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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" | |
] | |
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") | |
# Initialize session state variables | |
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" | |
# 🔑 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": "📝", | |
"mp3": "🎵", | |
"wav": "🔊" | |
} | |
# Functions | |
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'<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): | |
"""Save Q&A to markdown and generate audio""" | |
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: {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 perform_ai_lookup(q, vocal_summary=True, extended_refs=False, | |
titles_summary=True, full_audio=False, marquee_settings=None): | |
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"### 🔎 {q}\n\n{r2}\n\n{refs}" | |
st.markdown(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']) | |
papers = parse_arxiv_refs(refs) | |
if papers: | |
create_paper_audio_files(papers, input_question=q) | |
if marquee_settings: | |
display_papers(papers, marquee_settings) | |
else: | |
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("🔍 Search Results") | |
result = perform_ai_lookup( | |
text, | |
vocal_summary=True, | |
extended_refs=False, | |
titles_summary=True, | |
full_audio=True, | |
marquee_settings=marquee_settings) | |
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']) | |
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("🎵 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("🗑 DelMD"): | |
for f in all_md: | |
os.remove(f) | |
st.session_state.should_rerun = True | |
with col2: | |
if st.button("🗑 DelMP3"): | |
for f in all_mp3: | |
os.remove(f) | |
st.session_state.should_rerun = True | |
with col3: | |
if st.button("🗑 DelWAV"): | |
for f in all_wav: | |
os.remove(f) | |
st.session_state.should_rerun = True | |
with col4: | |
if st.button("⬇️ 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"📁 {group_label} ({len(files)})", expanded=True): | |
c1, c2 = st.columns(2) | |
with c1: | |
if st.button("👀 View", key=f"view_group_{group_name}"): | |
st.session_state.viewing_prefix = group_name | |
with c2: | |
if st.button("🗑 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 get_marquee_settings(): | |
st.sidebar.markdown("### 🎯 Marquee Settings") | |
cols = st.sidebar.columns(2) | |
with cols[0]: | |
bg_color = st.color_picker("🎨 Background", "#1E1E1E", key="bg_color_picker") | |
text_color = st.color_picker("✍️ Text", "#FFFFFF", 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, 10, key="duration_slider") | |
return { | |
"background": bg_color, | |
"color": text_color, | |
"font-size": f"{font_size}px", | |
"animationDuration": f"{duration}s", | |
"width": "100%", | |
"lineHeight": "35px" | |
} | |
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 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 process_paper_content(paper): | |
marquee_text = f"📄 {paper['title']} | 👤 {paper['authors'][:100]} | 📝 {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}. 📄 {paper['title']}", expanded=True): | |
st.markdown(f"**{paper['date']} | {paper['title']} | ⬇️**") | |
st.markdown(f"*{paper['authors']}*") | |
st.markdown(paper['summary']) | |
if paper.get('full_audio'): | |
st.write("📚 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 main(): | |
marquee_settings = get_marquee_settings() | |
display_marquee(st.session_state['marquee_content'], | |
{**marquee_settings, "font-size": "28px", "lineHeight": "50px"}, | |
key_suffix="welcome") | |
groups_sorted = load_files_for_sidebar() | |
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] | |
st.sidebar.markdown("### 🎤 Voice Settings") | |
selected_voice = st.sidebar.selectbox( | |
"Select TTS Voice:", | |
options=EDGE_TTS_VOICES, | |
index=EDGE_TTS_VOICES.index(st.session_state['tts_voice']) | |
) | |
st.sidebar.markdown("### 🔊 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() | |
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", "GPT-4o", "Claude-3.5"]) | |
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 | |
result = perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False, | |
titles_summary=True, full_audio=full_audio, | |
marquee_settings=marquee_settings) | |
else: | |
if st.button("▶ 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, | |
marquee_settings=marquee_settings) | |
if tab_main == "🔍 ArXiv": | |
st.subheader("🔍 Query ArXiv") | |
q = st.text_input("🔍 Query:") | |
st.markdown("### 🎛 Options") | |
vocal_summary = st.checkbox("🎙ShortAudio", value=True) | |
extended_refs = st.checkbox("📜LongRefs", value=False) | |
titles_summary = st.checkbox("🔖TitlesOnly", value=True) | |
full_audio = st.checkbox("📚FullAudio", value=False) | |
full_transcript = st.checkbox("🧾FullTranscript", value=False) | |
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, | |
marquee_settings=marquee_settings) | |
elif tab_main == "🎤 Voice": | |
st.subheader("🎤 Voice Input") | |
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("📸 Images & 🎥 Videos") | |
tabs = st.tabs(["🖼 Images", "🎥 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"👀 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"🎥 {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 == "📝 Editor": | |
if st.session_state.editing_file: | |
st.subheader(f"Editing: {st.session_state.editing_file}") | |
new_text = st.text_area("✏️ Content:", st.session_state.edit_new_content, height=300) | |
if st.button("💾 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_sidebar(groups_sorted) | |
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("❌ Close"): | |
st.session_state.viewing_prefix = None | |
st.session_state['marquee_content'] = "🚀 Welcome to TalkingAIResearcher | 🤖 Your Research Assistant" | |
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() |