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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 | |
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 | |
# π§ Config & Setup | |
st.set_page_config( | |
page_title="π²BikeAIπ Claude/GPT Research", | |
page_icon="π²π", | |
layout="wide", | |
initial_sidebar_state="auto", | |
menu_items={ | |
'Get Help': 'https://huggingface.co/awacke1', | |
'Report a bug': 'https://huggingface.co/spaces/awacke1', | |
'About': "π²BikeAIπ Claude/GPT Research AI" | |
} | |
) | |
load_dotenv() | |
openai.api_key = os.getenv('OPENAI_API_KEY') or st.secrets['OPENAI_API_KEY'] | |
anthropic_key = os.getenv("ANTHROPIC_API_KEY_3") or st.secrets["ANTHROPIC_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') | |
# Session states | |
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_file' not in st.session_state: | |
st.session_state['viewing_file'] = None | |
if 'viewing_file_type' not in st.session_state: | |
st.session_state['viewing_file_type'] = None | |
if 'should_rerun' not in st.session_state: | |
st.session_state['should_rerun'] = False | |
# π¨ Minimal 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": "π", | |
"mp3": "π΅", | |
} | |
def generate_filename(prompt, file_type="md"): | |
ctz = pytz.timezone('US/Central') | |
date_str = datetime.now(ctz).strftime("%m%d_%H%M") | |
safe = re.sub(r'[<>:"/\\\\|?*\n]', ' ', prompt) | |
safe = re.sub(r'\s+', ' ', safe).strip()[:90] | |
return f"{date_str}_{safe}.{file_type}" | |
def create_file(filename, prompt, response): | |
# Creating file does not trigger immediate rerun | |
with open(filename, 'w', encoding='utf-8') as f: | |
f.write(prompt + "\n\n" + response) | |
def get_download_link(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)}">π Download {os.path.basename(file)}</a>' | |
def speech_synthesis_html(result): | |
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): | |
# Just create mp3 file, no immediate rerun | |
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,"mp3") | |
await communicate.save(out_fn) | |
return out_fn | |
def speak_with_edge_tts(text, voice="en-US-AriaNeural", rate=0, pitch=0): | |
return asyncio.run(edge_tts_generate_audio(text, voice, rate, pitch)) | |
def play_and_download_audio(file_path): | |
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 process_image(image_path, user_prompt): | |
with open(image_path, "rb") as imgf: | |
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=[ | |
{"role": "system", "content": "You are a helpful assistant."}, | |
{"role": "user", "content": [ | |
{"type": "text", "text": user_prompt}, | |
{"type": "image_url", "image_url": {"url": f"data:image/png;base64,{b64img}"}} | |
]} | |
], | |
temperature=0.0, | |
) | |
return resp.choices[0].message.content | |
def process_audio(audio_path): | |
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}) | |
# No immediate rerun | |
return transcription.text | |
def process_video(video_path, seconds_per_frame=1): | |
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): | |
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 | |
def search_arxiv(query): | |
st.write("π Searching ArXiv...") | |
client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern") | |
r1 = client.predict(prompt=query, llm_model_picked="mistralai/Mixtral-8x7B-Instruct-v0.1", stream_outputs=True, api_name="/ask_llm") | |
st.markdown("### Mistral-8x7B-Instruct-v0.1 Result") | |
st.markdown(r1) | |
r2 = client.predict(prompt=query, llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2", stream_outputs=True, api_name="/ask_llm") | |
st.markdown("### Mistral-7B-Instruct-v0.2 Result") | |
st.markdown(r2) | |
return f"{r1}\n\n{r2}" | |
def perform_ai_lookup(q, vocal_summary=True, extended_refs=False, titles_summary=True): | |
start = time.time() | |
client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern") | |
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"### π {q}\n\n{r2}\n\n{refs}" | |
st.markdown(result) | |
if vocal_summary: | |
audio_file_main = speak_with_edge_tts(r2, voice="en-US-AriaNeural", rate=0, pitch=0) | |
st.write("### ποΈ Vocal Summary (Short Answer)") | |
play_and_download_audio(audio_file_main) | |
if extended_refs: | |
summaries_text = "Here are the summaries from the references: " + refs.replace('"','') | |
audio_file_refs = speak_with_edge_tts(summaries_text, voice="en-US-AriaNeural", rate=0, pitch=0) | |
st.write("### π Extended References & Summaries") | |
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 = "Here are the titles of the papers: " + ", ".join(titles) | |
audio_file_titles = speak_with_edge_tts(titles_text, voice="en-US-AriaNeural", rate=0, pitch=0) | |
st.write("### π Paper Titles") | |
play_and_download_audio(audio_file_titles) | |
elapsed = time.time()-start | |
st.write(f"**Total Elapsed:** {elapsed:.2f} s") | |
fn = generate_filename(q,"md") | |
create_file(fn,q,result) | |
return result | |
def process_with_gpt(text): | |
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(generate_filename(text,"md"),text,ans) | |
st.session_state.messages.append({"role":"assistant","content":ans}) | |
return ans | |
def process_with_claude(text): | |
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: " + ans) | |
create_file(generate_filename(text,"md"),text,ans) | |
st.session_state.chat_history.append({"user":text,"claude":ans}) | |
return ans | |
def create_zip_of_files(md_files, mp3_files): | |
# Exclude README.md if present | |
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 | |
# Build a descriptive name from file stems | |
stems = [os.path.splitext(os.path.basename(f))[0] for f in all_files] | |
# Join them | |
joined = "_".join(stems) | |
# Truncate if too long | |
if len(joined) > 50: | |
joined = joined[:50] + "_etc" | |
zip_name = f"{joined}.zip" | |
with zipfile.ZipFile(zip_name,'w') as z: | |
for f in all_files: | |
z.write(f) | |
return zip_name | |
def get_media_html(p,typ="video",w="100%"): | |
d = base64.b64encode(open(p,'rb').read()).decode() | |
if typ=="video": | |
return f'<video width="{w}" controls autoplay muted loop><source src="data:video/mp4;base64,{d}" type="video/mp4"></video>' | |
else: | |
return f'<audio controls style="width:{w};"><source src="data:audio/mpeg;base64,{d}" type="audio/mpeg"></audio>' | |
def load_files_for_sidebar(): | |
# Gather all md and mp3 files | |
md_files = glob.glob("*.md") | |
mp3_files = glob.glob("*.mp3") | |
# Exclude README.md from listings | |
md_files = [f for f in md_files if os.path.basename(f).lower() != 'readme.md'] | |
files_by_ext = defaultdict(list) | |
if md_files: files_by_ext['md'].extend(md_files) | |
if mp3_files: files_by_ext['mp3'].extend(mp3_files) | |
# Sort each extension group by modification time descending | |
for ext in files_by_ext: | |
files_by_ext[ext].sort(key=lambda x: os.path.getmtime(x), reverse=True) | |
return files_by_ext | |
def display_file_manager_sidebar(files_by_ext): | |
st.sidebar.title("π΅ Audio & Document Manager") | |
md_files = files_by_ext.get('md', []) | |
mp3_files = files_by_ext.get('mp3', []) | |
# Buttons to delete all except README.md (already excluded) | |
col_del = st.sidebar.columns(3) | |
with col_del[0]: | |
if st.button("π Del All MD"): | |
for f in md_files: | |
os.remove(f) | |
st.session_state.should_rerun = True | |
with col_del[1]: | |
if st.button("π Del All MP3"): | |
for f in mp3_files: | |
os.remove(f) | |
st.session_state.should_rerun = True | |
with col_del[2]: | |
if st.button("β¬οΈ Zip All"): | |
# create a zip of all md and mp3 except README.md | |
z = create_zip_of_files(md_files, mp3_files) | |
if z: | |
st.sidebar.markdown(get_download_link(z),unsafe_allow_html=True) | |
ext_counts = {ext: len(files) for ext, files in files_by_ext.items()} | |
sorted_ext = sorted(files_by_ext.keys(), key=lambda x: ext_counts[x], reverse=True) | |
# Display files with actions | |
for ext in sorted_ext: | |
emoji = FILE_EMOJIS.get(ext, "π¦") | |
count = len(files_by_ext[ext]) | |
with st.sidebar.expander(f"{emoji} {ext.upper()} Files ({count})", expanded=True): | |
for f in files_by_ext[ext]: | |
fname = os.path.basename(f) | |
ctime = datetime.fromtimestamp(os.path.getmtime(f)).strftime("%Y-%m-%d %H:%M:%S") | |
# Show filename and buttons in a row | |
st.write(f"**{fname}** - {ctime}") | |
file_buttons_col = st.columns([1,1,1]) | |
with file_buttons_col[0]: | |
if st.button("πView", key="view_"+f): | |
st.session_state.viewing_file = f | |
st.session_state.viewing_file_type = ext | |
# No rerun needed, just set state | |
with file_buttons_col[1]: | |
if ext == "md": | |
if st.button("βοΈEdit", key="edit_"+f): | |
st.session_state.editing_file = f | |
st.session_state.edit_new_name = fname.replace(".md","") | |
st.session_state.edit_new_content = open(f,'r',encoding='utf-8').read() | |
st.session_state.should_rerun = True | |
with file_buttons_col[2]: | |
if st.button("πDel", key="del_"+f): | |
os.remove(f) | |
st.session_state.should_rerun = True | |
# If editing an md file | |
if st.session_state.editing_file and os.path.exists(st.session_state.editing_file): | |
st.sidebar.subheader(f"Editing: {os.path.basename(st.session_state.editing_file)}") | |
st.session_state.edit_new_name = st.sidebar.text_input("New name (no extension):", value=st.session_state.edit_new_name) | |
st.session_state.edit_new_content = st.sidebar.text_area("Content:", st.session_state.edit_new_content, height=200) | |
c1,c2 = st.sidebar.columns(2) | |
with c1: | |
if st.button("Save"): | |
old_path = st.session_state.editing_file | |
new_path = st.session_state.edit_new_name + ".md" | |
if new_path != os.path.basename(old_path): | |
os.rename(old_path, new_path) | |
with open(new_path,'w',encoding='utf-8') as f: | |
f.write(st.session_state.edit_new_content) | |
st.session_state.editing_file = None | |
st.session_state.should_rerun = True | |
with c2: | |
if st.button("Cancel"): | |
st.session_state.editing_file = None | |
st.session_state.should_rerun = True | |
def main(): | |
st.sidebar.markdown("### π²BikeAIπ Multi-Agent Research AI") | |
tab_main = st.radio("Action:",["π€ Voice Input","πΈ Media Gallery","π Search ArXiv","π File Editor"],horizontal=True) | |
model_choice = st.sidebar.radio("AI Model:", ["Arxiv","GPT-4o","Claude-3","GPT+Claude+Arxiv"], index=0) | |
# Main Input Component | |
mycomponent = components.declare_component("mycomponent", path="mycomponent") | |
val = mycomponent(my_input_value="Hello") | |
if val: | |
user_input = val.strip() | |
if user_input: | |
if model_choice == "GPT-4o": | |
process_with_gpt(user_input) | |
elif model_choice == "Claude-3": | |
process_with_claude(user_input) | |
elif model_choice == "Arxiv": | |
st.subheader("Arxiv Only Results:") | |
perform_ai_lookup(user_input, vocal_summary=True, extended_refs=False, titles_summary=True) | |
else: | |
col1,col2,col3=st.columns(3) | |
with col1: | |
st.subheader("GPT-4o Omni:") | |
try: process_with_gpt(user_input) | |
except: st.write('GPT 4o error') | |
with col2: | |
st.subheader("Claude-3 Sonnet:") | |
try: process_with_claude(user_input) | |
except: st.write('Claude error') | |
with col3: | |
st.subheader("Arxiv + Mistral:") | |
try: | |
perform_ai_lookup(user_input, vocal_summary=True, extended_refs=False, titles_summary=True) | |
except: | |
st.write("Arxiv error") | |
if tab_main == "π Search ArXiv": | |
st.subheader("π Search ArXiv") | |
q=st.text_input("Research query:") | |
# ποΈ Audio Generation Options | |
st.markdown("### ποΈ Audio Generation Options") | |
vocal_summary = st.checkbox("ποΈ Vocal Summary (Short Answer)", value=True) | |
extended_refs = st.checkbox("π Extended References & Summaries (Long)", value=False) | |
titles_summary = st.checkbox("π Paper Titles Only", value=True) | |
if q: | |
q = q.strip() | |
if q and st.button("Run ArXiv Query"): | |
perform_ai_lookup(q, vocal_summary=vocal_summary, extended_refs=extended_refs, titles_summary=titles_summary) | |
elif tab_main == "π€ Voice Input": | |
st.subheader("π€ Voice Recognition") | |
user_text = st.text_area("Message:", height=100) | |
user_text = user_text.strip() | |
if st.button("Send π¨"): | |
if user_text: | |
if model_choice == "GPT-4o": | |
process_with_gpt(user_text) | |
elif model_choice == "Claude-3": | |
process_with_claude(user_text) | |
elif model_choice == "Arxiv": | |
st.subheader("Arxiv Only Results:") | |
perform_ai_lookup(user_text, vocal_summary=True, extended_refs=False, titles_summary=True) | |
else: | |
col1,col2,col3=st.columns(3) | |
with col1: | |
st.subheader("GPT-4o Omni:") | |
process_with_gpt(user_text) | |
with col2: | |
st.subheader("Claude-3 Sonnet:") | |
process_with_claude(user_text) | |
with col3: | |
st.subheader("Arxiv & Mistral:") | |
res = perform_ai_lookup(user_text, vocal_summary=True, extended_refs=False, titles_summary=True) | |
st.markdown(res) | |
st.subheader("π 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 == "πΈ Media Gallery": | |
st.header("π¬ Media Gallery - Images and Videos") | |
tabs = st.tabs(["πΌοΈ Images", "π₯ Video"]) | |
with tabs[0]: | |
imgs = glob.glob("*.png")+glob.glob("*.jpg") | |
if imgs: | |
c = st.slider("Cols",1,5,3) | |
cols = st.columns(c) | |
for i,f in enumerate(imgs): | |
with cols[i%c]: | |
st.image(Image.open(f),use_container_width=True) | |
if st.button(f"π Analyze {os.path.basename(f)}", key=f"analyze_{f}"): | |
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"π₯ {os.path.basename(v)}"): | |
st.markdown(get_media_html(v,"video"),unsafe_allow_html=True) | |
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 == "π 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.") | |
# After main content, load files and display in sidebar | |
files_by_ext = load_files_for_sidebar() | |
display_file_manager_sidebar(files_by_ext) | |
# If viewing a file, show its content below (in the main area) | |
if st.session_state.viewing_file and os.path.exists(st.session_state.viewing_file): | |
st.write("---") | |
st.write(f"**Viewing File:** {os.path.basename(st.session_state.viewing_file)}") | |
if st.session_state.viewing_file_type == "md": | |
# show markdown | |
content = open(st.session_state.viewing_file,'r',encoding='utf-8').read() | |
st.markdown(content) | |
elif st.session_state.viewing_file_type == "mp3": | |
# show audio | |
st.audio(st.session_state.viewing_file) | |
# Optionally add a "Close View" button | |
if st.button("Close View"): | |
st.session_state.viewing_file = None | |
st.session_state.viewing_file_type = None | |
# If user-triggered changes happened, rerun once at the end | |
if st.session_state.should_rerun: | |
st.session_state.should_rerun = False | |
st.rerun() | |
if __name__=="__main__": | |
main() | |