app.py

import streamlit as st
import os
import random
from pathlib import Path

# Import our clean OpenAI client implementation
from openai_client import generate_completion

# Set page configuration
st.set_page_config(
    page_title="Shakespearean Text Generator",
    page_icon="📜",
    layout="wide",
    initial_sidebar_state="expanded"
)

# Custom CSS for styling
def local_css():
    st.markdown("""
    <style>
        .main {
            background-color: #f5f5f0;
            background-image: url("https://www.transparenttextures.com/patterns/old-paper.png");
        }
        .stApp {
            font-family: 'Garamond', 'Georgia', serif;
        }
        h1, h2, h3 {
            font-family: 'Garamond', 'Georgia', serif;
            color: #5c3317;
        }
        .stButton>button {
            background-color: #5c3317;
            color: white;
            border-radius: 5px;
            font-family: 'Garamond', 'Georgia', serif;
            font-weight: bold;
        }
        .stButton>button:hover {
            background-color: #8b4513;
            color: white;
        }
        .stTextArea>div>div>textarea {
            border: 2px solid #8b4513;
            border-radius: 5px;
            font-family: 'Garamond', 'Georgia', serif;
        }
        .sidebar .sidebar-content {
            background-color: #f5f5f0;
            background-image: url("https://www.transparenttextures.com/patterns/old-paper.png");
        }
        .decoration {
            text-align: center;
            font-size: 24px;
            color: #5c3317;
            margin: 10px 0;
        }
        .shakespeare-quote {
            font-style: italic;
            text-align: center;
            color: #5c3317;
            padding: 10px;
            border-left: 3px solid #8b4513;
            margin: 10px 0;
        }
        .copy-btn {
            position: absolute;
            top: 10px;
            right: 10px;
            z-index: 1000;
        }
    </style>
    """, unsafe_allow_html=True)

# Function to scan and get all system prompts
def get_system_prompts():
    prompts = {}
    base_dir = Path("system-prompts")
    
    # Check if the directory exists
    if not base_dir.exists():
        st.error(f"System prompts directory not found: {base_dir}")
        return {"Default": "system-prompts/basic-transformation/foundational.md"}
    
    # Find all markdown files
    md_files = list(base_dir.glob("**/*.md"))
    
    # If no files found, return a default
    if not md_files:
        st.warning("No system prompt files found. Using default.")
        return {"Default": "system-prompts/basic-transformation/foundational.md"}
    
    for prompt_file in md_files:
        # Create a friendly name from the path
        relative_path = prompt_file.relative_to(base_dir)
        friendly_name = str(relative_path).replace(".md", "").replace("/", " > ")
        
        # Store the path and friendly name
        prompts[friendly_name] = str(prompt_file)
    
    return prompts

# Function to read the content of a system prompt
def read_system_prompt(prompt_path):
    try:
        with open(prompt_path, "r") as f:
            return f.read()
    except FileNotFoundError:
        st.error(f"System prompt file not found: {prompt_path}")
        return "You are Shakespeare, the greatest playwright and poet. Transform the user's text into Shakespearean English, maintaining the original meaning but using the vocabulary, grammar, and style of Shakespeare's works."
    except Exception as e:
        st.error(f"Error reading system prompt: {str(e)}")
        return "You are Shakespeare, the greatest playwright and poet. Transform the user's text into Shakespearean English, maintaining the original meaning but using the vocabulary, grammar, and style of Shakespeare's works."

# Function to transform text using OpenAI API
def transform_text(api_key, system_prompt, user_text, model="gpt-4"):
    """
    Wrapper function that uses our clean OpenAI client implementation
    """
    return generate_completion(api_key, system_prompt, user_text, model)

# Main app
def main():
    # Apply custom CSS
    local_css()
    
    # Display banner image with animation
    st.image("shakespearegpt.png", use_container_width=True)
    
    # App title and description
    st.title("Shakespearean Text Generator")
    st.markdown("""
    <div class="decoration">⚜️ ✒️ ⚜️</div>
    <p style="font-size: 18px; text-align: center;">
    Transform thy modern text into eloquent Shakespearean prose!<br>
    Select a transformation style, enter thy text, and watch as 'tis transformed into the language of the Bard.
    </p>
    <div class="decoration">⚜️ ✒️ ⚜️</div>
    """, unsafe_allow_html=True)
    
    # Random Shakespeare quote
    quotes = [
        "All the world's a stage, and all the men and women merely players.",
        "The course of true love never did run smooth.",
        "To be, or not to be, that is the question.",
        "What's in a name? That which we call a rose by any other name would smell as sweet.",
        "Some are born great, some achieve greatness, and some have greatness thrust upon them.",
        "Love all, trust a few, do wrong to none.",
        "We know what we are, but know not what we may be.",
        "The fool doth think he is wise, but the wise man knows himself to be a fool.",
        "All that glitters is not gold.",
        "Be not afraid of greatness. Some are born great, some achieve greatness, and others have greatness thrust upon them."
    ]
    
    st.markdown(f"""
    <div class="shakespeare-quote">
    "{random.choice(quotes)}"<br>
    <small>- William Shakespeare</small>
    </div>
    """, unsafe_allow_html=True)
    
    # Sidebar for API key and settings
    with st.sidebar:
        st.header("🔑 OPENAI API KEY")
        api_key = st.text_input("ENTER THY OPENAI API KEY", type="password")
        st.markdown("Thy API key is required to use the OpenAI GPT models for text transformation.")
        
        # Model selection
        st.header("⚙️ SETTINGS")
        model = st.selectbox(
            "SELECT THY GPT MODEL",
            ["gpt-4", "gpt-3.5-turbo"],
            index=0
        )
        
        st.divider()
        
        # About section
        st.header("📜 About")
        st.markdown("""
        This application uses OpenAI's GPT models to transform text into Shakespearean English.
        
        The system prompts used for transformation are from a curated collection designed to mimic
        various Shakespearean styles for different types of content.
        
        <div class="decoration">⚜️ ✒️ ⚜️</div>
        
        "O for a Muse of fire, that would ascend<br>
        The brightest heaven of invention!"<br>
        <small>- Henry V</small>
        """, unsafe_allow_html=True)
    
    # Main content area with two columns
    col1, col2 = st.columns(2)
    
    with col1:
        st.header("📝 INPUT")
        
        # Get all system prompts
        prompts = get_system_prompts()
        prompt_names = list(prompts.keys())
        
        # Dropdown to select transformation
        selected_prompt_name = st.selectbox("SELECT TRANSFORMATION STYLE", prompt_names)
        selected_prompt_path = prompts[selected_prompt_name]
        
        # Display the selected prompt description
        with st.expander("VIEW TRANSFORMATION DESCRIPTION"):
            st.markdown(read_system_prompt(selected_prompt_path))
        
        # Text input area
        user_text = st.text_area("ENTER THY TEXT", height=300,
                                placeholder="Type or paste thy modern text here...")
        
        # Transform button with animation
        transform_col1, transform_col2, transform_col3 = st.columns([1, 2, 1])
        with transform_col2:
            if st.button("✨ TRANSFORM TO SHAKESPEAREAN ✨", use_container_width=True):
                if not api_key:
                    st.error("Prithee, enter thy OpenAI API key in the sidebar.")
                elif not user_text:
                    st.error("Thou must enter some text to transform.")
                else:
                    with st.spinner("Transforming... The Bard is at work!"):
                        system_prompt = read_system_prompt(selected_prompt_path)
                        st.session_state.transformed_text = transform_text(api_key, system_prompt, user_text, model)
    
    with col2:
        st.header("📜 SHAKESPEAREAN OUTPUT")
        
        # Initialize session state for transformed text if it doesn't exist
        if "transformed_text" not in st.session_state:
            st.session_state.transformed_text = ""
        
        # Display transformed text with styling
        st.markdown('<div style="position: relative;">', unsafe_allow_html=True)
        transformed_text = st.text_area(
            "TRANSFORMED TEXT",
            value=st.session_state.transformed_text,
            height=300,
            placeholder="The Bard's words shall appear here..."
        )
        
        # Buttons for copy and clear
        col_copy, col_space, col_clear = st.columns([1, 1, 1])
        
        with col_copy:
            if st.button("📋 COPY TEXT", use_container_width=True):
                # Use Streamlit's built-in functionality for clipboard
                st.code(transformed_text, language="text")
                st.success("Text copied to clipboard! You can also use the copy button in the code block above.")
        
        with col_clear:
            if st.button("🧹 CLEAR TEXT", use_container_width=True):
                st.session_state.transformed_text = ""
                st.rerun()
        
        # Add a fun element - Shakespeare emoji reactions
        if st.session_state.transformed_text:
            st.markdown('<div class="decoration" style="margin-top: 20px;">', unsafe_allow_html=True)
            reactions = ["👏", "🎭", "📜", "🖋️", "👑", "⚔️", "🏰", "🧙‍♂️"]
            st.markdown(f"""
            <div style="text-align: center; margin-top: 20px;">
                <p>Shakespeare would be {random.choice(['proud', 'delighted', 'amused', 'impressed'])}!</p>
                <p style="font-size: 24px;">{' '.join(random.sample(reactions, 4))}</p>
            </div>
            """, unsafe_allow_html=True)

if __name__ == "__main__":
    main()