Update app.py

app.py

@@ -24,10 +24,7 @@ from langchain.agents import Tool, initialize_agent
 from huggingface_hub import login
 
 
-import requests
-from requests_oauthlib import OAuth2Session
-from oauthlib.oauth2 import BackendApplicationClient
-import os
+
 
 # Check if the token is already set in the environment variables
 hf_token = os.getenv("HF_TOKEN")
@@ -837,26 +834,6 @@ def update_images():
     return image_1, image_2, image_3
 
 
-# OAuth 2.0 endpoints for Google
-authorization_base_url = 'https://accounts.google.com/o/oauth2/auth'
-token_url = 'https://accounts.google.com/o/oauth2/token'
-scope = ['https://www.googleapis.com/auth/userinfo.profile', 'https://www.googleapis.com/auth/userinfo.email']
-
-GOOGLE_CLIENT_ID=os.environ(['GOOGLE_CLIENT_ID'])
-
-# Function to initiate the OAuth flow
-def login():
-    google = OAuth2Session(GOOGLE_CLIENT_ID, scope=scope, redirect_uri=REDIRECT_URI)
-    authorization_url, state = google.authorization_url(authorization_base_url, access_type="offline", prompt="select_account")
-    return f'<a href="{authorization_url}" target="_self">Login with Google</a>'
-
-# Function to handle the callback
-def oauth_callback(url):
-    google = OAuth2Session(GOOGLE_CLIENT_ID, redirect_uri=REDIRECT_URI, scope=scope)
-    google.fetch_token(token_url, client_secret=GOOGLE_CLIENT_SECRET, authorization_response=url)
-    userinfo = google.get('https://www.googleapis.com/oauth2/v1/userinfo').json()
-    return f"Logged in as: {userinfo['name']} ({userinfo['email']})"
-
 
 with gr.Blocks(theme='Pijush2023/scikit-learn-pijush') as demo:
     
@@ -898,511 +875,8 @@ with gr.Blocks(theme='Pijush2023/scikit-learn-pijush') as demo:
 
             refresh_button = gr.Button("Refresh Images")
             refresh_button.click(fn=update_images, inputs=None, outputs=[image_output_1, image_output_2, image_output_3])
-        with gr.Column():
-            login_button = gr.HTML(login)
-            oauth_callback_url = gr.Textbox(label="Callback URL")
-            user_info = gr.HTML()
-            
-            oauth_callback_url.submit(oauth_callback, inputs=[oauth_callback_url], outputs=[user_info])
+     
 demo.queue()
 demo.launch(share=True)
 
 
-# import os
-# import re
-# import time
-# import requests
-# import logging
-# import folium
-# import gradio as gr
-# import tempfile
-# import torch
-# from datetime import datetime
-# import numpy as np
-# from gtts import gTTS
-# from googlemaps import Client as GoogleMapsClient
-# import concurrent.futures
-# from PIL import Image
-# from huggingface_hub import login
-
-# # Check if the token is already set in the environment variables
-# hf_token = os.getenv("HF_TOKEN")
-
-# if hf_token is None:
-#     # If the token is not set, prompt for it (this should be done securely)
-#     print("Please set your Hugging Face token in the environment variables.")
-# else:
-#     # Login using the token
-#     login(token=hf_token)
-
-# # Your application logic goes here
-# print("Logged in successfully to Hugging Face Hub!")
-
-# # Set up logging
-# logging.basicConfig(level=logging.DEBUG)
-
-# # Initialize OpenAI embeddings
-# from langchain_openai import OpenAIEmbeddings, ChatOpenAI
-# from langchain_pinecone import PineconeVectorStore
-# from langchain.prompts import PromptTemplate
-# from langchain.chains import RetrievalQA
-# from langchain.chains.conversation.memory import ConversationBufferWindowMemory
-# from langchain.agents import Tool, initialize_agent
-
-# embeddings = OpenAIEmbeddings(api_key=os.environ['OPENAI_API_KEY'])
-
-# # Initialize Pinecone
-# from pinecone import Pinecone
-# pc = Pinecone(api_key=os.environ['PINECONE_API_KEY'])
-
-# index_name = "omaha-details"
-# vectorstore = PineconeVectorStore(index_name=index_name, embedding=embeddings)
-# retriever = vectorstore.as_retriever(search_kwargs={'k': 5})
-
-# chat_model = ChatOpenAI(api_key=os.environ['OPENAI_API_KEY'], temperature=0, model='gpt-4o')
-
-# conversational_memory = ConversationBufferWindowMemory(
-#     memory_key='chat_history',
-#     k=10,
-#     return_messages=True
-# )
-
-# # Define function to get current time and date
-# def get_current_time_and_date():
-#     now = datetime.now()
-#     return now.strftime("%Y-%m-%d %H:%M:%S")
-
-# current_time_and_date = get_current_time_and_date()
-
-# # Define functions for fetching events, weather, and news
-# def fetch_local_events():
-#     api_key = os.environ['SERP_API']
-#     url = f'https://serpapi.com/search.json?engine=google_events&q=Events+in+Omaha&hl=en&gl=us&api_key={api_key}'
-#     response = requests.get(url)
-#     if response.status_code == 200:
-#         events_results = response.json().get("events_results", [])
-#         events_html = """
-#         <h2 style="font-family: 'Georgia', serif; color: #ff0000; background-color: #f8f8f8; padding: 10px; border-radius: 10px;">Local Events</h2>
-#         <style>
-#             .event-item {
-#                 font-family: 'Verdana', sans-serif;
-#                 color: #333;
-#                 margin-bottom: 15px;
-#                 padding: 10px;
-#                 font-weight: bold;
-#             }
-#             .event-item a {
-#                 color: #1E90FF;
-#                 text-decoration: none;
-#             }
-#             .event-item a:hover {
-#                 text-decoration: underline;
-#             }
-#         </style>
-#         """
-#         for index, event in enumerate(events_results):
-#             title = event.get("title", "No title")
-#             date = event.get("date", "No date")
-#             location = event.get("address", "No location")
-#             link = event.get("link", "#")
-#             events_html += f"""
-#             <div class="event-item">
-#                 <a href='{link}' target='_blank'>{index + 1}. {title}</a>
-#                 <p>Date: {date}<br>Location: {location}</p>
-#             </div>
-#             """
-#         return events_html
-#     else:
-#         return "<p>Failed to fetch local events</p>"
-
-# def fetch_local_weather():
-#     try:
-#         api_key = os.environ['WEATHER_API']
-#         url = f'https://weather.visualcrossing.com/VisualCrossingWebServices/rest/services/timeline/omaha?unitGroup=metric&include=events%2Calerts%2Chours%2Cdays%2Ccurrent&key={api_key}'
-#         response = requests.get(url)
-#         response.raise_for_status()
-#         jsonData = response.json()
-#         current_conditions = jsonData.get("currentConditions", {})
-#         temp_celsius = current_conditions.get("temp", "N/A")
-#         if temp_celsius != "N/A":
-#             temp_fahrenheit = int((temp_celsius * 9/5) + 32)
-#         else:
-#             temp_fahrenheit = "N/A"
-#         condition = current_conditions.get("conditions", "N/A")
-#         humidity = current_conditions.get("humidity", "N/A")
-
-#         weather_html = f"""
-#         <div class="weather-theme">
-#             <h2 style="font-family: 'Georgia', serif; color: #ff0000; background-color: #f8f8f8; padding: 10px; border-radius: 10px;">Local Weather</h2>
-#             <div class="weather-content">
-#                 <div class="weather-icon">
-#                     <img src="https://www.weatherbit.io/static/img/icons/{get_weather_icon(condition)}.png" alt="{condition}" style="width: 100px; height: 100px;">
-#                 </div>
-#                 <div class="weather-details">
-#                     <p style="font-family: 'Verdana', sans-serif; color: #333; font-size: 1.2em;">Temperature: {temp_fahrenheit}°F</p>
-#                     <p style="font-family: 'Verdana', sans-serif; color: #333; font-size: 1.2em;">Condition: {condition}</p>
-#                     <p style="font-family: 'Verdana', sans-serif; color: #333; font-size: 1.2em;">Humidity: {humidity}%</p>
-#                 </div>
-#             </div>
-#         </div>
-#         <style>
-#             .weather-theme {{
-#                 animation: backgroundAnimation 10s infinite alternate;
-#                 border-radius: 10px;
-#                 padding: 10px;
-#                 margin-bottom: 15px;
-#                 background: linear-gradient(45deg, #ffcc33, #ff6666, #ffcc33, #ff6666);
-#                 background-size: 400% 400%;
-#                 box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
-#                 transition: box-shadow 0.3s ease, background-color 0.3s ease;
-#             }}
-#             .weather-theme:hover {{
-#                 box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
-#                 background-position: 100% 100%;
-#             }}
-#             @keyframes backgroundAnimation {{
-#                 0% {{ background-position: 0% 50%; }}
-#                 100% {{ background-position: 100% 50%; }}
-#             }}
-#             .weather-content {{
-#                 display: flex;
-#                 align-items: center;
-#             }}
-#             .weather-icon {{
-#                 flex: 1;
-#             }}
-#             .weather-details {{
-#                 flex: 3;
-#             }}
-#         </style>
-#         """
-#         return weather_html
-#     except requests.exceptions.RequestException as e:
-#         return f"<p>Failed to fetch local weather: {e}</p>"
-
-# def get_weather_icon(condition):
-#     condition_map = {
-#         "Clear": "c01d",
-#         "Partly Cloudy": "c02d",
-#         "Cloudy": "c03d",
-#         "Overcast": "c04d",
-#         "Mist": "a01d",
-#         "Patchy rain possible": "r01d",
-#         "Light rain": "r02d",
-#         "Moderate rain": "r03d",
-#         "Heavy rain": "r04d",
-#         "Snow": "s01d",
-#         "Thunderstorm": "t01d",
-#         "Fog": "a05d",
-#     }
-#     return condition_map.get(condition, "c04d")
-
-# def fetch_local_news():
-#     api_key = os.environ['SERP_API']
-#     url = f'https://serpapi.com/search.json?engine=google_news&q=omaha headline&api_key={api_key}'
-#     response = requests.get(url)
-#     if response.status_code == 200:
-#         results = response.json().get("news_results", [])
-#         news_html = """
-#         <h2 style="font-family: 'Georgia', serif; color: #ff0000; background-color: #f8f8f8; padding: 10px; border-radius: 10px;">Omaha Today</h2>
-#         <style>
-#             .news-item {
-#                 font-family: 'Verdana', sans-serif;
-#                 color: #333;
-#                 background-color: #f0f8ff;
-#                 margin-bottom: 15px;
-#                 padding: 10px;
-#                 border-radius: 5px;
-#                 transition: box-shadow 0.3s ease, background-color 0.3s ease;
-#                 font-weight: bold;
-#             }
-#             .news-item:hover {
-#                 box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
-#                 background-color: #e6f7ff;
-#             }
-#             .news-item a {
-#                 color: #1E90FF;
-#                 text-decoration: none;
-#                 font-weight: bold;
-#             }
-#             .news-item a:hover {
-#                 text-decoration: underline;
-#             }
-#             .news-preview {
-#                 position: absolute;
-#                 display: none;
-#                 border: 1px solid #ccc;
-#                 border-radius: 5px;
-#                 box-shadow: 0 2px 4px rgba(0, 0, 0, 0.2);
-#                 background-color: white;
-#                 z-index: 1000;
-#                 max-width: 300px;
-#                 padding: 10px;
-#                 font-family: 'Verdana', sans-serif;
-#                 color: #333;
-#             }
-#         </style>
-#         <script>
-#             function showPreview(event, previewContent) {
-#                 var previewBox = document.getElementById('news-preview');
-#                 previewBox.innerHTML = previewContent;
-#                 previewBox.style.left = event.pageX + 'px';
-#                 previewBox.style.top = event.pageY + 'px';
-#                 previewBox.style.display = 'block';
-#             }
-#             function hidePreview() {
-#                 var previewBox = document.getElementById('news-preview');
-#                 previewBox.style.display = 'none';
-#             }
-#         </script>
-#         <div id="news-preview" class="news-preview"></div>
-#         """
-#         for index, result in enumerate(results[:7]):
-#             title = result.get("title", "No title")
-#             link = result.get("link", "#")
-#             snippet = result.get("snippet", "")
-#             news_html += f"""
-#             <div class="news-item" onmouseover="showPreview(event, '{snippet}')" onmouseout="hidePreview()">
-#                 <a href='{link}' target='_blank'>{index + 1}. {title}</a>
-#                 <p>{snippet}</p>
-#             </div>
-#             """
-#         return news_html
-#     else:
-#         return "<p>Failed to fetch local news</p>"
-
-# # Define prompt templates
-# template1 = """You are an expert concierge who is helpful and a renowned guide for Omaha, Nebraska. Based on weather being a sunny bright day and today's date is 20th June 2024, use the following pieces of context, 
-# memory, and message history, along with your knowledge of perennial events in Omaha, Nebraska, to answer the question at the end. If you don't know the answer, just say "Homie, I need to get more data for this," and don't try to make up an answer. 
-# Use fifteen sentences maximum. Keep the answer as detailed as possible. Always include the address, time, date, and
-# event type and description. Always say "It was my pleasure!" at the end of the answer.
-# {context}
-# Question: {question}
-# Helpful Answer:"""
-
-# template2 = """You are an expert concierge who is helpful and a renowned guide for Omaha, Nebraska. Based on today's weather being a sunny bright day and today's date is 20th June 2024, take the location or address but don't show the location or address on the output prompts. Use the following pieces of context, 
-# memory, and message history, along with your knowledge of perennial events in Omaha, Nebraska, to answer the question at the end. If you don't know the answer, just say "Homie, I need to get more data for this," and don't try to make up an answer. 
-# Keep the answer short and sweet and crisp. Always say "It was my pleasure!" at the end of the answer.
-# {context}
-# Question: {question}
-# Helpful Answer:"""
-
-# QA_CHAIN_PROMPT_1 = PromptTemplate(input_variables=["context", "question"], template=template1)
-# QA_CHAIN_PROMPT_2 = PromptTemplate(input_variables=["context", "question"], template=template2)
-
-# def build_qa_chain(prompt_template):
-#     qa_chain = RetrievalQA.from_chain_type(
-#         llm=chat_model,
-#         chain_type="stuff",
-#         retriever=retriever,
-#         chain_type_kwargs={"prompt": prompt_template}
-#     )
-#     tools = [
-#         Tool(
-#             name='Knowledge Base',
-#             func=qa_chain,
-#             description='Use this tool when answering general knowledge queries to get more information about the topic'
-#         )
-#     ]
-#     return qa_chain, tools
-
-# def initialize_agent_with_prompt(prompt_template):
-#     qa_chain, tools = build_qa_chain(prompt_template)
-#     agent = initialize_agent(
-#         agent='chat-conversational-react-description',
-#         tools=tools,
-#         llm=chat_model,
-#         verbose=False,
-#         max_iteration=5,
-#         early_stopping_method='generate',
-#         memory=conversational_memory
-#     )
-#     return agent
-
-# def generate_answer(message, choice):
-#     logging.debug(f"generate_answer called with prompt_choice: {choice}")
-#     if choice == "Details":
-#         agent = initialize_agent_with_prompt(QA_CHAIN_PROMPT_1)
-#     elif choice == "Conversational":
-#         agent = initialize_agent_with_prompt(QA_CHAIN_PROMPT_2)
-#     else:
-#         logging.error(f"Invalid prompt_choice: {choice}. Defaulting to 'Conversational'")
-#         agent = initialize_agent_with_prompt(QA_CHAIN_PROMPT_2)
-#     response = agent(message)
-#     addresses = extract_addresses(response['output'])
-#     return response['output'], addresses
-
-# def bot(history, choice):
-#     if not history:
-#         return history
-#     response, addresses = generate_answer(history[-1][0], choice)
-#     history[-1][1] = ""
-#     with concurrent.futures.ThreadPoolExecutor() as executor:
-#         audio_future = executor.submit(generate_audio_elevenlabs, response)
-#         for character in response:
-#             history[-1][1] += character
-#             time.sleep(0.05)
-#             yield history, None
-#         audio_path = audio_future.result()
-#         yield history, audio_path
-
-# def add_message(history, message):
-#     history.append((message, None))
-#     return history, gr.Textbox(value="", interactive=True, placeholder="Enter message or upload file...", show_label=False)
-
-# def print_like_dislike(x: gr.LikeData):
-#     print(x.index, x.value, x.liked)
-
-# def extract_addresses(response):
-#     if not isinstance(response, str):
-#         response = str(response)
-#     address_patterns = [
-#         r'([A-Z].*,\sOmaha,\sNE\s\d{5})',
-#         r'(\d{4}\s.*,\sOmaha,\sNE\s\d{5})',
-#         r'([A-Z].*,\sNE\s\d{5})',
-#         r'([A-Z].*,.*\sSt,\sOmaha,\sNE\s\d{5})',
-#         r'([A-Z].*,.*\sStreets,\sOmaha,\sNE\s\d{5})',
-#         r'(\d{2}.*\sStreets)',
-#         r'([A-Z].*\s\d{2},\sOmaha,\sNE\s\d{5})'
-#     ]
-#     addresses = []
-#     for pattern in address_patterns:
-#         addresses.extend(re.findall(pattern, response))
-#     return addresses
-
-# all_addresses = []
-
-# def generate_map(location_names):
-#     global all_addresses
-#     all_addresses.extend(location_names)
-#     api_key = os.environ['GOOGLEMAPS_API_KEY']
-#     gmaps = GoogleMapsClient(key=api_key)
-#     m = folium.Map(location=[41.2565, -95.9345], zoom_start=12)
-#     for location_name in all_addresses:
-#         geocode_result = gmaps.geocode(location_name)
-#         if geocode_result:
-#             location = geocode_result[0]['geometry']['location']
-#             folium.Marker(
-#                 [location['lat'], location['lng']],
-#                 tooltip=f"{geocode_result[0]['formatted_address']}"
-#             ).add_to(m)
-#     map_html = m._repr_html_()
-#     return map_html
-
-# def update_map_with_response(history):
-#     if not history:
-#         return ""
-#     response = history[-1][1]
-#     addresses = extract_addresses(response)
-#     return generate_map(addresses)
-
-# def clear_textbox():
-#     return ""
-
-# def show_map_if_details(history, choice):
-#     if choice in ["Details", "Conversational"]:
-#         return gr.update(visible=True), update_map_with_response(history)
-#     else:
-#         return gr.update(visible=False), ""
-
-# def generate_audio_elevenlabs(text):
-#     XI_API_KEY = os.environ['ELEVENLABS_API']
-#     VOICE_ID = 'd9MIrwLnvDeH7aZb61E9'
-#     tts_url = f"https://api.elevenlabs.io/v1/text-to-speech/{VOICE_ID}/stream"
-#     headers = {
-#         "Accept": "application/json",
-#         "xi-api-key": XI_API_KEY
-#     }
-#     data = {
-#         "text": str(text),
-#         "model_id": "eleven_multilingual_v2",
-#         "voice_settings": {
-#             "stability": 1.0,
-#             "similarity_boost": 0.0,
-#             "style": 0.60,
-#             "use_speaker_boost": False
-#         }
-#     }
-#     response = requests.post(tts_url, headers=headers, json=data, stream=True)
-#     if response.ok:
-#         with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as f:
-#             for chunk in response.iter_content(chunk_size=1024):
-#                 f.write(chunk)
-#             temp_audio_path = f.name
-#         logging.debug(f"Audio saved to {temp_audio_path}")
-#         return temp_audio_path
-#     else:
-#         logging.error(f"Error generating audio: {response.text}")
-#         return None
-
-# # Stable Diffusion setup
-# import torch
-# from diffusers import StableDiffusion3Pipeline
-
-# pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16)
-# pipe = pipe.to("cuda")
-
-# def generate_image(prompt):
-#     image = pipe(
-#         prompt,
-#         negative_prompt="",
-#         num_inference_steps=28,
-#         guidance_scale=3.0,
-#     ).images[0]
-#     return image
-
-# hardcoded_prompt_1 = "Give a high quality photograph of a great looking red 2026 toyota coupe against a skyline setting in the night, michael mann style in omaha enticing the consumer to buy this product"
-# hardcoded_prompt_2 = "A vibrant and dynamic football game scene in the style of Peter Paul Rubens, showcasing the intense match between Alabama and Nebraska. The players are depicted with the dramatic, muscular physiques and expressive faces typical of Rubens' style. The Alabama team is wearing their iconic crimson and white uniforms, while the Nebraska team is in their classic red and white attire. The scene is filled with action, with players in mid-motion, tackling, running, and catching the ball. The background features a grand stadium filled with cheering fans, banners, and the natural landscape in the distance. The colors are rich and vibrant, with a strong use of light and shadow to create depth and drama. The overall atmosphere captures the intensity and excitement of the game, infused with the grandeur and dynamism characteristic of Rubens' work."
-# hardcoded_prompt_3 = "Create a high-energy scene of a DJ performing on a large stage with vibrant lights, colorful lasers, a lively dancing crowd, and various electronic equipment in the background."
-
-# def update_images():
-#     image_1 = generate_image(hardcoded_prompt_1)
-#     image_2 = generate_image(hardcoded_prompt_2)
-#     image_3 = generate_image(hardcoded_prompt_3)
-#     return image_1, image_2, image_3
-
-# def login_with_google():
-#     response = requests.get('http://localhost:5000/login')
-#     return response.url
-
-# with gr.Blocks(theme='Pijush2023/scikit-learn-pijush') as demo:
-#     with gr.Row():
-#         with gr.Column():
-#             state = gr.State()
-#             chatbot = gr.Chatbot([], elem_id="RADAR:Channel 94.1", bubble_full_width=False)
-#             choice = gr.Radio(label="Select Style", choices=["Details", "Conversational"], value="Conversational")
-#             gr.Markdown("<h1 style='color: red;'>Talk to RADAR</h1>", elem_id="voice-markdown")
-#             chat_input = gr.Textbox(show_copy_button=True, interactive=True, show_label=False, label="ASK Radar !!!")
-#             chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])
-#             bot_msg = chat_msg.then(bot, [chatbot, choice], [chatbot, gr.Audio(interactive=False, autoplay=True)])
-#             bot_msg.then(lambda: gr.Textbox(value="", interactive=True, placeholder="Ask Radar!!!...", show_label=False), None, [chat_input])
-#             chatbot.like(print_like_dislike, None, None)
-#             clear_button = gr.Button("Clear")
-#             clear_button.click(fn=clear_textbox, inputs=None, outputs=chat_input)
-#             audio_input = gr.Audio(sources=["microphone"], streaming=True, type='numpy')
-#             audio_input.stream(transcribe_function, inputs=[state, audio_input], outputs=[state, chat_input], api_name="SAMLOne_real_time")
-#             gr.Markdown("<h1 style='color: red;'>Map</h1>", elem_id="location-markdown")
-#             location_output = gr.HTML()
-#             bot_msg.then(show_map_if_details, [chatbot, choice], [location_output, location_output])
-#         with gr.Column():
-#             weather_output = gr.HTML(value=fetch_local_weather())
-#             news_output = gr.HTML(value=fetch_local_news())
-#             events_output = gr.HTML(value=fetch_local_events())
-#         with gr.Column():
-#             image_output_1 = gr.Image(value=generate_image(hardcoded_prompt_1), width=400, height=400)
-#             image_output_2 = gr.Image(value=generate_image(hardcoded_prompt_2), width=400, height=400)
-#             image_output_3 = gr.Image(value=generate_image(hardcoded_prompt_3), width=400, height=400)
-#             refresh_button = gr.Button("Refresh Images")
-#             refresh_button.click(fn=update_images, inputs=None, outputs=[image_output_1, image_output_2, image_output_3])
-#         with gr.Column():
-#             login_button = gr.Button("Login with Google")
-#             login_button.click(fn=login_with_google)
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-# demo.queue()
-# demo.launch(share=True)
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