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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
# 🎯 1. Core Configuration & Setup
st.set_page_config(
page_title="🚲TalkingAIResearcher🏆",
page_icon="🚲🏆",
layout="wide",
initial_sidebar_state="auto",
menu_items={
'Get Help': 'https://huggingface.co/awacke1',
'Report a bug': 'https://huggingface.co/spaces/awacke1',
'About': "🚲TalkingAIResearcher🏆"
}
)
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": "20s",
"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'] = "🚀 Welcome to TalkingAIResearcher | 🤖 Your Research Assistant"
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
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')
FILE_EMOJIS = {
"md": "📝",
"mp3": "🎵",
"wav": "🔊"
}
def get_central_time():
central = pytz.timezone('US/Central')
return datetime.now(central)
def format_timestamp_prefix():
ct = get_central_time()
return ct.strftime("%m_%d_%y_%I_%M_%p")
def initialize_marquee_settings():
if 'marquee_settings' not in st.session_state:
st.session_state['marquee_settings'] = {
"background": "#1E1E1E",
"color": "#FFFFFF",
"font-size": "14px",
"animationDuration": "20s",
"width": "100%",
"lineHeight": "35px"
}
def get_marquee_settings():
initialize_marquee_settings()
return st.session_state['marquee_settings']
def update_marquee_settings_ui():
st.sidebar.markdown("### 🎯 Marquee Settings")
cols = st.sidebar.columns(2)
with cols[0]:
bg_color = st.color_picker("🎨 Background",
st.session_state['marquee_settings']["background"],
key="bg_color_picker")
text_color = st.color_picker("✍️ Text",
st.session_state['marquee_settings']["color"],
key="text_color_picker")
with cols[1]:
font_size = st.slider("📏 Size", 10, 24, 14, key="font_size_slider")
duration = st.slider("⏱️ Speed", 1, 20, 20, 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=""):
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()
# remove short or unhelpful words
stop_short = set(['the', 'and', 'for', 'with', 'this', 'that', 'ai', 'library'])
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", max_length=200):
prefix = format_timestamp_prefix() + "_"
combined_text = (prompt + " " + response)[:200]
info_terms = get_high_info_terms(combined_text, top_n=5)
snippet = (prompt[:40] + " " + response[:40]).strip()
snippet_cleaned = clean_text_for_filename(snippet)
# remove duplicates
name_parts = info_terms + [snippet_cleaned]
seen = set()
unique_parts = []
for part in name_parts:
if part not in seen:
seen.add(part)
unique_parts.append(part)
full_name = '_'.join(unique_parts).strip('_')
leftover_chars = max_length - len(prefix) - len(file_type) - 1
if len(full_name) > leftover_chars:
full_name = full_name[:leftover_chars]
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'<a href="data:application/zip;base64,{b64}" download="{os.path.basename(file)}">📂 Download {os.path.basename(file)}</a>'
elif file_type == "mp3":
return f'<a href="data:audio/mpeg;base64,{b64}" download="{os.path.basename(file)}">🎵 Download {os.path.basename(file)}</a>'
elif file_type == "wav":
return f'<a href="data:audio/wav;base64,{b64}" download="{os.path.basename(file)}">🔊 Download {os.path.basename(file)}</a>'
elif file_type == "md":
return f'<a href="data:text/markdown;base64,{b64}" download="{os.path.basename(file)}">📝 Download {os.path.basename(file)}</a>'
else:
return f'<a href="data:application/octet-stream;base64,{b64}" download="{os.path.basename(file)}">Download {os.path.basename(file)}</a>'
def clean_for_speech(text: str) -> str:
text = text.replace("\n", " ")
text = text.replace("</s>", " ")
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):
if not voice:
voice = st.session_state['tts_voice']
combined_text = f"# Question\n{question}\n\n# Answer\n{answer}"
md_file = create_file(question, answer, "md")
audio_text = f"{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 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': '',
'full_audio': None,
'download_base64': '',
}
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 create_paper_links_md(papers):
lines = ["# Paper Links\n"]
for i, p in enumerate(papers, start=1):
lines.append(f"{i}. **{p['title']}** — [Arxiv]({p['url']})")
return "\n".join(lines)
def create_paper_audio_files(papers, input_question):
for paper in papers:
try:
audio_text = f"{paper['title']} by {paper['authors']}. {paper['summary']}"
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
if audio_file:
with open(audio_file, "rb") as af:
b64_data = base64.b64encode(af.read()).decode()
download_filename = os.path.basename(audio_file)
mime_type = "mpeg" if file_format == "mp3" else "wav"
paper['download_base64'] = (
f'<a href="data:audio/{mime_type};base64,{b64_data}" '
f'download="{download_filename}">🎵 Download {download_filename}</a>'
)
except Exception as e:
st.warning(f"Error processing paper {paper['title']}: {str(e)}")
paper['full_audio'] = None
paper['download_base64'] = ''
def display_papers(papers, marquee_settings):
st.write("## Research Papers")
for i, paper in enumerate(papers, start=1):
marquee_text = f"📄 {paper['title']} | 👤 {paper['authors'][:120]} | 📝 {paper['summary'][:200]}"
display_marquee(marquee_text, marquee_settings, key_suffix=f"paper_{i}")
with st.expander(f"{i}. 📄 {paper['title']}", expanded=True):
st.markdown(f"**{paper['date']} | {paper['title']} |** [Arxiv Link]({paper['url']})")
st.markdown(f"*Authors:* {paper['authors']}")
st.markdown(paper['summary'])
if paper.get('full_audio'):
st.write("📚 Paper Audio")
st.audio(paper['full_audio'])
if paper['download_base64']:
st.markdown(paper['download_base64'], unsafe_allow_html=True)
def display_papers_in_sidebar(papers):
st.sidebar.title("🎶 Papers & Audio")
for i, paper in enumerate(papers, start=1):
with st.sidebar.expander(f"{i}. {paper['title']}"):
st.markdown(f"**Arxiv:** [Link]({paper['url']})")
if paper['full_audio']:
st.audio(paper['full_audio'])
if paper['download_base64']:
st.markdown(paper['download_base64'], unsafe_allow_html=True)
st.markdown(f"**Authors:** {paper['authors']}")
if paper['summary']:
st.markdown(f"**Summary:** {paper['summary'][:300]}...")
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 for term in info_terms[:5])
short_zip_name = (timestamp + "_" + name_text)[:20] + ".zip"
with zipfile.ZipFile(short_zip_name, 'w') as z:
for f in all_files:
z.write(f)
return short_zip_name
def perform_ai_lookup(q, vocal_summary=True, extended_refs=False,
titles_summary=True, full_audio=False):
start = time.time()
ai_constitution = """
You are a talented AI coder and songwriter...
"""
# Claude:
client = anthropic.Anthropic(api_key=anthropic_key)
user_input = q
response = client.messages.create(
model="claude-3-sonnet-20240229",
max_tokens=1000,
messages=[
{"role": "user", "content": user_input}
])
st.write("Claude's reply 🧠:")
st.markdown(response.content[0].text)
result = response.content[0].text
create_file(q, result)
md_file, audio_file = save_qa_with_audio(q, result)
st.subheader("📝 Main Response Audio")
play_and_download_audio(audio_file, st.session_state['audio_format'])
# Arxiv:
st.write("Arxiv's AI this Evening...")
from gradio_client import Client
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"### 🔎 {q}\n\n{r2}\n\n{refs}"
md_file, audio_file = save_qa_with_audio(q, result)
st.subheader("📝 Main Response Audio")
play_and_download_audio(audio_file, st.session_state['audio_format'])
papers = parse_arxiv_refs(refs)
if papers:
paper_links = create_paper_links_md(papers)
links_file = create_file(q, paper_links, "md")
st.markdown(paper_links)
create_paper_audio_files(papers, input_question=q)
display_papers(papers, get_marquee_settings())
display_papers_in_sidebar(papers)
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("🔍 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("📝 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'])
# ----------------------------------------------------------------------------
# ADD HERE — FILE HISTORY SIDEBAR
def display_file_history_in_sidebar():
"""
Shows a history of each local .md, .mp3, .wav file in descending
order of modification time, with quick icons and optional download links.
"""
st.sidebar.markdown("---")
st.sidebar.markdown("### 📂 File History")
# Gather all files of interest
md_files = glob.glob("*.md")
mp3_files = glob.glob("*.mp3")
wav_files = glob.glob("*.wav")
all_files = md_files + mp3_files + wav_files
if not all_files:
st.sidebar.write("No files found.")
return
# Sort by newest first
all_files = sorted(all_files, key=os.path.getmtime, reverse=True)
for f in all_files:
fname = os.path.basename(f)
ext = os.path.splitext(fname)[1].lower().strip('.')
emoji = FILE_EMOJIS.get(ext, '📦')
time_str = datetime.fromtimestamp(os.path.getmtime(f)).strftime("%Y-%m-%d %H:%M:%S")
with st.sidebar.expander(f"{emoji} {fname}"):
st.write(f"**Modified:** {time_str}")
# Optionally show a snippet for .md:
if ext == "md":
with open(f, "r", encoding="utf-8") as file_in:
snippet = file_in.read(200).replace("\n", " ")
if len(snippet) == 200:
snippet += "..."
st.write(snippet)
st.markdown(get_download_link(f, file_type="md"), unsafe_allow_html=True)
# If it's audio, let user play it
elif ext in ["mp3","wav"]:
st.audio(f)
st.markdown(get_download_link(f, file_type=ext), unsafe_allow_html=True)
else:
st.markdown(get_download_link(f), unsafe_allow_html=True)
# ----------------------------------------------------------------------------
def main():
update_marquee_settings_ui()
marquee_settings = get_marquee_settings()
display_marquee(st.session_state['marquee_content'],
{**marquee_settings, "font-size": "28px", "lineHeight": "50px"},
key_suffix="welcome")
# -- Insert your main app tabs, logic, etc. --
tab_main = st.radio("Action:", ["🎤 Voice", "📸 Media", "🔍 ArXiv", "📝 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("✏️ Edit Input:", value=val_stripped, height=100)
run_option = st.selectbox("Model:", ["Arxiv"])
col1, col2 = st.columns(2)
with col1:
autorun = st.checkbox("⚙ AutoRun", value=True)
with col2:
full_audio = st.checkbox("📚FullAudio", 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
perform_ai_lookup(edited_input,
vocal_summary=True,
extended_refs=False,
titles_summary=True,
full_audio=full_audio)
else:
if st.button("▶ Run"):
st.session_state.old_val = val
st.session_state.last_query = edited_input
perform_ai_lookup(edited_input,
vocal_summary=True,
extended_refs=False,
titles_summary=True,
full_audio=full_audio)
if tab_main == "🔍 ArXiv":
st.subheader("🔍 Query ArXiv")
q = st.text_input("🔍 Query:", key="arxiv_query")
st.markdown("### 🎛 Options")
vocal_summary = st.checkbox("🎙ShortAudio", value=True, key="option_vocal_summary")
extended_refs = st.checkbox("📜LongRefs", value=False, key="option_extended_refs")
titles_summary = st.checkbox("🔖TitlesOnly", value=True, key="option_titles_summary")
full_audio = st.checkbox("📚FullAudio", value=False, key="option_full_audio")
full_transcript = st.checkbox("🧾FullTranscript", value=False, key="option_full_transcript")
if q and st.button("🔍Run"):
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 == "🎤 Voice":
st.subheader("🎤 Voice Input")
st.markdown("### 🎤 Voice Settings")
selected_voice = st.selectbox(
"Select TTS Voice:",
options=EDGE_TTS_VOICES,
index=EDGE_TTS_VOICES.index(st.session_state['tts_voice'])
)
st.markdown("### 🔊 Audio Format")
selected_format = st.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()
user_text = st.text_area("💬 Message:", height=100)
user_text = user_text.strip().replace('\n', ' ')
if st.button("📨 Send"):
process_voice_input(user_text)
st.subheader("📜 Chat History")
for c in st.session_state.chat_history:
st.write("**You:**", c["user"])
st.write("**Response:**", c["claude"])
elif tab_main == "📸 Media":
st.header("📸 Media Gallery")
tabs = st.tabs(["🎵 Audio", "🖼 Images", "🎥 Video"]) # audio first
with tabs[0]:
st.subheader("🎵 Audio Files")
audio_files = glob.glob("*.mp3") + glob.glob("*.wav")
if audio_files:
for a in audio_files:
with st.expander(os.path.basename(a)):
st.audio(a)
ext = os.path.splitext(a)[1].replace('.', '')
dl_link = get_download_link(a, file_type=ext)
st.markdown(dl_link, unsafe_allow_html=True)
else:
st.write("No audio files found.")
with tabs[1]:
st.subheader("🖼 Image Files")
imgs = glob.glob("*.png") + glob.glob("*.jpg") + glob.glob("*.jpeg")
if imgs:
c = st.slider("Cols", 1, 5, 3, key="cols_images")
cols = st.columns(c)
for i, f in enumerate(imgs):
with cols[i % c]:
st.image(Image.open(f), use_container_width=True)
else:
st.write("No images found.")
with tabs[2]:
st.subheader("🎥 Video Files")
vids = glob.glob("*.mp4") + glob.glob("*.mov") + glob.glob("*.avi")
if vids:
for v in vids:
with st.expander(os.path.basename(v)):
st.video(v)
else:
st.write("No videos found.")
elif tab_main == "📝 Editor":
st.write("Select or create a file to edit. (Currently minimal)")
# --- IMPORTANT: Display the file-history in the sidebar
display_file_history_in_sidebar()
st.markdown("""
<style>
.main { background: linear-gradient(to right, #1a1a1a, #2d2d2d); color: #fff; }
.stMarkdown { font-family: 'Helvetica Neue', sans-serif; }
.stButton>button { margin-right: 0.5rem; }
</style>
""", unsafe_allow_html=True)
if st.session_state.should_rerun:
st.session_state.should_rerun = False
st.rerun()
if __name__ == "__main__":
main()