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| import streamlit as st | |
| import anthropic, openai, base64, cv2, glob, json, math, os, pytz, random, re, requests, 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 | |
| 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 | |
| # 🎯 1. Core Configuration & Setup | |
| st.set_page_config( | |
| 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 & 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') | |
| # 📝 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; | |
| } | |
| .audio-player { | |
| margin: 1rem 0; | |
| padding: 1rem; | |
| border-radius: 10px; | |
| background: #f5f5f5; | |
| box-shadow: 0 2px 4px rgba(0,0,0,0.1); | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| FILE_EMOJIS = { | |
| "md": "📝", | |
| "mp3": "🎵", | |
| } | |
| def clean_for_speech(text: str) -> str: | |
| """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 | |
| 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 using Edge TTS""" | |
| 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, "mp3") | |
| await communicate.save(out_fn) | |
| return out_fn | |
| 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)) | |
| 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) | |
| def save_full_transcript(query, text): | |
| """Save full transcript of Arxiv results as a file.""" | |
| create_file(query, text, "md") | |
| 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] | |
| 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"Complete response for query: {q}. {clean_for_speech(r2)} {clean_for_speech(refs)}" | |
| audio_file_full = speak_with_edge_tts(complete_text) | |
| st.write("### 📚 Full Audio") | |
| play_and_download_audio(audio_file_full) | |
| if vocal_summary: | |
| main_text = clean_for_speech(r2) | |
| audio_file_main = speak_with_edge_tts(main_text) | |
| st.write("### 🎙 Short Audio") | |
| play_and_download_audio(audio_file_main) | |
| if extended_refs: | |
| summaries_text = "Extended references: " + refs.replace('"','') | |
| summaries_text = clean_for_speech(summaries_text) | |
| audio_file_refs = speak_with_edge_tts(summaries_text) | |
| st.write("### 📜 Long Refs") | |
| play_and_download_audio(audio_file_refs) | |
| if titles_summary: | |
| titles = [] | |
| for line in refs.split('\n'): | |
| m = re.search(r"\[([^\]]+)\]", line) | |
| if m: | |
| titles.append(m.group(1)) | |
| if titles: | |
| titles_text = "Titles: " + ", ".join(titles) | |
| titles_text = clean_for_speech(titles_text) | |
| audio_file_titles = speak_with_edge_tts(titles_text) | |
| st.write("### 🔖 Titles") | |
| play_and_download_audio(audio_file_titles) | |
| elapsed = time.time()-start | |
| st.write(f"**Total Elapsed:** {elapsed:.2f} s") | |
| # Create file with result | |
| create_file(q, result, "md") | |
| return result | |
| def process_with_gpt(text): | |
| """Process text with GPT-4""" | |
| 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("assistant"): | |
| c = openai_client.chat.completions.create( | |
| model=st.session_state["openai_model"], | |
| messages=st.session_state.messages, | |
| stream=False | |
| ) | |
| 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) | |
| with st.chat_message("assistant"): | |
| r = claude_client.messages.create( | |
| model="claude-3-sonnet-20240229", | |
| max_tokens=1000, | |
| messages=[{"role":"user","content":text}] | |
| ) | |
| 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 generate_filename(prompt, response, file_type="md"): | |
| """Generate filename with timestamp and cleaned text.""" | |
| timestamp = datetime.now().strftime("%y%m_%H%M") | |
| safe_text = re.sub(r'[^\w\s-]', '', prompt[:50]) | |
| return f"{timestamp}_{safe_text}.{file_type}" | |
| def create_file(prompt, response, file_type="md"): | |
| """Create file with content.""" | |
| 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): | |
| """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>' | |
| import streamlit as st | |
| import anthropic, openai, base64, cv2, glob, json, math, os, pytz, random, re, requests, 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 | |
| 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 | |
| # 🎯 1. Core Configuration & Setup | |
| st.set_page_config( | |
| 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 & 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') | |
| # 📝 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; | |
| } | |
| .audio-player { | |
| margin: 1rem 0; | |
| padding: 1rem; | |
| border-radius: 10px; | |
| background: #f5f5f5; | |
| box-shadow: 0 2px 4px rgba(0,0,0,0.1); | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| FILE_EMOJIS = { | |
| "md": "📝", | |
| "mp3": "🎵", | |
| } | |
| def clean_for_speech(text: str) -> str: | |
| """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 | |
| 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 using Edge TTS""" | |
| 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, "mp3") | |
| await communicate.save(out_fn) | |
| return out_fn | |
| 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)) | |
| 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) | |
| def save_full_transcript(query, text): | |
| """Save full transcript of Arxiv results as a file.""" | |
| create_file(query, text, "md") | |
| 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] | |
| 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"Complete response for query: {q}. {clean_for_speech(r2)} {clean_for_speech(refs)}" | |
| audio_file_full = speak_with_edge_tts(complete_text) | |
| st.write("### 📚 Full Audio") | |
| play_and_download_audio(audio_file_full) | |
| if vocal_summary: | |
| main_text = clean_for_speech(r2) | |
| audio_file_main = speak_with_edge_tts(main_text) | |
| st.write("### 🎙 Short Audio") | |
| play_and_download_audio(audio_file_main) | |
| if extended_refs: | |
| summaries_text = "Extended references: " + refs.replace('"','') | |
| summaries_text = clean_for_speech(summaries_text) | |
| audio_file_refs = speak_with_edge_tts(summaries_text) | |
| st.write("### 📜 Long Refs") | |
| play_and_download_audio(audio_file_refs) | |
| if titles_summary: | |
| titles = [] | |
| for line in refs.split('\n'): | |
| m = re.search(r"\[([^\]]+)\]", line) | |
| if m: | |
| titles.append(m.group(1)) | |
| if titles: | |
| titles_text = "Titles: " + ", ".join(titles) | |
| titles_text = clean_for_speech(titles_text) | |
| audio_file_titles = speak_with_edge_tts(titles_text) | |
| st.write("### 🔖 Titles") | |
| play_and_download_audio(audio_file_titles) | |
| elapsed = time.time()-start | |
| st.write(f"**Total Elapsed:** {elapsed:.2f} s") | |
| # Create file with result | |
| create_file(q, result, "md") | |
| return result | |
| def process_with_gpt(text): | |
| """Process text with GPT-4""" | |
| 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("assistant"): | |
| c = openai_client.chat.completions.create( | |
| model=st.session_state["openai_model"], | |
| messages=st.session_state.messages, | |
| stream=False | |
| ) | |
| 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) | |
| with st.chat_message("assistant"): | |
| r = claude_client.messages.create( | |
| model="claude-3-sonnet-20240229", | |
| max_tokens=1000, | |
| messages=[{"role":"user","content":text}] | |
| ) | |
| 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 generate_filename(prompt, response, file_type="md"): | |
| """Generate filename with timestamp and cleaned text.""" | |
| timestamp = datetime.now().strftime("%y%m_%H%M") | |
| safe_text = re.sub(r'[^\w\s-]', '', prompt[:50]) | |
| return f"{timestamp}_{safe_text}.{file_type}" | |
| def create_file(prompt, response, file_type="md"): | |
| """Create file with content.""" | |
| 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): | |
| """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>' | |
| def main(): | |
| st.sidebar.markdown("### 🚲BikeAI🏆 Multi-Agent Research") | |
| tab_main = st.radio("Action:",["🎤 Voice","📸 Media","🔍 ArXiv","📝 Editor"],horizontal=True) | |
| mycomponent = components.declare_component("mycomponent", path="mycomponent") | |
| val = mycomponent(my_input_value="Hello") | |
| # Show input in text box for editing if detected | |
| 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, | |
| help="Full audio of results") | |
| full_transcript = st.checkbox("🧾FullTranscript", value=False, | |
| help="Generate a full transcript file") | |
| if q and st.button("🔍Run"): | |
| result = perform_ai_lookup(q, vocal_summary=vocal_summary, extended_refs=extended_refs, | |
| titles_summary=titles_summary, full_audio=full_audio) | |
| if full_transcript: | |
| save_full_transcript(q, result) | |
| st.markdown("### Change Prompt & Re-Run") | |
| q_new = st.text_input("🔄 Modify Query:") | |
| if q_new and st.button("🔄 Re-Run with Modified Query"): | |
| result = perform_ai_lookup(q_new, vocal_summary=vocal_summary, extended_refs=extended_refs, | |
| titles_summary=titles_summary, full_audio=full_audio) | |
| if full_transcript: | |
| save_full_transcript(q_new, result) | |
| 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_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": | |
| 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}"): | |
| 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 == "📝 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"): | |
| st.session_state.viewing_prefix = None | |
| if st.session_state.should_rerun: | |
| st.session_state.should_rerun = False | |
| st.rerun() | |
| if __name__ == "__main__": | |
| main() |