Spaces:
Sleeping
Sleeping
import streamlit as st | |
import time | |
import random | |
import json | |
from datetime import datetime | |
import pytz | |
import platform | |
import uuid | |
import extra_streamlit_components as stx | |
import requests | |
from urllib.parse import quote | |
from openai import OpenAI | |
# Set page config | |
st.set_page_config(page_title="Personalized Real-Time Chat with ArXiv Search and AI", page_icon="💬", layout="wide") | |
# Initialize cookie manager | |
cookie_manager = stx.CookieManager() | |
# File to store chat history and user data | |
CHAT_FILE = "chat_history.txt" | |
# Function to save chat history and user data to file | |
def save_data(): | |
with open(CHAT_FILE, 'w') as f: | |
json.dump({ | |
'messages': st.session_state.messages, | |
'users': st.session_state.users | |
}, f) | |
# Function to load chat history and user data from file | |
def load_data(): | |
try: | |
with open(CHAT_FILE, 'r') as f: | |
data = json.load(f) | |
st.session_state.messages = data['messages'] | |
st.session_state.users = data['users'] | |
except FileNotFoundError: | |
st.session_state.messages = [] | |
st.session_state.users = [] | |
# Load data at the start | |
if 'data_loaded' not in st.session_state: | |
load_data() | |
st.session_state.data_loaded = True | |
# Function to get or create user | |
def get_or_create_user(): | |
user_id = cookie_manager.get(cookie='user_id') | |
if not user_id: | |
user_id = str(uuid.uuid4()) | |
cookie_manager.set('user_id', user_id) | |
user = next((u for u in st.session_state.users if u['id'] == user_id), None) | |
if not user: | |
user = { | |
'id': user_id, | |
'name': random.choice(['Alice', 'Bob', 'Charlie', 'David', 'Eve', 'Frank', 'Grace', 'Henry']), | |
'browser': f"{platform.system()} - {st.session_state.get('browser_info', 'Unknown')}" | |
} | |
st.session_state.users.append(user) | |
save_data() | |
return user | |
# Initialize session state | |
if 'messages' not in st.session_state: | |
st.session_state.messages = [] | |
if 'users' not in st.session_state: | |
st.session_state.users = [] | |
if 'current_user' not in st.session_state: | |
st.session_state.current_user = get_or_create_user() | |
# ArXiv search function | |
def search_arxiv(query): | |
base_url = "http://export.arxiv.org/api/query?" | |
search_query = f"search_query=all:{quote(query)}&start=0&max_results=5" | |
response = requests.get(base_url + search_query) | |
if response.status_code == 200: | |
results = [] | |
for entry in response.text.split('<entry>')[1:]: | |
title = entry.split('<title>')[1].split('</title>')[0] | |
summary = entry.split('<summary>')[1].split('</summary>')[0] | |
link = entry.split('<id>')[1].split('</id>')[0] | |
results.append(f"Title: {title}\nSummary: {summary}\nLink: {link}\n") | |
return "\n".join(results) | |
else: | |
return "Error fetching results from ArXiv." | |
# Initialize OpenAI client | |
client = OpenAI(api_key=st.secrets['OPENAI_API_KEY']) | |
MODEL = "gpt-4-0125-preview" # Use the appropriate model | |
# Function to get AI response | |
def get_ai_response(prompt, context=""): | |
try: | |
messages = [ | |
{"role": "system", "content": "You are a helpful assistant in a chat room that can also search ArXiv."}, | |
{"role": "user", "content": f"Context: {context}\n\nUser Query: {prompt}"} | |
] | |
response = client.chat.completions.create( | |
model=MODEL, | |
messages=messages, | |
max_tokens=150, | |
temperature=0.7 | |
) | |
return response.choices[0].message.content | |
except Exception as e: | |
return f"An error occurred: {str(e)}" | |
# Sidebar for user information and settings | |
with st.sidebar: | |
st.title("User Info") | |
st.write(f"Current User: {st.session_state.current_user['name']}") | |
st.write(f"Browser: {st.session_state.current_user['browser']}") | |
new_name = st.text_input("Change your name:") | |
if st.button("Update Name"): | |
if new_name: | |
for user in st.session_state.users: | |
if user['id'] == st.session_state.current_user['id']: | |
user['name'] = new_name | |
st.session_state.current_user['name'] = new_name | |
save_data() | |
st.success(f"Name updated to {new_name}") | |
st.rerun() | |
st.title("Active Users") | |
for user in st.session_state.users: | |
st.write(f"{user['name']} ({user['browser']})") | |
# Main chat area | |
st.title("Personalized Real-Time Chat with ArXiv Search and AI") | |
# Display chat messages | |
for message in st.session_state.messages: | |
with st.chat_message(message["role"]): | |
st.markdown(message["content"]) | |
# Input for new message | |
if prompt := st.chat_input("Type your message or ArXiv search query:"): | |
st.session_state.messages.append({"role": "user", "content": prompt}) | |
with st.chat_message("user"): | |
st.markdown(prompt) | |
# Check if it's an ArXiv search query | |
if prompt.lower().startswith("arxiv:"): | |
query = prompt[6:].strip() | |
with st.chat_message("assistant"): | |
with st.spinner("Searching ArXiv..."): | |
search_results = search_arxiv(query) | |
st.markdown(f"Search results for '{query}':\n\n{search_results}") | |
# Get AI commentary on the search results | |
ai_commentary = get_ai_response(f"Provide a brief analysis of these ArXiv search results: {search_results}") | |
st.markdown(f"\nAI Analysis:\n{ai_commentary}") | |
st.session_state.messages.append({"role": "assistant", "content": f"Search results for '{query}':\n\n{search_results}\n\nAI Analysis:\n{ai_commentary}"}) | |
else: | |
# Get AI response for regular chat | |
with st.chat_message("assistant"): | |
with st.spinner("AI is thinking..."): | |
ai_response = get_ai_response(prompt) | |
st.markdown(ai_response) | |
st.session_state.messages.append({"role": "assistant", "content": ai_response}) | |
save_data() | |
st.rerun() | |
# Polling for updates | |
if st.button("Refresh Chat"): | |
st.rerun() | |
# Auto-refresh | |
if 'last_refresh' not in st.session_state: | |
st.session_state.last_refresh = time.time() | |
if time.time() - st.session_state.last_refresh > 5: # Refresh every 5 seconds | |
st.session_state.last_refresh = time.time() | |
st.rerun() |