app.py

import gradio as gr
import tempfile, requests, os
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain.chat_models import ChatOpenAI
from gtts import gTTS
from bs4 import BeautifulSoup
from PIL import Image, ImageDraw, ImageFont
import ffmpeg
import textwrap
import subprocess

# OpenAI LLM
llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0.3)
summary_prompt = PromptTemplate.from_template("""
Provide a crisp, promotional-style summary (under 50 words) of the following:

{text}

Summary:
""")
summary_chain = LLMChain(llm=llm, prompt=summary_prompt)

# Extract article content
def extract_main_content(url):
    resp = requests.get(url, timeout=10)
    soup = BeautifulSoup(resp.content, "html.parser")
    for tag in soup(["nav", "header", "footer", "aside", "script", "style", "noscript"]): tag.decompose()
    paras = [p.get_text() for p in soup.find_all("p") if len(p.get_text()) > 60]
    return "\n".join(paras[:20]) or None

# Convert uploaded PNG logo to local use
def get_uploaded_logo():
    from_path = "CSHARP logo.png"
    logo_path = tempfile.NamedTemporaryFile(delete=False, suffix=".png").name
    with open(from_path, 'rb') as src, open(logo_path, 'wb') as dst:
        dst.write(src.read())
    return logo_path

# Create image slides from text chunks
def create_slides(text, duration, output_folder, max_lines=6):
    font_path = "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf"
    font = ImageFont.truetype(font_path, 48)
    logo_path = get_uploaded_logo()

    chunks = textwrap.wrap(text, width=40)
    slides = ["\n".join(chunks[i:i+max_lines]) for i in range(0, len(chunks), max_lines)]
    per_slide_time = duration / len(slides)
    slide_paths = []

    for i, slide_text in enumerate(slides):
        img = Image.new("RGB", (1280, 720), color=(20, 30, 60))
        draw = ImageDraw.Draw(img)

        lines = slide_text.split("\n")
        total_height = sum([draw.textbbox((0, 0), line, font=font)[3] - draw.textbbox((0, 0), line, font=font)[1] for line in lines]) + (len(lines)-1)*10
        y = (720 - total_height) // 2

        for line in lines:
            bbox = draw.textbbox((0, 0), line, font=font)
            w = bbox[2] - bbox[0]
            h = bbox[3] - bbox[1]
            draw.text(((1280 - w) // 2, y), line, font=font, fill="white")
            y += h + 10

        logo = Image.open(logo_path).convert("RGBA").resize((120, 120))
        img.paste(logo, (40, 40), logo)

        frame_path = os.path.join(output_folder, f"slide_{i}.png")
        img.save(frame_path)
        slide_paths.append((frame_path, per_slide_time))

    return slide_paths

# Generate AV summary
def url_to_av_summary(url, duration):
    content = extract_main_content(url)
    if not content:
        return "Failed to extract article content.", None
    summary = summary_chain.invoke({"text": content[:3000]})["text"].replace('"','')[:300]

    audio_path = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3").name
    gTTS(text=summary).save(audio_path)

    frame_dir = tempfile.mkdtemp()
    slides = create_slides(summary, duration, frame_dir)

    slide_inputs = []
    for path, t in slides:
        slide_inputs.extend(["-t", str(t), "-loop", "1", "-i", path])

    filter_complex = "".join([f"[{i}:v]" for i in range(len(slides))]) + f"concat=n={len(slides)}:v=1[outv]"
    concat_img = os.path.join(frame_dir, "video_input.mp4")

    cmd = ["ffmpeg", "-y"] + slide_inputs + ["-filter_complex", filter_complex, "-map", "[outv]", concat_img]
    subprocess.run(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)

    final_video = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4").name
    ffmpeg.input(concat_img).output(audio_path, final_video, vcodec='libx264', acodec='aac', pix_fmt='yuv420p', shortest=None).run(overwrite_output=True, quiet=True)

    return summary, final_video

iface = gr.Interface(
    fn=url_to_av_summary,
    inputs=[
        gr.Textbox(label="Article URL"),
        gr.Radio([5, 10], label="Video Duration (sec)", value=5)
    ],
    outputs=[
        gr.Textbox(label="Summary"),
        gr.Video(label="Generated AV Summary")
    ],
    title="🎞️ AV Summary Generator (Multislide with Uploaded Logo)",
    description="Generates a 5/10 sec video summary from article URL with large text, uploaded logo, and slide animation."
)

if __name__ == '__main__':
    iface.launch()