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import streamlit as st |
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import time |
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import random |
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import json |
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from datetime import datetime |
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import pytz |
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import platform |
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import uuid |
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import extra_streamlit_components as stx |
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from io import BytesIO |
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from PIL import Image |
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import base64 |
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import cv2 |
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import requests |
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from moviepy.editor import VideoFileClip |
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from gradio_client import Client |
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from openai import OpenAI |
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import openai |
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import os |
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from collections import deque |
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st.set_page_config(page_title="Personalized Real-Time Chat", page_icon="💬", layout="wide") |
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cookie_manager = stx.CookieManager() |
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CHAT_FILE = "chat_history.txt" |
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def save_data(): |
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with open(CHAT_FILE, 'w') as f: |
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json.dump({ |
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'messages': st.session_state.messages, |
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'users': st.session_state.users |
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}, f) |
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def load_data(): |
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try: |
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with open(CHAT_FILE, 'r') as f: |
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data = json.load(f) |
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st.session_state.messages = data['messages'] |
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st.session_state.users = data['users'] |
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except FileNotFoundError: |
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st.session_state.messages = [] |
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st.session_state.users = [] |
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load_data() |
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def get_or_create_user(): |
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user_id = cookie_manager.get(cookie='user_id') |
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if not user_id: |
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user_id = str(uuid.uuid4()) |
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cookie_manager.set('user_id', user_id) |
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user = next((u for u in st.session_state.users if u['id'] == user_id), None) |
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if not user: |
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user = { |
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'id': user_id, |
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'name': random.choice(['Alice', 'Bob', 'Charlie', 'David', 'Eve', 'Frank', 'Grace', 'Henry']), |
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'browser': f"{platform.system()} - {st.session_state.get('browser_info', 'Unknown')}" |
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} |
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st.session_state.users.append(user) |
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save_data() |
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return user |
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if 'messages' not in st.session_state: |
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st.session_state.messages = [] |
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if 'users' not in st.session_state: |
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st.session_state.users = [] |
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if 'current_user' not in st.session_state: |
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st.session_state.current_user = get_or_create_user() |
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with st.sidebar: |
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st.title("User Info") |
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st.write(f"Current User: {st.session_state.current_user['name']}") |
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st.write(f"Browser: {st.session_state.current_user['browser']}") |
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new_name = st.text_input("Change your name:") |
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if st.button("Update Name"): |
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if new_name: |
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for user in st.session_state.users: |
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if user['id'] == st.session_state.current_user['id']: |
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user['name'] = new_name |
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st.session_state.current_user['name'] = new_name |
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save_data() |
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st.success(f"Name updated to {new_name}") |
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break |
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st.title("Active Users") |
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for user in st.session_state.users: |
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st.write(f"{user['name']} ({user['browser']})") |
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st.title("Personalized Real-Time Chat") |
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def generate_filename(prompt, file_type): |
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central = pytz.timezone('US/Central') |
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safe_date_time = datetime.now(central).strftime("%m%d_%H%M") |
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replaced_prompt = prompt.replace(" ", "_").replace("\n", "_") |
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safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:90] |
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return f"{safe_date_time}_{safe_prompt}.{file_type}" |
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def create_file(filename, prompt, response, user_name, timestamp, is_image=False): |
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with open(filename, "w", encoding="utf-8") as f: |
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f.write(f"User: {user_name}\nTimestamp: {timestamp}\n\nPrompt:\n{prompt}\n\nResponse:\n{response}") |
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def process_text(user_name, text_input): |
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if text_input: |
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timestamp = datetime.now(pytz.utc).strftime('%Y-%m-%d %H:%M:%S %Z') |
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st.session_state.messages.append({"user": user_name, "message": text_input, "timestamp": timestamp}) |
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with st.chat_message(user_name): |
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st.markdown(f"{user_name} ({timestamp}): {text_input}") |
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with st.chat_message("Assistant"): |
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completion = client.chat.completions.create( |
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model=MODEL, |
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messages=[ |
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{"role": "user", "content": m["message"]} |
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for m in st.session_state.messages |
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], |
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stream=False |
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) |
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return_text = completion.choices[0].message.content |
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st.markdown(f"Assistant ({timestamp}): {return_text}") |
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filename = generate_filename(text_input, "md") |
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create_file(filename, text_input, return_text, user_name, timestamp) |
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st.session_state.messages.append({"user": "Assistant", "message": return_text, "timestamp": timestamp}) |
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save_data() |
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def process_image(user_name, image_input, user_prompt): |
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image = Image.open(BytesIO(image_input)) |
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base64_image = base64.b64encode(image_input).decode("utf-8") |
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response = client.chat.completions.create( |
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model=MODEL, |
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messages=[ |
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{"role": "system", "content": "You are a helpful assistant that responds in Markdown."}, |
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{"role": "user", "content": [ |
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{"type": "text", "text": user_prompt}, |
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{"type": "image_url", "image_url": {"url": f"data:image/png;base64,{base64_image}"}} |
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]} |
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], |
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temperature=0.0, |
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) |
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image_response = response.choices[0].message.content |
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timestamp = datetime.now(pytz.utc).strftime('%Y-%m-%d %H:%M:%S %Z') |
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st.session_state.messages.append({"user": user_name, "message": image_response, "timestamp": timestamp}) |
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with st.chat_message(user_name): |
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st.image(image) |
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st.markdown(f"{user_name} ({timestamp}): {user_prompt}") |
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with st.chat_message("Assistant"): |
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st.markdown(image_response) |
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filename_md = generate_filename(user_prompt, "md") |
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create_file(filename_md, user_prompt, image_response, user_name, timestamp) |
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save_data() |
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return image_response |
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def process_audio(user_name, audio_input, text_input): |
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if audio_input: |
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transcription = client.audio.transcriptions.create( |
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model="whisper-1", |
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file=audio_input, |
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) |
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timestamp = datetime.now(pytz.utc).strftime('%Y-%m-%d %H:%M:%S %Z') |
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st.session_state.messages.append({"user": user_name, "message": transcription.text, "timestamp": timestamp}) |
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with st.chat_message(user_name): |
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st.markdown(f"{user_name} ({timestamp}): {transcription.text}") |
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with st.chat_message("Assistant"): |
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st.markdown(transcription.text) |
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filename = generate_filename(transcription.text, "wav") |
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create_file(filename, text_input, transcription.text, user_name, timestamp) |
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st.session_state.messages.append({"user": "Assistant", "message": transcription.text, "timestamp": timestamp}) |
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save_data() |
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def process_video(user_name, video_input, user_prompt): |
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if isinstance(video_input, str): |
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with open(video_input, "rb") as video_file: |
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video_input = video_file.read() |
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base64Frames, audio_path = extract_video_frames(video_input) |
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transcript = process_audio_for_video(video_input) |
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response = client.chat.completions.create( |
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model=MODEL, |
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messages=[ |
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{"role": "system", "content": "You are generating a video summary. Create a summary of the provided video and its transcript. Respond in Markdown"}, |
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{"role": "user", "content": [ |
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"These are the frames from the video.", |
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*map(lambda x: {"type": "image_url", "image_url": {"url": f'data:image/jpg;base64,{x}', "detail": "low"}}, base64Frames), |
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{"type": "text", "text": f"The audio transcription is: {transcript}"}, |
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{"type": "text", "text": user_prompt} |
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]} |
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], |
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temperature=0, |
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) |
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video_response = response.choices[0].message.content |
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st.markdown(video_response) |
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timestamp = datetime.now(pytz.utc).strftime('%Y-%m-%d %H:%M:%S %Z') |
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filename_md = generate_filename(user_prompt, "md") |
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create_file(filename_md, user_prompt, video_response, user_name, timestamp) |
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st.session_state.messages.append({"user": user_name, "message": video_response, "timestamp": timestamp}) |
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save_data() |
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return video_response |
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def extract_video_frames(video_path, seconds_per_frame=2): |
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base64Frames = [] |
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video = cv2.VideoCapture(video_path) |
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total_frames = int(video.get(cv2.CAP_PROP_FRAME_COUNT)) |
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fps = video.get(cv2.CAP_PROP_FPS) |
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frames_to_skip = int(fps * seconds_per_frame) |
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curr_frame = 0 |
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while curr_frame < total_frames - 1: |
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video.set(cv2.CAP_PROP_POS_FRAMES, curr_frame) |
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success, frame = video.read() |
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if not success: |
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break |
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_, buffer = cv2.imencode(".jpg", frame) |
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base64Frames.append(base64.b64encode(buffer).decode("utf-8")) |
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curr_frame += frames_to_skip |
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video.release() |
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return base64Frames, None |
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def process_audio_for_video(video_input): |
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try: |
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transcription = client.audio.transcriptions.create( |
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model="whisper-1", |
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file=video_input, |
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) |
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return transcription.text |
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except: |
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return '' |
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openai.api_key = os.getenv('OPENAI_API_KEY') |
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openai.organization = os.getenv('OPENAI_ORG_ID') |
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client = OpenAI(api_key=openai.api_key, organization=openai.organization) |
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MODEL = "gpt-4o-2024-05-13" |
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should_save = st.sidebar.checkbox("💾 Save", value=True, help="Save your session data.") |
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def display_messages(): |
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for msg in st.session_state.messages: |
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with st.chat_message(msg['user']): |
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st.markdown(f"**{msg['user']}** ({msg['timestamp']}): {msg['message']}") |
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display_messages() |
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def main(): |
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st.markdown("##### GPT-4o Omni Model: Text, Audio, Image, & Video") |
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option = st.selectbox("Select an option", ("Text", "Image", "Audio", "Video")) |
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if option == "Text": |
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text_input = st.text_input("Enter your text:") |
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if text_input: |
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process_text(st.session_state.current_user['name'], text_input) |
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elif option == "Image": |
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text_input = st.text_input("Enter text prompt to use with Image context:") |
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uploaded_files = st.file_uploader("Upload images", type=["png", "jpg", "jpeg"], accept_multiple_files=True) |
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for image_input in uploaded_files: |
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image_bytes = image_input.read() |
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process_image(st.session_state.current_user['name'], image_bytes, text_input) |
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elif option == "Audio": |
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text_input = st.text_input("Enter text prompt to use with Audio context:") |
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uploaded_files = st.file_uploader("Upload an audio file", type=["mp3", "wav"], accept_multiple_files=True) |
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for audio_input in uploaded_files: |
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process_audio(st.session_state.current_user['name'], audio_input, text_input) |
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elif option == "Video": |
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video_input = st.file_uploader("Upload a video file", type=["mp4"]) |
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text_input = st.text_input("Enter text prompt to use with Video context:") |
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if video_input and text_input: |
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process_video(st.session_state.current_user['name'], video_input, text_input) |
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with st.sidebar: |
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if st.button("📝 Add Text"): |
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st.session_state.ui_option = "Text" |
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if st.button("🖼️ Add Image"): |
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st.session_state.ui_option = "Image" |
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if st.button("🎵 Add Audio"): |
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st.session_state.ui_option = "Audio" |
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if st.button("🎥 Add Video"): |
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st.session_state.ui_option = "Video" |
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if 'ui_option' in st.session_state: |
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main() |
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else: |
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st.session_state.ui_option = "Text" |
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main() |
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