import streamlit as st import asyncio import websockets import uuid 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 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 # ๐Ÿ› ๏ธ Patch asyncio for nesting nest_asyncio.apply() # ๐ŸŽจ Page Config st.set_page_config( page_title="๐ŸšฒTalkingAIResearcher๐Ÿ†", page_icon="๐Ÿšฒ๐Ÿ†", layout="wide", initial_sidebar_state="auto" ) # ๐ŸŒŸ Static Config icons = '๐Ÿค–๐Ÿง ๐Ÿ”ฌ๐Ÿ“' Site_Name = '๐Ÿค–๐Ÿง Chat & Quote Node๐Ÿ“๐Ÿ”ฌ' START_ROOM = "Sector ๐ŸŒŒ" FUN_USERNAMES = { "CosmicJester ๐ŸŒŒ": "en-US-AriaNeural", "PixelPanda ๐Ÿผ": "en-US-JennyNeural", "QuantumQuack ๐Ÿฆ†": "en-GB-SoniaNeural", "StellarSquirrel ๐Ÿฟ๏ธ": "en-AU-NatashaNeural", "GizmoGuru โš™๏ธ": "en-CA-ClaraNeural", "NebulaNinja ๐ŸŒ ": "en-US-GuyNeural", "ByteBuster ๐Ÿ’พ": "en-GB-RyanNeural", "GalacticGopher ๐ŸŒ": "en-AU-WilliamNeural", "RocketRaccoon ๐Ÿš€": "en-CA-LiamNeural", "EchoElf ๐Ÿง": "en-US-AnaNeural", "PhantomFox ๐ŸฆŠ": "en-US-BrandonNeural", "WittyWizard ๐Ÿง™": "en-GB-ThomasNeural", "LunarLlama ๐ŸŒ™": "en-AU-FreyaNeural", "SolarSloth โ˜€๏ธ": "en-CA-LindaNeural", "AstroAlpaca ๐Ÿฆ™": "en-US-ChristopherNeural", "CyberCoyote ๐Ÿบ": "en-GB-ElliotNeural", "MysticMoose ๐ŸฆŒ": "en-AU-JamesNeural", "GlitchGnome ๐Ÿงš": "en-CA-EthanNeural", "VortexViper ๐Ÿ": "en-US-AmberNeural", "ChronoChimp ๐Ÿ’": "en-GB-LibbyNeural" } EDGE_TTS_VOICES = list(set(FUN_USERNAMES.values())) FILE_EMOJIS = {"md": "๐Ÿ“", "mp3": "๐ŸŽต", "png": "๐Ÿ–ผ๏ธ", "mp4": "๐ŸŽฅ", "zip": "๐Ÿ“ฆ"} # ๐Ÿ“ Directories for d in ["chat_logs", "vote_logs", "audio_logs", "history_logs", "audio_cache", "paper_metadata"]: os.makedirs(d, exist_ok=True) CHAT_DIR = "chat_logs" VOTE_DIR = "vote_logs" MEDIA_DIR = "." AUDIO_CACHE_DIR = "audio_cache" AUDIO_DIR = "audio_logs" PAPER_DIR = "paper_metadata" STATE_FILE = "user_state.txt" CHAT_FILE = os.path.join(CHAT_DIR, "global_chat.md") QUOTE_VOTES_FILE = os.path.join(VOTE_DIR, "quote_votes.md") IMAGE_VOTES_FILE = os.path.join(VOTE_DIR, "image_votes.md") HISTORY_FILE = os.path.join(VOTE_DIR, "vote_history.md") # ๐Ÿ”‘ 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) # ๐Ÿ•’ 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}" # ๐Ÿ“ˆ 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) # ๐ŸŽ›๏ธ 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': {}, 'timer_start': time.time(), 'quote_index': 0, 'quote_source': "famous", 'last_sent_transcript': "", 'old_val': None, 'last_refresh': time.time(), 'paper_metadata': {}, 'paste_image_base64': "", 'use_arxiv': True, 'use_arxiv_audio': False, 'speech_processed': False } for k, v in defaults.items(): if k not in st.session_state: st.session_state[k] = v # ๐Ÿ–Œ๏ธ Marquee Helpers def update_marquee_settings_ui(): st.sidebar.markdown("### ๐ŸŽฏ Marquee Settings") cols = st.sidebar.columns(2) with cols[0]: st.session_state['marquee_settings']['background'] = st.color_picker("๐ŸŽจ Background", "#1E1E1E") st.session_state['marquee_settings']['color'] = st.color_picker("โœ๏ธ Text", "#FFFFFF") with cols[1]: st.session_state['marquee_settings']['font-size'] = f"{st.slider('๐Ÿ“ Size', 10, 24, 14)}px" st.session_state['marquee_settings']['animationDuration'] = f"{st.slider('โฑ๏ธ 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("") # ๐Ÿ“ 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())[:50] 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, username, file_type="md", title=None): timestamp = format_timestamp_prefix(username) if title: high_info = '-'.join(get_high_info_terms(title, 5)) return f"{timestamp}-{clean_text_for_filename(prompt[:20])}-{high_info}.{file_type}" hash_val = hashlib.md5(prompt.encode()).hexdigest()[:8] return f"{timestamp}-{hash_val}.{file_type}" def create_file(prompt, username, file_type="md", title=None): filename = generate_filename(prompt, username, file_type, title) with open(filename, 'w', encoding='utf-8') as f: f.write(prompt) 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() mime_types = {"mp3": "audio/mpeg", "png": "image/png", "mp4": "video/mp4", "md": "text/markdown", "zip": "application/zip"} st.session_state['download_link_cache'][cache_key] = f'{FILE_EMOJIS.get(file_type, "Download")} Download {os.path.basename(file)}' return st.session_state['download_link_cache'][cache_key] def save_username(username): try: with open(STATE_FILE, 'w') as f: f.write(username) except Exception as e: print(f"Failed to save username: {e}") def load_username(): if os.path.exists(STATE_FILE): try: with open(STATE_FILE, 'r') as f: return f.read().strip() except Exception as e: print(f"Failed to load username: {e}") return None def concatenate_markdown_files(exclude_files=["README.md"]): md_files = sorted([f for f in glob.glob("*.md") if os.path.basename(f) not in exclude_files], key=os.path.getmtime) all_md_content = "" for i, md_file in enumerate(md_files, 1): with open(md_file, 'r', encoding='utf-8') as f: content = f.read().strip() all_md_content += f"{i}. {content}\n" return all_md_content.rstrip() # ๐ŸŽถ 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 or text == "No text": print(f"Skipping audio generation for empty/invalid text: '{text}'") return None, 0 filename = f"{format_timestamp_prefix(username)}-{hashlib.md5(text.encode()).hexdigest()[:8]}.{file_format}" try: communicate = edge_tts.Communicate(text, voice, rate=f"{rate:+d}%", pitch=f"{pitch:+d}Hz") await communicate.save(filename) if os.path.exists(filename) and os.path.getsize(filename) > 0: st.session_state['audio_cache'][cache_key] = filename return filename, time.time() - start_time else: print(f"Audio file {filename} was not created or is empty.") return None, 0 except edge_tts.exceptions.NoAudioReceived as e: print(f"No audio received for text: '{text}' with voice: {voice}. Error: {e}") return None, 0 except Exception as e: print(f"Error generating audio for text: '{text}' with voice: {voice}. Error: {e}") return None, 0 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) else: st.warning(f"Audio file not found: {file_path}") def load_mp3_viewer(): mp3_files = sorted(glob.glob("*.mp3"), key=os.path.getmtime) for i, mp3 in enumerate(mp3_files, 1): filename = os.path.basename(mp3) if filename not in st.session_state['mp3_files']: st.session_state['mp3_files'][filename] = (i, mp3) async def save_chat_entry(username, message, voice, is_markdown=False): if not message.strip() or message == st.session_state.last_transcript: return None, None central = pytz.timezone('US/Central') timestamp = datetime.now(central).strftime("%Y-%m-%d %H:%M:%S") entry = f"[{timestamp}] {username} ({voice}): {message}" if not is_markdown else f"[{timestamp}] {username} ({voice}):\n```markdown\n{message}\n```" md_file = create_file(entry, username, "md") with open(CHAT_FILE, 'a') as f: f.write(f"{entry}\n") 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)] = (len(st.session_state['chat_history']) + 1, audio_file) if st.session_state.get('speech_processed', False) and st.session_state.get('message_input', '') == message: st.session_state['message_input'] = "" st.session_state['speech_processed'] = False else: st.warning(f"Failed to generate audio for: {message}") await broadcast_message(f"{username}|{message}", "chat") st.session_state.last_chat_update = time.time() st.session_state.chat_history.append(entry) st.session_state.last_transcript = message return md_file, 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! ๐ŸŽค\n") with open(CHAT_FILE, 'r') as f: content = f.read().strip() lines = content.split('\n') unique_lines = list(dict.fromkeys(line for line in lines if line.strip())) return unique_lines # Claude Search Function with Image Support async def perform_claude_search(query, username, image=None): if not query.strip() or query == st.session_state.last_transcript: return None, None, None client = anthropic.Anthropic(api_key=anthropic_key) message_content = [{"type": "text", "text": query}] if image: buffered = io.BytesIO() image.save(buffered, format="PNG") img_base64 = base64.b64encode(buffered.getvalue()).decode('utf-8') message_content.append({ "type": "image", "source": { "type": "base64", "media_type": "image/png", "data": img_base64 } }) try: response = client.messages.create( model="claude-3-sonnet-20240229", max_tokens=1000, messages=[{"role": "user", "content": message_content}] ) result = response.content[0].text st.markdown(f"### Claude's Reply ๐Ÿง \n{result}") except Exception as e: st.error(f"Claude processing failed: {e}") return None, None, None voice = FUN_USERNAMES.get(username, "en-US-AriaNeural") md_file, audio_file = await save_chat_entry(username, f"Claude Search: {query}\nResponse: {result}", voice, True) return md_file, audio_file, result # ArXiv Search Function async def perform_arxiv_search(query, username, claude_result=None): if not query.strip() or query == st.session_state.last_transcript: return None, None if claude_result is None: client = anthropic.Anthropic(api_key=anthropic_key) claude_response = client.messages.create( model="claude-3-sonnet-20240229", max_tokens=1000, messages=[{"role": "user", "content": query}] ) claude_result = claude_response.content[0].text st.markdown(f"### Claude's Reply ๐Ÿง \n{claude_result}") enhanced_query = f"{query}\n\n{claude_result}" gradio_client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern") refs = gradio_client.predict( enhanced_query, 10, "Semantic Search", "mistralai/Mixtral-8x7B-Instruct-v0.1", api_name="/update_with_rag_md" )[0] result = f"๐Ÿ”Ž {enhanced_query}\n\n{refs}" voice = FUN_USERNAMES.get(username, "en-US-AriaNeural") md_file, audio_file = await save_chat_entry(username, f"ArXiv Search: {query}\nClaude Response: {claude_result}\nArXiv Results: {refs}", voice, True) return md_file, audio_file async def perform_ai_lookup(q, vocal_summary=True, extended_refs=False, titles_summary=True, full_audio=False, useArxiv=True, useArxivAudio=False): start = time.time() client = anthropic.Anthropic(api_key=anthropic_key) response = client.messages.create( model="claude-3-sonnet-20240229", max_tokens=1000, messages=[{"role": "user", "content": q}] ) st.write("Claude's reply ๐Ÿง :") st.markdown(response.content[0].text) result = response.content[0].text md_file = create_file(result, "System", "md") audio_file, _ = await async_edge_tts_generate(result, st.session_state['tts_voice'], "System") st.subheader("๐Ÿ“ Main Response Audio") play_and_download_audio(audio_file) papers = [] if useArxiv: q = q + result st.write('Running Arxiv RAG with Claude inputs.') gradio_client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern") refs = gradio_client.predict( q, 20, "Semantic Search", "mistralai/Mixtral-8x7B-Instruct-v0.1", api_name="/update_with_rag_md" )[0] papers = parse_arxiv_refs(refs, q) for paper in papers: filename = create_file(generate_5min_feature_markdown(paper), "System", "md", paper['title']) paper['md_file'] = filename st.session_state['paper_metadata'][paper['title']] = filename if papers and useArxivAudio: await create_paper_audio_files(papers, q) elapsed = time.time() - start st.write(f"**Total Elapsed:** {elapsed:.2f} s") return result, papers # ๐ŸŒ 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): await save_chat_entry("System ๐ŸŒŸ", f"{username} has joined {START_ROOM}!", "en-US-AriaNeural") try: async for message in websocket: if '|' in message: username, content = message.split('|', 1) voice = FUN_USERNAMES.get(username, "en-US-AriaNeural") await save_chat_entry(username, content, voice) else: await websocket.send("ERROR|Message format: username|content") except websockets.ConnectionClosed: await save_chat_entry("System ๐ŸŒŸ", f"{username} has left {START_ROOM}!", "en-US-AriaNeural") 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.get('server_running', False): # Safe access with default server = await websockets.serve(websocket_handler, '0.0.0.0', 8765) st.session_state['server_running'] = True await server.wait_closed() def start_websocket_server(): loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) loop.run_until_complete(run_websocket_server()) # ๐Ÿ“š 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 cache_path 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 cache_path 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): audio_path = await audio_processor.create_audio(text, voice) if audio_path: audios[i] = audio_path 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 # ๐Ÿ” ArXiv & AI Lookup def parse_arxiv_refs(ref_text, query): 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': '', 'query': query} 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""" ## ๐Ÿ“„ {title} **Authors:** {authors} **Date:** {date} **Words:** Title: {wct}, Summary: {sw} **Links:** [Abstract]({url}) | [PDF]({pdf_url}) **Terms:** {', '.join(terms)} **ROUGE:** {rouge}% ### ๐ŸŽค TTF Read Aloud - **Title:** {title} - **Terms:** {', '.join(terms)} - **ROUGE:** {rouge}% #### Concepts Graph {mermaid} --- """ 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']) def save_vote(file, item, user_hash): timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") entry = f"[{timestamp}] {user_hash} voted for {item}" try: with open(file, 'a') as f: f.write(f"{entry}\n") with open(HISTORY_FILE, 'a') as f: f.write(f"- {timestamp} - User {user_hash} voted for {item}\n") return True except Exception as e: print(f"Vote save flop: {e}") return False def load_votes(file): if not os.path.exists(file): with open(file, 'w') as f: f.write("# Vote Tally\n\nNo votes yet - get clicking! ๐Ÿ–ฑ๏ธ\n") try: with open(file, 'r') as f: lines = f.read().strip().split('\n') votes = {} for line in lines[2:]: if line.strip() and 'voted for' in line: item = line.split('voted for ')[1] votes[item] = votes.get(item, 0) + 1 return votes except Exception as e: print(f"Vote load oopsie: {e}") return {} def generate_user_hash(): if 'user_hash' not in st.session_state: session_id = str(random.getrandbits(128)) hash_object = hashlib.md5(session_id.encode()) st.session_state['user_hash'] = hash_object.hexdigest()[:8] return st.session_state['user_hash'] async def save_pasted_image(image, username, prompt=""): img_hash = hashlib.md5(image.tobytes()).hexdigest()[:8] if img_hash in st.session_state.image_hashes: return None context = prompt if prompt else st.session_state.get('last_message', "pasted_image") timestamp = format_timestamp_prefix(username) filename = f"{timestamp}-{clean_text_for_filename(context)}-{img_hash}.png" filepath = filename try: image.save(filepath, "PNG") st.session_state.image_hashes.add(img_hash) await save_chat_entry(username, f"Pasted image saved: {filepath}", FUN_USERNAMES.get(username, "en-US-AriaNeural")) return filepath except Exception as e: st.error(f"Failed to save image: {e}") return None # ๐Ÿ“ฆ Zip Files def create_zip_of_files(files, prefix="All", query="latest"): if not 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 files] + [query]), 5) zip_name = f"{prefix}_{format_timestamp_prefix()}_{'-'.join(terms)[:20]}.zip" with zipfile.ZipFile(zip_name, 'w') as z: [z.write(f) for f in files] return zip_name # Custom Paste Image Component def paste_image_component(): with st.form(key="paste_form"): paste_input = st.text_input("Paste Base64 Image Here (hidden)", value="", key="paste_input", label_visibility="collapsed") st.markdown(""" """, unsafe_allow_html=True) paste_button = st.form_submit_button("Paste Image ๐Ÿ“‹", on_click=lambda: st.markdown("", unsafe_allow_html=True)) if paste_button and paste_input: if paste_input.startswith('ERROR:'): st.warning(f"Paste failed: {paste_input}") return None if paste_input.startswith('data:image'): try: base64_str = paste_input.split(',')[1] img_bytes = base64.b64decode(base64_str) img = Image.open(io.BytesIO(img_bytes)) st.image(img, caption="Image Pasted Successfully", use_column_width=True) return img except Exception as e: st.error(f"Error decoding pasted image: {e}") return None else: st.warning("Clipboard does not contain a valid image (expected base64 data:image)") return None return None # ๐ŸŽฎ Main Interface def main(): init_session_state() # Ensure session state is initialized before any threads load_mp3_viewer() saved_username = load_username() if saved_username and saved_username in FUN_USERNAMES: st.session_state.username = saved_username 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 asyncio.run(load_chat()))] st.session_state.username = random.choice(available or list(FUN_USERNAMES.keys())) st.session_state.tts_voice = FUN_USERNAMES[st.session_state.username] asyncio.run(save_chat_entry("System ๐ŸŒŸ", f"{st.session_state.username} has joined {START_ROOM}!", "en-US-AriaNeural")) save_username(st.session_state.username) st.title(f"{Site_Name} for {st.session_state.username}") update_marquee_settings_ui() display_marquee(f"๐Ÿš€ Welcome to {START_ROOM} | ๐Ÿค– {st.session_state.username}", st.session_state['marquee_settings'], "welcome") mycomponent = components.declare_component("mycomponent", path="mycomponent") val = mycomponent(my_input_value="", key=f"speech_{st.session_state.get('speech_processed', False)}") if val and val != st.session_state.last_transcript: val_stripped = val.strip().replace('\n', ' ') if val_stripped: voice = FUN_USERNAMES.get(st.session_state.username, "en-US-AriaNeural") st.session_state['speech_processed'] = True md_file, audio_file = asyncio.run(save_chat_entry(st.session_state.username, val_stripped, voice)) if audio_file: play_and_download_audio(audio_file) st.rerun() tab_main = st.radio("Action:", ["๐ŸŽค Chat & Voice", "๐Ÿ” ArXiv", "๐Ÿ“š PDF to Audio"], horizontal=True, key="tab_main") st.checkbox("Search ArXiv", key="use_arxiv") st.checkbox("ArXiv Audio", key="use_arxiv_audio") st.checkbox("Autosend Chat", key="autosend") st.checkbox("Autosearch ArXiv", key="autosearch") if tab_main == "๐ŸŽค Chat & Voice": st.subheader(f"{START_ROOM} Chat ๐Ÿ’ฌ") chat_content = asyncio.run(load_chat()) chat_container = st.container() with chat_container: numbered_content = "\n".join(f"{i+1}. {line}" for i, line in enumerate(chat_content)) st.code(numbered_content, language="python") message = st.text_input(f"Message as {st.session_state.username}", key="message_input") pasted_image = paste_image_component() if pasted_image is not None: if st.session_state['paste_image_base64'] != base64.b64encode(pasted_image.tobytes()).decode('utf-8'): st.session_state['paste_image_base64'] = base64.b64encode(pasted_image.tobytes()).decode('utf-8') voice = FUN_USERNAMES.get(st.session_state.username, "en-US-AriaNeural") image_prompt = st.text_input("Add a prompt for Claude (e.g., 'OCR this image')", key="image_prompt", value="") with st.spinner("Saving image..."): filename = asyncio.run(save_pasted_image(pasted_image, st.session_state.username, image_prompt)) if filename: st.success(f"Image saved as: {filename}") if image_prompt: with st.spinner("Processing with Claude..."): md_file_claude, audio_file_claude, claude_result = asyncio.run( perform_claude_search(image_prompt, st.session_state.username, pasted_image) ) if audio_file_claude: play_and_download_audio(audio_file_claude) if claude_result: with st.spinner("Searching ArXiv..."): md_file_arxiv, audio_file_arxiv = asyncio.run( perform_arxiv_search(image_prompt, st.session_state.username, claude_result) ) if audio_file_arxiv: play_and_download_audio(audio_file_arxiv) st.session_state.pasted_image_data = None st.session_state['paste_image_base64'] = "" st.session_state.timer_start = time.time() save_username(st.session_state.username) st.rerun() if (message and message != st.session_state.last_message) or (st.session_state.pasted_image_data and not st.session_state['paste_image_base64']): st.session_state.last_message = message col_send, col_claude, col_arxiv = st.columns([1, 1, 1]) with col_send: if st.session_state.autosend or st.button("Send ๐Ÿš€", key="send_button"): voice = FUN_USERNAMES.get(st.session_state.username, "en-US-AriaNeural") if message.strip(): md_file, audio_file = asyncio.run(save_chat_entry(st.session_state.username, message, voice, True)) if audio_file: play_and_download_audio(audio_file) if st.session_state.pasted_image_data: asyncio.run(save_chat_entry(st.session_state.username, f"Pasted image: {st.session_state.pasted_image_data}", voice)) st.session_state.pasted_image_data = None st.session_state.timer_start = time.time() save_username(st.session_state.username) st.rerun() with col_claude: if st.button("๐Ÿง  Claude", key="claude_button"): voice = FUN_USERNAMES.get(st.session_state.username, "en-US-AriaNeural") if message.strip(): md_file, audio_file, _ = asyncio.run(perform_claude_search(message, st.session_state.username)) if audio_file: play_and_download_audio(audio_file) st.session_state.timer_start = time.time() save_username(st.session_state.username) st.rerun() with col_arxiv: if st.button("๐Ÿ” ArXiv", key="arxiv_button"): voice = FUN_USERNAMES.get(st.session_state.username, "en-US-AriaNeural") if message.strip(): md_file, audio_file = asyncio.run(perform_arxiv_search(message, st.session_state.username)) if audio_file: play_and_download_audio(audio_file) st.session_state.timer_start = time.time() save_username(st.session_state.username) st.rerun() elif tab_main == "๐Ÿ” ArXiv": st.subheader("๐Ÿ” Query ArXiv") q = st.text_input("๐Ÿ” 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("๐Ÿ” Run", key="arxiv_run"): result, papers = asyncio.run(perform_ai_lookup(q, useArxiv=st.session_state['use_arxiv'], useArxivAudio=st.session_state['use_arxiv_audio'])) st.markdown(f"### Query: {q}") for i, p in enumerate(papers, 1): expander_label = f"{p['title']} | [arXiv Link]({p['url']})" with st.expander(expander_label): with open(p['md_file'], 'r', encoding='utf-8') as f: content = f.read() numbered_content = "\n".join(f"{j+1}. {line}" for j, line in enumerate(content.split('\n'))) st.code(numbered_content, language="python") elif tab_main == "๐Ÿ“š PDF to Audio": audio_processor = AudioProcessor() pdf_file = st.file_uploader("Choose PDF", "pdf", key="pdf_upload") max_pages = st.slider('Pages', 1, 100, 10, key="pdf_pages") 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.get(i): st.audio(audios[i]) st.markdown(get_download_link(audios[i], "mp3"), unsafe_allow_html=True) voice = FUN_USERNAMES.get(st.session_state.username, "en-US-AriaNeural") asyncio.run(save_chat_entry(st.session_state.username, f"PDF Page {i+1} converted to audio: {audios[i]}", voice)) # Always Visible Media Gallery st.header("๐Ÿ“ธ Media Gallery") all_files = sorted(glob.glob("*.md") + glob.glob("*.mp3") + glob.glob("*.png") + glob.glob("*.mp4"), key=os.path.getmtime) md_files = [f for f in all_files if f.endswith('.md') and os.path.basename(f) != "README.md"] mp3_files = [f for f in all_files if f.endswith('.mp3')] png_files = [f for f in all_files if f.endswith('.png')] mp4_files = [f for f in all_files if f.endswith('.mp4')] st.subheader("All Submitted Text") all_md_content = concatenate_markdown_files() with st.expander("View All Markdown Content"): st.markdown(all_md_content) st.subheader("๐ŸŽต Audio (MP3)") for filename, (num, mp3) in sorted(st.session_state['mp3_files'].items(), key=lambda x: x[1][0]): with st.expander(f"{num}. ${filename}"): st.audio(mp3) st.markdown(get_download_link(mp3, "mp3"), unsafe_allow_html=True) st.subheader("๐Ÿ–ผ๏ธ Images (PNG)") for png in sorted(png_files, key=os.path.getmtime): with st.expander(os.path.basename(png)): st.image(png, use_container_width=True) st.markdown(get_download_link(png, "png"), unsafe_allow_html=True) st.subheader("๐ŸŽฅ Videos (MP4)") for mp4 in sorted(mp4_files, key=os.path.getmtime): with st.expander(os.path.basename(mp4)): st.video(mp4) st.markdown(get_download_link(mp4, "mp4"), unsafe_allow_html=True) # ๐Ÿ—‚๏ธ 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), key="username_select") if new_username != st.session_state.username: asyncio.run(save_chat_entry("System ๐ŸŒŸ", f"{st.session_state.username} changed to {new_username}", "en-US-AriaNeural")) st.session_state.username, st.session_state.tts_voice = new_username, FUN_USERNAMES[new_username] st.session_state.timer_start = time.time() save_username(st.session_state.username) st.rerun() st.sidebar.markdown("### ๐Ÿ’ฌ Chat Dialog") chat_content = asyncio.run(load_chat()) with st.sidebar.expander("Chat History"): numbered_content = "\n".join(f"{i+1}. {line}" for i, line in enumerate(chat_content)) st.code(numbered_content, language="python") st.sidebar.subheader("Vote Totals") chat_votes = load_votes(QUOTE_VOTES_FILE) image_votes = load_votes(IMAGE_VOTES_FILE) for item, count in chat_votes.items(): st.sidebar.write(f"{item}: {count} votes") for image, count in image_votes.items(): st.sidebar.write(f"{image}: {count} votes") st.sidebar.markdown("### ๐Ÿ“‚ File History") for f in all_files[:10]: st.sidebar.write(f"{FILE_EMOJIS.get(f.split('.')[-1], '๐Ÿ“„')} {os.path.basename(f)}") st.sidebar.subheader("๐Ÿ“ฆ Zip Downloads") if st.sidebar.button("โฌ‡๏ธ Zip All", key="zip_all"): zip_name = create_zip_of_files(all_files, "All") if zip_name: st.session_state['download_link_cache'] = {} if st.sidebar.button("โฌ‡๏ธ Zip All MD", key="zip_md"): zip_name = create_zip_of_files(md_files, "MD") if zip_name: st.session_state['download_link_cache'] = {} if st.sidebar.button("โฌ‡๏ธ Zip All MP3", key="zip_mp3"): zip_name = create_zip_of_files(mp3_files, "MP3") if zip_name: st.session_state['download_link_cache'] = {} if st.sidebar.button("โฌ‡๏ธ Zip All PNG", key="zip_png"): zip_name = create_zip_of_files(png_files, "PNG") if zip_name: st.session_state['download_link_cache'] = {} if st.sidebar.button("โฌ‡๏ธ Zip All MP4", key="zip_mp4"): zip_name = create_zip_of_files(mp4_files, "MP4") if zip_name: st.session_state['download_link_cache'] = {} zip_files = sorted(glob.glob("*.zip"), key=os.path.getmtime, reverse=True) for zip_file in zip_files: st.sidebar.markdown(get_download_link(zip_file, "zip"), unsafe_allow_html=True) # Refresh Timer in Sidebar st.sidebar.subheader("Set Refresh Rate โณ") st.markdown(""" """, unsafe_allow_html=True) refresh_rate = st.sidebar.slider("Refresh Rate (seconds)", min_value=1, max_value=300, value=st.session_state.refresh_rate, step=1) if refresh_rate != st.session_state.refresh_rate: st.session_state.refresh_rate = refresh_rate st.session_state.timer_start = time.time() save_username(st.session_state.username) col1, col2, col3 = st.sidebar.columns(3) with col1: if st.button("๐Ÿ‡ Small (1s)"): st.session_state.refresh_rate = 1 st.session_state.timer_start = time.time() save_username(st.session_state.username) with col2: if st.button("๐Ÿข Medium (5s)"): st.session_state.refresh_rate = 5 st.session_state.timer_start = time.time() save_username(st.session_state.username) with col3: if st.button("๐Ÿ˜ Large (5m)"): st.session_state.refresh_rate = 300 st.session_state.timer_start = time.time() save_username(st.session_state.username) timer_placeholder = st.sidebar.empty() start_time = st.session_state.timer_start remaining_time = int(st.session_state.refresh_rate - (time.time() - start_time)) if remaining_time <= 0: st.session_state.timer_start = time.time() st.session_state.last_refresh = time.time() st.rerun() else: timer_placeholder.markdown(f"

โณ Next refresh in: {remaining_time} seconds

", unsafe_allow_html=True) # Start WebSocket server only after session state is initialized if not st.session_state.get('server_running', False) and not st.session_state.get('server_task', None): st.session_state.server_task = threading.Thread(target=start_websocket_server, daemon=True) st.session_state.server_task.start() if __name__ == "__main__": main()