    cache_key = f"{text[:100]}_{voice}_{rate}_{pitch}_{file_format}"
    if cache_key in st.session_state['audio_cache']: return st.session_state['audio_cache'][cache_key], 0
    start_time = time.time()
    text = clean_text_for_tts(text)
    if not text: return None, 0
    filename = f"{AUDIO_DIR}/{format_timestamp_prefix(username)}_{voice}.{file_format}"
    communicate = edge_tts.Communicate(text, voice, rate=f"{rate:+d}%", pitch=f"{pitch:+d}Hz")
    await communicate.save(filename)
    st.session_state['audio_cache'][cache_key] = filename
    
    md_filename = filename.replace(".mp3", ".md")
    md_content = f"# Chat Audio Log\n\n**Player:** {username}\n**Voice:** {voice}\n**Text:**\n```markdown\n{text}\n```"
    with open(md_filename, 'w', encoding='utf-8') as f: f.write(md_content)
    
    return filename, time.time() - start_time

def play_and_download_audio(file_path):
    if file_path and os.path.exists(file_path):
        st.audio(file_path)
        st.markdown(get_download_link(file_path), unsafe_allow_html=True)

def load_mp3_viewer():
    mp3_files = glob.glob(f"{AUDIO_DIR}/*.mp3")
    for mp3 in mp3_files:
        filename = os.path.basename(mp3)
        if filename not in st.session_state['mp3_files']:
            st.session_state['mp3_files'][filename] = mp3

async def save_chat_entry(username, message, is_markdown=False):
    central = pytz.timezone('US/Central')
    timestamp = datetime.now(central).strftime("%Y-%m-%d %H:%M:%S")
    entry = f"[{timestamp}] {username}: {message}" if not is_markdown else f"[{timestamp}] {username}:\n```markdown\n{message}\n```"
    with open(CHAT_FILE, 'a') as f: f.write(f"{entry}\n")
    voice = FUN_USERNAMES.get(username, "en-US-AriaNeural")
    audio_file, _ = await async_edge_tts_generate(message, voice, username)
    if audio_file:
        with open(HISTORY_FILE, 'a') as f: f.write(f"[{timestamp}] {username}: Audio - {audio_file}\n")
        st.session_state['mp3_files'][os.path.basename(audio_file)] = audio_file
    await broadcast_message(f"{username}|{message}", "chat")
    st.session_state.last_chat_update = time.time()
    st.session_state.chat_history.append(entry)
    return audio_file

async def load_chat():
    if not os.path.exists(CHAT_FILE):
        with open(CHAT_FILE, 'a') as f: f.write(f"# {START_ROOM} Chat\n\nWelcome to the cosmic hub! 🎤\n")
    with open(CHAT_FILE, 'r') as f: 
        content = f.read().strip()
    lines = content.split('\n')
    numbered_content = "\n".join(f"{i+1}. {line}" for i, line in enumerate(lines) if line.strip())
    return numbered_content

# 🌐 WebSocket Handling
async def websocket_handler(websocket, path):
    client_id = str(uuid.uuid4())
    room_id = "chat"
    if room_id not in st.session_state.active_connections:
        st.session_state.active_connections[room_id] = {}
    st.session_state.active_connections[room_id][client_id] = websocket
    username = st.session_state.get('username', random.choice(list(FUN_USERNAMES.keys())))
    chat_content = await load_chat()
    if not any(f"Client-{client_id}" in line for line in chat_content.split('\n')):
        await save_chat_entry("System 🌟", f"{username} has joined {START_ROOM}!")
    try:
        async for message in websocket:
            if '|' in message:
                username, content = message.split('|', 1)
                await save_chat_entry(username, content)
            else:
                await websocket.send("ERROR|Message format: username|content")
    except websockets.ConnectionClosed:
        await save_chat_entry("System 🌟", f"{username} has left {START_ROOM}!")
    finally:
        if room_id in st.session_state.active_connections and client_id in st.session_state.active_connections[room_id]:
            del st.session_state.active_connections[room_id][client_id]

async def broadcast_message(message, room_id):
    if room_id in st.session_state.active_connections:
        disconnected = []
        for client_id, ws in st.session_state.active_connections[room_id].items():
            try:
                await ws.send(message)
            except websockets.ConnectionClosed:
                disconnected.append(client_id)
        for client_id in disconnected:
            if client_id in st.session_state.active_connections[room_id]:
                del st.session_state.active_connections[room_id][client_id]

async def run_websocket_server():
    if not st.session_state.server_running:
        server = await websockets.serve(websocket_handler, '0.0.0.0', 8765)
        st.session_state.server_running = True
        await server.wait_closed()

# 📚 PDF to Audio
class AudioProcessor:
    def __init__(self):
        self.cache_dir = AUDIO_CACHE_DIR
        os.makedirs(self.cache_dir, exist_ok=True)
        self.metadata = json.load(open(f"{self.cache_dir}/metadata.json")) if os.path.exists(f"{self.cache_dir}/metadata.json") else {}

    def _save_metadata(self):
        with open(f"{self.cache_dir}/metadata.json", 'w') as f: json.dump(self.metadata, f)

    async def create_audio(self, text, voice='en-US-AriaNeural'):
        cache_key = hashlib.md5(f"{text}:{voice}".encode()).hexdigest()
        cache_path = f"{self.cache_dir}/{cache_key}.mp3"
        if cache_key in self.metadata and os.path.exists(cache_path):
            return open(cache_path, 'rb').read()
        text = clean_text_for_tts(text)
        if not text: return None
        communicate = edge_tts.Communicate(text, voice)
        await communicate.save(cache_path)
        self.metadata[cache_key] = {'timestamp': datetime.now().isoformat(), 'text_length': len(text), 'voice': voice}
        self._save_metadata()
        return open(cache_path, 'rb').read()

def process_pdf(pdf_file, max_pages, voice, audio_processor):
    reader = PdfReader(pdf_file)
    total_pages = min(len(reader.pages), max_pages)
    texts, audios = [], {}
    async def process_page(i, text): audios[i] = await audio_processor.create_audio(text, voice)
    for i in range(total_pages):
        text = reader.pages[i].extract_text()
        texts.append(text)
        threading.Thread(target=lambda: asyncio.run(process_page(i, text))).start()
    return texts, audios, total_pages

# 🔍 ArXiv & AI Lookup
def parse_arxiv_refs(ref_text):
    if not ref_text: return []
    papers = []
    current = {}
    for line in ref_text.split('\n'):
        if line.count('|') == 2:
            if current: papers.append(current)
            date, title, *_ = line.strip('* ').split('|')
            url = re.search(r'(https://arxiv.org/\S+)', line).group(1) if re.search(r'(https://arxiv.org/\S+)', line) else f"paper_{len(papers)}"
            current = {'date': date, 'title': title, 'url': url, 'authors': '', 'summary': '', 'full_audio': None, 'download_base64': ''}
        elif current:
            if not current['authors']: current['authors'] = line.strip('* ')
            else: current['summary'] += ' ' + line.strip() if current['summary'] else line.strip()
    if current: papers.append(current)
    return papers[:20]

def generate_5min_feature_markdown(paper):
    title, summary, authors, date, url = paper['title'], paper['summary'], paper['authors'], paper['date'], paper['url']
    pdf_url = url.replace("abs", "pdf") + (".pdf" if not url.endswith(".pdf") else "")
    wct, sw = len(title.split()), len(summary.split())
    terms = get_high_info_terms(summary, 15)
    rouge = round((len(terms) / max(sw, 1)) * 100, 2)
    mermaid = "```mermaid\nflowchart TD\n" + "\n".join(f'    T{i+1}["{t}"] --> T{i+2}["{terms[i+1]}"]' for i in range(len(terms)-1)) + "\n```"
    return f"""
## 📄 {title}
**Authors:** {authors} | **Date:** {date} | **Words:** Title: {wct}, Summary: {sw}  
**Links:** [Abstract]({url}) | [PDF]({pdf_url})  
**Terms:** {', '.join(terms)} | **ROUGE:** {rouge}%  
### 🎤 TTF Read Aloud
- **Title:** {title} | **Terms:** {', '.join(terms)} | **ROUGE:** {rouge}%  
#### Concepts Graph
{mermaid}
---
"""

def create_detailed_paper_md(papers): return "# Detailed Summary\n" + "\n".join(generate_5min_feature_markdown(p) for p in papers)

async def create_paper_audio_files(papers, query):
    for p in papers:
        audio_text = clean_text_for_tts(f"{p['title']} by {p['authors']}. {p['summary']}")
        p['full_audio'], _ = await async_edge_tts_generate(audio_text, st.session_state['tts_voice'], p['authors'])
        if p['full_audio']: p['download_base64'] = get_download_link(p['full_audio'])

async def perform_ai_lookup(q, useArxiv=True, useArxivAudio=False):
    client = anthropic.Anthropic(api_key=anthropic_key)
    response = client.messages.create(model="claude-3-sonnet-20240229", max_tokens=1000, messages=[{"role": "user", "content": q}])
    result = response.content[0].text
    st.markdown("### Claude's Reply 🧠\n" + result)
    md_file = create_file(q, result)
    audio_file, _ = await async_edge_tts_generate(result, st.session_state['tts_voice'], "System")
    play_and_download_audio(audio_file)

    if useArxiv:
        q += result
        gradio_client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
        refs = gradio_client.predict(q, 10, "Semantic Search", "mistralai/Mixtral-8x7B-Instruct-v0.1", api_name="/update_with_rag_md")[0]
        result = f"🔎 {q}\n\n{refs}"
        md_file, audio_file = create_file(q, result), (await async_edge_tts_generate(result, st.session_state['tts_voice'], "System"))[0]
        play_and_download_audio(audio_file)
        papers = parse_arxiv_refs(refs)
        if papers and useArxivAudio: await create_paper_audio_files(papers, q)
        return result, papers
    return result, []

# 📦 Zip Files
def create_zip_of_files(md_files, mp3_files, query):
    all_files = md_files + mp3_files
    if not all_files: return None
    terms = get_high_info_terms(" ".join([open(f, 'r', encoding='utf-8').read() if f.endswith('.md') else os.path.splitext(os.path.basename(f))[0].replace('_', ' ') for f in all_files] + [query]), 5)
    zip_name = f"{format_timestamp_prefix()}_{'-'.join(terms)[:20]}.zip"
    with zipfile.ZipFile(zip_name, 'w') as z: [z.write(f) for f in all_files]
    return zip_name

# 🎮 Main Interface
async def async_interface():
    init_session_state()
    load_mp3_viewer()
    if not st.session_state.username:
        available = [n for n in FUN_USERNAMES if not any(f"{n} has joined" in l for l in (await load_chat()).split('\n'))]
        st.session_state.username = random.choice(available or list(FUN_USERNAMES.keys()))
        st.session_state.tts_voice = FUN_USERNAMES[st.session_state.username]
        await save_chat_entry("System 🌟", f"{st.session_state.username} has joined {START_ROOM}!")

    st.title(f"🤖🧠MMO Chat & Research for {st.session_state.username}📝🔬")
    update_marquee_settings_ui()
    display_marquee(f"🚀 Welcome to {START_ROOM} | 🤖 {st.session_state.username}", st.session_state['marquee_settings'], "welcome")

    if not st.session_state.server_task:
        st.session_state.server_task = asyncio.create_task(run_websocket_server())

    tab_main = st.radio("Action:", ["🎤 Chat & Voice", "📸 Media", "🔍 ArXiv", "📚 PDF to Audio"], horizontal=True)
    useArxiv, useArxivAudio = st.checkbox("Search ArXiv", True), st.checkbox("ArXiv Audio", False)
    st.session_state.autosend = st.checkbox("Autosend Chat", value=True)
    st.session_state.autosearch = st.checkbox("Autosearch ArXiv", value=True)

    # 🎤 Chat & Voice
    if tab_main == "🎤 Chat & Voice":
        st.subheader(f"{START_ROOM} Chat 💬")
        chat_content = await load_chat()
        chat_container = st.container()
        with chat_container:
            lines = chat_content.split('\n')
            for i, line in enumerate(lines):
                if line.strip():
                    st.markdown(line)
                    for mp3_name, mp3_path in st.session_state['mp3_files'].items():
                        if line.strip() in mp3_name and st.session_state.username in mp3_name:
                            st.audio(mp3_path, key=f"audio_{i}_{mp3_name}")
                            break
        
        message = st.text_input(f"Message as {st.session_state.username}", key="message_input")
        if message and message != st.session_state.last_message:
            st.session_state.last_message = message
            if st.session_state.autosend or st.button("Send 🚀"):
                await save_chat_entry(st.session_state.username, message, True)
                st.rerun()

        st.subheader("🎤 Speech-to-Chat")
        from mycomponent import speech_component
        transcript_data = speech_component(default_value=st.session_state.get('last_transcript', ''))
        if transcript_data and 'value' in transcript_data:
            transcript = transcript_data['value'].strip()
            st.write(f"🎙️ You said: {transcript}")
            if transcript and transcript != st.session_state.last_transcript:
                st.session_state.last_transcript = transcript
                if st.session_state.autosend:
                    await save_chat_entry(st.session_state.username, transcript, True)
                    st.rerun()
                elif st.button("Send to Chat"):
                    await save_chat_entry(st.session_state.username, transcript, True)
                    st.rerun()

    # 📸 Media
    elif tab_main == "📸 Media":
        st.header("📸 Media Gallery")
        tabs = st.tabs(["🎵 Audio", "🖼 Images", "🎥 Video"])
        with tabs[0]:
            for a in glob.glob(f"{MEDIA_DIR}/*.mp3"):
                with st.expander(os.path.basename(a)): play_and_download_audio(a)
        with tabs[1]:
            imgs = glob.glob(f"{MEDIA_DIR}/*.png") + glob.glob(f"{MEDIA_DIR}/*.jpg")
            if imgs:
                cols = st.columns(3)
                for i, f in enumerate(imgs): cols[i % 3].image(f, use_container_width=True)
        with tabs[2]:
            for v in glob.glob(f"{MEDIA_DIR}/*.mp4"):
                with st.expander(os.path.basename(v)): st.video(v)

        uploaded_file = st.file_uploader("Upload Media", type=['png', 'jpg', 'mp4', 'mp3'])
        if uploaded_file:
            filename = f"{format_timestamp_prefix(st.session_state.username)}-{hashlib.md5(uploaded_file.getbuffer()).hexdigest()[:8]}.{uploaded_file.name.split('.')[-1]}"
            with open(f"{MEDIA_DIR}/{filename}", 'wb') as f: f.write(uploaded_file.getbuffer())
            await save_chat_entry(st.session_state.username, f"Uploaded: {filename}")
            st.rerun()

    # 🔍 ArXiv
    elif tab_main == "🔍 ArXiv":
        q = st.text_input("🔍 Query:", key="arxiv_query")
        if q and q != st.session_state.last_query:
            st.session_state.last_query = q
            if st.session_state.autosearch or st.button("🔍 Run"):
                result, papers = await perform_ai_lookup(q, useArxiv, useArxivAudio)
                for i, p in enumerate(papers, 1):
                    with st.expander(f"{i}. 📄 {p['title']}"):
                        st.markdown(f"**{p['date']} | {p['title']}** — [Link]({p['url']})")
                        st.markdown(generate_5min_feature_markdown(p))
                        if p.get('full_audio'): play_and_download_audio(p['full_audio'])

    # 📚 PDF to Audio
    elif tab_main == "📚 PDF to Audio":
        audio_processor = AudioProcessor()
        pdf_file = st.file_uploader("Choose PDF", "pdf")
        max_pages = st.slider('Pages', 1, 100, 10)
        if pdf_file:
            with st.spinner('Processing...'):
                texts, audios, total = process_pdf(pdf_file, max_pages, st.session_state['tts_voice'], audio_processor)
                for i, text in enumerate(texts):
                    with st.expander(f"Page {i+1}"):
                        st.markdown(text)
                        while i not in audios: time.sleep(0.1)
                        if audios[i]:
                            st.audio(audios[i], format='audio/mp3')
                            st.markdown(get_download_link(io.BytesIO(audios[i]), "mp3"), unsafe_allow_html=True)

    # 🗂️ Sidebar with Dialog and Audio
    st.sidebar.subheader("Voice Settings")
    new_username = st.sidebar.selectbox("Change Name/Voice", list(FUN_USERNAMES.keys()), index=list(FUN_USERNAMES.keys()).index(st.session_state.username))
    if new_username != st.session_state.username:
        await save_chat_entry("System 🌟", f"{st.session_state.username} changed to {new_username}")
        st.session_state.username, st.session_state.tts_voice = new_username, FUN_USERNAMES[new_username]
        st.rerun()

    st.sidebar.markdown("### 💬 Chat Dialog & Audio")
    chat_content = await load_chat()
    lines = chat_content.split('\n')
    audio_files = sorted(glob.glob(f"{AUDIO_DIR}/*.mp3"), key=os.path.getmtime, reverse=True)
    for line in lines[-10:]:  # Show last 10 lines for brevity
        if line.strip():
            st.sidebar.markdown(f"**{line}**")
            for mp3 in audio_files:
                mp3_name = os.path.basename(mp3)
                if st.session_state.username in mp3_name and any(word in mp3_name for word in line.split()):
                    st.sidebar.audio(mp3, key=f"sidebar_audio_{mp3_name}")
                    st.sidebar.markdown(get_download_link(mp3), unsafe_allow_html=True)
                    break

    md_files, mp3_files = glob.glob("*.md"), glob.glob(f"{AUDIO_DIR}/*.mp3")
    st.sidebar.markdown("### 📂 File History")
    for f in sorted(md_files + mp3_files, key=os.path.getmtime, reverse=True)[:10]:
        st.sidebar.write(f"{FILE_EMOJIS.get(f.split('.')[-1], '📄')} {os.path.basename(f)}")
    if st.sidebar.button("⬇️ Zip All"):
        zip_name = create_zip_of_files(md_files, mp3_files, "latest_query")
        if zip_name: st.sidebar.markdown(get_download_link(zip_name, "zip"), unsafe_allow_html=True)

def main():
    asyncio.run(async_interface())

if __name__ == "__main__":
    main()