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Update app.py
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‎app.py‎

Lines changed: 64 additions & 173 deletions
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import streamlit as st
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from g4f.client import Client
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import sqlite3
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import google.generativeai as genai
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import csv
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import os
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# import pyttsx3
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import pyperclip
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st.set_page_config(page_title="DarkGPT",
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page_icon="🤖",
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layout="wide",
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initial_sidebar_state="expanded"
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# Set page configuration
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st.set_page_config(
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page_title="DarkGPT",
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page_icon="🤖",
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layout="wide",
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initial_sidebar_state="expanded"
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)
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def local_css(file_name):
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with open(file_name) as f:
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st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
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local_css("style.css")
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# Create a connection to the database
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conn = sqlite3.connect('chat_history.db')
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c = conn.cursor()
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# Create table if not exists
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try:
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c.execute('''CREATE TABLE IF NOT EXISTS chat_history
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(conversation_id INTEGER, role TEXT, content TEXT)''')
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conn.commit()
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except Exception as e:
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st.error(f"An error occurred: {e}")
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# Streamlit app
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def main():
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try:
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if "chat_history" not in st.session_state:
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st.session_state.chat_history = []
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if "conversation_id" not in st.session_state:
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st.session_state.conversation_id = 1
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models = {
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"🚀 Airoboros 70B": "airoboros-70b",
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"👑 Gemini 1.0": "gemini-1.0-pro",
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"🧨 Gemini 1.0 Pro ": "gemini-1.0-pro-001",
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"⚡ Gemini 1.0 pro latest": "gemini-1.0-pro-latest",
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"🔮 Gemini Pro": "gemini-pro"
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}
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columns = st.columns(3) # Split the layout into three columns
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with columns[0]:
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st.header("DarkGPT")
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with columns[2]:
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selected_model_display_name = st.selectbox("Select Model", list(models.keys()), index=0)
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selected_model = models[selected_model_display_name]
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with columns[1]:
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pass
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# if st.button("summarize"):
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# st.switch_page('pages/summarize.py')
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# Sidebar (left side) - New chat button
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if st.sidebar.button("✨ New Chat", key="new_chat_button"):
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st.session_state.chat_history.clear()
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st.session_state.conversation_id += 1
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# Sidebar (left side) - Display saved chat
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st.sidebar.write("Chat History")
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c.execute("SELECT DISTINCT conversation_id FROM chat_history")
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conversations = c.fetchall()
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for conv_id in reversed(conversations):
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c.execute("SELECT content FROM chat_history WHERE conversation_id=? AND role='bot' LIMIT 1",
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(conv_id[0],))
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first_bot_response = c.fetchone()
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if first_bot_response:
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if st.sidebar.button(" ".join(first_bot_response[0].split()[0:5])):
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display_conversation(conv_id[0])
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# Sidebar (left side) - Clear Chat History button
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if st.sidebar.button("Clear Chat History ✖️"):
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st.session_state.chat_history.clear()
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c.execute("DELETE FROM chat_history")
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conn.commit()
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# Main content area (center)
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st.markdown("---")
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user_input = st.chat_input("Ask Anything ...")
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if user_input:
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if selected_model == "airoboros-70b":
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try:
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client = Client()
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response = client.chat.completions.create(
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model=models[selected_model_display_name],
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messages=[{"role": "user", "content": user_input}],
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)
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bot_response = response.choices[0].message.content
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st.session_state.chat_history.append({"role": "user", "content": user_input})
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st.session_state.chat_history.append({"role": "bot", "content": bot_response})
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# Store chat in the database
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for chat in st.session_state.chat_history:
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c.execute("INSERT INTO chat_history VALUES (?, ?, ?)",
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(st.session_state.conversation_id, chat["role"], chat["content"]))
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conn.commit()
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# Display chat history
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for index, chat in enumerate(st.session_state.chat_history):
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with st.chat_message(chat["role"]):
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if chat["role"] == "user":
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st.markdown(chat["content"])
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elif chat["role"] == "bot":
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st.markdown(chat["content"])
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except Exception as e:
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st.error(f"An error occurred: {e}")
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else:
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try:
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# GEMINI Replace with your Gemini Api key
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GOOGLE_API_KEY = os.getenv('gemini-api')
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genai.configure(api_key=GOOGLE_API_KEY)
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model = genai.GenerativeModel(selected_model)
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prompt = user_input
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response = model.generate_content(prompt)
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bot_response = response.candidates[0].content.parts[0].text
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st.session_state.chat_history.append({"role": "user", "content": user_input})
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st.session_state.chat_history.append({"role": "bot", "content": bot_response})
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# Store chat in the database
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for chat in st.session_state.chat_history:
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c.execute("INSERT INTO chat_history VALUES (?, ?, ?)",
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(st.session_state.conversation_id, chat["role"], chat["content"]))
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conn.commit()
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for index, chat in enumerate(st.session_state.chat_history):
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with st.chat_message(chat["role"]):
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if chat["role"] == "user":
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st.markdown(chat["content"])
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elif chat["role"] == "bot":
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st.markdown(chat["content"])
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except Exception as e:
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st.error(f"An error occurred: {e}")
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# export_to_csv(st.session_state.chat_history)
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except Exception as e:
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st.error(f"An error occurred: {e}")
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# def export_to_csv(chat_history):
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# filename = "chat_history.csv"
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# latest_conversation = chat_history[-2:] # Get only the latest conversation
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# with open(filename, "a+", newline="") as csvfile:
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# fieldnames = ["User Input", "Bot Response"]
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# writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
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# if csvfile.tell() == 0: # Check if the file is empty
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# writer.writeheader() # Write header if file is empty
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# if len(latest_conversation) == 2: # Check if the latest conversation is complete
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# writer.writerow({"User Input": latest_conversation[0]["content"], "Bot Response": latest_conversation[1]["content"]})
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def display_conversation(conversation_id):
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c.execute("SELECT * FROM chat_history WHERE conversation_id=?", (conversation_id,))
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chats = c.fetchall()
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st.markdown(f"### Conversation")
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for chat in chats:
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st.markdown(f"{chat[1]}")
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st.markdown(f"{chat[2]}")
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def display_homepage():
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st.markdown("<h1 style='text-align: center; color: white; font-size: 36px;'>Welcome to DarkGPT! 🧨</h1>", unsafe_allow_html=True)
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st.markdown("<h3 style='text-align: center; font-size: 56px;'>🤖</h3>", unsafe_allow_html=True)
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st.markdown("<h3 style='text-align: center; color: grey; font-size: 20px;'>DarkGPT: Your AI text assistant for quick summarization and analysis. Summarize text, analyze complexity, and get insights instantly!</h3>", unsafe_allow_html=True)
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st.markdown('---')
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st.markdown("<h3 style='text-align: left; color:#F63366; font-size: 24px;'><b>What is DarkGPT?</b></h3>", unsafe_allow_html=True)
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st.markdown("""
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DarkGPT is a versatile AI-powered text assistant designed to enhance your reading and writing experience.
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Leveraging advanced natural language processing models, DarkGPT provides two main functionalities:
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text summarization and text analysis. Whether you need to quickly understand the essence of a lengthy article or
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dive deep into the complexity of a text, DarkGPT is here to help.
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""")
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st.markdown("<h3 style='text-align: left; color:#F63366; font-size: 24px;'><b>Features</b></h3>", unsafe_allow_html=True)
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st.markdown("### 🤖 DarkGPT - AI-Powered Chatbot:\n"
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"DarkGPT is an advanced AI-powered chatbot designed to simulate human-like conversations.\n"
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"Using state-of-the-art natural language processing models, DarkGPT can understand and generate\n"
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"responses based on user input, making it ideal for various applications such as customer support,\n"
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"virtual assistants, and interactive content generation.\n\n"
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"DarkGPT supports multiple AI models, each tailored for different tasks and levels of complexity.\n"
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"Users can select from a range of models, including those optimized for general chat, technical queries,\n"
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"creative writing, and more, providing flexibility and customization to suit specific needs.\n\n"
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"**Key Features:**\n"
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"- **AI Models:** Utilizes models like Airoboros 70B and Gemini Pro for robust conversation handling.\n"
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"- **Natural Language Processing:** Processes user input to generate contextually relevant responses.\n"
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"- **Chat History:** Stores and retrieves chat history to maintain continuity across sessions.\n"
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"- **Customization:** Offers options to fine-tune responses and personalize user interaction.\n\n"
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"Explore DarkGPT's capabilities and start conversing today!", unsafe_allow_html=True)
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st.markdown("### 🔍 Summarization Page:\n"
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"- **Input Options:** Users can input text directly or upload a text file for summarization.\n"
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"- **Example Text:** An example text is provided to help users get started quickly.\n"
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"- **Summarize Button:** Click the 'Summarize' button to generate a summary using the BART model.\n"
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"- **Error Handling:** Error messages are displayed if the input text length requirements are not met.", unsafe_allow_html=True)
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st.markdown("### 📊 Analysis Page:\n"
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"- **Input Options:** Users can input text directly or upload a text file for analysis.\n"
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"- **Example Text:** An example text is provided to help users get started quickly.\n"
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"- **Analyze Button:** Click the 'Analyze' button to generate various metrics such as reading time, text complexity, lexical richness, and number of sentences.\n"
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"- **Error Handling:** Error messages are displayed if the input text length requirements are not met.", unsafe_allow_html=True)
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footer = '''
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<footer style="text-align: center; margin-top: 50px; font-family: Arial, sans-serif; color: #555;">
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<p>Developed by DarkCoder</p>
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<p>
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<a href="https://github.com/codewithdark-git" target="_blank" style="text-decoration: none; color: #007bff; margin-right: 10px;">GitHub</a>
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| <a href="https://www.linkedin.com/in/codewithdark/" target="_blank" style="text-decoration: none; color: #007bff; margin-right: 10px;">Linkedin</a>
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| <a href="https://www.facebook.com/codewithdark.fb/" target="_blank" style="text-decoration: none; color: #007bff;">Facebook</a>
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</p>
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</footer>
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'''
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# Display the footer
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st.markdown(footer, unsafe_allow_html=True)
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if __name__ == "__main__":
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main()
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display_homepage()

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