app.py

import streamlit as st
import openai
import urllib.parse
import io
from PIL import Image

# Function to call OpenAI GPT model for prompt processing
def get_diagram_code(prompt, diagram_type, api_key):
    try:
        # Set the OpenAI API key dynamically based on user input
        openai.api_key = api_key

        # For GPT-4 and other chat models, use the v1/chat/completions endpoint
        response = openai.ChatCompletion.create(
            model="gpt-4o",  # Make sure you're using the right model
            messages=[ 
                {"role": "system", "content": "You are a helpful assistant."},
                {"role": "user", "content": f"Generate a {diagram_type} diagram in Mermaid.js syntax based on the following prompt: {prompt}"}
            ],
            max_tokens=500
        )

        return response['choices'][0]['message']['content'].strip()
    
    except Exception as e:
        st.error(f"Error: {e}")
        return None

# Function to convert SVG to PNG
def convert_svg_to_png(svg_file):
    try:
        # Read the uploaded SVG file and convert it to PNG using cairosvg
        png_output = io.BytesIO()
        cairosvg.svg2png(file_obj=svg_file, write_to=png_output)
        png_output.seek(0)
        return png_output
    except Exception as e:
        st.error(f"Error during SVG to PNG conversion: {e}")
        return None

# Adding custom CSS
def custom_css():
    st.markdown("""
        <style>
            body {
                background-color: #f0f4f8;
                font-family: 'Roboto', sans-serif;
            }
            .stButton>button {
                background-color: #4CAF50;
                color: white;
                font-size: 18px;
                padding: 12px 24px;
                border-radius: 8px;
                transition: background-color 0.3s ease;
            }
            .stButton>button:hover {
                background-color: #45a049;
            }
            .stTextInput, .stTextArea {
                background-color: #fff;
                border: 2px solid #ddd;
                border-radius: 8px;
                padding: 12px;
                font-size: 16px;
                transition: border 0.3s ease;
            }
            .stTextInput:focus, .stTextArea:focus {
                border-color: #4CAF50;
            }
            .stImage {
                margin-bottom: 20px;
                border-radius: 10px;
            }
            h1 {
                color: #333;
                text-align: center;
                font-size: 36px;
            }
            .expandable-section {
                margin-top: 20px;
            }
            iframe {
                border: 0;
                border-radius: 10px;
            }
            .loading-spinner {
                display: none;
                animation: spin 2s infinite linear;
                border: 6px solid #f3f3f3;
                border-top: 6px solid #3498db;
                border-radius: 50%;
                width: 50px;
                height: 50px;
                margin: 0 auto;
            }
            @keyframes spin {
                0% { transform: rotate(0deg); }
                100% { transform: rotate(360deg); }
            }
        </style>
    """, unsafe_allow_html=True)

# Streamlit App UI
def main():
    custom_css()  # Apply custom CSS
    
    st.title("Generate Diagrams using AI and MermaidFlow")
    
    # Display a logo or icon with subtle animation
    image = Image.open("11.png")  # Path to your image file
    st.image(image, width=300) 

    # Display sample prompt
    with st.expander("Sample Prompt For Users", expanded=True):
        st.markdown("""
            Create a UML diagram for a **Library Management System** that includes classes such as **Book** (with attributes like `bookID`, `title`, `author`, `publisher`, `genre`, `availabilityStatus` and methods like `checkAvailability()`, `updateAvailability()`), **Member** (with attributes such as `memberID`, `name`, `email`, `phoneNumber`, `membershipDate` and methods like `borrowBook()`, `returnBook()`, `reserveBook()`), **Staff** (with attributes such as `staffID`, `name`, `role`, `email`, `phoneNumber` and methods like `addBook()`, `removeBook()`, `updateBookInfo()`), **Transaction** (with attributes like `transactionID`, `transactionDate`, `dueDate`, `fineAmount` and methods like `calculateFine()`, `generateReceipt()`), and **Reservation** (with attributes like `reservationID`, `reservationDate`, `expirationDate` and methods like `cancelReservation()`, `checkReservationStatus()`). Define the relationships where a **Member** can borrow many **Books**, a **Staff** can manage many **Books**, a **Transaction** is linked to one **Book** and one **Member**, and a **Reservation** is made by a **Member** for a **Book**. Ensure appropriate visibility markers for methods and attributes, and include necessary relationships such as associations, multiplicities, and inheritance. Optionally, consider adding sequence or activity diagrams for processes like book borrowing.
        """)

    # User input for OpenAI API key
    api_key = st.text_input("Enter your OpenAI API Key:", type="password")
    
    # Check if API key is provided
    if not api_key:
        st.warning("Please enter your OpenAI API Key to continue.")
        return

    # User prompt for diagram type
    prompt = st.text_area("Enter your prompt for the diagram:", "")
    
    diagram_types = ["UML Diagram", "ER Diagram", "State Diagram", "Class Diagram", "Sequence Diagram"]
    diagram_choice = st.selectbox("Select the type of diagram to generate:", diagram_types)

    # Show loading spinner when generating the diagram
    loading_spinner = st.empty()
    
    if st.button("Generate Diagram"):
        if prompt:
            # Show loading animation
            loading_spinner.markdown("<div class='loading-spinner'></div>", unsafe_allow_html=True)
            
            diagram_code = get_diagram_code(prompt, diagram_choice, api_key)
            
            if diagram_code:
                # Hide the spinner after diagram code is generated
                loading_spinner.empty()

                # Render Mermaid code to Streamlit
                st.code(diagram_code, language='mermaid')

                # Encode the Mermaid code for use in the MermaidFlow editor URL
                encoded_code = urllib.parse.quote(diagram_code)  # URL encode the Mermaid code

                # MermaidFlow Editor URL with the encoded Mermaid code
                mermaidflow_url = f"https://www.mermaidflow.app/editor?code={encoded_code}"

                # Embed MermaidFlow Editor in iframe
                st.markdown(f'<iframe src="{mermaidflow_url}" width="100%" height="600px"></iframe>', unsafe_allow_html=True)

                # Provide a direct link to MermaidFlow editor for convenience
                st.markdown(f"Copy and paste the Generated Mermaid Code in the Live Editor and download the generated diagram by clicking on Export as SVG format to get a high-resolution generated image.")
            else:
                st.error("Failed to generate diagram code.")
        else:
            st.error("Please enter a prompt.")

if __name__ == "__main__":
    main()