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Initial commit with Git LFS for images
Browse files- .gitattributes +36 -0
- README.md +72 -0
- app.py +270 -0
- openai_client.py +48 -0
- requirements.txt +2 -0
- restart_app.sh +11 -0
.gitattributes
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README.md
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---
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title: Shakespeare AI
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emoji: π»
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colorFrom: yellow
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colorTo: gray
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sdk: streamlit
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sdk_version: 1.44.1
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app_file: app.py
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pinned: false
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license: cc-by-nc-sa-4.0
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short_description: Rewrites .. stuff .. in Shakespearean English
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---
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A Streamlit application that transforms modern text into Shakespearean English using various system prompts.
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## Features
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- Transform any text into Shakespearean English
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- Multiple transformation styles for different types of content
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- Easy-to-use interface with input and output areas
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- Copy and clear functionality for convenience
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- Secure API key input
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## Usage
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1. Run the Streamlit application:
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```
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streamlit run app.py
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```
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2. Open your web browser and navigate to the URL displayed in the terminal (usually http://localhost:8501)
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3. Enter your OpenAI API key in the sidebar
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4. Select a transformation style from the dropdown menu
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5. Enter your text in the input area
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6. Click the "Transform to Shakespearean" button
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7. View the transformed text in the output area
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8. Use the "Copy Text" button to copy the transformed text to your clipboard
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9. Use the "Clear Text" button to clear the output
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## System Prompts
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The application uses a collection of system prompts organized in the `system-prompts` directory. These prompts are designed to transform different types of content into Shakespearean English, including:
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- Basic transformations
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- Business tools
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- Various formats (emails, social media posts, etc.)
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- Different purposes (documentation, copywriting, etc.)
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Each prompt provides specific instructions for transforming text in a way that's appropriate for the content type.
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## Requirements
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- Python 3.7+
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- Streamlit
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- OpenAI API key
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## Note
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This application requires an OpenAI API key to function. You can obtain an API key by signing up at [OpenAI's website](https://platform.openai.com/signup).
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app.py
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import streamlit as st
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import os
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import random
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from pathlib import Path
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# Import our clean OpenAI client implementation
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from openai_client import generate_completion
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# Set page configuration
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st.set_page_config(
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page_title="Shakespearean Text Generator",
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page_icon="π",
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layout="wide",
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initial_sidebar_state="expanded"
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)
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# Custom CSS for styling
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def local_css():
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st.markdown("""
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<style>
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.main {
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background-color: #f5f5f0;
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background-image: url("https://www.transparenttextures.com/patterns/old-paper.png");
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}
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.stApp {
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font-family: 'Garamond', 'Georgia', serif;
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}
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h1, h2, h3 {
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font-family: 'Garamond', 'Georgia', serif;
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color: #5c3317;
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}
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.stButton>button {
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background-color: #5c3317;
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color: white;
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border-radius: 5px;
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font-family: 'Garamond', 'Georgia', serif;
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font-weight: bold;
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}
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.stButton>button:hover {
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background-color: #8b4513;
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color: white;
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}
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.stTextArea>div>div>textarea {
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border: 2px solid #8b4513;
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border-radius: 5px;
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font-family: 'Garamond', 'Georgia', serif;
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}
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.sidebar .sidebar-content {
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background-color: #f5f5f0;
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background-image: url("https://www.transparenttextures.com/patterns/old-paper.png");
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}
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.decoration {
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text-align: center;
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font-size: 24px;
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color: #5c3317;
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margin: 10px 0;
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}
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.shakespeare-quote {
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font-style: italic;
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text-align: center;
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color: #5c3317;
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padding: 10px;
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border-left: 3px solid #8b4513;
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margin: 10px 0;
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}
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.copy-btn {
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position: absolute;
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top: 10px;
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right: 10px;
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z-index: 1000;
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}
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</style>
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""", unsafe_allow_html=True)
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# Function to scan and get all system prompts
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def get_system_prompts():
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prompts = {}
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base_dir = Path("system-prompts")
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# Check if the directory exists
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if not base_dir.exists():
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st.error(f"System prompts directory not found: {base_dir}")
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return {"Default": "system-prompts/basic-transformation/foundational.md"}
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# Find all markdown files
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md_files = list(base_dir.glob("**/*.md"))
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# If no files found, return a default
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if not md_files:
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st.warning("No system prompt files found. Using default.")
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return {"Default": "system-prompts/basic-transformation/foundational.md"}
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for prompt_file in md_files:
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# Create a friendly name from the path
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relative_path = prompt_file.relative_to(base_dir)
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friendly_name = str(relative_path).replace(".md", "").replace("/", " > ")
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# Store the path and friendly name
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prompts[friendly_name] = str(prompt_file)
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return prompts
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# Function to read the content of a system prompt
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def read_system_prompt(prompt_path):
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try:
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with open(prompt_path, "r") as f:
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return f.read()
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except FileNotFoundError:
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st.error(f"System prompt file not found: {prompt_path}")
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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."
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except Exception as e:
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st.error(f"Error reading system prompt: {str(e)}")
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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."
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# Function to transform text using OpenAI API
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def transform_text(api_key, system_prompt, user_text, model="gpt-4"):
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"""
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Wrapper function that uses our clean OpenAI client implementation
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"""
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return generate_completion(api_key, system_prompt, user_text, model)
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# Main app
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def main():
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# Apply custom CSS
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local_css()
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# Display banner image with animation
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st.image("shakespearegpt.png", use_column_width=True)
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# App title and description
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st.title("Shakespearean Text Generator")
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st.markdown("""
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<div class="decoration">βοΈ βοΈ βοΈ</div>
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<p style="font-size: 18px; text-align: center;">
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Transform thy modern text into eloquent Shakespearean prose!<br>
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Select a transformation style, enter thy text, and watch as 'tis transformed into the language of the Bard.
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</p>
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<div class="decoration">βοΈ βοΈ βοΈ</div>
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""", unsafe_allow_html=True)
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# Random Shakespeare quote
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quotes = [
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"All the world's a stage, and all the men and women merely players.",
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"The course of true love never did run smooth.",
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"To be, or not to be, that is the question.",
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"What's in a name? That which we call a rose by any other name would smell as sweet.",
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"Some are born great, some achieve greatness, and some have greatness thrust upon them.",
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"Love all, trust a few, do wrong to none.",
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"We know what we are, but know not what we may be.",
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"The fool doth think he is wise, but the wise man knows himself to be a fool.",
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"All that glitters is not gold.",
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"Be not afraid of greatness. Some are born great, some achieve greatness, and others have greatness thrust upon them."
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]
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st.markdown(f"""
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<div class="shakespeare-quote">
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"{random.choice(quotes)}"<br>
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<small>- William Shakespeare</small>
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</div>
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""", unsafe_allow_html=True)
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# Sidebar for API key and settings
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with st.sidebar:
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st.header("π OPENAI API KEY")
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api_key = st.text_input("ENTER THY OPENAI API KEY", type="password")
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st.markdown("Thy API key is required to use the OpenAI GPT models for text transformation.")
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# Model selection
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st.header("βοΈ SETTINGS")
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model = st.selectbox(
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"SELECT THY GPT MODEL",
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172 |
+
["gpt-4", "gpt-3.5-turbo"],
|
173 |
+
index=0
|
174 |
+
)
|
175 |
+
|
176 |
+
st.divider()
|
177 |
+
|
178 |
+
# About section
|
179 |
+
st.header("π About")
|
180 |
+
st.markdown("""
|
181 |
+
This application uses OpenAI's GPT models to transform text into Shakespearean English.
|
182 |
+
|
183 |
+
The system prompts used for transformation are from a curated collection designed to mimic
|
184 |
+
various Shakespearean styles for different types of content.
|
185 |
+
|
186 |
+
<div class="decoration">βοΈ βοΈ βοΈ</div>
|
187 |
+
|
188 |
+
"O for a Muse of fire, that would ascend<br>
|
189 |
+
The brightest heaven of invention!"<br>
|
190 |
+
<small>- Henry V</small>
|
191 |
+
""", unsafe_allow_html=True)
|
192 |
+
|
193 |
+
# Main content area with two columns
|
194 |
+
col1, col2 = st.columns(2)
|
195 |
+
|
196 |
+
with col1:
|
197 |
+
st.header("π INPUT")
|
198 |
+
|
199 |
+
# Get all system prompts
|
200 |
+
prompts = get_system_prompts()
|
201 |
+
prompt_names = list(prompts.keys())
|
202 |
+
|
203 |
+
# Dropdown to select transformation
|
204 |
+
selected_prompt_name = st.selectbox("SELECT TRANSFORMATION STYLE", prompt_names)
|
205 |
+
selected_prompt_path = prompts[selected_prompt_name]
|
206 |
+
|
207 |
+
# Display the selected prompt description
|
208 |
+
with st.expander("VIEW TRANSFORMATION DESCRIPTION"):
|
209 |
+
st.markdown(read_system_prompt(selected_prompt_path))
|
210 |
+
|
211 |
+
# Text input area
|
212 |
+
user_text = st.text_area("ENTER THY TEXT", height=300,
|
213 |
+
placeholder="Type or paste thy modern text here...")
|
214 |
+
|
215 |
+
# Transform button with animation
|
216 |
+
transform_col1, transform_col2, transform_col3 = st.columns([1, 2, 1])
|
217 |
+
with transform_col2:
|
218 |
+
if st.button("β¨ TRANSFORM TO SHAKESPEAREAN β¨", use_container_width=True):
|
219 |
+
if not api_key:
|
220 |
+
st.error("Prithee, enter thy OpenAI API key in the sidebar.")
|
221 |
+
elif not user_text:
|
222 |
+
st.error("Thou must enter some text to transform.")
|
223 |
+
else:
|
224 |
+
with st.spinner("Transforming... The Bard is at work!"):
|
225 |
+
system_prompt = read_system_prompt(selected_prompt_path)
|
226 |
+
st.session_state.transformed_text = transform_text(api_key, system_prompt, user_text, model)
|
227 |
+
|
228 |
+
with col2:
|
229 |
+
st.header("π SHAKESPEAREAN OUTPUT")
|
230 |
+
|
231 |
+
# Initialize session state for transformed text if it doesn't exist
|
232 |
+
if "transformed_text" not in st.session_state:
|
233 |
+
st.session_state.transformed_text = ""
|
234 |
+
|
235 |
+
# Display transformed text with styling
|
236 |
+
st.markdown('<div style="position: relative;">', unsafe_allow_html=True)
|
237 |
+
transformed_text = st.text_area(
|
238 |
+
"TRANSFORMED TEXT",
|
239 |
+
value=st.session_state.transformed_text,
|
240 |
+
height=300,
|
241 |
+
placeholder="The Bard's words shall appear here..."
|
242 |
+
)
|
243 |
+
|
244 |
+
# Buttons for copy and clear
|
245 |
+
col_copy, col_space, col_clear = st.columns([1, 1, 1])
|
246 |
+
|
247 |
+
with col_copy:
|
248 |
+
if st.button("π COPY TEXT", use_container_width=True):
|
249 |
+
# Use Streamlit's built-in functionality for clipboard
|
250 |
+
st.code(transformed_text, language="text")
|
251 |
+
st.success("Text copied to clipboard! You can also use the copy button in the code block above.")
|
252 |
+
|
253 |
+
with col_clear:
|
254 |
+
if st.button("π§Ή CLEAR TEXT", use_container_width=True):
|
255 |
+
st.session_state.transformed_text = ""
|
256 |
+
st.rerun()
|
257 |
+
|
258 |
+
# Add a fun element - Shakespeare emoji reactions
|
259 |
+
if st.session_state.transformed_text:
|
260 |
+
st.markdown('<div class="decoration" style="margin-top: 20px;">', unsafe_allow_html=True)
|
261 |
+
reactions = ["π", "π", "π", "ποΈ", "π", "βοΈ", "π°", "π§ββοΈ"]
|
262 |
+
st.markdown(f"""
|
263 |
+
<div style="text-align: center; margin-top: 20px;">
|
264 |
+
<p>Shakespeare would be {random.choice(['proud', 'delighted', 'amused', 'impressed'])}!</p>
|
265 |
+
<p style="font-size: 24px;">{' '.join(random.sample(reactions, 4))}</p>
|
266 |
+
</div>
|
267 |
+
""", unsafe_allow_html=True)
|
268 |
+
|
269 |
+
if __name__ == "__main__":
|
270 |
+
main()
|
openai_client.py
ADDED
@@ -0,0 +1,48 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
"""
|
2 |
+
A direct implementation using requests to bypass the OpenAI SDK entirely.
|
3 |
+
This avoids any issues with the OpenAI client configuration.
|
4 |
+
"""
|
5 |
+
import requests
|
6 |
+
import json
|
7 |
+
|
8 |
+
def generate_completion(api_key, system_prompt, user_text, model="gpt-4"):
|
9 |
+
"""
|
10 |
+
Generate a completion by directly calling the OpenAI API using requests.
|
11 |
+
This bypasses the OpenAI SDK entirely.
|
12 |
+
"""
|
13 |
+
if not api_key or not system_prompt or not user_text:
|
14 |
+
return "Please provide an API key, select a transformation, and enter some text."
|
15 |
+
|
16 |
+
try:
|
17 |
+
# OpenAI API endpoint
|
18 |
+
url = "https://api.openai.com/v1/chat/completions"
|
19 |
+
|
20 |
+
# Headers with API key
|
21 |
+
headers = {
|
22 |
+
"Content-Type": "application/json",
|
23 |
+
"Authorization": f"Bearer {api_key}"
|
24 |
+
}
|
25 |
+
|
26 |
+
# Request payload
|
27 |
+
payload = {
|
28 |
+
"model": model,
|
29 |
+
"messages": [
|
30 |
+
{"role": "system", "content": system_prompt},
|
31 |
+
{"role": "user", "content": user_text}
|
32 |
+
],
|
33 |
+
"temperature": 0.7,
|
34 |
+
"max_tokens": 2000
|
35 |
+
}
|
36 |
+
|
37 |
+
# Make the API call directly using requests
|
38 |
+
response = requests.post(url, headers=headers, json=payload)
|
39 |
+
|
40 |
+
# Check if the request was successful
|
41 |
+
if response.status_code == 200:
|
42 |
+
response_data = response.json()
|
43 |
+
return response_data["choices"][0]["message"]["content"]
|
44 |
+
else:
|
45 |
+
return f"Error: API returned status code {response.status_code}. {response.text}"
|
46 |
+
|
47 |
+
except Exception as e:
|
48 |
+
return f"Error: {str(e)}"
|
requirements.txt
ADDED
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
1 |
+
streamlit==1.32.0
|
2 |
+
openai==1.12.0
|
restart_app.sh
ADDED
@@ -0,0 +1,11 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/bin/bash
|
2 |
+
|
3 |
+
# Kill any running Streamlit processes
|
4 |
+
pkill -f streamlit
|
5 |
+
|
6 |
+
# Wait a moment for processes to terminate
|
7 |
+
sleep 1
|
8 |
+
|
9 |
+
# Activate virtual environment and run the app
|
10 |
+
source .venv/bin/activate
|
11 |
+
streamlit run app.py --server.fileWatcherType none
|