app.backup06102025.py

import io
import os
import re
import glob
import textwrap
from datetime import datetime
from pathlib import Path

import streamlit as st
import pandas as pd
from PIL import Image
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import letter
from reportlab.lib.utils import ImageReader
import mistune
from gtts import gTTS

# --- Helper Functions ---

# 🗑️ Deletes a specified file and reruns the app.
def delete_asset(path):
    """Safely deletes a file if it exists and reruns the Streamlit app."""
    try:
        os.remove(path)
    except OSError as e:
        st.error(f"Error deleting file {path}: {e}")
    st.rerun()

# 📥 Gets text input from either a file upload or a text area.
def get_text_input(file_uploader_label, accepted_types, text_area_label):
    """
    Provides UI for uploading a text file or entering text manually.
    Returns the text content and a filename stem.
    """
    md_text = ""
    stem = datetime.now().strftime('%Y%m%d_%H%M%S')

    uploaded_file = st.file_uploader(file_uploader_label, type=accepted_types)
    if uploaded_file:
        md_text = uploaded_file.getvalue().decode("utf-8")
        stem = Path(uploaded_file.name).stem
    else:
        md_text = st.text_area(text_area_label, height=200)

    # Convert markdown to plain text for processing
    renderer = mistune.HTMLRenderer()
    markdown = mistune.create_markdown(renderer=renderer)
    html = markdown(md_text or "")
    plain_text = re.sub(r'<[^>]+>', '', html)

    return plain_text, stem

# 🗣️ Generates an MP3 voice file from text using gTTS.
def generate_voice_file(text, lang, is_slow, filename):
    """
    Creates an MP3 from text, saves it, and provides it for playback and download.
    """
    if not text.strip():
        st.warning("No text to generate voice from.")
        return

    voice_file_path = f"{filename}.mp3"
    try:
        tts = gTTS(text=text, lang=lang, slow=is_slow)
        tts.save(voice_file_path)
        st.audio(voice_file_path)
        with open(voice_file_path, 'rb') as fp:
            st.download_button("📥 Download MP3", data=fp, file_name=voice_file_path, mime="audio/mpeg")
    except Exception as e:
        st.error(f"Failed to generate audio: {e}")

# 📄 Creates a PDF document from text and images.
def generate_pdf(text_content, images, pdf_params):
    """
    Generates a PDF buffer from text and a list of images based on specified parameters.
    """
    buf = io.BytesIO()
    c = canvas.Canvas(buf)
    page_w, page_h = letter
    margin = 40
    gutter = 20
    col_w = (page_w - 2 * margin - (pdf_params['columns'] - 1) * gutter) / pdf_params['columns']

    c.setFont(pdf_params['font_family'], pdf_params['font_size'])
    line_height = pdf_params['font_size'] * 1.2
    wrap_width = int(col_w / (pdf_params['font_size'] * 0.6))

    y = page_h - margin
    col_idx = 0

    # --- Render Text ---
    for paragraph in text_content.split("\n"):
        wrapped_lines = textwrap.wrap(paragraph, wrap_width) if paragraph.strip() else [""]
        for line in wrapped_lines:
            if y < margin:
                col_idx += 1
                if col_idx >= pdf_params['columns']:
                    c.showPage()
                    c.setFont(pdf_params['font_family'], pdf_params['font_size'])
                    col_idx = 0
                y = page_h - margin
            
            x = margin + col_idx * (col_w + gutter)
            c.drawString(x, y, line)
            y -= line_height
        y -= line_height # Add extra space for paragraph breaks

    # --- Render Images ---
    for img_file in images:
        try:
            img = Image.open(img_file)
            w, h = img.size
            c.showPage()
            c.setPageSize((w, h))
            c.drawImage(ImageReader(img), 0, 0, w, h, preserveAspectRatio=True, mask='auto')
        except Exception as e:
            st.warning(f"Could not process image {img_file.name}: {e}")
            continue

    c.save()
    buf.seek(0)
    return buf

# 🗂️ Displays a list of generated assets with download/delete options.
def show_asset_manager():
    """Scans for local files and displays them with management controls."""
    st.markdown("---")
    st.subheader("📂 Available Assets")
    assets = sorted(glob.glob("*.*"))
    if not assets:
        st.info("No assets generated yet.")
        return

    for asset_path in assets:
        ext = asset_path.split('.')[-1].lower()
        cols = st.columns([3, 1, 1])
        cols[0].write(asset_path)
        
        try:
            with open(asset_path, 'rb') as fp:
                file_bytes = fp.read()
            
            if ext == 'pdf':
                cols[1].download_button("📥", data=file_bytes, file_name=asset_path, mime="application/pdf", key=f"dl_{asset_path}")
            elif ext == 'mp3':
                cols[1].audio(file_bytes)
        except Exception as e:
            cols[1].error("Error reading file.")

        cols[2].button("🗑️", key=f"del_{asset_path}", on_click=delete_asset, args=(asset_path,))

# � Renders the entire UI and logic for the Python code interpreter.
def render_code_interpreter():
    """Sets up the UI and execution logic for the code interpreter tab."""
    st.header("🧪 Python Code Executor & Demo")

    # --- Nested Helper Functions for this Tab ---
    def extract_python_code(md_text):
        return re.findall(r"```python\s*(.*?)```", md_text, re.DOTALL)

    def execute_code(code_str):
        output_buffer = io.StringIO()
        try:
            with redirect_stdout(output_buffer):
                exec(code_str, {})
            return output_buffer.getvalue(), None
        except Exception as e:
            return None, str(e)

    # --- Main Logic for the Tab ---
    DEFAULT_CODE = "import streamlit as st\n\nst.balloons()\nst.write('Hello, World!')"
    if 'code' not in st.session_state:
        st.session_state.code = DEFAULT_CODE

    uploaded_file = st.file_uploader("Upload .py or .md", type=['py', 'md'])
    if uploaded_file:
        file_content = uploaded_file.getvalue().decode()
        if uploaded_file.type == 'text/markdown':
            codes = extract_python_code(file_content)
            st.session_state.code = codes[0] if codes else ''
        else:
            st.session_state.code = file_content
        st.code(st.session_state.code, language='python')
    else:
        st.session_state.code = st.text_area("💻 Code Editor", value=st.session_state.code, height=300)

    c1, c2 = st.columns(2)
    if c1.button("▶️ Run Code", use_container_width=True):
        output, err = execute_code(st.session_state.code)
        if err:
            st.error(err)
        elif output:
            st.code(output, language='text')
        else:
            st.success("Executed successfully with no output.")
    if c2.button("🗑️ Clear Code", use_container_width=True):
        st.session_state.code = ''
        st.rerun()

# --- Main App ---
def main():
    """Main function to run the Streamlit application."""
    st.set_page_config(page_title="PDF & Code Interpreter", layout="wide", page_icon="🚀")

    tab1, tab2 = st.tabs(["📄 PDF Composer", "🧪 Code Interpreter"])

    with tab1:
        st.header("📄 PDF Composer & Voice Generator 🚀")

        # --- Sidebar Controls ---
        st.sidebar.title("PDF Settings")
        pdf_params = {
            'columns': st.sidebar.slider("Text columns", 1, 3, 1),
            'font_family': st.sidebar.selectbox("Font", ["Helvetica", "Times-Roman", "Courier"]),
            'font_size': st.sidebar.slider("Font size", 6, 24, 12),
        }

        # --- Main UI ---
        plain_text, filename_stem = get_text_input(
            "Upload Markdown (.md)", ["md"], "Or enter markdown text directly"
        )

        st.subheader("🗣️ Voice Generation")
        languages = {"English (US)": "en", "English (UK)": "en-uk", "Spanish": "es"}
        voice_choice = st.selectbox("Voice Language", list(languages.keys()))
        slow_speech = st.checkbox("Slow Speech")

        if st.button("🔊 Generate Voice MP3"):
            generate_voice_file(plain_text, languages[voice_choice], slow_speech, filename_stem)

        st.subheader("🖼️ Image Upload")
        uploaded_images = st.file_uploader(
            "Upload Images for PDF", type=["png", "jpg", "jpeg"], accept_multiple_files=True
        )
        
        ordered_images = []
        if uploaded_images:
            df_imgs = pd.DataFrame([{"name": f.name, "order": i} for i, f in enumerate(uploaded_images)])
            edited_df = st.data_editor(df_imgs, use_container_width=True, key="img_order_editor")
            
            # Create a map for quick lookup
            image_map = {f.name: f for f in uploaded_images}
            
            # Sort and append images based on the edited order
            for _, row in edited_df.sort_values("order").iterrows():
                if row['name'] in image_map:
                    ordered_images.append(image_map[row['name']])

        st.subheader("🖋️ PDF Generation")
        if st.button("Generate PDF with Markdown & Images"):
            pdf_buffer = generate_pdf(plain_text, ordered_images, pdf_params)
            st.download_button(
                "⬇️ Download PDF",
                data=pdf_buffer,
                file_name=f"{filename_stem}.pdf",
                mime="application/pdf"
            )
        
        show_asset_manager()

    with tab2:
        render_code_interpreter()

if __name__ == "__main__":
    main()