import streamlit as st
import anthropic, openai, base64, cv2, glob, json, math, os, pytz, random, re, requests, textract, time, zipfile
import plotly.graph_objects as go
import streamlit.components.v1 as components
from datetime import datetime
from audio_recorder_streamlit import audio_recorder
from bs4 import BeautifulSoup
from collections import defaultdict, deque, Counter
from dotenv import load_dotenv
from gradio_client import Client
from huggingface_hub import InferenceClient
from io import BytesIO
from PIL import Image
from PyPDF2 import PdfReader
from urllib.parse import quote
from xml.etree import ElementTree as ET
from openai import OpenAI
import extra_streamlit_components as stx
from streamlit.runtime.scriptrunner import get_script_run_ctx
import asyncio
import edge_tts
from streamlit_marquee import streamlit_marquee
# π― 1. Core Configuration & Setup
st.set_page_config(
page_title="π²TalkingAIResearcherπ",
page_icon="π²π",
layout="wide",
initial_sidebar_state="auto",
menu_items={
'Get Help': 'https://huggingface.co/awacke1',
'Report a bug': 'https://huggingface.co/spaces/awacke1',
'About': "π²TalkingAIResearcherπ"
}
)
load_dotenv()
# Add available English voices for Edge TTS
EDGE_TTS_VOICES = [
"en-US-AriaNeural",
"en-US-GuyNeural",
"en-US-JennyNeural",
"en-GB-SoniaNeural",
"en-GB-RyanNeural",
"en-AU-NatashaNeural",
"en-AU-WilliamNeural",
"en-CA-ClaraNeural",
"en-CA-LiamNeural"
]
# Initialize session state variables
if 'marquee_settings' not in st.session_state:
st.session_state['marquee_settings'] = {
"background": "#1E1E1E",
"color": "#FFFFFF",
"font-size": "14px",
"animationDuration": "10s",
"width": "100%",
"lineHeight": "35px"
}
if 'tts_voice' not in st.session_state:
st.session_state['tts_voice'] = EDGE_TTS_VOICES[0]
if 'audio_format' not in st.session_state:
st.session_state['audio_format'] = 'mp3'
if 'transcript_history' not in st.session_state:
st.session_state['transcript_history'] = []
if 'chat_history' not in st.session_state:
st.session_state['chat_history'] = []
if 'openai_model' not in st.session_state:
st.session_state['openai_model'] = "gpt-4o-2024-05-13"
if 'messages' not in st.session_state:
st.session_state['messages'] = []
if 'last_voice_input' not in st.session_state:
st.session_state['last_voice_input'] = ""
if 'editing_file' not in st.session_state:
st.session_state['editing_file'] = None
if 'edit_new_name' not in st.session_state:
st.session_state['edit_new_name'] = ""
if 'edit_new_content' not in st.session_state:
st.session_state['edit_new_content'] = ""
if 'viewing_prefix' not in st.session_state:
st.session_state['viewing_prefix'] = None
if 'should_rerun' not in st.session_state:
st.session_state['should_rerun'] = False
if 'old_val' not in st.session_state:
st.session_state['old_val'] = None
if 'last_query' not in st.session_state:
st.session_state['last_query'] = ""
if 'marquee_content' not in st.session_state:
st.session_state['marquee_content'] = "π Welcome to TalkingAIResearcher | π€ Your Research Assistant"
# π 2. API Setup & Clients
openai_api_key = os.getenv('OPENAI_API_KEY', "")
anthropic_key = os.getenv('ANTHROPIC_API_KEY_3', "")
xai_key = os.getenv('xai',"")
if 'OPENAI_API_KEY' in st.secrets:
openai_api_key = st.secrets['OPENAI_API_KEY']
if 'ANTHROPIC_API_KEY' in st.secrets:
anthropic_key = st.secrets["ANTHROPIC_API_KEY"]
openai.api_key = openai_api_key
claude_client = anthropic.Anthropic(api_key=anthropic_key)
openai_client = OpenAI(api_key=openai.api_key, organization=os.getenv('OPENAI_ORG_ID'))
HF_KEY = os.getenv('HF_KEY')
API_URL = os.getenv('API_URL')
# Constants
FILE_EMOJIS = {
"md": "π",
"mp3": "π΅",
"wav": "π"
}
def get_central_time():
"""Get current time in US Central timezone"""
central = pytz.timezone('US/Central')
return datetime.now(central)
def format_timestamp_prefix():
"""Generate timestamp prefix in format MM_dd_yy_hh_mm_AM/PM"""
ct = get_central_time()
return ct.strftime("%m_%d_%y_%I_%M_%p")
def initialize_marquee_settings():
"""Initialize marquee settings in session state"""
if 'marquee_settings' not in st.session_state:
st.session_state['marquee_settings'] = {
"background": "#1E1E1E",
"color": "#FFFFFF",
"font-size": "14px",
"animationDuration": "10s",
"width": "100%",
"lineHeight": "35px"
}
def get_marquee_settings():
"""Get or update marquee settings from session state"""
initialize_marquee_settings()
return st.session_state['marquee_settings']
def update_marquee_settings_ui():
"""Update marquee settings via UI controls"""
initialize_marquee_settings()
st.sidebar.markdown("### π― Marquee Settings")
cols = st.sidebar.columns(2)
with cols[0]:
bg_color = st.color_picker("π¨ Background",
st.session_state['marquee_settings']["background"],
key="bg_color_picker")
text_color = st.color_picker("βοΈ Text",
st.session_state['marquee_settings']["color"],
key="text_color_picker")
with cols[1]:
font_size = st.slider("π Size", 10, 24, 14, key="font_size_slider")
duration = st.slider("β±οΈ Speed", 1, 20, 10, key="duration_slider")
st.session_state['marquee_settings'].update({
"background": bg_color,
"color": text_color,
"font-size": f"{font_size}px",
"animationDuration": f"{duration}s"
})
def display_marquee(text, settings, key_suffix=""):
"""Display marquee with given text and settings"""
truncated_text = text[:280] + "..." if len(text) > 280 else text
streamlit_marquee(
content=truncated_text,
**settings,
key=f"marquee_{key_suffix}"
)
st.write("")
def get_high_info_terms(text: str, top_n=10) -> list:
stop_words = set(['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:])]
combined = words + bi_grams
filtered = [term for term in combined if term not in stop_words and len(term.split()) <= 2]
counter = Counter(filtered)
return [term for term, freq in counter.most_common(top_n)]
def clean_text_for_filename(text: str) -> str:
text = text.lower()
text = re.sub(r'[^\w\s-]', '', text)
words = text.split()
stop_short = set(['the', 'and', 'for', 'with', 'this', 'that'])
filtered = [w for w in words if len(w) > 3 and w not in stop_short]
return '_'.join(filtered)[:200]
def generate_filename(prompt, response, file_type="md"):
prefix = format_timestamp_prefix() + "_"
combined = (prompt + " " + response).strip()
info_terms = get_high_info_terms(combined, top_n=10)
snippet = (prompt[:100] + " " + response[:100]).strip()
snippet_cleaned = clean_text_for_filename(snippet)
name_parts = info_terms + [snippet_cleaned]
full_name = '_'.join(name_parts)
if len(full_name) > 150:
full_name = full_name[:150]
return f"{prefix}{full_name}.{file_type}"
def create_file(prompt, response, file_type="md"):
filename = generate_filename(prompt.strip(), response.strip(), 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="zip"):
with open(file, "rb") as f:
b64 = base64.b64encode(f.read()).decode()
if file_type == "zip":
return f'π Download {os.path.basename(file)}'
elif file_type == "mp3":
return f'π΅ Download {os.path.basename(file)}'
elif file_type == "wav":
return f'π Download {os.path.basename(file)}'
elif file_type == "md":
return f'π Download {os.path.basename(file)}'
else:
return f'Download {os.path.basename(file)}'
def clean_for_speech(text: str) -> str:
text = text.replace("\n", " ")
text = text.replace("", " ")
text = text.replace("#", "")
text = re.sub(r"\(https?:\/\/[^\)]+\)", "", text)
text = re.sub(r"\s+", " ", text).strip()
return text
async def edge_tts_generate_audio(text, voice="en-US-AriaNeural", rate=0, pitch=0, file_format="mp3"):
text = clean_for_speech(text)
if not text.strip():
return None
rate_str = f"{rate:+d}%"
pitch_str = f"{pitch:+d}Hz"
communicate = edge_tts.Communicate(text, voice, rate=rate_str, pitch=pitch_str)
out_fn = generate_filename(text, text, file_type=file_format)
await communicate.save(out_fn)
return out_fn
def speak_with_edge_tts(text, voice="en-US-AriaNeural", rate=0, pitch=0, file_format="mp3"):
return asyncio.run(edge_tts_generate_audio(text, voice, rate, pitch, file_format))
def play_and_download_audio(file_path, file_type="mp3"):
if file_path and os.path.exists(file_path):
st.audio(file_path)
dl_link = get_download_link(file_path, file_type=file_type)
st.markdown(dl_link, unsafe_allow_html=True)
def save_qa_with_audio(question, answer, voice=None):
"""Save Q&A to markdown and generate audio"""
if not voice:
voice = st.session_state['tts_voice']
# Create markdown file
combined_text = f"# Question\n{question}\n\n# Answer\n{answer}"
md_file = create_file(question, answer, "md")
# Generate audio file
audio_text = f"Question: {question}\n\nAnswer: {answer}"
audio_file = speak_with_edge_tts(
audio_text,
voice=voice,
file_format=st.session_state['audio_format']
)
return md_file, audio_file
def process_paper_content(paper):
marquee_text = f"π {paper['title']} | π€ {paper['authors'][:100]} | π {paper['summary'][:100]}"
audio_text = f"{paper['title']} by {paper['authors']}. {paper['summary']}"
return marquee_text, audio_text
def create_paper_audio_files(papers, input_question):
for paper in papers:
try:
marquee_text, audio_text = process_paper_content(paper)
audio_text = clean_for_speech(audio_text)
file_format = st.session_state['audio_format']
audio_file = speak_with_edge_tts(audio_text,
voice=st.session_state['tts_voice'],
file_format=file_format)
paper['full_audio'] = audio_file
st.write(f"### {FILE_EMOJIS.get(file_format, '')} {os.path.basename(audio_file)}")
play_and_download_audio(audio_file, file_type=file_format)
paper['marquee_text'] = marquee_text
except Exception as e:
st.warning(f"Error processing paper {paper['title']}: {str(e)}")
paper['full_audio'] = None
paper['marquee_text'] = None
def display_papers(papers, marquee_settings):
st.write("## Research Papers")
papercount = 0
for paper in papers:
papercount += 1
if papercount <= 20:
if paper.get('marquee_text'):
display_marquee(paper['marquee_text'],
marquee_settings,
key_suffix=f"paper_{papercount}")
with st.expander(f"{papercount}. π {paper['title']}", expanded=True):
st.markdown(f"**{paper['date']} | {paper['title']} | β¬οΈ**")
st.markdown(f"*{paper['authors']}*")
st.markdown(paper['summary'])
if paper.get('full_audio'):
st.write("π Paper Audio")
file_ext = os.path.splitext(paper['full_audio'])[1].lower().strip('.')
if file_ext in ['mp3', 'wav']:
st.audio(paper['full_audio'])
def parse_arxiv_refs(ref_text: str):
if not ref_text:
return []
results = []
current_paper = {}
lines = ref_text.split('\n')
for i, line in enumerate(lines):
if line.count('|') == 2:
if current_paper:
results.append(current_paper)
if len(results) >= 20:
break
try:
header_parts = line.strip('* ').split('|')
date = header_parts[0].strip()
title = header_parts[1].strip()
url_match = re.search(r'(https://arxiv.org/\S+)', line)
url = url_match.group(1) if url_match else f"paper_{len(results)}"
current_paper = {
'date': date,
'title': title,
'url': url,
'authors': '',
'summary': '',
'content_start': i + 1
}
except Exception as e:
st.warning(f"Error parsing paper header: {str(e)}")
current_paper = {}
continue
elif current_paper:
if not current_paper['authors']:
current_paper['authors'] = line.strip('* ')
else:
if current_paper['summary']:
current_paper['summary'] += ' ' + line.strip()
else:
current_paper['summary'] = line.strip()
if current_paper:
results.append(current_paper)
return results[:20]
def perform_ai_lookup(q, vocal_summary=True, extended_refs=False,
titles_summary=True, full_audio=False):
start = time.time()
client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
refs = client.predict(q, 20, "Semantic Search",
"mistralai/Mixtral-8x7B-Instruct-v0.1",
api_name="/update_with_rag_md")[0]
r2 = client.predict(q, "mistralai/Mixtral-8x7B-Instruct-v0.1",
True, api_name="/ask_llm")
result = f"### π {q}\n\n{r2}\n\n{refs}"
st.markdown(result)
md_file, audio_file = save_qa_with_audio(q, result)
st.subheader("π Main Response Audio")
play_and_download_audio(audio_file, st.session_state['audio_format'])
papers = parse_arxiv_refs(refs)
if papers:
create_paper_audio_files(papers, input_question=q)
display_papers(papers, get_marquee_settings())
else:
st.warning("No papers found in the response.")
elapsed = time.time()-start
st.write(f"**Total Elapsed:** {elapsed:.2f} s")
return result
def process_voice_input(text):
if not text:
return
st.subheader("π Search Results")
result = perform_ai_lookup(
text,
vocal_summary=True,
extended_refs=False,
titles_summary=True,
full_audio=True
)
md_file, audio_file = save_qa_with_audio(text, result)
st.subheader("π Generated Files")
st.write(f"Markdown: {md_file}")
st.write(f"Audio: {audio_file}")
play_and_download_audio(audio_file, st.session_state['audio_format'])
def load_files_for_sidebar():
md_files = glob.glob("*.md")
mp3_files = glob.glob("*.mp3")
wav_files = glob.glob("*.wav")
md_files = [f for f in md_files if os.path.basename(f).lower() != 'readme.md']
all_files = md_files + mp3_files + wav_files
groups = defaultdict(list)
prefix_length = len("MM_dd_yy_hh_mm_AP")
for f in all_files:
basename = os.path.basename(f)
if len(basename) >= prefix_length and '_' in basename:
group_name = basename[:prefix_length]
groups[group_name].append(f)
else:
groups['Other'].append(f)
sorted_groups = sorted(groups.items(),
key=lambda x: x[0] if x[0] != 'Other' else '',
reverse=True)
return sorted_groups
def display_file_manager_sidebar(groups_sorted):
st.sidebar.title("π΅ Audio & Docs Manager")
all_md = []
all_mp3 = []
all_wav = []
for _, files in groups_sorted:
for f in files:
if f.endswith(".md"):
all_md.append(f)
elif f.endswith(".mp3"):
all_mp3.append(f)
elif f.endswith(".wav"):
all_wav.append(f)
col1, col2, col3, col4 = st.sidebar.columns(4)
with col1:
if st.button("π DelMD"):
for f in all_md:
os.remove(f)
st.session_state.should_rerun = True
with col2:
if st.button("π DelMP3"):
for f in all_mp3:
os.remove(f)
st.session_state.should_rerun = True
with col3:
if st.button("π DelWAV"):
for f in all_wav:
os.remove(f)
st.session_state.should_rerun = True
with col4:
if st.button("β¬οΈ ZipAll"):
zip_name = create_zip_of_files(all_md, all_mp3, all_wav, st.session_state.get('last_query', ''))
if zip_name:
st.sidebar.markdown(get_download_link(zip_name, "zip"), unsafe_allow_html=True)
for group_name, files in groups_sorted:
if group_name == 'Other':
group_label = 'Other Files'
else:
try:
timestamp_dt = datetime.strptime(group_name, "%m_%d_%y_%I_%M_%p")
group_label = timestamp_dt.strftime("%b %d, %Y %I:%M %p")
except ValueError:
group_label = group_name
with st.sidebar.expander(f"π {group_label} ({len(files)})", expanded=True):
c1, c2 = st.columns(2)
with c1:
if st.button("π View", key=f"view_group_{group_name}"):
st.session_state.viewing_prefix = group_name
with c2:
if st.button("π Del", key=f"del_group_{group_name}"):
for f in files:
os.remove(f)
st.success(f"Deleted group {group_label}!")
st.session_state.should_rerun = True
for f in files:
fname = os.path.basename(f)
ext = os.path.splitext(fname)[1].lower()
emoji = FILE_EMOJIS.get(ext.strip('.'), '')
mtime = os.path.getmtime(f)
ctime = datetime.fromtimestamp(mtime).strftime("%I:%M:%S %p")
st.write(f"{emoji} **{fname}** - {ctime}")
def create_zip_of_files(md_files, mp3_files, wav_files, input_question):
md_files = [f for f in md_files if os.path.basename(f).lower() != 'readme.md']
all_files = md_files + mp3_files + wav_files
if not all_files:
return None
all_content = []
for f in all_files:
if f.endswith('.md'):
with open(f, 'r', encoding='utf-8') as file:
all_content.append(file.read())
elif f.endswith('.mp3') or f.endswith('.wav'):
basename = os.path.splitext(os.path.basename(f))[0]
words = basename.replace('_', ' ')
all_content.append(words)
all_content.append(input_question)
combined_content = " ".join(all_content)
info_terms = get_high_info_terms(combined_content, top_n=10)
timestamp = format_timestamp_prefix()
name_text = '_'.join(term.replace(' ', '-') for term in info_terms[:10])
zip_name = f"{timestamp}_{name_text}.zip"
with zipfile.ZipFile(zip_name, 'w') as z:
for f in all_files:
z.write(f)
return zip_name
def main():
# Update marquee settings UI first
update_marquee_settings_ui()
marquee_settings = get_marquee_settings()
# Initial welcome marquee
display_marquee(st.session_state['marquee_content'],
{**marquee_settings, "font-size": "28px", "lineHeight": "50px"},
key_suffix="welcome")
# Load files for sidebar
groups_sorted = load_files_for_sidebar()
# Update marquee content when viewing files
if st.session_state.viewing_prefix:
for group_name, files in groups_sorted:
if group_name == st.session_state.viewing_prefix:
for f in files:
if f.endswith('.md'):
with open(f, 'r', encoding='utf-8') as file:
st.session_state['marquee_content'] = file.read()[:280]
# Voice Settings
st.sidebar.markdown("### π€ Voice Settings")
selected_voice = st.sidebar.selectbox(
"Select TTS Voice:",
options=EDGE_TTS_VOICES,
index=EDGE_TTS_VOICES.index(st.session_state['tts_voice'])
)
# Audio Format Settings
st.sidebar.markdown("### π Audio Format")
selected_format = st.sidebar.radio(
"Choose Audio Format:",
options=["MP3", "WAV"],
index=0
)
if selected_voice != st.session_state['tts_voice']:
st.session_state['tts_voice'] = selected_voice
st.rerun()
if selected_format.lower() != st.session_state['audio_format']:
st.session_state['audio_format'] = selected_format.lower()
st.rerun()
# Main Interface
tab_main = st.radio("Action:", ["π€ Voice", "πΈ Media", "π ArXiv", "π Editor"],
horizontal=True)
mycomponent = components.declare_component("mycomponent", path="mycomponent")
val = mycomponent(my_input_value="Hello")
if val:
val_stripped = val.replace('\\n', ' ')
edited_input = st.text_area("βοΈ Edit Input:", value=val_stripped, height=100)
run_option = st.selectbox("Model:", ["Arxiv"])
col1, col2 = st.columns(2)
with col1:
autorun = st.checkbox("β AutoRun", value=True)
with col2:
full_audio = st.checkbox("πFullAudio", value=False)
input_changed = (val != st.session_state.old_val)
if autorun and input_changed:
st.session_state.old_val = val
st.session_state.last_query = edited_input
result = perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False,
titles_summary=True, full_audio=full_audio)
else:
if st.button("βΆ Run"):
st.session_state.old_val = val
st.session_state.last_query = edited_input
result = perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False,
titles_summary=True, full_audio=full_audio)
if tab_main == "π ArXiv":
st.subheader("π Query ArXiv")
q = st.text_input("π Query:", key="arxiv_query")
st.markdown("### π Options")
vocal_summary = st.checkbox("πShortAudio", value=True, key="option_vocal_summary")
extended_refs = st.checkbox("πLongRefs", value=False, key="option_extended_refs")
titles_summary = st.checkbox("πTitlesOnly", value=True, key="option_titles_summary")
full_audio = st.checkbox("πFullAudio", value=False, key="option_full_audio")
full_transcript = st.checkbox("π§ΎFullTranscript", value=False, key="option_full_transcript")
if q and st.button("πRun"):
st.session_state.last_query = q
result = perform_ai_lookup(q, vocal_summary=vocal_summary, extended_refs=extended_refs,
titles_summary=titles_summary, full_audio=full_audio)
if full_transcript:
create_file(q, result, "md")
elif tab_main == "π€ Voice":
st.subheader("π€ Voice Input")
user_text = st.text_area("π¬ Message:", height=100)
user_text = user_text.strip().replace('\n', ' ')
if st.button("π¨ Send"):
process_voice_input(user_text)
st.subheader("π Chat History")
for c in st.session_state.chat_history:
st.write("**You:**", c["user"])
st.write("**Response:**", c["claude"])
elif tab_main == "πΈ Media":
st.header("πΈ Images & π₯ Videos")
tabs = st.tabs(["πΌ Images", "π₯ Video"])
with tabs[0]:
imgs = glob.glob("*.png") + glob.glob("*.jpg")
if imgs:
c = st.slider("Cols", 1, 5, 3)
cols = st.columns(c)
for i, f in enumerate(imgs):
with cols[i % c]:
st.image(Image.open(f), use_container_width=True)
if st.button(f"π Analyze {os.path.basename(f)}", key=f"analyze_{f}"):
response = openai_client.chat.completions.create(
model=st.session_state["openai_model"],
messages=[
{"role": "system", "content": "Analyze the image content."},
{"role": "user", "content": [
{"type": "image_url",
"image_url": {"url": f"data:image/jpeg;base64,{base64.b64encode(open(f, 'rb').read()).decode()}"}}
]}
]
)
st.markdown(response.choices[0].message.content)
else:
st.write("No images found.")
with tabs[1]:
vids = glob.glob("*.mp4")
if vids:
for v in vids:
with st.expander(f"π₯ {os.path.basename(v)}"):
st.video(v)
if st.button(f"Analyze {os.path.basename(v)}", key=f"analyze_{v}"):
frames = process_video(v)
response = openai_client.chat.completions.create(
model=st.session_state["openai_model"],
messages=[
{"role": "system", "content": "Analyze video frames."},
{"role": "user", "content": [
{"type": "image_url",
"image_url": {"url": f"data:image/jpeg;base64,{frame}"}}
for frame in frames
]}
]
)
st.markdown(response.choices[0].message.content)
else:
st.write("No videos found.")
elif tab_main == "π Editor":
if st.session_state.editing_file:
st.subheader(f"Editing: {st.session_state.editing_file}")
new_text = st.text_area("βοΈ Content:", st.session_state.edit_new_content, height=300)
if st.button("πΎ Save"):
with open(st.session_state.editing_file, 'w', encoding='utf-8') as f:
f.write(new_text)
st.success("File updated successfully!")
st.session_state.should_rerun = True
st.session_state.editing_file = None
else:
st.write("Select a file from the sidebar to edit.")
# Display file manager in sidebar
display_file_manager_sidebar(groups_sorted)
# Display viewed group content
if st.session_state.viewing_prefix and any(st.session_state.viewing_prefix == group for group, _ in groups_sorted):
st.write("---")
st.write(f"**Viewing Group:** {st.session_state.viewing_prefix}")
for group_name, files in groups_sorted:
if group_name == st.session_state.viewing_prefix:
for f in files:
fname = os.path.basename(f)
ext = os.path.splitext(fname)[1].lower().strip('.')
st.write(f"### {fname}")
if ext == "md":
content = open(f, 'r', encoding='utf-8').read()
st.markdown(content)
elif ext in ["mp3", "wav"]:
st.audio(f)
else:
st.markdown(get_download_link(f), unsafe_allow_html=True)
break
if st.button("β Close"):
st.session_state.viewing_prefix = None
st.session_state['marquee_content'] = "π Welcome to TalkingAIResearcher | π€ Your Research Assistant"
st.markdown("""
""", unsafe_allow_html=True)
if st.session_state.should_rerun:
st.session_state.should_rerun = False
st.rerun()
if __name__ == "__main__":
main()