Update app.py

app.py

@@ -1,105 +1,204 @@
 import streamlit as st
-import anthropic, openai, base64, cv2, glob, os, re, time, zipfile
+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 collections import defaultdict
+from audio_recorder_streamlit import audio_recorder
+from bs4 import BeautifulSoup
+from collections import defaultdict, deque
 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 asyncio, edge_tts
+import extra_streamlit_components as stx
+from streamlit.runtime.scriptrunner import get_script_run_ctx
+import asyncio
+import edge_tts
 
 # 🎯 1. Core Configuration & Setup
 st.set_page_config(
-    page_title="🚲BikeAI Research", page_icon="🚲", layout="wide",
-    menu_items={'About': "🚲BikeAI Research Assistant"}
+    page_title="🚲BikeAI🏆 Claude/GPT Research",
+    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': "🚲BikeAI🏆 Claude/GPT Research AI"
+    }
 )
 load_dotenv()
 
-# 🔑 2. API Setup
-openai_api_key = st.secrets.get('OPENAI_API_KEY', os.getenv('OPENAI_API_KEY', ""))
-anthropic_key = st.secrets.get('ANTHROPIC_API_KEY', os.getenv('ANTHROPIC_API_KEY_3', ""))
-openai_client = OpenAI(api_key=openai_api_key, organization=os.getenv('OPENAI_ORG_ID'))
-claude_client = anthropic.Anthropic(api_key=anthropic_key)
-
-# 📝 3. Session State
-for key in ['transcript_history', 'chat_history', 'messages', 'viewing_prefix', 'should_rerun', 'old_val']:
-    if key not in st.session_state:
-        st.session_state[key] = [] if key in ['transcript_history', 'chat_history', 'messages'] else None
+# 🔑 2. API Setup & Clients
+openai_api_key = os.getenv('OPENAI_API_KEY', "")
+anthropic_key = os.getenv('ANTHROPIC_API_KEY_3', "")
+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"]
 
-st.session_state.setdefault('openai_model', "gpt-4o-2024-05-13")
-
-# 🧠 4. Content Processing
+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')
+
+# 📝 3. Session State Management
+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
+
+# 🎨 4. Custom CSS
+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)
+
+FILE_EMOJIS = {
+    "md": "📝",
+    "mp3": "🎵",
+}
+
+# 🧠 5. High-Information Content Extraction
 def get_high_info_terms(text: str) -> list:
-    """Extract high-information terms from text"""
+    """Extract high-information terms from text, including key phrases"""
     stop_words = set([
         'the', 'a', 'an', 'and', 'or', 'but', 'in', 'on', 'at', 'to', 'for', 'of', 'with',
-        'by', 'from', 'up', 'about', 'into', 'over', 'after', 'be', 'been', 'being', 'have',
-        'has', 'had', 'do', 'does', 'did', 'will', 'would', 'should', 'could', 'this', 'that'
+        'by', 'from', 'up', 'about', 'into', 'over', 'after', 'is', 'are', 'was', 'were',
+        'be', 'been', 'being', 'have', 'has', 'had', 'do', 'does', 'did', 'will', 'would',
+        'should', 'could', 'might', 'must', 'shall', 'can', 'may', 'this', 'that', 'these',
+        'those', 'i', 'you', 'he', 'she', 'it', 'we', 'they', 'what', 'which', 'who',
+        'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most',
+        'other', 'some', 'such', 'than', 'too', 'very', 'just', 'there'
     ])
 
     key_phrases = [
         'artificial intelligence', 'machine learning', 'deep learning', 'neural network',
-        'natural language', 'computer vision', 'data science', 'reinforcement learning',
-        'large language model', 'transformer model', 'quantum computing', 'arxiv search'
+        'personal assistant', 'natural language', 'computer vision', 'data science',
+        'reinforcement learning', 'knowledge graph', 'semantic search', 'time series',
+        'large language model', 'transformer model', 'attention mechanism',
+        'autonomous system', 'edge computing', 'quantum computing', 'blockchain technology',
+        'cognitive science', 'human computer', 'decision making', 'arxiv search',
+        'research paper', 'scientific study', 'empirical analysis'
     ]
 
-    preserved_phrases = [phrase for phrase in key_phrases if phrase in text.lower()]
-    text = text.lower()
-    for phrase in preserved_phrases:
-        text = text.replace(phrase, '')
+    # First identify key phrases
+    preserved_phrases = []
+    lower_text = text.lower()
+    for phrase in key_phrases:
+        if phrase in lower_text:
+            preserved_phrases.append(phrase)
+            text = text.replace(phrase, '')
+
+    # Then extract individual high-info words
+    words = re.findall(r'\b\w+(?:-\w+)*\b', text)
+    high_info_words = [
+        word.lower() for word in words 
+        if len(word) > 3
+        and word.lower() not in stop_words
+        and not word.isdigit()
+        and any(c.isalpha() for c in word)
+    ]
 
-    words = [word.lower() for word in re.findall(r'\b\w+(?:-\w+)*\b', text)
-             if len(word) > 3 and word.lower() not in stop_words
-             and not word.isdigit() and any(c.isalpha() for c in word)]
+    # Combine and deduplicate while preserving order
+    all_terms = preserved_phrases + high_info_words
+    seen = set()
+    unique_terms = []
+    for term in all_terms:
+        if term not in seen:
+            seen.add(term)
+            unique_terms.append(term)
 
-    unique_terms = list(dict.fromkeys(preserved_phrases + words))
-    return unique_terms[:5]
+    max_terms = 5
+    return unique_terms[:max_terms]
 
-# 📁 5. File Operations
+# 📁 6. File Operations
 def generate_filename(content, file_type="md"):
-    """Generate filename with high-information terms"""
+    """Generate filename with meaningful terms"""
     prefix = datetime.now().strftime("%y%m_%H%M") + "_"
     info_terms = get_high_info_terms(content)
     name_text = '_'.join(term.replace(' ', '-') for term in info_terms) if info_terms else 'file'
-    return f"{prefix}{name_text[:100]}.{file_type}"
+    
+    max_length = 100
+    if len(name_text) > max_length:
+        name_text = name_text[:max_length]
+    
+    filename = f"{prefix}{name_text}.{file_type}"
+    return filename
 
 def create_file(prompt, response, file_type="md"):
-    """Create a new file with generated filename"""
-    filename = generate_filename(response.strip() or prompt.strip(), file_type)
+    """Create file with intelligent naming"""
+    filename = generate_filename(response.strip() if response.strip() else prompt.strip(), file_type)
     with open(filename, 'w', encoding='utf-8') as f:
-        f.write(f"{prompt}\n\n{response}")
+        f.write(prompt + "\n\n" + response)
     return filename
 
-def create_zip_of_files(md_files, mp3_files):
-    """Create zip with intelligent naming"""
-    all_files = [f for f in md_files if 'readme.md' not in f.lower()] + mp3_files
-    if not all_files:
-        return None
-
-    content = " ".join(open(f, 'r', encoding='utf-8').read() if f.endswith('.md')
-                      else os.path.basename(f) for f in all_files)
-    
-    timestamp = datetime.now().strftime("%y%m_%H%M")
-    info_terms = get_high_info_terms(content)[:3]
-    zip_name = f"{timestamp}_{'_'.join(t.replace(' ', '-') for t in info_terms)}.zip"
-    
-    with zipfile.ZipFile(zip_name, 'w') as z:
-        for f in all_files:
-            z.write(f)
-    return zip_name
+def get_download_link(file):
+    """Generate download link for file"""
+    with open(file, "rb") as f:
+        b64 = base64.b64encode(f.read()).decode()
+    return f'<a href="data:file/zip;base64,{b64}" download="{os.path.basename(file)}">📂 Download {os.path.basename(file)}</a>'
 
-# 🔊 6. Audio Processing
+# 🔊 7. Audio Processing
 def clean_for_speech(text: str) -> str:
-    """Prepare text for speech synthesis"""
-    text = re.sub(r'\n|</s>|#|\(https?:\/\/[^\)]+\)|\s+', ' ', text)
-    return text.strip()
+    """Clean text for speech synthesis"""
+    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
+
+@st.cache_resource
+def speech_synthesis_html(result):
+    """Create HTML for speech synthesis"""
+    html_code = f"""
+    <html><body>
+    <script>
+    var msg = new SpeechSynthesisUtterance("{result.replace('"', '')}");
+    window.speechSynthesis.speak(msg);
+    </script>
+    </body></html>
+    """
+    components.html(html_code, height=0)
 
 async def edge_tts_generate_audio(text, voice="en-US-AriaNeural", rate=0, pitch=0):
-    """Generate audio file using Edge TTS"""
+    """Generate audio using Edge TTS"""
     text = clean_for_speech(text)
     if not text.strip():
         return None
-    communicate = edge_tts.Communicate(text, voice, rate=f"{rate:+d}%", pitch=f"{pitch:+d}Hz")
+    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, "mp3")
     await communicate.save(out_fn)
     return out_fn
@@ -108,11 +207,19 @@ def speak_with_edge_tts(text, voice="en-US-AriaNeural", rate=0, pitch=0):
     """Wrapper for edge TTS generation"""
     return asyncio.run(edge_tts_generate_audio(text, voice, rate, pitch))
 
-# 🎬 7. Media Processing
+def play_and_download_audio(file_path):
+    """Play and provide download link for audio"""
+    if file_path and os.path.exists(file_path):
+        st.audio(file_path)
+        dl_link = f'<a href="data:audio/mpeg;base64,{base64.b64encode(open(file_path,"rb").read()).decode()}" download="{os.path.basename(file_path)}">Download {os.path.basename(file_path)}</a>'
+        st.markdown(dl_link, unsafe_allow_html=True)
+
+# 🎬 8. Media Processing
 def process_image(image_path, user_prompt):
     """Process image with GPT-4V"""
     with open(image_path, "rb") as imgf:
-        b64img = base64.b64encode(imgf.read()).decode("utf-8")
+        image_data = imgf.read()
+    b64img = base64.b64encode(image_data).decode("utf-8")
     resp = openai_client.chat.completions.create(
         model=st.session_state["openai_model"],
         messages=[
@@ -126,129 +233,380 @@ def process_image(image_path, user_prompt):
     )
     return resp.choices[0].message.content
 
-# 🤖 8. AI Integration
+def process_audio(audio_path):
+    """Process audio with Whisper"""
+    with open(audio_path, "rb") as f:
+        transcription = openai_client.audio.transcriptions.create(model="whisper-1", file=f)
+    st.session_state.messages.append({"role": "user", "content": transcription.text})
+    return transcription.text
+
+def process_video(video_path, seconds_per_frame=1):
+    """Extract frames from video"""
+    vid = cv2.VideoCapture(video_path)
+    total = int(vid.get(cv2.CAP_PROP_FRAME_COUNT))
+    fps = vid.get(cv2.CAP_PROP_FPS)
+    skip = int(fps*seconds_per_frame)
+    frames_b64 = []
+    for i in range(0, total, skip):
+        vid.set(cv2.CAP_PROP_POS_FRAMES, i)
+        ret, frame = vid.read()
+        if not ret: break
+        _, buf = cv2.imencode(".jpg", frame)
+        frames_b64.append(base64.b64encode(buf).decode("utf-8"))
+    vid.release()
+    return frames_b64
+
+def process_video_with_gpt(video_path, prompt):
+    """Analyze video frames with GPT-4V"""
+    frames = process_video(video_path)
+    resp = openai_client.chat.completions.create(
+        model=st.session_state["openai_model"],
+        messages=[
+            {"role":"system","content":"Analyze video frames."},
+            {"role":"user","content":[
+                {"type":"text","text":prompt},
+                *[{"type":"image_url","image_url":{"url":f"data:image/jpeg;base64,{fr}"}} for fr in frames]
+            ]}
+        ]
+    )
+    return resp.choices[0].message.content
+
+# 🤖 9. AI Model Integration
 def perform_ai_lookup(q, vocal_summary=True, extended_refs=False, titles_summary=True, full_audio=False):
     """Perform Arxiv search and generate audio summaries"""
     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]
-    answer = client.predict(q, "mistralai/Mixtral-8x7B-Instruct-v0.1", True, api_name="/ask_llm")
-    result = f"### 🔎 {q}\n\n{answer}\n\n{refs}"
+    r = client.predict(q,20,"Semantic Search","mistralai/Mixtral-8x7B-Instruct-v0.1",api_name="/update_with_rag_md")
+    refs = r[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)
 
+    # Generate full audio version if requested
     if full_audio:
-        complete_text = f"Query: {q}. {clean_for_speech(answer)} {clean_for_speech(refs)}"
+        complete_text = f"Complete response for query: {q}. {clean_for_speech(r2)} {clean_for_speech(refs)}"
+        audio_file_full = speak_with_edge_tts(complete_text)
         st.write("### 📚 Complete Audio Response")
-        play_and_download_audio(speak_with_edge_tts(complete_text))
+        play_and_download_audio(audio_file_full)
 
     if vocal_summary:
-        st.write("### 🎙️ Vocal Summary")
-        play_and_download_audio(speak_with_edge_tts(clean_for_speech(answer)))
+        main_text = clean_for_speech(r2)
+        audio_file_main = speak_with_edge_tts(main_text)
+        st.write("### 🎙️ Vocal Summary (Short Answer)")
+        play_and_download_audio(audio_file_main)
 
     if extended_refs:
-        st.write("### 📜 Extended References")
-        play_and_download_audio(speak_with_edge_tts(
-            "Reference summaries: " + clean_for_speech(refs)))
+        summaries_text = "Here are the summaries from the references: " + refs.replace('"','')
+        summaries_text = clean_for_speech(summaries_text)
+        audio_file_refs = speak_with_edge_tts(summaries_text)
+        st.write("### 📜 Extended References & Summaries")
+        play_and_download_audio(audio_file_refs)
 
     if titles_summary:
-        titles = [m.group(1) for m in re.finditer(r"\[([^\]]+)\]", refs)]
+        titles = []
+        for line in refs.split('\n'):
+            m = re.search(r"\[([^\]]+)\]", line)
+            if m:
+                titles.append(m.group(1))
         if titles:
+            titles_text = "Here are the titles of the papers: " + ", ".join(titles)
+            titles_text = clean_for_speech(titles_text)
+            audio_file_titles = speak_with_edge_tts(titles_text)
             st.write("### 🔖 Paper Titles")
-            play_and_download_audio(speak_with_edge_tts(
-                "Paper titles: " + ", ".join(titles)))
+            play_and_download_audio(audio_file_titles)
 
-    st.write(f"**Time:** {time.time()-start:.2f} s")
-    create_file(q, result)
+    elapsed = time.time()-start
+    st.write(f"**Total Elapsed:** {elapsed:.2f} s")
+    create_file(q, result, "md")
     return result
 
 def process_with_gpt(text):
     """Process text with GPT-4"""
-    if not text:
-        return
+    if not text: return
     st.session_state.messages.append({"role":"user","content":text})
-    with st.chat_message("user"): st.markdown(text)
+    with st.chat_message("user"):
+        st.markdown(text)
     with st.chat_message("assistant"):
-        resp = openai_client.chat.completions.create(
+        c = openai_client.chat.completions.create(
             model=st.session_state["openai_model"],
             messages=st.session_state.messages,
             stream=False
         )
-        ans = resp.choices[0].message.content
-        st.write(f"GPT-4o: {ans}")
-        create_file(text, ans)
+        ans = c.choices[0].message.content
+        st.write("GPT-4o: " + ans)
+        create_file(text, ans, "md")
         st.session_state.messages.append({"role":"assistant","content":ans})
     return ans
 
 def process_with_claude(text):
     """Process text with Claude"""
-    if not text:
-        return
-    with st.chat_message("user"): st.markdown(text)
+    if not text: return
+    with st.chat_message("user"):
+        st.markdown(text)
     with st.chat_message("assistant"):
-        resp = claude_client.messages.create(
+        r = claude_client.messages.create(
             model="claude-3-sonnet-20240229",
             max_tokens=1000,
             messages=[{"role":"user","content":text}]
         )
-        ans = resp.content[0].text
-        st.write(f"Claude-3.5: {ans}")
-        create_file(text, ans)
+        ans = r.content[0].text
+        st.write("Claude-3.5: " + ans)
+        create_file(text, ans, "md")
         st.session_state.chat_history.append({"user":text,"claude":ans})
     return ans
 
-def play_and_download_audio(file_path):
-    """Play and provide download link for audio file"""
-    if file_path and os.path.exists(file_path):
-        st.audio(file_path)
-        dl_link = f'<a href="data:audio/mpeg;base64,{base64.b64encode(open(file_path,"rb").read()).decode()}" download="{os.path.basename(file_path)}">Download {os.path.basename(file_path)}</a>'
-        st.markdown(dl_link, unsafe_allow_html=True)
+# 📂 10. File Management
+def create_zip_of_files(md_files, mp3_files):
+    """Create zip with intelligent naming"""
+    md_files = [f for f in md_files if os.path.basename(f).lower() != 'readme.md']
+    all_files = md_files + mp3_files
+    if not all_files:
+        return None
 
-# 🎯 9. Main Application
+    # Collect content for high-info term extraction
+    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'):
+            all_content.append(os.path.basename(f))
+    
+    combined_content = " ".join(all_content)
+    info_terms = get_high_info_terms(combined_content)
+    
+    timestamp = datetime.now().strftime("%y%m_%H%M")
+    name_text = '_'.join(term.replace(' ', '-') for term in info_terms[:3])
+    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 load_files_for_sidebar():
+    """Load and group files for sidebar display"""
+    md_files = glob.glob("*.md")
+    mp3_files = glob.glob("*.mp3")
+
+    md_files = [f for f in md_files if os.path.basename(f).lower() != 'readme.md']
+    all_files = md_files + mp3_files
+
+    groups = defaultdict(list)
+    for f in all_files:
+        fname = os.path.basename(f)
+        prefix = fname[:10]
+        groups[prefix].append(f)
+
+    for prefix in groups:
+        groups[prefix].sort(key=lambda x: os.path.getmtime(x), reverse=True)
+
+    sorted_prefixes = sorted(groups.keys(), 
+                           key=lambda pre: max(os.path.getmtime(x) for x in groups[pre]), 
+                           reverse=True)
+    return groups, sorted_prefixes
+
+def extract_keywords_from_md(files):
+    """Extract keywords from markdown files"""
+    text = ""
+    for f in files:
+        if f.endswith(".md"):
+            c = open(f,'r',encoding='utf-8').read()
+            text += " " + c
+    return get_high_info_terms(text)
+
+def display_file_manager_sidebar(groups, sorted_prefixes):
+    """Display file manager in sidebar"""
+    st.sidebar.title("🎵 Audio & Document Manager")
+
+    all_md = []
+    all_mp3 = []
+    for prefix in groups:
+        for f in groups[prefix]:
+            if f.endswith(".md"):
+                all_md.append(f)
+            elif f.endswith(".mp3"):
+                all_mp3.append(f)
+
+    top_bar = st.sidebar.columns(3)
+    with top_bar[0]:
+        if st.button("🗑 Del All MD"):
+            for f in all_md:
+                os.remove(f)
+            st.session_state.should_rerun = True
+    with top_bar[1]:
+        if st.button("🗑 Del All MP3"):
+            for f in all_mp3:
+                os.remove(f)
+            st.session_state.should_rerun = True
+    with top_bar[2]:
+        if st.button("⬇️ Zip All"):
+            z = create_zip_of_files(all_md, all_mp3)
+            if z:
+                st.sidebar.markdown(get_download_link(z),unsafe_allow_html=True)
+
+    for prefix in sorted_prefixes:
+        files = groups[prefix]
+        kw = extract_keywords_from_md(files)
+        keywords_str = " ".join(kw) if kw else "No Keywords"
+        with st.sidebar.expander(f"{prefix} Files ({len(files)}) - Keywords: {keywords_str}", expanded=True):
+            c1,c2 = st.columns(2)
+            with c1:
+                if st.button("👀View Group", key="view_group_"+prefix):
+                    st.session_state.viewing_prefix = prefix
+            with c2:
+                if st.button("🗑Del Group", key="del_group_"+prefix):
+                    for f in files:
+                        os.remove(f)
+                    st.success(f"Deleted all files in group {prefix} successfully!")
+                    st.session_state.should_rerun = True
+
+            for f in files:
+                fname = os.path.basename(f)
+                ctime = datetime.fromtimestamp(os.path.getmtime(f)).strftime("%Y-%m-%d %H:%M:%S")
+                st.write(f"**{fname}** - {ctime}")
+
+# 🎯 11. Main Application
 def main():
-    st.sidebar.title("🚲BikeAI Research")
-    tab_main = st.radio("Action:", ["🔍 Search ArXiv", "🎤 Voice", "📸 Media", "📝 Files"], horizontal=True)
+    st.sidebar.markdown("### 🚲BikeAI🏆 Multi-Agent Research AI")
+    tab_main = st.radio("Action:",["🎤 Voice Input","📸 Media Gallery","🔍 Search ArXiv","📝 File Editor"],horizontal=True)
+
+    mycomponent = components.declare_component("mycomponent", path="mycomponent")
+    val = mycomponent(my_input_value="Hello")
+
+    # Show input in a text box for editing if detected
+    if val:
+        val_stripped = val.replace('\n', ' ')
+        edited_input = st.text_area("Edit your detected input:", value=val_stripped, height=100)
+        run_option = st.selectbox("Select AI Model:", ["Arxiv", "GPT-4o", "Claude-3.5"])
+        col1, col2 = st.columns(2)
+        with col1:
+            autorun = st.checkbox("AutoRun on input change", value=False)
+        with col2:
+            full_audio = st.checkbox("Generate Complete Audio", value=False, 
+                                   help="Generate audio for the complete response including all papers and summaries")
+
+        input_changed = (val != st.session_state.old_val)
+
+        if autorun and input_changed:
+            st.session_state.old_val = val
+            if run_option == "Arxiv":
+                perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False, 
+                                titles_summary=True, full_audio=full_audio)
+            else:
+                if run_option == "GPT-4o":
+                    process_with_gpt(edited_input)
+                elif run_option == "Claude-3.5":
+                    process_with_claude(edited_input)
+        else:
+            if st.button("Process Input"):
+                st.session_state.old_val = val
+                if run_option == "Arxiv":
+                    perform_ai_lookup(edited_input, vocal_summary=True, extended_refs=False, 
+                                    titles_summary=True, full_audio=full_audio)
+                else:
+                    if run_option == "GPT-4o":
+                        process_with_gpt(edited_input)
+                    elif run_option == "Claude-3.5":
+                        process_with_claude(edited_input)
 
     if tab_main == "🔍 Search ArXiv":
+        st.subheader("🔍 Search ArXiv")
         q = st.text_input("Research query:")
-        st.markdown("### 🎛️ Audio Options")
-        cols = st.columns(4)
-        options = {
-            'vocal_summary': cols[0].checkbox("🎙️ Summary", value=True),
-            'extended_refs': cols[1].checkbox("📜 References", value=False),
-            'titles_summary': cols[2].checkbox("🔖 Titles", value=True),
-            'full_audio': cols[3].checkbox("📚 Full Response", value=False,
-                help="Generate complete audio including papers")
-        }
-        if q and st.button("Search"):
-            perform_ai_lookup(q, **options)
-
-    elif tab_main == "🎤 Voice":
-        user_text = st.text_area("Message:", height=100).strip()
-        model = st.selectbox("Model:", ["GPT-4o", "Claude-3.5"])
-        if st.button("Send 📨"):
-            if model == "GPT-4o":
-                process_with_gpt(user_text)
-            else:
-                process_with_claude(user_text)
 
-    elif tab_main == "📸 Media":
+        st.markdown("### 🎛️ Audio Generation Options")
+        vocal_summary = st.checkbox("🎙️ Vocal Summary (Short Answer)", value=True)
+        extended_refs = st.checkbox("📜 Extended References & Summaries (Long)", value=False)
+        titles_summary = st.checkbox("🔖 Paper Titles Only", value=True)
+        full_audio = st.checkbox("📚 Generate Complete Audio Response", value=False,
+                               help="Generate audio for the complete response including all papers and summaries")
+
+        if q and st.button("Run ArXiv Query"):
+            perform_ai_lookup(q, vocal_summary=vocal_summary, extended_refs=extended_refs, 
+                            titles_summary=titles_summary, full_audio=full_audio)
+
+    elif tab_main == "🎤 Voice Input":
+        st.subheader("🎤 Voice Recognition")
+        user_text = st.text_area("Message:", height=100)
+        user_text = user_text.strip().replace('\n', ' ')
+        if st.button("Send 📨"):
+            process_with_gpt(user_text)
+        st.subheader("📜 Chat History")
+        t1,t2=st.tabs(["Claude History","GPT-4o History"])
+        with t1:
+            for c in st.session_state.chat_history:
+                st.write("**You:**", c["user"])
+                st.write("**Claude:**", c["claude"])
+        with t2:
+            for m in st.session_state.messages:
+                with st.chat_message(m["role"]):
+                    st.markdown(m["content"])
+
+    elif tab_main == "📸 Media Gallery":
+        st.header("🎬 Media Gallery - Images and Videos")
         tabs = st.tabs(["🖼️ Images", "🎥 Video"])
         with tabs[0]:
-            for f in glob.glob("*.png") + glob.glob("*.jpg"):
-                st.image(Image.open(f))
-                if st.button(f"Analyze {os.path.basename(f)}", key=f"analyze_{f}"):
-                    st.markdown(process_image(f, "Describe this image."))
-
-    elif tab_main == "📝 Files":
-        md_files = [f for f in glob.glob("*.md") if 'readme.md' not in f.lower()]
-        mp3_files = glob.glob("*.mp3")
-        if st.button("Create Archive"):
-            zip_file = create_zip_of_files(md_files, mp3_files)
-            if zip_file:
-                with open(zip_file, "rb") as f:
-                    st.download_button("Download Archive", f, zip_file)
-
-if __name__ == "__main__":
+            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}"):
+                            a = process_image(f,"Describe this image.")
+                            st.markdown(a)
+            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}"):
+                            a = process_video_with_gpt(v,"Describe video.")
+                            st.markdown(a)
+            else:
+                st.write("No videos found.")
+
+    elif tab_main == "📝 File Editor":
+        if getattr(st.session_state,'current_file',None):
+            st.subheader(f"Editing: {st.session_state.current_file}")
+            new_text = st.text_area("Content:", st.session_state.file_content, height=300)
+            if st.button("Save"):
+                with open(st.session_state.current_file,'w',encoding='utf-8') as f:
+                    f.write(new_text)
+                st.success("Updated!")
+                st.session_state.should_rerun = True
+        else:
+            st.write("Select a file from the sidebar to edit.")
+
+    groups, sorted_prefixes = load_files_for_sidebar()
+    display_file_manager_sidebar(groups, sorted_prefixes)
+
+    if st.session_state.viewing_prefix and st.session_state.viewing_prefix in groups:
+        st.write("---")
+        st.write(f"**Viewing Group:** {st.session_state.viewing_prefix}")
+        for f in groups[st.session_state.viewing_prefix]:
+            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 == "mp3":
+                st.audio(f)
+            else:
+                st.markdown(get_download_link(f), unsafe_allow_html=True)
+        if st.button("Close Group View"):
+            st.session_state.viewing_prefix = None
+
+    if st.session_state.should_rerun:
+        st.session_state.should_rerun = False
+        st.rerun()
+
+if __name__=="__main__":
     main()