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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 | |
from io import BytesIO | |
from PIL import Image | |
import base64 | |
import cv2 | |
import requests | |
from moviepy.editor import VideoFileClip | |
from gradio_client import Client | |
from openai import OpenAI | |
import openai | |
import os | |
from collections import deque | |
# Set page config | |
st.set_page_config(page_title="Personalized Real-Time Chat", 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 | |
load_data() | |
# 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() | |
# 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}") | |
break | |
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") | |
# Function to generate filenames | |
def generate_filename(prompt, file_type): | |
central = pytz.timezone('US/Central') | |
safe_date_time = datetime.now(central).strftime("%m%d_%H%M") | |
replaced_prompt = prompt.replace(" ", "_").replace("\n", "_") | |
safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:90] | |
return f"{safe_date_time}_{safe_prompt}.{file_type}" | |
# Function to create files | |
def create_file(filename, prompt, response, user_name, timestamp, is_image=False): | |
with open(filename, "w", encoding="utf-8") as f: | |
f.write(f"User: {user_name}\nTimestamp: {timestamp}\n\nPrompt:\n{prompt}\n\nResponse:\n{response}") | |
# Function to process text | |
def process_text(user_name, text_input): | |
if text_input: | |
timestamp = datetime.now(pytz.utc).strftime('%Y-%m-%d %H:%M:%S %Z') | |
st.session_state.messages.append({"user": user_name, "message": text_input, "timestamp": timestamp}) | |
with st.chat_message(user_name): | |
st.markdown(f"{user_name} ({timestamp}): {text_input}") | |
with st.chat_message("Assistant"): | |
completion = client.chat.completions.create( | |
model=MODEL, | |
messages=[ | |
{"role": "user", "content": m["message"]} | |
for m in st.session_state.messages | |
], | |
stream=False | |
) | |
return_text = completion.choices[0].message.content | |
st.markdown(f"Assistant ({timestamp}): {return_text}") | |
filename = generate_filename(text_input, "md") | |
create_file(filename, text_input, return_text, user_name, timestamp) | |
st.session_state.messages.append({"user": "Assistant", "message": return_text, "timestamp": timestamp}) | |
save_data() | |
# Function to process image | |
def process_image(user_name, image_input, user_prompt): | |
image = Image.open(BytesIO(image_input)) | |
base64_image = base64.b64encode(image_input).decode("utf-8") | |
response = client.chat.completions.create( | |
model=MODEL, | |
messages=[ | |
{"role": "system", "content": "You are a helpful assistant that responds in Markdown."}, | |
{"role": "user", "content": [ | |
{"type": "text", "text": user_prompt}, | |
{"type": "image_url", "image_url": {"url": f"data:image/png;base64,{base64_image}"}} | |
]} | |
], | |
temperature=0.0, | |
) | |
image_response = response.choices[0].message.content | |
timestamp = datetime.now(pytz.utc).strftime('%Y-%m-%d %H:%M:%S %Z') | |
st.session_state.messages.append({"user": user_name, "message": image_response, "timestamp": timestamp}) | |
with st.chat_message(user_name): | |
st.image(image) | |
st.markdown(f"{user_name} ({timestamp}): {user_prompt}") | |
with st.chat_message("Assistant"): | |
st.markdown(image_response) | |
filename_md = generate_filename(user_prompt, "md") | |
create_file(filename_md, user_prompt, image_response, user_name, timestamp) | |
save_data() | |
return image_response | |
# Function to process audio | |
def process_audio(user_name, audio_input, text_input): | |
if audio_input: | |
transcription = client.audio.transcriptions.create( | |
model="whisper-1", | |
file=audio_input, | |
) | |
timestamp = datetime.now(pytz.utc).strftime('%Y-%m-%d %H:%M:%S %Z') | |
st.session_state.messages.append({"user": user_name, "message": transcription.text, "timestamp": timestamp}) | |
with st.chat_message(user_name): | |
st.markdown(f"{user_name} ({timestamp}): {transcription.text}") | |
with st.chat_message("Assistant"): | |
st.markdown(transcription.text) | |
filename = generate_filename(transcription.text, "wav") | |
create_file(filename, text_input, transcription.text, user_name, timestamp) | |
st.session_state.messages.append({"user": "Assistant", "message": transcription.text, "timestamp": timestamp}) | |
save_data() | |
# Function to process video | |
def process_video(user_name, video_input, user_prompt): | |
if isinstance(video_input, str): | |
with open(video_input, "rb") as video_file: | |
video_input = video_file.read() | |
base64Frames, audio_path = extract_video_frames(video_input) | |
transcript = process_audio_for_video(video_input) | |
response = client.chat.completions.create( | |
model=MODEL, | |
messages=[ | |
{"role": "system", "content": "You are generating a video summary. Create a summary of the provided video and its transcript. Respond in Markdown"}, | |
{"role": "user", "content": [ | |
"These are the frames from the video.", | |
*map(lambda x: {"type": "image_url", "image_url": {"url": f'data:image/jpg;base64,{x}', "detail": "low"}}, base64Frames), | |
{"type": "text", "text": f"The audio transcription is: {transcript}"}, | |
{"type": "text", "text": user_prompt} | |
]} | |
], | |
temperature=0, | |
) | |
video_response = response.choices[0].message.content | |
st.markdown(video_response) | |
timestamp = datetime.now(pytz.utc).strftime('%Y-%m-%d %H:%M:%S %Z') | |
filename_md = generate_filename(user_prompt, "md") | |
create_file(filename_md, user_prompt, video_response, user_name, timestamp) | |
st.session_state.messages.append({"user": user_name, "message": video_response, "timestamp": timestamp}) | |
save_data() | |
return video_response | |
# Function to extract video frames | |
def extract_video_frames(video_path, seconds_per_frame=2): | |
base64Frames = [] | |
video = cv2.VideoCapture(video_path) | |
total_frames = int(video.get(cv2.CAP_PROP_FRAME_COUNT)) | |
fps = video.get(cv2.CAP_PROP_FPS) | |
frames_to_skip = int(fps * seconds_per_frame) | |
curr_frame = 0 | |
while curr_frame < total_frames - 1: | |
video.set(cv2.CAP_PROP_POS_FRAMES, curr_frame) | |
success, frame = video.read() | |
if not success: | |
break | |
_, buffer = cv2.imencode(".jpg", frame) | |
base64Frames.append(base64.b64encode(buffer).decode("utf-8")) | |
curr_frame += frames_to_skip | |
video.release() | |
return base64Frames, None | |
# Function to process audio for video | |
def process_audio_for_video(video_input): | |
try: | |
transcription = client.audio.transcriptions.create( | |
model="whisper-1", | |
file=video_input, | |
) | |
return transcription.text | |
except: | |
return '' | |
# Initialize OpenAI client | |
openai.api_key = os.getenv('OPENAI_API_KEY') | |
openai.organization = os.getenv('OPENAI_ORG_ID') | |
client = OpenAI(api_key=openai.api_key, organization=openai.organization) | |
MODEL = "gpt-4o-2024-05-13" | |
should_save = st.sidebar.checkbox("💾 Save", value=True, help="Save your session data.") | |
# Function to display chat messages | |
def display_messages(): | |
for msg in st.session_state.messages: | |
with st.chat_message(msg['user']): | |
st.markdown(f"**{msg['user']}** ({msg['timestamp']}): {msg['message']}") | |
# Display messages | |
display_messages() | |
# Main function | |
def main(): | |
st.markdown("##### GPT-4o Omni Model: Text, Audio, Image, & Video") | |
option = st.selectbox("Select an option", ("Text", "Image", "Audio", "Video")) | |
if option == "Text": | |
text_input = st.text_input("Enter your text:") | |
if text_input: | |
process_text(st.session_state.current_user['name'], text_input) | |
elif option == "Image": | |
text_input = st.text_input("Enter text prompt to use with Image context:") | |
uploaded_files = st.file_uploader("Upload images", type=["png", "jpg", "jpeg"], accept_multiple_files=True) | |
for image_input in uploaded_files: | |
image_bytes = image_input.read() | |
process_image(st.session_state.current_user['name'], image_bytes, text_input) | |
elif option == "Audio": | |
text_input = st.text_input("Enter text prompt to use with Audio context:") | |
uploaded_files = st.file_uploader("Upload an audio file", type=["mp3", "wav"], accept_multiple_files=True) | |
for audio_input in uploaded_files: | |
process_audio(st.session_state.current_user['name'], audio_input, text_input) | |
elif option == "Video": | |
video_input = st.file_uploader("Upload a video file", type=["mp4"]) | |
text_input = st.text_input("Enter text prompt to use with Video context:") | |
if video_input and text_input: | |
process_video(st.session_state.current_user['name'], video_input, text_input) | |
# Add buttons for quick access to different UI options | |
with st.sidebar: | |
if st.button("📝 Add Text"): | |
st.session_state.ui_option = "Text" | |
if st.button("🖼️ Add Image"): | |
st.session_state.ui_option = "Image" | |
if st.button("🎵 Add Audio"): | |
st.session_state.ui_option = "Audio" | |
if st.button("🎥 Add Video"): | |
st.session_state.ui_option = "Video" | |
if 'ui_option' in st.session_state: | |
main() | |
else: | |
st.session_state.ui_option = "Text" | |
main() | |